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NASA NTRS2004

Comparison of Local Scale Measured and Modeled Brightness Temperatures and Snow Parameters from the CLPX 2003 by Means of a Dense Medium Radiative Transfer Theory Model

Microwave remote sensing offers distinct advantages for observing the cryosphere. Solar illumination is not required, and spatial and temporal coverage are excellent from polar-orbiting satellites. Passive microwave measurements are sensitive to the two most useful physical quantities for many hydrological applications: physical temperature and water content/state. Sensitivity to the latter is a direct result of the microwave sensitivity to the dielectric properties of natural media, including snow, ice, soil (frozen or thawed), and vegetation. These considerations are factors motivating the development of future cryospheric satellite remote sensing missions, continuing and improving on a 26-year microwave measurement legacy. Perhaps the biggest issues regarding the use of such satellite measurements involve how to relate parameter values at spatial scales as small as a hectare to observations with sensor footprints that may be up to 25 x 25 km. The NASA Cold-land Processes Field Experiment (CLPX) generated a dataset designed to enhance understanding of such scaling issues. CLPX observations were made in February (dry snow) and March (wet snow), 2003 in Colorado, USA, at scales ranging from plot scale to 25 x 25 km satellite footprints. Of interest here are passive microwave observations from ground-based, airborne, and satellite sensors, as well as meteorological and snowpack measurements that will enable studies of the effects of spatial heterogeneity of surface conditions on the observations. Prior to performing such scaling studies, an evaluation of snowpack forward modelling at the plot scale (least heterogeneous scale) is in order. This is the focus of this paper. Many forward models of snow signatures (brightness temperatures) have been developed over the years. It is now recognized that a dense medium radiative transfer (DMRT) treatment represents a high degree of physical fidelity for snow modeling, yet dense medium models are particularly sensitive to snowpack structural parameters such as grain size, density, and depth---parameters that may vary substantially within a snowpack. Microwave radiometric data and snow pit measurements collected at the Local-Scale Observation Site (LSOS) during the third Intensive Observation Period (IOP3) of the CLPX have been used to test the capabilities of a DMRT model using the Quasi Crystalline Approximation with Coherent Potential (QCA-CP). The radiometric measurements were made by the University of Tokyo s Ground Based Microwave Radiometer-7 (GBMR-7) system. We evaluate the degree to which a DMRT-based model can accurately reproduce the GBMR-7 brightness temperatures at different frequencies and incidence angles.

Tedescol, Marco↗

NASA NTRS2003

Transonic Experimental Observations of Abrupt Wing Stall on an F/A-18E Model (Invited)

A transonic wind tunnel test of an 8% F/A-18E model was conducted in the NASA Langley Research Center (LaRC) 16 ft Transonic Tunnel (16-ft TT) to investigate on-surface flow physics during stall. The technical approach employed focused on correlating static (or time-averaged) and unsteady wind-tunnel test data to the unsteady wing-stall events using force, moment, pressure, and pressure-sensitive-paint measurements. This paper focuses on data obtained on the pre-production configuration of the F/A-18E aircraft at Mach number of 0.90. The flow unsteadiness occurring on the wing as the wing went through the stall process was captured using the time history of balance and pressure measurements and by calculating the root mean square (RMS) for a number of instrument signals. The second step was to gather global perspectives on the pressures influencing the wing stall process. The abrupt wing stall experienced by the 8% F/A-18E Model was observed to be an unsteady event triggered by the rapid advancement of separation, which had migrated forward from the trailing edge, to the leading-edge flap hingeline over a very small increment in angle of attack. The angle of attack at which this stall occurred varied, from run to run, over an 1 deg increment. The abrupt wing stall was observed, using pressure-sensitive-paint, to occur simultaneously on both wing panels or asymmetrically. The pressure-sensitive paint data and wingroot bending moment data were essential in providing insight to the flow structures occurring over the wing and the possible asymmetry of those flow structures. A repeatability analysis conducted on eight runs of static data provided a quick and inexpensive examination of the unsteady aerodynamic characteristics of abrupt wing stall. The results of the repeatability analysis agreed extremely well with data obtained using unsteady measurement techniques. This approach could be used to identify test conditions for more complex unsteady data measurements using special instrumentation.

McMillin, S. Naomi↗

NASA NTRS2003

Transonic Experimental Observations of Abrupt Wing Stall on an F/A-l8E Model

A transonic wind tunnel test of an 8% F/A-18E model was conducted in the NASA Langley Research Center (LaRC) 16 ft Transonic Tunnel (16-ft TT) to investigate on-surface flow physics during stall. The technical approach employed focused on correlating static (or time-averaged) and unsteady wind-tunnel test data to the unsteady wing-stall events using force, moment, pressure, and pressure-sensitive-paint measurements. This paper focuses on data obtained on the pre-production configuration of the F/A-18E aircraft at Mach number of 0.90. The flow unsteadiness occurring on the wing as the wing went through the stall process was captured using the time history of balance and pressure measurements and by calculating the root mean square (RMS) for a number of instrument signals. The second step was to gather global perspectives on the pressures influencing the wing stall process. The abrupt wing stall experienced by the 8% F/A-18E Model was observed to be an unsteady event triggered by the rapid advancement of separation, which had migrated forward from the trailing edge, to the leading-edge flap hingeline over a very small increment in angle of attack. The angle of attack at which this stall occurred varied, from run to run, over an 1 degree increment. The abrupt wing stall was observed, using pressure-sensitive-paint, to occur simultaneously on both wing panels or asymmetrically. The pressure-sensitive paint data and wing-root bending moment data were essential in providing insight to the flow structures occurring over the wing and the possible asymmetry of those flow structures. A repeatability analysis conducted on eight runs of static data provided a quick and inexpensive examination of the unsteady aerodynamic characteristics of abrupt wing stall. The results of the repeatability analysis agreed extremely well with data obtained using unsteady measurement techniques. This approach could be used to identify test conditions for more complex unsteady data measurements using special instrumentation.

McMillin, S. Naomi↗

DOE OSTI2020

An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

Determining a process–structure–property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in the inverse direction are essential. Problems in materials design are often considered in the context of process–property linkage by bypassing the materials structure, or in the context of structure–property linkage as in microstructure-sensitive design problems. However, there is a lack of research effort in studying materials design problems in the context of process–structure linkage, which has a great implication in reverse engineering. In this paper, given a target microstructure, we propose an active learning high-throughput microstructure calibration framework to derive a set of processing parameters, which can produce an optimal microstructure that is statistically equivalent to the target microstructure. The proposed framework is formulated as a noisy multi-objective optimization problem, where each objective function measures a deterministic or statistical difference of the same microstructure descriptor between a candidate microstructure and a target microstructure. Furthermore, to significantly reduce the physical waiting wall-time, we enable the high-throughput feature of the microstructure calibration framework by adopting an asynchronously parallel Bayesian optimization to exploit high-performance computing resources. Case studies in additive manufacturing and grain growth are used to demonstrate the applicability of the proposed framework, where kinetic Monte Carlo (kMC) simulation is used as a forward predictive model, such that for a given target microstructure, the target processing parameters that produced this microstructure are successfully recovered.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Quantum-enhanced detection of viral cDNA via luminescence resonance energy transfer using upconversion and gold nanoparticles

Abstract The COVID-19 pandemic has profoundly impacted global economies and healthcare systems, revealing critical vulnerabilities in both. In response, our study introduces a sensitive and highly specific detection method for cDNA, leveraging Luminescence Resonance Energy Transfer (LRET) between upconversion nanoparticles (UCNPs) and gold nanoparticles (AuNPs), and achieves a detection limit of 242 fM for SARS-CoV-2 cDNA. This innovative sensing platform utilizes UCNPs conjugated with one primer and AuNPs with another, targeting the 5′ and 3′ ends of the SARS-CoV-2 cDNA, respectively, enabling precise differentiation of mismatched cDNA sequences and significantly improving detection specificity. Through rigorous experimental analysis, we established a quenching efficiency range from 10.4 % to 73.6 %, with an optimal midpoint of 42 %, thereby demonstrating the superior sensitivity of our method. Our work uses SARS-CoV-2 cDNA as a model system to demonstrate the potential of our LRET-based detection method. This proof-of-concept study highlights the adaptability of our platform for future diagnostic applications. Instrumental validation confirms the synthesis and formation of AuNPs, addressing the need for experimental verification of the preparation of nanomaterial. Our comparative analysis with existing SARS-CoV-2 detection methods revealed that our approach provides a low detection limit and high specificity for target cDNA sequences, underscoring its potential for targeted COVID-19 diagnostics. This study demonstrates the superior sensitivity and adaptability of using UCNPs and AuNPs for cDNA detection, offering significant advances in rapid, accessible diagnostic technologies. Our method, characterized by its low detection limit and high precision, represents a critical step forward in developing next-generation biosensors for managing current and future viral outbreaks. By adjusting primer sequences, this platform can be tailored to detect other pathogens, contributing to the enhancement of global healthcare responsiveness and infectious disease control.

Esmaeili, Shahriar [Institute for Quantum Science ↗

NASA NTRS1962

Influence of Tire Tread Pattern and Runway Surface Condition on Braking Friction and Rolling Resistance of a Modern Aircraft Tire

A series of taxiing tests was conducted at the Langley landing loads track with both braked and unbraked (freely rolling) single and tandem wheels equipped with 32x8.8 type VII aircraft tires of different tread designs to obtain data on tire and braking characteristics during operation on dry and on contaminated concrete and asphalt run ways. Contaminants used were water, slush, JP-4 jet fuel, and organic and detergent fire-extinguishing foams. Forward velocities for the tests ranged from approximately 13 to 104 knots. Vertical loads of approximately 9,000 to 22,000 pounds and tire inflation pressures of 85 to 350 pounds per square inch were used. Results indicated that the unbraked tire rolling resistance increased with increasing forward velocity on dry and on contaminated runway surfaces. Peak tire-ground friction coefficients developed during wheel braking decreased rapidly with increasing velocity on contaminated runways but remained relatively unchanged on dry runways as the forward velocity was increased. Dry-runway friction coefficients were found to be relatively insensitive to tire tread pattern. However, the magnitude of the friction coefficients developed by tires on contaminated runways was extremely sensitive to the tire tread pat tern used, with circumferential-groove treads developing the highest values of friction coefficient, and smooth and dimple treads the lowest values for the tread patterns and runway conditions investigated.

Horne, Walter B.↗

NASA NTRS1992

Automatic differentiation as a tool in engineering design

Automatic Differentiation (AD) is a tool that systematically implements the chain rule of differentiation to obtain the derivatives of functions calculated by computer programs. AD is assessed as a tool for engineering design. The forward and reverse modes of AD, their computing requirements, as well as approaches to implementing AD are discussed. The application of two different tools to two medium-size structural analysis problems to generate sensitivity information typically necessary in an optimization or design situation is also discussed. The observation is made that AD is to be preferred to finite differencing in most cases, as long as sufficient computer storage is available; in some instances, AD may be the alternative to consider in lieu of analytical sensitivity analysis.

Barthelemy, Jean-Francois↗

NASA NTRS1993

Precise navigation for the Earth Observing System (EOS)-AM1 spacecraft using the TDRSS Onboard Navigation System (TONS)

As the baseline navigation system for the Earth Observing System (EOS)-AM1 spacecraft, the Tracking and Data Relay Satellite System (TDRSS) Onboard Navigation System (TONS) is required to provide precise position and velocity information for imaging instrument calibration and routine operations. This paper presents the results of real-time navigation performance evaluations with respect to TONS-based orbit and frequency determination to satisfy this requirement. Both covariance and simulation analysis of EOS-AM1 navigation accuracy and analysis using operational data from Landsat-4 are presented. Local (half orbit) and global (multiple orbits) tracking are considered using a way-forward link services. Improvements in navigation accuracies by using enhanced gravity models beyond the Goddard Earth Model (GEM)-T3 are also discussed. Key objectives of the analysis are to evaluate nominal performance and potential sensitivities and to address algorithm improvements such as TDRS ephemeris biasing, ionosphere model, and gravity process noise models slated for implementation. Results indicate that TONS can be configured to meet the proposed instrument navigation requirements of 20 meters, 3-sigma.

Folta, David C.↗

NASA NTRS1994

A Role for MST Neurons in Heading Estimation

A template model of human visual self-motion perception, which uses neurophysiologically realistic "heading detectors", is consistent with numerous human psychophysical results including the failure of humans to estimate their heading (direction of forward translation) accurately under certain visual conditions. We tested the model detectors with stimuli used by others in single-unit studies. The detectors showed emergent properties similar to those of MST neurons: (1) Sensitivity to non-preferred flow; Each detector is tuned to a specific combination of flow components and its response is systematically reduced by the addition of nonpreferred flow, and (2) Position invariance; The detectors maintain their apparent preference for particular flow components over large regions of their receptive fields. It has been argued that this latter property is incompatible with MST playing a role in heading perception. The model however demonstrates how neurons with the above response properties could still support accurate heading estimation within extrastriate cortical maps.

Stone, L. S.↗

NASA NTRS1949

General Characteristics of a Airspeed System using Fuselage Static Vents on a Swept-Wing Airplane

Studies have been made by the NACA wing-flow method of the use of fuselage static orifices between the wing and tail of a swept-wing airplane for possible application to service airspeed installations. The tests were made at zero angle of attack. The results indicate that, although the maximum errors are large, these locations are usable from the consideration that the local Mach numbers at the locations studied are sensitive to variation of the true Mach number within the test Mach number range of 0.7 to 1.2. The maximum errors in Mach number in the subsonic range varied from zero for the most forward location to -0.05 for the most rearward location (indicated Mach number less than true). At Mach numbers above 1.0, the maximum errors were from 0.14 for the most forward location to 0.04 for the most rearward location.

Johnston, J. Ford↗

NASA NTRS2016

Determining the 3D Subsurface Density Structure of Taurus Littrow Valley Using Apollo 17 Gravity Data

Surface gravity surveys can detect subsurface density variations that can reveal subsurface geologic features. In 1972, the Apollo 17 (A17) mission conducted the Traverse Gravimeter Experiment (TGE) using a gravimeter that measured the local gravity field near Taurus Littrow Valley (TLV), located on the south-eastern rim of the Serenitatis basin. TLV is hypothesized to be a basaltfilled radial graben resulting from the impact that formed Mare Serenitatis. It is bounded by both the North and South Massifs (NM and SM) as well as other smaller mountains to the East that are thought to be mainly composed of brecciated highland material. The TGE is the first and only successful gravity survey on the surface of the Moon. Other more recent satellite surveys, such as NASA's Gravity Recovery and Interior Laboratory (GRAIL) mission (2011- 2012), have produced the best global gravity field to date (approx. 13km resolution). However, these satellite surveys are not sensitive enough to detect fine-scale (<1km) lunar subsurface structures. This underscores the value of the data collected at the surface by A17. In the original analysis of the data a 2D forward-modelling approach was used to derive a thickness of the subsurface basalt layer of 1.0 km by assuming a simple flat-faced rectangular geometry and using densities derived from Apollo lunar samples. We are investigating whether modern 3D modelling techniques in combination with high-resolution topographical and image datasets can reveal additional fine-scale subsurface structure in TLV.

TGE↗

NASA NTRS2015

Inficon Transpector MPH Mass Spectrometer Random Vibration Test Report

The purpose of this test report is to summarize results from the vibration testing of the INFICON Transpector MPH100M model Mass Spectrometer. It also identifies requirements satisfied, and procedures used in the test. As a payload of Resource Prospector, it is necessary to determine the survivability of the mass spectrometer to proto-qualification level random vibration. Changes in sensitivity of the mass spectrometer can be interpreted as a change in alignment of the instrument. The results of this test will be used to determine any necessary design changes as the team moves forward with flight design.

Transpector↗

DOE OSTI2022

Anisotropic superconductivity of niobium based on its response to nonmagnetic disorder

Niobium is one of the most studied superconductors, both theoretically and experimentally. It is tremendously important for applications, and it has the highest superconducting transition temperature, T c = 9.32 K, of all pure metals. In addition to power applications in alloys, pure niobium is used for sensitive magnetosensing, radio-frequency cavities, and, more recently, as circuit metallization layers in superconducting qubits. A detailed understanding of its electronic and superconducting structure, especially its normal and superconducting state anisotropies, is crucial for mitigating the loss of quantum coherence in such devices. Recently, a microscopic theory of the anisotropic properties of niobium with the disorder was put forward. To verify theoretical predictions, we studied the effect of disorder produced by 3.5 MeV proton irradiation of thin Nb films grown by the same team and using the same protocols as those used in transmon qubits. By measuring the superconducting transition temperature and upper critical fields, we show a clear suppression of T c by potential (nonmagnetic) scattering, which is directly related to the anisotropic order parameter. Here, we obtain a very close quantitative agreement between the theory and the experiment.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

BUZZ : an essential gene for postinitiation root hair growth and a mediator of root architecture in Brachypodium distachyon

Here, we discover a player in root development. Recovered from a forward-genetic screen in Brachypodium distachyon, the buzz mutant initiates root hairs but they fail to elongate. In addition, buzz roots grow twice as fast as wild-type roots. Also, lateral roots show increased sensitivity to nitrate, whereas primary roots are less sensitive to nitrate. Using whole-genome resequencing, we identified the causal single nucleotide polymorphism as occurring in a conserved but previously uncharacterized cyclin-dependent kinase (CDK)-like gene. The buzz mutant phenotypes are rescued by the wild-type B. distachyon BUZZ coding sequence and by an apparent homolog in Arabidopsis thaliana. Moreover, T-DNA mutants in A. thaliana BUZZ have shorter root hairs. BUZZ mRNA localizes to epidermal cells and develops root hairs and, in the latter, partially colocalizes with the NRT1.1A nitrate transporter. Based on qPCR and RNA-Seq, buzz overexpresses ROOT HAIRLESS LIKE SIX-1 and -2 and misregulates genes related to hormone signaling, RNA processing, cytoskeletal, and cell wall organization, and to the assimilation of nitrate. Overall, these data demonstrate that BUZZ is required for tip growth after root hair initiation and root architectural responses to nitrate.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2017

X-Ray Spectro-Polarimetry with Photoelectric Polarimeters

We derive a generalization of forward fitting for X-ray spectroscopy to include linear polarization of X-ray sources, appropriate for the anticipated next generation of space-based photoelectric polarimeters. We show that the inclusion of polarization sensitivity requires joint fitting to three observed spectra, one for each of the Stokes parameters, I(E), U(E), and Q(E). The equations for StokesI (E) (the total intensity spectrum) are identical to the familiar case with no polarization sensitivity, and for which the model-predicted spectrum is obtained by a convolution of the source spectrum, F (E), with the familiar energy response function,(E) R(E,E), where (E) and R(E,E) are the effective area and energy redistribution matrix, respectively. In addition to the energy spectrum, the two new relations for U(E) and Q(E) include the source polarization fraction and position angle versus energy, a(E), and 0(E), respectively, and the model-predicted spectra for these relations are obtained by a convolution with the modulated energy response function, (E)(E) R(E,E), where(E) is the energy-dependent modulation fraction that quantifies a polarimeters angular response to 100 polarized radiation. We present results of simulations with response parameters appropriate for the proposed PRAXyS Small Explorer observatory to illustrate the procedures and methods, and we discuss some aspects of photoelectric polarimeters with relevance to understanding their calibration and operation.

polarization↗

NASA NTRS2017

Implicit Formulation of Muscle Dynamics in OpenSim

Astronauts lose bone and muscle mass during spaceflight. Exercise countermeasure is the primary method for counteracting bone and muscle mass loss in space. New spacecraft exercise device concepts are currently being developed for the NASAs new crew exploration vehicle. The NASA Digital Astronaut Project (DAP) uses computational modeling to help determine if the new exercise devices will be effective as countermeasures. The NASA Digital Astronaut Project is developing the ability to utilize predictive simulation to provide insight into the change in kinematics and kinetics with a change in device and gravitational environment (1-g versus 0-g). For example, in space exercise the subject's body weight is applied in addition to the loads prescribed for musculoskeletal maintenance. How and where these loads are applied obviously directly impacts bone and tissue loads. Additionally, due to space vehicle structural requirements, exercise devices are often placed on vibration isolation systems. This changes the apparent impedance or stiffness of the device as seen by the user. Data collection under these conditions is often impractical and limited. Predictive modeling provides a means to have a virtual subject to test hypotheses. Predictive simulation provides a virtual subject for which we are able to perform studies such as sensitivity to device loading and vibration isolation without the need for laboratory kinematic or kinetic test data.Direct Collocation optimization provides an efficient means to perform task based optimization and predictive modeling. It is relatively straight forward to structure a physical exercise task in a Direct Collocation mathematical formulation: perform a motion such that you start at an initial pose, achieve a given amount of deflection i.e a squat, return to the initial pose, and minimize muscle activation cost. Direct Collocation is advantageous in that it does not require numerical integration to evaluate the objective function. Instead, the system dynamics are transformed to discrete time and the optimizer is constrained such that the solution is not considered to be a valid unless the dynamic equations are satisfied at all time points. The simulation and optimization are effectively done simultaneously. Due to the implicit integration, time steps can be more coarse than in a differential equation solver. In a gait scenario this means that that the model constraints and cost function are evaluated at 100 nodes in the gait cycle versus 10,000 integration steps in a variable-step forward dynamic simulation. Furthermore, no time is wasted on accurate simulations of movements that are far from the optimum. Constrained optimization algorithms require a Jacobian matrix that contains the partial derivatives of each of the dynamic constraints with respect to of each of the state and control variables at all time points. This is a large but sparse matrix. An implicit dynamics formulation requires computation of the dynamic residuals f as a function of the states x and their derivatives, and controls u:f(x, dxdt, u) 0If the dynamics of musculoskeletal system are formulated implicitly, the Jacobian elements are often available analytically, eliminating the need for numerical differentiation; this is obviously computationally advantageous. Additionally, implicit formulation of musculoskeletal dynamics do not suffer from singularities from low mass bodies, zero muscle activation, or other stiff system or

physical exercise↗

DOE OSTI2024

CCUS 2024, Interpreting the strain tensor Larry Murdoch Interpreting strain tensor data to characterize and monitor reservoirs for CO2 storage and other applications

Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and this has opened the door to new opportunities for characterization and monitoring during CCUS. We have demonstrated this method by deploying strainmeters at shallow depths (30 to 40m) and then conducting injection well tests in an underlying reservoir at 530m depth. The resulting data indicated that the horizontal strain at shallow strainmeters was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 ne/d over a few days (1 nanostrain = 1 part per billion strain). We then used the strain data to estimate reservoir properties, geometry and pressure through inversion of poroelastic forward models using both numerical and novel analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed fast, closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. This approach markedly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. Bayesian inversion is important because it provides predictions with uncertainties, which makes the results useful for decision making. We have shown with field tests and simulations that the strain tensor in the caprock is sensitive to pressure in the reservoir, reservoir properties and boundaries, and pressure in the caprock caused by leaks. These results indicate that measuring and interpreting the shallow strain tensor could be a valuable tool for both initial reservoir characterization efforts and long-term monitoring during CCUS. Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and our objective was to evaluate opportunities for strain monitoring during characterization and monitoring for CCUS. Our approach was to deploy strainmeters at shallow depths (30 to 40m) and then conduct injection well tests in an underlying reservoir at 530m depth. The results indicate that the horizontal strain at shallow strainmeters was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 ne/d over a few days (1 nanostrain = 1 part per billion strain). We then used the strain data to estimate reservoir properties, geometry and pressure through inversion of poroelastic forward models using both numerical and novel analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed fast, closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. This approach markedly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. Bayesian inversion is important because it provides predictions with uncertainties, which makes the results useful for decision making. In conclusion, we have shown with field tests and simulations that the strain tensor in the caprock is sensitive to pressure in the reservoir, reservoir properties and boundaries, and pressure in the caprock caused by leaks. These results indicate that measuring and interpreting the shallow strain tensor could be a valuable tool for both initial reservoir characterization efforts and long-term monitoring during CCUS.

Murdoch, Larry↗

DOE OSTI2020

Validation of SAS4A/SASSYS-1 for Steady-State Single-Phase Natural Circulation

The development of numerical software for engineering applications requires the validation of the code against experimental benchmark datasets. To support the validation of SAS4A/SASSYS-1 in simulating the single-phase natural circulation within nuclear reactor systems, high-precision steady-state experiments are performed to capture single-phase natural circulation phenomena on an existing scaled facility with comprehensive instrumentation. Forced convection tests are designed precisely capturing the facility’s critical thermal-hydraulic parameters required for one-dimensional modeling, and a comprehensive single-phase natural circulation dataset is obtained with well-documented experimental uncertainty and facility description. Analysis and discussion based on the finalized dataset confirm the dataset’s ability in capturing dominant phenomena and address important physical interpretation of parameters. The dataset reported in this project provides a valuable benchmark resource for the validation of system analysis codes under single-phase natural circulation inside nuclear reactors. Validation of SAS4A/SASSYS-1 is then performed against the obtained benchmark dataset to confirm the capability of its physics model in simulating the steady-state single-phase natural circulation. The experimental facility is modeled in the candidate code. Solution verification is performed using Richardson-extrapolation-based estimators to quantify and restrict numerical errors from discretization. Numerical uncertainty originating from finite maximum pseudo-transient time is also quantified and restricted. Input uncertainty provided by the benchmark dataset is forward propagated through the candidate code, directly quantifying the simulation output in a Monte Carlo approach. The composition of the output uncertainty is further determined by the estimators of Sobol’ indices through a variance-based sensitivity analysis. With uncertainty quantified for each individual condition, detailed comparison between the simulation results and experimental data is performed covering the whole dataset, which shows consistent agreement for all important quantities. The validation activity reported in this project demonstrates that SAS4A/SASSYS-1 can predict the primary parameters with satisfactorily accuracy under steady-state single-phase natural circulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗