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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

MO-B-BRB-03: 3D Dosimetry in the Clinic: Validating Special Techniques

Full three-dimensional (3D) dosimetry using volumetric chemical dosimeters probed by 3D imaging systems has long been a promising technique for the radiation therapy clinic, since it provides a unique methodology for dose measurements in the volume irradiated using complex conformal delivery techniques such as IMRT and VMAT. To date true 3D dosimetry is still not widely practiced in the community; it has been confined to centres of specialized expertise especially for quality assurance or commissioning roles where other dosimetry techniques are difficult to implement. The potential for improved clinical applicability has been advanced considerably in the last decade by the development of improved 3D dosimeters (e.g., radiochromic plastics, radiochromic gel dosimeters and normoxic polymer gel systems) and by improved readout protocols using optical computed tomography or magnetic resonance imaging. In this session, established users of some current 3D chemical dosimeters will briefly review the current status of 3D dosimetry, describe several dosimeters and their appropriate imaging for dose readout, present workflow procedures required for good dosimetry, and analyze some limitations for applications in select settings. We will review the application of 3D dosimetry to various clinical situations describing how 3D approaches can complement other dose delivery validation approaches already available in the clinic. The applications presented will be selected to inform attendees of the unique features provided by full 3D techniques. Learning Objectives: L. John Schreiner: Background and Motivation Understand recent developments enabling clinically practical 3D dosimetry, Appreciate 3D dosimetry workflow and dosimetry procedures, and Observe select examples from the clinic. Sofie Ceberg: Application to dynamic radiotherapy Observe full dosimetry under dynamic radiotherapy during respiratory motion, and Understand how the measurement of high resolution dose data in an irradiated volume can help understand interplay effects during TomoTherapy or VMAT. Titania Juang: Special techniques in the clinic and research Understand the potential for 3D dosimetry in validating dose accumulation in deformable systems, and Observe the benefits of high resolution measurements for precision therapy in SRS and in MicroSBRT for small animal irradiators Geoffrey S. Ibbott: 3D Dosimetry in end-to-end dosimetry QA Understand the potential for 3D dosimetry for end-to-end radiation therapy process validation in the in-house and external credentialing setting. Canadian Institutes of Health Research; L. Schreiner, Modus QA, London, ON, Canada; T. Juang, NIH R01CA100835.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-B-BRB-04: 3D Dosimetry in End-To-End Dosimetry QA

Full three-dimensional (3D) dosimetry using volumetric chemical dosimeters probed by 3D imaging systems has long been a promising technique for the radiation therapy clinic, since it provides a unique methodology for dose measurements in the volume irradiated using complex conformal delivery techniques such as IMRT and VMAT. To date true 3D dosimetry is still not widely practiced in the community; it has been confined to centres of specialized expertise especially for quality assurance or commissioning roles where other dosimetry techniques are difficult to implement. The potential for improved clinical applicability has been advanced considerably in the last decade by the development of improved 3D dosimeters (e.g., radiochromic plastics, radiochromic gel dosimeters and normoxic polymer gel systems) and by improved readout protocols using optical computed tomography or magnetic resonance imaging. In this session, established users of some current 3D chemical dosimeters will briefly review the current status of 3D dosimetry, describe several dosimeters and their appropriate imaging for dose readout, present workflow procedures required for good dosimetry, and analyze some limitations for applications in select settings. We will review the application of 3D dosimetry to various clinical situations describing how 3D approaches can complement other dose delivery validation approaches already available in the clinic. The applications presented will be selected to inform attendees of the unique features provided by full 3D techniques. Learning Objectives: L. John Schreiner: Background and Motivation Understand recent developments enabling clinically practical 3D dosimetry, Appreciate 3D dosimetry workflow and dosimetry procedures, and Observe select examples from the clinic. Sofie Ceberg: Application to dynamic radiotherapy Observe full dosimetry under dynamic radiotherapy during respiratory motion, and Understand how the measurement of high resolution dose data in an irradiated volume can help understand interplay effects during TomoTherapy or VMAT. Titania Juang: Special techniques in the clinic and research Understand the potential for 3D dosimetry in validating dose accumulation in deformable systems, and Observe the benefits of high resolution measurements for precision therapy in SRS and in MicroSBRT for small animal irradiators Geoffrey S. Ibbott: 3D Dosimetry in end-to-end dosimetry QA Understand the potential for 3D dosimetry for end-to-end radiation therapy process validation in the in-house and external credentialing setting. Canadian Institutes of Health Research; L. Schreiner, Modus QA, London, ON, Canada; T. Juang, NIH R01CA100835.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

SAGIPS: A scalable Framework for scidac quantom

As part of the Scientific Discovery through Advanced Computing (SciDAC) program, the Quantum Chromodynamics Nuclear Tomography (QuantOM) project aims to analyze data from Deep Inelastic Scattering (DIS) experiments conducted at Thomas Jefferson National Accelerator Facility and the upcoming Electron Ion Collider. The DIS data analysis is performed on an event level by taking into leveraging nuclear theory models and accounting for experimental conditions. In order to efficiently run multiple analyses under varying conditions, a composable workflow was designed where each section (theory, experiment, objective minimization, etc.) has its own dedicated module. This presentation gives an overview over of the current status of this workflow, highlights present and future challenges, and highlights possible extensions to other projects with similar requirements.

Lersch, Daniel [Thomas Jefferson National Accelera↗
DOE OSTI2021

Design-Space Data: Informing Common Design Decisions with Pre-Simulated Data

Design Space Exploration (DSE) analysis techniques represent a data-centric approach to integrating performance analysis in early design phases when there is the greatest potential to cheaply improve the energy efficiency of a building. We focus on a novel extension of DSE called Universal Design Space Exploration (UDSE), which leverages massive databases of pre-simulated analysis that represent all possible outcomes of common analysis workflows. These databases, called Design Spaces, become “universal” when a single pre-simulated design space can be re-applied to future unknown projects. Unlike current simulation methods, which require a design to exist before it can be analyzed and often take minutes or hours to simulate, UDSE leverages pre-simulation to deliver rapid and relevant insight as new designs are conceptualized. The data underpinning UDSE enables advanced statistical and Artificial Intelligence methods, allowing UDSE to deliver a greater understanding of the larger problem being explored, rather than simply delivering analysis of several pre-conceived design options. We believe that UDSE can provide instantaneous, relevant analysis for all building design projects at negligible cost. This paper has two main goals, to develop a relevant Universal Design Space that showcases the potential of UDSE and to release this data freely to industry and academia; thereby lowering the barrier to entry to digital literacy in statistics, ML and AI within the architecture, engineering, construction (AEC) industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Solar Spectrum Conversion for an Algae Bioreactor (CRADA Final Report)

This project focused on developing advanced optical coatings to improve solar energy utilization. The research aimed to create lanthanide-doped upconversion nanoparticles (UCNPs) capable of capturing unused near-infrared (NIR) light from the sun and converting it into visible light (blue and red photons) that can be used for photosynthesis. The primary goal was to identify, synthesize, and integrate highly efficient UCNPs into a transparent thin-film device. Through a comprehensive workflow involving computer simulations, high-throughput robotic synthesis, and detailed optical characterization, the project successfully developed a high-performance material. The key technical achievement was the creation of a core-shell UCNP (NaYF₄:20%Yb³⁺, 2%Er³⁺ coated with a 10 nm NaYF₄ shell) that demonstrated a quantum yield of 3.2% for converting 980 nm NIR light into visible light. Transparent thin films fabricated from these nanoparticles showed excellent optical properties, confirming their potential for practical applications. This research adds to the scientific understanding of energy transfer in lanthanide materials and demonstrates a technically effective method for creating efficient light-converting coatings. The primary benefit to the public lies in the potential for these coatings to enhance the efficiency of solar-driven processes, such as boosting the growth of algae in photobioreactors for biofuel production.

14 SOLAR ENERGY↗
DOE OSTI2026

Active learning enables generation of molecules that advance the known Pareto front

Although generative models hold promise for discovering molecules with optimized desired properties, they often fail to suggest synthesizable molecules that improve upon the properties of the structures represented in the training distribution. We find that this limitation arises not only from the molecule generation process itself, but also from the poor generalization capabilities of molecular property predictors. We address this challenge by creating a closed-loop molecule generation pipeline with iterative retraining on new quantum chemical simulation data. Compared against static, single-pass generative modeling approaches, only our closed-loop iterative workflow generates molecules with properties extending beyond the training distribution (up to 0.44 standard deviations beyond the original range) and achieves a 79% improvement in out-of-distribution molecule classification accuracy. Furthermore, by conditioning molecular generation on thermodynamic stability data obtained during the iterative loop, the proportion of stable and hence potentially synthesizable molecules generated is 3.5x higher than the next-best model.

Chemistry↗
DOE OSTI2025

Tailoring composition and deformation modes at the microstructural level for next generation low-cost high-strength austenitic stainless steels

The objective of this project is to enable deliberate development of cost-effective, hydrogen resistant alloys by establishing detailed relationships specific to the effects of alloy composition, short-range order (SRO), and microsegregation in the presence of hydrogen on the transition between homogeneous deformation and localized plasticity in shear bands. In collaboration with the International Institute for Carbon-Neutral Energy Research, I2CNER, at Kyushu University in Japan, we conceptualized, designed, and manufactured four austenitic alloys that maintain corrosion resistance and ensure lower cost relative to baseline commercial alloys. The mechanical properties and deformation modes of the novel alloys (KU alloys) were assessed in the presence of hydrogen (H). Correlations between composition and performance revealed that two of the KU alloys are suitable replacements for 316 steel, while another is a viable replacement for 304 steel at room temperature. We found that, in the presence of other austenite stabilizing elements namely Mn and N, replacing Ni with Cu does not lead to martensite formation as has been previously reported.1–3 Furthermore, we found that the addition of Cu leads to an earlier onset of multiple slip resulting in an relative earlier onset of a higher work hardening rate (WHR). Greater understanding of the relationships between alloy composition and SRO required the development of a novel advanced electron diffraction methodology to characterize SRO in complex FCC alloys. This innovative approach, which combines fluctuation and correlation analyses of diffuse-scattering signals, successfully differentiated between SRO and long-range ordering (LRO). Further investigations into annealed austenitic stainless steels could provide insights into manipulating SRO and its effects on material properties. Atomistic simulations provided understanding of SRO behavior that was difficult to capture experimentally. This project created the first spin cluster expansion model that is able to capture and describe SRO effects in Fe-Ni-Cr FCC alloys, accounting for the non-negligible effects of magnetism. An automated computational workflow was established to provide reliable predictions of SRO in Fe-Ni-Cr austenitic alloys, both with and without the presence of H atoms. Analysis of the propensity for SRO in Fe-Ni-Cr alloys revealed that H tends to cluster with specific, well-defined SRO domains. The computational framework is general purpose and can be extended to realistic stainless steels across diverse composition ranges. With confidence that SRO is possible in austenitic stainless steels, we developed a discrete dislocation finite element code to understand the interaction of dislocations with SRO in the presence of H. By incorporating H effects on the dislocation emission and SRO stress field we show that the critical stress for the dislocation pileup to breakthrough the SRO domain decreases in the presence of H, which directly contributes localized deformation at the macroscale. Through the simulation of a uniaxial tension test, we demonstrated that H-induced weakening of SRO stress field and H-enhanced dislocation emission can lead to the onset of shear localization at lower macroscopic strains. As a whole, this project identified three novel alloys that show improvements in performance and cost efficiency for H-facing applications by studying correlations between alloy chemistry and deformation behavior. We also made significant advancements to experimental and computational methodologies necessary to study the chemistry and distribution of SRO across a range of alloys, which in turn allowed us to demonstrate how deformation mechanisms change due to the contributions of SRO in austenitic alloys in the presence of H. The combined advancements in fundamental understanding with novel alloy development in this project has increased the viability of next generation H-technologies for the broader public through accessible low-cost alloys and accelerated development towards future H-infrastructure.

08 HYDROGEN↗
DOE OSTI2018

Design-to-Device Approach Affords Panchromatic Co-sensitized Solar Cells

Data–driven materials discovery has become increasingly important in identifying materials that exhibit specific, desirable properties from a vast chemical search space. Synergic prediction and experimental validation are needed to accelerate scientific advances related to critical societal applications. A design–to–device study that uses high–throughput screens with algorithmic encodings of structure–property relationships is reported to identify new materials with panchromatic optical absorption, whose photovoltaic device applications are then experimentally verified. The data–mining methods source 9431 dye candidates, which are auto–generated from the literature using a custom text–mining tool. These candidates are sifted via a data–mining workflow that is tailored to identify optimal combinations of organic dyes that have complementary optical absorption properties such that they can harvest all available sunlight when acting as co–sensitizers for dye–sensitized solar cells (DSSCs). Six promising dye combinations are shortlisted for device testing, whereupon one dye combination yields co–sensitized DSSCs with power conversion efficiencies comparable to those of the high–performance, organometallic dye, N719. Here, these results demonstrate how data–driven molecular engineering can accelerate materials discovery for panchromatic photovoltaic or other applications.

14 SOLAR ENERGY↗
DOE OSTI2026

A Step-by-Step Protocol from METASPACE to Biological Interpretation

Mass spectrometry imaging (MSI) represents an exceptional tool for exploring complex biological systems spatially at the molecular level. However, due to its multidimensional nature and large-scale data output, it presents considerable challenges when it comes to extracting meaningful biological insights. Recent advancements, such as the METASPACE platform, have enabled researchers to efficiently process, annotate, and interpret MSI datasets by leveraging machine learning and cloud-based infrastructure. In this tutorial, we present a detailed and user-friendly R-pipeline designed to help METASPACE users navigate untargeted metabolomic annotations and transform them into practical insights about their biological systems. By combining METASPACE annotations with rapid R-based screening, this workflow not only streamlined the analytical process but also enhanced the understanding of spatial molecular distribution, especially for complex systems. Here, this easy-to-follow approach has the potential for applications in diagnostics, drug discovery, environmental and ecological processes, and more. We envision this pipeline to be particularly useful for newcomers to the field of MSI and

Moreno Pedraza, Abigail↗
DOE OSTI2020

Accelerating Scientific Computing in the Post-Moore’s Era

Novel uses of graphical processing units for accelerated computation revolutionized the field of high-performance scientific computing by providing specialized workflows tailored to algorithmic requirements. As the era of Moore’s law draws to a close, many new non–von Neumann processors are emerging as potential computational accelerators, including those based on the principles of neuromorphic computing, tensor algebra, and quantum information. While development of these new processors is continuing to mature, the potential impact on accelerated computing is anticipated to be profound. We discuss how different processing models can advance computing in key scientific paradigms: machine learning and constraint satisfaction. Significantly, each of these new processor types utilizes a fundamentally different model of computation, and this raises questions about how to best use such processors in the design and implementation of applications. While many processors are being developed with a specific domain target, the ubiquity of spin-glass models and neural networks provides an avenue for multi-functional applications. Furthermore, this also hints at the infrastructure needed to integrate next-generation processing units into future high-performance computing systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Surrogate Model Integration with MOOSE XFEM for Creep Crack Growth

Ferritic-martensitic steels are key structural materials for advanced reactors but experience time-dependent deformation and damage under prolonged high temperature and irradiation, leading to creep-driven crack initiation and growth. High-fidelity models—crystal plasticity with irradiation mechanisms, phase-field for microstructural evolution, and continuum-damage viscoplasticity—capture the underlying physics but are too computationally intensive for broad design-space exploration and uncertainty quantification. This milestone advances a scalable alternative by integrating a microstructure-sensitive surrogate creep model into the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework and extending it to fracture via the extended finite element method (XFEM). The surrogate model, developed with collaborators at Sandia and Los Alamos National Laboratories, maps relevant microstructural descriptors to the viscoplastic response of HT9. We embed this surrogate within a coupled deformation-damage workflow in MOOSE/XFEM to simulate creep-driven crack initiation and propagation. Implementation enhancements include updates to the material interface, a plastic correction phase involving microstructure evolution, and fracture criteria to ensure numerical robustness and compatibility with the surrogate structure. Demonstrations on canonical creep benchmarks spanning uniaxial and multiaxial states show that the surrogate reproduces key trends of high-fidelity models while substantially reducing computational cost. The resulting capability bridges physics fidelity and performance, providing a practical path to a predictive, microstructure-aware assessment of creep and fracture in reactor materials.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Two-step neutronics calculations with Shift and Griffin for advanced reactor systems

This research develops the initial coupling of the Shift Monte Carlo (MC) code and the Griffin reactor physics code for reactor analysis of non–light-water reactor systems. The novelty of this work is twofold. It is the first application of Shift to produce the multigroup cross sections needed for Griffin as applied to a non–light-water reactor system; and, the first investigation and analysis of characteristics of the Empire microreactor benchmark that should be considered for steady state and transient reactor physics calculations. This application uses the previously developed two-step neutronics analysis workflow to demonstrate this initial coupling. Here, we outline the two-step neutronics analysis workflow in which the Shift MC code is used to generate the multigroup cross sections and fluxes needed by the Griffin deterministic solver. Details on how these multigroup cross sections are generated using MC tallies are given, as well as the practicalities and limitations of the two-step neutronics workflow. The Empire microreactor benchmark was used to investigate and validate this coupling. Results using this benchmark show good agreement between Griffin calculations using Serpent-generated cross sections and Shift-generated cross sections. Analysis of the characteristics of this Empire benchmark show larger eigenvalue differences between heterogeneous and pin–homogenized solutions compared to those of traditional light-water reactor (LWR) designs, thus requiring super homogenization factor corrections for accurate eigenvalue and power distribution predictions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Crossroads Workflows

The Department of Energy (DOE) compute facilities operate as resources for the National Nuclear Security Administration (NNSA) and Office of Science. In this document we describe a subset of scientific work flows which are run on current platforms. There is significant commonality to how Los Alamos National Laboratory (LANL), Sandia National Laboratory (SNL), Lawrence Liver- more National Laboratory (LLNL) and the National Energy Research Scientific Computing Center (NERSC) operate and conduct scienti c inquiry with supercomputers. In addition to presenting the commonality between the sites, we believe that opportunities exist to significantly optimize the operation of our facilities and more rapidly advance our scientific goals. In describing how our scientific work flows move from inception to realization we believe that we can enable significant improvements in how computer architectures support real scientific work flows. Briefly, in order for a team of scientists to access the large supercomputers at these facilities, the team must be granted an allocation. Allocations last for a fixed amount of time (usually 6 or 12 months), and a large number of teams will have overlapping allocations ensuring that a large amount of work is available in the scheduling queue. During the allocation, the scientists will construct work flows as described in this document. Many simultaneous allocations may use identical work flows with different data and scientific goals.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Structural and Stratigraphic Controls on Methane Hydrate occurrence and distribution: Gulf of Mexico, Walker Ridge 313 and Green Canyon 955: Final Report

The goal of this project was to determine structural and stratigraphic controls on hydrate occurrence and distribution in Green Canyon (GC) 955 and Walker Ridge (WR) 313 blocks using seismic and well data. Gas hydrate was discovered in these blocks in coarse- and fine-grained sediments during the 2009 Joint Industrial project (JIP) Leg 11 drilling expedition. Although the immediate interest of the exploration community is exclusively hydrate which is present in coarse–grained sediments, factors that control hydrate and free gas distribution in the two blocks and whether coarse and fine-grained hydrate-bearing units are related in any manner, formed the core of this research. The project spanned from 10/01/2012 to 07/31/2016. In the project, in both the leased blocks, the interval spanning the gas hydrate stability zone (GHSZ) was characterized using a joint analysis of sparse Ocean Bottom Seismic (OBS) and dense, surface–towed multichannel seismic (MCS) data. The project team had the luxury of calibrating their results with two well logs. Advance processing methods such as depth migration and full-waveform inversion (FWI) were used for seismic data analysis. Hydrate quantification was achieved through interpretation of the FWI velocity field using appropriate rock physics models at both blocks. The seismic modeling/inversion methodology (common to both GC955 and WR313 blocks) was as follows. First, the MCS data were depth migrated using a P-wave velocity (VP) model constructed using inversion of reflection arrival times of a few (four in both cases) key horizons carefully picked in the OBS data to farthest possible offsets. Then, the resolution of the traveltime VP model was improved to wavelength scale by inverting OBS gathers up to the highest frequency possible (21.75 Hz for GC955 and 17.5 for WR313) using FWI. Finally, the hydrate saturation (or the volume fraction) was estimated at the well location assuming one of the other hydrate morphology (filling the primary or the secondary porosity) was extrapolated out from the wells using the FWI VP as a guide. General outcomes were as follows. First and foremost, an imaging methodology using sparse seismic data, which is easily replicable at other sites with similar datasets, has been demonstrated. The end product of this methodology at both the leased blocks is quantitative estimates of hydrate distribution. Second, at both locations there is strong evidence that the base of the GHSZ, which does not appear as a clear Bottom Simulating Reflection (BSR), manifests in the VP perturbations created by FWI, suggesting that FWI is sensitive to subtle compositional changes in shallow sediments and establishes it as a valuable tool for investigations of hydrate-bearing basins. Third, through joint interpretation of the depth migrated image and the FWI VP model, how structure and stratigraphy jointly determine hydrate and free gas distribution in both blocks could be clearly visualized. The joint interpretation also suggests that the coarse and fine grained hydrate-bearing sediments at both leased are connected. Site specific results, in addition to general results, are as follows. At GC955 the overlying fine-grained hydrate-bearing unit could have been sourced from the underlying hydrate coarse-grained channel-levee complex through a chimney feature. The channel-levee system at GC955 is compartmentalized by faults, of which only a few may be impermeable. Although compartmentalized, the channel-levee system in the GC955 as a whole might be in communication except selected zones. At WR313 the overlying fine-grained fracture-filled hydrate unit appears to be sourced from below the GHSZ. The reason that only a particular fine-grained unit has hydrate, despite having lower porosity that the bounding units, could be the presence of secondary porosity (such as those formed from clay dewatering under compaction). In conclusion, the project was a pioneering effort in in joint analysis of OBS and MCS datasets for advancing the knowledge about a hydrate and free–gas system dynamics using advanced processing methods such as FWI and depth migration. Results obtained in this project can greatly advance the tools and techniques used for delineating specific hydrate prospects. Results obtained in this project can also be seamlessly incorporated into other DOE funded project on modeling the potential productivity and commercial viability of hydrate from sand-dominated reservoirs. The OBS and MCS data in this project were acquired in 2012 (after the JIP II drilling) by the USGS and therefore the results are a posteriori. Nonetheless, the seismic inversion workflow established through this project can be used to generate various what-if quantification scenarios even in absence of logs and serve as a valuable tool for guiding drilling operations. Results from this project can augment other DOE sponsored projects on determining the commercial viability of methane production from the Gulf of Mexico.

03 NATURAL GAS↗
DOE OSTI2017

Digital Rock Physics and 3D Printing for Fractured Porous Media

Imaging techniques for the analysis of porous structures have revolutionized our ability to quantitatively characterize geomaterials. Digital representations of rock from CT images and physics modeling based on these pore structures provide the opportunity to further advance our quantitative understanding of fluid flow, geomechanics, and geochemistry, and the emergence of coupled behaviors. Additive manufacturing, commonly known as 3D printing, has revolutionized production of custom parts with complex internal geometries. For the geosciences, recent advances in 3D printing technology may be co-opted to print reproducible porous structures derived from CT-imaging of actual rocks for experimental testing. The use of 3D printed microstructure allows us to surmount typical problems associated with sample-to-sample heterogeneity that plague rock physics testing and to test material response independent from pore-structure variability. Together, imaging, digital rocks and 3D printing potentially enables a new workflow for understanding coupled geophysical processes in a real, but well-defined setting circumventing typical issues associated with reproducibility, enabling full characterization and thus connection of physical phenomena to structure. Here we report on our research exploring the possibilities that these technologies can bring to geosciences for coupled multiscale experimental and numerical analysis using 3D printed fractured rock specimens.

42 ENGINEERING↗
DOE OSTI2023

BUILD: Binary Understanding and Integration Logic for Dependencies (Final Report)

Increasingly diverse mission needs, the emergence of AI and cloud, and increasing hardware diversity are driving HPC software to be more complex. Modern codes are built from hundreds of small, complex components, and much of the software development process involves integrating these components rather than developing new components from scratch. The goal of the BUILD project was to ease the task of software integration for developers across LLNL’s programs. The project focused on (1) modeling software compatibility, (2) modeling ABI compatibility with binary analysis, (3) developing solver techniques to reason about compatibility, and (4) developing AI/ML models to fill gaps in our understanding of software compatibility. The project has developed several key technologies that help developers—by accelerating development workflows, removing the need for rebuilds, and enabling faster, automatic, and less error-prone code sharing. These technologies are used in LLNL codes and will be ready for the new El Capitan Exascale system in Livermore Computing. Many of these technologies have been hardened and integrated with LLNL’s Spack package manager, and they are already in use by production code teams. Results of BUILD have laid the groundwork for future advances in software integration—the ML and binary modification techniques developed in this project still need to be operationalized but have great potential to further speed up software integration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Data, model inputs, and analysis scripts associated with a manuscript on stream intermittency controls across spatial scales in Pacific Northwest watersheds

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript "Hydroclimatic Memory and Watershed Template Shape Stream Intermittency: Multi-scale Attribution Using Process-based Simulation and Explainable ML" by Niroula et al. (2026), submitted to Water Resources Research (WRR). The study investigates the dominant controls on stream intermittency across local, reach, and watershed scales using a coupled process-based simulation and explainable machine-learning framework. Long-term daily simulations from the Advanced Terrestrial Simulator (ATS) were used to generate wetness states and ponded-depth responses over river-corridor cells. These ATS outputs were then aggregated across scales and used to train XGBoost (eXtreme Gradient Boosting) models. SHAP (SHapley Additive exPlanations) was applied to quantify the relative importance of hydroclimatic forcings, watershed template attributes, and antecedent-memory effects in shaping intermittency behavior. The analysis is carried out for three contrasting Pacific Northwest watersheds: Oak Creek (OCW), American River Watershed (ARW), and H.J. Andrews (HJA). Across these testbeds, the package contains ATS-ready watershed inputs, ATS run configuration and selected output files, model-evaluation data products, intermittency-analysis datasets, machine-learning target-feature tables, SHAP outputs, and notebooks used to organize, analyze, and visualize results. At a high level, the package documents a workflow in which ATS provides the physically based simulation backbone and explainable machine learning is used as a post-processing attribution tool. The contents are intended to support interpretation of the manuscript figures and results, provide context for how intermittency metrics were generated at multiple scales, and preserve the key artifacts needed to understand and reuse the analysis workflow. The package contains a high-level directory summary file (`summary.txt`) and four main content folders (1) `evaluation_plots` contains evaluation figures and supporting evaluation datasets; (2) `intermittency_plots` contains intermittency-focused analysis notebook and prepared datasets; (3) `ml-training-and-shap_values_plots` contains ML training inputs, SHAP outputs, and figure-generation notebooks; and (4) `watershed_mesh_and_ats_input` contains ATS model setup materials, forcing inputs, geometry, and selected run files. More specifically, the `evaluation_plots` folder contains the notebook used for ATS evaluation plotting and site-specific evaluation datasets. These include evapotranspiration and water-balance products for three watersheds, as well as an Oak Creek field-measurement discharge file. The `intermittency_plots` folder contains the notebook used for intermittency analysis and the prepared datasets used to analyze intermittent and non-intermittent wetness behavior across the study watersheds. The `ml-training-and-shap_values_plots` folder contains notebooks and outputs for the machine-learning and explainability workflow. This includes the main XGBoost and SHAP notebook(s), a beeswarm plotting notebook, target-feature tables for machine-learning training, SHAP summary tables, and per-sample SHAP value archives. The `watershed_mesh_and_ats_input` folder contains ATS-related watershed inputs and supporting materials. This includes mesh and shape products, ATS-readable LAI and meteorological forcing inputs, selected ATS spinup and transient-run files, and a watershed workflow example notebook. Subdirectories are organized by watershed where applicable.All files are .cpg (codepage files), .csv (comma-separated values), .dbf (database files), .exo (Exodus mesh format), .h5 (HDF5 format), .ipynb (Jupyter notebooks), .pkl (Python pickle), .prj (projection files), .sh (shell scripts), .shp (shapefile geometry), .shx (shapefile index), .txt (text files), or .xml (markup data).

Advanced Terrestrial Simulator↗
NASA NTRSDate not supplied

Enabling Metric-Based Mesh Adaptation for Advanced Compressible Flow Simulations Using US3D

This work presents a metric-based mesh adaptation capability added to the flow solver US3D that is used to improve the accuracy of atmospheric entry simulations. Flow past an entry vehicle in free-flight is usually unsteady and characterized by anisotropic flow features like a strong bow shock and small-scale isotropic flow features like turbulent eddies in the wake. The results presented in this paper demonstrate that we are currently able to iteratively apply metric-based mesh adaptation to improve the solution accuracy by simultaneously targeting isotropic and anisotropic flow features. A simplified workflow of running CFD simulations for entry vehicles is presented where we start off with a coarse initial mesh to compute a first approximation of the flow. This coarse mesh is then iteratively refined using the newly developed metric to improve the resolution of the CFD computation. Furthermore, we demonstrate that we are able to adapt large mesh sizes in a timely fashion which allows us to start thinking about applying this adaptive framework to unsteady atmospheric entry CFD simulations.

Mesh adaptation↗