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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing

While the complementary metal-oxide semiconductor (CMOS) technology is the mainstream for the hardware implementation of neural networks, an alternative route is explored based on a new class of spiking oscillators called “thermal neuristors”, which operate and interact solely via thermal processes. Utilizing the insulator-to-metal transition (IMT) in vanadium dioxide, a wide variety of reconfigurable electrical dynamics mirroring biological neurons is demonstrated. Notably, inhibitory functionality is achieved just in a single oxide device, and cascaded information flow is realized exclusively through thermal interactions. To elucidate the underlying mechanisms of the neuristors, a detailed theoretical model is developed, which accurately reflects the experimental results. In conclusion, this study establishes the foundation for scalable and energy-efficient thermal neural networks, fostering progress in brain-inspired computing.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multiple social platforms reveal actionable signals for software vulnerability awareness: A study of GitHub, Twitter and Reddit

Software vulnerabilities are flaws in computer systems that leave users open to attack. In many cases, these vulnerabilities go unnoticed and remain unresolved in codebases. Thus, awareness of software vulnerabilities among the public is crucial to ensure effective cybersecurity practices, the development of high quality software, and ultimately national security. This awareness can be better understood by studying the spread and evolution of software vulnerability discussions in online communities. This work is the first to evaluate and contrast how discussions about software vulnerabilities spread on three social platforms -- Twitter, GitHub, and Reddit. To lay the groundwork, we showcase a novel fundamental framework for measuring information spread that identifies the spread mechanisms and observables across platforms, the units of information, and the groups of measurements that can be applied to focus on a specific phenomena e.g., information cascades. We then analyze and contrast social network topologies for three example social networks and measure the scale and speed of the spread of discussion of specific vulnerabilities to understand how far and how widely they spread, how many users participate in discussions, and the duration of their spread. To demonstrate the awareness of more impactful software vulnerabilities, a subset of our analysis focuses on vulnerabilities targeted during recent major cyber attacks as well as vulnerabilities exploited by advanced persistent threat groups. We discover that usually, vulnerability discussions start on GitHub, before occurring on Twitter and Reddit. While studying how some user-level and content-level characteristics influence vulnerability spread, we observe that Twitter discussions started by users predicted to be humans have larger size, breadth, depth, adoption rate, lifetime, and structural virality compared to those started by users predicted to be bots. On Reddit, we contrast the differences in thread structure that originate from posts with positive, negative and neutral polarity. We find that posts that are positive have larger, deeper and wider discussions compared to negative and neutral posts. We anticipate the results of our analysis to not only increase the understanding of software vulnerability awareness but also inform models for simulating information spread across multiple social environments online.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Flow Reconstruction in A Transonic Turbine Cascade Using Physics-Informed Neural Networks (PINNS)

This paper investigates the application of Physics-Informed Neural Networks (PINNs) for the analysis of turbine blades in a transonic cascade. The 2-D flow field in a transonic turbine cascade is reconstructed in three ways: the traditional forward approach (PINN not trained on experimental data), by training the PINN using discrete sets of experimentally measured pressure at midspan, and in the inverse sense where no inlet or outlet pressure boundary conditions are applied. Comparisons between the PINN solutions to measured data are made. This is repeated for three different turbine blades with distinct loading characteristics. Good agreement is shown between a CFD calculation of the CMC7 blade, and the PINN model trained with all data. The PINN is trained utilizing all available data, half the available data, data from only the leading edge region, and data from only the trailing edge region. The forward problem results deviate the most from experimental data but show promise. Solutions from the assisted training cases show that the PINN can reconstruct the flow field with acceptable accuracy when trained on measurements along the entire blade. In the inverse case, it is shown that to simultaneously achieve acceptable errors for inlet Mach number and outlet isentropic Mach number, the PINN must be trained on the static pressure data along the entire blade.

Machine Learning↗
NASA NTRSDate not supplied

GT2024-128885: Flow Reconstruction in a Transonic Turbine Cascade using Physics-Informed Neural Networks (PINNs)

This presentation investigates the application of Physics-Informed Neural Networks (PINNs) for the analysis of turbine blades in a transonic cascade. PINNs are a machine learning method trained on losses calculated from reconstructed governing equations, assigned boundary/initial conditions, and measured data. We reconstruct the 2-D flow field in a transonic turbine cascade in two ways: the traditional forward approach (without training/experimental data) and by training the PINN using experimental data. We then compare the PINN solutions to measured data. This is repeated for three different turbine blades with distinct loading characteristics. The experimental data used for training is the static pressure measurements along the suction and pressure sides of each blade. The PINN is trained utilizing all available data, half the available data, data from only the leading edge region, and data from only the trailing edge region. It's shown that the PINN can reconstruct the flow field in all cases with acceptable errors. Cases where the PINN is trained on all the data, and even half the data, resulted in the lowest errors. The exit Mach number is inferred for each case and compared to the experimentally calculated value.

Machine Learning↗
DOE OSTI2022

Epidermal growth factor receptor cascade prioritizes the maximization of signal transduction

Many studies have been performed to quantify cell signaling. Cell signaling molecules are phosphorylated in response to extracellular stimuli, with the phosphorylation sequence forming a signal cascade. The information gain during a signal event is given by the logarithm of the phosphorylation molecule ratio. The average information gain can be regarded as the signal transduction quantity (ST), which is identical to the Kullback–Leibler divergence (KLD), a relative entropy. We previously reported that if the total ST value in a given signal cascade is maximized, the ST rate (STR) of each signaling molecule per signal duration (min) approaches a constant value. To experimentally verify this theoretical conclusion, we measured the STR of the epidermal growth factor (EGF)-related cascade in A431 skin cancer cells following stimulation with EGF using antibody microarrays against phosphorylated signal molecules. The results were consistent with those from the theoretical analysis. Thus, signaling transduction systems may adopt a strategy that prioritizes the maximization of ST. Furthermore, signal molecules with similar STRs may form a signal cascade. In conclusion, ST and STR are promising properties for quantitative analysis of signal transduction.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1950

Attainable circulation about airfoils in cascade

From consideration of available information on boundary-layer behavior, a relation among profile thickness, maximum surface velocity, Reynolds number, velocity diagram, and solidity is established for a cascade of airfoils immersed in a two-dimensional incompressible fluid flow. Several cascades are computed to show the effect of various cascade design parameters on minimum required cascade solidity. Comparisons with experimentally determined blade performance show that the derived blade loadings are equal or higher for moderate flow deceleration and somewhat lower for large deceleration. Blades with completely laminar flow appear practical for impulse or reaction blading.

Goldstein, Arthur W↗
DOE OSTI2025

Process Systems Engineering-Informed Design and Scale-Up of Multi-stage Diafiltration Cascades for Lithium and Cobalt Recovery from Spent Lithium-Ion Batteries

These slides present work jointly completed by Tasks in PrOMMiS. The first half of the presentation motivates the importance of critical materials for national security and how the recovery of critical minerals via membrane separations can be more cost effective than currently used technology. The second half of the presentation presents cost-optimal results for the custom cost model for diafiltration using the superstructure flowsheet developed by CMU. These results highlight how PSE can inform process targets (i.e., product purity targets) and suitable design strategies for scaled-up membrane cascades.

critical materials↗
DOE OSTI2023

Thermodynamics of signal transduction systems and fluctuation theorem in a signal cascade

Biochemical chain reactions are signal transduction cascades that can transmit biological information about the intracellular environment. In this study, we modelled a chain reaction as a code string for applying information theory. Herein, we assumed that cell signal transduction selects a strategy to maximize the transduced signal per signal event duration. To investigate the same, we calculated the information transmission capacity of the reaction chain by maximizing the average entropy production rate per reaction time, indicating the idea of the entropy coding method. Moreover, we defined a signal cascade trajectory. Subsequently, we found that the logarithm of the forward and reverse transition ratio per reaction time is equal to the entropy production rate, which derives the form of the fluctuation theorem in signal transduction. Our findings suggest the application of information entropy theory for analysing signal transduction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Hydrologic connectivity and dynamics of solute transport in a mountain stream: Insights from a long-term tracer test and multiscale transport modeling informed by machine learning

The movement of solutes in a watershed is a complex process with multiple interactions and feedbacks across spatial and temporal scales. Modeling the dynamics of solute transport along diverse hydrologic pathways within watersheds – from hillslopes to stream channels and in and out of the hyporheic zones – is challenging but critically important, as these processes integrate and contribute to the biogeochemical functioning of the river corridor up to the river network scale. Here we use results from a long-term network-scale tracer test at the H.J. Andrews experimental forest in western Cascade Mountains, Oregon, USA to inform a multiscale framework for transport in stream corridors. The framework uses a Lagrangian-based subgrid model to represent the effects of hyporheic exchange flow and advective transport at stream network scales. The spatially and temporally resolved stream discharge needed for the transport model is imputed across the river system by an entity-aware long short-term memory network. Modeled concentrations show good agreements with the observations and exhibit power scaling laws indicative of a very wide range of timescales over which hyporheic exchange flow occurs. Our results demonstrate a data-informed modeling framework that links dynamical processes occurring at small scales to a network context to help understand how changes at reach scale cascade into network-scale effects, providing a useful tool for sustainable river basin management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Assessing high fidelity multi-component models to facilitate safeguards at Gas Centrifuge Enrichment Plants

We report that the International Atomic Energy Agency (IAEA) inspectors routinely carry out environmental sampling (ES) as a verification method. Collection of environmental swipe samples at various locations in Gas Centrifuge Enrichment Facilities (GCEPs) is an important process in detecting misuse of a declared facility and possibly the existence of undeclared nuclear material. These samples are measured for isotopic composition in uranium containing particles by Thermal Ionization Mass Spectrometry (TIMS) or Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Even though ES is highly effective in detecting the absolute value of enrichments and their deviations from the declared values, it cannot explain the cause of those changes. Several potential explanations can serve as possibilities for particles detected above or other than the declared enrichment. These include normal and non-malicious events such as the design of the enrichment cascades, unintentional failures of the machines, or overshoot during startup of a cascade. It can also be the result of deliberate misuse by the facility operators. The primary objective of this work is to understand how these factors affect the enrichments produced by a cascade and quantify anticipated multi-isotopic concentrations for each case. The following methodology is employed to determine signatures at a particular facility. 1) Utilize a new two-dimensional multi-component diffusion code to obtain centrifuge performance data and use that information to design and perform cascade analysis. Compare and contrast the results with previous 1-D radially averaged solutions from the Pancake code. 2) Design a GCEP cascade with the production goal of 19.75% 235 U for each set of machine data above. Investigate two cascade scenarios that include enrichment of natural uranium (NU) feed to 19.75% 235U in a single cascade compared to a two-step process of NU to 5% and then 5% to 19.75%. 3) Simulate the intentional vs. unintentional off-normal scenarios in the cascades to assess the differences in isotopic concentrations. A non-ideal squared-off cascade model developed at the University of Virginia is used to calculate flow rates and isotopic concentrations of the process gas. The analysis is performed using the Rome machine model operated at 600 m/s rotor speed. The upper and lower bounds of normal and abnormal enrichments in a typical facility are used in conjunction with ES results to understand the root causes of such observations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1985

New analysis of nuclear interaction observed by Mt. Kanbara emulsion chamber experiment

To date the analysis of the air cascade family has been performed using a full Monte Carlo simulation. It is difficult to draw a definite conclusion about the interaction mechanism by using only this kind of simulation. On the other hand, attempts to reproduce the original gamma ray at the interaction point, for example decascading, have also been made. This method makes it possible to observe the interaction directly and to analyze the data from various angles. All of these methods, however, assume a constant ER in the cascade shower, where E is energy and R is the distance from the center of the cascade shower. It is impossible to reproduce the exact interaction height and energy by these methods. A relative method in separating one cascade shower from others is adopted. This method makes it possible to estimate the interaction height and energy by using information about the lateral spread of the cascade shower.

Nanjo, H.↗
NASA NTRS1984

The boundary layer on compressor cascade blades

The flow field about an airfoil in a cascade at chord Reynolds number (R sub C) near 50,000. The program is experimental and combines laser Doppler anemometry (LDA) with flow visualization techniques in order to obtain detailed flow data (e.g., boundary layer profiles, points of separation and the transition zone) on a cascade of highly-loaded compressor blades. The information provided is to serve as benchmark data for the evaluation of current and future compressor cascade predictive models, in this way aiding in the compressor design process. The completed pressure surface mean velocity profiles, as well as two detailed near wake velocity profiles, all at a single incidence angle are provided.

Deutsch, S.↗
DOE OSTI2023

Generation of entangled-photons by a quantum dot cascade source in polarized cavities: Using cavity resonances to boost signals and preserve the entanglements

Motivated by recent advances in the development of single photon emitters for quantum information sciences, here we design and formulate a quantum cascade model that describes cascade emission by a quantum dot (QD) in a cavity structure while preserving entanglement that stores information needed for single photon emission. The theoretical approach is based on a photonic structure that consists of two orthogonal cavities in which resonance with either the first or second of the two emitted photons is possible, leading to amplification and rerouting of the entangled light. The cavity–QD scheme uses a four-level cascade emitter that involves three levels for each polarization, leading to two spatially entangled photons for each polarization. By solving the Schrodinger equation, we identify the characteristic properties of the system, which can be used in conjunction with optimization techniques to achieve the “best” design relative to a set of prioritized criteria or constraints in our optical system. The theoretical investigations include an analysis of emission spectra in addition to the joint spectral density profile, and the results demonstrate the ability of the cavities to act as frequency filters for the photons that make up the entanglements and to modify entanglement properties. The results provide new opportunities for the experimental design and engineering of on-demand single photon sources.

Chemistry↗
NASA NTRS1986

The boundary layer on compressor cascade blades

The purpose of NASA Research Grant NSG-3264 is to characterize the flowfield about an airfoil in a cascade at chord Reynolds number(R sub C)near 5 x 10 to the 5th power. The program is experimental and combines laser Doppler velocimeter (LDV) measurements with flow visualization techniques in order to obtain detailed flow data, e.g., boundary layer profiles, points of separation and the transition zone, on a cascade of highly-loaded compressor blades. The information provided by this study is to serve as benchmark data for the evaluation of current and future compressor cascade predictive models, in this way aiding in the compressor design process. Summarized is the research activity for the period 1 December 1985 through 1 June 1986. Progress made from 1 June 1979 through 1 December 1985 is presented. Detailed measurements have been completed at the initial cascade angle of 53 deg. (incidence angle 5 degrees). A three part study, based on that data, has been accepted as part of the 1986 Gas Turbine Conference and will be submitted for subsequent journal publication. Also presented are data for a second cascade angle of 45 deg (an incidence angle of 3 degrees).

Deutsch, S.↗
NASA NTRS1995

Forest and wildlife habitat analysis using remote sensing and geographic information systems

Forest and wildlife habitat analyses were conducted at the H.J. Andrews Experimental Forest in the Central Cascade Mountains of Oregon using remotely sensed data and a geographic information system (GIS). Landsat Thematic Mapper (TM) data were used to determine forest successional stages, and to analyze the structure of both old and young conifer forests. Two successional stage maps were developed. One was developed from six TM spectral bands alone, and the second was developed from six TM spectral bands and a relative sun incidence band. Including the sun incidence band in the classification improved the mapping accuracy in the two youngest successional stages, but did not improve overall accuracy or accuracy of the two oldest successional stages. Mean spectral values for old-growth and mature stands were compared in seven TM bands and seven band transformations. Differences between mature and old-growth successional stages were greatest for the band ratio of TM 4/5 (P = 0.00005) and the multiband transformation of wetness (P = 0.00003). The age of young conifer stands had the highest correlation to TM 4/5 values (r = 0.9559) of any of the TM band or band transformations used. TM 4/5 ratio values of poorly regenerated conifer stands were significantly different from well regenerated conifer stands after age 15 (P = 0.0000). TM 4/5 was named a 'Successional Stage Index' (SSI) because of its ability to distinguish forest successional stages. The forest successional stage map was used as input into a vertebrate richness model using GIS. The three variables of (1) successional stage, (2) elevation, and (3) site moisture were used in the GIS to predict the spatial occurrence of small mammal, amphibian, and reptile species based on primary and secondary habitat requirements. These occurrence or habitat maps were overlayed to tally the predicted number of vertebrate at any given point in the study area. Overall, sixty-three and sixty-seven percent of the model predictions for vertebrate occurrence matched the vertebrates that were trapped in the field in eight forested stands. Of the three model variables, site moisture appeared to have the greatest influence on the pattern of high vertebrate richness in all vertebrate classes.

Fiorella, Maria↗
DOE OSTI2022

Search for high-mass resonances decaying to a jet and a Lorentz-boosted resonance in proton-proton collisions at s = 13 TeV

A search is reported for high-mass hadronic resonances that decay to a parton and a Lorentz-boosted resonance, which in turn decays into a pair of partons. The search is based on data collected with the CMS detector at the LHC in proton-proton collisions at $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$. The boosted resonance is reconstructed as a single wide jet with substructure consistent with a two-body decay. The high-mass resonance is thus considered as a dijet system. The jet substructure information and the kinematic properties of cascade resonance decays are exploited to disentangle the signal from the large quantum chromodynamics multijet background. The dijet mass spectrum is analyzed for the presence of new high-mass resonances, and is found to be consistent with the standard model background predictions. Results are interpreted in a warped extra dimension model where the high-mass resonance is a Kaluza-Klein gluon, the boosted resonance is a radion, and the final state partons are all gluons. Limits on the production cross section are set as a function of the Kaluza-Klein gluon and radion masses. These limits exclude at 95% confidence level models with Kaluza-Klein gluon masses in the range from 2.0 to 4.3 TeV and radion masses in the range from 0.20 to 0.74 TeV. By exploring a novel experimental signature, the observed limits on the Kaluza-Klein gluon mass are extended by up to about 1 TeV compared to previous searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1990

Adaptive noncolocated velocity feedback for vibration damping

A method is proposed for adaptive noncolocated velocity feedback control of flexible structure vibrations. The approach, denoted as auto-tuning, is to drive the system into a sequence of controlled oscillations to provide accurate knowledge of the plant characteristics in the vicinity of the phase cross-over frequencies. An allpass phase notch filter cascade is used as the control architecture to phase stabilize each destabilizing mode in the plant transfer function. The allpass phase notch filter cascade is tuned precisely by the information extracted from the controlled oscillations.

Bayard, David S.↗
NASA NTRS1993

Subband/transform functions for image processing

Functions for image data processing written for use with the MATLAB(TM) software package are presented. These functions provide the capability to transform image data with block transformations (such as the Walsh Hadamard) and to produce spatial frequency subbands of the transformed data. Block transforms are equivalent to simple subband systems. The transform coefficients are reordered using a simple permutation to give subbands. The low frequency subband is a low resolution version of the original image, while the higher frequency subbands contain edge information. The transform functions can be cascaded to provide further decomposition into more subbands. If the cascade is applied to all four of the first stage subbands (in the case of a four band decomposition), then a uniform structure of sixteen bands is obtained. If the cascade is applied only to the low frequency subband, an octave structure of seven bands results. Functions for the inverse transforms are also given. These functions can be used for image data compression systems. The transforms do not in themselves produce data compression, but prepare the data for quantization and compression. Sample quantization functions for subbands are also given. A typical compression approach is to subband the image data, quantize it, then use statistical coding (e.g., run-length coding followed by Huffman coding) for compression. Contour plots of image data and subbanded data are shown.

Glover, Daniel↗