Article
Engineering, Manufacturing
Matthew Caputo, Ola Rashwan, Daudi Waryoba, Kevin McDade
Summary: This study investigates the effects of the ironing process on the physical properties of material extruded PLA. The ironing process can improve the surface morphology and affect the storage modulus and glass transition temperature. Parameter control can enhance the additive manufacturing process and be applied to various engineering applications.
ADDITIVE MANUFACTURING
(2022)
Article
Thermodynamics
Justine Noel, Christel Metivier, Simon Becker, Sebastien Leclerc
Summary: Natural convection in melting material was experimentally studied using Magnetic Resonance Imaging. The experiments revealed enhanced transient evolution of liquid height under convection, as well as a 4-fold increase in steady averaged liquid height in the convective regime. The convection patterns observed were in the form of hexagons/polygons, with scaling laws converging to beta = 1/4 showing an increase in convective intensity.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2022)
Article
Green & Sustainable Science & Technology
A. Vinod, M. R. Sanjay, Suchart Siengchin
Summary: This study utilized Morinda citrifolia fiber as a natural fiber material, improving the mechanical properties and thermal stability of fibers and composites through chemical treatments and the use of bio-based resins. The results demonstrated that Morinda citrifolia fiber is a potential sustainable raw material resource for reinforcement in polymer composites and lightweight structural applications.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Construction & Building Technology
Shuang Shi, Jusheng Tong, Feng Chen, Jianying Hu, Tao Ma
Summary: An advanced numerical modelling process was successfully implemented to accurately predict the evolution of asphalt pavement rutting using the finite element software ABAQUS. The process involved the derivation of a thermal-visco-elastic-plastic constitutive model for asphalt mixture and the implementation of a mathematical loading model based on tire-pavement interaction. Additionally, a heat transfer model was calculated to provide boundary conditions for the mechanical calculation. The numerical simulations showed that severe rutting at pavement intersections or parking lots is caused by both longer loading time and deeper plastic deformation region. The numerical model can also quantitatively identify the critical temperature at which pavement rutting starts to grow rapidly, allowing for the proposal of strategies to prevent or slow down rutting distress.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2023)
Article
Mechanics
A. Francisca Carvalho Alves, Bernardo P. Ferreira, F. M. Andrade Pires
Summary: A finite strain visco-elastic visco-plastic (three-dimensional) constitutive model is proposed in this study to predict the nonlinear behavior of amorphous polymers. The model modifies a well-known nucleation law and couples it with a nucleation criterion to suppress nucleation under compression and shear loadings. The growth of nucleated and initial voids is controlled by a modified Gurson's potential. The model is validated against literature results for polycarbonate and rubber-filled polycarbonate blends.
INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES
(2023)
Article
Materials Science, Multidisciplinary
Benjamin C. Cameron, C. Cem Tasan
Summary: Recent advancements in imaging techniques and correlation algorithms have enabled accurate measurement of strain fields and computation of stress fields on deforming materials, known as inverse problems. While current approaches face challenges and resort to statistical methods, a deterministic solution has been proposed and validated across various material categories.
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS
(2021)
Article
Construction & Building Technology
Jaehoon Bae, Young-Ju Kim, Chang-Hwan Lee
Summary: This paper discusses the advantages and importance of visco-plastic braces in improving seismic performance of steel structures, and simulation results demonstrate its positive effects on reducing structural drifts and plastic deformations, effectively controlling peak forces in the structure.
INTERNATIONAL JOURNAL OF STEEL STRUCTURES
(2022)
Article
Green & Sustainable Science & Technology
Mahdi Kazemi, Ali Kianifar, Hamid Niazmand
Summary: The research aimed to investigate the feasibility of using phase change material (PCM) to fabricate an air-PCM heat exchanger for buildings, showing that nano-PCMs can improve heat transfer efficiency and reduce melting and solidification time.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Materials Science, Multidisciplinary
Z. Liu, J. Reinoso, M. Paggi
Summary: A three-dimensional hygro-thermo-mechanical computational framework for photovoltaic laminates has been established and successfully implemented in this study. The method takes into account the thermal properties in thin-walled structures and the characteristics of polymeric interfaces, showing efficiency and reliability.
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS
(2022)
Article
Engineering, Geological
Ze-Jian Chen, Wei-Qiang Feng, Jian-Hua Yin, Xiu-Song Shi
Summary: This study developed a fully coupled finite element (FE) model and a simplified Hypothesis B method for predicting the long-term deformation of natural soft soils under embankments. The FE simulations showed good agreement with measured data, and the parametric studies indicated significant contributions to the accuracy of simulations from using averaged soil indices and updating static pore pressure. The improved simplified Hypothesis B method provided settlement results that closely matched the FE simulation results and measured data.
Article
Construction & Building Technology
Aboelkasim Diab
Summary: This study aims to investigate the linear and nonlinear viscoelastic responses as well as the healing efficiency of binder-filler systems. Rheometric tests and a rheological model were used to explore the relationship between stress and strain in the systems. A strain-dependent healing protocol was proposed to evaluate the healability of materials. The study found that the damage-mending process was more effective at small-amplitude strains, and the healing efficiency decreased with increasing strain levels. Additionally, it was observed that the presence of mineral fillers in the binder reduced the healing efficiency, but the binder-hydrated lime system showed better healing performance.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Instruments & Instrumentation
Jian Li, Zhihong Liang, Junjie Liu, Chao Yu, Xuelian Zhang, Qianhua Kan
Summary: The cyclic shape memory effect of thermo-induced shape memory polymers can be influenced by thermo-mechanical loading histories. During deformation, polymer chains undergo the initial dissociation of sub-entanglements, slipping, and orientation. The strain can be recovered through the internal rotation of the dihedral angle during reheating. A thermo-viscoelastic model is proposed to capture the cyclic shape memory effect, considering the slipping of polymer chains and the relationship between strain and orientation. The model is verified through experimental and simulated results, showing reasonable predictions of the cyclic shape memory effect.
SMART MATERIALS AND STRUCTURES
(2023)
Article
Chemistry, Physical
Wangyang Zhang, Jian Chen, Chenglong Wang, Di Liu, Linbo Zhu
Summary: This paper investigates the flattening contact behavior of an elastic-perfectly plastic hemisphere pressed by a rigid plane using the finite element method. The study compares and analyzes the behavior influenced by different elastic moduli, Poisson's ratios, and yield strengths in a wide range of interference values. The study proposes a new elastic-plastic constitutive model to predict the contact area and load in the elastic-plastic range and verifies its rationality compared to previous models and experiments.
Article
Engineering, Marine
Xin Bao, Jing-bo Liu, Shu-tao Li, Fei Wang
Summary: In this study, a visco-elastoplastic dynamic constitutive model and subroutine for coral sand material were developed to investigate the nonlinear seismic response of the reef-coral sand site in the South China Sea. The Matasovic skeleton curve and derived hysteretic curve were refined by introducing a critical shear modulus. Hysteresis criteria under irregular cyclic loads were established based on the improved Masing criteria. The study found that the coral sand layer significantly increases the site seismic responses, posing a threat to the seismic safety of buildings and constructions in the area. Moreover, the deformation of the reef-coral sand site tends to be concentrated on one side, resulting in residual displacement after earthquakes.
Article
Thermodynamics
Nicolo R. Sgreva, Justine Noel, Christel Metivier, Philippe Marchal, Hadrien Chaynes, Mykola Isaiev, Yves Jannot
Summary: This study provides a comprehensive characterization of an organic Phase Change Material (PCM) called hexadecane at multiple scales and physical aspects. The research investigates the macroscopic thermal and physical properties, as well as the behavior of hexadecane during phase transition. It is found that there is a thermal hysteresis between melting and solidification temperatures, and the interface conditions play a significant role in the phase transition.
THERMOCHIMICA ACTA
(2022)
Article
Engineering, Mechanical
Diab W. Abueidda, Seid Koric, Nahil A. Sobh, Huseyin Sehitoglu
Summary: This study applied sequence learning models to predict the history-dependent responses of materials, showing that gated recurrent unit and temporal convolutional network can accurately learn and instantly predict such phenomena, with TCN being more computationally efficient during the training process.
INTERNATIONAL JOURNAL OF PLASTICITY
(2021)
Article
Materials Science, Multidisciplinary
Hyunjin Yang, Hamed Olia, Brian G. Thomas
Summary: Air aspiration is a significant issue in continuous casting of steel, leading to nozzle clogging and inclusions in final products. A 1-D pressure-energy model was developed to predict pressure distribution and throughput under dynamic operating conditions and varying clogging scenarios. Parametric studies showed that a smaller submerged entry nozzle diameter can reduce negative pressure by increasing friction losses.
Article
Computer Science, Interdisciplinary Applications
Fereshteh A. Sabet, Seid Koric, Ashraf Idkaidek, Iwona Jasiuk
Summary: This study compared implicit and explicit methods in investigating the mechanical properties of trabecular bone using finite element analysis. The results indicated that the two methods gave comparable results, with the explicit method performing faster and consuming less memory.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2021)
Article
Materials Science, Multidisciplinary
Seid Koric, Diab W. Abueidda
Summary: This study utilizes advanced numerical modeling techniques and deep learning methods to accurately capture and predict the nonlinear thermo-mechanical behavior of solidifying steel, even in unseen test data samples.
Article
Engineering, Multidisciplinary
Diab W. Abueidda, Qiyue Lu, Seid Koric
Summary: Deep learning and the collocation method are merged to solve partial differential equations describing structures' deformation, offering a meshfree approach that avoids spatial discretization and data generation bottlenecks.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2021)
Article
Multidisciplinary Sciences
Patricia M. Gregg, Yan Zhan, Falk Amelung, Dennis Geist, Patricia Mothes, Seid Koric, Zhang Yunjun
Summary: By combining satellite InSAR data with numerical models using high-performance computing data assimilation, the prolonged unrest and eruption timing of the Sierra Negra volcano in the Galapagos were successfully predicted. The evolution of the stress state in the surrounding rock and a faulting event were found to be key factors in the eruption.
Article
Engineering, Chemical
Mingyi Liang, Seong-Mook Cho, Xiaoming Ruan, Brian G. Thomas
Summary: A new model of particle entrapment during continuous casting of steel, considering the effects of multiphase flow and thermal buoyancy, is presented. The model simulates three capture mechanisms and the results are validated with plant measurements. It is found that superheat has negligible effect on mold flow, but higher superheat results in more complex flow in the lower strand, leading to fewer particle captures.
Article
Computer Science, Interdisciplinary Applications
Shantanu Shahane, Erman Guleryuz, Diab W. Abueidda, Allen Lee, Joe Liu, Xin Yu, Raymond Chiu, Seid Koric, Narayana R. Aluru, Placid M. Ferreira
Summary: Surrogate neural network models are used in cell phone camera systems to accurately evaluate lens configurations and analyze optical properties. They provide efficient handling of large amounts of data for sensitivity and uncertainty analysis, and are valuable tools for optimizing tolerance design and component matching.
COMPUTERS & STRUCTURES
(2022)
Article
Engineering, Multidisciplinary
Junyan He, Diab Abueidda, Seid Koric, Iwona Jasiuk
Summary: This paper investigates the application of graph convolutional networks in the deep energy method model for solving the momentum balance equation of linear elastic and hyperelastic materials in three-dimensional space. Numerical examples demonstrate that the proposed method achieves similar accuracy with shorter run time compared to traditional methods. The study also discusses two different spatial gradient computation techniques.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2023)
Article
Materials Science, Multidisciplinary
Ghavam Azizi, Brian G. Thomas, Mohsen Asle Zaeem
Summary: The study found that during solidification, gaps caused by thermal contraction form and grow the most in the early stages, remaining unchanged afterward. Increasing heat flux decreases the time for gap evolution and increases its depth. Alloys with lower carbon content are more sensitive to heat flux, while alloys with higher carbon contents show weaker sensitivity.
Article
Engineering, Multidisciplinary
Diab W. Abueidda, Seid Koric, Erman Guleryuz, Nahil A. Sobh
Summary: Physics-informed neural networks are used to solve equations governing physical phenomena, but they have issues that can be resolved using techniques like Fourier transform. This paper proposes a physics-informed neural network model with multiple loss terms and weight assignment using the coefficient of variation scheme. The model is standalone and meshfree, accurately capturing mechanical response. The study focuses on 3D hyperelasticity and demonstrates the model's performance by solving various problems.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2023)
Article
Engineering, Manufacturing
V. Perumal, D. Abueidda, S. Koric, A. Kontsos
Summary: Metal additive manufacturing (AM) involves complex multiscale and multiphysics processes. Deep learning-based approaches, specifically temporal convolutional networks (TCNs), have been proposed as a solution to the challenges faced by physics-based modeling methods in predicting thermal histories in AM. This study presents the use of TCNs for fast inferencing in directed energy deposition (DED) processes, achieving comparable accuracy to other deep learning methods with significantly reduced compute and training times.
JOURNAL OF MANUFACTURING PROCESSES
(2023)
Article
Automation & Control Systems
Bryan Petrus, Zhelin Chen, Hamza El-Kebir, Joseph Bentsman, Brian G. Thomas
Summary: This paper investigates the one-dimensional Stefan problem and expresses the system state using enthalpy. By combining a full-state controller and an observer, output feedback trajectory tracking control strategies are proposed, and the closed-loop convergence of the temperature and interface errors for both single-sided and two-sided Stefan problems is proven. Simulation results demonstrate exponential-like trajectory convergence achieved by implementable smooth bounded control signals.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Thermodynamics
Seid Koric, Diab W. Abueidda
Summary: DeepONet approximates linear and nonlinear PDE solution operators by using parametric functions as inputs and mapping them to different PDE solution function output spaces. Unlike PINN, DeepONet models can predict parametric solutions in real-time without the need for retraining or transfer learning. It shows good performance in solving the heat conduction equation and is orders of magnitude faster than classical numerical solvers.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2023)
Article
Engineering, Mechanical
Daegun You, Orcun Koray Celebi, Ahmed Sameer Khan Mohammed, Diab W. Abueidda, Seid Koric, Huseyin Sehitoglu
Summary: A predictive model is developed to accurately predict the dislocation glide stress in FCC materials, considering the anisotropic continuum energy, the atomistic misfit energy, and the minimum energy path for the intermittent motion of Shockley partials. By generating a large material dataset and using machine learning, the model achieves a 94% accuracy in predicting the critical resolved shear stress for 1033 materials, revealing the sensitivity of material parameters to the predicted stress.
INTERNATIONAL JOURNAL OF PLASTICITY
(2023)