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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Countering Weapons of Mass Destruction (CWMD) Device Cybersecurity Characterization Process and Profile

Countering Weapons of Mass Destruction (CWMD) recognizes that threats in the cyberspace domain continue to grow, which requires CWMD devices and supporting systems to be both cybersecure (ability to protect or defend from cyber-attacks) and resilient (ability to maintain required capability in the face of adversity) to cyber threats. The CWMD cybersecurity characterization approach in this document supports existing cyber resilience activities within the Acquisition Lifecycle Framework. Similarly, this process supports existing Department of Homeland Security Cyber Resilience Test and Evaluation activities, which consist of iterative processes, starting at the initiation of system acquisition and continuing throughout the entire device and system life cycle. Cyber resilience is the ability of an information system to continue to operate while under attack, even if in a degraded or debilitated state, and to rapidly recover operational capabilities for essential functions after a successful attack. The goal of the security characterization task for CWMD is to support the development of a CBRN device-dependent profile that aligns with device network capabilities and maps to recommended security controls to create a characterization security profile impact levels. The impact levels for CWMD devices should be characterized as Low (L), Moderate (M), High (H) to align with the low, moderate, high control baselines. To estimate the impact levels, the device’s security-related attributes are translated into the security objectives: Confidentiality (C), Integrity (I), and Availability (A), known as the CIA triad. The potential impact for each device can be L, M, H, for devices that connect and transmit different types of data and may have different impact levels. National Institute of Standards and Technology Federal Information Processing Standards Publication 199 states, “the potential impact values assigned to the respective security objectives shall be the highest value from among those security categories that have been determined for each type of information resident on the information system.” As CWMD is determining the cybersecurity impact levels of CBRN devices based on network connections and data transfers, the impact levels are aligned with the associated attributes of network connections and communications. For example, if the device system is connected to a wireless network and transmits different data types based on the confidentiality of the data, the highest impact value for each security objective should represent the device’s CIA impact level. This document is intended to be used by test managers, test team, and program managers.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Countering Weapons of Mass Destruction (CWMD) Device Cybersecurity Characterization Process and Profile

Countering Weapons of Mass Destruction (CWMD) recognizes that threats in the cyberspace domain continue to grow, which requires CWMD devices and supporting systems to be both cybersecure (ability to protect or defend from cyber-attacks) and resilient (ability to maintain required capability in the face of adversity) to cyber threats. The CWMD cybersecurity characterization approach in this document supports existing cyber resilience activities within the Acquisition Lifecycle Framework. Similarly, this process supports existing Department of Homeland Security Cyber Resilience Test and Evaluation activities, which consist of iterative processes, starting at the initiation of system acquisition and continuing throughout the entire device and system life cycle. Cyber resilience is the ability of an information system to continue to operate while under attack, even if in a degraded or debilitated state,1 and to rapidly recover operational capabilities for essential functions after a successful attack.2 The goal of the security characterization task for CWMD is to support the development of a CBRN device-dependent profile that aligns with device network capabilities and maps to recommended security controls to create a characterization security profile impact levels. The impact levels for CWMD devices should be characterized as Low (L), Moderate (M), High (H) to align with the low, moderate, high control baselines. To estimate the impact levels, the device’s security-related attributes are translated into the security objectives: Confidentiality (C), Integrity (I), and Availability (A), known as the CIA triad. The potential impact for each device can be L, M, H, for devices that connect and transmit different types of data and may have different impact levels. National Institute of Standards and Technology Federal Information Processing Standards Publication 199 states, “the potential impact values assigned to the respective security objectives shall be the highest value from among those security categories that have been determined for each type of information resident on the information system.”3 As CWMD is determining the cybersecurity impact levels of CBRN devices based on network connections and data transfers, the impact levels are aligned with the associated attributes of network connections and communications. For example, if the device system is connected to a wireless network and transmits different data types based on the confidentiality of the data, the highest impact value for each security objective should represent the device’s CIA impact level. This document is intended to be used by test managers, test team, and program managers.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Three-Dimensional Network Adjustment of Laser Tracker Measurements for Large-Scale Metrology Applications

The adjustment of laser tracker network measurements for large-scale metrology applications has unique considerations not commonly encountered in the network adjustment approaches generally used in either standard metrology or in traditional geodetic surveying. Many applications that require the measurement accuracy of a laser tracker are confined to small working areas to measure the dimensional quality of manufactured parts. Large-scale metrology applications require the same high measurement accuracy, but over a comparatively larger working area. This paper describes a unified least-squares approach to adjust three-dimensional survey network measurements that takes into account the unique considerations of large-scale metrology networks. The impetus for these unique considerations arises from an application that falls neatly between the disciplines of metrology and geodesy—resembling a mixture of the conditions and requirements from both. In conclusion, this paper will also describe a case study of a large-scale metrology survey network used to align the particle accelerator at Michigan State University’s Facility for Rare Isotope Beams (FRIB).

42 ENGINEERING↗
DOE OSTI2014

Dynamic Provisioning for Terascale Science Applications Using Hybrid Circuit/Packet Technologies and 100G Transmission Systems (Final Report)

This project investigated dynamic hybrid circuit/packet network architectures and examined technologies that are beneficial to enhance the performance of Future Internet architectures with a specific emphasis on their potential deployment in the Department of Energy (DOE) Energy Sciences Network (ESnet). Our research was very much aligned with the new “OpenFlow Network Architecture” which has caught the attention of the telecom networking industry.

Mukherjee, Biswanath↗
DOE OSTI2025

ecospec v0.1.0

Bespoke software for segmenting plants in ecoFABs to monitor growth and health. Contains python libraries for image alignment, training neural networks and running inference.

Zwart, PetrusH [Lawrence Berkeley National Laborat↗
NASA NTRS1970

Solar electric propulsion system evaluation

Solar electric propulsion system performance consisting of thrustors with thrust vector aligning actuators, switching network and flight type power conditioner

Costogue, E. N.↗
DOE OSTI2023

Compositions having reduced thermal conductivities and methods of making the same

The present disclosure relates to a composition that includes a film having a network of randomly aligned carbon nanotubes, where the carbon nanotubes have an average diameter between about 0.6 nm and about 2.0 nm and the carbon nanotubes form bundles having an average diameter between about 3 nm and about 50 nm. In addition, the composition is characterized by a power factor α 2 σ between 1 μW/mK 2 and about 3500 μW/mK 2 and by ZT=α 2 σT/k between about 0.02 and about 2.0 over a temperature range between about 100 K and about 500 K.

Blackburn, Jeffrey Lee↗
DOE OSTI2019

ManiNetCluster: a novel manifold learning approach to reveal the functional links between gene networks

BACKGROUND:The coordination of genomic functions is a critical and complex process across biological systems such as phenotypes or states (e.g., time, disease, organism, environmental perturbation). Understanding how the complexity of genomic function relates to these states remains a challenge. To address this, we have developed a novel computational method, ManiNetCluster, which simultaneously aligns and clusters gene networks (e.g., co-expression) to systematically reveal the links of genomic function between different conditions. Specifically, ManiNetCluster employs manifold learning to uncover and match local and non-linear structures among networks, and identifies cross-network functional links. RESULTS:We demonstrated that ManiNetCluster better aligns the orthologous genes from their developmental expression profiles across model organisms than state-of-the-art methods (p-value <2.2×10-16). This indicates the potential non-linear interactions of evolutionarily conserved genes across species in development. Furthermore, we applied ManiNetCluster to time series transcriptome data measured in the green alga Chlamydomonas reinhardtii to discover the genomic functions linking various metabolic processes between the light and dark periods of a diurnally cycling culture. We identified a number of genes putatively regulating processes across each lighting regime. CONCLUSIONS:ManiNetCluster provides a novel computational tool to uncover the genes linking various functions from different networks, providing new insight on how gene functions coordinate across different conditions. ManiNetCluster is publicly available as an R package at https://github.com/daifengwanglab/ManiNetCluster.

Comparative network analysis↗
NASA NTRS1992

Self-Aligning Optical Measurement Systems

The paper discusses how to teach a system of neural networks to respond to the alignment clues used by a human operator in performing routine, initial alignments. A paradigm is proposed for automating the alignment of the components of optical measurement systems. The paradigm which was tested on a spatial filter has proved to be successful for optical alignment.

Decker, Arthur J.↗
NASA NTRS1991

Neural nets for aligning optical components in harsh environments: Beam smoothing spatial filter as an example

The goal is to develop an approach to automating the alignment and adjustment of optical measurement, visualization, inspection, and control systems. Classical controls, expert systems, and neural networks are three approaches to automating the alignment of an optical system. Neural networks were chosen for this project and the judgements that led to this decision are presented. Neural networks were used to automate the alignment of the ubiquitous laser-beam-smoothing spatial filter. The results and future plans of the project are presented.

Decker, Arthur J.↗
DOE OSTI2022

Artificial intelligence inferred microstructural properties from voltage–capacity curves

Abstract The quantification of microstructural properties to optimize battery design and performance, to maintain product quality, or to track the degradation of LIBs remains expensive and slow when performed through currently used characterization approaches. In this paper, a convolution neural network-based deep learning approach (CNN) is reported to infer electrode microstructural properties from the inexpensive, easy to measure cell voltage versus capacity data. The developed framework combines two CNN models to balance the bias and variance of the overall predictions. As an example application, the method was demonstrated against porous electrode theory-generated voltage versus capacity plots. For the graphite|LiMn $$_2$$ 2 O $$_4$$ 4 chemistry, each voltage curve was parameterized as a function of the cathode microstructure tortuosity and area density, delivering CNN predictions of Bruggeman’s exponent and shape factor with 0.97 $$R^2$$ R 2 score within 2 s each, enabling to distinguish between different types of particle morphologies, anisotropies, and particle alignments. The developed neural network model can readily accelerate the processing-properties-performance and degradation characteristics of the existing and emerging LIB chemistries.

25 ENERGY STORAGE↗
DOE OSTI2014

Core and filament formation in magnetized, self-gravitating isothermal layers

We examine the role of the gravitational instability in an isothermal, self-gravitating layer threaded by magnetic fields on the formation of filaments and dense cores. Using a numerical simulation, we follow the non-linear evolution of a perturbed equilibrium layer. The linear evolution of such a layer is described in the analytic work of Nagai et al. We find that filaments and dense cores form simultaneously. Depending on the initial magnetic field, the resulting filaments form either a spiderweb-like network (for weak magnetic fields) or a network of parallel filaments aligned perpendicular to the magnetic field lines (for strong magnetic fields). Although the filaments are radially collapsing, the density profile of their central region (up to the thermal scale height) can be approximated by a hydrodynamical equilibrium density structure. Thus, the magnetic field does not play a significant role in setting the density distribution of the filaments. The density distribution outside of the central region deviates from the equilibrium. The radial column density distribution is then flatter than the expected power law of r {sup –4} and similar to filament profiles observed with Herschel. Our results do not explain the near constant filament width of ∼0.1pc. However, our model does not include turbulent motions. It is expected that the accretion-driven amplification of these turbulent motions provides additional support within the filaments against gravitational collapse. Finally, we interpret the filamentary network of the massive star forming complex G14.225-0.506 in terms of the gravitational instability model and find that the properties of the complex are consistent with being formed out of an unstable layer threaded by a strong, parallel magnetic field.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Sn-InAs Nanowire Shadow-Defined Josephson Junctions

Hybrid superconductor–semiconductor platforms are foundational to advancing quantum information technologies, motivating the integration of materials with clean interfaces, robust superconductivity, and scalable architectures. Here, in this work, we report the synthesis and analysis of inclined InAs nanowires, conformally coated with β-Sn shells. These nanowires extend in opposite in-plane directions, forming a self-aligned, criss-cross network. This enables the deterministic formation of nanowire-shadow Josephson junctions through angle-controlled, low-temperature Sn deposition. Structural characterization shows uniform polycrystalline β-Sn shells forming a sharp, diffusion-free interface with InAs. Low-temperature transport measurements reveal a hard induced superconducting gap ≈ 600 μeV, switching currents up to ≈ 500 nA, and parallel magnetic field resilience beyond 1T. These results establish β-Sn/InAs nanowire networks as a promising platform for superconducting qubits, low-noise microwave devices, and the exploration of exotic superconducting phases including triplet pairing and topological superconductivity.

B-Sn↗
DOE OSTI2024

Gene-Metabolite Association Prediction with Interactive Knowledge Transfer Enhanced Graph for Metabolite Production

Identifying gene targets for enhancing metabolite production in metabolic engineering is challenging due to the vast research literature and the approximation in genome-scale metabolic model (GEM) simulations. Here, to address this, we propose the Gene-Metabolite Association Prediction task, which automates gene discovery for given metabolite-gene pairs, accompanied by a benchmark dataset of 2474 metabolites and 1947 genes for Saccharomyces cerevisiae (SC) and Issatchenkia orientalis (IO). This task is complicated by incomplete metabolic graphs and metabolic heterogeneity. We introduce an Interactive Knowledge Transfer mechanism based on Metabolism Graphs (IKT4Meta) to enhance prediction accuracy by integrating cross-metabolism knowledge. Using Pretrained Language Models (PLMs) to generate inter-graph links mitigates heterogeneity issues, while intra-graph links are propagated via these anchors. Gene-metabolite predictions are then performed on the enriched graphs integrating multiple microorganisms’ knowledge. Experiments show that IKT4Meta outperforms baselines by up to 12.3% in link prediction.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2004

Discrete Wavelength-Locked External Cavity Laser

A prototype improved external cavity laser (ECL) was demonstrated in the second phase of a continuing effort to develop wavelength-agile lasers for fiber-optic communications and trace-gas-sensing applications. This laser is designed to offer next-generation performance for incorporation into fiber-optic networks. By eliminating several optical components and simplifying others used in prior designs, the design of this laser reduces costs, making lasers of this type very competitive in a price-sensitive market. Diode lasers have become enabling devices for fiber optic networks because of their cost, compactness, and spectral properties. ECLs built around diode laser gain elements further enhance capabilities by virtue of their excellent spectral properties with significantly increased (relative to prior lasers) wavelength tuning ranges. It is essential to exploit the increased spectral coverage of ECLs while simultaneously insuring that they operate only at precisely defined communication channels (wavelengths). Heretofore, this requirement has typically been satisfied through incorporation of add-in optical components that lock the ECL output wavelengths to these specific channels. Such add-in components contribute substantially to the costs of ECL lasers to be used as sources for optical communication networks. Furthermore, the optical alignment of these components, needed to attain the required wavelength precision, is a non-trivial task and can contribute substantially to production costs. The design of the present improved ECL differs significantly from the designs of prior ECLs. The present design relies on inherent features of components already included within an ECL, with slight modifications so that these components perform their normal functions while simultaneously effecting locking to the required discrete wavelengths. Hence, add-in optical components and the associated cost of alignment can be eliminated. The figure shows the locking feedback signal, and the frequency locking achieved by use of this signal, as a mirror is tilted through a range of angles to tune the ECL through 48 channels. The data for the frequency plot were obtained, simultaneously with the data for the locking-signal plot, by using a scanning Michelson interferometer to precisely determine the ECL wavelength (and, hence, frequency). Given the ability of the Michelson interferometer to obtain highly precise readings, the frequency plot can be taken to be a reliable indication of single-mode operation. The discontinuities in the frequency plot signify the switching of the ECL between channels; in other words, they indicate tuning with locking to discrete frequencies. The peaks of the feedbacklocking signal correspond to the centers, or near centers, of the mirror angle scan through the corresponding channels. Thus, it is clear that when the feedback-locking signal is at a local maximum, the ECL is operating at single frequency at or near the middle frequency of the selected channel. This is all that is required for precisely locking the ECL output wavelength. The locking is achieved without additional external optical components.

Pilgrim, Jeffrey S.↗