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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 469 records · Page 26

Estella Atekwana: Autobiographical Notes

I describe my career journey from a young girl in Cameroon, West Africa, to a trailblazing geophysicist to my current role as dean. I chronicle my time as a student, the transition to being an early career faculty, launching my research career, and ultimately finding my way to administration. Along the way I helped pioneer biogeophysics as a subdiscipline in geophysics while simultaneously maintaining an international research program in continental rift tectonics. I also describe the many intersectionalities in my life including being the first Black woman in many spaces, being a champion for student success, developing a diverse talent pipeline by enhancing diversity in the geosciences, and navigating academic job searches as part of a dual-career couple. Finally, I acknowledge all those who helped shape my career including the many students I had the opportunity to mentor. • Many underrepresented minority geoscientists lack the social capital and professional networks critical for their success. • Geoscience departments must be intentional and deliberate in promoting and ensuring more inclusive workplace environments. • Dual-career couples remain a major challenge, impacting retention and recruitment of top talent; universities should provide resources to alleviate this challenge. • Biogeophysics has untapped potential for advancing understanding of subsurface biogeochemical processes and the search for life in extreme environments. • To date, considerable speculation remains regarding the fundamental geodynamic processes that initiate and sustain the evolution of magma-deficient rifts.

99 GENERAL AND MISCELLANEOUS↗

Hydrogen: Targeting $1/kg in 1 Decade

The societal energy system is evolving rapidly as the impacts of our existing energy system are better appreciated and technological advances have dramatically decreased the cost of renewable resources. Simultaneously, the importance of energy transfer across timeframes and the difficulty of decarbonizing the industrial loads and transportation demands using electricity are being recognized. At the center of this need is achieving low-cost clean hydrogen. The U.S. Department of Energy launched the Hydrogen Energy EarthShot which seeks to reduce the cost of clean hydrogen to $1 per 1 kilogram in one decade. Reaching the $1/kg goal is dependent on the evolution of the electrical energy system to increase renewable energy deployment and low electricity costs; advances in electrolysis technology and manufacturing readiness; and infrastructure build-out and hydrogen market establishment that results in the ability to make, move, store, and use clean hydrogen economically while spurring job creation.

08 HYDROGEN↗

XRFtomo

Based on [1], XRFtomo brings together a variety of image processing tools used for preparing, processing and reconstructing 3D renditions of samples imaged using a synchrotron-based x-ray fluorescence (XRF) microprobe or nanoprobe at the Advanced Photon Source (APS). This software bridges the gap between data acquisition and visualization by providing tools to adjust for misalignment in the imaging process and tools for running reconstructions[2], all with the use of a GUI or command line. XRFtomo accepts .h5 files processed through MAPS[3] and it outputs reconstructed cross-sections, projections, sinograms, metadata, and a configuration file with last-used parameters for rapid processing the next time the program is launched. These images serve as inputs for other 3D visualization software for generating volumetric renderings and animations.

Marin, Fabrico↗

NRWAL (NLR formerly known as NREL Wind Analysis Library) [SWR-21-26]

NRWAL (NLR (National Laboratory of the Rockies) formerly known as NREL (National Renewable Energy Laboratory) Wind Analysis Library: A library of offshore wind cost equations (plus new energy technologies like marine hydro!) Easy equation manipulation without editing source code Full continental-scale integration with the NREL Renewable Energy Potential Model (reV) https://nrel.github.io/reV/ Ready-to-use configs for basic users Dynamic python tools for intuitive equation handling One seriously badass sea unicorn To get started with NRWAL, check out the NRWAL Config documentation or the NRWAL example notebook. You can also launch the notebook in an interactive jupyter shell right in your browser without any downloads or software using binder. Ready to build a model with NRWAL but don't want to contribute to the library? No problem! Check out the example getting started project here. Here is the important stuff: The NRWAL Equation Library. Default NRWAL Configs

Nunemaker, Jacob↗

edmbutton

A PyDM widget for launching EDM displays.

Gibbs, Matt↗

pnnl/PTMPSI

PTM-Psi is a Python 3 package that combines several capabilities to streamline the workflow to interrogate the impact of PTMs on proteins using well-established software packages. The workflow of the PTM-Psi software package includes input files and launch instances from standard packages such as AlphaFold, NWChem, GROMACS, and the Autodock Suite

Mejia-Rodriguez, Daniel↗

Inference-Engine v0.1.0

Given a pre-trained neural network, Inference-Engine performs maps network inputs to outputs by executing the forward pass through the provided network. Although the predominant programming language for machine-learning is Python, most high-performance computing (HPC) applications are written in Fortran, C, or C++. Inference-Engine aims to support HPC programs and is written in Fortran, a language with a large feature set supporting interoperability with C. This software exposes concurrency in a portable way by using standard language features that some modern Fortran compilers can exploit with various optimizations, including offloading computation to a Graphics Processing Unit (GPU). In particular, this software makes extensive use of Fortran's "do concurrent" parallel loop construct, implicitly parallel array statements, and pure procedures that can be invoked inside "do concurrent" blocks. Inference-Engine also supports dynamic choice of inference methods at runtime. Two current options include one method that uses Fortran's "dot_product" intrinsic function inside "do concurrent" blocks and another method that instead uses Fortran' "matmul" array intrinsic function. We plan to investigate automatic compiler offloading of "do concurrent" calculations to GPUs and compile-time substitution of optimized libraries such as the Basic Linear Algebra Library (BLAS) for "matmul" invocations. We also envision the potential for the choice of which method to use could happen at program launch based on in situ performance measurements on any given platform.

Rouson, Damian↗

SolarAPP+ ® (Solar Automated Permit Processing Plus) [SWR-19-51]

SolarAPP+ ®: Safe and affordable home solar through permitting automation. NREL has launched a collaborative effort with key code officials, authorities having jurisdiction (AHJs), and the solar industry to develop an instant online solar permitting platform for code compliant residential systems. SolarAPP (Solar Automated Permit Processing) will: -Provide a flexible, web-based PV-permitting tool for residential systems at no-cost to AHJs. -Enable standardization of instant permitting processes. -Evaluate applications for safety and code compliance. -Offer opportunities to incorporate energy storage and expand to other market segments.

Cook, Jeffrey↗

Polaris Studio

SF-24-040 Polaris-studio is the Python entry point/front end for using the Polaris transportation simulator. The package contains the code used to create new models from open and user-provided data, an extensive range of convenience tools for data preparation and result analysis and the ability of designing, launching and tracking studies combining multiple individual Polaris simulations from a Python terminal. The Polaris Studio software contains several modules for accomplishing the above tasks, including the PolarisLib - the Polaris object model, Polaris Manager - code for setting up and running Polaris studies, QPOLARIS - an add-on for the QGis software to allow model files to be created and edited, PolarisVis - a juptyer-based postprocessing library, and Polaris Tools - a useful collection of supplemental tools for interacting with Polaris files.

Auld, Joshua↗

Agn-201 Digital Twin

This is the repository for all code related to the AGN-201 Nuclear Reactor Digital Twin at Idaho State University. The goal of this code repository is to consolidate all pieces required to run the AGN-201 Digital Twin in the [DeepLynx](https://github.com/idaholab/Deep-Lynx) ecosystem. This is the first successfully launched digital twin of a fissile nuclear reactor that we are aware of. While the code is not complex, the problems of networking, policy, and initial groundwork were significant to overcome.

Darrington, JohnW.↗

Mneme

A simple tool allowing recording the execution of a GPU (CUDA) kernel and replaying that kernel as an independent executable. The tool operates in 3 phases. During compile time the user needs to apply a provided LLVM pass to instrument the code. The pass detects all device global variables and device functions and stores this information with the respective LLVM-IR in the global device memory. The compilation generates a record-able executable. The second phase involves running the application executable with a desired input and using LD_PRELOAD to enable recording. When recording before invoking a device kernel the pre-loaded library stores device memory in persistent storage and associates the memory with the device kernel and an LLVM IR file. At the end of the recorded execution the pre-load library generates a database in the form of a JSON file containing information regarding the LLVM-IR files and the snapshots of device memory. During the third and last phase the user can replay the execution of an kernel as a separate independent executable. Besides executing it the user can modify the LLVM IR file and auto-tune parameters such as kernel launch-bounds or kernel runtime execution parameters (e.g. Kernel Block and Grid Dimensions). Is

Parasyris, Konstantinos↗

Machine Learning Automation Pipeline

Machine Learning Automation Pipeline (MLAP) is a package to perform machine learning (ML) analysis in a step by step manner, starting with data extraction until analysis and prediction. The scripts provide the users option to chose an action such as "Extract", "Prep", and "Train" and numerous cases can be launched with just a single command. The inputs for each case are provided using a JSON file. The simulation results of several cases can be assessed using an automated process and analyzed for various metrics pertinent to ML analysis.

Jha, Pankaj↗

Eev (enrich Enforce Validate) With Cpefinder

This code is designed to take an existing STIX bundle with vulnerability data and enrich it with additional potential vulnerabilities to provide further insight during threat analysis. It also acts as a launch platform for other enrichments tools. The additional tools include, WAVgraph and STIXEnforcer.

Beckman, BryanR [Idaho National Laboratory (INL), ↗

MADA: Multi-Agent Design Assistant

MADA (Multi-Agent Design Assistant) is a Large Language Model (LLM) powered multi-agent framework that coordinates specialized agents for complex design workflows. The system was designed for HPC workflows with the following agents in mind: 1) A Job Management Agent (JMA) launches and manages ensemble simulations on HPC systems, 2) a Geometry Agent (GA) generates meshes, and 3) an Inverse Design Agent (IDA) proposes new designs informed by simulation outcomes. Our framework reduces cumbersome manual workflow setup, and enables automated design exploration at scale. However, the software also enables users to rapidly create new multi-agent systems. Simply define new agents in a configuration file, giving each their own set of tools (via MCP), and then chat and prompt your new multi-agent system. Is

Gunnarson, BrianS [Lawrence Livermore National Lab↗

mada-tools: MCP servers, configurations, skills, and examples for MADA

MADA-tools (Multi-Agent Design Assistant tools) is a library for defining MCP (Model Context Protocol) servers that can be used by AI agents in the MADA project. Each MCP server provides a focused set of tools that enhances an LLM's knowledge and capabilities for a specific domain, for example, how to launch jobs with Flux versus Slurm. The library makes it easy to configure and start multiple MCP servers using configuration files or command line options. Once running, these servers are intended to be consumed by one or more agents in the MADA ecosystem. The system is designed to be extensible so that future projects can contribute their own MCP servers, skills, and toolsets.

Gunnarson, BrianS [Lawrence Livermore National Lab↗

Energy Exascale Earth System Model v2.0

First release of version 2 of the Energy Exascale Earth System Model. The atmosphere component remains EAM. Major changes since version 1 include: all column-physics parameterizations are computed on a separate grid that has approximately half the number of points of the dynamics grid, a new nonhydrostatic dynamical core (running in hydrostatic mode) with semi-Lagrangian tracer transport, CLUBB updated from v1 to v2, a new convective trigger (dCAPE/ULL) based on the dynamic Convective Available Potential Energy (CAPE) (dCAPE) and the Unrestricted Launch Level (ULL) concepts is used in ZM. minimum cloud droplet number changed, gravity wave drag energy conservation fixed and new tunings used, dust emission size distribution changed to emit more coarse dust particles The land component is still ELM. Major changes since version 1 include: using SNICAR-AD for radiation in snow to match the sea-ice model and fixing bugs in snow compaction and water state calculation. The ocean component remains MPAS-ocean. Major change since version 1 include: Redi isopycnal mixing has been updated, tested, and tuned in combination with the Gent-McWilliams parameterization, a sign error was fixed in the 3rd-order flux routines, the mesh used in low-resolution coupled cases was modified and the time steps adjusted, new regionally refined meshes were created, one focused on North America and another on the Southern Ocean, including ice shelf cavities. The sea-ice component remains MPAS-seaice. Major changes since version 1 include: A new heat- and freshwater-conserving coupling of frazil ice, turning off of SSH filtering, addition of SNICAR-AD and snow grain aging. The land-ice component remains MPAS-Albany-landIce (MALI) and is a static ice sheet. There is more out-of-the-box support for cryosphere configurations including the new regionally refined configuration around Antarctica with ice shelf cavities. The river model is MOSART. The half-degree river mesh was redone so it no longer treats Black and Caspian seas as ocean. The coupler remains cpl7/MCT. Major changes since version 1 include handling of ice shelf melt fluxes (heat / freshwater exchange with the ocean), and data icebergs. All components allow regional refinement of their meshes and two separate example of refinement, one in and around North America and one around Antarctica and the Southern Ocean, are provided.

E3SM Project, DOE↗

New WMO Certified Megaflash Lightning Extremes for Flash Distance (768 km) and Duration (17.01 seconds) Recorded from Space

Initial global extremes in lightning duration and horizontal distance were established in 2017 by an international panel of atmospheric lightning scientists and engineers assembled by the WMO. The subsequent launch of NOAA’s latest GOES-16/17 satellites with their Geostationary Lightning Mappers (GLMs) enabled extreme lightning to be monitored continuously over the western hemisphere up to 55⁰ latitude for the first time. Consequently, the former lightning extremes were more than doubled in 2019 to 709 km for distance and 16.730 s for duration. Continued detection and analysis of lightning “megaflashes” has now revealed two flashes that even exceed those 2019 records. As part of the ongoing work of the WMO in detection and documentation of global weather extremes, an international WMO evaluation committee was created to critically adjudicate these two GLM megaflash cases as new records for extreme lightning.

54 ENVIRONMENTAL SCIENCES↗

Characterizing Overwater High Ozone Events in the Houston–Galveston–Brazoria Region during the 2021 GO3 and TRACER-AQ Campaigns

Photochemical modeling outputs showing high ozone concentrations over the Gulf of Mexico and Galveston Bay during ozone episodes in the Houston–Galveston–Brazoria (HGB) region have not been previously verified using in situ observations. Such data were collected systematically, for the first time, from July to October 2021 from three boats deployed for the Galveston Offshore Ozone Observations (GO3) and Tracking Aerosol Convection Interactions Experiment—Air Quality (TRACER-AQ) field campaigns. A pontoon boat and a commercial vessel operated in Galveston Bay, while another commercial vessel operated in the Gulf of Mexico offshore of Galveston. All three boats had continuously operating sampling systems that included ozone analyzers and weather stations, and the two boats operating in Galveston Bay had a ceilometer. The sampling systems operated autonomously on the two commercial boats as they traveled their daily routes. Thirty-seven ozonesondes were launched over water on forecast high ozone days in Galveston Bay and the Gulf of Mexico. During the campaigns, multiple periods of ozone exceeding 100 ppbv were observed over water in Galveston Bay and the Gulf of Mexico. These events included previously identified conditions for high ozone events in the HGB region, such as the bay/sea-breeze recirculation and postfrontal environments, as well as a localized coastal high ozone event after the passing of a tropical system (Hurricane Nicholas) that was not well forecast.

54 ENVIRONMENTAL SCIENCES↗