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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

XMark: Reliable Multi-Bit Watermarking for LLM-Generated Texts

Multi-bit watermarking has emerged as a promising solution for embedding imperceptible binary messages into Large Language Model (LLM)-generated text, enabling reliable attribution and tracing of malicious usage of LLMs. Despite recent progress, existing methods still face key limitations: some become computationally infeasible for large messages, while others suffer from a poor trade-off between text quality and decoding accuracy. Moreover, the decoding accuracy of existing methods drops significantly when the number of tokens in the generated text is limited, a condition that frequently arises in practical usage. To address these challenges, we propose XMark, a novel method for encoding and decoding binary messages in LLM-generated texts. The unique design of XMark’s encoder produces a less distorted logit distribution for watermarked token generation, preserving text quality, and also enables its tailored decoder to reliably recover the encoded message with limited tokens. Extensive experiments across diverse downstream tasks show that XMark significantly improves decoding accuracy while preserving the quality of watermarked text, outperforming prior methods. The code will be made publicly available upon acceptance.

Xu, Jiahao [University of Nevada, Reno]↗
NASA NTRS2016

500 C Electronic Packaging and Dielectric Materials for High Temperature Applications

High-temperature environment operable sensors and electronics are required for exploring the inner solar planets and distributed control of next generation aeronautical engines. Various silicon carbide (SiC) high temperature sensors, actuators, and electronics have been demonstrated at and above 500C. A compatible packaging system is essential for long-term testing and application of high temperature electronics and sensors. High temperature passive components are also necessary for high temperature electronic systems. This talk will discuss ceramic packaging systems developed for high temperature electronics, and related testing results of SiC circuits at 500C and silicon-on-insulator (SOI) integrated circuits at temperatures beyond commercial limit facilitated by these high temperature packaging technologies. Dielectric materials for high temperature multilayers capacitors will also be discussed. High-temperature environment operable sensors and electronics are required for probing the inner solar planets and distributed control of next generation aeronautical engines. Various silicon carbide (SiC) high temperature sensors, actuators, and electronics have been demonstrated at and above 500C. A compatible packaging system is essential for long-term testing and eventual applications of high temperature electronics and sensors. High temperature passive components are also necessary for high temperature electronic systems. This talk will discuss ceramic packaging systems developed for high electronics and related testing results of SiC circuits at 500C and silicon-on-insulator (SOI) integrated circuits at temperatures beyond commercial limit facilitated by high temperature packaging technologies. Dielectric materials for high temperature multilayers capacitors will also be discussed.

dielectric performance↗
NASA NTRSDate not supplied

Hopping with an Adaptive Hop Probability Distribution

Monotonic Basin Hopping (MBH) is a stochastic global search technique that may be used to design complex interplanetary trajectories. Previous research on MBH empirically demonstrated that a bi-polar Pareto distribution is an effective way to generate search “hops.” However, no analytical foundation exists to explain this performance. In this work we provide the beginning of that analytical foundation and also introduce a new variant of MBH that uses an adaptive probability distribution to generate the hops. The technique is demonstrated on historical interplanetary trajectory design problems.

A C Englander↗
NASA NTRS1978

Wave production in an ultrarelativistic electron-positron plasma

In this paper we calculate the eigenmodes associated with an ultrarelativistic electron-positron beam traversing a low-energy electron-positron plasma under physical conditions that may exist along open magnetic field lines above pulsar polar caps. We assume that both beam and plasma are cold and charge neutral, and that magnetic field strength and particle density decrease as the cube of (1/R). In the superstrong magnetic fields near the stellar surface where cyclotron frequencies exceed plasma frequencies, electrostatic waves and associated transverse low-frequency waves are driven unstable by the two-stream type particle distribution. At larger distances above the stellar surface the slow beam cyclotron wave is driven unstable. At even greater radial distance (approximately when particle energy density exceeds magnetic energy density) both the Ordinary and Alfven modes become unstable. All of these instabilities can lead to generation of radiation. If the particle distribution as generated at the stellar surface, assumed to consist of two streams, is modified only by plasma effects, then electrostatic and associated transverse waves may only be unstable near the stellar surface. The beam cyclotron mode which is driven by a two-stream or an inverted particle distribution may be stable.

Hardee, P. E.↗
NASA NTRS1988

Extremely luminous far-infrared colliding galaxies - Computation of colliding-galaxy luminosity function

A computational model used to determine the luminosity function for gaseous galaxies in collision is described. It is based on the assumption of high-velocity encounters of two thin, gas-rich disks having identical radii and thickness, able to approach each other from arbitrary directions, with arbitrary orientations and with arbitrary degree of overlap. The distribution of expected luminosities generated in the dissipation of translational energy is then found to closely fit the observed distribution of luminosities of extremely luminous IRAS galaxies. Bursts of star formation resulting from such collisions would not have the correct luminosity function.

Harwit, Martin↗
NASA NTRS2014

Tuning Monotonic Basin Hopping: Improving the Efficiency of Stochastic Search as Applied to Low-Thrust Trajectory Optimization

Trajectory optimization methods using monotonic basin hopping (MBH) have become well developed during the past decade [1, 2, 3, 4, 5, 6]. An essential component of MBH is a controlled random search through the multi-dimensional space of possible solutions. Historically, the randomness has been generated by drawing random variable (RV)s from a uniform probability distribution. Here, we investigate the generating the randomness by drawing the RVs from Cauchy and Pareto distributions, chosen because of their characteristic long tails. We demonstrate that using Cauchy distributions (as first suggested by J. Englander [3, 6]) significantly improves monotonic basin hopping (MBH) performance, and that Pareto distributions provide even greater improvements. Improved performance is defined in terms of efficiency and robustness. Efficiency is finding better solutions in less time. Robustness is efficiency that is undiminished by (a) the boundary conditions and internal constraints of the optimization problem being solved, and (b) by variations in the parameters of the probability distribution. Robustness is important for achieving performance improvements that are not problem specific. In this work we show that the performance improvements are the result of how these long-tailed distributions enable MBH to search the solution space faster and more thoroughly. In developing this explanation, we use the concepts of sub-diffusive, normally-diffusive, and super-diffusive random walks (RWs) originally developed in the field of statistical physics.

autonomous↗
NASA NTRS1980

IEA/SPS 500 kW distributed collector system

Engineering studies for an International Energy Agency project for the design and construction of a 500 kW solar thermal electric power generation system of the distributed collector system (DCS) type are reviewed. The DCS system design consists of a mixed field of parabolic trough type solar collectors which are used to heat a thermal heat transfer oil. Heated oil is delivered to a thermocline storage tank from which heat is extracted and delivered to a boiler by a second heat transfer loop using the same heat transfer oil. Steam is generated in the boiler, expanded through a steam turbine, and recirculated through a condenser system cooled by a wet cooling tower.

Neumann, T. W.↗
DOE OSTI2024

Prediction of Distributed River Sediment Respiration Rates Using Community-Generated Data and Machine Learning

River sediment microbial respiration is a key indicator of ecosystem functioning and the biogeochemical fluxes across this critical zone link surface and subsurface waters. As such, there is tremendous interest in measuring and mapping these respiration rates. Respiration observations are expensive and labor intensive; there is limited data available to the community. An open science, collaborative initiative is collecting samples for respiration rate analysis and multi-scale metadata; this evolving data set is being used for making machine learning (ML) predictions at unsampled sites to help inform continued community engagement. However, it is a challenge to find an optimum configuration for ML models to work with this feature-rich (i.e., 100+ possible input variables) data set. Here, we present results from a two-tiered approach to managing the analysis of this complex data set: (a) a stacked ensemble of models that automatically optimizes hyperparameters and manages the training of many models and (b) feature permutation importance to detect the most important features in the models. The major elements of this workflow are modular, portable, open, and cloud-based thus making this implementation a potential template for other applications. The models developed here predict that sediment organic matter chemistry is one of the most important features for predicting sediment respiration rate. Other larger-scale, important features fall into the categories of climatic, ecological, geological, and fluvial settings. Leveraging these larger-scale features to generate data-driven estimates of river sediment respiration rates reveals spatially consistent but heterogeneous patterns across the river network of the Columbia River Basin.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Error propagation in a digital avionic processor: A simulation-based study

An experimental analysis to study error propagation from the gate to the chip level is described. The target system is the CPU in the Bendix BDX-930, an avionic miniprocessor. Error activity data for the study was collected via a gate-level simulation. A family of distributions to characterize the error propagation, both within the chip and at the pins, was then generated. Based on these distributions, measures of error propagation and severity were defined. The analysis quantifies the dependency of the measured error propagation on the location of the fault and the type of instruction/microinstruction executed.

Lomelino, D.↗
NASA NTRS2001

Nonstationary Dynamics Data Analysis with Wavelet-SVD Filtering

Nonstationary time-frequency analysis is used for identification and classification of aeroelastic and aeroservoelastic dynamics. Time-frequency multiscale wavelet processing generates discrete energy density distributions. The distributions are processed using the singular value decomposition (SVD). Discrete density functions derived from the SVD generate moments that detect the principal features in the data. The SVD standard basis vectors are applied and then compared with a transformed-SVD, or TSVD, which reduces the number of features into more compact energy density concentrations. Finally, from the feature extraction, wavelet-based modal parameter estimation is applied.

Brenner, Marty↗
NASA NTRS1998

High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated with the monitoring architecture to reduce the volume of event traffic flow in the system, and thereby reduce the intrusiveness of the monitoring process. We are developing an event filtering architecture to efficiently process the large volume of event traffic generated by LSD systems (such as distributed interactive applications). This filtering architecture is used to monitor collaborative distance learning application for obtaining debugging and feedback information. Our architecture supports the dynamic (re)configuration and optimization of event filters in large-scale distributed systems. Our work represents a major contribution by (1) survey and evaluating existing event filtering mechanisms In supporting monitoring LSD systems and (2) devising an integrated scalable high- performance architecture of event filtering that spans several kev application domains, presenting techniques to improve the functionality, performance and scalability. This paper describes the primary characteristics and challenges of developing high-performance event filtering for monitoring LSD systems. We survey existing event filtering mechanisms and explain key characteristics for each technique. In addition, we discuss limitations with existing event filtering mechanisms and outline how our architecture will improve key aspects of event filtering.

Maly, K.↗
NASA NTRS1962

Combined Radiation and Forced Convection for Flow of a Transparent Gas in a Tube with Sinusoidal Axial Wall Heat Flux Distribution

An analysis is made of the influence that radiation exchanges between elements on the inside surface of a tube have on the wall and gas temperature distributions for forced-convection flow. The wall heat generation has a chopped sine distribution with length along the tube, which is a distribution often encountered in nuclear-reactor channels. The flowing gas is assumed transparent to thermal radiation and hence does not participate directly in the radiative exchange process. Axial heat conduction is neglected in the gas and tube wall, and the convective-heat-transfer coefficient and fluid properties are assumed constant. Several numerical examples are given to illustrate the effects of eight independent parameters such as wall emissivity, Stanton number, and length-diameter ratio. In some instances the radiation exchanges reduced the peak wall temperature or caused a reduction in the exit gas temperature because of radiation losses from the tube end openings.

TUBE↗
NASA NTRS2011

Estimated Accuracy of Three Common Trajectory Statistical Methods

Three well-known trajectory statistical methods (TSMs), namely concentration field (CF), concentration weighted trajectory (CWT), and potential source contribution function (PSCF) methods were tested using known sources and artificially generated data sets to determine the ability of TSMs to reproduce spatial distribution of the sources. In the works by other authors, the accuracy of the trajectory statistical methods was estimated for particular species and at specified receptor locations. We have obtained a more general statistical estimation of the accuracy of source reconstruction and have found optimum conditions to reconstruct source distributions of atmospheric trace substances. Only virtual pollutants of the primary type were considered. In real world experiments, TSMs are intended for application to a priori unknown sources. Therefore, the accuracy of TSMs has to be tested with all possible spatial distributions of sources. An ensemble of geographical distributions of virtual sources was generated. Spearman s rank order correlation coefficient between spatial distributions of the known virtual and the reconstructed sources was taken to be a quantitative measure of the accuracy. Statistical estimates of the mean correlation coefficient and a range of the most probable values of correlation coefficients were obtained. All the TSMs that were considered here showed similar close results. The maximum of the ratio of the mean correlation to the width of the correlation interval containing the most probable correlation values determines the optimum conditions for reconstruction. An optimal geographical domain roughly coincides with the area supplying most of the substance to the receptor. The optimal domain s size is dependent on the substance decay time. Under optimum reconstruction conditions, the mean correlation coefficients can reach 0.70 0.75. The boundaries of the interval with the most probable correlation values are 0.6 0.9 for the decay time of 240 h and 0.5 0.95 for the decay time of 12 h. The best results of source reconstruction can be expected for the trace substances with a decay time on the order of several days. Although the methods considered in this paper do not guarantee high accuracy they are computationally simple and fast. Using the TSMs in optimum conditions and taking into account the range of uncertainties, one can obtain a first hint on potential source areas.

Kabashnikov, Vitaliy P.↗
NASA NTRS2000

A Tool for Automatic Data Distribution for CFD Applications on Structured Grids

Development of HPF versions of NPB and ARC3D has shown that HPF provides an efficient, concise way to express parallelism and to organize data traffic. The use of HPF, as noted in the papers, requires an intimate knowledge of the applications and a detailed analysis of data affinity, data movement, and data granularity. To simplify and accelerate the task of developing HPF versions of existing CFD applications we have designed and implemented ADAPT (Automatic Data Alignment and Placement Tool). ADAPT analyzes a CFD application working on a single structured grid and generates HPF TEMPLATE, (RE)DISTRIBUTION, ALIGNMENT, and INDEPENDENT directives. The directives can be generated on the nest level, subroutine level, application level, or on the application interface level. ADAPT annotates an existing CFD FORTRAN application, performing computations on single or multiple grids. On each grid the application is considered as a sequence of operators, each applied to a set of variables defined in a particular grid domain. ADAPT automatically detects implicit operators (i.e., having data dependences) and explicit operators (without data dependences). For parallelization of an explicit operator ADAPT creates a template for the operator domain, aligns arrays used in the operator with the template, distributes the template, and declares the loops over the distributed dimensions as INDEPENDENT. For parallelization of an implicit operator, the distribution of the operator's domain should be consistent with the operator's dependences. Any dependence between sections distributed on different processors would preclude parallelization if the compiler does not have an ability to pipeline computations. If a data distribution is "orthogonal" to the dependences of an implicit operator, then the loop which implements the operator can be declared as INDEPENDENT. ADAPT starts with an analysis of array index expressions of the loop nests. For each pair of arrays referenced in an assignment statement, it generates an arc in the alignment graph and annotates it with an affinity relation. The template, alignment, and distribution directives for a particular loop nest are then derived from a transitive closure of the affinity relation. A compromise of data distributions in different nests and subroutines is achieved by merging annotated alignment graphs for adjacent nests/stibroutine calls in the nest/call graph of the application in the process called distribution lifting. ADAPT has been implemented as a C++ program running in conjunction with a parallelization tool called CAPTools. ADAPT uses the parse tree, interprocedural analysis and application database generated by CAPTools. It also uses the Directed Graph class, initially implemented in p2d2 (parallel debugger oi distributed programs), and some other classes supporting symbolic computations. ADAPT uses data distribution techniques described. ADAPT was tested with ARC3D and the FT benchmark and has demonstrated a code performance within a factor of 1.5 of handwritten versions.

Frumkin, Michael↗
DOE OSTI2024

MENT-Flow: maximum-entropy phase space tomography using normalizing flows

Generative models can be trained to reproduce low-dimensional projections of high-dimensional phase space distributions. Normalizing flows are generative models that parameterize invertible transformations, allowing exact probability density evaluation and sampling. Consequently, flows are unbiased entropy estimators and could be used to solve the high-dimensional maximum-entropy tomography (MENT) problem. In this work, we evaluate a flow-based MENT solver (MENT-Flow) against exact maximum-entropy solutions and Minerbo's iterative MENT algorithm in two dimensions.

Hoover, Austin↗
DOE OSTI2025

Generative learning for slow manifolds and bifurcation diagrams

In dynamical systems characterized by separation of time scales, the approximation of so called “slow manifolds”, on which the long term dynamics lie, is a useful step for model reduction. Initializing on such slow manifolds is a useful step in modeling, since it circumvents fast transients, and is crucial in multiscale algorithms (like the equation-free approach) alternating between fine scale (fast) and coarser scale (slow) simulations. In a similar spirit, when one studies the infinite time dynamics of systems depending on parameters, the system attractors (e.g., its steady states) lie on bifurcation diagrams (curves for one-parameter continuation, and more generally, on manifolds in state parameter space. Sampling these manifolds gives us representative attractors (here, steady states of ODEs or PDEs) at different parameter values. Algorithms for the systematic construction of these manifolds (slow manifolds, bifurcation diagrams) are required parts of the “traditional” numerical nonlinear dynamics toolkit. In more recent years, as the field of Machine Learning develops, conditional score-based generative models (cSGMs) have been demonstrated to exhibit remarkable capabilities in generating plausible data from target distributions that are conditioned on some given label. It is tempting to exploit such generative models to produce samples of data distributions (points on a slow manifold, steady states on a bifurcation surface) conditioned on (consistent with) some quantity of interest (QoI, observable). In this work, we present a framework for using cSGMs to quickly (a) initialize on a low-dimensional (reduced-order) slow manifold of a multi-time-scale system consistent with desired value(s) of a QoI (a “label”) on the manifold, and (b) approximate steady states in a bifurcation diagram consistent with a (new, out-of-sample) parameter value. This conditional sampling can help uncover the geometry of the reduced slow-manifold and/or approximately “fill in” missing segments of steady states in a bifurcation diagram. Finally, the quantity of interest, which determines how the sampling is conditioned, is either known a priori or identified using manifold learning-based dimensionality reduction techniques applied to the training data.

Dynamical systems↗
NASA NTRS1983

Effects of voltage control in utility interactive dispersed storage and generation systems

When a small generator is connected to the distribution system, the voltage at the point of interconnection is determined largely by the system and not the generator. The effect on the generator, on the load voltage and on the distribution system of a number of different voltage control strategies in the generator is examined. Synchronous generators with three kinds of exciter control are considered, as well as induction generators and dc/ac inverters, with and without capacitor compensation. The effect of varying input power during operation (which may be experienced by generators based on renewable resources) is explored, as well as the effect of connecting and disconnecting the generator at ten percent of its rated power. Operation with a constant slightly lagging factor is shown to have some advantages.

Kirkham, H.↗
NASA NTRS1972

Multiple element airfoils optimized for maximum lift coefficient.

Optimum airfoils in the sense of maximum lift coefficient are obtained for incompressible fluid flow at large Reynolds number. The maximum lift coefficient is achieved by requiring that the turbulent skin friction be zero in the pressure rise region on the airfoil upper surface. Under this constraint, the pressure distribution is optimized. The optimum pressure distribution is a function of Reynolds number and the trailing edge velocity. Geometries of those airfoils which will generate these optimum pressure distributions are obtained using a direct-iterative method which is developed in this study. This method can be used to design airfoils consisting of any number of elements. Numerical examples of one- and two-element airfoils are given. The maximum lift coefficients obtained range from 2 to 2.5.

Ormsbee, A. I.↗