A Structural Design Optimization System Exploiting Distributed Grid Resources

PurposeThe purpose of this paper is to propose and demonstrate criteria for omnibearing imbalance of macroeconomic system structure (regions, industries, urban and rural areas, departments, ownership, etc.) and their strategic optimization, for structural optimization of the global regional macroeconomic system, providing universal application of the formula for calculating, and quantitative basis.Design/methodology/approachRelevant statistical data will compare receipts (GBC) model calculation to quantitatively determine structural imbalance and the formation of structural optimization and direction and intensity of the strategic program.FindingsContemporary system science believes that all things take the form of systems, and that the output function depends on the internal structure of systems. Therefore, the system structure must be judged by the output benefit. Although the output benefit of a society's macroeconomic system is enslaved to the system's external environment (the peripheral environment, international economy, or even global economy), the state of the system's internal structure directly determines its output benefit. In reverse, the output benefit of the macroeconomic system is also the reference to evaluate its internal structure.Research limitations/implicationsResearch on the macroeconomic system structural imbalances and optimization with universal applicability.Originality/valueThe paper is of great significance with regard to the theory, methodology, and practice for structural optimization of the global regional macroeconomic system.

The modal-based aeroelastic optimization approach is reformulated and extended such that it can deal with more structural analysis and optimization features. The disciplines treated in this paper are statics under fixed loads and static aeroelasticity of free-free aircraft. The new formulation includes the application of stress constraints under fixed and varied external loads, and the effects of inertial changes on aeroelastic trim. It also facilitates the integration of the modal-based option in common finite element structural optimization schemes. The new scheme is applied to realistic design cases using the multidisciplinary automated structural optimization system ASTROS code. Application cases of 3761 and 26,259 degrees of freedom exhibit CPU time reduction factors of 4-122 in comparison with the conventional discrete approach.

These are the proceedings of the twenty-first working conference of the International Federation of Information Processing (IFIP) Working Group 7.5 on Reliability and Optimization of Structural Systems, which took place at the University of California, Berkeley, USA, on August 19–21, 2024. This volume contains 15 selected papers from the 20 presentations delivered at the conference. The conference was supported by Pacific Earthquake Engineering Research (PEER) Center, and by the University of California, Berkeley, which provided outstanding facilities in the conference venue and remarkable logistic support throughout the event. The purpose of the WG7.5 Working Group is to promote modern theories and methods of structural and system reliability and optimization, to stimulate research, development, and applications in these areas, to foster the dissemination and exchange of information, and to encourage education on those subjects. The main themes of the conference included structural reliability methods, engineering risk and resilience analysis, Bayesian methods, reliability-based design optimization, and sensitivity analysis, along with their applications in civil engineering, dynamics, and natural hazards. The conference facilitated engaging discussions among participants, both during and after the technical sessions. Notably, a significant number of presentations were delivered by promising young researchers, who contributed fresh perspectives and innovative ideas to the field.

Machine Learning User Preferences for Structural Design

Mathematical optimization theories are employed for the design of structures in structural optimization. Structural optimization is being widely utilized for practical problems due to well-developed commercial software systems. Three representative structural optimization systems such as Genesis, MSC Nastran and OptiStruct are investigated and evaluated by solving various test examples in different scales. The design capabilities of three software systems are explored and the performances of the systems are compared. The performance of structural optimization depends on the quality of the optimum solution and the computational time, and these aspects are compared from an application viewpoint. For a fair comparison, the same formulations are utilized, and the same optimization methods are employed for each example. Also, the same system environment is prepared, and the same optimization parameters are used. Additionally, various design options of each software system are tested for the best performance. Linear static response size, shape, topology, topometry and topography optimizations are applied to the examples and the results are compared. No system seems to be the best in all cases and each system has advantages and disadvantages depending on the application. In general, Genesis is excellent in computational time while OptiStruct gives excellent optimum solutions, in size, topometry and topology optimizations. Meanwhile, MSC Nastran presents good solutions in shape and topography optimizations.

The implementation of a general and flexible method of formulating problems of mathematical programming in structural and multidisciplinary optimization systems is described. The method, which is based on the so-called bound formulation, enables the formulation and solution of problems involving local, integral, mintmax, maxlmin and possibly non-differentiable user-defined functions in any conceivable mix and using user-defined mathematical functions. The computer implementation involves a parser capable of interpreting and performing symbolic dfierentiation of the user defined functions. A sample problem of thermo-elasticity is given. It is concluded that this approach is well suited for multidisciplinary design optimization systems. 1. Motivation One of the great challenges of research in design automation is the development of practically applicable systems for multidisciplinary design optimization. Such systems will, if they are truly generally applicable, cause a revolution in the way design laboratories work. Several papers with the focus on system design rather than single applications have emerged in recent years. Some examples are Esping (1986), Rasmussen (1989), Papalarnbros & Chirehdast (1990), Choi & Chang (1991), Botlun et. al. (1 992), Rasmussen et. al. (1993), and Cardoso & Santos (1 993). Obtaining the necessary generality, however, is a very difficult task. Designing even simple components involves many different considerations. For the sake of the argument, we may categorize them into groups of increasing complexity: The functional behavior, for instance weight, energy consumption, power output, efficiency, eigenfrequencies, strength, stiffness, pressures, velocities, accelerations, temperatures, electric and magnetic properties, etc. These qualities can often be modeled mathematically and analyzed by means of digital computers. The fabricational behavior, for instance the cost of machining, the necessary production facilities, the necessary manpower, stock and inventory, financial requirements, etc. These properties are usually very difficult to analyze because of the many degrees of freedom in choice of production planning and processes, the dependency of other products manufactured simultaneously, and even the dependence on the economic boundary conditions formed by the outside world. The aesthetic properties that are impossible to evaluate objectively, but are none the less tightly connected with the functional and fabricational properties. For instance, the shape of the hull of a ship determines strength, stiffness and drag properties, but it also forms an important part of the visual impression. In the development of multidisciplinary systems, we have only begun to cover the first category of product properties, so it may be argued that there is still a long way to go. At the Institute of Mechanical Engineering, Aalborg University, Denmark, a system for multidisciplinary design optimization is under development. The system is called 'Associate Professor of Mechanical Engineering '+~esearch Assistant Copyright O 1994 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

During the last 20 years, structural optimization has become one of the most important topics of engineering applications. Design optimization of structure has been an interesting area of research in the field of engineering design for its ability to short the design cycle and to enhance product quality. Significant research activity has occurred in the area of structural optimization in the last decade. Especially for topology optimization of structure, many new theoretical, algorithmic, and computational contributions have resulted by researchers and engineers. Topology optimization is a powerful tool for global and multi-scale design of macrostructures, microstructures, and the cell of prescribed composite materials. The population based evolutionary algorithms have emerged as powerful mechanism for finding optimum solutions of complex optimization problems in engineering during the last two decades. Evolutionary computation is the study of computational systems which use ideas and get inspiration from natural evolution and adaptation [1]. The thinking has wide application in various engineering fields, such as computer science, artificial intelligence, operations research. Genetic algorithm is another kind of bio-inspired optimization method and it is playing an increasingly important role in studies of complex adaptive systems. Its application ranges from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices and structures, such as aircraft turbines and integrated circuits [2]. Optimization of structures can be classified into three categories: sizing, shaping, and topology optimization. In the topology optimization, it is concerned with the structure members and connectivity between members. In general, it is easily represented by discrete variables rather than by those used for continuous optimization problems. Topology optimization is the most difficult and complex among three categories and it is special useful in developing innovative conceptual designs. Structural optimization, in particular the topology optimization, has been identified as one of the most challenging tasks in structural design. Various techniques and approaches have been established during the last two decades. Topology optimization usually referred to as layout optimization or general shape optimization [3]. It lets engineers get the optimal topology of structure or new configurations during product design phase, as they are implementing the design of the size

Optimization of process parameters and process intelligent control of the production process is an important part of the design and development of drying equipment. This research proposed a new type of jacket and conical screw belt composite heating device dryer, to achieve the material fully turned over, drying layer temperature uniformity, improve the drying efficiency of the material and energy efficiency. We design the humidity and temperature control system of the dryer for the overall design based on the PID, and optimise the drying control method, to ensure that the quality of the material drying, and to improve the automation and production efficiency of the equipment. The study helps to determine the process parameters of the material production process and improve the stability and quality of the product.

Structural reliability-based design optimization with non-probabilistic credibility level

As engineering systems become more complex, the need for 'optimal' designs becomes apparent and very important. A centralised approach can be economically unfeasible, owing to computer limitations, or because it is too complex and cumbersome to be implemented. In this paper, an approach using a suboptimal controller is proposed leading to a structural optimisation problem of large scale systems (LSS). The mathematical formulation of this problem is provided. A new structural controller is developed, and a step-by-step algorithm to design it is provided. An overall cost is defined and can be computed from the proposed algorithm. Two simple examples illustrating the applicability and usefulness of the new structural optimisation approach are included.

Isogeometric analysis (IGA) connects CAE with standard CAD design tools and has been utilized for a decade in structural optimization. FEA has a number of drawbacks, including a lack of linkage between analytic and geometric models, a shortage of continuity between components, and a lack of accuracy for high-order elements. Isogeometric analysis effectively overcomes these obstacles. This paper proposes the isogeometric topological optimization mathematical model depending on the asymmetric constitutive relationship of tension and compression microscopic materials. We provide a new density-based topology optimization formulation in which the design domain is limited to the B-spline space. A rectangular domain with a tensor-product is embedded in a design domain that is arbitrarily shaped. The density field is represented using B-splines. The intrinsic filter provided by the B-spline representation for topology optimization is governed by the degrees of B-spline and the knot spans. This B-spline effectively removes numerical artifacts and controls the minimum feature-length in; when the B-spline basis functions span many analysis elements. Benchmark problems in structural topology optimization are computed through Evolutionary Structural Optimization (ESO) algorithm. Comparisons of the optimal structure topologies using finite element analysis and isogeometric collocation methods are analyzed. The influence of different tension-compression stiffness ratios on the final structure topologies is listed and analyzed. The numerical results show the reliability and performance of the proposed mathematical formulation and asymmetry of natural structure.

PurposeThis paper aims to summarize design rules based on the process characteristics of selective laser melting (SLM) and structural optimization and apply the design rules in the lightweight design of an aluminum alloy antenna bracket. The design goal is to reduce 30 per cent of the weight while maintaining the stress levels in the original part.Design/methodology/approachTo reduce weight as much as possible, the titanium alloy with higher specific strength was selected during the process of optimization. The material distribution of the bracket was improved by the topology optimization design. The redesign for SLM was used to obtain an optimization model, which was more suitable for SLM. The component performance was improved by shape optimization. The modal analysis data of the structural optimization model were compared with those of the stochastic lightweight model to verify the structural optimization model. The scanning data were compared with those of the original model to verify whether the model was suitable for SLM.FindingsStructural optimization design for antenna bracket realized the mass decrease of 30.43 per cent and the fundamental frequency increase of 50.18 per cent. The modal analysis data of the stochastic lightweight model and the structural optimization model indicated that the optimization performance of structural optimization method was better than that of the stochastic lightweight method. The comparison results between the scanning data of the forming part and the original data confirmed that the structural optimization design for SLM lightweight component could achieve the desired forming accuracy.Originality/valueThis paper summarizes geometric constraints in SLM and derives design rules of structural optimization based on the process characteristics of SLM. SLM design rules make structural optimization design more reasonable. The combination of structural optimization design and SLM can improve the performance of lightweight antenna bracket significantly.

Fibre Reinforced Plastics (FRPs) have been used in many practical structural applications due to their excellent strength and weight characteristics as well as the ability for their properties to be tailored to the requirements of a given application. Thus, designing with FRPs can be extremely challenging, particularly when the number of design variables contained in the design space is large. For example, to determine the ply orientations and the material properties optimally is typically difficult without a considered approach. Optimization of composite structures with respect to the ply angles is necessary to realize the full potential of fibre-reinforced materials. Evaluating the fitness of each candidate in the design space, and selecting the most efficient can be very time consuming and costly. Structures composed of composite materials often contain components which may be modelled as rectangular plates or cylindrical shells, for example. Modelling of components such as plates can be useful as it is a means of simplifying elements of structures, and this can save time and thus cost. Variations in manufacturing processes and user environment may affect the quality and performance of a product. It is usually beneficial to account for such variances or tolerances in the design process, and in fact, sometimes it may be crucial, particularly when the effect is of consequence. The work conducted within this project focused on methodologies for optimally designing fibre-reinforced laminated composite structures with the effects of manufacturing tolerances included. For this study it is assumed that the probability of any tolerance value occurring within the tolerance band, compared with any other, is equal, and thus the techniques are aimed at designing for the worst-case scenario. This thesis thus discusses four new procedures for the optimization of composite structures with the effects of manufacturing uncertainties included.

A multilayer feedforward neural network with a modification to the standard backpropagation training of neural nets is considered. Information on the gradients of target outputs with respect to network inputs is used in this modification. This modified neural network is then applied for approximating design requirements of aerospace composite components, such as an aircraft engine guide vane and a satellite reflector assembly. This neural network functional approximator is then used with an optimization algorithm for determining the optimal parameters for component design requirements. The modified neural network provides for faster convergence of learning process and requires a smaller number of hidden layer nodes for convergence to similar training error levels. HE application of neural networks as universal approximators has been the focus of tremendous amount of activity in the past few years.16 Neural networks have been used for approximating and modeling both memoryless systems and dynamical systems with memory. This paper does not go into the various neural net architectures and training schemes, and the interested reader could refer to standard texts on this subject matter.1'2 This paper considers static neural networks (systems without memory) formed by interconnections without loops, called feedforward networks.2 In addition, this work considers a backpropagation learning scheme with adaptation of learning rate. There have been many additions to, or adaptations of, the basic backpropagation scheme, such as adaptive learning rate, learning with momentum, and the like,1'2 for improving convergence of the learning scheme, and these are not addressed in this paper. This paper explores a modification of the backpropagation learning scheme using information on the gradient of the target outputs with respect to the inputs of the network. The performance of the modified learning scheme is compared with that of the standard backpropagation learning scheme.2 A feedforward network with a single hidden layer trained with this modified learning scheme is applied in structural optimization problems. Figure 1 shows a feedforward net with a single hidden layer. The restriction to a single hidden layer is not a limitation of the modified learning scheme, and the new training scheme can be used on networks with multiple hidden layers also. The use of neural networks for structural response approximation has been reported by several authors.46 The primary reason for investigating such properties is to assess the applicability of trained neural networks for quick and accurate approximation of response functions during structural design optimization. Structural optimization, utilizing either gradient-based numerical search or genetic search algorithms, requires repeated function (response) evaluations during the search process. A single finite element analysis of large-scale structures requires a significant amount of computational time and resource and hence the need for robust approxima

In this paper we present a formulation of the wellknown structural topology optimization problem that accounts for the presence of loads capable of causing permanent damage to the structure. Damage is represented in the form of an internal variable model which is standard in continuum damage mechanics. Here we employ an interpretation of this model as an optimum remodeling problem for maximal compliance over all damage distributions, making also the analysis of the damage model a study in structural optimization. The damage criterion can be included in the optimal design model in a number of ways. We present results for finding the optimal topology of the reinforcement of an existing design with the goal of minimizing damage. Also, we treat the problem of finding the topology of a structure where we seek maximal stiffness under service loads with a constraint on the amount of damage which occurs under a separate set of damage loads.