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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Pilot Demonstration Test Bed for ICC Desiccant Based Cooling System Final Report CRADA No. TSB-737-93

In this CRADA project, LLNL provided a field engineering, operation, and maintenance evaluation of ICC’s Desiccant Based Cooling (DBC) System by installing and activating an instrumented test bed in a real application at LLNL. LLNL was approached by two manufacturers of newly emerging heating, ventilation and air-conditioning (HVAC) equipment for technical assistance in obtaining engineering thermodynamic evaluation of their units. Despite promising improvements in technical HVAC performance and the elimination of environmentally sensitive materials (CFC’S), they experienced market resistance in the federal sector because of the need to develop a record of technical and reliability data. LLNL selected three sites as areas where the units could potentially produce significant improvements in energy consumption and healthy air conditions. This project covered the installation activation of the pilot test bed at LLNL. The collaborative effort provided statistical and requirements bases to make a valid evaluation of the units.

42 ENGINEERING↗
NASA NTRSDate not supplied

Using Distributed Fiber-optic Strain Sensing to Estimate Generalized Modal Coordinates from Flight-test Data

A method for estimating the generalized modal coordinates of an aircraft during flight has been developed. The Fiber-optic Sensing System (FOSS) offers an efficient and cost-effective method of measuring the strain at thousands of points along the wings. The estimation of modal coordinates was implemented as a two-step process. First, a maximum likelihood method is used to estimate the statistical properties of the sensors and generalized modal coordinates. Second, the strain mode shapes from the finite element model are used along with the statistical properties from the first step to estimate the generalized modal coordinates over time. Using simulated data from the X-56A Multi-Utility Technology Testbed (MUTT), different methods of modal coordinate estimation were compared to demonstrate the benefits and weaknesses of each. These were compared against the exact solution and an ordinary least squares (a more traditional method) estimate. Modal coordinate estimation methods were then applied to flight-test data from the X-56A aircraft to show that the method continues to work well with actual test data. The new estimation method provides insights unavailable from more classical approaches.

Jeffrey Ouellette↗
DOE OSTI2023

National forest timber bids and export price interlinkages in the USA: The bounds testing approach

We examine the interrelationships of national forest timber bid and log export prices for Douglas-fir (Region 6) in 2003–2021 and loblolly pine (Region 8) using time-series stationarity and bounds-testing approaches. The analysis shows the difference in time series properties across different geographies and time scales. Bid prices for these dominant species of timber in each of two Forest Service regions are found to be stationary, while log export prices for those same species appear to be non-stationary. Bounds testing conducted with autoregressive distributed lag modeling methods provides strong evidence for a cointegrating relationship between timber bid prices and log export prices in Forest Service Region 6. In Region 8, evidence for a cointegrating relationship was weak. Here, the share of salvage wood in national forest timber sales is a statistically significant control variable in all models estimated.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

SAVS: A Space Analysis and Visualization System

We propose to develop, test, demonstrate, and deliver to NASA a powerful and versatile data acquisition, manipulation, analysis and visualization system which will enhance scientific capabilities in the display and interpretation of diverse and distributed data within an integrated user-friendly environment. Our approach exploits existing technologies and combines three major elements into an easy-to-use interactive package: (1) innovative visualization software; (2) advanced database techniques; and (3) a rich set of mathematical and image processing tools. Visualization capabilities will include one-, two-, and three-dimensional displays, along with animation, compression, warping and slicing functions. Analysis tools will include generic mathematical and statistical techniques along with the ability to use large scale models for interactive interpretation of large volume data sets. Our system will be implemented on Sun and DEC UNIX workstations and on the Stardent Graphics Super computer. Our final deliverable will include complete documentation and a NASA/NSF-CDAW/SUNDIAL campaign demonstration.

Szuszczewicz, Edward P.↗
NASA NTRS1992

Inversion of surface parameters using fast learning neural networks

A neural network approach to the inversion of surface scattering parameters is presented. Simulated data sets based on a surface scattering model are used so that the data may be viewed as taken from a completely known randomly rough surface. The fast learning (FL) neural network and a multilayer perceptron (MLP) trained with backpropagation learning (BP network) are tested on the simulated backscattering data. The RMS error of training the FL network is found to be less than one half the error of the BP network while requiring one to two orders of magnitude less CPU time. When applied to inversion of parameters from a statistically rough surface, the FL method is successful at recovering the surface permittivity, the surface correlation length, and the RMS surface height in less time and with less error than the BP network. Further applications of the FL neural network to the inversion of parameters from backscatter measurements of an inhomogeneous layer above a half space are shown.

Dawson, M. S.↗
NASA NTRS1993

SAVS: A Space Analysis and Visualization System

We propose to develop, test, demonstrate, and deliver to NASA a powerful and versatile data acquisition, manipulation, analysis and visualization system which will enhance scientific capabilities in the display and interpretation of diverse and distributed data within an integrated user-friendly environment. Our approach exploits existing technologies and combines three major elements into an easy-to-use interactive package: (1) innovative visualization software; (2) advanced database techniques; and (3) a rich set of mathematical and image processing tools. Visualization capabilities will include one-, two-, and three-dimensinal displays, along with animation, compression, warping and slicing functions. Analysis tools will include generic mathematical and statistical techniques along with the ability to use large scale models for interactive interpretation of large volume data sets. Our system will be implemented on Sun and EC UNIX workstations and on the Stardent Graphics Supercomputer. Our final deliverable will include complete documentation and a NASA/NSF-CDAW/SUNDIAL campaign demonstration.

Szuszczewicz, Edward P.↗
DOE OSTI2026

Asymptotic inconsistency of the cumulative algorithm for laser-induced damage probability analysis

The “cumulative algorithm” is a data analysis method that has been proposed to provide an objective, nonparametric determination of laser-induced damage probability as a function of fluence from experimental data that contain both damaged sites and undamaged sites (i.e., 1-on-1 or S-on-1 testing protocols). In this work, the limitations of this approach are explored by considering the asymptotic limit of a large number of test sites. It is shown that the cumulative algorithm does not converge to the true probability distribution and significantly underestimates the damage probability near the damage onset. Here, based on the results of this work, the cumulative algorithm is not recommended for accurate estimation of damage probability.

Computational methods↗
DOE OSTI2025

Adaptive Client Selection in Federated Learning: A Network Anomaly Detection Use Case

Federated Learning (FL) has become a ubiquitous approach for training machine learning models on decentralized data, addressing the myriad privacy concerns inherent in traditional centralized methods. However, the efficiency of FL depends on effective client selection and robust privacy preservation mechanisms. Inadequate client selection may lead to suboptimal model performance, while insufficient privacy measures risk exposing sensitive data. This paper proposes a client selection framework for FL that integrates differential privacy and fault tolerance. Our adaptive approach dynamically adjusts the number of selected clients based on model performance and system constraints, ensuring privacy through calibrated noise addition. We evaluate our method on a network anomaly detection use case using the UNSW-NB15 and ROAD datasets. Results show up to a 7% increase in accuracy and a 25% reduction in training time compared to FedL2P. Moreover, we highlight the trade-offs between privacy budgets and model performance, with higher privacy budgets reducing noise and improving accuracy. Our fault tolerance mechanism, while causing a slight performance drop, enhances robustness to client failures. Statistical validation using Mann-Whitney U tests confirms the significance of these improvements (p < 0.05).

Marfo, William [University of Texas at El Paso,Dep↗
NASA NTRSDate not supplied

Supersonic Traveling Crossflow Wave Characteristics in Ground and Flight Tests

This paper continues analysis of data acquired in a series of supersonic crossflow transition experiments on a 65° swept- wing model tested in both wind tunnel and flight. Flow visualization data are summarized to provide context for the swept-wing instability mechanisms of interest. Unsteady pressure measurements obtained near the wing model leading edge (LE) are studied using 2nd- and 3rd-order statistical methods to extract traveling crossflow wave characteristics from these data. Comparisons between tunnel and flight data with boundary-layer (BL) Linear Stability Theory (LST) predictions provide insights into BL transition phenomena similarities and differences observed in tests using the same swept-wing model configurations. Comparisons of unsteady pressure data results for wing LE configurations with and without distributed-roughness-element (DRE) patterns installed, suggest traveling crossflow disturbance growth is reduced when this type of flow control is applied. A brief stud y of different background surface roughness levels on the wing LE suggests the potential for another flow control approach to promote laminar flow on swept wings using streamwise-biased surface finishes.

Lewis R Owens↗
DOE OSTI2016

Applying the Scientific Method of Cybersecurity Research

The cyber environment has rapidly evolved from a curiosity to an essential component of the contemporary world. As the cyber environment has expanded and become more complex, so have the nature of adversaries and styles of attacks. Today, cyber incidents are an expected part of life. As a result, cybersecurity research emerged to address adversarial attacks interfering with or preventing normal cyber activities. Historical response to cybersecurity attacks is heavily skewed to tactical responses with an emphasis on rapid recovery. While threat mitigation is important and can be time critical, a knowledge gap exists with respect to developing the science of cybersecurity. Such a science will enable the development and testing of theories that lead to understanding the broad sweep of cyber threats and the ability to assess trade-offs in sustaining network missions while mitigating attacks. The Asymmetric Resilient Cybersecurity Initiative at Pacific Northwest National Laboratory is a multi-year, multi-million dollar investment to develop approaches for shifting the advantage to the defender and sustaining the operability of systems under attack. The initiative established a Science Council to focus attention on the research process for cybersecurity. The Council shares science practices, critiques research plans, and aids in documenting and reporting reproducible research results. The Council members represent ecology, economics, statistics, physics, computational chemistry, microbiology and genetics, and geochemistry. This paper reports the initial work of the Science Council to implement the scientific method in cybersecurity research. The second section describes the scientific method. The third section in this paper discusses scientific practices for cybersecurity research. Section four describes initial impacts of applying the science practices to cybersecurity research.

Tardiff, Mark F.↗
NASA NTRS1998

Progressive Failure And Life Prediction of Ceramic and Textile Composites

An engineering approach to predict the fatigue life and progressive failure of multilayered composite and textile laminates is presented. Analytical models which account for matrix cracking, statistical fiber failures and nonlinear stress-strain behavior have been developed for both composites and textiles. The analysis method is based on a combined micromechanics, fracture mechanics and failure statistics analysis. Experimentally derived empirical coefficients are used to account for the interface of fiber and matrix, fiber strength, and fiber-matrix stiffness reductions. Similar approaches were applied to textiles using Repeating Unit Cells. In composite fatigue analysis, Walker's equation is applied for matrix fatigue cracking and Heywood's formulation is used for fiber strength fatigue degradation. The analysis has been compared with experiment with good agreement. Comparisons were made with Graphite-Epoxy, C/SiC and Nicalon/CAS composite materials. For textile materials, comparisons were made with triaxial braided and plain weave materials under biaxial or uniaxial tension. Fatigue predictions were compared with test data obtained from plain weave C/SiC materials tested at AS&M. Computer codes were developed to perform the analysis. Composite Progressive Failure Analysis for Laminates is contained in the code CPFail. Micromechanics Analysis for Textile Composites is contained in the code MicroTex. Both codes were adapted to run as subroutines for the finite element code ABAQUS and CPFail-ABAQUS and MicroTex-ABAQUS. Graphic user interface (GUI) was developed to connect CPFail and MicroTex with ABAQUS.

Xue, David Y.↗
NASA NTRS2022

STITCH: A Subgrid-Scale Model for Energy Buildup in the Solar Corona

The solar corona routinely exhibits explosive activity, in particular coronal mass ejections and their accompanying eruptive ares, that have global-scale consequences. These events and their smaller counterparts, coronal jets, originate in narrow, sinuous lament channels. The key processes that form and evolve the channels operate on still smaller spatial scales and much longer time scales, culminating in a vast separation of characteristic lengths and times that govern these explosive phenomena. In this article, we describe implementation and tests of an efficient subgrid-scale model for generating eruptive structures in magnetohydrodynamics (MHD) coronal simulations. STITCH {STatistical InjecTion of Condensed Helicity { is a physics-based, reduced representation of helicity condensation: a process wherein small-scale vortical surface convection forms ubiquitous current sheets, and pervasive reconnection across the sheets mediates an inverse cascade of magnetic helicity and free energy, thereby forming the lament channels. We have developed a formalism, STITCH, that abstracts these complex processes into a single term in Ohm's law and the induction equation that directly injects tangential magnetic flux into the low corona. We show that our approach is in very good agreement with a full helicity-condensation calculation that treats all of the dynamics explicitly, while enabling substantial reductions in temporal duration and spatial resolution. In addition, we illustrate the flexibility of STITCH at forming localized lament channels and at energizing complex surface flux distributions that have sinuous boundaries. STITCH is simple to implement and computationally ecient, making it a powerful technique for physics-based modeling of solar eruptive events.

J T Dahlin↗
DOE OSTI2022

Predicting initial dissolution rates using structural features from molecular dynamics simulations

Predicting chemical durability of glass materials is important for various applications from daily life such as drink glass and kitchen ware to advanced technologies such as nuclear waste disposal and biomedicine. In this work, we explored prediction of initial dissolution rate through structural features from molecular dynamics (MD) simulations for a wide range of glass compositions (total 28) including borosilicate and aluminosilicate glasses, ZrO 2 -containing and V 2 O 5 -containing boroaluminosilicate glasses. The initial dissolution rates (r 0 ) measured experimentally at 90 °C with varying solution conditions were correlated with structural features (e.g., polyhedral linkages and non-bridging oxygen species) obtained from MD simulations, either from this study or from literature. Since hydrolysis of the glass network through breaking of the network former linkages (e.g., Si-O-Si, Si-O-Al, etc.) is a critical step of network glass dissolution, the statistics of these linkages obtained from MD were correlated to r0 through linear regression, where the coefficient of determination (R 2 ) and root mean square error are found to be 0.949 and 0.681, respectively. This model was compared and discussed with existing models developed by various approaches including machine learning, the kinetic rate equation, topological constraint theory, and other descriptors from MD simulations. The discussion provides insights on future model improvements to predict glass dissolution. In addition, the impact of V 2 O 5 on the glass dissolution was examined in detail, implicating that the impact is not the same across all glass compositions and test conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2016

SU-F-T-312: Identifying Distinct Radiation Therapy Plan Classes Through Multi-Dimensional Analysis of Plan Complexity Metrics

Purpose: To determine whether body site-specific treatment plans form unique “plan class” clusters in a multi-dimensional analysis of plan complexity metrics such that a single beam quality correction determined for a representative plan could be universally applied within the “plan class”, thereby increasing the dosimetric accuracy of a detector’s response within a subset of similarly modulated nonstandard deliveries. Methods: We collected 95 clinical volumetric modulated arc therapy (VMAT) plans from four body sites (brain, lung, prostate, and spine). The lung data was further subdivided into SBRT and non-SBRT data for a total of five plan classes. For each control point in each plan, a variety of aperture-based complexity metrics were calculated and stored as unique characteristics of each patient plan. A multiple comparison of means analysis was performed such that every plan class was compared to every other plan class for every complexity metric in order to determine which groups could be considered different from one another. Statistical significance was assessed after correcting for multiple hypothesis testing. Results: Six out of a possible 10 pairwise plan class comparisons were uniquely distinguished based on at least nine out of 14 of the proposed metrics (Brain/Lung, Brain/SBRT lung, Lung/Prostate, Lung/SBRT Lung, Lung/Spine, Prostate/SBRT Lung). Eight out of 14 of the complexity metrics could distinguish at least six out of the possible 10 pairwise plan class comparisons. Conclusion: Aperture-based complexity metrics could prove to be useful tools to quantitatively describe a distinct class of treatment plans. Certain plan-averaged complexity metrics could be considered unique characteristics of a particular plan. A new approach to generating plan-class specific reference (pcsr) fields could be established through a targeted preservation of select complexity metrics or a clustering algorithm that identifies plans exhibiting similar modulation characteristics. Measurements and simulations will better elucidate potential plan-class specific dosimetry correction factors.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2019

Satellite Conjunction Assessment Risk Analysis for "Dilution Region" Events: Issues and Operational Approaches

An important activity within Space Traffic Management is the detection and prevention of possible on-orbit collisions between space objects. The principal parameter for assessing collision likelihood is the probability of collision, which is widely accepted among conjunction assessment practitioners; but it possesses a known deficiency in that it can produce a false sense of safety when the orbital position uncertainties for the conjuncting objects are high. The probability of collision is said to be “diluted” in such a situation and to understate the possible risk; certain approaches have been recommended by researchers to provide (largely conservative) risk estimates and remediation methodologies in these cases. The present analysis explores two of the main proposals for quantifying and remediating possible risk in the dilution region and quantifies their operational implications. These implications with regard to imputed additional workload are considerable, especially in anticipating the conjunction event levels expected with the deployment of the USAF Space Fence radar. This effort has been undertaken as part of a larger enterprise that seeks to clarify the philosophical and statistical underpinnings of the conjunction risk assessment process. The analysis presented herein argues that a form of hypothesis testing is implicitly used in conjunction assessment risk analysis, and that there are a number of conceptual and practical reasons for constructing the associated null hypothesis to counsel against a satellite conjunction remediation action. In short, it is concluded that, for the purposes of determining whether a conjunction remediation action should be pursued, dilution-region probabilities of collision should be treated no differently from those produced under other circumstances.

Probability of collision↗
DOE OSTI2017

Integrating Sudo-Kaminaga Correlation to the Safety Analysis Code PARET-ANL

The accuracy and reliability of the reactor safety analysis code are critical because the specifications of the safety systems will depend on the analytical results for initiating events that could occur to the reactor. In safety analyses for power reactors, there exist many proficient and applicable computer codes such as RELAP5, CATHARE, RETRAN, or CATHENA. For non-power research reactors, an issue arises, however, due to lacking of such specialized codes. As a result, computer codes developed for the transient analysis of power reactors need to be applied carefully after proving their applicability to a specified research reactor. The safety analysis discussed in this paper concerns the prevention of fuel damage in hypothetical accidental scenarios for the new research reactor design at National Institute of Standards and Technology (NIST). One fuel integrity criterion is analyzed by investigating the Minimum Critical Heat Flux Ratio (MCHFR) in the core during the accidental transients. Some previous studies develop a relationship that correlates the nominal value of the minimum CHFR with the probability of CHF occurring and causing fuel damage. Using a statistical approach, the nominal value of the MCHFR for the low-enriched uranium (LEU) reactor needs to remain above the recommended limiting value to better ensure the safety of the research reactor. The probability of no fuel failure increases as the MCHFR increases. More importantly, as long as the MCHFR remains above the recommended limiting value of 1.301, the reactor will have a 90% probability that CHF is not reached. The safety analysis program PARET, developed by Argonne National Laboratory (ANL), is employed to obtain the CHFR information in this study. PARET/ANL is a digital computer programming code intended primarily for the analysis of test and research reactors that use plate-type (flat) fuel elements. This program has its own set of correlations that are used to calculate the CHFR. One of them is the Mirshak correlation, which was believed to provide the best estimation of the critical heat flux under the operating conditions of the new reactor at the time. Following the critical heat flux (CHF) experiments for vertical rectangular channels in the JRR-3 (Japan Research Reactor unit 3), the CHF calculations now use the Sudo- Kaminaga correlation. This correlation is of our interest because this method has an enhanced geometric similarity and an increased range of applicability that are more representative of the actual operating conditions of our current design, and has a more mechanistic approach [9]. Since the source code of PARET/ANL is inaccessible, a MATLAB-based utility has been written to integrate the Sudo-Kaminaga correlation as a substitute for the Mirshak correlation in the code. As a result, both the Mirshak and the Sudo-Kaminaga correlations are used to analyze the standard output from the PARET program to calculate the CHFR.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Non-Intrusive Appliance Identification with Appliance-Specific Networks

The problem of noninstrusive load monitoring (NILM) is usually formulated as a single-channel blind source separation task, whose successful solution enable fast and convenient load identification and energy disaggregation. When applied at test time, NILM algorithms aim to identify the operating characteristics of individual appliances from an aggregate power measurement of the entire house. Recent advances in deep learning gave rise to many methods that mostly focus on learning a direct mapping from aggregate measurement to individual appliance power. However, these methods are not only computationally expensive, but they often suffer from overfitting and do not generalize very well. In this article, we propose a novel NILM method that leverages advances in statistical learning that have not been properly applied in this domain before. The proposed method consists of three stages: first, a Bayesian nonparametric learning-based approach for appliance state extraction; second, synthetic minority oversampling technique for data augmentation and mitigating the heavy imbalance in switching events; and third, appliance-specific lightweight long short-term memory networks for status classification for each appliance. Here, we adopt a “differential” input (the difference before and after the switching event) to reduce the complexity of network training and make the proposed method robust to multiappliance switching events. Experiments are conducted to demonstrate the effectiveness of the proposed method, achieving superior performance when compared to recent methods. An ablation study is conducted to demonstrate the effectiveness of each module of our method. Finally, we investigate the quality of generated synthetic samples.

42 ENGINEERING↗
NASA NTRS2020

Recommendations for Using Noise Monitors to Estimate Noise Exposure During X-59 Community Tests

A low fidelity simulation approach is used to explore how to place and use noise monitors during X-59 QueSST community tests, where people’s annoyance to the noise produced by the X-59 aircraft will be gathered. Several recommendations are provided including: 1) the desired number of sparsely spaced noise monitor sites within the survey area, 2) whether to group and average measurements across multiple noise monitors located at a site, 3) what spacing should be used if grouped noise monitors are used, 4) an approach to mitigate ambient noise contamination at the measurement sites, 5) a method to combine empirical and predicted dose estimates to provide a single dose estimate for respondents, and 6) assessing how changes in turbulence intensity and array configuration affect dose uncertainty. To make these recommendations, the error that is expected when fitting contrived, smoothly varying sonic boom “reference exposure surfaces” is studied when a spatially sparse and scattered set of samples is used as responses for the fit. The reference exposure surfaces mimic the sonic boom exposure at ground level that might be expected in the X-59 survey area in the absence of atmospheric turbulence, ambient noise, and other localized effects. The spatial extent of these surfaces varies and is representative of the different survey area sizes that might be expected during future X-59 community overflight tests. These contrived reference surfaces are sampled, and those reference samples are then perturbed to mimic atmospheric turbulence, ambient noise and other localized effects that might affect noise monitor measurements within overflown communities. Two different surface fitting methods are investigated when fitting these perturbed samples to approximate the reference surface. The first method uses interpolation between the perturbed data at the scattered sites to compute the fit. The second method fits a polynomial surface model to the perturbed data using ordinary least squares regression analysis. For both fitting methods, the root mean square fit error is computed from the pointwise difference between the fit surface and the reference surface as the count and configuration of the sites is varied while also averaging the error across many different realizations of both the smooth variation of the reference exposure surface and the random, localized perturbations at the sample sites. Different site configurations are compared using this error statistic to make the recommendations noted above. Additionally, the two fitting approaches (interpolation vs linear regression) are compared based on the fit error observed in these simulations. These analyses, comparisons, and recommendations should inform future decisions on the noise monitor placement and the methods used to analyze the noise monitor data that is collected during X-59 community overflights.

sonic boom↗