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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 901 records · Page 50

WaterTAP 1.0 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

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Dynamic Model of a supercritical CO2 10MW Recompression Closed Brayton Cycle

This model of the 10MW recompression closed Brayton cycle (RCBC) was developed in conjunction with the DOE’s Supercritical Transformational Electric Power (STEP) project. A high-fidelity dynamic model was used extensively to study the dynamic characteristics of the cycle and develop the process control architecture and strategies for start-up and shutdown procedures. This version of the model has been simplified from the original version to be more accessible for a variety of applications and research. The controllers developed for the original model have been maintained for this version and tuned to give a similar performance to the original model. This model can be used to perform similar studies as those performed in Liese et al (2020). The overall cycle performance will not be identical but will perform similarly.

Controls,Power Cycles,Process Systems Engineering,↗

PARETO UI 1.1.0 Release

PARETO is an open-source Python-based software package for oilfield produced water management and beneficiary reuse optimization. PARETO supports produced water industry by providing cost-effective water management solutions. This version introduced an updated User Interface (UI) which makes it easier to navigate and understand the solution for industry users. New Features: - Map files are added for visualization - Added output export function button - Water residual view added - Workflow was streamlined - File extension was expanded - Minor bugfix

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CCSI Toolset 3.17 Release

CCSI Toolset 3.17 Release Highlights A workaround was developed to allow complex Aspen Custom Modeler (ACM) models to be used in FOQUS. This workaround uses Visual Basic for Applications to connect the ACM models to FOQUS. The ability for User plugins to be uploaded to FOQUS Cloud was added. The documentation was updated to include Optional Software Install and Tutorial Notes to clarify the usage of Turbine and SimSinter in installation instructions and adds a link to the relevant tutorial page. The Sequential Design of Experiments documentation was updated with current screenshots. The copyright was updated to include 2023.

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CCSI Toolset 3.18 Release

CCSI Toolset 3.18 Release Highlights FOQUS was updated to allow installation for users using MacOS on Apple silicon. FOQUS Cloud support was added for user plugins. The Optimality-Based Design of Experiments tutorials were updated to reflect the latest changes in the user interface flow. The plot discrete sliders were fixed for CDF and 3D plots within Uncertainty Quantification, which were not working due to a matplotlib depreciation. The installation was updated to set the default location for the PSUADE executable if found in the environment. Updates were made to allow compatibility with NumPy 1.25. Additional documentation changes were made to fix typographical errors and fix a broken link to optional software.

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CCSI Toolset 3.19 Release

CCSI Toolset 3.19 Release Highlights A gradient generation tool was developed to support GENN models in FOQUS. Certain machine learning tools train gradient-enhanced neural network (GENN) models which can be more accurate for complex datasets given a priori knowledge of model derivatives. However, the derivatives must be known beforehand and are not often available for process data. This tool automatically predicts the gradients for a training dataset in a form usable by common GENN trainers, such as Surrogate Modeling Toolbox. Support was added for Surrogate Modeling Toolbox GENN models in FOQUS, including updates to the run methods, node properties, test framework, documentation and optional dependencies list. Users can train/save Surrogate Modeling Toolbox gradient-enhanced neural network (GENN) models with custom objects and produce .pkl files compatible with the Machine Learning/Artificial Intelligence Plugin in FOQUS. A simpler implementation of the ordering algorithm in the Sequential Design of Experiments (SDOE) module was included. The SDOE examples documentation was updated. The Optimality-Based Design of Experiments was updated to improve the error handling when the results are None.

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CCSI Toolset 3.20 Release

CCSI Toolset 3.20 Release Highlights Minimum Viable Product surrogate plugin was added for creating Machine Learning/Artificial Intelligence models. Corresponding documentation was added for the plugin. Sequential Design of Experiments plots were updated to eliminate an issue with the window stack ordering upon closure of the plots. Support for Python 3.7 was removed. Documentation was improved by adding new mandatory section to the ReadTheDocs configuration and adding installation instructions back for NLOpt. TurbineLite was updated to 3.0.0, which is compatible with SimSinter 3.0.0. The developer environment was updated and 32-bit support was removed. SimSinter was updated to 3.0.0. This version removed gPROMS support and included security updates.

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CCSI Toolset 3.21 Release

CCSI Toolset 3.21 Release Highlights Parallelization support was added for Sequential Design of Experiments (SDOE) computations using Dask (preliminary). Input type dependent ordering capability was added to the SDOE module. With this implementation the user can specify the level of difficulty to change an input (Easy or Hard) and FOQUS will generate the appropriate ordered design depending on the input difficulty combination. Python version support was extended. FOQUS is now compatible with Python 3.8 through 3.12. Platforms used for automated testing were expanded to include macOS ARM (Apple Silicon). Updates to the FOQUS documentation to include information on how to set paths for SimSinter and TurbineLite. Turbine configuration section was added to Debugging Documentation.

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CCSI Toolset 3.22 Release

CCSI Toolset 3.22 Release Highlights The Sequential Design of Experiments user interface was updated to resolve an issue where the results would fail to plot in some cases (e.g., Non-Uniform Space Filling designs). The Machine Learning/Artificial Intelligence module was updated to support Keras 3 and to reflect changes made to dependencies’ syntax. A check was added to ensure PSUADE is installed and available at FOQUS startup. If PSUADE is not installed, a link to the FOQUS documentation is displayed and FOQUS is closed. The copyright year was updated to include 2024 in places where it had not previously been updated. Typographical errors were corrected to improve clarity in variable names and documentation. The FOQUS documentation was updated to reflect the fact that ALAMO can have two executables and indicates the correct executable to add to the Settings path. SimSinter was updated to version 3.1.0. This version removed gPROMS support and included security updates.

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CCSI Toolset 3.23 Release

CCSI Toolset 3.23 Release Highlights The user interface was updated to allow timeouts in Aspen Custom Modeler and AspenPlus. The installation was updated to use 64-bit versions of TurbineLite and SimSinter by default. The documentation was improved for clarity.

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CCSI Toolset 3.24 Release

CCSI Toolset 3.24 Release Highlights Support for Python 3.8 was removed. Extraneous and wildcard imports were removed.

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CCSI Toolset 3.25 Release

CCSI Toolset 3.25 Release Highlights The copyright in the CCSI Toolset was updated to include the year 2025. The code and notes within it were revised to correct minor typographical errors and clarify meanings of variables. The configuration of the FOQUS documentation via Read the Docs was updated to explicitly set the path.

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Galfenol Energy Harvesting Device Proposal

This CRADA involved an integrated approach of synthesizing Fe-Ga (Galfenol) powder using high-pressure gas atomization (HPGA) and 3D printing via laser engineered net shaping (LENS) processing to produce free standing magnetostricitve sensors.

36 MATERIALS SCIENCE↗

Tank Farm Safety Programmable System Software Management Plan

This Software Management Plan (SMP) applies to the configurable programmable logic controller (PLC) software configured as the Tank Farms Safety Programmable System (TFSPS). The TFSPS is identified as a safety-significant (SS) system to prevent loss of the safety function of SS structures, systems, and components (SSC). The TFSPS software is classified as grade level A configurable safety software. The TFSPS consists of safety instrumented systems (SIS) and safety instrumented alarm (SIA) systems.The purpose of this management plan is to describe how Washington River Protection Solutions (WRPS) will configure and manage the TFSPS software and the associated software life cycle (SLC). TFSPS software shall be configured by Process and Control Systems Engineering (P&CSE) as grade level A safety software for use by Production Operations as the primary stakeholders.

97 MATHEMATICS AND COMPUTING↗

Radioisotope Power System Dose Estimation Tool (RPS-DET) User Manual

Radioisotope power systems (RPSs) convert decay heat from radioactive materials to electrical power. The National Aeronautics and Space Administration (NASA) uses RPSs for certain orbiters, landers, rovers, and probes that cannot rely on solar or chemical power. Most of the emitted charged particles in RPS fuels are locally absorbed, and the particles’ kinetic energy is converted into thermal energy as they slow down in the surrounding materials. This heat is subsequently converted into electricity through some form of energy conversion process (e.g., thermoelectric, heat engine, thermionic). While nearly all the charged particles are stopped locally, a non-trivial portion of the emitted neutral particles (neutrons and photons) escape the fuel and are free to interact with surrounding materials. This escaping radiation field can be operationally problematic for certain instruments, materials, electronics, etc., and can cause problems during terrestrial shipping, integration, testing for personnel, instrumentation, etc. Furthermore, the fuel’s emission spectrum evolves over time as the parent isotopes decay away and daughter products accumulate. This changing fuel composition alters characteristics of the ambient radiation field over time, which is further affected by RPS orientation and the surrounding environment. Tools that can rapidly estimate the radiation characteristics of RPSs with various fuel compositions, fuel ages, various RPS orientations, and in/on different spaceflight and planetary scenarios provide researchers with an opportunity to quickly estimate the radiation implications of a given RPS scenario. The RPS dose estimation tool (RPS-DET) provides engineers, scientists and analysts who are not trained in the art of particle transport software with a solution for quickly building, simulating, and analyzing the radiation impacts of various RPS designs in relevant spaceflight and terrestrial environments.

30 DIRECT ENERGY CONVERSION↗

Reliability and Maintainability Changing the Culture

The Reliability and Maintainability team strives to ensure the reliability, availability, and maintainability of plant assets throughout their life cycle. This objective is accomplished by providing world-class maintenance engineering support and maintenance processes. University of Tennessee’s Reliability and Maintainability Center (UT RMC) Partnership – Provided subject matter expert (SME) analysis of current state of both sites integrated work control (IWC) and maintenance execution processes.

47 OTHER INSTRUMENTATION↗