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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Parametrized process characterization with reduced resource requirements

Quantum process tomography (QPT) is a powerful tool to characterize quantum operations, but it requires considerable resources, making it impractical for more than two-qubit systems. This study proposes an alternative approach that requires significantly fewer resources for unitary process characterization with a built-in method for state preparation and measurement error mitigation. By measuring the quantum process as rotated through the X and Y axes on the Bloch sphere, we can acquire enough information to reconstruct the quantum process matrix χ and measure its fidelity. We test the algorithm's performance against standard QPT using simulated and physical experiments on several IBM quantum processors and compare the resulting process matrices. We demonstrate with numerical experiments that the method can improve gate fidelity via a noise reduction in the imaginary part of the process matrix, along with a stark decrease in the number of experiments needed to perform the characterization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Edge localized mode characteristics and divertor heat flux during stationary and transient phase for CFETR hybrid scenario

The study of edge localized mode (ELM) behavior, stationary heat flux and transient heat flux during the ELM crash phase is performed for a China Fusion Engineering Test Reactor (CFETR) 1 GW hybrid mode operation scenario ($R$ = 7.2 m, ${B_{\text{T}}}$ = 6.5 T, ${I_{\text{p}}}$ = 13.78 MA). Modeling and simulation start with a scenario obtained by multi-code integrated modeling on the one modeling framework for integrated tasks framework. Linear stability and nonlinear simulations of ELM dynamics are carried out using the BOUT++ six-field reduced magnetohydrodynamic module, which show a much smaller ELM energy loss (Δ ELM ~ 0.13%) compared to that of a Type-I ELM. Parametric analysis of the weak linear growth rate and small ELM energy loss characteristics shed light on physics corresponding to a grassy ELM regime for CFETR 1 GW hybrid scenario. The transient heat flux on the divertor target during this small ELM phase is investigated using BOUT++. Here we found that upstream radial transport in the scrape-off-layer (SOL) induced by small ELMs is weak, which keeps it in the drift-dominated region. However, the heat flux width is still broadened to ${\lambda _{\text{q}}}$ = 4.64 mm by the increase of separatrix temperature during ELM nonlinear evolution. The impact of transient peak heat load and ELM energy fluence on tungsten melting and net erosion rate of divertor target is evaluated for the first-time using physics-based transport that connects the pedestal with the SOL. Energy fluence caused by a single ELM pulse is below the tungsten melting limit, while tungsten erosion would exceed the material requirements. We conclude that external mitigation methods, such as divertor detachment and advanced divertor geometry are likely needed for the steady state operation of CFETR.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Room Temperature Quasi-static Characterization and Constitutive Model Parametrization of Flexible Polyurethane Foams of Different Densities Loaded in Different Orientations

This report describes the efforts to characterize and model General Plastics TF6070 and EF4000 flexible polyurethane foams under room temperature, large deformation quasi-static cyclic mechanical loading conditions. Densities from three to fifteen pound per cubic foot (PCF) are examined, which correspond to relative densities of approximately 4 to 20%. These foams are open cell structured and flexible at room temperature with a glass transition transition less than -30°C, and they fully recover their original shape when unloaded (at room temperature). Uniaxial compression tests were conducted with accompanying lateral image series for Digital Image Correlation (DIC) analysis with the goal of extracting transverse strain responses. Due to difficulties with DIC analysis at large strains, lateral strains were instead extracted for each test via edge tracking. The experimental results exhibit a nonlinear elastic response and anisotropic material behavior (particularly for the lower densities). Some hysteresis is observed that is different between the first and subsequent cycles of deformation indicating both a small degree of permanent damage (reduced stiffness during reloading) and viscoelasticity. These inelastic mechanisms are not considered in the modeling and calibration in this report. This work considers only the rate independent, room temperature foam behavior. Individual foam densities were calibrated for loading in two directions, parallel and perpendicular to the foam bubble rise direction, since the mechanical behavior is different in these two directions. The Flex Foam constitutive model was used for all parameterizations despite the fact that the model is isotropic. A review of the constitutive model is given as well as necessary data reduction procedures to parameterize it for each foam density and orientation are discussed. Finally, two different parameterizations are developed that take the undeformed foam density as an input that span all densities considered. These two parameterized models represent foams loaded in the rise and transverse directions respectively. We summarize the assumptions and limitations of the parameterizations provided in this report to guide analysis choices with them. All parameterizations presented herein have the following traits, room temperature, rate independent, damage-free, and non-dissipative . Isotropy (even if they are representing anisotropic data). Supplied Sierra Solid Mechanics Flex Foam Model Inputs are in units: pounds, inches, Celsius, and seconds

36 MATERIALS SCIENCE↗
DOE OSTI2022

Stable and unstable supersonic stagnation of an axisymmetric rotating magnetized plasma

The Naval Research Laboratory ‘Mag Noh problem’, described in this paper, is a self-similar magnetized implosion flow, which contains a fast magnetohydrodynamic (MHD) outward propagating shock of constant velocity. We generalize the classic Noh ( OSTI Tech. Rep. 577058, 1983) problem to include azimuthal and axial magnetic fields as well as rotation. Our family of ideal MHD solutions is five parametric, each solution having its own self-similarity index, gas gamma, magnetization, the ratio of axial to the azimuthal field and rotation. While the classic Noh problem must have a supersonic implosion velocity to create a shock, our solutions have an interesting three-parametric special case with zero initial velocity in which magnetic tension, instead of implosion flow, creates the shock at $t=0+$ . Our self-similar solutions are indeed realized when we solve the initial value MHD problem with the finite volume MHD code Athena. We numerically investigated the stability of these solutions and found both stable and unstable regions in parameter space. Stable solutions can be used to test the accuracy of numerical codes. Unstable solutions have also been widely used to test how codes reproduce linear growth, transition to turbulence and the practically important effects of mixing. Now we offer a family of unstable solutions featuring all three elements relevant to magnetically driven implosions: convergent flow, magnetic field and a shock wave.

Mechanics↗
DOE OSTI2022

Koopman-based Differentiable Predictive Control for the Dynamics-Aware Economic Dispatch Problem

The dynamics-aware economic dispatch (DED) problem embeds low-level generator dynamics and operational constraints to enable near real-time scheduling of generation units in a power network. DED produces a more dynamic supervisory control policy than traditional economic dispatch (T-ED) that reduces overall generation costs. However, the incorporation of differential equations that govern the system dynamics makes DED an optimization problem that is computationally prohibitive to solve. In this work, we present a new data-driven approach based on differentiable programming to efficiently obtain offline parametric solutions to the underlying DED problem. In particular, we employ the recently proposed differentiable predictive control (DPC) for offline learning of explicit neural control policies based on identified Koopman operator (KO) model of the system dynamics. We demonstrate the high solution quality and five orders of magnitude computational-time savings of the DPC method over the original optimization-based DED approach on a 9-bus test power grid network.

King, Ethan↗
DOE OSTI2020

The Role of Subsurface Flow on Evapotranspiration: A Global Sensitivity Analysis

Abstract Water resources are impacted by water‐energy balance fluxes at the land surface, most notably evapotranspiration ( ET ), the largest component of surface energy balance. While integrated hydrologic models show promise in quantifying the nonlinear dynamics at this interface, the model results are plagued by parametric uncertainties. Given the high computational demand of running multiple parameter spaces of these models, little is known about how these uncertainties propagate into land surface processes. In this work, we perform a global sensitivity analysis by computing Sobol and AMAE indices using a surrogate model constructed with a polynomial chaos expansion to assess the impacts of the subsurface physical properties on ET . We do so by modeling a semisynthetic test case. Our results show that the effects of vertical hydraulic conductivity, porosity, and the water retention curve parameter Van Genuchten α mainly control ET . However, we note that while evaporation ( E ) shows behavior similar to the ET with high sensitivity to the parameters controlling the flow in the unsaturated zone, transpiration ( T ) is very sensitive to the saturated zone parameters and groundwater flow, especially during periods without rain. Our results also show that heterogeneities in land cover impact the flow in the saturated zone. Furthermore, our work demonstrates that reduced‐order models can be developed to make integrated models more accessible for rigorous sensitivity analyses and calibration purposes.

Maina, Fadji Zaouna↗
DOE OSTI2022

SC Wall-to-RC Basemat Over-Strength Connection: Behavior and Design

This paper presents results from experimental and analytical investigations conducted to evaluate the lateral load behavior and capacity of steel-plate composite (SC) wall-to-reinforced concrete (RC) basemat connections. Two SC wall-to-reinforced concrete basemat connection specimens were tested. These SC wall specimens had a height-to-length ratio of 0.6 and did not include boundary elements. The experimental results include the lateral force-displacement (V-Δ) responses of the specimens and observations of local damage such as steel plate local buckling and concrete crushing. 3D finite element models were developed and benchmarked using the experimental results. The benchmarked models were used to conduct analytical parametric studies, expand the database, and gain additional insights into the behavior of SC wall-to-RC basemat connections. The parameters included in analytical investigations were the wall aspect ratio (h/lw), reinforcement ratio (ρ), and wall thickness (T).

Kurt, Efe G.↗
DOE OSTI2021

Parametric Study of Used Nuclear Oxide Fuel Constituent Dissolution in Molten LiCl-KCl-UCl 3

Prior work identified dissolution of used nuclear oxide fuel constituents from a uranium oxide matrix into molten LiCl-KCl-UCl 3 at 500°C, prompting a subsequent series of three progressive studies (including an initial scoping study, an electrolytic dissolution study, and a chemical-seeded dissolution study) to further investigate associated parameters and mechanisms. Thermodynamic calculations were performed to identify possible reaction mechanisms and their propensities in used oxide fuel constituent dissolution. Used nuclear oxide fuels with varying preconditions from fast and thermal test reactors were separately immersed in the subject salt system to assess fuel constituent migration from the bulk fuel matrix to the salt phase in an initial scoping study. Dissolution of expected fuel constituents, including alkali, alkaline earth, lanthanide, and transuranium oxides, into the chloride salt phase varied widely, ranging from 12% to 99% in the initial study. Uranium isotope blending between the salt phase and bulk fuel matrix was also observed, which was attributed to reducing conditions in the fuel matrix. Electrolytic and chemical-seeded dissolution studies were subsequently performed to effect reducing conditions in the fuel. Other parameters, including temperature (at 500°C, 650°C, 725°C, and 800°C) and uranium trichloride concentrations (at 6, 9, and 19 wt% uranium), were investigated in the latter two studies, resulting in fuel constituent dissolution above 90%. Extents of dissolution were based on initial and final fuel constituent concentrations in the oxide fuels following operations in the salt and subsequent removal of the salt via distillation. Finally, in this series of progressive studies, oxide fuel preconditioning and in situ reducing conditions, along with elevated temperature and uranium trichloride concentrations, were the primary parameters promoting used nuclear oxide fuel constituent dissolution in accordance with identified reaction mechanisms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

A systematic approach to resolve high impedance of multifunctional energy storage composites

Previous work has proposed and characterized the structural and electrical performance of Multifunctional Energy Storage Composite (MESC) structures: structural elements with embedded lithium-ion batteries which were developed by the Structures and Composite Laboratory (SACL) at Stanford University. This work conducts a comprehensive parametric study over the design variables in the manufacturing process to determine the root cause of increased DC impedance compared to commercial pouch cell batteries. Several MESC samples were assembled under various controlled environmental temperatures and pressures. The samples underwent Hybrid Peak Pulse Characterization (HPPC) to approximate the DC impedance as a function of state of charge (SOC). Failure limits of the battery with respect to assembly temperature and pressure were tested, and an MESC manufacturing simulation model was constructed in Abaqus to validate the manufacturing limits. Samples assembled without enough temperature or pressure failed due to a lack of structural integrity or hermetic seal. Conversely, samples which underwent elevated temperatures and pressures resulted in high DC impedance due to nonuniform electrolyte wetting. This work resolves the primary concern of MESC by achieving comparable DC impedance to commercial pouch cells of the same chemistry and testing procedure.

25 ENERGY STORAGE↗
DOE OSTI2024

Automating galaxy morphology classification using k -nearest neighbours and non-parametric statistics

ABSTRACT Morphology is a fundamental property of any galaxy population. It is a major indicator of the physical processes that drive galaxy evolution and in turn the evolution of the entire Universe. Historically, galaxy images were visually classified by trained experts. However, in the era of big data, more efficient techniques are required. In this work, we present a k-nearest neighbours based approach that utilizes non-parametric morphological quantities to classify galaxy morphology in Sloan Digital Sky Survey images. Most previous studies used only a handful of morphological parameters to identify galaxy types. In contrast, we explore 1023 morphological spaces (defined by up to 10 non-parametric statistics) to find the best combination of morphological parameters. Additionally, while most previous studies broadly classified galaxies into early types and late types or ellipticals, spirals, and irregular galaxies, we classify galaxies into 11 morphological types with an average accuracy of ${\sim} 80\!-\!90 \, {{\rm per\, cent}}$ per T-type. Our method is simple, easy to implement, and is robust to varying sizes and compositions of the training and test samples. Preliminary results on the performance of our technique on deeper images from the Hyper Suprime-Cam Subaru Strategic Survey reveal that an extension of our method to modern surveys with better imaging capabilities might be possible.

Mukundan, Kavya↗
DOE OSTI2024

Hawai‘i Supernova Flows: a peculiar velocity survey using over a Thousand Supernovae in the near-infrared

ABSTRACT We introduce the Hawai‘i Supernova Flows project and present summary statistics of the first 1217 astronomical transients observed, 668 of which are spectroscopically classified Type Ia Supernovae (SNe Ia). Our project is designed to obtain systematics-limited distances to SNe Ia while consuming minimal dedicated observational resources. To date, we have performed almost 5000 near-infrared (NIR) observations of astronomical transients and have obtained spectra for over 200 host galaxies lacking published spectroscopic redshifts. In this survey paper, we describe the methodology used to select targets, collect/reduce data, calculate distances, and perform quality cuts. We compare our methods to those used in similar studies, finding general agreement or mild improvement. Our summary statistics include various parametrizations of dispersion in the Hubble diagrams produced using fits to several commonly used SN Ia models. We find the lowest dispersions using the SNooPy package’s EBV_model2, with a root mean square deviation of 0.165 mag and a normalized median absolute deviation of 0.123 mag. The full utility of the Hawai‘i Supernova Flows data set far exceeds the analyses presented in this paper. Our photometry will provide a valuable test bed for models of SN Ia incorporating NIR data. Differential cosmological studies comparing optical samples and combined optical and NIR samples will have increased leverage for constraining chromatic effects like dust extinction. We invite the community to explore our data by making the light curves, fits, and host galaxy redshifts publicly accessible.

Do, Aaron (ORCID:0000000334297845)↗
DOE OSTI2024

THERMAL MODELING OF HANFORD CESIUM AND STRONTIUM CANISTERS DURING SIMULATED LOADING

A computational fluid dynamics (CFD) model was built to simulate planned testing of heater assemblies within a canister and overpack for the Hanford Lead Canister (HLC) project. The HLC is a canister storage system that will contain heaters to simulate the decay heat of nuclear material and provide the canister storage system with environmental conditions equivalent to the operating conditions on a dry storage pad. The HLC will be equipped with long-term data collection and monitoring systems to provide an early warning of corrosion, pitting, cracking, or other signs of canister degradation that might threaten the integrity of the containment boundary over the potentially long term of dry storage. An important part of the HLC development is to make pretest numerical predictions for the behavior of the heated canister during the simulated radiolytic decay heat testing, which simulates the dry storage system during loading operations. The simulated radiolytic decay heat test is planned for mid-2024 in a configuration that includes the heater assembly, overpack, and canister, but with the lids removed to allow loading cesium and strontium capsules into the canister. One of the goals of the test is to evaluate the thermal behavior of the canister and overpack assembly in the ambient air of the test facility, which will provide data critical to validating the thermal models and understanding how the HLC will perform as a system once deployed. To best approximate real-world conditions, the CFD model includes the full air volume of the mock-up truck bay the heated canister test will be performed in, enabling detailed investigation of how the heated canister affects airflow around it. Rigorous pre-deployment testing of the complete HLC cask and canister system is intended to be completed before the HLC is deployed in the 2028 timeframe. This study presents the pre-test temperature predictions of the simulated radiolytic decay heat test. A description of the heater assembly, canister, and overpack system is presented. The model was developed with the commercial CFD software STAR-CCM+. An uncertainty analysis was run with the CFD model to determine the uncertainty in the temperature predictions and provide a range over which the predicted temperatures are expected to vary. The uncertainty analysis was preformed by coupling STAR-CCM+ with the software Dakota, which provides advanced parametric analyses, including quantification of margins and uncertainty with computational models. This work is expected to provide insight into SNF canister behavior.

Carpenter-Graffy, Dina E.↗
DOE OSTI2020

Fast Computational Algorithms for Partial Differential Equations and Uncertainty Quantifications

This project concerned the construction, testing and analysis of computational algorithms for solving parameterized and stochastic partial differential equations. The study and understanding of equations of this type is of fundamental importance in numerous engineering and scientific applications. Examples include simulation of plasma dynamics in models of electric propulsion and nuclear fusion, simulation of multiphase flows, such as the flow of water, gas and oil in reservoirs, and structural analysis of the dependence of structures on materials. Parametrization is used in such settings when properties of the models such as viscosity of fluids or electric resistivity of materials are not precisely understood and instead are treated as random variables. The resulting solutions are themselves random, and having such solutions will enable engineers to use probabilistic methods to assess the likelihood of events, for example, whether a pollutant in a liquid will exceed a limit, and to use such analyses to develop ways to ensure positive outcomes. Construction of accurate (high resolution) computational solutions is expensive, requiring significant computer time and computational resources, and there is need to reduce computational cost to make simulation useful and effective. The aim of the project was to construct algorithms to efficiently compute surrogate solutions to parameterized problems to allow for efficient and accurate simulation. The technical approach used focused on two related strategies, based on rank-reduction methods and reduced-order models. These methods construct surrogate solutions of parameter-dependent models by projection or interpolation into low-dimensional approximation spaces. Cost savings are achieved if the low-dimensional spaces can be identified and constructed efficiently and if the resulting low-dimensional algebraic systems can be solved cheaply. Accomplishments include: Theoretical and empirical demonstration of the effectiveness of fast multigrid solution strategies for computing low-rank representations of parameter-dependent solutions to discrete partial differential equations, including the first proof establishing so-called textbook convergence properties for low-rank methods. Development of efficient solution algorithms for solving nonlinear parameter-dependent partial differential equations used in models of fluid dynamics. Developent of efficient algorithms for low-rank representation of solutions of time-dependent simulations of fluid dynamics using multi-dimensional tensor representations of solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Modeling occupancy-driven building loads for large and diversified building stocks through the use of parametric schedules

Building energy modeling provides a fundamental tool to assess the potential for energy efficiency to contribute to reducing world energy consumption and global emissions. Occupancy-related operations are a key source of uncertainty for building energy analysis, particularly for aggregated building stocks. At a district or city level, it is critical to estimate aggregated power load profiles for sizing power grid infrastructure, power plant capacity allocation, and energy efficiency measures. The stochastic nature of behavior-related operations complicates the creation of models that accurately capture building load profiles for entire building stocks. This research introduces a new methodology called parametric schedules to model occupancy-driven schedules for large and diverse building stocks. In contrast to computationally expensive methodologies proposed in the literature, our work does not use a recursive time-consuming step. Occupancy is estimated by the extrapolation of operation times directly from metered electric consumption data; occupancy-related schedules are stochastically assigned to each building model, guaranteeing diversity of operation times in the stock. Our procedure has been tested on a large, diversified data-set of 25,000 commercial buildings in Los Angeles, California. It proved to be able to adequately represent the stochastic schedules diversity of the stock and to refine the stock calibration process by 1%. This innovative approach represents a useful asset for utility companies, grid operators, urban planners, and balancing authorities, seeking to improve building stock modeling and better estimate the impact of energy conservation measures. – This work is part of a larger stock modeling tool called ComStock, which is under development by NREL.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Improving ideal MHD equilibrium accuracy with physics-informed neural networks

We present a novel approach to compute three-dimensional magnetohydrodynamic equilibria with isotropic pressure profiles and nested surfaces by parametrizing Fourier modes with artificial neural networks (NNs). The full nonlinear global force residual of single equilibria across the volume in real space is then minimized with first order optimizers and compared to equilibria computed by conventional solvers. Already, we observe competitive computational cost to arrive at the same minimum residuals computable with existing codes. With increased computational cost, lower minima of the residual are computable with the NNs than with any other tested solver, establishing a new lower bound for the force residual. We use minimally complex NNs, and we expect significant improvements for solving not only single equilibria with NNs, but also for creating NN models valid over continuous distributions of equilibria.

ideal magnetohydrodynamics↗
DOE OSTI2021

Multichannel deconvolution of vibrational signals: A state-space inverse filtering approach

Deconvolution of noisy measurements, especially when they are multichannel, has always been a challenging problem. The processing techniques developed range from simple Fourier methods to more sophisticated model-based parametric methodologies based on the underlying acoustics of the problem at hand. Methods relying on multichannel mean-squared error processors (Wiener filters) have evolved over long periods from the seminal efforts in seismic processing. However, when more is known about the acoustics, then model-based state-space techniques incorporating the underlying process physics can improve the processing significantly. The problems of interest are the vibrational response of tightly coupled acoustic test objects excited by an out-of-the-ordinary transient, potentially impairing their operational performance. Further, employing a multiple input/multiple output structural model of the test objects under investigation enables the development of an inverse filter by applying subspace identification techniques during initial calibration measurements. Feasibility applications based on a mass transport experiment and test object calibration test demonstrate the ability of the processor to extract the excitations successfully.

42 ENGINEERING↗
DOE OSTI2025

Q2 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q2: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis: $\circ$ Run CESOL with BOUT++/Hermes-3 and immersed boundary condition to directly map to wall: • Run BOUT++/Hermes-3 through the IPS workflow to find radial particle and energy diffusivities to match either the Eich or the physics-based scaling of the SOL heat flux width, and • Expand source of first wall heat flux to include charged particles, neutrals, and radiation from the core+edge. 2. Generate medium fidelity parametrized CAD: $\circ$ Develop the TRACER tool to read an existing CAD, regenerate the geometry based on vertex location and connectivity information, define vertex translation and parameters needed for scaling the CAD, and $\circ$ Utilize the FreeGS code to determine CAT PF coil placement, including minimizing the number of coils, coil current, and electromechanical stresses. 3. Utilize plasma loading for engineering analysis: $\circ$ Couple the plasma loading to input for OpenFOAM and demonstrate initial test of thermal analysis of CAT first wall loading with typical DCLL blanket component cooling boundary conditions. 4. Demonstrate nuclear analysis: $\circ$ Apply initial analysis of tritium transport in DCLL blanket by evaluating spatially resolved tritium generation rates, tritium diffusion and convection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Characterization of Temperature Heterogeneity in Utility-Scale Power Plant Boilers by Spatially Distributed Ultrasonic Measurements

In extreme environments, even hardened insertion sensors fail quickly. For such environments, we have developed an ultrasonic (US) method for measuring the spatial distribution of temperatures in solid materials and, specifically, across containments of extreme processes. By deploying US sensors in multiple locations, spatial heterogeneity in temperatures inside harsh environments may be characterized. In this note, we update our progress on testing the developed approach in an industrial setting and its performance in describing the temperature distribution inside a 500 MW (electrical) coalfired utility boiler of an electrical power generation plant. We use waveguides (WG) structured to contain echogenic features that produce a train of echoes in response to an excitation pulse. The time of flight between echoes encodes the information on the temperature distribution in the corresponding segment of the WG, which we reconstruct using its parametrization. Five waveguides were welded to the boiler’s heat exchange surface (waterwall) and different locations at the same boiler elevation and produced reliable US waveforms 18 months after the installation. For several weeks during the latest trial, we performed US measurements in five locations spanning half of the boiler’s 14-meter width. The measurements were acquired during regular operation, including load cycling to adjust for demand and intermittent contributions of renewable power sources, and during boiler shutdown for emergency maintenance and the subsequent restart. The interpretation of US waveforms by signal processing resulted in an accurate estimation of temperature distribution along the waveguides. We captured daily cyclical variations in demand-following load. Measurements performed in multiple locations revealed unexpected temperature variations across the boiler. We conclude that an array of developed sensors can provide responsive and spatial temperature measurements while maintaining functionality despite prolonged exposure to an extreme environment.

Walton, Kenneth↗