SCD
The Scientific Computing Department provides large scale HPC facilities, computing data services and infrastructure at both STFC Daresbury Laboratory and STFC Rutherford Appleton Laboratory.
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- Supplementary data to RAL Technical Report "Ab initio interpretation of neutron scattering data for aqueous solutions"(2018) Holzmann, Nicole; Bernasconi, LeonardoThis dataset contains a collection of scripts, input and output files as supplementary data to the RAL Technical Report "Ab initio interpretation of neutron scattering data for aqueous solutions". The Technical Report aims to enable the reader to carry out AIMD (ab inito molecular dynamics) simulations from freely accessible Software and to compare the results with EPSR data based on neutron scattering experiments. The data stored contains example input files for some of these programs and also some scripts for the processing, conversion and analysis of simulation data.
- Neutron Cross Sections generated and used during the project: "Feasibility of the use of frozen walls in molten salt fast reactors (MSFR-FW)"(2019) Cartland-Glover, Gregory; Rolfo, Stefano; Litskevich, Dzianis; Skillen, Alex; Emerson, David; Merk, Bruno; Moulinec, CharlesThe data enclosed in this repository is associated with the manuscripts submitted to the European Physical Journal - Nuclear mid February 2019 and Nuclear Engineering and Design end of March 2019. The articles are adaptations of conference papers presented at the ICONE26 Conference in London, July 2018, the CFD4NRS-7 Workshop in Shanghai, September 2018 and the NUTHOS-12 topical meeting in Qingdao, October 2018. The data are neutron cross-sections, which were generated during the project "Feasibility of the use of frozen walls in molten salt fast reactors (MSFR-FW)". The neutron cross sections take the form of ascii files that have been formatted for the DYN3D-MG code. The subdirectory coreregion contains the reactor core neutron cross sections for the fuel salt eutectic LiF-PuF3-UF4 over the temperature range 623.15 K - 1198.15 K. The cross-sections were used in the coupled neutronic and computational fluid dynamic simulation of a cylindrical reactor with a low resolution. The subdirectory coreandreflector contains the reactorcore, wall and reflector neutron cross sections for the fuel salt eutectic LiF-PuF3-UF4 over the temperature range 623.15 K - 1198.15 K. The cross-sections were used in the coupled neutronic and computational fluid dynamic simulation of a reactor with the EVOL-optimized configuration. Below 814.22 K the fuel salt eutectic is assumed solid. All cross-sections above 841.55 K temperature are liquid. Between these temperatures the media is assumed to be a temperature dependent mixture of solid and liquid phases. Details of the assumed physical properties of the fuel-salt eutectic are given in the above references. The raw data was prepared using the SCARF (scarf.rl.ac.uk). The data was generated using SERPENT (http://montecarlo.vtt.fi/). SERPENT (version 2.1.29) modelled the neutronic behaviour of the molten salt fast reactor using the Monte Carlo method. The data was reformatted for the nodal neutron diffusion solver DYN3D-MG (https://www.hzdr.de/db/Cms?pOid=11771&pNid=542) to read. This is the format in which neutron cross-sections are given.
- Figures and Tables from the journal article: "On the numerical modelling of frozen walls in a molten salt fast reactor"(2019) Cartland-Glover, Gregory; Rolfo, Stefano; Litskevich, Dzianis; Skillen, Alex; Emerson, David; Merk, Bruno; Moulinec, CharlesThe data enclosed in this repository is associated with the manuscript for an article "On the numerical modelling of frozen walls in a molten salt fast reactor" submitted to the Nuclear Engineering and Design Journal at the end of March 2019. The article was selected for the CFD4NRS-7 Special Issue of the Journal. The data in the article was presented at the CFD4NRS-7 Workshop in Shanghai, September 2018 and the NUTHOS-12 topical meeting in Qingdao, October 2018. The data is in the form of figures and tables. The figures in the corresponding directory were prepared using bash scripts, python version 2.7, gnuplot version 4.6 and latex to extract and analyse simulated data. The tables in the corresponding directory were prepared using bash scripts and python version 2.7 to extract and analyse simulated data. The python scripts can be found in the repository. Note that numpy is a requirement. The raw data was prepared using the SCARF (scarf.rl.ac.uk), CIRRUS (cirrus.ac.uk), University of Liverpool (https://www.liverpool.ac.uk/csd/advanced-research-computing/facilities/high-performance-computing/) and SCAFELLPIKE (http://community.hartree.stfc.ac.uk/wiki/site/admin/home.html) clusters. There is inexcess of 10Gb of data generated by the solvers Code_Saturne (https://www.code-saturne.org/cms/), DYN3D-MG (https://www.hzdr.de/db/Cms?pOid=11771&pNid=542) and SERPENT (http://montecarlo.vtt.fi/). Code_Saturne (version 5.0) was used to perform simulations of thermal fluid dynamic and conjugate heat transfer of a molten salt fast reactor. The models studied the formation of frozen salt films on cooled reactor vessel walls. DYN3D-MG modelled the nodal diffusion neutronic behaviour of the molten salt fast reactor. SERPENT (version 2.1.29) modelled the neutronic behaviour of the molten salt fast reactor using the Monte Carlo method. Both Code_Saturne and DYN3D-MG were coupled to one another in 3-D simulations of the reactor. The coupling procedures were implemented with the Multiscale Universal Interface, MUI (https://github.com/MxUI/MUI).
- Figures and Tables from the journal article: "Application of DYN3D-MG to the neutronics of a molten salt fast reactor"(2019) Cartland-Glover, Gregory; Rolfo, Stefano; Litskevich, Dzianis; Skillen, Alex; Emerson, David; Merk, Bruno; Moulinec, CharlesThe data enclosed in this repository is associated with the manuscript for an article submitted to the European Physical Journal - Nuclear mid February 2019. The article is an adaptation of an article presented at the ICONE26 Conference in London, July 2018. Some of the neutronic data also presented in the article was presented at the CFD4NRS-7 Workshop in Shanghai, September 2018. The figures and tables presents the specifications and results of the neutron simulations performed for these papers. They show cross-sections, power distributions and variation of effective multiplification factor with temperature and population density. The data is in the form of figures and tables. The figures in the corresponding directory were prepared using bash scripts, python version 2.7, gnuplot version 4.6 and latex to extract and analyse simulated data. The tables in the corresponding directory were prepared using bash scripts and python version 2.7 to extract and analyse simulated data. The python scripts can be found in the repository. Note that numpy is a requirement. The raw data was prepared using the SCARF (scarf.rl.ac.uk) and the University of Liverpool (https://www.liverpool.ac.uk/csd/advanced-research-computing/facilities/high-performance-computing/). The data was generated by the solvers DYN3D-MG (https://www.hzdr.de/db/Cms?pOid=11771&pNid=542) and SERPENT (http://montecarlo.vtt.fi/). DYN3D-MG modelled the nodal diffusion neutronic behaviour of the molten salt fast reactor. SERPENT (version 2.1.29) modelled the neutronic behaviour of the molten salt fast reactor using the Monte Carlo method.
- 3D datasets for "Thermal transients in a U-Bend"(2019-07-19) Skillen, AlexData accompanying the manuscript "Thermal transients in a U-Bend" submitted to the International Journal of Heat and Mass Transfer (IJHMT) July 2019. 3D volumetric cell-centre data, in vtk format (readable by Paraview, https://www.paraview.org/, for instance) at times \tilde{t}=0, 15, 30, 45, and 70 are enclosed. The file names are {SOLID|FLUID}_t{N}.vtu which denote data for either the fluid or solid domain at time \tilde{t}=N. The field variables comprise: "T"; the ensemble averaged normalised temperature. "V"; the ensemble averaged normalised velocity. "uu", "uv", etc.; the ensemble averaged resolved Reynolds stress components, normalised by bulk velocity.
- Resubmitted Figures and Tables from the journal article: "On the numerical modelling of frozen walls in a molten salt fast reactor"(2019-08) Cartland-Glover, Gregory; Skillen, Alex; Litskevich, Dzianis; Rolfo, Stefano; Emerson, David; Merk, Bruno; Moulinec, CharlesThe data enclosed in this repository is associated with the manuscript for an article "On the numerical modelling of frozen walls in a molten salt fast reactor" resubmitted to the Nuclear Engineering and Design Journal in August 2019. The article was selected for the CFD4NRS-7 Special Issue of the Journal. The data in the article was presented at the CFD4NRS-7 Workshop in Shanghai, September 2018 and the NUTHOS-12 topical meeting in Qingdao, October 2018. References: G.M. Cartland-Glover, A. Skillen, D. Litskevich, S. Rolfo, D.R. Emerson, B. Merk, C. Moulinec. "On the numerical modelling of frozen walls in a molten salt fast reactor". In proceedings of the OECD/NEA&IAEA CFD4NRS-7 Workshop, Application of CFD/CMFD Codes to Nuclear Reactor Safety and Design and their Experimental Validation, Shanghai, September 4-6, 2018. G.M. Cartland-Glover, A. Skillen, S. Rolfo, D.R. Emerson, C. Moulinec, D. Litskevich, B. Merk. "On the feasibility of the application of frozen walls to a molten salt fast reactor". In proceedings of the 12th International Topical Meeting on Nuclear Reactor Thermal-Hydraulics, Operation and Safety -- NUTHOS-12, Qingdao, China, October 14-18, 2018. ---------------- The data is in the form of figures and tables. The figures in the corresponding directory were prepared using bash scripts, python version 2.7, gnuplot version 4.6 and latex to extract and analyse simulated data. The tables in the corresponding directory were prepared using bash scripts and python version 2.7 to extract and analyse simulated data. The python scripts can be found in the repository. Note that numpy is a requirement. ---------------- The raw data was prepared using the SCARF (scarf.rl.ac.uk), CIRRUS (cirrus.ac.uk), University of Liverpool (https://www.liverpool.ac.uk/csd/advanced-research-computing/facilities/high-performance-computing/) and SCAFELLPIKE (http://community.hartree.stfc.ac.uk/wiki/site/admin/home.html) clusters. There is inexcess of 10Gb of data generated by the solvers Code_Saturne (https://www.code-saturne.org/cms/), DYN3D-MG (https://www.hzdr.de/db/Cms?pOid=11771&pNid=542) and SERPENT (http://montecarlo.vtt.fi/). Code_Saturne (version 5.0) was used to perform simulations of thermal fluid dynamic and conjugate heat transfer of a molten salt fast reactor. The models studied the formation of frozen salt films on cooled reactor vessel walls. DYN3D-MG modelled the nodal diffusion neutronic behaviour of the molten salt fast reactor. SERPENT (version 2.1.29) modelled the neutronic behaviour of the molten salt fast reactor using the Monte Carlo method. Both Code_Saturne and DYN3D-MG were coupled to one another in 3-D simulations of the reactor. The coupling procedures were implemented with the Multiscale Universal Interface, MUI (https://github.com/MxUI/MUI). ---------------- The project was funded by the following grants: - EPSRC through the Feasibility Study in Energy Research scheme (Ref: EP/R001618/1) Additional support was obtained from the following grants: - EPSRC EP/N016602/1 and EP/N033841/1 - Future Emerging Technologies funding scheme of the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671564 - EPSRC RAP-Tier 2 allocation provided access to the CIRRUS cluster
- Supercell test configurations for wannier90 development(2020) Jackson, JeromeSeries of bcc vanadium supercell input files for wannier90 with reference outputs from wannier90 3.0.0.
- Electronic structure and finite temperature magnetism of yttrium iron garnet: inputs and converged self-energy(2020-11-17) Jackson, JeromeElectronic structure and finite temperature magnetism of yttrium iron garnet (Joseph Barker, Dimitar Pashov, Jerome Jackson) This archive contains the configuration files, converged self-energy, and restart data needed to reproduced the published calculations: QSGW description of electronic and magnetic properties of YIG. Tabulated Heisenberg interactions for LDA and QSGW are included. https://arxiv.org/abs/2009.14601 https://www.questaal.org.
- EMMC Software and Modelling Questionnaire(2021-06-15) Todorov, IlianEMMC Software and Modelling Questionnaire and associated analisys and graphs
- Microfluidics and Nanofluidics journal article - "Numerical investigation of transmission probability characteristics in the first low-density region of a laser wakefield accelerator"(2023) John, BenziRelevant data supporting the manuscript "Numerical investigation of transmission probability characteristics in the first low‑density region of a laser wakefield accelerator" submitted to the Microfluidics and Nanofluidics journal (accepted for publication in July 2023).
- Molecular simulation trajectories and atomic interaction descriptions of 1,1,1,2-tetrefluoroethane liquids.(2023-05-22) Yong, Chin; Vivian, BarronData on raw atomic trajectories (5 ns) produced by DL_POLY molecular dynamics simulation package. The system model is described in the DL_F Notation, which contained chemical information of the atoms. The DL_ANALYSER Notation for Atomic Interaction (DANAI) is used to annotate the atomic interaction networks in the system, to provide an overall view of the molecular interaction behaviour. The dataset contains five different sets of simulation data, over a range of temperatures: 203K, 233K. 263K. 293K and 323K.
- Demonstrations of fast approximate variable-width broadening(2023-09) Jackson, Adam; Farmer, JessicaWe have developed a fast approximate method of applying variable-width broadening to spectral data. This dataset contains demonstration scripts which generate the plots for a related academic manuscript. They also reproduce the parametrisation of polynomial fits to the relationship between the approximation error and the scale factor between broadening kernels used in the method. Some of the scripts use the implementation in the Euphonic library: to reproduce published results use Euphonic v1.3.0 - https://pace-neutrons.github.io/Euphonic/versions/v1.3.0.html - https://github.com/pace-neutrons/Euphonic/releases/tag/v1.3.0 Most of the scripts are written in Python. One Bash shell script is also included which needs to call the euphonic-powder-map program included in the Euphonic package. A Makefile is provided so that all plots can be generated with "make plots" using GNU Make. .yaml datafiles were derived from data in the Kyoto phonon database ("phonondb") under a CC-by license: the Phonopy calculation directories were downloaded and Phonopy was run with =--include-all= and =--nac= options to create .yaml files containing all the information needed by Euphonic.
- Experimental and Computational Investigation of the Emission and Dispersion of Fine Particulate Matter (PM2.5) During Domestic Cooking - Dataset(2024) Jones, Harriet; Kumar, Ashish; O'Leary, Catherine; Dillon, Terry James; Rolfo, StefanoThis dataset contains the computational and experimental data for the STFC Air Quality Network project "Experimental Validation of Lagrangian Stochastic Methods Targeting Indoor Air Quality". In this project, 12 minute stir frying experiments were conducted in the DOMESTIC kitchen laboratory, and the spatial particulate matter (PM) concentrations during these experiments was measured using a range of low-cost sensors. The data from these experiments was then used as validation data for computational fluid dynamics simulations of stir frying in DOMESTIC, which were performed using the finite volume solver code saturne (version 8.0.3). Cases were run on the Scientific Computing Application Resource for Facilities (SCARF). The experimental data includes the PM, humidity and temperature readings from the sensors, in the form of csv files, as well as the data from two anemometers (also as csv files), the experimental times and dates, and the cooking protocols, and a schematic of the kitchen laboratory along with a list of sensor locations. The computational data contains the setup and outputs for all cases. Full details can be found in the README files enclosed.