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

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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

MCS solutions for the TVA Watts Bar Unit 1 multi-physics depletion benchmark

The high-fidelity solution for exercises 1-3 of the recently developed TVA Watts Bar Unit 1 multi-physics and multi-cycle depletion benchmark using MCS was coupled with two different thermal-hydraulics (TH) codes: TH1D and COBRA-TF (CTF), and their solutions were compared. The solutions from MCS/CTF and MCS/TH1D for typical Pressurized Water Reactor (PWR) problems are quite close. And to evaluate MCS solutions for the benchmark, their results were also compared against measured data as well as publicly available high-fidelity solutions. The MCS criticality solutions at Hot Zero Power (HZP) deviate within 50 pcm against the reference solutions. While for the critical boron concentration (CBC) search calculations, the difference on the MCS calculated CBC is about 7 ppm, and the root-mean-squared (RMS) errors for the assembly power distribution and outlet coolant temperature are less than 0.5% and 1 Celsius degree respectively. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Thermal interpretation of infrared dynamics in de Sitter

The infrared dynamics of a light, minimally coupled scalar field in de Sitter spacetime with Ricci curvature R = 12 H {sup 2}, averaged over horizon sized regions of physical volume V {sub H} = (4π/3)(1/ H ){sup 3}, can be interpreted as Brownian motion in a medium with de Sitter temperature T {sub DS} = h-bar H /2π. We demonstrate this by directly deriving the effective action of scalar field fluctuations with wavelengths larger than the de Sitter curvature radius and generalizing Starobinsky's seminal results on stochastic inflation. The effective action describes stochastic dynamics and the fluctuating force drives the field to an equilibrium characterized by a thermal Gibbs distribution at temperature T {sub DS} which corresponds to a de Sitter invariant state. Hence, approach towards this state can be interpreted as thermalization. We show that the stochastic kinetic energy of the coarse-grained description corresponds to the norm of ∂{sub μ}φ and takes a well defined value per horizon volume ½((∇φ){sup 2}) = − ½ T {sub DS}/ V {sub H} . This approach allows for the non-perturbative computation of the de Sitter invariant stress energy tensor ( T {sub μν}) for an arbitrary scalar potential.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Development of a Kalman filter estimator for simulation and control of particulate matter distribution of a diesel catalyzed particulate filter

The knowledge of the temperature and particulate matter mass distribution is essential for monitoring the performance and durability of a catalyzed particulate filter. A catalyzed particulate filter model was developed, and it showed capability to accurately predict temperature and particulate matter mass distribution and pressure drop across the catalyzed particulate filter. However, the high-fidelity model is computationally demanding. Therefore, a reduced order multi-zone particulate filter model was developed to reduce computational complexity with an acceptable level of accuracy. In order to develop a reduced order model, a parametric study was carried out to determine the number of zones necessary for aftertreatment control applications. The catalyzed particulate filter model was further reduced by carrying out a sensitivity study of the selected model assumptions. The reduced order multi-zone particulate filter model with 5 × 5 zones was selected to develop a catalyzed particulate filter state estimator considering its computational time and accuracy. Next, a Kalman filter–based catalyzed particulate filter estimator was developed to estimate unknown states of the catalyzed particulate filter such as temperature and particulate matter mass distribution and pressure drop (Δ P) using the sensor inputs to the engine electronic control unit and the reduced order multi-zone particulate filter model. A diesel oxidation catalyst estimator was also integrated with the catalyzed particulate filter estimator in order to provide estimates of diesel oxidation catalyst outlet concentrations of NO 2 and hydrocarbons and inlet temperature for the catalyzed particulate filter estimator. The combined diesel oxidation catalyst–catalyzed particulate filter estimator was validated for an active regeneration experiment. The validation results for catalyzed particulate filter temperature distribution showed that the root mean square temperature error by using the diesel oxidation catalyst–catalyzed particulate filter estimator is within 3.2 °C compared to the experimental data. Similarly, the Δ P estimator closely simulated the measured total Δ P and the estimated cake pressure drop error is within 0.2 kPa compared to the high-fidelity catalyzed particulate filter model.

Engineering↗
DOE OSTI2019

EGS Collab Project: Accomplishments and Plan

To better understand stimulation and inter-well flow in crystalline rock with the goal of developing and improving subsurface heat exchangers for enhanced geothermal energy recovery, the EGS (Enhanced Geothermal Systems) Collab project is developing highly monitored, well- characterized intermediate scale (~10-20 m) field test beds, stimulating, and performing flow tests. These tests provide the ability to evaluate concepts, data to test and validate models, and tools to be used for EGS development, which may be evaluated at DOE’s Frontier Observatory for Research in Geothermal Energy (FORGE) project. Numerical simulation is key to the project, for experiment design and interpretation of results. Testbed characterization included optical and acoustic televiewers, full waveform seismic, electromagnetic, gamma, and temperature. The test block was further characterized using seismic tomography (p- and s-), electrical resistance tomography (ERT), and hydrologic characterization including tracer tests. Coupled process models are constrained by the detailed site characterization data. Installed monitoring systems include: 1) passive seismic/acoustic emissions; 2) continuous active source seismic; 3) ERT, with dynamic imaging using high contrast fluids; and 4) distributed acoustic, temperature, and strain fiber optic sensors. During flow and stimulation tests, fracture aperture strain monitoring is performed using the Step-rate Injection Method for Fracture In-situ Properties (SIMFIP) tool. Pressure and flow in the injection and production boreholes are monitored, and tracer tests and wavefield imaging and inversion are performed to provide additional constraints. Stimulations have been performed at several locations, connecting our injection and production wells. An overview of the EGS Collab project is presented to provide a framework for other EGS Collab presentations, along with results from numerical simulations and experiments performed at the Sanford Underground Research Facility in South Dakota.

Enhanced Geothermal Systems, EGS Collab, stimulati↗
DOE OSTI2022

Heat pulse testing at monitoring wells to estimate subsurface fluid velocities in geological CO 2 storage

Monitoring the injected CO 2 during geological CO 2 storage (GCS) is essential to assure containment and identify CO 2 leakage. Here in this work, a new approach is introduced to estimate the evolution of the downhole fluid velocity at a monitoring well and identify CO 2 arrival time using in-well heat pulse/tracer test. The proposed technique involves using a downhole heater to generate a series of heat pulses and measuring their corresponding temperature response. The surface temperature of the downhole heater is controlled by the supplied electrical power and the heat loss by convection to the surroundings. Convective heat transfer is well described using Newton's law of cooling in which the temperature difference between the heater and the surrounding fluids drives the heat transfer, for which the convection heat transfer coefficient (h) controls the magnitude of heat loss. Among various factors that control h, it depends on the type of the flowing fluid and its velocity. Through analyzing the measured temperature at different heat pulses, the changes in h - due to mobilization of the in-situ brine or CO 2 arrival - can be estimated. Consequently, the velocity of the flowing fluid across the heater can be obtained. Since heat transfer by convection is sensitive to the type of the surrounding fluid, intrusion of CO 2 can be detected from the relatively higher surface temperature obtained at CO 2 arrival. Churchill and Bernstein (1977)'s correlation is adopted to estimate the change of fluid velocity in terms of the change in h. To demonstrate the validity of the proposed technique, the results are applied and validated against those of COMSOL Multiphysics simulation tool for single-phase brine (before CO 2 arrival) and single-phase CO 2 (after CO 2 arrival). The observed temperature heating is sensitive to the flowing fluid velocity and fluid type. The temperature signal observed at CO 2 arrival is large and easily detectable using temperature monitoring tool which provides reliable indication for tracking CO 2 arrival at monitoring wells compared with passive temperature monitoring. The results obtained using the proposed technique agree very well with the numerical results obtained from the simulation tool with a maximum estimation error of 7 percent.

02 PETROLEUM↗
DOE OSTI2016

The role of zonal flows in the saturation of multi-scale gyrokinetic turbulence

The 2D spectrum of the saturated electric potential from gyrokinetic turbulence simulations that include both ion and electron scales (multi-scale) in axisymmetric tokamak geometry is analyzed. The paradigm that the turbulence is saturated when the zonal (axisymmetic) ExB flow shearing rate competes with linear growth is shown to not apply to the electron scale turbulence. Instead, it is the mixing rate by the zonal ExB velocity spectrum with the turbulent distribution function that competes with linear growth. A model of this mechanism is shown to be able to capture the suppression of electron-scale turbulence by ion-scale turbulence and the threshold for the increase in electron scale turbulence when the ion-scale turbulence is reduced. The model computes the strength of the zonal flow velocity and the saturated potential spectrum from the linear growth rate spectrum. The model for the saturated electric potential spectrum is applied to a quasilinear transport model and shown to accurately reproduce the electron and ion energy fluxes of the non-linear gyrokinetic multi-scale simulations. The zonal flow mixing saturation model is also shown to reproduce the non-linear upshift in the critical temperature gradient caused by zonal flows in ion-scale gyrokinetic simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Future Projections of the Large-Scale Meteorology Associated with California Heat Waves in CMIP5 Models

Previous work showed that climate models capture historical large-scale meteorological patterns (LSMPs) associated with California Central Valley heat waves including both ways these heat waves form. This work examines what models predict under the Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios. Model performance varies, so a multimodel average weights each model based on its historical performance in four parameters. An LSMP index (LSMPi) defined using upper atmosphere variables captures dates of past extreme surface temperature maxima. LSMPi correlates well with all values of California Central Valley-average surface maximum temperature. LSMPi distributions in future simulations shift ~0.6 standard deviations higher between 1961–2000 and 2061–2100 for RCP8.5 data. Based on the historical climatology, future scenarios show a large increase in the frequency and duration of heat waves in every model. Four times as many heat waves occur and their median duration doubles, using historical thresholds. Of the two ways heat waves form, Type 1 has similar frequency in the future. But, Type 2 becomes much more common because Type 2 has a preexisting hot anomaly in Southwestern Canada, much like the historical to future climatological change in that region (a “global warming” signal). The 20-year return value anomaly increases by 30–40%. The average of the 50 hottest temperatures increases 3.5–6 K depending on the scenario. When extreme values are defined using the future climatology, the models and their average have no consistent increase or decrease of distribution properties such as shape, scale, and return values of the extremes compared to historical values.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Initial position optimization in molecular dynamics simulations for a Coulomb system

A new algorithm for molecular dynamics (MD) simulations is developed to optimize plasma particle distributions at given initial temperatures. By combining velocity scaling and reassignment, the method effectively eliminates the initial rise and oscillation in temperatures observed with randomly distributed positions. These rises and oscillations are undesired numerical artifacts observed in conventional plasma MD simulations, arising from unoptimized particle positions. The algorithm demonstrates temperature relaxation without initial rises or oscillations, as well as precise flow velocity relaxation, enabling accurate measurement of relaxation times. The code is accelerated using graphics processing units for parallel processing, enhancing the study of plasma dynamics. The proposed method for distributing physically valid particles in MD simulations enables accurate studies of intrinsic collision processes in plasmas, including the dynamics of strongly coupled plasmas, plasma–wave interactions, and transport phenomena in magnetized plasmas. The paper concludes with a discussion of potential applications and future enhancements to the algorithm.

Jo, Jawon (ORCID:0009000924193285)↗
DOE OSTI2016

Effect of total and pair configurational entropy in determining dynamics of supercooled liquids over a range of densities

In this paper, we present a study of supercooled liquids interacting with the Lennard Jones potential and the corresponding purely repulsive (Weeks-Chandler-Andersen) potential, over a range of densities and temperatures, in order to understand the origin of their different dynamics in spite of their structures being similar. Using the configurational entropy as the thermodynamic marker via the Adam Gibbs relation, we show that the difference in the dynamics of these two systems at low temperatures can be explained from thermodynamics. At higher densities both the thermodynamical and dynamical difference between these model systems decrease, which is quantitatively demonstrated in this paper by calculating different parameters. The study also reveals the origin of the difference in pair entropy despite the similarity in the structure. Although the maximum difference in structure is obtained in the partial radial distribution function of the B type of particles, the rdf of AA pairs and AB pairs gives rise to the differences in the entropy and dynamics. This work supports the observation made in an earlier study [A. Banerjee et al., Phys. Rev. Lett. 113, 225701 (2014)] and shows that they are generic in nature, independent of density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

An innovative and alternative approach toward gear fabrication

In this paper, we present the first demonstration of single-step gear manufacturing via an innovative in-situ friction stir forging approach. This novel process is a natural extension to the friction stir processing technique and relies on shear and normal stresses to form the complex shapes. Friction stir welding pin tool with shoulder is plunged at high revolutions per minute (rpm) into the sample to heat it to the desired temperature and enable plastic flow. Then, the tool is forged at high plunge rate to form the desired structurally-sound and defect free complex shapes. To better visualize the process the experiments are complemented by a 3D thermomechanically coupled, smoothed particle hydrodynamics (SPH) model to understand the material flow pattern both radially and through thickness in the gear teeth, plastic strain distribution, and temperature profile. We have demonstrated application of I-FSF to inherently poor formable AZ31 Mg, AA 7075-T6, and AA5083–10 vol% TiB 2 composite and fabricated 14-tooth spur gears from these materials with minimal farther machining. In conclusion, microstructure of the forged gears exhibited a directional material flow pattern due to the normal forging action and refinement of grains to 6–13 μm through dynamically recrystallization across the radial, through-thickness direction, which is in good agreement with the corresponding SPH simulation results.

42 ENGINEERING↗
DOE OSTI2022

Probing plasma physics with spectral index maps of accreting black holes on event horizon scales

The Event Horizon Telescope (EHT) collaboration has produced the first resolved images of the supermassive black holes at the centre of our galaxy and at the centre of the elliptical galaxy M87. As both technology and analysis pipelines improve, it will soon become possible to produce spectral index maps of black hole accretion flows on event horizon scales. Here, in this work, we predict spectral index maps of both M87* and Sgr A* by applying the general relativistic radiative transfer (GRRT) code IPOLE to a suite of general relativistic magnetohydrodynamic (GRMHD) simulations. We analytically show that the spectral index increases with increasing magnetic field strength, electron temperature, and optical depth. Consequently, spectral index maps grow more negative with increasing radius in almost all models, since all of these quantities tend to be maximized near the event horizon. Additionally, photon ring geodesics exhibit more positive spectral indices, since they sample the innermost regions of the accretion flow with the most extreme plasma conditions. Spectral index maps are sensitive to highly uncertain plasma heating prescriptions (the electron temperature and distribution function). However, if our understanding of these aspects of plasma physics can be tightened, even the spatially unresolved spectral index around 230 GHz can be used to discriminate between models. In particular, Standard and Normal Evolution (SANE) flows tend to exhibit more negative spectral indices than Magnetically Arrested Disc (MAD) flows due to differences in the characteristic magnetic field strength and temperature of emitting plasma.

(magnetohydrodynamics) MHD↗
DOE OSTI2018

Application of LES-CFD for predicting pulverized-coal working conditions after installation of NOx control system

The upcoming environmental requirements outlined at the 2017 European Commission Integrated Pollution Prevention and Control (IPPC) are becoming more and more strict in comparison to the existing standards – IED 2010/75/EU. Questions arise about changes in boiler operating conditions after the adoption of the regulations to fulfill specified emission limits. Of initial concern is the question of which technology to pursue in order to reach the specified level of NOx emissions at 150 mg/Nm 3 @6%O 2 . By introducing an air staging technique the NOx limit can be partially achieved; however these changes affect the boiler operation in a detrimental way. In order to investigate impact of de-NOx installation on the temperature and heat flux distribution, numerical techniques can be used. In order to determine the impact of the changes in the boiler operation, here this paper presents the application of an advanced, multiphase open-source code Arches, developed at the University of Utah for modeling pulverized-coal combustion using Large-Eddy Simulation (LES). Numerical simulations showed the effect on the boiler's working parameters e.g., heat-transfer rate, temperature distribution, species concentration, and NOx emission before and after proposed modifications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Ion kinetics and nonlinear saturation of current-driven instabilities relevant to hollow cathode plasmas

Ion kinetics and time evolution of bulk plasma properties in the nonlinear saturation regime of a collisionless current-driven instability are studied using a 1D Vlasov–Poisson simulation. In the simulations, the ratio of initial electron bulk velocity to initial electron thermal velocity, called the electron Mach number, ranges from 0.5 to 2.5, and electron-to-ion temperature ratio is 10. A significant population of backstreaming high-energy ions is observed when the initial electron Mach number is larger than or equal to 1.3, which agrees with previous literature indicating transition to the Buneman instability. The simulations suggest that the electrons trapped in large-amplitude waves result in a bi-directional ion acoustic wave, which generates a backward-propagating high-energy ion distribution. Here, a concise formula that describes the high-energy ion distribution and potential fluctuation amplitude are obtained as a function of initial electron Mach numbers. Sputtering rate calculations using the non-Maxwellian distributions for ions obtained from the simulation and Maxwellian ion distributions of temperatures ranging from 0.5 to 4.0 eV are compared, illustrating the potential contribution of kinetic effects on cathode erosion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Microstructure characterization of 316L deformed at high strain rates using EBSD

Specimens from split Hopkinson pressure bar experiments, at strain rates between ~ 1000–9000 s{sup −1} at room temperature and 500 °C, have been studied using electron backscatter diffraction. No significant differences in the microstructures were observed at different strain rates, but were observed for different strains and temperatures. Size distribution for subgrains with boundary misorientations > 2° can be described as a bimodal lognormal area distribution. The distributions were found to change due to deformation. Part of the distribution describing the large subgrains decreased while the distribution for the small subgrains increased. This is in accordance with deformation being heterogeneous and successively spreading into the undeformed part of individual grains. The variation of the average size for the small subgrain distribution varies with strain but not with strain rate in the tested interval. The mean free distance for dislocation slip, interpreted here as the average size of the distribution of small subgrains, displays a variation with plastic strain which is in accordance with the different stages in the stress-strain curves. The rate of deformation hardening in the linear hardening range is accurately calculated using the variation of the small subgrain size with strain. - Highlights: •Only changes in strain, not strain rate, gave differences in the microstructure. •A bimodal lognormal size distribution was found to describe the size distribution. •Variation of the subgrain fraction sizes agrees with models for heterogeneous slip. •Variation of subgrain size with strain describes part of the stress strain curve.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Distributed fiber sensing systems for 3D combustion temperature field monitoring in coal-fired boilers using optically generated acoustic waves (Final Report)

In this project, we have developed and tested three kinds of fiber optic sensing systems for real time monitoring of temperature variations within an industrial scale boiler furnace. The fiber optic sensing systems target spatial and temporal distributions of high temperature profiles in a boiler furnace in fossil power plants. The reconstructed temperature profile will provide critical input for the control mechanisms to optimize the combustion process. This temperature profile will address the essential problem for fossil power plants in achieving higher efficiency and fewer pollutant emissions. Acoustic pyrometer systems have been used to reconstruct temperature field of power plant boilers based on measuring TOF (times-of-flight) of sound waves along some straight paths in a 2D cross-section of the boiler. In this project, optically generated acoustic signals from a fiber optic sensing system have replaced the acoustic signals generated from an electrical transducer. A 3D reconstruction algorithm replaced the previous 2D model. In this project, three kinds of fiber optic sensing systems have been developed and tested. They are fiber optic sensing system I, fiber optic sensing system II (Distributed Sensing System I) and fiber optic sensing system III (Distributed Sensing System II). For fiber optic sensing system I, the fiber optic ultrasound generator acts as a signal generator. A microphone, hydrophone or other electronic devices serve as a signal receiver. In this system, there are one generator and one receiver. Distance test, water temperature test, air temperature test, air temperature reconstruction, and GE ISBF pilot test were performed by Fiber optic sensing system I. The fiber optic sensing system I successfully detected temperature in all these tests. We got 2D temperature reconstruction results by using the fiber optic sensing system I and it matched the reference data. The fiber optic sensing system I successfully survived in GE ISBF boiler environment (480 °F). For fiber optic sensing system II (Distributed Sensing System I), it is an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Fiber Bragg Grating (FBG) and Fabry-Perot (FP) sensor act as a signal receiver. In this system, there is one generator and one receiver. Aluminum plate temperature test, furnace high temperature test, and GE ISBF pilot test were performed by the fiber optic sensing system II. Fiber optic sensing system II successfully detected the temperature in all these tests. The fiber optic sensing system II successfully survived at up to 700 °C furnace environment and 320 °C GE ISBF boiler environment. For fiber optic sensing system III (Distributed Sensing System II), it is also an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Multiple FP fiber sensors act as signal receivers. In this system, there is one generator and three receivers. Three GE ISBF pilot tests were performed by fiber optic sensing system III. The fiber optic sensing system III survived in the cold flow tests in GE’s ISBF pilot test facility. However, we didn’t get high temperature data by using this system since the nanosecond laser issues. During the period of the project, test trials, data simulation and algorithm optimization was performed successfully. For real time temperature field construction, the sampling rate must be fast enough to capture the field variations. The technology of Code-division multiple access (CDMA) is well studied which could allow parallel multiplexing, even if signals overlap in time or frequencies. Moreover, it has been known that extending the length of signal significantly improves SNR. For acoustic signals, these multiplexing techniques have also been widely used, mainly for sonar and acoustic communications. The CDMA modulation technique has been proposed and studied to guarantee high network throughput, low channel access delay and low energy consumption. We have studied the temperature field reconstruction using Gaussian Radial Basis Functions (GRBF)-based approximation approach. Reconstruction of 3D temperature field using Neural Networks with measured TOF and known propagation paths is feasible. 2D and 3D temperature field reconstruction simulation results are achieved. The milestone status is shown in Table 1. We finished milestone 1-8 and milestone 10. For milestone 9, we did three pilot tests by using the fiber optic sensing system III (Distributed Sensing System II) at GE Power. However, due to the failure of the ns laser, we did not get the temperature results. We conducted some additional tasks that were not originally proposed: 1) We fabricated a fiber optic sensing system I and did a pilot test based on this system. 2) In the proposal, we proposed two pilot tests at GE Power. In reality, we finished at least seven pilot tests at GE Power. GE Power has made a lot of efforts for supporting the pilot tests. 3) We got a simulation results based on CDMA. In summary, most of the tasks have been accomplished. The outcome of this project removed a few barriers that hinder the achievement of the final product of the distributed sensing systems. With the successful accomplishment of this project, a prototype of the fiber optic sensing system can be fabricated to attract more interests from companies and other funding agencies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Machine-Learning-aided Approach for Predicting the Thermal Expansion Behaviors in Advanced Test Reactor Capsules (NURETH-20 full paper)

Instrumented experiments at test reactors are essential to deploying new advanced reactor systems. Designing new experiments and generating data on specific conditions require both time and cost investment. A high-fidelity model of the experiment environment can be created using finite element analysis software to support the actual experiments, but computation time is still a concern in applying outcomes to real-time usage (e.g., a digital twin). This research proposes a machine-learning-aided approach to temperature and displacement predictions, based on the thickness of the outer gas gap on the experimental capsule used for the in-pile demonstration of a novel thermal conductivity probe in the Advanced Test Reactor. The capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. There were gas gaps between the fuel and rodlet and between the inner and outer capsule. The learning data consisted of an experimental capsule’s radial distributions of temperature and displacement, as obtained from Abaqus and the physical features. For the first step, temperature was predicted using three positional parameters. Then the displacement was predicted using six different positional parameters. Each physical feature was normalized to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement in all cases involving interpolation and extrapolation. Also, data similarity enhancement increased the similarity between training and target data increasing the predictive accuracy of machine-learning models. In some cases of extrapolation, the accuracy of the machine-learning model showed limited performance, but still data similarity enhancement improved the accuracy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

A machine-learning-aided data recovery approach for predicting multi-material thermal behaviors in advanced test reactor capsules

Instrumented experiments conducted at test reactors are essential to the deployment of new advanced reactor systems. Designing new experiments and generating data on specific reactor conditions require significant investments in terms of both time and cost. Finite element analysis software can be used to create high-fidelity models of experiment environments in order to support the actual experiments, but computation time remains a concern in terms of applying outcomes to real-time usage of data (e.g., a digital twin [DT]). Here, the present research proposes a machine-learning (ML) aided approach to making temperature and displacement predictions based on the thickness of the outer gas gap on the experimental capsule used for in-pile demonstration of a novel new thermal conductivity probe in the Advanced Test Reactor (ATR). This capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. Gas gaps existed between the fuel and the rodlet, and between the inner and the outer capsule. The learning data pertained to an experimental capsule's radial distributions of temperature and displacement, as obtained based on Abaqus and the physical features. For the first step of ML sequence, the temperature was predicted using three positional parameters. Next, the displacement was predicted using seven additional parameters. Each physical feature was normalized in order to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement with the simulation results in all cases involving interpolation and extrapolation. Furthermore, data similarity enhancement increased the similarity between the training and the target data, thereby increasing the predictive accuracy of the ML models. In certain extrapolation cases involving limited original ML model accuracy, data similarity enhancement and data recovery was able to somewhat improve this accuracy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

The Pilatus unmanned aircraft system for lower atmospheric research

This study presents details of the University of Colorado (CU) “Pilatus” unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take-off weight of 25 kg, and it is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. In order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and its orientation to the upward-looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research-grade lower tropospheric measurement missions.

54 ENVIRONMENTAL SCIENCES↗