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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Combined selection of the dynamic model and modeling error in nonlinear aeroelastic systems using Bayesian Inference

Here, we report a Bayesian framework for concurrent selection of physics-based models and (modeling) error models. We investigate the use of colored noise to capture the mismatch between the predictions of calibrated models and observational data that cannot be explained by measurement error alone within the context of Bayesian estimation for stochastic ordinary differential equations. Proposed models are characterized by the average data-fit, a measure of how well a model fits the measurements, and the model complexity measured using the Kullback–Leibler divergence. The use of a more complex error models increases the average data-fit but also increases the complexity of the combined model, possibly over-fitting the data. Bayesian model selection is used to find the optimal physical model as well as the optimal error model. The optimal model is defined using the evidence, where the average data-fit is balanced by the complexity of the model. The effect of colored noise process is illustrated using a nonlinear aeroelastic oscillator representing a rigid NACA0012 airfoil undergoing limit cycle oscillations due to complex fluid–structure interactions. Several quasi-steady and unsteady aerodynamic models are proposed with colored noise or white noise for the model error. The use of colored noise improves the predictive capabilities of simpler models.

42 ENGINEERING↗
DOE OSTI2016

Residual position errors of lymph node surrogates in breast cancer adjuvant radiotherapy: Comparison of two arm fixation devices and the effect of arm position correction

Residual position errors of the lymph node (LN) surrogates and humeral head (HH) were determined for 2 different arm fixation devices in radiotherapy (RT) of breast cancer: a standard wrist-hold (WH) and a house-made rod-hold (RH). The effect of arm position correction (APC) based on setup images was also investigated. A total of 113 consecutive patients with early-stage breast cancer with LN irradiation were retrospectively analyzed (53 and 60 using the WH and RH, respectively). Residual position errors of the LN surrogates (Th1-2 and clavicle) and the HH were investigated to compare the 2 fixation devices. The position errors and setup margins were determined before and after the APC to investigate the efficacy of the APC in the treatment situation. A threshold of 5 mm was used for the residual errors of the clavicle and Th1-2 to perform the APC, and a threshold of 7 mm was used for the HH. The setup margins were calculated with the van Herk formula. Irradiated volumes of the HH were determined from RT treatment plans. With the WH and the RH, setup margins up to 8.1 and 6.7 mm should be used for the LN surrogates, and margins up to 4.6 and 3.6 mm should be used to spare the HH, respectively, without the APC. After the APC, the margins of the LN surrogates were equal to or less than 7.5/6.0 mm with the WH/RH, but margins up to 4.2/2.9 mm were required for the HH. The APC was needed at least once with both the devices for approximately 60% of the patients. With the RH, irradiated volume of the HH was approximately 2 times more than with the WH, without any dose constraints. Use of the RH together with the APC resulted in minimal residual position errors and setup margins for all the investigated bony landmarks. Based on the obtained results, we prefer the house-made RH. However, more attention should be given to minimize the irradiation of the HH with the RH than with the WH.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

Quantifying local and global mass balance errors in physics-informed neural networks

Physics-informed neural networks (PINN) have recently become attractive for solving partial differential equations (PDEs) that describe physics laws. By including PDE-based loss functions, physics laws such as mass balance are enforced softly in PINN. This paper investigates how mass balance constraints are satisfied when PINN is used to solve the resulting PDEs. We investigate PINN’s ability to solve the 1D saturated groundwater flow equations (diffusion equations) for homogeneous and heterogeneous media and evaluate the local and global mass balance errors. We compare the obtained PINN’s solution and associated mass balance errors against a two-point finite volume numerical method and the corresponding analytical solution. We also evaluate the accuracy of PINN in solving the 1D saturated groundwater flow equation with and without incorporating hydraulic heads as training data. We demonstrate that PINN’s local and global mass balance errors are significant compared to the finite volume approach. Tuning the PINN’s hyperparameters, such as the number of collocation points, training data, hidden layers, nodes, epochs, and learning rate, did not improve the solution accuracy or the mass balance errors compared to the finite volume solution. Mass balance errors could considerably challenge the utility of PINN in applications where ensuring compliance with physical and mathematical properties is crucial.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Precise method of compensating radiation-induced errors in a hot-cathode-ionization gauge with correcting electrode

To compensate pressure-measurement errors caused by a synchrotron radiation environment, a precise method using a hot-cathode-ionization-gauge head with correcting electrode, was developed and tested in a simulation experiment with excess electrons in the SPring-8 storage ring. This precise method to improve the measurement accuracy, can correctly reduce the pressure-measurement errors caused by electrons originating from the external environment, and originating from the primary gauge filament influenced by spatial conditions of the installed vacuum-gauge head. As the result of the simulation experiment to confirm the performance reducing the errors caused by the external environment, the pressure-measurement error using this method was approximately less than several percent in the pressure range from 10{sup −5} Pa to 10{sup −8} Pa. After the experiment, to confirm the performance reducing the error caused by spatial conditions, an additional experiment was carried out using a sleeve and showed that the improved function was available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Notes on power of normality tests of error terms in regression models

Normality is one of the basic assumptions in applying statistical procedures. For example in linear regression most of the inferential procedures are based on the assumption of normality, i.e. the disturbance vector is assumed to be normally distributed. Failure to assess non-normality of the error terms may lead to incorrect results of usual statistical inference techniques such as t-test or F-test. Thus, error terms should be normally distributed in order to allow us to make exact inferences. As a consequence, normally distributed stochastic errors are necessary in order to make a not misleading inferences which explains a necessity and importance of robust tests of normality. Therefore, the aim of this contribution is to discuss normality testing of error terms in regression models. In this contribution, we introduce the general RT class of robust tests for normality, and present and discuss the trade-off between power and robustness of selected classical and robust normality tests of error terms in regression models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Suppression of vapor cell temperature error for spin-exchange-relaxation-free magnetometer

This paper presents a method to reduce the vapor cell temperature error of the spin-exchange-relaxation-free (SERF) magnetometer. The fluctuation of cell temperature can induce variations of the optical rotation angle, resulting in a scale factor error of the SERF magnetometer. In order to suppress this error, we employ the variation of the probe beam absorption to offset the variation of the optical rotation angle. The theoretical discussion of our method indicates that the scale factor error introduced by the fluctuation of the cell temperature could be suppressed by setting the optical depth close to one. In our experiment, we adjust the probe frequency to obtain various optical depths and then measure the variation of scale factor with respect to the corresponding cell temperature changes. Our experimental results show a good agreement with our theoretical analysis. Under our experimental condition, the error has been reduced significantly compared with those when the probe wavelength is adjusted to maximize the probe signal. The cost of this method is the reduction of the scale factor of the magnetometer. However, according to our analysis, it only has minor effect on the sensitivity under proper operating parameters.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Effect of initial phase on error in electron energy obtained using paraxial approximation for a focused laser pulse in vacuum

We have investigated the effect of initial phase on error in electron energy obtained using paraxial approximation to study electron acceleration by a focused laser pulse in vacuum using a three dimensional test-particle simulation code. The error is obtained by comparing the energy of the electron for paraxial approximation and seventh-order correction description of the fields of Gaussian laser. The paraxial approximation predicts wrong laser divergence and wrong electron escape time from the pulse which leads to prediction of higher energy. The error shows strong phase dependence for the electrons lying along the axis of the laser for linearly polarized laser pulse. The relative error may be significant for some specific values of initial phase even at moderate values of laser spot sizes. The error does not show initial phase dependence for a circularly laser pulse.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Statistical and systematic errors in the measurement of weak-lensing Minkowski functionals: Application to the Canada-France-Hawaii Lensing Survey

The measurement of cosmic shear using weak gravitational lensing is a challenging task that involves a number of complicated procedures. We study in detail the systematic errors in the measurement of weak-lensing Minkowski Functionals (MFs). Specifically, we focus on systematics associated with galaxy shape measurements, photometric redshift errors, and shear calibration correction. We first generate mock weak-lensing catalogs that directly incorporate the actual observational characteristics of the Canada-France-Hawaii Lensing Survey (CFHTLenS). We then perform a Fisher analysis using the large set of mock catalogs for various cosmological models. We find that the statistical error associated with the observational effects degrades the cosmological parameter constraints by a factor of a few. The Subaru Hyper Suprime-Cam (HSC) survey with a sky coverage of ∼1400 deg{sup 2} will constrain the dark energy equation of the state parameter with an error of Δw {sub 0} ∼ 0.25 by the lensing MFs alone, but biases induced by the systematics can be comparable to the 1σ error. We conclude that the lensing MFs are powerful statistics beyond the two-point statistics only if well-calibrated measurement of both the redshifts and the shapes of source galaxies is performed. Finally, we analyze the CFHTLenS data to explore the ability of the MFs to break degeneracies between a few cosmological parameters. Using a combined analysis of the MFs and the shear correlation function, we derive the matter density Ω{sub m0}=0.256±{sub 0.046}{sup 0.054}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Taylor approximation variance reduction for approximation errors in PDE-constrained Bayesian inverse problems

In numerous applications, surrogate models are used as a replacement for accurate parameter-to-observable mappings when solving large-scale inverse problems governed by partial differential equations (PDEs). The surrogate model may be a computationally cheaper alternative to the accurate parameter-to-observable mappings and/or may ignore additional unknowns or sources of uncertainty. The Bayesian approximation error (BAE) approach provides a means to account for the induced uncertainties and approximation errors, i.e. the errors between the accurate parameter-to-observable mapping and the surrogate. The statistics of these errors are, however, in general unknown a priori, and are thus calculated using Monte Carlo sampling. Although the sampling is typically carried out offline, i.e. before considering the data, the process can still represent a computational bottleneck. In this work, we develop a scalable computational approach for reducing the costs associated with the sampling stage of the BAE approach. Specifically, we consider the Taylor expansion of the accurate and surrogate forward models with respect to the uncertain parameter fields either as a control variate for variance reduction or as a means to directly and efficiently approximate the mean and covariance of the approximation errors. We propose efficient methods for evaluating the expressions for the mean and covariance of the Taylor approximations based on linear(-ized) PDE solves. Furthermore, the proposed approach is independent of the dimension of the uncertain parameter, depending instead on the intrinsic dimension of the data, ensuring scalability to high-dimensional problems. The potential benefits of the proposed approach are demonstrated for two high-dimensional inverse problems governed by PDE examples, namely for the estimation of a distributed Robin boundary coefficient in a linear diffusion problem, and for a coefficient estimation problem governed by a nonlinear diffusion problem.

Bayesian approximation error↗
DOE OSTI2019

Ancilla-Free Quantum Error Correction Codes for Quantum Metrology

Quantum error correction has recently emerged as a tool to enhance quantum sensing under Markovian noise. It works by correcting errors in a sensor while letting a signal imprint on the logical state. This approach typically requires a specialized error-correcting code, as most existing codes correct away both the dominant errors and the signal. To date, however, few such specialized codes are known, among which most require noiseless, controllable ancillas. We show here that such ancillas are not needed when the signal Hamiltonian and the error operators commute, a common limiting type of decoherence in quantum sensors. We give a semidefinite program for finding optimal ancilla-free sensing codes in general, as well as closed-form codes for two common sensing scenarios: qubits undergoing dephasing, and a lossy bosonic mode. Lastly, we analyze the sensitivity enhancement offered by the qubit code under arbitrary spatial noise correlations, beyond the ideal limit of orthogonal signal and noise operators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Destructive Error Interference in Product-Formula Lattice Simulation

Quantum computers can efficiently simulate the dynamics of quantum systems. Here, we study the cost of digitally simulating the dynamics of several physically relevant systems using the first-order product-formula algorithm. We show that the errors from different Trotterization steps in the algorithm can interfere destructively, yielding a much smaller error than previously estimated. In particular, we prove that the total error in simulating a nearest-neighbor interacting system of n sites for time t using the first-order product formula with r time slices is O ( n t / r + n t 3 / r 2 ) when n t 2 / r is less than a small constant. Given an error tolerance ϵ , the error bound yields an estimate of max { O ( n 2 t / ϵ ) , O ( n 2 t 3 / 2 / ϵ 1 / 2 ) } for the total gate count of the simulation. The estimate is tighter than previous bounds and matches the empirical performance observed in Childs et al. [ Proc. Natl. Acad. Sci. U.S.A. 115 , 9456 (2018) ]. We also provide numerical evidence for potential improvements and conjecture an even tighter estimate for the gate count.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Error-Detectable Bosonic Entangling Gates with a Noisy Ancilla

Bosonic quantum error correction has proven to be a successful approach for extending the coherence of quantum memories, but to execute deep quantum circuits, high-fidelity gates between encoded qubits are needed. To that end, we present a family of error-detectable two-qubit gates for a variety of bosonic encodings. From a new geometric framework based on a “Bloch sphere” of bosonic operators, we construct ZZ L ⁡(θ) and exponential-swap(θ) gates for the binomial, four-legged cat, dual-rail, and several other bosonic codes. The gate Hamiltonian is simple to engineer, requiring only a programmable beam splitter between two bosonic qubits and an ancilla dispersively coupled to one qubit. This Hamiltonian can be realized in circuit QED hardware with ancilla transmons and microwave cavities. The proposed theoretical framework was developed for circuit QED but is generalizable to any platform that can effectively generate this Hamiltonian. Crucially, one can also detect first-order errors in the ancilla and the bosonic qubits during the gates. We show that this allows one to reach error-detected gate fidelities at the 0.01% level with today’s hardware, limited only by second-order hardware errors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Small Bragg-plane slope errors revealed in synthetic diamond crystals

Wavefront-preserving X-ray diamond crystal optics are essential for numerous applications in X-ray science. Perfect crystals with flat Bragg planes are a prerequisite for wavefront preservation in Bragg diffraction. However, this condition is difficult to realize in practice because of inevitable crystal imperfections. Here, X-ray rocking curve imaging is used to study the smallest achievable Bragg-plane slope errors in the best presently available synthetic diamond crystals and how they compare with those of perfect silicon crystals. It is shown that the smallest specific slope errors in the best diamond crystals are about 0.08 (3) µrad mm -2 . These errors are only 50% larger than the 0.05 (2) µrad mm -2 specific slope errors measured in perfect silicon crystals. High-temperature annealing at 1450°C of almost flawless diamond crystals reduces the slope errors very close to those of silicon. Further investigations are in progress to establish the wavefront-preservation properties of these crystals.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Optimizing Error-Bounded Lossy Compression for Scientific Data With Diverse Constraints

Vast volumes of data are produced by today's scientific simulations and advanced instruments. These data cannot be stored and transferred efficiently because of limited I/O bandwidth, network speed, and storage capacity. Error-bounded lossy compression can be an effective method for addressing these issues: not only can it significantly reduce data size, but it can also control the data distortion based on user-defined error bounds. In practice, many scientific applications have specific requirements or constraints for lossy compression, in order to guarantee that the reconstructed data are valid for post hoc analysis. For example, some datasets contain irrelevant data that should be isolated in particular and users often have intuition regarding value ranges, geospatial regions, and other data subsets that are crucial for subsequent analysis. Existing state-of-the-art error-bounded lossy compressors, however, do not consider these constraints during compression, resulting in inferior compression ratios with respect to user's post hoc analysis, due to the fact that the data itself provides little or no value for post hoc analysis. In this work we address this issue by proposing an optimized framework that can preserve diverse constraints during the error-bounded lossy compression, e.g., cleaning the irrelevant data, efficiently preserving different precision for multiple value intervals, and allowing users to set diverse precision over both regular and irregular regions. We perform our evaluation on a supercomputer with up to 2,100 cores. Experiments with six real-world applications show that our proposed diverse constraints based error-bounded lossy compressor can obtain a higher visual quality or data fidelity on reconstructed data with the same or even higher compression ratios compared with the traditional state-of-the-art compressor SZ. Furthermore, our experiments also demonstrate very good scalability in compression performance compared with the I/O throughput of the parallel file system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Rapid Commissioning of Large Machine Tools Using Finite Element-Based Correction of Geometric Errors

Large computer numerical control (CNC) machine tools derive their stiffness from monolithic cast iron bases or weldments that are sometimes integral to machine motion systems like box ways or guideways. However, the sheer size of castings and even floor flatness deviations result in dimensional errors in these systems, which manifest as machine motion errors. Typical geometric alignment processes rely on an iterative approach, where measurements are taken to assess alignment (straightness, squareness, and parallelism), followed by adjustment of the machine supports (fixators or leveling pads), which can take weeks even for an experienced operator. Conversely, a novel method is proposed to shorten the correction time by eliminating the trial-and-error process in favor of a more deterministic approach guided by a finite element (FE) method. A feasibility study is conducted on a CNC polymer hybrid machine, with a steel weldment frame, supported by six leveling pads. An FE model of the frame is utilized to obtain recommended leveling pad adjustments, based on measurement of machine errors taken using a laser tracker. After a single adjustment cycle, measurements reveal that geometric errors of the machine tool are reduced from 2.22 mm of flatness deviation to 0.32 mm, achieving an 85.6% reduction. Furthermore, the entire process including measurement, adjustment, and assessment is completed in just 6 h by two operators who are not professional service engineers. In conclusion, this methodology demonstrates feasibility for scaling up, especially to large, high-precision CNC machine tools with bases mounted by fixators, offering the capability for bidirectional adjustment.

42 ENGINEERING↗
DOE OSTI2014

Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI-RADS features

Purpose: The purpose of this study is to explore Breast Imaging-Reporting and Data System (BI-RADS) features as predictors of individual errors made by trainees when detecting masses in mammograms. Methods: Ten radiology trainees and three expert breast imagers reviewed 100 mammograms comprised of bilateral medial lateral oblique and craniocaudal views on a research workstation. The cases consisted of normal and biopsy proven benign and malignant masses. For cases with actionable abnormalities, the experts recorded breast (density and axillary lymph nodes) and mass (shape, margin, and density) features according to the BI-RADS lexicon, as well as the abnormality location (depth and clock face). For each trainee, a user-specific multivariate model was constructed to predict the trainee's likelihood of error based on BI-RADS features. The performance of the models was assessed using area under the receive operating characteristic curves (AUC). Results: Despite the variability in errors between different trainees, the individual models were able to predict the likelihood of error for the trainees with a mean AUC of 0.611 (range: 0.502–0.739, 95% Confidence Interval: 0.543–0.680,p < 0.002). Conclusions: Patterns in detection errors for mammographic masses made by radiology trainees can be modeled using BI-RADS features. These findings may have potential implications for the development of future educational materials that are personalized to individual trainees.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-F-BRD-03: Determination of Plan Robustness for Systematic Setup Errors Using Trilinear Interpolation

Purpose: Treatment plan evaluations in radiotherapy are currently ignoring the dosimetric impact of setup uncertainties. The determination of the robustness for systematic errors is rather computational intensive. This work investigates interpolation schemes to quantify the robustness of treatment plans for systematic errors in terms of efficiency and accuracy. Methods: The impact of systematic errors on dose distributions for patient treatment plans is determined by using the Swiss Monte Carlo Plan (SMCP). Errors in all translational directions are considered, ranging from −3 to +3 mm in mm steps. For each systematic error a full MC dose calculation is performed leading to 343 dose calculations, used as benchmarks. The interpolation uses only a subset of the 343 calculations, namely 9, 15 or 27, and determines all dose distributions by trilinear interpolation. This procedure is applied for a prostate and a head and neck case using Volumetric Modulated Arc Therapy with 2 arcs. The relative differences of the dose volume histograms (DVHs) of the target and the organs at risks are compared. Finally, the interpolation schemes are used to compare robustness of 4- versus 2-arcs in the head and neck treatment plan. Results: Relative local differences of the DVHs increase for decreasing number of dose calculations used in the interpolation. The mean deviations are <1%, 3.5% and 6.5% for a subset of 27, 15 and 9 used dose calculations, respectively. Thereby the dose computation times are reduced by factors of 13, 25 and 43, respectively. The comparison of the 4- versus 2-arcs plan shows a decrease in robustness; however, this is outweighed by the dosimetric improvements. Conclusion: The results of this study suggest that the use of trilinear interpolation to determine the robustness of treatment plans can remarkably reduce the number of dose calculations. This work was supported by Varian Medical Systems. This work was supported by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Poster — Thur Eve — 08: Rotational errors with on-board cone beam computed tomography

The focus of this study is on the Elekta XVI on-board cone beam computed tomography (CBCT) system. A rotational mismatch as large as 0.5° is observed between clockwise (CW) and counter-clockwise (CCW) CBCT scans. The error could affect non-isocentric treatments (e.g., lung SBRT and acoustic neuroma), as well as off-axis organs-at-risk. The error is caused by mislabeling of the projections with a lagging gantry angle, which is caused by the finite image acquisition time and delays in the imaging system. A 30 cm diameter cylindrical phantom with 5 mm diameter holes is used for the scanning. CW and CCW scans are acquired for five gantry speeds (360 to 120 deg./min.) on six linacs from three generations (MLCi, MLCi2, and Agility). Additional scans are acquired with different x-ray pulse widths for the same mAs. In the automated CBCT analysis (using ImageJ), the CW/CCW mismatch in a series of line profiles is identified and used to calculate the rotational error. Results are consistent among all linacs and indicate that the error varies linearly with gantry speed. The finite width of the x-ray pulses is a major but predictable contributor to the delay causing the error. For 40 ms pulses, the delay is 34 ± 1 ms. A simple solution applied in our clinic is adjusting the gantry angle offset to make the CCW one-minute scans correct. A more involved approach we are currently investigating includes adjustments of pulse width and mA, resulting in focal spot changes, with potential impact on image quality.

60 APPLIED LIFE SCIENCES↗