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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Synthesis Methodology for Intelligent Memory Interfaces in Accelerator Systems

Domain-specific systems improve the performance of a specific set of applications compared to general-purpose processing systems by deploying custom hardware accelerators. These hardware accelerators are generated using high-level synthesis (HLS) tools. The HLS tools enable a comprehensive design space exploration to optimize the compute performance of the generated accelerators. However, they often ignore the challenges of implementing the accelerators in a system-on-chip, particularly how the accelerators access memory. Our work introduces a buffering system design that improves accelerators' memory accesses by intelligently employing burst transactions to prefetch useful data from external memory to on-chip local buffers. Our design is dynamic, parametric, and transparent to the accelerators generated by HLS tools. We derive the buffering system parameters using appropriate compiler-based analysis passes and memory channel latency constraints. The proposed buffering system design results in, on average, 8.8x performance improvements while lowering memory channel utilization on average by 53.2% for a set of PolyBench kernels.

Limaye, Ankur M. (ORCID:0000000194062584)↗
NASA NTRS1999

Bone Blood Flow During Simulated Microgravity: Physiological and Molecular Mechanisms

Blood flow to bone has been shown to affect bone mass and presumably bone strength. Preliminary data indicate that blood flow to the rat femur decreases after 14 days of simulated microgravity, using hindlimb suspension (HLS). If adult rats subjected to HLS are given dobutamine, a synthetic catecholamine which can cause peripheral vasodilation and increased blood flow, the loss of cortical bone area usually observed is prevented. Further, mechanisms exist at the molecular level to link changes in bone blood flow to changes in bone cell activity, particularly for vasoactive agents like nitric oxide (NO). The decreases in fluid shear stress created by fluid flow associated with the shifts of plasma volume during microgravity may result in alterations in expression of vasoactive agents such as NO, producing important functional effects on bone cells. The primary aim of this project is to characterize changes in 1) bone blood flow, 2) indices of bone mass, geometry, and strength, and 3) changes in gene expression for modulators of nitric oxide activity (e.g., nitric oxide synthase) and other candidate genes involved in signal transduction of mechanical loading after 3, 7, 14, 21, and 28 days of HLS in the adult rat. Using a rat of at least 5 months of age avoids inadvertently studying effects of simulated microgravity on growing, rather than adult, bone. Utilizing the results of these studies, we will then define how altered blood flow contributes to changes in bone with simulated microgravity by administering a vasodilatory agent (which increases blood flow to tissues) during hindlimb suspension. In all studies, responses in the unloaded hindlimb bones (tibial shaft, femoral neck) will be compared with those in the weightbearing humeral shaft and the non-weightbearing calvarium (skull) from the same animal. Bone volumetric mineral density and geometry will be quantified by peripheral quantitative CT; structural and material properties of the long bones will be determined by 3-point bending (tibia, humerus) or compression (femoral neck) testing to failure. A unique aspect of these studies will be defining the time course of changes in gene expression in bone cell populations with unloading, accomplished with Northern blots, in situ hybridization, and immunohistochemistry. These studies have high relevance for concurrent protocols being proposed by investigators on NSBRI Cardiovascular and Muscle teams, with blood flow data available on a number of tissues other than bone. Further, dobutamine and other Beta-agonists have been tested as countermeasures for altered muscle and cardiovascular function. Results of the intervention tested in our studies have potential relevance for a number of systemic changes seen with prolonged spaceflight.

Bloomfield, Susan A.↗
NASA NTRS1996

Synergistic ablation does not affect atrophy or altered myosin heavy chain expression in the non-weight bearing soleus muscle

The purpose of this study was to investigate whether the soleus muscle undergoes atrophy and alterations in myosin heavy chain (MHC) composition during non-weight bearing in the absence of synergists. Thirty-two female rats were randomly assigned to four groups: control (C), synergistic ablation (ABL) of the gastrocnemius and plantaris muscles to overload the soleus muscle, hindlimb suspension (HLS), or a combination of synergistic ablation and hindlimb suspension (HLS-ABL). After 28 days of hindlimb suspension, soleus atrophy was more pronounced in HLS (58%) than in HLS-ABL (43%) rats. Compared to C rats, non-weight bearing decreased mixed and myofibrillar protein contents and Type I MHC 49%, 45%, and 7%, respectively, in HLS animals. In addition, de novo expression of fast Type IIx and Type IIb MHC (5% and 2%, respectively) was observed in HLS animals. Similarly, when compared to C rats, mixed and myofibrillar protein contents and Type I MHC decreased 43%, 46%, and 4%, respectively, in HLS-ABL animals. Also, de novo expression of Type IIx (4%) and IIb (1%) MHC was observed. Collectively, these data indicate that the loss of muscle protein and Type I MHC, and the de novo expression of Type IIx and Type IIb MHC in the rat soleus occur independently of the presence of synergists during non-weight bearing. Furthermore, these results confirm the contention that soleus mass and MHC expression are highly sensitive to alterations in mechanical load.

NASA Center ARC↗
NASA NTRSDate not supplied

2023 Artemis Crew Health and Performance System Model Development

While the NASA Human Research Program (HRP) utilizes a Crew Health and Performance (CHP) System to represent all the Agency’s efforts to ensure the health and performance of NASA astronauts, there is no shared mental model of a CHP system at NASA. Some groups may consider a CHP system to be only a medical kit, while others may not be using the concept at all. To facilitate the integration of functions and capabilities to ensure astronaut health and performance during vehicle development, HRP has proposed a CHP Shared Mental Model derived from the NASA Human Health, Medical, and Performance Spaceflight Standards (NASA-STD-3001 Vol.1/Vol.2). [1] Even though many vehicle, ground, and communication systems as well as mission operations are modeled for the Artemis Campaigns, no mission level CHP system model was created to achieve the intent of the HRP CHP Shared Mental Model. The lack of this model renders it difficult to visualize and understand how the many programs work together to provide the necessary cross program functions and capabilities to ensure the health and performance of the crew throughout an Artemis mission. For this purpose, the Exploration Medical Capability (ExMC) element of HRP developed a CHP system model for the Artemis III and IV missions to provide a view of how each program contributes to and interacts with the overall CHP system. To develop the 2023 Artemis CHP system model, ExMC leveraged existing data and models from the Moon to Mars Program Office, the Office of the Chief Health and Medical Officer (OCHMO) and the Orion, Gateway, Extravehicular Activity and Human Surface Mobility (EHP) and Human Landing System (HLS) programs. By using a Model-Based Systems Engineering (MBSE) approach, existing requirements, functions, and concepts of operations were combined to create a single system model focused on representing CHP from the launch to the return to Earth segments of the Artemis III and IV missions. Additionally, by incorporating the HRP Systems Platform for Aggregating and Relating Capabilities, or SPARC tool, the data from the programs was also related back to the 2nd volume of the NASA Human Health, Medical, and Performance Spaceflight Standard (NASA-STD-3001, Vol.2) and the human system risks identified by the Human System Risk Board (HSRB). The first version of the 2023 Artemis CHP system model was baselined in Fall of 2023 after the model was demonstrated to be a potentially useful tool for systems engineers integrating CHP capabilities in vehicle development as well as members of the Health and Medical Technical Authority providing oversight of those programs. The model may also be useful to any stakeholder of astronaut health and performance by providing insights on how an Artemis mission satisfies the NASA Human Health, Medical, and Performance Spaceflight Standards as well as how they mitigate the HSRB Human System Risks. This presentation highlights how the model was developed and the possible benefits of the model. [1] NASA HRP (2022), Crew Health and Performance System Whitepaper

Systems engineering↗
NASA NTRS2024

2023 Artemis Crew Health and Performance (CHP) System Model Development

While the NASA Human Research Program (HRP) utilizes a Crew Health and Performance (CHP) System to represent all the Agency’s efforts to ensure the health and performance of NASA astronauts, there is no shared mental model of a CHP system at NASA. Some groups may consider a CHP system to be only a medical kit, while others may not be using the concept at all. To facilitate the integration of functions and capabilities to ensure astronaut health and performance during vehicle development, HRP has proposed a CHP Shared Mental Model derived from the NASA Human Health, Medical, and Performance Spaceflight Standards (NASA-STD-3001 Vol.1/Vol.2). [1] Even though many vehicle, ground, and communication systems as well as mission operations are modeled for the Artemis Campaigns, no mission level CHP system model was created to achieve the intent of the HRP CHP Shared Mental Model. The lack of this model renders it difficult to visualize and understand how the many programs work together to provide the necessary cross program functions and capabilities to ensure the health and performance of the crew throughout an Artemis mission. For this purpose, the Exploration Medical Capability (ExMC) element of HRP developed a CHP system model for the Artemis III and IV missions to provide a view of how each program contributes to and interacts with the overall CHP system. To develop the 2023 Artemis CHP system model, ExMC leveraged existing data and models from the Moon to Mars Program Office, the Office of the Chief Health and Medical Officer (OCHMO) and the Orion, Gateway, Extravehicular Activity and Human Surface Mobility (EHP) and Human Landing System (HLS) programs. By using a Model-Based Systems Engineering (MBSE) approach, existing requirements, functions, and concepts of operations were combined to create a single system model focused on representing CHP from the launch to the return to Earth segments of the Artemis III and IV missions. Additionally, by incorporating the HRP Systems Platform for Aggregating and Relating Capabilities, or SPARC tool, the data from the programs was also related back to the 2nd volume of the NASA Human Health, Medical, and Performance Spaceflight Standard (NASA-STD-3001, Vol.2) and the human system risks identified by the Human System Risk Board (HSRB). The first version of the 2023 Artemis CHP system model was baselined in Fall of 2023 after the model was demonstrated to be a potentially useful tool for systems engineers integrating CHP capabilities in vehicle development as well as members of the Health and Medical Technical Authority providing oversight of those programs. The model may also be useful to any stakeholder of astronaut health and performance by providing insights on how an Artemis mission satisfies the NASA Human Health, Medical, and Performance Spaceflight Standards as well as how they mitigate the HSRB Human System Risks. This presentation highlights how the model was developed and the possible benefits of the model. [1] NASA HRP (2022), Crew Health and Performance System Whitepaper

Systems engineering↗
NASA NTRS2004

Decreased Estrogen May Contribute to Osteopenia in Unloaded Bones

Progressive loss of weight-bearing bone in astronauts is one of the most serious impediments to long-duration spaceflight. Estrogen deficiency in women is an established factor in bone loss. Reduced sex hormone levels have been reported in male astronauts, but no data is available regarding spaceflight effects on female sex hormones. The objective of our study was to determine the role of estrogen in disuse osteopenia. The NASA developed hindlimb suspension (HLS) model was used to simulate the unloading disuse of weight-bearing bones experienced in space. Female Sprague-Dawley rats (age 77d; n = 20/group) were HLS or kept ambulatory (AMB) for 38 d and endocrine and bone indices determined. HLS of rats resulted in lower (p less than 0.01) bone mass (9%0), bone mineral content (BMC 13%) and mechanical strength (28%) compared to AMB animals. Plasma estradiol (E2) was lower (p = 0.03) in HLS (10.1 +/- 1.4 pg/ml) compared to AMB rats (16.7 +/- 2.6 pg/ml). E2 was positively correlated to BMC r(sup 2) = 0.67 and mechanical strength r(sup 2) = 0.61. These results suggest that reduced E2 plays a role in disuse osteopenia induced by HLS. Plasma or pituitary lutenizing hormone (LH) and follicle stimulating hormone (FSH) levels were not different in HLS versus AMB rats. However, pituitary LH was correlated to E2 (r(sup 2) = 0.57), suggesting changes in E2 were exerted at the level of the hypothalamus-pituitary axis. Understanding the role of estrogen in disuse osteopenia is necessary to the development of efficacious therapies for female astronauts, bed rest patients and the increasing number of individuals in our sedentary population suffering bone loss.

Tou, Janet↗
NASA NTRS2024

Expansion of Check-Cases for 6DOF Simulation

This effort expands upon a previous NASA activity that developed flight simulation benchmark check-cases to include new check-cases for the Cislunar domain, comparing multiple NASA simulation tools. The results of this effort describe the benefits of standardizing inputs, simulation comparisons and describe an interactive website that enables comparison of externally provided simulation data. Participating simulations improved their software and identified implementation errors. This activity elevated simulation credibility and provided a measure of validation for the simulations actively in use for NASA’s Human Landing Systems (HLS).

Modeling↗
NASA NTRS2024

Expansion of Check-Cases for 6DOF Simulation: Appendix A

This is the Appendix containing figures of simulation output data plots for comparison from the assessment, “Expansion of Check-Cases for 6DOF Simulation”. This effort expands upon a previous NASA activity that developed flight simulation benchmark check-cases to include new check-cases for the Cislunar domain, comparing multiple NASA simulation tools. The results of this effort describe the benefits of standardizing inputs, simulation comparisons and describe an interactive website that enables comparison of externally provided simulation data. Participating simulations improved their software and identified implementation errors. This activity elevated simulation credibility and provided a measure of validation for the simulations actively in use for NASA’s Human Landing Systems (HLS).

Modeling↗
DOE OSTI2025

Even Higher-Level Synthesis: An Exploration of AI Hardware Accelerators using HLS4ML

With the rise of artificial intelligence, the popularization of deep learning, and a constantly evolving industry, the demand for flexible and efficient tools has never been greater. As algorithms grow more complex, their runtime and energy consumption increase exponentially. Customized hardware accelerators, long used for specific mathematical operations, remain essential for managing modern applications' computational and power demands. Hardware accelerators can speed up complex computations by orders of magnitude, but their manual design and verification processes are often challenging and time-consuming. High-Level Synthesis (HLS) provides a solution by transforming high-level algorithm descriptions, typically written in C++ or SystemC, into synthesizable RTL suitable for hardware implementation. This approach reduces development time for RTL engineers while offering flexibility beyond what traditional handwritten RTL can provide. We extended this capability to the machine-learning domain with the open-source framework hls4ml, which allows neural networks trained in Python frameworks like Tensorflow or PyTorch to be synthesized into efficient hardware representations for the traditional FPGA and ASIC flows. This breakthrough addresses the growing need for reduced design turnaround and easy verification of ML hardware accelerators with low latency and power efficiency constraints. During this tutorial, we will demonstrate how Python complements HLS by simplifying the ML design process, bridging the gap between software and hardware development. Attendees will explore how we translate neural networks modeled in Python into fixed-point C++ models suitable for HLS workflows. We will dive into strategies like Value-Range Analysis and Quantization-Aware Training, which optimize these designs for deployment and evaluate their accuracy, power consumption, and energy efficiency. To exemplify these concepts, experts from Fermilab will share their experiences applying this technology to high-energy physics experiments, where real-time, low-latency processing is critical. Over the years, Fermilab engineers have demonstrated how deep neural networks, optimized for hardware using hls4ml, can meet the stringent requirements of trigger systems at the CERN Large Hadron Collider. These systems rely on rapid decision-making to process immense data volumes while retaining only the most relevant events for further analysis. The application of hls4ml has also been extended to innovative technologies like smart pixel arrays. These smart pixels integrate ML inference capabilities directly into sensor devices, enabling localized data processing at the pixel level. This approach drastically reduces the need to transmit raw data to external processing units, significantly decreasing power consumption and latency. By embedding neural networks within the pixel architecture, the smart pixels can identify and prioritize relevant data in real time, providing a highly efficient solution for edge computing in scenarios such as particle detectors and imaging systems. Fermilab's work highlights the potential of hardware-accelerated ML in scenarios where both speed and power efficiency are mission-critical. Through this tutorial, attendees will gain valuable insights into the challenges and solutions of deploying ML in hardware. Understanding how HLS and hls4ml streamline the development of neural network-based hardware accelerators is fundamental for the industry's future. Participants will learn how these technologies are shaping the future of AI and scientific computing.

Di Guglielmo, Giuseppe [Fermilab]↗
DOE OSTI2023

HP-LSP: A reference of land surface phenology from fused Harmonized Landsat and Sentinel-2 with PhenoCam data

Abstract Land surface phenology (LSP) products are currently of large uncertainties due to cloud contaminations and other impacts in temporal satellite observations and they have been poorly validated because of the lack of spatially comparable ground measurements. This study provided a reference dataset of gap-free time series and phenological dates by fusing the Harmonized Landsat 8 and Sentinel-2 (HLS) observations with near-surface PhenoCam time series for 78 regions of 10 × 10 km 2 across ecosystems in North America during 2019 and 2020. The HLS-PhenoCam LSP (HP-LSP) reference dataset at 30 m pixels is composed of: (1) 3-day synthetic gap-free EVI2 (two-band Enhanced Vegetation Index) time series that are physically meaningful to monitor the vegetation development across heterogeneous levels, train models (e.g., machine learning) for land surface mapping, and extract phenometrics from various methods; and (2) four key phenological dates (accuracy ≤5 days) that are spatially continuous and scalable, which are applicable to validate various satellite-based phenology products (e.g., global MODIS/VIIRS LSP), develop phenological models, and analyze climate impacts on terrestrial ecosystems.

Science & Technology - Other Topics↗
NASA NTRSDate not supplied

Plume-surface interaction testing for crewed lunar lander risk reduction

Spacecraft conducting propulsive near-surface operations such as landing or initial ascent must consider potential hazards caused by rocket exhaust interacting with planetary regolith. Gas-granular interactions can erode the surface and eject material, altering the landing site, obscuring views of the surface, and creating abrasion or impact risks. The next generation of lunar landers under development for NASA’s Human Landing System program will push us outside Apollo flight experience for plume-surface interaction. Strategic knowledge gaps and poorly constrained flight data inhibit our ability to accurately and precisely predict the plume-surface interaction environment for a given flight vehicle. We present an overview of a lunar relevant, supersonic plume-surface interaction test that will be conducted in 2024 to improve our understanding of lunar PSI and reduce associated risks to the HLS program.

Wesley A. Chambers↗
NASA NTRSDate not supplied

DLES Unreal Simulation Tool (DUST)

NASA’s future Artemis missions to the Moon seek to explore areas around the Lunar South Pole. Though humans have previously set foot on the lunar surface, the proposed region provides unique and challenging environments that require insight and investigation prior to arrival. Several teams throughout the agency are performing this site and mission planning, design, and analysis to support areas like the Human Landing System (HLS), surface mobility, habitation elements, and scientific exploration. The NASA Exploration Systems Simulation (NExSyS) team at Johnson Space Center is developing a graphical environment of the Lunar South Pole region. Lunar terrain information collected from the Lunar Reconnaissance Orbiter (LRO) is compiled and made available through Johnson Space Center’s Digital Lunar Exploration Sites (DLES) data sets. The DLES data is used to build this graphic environment. The process of ingesting and accurately modeling this information in a meaningful way for analysis creates its own challenges such as generating a performant model from the source data and the application of curvature. Additionally, the area around the Lunar South Pole experiences different lighting conditions than those observed from the Apollo missions. The need to use the lunar environmental data products provided by DLES combined with the capability to calculate date specific ephemerides in real-time has given rise to the development of the DLES Unreal Simulation Tool (DUST). DUST incorporates augmented terrain from the DLES product into a desktop application that allows exploration of the Lunar South Pole region and its complex lighting conditions. DUST leverages advanced capabilities in the recently released Unreal Engine 5 renderer by Epic Games such as double precision for positioning of planetary bodies and surface elements, multiple infinite light sources to represent the Sun and eventually Earthshine, high resolution shadow maps for dynamic shadow accuracy, real-time software ray-tracing for multi-surface bounce lighting to render sunlight reflected off surface elements and terrain features, and performance optimized level of detail shifting as the eyepoint changes in a scene. This paper details the DUST application, the technologies of the engine platform that enable scientific and engineering analysis, the unique techniques and processes developed to consume the DLES data sets, and how the tool is being used to support the Artemis program.

Lunar Visualization↗
NASA NTRSDate not supplied

A Hybrid CFD/Engineering Model for Predicting Plume Induced Erosion and Cratering

The Descent Interpolated Gas-Granular Erosion Model (DIGGEM) is a hybrid computational fluid dynamics (CFD) / engineering model calibrated with flight data from Apollo. It is used for the prediction of plume induced viscous erosion and cratering during the descent of landing vehicles. The model assumes a functional relationship between local shear stress and eroded mass flux. It is used along with a suite of other tools to predict complex plume induced environments for Human Landing System (HLS) and Commercial Lunar Payload Services (CLPSS) vehicles.

PSI↗
NASA NTRSDate not supplied

Analytical Study of a Cryogenic Thermal Control Coating

This study focuses on the analysis of a cryogenic thermal control coating designed to reflect most of the Sun’s irradiance while emitting long wavelength radiation, thus enabling propulsion systems to maintain cryogenic temperatures while in deep space. This “solar white” coating is composed of yttrium oxide (Y2O3) which has properties that are well-suited for cryogenic propellant storage applications. To conduct proof of concept and material development, many tests have been run at both NASA Kennedy Space Center (KSC) and Glenn Research Center (GRC) to demonstrate the performance of the coating in the cryogenic regime in both powder and ceramic forms. At GRC, the Deep Space Solar Simulator (DS3) was used to run thermal vacuum tests where the coating was exposed to a deep space environment (~10 K) with some tests conducted under the illumination of a solar lamp. Using the test data, a thermal model of the DS3 test setup was developed to correlate the test results to predict the optical properties of the coating. Once the optical properties were determined, an additional thermal model, based on previous work by R.C. Young quist et al., was developed to verify the performance of a theoretical lunar, cryogenic propellant depot. The latter thermal model also demonstrates the usage of the HLS-UG-001 Human Landing System Lunar Thermal Analysis Guidebook published to baseline Artemis-related lunar studies.

Cryogenic↗
NASA NTRSDate not supplied

Evolution of the Next Exploration Toilet through Human-in-the-Loop (HITL) Testing

Human waste collection in space is a unique and necessary function that all crewmembers must perform. The variability in how each crewmember uses the toilet to urinate and defecate introduces complexities and challenges with regards to overall hardware design. Because of this variability, it is important to consider crew inputs in all aspects of a toilet design especially with regards to crew interfaces that could impact overall waste collection. Access to crew feedback is essential to the design process and should be considered early and often through the various design phases. In 2020, NASA started a project for the Human Landing System (HLS) program to develop a Government Furnished Equipment (GFE) toilet option. The project is known as the Lavatory On-Orbit (LOO). During the early development of the LOO, the project team conducted several crew evaluations to collect and summarize valuable crew feedback on system design, function, and overall usability to influence the next design iteration. Because every person could use the system differently in space, it was extremely important to collect and analyze the data in a very methodical manner to appropriately influence the design based on the evaluation results. Establishing a standard process ensures consistent data collection from one evaluation to another, helps to maintain privacy for each test subject’s inputs and removes any potential bias from test subject to test subject. To date, the team has completed four crew evaluations on prototypes for the different LOO hardware. This paper will summarize the methodology used to conduct the evaluations as well as how data was collected and analyzed. The paper will also provide details on each of the evaluations and how the design was updated based on the results.

toilet↗
NASA NTRSDate not supplied

Evolution of the Next Exploration Toilet Through Human-in-the-Loop (HITL) Testing

Human waste collection in space is a unique and necessary function that all crewmembers must perform. The variability in how each crewmember uses the toilet to urinate and defecate introduces complexities and challenges with regards to overall hardware design. Because of this variability, it is important to consider crew inputs in all aspects of a toilet design especially with regards to crew interfaces that could impact overall waste collection. Access to crew feedback is essential to the design process and should be considered early and often through the various design phases. In 2020, NASA started a project for the Human Landing System (HLS) program to develop a Government Furnished Equipment (GFE) toilet option. The project is known as the Lavatory On-Orbit (LOO). During the early development of the LOO, the project team conducted several crew evaluations to collect and summarize valuable crew feedback on system design, function, and overall usability to influence the next design iteration. Because every person could use the system differently in space, it was extremely important to collect and analyze the data in a very methodical manner to appropriately influence the design based on the evaluation results. Establishing a standard process ensures consistent data collection from one evaluation to another, helps to maintain privacy for each test subject’s inputs and removes any potential bias from test subject to test subject. To date, the team has completed four crew evaluations on prototypes for the different LOO hardware. This paper will summarize the methodology used to conduct the evaluations as well as how data was collected and analyzed. The paper will also provide details on each of the evaluations and how the design was updated based on the results.

toilet↗
NASA NTRSDate not supplied

Evolution of the Next Exploration Toilet Through Human-in-the-Loop (HITL) Testing

Human waste collection in space is a unique and necessary function that all crewmembers must perform. The variability in how each crewmember uses the toilet to urinate and defecate introduces complexities and challenges with regards to overall hardware design. Because of this variability, it is important to consider crew inputs in all aspects of a toilet design especially with regards to crew interfaces that could impact overall waste collection. Access to crew feedback is essential to the design process and should be considered early and often through the various design phases. In 2020, NASA started a project for the Human Landing System (HLS) program to develop a Government Furnished Equipment (GFE) toilet option. The project is known as the Lavatory On-Orbit (LOO). During the early development of the LOO, the project team conducted several crew evaluations to collect and summarize valuable crew feedback on system design, function, and overall usability to influence the next design iteration. Because every person could use the system differently in space, it was extremely important to collect and analyze the data in a very methodical manner to appropriately influence the design based on the evaluation results. Establishing a standard process ensures consistent data collection from one evaluation to another, helps to maintain privacy for each test subject’s inputs and removes any potential bias from test subject to test subject. To date, the team has completed four rounds of crew evaluations with multiple crewmembers on prototypes for the different LOO subsystems. This paper will summarize the methodology used to conduct the evaluations as well as how data was collected and analyzed. The paper will also provide details on each of the evaluations and how the design was updated based on the results.

toilet↗
NASA NTRSDate not supplied

Evolution of the Next Exploration Toilet Through Human-in-the-Loop (HITL) Testing

Human waste collection in space is a unique and necessary function that all crewmembers must perform. The variability in how each crewmember uses the toilet to urinate and defecate introduces complexities and challenges with regards to overall hardware design. Because of this variability, it is important to consider crew inputs in all aspects of a toilet design especially with regards to crew interfaces that could impact overall waste collection. Access to crew feedback is essential to the design process and should be considered early and often through the various design phases. In 2020, NASA started a project for the Human Landing System (HLS) program to develop a Government Furnished Equipment (GFE) toilet option. The project is known as the Lavatory On-Orbit (LOO). During the early development of the LOO, the project team conducted several crew evaluations to collect and summarize valuable crew feedback on system design, function, and overall usability to influence the next design iteration. Because every person could use the system differently in space, it was extremely important to collect and analyze the data in a very methodical manner to appropriately influence the design based on the evaluation results. Establishing a standard process ensures consistent data collection from one evaluation to another, helps to maintain privacy for each test subject’s inputs and removes any potential bias from test subject to test subject. To date, the team has completed four rounds of crew evaluations with multiple crewmembers on prototypes for the different LOO subsystems. This paper will summarize the methodology used to conduct the evaluations as well as how data was collected and analyzed. The paper will also provide details on each of the evaluations and how the design was updated based on the results.

toilet↗