Article
Mechanics
B. P. van de Weg, L. Greve, M. Andres, T. K. Eller, B. Rosic
Summary: The study combines finite element model and neural network to predict the parameterized solution of a tensile specimen with a hardness transition zone, successfully capturing the local mesh deformation. The internal solution strategy of the RNN for predicting bifurcation phenomenon is investigated and visualized.
ENGINEERING FRACTURE MECHANICS
(2021)
Article
Mechanics
B. P. van de Weg, L. Greve, M. Andres, T. K. Eller, B. Rosic
Summary: The study utilizes a finite element model and neural network to predict the structural response of a tapered tensile specimen with a hardness transition zone and varying width parameter, allowing real-time model evaluation and capturing bifurcating local mesh deformation.
ENGINEERING FRACTURE MECHANICS
(2021)
Article
Engineering, Multidisciplinary
Suhan Kim, Hyunseong Shin
Summary: A deep learning framework is proposed for multiscale finite element analysis, in which a data-driven computational mechanics approach is adopted to overcome the inefficiency of the traditional FE2 method. Macroscopic strain and stress data are directly assigned to material points without using constitutive model. The proposed approach uses a deep neural network to enable adaptive sampling points and significantly improves the computational efficiency of offline computing.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2023)
Article
Construction & Building Technology
Murat Yaylaci, Ecren Uzun Yaylaci, Mehmet Emin Ozdemir, Sevil Ay, Sevval Ozturk
Summary: In this study, a two-dimensional model of the contact problem was examined using finite element method (FEM) and artificial neural network (ANN). The analysis showed that the non-dimensional quantities considered have a significant influence on the contact stress distribution. It was concluded that FEM and ANN can be efficient alternative methods if used correctly.
STEEL AND COMPOSITE STRUCTURES
(2022)
Article
Mathematics, Applied
Thang Le-Duc, H. Nguyen-Xuan, Jaehong Lee
Summary: In this study, a novel deep learning model called Finite-element-informed neural network (FEI-NN) is proposed for parametric simulation of static problems in structural mechanics. The approach uses supervised training to consider the parametric variables of structures as input features and implicitly embeds the spatial variables into the loss function through a soft constraint called finite element analysis (FEA) loss. The training process minimizes the empirical risk function while partially respecting the mechanical behaviors through the FEA loss, which is defined as a residual calculated from the weak form of the surrogate system scaled from the actual structure. Additionally, a technique based on batch matrix multiplication is introduced to reduce the time complexity for estimating the FEA loss. The method is demonstrated to outperform traditional data-driven approaches in terms of faster convergence and better DNN models for both generalization and extrapolation performance through several experiments.
FINITE ELEMENTS IN ANALYSIS AND DESIGN
(2023)
Article
Construction & Building Technology
Zi-Qing Yuan, Yu Xin, Zuo-Cai Wang, Ya-Jie Ding, Jun Wang, Dong-Hui Wang
Summary: This study proposes a novel nonlinear model updating approach based on an improved generative adversarial network (GAN). The improved GAN incorporates a convolutional neural network (CNN) surrogate model into the discriminator network to enhance its learning capability. The trained network model based on measured acceleration amplitudes can accurately estimate the nonlinear model parameters. Numerical simulations and experimental tests confirm the reliability and effectiveness of the improved GAN model for structural nonlinear model updating under seismic excitations.
STRUCTURAL CONTROL & HEALTH MONITORING
(2023)
Article
Engineering, Multidisciplinary
Saurabh Balkrishna Tandale, Bernd Markert, Marcus Stoffel
Summary: In this study, new methods using artificial neural networks (ANNs) are proposed to replace the constitutive law and the entire tangent stiffness matrix in finite element analysis. The combination of FEM with ANN leads to the development of intelligent elements. Sobolev training is introduced to ensure that the ANN learns the stress behavior function and its first derivative (material stiffness). Three methods are introduced to approximate the generalized force-displacement relations and replace the local stiffness matrix of an element. Neural networks are used to extract stiffness information for elements undergoing plastic deformation. The focus of this research is to establish a neural network-based FEM framework to introduce an enhanced-material law and approximate stiffness information of different elements.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2022)
Article
Multidisciplinary Sciences
Kiana Peiro Ahmady Langeroudy, Parsa Kharazi Esfahani, Mohammad Reza Khorsand Movaghar
Summary: Oil viscosity is crucial in petroleum engineering, and experimental methods and compositional methods can accurately estimate it. However, experimental data is difficult to obtain, so there is a need for convenient and fast methods to predict viscosity. This study uses machine learning methods (XGBoost, CatBoost, and GradientBoosting) based on gradient boosting decision tree to reduce the prediction error of viscosity by considering dissolved gas content, temperature, pressure, and API gravity. XGBoost outperforms other methods with higher precision and lower error, showing the effectiveness of the approach.
SCIENTIFIC REPORTS
(2023)
Article
Engineering, Geological
Cheng-Hsi Hsiao, Albert Y. Chen, Louis Ge, Fu-Hsuan Yeh
Summary: In this study, a pretrained model using machine learning techniques is proposed to directly estimate the safety factor and slip surface trace, providing a quick evaluation of the probability of failure. The convolutional neural network model outperforms the artificial neural network model, especially when considering additional random fields. This method effectively reduces the computation time compared to the traditional random finite element method.
Article
Materials Science, Multidisciplinary
Meijiaou Qu, Mengqi Li, Zhichao Wen, Weifeng He
Summary: This paper proposes a data-driven method for constructing a material mechanical behavior model, which can predict the mechanical behavior of any material under different loads. The accuracy of the prediction model is verified based on experimental data.
Article
Computer Science, Artificial Intelligence
Umar Farooq, Muhammad Wasif Shabir, Muhammad Awais Javed, Muhammad Imran
Summary: This paper presents two energy prediction techniques for fog nodes, based on Recursive Least Square and Artificial Neural Network, to enable intelligent energy-aware task offloading. Simulation results show that the ANN-based technique has up to 20% less root mean square error compared to the RLS-based technique.
APPLIED SOFT COMPUTING
(2021)
Article
Mechanics
Arturo Mendoza, Orestis Friderikos, Roger Trullo, Emmanuel Baranger
Summary: This work presents a data-driven approach based on Artificial Neural Networks (ANN), that provides a cheapernumerical alternative to experimental testing of advanced composite laminates. The chosen subject of study is the damage evolution and associated delamination failures of ply drops. The work aims at providing first-hand experience into the procedure of obtaining an ANN and employs dimensionality reduction techniques to propose a geometrical visualization of the nonlinear transformations performed by the ANN. Additional tests showed that the optimal well-trained ANN is accurate and robust enough for near real-time predictions of damage evolution patterns, outperforming other data-driven methods.
COMPOSITE STRUCTURES
(2023)
Article
Chemistry, Physical
Suria Devi Vijaya Kumar, Saravanan Karuppanan, Mark Ovinis
Summary: This study presents an assessment method for predicting failure pressure of high toughness corroded pipes under combined loading, which is currently unavailable in the industry. A correlation between corrosion defect geometry, longitudinal compressive stress, and failure pressure is established. Using an artificial neural network trained with failure pressure data from FEA, the proposed model accurately predicts failure pressure and investigates the effects of defect characteristics and compressive stress on corroded pipe failure pressure.
Review
Chemistry, Physical
Suria Devi Vijaya Kumar, Michael Lo Yin Kai, Thibankumar Arumugam, Saravanan Karuppanan
Summary: This paper discusses the use of artificial neural networks integrated with the finite element method to predict the failure pressure of corroded pipelines. The integration of ANN and FEM has been proven to significantly reduce the time taken to obtain accurate results compared to traditional methods.
Article
Mathematics
Suria Devi Vijaya Kumar, Saravanan Karuppanan, Veeradasan Perumal, Mark Ovinis
Summary: This paper proposes a set of empirical equations based on Artificial Neural Networks for predicting the failure pressure of pipe elbows subjected to combined loadings. The neural network was trained using data generated by the Finite Element Method. The study found that defect depth, length, spacing (longitudinal), and axial compressive stress significantly influenced the failure pressure of corroded pipe elbows, while the effects of circumferential defect spacing were insignificant.
Article
Engineering, Multidisciplinary
Dongxu Liu, Songyun Ma, Huang Yuan, Bernd Markert
Summary: This study develops an anisotropic poro-visco-hyperelastic-damage model to analyze the time-dependent fracture behavior of hydrogel composites. The model includes the coupling relationship between visco-hyperelasticity and fluid transport and describes the visco-hyperelasticity of the polymer networks and the fluid transport through the porous polymer networks. In addition, a continuum damage model is proposed to describe the mechanical degradation of hydrogel composites. The proposed model is validated through numerical simulations.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Automation & Control Systems
Shimaalsadat Mostafavi, Franz Bamer, Bernd Markert
Summary: This study investigated the mechanical deformations and diffusion patterns of the mating interface in ultrasonic welding of aluminum using molecular dynamics simulations, as well as the influence of two process parameters on the joints between aluminum strands. The research found that the orientations of the crystallites significantly affect the interface diffusion and tensile strength of the joint, with increasing sliding velocity leading to increased interface atom diffusion and friction heat generation that significantly raises the interface temperature.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Engineering, Mechanical
Daniel Frank Hesser, Kubilay Altun, Bernd Markert
Summary: The study utilizes the dynamic response of the suspension railway system Skytrain Dusseldorf to localize the train and monitor the infrastructure. Inertial measurement units gather data on vehicle movement and unique signal features are extracted to identify turns and stops along the track. Computational intelligence learns from operational data to recognize track features.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Chemistry, Multidisciplinary
Denny Thaler, Leonard Elezaj, Franz Bamer, Bernd Markert
Summary: This paper presents the use of machine learning algorithms to reduce the computational burden of Monte Carlo simulations. Artificial neural networks are used for supervised learning to predict structural response behavior, and a novel selection process for training data is proposed to reliably predict rare events.
APPLIED SCIENCES-BASEL
(2022)
Article
Materials Science, Composites
Sandeep P. Patil, Ambarish Kulkarni, Bernd Markert
Summary: A molecular-based three-dimensional (3D) continuum model of dragline silk of Araneus diadematus is proposed, which incorporates the plasticity of beta-sheet crystals, the rate-dependent behavior of the amorphous matrix, and the viscous interface friction between them. The model accurately predicts the tensile properties, velocity effects on mechanical properties, and hysteresis values based on available experimental data. This study sheds light on silk fiber mechanics and can be valuable for designing artificial composite materials.
JOURNAL OF COMPOSITES SCIENCE
(2022)
Article
Engineering, Geological
Mohamad Chaaban, Yousef Heider, Bernd Markert
Summary: In this paper, a reliable micro-to-macroscale framework is presented to model multiphase fluid flow through fractured porous media. The lattice Boltzmann method (LBM) is utilized within the phase-field modeling (PFM) of fractures to achieve this. New phase-field-dependent relationships for various parameters are proposed and a multiscale concept for coupling is achieved. Numerical simulations on real microgeometries of fractured porous media validate the reliability of the model.
INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS
(2022)
Review
Computer Science, Interdisciplinary Applications
Franz Bamer, Firaz Ebrahem, Bernd Markert, Benjamin Stamm
Summary: Disordered solids are widely used in engineering and everyday life. However, our understanding of the mechanics of these materials is still in its early stage. Particle-based molecular descriptions provide a powerful alternative to continuum-mechanical models due to the complexity of disorder.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Rutwik Gulakala, Bernd Markert, Marcus Stoffel
Summary: In this study, an artificial intelligence-based method is proposed for the rapid diagnosis of Covid infections using Generative Adversarial Network (GAN) and Convolutional Neural Networks (CNN). Synthetic and augmented data are generated to supplement the dataset, and two novel CNN architectures are proposed for the multi-class classification of chest X-rays. The proposed models achieved extremely high classification metrics with 40% fewer training parameters compared to existing models.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Engineering, Multidisciplinary
Cao Xiaodan, Abdelbacet Oueslati, An Danh Nguyen, Marcus Stoffel, Bernd Markert, Gery de Saxce
Summary: In a previous paper, the authors proposed a symplectic version of the Brezis-Ekeland-Nayroles principle for small deformations in plasticity. This work aims to extend this formalism to dissipative media with finite strains. It is achieved by developing Lagrangian and Hamiltonian formalisms for reversible media and then deriving a symplectic minimum principle for dissipative media in finite strains, which also gives a minimum principle for plasticity in finite strains.
INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE
(2023)
Article
Mechanics
Heiko Topol, Hadi Asghari, Marcus Stoffel, Bernd Markert, Jose Merodio
Summary: This article investigates the process of bubbling and bifurcation in a cylindrical membrane consisting of isotropic ground substance and fibers. It finds that material properties, fiber pre-stretch, fiber dispersion, and loading have significant effects on the initiation and post-bifurcation behavior.
EUROPEAN JOURNAL OF MECHANICS A-SOLIDS
(2023)
Article
Engineering, Mechanical
Y. S. Gao, S. Q. Zhang, Y. F. Zhao, S. Y. Ma, W. G. He, G. Z. Zhao, B. Markert
Summary: Sandwich structures with thick soft cores often deform in various modes, including bending, twisting, and compressing, when subjected to transverse loads. The compression of the core significantly affects the structural response. Classic plate theories are insufficient in predicting the behavior of such sandwich structures due to the assumption of no thickness change during deformation. In this study, a hybrid first/third-order shear deformation hypothesis is proposed, considering the compressive effect, to accurately analyze the mechanical response of sandwich structures with thick soft cores.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Mechanical
Hadi Asghari, Heiko Topol, Bernd Markert, Jose Merodio
Summary: This paper applies Sobol method and the Fourier Amplitude Sensitivity Test (FAST) method to analyze the influence of input parameters on the output variable in the problem of mixed extension, inflation, and torsion of a circular cylindrical tube with residual stress. The input parameters are distributed according to uniform, gamma, and normal distributions. The most influential factors are determined using Sobol and FAST methods, and the bias and standard deviation of Sobol and FAST indices are calculated to assess the results.
PROBABILISTIC ENGINEERING MECHANICS
(2023)
Article
Materials Science, Multidisciplinary
Baharin Ali, Yousef Heider, Bernd Markert
Summary: Additive manufacturing of metallic components has become a viable option for series production, and can produce dense parts with excellent properties by processing metallic powder layer-by-layer. However, the occurrence of residual stresses poses a major challenge in this process, negatively impacting the strength and functionality of the produced components. This study utilizes a phase-field model and a thermo-elastoplastic model to simulate the multi-layer additive manufacturing process and evaluate the resulting residual stresses.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Tobias Focks, Franz Bamer, Bernd Markert, Zhao Wu, Benjamin Stamm
Summary: This paper proposes a methodology to disentangle the interaction of two Stone-Wales defects in a two-dimensional model material. Numerical deformation tests validate the contribution of the defect interaction field to the mode of material failure.
Article
Engineering, Civil
Jian Xue, Weiwei Zhang, Jing Wu, Chao Wang, Hongwei Ma
Summary: This study integrates a plate-type local resonator with varying free boundaries within a plate to convert the initial low-order global vibration modes into localized vibration modes. A novel semi-analytical method is proposed to analyze the free vibration of the plate with thickness and displacement discontinuities. The results show that by applying free boundary conditions, the low-order localized vibration frequencies can be significantly reduced without affecting the low-order global frequencies.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Merve Tunay
Summary: In recent years, there has been an increasing number of studies on the mechanical properties of sandwich structures manufactured with the Fused Deposition Modeling (FDM) method. However, there is still a lack of experimental data on the mechanical characteristics of FDM-manufactured sandwich structures under different thermal aging durations. In this experiment, the energy absorption capabilities of sandwich structures with different core geometries were investigated under various thermal aging durations. The results showed that the core topology significantly influenced the energy absorption abilities of the sandwich structures.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Zi-qin Jiang, Zi-yao Niu, Ai-Lin Zhang, Xue-chun Liu
Summary: This paper proposes a crosssection corrugated plate steel special-shaped column (CCSC) that improves the bearing capacity and overall stability of structural columns by using smaller material input. Through theoretical analysis and numerical simulation, the overall stability of the CCSC under axial compression is analyzed. The design method and suggestions for the stability of CCSC are put forward. Compared with conventional square steel tube columns, the CCSC has obvious advantages in overall stability and steel consumption.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Yong Zhang, Yangang Chen, Jixiang Li, Jiacheng Wu, Liang Qian, Yuanqiang Tan, Kunyuan Li, Guoyao Zeng
Summary: A hybrid TPMS method was proposed to develop a new TPMS structure, and the mechanical properties of different TPMS structures were studied experimentally and numerically. Results showed that the hybrid TPMS structure had higher energy absorption and lower load-carrying capacity fluctuation. Further investigations revealed that the topological shape and material distribution had significant influence on mechanical properties, and the hybrid additive TPMS structure exhibited significant crashworthiness advantage in in-plane crushing condition.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Tongfei Sun, Ye Liu, Kaoshan Dai, Alfredo Camara, Yujie Lu, Lijie Wang
Summary: This paper presents a series of experimental and numerical studies on the performance of a novel double-stage coupling damper (DSCD). The effects of damper configuration, friction-yield ratio (Rfy), and loading protocol on the hysteresis performance of the DSCD are investigated. The test results demonstrate that the arrangement of ribs in the DSCD increases its energy dissipation capacity. Numerical analysis reveals that the length of the friction mechanism and the clearance between the yield segment and the restraining system affect the energy dissipation and stability of the damper.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Jeonghwa Lee, Young Jong Kang
Summary: This study investigates the local buckling behavior and strength of I-shape structural sections by considering flange-web interactions through three-dimensional finite element analysis. The study provides a more reasonable estimation of local buckling strength by considering the ratio of flange-web slenderness and height-to-width ratio, and presents design equations for flange local and web-bend buckling coefficients.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Yizhe Chen, Wenfeng Xiang, Qingsong Zhang, Hui Wang, Lin Hua
Summary: This study investigates the surface modification of a nickel plate to improve the bonding strength with carbon fiber-reinforced plastics (CFRP). The results show that different surface modification methods, including sandblasting, coupling agent treatment, and compound coupling agent treatment, significantly enhance the bonding strength of CFRP/Ni joints. The research provides insights into improving the connection between nickel and CFRP, as well as other heterogeneous materials.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Agha Intizar Mehdi, Fengping Zhang, Moon-Young Kim
Summary: A spatial stability theory of mono-symmetric thin-walled steel beams pre-stressed by spatially inclined cables is derived and its validity is demonstrated through numerical examples. The effects of initial tension, deviator numbers, inclined cable profiles, and bonded/un-bonded conditions on lateral-torsional buckling of the pre-stressed beams are investigated, with a specific emphasis on the effects of increasing initial tension.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Teng Ma, Jinxiang Wang, Liangtao Liu, Heng Li, Kui Tang, Yangchen Gu, Yifan Zhang
Summary: The structural response of water-back plate under the combined action of shock wave and bubble loads at water depths of 1-300 m was numerically investigated using an arbitrary Lagrange-Euler method. The accuracy of the numerical model was validated by comparing with experimental and theoretical results. The influences of water depth and length-to-diameter ratio of the charge on the combined damage effect were analyzed. The results show that as water depth increases, the plastic deformation energy of the water-back plate decreases, and the permanent deformation mode changes from convex to concave. When the charge has a large length-to-diameter ratio, the plastic deformation energy of the radial plate is higher than that of the axial plate, and the difference decreases with increasing water depth. Increasing the length-to-diameter ratio enhances the combined damage effect in the radial direction in deep-water environments.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Qiu-Yun Li, Ben Young
Summary: This paper investigates the flexural performance of CFS zed section members bent about the neutral axis parallel to the flanges through experimental and numerical analysis. The results show that the current direct strength method generally provides conservative predictions for the flexural strength of unstiffened zed section members, but slightly unconservative design for edge-stiffened zed section beams. The nominal flexural strengths of zed section members with edge stiffeners were found to be underestimated by 17% to 21% on average. Modified DSM formulae are recommended for the design of CFS zed section beams.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Weinan Gao, Bo Song, Xueyan Chen, Guochang Lin, Huifeng Tan
Summary: This paper presents a precise method for predicting deformation in large-scale inflatable structures, utilizing finite element modeling and laser scanning technique. The study shows a good agreement between the predictive model and non-contact measurement results.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Fei Gao, Zongyi Wang, Rui Zhu, Zhenming Chen, Quanxi Ye, Yaqi Duan, Yunlong Jia, Qin Zhang
Summary: This research investigates the mechanical properties of high-strength ring groove rivet assemblies and the load resistances of riveted T-stubs. Experimental tests reveal that Grade 10.9 rivets have higher yield strength and strain, and lower ultimate strain, making them suitable for high-strength ring groove rivet connections. Increasing the rivet diameter benefits the T-stubs, while increasing the flange thickness is not always advantageous. The Eurocode 3 method is not suitable for T-stubs connected through ring groove rivets, while the Demonceau method is conservative.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Shangchun Jiang, Liangfeng Sun, Haifei Zhan, Zhuoqun Zheng, Xijian Peng, Chaofeng Lue
Summary: This study investigates the bending behavior of two-dimensional nanomaterials, diamane and its analogous structure TBGIB, through atomistic simulations. It reveals that diamane experiences structural failure under bending, while TBGIB bends elastically before undergoing structural failure. The study provides valuable insights for the application of these materials in flexible electronics.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Qiang Zhang, Jianian Wen, Qiang Han, Hanqing Zhuge, Yulong Zhou
Summary: In this study, the mechanical properties of Q690 steel H-section columns under bi-directional cyclic loads are investigated, considering the time-varying characteristics of corrosion. A refined finite element (FE) model is built to analyze the degradation of mechanical property and failure mechanisms of steel columns with different design parameters during the whole life-cycle. The study proposes a quantitative calculation method for the ultimate resistance and damage index of steel columns, taking into account the ageing effects. The findings emphasize the importance of considering the ageing effects of steel columns in seismic design.
THIN-WALLED STRUCTURES
(2024)
Article
Engineering, Civil
Yuda Hu, Qi Zhou, Tao Yang
Summary: The magneto-thermo-elastic coupled free vibration of functionally graded materials cylindrical shell is investigated in this study. The vibration equation in multi-physical field is established and solved using the Hamilton principle and the multi-scale method. The numerical results show that the natural frequency is influenced by various factors such as volume fraction index, initial amplitude, temperature, and magnetic induction intensity.
THIN-WALLED STRUCTURES
(2024)