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@wangcj05 wangcj05 released this 08 Feb 16:31
· 110 commits to devel since this release
RAVENv3.0
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Official Release of the RAVEN code.

Version: 3.0

Important Features:

  1. Use Mamba to install RAVEN which can accelerate the installation process:

         ./scripts/establish_conda_env.sh --mamba

  2. Use “pip” to install RAVEN (https://pypi.org/project/raven-framework/) and RAVEN plugins (supported in Python 3.9 and Python 3.10):

         pip install raven-framework==3.0 teal-ravenframework==0.5 heron-ravenframework==0.4

Or if you just want the newest version of raven:

         pip install raven-framework

URLS:
https://pypi.org/project/raven-framework/
https://pypi.org/project/heron-ravenframework/
https://pypi.org/project/teal-ravenframework/

These should work on Linux, Mac OS and Windows with Python 3.9 and 3.10. After installation, the raven_framework command can be used to run raven.

  1. Improvement on parallelization, allow both Ray and Dask to be used for parallelization #2103

New Capabilities:

  • Bayesian Optimization #2123. A new optimizer node 'BayesianOptimizer' is added, which allows for the specification of a Bayesian Optimization algorithm. This method also requires the specification of a GPR ROM under the Models node. The GPR ROM node is also extended to include custom kernel specification and anisotropic kernels.
  • Sensor placement optimization via sparse sensing post-processor #2044. This post-processor will inform the users of the optimal locations to place their sensors in order to reconstruct the responses of interest with high precision.
  • Physics-guided coverage mapping (PCM) for model validation #2018. Develop and implement two separate approaches to handle time-dependence dataset for PCM.
  • Implement Markov-switching autoregressive models #2161 for time-series analysis
  • Implements data transformations in Time-Series Analysis (TSA) module #2121 and #2165

New Code Interfaces:

  • Add PARCS interface #2010 to support nuclear fuel loading pattern optimization.
  • Addition of SCALE CSAS sequence in scale interface #2155 to support nuclear reactor criticality safety analysis.
  • Add ABCE interface #2184 to support agent-based capacity expansion modeling. ABCE is a modeling tool used to model adding capacity (new generators) to an electricity market.

Other Features:

  • Switches the implementation of 1D probability distributions from C++ library Crow to appropriate python libraries #2201
  • Updating to tensorflow 2.13 for Macos arm issues #2138
  • Global TSA via ROMCollection #2189
  • Adds VARMA model to the TSA module #2180
  • Subdomain basic statistics post-processor #2119

Submodule Updates:

The updates for the submodules are tracked by issue #1114. In this release, there are significant updates in following Plugins. We recommend the users to check the following links for more details.
TEAL: https://github.com/idaholab/TEAL
HERON: https://github.com/idaholab/HERON
SR2ML: https://github.com/idaholab/SR2ML
LOGOS: https://github.com/idaholab/LOGOS
FARM: https://github.com/Argonne-National-Laboratory/FARM

Internal Developers:

We would like to thank all RAVEN internal developers for their significant contributions, including but not limit to: @wangcj05 @mandd @PaulTalbot-INL @joshua-cogliati-inl @Jimmy-INL @dylanjm @JunyungKim @worseliz @yoshiurr-INL @aadeshINL @GabrielSoto-INL

External Contributors:

We would like to thank all RAVEN external contributors for their significant contributions, including but not limit to @aalfonsi @wanghy-anl @ShimingYIN @j-bryan @Nhatkhang @AnthoneyGriffith

What's Changed

New Contributors

Full Changelog: RAVENv2.3...RAVENv3.0

Contributors

PaulTalbot-INL, joshua-cogliati-inl, and 16 other contributors
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