Materials

Research

15 pages, 1988 KiB

Open AccessArticle

Numerical Simulation of Dry Ice Compaction Process: Comparison of Drucker-Prager/Cap and Cam Clay Models with Experimental Results

by Maciej Berdychowski, Jan Górecki, Aleksandra Biszczanik and Krzysztof Wałęsa

Materials 2022, 15(16), 5771; https://doi.org/10.3390/ma15165771 - 21 Aug 2022

Cited by 12 | Viewed by 1617

Abstract

This article presents the results of a numerical experimental study on the simulation of the dry ice compaction process. The first part of the article presents a description of the material used, material models and the methodology of experimental research. In the second [...] Read more.

This article presents the results of a numerical experimental study on the simulation of the dry ice compaction process. The first part of the article presents a description of the material used, material models and the methodology of experimental research. In the second part, numerical and experimental study results are presented. For the purpose of comparison, a parametric method based on the residual sum of squares was used. The application of the indicated method fills the gap in the available literature as the authors are not aware of any existing data from previous studies on the method of comparing the results of numerical tests in terms of the obtained results and the change of the value of the tested parameter as a function of another variable. The results of this study can be useful in research work aimed at further development of the process of extrusion and compaction of dry ice using Drucker-Prager/Cap and modified Cam-Clay material models for instance for optimization of geometric parameters of parts and components of the main assembly of the machine used in the process of dry ice extrusion. Full article

(This article belongs to the Special Issue Numerical Modeling for Simulation of Different Processes in Manufacturing)

► Show Figures

Figure 1

25 pages, 14093 KiB

Open AccessArticle

Designing a Cruciform Specimen via Topology and Shape Optimisations under Equal Biaxial Tension Using Elastic Simulations

by Junxian Chen, Jianhai Zhang and Hongwei Zhao

Materials 2022, 15(14), 5001; https://doi.org/10.3390/ma15145001 - 18 Jul 2022

Cited by 4 | Viewed by 2021

Abstract

Stress uniformity within the gauge zone of a cruciform specimen significantly affects materials’ in-plane biaxial mechanical properties in material testing. The stress uniformity depends on the load transmission of the cruciform specimen from the fixtures to the gauge zone. Previous studies failed to [...] Read more.

Stress uniformity within the gauge zone of a cruciform specimen significantly affects materials’ in-plane biaxial mechanical properties in material testing. The stress uniformity depends on the load transmission of the cruciform specimen from the fixtures to the gauge zone. Previous studies failed to alter the nature of the load transmission of the geometric features using parametric optimisations. To improve stress uniformity in the gauge zone, we optimised the cross-arms to design a centre-reduced cruciform specimen with topology and shape optimisations. The simulations show that the optimised specimen obtains significantly less stress variation and range in the gauge zone than the optimised specimen under different observed areas, directions, and load ratios of von Mises, S₁₁, S₂₂, and S₁₂. In the quantified gauge zone, a more uniform stress distribution could be generated by optimizing specimen geometry, whose value should be estimated indirectly each time through simulations. We found that topology and shape optimisations could markedly improve stress uniformity in the gauge zone, and stress concentration at the cross-arms intersection. We first optimised the cruciform specimen structure by combining topology and shape optimisations, which provided a cost-effective way to improve stress uniformity in the gauge zone and reduce stress concentration at the cross-arms intersection, helping obtain reliable data to perform large strains in the in-plane biaxial tensile test. Full article

(This article belongs to the Special Issue Numerical Modeling for Simulation of Different Processes in Manufacturing)

► Show Figures

Figure 1

17 pages, 7906 KiB

Open AccessArticle

A Coupled Eulerian-Lagrangian Simulation and Tool Optimization for Belt Punching Process with a Single Cutting Edge

by Dominik Wojtkowiak, Krzysztof Talaśka, Dominik Wilczyński, Jan Górecki and Krzysztof Wałęsa

Materials 2021, 14(18), 5406; https://doi.org/10.3390/ma14185406 - 18 Sep 2021

Cited by 5 | Viewed by 1824

Abstract

The objective of this paper is to analyze the belt punching process with the use of a single cutting edge and discuss the influence of geometrical features of the piercing punch on the perforation force. Two basic shapes of the piercing punch with [...] Read more.

The objective of this paper is to analyze the belt punching process with the use of a single cutting edge and discuss the influence of geometrical features of the piercing punch on the perforation force. Two basic shapes of the piercing punch with a single cutting edge were tested: tools with the blade pointing inside or pointing outside. The analytical models of the stress distribution in the shearing cross sections were derived for both punches. The presented model, along with the series of empirical tests and Coupled Eulerian-Lagrangian simulation, was used for finding the effective geometry of the piercing punch with a single cutting edge for the belt perforation. The geometrical parameters taken into consideration for the tool optimization were the following: angle of the blade, thickness of the wall and diameter of the piercing punch cutting edge. The obtained results show that changing these parameters has a significant influence on the perforation force necessary to execute the machining process and affects the quality of the holes in the perforated belts. The most important geometrical features of the hollow sharpened punch are the angle and the direction of the blade, which change the force distribution and, as a result, the mechanics of the process. Full article

(This article belongs to the Special Issue Numerical Modeling for Simulation of Different Processes in Manufacturing)

► Show Figures

Figure 1

16 pages, 1999 KiB

Open AccessArticle

Comparison of NSGA-II, MOALO and MODA for Multi-Objective Optimization of Micro-Machining Processes

by Milan Joshi, Ranjan Kumar Ghadai, S. Madhu, Kanak Kalita and Xiao-Zhi Gao

Materials 2021, 14(17), 5109; https://doi.org/10.3390/ma14175109 - 6 Sep 2021

Cited by 28 | Viewed by 3027

Abstract

The popularity of micro-machining is rapidly increasing due to the growing demands for miniature products. Among different micro-machining approaches, micro-turning and micro-milling are widely used in the manufacturing industry. The various cutting parameters of micro-turning and micro-milling has a significant effect on the [...] Read more.

The popularity of micro-machining is rapidly increasing due to the growing demands for miniature products. Among different micro-machining approaches, micro-turning and micro-milling are widely used in the manufacturing industry. The various cutting parameters of micro-turning and micro-milling has a significant effect on the machining performance. Thus, it is essential that the cutting parameters are optimized to obtain the most from the machining process. However, it is often seen that many machining objectives have conflicting parameter settings. For example, generally, a high material removal rate (MRR) is accompanied by high surface roughness (SR). In this paper, metaheuristic multi-objective optimization algorithms are utilized to generate Pareto optimal solutions for micro-turning and micro-milling applications. A comparative study is carried out to assess the performance of non-dominated sorting genetic algorithm II (NSGA-II), multi-objective ant lion optimization (MOALO) and multi-objective dragonfly optimization (MODA) in micro-machining applications. The complex proportional assessment (COPRAS) method is used to compare the NSGA-II, MOALO and MODA generated Pareto solutions. Full article

(This article belongs to the Special Issue Numerical Modeling for Simulation of Different Processes in Manufacturing)

► Show Figures

Figure 1

21 pages, 36550 KiB

Open AccessArticle

Drilling Force Characterization during Inconel 718 Drilling: A Comparative Study between Numerical and Analytical Approaches

by Salman Pervaiz and Wael A. Samad

Materials 2021, 14(17), 4820; https://doi.org/10.3390/ma14174820 - 25 Aug 2021

Cited by 4 | Viewed by 2015

Abstract

In drilling operations, cutting forces are one of the major machinability indicators that contribute significantly towards the deviations in workpiece form and surface tolerances. The ability to predict and model forces in such operations is also essential as the cutting forces play a [...] Read more.

In drilling operations, cutting forces are one of the major machinability indicators that contribute significantly towards the deviations in workpiece form and surface tolerances. The ability to predict and model forces in such operations is also essential as the cutting forces play a key role in the induced vibrations and wear on the cutting tool. More specifically, Inconel 718—a nickel-based super alloy that is primarily used in the construction of jet engine turbines, nuclear reactors, submarines and steam power plants—is the workpiece material used in the work presented here. In this study, both mechanistic and finite element models were developed. The finite element model uses the power law that has the ability to incorporate strain hardening, strain rate sensitivity as well as thermal softening phenomena in the workpiece materials. The model was validated by comparing it against an analytical mechanistic model that considers the three drilling stages associated with the drilling operation on a workpiece containing a pilot hole. Both analytical and FE models were compared and the results were found to be in good agreement at different cutting speeds and feed rates. Comparing the average forces of stage II and stage III of the two approaches revealed a discrepancy of 11% and 7% at most. This study can be utilized in various virtual drilling scenarios to investigate the influence of different process and geometric parameters. Full article

(This article belongs to the Special Issue Numerical Modeling for Simulation of Different Processes in Manufacturing)

► Show Figures

Figure 1

16 pages, 10783 KiB

Open AccessArticle

A Geometry-Based Welding Distortion Prediction Tool

by Ignacio Granell, Abel Ramos and Alberto Carnicero

Materials 2021, 14(17), 4789; https://doi.org/10.3390/ma14174789 - 24 Aug 2021

Cited by 4 | Viewed by 3147

Abstract

The prediction of welding distortion requires expertise in computer simulation programs, a clear definition of the nonlinear material properties, and mesh settings together with the nonlinear solution settings of a coupled thermal–structural analysis. The purpose of this paper is to present the validation [...] Read more.

The prediction of welding distortion requires expertise in computer simulation programs, a clear definition of the nonlinear material properties, and mesh settings together with the nonlinear solution settings of a coupled thermal–structural analysis. The purpose of this paper is to present the validation of an automatic simulation tool implemented in Ansys using Python scripting. This tool allows users to automate the preparation of the simulation model with a reduced number of inputs. The goal was, based on some assumptions, to provide an automated simulation setup that enables users to predict accurate distortion during the welding manufacturing process. Any geometry prepared in a CAD software can be used as the input, which gave us much geometrical flexibility in the shapes and sizes to be modeled. A thermomechanical loosely coupled analysis approach together with element birth and death technology was used to predict the distortions. The automation of the setup enables both simulation and manufacturing engineers to perform welding-induced distortion prediction. The results showed that the method proposed predicts distortion with 80–98% accuracy. Full article

(This article belongs to the Special Issue Numerical Modeling for Simulation of Different Processes in Manufacturing)

► Show Figures

Figure 1

20 pages, 7884 KiB

Open AccessArticle

Optimal Design of Steel–Concrete Composite Beams Strengthened under Load

by Piotr Szewczyk and Maciej Szumigała

Materials 2021, 14(16), 4715; https://doi.org/10.3390/ma14164715 - 20 Aug 2021

Cited by 9 | Viewed by 2318

Abstract

This paper presents results of numerical analysis and experimental research on strengthening of steel–concrete composite beams. Studied members consisted of IPE200 I-beam and 90 × 700 mm reinforced concrete slab. The steel part of the section was strengthened by welding additional steel plates [...] Read more.

This paper presents results of numerical analysis and experimental research on strengthening of steel–concrete composite beams. Studied members consisted of IPE200 I-beam and 90 × 700 mm reinforced concrete slab. The steel part of the section was strengthened by welding additional steel plates at the bottom. The study was performed for plate thickness ranging between 6 to 22 mm. Spatial FEM models were developed to account for material and geometric nonlinearities and for stress and post-welding strain. Proposed numerical models were experimentally validated. One aim was to find an optimum solution which would minimize cost and maximize bending capacity. To achieve this, energy parameters available in numerical simulations were reviewed and analyzed. Recoverable strain energy value determined in Abaqus was used to find the optimum solution. Full article

(This article belongs to the Special Issue Numerical Modeling for Simulation of Different Processes in Manufacturing)

► Show Figures

Figure 1

22 pages, 24187 KiB

Open AccessArticle

Combining Structural Optimization and Process Assurance in Implicit Modelling for Casting Parts

by Tobias Rosnitschek, Maximilian Erber, Christoph Hartmann, Wolfram Volk, Frank Rieg and Stephan Tremmel

Materials 2021, 14(13), 3715; https://doi.org/10.3390/ma14133715 - 2 Jul 2021

Cited by 5 | Viewed by 2304

Abstract

The structural optimization of manufacturable casting parts is still a challenging and time-consuming task. Today, topology optimization is followed by a manual reconstruction of the design proposal and a process assurance simulation to endorse the design proposal. Consequently, this process is iteratively repeated [...] Read more.

The structural optimization of manufacturable casting parts is still a challenging and time-consuming task. Today, topology optimization is followed by a manual reconstruction of the design proposal and a process assurance simulation to endorse the design proposal. Consequently, this process is iteratively repeated until it reaches a satisfying compromise. This article shows a method to combine structural optimization and process assurance results to generate automatically structure- and process-optimized die casting parts using implicit geometry modeling. Therefore, evaluation criteria are developed to evaluate the current design proposal and qualitatively measure the improvement of manufacturability between two iterations. For testing the proposed method, we use a cantilever beam as an example of proof. The combined iterative method is compared to manual designed parts and a direct optimization approach and evaluated for mechanical performance and manufacturability. The combination of topology optimization (TO) and process assurance (PA) results is automated and shows a significant enhancement to the manual reconstruction of the design proposals. Further, the improvement of manufacturability is better or equivalent to previous work in the field while using less computational effort, which emphasizes the need for suitable metamodels to significantly reduce the effort for process assurance and enable much shorter iteration times. Full article

(This article belongs to the Special Issue Numerical Modeling for Simulation of Different Processes in Manufacturing)

► Show Figures

Figure 1

13 pages, 4288 KiB

Open AccessArticle

Dynamic Moduli of Polybutylene Terephthalate Glass Fiber Reinforced in High-Temperature Environments

by Carmelo Gómez, Jorge Mira, F.J. Carrión-Vilches and Francisco Cavas

Materials 2021, 14(3), 483; https://doi.org/10.3390/ma14030483 - 20 Jan 2021

Cited by 7 | Viewed by 2439

Abstract

The aim of this work was to show the evolution over time of the dynamic moduli in components made of Polybutylene Terephthalate reinforced with glass fiber when they are held to temperatures close to the glass transition temperature over time. For this purpose, [...] Read more.

The aim of this work was to show the evolution over time of the dynamic moduli in components made of Polybutylene Terephthalate reinforced with glass fiber when they are held to temperatures close to the glass transition temperature over time. For this purpose, PBT samples reinforced with short, glass fibers of Ultradur^® material with 0%, 20%, and 50% in weight content were tested. Dynamic moduli showed an increment with glass fiber content showing a nonlinear behavior with the temperature. The evolution of storage modulus was depicted by means of a modified law of mixtures with an effectiveness factor depending on temperature and fiber content, whereas the evolution over time was obtained with a time–temperature transformation generated with the TTS Data Analysis software of TA-instruments for a given temperature. Storage modulus showed a linear relationship with glass fiber content when components were held to temperatures near to their respective glass transition temperature, obtained from the maximum of loss modulus curve with temperature. In summary, the value and evolution of dynamic moduli of PBT samples improved with glass fiber content, allowing us to increase the durability of components when they are submitted to high-temperature environments. Full article

(This article belongs to the Special Issue Numerical Modeling for Simulation of Different Processes in Manufacturing)

► Show Figures

Figure 1

19 pages, 6641 KiB

Open AccessArticle

Fluidized Bed Jet Milling Process Optimized for Mass and Particle Size with a Fuzzy Logic Approach

by Jaroslaw Krzywanski, Dariusz Urbaniak, Henryk Otwinowski, Tomasz Wylecial and Marcin Sosnowski

Materials 2020, 13(15), 3303; https://doi.org/10.3390/ma13153303 - 24 Jul 2020

Cited by 21 | Viewed by 3149

Abstract

The milling process is a complex phenomenon dependent on various technological and material parameters. The development of a fluidized bed jet milling model is of high practical significance, since milling is utilized in many industries, and its complexity is still not sufficiently recognized. [...] Read more.

The milling process is a complex phenomenon dependent on various technological and material parameters. The development of a fluidized bed jet milling model is of high practical significance, since milling is utilized in many industries, and its complexity is still not sufficiently recognized. Therefore, this research aims to optimize fluidized bed jet milling with the use of fuzzy logic (FL) based approach as one of the primary artificial intelligence (AI) methods. The developed fuzzy logic model (FLMill) of the investigated process allows it to be described as a non-iterative procedure, over a wide range of operating conditions. Working air pressure, rotational speed of the classifier rotor, and time of conducting the test are considered as inputs, while mass and mean Sauter diameter of the product are defined as outputs. Several triangular and constant linguistic terms are used in the developed FLMill model, which was validated against the experimental data. The optimum working air pressure and the test’s conducting time are 500 kPa and 3000 s, respectively. The optimum rotational speed of the classifier is equal to 50 s⁻¹, considering the mass of the grinding product, and 250 s⁻¹ for the mean Sauter diameter of the product. Such operating parameters allow obtaining 243.3 g of grinding product with the mean Sauter diameter of 11 µm. The research proved that the use of fuzzy logic modeling as a computer-based technique of solving mechanical engineering problems allows effective optimization of the fluidized bed jet milling process. Full article

(This article belongs to the Special Issue Numerical Modeling for Simulation of Different Processes in Manufacturing)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Numerical Modeling for Simulation of Different Processes in Manufacturing

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Published Papers (10 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI