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Th effects of device technology and scaling on soft error rates are discussed, using information obtained from both the device and space communities as a guide to determine the net effect on soft errors.
We present a computational model of a closed-loop, pilot-aircraft-visual scene-taxiway system created to shed light on possible sources of taxi error. Creating the cognitive aspects of the model using ACT-R required us to conduct studies with subject matter experts to identify experiential adaptations pilots bring to taxiing. Five decision strategies were found, ranging from cognitively-intensive but precise, to fast, frugal but robust. We provide evidence for the model by comparing its behavior to a NASA Ames Research Center simulation of Chicago O'Hare surface operations. Decision horizons were highly variable; the model selected the most accurate strategy given time available. We found a signature in the simulation data of the use of globally robust heuristics to cope with short decision horizons as revealed by errors occurring most frequently at atypical taxiway geometries or clearance routes. These data provided empirical support for the model.
Reviewed NTSB reports of the 19 U.S. airline accidents between 1991-2000 attributed primarily to crew error. Asked: Why might any airline crew in situation of accident crew--knowing only what they knew--be vulnerable. Can never know with certainty why accident crew made specific errors but can determine why the population of pilots is vulnerable. Considers variability of expert performance as function of interplay of multiple factors.
We evaluate in detail the stability requirements for a band-limited coronagraph with an inner working angle as small as 2 lambda/D coupled to an off-axis, 3.8-m diameter telescope. We have updated our methodologies since presenting a stability error budget for the Terrestrial Planet Finder Coronagraph mission that worked at 4 lambda/D and employed an 8th-order mask to reduce aberration sensitives. In the previous work, we determined the tolerances relative to the total light leaking through the coronagraph. Now, we separate the light into a radial component, which is readily separable from a planet signal, and an azimuthal component, which is easily confused with a planet signal. In the current study, throughput considerations require a 4th-order coronagraph. This, combined with the more aggressive working angle, places extraordinarily tight requirements on wavefront stability and opto-mechanical stability. We find that the requirements are driven mainly by coma that leaks around the coronagraph mask and mimics the localized signal of a planet, and pointing errors that scatter light into the background, decreasing SNR. We also show how the requirements would be relaxed if a low-order aberration detection system could be employed.
Mobile and embedded applications are emerging in the growing field of free space optical links (FSOL). Some mobile applications for FSOL include spacecraft, aircraft, and automotive. These applications by nature require low size weight and power (SWaP) solutions. The main challenge with any FSOL system is the strict pointing requirements. Common solutions to pointing and alignment of FSOL include gimbals, fast steering mirrors, and adaptive optics. All of which provide viable solutions at the cost of increased SWaP. Previously, we presented the use of both large core fibers and double clad fibers (DCF) to interface FSOL transmit and receive optics with small form factor pluggable optical transceivers (SFP). Double clad fibers have been shown to enable a common optical path by transmitting through a single mode core and receiving through a large inner cladding. This enables a single set of symmetric transmit and receive optics, which decreases the SWaP. In addition, using DCF increases the received power stability of the link relative to a multi-mode fiber (MMF) transmitting. To determine the viability of the system, bit error rate performance needs to be investigated. The results of this paper show that at a bit rate of 10 Gbps, double clad fibers offer similar bit error rate performance to single mode fibers when transmitting and multi-mode fibers when receiving enabling a symmetric duplex FSOL reducing SWaP.
Mobile and embedded applications are emerging in the growing field of free space optical links (FSOL). Some mobile applications for FSOL include spacecraft, aircraft, and automotive. These applications by nature require low size weight and power (SWaP) solutions. The main challenge with any FSOL system is the strict pointing requirements. Common solutions to pointing and alignment of FSOL include gimbals, fast steering mirrors, and adaptive optics. All of which provide viable solutions at the cost of increased SWaP. Previously, we presented the use of both large core fibers and double clad fibers (DCF) to interface FSOL transmit and receive optics with small form factor pluggable optical transceivers (SFP). Double clad fibers have been shown to enable a common optical path by transmitting through a single mode core and receiving through a large inner cladding. This enables a single set of symmetric transmit and receive optics, which decreases the SWaP. In addition, using DCF increases the received power stability of the link relative to a multi-mode fiber (MMF) transmitting. To determine the viability of the system, bit error rate performance needs to be investigated. The results of this paper show that at a bit rate of 10 Gbps, double clad fibers offer similar bit error rate performance to single mode fibers when transmitting and multi-mode fibers when receiving enabling a symmetric duplex FSOL reducing SWaP.
Finite element models (FEM) are routinely developed and used during fabrication of high dollar-value hardware. NASA as part of the pre-flight certification of launch vehicles routinely conducts vibration and static tests to calibrate models used for flight-risk assessments. As part of the calibration process, certain areas in the model are modified, using engineering judgment and sensitivity analysis, to match the test results. Unfortunately, tools to identify problem areas in the FEM using test data directly are scarce. Over the years, Error Localization Algorithms (ELA) have been proposed with very limited success. Recently, the Analytical Dynamics Model Improvement (ADMI) algorithm, which computes closed-form mass and stiffness corrections to match the test data exactly, have been shown to be effective for error localization. The paper will present several FEM example problems where ELA is used with simulated test data to determine FEM problem areas. For each example, the correct answer is shown along with ELA results. It is shown that the ELA process is able to identify general problem areas in the FEM, which are consistent with known model perturbations. However, in most cases the ELA identified area of improvement is larger than the true answer. Nonetheless, with proper optimization tools, calibration results using the ELA identified areas provide excellent results.
Finite element models (FEM) are routinely developed and used during fabrication of high dollar-value hardware. NASA, as part of the pre-flight certification of launch vehicles, routinely conducts vibration and static tests to calibrate models used for flight-risk assessments. During model calibration, certain areas of the model are modified, using engineering judgment and sensitivity analysis, to match the test results. Unfortunately, tools to identify problem areas in the FEM using test data directly are scarce and infrequently applied. Over the years, error localization algorithms have been proposed with very limited success. Recently, the Analytical Dynamics Model Improvement (ADMI) algorithm, which computes closed-form mass and stiffness corrections to match the test data exactly, have been shown to be an effective Error Localization Algorithm (ELA). The paper discusses three examples where ELA is used with simulated test data to locate problem areas. To gain confidence in the approach, the exact answer is shown along with ELA results. Results show that ELA is able to identify general problem areas consistent with known problem areas. In all examples, the ELA identified area is larger than the exact problem area. Nonetheless, with proper optimization tools, calibration results using the ELA identified areas provide excellent results.
This paper discusses the effect of global model error on probability of collision (Pc) determination. Modifications to the Pc formulation for cross-correlation of orbital error in prediction are developed and assessed for recent conjunctions. While specific geometries can be identified or constructed to produce significant change in Pc for the modified formulation, it is of operational interest to quantify the relative occurrence of such cases for satellite conjunction risk assessment. Such analysis is feasible per data collections in place over the past year.
Beginning in 2025, the NASA Quesst mission will conduct a series of community response tests involving flyovers of the X-59 aircraft at select localities across the United States. Several waves of a longitudinal survey will be administered over approximately one month of testing in order to capture perceptual responses to low-amplitude sonic booms, or “sonic thumps”. Simultaneously, noise exposure levels will be estimated by fusing model-based predictions with measurements taken from a sparse network of monitors in the region. As one of the aims of the study is to produce a dose-response curve, a regression model relating perceptual response to noise exposure levels, it is important to acknowledge the potential attenuation bias that results from measurement error in the estimated noise exposure levels. In this presentation we review and compare several methods for dealing with measurement error in generalized linear mixed models. The methods are demonstrated on simulated data and real data collected during past NASA risk reduction studies.
Technology for a large-area, high-angular resolution mirror module for a future Great Observatory x-ray mission is progressing along different paths. To date, none of these are fully developed. Work at the Marshall Space Flight Center (MSFC) seeks to leverage the benefits of full shell optics while exploring the limits of using shell replication technology for optics production. Here, we provide an updated accounting of spatial-resolution-constraining error terms to give context to recent improvements in MSFC replicated optics, as well as guidance and justification for current and future directions of research. Content includes strawman error allocations for an optical system that is parametrically Lynx-like, where the replicated-optics technology stands relative to these allocations, and methodology for mapping development plans to efficiently identify the limiting factors and approaches to overcoming these.
This is training presentation for REA (Reading Error Analysis) software. REA is designed for analyzing UGT scope reading errors and for developing reading points optimization algorithms.
Active learning sequentially selects the best instance for labeling by optimizing an acquisition function to enhance data/label efficiency. The selection can be either from a discrete instance set (pool-based scenario) or a continuous instance space (query synthesis scenario). In this work, we study both active learning scenarios for Gaussian Process Classification (GPC). The existing active learning strategies that maximize the Estimated Error Reduction (EER) aim at reducing the classification error after training with the new acquired instance in a onestep-look-ahead manner. The computation of EER-based acquisition functions is typically prohibitive as it requires retraining the GPC with every new query. Moreover, as the EER is not smooth, it can not be combined with gradient-based optimization techniques to efficiently explore the continuous instance space for query synthesis. To overcome these critical limitations, we develop computationally efficient algorithms for EER-based active learning with GPC. Further, we derive the joint predictive distribution of label pairs as a one-dimensional integral, as a result of which the computation of the acquisition function avoids retraining the GPC for each query, remarkably reducing the computational overhead. We also derive the gradient chain rule to efficiently calculate the gradient of the acquisition function, which leads to the first query synthesis active learning algorithm implementing EER-based strategies. Our experiments clearly demonstrate the computational efficiency of the proposed algorithms. We also benchmark our algorithms on both synthetic and real-world datasets, which show superior performance in terms of sampling efficiency compared to the existing state-of-the-art algorithms.
Humans are an integral part of a nuclear power plant (NPP) from its construction, to its everyday maintenance and operation. In the nuclear industry there are many approaches to quantifying component reliability, which is called probability risk assessment (PRA). In PRA there are two considerations given to the quantification, static and dynamic. Static is quantified before or after an operation; and dynamic is time dependent, in that the probability changes as real time data are provided. In PRA, the importance of the components is calculated, but what of the importance of the human component? There are several methods for human reliability analysis (HRA), which include but are not limited to: THERP, ATHEANA, CREAM, SPAR-H, ASEP, and SLIM. Each of these methods aims to provide a more accurate and objective human error probability (HEP) quantification. Of the methods listed above, ASEP, THERP, and SPAR-H are all inextricably linked. The Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method was generated to better generalize the Technique for Human Error Rate Prediction (THERP) and Accident Sequence Precursor (ASEP). THERP is mapped to specific scenario templates, and ASEP is a simplified screening method, while SPAR-H employs generalizations to describe the spectrum of human behavior while maintaining the same theoretical underpinnings. SPAR-H is a well-known and accepted HRA method that uses performance shaping factors (PSFs) to classify inputs to the human component. PSFs capture a wide variety of input data, including plant status, crew dynamics, task description, and psychological aspects of the human operator. Current efforts have been focused to further generalize SPAR-H in to a dynamic framework. These methods can fit into dynamic NPP simulations such as RAVEN / RELAP-7. In order to do this, a dynamic methodology is applied to model the human as would be applied to the components. This method is applied in part one in the accompanying paper.
The environmental pollutant 3-nitrobenzanthrone produces bulky aminobenzanthrone (ABA) DNA adducts with both guanine and adenine nucleobases. A major product occurs at the C8 position of guanine (C8-dG-ABA). These adducts present a strong block to replicative polymerases but, remarkably, can be bypassed in a largely error-free manner by the human Y-family polymerase η (hPol η). Here, we report the crystal structure of a ternary Pol•DNA•dCTP complex between a C8-dG-ABA-containing template:primer duplex and hPol η. The complex was captured at the insertion stage and provides crucial insight into the mechanism of error-free bypass of this bulky lesion. Specifically, bypass involves accommodation of the ABA moiety inside a hydrophobic cleft to the side of the enzyme active site and formation of an intra-nucleotide hydrogen bond between the phosphate and ABA amino moiety, allowing the adducted guanine to form a standard Watson–Crick pair with the incoming dCTP.
Abstract Metal‐exchanged zeolites are complex catalytic systems with great potential for applications in hydrocarbon conversion processes. The numerous combinations of zeotypes and metal‐based Lewis acid motifs create a vast material space that can only be effectively navigated with robust structure‐function relationships. Exhaustive modeling of extraframework metal sites in all crystallographically distinct framework positions is not practical; thus, we quantified the uncertainties arising from the use of simplified active site representations using the C−H bond activation in methane as a probe reaction. Density functional theory calculations and statistical analysis of associated error ensembles suggest that the Lewis acid identity primarily determines the reactivity of the zeolite towards methane activation, with other factors such as zeolite model characteristics deemed secondary. The error ensemble distributions were used to predict the relative probability of creating active C−H bond scission fragments in metal‐exchanged zeolites, and thus can be used to efficiently screen various metal‐exchange candidates in their efficacy towards hydrocarbon conversion.
A holographic CFT description of asymptotically flat spacetimes inherits vacuum degeneracies and IR divergences from its gravitational dual. We devise a Quantum Error Correcting (QEC) framework to encode both effects as correctable fluctuations on the CFT dual. The framework is physically motivated by embedding a chain of qudits in the so-called Klein spacetime and then taking a continuum 𝑁 → ∞ limit. At finite 𝑁 the qudit chain 1) enjoys a discrete version of celestial symmetries and 2) supports a Gottesman-Kitaev-Preskill (GKP) code. The limit results in hard states with quantized BMS hair in the celestial torus forming the logical subspace, robust under errors induced by soft radiation. Technically, the construction leverages the recently studied 𝑤 1+∞ hierarchy of soft currents and its realization from a sigma model in twistor space.
Frustrated by worse than expected error for both peak area and time-of-flight (TOF) in matrix assisted laser desorption ionization (MALDI) experiments using samples prepared by electrospray deposition, it was finally determined that there was a correlation between sample location on the target plate and the measured TOF/peak area. Variations in both TOF and peak area were found to be due to small differences in the initial position of ions formed in the source region of the TOF mass spectrometer. These differences arise largely from misalignment of the instrument sample stage, with a smaller contribution arising from the non-ideal shape of the target plates used. By physically measuring the target plates used and comparing TOF data collected from three different instruments, an estimate of the magnitude and direction of the sample stage misalignment was determined for each of the instruments. A correction method was developed to correct the TOFs and peak areas obtained for a given combination of target plate and instrument. Two correction factors are determined, one by initially collecting spectra from each sample position used and another by using spectra from a single position for each set of samples on a target plate. For TOF and mass values, use of the correction factor reduced the error by a factor of 4, with the relative standard deviation (RSD) of the corrected masses being reduced to 12-24 ppm. For the peak areas, the RSD was reduced from 28% to 16% for samples deposited twice onto two target plates over two days. .