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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A “Master Curve” Describing Reaction Inhomogeneity and Plating Onset during Fast-Charging of Graphite Electrodes

Lithium plating in porous graphite electrodes is a major limitation for fast charging. Theoretical evidence suggests plating during fast charging is largely due to inhomogeneous intercalation through the electrode thickness (caused by ionic/mass transfer limitations and inherent thermodynamic properties of the graphite material). Numerical and analytical predictions of plating onset during fast charging have been proposed but not compared directly with experiments. This work validates these model predictions against plating onset measurements via the “dOCV” method in graphite half-cells, for various electrode thicknesses and C-rates. Remarkably, it is shown that experimental and theoretical trends in plating onset (vs C-rate and electrode thickness) collapse to a single “master curve” using a nondimensional “reaction inhomogeneity” parameter. This observation supports the hypothesized reaction inhomogeneity mechanism for accelerating plating onset and provides practical guidance for electrode design. Furthermore, this work develops theory to quantify reaction inhomogeneity in situ directly from voltage V vs capacity Q data, using dQ / dV analysis. Here again, experiments and numerical predictions show good agreement, where peaks that correspond to LiC 6 correlate with plating onset. This work provides experimental validation of theoretical tools that can predict plating onset, aid electrode design, and give insight for plating onset mechanisms during fast charging.

25 ENERGY STORAGE↗
DOE OSTI2021

Artificial Intelligence for Autonomous Molecular Design: A Perspective

Domain-aware artificial intelligence has been increasingly adopted in recent years to expedite molecular design in various applications, including drug design and discovery. Recent advances in areas such as physics-informed machine learning and reasoning, software engineering, high-end hardware development, and computing infrastructures are providing opportunities to build scalable and explainable AI molecular discovery systems. This could improve a design hypothesis through feedback analysis, data integration that can provide a basis for the introduction of end-to-end automation for compound discovery and optimization, and enable more intelligent searches of chemical space. Several state-of-the-art ML architectures are predominantly and independently used for predicting the properties of small molecules, their high throughput synthesis, and screening, iteratively identifying and optimizing lead therapeutic candidates. However, such deep learning and ML approaches also raise considerable conceptual, technical, scalability, and end-to-end error quantification challenges, as well as skepticism about the current AI hype to build automated tools. To this end, synergistically and intelligently using these individual components along with robust quantum physics-based molecular representation and data generation tools in a closed-loop holds enormous promise for accelerated therapeutic design to critically analyze the opportunities and challenges for their more widespread application. This article aims to identify the most recent technology and breakthrough achieved by each of the components and discusses how such autonomous AI and ML workflows can be integrated to radically accelerate the protein target or disease model-based probe design that can be iteratively validated experimentally. Taken together, this could significantly reduce the timeline for end-to-end therapeutic discovery and optimization upon the arrival of any novel zoonotic transmission event. Our article serves as a guide for medicinal, computational chemistry and biology, analytical chemistry, and the ML community to practice autonomous molecular design in precision medicine and drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

Microgravity Environment Characterization Program

The Microgravity Science and Applications Division (MSAD), a division within NASA's Office of Life and Microgravity Science and Applications, sponsors a broad range of space-based research in biotechnology, combustion science, fluid physics, fundamental physics, and materials science. To better understand and exploit the orbital environment, MSAD has developed methods and hardware to characterize accelerations on microgravity experiment carriers. MSAD supports research to verify analytically derived acceleration requirements for experiments and provides vibration isolation for sensitive experiments. The Microgravity Measurement and Analysis Project (MMAP), supported by MSAD, incorporates four projects: the Space Acceleration Measurement System (SAMS), the Orbital Acceleration Research Experiment (OARE), the SAMS for International Space Station (SAMS-II), and the Principal Investigator Microgravity Services (PIMS). SAMS was developed to record microgravity accelerations and the OARE was developed to record very low-frequency microgravity accelerations on-board the NASA Orbiters. The SAMS is also used for cooperative investigations on the Russian Mir space station. The SAMS-II is being developed for the same function on-board the International Space Station (ISS). PIMS utilizes microgravity acceleration data to develop a description of each microgravity mission's acceleration environment and to support microgravity investigators in interpreting possible effects of the acceleration environment on their experiments. These elements of the MSAD program will be used to define acceleration requirements for future Orbiter and ISS payloads. This paper describes the MMAP and summarizes the products and services available to principal investigators and other users. This paper also presents some microgravity acceleration characterization results from the last six years of Orbiter microgravity missions.

DeLombard, Richard↗
NASA NTRS2016

Suited and Unsuited Hybrid III Impact Testing and Finite Element Model Characterization

NASA spacecraft design requirements for occupant protection are a combination of the Brinkley Dynamic Response Criteria and injury assessment reference values (IARV) extracted from anthropomorphic test devices (ATD). For the ATD IARVs, the requirements specify the use of the 5th percentile female Hybrid III and the 95th percentile male Hybrid III. Each of these ATDs is required to be fitted with an articulating pelvis (also known as the aerospace pelvis) and a straight spine. The articulating pelvis is necessary for the ATD to fit into spacecraft seats, while the straight spine is required as injury metrics for vertical accelerations are better defined for this configuration. Sled testing of the Hybrid III 5th Percentile Female Anthropomorphic Test Device (ATD) was performed at Wright-Patterson Air Force Base (WAPFB). Two 5th Percentile ATDs were tested, the Air Force Research Lab (AFRL) and NASA owned Hybrid III ATDs with aerospace pelvises. Testing was also conducted with a NASA-owned 95th Percentile Male Hybrid III with aerospace pelvis at WPAFB. Testing was performed using an Orion seat prototype provided by Johnson Space Center (JSC). A 5-point harness comprised of 2 inch webbing was also provided by JSC. For suited runs, a small and extra-large Advanced Crew Escape System (ACES) suit and helmet were also provided by JSC. Impact vectors were combined frontal/spinal and rear/lateral. Some pure spinal and rear axis testing was also performed for model validation. Peak accelerations ranged between 15 and 20-g. This range was targeted because the ATD responses fell close to the IARV defined in the Human-Systems Integration Requirements (HSIR) document. Rise times varied between 70 and 110 ms to assess differences in ATD responses and model correlation for different impact energies. The purpose of the test series was to evaluate the Hybrid III ATD models in Orion-specific landing orientations both with and without a spacesuit. The results of these tests were used by the NASA Engineering and Safety Center (NESC) to validate the finite element model (FEM) of the Hybrid III 5th Percentile Female ATD. Physical test data was compared to analytical predictions from simulations, and modelling uncertainty factors have been determined for each injury metric. Additionally, the test data has been used to further improve the FEM, particularly in the areas of the ATD preload, harness, and suit and helmet effects.

Lawrence, C.↗
NASA NTRS2006

Accelerated Life Structural Benchmark Testing for a Stirling Convertor Heater Head

For proposed long-duration NASA Space Science missions, the Department of Energy, Lockheed Martin, Infinia Corporation, and NASA Glenn Research Center are developing a high-efficiency, 110 W Stirling Radioisotope Generator (SRG110). A structurally significant limit state for the SRG110 heater head component is creep deformation induced at high material temperature and low stress level. Conventional investigations of creep behavior adequately rely on experimental results from uniaxial creep specimens, and a wealth of creep data is available for the Inconel 718 material of construction. However, the specified atypical thin heater head material is fine-grained with a heat treatment that limits precipitate growth, and little creep property data for this microstructure is available in the literature. In addition, the geometry and loading conditions apply a multiaxial stress state on the component, far from the conditions of uniaxial testing. For these reasons, an extensive experimental investigation is ongoing to aid in accurately assessing the durability of the SRG110 heater head. This investigation supplements uniaxial creep testing with pneumatic testing of heater head-like pressure vessels at design temperature with stress levels ranging from approximately the design stress to several times that. This paper presents experimental results, post-test microstructural analyses, and conclusions for four higher-stress, accelerated life tests. Analysts are using these results to calibrate deterministic and probabilistic analytical creep models of the SRG110 heater head.

Krause, David L.↗
NASA NTRS1985

Ground effect aerodynamics

The results of experimental and analytical studies on an isolated lifting rotor in ground effect at low advance ratios are discussed. The experiments show that the favorable effect of ground proximity in hover disappears rapidly with small increases in advance ratio. Two flow regimes occur, a recirculation of the rotor wake is present at the low end of the advance ratio range investigated and a ground vortex is formed as advance ratio increases, causing irregular changes in the hub moments with advance ratio. Experimental results also show that translational acceleration has a significant effect on the ground effect of a lifting rotor. Hot wire measurements of the flow field under the ratio in ground effect are also presented. The experimental data are analyzed to determine effective values of the inflow in ground effect.

Curtiss, H. C., Jr.↗
NASA NTRS2000

Modal Analysis and Model Correlation of the Mir Space Station

This paper will discuss on-orbit dynamic tests, modal analysis, and model refinement studies performed as part of the Mir Structural Dynamics Experiment (MiSDE). Mir is the Russian permanently manned Space Station whose construction first started in 1986. The MiSDE was sponsored by the NASA International Space Station (ISS) Phase 1 Office and was part of the Shuttle-Mir Risk Mitigation Experiment (RME). One of the main objectives for MiSDE is to demonstrate the feasibility of performing on-orbit modal testing on large space structures to extract modal parameters that will be used to correlate mathematical models. The experiment was performed over a one-year span on the Mir-alone and Mir with a Shuttle docked. A total of 45 test sessions were performed including: Shuttle and Mir thruster firings, Shuttle-Mir and Progress-Mir dockings, crew exercise and pushoffs, and ambient noise during night-to-day and day-to-night orbital transitions. Test data were recorded with a variety of existing and new instrumentation systems that included: the MiSDE Mir Auxiliary Sensor Unit (MASU), the Space Acceleration Measurement System (SAMS), the Russian Mir Structural Dynamic Measurement System (SDMS), the Mir and Shuttle Inertial Measurement Units (IMUs), and the Shuttle payload bay video cameras. Modal analysis was performed on the collected test data to extract modal parameters, i.e. frequencies, damping factors, and mode shapes. A special time-domain modal identification procedure was used on free-decay structural responses. The results from this study show that modal testing and analysis of large space structures is feasible within operational constraints. Model refinements were performed on both the Mir alone and the Shuttle-Mir mated configurations. The design sensitivity approach was used for refinement, which adjusts structural properties in order to match analytical and test modal parameters. To verify the refinement results, the analytical responses calculated using original and refined math models were compared with the measured responses. The results from this study show that the refined models predict more accurately the dynamics of the actual structure. The MiSDE test and analysis results provided the information and experience on test design, flight testing, and data analysis for the ISS and other future spacecraft, which are critical to the verification of analytical models and structural loads.

Kim, Hyoung M.↗
DOE OSTI2021

Adaptive Spatially Aware I/O for Multiresolution Particle Data Layouts

Large-scale simulations on nonuniform particle distributions that evolve over time are widely used in cosmology, molecular dynamics, and engineering. Such data are often saved in an unstructured format that neither preserves spatial locality nor provides metadata for accelerating spatial or attribute subset queries, leading to poor performance of visualization tasks. Furthermore, the parallel I/O strategy used typically writes a file per process or a single shared file, neither of which is portable or scalable across different HPC systems. We present a portable technique for scalable, spatially aware adaptive aggregation that preserves spatial locality in the output. We evaluate our approach on two supercomputers, Stampede2 and Summit, and demonstrate that it outperforms prior approaches at scale, achieving up to 2.5× faster writes and reads for nonuniform distributions. Furthermore, the layout written by our method is directly suitable for visual analytics, supporting low-latency reads and attribute-based filtering with little overhead.

Usher, Will↗
DOE OSTI2021

Realizing the data-driven, computational discovery of metal-organic framework catalysts

Metal-organic frameworks (MOFs) have been widely investigated for challenging catalytic transformations due to their well-defined structures and high degree of synthetic tunability. These features, at least in principle, make MOFs ideally suited for a computational approach towards catalyst design and discovery. Nonetheless, the widespread use of data science and machine learning to accelerate the discovery of MOF catalysts has yet to be substantially realized. In this review, we provide an overview of recent work that sets the stage for future high-throughput computational screening and machine learning studies involving MOF catalysts. This is followed by a discussion of several challenges currently facing the broad adoption of data-centric approaches in MOF computational catalysis, and we share possible solutions that can help propel the field forward.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Molecular Dynamics Simulation of Complex Reactivity with the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) Software Package

Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time scales is a challenging task. Ab initio methods are unable to currently access these time scales routinely, and traditional molecular dynamics methods feature fixed bonding arrangements that cannot account for changes in the system’s bonding topology. The Multiscale Reactive Molecular Dynamics (MS-RMD) method, as implemented in the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) software package for the LAMMPS molecular dynamics code, offers a method to routinely sample longer time scale reactive simulation data with statistical precision. RAPTOR may also be interfaced with enhanced sampling methods to drive simulations toward the analysis of reactive rare events, and a number of collective variables (CVs) have been developed to facilitate this. Key advances to this methodology, including GPU acceleration efforts and novel CVs to model water wire formation are reviewed, along with recent applications of the method which demonstrate its versatility and robustness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Processing and Analytics System for Microscopy Data Workflows: The Pycroscopy Ecosystem of Packages

Major advancements in fields as diverse as biology and quantum computing have relied on a multitude of microscopy techniques. Despite the considerable proliferation of these instruments, significant bottlenecks remain in terms of processing, analysis, storage, and retrieval of the acquired datasets. Aside from lack of file standards, individual domain-specific analysis packages are often disjoint from the underlying datasets, and thus keeping track of analysis and processing steps remains tedious for the end-user, hampering reproducibility. Here, in this study, the pycroscopy ecosystem of packages is introduced, an open-source python-based ecosystem underpinned by a common data model. The data model, termed the N-dimensional spectral imaging data format, is realized in pycroscopy's sidpy package. This package is built on top of dask arrays, thus leveraging dask array attributes, but expanding them to accelerate microscopy relevant analysis and visualization. Several examples of the use of the pycroscopy ecosystem to create workflows for data ingestion and analysis of scanning transmission electron microscopy (STEM) and scanning probe microscopy data are shown. Adoption of such standardized routines will be critical to usher in the next generation of autonomous instruments where processing, computation, and meta-data storage will be critical to overall experimental operations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Energy diffusion of pickup ions upstream of comets

A steady state model of pickup ion energization upstream of a cometary bow wave is presented in order to investigate the effects of quasi-linear energy diffusion in the turbulence there. The model assumes that the ions are immediately isotropized at pickup, and it includes the effects of adiabatic acceleration in the slowing solar wind and of continual pickup of ions as the comet is approached. By taking all physical quantities to fall off as power laws with distance from the comet, an analytical expression is obtained for the distribution function of pickup ions in the reference frame moving with the solar wind. To illustrate the application of this model, the model results are compared to the observations of pickup ions at comet Giacobini-Zinner. At present, this is the only cometary encounter for which sufficient quantitative information is available. The model does not compare well with these observations, but it is not clear whether the differences are due to artificial problems in the model or the data analysis or to the action of other energization processes at this comet. Preliminary results from the Halley encounters appear to agree more closely with this model.

Isenberg, Philip A.↗
NASA NTRS2022

Spectral Power-law Formation by Sequential Particle Acceleration in Multiple Flare Magnetic Islands

We present a first-principles model of pitch-angle and energy distribution function evolution as particles are sequentially accelerated by multiple flare magnetic islands. Data from magnetohydrodynamic (MHD) simulations of an eruptive flare/coronal mass ejection provide ambient conditions for the evolving particle distributions. Magnetic islands, which are created by sporadic reconnection at the self-consistently formed flare current sheet, contract and accelerate the particles. The particle distributions are evolved using rules derived in our previous work. In this investigation, we assume that a prescribed fraction of particles sequentially "hops" to another accelerator and receives an additional boost in energy and anisotropy. This sequential process generates particle number spectra that obey an approximate power law at mid-range energies and presents low- and high-energy breaks. We analyze these spectral regions as functions of the model parameters. We also present a fully analytic method for forming and interpreting such spectra, independent of the sequential acceleration model. The method requires only a few constrained physical parameters, such as the percentage of particles transferred between accelerators, the energy gain in each accelerator, and the number of accelerators visited. Our investigation seeks to bridge the gap between MHD and kinetic regimes by combining global simulations and analytic kinetic theory. The model reproduces and explains key characteristics of observed flare hard X-ray spectra as well as the underlying properties of the accelerated particles. Our analytic model provides tools to interpret high-energy observations for missions and telescopes, such as RHESSI, FOXSI, NuSTAR, Solar Orbiter, EOVSA, and future high-energy missions.

magnetic reconnection↗
DOE OSTI2026

Surface Water Quality Data from Beaver-Impacted Streams; Trail Creek and East River, Colorado 2025

This data package contains surface water chemistry measurements collected in 2025 to evaluate how beaver damming and low-tech process-based stream restoration influence water quality and metal mobility in mountainous headwater systems of the Upper Colorado River Basin. Sampling was conducted at Trail Creek (Taylor Park watershed, Colorado), a tributary undergoing restoration through installation of low-tech process-based structures (i.e., beaver dam analogs), and at off-channel beaver ponds within the East River floodplain (East River watershed, Colorado). Samples were collected along longitudinal transects spanning upstream control reaches, beaver-influenced ponded reaches, and downstream segments. Additional samples were collected from near-surface pore waters within a beaver dam seepage face. The dataset includes concentrations of major and trace elements measured by inductively coupled plasma–mass spectrometry (ICP-MS) and inductively coupled plasma–optical emission spectrometry (ICP-OES), major anions measured by ion chromatography (IC), and dissolved organic carbon (DOC; reported as non-purgeable organic carbon, NPOC). Samples were size-fractionated at 0.45 micrometers (µm), 0.22 µm, and 0.02 µm to distinguish particulate (>0.45 µm), colloidal (0.22–0.02 µm), and dissolved (<0.02 µm) fractions. The data package consists of comma-separated value (.csv) files containing tabulated chemical concentration data, sample metadata (site identifiers, geographic coordinates, sampling dates, fraction type), and quality control flags. All files are provided in open, non-proprietary formats that can be accessed using standard data analysis software such as Microsoft Excel, R, Python, MATLAB, or other programs capable of reading .csv files. Units, detection limits, and analytical methods are documented in accompanying metadata files. The dataset is designed to support analyses of (1) how beaver impoundment and restoration structures alter elemental partitioning and transport, (2) the role of iron and organic carbon in mediating trace metal mobility, and (3) reach-scale changes in water quality across restoration gradients. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

Anions↗
NASA NTRS1978

Comparison of wing-span averaging effects on lift, rolling moment, and bending moment for two span load distributions and for two turbulence representations

An analytical method of computing the averaging effect of wing-span size on the loading of a wing induced by random turbulence was adapted for use on a digital electronic computer. The turbulence input was assumed to have a Dryden power spectral density. The computations were made for lift, rolling moment, and bending moment for two span load distributions, rectangular and elliptic. Data are presented to show the wing-span averaging effect for wing-span ratios encompassing current airplane sizes. The rectangular wing-span loading showed a slightly greater averaging effect than did the elliptic loading. In the frequency range most bothersome to airplane passengers, the wing-span averaging effect can reduce the normal lift load, and thus the acceleration, by about 7 percent for a typical medium-sized transport. Some calculations were made to evaluate the effect of using a Von Karman turbulence representation. These results showed that using the Von Karman representation generally resulted in a span averaging effect about 3 percent larger.

Lichtenstein, J. H.↗
NASA NTRSDate not supplied

Soyuz Landing Reconstructions

Introduction: Recent data show a landing-attributed injury rate among Soyuz crew members to be higher than predicted in original certification analysis. New vehicles being developed for NASA are being certified using analytical tools to quantify injury risk. This assessment will provide data to allow the Agency to evaluate whether these tools are able to capture true injury risk and allow a comparison between Soyuz landings and upcoming vehicles. Methods: A finite element model (FEM) of the Soyuz descent module (DM) and its landing environment were developed to recreate Soyuz landing conditions. Occupant breakout models composed of the Soyuz seat and Sokol helmet were then developed to evaluate occupant response. These models included both anthropomorphic test device (ATD) and human body model (HBM) surrogates in three anthropometric sizes. A generalized distribution analysis of the Soyuz landing environment was performed using landing variable distributions from available literature. Results were used to identify trends in vehicle landing acceleration with landing conditions and to compare landing model injury risk predictions with those estimated in vehicle certification analysis. Next, historic Soyuz landings identified as inducing occupant injury during were reconstructed using the developed landing model and estimated landing conditions. Results and Discussion: This assessment demonstrated the capability of certification metrics, which include a combination of vehicle- and occupant-level injury risk analysis, to identify elevated injury risk landing conditions. However, the developed landing load predictions were limited by available vehicle and landing condition data. Additional data, particularly landing acceleration data specific to historic Soyuz landing conditions, would greatly enhance this assessment’s findings.

Preston Greenhalgh↗
DOE OSTI2022

Exploring the Use of Novel Spatial Accelerators in Scientific Applications

Driven by the need to find alternative accelerators which can viably replace GPUs in next-generation Supercomputing systems, this paper proposes a methodology to enable agile application/hardware co-design. The application-first methodology provides the ability to come up with design of accelerators while working with real-world workloads, available accelerators, and system software. The iterative design process targets a set of kernels in a workload for performance estimates that can prune the design space for later phases of detailed architectural evaluations. To this effect, in this paper, a novel data-parallel device model is introduced that simulates the latency of performance-sensitive operations in an accelerator including data transfers and kernel computation using multi-core CPUs. The use of off-the-shelf simulators, such as pre-RTL simulator Aladdin or multiple tools available for exploring the design of deep neural network accelerators (e.g., Timeloop) is demonstrated for evaluation of various accelerator designs using applications with realistic inputs. Examples of multiple device configurations that are instantiable in a system are explored to evaluate the performance benefit of deploying novel accelerators. The proposed device is integrated with a programming model and system software to potentially explore the impacts of high-level programming languages/compilers and low-level effects such as task scheduling on multiple accelerators. We analyze our methodology for a set of applications that represent high-performance computing (HPC) and graph analytics. The applications include a computational chemistry kernel realized using tensor contractions, triangle counting, GraphSAGE and Breadth-first Search. These applications include kernels such as dense matrix-dense matrix multiplication, sparse matrix-spare matrix multiplication, and sparse matrix-dense vector multiplication. Our results indicate potential performance benefits and insights for system design by including accelerators that realize these kernels along-side general purpose accelerators.

AI, codesign, Accelerated Computing, Modeling and ↗
DOE OSTI2025

MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8) for advanced open-source tritium transport and fuel cycle modeling

Tritium management is critical for the safety, sustainability, and economics of fusion energy systems, and advanced and reliable modeling tools help accelerate the development of tritium technologies. This paper presents the Tritium Migration Analysis Program, Version 8 (TMAP8), an open-source, MOOSE-based application developed to provide state-of-the-art tritium transport and fuel cycle modeling capabilities. TMAP8 aims to expand the capabilities of previous versions (i.e., TMAP4 and TMAP7) by leveraging modern computational techniques, ensuring high software quality assurance standards (key to building trust), and enabling multispecies, multiscale, and multiphysics simulations for integrated tritium transport modeling in complex geometries. This paper outlines TMAP8’s scope and rigorous development practices, emphasizing its transparency, accessibility, modularity, and reliability. We present the current suite of verification and validation cases based on those from TMAP4, demonstrating TMAP8’s accuracy and reliability against analytical solutions and experimental data. Additionally, the paper showcases TMAP8’s integrated fuel cycle modeling capabilities, highlighting its applicability at various scales and levels. The TMAP8 code and documentation are openly available, promoting collaborative development and widespread adoption within the fusion community. Future work will soon expand TMAP8’s verification and validation suite to include those from TMAP7 and other recent experimental studies for validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗