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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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The Geophysical Monitoring Program Core Seismic Libraries contain a broad array of seismic and waveform analysis libraries useful for a wide range of seismic analysis processes. These include signal processing, travel time calculation, waveform correlation, array processing, geometry and geodesy, and plotting libraries.
CMS has deployed a number of different GPU algorithms at the High-Level Trigger (HLT) in Run 3. As the code base for GPU algorithms continues to grow, the burden for developing and maintaining separate implementations for GPU and CPU becomes increasingly challenging. To mitigate this, CMS has adopted the Alpaka (Abstraction Library for Parallel Kernel Acceleration) library as the performance portability solution to provide a single-code base for parallel execution on both GPUs and CPUs in CMS software (CMSSW). A direct CUDA version of HCAL energy reconstruction, called Minimization At Hcal, Iteratively (MAHI), has been deployed at the HLT in the 2022-2023 data taking period. This contribution will describe how the CUDA version is converted into a portable implementation using the Alpaka library. We will discuss the porting experience from CUDA to Alpaka, the validation process and the performance of the Alpaka version in CPU and GPU.
This document describes a standard library plant controller model to interface with the grid-forming hybrid control inverter-based resource (IBR) model. The initial version of model specification was jointly developed by Pacific Northwest National Laboratory (PNNL), Tesla Energy, and EPRI, and it was revised multiple times later to incorporate suggestions from WECC MVS members. Tesla Energy provided main control algorithms to support the development of this model specification. This standard library model is developed to help the utility industry better understand the GFM technology. The model could be used to represent equipment for long-term planning studies where vendor-specific models are not available. As equipment matures and improves, standard library models will be updated to capture the new functionalities of GFMs. It is not intended that these models will always remain representative of all future GFM technologies.
Visolis is developing a commercial process for the bioproduction of a chemical intermediate, towards the derivative production of a portfolio of bio-based chemicals with large application potential, from drop-in commodity chemicals, to innovative specialty chemical offerings, to materials for multiple end markets and industries, which will ultimately benefit consumers and the public. Visolis already has several variants of a microbe that produce the chemical intermediate at distinct levels (i.e. high, medium, and low). They are currently pursuing transcriptomics analysis for some of these strains, towards a better understanding of the biology behind what makes certain strains perform better than others. There exist genome-scale library approaches for the microbe that could be used to screen gene disruption, overexpression, or repression candidates for perturbations to the production of the chemical intermediate. These approaches often reveal opportunities for further production improvement that are not otherwise accessible using hypothesis-driven metabolic engineering approaches. However, Visolis, while it could generate or procure such genome-scale libraries, does not have the automated strain engineering workflows required to screen thousands of variants, obtaining a production phenotype and a genotype for each. The purpose of this collaboration is to use LBNL and SNL capabilities to enable Visolis to effectively screen thousands of genome-scale library strain variants for phenotype/genotype relationships that will complement Visolis’ transcriptomic investigations.
A computerized library acquisition system developed for control of informational materials acquired at NASA Ames Research Center is described. The system monitors the acquisition of both library and individual researchers' orders and supplies detailed financial, statistical, and bibliographical information. Applicability for other libraries and the future availability of the program is discussed.
ODIN/RLV is a digital computing system for the synthesis and optimization of reusable launch vehicle preliminary designs. The system consists of a library of technology modules in the form of independent computer programs and an executive program, ODINEX, which operates on the technology modules. The technology module library contains programs for estimating all major military flight vehicle system characteristics, for example, geometry, aerodynamics, economics, propulsion, inertia and volumetric properties, trajectories and missions, steady state aeroelasticity and flutter, and stability and control. A general system optimization module, a computer graphics module, and a program precompiler are available as user aids in the ODIN/RLV program technology module library.
System works with Library of Congress MARC II format. System composed of subsystems that provide wide range of library informationprocessing capabilities. Format is American National Standards Institute (ANSI) format for machine-readable bibliographic data. Adaptable to any medium-to-large library.
Efficient, easy-to-use program moved easily to different computers. Purpose of NAVIO, Input/Output Subroutine Library, provides input/output package of software for FORTRAN programs that is portable, efficient, and easy to use. Implemented as hierarchy of libraries. At bottom is very small library containing only non-portable routines called "I/O Kernel." Design makes NAVIO easy to move from one computer to another, by simply changing kernel. NAVIO appropriate for software system of almost any size wherein different programs communicate through files.
This User's Manual describes the Hypercluster Parallel Processing Library, composed of FORTRAN-callable subroutines which enable a FORTRAN programmer to manipulate and transfer information throughout the Hypercluster at NASA Lewis Research Center. Each subroutine and its parameters are described in detail. A simple heat flow application using Laplace's equation is included to demonstrate the use of some of the library's subroutines. The manual can be used initially as an introduction to the parallel features provided by the library. Thereafter it can be used as a reference when programming an application.
Phase 3 of a 4 part study was undertaken to study the use of scientific and technical information (STI) in the academic aerospace community. Phase 3 of this project used three questionnaires that were sent to three groups (i.e., faculty, librarians, and students) in the academic aerospace community. Specific attention was paid to the types of STI used and the methods in which academic users acquire STI. The responses of the academic libraries are focussed on herein. Demographic information on academic aerospace libraries is provided. Data regarding NASA interaction with academic aerospace libraries is also included, as is the survey instrument.
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.
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.
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)].
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.
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.
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.
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.
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.