1,372 research outputs found

    Design of hybrid components joining zone through sensitivity analysis

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    Multi-material structures are a trending topic for the industry. With a high application potential, such as lightweight or extended life cycle, different manufacturing technologies are further developed for this intent. One of these technologies is Tailored Forming, a process-chain capable of joining different metals and creating massive hybrid components. In parallel to this development, new challenges rise for design, which has the responsibility of finding an optimal use of this technology and produce higher-performance products. However, this task cannot be solved by conventional engineering approach, since strong manufacturing constraints are involved and a lack of understanding about the joining zone formed between the materials still exists. To fill this gap, the objective of this study is to analyse the influence of the joining zone design over the structure behaviour and establish a suitable design method. For that, a computer-aided environment was constructed and a parametric sensitivity analysis was executed, taking a hybrid shaft as example. At the end, the simulation's results allowed a multi-objective optimisation and were able to generate first design guidelines. © 2019 Design Society. All rights reserved

    Hybrid Bulk Metal Components

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    In recent years, the requirements for technical components have steadily been increasing. This development is intensified by the desire for products with a lower weight, smaller size, and extended functionality, but also with a higher resistance against specific stresses. Mono-material components, which are produced by established processes, feature limited properties according to their respective material characteristics. Thus, a significant increase in production quality and efficiency can only be reached by combining different materials in a hybrid metal component. In this way, components with tailored properties can be manufactured that meet the locally varying requirements. Through the local use of different materials within a component, for example, the weight or the use of expensive alloying elements can be reduced. The aim of this Special Issue is to cover the recent progress and new developments regarding all aspects of hybrid bulk metal components. This includes fundamental questions regarding the joining, forming, finishing, simulation, and testing of hybrid metal parts

    EG-ICE 2021 Workshop on Intelligent Computing in Engineering

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    The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

    Experimental Studies on Abrasive Water Jet Cutting of Nano SiC Particles Filled Hybrid Basalt-Glass Fibre-Reinforced Epoxy Composites

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    Abrasive water jet machining (AWJM) is extensively beneficial in machining materials that are hard to cut. This investigation deals with AWJM of Nano SiC filled Epoxy reinforced with basalt-glass fiber hybrid composite. The composite is prepared by compression moulding technique. Experimental trails are performed to evaluate the impact of every process parameter on the responses i.e., surface roughness (Ra) and Material Removal Rate (MRR). The experiments are conducted by changing the standoff distance (SD), traverse speed (TS) and water pressure. The performance of the conducted experiment is analysed using a Swarm intelligence algorithm. Surface roughness and MRR are maximized by using the combination of optimum process parameter levels of 9.72 mm/min speed, 5.78 mm stand-off distance and 553 MPa jet pressure. Scanning Electron Microscopic (SEM) images are employed in detecting the morphology of machined surface and confirmed the presence of voids and fibre pull-out

    EG-ICE 2021 Workshop on Intelligent Computing in Engineering

    Get PDF
    The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

    Storage Capacity Estimation of Commercial Scale Injection and Storage of CO2 in the Jacksonburg-Stringtown Oil Field, West Virginia

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    Geological capture, utilization and storage (CCUS) of carbon dioxide (CO2) in depleted oil and gas reservoirs is one method to reduce greenhouse gas emissions with enhanced oil recovery (EOR) and extending the life of the field. Therefore CCUS coupled with EOR is considered to be an economic approach to demonstration of commercial-scale injection and storage of anthropogenic CO2. Several critical issues should be taken into account prior to injecting large volumes of CO2, such as storage capacity, project duration and long-term containment. Reservoir characterization and 3D geological modeling are the best way to estimate the theoretical CO 2 storage capacity in mature oil fields. The Jacksonburg-Stringtown field, located in northwestern West Virginia, has produced over 22 million barrels of oil (MMBO) since 1895. The sandstone of the Late Devonian Gordon Stray is the primary reservoir.;The Upper Devonian fluvial sandstone reservoirs in Jacksonburg-Stringtown oil field, which has produced over 22 million barrels of oil since 1895, are an ideal candidate for CO2 sequestration coupled with EOR. Supercritical depth (\u3e2500 ft.), minimum miscible pressure (941 psi), favorable API gravity (46.5°) and good water flood response are indicators that facilitate CO 2-EOR operations. Moreover, Jacksonburg-Stringtown oil field is adjacent to a large concentration of CO2 sources located along the Ohio River that could potentially supply enough CO2 for sequestration and EOR without constructing new pipeline facilities.;Permeability evaluation is a critical parameter to understand the subsurface fluid flow and reservoir management for primary and enhanced hydrocarbon recovery and efficient carbon storage. In this study, a rapid, robust and cost-effective artificial neural network (ANN) model is constructed to predict permeability using the model\u27s strong ability to recognize the possible interrelationships between input and output variables. Two commonly available conventional well logs, gamma ray and bulk density, and three logs derived variables, the slope of GR, the slope of bulk density and Vsh were selected as input parameters and permeability was selected as desired output parameter to train and test an artificial neural network. The results indicate that the ANN model can be applied effectively in permeability prediction.;Porosity is another fundamental property that characterizes the storage capability of fluid and gas bearing formations in a reservoir. In this study, a support vector machine (SVM) with mixed kernels function (MKF) is utilized to construct the relationship between limited conventional well log suites and sparse core data. The input parameters for SVM model consist of core porosity values and the same log suite as ANN\u27s input parameters, and porosity is the desired output. Compared with results from the SVM model with a single kernel function, mixed kernel function based SVM model provide more accurate porosity prediction values.;Base on the well log analysis, four reservoir subunits within a marine-dominated estuarine depositional system are defined: barrier sand, central bay shale, tidal channels and fluvial channel subunits. A 3-D geological model, which is used to estimate theoretical CO2 sequestration capacity, is constructed with the integration of core data, wireline log data and geological background knowledge. Depending on the proposed 3-D geological model, the best regions for coupled CCUS-EOR are located in southern portions of the field, and the estimated CO2 theoretical storage capacity for Jacksonburg-Stringtown oil field vary between 24 to 383 million metric tons. The estimation results of CO2 sequestration and EOR potential indicate that the Jacksonburg-Stringtown oilfield has significant potential for CO2 storage and value-added EOR

    Numerical modelling of additive manufacturing process for stainless steel tension testing samples

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    Nowadays additive manufacturing (AM) technologies including 3D printing grow rapidly and they are expected to replace conventional subtractive manufacturing technologies to some extents. During a selective laser melting (SLM) process as one of popular AM technologies for metals, large amount of heats is required to melt metal powders, and this leads to distortions and/or shrinkages of additively manufactured parts. It is useful to predict the 3D printed parts to control unwanted distortions and shrinkages before their 3D printing. This study develops a two-phase numerical modelling and simulation process of AM process for 17-4PH stainless steel and it considers the importance of post-processing and the need for calibration to achieve a high-quality printing at the end. By using this proposed AM modelling and simulation process, optimal process parameters, material properties, and topology can be obtained to ensure a part 3D printed successfully

    On optimization of heterogeneous materials for enhanced resistance to bulk fracture

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    We propose a novel approach to optimize the design of heterogeneous materials, with the goal of enhancing their effective fracture toughness under mode-I loading. The method employs a Gaussian processes-based Bayesian optimization framework to determine the optimal shapes and locations of stiff elliptical inclusions within a periodic microstructure in two dimensions. To model crack propagation, the phase-field fracture method with an efficient interior-point monolithic solver and adaptive mesh refinement, is used. To account for the high sensitivity of fracture properties to initial crack location with respect to heterogeneities, we consider multiple cases of initial crack and optimize the material for the worst-case scenario. We also impose a minimum clearance constraint between the inclusions to ensure design feasibility. Numerical experiments demonstrate that the method significantly improves the fracture toughness of the material compared to the homogeneous case

    Optimisation de transducteurs piézoélectriques pour la génération d'ondes guidées

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    Résumé : Les systèmes de surveillance de santé structurale sont proposés pour la détection d’endommagement dans les infrastructures qui dépassent leur durée de vie en utilisant les ondes guidées (GW). Les ondes guidées peuvent parcourir de longues distances et sont sensibles à une variété d’imperfections. Les transducteurs piézoélectriques sont communément utilisés pour générer et mesurer les ondes guidées dans des structures minces. Comme la détection du défaut et sa localisation sont souhaitées, la nature de la génération des ondes guidées sous forme de plusieurs modes implique une complexité supérieure dans le traitement du signal. Pour remédier à cette limitation, une nouvelle méthode est présentée ici pour la génération des ondes guidées par sélection de mode, et un nouveau transducteur piézoélectrique est ensuite conçu, fabriqué et testé. Tout d'abord, la génération des ondes guidées par optimisation systématique du profil interfacial de la contrainte de cisaillement en mode sélectif est étudiée. En utilisant le principe de superposition, une méthode d'analyse est d'abord développée pour la modélisation de la génération des ondes guidées par un nombre fini de segments de contrainte de cisaillement uniforme, chacun contribuant à un profil élémentaire d’une contrainte constante de cisaillement. Sur cette base, deux fonctions coût sont définies afin de minimiser les modes indésirables et amplifier le mode sélectionné et le problème d'optimisation est résolu avec un cadre d'optimisation d’algorithme génétique parallèle. Les avantages de cette méthode par rapport à d'autres approches de conception de transducteurs classiques sont (1) la contrainte de cisaillement peut être explicitement optimisée à la fois pour exciter un mode et supprimer d'autres modes indésirables, (2) la taille de la zone d'excitation n’est pas limitée et l’excitation en mode sélectif est toujours possible, même si la largeur d'excitation est inférieure à toutes les longueurs d'onde excitées, et (3) la sélectivité est accrue et la largeur de bande est étendue. La méthode analytique et les fonctions coût sont ensuite développées pour concevoir un transducteur piézoélectrique à éléments multiples (MEPT) simple et performant. Une méthode numérique est tout d'abord mise au point pour extraire la contrainte interfaciale entre un seul élément piézocéramique et une structure d'accueil et ensuite utilisée comme entrée d'un modèle analytique pour prédire la propagation des ondes guidées à travers l'épaisseur d'une plaque isotrope. Deux nouvelles fonctions coût sont proposées pour optimiser la contrainte de cisaillement interfaciale pour supprimer le(s) mode(s) indésirable(s) et maximiser un mode désiré. Simplicité et faible coût de fabrication sont deux principales cibles visées dan la conception du MEPT. Un prototype TPEM est ensuite fabriqué à l'aide de micro-usinage laser. Une procédure expérimentale est présentée afin de valider les performances de la TPEM comme une nouvelle solution pour la génération des ondes guidées en mode sélectif. Des essais expérimentaux illustrent la forte capacité du TPEM pour la génération des ondes guidées en mode sélectif, puisque le mode indésirable est supprimé par un facteur allant jusqu'à 170 fois par rapport aux résultats obtenus avec un seul piézocéramique.Abstract : Structural Health Monitoring (SHM) systems are being proposed for damage detection of infrastructures that exceed their life using ultrasonic Guided waves (GWs). GWs can travel over long distances and are sensitive to variety of defects. Piezoelectric transducers (PZTs) are commonly used to generate and measure GWs in plate-like structures. As damage detection and localization is sought, the multi-mode nature of GW generation involves higher complexity in signal processing. To overcome this limitation, a new method is presented here for modeselective GW generation, and a novel mode-selective PZT is then designed, manufactured and tested. First, mode-selective generation of GWs by systematic optimization of the interfacial shear stress profile is investigated. Using the superposition principle, an analytical method is first developed for modeling GWs generation by a finite number of uniform shear stress segments, each contributing with a constant elementary shear stress profile. Based on this, two cost functions are defined in order to minimize the undesired modes and amplify the selected mode and the optimization problem is solved with a parallel Genetic Algorithm (GA) optimization framework. Advantages of this method over more conventional transducers tuning approaches are that (1) the shear stress can be explicitly optimized to both excite one mode and suppress other undesired modes, (2) the size of the excitation area is not constrained and mode-selective excitation is still possible even if excitation width is smaller than all excited wavelengths, and (3) the selectivity is increased and the bandwidth extended. The analytical method and objective functions are then developed to design a novel and costeffective multi-element piezoelectric transducer (MEPT). A numerical method is first developed to extract the interfacial stress between a single piezoceramic element and a host structure and then used as the input of an analytical model to predict the GW propagation through the thickness of an isotropic plate. Two novel objective functions are proposed to optimize the interfacial shear stress for both suppressing unwanted mode(s) and maximizing a desired mode. Simplicity and low manufacturing cost are two main targets driving the design of the MEPT. A prototype MEPT is then manufactured using laser micro-machining. An experimental procedure is presented to validate the performances of the MEPT as a new solution for mode-selective GW generation. Experimental tests illustrate the high capability of the MEPT for mode-selective GW generation, as unwanted mode is suppressed by a factor up to 170 times compared with the results obtained with a single piezoceramic
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