Development of Fixture Layout Optimization for Thin-Walled Parts:A Review

An increasing number of researchers have researched fixture layout optimization for thin-walled part assembly during the past decades.However,few papers systematically review these researches.By analyzing existing literature,this paper summarizes the process of fixture layout optimization and the methods applied.The process of optimization is made up of optimization objective setting,assembly variation/deformation modeling,and fixture layout optimization.This paper makes a review of the fixture layout for thin-walled parts according to these three steps.First,two different kinds of optimization objectives are introduced.Researchers usually consider in-plane variations or out-of-plane deformations when designing objectives.Then,modeling methods for assembly variation and deformation are divided into two categories:Mechanism-based and data-based methods.Several common methods are discussed respectively.After that,optimization algorithms are reviewed systematically.There are two kinds of optimization algorithms:Traditional nonlinear programming and heuristic algorithms.Finally,discussions on the current situation are provided.The research direction of fixture layout optimization in the future is discussed from three aspects:Objective setting,improving modeling accuracy and optimization algorithms.Also,a new research point for fixture layout optimization is discussed.This paper systematically reviews the research on fixture layout optimization for thin-walled parts,and provides a reference for future research in this field.

Optimizing wind farm layout for enhanced electricity extraction using a new hybrid PSO-ANN method

With the growing need for renewable energy,wind farms are playing an important role in generating clean power from wind resources.The best wind turbine architecture in a wind farm has a major influence on the energy extraction efficiency.This paper describes a unique strategy for optimizing wind turbine locations on a wind farm that combines the capabilities of particle swarm optimization(PSO)and artificial neural networks(ANNs).The PSO method was used to explore the solution space and develop preliminary turbine layouts,and the ANN model was used to fine-tune the placements based on the predicted energy generation.The proposed hybrid technique seeks to increase energy output while considering site-specific wind patterns and topographical limits.The efficacy and superiority of the hybrid PSO-ANN methodology are proved through comprehensive simulations and comparisons with existing approaches,giving exciting prospects for developing more efficient and sustainable wind farms.The integration of ANNs and PSO in our methodology is of paramount importance because it leverages the complementary strengths of both techniques.Furthermore,this novel methodology harnesses historical data through ANNs to identify optimal turbine positions that align with the wind speed and direction and enhance energy extraction efficiency.A notable increase in power generation is observed across various scenarios.The percentage increase in the power generation ranged from approximately 7.7%to 11.1%.Owing to its versatility and adaptability to site-specific conditions,the hybrid model offers promising prospects for advancing the field of wind farm layout optimization and contributing to a greener and more sustainable energy future.

Optimizing Memory Access Efficiency in CUDA Kernel via Data Layout Technique

Over the past decade, Graphics Processing Units (GPUs) have revolutionized high-performance computing, playing pivotal roles in advancing fields like IoT, autonomous vehicles, and exascale computing. Despite these advancements, efficiently programming GPUs remains a daunting challenge, often relying on trial-and-error optimization methods. This paper introduces an optimization technique for CUDA programs through a novel Data Layout strategy, aimed at restructuring memory data arrangement to significantly enhance data access locality. Focusing on the dynamic programming algorithm for chained matrix multiplication—a critical operation across various domains including artificial intelligence (AI), high-performance computing (HPC), and the Internet of Things (IoT)—this technique facilitates more localized access. We specifically illustrate the importance of efficient matrix multiplication in these areas, underscoring the technique’s broader applicability and its potential to address some of the most pressing computational challenges in GPU-accelerated applications. Our findings reveal a remarkable reduction in memory consumption and a substantial 50% decrease in execution time for CUDA programs utilizing this technique, thereby setting a new benchmark for optimization in GPU computing.

A Chaotic Local Search-Based Particle Swarm Optimizer for Large-Scale Complex Wind Farm Layout Optimization

Wind energy has been widely applied in power generation to alleviate climate problems.The wind turbine layout of a wind farm is a primary factor of impacting power conversion efficiency due to the wake effect that reduces the power outputs of wind turbines located in downstream.Wind farm layout optimization(WFLO)aims to reduce the wake effect for maximizing the power outputs of the wind farm.Nevertheless,the wake effect among wind turbines increases significantly as the number of wind turbines increases in the wind farm,which severely affect power conversion efficiency.Conventional heuristic algorithms suffer from issues of low solution quality and local optimum for large-scale WFLO under complex wind scenarios.Thus,a chaotic local search-based genetic learning particle swarm optimizer(CGPSO)is proposed to optimize large-scale WFLO problems.CGPSO is tested on four larger-scale wind farms under four complex wind scenarios and compares with eight state-of-the-art algorithms.The experiment results indicate that CGPSO significantly outperforms its competitors in terms of performance,stability,and robustness.To be specific,a success and failure memories-based selection is proposed to choose a chaotic map for chaotic search local.It improves the solution quality.The parameter and search pattern of chaotic local search are also analyzed for WFLO problems.

A Spacecra Equipment Layout Optimization Method for Diverse and Competitive Design

The spacecraequipment layout optimization design(SELOD)problems with complicated performance con-straints and diversity are studied in this paper.The previous literature uses the gradient-based algorithm to obtain optimized non-overlap layout schemes from randomly initialized cases eectively.However,these local optimal solutions are too dicult to jump out of their current relative geometry relationships,signi􀀀cantly limiting their further improvement in performance indicators.Therefore,considering the geometric diversity of layout schemes is put forward to alleviate this limitation.First,similarity measures,including modi􀀀ed cosine similarity and gaussian kernel function similarity,are introduced into the layout optimization process.Then the optimization produces a set of feasible layout candidates with the most remarkable dierence in geometric distribution and the most representative schemes are sampled.Finally,these feasible geometric solutions are used as initial solutions to optimize the physical performance indicators of the spacecra,and diversi􀀀ed layout schemes of spacecraequipment are generated for the engineering practice.The validity and eectiveness of the proposed methodology are demonstrated by two SELOD applications.

THE LAYOUT OPTIMIZATION OF STIFFENERS FOR PLATE-SHELL STRUCTURES

The plate-shell structures with stiffeners are widely used in a broad range of engineering structures. This study presents the layout optimization of stiffeners. The minimum weight of stiffeners is taken as the objective function with the global stiffness constraint. In the layout optimization, the stiffeners should be placed at the locations with high strain energy/or stress. Conversely, elements of stiffeners with a small strain energy/or stress are considered to be used inefficiently and can be removed. Thus, to identify the element efficiency so that most inefficiently used elements of stiffeners can be removed, the element sensitivity of the strain energy of stiffeners is introduced, and a search criterion for locations of stiffeners is presented. The layout optimization approach is given for determining which elements of the stiffeners need to be kept or removed. In each iterative design, a high efficiency reanalysis approach is used to reduce the computational effort. The present approach is implemented for the layout optimization of stiffeners for a bunker loaded by the hydrostatic pressure. The numerical results show that the present approach is effective for dealing with layout optimization of stiffeners for plate-shell structures.

Accessibility Evaluation and Layout Optimization of Urban Parks in Xihu District, Nanchang City Based on Walking of the Elderly People

Urban park is one of the few green spaces that retain natural traces and are easy for the elderly to reach,and it has become the main place for the elderly to carry out leisure,entertainment,physical fi tness and interpersonal activities.The reasonable layout of urban parks is of great signifi cance to improve the quality of life of the elderly in old age.In this article,using the network analysis method in ArcGIS software,the accessibility of urban parks in Xihu District of Nanchang City based on elderly walking was evaluated and analyzed,and three strategies for optimizing the layout of the urban parks were proposed,including increasing the number of urban parks,improving the urban traffic network,and strengthening urban greenway planning and construction.The research results can provide reference for the optimal layout of urban parks in Xihu District,Nanchang City,so that the urban parks can better meet the outdoor leisure needs of the elderly,and the elderly’s sense of well-being and gain is enhanced.

PARTICLE SWARM OPTIMIZATION BASED ON PYRAMID MODEL FOR SATELLITE MODULE LAYOUT

To improve the global search ability of particle swarm optimization （PSO）, a multi-population PSO based on pyramid model （PPSO） is presented. Then, it is applied to solve the layout optimization problems against the background of an international commercial communication satellite （INTELSAT-Ⅲ） module. Three improvements are developed, including multi-population search based on pyramid model, adaptive collision avoidance among particles, and mutation of degraded particles. In the numerical examples of the layout design of this simplified satellite module, the performance of PPSO is compared to global version PSO and local version PSO （ring and Neumann PSO）. The results show that PPSO has higher computational accuracy, efficiency and success ratio.

Current Research Situations,Problems and Recommendations of Land Use Structure and Layout Optimization

Land is the foundation for human survival and development,and all human social and economic activities are inseparable from the land as a space carrier.With the continuous development of China's social economy,China is facing new social development needs such as urban-rural integration and rural revitalization.At the same time,China starts to attach great importance to ecology and has proposed the concept that lucid waters and lush mountains are invaluable assets.In this situation,the rational use of land resources,the optimization of land use structure and layout are also facing new challenges and problems,and more comprehensive consideration is required to make relevant optimization.Using the method of literature comparative analysis,from the conceptual connotation,basic theory,method model,and specific practice of land use structure and layout optimization,this paper analyzed and summarized the current research situations and problems,and finally came up with recommendations for the future research.

Revisiting the analytical solutions for ultimate bearing capacity of pile embedded in rocks

This paper investigates the validity and shortcomings of the existing analytical solution for the ultimate bearing capacity of a pile embedded in a rock mass using the modified HoekeBrown failure criterion.Although this criterion is considered a reference value for empirical and numerical calculations,some limitations of its basic simplifications have not been clarified yet.This research compares the analytical results obtained from the novel discontinuity layout optimization(DLO)method and the numerical solutions from the finite difference method(FDM).The limitations of the analytical solution are considered by comparing different DLO failure modes,thus allowing for the first time a critical evaluation of its scope and conditioning for implementation.Errors of up to 40%in the bearing capacity and unrealistic failure modes are the main issues in the analytical solution.The main aspects of the DLO method are also analyzed with an emphasis on the linearization of the rock failure criterion and the accuracy resulting from the discretization size.The analysis demonstrates DLO as a very efficient and accurate tool to address the pile tip bearing capacity,presenting considerable advantages over other methods.

An Adaptive Strategy-incorporated Integer Genetic Algorithm for Wind Farm Layout Optimization

Energy issues have always been one of the most significant concerns for scientists worldwide.With the ongoing over exploitation and continued outbreaks of wars,traditional energy sources face the threat of depletion.Wind energy is a readily available and sustainable energy source.Wind farm layout optimization problem,through scientifically arranging wind turbines,significantly enhances the efficiency of harnessing wind energy.Meta-heuristic algorithms have been widely employed in wind farm layout optimization.This paper introduces an Adaptive strategy-incorporated Integer Genetic Algorithm,referred to as AIGA,for optimizing wind farm layout problems.The adaptive strategy dynamically adjusts the placement of wind turbines,leading to a substantial improvement in energy utilization efficiency within the wind farm.In this study,AIGA is tested in four different wind conditions,alongside four other classical algorithms,to assess their energy conversion efficiency within the wind farm.Experimental results demonstrate a notable advantage of AIGA.

CFD-Based Optimization of Hot Primary-Air Pipe Networks in Power Plant Milling Systems

A hot primary-air pipe system is the bridge connecting an air-preheater with a coal mill in power generation stations.The effective geometrical configuration of the pipe network greatly affects the air flow distribution and consequently influences the safe and economic operation of milling systems in power stations.In order to improve the properties of the air flow,in the present work the SIMPLEC method is used to simulate numerically the flow field for the original layout of the system.As a result,the internal mechanisms influencing the uneven pressure drop in each branch are explored and three optimization schemes are proposed accordingly.The numerical results indicate that,for the original layout,the local pressure drop of the tee section accounts for approximately 74%of the total drop of the system,with other pressure drops depending on the specific branch considered.It is shown that after optimization,a roughly balanced flow resistance and flow rate can be obtained.Compared with the original layout,the pressure drop relating to different branches is significantly reduced.

Urban Development Boundary Simulation Based on“Double Evaluation”and FLUS Model

The delimitation of urban development boundaries plays an important role in optimizing the nation land space.“Double evaluation”is one of the important means to study and predict the scale of new construction land in the future and to determine the spatial distribution of urban construction land.This study combines the“double evaluation”with the FLUS(Future Land-Use Simulation)model to study the delimitation of the urban development boundary of Yichang.The results show that:(1)the“double evaluation”method comprehensively considers the carrying capacity of the resource environmental bear and the suitability of urban development;(2)the FLUS model can better couple the“double evaluation”method for Land Use/Land Cover(LULC)suitability evaluation,Land Use/land Cover Change(LUCC)simulation and urban development boundary delineation,and the overall accuracy of the simulation reaches 96%;(3)according to the requirements of relevant national policies,this study divides the urban development boundary of the study area into concentrated construction areas,elastic development areas and special purpose areas.This function-based division can meet the requirements of urban flexible development,ecological protection and urban safety.This research combines the FLUS model,which is widely used in the simulation of LUCC,with the double evaluation method used in China’s new round of land and space planning to obtain the result of the urban development boundary.This result is consistent with the existing plan of the study area.

Placement Optimization Method of FPSO Gas Detectors Based on Leakage Risk

As the first step of the fire/gas-detection systems of floating production storage and offloading(FPSO)units is to iden-tify leakage accidents,gas detectors play an important role in controlling the leakage risk.To improve the leakage scenario detection rate and reduce the cumulative risk value,this paper presents an optimization method of the gas detector placement.The probability density distribution and cumulative probability density distribution of the leakage source variables and environmental variables were calculated based on the Offshore Reliability Data and the statistical data of the relevant leakage variables.A potential leakage sce-nario set was constructed using Latin hypercube sampling.The typical FPSO leakage scenarios were analyzed through computational fluid dynamics(CFD),and the impacts of different parameters on the leakage were addressed.A series of detectors was deployed according to the simulation results.The minimization of the product of effective detection time and gas leakage volume was the risk optimization objective,and the location and number of detectors were taken as decision variables.A greedy extraction heuristic algo-rithm was used to solve the optimization problem.The results show that the optimized placement had a better monitoring effect on the leakage scenario.

A novel sensitivity model for short nets

For modern processes at deep sub-micron technology nodes, yield design, especially the design at the layout stage is an important way to deal with the problem of manufacturability and yield. In order to reduce the yield loss caused by redundancy material defects, the choice of nets to be optimized at first is an important step in the process of layout optimization. This paper provides a new sensitivity model for a short net, which is net-based and reflects the size of the critical area between a single net and the nets around it. Since this model is based on a single net and includes the information of the surrounding nets, the critical area between the single net and surrounding nets can be reduced at the same time. In this way, the efficiency of layout optimization becomes higher. According to experimental observations~ this sensitivity model can be used to choose the position for optimization. Compared with the chip-area-based and basic- layout-based sensitivity models, our sensitivity model not only has higher efficiency, but also confirms that choosing the net to be optimized at first improves the design.

Open critical area model and extraction algorithm based on the net flow-axis

In the integrated circuit manufacturing process, the critical area extraction is a bottleneck to the layout optimization and the integrated circuit yield estimation. In this paper, we study the problem that the missing material defects may result in the open circuit fault. Combining the mathematical morphology theory, we present a new computation model and a novel extraction algorithm for the open critical area based on the net flow-axis. Firstly, we find the net flow-axis for different nets. Then, the net flow-edges based on the net flow-axis are obtained. Finally, we can extract the open critical area by the mathematical morphology. Compared with the existing methods, the nets need not to divide into the horizontal nets and the vertical nets, and the experimental results show that our model and algorithm can accurately extract the size of the open critical area and obtain the location information of the open circuit critical area.

Optimal layout model of feeder automation equipment oriented to the type of fault detection and local action

In feeder automation transformation there are difficulties in equipment and location selection.To help with this,an optimal layout model of feeder automation equipment oriented to the type of fault detection and local action is pro-posed.It analyzes the coordination relationship of the three most common types of automation equipment,i.e.,fault indicator,over-current trip switch and non-voltage trip switch in the fault handling process,and the explicit expres-sions of power outage time caused by a fault on different layouts of the above three types of equipment are given.Given constraints of power supply reliability and the goal of minimizing the sum of equipment-related capital invest-ment and power interruption cost,a mixed-integer quadratic programming model for optimal layout is established,in which the functional failure probability of equipment is linearized using the 3δprinciple in statistics.Finally,the basic characteristics of the proposed model are illustrated by different scenarios on the IEEE RBTS-BUS6 system.It can not only take into account fault location and fault isolation to enhance user power consumption perception,but also can guide precise investment to improve the operational quality and efficiency of a power company.

A Layout Optimization Method of Composite Wing Structures Based on Carrying Efficiency Criterion

A two-level layout optimization strategy is proposed in this paper for large-scale composite wing structures. Design requirements are adjusted at the system level according to structural deformation, while the layout is optimized at the subsystem level to satisfy the constraints from system level. The approaching degrees of various failure critical loads in wing panels are employed to gauge the structure’s carrying efficiency. By optimizing the efficiency as an objective, the continuity of the problem could be guaranteed. Stiffened wing panels are modeled by the equivalent orthotropic plates, and the global buckling load is predicted by energy method. The nonlinear effect of stringers’ support elasticity on skin local buckle resistance is investigated and approximated by neural network （NN） surrogate model. These failure predictions are based on analytical solutions, which could effectively save calculation resources. Finally, the integral optimization of a large-scale wing structure is completed as an example. The result fulfills design requirements and shows the feasibility of this method.

Concurrent topology optimization design of stiffener layout and cross-section for thin-walled structures

Stiffened plates or shells are widely used in engineering structures as primary or secondary load-bearing components.How to design the layout and sizes of the stiffeners is of great significance for structural lightweight.In this work,a new topology optimization method for simultaneously optimizing the layout and cross-section topology of the stiffeners is developed to solve this issue.The stilfeners and base plates are modeled by the beam and shell elements,respectively,significantly reducing the computational cost.The Giavotto beam theory,instead of the widely employed Euler or Timoshenko beam theory,is applied to model the stiffeners for considering the warping deformation in evaluating the section stiffness of the beam.A multi-scale topology optimization model is established by simultaneously optimizing the layout of the beam and the topology of the cross-section.The design space is significantly expanded by optimizing these two types of design variables.Several numerical examples are applied to illustrate the validity and effectiveness of the proposed method.The results show that the proposed two-scale optimization approach can generate better designs than the single-scale method.

Shear wall layout optimization of tall buildings using Quantum Charged System Search

This paper presents a developed meta-heuristic algorithm to optimize the shear walls of tall reinforced concrete buildings.These types of walls are considered as lateral resistant elements.In this paper,Quantum Charged System Search(QCSS)algorithm is presented as a new optimization method and used to improve the convergence capability of the original Charged System Search.The cost of tall building is taken as the objective function.Since the design of the lateral system plays a major role in the performance of the tall buildings,this paper proposes a unique computational technique that,unlike available works,focuses on structural efficiency or architectural design.This technique considers both structural and architectural requirements such as minimum structural costs,torsional effects,flexural and shear resistance,lateral deflection,openings and accessibility.The robustness of the new algorithm is demonstrated by comparing the outcomes of the QCSS with those of its standard algorithm.