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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Science Goal Driven Observing: A Step Towards Maximizing Science Returns and Spacecraft Autonomy

In the coming decade, the drive to increase the scientific returns on capital investment and to reduce costs will force automation to be implemented in many of the scientific tasks that have traditionally been manually overseen. Thus, spacecraft autonomy will become an even greater part of mission operations. While recent missions have made great strides in the ability to autonomously monitor and react to changing health and physical status of spacecraft, little progress has been made in responding quickly to science driven events. The new generation of space-based telescopes/observatories will see deeper, with greater clarity, and they will generate data at an unprecedented rate. Yet, while onboard data processing and storage capability will increase rapidly, bandwidth for downloading data will not increase as fast and can become a significant bottleneck and cost of a science program. For observations of inherently variable targets and targets of opportunity, the ability to recognize early if an observation will not meet the science goals of variability or minimum brightness, and react accordingly, can have a major positive impact on the overall scientific returns of an observatory and on its operational costs. If the observatory can reprioritize the schedule to focus on alternate targets, discard uninteresting observations prior to downloading, or download them at a reduced resolution its overall efficiency will be dramatically increased. We are investigating and developing tools for a science goal monitoring (SGM) system. The SGM will have an interface to help capture higher-level science goals from scientists and translate them into a flexible observing strategy that SGM can execute and monitor. SGM will then monitor the incoming data stream and interface with data processing systems to recognize significant events. When an event occurs, the system will use the science goals given it to reprioritize observations, and react appropriately and/or communicate with ground systems - both human and machine - for confirmation and/or further high priority analyses.

Koratkar, Anuradha↗
NASA NTRS2007

Fundamentals of Aerospace Medicine: Cosmic Radiation

Cosmic rays were discovered in 1911 by the Austrian physicist, Victor Hess. The planet earth is continuously bathed in high-energy galactic cosmic ionizing radiation (GCR), emanating from outside the solar system, and sporadically exposed to bursts of energetic particles from the sun referred to as solar particle events (SPEs). The main source of GCR is believed to be supernovae (exploding stars), while occasionally a disturbance in the sun's atmosphere (solar flare or coronal mass ejection) leads to a surge of radiation particles with sufficient energy to penetrate the earth's magnetic field and enter the atmosphere. The inhabitants of planet earth gain protection from the effects of cosmic radiation from the earth s magnetic field and the atmosphere, as well as from the sun's magnetic field and solar wind. These protective effects extend to the occupants of aircraft flying within the earth s atmosphere, although the effects can be complex for aircraft flying at high altitudes and high latitudes. Travellers in space do not have the benefit of this protection and are exposed to an ionizing radiation field very different in magnitude and quality from the exposure of individuals flying in commercial airliners. The higher amounts and distinct types of radiation qualities in space lead to a large need for understanding the biological effects of space radiation. It is recognized that although there are many overlaps between the aviation and the space environments, there are large differences in radiation dosimetry, risks and protection for airline crew members, passengers and astronauts. These differences impact the application of radiation protection principles of risk justification, limitation, and the principle of as low as reasonably achievable (ALARA). This chapter accordingly is divided into three major sections, the first dealing with the basic physics and health risks, the second with the commercial airline experience, and the third with the aspects of cosmic radiation appertaining to space travel including future considerations.

Bagshaw, Michael↗
NASA NTRS2014

Prognostic Analysis System and Methods of Operation

A prognostic analysis system and methods of operating the system are provided. In particular, a prognostic analysis system for the analysis of physical system health applicable to mechanical, electrical, chemical and optical systems and methods of operating the system are described herein.

MacKey, Ryan M. E.↗
NASA NTRS2016

Radiation Safety Program

This student intern poster demonstrates the knowledge learned during the summer 2016 AFRC STEM program. The individual detailed abstracts will be included in the summer 2016 abstract book.

radiation exposure↗
NASA NTRSDate not supplied

Preliminary Considerations for Microwave Consolidation/Sintering of Lunar Regolith Simulant

As NASA prepares to establish permanent habitats on the Moon, a significant first step is to be able to land multiple times in the same area. As was consistently shown during the Apollo program, the very fine granular structure of the lunar regolith (the Moon’s “soil”)poses significant physical and health challenges [1]. One of the most concerning is the hyper-velocity lunar surface ejecta that results from the engine exhaust that exits the rocket as it lands and takes off [2]. It has been determined that to mitigate this, the regolith must be consolidated.

microwave↗
DOE OSTI2025

Reactors Section Presentation - INL, HPS Society 2025

The ongoing Nuclear Renaissance includes many next generation reactor designs and testing, this means translates to increased demand for Health Physicists. These opportunities are not limited to just reactors but the entire fuel cycle from mining and extraction from existing tailings, R&D support efforts at new start-up companies, to shielding modeling and design, to Recycling and Reprocessing, and eventually Decommissioning.

Health Physics↗
NASA NTRSDate not supplied

Determining the Importance of In-Flight Treadmill Running Capabilities for Maintaining Astronaut Health and Performance

BACKGROUND: Physical deconditioning induced via spaceflight is most effectively attenuated through in-flight exercise training. Throughout its evolution, NASA has implemented advancements to in-flight exercise countermeasures, culminating in the triad of devices currently used aboard the International Space Station (ISS): a treadmill (T2), cycle ergometer (CEVIS), and resistance exercise device (ARED). Despite high-quality exercise devices and prescriptions, many crewmembers experience reductions in both aerobic capacity (VO2peak pre-post mean change: -10%) and strength (knee isokinetic pre-post mean change: -15%). As NASA moves towards exploration missions, which will impose greater size, power, and time constraints on exercise systems in addition to physically demanding surface extravehicular activities (EVAs), providing robust capabilities to protect crew health and performance should be prioritized. OVERVIEW: Future missions to the Lunar and Martian surfaces will include EVAs requiring ambulation and greater physical exertion than those in Apollo missions. While the exercise device concepts planned for exploration missions include resistive and aerobic capabilities, they do not allow for ambulation. Specifically, the countermeasure planned for Artemis Lunar transit is a flywheel device, which provides both exercise modalities through a single resistive cable. While more robust than the flywheel, the devices planned for the Lunar orbital space station, and subsequent Mars habitats, will provide distinct aerobic and resistance modalities capable of achieving high intensities. However, these modalities do not include a treadmill. Recent research suggests that greater in-flight running intensity and volume attenuate decrements in aerobic capacity and strength; however, this has not been experimentally confirmed. The Exploration Exercise Treadmill Requirements study is currently underway, aiming to determine the effects of exercising without a treadmill on aerobic capacity, strength, bone density, and sensorimotor function during long-duration spaceflight. DISCUSSION: Providing running capabilities on future exploration missions may help to maintain astronaut physical ability, reduce injury, and promote health. Studies quantifying the effects of using exploration exercise devices are in progress, which will help provide critical recommendations on whether a treadmill is a necessary component of the in-flight training regime. This presentation will discuss the capabilities of exploration exercise devices and the potential implications of not having running capabilities during long-duration spaceflight.

Alyssa N Varanoske↗
NASA NTRSDate not supplied

Spaceflight Food System Impacts to Nutritional Adequacy, Health, Performance, and Resources in Space Exploration

Despite high physical standards and training protocols, physiological and behavioral decrements have been documented in astronauts on both short (1-2 weeks) and long (6+ month) missions in spaceflight, including dysregulation of the immune system, cardiovascular and musculoskeletal deconditioning, ophthalmic changes, weight loss, and increased stress and fatigue. Optimizing food and nutrition intakes are key underpinnings for the proper function and performance of all physiological systems and the resulting physical and behavioral health and performance outcomes of astronauts. Much has been learned about the role of nutrition in human health on Earth over the past hundred years, from the identity and role of specific vitamins to the importance of the quantities of some nutrients to immune function. The requirements for providing adequate nutrition to astronauts seem obvious. However, providing a safe, reliable, and nutritious food system for space exploration missions remains a challenge. In fact, food is one of the greatest resource and logistical challenges, which is part of why it remains a “red” risk for Mars missions.

Grace L Douglas↗
NASA NTRSDate not supplied

Physics Informed Neural Nets for Systems Health Management

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Development in data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. The research work presents application of physics-informed neural nets application to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived and empirical equations, integrated with connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage.

Physics Informed↗
NASA NTRS1972

The use of remote sensors to relate biological and physical indicators to environmental and public health problems

Relationships between biological, ecological and botanical structures, and disease organisms and their vectors which might be detected and measured by remote sensing are determined. In addition to the use of trees as indicators of disease or potential disease, an attempt is made to identify environmental factors such as soil moisture and soil and water temperatures as they relate to disease or health problems and may be detected by remote sensing. The following three diseases and one major health problem are examined: Malaria, Rocky Mountain spotted fever, Encephalitis and Red Tide. It is shown that no single species of vascular plant nor any one environmental factor can be used as the indicator of disease or health problems. Entire vegetation types, successional stages and combinations of factors must be used.

Source record↗
NASA NTRS2019

Utilizing Satellite Based Observations and Physical Hydrological Modeling for Freshwater Ecosystem Health in the Lower Mekong River Basin

Freshwater availability is necessary to promote economic growth through agriculture, fisheries, transport, environmental health, and social equity.The National Aeronautics and Space Administration (NASA) and the Conservation International (CI) are partnering to use remote sensing Earth observations to improve regional efforts that assess natural resources for conservation and sustainable management. (Vollmer et al.,2018) have presented the social-ecological framework named the Freshwater Health Index (FHI), which takes account of the interplay between governance, stakeholders, freshwater ecosystems and the ecosystem services they provide.In this work, we develop decision support and making tools for natural resources conservation in the Lower Mekong by leveraging the FHI framework, multiple data products, and hydrological modeling capabilities (Mohammed et al., 2018). Modeling capabilities enable the integration of satellite-based daily gridded precipitation, air temperature, digital elevation model, soil characteristics, and land cover and land use information to simulate water flux framework.

Mohammed, Ibrahim N.↗
NASA NTRSDate not supplied

Investigating the Relationship between the Cell Wall Integrity Pathway and Unfolded Protein Response

Plants have made significant contributions to astronaut health in spaceflight missions. To further spaceflight research in optimizing plant viability, this study aims to understand the factors involved in maintaining cell wall integrity, which is vital to plant morphology and structural stability. Spaceflight can negatively impact the cell wall; thus, it is crucial to investigate how to mitigate spaceflight stressors to maintain the integrity of the cell wall. The structural integrity of plants’ cell walls depends on secondary cell wall biogenesis, which enables the repair and architectural support of plants like A. thaliana. This biogenesis is triggered by a signal transduction cascade: first initiated by cell wall stress, the CWI (cell wall integrity) pathway is activated, followed by the UPR (unfolded protein response), then the cell wall’s integrity is maintained through secondary cell wall biogenesis. Through a re-analysis of GeneLab Dataset 321 (GLDS-321), a study from NASA’s Open Science Data Repository that investigates the effects of spaceflight on the UPR, several genes were found to be associated with the cell wall. This proposal postulates a relationship between the UPR and the CWI pathway and their direct effect on secondary cell wall biogenesis by investigating IRX7, a gene associated with secondary cell wall biogenesis. The predicted outcome of overexpressing IRX7 is increased resilience of the cell wall by upregulating both the UPR and the CWI pathway, while silencing IRX7 is predicted to compromise the cell wall integrity by downregulating the UPR and the CWI pathway. This study will give insight into the needed measures to increase cell wall resilience in stressful environments: As spaceflight durations increase and uncertain climate change events progress on Earth, understanding how to optimize cell wall resilience – a fundamental pillar of plant health – can effectively enhance mass crop production and quality and ensure the physical and psychological health of astronauts in long-term space missions.

GL4HS↗
NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗
DOE OSTI2025

Efficient and assured reinforcement learning-based building HVAC control with heterogeneous expert-guided training

Abstract Building heating, ventilation, and air conditioning (HVAC) systems account for nearly half of building energy consumption and $$20\%$$ of total energy consumption in the US. Their operation is also crucial for ensuring the physical and mental health of building occupants. Compared with traditional model-based HVAC control methods, the recent model-free deep reinforcement learning (DRL) based methods have shown good performance while do not require the development of detailed and costly physical models. However, these model-free DRL approaches often suffer from long training time to reach a good performance, which is a major obstacle for their practical deployment. In this work, we present a systematic approach to accelerate online reinforcement learning for HVAC control by taking full advantage of the knowledge from domain experts in various forms . Specifically, the algorithm stages include learning expert functions from existing abstract physical models and from historical data via offline reinforcement learning, integrating the expert functions with rule-based guidelines, conducting training guided by the integrated expert function and performing policy initialization from distilled expert function. Moreover, to ensure that the learned DRL-based HVAC controller can effectively keep room temperature within the comfortable range for occupants, we design a runtime shielding framework to reduce the temperature violation rate and incorporate the learned controller into it. Experimental results demonstrate up to 8.8 X speedup in DRL training from our approach over previous methods, with low temperature violation rate.

Xu, Shichao↗
NASA NTRSDate not supplied

Enabling in-time Prognostics with Surrogate Modeling through Physics-enhanced Dynamic Mode Decomposition Method

Computational models provide essential quantitative tools for assessing and predicting the health and performance of physical systems. However, high-fidelity models are rarely used in real-time operations or large optimization loops, due to their time-intensive nature. A common approach to improving computational efficiency of prognosis is to employ surrogate models. Such models can significantly decrease computation time for some accuracy loss. In this context, use of Dynamic Mode Decomposition (DMD) is proposed to generate surrogate models for lithium-ion (Li-ion) battery discharge. DMD has been suggested and used successfully in the area of fluid dynamics for over a decade, but it has not been applied to the PHM domain, where far-ahead prediction of nonlinear behavior is crucial to propagate faults or predict Remaining Useful Life (RUL). For Li-ion battery health management, the standard application of DMD using only the observable quantities of interest was unable to capture the nonlinear discharge of batteries exhibited in lab testing. The Koopman theory, however, provides a mechanism to tradeoff low dimensional nonlinear models with high-dimensional linear ones in a DMD framework, by augmenting nonlinear state variables into the system representation. In this way, DMD allows for configurable simulation accuracy dependent on the dimensionality of the Koopman operator. For battery health management, we augmented the observable variables with the hidden states of a higher-fidelity physics model to build the DMD surrogate. In comparison to a high-fidelity model, the surrogate improved computational efficiency with only a minimal loss of accuracy, and enabled long-term prognostics horizons. A generalized method for this was implemented in the prog models python package.

prognostics and health management↗
NASA NTRS1988

A multiprocessing architecture for real-time monitoring

A multitasking architecture for performing real-time monitoring and analysis using knowledge-based problem solving techniques is described. To handle asynchronous inputs and perform in real time, the system consists of three or more distributed processes which run concurrently and communicate via a message passing scheme. The Data Management Process acquires, compresses, and routes the incoming sensor data to other processes. The Inference Process consists of a high performance inference engine that performs a real-time analysis on the state and health of the physical system. The I/O Process receives sensor data from the Data Management Process and status messages and recommendations from the Inference Process, updates its graphical displays in real time, and acts as the interface to the console operator. The distributed architecture has been interfaced to an actual spacecraft (NASA's Hubble Space Telescope) and is able to process the incoming telemetry in real-time (i.e., several hundred data changes per second). The system is being used in two locations for different purposes: (1) in Sunnyville, California at the Space Telescope Test Control Center it is used in the preflight testing of the vehicle; and (2) in Greenbelt, Maryland at NASA/Goddard it is being used on an experimental basis in flight operations for health and safety monitoring.

Schmidt, James L.↗
NASA NTRS2010

Human Health and Performance Considerations for Exploration of Near-Earth Asteroids

This presentation will describe the human health and performance issues that are anticipated for the human exploration of near-Earth asteroids (NEA). Humans are considered a system in the design of any such deep-space exploration mission, and exploration of NEA presents unique challenges for the human system. Key factors that define the mission are those that are strongly affected by distance and duration. The most critical of these is deep-space radiation exposure without even the temporary shielding of a nearby large planetary body. The current space radiation permissible exposure limits (PEL) restrict mission duration to 3-10 months depending on age and gender of crewmembers and stage of the solar cycle. Factors that affect mission architecture include medical capability; countermeasures for bone, muscle, and cardiovascular atrophy during continuous weightlessness; restricted food supplies; and limited habitable volume. The design of a habitat that can maintain the physical and psychological health of the crew and support mission operations with limited intervention from Earth will require an integrated research and development effort by NASA s Human Research Program, engineering, and human factors groups. Limited abort and return options for an NEA mission are anticipated to have important effects on crew psychology as well as influence medical supplies and training requirements of the crew. Other important factors are those related to isolation, confinement, communication delays, autonomous operations, task design, small crew size, and even the unchanging view outside the windows for most of the mission. Geological properties of the NEA will influence design of sample handling and containment, and extravehicular activity capabilities including suit ports and tools. A robotic precursor mission that collects basic information on NEA surface properties would reduce uncertainty about these aspects of the mission as well as aid in design of mission architecture and exploration tasks.

Kundrot, Craig↗
NASA NTRSDate not supplied

Medical System Requirements Development for Lunar Operations

The major health hazards of spaceflight include higher levels of damaging radiation, altered gravity, extended periods of isolation and confinement, a closed and potentially hostile living environment, and the stress associated with being a long distance from Earth. As we increase the duration of lunar stays with foreseeable communication latencies and disruptions, there will be a progressive need for crew to maintain their own health and independently respond to critical medical events. The Exploration Medical Capability element of the NASA Human Research Program is developing a set of Medical System requirements for lunar transit and surface operations. These requirements specify the capabilities, processes and procedures of a habitat Medical System needed for a range of conditions known to occur during spaceflight. Requirement text is written so as not to constrain innovative design solutions necessary for a resilient system. The requirement set includes attributes and functions the Medical System imposes on eight additional habitat systems. A key property of the Medical System is the provision of medical knowledge that will be stored, updated, analyzed, and secured within a Habitat Data System. A Task Performance Support System will aid in medical data acquisition and interpretation, crew training, medical condition prevention, diagnosis and treatment, provide interactive procedures, and track medical inventory. A Wellness System will focus on the provision of countermeasures to prevent, mitigate or treat adverse physical and behavioral health effects while the Medical System recommends adjustments to these countermeasures to maintain crew health. An Environmental Monitoring System will share out-of-bounds readings of air and water quality, acoustics, and radiation exposure levels with the Medical System to help identify issues before they affect crew health and performance. A Communications System will provide secured and private consultations between crew and the ground medical team and their loved ones on Earth. The Medical System also imposes requirements on a Research & Testbed System, fostering advanced medical science such as human research. A Waste Management System provides biohazard waste containment and waste disposal options (recycle and reuse). An Extravehicular Activity System supports crew health during lunar surface activities. And finally, a Maintenance Support System ensures that medical equipment is performing as expected. These requirements are being specifically developed for lunar surface operations but could help to identify Medical System requirements for any space habitat (e.g., I-Hab, commercial endeavors, etc.).

technology↗