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At least 757 records · Page 42

Higher-Order Ionospheric Effects on the GPS Observables and Means of Modeling Them

Based on realistic modeling of the electron density of the ionosphere and using a dipole moment approximation for the earth magnetic field, we are able to estimate the effect of the ionosphere on the GPS signal for a ground user. Our study implies reduction of the second-order ionospheric error to less than 2 mm on the average and, therefore, potential improvement of orbit determination and baseline solutions.

ionosphere↗

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Recent Advancements in spoken language processing technologies have enabled the development of reliable automation tools to assist air traffic control (ATC) operations. These advancements present a unique opportunity to strategically implement digital taxi instructions for aircraft movement on the ground. Digital taxi instructions issue taxiing procedures to pilots as textual or graphical instructions. There are several benefits of digital instructions, including a reduction in radio congestion, elimination of communication errors, and improved aircraft monitoring capabilities. Natural language understanding (NLU) models can extract digital taxi instructions from verbal instructions issued by air traffic controllers. This capability enables the implementation of a digital taxi communication framework with minimal changes to the existing air traffic controller operational environment. We explore a novel application for NLU: automatically generating digital taxi instructions from air traffic controller speech. We describe the development of an annotation scheme to represent (aircraft) ground traffic communications in the US National Airspace System (NAS).Our annotation scheme uses intent classification and slot filling to extract taxi instructions, enabling NLU models to leverage syntactic information. Several neural network models were trained to categorize the controller’s intent and label information relevant to his or her intent.Our research demonstrates that it is feasible to use NLU to automatically generate digitaltaxi instructions, suggesting that it is a powerful tool for the implementation of digital taxi communications.

Hillel Steinmetz↗

Planting data and wheat yield models

The author has identified the following significant results. A variable date starter model for spring wheat depending on temperature was more precise than a fixed date model. The same conclusions for fall-planted wheat were not reached. If the largest and smallest of eight temperatures were used to estimate daily maximum and minimum temperatures; respectively, a 1-4 F bias would be introduced into these extremes. For Kansas, a reduction of 0.5 bushels/acre in the root-mean-square-error between model and SRS yields was achieved by a six fold increase (7 to 42) in the density of weather stations. An additional reduction of 0.3 b/A was achieved by incorporating losses due to rusts in the model.

Feyerherm, A. M.↗

Training self-learning circuits for power-efficient solutions

As the size and ubiquity of artificial intelligence and computational machine learning models grow, the energy required to train and use them is rapidly becoming economically and environmentally unsustainable. Recent laboratory prototypes of self-learning electronic circuits, such as “physical learning machines,” open the door to analog hardware that directly employs physics to learn desired functions from examples at a low energy cost. In this work, we show that this hardware platform allows for an even further reduction in energy consumption by using good initial conditions and a new learning algorithm. Using analytical calculations, simulations, and experiments, we show that a trade-off emerges when learning dynamics attempt to minimize both the error and the power consumption of the solution—greater power reductions can be achieved at the cost of decreasing solution accuracy. Finally, we demonstrate a practical procedure to weigh the relative importance of error and power minimization, improving the power efficiency given a specific tolerance to error.

Stern, Menachem (ORCID:0000000302158082)↗

Model Evaluation by Measurements from Collocated Remote Sensors in Complex Terrain

Model improvement efforts involve an evaluation of changes in model skill in response to changes in model physics and parameterization. When using wind measurements from various remote sensors to determine model forecast accuracy, it is important to understand the effects of measurement-uncertainty differences among the sensors resulting from differences in the methods of measurement, the vertical and temporal resolution of the measurements, and the spatial variability of these differences. Here we quantify instrument measurement variability in 80-m wind speed during WFIP2 and its impact on the calculated errors and the change in error from one model version to another. Here the model versions tested involved updates in model physics from HRRRv1 to HRRRv4, and reductions in grid interval from 3 km to 750 m. Model errors were found to be 2–3 m s –1 . Differences in errors as determined by various instruments at each site amounted to about 10% of this value, or 0.2–0.3 m s –1 . Changes in model skill due to physics or grid-resolution updates also differed depending on the instrument used to determine the errors; most of the instrument-to-instrument differences were ~0.1 m s –1 , but some reached 0.3 m s –1 . All instruments at a given site mostly showed consistency in the sign of the change in error. In two examples, though, the sign changed, illustrating a consequence of differences in measurements: errors determined using one instrument may show improvement in model skill, whereas errors determined using another instrument may indicate degradation. This possibility underscores the importance of having accurate measurements to determine the model error.

54 ENVIRONMENTAL SCIENCES↗

Compiler-Directed Soft Error Detection and Recovery to Avoid DUE and SDC via Tail-DMR

This article presents Clover, a compiler-directed soft error detection and recovery scheme for lightweight soft error resilience. The compiler carefully generates soft-error-tolerant code based on idempotent processing without explicit checkpoints. During program execution, Clover relies on a small number of acoustic wave detectors deployed in the processor to identify soft errors by sensing the wave made by a particle strike. To cope with DUEs (detected unrecoverable errors) caused by the sensing latency of error detection, Clover leverages a novel selective instruction duplication technique called tail-DMR (dual modular redundancy) that provides a region-level error containment. Once a soft error is detected by either the sensors or the tail-DMR, Clover takes care of the error as in the case of exception handling. To recover from the error, Clover simply redirects program control to the beginning of the code region where the error is detected. The experimental results demonstrate that the average runtime overhead is only 26%, which is a 75% reduction compared to that of the state-of-the-art soft error resilience technique. In addition, this article evaluates an alternative technique called tail-wait, comparing it to Clover. According to the evaluation with the different processor configurations and the various error detection latencies, Clover turns out to be a superior technique, achieving 1.06 to 3.49× speedup over the tail-wait.

Computer Science↗

Space structure vibration modes: How many exist? Which ones are important?

Several assertions are argued regarding mode analysis of structural vibration. The idea of a "mode' is, in essence, a mathematical one. It is highly unlikely that any real structure can vibrate exactly so that all its points move in unison; in other words, it is highly unlikely that any structure has any modes. As an approximation, however, the use of a mode is an excellent one for many structures, especially for the "lower modes'. The agreement between experiment and theory for the "higher modes' tends to become weaker. In this approximate sense, most structures have a very large number of modes. It is elementary to show, however, that no real structure has an infinite number of modes. The only utility of the "infinite modes' idea is within the purely mathematical domain. Many "error indices' can be defined as guidelines for structural modal order reduction. Simple modal truncation, although suggested by experience with slender rods, is naive. The proper process is mode selection, based on a appropriate error criterion.

Hughes, P. C.↗

Implementing Computer-Based Procedures: Thinking Outside the Paper Margins

In the past year there has been increased interest from the nuclear industry in adopting the use of electronic work packages and computer-based procedures (CBPs) in the field. The goal is to incorporate the use of technology in order to meet the Nuclear Promise requirements of reducing costs and improve efficiency and decrease human error rates of plant operations. Researchers, together with the nuclear industry, have been investigating the benefits an electronic work package system and specifically CBPs would have over current paper-based procedure practices. There are several classifications of CBPs ranging from a straight copy of the paper-based procedure in PDF format to a more intelligent dynamic CBP. A CBP system offers a vast variety of improvements, such as context driven job aids, integrated human performance tools (e.g., placekeeping and correct component verification), and dynamic step presentation. The latter means that the CBP system could only display relevant steps based on operating mode, plant status, and the task at hand. The improvements can lead to reduction of the worker’s workload and human error by allowing the work to focus on the task at hand more. A team of human factors researchers at the Idaho National Laboratory studied and developed design concepts for CBPs for field workers between 2012 and 2016. The focus of the research was to present information in a procedure in a manner that leveraged the dynamic and computational capabilities of a handheld device allowing the worker to focus more on the task at hand than on the administrative processes currently applied when conducting work in the plant. As a part of the research the team identified type of work, instructions, and scenarios where the transition to a dynamic CBP system might not be as beneficial as it would for other types of work in the plant. In most cases the decision to use a dynamic CBP system and utilize the dynamic capabilities gained will be beneficial to the worker. However, tasks that are reliant on the skill of the craft or have a short set of instructions may not provide a way or even need to utilize all the advanced capabilities in a dynamic CBP system. Therefore, a hybrid CBP system that could handle all the classifications of a CBP would be the best solution to take advantage of all that a CBP system offers. The implementation of a CBP system does not automatically improve the quality of procedures. Utilities should look into why each procedure is written the way it currently is on paper. Utilities should take the time before implementation to review, standardize format and update current procedures. Implementation of a CBP system can be a time to break out of traditional procedure writing processes and create new processes and procedures that take advantage of the capabilities a CBP system. This paper will summarize the research on CBPs and provide suggestions to take into consideration when implementing a CBP system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Reducing Truncation Error In Integer Processing

Improved method of rounding off (truncation of least-significant bits) in integer processing of data devised. Provides for reduction, to extremely low value, of numerical bias otherwise generated by accumulation of truncation errors from many arithmetic operations. Devised for use in integer signal processing, in which rescaling and truncation usually performed to reduce number of bits, which typically builds up in sequence of operations. Essence of method to alternate direction of roundoff (plus, then minus) on alternate occurrences of truncated values contributing to bias.

Thomas, J. Brooks↗

Clover: Compiler directed lightweight soft error resilience

This paper presents Clover, a compiler directed soft error detection and recovery scheme for lightweight soft error resilience. The compiler carefully generates soft error tolerant code based on idem-potent processing without explicit checkpoint. During program execution, Clover relies on a small number of acoustic wave detectors deployed in the processor to identify soft errors by sensing the wave made by a particle strike. To cope with DUE (detected unrecoverable errors) caused by the sensing latency of error detection, Clover leverages a novel selective instruction duplication technique called tail-DMR (dual modular redundancy). Once a soft error is detected by either the sensor or the tail-DMR, Clover takes care of the error as in the case of exception handling. To recover from the error, Clover simply redirects program control to the beginning of the code region where the error is detected. Lastly, the experiment results demonstrate that the average runtime overhead is only 26%, which is a 75% reduction compared to that of the state-of-the-art soft error resilience technique.

97 MATHEMATICS AND COMPUTING↗

Real eigenvalue analysis in NASTRAN by the tridiagonal reduction (FEER) method

Implementation of the tridiagonal reduction method for real eigenvalue extraction in structural vibration and buckling problems is described. The basic concepts underlying the method are summarized and special features, such as the computation of error bounds and default modes of operation are discussed. In addition, the new user information and error messages and optional diagnostic output relating to the tridiagonal reduction method are presented. Some numerical results and initial experiences relating to usage in the NASTRAN environment are provided, including comparisons with other existing NASTRAN eigenvalue methods.

Newman, M.↗

Experimental Analysis of Work-piece's Diametrical Error in Ultrasonic-Vibration-Assisted Turning

Vibration at an ultrasonic frequency is superimposed on the ordinary cutting motion in ultrasonic-vibration-assisted turning (UAT). This combinatory cutting motion results in reduction of the cutting force and surface roughness, and improvement of the dimensional tolerances compared with conventional turning (CT). The advantages obtainable from UAT has made this process suitable for machining hard-to-cut and brittle materials such as super-alloys and ceramics, as well as ordinary materials. The elastic deflection of work-pieces is primarily responsible for the diametrical errors of the machined parts. This is of course more obvious for slender work-pieces. The influence of UAT process on the diametrical error has not yet been investigated. This has been partly undertaken by the authors of the present paper. It has been experimentally illustrated in this paper that ultrasonic vibration superimposed on the tool tip can result in reduction of the diametrical error and thus reduced scrap rate is ensued.

36 MATERIALS SCIENCE↗

Revisiting Competing Paths in Electrochemical CO 2 Reduction on Copper via Embedded Correlated Wavefunction Theory

We re-evaluate two key steps in the mechanism of CO 2 reduction on copper at a higher level of theory capable of correcting inherent errors in density functional theory (DFT) approximations, namely, embedded correlated wavefunction (ECW) theory. Here, we consider the CO reduction step on Cu(111), which is critical to understanding reaction selectivity. Here, we optimize embedding potentials at the periodic plane-wave DFT level using density functional embedding theory (DFET). All possible adsorption sites (adsites) for each adsorbate then are screened with ECW theory at the catalytically active site to refine the local electronic structure. Unsurprisingly, DFT and ECW theory predict different adsite preferences, largely because of DFT’s inability to properly situate the CO 2π* level. Differing preferred adsites suggest that different reaction pathways could emerge from DFT versus ECW theory. Starting from these preferred ECW theory adsites, we then obtain reaction pathways at the plane-wave DFT level using the climbing-image nudged elastic band method to determine minimum energy paths. Thereafter, we perform ECW calculations at the catalytically active site to correct the energetics at each interpolated structure (image) along the reaction pathways. Via this approach, we confirm that the first step in CO reduction via hydrogen transfer on Cu(111) is to form hydroxymethylidyne (*COH) instead of formyl (*CHO). Although the prediction to preferentially form *COH is consistent with that of DFT, the two theories predict quite different structural and mechanistic behaviors, suggesting that verification is needed for other parts of the mechanism of CO 2 reduction, which is the subject of ongoing work.

30 DIRECT ENERGY CONVERSION↗

Breaking Computational Barriers: Real-time Analysis and Optimization with Large-scale Nonlinear Models via Model Reduction

Model reduction for dynamical systems is a promising approach for reducing the computational cost of large-scale physics-based simulations to enable high-fidelity models to be used in many- query (e.g., Bayesian inference) and near-real-time (e.g., fast-turnaround simulation) contexts. While model reduction works well for specialized problems such as linear time-invariant systems, it is much more difficult to obtain accurate, stable, and efficient reduced-order models (ROMs) for systems with general nonlinearities. This report describes several advances that enable nonlinear reduced-order models (ROMs) to be deployed in a variety of time-critical settings. First, we present an error bound for the Gauss-Newton with Approximated Tensors (GNAT) nonlinear model reduction technique. This bound allows the state-space error for the GNAT method to be quantified when applied with the backward Euler time-integration scheme. Second, we present a methodology for preserving classical Lagrangian structure in nonlinear model reduction. This technique guarantees that important properties--such as energy conservation and symplectic time-evolution maps--are preserved when performing model reduction for models described by a Lagrangian formalism (e.g., molecular dynamics, structural dynamics). Third, we present a novel technique for decreasing the temporal complexity --defined as the number of Newton-like iterations performed over the course of the simulation--by exploiting time-domain data. Fourth, we describe a novel method for refining projection-based reduced-order models a posteriori using a goal-oriented framework similar to mesh-adaptive h -refinement in finite elements. The technique allows the ROM to generate arbitrarily accurate solutions, thereby providing the ROM with a 'failsafe' mechanism in the event of insufficient training data. Finally, we present the reduced-order model error surrogate (ROMES) method for statistically quantifying reduced- order-model errors. This enables ROMs to be rigorously incorporated in uncertainty-quantification settings, as the error model can be treated as a source of epistemic uncertainty. This work was completed as part of a Truman Fellowship appointment. We note that much additional work was performed as part of the Fellowship. One salient project is the development of the Trilinos-based model-reduction software module Razor , which is currently bundled with the Albany PDE code and currently allows nonlinear reduced-order models to be constructed for any application supported in Albany. Other important projects include the following: 1. ROMES-equipped ROMs for Bayesian inference: K. Carlberg, M. Drohmann, F. Lu (Lawrence Berkeley National Laboratory), M. Morzfeld (Lawrence Berkeley National Laboratory). 2. ROM-enabled Krylov-subspace recycling: K. Carlberg, V. Forstall (University of Maryland), P. Tsuji, R. Tuminaro. 3. A pseudo balanced POD method using only dual snapshots: K. Carlberg, M. Sarovar. 4. An analysis of discrete v. continuous optimality in nonlinear model reduction: K. Carlberg, M. Barone, H. Antil (George Mason University). Journal articles for these projects are in progress at the time of this writing.

97 MATHEMATICS AND COMPUTING↗

New main reflector, subreflector and dual chamber concepts for compact range applications

A compact range is a facility used for the measurement of antenna radiation and target scattering problems. Most presently available parabolic reflectors do not produce ideal uniform plane waves in the target zone. Design improvements are suggested to reduce the amplitude taper, ripple and cross polarization errors. The ripple caused by diffractions from the reflector edges can be reduced by adding blended rolled edges and shaping the edge contour. Since the reflected edge continues smoothly from the parabola onto the rolled surface, rather than being abruptly terminated, the discontinuity in the reflected field is reduced which results in weaker diffracted fields. This is done by blending the rolled edges from the parabola into an ellipse. An algorithm which enables one to design optimum blended rolled edges was developed that is based on an analysis of the continuity of the surface radius of curvature and its derivatives across the junction. Futhermore, a concave edge contour results in a divergent diffracted ray pattern and hence less stray energy in the target zone. Design equations for three-dimensional reflectors are given. Various examples were analyzed using a new physical optics method which eliminates the effects of the false scattering centers on the incident shadow boundaries. A Gregorian subreflector system, in which both the subreflector and feed axes are tilted, results in a substantial reduction in the amplitude taper and cross polarization errors. A dual chamber configuration is proposed to eliminate the effects of diffraction from the subreflector and spillover from the feed. A computationally efficient technique, based on ray tracing and aperture integration, was developed to analyze the scattering from a lossy dielectric slab with a wedge termination.

Pistorius, C. W. I.↗

System identification and model reduction using modulating function techniques

Weighted least squares (WLS) and adaptive weighted least squares (AWLS) algorithms are initiated for continuous-time system identification using Fourier type modulating function techniques. Two stochastic signal models are examined using the mean square properties of the stochastic calculus: an equation error signal model with white noise residuals, and a more realistic white measurement noise signal model. The covariance matrices in each model are shown to be banded and sparse, and a joint likelihood cost function is developed which links the real and imaginary parts of the modulated quantities. The superior performance of above algorithms is demonstrated by comparing them with the LS/MFT and popular predicting error method (PEM) through 200 Monte Carlo simulations. A model reduction problem is formulated with the AWLS/MFT algorithm, and comparisons are made via six examples with a variety of model reduction techniques, including the well-known balanced realization method. Here the AWLS/MFT algorithm manifests higher accuracy in almost all cases, and exhibits its unique flexibility and versatility. Armed with this model reduction, the AWLS/MFT algorithm is extended into MIMO transfer function system identification problems. The impact due to the discrepancy in bandwidths and gains among subsystem is explored through five examples. Finally, as a comprehensive application, the stability derivatives of the longitudinal and lateral dynamics of an F-18 aircraft are identified using physical flight data provided by NASA. A pole-constrained SIMO and MIMO AWLS/MFT algorithm is devised and analyzed. Monte Carlo simulations illustrate its high-noise rejecting properties. Utilizing the flight data, comparisons among different MFT algorithms are tabulated and the AWLS is found to be strongly favored in almost all facets.

Shen, Yan↗

Dosimetric Implications of Residual Tracking Errors During Robotic SBRT of Liver Metastases

Purpose: Although the metric precision of robotic stereotactic body radiation therapy in the presence of breathing motion is widely known, we investigated the dosimetric implications of breathing phase–related residual tracking errors. Methods and Materials: In 24 patients (28 liver metastases) treated with the CyberKnife, we recorded the residual correlation, prediction, and rotational tracking errors from 90 fractions and binned them into 10 breathing phases. The average breathing phase errors were used to shift and rotate the clinical tumor volume (CTV) and planning target volume (PTV) for each phase to calculate a pseudo 4-dimensional error dose distribution for comparison with the original planned dose distribution. Results: The median systematic directional correlation, prediction, and absolute aggregate rotation errors were 0.3 mm (range, 0.1-1.3 mm), 0.01 mm (range, 0.00-0.05 mm), and 1.5° (range, 0.4°-2.7°), respectively. Dosimetrically, 44%, 81%, and 92% of all voxels differed by less than 1%, 3%, and 5% of the planned local dose, respectively. The median coverage reduction for the PTV was 1.1% (range in coverage difference, −7.8% to +0.8%), significantly depending on correlation (P=.026) and rotational (P=.005) error. With a 3-mm PTV margin, the median coverage change for the CTV was 0.0% (range, −1.0% to +5.4%), not significantly depending on any investigated parameter. In 42% of patients, the 3-mm margin did not fully compensate for the residual tracking errors, resulting in a CTV coverage reduction of 0.1% to 1.0%. Conclusions: For liver tumors treated with robotic stereotactic body radiation therapy, a safety margin of 3 mm is not always sufficient to cover all residual tracking errors. Dosimetrically, this translates into only small CTV coverage reductions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗