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Predictive Modelling for Mechanical Behaviour (PMMB) of Materials
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Predictive Modelling for Mechanical Behaviour (PMMB) of Materials

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Materials Simulation and Design".

Deadline for manuscript submissions: closed (20 April 2022) | Viewed by 7242

Special Issue Editor

Prof. Dr. John Durodola

E-Mail Website
Guest Editor
School of Engineering, Computing and Mathematics, Oxford Brookes University, Oxford OX33 1HX, UK

Special Issue Information

Dear Colleagues,

Predictive modelling for mechanical behaviour (PMMB) of materials is a widely accepted method for virtual prototyping for materials design and application performance analysis for parts and components. The relatively cheap availability of computing power makes it possible for this method to provide inexpensive guidance and evaluation of performance prior to materials manufacture and testing. PMMB modelling covers considerations of fundamentals such as interatomic forces and dislocation effects, as well as constitutive and empirical relations to predict linear and nonlinear properties and response of materials under general thermomechanical loading. The methods of analysis include classical and quantum mechanics approaches. At micro and macro-levels, nonlinear response analyses are often carried out using finite difference, boundary element, finite volume and predominantly finite element methods. Artificial intelligence machine learning methods have found a lot of applications lately, especially for empirical description of materials behaviour and likely performance. Materials of interest in this collection include polymers, metal alloys, ceramics and composites made from these materials. Predictive response analysis of interest includes elastic, plastic and viscoplastic deformation under general thermomechanical loading. Measures of failure cover limits of ductility, creep, yield, strength, fatigue and fracture. Also of interest is quantitative characterization of the influence of composition, processing, heat treatment and mechanical working on properties and behaviour. The coverage of composite materials includes mean field theory and classical laminate analysis methods.

This Special Issue welcomes review and state-of-the-art predictive modelling articles covering the material types and methods of analysis highlighted. The issue will serve as a helpful reference to designers, engineers and researchers with interest in sustainable design and application of materials in general.

Prof. Dr. John Durodola
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Materials is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • materials modelling
  • machine learning
  • elasticity
  • creep
  • strength
  • ductility
  • fracture
  • classical and quantum mechanics
  • processing
  • treatment
  • linear and nonlinear materials response plasticity

Published Papers (4 papers)

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Research

14 pages, 2623 KiB  
Article
Low-Cycle Fatigue of FRP Strips Glued to a Quasi-Brittle Material
by Enzo Martinelli and Antonio Caggiano
Materials 2021, 14(24), 7753; https://0-doi-org.brum.beds.ac.uk/10.3390/ma14247753 - 15 Dec 2021
Cited by 3 | Viewed by 1733
Abstract
This paper aims at further advancing the knowledge about the cyclic behavior of FRP strips glued to quasi-brittle materials, such as concrete. The results presented herein derive from a numerical model based on concepts of based on fracture mechanics and already presented and [...] Read more.
This paper aims at further advancing the knowledge about the cyclic behavior of FRP strips glued to quasi-brittle materials, such as concrete. The results presented herein derive from a numerical model based on concepts of based on fracture mechanics and already presented and validated by the authors in previous works. Particularly, it assumes that fracture processes leading to debonding develop in pure mode II, as is widely accepted in the literature. Starting from this assumption (and having clear both its advantages acnd shortcomings), the results of a parametric analysis are presented with the aim of investigating the role of both the mechanical properties of the interface bond–slip law and a relevant geometric quantity such as the bond length. The obtained results show the influence of the interface bond–slip law and FRP bond length on the resulting cyclic response of the FRP-to-concrete joint, the latter characterized in terms of S-N curves generally adopted in the theory of fatigue. Far from deriving a fully defined correlation among those parameters, the results indicate general trends that can be helpful to drive further investigation, both experimental and numerical in nature. Full article
(This article belongs to the Special Issue Predictive Modelling for Mechanical Behaviour (PMMB) of Materials)
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18 pages, 33017 KiB  
Article
Determination of the Critical Value of Material Damage in a Cross Wedge Rolling Test
by Zbigniew Pater, Andrzej Gontarz, Janusz Tomczak, Tomasz Bulzak and Łukasz Wójcik
Materials 2021, 14(7), 1586; https://0-doi-org.brum.beds.ac.uk/10.3390/ma14071586 - 24 Mar 2021
Cited by 3 | Viewed by 1800
Abstract
This study investigates the problem of material fracture in cross wedge rolling (CWR). It was found that this problem could be analysed by means of well-known phenomenological criteria of fracture that are implemented in commercial FEM (Finite Element Method) simulation programs for forming [...] Read more.
This study investigates the problem of material fracture in cross wedge rolling (CWR). It was found that this problem could be analysed by means of well-known phenomenological criteria of fracture that are implemented in commercial FEM (Finite Element Method) simulation programs for forming processes. The accuracy of predicting material fracture depends on the critical damage value that is determined by calibration tests in which the modelled and real stresses must be in good agreement. To improve this accuracy, a new calibration test is proposed. The test is based on the CWR process. Owing to the shape of the tools and test piece used in CWR, the forming conditions in this process deteriorate with the distance from the centre of the test piece, which at a certain moment leads to fracture initiation. Knowing the location of axial crack initiation in the specimen, it is possible to determine the critical value of material damage via numerical simulation. The new calibration test is used to determine the critical damage of 42CrMo4 steel subjected to forming in the temperature range of 900–1100 °C. In addition, 12 criteria of ductile fracture are employed in the study. The results show that the critical damage significantly increases with the temperature. Full article
(This article belongs to the Special Issue Predictive Modelling for Mechanical Behaviour (PMMB) of Materials)
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14 pages, 3716 KiB  
Article
Analytical Model for Springback Prediction of CuZn20 Foil Considering Size Effects: Weakening versus Strengthening
by Xin Guan, Zhenwu Ma, Chunju Wang, Haidong He, Yuanjing Zhang, Xinwei Wang and Weiwei Zhang
Materials 2020, 13(21), 4929; https://0-doi-org.brum.beds.ac.uk/10.3390/ma13214929 - 02 Nov 2020
Cited by 4 | Viewed by 1362
Abstract
The prediction of springback angle for ultra-thin metallic sheets becomes extremely difficult with the existence of size effects. In this study, size effects on the springback behavior of CuZn20 foils are investigated by experiments and analytical methods. The experimental results reveal that the [...] Read more.
The prediction of springback angle for ultra-thin metallic sheets becomes extremely difficult with the existence of size effects. In this study, size effects on the springback behavior of CuZn20 foils are investigated by experiments and analytical methods. The experimental results reveal that the springback angle first decreases gradually and then increases markedly with the decrease of foil thickness, which cannot be analyzed by current theoretical models. Then, an analytical model based on the Taylor-based nonlocal theory of plasticity is developed, in which the drastic increases of both the proportion of surface grains and the strain gradient are taken into account. Moreover, the influence of strain gradient is modified by the grain-boundary blocking factor. The calculation results show that the springback angle of foils is determined by the intrinsic competition between the decrement angle caused by surface grains and the increment angle caused by the strain gradient. Besides, the relative error of predicted springback angle by the model is less than 15%, which means that the developed model is very useful for improving the quality of micro sheet parts with high accuracy of springback prediction. Full article
(This article belongs to the Special Issue Predictive Modelling for Mechanical Behaviour (PMMB) of Materials)
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18 pages, 7319 KiB  
Article
Semi-Empirical Prediction of Residual Stress Distributions Introduced by Turning Inconel 718 Alloy Based on Lorentz Function
by Huachen Peng, Penghao Dong, Xianqiang Cheng, Chen Zhang, Wencheng Tang, Yan Xing and Xin Zhou
Materials 2020, 13(19), 4341; https://0-doi-org.brum.beds.ac.uk/10.3390/ma13194341 - 29 Sep 2020
Cited by 7 | Viewed by 1622
Abstract
The residual stress of machined surface has a crucial influence on the performance of parts. It results in large deviations in terms of the position accuracy, dimension accuracy and service life. The purpose of the present study is to provide a novel semi-empirical [...] Read more.
The residual stress of machined surface has a crucial influence on the performance of parts. It results in large deviations in terms of the position accuracy, dimension accuracy and service life. The purpose of the present study is to provide a novel semi-empirical residual stress prediction approach for turning Inconel 718. In the method, the bimodal Lorentz function was originally applied to express the residual stress distribution. A statistical model between the coefficients of the bimodal Lorentz function and cutting parameters was established by the random forest regression, in order to predict the residual stress distribution along the depth direction. Finally, the turning experiments, electrolytic corrosion peeling, residual stress measurement and correlation analysis were carried out to verify the accuracy of predicted residual stress. The results show that the bimodal Lorentz function has a great fitting accuracy. The adjusted R2 (Ad-R2) are ranging from 95.4% to 99.4% and 94.7% to 99.6% in circumferential and axial directions, respectively. The maximum and minimum errors of the surface residual tensile stress (SRTS) are 124.564 MPa and 18.082 MPa, those of the peak residual compressive stress (PRCS) are 84.649 MPa and 3.009 MPa and those of the depth of the peak residual compressive stress (DPRCS) are 0.00875 mm and 0.00155 mm, comparing three key feature indicators of predicted and simulated residual stress. The predicted residual stress is highly correlated with the measured residual stress, with correlation coefficients greater than 0.8. In the range of experimental measurement error, the research in the present work provides a quite accurate method for predicting the residual stress in turning Inconel 718, and plays a vital role in controlling the machining deformation of parts. Full article
(This article belongs to the Special Issue Predictive Modelling for Mechanical Behaviour (PMMB) of Materials)
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