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DOE OSTI2023

Data-driven acoustic measurement of moisture content in flowing biomass

Measuring the moisture content in flowing biomass is critical to processes such as liquid biofuel conversion, such as biogasoline, biodiesel, bio jet kerosene, etc. However, biomass tends to flow in aggregates, which results in significant inhomogeneities in the amount of biomass flowing in front of a sensor at a given time, and there can be significant overlap in the material properties of dry vs wet biomass, leading to poor signal-to-noise ratio. We present a technique for identifying biomass moisture content using a series of acoustic pitch-catch measurements to quantify the sound speed and acoustic amplitude through the biomass, in conjunction with classical machine learning techniques, including Naive Bayes, Random Forest, and K-Nearest Neighbors classification. We amplify the differences between the acoustic measurements in different moisture levels by collecting a series of pulse-echo measurements, which we sort in order of ascending sound speed. We test the accuracy of the technique on experimentally-prepared batches of corn stover biomass with specified moisture levels and measure the average error in the estimated moisture level as a function of the number of pitch-catch measurements used. We observe average estimation errors as low as 6.7% by increasing the number of measurements and optimizing the hyperparameters. This work presents a novel method determining moisture content in flowing biomass with inhomogeneous flow. Additionally, this technique has application in optimizing biomass conversion processes, as well as other fields including, paper production, natural fiber processing, and mineral extraction.

09 BIOMASS FUELS↗

DOE OSTI2023

Coregistered positron emission particle tracking (PEPT) and X-ray computed tomography (CT) for engineering flow measurements

Increasingly, fully 3D experimental measurements of flow in complex engineering geometries are required to validate computational fluid dynamics models that support and inform reactor design and licensing. One barrier to such measurements is the complexity of typical reactor components and subsequent lack of optical access in these systems. To overcome this, the deployment of coregistered positron emission particle tracking (PEPT) and X-ray computed tomography (CT) is explored for flow measurement in reactor thermal hydraulic components and model (scaled) systems. Through this methodology, fully 3D flow information (via PEPT) and detailed internal geometry (via CT) are captured in opaque systems such as pipes, rod bundles, packed beds, etc. The reconstructed flow field and geometry can then be overlain to reveal detailed flow features around internal structures within a given test section. This is enabled through the use of a combined preclinical PET/CT scanner with overlapping PET and CT fields of view. Such measurements are useful for characterizing flow inside such intricate nuclear thermal hydraulic components as core geometries and heat exchangers, among others, and providing valuable 3D validation data for CFD models. In this work, basic tests of this 3D flow/geometry mapping are presented, and the implications of such measurements are discussed. Further, preliminary measurements are made with both point sources and flow in a simple pipe flow geometry to evaluate the capabilities of this technique. PEPT and CT features are coregistered with up to 0.1 mm precision, and pipe flow mean velocity and Reynolds stresses are reconstructed with similar accuracy to previous PEPT demonstrations. The utility of PEPT/CT is shown herein, and suggestions for future measurements are made.

3D flow measurement↗

DOE OSTI2022

Surrogate modeling for efficiently, accurately and conservatively estimating measures of risk

We present a surrogate modeling framework for conservatively estimating measures of risk from limited realizations of an expensive physical experiment or computational simulation. Risk measures combine objective probabilities with the subjective values of a decision maker to quantify anticipated outcomes. Given a set of samples, we construct a surrogate model that produces estimates of risk measures that are always greater than their empirical approximations obtained from the training data. These surrogate models limit over-confidence in reliability and safety assessments and produce estimates of risk measures that converge much faster to the true value than purely sample-based estimates. We first detail the construction of conservative surrogate models that can be tailored to a stakeholder’s risk preferences and then present an approach, based on stochastic orders, for constructing surrogate models that are conservative with respect to families of risk measures. Our surrogate models include biases that permit them to conservatively estimate the target risk measures. We provide theoretical results that show that these biases decay at the same rate as the L 2 error in the surrogate model. Numerical demonstrations confirm that risk-adapted surrogate models do indeed overestimate the target risk measures while converging at the expected rate.

42 ENGINEERING↗

DOE OSTI2026

Advancements in reflected target nonintrusive assessment (ReTNA) for large optical surface measurement

Reflected computer vision targets are a powerful tool for measurement of mirror surface shape, with several important advantages over traditional fringe deflectometry methods. This method was first presented in 2021 and has undergone significant improvement and demonstration since. We describe a new baseline system using reflected computer vision targets, and present results from a large-scale measurement campaign conducted on both commercial heliostats and test mirrors in the laboratory. Calibration of the measurement system with photogrammetry allows for accurate measurement without careful control of target shape or camera position. Overall, the results show that a baseline setup using this method achieves measurement uncertainties in the slope error root-mean-square less than ±0.11 milliradian due to a series of repeatability conditions, varying sample position, rotation, lighting, camera settings, and system rebuild and recalibration. We present a detailed description of the setup, the results generated by this measurement tool, repeated measurement results, and the strengths and limitations of this metrology system.

14 SOLAR ENERGY↗

DOE OSTI2022

Femtosecond ultraviolet laser absorption spectroscopy for simultaneous measurements of temperature and OH concentration

This Letter reports a femtosecond ultraviolet laser absorption spectroscopy (fs-UV-LAS) for simultaneous in situ measurements of temperature and species. Here, this fs-UV-LAS technique was demonstrated based on X 2 Π-A 2 Σ + transitions of OH radicals near 308 nm generated in low temperature plasmas and flames. The fs-UV-LAS technique has revealed three major diagnostic benefits. First, a series of absorption features within a spectral bandwidth of ~3.2 nm near 308 nm were simultaneously measured and then enabled simultaneous multi-parameter measurements with enhanced accuracy. The results show that the temperature and OH concentration could be measured with accuracy enhanced by 29–88% and 58–91%, respectively, compared to those obtained with past two-narrow-line absorption methods. Second, an ultrafast time resolution of ~120 picoseconds was accomplished for the measurements. Third, due to the large OH X 2 Π-A 2 Σ + transitions in the UV range, a simple single-pass absorption with a 3-cm path length was allowed for measurements in plasmas with low OH number density down to ~2 × 10 13 cm –3 . Also due to the large OH UV transitions, single-shot fs absorption measurements were accomplished in flames, which was expected to offer more insights into chemically reactive flow dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Quantification of air leakage paths: a comparison of airflow and acoustic measurements

Today, the fan pressurization method is the most frequently used method to evaluate a building's airtightness. However, the localization and quantification of leaks remain difficult. In this paper, an acoustic method is introduced to estimate the leakage size of single leaks. Acoustic and airflow measurements were conducted and compared in laboratory tests within the same boundary conditions. This work aims to investigate if various leak sizes can be predicted using acoustic measurement methods. The test apparatus consists of two chambers, separated by a test wall. This wall represents a single characteristic air leakage path. Various types of wall structures with different slit geometries, wall thicknesses, and insulation materials were investigated. The acoustic measurements were performed with a sound source placed in one chamber and ultrasonic microphones located in both chambers. These results were compared to measured airflows through the test wall to provide estimates of uncertainty in the acoustic approach, which indicate a linear trend. Finally, these laboratory measurements were compared to the same measurements at a real office building. Finally, although the acoustic measurement uncertainty is still significant (greater than +/- 50%), the acoustic method has the potential to give an order of magnitude of single leak sizes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Towards Integrating Data Quality Assessments and Radiometer Uncertainty for Determining the Expanded Uncertainty of Three-Component Solar Radiation Measurements

Accurate solar irradiance data are fundamental for determining the design and performance characteristics of photovoltaic systems. The uncertainty of solar irradiance measurements depends on many factors including radiometer design, calibration, installation, maintenance, and operational environment. The key contributors to this uncertainty can be classified as the measurement uncertainty of a particular radiometer and the operational uncertainty determined for the time of measurement. Radiometer measurement uncertainty estimates (U R ) can be based on well-established methods used as part of the radiometer calibration process. Estimates of operational uncertainties (U o ) require consideration of additional site-specific factors that affect data quality. A method is needed for establishing the accuracy of solar irradiance data by integrating an existing data quality process and measurement uncertainty estimates for specific radiometers. An algorithm has been developed to integrate data quality analyses and measurement uncertainty estimates for three-component solar irradiance data: global horizontal (total hemispheric) irradiance, direct normal (beam) irradiance, and diffuse horizontal (sky) irradiance collected at one- to 60-minute intervals. The algorithm has been tested using one-minute irradiance measurements. The goal of the project is to distribute a user-friendly software package based on the new algorithm.

data integrity↗

DOE OSTI2022

Recursive Gaussian Process over graphs for Integrating Multi-timescale Measurements in Low-Observable Distribution Systems

The transition to a smarter grid is empowered by enhanced sensor deployments and smart metering infrastructure in the distribution system. Measurements from these sensors and meters can be used for many applications, including distribution system state estimation (DSSE). However, these measurements are typically sampled at different rates and could be intermittent due to losses during the aggregation process. These multi timescale measurements should be reconciled in real-time to perform accurate grid monitoring. This paper tackles this problem by formulating a recursive multi-task Gaussian process (RGP-G) approach that sequentially aggregates sensor measurements. Specifically, we formulate a recursive multi-task GP with and without network connectivity information to reconcile the multi time-scale measurements in distribution systems. Here, the proposed framework is capable of aggregating the multi-time scale measurements batch-wise or in real-time. Following the aggregation of the multi time-scale measurements, the spatial states of the consistent time-series are estimated using matrix completion based DSSE approach. Simulation results on IEEE 37 and IEEE 123 bus test systems illustrate the efficiency of the proposed methods from the standpoint of both multi time-scale data aggregation and DSSE.

42 ENGINEERING↗

DOE OSTI2023

Bounding the Minimum Time of a Quantum Measurement

Measurements take a singular role in quantum theory. While they are often idealized as an instantaneous process, this is in conflict with all other physical processes in nature. In this Letter, we adopt a standpoint where the interaction with an environment is a crucial ingredient for the occurrence of a measurement. Within this framework, we derive lower bounds on the time needed for a measurement to occur. Our bound scales proportionally to the change in entropy of the measured system, and decreases as the number of of possible measurement outcomes or the interaction strength driving the measurement increases. We evaluate our bound in two examples where the environment is modelled by bosonic modes and the measurement apparatus is modelled by spins or bosons.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Deep Learning and Photogrammetric Reconstruction for Automated Crack Detection and Dimensional Measurement in Mining Operations

Surface crack detection and dimensional measurement at active mining sites present significant safety and operational challenges. Manual inspection methods are labor-intensive, spatially incomplete, and expose personnel to hazardous environments, while existing automated approaches have been developed primarily for concrete civil infrastructure and have not been validated on the complex, variable surfaces characteristic of mining environments. This dissertation presents an automated pipeline that integrates deep learning semantic segmentation with Structure-from-Motion photogrammetry to detect surface cracks and measure their aperture, length, and vertical displacement from standard RGB imagery acquired during routine Uncrewed Aerial Vehicle (UAV) survey operations, without requiring additional sensor hardware or manual measurement. The pipeline combines a U-Net architecture with an EfficientNet-B0 encoder, pretrained on the SDNET2018 concrete crack dataset and fine-tuned on a mining-specific dataset spanning laboratory concrete specimens, coal refuse impoundment embankments, and post-blast limestone quarry benches. Photogrammetric reconstruction is performed using COLMAP Structure-from-Motion and Multi-View Stereo, with crack segmentation masks projected into the reconstructed point cloud to enable three-dimensional vertical displacement measurement through local plane fitting and bimodal surface detection. The pipeline was validated across 36 controlled laboratory specimens at three imaging distances and four vertical displacement levels, achieving aperture measurement RMSE of 0.047 cm and R² of 0.954, and vertical displacement RMSE of 0.140 cm and R² of 0.966, against independent caliper measurements. Field application at a coal refuse impoundment in southwestern Pennsylvania detected 71 crack components across the embankment crest, with a dominant longitudinal crack exhibiting aperture values reaching 28 cm and a 95th percentile vertical displacement of 35.53 cm, consistent in magnitude and spatial distribution with simultaneously acquired LiDAR-derived estimates. Application across four post-blast limestone quarry bench datasets in California successfully characterized blast-induced fracture networks at ground sampling distances ranging from 0.59 to 1.23 cm/pixel, with detected crack geometries physically consistent with observable surface conditions at each site. The results demonstrate that deep learning-based crack detection and photogrammetric measurement can be integrated into routine UAV inspection workflows at mining sites, providing repeatable, scalable, and quantitative crack characterization across surface types, crack scales, and displacement magnitudes not previously addressed in the literature. The pipeline requires no dedicated surveying equipment beyond the UAV platforms already deployed at mine sites for survey and monitoring purposes, supporting practical adoption within existing operational workflows.

Crack detection, Dimensional Measurement↗

NASA NTRS2016

Accurate Measurements of the Dielectric Constant of Seawater at L Band

This paper describes measurements of the dielectric constant of seawater at a frequency of 1.413 GHz, the center of the protected band (i.e., passive use only) used in the measurement of sea surface salinity from space. The objective of the measurements is to accurately determine the complex dielectric constant of seawater as a function of salinity and temperature. A resonant cylindrical microwave cavity in transmission mode has been employed to make the measurements. The measurements are made using standard seawater at salinities of 30, 33, 35, and 38 practical salinity units over a range of temperatures from 0 degree C to 35 degree C in 5 degree C intervals. Repeated measurements have been made at each temperature and salinity. Mean values and standard deviations are then computed. The total error budget indicates that the real and imaginary parts of the dielectric constant have a combined standard uncertainty of about 0.3 over the range of salinities and temperatures considered. The measurements are compared with the dielectric constants obtained from the model functions of Klein and Swift and those of Meissner and Wentz. The biggest differences occur at low and high temperatures.

Measurements↗

NASA NTRS2018

Measurement of Atmospheric CO2 Column Concentrations to Cloud Tops With a Pulsed Multi-Wavelength Airborne Lidar

We have measured the column-averaged atmospheric CO2 mixing ratio to a variety of cloud tops by using an airborne pulsed multi-wavelength integrated-path differential absorption (IPDA) lidar. Airborne measurements were made at altitudes up to 13 km during the 2011, 2013 and 2014 NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) science campaigns flown in the United States West and Midwest and were compared to those from an in situ sensor. Analysis of the lidar backscatter profiles shows the average cloud top reflectance was approx. 5% for the CO2 measurement at 1572.335 nm except to cirrus clouds, which had lower reflectance. The energies for 1 micro-s wide laser pulses reflected from cloud tops were sufficient to allow clear identification of CO2 absorption line shape and then to allow retrievals of atmospheric column CO2 from the aircraft to cloud tops more than 90% of the time. Retrievals from the CO2 measurements to cloud tops had minimal bias but larger standard deviations when compared to those made to the ground, depending on cloud top roughness and reflectance. The measurements show this new capability helps resolve CO2 horizontal and vertical gradients in the atmosphere. When used with nearby full-column measurements to ground, the CO2 measurements to cloud tops can be used to estimate the partial-column CO2 concentration below clouds, which should lead to better estimates of surface carbon sources and sinks. This additional capability of the range-resolved CO2 IPDA lidar technique provides a new benefit for studying the carbon cycle in future airborne and space-based CO2 missions.

atmospheric↗

NASA NTRSDate not supplied

Modeling Measurement Error in Dose-Response Models of Community Annoyance to Low-Noise Supersonic Flight

The primary research goal of the forthcoming NASA Quesst mission community test campaign is to collect representative community response data in support of the development of supersonic overflight noise certification standards. Beginning in 2026, NASA will fly the novel X-59 demonstrator aircraft over select communities in United States in order to demonstrate the possibility of low-noise supersonic flight over land and to collect objective measurements and subjective data on the perceptual experience of this new noise source. It is believed that a regression of a binary perceptual response (‘highly annoyed’ or ‘not’) on estimated noise levels (doses, measured in decibels) will provide a useful dose-response relationship for regulators. However, as these estimated doses will be subject to measurement error, naïve estimators of regression coefficients are inconsistent and slopes may be subject to attenuation bias. In this presentation, I contrast functional modeling of measurement error via simulation extrapolation (SIMEX) with structural Bayesian measurement error models. These methods are applied to available data collected during two NASA risk reduction studies in California in 2011 and Texas in 2018. I’ll conclude noting that in the presence of nonnegligible measurement errors, probabilities of annoyance may be overpredicted for low noise levels and underpredicted for high noise levels, therefore, methods of correcting for measurement error will be necessary to improve the utility of the dose-response relationship for policy-making purposes.

simulation↗

NASA NTRS2024

Summary and Annotated Bibliography of Measurement Error Corrections with Potential Application in Future Quesst Mission Community Noise Studies

This document is motivated by likely needs of the Quesst mission community response tests, which will culminate in data collection and estimation of dose-response regression relationships for consideration by domestic and international aviation regulators. Furthermore, basic research questions evaluating interactions between rates of community annoyance, dose levels, and indicators of the presence of rattle, vibration, and startle hinge on hypothesis testing in the context of regression models. For a variety of reasons, noise doses may be known only imprecisely and may not reflect the actual level experienced by responding subjects. These differences between true dose and estimated dose, be they systematic or random, constitute covariate measurement error. Available statistics literature speaks to the impacts of measurement error on regression models, both in terms of bias in estimated coefficients and predicted values, and in terms of the loss of statistical power for hypothesis testing. Given the particulars of a categorical annoyance response variable and a continuous noise dose predictor variable subject to measurement error during testing, the emphasis of this report is on findings and methods pertinent to generalized linear (and mixed) models likely to be employed during the Quesst mission community tests. We reach the following conclusions: 1. Of four reviewed methods, structural Bayesian measurement error models and simulation extrapolation (SIMEX) may be the most readily applicable to Quesst mission community noise study objectives. 2. If warranted, a linear measurement model can help model systematic sources of measurement error that the classical measurement error does not. 3. For its ready implementation and small additional input requirements, simulation extrapolation may be ideally suited for addressing secondary research questions involving interactions between annoyance, noise dose, and other factors through hypothesis testing. 4. For their flexibility and ability to propagate uncertainty, structural Bayesian hierarchical models have great appeal for mission purposes; some care may be needed in developing appropriate probability models describing actual noise exposure during testing. An annotated bibliography logs additional papers and resources that may be of value to analysts in other projects and disciplines.

Dose-Response Model↗

DOE OSTI2023

In Situ Wind and Turbulence Measurements in a Field of Full-Size Parabolic Trough Solar Collectors

Concentrated Solar Power (CSP) is a promising method for using Solar power for electricity generation with thermal energy storage. One of the primary drivers of structural design costs of CSP collector structures is wind loading. To date, the design of these structures has relied on data from wind tunnels that do not adequately capture the dynamic effects observed at scale. NREL initiated a field measurement campaign at the operational Nevada Solar One (NSO) powerplant that uses parabolic troughs as solar collectors. The aim of the project is a detailed characterization of prevailing wind and turbulence conditions and resulting operational loads on parabolic troughs, providing insights on structural dynamic response, and generating a first-of-a-kind, comprehensive, high-resolution wind-loading dataset available for validating simulations of wind loading on collector structures. The measurements at NSO consist of Sonic anemometers on masts at different heights to characterize the incoming flow and conditions within and above the trough field, in combination with a Doppler Lidar scanning the horizontal plane above the troughs. The wind measurements at NSO have been continuously operating since October 2021 and provide a year-long dataset characterizing wind and turbulence conditions. The structural load measurements start in November 2022 and will complement the wind measurements. In this poster, we present first results of the wind measurement campaign by highlighting days with different atmospheric flow conditions. We identified three main factors altering the flow over the parabolic troughs: Wind speed, wind direction, and the angle of the parabolic troughs. The highest loads are expected when the wind blows perpendicular to the trough rows. In this case, the first rows experience the highest loads and block the subsequent rows, creating conditions with decreased wind speed and enhanced turbulence within the trough field. Also, turbulent length scales change. These affected conditions produce unique load cases on the structures that will be captured by the load measurements. If the wind blows along the trough rows, wind and turbulence conditions are less influenced by the troughs.

atmospheric turbulence↗

DOE OSTI2023

In Situ Wind and Turbulence Measurements in a Field of Full-Size Parabolic Trough Collectors

concentrated solar power↗

DOE OSTI2022

Itinerant G-type antiferromagnet SrCr 2 As 2 studied by magnetization, heat capacity, electrical resistivity, and NMR measurements

Here, the physical properties of itinerant antiferromagnetic (AFM) SrCr 2 As 2 with body-centered tetragonal ThCr 2 Si 2 structure were investigated in single crystalline and polycrystalline forms by electrical resistivity ρ, heat capacity C p , magnetic susceptibility χ versus temperature T, and magnetization M versus applied magnetic field H isotherm measurements as well as 75 As and 53 Cr nuclear magnetic resonance (NMR) measurements in the wide temperature range T = 1.6–900 K. From the χ(T) and 75 As NMR measurements, the G-type AFM state below T N = 615(15) K has been determined, consistent with the previous neutron-diffraction measurements. Direct evidence of magnetic ordering of the Cr spins was shown by the observation of the 53 Cr NMR spectrum under H = 0. From the χ( T) measurements on single-crystal SrCr 2 As 2 under the two different magnetic field directions H|| ab and H || c in the AFM state, the Cr ordered moments are shown to align along the c axis in the G-type AFM state. The metallic state is directly evidenced by the ρ, C p , and NMR measurements, and the density of states at the Fermi energy $\mathscr{D}$(E F ) in the AFM state is estimated to be 7.53 states/eV f.u. for both spin directions which is almost twice the bare $\mathscr{D}$(E F ) estimated from first-principles calculations, suggesting an enhancement of the conduction-carrier mass by a factor of two in the AFM state. The $\mathscr{D}$(E F ) is found to be nearly constant below at least 100 K and is independent of H. The ρ(T) is found to show T-linear behavior above T N and exhibits positive curvature below T N where significant loss of spin-disorder scattering upon magnetic ordering is observed. The resistivity anisotropy of the compound remains moderate ρ c /ρ a ~ 9 through most of the magnetically ordered phase but shows a rapid increase below 50 K.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Inclusive and differential measurements of the $\textrm{t}\overline{\textrm{t}}\mathcal{γ}$ cross section and the $\textrm{t}\overline{\textrm{t}}\mathcal{γ}/\textrm{t}\overline{\textrm{t}}$ cross section ratio in proton-proton collisions at $\sqrt{s}=13$ TeV

Inclusive and differential cross section measurements of top quark pair $(\textrm{t}\overline{\textrm{t}})$ production in association with a photon (γ) are performed as a function of lepton, photon, top quark, and $\textrm{t}\overline{\textrm{t}}$ kinematic observables, using data from proton-proton collisions at $\sqrt{s}=13$ TeV, corresponding to an integrated luminosity of 138 fb −1 , collected at the CERN LHC with the CMS detector. Events containing two leptons (electrons or muons) and a photon in the final state are considered. The fiducial cross section of $\textrm{t}\overline{\textrm{t}}$γ is measured to be 137 ± 8 fb, in a phase space including events with a high momentum, isolated photon. The fiducial cross section of $\textrm{t}\overline{\textrm{t}}$γ is also measured to be 56 ± 5 fb when considering only events where the photon is emitted in the production part of the process. Both measurements are in agreement with the theoretical predictions, of 126 ± 19 fb and 57 ± 5 fb, respectively. Differential measurements are performed at the particle and parton levels. Additionally, inclusive and differential ratios between the cross sections of $\textrm{t}\overline{\textrm{t}}$γ and $\textrm{t}\overline{\textrm{t}}$ production are measured. The inclusive ratio is found to be 0.0133 ± 0.0005, in agreement with the standard model prediction of 0.0127 ± 0.0008. The top quark charge asymmetry in $\textrm{t}\overline{\textrm{t}}$γ production is also measured to be −0.012 ± 0.042, compatible with both the standard model prediction and with no asymmetry.

Hadron-Hadron Scattering↗