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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Palmer Station, Antarctica: A Ground-Based Spaceflight Analog Suitable for Validation of Biomedical Countermeasures for Deep Space Missions

Astronauts are known to exhibit a variety of immunological alterations during spaceflight including changes in leukocyte distribution and plasma cytokine concentrations, a reduction in T-cell function, and subclinical reactivation of latent herpesviruses. These alterations are most likely due to mission-associated stressors including circadian misalignment, microgravity, isolation, altered nutrition, and increased exposure to cosmic radiation. Some of these stressors may also occur in terrestrial situations. This study sought to determine if crewmembers performing overwinter deployment at Palmer Station, Antarctica displayed similar immune alterations. The larger goal was to validate a ground analog suitable for the evaluation of countermeasures designed to protect astronauts during future deep space missions. For this pilot study, plasma, saliva, hair, and health surveys were collected from Palmer Station, Antarctica winterover participants at baseline, and at five overwinter timepoints. Twenty-six subjects consented to participate over the course of two seasons. Initial sample processing was performed at Palmer, and eventually stabilized samples were returned to the Johnson Space Center for analysis. A white blood cell differential was performed (real time) using a fingerstick blood sample to determine alterations in basic leukocyte subsets throughout the winterover. Plasma and saliva samples were analyzed for 30 and 13 cytokines, respectively. Saliva was analyzed for cortisol concentration and three latent herpesviruses (DNA by qPCR), EBV, HSV1, and VZV. Hair samples were analyzed for several hormones, as a measure of stress over prolonged periods of time. Voluntary surveys related to general health and adverse clinical events were distributed to participants. It is noteworthy that due to logistical constraints due to COVID-19, the baseline samples for each season were collected in Punta Arenas, Chile, after long international travel and during isolation. Therefore, the palmer pre mission samples may not reflect a true normal ‘baseline’. Minimal alterations were observed in leukocyte distribution during overwinter. The mean percentage of monocyte concentration elevated at one timepoint. Plasma G-CSF, IL1RA, MCP-1, MIP-1β, TNFα and VEGF were decreased during at least one overwinter timepoint, whereas RANTES was significantly increased. No statistically significant changes were observed in mean saliva cytokine concentrations. Salivary cortisol was substantially elevated throughout the entire winterover compared to baseline. Compared to shedding levels observed in healthy controls (23%), the percentage of participants who shed EBV was higher throughout all winterover timepoints (52-60%). Five subjects shed HSV1 during at least one timepoint throughout the season compared to no subjects shedding during pre-deployment. Finally, VZV reactivation, common in astronauts but exceptionally rare in ground-based stress analogs, was observed in one subject during pre-deployment and a different subject at WO2 and WO3. These pilot data, somewhat influenced by the COVID-19 situation, do suggest that participants at Palmer Station do undergo immunological alterations similar to, but likely in reduced magnitude, as those observed in astronauts. We suggest that overwinter at Palmer Station may be suitable test analog for spaceflight biomedical countermeasures designed to mitigate clinical risks for deep space missions.

Space↗
NASA NTRSDate not supplied

Active Volcanoes of Kamchatka as Suitable Terrestrial Analogs for Future Landing Missions and for Change Detection Analysis on Venus

The next decade will see the return to Venus due to a number of missions which have been recently selected and proposed for launch. The selected missions NASA DAVINCI and VERITAS, Roscosmos Venera-D, and ESA EnVision, along with the proposed missions ISRO Shukrayaan- 1, and CNSA VOICE, will open a new era for the exploration of the Earth’s hellish twin planet. These missions will shed new light on the science questions such as: (a) whether recent volcanic activity is locally constrained, or active volcanism occurs on a global scale; (b) the rate of the present-day volcanic activity; (c) the styles of volcanism on Venus, including possible occurrences of pyroclastic/explosive volcanism; and (d) how does the extreme environment on Venus effect volcanic activity. In preparation for these future missions to Venus, the Analogs for VENus’ GEologically Recent Surfaces (AVENGERS) initiative has the scope to select and analyze a number of active terrestrial volcanoes as suitable analogs for the identification and analysis of active volcanism on Venus. The Roscosmos Venera-D is the only mission, among the currently selected or planned mission, equipped with a lander to analyze the elemental and mineralogical composition of the surface. Therefore, it is crucial to find applicable volcanic areas on Earth to perform operational tests such as surface drilling and in-situ elemental composition analysis. To this regard, we propose the analysis of active volcanoes of the Kamchatka Peninsula, which is in a geodynamic setting (subduction) contrasting to that of the volcanic rises on Venus (hot spot). Thus, Kamchatka may represent a helpful geodynamic endmember to put the expected landing site of the Venera-D mission within the context of the entire variety of volcanic landforms and surface chemistry. The Kamchatka Peninsula is located on the eastern margin of the Eurasian plate, in proximity to the Kuril-Kamchatka subduction zone. The frequent eruptions characterizing the volcanoes of the Kamchatka Peninsula make them a suitable terrestrial analog for the possible detection of ongoing eruptions on Venus by future missions, which can be achieved by comparing a sequence of radar images of the same volcano and its surroundings taken at different times. Moreover, it is possible to collect samples of both unweathered and weathered volcanic deposits, to analyze their near infrared spectra in the laboratory for direct comparison with the spectra to be provided by the future missions to Venus. The chemical analyses of Venusian surface materials from the previous Soviet Venera and Vega missions are consistent with that of tholeiitic basalts. Since the volcanism of the Kamchatka Peninsula is characterized by both basaltic lava flows eruptions and pyroclastic activity, performing operational tests in the Kamchatka Peninsula also offers the unique opportunity to provide us the tools to potentially interpret the diverse output given by both effusive and explosive volcanic products.

Piero D'Incecco↗
NASA NTRSDate not supplied

Jet Noise Modeling Using an Acoustic Analogy: From Theoretical Formulation to Practical Noise Predictions

In this presentation an overview of the development of an acoustic analogy formulation, and its implementation into a reduced-order prediction method for turbulent jet mixing noise, will be given. The definition and rationale of an acoustic analogy approach to the prediction of flow-generated noise will be provided. A high-level description of the mathematical processes involved will be outlined in the context of a particular formulation developed at NASA Glenn Research Center. The modelling approximations needed to implement the general theoretical formulation into a practical noise prediction tool will be discussed. Sample results obtained using a noise prediction code based on the NASA Glenn formulation, and comparisons with experimental data, will be presented for a series of turbulent jet test cases. A view on the prospects for continued use of acoustic analogy-based methods for the prediction of flow-generated noise and the assessment of noise-reduction technologies will conclude the presentation.

Jet noise↗
DOE OSTI2025

Dual-ion ECRAM as a stable and accurate analog synapse

Electrochemical random-access memory (ECRAM) works by tuning the bulk electronic conductance of functional materials via reversible, electrochemical insertion of ions, resulting in stable analog resistive switching, attractive for analog in-memory and neuromorphic computing. However, achieving fast programming for training and long retention for inference has been elusive. Protonic ECRAM demonstrates fast programming but insufficient retention, while oxygen-based ECRAM with excellent retention requires elevated programming temperatures. Cu-based ECRAM offers a compromise, with an activation energy (E A ) of ≈0.76 eV between protons (E A ≈ 0.4 eV) and oxygen (E A > 1 eV), enabling extensive retention and room temperature programming. Combining Cu 2+ ions with protons to form a dual-ion ECRAM, we demonstrate two distinct switching behaviors: fast switching at ≤5 V, (E A ≈ 0.45 eV) via protons, and nonvolatile, room temperature switching at ≥8 V, with E A ≈ 0.76 eV via Cu 2+ ions. In conclusion, the Cu-based state exhibits a wide conductance range, with excellent retention, low noise, and linear current-voltage behavior, achieving digital-equivalent ImageNet inference accuracy.

analog in-memory computing↗
NASA NTRS2012

The International Space Station: Unique In-Space Testbed as Exploration Analog

Final assembly of the International Space Station (ISS) was completed in 2011. As articulated in the 2011 NASA Strategic Plan, the Agency's first goal is to extend and sustain human activities across the solar system. Thus, the emerging NASA vision is to launch a bold and ambitious new space initiative to enable human space exploration beyond low-Earth orbit to Lagrange points, the moon, near-Earth asteroids (NEAs), and Mars and its environs. To accomplish this vision, it is necessary to develop and validate innovative exploration technologies and operational concepts. With the extended life of the ISS to 2020 and possibly 2028, NASA has a mandate to maximize the potential of the Nation's newest National Laboratory. Exploration and ISS teams within NASA's Human Exploration and Operations Mission Directorate (HEOMD) have initiated a cooperative effort: the ISS Testbed for Analog Research (ISTAR), a high-fidelity operational analog that complements existing NASA terrestrial laboratory and field testing. To maximize use of the ISS platform to evaluate new exploration technologies, capabilities, and operational concepts to better comprehend and mitigate human spaceflight risks, ISTAR seeks out and encourages investigations dubbed "exploration detailed test objectives" (xDTOs). These xDTOs, building blocks of ISTAR missions, develop and optimize the operations concepts and the use of new technologies that should reduce risks and challenges facing astronauts on long exploration spaceflight voyages. In this paper, we describe (1) the rationale behind ISTAR, (2) a five-year strategic plan, (3) the approach for mission formulation, development, integration, and execution, (4) concepts for near-term missions that implement a phased approach for using ISS as an exploration testbed, and (5) the planned Mars mission simulation using the ISS. This paper will also document several challenges ISTAR must address to execute its missions.

Analog Mission↗
DOE OSTI2020

Expanded Analogs of Three-Dimensional Lead-Halide Hybrid Perovskites

Replacing the Pb-X octahedral building unit of A I PbX 3 perovskites (X=halide) with a pair of edge-sharing Pb-X octahedra affords the expanded perovskite analogs: A II Pb 2 X 6 . We report seven members of this new family of materials. In 3D hybrid perovskites, orbitals from the organic molecules do not participate in the band edges. In contrast, the more spacious inorganic sublattice of the expanded analogs accommodates larger pyrazinium-based cations with low-lying π* orbitals that form the conduction band, substantially decreasing the band gap of the expanded lattice. The molecular nature of the conduction band allows us to electronically dope the materials by reducing the organic molecules. By synthesizing derivatives with AII=pyridinium and ammonium, we can isolate the contributions of the pyrazinium-based orbitals in the band gap transition of A II Pb 2 X 6 . The organic-molecule-based conduction band and the inorganic-ion-based valence band provide an unusual electronic platform with localized states for electrons and more disperse bands for holes upon optical or thermal excitation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Elucidating the Gas-Phase Behavior of Nitazene Analog Protomers Using Structures for Lossless Ion Manipulations Ion Mobility-Orbitrap Mass Spectrometry

2-benzylbenzimidazoles, or “nitazenes”, are a class of novel synthetic opioids (NSOs) that are increasingly being detected alongside fentanyl analogs and other opioids in drug overdose cases. Nitazenes can be 20x more potent than fentanyl but are not routinely tested for during postmortem or clinical toxicology drug screens; thus, their prevalence in drug overdose cases may be under-reported. Traditional analytical workflows utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS) often require additional confirmation with authentic reference standards to identify a novel nitazene. However, additional analytical measurements with ion mobility spectrometry (IMS) may provide a path towards reference-free identification, which would greatly accelerate NSO identification rates in toxicology labs. Presented here are the first IMS and collision cross section (CCS) measurements on a set of fourteen nitazene analogs using a Structures for Lossless Ion Manipulations (SLIM)-Orbitrap MS. All nitazenes exhibited two high intensity baseline-separated IMS distributions, which fentanyls and other drug and drug-like compounds also exhibit. Incorporating water into the electrospray ionization (ESI) solution caused the intensities of the higher mobility IMS distributions to increase the intensities of the lower mobility IMS distributions to decrease. Nitazenes lacking a nitro group at the R1 position exhibited the greatest shifts in signal intensities due to water. Furthermore, IMS-MS/MS experiments showed that the higher mobility IMS distributions of all nitazenes produced fragment ions with m/z 72, 100, and other low intensity fragments while the lower mobility IMS distributions only produced fragment ions with m/z 72 and 100. The IMS, solvent, and fragmentation studies provide experimental evidence that nitazenes potentially exhibit three gas-phase protomers. In conclusion, the cyclic IMS capability of SLIM was also employed to partially resolve four sets of structurally similar nitazene isomers (e.g., protonitazene/isotonitazene, butonitazene/isobutonitazene/secbutonitazene), showcasing the potential of using high-resolution IMS separations in MS-based workflows for reference-free identification of emerging nitazenes and other NSOs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Scintillation and cherenkov photon counting detectors with analog silicon photomultipliers for TOF-PET

Objective. Standard signal processing approaches for scintillation detectors in positron emission tomography (PET) derive accurate estimates for 511 keV photon time of interaction and energy imparted to the detection media from aggregate characteristics of electronic pulse shapes. The ultimate realization of a scintillation detector for PET is one that provides a unique timestamp and position for each detected scintillation photon. Detectors with these capabilities enable advanced concepts for three-dimensional (3D) position and time of interaction estimation with methods that exploit the spatiotemporal arrival time kinetics of individual scintillation photons. Approach. In this work, we show that taking into consideration the temporal photon emission density of a scintillator, the channel density of an analog silicon photomultiplier (SiPM) array, and employing fast electronic readout with digital signal processing, a detector that counts and timestamps scintillation photons can be realized. To demonstrate this approach, a prototype detector was constructed, comprising multichannel electronic readout for a bismuth germanate (BGO) scintillator coupled to an SiPM array. Main Results. In proof-of-concept measurements with this detector, we were able to count and provide unique timestamps for 66% of all optical photons, where the remaining 34% (two-or-more-photon pulses) are also independently counted, but each photon bunch shares a common timestamp. We show this detector concept can implement 3D positioning of 511 keV photon interactions and thereby enable corrections for time of interaction estimators. The detector achieved 17.6% energy resolution at 511 keV and 237 ± 10 ps full-width-at-half-maximum coincidence time resolution (CTR) (fast spectral component) versus a reference detector. We outline the methodology, readout, and approach for achieving this detector capability in first-ever, proof-of-concept measurements for scintillation photon counting detector with analog silicon photomultipliers. Significance. The presented detector concept is a promising design for large area, high sensitivity TOF-PET detector modules that can implement advanced event positioning and time of interaction estimators, which could push state-of-the-art performance.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Analog and symbolic computation through the Koopman framework

We develop a Koopman operator framework for studying the computational structure of dynamical systems. Specifically, we show that the resolvent of the Koopman operator provides a natural abstraction of halting, yielding a ‘Koopman halting problem’ that is recursively enumerable in general. For symbolic systems, such as those defined on Cantor space, this operator formulation captures reachability between clopen sets, while for equicontinuous systems we prove that the Koopman halting problem is decidable. Our framework demonstrates that absorbing (halting) states in coarse-grained finite automata correspond to Koopman eigenfunctions with eigenvalue one, while cycles in the transition graph impose spectral constraints associated with periodic dynamics. These results provide a unifying perspective on computation in symbolic and analog systems, showing how computational universality is reflected in operator spectra, invariant subspaces, and algebraic structures. Beyond symbolic dynamics, this operator-theoretic lens opens pathways to analyze the computational properties of a broader class of dynamical systems, including polynomial and analog models, and suggests that computational hardness may admit dynamical signatures in terms of Koopman spectral structure.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

An Accurate, Error-Tolerant, and Energy-Efficient Neural Network Inference Engine Based on SONOS Analog Memory

In this work, we demonstrate SONOS (silicon-oxide-nitrideoxide- silicon) analog memory arrays that are optimized for neural network inference. The devices are fabricated in a 40nm process and operated in the subthreshold regime for in-memory matrix multiplication. Subthreshold operation enables low conductances to be implemented with low error, which matches the typical weight distribution of neural networks, which is heavily skewed toward near-zero values. This leads to high accuracy in the presence of programming errors and process variations. We simulate the end-to-end neural network inference accuracy, accounting for the measured programming error, read noise, and retention loss in a fabricated SONOS array. Evaluated on the ImageNet dataset using ResNet50, the accuracy using a SONOS system is within 2.16% of floating-point accuracy without any retraining. The unique error properties and high On/Off ratio of the SONOS device allow scaling to large arrays without bit slicing, and enable an inference architecture that achieves 20 TOPS/W on ResNet50, a >10× gain in energy efficiency over state-of-the-art digital and analog inference accelerators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

In situ Parallel Training of Analog Neural Network Using Electrochemical Random-Access Memory

In-memory computing based on non-volatile resistive memory can significantly improve the energy efficiency of artificial neural networks. However, accurate in situ training has been challenging due to the nonlinear and stochastic switching of the resistive memory elements. One promising analog memory is the electrochemical random-access memory (ECRAM), also known as the redox transistor. Its low write currents and linear switching properties across hundreds of analog states enable accurate and massively parallel updates of a full crossbar array, which yield rapid and energy-efficient training. While simulations predict that ECRAM based neural networks achieve high training accuracy at significantly higher energy efficiency than digital implementations, these predictions have not been experimentally achieved. In this work, we train a 3 × 3 array of ECRAM devices that learns to discriminate several elementary logic gates (AND, OR, NAND). We record the evolution of the network’s synaptic weights during parallel in situ (on-line) training, with outer product updates. Due to linear and reproducible device switching characteristics, our crossbar simulations not only accurately simulate the epochs to convergence, but also quantitatively capture the evolution of weights in individual devices. The implementation of the first in situ parallel training together with strong agreement with simulation results provides a significant advance toward developing ECRAM into larger crossbar arrays for artificial neural network accelerators, which could enable orders of magnitude improvements in energy efficiency of deep neural networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Structures of FOX-4 Cephamycinase in Complex with Transition-State Analog Inhibitors

Boronic acid transition-state analog inhibitors (BATSIs) are partners with β-lactam antibiotics for the treatment of complex bacterial infections. Herein, microbiological, biochemical, and structural findings on four BATSIs with the FOX-4 cephamycinase, a class C β-lactamase that rapidly hydrolyzes cefoxitin, are revealed. FOX-4 is an extended-spectrum class C cephalosporinase that demonstrates conformational flexibility when complexed with certain ligands. Like other β-lactamases of this class, studies on FOX-4 reveal important insights into structure–activity relationships. We show that SM23, a BATSI, shows both remarkable flexibility and affinity, binding similarly to other β-lactamases, yet retaining an IC 50 value < 0.1 μM. Our analyses open up new opportunities for the design of novel transition-state analogs of class C enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Assessing boundary condition and parametric uncertainty in numerical-weather-prediction-modeled, long-term offshore wind speed through machine learning and analog ensemble

To accurately plan and manage wind power plants, not only does the time-varying wind resource at the site of interest need to be assessed but also the uncertainty connected to this estimate. Numerical weather prediction (NWP) models at the mesoscale represent a valuable way to characterize the wind resource offshore, given the challenges connected with measuring hub-height wind speed. The boundary condition and parametric uncertainty associated with modeled wind speed is often estimated by running a model ensemble. However, creating an NWP ensemble of long-term wind resource data over a large region represents a computational challenge. Here, we propose two approaches to temporally extrapolate wind speed boundary condition and parametric uncertainty using a more convenient setup in which a mesoscale ensemble is run over a short-term period (1 year), and only a single model covers the desired long-term period (20 year). We quantify hub-height wind speed boundary condition and parametric uncertainty from the short-term model ensemble as its normalized across-ensemble standard deviation. Then, we develop and apply a gradient-boosting model and an analog ensemble approach to temporally extrapolate such uncertainty to the full 20-year period, for which only a single model run is available. As a test case, we consider offshore wind resource characterization in the California Outer Continental Shelf. Both of the proposed approaches provide accurate estimates of the long-term wind speed boundary condition and parametric uncertainty across the region (R 2 >0.75), with the gradient-boosting model slightly outperforming the analog ensemble in terms of bias and centered root-mean-square error. At the three offshore wind energy lease areas in the region, we find a long-term median hourly uncertainty between 10 % and 14 % of the mean hub-height wind speed values. Finally, we assess the physical variability in the uncertainty estimates. In general, we find that the wind speed uncertainty increases closer to land. Also, neutral conditions have smaller uncertainty than the stable and unstable cases, and the modeled wind speed in winter has less boundary condition and parametric sensitivity than summer.

17 WIND ENERGY↗
NASA NTRS2006

Extreme Temperature Electronics Using a Reconfigurable Analog Array

Temperature and radiation tolerant electronics, as well as long life survivability are key capabilities required for future NASA missions. Current approaches to electronics for extreme environments focus on component level robustness and hardening. Compensation techniques such as bias cancellation circuitry have also been employed. However, current technology can only ensure very limited lifetime in extreme environments. Previous work presented a novel approach, based on evolvable hardware technology, which allows adaptive in-situ circuit redesign/reconfiguration during operation in extreme environments. This technology would complement material/device advancements and increase the mission capability to survive harsh environments. This work describes a new reconfigurable analog chip developed by JPL and SPAWAR that is targeted for extreme temperature and evolutionary hardware experiments. Being based on Gm-C technology, this chip can have its functionality tuned and adapted to extreme temperatures through voltage bias adjustment. This tuning process will be controlled by Evolutionary Algorithms. This paper presents details of the reconfigurable analog chip as well as a system level overview. Some early experiments are also described.

evolvable hardware↗
NASA NTRS2006

Functional Recovery of Analog Circuits at Extreme Temperatures

This paper describes a new reconfigurable analog array (RAA) architecture and integrated circuit (IC) used to map analog circuits that can adapt to extreme temperatures under programmable control. Algorithm-driven adaptation takes place on the RAA IC. The algorithms are implemented in a separate Field Programmable Gate Array (FPGA) IC, co-located with the RAA in the extreme temperature environment. The experiments demonstrate circuit adaptation over a wide temperature range, from extremely low temperature of -180 C to high 120 C.

self-recovery↗