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In this study, the optimum dimensioning of a reinforced concrete retaining wall that meets the safety conditions under static and dynamic loads in terms of cost has been performed using Jaya algorithm, which is one of the metaheuristic algorithms. In the optimization process, reinforced concrete design rules and ground stress, sliding and overturn tests have been determined as design constraints for the safe design of the retaining wall. While 5 cross-section dimensions of the retaining wall are defined as the design variable, the objective function is targeted as the total cost per unit length of the retaining wall. In the study, optimum results are also presented by examining the changes of the toe projection length of the retaining wall, which is one of the design variables, narrowing between 0.2-10 m. The design variables minimizing the objective function were found via Jaya algorithm that have single-phase. In addition to achieving optimum dimensioning results in terms of safety and cost with the optimization method used as a result of the reinforced concrete design made by applying the rules of the regulation on buildings to be constructed in earthquake zones, the change in cost in seismic and static conditions was examined.
Nur Eroğlu; Sena Aral; Sinan Melih Nigdeli; Gebrail Bekdaş. Jaya algorithm based optimum design of reinforced concrete retaining walls under dynamic loads. Challenge Journal of Structural Mechanics 2021, 7, 64 .
AMA StyleNur Eroğlu, Sena Aral, Sinan Melih Nigdeli, Gebrail Bekdaş. Jaya algorithm based optimum design of reinforced concrete retaining walls under dynamic loads. Challenge Journal of Structural Mechanics. 2021; 7 (2):64.
Chicago/Turabian StyleNur Eroğlu; Sena Aral; Sinan Melih Nigdeli; Gebrail Bekdaş. 2021. "Jaya algorithm based optimum design of reinforced concrete retaining walls under dynamic loads." Challenge Journal of Structural Mechanics 7, no. 2: 64.
It is a very known issue that tuned mass dampers (TMDs) on an effective system for structures subjected to earthquake excitations. TMDs can be also used as a protective system for adjacent structures that may pound to each other. With a suitable optimization methodology, it is possible to find an optimally tuned TMD that is effective in reducing the responses of structure with an additional protective feature that reduces the amount of required seismic gap between adjacent structures by using an objective function. This function considers the displacement of structures with respect to each other. As the optimization methodology, the flower pollination algorithm (FPA) is used in finding the optimum parameters of TMDs of both structures. The method was evaluated on two 10-story adjacent structures and the optimum results were compared with harmony search (HS) based methodology.
Sinan Melih Nigdeli; Gebrail Bekdaş; Xin-She Yang. Optimum Design of Tuned Mass Dampers for Adjacent Structures via Flower Pollination Algorithm. Transactions on Petri Nets and Other Models of Concurrency XV 2021, 105 -115.
AMA StyleSinan Melih Nigdeli, Gebrail Bekdaş, Xin-She Yang. Optimum Design of Tuned Mass Dampers for Adjacent Structures via Flower Pollination Algorithm. Transactions on Petri Nets and Other Models of Concurrency XV. 2021; ():105-115.
Chicago/Turabian StyleSinan Melih Nigdeli; Gebrail Bekdaş; Xin-She Yang. 2021. "Optimum Design of Tuned Mass Dampers for Adjacent Structures via Flower Pollination Algorithm." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 105-115.
Total Potential Optimization using Metaheuristic Algorithms (TPO/MA) is an alternative tool for the analysis of structures. It is shown that this emerging method is advantageous in solving nonlinear problems like trusses, tensegrity structures, cable networks, and plane stress systems. In the present study, TPO/MA, which does not need any specific implementation for nonlinearity, is demonstrated to be successfully applied to the analysis of plane strain structures. A numerical investigation is performed using nine different metaheuristic algorithms and an adaptive harmony search in linear analysis of a structural mechanics problem having 8 free nodes defined as design variables in the minimization problem of total potential energy. For nonlinear stress-strain relation cases, two structural mechanics problems, one being a thick-walled pipe and the other being a cantilever retaining wall, are analyzed by employing adaptive harmony search, which was found to be the best one in linear analyses. The nonlinear stress-strain relations considered in these analyses are hypothetical ones due to the lack of any such relationship in the literature. The results have shown that TPO/MA can solve nonlinear plane strain problems that can be encountered as engineering problems in structural mechanics.
Yusuf Toklu; Gebrail Bekdaş; Melda Yücel; Sinan Nigdeli; Aylin Kayabekir; Sanghun Kim; Zong Geem. Total Potential Optimization Using Metaheuristic Algorithms for Solving Nonlinear Plane Strain Systems. Applied Sciences 2021, 11, 3220 .
AMA StyleYusuf Toklu, Gebrail Bekdaş, Melda Yücel, Sinan Nigdeli, Aylin Kayabekir, Sanghun Kim, Zong Geem. Total Potential Optimization Using Metaheuristic Algorithms for Solving Nonlinear Plane Strain Systems. Applied Sciences. 2021; 11 (7):3220.
Chicago/Turabian StyleYusuf Toklu; Gebrail Bekdaş; Melda Yücel; Sinan Nigdeli; Aylin Kayabekir; Sanghun Kim; Zong Geem. 2021. "Total Potential Optimization Using Metaheuristic Algorithms for Solving Nonlinear Plane Strain Systems." Applied Sciences 11, no. 7: 3220.
Active or passive control strategies are developed for the control of civil structures. Since the structures are huge systems as a mechanical system, the control must be feasible for application proposals and cost efficiency performance. For that reason, structural control methods are still an active research area by optimum tuning of system parameters. The tuning of control systems is the most essential subject in performance of control systems. Also, the classical methods are not effective for civil structures subjected to seismic activities. In this chapter, a state-of-the-art review about active, passive, semi-active, and hybrid control studies is presented especially for seismic structures. Then, two active control models are compared via metaheuristics. These models are active tuned mass damper (ATMD) and active tendon control (ATC). Advantages and disadvantages are given in the conclusion.
Serdar Ulusoy; Aylin Ece Kayabekir; Sinan Melih Nigdeli; Gebrail Bekdaş. Metaheuristic-Based Structural Control Methods and Comparison of Applications. Springer Tracts in Nature-Inspired Computing 2021, 251 -276.
AMA StyleSerdar Ulusoy, Aylin Ece Kayabekir, Sinan Melih Nigdeli, Gebrail Bekdaş. Metaheuristic-Based Structural Control Methods and Comparison of Applications. Springer Tracts in Nature-Inspired Computing. 2021; ():251-276.
Chicago/Turabian StyleSerdar Ulusoy; Aylin Ece Kayabekir; Sinan Melih Nigdeli; Gebrail Bekdaş. 2021. "Metaheuristic-Based Structural Control Methods and Comparison of Applications." Springer Tracts in Nature-Inspired Computing , no. : 251-276.
Tuned mass dampers (TMDs) are used to damp vibration of mechanical systems. TMDs are also used on structures to reduce the effects of strong forces such as winds and earthquakes. For the efficiency of TMD, optimization of TMD parameters is needed. Several classical formulations were proposed, but metaheuristic methods are generally used to find the best result. In addition, the metaheuristic based optimum results are used in machine learning of artificial intelligence-based models like artificial neural networks (ANN). These ANN models are also used in development of tuning equation via curve fitting. The classical and ANN-based formulations were found according to frequency domain responses. In the present study, the classical and ANN-based formulations were evaluated by comparing on time-history responses of seismic structure. In comparison, near-fault ground motion records including directivity pulses are used. The ANN based methods have advantages by providing smaller stroke requirement and damping for TMDs.
Melda Yucel; Sinan Melih Nigdeli; Gebrail Bekdaş. Evaluation of artificial neural network-based formulations for tuned mass dampers. Challenge Journal of Structural Mechanics 2021, 7, 17 .
AMA StyleMelda Yucel, Sinan Melih Nigdeli, Gebrail Bekdaş. Evaluation of artificial neural network-based formulations for tuned mass dampers. Challenge Journal of Structural Mechanics. 2021; 7 (1):17.
Chicago/Turabian StyleMelda Yucel; Sinan Melih Nigdeli; Gebrail Bekdaş. 2021. "Evaluation of artificial neural network-based formulations for tuned mass dampers." Challenge Journal of Structural Mechanics 7, no. 1: 17.
In this study, multi-story structures with different combinations (on each floor and only the first floor) of active tendon control systems driven by a proportional–integral–derivative (PID) controller were actively controlled. The PID parameters, Kp (proportional gain), Td (derivative gain), and Ti (integral gain) for each structure, were optimally tuned by using both the harmony search algorithm (HS) and flower pollination algorithm (FPA), which are metaheuristic algorithms. In two different active-controlled structures, which are formed according to the position of the PID, the structural responses under near-fault records defined in FEMA P-695 are examined to determine the appropriate feedback which was applied for displacement, velocity, acceleration, and total acceleration. The performance of the different feedback strategies on these two active-controlled structures is evaluated. As a result, the acceleration feedback is suitable for all combinations of the active control system with a PID controller. The HS algorithm outperforms the optimum results found according to the FPA.
Serdar Ulusoy; Gebrail Bekdaş; Sinan Nigdeli; Sanghun Kim; Zong Geem. Performance of Optimum Tuned PID Controller with Different Feedback Strategies on Active-Controlled Structures. Applied Sciences 2021, 11, 1682 .
AMA StyleSerdar Ulusoy, Gebrail Bekdaş, Sinan Nigdeli, Sanghun Kim, Zong Geem. Performance of Optimum Tuned PID Controller with Different Feedback Strategies on Active-Controlled Structures. Applied Sciences. 2021; 11 (4):1682.
Chicago/Turabian StyleSerdar Ulusoy; Gebrail Bekdaş; Sinan Nigdeli; Sanghun Kim; Zong Geem. 2021. "Performance of Optimum Tuned PID Controller with Different Feedback Strategies on Active-Controlled Structures." Applied Sciences 11, no. 4: 1682.
In the optimum design of reinforced concrete (RC) structural members, the robustness of the employed method is important as well as solving the optimization problem. In some cases where the algorithm parameters are defined as non-effective values, local-optimum solutions may prevail over the existing global optimum results. Any metaheuristic algorithm can be effective to solve the optimization problem but must give the same results for several runs. Due to the randomization nature of these algorithms, the performance may vary with respect to time. The essential and novel work done in this study is the comparative investigation of 10 different metaheuristic algorithms and two modifications of harmony search (HS) algorithm on the optimum cost design of RC retaining walls constrained with geotechnical and structural state limits. The employed algorithms include classical ones (genetic algorithm (GA), differential evaluation (DE), and particle swarm optimization (PSO)), proved ones on structural engineering applications (harmony search, artificial bee colony, firefly algorithm), and recent algorithms (teaching–learning-based optimization (TLBO), flower pollination algorithm (FPA), grey wolf optimization, Jaya algorithm (JA)). The modifications of HS include adaptive HS (AHS) concerning the automatic change of algorithm parameters and hybridization of AHS with JA that is developed for the investigated problem. According to the numerical investigations, recent algorithms such as TLBO, FPA, and JA are generally the best at finding the optimum values with less deviation than the others. The adaptive-hybrid HS proposed in this study is also competitive with these algorithms, while it can reach the best solution by using a lower population number which can lead to timesaving in the optimization process. By the minimization of material used in construction via best optimization, sustainable structures that support multiple types of constraints are provided.
Melda Yücel; Aylin Ece Kayabekir; Gebrail Bekdaş; Sinan Melih Nigdeli; Sanghun Kim; Zong Woo Geem. Adaptive-Hybrid Harmony Search Algorithm for Multi-Constrained Optimum Eco-Design of Reinforced Concrete Retaining Walls. Sustainability 2021, 13, 1639 .
AMA StyleMelda Yücel, Aylin Ece Kayabekir, Gebrail Bekdaş, Sinan Melih Nigdeli, Sanghun Kim, Zong Woo Geem. Adaptive-Hybrid Harmony Search Algorithm for Multi-Constrained Optimum Eco-Design of Reinforced Concrete Retaining Walls. Sustainability. 2021; 13 (4):1639.
Chicago/Turabian StyleMelda Yücel; Aylin Ece Kayabekir; Gebrail Bekdaş; Sinan Melih Nigdeli; Sanghun Kim; Zong Woo Geem. 2021. "Adaptive-Hybrid Harmony Search Algorithm for Multi-Constrained Optimum Eco-Design of Reinforced Concrete Retaining Walls." Sustainability 13, no. 4: 1639.
Truss structures are one of the major civil engineering members studied in the optimization research area. In this area, various optimization applications such as topology, size, cost, weight, material usage, etc., can be conducted for different truss structure types. In this scope with the present study, various optimization processes were carried out concerning two different large-scale space trusses to minimize the structural weight. According to this state, three structural models provided via two different truss structures, including 25 bar and 72 bar truss models, were handled for evaluation of six different metaheuristics together with the modification of Lèvy flight for three of the algorithms using swarm intelligence by considering both constant and variable populations, and different ranges for iterations, too. Additionally, the effects of the Lèvy flight function and whether it is successful or not in terms of the target of optimization were also investigated by comparing with some documented studies. In this regard, some statistical calculations were also realized to evaluate the optimization method performance and detection of optimum values for any data stably and successfully. According to the results, the Jaya algorithm can handle the optimization process successfully, including the case, without grouping truss members. The positive effect of Lèvy flight on swarm-based algorithms can be seen especially for the gray wolf algorithm.
Gebrail Bekdaş; Melda Yucel; Sinan Nigdeli. Evaluation of Metaheuristic-Based Methods for Optimization of Truss Structures via Various Algorithms and Lèvy Flight Modification. Buildings 2021, 11, 49 .
AMA StyleGebrail Bekdaş, Melda Yucel, Sinan Nigdeli. Evaluation of Metaheuristic-Based Methods for Optimization of Truss Structures via Various Algorithms and Lèvy Flight Modification. Buildings. 2021; 11 (2):49.
Chicago/Turabian StyleGebrail Bekdaş; Melda Yucel; Sinan Nigdeli. 2021. "Evaluation of Metaheuristic-Based Methods for Optimization of Truss Structures via Various Algorithms and Lèvy Flight Modification." Buildings 11, no. 2: 49.
Total Potential Optimization using Metaheuristic Algorithms (TPO/MA) is an alternative structural analysis method starting with the same principles of the Finite Element Method (FEM). In TPO/MA as in FEM, the structure at hand is divided into finite parts. In these parts, if FEM is to be used, the equilibrium equations are written in a matrix form in local coordinates, then they are combined to give a matrix equation valid for the totality of the structure. The final step is solving this matrix equation to find the displacements in the structure. On the other hand, in TPO/MA, potential energies of the elements are written, then they are summed for the totality of the structure, yielding a functional to be minimized to find the equilibrium position according to the minimum potential energy principle. This minimization gives the displacements of the structure. That is why this method can also be called Finite Element Method with Energy Minimization (FEMEM). FEM is very efficient for linear systems, but for nonlinear systems the matrix obtained depends on material properties, displacements, and loads, i.e. it is not constant and may be ill-conditioned. This makes solutions difficult and sometimes impossible. It has been shown in the literature that TPO/MA can overcome these difficulties much more easily, and can solve problems that cannot be solved by FEM. In this study, TPO/MA is applied to tunnel problems with plane stress properties. Minimization process is applied to several metaheuristic algorithms and hybrid ones, which are then compared with each other as to accuracy and precision.
Yusuf Cengiz Toklu; Gebrail Bekdaş; Aylin Ece Kayabekir; Sinan Melih Nigdeli; Melda Yucel. Total Potential Optimization Using Hybrid Metaheuristics: A Tunnel Problem Solved via Plane Stress Members. Developments in Advanced Control and Intelligent Automation for Complex Systems 2020, 221 -236.
AMA StyleYusuf Cengiz Toklu, Gebrail Bekdaş, Aylin Ece Kayabekir, Sinan Melih Nigdeli, Melda Yucel. Total Potential Optimization Using Hybrid Metaheuristics: A Tunnel Problem Solved via Plane Stress Members. Developments in Advanced Control and Intelligent Automation for Complex Systems. 2020; ():221-236.
Chicago/Turabian StyleYusuf Cengiz Toklu; Gebrail Bekdaş; Aylin Ece Kayabekir; Sinan Melih Nigdeli; Melda Yucel. 2020. "Total Potential Optimization Using Hybrid Metaheuristics: A Tunnel Problem Solved via Plane Stress Members." Developments in Advanced Control and Intelligent Automation for Complex Systems , no. : 221-236.
In recent years, artificial intelligence (AI) and one of the sub-fields for it, which is machine learning, became significant in numerous study disciplines. During the determination of some results or finding of required parameters/information, these technologies provides many advantages and easiness for the usage of people such as researchers, designers, engineers, inventors and each kind of person dealt with them in terms of ease of use, saving of time, besides cost and efficiency for effort. In this chapter, a comprehensive research was presented intended for AI and machine learning technology together with their historical evaluation and applications. Also, a review of frequently-used machine learning techniques were imparted. As addition to these, many applications respect to some fields and also several studies of the structural engineering area were explained detailly. Furthermore, prediction studies carried out in structural engineering were demonstrated with all stages. In this regard, all of studies performed with the usage of different machine learning techniques were given in six sub-headings. As it can be understood from many developments, AI and machine learning technologies and application of them are pretty significant in terms of providing of beneficial situations and the usage of them will be more substantial and remarkable day by day.
Melda Yucel; Sinan Melih Nigdeli; Gebrail Bekdaş. Artificial Intelligence and Machine Learning with Reflection for Structural Engineering: A Review. Developments in Advanced Control and Intelligent Automation for Complex Systems 2020, 23 -72.
AMA StyleMelda Yucel, Sinan Melih Nigdeli, Gebrail Bekdaş. Artificial Intelligence and Machine Learning with Reflection for Structural Engineering: A Review. Developments in Advanced Control and Intelligent Automation for Complex Systems. 2020; ():23-72.
Chicago/Turabian StyleMelda Yucel; Sinan Melih Nigdeli; Gebrail Bekdaş. 2020. "Artificial Intelligence and Machine Learning with Reflection for Structural Engineering: A Review." Developments in Advanced Control and Intelligent Automation for Complex Systems , no. : 23-72.
The purpose of this state-of-the-art review is to present the latest advances in design optimization and applications of metaheuristic algorithms in structural engineering. In the first part of this chapter, the importance of optimization in structural engineering and its differences with engineering problems are emphasized. Metaheuristic methods and the most appropriate techniques for various approaches are summarized and reviewed. These algorithms are effective in dealing with nonlinear design optimization with complex constraints, practical discrete design variables, and user-defined special conditions. Modifications of these algorithms have been made and applied to structural engineering applications. Finally, the results are presented with discussion about further potential improvements.
Aylin Ece Kayabekir; Gebrail Bekdaş; Sinan Melih Nigdeli. Developments on Metaheuristic-Based Optimization in Structural Engineering. Developments in Advanced Control and Intelligent Automation for Complex Systems 2020, 1 -22.
AMA StyleAylin Ece Kayabekir, Gebrail Bekdaş, Sinan Melih Nigdeli. Developments on Metaheuristic-Based Optimization in Structural Engineering. Developments in Advanced Control and Intelligent Automation for Complex Systems. 2020; ():1-22.
Chicago/Turabian StyleAylin Ece Kayabekir; Gebrail Bekdaş; Sinan Melih Nigdeli. 2020. "Developments on Metaheuristic-Based Optimization in Structural Engineering." Developments in Advanced Control and Intelligent Automation for Complex Systems , no. : 1-22.
In addition to classical methods in structural analysis, the exact solution of the deformed shape of the structure is by using a metaheuristic method. According to the theory of total potential energy minimization, the static condition of the deformed shape of structures can be found directly by assigning the coordinates of the deformed shape of the structure and finding the case with the minimum potential energy. In that case, the analysis process is an optimization process, and metaheuristics are effective in this process. The total potential optimization using metaheuristic algorithms (TPO/MA) is an effective approach for several including plane-stress members. A cantilever beam is presented in the study, and it is solved via plane-stress members using TPO/MA. The problem is presented via two meshing options. For the frequent meshing, a hybrid algorithm of Jaya Algorithm (JA) using student phase of Teaching–Learning-Based Optimization (TLBO) is presented. TPO/MA is effective to find similar results with the finite element method.
Yusuf Cengiz Toklu; Gebrail Bekdaş; Aylin Ece Kayabekir; Sinan Melih Nigdeli; Melda Yücel. Total Potential Optimization Using Metaheuristics: Analysis of Cantilever Beam via Plane-Stress Members. Advances in Intelligent Systems and Computing 2020, 127 -138.
AMA StyleYusuf Cengiz Toklu, Gebrail Bekdaş, Aylin Ece Kayabekir, Sinan Melih Nigdeli, Melda Yücel. Total Potential Optimization Using Metaheuristics: Analysis of Cantilever Beam via Plane-Stress Members. Advances in Intelligent Systems and Computing. 2020; ():127-138.
Chicago/Turabian StyleYusuf Cengiz Toklu; Gebrail Bekdaş; Aylin Ece Kayabekir; Sinan Melih Nigdeli; Melda Yücel. 2020. "Total Potential Optimization Using Metaheuristics: Analysis of Cantilever Beam via Plane-Stress Members." Advances in Intelligent Systems and Computing , no. : 127-138.
The pounding of building blocks is a dangerous happening during an earthquake. The collision forces occurring between two buildings may result with particular damage at the collision point, and this damage will lead to the collapse of buildings. For that reason, a required seismic gap must be provided, but the gap may not be provided in the required amounts. Also, if the structures have a flexible base like seismic isolated structures, base displacement must be limited in order to protect isolators from yielding and collision of blocks. For that reason, several control methods can be used, but the essential factor is a good optimization of parameters of the design. In this paper, the optimum parameters of an absorber system connecting both buildings were proposed. In the optimization method, a hybrid Harmony Search (HS) algorithm was proposed. The combined algorithm is Jaya algorithm (JA). The proposed method is more effective than classical HS approach for reduction of the amount of the required seismic gap.
Sinan Melih Nigdeli; Gebrail Bekdaş. Hybrid Harmony Search Algorithm for Optimum Design of Vibration Absorber System for Adjacent Buildings. Advances in Intelligent Systems and Computing 2020, 73 -79.
AMA StyleSinan Melih Nigdeli, Gebrail Bekdaş. Hybrid Harmony Search Algorithm for Optimum Design of Vibration Absorber System for Adjacent Buildings. Advances in Intelligent Systems and Computing. 2020; ():73-79.
Chicago/Turabian StyleSinan Melih Nigdeli; Gebrail Bekdaş. 2020. "Hybrid Harmony Search Algorithm for Optimum Design of Vibration Absorber System for Adjacent Buildings." Advances in Intelligent Systems and Computing , no. : 73-79.
Tuned Mass Dampers (TMDs) were used in control of mechanical systems including structures. The civil structure may expose to high vibrations due to earthquakes. In the present study, TMDs positioned on the top of the structure were optimized via a metaheuristic method called Jaya Algorithm. The structure models are modelled in a finite element analysis software to obtain mass and stiffness properties. Then, the structure is modelled as a shear building in the optimization process. The optimum TMD was applied to the example structures in the finite element method analysis software to find structural response including base shear force. According to the results, the optimum TMDs are excellently effective in reduction of the total base shear force of frame structures.
Apaer Mubuli; Sinan Melih Nigdeli; Gebrail Bekdaş. Passive Control of Frame Structures by Optimum Tuned Mass Dampers. Advances in Intelligent Systems and Computing 2020, 111 -126.
AMA StyleApaer Mubuli, Sinan Melih Nigdeli, Gebrail Bekdaş. Passive Control of Frame Structures by Optimum Tuned Mass Dampers. Advances in Intelligent Systems and Computing. 2020; ():111-126.
Chicago/Turabian StyleApaer Mubuli; Sinan Melih Nigdeli; Gebrail Bekdaş. 2020. "Passive Control of Frame Structures by Optimum Tuned Mass Dampers." Advances in Intelligent Systems and Computing , no. : 111-126.
A method has been presented for the design of reinforced concrete plane frame systems at minimum cost by using the Jaya algorithm. The total material cost is at the objective function, and the cross-sectional dimensions were taken as design variables. These design variables were assigned with candidate solutions according to the rules of the algorithm in the numerical iterations. The total material cost was calculated according to the amount of concrete and reinforcements, and the matrix displacement method was used to analyze structures. The reinforced concrete design was made according to ACI 318-05 (Building code requirements for structural concrete and commentary) rules published by American Concrete Institute. These rules are taken as design constraints. The developed method has been applied to a single-story structure for different loading cases. Since the results have a direct match with the expected optimum results, the method is feasible for the optimization problem.
Elmas Rakıcı; Gebrail Bekdaş; Sinan Melih Nigdeli. Optimal Cost Design of Single-Story Reinforced Concrete Frames Using Jaya Algorithm. Advances in Intelligent Systems and Computing 2020, 179 -186.
AMA StyleElmas Rakıcı, Gebrail Bekdaş, Sinan Melih Nigdeli. Optimal Cost Design of Single-Story Reinforced Concrete Frames Using Jaya Algorithm. Advances in Intelligent Systems and Computing. 2020; ():179-186.
Chicago/Turabian StyleElmas Rakıcı; Gebrail Bekdaş; Sinan Melih Nigdeli. 2020. "Optimal Cost Design of Single-Story Reinforced Concrete Frames Using Jaya Algorithm." Advances in Intelligent Systems and Computing , no. : 179-186.
In this study, considering the eco-friendly design necessities of reinforced concrete structures, the acquirement of minimizing both the cost and the CO2 emission of the reinforced concrete retaining walls in conjunction with ensuring stability conditions has been investigated using harmony search algorithm. Optimization analyses were conducted with the use of two different objective functions to discover the contribution rate of variants to the cost and CO2 emission individually. Besides this, the integrated relationship of cost and CO2 emission was also identified by multi-objective analysis in order to identify an eco-friendly and cost-effective design. The height of the stem and the width of the foundation were treated as design variables. Several optimization cases were fictionalized in relation with the change of the depth of excavation, the amount of the surcharge applied at the top of the wall system at the backfill side, the unit weight of the backfill soil, the costs, and CO2 emission amounts of both the concrete and the reinforcement bars. Consequently, the results of the optimization analyses were arranged to discover the possibility of supplying an eco-friendly design of retaining walls with the minimization of both cost and gas emission depending upon the comparison of outcomes of the identified objective functions. The proposed approach is effective to find both economic and ecological results according to hand calculations and flower pollination algorithm.
Aylin Ece Kayabekir; Zülal Akbay Arama; Gebrail Bekdaş; Sinan Melih Nigdeli; Zong Woo Geem. Eco-Friendly Design of Reinforced Concrete Retaining Walls: Multi-objective Optimization with Harmony Search Applications. Sustainability 2020, 12, 6087 .
AMA StyleAylin Ece Kayabekir, Zülal Akbay Arama, Gebrail Bekdaş, Sinan Melih Nigdeli, Zong Woo Geem. Eco-Friendly Design of Reinforced Concrete Retaining Walls: Multi-objective Optimization with Harmony Search Applications. Sustainability. 2020; 12 (15):6087.
Chicago/Turabian StyleAylin Ece Kayabekir; Zülal Akbay Arama; Gebrail Bekdaş; Sinan Melih Nigdeli; Zong Woo Geem. 2020. "Eco-Friendly Design of Reinforced Concrete Retaining Walls: Multi-objective Optimization with Harmony Search Applications." Sustainability 12, no. 15: 6087.
In the present study, an active structural control using metaheuristic tuned Proportional-Integral-Derivative (PID) type controllers is presented. The aim of the study is to propose a feasible active control application considering time delay and a feasible control force. In the optimum control methodology, near-fault directivity pulse was considered for ground motion. Three different metaheuristic algorithms are separately employed in the optimum tuning of PID parameters such as proportional gain, integral time and derivative time. The employed algorithms are Flower Pollination Algorithm, Teaching Learning Based Optimization and Jaya algorithm. The maximum control force limit is considered as a design constraint. The methodology contains the time delay consideration and a process to avoid the stability problem on the trial results during the optimization process. The method is explained in three stages as The Pre-Optimization Stage, The Dynamic Analysis Stage and The Optimization Stage. The optimum PID parameters of different algorithms are very different, but the performance of active control is similar since a similar control signal can be generated by different proportion of controller gains such as proportion, integral and derivative processes. As the conclusion of the study, the amount of control force must be chosen carefully since big control forces may resulted with stability problems if the control system has long delay.
Serdar Ulusoy; Sinan Melih Nigdeli; Gebrail Bekdaş. Novel metaheuristic-based tuning of PID controllers for seismic structures and verification of robustness. Journal of Building Engineering 2020, 33, 101647 .
AMA StyleSerdar Ulusoy, Sinan Melih Nigdeli, Gebrail Bekdaş. Novel metaheuristic-based tuning of PID controllers for seismic structures and verification of robustness. Journal of Building Engineering. 2020; 33 ():101647.
Chicago/Turabian StyleSerdar Ulusoy; Sinan Melih Nigdeli; Gebrail Bekdaş. 2020. "Novel metaheuristic-based tuning of PID controllers for seismic structures and verification of robustness." Journal of Building Engineering 33, no. : 101647.
The locations of structural members can be provided according to architectural projects in the design of reinforced concrete (RC) structures. The design of dimensions is the subject of civil engineering, and these designs are done according to the experience of the designer by considering the regulation suggestions, but these dimensions and the required reinforcement plan may not be optimum. For that reason, the dimensions and detailed reinforcement design of RC structures can be found by using optimization methods. To reach optimum results, metaheuristic algorithms can be used. In this study, several metaheuristic algorithms such as harmony search, bat algorithm and teaching learning-based optimization are used in the design of several RC beams for cost minimization. The optimum results are presented for different strength of concrete. The results show that using high strength material for high flexural moment capacity has lower cost than low stretch concrete since doubly reinforced design is not an optimum choice. The results prove that a definite metaheuristic algorithm cannot be proposed for the best optimum design of an engineering problem. According to the investigation of compressive strength of concrete, it can be said that a low strength material are optimum for low flexural moment, while a high strength material may be the optimum one by the increase of the flexural moment as expected.
Serdar Ulusoy; Aylin Ece Kayabekir; Gebrail Bekdaş; Sinan Melih Nigdeli. Metaheuristic algorithms in optimum design of reinforced concrete beam by investigating strength of concrete. Challenge Journal of Concrete Research Letters 2020, 11, 26 .
AMA StyleSerdar Ulusoy, Aylin Ece Kayabekir, Gebrail Bekdaş, Sinan Melih Nigdeli. Metaheuristic algorithms in optimum design of reinforced concrete beam by investigating strength of concrete. Challenge Journal of Concrete Research Letters. 2020; 11 (2):26.
Chicago/Turabian StyleSerdar Ulusoy; Aylin Ece Kayabekir; Gebrail Bekdaş; Sinan Melih Nigdeli. 2020. "Metaheuristic algorithms in optimum design of reinforced concrete beam by investigating strength of concrete." Challenge Journal of Concrete Research Letters 11, no. 2: 26.
In this study, the music-inspired Harmony Search (HS) algorithm is modified for the optimization of active tuned mass dampers (ATMDs). The modification of HS includes the consideration of the best solution with a defined probability and updating of algorithm parameters such as harmony memory, considering rate and pitch adjusting rate. The design variables include all the mechanical properties of ATMD, such as the mass, stiffness and damping coefficient, and the active controller parameters of the proposed proportional–integral–derivative (PID) type controllers. In the optimization process, the analysis of an ATMD implemented structure is done using the generated Matlab Simulink block diagram. The PID controllers were optimized for velocity feedback control, and the objective of the optimization is the minimization of the top story displacement by using the limitation of the stroke capacity of ATMD. The optimum results are presented for different cases of the stroke capacity limit of ATMD. According to the results, the method is effective in reducing the maximum displacement of the structure by 53.71%, while a passive TMD can only reduce it by 31.22%.
Aylin Ece Kayabekir; Gebrail Bekdaş; Sinan Melih Nigdeli; Zong Woo Geem. Optimum Design of PID Controlled Active Tuned Mass Damper via Modified Harmony Search. Applied Sciences 2020, 10, 2976 .
AMA StyleAylin Ece Kayabekir, Gebrail Bekdaş, Sinan Melih Nigdeli, Zong Woo Geem. Optimum Design of PID Controlled Active Tuned Mass Damper via Modified Harmony Search. Applied Sciences. 2020; 10 (8):2976.
Chicago/Turabian StyleAylin Ece Kayabekir; Gebrail Bekdaş; Sinan Melih Nigdeli; Zong Woo Geem. 2020. "Optimum Design of PID Controlled Active Tuned Mass Damper via Modified Harmony Search." Applied Sciences 10, no. 8: 2976.
By finding the minimum total potential energy of a structural system with a defined degree of freedoms assigned as design variables, it is possible to find the equilibrium condition of the deformed system. This method, called total potential optimization using metaheuristic algorithms (TPO/MA), has been verified on truss and truss-like structures, such as cable systems and tensegric structures. Harmony Search (HS) algorithm methods perfectly found the analysis results of the previous structure types. In this study, TPO/MA is presented for analysis of plates for plane stress members to solve general types of problems. Due to the complex nature of the system, a novel hybrid Harmony Search (HHS) approach was proposed. HHS is the hybridization of local search phases of HS and the global search phase of the Flower Pollination Algorithm (FPA). The results found via HHS were verified with the finite element method (FEM). When compared with classical HS, HHS provides smaller total potential energy values, and needs less iterations than other new generation metaheuristic algorithms.
Aylin Ece Kayabekir; Yusuf Cengiz Toklu; Gebrail Bekdaş; Sinan Melih Nigdeli; Melda Yücel; Zong Woo Geem. A Novel Hybrid Harmony Search Approach for the Analysis of Plane Stress Systems via Total Potential Optimization. Applied Sciences 2020, 10, 2301 .
AMA StyleAylin Ece Kayabekir, Yusuf Cengiz Toklu, Gebrail Bekdaş, Sinan Melih Nigdeli, Melda Yücel, Zong Woo Geem. A Novel Hybrid Harmony Search Approach for the Analysis of Plane Stress Systems via Total Potential Optimization. Applied Sciences. 2020; 10 (7):2301.
Chicago/Turabian StyleAylin Ece Kayabekir; Yusuf Cengiz Toklu; Gebrail Bekdaş; Sinan Melih Nigdeli; Melda Yücel; Zong Woo Geem. 2020. "A Novel Hybrid Harmony Search Approach for the Analysis of Plane Stress Systems via Total Potential Optimization." Applied Sciences 10, no. 7: 2301.