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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Flux Sensor Measurement and Calibration Requirements for High-Intensity Heat Flux Applications: A Trade Study

Stakeholders of CSP and non-CSP high-intensity broadband flux measurements were surveyed and interviewed to obtain flux sensor design and calibration requirements. Existing sensor technologies and existing calibration facilities were then compared against this standard. Stakeholders require a flux sensor designed for >5,000 kW/m2 flux measurements, >1,000 life cycles, <500 ms response time, >60-minute exposure at maximum flux, and <5% measurement uncertainty. Stakeholders also require a sensor with minimal cost, short procurement lead time, and a high-intensity broadband flux calibration. Commercial CSP stakeholders primarily rely on infrared (IR) temperature measurements of receiver equipment to control CSP plant process operation, whereas CSP research and development (R&D) and non-CSP stakeholders rely on accurate flux gauge measurements for a variety of applications. It was determined that existing flux sensor technologies and calibration facilities do not comprehensively meet stakeholder needs. This study suggests a more robust circular foil gauge with a high-intensity solar flux calibration comprehensively meets stakeholder flux measurement needs. Improved circular foil gauge designs and an improved flux sensor calibration facility are discussed.

McLaughlin, Luke (ORCID:0000000303711310)↗
DOE OSTI2023

Calibrated Radar Wind Profiler (RWP) Moments

The SGP Central Facility (C1) radar wind profiler (RWP) was calibrated using nearby surface disdrometer observations. Between 2011 and 2019, the SGP C1 RWP operated in two modes. The vertically pointing mode (named the precipitation mode) transmitted a short and long pulse length to have two different range resolutions and the beam-swinging mode (named the wind mode) transmitted one pulse length into three different beam directions. The precipitation-mode observations were available and calibrated from April 2011 through mid-August 2019. The wind-mode observations were available and calibrated between April 2014 and March 2019. The RWP spectra were processed to account for Nyquist velocity aliasing and coherent integration filtering effects before calculating the spectrum moments. During intense precipitation events, the calculated signal-to-noise ratio (SNR) is biased low due to signal power being distributed across the velocity spectrum such that some signal power is erroneously included in the noise level estimate, causing the noise level to be biased high. To correct for the low SNR bias, a new noise level is estimated using observations without precipitation and the SNR is increased accordingly. The adjusted SNR was converted to radar reflectivity factor and then calibrated against a nearby surface disdrometer. The calibration methodology is fully described in: Williams, CR, J Barrio, PE Johnston, P Muradyan, and S Giangrande. 2023. “Calibrating radar wind profiler reflectivity factor using surface disdrometer observations.” Atmospheric Measurement Techniques, https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1405/

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Advancing earth system model calibration: a diffusion-based method

Understanding of climate impact on ecosystems globally requires site-specific model calibration. Here we introduce a novel diffusion-based uncertainty quantification (DBUQ) method for efficient model calibration. DBUQ is a score-based diffusion model that leverages Monte Carlo simulation to estimate the score function and evaluates a simple neural network to quickly generate samples for approximating parameter posterior distributions. DBUQ is stable, efficient, and can effectively calibrate the model given diverse observations, thereby enabling rapid and site-specific model calibration on a global scale. This capability significantly advances Earth system modeling and our understanding of climate impacts on Earth systems. We demonstrate DBUQ's capability in E3SM land model calibration at the Missouri Ozark AmeriFlux forest site. Both synthetic and real-data applications indicate that DBUQ produces accurate parameter posterior distributions similar to those generated by Markov Chain Monte Carlo sampling but with 30X less computing time. This efficiency marks a significant stride in model calibration, paving the way for more effective and timely climate impact analyses.

Liu, Yanfang↗
DOE OSTI2021

Stepwise Dynamic Calibration of a Hydromechanical Simulation Using Time-Lapse Vertical Seismic Profile

This study aims to develop a methodology for calibrating subsurface stress changes through time-lapse Vertical Seismic Profiling (VSP) integration. The selected study site is the 13-10A injector well within the ongoing CO2-EOR operation of the Farnsworth Field Unit. The Time-lapse VSP dataset carries the combined effects of fluid substitution and mean effective stress changes, thereby providing a dataset amenable for the calibration of production and injection-induced stress changes. The concept is similar to calibrating a reservoir simulation model in that the process honor real field data to set up an inverse problem. The solution optimizes the independent and impactful geomechanical parameters that replicate the observed time-lapse seismic velocity changes. This stress calibration is enabled by 4D geomechanical modeling and the VSP Integration workflow. This calibration benefits from extensive geological, geophysical and geomechanical characterization through 3D seismic data, geophysical well logs, and core assessed as part of the 1D MEM conducted on the 13-10A subject well. These data are used to develop a site-specific rock physics model. The Biot Gassmann workflow combines rock physics and reservoir simulation outputs to determine the fluid substitution contribution to seismic velocity change. Additionally, modeled seismic velocity attributed to mean effective stress are determined from the geomechanical simulation outputs, and the stress-velocity relationship developed from the ultrasonic seismic velocity measurements on the extracted Morrow B core. A penalty function is then formed between the modeled seismic velocities and the observed time-lapse VSP dataset. Four independent and impactful geomechanical parameters have been determined. These are the bulk modulus and shear modulus for zero porosity and the shear and compressional seismic velocity to mean effective stress derivatives. The dataset of numerous coupled hydromechanical- geomechanical simulation realizations is built by combining variations of the four stated geomechanical parameters. A machine learning-assisted workflow comprised of an artificial neural network and a particle swarm optimizer are used to converge on the optimal geomechanical parameters. The successful execution of this workflow has affirmed the suitability of acoustic time-lapse measurements for 4D-VSP geomechanical stress calibration pending measurable stress sensitivities within the anticipated effective stress changes and the availability of suitable and reliable datasets for petroelastic modeling.

02 PETROLEUM↗
DOE OSTI2024

Data Acquisition System Selection and Calibration of Resistive Moisture Content Measurements for Large-Scale Field Studies in Cold Climate Residential Building Envelope Performance

The residential building stock built before the energy codes were enforced has several significant inefficiency problems in terms of insulation and air leakage. To decrease these inefficiencies, building retrofits are necessary. However, if the envelope is not appropriately designed, excessive accumulation of moisture content and thus mold formation and decay inside the envelope layers can be a vital problem. This risk becomes higher, especially in extreme climate conditions such as cold winters and hot and humid summers as in some northern regions of the U.S. Field studies are essential to test the long-term hygrothermal performance of building envelopes. Although in-situ temperature, RH, and heat flux measurements are straightforward, moisture content measurements are cumbersome. Mainly, because of the heterogeneous nature of the wood materials, deviations and nonuniformities within the materials are unavoidable. Resistance measurements are one of the oldest methods used to measure the moisture content of wood and other building materials. In large-scale studies, it is commonly preferred to use multi-purpose data acquisition systems (DAQ) and custom-made or prefabricated moisture pins to measure the electrical resistance (and thus moisture content) of critical building materials. These multi-purpose DAQ systems generally provide lower costs and offer more flexibility. However, these systems require calibration and fine-tuning to achieve accurate moisture content measurements. A large-scale, two-year-long field study was conducted in northern Minnesota to monitor the hygrothermal performance of residential retrofit wall systems in cold climates. Two base case walls and sixteen different wall treatments were tested. Moisture contents were measured at various layers in each wall treatment using 85 sets of moisture pins. This paper focuses on the overall approach, fabrication, and calibration methodology for the combination of custom-made moisture pins and a multi-purpose DAQ. The aim is to directly use the low-excitation multi-purpose DAQ without any extra voltage regulator. A half-bridge circuit is used to measure wood resistance with 4V excitation voltage and 100 kΩ and 500 kΩ reference resistors. The system is calibrated for four different materials: Douglas fir, lodgepole pine, western red cedar, and oriented strand board (OSB). Calibration experiments were done under controlled conditions in 50% and 65% RH test chambers. Resistance-based moisture content calibration curves are obtained for each species. Results show that higher reference resistors provided better calibration curves for lower excitation voltages.

Desjarlais, Andre Omer↗
DOE OSTI2026

An upgraded frequency-selectable laser source (FLS) calibrator for CMB bandpass characterization

One of the biggest challenges for Cosmic Microwave Background (CMB) experiments comes from the uncertainty in instrument bandpass calibration. Uncertainties in bandpass can limit foreground removal and spectral fitting, which are critical for inflationary and galaxy cluster measurements. CMB experiments currently use Fourier Transform Spectrometers (FTSes) to measure instrument bandpasses. However, FTS systems are currently systematics-limited, so significant improvements in bandpass measurements require novel calibrators. To this end, we developed a Frequency-selectable Laser Source (FLS) calibrator, which uses a laser with adjustable frequency coupled to a system that allows for laser power attenuation. Following initial testing with the first FLS prototype, we developed an upgraded version of the calibrator with improved performance. We present the upgrades to the FLS calibrator, the characterization of the upgraded calibrator and new laser source, and plans for testing with microwave instruments in the field.

Saunders, Lauren J. [Fermilab] (ORCID:000000016367↗
DOE OSTI2021

PV Reference Cells for Outdoor Use: An Investigation of Calibration Factors

Reference cells are widely used in the photovoltaic (PV) industry to measure irradiance. For field applications and outdoor use, a variety of products are on the market, and they are often perceived as a low-cost alternative to thermopile radiometers. But reference cell characteristics differ substantially from the latter, therefore measurements made by one category of instrument cannot be substituted for or directly compared with the other. The National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory is currently in a multiyear effort to develop guidance and recommendations for the design and use of outdoor reference cells, with a view to reducing inconsistencies and measurement uncertainty. The core of this effort is the long-term deployment of 39 units of 10 distinct types made by 6 manufacturers. This report compares the calibration factors provided by manufacturers - which most users rely upon - to those measured at a high level of accuracy by NREL's Cell Lab. It also reports on the application of the Broadband Outdoor Radiometer Calibration (BORCAL) method to reference cells. As a group, the factory calibrations for the crystalline silicon cells showed a small positive bias of +0.7%, with a tight distribution around this value. This is a very good result for the manufacturers. The two World Photovoltaic Scale cells constituted outliers, with a mean deviation of -0.8%, which is still within the reported uncertainty ranges. The data collected during the BORCAL procedures show a strong and systematic fluctuation of the apparent responsivity of the reference cells over the course of a day, which was anticipated. Consequently, the standard BORCAL R@45 calibration factors underestimated the reference cell responsivities by 1%-4%. An alternate responsivity indicator was developed, R'@30, incorporating adjustments for temperature response, spectral response, and directional response. This reduced the mean deviation to -0.4% compared to the Cell Lab. Further, two independent BORCAL sessions were able to produce the same values to within ±0.2%. This could be a viable approach for verifying reference cells using existing BORCAL infrastructure, for example, to evaluate their long-term stability. The daily profiles of responsivity obtained during the BORCAL sessions (provided in Appendix A) show clear patterns of differences between models, which provides evidence that their directional responses differ from each other; thus, two sensors that are calibrated correctly might give the same reading at 30° zenith angle but systematically different readings at 60°. The impact of these inconsistencies in field operation will be quantified using the long-term observations started in 2020.

14 SOLAR ENERGY↗
DOE OSTI2025

Bayesian Calibration of Stochastic Agent Based Model via Random Forest

Agent-based models (ABM) provide an excellent framework for modeling outbreaks and interventions in epidemiology by explicitly accounting for diverse individual interactions and environments. However, these models are usually stochastic and highly parametrized, requiring precise calibration for predictive performance. When considering realistic numbers of agents and properly accounting for stochasticity, this high-dimensional calibration can be computationally prohibitive. This paper presents a random forest-based surrogate modeling technique to accelerate the evaluation of ABMs and demonstrates its use to calibrate an epidemiological ABM named CityCOVID via Markov chain Monte Carlo (MCMC). The technique is first outlined in the context of CityCOVID's quantities of interest, namely hospitalizations and deaths, by exploring dimensionality reduction via temporal decomposition with principal component analysis (PCA) and via sensitivity analysis. The calibration problem is then presented, and samples are generated to best match COVID-19 hospitalization and death numbers in Chicago from March to June in 2020. Further, these results are compared with previous approximate Bayesian calibration (IMABC) results, and their predictive performance is analyzed, showing improved performance with a reduction in computation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation

This study proposes an automated calibration procedure for bond parameters in bonded discrete element modelling. By exploring the underlying physical correlations between microscopic parameters of bonds and macroscopic strength parameters of the continuum to be modelled, the microscopic shear strength and tensile strength are identified as independent variables for calibration purpose. Then a physics-informed iterative scheme is proposed to automatically approximate the bond parameters by viewing the micro-macro relation as an implicitly defined mathematical mapping function. As a result of highly non-convex features of this implicit mapping, the adaptive moment estimation (Adam), which is especially suitable for problems with noisy gradients, is adopted as the basic iterative scheme, in conjunction with other numerical techniques to approximately evaluate the partial derivatives involved. The whole procedure offers a simple and effective framework for bond parameter calibration. Finally, a numerical example of SiC ceramic is provided for validation. By compared with some existing calibration methods, the proposed method shows significant advantages in terms of calibration efficiency and accuracy.

42 ENGINEERING↗
DOE OSTI2021

A gain series method for accurate EMCCD calibration

Abstract Calibration of the gain and digital conversion factor of an EMCCD is necessary for accurate photon counting. We present a new method to quickly calibrate multiple gain settings of an EMCCD camera. Acquiring gain-series calibration data and analyzing the resulting images with the EMCCD noise model more accurately estimates the gain response of the camera. Furthermore, we develop a method to compare the results from different calibration approaches. Gain-series calibration outperforms all other methods in this self-consistency test.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Calibration of the underground muon detector of the Pierre Auger Observatory

To obtain direct measurements of the muon content of extensive air showers with energy above 10 16.5 eV, the Pierre Auger Observatory is currently being equipped with an underground muon detector (UMD), consisting of 219 10 m 2 -modules, each segmented into 64 scintillators coupled to silicon photomultipliers (SiPMs). Direct access to the shower muon content allows for the study of both of the composition of primary cosmic rays and of high-energy hadronic interactions in the forward direction. As the muon density can vary between tens of muons per m 2 close to the intersection of the shower axis with the ground to much less than one per m 2 when far away, the necessary broad dynamic range is achieved by the simultaneous implementation of two acquisition modes in the read-out electronics: the binary mode, tuned to count single muons, and the ADC mode, suited to measure a high number of them. In this work, we present the end-to-end calibration of the muon detector modules: first, the SiPMs are calibrated by means of the binary channel, and then, the ADC channel is calibrated using atmospheric muons, detected in parallel to the shower data acquisition. The laboratory and field measurements performed to develop the implementation of the full calibration chain of both binary and ADC channels are presented and discussed. The calibration procedure is reliable to work with the high amount of channels in the UMD, which will be operated continuously, in changing environmental conditions, for several years.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A laserball calibration device for the SNO+ scintillator phase

Located 2 km underground in SNOLAB, Sudbury, Canada, SNO+ is a large scale liquid scintillator experiment that primarily aims to search for neutrinoless double beta decay. Whilst SNO+ has light and radioactive calibration sources external to the inner volume, an internally deployed optical source is necessary for the full characterization of the detector model. A laser diffuser ball developed for SNO has previously demonstrated to be an effective optical calibration device for both SNO and SNO+ water phase. Since the introduction of liquid scintillator for SNO+, the material compatibility, cleanliness, and radiopurity requirements of any materials in contact with the internal medium have increased. Improving on the original SNO laserball design, a new laserball calibration device has been developed for the SNO+ scintillator phase with the goal of measuring the optical properties of the detector and performing routine PMT gain and timing calibrations. Simulations have been written to model the diffusion properties to optimise optical and temporal performance for calibration. Prototype laserballs have been built and characterised, demonstrating sub-ns timing resolution and a quasi-isotropic light distribution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Electron and photon energy calibration with the ATLAS detector using LHC Run 2 data

This paper presents the electron and photon energy calibration obtained with the ATLAS detector using 140 fb -1 of LHC proton-proton collision data recorded at $\sqrt{s}$ = 13 TeV between 2015 and 2018. Methods for the measurement of electron and photon energies are outlined, along with the current knowledge of the passive material in front of the ATLAS electromagnetic calorimeter. The energy calibration steps are discussed in detail, with emphasis on the improvements introduced in this paper. The absolute energy scale is set using a large sample of Z-boson decays into electron-positron pairs, and its residual dependence on the electron energy is used for the first time to further constrain systematic uncertainties. The achieved calibration uncertainties are typically 0.05% for electrons from resonant Z-boson decays, 0.4% at E T ~ 10 GeV, and 0.3% at E T ~ 1 TeV; for photons at E T ~ 60 GeV, they are 0.2% on average. This is more than twice as precise as the previous calibration. The new energy calibration is validated using J/ψ → ee and radiative Z-boson decays.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Detection and Calibration of Low-Energy Nuclear Recoils for Dark Matter and Neutrino Scattering Experiments

Detection of low-energy nuclear recoil events plays a central role in searches for particle dark matter interactions with atomic matter and studies of coherent neutrino scatters. Precise nuclear recoil calibration data allow the responses of these dark matter and neutrino detectors to be characterized and enable in situ evaluation of an experiment's sensitivity to anticipated signals. This article reviews the common methods for detection of nuclear recoil events and the wide variety of techniques that have been developed to calibrate detector response to nuclear recoils. We summarize the main experimental factors that are critical for accurate nuclear recoil calibrations, investigate mitigation strategies for different backgrounds and biases, and discuss how the presentation of calibration results can facilitate comparison between experiments. Lastly, we discuss the challenges for future nuclear recoil calibration efforts and the physics opportunities they may enable.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Robust Importance Sampling for Bayesian Model Calibration with Spatio-Temporal Data

This paper addresses two challenges in Bayesian calibration: 1) computational speed of existing sampling algorithms, and 2) calibration with spatio-temporal responses. The commonly used Markov Chain Monte Carlo (MCMC) approaches require many sequential model evaluations making the computational expense prohibitive. This paper proposes an efficient sampling algorithm: iterative importance sampling with genetic algorithm (IISGA). While iterative importance sampling enables computational efficiency, the genetic algorithm enables robustness by preventing sample degeneration and avoids getting stuck in multimodal search spaces. An inflated likelihood further enables robustness in high-dimensional parameter spaces by enlarging the target distribution. Spatio-temporal data complicate both surrogate modeling, which is necessary for expensive computational models, and the likelihood estimation. In this work, singular value decomposition is investigated for reducing the high-dimensional field data to a lower-dimensional space prior to Bayesian calibration. Then the likelihood is formulated and Bayesian inference is performed in the lower-dimension, latent space. An illustrative example is provided to demonstrate IISGA relative to existing sampling methods, and then IISGA is employed to calibrate a thermal battery model with 26 uncertain calibration parameters and spatio-temporal response data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Specifying Calibration of Energy-Measuring Equipment

A report on calibrating energy-measuring equipment to maximize energy efficiency of lighting and other systems. The report describes best practices for accrediting calibration laboratories and for calibrating measuring equipment, compares and contrasts service providers accredited for energy-measuring equipment calibration, presents a tailorable specification template for requesting such calibration, and offers recommendations to a range of stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Enhancing Camera Calibration for Traffic Surveillance with an Integrated Approach of Genetic Algorithm and Particle Swarm Optimization

Recent advancements in sensor technologies, coupled with signal processing and machine learning, have enabled real-time traffic control systems to effectively adapt to changing traffic conditions. Cameras, as sensors, offer a cost-effective means to determine the number, location, type, and speed of vehicles, aiding decision-making at traffic intersections. However, the effective use of cameras for traffic surveillance requires proper calibration. This paper proposes a new optimization-based method for camera calibration. In this approach, initial calibration parameters are established using the Direct Linear Transformation (DLT) method. Then, optimization algorithms are applied to further refine the calibration parameters for the correction of nonlinear lens distortions. A significant enhancement in the optimization process is achieved through the integration of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) into a combined Integrated GA and PSO (IGAPSO) technique. The effectiveness of this method is demonstrated through the calibration of eleven roadside cameras at three different intersections. The experimental results show that when compared to the baseline DLT method, the vehicle localization error is reduced by 22.30% with GA, 22.31% with PSO, and 25.51% with IGAPSO.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Excalibur: A Nonparametric, Hierarchical Wavelength Calibration Method for a Precision Spectrograph

Excalibur is a nonparametric, hierarchical framework for precision wavelength calibration of spectrographs. It is designed with the needs of extreme-precision radial-velocity (EPRV) instruments in mind, which require calibration or stabilization to better than 10{sup −4} pixels. Instruments vary along only a few dominant degrees of freedom, especially EPRV instruments that feature highly stabilized optical systems and detectors. Excalibur takes advantage of this property by using all calibration data to construct a low-dimensional representation of all accessible calibration states for an instrument. Excalibur also takes advantage of laser-frequency combs or etalons, which generate a dense set of stable calibration points. This density permits the use of a nonparametric wavelength solution that can adapt to any instrument or detector oddities better than parametric models, such as a polynomial. We demonstrate the success of this method with data from the Extreme Precision Spectrograph (EXPRES), which uses a laser-frequency comb. When wavelengths are assigned to laser comb lines using excalibur, the rms of the residuals is about one-fifth that of wavelengths assigned using polynomial fits to individual exposures. Radial-velocity measurements of HD 34411 show a reduction in rms scatter over a 10 month time baseline from 1.17 to 1.05 m s{sup −1}.

47 OTHER INSTRUMENTATION↗