جستجوی مقالات مرتبط با کلیدواژه « truss structure » در نشریات گروه « عمران »
تکرار جستجوی کلیدواژه « truss structure » در نشریات گروه « فنی و مهندسی »-
در این پژوهش در شرایط مختلف، رفتار سیستم نگهدارنده تیرک مایل و سازه نگهبان خرپایی بررسی شده است. برای این منظور حرکات افقی و عمودی خاک در اثر گودبرداری و سطح خرابی ساختمان های مجاور این سیستم ها برای نگهداری گود تعیین می شود. گودبرداری در سه عمق 4، 7 و 10متر مورد بررسی قرار گرفته است که به ترتیب نشان دهنده گود-های کم عمق، با عمق متوسط و با عمق زیاد هستند. از معیار رفتاری مور کولمب برای رفتار خاک استفاده شد. گودبرداری بصورت مرحله ای با نرم افزار PLAXIS مدل سازی گردید. با مقایسه خروجی های بدست آمده از مدل سازی عددی اینگونه نتیجه گیری گردید که جابجایی افقی و قایم خاک، در مدل های تیرک مایل بیشتر از مدل های سازه نگهبان خرپایی تست. دلیل آن عدم وجود عضو قایم و سیستم مهاربندی جانبی در تیرک مایل، برخلاف سازه نگهبان خرپایی است. مقادیر تنش و عکس العمل های تکیه گاهی در روش تیرک مایل، بیشتر از عضو مایل سازه نگهبان خرپایی بدست آمد که دلیل آن وجود درجات نامعینی بیشتر در خرپا است که باعث انتقال تنش از مسیرهای بیشتر و کمتر شدن مقدار عکس العمل های تکیه گاهی می شود. در نهایت براساس روش شاخص پتانسیل خرابیDPI مشخص گردید که از بین دو سیستم تیرک مایل و سازه نگهبان خرپایی برای پایدارسازی گودبرداری در مجاورت ساختمان همسایه در مناطق شهری ایمنی و مقاومت سازه نگهبان خرپایی بیشتر و استفاده از خرپا مطمین تر است.
کلید واژگان: گودبرداری, سازه های نگهبان خرپایی, پلاکسیس, سیستم تیرک مایل گود, اجزای محدود, شاخص پتانسیل خرابیDPI}In this research, in different conditions, the behavior of the inclined Struts support system and truss guard structure has been investigated. For this purpose, the horizontal and vertical movements of the soil due to excavation and the level of damage of buildings adjacent to these systems are determined to maintain the excavation. Excavation has been studied at three depths of 4, 7 and 10 meters, which indicate shallow, medium and high depth excavation, respectively. Mohr-Columb's behavioral criterion was used for soil behavior. The excavation was modeled in stages with PLAXIS software. Comparing the outputs obtained from numerical modeling, it was concluded that the horizontal and vertical soil displacement in the inclined Struts models is more than the truss guard structure models. The reason is the lack of vertical member and lateral bracing system in the Inclined Struts, unlike the truss guard structure. The values of stress and abutment reactions in the Inclined Struts method were obtained more than the oblique member of the truss guard structure due to the presence of more indefinite degrees in the truss, which causes stress transfer from more paths and less abutment reactions. Finally, based on the damage potential index DPI, it was determined that between the two systems of Inclined Struts and truss guard structure to stabilize the excavation in the vicinity of the neighboring building in urban areas, the safety and strength of the truss guard structure and the use of truss is safer.
Keywords: Excavation, Inclined Struts, Truss structure, Finite Element, Plaxis, Damage Potential Index DPI} -
International Journal of Optimization in Civil Engineering, Volume:9 Issue: 3, Summer 2019, PP 499 -523Opposition-based learning was first introduced as a solution for machine learning; however, it is being extended to other artificial intelligence and soft computing fields including meta-heuristic optimization. It not only utilizes an estimate of a solution but also enters its counter-part information into the search process. The present work applies such an approach to Colliding Bodies Optimization as a powerful meta-heuristic with several engineering applications. Special combination of static and dynamic opposition-based operators are hybridized with CBO so that its performance is enhanced. The proposed OCBO is validated in a variety of benchmark test functions in addition to structural optimization and optimal clustering. According to the results, the proposed method of opposition-based learning has been quite effective in performance enhancement of parameter-less colliding bodies optimization.Keywords: Opposition-based learning, truss structure, building frame, sizing design, geometry optimization, ground motion clustering.}
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International Journal of Optimization in Civil Engineering, Volume:7 Issue: 1, Winter 2017, PP 13 -23In this study an efficient meta-heuristic is proposed for layout optimization of truss structures by combining cellular automata (CA) and firefly algorithm (FA). In the proposed meta-heuristic, called here as cellular automata firefly algorithm (CAFA), a new equation is presented for position updating of fireflies based on the concept of CA. Two benchmark examples of truss structures are presented to illustrate the efficiency of the proposed algorithm. Numerical results reveal that the proposed algorithm is a powerful optimization technique with improved convergence rate in comparison with other existing algorithms.Keywords: layout optimization, firefly algorithm, cellular automata, truss structure}
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International Journal of Optimization in Civil Engineering, Volume:4 Issue: 2, Spring 2014, PP 187 -205This paper presents an improved multi-objective group search optimizer (IMGSO) that is based on Pareto theory that is designed to handle multi-objective optimization problems. The optimizer includes improvements in three areas: the transition-feasible region is used to address constraints, the Dealer’s Principle is used to construct the non-dominated set, and the producer is updated using a tabu search and a crowded distance operator. Two objective optimization problems, the minimum weight and maximum fundamental frequency, of four truss structures were optimized using the IMGSO. The results show that IMGSO rapidly generates the non-dominated set and is able to handle constraints. The Pareto front of the solutions from IMGSO is clearly dominant and has good diversity.Keywords: improved group search optimizer, multi, objective optimization, dynamic performance, truss structure}
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International Journal of Optimization in Civil Engineering, Volume:3 Issue: 3, Summer 2013, PP 431 -444A novel optimization algorithm named teaching-learning-based optimization (TLBO) algorithm and its implementation procedure were presented in this paper. TLBO is a meta-heuristic method, which simulates the phenomenon in classes. TLBO has two phases: teacher phase and learner phase. Students learn from teachers in teacher phases and obtain knowledge by mutual learning in learner phase. The suitability of TLBO for size and geometry optimization of structures in structural optimal design was tested by three truss examples. Meanwhile, these examples were used as benchmark structures to explore the effectiveness and robustness of TLBO. The results were compared with those of other algorithms. It is found that TLBO has advantages over other optimal algorithms in convergence rate and accuracy when the number of variables is the same. It is much desired for TLBO to be applied to the tasks of optimal design of engineering structures.Keywords: teaching, learning, based optimization (TLBO), size, geometry optimization, truss structure}
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In the present study, the computational performance of the particle swarm optimization (PSO) harmony search (HS) and firefly algorithm (FA), as popular metaheuristics, is investigated for size and shape optimization of truss structures. The PSO was inspired by the social behavior of organisms such as bird flocking. The HS imitates the musical performance process which takes place when a musician searches for a better state of harmony, while the FA was based on the idealized behavior of the flashing characteristics of natural fireflies. These algorithms were inspired from different natural sources and their convergence behavior is focused in this paper. Several benchmark size and shape optimization problems of truss structures are solved using PSO, HS and FA and the results are compared. The numerical results demonstrate the superiority of FA to HS and PSO.Keywords: Optimum design, Truss structure, Metaheuristic, Particle swarm optimization, Harmony search, Firefly algorithm}
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International Journal of Optimization in Civil Engineering, Volume:1 Issue: 3, Summer 2011, PP 485 -494The main aim of the present study is to propose a modified harmony search (MHS) algorithm for size and shape optimization of structures. The standard harmony search (HS) algorithm is conceptualized using the musical process of searching for a perfect state of the harmony. It uses a stochastic random search instead of a gradient search. The proposed MHS algorithm is designed based on elitism. In fact the MHS is a multi-staged version of the HS and in each stage a new harmony memory is created using the information of the previous stages. Numerical results reveal that the proposed algorithm is a powerful optimization technique with improved exploitation characteristics compared with the standard HS.Keywords: Shape optimization, harmony search algorithm, penalty functions, truss structure}
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