scholarly journals Thermal-Hydraulic Investigations of a Horizontal Dry Cask Simulator

2020 ◽  
Author(s):  
Ramon J. M. Pulido ◽  
Eric R. Lindgren ◽  
Samuel G. Durbin ◽  
Alex Salazar
Keyword(s):  
Best Practices ◽  
Thermal Loading ◽  
Spent Nuclear Fuel ◽  
Data Sets ◽  
Temperature Profiles ◽  
Benchmark Data ◽  
Axial Temperature ◽  
Wide Range ◽  
Cooling Air Flow ◽  
Cooling Air

Abstract Recent advances in horizontal cask designs for commercial spent nuclear fuel have significantly increased maximum thermal loading. This is due in part to greater efficiency in internal conduction pathways. Carefully measured data sets generated from testing of full-sized casks or smaller cask analogs are widely recognized as vital for validating thermal-hydraulic models of these storage cask designs. While several testing programs have been previously conducted, these earlier validation studies did not integrate all the physics or components important in a modern, horizontal dry cask system. The purpose of this investigation is to produce data sets that can be used to benchmark the codes and best practices presently used to calculate cladding temperatures and induced cooling air flows in modern, horizontal dry storage systems. The horizontal dry cask simulator (HDCS) has been designed to generate this benchmark data and complement the existing knowledge base. Transverse and axial temperature profiles along with induced-cooling air flow are measured using various backfills of gases for a wide range of decay powers and canister pressures. The data from the HDCS tests will be used to host a blind model validation effort.

scholarly journals CAMISIM: Simulating metagenomes and microbial communities

2018 ◽  
Author(s):  
Adrian Fritz ◽  
Peter Hofmann ◽  
Stephan Majda ◽  
Eik Dahms ◽  
Johannes Dröge ◽  
...  
Keyword(s):  
Microbial Communities ◽  
De Novo ◽  
Real Data ◽  
Small Data ◽  
Data Sets ◽  
Sequencing Data ◽  
Taxonomic Profiling ◽  
Benchmark Data ◽  
Sequencing Technologies ◽  
Wide Range

Shotgun metagenome data sets of microbial communities are highly diverse, not only due to the natural variation of the underlying biological systems, but also due to differences in laboratory protocols, replicate numbers, and sequencing technologies. Accordingly, to effectively assess the performance of metagenomic analysis software, a wide range of benchmark data sets are required. Here, we describe the CAMISIM microbial community and metagenome simulator. The software can model different microbial abundance profiles, multi-sample time series and differential abundance studies, includes real and simulated strain-level diversity, and generates second and third generation sequencing data from taxonomic profiles or de novo. Gold standards are created for sequence assembly, genome binning, taxonomic binning, and taxonomic profiling. CAMSIM generated the benchmark data sets of the first CAMI challenge. For two simulated multi-sample data sets of the human and mouse gut microbiomes we observed high functional congruence to the real data. As further applications, we investigated the effect of varying evolutionary genome divergence, sequencing depth, and read error profiles on two popular metagenome assemblers, MEGAHIT and metaSPAdes, on several thousand small data sets generated with CAMISIM. CAMISIM can simulate a wide variety of microbial communities and metagenome data sets together with truth standards for method evaluation. All data sets and the software are freely available at: https://github.com/CAMI-challenge/CAMISIM

Coupling of Convective and Radiative Heat Transfer in PV Cooling Ducts

2002 ◽  
Vol 124 (3) ◽  
pp. 250-255 ◽  
Author(s):  
B. J. Brinkworth
Keyword(s):  
Heat Transfer ◽  
Turbulent Flows ◽  
Radiative Heat ◽  
Radiation Exchange ◽  
Axial Temperature ◽  
Pv Cooling ◽  
Cooling Air Flow ◽  
Cooling Air ◽  
Cooling Ducts ◽  
Laminar And Turbulent Flows

In a PV cooling duct, heat transfer from the heated side to the cooling air flow takes place partly by convection at the walls and partly by radiation exchange between them. A method is developed for representing these effects in combination, avoiding the uncertainties and iterations involved in treating the two mechanisms as independent and parallel. Though the radiative element introduces two further parameters, the procedure has a straightforward closed form, convenient for routine engineering calculations. An approximation, that treats the radiation exchange as determined by the local wall temperatures, is validated by comparison with published results in which the diffusion due to the axial temperature distribution is fully represented. The method is applicable to both laminar and turbulent flows, employing coefficients already available in the literature. The incorporation of duct heat transfer within thermal models of the PV installation is discussed briefly, highlighting further areas which are being refined by on-going work.

scholarly journals Evaluating assembly and variant calling software for strain-resolved analysis of large DNA-viruses

2020 ◽  
Author(s):  
Z.-L. Deng ◽  
A. Dhingra ◽  
A. Fritz ◽  
J. Götting ◽  
P. C. Münch ◽  
...  
Keyword(s):  
Best Practices ◽  
High Throughput Sequencing ◽  
Large Fraction ◽  
Variant Calling ◽  
Data Sets ◽  
Library Preparation ◽  
Experimental Protocol ◽  
Dna Viruses ◽  
Benchmark Data ◽  
General Public License

AbstractInfection with human cytomegalovirus (HCMV) can cause severe complications in immunocompromised individuals and congenitally infected children. Characterizing heterogeneous viral populations and their evolution by high-throughput sequencing of clinical specimens requires the accurate assembly of individual strains or sequence variants and suitable variant calling methods. However, the performance of most methods has not been assessed for populations composed of low divergent viral strains with large genomes, such as HCMV. In an extensive benchmarking study, we evaluated 15 assemblers and six variant callers on ten lab-generated benchmark data sets created with two different library preparation protocols, to identify best practices and challenges for analyzing such data.Most assemblers, especially metaSPAdes and IVA, performed well across a range of metrics in recovering abundant strains. However, only one, Savage, recovered low abundant strains and in a highly fragmented manner. Two variant callers, LoFreq and VarScan2, excelled across all strain abundances. Both shared a large fraction of false positive (FP) variant calls, which were strongly enriched in T to G changes in a “G.G” context. The magnitude of this context-dependent systematic error is linked to the experimental protocol. We provide all benchmarking data, results and the entire benchmarking workflow named QuasiModo, Quasispecies Metric determination on omics, under the GNU General Public License v3.0 (https://github.com/hzi-bifo/Quasimodo), to enable full reproducibility and further benchmarking on these and other data.

Non-Covalent Interactions Atlas Benchmark Data Sets: Hydrogen Bonding

2019 ◽  
Author(s):  
Jan Řezáč
Keyword(s):  
Hydrogen Bonding ◽  
Basis Sets ◽  
Data Sets ◽  
Neutral Systems ◽  
Benchmark Data ◽  
Wide Range ◽  
Non Covalent Interactions ◽  
Dissociation Curves ◽  
New Generation ◽  
Covalent Interactions

The Non-Covalent Interactions Atlas project (www.nciatlas.org) aims to cover a wide range of non-covalent interactions with a new generation of benchmark data sets. This paper presents the first two data sets focused on hydrogen bonding: HB375, featuring neutral systems, and IHB100 for ionic H-bonds. Both data sets are complemented by ten-point dissociation curves (HB375x10, IHB100x10). The interaction energies are extrapolated to the CCSD(T)/CBS limit from calculations in large basis sets. The paper also summarizes the design principles that will be used to construct the subsequent data sets in the series. The testing of DFT-D methods on the HB375 set has revealed interesting, previously unnoticed issues. The application of the new data to the testing and parameterization of semiempirical QM methods is also discussed.

scholarly journals Evaluating assembly and variant calling software for strain-resolved analysis of large DNA viruses

2020 ◽  
Author(s):  
Zhi-Luo Deng ◽  
Akshay Dhingra ◽  
Adrian Fritz ◽  
Jasper Götting ◽  
Philipp C Münch ◽  
...  
Keyword(s):  
Best Practices ◽  
High Throughput Sequencing ◽  
Large Fraction ◽  
Variant Calling ◽  
Data Sets ◽  
Library Preparation ◽  
Experimental Protocol ◽  
Dna Viruses ◽  
Benchmark Data ◽  
General Public License

Abstract Infection with human cytomegalovirus (HCMV) can cause severe complications in immunocompromised individuals and congenitally infected children. Characterizing heterogeneous viral populations and their evolution by high-throughput sequencing of clinical specimens requires the accurate assembly of individual strains or sequence variants and suitable variant calling methods. However, the performance of most methods has not been assessed for populations composed of low divergent viral strains with large genomes, such as HCMV. In an extensive benchmarking study, we evaluated 15 assemblers and 6 variant callers on 10 lab-generated benchmark data sets created with two different library preparation protocols, to identify best practices and challenges for analyzing such data. Most assemblers, especially metaSPAdes and IVA, performed well across a range of metrics in recovering abundant strains. However, only one, Savage, recovered low abundant strains and in a highly fragmented manner. Two variant callers, LoFreq and VarScan2, excelled across all strain abundances. Both shared a large fraction of false positive variant calls, which were strongly enriched in T to G changes in a ‘G.G’ context. The magnitude of this context-dependent systematic error is linked to the experimental protocol. We provide all benchmarking data, results and the entire benchmarking workflow named QuasiModo, Quasispecies Metric determination on omics, under the GNU General Public License v3.0 (https://github.com/hzi-bifo/Quasimodo), to enable full reproducibility and further benchmarking on these and other data.

Axial Distribution of Bulk Temperature and Void Fraction in a Heated Channel With Inlet Subcooling

1970 ◽  
Vol 92 (4) ◽  
pp. 595-609 ◽  
Author(s):  
S. Y. Ahmad
Keyword(s):  
Bulk Temperature ◽  
Temperature Profiles ◽  
Axial Distribution ◽  
Subcooled Liquid ◽  
Axial Temperature ◽  
Proposed Model ◽  
Wide Range ◽  
Heated Channel ◽  
Different Sources ◽  
Heated Length

A theoretical model is developed to determine the axial temperature distribution of subcooled liquid. It is a simple function of a heat transfer and a condensation parameter. The proposed model satisfactorily correlates the measured bulk temperature profiles. The corresponding mid fraction is computed by using a new empirical slip correlation, valid in both subcooled and bulk boiling regions. The resulting axial void profile has been compared (over the entire heated length) with steam and water data from six different sources, covering a wide range of pressure, mass flux, surface heat flux, inlet subcooling and channel geometry. The method gives satisfactory agreement with experimental data.

Non-Covalent Interactions Atlas Benchmark Data Sets: Hydrogen Bonding

2019 ◽  
Author(s):  
Jan Řezáč
Keyword(s):  
Hydrogen Bonding ◽  
Basis Sets ◽  
Data Sets ◽  
Neutral Systems ◽  
Benchmark Data ◽  
Wide Range ◽  
Non Covalent Interactions ◽  
Dissociation Curves ◽  
New Generation ◽  
Covalent Interactions

The Non-Covalent Interactions Atlas project (www.nciatlas.org) aims to cover a wide range of non-covalent interactions with a new generation of benchmark data sets. This paper presents the first two data sets focused on hydrogen bonding: HB375, featuring neutral systems, and IHB100 for ionic H-bonds. Both data sets are complemented by ten-point dissociation curves (HB375x10, IHB100x10). The interaction energies are extrapolated to the CCSD(T)/CBS limit from calculations in large basis sets. The paper also summarizes the design principles that will be used to construct the subsequent data sets in the series. The testing of DFT-D methods on the HB375 set has revealed interesting, previously unnoticed issues. The application of the new data to the testing and parameterization of semiempirical QM methods is also discussed.

scholarly journals mtDNAcombine: tools to combine sequences from multiple studies

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Eleanor F. Miller ◽  
Andrea Manica
Keyword(s):  
Sequence Data ◽  
Data Extraction ◽  
Bayesian Skyline Plot ◽  
Model Organisms ◽  
Data Sets ◽  
Data Handling ◽  
Online Database ◽  
Genetic Studies ◽  
Wide Range ◽  
Existing Data

Abstract Background Today an unprecedented amount of genetic sequence data is stored in publicly available repositories. For decades now, mitochondrial DNA (mtDNA) has been the workhorse of genetic studies, and as a result, there is a large volume of mtDNA data available in these repositories for a wide range of species. Indeed, whilst whole genome sequencing is an exciting prospect for the future, for most non-model organisms’ classical markers such as mtDNA remain widely used. By compiling existing data from multiple original studies, it is possible to build powerful new datasets capable of exploring many questions in ecology, evolution and conservation biology. One key question that these data can help inform is what happened in a species’ demographic past. However, compiling data in this manner is not trivial, there are many complexities associated with data extraction, data quality and data handling. Results Here we present the mtDNAcombine package, a collection of tools developed to manage some of the major decisions associated with handling multi-study sequence data with a particular focus on preparing sequence data for Bayesian skyline plot demographic reconstructions. Conclusions There is now more genetic information available than ever before and large meta-data sets offer great opportunities to explore new and exciting avenues of research. However, compiling multi-study datasets still remains a technically challenging prospect. The mtDNAcombine package provides a pipeline to streamline the process of downloading, curating, and analysing sequence data, guiding the process of compiling data sets from the online database GenBank.

scholarly journals Towards Reduced CNNs for De-Noising Phase Images Corrupted with Speckle Noise

Photonics ◽  
2021 ◽  
Vol 8 (7) ◽  
pp. 255
Author(s):  
Marie Tahon ◽  
Silvio Montresor ◽  
Pascal Picart
Keyword(s):  
Phase Error ◽  
Speckle Noise ◽  
Experimental Conditions ◽  
Benchmark Data ◽  
Wide Range ◽  
Phase Images ◽  
Different Depths ◽  
Phase Data ◽  
Do So

Digital holography is a very efficient technique for 3D imaging and the characterization of changes at the surfaces of objects. However, during the process of holographic interferometry, the reconstructed phase images suffer from speckle noise. In this paper, de-noising is addressed with phase images corrupted with speckle noise. To do so, DnCNN residual networks with different depths were built and trained with various holographic noisy phase data. The possibility of using a network pre-trained on natural images with Gaussian noise is also investigated. All models are evaluated in terms of phase error with HOLODEEP benchmark data and with three unseen images corresponding to different experimental conditions. The best results are obtained using a network with only four convolutional blocks and trained with a wide range of noisy phase patterns.

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