synthetic-models
PRA/reliability models, typically event trees and fault trees, in various @openpra-org supported formats.
Science Score: 49.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 5 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (6.8%) to scientific vocabulary
Last synced: 6 months ago
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Repository
PRA/reliability models, typically event trees and fault trees, in various @openpra-org supported formats.
Basic Info
Statistics
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 1
Created 10 months ago
· Last pushed 10 months ago
Metadata Files
Readme
Citation
README.md
Synthetic PRA Models
PRA/reliability models, typically event trees and fault trees, in various @openpra-org supported formats.
Schema Validation
Schemas for these models can be found on the submoduled repo @openpra-org/mef-schema.
Initialize the submodule using:
git submodule update --init --recursive
Additional References
- E. M. Aras, Enhancement Methodology for Probabilistic Risk Assessment Tools through Diagnostics, Optimization, and Parallel Computing, Doctor of Philosophy, North Carolina State University, Raleigh, North Carolina, 2024. [Online]. Available: https://repository.lib.ncsu.edu/items/bb05f7f5-1cff-4beb-9312-331bc94b0b95
- E. M. Aras, A. S. Farag, A. Earthperson, and M. A. Diaconeasa, Methodology and Demonstration for Performance Analysis of a Probabilistic Risk Assessment Quantification Engine: SCRAM, in 18th International Probabilistic Safety Assessment and Analysis (PSA 2023), Knoxville, TN: American Nuclear Society, 2023, pp. 452459.
- E. M. Aras, A. S. Farag, A. Earthperson, and M. A. Diaconeasa, Method of Developing a SCRAM Parallel Engine for Efficient Quantification of Probabilistic Risk Assessment Models, in 18th International Probabilistic Safety Assessment and Analysis (PSA 2023), Knoxville, TN: American Nuclear Society, 2023, pp. 134140.
- E. M. Aras, A. S. Farag, A. Earthperson, and M. A. Diaconeasa, Benchmark Study of XFTA and SCRAM Fault Tree Solvers Using Synthetically Generated Fault Trees Models, in Volume 9: Mechanics of Solids, Structures, and Fluids; Micro- and Nano-Systems Engineering and Packaging; Safety Engineering, Risk, and Reliability Analysis; Research Posters, Columbus, Ohio, USA: American Society of Mechanical Engineers, Oct. 2022, p. V009T14A016. doi: 10.1115/IMECE2022-95783.
- A. Farag, S. Wood, A. Earthperson, E. Aras, J. Boyce, and M. Diaconeasa, Evaluating PRA Tools for Accurate and Efficient Quantifications: A Follow-Up Benchmarking Study Including FTREX, in Advanced Reactor Safety (ARS), Las Vegas, NV: American Nuclear Society, 2024, pp. 573582. doi: 10.13182/T130-43377.
- A. S. Farag, E. M. Aras, A. Earthperson, S. T. Wood, and J. Boyce, Preliminary Benchmarking of SAPHSOLVE, XFTA, and SCRAM using Synthetically Generated Fault Trees with Common Cause Failures, in 18th International Probabilistic Safety Assessment and Analysis (PSA 2023), Knoxville, TN: American Nuclear Society, 2023, pp. 4049.
Owner
- Name: OpenPRA
- Login: openpra-org
- Kind: organization
- Email: admin@openpra.org
- Website: https://openpra.org
- Repositories: 1
- Profile: https://github.com/openpra-org
OpenPRA
GitHub Events
Total
- Release event: 1
- Push event: 5
- Create event: 1
Last Year
- Release event: 1
- Push event: 5
- Create event: 1
Dependencies
generator/Dockerfile
docker
- python 3.9-alpine build
generator/requirements.txt
pypi
generator/setup.py
pypi
- argparse *
- setuptools *