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The purpose of this paper is to investigate the thermomechanical behavior of stainless steel AISI 304L during rolling at elevated temperatures.

Two-dimensional finite element analysis together with the upper-bound solution were used for predicting temperature field and required power in warm and hot rolling operations. The required power and heat of deformation were estimated employing an upper-bound solution based on cylindrical velocity field and at the same time, temperature distributions within the rolling steel and the work rolls were determined by means of a thermal finite element analysis. To consider the effect of flow stress and its dependence on temperature, strain and strain rate, a neural network model was used and combined with the thermal and mechanical models. Finally, the microstructure of rolled steel was studied and the effect of rolling conditions was justified employing the predictions.

The results have shown that the predicted temperature variations were in good agreement with the experiments. Moreover, the model was shown to be capable of determining the effects of various rolling parameters such as reduction and rolling speed with low-computational cost as well as reasonable accuracy.

A combined upper-bound finite element analysis was developed to predict the required power and temperature field during plate rolling while the model can be employed under both hot and warm rolling conditions.

The purpose of this paper is to develop a mathematical solution to estimate the deformation pattern and required power in cold plate rolling using coupled stream function method and upper bound theorem.

In the first place, an admissible velocity field and the geometry of deformation zone are derived from a new stream function. Then, the optimum velocity field is obtained by minimizing the corresponding power function. Also, to calculate the adiabatic heating during high speed rolling operations, a two-dimensional conduction-convection problem is sequentially coupled with the mechanical model. To verify the predictions, rolling experiments on aluminum plates are conducted and also, a finite element analysis is performed by Abaqus/Explicit. The predicted deformation zone is then compared with the experimentally measured region as well as with the results of the finite element analysis.

The results show that the predicted deformation zone and the temperature distribution fit reasonably with the experimental data while much lower computational cost needs comparing to the fully finite element analysis.

A new stream function is proposed to properly describe the velocity field and deformation pattern during plate rolling considering the neutral point. Furthermore, the employed algorithm can be simply coupled with the thermal finite element analysis.

The purpose of this paper is to propose a mathematical model to estimate required energy and temperature distribution during cold extrusion process.

An admissible velocity field is generated based on stream function technique. Then, the required energy and the temperature distributions in the metal and the extrusion die are determined by a coupled upper bound‐finite element analysis.

To examine the proposed model, cold extrusion of AA6061‐10%SiC_p is considered and the predicted extrusion force‐displacement diagrams in different reductions are compared with the experimental ones and reasonable agreement is observed. Furthermore, it is found that there is a linear relationship between maximum temperature and logarithm of ram velocity for the examined composite.

This approach requires shorter run‐time as compared with fully finite element analyses while the model is particularly appropriate for high speed extrusion processes where the adiabatic heating is of importance.

The purpose of this paper is to study the kinetics of static recovery in cold-rolled aluminum alloy under different heating rates.

Deformation modeling was first performed to assess the distributions of plastic strain and stress within the deformed alloy. In the next stage, thermal analysis and the rate equation of static recovery were employed to determine the progress of static recovery under non-isothermal conditions. Accordingly, a thermal finite element analysis and the Runge-Kutta method were utilized to handle the transient heat conduction and the progress of static recovery. Finally, low temperature annealing heat treatments were conducted to verify the model predictions. Accordingly, the tensile tests were conducted to measure the yield stresses of cold-rolled plates subjected to the subsequent annealing treatment at different temperatures and durations.

The results indicate that the employed algorithm can be used as an appropriate predictive tool for designing a low temperature heat treatment schedule to achieve the desired yield stress.

The kinetics of non-isothermal recovery and resulting yield stress are well predicted under practical annealing conditions.

This study aims to focus on numerical simulation investigations of phase transformation during cooling of 55SiMnMo steel, which is commonly applied to improve mechanical properties.

A mathematical model based on the finite element method (FEM) and the phase transformation kinetics model has been proposed to predict microstructure changes during continuous cooling of 55SiMnMo steel. This model can be employed to analyze the variation of austenite, special upper bainite and lump-like composite structure with cooling time at different cooling rates.

According to the continuous cooling experiments, when the cooling rate is lower than 0.1°C/s, the special upper bainite is the only transformation product which decreases with increasing cooling rate; when the cooling rate is above 0.5°C/s, the transformation products include special upper bainite and lump-like composite structure. Meanwhile, the results of continuous cooling experiment verified the correctness of this finite element model.

This model has a great value for proper controlling of the cooling process which can improve the quality of hollow drill steel and increase the service life of the final product.

The application of new technologies requires, however, modern rolling mills. Indeed, in manufacturing plants of older types, strict compliance with the developed rolling regimes is not always feasible. Improving the mechanical properties in such cases is possible only by means of cooling. Compressive deformation behavior of carbon–manganese (C-Mn) grade has been investigated at temperatures ranging from 800-900°C and strain rate from 0.01-50 s−1 on Gleeble-3800, a thermo-mechanical simulator. Simulation studies have been conducted mainly to observe the microstructural changes for various strain rate and deformation temperatures at a constant strain of 0.5 and a cooling rate of 20°C s−1.

The project begins with simulation of a hot rolling condition using the thermo-mechanical simulator; this was followed by microstructural examination and identification of phases present by using an optical microscope for hot-rolled coil and simulated samples; grain size measurement and size distribution studies; and optimization of finishing temperature, coiling temperature and cooling rate by mimicking plant processing parameters to improve the mechanical properties.

As the strain rate and temperature increase, pearlite banding decreases gradually and finally gets completely eliminated, thereby improving the mechanical properties. True stress–strain curves were plotted to extrapolate the effect of strain-hardening and strain rate sensitivity on austenite (γ) and austenite–ferrite (γ-a) regions. To validate the effect of strain rate and temperature over the grain size, the hardness of simulated samples was measured using the universal hardness tester and the corresponding tensile strength was found from the standard hardness chart.

The results of the study carried out have projected a new technology of thermo-mechanical simulation for the studied C-Mn grade. These results were used to optimize the plant processing parameter like finishing and coiling temperature and finishing stands strain rate.

By controlling the hot rolling conditions like finishing, coiling temperature and cooling rate, structures differing in mechanical properties can be obtained for the same material. Accurate understanding of a structure being formed when different temperatures are applied enables the control of the process that assures intended structures and mechanical properties are achieved.

To provide a selective bibliography for researchers working with bulk material forming (specifically the forging, rolling, extrusion and drawing processes) with sources which can help them to be up‐to‐date.

A range of published (1996‐2005) works, which aims to provide theoretical as well as practical information on the material processing namely bulk material forming. Bulk deformation processes used in practice change the shape of the workpiece by plastic deformations under forces applied by tools and dies.

Provides information about each source, indicating what can be found there. Listed references contain journal papers, conference proceedings and theses/dissertations on the subject.

It is an exhaustive list of papers (1,693 references are listed) but some papers may be omitted. The emphasis is to present papers written in English language. Sheet material forming processes are not included.

A very useful source of information for theoretical and practical researchers in computational material forming as well as in academia or for those who have recently obtained a position in this field.

There are not many bibliographies published in this field of engineering. This paper offers help to experts and individuals interested in computational analyses and simulations of material forming processes.

This study presents finite element (FE) and generalized regression neural network (GRNN) approaches for modeling multiple crack growth problems and predicting crack-growth directions under the influence of multiple crack parameters.

To determine the crack-growth direction in aluminum specimens, multiple crack parameters representing some degree of crack propagation complexity, including crack length, inclination angle, offset and distance, were examined. FE method models were developed for multiple crack growth simulations. To capture the complex relationships among multiple crack-growth variables, GRNN models were developed as nonlinear regression models. Six input variables and one output variable comprising 65 training and 20 test datasets were established.

The FE model could conveniently simulate the crack-growth directions. However, several multiple crack parameters could affect the simulation accuracy. The GRNN offers a reliable method for modeling the growth of multiple cracks. Using 76% of the total dataset, the NN model attained an R2 value of 0.985.

The models are presented for static multiple crack growth problems. No material anisotropy is observed.

In practical crack-growth analyses, the NN approach provides significant benefits and savings.

The proposed GRNN model is simple to develop and accurate. Its performance was superior to that of other NN models. This model is also suitable for modeling multiple crack growths with arbitrary geometries. The proposed GRNN model demonstrates its prediction capability with a simpler learning process, thus producing efficient multiple crack growth predictions and assessments.

This study aims to investigate the effect of financial inclusion on economic welfare in three religious country groups: majority Christian countries, majority Hindu countries and majority Muslim countries.

The study analyzed 30 religious countries during the 2004–2020 period using the two-stage least squares regression method. The economic welfare variables are the gross domestic product (GDP) growth rate, GDP per capita growth, inflation rate and the unemployment rate. The main explanatory variable is the composite financial inclusion index. The control variables are corruption control index, political stability index, total population growth, rule of law index and the regulatory quality index.

Financial inclusion is positively correlated with corruption control, political stability, rule of law and regulatory quality in religious countries, whereas financial inclusion is negatively correlated with total population growth, economic growth, GDP per capita growth, inflation rate and unemployment rate in religious countries. Regression results show that high level of financial inclusion decreases the unemployment rate in majority Muslim countries. A preexisting low unemployment rate is significantly associated with higher financial inclusion in majority Christian and Muslim countries. High level of financial inclusion decreases the inflation rate in countries that have significant Islamic finance activity. Financial inclusion has an insignificant effect on economic welfare in majority Hindu countries.

The type of religion and the size of Islamic finance activity matter in understanding the relationship between financial inclusion and economic welfare in religious countries.

To the best of the author’s knowledge, this study is the first to examine financial inclusion dynamics and its effect on economic welfare in the context of the major religions.

The aim of this paper is to investigate the failure probability in an irregular area in pipeline (elbow) over its lifetime. The reliability analysis is performed by using of an enhanced first-order reliability method / second-order reliability method (FORM/SORM) and Monte Carlo simulation methods: a numerical model of a corroded pipeline elbow was developed by using finite element method; also, an empirical mechanical behavior model has been proposed. A numerical case with high, moderate and low corrosion rates was conducted to calculate the deferent reliability indexes. The found results can be used in an application case for managing an irregular area in pipeline lifetime. Hence, it is necessary to ensure a rigorous inspection for this part of a pipeline to avoid human and environmental disasters.

The present paper deals a methodology for estimating time-dependent reliability of a corroded pipeline elbow. Firstly, a numerical model of corroded elbow is proposed by using the finite element method. A mechanical behavior under the corrosion defect in time is studied, and an empirical model was also developed.

The result of this paper can be summarized as: a mechanical characterization of the material was carried out experimentally. A numerical model of a corroded pipeline elbow was developed by using the finite element method. An empirical mechanical behavior model has been developed. The reliability of a corroding pipe elbow can be significantly affected by corrosion and residual stress. A proportional relationship has been found between probability of failure and corrosion rate. The yield stress and pressure service have an important sensitivity factor.

Aiming to help Algerian gas and oil companies' decision makers, the present paper illustrates a methodology for estimating time-dependent reliability of a corroded pipeline elbow over its lifetime using numerical models by applying the finite element method. Firstly, a numerical model of a corroded pipe elbow was developed and coupled with an empirical mechanical behavior model, which is also proposed. A probabilistic is then developed to provide realistic corrosion parameters and time modeling, leading to the real impact on the lifetime of an elbow zone in pipeline. The reliability indexes and probability of failure for various corrosion rates with and without issued residual stress are computed using Monte Carlo simulation and FORM.