Multi-objective crashworthiness optimization of perforated square tubes using modified NSGAII and MOPSO

Khalkhali, Abolfazl; Mostafapour, Majid; Tabatabaie, Seyed Mohamad; Ansari, Behnam

doi:10.1007/s00158-015-1385-y

Cited by 41 publications

(6 citation statements)

References 24 publications

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“…By defining functions training error (TE) and predicting error (PE) as objective functions, the optimal point regarding the model performance in both mentioned target function is evaluated and optimal point selected. To select an optimal point, nearest to ideal point (NIP) (Khalkhali et al 2016) method is used. The TE, PE, and Trd points presented in Fig.…”

Section: Bank Profile Of Threshold Channel Modeling By Anfis-de/svdmentioning

confidence: 99%

Analyzing bank profile shape of alluvial stable channels using robust optimization and evolutionary ANFIS methods

et al. 2019

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In natural rivers and artificial channels in addition to the channel dimensions (widening, reduction in slope and depth in the channel banks), formed shape profile in the case that the sediment on the banks with no movement (thresholds state) is of considerable importance for engineers. To determine the bank shape profiles, various theoretical, empirical and statistical relations have been provided based on physical and numerical models by different researchers. In this study, a simple model of adaptive neuro-fuzzy inference systems (ANFIS) is combined with two algorithms of differential evolution (DE) and singular value decomposition value (SVD) and the performance of these models to predict the stable shape profiles of the channels is evaluated and compared. In this paper, the main goal is to assess extensively the effect of hybrid models based on optimized algorithms (ANFIS-DE) and multi-objective evolutionary algorithm (ANFIS-DE/SVD) in improvement of performance of ANFIS and ANFIS-DE models, respectively. Accordingly, the results assessment show that all three ANFIS, ANFIS-DE and ANFIS-DE/SVD models are perfectly able to predict shape profiles in accordance with the observed profiles for the threshold channels. Using optimized and evolutionary algorithms has a positive impact on the performance of simple model of ANFIS. As compared to the simple ANFIS model, ANFIS-DE approximately 10.1% and ANFIS-DE/SVD model 7.2% is improved compared to the ANFIS-DE model. The accuracy of ANFIS-DE/SVD model showed better performance as well about 18.6% compared to the simple ANFIS model. Therefore, it can be said that not only DE optimization algorithms have a significant impact on increasing the performance of a simple ANFIS model but also using evolutionary algorithms (ANFIS-DE/SVD) reduce the ANFIS-DE model error accordingly. Polynomial equations of bank profiles proposed by hybrid ANFIS models in the present study can be used in design and implementation of cross section of stable channels.

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Section: Bank Profile Of Threshold Channel Modeling By Anfis-de/svdmentioning

confidence: 99%

Analyzing bank profile shape of alluvial stable channels using robust optimization and evolutionary ANFIS methods

et al. 2019

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show abstract

“…The energy absorption capacity is vitally influenced by mean collapse load. (Khalkhali et al, 2016) This exhibits the development of theoretical models in determining the mean collapse loads for square and circular cross-sections experiencing axisymmetric and asymmetric collapse modes. The strain rate effect plays a crucial role in improvement of yield stress of material.…”

Section: Quasi-static Crushing and Energy Absorption Characteristics mentioning

confidence: 99%

“…It assures the gradual loading through-out the process by avoiding the dynamic effects involved. Similarly, the quasi-static analysis was performed by employing AMPLITUDE and SMOOTHSTEP suboption for controlling the applied velocity was reported (Khalkhali et al, 2016); (Fan et al, 2013). Considering a thin-walled tube which was intersected with a hollow circular pipe whose crosssection is of ellipse with radii p and q.…”

Section: Description Of Numerical Modelmentioning

confidence: 99%

Quasi-Static Crushing and Energy Absorption Characteristics of Thin-Walled Cylinders with Geometric Discontinuities of Various Aspect Ratios

Baaskaran¹,

Ponappa²,

Shankar³

2017

Lat. Am. j. solids struct.

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“…The Multi-Objective Genetic Algorithm (MOGA) available within DE utilises the Non-dominated Sorted Genetic Algorithm-II (NSGA-II) (Evins 2013; Ansys 2013); described by Khalkhali et al (2016) as "one of the most powerful evolutionary algorithms for solving multiobjective optimisation problems". The NSGA-II, by using a population of solutions can find multiple "Pareto-optimal" solutions in one single optimisation run.…”

Section: The Optimisation Processmentioning

confidence: 99%

The use of CFD and multi-objective optimisation techniques to customise an industrial pre-mixer

Thompson

Walton

Hassan

et al. 2017

Struct Multidisc Optim

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Considering the use of commercial-off-the-shelf (COTS) devices in industry, a case study has been undertaken implementing the goal driven optimisation of a venturi-type pre-mixer. This COTS device is used to supply the correct ratio of a specific fuel and oxidiser to a pre-mix burner. Providing the correct quantity of excess air results in a reduction o f the NO x emissions; and this, in addition to the requirement for complete mixing of the constituents has been used to define the multi-objective optimisation of the device. A Computational Fluid Dynamics (CFD) simulation has been carried out using Fluent v14.5; verified by experimental data. To find an optimised design of the pre-mixer, four geometrical dimensions of its current design have been considered. An assessment of varying sampling and interpolation techniques has been made, in order to establish the most appropriate for use with this specific problem. The evolutionary-based NSGA-II and deterministic Nelder Mead optimisation algorithms have been used and their results compared to verify the optimisation outcome. Based on these findings suggested customisation of the COTS pre-mixer's design could result in improvements in mixing performance, in the region of 30 %.

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Multi-objective crashworthiness optimization of perforated square tubes using modified NSGAII and MOPSO

Cited by 41 publications

References 24 publications

Analyzing bank profile shape of alluvial stable channels using robust optimization and evolutionary ANFIS methods

Analyzing bank profile shape of alluvial stable channels using robust optimization and evolutionary ANFIS methods

Quasi-Static Crushing and Energy Absorption Characteristics of Thin-Walled Cylinders with Geometric Discontinuities of Various Aspect Ratios

The use of CFD and multi-objective optimisation techniques to customise an industrial pre-mixer

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