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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Mars2020 Entry, Descent, and Landing Instrumentation (MEDLI2): Science Objectives and Instrument Requirements

NASAs exploration and technology roadmaps call for capability advancements in Mars entry, descent, and landing (EDL) systems to enable increased landed mass, a higher landing precision, and a wider planetary access. It is also recognized that these ambitious EDL performance goals must be met while maintaining a low mission risk in order to pave the way for future human missions. As NASA is engaged in developing new EDL systems and technologies via testing at Earth, instrumentation of existing Mars missions is providing valuable engineering data for performance improvement, risk reduction, and an improved definition of entry loads and environment. The most notable recent example is the Mars Entry, Descent and Landing Instrument (MEDLI) suite hosted by Mars Science Laboratory for its entry in Aug 2012. The MEDLI suite provided a comprehensive dataset for Mars entry aerodynamics, aerothermodynamics and thermal protection system (TPS) performance. MEDLI data has since been used for unprecedented reconstruction of aerodynamic drag, vehicle attitude, in-situ atmospheric density, aerothermal heating, and transition to turbulence, in-depth TPS performance and TPS ablation. [1,2] In addition to validating predictive models, MEDLI data has demonstrated extra margin available in the MSL forebody TPS, which can potentially be used to reduce vehicle parasitic mass. The presentation will introduce a follow-on MEDLI instrumentation suite (called MEDLI2) that is being developed for Mars-2020 mission. MEDLI2 has an enhanced scope that includes backshell instrumentation, a wider forebody coverage, and instruments that specifically target supersonic aerodynamics. Similar to MEDLI, MEDLI2 uses thermal plugs with embedded thermocouples and ports through the TPS to measure surface pressure. MEDLI2, however, also includes heat flux sensors in the backshell and a low range pressure transducer to measure afterbody pressure.

Aerothermodynamics↗
NASA NTRS2008

Rescue Shuttle Flight Re-Entry: Controlling Astronaut Thermal Exposure

A rescue mission for the STS-125 Hubble Telescope Repair Mission requires reentry from space with 11 crew members aboard, exceeding past cabin thermal load experience and risking crew thermal stress potentially causing cognitive performance and physiological decrements. The space shuttle crew cabin air revitalization system (ARS) was designed to support a nominal crew complement of 4 to 7 crew and 10 persons in emergencies, all in a shirt-sleeve environment. Subsequent to the addition of full pressure suits with individual cooling units, the ARS cannot maintain a stable temperature in the crew cabin during reentry thermal loads. Bulk cabin thermal models, used for rescue mission planning and analysis of crew cabin air, were unable to accurately represent crew workstation values of air flow, carbon dioxide, and heat content for the middeck. Crew temperature models suggested significantly elevated core temperatures. Planning for an STS-400 potential rescue of seven stranded crew utilized computational fluid dynamics (CFD) models to demonstrate inhomogeneous cabin thermal properties and improve analysis compared to bulk models. In the absence of monitoring of crew temperature, heart rate, metabolic rate and incomplete engineering data on the performance of the integrated cooling garment/cooling unit (ICG/CU) at cabin temperatures above 75 degrees F, related systems & models were reevaluated and tests conducted with humans in the loop. Changes to the cabin ventilation, ICU placement, crew reentry suit-donning procedures, Orbiter Program wave-off policy and post-landing power down and crew extraction were adopted. A second CFD and core temperature model incorporated the proposed changes and confirmed satisfactory cabin temperature, improved air distribution, and estimated core temperatures within safe limits. CONCLUSIONS: These changes in equipment, in-flight and post-landing procedures, and policy were implemented for the STS-400 rescue shuttle & will be implemented in any future rescue flights from the International Space Station of stranded shuttle crews.

Gillis, David B.↗
NASA NTRS2011

Human Factors Analysis to Improve the Processing of Ares-1 Launch Vehicle

The Constellation Program (CxP) is composed of an array of vehicles used to go to the Moon and Mars. The Ares vehicle one of the components of CxP, goes through several stages of processing before it is launched at the Kennedy Space Center. In order to have efficient and effective ground processing inside and outside the vehicle, all of the ground processing activities should be analyzed. The analysis for this program was performed, by engineers, technicians, and human factors experts with spacecraft processing experience. The procedure used to gather data was accomplished by observing human activities within physical mockups. The paper will focus on the procedures, analysis and results from these observations.

Dippolito, Gregory M.↗
DOE OSTI2023

Efficient multi-scale representation of visual objects using a biologically plausible spike-latency code and winner-take-all inhibition

Deep neural networks have surpassed human performance in key visual challenges such as object recognition, but require a large amount of energy, computation, and memory. In contrast, spiking neural networks (SNNs) have the potential to improve both the efficiency and biological plausibility of object recognition systems. Here we present a SNN model that uses spike-latency coding and winner-take-all inhibition (WTA-I) to efficiently represent visual stimuli using multi-scale parallel processing. Mimicking neuronal response properties in early visual cortex, images were preprocessed with three different spatial frequency (SF) channels, before they were fed to a layer of spiking neurons whose synaptic weights were updated using spike-timing-dependent-plasticity. We investigate how the quality of the represented objects changes under different SF bands and WTA-I schemes. We demonstrate that a network of 200 spiking neurons tuned to three SFs can efficiently represent objects with as little as 15 spikes per neuron. Furthermore, studying how core object recognition may be implemented using biologically plausible learning rules in SNNs may not only further our understanding of the brain, but also lead to novel and efficient artificial vision systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Hierarchical semi-Markov models with duration-aware dynamics for activity sequences

Residential electricity demand at granular scales is driven by what people do and for how long. Accurately forecasting this demand for applications like microgrid management and demand response therefore requires generative models for activities that can produce realistic daily activity sequences, capturing both the timing and duration of human behavior. This paper develops a generative model of human activity sequences using nationally representative time-use diaries at a 10-min resolution. We use this model to quantify which demographic factors are most critical for improving predictive performance. We propose a hierarchical semi-Markov framework that addresses two key modeling challenges. First, a time-inhomogeneous Markov router learns the patterns of “which activity comes next.” Second, a semi-Markov hazard component explicitly models activity durations, capturing “how long” activities realistically last. To ensure statistical stability when data are sparse, the model pools information across related demographic groups and time blocks. The entire framework is trained and evaluated using survey design weights to ensure our findings are representative of the U.S. population. On a held-out test set, we demonstrate that explicitly modeling durations with the hazard component provides a substantial and statistically significant improvement over purely Markovian models. Furthermore, our analysis reveals a clear hierarchy of demographic factors: Sex, Day-Type, and Household Size provide the largest predictive gains, while Region and Season, though important for energy calculations, contribute little to predicting the activity sequence itself. The result is an interpretable and robust generator of synthetic activity traces, providing a high-fidelity foundation for downstream energy systems modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Microbes and Climate Change: a Research Prospectus for the Future

Climate change is the most serious challenge facing humanity. Microbes produce and consume three major greenhouse gases—carbon dioxide, methane, and nitrous oxide—and some microbes cause human, animal, and plant diseases that can be exacerbated by climate change. Hence, microbial research is needed to help ameliorate the warming trajectory and cascading effects resulting from heat, drought, and severe storms. We present a brief summary of what is known about microbial responses to climate change in three major ecosystems: terrestrial, ocean, and urban. We also offer suggestions for new research directions to reduce microbial greenhouse gases and mitigate the pathogenic impacts of microbes. These include performing more controlled studies on the climate impact on microbial processes, system interdependencies, and responses to human interventions, using microbes and their carbon and nitrogen transformations for useful stable products, improving microbial process data for climate models, and taking the One Health approach to study microbes and climate change.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Examining the Relationship between Self-Reported Workload and Resilient Performance in Airline Flight Crews

Workload has long been associated with human performance in aviation. High workload is typically viewed as a system design problem. The aim of this work was to find observable behaviors that guard cognitive resource margins; thus, improve handling of perturbations that arise. Twelve commercial airline flight crews participated in an experiment at NASA Langley Research Center. We explored workload data (NASA Task Load Index) self-reported after completing flight simulation scenarios to see how different individuals, using the same technologies, cope with challenging situations. A trained observer from the same airline as the study participants assessed performance. We differentiated a lower workload crew from a higher workload crew and analyzed their workload and performance. Results indicate that the workload may be a component of pilots’ resilient performance. Initial strategies that reduced workload were classified and these types of behaviors, if implemented correctly, might assist pilots in maintaining functional workload resource margins.

Michael Stewart↗
NASA NTRSDate not supplied

Examining the Relationship Between Workload and Resilient Performance in Airline Flight Crews

Workload has long been associated with human performance in aviation. High workload is typically viewed as a system design problem. The aim of this work was to find observable behaviors that guard cognitive resource margins; thus, improve handling of perturbations that arise. Twelve commercial airline flight crews participated in an experiment at NASA Langley Research Center. We explored workload data (NASA Task Load Index) self-reported after completing flight simulation scenarios to see how different individuals, using the same technologies, cope with challenging situations. A trained observer from the same airline as the study participants assessed performance. We differentiated a lower workload crew from a higher workload crew and analyzed their workload and performance. Results indicate that the workload may be a component of pilots’ resilient performance. Initial strategies that reduced workload were classified and these types of behaviors, if implemented correctly, might assist pilots in maintaining functional workload resource margins.

Michael Stewart↗
NASA NTRSDate not supplied

Artemis III and IV Crew Health and Performance System Model Development

To maintain Crew Health and Performance (CHP) during an Artemis mission, the NASA Human Research Program (HRP) and Exploration Medical Capabilities (ExMC) element recognize the challenge that many different vehicles, habitats, and operational groups must come together to develop and implement cross program capabilities. To address this challenge, the ExMC team created the prototype 2023 Artemis CHP System Model to analyze how human system requirements are implemented throughout an Artemis mission and help understand the effects of changing an individual vehicle or habitat requirement on a full mission. Since presenting this work at the 2024 HRP Investigators’ Workshop, ExMC has continued this effort, now called the Artemis III and IV CHP System Model, to better support its operational end users within the NASA Human Health and Performance Directorate (HHPD) workforce. In this presentation, we will recapitulate how visualizing requirements and their relationships using a Model-Based Systems Engineering approach (MBSE) serves to improve understanding of an Artemis mission’s CHP capabilities along with discussion on updates made to the model to increase accessibility for users within HHPD so that it may be used in the development of cross program CHP capabilities at NASA.

Crew Health and Performance↗
NASA NTRS2017

Flight Deck Surface Trajectory-Based Operations (STBO): A Four-Dimensional Trajectory (4DT) Simulation

Within human factors there is burgeoning interest in the Human-Autonomy Teaming (HAT) concept as away to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous automation as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as plays (Shively et al., 2017). It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations (Nourbakhsh et al., 2005), healthcare and medicine (Tsui Yanco, 2007), autonomous vehicles (Parasuraman, Barnes, Cosenzo, Mulgund, 2007), photography (Lachter, Brandt, Sadler, Shively, in press), and aviation (Shively et al., in press). The current paper presents one such effort to apply HAT. It details the design of a R-HAT Agent developed as part of a NASA Research Agreement awarded to Human-Autonomy Teaming Solutions Inc. (HATS Inc), and developed in collaboration with the Human-Autonomy Teaming Laboratory at NASA Ames Research Center. The role of this Agent is to mediate interaction between the automation and the human operator of an advanced ground dispatch station, with this mediation based upon previously mentioned core tenets for HAT and the many lessons learned from the HAT research literature. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO; Lachter, Brandt, Battiste, Matessa, Johnson, in press). Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by the Agent, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, the Agent determines what tasks need to be done and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. The R-HAT Agent has been designed to both support end users and research in RCO and HAT. Additionally, the Agent and its underlying architecture were developed with generalizability in mind as a modular piece of software applicable outside of RCO aviation in domains such as those mentioned above. This paper will also discuss future further development and testing of the R-HAT Agent.

Bakowski, Deborah L.↗
NASA NTRSDate not supplied

Precision Landing Navigation Performance of Human-Scale Lunar and Mars Landers

To meet the unique challenges of crewed Lunar and Mars precision landings, NASA’s Safe and Precise Landing Integrated Capabilities Evolution project has worked to advance autonomous spacecraft navigation by increasing the technology readiness level of key deorbit, entry, descent, and landing systems, including navigation sensors. Different sensors and their effects on overall system performance are evaluated using six-degree-of-freedom simulations with physics-based engineering models that capture the relevant vehicle systems and environmental effects. Building on an existing simulation framework, this work demonstrates how improved modeling fidelity enables rapid and detailed assessment of various navigation sensors on human-scale Lunar and Mars landing vehicles using NASA reference architectures.

navigation↗
DOE OSTI2023

Improv Dynamic Workflows

A workflow is a series of dependent computations which are executed to yield an experimental result, much like sheet music describes a musical performance. Dynamic workflows are like improvisational jazz, in which the musicians create unique, situation-driven, collaborative variations on themes. Dynamic workflows can potentially yield better results, save computation, and/or save human decision-making effort versus pre-specified or manual workflows, as they need not run the exhaustive set of studies which might be required in a pre-specified set, and they make their own experimental design decisions at run time. If you have an existing Maestro study where you would like to save computation and/or human time, Improv is for you. Improv provides core capabilities for creating a simple, hierarchical structure over Maestro studies, allowing you to connect ``experimental'' Maestro strudies with decision-making code to select parameters and run corresponding studies.

Goforth, John↗
NASA NTRS2005

An information maximization model of eye movements

We propose a sequential information maximization model as a general strategy for programming eye movements. The model reconstructs high-resolution visual information from a sequence of fixations, taking into account the fall-off in resolution from the fovea to the periphery. From this framework we get a simple rule for predicting fixation sequences: after each fixation, fixate next at the location that minimizes uncertainty (maximizes information) about the stimulus. By comparing our model performance to human eye movement data and to predictions from a saliency and random model, we demonstrate that our model is best at predicting fixation locations. Modeling additional biological constraints will improve the prediction of fixation sequences. Our results suggest that information maximization is a useful principle for programming eye movements.

NASA Discipline Neuroscience↗
NASA NTRS2011

The Heliogyro Reloaded

The heliogyro is a high-performance, spinning solar sail architecture that uses long - order of kilometers - reflective membrane strips to produce thrust from solar radiation pressure. The heliogyro s membrane blades spin about a central hub and are stiffened by centrifugal forces only, making the design exceedingly light weight. Blades are also stowed and deployed from rolls; eliminating deployment and packaging problems associated with handling extremely large, and delicate, membrane sheets used with most traditional square-rigged or spinning disk solar sail designs. The heliogyro solar sail concept was first advanced in the 1960s by MacNeal. A 15 km diameter version was later extensively studied in the 1970s by JPL for an ambitious Comet Halley rendezvous mission, but ultimately not selected due to the need for a risk-reduction flight demonstration. Demonstrating system-level feasibility of a large, spinning heliogyro solar sail on the ground is impossible; however, recent advances in microsatellite bus technologies, coupled with the successful flight demonstration of reflectance control technologies on the JAXA IKAROS solar sail, now make an affordable, small-scale heliogyro technology flight demonstration potentially feasible. In this paper, we will present an overview of the history of the heliogyro solar sail concept, with particular attention paid to the MIT 200-meter-diameter heliogyro study of 1989, followed by a description of our updated, low-cost, heliogyro flight demonstration concept. Our preliminary heliogyro concept (HELIOS) should be capable of demonstrating an order-of-magnitude characteristic acceleration performance improvement over existing solar sail demonstrators (HELIOS target: 0.5 to 1.0 mm/s2 at 1.0 AU); placing the heliogyro technology in the range required to enable a variety of science and human exploration relevant support missions.

Wilkie, William K.↗
NASA NTRS2011

Microlith-based Structured Sorbent for Carbon Dioxide, Humidity, and Trace Contaminant Control in Manned Space Habitats

To support continued manned space exploration, the development of atmosphere revitalization systems that are lightweight, compact, durable, and power efficient is a key challenge. The systems should be adaptable for use in a variety of habitats and should offer operational functionality to either expel removed constituents or capture them for closedloop recovery. As mission durations increase and exploration goals reach beyond low earth orbit, the need for regenerable adsorption processes for continuous removal of CO2 and trace contaminants from cabin air becomes critical. Precision Combustion, Inc. (PCI) and NASA Marshall (MSFC) have been developing an Engineered Structured Sorbents (ESS) approach based on PCI s patented Microlith technology to meet the requirements of future, extended human spaceflight explorations. This technology offers the inherent performance and safety attributes of zeolite and other sorbents with greater structural integrity, regenerability, and process control, thereby providing potential durability and efficiency improvements over current state-of-the-art systems. The major advantages of the ESS explored in this study are realized through the use of metal substrates to provide structural integrity (i.e., less partition of sorbents) and enhanced thermal control during the sorption process. The Microlith technology also offers a unique internal resistive heating capability that shows potential for short regeneration time and reduced power requirement compared to conventional systems. This paper presents the design, development, and performance results of the integrated adsorber modules for removing CO2, water vapor, and trace chemical contaminants. A related effort that utilizes the adsorber modules for sorption of toxic industrial chemicals is also discussed. Finally, the development of a 4-person two-leg ESS system for continuous CO2 removal is also presented.

Junaedi, Christian↗
NASA NTRSDate not supplied

Human Landing System Storable Propellant Architecture: Mission Design, Guidance, Navigation, and Control

In preparation of the NextSTEP-2 Appendix H awards, NASA’s Human Landing System (HLS) Program (HLSP) went through an abbreviated Design Analysis Cycle (DAC), or miniDAC, to characterize and quantify how a storable propellant design would affect and improve overall system performance of the Government reference design. As part of that miniDAC, HLSP ran multiple trade studies and assessments, including aspects of Mission Design, Flight Mechanics (FM), and Guidance, Navigation, and Control (GN\&C). The storable propellant designs were assessed through the baseline mission targeting the Near Rectilinear Halo Orbit (NRHO) and several alternate staging orbits. This paper focuses on the FM and GN\&C trades and assessments completed as part of the miniDAC as well as the GN\&C elements of the miniDAC Master Equipment List (MEL) developed for the storable propellant lander configurations.

A S Craig↗
NASA NTRS2016

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

airport surface traffic↗