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Embodiments of the present disclosure are related to training one or more of machine learning algorithms in a virtual reality environment for error detection and correction and/or for employing one or more trained machine learning models in an augmented reality environment to detect and/or correct user errors associated the performance of one or more tasks.
Accelerator control systems often represent relatively complex and safety-sensitive human-machine interfaces within process control industries. These systems are technically robust and reflect the cumulative integration of solutions built and adapted across decades. One of the regular, unfortunate casualties of provisional accelerator control system updates is their human-system interfaces (HSIs) which often lag behind modern usability and design standards. An additional challenge is that although there is a multitude of established human factors (HF), and user experience (UX) principles for everyday digital applications, there are very few (if any) established principles for complex and safety-critical applications for an accelerator. This paper argues for the importance of established HF and UX principles (herein referred to as human-centered design principles) into the development of accelerator HSIs, emphasizing the need for clarity, consistency, responsiveness, and cognitive accessibility. Drawing from HF/UX best practices and human-centered design, this paper discusses how these approaches can enhance operator performance, reduce human error, and improve accelerator personnel collaboration. Case studies from Accelerator Control Operations Research Network (ACORN) at Fermilab are explored to demonstrate how interfaces built with human-centered design principles can scale with system complexity while remaining intuitive and efficient for diverse user roles including operators, machine experts, and engineers. By bridging the gap between traditional control system design and modern human-centered design methods, this paper provides a roadmap for evolving accelerator HSIs into more usable, maintainable, and effective tools.
Future large astronomical telescopes in space will have architectures that will have complex and demanding requirements to meet the science goals. The Large UV/Optical/IR Surveyor (LUVOIR) mission concept being assessed by the NASA/Goddard Space Flight Center is expected to be 8 to 16 meters in diameter, have a segmented primary mirror, active control, and be diffraction limited at a wavelength of 500 nanometers. The optical stability is expected to be in the picometer range for minutes to hours. Architecture studies to support the NASA Science and Technology Definition teams (STDTs) are underway to evaluate systems performance. A wave front error budget has been developed to help define the technology needs and assess performance. The budget includes both spatial and temporal domain aspects for the active, adaptive and passive elements in the optical design.
The performance analysis results of a fault inferring nonlinear detection system (FINDS) using sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment is presented. First, a statistical analysis of the flight recorded sensor data was made in order to determine the characteristics of sensor inaccuracies. Next, modifications were made to the detection and decision functions in the FINDS algorithm in order to improve false alarm and failure detection performance under real modelling errors present in the flight data. Finally, the failure detection and false alarm performance of the FINDS algorithm were analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minute flight data. In general, the detection speed, failure level estimation, and false alarm performance showed a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed was faster for filter measurement sensors soon as MLS than for filter input sensors such as flight control accelerometers.
Indirect Drive Inertial Confinement Fusion Experiments on the National Ignition Facility (NIF) have achieved a burning plasma state with neutron yields exceeding 170 kJ, roughly 3 times the prior record and a necessary stage for igniting plasmas. The results are achieved despite multiple sources of degradations that lead to high variability in performance. Results shown here, for the first time, include an empirical correction factor for mode-2 asymmetry in the burning plasma regime in addition to previously determined corrections for radiative mix and mode-1. Analysis shows that including these three corrections alone accounts for the measured fusion performance variability in the two highest performing experimental campaigns on the NIF to within error. Here we quantify the performance sensitivity to mode-2 symmetry in the burning plasma regime and apply the results, in the form of an empirical correction to a 1D performance model. Furthermore, we find the sensitivity to mode-2 determined through a series of integrated 2D radiation hydrodynamic simulations to be consistent with the experimentally determined sensitivity only when including alpha-heating.
The phase control system is described. Potential sources of phase error are identified and the performance leading to selection of the allowable phase error for each source is summarized. The pilot transmitter, the effects of ionospheric, the master slave returnable timing system (MSRTS), the SPS receiver, and the high power amplifier for dc to microwave conversion are considered separately. Design parameters of the pilot transmitter and spacetenna transponder are presented.
An improved 2.4-m photorefractor ocular screening system was tested and evaluated. The photorefractor system works on the principal of obtaining a colored photograph of both human eyes; and, by analysis of the retinal reflex images, certain ocular defects can be detected such a refractive error, strabismus, and lens obstructions. The 2.4-m photorefractory system uses a 35-mm camera with a telephoto lens and an electronic flash attachment. Retinal reflex images obtained from the new 2.4-m system are significantly improved over earlier systems in image quality. Other features were also improved, notably portability and reduction in mass. A total of 706 school age children were photorefracted, 211 learning disabled and 495 middle school students. The total students having abnormal retinal reflexes were 156 or 22 percent, and 133 or 85 percent of the abnormal had refractive error indicated. Ophthalmological examination was performed on 60 of these students and refractive error was verified in 57 or 95 percent of those examined. The new 2.4-m system has a NASA patent pending and is authorized by the FDA. It provides a reliable means of rapidly screening the eyes of children and young adults for vision problems. It is especially useful for infants and other non-communicative children who cannot be screened by the more conventional methods such as the familiar E chart.
A parameterization scheme used at the European Centre for Medium Range Forecasting to model the average growth of the difference between forecasts on consecutive days was extended by including the effect of error growth on forecast model deficiencies. Error was defined as the difference between the forecast and analysis fields during the verification time. Systematic and random errors were considered separately in calculating the error variance for a 10 day operational forecast. A good fit was obtained with measured forecast errors and a satisfactory trend was achieved in the difference between forecasts. Fitting six parameters to forecast errors and differences that were performed separately for each wavenumber revealed that the error growth rate grew with wavenumber. The saturation error decreased with the total wavenumber and the limit of predictability, i.e., when error variance reaches 95 percent of saturation, decreased monotonically with the total wavenumber.
The Federal Aviation Administration (FAA) is implementing a satellite-based navigation system for aircraft using the Global Positioning System (GPS). Positioning accuracy of a few meters will be achieved by broadcasting corrections to the direct GPS signal. These corrections are derived using the wide-area augmentation system (WAAS), which includes a ground network of at least 24 GPS receivers across the Continental US (CONUS). WAAS will provide real-time total electron content (TEC) measurements that can be mapped to fixed grid points using a real-time mapping algorithm. These TECs will be converted into vertical delay corrections for the GPS L1 frequency and broadcast to users every five minutes via geosynchronous satellite. Users will convert these delays to slant calibrations along their own lines-of-sight (LOS) to GPS satellites. Uncertainties in the delay calibrations will also be broadcast, allowing users to estimate the uncertainty of their position. To maintain user safety without reverting to excessive safety margins an empirical model of user calibration errors has been developed. WAAS performance depends on factors that include geographic location (errors increase near WAAS borders), and ionospheric conditions, such as the enhanced spatial electron density gradients found during ionospheric storms.
For a multi-hole test probe undergoing wind tunnel tests, the resulting data needs to be analyzed for any significant trends. These trends include relating the pressure distributions, the geometric orientation, and the local velocity vector to one another. However, experimental runs always involve some sort of error. As a result, a calibration procedure is required to compensate for this error. For this case, it is the misalignment bias angles resulting from the distortion associated with the angularity of the test probe or the local velocity vector. Through a series of calibration steps presented here, the angular biases are determined and removed from the data sets. By removing the misalignment, smoother pressure distributions contribute to more accurate experimental results, which in turn could be then compared to theoretical and actual in-flight results to derive any similarities. Error analyses will also be performed to verify the accuracy of the calibration error reduction. The resulting calibrated data will be implemented into an in-flight RTF script that will output critical flight parameters during future CCIE experimental test runs. All of these tasks are associated with and in contribution to NASA Dryden Flight Research Center s F-15B Research Testbed s Small Business Innovation Research of the Channeled Centerbody Inlet Experiment.
The need to develop an operationally relevant figure of merit for the quality of performance of a complex system such as an aircraft cockpit stems from a hypothesized dissociation between measures of performance and those of workload. Performance can be measured in terms of time, errors, or a combination of these. In most tasks performed by expert operators, errors are relatively rare and often corrected in time to avoid consequences. Moreover, perfect performance is seldom necessary to accomplish a particular task. Moreover, how well an expert performs a complex task consisting of a series of discrete cognitive tasks superimposed on a continuous task, such as flying an aircraft, does not depend on how well each discrete task is performed, but on their smooth sequencing. This makes the amount of time spent on each subtask of paramount importance in measuring overall performance, since smooth sequencing requires a minimum amount of time spent on each task. Quality consists in getting tasks done within a crucial time interval while maintaining acceptable continuous task performance. Thus, a figure of merit for overall quality of performance should be primarily a measure of time to perform discrete subtasks combined with a measure of basic vehicle control. Thus, the proposed figure of merit requires doing a task analysis on a series of performance, or runs, of a particular task, listing each discrete task and its associated time, and calculating the mean and standard deviation of these times, along with the mean and standard deviation of tracking error for the whole task. A set of simulator data on 30 runs of a landing task was obtained and a figure of merit will be calculated for each run. The figure of merit will be compared for voice and data link, so that the impact of this technology on total crew performance (not just communication performance) can be assessed. The effect of data link communication on other cockpit tasks will also be considered.
Heavy ion irradiation of a display driver integrated circuit (DDIC) was performed, and persistent visual error signatures were captured. Based on the heavy ion results, error signatures were localized to configuration registers motivate potential mitigation techniques and observations relating to single event effect susceptibility. DDICs serve as an integral component of integrated display systems that will require the development of single event effects test methodologies in anticipation of extensive use in crewed spacecrafts outside of the Earth’s geomagnetic protection.
The Infrared Multi-Object Spectrometer (IRMOS) is a facility-class instrument for the Kitt Peak National Observatory 4 and 2.1 meter telescopes. IRMOS is a near-IR (0.8-2.5 micron) spectrometer and operates at approximately 80 K. The 6061-T651 aluminum bench and mirrors constitute an athermal design. The instrument produces simultaneous spectra at low- to mid-resolving power (R=lambda/delta lambda= 300-3000) of approximately 100 objects in its 2.8 x 2.0 arcmin field. We describe ambient and cryogenic optical testing of the IRMOS mirrors across a broad range in spatial frequency (figure error, mid-frequency error, and microroughness). The mirrors include three rotationally symmetric, off-axis conic sections, one off-axis biconic, and several flat fold mirrors. The symmetric mirrors include convex and concave prolate and oblate ellipsoids. They range in aperture from 94x86 mm to 286x269 mm and in f-number from 0.9 to 2.4. The biconic mirror is concave and has a 94x76 mm aperture, R(sub x)=377 mm, k(sub x)=0.0778, R(sub y)=407 mm, and k(sub y)=0.1265 and is decentered by -2 mm in X and 227 mm in Y. All of the mirrors have an aspect ratio of approximately 6:1. The surface error fabrication tolerances are less than 10 nm RMS microroughness, 'best effort' for mid-frequency error, and less than 63.3 nm RMS figure error. Ambient temperature (approximately 293 K) testing is performed for each of the three surface error regimes, and figure testing is also performed at approximately 80 K. Operation of the ADE Phaseshift MicroXAM white light interferometer (micro-roughness) and the Bauer Model 200 profilometer (mid-frequency error) is described. Both the sag and conic values of the aspheric mirrors make these tests challenging. Figure testing is performed using a Zygo GPI interferometer, custom computer generated holograms (CGH), and optomechanical alignment fiducials. Cryogenic CGH null testing is discussed in detail. We discuss complications such as the change in prescription with temperature and thermal gradients. Correction for the effect of the dewar window is also covered. We discuss the error budget for the optical test and alignment procedure. Data reduction is accomplished using commercial optical design and data analysis software packages. Results from CGH testing at cryogenic temperatures are encouraging thus far.
Understanding the characteristics of background error is vital to the design and performance of data assimilation systems. However, the true state of the atmosphere is unknown, and qualitative determination of background error is thus a challenge. We present an exploration of background error characteristics using the NASA Global Modeling and Assimilation Office Observing System Simulation Experiment framework, where the presence of the Nature Run allows direct calculation of the background error. The behavior of the data assimilation system (DAS) can be compared with the character of the background error, and performance of the DAS will be investigated in a series of both idealized and realistic experiments.
An approach is developed for the alignment and stability maintenance of the LUVOIR segmented primary mirror using a segment state estimation and wavefront control method based on a hybrid segment motion sensing architecture of laser truss metrology and segment edge sensors. Our current computer model was generated for LUVOIR Architecture Option A with a 15-meter aperture, 120segment primary mirror. The methodology and simulation results will be presented and analyzed. JPL has a long history of technology development in laser metrology and edge sensors, including work in SIM [7], Keck and TMT [8], CCAT [3] and LUVOIR [1]. We will discuss our current efforts of LUVOIR laser metrology and edge-sensor models development, showing sensitivities of sensor measurements to various mirror eigenmodes, removing global modes and strengthening weak modes by performing joint (hybrid) laser-metrology and edge sensing. We will define and derive an important performance metric called wavefront error multiplier (WEM), and show that WEM provides a simple link between sensor errors and the closed-loop (controlled) system wavefront error. We will show WEM values for several hybrid sensor configuration options studied. We will discuss an algorithm for mirror shape control and maintenance through segment state and wavefront estimations using joint edge-metrology sensing. We will compare simulated performance of mirror state estimation, wavefront estimation and wavefront control based on joint edge-metrology sensing among several sensor configurations, and show the impact of sensor error distributions on the segmented mirror alignment performance. Mirror shape control performance will be also be evaluated in terms of imaging contrast between inner working angles (IWA) and outer working angles (OWA) of a LUVOIR coronagraph. The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. LUVOIR is a mission concept under study for the next astronomy Decadal Survey—the information presented in this paper is pre-decisional and is provided for planning and discussion purposes only.
Price forecasting is in the center of decision making in electricity markets. Many researches have been done in forecasting energy prices while little research has been reported on forecasting price difference between day-ahead and realtime markets due to its high volatility, which however plays a critical role in virtual trading. To this end, this paper takes the first attempt to employ novel deep learning architecture with Bidirectional Long-Short Term Memory (LSTM) units to forecast the price difference between day-ahead and real-time markets for the same node. The raw data is collected from PJM market, processed and fed into the proposed network. The Root Mean Squared Error (RMSE) and customized performance metric are used to evaluate the performance of the proposed method. Case studies show that it outperforms the traditional statistical models like ARIMA, and machine learning models like XGBoost and SVR methods in both RMSE and the capability of forecasting the sign of price difference. Additionally, to cross-market price difference forecast, the proposed approach has the potential to be applied to solve other forecasting problems such as price spread forecast in DA market for Financial Transmission Right (FTR) trading purpose.
The entry-to-touchdown space shuttle orbiter simulation capability incorporated into the GEMASS subprogram 33 (3-DOF) is documented. A digital autopilot interfaces between GEMASS and the guidance. Vehicle attitude is determined by use of the ability of GEMASS to integrate differential equations in addition to the equations of motion. Vehicle aerodynamic characteristics are obtained from an aerodynamic data tape and control surface deflections required to trim the vehicle, and trimmed aerodynamic coefficients are determined internally. Several indicators to allow evaluation of subsystem performance are included; as is the ability of the user to activate any of several error dispersion sources. The performance of the simulation compares well with more sophisticated simulations.
The practical utility of Møller–Plesset (MP) perturbation theory is severely constrained by the use of Hartree–Fock (HF) orbitals. It has recently been shown that the use of regularized orbital-optimized MP2 orbitals and scaling of MP3 energy could lead to a significant reduction in MP3 error. In this work, we examine whether density functional theory (DFT)-optimized orbitals can be similarly employed to improve the performance of MP theory at both the MP2 and MP3 levels. We find that the use of DFT orbitals leads to significantly improved performance for prediction of thermochemistry, barrier heights, noncovalent interactions, and dipole moments relative to the standard HF-based MP theory. Indeed, MP3 (with or without scaling) with DFT orbitals is found to surpass the accuracy of coupled-cluster singles and doubles (CCSD) for several data sets. We also found that the results are not particularly functional sensitive in most cases (although range-separated hybrid functionals with low delocalization error perform the best). As such, MP3 based on DFT orbitals thus appears to be an efficient, noniterative O(N 6 ) scaling wave-function approach for single-reference electronic structure computations. Scaled MP2 with DFT orbitals is also found to be quite accurate in many cases, although modern double hybrid functionals are likely to be considerably more accurate.