scholarly journals Numerical Simulation of Ammonothermal Crystal Growth of GaN—Current State, Challenges, and Prospects

Crystals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 356
Author(s):  
Saskia Schimmel ◽  
Daisuke Tomida ◽  
Tohru Ishiguro ◽  
Yoshio Honda ◽  
Shigefusa Chichibu ◽  
...  
Keyword(s):  
Crystal Growth ◽  
Numerical Simulations ◽  
Numerical Models ◽  
Physical Models ◽  
Model Systems ◽  
Experimental Investigations ◽  
Process Conditions ◽  
Design And Optimization ◽  
Bulk Gan ◽  
Ammonothermal Growth

Numerical simulations are a valuable tool for the design and optimization of crystal growth processes because experimental investigations are expensive and access to internal parameters is limited. These technical limitations are particularly large for ammonothermal growth of bulk GaN, an important semiconductor material. This review presents an overview of the literature on simulations targeting ammonothermal growth of GaN. Approaches for validation are also reviewed, and an overview of available methods and data is given. Fluid flow is likely in the transitional range between laminar and turbulent; however, the time-averaged flow patterns likely tend to be stable. Thermal boundary conditions both in experimental and numerical research deserve more detailed evaluation, especially when designing numerical or physical models of the ammonothermal growth system. A key source of uncertainty for calculations is fluid properties under the specific conditions. This originates from their importance not only in numerical simulations but also in designing similar physical model systems and in guiding the selection of the flow model. Due to the various sources of uncertainty, a closer integration of numerical modeling, physical modeling, and the use of measurements under ammonothermal process conditions appear to be necessary for developing numerical models of defined accuracy.

scholarly journals Behavior of Beam-to-Column Connections with Angles. Part 2-Numerical Analysis

2016 ◽  
Vol 6 (1) ◽  
pp. 35-40
Author(s):  
M. Ghindea ◽  
A. Cătărig ◽  
R. Ballok
Keyword(s):  
Numerical Simulations ◽  
Deformation Process ◽  
High Speed ◽  
Rotation Curve ◽  
Numerical Models ◽  
Experimental Tests ◽  
3D Models ◽  
Experimental Investigations ◽  
Software Packages ◽  
Parametric Studies

Abstract Based on the results of experimental tests, presented in the first part of this paper, Part 1-Experimental Investigations (Ghindea M., Catarig A., Ballok R.) advanced numerical simulations were performed using FEM based software Abaqus. The recently arise of high speed computers and advanced FEM software packages allow to create and solve extensively detailed 3D models. The aim of this second part of the paper is to develop accurate FEM models for better approach of the studied beam-to-column connections. The paper presents the designed numerical models and the results for four bolted beam-to-column connections using top-and-seat and/or web angle cleats, in different configurations. The objective of this paper is to achieve functional numerical models which, by faithfully running, reproduce the experimental results. Thus, calibrating the numerical results with the experimental ones it can be perform then parametric studies, achieving reliable results for similar configurations of joints. The results obtained after numerical simulations were compared with experimental data. The behavior moment-rotation curve and the deformation process of the experimental captured specimens were virtually reproduced with minimum deviation.

Experimental Investigations and Numerical Simulations of the Viscous Flow around T-Profiles

2013 ◽  
Vol 332 ◽  
pp. 3-8
Author(s):  
Mihai Schiaua ◽  
Andrei Dragomirescu ◽  
Carmen Anca Safta
Keyword(s):  
Viscous Fluid ◽  
Numerical Simulations ◽  
Viscous Flow ◽  
Vortex Shedding ◽  
Flow Measurement ◽  
Numerical Models ◽  
Vortex Street ◽  
Open Channels ◽  
Experimental Investigations ◽  
Main Interest

This paper investigates both experimentally and numerically the flow of a viscous fluid around T-profiles, i.e. T-shaped bodies, having different geometries. Of main interest it was the vortex shedding behind the T-profiles with an eye towards its application to flow measurement in open channels. Another purpose of the study was to assess to what extent different numerical models can be used to accurately predict the flow in the vortex street behind T-profiles.

Identifying Physico-Chemical Laws from the Robotically Collected Data

2019 ◽  
Author(s):  
Liwei Cao ◽  
Danilo Russo ◽  
Vassilios S. Vassiliadis ◽  
Alexei Lapkin
Keyword(s):  
Experimental Data ◽  
Numerical Models ◽  
Predictor Variable ◽  
Physical Models ◽  
Training Data ◽  
Mixed Integer ◽  
Physico Chemical ◽  
Data Points ◽  
Future Work ◽  
The Relationship

<p>A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor variables and training data points. The globally optimal search was extended to identify physical models and to cope with noise in the experimental data predictor variable. The methodology was coupled with the collection of experimental data in an automated fashion, and was proven to be successful in identifying the correct physical models describing the relationship between the shear stress and shear rate for both Newtonian and non-Newtonian fluids, and simple kinetic laws of reactions. Future work will focus on addressing the limitations of the formulation presented in this work, by extending it to be able to address larger complex physical models.</p><p><br></p>

scholarly journals Two-Dimensional Numerical Modeling of Flow in Physical Models of Rock Vane and Bendway Weir Configurations

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 458
Author(s):  
Drew C. Baird ◽  
Benjamin Abban ◽  
S. Michael Scurlock ◽  
Steven B. Abt ◽  
Christopher I. Thornton
Keyword(s):  
Numerical Modeling ◽  
Physical Model ◽  
Numerical Models ◽  
Hydraulic Performance ◽  
Physical Models ◽  
Protection Measures ◽  
Design Engineers ◽  
Model Study ◽  
Study Results ◽  
Wide Range

While there are a wide range of design recommendations for using rock vanes and bendway weirs as streambank protection measures, no comprehensive, standard approach is currently available for design engineers to evaluate their hydraulic performance before construction. This study investigates using 2D numerical modeling as an option for predicting the hydraulic performance of rock vane and bendway weir structure designs for streambank protection. We used the Sedimentation and River Hydraulics (SRH)-2D depth-averaged numerical model to simulate flows around rock vane and bendway weir installations that were previously examined as part of a physical model study and that had water surface elevation and velocity observations. Overall, SRH-2D predicted the same general flow patterns as the physical model, but over- and underpredicted the flow velocity in some areas. These over- and underpredictions could be primarily attributed to the assumption of negligible vertical velocities. Nonetheless, the point differences between the predicted and observed velocities generally ranged from 15 to 25%, with some exceptions. The results showed that 2D numerical models could provide adequate insight into the hydraulic performance of rock vanes and bendway weirs. Accordingly, design guidance and implications of the study results are presented for design engineers.

scholarly journals An Alternative Statistical Model for Predicting Salinity Variations in Estuaries

2020 ◽  
Vol 12 (24) ◽  
pp. 10677
Author(s):  
Ronghui Ye ◽  
Jun Kong ◽  
Chengji Shen ◽  
Jinming Zhang ◽  
Weisheng Zhang
Keyword(s):  
Statistical Model ◽  
River Discharge ◽  
Numerical Models ◽  
Low Cost ◽  
River Estuary ◽  
Pearl River Estuary ◽  
Large River ◽  
Physical Models ◽  
Long Term Effects ◽  
Salinity Variations

Accurate salinity prediction can support the decision-making of water resources management to mitigate the threat of insufficient freshwater supply in densely populated estuaries. Statistical methods are low-cost and less time-consuming compared with numerical models and physical models for predicting estuarine salinity variations. This study proposes an alternative statistical model that can more accurately predict the salinity series in estuaries. The model incorporates an autoregressive model to characterize the memory effect of salinity and includes the changes in salinity driven by river discharge and tides. Furthermore, the Gamma distribution function was introduced to correct the hysteresis effects of river discharge, tides and salinity. Based on fixed corrections of long-term effects, dynamic corrections of short-term effects were added to weaken the hysteresis effects. Real-world model application to the Pearl River Estuary obtained satisfactory agreement between predicted and measured salinity peaks, indicating the accuracy of salinity forecasting. Cross-validation and weekly salinity prediction under small, medium and large river discharges were also conducted to further test the reliability of the model. The statistical model provides a good reference for predicting salinity variations in estuaries.

Phase equilibria modeling of biorefinery-related systems: a systematic review

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Marcos L. Corazza ◽  
Julia Trancoso
Keyword(s):  
Phase Equilibria ◽  
Phase Behavior ◽  
Fossil Fuel ◽  
Process Conditions ◽  
Design And Optimization ◽  
Waste Reuse ◽  
Wide Range ◽  
Prisma Statement ◽  
Fuel Substitution ◽  
The Subject

Abstract The search for sustainable ideas has gained prominence in recent decades at all levels of society since it has become imperative an economic, social, and environmental development in an integrated manner. In this context, biorefineries are currently present as the technology that best covers all these parameters, as they add the benefits of waste reuse, energy cogeneration, and fossil fuel substitution. Thus, the study of the various applicable biological matrices and exploring the technical capabilities of these processes become highly attractive. Thermodynamic modeling acts in this scenario as a fundamental tool for phase behavior predictions in process modeling, design, and optimization. Thus, this work aimed to systematize, using the PRISMA statement for systematic reviews, the information published between 2010 and 2020 on phase equilibria modeling in systems related to biorefineries to organize what is already known about the subject. As a result, 236 papers were categorized in terms of the year, country, type of phase equilibria, and thermodynamic model used. Also, the phase behavior predictions of different thermodynamic models under the same process conditions were qualitatively compared, establishing PC-SAFT as the model that best represents the great diversity of interest systems for biorefineries in a wide range of conditions.

Advanced Virtual Prototyping of Axial Piston Machines

2016 ◽  
Author(s):  
Rene Chacon ◽  
Monika Ivantysynova
Keyword(s):  
Numerical Models ◽  
Virtual Prototyping ◽  
Valve Plate ◽  
Cylinder Block ◽  
Plate Interface ◽  
Design And Optimization ◽  
Swash Plate ◽  
Axial Piston Machine ◽  
Axial Piston ◽  
Plate Type

This paper explains how a combination of advanced multidomain numerical models can be employed to design an axial piston machine of swash plate type within a virtual prototyping environment. Examples for the design and optimization of the cylinder block/valve plate interface are presented.

Leakage Flow Investigations on a Through-Wall Crack Related to Thermal Fatigue of Nuclear Power Plant Piping

2017 ◽  
Author(s):  
Stefan Schmid ◽  
Rudi Kulenovic ◽  
Eckart Laurien
Keyword(s):  
Experimental Data ◽  
Nuclear Power ◽  
Numerical Models ◽  
Measurement Techniques ◽  
Experimental Investigations ◽  
Leakage Flow ◽  
Test Rig ◽  
Reduced Pressure ◽  
Flow Rates ◽  
Set Up

For the validation of empirical models to calculate leakage flow rates in through-wall cracks of piping, reliable experimental data are essential. In this context, the Leakage Flow (LF) test rig was built up at the IKE for measurements of leakage flow rates with reduced pressure (maximum 1 MPA) and temperature (maximum 170 °C) compared to real plant conditions. The design of the test rig enables experimental investigations of through-wall cracks with different geometries and orientations by means of circular blank sheets with integrated cracks which are installed in the tubular test section of the test rig. In the paper, the experimental LF set-up and used measurement techniques are explained in detail. Furthermore, first leakage flow measurement results for one through-wall crack geometry and different imposed fluid pressures at ambient temperature conditions are presented and discussed. As an additional aspect the experimental data are used for the determination of the flow resistance of the investigated leak channel. Finally, the experimental results are compared with numerical results of WinLeck calculations to prove specifically in WinLeck implemented numerical models.

Accelerating Climate Model Computation by Neural Networks: A Comparative Study

2021 ◽  
Author(s):  
Maha Mdini ◽  
Takemasa Miyoshi ◽  
Shigenori Otsuka
Keyword(s):  
Neural Networks ◽  
Computational Complexity ◽  
Statistical Model ◽  
Physical Model ◽  
Climate Model ◽  
Numerical Models ◽  
Computation Time ◽  
High Accuracy ◽  
Physical Models ◽  
Computer Resources

&lt;p&gt;In the era of modern science, scientists have developed numerical models to predict and understand the weather and ocean phenomena based on fluid dynamics. While these models have shown high accuracy at kilometer scales, they are operated with massive computer resources because of their computational complexity.&amp;#160; In recent years, new approaches to solve these models based on machine learning have been put forward. The results suggested that it be possible to reduce the computational complexity by Neural Networks (NNs) instead of classical numerical simulations. In this project, we aim to shed light upon di&amp;#64256;erent ways to accelerating physical models using NNs. We test two approaches: Data-Driven Statistical Model (DDSM) and Hybrid Physical-Statistical Model (HPSM) and compare their performance to the classical Process-Driven Physical Model (PDPM). DDSM emulates the physical model by a NN. The HPSM, also known as super-resolution, uses a low-resolution version of the physical model and maps its outputs to the original high-resolution domain via a NN. To evaluate these two methods, we measured their accuracy and their computation time. Our results of idealized experiments with a quasi-geostrophic model [SO3] show that HPSM reduces the computation time by a factor of 3 and it is capable to predict the output of the physical model at high accuracy up to 9.25 days. The DDSM, however, reduces the computation time by a factor of 4 and can predict the physical model output with an acceptable accuracy only within 2 days. These &amp;#64257;rst results are promising and imply the possibility of bringing complex physical models into real time systems with lower-cost computer resources in the future.&lt;/p&gt;

Northeast Atlantic storminess in centennial reanalyses

2021 ◽  
Author(s):  
Oliver Krueger ◽  
Frauke Feser ◽  
Christopher Kadow ◽  
Ralf Weisse
Keyword(s):  
Climate Models ◽  
Numerical Models ◽  
Geostrophic Wind ◽  
Model Systems ◽  
Storm Activity ◽  
Northeast Atlantic ◽  
Wind Speeds ◽  
Long Term Trends ◽  
Storm Index

&lt;p&gt;Global atmospheric reanalyses are commonly applied for the validation of climate models, diagnostic studies, and driving higher resolution numerical models with the emphasis on assessing climate variability and long-term trends. Over recent years, longer reanalyses spanning a period of more than hundred years have become available. In this study, the variability and long-term trends of storm activity is assessed over the northeast Atlantic in modern centennial reanalysis datasets, namely ERA-20cm, ERA-20c, CERA-20c, and the 20CR-reanalysis suite with 20CRv3 being the most recent one. All reanalyses, except from ERA-20cm, assimilate surface pressure observations, whereby ERA-20C and CERA-20c additionally assimilate surface winds. For the assessment, the well-established storm index of higher annual percentiles of geostrophic wind speeds derived from pressure observations at sea level over a relatively densely monitored marine area is used.&lt;/p&gt;&lt;p&gt;The results indicate that the examined centennial reanalyses are not able to represent long-term trends of storm activity over the northeast Atlantic, particularly in the earlier years of the period examined when compared with the geostrophic wind index based on pressure observations. Moreover, the reanalyses show inconsistent long-term behaviour when compared with each other. Only in the latter half of the 20th century, the variability of reanalysed and observed storminess time series starts to agree with each other. Additionally, 20CRv3, the most recent centennial reanalysis examined, shows markedly improved results with increased uncertainty, albeit multidecadal storminess variability does not match observed values in earlier times before about 1920.&lt;/p&gt;&lt;p&gt;The behaviour shown by the centennial reanalyses are likely caused by the increasing number of assimilated observations, changes in the observational databases used, and the different underlying numerical model systems. Furthermore, the results derived from the ERA-20cm reanalysis that does not assimilate any pressure or wind observations suggests that the variability and uncertainty of storminess over the northeast Atlantic is high making it difficult to determine storm activity when numerical models are not bound by observations. The results of this study imply and reconfirm previous findings that the assessment of long-term storminess trends and variability in centennial reanalyses remains a rather delicate matter, at least for the northeast Atlantic region.&lt;/p&gt;

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