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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

Numerical Propulsion System Simulation (NPSS) Power Systems Library

This presentation covers the Numerical Propulsion System Simulation (NPSS) Power Systems Library being developed by NASA. This library is a set of components, models, and interfaces for the NPSS language to enable building electric power system models for electrified propulsion systems. The presentation is to be given at the 3rd annual RVLT Toolchain Workshop, where attendees from across the eVTOL industry will be informed of NASA’s tools for eVTOL conceptual design from the vehicle level down through subsystems including propulsion, noise, electrical power, and others. It covers where the NPSS Power System Library fits into NASA’s RVLT toolchain and RVLT work in general, and will inform the audience of how the tool can be useful in their own work.

Electric vertical takeoff and landing↗

Introduction of the NASA Microgravity Research Library

As opportunities for conducting experiments in space are rare, more studies have been published using ground-based analogs that simulate microgravity conditions. For example, when conducting a literature search in PubMed for peer-reviewed articles and studies that used simulated microgravity conditions, results will yield over 5,000 publications dating back to 1961. The issue with this search technique and medium is that these articles are vast in quantity and spread out across multiple web-based databases, repositories, and libraries; some of which, are wholly inaccessible. For example, in PubMed for a single year, we found 1,000+ microgravity research articles among more than 12,000 general, space research articles; these, were within an overarching 350,000+ total, general medical research articles for just 2020. The KSC Microgravity Simulation Support Facility (MSSF), with support from the KSC Information Technology (IT) Applications Development Team and the NASA Space Biology Program, took the initiative to develop a database that would serve as the central repository for existing microgravity research. This repository site is open to the public and houses not only peer-reviewed publications relating to microgravity research, but also dissertations, technical publications such as white papers, NASA technical publications, and patent publications. In this presentation, we will discuss some of our literature research findings as well as present a working prototype version of the Library. It is our goal that the future infrastructure of this database advance to become a fully-functional, NASA Space Life-Sciences Research Library.

Anna Maria Ruby↗

Artificial Intelligence (AI) Methods for Automating the Impact Tool Evidence Library

INTRODUCTION: The development of the Evidence Library for use with the IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) probability risk assessment tool involved a multilayered, time intensive process of data collection and analysis by subject matter experts from the Exploration Medical Capability (ExMC) Element Clinical and Science Team to produce clinical findings forms (CliFFs) for 120 medical conditions. Artificial Intelligence Large Language Models (LLMs) can be leveraged to facilitate this process, thus reducing labor and time. TOPIC: CliFFs contain information about medical conditions as they pertain to spaceflight. This includes condition definitions, incidence data, crew task impairment estimates caused by conditions, treatment protocols and references to literature used for gathering condition evidence. Guided by the Evidence Library Methods document and the CliFF development instructions, a team has leveraged Microsoft Azure AI services and open-source documentation to construct an AI-assisted automated pipeline for CliFF development. This process is designed to search, retrieve, and evaluate the applicable data, and ultimately generate a completed CliFF. The LLM evaluates the relevance of each of the source materials to spaceflight, either as direct evidence or as an analog. The model extracts keywords and generates brief summaries to enhance search and retrieval in later stages of CliFF development. For instance, it can calculate epidemiological statistical data, such as incidence rates and the likelihood of best or worst-case scenarios. APPLICATION: Large Language Models (LLMs) can efficiently summarize large amounts of text. Leveraging this technology will automate data retrieval and evidence gathering for medical databases, like the IMPACT tool, by aiding in the labor-intensive process of analyzing large bodies of literature and organizing it into a formatted document like a CliFF. This added efficiency will enable expeditious expansion of the Evidence Library with additional medical conditions and update previous CLiFFs as new technology becomes available.

Ali Al↗

NWGraph: A Library of Generic Graph Algorithms and Data Structures in C++20

The C++ Standard Library is a valuable collection of generic algorithms and data structures that improves the usability and reliability of C++ software. Graph algorithms and data structures are notably absent from the standard library, and previous attempts to fill this gap have not gained widespread adoption. In this paper we show that the richness of graph algorithms and data structures can in fact be captured by straightforward composition of existing C++ mechanisms. Generic programming is algorithm-oriented. Accordingly, we apply a systematic approach to analyzing a broad set of graph algorithms, “lift” unnecessary constraints from them, and organize the resulting set of minimal common type requirements, i.e., concepts, for defining their interfaces. By using the newly available ranges and concepts in C++20, the type requirements for generic graph algorithms can be succinctly expressed. The generic algorithms and data structures resulting from our analysis are realized in NWGraph, in a modern, composable, and extensible C++ library.

graphs and networks, programming language, C++20↗

Multiplex characterization of microbial traits using dual barcoded nucleic acid fragment expression library

Disclosed herein are barcoded expression libraries comprising a plurality of expression vectors, wherein each expression vector comprises a nucleic acid fragment flanked by a first barcode and a second barcode. Further disclosed herein are methods of making the barcoded expression libraries and methods of conducting functional analysis using the barcoded expression libraries.

Mutalik, Vivek K.↗

Nuclear Data Libraries Sensitivity Studies for ORSA Using SCALE

Subcritical assemblies offer valuable training capabilities in nuclear criticality safety (NCS) for individuals handling fissile material. At Oak Ridge National Laboratory(ORNL), the Oak Ridge Subcritical Assembly (ORSA), a new experimental facility, is being established to provide hands-on training for the Nuclear Criticality Safety Program (NCSP).It is essential to accurately determine the neutron multiplication factor (keff) to ensure that ORSA remains subcritical and safe during operations. This study investigated the sensitivity of keff to variations across Evaluated Nuclear Data File (ENDF/B) libraries, consisting of ENDF/B-VII.1, ENDF/B-VIII.0, and ENDF/B-VIII.1. The analysis was conducted using the CSAS6 sequence in the SCALE-6.3 code system. Individual isotopes in the ORSA model were replaced one at a time with ENDF/B-VII.1 as the base library and changing to ENDF/B-VIII.0or ENDF/B-VIII.1. The results demonstrated that the changes in keffof the nuclides associated with the ORSA model were mostly within the uncertainty of the base model (~24 pcm), except for primary nuclides like Uranium-235and H-poly with few other nuclides. The relative delta keff values of Uranium-235 and H-poly, expressed in pcm, were +280 and -212 in ENDF/B-VIII.0 and +332 and -275 in ENDF/B-VIII.1, respectively, which were notable changes in reactivity. These results demonstrated that ORSA was largely insensitive to variations across these nuclear data libraries.

Hong, Evan [North Carolina State University]↗

Advancing nuclear forensics competencies at the National Nuclear Center of the Republic of Kazakhstan and conceptual development of a National Nuclear Forensics Library

Since 2021, the National Nuclear Center (NNC) of the Republic of Kazakhstan has been successfully developing a project dedicated to nuclear forensics. The relevance of this project is underscored by Kazakhstan’s leading position in the global uranium mining and export market. The country operates research reactors and is involved in the production of experimental nuclear fuel. The nuclear forensics project is being implemented in several key areas: the project will develop competencies in laboratory research of samples, interpretation of results, and develop a prototype concept for the National Nuclear Forensics Library. In implementing these challenges, the NNC experts draw on the experience of colleagues from world-leading scientific and research centers. Designing a prototype National Nuclear Forensics Library (NNFL) is a challenging project. In conclusion, the solution to this task is based on the IAEA’s approaches, recommendations, and the experience gained from the construction of similar systems in other countries.

and nuclear chemistry↗

The ENDF/B Nuclear Data Library and Its Impact on Reactor Simulations

The ENDF/B library, which is developed, maintained, and distributed by the Cross Section Evaluation Working Group, is the main source of nuclear data for analyses and computational simulations in nuclear applications, like different nuclear reactors concepts, radiation shielding, medical applications, astrophysics, etc. The library is constantly being improved and updated, with each release bringing an optimal representation of nuclear interactions as they are understood in their time. The most recent release, ENDF/B-VIII.1, represents a significant improvement in terms of the performance and consistency of the measured differential data relative to previous versions, as it combines the most recent experimental differential data and advanced theoretical nuclear models. As one of the many highlights, ENDF/B-VIII.1 restores a high-burnup depletion performance, comparable to ENDF/B-VII.1, that had been degraded in ENDF/B-VIII.0, while further improving the performance in criticality benchmarks, such as those in the Mosteller’s suite. Additionally noteworthy is the improved performance of ENDF/B-VIII.1 in radiation shielding and thick-target leakage spectrum integral experiments, which are also important for fusion and reactor applications. In this work we present in a very summarized way the main updates implemented in the ENDF/B-VIII.1 release and its main impacts, and also begin to delineate the path forward as to what to expect in the future for the next ENDF/B release, which, based on the timeline of the past few releases, is estimated to happen around 5 years from now. We emphasize that the ENDF/B-VIII.1 release was the product of an enormous collaborative effort among many authors and that for a complete detailed picture, the reader is strongly encouraged to refer to the article accompanying the release, which is currently in the publication process, but available as preprint [G. P. A. Nobre et al. arXiv Preprint arXiv: 2511.03564 (2025)].

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Bioenergy Feedstock Library Annual Summary Report

The Bioenergy Feedstock Library (BFL), part of the Biomass Feedstock National User Facility (BFNUF) located at INL, is a physical sample repository and a web-accessible electronic database. The BFL stores physical and chemical characteristics of biomass and waste carbon sources for energy use as well as samples generated from across U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) funded projects. The objective of this Bioenergy Feedstock Library Annual Summary Report for 2022 is to focus on the (1) publicly available analytical data and equipment tracked through the BFNUF, (2) physical samples available for request, (3) sample and data archival progress from recent BETO-funded projects, and (4) publicly available data sets created upon request from BETO, INL projects, or outside entities. This report highlights key statistics from FY22 and available data and information important for INL, BFL users, academics, and industry.

09 BIOMASS FUELS↗

Bioenergy Feedstock Library Annual Summary Report 2024

The Bioenergy Feedstock Library (BFL), part of the Biomass Feedstock National User Facility (BFNUF) located at Idaho National Laboratory (INL), is a physical sample repository and a web-accessible electronic database. The BFL stores physical and chemical characteristics of biomass and waste carbon sources for energy use, as well as samples generated from U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) and U.S. Department of Agriculture-funded projects. The objective of this Bioenergy Feedstock Library Annual Summary Report for 2024, similar to the 2023 Annual Summary Report , is to focus on the updates to: (1) publicly available analytical data and equipment tracked through the BFNUF, (2) significant increases in the physical samples available for request, (3) sample and data archival progress from recent BETO-funded projects, and (4) publicly available data sets created upon request from BETO, INL projects, or outside entities compared to the previous annual summary reports. This report highlights key statistics and available data and information important for INL, BFL users, academics, and industry.

09 BIOMASS FUELS↗

MetaSci Tandem Mass Spectrometry Library

These data are pure standard mass spectral libraries were collected on Orbitrap (Thermo QE-HF) and Q-TOF (SCIEX 5600) mass spectrometers for 192 compounds using 6 different collision energies, respectively. Libraries were acquired while using different solvent additives, precursor adducts, and ion polarities.

47 OTHER INSTRUMENTATION↗

Trainable Cataloging for Digital Image Libraries with Applications to Volcano Detection

Users of digital image libraries are often not interested in image data per se but in derived products such as catalogs of objects of interest. Converting an image database into a usable catalog is typically carried out manually at present. For many larger image databases the purely manual approach is completely impractical. In this paper we describe the development of a trainable cataloging system: the user indicates the location of the objects of interest for a number of training images and the system learns to detect and catalog these objects in the rest of the database. In particular we describe the application of this system to the cataloging of small volcanoes in radar images of Venus. The volcano problem is of interest because of the scale (30,000 images, order of 1 million detectable volcanoes), technical difficulty (the variability of the volcanoes in appearance) and the scientific importance of the problem. The problem of uncertain or subjective ground truth is of fundamental importance in cataloging problems of this nature and is discussed in some detail. Experimental results are presented which quantify and compare the detection performance of the system relative to human detection performance. The paper concludes by discussing the limitations of the proposed system and the lessons learned of general relevance to the development of digital image libraries.

digital image libraries, trainable cataloging↗

Community-Controlled Transportation: The Western New York E-Bike Library Network: Preprint

Shared Mobility Inc. (SMI) has used their mission of community-controlled transportation to partner with community based organizations on the launch and operations of E-Bike Libraries (EBLs) in Western New York (WNY) and beyond since 2021. For almost four years, the WNY EBLs have provided e-bikes at no cost to underserved communities in Buffalo and Niagara Falls. Participants used the e-bikes for commuting, recreational rides, community bike rides, running errands, and accessing essential services. This program significantly increased e-bike accessibility, with 71% of participants being first-time riders and 78% identifying as Black/African American. Challenges such as bike maintenance, battery charging logistics, and the need for suitable storage were addressed through partnerships with community-based organizations and adjustments to program logistics. Those lessons have been applied to additional EBLs in Pacoima, California and Carlisle, Pennsylvania, which have also been launched by SMI with a continued emphasis on the importance of community based approaches to sustainable transportation. All of these programs demonstrate the potential of e-bikes to provide an affordable, efficient, and fun transportation option, particularly for underserved communities. By leveraging community partnerships and focusing on accessibility and inclusivity, E-Bike Libraries can significantly contribute to sustainable transportation solutions and promote broader participation in the transportation electrification revolution.

33 ADVANCED PROPULSION SYSTEMS↗

The IDAES process modeling framework and model library—Flexibility for process simulation and optimization

Abstract Energy systems and manufacturing processes of the 21st century are becoming increasingly dynamic and interconnected, which require new capabilities to effectively model and optimize their design and operations. Such next generation computational tools must leverage state‐of‐the‐art techniques in optimization and be able to rapidly incorporate new advances. To address these requirements, we have developed the Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform, which builds on the strengths of both process simulators (model libraries) and algebraic modeling languages (advanced solvers). This paper specifically presents the IDAES Core Modeling Framework (IDAES‐CMF), along with a case study demonstrating the application of the framework to solve process optimization problems. Capabilities provided by this framework include a flexible, modifiable, open‐source platform for optimization of process flowsheets utilizing state‐of‐the‐art solvers and solution techniques, fully open and extensible libraries of dynamic unit operations models and thermophysical property models, and integrated support for superstructure‐based conceptual design and optimization under uncertainty.

42 ENGINEERING↗

A Route to Design Novel Functional Peptides by Applying a Denoising Diffusional Model to mRNA Display Libraries

In vitro directed evolution techniques, such as mRNA display, enable peptide ligand discovery and optimization. However, physical libraries that rely on a genetic code can only search a small fraction of sequence space due to inherent biases in the genetic code and experimental limitations. To address this challenge, denoising diffusion implicit models (DDIMs) are applied to generate novel peptide ligands against B‐cell lymphoma extra‐large (Bcl‐x L ), a key cancer target. Starting with high‐throughput sequencing data from previous selections, a DDIM is trained to produce novel sequences with high affinity binding. Experimental validation confirms that most generated sequences are functionally equivalent to the original library members for Bcl‐x L binding and demonstrated comparable binding kinetics and affinity relative to the wildtype and nearest original neighbors. Importantly, this approach generated rare sequences not easily accessible via mutation and directed evolution. These results indicate that DDIMs can complement and expand directed evolution data, efficiently exploring underrepresented regions of sequence space. This approach provides a broadly applicable framework for accelerating ligand discovery and optimizing molecular properties across diverse targets.

Qi, Pearl [Mork Family Department of Chemical Engi↗

Screening a knowledge‐based library of low molecular weight compounds against the proline biosynthetic enzyme 1‐pyrroline‐5‐carboxylate 1 ( PYCR1)

Abstract Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 1 (PYCR1) is the last enzyme of proline biosynthesis and catalyzes the NAD(P)H‐dependent reduction of Δ 1 ‐pyrroline‐5‐carboxylate toL‐proline. High PYCR1 gene expression is observed in many cancers and linked to poor patient outcomes and tumor aggressiveness. The knockdown of thePYCR1gene or the inhibition of PYCR1 enzyme has been shown to inhibit tumorigenesis in cancer cells and animal models of cancer, motivating inhibitor discovery. We screened a library of 71 low molecular weight compounds (average MW of 131 Da) against PYCR1 using an enzyme activity assay. Hit compounds were validated with X‐ray crystallography and kinetic assays to determine affinity parameters. The library was counter‐screened against human Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 3 and proline dehydrogenase (PRODH) to assess specificity/promiscuity. Twelve PYCR1 and one PRODH inhibitor crystal structures were determined. Three compounds inhibit PYCR1 with competitive inhibition parameter of 100 μM or lower. Among these, (S)‐tetrahydro‐2H‐pyran‐2‐carboxylic acid (70 μM) has higher affinity than the current best tool compoundN‐formyl‐l‐proline, is 30 times more specific for PYCR1 over human Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 3, and negligibly inhibits PRODH. Structure‐affinity relationships suggest that hydrogen bonding of the heteroatom of this compound is important for binding to PYCR1. The structures of PYCR1 and PRODH complexed with 1‐hydroxyethane‐1‐sulfonate demonstrate that the sulfonate group is a suitable replacement for the carboxylate anchor. This result suggests that the exploration of carboxylic acid isosteres may be a promising strategy for discovering new classes of PYCR1 and PRODH inhibitors. The structure of PYCR1 complexed withl‐pipecolate and NADH supports the hypothesis that PYCR1 has an alternative function in lysine metabolism.

Biochemistry & Molecular Biology↗

Reduced-order modeling for efficient cross section library development in high-temperature gas reactor pebble-bed depletion analysis

Accurate modeling of running-in and equilibrium conditions in pebble-bed reactors (PBRs) requires precise microscopic multigroup neutron cross sections. In Griffin, deterministic neutronics calculations rely on multivariate interpolation over large cross section libraries, resulting in significant memory usage and performance bottlenecks. This work, together with a companion paper on Griffin integration, explores reduced-order models (ROMs) to replace interpolation with lightweight surrogates. Several ROM techniques are benchmarked, with deep neural networks (DNNs) demonstrating superior memory efficiency, scalability, and predictive accuracy. A total of 295 DNNs were trained to build a comprehensive isotope library, integrated into Griffin through a custom LibTorch interface for depletion analysis. Initial results demonstrate that DNN-based ROMs drastically reduce memory demands while preserving accuracy, enabling finer tabulations and additional state variables without overhead. In conclusion, the framework also supports online cross section generation and real-time DNN updates through transfer learning, improving fidelity by capturing self-shielding and evolving nuclide compositions during burnup.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Whole-building life-cycle analysis with a new GREET® tool: Embodied greenhouse gas emissions and payback period of a LEED-Certified library

Embodied greenhouse gas (GHG) emissions of building components and buildings operations need to be quantified to holistically address building sustainability. To evaluate embodied GHG emissions of buildings and to provide insights on building materials and building design decisions toward decarbonization, we have recently created a building life-cycle assessment (LCA) module in the widely used Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET (R)) LCA model. We applied the GREET building LCA module to examine embodied GHG impacts and the payback period of a LEED (Leadership in Energy and Environmental Design) certified public library in Chicago, USA. We developed localized, detailed life-cycle inventories to address individual building materials used in the library. We expanded the LCA system boundary to include the mechanical, electrical, and plumbing system, as well as refrigerant impacts, which are often ignored in previous studies. Results show that the total embodied GHG emissions are approximately 817 metric tons, or approximately 538 kg/m 2 . Sensitivity analysis highlights the positive role of increasing the use of recycled materials for reducing embodied GHG emissions. Sensitivity analysis on embodied GHG emissions payback periods shows the need to benchmark the embodied and operational carbon performance of buildings for comparison to alternative building designs and sustainability practices. Furthermore, this analysis demonstrates that building LCA models, such as the GREET building LCA module, which addresses embodied and operational GHG emission impacts of whole buildings holistically, could empower building architects, technology developers, manufacturers, and general contractors to address embodied and operational impacts holistically for building sustainability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗