Ground Motion Record Selection using Multi-objective Optimization Algorithms: A Comparative Study

Performing time history dynamic analysis using site-specific ground motion records according to the increasing interest in the performance-based earthquake engineering has encouraged studies related to site-specific Ground Motion Record (GMR) selection methods. This study addresses a ground motion record selection approach based on three different multi-objective optimization algorithms including Multi-Objective Particle Swarm Optimization (MOPSO), Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Pareto Envelope-based Selection Algorithm II (PESA-II). The method proposed in this paper selects records efficiently by matching dispersion and mean spectrum of the selected record set and target spectrums in a predefined period. Comparison between the results shows that NSGA II performs better than the other algorithms in the case of GMR selection.

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Ground Motion Record Selection Based on Broadband Spectral Compatibility

Earthquake Spectra ◽

10.1193/052312eqs197m ◽

2014 ◽

Vol 30 (4) ◽

pp. 1427-1448 ◽

Cited By ~ 66

Author(s):

Chiara Smerzini ◽

Carmine Galasso ◽

Iunio Iervolino ◽

Roberto Paolucci

Keyword(s):

Ground Motion ◽

Earthquake Engineering ◽

Time History ◽

Strong Motion ◽

Software Tool ◽

Engineering Practice ◽

Ongoing Research ◽

Research Activities ◽

Record Selection ◽

Ground Motion Record Selection

The increasing interest in performance-based earthquake engineering has promoted research on the improvement of hazard-consistent seismic input definition and on advanced criteria for strong motion record selection to perform nonlinear time history analyses. Within the ongoing research activities to improve the representation of seismic actions and to develop tools as a support for engineering practice, this study addresses the selection of displacement-spectrum-compatible real ground motions, with special reference to Italy. This involved (1) the definition of specific target displacement spectra for Italian sites, constrained—both at long and short periods—by results of probabilistic seismic hazard analyses; (2) the compilation of a high-quality strong ground motion database; and (3) the development of a software tool for computer-aided displacement-based record selection. Application examples show that sets of unscaled, or lightly scaled, accelerograms with limited record-to-record spectral variability can also easily be obtained when a broadband spectral compatibility is required.

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Impact of partially non-ergodic site-specific probabilistic seismic hazard on risk assessment of single buildings

Earthquake Spectra ◽

10.1177/8755293020938813 ◽

2020 ◽

pp. 875529302093881

Author(s):

Mohsen Kohrangi ◽

Sreeram Reddy Kotha ◽

Paolo Bazzurro

Keyword(s):

Risk Assessment ◽

Ground Motion ◽

A Priori ◽

Real Life ◽

Site Specific ◽

Risk Estimates ◽

The Difference ◽

Record Selection ◽

Ground Motion Record Selection ◽

The Impact

The growth of global ground-motion databases has allowed generation of non-ergodic ground-motion prediction equations (GMPEs) based on specific on-site recordings. Several studies have investigated the differences between the hazard estimates from ergodic versus non-ergodic GMPEs. Here instead we focus on the impact of non-ergodic PSHA estimates on the seismic risk of nonlinear single-degree-of-freedom systems representing ductile structures and compare it with the traditional risk estimates obtained using ergodic GMPEs. The structure-and-site-specific risk estimates depend not only on the difference in the hazard estimates but also on the different hazard-consistent ground-motion record selection that informs the response calculation. The more accurate structure-and-site-specific non-ergodic risk estimates show that traditional ones may be biased in a way impossible to predict a priori. Hence, the use of the non-ergodic approach is recommended, whenever possible. However, further advancements of non-ergodic GMPEs are necessary before being routinely utilized in real-life risk assessment applications.

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Synchronous R-NSGA-II: An Extended Preference-Based Evolutionary Algorithm for Multi-Objective Optimization

Informatica ◽

10.15388/informatica.2015.37 ◽

2015 ◽

Vol 26 (1) ◽

pp. 33-50 ◽

Cited By ~ 16

Author(s):

Ernestas Filatovas ◽

Olga Kurasova ◽

Karthik Sindhya

Keyword(s):

Evolutionary Algorithm ◽

Multi Objective Optimization ◽

Nsga Ii ◽

Multi Objective

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Multi-Objective Lightweight Optimization of Parameterized Suspension Components Based on NSGA-II Algorithm Coupling with Surrogate Model

Machines ◽

10.3390/machines9060107 ◽

2021 ◽

Vol 9 (6) ◽

pp. 107

Author(s):

Rongchao Jiang ◽

Zhenchao Jin ◽

Dawei Liu ◽

Dengfeng Wang

Keyword(s):

Ride Comfort ◽

Lightweight Design ◽

Dynamic Performance ◽

Vehicle Dynamic ◽

Multi Objective Optimization ◽

Original Design ◽

Dynamic Simulations ◽

Nsga Ii ◽

Torsion Beam ◽

Multi Objective

In order to reduce the negative effect of lightweighting of suspension components on vehicle dynamic performance, the control arm and torsion beam widely used in front and rear suspensions were taken as research objects for studying the lightweight design method of suspension components. Mesh morphing technology was employed to define design variables. Meanwhile, the rigid–flexible coupling vehicle model with flexible control arm and torsion beam was built for vehicle dynamic simulations. The total weight of control arm and torsion beam was taken as optimization objective, as well as ride comfort and handling stability performance indexes. In addition, the fatigue life, stiffness, and modal frequency of control arm and torsion beam were taken as the constraints. Then, Kriging model and NSGA-II were adopted to perform the multi-objective optimization of control arm and torsion beam for determining the lightweight scheme. By comparing the optimized and original design, it indicates that the weight of the optimized control arm and torsion beam are reduced 0.505 kg and 1.189 kg, respectively, while structural performance and vehicle performance satisfy the design requirement. The proposed multi-objective optimization method achieves a remarkable mass reduction, and proves to be feasible and effective for lightweight design of suspension components.

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Design and characterization of effective solar cells

Energy Systems ◽

10.1007/s12667-021-00451-x ◽

2021 ◽

Author(s):

Varun Ojha ◽

Giorgio Jansen ◽

Andrea Patanè ◽

Antonino La Magna ◽

Vittorio Romano ◽

...

Keyword(s):

Solar Cells ◽

Quantum Efficiency ◽

Cost Benefit Analysis ◽

Cost Minimization ◽

Cell Structure ◽

Cost Benefit ◽

Structure Design ◽

Multi Objective Optimization ◽

Nsga Ii ◽

Multi Objective

AbstractWe propose a two-stage multi-objective optimization framework for full scheme solar cell structure design and characterization, cost minimization and quantum efficiency maximization. We evaluated structures of 15 different cell designs simulated by varying material types and photodiode doping strategies. At first, non-dominated sorting genetic algorithm II (NSGA-II) produced Pareto-optimal-solutions sets for respective cell designs. Then, on investigating quantum efficiencies of all cell designs produced by NSGA-II, we applied a new multi-objective optimization algorithm II (OptIA-II) to discover the Pareto fronts of select (three) best cell designs. Our designed OptIA-II algorithm improved the quantum efficiencies of all select cell designs and reduced their fabrication costs. We observed that the cell design comprising an optimally doped zinc-oxide-based transparent conductive oxide (TCO) layer and rough silver back reflector (BR) offered a quantum efficiency ($$Q_e$$ Q e ) of 0.6031. Overall, this paper provides a full characterization of cell structure designs. It derives relationship between quantum efficiency, $$Q_e$$ Q e of a cell with its TCO layer’s doping methods and TCO and BR layer’s material types. Our solar cells design characterization enables us to perform a cost-benefit analysis of solar cells usage in real-world applications.

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Multi-objective optimization of energy efficiency and thermal comfort in an existing office building using NSGA-II with fitness approximation: a case study

Journal of Building Engineering ◽

10.1016/j.jobe.2021.102440 ◽

2021 ◽

pp. 102440

Author(s):

Mohammadamin Ghaderian ◽

Farzad Veysi

Keyword(s):

Energy Efficiency ◽

Thermal Comfort ◽

Office Building ◽

Multi Objective Optimization ◽

Nsga Ii ◽

Multi Objective ◽

Fitness Approximation

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Multi-objective optimization of squirrel cage fan for range hood based on Kriging model

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406221995863 ◽

2021 ◽

pp. 095440622199586

Author(s):

Qianhao Xiao ◽

Jun Wang ◽

Boyan Jiang ◽

Weigang Yang ◽

Xiaopei Yang

Keyword(s):

Flow Rate ◽

Optimization Design ◽

Volume Flow Rate ◽

Kriging Model ◽

Volume Flow ◽

Design Parameters ◽

Multi Objective Optimization ◽

Nsga Ii ◽

Multi Objective ◽

Squirrel Cage

In view of the multi-objective optimization design of the squirrel cage fan for the range hood, a blade parameterization method based on the quadratic non-uniform B-spline (NUBS) determined by four control points was proposed to control the outlet angle, chord length and maximum camber of the blade. Morris-Mitchell criteria were used to obtain the optimal Latin hypercube sample based on the evolutionary operation, and different subsets of sample numbers were created to study the influence of sample numbers on the multi-objective optimization results. The Kriging model, which can accurately reflect the response relationship between design variables and optimization objectives, was established. The second-generation Non-dominated Sorting Genetic algorithm (NSGA-II) was used to optimize the volume flow rate at the best efficiency point (BEP) and the maximum volume flow rate point (MVP). The results show that the design parameters corresponding to the optimization results under different sample numbers are not the same, and the fluctuation range of the optimal design parameters is related to the influence of the design parameters on the optimization objectives. Compared with the prototype, the optimized impeller increases the radial velocity of the impeller outlet, reduces the flow loss in the volute, and increases the diffusion capacity, which improves the volume flow rate, and efficiency of the range hood system under multiple working conditions.

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