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At least 793 records · Page 44

Information access in a dual-task context: testing a model of optimal strategy selection

Pilots were required to access information from a hierarchical aviation database by navigating under single-task conditions (Experiment 1) and when this task was time-shared with an altitude-monitoring task of varying bandwidth and priority (Experiment 2). In dual-task conditions, pilots had 2 viewports available, 1 always used for the information task and the other to be allocated to either task. Dual-task strategy, inferred from the decision of which task to allocate to the 2nd viewport, revealed that allocation was generally biased in favor of the monitoring task and was only partly sensitive to the difficulty of the 2 tasks and their relative priorities. Some dominant sources of navigational difficulties failed to adaptively influence selection strategy. The implications of the results are to provide tools for jumping to the top of the database, to provide 2 viewports into the common database, and to provide training as to the optimum viewport management strategy in a multitask environment.

User-Computer Interface↗

Influence of a fat layer on the near infrared spectra of human muscle: quantitative analysis based on two-layered Monte Carlo simulations and phantom experiments

The influence of fat thickness on the diffuse reflectance spectra of muscle in the near infrared (NIR) region is studied by Monte Carlo simulations of a two-layer structure and with phantom experiments. A polynomial relationship was established between the fat thickness and the detected diffuse reflectance. The influence of a range of optical coefficients (absorption and reduced scattering) for fat and muscle over the known range of human physiological values was also investigated. Subject-to-subject variation in the fat optical coefficients and thickness can be ignored if the fat thickness is less than 5 mm. A method was proposed to correct the fat thickness influence. c2005 Optical Society of America.

NASA Discipline Life Sciences Technologies↗

Expert system training and control based on the fuzzy relation matrix

Fuzzy knowledge, that for which the terms of reference are not crisp but overlapped, seems to characterize human expertise. This can be shown from the fact that an experienced human operator can control some complex plants better than a computer can. Proposed here is fuzzy theory to build a fuzzy expert relation matrix (FERM) from given rules or/and examples, either in linguistic terms or in numerical values to mimic human processes of perception and decision making. The knowledge base is codified in terms of many implicit fuzzy rules. Fuzzy knowledge thus codified may also be compared with explicit rules specified by a human expert. It can also provide a basis for modeling the human operator and allow comparison of what a human operator says to what he does in practice. Two experiments were performed. In the first, control of liquid in a tank, demonstrates how the FERM knowledge base is elicited and trained. The other shows how to use a FERM, build up from linguistic rules, and to control an inverted pendulum without a dynamic model.

Ren, Jie↗

Multi-Stage System for Automatic Target Recognition

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Chao, Tien-Hsin↗

Petri nets as a modeling tool for discrete concurrent tasks of the human operator

The basic concepts of Petri nets are reviewed as well as their application as the fundamental model of technical systems with concurrent discrete events such as hardware systems and software models of computers. The use of Petri nets is proposed for modeling the human operator dealing with concurrent discrete tasks. Their properties useful in modeling the human operator are discussed and practical examples are given. By means of and experimental investigation of binary concurrent tasks which are presented in a serial manner, the representation of human behavior by Petri nets is demonstrated.

Schumacher, W.↗

Microgravity-Induced Physiological Fluid Redistribution: Computational Analysis to Assess Influence of Physiological Parameters

Space flight impacts human physiology in many ways, the most immediate being the marked cephalad (headward) shift of fluid upon introduction into the microgravity environment. This physiological response to microgravity points to the redistribution of blood and interstitial fluid as a major factor in the loss of venous tone and reduction in heart muscle efficiency which impact astronaut performance. In addition, researchers have hypothesized that a reduction in astronaut visual acuity, part of the Visual Impairment and Intracranial Pressure (VIIP) syndrome, is associated with this redistribution of fluid. VIIP arises within several months of beginning space flight and includes a variety of ophthalmic changes including posterior globe flattening, distension of the optic nerve sheath, and kinking of the optic nerve. We utilize a suite of lumped parameter models to simulate microgravity-induced fluid redistribution in the cardiovascular, central nervous and ocular systems to provide initial and boundary data to a 3D finite element simulation of ocular biomechanics in VIIP. Specifically, the lumped parameter cardiovascular model acts as the primary means of establishing how microgravity, and the associated lack of hydrostatic gradient, impacts fluid redistribution. The cardiovascular model consists of 16 compartments, including three cerebrospinal fluid (CSF) compartments, three cranial blood compartments, and 10 thoracic and lower limb blood compartments. To assess the models capability to address variations in physiological parameters, we completed a formal uncertainty and sensitivity analysis that evaluated the relative importance of 42 input parameters required in the model on relative compartment flows and compartment pressures. Utilizing the model in a pulsatile flow configuration, the sensitivity analysis identified the ten parameters that most influenced each compartment pressure. Generally, each compartment responded appropriately to parameter variations associated with itself and adjacent compartments. However, several unexpected interactions between components, such as between the choroid plexus and the lower capillaries, were found, and are due to simplifications in the formulation of the model. The analysis illustrates that highly influential parameters and those that have unique influences within the model formulation must be tightly controlled for successful model application.

gravitational physiology↗

Computational Investigation of Retropropulsion Operating Environments with a GPU-Enabled Detached Eddy Simulation Approach

Human exploration of the surface of Mars will require an extended powered descent phase of flight, during which aerodynamic-propulsive interference effects can be significant. Characterization of these environments to enable implementation of this technology into a flight vehicle will rely heavily on computational simulation. This work advances the understanding of retropropulsion aerodynamics through application of a massively parallel detached eddy simulation approach on a GPU-accelerated computational framework, yielding data that are largely unachievable with conventional high-performance computing resources. This work includes time-dependent and time-averaged forces and moments on a conceptual, full-scale vehicle in environments and operating conditions relevant to human Mars exploration. Conditions are examined where the engine exhaust flow transitions between over-expanded and under-expanded flow structures, and flight operation will require the ability to maintain control of the vehicle during such a transition. These transitions occur as the vehicle decelerates, and as such, this investigation includes supersonic, transonic, and subsonic flight conditions. Options for vehicle control during powered flight include differential throttling of the engines. This paper provides an overview of the computational campaign, approach, and discussion of results in characterizing the resulting aerodynamics for differential throttling with retropropulsion in atmospheric environments.

EDL↗

Multi-Agent Swarm State of the Art Report

The Next-Generation Multi-Agent Swarm (NGS) Study conducted by NASA’s Ames Research Center for NASA’s Space Technology Mission Directorate (STMD) will develop a comprehensive understanding of emerging multi-agent swarm capabilities. The study aims to identify existing swarm capabilities and asses their potential for persistent lunar space situational awareness, surface monitoring, and distributed autonomy demonstrations. A key objective is to inform the design of a next-generation multi-agent swarm that can perform autonomous distributed remote sensing, position, navigation, and timing (PNT) services, automated deployment that leverages autonomy, edge computing, and interoperable networking to enable cooperative operations without the need for immediate human operation. This study will address specific shortfalls identified by STMD, including intelligent multi-agent constellations, autonomy, edge computation, position, navigation, and timing for small spacecraft, small spacecraft propulsion, and space situational awareness (1625, 1438, 1433, 1557, 1431, 1430, 1589). The NASA Ames Mission Design Center (MDC) will provide subject matter expertise to support systems engineering trades, while experts in autonomy and spacecraft swarms in NASA’s Intelligent Systems Division will lead the study and focus on identifying emerging next-generation swarm capabilities. The study objectives include: capturing the current state-of-the-art for multi-agent swarm capabilities, evaluating technologies and creating technology roadmaps, and developing at least one new technology demonstration mission concept. This initial NGS study report surveys the current state of the art in technology areas relevant for the next-generation multi-agent swarm design. Our primary focus is on surveying relevant deployed space systems1, supplemented with selective analysis of relevant proposed missions and technology developments that have yet to fly.

agent↗

NASA high performance computing and communications program

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 100-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientist's abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects as well as summaries of individual research and development programs within each project.

Holcomb, Lee↗

NASA High Performance Computing and Communications program

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 1(X)-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientists' abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project, exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects, as well as summaries of early accomplishments and the significance, status, and plans for individual research and development programs within each project. Areas of emphasis include benchmarking, testbeds, software and simulation methods.

Holcomb, Lee↗

Computational Modeling of Two Mars Powered Descent Vehicle Concepts Tested in the Langley Unitary Plan Wind Tunnel

Future human Mars missions will require powered descent starting at supersonic conditions, something which has never been done before at Mars. Computational powered descent flowfield simulations have been completed at full-scale Mars conditions, but the available ground test data are not suitable for calibrating computational uncertainties for aerodynamic interference on proposed Mars descent vehicles. Testing was conducted in the NASA Langley Unitary Plan Wind Tunnel in order to investigate the aerodynamic interference of sub-scale versions of two Mars powered descent vehicle concepts at supersonic Mach numbers (2.4 and 3.5): a model based on a blunt hypersonic inflatable aerodynamic decelerator (HIAD) and the second representing a more slender rigid vehicle with body flaps (CobraMRV). This paper covers computational flowfield predictions completed at wind tunnel conditions and comparisons to the test data. On the blowing HIAD models, the time-averaged pressure inboard of the nozzles was generally well-predicted, especially if the nozzles are canted outward, when the nozzles are located further from the nose. At intermediate CobraMRV thrust coefficients, CFD pressures are more accurately predicted than they are for the HIAD models, largely due to the nozzle locations and pointing directions. Overall, the CFD pressure coefficients were predicted within 0.2 of the steady pressure measurements for all blowing models, with smaller discrepancies at higher HIAD thrust, and larger discrepancies at lower HIAD CobraMRV thrust. All HIAD models were predicted to have a gradually decreasing axial force coefficient as the total thrust increases, in agreement with available pressure sensitive paint data. On models with canted nozzles or with nozzles further from the nose, the force coefficient was slightly higher for a given thrust. On the CobraMRV model, the CFD also shows consistent results between solvers and follows trends revealed in the data; the aerodynamic force coefficient remains near the non-blowing value at a tunnel Mach number of 2.4 regardless of thrust, and increases above that level at a Mach number of 3.5, consistent with the discrete pressure data. CFD analysis at tunnel and flight conditions will continue as flight system designs concepts mature.

Supersonic Retropropulsion↗

Computational Modeling of Two Mars Powered Descent Vehicle Concepts Tested in the Langley Unitary Plan Wind Tunnel

Future human Mars missions will require powered descent starting at supersonic conditions, something which has never been done before at Mars. Computational powered descent flowfield simulations have been completed at full-scale Mars conditions, but the available ground test data are not suitable for calibrating computational uncertainties for aerodynamic interference on proposed Mars descent vehicles. Testing was conducted in the NASA Langley Unitary Plan Wind Tunnel in order to investigate the aerodynamic interference of sub-scale versions of two Mars powered descent vehicle concepts at supersonic Mach numbers (2.4 and 3.5): a model based on a blunt hypersonic inflatable aerodynamic decelerator (HIAD) and the second representing a more slender rigid vehicle with body flaps (CobraMRV). This paper covers computational flowfield predictions completed at wind tunnel conditions and comparisons to the test data. On the blowing HIAD models, the time-averaged pressure inboard of the nozzles was generally well-predicted, especially if the nozzles are canted outward, when the nozzles are located further from the nose. At intermediate CobraMRV thrust coefficients, CFD pressures are more accurately predicted than they are for the HIAD models, largely due to the nozzle locations and pointing directions. Overall, the CFD pressure coefficients were predicted within 0.2 of the steady pressure measurements for all blowing models, with smaller discrepancies at higher HIAD thrust, and larger discrepancies at lower HIAD CobraMRV thrust. All HIAD models were predicted to have a gradually decreasing axial force coefficient as the total thrust increases, in agreement with available pressure sensitive paint data. On models with canted nozzles or with nozzles further from the nose, the force coefficient was slightly higher for a given thrust. On the CobraMRV model, the CFD also shows consistent results between solvers and follows trends revealed in the data; the aerodynamic force coefficient remains near the non-blowing value at a tunnel Mach number of 2.4 regardless of thrust, and increases above that level at a Mach number of 3.5, consistent with the discrete pressure data. CFD analysis at tunnel and flight conditions will continue as flight system designs concepts mature.

Supersonic Retropropulsion↗

Overview of a Generalized Numerical Predictor-Corrector Targeting Guidance with Application to Human-Scale Mars Entry, Descent, and Landing

Recent advances in planetary entry guidance algorithms are motived by precision landing criteria for human-scale Mars missions and improved in-space computing capabilities. An NPC targeting guidance algorithm, originally developed for the Mars Surveyor Program 2001 Missions, has been modified and extended to permit a fully generalized, flexible, and robust approach to spacecraft aerocapture and EDL guidance design. This paper describes this generalized targeting NPC guidance (NPCG) and how its modifications enable its use in precision targeting for human missions. System modeling, trajectory propagation, and guidance segment definition and design are described. Finally, the NPCG capability and performance is demonstrated using a human-scale Mars entry, descent, and landing mission simulation.

Rafael A Lugo↗

Effects of adaptive task allocation on monitoring of automated systems

The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.

Task Performance and Analysis↗

Training, transfer, and retention of three-dimensional spatial memory in virtual environments

Human orientation requires one to remember and visualize spatial arrangements of landmarks from different perspectives. Astronauts have reported difficulties remembering relationships between environmental landmarks when imagined in arbitrary 3D orientations. The present study investigated the effects of strategy training on humans' 1) ability to infer their orientation from landmarks presented ahead and below, 2) performance when subsequently learning a different array, and 3) retention of configurational knowledge over time. On the first experiment day, 24 subjects were tested in a virtual cubic chamber in which a picture of an animal was drawn on each wall. Through trial-by-trial exposures, they had to memorize the spatial relationships among the six pictures around them and learn to predict the direction to a specific picture when facing any view direction, and in any roll orientation. Half of the subjects ("strategy group") were taught methods for remembering picture groupings, while the remainder received no such training ("control group"). After learning one picture array, the procedure was repeated in a second. Accuracy (% correct) and response time learning curves were measured. Performance for the second array and configurational memory of both arrays were also retested 1, 7, and 30 days later. Results showed that subjects "learned how to learn" this generic 3D spatial memory task regardless of their relative orientation to the environment, that ability and configurational knowledge was retained for at least a month, that figure rotation ability and field independence correlate with performance, and that teaching subjects specific strategies in advance significantly improves performance. Training astronauts to perform a similar generic 3D spatial memory task, and suggesting strategies in advance, may help them orient in three dimensions.

Non-NASA Center↗

Validation of Cryogenic Propellant Tank Self-Pressurization

NASA’s near-future long-term space missions necessitate advancements in cryogenic fluid management (CFM), which includes safe and reliable long-term propellant storage. Consequently, NASA STMD (Space Technology Mission Directorate) has established the CFM Portfolio Project to improve CFM technologies for upcoming missions. As a part of CFM Modeling Portfolio, NASA Marshall Space Flight Center’s (MSFC) Fluid Dynamics branch within the Propulsion Systems Department is tasked with assessing and improving computational tools used to support flight projects such as Human Lander System and Commercial Lunar Payload Services. One of the challenging modeling problems is that of self-pressurization of propellant tank due to heat leakage over long time periods. Reduced order and nodal tools find it extremely difficult to accurately predict self-pressurization under transient conditions or where complex flow patterns or thermal gradients exist, and application of 3-D CFD (computational fluid dynamics) simulations is necessary to characterize these problems. Until recently, CFD simulations for these long-term processes (order of hours or days) have been too impractical to conduct due to prohibitive wall time and computational resource requirements. The requisite CFD tool need to be efficient, computationally scalable, modular with ability to incorporate various physics models, and robust enough to not accumulate conservation errors over several hours of simulated time. NASA MSFC’s Loci-Stream CFD tool along with the VOF module is a great candidate to fit this mold. In this paper, we validate Loci-Stream for predicting self-pressurization of a flight scale propellant tank so it can serve as a reliable design and analysis tool for NASA’s CFM application needs. Liquid hydrogen tank pressurization tests carried out at the K-site testing facility provide a reliable data set for this purpose. These tests were simulated using Loci-Stream solver with VOF module as well as a hybrid approach which uses a lumped model for the ullage gas domain and CFD simulation of the liquid propellant. Both are shown to have very good predictive capabilities over multiple K-site experiments.

Hong Q. Yang↗

Validation of Cryogenic Propellant Tank Self-Pressurization

NASA's near-future long-term space missions necessitate advancements in cryogenic fluid management (CFM), which includes safe and reliable long-term propellant storage. Consequently, NASA STMD (Space Technology Mission Directorate) has established the CFM Portfolio Project to improve CFM technologies for upcoming missions. As a part of CFM Modeling Portfolio, NASA Marshall Space Flight Center's (MSFC) Fluid Dynamics branch within the Propulsion Systems Department is tasked with assessing and improving computational tools used to support flight projects such as Human Lander System and Commercial Lunar Payload Services. One of the challenging modeling problems is that of self-pressurization of propellant tank due to heat leakage over long time periods. Reduced order and nodal tools find it extremely difficult to accurately predict self-pressurization under transient conditions or where complex flow patterns or thermal gradients exist, and application of 3-D CFD (computational fluid dynamics) simulations is necessary to characterize these problems. Until recently, CFD simulations for these long-term processes (order of hours or days) have been too impractical to conduct due to prohibitive wall time and computational resource requirements. The requisite CFD tool need to be efficient, computationally scalable, modular with ability to incorporate various physics models, and robust enough to not accumulate conservation errors over several hours of simulated time. NASA MSFC's Loci-Stream CFD tool along with the VOF module is a great candidate to fit this mold. In this paper, we validate Loci-Stream for predicting self-pressurization of a flight scale propellant tank so it can serve as a reliable design and analysis tool for NASA's CFM application needs. Liquid hydrogen tank pressurization tests carried out at the K-site testing facility provide a reliable data set for this purpose. These tests were simulated using Loci-Stream solver with VOF module as well as a hybrid approach which uses a lumped model for the ullage gas domain and CFD simulation of the liquid propellant. Both are shown to have very good predictive capabilities over multiple K-site experiments.

cryogenic fluid management↗