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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Identification of interactions in fractional-order systems with high dimensions

This article proposes an approach to identify fractional-order systems with sparse interaction structures and high dimensions when observation data are supposed to be experimentally available. This approach includes two steps: first, it is to estimate the value of the fractional order by taking into account the solution properties of fractional-order systems; second, it is to identify the interaction coefficients among the system variables by employing the compressed sensing technique. An error analysis is provided analytically for this approach and a further improved approach is also proposed. Moreover, the applicability of the proposed approach is fully illustrated by two examples: one is to estimate the mutual interactions in a complex dynamical network described by fractional-order systems, and the other is to identify a high fractional-order and homogeneous sequential differential equation, which is frequently used to describe viscoelastic phenomena. All the results demonstrate the feasibility of figuring out the system mechanisms behind the data experimentally observed in physical or biological systems with viscoelastic evolution characters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

More buck-per-shot: Why learning trumps mitigation in noisy quantum sensing

Quantum sensing is one of the most promising applications for quantum technologies. However, reaching the ultimate sensitivities enabled by the laws of quantum mechanics can be a challenging task in realistic scenarios where noise is present. While several strategies have been proposed to deal with the detrimental effects of noise, these come at the cost of an extra shot budget. Given that shots are a precious resource for sensing – as infinite measurements could lead to infinite precision – care must be taken to truly guarantee that any shot not being used for sensing is actually leading to some metrological improvement. In this work, we study whether investing shots in error-mitigation, inference techniques, or combinations thereof, can improve the sensitivity of a noisy quantum sensor on a (shot) budget. We present a detailed bias–variance error analysis for various sensing protocols. Our results show that the costs of zero-noise extrapolation techniques outweigh their benefits. We also find that pre-characterizing a quantum sensor via inference techniques leads to the best performance, under the assumption that the sensor is sufficiently stable.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Wave Measurements Using Multi-Frame Processing of Marine Radar Data

Marine radars have proven to be useful for measuring ocean waves, but the accuracy of the measurements is limited by several factors including the look-angle dependence of the radar signals as well as noise in the radar data. The look-angle dependence introduces a systematic error or bias in the measurements, and noise causes a random error. This paper describes a method of combining data from multiple radar frames that is optimal in the sense of minimizing the error for a set of biased measurements with random additive noise. The results are shown experimentally to increase the correlation of the radar estimates with buoy measurements.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Noise Constraints on Sensitivity Scaling in Quantum Nonlinear Metrology

Quantum-enhanced metrology surpasses classical metrology by improving estimation precision scaling with a resource 𝑁 (e.g., particle number or energy) from 1/√𝑁 to 1/𝑁. Through the use of nonlinear effects, Roy and Braunstein [Exponentially enhanced quantum metrology, Phys. Rev. Lett. 100, 220501 (2008)] derived a 1/𝑁 2 scaling. However, later works argued this exponential improvement is unphysical and that even modest gains, like 1/𝑁 2 , may vanish under noise. We show that, in the presence of small errors, the nonlinear interactions enabling metrological enhancement induce emergent errors. Here, the errors propagate through the sensing protocol and are magnified proportional to any intended nonlinear enhancement. We identify a critical value of the parameter to be estimated, for a fixed error, below which the emergent errors can be avoided.

Quantum Fisher information↗
DOE OSTI2023

High-speed Focal Plane Wave Front Sensing with an Optical Chopper

Focal plane wave front sensing and control is a critical approach to reducing noncommon path errors between a conventional astronomical adaptive optics (AO) wave front sensor (WFS) detector and a science camera. However, in addition to mitigating noncommon path errors, recent focal plane wave front sensing techniques have been developed to operate at speeds fast enough to enable "multi-WFS" AO, where residual atmospheric errors are further corrected by a focal plane WFS. Although a number of such techniques have been recently developed for coronagraphic imaging, here we present one designed for noncoronagraphic imaging. Utilizing conventional AO system components, this concept additionally requires (1) a detector imaging the focal plane of the WFS light source and (2) a pupil plane optical chopper device that is the noncommon path to the first WFS and is synchronized to the focal plane imager readout. These minimal hardware requirements enable the temporal amplitude modulation to resolve the sine ambiguity of even wave-front modes for low, mid, and high wave front spatial frequencies. Similar capabilities have been demonstrated with classical phase diversity by defocusing the detector, but such techniques are incompatible with simultaneous science observations. This optical chopping technique, however, enables science imaging at up to 50% duty cycle. In conclusion, we present both simulations and laboratory validation of this concept on SEAL, the Santa Cruz Extreme AO Laboratory testbed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Distributed fiber optic strain sensing of bending deformation of a well mockup in the laboratory

Well integrity is critical to the safety and success of subsurface energy exploration and management, as leakage of fluids from subsurface reservoirs is often induced by compromised wells. This study investigates bending deformation of a mockup of an oil/gas well that is subjected to loads expected in deviated wells under reservoir compaction and assesses the feasibility of utilizing distributed fiber optic strain sensing to monitor the deformation. Here, a well mockup, which consists of outer and inner steel pipes with a cemented annulus, is tested under three-point bending loading and its strain and curvature development is monitored by Brillouin optical time domain reflectometry/analysis (BOTDR/A) as well as optical frequency domain reflectometry (OFDR). The primary objective of this research is to assess the strain sensing performance of newly fabricated fiber optic cables and to identify key cable characteristics which could improve the quality of distributed strain measurements with BOTDR/A. Results show that the tight-buffered cable is best suited for strain sensing as its maximum errors in the strain measurement were -36% and -24% against conventional sensors at the maximum elastic and plastic bending loads, respectively, whereas those of the non-tight-buffered cable were -45% and -71%, respectively. Similar trends were obtained in the bending curvature measurement. The detailed design of the tight-buffered cable is presented to elucidate key characteristics of such a cable, which will facilitate accurate distributed strain sensing in oil and gas wells.

42 ENGINEERING↗
DOE OSTI2020

Exploratory Investigation of Disengagements and Crashes in Autonomous Vehicles Under Mixed Traffic: An Endogenous Switching Regime Framework

Autonomous Vehicles (AVs) have a large potential to improve traffic safety but also pose some critical challenges. While AVs may help reduce crashes caused by human error, they still may experience failures of technologies and sensing, as well as decision-making errors in a mixed traffic environment. A disengagement refers to an AV transitioning control from autonomous systems to the trained test driver. The safety critical nature of disengagements makes it imperative to analyze disengagements and crashes together. In this study, we analyze both crashes and disengagements from real-world AV driving in California to fill the knowledge gap regarding the relationship between disengagements and crashes in a mixed traffic environment. A nested logit model was calibrated using three different outcomes: (1) disengagement with a crash, (2) disengagement with no crash, and (3) no disengagement with a crash. Furthermore, endogenous switching regime models were also calibrated to draw distinctions between the relation of disengagements and crashes while accounting for endogeneity effects. The results show that factors related to AV systems (such as software failures) and other roadway participants increase the propensity of a disengagement without a crash. Furthermore, AVs were observed to disengage less often as the technology matured over time. Marginal effects revealed an 8% decrease. The results thus suggest that disengagements are a part of AVs' safe performance and disengagement alerts may need to be triggered in order to avoid certain failures with current technology.

42 ENGINEERING↗
DOE OSTI2022

Width-Based Discharge Partitioning in Distributary Networks: How Right We Are

River deltas are home to large populations and can be composed of complex channel networks which convey flows of matter to the shoreline. Knowledge of flow within individual channels is needed to quantify the distribution of discharge across the delta, and thus its sustainability over time. Due to a lack of field measurements at the local channel scale, researchers leverage remote sensing data to estimate the partitioning of flow. We compare data from 15 river deltas to discharge partitioning estimates based on channel network graphs derived from remote sensing imagery. We quantify errors in the common width-based method and test alternative partitioning techniques to find that width-based discharge partitioning is universally applicable, suggesting that absent any site-specific information, discharge partitioning by average channel width is an appropriate approach. We also provide networks, streamflow measurements, and flux partitioning estimates for 28 delta networks as the Discharge In Distributary NeTworks (DIDNT) dataset.

58 GEOSCIENCES↗
DOE OSTI2024

Simulation Analysis of Mode Hopping Impacts on OFDR Sensing Performance

This article examines the impacts of mode hopping on the sensing performance of optical frequency domain reflectometry (OFDR) and explores the potential for developing economical OFDR interrogators employing low-cost distributed feedback (DFB) lasers. By conducting numerical simulations, this study reveals that mode hopping has minimal effects on distance sensing measurements in free space due to the limited duration of beat interference signal at the incorrect frequency within the coherence length. Additionally, the simulations indicate that mode hopping only slightly affects the distributed strain sensing of OFDR, resulting in an error range of less than ±1µε when 100µε is applied to the sensing fiber. These findings highlight the potential of using low-cost DFB lasers with a 1-nm wavelength sweep range and a 1-MHz linewidth as tunable laser sources in OFDR while maintaining reliable and accurate sensing performance.

Wang, Qirui (ORCID:0000000336532984)↗
DOE OSTI2021

Reconstruction of the Density Power Spectrum from Quasar Spectra using Machine Learning

We describe a novel end-to-end approach using Machine Learning to reconstruct the power spectrum of cosmological density perturbations at high redshift from observed quasar spectra. State-of-the-art cosmological simulations of structure formation are used to generate a large synthetic dataset of line-of-sight absorption spectra paired with 1-dimensional fluid quantities along the same line-of-sight, such as the total density of matter and the density of neutral atomic hydrogen. With this dataset, we build a series of data-driven models to predict the power spectrum of total matter density. We are able to produce models which yield reconstruction to accuracy of about 1% for wavelengths $k \leq 2 h Mpc^{-1}$, while the error increases at larger $k$. We show the size of data sample required to reach a particular error rate, giving a sense of how much data is necessary to reach a desired accuracy. This work provides a foundation for developing methods to analyse very large upcoming datasets with the next-generation observational facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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 OSTI2013

Influence of sky radiance measurement errors on inversion-retrieved aerosol properties

Remote sensing of the atmospheric aerosol is a well-established technique that is currently used for routine monitoring of this atmospheric component, both from ground-based and satellite. The AERONET program, initiated in the 90's, is the most extended network and the data provided are currently used by a wide community of users for aerosol characterization, satellite and model validation and synergetic use with other instrumentation (lidar, in-situ, etc.). Aerosol properties are derived within the network from measurements made by ground-based Sun-sky scanning radiometers. Sky radiances are acquired in two geometries: almucantar and principal plane. Discrepancies in the products obtained following both geometries have been observed and the main aim of this work is to determine if they could be justified by measurement errors. Three systematic errors have been analyzed in order to quantify the effects on the inversion-derived aerosol properties: calibration, pointing accuracy and finite field of view. Simulations have shown that typical uncertainty in the analyzed quantities (5% in calibration, 0.2 Degree-Sign in pointing and 1.2 Degree-Sign field of view) yields to errors in the retrieved parameters that vary depending on the aerosol type and geometry. While calibration and pointing errors have relevant impact on the products, the finite field of view does not produce notable differences.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Seeing the forest beyond the trees: Correspondence

In a recent report (Mitchard etal. 2014, Global Ecology and Biogeography, 23, 935-946) a new map of forest biomass based on a geostatistical model of field data for the Amazon (and surrounding forests) was presented and contrasted with two earlier maps based on remote-sensing data Saatchi etal. (2011; RS1) and Baccini etal. (2012; RS2). Mitchard etal. concluded that both the earlier remote-sensing based maps were incorrect because they did not conform to Mitchard etal. interpretation of the field-based results. In making their case, yet, they misrepresented the fundamental nature of primary field and remote-sensing data and committed critical errors in their assumptions about the accuracy of research plots, the interpolation methodology and the statistical analysis. By ignoring the large uncertainty associated with ground estimates of biomass and the significant under-sampling and spatial bias of research plots, Mitchard etal. reported erroneous trends and artificial patterns of biomass over Amazonia. Due to these misrepresentations and methodological flaws, we find their critique of the satellite-derived maps to be invalid.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Unveiling a Drift Resistant Cryptotope within Marburgvirus Nucleoprotein Recognized by Llama Single-Domain Antibodies

Marburg virus (MARV) is a highly lethal hemorrhagic fever virus that is increasingly re-emerging in Africa, has been imported to both Europe and the US, and is also a Tier 1 bioterror threat. As a negative sense RNA virus, MARV has error prone replication which can yield progeny capable of evading countermeasures. To evaluate this vulnerability, we sought to determine the epitopes of 4 llama single-domain antibodies (sdAbs or VHH) specific for nucleoprotein (NP), each capable of forming MARV monoclonal affinity reagent sandwich assays. Here, we show that all sdAb bound the C-terminal region of NP, which was produced recombinantly to derive X-ray crystal structures of the three best performing antibody-antigen complexes. The common epitope is a trio of alpha helices that form a novel asymmetric basin-like depression that accommodates each sdAb paratope via substantial complementarity-determining region (CDR) restructuring. Shared core contacts were complemented by unique accessory contacts on the sides and overlooks of the basin yielding very different approach routes for each sdAb to bind the antigen. The C-terminal region of MARV NP was unable to be crystallized alone and required engagement with sdAb to form crystals suggesting the antibodies acted as crystallization chaperones. While gross structural homology is apparent between the two most conserved helices of MARV and Ebolavirus, the positions and morphologies of the resulting basins were markedly different. Naturally occurring amino acid variations occurring in bat and human Marburgvirus strains all mapped to surfaces distant from the predicted sdAb contacts suggesting a vital role for the NP interface in virus replication. As an essential internal structural component potentially interfacing with a partner protein it is likely the C-terminal epitope remains hidden or “cryptic” until virion disruption occurs. Conservation of this epitope over 50 years of Marburgvirus evolution should make these sdAb useful foundations for diagnostics and therapeutics resistant to drift.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

A procedure for the estimation of the numerical uncertainty of CFD calculations based on grid refinement studies

This paper offers a procedure for the estimation of the numerical uncertainty of any integral or local flow quantity as a result of a fluid flow computation; the procedure requires solutions on systematically refined grids. The error is estimated with power series expansions as a function of the typical cell size. These expansions, of which four types are used, are fitted to the data in the least-squares sense. The selection of the best error estimate is based on the standard deviation of the fits. The error estimate is converted into an uncertainty with a safety factor that depends on the observed order of grid convergence and on the standard deviation of the fit. For well-behaved data sets, i.e. monotonic convergence with the expected observed order of grid convergence and no scatter in the data, the method reduces to the well known Grid Convergence Index. Examples of application of the procedure are included. - Highlights: • Estimation of the numerical uncertainty of any integral or local flow quantity. • Least squares fits to power series expansions to handle noisy data. • Excellent results obtained for manufactured solutions. • Consistent results obtained for practical CFD calculations. • Reduces to the well known Grid Convergence Index for well-behaved data sets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Quantum Information Encoding and Decoding for Quantum Sensi

This two-year theory project focused on theoretical investigations of novel paradigms for quantum sensing, building on information encoding and techniques from quantum error correction, quantum computing and other quantum information domains. The outcomes facilitate quantum information technology development, especially at the interface of quantum computing and quantum sensing. The results of the project show new use cases and new paradigms for quantum sensing beyond what has so far been considered. One outcome shows how quantum sensing opens new opportunities for fundamental physics such as the capability of single graviton detection. Another outcome reveals a new application of NISQ quantum computers with error correction for metrology, building on recent advances in practical quantum error correction implementation. The third outcome of the project creates new paradigms of back-action-evading sensing inspired by collective quantum information encoding, which achieves quantum sensing beyond the quantum limit without the use of entanglement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Behavior and mechanisms of Doppler wind lidar error in varying stability regimes

Abstract. Wind lidars are widespread and important tools in atmospheric observations. An intrinsic part of lidar measurement error is due to atmospheric variability in the remote-sensing scan volume. This study describes and quantifies the distribution of measurement error due to turbulence in varying atmospheric stability. While the lidar error model is general, we demonstrate the approach using large ensembles of virtual WindCube V2 lidar performing a profiling Doppler-beam-swinging scan in quasi-stationary large-eddy simulations (LESs) of convective and stable boundary layers. Error trends vary with the stability regime, time averaging of results, and observation height. A systematic analysis of the observation error explains dominant mechanisms and supports the findings of the empirical results. Treating the error under a random variable framework allows for informed predictions about the effect of different configurations or conditions on lidar performance. Convective conditions are most prone to large errors (up to 1.5 m s−1 in 1 Hz wind speed in strong convection), driven by the large vertical velocity variances in convective conditions and the high elevation angle of the scanning beams (62∘). Range-gate weighting induces a negative bias into the horizontal wind speeds near the surface shear layer (−0.2 m s−1 in the stable test case). Errors in the horizontal wind speed and direction computed from the wind components are sensitive to the background wind speed but have negligible dependence on the relative orientation of the instrument. Especially during low winds and in the presence of large errors in the horizontal velocity estimates, the reported wind speed is subject to a systematic positive bias (up to 0.4 m s−1 in 1 Hz measurements in strong convection). Vector time-averaged measurements can improve the behavior of the error distributions (reducing the 10 min wind speed error standard deviation to <0.3 m s−1 and the bias to <0.1 m s−1 in strong convection) with a predictable effectiveness related to the number of decorrelated samples in the time window. Hybrid schemes weighting the 10 min scalar- and vector-averaged lidar measurements are shown to be effective at reducing the wind speed biases compared to cup measurements in most of the simulated conditions, with time averages longer than 10 min recommended for best use in some unstable conditions. The approach in decomposing the error mechanisms with the help of the LES flow field could be extended to more complex measurement scenarios and scans.

17 WIND ENERGY↗
DOE OSTI2015

Calculating tumor trajectory and dose-of-the-day using cone-beam CT projections

Purpose: Cone-beam CT (CBCT) projection images provide anatomical data in real-time over several respiratory cycles, forming a comprehensive picture of tumor movement. The authors developed and validated a method which uses these projections to determine the trajectory of and dose to highly mobile tumors during each fraction of treatment. Methods: CBCT images of a respiration phantom were acquired, the trajectory of which mimicked a lung tumor with high amplitude (up to 2.5 cm) and hysteresis. A template-matching algorithm was used to identify the location of a steel BB in each CBCT projection, and a Gaussian probability density function for the absolute BB position was calculated which best fit the observed trajectory of the BB in the imager geometry. Two modifications of the trajectory reconstruction were investigated: first, using respiratory phase information to refine the trajectory estimation (Phase), and second, using the Monte Carlo (MC) method to sample the estimated Gaussian tumor position distribution. The accuracies of the proposed methods were evaluated by comparing the known and calculated BB trajectories in phantom-simulated clinical scenarios using abdominal tumor volumes. Results: With all methods, the mean position of the BB was determined with accuracy better than 0.1 mm, and root-mean-square trajectory errors averaged 3.8% ± 1.1% of the marker amplitude. Dosimetric calculations using Phase methods were more accurate, with mean absolute error less than 0.5%, and with error less than 1% in the highest-noise trajectory. MC-based trajectories prevent the overestimation of dose, but when viewed in an absolute sense, add a small amount of dosimetric error (<0.1%). Conclusions: Marker trajectory and target dose-of-the-day were accurately calculated using CBCT projections. This technique provides a method to evaluate highly mobile tumors using ordinary CBCT data, and could facilitate better strategies to mitigate or compensate for motion during stereotactic body radiotherapy.

60 APPLIED LIFE SCIENCES↗