Iterative Coupling Hybrid Experimental Method and Apparatus for Fluid-Structure Boundary

Abstract

This disclosure provides a method and apparatus for iterative coupled hybrid experiments on fluid-structure interaction boundaries, applicable to fluid mechanics, solid mechanics, numerical simulation, and engineering fields. The experimental method includes: decomposing an initial fluid-structure interaction structure into multiple substructures, including physical and numerical substructures; determining the influencing factors of the experimental convergence index based on the response error between the physical and numerical substructures, where the response error characterizes the error between the input response information of the physical substructure and the output response information of the numerical substructure, and the influencing factors include the iterative algorithm and the substructures; updating the input response information, output response information, and substructures based on an algorithm optimization strategy and parameter update strategy using the iterative algorithm when the response error does not meet a preset error threshold, thereby obtaining the target structure; and determining the hydrodynamic pressure time history and target motion results based on the target numerical substructure, the target physical substructure, and the preset response flow.

Description

Technical Field

[0001] This disclosure relates to the fields of fluid mechanics, solid mechanics, numerical simulation and engineering technology, and specifically to a fluid-solid boundary iterative coupling hybrid test method and apparatus. Background Technology

[0002] Currently, bridge construction is gradually extending from inland areas to nearshore areas. During earthquakes, bridge piers in deep water move under the influence of seismic forces, altering the water's dynamic state. This causes the water to react on the piers through hydrodynamic pressure, creating an interaction between the piers and the water. This coupling between the piers and the water not only changes the vibration pattern of the bridge structure but also amplifies its dynamic response under seismic loading. Therefore, hydrodynamic effects are a crucial issue that must be considered in the seismic design of deep-water bridges. Related analytical methods for addressing the fluid-structure dynamic coupling effect under seismic loading include analytical methods, numerical methods, and experimental methods.

[0003] The inventors discovered that in related technologies, the analysis of the fluid-structure dynamic coupling effect of structures under seismic loading lacks support from response data in both analytical and numerical methods, resulting in relatively low accuracy. Among the experimental methods, underwater shaking table tests are limited by similarity rates, and real-time fluid-structure mixing tests have high equipment requirements and costs, and the water boundary is difficult to fully reproduce, resulting in low universality and accuracy, which makes it difficult to meet the needs of practical engineering applications. Summary of the Invention

[0004] In view of the above problems, this disclosure provides a method, apparatus, equipment, medium and program product for iterative coupling hybrid testing of fluid-structure boundary.

[0005] According to a first aspect of this disclosure, a fluid-structure interaction boundary iterative coupling hybrid experimental method is provided, comprising: decomposing an initial fluid-structure interaction structure into multiple substructures, wherein the multiple substructures include physical substructures and numerical substructures, the physical substructures corresponding to the fluid, the numerical substructures corresponding to the solid structure, and the boundary between the numerical substructures and the physical substructures corresponding to the boundary between the solid and the fluid; determining the influencing factor information of the experimental convergence index based on the response error between the physical substructures and the numerical substructures, wherein the response error characterizes the error between the input response information of the input physical substructure and the output response information of the numerical substructure, and the influencing factor information includes the iterative algorithm and the substructures. The iterative algorithm is used to correct the response error between the numerical substructure and the physical substructure, and to fit the substructure boundary. When the response error does not meet the preset error threshold, the algorithm optimization strategy and parameter update strategy based on the iterative algorithm are used to update the input response information, output response information, and substructure to obtain the target structure. The target structure includes the target numerical substructure and the target physical substructure. The algorithm optimization strategy of the iterative algorithm is used to update the input response information and output response information, and the parameter update strategy is used to update the substructure. Based on the target numerical substructure, the target physical substructure, and the preset response process, the hydrodynamic pressure time history and the target motion result are determined.

[0006] A second aspect of this disclosure provides a fluid-structure boundary iterative coupling hybrid experimental apparatus. The apparatus includes: a structure decomposition module for decomposing an initial fluid-structure mixture into multiple substructures, wherein the multiple substructures include physical substructures and numerical substructures, the physical substructures corresponding to the fluid, the numerical substructures corresponding to the solid structure, and the boundary between the numerical and physical substructures corresponding to the boundary between the solid and the fluid; and an influencing factor information determination module for determining influencing factor information of the experimental convergence index based on the response error between the physical and numerical substructures, wherein the response error characterizes the error between the input response information of the physical substructure and the output response information of the numerical substructure, and the influencing factor information includes the iterative algorithm and the substructures. An iterative algorithm is used to correct the response error between the numerical substructure and the physical substructure, and to fit the substructure boundary. A structure update module, when the response error does not meet a preset error threshold, updates the input response information, output response information, and substructure based on the algorithm optimization strategy and parameter update strategy of the iterative algorithm to obtain the target structure. The target structure includes a target numerical substructure and a target physical substructure. The algorithm optimization strategy of the iterative algorithm is used to update the input and output response information, and the parameter update strategy is used to update the substructure. Finally, a result determination module is used to determine the hydrodynamic pressure time history and the target motion result based on the target numerical substructure, the target physical substructure, and the preset response flow.

[0007] A third aspect of this disclosure provides an electronic device comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method described above.

[0008] A fourth aspect of this disclosure also provides a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed by a processor, implement the steps of the above-described method.

[0009] The fifth aspect of this disclosure also provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described method.

[0010] According to the fluid-structure boundary iterative coupling hybrid test method, apparatus, equipment, medium, and program products provided in this disclosure, the initial fluid-structure is decomposed into physical substructures and numerical substructures for independent solution. The response information and substructures are updated using response errors between substructures, algorithm optimization strategies, and parameter update strategies to obtain the target structure, thus improving the convergence of the test method. Furthermore, based on the target numerical substructure, the target physical substructure, and the preset response flow, the hydrodynamic pressure time history and target motion results are obtained. Since the target convergence index is obtained after double iteration of the test convergence index using optimization strategies and parameter update strategies based on multiple iterative algorithms, the scientific validity of the experimental results is guaranteed. This improves the accuracy of the hydrodynamic pressure time history and target motion results, avoiding the shortcomings of traditional methods such as difficult data collection, high experimental costs, and difficulty in converging experimental results, further enhancing the universality of the fluid-structure dynamic coupling analysis method. Attached Figure Description

[0011] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0012] Figure 1 The illustration schematically depicts an application scenario of the fluid-structure boundary iterative coupling hybrid test method, apparatus, device, medium, and program product according to embodiments of the present disclosure;

[0013] Figure 2 A flowchart illustrating an iterative coupling hybrid experimental method for fluid-structure boundary according to an embodiment of the present disclosure is shown schematically.

[0014] Figure 3 This schematically illustrates an initial fluid-structure divided into multiple substructures according to an embodiment of the present disclosure;

[0015] Figure 4This illustration schematically depicts a data exchange process for offline iterative hybrid experiments according to an embodiment of the present disclosure;

[0016] Figure 5 The diagram illustrates the convergence factors of an offline iterative hybrid experimental method according to an embodiment of the present disclosure.

[0017] Figure 6 A flowchart illustrating another fluid-structure interaction offline iterative hybrid experimental method according to an embodiment of the present disclosure is shown schematically;

[0018] Figure 7 An example diagram illustrating the structural splitting and updating process according to an embodiment of the present disclosure is shown.

[0019] Figure 8 A schematic diagram of a fluid-structure boundary iterative coupling hybrid experimental apparatus according to an embodiment of the present disclosure is shown.

[0020] Figure 9 A block diagram schematically illustrates an electronic device suitable for implementing a fluid-structure boundary iterative coupling hybrid experimental method according to an embodiment of the present disclosure. Detailed Implementation

[0021] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0022] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0023] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0024] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0025] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0026] In the technical solution disclosed herein, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, and displayed data) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with relevant laws, regulations, and standards, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding operation entry points are provided for users to choose to authorize or refuse.

[0027] In conceiving this disclosure, the inventors discovered that in related technologies, the analytical and numerical methods for analyzing the fluid-structure dynamic coupling effect of structures under seismic loading lack support from response data, resulting in relatively low accuracy. In terms of experimental methods, underwater shaking table tests are limited by similarity rates, and real-time fluid-structure mixing tests have high equipment requirements and costs, and the water boundary is difficult to fully reproduce, resulting in low universality and accuracy, making it difficult to meet the needs of practical engineering applications.

[0028] In view of this, this disclosure solves the initial fluid-structure interaction by decomposing it into physical and numerical substructures for independent calculation. It then utilizes the response error between substructures, algorithm optimization strategies, and parameter update strategies to update the response information and substructures, thus obtaining the target structure. This improves the convergence of the experimental method. Furthermore, based on the target numerical substructure, the target physical substructure, and the preset response flow, the hydrodynamic pressure time history and target motion results are obtained. Since the target convergence index is obtained through dual iteration of the experimental convergence index using multiple iterative algorithm optimization strategies and parameter update strategies, the scientific validity of the experimental results is guaranteed. This improves the accuracy of the hydrodynamic pressure time history and target motion results, avoiding the drawbacks of traditional methods such as difficult data collection, high experimental costs, and difficulty in converging experimental results. This further enhances the universality of the fluid-structure interaction dynamic coupling analysis method.

[0029] This disclosure provides a method, apparatus, device, medium, and program product for an iterative coupling hybrid fluid-structure boundary test. The method includes: decomposing an initial fluid-structure structure into multiple substructures, wherein the multiple substructures include physical substructures and numerical substructures, the physical substructures corresponding to the fluid, the numerical substructures corresponding to the solid structure, and the boundary between the numerical and physical substructures corresponding to the boundary between the solid and the fluid; determining the influencing factors of the test convergence index based on the response error between the physical and numerical substructures, wherein the response error characterizes the error between the input response information of the physical substructure and the output response information of the numerical substructure, and the influencing factors include an iterative algorithm. The algorithm is used to correct the response error between the numerical and physical substructures and fit the substructure boundaries. When the response error does not meet the preset error threshold, the algorithm optimization strategy and parameter update strategy based on the iterative algorithm are used to update the input response information, output response information, and substructure to obtain the target structure. The target structure includes the target numerical substructure and the target physical substructure. The algorithm optimization strategy of the iterative algorithm is used to update the input and output response information, and the parameter update strategy is used to update the substructure. Based on the target numerical substructure, the target physical substructure, and the preset response flow, the hydrodynamic pressure time history and the target motion result are determined.

[0030] Figure 1 The illustration schematically depicts an application scenario of a fluid-structure boundary iterative coupling hybrid test method, apparatus, device, medium, and program product according to embodiments of the present disclosure.

[0031] like Figure 1 As shown, application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, a server 105, and a monitoring device 106. The network 104 serves as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0032] The monitoring device 106 can be used to monitor the displacement and motion data of underwater engineering projects under external forces, including but not limited to underwater displacement sensors, underwater laser scanners, underwater radar, and underwater robots. The monitoring device 106 can connect to the server 105 or a server cluster via the network 104 to send the monitored hydrodynamic pressure data and motion data to the server 105 for storage and analysis.

[0033] For example, monitoring device 106 is an underwater pressure sensor, arranged on the physical substructure of the structural system, which is located in the water tank above loading device 107. Data from the numerical substructure of the structural system can be processed through server 105 or a server cluster connected to server 105. Server 105 transmits this data command to loading device 107, driving loading device 107 to perform loading. Monitoring device 106 can monitor the dynamic water pressure data, which is fed back to server 105. Server 105 can display the processing results through first terminal device 101, second terminal device 102, and third terminal device 103. Users can use first terminal device 101, second terminal device 102, and third terminal device 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on first terminal device 101, second terminal device 102, and third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0034] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0035] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0036] It should be noted that the fluid-structure boundary iterative coupling hybrid test method provided in this disclosure embodiment can generally be executed by server 105. Correspondingly, the fluid-structure boundary iterative coupling hybrid test apparatus provided in this disclosure embodiment can generally be located in server 105. The fluid-structure boundary iterative coupling hybrid test method provided in this disclosure embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the fluid-structure boundary iterative coupling hybrid test apparatus provided in this disclosure embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105.

[0037] It should be understood that Figure 1 The number of terminal devices, networks, monitoring devices, loading devices, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, monitoring devices, networks, loading devices, and servers can be included.

[0038] The following will be based on Figure 1 The described scene, through Figures 2-7 The fluid-structure boundary iterative coupling hybrid experimental method of the disclosed embodiments is described in detail.

[0039] Figure 2 A flowchart illustrating an iterative coupling hybrid experimental method for fluid-structure boundary according to an embodiment of the present disclosure is shown.

[0040] like Figure 2 As shown, the fluid-structure boundary iterative coupling hybrid experimental method of this embodiment includes operations S210 to S240.

[0041] In operation S210, the initial fluid-solid structure is divided into multiple substructures, including physical substructures and numerical substructures. The physical substructures correspond to the fluid, and the numerical substructures correspond to the solid structure. The boundary between the numerical substructures and the physical substructures corresponds to the boundary between the solid and the fluid.

[0042] In the embodiments of this disclosure, the initial fluid-structure interaction (FSI) is a total structure comprising both fluid and solid components. The structural portion corresponding to the fluid is designated as a physical substructure, and the structural portion corresponding to the solid is designated as a numerical substructure. This allows for independent solution of the fluid and solid components throughout the entire external force application period, enabling the analysis of the coupling effects of the FSI under external force. The boundaries between the separated substructures correspond to the boundaries between the solid and fluid components. It is understood that the fluid in this disclosure can include water and gas, and the solid structure can be a solid that interacts with the fluid to generate motion and displacement; the specific type is not limited herein.

[0043] In operation S220, based on the response error between the physical substructure and the numerical substructure, the influencing factors of the experimental convergence index are determined. The response error characterizes the error between the input response information of the physical substructure and the output response information of the numerical substructure. The influencing factors include the iterative algorithm and the substructure. The iterative algorithm is used to correct the response error between the numerical substructure and the physical substructure and to complete the fitting of the substructure boundary.

[0044] In the embodiments of this disclosure, the response error can also be referred to as the response convergence index, which is used to determine whether the experimental method has converged (it can be denoted as ε). j When the response convergence index is less than or equal to a preset error threshold (which can be denoted as ε), the convergence index is within the range of ε. maxUnder these circumstances, it can be determined that the experimental method meets the convergence requirements.

[0045] In the embodiments of this disclosure, the iterative algorithm can be an iterative algorithm for solving fixed-point problems, including at least one of the fixed-point iteration method, the Mann iteration method, and the Ishikawa iteration method. Using an iterative algorithm to correct the response error between the numerical substructure and the physical substructure, and to complete the fitting of the substructure boundary, can include: determining the initial response error between the numerical and physical substructures based on an initial iterative algorithm; if the initial response error is greater than a preset error threshold, updating and optimizing the initial iterative algorithm to determine an intermediate iterative algorithm, and iteratively determining the intermediate response error between the numerical and physical substructures based on the intermediate iterative algorithm; if the intermediate response error is less than or equal to the preset error threshold, determining the intermediate iterative algorithm as the target iterative algorithm to correct the response error between the numerical and physical substructures and complete the fitting of the substructure boundary. It should be noted that the analytical methods used to determine experimental convergence include, but are not limited to, spectral radius analysis methods and mapping relationship analysis methods.

[0046] In operation S230, when the response error does not meet the preset error threshold, the input response information, output response information, and substructure are updated based on the algorithm optimization strategy and parameter update strategy of the iterative algorithm to obtain the target structure. The target structure includes the target numerical substructure and the target physical substructure. The algorithm optimization strategy of the iterative algorithm is used to update the input response information and output response information, and the parameter update strategy is used to update the substructure.

[0047] In the embodiments of this disclosure, the algorithm optimization strategy can characterize updating the initial iterative algorithm (including algorithm replacement and algorithm optimization) to achieve experimental convergence when the initial iterative algorithm fails to meet a preset error threshold. The parameter update strategy can characterize updating the split numerical substructure and physical substructure to obtain a reference structure, determining the hydrodynamic pressure value and performing structure identification to obtain additional hydrodynamic units, and then combining the additional hydrodynamic units with the numerical substructure and physical substructure to obtain the target structure that satisfies experimental convergence.

[0048] In operation S240, based on the target numerical substructure, the target physical substructure, and the preset response process, the hydrodynamic pressure time history and the target motion result are determined.

[0049] In the embodiments of this disclosure, the preset response process may include a first response process and a second response process. The first response process may characterize the process of a solid structure moving through a boundary to a fluid response, and the second response process may characterize the process of a fluid moving through an interface pressure to a solid structure response.

[0050] In one feasible embodiment, the initial input response information can be passed to the physical substructure to determine the hydrodynamic pressure time history of the current iteration step based on experiments. This determined hydrodynamic pressure time history can then be substituted into the numerical substructure to obtain the initial output response signal of the numerical substructure for the current iteration step. After determining the initial output response signal, the response error (response convergence index) between the initial input response information and the initial output response signal can be calculated. If the response convergence index is greater than a preset error threshold, a cyclic iterative algorithm can be used until the response convergence index is less than or equal to the preset error threshold, thus obtaining the hydrodynamic pressure time history and the target motion result, achieving dynamic matching of interface vibration. It can be understood that the initial motion data may include the initial input response information, the hydrodynamic pressure time history, and the initial output response signal.

[0051] It is understood that the external forces described in this disclosure can characterize the external forces acting on the initial fluid-structure interaction and causing interactions between the fluid-structure components, including but not limited to seismic forces and wind forces. The target motion model can be used to calculate the motion of the fluid-structure under the action of external forces.

[0052] For example, the movement of deep-water bridge piers under seismic forces alters the water's dynamic state, causing the water to react on the piers with hydrodynamic pressure, creating an interaction between the piers and the water. Similarly, when wind acts on tall buildings, the buildings deform or move due to wind pressure. The height and shape of a building affect wind flow, thus altering how the wind affects the building. Wind not only exerts direct pressure but can also cause vibrations and displacements in buildings, thus forming a complex interaction between wind and building structures.

[0053] Figure 3 A schematic diagram illustrating the initial fluid-structure composition according to an embodiment of the present disclosure is shown, divided into multiple substructures.

[0054] like Figure 3 As shown in Figure (a), taking a deep-water bridge pier as an example, the initial fluid-structure 310 can include a fluid (water body) 311, a solid structure (bridge pier) 312, and an interface 313 between the fluid-structure; after the initial fluid-structure 310 is disassembled, as shown in Figure (a), the initial fluid-structure 310 can be further disassembled into the following structures: Figure 3 As shown in Figures (b) and (c), the part corresponding to the fluid 311 is taken as the physical substructure 320, and the part corresponding to the solid structure 312 is taken as the numerical substructure 330, so that the fluid part and the solid structure part can be solved independently throughout the entire time period of external force action (e.g., seismic force).

[0055] According to embodiments of this disclosure, by independently solving the initial fluid-structure interaction (FSI) substructure into physical and numerical substructures, the response information and substructures are updated using response errors between substructures, algorithm optimization strategies, and parameter update strategies, thus obtaining the target structure. This improves the convergence of the experimental method. Furthermore, based on the target numerical substructure, the target physical substructure, and the preset response flow, the hydrodynamic pressure time history and target motion results are obtained. Since the target convergence index is obtained by double iteration of the experimental convergence index using optimization strategies and parameter update strategies based on multiple iterative algorithms, the scientific nature of the experimental results is guaranteed. On this basis, the accuracy of the hydrodynamic pressure time history and target motion results is improved, avoiding the shortcomings of traditional methods such as difficult data collection, high experimental costs, and difficulty in converging experimental results. This further enhances the universality of the fluid-structure dynamic coupling analysis method.

[0056] As can be understood, the above text has already explained how to determine the hydrodynamic pressure time history and the target motion results. The following text will explain how to determine the target structure.

[0057] According to embodiments of this disclosure, when the response error does not meet a preset error threshold, an algorithm optimization strategy and a parameter update strategy based on an iterative algorithm are used to update the input response information, output response information, and substructure to obtain the target structure. This includes: updating the input response information and output response information based on an iterative algorithm to obtain an updated response error when the response error does not meet a preset error threshold; and updating the substructure based on a parameter update strategy to obtain the target structure when the updated response error does not meet a preset error threshold.

[0058] In the embodiments of this disclosure, the update response error can characterize the error between the input response information of the physical substructure and the output response information of the numerical substructure in the intermediate iteration stage obtained after updating, optimizing, or replacing the initial iterative algorithm. Furthermore, considering that updating and optimizing the iterative algorithm still cannot achieve experimental convergence or results in poor convergence, this disclosure can update the substructure using a parameter update strategy to obtain a target structure that meets the experimental convergence requirements.

[0059] According to embodiments of this disclosure, by combining iterative algorithms and parameter update strategies (dual guarantees), the convergence, accuracy, and efficiency of the experimental method can be effectively improved. This not only ensures the stable operation of the algorithm but also ensures that each update moves towards the optimal goal, making it suitable for complex optimization problems.

[0060] As we have already explained how to determine the target structure above, the following text will explain how to determine the input and output response information.

[0061] According to embodiments of this disclosure, the method further includes: constructing a target motion model of an initial fluid-structure interaction structure under external force; and determining input response information and output response information based on the physical substructure, numerical substructure, and target motion model.

[0062] In the embodiments of this disclosure, the target motion model can be constructed by fusing a first motion model corresponding to the physical substructure and a second motion model corresponding to the numerical substructure. The split physical and numerical substructures can be regarded as a structural system, thereby constructing a target motion model of the structural system under the action of external forces, including: constructing a first motion model using a hydrodynamic pressure model function and external force acceleration; constructing a second motion model using the first motion model, external force information, response information, and dynamic parameters; and then combining the first and second motion models to construct the target motion model.

[0063] In the embodiments of this disclosure, after obtaining the target motion model, offline iterative hybrid experiments can be performed based on the physical substructure, numerical substructure, and target motion model.

[0064] Figure 4 The diagram illustrates an offline iterative hybrid test data exchange process according to an embodiment of the present disclosure.

[0065] like Figure 4 As shown, the initial value of the hydrodynamic pressure 401 can be estimated empirically. Based on this, the initial input response information 403 (initial motion data) corresponding to different time points 402 is obtained. The time points can be denoted as T, where T = (t0, t1, ..., t2). n The initial input response information can be denoted as u. E (1) (T), u E (1) (T)={u E (1) (t0), u E (1) (t1), u E (1) (t2), ..., u E (1) (t n )}.

[0066] After determining the initial input response information 403, the initial input response information 403 can be passed to the physical substructure, thereby determining the hydrodynamic pressure time history 404 for the current iteration step (first iteration) based on the experiment. The hydrodynamic pressure time history can be denoted as F. (1) (T), F (1) (T)={F (1) (t0), F (1) (t1), F(1) (t2), ..., F (1) (t n After obtaining the hydrodynamic pressure time history 404, it can be substituted into the numerical substructure to obtain the initial output response signal 405 of the numerical substructure for the current iteration step (first iteration), which can be denoted as u. N (1) (T), u N (1) (T)={u N (1) (t0), u N (1) (t1), u N (1) (t2), ..., u N (1) (t n )}.

[0067] After obtaining the initial output response signal 405, the initial error between the initial input response information 403 and the initial output response signal 405 can be calculated, thereby obtaining the error convergence index ε. j Then compare the error convergence index ε j Compared with the preset error threshold ε max The comparison results between them; in ε j >ε max In this case, the iterative algorithm updates the current input information using the initial response information from the previous iteration, obtaining process input response information 406, process hydrodynamic pressure time history 407, and process output response signal 408, which can be denoted as u, respectively. E (2) (T), F (2) (T) and u N (2) (T); Based on this, the process error between the process input response information 406 and the process output response signal 408 is calculated, and the convergence index ε is obtained. j , in ε j ≤ε max In this case, ε can be j The target convergence index was determined, the substructure boundary was fitted, and the process hydrodynamic pressure time history 407 and the process output response signal 408 were used as the target hydrodynamic pressure time history and the target output response signal (target motion result), respectively. It can be understood that the response information was updated based on the same iterative algorithm throughout the entire offline iterative hybrid experiment.

[0068] Figure 5 A schematic diagram illustrating the convergence factor of the offline iterative hybrid experiment method according to an embodiment of the present disclosure is shown.

[0069] like Figure 5 As shown, after the initial input response information 403 is input into the iterative system, the initial output response signal 405 can be obtained based on the structural system 411 (including physical substructure and numerical substructure) in the iterative system. If the response error 420 does not meet the preset convergence threshold, the input response information is iteratively updated using the iterative algorithm 412 until the response error is less than or equal to the preset error threshold after the nth iteration, thus satisfying the convergence of the offline iterative hybrid experimental method. It can be understood that factors affecting the convergence of the experimental method include the substructure in the iterative system and the iterative algorithm. It should be noted that the type of iterative algorithm is based on satisfying the updating of the input response information, and is not specifically limited here.

[0070] As we can understand, the above text has already provided examples of how to determine the input and output response information. The following text will further explain how to determine the target structure.

[0071] According to embodiments of this disclosure, updating the substructure based on a parameter update strategy to obtain a target structure includes: constructing a reference structure corresponding to the initial fluid-structure interaction structure, wherein the reference structure includes a reference numerical substructure and a reference physical substructure; and updating the physical substructure and the numerical substructure based on the reference numerical substructure, the reference physical substructure, and the parameter update strategy to obtain the target structure.

[0072] In the embodiments of this disclosure, considering that the additional dynamic water units attached to the numerical substructure cannot be determined, the additional dynamic water units for the corresponding measuring points can be determined by constructing a reference structure; firstly, the number of target measuring points and the dynamic water pressure corresponding to the number of target measuring points are determined, and the additional dynamic water units are identified based on the dynamic water pressure value; furthermore, the additional dynamic water units can be combined with the water-contaminated solid structure (numerical substructure) to obtain the updated numerical substructure, thus obtaining the target structure.

[0073] In the embodiments of this disclosure, a suitable iterative algorithm can be selected to update the response error based on the actual requirements of the experiment (e.g., computational accuracy, convergence speed, memory consumption, etc.). Iterative algorithms include, but are not limited to, fixed-point iteration, Mann iteration, and Ishikawa iteration.

[0074] In one feasible embodiment, different iterative methods can be used to solve the fixed-point problem. Through iterative iteration, it can be determined whether the response error meets the convergence of the experimental method. In particular, when high-precision simulation calculations are required in the experimental scenario, the Ishikawa iterative method can be used to quickly approximate the required solution.

[0075] In the embodiments of this disclosure, different iterative algorithms are used to update the response information, which can meet the update requirements for different actual test scenarios. In particular, when the optimization problem involves multiple evaluation conditions (such as input response information and output response information), the Ishikawa iterative algorithm can better balance the various objectives, improve the convergence of the objectives, and make the test results more accurate.

[0076] As you can understand, the above text has already provided an example of how to determine the target structure, and the following text will further explain how to determine the target structure.

[0077] According to embodiments of this disclosure, updating the physical substructure and numerical substructure based on a reference numerical substructure, a reference physical substructure, and a parameter update strategy to obtain a target structure includes: determining the dynamic water pressure value and performing structure identification based on the parameter update strategy, the reference numerical substructure, and the reference physical substructure to obtain an additional dynamic water unit; and combining the additional dynamic water unit with the numerical substructure as the updated target numerical substructure to obtain the target structure.

[0078] In the embodiments of this disclosure, the parameter update strategy can characterize the acquisition of target numerical and physical substructures by constructing a reference structure, thereby achieving the convergence requirements of the experimental method. After constructing the reference structure, the hydrodynamic pressure can be obtained using the reference structure, and then additional hydrodynamic units can be identified based on the hydrodynamic pressure value; then, the target structure is constructed based on the additional hydrodynamic units, the reference structure, the numerical substructure, and the physical substructure.

[0079] According to the embodiments of this disclosure, by utilizing the structural decomposition and update method, the problems of high requirements for experimental equipment, difficulty in collecting measured hydrodynamic pressure data, errors caused by repeated loading process leading to physical substructure damage in offline iterative hybrid experiments, and difficulty in convergence of offline iterative hybrid experiment methods in existing fluid-structure interaction technologies can be avoided, thereby ensuring the convergence and accuracy of the experimental method.

[0080] As you can understand, the above text has already explained how to determine the target structure, and the following text will explain how to construct the reference structure.

[0081] According to embodiments of this disclosure, the measurement point corresponding to the reference physical substructure is the reference measurement point; constructing a reference structure corresponding to the initial fluid-structure structure includes: using the numerical substructure as the reference numerical substructure and using the physical substructure corresponding to the reference measurement point as the reference physical substructure to obtain the reference structure.

[0082] In the embodiments of this disclosure, a reference numerical substructure can characterize a substructure corresponding to a numerical substructure, and a target numerical substructure can characterize a substructure obtained by combining an additional dynamic water unit with a water-borne solid structure.

[0083] For example, an offline iterative hybrid test of fluid-structure interaction (FSI) can be conducted using a pre-constructed reference structure. Assuming the original FSI interface has Q measurement points, the dynamic water pressure at these q measurement points can be selected as the physical substructure (q < Q). The model that reduces the dynamic water pressure at the measurement points, i.e., the model subjected to the dynamic water pressure at these q measurement points, is used as the reference structure. Based on the response flow (pre-defined response flow), an initial offline iterative hybrid test is conducted to measure the dynamic water pressure values ​​for identification in the next step. The dynamic water pressure measured in the reference model test is used for model identification, thereby obtaining an accurate representation of the additional dynamic water units. Based on this, the target structure is constructed. The dynamic water pressure of the original structure is decomposed, with the dynamic water pressure values ​​at the q measurement points used as the physical substructure. The dynamic water pressure values ​​at the Qq measurement points are combined with the water-contacting structure (numerical substructure) in the form of additional dynamic water units to form the target numerical substructure, thus obtaining the target structure.

[0084] As can be understood, the above text has already illustrated how to construct a reference structure; the following text will explain how to determine the target iterative algorithm.

[0085] According to embodiments of this disclosure, the method further includes: updating the input response information and output response information using an intermediate iteration algorithm when the response error does not meet a preset error threshold, to obtain intermediate input response information and intermediate output response information; determining the intermediate response error between the intermediate input response information and the intermediate output response information; and determining the intermediate iteration algorithm as the target iteration algorithm when the intermediate response error meets the preset error threshold.

[0086] In embodiments of this disclosure, the initial response error ε1 can be obtained using an iterative algorithm A (e.g., the Mann iteration algorithm). j This allows the initial response error ε1 to be... j Compared with the preset error threshold ε max Compare, ε1 j >ε max In this case, the experiment cannot converge; therefore, iterative algorithm B (e.g., Ishikawa iterative algorithm) is used to replace the Mann iterative algorithm to obtain ε2. j By passing the intermediate response error ε2 j Compared with the preset error threshold ε max By comparison, ε2 was obtained. j ≤ε max In this case, the boundary between the numerical substructure and the physical substructure is fitted, thus achieving convergence of the experimental method. It can be understood that the Ishikawa iterative algorithm is the target iterative algorithm that satisfies the convergence requirement of the experimental method.

[0087] As we have already explained how to determine the target iterative algorithm above, the following text will explain how to determine the number of target measurement points.

[0088] According to an embodiment of this disclosure, the number of measuring points corresponding to the target physical substructure is the number of target measuring points that meet the preset evaluation conditions; the method further includes: when the physical substructure and the numerical substructure do not meet the preset evaluation conditions, determining the number of target measuring points based on the additional dynamic water mass corresponding to the initial measuring points, the mass of the numerical substructure, and the damping of the numerical substructure.

[0089] In embodiments of this disclosure, considering that the selected initial measuring points may not meet the preset evaluation conditions, the number of target measuring points can be determined using the additional dynamic water mass, the mass of the numerical substructure, and the damping of the numerical substructure. For example, the ratio η of the additional dynamic water mass (dynamic water pressure is expressed as additional mass) to the original structure mass at the height of the water-facing surface corresponding to q measuring points, and the damping ratio ξ of the numerical substructure are used. N Satisfying the relation η≤2ξ N Based on this, the number of target measurement points is determined.

[0090] According to embodiments of this disclosure, determining input response information and output response information based on a physical substructure, a numerical substructure, and a target motion model includes: constructing a target motion model based on a second motion model and a first motion model, wherein the first motion model represents the motion model corresponding to the physical substructure, and the second motion model represents the motion model corresponding to the numerical substructure; and determining input response information and output response information based on the physical substructure, the numerical substructure, and the target motion model.

[0091] In the embodiments of this disclosure, the first motion model may be a motion model corresponding to the physical substructure, and the second motion model may be a motion model corresponding to the numerical substructure. By merging the first motion model and the second motion model, the target motion model of the structural system can be obtained. The target motion model is then used to estimate the initial value of the hydrodynamic pressure, thereby obtaining the initial input response information in the initial motion data. Furthermore, the hydrodynamic pressure time history and the initial output response signal are determined through a preset response process.

[0092] For example, taking a deep-water bridge pier under seismic loading as the initial fluid-structure, the water body as the physical substructure, and the bridge pier as the numerical substructure, the equation of motion for a single-degree-of-freedom underwater structure under seismic loading can be expressed as follows (1):

[0093] (1);

[0094] Where m, c, and k can represent the mass, damping, and stiffness of a single-degree-of-freedom underwater structure, respectively. It can characterize seismic loads. It can be the ground motion acceleration, F h It can be used for dynamic water pressure loads. , , These can represent the acceleration, velocity, and displacement responses of a structure under excitation.

[0095] Based on this, and combined with the offline iterative hybrid experimental data exchange strategy, the first motion model of the physical substructure of the current iteration step can be determined as shown in the following formula (2):

[0096] (2);

[0097] Where f can be a hydrodynamic pressure model function. The input response information can be the physical substructure, and j can represent the current iteration step. Therefore, the second motion model of the numerical substructure at the current iteration step can be determined, as shown in formula (3) below:

[0098] (3);

[0099] in, , and The output response signals (output acceleration, output velocity, and output displacement) of the numerical substructure can be characterized separately. If the numerical substructure and the physical substructure are combined and understood as a single structural system, then the target motion model of the structural system in the current iteration step can be represented as:

[0100] (4);

[0101] It is understandable that, in the j-th iteration, the physical substructure driving signal... As input to the structural system, the numerical substructure response signal As the output of the structural system.

[0102] As you can understand, the above text has already explained how to determine the initial motion data. The following text will explain how to determine the target motion result.

[0103] In embodiments of this disclosure, the preset response process may include a first response process from the solid structure to the fluid via the boundary, and a second response process from the fluid to the solid structure via the boundary. The hydrodynamic pressure time history can characterize the motion data of the physical substructure corresponding to different time points obtained using the first motion model. The target motion result can characterize the motion result of the numerical substructure corresponding to different time points obtained using the second motion model. A response error less than or equal to a preset error threshold can be determined as the target response error.

[0104] In one feasible embodiment, taking a hybrid test of a water-bearing bridge pier as an example, the fluid-structure boundary iterative coupling hybrid test method based on the decomposition and updating of the hydrodynamic pressure model can include: First, the initial fluid-structure is decomposed, with the water body as the physical substructure and the solid structure (bridge pier) itself as the numerical substructure. The numerical calculation and servo loading of this test method can be performed independently throughout the entire seismic action period. By iteratively correcting the acceleration time history response error between the numerical and physical substructures, a balance and coordination are achieved at the boundary, thereby simulating the true state of hydrodynamic pressure. Second, key factors affecting the convergence of the test method can be identified, as described above. Figure 5 As shown, after evaluating the convergence of the experimental method, if convergence is achieved, offline iterative hybrid experiments of fluid-structure interaction (FSI) can be conducted. If convergence is not achieved, iterative algorithm optimization is required. After algorithm optimization, the convergence of the experimental method is evaluated again. If convergence is achieved, offline iterative hybrid experiments of FSI should be conducted. If convergence is still not achieved, parameter update strategies can be used to update the physical and numerical substructures to meet the convergence requirements of the experimental method.

[0105] Figure 6 A flowchart illustrating a fluid-structure interaction offline iterative hybrid experimental method according to an embodiment of the present disclosure is shown.

[0106] like Figure 6 As shown, the fluid-structure interaction offline iterative hybrid experimental method may include operations S61 to S67.

[0107] In operation S61, the initial signal is estimated based on empirical values, which can be denoted as: .

[0108] In operation S62, input response information. The displacement and deformation of the outer contour interface of the water-entry section in the physical substructure can be calculated by the numerical substructure and sent to the loading device controller to control the deformation and displacement of the interface, denoted as... .

[0109] When operating the S63, dynamic water pressure is monitored via a miniature underwater pressure sensor on the external contour interface. Take measurements.

[0110] In operation S64, the hydrodynamic pressure is fed back to the numerical substructure and the structural response is solved, denoted as the output response information. .

[0111] During operation S65, the response error ε is calculated based on the input response information and the output response signal. j calculate.

[0112] In operation S66, determine whether ε is satisfied. j ≤ε max .

[0113] When S67 is not satisfied, an iterative algorithm is used to correct the error between the two conditions, thus obtaining the input response information for the next iteration. Repeat steps S62-S67 until the convergence condition is met to achieve dynamic matching of interface vibrations.

[0114] Figure 7 An example diagram illustrating the structural splitting and updating process according to an embodiment of this disclosure is shown.

[0115] like Figure 7 As shown, a reference structure 71 corresponding to the initial fluid-structure interaction structure 70 is constructed. The reference structure 71 may include a reference physical substructure 711 and a reference numerical substructure 712. An offline iterative hybrid test of fluid-structure interaction is conducted. Based on the actual measured hydrodynamic pressure value of the reference structure 71, structural identification is performed to obtain additional hydrodynamic units. The hydrodynamic pressure of the original structure is then decomposed. The hydrodynamic pressure of q measuring points is used as the updated physical substructure 721, and the hydrodynamic pressure of Qq measuring points, together with the water-contact structure itself, is used as the target numerical substructure 722 in the form of additional hydrodynamic units to obtain the target structure 73. Then, an offline iterative hybrid test is conducted using the target structure 72 to measure and calculate the response of the original structure and the hydrodynamic pressure value.

[0116] According to embodiments of this disclosure, the preset response process includes a first response process from the solid structure to the fluid via the boundary, and a second response process from the fluid to the solid structure via the boundary; based on the target numerical substructure, the target physical substructure, and the preset response process, the dynamic water pressure time history and the target motion result are determined, including: determining the dynamic water pressure time history based on the first response process, the target input response information, and the target physical substructure; and determining the target motion result based on the dynamic water pressure time history, the second response process, and the target numerical substructure.

[0117] In the embodiments of this disclosure, the hydrodynamic pressure time history can characterize a dataset of multiple hydrodynamic pressure values ​​corresponding to different time points. The input command signal can be transmitted to the physical substructure based on the structural response-interface motion-fluid response, and the hydrodynamic pressure time history of the current iteration step can be obtained experimentally. Therefore, based on the fluid response-interface pressure-structural response, the experimentally measured hydrodynamic pressure is substituted into the numerical substructure to obtain the output response information of the current iteration step. The target motion result can be the structural response information obtained based on an experimental method that meets convergence requirements.

[0118] In another feasible embodiment, the fluid-structure interaction offline iterative hybrid experimental method may include the following operations S701 to S714.

[0119] When operating S701, the water-bearing bridge piers can be divided into numerical substructures and dynamic water pressure substructures.

[0120] In operating S702, a fluid-structure interaction motion model of a water-crossing bridge pier under seismic loading is constructed, and the fluid-structure interface in the fluid-structure system is replaced by a hybrid experimental numerical substructure and physical substructure boundary simulation.

[0121] In operating S703, factors affecting convergence are identified, including iterative algorithms and substructures.

[0122] In operation S704, the convergence of the experimental method is evaluated. If the experimental method is convergent (i.e., η≤2ξ), then... N Where η represents the mass ratio of the physical substructure's dynamic water-added mass to the numerical substructure's mass, ξ N If the damping ratio of the numerical substructure is not found, proceed to operation S705; otherwise, if convergence fails, proceed to operations S709-S710 to optimize or update the structural parameters using an algorithm (to ensure that the adjusted structure satisfies η≤2ξ). N To achieve the convergence objective.

[0123] When operating S705, initial signal estimation is performed. By estimating the initial value of the dynamic water pressure, the initial input response information can be obtained.

[0124] When operating S706, the input response information is transmitted to the physical substructure based on the structural response-interface motion-fluid response, and the hydrodynamic pressure time history of the current iteration step is obtained based on experimental measurements.

[0125] When operating S707, the hydrodynamic pressure measured in the experiment is substituted into the numerical substructure according to the fluid response-interface pressure-structural response to obtain the output response signal of the current iteration step.

[0126] During S708 operation, convergence is checked. The convergence condition (ε) is determined. j ≤ε max If the convergence condition is not met, proceed to the next loop and repeat operations S706 to S708. The input response information for the next loop can be obtained from the iterative algorithm. If the convergence condition is met, terminate the experiment.

[0127] When operating S709, optimize the iterative algorithm.

[0128] In operation S710, repeat operation S704 to evaluate the convergence of the optimized iterative algorithm. If convergence is achieved, proceed to S705~S708. If convergence is not achieved, directly proceed to operation S711~S714 to achieve the convergence target by adjusting the structural parameters.

[0129] In operation S711, a reference structure is constructed, and an offline iterative hybrid test of fluid-structure interaction is conducted. If the original fluid-structure interaction interface itself has Q measurement points, the hydrodynamic pressure at these q measurement points can be selected as the physical substructure (q < Q). The structure that reduces the hydrodynamic pressure at the measurement points, i.e., the structure subjected to the hydrodynamic pressure at these q measurement points, is used as the reference structure. According to S705~S708, a preliminary offline iterative hybrid test is conducted, and the hydrodynamic pressure values ​​are measured for identification in subsequent operations.

[0130] In operating S712, the structure is identified based on the actual measured dynamic water pressure from the reference structure experiment, thereby obtaining the expression of the additional dynamic water unit.

[0131] In operation S713, an updated structure is constructed. The hydrodynamic pressure of the original structure is decomposed. The hydrodynamic pressure at q measuring points is taken as a physical substructure, and the hydrodynamic pressure at Qq measuring points is taken as a numerical substructure together with the water-contacting structure itself in the form of additional hydrodynamic units. The expression of the additional hydrodynamic units is identified by S712, and this structure is determined as the target structure.

[0132] In operation S714, an offline iterative hybrid test is conducted on the target structure according to S705~S708, and the original structural response and hydrodynamic pressure values ​​are measured and calculated. Based on the above-mentioned fluid-structure boundary iterative coupled hybrid test method, this disclosure also provides a fluid-structure boundary iterative coupled hybrid test apparatus. The following will be combined with... Figure 8 The device is described in detail.

[0133] Figure 8 A schematic diagram of a structural block diagram of a fluid-structure boundary iterative coupling hybrid experimental apparatus according to an embodiment of the present disclosure is shown.

[0134] like Figure 8 As shown, the fluid-structure boundary iterative coupling hybrid experimental device of this embodiment includes a structure splitting module 810, an influencing factor information determination module 820, a structure updating module 830, and a result determination module 840.

[0135] The structure splitting module 810 is used to split the initial fluid-structure into multiple substructures, wherein the multiple substructures include physical substructures and numerical substructures. The physical substructures correspond to the fluid, and the numerical substructures correspond to the solid structure. The boundary between the numerical substructure and the physical substructure corresponds to the boundary between the solid and the fluid. In one embodiment, the structure splitting module 810 can be used to perform the operation S210 described above, which will not be repeated here.

[0136] The influencing factor information determination module 820 is used to determine the influencing factor information of the experimental convergence index based on the response error between the physical substructure and the numerical substructure. The response error characterizes the error between the input response information of the physical substructure and the output response information of the numerical substructure. The influencing factor information includes an iterative algorithm and the substructure. The iterative algorithm is used to correct the response error between the numerical and physical substructures and to complete the fitting of the substructure boundary. In one embodiment, the influencing factor information determination module 820 can be used to perform the operation S220 described above, which will not be repeated here.

[0137] The structure update module 830 is used to update the input response information, output response information, and substructure based on an iterative algorithm optimization strategy and a parameter update strategy when the response error does not meet a preset error threshold, thereby obtaining a target structure. The target structure includes a target numerical substructure and a target physical substructure. The iterative algorithm optimization strategy is used to update the input and output response information, and the parameter update strategy is used to update the substructure. In one embodiment, the structure update module 830 can be used to execute the operation S230 described above, which will not be repeated here.

[0138] The result determination module 840 is used to determine the hydrodynamic pressure time history and the target motion result based on the target numerical substructure, the target physical substructure, and the preset response process. In one embodiment, the result determination module 840 can be used to perform the operation S240 described above, which will not be repeated here.

[0139] According to embodiments of this disclosure, the fluid-structure boundary iterative coupling hybrid experimental device includes a structure decomposition module 810, an influencing factor information determination module 820, a structure update module 830, and a result determination module 840. By decomposing the initial fluid-structure into physical substructures and numerical substructures for independent solution, the response information and substructures are updated using the response error between substructures, algorithm optimization strategies, and parameter update strategies to obtain the target structure, thus improving the convergence of the experimental method. Furthermore, based on the target numerical substructure, the target physical substructure, and the preset response flow, the hydrodynamic pressure time history and target motion results are obtained. Since the target convergence index is obtained by double iteration of the experimental convergence index based on optimization strategies of multiple iterative algorithms and parameter update strategies, the scientific nature of the experimental results is guaranteed. On this basis, the accuracy of the hydrodynamic pressure time history and target motion results is improved, avoiding the defects of traditional methods such as difficult data collection, high experimental costs, and difficulty in convergence of experimental results, and further enhancing the universality of the fluid-structure dynamic coupling analysis method.

[0140] According to embodiments of this disclosure, the structure update module 830 includes a response information update submodule and a substructure update submodule. The response information update submodule is used to update the input response information and output response information based on an iterative algorithm to obtain an updated response error when the response error does not meet a preset error threshold. The substructure update submodule is used to update the substructure based on a parameter update strategy to obtain the target structure when the updated response error does not meet a preset error threshold.

[0141] According to embodiments of this disclosure, the apparatus further includes a motion model construction module and a response information determination module. The motion model construction module is used to construct a target motion model of the initial fluid-structure interaction structure under external force; and the response information determination module is used to determine input response information and output response information based on the physical substructure, numerical substructure, and target motion model.

[0142] According to embodiments of this disclosure, the substructure update submodule includes a reference structure construction unit and a substructure update unit. The reference structure construction unit is used to construct a reference structure corresponding to the initial fluid-structure interaction structure, wherein the reference structure includes a reference numerical substructure and a reference physical substructure; and the substructure update unit is used to update the physical substructure and the numerical substructure based on the reference numerical substructure, the reference physical substructure, and a parameter update strategy to obtain the target structure.

[0143] According to embodiments of this disclosure, the substructure updating unit includes a structure identification subunit and a target structure obtaining subunit. The structure identification subunit is used to determine the hydrodynamic pressure value and perform structure identification based on a parameter update strategy, a reference numerical substructure, and a reference physical substructure, thereby obtaining an additional hydrodynamic unit. The target structure obtaining subunit is used to combine the additional hydrodynamic unit with the numerical substructure as the updated target numerical substructure, thereby obtaining the target structure.

[0144] According to embodiments of this disclosure, the measurement point corresponding to the reference physical substructure is a reference measurement point; the reference structure construction unit includes: a reference structure obtaining subunit, used to obtain a reference structure by taking the numerical substructure as a reference numerical substructure and the physical substructure corresponding to the reference measurement point as a reference physical substructure.

[0145] According to embodiments of this disclosure, the apparatus further includes: a response information update module, an intermediate response error determination module, and an iterative algorithm determination module. The response information update module is used to update the input response information and output response information using an intermediate iterative algorithm when the response error does not meet a preset error threshold, thereby obtaining intermediate input response information and intermediate output response information. The intermediate response error determination module is used to determine the intermediate response error between the intermediate input response information and the intermediate output response information. The iterative algorithm determination module is used to determine the intermediate iterative algorithm as the target iterative algorithm when the intermediate response error meets the preset error threshold.

[0146] According to an embodiment of this disclosure, the number of measuring points corresponding to the target physical substructure is the number of target measuring points that meet the preset evaluation conditions; the device further includes: a target measuring point number determination module, used to determine the target measuring point number based on the additional dynamic water mass corresponding to the initial measuring point, the mass of the numerical substructure, and the damping of the numerical substructure when the physical substructure and the numerical substructure do not meet the preset evaluation conditions.

[0147] According to embodiments of this disclosure, the response information determination module includes: a target motion model construction submodule and a response information determination submodule. The target motion model construction submodule is used to construct a target motion model based on a second motion model and a first motion model, wherein the first motion model represents the motion model corresponding to the physical substructure, and the second motion model represents the motion model corresponding to the numerical substructure; and the response information determination submodule is used to determine input response information and output response information based on the physical substructure, the numerical substructure, and the target motion model.

[0148] According to embodiments of this disclosure, the preset response process includes a first response process from the solid structure to the fluid via the boundary, and a second response process from the fluid to the solid structure via the boundary; the result determination module 840 includes a hydrodynamic pressure time history determination submodule and a target motion result determination submodule. The hydrodynamic pressure time history determination submodule is used to determine the hydrodynamic pressure time history based on the first response process, the target input response information, and the target physical substructure; and the target motion result determination submodule is used to determine the target motion result based on the hydrodynamic pressure time history, the second response process, and the target numerical substructure.

[0149] According to embodiments of this disclosure, any multiple modules among the structure splitting module 810, the influencing factor information determination module 820, the structure update module 830, and the result determination module 840 can be merged into one module, or any one of these modules can be split into multiple modules. Alternatively, at least some of the functions of one or more of these modules can be combined with at least some of the functions of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the structure splitting module 810, the influencing factor information determination module 820, the structure update module 830, and the result determination module 840 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in any one of software, hardware, and firmware methods, or in a suitable combination of any of these methods. Alternatively, at least one of the structure splitting module 810, the influencing factor information determination module 820, the structure update module 830, and the result determination module 840 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0150] Figure 9 A block diagram schematically illustrates an electronic device suitable for implementing a fluid-structure boundary iterative coupling hybrid experimental method according to an embodiment of the present disclosure.

[0151] like Figure 9 As shown, an electronic device 900 according to an embodiment of the present disclosure includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage portion 908 into a random access memory (RAM) 903. The processor 901 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 901 may also include onboard memory for caching purposes. The processor 901 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0152] RAM 903 stores various programs and data required for the operation of electronic device 900. Processor 901, ROM 902, and RAM 903 are interconnected via bus 904. Processor 901 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 902 and / or RAM 903. It should be noted that the programs may also be stored in one or more memories other than ROM 902 and RAM 903. Processor 901 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0153] According to embodiments of this disclosure, the electronic device 900 may further include an input / output (I / O) interface 905, which is also connected to a bus 904. The electronic device 900 may also include one or more of the following components connected to the input / output (I / O) interface 905: an input section 906 including a keyboard, mouse, etc.; an output section 907 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the input / output (I / O) interface 905 as needed. A removable medium 911, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 910 as needed so that computer programs read from it can be installed into the storage section 908 as needed.

[0154] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0155] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 902 and / or RAM 903 and / or one or more memories other than ROM 902 and RAM 903 described above.

[0156] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code enables the computer system to implement the fluid-structure boundary iterative coupling hybrid experimental method provided in the embodiments of this disclosure.

[0157] When the computer program is executed by the processor 901, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0158] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via the communication section 909, and / or installed from a removable medium 911. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0159] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 909, and / or installed from the removable medium 911. When the computer program is executed by the processor 901, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0160] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on a user's computing device, partially on a user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0161] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0162] Those skilled in the art will understand that the features described in the various embodiments of this disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments of this disclosure can be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0163] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A fluid-structure boundary iterative coupled hybrid experimental method, characterized in that, The method includes: The initial fluid-structure is divided into multiple substructures, wherein the multiple substructures include physical substructures and numerical substructures, the physical substructures correspond to the fluid, the numerical substructures correspond to the solid structure, and the boundary between the numerical substructure and the physical substructure corresponds to the boundary between the solid and the fluid. Based on the response error between the physical substructure and the numerical substructure, the influencing factors of the experimental convergence index are determined. The response error characterizes the error between the input response information of the physical substructure and the output response information of the numerical substructure. The influencing factors include the iterative algorithm and the substructure. The iterative algorithm is used to correct the response error between the numerical substructure and the physical substructure and to complete the fitting of the substructure boundary. If the response error does not meet a preset error threshold, the input response information, the output response information, and the substructure are updated based on the algorithm optimization strategy and parameter update strategy of the iterative algorithm to obtain a target structure. The target structure includes a target numerical substructure and a target physical substructure. The algorithm optimization strategy of the iterative algorithm is used to update the input response information and the output response information, and the parameter update strategy is used to update the substructure. Based on the target numerical substructure, the target physical substructure, and the preset response process, the dynamic water pressure time history and the target motion result are determined.

2. The method according to claim 1, characterized in that, If the response error does not meet a preset error threshold, an algorithm optimization strategy and parameter update strategy based on an iterative algorithm are used to update the input response information, the output response information, and the substructure to obtain the target structure, including: If the response error does not meet the preset error threshold, the input response information and the output response information are updated based on the algorithm optimization strategy to obtain the updated response error; If the update response error does not meet the preset error threshold, the substructure is updated based on the parameter update strategy to obtain the target structure.

3. The method according to claim 1, characterized in that, The method further includes: Construct a target motion model of the initial fluid-structure interaction structure under external forces; and The input response information and the output response information are determined based on the physical substructure, the numerical substructure, and the target motion model.

4. The method according to claim 2, characterized in that, The substructure is updated based on a parameter update strategy to obtain the target structure, including: Construct a reference structure corresponding to the initial fluid-structure interaction structure, wherein the reference structure includes a reference numerical substructure and a reference physical substructure; and The physical substructure and the numerical substructure are updated based on the reference numerical substructure, the reference physical substructure, and the parameter update strategy to obtain the target structure.

5. The method according to claim 4, characterized in that, The physical substructure and numerical substructure are updated based on the reference numerical substructure, the reference physical substructure, and the parameter update strategy to obtain the target structure, including: Based on the parameter update strategy, the reference numerical substructure, and the reference physical substructure, the dynamic water pressure value is determined and the structure is identified to obtain the additional dynamic water unit. The target structure is obtained by combining the additional dynamic water unit with the numerical substructure as the updated target numerical substructure.

6. The method according to claim 4, characterized in that, The measurement point corresponding to the reference physical substructure is the reference measurement point; Constructing a reference structure corresponding to the initial fluid-structure structure includes: The reference structure is obtained by taking the numerical substructure as the reference numerical substructure and the physical substructure corresponding to the reference measurement point as the reference physical substructure.

7. The method according to claim 2, characterized in that, The method further includes: If the response error does not meet the preset error threshold, the input response information and the output response information are updated using an intermediate iteration algorithm to obtain intermediate input response information and intermediate output response information. Determine the intermediate response error between the intermediate input response information and the intermediate output response information; and If the intermediate response error meets the preset error threshold, the intermediate iteration algorithm is determined as the target iteration algorithm.

8. The method according to claim 1, characterized in that, The number of measurement points corresponding to the target physical substructure is the number of target measurement points that meet the preset evaluation conditions; The method further includes: If the physical substructure and numerical substructure do not meet the preset evaluation conditions, the number of target measurement points is determined based on the additional dynamic water mass corresponding to the initial measurement point, the mass of the numerical substructure, and the damping of the numerical substructure.

9. The method according to claim 3, characterized in that, Determining the input response information and the output response information based on the physical substructure, the numerical substructure, and the target motion model includes: Based on the second motion model and the first motion model, a target motion model is constructed, wherein the first motion model represents the motion model corresponding to the physical substructure, and the second motion model represents the motion model corresponding to the numerical substructure; and Based on the physical substructure, the numerical substructure, and the target motion model, the input response information and the output response information are determined.

10. The method according to claim 1, characterized in that, The preset response process includes a first response process from the solid structure to the fluid via the boundary, and a second response process from the fluid to the solid structure via the boundary. Based on the target numerical substructure, the target physical substructure, and the preset response procedure, the hydrodynamic pressure time history and target motion results are determined, including: Based on the first response process, the target input response information, and the target physical substructure, the dynamic water pressure time history is determined; as well as The target motion result is determined based on the dynamic water pressure time history, the second response process, and the target numerical substructure.

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