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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Operational Implications from Field Test Results: Sensorimotor Guidelines for Exploration Missions

Two key sensorimotor objectives of the joint NASA-Russian Field Test (FT) study were (1) to quantify functional performance on long duration crewmembers as close to landing as possible, and (2) to develop a recovery timeline back to preflight baseline. The purpose of this presentation is to provide an overview of the FT results and discuss the operational implications for future exploration missions. The NASA and Russian teams conducted a total of 48 Field Tests, including 18 using a reduced Pilot FT (PFT) protocol. The combined PFT/FT cohort included 14 first-time fliers, 4F, and nine cosmonauts who repeated FT during a second mission. The mission durations were 185 ± 42 days, mean ± std. Nominally, the initial postflight session was performed in the medical test at the Soyuz landing site or at the nearby airport (R+2.2 ± 1.3 hrs, mean ± std), and then repeated multiple times throughout the postflight recovery. The common tasks performed across PFT and full FT protocols included sit-to-stand, recovery from fall (prone to stand) and tandem walk, performed in that order of increasing difficulty. The full FT protocol also included seated tasks (eccentric gaze, dysmetria finger to nose, eye-hand coordination on a tablet, grip force discrimination), a standing posture test with an upper body perturbation, a timed up and go mobility test with obstacles, and a dynamic visual acuity task during vertical oscillations. While there was considerable variability in the postflight outcome measures across crewmembers, the level of vestibular/cerebellar and sensorimotor impairment was greater than previously observed during shorter spaceflight missions. Most striking was the higher incidence of motion sickness even without constraining the standard medical interventions. Motion sensitivity prevented some crewmembers from attempting and/or completing the early testing. The recovery timeline varied with task complexity, generally taking longer when either the basis of support was limited (e.g., tandem walk) or visual cues were deprived (eyes closed). Based on this evidence, mission planners need to expect a range of response across individuals and tasks following G-transitions. Individual health assessments are recommended along with development of pre-worked, prioritized content and timelines, with the ability to change roles depending on crew readiness. Handholds and balance aids are recommended to help stabilize the crewmembers to perform specific tasks (e.g., touch screen selection) or to allow the crewmember the ability to rest with onset of symptoms. Based on anecdotal reports and performance on computerized dynamic posturography, multiple testing on landing day appeared to be beneficial for some participants, while others may have pushed beyond their motion tolerance limit in an effort to complete more FT objectives. Instead of delaying planetary surface operations to allow for recovery, our results suggest that early mobility may be important. Early active self-administered retraining, individualized based on the level of initial impairment and motion sensitivity, will enable a more efficient motor learning and enhance crew performance.

S J Wood↗
NASA NTRS2000

Improving the Aircraft Design Process Using Web-Based Modeling and Simulation

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and multifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

Reed, John A.↗
NASA NTRS2003

Improving the Aircraft Design Process Using Web-based Modeling and Simulation

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and muitifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

Reed, John A.↗
DOE OSTI2025

Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting

Abstract Drug response prediction (DRP) methods tackle the complex task of associating the effectiveness of small molecules with the specific genetic makeup of the patient. Anti-cancer DRP is a particularly challenging task requiring costly experiments as underlying pathogenic mechanisms are broad and associated with multiple genomic pathways. The scientific community has exerted significant efforts to generate public drug screening datasets, giving a path to various machine learning models that attempt to reason over complex data space of small compounds and biological characteristics of tumors. However, the data depth is still lacking compared to application domains like computer vision or natural language processing domains, limiting current learning capabilities. To combat this issue and improves the generalizability of the DRP models, we are exploring strategies that explicitly address the imbalance in the DRP datasets. We reframe the problem as a multi-objective optimization across multiple drugs to maximize deep learning model performance. We implement this approach by constructing Multi-Objective Optimization Regularized by Loss Entropy loss function and plugging it into a Deep Learning model. We demonstrate the utility of proposed drug discovery methods and make suggestions for further potential application of the work to achieve desirable outcomes in the healthcare field.

Biochemistry & Molecular Biology↗
NASA NTRS1989

Dissociation revisited - Workload and performance in a simulated flight task

The multiple resource model has been used as the theoretical basis for interpreting single-to-dual task changes in measures of performance and workload ratings. Inconsistent relationships among these measures have been termed dissociation. It is possible they are an artifact of the way performance and workload measures are collected; performance measures are available for the components of a complex task whereas workload ratings are integrated across all of the tasks performed within an interval of time. This study compared component ratings with global ratings and found that component ratings provide better information about subjects' task strategies and in interpreting the resultant relationships between workload ratings and performance.

King, Teresa↗
NASA NTRS1988

Distributed computation of graphics primitives on a transputer network

A method is developed for distributing the computation of graphics primitives on a parallel processing network. Off-the-shelf transputer boards are used to perform the graphics transformations and scan-conversion tasks that would normally be assigned to a single transputer based display processor. Each node in the network performs a single graphics primitive computation. Frequently requested tasks can be duplicated on several nodes. The results indicate that the current distribution of commands on the graphics network shows a performance degradation when compared to the graphics display board alone. A change to more computation per node for every communication (perform more complex tasks on each node) may cause the desired increase in throughput.

Ellis, Graham K.↗
NASA NTRS2014

Low-latency Science Exploration of Planetary Bodies: a Demonstration Using ISS in Support of Mars Human Exploration

We summarize a proposed experiment to use the International Space Station to formally examine the application and validation of low-latency telepresence for surface exploration from space as an alternative, precursor, or potentially as an adjunct to astronaut "boots on the ground." The approach is to develop and propose controlled experiments, which build upon previous field studies and which will assess the effects of different latencies (0 to 500 msec), task complexity, and alternate forms of feedback to the operator. These experiments serve as an example of a pathfinder for NASA's roadmap of missions to Mars with low-latency telerobotic exploration as a precursor to astronaut's landing on the surface to conduct geological tasks.

ISS in Support↗
NASA NTRS2014

Low-Latency Science Exploration of Planetary Bodies: How ISS Might Be Used as Part of a Low-Latency Analog Campaign for Human Exploration

We suggest that the International Space Station be used to examine the application and validation of low-latency telepresence for surface exploration from space as an alternative, precursor, or potentially as an adjunct to astronaut "boots on the ground." To this end, controlled experiments that build upon and complement ground-based analog field studies will be critical for assessing the effects of different latencies (0 to 500 milliseconds), task complexity, and alternate forms of feedback to the operator. These experiments serve as an example of a pathfinder for NASA's roadmap of missions to Mars with low-latency telerobotic exploration as a precursor to astronaut's landing on the surface to conduct geological tasks.

robotic space exploration↗
NASA NTRS1984

POPCORN: a Supervisory Control Simulation for Workload and Performance Research

A multi-task simulation of a semi-automatic supervisory control system was developed to provide an environment in which training, operator strategy development, failure detection and resolution, levels of automation, and operator workload can be investigated. The goal was to develop a well-defined, but realistically complex, task that would lend itself to model-based analysis. The name of the task (POPCORN) reflects the visual display that depicts different task elements milling around waiting to be released and pop out to be performed. The operator's task was to complete each of 100 task elements that ere represented by different symbols, by selecting a target task and entering the desired a command. The simulated automatic system then completed the selected function automatically. Highly significant differences in performance, strategy, and rated workload were found as a function of all experimental manipulations (except reward/penalty).

Hart, S. G.↗
NASA NTRS1993

Mission activities planning for a Hermes mission by means of AI-technology

Mission Activities Planning is a complex task to be performed by mission control centers. AI technology can offer attractive solutions to the planning problem. This paper presents the use of a new AI-based Mission Planning System for crew activity planning. Based on a HERMES servicing mission to the COLUMBUS Man Tended Free Flyer (MTFF) with complex time and resource constraints, approximately 2000 activities with 50 different resources have been generated, processed, and planned with parametric variation of operationally sensitive parameters. The architecture, as well as the performance of the mission planning system, is discussed. An outlook to future planning scenarios, the requirements, and how a system like MARS can fulfill those requirements is given.

Pape, U.↗
NASA NTRS1993

Intelligent tutoring and aiding in satellite ground control

In supervisory control systems such as satellite ground control, there is a need for human-centered automation where the focus is to understand and enhance the human-system interaction experience in the complex task environment. Operator support in the form of off-line intelligent tutoring and on-line intelligent aiding is one approach towards this effort. The tutor/aid paradigm is proposed here as a design approach that integrates the two aspects of operator support in one system for technically oriented adults in complex domains. This paper also presents GT-VITA, a proof-of-concept graphical, interactive, intelligent tutoring system that is a first attempt to illustrate the tutoring aspect of the tutor/aid paradigm in the domain of satellite ground control. Evaluation on GT-VITA is conducted with NASA personnel with very positive results. GT-VITA is presented being fielded as it is at Goddard Space Flight Center.

Chu, Rose W.↗
DOE OSTI2021

Multisource Data Fusion Outage Location in Distribution Systems via Probabilistic Graphical Models

Efficient outage location is critical to enhancing the resilience of power distribution systems. However, accurate outage location requires combining massive evidence received from diverse data sources, including smart meter (SM) last gasp signals, customer trouble calls, social media messages, weather data, vegetation information, and physical parameters of the network. This is a computationally complex task due to the high dimensionality of data in distribution grids. In this paper, we propose a multi-source data fusion approach to locate outage events in partially observable distribution systems using Bayesian networks (BNs). A novel aspect of the proposed approach is that it takes multi-source evidence and the complex structure of distribution systems into account using a probabilistic graphical method. Our method can radically reduce the computational complexity of outage location inference in high-dimensional spaces. The graphical structure of the proposed BN is established based on the network’s topology and the causal relationship between random variables, such as the states of branches/customers and evidence. Utilizing this graphical model, accurate outage locations are obtained by leveraging a Gibbs sampling (GS) method, to infer the probabilities of de-energization for all branches. Compared with commonly-used exact inference methods that have exponential complexity in the size of the BN, GS quantifies the target conditional probability distributions in a timely manner. As a result, a case study of several real-world distribution systems is presented to validate the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Deep neural network uncertainty quantification for LArTPC reconstruction

We evaluate uncertainty quantification (UQ) methods for deep learning applied to liquid argon time projection chamber (LArTPC) physics analysis tasks. As deep learning applications enter widespread usage among physics data analysis, neural networks with reliable estimates of prediction uncertainty and robust performance against overconfidence and out-of-distribution (OOD) samples are critical for their full deployment in analyzing experimental data. While numerous UQ methods have been tested on simple datasets, performance evaluations for more complex tasks and datasets are scarce. Here we assess the application of selected deep learning UQ methods on the task of particle classification using the PiLArNet monte carlo 3D LArTPC point cloud dataset. We observe that UQ methods not only allow for better rejection of prediction mistakes and OOD detection, but also generally achieve higher overall accuracy across different task settings. We assess the precision of uncertainty quantification using different evaluation metrics, such as distributional separation of prediction entropy across correctly and incorrectly identified samples, receiver operating characteristic curves (ROCs), and expected calibration error from observed empirical accuracy. We conclude that ensembling methods can obtain well calibrated classification probabilities and generally perform better than other existing methods in deep learning UQ literature.

47 OTHER INSTRUMENTATION↗
NASA NTRS2003

Biological Visualization, Imaging and Simulation(Bio-VIS) at NASA Ames Research Center: Developing New Software and Technology for Astronaut Training and Biology Research in Space

The Bio- Visualization, Imaging and Simulation (BioVIS) Technology Center at NASA's Ames Research Center is dedicated to developing and applying advanced visualization, computation and simulation technologies to support NASA Space Life Sciences research and the objectives of the Fundamental Biology Program. Research ranges from high resolution 3D cell imaging and structure analysis, virtual environment simulation of fine sensory-motor tasks, computational neuroscience and biophysics to biomedical/clinical applications. Computer simulation research focuses on the development of advanced computational tools for astronaut training and education. Virtual Reality (VR) and Virtual Environment (VE) simulation systems have become important training tools in many fields from flight simulation to, more recently, surgical simulation. The type and quality of training provided by these computer-based tools ranges widely, but the value of real-time VE computer simulation as a method of preparing individuals for real-world tasks is well established. Astronauts routinely use VE systems for various training tasks, including Space Shuttle landings, robot arm manipulations and extravehicular activities (space walks). Currently, there are no VE systems to train astronauts for basic and applied research experiments which are an important part of many missions. The Virtual Glovebox (VGX) is a prototype VE system for real-time physically-based simulation of the Life Sciences Glovebox where astronauts will perform many complex tasks supporting research experiments aboard the International Space Station. The VGX consists of a physical display system utilizing duel LCD projectors and circular polarization to produce a desktop-sized 3D virtual workspace. Physically-based modeling tools (Arachi Inc.) provide real-time collision detection, rigid body dynamics, physical properties and force-based controls for objects. The human-computer interface consists of two magnetic tracking devices (Ascention Inc.) attached to instrumented gloves (Immersion Inc.) which co-locate the user's hands with hand/forearm representations in the virtual workspace. Force-feedback is possible in a work volume defined by a Phantom Desktop device (SensAble inc.). Graphics are written in OpenGL. The system runs on a 2.2 GHz Pentium 4 PC. The prototype VGX provides astronauts and support personnel with a real-time physically-based VE system to simulate basic research tasks both on Earth and in the microgravity of Space. The immersive virtual environment of the VGX also makes it a useful tool for virtual engineering applications including CAD development, procedure design and simulation of human-system systems in a desktop-sized work volume.

Smith, Jeffrey↗
NASA NTRS2002

Research on Intelligent Synthesis Environment

The ultimate goal of this research project is to develop a methodology for the assessment and continuous improvement of engineering team effectiveness in distributed collaborative environments. This review provides the theoretical foundation upon which subsequent empirical work will be based. Our review of the team performance literature has identified the following 12 conceptually distinct team interaction processes as characteristic of effective teams. 1) Mission Analysis; 2) Resource Distribution; 3) Leadership; 4) Timing; 5) Intra-team Feedback; 6) Motivational Functions; 7) Team Orientation; 8) Communication; 9) Coordination; 10) Mutual Performance Monitoring; 11) Back-up Behaviors; and 12) Cooperation. In addition, this review summarizes how team task characteristics (i.e., task type, task complexity, motivation, and temporal changes), team characteristics (i.e., team structure and team knowledge), and individual team member characteristics (i.e., dispositions and teamwork knowledge, skills, and abilities) affect team interaction processes, determine the relevance of these processes, and influence team performance. The costs and benefits of distributed team collaboration are also considered. The review concludes with a brief discussion of the nature of collaborative team engineering tasks.

Loftin, R. Bowen↗
NASA NTRS1999

New challenges for Life Sciences flight project management

Scientists have conducted studies involving human spaceflight crews for over three decades. These studies have progressed from simple observations before and after each flight to sophisticated experiments during flights of several weeks up to several months. The findings from these experiments are available in the scientific literature. Management of these flight experiments has grown into a system fashioned from the Apollo Program style, focusing on budgeting, scheduling and allocation of human and material resources. While these areas remain important to the future, the International Space Station (ISS) requires that the Life Sciences spaceflight experiments expand the existing project management methodology. The use of telescience with state-the-art information technology and the multi-national crews and investigators challenges the former management processes. Actually conducting experiments on board the ISS will be an enormous undertaking and International Agreements and Working Groups will be essential in giving guidance to the flight project management Teams forged in this matrix environment must be competent to make decisions and qualified to work with the array of engineers, scientists, and the spaceflight crews. In order to undertake this complex task, data systems not previously used for these purposes must be adapted so that the investigators and the project management personnel can all share in important information as soon as it is available. The utilization of telescience and distributed experiment operations will allow the investigator to remain involved in their experiment as well as to understand the numerous issues faced by other elements of the program The complexity in formation and management of project teams will be a new kind of challenge for international science programs. Meeting that challenge is essential to assure success of the International Space Station as a laboratory in space.

NASA Discipline General Space Life Sciences↗
DOE OSTI2025

ExtremeMETA: High-speed Lightweight Image Segmentation Model by Remodeling Multi-channel Metamaterial Imagers

Deep neural networks (DNNs) have heavily relied on traditional computational units, such as CPUs and GPUs. However, this conventional approach brings significant computational burden, latency issues, and high power consumption, limiting their effectiveness. This has sparked the need for lightweight networks such as ExtremeC3Net. Meanwhile, there have been notable advancements in optical computational units, particularly with metamaterials, offering the exciting prospect of energy-efficient neural networks operating at the speed of light. Yet, the digital design of metamaterial neural networks (MNNs) faces precision, noise, and bandwidth challenges, limiting their application to intuitive tasks and low-resolution images. In this study, we proposed a large kernel lightweight segmentation model, ExtremeMETA. Based on ExtremeC3Net, our proposed model, ExtremeMETA maximized the ability of the first convolution layer by exploring a larger convolution kernel and multiple processing paths. With the large kernel convolution model, we extended the optic neural network application boundary to the segmentation task. To further lighten the computation burden of the digital processing part, a set of model compression methods was applied to improve model efficiency in the inference stage. The experimental results on three publicly available datasets demonstrated that the optimized efficient design improved segmentation performance from 92.45 to 95.97 on mIoU while reducing computational FLOPs from 461.07 MMacs to 166.03 MMacs. The large kernel lightweight model ExtremeMETA showcased the hybrid design’s ability on complex tasks.

large convolution kernel↗
DOE OSTI2022

Development of a Configurable DERMS Test System in GridAPPS-D

Distributed Energy Resources and their increased penetration within the power grid are a suitable method to provide essential reliability services. In order to do so, they must operate in aggregate. Aggregation of a wide variety of systems with varying standards and protocols is a complex task, which could benefit from rules and standards to support interoperability. To this end, the Portland State University Power Lab has developed the Energy Grid of Things project, which includes a Distributed Energy Resource Management System to provide aggregation and demonstrate the usage of an Energy Services Interface: a set of rules governing the interface between resource owners and aggregator businesses. This thesis presents a Modeling Environment that provides a simulation and test platform reflecting the complex needs of an aggregator. A grid simulator is required that is able to reflect the effects of thousands of Distributed Energy Resources operating in tandem; furthermore, these effects must be communicated to external actors such as the Grid Operator, which provides grid service requests to the aggregator and requires feedback. The Modeling Environment provides all of this functionality by leveraging the GridAPPS-D platform to develop an interoperable class-based system that provides configurable simulations with modular input and output APIs. The Modeling Environment uses abstractions to allow any feasible type of input to be reflected within the model as a Distributed Energy Resource, and serves as a proof-of-concept for the development of aggregation simulation and testing within GridAPPS-D.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗