bluuebunny/crossref_metadata_2025_split huggingface dataset:
An OpenMP Based Parallel Solver for MLPG Analysis of Heat Conduction
Authors: Singh Abhishek Kumar , Singh Krishna Mohan 
Published: February 2023

Abstract
In the present work, we focus our attention on the development of an in-house parallel MLPG code for the analysis of the heat conduction problem. The parallel code has been implemented using OpenMP API on the shared memory multicore CPU architecture. A two-dimensional linear steady-state heat conduction problem is taken as a model test problem. Numerical simulations have been performed to find the critical regions of the serial code, and an OpenMP based parallel MLPG code is developed, considering the critical regions of the sequential code. Based on performance parameters such as speed-up and parallel efficiency, the credibility of the parallelization procedure has been established. This work attempts to develop a robust and fast parallel MLPG solver.
Nonlinear Transient Response of Isotropic and Composite Structures With Variable Kinematic Beam and Plate Finite Elements
Authors: Azzara Rodolfo , Filippi Matteo , Pagani Alfonso , Carrera Erasmo 
Published: February 2023

Abstract
The present research deals with the evaluation of nonlinear transient responses of several isotropic and composite structures with variable kinematic one-dimensional (1D) beam and two-dimensional (2D) plate finite elements with different initial deflection configurations. The aim of current investigations is to show the effect of large amplitudes and the need to adopt an accurate model to capture the correct solution. Particular attention is focused on detailed stress state distribution over time and in the thickness direction. The proposed nonlinear approach is formulated in the framework of the well-established Carrera Unified Formulation (CUF). The formalism enables one to consider the three-dimensional (3D) form of displacement-strain relations and constitutive law. In detail, different geometrical nonlinear strains from the full Green-Lagrange (GL) to the classical von Kármán (vK) models are automatically and opportunely obtained by adopting the CUF due to its intrinsic scalable nature. The Hilber-Hughes-Taylor (HHT)-α algorithm and the iterative Newton-Raphson method are employed to solve the geometrical nonlinear equations derived in a total Lagrangian domain. Both Lagrange (LE) and Taylor (TE) expansions are considered for developing the various kinematic models. The solutions are compared with results found in available literature or obtained using the commercial code Abaqus. The results demonstrated the validity of the proposed formulation and the need to adopt a full Green-Lagrange model in order to describe the highly nonlinear dynamic response and an Layerwise (LW) approach to accurately evaluate the stress distribution.
Influences of Groove Geometry of Friction Disk on the Flow in an Engaged Wet Dual Clutch
Authors: Wu Xiqian , Zhang Xiaofang , Ding Weiyun , Ruan Deng-Fang , Hou Yuanjing 
Published: February 2023

Abstract
Based on FLUENT software, the flow field of cooling oil between a friction pair in an engaged wet dual clutch is simulated and the influence of groove structural parameters on the flow filed characteristics of cooling oil is studied. The results show that the structural parameters of radial groove have a great influence on the cooling oil flow field between a friction pair. When the inclination direction of groove is opposite to the rotation direction of friction pair, the groove inclination angle has a great influence on oil flow field between fiction pair, and the influence is relatively small when the groove inclination angle is consistent with the rotation direction of friction pair. In addition, the velocity distribution trend in the inclined radial groove is the same as that of the inclination angle = 0, but the velocity magnitude is larger and the highest velocity appears near the opposite side of the groove to the inclined direction of the grooves either for clockwise or counter-clockwise rotation of the friction pair. On the other hand, when the cross sectional area of the groove is kept constant, the average velocity in the central circumferential section of the groove is decreased rapidly with the increase of the groove aspect ratio (width to depth ratio) until the aspect ratio is equal to 5, and then slowly.
Assembly Automation Using an Industrial Robot
Authors: Dragun Timofey , Mascaro Seth , Blanchard Jonathan , Chauhan Vedang 
Published: February 2023

Abstract
Industrial automation is a prominent process that has been around for many years and is continuing to evolve. An important aspect of automation is industrial robots. This paper focuses on an automated circuit board assembly process. Components of the assembly are described and identified, as well as a completed assembly is shown with 3D printed components. Important camera setup steps are documented and discussed in addition to the iRVision Geometric Pattern Matching (GPM) tool which is used to teach the camera how to find parts. The process was first developed using ROBOGUIDE simulation software, once validated the program was implemented on a physical FANUC LR Mate 200iD/4s robot. Trial runs were completed with both the physical robot and the ROBOGUIDE simulation, with the data being analyzed to determine the system performance. Comparing the physical robot to the ROBOGUIDE simulation has revealed that the physical robot can perform as well as the simulation in terms of part detection, but suffers when it comes to speed. Simulation in the virtual software is a quick and easy way to visualize and analyze the robotic work cell before investing money into implementing it in the real world.
Performance Evaluation of Conveyor-Less Matrix Assembly System Using Simulation and Mathematical Models
Authors: Kim Min-Soo , Oh Seog-Chan , Chang Eun Hyo , Wells James W. , Arinez Jorge , Jang Young Jae 
Published: February 2023

Abstract
The increasing demand for electric vehicles and the emergence of autonomous transport technologies within production like autonomous mobile robot or self-driving rolling chassis have raised the possibility of developing conveyor-less matrix assembly system. The conveyor-less matrix assembly system is characterized by high adaptability to demand changes with low-cost investments and asynchronous operations allowing high routing and process flexibilities where the sequence of assembly operations is only limited by the product-specific precedence orders. With high flexibility potentials, however, the system needs to face high complexity issues in modeling and control. The high complexity may reduce the system performance and thus, the performance evaluation is a key component in modeling and control of conveyor-less matrix systems. To study the evaluation methods for the conveyor-less matrix assembly, this paper introduces two models, a mixed-integer linear programming model as exact method and a simulation model as heuristic method, and then illustrates how two models are different but can work collaboratively in a hypothetical example drawn from automotive assembly trim area. Finally, this paper intends to provide insights on the business value calculation of conveyor-less matrix assembly system, for practitioners who are interested in building conveyor-less matrix assembly system in the future.
Experimental Investigation on Severe Plastic Deformation of AA7075 Alloy at Elevated Temperature
Authors: Kolla Lakshman Rao , Gupta Amit Kumar , Mathur Devanshi , Bhardwaj Akhil 
Published: February 2023

Abstract
Lightweight alloys play a significant role in different manufacturing applications in the aerospace, automobile, and medical industries. Among other light alloys, 7075 aluminum alloy (AA7075) is widely utilized due to its excellent mechanical strength, low weight to strength ratio, and good corrosion resistance. One of the prominent ways to improve the alloy’s properties is grain refinement, which is easily accomplished by severe plastic deformation (SPD) techniques. Among different SPD techniques, constrained groove pressing (CGP) is one of the prominent SPD techniques, particularly for the sheet/plate material. In this work, AA7075 alloy was subjected to the CGP process at 300°C with various heat treatments. The repetitive shear. Grain refinement of CGPed samples was observed through an optical microscope to measure the average grain size of the specimen. SEM and XRD were used to investigate the precipitation and crystallography of the processed alloy. Results indicate that the heat treatment significantly affects grain growth as precipitates are segregated along grain boundaries.
Physical and Virtual Robotic Cells in Industry 4.0 Towards Industry 5.0: An XR-Based Conceptual Framework
Authors: Kuts Vladimir , Singh Maulshree , Alsamhi Saeed Hamood , Devine Declan , Murray Niall 
Published: February 2023

Abstract
The Digital Twin (DT) in the manufacturing domain is already the everyday tool for visualizing the various industrial systems, equipment, and produced products. When designing a new manufacturing unit or enlarging an existing factory, it is important to do so without affecting the manufacturing process flow itself. There are opportunities through simulation and digital manufacturing to plan and optimize this design process. Within usage of the actual physical machinery data gathered from the Industrial Internet of Things (IIoT) sensors and feeding to the DT, optimizing the layout can be done more precisely and effectively. However, there is no way to test the potential equipment simultaneously with the physical one in real-time. This paper aims to propose a Mixed Reality (MR) based system framework and toolkit, which will enable physical industrial robots to interact with virtual equipment and other virtual robots. This way, via Virtual Reality (VR), it will be possible to design a system layout. Furthermore, via the Augmented Reality (AR) view, it will be possible to simulate the interaction between multiple robots by enhancing the possibilities of the physical environment and using the new precise scale real-time design method.
Multi-Objective Optimization of Composite Square Tube for Minimizing Peak Crushing Force and Maximizing Specific Energy Absorption Using Artificial Neural Network and Genetic Algorithm
Authors: Zende Pradnya , Dalir Hamid 
Published: February 2023

Abstract
Optimization of composite materials is essential considering their high costs and complex manufacturing processes. This paper includes optimization of composite material square tube for crashworthiness requirements using Artificial Neural Networks and Genetic Algorithms. Objectives of optimization were peak crushing force and maximizing specific energy absorbed by the composite square tube. Training data for the artificial neural network was obtained by crash analysis of a square tube against a rigid wall for various samples using LS Dyna. Latin Hypercube sampling technique was used to generate the required sampling plan. Neural Network Training was performed to obtain the highest regression value and minimum mean square error. The trained network was further combined with Multi-Objective Genetic Algorithms (MOGA) to find optimized values of the variables to fulfill the crashworthiness requirements. The fitness function used in MOGA was obtained by ANN with a 5% allowable error in the objective values. Optimized solutions obtained were presented by the Pareto frontier curve. The methodology was developed for square tubes with four and eight plies.
Asset Management in the Mining Sector Based on Reliable and Sustainable Supplier Selection: A South African Case Scenario
Authors: Gidiagba Joachim , Okwu Modestus , Tartibu Lagouge 
Published: February 2023

Abstract
Asset management is fast becoming the backbone of modern production as it enables production facilities to operate at a high level of availability, reliability, and operability. One of the major challenges facing the mining sector is the identification of reliable and sustainable suppliers necessary for a matured asset management program (MAMP). This study contributes to that direction. The classical techniques have been used for the selection of sustainable suppliers for optimal operations of mines. However, a survey was conducted among executives and mine operators in the South African mining industry, the results obtained clearly illustrate that the industry employs economic, environmental, and social criteria in the selection of reliable and sustainable suppliers for asset management necessary for the optimal operation of the mining industry. This study further revealed that for the mining industry to operate at an optimal level, it requires a global MAMP, comprising of systems, people, equipment, spare parts, and services. A computerized maintenance management system (CMMS) facilitates the planning, scheduling, workflow, material flow, information flow, purchasing, and inventory management of mining operations. The effectiveness of the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) and Best Worst Method (BWM) was demonstrated in this study to address the challenges encountered by decision-makers in selecting a reliable and sustainable CMMS within the mining space. In conclusion, selecting a reliable and sustainable supplier that satisfies the key performance indicators of the organization is crucial in attaining optimum operational performance and meeting the business needs of the organization.
Effective Behavior of Peridynamic Random Structure Composites Subjected to Body Force With Compact Support
Authors: Buryachenko Valeriy A. 
Published: February 2023

Abstract
We consider a static problem for statistically homogeneous matrix linear bond-based peridynamic composite materials (CMs). Even for locally elastic composites subjected to inhomogeneous loading, the effective deformations are described by a nonlocal (either the differential or integral) operator relating a statistical average of stresses in the point being considered with a statistical average of strains in the vicinity of this point. The basic hypotheses of locally elastic micromechanics are generalized to their peridynamic counterparts (see for details [1]). The method is based on estimation of a perturbator introduced by one inclusion that is, in fact, the solutions of the basic problem for one inclusion inside the infinite peristatic matrix subjected to the body force. The statistical averages of both the displacements and stresses are estimated by summation of these perturbators for all possible locations of inclusions (in so doing, renormalizing procedure is not required). It allows us to estimate not only the effective nonlocal constitutive equation but also to evaluate the statistical field averages (inhomogeneous and nonlocal) inside the phases at the fine scale that is critically important for advanced modelling (e.g. for any nonlinear phenomena). In particular, in the generalized effective field method (EFM) proposed, the effective field is evaluated from self-consistent estimations by the use of closing of a corresponding integral equation in the framework of the quasi-crystalline approximation. In so doing, the classical effective field hypothesis is relaxed, and the hypothesis of the ellipsoidal symmetry of the random structure of CMs is not used. Numerical results for the estimation of effective displacements are obtained for 1D statistically homogeneous CM bar with the prescribed self equilibrated body forces.
An Artificial Neural Network for Parametric Analysis of Metallic Additive Manufacturing Using Discrete Element Method
Authors: Wu Yuxuan , Namilae Sirish 
Published: February 2023

Abstract
Powder bed fusion (PBF) is a widely used metal additive manufacturing method. There is strong evidence that the performance of the final part built using PBF depends on the dispersive quality of the particle bed. Understanding this process through computational modeling and machine learning is an efficient low-cost way for process design. Discrete element method (DEM) is an effective tool for analyzing the particle flow behavior. However, one challenge for parametric modeling of highly multivariate powder spreading process through DEM is the high computational cost, for traversing the large parameter space. We address this problem through innovative use of parallel computing using GNU parallel, and by developing a machine learning algorithm to correlate the process parameters and spread quality. We first perform DEM simulations systematically varying four parameters, the particle size, the coefficient of friction, the spread layer thickness, and the recoating velocity. The dataset containing inputs with spread parameters and target variables that measure the spread quality are fed to a finely-tuned artificial neural network (ANN). We observe that the neural network presents at least 95% accuracy in predicting the test data. Ultimately this approach provides the parameter combinations that produce high quality compaction before sintering.
Modeling the Interplay Between Process Parameters and Part Attributes in Additive Manufacturing Process With Artificial Neural Network
Authors: Deb Jayanta , Ahsan Nazmul , Majumder Sharmin 
Published: February 2023

Abstract
In this study, we model the interplay between the process parameters and the part attributes with artificial neural networks (ANN) to predict the effect of a set of process parameters on the part attributes in extrusion-based AM process. Five process parameters including build orientation, print speed, extrusion temperature, deposition direction, and layer thickness with three levels are used in this study to fabricate parts following an orthogonal array experimental design. Three attributes including dimensional accuracy, surface roughness, and tensile strength of the fabricated parts are measured and used to train, validate, and test the proposed multilayer artificial neural network models. Four different ANN models are proposed where three of them are for the three individual part attributes and the fourth model is for the combination of all three attributes. The results indicate that the individual part attribute ANN models outperform the model for the combination of three attributes in terms of the RMSE and correlation coefficient. Comparison among the individual part attributes with respect to the process parameters is performed to analyze which parameters have a greater effect on the individual part attributes. The trained ANN models can be utilized to predict and optimize the part attributes in extrusion-based AM processes.
Mitigation of Thrust Deterioration at a High Flapping Frequency of a 2D Airfoil in Forwarding Flight Conditions Using Asymmetric Flapping Strokes
Authors: Sinha Jit , Roy Sohan , Manohar Dash Sunil 
Published: February 2023

Abstract
In this article, the detrimental time-averaged thrust performance of a two-dimensional elliptic symmetrical flapping airfoil at very high flapping frequencies is addressed, and an attempt is made to enhance the thrust performance by implementing two separate flapping frequencies during the downstroke and upstroke of a flapping cycle thus making it asymmetric. Three different pivot locations, three effective angle of attack amplitudes, and a specific range of St are considered for our investigation, keeping the Reynolds number fixed as 5000. In general, the downstroke flapping frequency is always selected with a value higher than the critical Strouhal number, but the upstroke flapping frequency is kept fixed as the critical Strouhal number. It is worth highlighting that the observations are periodic and swapped suitably when the flapping stroke frequency selection is reversed in the flapping cycle. Asymmetric flapping stroke configurations yield more time-averaged thrust and non-zero lift than symmetric flapping stroke at thrust degrading flapping frequency range. Interestingly, the leading edge side pivot point produces positive lift when the implementation of a faster downstroke and slower upstroke configuration. At the same time, it’s the opposite for the center and trailing edge pivot points. To understand these enhanced aerodynamic performances at high flapping frequencies, we have further analyzed the transient thrust and lift force profiles and their associated flow structures for all the pivot locations.
Dynamics of a Viscous Drag Pump for Maxwell Immiscible Fluids Under Interfacial Electroosmotic and Hydrophobic Effects in a Microannulus
Authors: Escandón Juan P. , Valencia Cesar A. , Torres David A. , Hernández Clara G. 
Published: February 2023

Abstract
The present study analyzes the flow dynamics of two immiscible viscoelastic fluids through a cylindrical microannulus with hydrophobic walls. The pumping technique is produced by electroosmotic effects that act on the conducting fluid dragging the non-conducting fluid by viscous forces. The dimensionless mathematical model considers the linearized Poisson Boltzmann equation, the Cauchy momentum equation, and the rheological Maxwell model, which is solved semi-analytically by the Laplace transform method. The results of the transient flow field are presented in terms of velocity profiles, velocity tracking, and flow rate. Due to the elastic properties of fluids, oscillatory behavior of the flow is produced, whose frequency, amplitude, and duration depend on the relaxation times of fluids. Also, other dimensionless parameters are investigated, such as the electrokinetic parameter of the conducting fluid, the viscosity ratios in both fluids, as well as the hydrodynamic slip length in the walls, and the liquid-liquid interface position, showing its influence on the velocity magnitude, flow rate, and time in which the flow reaches the steady-state regime. The present investigation extends the knowledge about the transport methods of non-Newtonian and non-conducting fluids in microfluidic devices.