Solid Particles Mass Flux Sensor; sensor measuring solid particles mass flux and indicative wind-speed measurements (b1-level)
Solid Particles Mass Flux Sensor; sensor measuring solid particles mass flux and indicative wind-speed measurements
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Solid Particles Mass Flux Sensor; sensor measuring solid particles mass flux and indicative wind-speed measurements
Embodiments of the subject invention relate to a gas sensor and method for sensing one or more gases. An embodiment incorporates an array of sensing electrodes maintained at similar or different temperatures, such that the sensitivity and species selectivity of the device can be fine tuned between different pairs of sensing electrodes. A specific embodiment pertains to a gas sensor array for monitoring combustion exhausts and/or chemical reaction byproducts. An embodiment of the subject device related to this invention operates at high temperatures and can withstand harsh chemical environments. Embodiments of the device are made on a single substrate. The devices can also be made on individual substrates and monitored individually as if they were part of an array on a single substrate. The device can incorporate sensing electrodes in the same environment, which allows the electrodes to be coplanar and, thus, keep manufacturing costs low. Embodiments of the device can provide improvements to sensitivity, selectivity, and signal interference via surface temperature control.
This presentation is in support of INL collaborations with the Nuclear University Consortium (NUC) and the Center for Advanced Energy Studies (CAES) member institutions. The presentation describes the content of two workscopes from the DOE-Office of Nuclear Energy Consolidated Innovative Nuclear Research Funding Opportunity Announcement (CINR FOA) for FY2020 concerning radiation testing of sensors and sensor materials.
We study the transport properties of graphene layers placed over ∼200 nm triangular holes via attached electrodes under applied pressure. We find that the injected current division between counter electrodes depends on pressure and can be used to realize a nanoscale pressure sensor. Estimating various potential contributions to the resistivity change of the deflected graphene membrane including piezoresistivity, changing gate capacitance, and the valley Hall effect due to the pressure-induced synthetic magnetic field, we find that the valley Hall effect yields the largest expected contribution to the longitudinal resistivity modulation for accessible device parameters. Such devices in the ballistic transport regime may enable the realization of tunable valley polarized electron sources.
A new type of large area sensor for infrared imaging bolometers has been developed. It replaces the thin and fragile free-standing metal foils, which typically have been used, with a multi-layer coated sapphire (or diamond) substrate. Sapphire is transparent to mid-infrared wavelengths, is robust against transients, and can be thick enough to even be the vacuum window. The primary radiation absorber is still a thin deposited metal layer, but now it is partially insulated from the supporting sapphire substrate by a black (carbon-based) layer, which also acts as a blackbody remitter. Test results indicate 6× more noise equivalent power density (estimated NEPD = 23 W/m 2 at 5 ms camera exposure time, foil temperature decay time 60 ms) for a 2 μm gold-coated sapphire disk compared to estimated NEP = 4 W/m 2 at 1.8 ms exposure time, with foil decay time 420 ms, for a nominal 2.5 μm thick platinum-free-standing foil.
Abstract not provided
In this paper, we describe the optimization of transition-edge-sensor (TES) detector arrays for the third-generation camera for the South PoleTelescope. The camera, which contains similar to 16 000 detectors, will make high-angular-resolution maps of the temperature and polarization of the cosmic microwave background. Our key results are scatter in the transition temperature of Ti/Au TESs is reduced by fabricating the TESs on a thin Ti(5 nm)/Au(5 nm) buffer layer and the thermal conductivity of the legs that support our detector islands is dominated by the SiOx dielectric in the microstrip transmission lines that run along the legs.
Here, we report a model that can be used to calculate superconducting transition temperature of a transition-edge sensor (TES), which is either a normal metal-superconductor-normal metal trilayer or a normal metal-superconductor bilayer. The model allows the T C estimation of a trilayer when the normal metals at the bottom and at the top are different. Furthermore, the model includes the spin flip time of the normal metals. We also use the T C calculations from this model for selected Ir-based trilayers and bilayers to help understand potential designs of low T C TESs. A Au/Ir/Au trilayer can have a low T C because the superconducting order parameter is reduced with normal metals at both sides. On the other hand, an Ir/Pt bilayer can have a low T C because the much larger electron density of states of Pt reduces the superconducting order parameter more effectively. Moreover, the spin flip scattering of paramagnetic Pt also contributes to the T C reduction.
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Overview and brief project update on 3 tasks within the RIC Advanced Sensors & Controls FWP with direct applications to coal fired boiler temperature sensing. Task 32, Field demonstration of distributed temperature measurement with optical fiber for fossil energy power generation applications. Task 47, In-situ temperature measurements via reactive particles. Task 48, Ultrafast laser measurements for power generation environments.
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Refrigerant mass flow rate is an important measurement for monitoring equipment performance and enabling fault detection and diagnostics. However, a traditional mass flow meter is expensive to purchase and install. A virtual refrigerant mass flow sensor (VRMF) uses a mathematical model to estimate flow rate using low-cost measurements and can potentially be implemented at low cost. This study evaluates three VRMFs for estimating refrigerant mass flow rate. The first model uses a compressor map that relates refrigerant flow rate to measurements of inlet and outlet pressure, and inlet temperature measurements. The second model uses an energy-balance method on the compressor that uses a compressor map for power consumption, which is relatively independent of compressor faults that influence mass flow rate. The third model is developed using an empirical correlation for an electronic expansion valve (EEV) based on an orifice equation. The three VRMFs are shown to work well in estimating refrigerant mass flow rate for various systems under fault-free conditions with less than 5% RMS error. Each of the three mass flow rate estimates can be utilized to diagnose and track the following faults: 1) loss of compressor performance, 2) fouled condenser or evaporator filter, 3) faulty expansion device, respectively. For example, a compressor refrigerant flow map model only provides an accurate estimation when the compressor operates normally. When a compressor is not delivering the expected flow due to a leaky suction or discharge valve or other internal fault, the energy-balance or EEV model can provide accurate flow estimates. In this paper, the flow differences provide an indication of loss of compressor performance and can be used for fault detection and diagnostics.
In an effort to characterize the fast neutron radiation background, 16 EJ-309 liquid scintillator cells were installed in the Radiological Multi-sensor Analysis Platform (RadMAP) to collect data in the San Francisco Bay Area. Each fast neutron event was associated with specific weather metrics (pressure, temperature, absolute humidity) and GPS coordinates. Furthermore, the expected exponential dependence of the fast neutron count rate on atmospheric pressure was demonstrated and event rates were subsequently adjusted given the measured pressure at the time of detection. Pressure adjusted data was also used to investigate the influence of other environmental conditions on the neutron background rate. Using National Oceanic and Atmospheric Administration (NOAA) coastal area lidar data, an algorithm was implemented to approximate sky-view factors (the total fraction of visible sky) for points along RadMAPs route. In the three areas we analyzed, San Francisco, Downtown Oakland, and Berkeley, all demonstrated a suppression in the background rate of over 50% for the range of sky-view factors measured. This effect, which is due to the shielding of cosmic-ray produced neutrons by surrounding buildings, was comparable to the pressure influence which yielded a 32% suppression in the count rate over the range of pressures measured.
Silicon pixel detectors are at the core of the current and planned upgrade of the ATLAS experiment at the LHC. Given their close proximity to the interaction point, these detectors will be exposed to an unprecedented amount of radiation over their lifetime. The current pixel detector will receive damage from non-ionizing radiation in excess of 10 15 1 MeV n eq /cm 2 , while the pixel detector designed for the high-luminosity LHC must cope with an order of magnitude larger fluence. We present a digitization model incorporating effects of radiation damage to the pixel sensors. The model is described in detail and predictions for the charge collection efficiency and Lorentz angle are compared with collision data collected between 2015 and 2017 (≤ 10 15 1 MeV n eq /cm 2 ).
Highly granular pixel detectors allow for increasingly precise measurements of charged particle tracks. Next-generation detectors require that pixel sizes will be further reduced, leading to unprecedented data rates exceeding those foreseen at the High- Luminosity Large Hadron Collider. Signal processing that handles data incoming at a rate of $\mathcal{O}$(40 MHz) and intelligently reduces the data within the pixelated region of the detector at rate will enhance physics performance at high luminosity and enable physics analyses that are not currently possible. Using the shape of charge clusters deposited in an array of small pixels, the physical properties of the traversing particle can be extracted with locally customized neural networks. In this first demonstration, we present a neural network that can be embedded into the on-sensor readout and filter out hits from low momentum tracks, reducing the detector's data volume by 57.1%–75.7%. The network is designed and simulated as a custom readout integrated circuit with 28 nm CMOS technology and is expected to operate at less than 300 μW with an area of less than 0.2 mm 2 . The temporal development of charge clusters is investigated to demonstrate possible future performance gains, and there is also a discussion of future algorithmic and technological improvements that could enhance efficiency, data reduction, and power per area.