Simulation of Mixing Induced by a Hot PAR Exhaust Plume

2012 ◽  
Author(s):  
Michele Andreani ◽  
Stephan Kelm
Keyword(s):  
Heat Source ◽  
Thermal Effect ◽  
Large Scale ◽  
Coarse Mesh ◽  
Mixing Process ◽  
Computational Tools ◽  
Simultaneous Injection ◽  
Exhaust Plume ◽  
Substantial Discrepancy ◽  
Ansys Cfx

Passive Autocatalytic Recombiners (PARs) are installed in various reactor containment designs to mitigate the hydrogen risk. For the evaluation of the effectiveness of these devices, validated computational tools are needed. To build confidence in the codes, their capability must also be assessed against separate effect tests addressing specific phenomena. Within the OECD SETH 2 project three experiments have been performed in the large-scale PANDA facility, where the thermal effect of a PAR was simulated by means of a heater and the plume generated by the heat source interacted with an initially stratified ambient. In these tests, helium was used instead of hydrogen. The position of the heater and the presence of simultaneous injection of steam were varied in these tests. These experiments have been analyzed with the GOTHIC and the ANSYS CFX codes. This paper reports only the results obtained with the GOTHIC code. In general, the GOTHIC code in conjunction with a coarse mesh could predict the mixing process reasonably well. The only substantial discrepancy with the experiments was the overprediction of the velocity at the inlet of the heater case, but this had little effect on the simulation of the overall mixing.

Experiments on Gas Mixing and Stratification Driven by Jets and Plumes in Large-Scale, Multi-Compartment Geometries

2006 ◽  
Author(s):  
Robert Zboray ◽  
Domenico Paladino ◽  
Olivier Auban
Keyword(s):  
High Resolution ◽  
Time Evolution ◽  
Large Scale ◽  
Nuclear Reactor ◽  
Safety Analysis ◽  
Mixing Process ◽  
Gas Mixing ◽  
Computational Tools ◽  
Different Gases

The present paper discusses experiments carried out to examine mixing of different gases (steam, air) and the evolution their distributions in large-scale, multi compartment geometry imitating nuclear reactor containment compartments. The flow and the mixing process in the experiments are driven by plumes and jets representing source structures with different momentum-to-buoyancy strength. The time evolution of the relevant parameters like gas concentrations, velocities and temperatures are followed using dedicated instrumentation. The data obtained is meant to be used for the validation and development of high-resolution, mainly CFD based, 3D computational tools for nuclear reactor containment safety analysis.

scholarly journals Advances in decomposing complex metabolite mixtures using substructure- and network-based computational metabolomics approaches

2021 ◽  
Author(s):  
Mehdi A. Beniddir ◽  
Kyo Bin Kang ◽  
Grégory Genta-Jouve ◽  
Florian Huber ◽  
Simon Rogers ◽  
...  
Keyword(s):  
Natural Product ◽  
Large Scale ◽  
Scale Analysis ◽  
Computational Tools ◽  
Natural Product Discovery ◽  
Large Scale Analysis ◽  
Metabolite Annotation

This review highlights the key computational tools and emerging strategies for metabolite annotation, and discusses how these advances will enable integrated large-scale analysis to accelerate natural product discovery.

A large-scale soil-mixing process for reclamation of heavily disturbed soils

2017 ◽  
Vol 109 ◽  
pp. 84-91 ◽  
Author(s):  
Peter L. O’Brien ◽  
Thomas M. DeSutter ◽  
Samantha S. Ritter ◽  
Francis X.M. Casey ◽  
Abbey F. Wick ◽  
...  
Keyword(s):  
Large Scale ◽  
Mixing Process ◽  
Soil Mixing ◽  
Disturbed Soils

scholarly journals The daunting polygenicity of mental illness: making a new map

2018 ◽  
Vol 373 (1742) ◽  
pp. 20170031 ◽  
Author(s):  
Steven E. Hyman
Keyword(s):  
Mental Health ◽  
Large Scale ◽  
Computational Models ◽  
Model Organisms ◽  
Human Biology ◽  
Genetic Studies ◽  
Computational Tools ◽  
Experimental Systems ◽  
Terra Incognita ◽  
Phenotypic Complexity

An epochal opportunity to elucidate the pathogenic mechanisms of psychiatric disorders has emerged from advances in genomic technology, new computational tools and the growth of international consortia committed to data sharing. The resulting large-scale, unbiased genetic studies have begun to yield new biological insights and with them the hope that a half century of stasis in psychiatric therapeutics will come to an end. Yet a sobering picture is coming into view; it reveals daunting genetic and phenotypic complexity portending enormous challenges for neurobiology. Successful exploitation of results from genetics will require eschewal of long-successful reductionist approaches to investigation of gene function, a commitment to supplanting much research now conducted in model organisms with human biology, and development of new experimental systems and computational models to analyse polygenic causal influences. In short, psychiatric neuroscience must develop a new scientific map to guide investigation through a polygenic terra incognita . This article is part of a discussion meeting issue ‘Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists’.

scholarly journals TADOSS: computational estimation of tandem domain swap stability

2018 ◽  
Vol 35 (14) ◽  
pp. 2507-2508 ◽  
Author(s):  
Aleix Lafita ◽  
Pengfei Tian ◽  
Robert B Best ◽  
Alex Bateman
Keyword(s):  
Large Scale ◽  
Domain Swapping ◽  
Coarse Grained ◽  
Supplementary Information ◽  
Simulation Studies ◽  
Computational Tools ◽  
Domain Swap ◽  
Computational Estimation ◽  
High Propensity ◽  
The Stability

Abstract Summary Proteins with highly similar tandem domains have shown an increased propensity for misfolding and aggregation. Several molecular explanations have been put forward, such as swapping of adjacent domains, but there is a lack of computational tools to systematically analyze them. We present the TAndem DOmain Swap Stability predictor (TADOSS), a method to computationally estimate the stability of tandem domain-swapped conformations from the structures of single domains, based on previous coarse-grained simulation studies. The tool is able to discriminate domains susceptible to domain swapping and to identify structural regions with high propensity to form hinge loops. TADOSS is a scalable method and suitable for large scale analyses. Availability and implementation Source code and documentation are freely available under an MIT license on GitHub at https://github.com/lafita/tadoss. Supplementary information Supplementary data are available at Bioinformatics online.

Adaptive-Curvature Structures with Auxetic Materials

2018 ◽  
Vol 1149 ◽  
pp. 53-63
Author(s):  
Roberto Naboni ◽  
Stefano Sartori ◽  
Lorenzo Mirante
Keyword(s):  
Large Scale ◽  
Morphological Features ◽  
Geometrical Parameters ◽  
Computational Tools ◽  
Auxetic Materials ◽  
Initial Geometry ◽  
Tools And Methods

Advancements in computational tools are offering designers the possibility to change their relationship with materials and establishing new synergies between matter, form and behaviour. This work explores this paradigm by introducing the use of auxetic metamaterials, specifically engineered to obtain properties beyond those found in nature, to generate structures with adaptive curvature obtained from planar construction elements. It is discussed how through programming an initial geometry with the strategic negotiation of several geometrical parameters it is possible to control finely the structural and morphological features of a structure. The paper presents approach, tools and methods for designing auxetics for large scale applications, and use them to create heterogeneous active-bending structures.

Predicting mesh density for adaptive modelling of the global atmosphere

2009 ◽  
Vol 367 (1907) ◽  
pp. 4523-4542 ◽  
Author(s):  
Hilary Weller
Keyword(s):  
Shallow Water ◽  
Shallow Water Equations ◽  
Large Scale ◽  
Mesh Adaptation ◽  
Similar Proportion ◽  
Test Case ◽  
Uniform Mesh ◽  
Coarse Mesh ◽  
Mesh Density ◽  
The Cost

The shallow water equations are solved using a mesh of polygons on the sphere, which adapts infrequently to the predicted future solution. Infrequent mesh adaptation reduces the cost of adaptation and load-balancing and will thus allow for more accurate mapping on adaptation. We simulate the growth of a barotropically unstable jet adapting the mesh every 12 h. Using an adaptation criterion based largely on the gradient of the vorticity leads to a mesh with around 20 per cent of the cells of a uniform mesh that gives equivalent results. This is a similar proportion to previous studies of the same test case with mesh adaptation every 1–20 min. The prediction of the mesh density involves solving the shallow water equations on a coarse mesh in advance of the locally refined mesh in order to estimate where features requiring higher resolution will grow, decay or move to. The adaptation criterion consists of two parts: that resolved on the coarse mesh, and that which is not resolved and so is passively advected on the coarse mesh. This combination leads to a balance between resolving features controlled by the large-scale dynamics and maintaining fine-scale features.

scholarly journals REVA as a Well-curated Database for Human Expression-modulating Variants

2021 ◽  
Author(s):  
Yu Wang ◽  
Fang-Yuan Shi ◽  
Yu Liang ◽  
Ge Gao
Keyword(s):  
Large Scale ◽  
Regulatory Mechanism ◽  
State Of The Art ◽  
Scale Analysis ◽  
Computational Tools ◽  
Functional Annotations ◽  
Link Type ◽  
Large Scale Analysis ◽  
Multiple State ◽  
Limited Sensitivity

AbstractMore than 80% of disease- and trait-associated human variants are noncoding. By systematically screening multiple large-scale studies, we compiled REVA, a manually curated database for over 11.8 million experimentally tested noncoding variants with expression-modulating potentials. We provided 2424 functional annotations that could be used to pinpoint plausible regulatory mechanism of these variants. We further benchmarked multiple state-of-the-art computational tools and found their limited sensitivity remains a serious challenge for effective large-scale analysis. REVA provides high-qualify experimentally tested expression-modulating variants with extensive functional annotations, which will be useful for users in the noncoding variants community. REVA is available at http://reva.gao-lab.org.

scholarly journals Large-Scale Flow in Micro Electrokinetic Turbulent Mixer

Micromachines ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 813 ◽  
Author(s):  
Keyi Nan ◽  
Zhongyan Hu ◽  
Wei Zhao ◽  
Kaige Wang ◽  
Jintao Bai ◽  
...  
Keyword(s):  
Flow Field ◽  
Electric Conductivity ◽  
Large Scale ◽  
Three Dimensional ◽  
Mixing Process ◽  
Mean Flow ◽  
Velocity Fluctuations ◽  
Two Fluids ◽  
Large Scale Flow ◽  
Particle Imaging

In the present work, we studied the three-dimensional (3D) mean flow field in a micro electrokinetic (μEK) turbulence based micromixer by micro particle imaging velocimetry (μPIV) with stereoscopic method. A large-scale solenoid-type 3D mean flow field has been observed. The extraordinarily fast mixing process of the μEK turbulent mixer can be primarily attributed to two steps. First, under the strong velocity fluctuations generated by μEK mechanism, the two fluids with different conductivity are highly mixed near the entrance, primarily at the low electric conductivity sides and bias to the bottom wall. Then, the well-mixed fluid in the local region convects to the rest regions of the micromixer by the large-scale solenoid-type 3D mean flow. The mechanism of the large-scale 3D mean flow could be attributed to the unbalanced electroosmotic flows (EOFs) due to the high and low electric conductivity on both the bottom and top surface.

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