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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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Shiny interface for the Lipid Mining and Ontology (Lipid Mini-On) tool, which uses the Rodin R package The software allows users to mine and perform enrichment of lipid based on their molecular characteristics, classification at multiple levels.
We plan to release the code used to perform the experiment described in our recent publication, entitled “Determining the dominant factors for carbon-1 mineralization in three-dimensional fracture networks.” This code fits a joint emulator to data from several Discrete Fracture Network (DFN) simulations, performed using the open-source software DFNworks (https://dfnworks.lanl.gov/). All code to be released implements existing methods; there are no novel algorithms nor any major innovations to existing software.
A software framework to study, from the performance and energy perspective, the efficacy of GPU-resident parallel Conjugate Gradient (CG) linear solver with different preconditioner options, including Gauss-Seidel, Jacobi, and incomplete Cholesky. We also propose a novel GPU-based preconditioner, in which the triangular solves are approximated by an iterative process
Final technical report for the "Exploiting Global View for Resilience" project. The GVR project aims to create a new approach to portable, resilient applications. The GVR approach builds on a global view data model,, adding versioning (multi-version), user control of timing and rate (multi-stream), and flexible cross layer error signalling and recovery. With a versioned array as a portable abstraction, GVR enables application programmers to exploit deep scientific and application code insights to manage resilience (and its overhead) in a flexible, portable fashion.
The Comprehensive Automated Welder System - PDRD SR-17-007 project was initiated to develop hardware and software to eliminate possible error pre-cursor functions of the pinch welding process that require manual manipulation and data entry as well as leveraging 21st century technology advances by replacing obsolete hardware with state of the art maintainable equipment. The project plan targeted three primary areas for improvement: 1. Replacing the existing welding power supply system with a solid-state power supply, 2. Improving the data acquisition system, sensors and controls, and 3. Updating the software to a FPGA “real-time” program with automated steps. SRNL purchased, designed and installed in 723-A, a system to meet the requirements for these areas. While improvements in hardware controls and sensor selection were achieved and a successful software automation routine was demonstrated, the performance goals were not met with the custom solid-state power transformer.
The existing methods that determine heliostat aiming strategies for concentrating solar power (CSP) central receiver plants typically use heuristics and/or are computationally expensive, and they lack flexibility for different desired flux profiles and receiver geometries. Because of the interaction between layout and aimpoint strategy, considering the former without accounting for the latter may yield solutions with superfluous heliostats that cannot be used efficiently without compromising receiver flux constraints. To that end, we develop a software decision tool that uses innovative optimization methods to both optimize aimpoint strategies and improve candidate layouts for the solar collection field of a CSP central receiver plant. A CSP plant’s effectiveness relies on the optical efficiency of the solar field, which may be limited by losses due to (i) the cosine effect, (ii) atmospheric attenuation, (iii) interference (i.e., shading and blocking) between heliostats, (iv) spillage as a result of heliostat positioning and geometry, and (iv) some heliostats’ inability to direct irradiance to the receiver without damage due to excessive thermal flux. The goal of this work is to obtain optimized aiming strategies and improved solar field layouts that reduce capital cost and increase field optical efficiency and utilization, while meeting the power requirements of a given CSP receiver design. We formulate the aimpoint optimization problem as a mixed-integer linear programming model, which we then decompose into submodels that we solve in parallel. The decomposition subdivides the solar field into sections, and aimpoint strategies for each section are obtained independently of the others. To improve existing layouts, we develop a utilization-weighted efficiency metric that we use to relocate heliostats to sections of the solar field with similar efficiency and higher utilization. Finally, to connect our software to high-fidelity flux models, we develop a Python application programming interface for SolarPILOT, a mature software package that characterizes solar field performance and generates the heliostat layouts and flux maps that serve as input to our models.
Closeout report for FALLACY project. The performance of Data Model Convergence Initiative (DMC) applications on parallel machines is far below the limit set by Amdahl’s law. Whether the machine is based on many-core, GPUs, FPGAs, or a heterogeneous combination, usually the most significant bottleneck is accessing data from the memory system. Aligning with DMC’s HW/architecture thrust, this project developed a set of memory-centric tools called ‘MemGaze’ that inform the HW/SW stack about an application’s memory behavior, including data access latency and diagnosing poor data layout and data composition. Our approach uses architectural modeling and analysis of workload data accesses.
With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary. AI applied to NPP operations could resemble the use of digital I&C (DI&C) because such applications involve digital computer hardware and custom-designed software that input plant data, execute complex software algorithms, and output the results to a system or licensed human operator to potentially provoke an action. For AI methods to be compliant with current safety requirements for DI&C, AI compatibility must be evaluated, and AI-related gaps may exist that prevent the prompt deployment of AI in NPPs. This effort aims to evaluate how example AI technologies align with the DI&C safety framework, and discusses how they could be analyzed, modeled, tested, and validated in a manner similar to typical DI&C technologies. Because AI is a broad field that encompasses areas such as machine learning (ML), natural language processing, and computer vision, this research focused on a subset of methods categorized as the computer vision ML (CVML) methods. This report explores two CVML use cases, gauge reading and fire watch, considered relevant to the DI&C standards, as they could play a safety-critical role. For the gauge reading use case, a CVML-enabled technology that can read gauges at oblique angles is utilized. For the fire watch use case, a CVML-enabled technology is utilized that migrates fire watch from a manual (human) approach to automated fire detection. These use cases are mainly intended to give context to the CVML system discussion. This effort assumes the worst-case scenario, with the CVML system being used to replace a safety-related or risk-significant system, thus requiring evaluation. Evaluating CVML against most of the relevant safety requirements for DI&C yielded several CVML-specific considerations due to the uniqueness of its characteristics in comparison with typical DI&C systems. For example, CVML models often employ commonly used (open-source) datasets, and it is not always possible to determine the level of overlap among open-source datasets. Therefore, the independence of the developed CVML models when demonstrating diversity is questionable, therefore creating vulnerability to common cause failure (CCF). The design verification process is also impacted since the data overlap could result in overestimation of the software validation and verification (V&V) performance results. Section 2 of this report evaluates a list of the identified CVML-specific characteristics and discusses the resulting considerations and potential solutions in the context of each referenced requirement. A summation is provided in Section 3. This report is not to be used as a guideline. It was developed to identify and consider issues in the implementation of ML technologies used to augment activities that may have a bearing on plant operation. The report draws parallels to the use of DI&C technologies, for which many standards are available to guide their use in nuclear plant operation. It considers the technologies and some of the potential implications of their use in safety-related applications but is not intended to address regulatory or licensing related issues.
In support of NA-23’s objective to accelerate the establishment of a reliable commercial United States (U.S.) domestic supply of 99Mo produced without the use of highly enriched uranium (HEU), the Pacific Northwest National Laboratory (PNNL) was tasked with modeling the performance of activated carbon delay and guard beds that may be typical for non-HEU 99Mo production processes. The specific tasks accomplished by PNNL included calculations of long-term effects of iodine on delay bed performance and development of a finite element simulation to better understand delay bed performance under various scenarios specifically with radioxenon and radioiodine decay heating of the delay beds. The main issue of interest in this study is understanding the effect of iodine on the abatement performance of the beds if iodine is not sufficiently removed from gases prior to reaching the delay beds. Finite element simulations of delay bed performance were developed using COMSOL Multiphysics® Software. These simulations are based on partial differential equations that describe xenon and iodine adsorption, heat transfer and decay of radioxenon and radioiodine isotopes. Heat transfer in the activated carbon beds is simulated with a heat source tied to the decay of radioactive xenon and iodine species. These simulations were used to investigate delay bed temperature and hold up time using radioxenon and radioiodine activities and flowrates expected from a non-HEU production process. A bounding case scenario was simulated, where all the iodine was released into the delay beds due to insufficient guarding of the delay beds. In addition, preliminary investigations of the guard beds were conducted.
This presentation will cover an abstract that has been submitted to the conference, but will not include a paper publication. The presentation details an experimental method for calibrating quantum bits and quantum circuits. All of the data on the slides has been gathered via PyGSTi, an open-source Python-based software developed by Sandia's Quantum Performance Laboratory.
In 2025, KAERI and Argonne initiated a collaboration based on software validation using data from tests performed at KAERI’s STELLA-2 facility. STELLA-2 is a large-scale sodium thermal-hydraulic test facility that was originally developed to support KAERI’s development of the PGSFR design concept. KAERI has performed a large number of tests at STELLA-2, providing valuable data to support sodium fast reactor code validation. KAERI will be conducting new tests in 2026, targeting system conditions that were not achieved during previous test campaigns. KAERI has requested from Argonne proposed tests that could be performed during the upcoming test campaign. This report documents Argonne’s proposed tests in fulfillment of KAERI’s request.
This project advances the development and application of the TEMPO transportation energy systems model to support DOE analysis of evolving mobility futures. Recent work has focused on improving model transparency, performance, and fidelity through a redesigned software architecture and updated technology adoption scenarios aligned with the latest data and assumptions. Ongoing efforts aim to expand TEMPO's ability to assess transportation affordability and consumer decision-making, including vehicle ownership dynamics and distributional impacts across households. These enhancements position TEMPO to better inform policy and R&D decisions by providing more behaviorally realistic and policy-relevant insights into transportation energy use, technology adoption, and system-level outcomes.
This Phase II Body-Fixed, Three-Axis Reference System Study Final Report is the result of a follow-on contract awarded by NASAIMSFC to TRW Systems in April 1966, under Contract No, NASS-20209. of the Phase I1 Study was to refine and supplement the strapdown inertial ’ reference assembly (SIRA), software, airborne computer, and alignment analyses performed during Phase I of the same contract. The purpose Specifically, the Phase I results in many areas were those which could be achieved using simplifying assumptions (linearization) and hand analyses. It was the purpose of the Phase I1 studies to investigate the validity of the Phase I results by means of more sophisticated computer simulations, in which no simplifying assumptions were made, for each of the areas analyzed. The Phase 11 analyses were directed, therefore, at confirming the analytical feasibility asserted by the Phase I results.
A family of computer programs facilitating the design, layout, evaluation, and testing of digital electronic circuitry is described. CADAT (computer aided design and test system) is intended for use by NASA and its contractors and is aimed predominantly at providing cost effective microelectronic subsystems based on custom designed metal oxide semiconductor (MOS) large scale integrated circuits (LSIC's). CADAT software can be easily adopted by installations with a wide variety of computer hardware configurations. Its structure permits ease of update to more powerful component programs and to newly emerging LSIC technologies. The components of the CADAT system are described stressing the interaction of programs rather than detail of coding or algorithms. The CADAT system provides computer aids to derive and document the design intent, includes powerful automatic layout software, permits detailed geometry checks and performance simulation based on mask data, and furnishes test pattern sequences for hardware testing.
A highly fault tolerant digital computer system has been configured based on extensive experience with flight proven, redundant digital flight control systems. The feasibility of minimizing hardware complexity is shown while maintaining high levels of fault tolerance. The emerging hardware design combines reconfiguration concepts with conventional hardware redundancy techniques and special operational software to provide dual fail operate performance with a basic triplex system. The design provides high reliability and flight safety, enhances maintainability, and reduces life cycle cost while offering improved performance for future aircraft.
Problems inherent in the deployment and management of a worldwide tracking and data acquisition network to support the two Viking Orbiters and two Viking Landers simultaneously over 320 million kilometers (200 million miles) of deep space are discussed. Activities described include tracking coverage of the launch phase, the deep space operations during the long cruise phase that occupied approximately 11 months, and the implementation of the a vast worldwide network of tracking sttions and global communications systems. The performance of the personnel, hardware, and software involved in this vast undertaking are evaluated.
A comprehensive computer program for the modeling of wind energy and storage systems utilizing any combination of five types of storage (pumped hydro, battery, thermal, flywheel and pneumatic) was developed. The level of detail of Simulation Model for Wind Energy Storage (SIMWEST) is consistent with a role of evaluating the economic feasibility as well as the general performance of wind energy systems. The software package consists of two basic programs and a library of system, environmental, and load components. The first program is a precompiler which generates computer models (in FORTRAN) of complex wind source storage application systems, from user specifications using the respective library components. The second program provides the techno-economic system analysis with the respective I/O, the integration of systems dynamics, and the iteration for conveyance of variables. SIMWEST program, as described, runs on the UNIVAC 1100 series computers.
The SMM attitude ground support system (AGSS) supports the acquisition of spacecraft roll attitude reference, performs the in-flight calibration of the attitude sensor complement, supports onboard control autonomy via onboard computer data base updates, and monitors onboard computer (OBC) performance. Initial roll attitude acquisition is accomplished by obtaining a coarse 3 axis attitude estimate from magnetometer and Sun sensor data and subsequently refining it by processing data from the fixed head star trackers. In-flight calibration of the attitude sensor complement is achieved by processing data from a series of slew maneuvers designed to maximize the observability and accuracy of the appropriate alignments and biases. To ensure autonomy of spacecraft operation, the AGSS selects guide stars and computes sensor occultation information for uplink to the OBC. The onboard attitude control performance is monitored on the ground through periodic attitude determination and processing of OBC data in downlink telemetry. In general, the control performance has met mission requirements. However, software and hardware problems have resulted in sporadic attitude reference losses.