Importance of microstructure modeling for additively manufactured metal post-process simulations

2021 ◽  
Vol 166 ◽  
pp. 103515
Author(s):  
Sumair Sunny ◽  
Glenn Gleason ◽  
Karl Bailey ◽  
Ritin Mathews ◽  
Arif Malik
2011 ◽  
Vol 29 ◽  
pp. 51-59 ◽  
Author(s):  
L. Zhao ◽  
Q. Duan ◽  
J. Schaake ◽  
A. Ye ◽  
J. Xia

Abstract. This paper evaluates the performance of a statistical post-processor for imperfect hydrologic model forecasts. Assuming that the meteorological forecasts are well-calibrated, we employ a "General Linear Model (GLM)" to post-process simulations produced by a hydrologic model. For a particular forecast date, the observations and simulations from an "analysis window" and hydrologic model forecasts for a "forecast window", the GLM Post-Processor (GLMPP) is used to produce an ensemble of predictions of the streamflow observations that will occur during the "forecast window". The objectives of the GLMPP are to: (1) preserve any skill in the original hydrologic ensemble forecast; (2) correct systematic model biases; (3) retain the equal-likelihood assumption for the ensemble; (4) preserve temporal scale dependency relationships in streamflow hydrographs and the uncertainty in the predictions; and, (5) produce reliable ensemble predictions. Observed and simulated daily streamflow data from the Second Workshop on Model Parameter Estimation Experiment (MOPEX) are used to test how well these objectives are met when the GLMPP is applied to ensemble hydrologic forecasts driven by well calibrated meteorological forecasts. A 39-year hydrologic dataset from the French Broad basin is split into calibration and verification periods. The results show that the GLMPP built using data from the calibration period removes the mean bias when applied to hydrologic model simulations from both the calibration and verification periods. Probability distributions of the post-processed model simulations are shown to be closer to the climatological probability distributions of observed streamflow than the distributions of the unadjusted simulated flows. A number of experiments with different GLMPP configurations were also conducted to examine the effects of different configurations for forecast and analysis window lengths on the robustness of the results.


2012 ◽  
Vol 17 (4) ◽  
pp. 207-216 ◽  
Author(s):  
Magdalena Szymczyk ◽  
Piotr Szymczyk

Abstract The MATLAB is a technical computing language used in a variety of fields, such as control systems, image and signal processing, visualization, financial process simulations in an easy-to-use environment. MATLAB offers "toolboxes" which are specialized libraries for variety scientific domains, and a simplified interface to high-performance libraries (LAPACK, BLAS, FFTW too). Now MATLAB is enriched by the possibility of parallel computing with the Parallel Computing ToolboxTM and MATLAB Distributed Computing ServerTM. In this article we present some of the key features of MATLAB parallel applications focused on using GPU processors for image processing.


2020 ◽  
pp. 607-612
Author(s):  
Bernard Coûteaux

This paper elaborates on the key solutions offered by De Smet Engineers & Contractors (DSEC) to optimize the efficiency of cane sugar producing and processing facilities. In order to meet customer needs, DSEC offers proprietary predictive models built using the latest versions of specialized software. These models allow factory managers to envision the whole picture of increased operational and capital efficiency before it becomes reality. An integrated energy model and the CAPEX/OPEX evaluation method are discussed as ways to estimate and optimize costs, both for new greenfield projects and revamping of existing factories. The models demonstrate that factory capacities can be successfully increased using equipment that is already available. Special attention is paid to crystallization and centrifugation process simulations and the potential improvement of the global energy balance. One case study shows the transformation of a beet sugar factory into a refinery to process raw cane sugar after beet crop season and the second case shows the integration of a refinery into a cane sugar factory. The primary focus of the article is optimization of the technological process through predictive modelling. DSEC’s suggested solutions, which lead to great improvements in a plant’s efficiency and its ability to obtain very low energy consumption, are discussed.


2021 ◽  
Author(s):  
Amir Al Ghatta ◽  
James D. E. T. Wilton-Ely ◽  
Jason P. Hallett

Process simulations allow the evaluation of the emissions and selling price for the production of the key monomer FDCA based on different feedstocks and solvent systems, alongside considerations of safety and current process development.


Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2197
Author(s):  
Nayara Rodrigues Marques Sakiyama ◽  
Jurgen Frick ◽  
Timea Bejat ◽  
Harald Garrecht

Predicting building air change rates is a challenge for designers seeking to deal with natural ventilation, a more and more popular passive strategy. Among the methods available for this task, computational fluid dynamics (CFD) appears the most compelling, in ascending use. However, CFD simulations require a range of settings and skills that inhibit its wide application. With the primary goal of providing a pragmatic CFD application to promote wind-driven ventilation assessments at the design phase, this paper presents a study that investigates natural ventilation integrating 3D parametric modeling and CFD. From pre- to post-processing, the workflow addresses all simulation steps: geometry and weather definition, including incident wind directions, a model set up, control, results’ edition, and visualization. Both indoor air velocities and air change rates (ACH) were calculated within the procedure, which used a test house and air measurements as a reference. The study explores alternatives in the 3D design platform’s frame to display and compute ACH and parametrically generate surfaces where air velocities are computed. The paper also discusses the effectiveness of the reference building’s natural ventilation by analyzing the CFD outputs. The proposed approach assists the practical use of CFD by designers, providing detailed information about the numerical model, as well as enabling the means to generate the cases, visualize, and post-process the results.


Polymers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 622
Author(s):  
Krzysztof Wilczyński ◽  
Kamila Buziak ◽  
Adrian Lewandowski ◽  
Andrzej Nastaj ◽  
Krzysztof J. Wilczyński

Wood polymer composites are materials with pseudoplastic and viscoelastic properties. They have yield stress and exhibit slip during flow. Studies on extrusion and rheology, as well as on process modeling of these highly filled materials are limited. Extensive rheological and extrusion modeling studies on the wood polymer composite based on the polypropylene matrix were performed. Viscous and slip flow properties were determined (with Rabinowitsch, Bagley, and Mooney corrections) at broad (extrusion) range of shear rate and temperature, using a high-pressure capillary rheometer. Rheological models of Klein and power-law were used for flow modeling, and Navier model was applied for slip modeling. A novel global computer model of WPC extrusion with slip effects has been developed, and process simulations were performed to compute the extrusion parameters (throughput, power consumption, pressure, temperature, etc.), and to study the effect of the material rheological characteristics on the process flow. Simulations were validated experimentally, and were discussed with respect to both rheological and process modeling aspects. It was concluded that the location of the operating point of extrusion process, which defines the thermo-mechanical process conditions, is fundamentally dependent on the rheological materials characteristics, including slip effects.


2021 ◽  
Vol 11 (4) ◽  
pp. 1794
Author(s):  
Luke Stone ◽  
Stefan Zigan ◽  
Lahiru L. Lulbadda Waduge ◽  
David B. Hastie

Traditionally, when undertaking feasibility studies for designing new storage facilities such as storage silos, engineers will extract design information from experiments and evaluate potential risks associated with health and safety, suitability design for reliable material flow, and quality of products. The simulation approach applied incorporates Computational Fluid Dynamics (CFD), and Discrete Element Modelling (DEM) approaches and experimental tests will be used for validating these simulation results. One important aspect related to handling fine and dusty materials (particles smaller than 100 microns) is the associated risk of dust explosions, which needs to be evaluated before the commissioning of storage silos; to evaluate the accumulation of fines during the silo filling process, simulations and experiments were conducted. Alumina and salt were used here as reference materials for calibration and the validation purposes. The validation efforts are significant due to the fact that the data that is accessible in simulations is vastly different to the accessible data in experiments, which is restricted by measurement techniques and equipment. Such restrictions are observed in the evaluation of particle concentrations in a large confined volume. A new methodology has been developed to evaluate concentrations in both simulations and experiments by employing a non-dimensional factor [k], here called “Concentration Rank Factor” (CRF). A significant finding of this research is that experiments and simulations can be compared using CRF. It has been found to be within 2% of the experiment averaged value of 0.64.


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