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At least 1,135 records · Page 63

The Xpress Transfer Protocol (XTP): A tutorial (short version)

The Xpress Transfer Protocol (XTP) is a reliable, light weight transfer layer protocol. Current transport layer protocols such as DoD's Transmission Control Protocol (TCP) and ISO's Transport Protocol (TP) were not designed for the next generation of high speed, interconnected reliable networks such as fiber distributed data interface (FDDI) and the gigabit/second wide area networks. Unlike all previous transport layer protocols, XTP is being designed to be implemented in hardware as a VLSI chip set. By streamlining the protocol, combining the transport and network layers, and utilizing the increased speed and parallelization possible with a VLSI implementation, XTP will be able to provide the end-to-end data transmission rates demanded in the high speed networks without compromising reliability and functionality. This tutorial briefly describes the operation of the XTP protocol and in particular, its error, flow and rate control; inter-networking addressing mechanisms; and multicast support features, as defined in the XTP Protocol Definition Revision 3.4.

Sanders, Robert M.↗

Least Reliable Bits Coding (LRBC) for high data rate satellite communications

An analysis and discussion of a bandwidth efficient multi-level/multi-stage block coded modulation technique called Least Reliable Bits Coding (LRBC) is presented. LRBC uses simple multi-level component codes that provide increased error protection on increasingly unreliable modulated bits in order to maintain an overall high code rate that increases spectral efficiency. Further, soft-decision multi-stage decoding is used to make decisions on unprotected bits through corrections made on more protected bits. Using analytical expressions and tight performance bounds it is shown that LRBC can achieve increased spectral efficiency and maintain equivalent or better power efficiency compared to that of Binary Phase Shift Keying (BPSK). Bit error rates (BER) vs. channel bit energy with Additive White Gaussian Noise (AWGN) are given for a set of LRB Reed-Solomon (RS) encoded 8PSK modulation formats with an ensemble rate of 8/9. All formats exhibit a spectral efficiency of 2.67 = (log2(8))(8/9) information bps/Hz. Bit by bit coded and uncoded error probabilities with soft-decision information are determined. These are traded with with code rate to determine parameters that achieve good performance. The relative simplicity of Galois field algebra vs. the Viterbi algorithm and the availability of high speed commercial Very Large Scale Integration (VLSI) for block codes indicates that LRBC using block codes is a desirable method for high data rate implementations.

Vanderaar, Mark↗

Reed Solomon error correction for the space telescope

This paper reports a single 8.2mm by 8.4mm, 200,000 transistor CMOS chip implementation of the Reed Solomon code required by the Space Telescope. The chip features a 10 MHz sustained byte rate independent of error pattern. The 1.6 micron CMOS integrated circuit has complete decoder and encoder functions and uses a single data/system clock. Block lengths up to 255 bytes as well as shortened codes are supported with no external buffering. Erasure corrections as well as random error corrections are supported with programmable corrections of up to 10 symbol errors. Correction time is independent of error pattern and the number of errors.

Whitaker, S.↗

PRESAGE: Protecting Structured Address Generation against Soft Errors

Modern computer scaling trends in pursuit of larger component counts and power efficiency have, unfortunately, lead to less reliable hardware and consequently soft errors escaping into application data ("silent data corruptions"). Techniques to enhance system resilience hinge on the availability of efficient error detectors that have high detection rates, low false positive rates, and lower computational overhead. Unfortunately, efficient detectors to detect faults during address generation (to index large arrays) have not been widely researched. We present a novel lightweight compiler-driven technique called PRESAGE for detecting bit-flips affecting structured address computations. A key insight underlying PRESAGE is that any address computation scheme that flows an already incurred error is better than a scheme that corrupts one particular array access but otherwise (falsely) appears to compute perfectly. Enabling the flow of errors allows one to situate detectors at loop exit points, and helps turn silent corruptions into easily detectable error situations. Our experiments using PolyBench benchmark suite indicate that PRESAGE-based error detectors have a high error-detection rate while incurring low overheads.

Sharma, Vishal C.↗

Distributed Quantum Error Correction for Chip-Level Catastrophic Errors

Quantum error correction holds the key to scaling up quantum computers. Cosmic ray events severely impact the operation of a quantum computer by causing chip-level catastrophic errors, essentially erasing the information encoded in a chip. Here, in this work, we present a distributed error correction scheme to combat the devastating effect of such events by introducing an additional layer of quantum erasure error correcting code across separate chips. We show that our scheme is fault tolerant against chip-level catastrophic errors and discuss its experimental implementation using superconducting qubits with microwave links. Our analysis shows that in state-of-the-art experiments, it is possible to suppress the rate of these errors from 1 per 10 s to less than 1 per month.

97 MATHEMATICS AND COMPUTING↗

Program documentation: Surface heating rate of thin skin models (THNSKN)

Program THNSKN computes the mean heating rate at a maximum of 100 locations on the surface of thin skin transient heating rate models. Output is printed in tabular form and consists of time history tabulation of temperatures, average temperatures, heat loss without conduction correction, mean heating rate, least squares heating rate, and the percent standard error of the least squares heating rates. The input tape used is produced by the program EHTS03.

Mcbryde, J. D.↗

Satellite microwave radiances correlated with radar rain rates over land

The characteristics of upwelling microwave radiation from raindrops as measured by satellite sensors are examined. The scanning multichannel microwave radiometers on board the Nimbus 7 and Seasat satellites have the capability of quantifying the perpendicularly polarized antenna temperatures at 37, 21, 18, 10.7, and 6.6 GHz. The instruments scan the earth at a constant 50 deg angle to the surface with a footprint that varies from 20-70 km. Radar rainfall measurements have an accuracy of within 60 percent, whereas a series of test measurements using SMMR data in comparison with radar data for rainfall in the same areas showed that the microwave data depicted rainfall rates with less than 1.55 mm/h error. Details of the rainfall rate algorithms used to treat the satellite microwave data are provided, noting that the identification of rainfall rates is dependent on quantifying the amount the upwelling radiance is reduced due to rainfall.

Spencer, R. W.↗

Cratering of the terrestrial planets by Apollo objects

An asteroidal collision model and Monte Carlo program used for studies of the terrestrial meteorite flux, the steady-state number of Apollo-Amor objects, and the orbital distribution of both meteorites and Apollo-Amor objects is used to calculate absolute and relative cratering rates on the terrestrial planets. It is found that the 'best' estimates of the predicted asteroidal cratering rate are three times lower than estimates of the observed terrestrial cratering rate. If this is due to errors in the asteroidal production rate of Apollo-Amor objects, the predicted present-day cratering rate per unit area on Mars is four times that on earth, whereas that on Mercury is twice that on earth.

Wetherill, G. W.↗

Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Measurement System Description and Mass Balance Approach

Natural gas is an abundant resource across the United States, of which methane (CH4) is the main component. About 2% of extracted CH4 is lost through leaks. The Remote Methane Leak Detector (RMLD)-Unmanned Aerial Vehicle (UAV) system was developed to investigate natural gas fugitive leaks in this study. The system is composed of three major technologies: miniaturized RMLD (mini-RMLD) based on Backscatter Tunable Diode Laser Absorption Spectroscopy (TDLAS), an autonomous quadrotor UAV and simplified quantification and localization algorithms. With a miniaturized, downward-facing RMLD on a small UAV, the system measures the column-integrated CH4 mixing ratio and can semi-autonomously monitor CH4 leakage from sites associated with natural gas production, providing an advanced capability in detecting leaks at hard-to-access sites compared to traditional manual methods. Automated leak characterization algorithms combined with a wireless data link implement real-time leak quantification and reporting. This study placed particular emphasis on the RMLD-UAV system description and the quantification algorithm development based on a mass balance approach. Early data were gathered to test the prototype system and to evaluate the algorithm performance. The quantification algorithm derived in this study tended to underestimate the gas leak rates and yielded unreliable estimations in detecting leaks under 7 × 10 − 6 m3/s (~1 Standard Cubic Feet per Hour (SCFH)). Zero-leak cases can be ascertained via a skewness indicator, which is unique and promising. The influence of the systematic error was investigated by introducing simulated noises, of which Global Positioning System (GPS) noise presented the greatest impact on leak rate errors. The correlation between estimated leak rates and wind conditions were investigated, and steady winds with higher wind speeds were preferred to get better leak rate estimations, which was accurate to approximately 50% during several field trials. High precision coordinate information from the GPS, accurate wind measurements and preferred wind conditions, appropriate flight strategy and the relative steady survey height of the system are the crucial factors to optimize the leak rate estimations.

03 NATURAL GAS↗

Error estimation for delta VLBI angle and angle rate measurements over baselines between a ground station and a geosynchronous orbiter

Baselines between a ground station and a geosynchronous orbiter provide high resolution Delta VLBI data which is beyond the capability of ground-based interferometry. The effects of possible error sources on such Delta VLBI data for the determination of spacecraft angle and angle rate are investigated. For comparison, the effects on spacecraft-only VLBI are also studied.

Wu, S. C.↗

On the Reliability of Photovoltaic Short-Circuit Current Temperature Coefficient Measurements

The changes in short-circuit current of photovoltaic (PV) cells and modules with temperature are routinely modeled through a single parameter, the temperature coefficient (TC). This parameter is vital for the translation equations used in system sizing, yet in practice is very difficult to measure. In this paper, we discuss these inherent problems and demonstrate how they can introduce unacceptably large errors in PV ratings. A method for quantifying the spectral dependence of TCs is derived, and then used to demonstrate that databases of module parameters commonly contain values that are physically unreasonable. Possible ways to reduce measurement errors are also discussed.

14 SOLAR ENERGY↗

Count Every Trip: Finding the Uncertainty in Energy Estimates Made from Inferred Travel Modes

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 9%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

Count Every Trip: Finding the Uncertainty in Energy Estimates Made from Inferred Travel Modes

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 9%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS↗

Estimating Travel Energy Consumption Uncertainty Based on Inferred Travel Mode and Sensed Travel Length

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 8%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

SU-G-BRB-03: Assessing the Sensitivity and False Positive Rate of the Integrated Quality Monitor (IQM) Large Area Ion Chamber to MLC Positioning Errors

Purpose: To examine both the IQM’s sensitivity and false positive rate to varying MLC errors. By balancing these two characteristics, an optimal tolerance value can be derived. Methods: An un-modified SBRT Liver IMRT plan containing 7 fields was randomly selected as a representative clinical case. The active MLC positions for all fields were perturbed randomly from a square distribution of varying width (±1mm to ±5mm). These unmodified and modified plans were measured multiple times each by the IQM (a large area ion chamber mounted to a TrueBeam linac head). Measurements were analyzed relative to the initial, unmodified measurement. IQM readings are analyzed as a function of control points. In order to examine sensitivity to errors along a field’s delivery, each measured field was divided into 5 groups of control points, and the maximum error in each group was recorded. Since the plans have known errors, we compared how well the IQM is able to differentiate between unmodified and error plans. ROC curves and logistic regression were used to analyze this, independent of thresholds. Results: A likelihood-ratio Chi-square test showed that the IQM could significantly predict whether a plan had MLC errors, with the exception of the beginning and ending control points. Upon further examination, we determined there was ramp-up occurring at the beginning of delivery. Once the linac AFC was tuned, the subsequent measurements (relative to a new baseline) showed significant (p <0.005) abilities to predict MLC errors. Using the area under the curve, we show the IQM’s ability to detect errors increases with increasing MLC error (Spearman’s Rho=0.8056, p<0.0001). The optimal IQM count thresholds from the ROC curves are ±3%, ±2%, and ±7% for the beginning, middle 3, and end segments, respectively. Conclusion: The IQM has proven to be able to detect not only MLC errors, but also differences in beam tuning (ramp-up). Partially supported by the Susan Scott Foundation.

60 APPLIED LIFE SCIENCES↗

A method for monitoring deposition at a solid cathode in an electro-refiner for a two-species system using electrode potentials

Currently, process monitoring of spent nuclear fuel electrorefining relies upon sampling and destructive analysis methods coupled with extrapolated thermodynamic process models for non-interrupted operations. An 'inverse' model was developed to predict the product deposition rates on a cathode using the cell current, cathode potential, and fundamental relations of electrochemistry. The model was applied to the following cases: pure uranium deposition, co-deposition of uranium and plutonium, and co-deposition of uranium and zirconium. The deposition rates predicted by this 'inverse' model were compared to those of a 'forward' model, ERAD. On average, the predicted deposition rates had relative errors of 3.88 % and 2.84 % for U and Pu, respectively, in the case of U/Pu co-deposition and 4.16 % and 7.44 % for U and Zr, respectively, in the case of U/Zr co-deposition. Thus, the 'inverse' model was able to predict the deposition rates without requiring information regarding the feed and salt composition, as the forward model, ERAD, does.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Emittance growth due to random force error

In Refs. Qiang (2019) and Kesting (2015), the authors showed that the emittance growth rate due to the force error of macroparticle sampling will be proportional to the step size of simulation. In this note, we show that for the random force error, the emittance growth rate will be independent of the step size, which is consistent with the simulation observation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Estimating Residual Uncertainties for Lunar Irradiance Measurements Due to Imaging Acquisition Parameters

Lunar calibration is a commonly used method to track a climate satellite sensor's long-term radiometric stability. We present a modeling approach to examine the satellite sensor lunar observation uncertainties due to several important aspects related to the lunar image acquisition by the satellite sensor: lunar pixel shift, point spread function (PSF), lunar orientation, pitch, and oversampling rates. Our analyses can be summarized as follows: (1) The sensor observed lunar irradiance can vary due to small lunar pixel shift if the PSF is less than ideal; (2) During lunar calibration, an unstable oversampling rate due to spacecraft control will result in errors in observed lunar irradiance. A drift in oversampling rate would result in a bias in observed lunar irradiance and a random variation in oversampling rate would cause random error in lunar irradiance. Increasing the overall oversampling rates can reduce random error in observed lunar irradiance but would not change the biases in the observation; (3) Furthermore, the biases can vary when the Moon is observed at different orientations. Our results show impacts on observed lunar irradiance are on the order of 0.1 percent, which is a significant part of the overall uncertainty for a lunar irradiance measurement of a climate satellite sensor.

Oversampling↗