Computer Aided Engineering Applications Research Articles

Parameter Optimization with Multi-criteria Decision-Making Methods in Rail Transport: A Case Study of Freight Wagon Bogie

The high safety factor expected from transport vehicles results in high costs. Moreover, the environmental and financial concerns in transport vehicle technology make the minimization of production factors obligatory. This causes a decision problem between high safety and production at low cost. In this study, modeling and analysis with multi-criteria decision-making methods for freight wagon bogie operating with high safety and minimum cost were aimed. The decision problem was created considering the factors of safety, manufacturability and cost for three different materials, and the most appropriate material combination was determined for the bogie construction. In data production for the decision factors, the application of computer-aided engineering and chemical content of the materials were taken into consideration. The real tonnage prices of the related material were used for the cost criterion. TOPSIS, VIKOR and SAW, which are among the multi-criteria decision-making methods, were used for the solution of the decision problem. Fishbone, Cronbach’s alpha and regression methods were used for quality and reliability analysis. It was found that the solutions obtained from the chosen models validate each other. Together with the concept of economy and computer-aided engineering applications, its successful applicability to decision problems developed for freight wagons and providing a solution to them is the originality of this paper. According to the methods, the ideal solution was found as the material S355 for the pivot, S235 for the carrier and the bolster. According to reliability analysis, the data produced were found statistically sufficient and significant (Adj. R-Sq’s obtained above 95%).

Interoperability of CAD models and SysML specifications for the automated checking of design requirements

Currently and in view of technological development, mechatronic systems have become more and more complex. This will undoubtedly influenc the design of products. For this reason, designers do not stop developing new solutions to best ensure customer satisfaction on functional dimensional and geometrical requirements. However, to achieve a finished product satisfying all stakeholders, designers should face a multitud of problems. Among them, the difficulty of data exchange between the different developers contributing to the design process of a finishe product. Several research works have focused on data exchange between Computer Aided Design (CAD) and Computer Aided Engineering applications (CAE) or at the CAD development and manufacturing levels. However, few works study the interoperability between all the produc development levels and the system engineering one. For instance, the lack of continuity between the system-engineering model which has global view on the product, and the CAD model which integrates the parts and assembly CAD data, causes an enormous lost time in th verification and validation process of requirements. In this paper a methodology allowing the interoperability between the system leve specifications and the CAD model of a product being designed is proposed. Based on SysML diagrams, the customer needs and the functiona analysis of the product lead to the definition of the initial structure of the product assembly. The results of this step are used as an input by th CAD designer to detail the architecture of the mechanical assembly. Finally, the product assembly data required for verification and validatio are extracted from the CAD model and then used back to enrich the preliminary SysML model. The system engineer uses the collected data i the SysML model to check and validate the product requirements according to a V model. A pedal of a bicycle was used as an example to illustrat and prove the effectiveness and efficiency of the proposed approach.

Embedding data analytics and CFD into the digital twin concept

Computer-Aided Engineering (CAE) has supported the industry in its transition from trial-and-error towards physics-based modelling, but our ways of treating and exploiting the simulation results have changed little during this period. Indeed, the business model of CAE centers almost exclusively around delivering base-case simulation results with a few additional operational conditions. In this contribution, we introduce a new paradigm for the exploitation of computational physics data, consisting in using machine learning to enlarge the simulation databases in order to cover a wider spectrum of operational conditions and provide quick response directly on field. The resulting product from this hybrid physics-informed and data-driven modelling is referred to as Simulation Digital Twin (SDT). While the paradigm can be equally used in different CAE applications, in this paper we address its implementation in the context of Computational Fluid Dynamics (CFD). We show that the generation of Simulation Digital Twins can be efficiently accomplished with the combination of the CFD tool TransAT and the data analytics platform eDAP.

Interoperability of CAD geometry and product manufacturing information for computer integrated manufacturing

ABSTRACT Model-Based 3D engineering has gained wide popularity in recent times for various Computer-Aided Engineering applications, bypassing the need for 2D drawings, thereby creating an efficient digital thread, reducing development time and improving the product quality. With the use of model-based definition, most data required to design, analyze and manufacture aproduct is stored in digital format. The primary focus of the paper is to create aseamless digital thread for exchanging data from anative CAD file to astandard data format like ISO STEP AP242 and vice versa, which enables smart manufacturing by attaching product manufacturing information. Prior to STEP AP242, the only successful translation among CAD systems was for the boundary representation with very little or no manufacturing data. These standards will not be enough unless defined in amachine-readable format and are equipped with tools that can read/write from these data structures. The method presented enhances the neutral data format ‘Constraint Tolerance Feature (CTF) Graph’ to ‘Augmented Constraint Tolerance (aCTF) Graph’, which holds additional information required for manufacturing. This paper discusses the elements needed during CAD data exchange, for multiple CAE applications like Computer-Aided Tolerance Analysis, Computer-Aided Manufacturing, etc., and discusses the implementation of required translators.

A Graph-based Approach to Manage CAE Data in a Data Lake

Computer-aided engineering (CAE) applications generate vast quantities of heterogeneous data. Domain experts often fail to explore and analyze these data, because they are not integrated across different applications. Existing data management solutions are rather tailored to scientific applications. In our approach, we tackle this issue by combining a data lake solution with graph-based metadata management. This provides a holistic view of all CAE data and of the data-generating applications in one interconnected structure. Based on a prototypical implementation, we discuss how this eases the task of domain experts to explore and extract data for further analyses.

Adapted Delaunay triangulation method for free-form surface generation from random point clouds for stochastic optimization applications

Free-form surfaces are defined with NURBS (non-uniform rational basis spline) for most computer-aided engineering (CAE) applications. The NURBS method requires the definition of parameters such as weights, knot vectors and degree of the curves which make the configuration of the surface computationally expensive and complex. When the control points are randomly spaced in the point cloud and the topology of the desired surface is unknown, surface configuration with NURBS method becomes a challenging task. Optimization attempts for such surfaces create enormous amounts of computing data when coupled with physics solvers such as finite element analysis (FEA) tools and computational fluid dynamics (CFD) tools. In this paper, an adapted Delaunay triangulation (ADT) method for surface generation from the random points cloud is proposed and compared with widely used implicit functions based NURBS fitting method. The surface generated from ADT method can be simultaneously used with stochastic optimization algorithms (SOA) and CFD applications to search for the optimal results with minimum computational costs. It was observed while comparing ADT with NURBS-based geometry configuration that the computation time can be reduced by 3 folds. The corresponding deviation between both geometry configuration methods has been observed as low as 5% for all optimisation scenarios during the comparison. In addition, ADT method can provide light weight CFD approach as any instance of design iteration has at least half storage footprint as compared to corresponding NURBS surface. The proposed approach provides novel methodology towards establishing light weight CFD geometry, absence of which currently isolates methodologies for optimization and CFD analysis.

Towards an integrated machine-learning framework for model evaluation and uncertainty quantification

We introduce a new paradigm for treating and exploiting simulation data, serving in parallel as an alternative workflow for model evaluation and uncertainty quantification. Instead of reporting simulations of base-case and specific variations scenarios, databases covering a wide spectrum of operational conditions are built by means of machine-learning using sophisticated mathematical algorithms. While the approach works for all sorts of computer-aided engineering applications, the present contribution addresses the CFD/CMFD sub-branch, with application to a widely used benchmark of convective flow boiling. In addition to comparing simulation and experimental results on a case-by-case basis, machine-learning is used to create their respective (CFD and experiment) data-driven models (DDM), which will in a later stage serve for assessing the predictive performance of the CFD models over a wider range of experimental conditions, hence providing a high-level classification of their range of applicability.

A priori evaluation of simulation models preparation processes using artificial intelligence techniques

Controlling the well-known triptych costs, quality and time during the different phases of the Product Development Process (PDP) is an everlasting challenge for the industry. Among the numerous issues that are to be addressed, the development of new methods and tools to adapt to the various needs the models used all along the PDP is certainly one of the most challenging and promising improvement area. This is particularly true for the adaptation of Computer-Aided Design (CAD) models to Computer-Aided Engineering (CAE) applications, and notably during the CAD models simplification steps. Today, even if methods and tools exist, such a preparation phase still requires a deep knowledge and a huge amount of time when considering Digital Mock-Up (DMU) composed of several hundreds of thousands of parts. Thus, being able to estimate a priori the impact of DMU adaptation scenarios on the simulation results would help identifying the best scenario right from the beginning. This paper addresses such a difficult problem and uses artificial intelligence (AI) techniques to learn and accurately predict behaviours from carefully selected examples. The main idea is to identify rules from these examples used as inputs of learning algorithms. Once those rules obtained, they can be used on a new case to a priori estimate the impact of a preparation process without having to perform it. To reach this objective, a method to build a representative database of examples has been developed, the right input (explanatory) and output (preparation process quality criteria) variables have been identified, then the learning model and its associated control parameters have been tuned. One challenge was to identify explanatory variables from geometrical key characteristics and data characterizing the preparation processes. A second challenge was to build a effective learning model despite a limited number of examples. The rules linking the output variables to the input ones are obtained using AI techniques such as well-known neural networks and decision trees. The proposed approach is illustrated and validated on industrial examples in the context of computational fluid dynamics simulations.

Using support vector machines for the computationally efficient identification of acceptable design parameters in computer-aided engineering applications

This paper addresses the problem of estimating continuous boundaries between acceptable and unacceptable engineering design parameters in complex engineering applications. In particular, a procedure is proposed to reduce the computational cost of finding and representing the boundary. The proposed methodology combines a low-discrepancy sequence (Sobol) and a support vector machine (SVM) in an active learning procedure able to efficiently and accurately estimate the boundary surface. The paper describes the approach and methodological choices resulting in the desired level of boundary surface refinement and the new algorithm is applied to both two highly-nonlinear test functions and a real-world train stability design problem. It is expected that the new method will provide designers with a tool for the evaluation of the acceptability of designs, particularly for engineering systems whose behaviour can only be determined through complex simulations.

Associative CAD references in the neutral parametric canonical form

ABSTRACTDue to the multiplicity of computer-aided engineering applications used in industry, interoperability between programs has become increasingly important. A 1999 study by the National Institute for Standards and Technology (NIST) estimated that inadequate interoperability between the original engineering manufacturers (OEM) and their suppliers cost the US automotive industry over $1 billion per year, with the majority spent fixing data after translations. The Neutral Parametric Canonical Form (NPCF) prototype standard developed by the BYU Site of the NSF Center for e-Design offers a solution to this problem by enabling real-time collaboration between heterogeneous systems while preserving design intent. The NPCF is implemented within a SQL database and defines the schema both for neutral features and for the parameters defining the inter-feature relationships and associations.

A kinetic model of viscosity development for in situ ring-opening anionic polymerization of ϵ-caprolactam

The in situ polymerization of ∈-caprolactam in a carbon fiber mat is a promising technology for the production of carbon fiber-reinforced polyamide 6 (CFRPA6) parts. There is a strong demand for a kinetic model of viscosity development of polyamide 6 (PA6) in computer-aided engineering applications. In this study, a viscosity model was developed by modifying the Castro-Macosko model to include simultaneous polymerization and crystallization effects. Differential scanning calorimetry (DSC) was used to measure a heat flow curve that involved the polymerization and crystallization kinetics from 50 to 250 °C at various heating rates. The peak separation of the measured heat flow curves was used to elucidate the individual polymerization and crystallization heat flow curves. The Kamal and generalized Avrami models were used to obtain kinetic parameters by fitting the heat flow curves of polymerization and crystallization, respectively. An isothermal rheological measurement was performed to measure the increase in viscosity caused by the polymerization and crystallization at a steady shear rate at reaction temperatures from 100 to 200 °C (at 10 °C intervals). A modified Castro-Macosko model was useful to fit the viscosity data at 110 and 140 °C to determine parameters using the monomer conversion estimation from the Kamal model and the degree of crystallization from the generalized Avrami model.

Multi-user collaborative tool path planning using process decomposition

Single-user computer-aided engineering applications force a strictly serial design process, which ultimately lengthens time to market. We created multi-user tool path planning software, which allow...

Extended precision data types for the development of the original computer aided engineering applications

Computer aided engineering is based on models of the phenomena which are expressed as algorithms. The implementations of the algorithms are usually software applications which are processing a large volume of numerical data, regardless the size of the input data. In this way, the finite element method applications used to have an input data generator which was creating the entire volume of geometrical data, starting from the initial geometrical information and the parameters stored in the input data file. Moreover, there were several data processing stages, such as: renumbering of the nodes meant to minimize the size of the band length of the system of equations to be solved, computation of the equivalent nodal forces, computation of the element stiffness matrix, assemblation of system of equations, solving the system of equations, computation of the secondary variables. The modern software application use pre-processing and post-processing programs to easily handle the information. Beside this example, CAE applications use various stages of complex computation, being very interesting the accuracy of the final results. Along time, the development of CAE applications was a constant concern of the authors and the accuracy of the results was a very important target. The paper presents the various computing techniques which were imagined and implemented in the resulting applications: finite element method programs, finite difference element method programs, applied general numerical methods applications, data generators, graphical applications, experimental data reduction programs. In this context, the use of the extended precision data types was one of the solutions, the limitations being imposed by the size of the memory which may be allocated. To avoid the memory-related problems the data was stored in files. To minimize the execution time, part of the file was accessed using the dynamic memory allocation facilities. One of the most important consequences of the paper is the design of a library which includes the optimized solutions previously tested, that may be used for the easily development of original CAE cross-platform applications. Last but not least, beside the generality of the data type solutions, there is targeted the development of a software library which may be used for the easily development of node-based CAE applications, each node having several known or unknown parameters, the system of equations being automatically generated and solved.

Approximation method to compute domain related integrals in structural studies

Various engineering calculi use integral calculus in theoretical models, i.e. analytical and numerical models. For usual problems, integrals have mathematical exact solutions. If the domain of integration is complicated, there may be used several methods to calculate the integral. The first idea is to divide the domain in smaller sub-domains for which there are direct calculus relations, i.e. in strength of materials the bending moment may be computed in some discrete points using the graphical integration of the shear force diagram, which usually has a simple shape. Another example is in mathematics, where the surface of a subgraph may be approximated by a set of rectangles or trapezoids used to calculate the definite integral. The goal of the work is to introduce our studies about the calculus of the integrals in the transverse section domains, computer aided solutions and a generalizing method. The aim of our research is to create general computer based methods to execute the calculi in structural studies. Thus, we define a Boolean algebra which operates with ‘simple’ shape domains. This algebraic standpoint uses addition and subtraction, conditioned by the sign of every ‘simple’ shape (-1 for the shapes to be subtracted). By ‘simple’ shape or ‘basic’ shape we define either shapes for which there are direct calculus relations, or domains for which their frontiers are approximated by known functions and the according calculus is carried out using an algorithm. The ‘basic’ shapes are linked to the calculus of the most significant stresses in the section, refined aspect which needs special attention. Starting from this idea, in the libraries of ‘basic’ shapes, there were included rectangles, ellipses and domains whose frontiers are approximated by spline functions. The domain triangularization methods suggested that another ‘basic’ shape to be considered is the triangle. The subsequent phase was to deduce the exact relations for the calculus of the integrals associated to the transverse section problems. Thus we use a virtual rectangle which is framing the triangle, being generated supplementary right angled triangles. The sign of rectangle and the signs of the supplementary triangles are conditioned by the sign of the initial triangle. In this way, a generally located triangle for which we have direct calculus relations may be used to generate the discretization of any domain in transverse section associated integrals. A significant consequence of the paper is the opportunity to create modern computer aided engineering applications for structural studies, which use: intelligent applied mathematics background, modern informatics technologies and advanced computing techniques, such as calculus parallelization.

A discrete geometry approach for tolerance analysis of mechanism

Tolerance analysis aims at predicting the effects of inevitable geometric deviations on the quality and function of mechanical products and is therefore an import tool in the design and dimensioning of mechanism. Since geometric deviations have various sources, different simulation tools and computer-aided engineering applications must be applied to determine them. Most of these tools are based on a surface or volume discretization, which leads to a workpiece representation in discrete geometry. In this contribution, an approach for the tolerance analysis of mechanism employing these discrete geometry representations is proposed. It is based on the processing of non-ideal workpiece representatives and helps to incorporate results from different validation applications. The approach is applied to the tolerance analysis of spur gears by employing a Tooth Contact Analysis algorithm.

Collaborative simulation and scientific big data analysis: Illustration for sustainability in natural hazards management and chemical process engineering

Classical approaches for remote visualization and collaboration used in Computer-Aided Design and Engineering (CAD/E) applications are no longer appropriate due to the increasing amount of data generated, especially using standard networks. We introduce a lightweight and computing platform for scientific simulation, collaboration in engineering, 3D visualization and big data management. This ICT based platform provides scientists an “easy-to-integrate” generic tool, thus enabling worldwide collaboration and remote processing for any kind of data. The service-oriented architecture is based on the cloud computing paradigm and relies on standard internet technologies to be efficient on a large panel of networks and clients. In this paper, we discuss the need of innovations in (i) pre and post processing visualization services, (ii) 3D large scientific data set scalable compression and transmission methods, (iii) collaborative virtual environments, and (iv) collaboration in multi-domains of CAD/E. We propose our open platform for collaborative simulation and scientific big data analysis. This platform is now available as an open project with all core components licensed under LGPL V2.1. We provide two examples of usage of the platform in CAD/E for sustainability engineering from one academic application and one industrial case study. Firstly, we consider chemical process engineering showing the development of a domain specific service. With the rise of global warming issues and with growing importance granted to sustainable development, chemical process engineering has turned to think more and more environmentally. Indeed, the chemical engineer has now taken into account not only the engineering and economic criteria of the process, but also its environmental and social performances. Secondly, an example of natural hazards management illustrates the efficiency of our approach for remote collaboration that involves big data exchange and analysis between distant locations. Finally we underline the platform benefits and we open our platform through next activities in innovation techniques and inventive design.

A Simulation and Fabrication Works on Optimization of High Pressure Aluminum Die Casting Part

High-pressure die casting o ers reduced costs due to its small tolerances and smooth surface nish. Casting parts produced are consumed by the automotive industry in millions. In this study, the use of computer aided engineering applications on design of high-pressure die-casting was studied. The in uence of casting process steps in die design was studied and analyzed. The casting simulation software was used to improve design and solve problems. By using the simulation software in analyses of die design, the nal design was reached in a few hours and thus the design process of pre-production was shortened and mold production was carried out with no revision on die material. Radiographic test was applied on the casting parts and the result shows good correlation between simulations of solidi cation result data. Also the results proved that the application of squeeze pressure in the intensi cation phase of high-pressure die casting process could be examined in the casting simulation.

1402 機械構造物を対象とした構想設計支援法の構築(OS16 モデルベースデザイン,ファーストオーダーアナリシス)

Computer Aided Engineering (CAE) has been successfully used in many mechanical industries such as automotive industries. However, most mechanical designers, in fact, cannot utilize CAE applications by themselves because of the sophisticated operations and a huge amount of time for the analysis. Recently, the concept of a new CAE, First Order Analysis (FOA), has been proposed in order to overcome these problems. This paper presents the method to support the conceptual designs using simplified model corresponding to the concept of FOA. First, thin-walled square hallow section T-joint model consideration of corner R on joint-section is introduced. Next, a procedure for determining the stiffness of joint-section is proposed, and the derived expression is presented. Finally, some examples are provided to confirm the method proposed here.

Architectural Limitations in Multi-User Computer-Aided Engineering Applications

The engineering design process evolves products by a collaborative synthesis of specifications, personnel and organizations. Unfortunately, collaborative effectiveness is thwarted by existing single-user computer-aided applications like computer-aided design, computer-aided analysis, and others. These applications and associated file management systems assign editing rights to one technical person, e.g., a designer, analyst, or a process planner. In the absence of collaborative computer-aided engineering applications, we conducted a survey to establish that product collaboration is limited to interactive, either formal or ad-hoc design sessions, social communication tools, serial model sharing, terminal/screen sharing, and to conference call interactions. Current computer-aided (CAx) tools do not permit simultaneous model changes by a collaborative team editing the same model. Although over a decade of prior research has demonstrated multi-user feasibility for computer-aided applications, the architectural breadth of this research has apparently not yet compelled developers and end-users to develop and adopt new multi-user computer-aided applications devoted to product development. Why have collaborative engineering CAx tools not been commercialized for mainstream use? This paper uses several multi-user prototypes, including the first Computer-Aided Engineering multi-user prototype called CUBIT Connect, to expose additional architectural hurdles to implementing new multi-user collaborative paradigms. These challenges relate to variable algorithmic performance times, multi-threading and event driven client notification processes, distributed access level security, and model change management in design sessions.

Self-Moving Tail Prototyping and Structural Improvements

virtual prototyping technology 1980s developed a computer-aided engineering and virtual prototyping technology applications in the research and development of self-moving tail can greatly enhance progress in the development of the mechanical design of fully mechanized coal miningthe surface level of mechanization upgrade of great significance.