1013 results about "Alloy composition" patented technology

The invention discloses preheating-free welding maritime work steel with excellent low-temperature toughness and a preparation method of the preheating-free welding maritime work steel, and belongs to the field of steel and iron material preparation. The produced steel plate has good comprehensive mechanical properties through alloy component-secondary rolling-controlled cooling process coupling design, the problem that the strength, plasticity, low-temperature toughness and preheating-free post-welding performance of the steel plate are difficult to match and harmonize is solved, the steel plate has ultrahigh-strength plasticity, excellent low-temperature toughness and excellent Z-direction performance, and room-temperature preheating-free welding can be achieved.

The invention discloses a neodymium-iron-boron magnet with double main phases and light rare earth diffusion based on asymmetric cerium distribution and a preparation method, and relates to the technical field of neodymium-iron-boron magnets. The method comprises the steps that a diffusion matrix is prepared through a double-main-phase technology, in the double-main-phase technology, the components of a main-phase alloy and an auxiliary-phase alloy are RaCebFe100-a-b-c-dMcBd, R is PrNd alloy or Nd metal, M is at least one of Cu, Al, Zr, Co and Ga, the content of Ce in the main-phase alloy is larger than that of Ce in the auxiliary-phase alloy, then the upper surface and the lower surface of the diffusion matrix are coated with a diffusion source solution, and the diffusion matrix is obtained through heat treatment. Carrying out heat treatment and aging treatment to obtain a neodymium-iron-boron magnet; the diffusion source solution is formed by mixing a diffusion source and a solvent, and the diffusion source is (PrmNdn) aAlbCucZrdCoeMgf. The neodymium-iron-boron magnet obtained through the method has high residual magnetism and high coercive force at the same time, the diffusion efficiency of the diffusion source is high, and the rare earth utilization rate is increased.

The invention relates to a data-driven deformation nickel-based superalloy multi-objective performance reverse design optimization method, which belongs to the technical field of metal material design and development, and comprises the following steps: calculating a stable high-strength deformation nickel-based superalloy system based on a first principle, and on this basis, calculating a deformation nickel-based superalloy system; constructing a deformed nickel-based superalloy component design space based on the knowledge of the nickel-based superalloy field; based on a deformed nickel-based superalloy component design space, the deformed nickel-based superalloy component design space is reduced by adopting an empirical formula in combination with thermodynamic high-throughput calculation to obtain the reduced deformed nickel-based superalloy component design space, and based on the reduced deformed nickel-based superalloy component design space, based on machine learning and a genetic algorithm, the deformation nickel-based superalloy component design space is obtained. And a deformed nickel-based high-temperature alloy reverse design model is established, and the deformed nickel-based high-temperature alloy with the target performance is screened. Compared with the prior art, the oriented development method for the high-strength and high-toughness nickel-based high-temperature alloy is achieved by fusing cross-scale calculation, domain knowledge constraint and machine learning reverse design.

The invention belongs to the technical field of aluminum alloy production, and particularly discloses a low-carbon environment-friendly method for producing a high-strength 8006 alloy container foil, aluminum alloy component proportion and melt treatment and cold rolling production processes are optimized, a large amount of regenerated aluminum waste can be digested, energy consumption is lower than that of a primary aluminum ingot by 50% or above, a blank with the thickness of 1.5 mm is produced through triple continuous rolling, and the production cost is low. The container foil finished product is rolled through 4-5 passes of cold foil rolling, compared with a conventional scheme, the rolling passes are reduced by 2-3, the machining cost is saved by 500 yuan / ton, the blank thickness can be reduced through the production scheme, the cold foil rolling production passes are reduced, high-temperature intermediate annealing is not needed in the cold rolling production process, about 280 kw.h annealing power consumption is saved for each ton, low-carbon short-process production is achieved, and the production cost is reduced. The tensile strength of the finished product is larger than or equal to 150 MPa, the ductility is larger than or equal to 18%, the tensile strength is about 20 MPa higher than that of container foil produced through a conventional scheme, deformation is not likely to happen after punching forming, and the terminal use effect is better.

The invention provides a flame-retardant magnesium alloy with efficient forming diversification and a preparation method of the flame-retardant magnesium alloy. The flame-retardant magnesium alloy comprises the following components in percentage by mass: 4.0-10.0% of Al, 0.2-1.6% of Ca, 0.01-0.5% of Mn, 0.1-1.5% of RE, less than or equal to 0.05% of inevitable impurities and the balance of Mg, and the added RE is one or any combination of Ce, Sm, La and Sr. The preparation method comprises the following steps: smelting and casting, granulating and pulping, and performing pressure injection molding. According to the preparation method, diversified efficient forming of complex curved surfaces, thin-wall parts, special-shaped components and the like can be achieved through cooperative regulation and control of components, the process and the structure, and the obtained flame-retardant magnesium alloy is compact in structure, has the multi-level structural characteristics including a spherical primary solid phase, a fine solidification secondary phase and a grain boundary net-shaped eutectic phase and meanwhile has good flame retardance and mechanical performance; the ignition point is 750-1200 DEG C, the yield strength is 130-200 MPa, the tensile strength is 230-300 MPa, the ductility is 5-20%, and the aluminum alloy is suitable for industrial production.

The invention relates to the technical field of welding materials, and discloses washable semiconductor solder paste and a preparation method and application thereof. The washable semiconductor solder paste comprises scaling powder and tin powder, wherein the mass ratio of the scaling powder to the tin powder is 1: (8-9.6); the soldering flux comprises the following raw material components: a film-forming agent, composite organic acid, a thixotropic agent, a surfactant, an antioxidant and a solvent, wherein the composite organic acid is composed of succinic acid and glutaric acid according to the mass ratio of (1-3): (1-2.5). According to the washable semiconductor solder paste, the particle size, the melting point and the alloy components of the tin powder are controlled, composite organic acid composed of succinic acid and glutaric acid in a specific proportion is adopted in the soldering flux, and other components are matched with one another; the tin powder and the soldering flux in a specific mass ratio are combined, so that the prepared washable semiconductor solder paste is good in wettability, the expansion rate is larger than or equal to 85%, the storage life reaches 3 months, and the washable semiconductor solder paste can be directly cleaned with water after being welded and is high in corrosion resistance and oxidation resistance.

The invention discloses a manufacturing method of 925 silver jewelry, which comprises the following steps: S1, preparing alloy components, S2, designing a cast tree structure, S3, casting, and S4, densifying a casting, the alloy components comprise 92.5-93.0% of silver, 1.0-3.0% of platinum, 0.05-0.5% of copper, 1.5-3.5% of zinc, 1.5-3.5% of indium, 0.03-0.3% of tin, 0.05-0.5% of germanium, 0.03-0.3% of rare earth, and 0.003-0.02% of boron. According to the manufacturing method, alloy components are optimized, the casting performance of the alloy components is improved, the casting process is optimized, the feeding capacity of molten metal is improved, shrinkage porosity and air holes are reduced, the initial density of the casting is improved, and subsequent composite treatment is carried out, so that the density from the surface to the shallow surface of the casting is further improved, grains are refined, and the surface roughness is further reduced; and the requirement of high brightness of the jewelry surface is met.

The present application relates to a kind of large thickness submarine pipeline steel plate and its production method, by the optimization design steel plate component of low-carbon low-alloy component, production method is with the special controlled rolling process of five-stage heating+recrystallization zone low temperature large reduction rolling+intermediate billet instant cooling+non-recrystallization zone high temperature large reduction rolling, and the multi-stage controlled cooling process of high temperature zone air cooling redistribution+ferrite zone cooling+waiting temperature+bainite zone cooling+air cooling self tempering cooling.The product steel plate of the present application has higher acicular ferrite proportion, and the average grain size of ferrite is finer, 3~6 μm, so that the steel plate has good strength and toughness match, the steel plate has higher strength, yield strength ≥500MPa, tensile strength ≥630MPa, and impact energy KV2 At-60 ℃, ≥250J.

The invention provides an aluminum alloy atmospheric corrosion prediction method and system based on machine learning, and relates to the technical field of aluminum alloy corrosion prediction. Comprising the following steps: collecting aluminum alloy atmospheric corrosion data including environmental meteorological data, aluminum alloy component characteristics and aluminum alloy corrosion rate to obtain an aluminum alloy atmospheric corrosion initial data set; performing screening and dimension reduction on the data in the initial data set to obtain an aluminum alloy atmospheric corrosion prediction data set; based on the aluminum alloy atmospheric corrosion prediction data set, the built CNN-SVM model is trained; and acquiring environment data of the to-be-tested aluminum alloy, and predicting the atmospheric corrosion rate of the to-be-tested aluminum alloy based on the trained CNN-SVM model. According to the method, accurate feature screening and short-time-consumption model training are carried out by utilizing limited experimental data, the atmospheric corrosion of the aluminum alloy is predicted at high precision, the cost input of a traditional experiment is reduced, the time cost is saved, and the prediction precision and efficiency are improved.

Provided are a solder alloy, a solder ball, a preformed solder, a solder joint, and a circuit, which are excellent in wettability and shear strength, suitable in failure mode, capable of suppressing the growth of an intermetallic compound at a bonding interface even after multiple reflow soldering, excellent in drop impact resistance, and suitable in the shape of a bump. The solder alloy has an alloy composition comprising, in mass%, 0.10 to 3.00% of Ag, 0.80 to 6.00% of Cu, 0.08 to 0.60% of Ni, 0.0010 to 0.0150% of Ge, and the balance of Sn. It is preferable that the alloy composition further contains 0.1% or less of at least one of Bi, Sb, In, Zn, Ga, Mn, Cr, Co, Si, Ti, and rare earths in total.

The invention relates to the technical field of aluminum alloy forming processes, and discloses an intelligent optimization method of an aluminum alloy round aluminum rod forming process. The method comprises the following steps: acquiring process parameter monitoring data of smelting, casting and rolling stages, wherein the process parameter monitoring data comprises temperature gradient, pressure fluctuation value and alloy component real-time variation; based on the time sequence relevance of the technological parameter monitoring data of the smelting stage and the casting stage, the technological parameter transmission delay amount between the two stages is calculated, and the parameter fluctuation compensation factor of the casting stage is determined accordingly. And determining the energy interference intensity of each process stage in the corresponding frequency domain according to the temperature gradient difference value, the pressure fluctuation change rate and the alloy component offset of the adjacent process stages in the short-time window. And generating a process nonlinear distortion probability based on the energy interference intensity distribution of all adjacent process stages. And the pressure control reference value in the rolling stage is dynamically adjusted according to the process nonlinear distortion probability. By means of the method, intelligent optimization of the aluminum alloy round aluminum rod forming process is achieved.

The invention belongs to the technical field of aluminum alloys, and particularly relates to a high-toughness anti-fatigue aluminum alloy and a preparation method thereof. The alloy comprises the following components in percentage by mass: 0.6-1.4% of Mg, 0.6-1.4% of Si, 0.5-1% of Mn, 0.3-0.8% of Cu, 0.1-0.4% of Cr, 0.1-0.3% of Mo, less than or equal to 0.15% of Fe, less than or equal to 0.05% of Ti, less than or equal to 0.05% of other impurities and the balance of Al. In the alloy, the ratio of Mn to (Cr + Mo) is 2-5, and Cr + Mo is less than or equal to 0.4. The aluminum alloy is subjected to synergistic microalloying of elements Mn, Cr and Mo and three-stage homogenization treatment, then a high-density'core-shell 'structure dispersed phase is separated out, and the deformation structure regulation and control effect is effectively improved; through hot forging and multi-stage solution treatment, a mixed crystal structure in which sub-crystals and recrystallization coexist is obtained, the fatigue crack propagation rate is remarkably reduced, and the obdurability and the fatigue resistance are synchronously improved.

The application discloses a high-temperature alloy component and process design method, comprising the following steps: collecting data of a certain brand high-temperature alloy manual, experiment and literature, and constructing a database; using a machine learning algorithm to construct a corresponding performance prediction model, using a Bayesian optimization technology, taking the required optimized alloy component range as a search range, and taking a comprehensive performance index as an optimization target to realize alloy component optimization to obtain excellent comprehensive performance; through the machine learning algorithm, process optimization of small sample data comprehensive performance is realized; and the optimized alloy component and process casting alloy are used to verify the optimized comprehensive performance. Through collecting data as a training set to train the model, the application analyzes the influence law of alloy components and processing technology on the structure performance, designs the optimized alloy components and process, reduces the cost of manpower and material resources, and reduces the research and development cycle of cast nickel-based high-temperature alloy.

The invention discloses an Al-Mg-Zn aluminum alloy plate with excellent strong plasticity and light weight characteristics as well as a preparation method and application of the Al-Mg-Zn aluminum alloy plate. The alloy comprises the following components in percentage by mass: 5.0%-5.5% of Mg, 1.5%-2.0% of Zn, 0.4%-0.5% of Mn, 0.1%-0.3% of Cu, 0.15%-0.25% of Sc, 0.1%-0.15% of Zr, 0.05%-0.15% of Ag, less than or equal to 0.1% of impurities and the balance of Al. The density is not more than 2.63 g / cm < 3 >, the tensile strength is not less than 470 MPa, and the ductility is not less than 23%. The preparation method comprises the steps of high-purity raw material smelting and casting, two-stage homogenization, hot rolling, intermediate annealing, cold rolling, solid solution treatment and single-stage aging. Wherein the total pressing amount of hot rolling is 80-85%, the total pressing amount of cold rolling is 20-35%, and the single-stage aging time is 120-140 DEG C * 16-24 h. The microstructure of the alloy is characterized in that the average size of dispersed AlSc particles is smaller than or equal to 100 nm, the area fraction of deformed grains is larger than or equal to 70%, the average size of nanometer beta-AlMg and T-Mg (Al, Zn) composite precipitated phases is smaller than or equal to 20 nm, the number density is larger than or equal to 1 * 10 < m >, the area fraction of micron-order second phases is smaller than or equal to 0.5%, and the alloy is only formed by impurity Fe. According to the method, the traditional two-stage aging process is simplified, low density, high strength and high plasticity are synchronously improved, and the method is suitable for large-scale industrial application.

The invention discloses a low-cost, flame-retardant, high-strength, high-thermal-conductivity and corrosion-resistant Mg-Al-Ca-Mn alloy and a preparation method thereof, relates to an Mg-Al-Ca-Mn alloy and a preparation method thereof, and aims to solve the problem that an existing magnesium alloy is difficult to meet the requirements of high plasticity, corrosion resistance, thermal conductivity and flame resistance at the same time. The invention provides a low-cost, high-strength, corrosion-resistant, heat-conducting and flame-retardant Mg-Al-Ca-Mn-X alloy, X is one or a combination of more of Y, Gd, La, Ce, Sm and Nd according to any ratio, the microstructure of the alloy is regulated and controlled through alloy component optimization, rare earth microalloying, a heat treatment process and a plastic deformation process, and the mechanical property of the alloy is improved. The alloy prepared by the invention has excellent mechanical property, corrosion resistance, heat-conducting property and flame retardant property. The method is applied to the field of metal materials.

The invention discloses an ultrahigh-strength maraging steel wire as well as a preparation method and application thereof, and belongs to the field of steel product manufacturing. The steel wire alloy comprises the following components in percentage by weight: 0.02%-0.05% of C, 0.10%-0.35% of Si, 0.20%-0.60% of Mn, 0.60%-2.50% of Cr, 18.5%-22.0% of Ni, 8.0%-13.0% of Co, 1.2%-2.0% of Ti, 3.0%-5.5% of Mo, 0.10%-0.50% of Al, less than or equal to 1.50% of Cu, less than or equal to 1.50% of Nb, less than or equal to 0.05% of V, less than or equal to 0.04% of N, less than or equal to 0.02% of La + Ce and the balance of Fe and inevitable impurity elements. And the equivalence ratio Nieq / Creq of nickel to chromium is greater than or equal to 1.80. The steel wire provided by the invention has ultrahigh strength, excellent toughness and plasticity, wear resistance, heat resistance, drawing performance and bending and twisting performance.

The invention discloses a machine learning guidance laser forming ultrahigh strength and toughness steel design method based on fusion of physical and chemical characteristics, which combines the physical and chemical characteristics with Shapley additive interpretation and analysis, and overcomes the limitation that a traditional pure data driving model lacks theoretical support. The quantitative analysis of the influence between the input characteristics and the output performance is realized, the internal association between the physical and chemical characteristics and the material strengthening and toughening theoretical mechanism is disclosed, the contribution degree and the interaction effect of each alloy element and the heat treatment process parameters are determined, the theoretical basis of variable screening is provided for multi-objective optimization, and the optimization efficiency is improved. Therefore, the efficiency of obtaining the non-dominated solution set is remarkably improved. According to the method, the physical and chemical characteristic combination can be conveniently and rapidly determined, the relation between the input characteristic and the output performance can be quantified, and optimal design of the laser forming ultrahigh strength and toughness steel alloy components and the heat treatment process is achieved.

The invention discloses a high-value preservation utilization and harmless treatment system and method for waste aluminum. Comprising the steps of waste aluminum pretreatment (three-dimensional screening and nano bubble cleaning), dynamic paint removal (moving bed partition low-temperature catalytic pyrolysis), smelting, melt deep purification (Ar gas rotary dehydrogenation, ceramic filtration and electromagnetic refining) and aluminum ash resourceful treatment (80 DEG C hydrolysis and ammonia gas and composite salt crystallization recovery). According to the method, the problems of high cost, degraded utilization, environment-friendly defects and incomplete aluminum ash treatment of the existing waste aluminum regeneration raw materials are solved, direct regeneration of 3004 / 5052 and other high-added-value aluminum alloy plate strip foils is realized, and the alloy component deviation is less than or equal to 0.3 wt%; carbon emission is reduced to 0.82 t CO per ton of aluminum, and is reduced by 31% compared with that of traditional secondary aluminum; and the recovery rate of aluminum ash ammonia reaches 92.5%, the purity of the composite salt product is 96.3%, the double targets of high-valued cyclic utilization and harmless treatment of waste aluminum resources are achieved, and the method has remarkable economic, environment-friendly and technical advantages.

The invention discloses a high-thermal-conductivity Mg-Zn magnesium alloy suitable for rheoforming and a preparation and processing method of the high-thermal-conductivity Mg-Zn magnesium alloy. The alloy comprises the following components in percentage by weight: 1-8% of Zn, 0.5-5% of Cu, 0.2-2% of Sn, 0.2-1% of Sc and the balance of Mg and inevitable impurities. The preparation and processing method comprises the following steps: (1) preparing raw materials according to the composition of the alloy components, and smelting by adopting a medium-frequency induction furnace and taking mixed gas of tetrafluoroethane and argon as a protective atmosphere; (2) mechanical stirring and ultrasonic synergistic stirring are combined to form a uniform melt; (3) preparing semi-solid slurry with a solid phase ratio of 35-50%; (4) forming; (5) cooling and opening the mold; (6) the obtained rheoforming blank is heated to 340-430 DEG C, heat preservation is conducted for 2-12 h, and after heat preservation is finished, quenching is conducted immediately, and cooling is conducted to the room temperature; (7) pre-aging; and (8) aging. By reasonably designing alloy components and optimizing rheoforming parameters, the defects of shrinkage, hot cracking and segregation of a conventional cast Mg-Zn alloy are overcome, and meanwhile, high heat conductivity and mechanical properties are guaranteed.

The invention discloses a calculation method for waste aluminum optimal proportion and raw material cost in 6-series aluminum alloy round ingot smelting, which comprises the following steps of: firstly, determining suitability and maximum additive amount of waste aluminum: determining component calculation values of all elements according to a preset rule by comparing target alloy component requirements with actual components of the waste aluminum; and calculating the additive amount limited by each element, taking the minimum value of the additive amount as the theoretical maximum additive amount, and judging whether the economic threshold value is reached or not. And for the waste aluminum suitable for addition, cost-benefit analysis is carried out subsequently: the reference cost of not using the waste aluminum and the scheme cost of using the maximum addition amount of the waste aluminum are calculated respectively, and the economic feasibility of purchase and use is evaluated by comparing the reference cost and the scheme cost. According to the method, technical feasibility and economic analysis are combined, a quantitative decision support method is formed, whole-process optimization from casting matching to purchase decision is achieved, and the resource utilization rate is remarkably increased and the production cost is reduced while the stable quality of aluminum alloy products is guaranteed.

The invention discloses tin-lead bronze and a preparation method and application thereof.The tin-lead bronze comprises, by weight, 5%-11% of Sn, 2%-6% of Pb, 0.09%-4% of Ni, 0.05%-0.3% of P, 0.01%-1% of Zn and the balance Cu and inevitable impurities, the alloy structure of the tin-lead bronze comprises an alpha phase, an alpha + delta eutectoid and elemental Pb particles dispersed and distributed in the alpha phase, the area ratio of the alpha + delta eutectoid is smaller than or equal to 12%, and the area ratio of the elemental Pb particles is smaller than or equal to 10%. The as-cast average grain size of the tin-lead bronze is 20-70 microns, and the difference value delta D between the minimum grain size and the maximum grain size is smaller than or equal to 20 microns. Through improved design of alloy components and microstructures, a cast ingot with a specified structure is obtained by adopting a centrifugal casting process, meanwhile, the problem of dendritic segregation existing in a traditional casting method is solved, and the prepared material meets high requirements of special industries such as aerospace, ships and large engineering machinery.

A design method of high-capacity hydrogen storage alloy, the specific method comprises the following steps: obtaining data, data preprocessing, data set division, establishing a prediction model, determining the optimal prediction model and alloy composition design. By comparing various machine learning algorithms, the optimal prediction model is selected and determined. Compared with the alloy composition design method of a single prediction model, the high-precision prediction of the hydrogen storage capacity of the hydrogen storage alloy can be further improved, and the efficiency is higher than that of the traditional empirical criterion method and the linear fitting method. By using Xgboost algorithm as the fitness function, the average and maximum fitness function values of the population are converged, and after the preparation of the alloy, the relative error between the actual hydrogen storage capacity and the predicted hydrogen storage capacity is as low as 0.54%, that is, the high-precision prediction is achieved.

The invention discloses a production method of hydroelectric steel with high toughness and high lamellar tearing resistance. The steel comprises the following alloy components in percentage by mass: 0.14-0.15% of C, 0.30-0.40% of Si, 1.50-1.55% of Mn, less than or equal to 0.010% of P, less than or equal to 0.002% of S, 0.043-0.048% of Nb, 0.043-0.048% of V, 0.012-0.02% of Ti, less than or equal to 0.30% of Cr, less than or equal to 0.10% of Mo, less than or equal to 0.30% of Cu, 0.020-0.050% of Al, less than or equal to 0.015% of N, less than or equal to 0.45% of CEV, less than or equal to 0.27% of Pcm and the balance of Fe and inevitable impurities. The thickness of a plate blank is 260-350 mm, the thickness of a steel plate is 20-50 mm, the yield strength ReL of the steel plate is 380-500 Mpa, the tensile strength Rm is 500-650 Mpa, the elongation A is larger than or equal to 22%, the Charpy V-notch impact value KV2 at the temperature of-20 DEG C is larger than or equal to 100 J, the impact absorption energy KV2 after 5% strain aging at the temperature of-20 DEG C is larger than or equal to 100 J, the area reduction Z in the thickness direction is larger than or equal to 35%, and steel plate flaw detection can meet the T1-level requirement of the NB / T47013.3-2015 standard.

The invention relates to an iron-based high-temperature alloy design method based on multi-model machine learning and an alloy thereof, and the method comprises the following steps: 1, obtaining iron-based high-temperature alloy components, carrying out high-throughput calculation, and constructing a data set; 2, correlation analysis is carried out on the data set, feature importance sorting is carried out based on a random forest model, and key components are screened out; 3, constructing a machine learning algorithm model, training by using the key components, and adjusting and optimizing hyper-parameters of the machine learning algorithm model through an optimization algorithm to obtain a trained prediction model; 4, constraint conditions are constructed and optimized, an optimal solution set is obtained, the optimal solution set is input into the trained prediction model, and optimal alloy components are obtained; and 5, laser powder bed melting forming is conducted according to the optimal alloy components, and the iron-based high-temperature alloy is obtained. A data-driven machine learning method is adopted to replace a traditional trial and error method, the alloy research and development period is greatly shortened, and the research and development cost is reduced.

The invention discloses an alloy smelting batching scheme generation method and system, particularly relates to the technical field of metal material production and supply chain collaborative optimization, and is used for solving the problems of uncontrollable execution, cost waste and quality risk caused by disconnection of static parameters and a dynamic supply chain in an existing batching scheme. The method comprises the following steps: acquiring target alloy component demand parameters, raw material inventory allowance and purchase cycle parameters; identifying a dynamic constraint key material with a supply interruption risk; establishing a dynamic constraint model containing an inventory safety buffer threshold based on the historical consumption volatility; candidate batching schemes are generated through multi-level optimization; verifying inventory performability and compatibility of alternative material components; sorting and outputting the effective schemes according to the cost and inventory suitability; through supply chain risk quantification and dynamic constraint modeling, the feasibility of a batching scheme is remarkably improved, and production halt loss and potential quality hazards caused by supply interruption or blind substitution are reduced.

The invention relates to the technical field of high-temperature alloys, and provides a low-segregation high-temperature alloy and a control method for segregation defects of the high-temperature alloy, and the control method comprises the following steps: S1, according to the ingot type size of a high-temperature alloy vacuum consumable ingot, determining the height of the high-temperature alloy vacuum consumable ingot corresponding to the reduction of the melting speed in a vacuum consumable steady-state smelting period; according to the content range of segregation elements in the high-temperature alloy, the melting speed decreasing range is determined; according to the ingot shape size of the high-temperature alloy vacuum consumable ingot, the helium pressure drop range in the heat top sealing period is determined; and S2, carrying out vacuum consumable smelting on the high-temperature alloy according to the vacuum consumable smelting process determined in the step S1. According to the control method provided by the invention, the problem of black spot control of high-temperature alloy vacuum consumable ingots with different ingot types and alloy component marks is solved, and the low-segregation high-temperature alloy consumable ingots are prepared.

The Fe-Ni-based invar alloy comprises the following chemical components in percentage by weight: more than or equal to 0.01% and less than or equal to 0.5% of C, more than or equal to 0.01% and less than or equal to 0.25% of Si, more than or equal to 0.2% and less than or equal to 0.4% of Mn, more than or equal to 0.01% and less than or equal to 0.1% of P, more than or equal to 0.01% and less than or equal to 0.2% of S, more than or equal to 30% and less than or equal to 37% of Ni, more than or equal to 0.2% and less than or equal to 0.6% of Al, more than or equal to 0.2% and less than or equal to 0.4% of Mg and the balance of Fe and inevitable impurities. According to the invention, alloy components are optimized, and processing is carried out through a two-stage thermal deformation process, so that on the premise of ensuring the expansion performance of the alloy, the thermal processing performance of the alloy is further improved, and the thermoplasticity of the alloy is improved.

The invention discloses a beta-type titanium alloy microstructure phase change prediction method and system, and the method comprises the steps: obtaining the composition proportion information of a to-be-predicted beta-type titanium alloy sample, and obtaining corresponding electronic structure parameters, lattice distortion parameters, thermodynamic parameters and other physical characteristic data based on the analysis; and inputting the physical characteristic data into a constructed phase change prediction model to obtain a phase change prediction result which is used for guiding and adjusting the composition proportion of the titanium alloy. Wherein the phase change prediction model constructs an initial prediction model through a machine learning mechanism fusing uncertainty quantization, robust mode recognition and decision boundary learning, adopts a layered five-fold cross validation strategy for training, and determines an integrated weight based on prediction accuracy and diversity indexes of each mechanism on a validation set; and finally carrying out weighted integration to obtain a high-precision prediction model. According to the method, the accuracy and reliability of phase change prediction of the beta-type titanium alloy are effectively improved.

The invention discloses a cast iron cylinder sleeve structure and alloy component optimization method based on friction and wear performance prediction, and belongs to the technical field of material science and machine manufacturing. The problems that a traditional cylinder sleeve alloy design method is low in efficiency and the material performance of the designed cylinder sleeve alloy is limited are solved. The method comprises the following steps: collecting an existing large-cylinder-diameter engine sample, and carrying out metallographic characterization and microhardness test on an engine cylinder sleeve to obtain cylinder sleeve structure characteristics and alloy component data; the wear volumes of different parts are obtained through a friction wear experiment, and then the wear rate is calculated based on the wear volumes. After tissue characteristic data, alloy component data and frictional wear test data of the cylinder sleeve are collected, the data are imported into different machine learning models, the models learn the corresponding relation between the tissue characteristic data and the frictional wear performance of the existing cylinder sleeve, and optimization of material tissue and alloy components is guided according to the prediction result of the optimal model. The method can be applied to optimization of cylinder sleeve structures and alloy components.

The invention relates to a production method of high-grade non-oriented silicon steel hot-rolled strip steel, and belongs to the technical field of steel preparation. The method comprises the following steps: carrying out heating treatment on a non-oriented silicon steel continuous casting sheet billet containing specific alloy components, and controlling the tapping temperature of the heating treatment to be a set tapping temperature; carrying out rough rolling on the heated non-oriented silicon steel continuous casting sheet billet to obtain an intermediate billet; the intermediate billet is subjected to finish rolling, and hot-rolled strip steel is obtained; and the hot-rolled strip steel is subjected to laminar cooling, coiling, heat preservation and edge cutting, and the high-grade non-oriented silicon steel hot-rolled strip steel is obtained. Key process parameters of each hot rolling process are accurately controlled, and batch stable production of the high-grade non-oriented silicon steel with high silicon and high nickel alloy components is realized. According to the method, the edge qualification rate and the yield are increased, the harsh requirements of users for the material performance, the size and the strength are met, and key material support is provided for strategic emerging industries such as new energy automobiles and unmanned aerial vehicles.