First-principle SiPM Characterization to Enable Radiation Detection in Harsh Environments.
Abstract not provided.
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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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Abstract not provided.
Nearly all high temperature heat exchangers are currently constructed from metallic alloys that can have good capability but are limited to hot inlet temperatures in the range of 1,200 to 1,400 °F. In general, increasing the hot inlet temperature will improve existing application cycles to operate more efficiently, and it will enable new application cycles to be viable that otherwise would not be. The objective of this project was to mature the technologies associated with the development of a ceramic-class heat exchanger that would significantly increase the operating temperature to 1,600 °F and above. The approach taken was to use Glass-Ceramic Matrix Composite (G-CMC) material and to fabricate coupon-scale tube sheet heat exchangers (HXs) to identify risks, refine details of the process and develop a pathway for this novel approach.
This presentation covers development of single crystal fibers and distributed temperature sensing system given at the NRC workshop.
Renewable energy technologies used for electric vehicles and wind turbines are heavily reliant upon metals, such as rare earth elements, cobalt, lithium, and nickel. Indeed, there are 50 minerals that are currently considered “economically critical” by the 2022 United States Geological Survey. With anticipated global adoption of renewable energy technologies, producing sufficient metals to meet this demand presents a significant challenge, particularly due to the current monopolistic market for many of these metals. The production of metals from unconventional sources, such as coal utilization byproducts, is one of many promising strategies to boost domestic supply. However, sensitive, rapid, and inexpensive characterization technologies are needed to minimize production costs associated with metals prospecting and processing. Photoluminescence-based sensing techniques are particularly intriguing due to their potential for low cost and portability, coupled with high sensitivity and selectivity. This presentation focuses on the development of high-performance sensing materials for a range of critical metals, including metal-organic frameworks capable of sensitizing detection of parts-per-billion concentrations of six different rare earth elements, nanoparticles that can detect down to 600 parts-per-billion levels of cobalt, and thin films that sense aluminum down to 120 parts-per-billion. These materials are highly selective, capable of withstanding low pH conditions, and provide a response within minutes. Importantly, each sensing material is integrated with a custom-built, fully portable fiber-optic spectrometer for potential field deployment, providing significant cost savings over commercial instruments, along with potential advantages such as material regeneration for use across multiple sensing cycles and solvent removal for enhanced emission signal. These results highlight the exciting potential of luminescence platforms as cost-effective alternatives for metals characterization.
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Summarizes ferroelectric work at Sandia
Microgrid implementation can help improve electrical service, reliability, and resilience for localized communities. However, they may be susceptible to damage from natural disasters and extreme weather events, which often coincide with times of greater community dependence on microgrids due to likely increased vulnerability of equipment on the main grid. Microgrid equipment can be protected against these hazards through various hardening techniques. The selection of hardening mitigations may depend on the actual risk of the hazard in the specific location and for the specific type of system, as well as cost and feasibility factors. This report summarizes a framework that can be used to characterize risk to a microgrid system from a list of natural hazards enumerated by FEMA. We also describe hardening techniques and mitigations that can be used for specific energy generation, storage, loads, and power delivery elements within a microgrid.
Abstract not provided.
Accurate and high-speed transient surface-temperature measurements of combustion devices including internal combustion (IC) engines, gas turbines, etc., provide validation targets and boundary conditions for computational fluid dynamics models, and are broadly relevant to technology advancements such as performance improvement and emissions reduction. Development and demonstration of a multi-infrared-channel pyrometry-based optical instrument for high-speed surface-temperature measurement is described. The measurement principle is based on multi-spectral radiation thermometry (MRT) and uses surface thermal radiation at four discrete spectral regions and a corresponding emissivity model to obtain surface temperature via non-linear least squares (NLLS) optimization. Rules of thumb for specifying the spectral regions and considerations to avoid interference with common combustion products are developed; the impact of these along with linear and non-linear MRT analysis are assessed as a function of temperature and signal-to-noise ratio. A multi-start method to determine the MRT-solution global optimum is described and demonstrated. The resulting multi-channel transient pyrometry instrument is described along with practical considerations including optical-alignment drift, matching intra-channel transient response, and solution-confidence indicators. The instrument demonstrated excellent >97% accuracy and >99% 2-sigma precision over the 400–800 °C range, with ~20 µs (50 kHz, equivalent to 0.2 cad at 2000 RPM IC-engine operation) transient response in the bench validation.
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Penicillium mutant chemical stress tolerance in boric acid and potassium chloride selective media, studying carbohydrate and inosine-5-phosphate effects on growth rate
The goal is to develop an approach to automating the alignment and adjustment of optical measurement, visualization, inspection, and control systems. Classical controls, expert systems, and neural networks are three approaches to automating the alignment of an optical system. Neural networks were chosen for this project and the judgements that led to this decision are presented. Neural networks were used to automate the alignment of the ubiquitous laser-beam-smoothing spatial filter. The results and future plans of the project are presented.
The status of work at NASA Glenn Research Center to develop a minimally intrusive integrated sensor to provide realtime measurement of strain, heat flux and flow in high temperature environments is presented in this paper. The sensor can be beneficial as a single package to characterize multiple stress and strain modes simultaneously on materials and components during engine development and validation. A major technical challenge is to take existing individual gauge designs and modify them into one integrated thin film sensor. Ultimately, the goal is to develop the ability to deposit the sensors directly onto internal engine parts or on a small thin substrate that can be attached to engine components. Several prototype sensors constructed of platinum, platinum-rhodium alloy, and alumina on constant-strain alumina beams have been built and bench-tested. The technical challenges of the design. construction, and testing are discussed. Data from the preliminary testing of the sensor array is presented. The future direction for the sensor development is discussed as well.
The status of work to develop a reliable high temperature dielectric thin film for use with thin film sensors is presented. The use of thin films to electrically insulate thin film sensors on engine components minimizes the intrusiveness of the sensor and allows a more accurate measurement of the environment. A variety of insulating films were investigated for preventing electrical shorting caused by insulator failure between the sensor and the component. By alternating layers of sputtered high temperature ceramics, a sequence of insulating layers was devised that prevents pinholes from forming completely through the insulator and maintains high electrical resistivity at high temperatures. The major technical challenge remaining is to optimize the fabrication of the insulator with respect to composition to achieve a reliable high temperature insulating film. Data from the testing of various potentially insulating thin film systems is presented and their application to thin film sensors is also discussed.
Methods of bulk manufacturing high temperature sensor sub-assembly packages are disclosed and claimed. Sensors are sandwiched between a top cover and a bottom cover so as to enable the peripheries of the top covers, sensors and bottom covers to be sealed and bound securely together are disclosed and claimed. Sensors are placed on the bottom covers leaving the periphery of the bottom cover exposed. Likewise, top covers are placed on the sensors leaving the periphery of the sensor exposed. Individual sensor sub- assemblies are inserted into final packaging elements which are also disclosed and claimed. Methods of directly attach- ing wires or pins to contact pads on the sensors are disclosed and claimed. Sensors, such as pressure sensors and accelerometers, and headers made out of silicon carbide and aluminum nitride are disclosed and claimed. Reference cavities are formed in some embodiments disclosed and claimed herein where top covers are not employed.
This paper presents results of electromyographic-based (EMG-based) speech recognition on a small vocabulary of 15 English words. The work was motivated in part by a desire to mitigate the effects of high acoustic noise on speech intelligibility in communication systems used by first responders. Both an off-line and a real-time system were constructed. Data were collected from a single male subject wearing a fireghter's self-contained breathing apparatus. A single channel of EMG data was used, collected via surface sensors at a rate of 104 samples/s. The signal processing core consisted of an activity detector, a feature extractor, and a neural network classifier. In the off-line phase, 150 examples of each word were collected from the subject. Generalization testing, conducted using bootstrapping, produced an overall average correct classification rate on the 15 words of 74%, with a 95% confidence interval of [71%, 77%]. Once the classifier was trained, the subject used the real-time system to communicate and to control a robotic device. The real-time system was tested with the subject exposed to an ambient noise level of approximately 95 decibels.
The JPL-led CSP Consortium of enterprises representing government agencies and private companies has jointed together to pool in-kind resources for developing the quality and reliability of chip scale packages (CSPs) for a variety of projects.