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NASA NTRS2020

Improvements in the Calibration of the NOAA-20 VIIRS Day-Night Band Low Gain Stage Using a Solar Diffuser

We aim to introduce and demonstrate several improvements that are applied to the on-orbit solar diffuser (SD) calibration of the day-night band (DNB) low gain stage (LGS) of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the NOAA-20 satellite. The most important improvement is the expansion of the angular range, referred to “sweet spot”, from 4° to 7.8° in order to increase the number of fully-illuminated scans considered for the SD calculation. The increase in scan number enables the completion of on-orbit calibration using the SD within one orbit, compared with the multiple orbits approach, which is required in the current standard approach applied in operational DNB LGS calibration coefficients look-up tables (LUTs) updates. The NOAA-20 DNB LGS calibration coefficients have been derived with the new methodology and the results show a more stable, smoother, and less noisy trend when compared with the current standard approach. The results also demonstrate that the NOAA-20 VIIRS DNB overall on-orbit performance has been very stable.

NOAA-20↗

NASA NTRS2020

Assessment of MODIS and VIIRS Calibration Consistency for Reflective Solar Bands Using Vicarious Approaches

The Moderate-Resolution Imaging Spectroradiometer (MODIS) is the key instrument of the NASA’s Earth Observing System (EOS) Terra and Aqua missions, launched in December 1999 and May 2002, respectively. The Visible Infrared Imaging Radiometer Suite (VIIRS) expands the MODIS legacy, launched onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite in October 2011 and NOAA20 satellite in November 2017, respectively. The MODIS and VIIRS sensors have a similar design with spectrally matched reflective solar spectral bands (RSB). Their on-board calibration components include a solar diffuser and a solar diffuser stability monitor for RSB, a V-grooved blackbody for the thermal emissive bands (TEB), and a space view as a background reference. This study evaluates the calibration consistency of the Terra and Aqua MODIS RSB based on the current Collection 6.1 L1B data products generated by the NASA MODAPS, which have used consistent calibration coefficient look up tables (LUT) for the entire data-record. In the case of SNPP and NOAA20 VIIRS, the latest L1B data produced by NASA Land SIPS are used. Several independent vicarious approaches are used to examine the stability and consistency of the at-sensor reflectance among MODIS and VIIRS instruments. Vicarious approaches include observations from simultaneous nadir overpasses (SNO), the Libya-4 desert and Dome C snow sites, as well as deep convective clouds (DCC). Impact of existing band spectral difference on the reflectance is corrected using hyperspectral observations provided by Europe Space Agency’s SCIAMACHY sensor. Results of this study provide comprehensive assessments of calibration performance, radiometric agreement and associated uncertainties.

MODIS↗

NASA NTRSDate not supplied

X-59 Air Data Probe Calibration Wind Tunnel Test

NASA's aeronautical innovators are working with Lockheed Martin to design and build a supersonic X-plane, the X-59, under the the Low Boom Flight Demonstrator (LBFD) Project, that produces a gentle thump rather than a loud sonic boom. The plane will be used to collect human response data over select U.S. communities. The data from the X-59 test flights will be provided to U.S. and international regulators to potentially allow supersonic flight over land, drastically reducing travel time within the U.S. and around the world. Two wind tunnel tests were conducted in the NASA Glenn Research Center (GRC) 8- by 6-Foot Supersonic Wind Tunnel to calibrate the nose probe for the X-59. The probe was successfully tested and calibrated at 19 Mach numbers between Mach 0.25 and Mach 1.7. Most data were collected using continuous roll angle sweeps at a set Mach number and pitch angle. About 725 high quality data runs were recorded during testing to be used in the calibration of the probe. A backup nose probe was also run through the same test matrix as the primary probe. The probe will be the primary instrument for the flight test of the X-59 for determining angle of attack, angle of sideslip, airspeed, and pressure altitude of the aircraft in flight. Knowing the aircraft's speed and attitude is critical for flight safety and is also critical data for the Sonic Boom mission. Areas of interest for the test were sea level takeoff and landing at Mach 0.2, subsonic cruise at Mach 0.9, and supersonic cruise at Mach 1.4. During Phase I flight testing, the air data nose probe and air data system as a whole will be further calibrated in flight to account for additional installed effects of the airframe on the air data system.

X-59↗

NASA NTRSDate not supplied

X-59 Air Data Probe Calibration Wind Tunnel Test

X-59↗

NASA NTRS2023

Efficient Calibration of Expensive Computational Models

Accounting for uncertainty when calibrating expensive computational models is a common challenge faced by scientists and engineers. Often Bayesian techniques are adopted to estimate a probability density function over the model parameters given noisy empirical data. The methods used to perform this type of probabilistic calibration are computationally prohibitive in that they require a large number of evaluations of the expensive model. In these cases, surrogate modeling -- that is, using a fast-to-evaluate, lower fidelity stand-in for the original computational model -- may be the only option to alleviate this computational burden. However, the upfront cost of generating training data to build a surrogate model can itself be expensive. As such, it is important to be judicious when selecting training points at which the full-fidelity model is evaluated. Here, an active learning approach is proposed that enables efficient selection of training points using approximate samples of the calibrated parameter probability density function. In this way, the training points can be concentrated in regions where the calibration algorithm requires high model accuracy.

active learning↗

NASA NTRSDate not supplied

An Inverse Chance-constrained Approach to the Calibration of Robust Models

This paper proposes a strategy to calibrate computational models according to uncertain input-output data. To this end, uncertainty in the data is first quantified by creating adversarial data sets. Samples drawn from such sets are then mapped from the input-output space to the parameter space using an inverse mapping. This mapping minimizes the collective output spread of an ensemble of point predictions while satisfying a set of individual data-matching requirements. The distribution of the resulting parameter points, which often exhibits strong parameter dependencies, is then modeled using sliced-normals. The chance-constrained formulation used to learn this distribution enables the analyst to trade-off a greater likelihood for most of the data against a lower likelihood for some of the data thereby relaxing the conservatism of the calibrated model. This formulation not only neglects the worst-performing quantiles of each adversarial distribution but also eliminates the potentially serious effects that outliers might have on the resulting model. This calibration approach not only has a considerably lower computational cost than the standard forward approach but it also allows for the identification of suitable distribution classes, which in turn yield better calibrated models.

Calibration↗

NASA NTRSDate not supplied

Using Scattered Light From Nadir Port to Aid the Terra and Aqua MODIS Reflective Solar Band Calibration

The MODIS instruments on the Terra and Aqua spacecraft employ a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) system to calibrate their reflective solar bands (RSBs), covering a spectral range from 0.4 to 2.1 µm. The UV exposure of the SD, from its sun-view port as well as the scattered light (sunlight reflected from top-of-atmosphere), has led to a wavelength dependent degradation of the SD, with larger degradation observed at shorter wavelengths. The scatter off the diffuser onto the scan mirror is in the forward direction, whereas the scatter off the diffuser onto the SDSM fold mirror is in the backward direction. Since the outgoing angles (viewed by MODIS detectors) are the same as the scheduled SD calibration, the gain derived from scattering light facilitates monitoring the dependence of the SD’s degradation on incident angles. In this paper, we present a method that uses multiple orbits over each mission to obtain a SD response to the nadir port illumination. The SD degradation estimated from the nadir port illumination is compared with the degradation derived from the sun-illuminated SD. As both Terra and Aqua spacecraft continue to drift from their nominal orbits, the SD calibration mechanism has been adapted to these drifts, especially in terms of characterizing the transmission screen function. This paper also presents the utility of this scattering light data to support the RSB calibration in the post-nominal orbit drift era of operations.

MODIS↗

DOE OSTI2017

FAST Model Calibration and Validation of the OC5- DeepCwind Floating Offshore Wind System Against Wave Tank Test Data: Preprint

During the course of the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project, which focused on the validation of numerical methods through comparison against tank test data, the authors created a numerical FAST model of the 1:50-scale DeepCwind semisubmersible system that was tested at the Maritime Research Institute Netherlands ocean basin in 2013. This paper discusses several model calibration studies that were conducted to identify model adjustments that improve the agreement between the numerical simulations and the experimental test data. These calibration studies cover wind-field-specific parameters (coherence, turbulence), hydrodynamic and aerodynamic modeling approaches, as well as rotor model (blade-pitch and blade-mass imbalances) and tower model (structural tower damping coefficient) adjustments. These calibration studies were conducted based on relatively simple calibration load cases (wave only/wind only). The agreement between the final FAST model and experimental measurements is then assessed based on more-complex combined wind and wave validation cases.

17 WIND ENERGY↗

DOE OSTI2017

FAST Model Calibration and Validation of the OC5-DeepCwind Floating Offshore Wind System Against Wave Tank Test Data

17 WIND ENERGY↗

DOE OSTI2017

Reduced chemistry model calibration using unsteady flames with repetitive extinction and ignition

In this paper, combustion in a narrow channel with an imposed temperature gradient is used to calibrate a reduced chemical mechanism. The focus is placed on unsteady flames with repetitive extinction and ignition (FREI) at high pressure. The reduced mechanism follows a hybrid approach, combining a small fuel-dependent submechanism with a detailed fuel-independent submechanism for the core species chemistry. The fuel-dependent submechanism consists of three species and nine reactions describing both the low and high-temperature fuel decomposition pathways. The sensitivity of the extinction and ignition locations to the fuel-dependent reactions is assessed and multiple reactions are found to affect the FREI behavior. The sensitive reactions are calibrated following a Bayesian approach. The calibrated reduced model is compared to a detailed model and good agreement in ignition delay times and laminar flame speeds is observed. Finally, this illustrates the potential of a micro flow reactor with a controlled temperature profile to test fuels, calibrate chemical models, and infer kinetic data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Neutronics Analysis of TREAT Multi-SERTTA Calibration Test Vehicle (Multi-SERTTA CAL)

Transient testing is a necessary step in the performance evaluation of Accident Tolerant Fuels (ATF) developed as part of the Fuel Cycle Research and Development Advanced Fuels Campaign initiated and supported by the United States Department of Energy (DOE-NE). These advanced fuels are expected to be used in future reactors or replace the current fuel design used in existing power reactors for enhanced performance and safety. Upon completion of a process proscribed by the National Environmental Policy Act, the Transient Reactor Test (TREAT) facility, located at Idaho National Laboratory (INL), was chosen by DOE-NE to provide the desired specialized testing. TREAT has successfully operated from start-up in 1959 to 1994 when it was placed on operational stand-by. Careful preparations are being made for operational readiness and TREAT is projected to resume testing no later than 2018. Past TREAT testing primarily focused on sodium-cooled reactor fuels (SRF). Test vehicle designs varied to accommodate testing needs ranging from separate effects tests to integral tests approaching simulation of actual reactor environment conditions including forced convection cooling. The current focus on light water reactor (LWR) ATF requires design of new experiment vehicles to accommodate the water/steam environment and associated complexities regarding desired energy deposition into the specimen and proper containment. The first set of experiments in TREAT restart is expected to be conducted with the Multi-SERTTA (Static Environment Rodlet Transient Test Apparatuses). Difficult to quantify and calculate integral and time dependent effects inherent in transient testing limit predictive modeling capability; therefore, calibration testing in TREAT prior to the actual experiment is necessary to empirically determine the effectiveness of core-to-specimen power coupling in order to achieve the desired energy deposition into the test specimen during a nuclear power transient. This has been done in the past, in part, by evaluating the difference in energy deposition into dosimeter wires subjected to various TREAT time dependent power conditions. These calibration tests were typically conducted in a test vehicle neutronically similar to the actual test vehicle, but more simplistic in design in order to quickly retrieve and analyze dosimeter wires and minimize containment structure costs due to several trials. Prior calibration testing for SRF experiments could be conducted without coolant as sodium has no notable neutronic effect on the core-to-specimen power coupling factor (PCF). Such is not the case with LWR fuel where water serves as both moderator and coolant. This presents a design challenge as the calibration test vehicle must retain heated, high-pressure water to preserve neutronic equivalence representative of near prototypic reactor conditions while allowing for quick retrieval of dosimeters. The solution to this challenge comes in the form of a thin walled dry well positioned through the center of the basic Multi-SERTTA design. Test vehicle reactivity worth and PCF are two important factors with respect to ascertainment of neutronic equivalence. Similarity in test vehicle reactivity worth is desired to avoid the need to change operational core rod positions in TREAT which could significantly alter neutron flux distribution and consequently power distribution throughout the core and into the test specimen. The geometry and composition of various materials within the experiment containment structure can also significantly alter the quality of neutron signal delivery from the core to the test specimen. Introduction of an Inconel tube, albeit very thin, is expected to impact PCF. Simple modifications to the CAL design may compensate for the anticipated change. Evaluation of these factors and proposed modifications through neutronics analysis serves to inform experiment design and is a valuable tool towards achieving the optimal CAL design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Calibration of COBRA-TF and STAR-CCM+ with Dakota 6.5 for CASL

High-to-low (Hi2Lo) is utilizing a validated model in a high resolution code to generate synthetic data for improvement of the same model in a lower resolution code. This process is useful in cases where experimental data does not exist or is not sufficient. Data from the high resolution code is treated as calibration data (with appropriate uncertainties and error bounds) which can be used to train parameters that affect solution accuracy in the lower resolution code model and reduce uncertainty. Implementing the Hi2Lo process between COBRA-TF (CTF) and STAR-CCM+ (STAR) within a Dakota 6.5 framework is the goal of this work. High resolution results provided by STAR will eventually be used in addition to experimental data from Westinghouse Electric Company (WEC) to reduce uncertainty in the CTF model. The scope of the work presented herein is a proof of concept for deterministic calibration using Dakota and is not a demonstration of the Hi2Lo process. CTF temperatures will be calibrated to WEC experimental data as a first demonstration of the calibration process. Validation of the CTF model with experimental data was performed previously.

42 ENGINEERING↗

DOE OSTI2024

VALIDATION, VERIFICATION, AND CALIBRATION THROUGH A CAUSAL LENS

This paper presents an alternative method based on causal inference to perform validation, verification, and calibration of simulation models. While classical validation and verification approaches focus on the identification of the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on the identification of causal relationships between data elements. Statistical and machine learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between datasets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, then the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles it is known as a directed acyclic graph (DAG). A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and from experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts have a means to identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Radiometer Calibration and Characterization (RCC) User's Manual: Windows Version 4.0

The Radiometer Calibration and Characterization (RCC) software is a data acquisition and data archival system for performing Broadband Outdoor Radiometer Calibrations (BORCAL). RCC provides a unique method of calibrating broadband atmospheric longwave and solar shortwave radiometers using techniques that reduce measurement uncertainty and better characterize a radiometer's response profile. The RCC software automatically monitors and controls many of the components that contribute to uncertainty in an instrument's responsivity. This is a user's manual and guide to the RCC software.

47 OTHER INSTRUMENTATION↗

DOE OSTI2019

Characterization of Calibrated Gelatin Sponge Particles in a Rabbit Renal Embolization Model

Purpose: To evaluate the level of artery occlusion, degradation periods, tissue response and vessel recanalization of calibrated gelatin sponge particles after segmental renal artery embolization. Materials and Methods: Superselective embolization of 14 adult rabbits was performed with calibrated gelatin sponge particles (150–350 μm). Two rabbits were killed immediately after the procedure (day 0). One pair of rabbits was killed on each of the following days: 1, 3, 7, 14, 28 and 56. One rabbit from each pair underwent CT angiography before embolization and killing. The pathologic changes of the embolized renal parenchyma and embolic characteristics of calibrated gelatin sponge particles were evaluated histologically and angiographically. Results: Calibrated gelatin sponge particles were distally located in interlobular artery with a dense packing on day 0. The level of occlusion paralleled the size of the particles. Partial degradation of the particles was observed on day 3, and complete degradation was observed on day 14. Vessel recanalization was observed through both CTA and histological analysis starting on day 3. Vascular inflammation responding to gelatin sponge particles was mild and subsided with the degradation of the particles. On day 28 and day 56, attenuation of embolized vessels occurred due to marked intimal proliferation, and vascular occlusion developed. Conclusions: Gelatin sponge particles of 150–350 μm produced dense and distal embolization, and were resorbed before day 14 with a mild tissue reaction. Vessel recanalization occurred secondary to the resorption of gelatin sponge particles, but permanent vascular occlusion developed due to marked intimal hyperplasia after day 28.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2020

Understanding Calibration and Error Propagation in Longitudinal and Lateral Manganin Gauge Shock Experiments

Soda-lime glass remains elastic under shock pressures up to approximately 6.5 GPa. In this paper, soda lime glass shock experiments are used to understand the calibration and error propagation in longitudinal and lateral manganin gauge experiments. The errors in the calibration process for both longitudinal and lateral manganin gauge experiments are identified and discussed. Five soda-lime glass experiments up to 3 GPa are analyzed using this refined technique. The results show good agreement between the experimental data and the published calibration by Rosenberg and Moshel. Errors are propagated from the experimental data measurements and the assumptions that are made in the calibration, where the bulk of the error seems to come from uncertainty in the dynamic yield strength of manganin. Finally, the method presented in this paper allows for analysis of dynamic shock experiments with longitudinal and lateral manganin gauges including error propagation.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Further Development of the Tamped Richtmyer-Meshkov Instability Method and Application to Molybdenum Dynamic Strength Calibration and Tabulation

The high pressure and high strain rate dynamic strength of Mo is experimentally and computationally investigated in the 3–20 GPa stress, 50–600 C temperature, and 10 5 –10 6 /s strain rate regimes using a modified tamped Richtmyer-Meshkov instability (RMI) method. Modifications to the tamped RMI method include a method to determine loading states during strain, a new strength calibration function based on interface shape, and a robust uncertainty quantification method. These modifications improve fidelity of the tamped RMI method, allowing evaluation of the compensating effects of pressure hardening, strain rate hardening, strain hardening, and thermal softening. The new calibration function based on interface shape is not limited to sinusoidal corrugations and could be applied to additional interface shapes. Plate impact experiments are performed at Argonne National Laboratory’s Advanced Photon Source’s Dynamic Compression Sector operated by Washington State University (DCS), driving a planar shock front through a corrugated Mo-D 2 O or Mo-C 8 F 18 interface, forcing the corrugation to significantly deform. The extent of interfacial deformation, RMI growth, is experimentally observed using X-ray phase contrast imaging at the DCS. RMI jet lengths and jet shapes are extracted from the experimental radiographs, then used to calibrate numerical simulations performed with the Sandia National Laboratories (SNL) hydrocode CTH. Mo yield strength, Y, as a function of shock pressure, P, strain rate, $\dot{\varepsilon }$, accumulated strain, ϵ, relative volumetric compression, RD , and temperature, T , is determined for each impact experiment and presented. The calibrated Mo yield strength values range 1.2–1.8 GPa, with strength generally decreasing as the impact stress increases. This trend is likely caused by thermal softening or strain localization. The tabular yield strength versus loading condition data presented in this paper can be used to fit complex strength models.

Voorhees, T. J. [Sandia National Lab. (SNL-CA), Li↗

DOE OSTI2022

Dynamic calibration of differential equations using machine learning, with application to turbulence models

We present a methodology for calibration of parametric ordinary and partial differential equation models, using off-the-shelf software for back-propagation in Neural Networks (NN). As a prototypical example, we consider calibration of a Reynolds-averaged Navier-Stokes (RANS) turbulence closure model, against ground truth data from direct numerical simulations (DNS) of two different turbulent flows. Numerical time integration is represented as a custom NN, where only the RANS model parameters are trainable. A loss function is defined to quantify the mismatch between the NN prediction and the ground truth over a predefined, finite time integration window. This loss function is then minimized using a gradient descent method utilizing the back-propagation algorithm. Furthermore, this dynamic approach to training is to be contrasted with a static approach, wherein a least square regression estimate for parameters is obtained in the limit of an infinitesimal time integration window. In a first test of static and dynamic approaches against ground truth data generated by the model, the former proves to be significantly faster and more accurate than the latter at recovering the parameters. When both calibration approaches are tested against DNS data, for which it is known that the model cannot achieve a perfect fit, the static approach yields a good prediction only for short times, while the dynamic approach results in physical and stable predictions over the entire integration window. After optimization of the dynamic approach for time step, spatial resolution, stability, and physics-based constraints, we obtain a 50% improvement of outcomes over those obtained from the existing, manually calibrated set of parameters, demonstrating the merits of this systematic and automated procedure.

97 MATHEMATICS AND COMPUTING↗