Method for determining a connector layout for a construction assembly

Abstract

Disclosed is a computer-implemented method for determining a connector layout of a construction assembly. The method may comprise determining a set of fastener and base plate layout combinations based on a first set of predefined parameters for determining the connector layout. The method may comprise evaluating the set of fastener and base plate layout combinations to obtain a set of connector layout solutions. The method may comprise ranking the set of connector layout solutions based on a second set of predefined parameters for determining the connector layout. In addition, a method for manufacturing a construction assembly is disclosed.

Description

[0001] METHOD FOR DETERMINING A CONNECTOR LAYOUT FOR A CONSTRUCTION ASSEMBLY

[0002] TECHNICAL FIELD

[0003] The present disclosure generally relates to the field of connector layouts, and more particularly to techniques for determining connector layouts of construction assemblies.

[0004] BACKGROUND

[0005] A use of connector layouts is mounting a construction assembly to a construction foundation. Determining optimal connector layouts for construction assemblies have a major practical importance in civil engineering. This is because the safety of a construction assembly mainly depends on connector layouts being constructed in a way that the construction assembly is stable with respect to physical forces acting on the construction assembly.

[0006] However, finding an optimal connector layout is a cumbersome endeavor for several reasons. One reason is that construction assemblies come with a variety of elements and geometries. Furthermore, boundary conditions of connector layouts for different construction assemblies vary strongly making standardized approaches for determining optimal connector layouts inefficient. A further reason is that a large variety of different fastener types are available and that finding an optimal connector layout does not merely require finding the positioning of fasteners but also the amount of required fasteners and the corresponding fastener types required. In addition, these factors may mutually affect each other making the problem of finding an optimal connector layout a difficult and complex problem to be solved.

[0007] It is therefore an objective of the present disclosure to provide a method for determining an connector layout of a construction assembly, thereby overcoming the above-mentioned disadvantages of the prior art at least in part. SUMMARY OF THE DISCLOSURE

[0008] The objective is solved by the subject-matter defined in the independent claims. Advantageous modifications of embodiments of the present disclosure are defined in the dependent claims as well as in the description and the figures.

[0009] As a general overview, certain aspects of the present disclosure provide for an efficient way of determining an connector layout of a construction assembly. The connector layout determined this way may allow to manufacture a safe and stable construction assembly satisfying the individual requirements of construction projects. Thus, a new method is provided which is not only able to cope with varying construction conditions but is also able to provide optimal connector layouts for construction assemblies.

[0010] One aspect of the present disclosure relates to a computer-implemented method for determining an connector layout of a construction assembly. The method may comprise determining a set of fastener and base plate layout combinations based on a first set of predefined parameters for determining the connector layout. The method may comprise evaluating the set of fastener and base plate layout combinations to obtain a set of connector layout solutions. The method may comprise ranking the set of connector layout solutions based on a second set of predefined parameters for determining the connector layout.

[0011] This way, a method is provided which is able to solve the complex problem of determining an optimal connector layout of a construction assembly. The connector layout provided may be used to manufacture the construction assembly in safe and stable manner.

[0012] According to another aspect of the present disclosure, evaluating may comprise performing a feasibility test verifying if a fastener and base plate layout combination is in accordance with the first set of predefined parameters. Evaluating may further comprise, if the fastener and base plate layout combination is verified, optimizing the fastener and base plate layout combination based at least in part on a layout type of the layout to obtain an connector layout solution.

[0013] This way, only feasible fastener and base plate layout combinations are used as a starting point for the optimizing. As a result, efficiency of the optimizing is improved. For example, an optimization starting from a suitable starting point (i.e., a feasible fastener and base plate layout combination) may converge faster compared to when starting from an infeasible starting point. Due to the faster convergence, less computational resources are required. Furthermore, the quality of the result of the optimization is improved because chances of finding a better solution (e.g., a lower local minimum compared to when starting from an infeasible starting point) are higher. As a result, the obtained connector layout solution when starting the optimizing from a feasible starting point will best match the given requirements for manufacturing the construction assembly (e.g., as defined by the first set of predefined parameters).

[0014] According to another aspect of the present disclosure, performing the feasibility test may comprise determining whether a first layout for the given fastener and base plate layout combination is feasible. The first layout may comprise a largest possible base plate, a largest possible embedment depth, anchors being placed as close as possible to edges of the base plate or any combination thereof.

[0015] This way, it can be efficiently determined whether the given fastener and base plate layout combination is feasible. This is because the first layout represents a best-case layout (i.e., largest possible base plate / embedment depth, anchors positioned close to the edges etc.) which if determined as infeasible makes further optimization (e.g., trying to obtain a smaller base plate size) unnecessary. As a result, computational resources required for determining the connector layout solution are efficiently utilized.

[0016] According to another aspect of the present disclosure optimizing the fastener and base plate layout combination may comprise determining that the layout type of the layout is a centered layout type without concrete edges and / or performing a pattern search optimization for the fastener and base plate layout combination. Additionally or alternatively, optimizing may comprise determining that the layout type of the layout is a non-centered layout type and / or a layout type with concrete edges, and / or performing a nonlinear optimization for the fastener and base plate layout combination.

[0017] This way, computational resource usage is further improved. This is because adapting the optimizing approach (i.e., either pattern search or non-linear) to the layout type was found to positively affect the computational duration required for determining the connector layout solution. In addition, the adapting of the optimizing approach yields better results in terms of anchor solutions compared to using a static approach in which the optimizing is always performed in the same manner. For example, for center layout types without concrete edges it was found that pattern search optimization is able to yield optimal solutions while requiring less computational duration compared to the non-linear optimization. For example, for non-centered layout types and / or layout types with concrete edges, a non-linear optimization algorithm is able to yield better results compared to the pattern search optimization.

[0018] According to another aspect of the present disclosure, the pattern search optimization may be based on: an indication for a pattern search approach of a plurality of pattern search approaches and / or a set of parameters dedicated for the indicated pattern search approach. The plurality of pattern search approaches may comprise a simple grid, a simple grid with area sorting, bracketing, isoline grid and / or isoline grid with profile integration.

[0019] This way, different approaches for the pattern search optimization can be utilized individually or even in combination to determine the best possible connector layout solution.

[0020] According to another aspect of the present disclosure, the non-linear optimization may be an Interior Point Optimizer, IPOPT.

[0021] According to another aspect of the present disclosure, a vector of optimization variables for the IPOPT may comprises one or more of: a set of 2-dimensional coordinates for anchor points; a size of the base plate, preferably a rectangular base plate, a 2- dimensional eccentricity of a profile of the layout and / or a anchor embedment depth.

[0022] The IPOPT is able to yield optimal connector layout solutions even for more complex cases such as non-centered layout types.

[0023] According to another aspect of the present disclosure, a fastener and base plate layout combination may comprise a fastener type and a layout type. A corresponding anchor solution may comprise an amount of required fasteners of the fastener type and / or a position of each fastener on the layout and / or a base plate size and / or an embedment depth.

[0024] This way, an connector layout solution is provided which comprises the optimal number and / or the optimal type(s) of fasteners with optimal positioning on a base plate of optimal size such that at least the first set of predefined parameters is satisfied.

[0025] According to another aspect of the present disclosure, the first set of predefined parameters may define boundary conditions for determining the set of fastener and base plate layout combinations. According to another aspect of the present disclosure, the second set of predefined parameters defines weighting criteria for ranking the set of connector layout solutions.

[0026] According to another aspect of the present disclosure, the method may further comprise obtaining the first set of predefined parameters and / or the second set of predefined parameters from a request. The request may comprise the first set of predefined parameters and / or the second set of predefined parameters. The request may comprise an indication of the first set of predefined parameters and / or the second set of predefined parameters.

[0027] This way, the determining of the connector layout solution can be implemented in a flexible and dynamic manner wherein a request (e.g., a HTTPs request) is received. This means that the first set of predefined parameters does not have to be statically defined but instead can be dynamically provided which allows to dynamically determine connector layout solutions for different construction projects.

[0028] According to another aspect of the present disclosure, the first set of predefined parameters and / or the second set of predefined parameters may be user-selected parameters.

[0029] This way, a user (e.g., a construction planner or engineer) may provide the first set of predefined parameters which describe the boundary conditions which are required to be satisfied so that the construction assembly can be safely manufactured based on the connector layout.

[0030] A further aspect of the present disclosure relates to a method for manufacturing a construction assembly. The method may comprise obtaining a ranked set of connector layout solutions for the construction assembly in accordance with the method of any one of the preceding aspects. The method may comprise selecting an connector layout for the construction assembly from the set of connector layout solutions. The method may comprise manufacturing the construction assembly based on the connector layout of the construction assembly.

[0031] A further aspect of the present disclosure relates to a data-processing device comprising means for performing the method of any one of the aspects described herein. A further aspect of the present disclosure relates to a computer program comprising instructions which when executed by a computer cause the computer to perform the method of any one of the aspects described herein.

[0032] A further aspect of the present disclosure relates to a computer-readable medium having stored thereon a computer program comprising instructions, which when executed by a computer cause the computer to perform the method of any one of the aspects described herein.

[0033] BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The disclosure may be better understood by reference to the following drawings:

[0035] Fig. 1: A flow chart of a computer-implemented method for determining an connector layout of a construction assembly in accordance with embodiments of the present disclosure.

[0036] Fig. 2: A flowchart of a method for manufacturing a construction assembly in accordance with embodiments of the present disclosure.

[0037] Fig. 3: A flow chart of a computer-implemented method for determining an connector layout of a construction assembly in accordance with embodiments of the present disclosure.

[0038] Fig. 4a: A visualization of a simple grid approach for a pattern search optimization in accordance with embodiments of the present disclosure.

[0039] Fig. 4b: A visualization of a simple grid with area sorting approach for a pattern search optimization in accordance with embodiments of the present disclosure.

[0040] Fig. 5: A visualization of a bracketing approach for a pattern search optimization in accordance with embodiments of the present disclosure.

[0041] Fig. 6a: A visualization of an isoline grid approach for a pattern search optimization in accordance with embodiments of the present disclosure.

[0042] Fig. 6b: A visualization of an isoline grid with profile integration approach for a pattern search optimization in accordance with embodiments of the present disclosure. Fig. 7: A visualization of a triangular joint in accordance with embodiments of the present disclosure.

[0043] Fig. 8a: A three-dimensional visualization of an connector layout for a construction assembly in accordance with embodiments of the present disclosure.

[0044] Fig. 8b: A top view visualization of an connector layout for a construction assembly in accordance with embodiments of the present disclosure.

[0045] Fig. 9: Exemplary fastener and base plate layout combinations in accordance with embodiments of the present disclosure.

[0046] Fig. 10a: An connector layout solution in accordance with embodiments of the present disclosure.

[0047] Fig. 10b: An connector layout solution in accordance with embodiments of the present disclosure.

[0048] Fig. 11: Connector layout solutions in accordance with embodiments of the present disclosure.

[0049] Fig. 12a: An connector layout solution in accordance with embodiments of the present disclosure.

[0050] Fig. 12b: An connector layout solution in accordance with embodiments of the present disclosure.

[0051] Fig. 13: A data -processing apparatus in accordance with embodiments of the present disclosure.

[0052] Fig. 14: A manufactured construction assembly in accordance with embodiments of the present disclosure.

[0053] Fig. 15: A connector layout

[0054] DETAILED DESCRIPTION

[0055] In the following, representative embodiments illustrated in the accompanying drawings will be explained. It should be understood that the illustrated embodiments and the following descriptions refer to examples which are not intended to limit the embodiments to one preferred embodiment.

[0056] Fig. 1 illustrates a flow chart of a computer-implemented method too for determining an connector layout of a construction assembly in accordance with an exemplary embodiment.

[0057] The method too may comprise determining a set of fastener and base plate layout combinations based on a first set of predefined parameters for determining the connector layout (step 102). The first set of predefined parameters may define boundary conditions for determining the set of fastener and base plate layout combinations. The first set of predefined parameters may be user-selected parameters. The first set of predefined parameters may be parameters given by stability and rigidity demands on a structure supported by fastener and base plate layout.

[0058] The method too may comprise evaluating the set of fastener and base plate layout combinations to obtain a set of connector layout solutions (step 104). A fastener and base plate layout combination may comprise a fastener type and a layout type. A corresponding anchor solution may comprise a number of required fasteners of the fastener type and / or a position of each fastener on the layout.

[0059] For example, a fastener type may be defined by properties as shown in the following table:

[0060] Table 1: Exemplary fastener types and their properties.

[0061] In table 1, the index i represents a corresponding fastener type (i.e., the first row represents the fastener type 1, the second row represents the fastener type 2 and the third row represents the fastener type 3). Dminff represents the minimum distance between fasteners on the base plate (e.g., given in mm). Dminfb represents the minimum distance between each fastener and borders of the base plate. Dminfp represents the minimum distance between each fastener and the pole center (i.e., load point) on the base plate. As represents the size of the area S (see Fig. 7) and Tmaxrepresents the maximum allowed tension force on a single fastener, which may dependent on the fastener type.

[0062] Determining the set of fastener and base plate layout combinations and / or evaluating the set of fastener and base plate layout combinations may be further based on a third set of predefined parameters. The third set of predefined parameters may define computational boundaries. For example, the third set of predefined parameters may comprise convergence criteria, a maximum number of allowed iterations for the evaluating, in particular the optimizing, a maximum number of fastener and base plate layout combinations for the set of fastener and base plate layout combinations, assumptions about the baseplate for the construction assembly (e.g., a rigid baseplate), a used anchor design (e.g., anchor design in concrete), applied load (e.g., an expected and / or maximum amount of load applied by the construction assembly and / or dynamic load and / or static load), manufacturing standards (e.g., European norm EN 1992-4, ACI norms such as ACI 318-11, 318-14, 318-19 etc.), size of the baseplate, shape of the baseplate (e.g., rectangular), patterns of positioning anchors (e.g., regular patterns as explained with respect to Fig. 9) and / or an amount of anchors used (e.g., 4, 6, 8, 9, 10, 20, ... anchors). The third set of predefined parameters maybe statically configured (e.g., defined via system or static variables). In other words, the third set of predefined parameters may not be user-selectable. Alternatively, one more or all of the parameters of the third set of predefined parameters may be user-selectable (e.g., the manufacturing standard as the standard may vary depending on a location at which the construction assembly is built). This way, efficiency of the system is ensured with respect to computational boundaries. The maximum number of allowed iterations for the evaluating, in particular the optimizing, may be 15.

[0063] Evaluating may comprise performing a feasibility test verifying if a fastener and base plate layout combination is in accordance with the first set of predefined parameters. Performing the feasibility test may comprise determining whether a first layout for the given fastener and base plate layout combination is feasible. The first layout may comprise a largest possible base plate, a largest possible embedment depth, anchors being placed as close as possible to edges of the base plate or any combination thereof.

[0064] Evaluating may further comprise, if the fastener and base plate layout combination is verified, optimizing the fastener and base plate layout combination based at least in part on a layout type of the layout to obtain an connector layout solution. Optimizing the fastener and base plate layout combination may comprise determining that the layout type of the layout is a centered layout type without concrete edges and / or performing a pattern search optimization for the fastener and base plate layout combination. The pattern search optimization may be based on an indication for a pattern search approach of a plurality of pattern search approaches and / or a set of parameters dedicated for the indicated pattern search approach. The plurality of pattern search approaches may comprise a simple grid, a simple grid with area sorting, bracketing, isoline grid and / or isoline grid with profile integration. These approaches are explained in more details with respect to Figs. 4a-6b.

[0065] Additionally or alternatively, optimizing may comprise determining that the layout type of the layout is a non-centered layout type and / or a layout type with concrete edges, and / or performing a nonlinear optimization for the fastener and base plate layout combination. The non-linear optimization may be an Interior Point Optimizer, IPOPT. A vector of optimization variables for the IPOPT may comprises one or more of: a set of 2- dimensional coordinates for anchor points; a size of the base plate, preferably a rectangular base plate, a 2 -dimensional eccentricity of a profile of the layout and / or an anchor embedment depth. The IPOPT algorithm may be used to find local minima of non-linear problems of the form:

[0066] Equation 1

[0067] In equation 1, x e Rnis the vector of optimization variables (with upper and lower bounds xuand xL), f(x) is the objective function to be minimized and g(x) represents the constraints on the problem. The functions f and g are assumed to be continuous and differentiable. As explained above, the vector of optimization variables x may be composed by the x and y coordinates of the anchor points, the x and y size of the rectangular base plate Xp and Yp, the excentricity of the profile in x and y direction and the anchor embedment depth h. All values may be expressed in mm units but of course other metrics can be used as well (e.g., depending on the dimensions of the construction assembly as for example provided by the first set of predefined parameters). The objective function may be defined as:

[0068] Equation 2

[0069] In equation 2, the parameter s may be used for scaling and may be predefined, preferably statically predefined. The parameter a is determinant in the behaviour of the algorithm for anchors with variable embedment depth and it can attain two different values depending on the first set of predefined parameters (i.e., the parameter a is an example of a parameter comprised by the first set of predefined parameters). If a is set to a first value (e.g., a small value such as io) minimization of the base plate size may be prioritized over the embedment depth h. This may be advantageous if the construction assembly is built in an area where usage of a base plate of large size is not possible (e.g., due to restricted space). If a is set to a second value larger than the first value (e.g., a large value such as 10000) minimization of the embedment depth h. This may be advantageous if the construction assembly is built in an area where a deep embedment into the ground is not possible (e.g., for geographical reasons).

[0070] The constraint function g(x) may be composted by scope check constraints (e.g., a minimum distance between anchor points and / or a minimum distance between anchor points and edges of the base plate) and / or utilization values (e.g., determined by a traditional anchor design calculation ) which have to be below a maximum utilization value. The maximum utilization value is a further example of a parameter composed by the first set of predefined parameters. During execution of the IPOPT algorithm, derivate values of the objective and / or constraint function(s) may be determined during convergence. The derivative values may be determined based on a finite difference method. The finite difference method may comprise a set of finite difference parameters. The set of finite difference parameters may comprise a finite difference type, an order of error and / or a step size. The finite difference type may be central or forward, wherein central may be set as a preferred default value. The order of the error may comprise an order approximation. The order of approximation may be a first or a second order, wherein the second order approximation may be set as a preferred default value. Setting the order of error to a second order approximation has proven to provide a better result quality compared to a first order approximation. The step size may be used for calculating the finite difference. The step size may be set in mm or in any other suitable metric. The step size may be set to a preferred default value of 1.1 mm. A value of 1.1. has proven to avoid problems generated by jumps in the constraint functions located at 1 mm variable shift from some layout. Accordingly, better convergence may be achieved this way. Preferably, the derivative values selected for the objective function and the constraint function are in the same order of magnitude. This way, numerical issues during convergence may be avoided.

[0071] The algorithm may terminate based on a first order optimality error and a set of corresponding thresholds. In particular, the algorithm may terminate once the first order optimality error lies below the set of corresponding thresholds. The one or more thresholds of the set of corresponding thresholds may be predefined. The optimality error may comprise a dual infeasibility, constraints violation and / or complementarity condition. The dual infeasibility may be a maximum norm of the dual infeasibility. The constraints violation may be a maximum norm of the constraints violation. The complementary condition may be a maximum norm of a complementarity equation. The set of corresponding thresholds may comprise one threshold for each component of the optimality error. For example, a dual infeasibility threshold for the dual infeasibility, a constraint violation threshold for the constraints violation and / or a complementarity condition threshold for the complementarity condition.

[0072] The non-linear algorithm (e.g., the IPOPT algorithm) may be configured to output one result of a plurality of results. The plurality of results may comprise a first result representing a found local minimum, a second result representing a solution at an acceptable level, a third result representing an intermediate stopping criterion, a fourth result representing a best found feasible point and / or a fifth result representing no feasible points found. Each result may be associated with a corresponding index (e.g. an exit flag). For example, the first result may be associated with exit flag 1, the second result may be associated with exit flag 2, the third result may be associated with exit flag 5, the fourth result may be associated with exit flag 10 and the fifth result may be associated with exit flag -10.

[0073] The first result may represent that a local minimum was found. In other words, the algorithm has converged to a point (i.e. , the local minimum) where the three components of the first order optimality error lie below the set of corresponding thresholds. An amount of iterations required for finding the local minimum may be below a maximum amount of iterations allowed.

[0074] The second result may represent a solution at an acceptable level. This may be the case if due to numerical issues (e.g., kinks or jumps in the constraint function g are close to a local minimum), the set of corresponding thresholds cannot be satisfied. In this case, it may be determined that the components of the first order optimality error lie within a predefined range associated with the corresponding threshold value. One or more components of the optimality error may be ignored (e.g., the dual infeasibility). Additionally or alternatively, a further component / criterion may be added, which relates to a threshold for the maximum relative change of the objective function relative to the previous iteration. The second result may be outputted if the conditions required for the first result are not satisfied.

[0075] The third result may represent a solution obtained based on an intermediate stopping criterion. This criterion may be additionally defined. This criterion may catch the cases where the algorithm converges close to a local minimum but does not satisfy the conditions required for the second result. This may happen if the optimum lies close to a jump. The intermediate stopping criterion maybe based on changes of the objective function value over one or more previous iterations. For example, if the objective function values are small enough over the one or more previous iterations and if at least one feasible point was fond, the algorithm stops and outputs the at least one feasible point. An objective function value may be considered small enough if a relative difference between the objective function value and an average of objective functions values of n previous iterations is smaller than maxDelta for every single iteration. MaxDelta may refer to a predefined maximum allowed difference. Additionally or alternatively, the objective function value may be considered small enough if a ratio between a standard deviation and a mean of the objective function over n previous iterations is smaller than maxRelChange. MaxRelChange may refer a predefined maximum allowed relative change. The value n may be predefined. Determining whether the intermediate stopping criteria is fulfilled may be performed after a predefined amount of performed iterations (i.e., a first iteration at which the criterion is evaluated). The third result may be outputted if the conditions required for the first and second results are not satisfied. The fourth result may represent a best feasible point found. The fourth result may be outputted if the conditions required for the first, second and third results are not satisfied. Typically this result is be outputted if the maximum number of iterations is reached. If the maximum number of iterations is reached, a best feasible point is determined. Determining the best feasible point may be based on identifying a feasible point associated with the smallest value of the objective function. The beast feasible point is then outputted as result. Identifying the feasible point associated with the smallest value of the objective function may comprise searching through all found feasible points and comparing their associated objective function values. The points of the first m iterations may not be considered during searching. The value m may be predefined. This way, it may be avoided that a solution close to the starting point (i.e. , the first layout) is returned.

[0076] The fifth result may represent that no feasible points were found. The fifth result may be outputted if the conditions required for the first, second, third and fourth results are not satisfied.

[0077] In some embodiments, for fastener and base plate layout combinations without a profile, a single run of the IPOPT algorithm maybe performed. For fastener and base plate layout combinations with a centered layout with concrete edges with profile, a parameter search may be performed to determine a minimum possible base plate size based one or more constraints defining the minimum distance between anchors and / or the minimum distance between anchors and the plate edges and / or the minimum distance between anchors and the profile. A step size to be used in the parameter search for the distance between anchors and / or a step size for an embedment depth may be determined. Both step sizes may be predefined. For an connector layout found this way, a feasibility test may be performed. If feasible, the connector layout may represent an optimal solution and the algorithm stops. If infeasible, it may be determined whether the profile has a convex shape or non-convex shape. For profiles with convex shape (e.g., a square bar), a single run of the IOPT algorithm may be performed. For profiles with non-convex shape, a further parameter scan may be performed to search for a feasible connector layout with anchors close to the profile. For example, the anchors may be placed inside a x-y bounding box of the profile shape. Then, a step size to be used in the parameter search for the distance between anchors and / or a step size to be used in the parameter search for an embedment depth may be determined. Both step sizes may be predefined. In addition, a Nolasoft kernel may be called at each iteration of the parameter search. If a feasible layout is found, a single run of the IPOPT algorithm is performed using the found feasible layout as starting point. Additionally, preferably in parallel, another run of the IPOPT algorithm is performed using the feasible layout found by the feasibility test and additionally under the assumption that a convex hull of the profile is the external profile shape. For non-centered layouts with profile, a first run of the IPOPT algorithm may be performed where the constraint for the minimum distance between the profile and anchors is not considered. The feasibility of a solution of the IPOPT algorithm found under this configuration is then verified taking into account all constraints (i.e., also the constraint for the minimum distance between the profile and anchors). If feasible, the solutions represent a local optimum (i.e., minimum), the solution is outputted and the algorithm stops. If infeasible, the IPOPT is again run using the infeasible layout as starting position, wherein the IPOPT is executed in restoration mode. If the IPOPT is able to converge and find a feasible solution, the feasible solution is outputted and the algorithm stops. Otherwise, a further run of the IPOPT algorithm taking into account all constraints is performed using a first layout found to be feasible by a feasibility test as starting point.

[0078] The method too may comprise ranking the set of connector layout solutions based on a second set of predefined parameters for determining the connector layout (step 106). The second set of predefined parameters defines weighting criteria for ranking the set of connector layout solutions. The second set of predefined parameters may be user- selected parameters. The second set of predefined parameters may be parameters affecting the efficacy and efficiency of constructing the building.

[0079] The method too may further comprise obtaining the first set of predefined parameters and / or the second set of predefined parameters from a request. The request may comprise the first set of predefined parameters and / or the second set of predefined parameters. The request may comprise an indication of the first set of predefined parameters and / or the second set of predefined parameters.

[0080] Fig. 2 illustrates a flowchart of a method 200 for manufacturing a construction assembly in accordance with an exemplary embodiment.

[0081] The method 200 may comprise obtaining (step 202) a ranked set of connector layout solutions for the construction assembly in accordance with the method of any one of the aspects described herein (e.g., the method 100 of Fig. 1). The method 200 may comprise selecting an connector layout for the construction assembly from the set of connector layout solutions (step 204). The method 200 may comprise manufacturing the construction assembly based on the connector layout of the construction assembly (step 206).

[0082] Fig. 3 illustrates a flow chart of a computer-implemented method 300 for determining an connector layout of a construction assembly in accordance with an exemplary embodiment.

[0083] In the illustrated example, a user may provide a first set of predefined parameters 302 and a second set of predefined parameters 312. The first set of predefined parameters 302 and / or the second set of predefined parameters 312 may be selected by the user. The first set of predefined parameters 302 may define boundary conditions for determining a set of fastener and base plate layout combinations 304. The second set of predefined parameters defines weighting criteria for ranking the set of connector layout solutions. The weighting criteria may relate to fastener preferences with respect to work experience with a certain fastener type, availability of a fastener type, durability of a fastener type etc. For example, a construction engineer may have knowledge about a certain fastener type being more durable than other fastener type, because circumstances (e.g., environmental impact such as salt water) at the construction site may negatively affect the durability of some fastener types more than others.

[0084] The user may provide the first set of predefined parameters 302 and / or the second set of predefined parameters 312 via a user interface (e.g., a user interface of an app, a user interface of a webapp / website). For example, the user may have the possibility to upload the first set of predefined parameters 302 and / or the second set of predefined parameters 312 to the app / webapp / website (e.g., via a drag and drop option or any other menu option suitable for uploading files). The user may provide the first set of predefined parameters 302 and / or the second set of predefined parameters 312 via a request. For example, once the first set of predefined parameters 302 and / or the second set of predefined parameters 312 have been selected, the user may click on a corresponding button (e.g., an upload button) which may cause the issue of the request. The request may thus comprise the first set of predefined parameters 302 and / or the second set of predefined parameters 312. Accordingly, the first set of predefined parameters 302 and / or the second set of predefined parameters 312 maybe obtained from the request.

[0085] Based on the first set of predefined parameters 302, the set of fastener and base plate layout combinations 304 for determining the connector layout maybe determined. A fastener and base plate layout combination may comprise a fastener type and a layout type. A fastener type may be identified by using a fastener ID (e.g., I of table 1). The fastener ID may for example be stored in a data base. For example, it may be determined based on the first set of predefined parameters 302 that a first fastener (i.e., a fastener of a first type) and a second fastener (i.e., a fastener of a second type) may be suitable for the connector layout. The first fastener and the second fastener may be different. Additionally, for the first fastener two different layouts (i.e., a first and a second layout type) and for the second fastener one layout (i.e., the first layout type) may be determined. Thus, in the illustrated example, the set of fastener and base plate layout combinations 304 may comprise three fastener and base plate layout combinations.

[0086] The set of fastener and base plate layout combinations 304 may then be evaluated 306 to obtain a set of connector layout solutions (i.e., one or more solutions for an connector layout for manufacturing a construction assembly in accordance with the first set of predefined parameters 302). A corresponding anchor solution may comprise an amount of required fasteners of the fastener type and / or a position of each fastener on the layout.

[0087] As part of the evaluation, a feasibility test may be performed for each fastener and base plate layout combination of the set of fastener and base plate layout combinations 304. The feasibility test may verify if a fastener and base plate layout combination is in accordance with the first set of predefined parameters 302. For example, the feasibility test may be successful if the fastener and base plate layout combination is in accordance with the boundary conditions as defined by the first set of predefined parameters 302.

[0088] Performing the feasibility test may comprise determining whether a first layout for the given fastener and base plate layout combination is feasible. The first layout may comprise a largest possible base plate, a largest possible embedment depth, anchors being placed as close as possible to edges of the base plate or any combination thereof. In addition, the first layout may be a centered layout type. The first layout may comprise no concrete edges. The first layout may be considered as a “best case test” for the evaluated fastener and base plate layout combination. Accordingly, if the “best case test” does indicate that the fastener and base plate layout combination is infeasible, further optimizing can be avoided as there will most likely be no anchor solution which can be derived from the fastener and base plate layout combination. This is because for centered cases without concrete edges, the layout with the smallest utilization values is achieved with the base plate as large as possible, the anchors as close as possible to the base plate edges and the embedment depth as large as possible. For the same geometry, the presence of concrete edges does always lead to higher utilization values. For non-centered cases it may be assumed that if the ’best case test’ is not satisfied the case is infeasible. This is because, even if there would exist a feasible solution, this solution would comprise a relatively large base plate and would thus be irrelevant for practical usages, in particular for manufacturing a construction assembly.

[0089] If the first layout comprises no concrete edges, if the fastener and base plate layout combination is evaluated for a base plate with concrete edges and if the first layout was determined to be feasible, performing the feasibility test may further comprise performing a further feasibility test with the first layout comprising concrete edges. If it is determined that the first layout comprising concrete edges is also feasible, the first layout may be used for the optimizing of the fastener and base plate layout combination. If it is determined that the first layout comprising concrete edges is infeasible, a parameter scan may be performed if the first layout is a centered layout or a nonlinear optimization algorithm (e.g., an IPOPT algorithm as explained above) is performed if the first layout is a non-centered layout.

[0090] Performing the parameter scan may comprise varying a distance between a first anchor and a second anchor. In other words, distance between the anchors may be varied. Additionally, the size of the base plate may be kept as large as possible. This way, a feasible solution may be found. This feasible solution may then serve as a starting point for the optimizing. If no feasible solution is found, the evaluated fastener and base plate layout solution may be considered to be infeasible. Performing the nonlinear optimization algorithm (e.g., an IPOPT algorithm as explained above) may comprise performing the nonlinear optimization algorithm starting from the first layout (e.g., the best-case layout which was found to be infeasible based on the feasibility test). Other than for optimizing an already feasible layout, the non-linear optimization algorithm (e.g., IPOPT) with the aim of finding a feasible layout as starting point may be performed in restoration mode. In restoration mode, the non-linear optimization algorithm may be configured to minimize constraint violations (i.e., the non-linear optimization algorithm maybe configured to minimize violation with respect to the first set of predefined parameters or in other words, a constraint function g(x) may be minimized). For this purpose, the non-linear optimization algorithm may be configured to temporarily (i.e., for the duration required for finding a feasible layout) ignore an objective function. In order to ignore the objective function, the objective function maybe set to a constant objective function (e.g.,f(x)=o). In addition, other thresholds (e.g., dual infeasibility threshold and / or complementarity condition threshold) may be set to high values (e.g., infinity) so that only the constraints violation (i.e., the violation with respect to the first set of predefined parameters) is relevant for the convergence of the non-linear optimization algorithm. In addition, a maximum number of iterations of the non-linear optimization algorithm may be limited to avoid long execution times in case the evaluated fastener and base plate layout combination is indeed infeasible. Limiting the maximum number of iterations may be done by setting the maximum number of iterations to a value (e.g., 15) as defined in the third set of predefined parameters (see above).

[0091] If the feasibility test for a fastener and base plate layout combination is not successful (i.e., the fastener and base plate layout combination is not in accordance with the first set of predefined parameters 302 or in other words, the fastener and base plate layout combination is infeasible), the fastener and base plate layout combination may be discarded from the set of fastener and base plate layout combinations 304 and the feasibility test may be performed for the next fastener and base plate layout combination of the set of fastener and base plate layout combinations 304. If the feasibility test for a fastener and base plate layout combination is successful (i.e., the fastener and base plate layout combination is in accordance with the first set of predefined parameters 302 or in other words, the fastener and base plate layout combination is feasible), the fastener and base plate layout combination is kept in the set of fastener and base plate layout combinations 304 and may be optimized. In other words, the fastener and base plate layout combination determined to be feasible, is identified as a suitable starting point for the optimization.

[0092] Optimizing a feasible fastener and base plate layout combination may be based at least in part on a layout type of the layout. For example, if it is determined that the layout type of the layout is a centered layout type without concrete edges, a pattern search optimization may be performed for the fastener and base plate layout combination. For example, if it is determined that the layout type of the layout is a non-centered layout type and / or a layout type with concrete edges, a nonlinear optimization may be performed for the fastener and base plate layout combination. Using different ways of optimizing depending on properties of the fastener and base plate layout combination (e.g., the layout type of the layout and / or the type of fastener used) ensures that an optimal connector layout solution is found. Optimizing may be based on the first layout (e.g., the first layout may be used as a starting point for the optimizing of the fastener and base plate layout combination).

[0093] A layout may be considered as a centered layout if a load point (e.g., profile center), a center of mass of the base plate and a center of the anchors coincides. A layout may be considered as a non-centered layout if a position of the load point and the center of the anchors are free to move on the base (i.e., do not coincide).

[0094] An connector layout may be identified by a value specifying the number of anchors and a layout number. For example, for regular layouts with 1, 4, 8 and 9 anchors, the layout number 2 maybe associated to centered cases, the value 4 to non-centered ones. For example, for regular layouts with 2, 3 and 6 anchors the layout numbers 2 and 4 may represent centered resp. non-centered layouts with the anchors oriented in y direction, whereas the layout numbers 3 and 5 are associated to layouts with the anchors oriented in x direction.

[0095] As explained above, a pattern search optimization may be performed for a fastener and base plate layout combination if a layout type of the layout is a centered layout type. The first layout (e.g., the best case) which was found to be feasible, may be used as starting point for the pattern search optimization. The pattern search optimization may for example vary the size of the base plate in both directions (i.e., x and y direction) and look for the base plate with the smallest size which is still in accordance with at least the first set of predefined parameters.

[0096] For the pattern search optimization one or more pattern search approaches of a plurality of pattern search approaches may be used. The plurality of pattern search approaches may comprise a simple grid (see Fig. 4a), a simple grid with area sorting (see Fig. 4b), bracketing (see Fig. 5), isoline grid (see Fig. 6a) and isoline grid with profile integration (see Fig. 6b).

[0097] The pattern search optimization may be based on an indication indicating which pattern search approach of the plurality of pattern search approaches is used. For example, each pattern search approach may be associated with an index and the indication may indicate the index of the corresponding pattern search approach to be used. Additionally or alternatively, the pattern search optimization may be based on a set of parameters dedicated for the pattern search approach indicated by the indication. In other words, each pattern search approach may be associated with a set of parameters dedicated for the corresponding pattern search approach. The set of parameters dedicated for the pattern search approach may be dynamically signaled (e.g., as part of the first set of predefined parameters) or statically defined (e.g., defined as static / system variables). Examples for the corresponding parameter sets are explained with respect to the Figs. 4a-6b.

[0098] As explained above, a non-linear optimization may be performed for a fastener and base plate layout combination if a layout type of the layout is a non-centered layout type and / or a layout type with concrete edges. An example for a non-linear optimization is an IPOPT algorithm.

[0099] Once a set of connector layout solutions 308 is obtained, these may be ranked based on the second set of predefined parameters 312. The set of connector layout solutions 308 may be provided to the user via a user interface (e.g., the set of connector layout solutions 308 may be displayed on a display of a user device, may be provided as part of a report wherein the report may comprise a logfile and / or may be provided for download for the user). The user may decide whether to rank the connector layout solutions 308. It is also possible that only the best connector layout solution (i.e., the highest ranked connector layout solution) is provided to the user. Once the user is provided with the set of connector layout solutions 308, the user may select an connector layout from the set of connector layout solutions 308 for the construction assembly. The construction assembly may then be manufactured based on the (selected) connector layout of the construction assembly.

[0100] The steps performed in order to determine the connector layout may be logged into a log file. Additionally, the logfile may comprise indications (e.g., error messages indicating problems of the algorithms and / or warnings indicating potentially problematic points and / or information that could be useful for debugging). The logfile may comprise a plurality of entries wherein each entry represents one step performed in order to determine the connector layout. Each entry may be associated with a time stamp and a description of the step performed at the time stamp. For example, the logfile may comprise an entry describing the evaluating of a fastener and base plate layout combination as well as a corresponding time stamp of the evaluating. In addition, the logfile may comprise the first set of predefined parameters and / or the second set of predefined parameters. The logfile may be provided as a summary report (e.g., at the end of the method when an connector layout was found). Fig. 4a illustrates a visualization of a simple grid approach 400a for a pattern search optimization in accordance with an exemplary embodiment. Fig. 4a shows a grid with a grid size of dx*dx. The points highlighted dark, such as the point 404a, represent invalid solutions while the points highlighted in light grey, such as the point 402a, represent valid solutions. Each point is associated with a corresponding base plate size. During the simple grid approach 400a, each point on the grid is searched (i.e., it is determined whether the point represent a valid or invalid solution). Once all points are searched, the point associated with the smallest valid base plate size is output as the result. The simple gird approach 400a may be associated with the index 1. A set of parameters dedicated for the simple grid approach 400a may comprise a grid size (e.g., dx*dx). The grid size may be defined in millimeter, centimeter or in another length dimension. Defining the grid size in millimeter may be preferable.

[0101] Fig. 4b illustrates a visualization of a simple grid with area sorting approach 400b for a pattern search optimization in accordance with an exemplary embodiment. Fig. 4b shows a grid with a grid size of dx*dx. The points highlighted dark, such as the point 404b, represent invalid solutions while the points highlighted in light grey, such as the point 402b, represent valid solutions. Each point is associated with a corresponding base plate size. One difference compared to the simple grid approach 400a is that the points are sorted beforehand according to their associated base plate size. For example, the point in the bottom left corner represents the point associated with the smallest base plate size. This is also the starting point of the simple grid with area sorting approach 400b. During the simple grid with area sorting approach 400a, points on the grid are searched from lowest to largest associated base plate size (i.e., it is determined whether the point represent a valid or invalid solution). The first point found to be valid (i.e., point 402b) is thus also the point associated with the smallest valid base plate size and is outputted as the result. The simple gird approach with area sorting 400b may be associated with the index 2. A set of parameters dedicated for the simple grid approach with area sorting 400b may comprise a grid size (e.g., dx*dx). The grid size may be defined in millimeter, centimeter or in another length dimension. Defining the grid size in millimeter may be preferable.

[0102] Fig. 5 illustrates a visualization of a bracketing approach 500 for a pattern search optimization in accordance with an exemplary embodiment. Valid solutions are represented by light grey points (e.g., point 405 and point 508c), whereas invalid solutions are represented by dark point (e.g., point 502, points so6a-c and 508a-b). Performing the bracketing approach 500 may comprise setting an alpha value (e.g., as a percentage). For example, the alpha value may be set to 0.3. This means that a first point 506b is set at a position representing a third of the length of the diagonal between the bottom left corner and the upper right corner. The bottom left corner is represented by a point 502 which represents an invalid solution (e.g., because the point 502 is associated with a smallest possible base plate size, such as zero). The upper right corner is represented by a point 504 which represents a valid solution (e.g., because the point 503 is associated with a largest possible base plate size, such as the base plate size of the first layout). At this point 506, an isoline (1. isoline) is drawn for the area and the edge points 506a and 506c are included. These three points are tested and depending on the result the next isoline (2. isoline) is drawn. In general, if one of the three points or more is valid, the next smaller one is calculated, otherwise the next larger one. In general, this procedure is repeated until the accuracy limit is reached (e.g., indicated by an error size of the base plate). In the illustrated example, a next point 508b on the diagonal is determined and the corresponding edge points 508a and 508c are included and tested. In the illustrated example, it was determined that point 508c represents a valid solution and that point 508c also reaches the accuracy limit. Thus, no further iterations are performed in this example and point 508c is outputted as result. The bracketing approach 500 may be associated with the index 3. A set of parameters dedicated for the bracketing approach 500 may comprise an error size of the base plate size and a subdivision of the base plate (e.g., represented by an alpha value), both preferably given in percentage. The error size may define a termination criterion for the bracketing approach 500.

[0103] Fig. 6a illustrates a visualization of an isoline grid approach 600a for a pattern search optimization in accordance with an exemplary embodiment. Fig. 6a shows a grid similar to the grid used in the simple grid approach 400a and in the simple grid approach with area sorting 400b. A difference compared to these approaches is that in the isoline grid approach 600a, no fixed gride size of dx*dx is used. Instead, a percentage grid dA / A, with dA=dx*dx is specified. In other words, the isoline grid approach 600a is based on a grid which is finer for smaller base plate sizes and coarser for larger base plate sizes. The points highlighted dark, such as the point 604a, represent invalid solutions while the points highlighted in light grey, such as the point 602a, represent valid solutions. Each point is associated with a corresponding base plate size. Same as compared to the simple grid with area sorting approach 400b, the points are sorted beforehand according to their associated base plate size. For example, the point in the bottom left corner represents the point associated with the smallest base plate size. This is also the starting point of the isoline grid approach 6ooa. During the isoline grid approach 6ooa, points on the grid are searched from lowest to largest associated base plate size (i.e., it is determined whether the point represent a valid or invalid solution). The first point found to be valid (i.e., point 602a) is thus also the point associated with the smallest valid base plate size and is outputted as the result. The isoline grid approach 600a may be associated with the index 4. A set of parameters dedicated for the isoline grid approach 600a may comprise an abort criterion. The abort criterion may comprise an error size if the base plate size in percent.

[0104] Fig. 6b illustrates a visualization of an isoline grid with profile integration approach 600b for a pattern search optimization in accordance with an exemplary embodiment.

[0105] The isoline grid with profile integration approach 600b may be seen as an extension of the isoline grid approach 600a. In the illustrated example, a profile having the shape of a “H” is integrated. The first value YA represent the height of the profile and the second value XA represent the distance between the left and the right side of the profile (i.e., the length of the connecting line of the H). Fig. 6b illustrates three different ways 602b- 606b of integration the “H” profile. As one can see, depending on the positioning of the profile, the size of the base plate, the size of the anchors as well as the number of anchors may vary. Performing the isoline grid with profile integration approach 600b may comprise a first step of determining a first value (e.g., YA) and a second value (e.g., XA). Determining the first and the second value may comprise performing a parameter scan. Determining the first value and the second value may be based on the base plate size. In particular, determining the first value and the second value based on the base plate size may comprise keeping the base plate size to a smallest possible size based on the profile size (e.g., as represented by the first and the second value). Performing the isoline grid with profile integration approach 600b may further comprise a second step of adjusting the base plate size based on the profile size and positions of the anchors. The second step may be performed if no valid solution was found by the first step. For example, the base plate size may be adjusted by adding a predefined value. The predefined value may be based on the profile size and / or the positions of the anchors. For example, the new base plate size may be determined as follows: new base plate size = current base plate size + 2dmin +2rmin. The second step may further comprise performing the parameter scan for the first value YA and the second value YA. Performing the isoline grid with profile integration approach 600b may further comprise a third step of performing the isoline grid approach 600a. The third step may be performed if no valid solution was found by the second step. The third step may be performed starting from a base plate size which is larger than the new base plate size. The steps may be performed in sequence with increasing base plate size. Once a feasible solution is found, this solution is outputted as result and can be considered the optimal one. The isoline grid with profile integration approach 6oob may be associated with the index 5. A set of parameters dedicated for the isoline grid with profile integration approach 600b may comprise an abort criterion. The abort criterion may comprise an error size if the base plate size in percent.

[0106] Fig. 7 illustrates a visualization of a triangular joint 700 in accordance with an exemplary embodiment. A joint may be considered as a 2-dimensional connected surface S, at which two different bodies A and B are in contact as illustrated on the left part (a) of Fig. 7. The surface S may be curved or non-curved, preferably non-curved.

[0107] The surface S may also be referred to as contact area S. Each position on the surface S may be identified by a two-dimensional position (x, y) in a two-dimensional coordinate system. The mechanical connection of the two bodies at the joint area S is provided by N fasteners. The fasteners can be placed on the positioning area Spe S, which is a subset of S (see part (b) of Fig. 7). Typically, the positioning area Spis smaller than S, since: (a) there is a minimal distance between a fastener and the boundary of S, or (b) certain parts of S are not available for fastener positioning for constructive reason (e.g. there is a profile). In some cases the contact area S and the positioning area Spare fixed and cannot be changed during execution of the method according to the aspects of the present disclosure. The size of S, the dimensions of S, the positioning area Sp, are examples for parameters of the first set of predefined parameters. Further examples of parameters of the first set of predefined parameters is a profile shape (e.g., defined by a polygon) or loads .The surface S may be referred to as the baseplate.

[0108] The positioning of the fasteners may follow a certain pattern (e.g. a rectangular pattern as explained with respect to Fig. 9) or share a certain symmetry (e.g. the positioning area Spand the pattern share the same symmetry group). Non-symmetric positionings may also be accepted as anchor solutions. There may be I (e.g., 1=3 as illustrated in table 1) different fasteners types, which can be used for the joint. Different fastener types differ in their properties, such as size, material, maximal loads or costs. We assume here, for simplicity, that all fasteners used for a given anchor solution are of the same type. However, anchor solutions comprising fasteners of different types are possible.

[0109] The right part b) of Fig. 7 illustrates a planar view of the surface S with a schematic representation of the positioning area Sp(dotted line) with three fasteners (filled circles), two external forces (Fi and F2) and a single external moment (Ml) acting on joint S. In order to achieve a stable and secure construction, certain constraints for each fastener have to be satisfied. An connector layout solution considered as optimal may thus be required to satisfy these constraints. Accordingly, the optimization problem also refer to as universal multi-fastener joint problem which is to be solved in order to achieve an optimal connector layout solution, can be formulated as how to identify an optimal number and optimal type(s) of fasteners with optimal positioning on the joint S (respectively the positioning area Sp) such that for every single fastener the positioning is feasible, the physical constraints are fulfilled and / or a predefined goal (e.g., as indicated by the of predefined parameters) is reached. The predefined goal may comprise minimum manufacturing costs, minimum strain of the fasteners, maximal lifetime of the fasteners etc. The physical constraints and / or the predefined goal may be examples of parameters comprised by the first set of predefined parameters.

[0110] Fig. 8a illustrates a three-dimensional visualization of an connector layout 8ooa for a construction assembly in accordance with an exemplary embodiment. The illustrated example comprises a body A (i.e., a rectangular base plate) is connected to a body B (e.g., an infinitely extended body with a planar surface) with four fasteners. On the base plate a pole is equipped on which a normal force N and a bending moment M along the plane of the base plate is acting. The base plate may be considered as a xy-plane as indicated by the coordinate system (i.e., each position on the base plate may be identified by a 2-dimensional coordinate tuple (x, y)).

[0111] Fig. 8b illustrates a top view visualization of an connector layout 800b for a construction assembly in accordance with an exemplary embodiment. Fig. 8b shows the top view of the three-dimensional visualization of the connector layout 800a. Xprepresent the size of the base pate in X direction and Ypthe size of the base plate in Y direction. Accordingly, the center of the base plate maybe determined as (Xp / 2, Yp / 2). The center of the pole positioned on the base plate may be determined as (XE, YE)

[0112] Fig. 9 illustrates exemplary fastener and base plate layout combinations 900 in accordance with an exemplary embodiment. The illustrated fastener and base plate layout combinations 900 may be part of a set of fastener and base plate layout combinations 304. The illustrated fastener and base plate layout combinations 900 may be understood as regular fastener patterns with a corresponding amount of fasteners n and a pattern layout number I (i.e., a layout type). The position of each fastener as well as the corresponding anchor maybe indicated by 2-dimensional coordinates (e.g., x and y). The position indicated by the 2-dimensional coordinates may refer to the position of the fastener on the base plate with respect to an origin (e.g., a corner such as the bottom left corner of the base plate if the base plate is a rectangular base plate). For illustrative purposes, it is assumed that only a single fastener type is used in the shown example. The top row illustrates for a first layout type 1=1 how a given amount of fasteners n (e.g., 2-6) maybe placed on the base plate. The lower row illustrates for a second layout type 1=2 how a given amount of fasteners n (e.g., 2-6) may be placed on the base plate.

[0113] Fig. toa illustrates an connector layout solution toooa in accordance with an exemplary embodiment. The connector layout solution 1000a represent the result of a first experiment. For the first experiment, only fasteners of type 2 (see table 1) were considered. The connector layout solution toooa represents a local minimum found by starting the IPOPT algorithm from a feasible layout (e.g., a first layout with the pole being placed on the center of the base plate and the fasteners being placed as close as possible to the base plate borders). As can be seen, a pole 1002a of predefined size (e.g., a radius of Rc- 30) is placed onto the base plate 1004a. In order to be stable (i.e., to be capable of dealing with the acting bending moment M given in kNm), the connector layout solution defines a size of the base plate 1004a to be 196mm wide (i.e., 196 mm long in the x domain) and 130 mm long (i.e., 130 mm long in the y domain). Additionally, the connector layout solution comprises n=6 anchor points 1006a for the fasteners wherein each anchor point is defined by 2 -dimensional coordinates. Additionally, base plate is defined as rectangular.

[0114] Fig. 10b illustrates an connector layout solution 1000b in accordance with an exemplary embodiment. The illustrated connector layout solution 1000b corresponds to the same experiment (i.e., the first experiment) as connector layout solution 1000a with the difference that the connector layout solution 1000b represents a local minimum which was found with multiple restarts of the IPOPT algorithm with differently initialized vectors of optimization variables (i.e., with randomly initialized values of the optimization variables). In the illustrated example, the local minimum corresponds to the global minimum which is why the illustrated connector layout solution 1000b can be considered optimal. Compared to the connector layout solution 1000a, the base plate 1004b of connector layout solution 1000b is smaller (i.e., only 138 mm wide and only 120 mm long). In order to be stable (i.e., to be capable of dealing with the bending moment M acting on the pole 1002b of the predefined size), the layout solution also comprises n=6 anchor points 1006b for the fasteners wherein each anchor point is defined by 2-dimensional coordinates. Additionally, base plate is defined as rectangular. However, due to the smaller base plate size the positioning of these anchor points is different compared to the positioning of connector layout solution 1000a.

[0115] Fig. 11 illustrates connector layout solutions nooa-c in accordance with an exemplary embodiment. The connector layout solutions liooa-c represent results of a second experiment. For the second experiment, only fasteners of type 2 (see table i) were considered. A pole H02a-c of predefined size is placed on the corresponding base plate iiO4a-c. The connector layout solutions liooa-c comprise n=4 anchor points no6a-c for the fasteners wherein each anchor point is defined by 2-dimensional coordinates. Additionally, the base plate iiO4a-c is defined as rectangular. Compared to the connector layout solutions loooa-b, the connector layout solutions nooa-c are not limited to regular layout patterns. Instead, a free fastener respectively anchor positioning was utilized. While regular layout patterns may represent a lower complexity of the optimization problem and thus require less computational resources, free positioning may yield better results. The shown connector layout solutions nooa-c were found by starting the IPOPT algorithm from feasible starting layouts. Accordingly, the connector layout solutions toooa-c represent local minima whereas connector layout solution 1100c may be considered the global minimum.

[0116] Fig. 12a illustrates an connector layout solution 1200a in accordance with an exemplary embodiment of the present disclosure. The connector layout solution 1200a represents a result of a third experiment. For the third experiment, fastener of types 1, 2 and 3 (see table 1) were considered. A pole 1202a of predefined size is placed on the corresponding base plate 1104a. The connector layout solutions 1200a comprise n-2 anchor points 1206a for the fasteners wherein each anchor point is defined by 2-dimensional coordinates. Additionally, the base plate 1204a is defined as rectangular. The connector layout solution 1200a corresponds to a global minimum (i.e., an optimal solution) with the base plate being 109.5mm wide and 118.2mm long). In order to be stable (i.e., to be capable of dealing with the bending moment M acting on the pole 1200a of the predefined size), the two anchor points 1206a for the corresponding fasteners were placed as illustrated. In this example, a regular pattern was used. In this example, both fasteners are of type 3.

[0117] Fig. 12b illustrates an connector layout solution 1200b in accordance with an exemplary embodiment of the present disclosure. The connector layout solution 1200a represents another result of the third experiment as illustrated with respect to Fig. 12b. A pole 1202b of predefined size is placed on the corresponding base plate 1104b. The connector layout solutions 1200b comprise n=2 anchor points 1206b for the fasteners wherein each anchor point is defined by 2-dimensional coordinates. Additionally, the base plate 1204b is defined as rectangular. The connector layout solution 1200b corresponds to a global minimum (i.e., an optimal solution) with the base plate being 104.4mmwide and 129.1 mm long). In order to be stable (i.e., to be capable of dealing with the bending moment M acting on the pole 1200b of the predefined size), the two anchor points 1206b for the corresponding fasteners were placed as illustrated. In this example, a regular pattern was used. In this example, all three fasteners are of type 2. Fig. 13 illustrates a data-processing apparatus 1300 in accordance with an exemplary embodiment of the present disclosure. The data-processing apparatus 1300 may comprise at least one means for performing the method according to the aspects of the present disclosure (e.g., as explained with respect to the above Figs.). The at least one means may comprise one or more processors 1302 and a memory 1304. The memory13°4 may be coupled with the one or more processors 1302. The memory 1304 may have stored a computer program 1306 comprising instructions which when executed by a computer or by one of the one or more processors 1302 may cause the computer or the one or more processors 1302 to perform the method(s) according to any one of the aspects described herein. Fig. 14 illustrates a manufactured construction assembly 1400 in accordance with an exemplary embodiment of the present disclosure. The construction assembly 1400 comprises a building 1400 or part of a building that is mounted via connector layouts i4O4a-d to a foundation 1402. The building 1401 can be a residential building, industrial building, infrastructure building, bridge, railway, and other civil engineering building. The construction assembly 1400 uses connector layouts i4O4a-d as obtained using the method of the present disclosure. The connector layouts i4O4a-d comprise base plates 1410 and a set of fasteners 1411.

[0118] The exemplary building 1401 stands with several pillars I4o6a-d on the foundation 1402. The pillars I4o6a-d can be an integral part of the building’s structure. The pillars may extend over the whole height or a significant part of the building 1401. The type of the pillar I4o6a-d is a parameter of the building structure that is typically defined along with the building design. The pillar I4o6a-d can be, for instance, a column having an I- shaped, H-shaped, T-shaped, Z-shaped, L-shaped profile, or having a hollow or filled rectangular, quadratic profile. The column can be made of steel. The profile of the pillar I4o6a-d has an impact on the rigidity. The type of profile can within the first set of parameters.

[0119] The pillars I4o6a-d are welded to a front side of the base plates 1410. The base plate 1410 is a plate, preferably made of steel. A thickness of the base plate 1410 can be a parameter of the building structure. The thickness can influence the stiffness of construction assembly. The thickness can be a parameter among the first set of parameters. The parameter can be a single value of the thickness, upper and / or lower boundaries to the thickness. A surface size of the front side of the base plate 1410 may be a parameter of the building structure. The base plate 1410 may be restrained to have a minimum surface size in view of a required stiffness of the connector layouts 14043-d.

[0120] The base plate 1410 maybe restrained to have a maximum surface size, because for instance to stay within boundaries of the foundation or to not interfere with neighboring structures. The surface size can be a parameter of the first set. The parameter can be a value of the surface size or an upper and / or lower boundary to the surface size. The base plate 1410 has a pattern of holes for placing the fasteners 1412.

[0121] The pattern is preferably not a parameter of the first set. Even though, parameters may give limitations minimum distances of holes and minimum distances of the holes from the edges. These limiting parameters are preferably set by default. The base plate 1410 is fixed to the foundation 1402 by fasteners 1412. The fasteners 1412 can be mechanical fasteners like screws, concrete screws, dowels, bolts, anchoring bolts. The fasteners 1412 can be so called chemical anchors. A chemical anchor uses a resin or other chemical compound that is initially wet, such that a stud element can be inserted into, and hardens over time.

[0122] The foundation 1402 can be a basement on which the building is standing. The foundation 1402 can be a wall-like structure to which a building structure is fixed, or a ceiling-like structure from which a building structure is hanging. The foundation 1402 can be made of concrete or stone. In other embodiments the foundation 1402 can be made of wood. It is to be understood that the construction assembly as referred to within this disclosure may relate to any type of construction built using one or more connector layout(s) as obtained according to the method of the present disclosure.

[0123] Fig. 15 illustrates a set of first parameters. The exemplary parameters are the profile of the pillar, minimum forces and torques the connector layout 1404 needs to sustain, material and dimensions of the foundation. Fig. 16 illustrates a solution of the connector layout 1404. The exemplary layout has a base plate optimized for small dimensions and four anchors of a certain kind. The illustrated solution is one of the several ranked solutions. The second set of parameters can be parameters influencing efficiency and efficacy of installing the connector layout 1404, but not necessarily the integrity of the structure. The anchors require for different installation times. There is a tradeoff between setting several small anchors versus a few larger anchors. Chemical anchors support high tensile loads but require for a curing time. The second set of parameters weighs the different aspects, and can provide for an optimization. As used herein the term “and / or” includes any and all combinations of one or more of the associated listed items and maybe abbreviated as

[0124] Although some aspects have been described in the context of an apparatus, it is clear that these aspects also represent a description of the corresponding method, where a block or device corresponds to a method step or a feature of a method step. Analogously, aspects described in the context of a method step also represent a description of a corresponding block or item or feature of a corresponding apparatus.

[0125] Embodiments of the present disclosure may be implemented on a computer system. The computer system may be a local computer device (e.g., personal computer, laptop, tablet computer or mobile phone) with one or more processors and one or more storage devices or may be a distributed computer system (e.g., a cloud computing system with one or more processors and one or more storage devices distributed at various locations, for example, at a local client and / or one or more remote server farms and / or data centers). The computer system may comprise any circuit or combination of circuits. In one embodiment, the computer system may include one or more processors which can be of any type. As used herein, processor may mean any type of computational circuit, such as but not limited to a microprocessor, a microcontroller, a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a graphics processor, a digital signal processor (DSP), multiple core processor, a field programmable gate array (FPGA), or any other type of processor or processing circuit. Other types of circuits that may be included in the computer system may be a custom circuit, an application-specific integrated circuit (ASIC), or the like, such as, for example, one or more circuits (such as a communication circuit) for use in wireless devices like mobile telephones, tablet computers, laptop computers, two-way radios, and similar electronic systems. The computer system may include one or more storage devices, which may include one or more memory elements suitable to the particular application, such as a main memory in the form of random-access memory (RAM), one or more hard drives, and / or one or more drives that handle removable media such as compact disks (CD), flash memory cards, digital video disk (DVD), and the like. The computer system may also include a display device, one or more speakers, and a keyboard and / or controller, which can include a mouse, trackball, touch screen, voice-recognition device, or any other device that permits a system user to input information into and receive information from the computer system. Some or all of the method steps may be executed by (or using) a hardware apparatus, like for example, a processor, a microprocessor, a programmable computer or an electronic circuit. In some embodiments, some one or more of the most important method steps may be executed by such an apparatus.

[0126] Depending on certain implementation requirements, embodiments of the present disclosure can be implemented in hardware or in software. The implementation can be performed using a non-transitory storage medium such as a digital storage medium, for example a floppy disc, a DVD, a Blu-Ray, a CD, a ROM, a PROM, and EPROM, an EEPROM or a FLASH memory, having electronically readable control signals stored thereon, which cooperate (or are capable of cooperating) with a programmable computer system such that the respective method is performed. Therefore, the digital storage medium may be computer readable.

[0127] Some embodiments according to the present disclosure comprise a data carrier having electronically readable control signals, which are capable of cooperating with a programmable computer system, such that one of the methods described herein is performed.

[0128] Generally, embodiments of the present disclosure can be implemented as a computer program product with a program code, the program code being operative for performing one of the methods when the computer program product runs on a computer. The program code may, for example, be stored on a machine-readable carrier.

[0129] Other embodiments comprise the computer program for performing one of the methods described herein, stored on a machine-readable carrier. In other words, an embodiment of the present disclosure is, therefore, a computer program having a program code for performing one of the methods described herein, when the computer program runs on a computer.

[0130] A further embodiment of the present disclosure is, therefore, a storage medium (or a data carrier, or a computer-readable medium) comprising, stored thereon, the computer program for performing one of the methods described herein when it is performed by a processor. The data carrier, the digital storage medium or the recorded medium are typically tangible and / or non-transitory. A further embodiment of the present disclosure is an apparatus as described herein comprising a processor and the storage medium.

[0131] A further embodiment of the present disclosure is, therefore, a data stream or a sequence of signals representing the computer program for performing one of the methods described herein. The data stream or the sequence of signals may, for example, be configured to be transferred via a data communication connection, for example, via the internet.

[0132] A further embodiment comprises a processing means, for example, a computer or a programmable logic device, configured to, or adapted to, perform one of the methods described herein.

[0133] A further embodiment comprises a computer having installed thereon the computer program for performing one of the methods described herein.

[0134] A further embodiment according to the present disclosure comprises an apparatus or a system configured to transfer (for example, electronically or optically) a computer program for performing one of the methods described herein to a receiver. The receiver may, for example, be a computer, a mobile device, a memory device or the like. The apparatus or system may, for example, comprise a file server for transferring the computer program to the receiver.

[0135] In some embodiments, a programmable logic device (for example, a field programmable gate array) may be used to perform some or all of the functionalities of the methods described herein. In some embodiments, a field programmable gate array may cooperate with a microprocessor in order to perform one of the methods described herein. Generally, the methods are preferably performed by any hardware apparatus.

Claims

CLAIMS1. A computer-implemented (too) method for determining an connector layout (i4O4a-d) of a construction assembly (1400), the method comprising: determining (102) a set of fastener (1412) and base plate (1410) layout combinations (900) based on a first set of predefined parameters for determining the connector layout; evaluating (104) the set of fastener and base plate layout combinations (900) to obtain a set of connector layout solutions (loooa-b, nooa-c, i2ooa-b); ranking (106) the set of connector layout solutions (toooa-b, liooa-c, I2ooa-b) based on a second set of predefined parameters for determining the connector layout (i4O4a-d).

2. The method of claim 1, wherein evaluating comprises: performing a feasibility test verifying if a fastener and base plate layout combination is in accordance with the first set of predefined parameters; and if the fastener and base plate layout combination is verified, optimizing the fastener and base plate layout combination based at least in part on a layout type of the fastener and base plate layout to obtain an connector layout solution.

3. The method of the preceding claim, wherein performing the feasibility test comprises: determining whether a first layout for the given fastener and base plate layout combination is feasible, wherein the first layout comprises: a largest possible base plate, a largest possible embedment depth, anchors being placed as close as possible to edges of the base plate, or any combination thereof.

4. The method of any one of the claims 2-3, wherein optimizing the fastener and base plate layout combination comprises: determining that the layout type of the layout is a centered layout type without concrete edges, andperforming a pattern search optimization for the fastener and base plate layout combination; or determining that the layout type of the layout is a non-centered layout type and / or a layout type with concrete edges, and performing a nonlinear optimization for the fastener and base plate layout combination.

5. The method of the preceding claim, wherein the pattern search optimization is based on: an indication for a pattern search approach of a plurality of pattern search approaches, wherein the plurality of pattern search approaches comprises: a simple grid, a simple grid with area sorting, bracketing, isoline grid and isoline grid with profile integration; and / or a set of parameters dedicated for the indicated pattern search approach.

6. The method of any one of the claims 4-5, wherein the non-linear optimization is an Interior Point Optimizer, IPOPT.

7. The method of the preceding claim, wherein a vector of optimization variables for the IPOPT comprises one or more of: a set of 2-dimensional coordinates for anchor points; a size of the base plate, preferably a rectangular base plate; a 2-dimensional eccentricity of a profile of the layout; an anchor embedment depth.

8. The method of any one of the preceding claims, wherein a fastener and base plate layout combination comprise a fastener type and a layout type; and wherein a corresponding anchor solution comprises an amount of required fasteners of the fastener type and a position of each fastener on the layout.

9. The method of any one of the preceding claims, wherein the first set of predefined parameters defines boundary conditions for determining the set of fastener and base plate layout combinations.

10. The method of any one of the preceding claims, wherein the second set of predefined parameters defines weighting criteria for ranking the set of connector layout solutions. n. The method of any one of the preceding claims, further comprising: obtaining the first set of predefined parameters and / or the second set of predefined parameters from a request; wherein the request comprises the first set of predefined parameters and / or the second set of predefined parameters.

12. The method of any one of the preceding claims, wherein the first set of predefined parameters and / or the second set of predefined parameters are user- selected parameters.

13. A method (200) for manufacturing a construction assembly (1400), the method comprising. obtaining (202) a ranked set of connector layout solutions (loooa-b, liooa-c, I2ooa-b) for the construction assembly (1400) in accordance with the method (100) of any one of the preceding claims; selecting (204) an connector layout (i4O4a-d) for the construction assembly (1400) from the set of connector layout solutions; and manufacturing (206) the construction assembly (1400) based on the connector layout (i4O4a-d) of the construction assembly (1400).

14. A data-processing device (1300) comprising means for performing the method of any one of the claims 1-12.

15. A computer program (1306) comprising instructions which when executed by a computer cause the computer to perform the method of any one of the claims 1-12.

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