Results for “Research process automation” — Page 19

NASA NTRS1991

Robot graphic simulation testbed

The objective of this research was twofold. First, the basic capabilities of ROBOSIM (graphical simulation system) were improved and extended by taking advantage of advanced graphic workstation technology and artificial intelligence programming techniques. Second, the scope of the graphic simulation testbed was extended to include general problems of Space Station automation. Hardware support for 3-D graphics and high processing performance make high resolution solid modeling, collision detection, and simulation of structural dynamics computationally feasible. The Space Station is a complex system with many interacting subsystems. Design and testing of automation concepts demand modeling of the affected processes, their interactions, and that of the proposed control systems. The automation testbed was designed to facilitate studies in Space Station automation concepts.

Cook, George E.↗

NASA NTRS1991

Theoretical foundations for information representation and constraint specification

Research accomplished at the Knowledge Based Systems Laboratory of the Department of Industrial Engineering at Texas A&M University is described. Outlined here are the theoretical foundations necessary to construct a Neutral Information Representation Scheme (NIRS), which will allow for automated data transfer and translation between model languages, procedural programming languages, database languages, transaction and process languages, and knowledge representation and reasoning control languages for information system specification.

Menzel, Christopher P.↗

NASA NTRS1978

Manufacturing Process Applications Team (MATeam)

The activities of the Manufacturing Process Applications Team concerning the promotion of joint Industry/Federal Agency/NASA funded research and technology operating plan (RTOP) programs are reported. Direct transfers occurred in cutting tools, laser wire stripping, soldering, and portable X-ray unit technology. TROP program funding approval was obtained for the further development of the cutting tool Sialon and development of an automated nondestructive fracture toughness testing system.

Source record↗

NASA NTRS1993

Value added data archiving

Researchers in the Molecular Sciences Research Center (MSRC) of Pacific Northwest Laboratory (PNL) currently generate massive amounts of scientific data. The amount of data that will need to be managed by the turn of the century is expected to increase significantly. Automated tools that support the management, maintenance, and sharing of this data are minimal. Researchers typically manage their own data by physically moving datasets to and from long term storage devices and recording a dataset's historical information in a laboratory notebook. Even though it is not the most efficient use of resources, researchers have tolerated the process. The solution to this problem will evolve over the next three years in three phases. PNL plans to add sophistication to existing multilevel file system (MLFS) software by integrating it with an object database management system (ODBMS). The first phase in the evolution is currently underway. A prototype system of limited scale is being used to gather information that will feed into the next two phases. This paper describes the prototype system, identifies the successes and problems/complications experienced to date, and outlines PNL's long term goals and objectives in providing a permanent solution.

Berard, Peter R.↗

NASA NTRS2007

Modeling Spacecraft Fuel Slosh at Embry-Riddle Aeronautical University

As a NASA-sponsored GSRP Fellow, I worked with other researchers and analysts at Embry-Riddle Aeronautical University and NASA's ELV Division to investigate the effect of spacecraft fuel slosh. NASA's research into the effects of fuel slosh includes modeling the response in full-sized tanks using equipment such as the Spinning Slosh Test Rig (SSTR), located at Southwest Research Institute (SwRI). NASA and SwRI engineers analyze data taken from SSTR runs and hand-derive equations of motion to identify model parameters and characterize the sloshing motion. With guidance from my faculty advisor, Dr. Sathya Gangadharan, and NASA flight controls analysts James Sudermann and Charles Walker, I set out to automate this parameter identification process by building a simple physical experimental setup to model free surface slosh in a spherical tank with a simple pendulum analog. This setup was then modeled using Simulink and SimMechanics. The Simulink Parameter Estimation Tool was then used to identify the model parameters.

Schlee, Keith L.↗

NASA NTRS1998

Flight Operations in the New Millennium

New approaches are being studied for real-time interaction and related supporting processes with spacecraft and instruments in deep space. Spacecraft are evolving, improving in many ways, and generally becoming more robust. Opertions is changing also. Operatins will be more automated in the future. However, there is a chanllenge. Deep space missions are not all alike. The Operations phases of discovery and exploration are an extension of the research that creates the mission; they are the time of obtaining results.

New↗

NASA NTRS1993

Brain wave correlates of attentional states: Event related potentials and quantitative EEG analysis during performance of cognitive and perceptual tasks

The increased use of automation in the cockpits of commercial planes has dramatically decreased the workload requirements of pilots, enabling them to function more efficiently and with a higher degree of safety. Unfortunately, advances in technology have led to an unexpected problem: the decreased demands on pilots have increased the probability of inducing 'hazardous states of awareness.' A hazardous state of awareness is defined as a decreased level of alertness or arousal which makes an individual less capable of reacting to unique or emergency types of situations. These states tend to be induced when an individual is not actively processing information. Under such conditions a person is likely to let his/her mind wander, either to internal states or to irrelevant external conditions. As a result, they are less capable of reacting quickly to emergency situations. Since emergencies are relatively rare, and since the high automated cockpit requires progressively decreasing levels of engagement, the probability of being seduced into a lowered state of awareness is increasing. This further decreases the readiness of the pilot to react to unique circumstances such as system failures. The HEM Lab at NASA-Langley Research Center has been studying how these states of awareness are induced and what the physiological correlates of these different states are. Specifically, they have been interested in studying electroencephalographic (EEG) measures of different states of alertness to determine if such states can be identified and, hopefully, avoided. The project worked on this summer involved analyzing the EEG and the event related potentials (ERP) data collected while subjects performed under two conditions. Each condition required subjects to perform a relatively boring vigilance task. The purpose of using these tasks was to induce a decreased state of awareness while still requiring the subject to process information. Each task involved identifying an infrequently presented target stimulus. In addition to the task requirements, irrelevant tones were presented in the background. Research has shown that even though these stimuli are not attended, ERP's to them can still be elicited. The amplitude of the ERP waves has been shown to change as a function of a person's level of alertness. ERP's were also collected and analyzed for the target stimuli for each task. Brain maps were produced based on the ERP voltages for the different stimuli. In addition to the ERP's, a quantitative EEG (QEEG) was performed on the data using a fast Fourier technique to produce a power spectral analysis of the EEG. This analysis was conducted on the continuous EEG while the subjects were performing the tasks. Finally, a QEEG was performed on periods during the task when subjects indicated that they were in an altered state of awareness. During the tasks, subjects were asked to indicate by pressing a button when they realized their level of task awareness had changed. EEG epochs were collected for times just before and just after subjects made this reponse. The purpose of this final analysis was to determine whether or not subjective indices of level of awareness could be correlated with different patterns of EEG.

Freeman, Frederick G.↗

NASA NTRS1982

Large-area silicon sheet task

A set of computer models was used to define a growth system configuration that was then built and used to grow web with lower thermally generated stress. Aspects of research in the edge-defined film-fed growth (EFG) method of making Si ribbon are reported. A technique was developed to determine base resistivity and carrier lifetime in semicrystalline wafers. Automated growth of 150 kg of 15 cm-dia ingot material per crucible is reviewed. Scanning transmisson electron microscopy (STEM) and microprobe investigations of processed EFG ribbon are reported. The chemical composition of the large precipitates was studied. The structural arrangement and the electrical activity of distentions or close to the central twin plane in processed material were studied. The electrical and structural properties of grain boundaries in silicon are discussed. Temperature-dependence measurements of zero-bias conductance, a photoconductivity technique, and deep-level transient spectroscopy (DLTS) were developed. A grooving and staining technique, secondary ion mass spectroscopy, and EBIC measurements in scanning electron microscopy were used to study enhanced diffusion of phosphorus at grain boundaries in polycrystaline silicon. The fundamental mechanisms of abrasion and wear and the deformation of Si by a diamond in various fluid environments are described. The efficiency of solar cells made from EFG ribbon and Semix Inc. material is reported.

Morrison, A. D.↗

NASA NTRS1986

An artificial intelligence approach to onboard fault monitoring and diagnosis for aircraft applications

Real-time onboard fault monitoring and diagnosis for aircraft applications, whether performed by the human pilot or by automation, presents many difficult problems. Quick response to failures may be critical, the pilot often must compensate for the failure while diagnosing it, his information about the state of the aircraft is often incomplete, and the behavior of the aircraft changes as the effect of the failure propagates through the system. A research effort was initiated to identify guidelines for automation of onboard fault monitoring and diagnosis and associated crew interfaces. The effort began by determining the flight crew's information requirements for fault monitoring and diagnosis and the various reasoning strategies they use. Based on this information, a conceptual architecture was developed for the fault monitoring and diagnosis process. This architecture represents an approach and a framework which, once incorporated with the necessary detail and knowledge, can be a fully operational fault monitoring and diagnosis system, as well as providing the basis for comparison of this approach to other fault monitoring and diagnosis concepts. The architecture encompasses all aspects of the aircraft's operation, including navigation, guidance and controls, and subsystem status. The portion of the architecture that encompasses subsystem monitoring and diagnosis was implemented for an aircraft turbofan engine to explore and demonstrate the AI concepts involved. This paper describes the architecture and the implementation for the engine subsystem.

Schutte, P. C.↗

NASA NTRS1994

Development and application of structural dynamics analysis capabilities

Extensive research activities were performed in the area of multidisciplinary modeling and simulation of aerospace vehicles that are relevant to NASA Dryden Flight Research Facility. The efforts involved theoretical development, computer coding, and debugging of the STARS code. New solution procedures were developed in such areas as structures, CFD, and graphics, among others. Furthermore, systems-oriented codes were developed for rendering the code truly multidisciplinary and rather automated in nature. Also, work was performed in pre- and post-processing of engineering analysis data.

Heinemann, Klaus W.↗

NASA NTRS2005

Automated Status Notification System

NASA Lewis Research Center's Automated Status Notification System (ASNS) was born out of need. To prevent "hacker attacks," Lewis' telephone system needed to monitor communications activities 24 hr a day, 7 days a week. With decreasing staff resources, this continuous monitoring had to be automated. By utilizing existing communications hardware, a UNIX workstation, and NAWK (a pattern scanning and processing language), we implemented a continuous monitoring system.

Source record↗

NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

NASA NTRSDate not supplied

Selection Factors for Space Crops

NASA is actively researching space crop production to determine its potential to contribute to food system security on long duration missions beyond Low Earth Orbit. Our near-term focus is on nutrient and variety supplementation of prepackaged food with fresh produce that requires little or no processing. The longer-term goal is caloric replacement to become less dependent on Earth, and this will require cultivation of staple crops, processing and cooking equipment, integration with spacecraft air, water, and power systems, and automation. There are numerous technology and knowledge gaps remaining for sustainable space crop production systems, but one high-impact area is in the development of crops specifically customized to meet the needs of controlled environment crop production, astronaut health and well-being, and space-unique environments. Modern crop breeding and genome engineering tools are allowing for rapid development of new genotypes with incredible specificity. Targeted aspects to optimize crops for space have been identified and characterized into five categories: plant growth and development, plant physiology, produce nutrition, produce organoleptic acceptability, and postharvest characteristics. Within each category there are several targets that further the development of crop production systems for spaceflight, such as crop size and harvest index, tolerance to specific environmental stresses, optimizing target nutrients that are low or degrade in the packaged diet, maintenance time requirements, and less indigestible structural material. NASA-funded PIs are already beginning to develop candidate crops, and spaceflight testing and validation of novel space crops is on the horizon. Crops developed for space also have the potential to benefit terrestrial controlled environment agriculture crop production systems. This research was supported by NASA’s Space Biology and Human Research Programs.

Space Crop Production↗

NASA NTRSDate not supplied

Selection Factors for Space Crops

NASA is actively researching space crop production to determine its potential to contribute to food system security on long duration missions beyond Low Earth Orbit. Our near-term focus is on nutrient and variety supplementation of prepackaged food with fresh produce that requires little or no processing. The longer-term goal is caloric replacement to become less dependent on Earth, and this will require cultivation of staple crops, processing and cooking equipment, integration with spacecraft air, water, and power systems, and automation. There are numerous technology and knowledge gaps remaining for sustainable space crop production systems, but one high-impact area is in the development of crops specifically customized to meet the needs of controlled environment crop production, astronaut health and well-being, and space-unique environments. Modern crop breeding and genome engineering tools are allowing for rapid development of new genotypes with incredible specificity. Targeted aspects to optimize crops for space have been identified and characterized into five categories: plant growth and development, plant physiology, produce nutrition, produce organoleptic acceptability, and postharvest characteristics. Within each category there are several targets that further the development of crop production systems for spaceflight, such as crop size and harvest index, tolerance to specific environmental stresses, optimizing target nutrients that are low or degrade in the packaged diet, maintenance time requirements, and less indigestible structural material. NASA-funded PIs are already beginning to develop candidate crops, and spaceflight testing and validation of novel space crops is on the horizon. Crops developed for space also have the potential to benefit terrestrial controlled environment agriculture crop production systems. This research was supported by NASA’s Space Biology and Human Research Programs.

Space Crop Production↗

NASA NTRS1989

Overcoming limitations of model-based diagnostic reasoning systems

The development of a model-based diagnostic system to overcome the limitations of model-based reasoning systems is discussed. It is noted that model-based reasoning techniques can be used to analyze the failure behavior and diagnosability of system and circuit designs as part of the system process itself. One goal of current research is the development of a diagnostic algorithm which can reason efficiently about large numbers of diagnostic suspects and can handle both combinational and sequential circuits. A second goal is to address the model-creation problem by developing an approach for using design models to construct the GMODS model in an automated fashion.

Holtzblatt, Lester J.↗

NASA NTRS1990

A curriculum for real-time computer and control systems engineering

An outline of a syllabus for the education of real-time-systems engineers is given. This comprises the treatment of basic concepts, real-time software engineering, and programming in high-level real-time languages, real-time operating systems with special emphasis on such topics as task scheduling, hardware architectures, and especially distributed automation structures, process interfacing, system reliability and fault-tolerance, and integrated project development support systems. Accompanying course material and laboratory work are outlined, and suggestions for establishing a laboratory with advanced, but low-cost, hardware and software are provided. How the curriculum can be extended into a second semester is discussed, and areas for possible graduate research are listed. The suitable selection of a high-level real-time language and supporting operating system for teaching purposes is considered.

Halang, Wolfgang A.↗

NASA NTRSDate not supplied

Aerospace Cognitive Engineering Laboratory (ACELAB) Simulator for Electric Vertical Takeoff and Landing (eVOTL) Research and Development

A new generation of aerospace innovators are looking for ways to quickly and efficiently transport people in a safe and environmentally friendly manner. In the not-too-distant future, passengers and goods are expected to routinely fly aboard a new breed of cleaner, smarter air vehicles. This represents a new and significant challenge to the Federal Aviation Agency (FAA) which is responsible for aircraft certification, pilot licensing, operating approval and airspace integration. To help streamline this process, NASA has formulated its Advanced Air Mobility (AAM) project to provide research capabilities for development and evaluation of these new concepts and an environment where industry and regulators can work together to understand the requirements and work toward consensus standards for the new market. This paper will describe the development of the Aerospace Cognitive Engineering Lab Rapid Automation Test (ACELeRATE) simulator. ACELeRATE is an adaptable fixed-base aircraft simulator focused on the investigation of the performance and interaction of pilots and increasingly automated aircraft systems. ACELeRATE can be re-configured to support various simulation environments. The simulator includes a simple reconfigurable cockpit placed within a 10-foot spherical dome with a cluster of real-time image generators, high-resolution displays and highly realistic scenery with the surrounding digital terrain and required cultural area details (e.g., hangars, runways, ramp areas, taxiways, test range apparatus, buildings with designated rooftop landing areas, and other man-made 3D structures). This paper will also describe the various hardware and software tools employed in the ACELeRATE simulator, including engineering tools used by NASA for electric Vertical Takeoff and Landing (eVTOL) vehicle equations of motion, wind-model simulation in an urban environment, as well as the various modeling techniques and tools used to quickly generate highly realistic 3D terrain models for low level flight including urban terrain and obstacle depictions.

AAM Simulation Cockpit↗