Optimization of tower designs

Abstract

The present relates to methods and systems for optimizing tower design The system (100) includes a geometry module (210) to receive from a user, input data comprising plurality of parameters to model an initial geometry of a tower indicative of one or more physical parameters. A load case generation module (212) is configured to generate load cases for testing the initial geometry. An iteration module (214) is configured to apply each load case to assess the initial geometry to withstand loads. Based on this assessment, a design alteration module (216) may sequentially alter at least one physical parameter of the initial geometry to obtain a plurality of tower designs. The load case generation module (212) determines a set of load cases corresponding to each design, which may be applied iteratively to the respective designs. An optimization analysis module (218) may identify an optimized design based on outputs corresponding to execution of the load cases on each of the plurality of designs.

Description

OPTIMIZATION OF TOWER DESIGNSTECHNICAL FIELD

[0001] The present subject matter relates, in general, to towers, and, particularly but not exclusively, to optimization of the design of towers to be used for various applications, such as power transmission, and supporting overhead communication cables.BACKGROUND

[0002] Towers of various kinds are essential in numerous industries and are often designed to meet specific functional requirement. For example, power transmission towers are a common sight across landscapes worldwide. These structures are integral to the power transmission infrastructure, serving as the physical support for overhead power lines. They are positioned to span vast geographies, effectively forming a network that facilitates the transmission of electrical energy from power generation plants to the end consumers.

[0003] Often these towers, including those for power transmission, communication, etc, are constructed from materials like steel due to its high strength, high durability, and cost-effectiveness. These towers are designed to withstand a variety of environmental conditions, including high winds, heavy snowfall, and even seismic activities. For instance, the design of the towers for power transmission also accounts for withstanding substantial reaction force in case of the breakage of power cables. Therefore, designing these towers is a complex process, requiring a high level of expertise and precision, while also involving a careful balance of structural integrity and cost-effectiveness.SUMMARY

[0004] The details of some embodiments of the invention described in this specification are set forth in the accompanying drawings and the description below. Other features, aspects, and advantages of the invention will become apparent from the description, the drawings, and the claims.

[0005] The present subject matter relates to systems and methods for optimized tower designs.

[0006] In accordance with an embodiment of the present subject matter, a system to optimize a tower design comprises at least one processor and a memory in communication with the at least one processor. The system includes a geometry module coupled to the at least one processor to receive from a user, input data comprising plurality of parameters to model an initial geometry of a tower, the plurality of parameters being indicative of one or more physical parameters of the tower. A load case generation module coupled to the at least one processor generates a plurality of load cases for testing the initial geometry, each load case representing a different combination of loads to be applied to the initial geometry. An iteration module coupled to the at least one processor provides the plurality of load cases to a finite element analysis (FEA) system for iterative application of each of the load cases to the initial geometry to determine if the initial geometry withstands the different combination of loads. A design alteration module coupled to the at least one processor, based on the determination that the initial geometry withstands the different combination of loads, which sequentially alters at least one physical parameter of the one or more physical parameters of the initial geometry to obtain a plurality of designs of the tower. The load case generation module may determine a set of load cases corresponding to each of the plurality of designs of the tower, and the iteration module provide the set of load cases to the FEA system for iterative application of the set of load cases to the respective plurality of designs of the tower. An optimization analysis module coupled to the at least one processor identifies, based on outputs corresponding to execution of the load cases on each of the plurality of designs of the tower, an optimized design.

[0007] In accordance with another aspect of the present invention, a method for optimizing a tower design comprises receiving, from a user, input data comprising plurality of parameters to model an initial geometry of a tower, the plurality of parameters being indicative of one or more physical parameters of the tower. The method includes generating a plurality of load cases for testing the initial geometry, each load case representing a different combination of loads to be applied to the initial geometry. The method further includes providing to apply, iteratively, each of the load cases to the initial geometry to determine if the initialgeometry withstands the different combination of loads. Based on the determination that the initial geometry withstands the different combination of loads, the method includes sequentially altering at least one physical parameter of the one or more physical parameters of the initial geometry to obtain a plurality of designs of the tower. The method also includes determining a set of load cases corresponding to each of the plurality of designs of the tower, and providing to apply, iteratively, the set of load cases to the respective plurality of designs of the tower. The method further includes identifying, based on outputs corresponding to execution of the load cases on each of the plurality of designs of the tower, an optimized design.

[0008] As per the embodiments of the present subject matter, the tower design optimization system enables efficient identification and evaluation of optimal tower configurations.

[0009] The present subject matter thus facilitates streamlined optimization in the tower design process by systematically altering physical parameters associated with a tower's performance without human intervention. As the system identifies and modifies the appropriate parameters, the overall tower optimization process is not just expedited but also made more efficient by reducing redundant calculations and potential oversights in design iterations.

[0010] Additional features and advantages are realized through the concepts of the present invention, including improved tower design management, reduced computational time, and enhanced structural efficiency. Other embodiments and aspects of the invention are described in detail herein and are considered a part of the claimed invention.BRIEF DESCRIPTION OF DRAWINGS

[0011] The detailed description is described with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawings to reference like features and components.

[0012] Figure 1 illustrates a block diagram of a computing environment for implementing example techniques for optimizing tower designs, in accordance with an example implementation of the present subject matter;

[0013] Figure 2 illustrates a system for implementing example techniques for optimizing tower designs, in accordance with an example implementation of the present subject matter;

[0014] Figure 3 illustrates a method for implementing example techniques for optimizing tower designs, in accordance with an example implementation of the present subject matter;

[0015] Figure 4A & 4B illustrates a flow diagram of a process for optimizing one or more physical parameters of the tower designs, in accordance with an example implementation of the present subject matter;

[0016] In the figures, the left-most digits of a reference number identify the figure in which the reference number first appears. The same numbers are used throughout the drawings to reference like features and components.DETAILED DESCRIPTION

[0017] The present subject matter relates to an optimization and construction of towers to achieve an efficient and cost-effective tower designs.

[0018] As mentioned above, designing the geometry of towers is a complex process that requires a high level of expertise and precision. A typical tower comprises a tower body, cage portion, cross arm, peak, body extension, leg extension, etc. Each component of the tower serves a specific function in the overall structure. The design of these components is contingent upon a variety of factors, including the intended load capacity, environmental conditions, cost, and regulatory requirements.

[0019] In a typical tower construction project, the complexity and scale of the design process are immense. For instance, a project may involve the design and construction of more than 300 individual towers. These towers may not be identical but may be categorized into 5 to 10 different types, each with its own specific design parameters and requirements. Moreover, each tower type has large numbersof members and parts. Project engineers must consider all possible combinations while determining the optimum configuration for each tower type.

[0020] Conventionally, the process of designing towers is a multi-step procedure. The initial step may involve manual design calculations based on specifications outlining the requirements for the towers, which may include one or more physical parameters, such as height, base width, intended load capacity, environmental conditions, cost, regulatory requirements, etc.

[0021] Following the initial design calculations, vector loads for the tower design are generated. Vector loads represent the forces that the tower will be subjected to, such as wind loads, ice loads, weight of the transmission lines, etc. These loads are calculated for various scenarios and conditions to ensure that the tower will be able to withstand them. Once the vector loads have been generated, an initial 3D concept of the tower's geometry is developed. This initial geometry provides a possible shape and size of the tower, as well as the potential arrangement of its components. These steps are performed using a geometry creation tool. Examples of such tools include, but are not limited, to TowGeom.

[0022] The initial design of the tower's geometry is then analysed and optimized using a Finite Element Analysis (FEA) software, an example of which is the widely used Powerline Systems (PLS), that aims to minimize the weight and cost of the tower while adhering to other constraints. Following the analysis, a Single Line Diagram (SLD) is generated of the tower design.

[0023] The optimization of tower geometry is an important aspect of the design process, aimed at achieving the maximum structural efficiency and cost savings. This involves careful evaluation of each component to ensure that the members are utilized to their full potential, thereby reducing waste and excess costs.

[0024] Different types of optimization strategy of tower designs can be adopted to minimize weight of the towers while adhering to other constraints. One optimization strategy involves ensuring that all members and bolts in the tower are fully utilized. Any steel member loaded to merely 20% of its capacity, for example, indicates a redundancy that increases both the weight and cost of the tower. With a typical tower comprising between 400 to 800 members, engineers are tasked withthe laborious job of going through each member to identify and eliminate such redundancies.

[0025] Another strategy of cost optimization is the iterative adjustment of the tower's patterns to find the combination that yields the lowest weight while still meeting load requirements. Additionally, in another example strategy, the basewidth of the tower can be altered within the constraints of the site to optimize costs. Increasing the base- width reduces the pressure on the footings of the tower, thereby decreasing the cost of the overall tower structure.

[0026] The optimization strategies mentioned above, while effective, are labour-intensive and time-consuming as they have to be performed manually. For instance, consider the base width optimization strategy. In this there can be more than 20 different base width combinations for a single tower out of 4-5 tower designs, in any large project. Each of these combinations requires numerous iterations to find the optimum base width that balances structural integrity and costeffectiveness.

[0027] To illustrate, it may be assumed that for each base width combination, it takes approximately 6 hours to generate an optimized tower design. This time includes the process of adjusting the base width, running in the Finite Element Analysis software, analyzing the results, and making further adjustments based on the analysis. Now, if this process is repeated for over 20 different base width combinations, the total time spent on just the base width optimization can be substantial.

[0028] This manual process not just demands a high level of expertise and precision, but also a considerable amount of time. Given the scale and complexity of tower building projects, where hundreds of towers may be involved, the time and effort spent on manual optimization can become a limiting factor. It restricts the number of iterations that can be performed and, consequently, the level of optimization that can be achieved.

[0029] After each optimization step, an analysis report is generated by the FEA software, which includes detailed information on each member and bolt of each section of the tower. This analysis report helps in identifying the exact members orbolts that may be over-stressed or under-utilized, allowing for targeted adjustments in the design to optimize the distribution of forces and the use of materials.

[0030] If the analysis report generated by the FEA software indicates that the members of the tower are understressed or not utilized efficiently, it signifies that the current design of the tower is not optimized. Understressed members suggest that the tower's design could be adjusted to make better use of the materials, thereby reducing the overall weight and cost of the tower. Similarly, inefficiently utilized members indicate that there is room for improvement in the arrangement and configuration of the tower's components.

[0031] In such cases, another design of the tower has to be created using the geometry creation tool with a modified arrangement of members. This new design is based on the insights gained from the PLS report and aims to address the identified inefficiencies. The new design may involve changes in the size, shape, or placement of the tower's members, or it may involve the use of different connection techniques.

[0032] Once the new design is created, it then goes through the process of optimization and testing, much like the initial design to evaluate the performance of the new design under various conditions for continuous refinement of the tower's design. This process of creating new designs based on the results of previous iterations and testing them for optimization is repeated until an optimized design is achieved. This optimized design is one that meets all the performance and safety requirements while also being as cost-effective as possible.

[0033] However, this iterative process of design, optimization, and testing for each of the different tower geometry is time-consuming and requires a high level of precision and expertise. For instance, using this conventional process, it typically takes around 15 days to design a tower. Within this timeframe, only a maximum of 70-80 iterations can be manually performed considering the time constraints.

[0034] Consequently, the number of iterations that can be performed is limited, which in turn limits the level of optimization that can be achieved. In other words, the traditional process may not yield the optimum design due to the constraints ofmanual input and time. This implies that there is a need for further optimization that is presently not realized due to these limitations. The level of optimization that could have been achieved for a tower is not reached, indicating a gap in the current design process.

[0035] Therefore, there is a need for a technique that allows to evaluate a multitude of design variations of the members of the tower automatically, thereby facilitating the creation of more efficient and cost-effective towers.

[0036] In accordance with the present subject matter, a method and system for optimizing design of towers is provided. In example implementations, the method and system of the present subject matter provides to solve the above-mentioned problems by providing for efficiently optimizing the design of the towers.

[0037] In accordance with an implementation, the optimizing the design of a tower involves receiving, from a user, input data comprising plurality of parameters to model an initial geometry of the tower. The plurality of parameters being indicative of one or more predetermined physical parameters of the tower. Further, a plurality of load cases for testing the initial geometry is generated to determine if the initial geometry withstands the different combinations of loads. Based on the determination that the initial geometry withstands the different combination of loads, optimizing the design comprises sequentially altering at least one of the one or more physical parameters of the initial geometry to obtain a plurality of designs of the tower. Further, a set of load cases corresponding to each of the plurality of designs of the tower is determined and is provided to be applied, iteratively, to the respective plurality of designs of the tower. Based on outputs corresponding to execution of the load cases on each of the plurality of designs of the tower, an optimized tower design is identified.

[0038] The present subject matter presents several advantages over conventional design processes. One of the primary benefits is the ability to quickly and efficiently evaluate large number of design variations in the tower geometry. This allows for utilizing more efficient and cost-effective tower configurations that may not be apparent through manual design processes. By identifying and eliminating underutilized or overstressed components, the present method ensuresthat materials are used more efficiently, which can result in a reduction of material costs. Thus, the present invention can lead to substantial cost savings. Additionally, the automated nature of the optimization process reduces the likelihood of human error, and the variability introduced by manual calculations.

[0039] The above-mentioned implementations are further described herein with reference to the accompanying figures. It should be noted that the description and figures relate to exemplary implementations and should not be construed as a limitation to the present subject matter. It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present subject matter. Moreover, all statements herein reciting principles, aspects, and embodiments of the present subject matter, as well as specific examples, are intended to encompass equivalents thereof.

[0040] Figure 1 illustrates a computing environment 100 for optimizing designs of towers in accordance with an implementation of the present subject matter.

[0041] In accordance with one example embodiment of the present subject matter, the computing environment 100 comprises three primary components, namely, a geometry creation system 102, an optimization system 104, and a finite element analysis (FEA) system 106.

[0042] The geometry creation system 102, the optimization system 104, and the FEA system 106 each have distinct functionalities and can be implemented on separate computing devices that are interfaced via a communication network to work in tandem to carry out the task of optimizing tower designs in some example implementations such as the one depicted in Figure 1. For example, the geometry creation system 102 may be implemented on a workstation equipped with geometry modelling software such as, but not limited to, TowGeom or AutoCAD, the optimization system 104 on a high-performance computing server running optimization algorithms, and the FEA system 106 on a dedicated analysis server with FEA software like Powerline Systems. These computing devices can rangefrom desktop computers, workstations, and servers to cloud-based computing resources.

[0043] While FIG. 1 does not depict this distributed architecture, in other example embodiments, the functionality of the three systems can be consolidated and implemented on a single physical computing device, such as a powerful workstation or server that is capable of handling the computational load of all three systems. Alternatively, any two of the systems can be combined into one physical computing device, with the third system remaining separate. This flexible architecture allows for scalability and adaptability to the specific requirements of the tower design optimization process.

[0044] In accordance with an example, the geometry creation system 102 is configured to create an initial geometry or a concept of the tower. The initial geometry is indicative of plurality of parameters indicating one or more predefined physical parameters of the tower, such as height, and base width. As mentioned previously, the initial geometry is based on the specific requirements of the tower, such as its intended load capacity, wind loads, and environmental conditions that the tower will be subjected to, and regulatory requirements the tower has to comply with. The geometry creation system 102 is equipped with multiple libraries, which may be predefined prior to creating the initial geometry. These libraries comprise multiple design elements that can be combined in numerous ways to form a tower geometry.

[0045] The geometry creation system 102 creates a 2D single line diagram (SLD) model of the tower, which is then used for further analysis and optimization. This SLD generated by the geometry creation system 102 serves as a preliminary concept or blueprint of the tower's structure. It provides a visual representation of the tower's initial geometry. In an example, the tower’s initial geometry is based on the predetermined height of the tower, calculated by the site engineers.

[0046] However, this initial SLD is not a rigid or final design. It does not specify specific quantities, such as the number of bolts, the number of members, or their precise dimensions. Instead, it offers a flexible framework that can be adjusted and optimized in subsequent stages of the design process.

[0047] As mentioned previously, this initial design is, however, not optimized as there can be members or bolts which are underutilized. The initial SLD serves as a conceptual starting point for making the complete geometry of the tower, which, while flexible, may include components that are not fully utilized in terms of their load-bearing capacities.

[0048] Once the initial geometry of the tower is created, the geometry creation system 102 interacts with the optimization system 104. The geometry creation system 102 provides the initial geometry data of the tower to the optimization system 104. The optimization system 104 uses this initial geometry data as an input for the iterative refinement of the tower design. The optimization system 104 is designed to perform a series of tests on the initial geometry of the tower, with the goal of optimizing the tower's structure for efficiency and cost-effectiveness.

[0049] For said testing, the optimization system 104 generates a plurality of load cases for testing the initial geometry created of the tower. Each load case represents a different combination of loads that the tower might be subjected to in its operational environment. These loads can include, but are not limited to, wind loads, ice loads, seismic loads, and the weight of the transmission lines. In the case of power transmission towers, the load cases also consider operational scenarios, such as the breaking of one or both transmission wires. The breaking of a transmission wire can cause a sudden shift in the load distribution on the tower, and the tower's design has to be robust enough to withstand such sudden changes in load. These operational scenarios are factored into the load cases to ensure that the tower's design is not just optimized for environmental conditions but also for potential operational challenges.

[0050] After the different combinations of load cases have been created, the optimization system 104 iteratively applies the load cases to the initial geometry of the tower. This is done to check whether the initial geometry of the tower is capable of withstanding high loads without compromising its structural integrity. Similarly, if the analysis reveals that few members or bolts of the tower are underutilized, it suggests that the design could be further optimized. Underutilization of members or bolts may indicate that the materials are not beingused to their full potential, which can lead to inefficiencies and increased costs. This iterative process is designed to thoroughly test the structural integrity of the initial geometry under a wide array of conditions. In each iteration, a specific load case is applied to the initial geometry, and the resulting stress distribution and deformation of the tower structure are analysed. This analysis is done by the FEA system 106, which provides valuable insights into how the initial tower geometry responds to the specific combination of loads represented by the load case.

[0051] In an example, in order to apply the load cases on the initial geometry in the FEA system 106, data pertaining to the plurality of load case generated by the optimization system 104, may need to be converted into a specific file format that is compatible with the FEA system 106. In some implementations, this format may be the .LCA file format. The optimization system 104 may be equipped with functionality to convert each of the plurality of load cases into the desired format, which can be easily read and analyzed by the FEA system 106.

[0052] To illustrate the operation of the systems by way of an example, the following scenario may be considered: once the initial geometry of the tower is obtained by the geometry creation system 102, the optimization system 104 generates a series of load cases. For each load case, the optimization system 104 initiates an iterative process, applying the load case to the tower's geometry and analyzing the response. During each iteration, the optimization system 104 adjusts the geometry of the tower, such as by altering member sizes or altering the bolt numbers, to better withstand the applied loads. After each adjustment, the FEA system 106 evaluates the revised design and calculates stress distributions, deformations, and other relevant structural responses to determine if the modified design meets the performance criteria.

[0053] A threshold is set in the FEA system 106 for different component utilizations, for example, at 90 percent, meaning that the iterative process may continue until the member utilization reaches close to 90 percent for all specific load cases. If the threshold is not met, the optimization system 104 makes further adjustments to the tower’s geometry and the process repeats. This ensures that the majority of the tower's structural components are effectively utilized, contributingto the overall strength and stability of the tower without excess material use. This iterative process is repeated for each load case generated by the optimization system 104. With each iteration, the tower's design is progressively refined. The system continues to cycle through the load cases, adjusting and re-evaluating the design until an optimized geometry of the tower is achieved that can efficiently withstand the plurality of load cases.

[0054] Once an optimized initial geometry of the tower is achieved for the plurality of load cases, the optimization system 104 may assess the corresponding optimization efficiency. This assessment may include calculating the cost associated with the optimized design. However, there may be alternative designs that exist which can withstand the same load cases with greater optimization efficiency. Consequently, the optimization system 104 undertakes additional steps to evaluate all the alternative design trials. This evaluation involves comparing the cost-effectiveness and structural performance of the alternative designs against the optimized initial geometry.

[0055] Subsequently, the optimization system 104 sequentially alters at least one physical parameter of the one or more physical parameters of the initial geometry to obtain a plurality of designs of the tower based on the determination that the initial geometry withstands the different combination of loads. The alteration of these physical parameters is done in a sequential manner, meaning that one parameter is altered at a time. This allows for a systematic and controlled approach to the optimization process, ensuring that the impact of each alteration can be accurately assessed.

[0056] Each of these alterations results in a new design for the tower, and for each of the plurality of designs of tower, the optimization system 104 determines a set of load cases and provides to apply, iteratively, the set of load cases to the respective plurality of designs of the tower. This iterative process of alteration in optimization system 104 and testing in FEA system 106 continues until a state of convergence is reached. The convergence is a point where an optimized design is identified based on the outputs corresponding to the execution of the load cases on each of the plurality of designs of the tower, which is capable of withstanding allthe different combinations of loads while also being cost-effective and efficient. For a detailed explanation of the implementation and operation of the optimization system 104 to perform optimization of the geometry of the tower, reference is made to Figure 2.

[0057] Figure 2 illustrates the optimization system 104 for optimizing the geometry of a tower, in accordance with an example implementation of the present subject matter.

[0058] The optimization system 104 implements a technical process for optimizing tower designs. It analyzes the initial tower geometry, generates multiple load cases, and employs an iterative optimization algorithm to refine the tower design. The optimization system 104, as described herein, addresses the technical limitations of conventional design methods, which often struggle to efficiently explore the vast design space and balance multiple competing objectives such as structural integrity, cost-effectiveness, and material utilization.

[0059] As depicted in Figure 2, in an example implementation, the present optimization system 104 may include at least one processor 202 and a memory 204 coupled to the processor 202. In an example, the processor 202 may be implemented as microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and / or any devices that manipulate signals based on operational instructions. The memory 204 may include any computer-readable medium known in the art including, for example, volatile memory (e.g., RAM), and / or non-volatile memory (e.g., EPROM, flash memory, etc.). The memory 204 may also be an external memory unit, such as a flash drive, a compact disk drive, an external hard disk drive, or the like.

[0060] As also depicted in Figure 2, in an example implementation, interface(s) 206 may be coupled to the processor 202. The interface(s) 206 may include a variety of software and hardware interfaces that allow interaction of the system 102 with other communication and computing devices, such as network entities, external repositories, and peripheral devices, such as the FEA system 106.The interface(s) 206 may also enable the coupling of components of the system 104 with each other.

[0061] The optimization system 104 may also comprise module(s) 208 and data 220 coupled to the processor 202. In one example, the module(s) 208 and data 220 may reside in the memory 204.

[0062] In an example implementation, the data 222 may comprise initial geometry data 224, load cases data 226, pattern library 228, simulation data 230, and other data 232. The module(s) 208 may include routines, programs, objects, components, data structures, and the like, which perform particular tasks or implement particular abstract data types. The module(s) 208 may further include modules that supplement applications on the optimization system 104, for example, modules of an operating system. The module(s) 208 further includes modules that implement certain functionalities of the optimization system 104, such as processing the information received from the users, such as the site engineers. The data 222 serves, amongst other things, as a repository for storing data that may be fetched, processed, received, or generated by one or more of the module(s) 208. The module(s) 208 may include a geometry module 210, a load case generation module 212, an iteration module 214, a design alteration module 216, an optimization analysis module 218, and other module(s) 220. The other module(s) 220 may include programs or coded instructions that supplement applications and functions, for example, programs in the operating system of the optimization system 104.

[0063] In operation, in an example implementation of the present subject matter, to initiate the optimization process of the tower, the optimization system 104 receives an initial geometry data 224 from the geometry creation system 102. The initial geometry data 224 comprises indicative values of one or more predefined physical parameters of the tower, such as height, and base width, which can later be altered for optimization if required. After receiving the initial geometry data 224, the optimization system 104 utilizes the FEA system 106 for analyzing the initial geometry of the tower. This analysis process may involve providing the initial geometry data 224 to the FEA system 106 and receiving analysis resultsback from the FEA system 106. This back-and-forth exchange of data between the optimization system 104 and the FEA system 106 may continue iteratively until an optimized design of the tower is created.

[0064] The optimization system 104 comprises a geometry module 210, which is coupled to the at least one processor 202. The geometry module 210 is to obtain an initial geometry of the tower, the geometry being indicative of one or more physical parameters of the tower. The one or more physical parameters may include at least one of tower members, bolts, patterns, and a base width of the tower. For instance, the geometry module 210 may obtain the initial geometry of the tower from the geometry creation system 102 and store the same as the initial geometry data 224 in data 222 of the optimization system 104. As explained previously, the initial geometry may be in the form of SLD, which serves as conceptual representation of the tower’s structure, and is used as an input from the geometry creation system 102. This initial geometry data 224 may include information about the tower's height, base width, and other physical parameters that define the tower’s structure. It should be noted that these parameters in the initial geometry are not fixed or rigid, but rather serve as starting points that may be adjusted and optimized during the further processes.

[0065] In an example, the tower's height may be initially set based on preliminary site requirements. However, this height may be modified to achieve better structural performance or to meet specific load-bearing needs. Similarly, the base width, which may be initially determined by site constraints or standard practices, may be altered to improve stability or reduce material weight. The initial geometry data 224 may also include other physical parameters such as the number and arrangement of structural members, the types and sizes of bolts used, pattern configurations, and the overall shape of the tower. These parameters, like height and base width, may also be subject to modification during the optimization process.

[0066] In an example, the geometry module 210 may also comprise a preconfigured library of 500-600 patterns, herein referred to as pattern library 228. The ‘patterns’ refer to different configurations of members and bolts, includingtheir arrangement within the tower structure to achieve different levels of strength, stability, and efficiency in the tower design. This predefined pattern library 228 may be created by structural engineers and experts and stored as pattern library 228 in data 222 of the optimization system 104, providing a wide range of structural configurations that can be applied to the tower design. By leveraging these pre- established configurations, the optimization system 104 may avoid the need to generate tower designs or perform iterations from scratch for each optimization task.

[0067] In an example, during the optimization process, the user may be provided with an option to select patterns from the pattern library 228. This selection allows the optimization system 104 to carry out iterations on these chosen patterns, without having to create such patterns each time a set iteration is to be run. For instance, the user may select a subset of 5-8 patterns. By focusing on these selected patterns, the optimization system 104 can more efficiently explore design variations within the chosen structural configurations, leading to faster convergence on the optimized tower design. Also, since these 5-8 patterns are already pre-stored, the optimization system 104 does not have to create them every time by defining the different parameters that constitute the pattern. This prestorage of patterns may significantly reduce computational time and resources, as the system can directly access and utilize these pre-defined patterns rather than generating them anew for each iteration.

[0068] The optimization system 104 further comprises a load case generation module 212 coupled to the at least one processor 202. The load case generation module 212, which may also be referred as ‘LCG’ or ‘Load Case Generator’ in an example, is to generate load case data 226 comprising plurality of load cases for testing the initial geometry of the tower created by the tower creation system 102. Each load case within the load case data 226 represents a different combination of loads to be applied to the physical parameters of the initial geometry of the tower created by the geometry creation system 102. These physical parameters may include the tower's height, base width, member sizes, bolt configurations, and overall structural arrangement. In an example, the load case generation module 212may generate the load case data 226 comprising plurality of load cases to test the initial geometry of the tower, wherein the initial geometry may comprise one or more patterns from the pattern library 228.

[0069] As explained previously, the load cases typically represent combinations of environmental and operational forces that the tower must withstand. This may include factors such as wind loads from different directions, ice accumulation, seismic activity, and the weight and tension of transmission lines. For example, it can assess whether the current tower members withstand the combined forces or whether the tower members are utilized efficiently. By evaluating the tower's response to various load cases, the optimization system 104 may allow modifications to improve both the structural performance and material efficiency of the design.

[0070] Further, the optimization system 104 comprises an iteration module 214 coupled to the at least one processor 202. The iteration module 214 is to provide the plurality of load cases to FEA system 106 for iterative application of each of the load cases to the initial geometry of the tower to determine if the initial geometry withstands the different combination of loads.

[0071] In an example implementation, the iteration module 214 may be configured to receive simulation data 230, comprising the analysis results, from the FEA system 106. The simulation data 230 may comprise detailed information about the tower's performance under various load cases, including stress distributions, deformations, and potential failure points for all tower members. In an example, the simulation data 230 may also provide data regarding the optimized weight of the tower, maximum compression forces, and other critical structural parameters. By processing this data, the iteration module 214 may evaluate the tower design's performance and determine whether optimization is necessary. This capability allows for a thorough assessment of the tower's structural integrity and efficiency, potentially leading to more refined and cost-effective designs.

[0072] In operation, when the iteration module 214 provides the load case data to the FEA system 106, it initiates a series of simulations on one or more physical parameters of the tower. In each simulation, the FEA system 106 applies each loadcase from the load case data to each of the one or more physical parameters of the tower, analyzing how the individual components within these one or more physical parameters respond to the applied loads. This may involve re-evaluating the stress distribution, deformation, and potential failure points of each component within the one or more physical parameters of the tower, allowing for a comprehensive assessment of their performance under various load conditions.

[0073] The iterative nature of this process enables a detailed evaluation of one or more physical parameters of each tower which contributes to the overall structural integrity. For each load case, the FEA system 106 calculates the structural response of all tower members individually, with the iteration module 214 collecting and interpreting these results. This analysis allows the iteration module to determine the utilization of each of one or more physical parameters of the tower up to its strength capacity, identifying scope of optimization. For example, the iteration module 214 may evaluate the stress levels in each member relative to its maximum allowable stress, ensuring efficient material usage.

[0074] In an example, the optimization process may employ a set threshold, such as 70% utilization, for tower members. Members falling below this threshold may be flagged for reconfiguration to enhance overall structural efficiency. Based on the analysis results, adjustments may be required to be made to physical parameters of the underutilized members, bolts, and pattern configurations of the initial tower geometry to optimize the design. These adjustments may include modifying the size, shape, or arrangement of underutilized members, altering bolt specifications or placements, and reconfiguring structural patterns to achieve more efficient load distribution and material usage. The adjustments may be continued until an optimal balance between structural integrity and cost-effectiveness may be achieved.

[0075] A design alteration module 216 of the optimization system 104 is configured to sequentially alter at least one physical parameter of the initial geometry. In an example, the adjustments for optimizing tower members may involve several steps. The design alteration module 216 may adjust the section size based on the current utilization level of each member. This process may includeincreasing the size of over-stressed members or reducing the size of under-utilized members to achieve optimal material usage. In an example, the design alteration module 216 may select appropriate curve numbers for tower members corresponding to predefined curve codes and slenderness ratio limits, which may aid in determining the buckling strength of compression members under various loading conditions.

[0076] In an example, for bolt optimization, the design alteration module 216 may select appropriate bolt sizes and materials based on the current utilization level of the bolts. This may include analyzing the shear and tensile forces acting on each bolt and adjusting bolt specifications to ensure they can withstand these forces and are utilized efficiently. The design alteration module 216 may consider factors such as bolt diameter, material strength, and spacing to achieve an optimal balance between structural integrity and cost-effectiveness.

[0077] In an example, in pattern optimization, the design alteration module 216 may run iterations of different patterns selected from a subset of the pattern library 228 in the FEA system 106 to identify the most efficient arrangement of members and bolts. The module may evaluate each pattern based on its performance under the applied load cases, its material efficiency, and its overall cost-effectiveness.

[0078] In an example, the design alteration module 216 may allow users to select a subset of patterns from the pattern library 228. The design alteration module 216 may then iteratively apply these user-selected patterns while applying a specific load case to generate an optimized tower design. This iterative process may involve systematically altering the arrangement of structural members, bolt placements, and other design elements within the constraints of the selected patterns until the initial design of the tower is not completely optimized. For each iteration, the module may evaluate how well the resulting tower design withstands the applied loads. Through this iterative process, an optimized initial geometry of the tower may be achieved. This optimized geometry may balance structural integrity, material efficiency, and cost-effectiveness while meeting the required load-bearing capabilities.

[0079] Once an optimized initial geometry of the tower is achieved, there may be other designs of the tower with slightly different physical parameters that could potentially offer improved performance or cost-effectiveness. For example, designs having slight variations in tower height or base width may yield designs that better meet project requirements or offer additional optimization opportunities. To explore these possibilities, the design alteration module 216 is configured to vary at least one physical parameter within a predefined range and incrementally adjust the at least one physical parameter by a predefined increment. This allows for creation of more than one design other than the initial design of the tower has been optimized. Each new design represents a unique configuration of the tower's physical parameters, such as base width, member sizes, bolt arrangements, or pattern selections.

[0080] For instance, in the case of base width variation, the design alteration module 216 may operate within a predefined range of 6 m to 9 m, applying a predefined increment of 0.5 m. This results in the generation of multiple tower designs with base widths of 6.0 m, 6.5 m, 7.0 m, 7.5 m, 8.0 m, 8.5 m, and 9.0 m. The design alteration module 216 may apply these variation to analyze how changes in base width affect the tower's overall performance and efficiency. For each generated design, the design alteration module 216 may initiate a new round of analysis using the load case generation module 212 and the iteration module 214. This process allows the optimization system 104 to evaluate how different base widths impact the tower's stability, material requirements, and if the tower members are efficiently utilized.

[0081] In some implementations, the design alteration module 216 may simultaneously adjust multiple parameters. For instance, while varying the base width, the design alteration module 216 may also modify other aspects such as the tower height, member sizes, or bolt configurations.

[0082] In an example, for each of the plurality of designs of tower obtained by the design alteration module 216, the load cases generation module 212 again generates load case data 226 comprising a set of load cases to be applied on each of the plurality of designs. The load case generation module 212 may considervarious factors when determining the set of load cases for each design. These factors may include the altered physical parameters of the tower, such as height, base width, or member configurations. For example, a taller tower design may require additional load cases to account for increased wind loads at higher elevations.

[0083] Once the load case generation module 212 has determined the appropriate set of load cases for each tower design, the iteration module 214 may provide these sets to the finite element analysis system 106. The finite element analysis system 106 may then iteratively apply the set of load cases to the respective plurality of designs of the tower. This iterative application allows for a thorough evaluation of each design's performance under various stress conditions.

[0084] During this process, the iteration module 214 coordinates the application of load cases and the collection of simulation data 230 comprising the analysis results from the finite element analysis system 106. For each design iteration, the iteration module 214 iteratively applies the determined load cases, analyzes the structural response, and compiles the results. In an example, for each alteration of one or more physical parameters in the initial design and subsequent designs of the tower, the output generated by the FEA system 106 may be stored as simulation data 230 in data 222. For each of the multiple designs, the output generated by the FEA system 106 may comprise optimized weight, maximum compression, and maximum uplift and so on.

[0085] Further, the optimization module 104 comprises an optimization analysis module 218 coupled to the at least one processor. The optimization analysis module 218 is to identify, based on outputs corresponding to execution of the load cases on each of the initial design and plurality of designs of the tower, an optimized design. The optimization analysis module 218 analyzes the outputs from the FEA system 106 for each design variation, considering factors such as structural integrity, material efficiency, and cost-effectiveness.

[0086] In an example, the optimization analysis module 218 may compare the performance of each design of the tower against predefined criteria. These criteria may include factors, such as overall weight, material utilization efficiency, andmaterial cost. The module also considers the ability of each design to withstand all the applied load cases, ensuring that the final optimized design meets or exceeds all safety and performance requirements.

[0087] By using the present optimization techniques, the optimization system 104 can evaluate and compare hundreds or even thousands of design variations. This capability allows it to explore the design space far more thoroughly than would be possible through conventional techniques. The identified optimized design indicates a tower structure that is not only capable of withstanding all specified load cases but also optimized for factors such as material usage, construction cost, and overall efficiency.

[0088] Reference is made to Figure 3 that illustrates a method for optimizing tower designs, in accordance with an example implementation of the present subject matter.

[0089] The order in which the method 300 is described is not intended to be construed as a limitation, and any number of the described method blocks may be combined in any order to implement method 300, or an alternative method. Furthermore, the method 300 may be implemented by processor(s) or computing device(s) through any suitable hardware, non-transitory machine -readable instructions, or combination thereof.

[0090] The method 300 for optimizing the design of the tower comprises various steps as illustrated below.

[0091] At block 302, the method 300 comprises receiving from a user, input data comprising plurality of parameters to model an initial geometry of a tower, the plurality of parameters being indicative of one or more physical parameters of the tower. The initial geometry may be in a form of a single line diagram (SLD) representing the conceptual structure of the tower. As explained previously, the initial geometry may include, but is not limited to, information about the tower's height, base width, member configurations, and overall structural layout. The one or more physical parameters indicated by the initial geometry may comprise structural elements such as tower members, bolts, and patterns, as well as dimensional attributes like the tower's height and base width. However, it shouldbe noted that this initial geometry serves as a starting point for the optimization process and may be subject to modifications and refinements in subsequent steps of the method. The obtained initial geometry may be used as input for further analysis and optimization processes.

[0092] At block 304, the method 300 comprises generating a plurality of load cases for testing the initial geometry, each load case representing a different combination of loads to be applied to the initial geometry. The load cases may be generated based on various environmental and operational factors that the tower may encounter during its lifetime. These factors may include, but are not limited to, wind loads from different directions and intensities, ice accumulation on the tower structure and transmission lines, seismic activities of varying magnitudes, and the weight and tension of the transmission lines under different operational conditions.

[0093] In an example implementation, the method may utilize predefined load case templates that are customized based on the specific requirements of the tower design and its intended location. The generation of load cases may involve combination of these various factors. For instance, the method may create load cases that simulate the simultaneous occurrence of high winds and ice accumulation, or the combination of seismic activity with maximum operational loads on the transmission lines.

[0094] At block 306, the method 300 comprises applying, iteratively, each of the load cases to the initial geometry to determine if the initial geometry withstands the different combination of loads. This iterative application process may involve subjecting the initial geometry of the tower to each generated load case, evaluating the structural response, and assessing the tower's ability to withstand the applied loads. In an example, the method may simulate the effects of each load case on the tower structure.

[0095] For each iteration, calculations may be performed to determine stress distributions, deformations, and potential failure points throughout the tower's components. If the initial geometry successfully withstands a particular load case, the method may proceed to the next load case in the sequence. However, if theanalysis reveals that the structure fails to meet the required performance criteria for any load case, the method may flag this result for further optimization steps.

[0096] At block 308, the method 300 comprises, based on the determination that the initial geometry withstands the different combination of loads, sequentially altering at least one physical parameter of the one or more physical parameters of the initial geometry to obtain a plurality of designs of the tower. This step may involve a systematic approach to refining the tower design for improved efficiency and performance. The sequential alteration process may begin by identifying the physical parameters that are most influential in the tower's structural performance. These parameters may include, but are not limited to, member sizes, bolt configurations, pattern configurations, and overall tower dimensions such as height and base width.

[0097] For each identified parameter, the method may implement a series of controlled modifications. These modifications may be applied incrementally, with each change carefully evaluated for its impact on the tower's overall performance. The alterations may be guided by predefined rules or optimization algorithms that consider factors such as material efficiency, structural integrity, and costeffectiveness.

[0098] At block 310, the method 300 comprises determining a set of load cases corresponding to each of the plurality of designs of the tower. This involves identifying and selecting appropriate load cases for each modified tower design generated in the previous step. The set of load cases for each design may be derived from the initial load cases used to test the original geometry, but they may be adjusted or refined based on the specific characteristics of each new design. For each modified tower design, the method may analyse its unique structural properties, such as changes in height, base width, member configurations, or material properties. Based on these characteristics load cases that are most relevant for that particular design may be obtained.

[0099] At block 312, the method 300 comprises providing to apply, iteratively, the set of load cases to the respective plurality of designs of the tower. This involves systematically subjecting each modified tower design to its correspondingset of load cases determined in the previous step. The iterative application process allows for a comprehensive evaluation of how each design variant performs under various loading conditions.

[0100] For each design iteration, the method 300 may simulate the effects of the load cases on the tower structure. These simulations calculate stress distributions, deformations, and potential failure points throughout the tower's components, providing detailed insights into the structural behavior of each design under different loading scenarios.

[0101] During each iteration, the method may evaluate specific performance criteria, such as maximum stress levels, weight, and material costs. These calculated values are compared against predefined thresholds to determine if the tower is optimized. The results of each iteration are recorded and stored, creating a performance profile for each design variant across all applied load cases. This detailed dataset allows for quantitative comparisons between different design iterations, facilitating the identification of the most promising design solutions.

[0102] At block 314, the method 300 comprises identifying, based on outputs corresponding to execution of the load cases on each of the plurality of designs of the tower, an optimized design. This may involve analysing and comparing the performance data collected from the iterative application of load cases to each design variant. This analysis may include evaluating performance indicators such as overall structural integrity, material efficiency, and cost-effectiveness.

[0103] The optimized design identified through this process represents the best balance of structural performance, cost-effectiveness, and compliance with project requirements among all the evaluated design variants.

[0104] By employing the present iterative and systematic approach, the method allows for obtaining a more efficient tower design that might be overlooked in conventional tower design processes. This may enable the utilization of more efficient and cost-effective tower configurations that may not be apparent through manual design processes. By identifying and eliminating underutilized or overstressed components, the present method ensures that materials are used more efficiently, which can result in a reduction of material costs. Additionally, theoptimized designs can lead to lower manufacturing and assembly costs due to the streamlined number of components and improved ease of construction. Thus, the present invention can lead to substantial cost savings while also reducing the likelihood of human error.

[0105] Reference is made to Figure 4A & 4B that illustrates a flow diagram of a process for optimizing one or more physical parameters of the tower designs, in accordance with an example implementation of the present subject matter.

[0106] The order in which the method 400 is described is not intended to be construed as a limitation, and any number of the described method blocks may be combined in any order to implement method 400, or an alternative method. Furthermore, the method 400 may be implemented by processor(s) or computing device(s) through any suitable hardware, non-transitory machine -readable instructions, or combination thereof.

[0107] Referring to Figure 4A & 4B, at block 402, an initial geometry of a tower is obtained, for example, from the geometry creation system 102. As explained previously, in order to create the initial geometry, an input data is received from a user. In an example, the input data comprises plurality of parameters to model the initial geometry of a tower. The plurality of parameters may be indicative of one or more physical parameters of the tower. The initial geometry may be in a form of a single line diagram (SLD) representing the conceptual structure of the tower. The initial geometry may include, but is not limited to, information about the tower's height, base width, member configurations, and overall structural layout. The one or more physical parameters indicated by the initial geometry may comprise structural elements such as tower members, bolts, and patterns, as well as dimensional attributes like the tower's height and base width.

[0108] At block 404, a plurality of load cases are generated for testing the initial geometry created of the tower. As explained previously, each load case represents a different combination of loads to be applied to the physical parameters of the initial geometry of the tower. These physical parameters may include thetower's height, base width, member sizes, bolt configurations, and overall structural arrangement.

[0109] At block 406, the each of the plurality of load cases generated in the previous step are applied iteratively to the initial geometry of the tower. This is done to check whether the initial geometry of the tower is capable of withstanding high loads without compromising its structural integrity. As explained previously, if the analysis reveals that few members or bolts of the tower are underutilized, it suggests that the design could be further optimized. Underutilization of members or bolts may indicate that the materials are not being used to their full potential, which can lead to inefficiencies and increased costs. This iterative process is designed to thoroughly test the structural integrity of the initial geometry under a wide array of conditions.

[0110] At block 408, an assessment is made by the FEA system 106 as to whether the utilization of any of the tower members is close to a predefined threshold. If it is determined that the utilization of any of the tower members is not close to the predefined threshold, the process may proceed to block 410. However, if at block 408 it is determined that the utilization of any of the tower member is close to the predetermined threshold, the process may proceed directly to block 412.

[0111] At block 410, the section size of each of the tower members is iterated and adjusted based on a current utilization level of the tower members. Further, the appropriate curve numbers for each of the tower members are selected that correspond to predefined curve codes and slenderness ratio limits to obtain an optimized tower member configuration replacing the underutilized pattern configuration, resulting in a more efficient use of materials and improved overall structural performance of the tower. By adhering to these predefined limits, the process may ensure that each member maintains its structural stability while optimizing its dimensions.

[0112] At block 412, the initial geometry of the tower is obtained where all the tower members are utilized to the predefined threshold. For example, the predefined threshold may be set at a certain percentage, such as 90% of eachmember's load-bearing capacity. If any members are found to be underutilized, their dimensions or properties may be adjusted to bring their utilization closer to the threshold. This process may help optimize material usage and overall structural efficiency. The initial geometry obtained at this stage may serve as a starting point for further refinement and optimization in subsequent steps of the tower design process.

[0113] Simultaneously to the assessment made at the block 408, at block 414, another assessment is made as to whether the utilization of any of the bolts close to the predefined threshold. If it is determined that the utilization of any of the bolts is not close to the predefined threshold, the process may proceed to block 416. However, if at block 414 it is determined that the utilization of any of the bolts is close to the threshold, the process may proceed directly to block 418.

[0114] At block 416, the appropriate bolt sizes and materials based on the current utilization level of the bolts may be selected to replace the underutilized bolt. As explained previously, this may include analyzing the shear and tensile forces acting on each bolt and adjusting bolt specifications to ensure they can withstand these forces and are utilized efficiently. The factors such as bolt diameter, material strength, and spacing may be considered to achieve an optimal balance between structural integrity and cost-effectiveness.

[0115] At block 418, an initial geometry of the tower may be obtained where all the bolts are utilized close to the predefined threshold. For example, the predefined threshold may be set at a certain percentage, such as 80% of each bolt's load-bearing capacity. If any bolts are found to be underutilized, their specifications or arrangements may be adjusted to bring their utilization closer to the threshold. This process may help optimize material usage and overall structural efficiency.

[0116] Simultaneously to the determination made at the blocks 408 and 414, at block 420, another assessment is made as to whether the utilization of any of the pattern configurations is close to a predefined threshold. If it is determined that the utilization of any of the pattern configurations is not close to the predefined threshold, the process may proceed to block 422. However, if at block 420, it isdetermined that the utilization of any of the pattern configuration is close to the predetermined threshold, the process may proceed directly to block 424.

[0117] At block 422, different tire configuration selected from a subset of a pattern library are iterated and applied to replace the underutilized pattern configuration. This involves evaluating various structural patterns from a predefined library to identify the most efficient arrangement for the tower. As explained previously, the pattern library 228 may be created by structural engineers and experts, providing a wide range of structural configurations that can be applied to the tower design. Thereby each pattern configuration is evaluated based on its performance under the applied load cases, its material efficiency, and its overall cost-effectiveness.

[0118] At block 424, an initial geometry of the tower may be obtained where all pattern configurations are utilized close to the predefined threshold. This may involve analyzing the utilization levels of various pattern configurations within the tower structure and making adjustments to ensure optimal use of materials and structural efficiency. The predefined threshold may be set at a certain percentage, such as 85% of each pattern's optimal performance capacity. If any pattern configurations are found to be underutilized, their arrangement or composition may be modified to bring their utilization closer to the threshold. This process may help balance the load distribution across the tower structure, potentially improving overall stability and reducing material waste.

[0119] At block 426, an optimized initial design of the tower may be obtained that withstands each of the plurality of load cases. This optimized design, where each of the plurality tower members, bolts, and pattern configurations are optimized, may be the result of the subsequent optimization processes that occurred at blocks 410, 416, and 422. The design at this stage may incorporate the optimized tower members from block 412, the optimized bolt configurations from block 418, and the optimized pattern configurations from block 424. This result in a tower design that efficiently utilizes materials, effectively distributes loads, and meets all structural requirements while potentially reducing overall costs.

[0120] At block 428, after the optimized initial design of the tower is obtained, the one or more physical parameters of the initial geometry is altered sequentially to obtain a plurality of designs of the tower. This step may generate multiple tower designs, each representing a unique configuration of physical parameters such as base width, member sizes, bolt arrangements, or pattern selections. As explained previously in an example, in base width variations, a range of 6 m to 9 m, using 0.5 m increments may be operated. This may produce plurality of tower designs with base widths of 6.0 m, 6.5 m, 7.0 m, 7.5 m, 8.0 m, 8.5 m, and 9.0 m.

[0121] At block 430, a set of load cases corresponding to each of the plurality of designs may be determined. This step involves identifying and selecting appropriate load cases for each modified tower design generated in the previous step. As explained previously, various factors may be considered when determining the set of load cases for each design. These factors may include the altered physical parameters of the tower, such as height, base width, or member configurations. For example, a taller tower design may require additional load cases to account for increased wind loads at higher elevations.

[0122] At block 432, the set of load cases are provided to apply iteratively to the to the respective plurality of designs of the tower. This iterative process continues until a state of convergence is reached. The convergence is a point where an optimized design is identified based on the outputs corresponding to the execution of the load cases on each of the plurality of designs of the tower, which is capable of withstanding all the different combinations of loads while also being cost-effective and efficient.

[0123] At block 434, identifying, based on outputs corresponding to execution of the load cases on each of the plurality of designs of the tower, an optimized design may involve analyzing and comparing the performance data collected from the iterative application of load cases to each design variant. As explained previously, this analysis includes evaluating performance indicators such as overall structural integrity, material efficiency, and cost-effectiveness. The optimized design identified through this process may represent a balance of structuralperformance, cost-effectiveness, and compliance with project requirements among the evaluated design variants.

[0124] Thus, the methods and systems of the present subject matter streamline the tower design processes. By employing an iterative and systematic approach, the present optimization techniques allow for evaluating a significantly larger number of design variations in a shorter time frame, which may lead to discover more efficient and cost-effective tower configurations. Additionally, by identifying and eliminating underutilized or overstressed components, the optimization may enable more efficient use of materials, potentially resulting in reduced material costs and improved overall structural performance.

[0125] While specific implementations of the optimization system 104 have been discussed, it is to be understood that the appended claims are not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as example implementations for obtaining a more efficient tower design that could be overlooked in conventional tower design processes.

Claims

AMENDED CLAIMS received by the International Bureau on 06 April 2026 (06.04.2026)I / We Claim:

1. A method (300) for optimizing a tower design, comprising: receiving (302), from a user, input data comprising plurality of parameters to model an initial geometry of a tower, the plurality of parameters being indicative of one or more physical parameters of the tower; generating (304) a plurality of load cases for testing the initial geometry, each load case representing a different combination of loads to be applied to the initial geometry; providing to apply (306), iteratively, each of the load cases to the initial geometry to determine if the initial geometry withstands the different combination of loads; based on the determination that the initial geometry withstands the different combination of loads, optimizing the one or more physical parameters of the initial geometry by altering each until a predefined threshold of utilization is reached for the respective physical parameter to obtain an optimized initial design; sequentially altering (308) at least one physical parameter of the one or more physical parameters of the optimized initial design to obtain a plurality of designs of the tower; determining (310) a set of load cases corresponding to each of the plurality of designs of the tower; providing to apply (312), iteratively, the set of load cases to the respective design of the plurality of designs of the tower; and identifying (314), based on outputs corresponding to execution of the load cases on each of the plurality of designs of the tower, an optimized design.

2. The method of claim 1, wherein the one or more physical parameters include at least one of tower members, bolts, patterns, and a base width of the initial geometry of the tower.

3. The method of claim 2, wherein optimizing the tower members, the bolts, and the patterns of the initial geometry comprises:optimizing the tower members by adjusting section size of the tower members based on a current utilization level of the tower members, and selecting curve numbers for the tower members that correspond to predefined curve codes and slenderness ratio limits; optimizing the bolts by selecting bolt sizes and materials based on a current utilization level of the bolts; and optimizing the patterns by conducting iterations of different patterns selected from a subset of a pattern library.

4. The method of claim 1, further comprising generating an output summary after each iteration of executing the load cases for the initial and the plurality of updated tower designs, the output summary comprising details of weight of the tower and foundation forces for the respective iteration.

5. The method of claim 1, wherein sequentially altering the at least one physical parameter of the optimized initial design continues until a state of convergence is reached, the convergence being a point where the tower design is optimized for cost efficiency.

6. The method of claim 1, wherein sequentially altering the at least one physical parameter of the optimized initial design comprises varying the at least one physical parameter within a predefined range and incrementally adjusting the at least one physical parameter by a predefined increment.

7. The method of claim 2, wherein altering the at least one physical parameter of the optimized initial design comprises optimizing the base width of the tower, wherein optimizing the base width comprises modifying dimensions of the base width of the optimized initial design within a predefined range of dimensions.

8. A system (104) to optimize a tower design, comprising: at least one processor (202);a memory (204) in communication with the at least one processor (202); a geometry module (210) coupled to the at least one processor (202), to receive from a user, input data comprising plurality of parameters to model an initial geometry of a tower, the plurality of parameters being indicative of one or more physical parameters of the tower; a load case generation module (212) coupled to the at least one processor (202), to generate a plurality of load cases for testing the initial geometry, each load case representing a different combination of loads to be applied to the initial geometry; an iteration module (214) coupled to the at least one processor (202), to provide the plurality of load cases to a finite element analysis (FEA) system (106) for iterative application of each of the load cases to the initial geometry to determine if the initial geometry withstands the different combination of loads; a design alteration module (216) coupled to the at least one processor (202), based on the determination that the initial geometry withstands the different combination of loads, to optimize the one or more physical parameters of the initial geometry by altering each until a predefined threshold of utilization is reached for the respective physical parameter to obtain an optimized initial design, and to sequentially alter at least one physical parameter of the one or more physical parameters of the optimized initial design to obtain a plurality of designs of the tower, wherein the load case generation module (212) is to determine a set of load cases corresponding to each of the plurality of designs of the tower, and the iteration module (214) is to provide the set of load cases to the FEA system (106) for iterative application of the set of load cases to the respective design of the plurality of designs of the tower; and an optimization analysis module (218) coupled to the at least one processor (202), to identify, based on outputs corresponding to execution of the load cases on each of the plurality of designs of the tower, an optimized design.

9. The system of claim 8, wherein the one or more physical parameters include at least one of tower members, bolts, patterns, and a base width of the tower.

10. The system of claim 8, wherein the design alteration module (216) is to continue altering the at least one physical parameter of the optimized initial design until a state of convergence is reached, the convergence being a point where the tower design is optimized for cost efficiency.

11. The system of claim 8, wherein the design alteration module is to vary the at least one physical parameter within a predefined range and incrementally adjust the at least one physical parameter by a predefined increment.

12. The system of claim 8, wherein the geometry module (210) is configured to select, from a preconfigured library of tower geometries, the initial geometry of the tower.

13. The system of claim 8, wherein the optimization analysis module (218) is to select the optimized design of the tower such that the optimized design comprises all the tower members that withstand the load cases for the respective designs of the tower.STATEMENT UNDER ARTICLE 19Regarding Item 2In response to the objections raised in the Written Opinion of the International Searching Authority, the Applicant has amended the original independent claims 1 and 8 and corresponding dependent claims. The Applicant submits that the scope of the amended claim set is within the scope of the originally filed subject matter, and no new subject matter is added.The present subject matter provides for optimizing tower designs that is efficient, cost- effective, and ensures that physical parameters of the tower are utilized to their full potential. The optimization process that involves determining whether the utilization of the one or more physical parameters is close to a predefined threshold, and altering each until the predefined threshold of utilization is reached for the respective physical parameter, ensures that the one or more physical parameters are optimized until they reach a predefined utilization level, thereby eliminating underutilized components and reducing material waste. The two-stage optimization process wherein the one or more physical parameters of the initial geometry are first optimized to obtain an optimized initial design, and then at least one physical parameter of the optimized initial design is sequentially altered to generate multiple design variants, allows for comprehensive evaluation of design alternatives. Accordingly, the present subject matter allows for streamlined optimization in the tower design process by systematically altering physical parameters associated with the performance of the tower without humanintervention, thereby reducing redundant calculations and potential oversights in design iterations.In view of the above, the Applicant believes that the following aspects of the amended independent claim 1: "....based on the determination that the initial geometry withstands the different combination of loads, optimizing the one or more physical parameters of the initial geometry by altering each until a predefined threshold of utilization is reached for the respective physical parameter to obtain an optimized initial design; sequentially altering at least one physical parameter of the one or more physical parameters of the optimized initial design to obtain a plurality of designs of the tower; determining a set of load cases corresponding to each of the plurality of designs of the tower; applying, iteratively, the set of load cases to the respective design of the plurality of designs of the tower; and identifying, based on outputs corresponding to execution of the load cases on each of the plurality of designs of the tower, an optimized design. ", is not described by DI and D2.In view of the above, the amended claim 1 of the present Application is hence considered to possess inventive step. Similar reasoning is also applicable for amended claim 8.Further, dependent claims 2-7, 9-13 which are dependent on claims 1 and 8 are also inventive over the Documents DI and D2 cited in the ISR.

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