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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Perturbation-Based Diagnosis of False Data Injection Attack Using Distributed Energy Resources

Modern smart grid relies on various sensor measurements for its operational control. In a successful false data injection attack, the attacker manipulates the measurements from the grid sensors such that undetected errors are introduced into the estimates of the system parameters leading to catastrophic situations. This paper proposes a novel perturbation based false data injection attack detection mechanism that utilizes inverter based distributed energy resources (DERs) to create low magnitude perturbation signal in the distribution system voltage that is inconsequential to the normal grid operation. Two voltage sensitivity analysis based algorithms are designed to identify the optimal set of DERs that can create the voltage perturbation signal of desired magnitude. An analytical method of voltage sensitivity analysis is used to compute the magnitude of voltage perturbation signal at each node in a computationally efficient manner. Then, a detection mechanism is developed that checks for the presence of the perturbation sequence in each sensor measurement. A sensor measurement is deemed authentic if the voltage perturbation signal is present in the data. In case of sensor malfunction or cyber-attack, the perturbation signal will not be present in the measurement data. Performance of the proposed attack detection mechanism is validated via simulation of the IEEE 69 bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Observed and Imputed Volumetric Soil Water Content Timeseries for the New Mexico Elevation Gradient

Reliable soil water content (SWC) data are essential for understanding dryland ecosystem dynamics, but high-frequency SWC sensors often fail, creating gaps in critical datasets. To address this, we developed a Bayesian mixture model that imputes missing SWC using both linear interpolation and an ecosystem water balance model (SOILWAT2), tested across six AmeriFlux eddy covariance tower sites in the New Mexico Elevation Gradient, demonstrating its effectiveness in reconstructing SWC patterns while providing insights into the factors driving SWC variability. Daily volumetric soil water content (SWC) data are provided as csv-formatted spreadsheets for the six AmeriFlux sites (US-Seg, US-Ses, US-Wjs, US-Mpi, US-Vcp, and US-Vcs). For each site there is an observed SWC file (site_SWC_gapfill.csv) and a file that contains imputed SWC (imputed_SWC_site.csv). The observed SWC files contain temperature corrected sensor values, tower precipitation data, as well as outputs from SOILWAT2 simulations that were used to impute SWC. The imputed files contain the original observed SWC values and the imputed missing SWC values. When SWC was missing from the original data, the missing value was imputed based on the Bayesian imputation mixture model. The posterior mean of all imputed values is reported as "mean_X". When the observed SWC was NOT missing, mean_X = observed SWC value (original data). The standard deviation, 2.5th percentile and the 97.5th percentile for the imputed values are also reported in the imputed files. There are readme text files for each file type explaining the contents of each column.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Performance Demonstration of an Occupancy Sensor-enabled Integrated Solution for Commercial Buildings

Traditionally, a single-loop fixed-gain controller is applied to supply fan (SF) and cooling coil (CC) valve controls while a fixed-damper position control is applied to outdoor air (OA) damper control at air handling units (AHUs) in commercial buildings. With the increasing application of occupancy sensors, the information generated by occupancy sensors is applied to not only reduce the electricity loads from lighting and controllable plug loads, but also reset OA intake and minimum supply airflow setpoints. Meanwhile, these intermittent operation actions greatly elevate the dynamics of AHU systems, which may introduce unstable SF and CC valve operations and inaccurate OA flow control at AHUs and consequently degrade maximum energy efficiency gains. With virtual fan and valve flow meter technologies, two advanced controls, including cascade control and gain scheduling control, can be implemented on both the SF and CC valve, and an advanced control using a virtual OA flow meter can be implemented on OA damper integrated with occupancy sensors. The goal of this project is to demonstrate the savings, cost, and performance of an integrated solution that integrates the three advanced HVAC controls with occupancy sensors to allow accurate and stable AHU operations in real buildings. The project objectives are to: 1) develop and validate an advance SF control algorithm; 2) develop and validate an advanced CC valve control algorithm; 3) validate an algorithm to implement a virtual OA flow meter; and 4) demonstrate the savings, cost, and performance of the integrated solution in real buildings. The technical approaches are to: 1) select a test system at the University of Oklahoma; 2) develop and implement the algorithms of advanced SF and CC valve controls and validate the performance; 3) develop and implement the advanced OA control using a virtual OA flow meter and validate the performance; 4) demonstrate the savings, cost, and performance of the proposed integrated solution with and without three advanced HVAC controls; and 5) disseminate the project results through publications and presentations. For the SF control, both the gain scheduling and cascade controls can improve the fan energy performance by reducing the fan power during the transient period and the fan control performance at lower speeds by reducing fan speed variation. Moreover, the gain scheduling control provides a simple and low-cost solution and is recommended. The fan power savings can reach 30% in a transient period. For the CC valve control, the gain scheduling control can considerably reduce the supply air temperature oscillation range and frequency under both higher and lower load conditions and the control valve response is much more stable. As a result, the gain scheduling control is recommended. The projected pump energy consumption can be reduced by 68.5%. With the developed virtual OA flow meter, the OA can be accurately controlled at its setpoint, which is determined based on the actual number of occupants in the building provided by occupancy sensors. The RMSE of the proposed OA control is 15.9 L/s. The energy data shows that the fan power and CC cooling energy were significantly reduced. On the other hand, the energy savings majorly results from the occupancy sensors and the energy savings by the advanced HVAC controls is minimal because that the controllers in the test AHU were tuned with very slow response. An annual technical savings potential is estimated as 0.5 quads in the commercial sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Construction of genetic logic gates based on the T7 RNA polymerase expression system in Rhodococcus opacus PD630

Rhodococcus opacus PD630 (R. opacus) is a non-model, gram-positive bacterium which holds promise as a biological catalyst for the conversion of lignocellulosic biomass into value-added products. In particular, it demonstrates both a high tolerance for and an ability to consume inhibitory lignin-derived aromatics, generates large quantities of lipids, exhibits a relatively rapid growth rate, and has a growing genetic toolbox for engineering. Yet, the availability of genetic parts for tunable, high-activity gene expression is still limited in R. opacus. Moreover, genetic logic circuits for sophisticated gene regulation have never been demonstrated in Rhodococcus spp. To address these shortcomings, two inducible T7 RNA polymerase-based expression systems were implemented for the first time in R. opacus and applied to constructing AND and NAND genetic logic gates. Additionally, three IPTG-inducible promoters were created by inserting LacI binding sites into newly-characterized constitutive promoters. Furthermore, four novel aromatic sensors for 4-hydroxybenzoic acid, vanillic acid, sodium benzoate, and guaiacol were developed, expanding the gene expression toolbox. Lastly, the T7 RNA polymerase platform was combined with a synthetic IPTG-inducible promoter to create an IMPLY logic gate. Overall, this work represents the first demonstration of a heterologous RNA polymerase system and synthetic genetic logic in R. opacus, enabling complex and tunable gene regulation in this promising non-model host for bioproduction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

FY 2016 Site-Directed Research & Development Annual Report

As the Nevada National Security Site (NNSS) continues to evolve and transition its mission to a broader scope, significant challenges lie ahead that present unique opportunities for our research and development (R&D) enterprise. At the juncture, we are poised to create a different future investment strategy. Our decisions at the beginning of a new tri-decade span must be guided as expertly as possible given the greater complexity and multifaceted nature of our work.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Collaborative Research On Ecophysiological Controls on Amazonian Precipitation Seasonality And Variability

We developed and deployed a robust and accurate instrumentation package for measurement of solar induced chlorophyll fluorescence (SIF) from above a plant canopy. The sensor collects light from identical up and down facing hemispheric collectors. A fiber optic transmits the collected light (selected by a rotatable prism) to spectrometers located at the base of the tower. Spectra of the down welling and upwelling light were collected alternatively and stored for later analysis. SIF was retrieved by a spectral unmixing approach using high resolution spectra in the 730-760 nm band. Most other ground-based sensors base their analysis on O 2 -alpha band (760-780 nm) for SIF retrieval. We found that the former gave identical results when the atmosphere was clear, but the former was more stable in the cloudy conditions that often prevailed in the Amazon. The mechanical design and software developed for the system are available on request. The sensor was mounted near the top of an 80 m tower at K34 near Manaus in the Brazilian Amazon Forest. The sensor system proved weather-tight and functioned flawlessly over the time of deployment. Our experiment was cut short at 6 months by failure of air conditioning infrastructure at the tower. We found that SIF emitted by canopy was remarkably stable when scaled by the downwelling photosynthetically active radiation or the upwelling near infrared light. We detected a 3.4% increase in SIF over the course of the dry season. This finding is consistent with the observation that several trees in the field of view flushed new leaves in the dry season. We saw no evidence of drought stress or photo damage of the forest canopy during our study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring: Supporting Data

This dataset was used to assess the performance of a compression algorithm for Soil Deformation and Temperature Monitoring data. The development of this technology is presented in the article named time division duplex (TDD) "TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring" and published in Springer's Journal on Signal Processing Systems. [Time Division Duplex (TDD); Long Range (LoRa)]Field experiment data includes: 1) soil temperature measurements, 2) snow temperature data, 3) soil temperature and deformation data. In these files, the first column contains the time (UTC), followed by the sensor's battery voltage and temperature and acceleration values (X, Y, Z) in subsequent columns. The measurements were acquired every 15 minutes. Lists included for probe, datalogger, and packaging components. The two temperature data sets were acquired at a site at the East River Watershed, Colorado, while the temperature/deformation data were collected at the Teller Road (mile 27) site near Nome, Alaska. The package includes 8 comma-separated files (.csv) and one .pdf file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Methods for Continuously Resolving Spectral Shifts in Distributed Optical Fiber Sensors Irradiated to Extreme Neutron Fluence

Optical frequency domain reflectometry (OFDR) is a technique for interrogating distributed optical fiber sensors (DOFS) and involves correlating changes in the Rayleigh backscatter fingerprint for a fiber under test (FUT) with a reference measurement. Recently, under the WIRE-21 experiment sponsored by Nuclear Science User Facilities (NSUF) and performed at the High-Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL), silica optical fibers were irradiated to a fast neutron fluence of 1x10^21 n/cm^2/s at temperatures from 200--400 C. As in the cases of high-temperature and high-strain conditions, such high levels of neutron bombardment result in a highly dynamic RBS that evades analysis with conventional methods. This work describes the further development and application of graphical signal processing techniques applied to OFDR-based distributed optical fiber sensors specifically deployed in in-pile applications. While the signal processing techniques developed in this work are applied to DOFS in nuclear environments, they provide a general framework for the analysis of OFDR measurements and a tangible method to yield higher quality data, without imposing additional hardware requirements.

Sweeney, Dan↗
DOE OSTI2021

Effect of Image Classification Accuracy on Dasymetric Population Estimation

Dasymetric mapping involves the disaggregation of count data, usually relating to population/demographics, from census enumeration areas to smaller target zones with the aid of an ancillary layer related to population density. The ancillary layer is often a binary classification such as developed versus undeveloped, building versus non-building, and residential versus non-residential, in which one class is treated as populated and the other as unpopulated. While dasymetric mapping relies heavily on ancillary data, little research has been done to address the error in ancillary data and its effects on dasymetric mapping accuracy. This chapter reports our research effort to investigate the effect of image classification accuracy on dasymetric population estimates by developing a binomial classification of buildings from high-resolution remote sensor imagery. The classifier was systematically and iteratively manipulated to generate a series of outputs with variegated accuracy characteristics. Lastly, we generated a corresponding series of population estimates based on the mapped building area from each iteration to investigate the relationship between the accuracy of classification and population estimation.

McKee, Jacob↗
DOE OSTI2017

Energy savings potential from improved building controls for the US commercial building sector

The U.S. Department of Energy’s (DOE’s) Building Technologies Office (BTO) sponsored a study to determine the potential national savings achievable in the commercial building sector through widespread deployment of best practice controls, elimination of system and component faults, and use of better sensing. Detailed characterization of potential savings was one source of input to set research, development, and deployment (RD&D) goals in the field of building sensors and controls. DOE’s building energy simulation software, EnergyPlus, was employed to estimate the potential savings from 34 measures in 9 building types and across 16 climates representing almost 57% of commercial building sector energy consumption. In addition to estimating savings from individual measures, three packages of measures were created to estimate savings from the packages. These packages represented an 1) efficient building, 2) typical building, and 3) inefficient building. To scale the results from individual measures or a package to the national scale, building weights by building type and climate locations from the Energy Information Administration’s 2012 Commercial Building Energy Consumption Survey (CBECS) were used. The results showed significant potential for energy savings across all building types and climates. The total site potential savings from individual measures by building type and climate location ranged between 0% and 25%. The total site potential savings by building type aggregated across all climates (using the CBECS building weights) for each measure varied between 0% and 16%. The total site potential savings aggregated across all building types and climates for each measure varied between 0% and 11%. Some individual measures had negative savings because correcting underlying operational problems (e.g., inadequate ventilation) resulted in increased energy consumption. When combined into packages, the overall national savings potential is estimated to be 29%; seven of the nine building types were in the range of 23 to 29% and two exceeded 40%. The total potential national site savings in for each building type ranged between 95x106 GJ (0.09 Quadrillion British thermal units [Quads]; Large Hotels) to 222x106 GJ (0.21 Quads; Large Office, Hospital Administrative areas, and College/University), resulting in total site savings of 1,393x106 GJ (1.32 Quads) when the three packages are applied to the U.S. commercial buildings stock. Using the source (or primary) energy conversion factors of 1.05 for natural gas and 3.14 for electricity resulted in an approximate potential primary energy savings of 2,912x106 GJ (2.76 Quads), which would be 15% of the sector’s 2015 use of approximately 18,991x106 GJ (18 Quads). Extrapolating the results for other building types not analyzed as part of this study, the primary energy savings could be in the range of 4,220x106 GJ to 5,275x106 GJ (4 to 5 Quads). If this savings potential is realized, it would be equivalent to not combusting 180 to 230 million tons of coal or reducing the energy impacts, at today’s energy intensities, of the per capita consumption of 12 to 15 million people in the U.S. To realize most of this potential savings, many gaps can be addressed through RD&D, as recommended in this paper.

Fernandez, Nick↗
DOE OSTI2022

Investigation of signal characteristics and charge sharing in AC-LGADs with laser and test beam measurements

AC-LGADs, also referred to as resistive silicon detectors, are a recent development of low-gain avalanche detectors (LGADs), based on a sensor design where the multiplication layer and n + contact are continuous, and only the metal layer is patterned. In AC-LGADs, the signal is capacitively coupled from the continuous, resistive n + layer over a dielectric to the metal electrodes. Therefore, the spatial resolution is not only influenced by the electrode pitch, but also the relative size of the metal electrodes. Signal propagation between the metallized areas and charge sharing between electrodes plays a larger role in these detectors than in conventional silicon sensors read out in DC mode. AC-LGADs from two manufacturers were studied in beam tests and with infrared laser scans. The impact of n + layer resistivity and metal electrode pitch on the charge sharing and achievable position resolution is shown. For strips with 100 μm pitch, a resolution of ¡ 5 μm can be reached. Additionally, the charge sharing between neighboring strips is investigated in more detail, indicating the induction of signal charge and subsequent re-sharing over the n + layer. Furthermore, an approach to identify signal sharing over large distances is presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Multiplexable intrinsic Fabry-Pérot interferometers inscribed by femtosecond laser for vibration measurement in high temperature environments

This article reports fabrication technique and demodulation algorithm developments to use multiplexable intrinsic Fabry-Pérot interferometer (IFPI) fiber sensor array for distributed vibration measurements at high temperatures. Using femtosecond laser direct writing scheme, IFPI array were fabricated through laser-induced Type II scattering points in single mode fiber cores. Reflection spectra of IFPI array were demodulated in real-time using modified Bunemen frequency analysis. The demodulation algorithm, which was implemented using a photodetector-array spectrometer, achieves 64-nε dynamic strain resolution at 1-kHz spectral acquisition rate and 2-kHz maximum vibration bandwidth. Performance and stabilities of IFPI sensor array were characterized from room temperatures to 800 °C. The static strain resolution was 0.6 με and the minimum detectable dynamic strain amplitude was 23 nε/√Hz at 800 °C. The multiplex performance was also tested by measuring dynamic strain in time domain through six IFPI sensor array fabricated in one fiber. This paper presents an integrated and low-cost sensing solution to perform distributed vibration measurements in harsh environments.

42 ENGINEERING↗
DOE OSTI2020

Multiamorphous Phases in Diketopyrrolopyrrole-Based Conjugated Polymers: From Bulk to Ultrathin Films

The glass transition temperature (T g ) of conjugated polymers is a crucial physical parameter that governs their mechanical and electrical properties for applications from sensor technology to skin-like electronics. Despite some well-developed methods that exist for detecting T g of conjugated polymers, there is still a need for the combination of advanced calorimetric methodologies to characterize T g in a broad range of temperatures and scales from bulk to nanometer-thin films. In this work, alternating current (ac) chip calorimetry and flash differential scanning calorimetry (flash DSC) are applied to successfully identify the Tgs and segmental relaxations of conjugated polymers. The detected relaxations were interpreted, in agreement with existing observations in similar systems, as a side-chain relaxation (low temperature), mobile amorphous fractions (MAF), and rigid amorphous fractions (RAF). T g s of MAF and RAF increase and decrease with increasing size of fused thiophene units in the backbone, respectively. The T g s of diketopyrrolopyrrole-based conjugated polymer thin films are also identified by the same method, with both T g s showing a decreased value compared to those of bulk samples. Furthermore, the weight fractions of MAF and RAF with various film thicknesses are qualitatively analyzed based on the heat capacity step of each amorphous fraction during the glass transition. This facile method gives insights into the physical nature of amorphous phases in conjugated polymers for better revealing their structure-property relationships, which will guide the designs of new materials with optimized electrical and mechanical properties in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Multi-parametric approach towards the assessment of radon and thoron progeny exposures

Conventionally, the dosimetry is carried out using radon and thoron gas concentration measurements and doses have been assigned using assumed equilibrium factors for the progeny species, which is inadequate pertaining to the variations in equilibrium factors and possibly due to significant thoron. In fact, since the true exposures depend upon the intricate mechanisms of progeny deposition in the lung, therefore an integrated approach for the assessment of progeny is essential. In this context, the recently developed deposition based progeny concentration measurement techniques (DTPS: Direct Thoron progeny sensors and DRPS: Direct Radon progeny sensors) appear to be best suited for radiological risk assessments both among occupational workers and general study populations. DTPS and DRPS consist of aluminized mylar mounted LR115 type passive detectors, which essentially detects the alpha particles emitted from the deposited progeny atoms on the detector surface. It gives direct measure of progeny activity concentrations in air. DTPS has a lower limit of detection limit of 0.1 Bq/m{sup 3} whereas that for DRPS is 1 Bq/m{sup 3}, hence are perfectly suitable for indoor environments. These DTPS and DRPS can be capped with 200-mesh type wire-screen to measure the coarse fraction of the progeny concentration and the corresponding coarse fraction deposition velocities as well as the time integrated fine fraction. DTPS and DRPS can also be lodged in an integrated sampler wherein the wire-mesh and filter-paper are arranged in an array in flow-mode, to measure the fine and coarse fraction concentration separately and simultaneously. The details are further discussed in the paper.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Graphene based biosensors

Nanometer-sized graphene as a 2D material has unique chemical and electronic properties. Because of its unique physical, chemical, and electronic properties, its interesting shape and size make it a promising nanomaterial in many biological applications. It is expected that biomaterials incorporating graphene will be developed for the graphene-based drug delivery systems and biomedical devices. The interactions of biomolecules and graphene are long-ranged and very weak. Development of new techniques is very desirable for design of bioelectronics sensors and devices. In this work, we present first-principles calculations within density functional theory to calculate effects of charging on nucleobases on graphene. It is shown that how modify structural and electronic properties of nucleobases on graphene by applied charging.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2016

Biological applications of graphene oxide

Graphene as a 2D material has unique chemical and electronic properties. Because of its unique physical, chemical, and electronic properties, its interesting shape and size make it a promising nanomaterial in many biological applications. However, the lower water-solubility and the irreversible aggregation due to the strong π-π stacking hinder the wide application of graphene nanosheets in biomedical field. Thus, graphene oxide (GO), one derivative of graphene, has been used more frequently in the biological system owing to its relatively higher water solubility and biocompatibility. Recently, it has been demonstrated that nanomaterials with different functional groups on the surface can be used to bind the drug molecules with high affinity. GO has different functional groups such as H, OH and O on its surface; it can be a potential candidate as a drug carrier. The interactions of biomolecules and graphene like structures are long-ranged and very weak. Development of new techniques is very desirable for design of bioelectronics sensors and devices. In this work, we present first-principles spin polarized calculations within density functional theory to calculate effects of charging on DNA/RNA nucleobases on graphene oxide. It is shown that how modify structural and electronic properties of nucleobases on graphene oxide by applied charging.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Prospects of federated machine learning in fluid dynamics

Physics-based models have been mainstream in fluid dynamics for developing predictive models. In recent years, machine learning has offered a renaissance to the fluid community due to the rapid developments in data science, processing units, neural network based technologies, and sensor adaptations. So far in many applications in fluid dynamics, machine learning approaches have been mostly focused on a standard process that requires centralizing the training data on a designated machine or in a data center. In this article, we present a federated machine learning approach that enables localized clients to collaboratively learn an aggregated and shared predictive model while keeping all the training data on each edge device. We demonstrate the feasibility and prospects of such a decentralized learning approach with an effort to forge a deep learning surrogate model for reconstructing spatiotemporal fields. Our results indicate that federated machine learning might be a viable tool for designing highly accurate predictive decentralized digital twins relevant to fluid dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Eddy current flow meter model validation with a moving solid rod*

We report that the eddy current flow meter (ECFM) has been used to measure velocities and temperatures of conductive flows, such as liquid metal flows in a nuclear fission reactor. The goal of this paper is to develop a finite element electromagnetic model that can characterize the ECFM sensor performance and validate this finite element model with detailed velocity measurements of a controlled, well-characterized moving conductive solid rod. Both measurements and modeling were performed for various parameters that are important for ECFM performance such as rod velocity, rod material, ECFM sensor coil length, number of sensor coils, applied alternating current (AC) current amplitude, and applied ECFM AC frequency. For all parametric scans, the measurement and modeling agree well in both magnitude and trend. The normalized root-mean-square error between measurement and modeling is less than 10% for all cases. These results suggest that electromagnetic modeling could eventually be used to cost-effectively design future ECFM sensors in arbitrary geometry for more challenging applications such as liquid metal nuclear fission reactors.

47 OTHER INSTRUMENTATION↗