Showing 114 results for Design
M. Shahrouzi, R. Jafari,
Volume 12, Issue 2 (4-2022)
Abstract
Despite comprehensive literature works on developing fitness-based optimization algorithms, their performance is yet challenged by constraint handling in various engineering tasks. The present study, concerns the widely-used external penalty technique for sizing design of pin-jointed structures. Observer-teacher-learner-based optimization is employed here since previously addressed by a number of investigators as a powerful meta-heuristic algorithm. Several cases of penalty handling techniques are offered and studied using either maximum or summation of constraint violations as well as their combinations. Consequently, the most successive sequence, is identified for the treated continuous and discrete structural examples. Such a dynamic constraint handling is an affordable generalized solution for structural sizing design by iterative population-based algorithms.
R. Babaei Semriomi, A. Keyhani,
Volume 12, Issue 2 (4-2022)
Abstract
This paper introduces a reliability-based multi-objective design method for spatial truss structures. A multi-objective optimization problem has been defined considering three conflicting objective functions including truss weight, nodal deflection, and failure probability of the entire truss structure with design variables of cross sectional area of the truss members. The failure probability of the entire truss system has been determined considering the truss structure as a series system. To this end, the uncertainties of the applied load and the resistance of the truss members have been accounted by generating a set of 50 random numbers. The limitations of members' allowable have been defined as constraints. To explain the methodology, a 25-bar benchmark spatial truss has been considered as the case study structure and has been optimally designed using the game theory concept and genetic algorithm (GA). The results show effectiveness and simplicity of the proposed method which can provide Pareto optimal solution. These optimal solutions can provide both safety and reliability for the truss structure.
Sh. Bijari, M. Sheikhi Azqandi,
Volume 12, Issue 2 (4-2022)
Abstract
In this paper, a new robust metaheuristic optimization algorithm called improved time evolutionary optimization (ITEO) is applied to design reinforced concrete one-way ribbed slabs. Geometric and strength characteristics of concrete slabs are considered as design variables. The optimal design is such that in addition to achieving the minimum cost, all design constraints are satisfied under American Concrete Institute’s ACI 318-05 Standard. So, the numerical examples considered in this study have a large number of design variables and design constraints that make it complicated to converge the global optimal design. The ITEO has an excellent balance between the two phases of exploration and extraction and it has a high ability to find the optimal point of such problems. The comparison results between the ITEO and some other metaheuristic algorithms show the proposed method is competitive compared to others, and in some cases, superior to some other available metaheuristic techniques in terms of the faster convergence rate, performance, robustness of finding an optimal design solution, and needs a smaller number of function evaluations for designing considered constrained engineering problems.
B. Ganjavi, M. Bararnia,
Volume 12, Issue 3 (4-2022)
Abstract
In present study, the effects of optimization on seismic energy spectra including input energy, damping energy and yielding hysteretic energy are parametrically discussed. To this end, 12 generic steel moment-resisting frames having fundamental periods ranging from 0.3 to 3s are optimized by using uniform damage and deformation approaches subjected to a series of 40 non-pule strong ground motions. In order to obtain the optimum distribution of structural properties, an iterative optimization procedure has been adopted. In this approach, the structural properties are modified so that inefficient material is gradually shifted from strong to weak areas of a structure. This process is continued until a state of uniform damage is achieved. Then, the maximum energy demand parameters are computed for different structures designed by optimum load pattern as well as code-based pattern, and the mean energy spectra, energy-based reduction factor and the dispersion of the results are compared and discussed. Results indicate that optimum seismic load pattern can significantly affect the energy demands spectra especially in inelastic range of response. In addition, using energy-based reduction factors of optimum structures in short-period and long-period regions will result in respectively overestimation and underestimation of the required input energy demands for code-based structures, reflecting the difference dose exists in reality between the conventional forced-based methodology and energy-based seismic design approach that can more realistically incorporate the frequency content and duration of earthquake ground motions.
R. Bagherzadeh, A. Riahi Nouri, M. S. Massoudi, M. Ghazi , F. Haddad Sharg,
Volume 12, Issue 3 (4-2022)
Abstract
The main purpose of this paper was to use a combination of Energy-based design method and whale algorithm (WOA), hereinafter referred to as E-WOA, to optimize steel moment frames and improve the seismic performance. In E-WOA, by properly estimating the seismic input energy and determining the optimal mechanism for the structure, steel frames are designed based on the energy balance method; according to the results, in a suitable search space, optimization is performed using the WOA algorithm. The objective function of the WOA algorithm, in addition to the frame weight, is meant to improve the behavior of the structure based on the performance level criteria of the ASCE41-17 standard and the uniformity of the drift distribution at the frame height. The results show that the initial design of the Energy method reduces the computational volume of the WOA algorithm to achieve the optimal solution and the plastic hinge pattern in frame is more favorable in the E-WOA method than in the design done by the Energy method.
P. Hosseini, A. Kaveh, N. Hatami, S. R. Hoseini Vaez,
Volume 12, Issue 3 (4-2022)
Abstract
Metaheuristic algorithms are preferred by the many researchers to reach the reliability based design optimization (RBDO) of truss structures. The cross-sectional area of the elements of a truss is considered as design variables for the size optimization under frequency constraints. The design of dome truss structures are optimized based on reliability by a popular metaheuristic optimization technique named Enhanced Vibrating Particle System (EVPS). Finite element analyses of structures and optimization process are coded in MATLAB. Large-scale dome truss of 600-bar, 1180-bar and 1410-bar are investigated in this paper and are compared with the previous studies. Also, a comparison is made between the reliability indexes of Deterministic Design Optimization (DDO) for large dome trusses and Reliability-Based Design Optimization (RBDO).
H. Fazli,
Volume 12, Issue 4 (8-2022)
Abstract
A dual structural fused system consists of replaceable ductile elements (fuses) that sustain major seismic damage and leave the primary structure (PS) virtually undamaged. The seismic performance of a fused structural system is determined by the combined behavior of the individual PS and fuse components. In order to design a feasible and economic structural fuse concept, we need a procedure to choose the most efficient combination of the PS and fuse systems subject to the stringent constraints of seismic performance and minimum structural cost objectives, simultaneously. In this paper, an efficient method is developed for minimum cost design of dual fused building structures using a performance-based seismic design procedure. The method involves updating a set of reference parameters to find the most suitable combination of PS and fuse structures with satisfactory seismic performance and optimum total structural cost, concurrently. For a set of preselected reference parameters, the structural design variables including primary and fuse structural member sizes are determined through individual linear elastic design processes. Therefore, a limited number of inelastic analyses are required to evaluate seismic response of the combined fused system. The proposed method is applied to seismic design optimization of a moment resisting frame equipped with BRBs as structural fuses. The obtained results indicate that proposed design optimization procedure is sufficiently robust and reliable to design cost-effective structural fuse systems with satisfactory seismic performance.
P. Hosseini, A. Kaveh, S. R. Hoseini Vaez,
Volume 12, Issue 4 (8-2022)
Abstract
The existence of uncertainties in engineering problems makes it essential to consider these effects at all times. Robust design optimization allows a design to be made less sensitive to uncertain input parameters. Actually, robust design optimization reduces the sensitivity of the objective function and the variations in design performance when uncertainty exists. In this study, two space trusses were optimized based on the modulus of elasticity, yield stress, and cross-sectional uncertainties in order to increase the response robustness and decrease the weight. The displacement of one node has been used as the criterion for Robust Design Optimization (RDO) of these two structures. Two trusses with 72 members and 582 members are considered, which are famous trusses in the field of structural optimization. Also, the EVPS meta-heuristic algorithm was employed which is an enhanced version of the VPS algorithm based on the single degrees of freedom of a system with viscous damping.
M. Ilchi Ghazaan , A.h. Salmani Oshnari , A. M. Salmani Oshnari,
Volume 13, Issue 1 (1-2023)
Abstract
Colliding Bodies Optimization (CBO) is a population-based metaheuristic algorithm that complies physics laws of momentum and energy. Due to the stagnation susceptibility of CBO by premature convergence and falling into local optima, some meritorious methodologies based on Sine Cosine Algorithm and a mutation operator were considered to mitigate the shortcomings mentioned earlier. Sine Cosine Algorithm (SCA) is a stochastic optimization method that employs sine and cosine based mathematical models to update a randomly generated initial population. In this paper, we developed a new hybrid approach called hybrid CBO with SCA (HCBOSCA) to obtain reliable structural design optimization of discrete and continuous variable structures, where a memory was defined to intensify the convergence speed of the algorithm. Finally, three structural problems were studied and compared to some state of the art optimization methods. The experimental results confirmed the competence of the proposed algorithm.
S. Mohammadhosseini , S. Gholizadeh,
Volume 13, Issue 1 (1-2023)
Abstract
The main aim of this study, is to evaluate the seismic reliability of steel concentrically braced frame (SCBF) structures optimally designed in the context of performance-based design. The Monte Carlo simulation (MCS) method and neural network (NN) techniques were utilized to conduct the reliability analysis of the optimally designed SCBFs. Multi-layer perceptron (MLP) trained by back propagation technique was used to evaluate the required structural responses and then the total exceedence probability associated with the seismic performance levels was estimated by the MCS method. Three numerical examples of 5-, 10-, and 15-story SCBFs with fixed and optimal topology of braces are presented and their probability of failure was evaluated considering the resistance characteristics and the seismic loading of the structures. The numerical results indicate that the SCBFs with optimal topology of braces were more reliable than those with fixed topology of braces.
M. Nabati , S. Gholizadeh,
Volume 13, Issue 2 (4-2023)
Abstract
The purpose of the current study is to design steel moment resisting frames for optimal weight in the context of performance-based design. The performance-based design optimization of steel moment frames is a highly nonlinear and complex optimization problem having many local optima. Therefore, an efficient algorithm should be used to deal with this class of structural optimization problems. In the present study, a modified Newton metaheuristic algorithm (MNMA) is proposed for the solution of the optimization problem. In fact, MNMA is the improved version of the original Newton metaheuristic algorithm (NMA), which is a multi-stage optimization technique in which an initial population is generated at each stage based on the results of the previous stages. Two illustrative examples of 5-, and 10-story steel moment frames are presented and a number of independent optimization runs are achieved by NMA and MNMA. The numerical results demonstrate the better performance of the proposed MNMA compared to the NMA in solving the performance-based optimization problem of steel moment frames.
A. Kaveh, A. Zaerreza, J. Zaerreza,
Volume 13, Issue 2 (4-2023)
Abstract
Vibrating particles system (VPS) is a swarm intelligence-based optimizer inspired by free vibration with a single degree of freedom systems. VPS is one of the well-known algorithms in structural optimization problems. However, its performance can be improved to find a better solution. This study introduces an improved version of the VPS using the statistical regeneration mechanism for the optimal design of the structures with discrete variables. The improved version is named VPS-SRM, and its efficiency is tested in the three real-size optimization problems. The optimization results reveal the capability and robustness of the VPS-SRM for the optimal design of the structures with discrete sizing variables.
S. Gholizadeh, C. Gheyratmand , N. Razavi,
Volume 13, Issue 3 (7-2023)
Abstract
The main objective of this study is to optimize reinforced concrete (RC) frames in the framework of performance-based design using metaheuristics. Three improved and efficient metaheuristics are employed in this work, namely, improved multi-verse (IMV), improved black hole (IBH) and modified newton metaheuristic algorithm (MNMA). These metaheuristic algorithms are applied for performance-based design optimization of 6- and 12-story planar RC frames. The seismic response of the structures is evaluated using pushover analysis during the optimization process. The obtained results show that the IBH outperforms the other algorithms.
G. Sedghi, S. Gholizadeh, S. Tariverdilo ,
Volume 13, Issue 4 (10-2023)
Abstract
In this paper an enhanced ant colony optimization algorithm with a direct constraints handling strategy is proposed for the optimization of reinforced concrete frames. The construction cost of reinforced concrete frames is considered as the objective function, which should be minimized subject to geometrical and behavioral strength constraints. For this purpose, a new probabilistic function is added to the ant colony optimization algorithm to directly satisfy the geometrical constraints. Furthermore, the position of an ant in each iteration is updated if a better solution is found in terms of objective value and behavioral strength constraints satisfaction. Five benchmark design examples of planar reinforced concrete frames are presented to illustrate the efficiency of the proposed algorithm.
A. Hadinejad, B. Ganjavi,
Volume 14, Issue 1 (1-2024)
Abstract
In this study, the investigation of maximum inelastic displacement demands in steel moment- resisting (SMR) frames designed using the Performance-Based Plastic Design (PBPD) method is conducted under both near-fault and far-fault earthquake records. The PBPD method utilizes a target drift and predetermined yield mechanism as the functional limit state. To accomplish this, 6 steel moment frames having various heights were scaled using well-known sa(T1) method and, then, were analyzed by OPENSEES software. A total of 22 far-fault records and 90 near-fault records were compiled and employed for parametric nonlinear dynamic analysis. The near-fault records were classified into two categories: T1/Tp≥1 and T1/Tp<1 . The study aimed at investigate their impacts on the inter-story drift and the relative distribution of base shear along the height of the structure. The results revealed that the records with T1/Tp≥1 exerted the greatest influence on the drift demands of upper stories in all frames. Conversely, the near-fault records with T1/Tp<1 demonstrated the most significant impact on the lower stories of mid-rise frames. Additionally, the distribution of relative story shears was examined through genetic programming for optimum PBPD design of steel moment frame structures. As a result, a proposed relationship, denoted as b (seismic parameter for design lateral force distribution), was developed and optimized for both near-fault and far-fault records. This relationship depends on the fundamental period of vibration and the total height of the structure. The accuracy of the predicted model was assessed using R2 , which confirmed the reliability of the proposed relationship.
V. Goodarzimehr, F. Salajegheh,
Volume 14, Issue 1 (1-2024)
Abstract
The analysis and design of high-rise structures is one of the challenges faced by researchers and engineers due to their nonlinear behavior and large displacements. The moment frame system is one of the resistant lateral load-bearing systems that are used to solve this problem and control the displacements in these structures. However, this type of structural system increases the construction costs of the project. Therefore, it is necessary to develop a new method that can optimize the weight of these structures. In this work, the weight of these significant structures is optimized by using one of the latest metaheuristic algorithms called special relativity search. The special relativity search algorithm is mainly developed for the optimization of continuous unconstrained problems. Therefore, a penalty function is used to prevent violence of the constraints of the problem, which are tension, displacement, and drift. Also, using an innovative technique to transform the discrete problem into a continuous one, the optimal design is carried out. To prove the applicability of the new method, three different problems are optimized, including an eight-story one-span, a fifteen-story three-span bending frame, and a twenty-four-story three-span moment frame. The weight of the structure is the objective function, which should be minimized to the lowest possible value without violating the constraints of the problem. The calculation of stress and displacements of the structure is done based on the regulations of AISC-LRFD requirements. To validate, the results of the proposed algorithm are compared with other advanced metaheuristic methods.
P. Hosseini, A. Kaveh, A. Naghian, A. Abedi,
Volume 14, Issue 3 (6-2024)
Abstract
This study aimed to develop and optimize artificial stone mix designs incorporating microsilica using artificial neural networks (ANNs) and metaheuristic optimization algorithms. Initially, 10 base mix designs were prepared and tested based on previous experience and literature. The test results were used to train an ANN model. The trained ANN was then optimized using SA-EVPS and EVPS algorithms to maximize 28-day compressive strength, with aggregate gradation as the optimization variable. The optimized mixes were produced and tested experimentally, revealing some discrepancies with the ANN predictions. The ANN was retrained using the original and new experimental data, and the optimization process was repeated iteratively until an acceptable agreement was achieved between predicted and measured strengths. This approach demonstrates the potential of combining ANNs and metaheuristic algorithms to efficiently optimize artificial stone mix designs, reducing the need for extensive physical testing.
F. Biabani, A. A. Dehghani, S. Shojaee, S. Hamzehei-Javaran,
Volume 14, Issue 3 (6-2024)
Abstract
Optimization has become increasingly significant and applicable in resolving numerous engineering challenges, particularly in the structural engineering field. As computer science has advanced, various population-based optimization algorithms have been developed to address these challenges. These methods are favored by most researchers because of the difficulty of calculations in classical optimization methods and achieving ideal solutions in a shorter time in metaheuristic technique methods. Recently, there has been a growing interest in optimizing truss structures. This interest stems from the widespread utilization of truss structures, which are known for their uncomplicated design and quick analysis process. In this paper, the weight of the truss, the cross-sectional area of the members as discrete variables, and the coordinates of the truss nodes as continuous variables are optimized using the HGPG algorithm, which is a combination of three metaheuristic algorithms, including the Gravity Search Algorithm (GSA), Particle Swarm Optimization (PSO), and Gray Wolf Optimization (GWO). The presented formulation aims to improve the weaknesses of these methods while preserving their strengths. In this research, 15, 18, 25, and 47-member trusses were utilized to show the efficiency of the HGPG method, so the weight of these examples was optimized while their constraints such as stress limitations, displacement constraints, and Euler buckling were considered. The proposed HGPG algorithm operates in discrete and continuous modes to optimize the size and geometric configuration of truss structures, allowing for comprehensive structural optimization. The numerical results show the suitable performance of this process.
S. Gholizadeh, S. Tariverdilo,
Volume 14, Issue 3 (6-2024)
Abstract
The primary objective of this paper is to assess the seismic life-cycle cost of optimally designed steel moment frames. The methodology of this paper involves two main steps. In the first step, we optimize the initial cost of steel moment frames within the performance-based design framework, utilizing nonlinear static pushover analysis. In the second step, we perform a life cycle-cost analysis of the optimized steel moment frames using nonlinear response history analysis with a suite of earthquake records. We consider content losses due to floor acceleration and inter-story drift for the life cycle cost analysis. The numerical results highlight the critical role of integrating life-cycle cost analysis into the seismic optimization process to design steel moment frames with optimal seismic life-cycle costs.
B. Ahmadi-Nedushan, A. M. Almaleeh,
Volume 14, Issue 4 (10-2024)
Abstract
This study uses an elitist Genetic Algorithm (GA) to optimize material costs in one-way reinforced concrete slabs, adhering to ACI 318-19. A sensitivity analysis demonstrated the critical role of elitism in GA performance. Without elitism, the GA consistently failed to reach the target objective, with success rates often nearing zero across various crossover fractions. Incorporating elitism dramatically increased success rates, highlighting the importance of preserving high-performing individuals. With an optimal configuration of 0.3 crossover fraction and 0.45 elite percentage, a 92% success rate was achieved, finding a cost of 24.91 in 46 of 50 runs for a simply supported slab. This optimized design, compared to designs based on ACI 318-99 and ACI 318-08, yielded material cost savings of between 5.8% to 8.6% for simply supported, one-end continuous, both-ends continuous, and cantilevered slabs. The influence of slab dimensions on cost was evaluated across 64 scenarios, varying slab lengths from 5 to 20 feet for each support condition. Resulting cost versus slab length diagrams illustrate the economic benefits of GA optimization.
