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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Application of Human-Autonomy Teaming to an Advanced Ground Station for Reduced Crew Operations

Within human factors there is burgeoning interest in the "human-autonomy teaming" (HAT) concept as a way to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous systems as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as "plays." It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations, healthcare and medicine, autonomous vehicles, photography, and aviation. The current paper presents one such effort to apply HAT. It details the design of a HAT agent, developed by Human Automation Teaming Solutions, Inc., to facilitate teamwork between the automation and the human operator of an advanced ground dispatch station. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO); consequently, we have named the agent R-HATS. Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by R-HATS, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, R-HATS determines what tasks need to be completed and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. R-HATS has been designed to both support end users and researchers in RCO and HAT. Additionally, R-HATS and its underlying architecture were developed with generalizability in mind as a modular software applicable outside of RCO/aviation domains. This paper will also discuss future further development and testing of RHATS.

automation↗
NASA NTRS2016

Atmosphere Processing Module Automation and Catalyst Durability Analysis for Mars ISRU Pathfinder

The Mars In-Situ Resource Utilization Pathfinder was designed to create fuel using components found in the planet’s atmosphere and regolith for an ascension vehicle to return a potential sample return or crew return vehicle from Mars. The Atmosphere Processing Module (APM), a subunit of the pathfinder, uses cryocoolers to isolate and collect carbon dioxide from Mars simulant gas. The carbon dioxide is fed with hydrogen into a Sabatier reactor where methane is produced. The APM is currently undergoing the final stages of testing at Kennedy Space Center prior to process integration testing with the other subunits of the pathfinder. The automation software for the APM cryocoolers was tested and found to perform nominally. The catalyst used for the Sabatier reactor was investigated to determine the factors contributing to catalyst failure. The results from the catalyst testing require further analysis, but it appears that the rapid change in temperature during reactor start up or the elevated operating temperature is responsible for the changes observed in the catalyst.

Atmosphere Processing Module↗
NASA NTRS1998

X-33/RLV System Health Management/Vehicle Health Management

To reduce operations costs, Reusable Launch Vehicles (RLVS) must include highly reliable robust subsystems which are designed for simple repair access with a simplified servicing infrastructure, and which incorporate expedited decision-making about faults and anomalies. A key component for the Single Stage To Orbit (SSTO) RLV system used to meet these objectives is System Health Management (SHM). SHM incorporates Vehicle Health Management (VHM), ground processing associated with the vehicle fleet (GVHM), and Ground Infrastructure Health Management (GIHM). The primary objective of SHM is to provide an automated and paperless health decision, maintenance, and logistics system. Sanders, a Lockheed Martin Company, is leading the design, development, and integration of the SHM system for RLV and for X-33 (a sub-scale, sub-orbit Advanced Technology Demonstrator). Many critical technologies are necessary to make SHM (and more specifically VHM) practical, reliable, and cost effective. This paper will present the X-33 SHM design which forms the baseline for the RLV SHM, and it will discuss applications of advanced technologies to future RLVs. In addition, this paper will describe a Virtual Design Environment (VDE) which is being developed for RLV. This VDE will allow for system design engineering, as well as program management teams, to accurately and efficiently evaluate system designs, analyze the behavior of current systems, and predict the feasibility of making smooth and cost-efficient transitions from older technologies to newer ones. The RLV SHM design methodology will reduce program costs, decrease total program life-cycle time, and ultimately increase mission success.

Mouyos, William↗
NASA NTRS2003

Odyssey in Space Human Factors: The Challenges of Going Where No One has Gone Before

Some human factors challenges for space missions include: 1) Reduced Gravity; 2) Remote Operation; 3) Information; 4) Multi-Purpose Design. This viewgraph presentation addresses each of these topics. It describes how the design and layout of equipment on spacecraft can accomodate human activity in a microgravity environment. It describes the remote operation of robotic arms and robots. Displays, procedures, information sharing, and automation are means of conveying information. Multi-purpose design facilitates accomodating and supporting tasks onboard a single vehicle.

Blume, Jenifer Linda↗
NASA NTRS2005

Characterization of Space Shuttle Ascent Debris Aerodynamics Using CFD Methods

An automated Computational Fluid Dynamics process for determining the aerodynamic Characteristics of debris shedding from the Space Shuttle Launch Vehicle during ascent is presented. This process uses Cartesian fully-coupled, six-degree-of-freedom simulations of isolated debris pieces in a Monte Carlo fashion to produce models for the drag and crossrange behavior over a range of debris shapes and shedding scenarios. A validation of the Cartesian methods against ballistic range data for insulating foam debris shapes at flight conditions, as well as validation of the resulting models, are both contained. These models are integrated with the existing shuttle debris transport analysis software to provide an accurate and efficient engineering tool for analyzing debris sources and their potential for damage.

Murman, Scott M.↗
NASA NTRSDate not supplied

Predictive Model for Workload in Remote Operators During sUAS Contingency Scenarios

The increase in automated capabilities of small Uncrewed Aerial Systems (sUAS) has enabled the human operators to manage larger numbers of vehicles simultaneously. As this happens, the operational paradigm shifts to an m:N configuration where multiple operators (m) are managing multiple vehicles (N) together. However, many questions about how operators will interact with each other and share interaction across the vehicle pool are yet unanswered. Therefore, stakeholders from government and industry have partnered to develop ground control station concepts for such operations. The work presented in this paper aims to identify factors that contribute to operator workload. A supervised machine learning-based method built using Support Vector Machines and K-fold cross-validation was used to create workload prediction models for various NASA TLX subscales by leveraging features related to interactions and their relative timings during m:N operations. Results show that the models yielded fairly high predictive accuracies ranging from ~60-75%.

workload prediction↗
NASA NTRS1999

Electronic Systems for Spacecraft Vehicles: Required EDA Tools

The continuous increase in complexity of electronic systems is making the design and manufacturing of such systems more challenging than ever before. As a result, designers are finding it impossible to design efficient systems without the use of sophisticated Electronic Design Automation (EDA) tools. These tools offer integrated simulation of the electrical, mechanical, and manufacturing functions and lead to a correct by design methodology. This report identifies the EDA tools that would be needed to design, analyze, simulate, and evaluate electronic systems for spacecraft vehicles. In addition, the report presents recommendations to enhance the current JSC electronic design capabilities. This includes cost information and a discussion as to the impact, both positive and negative, of implementing the recommendations.

Bachnak, Rafic↗
NASA NTRS2007

Automated Simulation Updates based on Flight Data

A statistically-based method for using flight data to update aerodynamic data tables used in flight simulators is explained and demonstrated. A simplified wind-tunnel aerodynamic database for the F/A-18 aircraft is used as a starting point. Flight data from the NASA F-18 High Alpha Research Vehicle (HARV) is then used to update the data tables so that the resulting aerodynamic model characterizes the aerodynamics of the F-18 HARV. Prediction cases are used to show the effectiveness of the automated method, which requires no ad hoc adjustments by the analyst.

Morelli, Eugene A.↗
DOE OSTI2025

Optimizing Traffic Signal Control to Enhance Transportation Efficiency and Maximize Pedestrian Benefits in the Road Network

Increasing urban mobility requirements demand efficient transportation system strategies for both vehicular and pedestrian movement. This study enhances the Decentralized Graph-based Multi-Agent Reinforcement Learning (DGMARL) approach, originally tailored for vehicular traffic signal timing, to incorporate pedestrian traffic dynamics. The improved algorithm considers crucial metrics such as Eco_PI, assesses vehicle fuel consumption by factoring in stops and delays, and addresses pedestrian waiting time, crucial for system efficiency while acknowledging driver waiting time impact. Utilizing Digital Twin simulation along the MLK Smart Corridor in Chattanooga, Tennessee, the algorithm's performance is compared for various pedestrian control scenarios. To evaluate the effectiveness of DGMARL, this study compared DGMARL-enabled signal management with automated pedestrian traffic detection and an actuated signal management system (real-word baseline) with pedestrian recall, which predetermingly enforces a pedestrian phase every cycle. Findings indicate substantial improvements with DGMARL, showing a 28.29% enhancement in vehicle Eco_PI, a 60.55 % reduction in pedestrian waiting time, and a 55.74% decrease in driver stop delay, on average, compared to the baseline actuated signal timing plan.

Kumarasamy, Vijayalakshmi K [The University of Ten↗
NASA NTRS2018

A Novel Multi-Spacecraft Interplanetary Global Trajectory Optimization Transcription

As the frontier of space exploration continues to advance, so does the design complexity of future interplanetary missions. One avenue of this increasing complexity includes a class of designs known as "Distributed Spacecraft Missions"; missions where multiple spacecraft coordinate to perform shared objectives. Current approaches for the global trajectory optimization of these Multi-Vehicle Missions (MVMs) are prone to shortcomings including laborious iterative design, considerable human-in-the-loop effort, treatment of the multi-vehicle problem as multiple separate trajectory optimization subproblems (resulting in suboptimal solutions where the whole is less than the sum of its parts), and poor handling of coordination objectives and constraints. There are only a handful of software platforms in existence capable of fully-automated, rapid, interplanetary mission and systems global optimization including the Parallel Global Multiobjective Optimizer (PaGMO), the Gravity Assisted Low-thrust Local Optimization Program (GALLOP), and the Evolutionary Mission Trajectory Generator (EMTG). However, none of these tools is capable of performing such tasks for MVM designs. The work outlined in this paper lays the groundwork for a technique to begin addressing these shortcomings. We present a fully-automated technique which frames interplanetary MVMs as Multi-Objective, Multi-Agent Hybrid Optimal Control Problems (MOMA HOCP). First, the basic functionality of this technique is validated on the single-vehicle problem of reproducing the Cassini interplanetary cruise.

Interplanetary↗
NASA NTRS2018

A Novel Multi-Spacecraft Interplanetary Global Trajectory Optimization Transcription

As the frontier of space exploration continues to advance, so does the design complexity of future interplanetary missions. One avenue of this increasing complexity includes a class of designs known as ``Distributed Spacecraft Missions"; missions where multiple spacecraft coordinate to perform shared objectives. Current approaches for the global trajectory optimization of these Multi-Vehicle Missions (MVMs) are prone to shortcomings including laborious iterative design, considerable human-in-the-loop effort, treatment of the multi-vehicle problem as multiple separate trajectory optimization subproblems (resulting in suboptimal solutions where the whole is less than the sum of its parts), and poor handling of coordination objectives and constraints. There are only a handful of software platforms in existence capable of fully-automated, rapid, interplanetary mission and systems global optimization including the Parallel Global Multiobjective Optimizer (PaGMO), the Gravity Assisted Low-thrust Local Optimization Program (GALLOP), and the Evolutionary Mission Trajectory Generator (EMTG). However, none of these tools is capable of performing such tasks for MVM designs. The work outlined in this paper lays the groundwork for a technique to begin addressing these shortcomings. We present a fully-automated technique which frames interplanetary MVMs as Multi-Objective, Multi-Agent Hybrid Optimal Control Problems (MOMA HOCP). First, the basic functionality of this technique is validated on the single-vehicle problem of reproducing the Cassini interplanetary cruise.

Napier, Sean W.↗
NASA NTRS2008

Video Guidance Sensor for Surface Mobility Operations

Robotic systems and surface mobility will play an increased role in future exploration missions. Unlike the LRV during Apollo era which was an astronaut piloted vehicle future systems will include teleoperated and semi-autonomous operations. The tasks given to these vehicles will run the range from infrastructure maintenance, ISRU, and construction to name a few. A common task that may be performed would be the retrieval and deployment of trailer mounted equipment. Operational scenarios may require these operations to be performed remotely via a teleoperated mode,or semi-autonomously. This presentation describes the on-going project to adapt the Automated Rendezvous and Capture (AR&C) sensor developed at the Marshall Space Flight Center for use in an automated trailer pick-up and deployment operation. The sensor which has been successfully demonstrated on-orbit has been mounted on an iRobot/John Deere RGATOR autonomous vehicle for this demonstration which will be completed in the March 2008 time-frame.

Fernandez, Kenneth R.↗
NASA NTRSDate not supplied

Multi-Vehicle (m:N) Operations in the NAS - NASA's Research Plans

The Advanced Air Mobility movement is occurring across the world with goals of enabling, affordable, efficient, accessible, and safe air transportation at a much larger scale than today’s operations, largely enabled by electrification and automation. Transformative and disruptive innovations are emerging that will support an ecosystem designed to transport goods and people to locations not traditionally served by air transportation. To realize the full vision of AAM, technology will be needed to allow a few operators to operate many vehicles (m:N). The benefits of m:N operations are described, along with the current state-of-the-art, barriers, need, and NASA’s plans to address some of the barriers, including a Multi-Vehicle (m:N) Working Group with goals of producing a community-developed operational approval roadmap for various domains.

multi-vehicle↗
NASA NTRS1989

ASTROS: A multidisciplinary automated structural design tool

ASTROS (Automated Structural Optimization System) is a finite-element-based multidisciplinary structural optimization procedure developed under Air Force sponsorship to perform automated preliminary structural design. The design task is the determination of the structural sizes that provide an optimal structure while satisfying numerous constraints from many disciplines. In addition to its automated design features, ASTROS provides a general transient and frequency response capability, as well as a special feature to perform a transient analysis of a vehicle subjected to a nuclear blast. The motivation for the development of a single multidisciplinary design tool is that such a tool can provide improved structural designs in less time than is currently needed. The role of such a tool is even more apparent as modern materials come into widespread use. Balancing conflicting requirements for the structure's strength and stiffness while exploiting the benefits of material anisotropy is perhaps an impossible task without assistance from an automated design tool. Finally, the use of a single tool can bring the design task into better focus among design team members, thereby improving their insight into the overall task.

Neill, D. J.↗
NASA NTRS2017

Automation of POST Cases via External Optimizer and "Artificial p2" Calculation

During conceptual design speed and accuracy are often at odds. Specifically in the realm of launch vehicles, optimizing the ascent trajectory requires a larger pool of analytical power and expertise. Experienced analysts working on familiar vehicles can produce optimal trajectories in a short time frame, however whenever either "experienced" or "familiar " is not applicable the optimization process can become quite lengthy. In order to construct a vehicle agnostic method an established global optimization algorithm is needed. In this work the authors develop an "artificial" error term to map arbitrary control vectors to non-zero error by which a global method can operate. Two global methods are compared alongside Design of Experiments and random sampling and are shown to produce comparable results to analysis done by a human expert.

Dees, Patrick D.↗
NASA NTRS1972

DORCA 2 computer program. Volume 1: User's guide

The Dynamic Operational Requirements and Cost Analysis Program (DORCA 2) is described. The computer program provides a top level analysis tool for NASA and relies on a man machine interaction to optimize results based on external criteria. The computer program relies heavily on outside sources to provide cost information and vehicle parameters. Given data describing mission, vehicles, payloads, containers, space facilities, schedules, cost values, and costing procedures, the program computes flight schedules, cargo manifests, vehicle fleet requirements, acquisition schedules, and cost summaries. The program is designed to consider earth orbit, lunar, interplanetary, and automated satellite missions.

Wray, S. T., Jr.↗
NASA NTRS1973

Structural technologies - Systems challenges and NASA thrusts.

Some significant areas of emphasis in the NASA airframes structures program are highlighted. The topics treated include automated analysis and design processes, building confidence in advanced composites, improving the technology base for future supersonic and hypersonic vehicles, validation of concepts for active control systems, development of predictive methods for aircraft loads and aeroelasticity, and generation of methodology to assure structural integrity as a part of the design process. An integrated long-range program for fatigue and fracture is recommended.

Brooks, G. W.↗
NASA NTRS1996

Dynamics and Control of Orbiting Space Structures NASA Advanced Design Program (ADP)

The report summarizes the advanced design program in the mechanical engineering department at Vanderbilt University for the academic years 1994-1995 and 1995-1996. Approximately 100 students participated in the two years of the subject grant funding. The NASA-oriented design projects that were selected included lightweight hydrogen propellant tank for the reusable launch vehicle, a thermal barrier coating test facility, a piezoelectric motor for space antenna control, and a lightweight satellite for automated materials processing. The NASA supported advanced design program (ADP) has been a success and a number of graduates are working in aerospace and are doing design.

Cruse, T. A.↗