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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 217 records · Page 12

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DOE OSTI2026

Datashare

Datashare facilitates communication and data sharing within local networks in potentially dangerous situations such as an explosive ordnance disposal. During such events, there is a need to transmit information rapidly around the incident area. It is a distributed database that does not require an internet connection for operation. In addition, Datashare interfaces with XTK and other software applications, allowing for seamless integration and data management. Datashare supports video calls over the network, enabling real-time communication among users. This software serves to organize, package, and share between responders on location and export data to those off location. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Eldridge, Bryce [Sandia National Lab. (SNL-CA), Li↗

DOE OSTI2018

Investigation of protein quaternary structure via stoichiometry and symmetry information

The Protein Data Bank (PDB) is the single worldwide archive of experimentally-determined three-dimensional (3D) structures of proteins and nucleic acids. As of January 2017, the PDB housed more than 125,000 structures and was growing by more than 11,000 structures annually. Since the 3D structure of a protein is vital to understand the mechanisms of biological processes, diseases, and drug design, correct oligomeric assembly information is of critical importance. Unfortunately, the biologically relevant oligomeric form of a 3D structure is not directly obtainable by X-ray crystallography, whilst in solution methods (NMR or single particle EM) it is known from the experiment. Instead, this information may be provided by the PDB Depositor as metadata coming from additional experiments, be inferred by sequence-sequence comparisons with similar proteins of known oligomeric state, or predicted using software, such as PISA (Proteins, Interfaces, Structures and Assemblies) or EPPIC (Evolutionary Protein Protein Interface Classifier). Despite significant efforts by professional PDB Biocurators during data deposition, there remain a number of structures in the archive with incorrect quaternary structure descriptions (or annotations). Further investigation is, therefore, needed to evaluate the correctness of quaternary structure annotations. In this study, we aim to identify the most probable oligomeric states for proteins represented in the PDB. Our approach evaluated the performance of four independent prediction methods, including text mining of primary publications, inference from homologous protein structures, and two computational methods (PISA and EPPIC). Aggregating predictions to give consensus results outperformed all four of the independent prediction methods, yielding 83% correct, 9% wrong, and 8% inconclusive predictions, when tested with a well-curated benchmark dataset. We have developed a freely-available web-based tool to make this approach accessible to researchers and PDB Biocurators.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Exploring Applications of Random Walks on Spiking Neural Algorithms

Neuromorphic computing has many promises in the future of computing due to its energy efficient and scalable implementation. Here we extend a neural algorithm that is able to solve the diffusion equation PDE by implementing random walks on neuromorphic hardware. Additionally, we introduce four random walk applications that use this spiking neural algorithm. The four applications currently implemented are: generating a random walk to replicate an image, finding a path between two nodes, finding triangles in a graph, and partitioning a graph into two sections. We then made these four applications available to be implemented on software using a graphical user interface (GUI).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Developing an Automated Uncertainty Quantification Tool to Improve Watershed-Scale Predictions of Water and Nutrient Cycling

Managing the flow of water, nutrients, and contaminants in watersheds is vital to addressing pressing issues related to water scarcity, access to clean drinking water, energy production, resilience to natural and anthropogenic perturbations, and ecological restoration. Decisions about the management of watersheds critically depend on the accuracy with which the flow of water and chemicals through the watershed can be predicted by computer models. Prediction uncertainty can be reduced by matching the model to data, which are collected in the field at great expense. The contribution of watershed characterization data to reducing uncertainty of relevant model predictions can be evaluated in a so-called data-worth analysis, which provides transparent, quantitative metrics about a data set’s value for the support of relevant watershed management objectives. To achieve this goal, we developed a software package that implements the data-worth analysis approach for use with state-of-the-art watershed models. The purpose of the proposed data-worth analysis is to help decision-makers allocate resources for watershed characterization such that the uncertainty in model predictions can be significantly reduced, which leads to better, more effective management decisions. At the same time, watershed characterization costs can be reduced. The specific technical objectives of this SBIR/STTR Phase II project were to develop a framework and associated software toolsets that implement the uncertainty quantification and data-worth analysis approach for use with state-of-the-art watershed models. This goal was achieved by (A) developing a user-friendly, robust software package that is accessible to a wide audience, including watershed managers, policy-makers, and public stakeholders; (B) by demonstrating application of the prototype on several use cases that are representative of complex watershed management challenges spanning a range of scales and that consider different open-source, DOE-based codes and other modeling platforms; and (C) by gathering information about the needs and requirements from potential users to help guide future developments, ensuring that the final product will be commercially viable. The developed software consists of a graphical user interface that guides the user through a sequence of analysis steps, supported by toolsets that leverage state-of-the-art computational simulation-optimization capabilities. A prototype of the software runs on multiple platforms (PC, Mac, multi-processor Linux environment), is linked to diverse watershed simulators (e.g., ECOSYS, TOUGH2, TOUGHREACT, Amanzi-ATS), performs multiple analysis tasks (predictive simulations, sensitivity analysis, uncertainty analysis, automatic parameter estimation, and data-worth analysis, multicomponent geothermometry), and is readily extensible to include external simulators and analysis tools. The software is being commercialized and will be continually updated to address user needs.

58 GEOSCIENCES↗

DOE OSTI2022

Securing Inverter Communication: Proactive Intrusion Detection and Mitigation System to Tap, Analyze, and Act

The electric grid has undergone rapid, revolutionary changes in recent years; from the addition of advanced smart technologies to the growing penetration of distributed energy resources (DERs) to increased interconnectivity and communications. However, these added communications, access interfaces, and third-party software to enable autonomous control schemes and interconnectivity also expand the attack surface of the grid. To address the gap of DER cybersecurity and secure the grid-edge to motivate a holistic, defense-in-depth approach, a proactive intrusion detection and mitigation system (PIDMS) device was developed to secure PV smart inverter communications. The PIDMS was developed as a distributed, flexible bump-in-the-wire (BITW) solution for protecting PV smart inverter communications. Both cyber (network traffic) and physical (power system measurements) are processed using network intrusion monitoring tools and custom machinelearning algorithms for deep packet analysis and cyber-physical event correlation. The PIDMS not only detects abnormal events but also deploys mitigations to limit or eliminate system impact; the PIDMS communicates with peer PIDMSs at different locations using the MQTT protocol for increased situational awareness and alerting. The details of the PIDMS methodology and prototype development are detailed in this report as well as the evaluation results within a cyber-physical emulation environment and subsequent industry feedback.

14 SOLAR ENERGY↗

DOE OSTI2023

(U) MIT Capstone Project (Final Report)

This capstone project focuses on modernizing the design development processes, production development processes, and communication between design agencies (DAs) and production agencies (PAs) to decrease the timeline from conceptual study to first production unit. To focus the scope, the researchers looked only at interactions between the DA, Lawrence Livermore National Lab (LLNL), and the PA, Kansas City National Security Campus (KCNSC). The project’s system problem statement (SPS) is: TO decrease the time from conceptual study to first production unit BY reducing the DA to-PA engineering interface complexity USING digital engineering software that centralizes product definition and information exchange protocols.

42 ENGINEERING↗

DOE OSTI2023

Preliminary Enhanced LAW Glass Formulation Algorithm

This report summarizes the Preliminary Enhanced Low-Activity Waste Glass Formulation Algorithm (GFA), its background information, and the calculations it performs. The Preliminary Enhanced Low-Activity Waste GFA is a tool developed in MATLAB to formulate glass for a given waste composition while attempting to maximize waste loading. It is intended for use at the Waste Treatment and Immobilization Plant, where nuclear waste will be vitrified into glass. The formulated glass is required to satisfy several processing and product quality constraints. In addition, calculations must account for associated uncertainties in constraint prediction and measurement. The GFA adheres to Pacific Northwest National Laboratory nuclear quality assurance procedures and has been validated and verified. In this second revision to the report, two constraints: the lithium and zirconia target constraints were amended to Table 3.1 and programmed into the algorithm. Additionally, three sections were added. Section 3.2.1 includes the Enhanced LAW Correlation Rules, an addition to the glass optimality criteria. Section 4.0 discusses a stepped process approach taken to ensure the algorithm can adequately react to differences between its recommended output and the actual measurements and transfers made during plant operation, and calculation of specific radionuclide concentrations. Section 5.2 describes changes to the user interaction with the algorithm program including the addition of a graphical user interface and compilation of the software.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Final Report

This final progress report describes the development of the CANDO Software package at ThirdLaw Technologies LLC (TLT) towards a software platform that will be used by its subsidiary company ThirdLaw Molecular LLC (TLM) for the development of therapeutic Spiroligomer™ molecules. ThirdLaw Molecular LLC is 95% owned by ThirdLaw Technologies LLC. TLM is developing a new therapeutics platform based on Spiroligomer™ molecules and is currently funded by the Department of Defense, Defense Threat Reduction Agency (DOD/DTRA W15QKN209C004). Spiroligomer™ molecules are complex, highly-preorganized macromolecules with programmable three-dimensional shapes. Spiroligomer™ molecules are currently synthesized by TLM in the form of large (>880,000 member) DNA-encoded libraries and screened against dangerous bacteria and viruses as part of the DOD/DTRA project. The CANDO software package is being developed to enable the computational design of Spiroligomer™ molecules for the development of therapeutic and diagnostic molecules. Towards this end, over the period of the grant we implemented software algorithms and a user interface within CANDO to enable the computational design of Spiroligomer™ molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Connecting Minds: AI Use Cases to Bridge Power Systems and Large Language Models for Practical Applications

Recent advances in artificial intelligence (AI) and development of large language models (LLMs) present the opportunity to develop a new generation of power systems applications. In contrast with early power system AI applications based on structured numerical data, LLMs offer unique capabilities to perform logical reasoning using text documents, unstructured data, and application programming interface (API) calls to computational software. This paper seeks to bridge the knowledge gap between power systems engineers and LLM developers through a crosscutting explanation of use cases, characteristics, requirements, practical considerations from the perspectives of both LLM capabilities and industry needs. Specific focus is given to applications that can be realistically deployed by electric utilities. After introducing the architecture of LLMs and unique challenges of the power systems domain, this paper proposes twenty representative LLM applications grouped into categories of 1) power system operations, 2) asset management, 3) system planning and analytics, and 4) energy management and protection systems. Five use cases are presented within each category with descriptions of the motivation, objectives, approaches, example inputs / outputs, and benefits of each use case.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Full-sky Models of Galactic Microwave Emission and Polarization at Subarcminute Scales for the Python Sky Model

Polarized foreground emission from the Galaxy is one of the biggest challenges facing current and upcoming cosmic microwave background (CMB) polarization experiments. We develop new models of polarized Galactic dust and synchrotron emission at CMB frequencies that draw on the latest observational constraints; that employ the “polarization fraction tensor” framework to couple intensity and polarization in a physically motivated way; and that allow for stochastic realizations of small-scale structure at subarcminute angular scales currently unconstrained by full-sky data. We implement these models into the publicly available Python Sky Model (PySM) software and additionally provide PySM interfaces to select models of dust and CO emission from the literature. We characterize the behavior of each model by quantitatively comparing it to observational constraints in both maps and power spectra, demonstrating an overall improvement over previous PySM models. Finally, we synthesize models of the various Galactic foreground components into a coherent suite of three plausible microwave skies that span a range of astrophysical complexity allowed by current data. Author contributions to this paper can be found at the end of this work.

Group, The Pan-Experiment Galactic Science↗

DOE OSTI2018

Modelling feedbacks between human and natural processes in the land system

Abstract. The unprecedented use of Earth's resources by humans, in combination with increasing natural variability in natural processes over the past century, is affecting the evolution of the Earth system. To better understand natural processes and their potential future trajectories requires improved integration with and quantification of human processes. Similarly, to mitigate risk and facilitate socio-economic development requires a better understanding of how the natural system (e.g. climate variability and change, extreme weather events, and processes affecting soil fertility) affects human processes. Our understanding of these interactions and feedback between human and natural systems has been formalized through a variety of modelling approaches. However, a common conceptual framework or set of guidelines to model human–natural-system feedbacks is lacking. The presented research lays out a conceptual framework that includes representing model coupling configuration in combination with the frequency of interaction and coordination of communication between coupled models. Four different approaches used to couple representations of the human and natural system are presented in relation to this framework, which vary in the processes represented and in the scale of their application. From the development and experience associated with the four models of coupled human–natural systems, the following eight lessons were identified that if taken into account by future coupled human–natural-systems model developments may increase their success: (1) leverage the power of sensitivity analysis with models, (2) remember modelling is an iterative process, (3) create a common language, (4) make code open-access, (5) ensure consistency, (6) reconcile spatio-temporal mismatch, (7) construct homogeneous units, and (8) incorporating feedback increases non-linearity and variability. Following a discussion of feedbacks, a way forward to expedite model coupling and increase the longevity and interoperability of models is given, which suggests the use of a wrapper container software, a standardized applications programming interface (API), the incorporation of standard names, the mitigation of sunk costs by creating interfaces to multiple coupling frameworks, and the adoption of reproducible workflow environments to wire the pieces together.

58 GEOSCIENCES↗

DOE OSTI2024

Predicting Instability and the Effect of Wind Loading on Single-Axis Trackers

As PV modules continue to trend toward larger, thinner, and more flexible forms they grow more susceptible to damage from dynamic wind loading. As a result, understanding the impact of wind on PV systems, particularly when mounted on solar-tracking hardware, and identifying robust, stable array layouts and stow strategies is becoming increasingly important for the PV community. In our ongoing DuraMAT project, we are developing an open-source software package, PVade (PV aerodynamic design engineering), to simulate the cascading fluid-structure interaction that occurs within solar-tracking arrays to enable researchers to test hardware, layout, and tracker control changes, leading to enhanced stability and a reduction in wind-driven damage. We will give an overview of the PVade software, highlighting recent user-interface and algorithm developments, before presenting the latest outcomes from our ongoing validation campaign in which we analyze and compare with experimental data obtained from a DuraMAT 1 project. From there, we will present simulated results from a larger, multi-row array and highlight relationships between varying tracker angles and stability as measured by different experimentally validated metrics.

fluid structure interaction↗

DOE OSTI2022

Effects of Absorber Near-Interface Compensation on Cd(Se,Te) Solar Cell Performance

Arsenic (As) has been shown to be an effective p-type dopant for CdTe, although high performance in As-doped devices remains difficult to achieve. Arsenic is prone to self-compensation in CdTe, as evidenced by the accumulation of dopant atoms in CdTe/Cd(Se,Te) near the interface with MgxZn1-xO (MZO). In this study, we use SCAPS 1D modeling software to investigate the effect of near-interface compensation, helping elucidate loss pathways in present-day As-doped devices and informing future growth directions. We consider three possible results of As accumulation: shallow donors, deep recombination centers, and a thin layer of excess acceptor accumulation. The reduction in near-interface carrier concentration caused by shallow donors is shown to improve open-circuit voltages (VOC), whereas deep levels are detrimental to all performance parameters. The thin charge layer affects capacitance-voltage (CV) measurements by reducing the depletion width while maintaining the same carrier concentration, replicating CV behavior that has been observed in actual devices. These results illustrate the importance of monitoring dopant accumulation within 100 nm of the interface, and suggest that reducing or eliminating the As concentration in this region would be beneficial. An undoped Cd(Se,Te) layer at the interface is suggested as a possible device structure to boost performance.

absorber↗

DOE OSTI2023

Influence of processing on secondary phase formation and microstructural evolution at U-10Mo alloy and Zr interlayer interfaces

Thermo-mechanical processing of uranium-10 wt. % molybdenum (U-10Mo) fuel plates leads to microstructure changes at the U-10Mo/Zr interfaces. Secondary phases formed at this interface are particularly important to interfacial bond strength, process optimization, and maintaining structural integrity of the U-10Mo fuel plates during irradiation. In this work, we determined the phases and phase transformation products occurring at the interface of the U-10Mo fuel and Zr interlayer when the fuel plate is subjected to short and long hot isostatic pressure times. Interfacial morphology, structure and composition of phases formed, and relative hardness across the U-10Mo/Zr interfaces were studied using a multi-length scale, multi-modal characterization approach involving electron microscopy, atom probe tomography, and atomic force microscopy. Here, results highlight that the extent of phase transformations, secondary phase formation, and hardness variability across interfaces can be controlled by modifying processing parameters. Phase diagram construction and thermodynamic calculations were performed using the Thermocalc software to identify expected phases formed at interfaces during the maximum hold temperature of 560 °C experienced during HIP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Chemist: A Domain-Specific Language by Chemists for Chemists

Managing the complexity of quantum chemistry (QC) software is key to ensuring it remains accessible, maintainable, and reusable. Noticeably missing from the QC ecosystem are modules targeting bottleneck routines. Here we argue that this is likely due to the difficulty in defining interfaces for such modules. To that end, we introduce the open-source, publicly available Chemist library https://github.com/NWChemEx/Chemist. Chemist is a domain-specific language targeting the QC domain. Chemist has been developed focusing on performance and user-friendliness. Using Chemist, QC tasks are defined using familiar domain concepts such as molecules, wave functions, and operators. The domain objects are hierarchical to ensure a systematic encapsulation of information. Key features of Chemist include: extensibility, the ability to alias existing data, and the ability to succinctly define many common QC tasks. The usefulness of Chemist is demonstrated by discussing the interface of NWChemEx’s Fock build module and by showcasing a proof-of-concept self-consistent field algorithm containing uncertainty propagation.

Algorithms↗

DOE OSTI2017

Accessing Data Federations with CVMFS

Data federations have become an increasingly common tool for large collaborations such as CMS and Atlas to efficiently distribute large data files. Unfortunately, these typically are implemented with weak namespace semantics and a non-POSIX API. On the other hand, CVMFS has provided a POSIX-compliant read-only interface for use cases with a small working set size (such as software distribution). The metadata required for the CVMFS POSIX interface is distributed through a caching hierarchy, allowing it to scale to the level of about a hundred thousand hosts. In this paper, we will describe our contributions to CVMFS that merges the data scalability of XRootD-based data federations (such as AAA) with metadata scalability and POSIX interface of CVMFS. We modified CVMFS so it can serve unmodified files without copying them to the repository server. CVMFS 2.2.0 is also able to redirect requests for data files to servers outside of the CVMFS content distribution network. Finally, we added the ability to manage authorization and authentication using security credentials such as X509 proxy certificates. We combined these modifications with the OSGs StashCache regional XRootD caching infrastructure to create a cached data distribution network. Here, we will show performance metrics accessing the data federation through CVMFS compared to direct data federation access. Additionally, we will discuss the improved user experience of providing access to a data federation through a POSIX filesystem.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2024

Milestone 49 Report: Batched Sparse LA Phase 5 Implementation

Batched sparse linear algebra operations in general, and solvers in particular, have become the major algorithmic development activity and foremost performance engineering effort in the numerical software libraries work on modern hardware with accelerators such as GPUs. Many applications, ECP and non-ECP alike, require simultaneous solutions of many small linear systems of equations that are structurally sparse in one form or another. In order to move towards high hardware utilization levels, it is important to provide these applications with appropriate interface designs to be both functionally efficient and performance portable and give full access to the appropriate batched sparse solvers running on modern hardware accelerators prevalent across DOE supercomputing sites since the inception of ECP. To this end, we present here a summary of recent advances on the interface designs in use by HPC software libraries supporting batched sparse linear algebra and the development of sparse batched kernel codes for solvers and preconditioners. We also address the potential interoperability opportunities to keep the corresponding software portable between the major hardware accelerators from AMD, Intel, and NVIDIA, while maintaining the appropriate disclosure levels conforming to the active NDA agreements. The presented interface specifications include a mix of batched band, sparse iterative, and sparse direct solvers with their accompanying functionality that is already required by the application codes or we anticipated to be needed in the near future. This report summarizes progress in Kokkos Kernels and the xSDK libraries MAGMA, Ginkgo, hypre, PETSc, and SuperLU.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

rNets: a standalone package to visualize reaction networks

In the study of chemical processes, visualizing reaction networks is pivotal for identifying crucial compounds and transformations. Traditional methods, such as network schematics and reaction path linear plots, often struggle to effectively represent complex reaction networks due to their size and intricate connectivity. Alternatives capable of leading with complexity include graph methods, but they are not user-friendly, lacking simplicity and modularity, which hinders their integration with widely-used research software. This work introduces rNets an innovative tool designed for the efficient visualization of reaction networks with a user-friendly interface, modularity, and seamless integration with existing software packages. The effectiveness of rNets is demonstrated through its application in analyzing three catalytic reactions, showcasing its potential to significantly enhance research both in homogeneous and heterogeneous catalysis fields. This tool not only simplifies the visualization process but also opens new avenues for exploring complex reaction networks in diverse research contexts.

Pablo-García, Sergio↗