Article
Materials Science, Composites
Wang Shun, Ma Qi-hua, Gan Xue-hui, Zhou Tian-jun
Summary: Reasonable design of induced holes can enhance the crashworthiness performance of thin-walled structures. By optimizing the parameters of the induced holes, the overall crashworthiness of the Al/CFRP tube was improved.
POLYMER COMPOSITES
(2021)
Article
Chemistry, Multidisciplinary
Tingting Wang, Mengchun Li, Dongchen Qin, Jiangyi Chen, Hongxia Wu
Summary: Materials with negative Poisson's ratio are attracting more and more attention from research scholars, especially in the field of fuel-efficient vehicles, due to their superior structural and mechanical properties. In this study, a new concave I-shaped honeycomb structure was established by integrating the re-entrant hexagon and the I-shaped beam structure, and its negative Poisson's ratio characteristics and energy absorption properties were investigated. The effect of structural parameters on the energy absorption characteristics was analyzed using a finite element model, and the optimal structure with better crashworthiness was obtained by optimizing the cell sizes.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Aerospace
Quan Lin, Jiexiang Hu, Qi Zhou
Summary: This paper proposes two parallel multi-objective Bayesian optimization (MOBO) approaches based on multi-fidelity surrogate modeling to improve the optimization efficiency. The approaches utilize cheap auxiliary low-fidelity data for better performance. The modified hypervolume expected improvement function is used to determine the updating points and fidelity levels, and two parallel computing strategies are developed for multi-point sampling. Additionally, a constraint handling strategy is introduced for constrained problems. The proposed approaches are validated through numerical benchmark examples and real-world applications, showing significant improvements in terms of efficiency and overall performance compared to state-of-the-art MOBO methods.
AEROSPACE SCIENCE AND TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Krisztian Gado, Tamas Orosz
Summary: This paper discusses a novel solution for the multi-objective TEAM benchmark problem, which focuses on optimizing the shape of a coil to achieve uniform field distribution and robust design. Symmetrical solutions were found to perform better in terms of uniformity and sensitivity measures, but some asymmetric solutions previously neglected can be competitive and interesting for practical design.
Article
Chemistry, Multidisciplinary
Qianchen Gao, Shoune Xiao, Xiaorui Wang, Mingmeng Wang, Tao Zhu
Summary: This paper aims to provide guidance on the crashworthiness design of cutting energy-absorbing structures for subway vehicles. Through experimental and numerical methods, a new energy-absorbing tube structure is proposed and optimized to improve the crashworthiness and reliability of the cutting energy-absorption structure. Multiple failure modes were observed in the tool during impact tests, with mechanical wear occurring mainly in the middle of the cutting edge and tip failure primarily due to thermal wear. The proposed structure effectively reduces high temperatures and maintains uniform temperature distribution, resulting in smooth cutting forces. The optimal solution for the tool's steady-state temperature and mean average cutting force is determined using the Kriging surrogate model and NSGA-II algorithm as STT = 514 K and MCF = 131 kN.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Information Systems
Jingliang Lin, Haiyan Li, Yunbao Huang, Junjie Liang, Sheng Zhou, Zeying Huang, Guiming Liang
Summary: This paper proposes a multi-objective surrogate modeling (MSM) method based on closed-loop transfer learning to address the challenges in simulation and optimization methods for forklift design. The MSM method improves the stability and accuracy of the surrogate model by pre-training a deep neural network model and transferring it with measurement data. Experimental results demonstrate the superiority of the MSM method and its valuable reference for simulation optimization of complex electromechanical products.
Article
Computer Science, Artificial Intelligence
Artur Leandro da Costa Oliveira, Andre Britto, Rene Gusmao
Summary: This study aims to propose a framework that combines an inverse modeling approach with multi-objective evolutionary algorithms to enhance the capability of solving many-objective optimization problems. The results show that the proposed framework outperforms or performs equally well as traditional methods in various scenarios, including benchmark problems and real-world problems.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Interdisciplinary Applications
Hyan Candido Guedes, Joao Luiz Junho Pereira, Guilherme Ferreira Gomes
Summary: This study aims to develop and parametrically optimize a high-performance composite material using interpolation strategy, thickness variations, and the number of layers. Four different multi-objective optimizers were evaluated to minimize total mass and evaluate the Tsai-Wu failure criterion under different loading conditions. The MOPSO algorithm demonstrated superior robustness and significantly improved the optimal solution compared to the initial model.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Engineering, Multidisciplinary
Cheng-Wei Fei, Huan Li, Cheng Lu, Lei Han, Behrooz Keshtegar, Osman Taylan
Summary: A synchronous modeling concept is proposed to improve the computational cost and accuracy for the multi-objective reliability design of complex structures. The Vectorial Surrogate Modeling (VSM) method is developed for synchronously establishing an overall model with multiple objectives. The VSM method shows superior performances in computational efficiency and accuracy for high-dimensional nonlinear problems.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Environmental Sciences
Ruochen Sun, Qingyun Duan, Xueli Huo
Summary: Parameter optimization is crucial for accurate environmental model simulations and predictions. The MO-ASMOGS method proposed in this study efficiently constructs a surrogate model of the original model by using both parameter and spatial grid sampling, significantly improving simulation results with only a small portion of total grid cells sampled for a given PFT.
WATER RESOURCES RESEARCH
(2021)
Article
Energy & Fuels
Jiawei Lu, Qiong Wang, Zhuxiu Zhang, Jihai Tang, Mifen Cui, Xian Chen, Qing Liu, Zhaoyang Fei, Xu Qiao
Summary: The study proposed an approach that incorporates surrogate modeling into multi-objective optimization, using RBF neural networks to construct surrogate models, adopting central composite design as a sampling strategy, and constructing surrogate models individually for different optimization objectives to improve prediction accuracy. The multi-objective bat algorithm was used to obtain the Pareto front in the design of dividing wall column and side-reactor column configuration, successfully achieving design options that balance capital and operating costs.
CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION
(2021)
Article
Engineering, Multidisciplinary
Sallam A. Kouritem, Mohammed I. Abouheaf, Nabil Nahas, Mohamed Hassan
Summary: This paper introduces a multi-objective design mechanism to minimize the initial and running costs of industrial robot arms. It utilizes stress analysis to determine the material and physical dimensions of the robot arm, as well as vibration analysis for material architecture selection. The paper presents design equations and optimization algorithms for the robot arm's performance improvement.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Engineering, Biomedical
Nelson S. Ribeiro, Joao Folgado, Helder C. Rodrigues
Summary: This study focused on solving a multi-objective optimization problem on a representative coronary stent platform to find new geometric designs with improved biomechanical performance. Different surrogate-based algorithms were employed and compared, with P-hv-EGO showing the best overall performance. The quality of the non-dominated solution sets outputted by each algorithm was assessed against four quality indicators, and the highest quality Pareto front was chosen for further analysis of the optimization results. Through cluster analysis, families of solutions with similar performance behavior were identified, shedding light on trade-offs between objectives and trends in biomechanics.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Junfeng Tang, Handing Wang, Lin Xiong
Summary: In preference-based multi-objective optimization, knee solutions are the implicit preferred promising solutions. However, finding knee solutions is difficult and computationally expensive. To address this issue, we propose a surrogate-assisted evolutionary multi-objective optimization algorithm that uses surrogate models to replace expensive evaluations. Experimental results show that our proposed algorithm outperforms state-of-the-art knee identification evolutionary algorithms on most test problems within a limited computational budget.
SWARM AND EVOLUTIONARY COMPUTATION
(2023)
Article
Engineering, Multidisciplinary
N. Ganesh, Uvaraja Ragavendran, Kanak Kalita, Paras Jain, Xiao-Zhi Gao
Summary: This paper combines high-fidelity finite element method (FEM) with metaheuristic optimization algorithms to propose a method for optimizing composite plates. The study found that the performance of this method in multi-objective Pareto optimization is comparable to NSGA-III.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2021)
Article
Materials Science, Composites
M. Heidari-Rarani, N. Ezati, P. Sadeghi, M. R. Badrossamay
Summary: Fused deposition modeling (FDM) is a common method for additive manufacturing of polymers, which is capable of producing complex parts quickly. This study examines the effect of three important process parameters - infill density, printing speed, and layer thickness - on the tensile properties of polylactic acid (PLA) specimens. The optimal parameters for maximum mechanical properties, minimum weight, and minimum printing time are determined using the Taguchi design of experiment method. The accuracy of the Taguchi method in predicting the mechanical properties of FDM-3D printed specimens is also assessed.
JOURNAL OF THERMOPLASTIC COMPOSITE MATERIALS
(2022)
Article
Mechanics
Kobye Bodjona, Sean Fielding, Mohammad Heidari-Rarani, Larry Lessard
Summary: The compliance of the adhesive layer has an impact on the strength of single-lap hybrid bonded-bolted joints. For joints with low compliance adhesive, adding a fastener does not provide benefits, while for joints with high compliance adhesive, adding a fastener significantly delays the initial failure. A proposed mechanism, supported by a numerical model, explains the observed behavior.
COMPOSITE STRUCTURES
(2021)
Article
Mechanics
F. Teimouri, M. Heidari-Rarani, F. Haji Aboutalebi
Summary: In this study, the fatigue damage models by Turon et al. and Kawashita-Hallett are extended with a trilinear cohesive law to simulate mode I fatigue delamination in composites with large-scale fiber bridging. The trilinear CZMs are found to be more accurate than bilinear CZMs in predicting fatigue delamination with fiber bridging effects, as validated by finite element analyses and experimental data comparisons. Additionally, a parametric study was conducted to investigate the sensitivity of the extended models to fitting parameters and quasi-static CZM parameters.
COMPOSITE STRUCTURES
(2021)
Article
Mechanics
Farhad Teimouri, Mohammad Heidari-Rarani, Farhad Haji Aboutalebi
Summary: In this study, VCCT and XFEM are combined to simulate fatigue delamination growth, comparing force and displacement control methods for accuracy. Challenges and advantages of VCCT and XFEM-VCCT approaches are discussed, with XFEM-VCCT showing high accuracy and low computational time.
ENGINEERING FRACTURE MECHANICS
(2021)
Article
Engineering, Multidisciplinary
Valentin S. Romanov, Mohammad Heidari-Rarani, Larry Lessard
Summary: The combination of bonding and bolting in a hybrid joint can result in a stronger and more durable joint. The overlap length of the joint significantly influences its strength, while the positioning of the bolts has a less pronounced impact. Joint stiffness is mainly governed by the overlap length, and load sharing between adhesive and bolts is geometry-dependent.
COMPOSITES PART B-ENGINEERING
(2021)
Article
Engineering, Mechanical
Mohammad Hossein Zamani, Mohammad Heidari-Rarani, Keivan Torabi
Summary: A novel angle graded auxetic honeycomb (AGAH) core with varying cell angles and constant wall thickness along the gradation has been designed. New analytical relations were proposed to predict the equivalent elastic properties of the core, which enhances specific stiffness and natural frequencies of sandwich structures. Analytical and finite element analyses were conducted to assess the core performance and investigate its impact on the vibration response of sandwich panels.
JOURNAL OF SANDWICH STRUCTURES & MATERIALS
(2022)
Article
Engineering, Mechanical
Mohsen Ahmadi Jebeli, Mohammad Heidari-Rarani
Summary: The study focused on the simulation and research of the two main challenges in the design of type IV composite pressure vessels, demonstrating a good correlation between numerical simulations and experimental results.
ENGINEERING FAILURE ANALYSIS
(2022)
Article
Engineering, Mechanical
Vahid Pourriahi, Mohammad Heidari-Rarani, Amir Torabpour Isfahani
Summary: The study presents analytical formulations for predicting the equivalent elastic properties of hexagonal aluminum honeycomb including all geometric parameters. Experimental results show good agreement between high-fidelity and low-fidelity models. The influence of various geometric parameters on the natural frequencies of sandwich beams is also investigated.
JOURNAL OF SANDWICH STRUCTURES & MATERIALS
(2022)
Article
Mechanics
Jianxia Wang, Tianliang Qin, Narasimha Rao Mekala, Yujun Li, Mohammad Heidari-Rarani, Kai-Uwe Schroeder
Summary: A three-dimensional progressive damage model for composite bolted joints under tensile loading was developed and validated. The model considered significant damage phenomena and showed high accuracy in predicting inflection load, failure load, load-displacement response, and failure modes. The study revealed that matrix cracking is the dominant failure mode in these joints.
COMPOSITE STRUCTURES
(2022)
Article
Engineering, Mechanical
Saeid Karimi, Farhad Haji Aboutalebi, Mohammad Heidari-Rarani
Summary: The present study aims to evaluate and improve the remeshing-free fatigue crack growth simulation and life estimation through the development of two algorithms, FEM-VCCT and XFEMPN-VCCT, in Abaqus. A new adaptive VCCT algorithm is introduced to enhance the accuracy of FCG simulation and life estimation.
FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES
(2022)
Article
Engineering, Chemical
Ali Sadeghi, Rasoul Mahshid, Mohammad Heidari-Rarani, Larry Lessard
Summary: This study investigates the influence of various parameters on the strength and failure mode of bonded composite-to-composite single-lap joints. The results show that the fiber angle has a significant effect on the shear and peel stresses in the adhesive layer. Experimental and numerical findings demonstrate that the failure of composite joints is greatly influenced by shear stress.
INTERNATIONAL JOURNAL OF ADHESION AND ADHESIVES
(2022)
Article
Materials Science, Composites
Mohammad Danesh, Hamid Beheshti, Mohammad Heidari-Rarani
Summary: The main challenge in the design of radar-absorbing composite structures is the variety of parameters affecting the absorbing performance. This study investigates the impact of different parameters, including reinforcing materials, geometric parameters, and manufacturing methods, on the radar-absorbing feature of composite structures.
JOURNAL OF REINFORCED PLASTICS AND COMPOSITES
(2023)
Article
Materials Science, Multidisciplinary
Ramin Jahadi, Hamid Beheshti, Mohammad Heidari-Rarani
Summary: This study proposes a novel micromechanics-based damage model to analyze the damage evolution of a two-component microencapsulated-based self-healing polymer composite. By implementing cohesive elements with a bilinear traction-separation law, the progressive damage of the epoxy matrix, PMMA shell, and capsule-matrix interfaces is investigated. The effects of interface bonding strength, fracture energy, and PMMA microcapsules volume fraction on the load-carrying capacity of the composite are studied. The results show that increasing interfacial strength and fracture energy leads to improved tensile strength, while a higher volume fraction of PMMA microcapsules decreases the load-carrying capacity.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
(2023)
Article
Engineering, Civil
Ramin Jahadi, Hamid Beheshti, Mohammad Heidari-Rarani, Amir H. Navarchian
Summary: This study investigated the effect of agitation speed on the morphology and particle size of epoxy/PMMA microcapsules, showing that the average diameter increased with higher mixing rates. The chemical structure of epoxy and hardener PMMA capsules was analyzed, and the reinforcing role of microcapsules in polymer composite materials was explored. The experimental results demonstrated a slight increase in tensile strength of the self-healing polymer composite with 1 wt.% PMMA microcapsules prepared at 1000 rpm, followed by a decrease with higher concentrations and larger sizes of PMMA microcapsules.
SMART STRUCTURES AND SYSTEMS
(2021)
