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At least 343 records · Page 19

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Battery State-of-Health Aware Path Planning for a Mars Rover

A rover mission consists of visiting waypoints to gather scientific samples based on set requirements. However, rovers face operational uncertainties during the mission, affecting the performance of its electrical and mechanical components and overall mission success. Hence, it is critical to have a decision-making framework that is aware of the health state of the components when planning the path of the vehicle. In particular, battery degradation, and consequently the battery State of Health (SOH), can affect the optimality of decisions made by the autonomous system in the long term. This paper presents a decision-making system that incorporates information on the energy drawn from the battery (based on the vehicle’s velocity), terrain conditions, and model-based prognostic modules to assess the impact on the battery’s state of charge (SoC). The decision-making system was formulated as a Markov Decision Process (MDP) to reach the goal destination by sending commands in a determined amount of time while maintaining the battery SoC within the policy stated. The MDP problem was programmed using the open-source framework POMDPs.jl, which has a variety of online and offline solvers. To solve the MDP problem online, we used Monte Carlo Tree Search (MCTS). Results from simulations demonstrate the effect that battery degradation and charging plans have on decision-making.

Prognostics↗

NASA NTRS1985

Scattered light in the IUE spectra of Epsilon Aurigae

As a result of this work it was found that light scattered from the longer wavelengths constitutes a small but non-negligible, wavelength and time dependent fraction of the measured flux in the far UV. The reality of the UV excess has not been unambigiously ruled out. However, it is noted that there are still uncertainties in the assumed scattering profile. New measurements of the scattering properties of the cross disperser grating are planned in order to verify the results of Mount and Fastie and extend the wavelength coverage into the far wings of the profile. The results of these measurements will no doubt reduce some of these uncertainties. For the present, it is felt that the BCH approach is a significant improvement over the methods heretofore available for the treatment of scattered light in IUE spectra.

Aitner, B.↗

NASA NTRS2010

The NASA VLBI2010 Proof-of-Concept Demonstration and Future Plans

The next generation geodetic VLBI instrument is being developed with a goal of 1 mm position uncertainty in twenty-four hours. We have implemented a proof-of-concept system for a possible VLBI2010 signal chain, from feed through recorder, on the Westford (Massachusetts, USA) 18-m and MV-3 (Maryland, USA) 5-m antennas. Data have been obtained in four 512 MHz bands spanning the range 3.5 to 11 GHz to investigate the sensitivity and phase delay capability of the system. Using a new phase cal design, the phases have been aligned across four bands spanning 2 GHz with an RMS deviation of approximately eight degrees. Several components of the system will be improved for the prototype version of VLBI2010, including the feed, digital backend, and recorder, and these will be installed on a 12-m antenna that has been purchased and is ready for installation at the Goddard Space Flight Center outside of Washington, D.C., USA, site of the MV-3 antenna.

Niell, Arthur↗

DOE OSTI2024

Advancing environmental assessment of the circular economy: Challenges and opportunities

The lifecycle assessment (LCA) framework is widely applied to comprehensively evaluate and improve the environmental performance of a circular economy (CE). The advances and application of LCA has been primarily restricted to evaluate the environmental performance of the CE at a micro-level, wherein the CE is implemented for a single product system. However, the CE can be operationalized at two broader levels: the meso–level (for eco-industrial parks) and the macro-level (for a city, state, or nation). Six methodological challenges emerge when applying LCA to a meso- or macro-level CE and remain unaddressed in the existing literature. This includes: selecting a relevant system boundary and functional unit, addressing data paucity and uncertainty, accounting for stakeholder behavior, assessing the trade-offs from renewable energy (RE) use, accounting for manufacturing and technology evolution, and quantifying displacement and rebound. This article proposes potential solutions and research priorities to address the above challenges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1988

Precise orbit determination for NASA's earth observing system using GPS (Global Positioning System)

An application of a precision orbit determination technique for NASA's Earth Observing System (EOS) using the Global Positioning System (GPS) is described. This technique allows the geometric information from measurements of GPS carrier phase and P-code pseudo-range to be exploited while minimizing requirements for precision dynamical modeling. The method combines geometric and dynamic information to determine the spacecraft trajectory; the weight on the dynamic information is controlled by adjusting fictitious spacecraft accelerations in three dimensions which are treated as first order exponentially time correlated stochastic processes. By varying the time correlation and uncertainty of the stochastic accelerations, the technique can range from purely geometric to purely dynamic. Performance estimates for this technique as applied to the orbit geometry planned for the EOS platforms indicate that decimeter accuracies for EOS orbit position may be obtainable. The sensitivity of the predicted orbit uncertainties to model errors for station locations, nongravitational platform accelerations, and Earth gravity is also presented.

Williams, B. G.↗

NASA NTRSDate not supplied

Planetary Surface Operations and Utilization: How ISS and Artemis Missions Can Be Used to Model Human Exploration of Mars

As NASA moves forward with plans to send astronauts to the Moon under Artemis missions and prepare for human exploration of Mars, the Agency is developing a set of high-level objectives for human spaceflight, identifying 50 points falling into four overarching categories of exploration. An element in NASA’s overall process of achieving these objectives is to leverage its assets and missions – such as the many crew increments sent to the International Space Station and future Artemis expeditions sent to the Moon – to develop more robust spaceflight systems and build a culture of interplanetary human exploration. This paper describes several examples of how NASA is exercising a process to achieve these objectives for future human Mars surface missions; both (a) building on lessons learned from ISS missions and maturing plans for Artemis missions, and (b) using human Mars mission planning to inform the plans for future ISS and Artemis missions so that the knowledge gained will reduce uncertainty and risk for Mars. One focal point for this two-way interaction between ISS and Artemis with future human Mars missions is a document titled “Reference Surface Activities for Crewed Mars Mission Systems and Utilization” (HEOMD-415), which describes the systems and operations of the crew thought necessary for the first human Mars surface mission. The details described in this paper will address three specific aspects of HEOMD-415 that have been influenced by ISS and where HEOMD-415 is influencing plans in ISS, Artemis, research and technology development, and other related aspects: (1) crew (activity planning and medical), (2) Mars surface infrastructure, and (3) communication and navigation support. The paper will close by describing near-term opportunities for tests and analogs relevant to these aspects of HEOMD-415.

Mars↗

NASA NTRSDate not supplied

PLANETARY SURFACE OPERATIONS AND UTILIZATION: HOW ISS AND ARTEMIS MISSIONS CAN BE USED TO MODEL HUMAN EXPLORATION OF MARS

Mars↗

DOE OSTI2020

Impact of climate change on adaptive management decisions in the face of water scarcity

Reoccurring drought through the early 2000s has caused a serious water scarcity issue in the Colorado River Basin. Previous modeling studies have focused on the impact of climate change without considering the adaptive behaviors of farmers and under-utilized Indian water rights. Here, we use a coupled agent-based water resource model (ABM) to investigate how the adaptive decisions of farmers can affect water resource management under both climate change impacts and fully utilized Indian water right conditions. We used five General Circulation Model projections with RCP8.5 scenarios for the study. The results of farm-level decision-making showed different responses in irrigated areas that were changing due to climate change impact. While winter precipitation changes might partially explain the behavior changes, no specific pattern could be concluded based on their location. Also, farmers’ responses about annual water diversion showed more significant inter-year variation compared to irrigated areas. Basin-level metrics showed that climate change impacts will generally worsen water scarcity issues as measured in Navajo Reservoir storage, flow to Lake Powell, and instream flow requirement. But these basin-level water scarcity metrics cannot reflect individual farm-level impacts under climate change, which is why modeling the bottom-up management actions is necessary. When the under-utilized Indian water rights are fully used, it is more likely to trigger the shortage sharing agreement due to the higher tribal water depletion. Evaluation of model uncertainty and a more realistic setup for adaptive actions under drought contingency plans are suggested for future research.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Machine-learning-assisted automation of single-crystal neutron diffraction

Neutron scattering is a powerful but expensive technique to study materials and discover new matter. Advanced detector technology has significantly improved the efficiency of neutron experiments, increasing the complexity of neutron data reduction and analysis. Machine learning (ML) brings new directions for neutron diffraction data reduction and experiment operation. Here, this work presents an ML-assisted data reduction and analysis method for precise recognition of Bragg peaks and the corresponding regions of interest; it can then automatically screen and align a measured crystal using the recognized peaks, and subsequently plan and optimize the data collection with user-provided information and uncertainty quantification values of detected peaks. This method shows robust performance in different complex sample environments and enables automated single-crystal neutron diffraction.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Bi-Level Adaptive Storage Expansion Strategy for Microgrids Using Deep Reinforcement Learning

Battery energy storage (BES) is a versatile resource for the secure and economic operation of microgrids (MGs). Prevailing stochastic optimization-based approaches for BES expansion planning for MGs are computationally complicated. This work proposes a data-driven bi-level multi-period BES expansion planning framework to determine the siting, sizing, and timing of BES installations. The proposed planning framework unifies deep reinforcement learning (DRL) and linear programming, thereby decoupling the determinations for the integer and continuous decision variables in two time scales, respectively. In the upper level, a rainbow DRL agent with quantile regression is trained to provide dynamic planning policies to accommodate stochastic renewable energy resources (RESs), load, and battery price changes efficiently. Further, the lower level computes the optimal operation of MGs with frequency constraints to hedge the islanding contingency. The two levels communicate with one another by exchanging storage configuration and operating expenses in order to accomplish the shared goal of minimizing investment and operation costs. Comparative case studies on an MG are carried out to demonstrate the superiority of the proposed DRL-based solution to the mixed-integer linear programming counterpart on efficiency, scalability, and adaptability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Quantification of 238U Holdup using Iterative, Point-Cloud-Based Compton Imaging

U holdup has impacts on several aspects of operation: Worker dose, Criticality safety, Safeguards, Outage planning. Generalized Geometry Holdup (GGH) currently estimates U mass within a high uncertainty band (± 50%). This method seeks to improve this uncertainty via quantitative Compton imaging.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

The K2 and TESS Synergy. I. Updated Ephemerides and Parameters for K2-114, K2-167, K2-237, and K2-261

Although the Transiting Exoplanet Survey Satellite (TESS) primary mission observed the northern and southern ecliptic hemispheres, generally avoiding the ecliptic, and the Kepler space telescope during the K2 mission could only observe near the ecliptic, many of the K2 fields extend far enough from the ecliptic plane that sections overlap with TESS fields. Using photometric observations from both K2 and TESS, combined with archival spectroscopic observations, we globally modeled four known planetary systems discovered by K2 that were observed in the first year of the primary TESS mission. Specifically, we provide updated ephemerides and system parameters for K2-114 b, K2-167 b, K2-237 b, and K2-261 b. These were some of the first K2 planets to be observed by TESS in the first year and include three Jovian sized planets and a sub-Neptune with orbital periods less than 12 days. In each case, the updated ephemeris significantly reduces the uncertainty in prediction of future times of transit, which is valuable for planning observations with the James Webb Space Telescope and other future facilities. The TESS extended mission is expected to observe about half of the K2 fields, providing the opportunity to perform this type of analysis on a larger number of systems.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Community-Informed Urban Flood Modeling for Impact Mitigation

The intensification of the hydrologic cycle due to climate change poses a threat to aging and under-designed water infrastructure systems which cannot adequately manage intense storm events. Developing a comprehensive plan for managing rain-driven flooding events is challenging due to uncertainties in the magnitude and frequency of future storm events and conflicting stakeholder objectives. In the City of Baltimore, Maryland, stormwater infrastructure is struggling to keep up with rainfall-driven (pluvial) flooding events, which regularly damage housing and disrupt transportation for residents. In this study, a hybrid of community engagement, numerical modeling, and artificial intelligence techniques are employed to explore prospective urban flooding adaptations. Community engagement drives the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed. The model integrates complex surface and subsurface stormwater infrastructure data from the City, high-resolution spatial data, insights from local public works experts, and the lived experiences of City residents. This co-developed model simulates adaptations of interest to stakeholders in the city, including green and grey infrastructure and operational management strategies. Stormwater management scenarios focused on inlet cleaning and spatially concentrated green infrastructure are found to be the most effective in reducing flood depths in community priority locations. Together, these adaptations can reduce the duration of intersection inundation by more than twenty minutes, allowing for quicker emergency response and restoration of typical transportation systems. Future work will combine this community engaged flooding model with the Deep Uncertainties Pathways framework to explore tradeoffs between adaptations and develop dynamic adaptations which align with community objectives, enhance climate resilience in Baltimore, and can be adjusted in response to changing future conditions.

Ava, Spangler [Pennsylvania State University]↗

NASA NTRS2012

The Mars Science Laboratory (MSL) MMRTG In-Flight: A Power Update

The MSL Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) was fueled on October 28, 2008 by the Department Of Energy (DOE) in preparation for a late 2009 launch. Shortly after, the MSL launch was delayed approximately 2 years until 2011. The fueled MMRTG was placed in storage to await the new date for liftoff. Occasional measurements of the MMRTG's power output were taken and compared with power predictions that pre-dated fueling. An error in the predictive models was quickly recognized and remedied. The predictions, while improved, carried significant uncertainty. This uncertainty did not deter the launch of MSL, but did alter the planned mission on the surface of Mars. Once launched, the MSL spacecraft provided a hi-fidelity telemetry stream measuring the generator's electrical and thermal performance. These data were used to update the predictive models and a new prediction of the performance of the MMRTG on the surface of Mars was run just before Entry, Descent, and Landing (EDL) at Mars. The MSL MMRTG is working extremely well, providing power above predictions and operating within its flight allowable temperature limits. The generator was producing approximately 114 W at the beginning of the surface mission. This paper will elaborate on power modeling for the MSL MMRTG along with a review of some of the data recorded from the MSL cruise to Mars, EDL, and the early days of the surface mission.

thermoelectric generator↗

NASA NTRS2013

The Mars Science Laboratory (MSL) MMRTG In-Flight: A Power Update

The MSL Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) was fueled on October 28, 2008 by the Department Of Energy (DOE) in preparation for a late 2009 launch. Shortly after, the MSL launch was delayed approximately 2 years until 2011. The fueled MMRTG was placed in storage to await the new date for liftoff. Occasional measurements of the MMRTG's power output were taken and compared with power predictions that pre-dated fueling. An error in the predictive models was quickly recognized and remedied. The resultant predictions, while improved, carried significant uncertainty. This uncertainty did not deter the launch of MSL, but did alter the planned mission on the surface of Mars. Once launched, the MSL spacecraft provided a hi-fidelity telemetry stream measuring the generator's electrical and thermal performance. These data were used to update the predictive models and a new prediction of the performance of the MMRTG on the surface of Mars was run just before Entry, Descent, and Landing (EDL) at Mars. The MSL MMRTG is working extremely well, providing power above predictions and operating within its flight allowable temperature limits. The generator was producing approximately 114 W at the beginning of the surface mission. This paper will elaborate on power modeling for the MSL MMRTG along with a review of some of the data recorded from the MSL cruise to Mars, EDL, and the early days of the surface mission.

thermoelectric↗

NASA NTRS2015

Capabilities, Calibration, and Impact of the ISS-RAD Fast Neutron Detector

In the current NASA crew radiation health risk assessment framework, estimates for the neutron contributions to crew radiation exposure largely rely on simulated data with sizeable uncertainties due to the lack of experimental measurements inside the ISS. Integrated in the ISS-RAD instrument, the ISS-RAD Fast Neutron Detector (FND) will deploy to the ISS on one of the next cargo supply missions. Together with the ISS-RAD Charged Particle Detector, the FND will perform, for the first time, routine and precise direct neutron measurements inside the ISS between 0.5 and 80 MeV. The measurements will close the NASA Medical Operations Requirement to monitor neutrons inside the ISS and impact crew radiation health risk assessments by reducing uncertainties on the neutron contribution to crew exposure, enabling more efficient mission planning. The presentation will focus on the FND detection mechanism, calibration results and expectations about the FND's interaction with the mixed radiation field inside the ISS.

Leitgab, Martin↗

NASA NTRSDate not supplied

LAVA CFD Analysis of the Check Standard Model within the Langley Unitary Plan Wind Tunnel

This paper is part of an e ort to assess the current capability of Computational Fluid Dynamics (CFD) to accurately predict the experimental forces and base pressure on the Check Standard Model (CSM). The wind tunnel data for this model is gathered during annual monitoring of test-to-test repeatability for the Langley Unitary Plan Wind Tunnel (LUPWT). A blind database designed to help quantify the uncertainty of simulating LUPWT for the CSM repeatability tests was run using the Launch, Ascent and Vehicle Aerodynamics (LAVA) CFD code. The Reynolds-averaged Navier-Stokes equations were used for the predictions presented in the paper. Prior to running the database, best practices were established both for simulating and characterizing the ow of the high-speed legof the LUPWT where the test took place, as well the CSM when inserted within its test section.

ARMD↗

DOE OSTI2025

Long-Term Evaluation of Remedial Technology Performance in the Laboratory: Multi-year Experimental Test Plan

An understanding of the long-term effectiveness of remediation technologies is central to sustainable environmental cleanup. Long-term experiments are valuable for reducing uncertainty and predicting remediation outcomes at scales required for regulatory compliance. However, these types of tests can be costly and challenging to interpret. Therefore, contaminated sites often rely on short-term laboratory experiments that may not account for the potentially significant effects of gradual, time- dependent processes governing contaminant retention, release, and species transformation. For example, short-term lab experiments (from months to a year) conducted with sediments from the unsaturated and saturated zones at the Hanford Site play an important role in initial evaluations of remediation technologies but cannot capture the full extent of time-dependent reactions, leaving uncertainties in field-scale deployment. Here, long-term testing will be conducted on select technologies based on their performance in short-term testing. The overall objective is to directly address the challenges described above by generating and analyzing data on long-term (2–10 years) efficacy of selected remediation technologies, integrating this understanding into models, and providing critical input for remediation planning, monitoring, and 5-year review cycles for field-implemented remedies. Specific objectives include: 1. Evaluating long-term efficiency of promising remedies under site-specific conditions. 2. Generating robust parameters for modeling, reducing uncertainty in predictive simulations. 3. Advancing integrated monitoring by combining geochemical and geophysical observations. 4. Informing field-scale implementation by incrementally advancing technologies, identifying failure mechanisms early, and prioritizing robust, cost-effective remedies. Through systematic evaluation of technologies in laboratory-scale column experiments, integrated monitoring, and modeling support, this project is designed to bolster confidence in the long-term robustness of selected technologies. The ultimate outcome is the identification and deployment of more reliable, cost-effective remedies that safeguard human health and the environment while reducing the uncertainties that have historically hindered cleanup progress at Hanford Site. An experimental approach was developed and initiated for long-term testing potentially up to 10 years. The table below summarizes the experimental approach developed for testing select technologies and presented in this multi-year experimental test plan.

54 ENVIRONMENTAL SCIENCES↗