scholarly journals Earthquake Design of Reinforced Concrete Buildings Using NSGA-II

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Herian A. Leyva ◽  
Edén Bojórquez ◽  
Juan Bojórquez ◽  
Alfredo Reyes-Salazar ◽  
José H. Castorena ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Reinforced Concrete ◽  
Seismic Design ◽  
Engineering Practice ◽  
Objective Functions ◽  
Rc Buildings ◽  
Nsga Ii ◽  
Earthquake Design ◽  
The Cost ◽  
Nondominated Sorting

In the present study, the optimal seismic design of reinforced concrete (RC) buildings is obtained. For this purpose, genetic algorithms (GAs) are used through the technique NSGA-II (Nondominated Sorting Genetic Algorithm), thus a multiobjective procedure with two objective functions is established. The first objective function is the control of maximum interstory drift which is the most common parameter used in seismic design codes, while the second is to minimize the cost of the structure. For this aim, several RC buildings are designed in accordance with the Mexico City Building Code (MCBC). It is assumed that the structures are constituted by rectangular and square concrete sections for the beams, columns, and slabs which are represented by a binary codification. In conclusion, this study provides complete designed RC buildings which also can be used directly in the structural and civil engineering practice by means of genetic algorithms. Moreover, genetic algorithms are able to find the most adequate structures in terms of seismic performance and economy.

Multi-objective seismic design of BRBs-reinforced concrete buildings using genetic algorithms

2021 ◽  
Author(s):  
Herian Leyva ◽  
Juan Bojórquez ◽  
Edén Bojórquez ◽  
Alfredo Reyes-Salazar ◽  
Julián Carrillo ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Reinforced Concrete ◽  
Seismic Design ◽  
Reinforced Concrete Buildings ◽  
Concrete Buildings ◽  
Multi Objective

scholarly journals Eco-Friendly Design of Reinforced Concrete Retaining Walls: Multi-objective Optimization with Harmony Search Applications

2020 ◽  
Vol 12 (15) ◽  
pp. 6087 ◽  
Author(s):  
Aylin Ece Kayabekir ◽  
Zülal Akbay Arama ◽  
Gebrail Bekdaş ◽  
Sinan Melih Nigdeli ◽  
Zong Woo Geem
Keyword(s):  
Reinforced Concrete ◽  
Co2 Emission ◽  
Search Algorithm ◽  
Harmony Search ◽  
Retaining Walls ◽  
Unit Weight ◽  
Flower Pollination Algorithm ◽  
Objective Functions ◽  
Multi Objective ◽  
The Cost

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.

scholarly journals Steel Reinforcement and Concrete for Multipurpose Hall Building with Seismic Design

2019 ◽  
Vol 8 (3S3) ◽  
pp. 543-547
Keyword(s):  
Reinforced Concrete ◽  
Seismic Design ◽  
Soil Type ◽  
Steel Reinforcement ◽  
Lower Amount ◽  
Public Building ◽  
Two Parameters ◽  
The Cost ◽  
Cost Of Construction ◽  
New Buildings

Multipurpose hall is a public building of people assembly for various function and activities. It can be converted to be a temporary shelter during disaster like flood and earthquake. After experiencing tremors from both local and distant earthquakes, the time has come to implement the seismic design to new buildings in Malaysia to ensure public safety. The implementation of seismic design also affecting the cost of construction, especially materials. Therefore, this paper presents the taking off results for reinforced concrete multipurpose hall building with seismic design. In this study two parameters namely as soil type and concrete grade had been considered as design variable. Result from design and taking off demonstrated that the amount of steel reinforcement is strongly influenced by both parameters. The usage of steel for reinforced concrete buildings with seismic design is estimated to increase around 3% to 59% depend on soil type and concrete grade. Results also demonstrated that higher concrete grade require lower amount of steel as reinforcement.

scholarly journals Performance of reinforced concrete buildings in the 2016 Kumamoto earthquakes and seismic design in Japan

2017 ◽  
Vol 50 (3) ◽  
pp. 394-435 ◽  
Author(s):  
Mehdi Sarrafzadeh ◽  
Ken J. Elwood ◽  
Rajesh P. Dhakal ◽  
Helen Ferner ◽  
Didier Pettinga ◽  
...  
Keyword(s):  
Reinforced Concrete ◽  
New Zealand ◽  
Seismic Design ◽  
Evaluation Methods ◽  
Design Practice ◽  
Reinforced Concrete Buildings ◽  
Rc Buildings ◽  
Design Practices ◽  
The 2016 Kumamoto Earthquakes ◽  
2016 Kumamoto Earthquakes

This report outlines the observations of an NZSEE team of practitioners and researchers who travelled to the Kumamoto Prefecture of Japan on a reconnaissance visit following the April 2016 earthquakes. The observations presented in this report are focussed on the performance of reinforced concrete (RC) buildings throughout Kumamoto Prefecture. It was found overall that modern RC buildings performed well, with patterns of damage which highlighted a philosophy of designing stiffer buildings with less of an emphasis on ductile behaviour. To explore this important difference in design practice, the Japanese Building Standard Law (BSL) is summarised and compared with standard New Zealand seismic design practices and evaluation methods.

Research on Influence of Moment Augment Factor of Column on Building Cost

2014 ◽  
Vol 487 ◽  
pp. 230-233
Author(s):  
Bin Cai ◽  
Xin Hui Liu
Keyword(s):  
Reinforced Concrete ◽  
Seismic Design ◽  
Concrete Structure ◽  
Reinforced Concrete Structure ◽  
Computer Design ◽  
Building Cost ◽  
Weak Beam ◽  
Design Software ◽  
The Cost

The new moment augment factor of column of the national Code for Seismic Design of Buildings (GB500112010) were increased, the strong column weak beam reliability of reinforced concrete structure were improved, at the same time, the cost of building were improved also. Influence of moment augment factor column on building cost was discussed by computer design software Guang Sha CAD. Result indicates that the increase of cost is very small.

scholarly journals An Improved Nondominated Sorting Genetic Algorithm III Method for Solving Multiobjective Weapon-Target Assignment Part I: The Value of Fighter Combat

2018 ◽  
Vol 2018 ◽  
pp. 1-23 ◽  
Author(s):  
You Li ◽  
Yingxin Kou ◽  
Zhanwu Li
Keyword(s):  
Reference Points ◽  
Sorting Algorithm ◽  
Nsga Ii ◽  
Target Assignment ◽  
Objective Model ◽  
Typical Instance ◽  
Attack And Defense ◽  
Battlefield Environment ◽  
The Cost ◽  
Nondominated Sorting

Multiobjective weapon-target assignment is a type of NP-complete problem, and the reasonable assignment of weapons is beneficial to attack and defense. In order to simulate a real battlefield environment, we introduce a new objective—the value of fighter combat on the basis of the original two-objective model. The new three-objective model includes maximizing the expected damage of the enemy, minimizing the cost of missiles, and maximizing the value of fighter combat. To solve the problem with complex constraints, an improved nondominated sorting algorithm III is proposed in this paper. In the proposed algorithm, a series of reference points with good performances in convergence and distribution are continuously generated according to the current population to guide the evolution; otherwise, useless reference points are eliminated. Moreover, an online operator selection mechanism is incorporated into the NSGA-III framework to autonomously select the most suitable operator while solving the problem. Finally, the proposed algorithm is applied to a typical instance and compared with other algorithms to verify its feasibility and effectiveness. Simulation results show that the proposed algorithm is successfully applied to the multiobjective weapon-target assignment problem, which effectively improves the performance of the traditional NSGA-III and can produce better solutions than the two multiobjective optimization algorithms NSGA-II and MPACO.

scholarly journals MULTI-OBJECTIVE OPTIMIZATION OF REINFORCED CONCRETE FRAMES USING NSGA-II ALGORITHM

2016 ◽  
Vol 8 (4) ◽  
pp. 157-164 ◽  
Author(s):  
Mehdi Babaei ◽  
Masoud Mollayi
Keyword(s):  
Genetic Algorithm ◽  
Reinforced Concrete ◽  
Steel Structures ◽  
American Concrete Institute ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Design Variables ◽  
Pareto Fronts

In recent decades, the use of genetic algorithm (GA) for optimization of structures has been highly attractive in the study of concrete and steel structures aiming at weight optimization. However, it has been challenging for multi-objective optimization to determine the trade-off between objective functions and to obtain the Pareto-front for reinforced concrete (RC) and steel structures. Among different methods introduced for multi-objective optimization based on genetic algorithms, Non-Dominated Sorting Genetic Algorithm II (NSGA II) is one of the most popular algorithms. In this paper, multi-objective optimization of RC moment resisting frame structures considering two objective functions of cost and displacement are introduced and examined. Three design models are optimized using the NSGA-II algorithm. Evaluation of optimal solutions and the algorithm process are discussed in details. Sections of beams and columns are considered as design variables and the specifications of the American Concrete Institute (ACI) are employed as the design constraints. Pareto-fronts for the objective space have been obtained for RC frame models of four, eight and twelve floors. The results indicate smooth Pareto-fronts and prove the speed and accuracy of the method.

scholarly journals Enhanced Seismic Structural Reliability on Reinforced Concrete Buildings by Using Buckling Restrained Braces

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Victor Baca ◽  
Juan Bojórquez ◽  
Edén Bojórquez ◽  
Herian Leyva ◽  
Alfredo Reyes-Salazar ◽  
...  
Keyword(s):  
Reinforced Concrete ◽  
Seismic Behavior ◽  
Structural Reliability ◽  
Ground Motions ◽  
Soft Soil ◽  
Reinforced Concrete Buildings ◽  
Rc Buildings ◽  
Nsga Ii ◽  
Concrete Buildings ◽  
Buckling Restrained Braces

The control of vibrations and damage in traditional reinforced concrete (RC) buildings under earthquakes is a difficult task. It requires the use of innovative devices to enhance the seismic behavior of concrete buildings. In this paper, we design RC buildings with buckling restrained braces (BRBs) to achieve this objective. For this aim, three traditional RC framed structures with 3, 6, and 9 story levels are designed by using the well-known technique nondominated sorting genetic algorithm (NSGA-II) in order to reduce the cost and maximize the seismic performance. Then, equivalent RC buildings are designed but including buckling restrained braces. Both structural systems are subjected to several narrow-band ground motions recorded at soft soil sites of Mexico City scaled at different levels of intensities in terms of the spectral acceleration at first mode of vibration of the structure Sa(T1). Then, incremental dynamic analysis, seismic fragility, and structural reliability in terms of the maximum interstory drift are computed for all the buildings. For the three selected structures and the equivalent models with BRBs, it is concluded that the annual rate of exceedance is considerably reduced when BRBs are incorporated. For this reason, the structural reliability of the RC buildings with BRBs has a better behavior in comparison with the traditional reinforced concrete buildings. The use of BRBs is a good option to improve strength and seismic behavior and hence the structural reliability of RC buildings subjected to strong earthquake ground motions.

An Efficient Non-dominated Sorting Method for Evolutionary Algorithms

2008 ◽  
Vol 16 (3) ◽  
pp. 355-384 ◽  
Author(s):  
Hongbing Fang ◽  
Qian Wang ◽  
Yi-Cheng Tu ◽  
Mark F. Horstemeyer
Keyword(s):  
Evolutionary Algorithms ◽  
Divide And Conquer ◽  
Computational Time ◽  
Sorting Algorithm ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Overall Efficiency ◽  
Dominance Tree ◽  
The Cost

We present a new non-dominated sorting algorithm to generate the non-dominated fronts in multi-objective optimization with evolutionary algorithms, particularly the NSGA-II. The non-dominated sorting algorithm used by NSGA-II has a time complexity of O(MN2) in generating non-dominated fronts in one generation (iteration) for a population size N and M objective functions. Since generating non-dominated fronts takes the majority of total computational time (excluding the cost of fitness evaluations) of NSGA-II, making this algorithm faster will significantly improve the overall efficiency of NSGA-II and other genetic algorithms using non-dominated sorting. The new non-dominated sorting algorithm proposed in this study reduces the number of redundant comparisons existing in the algorithm of NSGA-II by recording the dominance information among solutions from their first comparisons. By utilizing a new data structure called the dominance tree and the divide-and-conquer mechanism, the new algorithm is faster than NSGA-II for different numbers of objective functions. Although the number of solution comparisons by the proposed algorithm is close to that of NSGA-II when the number of objectives becomes large, the total computational time shows that the proposed algorithm still has better efficiency because of the adoption of the dominance tree structure and the divide-and-conquer mechanism.

scholarly journals Probabilistic building block identification for the optimal design and rehabilitation of water distribution systems

2009 ◽  
Vol 11 (2) ◽  
pp. 89-105 ◽  
Author(s):  
Ralph J. Olsson ◽  
Zoran Kapelan ◽  
Dragan A. Savic
Keyword(s):  
Genetic Algorithms ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Building Blocks ◽  
Probabilistic Methods ◽  
Chi Square ◽  
Nsga Ii ◽  
Multi Objective ◽  
The Cost

The multi-objective design and rehabilitation of water distribution systems (WDS) is defined as the search for the set of system designs which offers the best trade-off between competing design objectives. Typically these objectives will consist of the cost of implementing a system design and a measure of the performance of that system. These measures are often in competition since improvements in the performance of a system generally come at a cost. Here three genetic algorithms which use probabilistic methods to identify building blocks—the Univariate Marginal Distribution Algorithm (UMDA) (Mühlenbein 1997), the hierarchical Bayesian Optimisation Algorithm (hBOA) (Pelikan 2002) and the Chi-Square Matrix methodology (Aporntewan & Chongstitvatana 2004)—are compared to the well-known multi-objective evolutionary algorithm NSGAII (Deb et al. 2002) for the multi-objective design and rehabilitation of water distribution systems. For single-objective problems the identification of building blocks has been seen to make evolutionary algorithms more scalable to large problems than simple genetic algorithms. In this paper these algorithms are shown to offer significantly better solutions than NSGA-II for the case of large systems. However, this improvement comes at the expense of diversity of solutions in the fronts identified.

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