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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Absolute Neutron Rate Measurement and Non-Thermal/Thermonuclear Fusion Differentiation

The goal of fusion energy is to produce significantly more energy from fusion reactions than is input into the device. One of the products of fusion reactions is neutrons, which, due to their lack of charge, provide a unique view into the parameters of the device. Lawrence Livermore National Laboratory (LLNL) in collaboration with the University of California, Berkeley (UCB) have designed, assembled, and fielded a robust and portable neutron detection system known as PANDA (Portable and Adaptable Neutron Diagnostics for ARPA-E). This detector suite consists of three LaBr activation detectors that are calibrated to give a total neutron yield on shot, and twenty-four scintillators coupled to photo-multiplier tubes (SPMT). The SPMTs can be configured to attain spatial, temporal and/or energy information from fusion neutrons. The system was designed to be portable and is compartmentalized so that individual components can be used at different fusion facilities. During the duration of this work, part of the system was installed at the FuZE facility, a part of Zap Energy. Another component was installed that the CESZAR facility at the University of California, San Diego (UCSD) to support experiments by Magneto-Inertial Fusion Technologies, Inc. (MIFTI). The diagnostics were successful at both locations and the LLNL/UCB team supported the data analysis by creating and running analysis scripts and Monte-Carlo calculations. At Zap Energy the diagnostics demonstrated that the fusion from the FuZE device is thermonuclear in nature, a result that resulted in an invited talk at the American Physical Society Division of Plasma Physics and an invited paper. Additionally, temporal and spatial data was taken using the SPMTs to understand the duration and length of fusion production. At UCSD the neutron yield from the diagnostics was used to show improvements to fusion yields on their gas puff Z-pinch when using a gas shell surrounding the fuel. The success in this diagnostic has led to continued work at both Zap Energy and MIFTI, as well as follow on funding and interest at other fusion energy companies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

MLOps for Beam Controls

Machine learning operations (MLOps) is the standardization and streamlining of the ML development lifecycle to address the challenges associated with large-scale machine learning applications. The full MLOps pipeline consists of open-source tools: DataHub, MinIO and MLflow. It is being used for dataset management and model development to handle changing data dependencies, varying business needs, reproducibility, and diverse teams working with differing tools and skills. To demonstrate the completion of an MLOps pipeline for particle accelerator operations, we are deploying a simple script that computes settings for the Booster’s gradient magnet power supply. Once the demonstration is complete, we will develop and deploy ML-based optimization algorithms to improve Booster’s overall efficiency. This MLOps pipeline opens the gate to systematically develop and deploy ML applications for accelerator controls and diagnostics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Automated Generation of Weather and Climate Analysis Products

Wind roses are an important part to site operations as they depict the wind speed and direction percentage over a time period. In this project, I automated the production of wind roses for SRS meteorological towers. I developed a script to sequence through the dataset by period and create a wind rose for each of those period sets. Graphics were generated for every 4-hour period of the day, for each of the 4 heights of the instruments, for every half of each month. A 10-year climatological period consisted of wind speed and directions measurements at 15-minute intervals. We used the years 2014-2024 as the wind instruments on the tower were upgraded to sonic anemometers in early 2014. I then compared these wind roses to those from a previous study done in 2003 to analyze the differences and similarities in the wind patterns. The wind roses are also used to understand environmental transport conditions at SRS. When comparing the different heights of the anemometers to the 2003 report, there is a similarity in the fact that the direction is relatively the same across the levels, with the wind speeds increasing as you get higher in the air. When comparing the season of our graphs against the 2003 report, we noticed that the winter and summer months appear to have very similar wind directions. However, in the spring we noticed that there were more southerly winds compared to the 2003 report which had more westerly winds. Finally, in the fall months, we noticed that there was a higher percentage of northeasterly winds, while the 2003 report showed more southeasterly winds. We can use these summaries to estimate the directional dependence of dose that the surrounding areas receive throughout the year according to time of day.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Processing MCNP Elemental Edit Outputs

The Monte Carlo N-Particle (MCNP) transport code version 6 (also known as MCNP6) has the capability for tracking particles on unstructured mesh (UM) geometry models embedded into constructive solid geometry (CSG) cells. A UM geometry is a collection of elements representing a solid geometry. The first step of MCNP UM modeling is using other software packages to create a finite element mesh representation of a solid 3D geometry. Computer-aided design (CAD) or computer-aided manufacturing (CAM) software is typically used to create a solid geometry model, which is later imported into mesh generation software to create a UM model. The MCNP UM feature was originally designed for models generated by the Abaqus/CAE software. The MCNP code version 6.0 and later can process UM models formatted as Abaqus input files. MCNP can process a UM model consisting of several different element types including linear tetrahedral or hexahedral elements and calculate quantities of interest such as flux and energy deposition at elements. An MCNP UM simulation provides high-fidelity elemental edit (i.e., tally) outputs, which can be further used in multiphysics calculations. The MCNP UM feature was used for multiphysics simulations where quantities of interest calculated by MCNP are used as inputs for heat transfer calculations in Abaqus. MCNP6.3 can produce two types of elemental edit output (EEOUT) file formats: ASCII and HDF5. An EEOUT file type must be requested on an EMBED card while output type (flux or energy deposition) must be requested on an EMBEE card. We wrote Python3 scripts to extract energy deposition values in an ASCII or HDF5 EEOUT file and compute a heat flux profile for an Abaqus heat transfer calculation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Evaluating the Nation's Pipeline Infrastructure with NETL's Advanced Infrastructure Integrity Model (AIIM)

This poster is a part of BIL-EDX4CCS Task 36: Advanced Infrastructure Integrity Modeling to Evaluate Existing Energy Infrastructure Reusability and Risk, the goal of which is to produce a smart tool that will assess existing energy infrastructure reusability and risk using the Advanced Infrastructure Integrity Model (AIIM). This model forecasts lifespan and potential risk using a multitude of factors such as incidents reports, structural characteristics, and the surrounding environment. The project aims to provide scientific insights for a better understanding of carbon storage (CS), potential to support CS stakeholder needs, national decarbonization, and mitigating climate change. AIIM will utilize an energy infrastructure database as its input, developed by acquiring publicly available data as well as NETL derived products. These resources include incidents, geohazards, and infrastructure variables. Soil data in the form of rasters and pipeline incident reports were processed and a script was developed to count the number of times features such as roads, railroads, and rivers intersected with pipeline segments which were then converted to points. Distance to oil and natural gas wells, petroleum ports, intermodal freight facilities, and geologic structures were also calculated. After data preparation and quality control was completed, the data was integrated into the pipeline points. Once models are complete, a smart tool will be created in the form of an online dashboard.

Malay, Caleb↗
DOE OSTI2024

Integration Development and Testing of Rear Transition Monitor for Beam Current Monitoring System

Addressing baseline effects in accelerator environments is crucial for accurate data acquisition and analysis, since baseline effects can obscure signal clarity and impact the reliability of beam current monitoring systems. There are many potential contributors to baseline noise, such as variations in beam dynamics, electromagnetic interference from nearby equipment, or RF interference. Previous applications of noise reduction systems don t sufficiently filter sources of asynchronous noise, so a new algorithm was implemented. A simulation dataset was created to replicate beam conditions and a Red Pitaya FPGA was used to collect data through the streaming application. A Python script was developed to implement noise reduction algorithms and efforts were made to integrate real-time data streaming with the Redis platform and Acnet Front End infrastructure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

WELLBASE - An Interactive Platform for Wellbore Material Assessment

This project seeks to build an open-source wellbore material data repository with adequate material performance and contextual data to support Geological Carbon Storage (GCS). By appropriately evaluating the data types as mentioned earlier made available by the WELLBASE tool, stakeholders can make more informed decisions regarding well selections, risk assessment, and economic analysis for geologic carbon storage projects. Advanced Natural Language Processing models and other custom python scripts will be deployed in an automated process to extract unstructured data from documents, reports, and web applications and subsequently parse to more usable formats. The processed data will then be integrated into a robust and comprehensive database architecture, optimizing data accessibility, and usability for analytical purposes. The final data products will be accessible through a user-friendly visualization platform that will allow users to query and visualize the data, as well as download data in usable formats.

Tetteh, Daniel A.↗
DOE OSTI2023

Finite Element Analysis System Workflow Tools

A collection of MATLAB functions and class definitions called System Workflow Tools (SWFT) are available to semi-automate steps in the simulation process. Some of these steps are often simple and routine for smaller finite element models, but if done directly by an analyst can quickly become labor intensive, cumbersome, and error prone for larger, system level models. Some of SWFT’s capabilities demonstrated in this report includes writing Sierra input decks and processing Quantities of Interest (QOI) from results files. SWFT also writes scripts in order to utilize other software programs such as Cubit (separating system level CAD into subassemblies and components, creating nodesets and sidesets), DAKOTA (ensemble management), and ParaView (contour plots and animations). Detailed commands and workflows from mesh generation to report generation are provided as examples for analysts to utilize SWFT capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Numerical Modeling and Optimization of the iProTech Pitching Inertial Pump (PIP) Wave Energy Converter (WEC) (Cooperative Research and Development Final Report, CRADA Number: CRD-22-22968)

This work generated a first-of-its-kind automated workflow to couple time-domain simulations of wave energy converters written in one software language with a set of design generation and evaluation scripts written in another software language. This automated workflow used an existing optimization package to analyze the sensitivity of different design parameters on the power output of a specific WEC, iProTech’s Pitching Inertial Pump (PIP). Geometric, inertial, and power take-off variables were all varied and optimized to find values that produced the highest amount of power generated over varying wave conditions. The findings on these parameter sensitivity studies are used to inform future design iterations of the PIP WEC. Including more design variables in the optimizations will only increase computational run time and further software development is needed to analyze a larger optimization.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile

This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data.<p>To access the NETL Natural Gas Lifecycle model, visit https://doi.org/10.18141/2476250.</p><p>To access the 2020 Report Appendices, visit https://doi.org/10.18141/2438472.</p>

03 NATURAL GAS↗
DOE OSTI2024

Training NuGraph2 for ICARUS

This presentation describes the process of training NuGraph2, a Graphical Neural Network for event reconstruction, on simulated ICARUS neutrino event data. This began with an investigation into filtering ICARUS spacepoint data. Then NuGraph2 was repeatedly trained on three event samples, which were used for finding optimized machine-learning parameters and to find and fix the causes of several crashes in NuGraph2 s preprocessing and training scripts.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

DASSH-F: Subchannel Based Thermal Analysis

The DASSH thermal analysis code is designed to rapidly allow a reactor design engineer to obtain flow rates requirements that satisfy peak temperature constraints in the domain. The advantage of using DASSH over a hand calculation is that it has a more rigorous treatment of the pin power distribution and coolant heat transfer within an assembly and between assemblies. The advantage of using DASSH over a conventional 3D subchannel code or a computational fluid dynamics code (CFD) is that it can obtain the desired solution in a matter of minutes in serial with minor computer memory needs. The DASSH methodology is virtually identical to SUPERENERGY-2 with additional functionalities taken from follow on work to SUPERENERGY-2 done at ANL in the 1980s. DASSH today is an integral component of the Argonne Fast Reactor analysis suite for reactor design work. DASSH obtains the power distribution from a coupled neutron-gamma heating calculation in GAMSOR (including DIF3D) at each time point of a companion fuel cycle analysis calculation with REBUS. The domain in DASSH assumes a hexagonal grid typical for fast reactors with much of the geometry information taken from the DIF3D model. DASSH assumes the assemblies that are loaded into each grid position are ducted to control the coolant flow. Considerable detail is given on the subchannel formulation of DASSH in this document. Much of the formulation and design of the code builds upon research done by previous authors with little new investigation. Thus the decisions made in developing the subchannel model used in DASSH have their origins over 50 years ago. Much of the heat transfer methodology in DASSH is built upon correlations for both the coolant mixing and heat transfer coefficients for pins and ducts. DASSH is thus not a rigorous treatment of a given problem, but a rapid assessment of the temperature field that has known limitations with respect to an experimental measurement or CFD calculation. The DASSH input and output are detailed along with usage of the software. The DASSH output provides tables of evaluated material properties and key coolant and pin temperature results. DASSH can create Python scripts that generate domain summary pictures. DASSH can also generate assembly temperature maps and VTK output files which allow the DASSH solution to be visualized. As the primary purpose of the DASSH software is to compute the coolant and fuel pin temperature distribution for a given model of a reactor, much of the output focus is giving the user quick summary tables needed to assess the performance of a given orifice flow specification. The present version of DASSH has a crude orifice search capability and an efficient orifice flow search capability. The flow search tries to meet user specified constraints for 1) peak 2-sigma clad midwall temperature, 2) peak coolant temperature, and 3) desired bulk outlet temperature. There are many development shortcomings in DASSH detailed in this document, but this version is functional for modern analysis needs. This document serves as the manual for the Fortran based DASSH software that was developed to replace the Python version of DASSH developed as part of the VTR program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Light Output Fitting Software

Light output response of scintillators is crucial to the utilization of organic scintillators as effective tools in radiation detection and measurement. While the response is a continuous distribution, the light output corresponding to the maximum energy deposition is crucial in effectively understanding and simulating a detector. There are a variety of fits derived in literature that will vary for every detector material. The Light Output Response Fitter, or LORF Program is a python script designed to easily and quickly compute and plot fits for a variety of scintillator light output models. It includes a stopping power library constructed from SRIM including Organic Glass, EJ309, EJ301, Stilbene, EJ276, and their deuterated counterparts by default, with the ability for the user to add custom stopping power libraries. The user is also capable of importing the python package and utilizing its in-built functions as appropriate. Uses for this capability include plotting and computing a model with known parameters.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Developing a Prototype Methodology to Rank CO2-EOR Wells and Assess Their Reuse Potential for Geologic Carbon Sequestration

This study presents a prototype methodology for evaluating the reuse potential of Class II CO₂-enhanced oil recovery (CO₂-EOR) wells as Class VI wells for geologic carbon sequestration. The approach focuses on assessing wellbore construction materials—casing, cement, tubing, and packers—based on U.S. Environmental Protection Agency (EPA) Class VI well conversion guidelines. Utilizing Python scripts and JSON representations, the methodology automates checks on digitized Texas Railroad Commission (TRRC) data to rank wells based on regulatory and integrity criteria. Key factors include casing integrity, cementing techniques, tubing compatibility, and packer selection. Due to limitations in digitized data, manual verification is required for certain sections. Future enhancements include incorporating non-digitized data via web scraping and machine learning. This research provides a practical framework for well owners and regulators, supporting informed decision-making for sustainable CO₂ storage.

carbon sequestration↗
DOE OSTI2025

On the Computation of the Beam Position in the Arcs of the Hadron Storage Ring

To compensate for the velocity differences of the hadrons and electrons in the Electron-Ion Collider, the hadron beam will be operated in a large range of the radial displacement (±20 mm in the 64 mm wide vacuum chamber). Machine protection and beam optics measurement require high-accuracy calculations of the beam position from the signal induced on the pickup electrodes. For the HSR, we need at least the fifth-order polynomial fit, which provides 70 microns r.m.s. error in the 40 by 20 mm region of interest as shown in Fig. 1. The calculations are made using a MATLAB script solving the 2D electrostatic problem.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Flexible Integration of Diverse HVAC Technologies in EnergyPlus via Python-Enabled Workflows

Analysis of advanced controls and novel system types is often not directly feasible in building energy simulation tools. Various techniques extend building energy simulation tool capabilities to allow the use of user-defined scripts and programs, but these approaches have limitations. The EnergyPlus Python plugin offers users new flexibility to use EnergyPlus to call an external Python module at specific points in the simulation, as well as to use Python to call EnergyPlus functionality through an application programming interface (API). This paper presents four case studies leveraging the EnergyPlus Python plugin to facilitate analysis of advanced controls and system types. The use of the Python plugin offers greater modularity and flexibility relative to previous approaches, is less error prone, and is simpler for users to adopt. The Python plugin allows EnergyPlus to be used in a more flexible manner and to accommodate the expanding realm of energy modeling applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Electron Beam Irradiation for Water Treatment of Per- and Polyfluoroalkyl Substances (PFAS)

Per- and polyfluoroalkyl substances (PFAS) are widely used but are now considered a water contamination risk. Fermi National Accelerator Laboratory’s IARC group has demonstrated that passing water through electron beam radiation can destroy PFAS. This project aims to develop a process to scale the system for bulk water treatment. The key is efficient radiation usage, ensuring that all water receives only the minimum dose. Software was developed for this purpose, consisting of a computational fluid dynamics model (CFD) in COMSOL, which calculates particle trajectories through the radiation area. A MATLAB script integrates the radiation dose of these particles, and statistical analysis is performed to evaluate the radiation utilization efficiency. These models are validated with a flow test where colored dye is injected and optically tracked. Radiation dose is measured by testing under an e-beam to measure the degradation of a PFAS analog.

Mueller, Scott [Northern Illinois U.]↗
DOE OSTI2025

Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile

This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data. This is revision 1 of the 2024 study (published December 17, 2024 and updated on January 24, 2025) and corrects a modeling error in natural gas composition. See the errata on page 2 for more information.

03 NATURAL GAS↗