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At least 397 records · Page 22

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NASA NTRS2025

Mission-Maps For Outbound Cislunar Transfer Trajectories

This study quantifies the robustness and sensitivity of an outbound cislunar trajectory for a lunar lander in the form of mission-maps, or topological maps that allows either a computer program or mission designer to intuitively optimize the placement of critical outbound correction burns from the derived sensitivity data. The non-linear multi-body dynamics are applied to generate an outbound cislunar reference profile used by a linear covariance analysis (LinCov) tool to compute the expected Δv and trajectory dispersions due to the initial state uncertainty, sensor errors, maneuver execution errors, and disturbance accelerations along the outbound cislunar profile. The rapid performance analysis capabilities of LinCov are complimented with parallel processing techniques to evaluate hundreds and thousands of different translational burn locations, placements, and targeting constraints to identify the combination that minimizes the total Δv usage (nominal plus 3σ Δv) and trajectory dispersions at lunar orbit insertion. This study utilizes a generalized reference targeting algorithm to quickly assess the integrated closed-loop GN&C system performance due to different targeting configurations and constraints. The resulting mission maps provide an intuitive insight to ascertain each trajectory correction maneuver’s (TCM) sensitivity to different burn times along an outbound cislunar trajectory and quickly identify desirable engineering tradeoffs when performing analysis on the number and placement of these burns that nominally zero. Multiple mission maps are generated for a variety of different performance parameters that allow engineers to visually identify optimal solutions for trajectory correction maneuver placements, the number of correction burns, and the targeting constraints for each burn.

GN&C↗

DOE OSTI2017

Savannah River Remediation Liquid Waste Operations Making the Workplace Safer - Lean and Human Performance Improvement Initiatives - 17244

The Savannah River Site, a U.S. Department of Energy facility, contracted Savannah River Remediation (SRR) to manage its liquid waste project, which is a unique, high hazard nuclear waste treatment and disposal facility consisting of 51, one million gallon underground waste tanks, a solvent extraction processing unit, a vitrification facility for the highest radioactive waste, and a grout solidification and disposal facility for a decontaminated salt solution. Our Project mission is to treat the nuclear waste and close the associated storage and treatment facilities, of which, 8 of the 51 tanks have been closed to date. Over the past three years, SRR implemented a Lean Business Management System to address site inefficiencies, aging infrastructure concerns and budget constraints. The Lean philosophy started with the work of W. Edwards Deming and his contemporaries. In more recent years the process has matured in the Toyota Production System and migrated into fields as diverse as services industries, health-care, and now the DOE complex. Like safety, continuous improvement is a fundamental core business value that starts at the top. The Lean Business System, led by our executive management team, drives quality, production and waste elimination by focusing on People using a structured Process that allows the workforce to identify and fix problems in their workplace. Many inefficiencies and quality related issues start with the desire to make systems fail-safe without defining the core requirements for which that process or program was created. This leads to added complexity and latent or inherent human performance issues embedded within our processes. While Lean can't fix all problems, a combination of strong nuclear safety culture, robust conduct of operations, active human performance improvement process, and a business practice of continuously looking for improvements leads to excellence across our industry and creates a culture that is worthy of promoting. Without strong management, our systems fail because no one sponsors or encourages those attributes we covet. Leadership starts at the top with our customer defining what provides 'value' to them, and filters down through to the organization and ultimately the workforce in day to day conduct of operations. It is imperative that our customer drives these desirable ideals through recognition and contractual requirements to encourage and support those behavioral traits that are critical to our ongoing success.This paper focuses on how the Lean Business Management System supports those attributes that we value: a strong nuclear safety culture; disciplined conduct of operations; and a culture of robust human performance and continuous improvement. These attributes in our daily work environment propel a safer, more consistent, more efficient workplace. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Graph-Learning-Assisted State and Event Tracking for Solar-Penetrated Power Grids with Heterogeneous Data Sources

Unlike transmission systems, distribution systems do not typically contain sufficient metering to enable real-time state estimation. The lack of sufficient real-time measurements prohibits accurate and timely monitoring of the state of distribution systems. As a result, control and optimal operation of distribution systems, especially those containing large numbers of renewable generation units are not possible without proper data and information about the current state of the system. The main motivation of this project is to address this shortcoming by developing an approach which provides “predicted” real-time measurements so that they can be used to execute a distribution system state estimator. Thus, the objective of the project is to make the distribution systems fully observable, such that the hosting capacity for solar generation can be accurately estimated, and unnecessary solar curtailments can be avoided. In order to accomplish this goal, the project investigated the use of a grid-model-informed machine learning (ML) tool which integrates heterogeneous data streams obtained from AMI meters, SCADA as well as PMU measurements and created synchronous measurement snapshots for the state estimator (SE); and developed a hybrid robust SE which provides not only accurate state estimates but also real-time feedback for the ML model refinement.

14 SOLAR ENERGY↗

NASA NTRS1992

Methodologies for building robust schedules

COMPASS is the name of a Computer Aided Scheduling System designed and built for NASA. COMPASS can be used to develop schedule of activities based upon the temporal relationships of the activities and their resource requirements. COMPASS uses this information, and guided by the user, develops precise start and stop times for the activities. In actual practice however, it is impossible to know with complete certainty what the actual durations of the scheduled activities will really be. The best that one can hope for is knowledge of the probability distribution for the durations. This paper investigates methodologies for using a scheduling tool like COMPASS that is based upon definite values for the resource requirements, while building schedules that remain valid in the face of the schedule execution perturbations. Representations for the schedules developed by these methodologies are presented, along with a discussion of the algorithm that could be used by a computer onboard a spacecraft to efficiently monitor and execute these schedules.

Dean, John H.↗

DOE OSTI2013

A monolithic mass tracking formulation for bubbles in incompressible flow

We devise a novel method for treating bubbles in incompressible flow that relies on the conservative advection of bubble mass and an associated equation of state in order to determine pressure boundary conditions inside each bubble. We show that executing this algorithm in a traditional manner leads to stability issues similar to those seen for partitioned methods for solid–fluid coupling. Therefore, we reformulate the problem monolithically. This is accomplished by first proposing a new fully monolithic approach to coupling incompressible flow to fully nonlinear compressible flow including the effects of shocks and rarefactions, and then subsequently making a number of simplifying assumptions on the air flow removing not only the nonlinearities but also the spatial variations of both the density and the pressure. The resulting algorithm is quite robust, has been shown to converge to known solutions for test problems, and has been shown to be quite effective on more realistic problems including those with multiple bubbles, merging and pinching, etc. Notably, this approach departs from a standard two-phase incompressible flow model where the air flow preserves its volume despite potentially large forces and pressure differentials in the surrounding incompressible fluid that should change its volume. Our bubbles readily change volume according to an isothermal equation of state.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2022

Maturation of Dynamic Power Convertors for RPS Robotic Space Exploration

NASA is developing dynamic power conversion technologies for future robotic space science and exploration missions powered by Radioisotope Power Systems (RPS). The Dynamic Radioisotope Power Systems (DRPS) Project is working to mature numerous dynamic power convertors and controllers for potential infusion into future flight generators. Maturation of power conversion technologies is being managed by the RPS Program and executed by the DRPS Project and Thermal Energy Conversion Branch located at NASA’s Glenn Research Center (GRC). Convertor maturation includes multiple convertor technology development contracts to deliver new prototypes and continued testing of relevant legacy convertors, commissioned during past projects. The convertor technology development contracts include two Stirling contractor teams and one Brayton team. All contracts have now completed prototype fabrication and testing planned during Phase 2. Government assessment of the new prototypes includes verification of performance in relevant environments and validation of the design with a focus on robustness.

Scott Wilson↗

NASA NTRSDate not supplied

Maturation of Dynamic Power Convertors for RPS Robotic Space Exploration

Scott Wilson↗

NASA NTRS2020

Is a Linear or a Walkabout Protocol More Efficient When Using a Rover to Choose Biologically Relevant Samples in a Small Region of Interest?

We conducted a field test at a potential Mars analog site to provide insight into planning for future robotic missions such as Mars 2020, where science operations must facilitate efficient choice of biologically relevant sampling locations. We compared two data acquisition and decision-making protocols currently used by Mars Science Laboratory: (1) a linear approach, where sites are examined as they are encountered and (2) a walkabout approach, in which the field site is first examined with remote rover instruments to gain an understanding of regional context followed by deployment of time- and power-intensive contact and sampling instruments on a smaller subset of locations. The walkabout method was advantageous in terms of both the time required to execute and a greater confidence in results and interpretations, leading to enhanced ability to tailor follow-on observations to better address key science and sampling goals. This advantage is directly linked to the walkabout method's ability to provide broad geological context earlier in the science analysis process. For Mars 2020, and specifically for small regions to be explored (e.g., <1 sq. km), we recommend that the walkabout approach be considered where possible, to provide early context and time for the science team to develop a coherent suite of hypotheses and robust ways to test them.

R. Aileen Yingst↗

DOE OSTI2024

OASIS: Offsetting Active Reconstruction Attacks in Federated Learning

Federated Learning (FL) has garnered significant attention for its potential to protect user privacy while enhancing model training efficiency. For that reason, FL has found its use in various domains, from health care to industrial engineering, especially where data cannot be easily exchanged due to sensitive information or privacy laws. However, recent research has demonstrated that FL protocols can be easily compromised by active reconstruction attacks executed by dishonest servers. These attacks involve the malicious modification of global model parameters, allowing the server to obtain a verbatim copy of users' private data by inverting their gradient updates. Tackling this class of attack remains a crucial challenge due to the strong threat model. In this paper, we propose a defense mechanism, namely OASIS, based on image augmentation that effectively counteracts active reconstruction attacks while preserving model performance. We first uncover the core principle of gradient inversion that enables these attacks and theoretically identify the main conditions by which the defense can be robust regardless of the attack strategies. We then construct our defense with image augmentation showing that it can undermine the attack principle. Comprehensive evaluations demonstrate the efficacy of the defense mechanism highlighting its feasibility as a solution.

deep neural networks↗

DOE OSTI2020

Nonlinear sparse Bayesian learning for physics-based models

This paper addresses the issue of overfitting while calibrating unknown parameters of over-parameterized physics-based models with noisy and incomplete observations. Here, a semi-analytical Bayesian framework of nonlinear sparse Bayesian learning (NSBL) is proposed to identify sparsity among model parameters during Bayesian inversion. NSBL offers significant advantages over machine learning algorithm of sparse Bayesian learning (SBL) for physics-based models, such as 1) the likelihood function or the posterior parameter distribution is not required to be Gaussian, and 2) prior parameter knowledge is incorporated into sparse learning (i.e. not all parameters are treated as questionable). NSBL employs the concept of automatic relevance determination (ARD) to facilitate sparsity among questionable parameters through parameterized prior distributions. The analytical tractability of NSBL is enabled by employing Gaussian ARD priors and by building a Gaussian mixture-model approximation of the posterior parameter distribution that excludes the contribution of ARD priors. Subsequently, type-II maximum likelihood is executed using Newton's method whereby the evidence and its gradient and Hessian information are computed in a semi-analytical fashion. We show numerically and analytically that SBL is a special case of NSBL for linear regression models. Subsequently, a linear regression example involving multimodality in both parameter posterior pdf and model evidence is considered to demonstrate the performance of NSBL in cases where SBL is inapplicable. Next, NSBL is applied to identify sparsity among the damping coefficients of a mass-spring-damper model of a shear building frame. These numerical studies demonstrate the robustness and efficiency of NSBL in alleviating overfitting during Bayesian inversion of nonlinear physics-based models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Plan for IER-443 Testing of the Y-12 and AWE Criticality Accident Alarm System Detectors at the Godiva IV Burst Reactor

This document provides the scope and details of the “Plan for Testing the Y-12 and AWE Criticality Accident Alarm System Detectors at the Godiva IV Burst Reactor”. Due to the relative simplicity of the testing goals, scope, and methodology, the NCSP Manager approved execution of the test when ready. No preliminary CED-1 or final design CED-2 reports were required or issued. The test will subject Criticality Accident Alarm System (CAAS) detectors supplied by Y- 12 and AWE to very intense and short duration mixed neutron and gamma radiation fields. The goals of the test will be to (1) substantiate functionality, for both existing and newly acquired Y- 12 CAAS detectors, and (2) the ability of the AWE detectors to provide quality temporal dose information after a hypothetical criticality accident. ANSI/ANS-8.3.1997 states that the “system shall be sufficiently robust as to actuate an alarm signal when exposed to the maximum radiation expected”, which has been defined at Y-12, in Documented Safety Analyses (DSAs), to be a dose rate of 10 Rad/s. ANSI/ANS-8.3.1997 further states that “alarm actuation shall occur as a result of a minimum duration transient” which may be assumed to be 1 msec. The pulse widths and dose rates which will be achieved in this test will exceed these requirements. Pulsed radiation fields will be produced by the Godiva IV fast metal burst reactor at the National Criticality Experimental Research Center (NCERC) at the Nevada National Security Site (NNSS). The magnitude of the pulses and the relative distances to the detectors will be varied to afford a wide range of radiation fluence and pulse widths. The magnitude of the neutron and gamma fields will be determined by reactor temperature rise to fluence and dose conversions which have been previously established through extensive measurements performed under IER-147. The requirements for CAAS systems to detect and alarm under a “minimum accident of concern” as well as other functional requirements specified in ANSI/ANS-8.3.1997, are not included in the test. Routine and periodic maintenance and calibrations performed at Y-12 and AWE are intended to provide adequate confirmation for meeting these requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1993

Fuzzy logic particle tracking velocimetry

Fuzzy logic has proven to be a simple and robust method for process control. Instead of requiring a complex model of the system, a user defined rule base is used to control the process. In this paper the principles of fuzzy logic control are applied to Particle Tracking Velocimetry (PTV). Two frames of digitally recorded, single exposure particle imagery are used as input. The fuzzy processor uses the local particle displacement information to determine the correct particle tracks. Fuzzy PTV is an improvement over traditional PTV techniques which typically require a sequence (greater than 2) of image frames for accurately tracking particles. The fuzzy processor executes in software on a PC without the use of specialized array or fuzzy logic processors. A pair of sample input images with roughly 300 particle images each, results in more than 200 velocity vectors in under 8 seconds of processing time.

Wernet, Mark P.↗

NASA NTRS2019

Uncertainty Quantification of a Rotorcraft Conceptual Sizing Toolsuite

A computational framework to support the quantification of system uncertainties and sensitivities for rotorcraft applications is presented using the NASA Design and Analysis of Rotorcraft (NDARC) conceptual sizing tool. A 90 passenger conceptual tiltrotor configuration was used for case demonstration in the modeling of uncertainties in NDARCs emission module. A non-intrusive forward propagation uncertainty quantification approach was applied to ensemble simulations using a Monte Carlo methodology with stratified Latin hypercube sampling. An off-the-shelf software, DAKOTA, which supports trade studies and design space exploration, including optimization, surrogate modeling and uncertainty analysis was used to address the research goals. A toolsuite was further developed incorporating DAKOTA with automated design processes and methods using function wrappers to execute program routines including support for data post-processing. Uncertainties in rotorcraft emissions modeling using the Average Temperature Response metric for a set mission profile were studied. It was shown that for the current study, using the base-line best estimate modeling parameters for the Average Temperature Response metric, NDARC under-estimates the effects of emissions when compared with results from Monte Carlo simulations. A global sensitivity analysis was further undertaken to quantify the contribution of the various emission species on output sensitivity, hence uncertainty. The work demonstrates that the developed toolsuite is robust and will support the quantification of system uncertainties and sensitivities in future rotorcraft design efforts.

Rotorcraft↗

NASA NTRS2012

Active Debris Removal

Orbital debris in Low Earth Orbit (LEO) is an international problem that threatens the success of future space ventures. An analysis of a wide variety of alternative solutions for active debris removal (ADR) has been performed. The solution selected is an efficient, effective, and executable solution to remove large debris in LEO, primarily spent rocket bodies. Removing large debris objects is a critical step in reducing the hazard from orbital debris, because of the large amount of medium and small debris created through large body collisions. Based on the analysis of alternatives, the concept and design for a vehicle which could efficiently address the debris hazard by disposing of several large objects per mission has been developed. This concept establishes a comprehensive, detailed technical approach for an actual end-to-end, on-orbit ADR solution to remove large debris. This robust solution enables the start of solving the problem of debris removal before it reaches a critical and potentially irreversible state by "getting there as soon as possible, as economically as possible, with the most capability".

Burns, Susan H.↗

DOE OSTI2026

An uncertainty visualization framework for large-scale cardiovascular flow simulations: A case study on aortic stenosis

We present a generalizable uncertainty quantification (UQ) and visualization framework for lattice Boltzmann method simulations of high Reynolds number vascular flows, demonstrated on a patient-specific stenosed aorta. The framework combines EasyVVUQ for parameter sampling with large-eddy simulation turbulence modeling in HemeLB, and executes ensembles on the Frontier exascale supercomputer. Spatially resolved metrics, including entropy and isosurface-crossing probability, are used to map uncertainty in pressure and wall shear stress fields directly onto vascular geometries. Two sources of model variability are examined: inlet peak velocity and the Smagorinsky constant. Inlet velocity variation produces high uncertainty downstream of the stenosis where turbulence develops, while upstream regions remain stable. Smagorinsky constant variation has little effect on the large-scale pressure field but increases WSS uncertainty in localized high-shear regions. In both cases, the stenotic throat manifests low entropy, indicative of robust identification of elevated WSS. By linking quantitative UQ measures to three-dimensional anatomy, the framework improves interpretability over conventional 1D UQ plots and supports clinically relevant decision-making, with broad applicability to vascular flow problems requiring both accuracy and spatial insight.

Hemodynamics↗

DOE OSTI2022

Stabilized Hyperfoam Modeling of the General Plastics EF4003 (3 PCF) Flexible Foam

Constitutive model parameterizations for the General Plastics EF4003 low density 3 pound per cubic foot are needed for design and qualification purposes in normal and abnormal mechanical simulations. The material is expected to be deformed in two ways: first during preloading, and second under impact conditions of the system (transient dynamic). All analyses are to be performed at room temperature. The goal is to provide the analysis community a robust constitutive model parameterization to represent the compression behavior of the EF4003 foam from small deformations up to massive compressive deformations when the foam is densifying. It is worth noting the EF4003 exhibits anisotropy in its stress-strain behavior between the rise and transverse directions (See figure 2.8c-d) as well as plateau behavior that is very likely to cause material stability issues, due to the buckling transition, (and has historically done so) when using Sandia’s current workhorse models for flexible foams, Hyperfoam and Flex Foam. A Stability-informed Hyperfoam parameterization procedure is developed and executed to calibrate a hyperfoam model for the EF4003 room temperature, transversely loaded data. A rise orientation parameterization was not attempted due to localization in the experiments.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Efficient Generalized Boundary Detection Using a Sliding Information Distance

In this work, we present a general machine learning algorithm for boundary detection within general signals based on an efficient, accurate, and robust approximation of the universal normalized information distance. Our approach uses an adaptive sliding information distance (SLID) combined with a wavelet-based approach for peak identification to locate the boundaries. Special emphasis is placed on developing an adaptive formulation of SLID to handle general signals with multiple unknown and/or drifting section lengths. Although specialized algorithms may outperform SLID when domain knowledge is available, these algorithms are limited to specific applications and do not generalize. SLID excels in these cases. We demonstrate the versatility and efficacy of SLID on a variety of signal types, including synthetically generated sequences of tokens, binary executables for reverse engineering applications, and time series of seismic events.

42 ENGINEERING↗

DOE OSTI2019

Los Alamos National Laboratory Fall Avian Migration Monitoring Report 2010-2018

During the fall of 2018, biologists at Los Alamos National Laboratory completed the ninth year of monitoring fall migration passerines (songbirds). Songbirds were captured at a mist-netting station located in a wetland/riparian complex in Technical Area 36 on the north side of Pajarito Road in Los Alamos County. Captured birds were identified, measured, and banded with a United States Fish and Wildlife Service (USFWS) migratory bird band. Banding operations took place between August and October, with the completion of a total of 10 mist-netting sessions annually. This project was conducted as part of the implementation of the Biological Resources Management Plan and is in compliance with the 2013 Memorandum of Understanding between the USFWS and the United States Department of Energy/National Nuclear Security Administration and Executive Order 13186. Between 2010 and 2018 the overall number of birds and species captured was variable. We saw significant differences in the bird community composition when we compared earlier years to later years. Although environmental variables including a drought severity index, were not shown to influence the community composition, insectivorous birds and the percentage of hatch year birds were influenced by drought severity. Additionally, Audubon’s Warbler and Virginia’s Warbler numbers decreased from 2010 and showed declining trends in their abundances. The variability in bird populations is likely driven by regional climatic factors, but more data are needed for robust assessments.

54 ENVIRONMENTAL SCIENCES↗