L19
CAE in the Design Process

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16:05
conference time (CEST, Berlin)
Evaluation of Automated Tools to Construct CAD Geometry from Discrete Mesh Data
28/10/2021 16:05 conference time (CEST, Berlin)
Room: L
R. Jennings (Honeywell Federal Manufacturing & Technologies, USA)
R. Jennings (Honeywell Federal Manufacturing & Technologies, USA)
The necessity of manually converting discrete geometry to computer-aided design (CAD) is one of the challenges preventing the adoption of generative design and additive manufacturing. The output data type of most topology optimization software programs is a triangular surface mesh tessellation, typically in the stereolithography (STL) file format. However, for various product lifecycle management (PLM) activities, a smooth boundary representation that can be modeled in traditional CAD software is often preferred or required. Manually creating a CAD model from this discrete triangular surface mesh data requires hours of tedious labor for each part and introduces uncertainty and error into the workflow. There are also other areas outside of topology optimization and additive manufacturing where this model workflow is a problem. One is as-built-to-analysis workflows such as sequential process modeling, where inter-process impacts (e.g. forging impacts on machined part warping) require a multi-step simulation process, often transitioning between different software programs. Another is reverse engineering, or creating a CAD geometry from inspection scan data. All of these are long-term necessities for implementation and adoption of a model based enterprise and digital twin, and their associated efficiency and efficacy gains. Industry has responded to this demand with the creation of various tools to improve the level of automation in reconstructing CAD geometry from discrete triangular surface mesh tessellation data. In this study, several benchmark tessellations were created, either via optimization, sequential process modeling, or inspection scanning. Multiple software tools were then used to reconstruct CAD geometry from the discrete data of the benchmark tessellations. Speed and difficulty of the process were assessed, along with comparing both the geometrical accuracy and functional performance differences between the original tessellated design and the reconstructed CAD geometry. The Department of Energy’s Kansas City National Security Campus is operated and managed by Honeywell Federal Manufacturing & Technologies, LLC under contract number DE-NA0002839.
Generative Design, Digital Twin, CAD-CAE Integration, Optimisation
16:25
conference time (CEST, Berlin)
Smart-engineering Tools Dedicated to Sports Product Design
28/10/2021 16:25 conference time (CEST, Berlin)
Room: L
L. Chec, P. Maury (DATADVANCE France SAS, FRA); A. Callens (Decathlon, FRA)
L. Chec, P. Maury (DATADVANCE France SAS, FRA); A. Callens (Decathlon, FRA)
Make product design easier, faster and smarter, that’s the ultimate goal of many companies. Moreover, companies involved in sports design and manufacturing require fast innovations to remain competitive in their business. In pursuit of this goal, Decathlon has developed a simple interface called “Technical Configurator”, accessible for the simulation engineers, non-expert in design optimization and predictive modeling, allowing its development team to be autonomous in optimizing their product easier and to accelerate overall time to market. Once developed and validated, each “Technical Configurator” is released and hosted in a “Design Application Store” to be used by the whole authorized engineering team. It is easily accessible worldwide through a simple web browser and absolutely user-friendly. While developing the “Technical Configurator”, Decathlon has explored the idea of server-based solution for predictions and optimization powered by approximation models. A true cloud collaborative platform developed by DATADVANCE was used as enabler. Inputs are provided by domain experts through a simple web page, and back-end server sends the request to the expert module of Design of Experiment, Optimization, Surrogate modelling and Simulation. As it has full interoperability with other engineering tools, the platform allows to combine in-house routines related to performance (mechanical and feeling), cost estimation, and environmental impact, to ultimately validate design alternatives with respect to multiple complex parameters, exposed as tunable variables.. All of it is possible thanks to use of external APIs (REST, GraphQL). The immediate benefit is to obtain an almost real time prediction of product performance taking into account a growing number of design parameters. By democratizing access and usage of its configurator, Decathlon enables capitalization of knowledge from all configurations analysed by all users. Opportunity is given to transparently collect results of all design alternatives and enrich a common database to improve the quality of predictive models and finally the knowhow on product design.
Optimization,Configurator,Decathlon,Datadvance,serverbased,surrogatemodelling,webapp
16:45
conference time (CEST, Berlin)
A Comparative Study of a Lubricating System of Reciprocating Compressors for Refrigerators Using Two Commercial CFD Codes
28/10/2021 16:45 conference time (CEST, Berlin)
Room: L
M. Tada (Embraco-Nidec, BRA)
M. Tada (Embraco-Nidec, BRA)
The main demands for the industry of commercial and household refrigeration appliances are: eco-friendly, lower power consumption, better performance, finer temperature control and lower noise levels. One example into this direction is the innovating variable speed reciprocating compressors – a component of the refrigeration system – gaining space in the market due to the benefits which they bring. The variable speed compressor differs from the conventional compressor in adjusting the rotational speed according to the refrigeration system’s demand. This is achieved by the presence of an electronic device – the frequency inverter – capable of measuring the temperature variations of the system and automatically adjusting the compressor speed, making the refrigeration more efficient. When a hermetic reciprocating compressor works at different speeds all its components need to be designed to operate under these conditions. One fundamental function of the compressor ‘s cranktrain is ensuring proper lubrication for the mechanical components for all speed range of the compressor. For this purpose, the cranktrain’s oil pump system must perform such function. In the last decade, techniques of physical and computational experiments have aided the robust design of the oil pumping system, optimizing the oil flow rate for into a wide range of crankshaft speeds. Through computational and physical experiments, this study aims to analyse the biphasic and immiscible fluid flow through a centrifugal oil pump system of reciprocating compressors by using two commercial software: a) Ansys CFX; and b) Ansys Fluent. The main physical response variables analysed were: a) the volumetric oil flow rate; b) the oil volume fractions; c) the oil velocity fields; and d) pressure fields. The main software variables analysed were: a) CPU time; b) convergence; c) accuracy of the solution. Both software’s solutions were compared with the physical experiment. A brief description and discussion of the numerical methods of each software was presented.
CFD, Refrigeration, Oil pump system, Multiphase flow, Hermetic reciprocating compressors
17:05
conference time (CEST, Berlin)
CFD Modeling in Design of 3D Printer Enclosures
28/10/2021 17:05 conference time (CEST, Berlin)
Room: L
T. May, K.Fouladi, B. Eslami (Widener University School of Engineering, USA)
T. May, K.Fouladi, B. Eslami (Widener University School of Engineering, USA)
Additive manufacturing, commonly known as 3D printing, is a time-efficient and cost-effective alternative to machining and milling in the manufacturing process. It offers promising capabilities to fabricate custom-designed parts for complex applications. Fused Deposition Modeling (FDM) is one of the most commonly used printing techniques for creating prototype pieces. This technique is relatively inexpensive, easy to use, and has been estimated to reduce the creation time of manufacturing tools by up to 85%. However, non-optimal environmental conditions can cause significant issues in the 3D printing process, including jammed nozzles and defective parts such as stringy prints, parts with bubbly or uneven surface textures, and soft or brittle parts. For example, higher relative humidity levels in the printer vicinity significantly decrease the ultimate strength and Young’s modulus of 3D printed parts. An enclosure is an effective tool and an efficient way to control and set the airflow patterns, temperature distribution, or humidity level in the vicinity of the printer for a more optimum printing process. A well-designed enclosure to encapsulate the printer can play a vital role in reducing waste and generating quality parts by controlling the printing environmental conditions. Accurate and efficient CFD modeling can be instrumental in designing and optimizing these enclosures, which is a major focus of the current research project. The present effort reports on the development of a CFD-based simulation model for providing detailed and accurate information on the conditions inside the printer enclosure. It also details the validation of the model using experimentally measured airflow, temperature, and humidity data obtained from inside the enclosure. The simulation results obtained from this new CFD model were shown to compare well with the physical model's measured data. The comparison of temperature measured at four different locations showed a difference of less than 0.5% for values obtained from computational and physical models. The time variation of predicted humidity level also compared favorably with measured data from the physical model both in trend and magnitude. Finally, the fan models used in the computational study were validated using measured data and flow rate values provided by the manufacturer’s fan curve. The next phase of this work involves utilizing this CFD model along with optimization software for the design and optimization of 3D printer enclosures with external fans and humidity controls for the ability to set optimal printing conditions.
Additive manufacturing, 3D printer, CFD, temperature modeling, humidity modeling, fan model
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