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Performance-based sizing optimization method for steel frame structures

STRUCTURES 2025年 71卷

作者： Wan, Yinyuan Hu, Bo Zhou, Jianlu Ye, Fangfang Jin, Xin Miao, Sai Wu, Chenliang Gao, Boqing Zhejiang Univ Coll Civil Engn & Architecture Hangzhou 310058 Peoples R China Zhejiang Univ Architectural Design & Res Inst Hangzhou 310058 Peoples R China Zhejiang Univ Ctr Balance Architecture Hangzhou 310058 Peoples R China

By modifying the sizing of the components, different performance levels can be achieved in the structure, thereby enabling a performance-based design for steel frame structures. In this paper, a performance-based seismic optimization design method for steel frame structures is presented. The combined response surface model is used to approximate the constraint and objective functions, and the optimal solution for sizing is obtained by continuously improving the response surface. In order to efficiently and accurately obtain the performance of steel frame structures, a simplified pseudo elasto-plastic analysis method based on the energy equivalence principle is proposed. This simplified method equates the energy of components in the elastic analysis process with that in the elasto-plastic state and derives the formula for the stiffness reduction factor, which describes the damage location and damage degree of the components under an earthquake. With the help of programming software, an optimization program for the performance-based design of steel frame structures was prepared to realize the automated calculation. The proposed optimization method was applied to four steel frames, demonstrating its ability to satisfy various performance targets while reducing material consumption. These results indicate that the performance-based design based on the combined response surface method and the pseudo elasto-plastic analysis method is feasible and effective.

关键词： Steel frame structures Performance-based design Combined response surfaces Pseudo elasto-plastic analysis sizing optimization

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sizing optimization of truss structures using flower pollination algorithm

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APPLIED SOFT COMPUTING 2015年 37卷 322-331页

作者： Bekdas, Gebrail Nigdeli, Sinan Melih Yang, Xin-She Istanbul Univ Dept Civil Engn TR-34320 Istanbul Turkey Middlesex Univ Design Engn & Math London N17 8HR England

The recently developed flower pollination algorithm is used to minimize the weight of truss structures, including sizing design variables. The new algorithm can efficiently combine local and global searches, inspired by cross-pollination and self-pollination of flowering plants, respectively. Furthermore, it implements an iterative constraint handling strategy where trial designs are accepted or rejected based on the allowed amount of constraint violation that is progressively reduced as the search process approaches the optimum. This strategy aims to obtain always feasible optimized designs. The new algorithm is tested using three classical sizing optimization problems of 2D and 3D truss structures. optimization results show that the proposed method is competitive with other state-of-the-art metaheuristic algorithms presented in the literature. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Flower pollination algorithm Truss structures sizing optimization Iterative constraint handling strategy

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sizing optimization, dynamic modeling and energy management strategies of a stand-alone PV/hydrogen/battery-based hybrid system

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2013年第10期38卷 3830-3845页

作者： Castaneda, Manuel Cano, Antonio Jurado, Francisco Sanchez, Higinio Fernandez, Luis M. Univ Cadiz EPS Algeciras Dept Elect Engn Algeciras 11202 Cadiz Spain Univ Jaen EPS Linares Dept Elect Engn Linares 23700 Jaen Spain Univ Cadiz ESI Cadiz Dept Elect Engn Cadiz 11002 Spain

This paper presents a sizing method and different control strategies for the suitable energy management of a stand-alone hybrid system based on photovoltaic (PV) solar panels, hydrogen subsystem and battery. The battery and hydrogen subsystem, which is composed of fuel cell (FC), electrolyzer and hydrogen storage tank, act as energy storage and support system. In order to efficiently utilize the energy sources integrated in the hybrid system, an appropriate sizing is necessary. In this paper, a new sizing method based on Simulink Design optimization (SDO) of MATLAB was used to perform a technical optimization of the hybrid system components. An analysis cost has been also performed, in that the configuration under study has been compared with those integrating only batteries and only hydrogen system. The dynamic model of the designed hybrid system is detailed in this paper. The models, implemented in MATLAB-Simulink environment, have been designed from commercially available components. Three control strategies based on operating modes and combining technical-economic aspects are considered for the energy management of the hybrid system. They have been designed, primarily, to satisfy the load power demand and, secondarily, to maintain a certain level at the hydrogen tank (hydrogen energy reserve), and at the state of charge (SOC) of the battery bank to extend its life, taking into account also technical-economic analysis. Dynamic simulations were performed to evaluate the configuration, sizing and control strategies for the energy management of the hybrid system under study in this work. Simulation results show that the proposed hybrid system with the presented controls is able to provide the energy demanded by the loads, while maintaining a certain energy reserve in the storage sources. Copyright (C) 2013, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

关键词： sizing optimization Hydrogen Battery Photovoltaic Control strategies

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sizing optimization and Energy Management Strategy for Hybrid Energy Storage System Using Multiobjective optimization and Random Forests

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IEEE TRANSACTIONS ON POWER ELECTRONICS 2021年第10期36卷 11421-11430页

作者： Li, Mince Wang, Li Wang, Yujie Chen, Zonghai Univ Sci & Technol China Dept Automat Hefei 230052 Peoples R China

sizing optimization and energy management strategy (EMS) are two key points for the application of the hybrid energy storage system (HESS) in electric vehicles. This article aims to conduct the sizing optimization of HESS and apply an adaptive real-time EMS for practice. First, considering the system cost and battery lifespan, the multiobjective grey wolf optimizer is used to obtain the Pareto front. Second, with optimal parameters, the offline optimal power splitting results by dynamic programming (DP) under different driving patterns are analyzed. Then, the random forests (RF) method is used to learn control rules from the DP results. Driving pattern recognition (DPR) is implemented by the support vector machine (SVM). The intelligent EMS is composed of RF to guide power distribution and SVM to realize DPR. Finally, a combined load cycle involving different driving patterns is used for verification. Results illustrate that the proposed adaptive RF-based EMS can demonstrate a notable superiority in terms of battery protection, ultra-capacitor utilization, and system efficiency. Compared with the ordinary RF-based EMS without DPR, the proposed method can reduce total energy loss by 0.74%-9.49%, and reduce the battery Ah-throughput by 0.5%-19.83% under unknown driving cycles.

关键词： Batteries Energy management Topology optimization Resistance Energy storage Support vector machines Energy management strategy (EMS) hybrid energy storage system (HESS) multiobjective grey wolf optimizer (GWO) random forests (RF) sizing optimization

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sizing optimization of exposed steel penstocks supported by ring girders using the combined ANN-GA technique

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STRUCTURES 2020年 24卷 705-716页

作者： Haddouch, Manal Hajjout, Imane Boudi, El Mostapha Mohammadia Sch Engn Dept Mech Engn Rabat Morocco

The design of penstock is a major concern in the implementation of large hydropower plants, where penstock is a large-scale structure. A design procedure incorporating the combined ANN-GA approach was developed for optimizing the exposed penstock supported by ring girders. The objective function considered is the total mass of the penstock to be minimized under the strength requirements. For this purpose, a numerical finite element analysis (FEA) model of a steel exposed penstock supported by ring girders was used to evaluate the equivalent and local stresses on the penstock shell. Parametric analysis was conducted to examine the influence of penstock thickness, ring girders spacing, and sectional size of the T-shaped ring girders on the weight of the penstock and the maximum equivalent stress. Subsequently, an artificial neural network (ANN) was developed by collecting data from the FEA numerical results, before being combined with a genetic algorithm to provide the optimal design of the penstock. The results of the FEA give a detailed distribution of local stresses in the penstock shell. The performance of the trained ANN was illustrated, and its prediction results show good agreement with the FEA numerical results. The results obtained by the ANN-GA approach proved the efficiency of the proposed process in optimizing the exposed penstock supported by ring girders. This process should be a valuable aid for the design of large penstocks.

关键词： Exposed penstock sizing optimization Ring girders ANN-GA

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sizing optimization OF LIGHTWEIGHT MULTILAYER THERMAL PROTECTION STRUCTURES FOR HYPERSONIC AIRCRAFT

SIZING OPTIMIZATION OF LIGHTWEIGHT MULTILAYER THERMAL PROTEC...

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ASME International Mechanical Engineering Congress and Exposition

作者： Wang, Qi Xie, Gongnan Xiao, Manyu Zhang, Weihong Sunden, Bengt Northwestern Polytech Univ Lab Engn Simulat & Aerosp Comp Xian 710072 Shaanxi Peoples R China

ISBN: (纸本)9780791845172

In the context of hypersonic aircraft design, the major issue of the thermal protection system (TPS) is to obtain the optimal thickness of the insulation layers due to intense aerodynamic heating during re-entering earth's atmosphere. In this study, an idea combining a transient heat transfer model and an efficient optimization model is introduced for multi-layer insulation of TPS. The TPS geometric dimensions in the thickness direction are particularly considered as the design variables and the objective function is the mass of the thermal protection structure with the limitation of the extreme temperatures of the hypersonic vehicle structure. In order to decrease the computational complexity, the Globally Convergent Method of Moving Asymptotes (GCMMA) method is specially used to search the optimal solution. The results show that the usage of multilayer insulation materials for the TPS can save more than 25% weight compared to a single-layer TPS. The detailed analysis and comparison indicate the advantages of the presented optimization model

关键词： Hypersonic aircraft Thermal protection system sizing optimization Thermal analyses

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sizing optimization of a Charging Station Based on the Multi-scale Current Profile and Particle Swarm optimization: Application to Power-assisted Bikes 16

Sizing Optimization of a Charging Station Based on the Multi...

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16th International Conference on Ecological Vehicles and Renewable Energies (EVER)

作者： Nkounga, Willy Magloire Ndiaye, Mouhamadou Falilou Ndiaye, Mamadou Lamine Grandvaux, Francoise Tabourot, Laurent Conde, Mamady Univ Savoie Mt Blanc SYMME F-74000 Annecy France Univ Cheikh Anta Diop UCAD Ecole Super Polytech ESP Lab Eau Energie Environm Proc Ind LE3PI Dakar Senegal LE3PI ESP UCAD Dakar Senegal Univ Gamal Abdel Nasser Lab Machines Elect Conakry Guinea

ISBN: (纸本)9781665449021

The development of power-assisted bikes (ebike) is of growing interest because of their economic and environmental advantages. The present work deals with the sizing optimization of a charging station for ebike based on particle swarm optimization. It is based on the consumption profile of ebike batteries, solar and wind power, installation, replacement and maintenance costs of components. In a first step, the consumption profile of the ebike batteries is determined using the second order non-linear electrothermal model. Then, the solar and wind data over one year are used to determine the availability of energy at the implementation site of the charging station. Finally, the cost is defined as an objective function, taking into account the constraints on the number of solar photovoltaic panels, the number of wind turbines, the number of storage batteries and the annual charging demand. The context of a charging station to be implemented in the Polytech Annecy campus in France is studied. The results show that the particle swarm optimization allows a cost reduction of around 56.04% compared to a sizing without optimization.

关键词： sizing optimization charging station particle swarm optimization costs ebike

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Component sizing optimization of plug-in hybrid electric vehicles with the hybrid energy storage system

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ENERGY 2018年 144卷 393-403页

作者： Song, Ziyou Zhang, Xiaobin Li, Jianqiu Hofmann, Heath Ouyang, Minggao Du, Jiuyu Tsinghua Univ State Key Lab Automot Safety & Energy Beijing 100084 Peoples R China Collaborat Innovat Ctr Elect Vehicles Beijing Beijing 100081 Peoples R China Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA

The Pontryagin's minimum principle is utilized in this paper to determine the best solution of component sizing and energy management strategy for a plug-in hybrid electric vehicle which is equipped with a hybrid energy storage system. The hybrid energy storage system, including batteries and super capacitors, is an effective solution to extend battery life span and reduce the vehicle operating cost. The operating costs of different hybrid energy storage system candidates, including fuel cost, electricity cost, and battery degradation cost over 6 consecutive China bus driving cycles, are minimized by using a 2-dimensional Pontryagin's minimum principle algorithm proposed in this paper. The proposed Pontryagin's minimum principle algorithm not only determines the optimal energy management strategy, but also globally finds the optimal battery and supercapacitor sizes. It is shown that the operating cost strictly decreases with increasing battery and supercapacitor sizes. In addition, simulation results show that the operating cost is reduced'by up to 28.6% when compared to a conventional hybrid powertrain without supercapacitors. Thus the effectiveness of adopting supercapacitors in plug-in hybrid electric vehicles is verified. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Plug-in hybrid electric vehicle Hybrid energy storage system sizing optimization Pontryagin's minimum principle Battery degradation Operating cost

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Optimal Dosing and sizing optimization for a Ground-Vehicle Diesel-Engine Two-Cell Selective Catalytic Reduction System

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2016年第6期65卷 4740-4751页

作者： Zhang, Hui Wang, Junmin Wang, Yue-Yun Beihang Univ Sch Transportat Sci & Engn Beijing 100191 Peoples R China Ohio State Univ Dept Mech & Aerosp Engn Columbus OH 43210 USA Gen Motors Global Res & Dev Ctr Prop Syst Res Lab Warren MI 48090 USA

In this paper, we investigate the cycle-based sizing optimization for diesel-engine two-cell selective catalytic reduction ( SCR) systems. In modeling the SCR system, it is generally assumed that the states inside the catalyst can are homogeneous to simplify the modeling work. However, the actual states are not homogeneous, and the modeling error becomes large if the catalyst length is long. To reduce the modeling error, the states are assumed piecewise homogeneous, i. e., the catalyst is sliced into multicells and the states for each cell are assumed homogeneous. In this paper, we focus on the two-cell SCR systems where the two cells are connected in series and where the chemical reaction rates are assumed identical for the two cells. Considering the main chemical reactions and assuming that each cell is a continuous stirred tank reactor, a nonlinear system model with six states is obtained. To simultaneously reduce the tailpipe NOx and ammonia slip, it is quite interesting to study the optimal control of the urea dosing such that the NOx emissions can be maximally converted and where the ammonia slip is constrained. A dynamic programming ( DP) algorithm that has a tolerable computational load is proposed. Since the whole catalyst is sliced into two cells, the next motivation is how to divide the catalyst such that the NOx conversion efficiency can be maximized while meeting the tailpipe ammonia constraint. The best sizing ratio of the SCR system in our application for the US06 test cycle is found to be 60%-40%.

关键词： Dynamic programming (DP) emission control modeling and identification selective catalytic reduction (SCR) sizing optimization

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Adaptive dimensional search: A new metaheuristic algorithm for discrete truss sizing optimization

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COMPUTERS & STRUCTURES 2015年 154卷 1-16页

作者： Hasancebi, Oguzhan Azad, Saeid Kazemzadeh Middle E Tech Univ Dept Civil Engn TR-06531 Ankara Turkey Atilim Univ Dept Civil Engn Ankara Turkey

In the present study a new metaheuristic algorithm called adaptive dimensional search (ADS) is proposed for discrete truss sizing optimization problems. The robustness of the ADS lies in the idea of updating search dimensionality ratio (SDR) parameter online during the search for a rapid and reliable convergence towards the optimum. In addition, several alternative stagnation-control strategies are integrated with the algorithm to escape from local optima, in which a limited uphill (non-improving) move is permitted when a stagnation state is detected in the course of optimization. Besides a remarkable computational efficiency, the ease of implementation and capability of locating promising solutions for challenging instances of practical design optimization are amongst the remarkable features of the proposed algorithm. The efficiency of the ADS is investigated and verified using two benchmark examples as well as three real-world problems of discrete sizing truss optimization. A comparison of the numerical results obtained using the ADS with those of other metaheuristic techniques indicates that the proposed algorithm is capable of locating improved solutions using much lesser computational effort. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Structural optimization Optimal design Metaheuristic techniques Discrete variables sizing optimization Steel truss structures

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