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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Evaluate the impact of sensor accuracy on model performance in data-driven building fault detection and diagnostics using Monte Carlo simulation

The performance of data-driven fault detection and diagnostics (FDD) is heavily dependent on sensors. However, sensor inaccuracy and sensor faults are pervasive in building operation: inaccurate and missing sensor readings deteriorate FDD performance; sensor inaccuracy will also affect the selection of sensor for data-driven FDD in the model training process, which is another key factor of data-driven FDD performance. Sensor accuracy and sensor selection individually are well-studied research topics in this field, but the impact of sensor accuracy on sensor selection and its further impact on FDD performance has not been evaluated and quantified. In this paper, we developed a novel analysis methodology that comprehensively evaluates sensor fault on sensor selection and FDD accuracy. Monte Carlo simulation is applied to deal with multiple stochastic sensor inaccuracy and provide probabilistic analysis results of the impact of sensor inaccuracy on sensor selection and FDD accuracy. This methodology focuses on the net impact of fault states across a full sensor set. The developed methodology can be used for the early-stage sensor design and operation-stage sensor maintenance. Furthermore, a case study is conducted to demonstrate the analysis methodology using a commercial building model crated to Flexible Research Platform located at Oak Ridge National Laboratory, USA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A Review of Inkjet Printed Graphene and Carbon Nanotubes Based Gas Sensors

Graphene and carbon nanotube (CNT)-based gas/vapor sensors have gained much traction for numerous applications over the last decade due to their excellent sensing performance at ambient conditions. Inkjet printing various forms of graphene (reduced graphene oxide or modified graphene) and CNT (single-wall nanotubes (SWNTs) or multiwall nanotubes (MWNTs)) nanomaterials allows fabrication onto flexible substrates which enable gas sensing applications in flexible electronics. This review focuses on their recent developments and provides an overview of the state-of-the-art in inkjet printing of graphene and CNT based sensors targeting gases, such as NO 2 , Cl 2 , CO 2 , NH 3 , and organic vapors. Moreover, this review presents the current enhancements and challenges of printing CNT and graphene-based gas/vapor sensors, the role of defects, and advanced printing techniques using these nanomaterials, while highlighting challenges in reliability and reproducibility. The future potential and outlook of this rapidly growing research are analyzed as well.

flexible electronics↗
DOE OSTI2025

Non-destructive structural characterization of graphite components using mechanical resonance and deep learning

As compared to conventional nuclear reactors, microreactors have the potential to significantly reduce construction timelines and capital costs, decreasing the barriers for advanced nuclear reactor technologies. However, the lower power output of these microreactors (typically < 20 MWe) creates challenging economics if operation and maintenance costs cannot be sufficiently reduced. The compact size of these designs presents an opportunity for comprehensive in-situ structural health monitoring to provide real-time feedback in order to reduce operational costs associated with maintenance and downtime. Many microreactor concepts use graphite for both in-core neutron moderation and as a structural material, which has typically required some form of periodic and laborious inspection. This report provides a description and assessment of recent work with graphite to couple acoustic-based experimental measurements and characterization with machine learning models to mature structural health monitoring capabilities and generate benefits for the nuclear microreactor industry. With resilient embedded sensors in development in other programs funded by the US Department of Energy’s Office of Nuclear Energy and elsewhere, the work described herein builds upon previously funded efforts to mature non-destructive testing technology that relates measured vibrational signatures to structural changes, using a combination of new experimental measurements and machine learning processing. Building on past successful demonstrations of predictive workflows to identify structural changes in a hexagonal stainless steel test article with excellent acoustic propagation, we first performed baseline characterization on graphite samples with canonical geometries to ensure compatibility and confidence in the applied techniques for a material with distinctly different mechanical properties. In contrast to efforts in previous years, we worked exclusively with unidirectional vibration data that is more comparable to those expected from the existing embedded sensor technologies which are suitable for deployment in a reactor setting. Established acoustic and modern machine-learning-based characterization approaches were applied to the resulting datasets from these simple geometries. Both approaches were found to be highly capable of detecting even small geometric irregularities amongst nominally identical samples. As such, we then moved to testing these approaches for detection of artificial local stress perturbations introduced into a more complex geometry: a hexagonal block with drilled holes. A main outcome of this work is that a generalizable ML workflow can be used to detect and predict the characteristics of small artificial anomalies in a graphite component with a relevant geometry. While this work was performed using surficial vibration data, we expect the approach to be flexible and viable for other monitoring scenarios, such as those with different arrangements or types of sensor arrays. As compared to previously funded efforts, an existing ML workflow based on neural networks was enhanced through the addition of recently developed Fourier neural operators. As applied to previously collected and new vibration datasets, prediction accuracies of anomaly characterizations were greatly improved with minimal added computational cost. As trained on small durations of vibration data (tens of seconds) collected over a realistic number of locations, the model was able to reliably determine the presence of a subtle stress anomaly and begin to provide location estimates. Such an approach is likely to be viable for more relevant reactor damage scenarios for graphite components, such as progressive crack growth or creep.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A flexible event reconstruction based on machine learning and likelihood principles

Event reconstruction is a central step in many particle physics experiments, turning detector observables into parameter estimates; for example estimating the energy of an interaction given the sensor readout of a detector. A corresponding likelihood function is often intractable, and approximations need to be constructed. Here, in our work, we first show how the full likelihood for a many-sensor detector can be broken apart into smaller terms, and secondly how we can train neural networks to approximate all terms solely based on forward simulation. Our technique results in a fast, flexible, and close-to-optimal surrogate model proportional to the likelihood and can be used in conjunction with standard inference techniques allowing for a consistent treatment of uncertainties. We illustrate our technique for parameter inference in neutrino telescopes based on maximum likelihood and Bayesian posterior sampling. Given its great flexibility, we also showcase our method for geometry optimization enabling to learn optimal detector designs. Lastly, we apply our method to realistic simulation of a ton-scale water-based liquid scintillator detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory

Ground-based observatories use multi-sensor observations to characterize cloud and precipitation properties. One of the challenges is how to design strategies to best use these observations to understand these properties and evaluate weather and climate models. This paper introduces the Cloud resolving model Radar SIMulator (CR-SIM), which uses output from high-resolution cloud resolving models (CRMs) to emulate multi-wavelength, zenith-pointing, and scanning radar observables and multi-sensor (radar and lidar) products. CR-SIM allows direct comparison between an atmospheric model simulation and remote-sensing products using a forward-modeling framework consistent with the microphysical assumptions used in the atmospheric model. CR-SIM has the flexibility to easily incorporate additional microphysical modules, such as microphysical schemes and scattering calculations, and expand the applications to simulate multi-sensor retrieval products. In this paper, we present several applications of CR-SIM for evaluating the representativeness of cloud microphysics and dynamics in a CRM, quantifying uncertainties in radar-lidar integrated cloud products and multi-Doppler wind retrievals, and optimizing radar sampling strategy using observing system simulation experiments. These applications demonstrate the application of CR-SIM as a virtual observatory operator on high-resolution model output for a consistent comparison between model results and observations to aid interpretation of the differences and improve understanding of the representativeness errors due to the sampling limitations of the ground-based measurements. CR-SIM is licensed under the GNU GPL package and both the software and the user guide are publicly available to the scientific community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Large Area Transfer of Bismuth‐Based Layered Oxide Thin Films Using a Flexible Polymer Transfer Method

Magnetic and ferroelectric oxide thin films have long been studied for their applications in electronics, optics, and sensors. The properties of these oxide thin films are highly dependent on the film growth quality and conditions. To maximize the film quality, epitaxial oxide thin films are frequently grown on single-crystal oxide substrates such as strontium titanate (SrTiO 3 ) and lanthanum aluminate (LaAlO 3 ) to satisfy lattice matching and minimize defect formation. However, these single-crystal oxide substrates cannot readily be used in practical applications due to their high cost, limited availability, and small wafer sizes. One leading solution to this challenge is film transfer. In this demonstration, a material from a new class of multiferroic oxides is selected, namely bismuth-based layered oxides, for the transfer. A water-soluble sacrificial layer of Sr 3 Al 2 O 6 is inserted between the oxide substrate and the film, enabling the release of the film from the original substrate onto a polymer support layer. The films are transferred onto new substrates of silicon and lithium niobate (LiNbO 3 ) and the polymer layer is removed. These substrates allow for the future design of electronic and optical devices as well as sensors using this new group of multiferroic layered oxide films.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Self-contained, automated, long-term sensor system for monitoring of soil and water nutrients in fields

An automated, fieldable ion-selective sensor system for frequent detection of nutrients in soils or water is set forth. In one aspect, an integrated small form-factor housing includes a battery, processor, a fluid manipulation unit and reservoirs, and a chemical species detection cell. A flow-through sampling head can be connected to the detection cell and a waste reservoir by flexible tubing sealingly connected at opposite ends of the tube. In one aspect, improved performance of the ion-selective sensor includes adding an ion-to-electron transfer interlayer between an ion-selective membrane and its working electrode. In one aspect, the sensor is solid-state and uses printed polymeric composite of POT-MoS$_{2}$. The use of a porous tube for a sampling head and fluid connection at opposite ends allows not only fluid to be removed from the head to the detection cell for measurement but also flow in an opposite direction and out to a waste reservoir to clean and reset for a next sample measurement.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Upgrade of the gated laser entrance hole imager G-LEH-2 on the National Ignition Facility

A major upgrade has been implemented for the ns-gated laser entrance hole imager on the National Ignition Facility (NIF) to obtain high-quality data for Hohlraum physics study. In this upgrade, the single “Furi” hCMOS sensor (1024 × 448 pixel arrays with two-frame capability) is replaced with dual “Icarus” sensors (1024 × 512 pixel arrays with four-frame capability). Both types of sensors were developed by Sandia National Laboratories for high energy density physics experiments. With the new Icarus sensors, the new diagnostic provides twice the detection area with improved uniformity, wider temporal coverage, flexible timing setup, and greater sensitivity to soft x rays (<2 keV). These features, together with the fact that the diagnostic is radiation hardened and can be operated on the NIF for high neutron yield deuterium–triterium experiments, enable significantly greater return of data per experiment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Versatile multi-energy hard x-ray camera to study confined and unconfined fast electron dynamics and anisotropies (Invited)

A powerful and flexible hard x-ray (HXR) camera has been recently installed and tested on the WEST tokamak (CEA, France) in collaboration with the Princeton Plasma Physics Laboratory. The diagnostic is a pinhole camera fielded with a 2D pixel detector equipped with a 1 mm thick CdTe sensor. The novelty of this diagnostic technique is the detector’s capability of adjusting the threshold energy at the pixel level. This innovation provides great flexibility in the energy configuration, allowing simultaneous space, energy, and time resolved x-ray measurements. The novel camera has been used to measure the core radiation from non-Maxwellian (fast) electrons accelerated by Lower Hybrid (LH) waves and also the beam–target emission of tungsten in the divertor region produced by fast electron losses interacting with the target. In addition, anisotropic hard x-ray emission has been detected for the first time at the WEST core and edge plasma, with opposite toroidal intensity trends. Finally, experimental vertical and toroidal HXR profiles have been successfully reproduced with the LH code LUKE.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Test and Validate Distributed Coaxial Cable Sensors for in situ Condition Monitoring of Coal-Fired Boiler Tubes

This project aims to test, validate, and advance the technology readiness level (from TRL5 to TRL7) of a novel low-cost distributed stainless-steel/ceramic coaxial cable sensing (SSC-CCS) technology for in situ monitoring of the boiler tube temperature in existing coal-fired power plants. The novel SSC-CCS sensing technology and associated condition-based monitoring (CBM) software to be demonstrated in this project will lead to an improved understanding of the boiler tube failure mechanisms and a prognostic system to improve the overall performance, reliability, and flexibility of the nation’s coal-fired power plant fleet. A boiler tube monitoring system with distributed coaxial cable temperature sensors and a sensor acquisition system was constructed. The high-temperature coaxial cable sensor with a length of 1.3m was made by using a quartz tube (1mm inner diameter (ID) and 6mm outer diameter (OD)) to concentrically separate a 304 stainless-steel (SS) rod (1mm OD) and SS tube (7.94mm OD and 6.16mm ID). The sensor acquisition system includes a vector network analyzer (VNA), a radio frequency (RF) power amplifier, multiple switches and a USB hub. The distributed stainless-steel quartz coaxial cable sensor (SSQ-CCS) had a linear response to temperature with a resolution uncertainty of σ = 0.77℃. To withstand the harsh conditions of 3,300 steam pressures and 800℃ high temperatures, the sensor was shielded by a protective tube made of the same material as the boiler tube. The protection tube had an OD of 1.5 inches and a thickness of 0.25 inches. In the laboratory tests, the sensor showed good sensitivity and fast response. The drift was bounded between +0.33% and -0.67% during a test at 600℃ for 350 hours, indicating good stability of the sensor. A field test was conducted where four sensors were welded on four superheat tubes (SH-Ts) at a coal-fired power station over 400 days. Conventional thermocouples were welded to the superheater tubes alongside the coaxial cable sensors for the purpose of comparison. Two sensors were capable of distributed sensing, with three multiplexed sensing sections. The other two sensors were single section. During the 400-day test period, the power plant experienced startups and shutdowns. At the steady state operations, the temperature of the boiler tube is about 600℃ (1112°F). The sensors recorded the entire coal-firing processes (start-up, steady state, and shut-down) and the glitch event. A GSM modem and a Watchdog were added to the system to ensure reliable data recording. The GSM modem sent daily messages to plant managers and Clemson team to inform the status of the sensor system. If the system was not normally working, the Watchdog would reboot the system automatically. The new coaxial cable based distributed sensing technology has been proven to be successful in both laboratory and field tests. A comprehensive four-stage multi-physics computational framework has been developed to assist the design, optimization, installation, and operation of SSQ-CCS. With the consideration of various operation conditions, we predict the distributions of flue gas temperatures within coal-fired boilers, the temperature correlation between the boiler tube and SSQ-CCS, and the safety of SSQ-CCS. A conditional-based monitoring system is implemented as well. The computational framework developed in this work can guide the future operation of coal-fired plants and other power plants for the safety prediction of boiler operations.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Glass 3D Printing of Microfluidic Pressure Sensor Interrogated by Fiber-Optic Refractometry

This letter reports a novel fused silica microfluidic device with pressure sensing capability that is fabricated by integrated additive and subtractive manufacturing (IASM) method. The sensor consists of a capillary and a 3D printed glass reservoir, where the reservoir volume change under pressure manifests liquid level deviation inside the capillary, thus realizing the conversion between small pressure change into large liquid level variation. Thanks to the design flexibility of this unique IASM method, the proposed microfluidic device is fabricated with liquid-in-glass thermometer configuration, where the reservoir is sealed following a novel 3D printing assisted glass bonding process. And liquid level is interrogated by a fiber-optic sensor based on multimode interference (MMI) effect. This proposed microfluidic device is attractive for chemical and biomedical sensing because it is flexible in design, and maintains good chemical and mechanical stability, and adjustable sensitivity and range.

42 ENGINEERING↗
DOE OSTI2024

Single-atom materials boosting wearable orthogonal uric acid detection

Abstract Uric acid (UA) is a vital biomarker for the diagnosis and management of various health conditions, including cardiovascular diseases, gout, kidney disorders, metabolic syndrome, and wound healing. Despite significant advances in wearable sensor technology, challenges persist in developing wearable sensors that are capable of maintaining high sensitivity, selectivity, and stability. In this study, we present an epidermal sensing platform enhanced with single-atom materials (SAMs) designed for flexible and orthogonal electrochemical detection of UA. We designed and synthesized an SAM with Fe-N 5 active sites to boost the electrochemical sensing signals, integrating it with laser-engraved graphene (LEG) to fabricate a wearable SAM-based UA patch sensor. This design provides superior UA detection performance compared to sensors based on conventional nanomaterials. In addition, we enhanced the detection accuracy and range by using an orthogonal approach that combines direct oxidation through differential pulse voltammetry (DPV) along with parallel biocatalytic amperometric detection. The resulting SAM-based UA orthogonal sensor patch demonstrated exceptional performance in wearable applications through tests measuring sweat UA levels in subjects before and after consuming a purine-rich diet. Graphical Abstract

Ding, Shichao↗
DOE OSTI2023

Aerosol‐Jet‐Printable Covalent Organic Framework Colloidal Inks and Temperature‐Sensitive Nanocomposite Films

Abstract With molecularly well‐defined and tailorable 2D structures, covalent organic frameworks (COFs) have emerged as leading material candidates for chemical sensing, storage, separation, and catalysis. In these contexts, the ability to directly and deterministically print COFs into arbitrary geometries will enable rapid optimization and deployment. However, previous attempts to print COFs have been restricted by low spatial resolution and/or post‐deposition polymerization that limits the range of compatible COFs. Here, these limitations are overcome with a pre‐synthesized, solution‐processable colloidal ink that enables aerosol jet printing of COFs with micron‐scale resolution. The ink formulation utilizes the low‐volatility solvent benzonitrile, which is critical to obtaining homogeneous printed COF film morphologies. This ink formulation is also compatible with other colloidal nanomaterials, thus facilitating the integration of COFs into printable nanocomposite films. As a proof‐of‐concept, boronate‐ester COFs are integrated with carbon nanotubes (CNTs) to form printable COF‐CNT nanocomposite films, in which the CNTs enhance charge transport and temperature sensing performance, ultimately resulting in high‐sensitivity temperature sensors that show electrical conductivity variation by 4 orders of magnitude between room temperature and 300 °C. Overall, this work establishes a flexible platform for COF additive manufacturing that will accelerate the incorporation of COFs into technologically significant applications.

2D materials↗
DOE OSTI2021

Creation of a prototype biomimetic fish to better understand impact trauma caused by hydropower turbine blade strikes

Biomimetic model organisms could be useful surrogates for live animals in many applications if the models have sufficient biofidelity. One such application is for use in field and laboratory tests of fish mortality associated with passage through hydropower turbines. Laboratory trials suggest that blade strikes are especially injurious and often causes mortality when fish are struck by thinner blades moving at higher velocities. Dose-response relationships have been created from these data, but the exact relationship between fish mortality and the actual forces enacted on fish during simulated blade strike testing remains unknown. Here, we describe the methods used to create a prototype biomimetic model fish composed of ballistic gelatin and covered with a surrogate skin to better approximate the biomechanical properties of a fish body. Frozen fish were scanned with high-fidelity laser scanners, and a 3D-printed, reusable mold was created from which to cast our gelatin model. Computed tomography scan data, imaged directly or taken from online data repositories, were also successfully used to create CAD models for use in additive manufacturing of molds. One 3-axis accelerometer was embedded into the gelatin to compare accelerometer data to dose-response data from previous laboratory research on live fish. The resulting model ( i.e. , Gelfish) had a statistically indistinguishable tissue durometer to that of real fish tissue and preliminary blade strike impact testing suggested its overall flexibility was similar to that of live fish. Gelfish was designed with biofidelity as its guiding principle and our results suggest initial experimentation was successful. Future research will include replication of initial Gelfish test results, quantitative measurement of model flexibility relative to real fish, and inclusion of surrogate skeletal structures to enhance biofidelity. Use of more sophisticated sensors would also better quantify the physical forces of blade strike impact and help determine how said forces correlate with rates of mortality observed during tests on live fish.

36 MATERIALS SCIENCE↗
DOE OSTI2020

INTEGRATION OF FLEX EQUIPMENT AND OPERATOR ACTIONS IN PLANT FORCE-ON-FORCE MODELS WITH DYNAMIC RISK ASSESSMENT

The overall operation and maintenance cost to protect nuclear power plants accounts for approximately 7% of the total cost of power generation, with labor accounting for half of this cost. In the current research, from interaction with utilities and other stakeholders, it was determined that physical security forces account for nearly 20% of the entire workforce at several nuclear power plants. Labor costs continue to rise in the U.S., so any measures to reduce the cost of operating a nuclear power plant will need to include a reduction in labor. The physical security pathway within the DOE’s Light Water Reactor Sustainability program aims to lower the cost of physical security through directed research into modeling and simulation, application of advanced sensors or deployment of advanced weapons. This report presents a modeling and simulation framework for integrating Diverse and Flexible Mitigation Capability (FLEX) portable equipment performance with Force on Force models of a plant’s physical security posture. The generic framework is described in detail, followed by a case study of modeling an adversarial attack aimed at causing a radiological release by sabotaging the plant’s power supply and its ultimate heat sink capabilities at a hypothetical nuclear power plant. Two different FLEX deployment strategies, series and parallel, are modeled with distinct timelines. The results of the adversarial attack modeled in a commercial Force on Force tool are integrated with the FLEX deployment model in INL’s dynamic modeling tool EMRALD. Monte Carlo simulation is used to model the distribution of the timeline in FLEX deployment strategies. The results demonstrate that, even in the extreme case of a successful adversarial attack, deployment of FLEX equipment can result in a significantly high likelihood of preventing radiological release. The modeling and simulation framework integrating FLEX equipment with Force on Force models enables the nuclear power plants to credit FLEX portable equipment in the plant security posture, resulting in an efficient and optimized physical security.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Additive manufacturing and applications of nanomaterial-based sensors

Nanoscale materials possess distinct physical and chemical attributes including size-dependent properties, quantum confinement, high surface-to-volume ratio, and superior catalytic activity. These unique qualities enable sensors with high sensitivity, robustness, and fast time response. As the emergence of the Internet of Things (IoT) demands increased production of sensors, it also provides an impetus for concentrated nanomaterial-based sensor research. Meanwhile, additive manufacturing (AM) of nanomaterial-based sensors is critical to bridge the gap between one-off, lab-scale fabrication and cost-effective, industrial-scale production with high reproducibility. By applying the design flexibility and cost savings of AM techniques, a new generation of nanomaterial-based sensing platforms can be integrated with IoT devices in the consumer space. Furthermore, emergent research in human-machine interfaces, food safety, and point-of-care diagnostics will be expedited by the development of sensors that can be printed with irregular form factors. In this Review, the relative strengths and weaknesses of printed sensor systems based on zero-, one-, and two-dimensional nanomaterials are discussed. In addition, sensors enabled by printable soft nanomaterials, heterostructures, and nanocomposites are surveyed due to their synergistic advantages for wearable healthcare monitoring and soft robotics. Lastly, a roadmap for the next decade of research on this topic is provided.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Yeast Nup84-Nup133 complex structure details flexibility and reveals conservation of the membrane anchoring ALPS motif

The hallmark of the eukaryotic cell is the complex endomembrane system that compartmentalizes cellular functions. Transport into and out of the nucleus occurs through the nuclear pore complex (NPC). The heptameric Nup84 or Y complex is an essential scaffolding component of the NPC. Here we report two nanobody-bound structures: the full-length Nup84-Nup133 C-terminal domain complex and the Nup133 N-terminal domain, both from S. cerevisiae. Together with previously published structures, this work enables the structural description of the entire 575 kDa Y complex from one species. The structure of Nup84-Nup133CTD details the high flexibility of this dimeric unit of the Y complex. Further, the Nup133NTD contains a structurally conserved amphipathic lipid packing sensor motif, confirmed by liposome interaction studies. The presented structures reveal important details about the function of the Y complex that affect our understanding of NPC structure and assembly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

First Annual Report on Development of Microwave Resonant Cavity Transducer for Fluid Flow Sensing: Development of Sensor Performance Model of Microwave Cavity Flow Meter for Advanced Reactor High Temperature Fluids

We are investigating a microwave cavity-based transducer for in-core high-temperature fluid flow sensing in molten salt cooled reactors (MSCR) and sodium fast reactors (SFR). This sensor is a hollow metallic cylindrical cavity, which can be fabricated from stainless steel, and as such is expected to be resilient to radiation, high temperature and corrosive environment of MSCR and SFR. The principle of sensing consists of making one wall of the cylindrical cavity flexible enough so that dynamic pressure, which is proportional to fluid velocity, will cause membrane deflection. Membrane deflection causes cavity volume change, which leads to a shift in the resonant frequency. Feasibility of the sensor was initially investigated with analytical derivations and with COMSOL RF Module computer simulations of resonant frequency spectral shift due to uniform load. We also investigated the mechanical integrity of the flowmeter’s membrane through analytical modelling and COMSOL Structural Mechanics Module computer simulations. Both the analytic model and COMSOL model showed that maximum stresses on the plate, which are at the radial boundary of the plate, are three orders of magnitude smaller than the material’s yield strength and ultimate tensile strength. This indicates that the sensor is at a low risk of mechanical failure. Using results from models, we have developed an initial design for a microwave K-band sensor. A cylindrical resonator prototype was fabricated from brass for the initial tests. The external dimensions of the cavity are matched to the flange of a standard WR-42 waveguide. Microwave field is coupled into the resonant cavity through a subwavelength-size aperture. A test article was developed consisting of a piping Tee with a bulkhead WR-42 microwave waveguide installed in a leak-proof assembly. A microwave waveguide circulator was installed in the setup to suppress the effect of reflections at the cavity entrance by increasing the isolation between the input and the output port. Preliminary spectral characterization of cavity spectral response was performed with a portable PXIe chassis microwave VNA with a custom GUI. Preliminary dry tests of the transducer response were conducted with a set of calibrated weights. Transducer frequency shift was shown to be monotonically increasing with increasing pressure. The next steps will involve investigation of the transducer performance for water flow sensing.

42 ENGINEERING↗