Journal articles on the topic 'Automated CFD Process'
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Vu, Anh Ngoc, and Tung Nguyen Minh Huynh. "An automated analysis process for vertical axis wind turbine." Science and Technology Development Journal 18, no. 4 (December 30, 2015): 145–52. http://dx.doi.org/10.32508/stdj.v18i4.1000.
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This paper presents an automated process for analyzing the performance of vertical axis wind turbine (VAWT). The details of this process will be demonstrated, which include the airfoil geometry representation using CST method, a hybrid meshing process combining structured grids and unstructured grids, CFD calculation process and processing data results to calculate the power coefficient of VAWT. These processes are designed as separate modules. CFD methods used in this research is RANS 2D using Realizable k turbulence model. Meshing process will be done on the GAMBIT software, the CFD calculations are done on commercial ANSYS FLUENT software and these processes are controlled by mathematical software MATLAB. The formulas used to calculate the power coefficient will be also introduced in this paper.
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Millot, Grégory, Olivier Scholz, Saïd Ouhamou, Mathieu Becquet, and Sébastien Magnabal. "Development of a 3D CFD aerodynamic optimization tool and application to engine air intake design." International Journal of Numerical Methods for Heat & Fluid Flow 30, no. 9 (June 6, 2019): 4219–39. http://dx.doi.org/10.1108/hff-06-2018-0276.
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PurposeThe paper deals with research activities to develop optimization workflows implying computational fluid dynamics (CFD) modelling. The purpose of this paper is to present an industrial and fully-automated optimal design tool, able to handle objectives, constraints, multi-parameters and multi-points optimization on a given CATIA CAD. The work is realized on Rapid And CostEffective Rotorcraft compound rotorcraft in the framework of the Fast RotorCraft Innovative Aircraft Demonstrator Platform (IADP) within the Clean Sky 2 programme.Design/methodology/approachThe proposed solution relies on an automated CAD-CFD workflow called through the optimization process based on surrogate-based optimization (SBO) techniques. The SBO workflow has been specifically developed.FindingsThe methodology is validated on a simple configuration (bended pipe with two parameters). Then, the process is applied on a full compound rotorcraft to minimize the flow distortion at the engine entry. The design of the experiment and the optimization loop act on seven design parameters of the air inlet and for each individual the evaluation is performed on two operation points, namely, cruise flight and hover case. Finally, the best design is analyzed and aerodynamic performances are compared with the initial design.Originality/valueThe adding value of the developed process is to deal with geometric integration conflicts addressed through a specific CAD module and the implementation of a penalty function method to manage the unsuccessful evaluation of any individual.
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Ciampoli, Fabio, John W. Chew, Shahrokh Shahpar, and Elisabeth Willocq. "Automatic Optimization of Preswirl Nozzle Design." Journal of Engineering for Gas Turbines and Power 129, no. 2 (February 1, 2006): 387–93. http://dx.doi.org/10.1115/1.2364194.
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The objective of the research described here is to develop and demonstrate use of automatic design methods for preswirl nozzles. Performance of preswirled cooling air delivery systems depends critically on the design of these nozzles which is subject to manufacturing and stress constraints. The best solution may be a compromise between cost and performance. Here it is shown that automatic optimization using computational fluid dynamics (CFD) to evaluate nozzle performance can be useful in design. A parametric geometric model of a nozzle with appropriate constraints is first defined and the CFD meshing and solution are then automated. The mesh generation is found to be the most delicate task in the whole process. Direct hill climbing (DHC) and response surface model (RSM) optimization methods have been evaluated. For the test case considered, significant nozzle performance improvements were obtained using both methods, but the RSM model was preferred.
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Peric, Milovan, and Volker Bertram. "Trends in Industry Applications of Computational Fluid Dynamics for Maritime Flows." Journal of Ship Production and Design 27, no. 04 (November 1, 2011): 194–201. http://dx.doi.org/10.5957/jspd.2011.27.4.194.
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This paper surveys developments in Computational Fluid Dynamics (CFD) applications for maritime structures (ships, propellers, and offshore structures) over the past decade. Progress is significant in integrating the process chain, particularly more automated model generation. Increased hardware power and progress in various aspects of the flow solvers allow more sophisticated applications and wider scope of applications. Selected examples taken from industry and research applications show the increasing importance of CFD in earlier design stages.
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Johnson, Engr Nnadikwe, Ikputu Woyengikuro Hilary, Okiki Esther E, and Ibe Raymond Obinna. "Design and CFD Application Value Series from Raw Natural Gas Processing to Automated Utilization Need." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (March 31, 2022): 2150–56. http://dx.doi.org/10.22214/ijraset.2022.41029.
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Abstract: Fluid flow systems are common in the energy value chain and are typically complex. To assure the system's performance, understanding and control are essential. Computational fluid dynamics (CFD) is a one-of-a-kind tool that predicts fluid flow events using numerical methods. It allows you to study fluid flow patterns and access non-measurable variables. Because of the rapid advancement of computer science, CFD can currently be used to handle the bulk of industrial operations that require fluid flows. The application's scope is extensive, and the problems it can solve are diverse, spanning from process design validation and optimization to operating condition management and troubleshooting. A few experiments done by Imo State University Petroleum and Gas Lab on upstream natural gas treatment systems to downstream industrial end-use for combined heat and power plants and petrochemical furnaces will demonstrate the application of CFD in troubleshooting. Keywords: CFD, Utilization, Automated, Natural Gas
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Olivetti, Micaela, Federico Giulio Monterosso, Gianluca Marinaro, Emma Frosina, and Pietro Mazzei. "Valve Geometry and Flow Optimization through an Automated DOE Approach." Fluids 5, no. 1 (January 30, 2020): 17. http://dx.doi.org/10.3390/fluids5010017.
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The objective of this paper is to show how a completely virtual optimization approach is useful to design new geometries in order to improve the performance of industrial components, like valves. The standard approach for optimization of an industrial component, as a valve, is mainly performed with trials and errors and is based on the experience and knowledge of the engineer involved in the study. Unfortunately, this approach is time consuming and often not affordable for the industrial time-to-market. The introduction of computational fluid dynamic (CFD) tools significantly helped reducing time to market; on the other hand, the process to identify the best configuration still depends on the personal sensitivity of the engineer. Here a more general, faster and reliable approach is described, which uses a CFD code directly linked to an optimization tool. CAESES® associated with SimericsMP+® allows us to easily study many different geometrical variants and work out a design of experiments (DOE) sequence that gives evidence of the most impactful aspects of a design. Moreover, the result can be further optimized to obtain the best possible solution in terms of the constraints defined.
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Bisgaard, Jonas, Tannaz Tajsoleiman, Monica Muldbak, Thomas Rydal, Tue Rasmussen, Jakob K. Huusom, and Krist V. Gernaey. "Automated Compartment Model Development Based on Data from Flow-Following Sensor Devices." Processes 9, no. 9 (September 13, 2021): 1651. http://dx.doi.org/10.3390/pr9091651.
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Due to the heterogeneous nature of large-scale fermentation processes they cannot be modelled as ideally mixed reactors, and therefore flow models are necessary to accurately represent the processes. Computational fluid dynamics (CFD) is used more and more to derive flow fields for the modelling of bioprocesses, but the computational demands associated with simulation of multiphase systems with biokinetics still limits their wide applicability. Hence, a demand for simpler flow models persists. In this study, an approach to develop data-based flow models in the form of compartment models is presented, which utilizes axial-flow rates obtained from flow-following sensor devices in combination with a proposed procedure for automatic zoning of volume. The approach requires little experimental effort and eliminates the necessity for computational determination of inter-compartmental flow rates and manual zoning. The concept has been demonstrated in a 580 L stirred vessel, of which models have been developed for two types of impellers with varying agitation intensities. The sensor device measurements were corroborated by CFD simulations, and the performance of the developed compartment models was evaluated by comparing predicted mixing times with experimentally determined mixing times. The data-based compartment models predicted the mixing times for all examined conditions with relative errors in the range of 3–27%. The deviations were ascribed to limitations in the flow-following behavior of the sensor devices, whose sizes were relatively large compared to the examined system. The approach provides a versatile and automated flow modelling platform which can be applied to large-scale bioreactors.
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Lange, Christopher, Patrick Barthelmäs, Tobias Rosnitschek, Stephan Tremmel, and Frank Rieg. "Impact of HPC and Automated CFD Simulation Processes on Virtual Product Development—A Case Study." Applied Sciences 11, no. 14 (July 16, 2021): 6552. http://dx.doi.org/10.3390/app11146552.
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High-performance computing (HPC) enables both academia and industry to accelerate simulation-driven product development processes by providing a massively parallel computing infrastructure. In particular, the automation of high-fidelity computational fluid dynamics (CFD) analyses aided by HPC systems can be beneficial since computing time decreases while the number of significant design iterations increases. However, no studies have quantified these effects from a product development point of view yet. This article evaluates the impact of HPC and automation on product development by studying a formula student racing team as a representative example of a small or medium-sized company. Over several seasons, we accompanied the team, and provided HPC infrastructure and methods to automate their CFD simulation processes. By comparing the team’s key performance indicators (KPIs) before and after the HPC implementation, we were able to quantify a significant increase in development efficiency in both qualitative and quantitative aspects. The major aerodynamic KPI increased up to 115%. Simultaneously, the number of expedient design iterations within one season increased by 600% while utilizing HPC. These results prove the substantial benefits of HPC and automation of numerical-intensive simulation processes for product development.
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Deininger, Martina E., Maximilian von der Grün, Raul Piepereit, Sven Schneider, Thunyathep Santhanavanich, Volker Coors, and Ursula Voß. "A Continuous, Semi-Automated Workflow: From 3D City Models with Geometric Optimization and CFD Simulations to Visualization of Wind in an Urban Environment." ISPRS International Journal of Geo-Information 9, no. 11 (October 31, 2020): 657. http://dx.doi.org/10.3390/ijgi9110657.
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The concept and implementation of Smart Cities is an important approach to improve decision making as well as quality of life of the growing urban population. An essential part of this is the presentation of data from different sources within a digital city model. Wind flow at building scale has a strong impact on many health and energy issues in a city. For the analysis of urban wind, Computational Fluid Dynamics (CFD) has become an established tool, but requires specialist knowledge to prepare the geometric input during a time-consuming process. Results are available only as predefined selections of pictures or videos. In this article, a continuous, semi-automated workflow is presented, which ❶ speeds-up the preparation of CFD simulation models using a largely automated geometry optimization; and ❷ enables web-based interactive exploration of urban wind simulations to a large and diverse audience, including experts and layman. Results are evaluated based on a case study using a part of a district in Stuttgart in terms of: ➀ time saving of the CFD model preparation workflow (85% faster than the manual method), ➁ response time measurements of different data formats within the Smart City platform (3D Tiles loaded 30% faster than geoJSON using the same data representations) and ➂ protocols (3DPS provided much higher flexibility than static and 3D container API), as well as ➃ subjective user experience analysis of various visualization schemes of urban wind. Time saving for the model optimization may, however, vary depending on the data quality and the extent of the study area.
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Guo, Jinglan, and Siyuan Wang. "Multiphase Flow Coupling Behavior of Bubbles Based on Computational Fluid Dynamics during AFP Process: The Behavior Characteristics of Bubbles during AFP Process." Advances in Materials Science and Engineering 2021 (July 31, 2021): 1–12. http://dx.doi.org/10.1155/2021/3237713.
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To investigate the mechanism of the effect of process parameters on bubble flow behavior during automated fiber placement (AFP) and the relationship between the bubble and voids, mechanical properties of laminates, this paper analyzes the multiphase flow coupling behavior of the bubble and fiber formation using computational fluid dynamics (CFD) and finite element (FE) method under different AFP process parameters. The effects of AFP process parameters on bubble characteristics and fiber deformation are then discussed, respectively, including bubble displacement, maximum cross-sectional area, the lowest internal temperature of the bubble, bubble breakup, and maximum deformation of the fiber. Furthermore, the AFP and corresponding test experiments are performed to investigate the relationships between different bubble characteristics and void content, mechanical properties, mainly interlaminar shear strength (ILSS) and flexural strength (FS). The results show that the maximum cross-sectional area of bubbles is closely related to the AFP process parameters. The FS and ILSS are positively correlated with the maximum cross-sectional area. With the increase of bubble displacement and fiber maximum deformation, FS and ILSS are first increased and then decreased.
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Carrigan, Travis J., Brian H. Dennis, Zhen X. Han, and Bo P. Wang. "Aerodynamic Shape Optimization of a Vertical-Axis Wind Turbine Using Differential Evolution." ISRN Renewable Energy 2012 (January 16, 2012): 1–16. http://dx.doi.org/10.5402/2012/528418.
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The purpose of this study is to introduce and demonstrate a fully automated process for optimizing the airfoil cross-section of a vertical-axis wind turbine (VAWT). The objective is to maximize the torque while enforcing typical wind turbine design constraints such as tip speed ratio, solidity, and blade profile. By fixing the tip speed ratio of the wind turbine, there exists an airfoil cross-section and solidity for which the torque can be maximized, requiring the development of an iterative design system. The design system required to maximize torque incorporates rapid geometry generation and automated hybrid mesh generation tools with viscous, unsteady computational fluid dynamics (CFD) simulation software. The flexibility and automation of the modular design and simulation system allows for it to easily be coupled with a parallel differential evolution algorithm used to obtain an optimized blade design that maximizes the efficiency of the wind turbine.
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Sagimbayev, Sagi, Yestay Kylyshbek, Sagidolla Batay, Yong Zhao, Sai Fok, and Teh Soo Lee. "3D Multidisciplinary Automated Design Optimization Toolbox for Wind Turbine Blades." Processes 9, no. 4 (March 26, 2021): 581. http://dx.doi.org/10.3390/pr9040581.
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This paper presents two novel automated optimization approaches. The first one proposes a framework to optimize wind turbine blades by integrating multidisciplinary 3D parametric modeling, a physics-based optimization scheme, the Inverse Blade Element Momentum (IBEM) method, and 3D Reynolds-averaged Navier–Stokes (RANS) simulation; the second method introduces a framework combining 3D parametric modeling and an integrated goal-driven optimization together with a 4D Unsteady Reynolds-averaged Navier–Stokes (URANS) solver. In the first approach, the optimization toolbox operates concurrently with the other software packages through scripts. The automated optimization process modifies the parametric model of the blade by decreasing the twist angle and increasing the local angle of attack (AoA) across the blade at locations with lower than maximum 3D lift/drag ratio until a maximum mean lift/drag ratio for the whole blade is found. This process exploits the 3D stall delay, which is often ignored in the regular 2D BEM approach. The second approach focuses on the shape optimization of individual cross-sections where the shape near the trailing edge is adjusted to achieve high power output, using a goal-driven optimization toolbox verified by 4D URANS Computational Fluid Dynamics (CFD) simulation for the whole rotor. The results obtained from the case study indicate that (1) the 4D URANS whole rotor simulation in the second approach generates more accurate results than the 3D RANS single blade simulation with periodic boundary conditions; (2) the second approach of the framework can automatically produce the blade geometry that satisfies the optimization objective, while the first approach is less desirable as the 3D stall delay is not prominent enough to be fruitfully exploited for this particular case study.
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Pachidis, Vassilios, Pericles Pilidis, Fabien Talhouarn, Anestis Kalfas, and Ioannis Templalexis. "A Fully Integrated Approach to Component Zooming Using Computational Fluid Dynamics." Journal of Engineering for Gas Turbines and Power 128, no. 3 (March 1, 2004): 579–84. http://dx.doi.org/10.1115/1.2135815.
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Background . This study focuses on a simulation strategy that will allow the performance characteristics of an isolated gas turbine engine component, resolved from a detailed, high-fidelity analysis, to be transferred to an engine system analysis carried out at a lower level of resolution. This work will enable component-level, complex physical processes to be captured and analyzed in the context of the whole engine performance, at an affordable computing resource and time. Approach. The technique described in this paper utilizes an object-oriented, zero-dimensional (0D) gas turbine modeling and performance simulation system and a high-fidelity, three-dimensional (3D) computational fluid dynamics (CFD) component model. The work investigates relative changes in the simulated engine performance after coupling the 3D CFD component to the 0D engine analysis system. For the purposes of this preliminary investigation, the high-fidelity component communicates with the lower fidelity cycle via an iterative, semi-manual process for the determination of the correct operating point. This technique has the potential to become fully automated, can be applied to all engine components, and does not involve the generation of a component characteristic map. Results. This paper demonstrates the potentials of the “fully integrated” approach to component zooming by using a 3D CFD intake model of a high bypass ratio turbofan as a case study. The CFD model is based on the geometry of the intake of the CFM56-5B2 engine. The high-fidelity model can fully define the characteristic of the intake at several operating condition and is subsequently used in the 0D cycle analysis to provide a more accurate, physics-based estimate of intake performance (i.e., pressure recovery) and hence, engine performance, replacing the default, empirical values. A detailed comparison between the baseline engine performance (empirical pressure recovery) and the engine performance obtained after using the coupled, high-fidelity component is presented in this paper. The analysis carried out by this study demonstrates relative changes in the simulated engine performance larger than 1%. Conclusions. This investigation proves the value of the simulation strategy followed in this paper and completely justifies (i) the extra computational effort required for a more automatic link between the high-fidelity component and the 0D cycle, and (ii) the extra time and effort that is usually required to create and run a 3D CFD engine component, especially in those cases where more accurate, high-fidelity engine performance simulation is required.
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Baheri Islami, Sima, Mike Wesolowski, William Revell, and Xiongbiao Chen. "Virtual Reality Visualization of CFD Simulated Blood Flow in Cerebral Aneurysms Treated with Flow Diverter Stents." Applied Sciences 11, no. 17 (August 31, 2021): 8082. http://dx.doi.org/10.3390/app11178082.
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Virtual reality (VR) has the potential to be a powerful tool for the visualization of simulated blood flow in cerebral aneurysms. This paper presents our study aimed at developing the VR visualization of computational fluid dynamics (CFD) simulations of cerebral aneurysms treated with flow-diverting (FD) stents. First, a spherical sidewall aneurysm located at a simplified internal carotid artery was considered for investigating the impact of stent deployment and positioning on the corresponding spatially time-varying blood flow behavior. The three-dimensional unsteady blood flow over a cardiac cycle was simulated numerically using the finite volume method, and the distributions of hemodynamic parameters inside the aneurysm sac, and on its wall, were presented with and without stent cases. Two stent positions, with and without a gap between the artery wall and stent, were considered to show the influence of correct stent position on aneurysm treatment. Second, a straightforward workflow was developed to import, process, and visualize the CFD analysis data in a VR environment by using open-source software with a high resolution. The Unity3D engine was used for displaying the processed animations in a VR environment operated on a head-mounted display (HMD). The refining process of each frame of time-varying CFD data was automated. The animated flow elements rendered in the VR environment were velocity vectors, velocity contours, streamlines, particle traces, and point clouds. CFD results showed that proper stenting facilitates thrombosis and occlusion of the aneurysm by modification of the flow patterns, which leads to lower inflow jet velocities into the aneurysm, longer turnover time, lower aneurysm-averaged kinetic energy, and lower wall shear stress. Additionally, the results indicated that a gap between the stent and the parent artery may lead to undesirable hemodynamic alterations. The VR visualization illustrated that the recognition of the potential in danger regions of aneurysms and the evaluation of the performance of FD stents in aneurysm treatment can be conducted without the need for several slices through the parent artery and aneurysm, as is required for traditional postprocessing methods. Through VR visualization, the details of the simulation results become readily available by navigating in the 3D animated flow elements using a high-degree-of-freedom headset.
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GLÄNZEL, Janine, Tharun Suresh . KUMAR, Christian NAUMANN, and Matthias PUTZ. "PARAMETERIZATION OF ENVIRONMENTAL INFLUENCES BY AUTOMATED CHARACTERISTIC DIAGRAMS FOR THE DECOUPLED FLUID AND STRUCTURAL-MECHANICAL SIMULATIONS." Journal of Machine Engineering 19, no. 1 (February 20, 2019): 98–113. http://dx.doi.org/10.5604/01.3001.0013.0461.
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Thermo-elastic effects contribute the most to positioning errors in machine tools especially in operations where high precision machining is involved. When a machine tool is subjected to changes in environmental influences such as ambient air temperature, velocity or direction, then flow (CFD) simulations are necessary to effectively quantify the thermal behaviour between the machine tool surface and the surrounding air (fluid). Heat transfer coefficient (HTC) values effectively represent this solid-fluid heat transfer and it serves as the boundary data for thermo-elastic simulations. Thereby, deformation results can be obtained. This two-step simulation procedure involving fluid and thermo-structural simulations is highly complex and time-consuming. A suitable alternative for the above process can be obtained by introducing a clustering algorithm (CA) and characteristic diagrams (CDs) in the workflow. CDs are continuous maps of a set of input variables onto a single output variable, which are trained using data from a limited number of CFD simulations which is optimized using the clustering technique involving genetic algorithm (GA) and radial basis function (RBF) interpolation. The parameterized environmental influences are mapped directly onto corresponding HTC values in each CD. Thus, CDs serve as look-up tables which provide boundary data (HTC values along with nodal information) under several load cases (combinations of environmental influences) for thermo-elastic simulations. Ultimately, a decoupled fluid-structural simulation system is obtained where boundary (convection) data for thermo-mechanical simulations can be directly obtained from CDs and would no longer require fluid simulations to be carried out again. Thus, a novel approach for the correction of thermo-elastic deformations on a machine tool is obtained.
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Aziz, NA, NAM Amin, A. Mohamad, MS Bin Mohamad, MAM Saad, MTA Rahman, and M. Izham. "Design and analysis of a solar integrated agriculture irrigation system for rural farming area." Journal of Physics: Conference Series 2051, no. 1 (October 1, 2021): 012036. http://dx.doi.org/10.1088/1742-6596/2051/1/012036.
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Abstract Precision farming involves a management strategy to increase productivity and economic returns with reduced environmental impacts. Precision farming is available for small farm agriculture and big farm agriculture, and it plays a significant role in rural development programs in the agriculture industry. Accordingly, an automated solar integrated agriculture irrigation system is proposed to effectively help farmers in rural areas supply the water to their farms. The proposed automated system is expected to increase productivity and provide better quality control, as well as minimising the work labour time. The system was designed by considering various design factors, such as the reliability, safety, and ergonomic factors, to ensure the product is user friendly. Besides, the material selection process and parametric studies conducted to determine the right sizing and position of the components are discussed. Computational Fluid Dynamic (CFD) analysis was used to simulate the water tank to visualise the water flow. From the design analysis, a higher water tank placement and bigger pipe diameter are found to make the system more efficient.
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Salvadore, Francesco, Raffaele Ponzini, Javier Hernández Duque, Cristian Alcántara Reinaldos, and Jordi Mas Soler. "CFD analysis of a multiplatform catamaran by means of a web-based application: Experimental data comparison for a fully automated analysis process." Applied Ocean Research 116 (November 2021): 102886. http://dx.doi.org/10.1016/j.apor.2021.102886.
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Moreno-Armendáriz, Marco A., Eddy Ibarra-Ontiveros, Hiram Calvo, and Carlos A. Duchanoy. "Integrated Surrogate Optimization of a Vertical Axis Wind Turbine." Energies 15, no. 1 (December 30, 2021): 233. http://dx.doi.org/10.3390/en15010233.
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In this work, a 3D computational model based on computational fluid dynamics (CFD) is built to simulate the aerodynamic behavior of a Savonius-type vertical axis wind turbine with a semi-elliptical profile. This computational model is used to evaluate the performance of the wind turbine in terms of its power coefficient (Cp). Subsequently, a full factorial design of experiments (DOE) is defined to obtain a representative sample of the search space on the geometry of the wind turbine. A dataset is built on the performance of each geometry proposed in the DOE. This process is carried out in an automated way through a scheme of integrated computational platforms. Later, a surrogate model of the wind turbine is fitted to estimate its performance using machine learning algorithms. Finally, a process of optimization of the geometry of the wind turbine is carried out employing metaheuristic optimization algorithms to maximize its Cp; the final optimized designs are evaluated using the computational model for validating their performance.
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Benaouali, Abdelkader, and Stanisław Kachel. "A surrogate-based integrated framework for the aerodynamic design optimization of a subsonic wing planform shape." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 232, no. 5 (March 22, 2017): 872–83. http://dx.doi.org/10.1177/0954410017699007.
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Due to the development in computer technology, computational simulations have become indispensable for most engineering system design processes, particularly in aerospace applications. Performing a simulation-driven aerodynamic design optimization is a challenging task due to the computational expensiveness of high fidelity models, the considerable number of design parameters, the variety of disciplines that must be considered… etc. In this paper, the preliminary design of an aircraft wing through the use of a fully automated design environment, coupled with surrogate-based optimization, is presented. A parametric modeling framework was developed based on the seamless integration of several commercial software through built-in scripting languages. The design process goes through geometry modeling, Aerodynamic grid generation and flow solution which involves SIEMENS NX, ICEM CFD and FLUENT respectively. The optimization is made feasible using surrogate modeling techniques combined with a Sequential Quadratic Programing (SQP) algorithm.
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SUCHANEK, Grzegorz, and Roman FILIPEK. "COMPUTATIONAL FLUID DYNAMICS (CFD) AIDED DESIGN OF A MULTI-ROTOR FLYING ROBOT FOR LOCATING SOURCES OF PARTICULATE MATTER POLLUTION." Applied Computer Science 18, no. 3 (September 30, 2022): 86–104. http://dx.doi.org/10.35784/acs-2022-23.
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The use of flying robots for various environmental protection issues is a very important and current research topic. Designing a dedicated multi-rotor flying robot is necessary for the efficient and automated localization of sources of air pollution, especially solid particles. In particular, one of the most important requirements that must be met by such a robot is its appropriate impact on the measurement process, i.e., increasing the sensitivity of sensors or reducing the interference. This is particularly difficult because its rotating rotors introduce significant disturbances to the surrounding fluid. In these studies, the design process is supported by the creation of a mathematical flow model and a series of analyzes to optimize the PM measurement system. The model is built using the finite-volume method in ANSYS Fluent software and steady-state RANS averaging. First, a flow field model with one propeller was modeled and its parameters identified by comparison with the results from the dedicated original dynamometer stand -- characteristics of the propeller performance. On the basis of the simulations and measurement of one rotor, subsequent systems of the highest practical importance are built. The effect of that design process was the preparation and testing of a functional robot prototype. The field parameter distributions resulting from the analyzes, in particular the turbulence intensity, allow one to propose a criterion on the basis of which both the best rotor configuration and localization of sensors are selected.
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Tesch, Krzysztof, and Katarzyna Kaczorowska-Ditrich. "The Discrete-Continuous, Global Optimisation of an Axial Flow Blood Pump." Flow, Turbulence and Combustion 104, no. 4 (November 20, 2019): 777–93. http://dx.doi.org/10.1007/s10494-019-00100-5.
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AbstractThis paper presents the results of the discrete-continuous optimisation of an axial flow blood pump. Differential evolution (DE) is used as a global optimisation method in order to localise the optimal solution in a relatively short time. The whole optimisation process is fully automated. This also applies to geometry modelling. Numerical simulations of the flow inside the pump are performed by means of the Reynolds-Average Navier-Stokes approach. All equations are discretised by means of the finite volume method, and the corresponding algebraic equation systems are solved by the open source software for CFD, namely OpenFOAM. Finally, the optimisation results are presented and discussed. The objective function to be maximised is simply pressure increase. The higher pressure increase the lower angular velocities required. This makes it possible to minimise the effect of haemolysis because it is mainly caused by high shear stresses which are related, among others, to angular velocities.
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Bae, Jun Ho, Hyo Seo Kwak, Sereisith San, and Chul Kim. "Design and CFD analysis of gerotor with multiple profiles (ellipse–involute–ellipse type and 3-ellipses type) using rotation and translation algorithm." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 230, no. 5 (April 22, 2015): 804–23. http://dx.doi.org/10.1177/0954406215583888.
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Gerotor is a key component used in internal gear pumps of vehicles, and as the technology of sintering process is highly advanced, the gerotor has advantages for manufacturing complex profiles and obtaining durability and minimization. But internal gear pumps have been continuously required to improve flow rate and noise for fuel efficiency. The existing gerotors with multiple profiles have been designed by only translation algorithm, which is limited to improve the performances. In this study, a new automated design and multiple calculation programs using rotation and translation algorithm were developed for improving the performances of multiple profiles, and two types of combined multiple profiles (ellipse 1-involute-ellipse 2 type and 3-ellipses type) were generated. The performances (flow rate, irregularity, specific sliding and pressure angle) of the profiles were calculated by using theoretical analysis, and optimal designs of the two types were carried out on the basis of analysis results. Also, internal flow characteristics in the optimized gerotor generated were analyzed by using commercial CFD (computational fluid dynamics) code, ANSYS-CFX.
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Farid, Omar J., Alexandre França Velo, Binbin Qi, and Muthanna Al-Dahhan. "New Methodology for Benchmarking Hydrodynamics in Bubble Columns with Intense Internals Using the Radioactive Particle Tracking (RPT) Technique." Processes 11, no. 7 (July 14, 2023): 2107. http://dx.doi.org/10.3390/pr11072107.
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A new methodology for implementing radioactive particle tracking (RPT) in bubble columns with intense vertical rod internals was developed and implemented to investigate the effect of dense internals on hydrodynamics. The methodology utilizes a hybrid of Monte Carlo N-Particle (MCNP) simulation and an automated RPT calibration device to generate a large number of calibration points for accurate reconstruction of the instantaneous positions of radioactive particles using a similarity algorithm. Measurements were conducted in a 6-inch (15.24 cm) Plexiglas column using an air–water system at a superficial gas velocity of 40 cm/s. Vertical Plexiglas rods 0.5 in (1.27 cm) in diameter were used to cover ~25% of the total cross-sectional area of the column to represent the effect of a heat-exchanging tube in industrial Fisher–Tropsch synthesis. The results showed that the internals increased liquid velocity near the center of the column by more than 30%, resulting in enhanced liquid circulation and frequency of liquid eddy movement. In addition, turbulence parameters decreased noticeably when using vertical internals in the bubble column due to a reduction in velocity fluctuations. Reliable data can help validate computational fluid dynamics (CFD) models to predict hydrodynamic parameters at other various conditions.
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Cravero, Carlo, Davide De Domenico, and Andrea Ottonello. "Uncertainty Quantification Approach on Numerical Simulation for Supersonic Jets Performance." Algorithms 13, no. 5 (May 22, 2020): 130. http://dx.doi.org/10.3390/a13050130.
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One of the main issues addressed in any engineering design problem is to predict the performance of the component or system as accurately and realistically as possible, taking into account the variability of operating conditions or the uncertainty on input data (boundary conditions or geometry tolerance). In this paper, the propagation of uncertainty on boundary conditions through a numerical model of supersonic nozzle is investigated. The evaluation of the statistics of the problem response functions is performed following ‘Surrogate-Based Uncertainty Quantification’. The approach involves: (a) the generation of a response surface starting from a DoE in order to approximate the convergent–divergent ‘physical’ model (expensive to simulate), (b) the application of the UQ technique based on the LHS to the meta-model. Probability Density Functions are introduced for the inlet boundary conditions in order to quantify their effects on the output nozzle performance. The physical problem considered is very relevant for the experimental tests on the UQ approach because of its high non-linearity. A small perturbation to the input data can drive the solution to a completely different output condition. The CFD simulations and the Uncertainty Quantification were performed by coupling the open source Dakota platform with the ANSYS Fluent® CFD commercial software: the process is automated through scripting. The procedure adopted in this work demonstrate the applicability of advanced simulation techniques (such as UQ analysis) to industrial technical problems. Moreover, the analysis highlights the practical use of the uncertainty quantification techniques in predicting the performance of a nozzle design affected by off-design conditions with fluid-dynamic complexity due to strong nonlinearity.
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Reimer, Uwe, Dieter Froning, Gert Nelissen, Leonard F. J. M. Raymakers, Shidong Zhang, Steven B. Beale, and Werner Lehnert. "An Engineering Toolbox for the Evaluation of Metallic Flow Field Plates." ChemEngineering 3, no. 4 (October 11, 2019): 85. http://dx.doi.org/10.3390/chemengineering3040085.
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Metallic flow field plates, also called bipolar plates, are an important component of fuel cell stacks, electrolyzers, hydrogen purification and compression stacks. The manufacturing of these plates by means of stamping or hydroforming is highly suitable for mass production. In this work, a toolbox is created that is suitable for a screening process of different flow field design variants. For this purpose, the geometry and computational mesh are generated in an automated manner. Basic building blocks are combined using the open source software SALOME, and these allow for the construction of a large variant of serpentine-like flow field structures. These geometric variants are evaluated through computational fluid dynamics (CFD) simulations with the open source software OpenFOAM. The overall procedure allows for the screening of more than 100 variants within one week using a standard desktop computer. The performance of the flow fields is evaluated on the basis of two parameters: the overall pressure difference across the plate and the relative difference of the hydrogen concentration at the outlet of the channels. The results of such a screening first provide information about optimum channel geometry and the best choice of the general flow field layout. Such results are important at the beginning of the design process, as the channel geometry has an influence on the selection of the metal for deep drawing or hydroforming processes.
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Chaquet-Ulldemolins, Jacobo, Francisco-Javier Gimeno-Blanes, Santiago Moral-Rubio, Sergio Muñoz-Romero, and José-Luis Rojo-Álvarez. "On the Black-Box Challenge for Fraud Detection Using Machine Learning (II): Nonlinear Analysis through Interpretable Autoencoders." Applied Sciences 12, no. 8 (April 11, 2022): 3856. http://dx.doi.org/10.3390/app12083856.
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Artificial intelligence (AI) has recently intensified in the global economy due to the great competence that it has demonstrated for analysis and modeling in many disciplines. This situation is accelerating the shift towards a more automated society, where these new techniques can be consolidated as a valid tool to face the difficult challenge of credit fraud detection (CFD). However, tight regulations do not make it easy for financial entities to comply with them while using modern techniques. From a methodological perspective, autoencoders have demonstrated their effectiveness in discovering nonlinear features across several problem domains. However, autoencoders are opaque and often seen as black boxes. In this work, we propose an interpretable and agnostic methodology for CFD. This type of approach allows a double advantage: on the one hand, it can be applied together with any machine learning (ML) technique, and on the other hand, it offers the necessary traceability between inputs and outputs, hence escaping from the black-box model. We first applied the state-of-the-art feature selection technique defined in the companion paper. Second, we proposed a novel technique, based on autoencoders, capable of evaluating the relationship among input and output of a sophisticated ML model for each and every one of the samples that are submitted to the analysis, through a single transaction-level explanation (STE) approach. This technique allows each instance to be analyzed individually by applying small fluctuations of the input space and evaluating how it is triggered in the output, thereby shedding light on the underlying dynamics of the model. Based on this, an individualized transaction ranking (ITR) can be formulated, leveraging on the contributions of each feature through STE. These rankings represent a close estimate of the most important features playing a role in the decision process. The results obtained in this work were consistent with previous published papers, and showed that certain features, such as living beyond means, lack or absence of transaction trail, and car loans, have strong influence on the model outcome. Additionally, this proposal using the latent space outperformed, in terms of accuracy, our previous results, which already improved prior published papers, by 5.5% and 1.5% for the datasets under study, from a baseline of 76% and 93%. The contribution of this paper is twofold, as far as a new outperforming CFD classification model is presented, and at the same time, we developed a novel methodology, applicable across classification techniques, that allows to breach black-box models, erasingthe dependencies and, eventually, undesirable biases. We conclude that it is possible to develop an effective, individualized, unbiased, and traceable ML technique, not only to comply with regulations, but also to be able to cope with transaction-level inquiries from clients and authorities.
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Younis, Adel, and Zuomin Dong. "High-Fidelity Surrogate Based Multi-Objective Optimization Algorithm." Algorithms 15, no. 8 (August 7, 2022): 279. http://dx.doi.org/10.3390/a15080279.
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The employment of conventional optimization procedures that must be repeatedly invoked during the optimization process in real-world engineering applications is hindered despite significant gains in computing power by computationally expensive models. As a result, surrogate models that require far less time and resources to analyze are used in place of these time-consuming analyses. In multi-objective optimization (MOO) problems involving pricey analysis and simulation techniques such as multi-physics modeling and simulation, finite element analysis (FEA), and computational fluid dynamics (CFD), surrogate models are found to be a promising endeavor, particularly for the optimization of complex engineering design problems involving black box functions. In order to reduce the expense of fitness function evaluations and locate the Pareto frontier for MOO problems, the automated multiobjective surrogate based Pareto finder MOO algorithm (AMSP) is proposed. Utilizing data samples taken from the feasible design region, the algorithm creates three surrogate models. The algorithm repeats the process of sampling and updating the Pareto set, by assigning weighting factors to those surrogates in accordance with the values of the root mean squared error, until a Pareto frontier is discovered. AMSP was successfully employed to identify the Pareto set and the Pareto border. Utilizing multi-objective benchmark test functions and engineering design examples such airfoil shape geometry of wind turbine, the unique approach was put to the test. The cost of computing the Pareto optima for test functions and real engineering design problem is reduced, and promising results were obtained.
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Mushtaq, Noraiz, Gabriele Colella, and Paolo Gaetani. "Design and Parametric Analysis of a Supersonic Turbine for Rotating Detonation Engine Applications." International Journal of Turbomachinery, Propulsion and Power 7, no. 1 (January 4, 2022): 1. http://dx.doi.org/10.3390/ijtpp7010001.
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Pressure gain combustion is a promising alternative to conventional gas turbine technologies and within this class the Rotating Detonation Engine has the greatest potential. The Fickett–Jacobs cycle can theoretically increase the efficiency by 15% for medium pressure ratios, but the combustion chamber delivers a strongly non-uniform flow; in these conditions, conventionally designed turbines are inadequate with an efficiency below 30%. In this paper, an original mean-line code was developed to perform an advanced preliminary design of a supersonic turbine; self-starting capability of the supersonic channel has been verified through Kantrowitz and Donaldson theory; the design of the supersonic profile was carried out employing the Method of Characteristics; an accurate evaluation of the aerodynamic losses has been achieved by considering shock waves, profile, and mixing losses. Afterwards, an automated Computational Fluid Dynamics (CFD) based optimization process was developed to find the optimal loading condition that minimizes losses while delivering a sufficiently uniform flow at outlet. Finally, a novel parametric analysis was performed considering the effect of inlet angle, Mach number, reaction degree, peripheral velocity, and blade height ratio on the turbine stage performance. This analysis has revealed for the first time, in authors knowledge, that this type of machines can achieve efficiencies over 70%.
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Mohr, L., R. Benauer, P. Leitl, and F. Fraundorfer. "DAMAGE ESTIMATION OF EXPLOSIONS IN URBAN ENVIRONMENTS BY SIMULATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W8 (August 21, 2019): 253–60. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w8-253-2019.
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<p><strong>Abstract.</strong> Precise models of the impact of explosions in urban environments provide novel and valuable information in disaster management for developing precautionary, preventive and mitigating measures. Yet to date, no methods enabling accurate predictions of the process and effect of detonations at particular locations exist. We propose a novel approach mitigating this gap by combining state-of-the-art methods from photogrammetric 3D reconstruction, semantic segmentation and computational based numerical simulations. In a first step, we create an accurate urban 3D reconstruction from georeferenced aerial images. The resulting city model is then enriched with semantic information obtained from the original source images as well as from registered terrestrial images using deep neural networks. This allows for an efficient automatic preparation of a 3D model suitable for the use as a geometry for the numerical investigations. Using this approach, we are able to provide recent and precise models of an area of interest in an automated fashion. Within the model, we are now able to define the explosive charge size and location and simulate the resulting blast wave propagation using CFD simulation. This provides a full estimation for the expected pressure propagation of a defined charge size. From these results, arising damages and their extent, as well as possible access routes or countermeasures, can be estimated. Using georeferenced sources allows for the integration and utilization of simulation results into existing geoinformation systems of disaster management units, providing novel inputs for training, preparation and prevention. We demonstrate our proposed approach by evaluating expected glass breakage and expected damages impairing the structural integrity of buildings depending on the charge size using a 3D reconstruction from aerial images of an area in the inner city of Graz, Austria.</p>
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Park, John. "Path Finding for Multiple Platforms." Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT) 2014, DPC (January 1, 2014): 002036–56. http://dx.doi.org/10.4071/2014dpc-tha24.
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With the increasing complexity of today's SOCs and the growth in multi-die packaging, companies are recognizing the value of cross-domain collaboration between the IC, package substrate and PCB design groups. High pin count devices coupled with cost sensitivity drive engineers to reconsider how they plan, optimize and automate the I/O placement on their chips, while targeting multiple packaging variables, which have direct impact on how the PCB will be designed. In some instances, informal design flows based on multiple EDA design tools have been pieced together. This is a step in the right direction; however, without a central repository for the data or accurate device modeling and rule-based optimization, design intent is often misinterpreted or lost and redundancy is often introduced into the flow. This presentation outlines a co-design methodology that allows design teams the ability to easily plan and optimize I/O and connectivity from a chip(s), through multiple packaging variables while targeting multiple different system platforms (PCBs). Using this planning, optimization and design methodology, engineering teams for the IC, the Package and the PCB would drive rule-based I/O level optimization and perform ball-out studies from their respective domains, all while visualizing the impact across the complete system. Key features and advantages of this methodology are:Multi-mode connectivity management for cross-domain pin/signal mapping/shortingUser definable rules for I/O and ball-out assignmentsRobust support for feasibility analysis and rapid prototypingFully automated library developmentDirect integration to multi-mode physical layout toolSeamless interface to 2D and 3D EM analysis enginesTight interface with CFD based thermal analysis solutionEDA vendor neutral flow The result of implementing this methodology will be a chip(s) that is fully optimized for its package(s) and PCB(s). This solution drives down the cost of the package and PCB through layer reduction and tighter control of the design process without impacting the cost of the chip.
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Arif, Mohammad Shafi, Peter Schade, Rainer Lehfeldt, Vikram Notay, Georg Carstens, and Frank Kösters. "From simulation to dissemination: automation of data and metadata management." IOP Conference Series: Earth and Environmental Science 1136, no. 1 (January 1, 2023): 012006. http://dx.doi.org/10.1088/1755-1315/1136/1/012006.
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Abstract Working with Computational Fluid Dynamics (CFD) can produce numerous datasets, which contain different physical parameters and study settings. Management and dissemination of such data benefits greatly from a comprehensive data description (metadata), ideally a specialized Metadata Information System (MIS), and adequate long-term storage (data warehouse). To avoid the manual creation of rival metadata, an automation method has been developed, which adds metadata automatically by the simulation and post-processing programs. The automation method described here is an example for data curation suitable for a professional work environment. This method begins with the collection and creation of metadata and ends with the dissemination and publication of the data. This procedure reduces the challenging amount of tedious and error-prone workload, avoids redundancy, enhances efficiency, and is thus a means of quality assurance. Basis for the automation process is an open-source metadata information system (MIS) which has been adapted to the techno-scientific demand of simulation metadata. It stores the metadata in an SQL database and provides Open Geospatial Consortium (OGC) compliant services and communication interface. A hierarchical metadata management concept was initiated for efficient management of numerous datasets. Subsequently, the metadata validation and dissemination are automated via a middleware, which compiles metadata in an XML file, imports the metadata into the MIS and transfers the data to a long-term repository via a Representational State Transfer (REST) interface. Finally, the data and metadata are interlinked and published.
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Rotondi, Marco, Ned Grace, John Betts, Neil Bargh, Elena Costariol, Barney Zoro, Christopher J. Hewitt, Alvin W. Nienow, and Qasim A. Rafiq. "Design and development of a new ambr250® bioreactor vessel for improved cell and gene therapy applications." Biotechnology Letters 43, no. 5 (February 2, 2021): 1103–16. http://dx.doi.org/10.1007/s10529-021-03076-3.
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AbstractThe emergence of cell and gene therapies has generated significant interest in their clinical and commercial potential. However, these therapies are prohibitively expensive to manufacture and can require extensive time for development due to our limited process knowledge and understanding. The automated ambr250® stirred-tank bioreactor platform provides an effective platform for high-throughput process development. However, the original dual pitched-blade 20 mm impeller and baffles proved sub-optimal for cell therapy candidates that require suspension of microcarriers (e.g. for the culture of adherent human mesenchymal stem cells) or other particles such as activating Dynabeads® (e.g. for the culture of human T-cells). We demonstrate the development of a new ambr250® stirred-tank bioreactor vessel which has been designed specifically to improve the suspension of microcarriers/beads and thereby improve the culture of such cellular systems. The new design is unbaffled and has a single, larger elephant ear impeller. We undertook a range of engineering and physical characterizations to determine which vessel and impeller configuration would be most suitable for suspension based on the minimum agitation speed (NJS) and associated specific power input (P/V)JS. A vessel (diameter, T, = 60 mm) without baffles and incorporating a single elephant ear impeller (diameter 30 mm and 45° pitch-blade angle) was selected as it had the lowest (P/V)JS and therefore potentially, based on Kolmogorov concepts, was the most flexible system. These experimentally-based conclusions were further validated firstly with computational fluid dynamic (CFD) simulations and secondly experimental studies involving the culture of both T-cells with Dynabeads® and hMSCs on microcarriers. The new ambr250® stirred-tank bioreactor successfully supported the culture of both cell types, with the T-cell culture demonstrating significant improvements compared to the original ambr250® and the hMSC-microcarrier culture gave significantly higher yields compared with spinner flask cultures. The new ambr250® bioreactor vessel design is an effective process development tool for cell and gene therapy candidates and potentially for autologous manufacture too.
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Gurau, Vladimir, and Emory De Castro. "Prediction of Performance Variation Caused by Manufacturing Tolerances and Defects in Gas Diffusion Electrodes of Phosphoric Acid (PA)–Doped Polybenzimidazole (PBI)-Based High-Temperature Proton Exchange Membrane Fuel Cells." Energies 13, no. 6 (March 13, 2020): 1345. http://dx.doi.org/10.3390/en13061345.
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The automated process of coating catalyst layers on gas diffusion electrodes (GDEs) for high-temperature proton exchange membrane fuel cells results inherently into a number of defects. These defects consist of agglomerates in which the platinum sites cannot be accessed by phosphoric acid and which are the consequence of an inconsistent coating, uncoated regions, scratches, knots, blemishes, folds, or attached fine particles—all ranging from μm to mm size. These electrochemically inactive spots cause a reduction of the effective catalyst area per unit volume (cm2/cm3) and determine a drop in fuel cell performance. A computational fluid dynamics (CFD) model is presented that predicts performance variation caused by manufacturing tolerances and defects of the GDE and which enables the creation of a six-sigma product specification for Advent phosphoric acid (PA)-doped polybenzimidazole (PBI)-based membrane electrode assemblies (MEAs). The model was used to predict the total volume of defects that would cause a 10% drop in performance. It was found that a 10% performance drop at the nominal operating regime would be caused by uniformly distributed defects totaling 39% of the catalyst layer volume (~0.5 defects/μm2). The study provides an upper bound for the estimation of the impact of the defect location on performance drop. It was found that the impact on the local current density is higher when the defect is located closer to the interface with the membrane. The local current density decays less than 2% in the presence of an isolated defect, regardless of its location along the active area of the catalyst layer.
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Piepereit, R., M. Deininger, M. Kada, M. Pries, and U. Voß. "A SWEEP-PLANE ALGORITHM FOR THE SIMPLIFICATION OF 3D BUILDING MODELS IN THE APPLICATION SCENARIO OF WIND SIMULATIONS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W10 (September 12, 2018): 151–56. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w10-151-2018.
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<p><strong>Abstract.</strong> As the number of virtual 3D city models is steadily increasing, so are the possible applications that take advantage of them. 3D models can be used for applications that range from simple graphic visualizations to complex simulations, such as air flow and acoustic simulations. The geometric requirements needed for Computer Aided Engineering (CAE) and Computational Fluid Dynamics (CFD) increase the already very high complexity of processing 3D models. If there are too many small geometric details, mesh generation may fail. In addition it will create small grid cells that consequently lead to a high computation time. So far, the necessary simplifications have been performed in a time consuming manual process. To reduce the preprocessing time for the considered simulation topic, the simplifications and modifications have to be automated. In this paper we introduce a sweep-plane algorithm designed to automatically simplify virtual 3D models (e.g. CityGML) by removing geometry information unnecessary for numerical simulations. The algorithm will search for edges whose length does not reach a predefined threshold and dissolve them by sweeping nearby faces. As a result we obtain a simplified geometry that can be meshed properly. This algorithm serves as a general basis for the creation of future simplification algorithms that may even be applicable to any simulation necessary. For this paper, one of Stuttgart’s city blocks was processed with the developed algorithm and then used in a wind simulation carried out with ANSYS Fluent.</p>
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Tanaka, Hidetake, Soichiro Naka, and Naoki Asakawa. "Development of CAM System Using Linear Servo Motor to Automate Metal Hammering – A Study on Forging-Type Rapid Prototyping System –." International Journal of Automation Technology 6, no. 5 (September 5, 2012): 604–10. http://dx.doi.org/10.20965/ijat.2012.p0604.
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This study deals with the use of a linear motor to automate a metal hammering process based on CAD data. In the study, a linear servo hammering system is adopted to automate the hammering work, and a CAM system generating arbitrary tool path modes for metal hammering bases on CAD data is developed. By utilizing the developed CAM system, formability of automated metal hammering using different tool path modes is clarified, and forming characteristics through the integration of discrete deformation throughout the hammering progress is experimentally demonstrated.
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King, D. A., and A. de Sam Lazaro. "Process and Tolerance Considerations in the Automated Design of Fixtures." Journal of Mechanical Design 116, no. 2 (June 1, 1994): 480–86. http://dx.doi.org/10.1115/1.2919404.
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The long lead time for jig and fixture design is a serious bottleneck in modern manufacturing. Efforts to automate the design process using intelligent CAD systems have not been taken beyond the prototype stage mainly because of several impediments. These include the requirement of complex data structures to represent the workpiece and its attributes. Two deficiencies in existing systems for fixture design are addressed. These are (a) design for a sequence of operations and (b) design with tolerance considerations. Tolerance and process specifications are obtained from the user during an interactive session. A knowledge-based design system, REFIX, then designs a fixture for the workpiece. The fixture is optimized for a particular datum specification and sequence of operations. It is then analyzed and presented via the CAD system. REFIX is automated to minimize user-induced errors.
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Mihaylov, Oleg. "DETERMINING THE POSITIONS OF THE ELEMENTS FOR THE 3-2-1 PRINCIPLE OF LOCATION IN A SOLIDWORKS ADD-IN." ENVIRONMENT. TECHNOLOGIES. RESOURCES. Proceedings of the International Scientific and Practical Conference 3 (June 20, 2019): 160. http://dx.doi.org/10.17770/etr2019vol3.4138.
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This paper presents the methodology behind the positioning of modular fixtures (for the 3-2-1 principle in particular) in a CAFD application (add-in) for SolidWorks. The application is integrated into SolidWorks and it’s used to automate the design process of modular fixturing devices. Part of it is a methodology for automated determination of the positions of the modular elements by using rule-based logic and mathematical formulas.
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McGhee, Scott, Sivrama Nalluri, Ron Reeve, Robert Rongo, Fritz Prinz, and Jim Hemmerle. "Automatic Programming System for Shipyard Robots." Journal of Ship Production 13, no. 02 (May 1, 1997): 93–100. http://dx.doi.org/10.5957/jsp.1997.13.2.93.
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The application of robots to variable tasks in unstructured environments presents a series of problems that must be solved in order to achieve viable results Common teaching-type robots cannot be applied in these cases as the programming time and labor investment far exceed the time and cost of direct manual production. Numerically controlled (NC) robots programmed off-line by modified NC methods have been applied with economic success to program robots directly from computer-aided design (CAD) data where tasks are sufficiently repetitive and the operating environment is sufficiently structured Similarly, off-line programming systems have been developed by various robot manufacturers to generate instructions from CAD data for their robots. Likewise, developers of 3D simulation software have devised methods to merge CAD data with physical models of robots and system hardware to produce robot path programs that approximate the tasks to be performed. Each of these systems is unable to provide a totally automated means to program robot tasks directly from CAD data due to inaccuracies in the real-world elements and/or the models, and due to a lack of knowledge about the processes. A new approach to automatic robot programming is needed that is capable of dealing with:inherent differences between the CAD models and the real-world parts;uncertainties regarding the precise location and accessibility of the parts relative to the robot:process knowledge required to adapt these differences and uncertainties; andprocess knowledge essential to optimizing robot activities. Such an automatic robot programming system is being developed to meet the dual-use defense and commercial ship construction needs of American shipyards under the Technology Reinvestment Project (TRP) for Shipbuilding Robotics. This system automates the programmer's task of identifying location of welds, assigning weld process parameters and adaptive welding strategies to each joint. A procedural diagram for this system is shown in Figure 1. The results and benefits of this approach are described herein. Fig. 1Procedure for automatic off-line robot task planning
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Ting, Chun-Chien, Cheng-Kai Huang, Shean-Juinn Chiou, and Kun-Ying Li. "The 3D Deburring Processing Trajectory Recognition Method and Its Application Base on Random Sample Consensus." Applied Sciences 12, no. 10 (May 11, 2022): 4852. http://dx.doi.org/10.3390/app12104852.
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As of 2022, most automatic deburring trajectories are still generated using offline programming methods. The trajectories generated using these methods are often suboptimal, which limits the precision of the robotic arms used to perform automatic deburring and, in turn, results in workpiece dimensional errors. Therefore, despite advances in automated deburring trajectory generation, deburring is still mostly performed manually. However, manual deburring is a time-consuming, labor-intensive, and expensive process that results in small profit margins for organizational equipment manufacturers (OEMs). To address these problems and the obstacles to the implementation of automated deburring in the robotics industry, the present study developed an online automated deburring trajectory generation method that uses 2D contouring information obtained from linear contour scanning sensors, a CAD model, and curve fitting to detect burrs and generate appropriate trajectories. The method overcomes many of the limitations of common deburring methods, especially by enabling real-time trajectory tracking. When the method was tested using bicycle forks, work that originally took three to four people 8–12-h to complete was completed by one person in 30 min, and the production cost was reduced by 70%.
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Heijmans, Ad. "The Right Mix." Mechanical Engineering 131, no. 03 (March 1, 2009): 46–48. http://dx.doi.org/10.1115/1.2009-mar-5.
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This review explores the use of computation fluid dynamics (CFD) tools embedded in its computer-aided design (CAD) software to create a right mix of gas and air for a wide range of applications. The new tools provide the ability to evaluate the performance of many potential alternatives in the initial stages of the design process. Early stage analysis makes it possible to improve the performance of the product and resolve design problems quickly and before large sums have been spent on a design that must be changed. The review also discusses that several best practices can help ensure the accuracy of CFD gas and air mixing simulation. The utilization of native 3D data places a premium on the quality of the solid model. The newest generation of CFD software contains sophisticated automatic control functions that make it possible to converge to a solution in almost every application without the need for manual tuning. CFD simulation in the preliminary stages in the design of products involving gas mixing can save time and money. Best practices tuned for the requirements of a particular industry can help design engineers avoid analysis mistakes.
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Granell, Ignacio, Abel Ramos, and Alberto Carnicero. "A Geometry-Based Welding Distortion Prediction Tool." Materials 14, no. 17 (August 24, 2021): 4789. http://dx.doi.org/10.3390/ma14174789.
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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.
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Williams, A. J., D. G. Blair, R. Burman, M. Evans, R. Martin, P. V. Birch, M. P. Candy, et al. "Status of the Perth Observatory Automated Supernova Search Program." Publications of the Astronomical Society of Australia 9, no. 1 (1991): 84–85. http://dx.doi.org/10.1017/s132335800002498x.
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AbstractThe Perth Astronomy Research Group (PARG), consisting of members from Curtin University of Technology, Perth Observatory and the University of Western Australia, is in the process of developing an automated supernova search system, using the 61-cm Lowell-Perth reflector, a CCD camera and an 80386-based computer for image analysis. Computer control of the telescope and dome, a liquid-nitrogen-cooled CCD camera, and modified VISTA image analysis software will be completed in late 1990, allowing initial semi-automatic searching of external galaxies, together with CCD photometry of flare stars and newly discovered supernovae. Full-scale automation will be introduced subsequently, in collaboration with the Berkeley group. This paper describes the project, and reports on its current status.
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Fritz, Christian. "Automated Process Planning for CNC Machining." AI Magazine 37, no. 3 (October 7, 2016): 116–17. http://dx.doi.org/10.1609/aimag.v37i3.2665.
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This article describes our application of AI planning to the problem of automated process planning for machining parts, given raw stock and a CAD file describing the desired part geometry. We have found that existing planners from the AI community were falling short on several requirements, most importantly regarding the expressivity of state and action representations, and the ability to exploit domain-specific knowledge to prune the search space. In this article we describe the requirements we had in this application and what kind of results from the planning community helped us most. Overall, in this project as well as others, we found that even significant results from domain-independent planning may not be relevant in practice.
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Merkel, M., and A. Schumacher. "An Automated Optimization Process for a CAE Driven Product Development." Journal of Mechanical Design 125, no. 4 (December 1, 2003): 694–700. http://dx.doi.org/10.1115/1.1631570.
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Within the product development the need for generating design variants is given in many situations, for example to optimize an existing initial design with respect to new or modified requirements. For an efficient process it is essential that these variations can be done very easily within a small timeframe. In the virtual product development the physical characteristic of a component is determined by numerical simulation. Commercial software products exist for nearly each physical phenomenon. Often these methods are covered under CAE. A fundamental issue for building and analyzing variants easily and fast is a seamless interaction between the CAD and CAE software tools. This paper presents a powerful CAD/CAE sequence to the engineer’s community, where in contrast to other approaches results of the CAE analysis directly interact with CAD data. This strategy is supported by describing the product’s geometry by parameters. The CAD/CAE sequence is integrated in an optimization loop. The presented application example is an automotive part.
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Jones, Benjamin, Dalton Hildreth, Duowen Chen, Ilya Baran, Vladimir G. Kim, and Adriana Schulz. "AutoMate." ACM Transactions on Graphics 40, no. 6 (December 2021): 1–18. http://dx.doi.org/10.1145/3478513.3480562.
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Assembly modeling is a core task of computer aided design (CAD), comprising around one third of the work in a CAD workflow. Optimizing this process therefore represents a huge opportunity in the design of a CAD system, but current research of assembly based modeling is not directly applicable to modern CAD systems because it eschews the dominant data structure of modern CAD: parametric boundary representations (BREPs). CAD assembly modeling defines assemblies as a system of pairwise constraints, called mates , between parts, which are defined relative to BREP topology rather than in world coordinates common to existing work. We propose SB-GCN, a representation learning scheme on BREPs that retains the topological structure of parts, and use these learned representations to predict CAD type mates. To train our system, we compiled the first large scale dataset of BREP CAD assemblies, which we are releasing along with benchmark mate prediction tasks. Finally, we demonstrate the compatibility of our model with an existing commercial CAD system by building a tool that assists users in mate creation by suggesting mate completions, with 72.2% accuracy.
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Goto, Akira, Motohiko Nohmi, Takaki Sakurai, and Yoshiyasu Sogawa. "Hydrodynamic Design System for Pumps Based on 3-D CAD, CFD, and Inverse Design Method." Journal of Fluids Engineering 124, no. 2 (May 28, 2002): 329–35. http://dx.doi.org/10.1115/1.1471362.
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A computer-aided design system has been developed for hydraulic parts of pumps including impellers, bowl diffusers, volutes, and vaned return channels. The key technologies include three-dimensional (3-D) CAD modeling, automatic grid generation, CFD analysis, and a 3-D inverse design method. The design system is directly connected to a rapid prototyping production system and a flexible manufacturing system composed of a group of DNC machines. The use of this novel design system leads to a drastic reduction of the development time of pumps having high performance, high reliability, and innovative design concepts. The system structure and the design process of “Blade Design System” and “Channel Design System” are presented. Then the design examples are presented briefly based on the previous publications, which included a centrifugal impeller with suppressed secondary flows, a bowl diffuser with suppressed corner separation, a vaned return channel of a multistage pump, and a volute casing. The results of experimental validation, including flow fields measurements, were also presented and discussed briefly.
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Denkena, Berend, Marcel Wichmann, Klaas Maximilian Heide, and René Räker. "Laser Scanning Based Object Detection to Realize Digital Blank Shadows for Autonomous Process Planning in Machining." Journal of Manufacturing and Materials Processing 6, no. 1 (December 22, 2021): 1. http://dx.doi.org/10.3390/jmmp6010001.
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The automated process chain of an unmanned production system is a distinct challenge in the technical state of the art. In particular, accurate and fast raw-part recognition is a current problem in small-batch production. This publication proposes a method for automatic optical raw-part detection to generate a digital blank shadow, which is applied for adapted CAD/CAM (computer-aided design/computer-aided manufacturing) planning. Thereby, a laser-triangulation sensor is integrated into the machine tool. For an automatic raw-part detection and a workpiece origin definition, a dedicated algorithm for creating a digital blank shadow is introduced. The algorithm generates adaptive scan paths, merges laser lines and machine axis data, filters interference signals, and identifies part edges and surfaces according to a point cloud. Furthermore, a dedicated software system is introduced to investigate the created approach. This method is integrated into a CAD/CAM system, with customized software libraries for communication with the CNC (computer numerical control) machine. The results of this study show that the applied method can identify the positions, dimensions, and shapes of different raw parts autonomously, with deviations less than 1 mm, in 2.5 min. Moreover, the measurement and process data can be transferred without errors to different hardware and software systems. It was found that the proposed approach can be applied for rough raw-part detection, and in combination with a touch probe for accurate detection.
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Pajaziti, Endrit, Javier Montalt-Tordera, Claudio Capelli, Raphaël Sivera, Emilie Sauvage, Michael Quail, Silvia Schievano, and Vivek Muthurangu. "Shape-driven deep neural networks for fast acquisition of aortic 3D pressure and velocity flow fields." PLOS Computational Biology 19, no. 4 (April 24, 2023): e1011055. http://dx.doi.org/10.1371/journal.pcbi.1011055.
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Computational fluid dynamics (CFD) can be used to simulate vascular haemodynamics and analyse potential treatment options. CFD has shown to be beneficial in improving patient outcomes. However, the implementation of CFD for routine clinical use is yet to be realised. Barriers for CFD include high computational resources, specialist experience needed for designing simulation set-ups, and long processing times. The aim of this study was to explore the use of machine learning (ML) to replicate conventional aortic CFD with automatic and fast regression models. Data used to train/test the model consisted of 3,000 CFD simulations performed on synthetically generated 3D aortic shapes. These subjects were generated from a statistical shape model (SSM) built on real patient-specific aortas (N = 67). Inference performed on 200 test shapes resulted in average errors of 6.01% ±3.12 SD and 3.99% ±0.93 SD for pressure and velocity, respectively. Our ML-based models performed CFD in ∼0.075 seconds (4,000x faster than the solver). This proof-of-concept study shows that results from conventional vascular CFD can be reproduced using ML at a much faster rate, in an automatic process, and with reasonable accuracy.
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Lin, Yueh-Jaw, Rahul Mahabaleshwarkar, and Elena Massina. "CAD-based CMM dimensional inspection path planning – a generic algorithm." Robotica 19, no. 2 (March 2001): 137–48. http://dx.doi.org/10.1017/s0263574700003076.
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This paper describes a newly developed algorithm for CAD-based dimensional inspection path planning utilizing coordinate measuring machines (CMMs). The algorithm guarantees to provide optimum collision-free inspection probe paths by using the topological structure of the boundary representation (B-rep) solid CAD models of the inspected parts. A concept of automatic generation of optimum and collision free path in three dimensional space using available CAD database is proposed. The algorithm is generic for generating probe path over prismatic polyhedral parts. It serves as a principal part of the inspection path planning system. It is based on the modified ray tracing technique which uses a B-Rep data from any geometric modeling systems. Between start point and target point, an imaginary ray is established and if an intersection with part is encountered, an optimal detour path is created avoiding interference of the probe with the part. The generated path consists of linear segments joining start point and target point by various intermediate points. To locate these intermediate points in the consideration space, topological and geometrical structures of the part models are used at the time of decision making. To examine and implement the algorithm, a user-friendly application is developed employing AutoCAD Runtime Extension (ARX) development environment with object oriented programming (OOP) techniques, running on a Windows NT workstation. The effectiveness of the proposed algorithm is verified by the results of the implementation demonstrating optimum collision-free dimensional inspection path generation for four representative prismatic part models. All in all, this work contributes to the knowledge-base formation of automated dimensional inspection research area and paves a way for the integration of CMMs into a CAD/CAM environment, thus automate the process of design, manufacturing and quality assurance.
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Chan, V. H., C. Bradley, and G. W. Vickers. "A Multi-Sensor Approach for Rapid Digitization and Data Segmentation in Reverse Engineering." Journal of Manufacturing Science and Engineering 122, no. 4 (October 1, 1999): 725–33. http://dx.doi.org/10.1115/1.1286125.
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The development of a fully automated reverse engineering system currently faces two challenges; the time consuming digitization of the object due to the multi-view requirement of current industrial sensors and the conversion of copious amounts of 3-D cloud data into a compact form, compatible with CAD/CAM packages. An ideal reverse engineering system will automatically digitize the object from multiple viewpoints, segment the cloud data into constituent surface patches and generate an accurate solid model. The utilization of both a charged coupled device (CCD) camera and a 3-D laser digitizer, in the reverse engineering process, is a major step to attaining this goal. A neural network based segmentation algorithm is applied to stereo images for the location of the target object in the laser scanner work space and to generate the laser scanner path. The process automatically generates a description of an object’s surface which can be exported to a CAD/CAM package for design or manufacturing applications. [S1087-1357(00)00503-7]