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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

On the connection between least squares, regularization, and classical shadows

Classical shadows (CS) offer a resource-efficient means to estimate quantum observables, circumventing the need for exhaustive state tomography. Here, we clarify and explore the connection between CS techniques and least squares (LS) and regularized least squares (RLS) methods commonly used in machine learning and data analysis. By formal identification of LS and RLS ``shadows'' completely analogous to those in CS---namely, point estimators calculated from the empirical frequencies of single measurements---we show that both RLS and CS can be viewed as regularizers for the underdetermined regime, replacing the pseudoinverse with invertible alternatives. Through numerical simulations, we evaluate RLS and CS from three distinct angles: the tradeoff in bias and variance, mismatch between the expected and actual measurement distributions, and the interplay between the number of measurements and number of shots per measurement. Compared to CS, RLS attains lower variance at the expense of bias, is robust to distribution mismatch, and is more sensitive to the number of shots for a fixed number of state copies---differences that can be understood from the distinct approaches taken to regularization. Conceptually, our integration of LS, RLS, and CS under a unifying ``shadow'' umbrella aids in advancing the overall picture of CS techniques, while practically our results highlight the tradeoffs intrinsic to these measurement approaches, illuminating the circumstances under which either RLS or CS would be preferred, such as unverified randomness for the former or unbiased estimation for the latter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1993

The WorkPlace distributed processing environment

Real time control problems require robust, high performance solutions. Distributed computing can offer high performance through parallelism and robustness through redundancy. Unfortunately, implementing distributed systems with these characteristics places a significant burden on the applications programmers. Goddard Code 522 has developed WorkPlace to alleviate this burden. WorkPlace is a small, portable, embeddable network interface which automates message routing, failure detection, and re-configuration in response to failures in distributed systems. This paper describes the design and use of WorkPlace, and its application in the construction of a distributed blackboard system.

Ames, Troy↗
DOE OSTI2025

Out-of-distribution detection with non-parametric density estimation for models predicting processing history of uranium ore concentrates

The rapid advancement in machine learning (ML) and computer vision (CV) coincides with the growth of interest in deploying these ML/CV models in numerous fields from medicine to social science. Similar to those areas, we have witnessed a great number of works in materials science employing ML/CV models – neural networks in particular – in their studies in recent years. These models have proven to obtain accurate performance in various tasks. However, these models struggle to attain a similar performance when encountering test samples coming from a distribution that is different from the training set. More importantly, they fail without providing any warning to the users. Therefore, we propose a framework for detecting out-of-distribution (OOD) samples to alert users when a human intervention might be necessary in this work. Specifically, we explore the use of a non-parametric density estimation method to detect OOD samples. Here, we assess OOD detection capability of the proposed framework on ML models developed for categorizing precipitation routes of U 3 O 8 when encountering OOD datasets that contain samples (1) undergone different imaging acquisition process, (2) undergone different material synthesis process, and (3) different materials than ID set. Through those experiments, we achieve an average area under the receiver operating characteristic (AUROC) of at least 91% on average in detecting OOD samples. With minimal overhead cost and superior performance, the proposed framework enables a reliable and safe system when deploying in real-world scenarios.

Convolutional neural networks↗
DOE OSTI2025

Physics-constrained superresolution diffusion for six-dimensional phase space diagnostics

Adaptive physics-constrained superresolution diffusion is developed for noninvasive virtual diagnostics of the six-dimensional (6D) phase space density of charged particle beams. An adaptive variational autoencoder embeds initial beam condition images and scalar measurements to a low-dimensional latent space from which a 32 6 pixel 6D tensor representation of the beam's 6D phase space density is generated. Projecting from a 6D tensor generates physically consistent two-dimensional projections. Physics-guided superresolution diffusion transforms low-resolution images of the 6D density to high resolution 256 × 256 pixel images. Unsupervised adaptive latent space tuning enables tracking of time-varying beams without knowledge of time-varying initial conditions. The method is demonstrated with experimental data and multiparticle simulations at the HiRES UED. The general approach is applicable to a wide range of complex dynamic systems evolving in high-dimensional phase space. The method is shown to be robust to distribution shift without retraining. Published by the American Physical Society 2025

43 PARTICLE ACCELERATORS↗
NASA NTRS1999

Ionized Outflows in 3-D Insights from Herbig-Haro Objects and Applications to Nearby AGN

HST shows that the gas distributions of these objects are complex and clump at the limit of resolution. HST spectra have lumpy emission-line profiles, indicating unresolved sub-structure. The advantages of 3D over slits on gas so distributed are: robust flux estimates of various dynamical systems projected along lines of sight, sensitivity to fainter spectral lines that are physical diagnostics (reddening-gas density, T, excitation mechanisms, abundances), and improved prospects for recovery of unobserved dimensions of phase-space. These advantages al- low more confident modeling for more profound inquiry into underlying dynamics. The main complication is the effort required to link multi- frequency datasets that optimally track the energy flow through various phases of the ISM. This tedium has limited the number of objects that have been thoroughly analyzed to the a priori most spectacular systems. For HHO'S, proper-motions constrain the ambient B-field, shock velocity, gas abundances, mass-loss rates, source duty-cycle, and tie-ins with molecular flows. If the shock speed, hence ionization fraction, is indeed small then the ionized gas is a significant part of the flow energetics. For AGN'S, nuclear beaming is a source of ionization ambiguity. Establishing the energetics of the outflow is critical to determining how the accretion disk loses its energy. CXO will provide new constraints (especially spectral) on AGN outflows, and STIS UV-spectroscopy is also constraining cloud properties (although limited by extinction). HHO's show some of the things that we will find around AGN'S. I illustrate these points with results from ground-based and HST programs being pursued with collaborators.

Cecil, Gerald↗
NASA NTRS2012

Magnetization of the Lunar Crust

Magnetic fields measured by the satellite Lunar Prospector show large scale features resulting from remanently magnetized crust. Vector data synthesized at satellite altitude from a spherical harmonic model of the lunar crustal field, and the radial component of the magnetometer data, have been used to produce spatially continuous global magnetization models for the lunar crust. The magnetization is expressed in terms of localized basis functions, with a magnetization solution selected having the smallest root-mean square magnetization for a given fit to the data, controlled by a damping parameter. Suites of magnetization models for layers with thicknesses between 10 and 50 km are able to reproduce much of the input data, with global misfits of less than 0.5 nT (within the uncertainties of the data), and some surface field estimates. The magnetization distributions show robust magnitudes for a range of model thicknesses and damping parameters, however the magnetization direction is unconstrained. These global models suggest that magnetized sources of the lunar crust can be represented by a 30 km thick magnetized layer. Average magnetization values in magnetized regions are 30-40 mA/m, similar to the measured magnetizations of the Apollo samples and significantly weaker than crustal magnetizations for Mars and the Earth. These are the first global magnetization models for the Moon, providing lower bounds on the magnitude of lunar crustal magnetization in the absence of multiple sample returns, and can be used to predict the crustal contribution to the lunar magnetic field at a particular location.

Lunar↗
NASA NTRS2016

NASA's Preparations for ESA's L3 Gravitational Wave Mission

Telescope Subsystem - Jeff Livas (GSFC): Demonstrate pathlength stability, straylight and manufacturability. Phase Measurement System - Bill Klipstein (JPL): Key measurement functions demonstrated. Incorporate full flight functionality. Laser Subsystem - Jordan Camp (GSFC): ECL master oscillator, phase noise of fiber power amplifier, demonstrate end-to-end performance in integrated system, lifetime. Micronewton Thrusters - John Ziemer (JPL): Propellant storage and distribution, system robustness, manufacturing yield, lifetime. Arm-locking Demonstration - Kirk McKenzie (JPL): Studying a demonstration of laser frequency stabilization with GRACE Follow-On. Torsion Pendulum - John Conklin (UF): Develop U.S. capability with GRS and torsion pendulum test bed. Multi-Axis Heterodyne Interferometry - Ira Thorpe (GSFC): Investigate test mass/optical bench interface. UV LEDs - John Conklin+ (UF): Flight qualify UV LEDs to replace mercury lamps in discharging system. Optical Bench - Guido Mueller (UF): Investigate alternate designs and fabrication processes to ease manufacturability. LISA researchers at JPL are leading the Laser Ranging Interferometer instrument on the GRACE Follow-On mission.

Midterm Assessment↗
NASA NTRS2020

Simultaneous Optical Links with the Inter-Satellite Omnidirectional Optical Communicator

As the onboard data volume for smaller platforms such as CubeSats increases, Radio Frequency (RF) communications systems may be unable to adequately support the required downlink demand. Optical communications (lasercom) systems can relieve the data bottleneck as they can support higher data throughput than RF for comparable Size, Weight, and Power (SWaP). Lasercom crosslinks are of particular interest for spacecraft swarms and constellations because they enable additional mission robustness for distributed science observations and remote sensing applications. The Inter-Satellite Omnidirectional optical Communicator (ISOC) is capable of supporting simultaneous lasercom crosslinks between multiple spacecraft at separations of up to thousands of kilometers in orbit. The ISOC architecture features a truncated dodecahedron chassis containing an array of photodetectors and gimbal-less MEMS mirrors, enabling full-duplex communications. The main objectives of the ISOC terminal include: 1) full sky coverage, 2) Gbps data rates, and 3) the ability to maintain multiple simultaneous links. We show ISOC can support up to 12 simultaneous links with the current architecture at 1-Gbps at 200-km separation with 10-9 BER. Compared to current lasercom transceivers (i.e., point-to-point), ISOC offers increased throughput performance for similar SWaP. A detailed link budget for both scenarios is presented, and the limiting factors for maximum number of simultaneous links are discussed.

Cahoy, Kerri↗
NASA NTRS2022

New Directions in Tropical Phenology

Earth’s most speciose biomes are in the tropics, yet tropical plant phenology remains poorly understood. Tropical phenological data are comparatively scarce and viewed through the lens of a ‘temperate phenological paradigm’ expecting phenological traits to respond to strong, predictably annual shifts in climate (e.g., between subfreezing and frost-free periods). Digitized herbarium data greatly expand existing phenological data for tropical plants; and circular data, statistics, and models are more appropriate for analyzing tropical (and temperate) phenological datasets. Phylogenetic information, which remains seldom applied in phenological investigations, provides new insights into phenological responses of large groups of related species to climate. Consistent combined use of herbarium data, circular statistical distributions, and robust phylogenies will rapidly advance our understanding of tropical – and temperate – phenology.

tropical phenology↗
NASA NTRS2005

A Scalable and Robust Multi-Agent Approach to Distributed Optimization

Modularizing a large optimization problem so that the solutions to the subproblems provide a good overall solution is a challenging problem. In this paper we present a multi-agent approach to this problem based on aligning the agent objectives with the system objectives, obviating the need to impose external mechanisms to achieve collaboration among the agents. This approach naturally addresses scaling and robustness issues by ensuring that the agents do not rely on the reliable operation of other agents We test this approach in the difficult distributed optimization problem of imperfect device subset selection [Challet and Johnson, 2002]. In this problem, there are n devices, each of which has a "distortion", and the task is to find the subset of those n devices that minimizes the average distortion. Our results show that in large systems (1000 agents) the proposed approach provides improvements of over an order of magnitude over both traditional optimization methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents fail midway through the simulation) the system remains coordinated and still outperforms a failure-free and centralized optimization algorithm.

Tumer, Kagan↗
DOE OSTI2024

A consistent dataset for the net income distribution for 190 countries and aggregated to 32 geographical regions from 1958 to 2015

Abstract. Data on income distributions within and across countries are becoming increasingly important for informing analysis of income inequality and understanding the distributional consequences of climate change. While datasets on income distribution collected from household surveys are available for multiple countries, these datasets often do not represent the same concept of inequality (or income concept) and therefore make comparisons across countries, over time and across datasets difficult. Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the Gini coefficient. For the imputation, we use a recently developed nonparametric principal-component-based approach that shows an excellent fit to data on income distributions compared to other approaches. We also present another version of this dataset aggregated from the country level to 32 geographical regions. Our dataset is developed for the purpose of calibrating models such as integrated human–Earth system models with detailed data on income distributions. This dataset will enable more robust analysis of income distribution at multiple scales. The latest version of our data are available on Zenodo: https://doi.org/10.5281/zenodo.7093997 (Narayan et al., 2022b).

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1973

The robustness of reliability predictions for series systems of identical components.

The robustness of reliability predictions based on the exponential failure law is investigated under possible deviations within the Weibull family of failure distributions. Regions of robustness are provided for series systems of N identical components, N = 1(1)15; i.e., regions in the space of the Weibull shape parameter, within which one may safely use the exponential prediction procedure and have no more than a prespecified error.

Posten, H. O.↗
NASA NTRS2006

Efficient and Robust Data Collection Using Compact Micro Hardware, Distributed Bus Architectures and Optimizing Software

Future In-Space propulsion systems for exploration programs will invariably require data collection from a large number of sensors. Consider the sensors needed for monitoring several vehicle systems states of health, including the collection of structural health data, over a large area. This would include the fuel tanks, habitat structure, and science containment of systems required for Lunar, Mars, or deep space exploration. Such a system would consist of several hundred or even thousands of sensors. Conventional avionics system design will require these sensors to be connected to a few Remote Health Units (RHU), which are connected to robust, micro flight computers through a serial bus. This results in a large mass of cabling and unacceptable weight. This paper first gives a survey of several techniques that may reduce the cabling mass for sensors. These techniques can be categorized into four classes: power line communication, serial sensor buses, compound serial buses, and wireless network. The power line communication approach uses the power line to carry both power and data, so that the conventional data lines can be eliminated. The serial sensor bus approach reduces most of the cabling by connecting all the sensors with a single (or redundant) serial bus. Many standard buses for industrial control and sensor buses can support several hundreds of nodes, however, have not been space qualified. Conventional avionics serial buses such as the Mil-Std-1553B bus and IEEE 1394a are space qualified but can support only a limited number of nodes. The third approach is to combine avionics buses to increase their addressability. The reliability, EMI/EMC, and flight qualification issues of wireless networks have to be addressed. Several wireless networks such as the IEEE 802.11 and Ultra Wide Band are surveyed in this paper. The placement of sensors can also affect cable mass. Excessive sensors increase the number of cables unnecessarily. Insufficient number of sensors may not provide adequate coverage of the system. This paper also discusses an optimal technique to place and validate sensors.

micro hardware↗
NASA NTRS2020

Robustness Computation of Dynamic Controllability in Probabilistic Temporal Networks with Ordinary Distributions

Most existing works in Probabilistic Simple Temporal Networks (PSTNs) base their frameworks on well-defined probability distributions. This paper addresses on PSTN Dynamic Controllability (DC) robustness measure, i.e. the execution success probability of a network under dynamic control.We consider PSTNs where the probability distributions of the contingent edges are ordinary distributed (e.g. non-parametric, non-symmetric). We introduce the concepts of dispatching protocol (DP) as well as DP-robustness, the probability of success under a predefined dynamic policy.We propose a fixed-parameter pseudo-polynomial time algorithm to compute the exact DP-robustness of any PSTN under \textit{NextFirst} protocol, and apply to various PSTN datasets, including the real case of planetary exploration in the context of the Mars 2020 rover, and propose an original structural analysis.

Saint-Guillain, Michael↗
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 NTRS2014

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

Trajectory optimization methods using MBH have become well developed during the past decade. 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 RVs 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 Englander significantly improves MBH performance, and that Pareto distributions provide even greater improvements. Improved performance is defined in terms of efficiency and robustness, where efficiency is finding better solutions in less time, and 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 RWs originally developed in the field of statistical physics.

mission design↗