Man-machine cooperation intelligent modeling and optimizing method for half-through steel arch bridge

Abstract

The invention discloses a half-through steel arch bridge man-machine cooperation intelligent modeling and optimizing method, which comprises the following steps: 1) determining a half-through steel arch bridge structure system, span, rise span ratio, arch axis shape, support form and steel-concrete combined bridge deck system section, and drawing an initial condition graph; 2) based on the initial condition graph, establishing a half-through steel arch bridge structure intelligent design model based on man-machine cooperation; 3) establishing a half-through steel arch bridge structure parameter optimization model based on the half-through steel arch bridge structure intelligent design model; and 4) resolving the half-through steel arch bridge structure parameter optimization model to obtain each half-through steel arch bridge structure optimization parameter. According to the method, only a small amount of man-machine interaction operation is needed, initial condition graph information is extracted by utilizing a layer analysis algorithm, and rapid modeling of the half-through steel arch bridge can be realized in combination with priori knowledge, so that manual modeling errors are avoided, and the modeling efficiency and quality are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent design of bridge structure, and particularly relates to a method for intelligent modeling and optimization of a half-through steel arch bridge in man-machine cooperation. BACKGROUND

[0002] Under the traditional bridge design mode, engineers need to repeatedly adjust the structural scheme for trial calculation according to the bridge construction conditions and requirements, combined with their own experience and knowledge, bridge design rules and the like, so as to obtain a relatively optimal design scheme. However, the traditional mode inevitably brings a large amount of modeling work, and each time the engineers adjust the bridge structural arrangement scheme, the overall arrangement of the structure, the cross section setting, the load arrangement and the like in the model need to be reconstructed, resulting in a long design cycle, and the structural optimization result often depends on the personal experience of the engineers, and it is difficult to take into account the safety, economy and advancement, especially for large bridge design such as arch bridge, the contradiction is more prominent. Therefore, it is urgent to propose an intelligent design technology mainly based on parameterization and intelligentization. At present, the research at home and abroad has made certain progress in parameterized modeling, but generally still has problems such as being only applicable to specific cross section components and simple structural forms, incomplete model, and dependence on specific software. In the aspect of intelligent optimization of bridge structure, there has been preliminary exploration, but generally it is still carried out for specific bridge structural forms under simple load action, and the adaptability to the optimization of similar bridges is still insufficient. SUMMARY

[0003] The purpose of the present application is to provide a method for intelligent modeling and optimization of a half-through steel arch bridge in man-machine cooperation, comprising the following steps:

[0004] 1) determining the structural system, span, rise-span ratio, arch axis shape, support form and steel-concrete composite bridge deck system section of the half-through steel arch bridge, and drawing an initial condition diagram;

[0005] 2) establishing an intelligent design model of the half-through steel arch bridge based on man-machine cooperation based on the initial condition diagram;

[0006] 3) establishing a parameter optimization model of the half-through steel arch bridge based on the intelligent design model of the half-through steel arch bridge;

[0007] 4) solving the parameter optimization model of the half-through steel arch bridge to obtain the optimization parameters of each half-through steel arch bridge.

[0008] Further, the initial condition diagram comprises an initial condition elevation diagram of the half-through steel arch bridge, an initial condition plan diagram of the half-through steel arch bridge and an initial condition section diagram of the steel-concrete composite bridge deck system.

[0009] The initial condition diagram records the arch axis center line elevation positioning, arch rib plan positioning, support plan positioning, bridge deck elevation and steel-concrete composite bridge deck system section arrangement.

[0010] Further, in step 2), the step of establishing the intelligent design model of the half-through steel arch bridge based on human-computer collaboration includes:

[0011] 2.1) reading the key component information in the initial condition graph by using the layer analysis algorithm;

[0012] The key component information includes the coordinates of the arch axis center line arch top and the arch stand elevation, the plane coordinates of the support and the arch rib inner side line, the bridge deck top elevation information, and the steel longitudinal beam web coordinate information in the steel-concrete composite bridge deck section graph;

[0013] 2.2) automatically generating each component and connection unit of the half-through steel arch bridge based on spatial information reasoning and using the read key component information;

[0014] 2.3) automatically defining constraints;

[0015] 2.4) automatically arranging loads, including but not limited to the self-weight of each component of the half-through steel arch bridge, the self-weight of asphalt pavement, the self-weight of railings, and the lane load;

[0016] 2.5) outputting the intelligent design model of the half-through steel arch bridge.

[0017] Further, in step 2.1), the step of reading the key component information in the initial condition graph by using the layer analysis algorithm includes:

[0018] 2.1.1) marking the support and the arch rib inner side line of the initial condition plan of the bridge;

[0019] 2.1.2) marking the arch axis center line and the bridge deck top line of the initial condition elevation graph of the bridge;

[0020] 2.1.3) marking the steel longitudinal beam web of the steel-concrete composite bridge deck section graph of the bridge;

[0021] 2.1.4) reading various curve information by using the layer analysis algorithm to determine the coordinates of the arch axis center line arch top and the arch stand elevation, the plane coordinates of the support and the arch rib inner side line, the bridge deck top elevation information, and the steel longitudinal beam web coordinate information in the steel-concrete composite bridge deck section graph.

[0022] Further, in step 2.2), the step of generating each component and connection unit of the half-through steel arch bridge includes:

[0023] 2.2.1) determining the section form, preliminary geometric size, and material information of the arch rib, support, inter-arch beam, steel-concrete composite bridge deck system, and suspender, determining the support information and arch axis coefficient;

[0024] 2.2.2) determining the size and start-stop coordinates of each component based on spatial information reasoning and combining the key component information, the preliminary geometric size of the arch rib, support, inter-arch beam, steel-concrete composite bridge deck system, and suspender;

[0025] The components include arch ribs, inter-arch transverse beams, supports, steel longitudinal beams, steel transverse beams, bridge deck slabs, bearings;

[0026] 2.2.3) According to the component unit size, a unit division criterion is formulated, the number of each component unit is determined, and these component nodes are automatically numbered in the order of arch ribs, inter-arch transverse beams, supports, steel longitudinal beams, steel transverse beams, bridge deck slabs, and bearings;

[0027] 2.2.4) In combination with the arch rib, inter-arch transverse beam, support, steel longitudinal beam, steel transverse beam, bridge deck slab, bearing node numbering, the arch rib, inter-arch transverse beam, support, steel longitudinal beam, steel transverse beam, bridge deck slab, bearing, suspender, and steel longitudinal beam-bridge deck slab connection unit numbering are performed, and the start and end nodes of each connection unit are recorded;

[0028] 2.2.5) The fiber section of each component unit is defined, and the steps include:

[0029] 2.2.5.1) According to the size of the component unit in the thickness, width, and height directions, a section fiber division criterion is formulated;

[0030] 2.2.5.2) The constitutive relationship of each type of material is defined, and a material library and a constitutive relationship library are established;

[0031] 2.2.5.3) According to the section shape and geometric size information of each component unit, a section contour is automatically generated, the fiber section is divided, and the material index and constitutive relationship are read according to the material information;

[0032] 2.2.6) The category of each component unit is defined, and the components and connection units of the half-through steel arch bridge are generated.

[0033] Further, in step 2.3), the step of automatically defining constraints includes:

[0034] 2.3.1) The nodes at the bottom of the abutments and the abutments at both ends of the bridge deck system are extracted, and boundary conditions are defined;

[0035] 2.3.2) Based on prior knowledge, a bridge deck system abutment arrangement criterion is formulated, and an abutment performance index library is established;

[0036] 2.3.3) The nodes at the bottom of the abutments at both ends of the bridge deck system and the corresponding positions of the steel longitudinal beams of the bridge deck system are extracted, and the abutment units at the top of the inter-arch transverse beams and at both ends of the bridge deck system are automatically generated;

[0037] 2.3.4) The boundary conditions and abutment unit information at the bottom of the abutments and the abutments at both ends of the bridge deck system are written into a file, thereby achieving the automatic definition of the boundary conditions and abutment units.

[0038] Further, in step 2.4), the step of automatically arranging loads includes:

[0039] 2.4.1) The self-weights of various components, the self-weights of asphalt pavement and the self-weights of railings are applied in the form of uniformly distributed line loads;

[0040] wherein the line load intensity g L As shown below:

[0041] g L =A x p (1)

[0042] In the formula, A is the cross-sectional area; p is the material density;

[0043] 2.4.2) The lane load is calculated based on the read information of the half-through steel arch bridge according to the requirements of the General Specification for Design of Highway Bridges and Culverts, and is applied in the form of uniformly distributed loads and concentrated loads.

[0044] Further, in step 3), the step of establishing the structural parameter optimization model of the half-through steel arch bridge comprises:

[0045] 3.1) Selecting variables to be optimized for various components, and determining the value range of the decision variables;

[0046] The variables to be optimized include but are not limited to: the cross-sectional height of the arch rib at the bottom and the width-height ratio, the height ratio of the cross-section at the top of the arch rib to the cross-section at the bottom, the thickness of the flange and web of the arch rib, the thickness of the bridge deck and the concrete strength, the height of the steel beam of the bridge deck system, the width and thickness of the flange of the steel beam of the bridge deck system, and the thickness of the web of the steel beam of the bridge deck system;

[0047] 3.2) Establishing a constraint mathematical model of the structural parameter optimization model of the half-through steel arch bridge, including the constraint mathematical model under the ultimate limit state of bearing capacity, the constraint mathematical model under the normal use limit state, and the geometric constraint mathematical model;

[0048] 3.3) Establishing a target function with material cost as the optimization objective, i.e.:

[0049]

[0050] In the formula, i is the component material number; i = 1, 2, 3, …, n; n is the total number of component materials; A i is the cross-sectional area of the component material; L i is the length of the component material; and P i is the unit price of the component material.

[0051] 3.4) Establishing a pseudo-target function F based on the external penalty method, and taking the pseudo-target function F as the target function of the structural parameter optimization model of the half-through steel arch bridge;

[0052] The pseudo-target function F is shown below:

[0053]

[0054] In the formula, j is the number of constraints in the bearing capacity limit state and the normal use limit state; j = 1, 2, 3…, m; m is the total number of constraints in the bearing capacity limit state and the normal use limit state; C j The penalty function of the jth constraint is 0 when the constraint is not violated, and is a predetermined penalty value when the constraint is violated.

[0055] Further, the constraint mathematical model in the bearing capacity limit state includes but is not limited to: a constraint that the cross-section bending capacity does not exceed the cross-section bending capacity limit value, a constraint that the cross-section shear capacity does not exceed the cross-section shear capacity limit value;

[0056] The constraint that the cross-section bending capacity does not exceed the cross-section bending capacity limit value is as follows:

[0057] M-M lim ≤0(4)

[0058] In the formula, M is the cross-section bending capacity, M lim is the cross-section bending capacity limit value;

[0059] The constraint that the cross-section shear capacity does not exceed the cross-section shear capacity limit value is as follows:

[0060] V-V lim ≤0(5)

[0061] In the formula, V is the cross-section shear capacity, V lim is the cross-section shear capacity limit value;

[0062] The constraint mathematical model in the normal use limit state includes but is not limited to: a constraint that the member deflection does not exceed the deflection limit value, a constraint that the crack width does not exceed the crack width limit value;

[0063] The constraint that the member deflection does not exceed the deflection limit value is as follows:

[0064] δ-δ lim ≤0(6)

[0065] In the formula, δ is the member deflection, δ lim is the member deflection limit value;

[0066] The constraint that the crack width does not exceed the crack width limit value is as follows:

[0067] w cr -w crlim ≤0(7)

[0068] In the formula, w cr is the crack width, w crlim is the crack width limit value;

[0069] The geometric constraint mathematical model includes but is not limited to: a constraint that a flange width-thickness ratio of the steel structural member does not exceed a limit value, and a constraint that a web height-thickness ratio of the steel structural member does not exceed a limit value.

[0070] The constraint that the flange width-thickness ratio of the steel structural member does not exceed the limit value is as follows:

[0071] B f / t f ≤rf lim (8)

[0072] In the formula, B f is a flange width parameter of the steel structural member, t f is a flange thickness of the steel structural member, and rf lim is a flange width-thickness ratio limit value of the steel structural member.

[0073] The constraint that the web height-thickness ratio of the steel structural member does not exceed the limit value is as follows:

[0074] h w / t w ≤=rw lim (9)

[0075] In the formula, h w is a web height of the steel structural member, t w is a web thickness of the steel structural member, and rw lim is a web height-thickness ratio limit value of the steel structural member.

[0076] Further, the algorithm for solving the structural parameter optimization model of the half-through steel arch bridge includes but is not limited to: a genetic algorithm, a particle swarm algorithm, and a differential evolution algorithm.

[0077] The optimization algorithm adopts a parameter self-adaptive adjustment strategy to optimize population quality when generating individuals, so as to avoid generating invalid individuals.

[0078] When adjusting the arch rib section parameters, the self-adaptive adjustment strategy includes the following steps:

[0079] a) fixing the flange width of the arch rib section, and judging whether the flange width-thickness ratio of the steel structural member exceeds the limit value, if yes, automatically updating to the minimum flange thickness that satisfies the flange width-thickness ratio limit value constraint of the steel structural member, and if no, not changing the flange thickness;

[0080] b) determining the web height of the arch rib section according to the height and the flange thickness of the arch rib section, and judging whether the web height-thickness ratio of the steel structural member exceeds the limit value, if yes, automatically updating to the minimum web thickness that satisfies the web height-thickness ratio limit value constraint of the steel structural member, and if no, not changing the web thickness;

[0081] c) the adjustment sequence of the arch rib section is from the arch top section to the arch bottom section.

[0082] when the cross-sectional web thickness adjacent to the side close to the arch bottom is less than the cross-sectional web thickness adjacent to the side close to the arch top, the cross-sectional web thickness is automatically updated to the cross-sectional web thickness adjacent to the side close to the arch top;

[0083] when the cross-sectional web thickness adjacent to the side close to the arch bottom is less than the cross-sectional web thickness adjacent to the side close to the arch top, the cross-sectional web thickness is automatically updated to the cross-sectional web thickness adjacent to the side close to the arch top;

[0084] When adjusting the upper flange width cross-sectional parameters of the bridge system steel beam, the adaptive adjustment strategy includes the following steps:

[0085] I) Fix the steel beam cross-sectional flange width, and determine whether the flange width-thickness ratio of the steel structure member exceeds the limit value. If yes, it is automatically updated to the minimum flange thickness that meets the flange width-thickness ratio limit of the steel structure member. If not, the flange thickness is not changed;

[0086] II) Determine the steel beam cross-sectional web height according to the steel beam cross-sectional height and flange thickness, and determine whether the web height-thickness ratio of the steel structure member exceeds the limit value. If yes, it is automatically updated to the minimum web thickness that meets the web height-thickness ratio limit of the steel structure member. If not, the web thickness is not changed.

[0087] The technical effect of the present application is self-evident. The present application proposes a half-through steel arch bridge human-computer collaborative intelligent modeling and optimization framework. This method only needs a small amount of human-computer interaction operation, uses layer analysis algorithm to extract initial condition graph information, and combines prior knowledge to realize rapid modeling of half-through steel arch bridge, avoids artificial modeling error, and improves modeling efficiency and quality. At the same time, based on the established intelligent design model of half-through steel arch bridge structure, the optimization algorithm is used to optimize the structure parameters, effectively improving the bridge design quality and efficiency. This method has strong flexibility and adaptability, and can be popularized to different types of bridge design. BRIEF DESCRIPTION OF DRAWINGS

[0088] Figure 1 The intelligent modeling and optimization method flowchart of the embodiment of the present application;

[0089] Figure 2 The intelligent modeling flowchart of the embodiment of the present application;

[0090] Figure 3 The initial condition graph drawing example of the half-through steel arch bridge of the embodiment of the present application;

[0091] Figure 4 The initial condition graph reading example of the half-through steel arch bridge of the embodiment of the present application;

[0092] Figure 5 The intelligent modeling result example of the half-through steel arch bridge of the embodiment of the present application;

[0093] Figure 6 Intelligent optimization flowchart for the embodiment of the present application;

[0094] Figure 7 Intelligent optimization process for the embodiment of the present application. DETAILED DESCRIPTION

[0095] The present application will be further described in conjunction with the embodiments, but should not be understood as limiting the above-mentioned subject matter of the present application to the following embodiments. Various substitutions and modifications can be made according to ordinary technical knowledge and conventional means in the art without departing from the above-mentioned technical idea of the present application, and all should be included in the protection scope of the present application.

[0096] Example 1:

[0097] Referring to Figures 1 to 7 A man-machine collaborative intelligent modeling and optimization method for a half-through steel arch bridge, comprising the following steps:

[0098] 1) determining the structural system, span, rise-span ratio, arch axis shape, support form, and steel-concrete composite bridge deck section of the half-through steel arch bridge, and drawing an initial condition diagram;

[0099] 2) establishing a man-machine collaborative intelligent design model for the half-through steel arch bridge structure based on the initial condition diagram;

[0100] 3) establishing a half-through steel arch bridge structure parameter optimization model based on the intelligent design model for the half-through steel arch bridge structure;

[0101] 4) solving the half-through steel arch bridge structure parameter optimization model to obtain the optimized parameters of each half-through steel arch bridge structure.

[0102] The initial condition diagram includes an initial condition elevation diagram of the half-through steel arch bridge, an initial condition plan diagram of the half-through steel arch bridge, and an initial condition section diagram of the steel-concrete composite bridge deck system.

[0103] The initial condition diagram records the arch axis center line elevation positioning, arch rib plan positioning, support plan positioning, bridge deck elevation, and steel-concrete composite bridge deck section arrangement.

[0104] In step 2), the steps of establishing the man-machine collaborative intelligent design model for the half-through steel arch bridge include:

[0105] 2.1) reading the key component information in the initial condition diagram using a layer analysis algorithm; the layer analysis algorithm can obtain relevant curve information such as straight lines by marking layers in cad and then reading DXF files (for example, reading in python), that is, two end point coordinates.

[0106] The key component information includes the coordinates of the arch axis center line, the arch top and the arch seat elevation, the coordinates of the support and the arch rib inner side line plane, the bridge deck top elevation information, and the steel longitudinal beam web coordinate information in the steel-concrete composite bridge deck system section view;

[0107] 2.2) Based on spatial information reasoning, automatically generate each component and connection unit of the half-through steel arch bridge using the read key component information;

[0108] 2.3) Automatically define constraints;

[0109] 2.4) Automatically arrange loads, including but not limited to the self-weight of each component of the half-through steel arch bridge, the self-weight of asphalt pavement, the self-weight of railings, and lane loads;

[0110] 2.5) Output the intelligent design model of the half-through steel arch bridge.

[0111] In step 2.1), the step of reading the key component information in the initial condition graph using the layer analysis algorithm includes:

[0112] 2.1.1) Mark the support and arch rib inner side line of the bridge initial condition plan view;

[0113] 2.1.2) Mark the arch axis center line and the bridge deck top line of the bridge initial condition elevation view;

[0114] 2.1.3) Mark the steel longitudinal beam web of the bridge steel-concrete composite bridge deck system section view;

[0115] 2.1.4) Read various curve information using the layer analysis algorithm to determine the coordinates of the arch axis center line, the arch top and the arch seat elevation, the coordinates of the support and the arch rib inner side line plane, the bridge deck top elevation information, and the steel longitudinal beam web coordinate information in the steel-concrete composite bridge deck system section view.

[0116] In step 2.2), the step of generating each component and connection unit of the half-through steel arch bridge includes:

[0117] 2.2.1) Determine the section form, preliminary geometric dimensions and material information of the arch rib, support, arch interbeam, steel-concrete composite bridge deck system and suspender, determine the support information and arch axis coefficient;

[0118] 2.2.2) Based on spatial information reasoning, determine the size and start-stop coordinates of each component in combination with the key component information, the preliminary geometric dimensions of the arch rib, support, arch interbeam, steel-concrete composite bridge deck system and suspender;

[0119] The components include arch rib, arch interbeam, support, steel longitudinal beam, steel transverse beam, bridge deck, and support;

[0120] 2.2.3) According to the size of the component unit, the unit division criterion is formulated, the number of each component unit is determined, and these component nodes are automatically numbered in the order of arch rib, inter-arch beam, support, steel longitudinal beam, steel transverse beam, bridge deck, and support;

[0121] The unit division criterion can be formulated as: the component unit division length is not greater than its cross-section height. For composite beams, since it is a double-layer beam unit, the steel beam unit is divided in a length not exceeding the cross-section height of the steel beam, and the bridge deck unit length is the same as the steel beam unit length.

[0122] 2.2.4) Combined with the arch rib, inter-arch beam, support, steel longitudinal beam, steel transverse beam, bridge deck, and support node numbering, the arch rib, inter-arch beam, support, steel longitudinal beam, steel transverse beam, bridge deck, support, suspender, and steel longitudinal beam-bridge deck connection unit numbering are performed, and the start and end nodes of each connection unit are recorded;

[0123] 2.2.5) Define the fiber cross-section of each component unit, the steps include:

[0124] 2.2.5.1) According to the size of the component unit in the thickness, width, and height directions, the cross-section fiber division criterion is formulated;

[0125] For example, the steel structure unit plate thickness direction is divided into 4 fibers, the width or height direction fiber length is not greater than 50mm, and the concrete bridge deck unit thickness and width direction fiber length is not greater than 40mm and 100mm respectively.

[0126] 2.2.5.2) Define the constitutive relationship of each type of material, establish the material library and constitutive relationship library;

[0127] 2.2.5.3) According to the cross-section shape and geometric size information of each component unit, the cross-section profile is automatically generated, the fiber cross-section is divided, and the material index and constitutive relationship are read according to the material information;

[0128] 2.2.6) Define the category of each component unit, and generate the components and connection units of the half-through steel arch bridge.

[0129] In step 2.3), the step of automatically defining constraints includes:

[0130] 2.3.1) Extract the nodes at the bottom of the arch supports and the bridge deck system end supports, and define the boundary conditions (set according to specific conditions, such as fixed and hinged);

[0131] 2.3.2) Based on prior knowledge, formulate the bridge deck system support arrangement criterion (formulate rules in combination with the designer's experience), and establish the support performance index library;

[0132] 2.3.3) Extract the nodes at the bottom of the support of the transverse beam between arches and bridge deck system and the corresponding position of the steel longitudinal beam of the bridge deck system, and automatically generate the support unit at the top of the transverse beam between arches and the two ends of the bridge deck system;

[0133] 2.3.4) Write the boundary conditions and support unit information into a file, so as to realize the automatic definition of the boundary conditions and support unit at the bottom of the support of the arch and the bridge deck system.

[0134] In step 2.4), the step of automatically arranging the load includes:

[0135] 2.4.1) The self-weight of various components, the self-weight of asphalt pavement and the self-weight of railings are applied in the form of uniform line load;

[0136] Wherein, the line load set g L As follows:

[0137] g L =A×ρ (1)

[0138] In the formula, A is the cross-sectional area; and p is the material density;

[0139] 2.4.2) The lane load is calculated based on the read information of the half-through steel arch bridge according to the requirements of the "General Code for Design of Highway Bridges and Culverts", and is applied in the form of uniform load and concentrated load.

[0140] In step 3), the step of establishing the optimization model of the structural parameters of the half-through steel arch bridge includes:

[0141] 3.1) Select the variables of various components to be optimized, and determine the value range of the decision variables;

[0142] The variables to be optimized include but are not limited to: the cross-sectional height of the arch rib at the bottom and the width-height ratio, the height ratio of the cross-section at the top of the arch rib to the cross-section at the bottom, the thickness of the flange and web of the arch rib, the thickness of the bridge deck and the concrete strength, the height of the steel beam of the bridge deck system, the width and thickness of the flange of the steel beam of the bridge deck system, and the thickness of the web of the steel beam of the bridge deck system;

[0143] 3.2) Establish the constraint mathematical model of the optimization model of the structural parameters of the half-through steel arch bridge, including the constraint mathematical model under the limit state of bearing capacity, the constraint mathematical model under the limit state of normal use and the geometric constraint mathematical model;

[0144] 3.3) Establish the objective function with the material cost as the optimization target, that is:

[0145]

[0146] In the formula, i is the component material number; i=1, 2, 3…, n; n is the total number of component materials; A i is the cross-sectional area of the component material; L i is the length of the component material; Pi Unit price of component material.

[0147] 3.4) Establish a pseudo-objective function F based on external penalty method, and take the pseudo-objective function F as the objective function of the structural parameter optimization model of the half-through steel arch bridge;

[0148] The pseudo-objective function F is as follows:

[0149]

[0150] In the formula, j is the number of constraints under the bearing capacity limit state and the normal use limit state; j = 1, 2, 3…, m; m is the total number of constraints under the bearing capacity limit state and the normal use limit state; C j is the penalty function of the jth constraint, which is 0 when the constraint is not violated, and is a predetermined penalty value when the constraint is violated.

[0151] The mathematical model of the constraint under the bearing capacity limit state includes but is not limited to the constraint that the sectional flexural capacity does not exceed the sectional flexural capacity limit value, and the constraint that the sectional shear capacity does not exceed the sectional shear capacity limit value.

[0152] The constraint that the sectional flexural capacity does not exceed the sectional flexural capacity limit value is as follows:

[0153] M-M lim ≤ 0 (4)

[0154] In the formula, M is the sectional flexural capacity, M lim is the sectional flexural capacity limit value.

[0155] The constraint that the sectional shear capacity does not exceed the sectional shear capacity limit value is as follows:

[0156] V-V lim ≤ 0 (5)

[0157] In the formula, V is the sectional shear capacity, V lim is the sectional shear capacity limit value.

[0158] The mathematical model of the constraint under the normal use limit state includes but is not limited to the constraint that the member deflection does not exceed the deflection limit value, and the constraint that the crack width does not exceed the crack width limit value.

[0159] The constraint that the member deflection does not exceed the deflection limit value is as follows:

[0160] δ-δ lim ≤ 0 (6)

[0161] In the formula, δ is the member deflection, δ lim is the member deflection limit value.

[0162] The crack width does not exceed the crack width limit value constraint is as follows:

[0163] w cr -w crlim ≤0(7)

[0164] In the formula, w cr is the crack width, w crlim is the crack width limit value;

[0165] The geometric constraint mathematical model includes but is not limited to: the steel structure member flange width-thickness ratio does not exceed the limit value constraint, the steel structure member web height-thickness ratio does not exceed the limit value constraint.

[0166] The steel structure member flange width-thickness ratio does not exceed the limit value constraint is as follows:

[0167] B f / t f ≤rf lim (8)

[0168] In the formula, B f is the steel structure member flange width parameter, t f is the steel structure member flange thickness, and rf lim is the steel structure member flange width-thickness ratio limit value.

[0169] The steel structure member web height-thickness ratio does not exceed the limit value constraint is as follows:

[0170] h w / t w ≤=rw lim (9)

[0171] In the formula, h w is the steel structure member web height, t w is the steel structure member web thickness, and rw lim is the steel structure member web height-thickness ratio limit value.

[0172] The algorithm for solving the half-through steel arch bridge structure parameter optimization model includes but is not limited to: genetic algorithm, particle swarm algorithm, differential evolution algorithm;

[0173] The optimization algorithm adopts a parameter adaptive adjustment strategy to optimize the population quality when generating individuals, and avoids generating invalid individuals;

[0174] Wherein, when adjusting the arch rib section parameters, the adaptive adjustment strategy includes the following steps:

[0175] a) Fix the arch rib section flange width, and judge whether the steel structure member flange width-thickness ratio exceeds the limit value, if yes, automatically update to the minimum flange thickness that satisfies the steel structure member flange width-thickness ratio limit value constraint, if not, do not change the flange thickness;

[0176] b) determining the web height of the arch rib section according to the section height and the flange thickness of the arch rib, and determining whether the web height-thickness ratio of the steel structural member exceeds the limit value, if yes, automatically updating to the minimum web thickness meeting the constraint that the web height-thickness ratio of the steel structural member does not exceed the limit value, if not, not changing the web thickness;

[0177] c) the adjustment sequence of the arch rib section is from the arch top section to the arch bottom section;

[0178] when the flange thickness of the section close to the arch bottom side is less than the flange thickness of the section adjacent to the section close to the arch top side, the flange thickness of the section is automatically updated to the flange thickness of the section adjacent to the section close to the arch top side;

[0179] when the web thickness of the section close to the arch bottom side is less than the web thickness of the section adjacent to the section close to the arch top side, the web thickness of the section is automatically updated to the web thickness of the section adjacent to the section close to the arch top side;

[0180] when adjusting the upper flange width section parameters of the bridge deck system steel beam, the adaptive adjustment strategy includes the following steps:

[0181] I) fixing the flange width of the steel beam section, and determining whether the flange width-thickness ratio of the steel structural member exceeds the limit value, if yes, automatically updating to the minimum flange thickness meeting the flange width-thickness ratio limit value constraint of the steel structural member, if not, not changing the flange thickness;

[0182] II) determining the web height of the steel beam section according to the section height and the flange thickness of the steel beam, and determining whether the web height-thickness ratio of the steel structural member exceeds the limit value, if yes, automatically updating to the minimum web thickness meeting the constraint that the web height-thickness ratio of the steel structural member does not exceed the limit value, if not, not changing the web thickness.

[0183] Embodiment 2:

[0184] A man-machine collaborative intelligent modeling and optimization method for half-through steel arch bridges, comprising the following steps:

[0185] 1) determining the structural system, span, rise-span ratio, arch axis shape, support form, and steel-concrete composite bridge deck section of the half-through steel arch bridge, and drawing an initial condition diagram;

[0186] 2) establishing a man-machine collaborative intelligent design model for the half-through steel arch bridge structure based on the initial condition diagram;

[0187] 3) establishing a half-through steel arch bridge structure parameter optimization model based on the intelligent design model of the half-through steel arch bridge structure;

[0188] 4) solving the half-through steel arch bridge structure parameter optimization model to obtain the optimization parameters of each half-through steel arch bridge structure.

[0189] Embodiment 3:

[0190] A human-computer collaborative intelligent modeling and optimization method for half-through steel arch bridges, the technical content is the same as that of embodiment 2, further, the initial condition diagram includes a half-through steel arch bridge initial condition elevation, a half-through steel arch bridge initial condition plan, and a steel-concrete composite bridge deck system initial condition section diagram.

[0191] The initial condition diagram records the positioning of the arch axis center line elevation, the arch rib plane, the support plane, the bridge deck elevation, and the steel-concrete composite bridge deck system section arrangement.

[0192] Embodiment 4:

[0193] A human-computer collaborative intelligent modeling and optimization method for half-through steel arch bridges, the technical content is the same as that of any one of embodiments 2-3, further, in step 2), the step of establishing a human-computer collaborative intelligent design model for a half-through steel arch bridge includes:

[0194] 2.1) reading the key component information in the initial condition diagram using a layer analysis algorithm;

[0195] The key component information includes the arch axis center line crown and arch seat elevation coordinates, the support and arch rib inside edge line plane coordinates, the bridge deck slab top elevation information, and the steel longitudinal beam web coordinate information in the steel-concrete composite bridge deck system section diagram;

[0196] 2.2) based on spatial information reasoning, automatically generating each component and connection unit of the half-through steel arch bridge using the read key component information;

[0197] 2.3) automatically defining constraints;

[0198] 2.4) automatically arranging loads, including but not limited to the self-weight of each component of the half-through steel arch bridge, the self-weight of asphalt pavement, the self-weight of railings, and lane loads;

[0199] 2.5) outputting the intelligent design model of the half-through steel arch bridge.

[0200] Embodiment 5:

[0201] A human-computer collaborative intelligent modeling and optimization method for half-through steel arch bridges, the technical content is the same as that of any one of embodiments 2-4, further, in step 2.1), the step of reading the key component information in the initial condition diagram using a layer analysis algorithm includes:

[0202] 2.1.1) marking the support and arch rib inside edge line of the bridge initial condition plan;

[0203] 2.1.2) marking the arch axis center line and bridge deck slab top line of the bridge initial condition elevation;

[0204] 2.1.3) marking the steel longitudinal beam web of the bridge steel-concrete composite bridge deck system section diagram;

[0205] 2.1.4) Reading various types of curve information by using layer analysis algorithm, determining the coordinates of arch axis center line, arch crown and arch spring, the coordinates of support and inner side line of arch rib, the top elevation information of bridge deck slab, and the coordinates of steel girder web in steel-concrete composite bridge deck system section diagram.

[0206] Embodiment 6:

[0207] A human-computer collaborative intelligent modeling and optimization method for half-through steel arch bridges, the technical content of which is the same as any one of embodiments 2-5, further, in step 2.2), the step of generating each component and connecting unit of the half-through steel arch bridge comprises:

[0208] 2.2.1) determining the section form, preliminary geometric size and material information of arch rib, support, inter-arch beam, steel-concrete composite bridge deck system and suspender, determining support information and arch axis coefficient;

[0209] 2.2.2) determining the size and start-stop coordinates of each component based on spatial information reasoning, combining key component information, preliminary geometric size of arch rib, support, inter-arch beam, steel-concrete composite bridge deck system and suspender;

[0210] The components include arch rib, inter-arch beam, support, steel girder, steel cross beam, bridge deck slab and support;

[0211] 2.2.3) formulating unit division criteria, determining the number of units of each component, and automatically numbering the nodes of these components in the order of arch rib, inter-arch beam, support, steel girder, steel cross beam, bridge deck slab and support;

[0212] 2.2.4) combining the node numbers of arch rib, inter-arch beam, support, steel girder, steel cross beam, bridge deck slab and support, numbering arch rib, inter-arch beam, support, steel girder, steel cross beam, bridge deck slab, support, suspender and steel girder-bridge deck slab connecting unit, and recording the start-stop nodes of each connecting unit;

[0213] 2.2.5) defining the fiber section of each component unit, the steps comprising:

[0214] 2.2.5.1) formulating section fiber division criteria;

[0215] 2.2.5.2) defining the constitutive relationship of various types of materials, establishing material library and constitutive relationship library;

[0216] 2.2.5.3) automatically generating section contour according to the section shape and geometric size information of each component unit, dividing fiber section, and reading material index and constitutive relationship according to material information;

[0217] 2.2.6) defining the category of each component unit, generating components and connecting units of the half-through steel arch bridge.

[0218] Embodiment 7:

[0219] A man-machine collaborative intelligent modeling and optimization method for half-through steel arch bridges, the technical content of any one of embodiments 2-6, further, in step 2.3), the step of automatically defining constraints includes:

[0220] 2.3.1) Extract the nodes at the bottom of the abutments of the arch supports and the bridge deck system, and define the boundary conditions;

[0221] 2.3.2) Based on prior knowledge, develop bridge deck system abutment arrangement guidelines and establish a support performance index library;

[0222] 2.3.3) Extract the nodes at the bottom of the arch supports and the bridge deck system at the corresponding positions of the arch interbeam and the bridge deck system steel longitudinal beam, and automatically generate the abutment units at the top of the arch interbeam and the two ends of the bridge deck system;

[0223] 2.3.4) Write the boundary conditions and abutment unit information into a file, thereby achieving automatic definition of various constraints.

[0224] Embodiment 8:

[0225] A man-machine collaborative intelligent modeling and optimization method for half-through steel arch bridges, the technical content of any one of embodiments 2-7, further, in step 2.4), the step of automatically arranging loads includes:

[0226] 2.4.1) The self-weight of various components, the self-weight of asphalt pavement, and the self-weight of railings are applied in the form of uniform line loads;

[0227] Wherein, the line load intensity g L As follows:

[0228] g L =A x p (1)

[0229] Wherein, A is the cross-sectional area; p is the material density;

[0230] 2.4.2) The lane load is calculated based on the information of the half-through steel arch bridge read according to the requirements of the specification, and is applied in the form of uniform load and concentrated load.

[0231] Embodiment 9:

[0232] A man-machine collaborative intelligent modeling and optimization method for half-through steel arch bridges, the technical content of any one of embodiments 2-8, further, in step 3), the step of establishing a half-through steel arch bridge structure parameter optimization model includes:

[0233] 3.1) Select the variables of various components to be optimized, and determine the value range of the decision variables;

[0234] The variables to be optimized include, but are not limited to: the cross-section height and width-height ratio of the arch rib bottom, the height ratio of the cross-section of the arch rib top to the cross-section of the arch bottom, the thickness of the arch rib flange and web, the thickness of the bridge deck and the concrete strength, the height of the bridge deck system steel beam, the width and thickness of the bridge deck system steel beam flange, and the thickness of the bridge deck system steel beam web;

[0235] 3.2) Establish a constraint mathematical model of the half-through steel arch bridge structure parameter optimization model, including bearing capacity limit state constraints, normal use limit state constraints, and geometric constraint mathematical models;

[0236] 3.3) Establish a target function with material cost as the optimization objective, that is:

[0237]

[0238] In the formula, i is the component material number; i = 1, 2, 3…, n; n is the total number of component materials; A i is the cross-sectional area of the component material; L i is the length of the component material; P i is the unit price of the component material.

[0239] 3.4) Establish a pseudo-objective function F based on the external penalty method, and use the pseudo-objective function F as the objective function of the half-through steel arch bridge structure parameter optimization model;

[0240] The pseudo-objective function F is as follows:

[0241]

[0242] In the formula, j is the number of bearing capacity limit state constraints and normal use limit state constraints; j = 1, 2, 3…, m; m is the total number of bearing capacity limit state constraints and normal use limit state constraints; C j is the penalty function of the jth constraint, which is 0 when the constraint is not violated, and is a predetermined penalty value when the constraint is violated.

[0243] Example 10:

[0244] A half-through steel arch bridge man-machine collaborative intelligent modeling and optimization method, the technical content is the same as any one of examples 2-9, further, the bearing capacity limit state constraint mathematical model includes but is not limited to: the cross-section bending resistance capacity does not exceed the cross-section bending resistance capacity limit value constraint, the cross-section shear capacity does not exceed the cross-section shear capacity limit value constraint;

[0245] The cross-section bending resistance capacity does not exceed the cross-section bending resistance capacity limit value constraint is as follows:

[0246] M-M lim ≤0(4)

[0247] In the formula, M is the flexural capacity of the section, M lim This refers to the limit value of the flexural bearing capacity of the cross section;

[0248] The shear capacity ratio of the section does not exceed the shear capacity limit constraint as shown below:

[0249] VV lim ≤0(5)

[0250] In the formula, V is the shear capacity of the section, V lim This refers to the limit value of the shear capacity of the cross section;

[0251] The mathematical model for constraints under normal serviceability limit states includes, but is not limited to: constraints that the component deflection does not exceed the deflection limit and constraints that the crack width does not exceed the crack width limit;

[0252] The component deflection shall not exceed the deflection limit constraint as follows:

[0253] δ-δ lim ≤0(6)

[0254] In the formula, δ is the deflection of the component, δ lim The deflection limit of the component;

[0255] The requirement that the crack width does not exceed the crack width limit is as follows:

[0256] w cr -w crlim ≤0(7)

[0257] In the formula, w cr w is the crack width. crlim This is the limit for crack width;

[0258] Geometric constraint mathematical models include, but are not limited to: the flange width-to-thickness ratio of steel structure members does not exceed the limit constraint, and the web height-to-thickness ratio of steel structure members does not exceed the limit constraint.

[0259] The width-to-thickness ratio of the flange of the steel structure member shall not exceed the following limit constraint:

[0260] B f / t f ≤rf lim (8)

[0261] In the formula, B f t is the flange width parameter for steel structural members. f For the flange thickness of the steel structure component, rf lim This refers to the limit value for the width-to-thickness ratio of the flange of a steel structure component.

[0262] The web height-to-thickness ratio of the steel structure member shall not exceed the following limit constraint:

[0263] hw / t w ≤=rw lim (9)

[0264] wherein, h w is the web height of the steel structural member, t w is the web thickness of the steel structural member, rw lim is the web height-to-thickness ratio limit of the steel structural member.

[0265] Embodiment 11:

[0266] A human-computer collaborative intelligent modeling and optimization method for half-through steel arch bridges, the technical content of which is the same as any one of embodiments 2-10, further, the algorithm for solving the structural parameter optimization model of the half-through steel arch bridge includes but is not limited to: genetic algorithm, particle swarm algorithm, differential evolution algorithm; the optimization algorithm adopts a parameter self-adaptive adjustment strategy to optimize the population quality when generating individuals, so as to avoid generating invalid individuals;

[0267] When adjusting the section parameters of the arch rib, the self-adaptive adjustment strategy includes the following steps:

[0268] a) Fix the flange width of the arch rib section, and determine whether the flange width-to-thickness ratio of the steel structural member exceeds the limit value, if yes, automatically update to the minimum flange thickness that satisfies the flange width-to-thickness ratio limit constraint of the steel structural member, if not, do not change the flange thickness;

[0269] b) Determine the web height of the arch rib section according to the section height and flange thickness of the arch rib, and determine whether the web height-to-thickness ratio of the steel structural member exceeds the limit value, if yes, automatically update to the minimum web thickness that satisfies the web height-to-thickness ratio limit constraint of the steel structural member, if not, do not change the web thickness;

[0270] c) The adjustment sequence of the arch rib section is from the arch top section to the arch bottom section;

[0271] When the flange thickness of the section near the arch bottom side is less than the flange thickness of the section adjacent to the arch top side, the flange thickness of the section is automatically updated to the flange thickness of the section adjacent to the arch top side;

[0272] When the web thickness of the section near the arch bottom side is less than the web thickness of the section adjacent to the arch top side, the web thickness of the section is automatically updated to the web thickness of the section adjacent to the arch top side;

[0273] When adjusting the upper flange width section parameters of the bridge deck system steel beam, the self-adaptive adjustment strategy includes the following steps:

[0274] I) Fix the flange width of the steel beam section, and determine whether the flange width-to-thickness ratio of the steel structural member exceeds the limit value, if yes, automatically update to the minimum flange thickness that satisfies the flange width-to-thickness ratio limit constraint of the steel structural member, if not, do not change the flange thickness;

[0275] II) determining the steel beam section web height according to the steel beam section height and the flange thickness, and judging whether the steel structure member web height-thickness ratio exceeds the limit value, if yes, automatically updating to the minimum web thickness meeting the constraint that the steel structure member web height-thickness ratio does not exceed the limit value, if not, not changing the web thickness.

[0276] Embodiment 12:

[0277] A man-machine collaborative intelligent modeling and optimization method for half-through steel arch bridges, comprising the following steps:

[0278] 1) determining the structure system, span, rise-span ratio, arch axis shape, support form, steel-concrete composite deck section, etc. of the half-through steel arch bridge, and drawing an initial condition diagram.

[0279] 2) establishing a half-through steel arch bridge structure intelligent design model based on man-machine collaboration.

[0280] 3) based on the half-through steel arch bridge structure intelligent design model, establishing a half-through steel arch bridge structure parameter optimization model.

[0281] 4) solving the half-through steel arch bridge structure parameter optimization model to obtain the optimized parameters of each half-through steel arch bridge structure.

[0282] The initial condition diagram of step 1) includes the initial condition elevation diagram of the half-through steel arch bridge, the initial condition plan diagram of the half-through steel arch bridge, and the initial condition section diagram of the steel-concrete composite deck system.

[0283] The initial condition diagram of step 1) records information such as arch axis center line elevation positioning, arch rib plane positioning, support plane positioning, bridge deck elevation, and steel-concrete composite deck system section arrangement.

[0284] Step 2) the step of establishing a half-through steel arch bridge intelligent design model based on man-machine collaboration comprises:

[0285] 2.1) reading key component information in the initial condition diagram DXF vector graphics file using layer analysis algorithm.

[0286] 2.2) based on spatial information reasoning, automatically generating each component and connection unit of the half-through steel arch bridge using the read initial design information.

[0287] 2.3) automatically defining constraints.

[0288] 2.4) automatically arranging loads, including but not limited to the self-weight of various components, the self-weight of asphalt pavement, the self-weight of railings, and lane loads.

[0289] 2.5) outputting the half-through steel arch bridge intelligent design model.

[0290] Step 2.1) includes the following sub-steps:

[0291] 2.1.1) Mark the support and the inner side line of the arch rib in the initial condition plan of the bridge.

[0292] 2.1.2) Mark the center line of the arch axis and the top line of the deck slab in the initial condition elevation of the bridge.

[0293] 2.1.3) Mark the web of the steel girder in the section drawing of the steel-concrete composite bridge deck system of the bridge.

[0294] 2.1.4) Read the curve information of various types by using the layer analysis algorithm, determine the elevation coordinates of the arch crown and the arch abutment, the plan coordinates of the support and the inner side line of the arch rib, the elevation information of the top of the deck slab, and the coordinate information of the web of the steel girder in the section drawing of the steel-concrete composite bridge deck system.

[0295] Step 2.2) includes the following sub-steps:

[0296] 2.2.1) Determine the section form, preliminary geometric dimensions, and material information of the arch rib, the support, the inter-arch beam, the steel-concrete composite bridge deck system, and the suspender, determine the support information, the arch axis coefficient, etc.

[0297] 2.2.2) Based on spatial information reasoning, determine the size and start-stop coordinates of each component in combination with the initial design information reading results of step 2.1.3) and the geometric information in step 2.2.1).

[0298] 2.2.3) Develop unit division criteria, determine the number of units of each component, and automatically perform node numbering in the order of the arch rib, the inter-arch beam, the support, the steel girder, the steel beam, the deck slab, and the support.

[0299] 2.2.4) Combine the node numbering of the arch rib, the inter-arch beam, the support, the steel girder, the steel beam, the deck slab, and the support, perform unit numbering of the arch rib, the inter-arch beam, the support, the steel girder, the steel beam, the deck slab, the support, the suspender, and the steel girder-deck slab connection unit, and record the start-stop nodes of each unit.

[0300] 2.2.5) Define the fiber section of each component unit.

[0301] 2.2.6) Define the category of each component unit, combine the information of steps 2.2.2)-2.2.5), and generate the components and connection units of the half-through steel arch bridge.

[0302] Step 2.2.5) includes the following steps:

[0303] 2.2.5.1) Develop section fiber division criteria.

[0304] 2.2.5.2) Define the constitutive relationship of various types of materials, establish a material library and a constitutive relationship library.

[0305] 2.2.5.3) According to the cross-section shape and geometric size information of each component unit, the cross-section profile is automatically generated, the fiber cross-section is divided, and the material index and constitutive relation are read according to the material information.

[0306] Step 2.3) includes the following sub-steps:

[0307] 2.3.1) Extract the nodes at the bottom of the abutment and the bridge deck system end support, and define the boundary conditions.

[0308] 2.3.2) Based on prior knowledge, develop bridge deck system support arrangement criteria and establish support performance index library.

[0309] 2.3.3) Extract the nodes at the bottom of the inter-arch beam and the bridge deck system end support, and the corresponding positions of the bridge deck system steel longitudinal beam, and automatically generate the abutment units at the top of the inter-arch beam and the two ends of the bridge deck system.

[0310] 2.3.4) Write the boundary conditions and abutment unit information into a file, thereby realizing the automatic definition of various constraints.

[0311] Step 2.4) includes the following sub-steps:

[0312] 2.4.1) The self-weight of various components, the self-weight of asphalt pavement and the self-weight of railings are applied in the form of uniform line load, and the line load intensity g L which is calculated by the material density of the component, and the calculation formula is as follows:

[0313] g L = A x p (1)

[0314] In the formula, A is the cross-sectional area, and p is the material density.

[0315] 2.4.2) The lane load is calculated based on the read information of the half-through steel arch bridge according to the requirements of the specification, and is applied in the form of uniform load and concentrated load.

[0316] Step 3) includes the following sub-steps:

[0317] 3.1) Select the variables to be optimized for various components and determine the value range of the decision variables.

[0318] 3.2) Establish the constraint mathematical model, including the constraints under the ultimate limit state of bearing capacity, the constraints under the normal use limit state, and the geometric constraints.

[0319] 3.3) Establish the objective function with material cost as the optimization target, that is:

[0320]

[0321] Where, i is the component material number; i = 1, 2, 3…, n; n is the total number of component materials; A i is the component material cross-sectional area; L i is the component material length; P i is the component material unit price.

[0322] 3.4) Establish a pseudo-objective function F based on the external penalty method, as follows:

[0323]

[0324] Where, j is the number of constraints under the bearing capacity limit state and the serviceability limit state; j = 1, 2, 3…, m; m is the total number of constraints under the bearing capacity limit state and the serviceability limit state; C j is the penalty function of the jth constraint, which is 0 when the constraint is not violated, and is a predetermined penalty value when the constraint is violated.

[0325] The optimization variables involved in step 3.1) include but are not limited to: the cross-sectional height of the arch rib at the arch bottom and the width-height ratio, the height ratio of the cross-section at the arch top to the cross-section at the arch bottom, the thickness of the arch rib flange and web, the thickness of the bridge deck and the concrete strength, the height of the bridge deck system steel beam, the width and thickness of the bridge deck system steel beam flange, and the thickness of the bridge deck system steel beam web.

[0326] The total number of arch rib optimization variables is determined according to the product of the number of individual cross-section optimization variables and the number of different cross-section sizes.

[0327] The mathematical model of the constraints under the bearing capacity limit state involved in step 3.2) includes but is not limited to: the constraint that the cross-sectional flexural capacity does not exceed the cross-sectional flexural capacity limit value, and the constraint that the cross-sectional shear capacity does not exceed the cross-sectional shear capacity limit value.

[0328] The constraint that the cross-sectional flexural capacity does not exceed the cross-sectional flexural capacity limit value is as follows:

[0329] M-M lim ≤0(4)

[0330] Where, M is the cross-sectional flexural capacity, M lim is the cross-sectional flexural capacity limit value.

[0331] The constraint that the cross-sectional shear capacity does not exceed the cross-sectional shear capacity limit value is as follows:

[0332] V-V lim ≤0(5)

[0333] Where, V is the cross-sectional shear capacity, V lim is the cross-sectional shear capacity limit value.

[0334] The constraints of the mathematical model involved in step 3.2) in the normal use limit state include, but are not limited to: a member deflection constraint that the member deflection does not exceed a deflection limit value constraint, a crack width constraint that the crack width does not exceed a crack width limit value constraint.

[0335] The member deflection constraint that the member deflection does not exceed a deflection limit value constraint is described as follows:

[0336] δ - δ lim ≤ 0 (6)

[0337] In the formula, δ is the member deflection, δ lim is the member deflection limit value.

[0338] The crack width constraint that the crack width does not exceed a crack width limit value constraint is described as follows:

[0339] w cr -w crlim ≤ 0 (7)

[0340] In the formula, w cr is the crack width, w crlim is the crack width limit value.

[0341] The geometric constraint mathematical model involved in step 3.2) includes, but is not limited to: a steel structure member flange width-thickness ratio constraint that the steel structure member flange width-thickness ratio does not exceed a limit value constraint, a steel structure member web height-thickness ratio constraint that the steel structure member web height-thickness ratio does not exceed a limit value constraint.

[0342] The steel structure member flange width-thickness ratio constraint that the steel structure member flange width-thickness ratio does not exceed a limit value constraint is described as follows:

[0343] B f / t f ≤ rf lim (8)

[0344] In the formula, B f is a steel structure member flange width parameter, t f is a steel structure member flange thickness, and rf lim is a steel structure member flange width-thickness ratio limit value.

[0345] The steel structure member web height-thickness ratio constraint that the steel structure member web height-thickness ratio does not exceed a limit value constraint is described as follows:

[0346] h w / t w ≤ rw lim (9)

[0347] In the formula, h w is a steel structure member web height, t w is a steel structure member web thickness, and rw lim is a steel structure member web height-thickness ratio limit value.

[0348] The algorithm involved in the calculation of the structural parameter optimization model of the half-through steel arch bridge in step 4 includes but is not limited to genetic algorithm, particle swarm algorithm and differential evolution algorithm.

[0349] The optimization algorithm adopts a parameter self-adaptive adjustment strategy to optimize the population quality when generating individuals, thereby avoiding generating invalid individuals.

[0350] The arch rib section parameter self-adaptive adjustment strategy includes the following steps:

[0351] a) Fix the arch rib section flange width, judge according to the flange width-thickness ratio constraint of the steel structure member, if the requirement is met, do not change the flange thickness, if not, automatically update to the minimum flange thickness that meets the flange width-thickness ratio constraint of the steel structure member.

[0352] b) Determine the arch rib section web height according to the section height and flange thickness, judge according to the web height-thickness ratio constraint of the steel structure member, if the requirement is met, do not change the web thickness, if not, automatically update to the minimum web thickness that meets the web height-thickness ratio constraint of the steel structure member.

[0353] c) The adjustment sequence of the arch rib section is from the arch top section to the arch bottom section. When the flange thickness of the section close to the arch bottom side is less than the flange thickness of the section close to the arch top side, the flange thickness is automatically updated to the flange thickness of the section close to the arch top side; when the web thickness of the section close to the arch bottom side is less than the web thickness of the section close to the arch top side, the web thickness is automatically updated to the web thickness of the section close to the arch top side.

[0354] The bridge system steel beam upper flange width section parameter self-adaptive adjustment strategy includes the following steps:

[0355] a) Fix the steel beam section flange width, judge according to the flange width-thickness ratio constraint of the steel structure member, if the requirement is met, do not change the flange thickness, if not, automatically update to the minimum flange thickness that meets the flange width-thickness ratio constraint of the steel structure member.

[0356] b) Determine the steel beam section web height according to the section height and flange thickness, judge according to the web height-thickness ratio constraint of the steel structure member, if the requirement is met, do not change the web thickness, if not, automatically update to the minimum web thickness that meets the web height-thickness ratio constraint of the steel structure member.

[0357] Embodiment 13:

[0358] Referring to Figures 1 to 7 A half-through steel arch bridge human-computer collaborative intelligent modeling and optimization method, including the following steps:

[0359] 1) Determine the structural system, span, rise-span ratio, arch axis shape, support form, steel-concrete composite bridge deck section, etc. according to the function of use, natural conditions and prior knowledge, and draw the initial condition diagram.

[0360] 2) Mark the arch rib inner side line plane and support plane in the initial condition plan of the half-through steel arch bridge.

[0361] 3) Mark the bearing top, arch axis center line and bridge deck top line in the initial condition elevation of the bridge.

[0362] 4) Mark the steel longitudinal beam web line in the initial condition section of the steel-concrete composite bridge deck.

[0363] 5) Read the key component information in the DXF vector graphics file of the initial condition diagram using layer analysis algorithm, determine the arch axis center line arch top and arch stand elevation coordinates, support and arch rib inner side edge plane coordinates, bridge deck top elevation information, and steel-concrete composite bridge deck section steel longitudinal beam web coordinate information.

[0364] 6) Determine the section form, preliminary geometric dimensions and material information of the arch rib, support, inter-arch beam, steel-concrete composite bridge deck and suspender, determine the bearing information, arch axis coefficient, etc.

[0365] 7) Combine the size information of step 6) and the key information reading results of step 5) to perform spatial information reasoning, the size and start-stop coordinates of each component.

[0366] 8) Develop unit division criteria, determine the number of units of each component, and automatically perform node numbering in the order of arch rib, inter-arch beam, support, steel longitudinal beam, steel cross beam, bridge deck, and bearing.

[0367] 9) Combine the node numbering of arch rib, inter-arch beam, support, steel longitudinal beam, steel cross beam, bridge deck, and bearing, and perform unit numbering of arch rib, inter-arch beam, support, steel longitudinal beam, steel cross beam, bridge deck, bearing, suspender, and steel longitudinal beam-bridge deck connection unit, and record the start-stop nodes of each unit.

[0368] 10) Define the fiber section of each component unit.

[0369] 11) Define the category of each component unit, combine the information of steps 7)-10), and generate the components and connection units of the half-through steel arch bridge.

[0370] 12) Write the node and unit numbering and section information into a file, thereby realizing the automatic generation of each component.

[0371] 13) Extract the nodes at the bottom of the arch stand and bridge deck system, and define the boundary conditions.

[0372] 14) Based on prior knowledge, make bridge deck support arrangement guidelines, and establish support performance index library.

[0373] 15) Extract the nodes at the bottom of the support at the top of the bent cap and abutment, and the nodes at the corresponding positions of the steel main beam, and automatically generate the support units at the top of the bent cap and abutment.

[0374] 16) Write the boundary conditions and support unit information into a file to realize the automatic definition of various constraints.

[0375] 17) The self-weight of various components, the self-weight of asphalt pavement, and the self-weight of railings are applied as uniformly distributed line loads, and the line load intensity g L which is calculated by the material density of the component, and the calculation formula is as follows:

[0376] g L = A x p (1)

[0377] In the formula, A is the cross-sectional area, and p is the material density.

[0378] 18) The lane load is calculated based on the read information of the half-through steel arch bridge according to the requirements of the specification, and is applied as uniformly distributed load and concentrated load.

[0379] 19) Select the variables to be optimized for various components and determine the value range of the decision variables.

[0380] 20) Establish a constraint mathematical model, including constraints under the ultimate limit state of bearing capacity, constraints under the serviceability limit state, and geometric constraints.

[0381] 21) Establish the objective function of material cost optimization, that is:

[0382]

[0383] In the formula, i is the component material number, i = 1, 2, 3…, n, n is the total number of component materials, A i is the cross-sectional area of the component material, L i is the length of the component material, and P i is the unit price of the component material.

[0384] 22) Establish a pseudo-objective function F based on the external penalty method, as follows:

[0385]

[0386] In the formula, j is the number of constraints under the ultimate limit state of bearing capacity and the serviceability limit state; j = 1, 2, 3…, m; m is the total number of constraints under the ultimate limit state of bearing capacity and the serviceability limit state; C j is the penalty function of the jth constraint, which is 0 when the constraint is not violated, and is a predetermined penalty value when the constraint is violated.

[0387] 23) Using optimization algorithm to solve the optimization variables, and get the optimization parameters of each component.

Claims

1. A human-computer collaborative intelligent modeling and optimization method for a half-through steel arch bridge, characterized in that, The method comprises the following steps: 1) determining the structure system, span, rise-span ratio, arch axis shape, support form and steel-concrete composite bridge deck section of the half-through steel arch bridge, and drawing an initial condition diagram; 2) establishing a half-through steel arch bridge structure intelligent design model based on human-computer collaboration based on the initial condition diagram; 3) establishing a half-through steel arch bridge structure parameter optimization model based on the half-through steel arch bridge structure intelligent design model; 4) solving the half-through steel arch bridge structure parameter optimization model to obtain the optimized parameters of each half-through steel arch bridge structure.

2. The man-machine collaborative intelligent modeling and optimization method for a half-through steel arch bridge according to claim 1, characterized in that, The initial condition diagram comprises a half-through steel arch bridge initial condition elevation diagram, a half-through steel arch bridge initial condition plan diagram and a steel-concrete composite bridge deck section initial condition diagram; The initial condition diagram records the arch axis center line elevation positioning, arch rib plane positioning, support plane positioning, bridge deck elevation and steel-concrete composite bridge deck section arrangement.

3. The man-machine collaborative intelligent modeling and optimization method for a half-through steel arch bridge according to claim 1, characterized in that, In step 2), the step of establishing the half-through steel arch bridge intelligent design model based on human-computer collaboration comprises: 2.1) reading key component information in the initial condition diagram by using a layer analysis algorithm; The key component information comprises arch axis center line crown and abutment elevation coordinates, support and arch rib inner side line plane coordinates, bridge deck slab top elevation information and steel longitudinal beam web coordinate information in the steel-concrete composite bridge deck section diagram; 2.2) automatically generating each component and connection unit of the half-through steel arch bridge by using the read key component information based on spatial information reasoning; 2.3) automatically defining constraints; 2.4) automatically arranging loads, including but not limited to the self-weight of each component of the half-through steel arch bridge, the self-weight of asphalt pavement, the self-weight of railings and lane loads; 2.5) outputting the half-through steel arch bridge intelligent design model.

4. The man-machine collaborative intelligent modeling and optimization method for a half-through steel arch bridge according to claim 3, characterized in that, In step 2.1), the step of reading key component information in the initial condition diagram by using a layer analysis algorithm comprises: 2.1.1) marking the support and arch rib inner side line of the initial condition plan diagram of the bridge; 2.1.2) marking the arch axis center line and bridge deck slab top line of the initial condition elevation diagram of the bridge; 2.1.3) marking the steel longitudinal beam web of the steel-concrete composite bridge deck section diagram of the bridge; 2.1.4) reading various curve information by using a layer analysis algorithm to determine the arch axis center line crown and abutment elevation coordinates, support and arch rib inner side line plane coordinates, bridge deck slab top elevation information and steel longitudinal beam web coordinate information in the steel-concrete composite bridge deck section diagram.

5. The man-machine collaborative intelligent modeling and optimization method for a half-through steel arch bridge according to claim 4, characterized in that, In step 2.2), the step of generating each component and connection unit of the half-through steel arch bridge comprises: 2.2.1) determining the section form, preliminary geometric dimensions and material information of the arch rib, support, inter-arch beam, steel-concrete composite bridge deck and suspender, determining support information and arch axis coefficient; 2.2.2) determining the size and start-stop coordinates of each component based on spatial information reasoning and combining the key component information, preliminary geometric dimensions of the arch rib, support, inter-arch beam, steel-concrete composite bridge deck and suspender; The components comprise the arch rib, inter-arch beam, support, steel longitudinal beam, steel cross beam, bridge deck slab and support; 2.2.3) formulating unit division criteria according to the component unit size, determining the number of each component unit, and automatically numbering the nodes of these components in the order of the arch rib, inter-arch beam, support, steel longitudinal beam, steel cross beam, bridge deck slab and support; 2.2.4) Numbering of arch ribs, inter-arch transverse beams, supports, steel girders, steel cross beams, bridge decks, and support nodes, numbering of arch ribs, inter-arch transverse beams, supports, steel girders, steel cross beams, bridge decks, supports, hangers, and steel girder-bridge deck connection units, and recording the start and end nodes of each connection unit; 2.2.5) Defining the fiber section of each component unit, the steps including: 2.2.5.1) According to the size of the component unit in the thickness, width, and height directions, the section fiber division criteria are formulated; 2.2.5.2) Defining the constitutive relationship of each type of material, establishing a material library and a constitutive relationship library; 2.2.5.3) Automatically generating a section profile according to the section shape and geometric size information of each component unit, dividing the fiber section, and reading the material index and constitutive relationship according to the material information; 2.2.6) Defining the category of each component unit, generating the components and connection units of the half-through steel arch bridge.

6. The man-machine collaborative intelligent modeling and optimization method for a half-through steel arch bridge according to claim 3, characterized in that, In step 2.3), the step of automatically defining constraints includes: 2.3.1) Extracting the nodes at the bottom of the arch supports and the end supports of the bridge deck system to define boundary conditions; 2.3.2) Based on prior knowledge, formulating the support arrangement criteria of the bridge deck system, and establishing a support performance index library; 2.3.3) Extracting the nodes at the bottom of the inter-arch transverse beams and the end supports of the bridge deck system, and the corresponding positions of the steel girders of the bridge deck system, and automatically generating the top of the inter-arch transverse beams and the end supports of the bridge deck system; 2.3.4) Writing the boundary conditions and support unit information into a file, thereby realizing the automatic definition of the boundary conditions and support units at the bottom of the arch supports and the end supports of the bridge deck system.

7. The man-machine collaborative intelligent modeling and optimization method for half-through steel arch bridges of claim 3, characterized in that, In step 2.4), the step of automatically arranging loads includes: 2.4.1) The self-weight of each type of component, the self-weight of asphalt pavement, and the self-weight of railings are applied in the form of uniformly distributed line loads; wherein the line load intensity g L As shown below: g L = A x p (1) where A is the cross-sectional area and ρ is the material density; 2.4.2) The lane load is calculated based on the read information of the half-through steel arch bridge according to the requirements of the "General Code for Design of Highway Bridges and Culverts", and is applied in the form of uniformly distributed loads and concentrated loads.

8. The human-machine collaborative intelligent modeling and optimization method for a half-through steel arch bridge according to claim 1, characterized in that, In step 3), the steps of establishing a structural parameter optimization model for a half-through steel arch bridge include: 3.1) Selecting the variables to be optimized for each type of component, and determining the value range of the decision variables; The variables to be optimized include but are not limited to: the height of the arch rib at the arch bottom, the width-height ratio of the arch rib, the height ratio of the arch rib at the arch top to the arch bottom, the thickness of the arch rib flange and web, the thickness of the bridge deck and the concrete strength, the height of the steel beam of the bridge deck system, the width and thickness of the flange of the steel beam of the bridge deck system, and the thickness of the web of the steel beam of the bridge deck system; 3.2) Establishing the constraint mathematical model of the structural parameter optimization model of the half-through steel arch bridge, including the constraints under the ultimate limit state of bearing capacity, the constraints under the normal use limit state, and the geometric constraint mathematical model; 3.3) Establishing the objective function with material cost as the optimization objective, i.e.: Wherein, i is the component material number; i = 1, 2, 3…, n; n is the total number of component materials; A i is the cross-sectional area of the component material; L i is the length of the component material; P i is the unit price of the component material. 3.4) Establishing a pseudo-objective function F based on the external penalty method, taking the pseudo-objective function F as the objective function of the structural parameter optimization model of the half-through steel arch bridge; The pseudo-objective function F is as follows: where j is the number of constraints at the ultimate limit state of load bearing capacity and at the ultimate limit state of normal use; j = 1, 2, 3…, m; m is the total number of constraints at the ultimate limit state of load bearing capacity and at the ultimate limit state of normal use; C j is the penalty function of the jth constraint, which is 0 when the constraint is not violated and is a predetermined penalty value when the constraint is violated.

9. The human-machine collaborative intelligent modeling and optimization method for a half-through steel arch bridge according to claim 8, characterized in that, The constraint mathematical model under the ultimate limit state of bearing capacity includes but is not limited to: the constraint that the sectional flexural bearing capacity does not exceed the sectional flexural bearing capacity limit value, and the constraint that the sectional shear bearing capacity does not exceed the sectional shear bearing capacity limit value. The cross-section bending resistance capacity does not exceed the cross-section bending resistance capacity limit value constraint as follows: M-M lim ≤0 (4) In the formula, M is the cross-sectional flexural bearing capacity, M lim is the cross-sectional flexural bearing capacity limit value; The cross-section shear resistance ratio does not exceed the cross-section shear resistance limit value constraint as follows: V-V lim ≤0 (5) where V is the shear capacity of the cross-section, V lim is the shear capacity limit of the cross-section; The constraint mathematical model under the normal use limit state includes but is not limited to: the member deflection does not exceed the deflection limit value constraint, the crack width does not exceed the crack width limit value constraint. The member deflection does not exceed the deflection limit value constraint is as follows: delta-delta lim ≤ 0 (6) where δ is the deflection of the member, δ lim is the deflection limit of the member; The crack width does not exceed the crack width limit value constraint is as follows: w cr -w crlim ≤0 (7) where w cr is the crack width, w crlim is the crack width limit; The geometric constraint mathematical model includes but is not limited to: the flange width-thickness ratio of the steel structure member does not exceed the limit value constraint, the web height-thickness ratio of the steel structure member does not exceed the limit value constraint. The flange width-thickness ratio of the steel structure member does not exceed the limit value constraint is as follows: B f / t f ≤rf lim (8) In the formula, B f is the flange width parameter of the steel structural member, t f is the flange thickness of the steel structural member, rf lim is the flange width-thickness ratio limit value of the steel structural member. The web height-thickness ratio of the steel structure member does not exceed the limit value constraint is as follows: h w / t w ≤=rw lim (9) wherein h w is the web height of the steel structural member, t w is the web thickness of the steel structural member, rw lim is the web height-to-thickness ratio limit of the steel structural member.

10. The man-machine collaborative intelligent modeling and optimization method for half-through steel arch bridges according to claim 1, characterized in that, The algorithm for solving the structural parameter optimization model of the half-through steel arch bridge includes but is not limited to: genetic algorithm, particle swarm algorithm, differential evolution algorithm; The optimization algorithm generates individuals using a parameter adaptive adjustment strategy to optimize the population quality and avoid generating invalid individuals; When adjusting the arch rib cross-section parameters, the adaptive adjustment strategy includes the following steps: a) Fix the flange width of the arch rib cross-section, and determine whether the flange width-thickness ratio of the steel structure member exceeds the limit value. If yes, automatically update to the minimum flange thickness that satisfies the flange width-thickness ratio limit value constraint of the steel structure member; if no, do not change the flange thickness; b) Determine the web height of the arch rib cross-section according to the height and flange thickness of the arch rib cross-section, and determine whether the web height-thickness ratio of the steel structure member exceeds the limit value. If yes, automatically update to the minimum web thickness that satisfies the web height-thickness ratio limit value constraint of the steel structure member; if no, do not change the web thickness; c) The adjustment sequence of the arch rib cross-section is from the arch top cross-section to the arch bottom cross-section; When the flange thickness of the cross-section near the arch bottom side is less than the flange thickness of the adjacent cross-section near the arch top side, the flange thickness of the cross-section is automatically updated to the flange thickness of the adjacent cross-section near the arch top side; When the web thickness of the cross-section near the arch bottom side is less than the web thickness of the adjacent cross-section near the arch top side, the web thickness of the cross-section is automatically updated to the web thickness of the adjacent cross-section near the arch top side; When adjusting the upper flange width cross-section parameters of the bridge system steel beam, the adaptive adjustment strategy includes the following steps: I) Fix the flange width of the steel beam cross-section, and determine whether the flange width-thickness ratio of the steel structure member exceeds the limit value. If yes, automatically update to the minimum flange thickness that satisfies the flange width-thickness ratio limit value constraint of the steel structure member; if no, do not change the flange thickness; II) Determine the web height of the steel beam cross-section according to the height and flange thickness of the steel beam cross-section, and determine whether the web height-thickness ratio of the steel structure member exceeds the limit value. If yes, automatically update to the minimum web thickness that satisfies the web height-thickness ratio limit value constraint of the steel structure member; if no, do not change the web thickness.

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