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NASA NTRS1993

Infrared sensors and systems for enhanced vision/autonomous landing applications

There exists a large body of data spanning more than two decades, regarding the ability of infrared imagers to 'see' through fog, i.e., in Category III weather conditions. Much of this data is anecdotal, highly specialized, and/or proprietary. In order to determine the efficacy and cost effectiveness of these sensors under a variety of climatic/weather conditions, there is a need for systematic data spanning a significant range of slant-path scenarios. These data should include simultaneous video recordings at visible, midwave (3-5 microns), and longwave (8-12 microns) wavelengths, with airborne weather pods that include the capability of determining the fog droplet size distributions. Existing data tend to show that infrared is more effective than would be expected from analysis and modeling. It is particularly more effective for inland (radiation) fog as compared to coastal (advection) fog, although both of these archetypes are oversimplifications. In addition, as would be expected from droplet size vs wavelength considerations, longwave outperforms midwave, in many cases by very substantial margins. Longwave also benefits from the higher level of available thermal energy at ambient temperatures. The principal attraction of midwave sensors is that staring focal plane technology is available at attractive cost-performance levels. However, longwave technology such as that developed at FLIR Systems, Inc. (FSI), has achieved high performance in small, economical, reliable imagers utilizing serial-parallel scanning techniques. In addition, FSI has developed dual-waveband systems particularly suited for enhanced vision flight testing. These systems include a substantial, embedded processing capability which can perform video-rate image enhancement and multisensor fusion. This is achieved with proprietary algorithms and includes such operations as real-time histograms, convolutions, and fast Fourier transforms.

Kerr, J. Richard↗

DOE OSTI2024

Calcined Polyethyleneimine-Coated Optical Fibers for Distributed pH Monitoring at High Pressures and Temperatures

In the oil and gas, CO2 sequestration, H2 subsurface storage, and geothermal energy sectors, subsurface pH measurements are critical for monitoring the geochemical conditions and estimating potential corrosion rates of wellbore systems. Real-time pH measurements in these conditions are vital for detecting and predicting corrosion deterioration of wellbore components that may jeopardize the safety and continued operation of wellbore systems. Previous tests using metal oxide-based coatings (TiO2) provided strong responses at elevated temperatures and moderate pressure stability but provided poor differentiation between acidic and alkaline solutions. Building off the pH responsiveness of the TiO2 surface and known pH sensitivity of amine-based polymers, a coating based on the secondary amine polymer polyethyleneimine (PEI) was developed. As the polymer itself is highly water soluble and easily removed by aqueous solutions, the sensor coating was treated with a high temperature (500 °C) calcination procedure in air to convert it into a more stable oxidized coating capable of withstanding hot aqueous solutions without dissolving while retaining linear pH sensitivity from pH values between 2 and 11. The sensor performance was measured using optical transmission measurements in solutions of various pHs and using optical backscatter reflectometry for distributed pH sensing demonstration in wellbore-relevant pressures (up to 1,000 psi) and temperatures (80 °C).

Shumski, Alexander↗

DOE OSTI2023

Lithium-Ion Battery Diagnostics Using Electrochemical Impedance via Machine-Learning

Diagnosing battery states such as health, state-of-charge, or temperature is crucial for ensuring the safety and reliability of electrochemical energy storage systems. While some states, such as temperature, may be measured using cheap sensors, accurate diagnosis of battery health metrics usually requires time-consuming performance measurements, making them infeasible for use in real-world operation. These health metrics can be measured during lab-testing and then estimated on-line using predictive life models or via state observer algorithms such as Kalman filters, but these predictive methods should be supplemented by actual measurement of battery health whenever possible to ensure reliability. Rapid measurement of battery health may be done by various types of fast diagnostic techniques such as electrochemical impedance spectroscopy (EIS), which can be performed in only a few minutes and require only a fraction of the energy and power needed for a full charge and discharge measurement. But there is a substantial challenge for estimating battery health using EIS data, as EIS is sensitive to cell temperature, state-of-charge, current, and resting time in addition to health. Thus, utilizing EIS data to predict battery capacity requires correcting for all these additional variables, a task that is extremely difficult to handle analytically. This talk utilizes machine-learning methods to estimate the effectiveness of battery capacity prediction from EIS data, leveraging a data set of hundreds of EIS measurements recorded at varying temperature and state-of-charge throughout a 500-day aging study of 32 commercial, large-format NMC-Graphite lithium-ion batteries. Using EIS as input to machine-learning models is complicated by the nonlinear response of impedance to battery health, temperature, and state-of-charge, as well as the collinearity between the impedance response at neighboring frequencies, which can easily lead to overfit models. To train robust models, features from EIS data need to be extracted from the data or some subset of critical frequencies selected. Many approaches for extracting and selecting features from EIS data from electrochemical analysis and machine-learning fields were identified for analysis: using the entire raw spectra; selection of one, two, or many frequencies from the entire spectra; selecting interesting points from the EIS measurement using domain knowledge; fitting EIS with an equivalent-circuit model; calculating statistics on the raw impedance values; and reducing the dimensionality of the data using unsupervised linear (principal component analysis) and non-linear (uniform manifold approximation and projection) methods. These approaches were rigorously compared using a machine-learning pipeline approach, training linear, Gaussian process, and random forest regression models and quantifying performance using cross-validation as well as a held-out test set. An artificial neural network model trained on the raw spectra was also tested. Promising pipelines were fine-tuned via Bayesian hyperparameter optimization using cross-validation loss and training with class-specific weights to counter data set imbalance. The most reliable method for utilizing impedance in this work was the selection of two optimal frequencies through an exhaustive search, resulting in about 2% mean absolute error on test data for both Gaussian process and random forest model architectures. Interrogation of a variety of models reveals critical frequencies of 100 Hz and 103 Hz for this data set, though the optimal set of frequencies is not necessarily intuitive, i.e., the best performing models are not simply those that use impedance at frequencies that have the highest correlation to the relative discharge capacity. The best performing model is an ensemble model, which is able to predict battery capacity with 1.9% mean absolute error for unseen cells using impedance recorded at a variety of temperatures and states-of-charge.

battery↗

NASA NTRS2012

Arctic PBL Cloud Height and Motion Retrievals from MISR and MINX

How Arctic clouds respond and feedback to sea ice loss is key to understanding of the rapid climate change seen in the polar region. As more open water becomes available in the Arctic Ocean, cold air outbreaks (aka. off-ice flow from polar lows) produce a vast sheet of roll clouds in the planetary boundary layer (PBl). The cold air temperature and wind velocity are the critical parameters to determine and understand the PBl structure formed under these roll clouds. It has been challenging for nadir visible/IR sensors to detect Arctic clouds due to lack of contrast between clouds and snowy/icy surfaces. In addition) PBl temperature inversion creates a further problem for IR sensors to relate cloud top temperature to cloud top height. Here we explore a new method with the Multiangle Imaging Spectro-Radiometer (MISR) instrument to measure cloud height and motion over the Arctic Ocean. Employing a stereoscopic-technique, MISR is able to measure cloud top height accurately and distinguish between clouds and snowy/icy surfaces with the measured height. We will use the MISR INteractive eXplorer (MINX) to quantify roll cloud dynamics during cold-air outbreak events and characterize PBl structures over water and over sea ice.

Wu, Dong L.↗

DOE OSTI2021

Time Series Surface Temperature of Variably Inundated Sediment across 30 North American Rivers

This dataset supports a broader study examining drivers of organic matter chemistry in variably inundated hyporheic zone sediments and further linking that chemistry to biogeochemical rates. The dataset provides surficial temperature time series that can be used to infer the dynamics of inundation prior to the collection of sediments. Those inferred inundation histories can then be used to help interpret variation in the organic matter chemistry. There are related data that will be published, such as FTICR-MS data on organic matter chemistry and sediment moisture. A data package with those data is forthcoming.This dataset is comprised of two folders: (1) ECA1_iButtonData and (2) ECA1_SitePhotos. The ECA1_iButtonData folder contains: (1) file-level metadata, (2) data dictionary, (3) field metadata, (4) installation methods, (5) iButton deployment protocol, (6) readme, and (7) folder of individual time series temperature csv files for each iButton sensor deployed. The ECA1_SitePhotos folder contains site photographs taken in the field. All files are .csv, .txt, .pdf, or .jpg.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1976

Thermal control systems for low temperature Shuttle payloads

Greater sensitivity and longer life for future space sensor systems place more stringent demands on cooling system technology. Results are presented for a study designed to determine and evaluate low-temperature thermal control system concepts for various cooling categories in the range 3-200 K and to generate hardware development plans for undeveloped viable system concepts. The study considered Shuttle launched payloads in the 1980-1991 time frame, with 1-5 yr of life. Cooling concepts are categorized as open-cycle (expendable), closed-cycle (mechanical), solid-state, and radiative. Particular attention is given to the concepts of multistage heat pipe radiator, diode heat pipe radiator, and radiator guarded cryostat. Results are given for parametric analyses of the Vuilleumier refrigerator, the rotary reciprocating refrigerator, the solid hydrogen refrigerator, the solid hydrogen/multistage radiator hybrid cooler, and the magneto-Peltier hybrid cooler.

Wright, J. P.↗

NASA NTRS2012

Space Shuttle Solid Rocket Motor Plume Pressure and Heat Rate Measurements

The Solid Rocket Booster (SRB) Main Flame Deflector (MFD) at Launch Complex 39A was instrumented with sensors to measure heat rates, pressures, and temperatures on the last three Space Shuttle launches. Because the SRB plume is hot and erosive, a robust Tungsten Piston Calorimeter was developed to compliment the measurements made by off-the-shelf sensors. Witness materials were installed and their melting and erosion response to the Mach 2 / 4500 F / 4-second duration plume was observed. The data show that the specification document used for the design of the MFD thermal protection system over-predicted heat rates by a factor of 3 and under-predicted pressures by a factor of 2. These findings will be used to baseline NASA Computational Fluid Dynamics models and develop innovative MFD designs for the Space Launch System (SLS) before this vehicle becomes operational in 2017.

vonEckroth, Wulf↗

NASA NTRSDate not supplied

ANALYSIS OF THE MSL/MEDLI ENTRY DATA WITH COUPLED CFD AND MATERIAL RESPONSE.

The Mars Science Laboratory (MSL) was protected during its atmospheric entry by an instrumented heat-shield using NASA's Phenolic Impregnated Carbon Ablator (PICA) material. PICA is a lightweight carbon fiber/polymeric resin material that offers out-standing performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of material response and atmospheric entry. MEDLI recorded, among other things, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP). The objective of this work is to showcase and analyze the coupling between the material response and the aerothermal environment. As shown in Figure 1, the workflow is divided into the following steps. First, the aerothermal properties are computed in the Data Parallel Line Relaxation (DPLR) code [3] and used with the Nonequilibrium air radiation (NEQAIR) program [8] to compute radiative heating. Second, the thermal response inside the material is computed in the Porous material Analysis Toolbox based on Open-FOAM (PATO) using a fixed blowing correction parameter. Third, the pyrolysis gases computed in PATO are used as inputs to a blowing boundary condition within DPLR. Fourth, the new environment properties from DPLR are used in NEQAIR to provide an updated solution, then both the updated aerothermal environment and radiative heating are used in PATO without blowing correction. The third and fourth steps are then repeated until convergence in surface temperature is obtained. Convergence in the radiative heating is generally achieved before surface temperature, at which point the radiative heating is no longer updated. Char mass loss rates are forced to zero to produce a non-receding surface condition. For early time points in the trajectory, where flow around the MSL aeroshell is rarefied, the Direct Simulation Monte Carlo (DSMC) code, SPARTA, is used to compute the aerothermal environment. Iteration between PATO and SPARTA is not performed due to the computational cost of DSMC simulations. Preliminary results of the coupling between PATO and DPLR for the MSL heatshield atmospheric entry model are presented in Figures 2-4 at 65 seconds after entry interface. Figure 2 shows the surface temperature results from an uncoupled simulation in PATO with the blowing correction parameter applied (left) along with the coupled surface temperature after iteration (right). Figure 3 shows the surface temperature along the centerline from windward to leeward for easier comparison. Figure 4 shows the coupled and uncoupled pyrolysis gas blowing rate. Mars 2020 used a similar heatshield consisting of PICA for thermal protection during entry, descent, and landing. In preparation for Mars 2020 post-flight analysis, the predictive material response capability is benchmarked against flight data from MEDLI. This work represents an important milestone toward the development of validated predictive capabilities for designing thermal protection systems for planetary probes.

Mars Science Laboratory↗

NASA NTRSDate not supplied

Analysis of MSL/MEDLI Entry Data with Coupled CFD and Material Response

The Mars Science Laboratory (MSL) was protected during its atmospheric entry by an instrumented heatshield using NASA's Phenolic Impregnated Carbon Ablator (PICA) material [1]. PICA is a lightweight carbon fiber/polymeric resin material that offers outstanding performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of material response and atmospheric entry. MEDLI recorded, among other things, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP) [2]. The objective of this work is to showcase and analyze the coupling between the material response and the aerothermal environment. As shown in Figure 1, the workflow is divided into the following steps. First, the aerothermal properties are computed in the Data Parallel Line Relaxation (DPLR) code [3] and used with the Nonequilibrium air radiation (NEQAIR) program [8] to compute radiative heating. Second, the thermal response inside the material is computed in the Porous material Analysis Toolbox based on OpenFOAM (PATO) [4,5,6] using a fixed blowing correction parameter. Third, the pyrolysis gases computed in PATO are used as inputs to a blowing boundary condition within DPLR. Fourth, the new environment properties from DPLR are used in NEQAIR to provide an updated solution, then both the updated aerothermal environment and radiative heating are used in PATO without blowing correction. The third and fourth steps are then repeated until convergence in surface temperature is obtained. Convergence in the radiative heating is generally achieved before surface temperature, at which point the radiative heating is no longer updated. Char mass loss rates are forced to zero to produce a non-receding surface condition. For early time points in the trajectory, where flow around the MSL aeroshell is rarefied, the Direct Simulation Monte Carlo (DSMC) code, SPARTA [7], is used to compute the aerothermal environment. Iteration between PATO and SPARTA is not performed due to the computational cost of DSMC simulations. Preliminary results of the coupling between PATO and DPLR for the MSL heatshield atmospheric entry model are presented in Figures 2-4 at 65 seconds after entry interface. Figure 2 shows the surface temperature results from an uncoupled simulation in PATO with the blowing correction parameter applied (left) along with the coupled surface temperature after iteration (right). Figure 3 shows the surface temperature along the centerline from windward to leeward for easier comparison. Figure 4 shows the coupled and uncoupled pyrolysis gas blowing rate. Mars 2020 used a similar heatshield consisting of PICA for thermal protection during entry, descent, and landing. In preparation for Mars 2020 post-flight analysis, the predictive material response capability is benchmarked against flight data from MEDLI. This work represents an important milestone toward the development of validated predictive capabilities for designing thermal protection systems for planetary probes.

Thermal Protection Systems↗

NASA NTRS2020

Extension of the energy range accessible with a TES using bath temperature variations

The energy range of transition-edge sensor (TES) X-ray microcalorimeters with a multiplexed readout depends upon the width and shape of the TES superconducting transition, and also on the dynamic range of the readout. In many detector systems, the multiplexed readout slew rate capability will be the limiting factor for the energy range. In these cases, if we are willing to accept some energy resolution degradation, we can significantly extend the energy range by increasing the bath temperature of operation, essentially creating a second â€œextended energy rangeâ€ mode of operation. For example, if we require the very highest energy resolution up to 7 keV, and wish to optimize the design up to this energy, for some measurements it could be very beneficial to have a mode where we can extend the energy range to 15â€“20 keV even if some energy resolution is sacrificed. In this paper, we explore the trade-off between dynamic range and energy resolution from changing the bath temperature of the TES. We present measurements of TES resolution and slew rate as a function of bath temperature and compare to numerical simulations.

S Beaumont↗

NASA NTRS2019

The Seismic Experiment for Interior Structure (SEIS): Experiment Data Distribution

The six sensors of SEIS (The Seismic Experiment for Interior Structure) [- one of three primary instruments on NASA's Mars Lander Insight] cover a broad range of the seismic bandwidth, from 0.01 hertz to 50 hertz, with possible extension to longer periods. Data are transmitted in the form of three continuous VBB (Very Broad-Band) components at 2 samples per second (sps), an estimation of the short period (SP) energy content from the SP at 1 sps, and a continuous compound VBB/SP vertical axis at 10 sps. The continuous streams are augmented by requested event data with sample rates from 20 to 100 sps. SEIS data products are downlinked from the spacecraft in raw CCSDS (Consultative Committee for Space Data Systems) packets and converted to both the Standard for the Exchange of Earthquake Data (SEED) format files and ASCII tables (GeoCSV) for analysis and archiving. Metadata are available in dataless SEED and StionXML. Time series data (waveforms) are available in miniseed and GeoCSV. Data are distributed according to FDSN (Federation of Digital Seismograph Networks - http://www.fdsn.org) formats and interfaces. Wind, pressure and temperature data from the Auxiliary Payload Sensor Suite (APSS) will also be available in SEED format, and can be used for decorrelation and diagnostic purposes on SEIS.

Pardo, Constanza↗

NASA NTRS1990

Attitude sensor alignment calibration for the solar maximum mission

An earlier heuristic study of the fine attitude sensors for the Solar Maximum Mission (SMM) revealed a temperature dependence of the alignment about the yaw axis of the pair of fixed-head star trackers relative to the fine pointing Sun sensor. Here, new sensor alignment algorithms which better quantify the dependence of the alignments on the temperature are developed and applied to the SMM data. Comparison with the results from the previous study reveals the limitations of the heuristic approach. In addition, some of the basic assumptions made in the prelaunch analysis of the alignments of the SMM are examined. The results of this work have important consequences for future missions with stringent attitude requirements and where misalignment variations due to variations in the temperature will be significant.

Pitone, Daniel S.↗

NASA NTRS2008

Ultra-Stable Beacon Source for Laboratory Testing of Optical Tracking

The ultra-stable beacon source (USBS) provides a laser-beam output with a very low angular jitter and can be used as an absolute angular reference to simulate a beacon in the laboratory. The laser is mounted on the top of a very short (approximately equal to 1 m) inverted pendulum (IP) with its optical axis parallel to the carbon fiber pendulum leg. The 85-cm, carbon fiber rods making up the leg are very lightweight and rigid, and are supported by a flex-joint at the bottom (see figure). The gimbal-mounted laser is a weight-adjustable load of about 1.5 kg with its center of rotation co-located with the center of percussion of the inverted pendulum. This reduces the coupling of transverse motion at the base of the pendulum to angular motion of the laser at the top. The inverted pendulum is mounted on a gimbal with its center of rotation coinciding with the pivot position of the inverted pendulum flexure joint. This reduces coupling of ground tilt at the inverted pendulum base to motion of the laser mounted at the top. The mass of the top gimbal is adjusted to give the pendulum a very low resonant frequency (approximately equal to 10 mHz) that filters transverse seismic disturbances from the ground where the base is attached. The motion of the IP is monitored by an optical-lever sensor. The laser light is reflected by the mirror on the IP, and then is detected by a quadrant photo-detector (QPD). The position of the beam spot on the QPD corresponds to the tilt of the IP. Damping of this motion is provided by two coil and magnet pairs. The bottom gimbal mount consists of two plates. The IP is mounted on the second plate. The first plate is supported by two posts through needles and can be rotated about the axis connecting the tips of the needles. The second plate hangs from the first plate and can be rotated about the axis perpendicular to the first plate. As a result, the second plate acts as a two-axis rotation stage. Its center of rotation is located at the effective bending point of the flex-joint. The second plate is pressed against two screw actuators by the weight of the IP. The screw actuators are orthogonal to each other and are used to adjust the inclination of the second plate. The actuators are driven by stepper motors. The whole IP system is housed in a box made of Lexan plastic plates to provide isolation from air currents and temperature variations. The signals from the sensors are processed and recorded with a PC using the xPC Target realtime environment of Math- Works. The control algorithms are written using the Simulink package from The MathWorks.

Aso, Yoichi↗

NASA NTRS1980

Complexities of nadir-looking radiometric temperature measurements of plant canopies

Effective radiant temperatures (ERTs) of five wheat canopies in different stages of development were measured during morning and noon periods. The observed variability in nadir sensor response was quantitatively described as a function of canopy structure and the vertical temperature profile of canopy components. In many cases, the nadir sensor ERT was a poor measure of vegetation temperature due to effects of soil emissions. Strong vertical temperature profiles of vegetation components were also observed. The theory and measurements presented document that remote measurements of vegetation canopy temperatures cannot be made indiscriminately over large spatial regions without consideration of the underlying physical principles.

Kimes, D. S.↗

NASA NTRS1994

Development of sensors for ceramic components in advanced propulsion systems

The 'Development of Sensors for Ceramics Components in Advanced Propulsion Systems' program was divided into two phases. The objectives of Phase 1 were to analyze, evaluate and recommend sensor concepts for the measurement of surface temperature, strain and heat flux on ceramic components for advanced propulsion systems. The results of this effort were previously published in NASA CR-182111. As a result of Phase 1, three approaches were recommended for further development: pyrometry, thin-film sensors, and thermographic phosphors. The objectives of Phase 2 were to fabricate and conduct laboratory demonstration tests of these systems. A summary report of the Phase 2 effort, together with conclusions and recommendations for each of the categories evaluated, has been submitted to NASA. Emittance tests were performed on six materials furnished by NASA Lewis Research Center. Measurements were made of various surfaces at high temperature using a Thermogage emissometer. This report describes the emittance test program and presents a summary of the results.

Atkinson, William H.↗

DOE OSTI2021

Optical monitoring to detect contamination of power grid components

A monitoring system includes an array of optical sensors disposed within a transformer tank. Each optical sensor is configured to have an optical output that changes in response to a temperature within the transformer tank. An analyzer is coupled to the array of optical sensors. The analyzer is configured to determine a sensed temperature distribution based on the sensed temperature. The sensed temperature distribution is compared to an expected distribution. Exterior contamination of the transformer tank is detected based on the comparison.

Mostafavi, Saman↗

DOE OSTI2023

Optical monitoring to detect contamination of power grid components

Mostafavi, Saman↗

NASA NTRS2016

Unexpected Nonlinear Effects in Superconducting Transition-Edge Sensors

When a normal metal transitions into the superconducting state the DC resistance drops from a finite value to zero over some finite transition width in temperature, current, and magnetic field. Superconducting transition-edge sensors (TESs) operate within this transition region and uses resistive changes to measure deposited thermal energy. This resistive transition is not perfectly smooth and a wide range of TES designs and materials show sub-structure in the resistive transition (as seen in smooth nonmonotonic behavior, jump discontinuities, and hysteresis in the devices current-voltage relation and derivatives of the resistance with respect to temperature, bias current, and magnetic field). TES technology has advanced to the point where for many applications this structure is the limiting factor in performance and optimization consists of finding operating points away from these structures. For example, operating at or near this structure can lead to nonlinearity in the detectors response and gain scale, limit the spectral range of the detector by limiting the usable resistive range, and degrade energy resolution. The origin of much of this substructure is unknown. This presentation investigates a number of possible sources in turn. First we model the TES as a superconducting weak-link and solve for the characteristic differential equations current and voltage time dependence. We find:(1) measured DC biased current-voltage relationship is the time-average of a much higher frequency limit cycle solution.(2) We calculate the fundamental frequency and estimate the power radiated from the TES treating the bias leads as an antennae.(3) The solution for a set of circuit parameters becomes multivalued leading to current transitions between levels.(4)The circuit parameters can change the measure resistance and mask the true critical current. As a consequence the TES resistance surface is not just a function of temperature, current, and magnetic field but is also a function of the circuit elements (such as shunt resistor, SQUID inductance, and capacitor values). In other words, same device measured in different electrical circuits will have a different resistive surface in temperature, current, and magnetic field. Next we consider that at the transition temperature of a superconductor both the magnetic penetration depth and coherence length are divergent. As a consequence these important characteristic length scales are changing with operating point. We present measurements on devices showing commensurate behavior between these characteristic lengths and the length scale of added normal metal structures. Reordering of proximity vortices leads to discontinuities and irreversibility of the current-voltage curves. Last we consider a weak-link TES including both thermal activated resistance effects and the effect of the magnetic penetration depth being a function of temperature and magnetic field. We derive its impact on the resistive transition surface and the important device parameters a and b.

Superconducting Detectors↗