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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

The Effects of Space Flight and Microgravity Exposure on Female Astronaut Health and Performance

Over the past half century, our understanding of the physiological effects of space exploration and microgravity exposure have improved immensely. Microgravity causes incredible changes to the human body that increase risk of injury upon return to Earth and lunar/planetary egress scenarios. This is due to deconditioning of the cardiovascular and skeletal muscle systems that reduce aerobic capacity and muscular strength. With upcoming exploration class missions, such as NASA’s Artemis lunar exploration program which aims to send the first female astronaut to the lunar surface by 2030, as well as a long-term goal of Martian exploration, maintaining astronaut health during extended-duration space flight is critical for achieving mission objectives. However, our understanding of these physiological implications due to microgravity are based primarily on flight studies of male astronauts and 1g bed rest analog study participants, with few investigations focusing specifically on females. Innate physiologic differences in endocrine signaling and reproductive function impact sex-dependent responses to various health conditions, treatments, and environmental factors in nearly every system in the body. Therefore, to assume comparable alterations in females in response to microgravity exposure may be inappropriate and consequentially, could lead to lasting impacts on female astronaut health and impact mission success. Moreover, differences in sex hormones may also influence the regulation of cardiovascular control during egress activity after space flight-induced deconditioning and blood volume loss (i.e., risk for orthostatic intolerance). Other potential physiological systems and factors related to musculoskeletal health and aerobic capacity that warrant investigation with respect to microgravity include endocrine/reproductive function, vascular control, bone mineral density/microarchitecture, and soft-tissue health. The purpose of this investigation is two-fold: 1) to summarize the data available from space flight and simulated bed rest analog exposures to begin addressing these gaps in knowledge regarding impacts to female astronaut health, and 2) to describe differences in demographic health characteristics, injury prevalence, and aerobic capacity and muscular strength in NASA female and male astronauts. Female astronauts make up 50% of Artemis-specific astronaut corps and the extent to which microgravity exposure impacts female cardiovascular and musculoskeletal health, and whether these alterations are consistent with their male counterparts, is inconclusive. With the growing inclusion of female astronauts in the NASA space program and the increased duration of missions beyond low Earth orbit, a greater understanding of the sex-specific adaptation to space travel will help determine the development of appropriate countermeasures for minimizing risk and maintaining health of all astronauts.

Female Astronaut

Smart Planning for Radioactive Source Transport Advanced Tools for Increased Safety and Efficiency

End-of-life (EOL) management of high-activity radioactive sources is made uniquely challenging by the inherent risks associated with storage and transportation of these sources, the complex logistics involved, and the strict requirements for regulatory compliance. Traditional methods lack comprehensive tools for accurate site assessments and precision planning for the transportation of radioactive sources. They also frequently fail to provide the adaptability required to consider diverse operational environments, resulting in inefficiencies and potential safety concerns. This paper introduces a novel software solution developed to address these issues by integrating advanced technologies such as light detection and ranging (LiDAR)-based 3D environment modeling, smart dynamic route planning, and customizable measurement functionalities. This software enables detailed terrain visualizations, facilitating thorough environmental assessments and enabling users to virtually navigate, analyze, and plan site-specific operations. Among the key features are a user-centric interface for virtual navigation, precise site measurement tools for site evaluations, interactive visualizations that highlight potential operational hazards, dynamic route planning capabilities, and real-time collision detection to promote safe workflows. By demonstrating the effectiveness of this tool through real-world application, the present work underscores the tool’s potential to revolutionize radioactive source EOL management by improving operational efficiencies, minimizing risk, and advancing the state of practice to achieve suitable and secure radioactive material handling.

99 - GENERAL AND MISCELLANEOUS

SafeMAP: Safe Multi-Agent Planning Framework Based on Dynamic Probabilistic Risk Assessment

This paper proposes a risk-aware framework for Safe Multi-Agent Planning (SafeMAP) that unifies disparate models for multi-agent systems in a Markovian process that allows for simultaneous system health monitoring, decision making under uncertainty, and multi-agent system collaboration. As operations beyond low earth orbit mature, there is an increased need for autonomous cyber-physical systems with onboard decision making capabilities. Multi-agent cyber-physical systems in particular offer the potential of increased efficiency, resiliency, and mission capabilities for future applications such as multi-rover terrain operations, distributed satellite operations, and management of smart lunar habitats. SafeMAP utilizes physics-based models of each agent and the relevant components, probability models of the environment and component operational states, and reward models for mission-specific objectives such as scientific task completion or resource consumption. The output of SafeMAP is a set of mission plans that satisfy the mission objective under specified risk/reward constraints. A readable interpretation of each of these generated mission plans is provided as an additional output. SafeMAP has been demonstrated on a simulated case study involving a four-rover system performing surface mapping operations and science tasks. Results of this paper demonstrate SafeMAP’s ability to generate explainable mission plans that satisfy the mission objective while minimizing risk under nominal and off-nominal conditions.

Mohammad Hejase

SafeMAP: Safe Multi-Agent Planning framework based on Dynamic Probabilistic Risk Assessment

This paper proposes a risk-aware framework for Safe Multi-Agent Planning (SafeMAP) that unifies disparate models for multi-agent systems in a Markovian process that allows for simultaneous system health monitoring, decision making under uncertainty, and multi-agent system collaboration. As operations beyond low earth orbit mature, there is an increased need for autonomous cyber-physical systems with onboard decision making capabilities. Multi-agent cyber-physical systems in particular offer the potential of increased efficiency, resiliency, and mission capabilities for future applications such as multi-rover terrain operations, distributed satellite operations, and management of smart lunar habitats. SafeMAP utilizes physics-based models of each agent and the relevant components, probability models of the environment and component operational states, and reward models for mission-specific objectives such as scientific task completion or resource consumption. The output of SafeMAP is a set of mission plans that satisfy the mission objective under specified risk/reward constraints. A readable interpretation of each of these generated mission plans is provided as an additional output. SafeMAP has been demonstrated on a simulated case study involving a four-rover system performing surface mapping operations and science tasks. Results of this paper demonstrate SafeMAP’s ability to generate explainable mission plans that satisfy the mission objective while minimizing risk under nominal and off-nominal conditions.

Mohammad Hejase

Three‐trophic level food webs support the safety of a biocontrol agent 3 years after release

Biological control (biocontrol) is a powerful tool for managing invasive alien species and assisting the restoration of native ecosystems. Rigorous post‐release monitoring of biocontrol agents is critical to evaluate the success of biocontrol programs; however, this is still rarely implemented. Here, we combined the use of species interaction networks with a Before‐After Control‐Impact design to evaluate the target and non‐target, direct and indirect effects of the Australian gall wasp Trichilogaster acaciaelongifoliae , released to control the invasive plant Acacia longifolia in Portugal. We compared the structure of plant‐galling insect‐parasitoid food webs before and 3 years after the release of the biocontrol agent. Exhaustive sampling did not detect any non‐target effects, either direct (on non‐target plants) or indirect (on other galling insects via shared plants). Additionally, no significant changes were detected in network structure that could be related to the establishment of the biocontrol agent. This study shows that monitoring biocontrol at the community level is possible and that, when carefully planned, biocontrol poses minimal risk of non‐target effects.

López‐Núñez, Francisco A. [Centre for Functional E

Determining the oxidation stability of SnSe under atmospheric exposure

Abstract Understanding surface stability becomes critical as 2D materials like SnSe are developed for piezoelectric and optical applications. SnSe thin films deposited by molecular beam epitaxy showed no structural changes after a two-year exposure to atmosphere, as confirmed by X-ray diffraction and Raman spectroscopy. X-ray photoelectron spectroscopy and reflectivity show a stable 3.5 nm surface oxide layer, indicating a self-arresting oxidative process. Resistivity measurements show an electrical response dominated by SnSe post-exposure. This work shows that SnSe films can be used in ambient conditions with minimal risk of long-term degradation, which is critical for the development of piezoelectric or photovoltaic devices. Graphical Abstract

Chin, Jonathan R. (ORCID:0000000273205678)

Fracture Network Prediction Using Physics-based Machine Learning Algorithms

In recent years, systematic CO2 injection into geological reservoirs across the U.S. has gained traction as a strategy to mitigate greenhouse gas emissions. This approach necessitates precise monitoring to ensure secure containment, minimize risks, and optimize storage management. Our study leverages machine learning (ML) techniques to advance the understanding of CO2 injection processes, focusing on the Illinois Basin. Over a three-year injection period, we analyzed microseismic data, identifying 19 temporal intervals with significant bottom-hole pressure changes. By partitioning microseismic events into these intervals and estimating b-values, we revealed over 100 clusters of events related to fracture initiation or reactivation. Advanced spatial analysis highlighted horizontally-oriented fractures along the NNW-SSE axis. This quantification of fracture networks informs dynamic injection scheduling, work-over strategies, and risk assessments, enhancing carbon capture, utilization, and storage (CCUS) operations. Additionally, our methodology offers valuable insights for oil and gas operations and geothermal development, supporting fracture-based monitoring and risk mitigation.

Kumar, Abhash

Cyber-Physical System: Design for Sustainability and Resilience

When considering the design tools needed in the transition from numeric models to pilot plant, cyber-physical systems (CPS) come to the forefront as a method to model complex integrated energy systems. CPS approach has proven to be valuable to identify opportunities for economically viable early adoption of integrated energy technologies. This tutorial will introduce the concepts and the roles of CPS in co-design to minimize risks for pilot plant and technology deployment. This tutorial will also layout basic requirements for the CPS development, which requires a highly interdisciplinary effort with expertise in sensors, hardware testing, real-time modeling, controls, and system integration.

Harun, Nor Farida

FracML: A Machine Learning Based Tool to Quantify Reservoir Scale Fracture Network for CO2 Storage

Poster on “FRACML: A Machine Learning Based Tool to Quantify Reservoir Scale Fracture Network for CO2 Storage” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. The accurate characterization of subsurface fracture networks is essential for the secure operation of carbon capture, utilization, and storage (CCUS) projects. A thorough understanding of the spatial distribution of subsurface faults and fractures is crucial for predicting CO2 plume evolution and minimizing risks such as potential leakage into overlying formations or induced seismicity. In this context, robust fracture network quantification plays a pivotal role in reservoir management, providing the data necessary to fine-tune operational parameters, and ensure the environmental and economic viability of CCUS projects. As part of the U.S. Department of Energy’s SMART (Science-informed Machine Learning for Accelerating Real-time Decisions in Subsurface Applications) initiative, we focused on the development and application of a machine learning-based tool (FRACML) designed to quantify and map fracture networks using real-world (non-synthetic) data from an active CO2 injection site. Our objective is to demonstrate the utility of this tool in improving operational efficiency and safety across CCUS sites.

artifical intelligence / machine learning (AI/ML)

RCBC Automatic Monitoring and Control Recommendations

The recompression closed Brayton cycle (RCBC) test rig at the Sandia Brayton Laboratory provides a development platform to accelerate the commercialization of key technologies for supercritical CO 2 (sCO 2 ) closed loop Brayton cycles. The test rig enables testing to gain experience and confidence with new technologies, equipment, and processes, and automating monitors and controls will enhance Sandia’s ability to perform the types and amounts of testing needed. This report identifies candidates for automatic monitoring and control to ensure the loop remains within design limits and minimize risk to equipment due to off-normal events or conditions.

42 ENGINEERING

A Novel Optical Instrument for On-Line Measurement of Particle Size Distribution—Application to Clean Coal Technologies

A flow cell is a critical measurement interface for many optical instruments. However, the flows are often sampled under harsh conditions, such as under high pressure and/or high temperature, in the presence of particles, moisture, vapors with high dew points or corrosive gases. Therefore, obtaining a high-optical-quality flow cell that does not perturb the measurement is a significant challenge. To address this challenge, we proposed a new flow cell that employs a unique laminar coaxial flow field (for the purge and sample flows). A test system was built to conduct particle size distribution (PSD) measurements with no sampling bias using a state-of-the-art analyzer (Malvern Panalytical Insitec). The results revealed that the measurement zone is well defined solely by the sample flow, and the optical windows are well protected by the purge flow, with minimal risk of any depositions from the sample flow. Using this flow cell, the Insitec can successfully measure PSD under high pressure and temperature under moist, corrosive conditions without generating any sampling bias. Importantly, we successfully applied this flow cell for on-line PSD measurement for the flue gas of a 100 kWth pressurized oxy-coal combustor operating at 15 bara.

Cheng, Mao (ORCID:0000000213273900)

Uptake, Efflux, and Sequestration of Mercury in the Asian Clam, Corbicula fluminea , at Environmentally Relevant Concentrations, and the Implications for Mercury Remediation

(1) Mercury (Hg) is a persistent, ubiquitous contaminant that readily biomagnifies into higher trophic level species in aquatic environments across the globe. It is crucial to understand the movement of environmentally relevant concentrations of Hg in impacted freshwater streams to minimize risks to ecological and human health. (2) The bioconcentration kinetics of aqueous Hg exposure (20, 100, and 200 ng/L) in the invasive Asian Clam, Corbicula fluminea, were measured. A toxicokinetic model, the first parameterized for Hg accumulation in freshwater clams, was developed to estimate uptake and efflux parameters and compared to previous parameter values estimated for other mollusk species. (3) Results demonstrated that even at low Hg concentrations, Corbicula record signals of contamination through bioconcentration, and both direct measurement and toxicokinetic models demonstrate large Hg bioconcentration factors (as high as 1.34 × 10 5 mL/g dry tissue), similar to partitioning coefficients seen in engineered Hg sorbents. (4) Our study found that Corbicula accumulated Hg at aqueous concentrations relevant to impacted streams, but well below regulatory drinking water limits, demonstrating their utility as a sensitive sentinel species and potential bioremediator.

bioaccumulation

Deep nonparametric estimation of operators between infinite dimensional spaces

Learning operators between infinitely dimensional spaces is an important learning task arising in machine learning, imaging science, mathematical modeling and simulations, etc. This paper studies the nonparametric estimation of Lipschitz operators using deep neural networks. Non-asymptotic upper bounds are derived for the generalization error of the empirical risk minimizer over a properly chosen network class. Under the assumption that the target operator exhibits a low dimensional structure, our error bounds decay as the training sample size increases, with an attractive fast rate depending on the intrinsic dimension in our estimation. Our assumptions cover most scenarios in real applications and our results give rise to fast rates by exploiting low dimensional structures of data in operator estimation. We also investigate the influence of network structures (e.g., network width, depth, and sparsity) on the generalization error of the neural network estimator and propose a general suggestion on the choice of network structures to maximize the learning efficiency quantitatively.

97 MATHEMATICS AND COMPUTING

Spacecraft electric propulsion - Now?

JPL Solar Electric 1975 Jupiter Flyby program designed to minimize risks of introducing prime solar electric propulsion into spacecraft

Barber, T. A.

Estimation of incomplete multinomial data

Program estimates cell probabilities for data observed to fall in one of two or more categories when exact category cannot be determined. Data are assumed to be randomly incomplete. Estimation minimizes risk of quadratic loss. Program should be useful in projects where multinomial data is analyzed, but where observations are sometimes incomplete. Program is in FORTRAN IV and Assembler for batch execution on CYBER 173.

Credeur, K. R.

System safety in Stirling engine development

The DOE/NASA Stirling Engine Project Office has required that contractors make safety considerations an integral part of all phases of the Stirling engine development program. As an integral part of each engine design subtask, analyses are evolved to determine possible modes of failure. The accepted system safety analysis techniques (Fault Tree, FMEA, Hazards Analysis, etc.) are applied in various degrees of extent at the system, subsystem and component levels. The primary objectives are to identify critical failure areas, to enable removal of susceptibility to such failures or their effects from the system and to minimize risk.

Bankaitis, H.

The 30/20 GHz flight experiment system, phase 2. Volume 4: Experiment system development plan

The development plan for the 30/20 GHz flight experiment system is presented. A master program schedule with detailed development plans for each subsystem is planned with careful attention given to how technology items to ensure a minimal risk. The work breakdown structure shows the organization of the program management with detailed task definitions. The ROM costs based on the development plan are also given.

Bronstein, L.

Tool Releases Optical Elements From Spring Brackets

Threaded hooks retract bracket arms holding element. Tool uses three hooks with threaded shanks mounted in ring-shaped holder to pull on tabs to release optical element. One person can easily insert or remove optical element (such as prism or lens) from spring holder or bracket with minimal risk of damage.

Gum, J. S.