Laser melting forming method and system for complex flow channel structure of liquid hydrogen valve

Abstract

This invention relates to the field of laser melting forming technology, and particularly to a laser melting forming method and system for complex flow channel structures in liquid hydrogen valves. This method obtains a forming feasibility assessment value by comprehensively analyzing flow channel structure, equipment parameters, and material performance data to determine whether forming is feasible. If feasible, multiple forming path schemes are generated. By analyzing the process parameters of each path, its forming quality risk value is quantified to characterize the probability of defect occurrence. Finally, the path with the lowest risk value is selected for laser melting forming. This method, through data-driven decision-making, achieves accurate prediction of forming feasibility and intelligent selection of the optimal path, significantly reducing the risk of defects in complex structure forming and improving manufacturing quality and efficiency.

Description

Technical Field

[0001] This invention relates to the field of laser melting forming technology, and in particular to a laser melting forming method and system for complex flow channel structures of liquid hydrogen valves. Background Technology

[0002] Liquid hydrogen, as a high-specific-impulse, clean, and efficient propellant, is widely used in cryogenic engine systems for aerospace launch vehicles, placing extremely high demands on the sealing performance, reliability, and resistance to extreme environments of valve components. Liquid hydrogen valves typically have complex internal flow channel structures to achieve precise flow control and pressure regulation. Traditional manufacturing methods often involve forging blanks followed by multiple machining processes, resulting in low material utilization, long processing cycles, and difficulty in forming complex internal cavity structures. Furthermore, stress concentration and machining defects are prone to occur in areas such as intersecting holes and deep, narrow grooves, affecting the overall performance and service life of the valve.

[0003] In recent years, Laser Powder Bed Fusion (LPBF) technology, as an advanced additive manufacturing process, has shown great potential in the aerospace field due to its ability to directly form high-precision, complex-geometric metal parts, providing a new technical path for the integrated forming of complex flow channels in liquid hydrogen valves. However, liquid hydrogen valves operate in harsh environments of extremely low temperatures (-253°C), high pressure, and high cleanliness. Their flow channel structures are not only geometrically complex but also have extremely high requirements for density, surface quality, microstructure uniformity, and mechanical property stability. Existing laser powder bed fusion technology still faces many challenges when applied to such critical components: on the one hand, serious defects such as cracking, deformation, and incomplete fusion are easily introduced during the forming process; on the other hand, at the path planning level, the forming quality varies significantly under different path schemes, lacking scientific quantitative evaluation and optimal path selection criteria.

[0004] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] Analysis of the defects in existing laser melting forming technology for forming complex flow channel structures of liquid hydrogen valves reveals the following main causes: First, the lack of a systematic evaluation mechanism for the matching relationship between flow channel structure characteristics, equipment capabilities, and material properties makes it difficult to predict forming feasibility, and blind forming easily leads to serious defects such as cracking, deformation, and incomplete fusion. Second, traditional scanning strategies are mostly based on simple geometric rules and fail to fully consider the influence of local features of complex flow channels on heat accumulation, stress distribution, and defect formation, resulting in significant differences in forming quality under different path schemes, and a lack of scientific quantitative evaluation and optimal path selection basis. Based on the above analysis, the main objective of this invention is to provide a laser melting forming method and system for complex flow channel structures of liquid hydrogen valves, aiming to solve the technical problems of high forming defect risk and poor quality stability caused by the lack of a systematic evaluation mechanism for the process feasibility of complex flow channel structures of liquid hydrogen valves in laser melting forming and the lack of a path planning method based on optimal forming quality risk in existing technologies.

[0006] To achieve the above objectives, the present invention provides a laser melting forming method for complex flow channel structures of liquid hydrogen valves, the method comprising: By analyzing the structural feature data of the complex flow channel of the liquid hydrogen valve, the parameter data of the laser melting forming equipment, and the performance data of the forming material, a forming feasibility assessment value is obtained. The forming feasibility assessment value is used to evaluate the feasibility of the current laser melting forming and to determine whether the laser melting forming of the complex flow channel structure of the liquid hydrogen valve can be carried out. For cases where laser melting forming is deemed feasible based on forming feasibility assessment values, various forming path planning schemes for laser melting forming of complex flow channel structures are obtained. By combining the planning schemes of each forming path with the analysis of the forming-related process parameters of each path, the forming quality risk value of each forming path is obtained. The forming quality risk value is used to represent the probability of defects occurring when the path is selected for forming. By analyzing the forming quality risk value of each forming path, the forming path planning scheme with the minimum forming quality risk value is selected for laser melting forming of complex flow channel structure of liquid hydrogen valve.

[0007] Optionally, the specific process for determining whether laser melting forming of complex flow channel structures for liquid hydrogen valves is feasible is as follows: The forming feasibility assessment threshold is obtained based on the laser melting forming simulation training of a typical liquid hydrogen valve structure. The forming feasibility assessment threshold represents the limit value at which laser melting forming can be successfully carried out. The forming feasibility assessment value of the complex flow channel of the target liquid hydrogen valve is compared and analyzed with the forming feasibility assessment threshold. When the forming feasibility assessment value of the complex flow channel of the target liquid hydrogen valve is greater than or equal to the forming feasibility assessment threshold, it is determined that the complex flow channel of the target liquid hydrogen valve can be laser melting and forming, and the forming path planning scheme is automatically selected for forming. When the feasibility assessment value of forming the complex flow channel of the target liquid hydrogen valve is less than the feasibility assessment threshold, it is determined that the complex flow channel of the target liquid hydrogen valve is not suitable for laser melting forming and there is a risk of forming quality. An alarm mechanism is used to issue a prompt message to the process personnel to adjust the forming scheme. The forming scheme adjustment includes flow channel structure optimization, forming equipment parameter adjustment, forming material selection or pretreatment.

[0008] Optionally, the specific analytical process for obtaining the forming feasibility assessment value is as follows: The three-dimensional model data and structural feature parameters of the complex flow channel of the target liquid hydrogen valve are obtained based on computer-aided design technology and structural analysis technology. Finite element analysis and material database technology were used to analyze the parameters of laser melting forming equipment and the performance data of forming materials, and to extract the key process parameter dataset of laser melting forming equipment and the mechanical properties and formability dataset of forming materials. Preprocessing is performed on the target liquid hydrogen valve complex flow channel structure feature dataset, the laser melting forming equipment key process parameter dataset, and the forming material performance dataset to obtain target structure feature data, equipment parameter data, and material performance data. The preprocessing includes data cleaning, data transformation, data fusion, and data standardization. By analyzing the target structure feature data, equipment parameter data, and material performance data, the complexity assessment value of the flow channel structure, the equipment capability matching degree assessment value, and the material forming adaptability assessment value are obtained. By performing a weighted comprehensive analysis of the flow channel structure complexity assessment value, equipment capability matching degree assessment value, and material forming adaptability assessment value, a forming feasibility assessment value is obtained.

[0009] Optionally, the formula for calculating the forming feasibility assessment value is as follows:

[0010] In the formula, This represents the feasibility assessment value for forming. This represents the evaluation value of the flow channel structure complexity. This indicates the equipment capability matching evaluation value. This indicates the material's adaptability to forming assessment value. The weighting factors represent the evaluation values ​​of the complexity of the flow channel structure. The weighting factor represents the equipment capability matching evaluation value. The weighting factor represents the material forming adaptability assessment value.

[0011] Optionally, the specific method for obtaining the complexity evaluation value of the flow channel structure includes: By analyzing the three-dimensional model data of the complex flow channel of the target liquid hydrogen valve, the characteristic parameters of the flow channel are extracted. The characteristic parameters include the aspect ratio, the rate of change of curvature, the number of cross holes, the overhang angle and the minimum wall thickness. The characteristic parameters are assigned weights and weighted analysis is performed to obtain the flow channel structure complexity evaluation value. And / or, the specific method for obtaining the equipment capability matching degree evaluation value is as follows: by comparing and analyzing the parameters of the laser spot diameter, positioning accuracy, maximum forming size, powder thickness range and scanning speed range of the laser melting forming equipment with the flow channel structure characteristic parameters, assigning corresponding weights to the matching degree of different parameters, and obtaining the equipment capability matching degree evaluation value; And / or, the specific method for obtaining the material forming adaptability assessment value is as follows: by testing and evaluating the performance parameters of the forming material, such as powder flowability, density, mechanical properties, purity, and absorption rate of laser energy, and combining the service environment requirements of the liquid hydrogen valve, weights are assigned to these performance parameters for weighted analysis to obtain the material forming adaptability assessment value.

[0012] Optionally, the specific analysis process for obtaining the forming quality risk value of each forming path is as follows: Obtain the complex flow channel region of the liquid hydrogen valve that can be laser-melted and the optimal forming direction based on the forming feasibility assessment value; Based on the flow channel region and the optimal forming direction, multiple feasible forming path planning schemes are automatically generated using slicing software and path planning algorithms, and the path information of each forming path planning scheme is obtained. Finite element simulation technology is used to simulate the forming process of various forming path planning schemes, and to predict the behavior of the molten pool, temperature field distribution, stress and strain and possible defects. Based on the analysis of path information and forming process simulation results of each forming path planning scheme, path forming information and defect prediction information of each forming path are extracted. By analyzing the path forming information and defect prediction information of each forming path, the forming quality risk value of each forming path is obtained.

[0013] Optionally, the path forming information specifically includes: uniformity of scan line length, number of jumps, and consistency of overlap rate; the defect prediction information specifically includes: predicted porosity value, crack sensitivity index, and predicted deformation value.

[0014] Optionally, the specific calculation formula for the forming quality risk value of each forming path is as follows:

[0015] In the formula, r represents the number of each forming path planning scheme, r = 1, 2, 3, ..., R, and R represents the total number of forming path planning schemes. This represents the forming quality risk value of the r-th forming path planning scheme. This represents the standard deviation of the scan line length for the r-th scheme. Indicates the average scan line length. This represents the number of transitions in the r-th scheme. This represents the maximum number of transitions among all possible solutions. This represents the overlap rate of the r-th scheme. The target overlap rate is represented by k1, k2, and k3, which represent the weighting factors for scan line length uniformity, number of jumps, and overlap rate consistency, respectively. This represents the predicted porosity value for the r-th scheme. This represents the crack sensitivity index of the r-th scheme. Let m1, m2, and m3 represent the predicted deformation value of the r-th scheme, respectively, and m1, m2, and m3 represent the weighting factors of porosity, crack sensitivity, and deformation. α represents the weighting coefficient of path forming information on the forming quality risk value, and β represents the weighting coefficient of defect prediction information on the forming quality risk value.

[0016] Optionally, the specific implementation process of selecting the forming path planning scheme with the minimum forming quality risk value for laser melting forming of complex flow channel structures of liquid hydrogen valves further includes: Based on the selected forming path planning scheme, layer slicing is performed to generate scan path files for each layer; Based on the structural characteristics of different regions of the flow channel, the process parameters in the scan path file are optimized by partitioning. The optimized scanning path file is imported into the laser melting and forming equipment for the forming process. During the forming process, a real-time monitoring system is used to monitor the temperature of the molten pool and the state of the powder bed. When an abnormality is detected, the relevant process parameters are automatically adjusted or the forming process is paused, and an alarm is issued to remind the operator.

[0017] Furthermore, to achieve the above objectives, the present invention also provides a laser melting and forming system for complex flow channel structures of liquid hydrogen valves, the system comprising: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the steps of the laser melting and forming method for complex flow channel structures of liquid hydrogen valves as described in any of the above-mentioned methods.

[0018] This invention provides a laser melting forming method for complex flow channel structures in liquid hydrogen valves. The method constructs a forming feasibility assessment system, comprehensively analyzing flow channel structural characteristics, equipment parameters, and material properties to quantitatively predict the feasibility of the laser melting forming process, effectively avoiding forming failures caused by complex structures, incompatible equipment, or poor material adaptability. Based on this, by generating multiple path schemes and combining process parameter simulation analysis, a forming quality risk assessment model is established to quantify the defect risks under different paths. The path with the lowest risk is then selected for forming, significantly reducing the probability of defects such as porosity, cracks, and deformation in complex flow channels during the forming process, thus improving the stability and reliability of the forming quality. This method realizes a shift from experience-based trial production to data-driven, intelligent decision-making, not only improving the manufacturing precision and performance consistency of key components in liquid hydrogen valves but also shortening the R&D cycle and reducing trial-and-error costs, providing technical support for the efficient and high-quality additive manufacturing of high-end cryogenic valves. Attached Figure Description

[0019] Figure 1 This is a schematic flowchart of an embodiment of the laser melting and forming method for complex flow channel structures of liquid hydrogen valves according to the present invention; Figure 2 This is a flowchart illustrating the specific analysis process for obtaining a forming feasibility assessment value in an embodiment of the laser melting forming method for complex flow channel structures of liquid hydrogen valves according to the present invention. Figure 3 This is a schematic flowchart illustrating the specific analysis process for obtaining the forming quality risk value of each forming path in an embodiment of the laser melting forming method for complex flow channel structures of liquid hydrogen valves according to the present invention.

[0020] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0022] Reference Figure 1 , Figure 1 This is a schematic flowchart of an embodiment of the laser melting and forming method for complex flow channel structures of liquid hydrogen valves according to the present invention. An embodiment of the laser melting and forming method for complex flow channel structures of liquid hydrogen valves according to the present invention is presented.

[0023] In one embodiment, the laser melting forming method for the complex flow channel structure of the liquid hydrogen valve includes the following steps: Step S100: By analyzing the structural feature data of the complex flow channel of the liquid hydrogen valve, the parameter data of the laser melting forming equipment, and the performance data of the forming material, a forming feasibility assessment value is obtained. The forming feasibility assessment value is used to evaluate the feasibility of the current laser melting forming and to determine whether the laser melting forming of the complex flow channel structure of the liquid hydrogen valve can be carried out.

[0024] The complex flow channel structure of the liquid hydrogen valve can be a geometrically complex three-dimensional channel system inside the liquid hydrogen valve used to achieve flow control and pressure regulation. Furthermore, the complex flow channel structure of the liquid hydrogen valve can include, but is not limited to, one or more of the following: multi-directional converging flow channels, variable cross-section contraction-expansion flow channels, and spiral nested cooling flow channels. Preferably, the complex flow channel structure of the liquid hydrogen valve includes cross holes and deep narrow groove features to ensure precise flow and sealing of liquid hydrogen under extremely low temperature and high pressure conditions, which directly affects the valve's service performance and lifespan.

[0025] Structural feature data can be a set of digital parameters describing the geometry of complex flow channels in a liquid hydrogen valve. It can be used to characterize properties such as the geometric complexity of the flow channel, overhang angle, and the sensitivity of the minimum feature size to the forming process. In an exemplary embodiment, structural feature data can be obtained through CAD model extraction or CT scan reconstruction. For example, the structural feature data and the forming feasibility assessment value form an input-output relationship, providing geometric constraints for the evaluation system.

[0026] The parameter data of laser melting and forming equipment can be a set of technical parameters that can be set or monitored during the operation of the laser powder bed melting equipment. These parameters can reflect the equipment's capabilities in terms of energy input, layer thickness control, and atmosphere protection. In one specific embodiment, the parameter data can be read from the equipment control system or preset according to the equipment model. Furthermore, the parameter data can include, but is not limited to, one or more of the following: laser power and spot diameter combination, scanning galvanometer response frequency, and inert gas flow field uniformity parameters.

[0027] The performance data of the forming material can be the physical and mechanical properties of metallic materials suitable for laser melting forming under process conditions and low-temperature service conditions. Furthermore, the physical and mechanical properties data may include, but are not limited to, the ratio of thermal conductivity to coefficient of thermal expansion, the width of the solidification range, and low-temperature fracture toughness indicators. These can be used to characterize the material's response to thermal cycling, crack sensitivity, and strength and toughness at -253°C. For example, the performance data of the forming material can be obtained through material database queries or experimental testing.

[0028] The forming feasibility assessment value can be a quantitative indicator calculated based on the matching degree of structural features, equipment capabilities, and material properties. It can be used to determine whether the current configuration has the technological foundation for successfully forming the complex flow channel of a liquid hydrogen valve. In a specific embodiment, the forming feasibility assessment value is generated through a multi-dimensional parameter mapping function or a machine learning model. Furthermore, the forming feasibility assessment value relies on structural feature data, equipment parameter data, and material property data as inputs; its output determines whether to proceed to the path planning stage. The forming feasibility assessment value is obtained by analyzing the structural feature data of the complex flow channel of the liquid hydrogen valve, the parameter data of the laser melting forming equipment, and the performance data of the forming material. This can be achieved by substituting the three types of input data into a pre-built assessment model for matching calculations. Furthermore, this operation can be achieved by using a rule-based expert system, setting a geometry-equipment-material matching threshold for Boolean judgment, or constructing a neural network model and outputting continuous feasibility scores using historical success / failure cases as a training set. This allows for the early identification of infeasible process windows and avoids invalid trial production.

[0029] Step S200: For cases where laser melting forming is deemed feasible based on the forming feasibility assessment value, obtain various forming path planning schemes for laser melting forming of complex flow channel structures.

[0030] The forming path planning scheme can be a set of laser scanning trajectory strategies designed for a specific flow channel structure. It can guide the movement sequence and direction of the laser beam in each layer, influencing local heat accumulation and residual stress distribution. In an exemplary embodiment, the forming path planning scheme is automatically generated by a path generation algorithm based on geometric partitioning, thermal management requirements, or stress control objectives. Furthermore, the forming path planning scheme can include, but is not limited to, one or more of island-shaped partition scanning paths, contour offset filling paths, and stress-balanced staggered scanning paths. Obtaining various forming path planning schemes for laser melting forming of complex flow channel structures can be achieved by automatically generating multiple scanning strategies based on flow channel geometric features. Furthermore, this operation can be achieved by dividing the flow channel into functional regions, generating differentiated paths for control sections, transition sections, and exit sections, or by introducing topology optimization to back-calculate the scanning sequence with the goal of minimizing the maximum temperature gradient. This provides diverse heat input distribution patterns for optimization selection.

[0031] Step S300: Combine the analysis of each forming path planning scheme and the forming-related process parameters of each path to obtain the forming quality risk value of each forming path. The forming quality risk value is used to represent the probability of defects occurring when the path is selected for forming.

[0032] The forming-related process parameters can be combinations of laser processing parameters bound to a specific path scheme. These parameters can be used to control the molten pool size, cooling rate, and metallurgical bonding quality, directly affecting the defect formation tendency. In one specific embodiment, the forming-related process parameters are determined by a process database or simulation inversion and dynamically adjusted according to local path features. Further, the forming-related process parameters can include, but are not limited to, one or more of the following: local region laser power modulation parameters, interlayer rotation angle sequence, scanning spacing, and overlap rate configuration. The forming quality risk value can be a probabilistic index characterizing the generation of defects such as porosity, cracks, or deformation when forming using a specific path scheme. It can be used to provide a quantitative basis for path optimization and reduce quality uncertainty in actual forming. For example, the forming quality risk value is calculated through thermo-mechanical coupling simulation, historical data regression, or a defect formation mechanism model. Further, the forming quality risk value is generated jointly driven by the forming path planning scheme and the forming-related process parameters; it is used to guide the final path selection.

[0033] By combining the planning schemes of each forming path with the analysis of the forming-related process parameters of each path, the forming quality risk value of each forming path can be obtained. This can be achieved by inputting the path and corresponding process parameters into a simulation or evaluation model and outputting the probability of defect risk. Furthermore, this operation can be realized by using finite element thermo-mechanical coupling simulation to calculate residual stress and deformation and map them to risk levels, or by using a digital twin platform and combining online monitoring data feedback to correct the risk prediction model. This enables the predictability of the quality of the forming path scheme and supports scientific decision-making.

[0034] Step S400: By analyzing the forming quality risk value of each forming path, the forming path planning scheme with the smallest forming quality risk value is selected for laser melting forming of the complex flow channel structure of the liquid hydrogen valve.

[0035] By analyzing the forming quality risk values ​​of each forming path, the forming path planning scheme with the lowest forming quality risk value is selected for the laser melting forming of complex flow channel structures in liquid hydrogen valves. This can be achieved by comparing the risk values ​​of each path and selecting the one with the lowest value as the execution scheme. Furthermore, this operation can be achieved by setting a risk threshold, initiating forming only when the minimum risk value is below the threshold, or by combining multi-objective optimization to minimize risk while considering forming efficiency or surface roughness. This ensures that the actual forming process is carried out under optimal thermo-mechanical conditions, suppressing defect generation.

[0036] Example 1, taking the manufacturing of the main valve of a liquid hydrogen propulsion system as an example, the laser melting forming method for the complex flow channel structure of the liquid hydrogen valve in this example can be as follows: For a certain type of liquid hydrogen valve with a valve body structure containing multi-directional intersecting microchannels, firstly, its minimum channel diameter, cantilever length, and rate of curvature change are extracted as structural feature data; combined with the maximum laser power, minimum spot size, and oxygen content control capability of the LPBF equipment used, as well as the ductility data of the selected AlSi10Mg alloy at -253°C, the forming feasibility assessment value is calculated to be 0.82 (threshold 0.7), which is deemed feasible; then, three path schemes are generated: island partitioning, contour priority filling, and stress equalization staggered scanning; the corresponding laser power gradient, interlayer rotation angle, and other process parameters are bound respectively, and the forming quality risk values ​​of each scheme are obtained through thermo-mechanical simulation as 0.35, 0.48, and 0.29 respectively; finally, the stress equalization staggered scanning path with a risk value of 0.29 is selected for actual printing. The formed part is found to have no unfused defects after CT inspection, and the density reaches 99.95%, which meets the liquid hydrogen sealing requirements.

[0037] In one embodiment, the specific process for determining whether laser melting forming of complex flow channel structures for liquid hydrogen valves is feasible is as follows: The forming feasibility assessment threshold is obtained based on the laser melting forming simulation training of a typical liquid hydrogen valve structure. The forming feasibility assessment threshold represents the limit value at which laser melting forming can be successfully carried out. The typical structure of a liquid hydrogen valve can be a representative liquid hydrogen valve flow channel geometry, encompassing common features such as intersecting holes, deep grooves, and thin walls. This can serve as a benchmark model for laser melting forming simulation training to extract the process boundary conditions for successful forming. In an exemplary embodiment, the typical liquid hydrogen valve structure may include, but is not limited to, one or more of the following: a multi-channel converging valve core structure, a valve body structure with an internal cooling circuit, and a high-curvature transition flow channel structure. Laser melting forming simulation training can be a process of conducting multiple rounds of virtual forming experiments on a typical liquid hydrogen valve structure based on numerical simulation or a digital twin platform. This can be used to generate a large amount of successful and failed case data to support the calibration of forming feasibility assessment thresholds. Furthermore, laser melting forming simulation training can be achieved through iterative running of different parameter combinations using thermo-fluid-structure interaction simulation or machine learning proxy models. For example, laser melting forming simulation training can employ finite element-based thermal stress simulation training, fast proxy model training based on physical information neural networks, and reverse mapping training based on historical printing data.

[0038] The forming feasibility assessment threshold can be a critical limit of the forming feasibility assessment value determined by simulation training of typical structures. It can be used as a quantitative admission standard to determine whether a new flow channel structure is manufacturable. In a specific embodiment, the forming feasibility assessment threshold can be obtained by statistically analyzing the distribution of assessment values ​​of successful forming cases and taking the lower confidence limit or quantile as the threshold. Furthermore, the forming feasibility assessment threshold can be compared with the forming feasibility assessment value to determine whether to enter path planning or trigger an alarm mechanism. Obtaining the forming feasibility assessment threshold based on laser melting forming simulation training of typical liquid hydrogen valve structures can be achieved by conducting multiple sets of virtual forming experiments using typical structures, statistically analyzing the distribution of assessment values ​​of successful cases, and determining the threshold. Furthermore, this operation can be achieved by sampling in the parameter space using the Monte Carlo method, fitting the relationship curve between the success probability and the assessment value, and taking the value corresponding to 90% success rate as the threshold, or by dividing the forming results into feasible / infeasible categories based on cluster analysis, and using a support vector machine to determine the optimal classification boundary as the threshold. This allows the establishment of a feasibility criterion with engineering significance, giving the assessment value a clear decision-making basis.

[0039] The forming feasibility assessment value of the complex flow channel of the target liquid hydrogen valve is compared and analyzed with the forming feasibility assessment threshold. When the forming feasibility assessment value of the complex flow channel of the target liquid hydrogen valve is greater than or equal to the forming feasibility assessment threshold, it is determined that the complex flow channel of the target liquid hydrogen valve can be laser melting and forming, and the forming path planning scheme is automatically selected for forming. The target liquid hydrogen valve complex flow channel can be a specific liquid hydrogen valve flow channel design instance to be manufactured, which can be used as the object of forming feasibility assessment, and its assessment value is compared with a threshold. In a specific embodiment, the forming feasibility assessment value of the target liquid hydrogen valve complex flow channel can be input into the judgment logic module to drive subsequent process branches. Comparing and analyzing the forming feasibility assessment value of the target liquid hydrogen valve complex flow channel with the forming feasibility assessment threshold can be performed by executing numerical comparison judgment logic. Furthermore, this operation can be achieved by embedding a real-time comparison module in the process planning software to dynamically display the assessment status, or by combining it with a conservative judgment based on the uncertainty range, thereby realizing automated process access decision-making.

[0040] When the feasibility assessment value of the complex flow channel of the target liquid hydrogen valve is greater than or equal to the feasibility assessment threshold, it is determined that the complex flow channel of the target liquid hydrogen valve can currently be laser-melted and formed. A forming path planning scheme is automatically selected for forming, which can trigger an automatic path selection and forming command issuance process. Furthermore, this operation can be implemented by calling a pre-stored optimal path template library for matching, or by starting the path generation module to calculate and verify in real time before execution, thereby enabling the initiation of feasible part manufacturing without intervention.

[0041] When the feasibility assessment value of forming the complex flow channel of the target liquid hydrogen valve is less than the feasibility assessment threshold, it is determined that the complex flow channel of the target liquid hydrogen valve is not suitable for laser melting forming and there is a risk of forming quality. An alarm mechanism is used to issue a prompt message to the process personnel to adjust the forming scheme. The forming scheme adjustment includes flow channel structure optimization, forming equipment parameter adjustment, forming material selection or pretreatment.

[0042] The alarm mechanism can be an automatically triggered feedback system that detects when the evaluation result falls below a threshold. This system can promptly alert process engineers to potential forming risks, preventing ineffective manufacturing. In one exemplary embodiment, the alarm mechanism can be implemented by activating a notification module after a software logic condition is met. The alert message can be a structured message generated by the alarm mechanism, containing a risk description and adjustment suggestions, which can guide process engineers to make targeted modifications to the forming plan.

[0043] Process engineers can be technical operators responsible for the design and adjustment of additive manufacturing processes. They can receive prompts and execute decisions to adjust forming schemes. Forming scheme adjustments can be a set of process improvement measures taken in response to infeasibility assessments, used to improve the forming feasibility of the target flow channel to meet manufacturing requirements. For example, forming scheme adjustments can include, but are not limited to, one or more of the following: flow channel structure optimization, forming equipment parameter adjustment, forming material selection, or pretreatment. Flow channel structure optimization can involve modifying the topology or dimensions of the original flow channel geometry to reduce manufacturing difficulty, and can be used to reduce unfavorable forming features such as overhangs, sharp corners, or excessively narrow channels. Forming equipment parameter adjustment can involve modifying the operating parameters of the laser melting forming equipment to match flow channel requirements, and can be used to improve energy input stability or improve molten pool flowability. Furthermore, forming equipment parameter adjustment can be achieved by resetting the process window in the equipment control software. For example, forming equipment parameter adjustment can include, but is not limited to, one or more of the following: improving the stability control accuracy of laser power, optimizing the matching relationship between layer thickness and scanning speed, and enhancing the uniformity of the inert atmosphere. Forming material selection can involve replacing it with a metal material more suitable for ultra-low temperature LPBF forming, which can be used to improve metallurgical quality and low-temperature service performance. In one specific embodiment, the forming material can be selected from a material database by screening alloys with higher crack resistance or lower hot cracking sensitivity.

[0044] Pre-treatment of forming materials can involve physical or chemical treatment of powder or substrate before forming, which can be used to reduce oxygen content, eliminate internal stress, or improve powder uniformity. Furthermore, pre-treatment can be achieved by improving the material state through methods such as sieving, annealing, and surface modification. For example, pre-treatment can include, but is not limited to, one or more of the following: vacuum annealing to remove adsorbed gases, sphericity screening to improve flowability, and surface nano-coating to inhibit oxidation. When the forming feasibility assessment value of the target liquid hydrogen valve's complex flow channel is less than the forming feasibility assessment threshold, it is determined that the target liquid hydrogen valve's complex flow channel is currently unsuitable for laser melting forming, posing a forming quality risk. This can be achieved by marking the current design as high-risk and blocking the automated forming process. Furthermore, this operation can be achieved by recording failure reason tags for subsequent knowledge base updates or generating risk heat maps to annotate high-risk areas in the flow channel, thereby preventing resources from being wasted on infeasible designs.

[0045] Utilizing an alarm mechanism to prompt process engineers to adjust the forming scheme can be achieved by activating the notification system and pushing structured prompts to the user interface. Furthermore, this operation can be implemented by automatically sending alarms and suggestions via WeChat / email, or by highlighting areas requiring optimization on the 3D model with modification options, thus guiding manual intervention to correct the scheme. Adjustments to the forming scheme include optimizing the runner structure, adjusting forming equipment parameters, and selecting or pre-treating forming materials. This can be achieved by process engineers modifying the design or process configuration based on the prompts. Further, this operation can be achieved by directly editing the runner geometry and re-evaluating it in the integrated design environment, or by automatically calling the corresponding process parameter package to recalculate the evaluation value after switching material grades, thereby improving the manufacturability of the target runner and ensuring it meets forming feasibility requirements.

[0046] Example 2, taking the first trial production of a new type of liquid hydrogen servo valve as an example, the laser melting forming method of the complex flow channel structure of the liquid hydrogen valve in this example can be: A new type of liquid hydrogen servo valve contains 0.8mm micropores and a 45° cantilever channel, and its forming feasibility assessment value is calculated to be 0.68. The system calls the forming feasibility assessment threshold of 0.72 obtained from the simulation training of 20 typical valve structures, and determines that 0.68 < 0.72, triggering the alarm mechanism. The system automatically generates the prompt message: "There is a high risk of non-fusion in the cross micropore area. It is recommended that: (1) the aperture be enlarged to 1.0mm; (2) a low thermal cracking sensitivity Al-Mg-Sc alloy be selected; (3) the laser power stability be improved to ±2%." The process personnel adopted the suggestion, optimized the key aperture of the flow channel to 1.0mm, changed the material, and re-evaluated the assessment value to 0.75 > 0.72. The system automatically entered the path planning stage and finally successfully printed a defect-free valve body.

[0047] In some preferred embodiments, the specific analytical process for obtaining the forming feasibility assessment value includes: Step S101: Obtain the three-dimensional model data and structural feature parameters of the complex flow channel of the target liquid hydrogen valve based on computer-aided design technology and structural analysis technology; Step S102: Analyze the parameters of the laser melting forming equipment and the performance data of the forming material using finite element analysis and material database technology, and extract the key process parameter dataset of the laser melting forming equipment and the mechanical properties and formability dataset of the forming material; Step S103: Preprocess the target liquid hydrogen valve complex flow channel structure feature dataset (the 3D model data and structural feature parameters of the target liquid hydrogen valve complex flow channel obtained in step S101), the laser melting forming equipment key process parameter dataset, and the forming material performance dataset to obtain target structural feature data (which can be used as direct input for flow channel structure complexity assessment), equipment parameter data (which can be used to calculate equipment capability matching assessment), and material performance data. Preprocessing includes data cleaning, data conversion (format conversion), data fusion (multi-source fusion), and data standardization. Furthermore, this operation can be achieved by Z-score standardization for parameters of different dimensions, or by principal component analysis (PCA) to fuse highly correlated features for dimensionality reduction and noise reduction, thereby eliminating the incomparability between heterogeneous data and constructing a unified evaluation input space.

[0048] The target structural feature data can be the standardized results of preprocessed structural feature parameters, which can be used to eliminate dimensions and outliers, making it usable with other datasets within the same evaluation framework. Equipment parameter data can be the standardized results of preprocessed key process parameters of the equipment, which can be used to unify numerical scales and support fusion analysis with structural and material data. Material performance data can be the standardized results of preprocessed material mechanical properties and formability data, which can be used to ensure the comparability of material properties in multidimensional evaluations. Furthermore, material performance data can be obtained by imputing missing values, unifying units, and scaling the material dataset. In a specific embodiment, equipment parameter data can be obtained by performing data cleaning and normalization operations on the key process parameter dataset of the equipment.

[0049] Step S104: By analyzing the target structure feature data, equipment parameter data, and material performance data respectively, the flow channel structure complexity assessment value, equipment capability matching degree assessment value, and material forming adaptability assessment value are obtained. Step S105: By performing a weighted comprehensive analysis of the flow channel structure complexity assessment value, equipment capability matching degree assessment value, and material forming adaptability assessment value, a forming feasibility assessment value is obtained, which is used to provide a basis for decision-making on whether to start the forming process.

[0050] The 3D model data of the complex flow channel of the target liquid hydrogen valve can include, but is not limited to, one or more of parametric surface models, solid Boolean operation models, and mesh discretization models. It is typically a digital 3D representation of the internal flow channel geometry of the liquid hydrogen valve, generated through computer-aided design (e.g., CAD software modeling or reverse engineering reconstruction), and can be used as the geometric basis for structural feature extraction and subsequent process simulation. Structural feature parameters can be a set of indicators reflecting the geometric complexity of the flow channel, quantified and extracted from the 3D model. These parameters can be used to characterize the forming difficulty, such as overhang angle, minimum channel diameter, and rate of curvature change. Furthermore, structural feature parameters can be automatically identified and calculated using structural analysis algorithms to determine key geometric properties. In one specific embodiment, structural feature parameters can include, but are not limited to, one or more of the following: local overhang angle distribution parameters, channel cross-sectional abrupt change rate, and internal cavity topological connectivity.

[0051] The acquisition of 3D model data and structural feature parameters of the complex flow channel of the target liquid hydrogen valve based on computer-aided design and structural analysis techniques can be achieved by constructing or importing the flow channel model in a CAD environment and automatically extracting geometric features using a structural analysis module. Furthermore, this operation can be accomplished by directly outputting a B-rep model with feature labels using parametric modeling tools, or by scanning and extracting local geometric attributes such as curvature and overhang angles through voxelization or triangular mesh models, thereby enabling the digital and quantifiable expression of the flow channel complexity.

[0052] The key process parameter dataset for laser melting forming equipment can be a subset of equipment operating parameters that have a decisive impact on forming quality, selected through finite element analysis. This dataset can be used to focus on the core dimensions of equipment capability, avoiding redundant parameters from interfering with the evaluation. In an exemplary embodiment, the key process parameter dataset for laser melting forming equipment can be extracted by combining equipment specifications with thermo-mechanical simulation sensitivity analysis, or by extracting core formability indicators such as solidification range and thermal conductivity based on material phase diagrams and thermophysical databases. This allows for focusing on key variables and improving evaluation efficiency and accuracy. The mechanical properties and formability dataset for forming materials can be a subset of material properties related to LPBF process adaptability and low-temperature service, extracted from a material database. This dataset can be used to support the prediction of material behavior under rapid melting and extremely low-temperature environments. Furthermore, the mechanical properties and formability dataset for forming materials can be queried from a database based on material grades and key performance indicators can be selected using finite element simulation. In a specific embodiment, the mechanical properties and formability dataset for forming materials can include, but is not limited to, one or more of the following: thermophysical property parameter sets, solidification crack sensitivity parameter sets, and low-temperature toughness retention parameter sets.

[0053] The flow channel structure complexity assessment value can be an indicator that quantifies the impact of the geometric complexity of the liquid hydrogen valve flow channel on the forming difficulty of LPBF (Liquid Biological Processing). It can be used to reflect whether the structure itself exceeds the geometric forming capability boundary of the current additive manufacturing process. In a specific embodiment, the flow channel structure complexity assessment value can be calculated based on the target structure feature data through a weighted function or machine learning model. The equipment capability matching degree assessment value can be a quantitative indicator that measures whether the current LPBF equipment can meet the forming requirements of a specific flow channel structure. It can be used to determine whether the equipment hardware and control capabilities are sufficient to support high-quality forming. Furthermore, the equipment capability matching degree assessment value can be calculated by matching equipment parameter data with the minimum process capability (such as minimum spot size, maximum power density) required by the structure. In an exemplary embodiment, the equipment capability matching degree assessment value may include, but is not limited to, one or more of the following: energy field accuracy matching degree, motion system dynamic response matching degree, and atmosphere cleanliness assurance degree.

[0054] The material forming adaptability assessment value characterizes the ability of a selected material to resist defect formation during LPBF (Liquid-to-Boiler) and maintain performance at -253°C. It can be used to evaluate whether a material is suitable for additive manufacturing under extreme conditions in liquid hydrogen valves. In one specific embodiment, the material forming adaptability assessment value can be calculated based on material performance data, combined with a crack sensitivity model and low-temperature performance degradation laws. By analyzing the target structural feature data, equipment parameter data, and material performance data respectively, the flow channel structure complexity assessment value, equipment capability matching degree assessment value, and material forming adaptability assessment value can be obtained. This can be achieved by inputting the three types of preprocessed data into the corresponding evaluation sub-models. Furthermore, this operation can be implemented using a rule engine to map complexity levels according to threshold intervals, or by using a regression model to back-calculate the assessment values ​​of each dimension based on historical forming success rates, thereby achieving independent quantitative evaluation of the three dimensions of structure, equipment, and materials.

[0055] In an exemplary embodiment, the forming feasibility assessment value can be integrated using a linear or nonlinear combination function with adjustable weights. Furthermore, the forming feasibility assessment value can rely on the first three assessment values ​​as input, with its output determining whether to proceed to the path planning stage. The forming feasibility assessment value is obtained by weighted comprehensive analysis of the flow channel structure complexity assessment value, equipment capability matching degree assessment value, and material forming adaptability assessment value. This can be achieved by integrating the three assessment values ​​according to preset or adaptive weights. Further, this operation can use expert experience to set fixed weights (e.g., 0.4:0.3:0.3) for linear weighting, or dynamically adjust the weights based on a Bayesian network, updating prior probabilities based on historical success cases. This generates a comprehensive feasibility judgment index to support the decision on whether to proceed with forming.

[0056] Example 3, taking the development of a novel integrated liquid hydrogen servo valve body as an example, the laser melting forming method for the complex flow channel structure of the liquid hydrogen valve in this example can be as follows: After the design team completes the CAD model of the valve body containing a spiral cooling channel and multi-stage throttling orifices, the system automatically extracts structural feature parameters such as the minimum orifice diameter of 0.8mm and the maximum overhang angle of 65°; at the same time, it calls the key parameters such as the laser power fluctuation rate of ±2% and the minimum layer thickness of 20μm of a certain LPBF device in the equipment archive, and obtains the hot cracking sensitivity index and -253°C yield strength data of Inconel 718 alloy from the material library; after the three types of raw data are standardized and preprocessed, they are respectively input into the structural complexity model (output 0.78), the equipment matching model (output 0.85), and the material adaptability model (output 0.72); the forming feasibility evaluation value is obtained by weighting with 0.4 / 0.3 / 0.3, which is higher than the threshold of 0.7, so it is determined to be feasible and enters the path planning stage.

[0057] In one embodiment, the formula for calculating the forming feasibility assessment value is as follows:

[0058] In the formula, This represents the feasibility assessment value for forming. This represents the evaluation value of the flow channel structure complexity. This indicates the equipment capability matching evaluation value. This indicates the material's adaptability to forming assessment value. The weighting factors represent the evaluation values ​​of the complexity of the flow channel structure. The weighting factor represents the equipment capability matching evaluation value. The weighting factor represents the material forming adaptability assessment value.

[0059] The weighting factor for the flow channel structure complexity assessment value can be an adjustable coefficient used to adjust the proportion of the flow channel structure complexity assessment value in the comprehensive assessment of forming feasibility. It can reflect the weight of the impact of geometric complexity on overall forming feasibility and supports dynamic adjustment according to application scenarios. In an exemplary embodiment, the weighting factor for the flow channel structure complexity assessment value can be configured by combining historical defect data inversion, expert experience setting, or service condition sensitivity. For example, the weighting factor for the flow channel structure complexity assessment value can include, but is not limited to, one or more of the following: weights based on historical defect data inversion, fixed weights set by expert experience, and adaptive weights based on service condition sensitivity.

[0060] The weighting factor for the equipment capability matching evaluation value can be an adjustable coefficient used to adjust the proportion of the equipment capability matching evaluation value in the comprehensive evaluation of forming feasibility. It can reflect the criticality of current equipment performance to the success of forming and can be recalibrated during equipment upgrades or replacements. Furthermore, the weighting factor for the equipment capability matching evaluation value can adopt a low-weight configuration for high-precision equipment, a high-risk compensation weight for older equipment, or a standardized weight common to multiple equipment platforms. The weighting factor for the material forming adaptability evaluation value can be an adjustable coefficient used to adjust the proportion of the material forming adaptability evaluation value in the comprehensive evaluation of forming feasibility. It can highlight the impact of the material's reliability under extremely low temperatures and rapid solidification conditions on overall feasibility. In a specific embodiment, the weighting factor for the material forming adaptability evaluation value may include a low-temperature service-oriented weight, a crack resistance-priority weight, and a process window-wide guidance weight.

[0061] The forming feasibility assessment value can be obtained by multiplying the three assessment values ​​by their corresponding weighting factors, summing the results, and then calculating using the inverse function of the hyperbolic tangent function to generate a single numerical forming feasibility assessment value. Furthermore, a weighted comprehensive analysis can be performed on the flow channel structure complexity assessment value, equipment capability matching degree assessment value, and material forming adaptability assessment value to obtain the forming feasibility assessment value. This can be achieved by linearly weighting with fixed weights (e.g., 0.4, 0.3, 0.3) and calculating using the inverse function of the hyperbolic tangent function, suitable for mature material-equipment combinations, or by dynamically optimizing the weighting factors using a machine learning model (e.g., random forest feature importance). This allows for the quantifiable fusion of multi-dimensional assessment indicators and supports flexible adjustment of the importance of each factor to adapt to different engineering scenarios.

[0062] For example, in the scenario of batch process review of multiple models of liquid hydrogen valves, the laser melting forming method for complex flow channel structures of liquid hydrogen valves in this embodiment can be as follows: When reviewing three different designs of liquid hydrogen valves, the system calculates the flow channel structure complexity, equipment matching degree, and material adaptability evaluation value respectively; for high-reliability valves used for core power components, a material forming adaptability weight factor of 0.5 is assigned (0.25 for the others), because the consequences of failure at -253°C are severe; while for valves used for ground testing, a balanced weight (1 / 3 for each) is adopted; after calculation using a unified formula, only designs with evaluation values ​​higher than 0.75 enter the printing stage, while the rest are returned to design optimization, thus avoiding high-risk trial production.

[0063] In one embodiment, the specific method for obtaining the flow channel structure complexity evaluation value is as follows: By analyzing the three-dimensional model data of the complex flow channel of the target liquid hydrogen valve, the characteristic parameters of the flow channel are extracted. The characteristic parameters include aspect ratio, rate of curvature change, number of cross holes, overhang angle and minimum wall thickness. Weights are assigned to the characteristic parameters and weighted analysis is performed to obtain the flow channel structure complexity assessment value. The aspect ratio can be the ratio of the length of a local channel to its equivalent diameter, reflecting the impact of deep and narrow structures on powder filling, laser penetration, and heat conduction. In an exemplary embodiment, the aspect ratio may include, but is not limited to, one or more of the following: the aspect ratio of a straight hole, the equivalent aspect ratio of a curved channel, and the average aspect ratio of a variable cross-section segment. The rate of curvature change can be the gradient of the curvature of the channel centerline along the path direction, characterizing the degree of geometric abrupt change and affecting the stability of the molten pool and residual stress concentration. The number of intersecting holes can be the total number of interconnected or intersecting channels in the channel system, indicating the number of areas with support deficiency risks and points prone to incomplete fusion defects. The overhang angle can be the maximum tilt angle of the channel inner wall relative to the horizontal plane, determining whether process support is required and the difficulty of controlling the surface roughness of the formed surface. In a specific embodiment, the overhang angle may include the local maximum overhang angle, the proportion of the overhang area, and the critical self-supporting angle range. The minimum wall thickness can be the minimum material thickness between adjacent cavities of the channel or between a cavity and the outer contour, affecting heat conduction efficiency, cooling rate, and structural strength.

[0064] By analyzing the 3D model data of the complex flow channel of the target liquid hydrogen valve, characteristic parameters of the flow channel are extracted. These parameters include aspect ratio, rate of curvature change, number of intersecting holes, overhang angle, and minimum wall thickness. Five types of structurally sensitive parameters can be automatically identified and calculated based on the 3D geometric model. Furthermore, this operation can be achieved by directly reading parametric features using CAD API and calculating derived indices, or by extracting curvature and overhang information through geometric differential analysis using a triangular mesh model. This transforms geometric complexity into a quantifiable input to support structural difficulty assessment. Weighted analysis is performed on the characteristic parameters to obtain the flow channel structural complexity assessment value. This can be achieved by normalizing each characteristic parameter and then linearly combining them according to preset weights. In a specific embodiment, this operation can be achieved by using the Analytic Hierarchy Process (AHP) to determine the relative importance weights of each parameter, or by optimizing the weight coefficients based on historical forming failure cases. This generates a single numerical representation of the overall geometric forming difficulty.

[0065] The specific method for obtaining the equipment capability matching evaluation value is as follows: By comparing and analyzing the parameters of laser spot diameter, positioning accuracy, maximum forming size, powder thickness range and scanning speed range of laser melting and forming equipment with the flow channel structure characteristic parameters, and assigning corresponding weights to the matching degree of different parameters, the equipment capability matching degree evaluation value is obtained. The laser spot diameter can be the effective diameter of the energy distribution of the laser beam on the focusing plane, and can be used to determine the minimum geometric feature size and edge resolution that can be formed. For example, the laser spot diameter can include the Gaussian spot diameter (1 / e²), the effective working area of ​​the flat-top beam, and the spot drift range under dynamic focusing. Positioning accuracy can be the accuracy of the device's motion system in achieving the commanded position in three-dimensional space, and can be used to affect the dimensional consistency and assembly sealing of key mating surfaces in the flow channel. The maximum forming size can be the linear dimension corresponding to the maximum envelope volume of the parts that can be accommodated within the device's build chamber, and can be used to constrain whether the overall shape of the liquid hydrogen valve can be completed in a single forming operation. Further, the maximum forming size can include the independent maximum stroke in the X / Y / Z directions, the maximum diagonal buildable length, and the uniformity boundary of the effective forming area. The powder thickness range can be the range of single-layer metal powder thickness that the device can stably lay, and can be used to affect the interlayer bonding quality, surface roughness, and forming efficiency. The scanning speed range can be the range of scanning rates that the laser galvanometer system can stably operate within, and can be used to control the energy input density and the molten pool cooling rate.

[0066] By comparing and analyzing the parameters of the laser spot diameter, positioning accuracy, maximum forming size, powder thickness range, and scanning speed range of the laser melting forming equipment with the flow channel structural characteristic parameters, and assigning corresponding weights to the matching degree of different parameters, an evaluation value of the equipment capability matching degree is obtained. This can be achieved by establishing a mapping function between equipment capability parameters and structural requirements and calculating a matching score. Furthermore, this operation can be implemented by setting a threshold for each equipment parameter (e.g., spot diameter ≤ minimum channel width × 0.6), with full marks awarded for meeting the threshold and linear deductions for otherwise unmet requirements, or by constructing a multi-dimensional matching matrix and calculating the overall matching degree through fuzzy comprehensive evaluation. This allows for the quantification of whether the equipment possesses the hardware foundation to support high-quality forming of the flow channel.

[0067] The specific method for obtaining the material forming adaptability assessment value is as follows: By testing and evaluating the performance parameters of the forming material, such as powder flowability, density, mechanical properties, purity, and laser energy absorption rate, and combining these with the service environment requirements of the liquid hydrogen valve, weighted analysis was performed on these performance parameters to obtain the material forming adaptability evaluation value.

[0068] Powder flowability refers to the ability of metal powder to spread uniformly under gravity or airflow, which determines the uniformity of powder spreading and affects interlayer defects and density. Density is the ratio of the actual density to the theoretical density of the formed part, which directly relates to porosity and mechanical properties, and is a fundamental guarantee for liquid hydrogen sealing. In an exemplary embodiment, density may include volume average density, local micro-area density fluctuations, and near-surface density gradient. Mechanical properties can be the strength, plasticity, and toughness indicators exhibited by the material after LPBF forming and heat treatment, which can be used to ensure the structural integrity of the valve under high pressure conditions at -253°C. Further, mechanical properties may include low-temperature yield strength, fracture toughness K_IC, fatigue limit under cyclic loading, etc. Purity can be the content level of impurity elements such as oxygen, nitrogen, and sulfur, as well as inclusions in the material, which can be used to suppress low-temperature brittle fracture and hydrogen-induced cracking. Laser energy absorption rate can be the proportion of incident laser energy absorbed by the material surface, which can affect the molten pool formation efficiency and process window width. In one specific embodiment, the laser energy absorptivity may include the initial absorptivity at room temperature, the dynamic absorptivity in the molten state, and the sensitivity to surface oxidation state. Service environment requirements may be the performance constraints on materials and structures of liquid hydrogen valves under conditions of -253°C, high pressure, and high cleanliness; these can be used as boundary conditions for material evaluation to guide the weighting of performance parameters. Furthermore, service environment requirements may include cryogenic toughness thresholds, hydrogen compatibility standards, and upper limits for leakage rates.

[0069] By testing and evaluating the performance parameters of the powder material, including its flowability, density, mechanical properties, purity, and laser energy absorption rate, and considering the service environment requirements of the liquid hydrogen valve, weights are assigned to these performance parameters for weighted analysis to obtain a material forming adaptability assessment value. This can be achieved by benchmarking measured or database material performance data against service requirements and then weighting and synthesizing an adaptability score. In one specific embodiment, this operation can be achieved by setting a performance threshold based on service environment requirements (e.g., purity <200ppm), resetting the weights of items that do not meet the threshold to zero or giving a negative score, or by introducing a low-temperature performance attenuation factor to correct the room-temperature mechanical performance data before weighting. This allows for the evaluation of the material's dual applicability under both process and extreme service conditions.

[0070] Example 4, taking the feasibility assessment of the flow channel of the liquid hydrogen main control valve as an example, the laser melting forming method for the complex flow channel structure of the liquid hydrogen valve in this example can be as follows: For the flow channel of the valve core containing 3 intersecting holes, a minimum wall thickness of 0.6 mm, and a maximum overhang angle of 70°, the system extracts parameters such as the length-to-diameter ratio of 4.2 and the curvature change rate of 0.35 / mm from the CAD model; in terms of equipment, the LPBF equipment used has a spot diameter of 80 μm (less than the minimum channel of 1.2 mm), a positioning accuracy of ±5 μm, and a powder thickness of 20–50 μm; the material selected is high-purity AlSi10Mg, with a measured powder Hall flow rate of 18 s / 50 g, a density of 99.8%, and an elongation of >8% at -253°C. The structural parameters were weighted by AHP to obtain a complexity assessment value of 0.81; the equipment parameters were matched with the structural requirements item by item to obtain a weighted matching degree of 0.88; the material properties were combined with the liquid hydrogen service requirements (emphasizing purity and low temperature ductility) to obtain an adaptability of 0.85; the three inputs were subsequently used to generate a forming feasibility assessment value.

[0071] In one embodiment, the specific analysis process for obtaining the forming quality risk value of each forming path is as follows: Obtain the complex flow channel region of the liquid hydrogen valve that can be laser-melted and the optimal forming direction based on the forming feasibility assessment value; The complex flow channel region of the liquid hydrogen valve can be a subset of flow channel geometry that has been confirmed as successfully printable after a forming feasibility assessment. This subset can serve as a spatial constraint boundary for path planning, excluding unmanufacturable areas to improve path effectiveness. Furthermore, the complex flow channel region of the liquid hydrogen valve, together with the optimal forming direction, can constitute the initial input conditions for path generation. The optimal forming direction can be the best placement orientation of the part within the forming chamber, determined comprehensively based on structural features and equipment capabilities. This orientation can be used to reduce support dependence, improve heat dissipation, and reduce residual deformation, providing a reference coordinate system for path planning. In an exemplary embodiment, the optimal forming direction can be obtained through optimization using objective functions such as minimizing overhang area, support volume, or thermal stress concentration. Obtaining the complex flow channel region of the liquid hydrogen valve suitable for laser melting forming and the optimal forming direction based on the forming feasibility assessment value can be achieved by filtering manufacturable areas based on the calculated forming feasibility assessment value and calling the orientation optimization module to output the optimal placement posture. Furthermore, this operation can be achieved by marking infeasible areas as no-scan zones in the CAD model, performing path planning only for feasible areas, or using a multi-objective optimization algorithm to search for the direction that minimizes support and thermal stress while meeting the feasibility threshold. This ensures that subsequent path generation is confined within the process-feasible space, thereby improving the effectiveness of the solution.

[0072] Based on the flow channel region and the optimal forming direction, multiple feasible forming path planning schemes are automatically generated using slicing software and path planning algorithms, and the path information of each forming path planning scheme is obtained. The slicing software can be a specialized tool that discretizes a 3D CAD model layer by layer into 2D contour data along the forming direction, providing geometric boundary information for each layer to the path planning algorithm. In one specific embodiment, the slicing software can be one or more of the following: open-source slicing platforms (such as Slic3r-like tools), dedicated slicing systems, and self-developed high-precision flow channel adaptation slicing modules. The path planning algorithm can be a calculation program that automatically generates laser scanning trajectories based on the slice contour and process constraints, enabling the generation of diverse and repeatable path schemes, replacing manual experience-based settings.

[0073] Based on the flow channel region and optimal forming direction, multiple feasible forming path planning schemes are automatically generated using slicing software and path planning algorithms. This can be achieved by slicing the flow channel region under a defined forming direction and calling different path planning algorithms to generate diverse schemes. Furthermore, this operation can generate schemes by fixing slicing parameters and switching between three or more path planning algorithms (such as island, spiral, and contour offset), or by adjusting key parameters (such as island size and rotation angle step size) within the same algorithm framework to generate variant paths. This enables automated and diversified generation of path schemes, eliminating the need for manual intervention. Path information can be a set of digital data describing the scanning trajectories of each layer in the forming path planning scheme, which can be used as a geometric-temporal input for finite element simulation to drive the heat source movement model. In an exemplary embodiment, path information can be jointly output by slicing software and path planning algorithms, including vector coordinates, scanning order, and partition identifiers. Furthermore, path information can be used in conjunction with forming process simulation results to extract path forming information.

[0074] Obtaining path information for each established path planning scheme can be achieved by parsing scan vectors, layer sequences, and partition labels from the path planning output file. Furthermore, this operation can be accomplished by exporting standard CLI or SLIC format files and parsing them into structured data, or by directly reading the trajectory data stream from the path planning module's memory via API, thus providing accurate heat source motion input for subsequent simulations.

[0075] Finite element simulation technology is used to simulate the forming process of various forming path planning schemes, and to predict the behavior of the molten pool, temperature field distribution, stress and strain and possible defects. Finite element method (FEM) simulation can be a numerical simulation of the LPBF layer-by-layer forming process based on thermo-mechanical coupling control equations. It can be used to predict the evolution of key physical fields and defect initiation trends during forming, replacing some physical prototyping. Melt pool behavior can be the morphology and stability characteristics of the dynamic liquid phase region formed by the melting of metal powder under laser irradiation. It can directly affect metallurgical bonding quality, surface roughness, and porosity formation tendency. In a specific embodiment, melt pool behavior may include, but is not limited to, melt pool depth fluctuations, melt pool tail solidification front stability, and keyhole oscillation frequency. Temperature field distribution can be the three-dimensional temperature gradient and thermal accumulation state that evolves over time within the part during forming. It can determine the cooling rate, grain orientation, and thermal stress magnitude, and is a key driving factor for defect formation. Stress and strain can be the internal mechanical response state caused by non-uniform thermal expansion and phase transformation. It can be used to correlate deformation warpage, cracking risk, and structural stability under service loads. In an exemplary embodiment, stress and strain may include, but is not limited to, the volume of residual tensile stress concentration areas, plastic strain accumulation paths, and elastic recovery deformation. Potential defects can be forming anomalies predicted by simulation under specific path and process conditions, which can be used as a direct basis for risk assessment, covering types such as incomplete fusion, porosity, cracks, and interlayer delamination.

[0076] Finite element method (FEM) simulation is used to simulate the forming process of various forming path planning schemes, predicting molten pool behavior, temperature field distribution, stress and strain, and potential defects. This can be achieved by mapping path information to moving heat source loads, solving thermo-mechanical coupling equations, and identifying defects based on field variables. Furthermore, this operation can be achieved by using simplified heat source models (such as Gaussian distributions) for rapid macroscopic simulation to focus on the overall deformation trend, or by introducing a CFD-structural coupling model to finely simulate molten pool flow and the formation of microscopic defects during solidification. This allows for pre-simulation of the process response before physical forming and identification of high-risk paths.

[0077] Based on the analysis of path information and forming process simulation results of each forming path planning scheme, path forming information and defect prediction information of each forming path are extracted. The path forming information can be a quantitative feature directly related to the forming process extracted from path information and simulation results. It can be used to characterize the comprehensive performance of the path in terms of energy input efficiency, thermal management capability, and geometric adaptability. In a specific embodiment, the path forming information can be calculated by fusing the path file and simulation field variables through data post-processing. The defect prediction information can be a quantitative indicator of the location, type, and severity of potential defects identified based on the simulated physical field. It can be used to provide defect dimension input features for the forming quality risk value. In an exemplary embodiment, the defect prediction information can be extracted from data such as temperature field and stress field through threshold criteria or machine learning classifiers. Based on the analysis of path information and forming process simulation results of each forming path planning scheme, the path forming information and defect prediction information of each forming path are extracted. This can be achieved by fusing geometric path data and physical field simulation results, and extracting the two types of information through feature engineering. Furthermore, this operation can be achieved by automatically calculating the scan length and number of turns for each layer using a script and associating them with the maximum temperature gradient, or by training a convolutional neural network to directly regress the defect prediction index from the stress field image, thereby constructing a multi-dimensional input feature set that can be used for risk modeling.

[0078] By analyzing the path forming information and defect prediction information of each forming path, the forming quality risk value of each forming path is obtained.

[0079] By analyzing the path forming information and defect prediction information of each forming path, the forming quality risk value of each forming path can be obtained. This can be achieved by inputting the extracted multidimensional features into a risk assessment model and outputting a comprehensive risk score. Furthermore, this operation can be achieved by using a weighted linear combination to assign high weights to key indicators such as high stress ratio and porosity prediction value, or by constructing a random forest classifier to train a nonlinear risk mapping relationship using historical successful cases as labels. This allows for the comparability of path scheme quality and the basis for optimal selection.

[0080] Example 5, taking the optimized manufacturing of the flow channel of a liquid hydrogen valve core as an example, the laser melting forming method for the complex flow channel structure of the liquid hydrogen valve in this example can be as follows: In a certain type of valve core with a double spiral cooling channel, firstly, based on the forming feasibility assessment value of 0.85, it is confirmed that the entire flow channel area is manufacturable, and the optimal forming direction is determined to be the positive Z-axis; then, commercial slicing software is used in conjunction with three path planning algorithms (island, spiral filling, and stress equalization) to generate three sets of path schemes; after extracting the path information of each scheme, it is imported into the finite element platform for layer-by-layer thermo-mechanical simulation. The results show that the spiral filling scheme has local heat accumulation at the channel intersection (peak temperature exceeds 2100K), while the maximum residual tensile stress of the stress equalization scheme is lower than the material yield strength; further, path forming information (such as average scanning turning angle, local energy density) and defect prediction information (such as the volume ratio of high stress area is 0.7%, no unfused area) are extracted from the simulation results. Finally, the forming quality risk value of the stress equalization path is calculated to be the lowest (0.22). This scheme is selected for printing. The formed part is found to have no internal defects after X-ray inspection and meets the liquid hydrogen sealing requirements.

[0081] In one embodiment, the path forming information specifically includes: scan line length uniformity, number of jumps and overlap rate consistency; the defect prediction information specifically includes: porosity prediction value, crack sensitivity index and deformation prediction value.

[0082] The uniformity of scan line length can be an indicator of the dispersion of the length distribution of each scan line segment within the same layer. It can be used to reflect the spatial uniformity of laser energy input, affecting the stability and local density of the molten pool. In an exemplary embodiment, the uniformity of scan line length can be quantitatively characterized by parameters such as the difference between the maximum and minimum scan line lengths within the layer, the coefficient of variation of scan line length, or the proportion of short scan lines. The number of jumps can be the frequency of discontinuous movement (i.e., repositioning after the beam is turned off) in the laser scanning path. It can be used to assess the risk that a high number of jumps may lead to local thermal shock, residual stress concentration, and decreased forming efficiency. Furthermore, the number of jumps can be statistically analyzed using indicators such as the total number of jumps within the layer, the number of jumps across regions, or the overlap of jump positions between adjacent layers.

[0083] Overlap rate consistency refers to the degree of fluctuation in the overlap ratio between adjacent scan channels across the entire layer or a local area. It can be used to determine the metallurgical bonding quality, surface roughness, and porosity uniformity within the layer. In this embodiment, overlap rate consistency can be measured using parameters such as the standard deviation of the overlap rate, the proportion of the lowest overlap rate area, or the continuous length of insufficient overlap. Porosity prediction can be the proportion of pore volume within the formed part to the total volume, estimated based on simulation or data models. It can directly affect the sealing performance and structural strength of cryogenic fluid control valves under high pressure. Crack sensitivity index is a quantitative index of cracking tendency calculated by comprehensively considering thermal stress gradient, cooling rate, and material cryogenic brittleness. It can be used to assess the risk of hot or cold cracking in parts during forming or cryogenic service. In a specific embodiment, the crack sensitivity index can be constructed using sub-items such as the integral of the critical strain exceeding the limit for hot cracking, the stress weighted by the grain boundary weakening factor, or the probability of cracking induced by cryogenic phase transformation. Deformation prediction can be the dimensional deviation of the formed part relative to the ideal geometry, predicted through simulation. It can be used to assess the accuracy of key flow channel dimensions, assembly fit, and fluid dynamics performance. In this embodiment, the predicted deformation value may include, but is not limited to, the overall warping displacement amplitude, the volume of the local shrinkage out-of-tolerance area, and the flatness deviation of the key mating surfaces.

[0084] Example 6, taking the multi-channel integrated manufacturing of a cryogenic fluid control valve body as an example, the laser melting forming method for the complex flow channel structure of the liquid hydrogen valve in this example can be used for valve body structures containing three sets of parallel microchannels. In the path risk assessment stage, the system extracts path forming information for three candidate paths: Path A has a scan line length variation coefficient of 0.35, jump number of 12 times / layer, and overlap rate standard deviation of 8%; Path B has corresponding values ​​of 0.18, 6 times / layer, and 3%; Path C has 0.42, 18 times / layer, and 10%. At the same time, defect prediction information shows: Path A has a predicted porosity of 1.2%, a crack sensitivity index of 0.68, and a predicted deformation of ±85μm; Path B has 0.4%, 0.31, and ±32μm; Path C has 1.8%, 0.82, and ±110μm. Comprehensive analysis shows that path B performs best in terms of energy input uniformity, thermal disturbance control, and defect suppression, and has the lowest forming quality risk value. Path B was ultimately selected for printing, with a measured density of 99.92% and a flow channel size deviation of <±40μm, meeting the requirements for liquid hydrogen sealing and assembly.

[0085] In one embodiment, the specific formula for calculating the forming quality risk value of each forming path is as follows:

[0086] In the formula, r represents the number of each forming path planning scheme, r = 1, 2, 3, ..., R, and R represents the total number of forming path planning schemes. This represents the forming quality risk value of the r-th forming path planning scheme. This represents the standard deviation of the scan line length for the r-th scheme. Indicates the average scan line length. This represents the number of transitions in the r-th scheme. This represents the maximum number of transitions among all possible solutions. This represents the overlap rate of the r-th scheme. The target overlap rate is represented by k1, k2, and k3, which represent the weighting factors for scan line length uniformity, number of jumps, and overlap rate consistency, respectively. This represents the predicted porosity value for the r-th scheme. This represents the crack sensitivity index of the r-th scheme. Let m1, m2, and m3 represent the predicted deformation value of the r-th scheme, respectively, and m1, m2, and m3 represent the weighting factors of porosity, crack sensitivity, and deformation. α represents the weighting coefficient of path forming information on the forming quality risk value, and β represents the weighting coefficient of defect prediction information on the forming quality risk value.

[0087] The standard deviation of scan line length can be a statistical measure of the dispersion of each scan line length relative to its average value in the same forming path scheme. It can be used to characterize the spatial uniformity of laser energy input. The smaller the standard deviation, the more balanced the heat accumulation distribution, which helps to suppress residual stress concentration. In an exemplary embodiment, the standard deviation of scan line length can be combined with the average scan line length to assess the uniformity of the scanning path, thereby quantifying the consistency of heat input distribution and avoiding local overheating or cold areas. Furthermore, the standard deviation of scan line length can include, but is not limited to, one or more of the following: intra-layer scan line length variation coefficient, inter-region scan density standard deviation, and single-island scan segment length fluctuation. The number of jumps can be the total frequency of abrupt changes in the laser scanning direction in the forming path (such as 90° turning or backtracking). It can be used to reflect the dynamic stability risk of the molten pool. High jumps can easily lead to keyhole collapse, spatter, or incomplete fusion. In a specific embodiment, the number of jumps can be normalized to the number of jumps in the current scheme divided by the maximum number of jumps among all candidate schemes, thereby eliminating the absolute quantitative differences between schemes and supporting fair comparison across schemes. For example, the number of jumps may include, but is not limited to, one or more of the following: the number of acute angle turns, the frequency of scan vector reverse switching, and the number of cross-region jump connections.

[0088] The overlap ratio can be the percentage of the overlapping area between adjacent scan lines to the single-pass melt width. It can be used to influence the interlayer metallurgical bonding quality and surface roughness. Deviation from the target value can easily lead to porosity or excessive remelting. In this embodiment, the overlap ratio can be compared with the target overlap ratio to ensure sufficient overlap of melt channels to achieve dense metallurgical bonding, while avoiding excessive remelting that leads to surface deterioration. Furthermore, the overlap ratio can include, but is not limited to, one or more of the following: transverse overlap ratio, longitudinal interlayer overlap ratio, and functional area local overlap ratio. The porosity prediction value can be the proportion of internal pore volume of the formed part estimated based on simulation or data model. It can be used to directly correlate with pressure bearing capacity and fatigue life, and is a key indicator of the sealing performance of liquid hydrogen valves. In an exemplary embodiment, the porosity prediction value can participate in weighted fusion with other defect prediction information to quantify the tendency of the path to induce key service defects. For example, the porosity prediction value can include, but is not limited to, one or more of the following: spheroidized porosity ratio, unfused pore density, and solidification shrinkage pore distribution index.

[0089] The crack sensitivity index can be a quantitative indicator of cracking risk calculated by comprehensively considering the material's thermal cracking tendency, local stress state, and cooling rate. It can be used to predict the possibility of brittle fracture under low-temperature service conditions, ensuring structural integrity at -253°C. In this embodiment, the crack sensitivity index can be an important component of the physical risk component of defects, participating in the final risk value calculation through a weighted method. Furthermore, the crack sensitivity index can include, but is not limited to, one or more of the following: the time of exceeding the critical strain limit for thermal cracking, the duration index of the liquid film at grain boundaries, and the peak value of the constraint-weighted stress. The predicted deformation value can be the overall or local geometric deviation of the formed part obtained from simulation, which can be used to affect the dimensional accuracy of the flow channel and the sealing performance of the valve core-seat fit. In a specific embodiment, the predicted deformation value can be combined with the predicted porosity value and the crack sensitivity index to form a defect prediction information set, used to evaluate the impact of the path scheme on the final performance. For example, the predicted deformation value can include, but is not limited to, one or more of the following: the warpage displacement amplitude, the offset of the flow channel centerline, and the flatness error of the flange mounting surface.

[0090] The forming quality risk value of the r-th forming path planning scheme can be calculated by normalizing the path forming information and defect prediction information separately, then summing them according to their weights, and finally fusing them using α and β to obtain the final risk value. Furthermore, the forming quality risk value of the r-th forming path planning scheme can be calculated directly using a formula, where each parameter is automatically filled in by simulation and path analysis, or by constructing a risk value calculation microservice that receives feature vectors and returns standardized scores, thereby providing a unified and comparable quantitative indicator for path optimization.

[0091] Assessing scan path uniformity based on the standard deviation of scan line length and the average scan line length can be achieved by calculating the standard deviation of each scan line length and comparing it with the average value to form a dimensionless uniformity index. In an exemplary embodiment, assessing scan path uniformity based on the standard deviation of scan line length and the average scan line length can be achieved by calculating the standard deviation segmented by functional region and weighting it to synthesize an overall uniformity score, or by introducing a sliding window to analyze the length fluctuations of 10 consecutive scan lines in a local area. This can quantify the consistency of heat input distribution and avoid local overheating or cold spots.

[0092] Normalizing the number of jumps in the r-th scheme relative to the maximum number of jumps among all schemes can be achieved by dividing the number of jumps in the current scheme by the maximum value among all candidate schemes, resulting in a normalized value in the [0, 1] interval. In this embodiment, logarithmic compression is used to process schemes with extremely high jumps to reduce the impact of outliers, thereby eliminating the absolute difference in the number of schemes and supporting fair comparison across schemes. Comparing the consistency between the overlap rate of the r-th scheme and the target overlap rate can be achieved by calculating the absolute deviation or relative error between the actual overlap rate and the target value. For example, comparing the consistency between the overlap rate of the r-th scheme and the target overlap rate can be achieved by setting a tolerance band (e.g., ±5%), applying a penalty term if it exceeds the tolerance band, or by using a Gaussian function to model the consistency score, with a score of 1 at the target value and attenuation if it deviates. This ensures sufficient overlap of the melt channels to achieve dense metallurgical bonding while avoiding excessive remelting that leads to surface deterioration.

[0093] The weighted fusion of path forming information (k1, k2, k3) generates path structure risk components, which can be achieved by linearly combining normalized scan uniformity, jump count, and overlap consistency according to k1 to k3. In a specific embodiment, the weighted fusion of path forming information (k1, k2, k3) to generate path structure risk components can be achieved by determining the weights of k1 to k3 through expert scoring or by optimizing the weight coefficients through regression analysis of historical successful cases, thereby comprehensively reflecting the contribution of path geometric rationality to forming stability. The weighted fusion of defect prediction information (m1, m2, m3) generates defect physical risk components, which can be achieved by weighting and summing the predicted values ​​of porosity, crack sensitivity, and deformation according to m1 to m3. Furthermore, the weighted fusion of defect prediction information (m1, m2, m3) to generate defect physical risk components can be weighted according to the severity of liquid hydrogen valve failure modes (m2 > m1 > m3), or the weights can be automatically determined after dimensionality reduction using principal component analysis, thereby quantifying the path's tendency to induce critical service defects.

[0094] The final forming quality risk value is obtained by combining the path structure risk and the physical risk of defects using weighting coefficients α and β. This can be achieved by weighting the two types of risk components according to α and β, typically satisfying α + β = 1. In this embodiment, the final forming quality risk value obtained by combining the path structure risk and the physical risk of defects using weighting coefficients α and β can be obtained by fixing α = 0.4 and β = 0.6 to emphasize defect control, or by dynamically adjusting according to the project stage: focusing on path stability during the R&D phase and focusing on performance consistency during the mass production phase, thereby balancing the dual objectives of process manufacturability and end-performance reliability.

[0095] Taking the optimal selection of multiple path risk levels as an example, the laser melting forming method for complex flow channel structures of liquid hydrogen valves in this embodiment can generate five path schemes (R=5) for a certain liquid hydrogen valve flow channel, extract the standard deviation of scan line length, number of jumps, and overlap rate of each scheme, and combine finite element simulation to obtain predicted values ​​of porosity, crack sensitivity, and deformation; set k1=0.4, k2=0.3, k3=0.3, m1=0.3, m2=0.5, m3=0.2, α=0.4 β = 0.6; Calculations show that Scheme 3 has the best scanning uniformity (smallest standard deviation), 8 jumps (maximum 15), 92% overlap (target 90%), predicted porosity of 0.12%, crack sensitivity index of 0.18, and deformation of 0.08 mm; Substituting into the formula, its forming quality risk value is 0.27, which is the lowest among all schemes. Therefore, Scheme 3 was selected for printing. The measured density is 99.96%, there are no cracks, and the dimensional deviation is <0.1 mm, which meets the liquid hydrogen sealing requirements.

[0096] In one embodiment, the specific implementation process of laser melting forming of complex flow channel structures for liquid hydrogen valves, which selects the forming path planning scheme with the lowest forming quality risk value, further includes: Based on the selected forming path planning scheme, layer slicing is performed to generate scan path files for each layer; The selected forming path planning scheme can be the optimal laser scanning strategy chosen after assessing the forming quality risk value, and can be used as the benchmark input for subsequent slicing and process parameter configuration. Furthermore, the selected forming path planning scheme can drive layered slicing processing to generate scan path files. Layered slicing processing can be the process of discretizing the three-dimensional path planning scheme into layer-by-layer two-dimensional scanning instructions along the forming direction, and can be used to realize the transformation of complex flow channel structures from digital models to executable manufacturing instructions. In an exemplary embodiment, layered slicing processing can use a slicing engine to partition the path geometry according to a set layer thickness. The scan path file for each layer can be a machine-readable file containing the laser scanning coordinate sequence of each layer, partition identifiers, and basic process markers, and can be used to directly drive the laser galvanometer movement and process parameter calls. In a specific embodiment, the scan path file for each layer can be a CLI format path file, an SLM equipment-specific JOB file, a G-code extended file with metadata annotations, etc. Based on the selected forming path planning scheme, layered slicing processing is performed to generate the scan path file for each layer, which can be the process of partitioning the preferred path scheme layer by layer according to a set layer thickness and outputting a file containing trajectory and metadata. Furthermore, this operation can be achieved by uniformly slicing with a fixed layer thickness of 50 μm, or by automatically switching to a layer thickness of 20 μm in thin-walled or high-curvature regions to improve accuracy, thereby completing the transformation from abstract path strategy to device-executable instructions.

[0097] Based on the structural characteristics of different regions of the flow channel, the process parameters in the scan path file are optimized by partitioning. The structural characteristics of different regions of the flow channel can be local geometric differences within the liquid hydrogen valve flow channel, which can serve as the basis for zonal optimization settings and guide differentiated configuration of process parameters. For example, the structural characteristics of different regions of the flow channel can include, but are not limited to, one or more of the following: thin-walled cantilever regions, multi-hole intersection nodes, and deep, narrow channel sections. Process parameters can be specific numerical settings controlling the energy input and scanning behavior of the laser melting process, and can directly affect the stability, density, and residual stress level of the molten pool. In a specific embodiment, process parameters can include, but are not limited to, laser power, scanning speed, and scanning spacing. Zonal optimization settings can differentiate the process parameters of corresponding regions in the scanning path file based on the local geometric characteristics of the flow channel, which can be used to achieve local adaptive adjustment of energy input and alleviate uneven heat accumulation and stress concentration. Furthermore, zonal optimization settings can be achieved by matching a preset parameter rule base or simulation inversion results using a region recognition algorithm. For example, zonal optimization settings can employ low-power, high-scanning-speed configurations in thin-walled regions, reduced layer thickness and increased contour scanning times in cantilever regions, and staggered filling in intersecting hole regions to reduce thermal superposition.

[0098] Based on the structural characteristics of different regions of the flow channel, the process parameters in the scanning path file are optimized by partitioning them. This can be achieved by identifying region labels in the path file and matching preset or simulation-derived local parameter sets. In an exemplary embodiment, this operation can be implemented by automatically labeling region types based on CAD feature recognition and calling parameter templates, or by using finite element simulation to back-calculate the optimal power-velocity combination for each region and embedding it into the path file. This allows for spatial adaptation of energy input and improves the uniformity of microstructure.

[0099] The optimized scan path file is imported into the laser melting and forming equipment for the forming process. This can be achieved by loading the path file containing partition parameters through the equipment control interface and initiating printing. Furthermore, this operation can be implemented by transferring the JOB file to the equipment controller via USB or network, or by using direct API connection to achieve dynamic streaming loading of paths and parameters, thereby enabling high-fidelity, adaptive physical forming.

[0100] During the forming process, a real-time monitoring system is used to monitor the temperature of the molten pool and the state of the powder bed. When an abnormality is detected, the relevant process parameters are automatically adjusted or the forming process is paused, and an alarm is issued to remind the operator.

[0101] The real-time monitoring system can be an online process sensing and intervention device integrating sensors and feedback control modules. It can be used to dynamically capture key physical states and trigger response mechanisms during the forming process. For example, the real-time monitoring system may include, but is not limited to, one or more of the following: a coaxial infrared melt pool temperature monitoring module, a high-speed CCD powder bed spreading quality detection unit, and an acoustic emission crack initiation sensing system. The melt pool temperature can be a characterizing quantity of the instantaneous thermodynamic state of the molten metal region under laser irradiation. It can be used to reflect energy coupling efficiency and solidification conditions and is a core indicator for judging forming stability. The powder bed state can be the spreading uniformity, density, and surface morphology characteristics of the powder to be melted. It can affect the laser absorption rate and the consistency of melt pool formation; abnormal states can easily lead to incomplete fusion or spheroidization. Abnormal conditions can be process instability phenomena deviating from the normal forming window, which can be used as triggering conditions for real-time control to prevent defect propagation.

[0102] Relevant process parameters can be dynamically adjusted laser or motion control variables that can be used to compensate for process disturbances online and restore a stable forming state. Alarm prompts can be warning signals issued to operators when the system cannot automatically restore a stable state, ensuring timely manual intervention and preventing the entire part from being scrapped. During the forming process, a real-time monitoring system monitors the molten pool temperature and powder bed status, which can be achieved by collecting and analyzing key process signals in real time using infrared, visual, or acoustic sensors. Furthermore, this operation can be implemented by sampling the molten pool radiation temperature every 10ms using a coaxial infrared camera, or by using a high-speed camera combined with image processing algorithms to detect powder spreading defects, thereby establishing closed-loop perception capabilities and capturing early signs of process instability. When an abnormality is detected, relevant process parameters are automatically adjusted or forming is paused, and an alarm is issued to the operator, which can be based on preset thresholds or AI criteria to trigger feedback control logic. In an exemplary embodiment, this operation can be achieved by automatically reducing the laser power by 10% and maintaining 3 layers of observation when the molten pool temperature exceeds the limit, or by pausing forming and triggering an audible and visual alarm when incomplete fusion is detected for 3 consecutive frames, thereby suppressing defect propagation and ensuring forming robustness.

[0103] Furthermore, this invention also proposes a laser melting and forming system for complex flow channel structures in liquid hydrogen valves, the system comprising: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the steps of the laser melting and forming method for complex flow channel structures of liquid hydrogen valves as described in any of the above-mentioned methods.

[0104] Other embodiments or specific implementations of the laser melting and forming system for complex flow channel structures of liquid hydrogen valves described in this invention can be found in the above-described method embodiments, and will not be repeated here.

[0105] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A laser melting forming method for complex flow channel structures of liquid hydrogen valves, characterized in that, The method includes: By analyzing the structural feature data of the complex flow channel of the liquid hydrogen valve, the parameter data of the laser melting forming equipment, and the performance data of the forming material, a forming feasibility assessment value is obtained. The forming feasibility assessment value is used to evaluate the feasibility of the current laser melting forming and to determine whether the laser melting forming of the complex flow channel structure of the liquid hydrogen valve can be carried out. For cases where laser melting forming is deemed feasible based on forming feasibility assessment values, various forming path planning schemes for laser melting forming of complex flow channel structures are obtained. By combining the forming path planning schemes with the forming information and defect prediction information of each path, the forming quality risk value of each forming path planning scheme is obtained. The forming quality risk value is used to represent the probability of defects occurring when the path is selected for forming. By analyzing the forming quality risk value of each forming path planning scheme, the forming path planning scheme with the smallest forming quality risk value is selected for laser melting forming of complex flow channel structure of liquid hydrogen valve.

2. The laser melting forming method for complex flow channel structures of liquid hydrogen valves as described in claim 1, characterized in that, The specific process for determining whether laser melting and forming of complex flow channel structures for liquid hydrogen valves is feasible includes: The forming feasibility assessment threshold is obtained based on the laser melting forming simulation training of a typical liquid hydrogen valve structure. The forming feasibility assessment threshold represents the limit value at which laser melting forming can be successfully carried out. The forming feasibility assessment value of the complex flow channel of the target liquid hydrogen valve is compared and analyzed with the forming feasibility assessment threshold. When the forming feasibility assessment value of the complex flow channel of the target liquid hydrogen valve is greater than or equal to the forming feasibility assessment threshold, it is determined that the complex flow channel of the target liquid hydrogen valve can be laser melting and forming, and the forming path planning scheme is automatically selected for forming. When the feasibility assessment value of forming the complex flow channel of the target liquid hydrogen valve is less than the feasibility assessment threshold, it is determined that the complex flow channel of the target liquid hydrogen valve is not suitable for laser melting forming and there is a risk of forming quality. An alarm mechanism is used to issue a prompt message to the process personnel to adjust the forming scheme. The forming scheme adjustment includes flow channel structure optimization, forming equipment parameter adjustment, forming material selection or pretreatment.

3. The laser melting forming method for complex flow channel structures of liquid hydrogen valves as described in claim 1, characterized in that, The specific analytical process for obtaining the feasibility assessment value includes: The three-dimensional model data and structural feature dataset of the complex flow channel of the target liquid hydrogen valve were obtained based on computer-aided design technology and structural analysis technology. Finite element analysis and material database technology were used to analyze the parameters of laser melting forming equipment and the performance data of forming materials, and to extract the key process parameter datasets of laser melting forming equipment that have a decisive influence on forming quality and the mechanical properties and formability datasets of forming materials. The structural feature dataset of the complex flow channel of the target liquid hydrogen valve, the key process parameter dataset of the laser melting forming equipment, and the performance dataset of the forming material are preprocessed to obtain target structural feature data, equipment parameter data, and material performance data. The preprocessing includes data cleaning, data transformation, data fusion, and data standardization. By analyzing the target structure feature data, equipment parameter data, and material performance data, the complexity assessment value of the flow channel structure, the equipment capability matching degree assessment value, and the material forming adaptability assessment value are obtained. By performing a weighted comprehensive analysis of the flow channel structure complexity assessment value, equipment capability matching degree assessment value, and material forming adaptability assessment value, a forming feasibility assessment value is obtained.

4. The laser melting forming method for complex flow channel structures of liquid hydrogen valves as described in claim 3, characterized in that, The specific formula for calculating the forming feasibility assessment value is as follows: In the formula, This indicates the feasibility assessment value for forming. This represents the evaluation value of the flow channel structure complexity. This indicates the equipment capability matching evaluation value. This indicates the material's adaptability to forming assessment value. The weighting factors represent the evaluation values ​​of the complexity of the flow channel structure. The weighting factor represents the equipment capability matching evaluation value. The weighting factor represents the material forming adaptability assessment value.

5. The laser melting forming method for complex flow channel structures of liquid hydrogen valves as described in claim 3, characterized in that, The specific methods for obtaining the complexity evaluation value of the flow channel structure include: By analyzing the three-dimensional model data of the complex flow channel of the target liquid hydrogen valve, the characteristic parameters of the flow channel are extracted. The characteristic parameters include the aspect ratio, the rate of change of curvature, the number of cross holes, the overhang angle and the minimum wall thickness. The characteristic parameters are assigned weights and weighted analysis is performed to obtain the flow channel structure complexity evaluation value. And / or, the specific method for obtaining the equipment capability matching degree evaluation value includes: comparing and analyzing the parameters of the laser spot diameter, positioning accuracy, maximum forming size, powder thickness range and scanning speed range of the laser melting forming equipment with the flow channel structure characteristic parameters, assigning corresponding weights to the matching degree of different parameters, and obtaining the equipment capability matching degree evaluation value; And / or, the specific method for obtaining the material forming adaptability assessment value includes: testing and evaluating the performance parameters of the forming material, such as powder flowability, density, mechanical properties, purity, and absorption rate of laser energy; combining these performance parameters with the service environment requirements of the liquid hydrogen valve; assigning weights to these performance parameters and performing weighted analysis to obtain the material forming adaptability assessment value.

6. The laser melting forming method for complex flow channel structures of liquid hydrogen valves as described in claim 1, characterized in that, The specific analysis process for obtaining the forming quality risk value of each forming path includes: Obtain the complex flow channel region and optimal forming direction of the liquid hydrogen valve that can be laser-melted based on the forming feasibility assessment value; Based on the flow channel region and the optimal forming direction, multiple feasible forming path planning schemes are automatically generated using slicing software and path planning algorithms, and the path information of each forming path planning scheme is obtained. Finite element simulation technology is used to simulate the forming process of various forming path planning schemes, and to predict the behavior of the molten pool, temperature field distribution, stress and strain and possible defects. Based on the analysis of path information and forming process simulation results of each forming path planning scheme, path forming information and defect prediction information of each forming path are extracted. By analyzing the path forming information and defect prediction information of each forming path, the forming quality risk value of each forming path is obtained.

7. The laser melting forming method for complex flow channel structures of liquid hydrogen valves as described in claim 6, characterized in that, The path forming information specifically includes: uniformity of scan line length, number of jumps, and consistency of overlap rate; the defect prediction information specifically includes: predicted porosity value, crack sensitivity index, and predicted deformation value.

8. The laser melting forming method for complex flow channel structures of liquid hydrogen valves as described in claim 6, characterized in that, The specific calculation formula for the forming quality risk value of each forming path is as follows: In the formula, r represents the number of each forming path planning scheme, r = 1, 2, 3, ..., R, and R represents the total number of forming path planning schemes. This represents the forming quality risk value of the r-th forming path planning scheme. This represents the standard deviation of the scan line length for the r-th scheme. Indicates the average scan line length. This represents the number of transitions in the r-th scheme. This represents the maximum number of transitions among all possible solutions. This represents the overlap rate of the r-th scheme. The target overlap rate is represented by k1, k2, and k3, which represent the weighting factors for scan line length uniformity, number of jumps, and overlap rate consistency, respectively. This represents the predicted porosity value for the r-th scheme. This represents the crack sensitivity index of the r-th scheme. Let m1, m2, and m3 represent the predicted deformation value of the r-th scheme, respectively, and m1, m2, and m3 represent the weighting factors of porosity, crack sensitivity, and deformation. α represents the weighting coefficient of path forming information on the forming quality risk value, and β represents the weighting coefficient of defect prediction information on the forming quality risk value.

9. The laser melting forming method for complex flow channel structures of liquid hydrogen valves as described in claim 6, characterized in that, The specific implementation process of selecting the forming path planning scheme with the minimum forming quality risk value for laser melting forming of complex flow channel structures of liquid hydrogen valves also includes: Based on the selected forming path planning scheme, layer slicing is performed to generate scan path files for each layer; Based on the structural characteristics of different regions of the flow channel, the process parameters in the scan path file are optimized by partitioning. The optimized scanning path file is imported into the laser melting and forming equipment for forming. During the forming process, a real-time monitoring system is used to monitor the temperature of the molten pool and the state of the powder bed. When an abnormality is detected, the relevant process parameters are automatically adjusted or the forming process is paused, and an alarm is issued to remind the operator.

10. A laser melting and forming system for a complex flow channel structure of a liquid hydrogen valve, characterized in that, The system includes: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the steps of the laser melting forming method for complex flow channel structures of liquid hydrogen valves as described in any one of claims 1-9.

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