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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 sources NASA NTRS DOE OSTI

NASA NTRS2016

Biomechanical Modeling of the Deadlift Exercise to Improve the Efficacy of Resistive Exercise Microgravity Countermeasures

During long-duration spaceflight missions, astronauts exposure to microgravity without adequate countermeasures can result in losses of muscular strength and endurance, as well as loss of bone mass. As a countermeasure to this challenge, astronauts engage in resistive exercise during spaceflight to maintain their musculoskeletal function. The Hybrid Ultimate Lifting Kit (HULK) has been designed as a prototype exercise device for an exploration-class vehicle; the HULK features a much smaller footprint than previous devices such as the Advanced Resistive Exercise Device (ARED) on the International Space Station (ISS), which makes the HULK suitable for extended spaceflight missions in vehicles with limited volume. As current ISS exercise countermeasure equipment represents an improvement over previous generations of such devices, the ARED is being employed as a benchmark of functional performance. This project involves the development of a biomechanical model of the deadlift exercise, and is novel in that it is the first exercise analyzed in this context to include the upper limbs in the loading path, in contrast to the squat, single-leg squat, and heel raise exercises also being modeled by our team. OpenSim software is employed to develop these biomechanical models of humans performing resistive exercises to assess and improve the new exercise device designs. Analyses include determining differences in joint and muscle forces when using different loading strategies with the device, comparing and contrasting with the ARED benchmark, and determining whether the loading is sufficient to maintain musculoskeletal health. During data collection, the number of repetitions, load, cadence, stance, and grip width are controlled in order to facilitate comparisons between loading configurations. To date, data have been collected for two human subjects performing the deadlift exercise on the HULK device using two different loading conditions. Recorded data include motion capture, electromyography (EMG), ground reaction forces, device load cell data, photos and videos, and anthropometric data. Work is ongoing to perform biomechanical analyses including inverse kinematics and inverse dynamics to compare different versions of the deadlift model in order to determine which provides an appropriate level of detail to study this exercise. This work is supported by the National Space Biomedical Research Institute through NCC 9-58.

physical exercise↗

NASA NTRS2011

Research and Technology Development to Advance Environmental Monitoring, Food Systems, and Habitat Design for Exploration Beyond Low Earth Orbit

Exploration missions will carry crews far beyond the relatively safe environs of cis-lunar space. Such trips will have little or no opportunity for resupply or rapid aborts and will be of a duration that far exceeds our experience to date. The challenges this imposes on the requirements of systems that monitor the life support and provide food and shelter for the crew are the focus of much research within the Human Research Program. Making all of these technologies robust and reliable enough for multi-year missions with little or no ability to run for home calls for a thorough understanding of the risks and impacts of failure. The way we currently monitor for microbial contamination of water, air, and surfaces, by sampling and growing cultures on nutrient media, must be reconsidered for exploration missions which have limited capacity for consumables. Likewise, the shelf life of food must be increased so that the nutrients required to keep the crewmembers healthy do not degrade over the life of the mission. Improved formulations, preservation, packaging, and storage technologies are all being investigated for ways slow this process or replace stowed food with key food items grown fresh in situ. Ensuring that the mass and volume of a spacecraft are used to maximum efficiency calls for infusing human factors into the design from its inception to increase efficiency, improve performance, and retain robustness toward operational realities. Integrating the human system with the spacecraft systems is the focus of many lines of investigation.

Sullivan, Thomas A.↗

NASA NTRS1987

Computational models of human vision with applications

The research program supported by this grant was initiated in l977 by the Joint Institute for Aeronautics and Acoustics of the Department of Aeronautics and Astronautics at Stanford University. The purpose of the research was to study human performance with the goal of improving the design of flight instrumentation. By mutual agreement between the scientists at NASA-Ames and Stanford, all research activities in this area were consolidated into a single funding mechanism, NCC 2-307 (Center of Excellence Grant, 7/1/84 - present). This is the final report on this research grant.

Wandell, Brian A.↗

NASA NTRS1988

Deep-reasoning fault diagnosis - An aid and a model

The design and evaluation are presented for the knowledge-based assistance of a human operator who must diagnose a novel fault in a dynamic, physical system. A computer aid based on a qualitative model of the system was built to help the operators overcome some of their cognitive limitations. This aid differs from most expert systems in that it operates at several levels of interaction that are believed to be more suitable for deep reasoning. Four aiding approaches, each of which provided unique information to the operator, were evaluated. The aiding features were designed to help the human's casual reasoning about the system in predicting normal system behavior (N aiding), integrating observations into actual system behavior (O aiding), finding discrepancies between the two (O-N aiding), or finding discrepancies between observed behavior and hypothetical behavior (O-HN aiding). Human diagnostic performance was found to improve by almost a factor of two with O aiding and O-N aiding.

Yoon, Wan Chul↗

NASA NTRS1990

Biological research on Space Station Freedom

The paper discusses laboratory capabilities of the SSF which permit long-term, systematic investigations into the effects of the space environment, particularly the effect of microgravity, on a range of biological specimens. The ability to manipulate gravity levels between 0 and 2.0 g makes it possible to examine gravitational effects along a continuum. Space centrifuge research is expected to lead to practical applications in areas such as aging, treating malfunctions of the body regulatory and defense mechanisms, improving agricultural production, and extending human performance.

Chambers, L. P.↗

NASA NTRS2004

Peer-to-Peer Human-Robot Interaction for Space Exploration

NASA has embarked on a long-term program to develop human-robot systems for sustained, affordable space exploration. To support this mission, we are working to improve human-robot interaction and performance on planetary surfaces. Rather than building robots that function as glorified tools, our focus is to enable humans and robots to work as partners and peers. In this paper. we describe our approach, which includes contextual dialogue, cognitive modeling, and metrics-based field testing.

Fong, Terrence↗

NASA NTRS2011

Simulating Visual Attention Allocation of Pilots in an Advanced Cockpit Environment

This paper describes the results of experiments conducted with human line pilots and a cognitive pilot model during interaction with a new 40 Flight Management System (FMS). The aim of these experiments was to gather human pilot behavior data in order to calibrate the behavior of the model. Human behavior is mainly triggered by visual perception. Thus, the main aspect was to setup a profile of human pilots' visual attention allocation in a cockpit environment containing the new FMS. We first performed statistical analyses of eye tracker data and then compared our results to common results of familiar analyses in standard cockpit environments. The comparison has shown a significant influence of the new system on the visual performance of human pilots. Further on, analyses of the pilot models' visual performance have been performed. A comparison to human pilots' visual performance revealed important improvement potentials.

Frische, F.↗

NASA NTRSDate not supplied

Humans to Mars, but How Many? Using Training Requirements Modeling to Inform Crew Size

Missions to Mars will differ from previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner due to the long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) is developing a methodology for assessing the trade space of factors that affect the number of crew for future missions. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew. The IMPRINT results will be presented in the modeling and simulation sub-tag. Here we present results of a model based on NASA’s crew qualification and responsibility matrix (CQRM), a tool used to identify the crew qualifications for each area of responsibility (operation, system, and payload) for a mission. The model outputs an optimized allocation of training assignments along with a flight-assigned CQRM that can be used to consider the expertise that can be trained within a crew of a given size. We discuss the CQRM model result implications on the trade space for Mars mission crew size.

Mars↗

NASA NTRSDate not supplied

Humans to Mars, but How Many? Using Imprint Human Performance Models to Inform Crew Size

HUMANS TO MARS, BUT HOW MANY? USING IMPRINT HUMAN PERFORMANCE MODELS TO INFORM CREW SIZE Missions to Mars will differ from previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner due to long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) is developing a methodology for assessing the trade space of factors that affect the number of crew for future missions. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew. The custom-built crew expertise model results will be presented in the training sub-tag. Here we present results of the three IMPRINT models. Two of these models were built using IMPRINT’s Operations Model capability, with detailed task networks for specific systems and scenarios allowing for a comprehensive mental workload analysis on certain crew positions. The third model was built using IMPRINT’s Force Model capability, allowing for a higher-level manpower analysis based on crew engagement in activities performed over a longer Mars transit scenario, and how those activities may be impacted by unplanned events and new tasking unique to the Mars mission. Differences between the models will be presented, as well as examples of model results and a discussion of how those results may inform future Mars mission manpower requirements, system design, and operating procedures.

Donna L Dempsey↗

NASA NTRSDate not supplied

Humans to Mars, but How Many? Using Training Requirements Modeling to Inform Crew Size

Mars↗

NASA NTRS2025

Humans to Mars, but How Many? Trade Space Analyses for Mars Mission Crew Size

Missions to Mars will differ from previous human spaceflight missions in that the crew of astronauts will be required to operate in an Earth-independent manner due to the long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) developed a methodology for assessing the trade space of factors that affect the number of crew for Mars missions based on human performance and expertise modeling. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew based on NASA’s crew qualification and responsibilities matrix (CQRM). We present example model results and discuss implications on trade space analyses for Mars mission crew size.

Mars Mission↗

DOE OSTI2024

Human-Machine Shared Control for Path Following Considering Driver Fatigue Characteristics

Fatigue driving has been regarded as one of the most important factors that cause traffic accidents. This paper proposes a robust human-machine shared control strategy to improve the vehicle performance for different driver fatigue states. Firstly, the time-varying driver steering model is proposed to address the model mismatch caused by fatigue driving. And the driver fatigue evaluation system is established based on facial features to quantify driver fatigue levels. Based on the quantified fatigue levels, a novel strategy for allocating authorities of the driver and controller is developed for building the driver-vehicle interaction system. Then, to weaken the influence of parameter perturbations caused by the time-varying driver states, we design a fatigue-based shared controller through state feedback. The actuator saturation and system constraints are considered in the controller design through the robust set-invariance property to improve vehicle safety and driving comfort. The driver-in-the-loop platform is conducted to validate the effectiveness of the proposed shared steering controller. In conclusion, the experimental results show that the proposed strategy can adaptively optimize the human-machine authorities according to fatigue states and comprehensively improve vehicle performance.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2017

Orion Multi-Purpose Crew Vehicle Solving and Mitigating the Two Main Cluster Pendulum Problem

The Orion Multi-purpose Crew Vehicle (MPCV) Orion spacecraft will return humans from beyond earth's orbit, including Mars and will be required to land 20,000 pounds of mass safely in the ocean. The parachute system nominally lands under 3 main parachutes, but the system is designed to be fault tolerant and land under 2 main parachutes. During several of the parachute development tests, it was observed that a pendulum, or swinging, motion could develop while the Crew Module (CM) was descending under two parachutes. This pendulum effect had not been previously predicted by modeling. Landing impact analysis showed that the landing loads would double in some places across the spacecraft. The CM structural design limits would be exceeded upon landing if this pendulum motion were to occur. The Orion descent and landing team was faced with potentially millions of dollars in structural modifications and a severe mass increase. A multidisciplinary team was formed to determine root cause, model the pendulum motion, study alternate canopy planforms and assess alternate operational vehicle controls & operations providing mitigation options resulting in a reliability level deemed safe for human spaceflight. The problem and solution is a balance of risk to a known solution versus a chance to improve the landing performance for the next human-rated spacecraft.

Ali, Yasmin↗

NASA NTRS1992

Spaceborne construction and operations planning - Decision rules for selecting EVA, telerobot, and combined work-systems

An approach is presented for selecting an appropriate work-system for performing construction and operations tasks by humans and telerobots. The decision to use extravehicular activity (EVA) performed by astronauts, extravehicular robotics (EVR), or a combination of EVA and EVR is determined by the ratio of the marginal costs of EVA, EVR, and IVA. The approach proposed here is useful for examining cost trade-offs between tasks and performing trade studies of task improvement techniques (human or telerobotic).

Smith, Jeffrey H.↗

DOE OSTI2020

The effect of lighting environment on task performance in buildings – A review

The effects of indoor environmental conditions on human health, satisfaction, and performance have been the focal point of research for decades. This paper reviews and summarizes the impact of lighting environment on task performance, specifically for the built environment audience. Existing studies included a variety of performance tests on cognitive performance and perception, visual acuity and reaction, memory, reasoning, and labor productivity. Illuminance, luminance ratio and correlated color temperature were found to affect performance in different ways, reflecting the impact of experimental techniques, conditions, performance evaluation methods used and data analysis methods. These were reviewed and categorized, with discussion on limitations related to sample size, modeling approach, carryover effects and other factors affecting individual differences in performance, with recommendations for future improvement. Although no universal conclusions can be made, in general, task performance seems to improve with higher illuminances, contrast ratios in the range of 7–11:1 (while always making sure that glare will not occur in the space) and higher correlated color temperature, while spectral tuning in the red or blue wavelengths has also shown positive effects. To obtain more generic evidence, future studies should be more consistent in terms of experimental procedures and overall light conditions, and also consider the effects of vertical illuminance, daylight provision/control, and outside views on task performance. Finally, studying performance with multi-factorial designs in a human-centered optimized manner (such as deploying variable lighting scenarios optimized for various tasks) can lead to deeper understanding of lighting effects on task performance, and ultimately to improved lighting design and operation in buildings overall.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Traffic Prediction for Merging Coordination Control in Mixed Traffic Scenarios

Connected and autonomous vehicles (CAVs) have the potential to bring in safety, mobility, and energy benefits to transportation. The control decisions of CAVs are usually determined for a look-ahead horizon based on previewed traffic information. This requires an effective prediction of future traffic conditions and its integration with the CAV control framework. However, the short-term traffic prediction using information from connectivity is a challenging research topic, especially for mixed traffic scenarios. This work focuses on the development of a traffic prediction framework for a merging coordination controller. The previously developed merging controller coordinates the merging sequence and travel speed of CAVs to maximize the energy efficiency and overall mobility. In mixed traffic scenarios, the controller receives information regarding the position of all the vehicles traveling inside a control zone and controls the desired speed of all CAVs. The controller has no control on the human-driven vehicles. The merging controller does not have direct information or an explicit prediction on the behaviors of human-driven vehicles. Aiming to improve the performance of the merging controller in various mixed traffic conditions, a traffic prediction algorithm is developed and evaluated in this work. The performance of this traffic prediction algorithm is investigated for various penetration rates of connectivity for a single-lane secondary road merging to a single-lane primary road. The results show that compared to a constant speed assumption of human-driven vehicles, the proposed traffic prediction algorithm is able to reduce the prediction error of the arrival time of human-driven vehicles at the merging zone by more than 50%.

Shao, Yunli↗

DOE OSTI2026

A multimodal large language model for materials science

Understanding and predicting the properties of inorganic materials is crucial for accelerating advancements in materials science and driving applications in energy, electronics and beyond. Integrating material structure data with language-based information through multimodal large language models (LLMs) offers great potential to support these efforts by enhancing human–artificial intelligence interaction. However, a key challenge lies in integrating atomic structures at full resolution into LLMs. In this work, we introduce MatterChat, a versatile structure-aware multimodal LLM that unifies material structural data and textual inputs into a single cohesive model. MatterChat uses a bridging module to effectively align a pretrained universal machine learning interatomic potential with a pretrained LLM, reducing training costs and enhancing flexibility. Our results demonstrate that MatterChat greatly improves performance in material property prediction and human–artificial intelligence interaction, surpassing general-purpose LLMs such as GPT-4. We also demonstrate its usefulness in applications such as more advanced scientific reasoning and step-by-step material synthesis.

Tang, Yingheng [Lawrence Berkeley National Laborat↗

NASA NTRS2015

Space Technology Game Changing Development Human Exploration Telerobotics 2

The purpose of the Human Exploration Tele robotics 2 (HET2) project is to mature telerobotics technology to increase the performance, reduce the cost, and improve the success of human space exploration. To do this, HET2 will develop a new robot, the Astrobee free-flying robot, and mature Robonaut 2 to offload routine and repetitive work from astronauts and extend and enhance crew capabilities. HET2 will test these robots in laboratories on the ground and on the International Space Station (ISS).

Robotics↗