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At least 1,531 records · Page 85

Quantitative water quality with ERTS-1

Analyses of ERTS-1 MSS computer compatible tapes of reservoir scenes in Kansas along with ground truth show that MSS bands and band ratios can be used for reliable prediction of suspended loads up to at least 900 ppm. The major reservoirs in Kansas, as well as in other Great Plains states, are playing increasingly important roles in flood control, recreation, agriculture, and urban water supply. Satellite imagery is proving useful for acquiring timely low cost water quality data required for optimum management of these fresh water resources.

Yarger, H. L.↗

Status of input design for aircraft parameter identification

Results are presented on the design of aircraft inputs (i.e. elevator, rudder and aeleron deflection time histories) to identify aircraft stability and control derivatives from flight test data. The problem is first reduced to an optimization problem with differential and integral constraints. The criteria used are either expressed in terms of the Cramer-Rao lower bound on the covariance matrix of the parameter estimates or in terms of the maximum prediction error variance. Both time-domain longitudinal and lateral dynamics of C-8 and Jet Star aircrafts and comparison with doublet type inputs are made.

Mehra, R. K.↗

The X-29 flight-research program

The X-29 experimental aircraft, which is a technology integration and evaluation platform for such features as static longitudinal instability, sweptforward wings and three-surface longitudinal control, offers an opportunity to validate the entire aircrft design process through careful correlation and comparison of flight test results with wind tunnel results and design predictions. Attention is presently given to the design features of the aircraft, which encompass supercritical airfoils, digital flight control, and aeroelastically tailored composite wings, as well as to the flight test program that was formulated to investigate the interactions and relative merits of these design features, in light of data gathered by carefully positioned sensors.

Putnam, T. W.↗

Characterization of good teleoperators - What aptitudes, interests, and experience correlate with measures of teleoperator performance

The use of aptitude tests and questionnaries to evaluate an individuals aptitude for teleoperation is studied. The Raven Progressive Matrices Test and Differential Aptitude Tests, and a 16-item questionnaire for assessing the subject's interests, academic background, and previous experience are described. The Proto-Flight Manipulator Arm, cameras, console, hand controller, and task board utilized by the 17 engineers are examined. The correlation between aptitude scores and questionnaire responses, and operator performance is investigated. Multiple regression data reveal that the eight predictor variables are not individually significant for evaluating operator performance; however, the complete test battery is applicable for predicting 49 percent of subject variance on the criterion task.

Yorchak, J. P.↗

Lunar and Planetary Science XXXV: Mars Impact Cratering

This document discusses the following topics: High Resolution Digital Elevation Models of Pristine Explosion Craters; Crater Degradation in the Martian Highlands: Morphometric Analysis of the Sinus Sabaeus Region and Simulation Modeling Suggest Fluvial Processes; Analysis of Impact Crater Preservation on Mars Using THEMIS Data; Atmospheric Entry Studies and the Smallest Impact Craters on Mars; Updating the Crater Count Chronology System for Mars; Control of Impact Crater-related Fracture Systems on the Subsurface Hydrology and Ground Collapse; Quantitative Analyses of Terrestrial Crater Deposits: Constraining Formation and Sediment Transport Processes on Mars; and Predicted Effects of Surface Processes on Martian Impact Crater Depth/Diameter Relationships

Stephen J Mackwell↗

Materials Science Research Rack Onboard the International Space Station Hardware and Operations

The Materials Science Research Rack (MSRR) is a research facility developed under a cooperative research agreement between NASA and ESA for materials science investigations on the International Space Station (ISS). MSRR was launched on STS-128 in August 2009, and is currently installed in the U.S. Destiny Laboratory Module. Since that time, MSRR has performed virtually flawlessly, logging more than 620 hours of operating time. The MSRR accommodates advanced investigations in the microgravity environment on the ISS for basic materials science research in areas such as solidification of metals and alloys. The purpose is to advance the scientific understanding of materials processing as affected by microgravity and to gain insight into the physical behavior of materials processing. MSRR allows for the study of a variety of materials including metals, ceramics, semiconductor crystals, and glasses. Materials science research benefits from the microgravity environment of space, where the researcher can better isolate chemical and thermal properties of materials from the effects of gravity. With this knowledge, reliable predictions can be made about the conditions required on Earth to achieve improved materials. MSRR is a highly automated facility with a modular design capable of supporting multiple types of investigations. Currently the NASA-provided Rack Support Subsystem provides services (power, thermal control, vacuum access, and command and data handling) to the ESA developed Materials Science Laboratory (MSL) which accommodates interchangeable Furnace Inserts (FI). Two ESA-developed FIs are presently available on the ISS: the Low Gradient Furnace (LGF) and the Solidification and Quenching Furnace (SQF). Sample-Cartridge Assemblies (SCAs), each containing one or more material samples, are installed in the FI by the crew and can be processed at temperatures up to 1400 C. Once an SCA is installed, the experiment can be run by automatic command or science conducted via telemetry commands from the ground. Initially, 12 SCAs were processed in the first furnace insert for a team of European and US investigators. After these samples were processed the Furnaces Inserts were exchanged and an additional single sample was processed. The processed samples have been returned to Earth for evaluation and comparison of their properties to samples similarly processed on the ground. A preliminary examination of the samples indicates that the majority of the desired science objectives have been successfully met leading to significant improvements in the understanding of alloy solidification processes. Six SCAs were launched on Space Shuttle Mission STS-135 in July 2011 for processing during the Fall of 2011. Additional batches are planned for future processing. This facility is available to support additional materials science investigations through programs such as the US National Laboratory, Technology Development, NASA Research Announcements, and others.

Lehman, John R.↗

MSRR Rack Materials Science Research Rack

The Materials Science Research Rack (MSRR) is a research facility developed under a cooperative research agreement between NASA and the European Space Agency (ESA) for materials science investigations on the International Space Station (ISS). The MSRR is managed at the Marshall Space Flight Center (MSFC) in Huntsville, AL. The MSRR facility subsystems were manufactured by Teledyne Brown Engineering (TBE) and integrated with the ESA/EADS-Astrium developed Materials Science Laboratory (MSL) at the MSFC Space Station Integration and Test Facility (SSITF) as part of the Systems Development Operations Support (SDOS) contract. MSRR was launched on STS-128 in August 2009, and is currently installed in the U. S. Destiny Laboratory Module on the ISS. Materials science is an integral part of developing new, safer, stronger, more durable materials for use throughout everyday life. The goal of studying materials processing in space is to develop a better understanding of the chemical and physical mechanisms involved, and how they differ in the microgravity environment of space. To that end, the MSRR accommodates advanced investigations in the microgravity environment of the ISS for basic materials science research in areas such as solidification of metals and alloys. MSRR allows for the study of a variety of materials including metals, ceramics, semiconductor crystals, and glasses. Materials science research benefits from the microgravity environment of space, where the researcher can better isolate chemical and thermal properties of materials from the effects of gravity. With this knowledge, reliable predictions can be made about the conditions required on Earth to achieve improved materials. MSRR is a highly automated facility with a modular design capable of supporting multiple types of investigations. Currently the NASA-provided Rack Support Subsystem provides services (power, thermal control, vacuum access, and command and data handling) to the ESA developed Materials Science Laboratory (MSL) which accommodates interchangeable Furnace Inserts (FI). Two ESA-developed FIs are presently available on the ISS: the Low Gradient Furnace (LGF) and the Solidification and Quenching Furnace (SQF). Sample-Cartridge Assemblies (SCAs), each containing one or more material samples, are installed in the FI by the crew and can be processed at temperatures up to 1400 C. Once an SCA is installed, the experiment can be run by automatic command or science conducted via telemetry commands from the ground. This facility is available to support materials science investigations through programs such as the US National Laboratory, Technology Development, NASA Research Announcements, and others. TBE and MSFC are currently developing NASA Sample Cartridge Assemblies (SCA's) with a planned availability for launch in 2017.

Reagan, Shawn↗

Effects of Eye Measures on Human Controller Remnant and Control Behavior

The aim of the current research was to investigate the possible relation between changes in eye activity parameters, variations in human remnant at the perceptual level and changes in human operator model parameters. Fourteen subjects performed a pitch tracking task, in which the display brightness was varied by changing the background color around a simplified primary flight display, in order to create a controlled, quasilinear change in the pupil diameter through the pupillary light reflex. Pupil diameter, blink, eye opening, and opening and closing amplitudes and speeds were recorded using an eye tracker. Participants controlled single integrator-like and double integrator-like dynamics. The variation in pupil diameter did not introduce significant differences in neither remnant characteristics nor the human operator model parameters. An interesting effect occurred in the human controller’s time delay for the single integrator task, where the time delay was significantly higher for the darkest brightness compared to the other levels of brightness. This effect was not observed for the double integrator dynamics. Data suggested that the more difficult controlled dynamics induced a squinting effect, visible in smaller eye opening, and smaller eye opening and closing amplitudes. These results suggest that performance, and control behavior are invariant to the display brightness. Moreover, monitoring changes in the eye activity could represent a method of predicting variations in human remnant characteristics and human controller model parameters, introduced by task difficulty.

Eye tracking↗

A Step Towards Machine Learning-based Coherent Generator Grouping for Emergency Control Applications in Modern Power Grid

A dynamic neural network (NN) based multi-class classifier is proposed for improving online prediction of coherent generator groups (CGGs), following the occurrences of various contingencies in the power grid. This is motivated by the increasing availability of the measurements from phasor measurement units (PMUs) and the number of grouping schemes is limited. The proposed method consists of three steps. First, by performing offline simulations, a library of system dynamic responses characterized by post-contingency rotor angles and speeds of individual generators is obtained. To generate sufficient data, up to N-2 contingencies and the uncertain parameters associated with the power grid including type and location of disturbance and fault clearing times are modeled. Secondly, the training data-set is produced by generating labels for individual contingencies using a hierarchical clustering method based on rotor angle and speed data. Lastly, the dynamic NN models are trained for online applications such as emergency controls and controlled islanding. The proposed method is tested on the standard 16-generator 68-bus system to demonstrate its performance. Furthermore, the impact of the sample data lengths on the CGG numbers is evaluated. It is interesting to observe that the time domain stability behaviors can be determined by examining the changes in the CGG numbers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Mountain-Top-to-Mountain-Top Optical Link Demonstration

A mountain-top-to-mountain-top optical communications demonstration was conducted between the JPL Table Mountain Facility (TMF), Wrightwood, California, and Strawberry Peak (SP), Lake Arrowhead, California, during the months of August and September of 2000. The link was nearly horizontal at an altitude of 2 km and spanned a range of 46.8 km. A 780-nm multibeam beacon broadcast from TMF was received by the JPL Optical Communications Demonstrator (OCD) located at SP. The received beacon was utilized as a pointing reference to retransmit an 852-nm communications laser beam, modulated at 400 Mb/s by a PN7 pseudo-random bit stream (PRBS) sequence. The long atmospheric path resulted in atmospheric-turbulence-induced angle-of-arrival fluctuations of the beacon at the OCD aperture. A .ne-steering control loop was used to track the resulting beacon centroid motion and update the pointing of the communications laser beam transmitted from SP to TMF. Fried parameters, or r0, inferred from focal spot sizes received at SP were 4 to 5 cm whereas, using the spot sizes received at TMF, they were 2 to 3 cm. In both cases, theory predicts larger r0 values. The predicted angle-of-arrival fluctuations compare well with measured rms displacements exhibited by the focal spots at either end of the link. An uncompensated error of ~1.1 rad in the x-axis and ~2 rad in the y-axis was obtained using centroid data logged by the OCD. Average bit-error rates of 10-5 were recorded for extended periods of time. An atmospheric coherence length r0 of 3 to 5 cm was inferred using the focal-plane spot size measured on the CCD tracking sensor and compared to a predicted value of 5 to 7 cm using reasonable atmospheric models. The irradiance bounds required for the CCD tracking sensor to perform centroiding was found to range from 2000 to 3000 integrated pixel counts, although a more reliable range was 600 to 3000, indicating a dynamic range of 6 to 11 dB. The motion of the spot on the focal plane was also recorded and yielded rms angle-of-arrival-induced focal-plane displacement of 9 to 11 m, compared to a predicted value of 7.8 to 11 m. The irradiance measurements made with the OCD clearly indicate that best tracking performance is obtained when the mean received signal is 2000 to 2200 counts. The best tracking performance resulted in an rms uncompensated error of 1.1 rad. The uncompensated error appeared to increase with either an increase or decrease in mean beacon-signal level. The rms uncompensated error determined by deriving the beacon displacement power spectral density from the beacon centroid-versustime data and the rejection function of the control loop yielded a higher value of 3.4 rad.

Biswas, A.↗

Parametric Studies of Flow Separation using Air Injection

Boundary Layer separation causes the airfoil to stall and therefore imposes dramatic performance degradation on the airfoil. In recent years, flow separation control has been one of the active research areas in the field of aerodynamics due to its promising performance improvements on the lifting device. These active flow separation control techniques include steady and unsteady air injection as well as suction on the airfoil surface etc. This paper will be focusing on the steady and unsteady air injection on the airfoil. Although wind tunnel experiments revealed that the performance improvements on the airfoil using injection techniques, the details of how the key variables such as air injection slot geometry and air injection angle etc impact the effectiveness of flow separation control via air injection has not been studied. A parametric study of both steady and unsteady air injection active flow control will be the main objective for this summer. For steady injection, the key variables include the slot geometry, orientation, spacing, air injection velocity as well as the injection angle. For unsteady injection, the injection frequency will also be investigated. Key metrics such as lift coefficient, drag coefficient, total pressure loss and total injection mass will be used to measure the effectiveness of the control technique. A design of experiments using the Box-Behnken Design is set up in order to determine how each of the variables affects each of the key metrics. Design of experiment is used so that the number of experimental runs will be at minimum and still be able to predict which variables are the key contributors to the responses. The experiments will then be conducted in the 1ft by 1ft wind tunnel according to the design of experiment settings. The data obtained from the experiments will be imported into JMP, statistical software, to generate sets of response surface equations which represent the statistical empirical model for each of the metrics as a function of the key variables. Next, the variables such as the slot geometry can be optimized using the build-in optimizer within JMP. Finally, a wind tunnel testing will be conducted using the optimized slot geometry and other key variables to verify the empirical statistical model. The long term goal for this effort is to assess the impacts of active flow control using air injection at system level as one of the task plan included in the NASAs URETI program with Georgia Institute of Technology.

Zhang, Wei↗

A review of artificial intelligence applications in manufacturing operations

Abstract Artificial intelligence (AI) and machine learning (ML) can improve manufacturing efficiency, productivity, and sustainability. However, using AI in manufacturing also presents several challenges, including issues with data acquisition and management, human resources, infrastructure, as well as security risks, trust, and implementation challenges. For example, getting the data needed to train AI models can be difficult for rare events or costly for large datasets that need labeling. AI models can also pose security risks when integrated into industrial control systems. In addition, some industry players may be hesitant to use AI due to a lack of trust or understanding of how it works. Despite these challenges, AI has the potential to be extremely helpful in manufacturing, particularly in applications such as predictive maintenance, quality assurance, and process optimization. It is important to consider the specific needs and capabilities of each manufacturing scenario when deciding whether and how to use AI in manufacturing. This review identifies current developments, challenges, and future directions in AI/ML relevant to manufacturing, with the goal of improving understanding of AI/ML technologies available for solving manufacturing problems, providing decision‐support for prioritizing and selecting appropriate AI/ML technologies, and identifying areas where further research can yield transformational returns for the industry. Early experience suggests that AI/ML can have significant cost and efficiency benefits in manufacturing, especially when combined with the ability to capture enormous amounts of data from manufacturing systems.

Plathottam, Siby Jose↗

A general infrastructure for data-driven control design and implementation in tokamaks

A general infrastructure for tokamak controllers based on data-driven neural net models is presented. The paradigm allows for more flexible choices of both the underlying model and the desired controlled variables and targets. The system is implemented and tested on the DIII-D tokamak, enacting simultaneous pressure and temperature control via a finite-set model-predictive controller. Traditional control methods such as proportional–integral–derivative (PID) have proven effective for decoupled control tasks, but scale poorly when trying to achieve more complicated goals such as full state control. This is exactly where model-based controllers succeed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MARS-F/K modeling of plasma response and fast ion losses due to RMP in KSTAR

Abstract The toroidal single-fluid magnetohydrodynamic (MHD) code MARS-F (Liu et al 2000 Phys. Plasmas 7 3681) and the MHD-kinetic hybrid code MARS-K (Liu et al 2008 Phys. Plasmas 15 112503) are utilized to study the plasma response to the n = 1 ( n is the toroidal mode number) resonant magnetic perturbation (RMP), applied to suppress the type-I edge localized mode (ELM) in a KSTAR discharge. Both the resistive-rotating and ideal-static plasma models identify strong screening of the resonant radial field harmonics of the applied RMP due to the plasma response, and predict a strong edge-peeling response of the plasma which is consistent with the optimal ELM control coil current configuration adopted in experiment. The RMP-induced radial displacement of the plasma, computed by the resistive-rotating plasma model, agrees reasonably well with that reconstructed from the measured data in the plasma core. Taking into account the drift kinetic response of fast ions, MARS-K hybrid modeling also finds quantitative agreement of the plasma core fluid pressure perturbation with experiment. Based on the MARS-F computed plasma response, a guiding-center orbit-tracing simulation finds about 0.3% of fast ion losses due the n = 1 RMP in the KSTAR ELM control experiment considered. Most losses are associated with counter-current fast ions located near the plasma edge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Development and Evaluation of Velocity Predictive Optimal Energy Management Strategies in Intelligent and Connected Hybrid Electric Vehicles

In this study, a thorough and definitive evaluation of Predictive Optimal Energy Management Strategy (POEMS) applications in connected vehicles using 10 to 20 s predicted velocity is conducted for a Hybrid Electric Vehicle (HEV). The presented methodology includes synchronous datasets gathered in Fort Collins, Colorado using a test vehicle equipped with sensors to measure ego vehicle position and motion and that of surrounding objects as well as receive Infrastructure to Vehicle (I2V) information. These datasets are utilized to compare the effect of different signal categories on prediction fidelity for different prediction horizons within a POEMS framework. Multiple artificial intelligence (AI) and machine learning (ML) algorithms use the collected data to output future vehicle velocity prediction models. The effects of different combinations of signals and different models on prediction fidelity in various prediction windows are explored. All of these combinations are ultimately addressed where the rubber meets the road: fuel economy (FE) enabled from POEMS. FE optimization is performed using Model Predictive Control (MPC) with a Dynamic Programming (DP) optimizer. FE improvements from MPC control at various prediction time horizons are compared to that of full-cycle DP. All FE results are determined using high-fidelity simulations of an Autonomie 2010 Toyota Prius model. The full-cycle DP POEMS provides the theoretical upper limit on fuel economy (FE) improvement achievable with POEMS but is not currently practical for real-world implementation. Perfect prediction MPC (PP-MPC) represents the upper limit of FE improvement practically achievable with POEMS. Real-Prediction MPC (RP-MPC) can provide nearly equivalent FE improvement when used with high-fidelity predictions. Constant-Velocity MPC (CV-MPC) uses a constant speed prediction and serves as a “null” POEMS. Results showed that RP-MPC, enabled by high-fidelity ego future speed prediction, led to significant FE improvement over baseline nearly matching that of PP-MPC.

33 ADVANCED PROPULSION SYSTEMS↗

Development of a high Reynolds number quiet tunnel for transition research

High noise levels in conventional supersonic and hypersonic wind tunnels prevent further advances in transition research. Recent data confirm previous results that transition is dominated by tunnel noise when the rms pressure intensities exceed about 1%. High facility noise levels also dominate fluctuating pressure loads under fully turbulent boundary layers. Recent data on the power spectra of surface pressures indicate that the basic structure of turbulent boundary layers may be modified by high facility noise levels. Experimental data for current techniques to control and reduce noise levels in supersonic and hypersonic wind tunnels by laminarization of nozzle wall boundary layers and by noise radiation shields are presented. These results and possible effects of Taylor-Gortler vortices observed in a nozzle wall boundary layer are used to predict the limits of quiet performance for a proposed 20-in. quiet tunnel.

Beckwith, I. E.↗

Error rate information in attention allocation pilot models

The Northrop urgency decision pilot model was used in a command tracking task to compare the optimized performance of multiaxis attention allocation pilot models whose urgency functions were (1) based on tracking error alone, and (2) based on both tracking error and error rate. A matrix of system dynamics and command inputs was employed, to create both symmetric and asymmetric two axis compensatory tracking tasks. All tasks were single loop on each axis. Analysis showed that a model that allocates control attention through nonlinear urgency functions using only error information could not achieve performance of the full model whose attention shifting algorithm included both error and error rate terms. Subsequent to this analysis, tracking performance predictions for the full model were verified by piloted flight simulation. Complete model and simulation data are presented.

Faulkner, W. H.↗

Computational modeling of jet induced mixing of cryogenic propellants in low-G

The SOLA-ECLIPSE Code is being developed to enable computational prediction of jet induced mixing in cryogenic propellant tanks in a low-gravity environment. Velocity fields, predicted for scale model tanks, are presented which compare favorably with the available experimental data. A full scale liquid hydrogen tank for a typical Orbit Transfer Vehicle is analyzed with the conclusion that coupling an axial mixing jet with a thermodynamic vent system appears tobe a viable concept for the control of tank pressure. Previously announced in STAR as N84-25000

Hochstein, J. I.↗