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DOE OSTI2021

Assimilation of citizen science data in snowpack modeling using a new snow data set: Community Snow Observations

A physically based snowpack evolution and redistribution model was used to test the effectiveness of assimilating crowd-sourced snow depth measurements collected by citizen scientists. The Community Snow Observations project gathers, stores, and distributes measurements of snow depth recorded by recreational users and snow professionals in high mountain environments. These citizen science measurements are valuable since they come from terrain that is relatively undersampled and can offer in situ snow information in locations where snow information is sparse or nonexistent. The present study investigates (1) the improvements to model performance when citizen science measurements are assimilated, and (2) the number of measurements necessary to obtain those improvements. Model performance is assessed by comparing time series of observed (snow pillow) and modeled snow water equivalent values, by comparing spatially distributed maps of observed (remotely sensed) and modeled snow depth, and by comparing fieldwork results from within the study area. The results demonstrate that few citizen science measurements are needed to obtain improvements in model performance, and these improvements are found in 62 % to 78 % of the ensemble simulations, depending on the model year. Model estimations of total water volume from a subregion of the study area also demonstrate improvements in accuracy after CSO measurements have been assimilated. These results suggest that even modest measurement efforts by citizen scientists have the potential to improve efforts to model snowpack processes in high mountain environments, with implications for water resource management and process-based snow modeling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Analytical closure to the spatially-filtered Euler equations for shock-dominated flows

To ensure numerical stability in the vicinity of shocks, a variety of methods have been used, including shock-capturing schemes such as weighted essentially non-oscillatory schemes, as well as the addition of artificial diffusivities to the governing equations. Centered finite difference schemes are often avoided near discontinuities due to the tendency for significant oscillations. However, such schemes have desirable conservation properties compared to many shock-capturing schemes. The objective of this work is to derive all necessary viscous/diffusion terms from first principles and then demonstrate the performance of these analytical terms within a centered differencing framework. The physical Euler equations are spatially-filtered with a Gaussian-like filter. Sub-filter scale (SFS) terms arise in the momentum and energy equations. Analytical closure is provided for each of them by leveraging the jump conditions for a shock. No SFS terms are present in the continuity or species equations. Here, this approach is tested for several problems involving shocks in one and two dimensions. Implemented within a centered difference code, the SFS terms perform well for a range of flow conditions without introducing excessive diffusion.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2001

Separating Spatial and Temporal Variations of the Aurora Using Two Nearly Colocated Satellites

This final report describes the efforts accomplished during the grant's period of performance, covering the period of 1 May 1997 to 30 April 2001, of a NASA Supporting Research and Technology Program grant under the Ionospheric, Thermospheric, and Mesospheric Physics component of the Sun-Earth Connections program. We have met and exceeded the goals set forth in the proposed research objectives. Referred publications have appeared in the scientific literature and several others are in the review process. In addition, numerous invited and contributed presentations of these studies were presented at national and international meetings during the performance period. One graduate student completed his PhD and won two AGU Best Student Paper awards based on research funded by this grant. These studies are summarized below. The science goal delineated in the initial proposal was "to systematically explore the temporal and spatial characteristics of the aurora in a way heretofore impossible, using data from two coplanar DMSP spacecraft." We accomplished this goal through a series of related studies. One study used these unique data to establish the role of Ps6 waves in coupling between the magnetosphere and the auroral ionosphere (omega bands) during the recovery phase of a magnetic storm; the published paper demonstrated the causal relationships between geospace processes occurring in different regions and established a simple conceptual model based on the fortuitous constellation of observations. In the second string of papers, we used these data to explore velocity-dispersed ions (VDIS) in and near the cusp, to test region identification models, and to look at space/time structure of auroral precipitation. On the first topic, the unique DMSP data revealed a remarkable double VDIS with a latitudinal overlap. This could only be explained in terms of a unified reconnection geometry that builds on several earlier unrelated models. The paper outlining this discovery has drawn considerable attention from the community and is currently in press - it adds significantly to the debate over whether reconnection is study state versus bursty and patchy versus global. The second paper develops the model further by incorporating the electron signature - these ionospheric particle precipitation signatures reveal the presence of magnetospheric "fossilized" FTEs, demonstrating the power of ionospheric measurements as a remote diagnostic of magnetospheric processes. Finally, the general nature of aurora] stability and coherence and region identification by particle characteristics were fully explored in a final paper. We identify candidate mechanisms controlling coherence time scales and length scales and refine boundary region identification criteria. We also use the dual-DMSP observations to identify the open and closed LLBL region and related its significance to the generalized bursty, multiple x-line model developed in the first paper. All of these topics are chapters of Dr. Boudouridis' recently completed PhD thesis.

Spence, Harlan E.↗

DOE OSTI2026

Computational Thermal Hydraulics of a High-Performance Low-Enriched-Uranium Annular Target for HFIR Irradiation

Molybdenum-99 has historically been generated via isolation from fissioned highly enriched uranium (HEU) targets. Here, this isotope is in high demand due to its daily use across the world in radiopharmaceutical medical procedures. The primary objective of this work was to design and analyze an experimental target assembly containing one low-enriched-uranium (LEU) annular target for irradiation at the High Flux Isotope Reactor (HFIR). Efforts included incorporating spatially dependent energy sources from neutron and gamma interactions, quantifying thermal contact conductance at material interfaces, performing grid-independent studies, comparing turbulence models, and simulating various steady-state and transient scenarios relevant for irradiation qualification and eventual insertion. These models provide velocity, pressure, and temperature distributions in both space and time. Such results enable the selection of an appropriate irradiation location, fission rate density, and flow-limiting orifice size and demonstrate compliance with HFIR safety requirements such that insertion into the reactor can be approved. This analysis shows that across all scenarios, wetted surface temperatures remain below the coolant saturation temperature with no net vapor formation in the coolant. In every scenario, all components stay below 30% of the aluminum 6061 melting temperature. Computational fluid dynamics and system-level models predict peak target temperatures that agree within 4%, though the predicted axial location of the peak differs by about 10% of the heated length due to differences in flow development length. These results de-risk the irradiation of LEU (annular targets) and strengthen a domestic, HEU-independent 99 Mo supply by providing important fuel performance data to form the foundation for a robust licensing basis.

Molybdenum-99↗

DOE OSTI2021

PERSIANN-CCS-CDR, a 3-hourly 0.04° global precipitation climate data record for heavy precipitation studies

Accurate long-term global precipitation estimates, especially for heavy precipitation rates, at fine spatial and temporal resolutions is vital for a wide variety of climatological studies. Most of the available operational precipitation estimation datasets provide either high spatial resolution with short-term duration estimates or lower spatial resolution with long-term duration estimates. Furthermore, previous research has stressed that most of the available satellite-based precipitation products show poor performance for capturing extreme events at high temporal resolution. Therefore, there is a need for a precipitation product that reliably detects heavy precipitation rates with fine spatiotemporal resolution and a longer period of record. Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System-Climate Data Record (PERSIANN-CCS-CDR) is designed to address these limitations. This dataset provides precipitation estimates at 0.04° spatial and 3-hourly temporal resolutions from 1983 to present over the global domain of 60°S to 60°N. Evaluations of PERSIANN-CCS-CDR and PERSIANN-CDR against gauge and radar observations show the better performance of PERSIANN-CCS-CDR in representing the spatiotemporal resolution, magnitude, and spatial distribution patterns of precipitation, especially for extreme events.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Importance of incorporating spatial and temporal variability of biomass yield and quality in bioenergy supply chain

Abstract Biofuels made from biomass and waste residues will largely contribute to United States’ 2050 decarbonization goal in the aviation sector. While cellulosic biofuels have the potential fuel performance equivalent to petroleum-based jet fuel, the biofuel industry needs to overcome the supply chain barrier caused by temporal and spatial variability of biomass yield and quality. This study highlights the importance of incorporating spatial and temporal variability during biomass supply chain planning via optimization modeling that incorporates 10 years of drought index data, a primary factor contributing to yield and quality variability. The results imply that the cost of delivering biomass to biorefinery may be significantly underestimated if the multi-year temporal and spatial variation in biomass yield and quality is not captured. For long term sustainable biorefinery operations, the industry should optimize supply chain strategy by studying the variability of yield and quality of biomass in their supply sheds.

09 BIOMASS FUELS↗

NASA NTRS1994

On-Orbit Thermal Performance of a Submillimeter Telescope Primary Reflector Panel

A detailed thermal analysis has been performed for a panel of a segmented primary mirror which is closest to the high side of the telescope sunshade. This panel was selected because the spatial temperature distribution was expected to be the worst. The JPL90-10 primary reflector panel configuration was investigated because of its superior figure error performance in ground-based testing.

SMILS↗

DOE OSTI2018

Coupled Approximation of U.S. Driving Speed and Volume Statistics Using Spatial Conflation and Temporal Disaggregation

The advent of mobile devices with embedded global positioning systems has allowed commercial providers of real-time traffic data to develop highly accurate estimates of network-level vehicle speeds. Traffic speed data have far outpaced the availability and accuracy of real-time traffic volume information. Limited to a relatively small number of permanent and temporary traffic counters in any city, traffic volumes typically only cover a handful of roadways with inconsistent temporal resolution. This work addressed this data gap by coupling a commercial dataset of typical traffic speeds (by roadway and time of week) from TomTom to the U.S. FHWA's Highway Performance Monitoring System database of annual average daily traffic (AADT) counts by roadway. This work is technically novel in its solution for establishing a national crosswalk between independent network geometries using spatial conflation and big data techniques. The resulting product is a national dataset providing traffic speed and volume estimates under typical conditions for all U.S. roadways with AADT values.

30 DIRECT ENERGY CONVERSION↗

NASA NTRSDate not supplied

Analytical and Experimental Demonstration of an Alternate Mixing Performance Metric for High-Speed Fuel Mixing Studies

To experimentally assess the fuel/air mixing performance of high-speed fuel injectors, one-dimensional metrics that quantify the degree of mixing completeness downstream of the fuel injection location are required. The most accurate assessment of mixing performance is achieved with the mixing efficiency parameter. In order to experimentally determine the mixing efficiency parameter, the spatial distributions of both mass flux and fuel mass fraction must be measured. In-stream gas sampling techniques are commonly used to measure the fuel mass fraction distribution; however, the mass flux distribution is not easily determined because it requires the measurement of three independent aerothermodynamic variables in addition to the gas composition. Therefore, to experimentally determine the mixing efficiency parameter, the spatial distributions of four independent properties must be measured, with each property generally requiring its own unique probe. Because of this difficulty, it is commonly assumed that alternate metrics, which rely solely on the fuel distribution, are good indicators of mixing performance. However, since these alternate metrics do not provide a mass flux-weighted measure of mixing completeness, they can lead to incorrect conclusions being drawn about the mixing performance of the studied fuel injector configuration. Recognizing this shortcoming, this work proposes two new alternate mixing performance metrics that are easier to obtain than the mixing efficiency parameter. The analytical development of the new metrics, as well as their application to relevant CFD and experimental data of high-speed fuel injector configurations, is presented in this work. For two different experiments, the new metrics are shown to provide an excellent representation of the true mass flux-weighted mixing performance, unlike the traditionally-used alternatives. The results presented herein suggest that the new metrics can serve as accurate surrogates for mixing efficiency in future high-speed fuel/air mixing studies.

Cody R Ground↗

DOE OSTI2018

A New Approach for Short-Term Solar Radiation Forecasting Using the Estimation of Cloud Fraction and Cloud Albedo

Solar generation is an increasing part of the energy portfolio in the United States. An accurate forecast of the available solar resource and power is essential to managing the electric grid, market operations, and reducing the cost of solar energy. High-frequency forecasts of solar radiation in intra-hour horizons is important for real-time electric power system energy management, especially at the distribution level. Conventional Numerical Weather Prediction models perform poorly in intra-hour, high-frequency forecasts because of the limits on real-time computing, spatial resolution, and infrequent availability of observations. Although a number of alternative technologies, e.g., time-series analysis and machine learning, have been used to fill this gap, the smart persistence model is among the top-performing models in short-term forecasting and therefore often serves as the baseline to evaluate other forecasting models. Although the smart persistence model often serves as the baseline model in these intra-hour forecasts, obvious uncertainties exist in the current smart persistence model: (1) clear-sky index does not respond to the variation of the solar incident angle when cloud conditions are persistent within the forecast horizon, and (2) cloud coverage is inherently persistent though it is constrained by cloud advection. In this study, we developed a Physics-Based Smart Persistence Model for Intra-Hour Solar Forecasting (PSPI) that integrates cloudy property estimation, a radiative transfer model, and cloud fraction forecasts to improve the performance of the smart persistence model. Compared to the smart persistence model, PSPI does not require additional observations of various atmospheric parameters past global horizontal irradiance, but it is customizable because additional observations, if available, can be ingested to further improve the forecast. Our results show that the PSPI outperforms the persistence and smart persistence model on 5-minute, 15-minute, and 30-minute forecast horizons. The software package of PSPI is flexible to users' needs and provides low computational time to run at site-specific locations across the continental United States.

14 SOLAR ENERGY↗

NASA NTRS1987

The performance of a multistep proportional counter for use in X-ray astronomy

The addition of a parallel field preamplification region has been shown to dramatically improve the performance of a standard multiwire proportional counter, permitting high overall gas gains to be achieved, a prerequisite for good spatial resolution, without in any way compromising energy resolution. The resulting device, known as a multistep detector, has been tested over a wide range of operating conditions and fill gas mixtures. Results are presented here detailing the performance available with argon and xenon as the principal gases, these being of particular relevance to X-ray astronomy.

Ramsey, B. D.↗

DOE OSTI2019

Applying the Aboveground-Belowground Interaction Concept in Agriculture: Spatio-Temporal Scales Matter

Interactions between aboveground and belowground organisms are important drivers of plant growth and performance in natural ecosystems. Making practical use of such above-belowground biotic interactions offers important opportunities for enhancing the sustainability of agriculture, as it could favor crop growth, nutrient supply, and defense against biotic and abiotic stresses. However, the operation of above- and belowground organisms at different spatial and temporal scales provides important challenges for application in agriculture. Aboveground organisms, such as herbivores and pollinators, operate at spatial scales that exceed individual fields and are highly variable in abundance within growing seasons. In contrast, pathogenic, symbiotic, and decomposer soil biota operate at more localized spatial scales from individual plants to patches of square meters, however, they generate legacy effects on plant performance that may last from single to multiple years. The challenge is to promote pollinators and suppress pests at the landscape and field scale, while creating positive legacy effects of local plant-soil interactions for next generations of plants. Here, we explore the possibilities to improve utilization of above-belowground interactions in agro-ecosystems by considering spatio-temporal scales at which aboveground and belowground organisms operate. We identified that successful integration of above-belowground biotic interactions initially requires developing crop rotations and intercropping systems that create positive local soil legacy effects for neighboring as well subsequent crops. These configurations may then be used as building blocks to design landscapes that accommodate beneficial aboveground communities with respect to their required resources. For successful adoption of above-belowground interactions in agriculture there is a need for context-specific solutions, as well as sound socio-economic embedding.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1976

Analytical and experimental studies of an optimum multisegment phased liner noise suppression concept

Results are presented from detailed analytical studies made to define methods for obtaining improved multisegment lining performance by taking advantage of relative placement of each lining segment. Properly phased liner segments reflect and spatially redistribute the incident acoustic energy and thus provide additional attenuation. A mathematical model was developed for rectangular ducts with uniform mean flow. Segmented acoustic fields were represented by duct eigenfunction expansions, and mode-matching was used to ensure continuity of the total field. Parametric studies were performed to identify attenuation mechanisms and define preliminary liner configurations. An optimization procedure was used to determine optimum liner impedance values for a given total lining length, Mach number, and incident modal distribution. Optimal segmented liners are presented and it is shown that, provided the sound source is well-defined and flow environment is known, conventional infinite duct optimum attenuation rates can be improved. To confirm these results, an experimental program was conducted in a laboratory test facility. The measured data are presented in the form of analytical-experimental correlations. Excellent agreement between theory and experiment verifies and substantiates the analytical prediction techniques. The results indicate that phased liners may be of immediate benefit in the development of improved aircraft exhaust duct noise suppressors.

Sawdy, D. T.↗

NASA NTRSDate not supplied

Numerical Study of Combustor-Turbine Interactions Considering a Two-Stage High-Pressure Turbine

In this study, preliminary results are presented from the Open National Combustion Code (OpenNCC) applied to the two-stage high-pressure turbine (HTP) from the energy efficient engine (E3) program. Although the combustor is designed for efficient fuel–air mixing and a relatively uniform exit temperature profile, temporal and spatial variation in combustor exit conditions inevitably lead to hot-streaks in the HPT. These hot streaks can cause local hot spots on the HPT blade surfaces that reduce blade life. To improve understanding of these effects and the overall design of combustor and HPT, we are developing a fully-coupled combustor-turbine computational fluid dynamics (CFD) capability. Previous work has simulated the E3 combustor at the simulated Sea-Level Take-off (SLTO) condition (P41 = 2.4 [atm]) with and without the first-stage HPT stator included. This work addresses HPT simulations using inflow conditions based on previous simulation results of the E3 combustor, as well as investigating the effects of spatial and temporal temperature non-uniformity of the combustor-exit flow on the HPT performance for a more realistic SLTO (P41 = 27.4 [atm])). First, we analyze existing results from the combustor and the HPT 1st-stage stator simulation, where the unsteady hot gas coming out of the combustor exit travels between the stationary stators and then directly exits the computational domain (i.e., no effect from the rotors). Second, we simulate the HPT including the 1st and 2nd stage stators and rotors with the time-averaged, spatially-nonuniform inflow to the HPT taken from the combustor (with HPT 1st-stage stators) solution. Differences in simulations results for the flow field in the 1st-stage stator region are presented. The results of these two simulations (combustor and HPT simulated in a sequential manner) will be compared to a fully-coupled EEE combustor/HPT simulation to understand the impacts of fully-coupled simulations on combustor and HPT performance for two different operating conditions.

LES↗

NASA NTRS2012

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

Tarabalka, Y.↗

NASA NTRSDate not supplied

Numerical Study of Combustor-Turbine Interactions Considering a Two-Stage High-Pressure Turbine

In this study, preliminary results are presented from the Open National Combustion Code (OpenNCC) applied to the two-stage high-pressure turbine (HTP) from the energy efficient engine (E3) program. Although the combustor is designed for efficient fuel–air mixing and a relatively uniform exit temperature profile, temporal and spatial variation in combustor exit conditions inevitably lead to hot-streaks in the HPT. These hot streaks can cause local hot spots on the HPT blade surfaces that reduce blade life. To improve understanding of these effects and the overall design of combustor and HPT, we are developing a fully-coupled combustor-turbine computational fluid dynamics (CFD) capability. Previous work has simulated the E^3 combustor at the simulated Sea-Level Take-off (SLTO) condition (P(41) = 2.4 [atm]) with and without the first-stage HPT stator included. This work addresses HPT simulations using inflow conditions based on previous simulation results of the E^3 combustor, as well as investigating the effects of spatial and temporal temperature non-uniformity of the combustor-exit flow on the HPT performance for a more realistic SLTO (P(41) = 27.4 [atm])). First, we analyze existing results from the combustor and the HPT 1st-stage stator simulation, where the unsteady hot gas coming out of the combustor exit travels between the stationary stators and then directly exits the computational domain (i.e., no effect from the rotors). Second, we simulate the HPT including the 1st and 2nd stage stators and rotors with the time-averaged, spatially-nonuniform inflow to the HPT taken from the combustor (with HPT 1st-stage stators) solution. Differences in simulations results for the flow field in the 1st-stage stator region are presented. The results of these two simulations (combustor and HPT simulated in a sequential manner) will be compared to a fully-coupled EEE combustor/HPT simulation to understand the impacts of fully-coupled simulations on combustor and HPT performance for two different operating conditions.

LES↗

DOE OSTI2018

Long-term nitrogen dioxide exposure assessment using back-extrapolation of satellite-based land-use regression models for Australia

Highlights: • We assessed how well a year-2006 satellite-based LUR model captures historical NO{sub 2}. • We used three methods to estimate annual mean NO{sub 2} during 1990–2005. • We measured their performance using standard LUR validation techniques. • Back-extrapolated 2006 levels captured up to 76% of spatial variability (90–05). Assessing historical exposure to air pollution in epidemiological studies is often problematic because of limited spatial and temporal measurement coverage. Several methods for modelling historical exposures have been described, including land-use regression (LUR). Satellite-based LUR is a recent technique that seeks to improve predictive ability and spatial coverage of traditional LUR models by using satellite observations of pollutants as inputs to LUR. Few studies have explored its validity for assessing historical exposures, reflecting the absence of historical observations from popular satellite platforms like Aura (launched mid-2004). We investigated whether contemporary satellite-based LUR models for Australia, developed longitudinally for 2006–2011, could capture nitrogen dioxide (NO{sub 2}) concentrations during 1990–2005 at 89 sites around the country. We assessed three methods to back-extrapolate year-2006 NO{sub 2} predictions: (1) ‘do nothing’ (i.e., use the year-2006 estimates directly, for prior years); (2) change the independent variable ‘year’ in our LUR models to match the years of interest (i.e., assume a linear trend prior to year-2006, following national average patterns in 2006–2011), and; (3) adjust year-2006 predictions using selected historical measurements. We evaluated prediction error and bias, and the correlation and absolute agreement of measurements and predictions using R{sup 2} and mean-square error R{sup 2} (MSE-R{sup 2}), respectively. We found that changing the year variable led to best performance; predictions captured between 41% (1991; MSE-R{sup 2} = 31%) and 80% (2003; MSE-R{sup 2} = 78%) of spatial variability in NO{sub 2} in a given year, and 76% (MSE-R{sup 2} = 72%) averaged over 1990–2005. We conclude that simple methods for back-extrapolating prior to year-2006 yield valid historical NO{sub 2} estimates for Australia during 1990–2005. These results suggest that for the time scales considered here, satellite-based LUR has a potential role to play in long-term exposure assessment, even in the absence of historical predictor data.

54 ENVIRONMENTAL SCIENCES↗

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↗