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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Influence of Vane Trailing Edge Flow on the Formation of Cavity Cells and Rim Sealing

Abstract Hot gas ingestion into the turbine rim seal cavity is an important concern for engine designers. To prevent ingestion, rim seals use high-pressure purge flow; however, the penalty is that excessive use of the purge flow decreases engine thermal efficiency. In this paper, a one-stage turbine operating at engine-representative conditions was used to study the effect of steady and time-resolved under-platform cavity temperatures and pressures across a range of coolant flowrates in the presence of vane trailing edge (VTE) flow. This study correlates time-resolved pressure with time-resolved temperature to identify primary frequencies driving ingestion. At certain flowrates, the time-resolved pressures are out of phase with the temperatures, indicating ingestion. Measurements from high-frequency response pressure sensors in the rim seal and vane platform were also used to determine rotational speed and quantity of large-scale structures (cells). In a parallel effort, a computational model using Unsteady Reynolds-averaged Navier–Stokes (URANS) was applied to determine swirl ratio in the rim seal cavity and time-resolved rim sealing effectiveness. The experimental results confirm that at low purge flowrates, the VTE flow influences the unsteady flow field by decreasing pressure unsteadiness in the rim seal cavity. Results show an increase in purge flow increases the number of unsteady large-scale structures in the rim seal and decreases their rotational speed. However, VTE flow was shown to not significantly change the cell speed and count in the rim seal. Simulations point to the importance of the large-scale cell structures in influencing rim sealing unsteadiness, which is not captured in current rim sealing predictive models.

Engineering↗
NASA NTRS2005

Implementing Recommendations of the Columbia Accident Investigation Board - Development of on-Orbit RCC Thermography

One of NASA s Space Shuttle Return-to-Flight (RTF) efforts has been to develop thermography for the on-orbit inspection of the Reinforced Carbon Carbon (RCC) portion of the Orbiter Wing Leading Edge (WLE). This paper addresses the capability of thermography to detect cracks in RCC by using in-plane thermal gradients that naturally occur on-orbit. Crack damage, which can result from launch debris impact, is a detection challenge for other on-orbit sensors under consideration for RTF, such as the Intensified Television Camera and Laser Dynamic Range Imager. We studied various cracks in RCC, both natural and simulated, along with material characteristics, such as emissivity uniformity, in steady-state thermography. Severity of crack, such as those likely and unlikely to cause burn through were tested, both in-air and in-vacuum, and the goal of this procedure was to assure crew and vehicle safety during re-entry by identification and quantification of a damage condition while on-orbit. Expected thermal conditions are presented in typical shuttle orbits, and the expected damage signatures for each scenario are presented. Finally, through statistical signal detection, our results show that even at very low in-plane thermal gradients, we are able to detect damage at or below the threshold for fatality in the most critical sections of the WLE, with a confidence exceeding 1 in 10,000 probability of false negative.

Ottens, Brian↗
NASA NTRS2005

Implementing Recommendations of the Columbia Accident Investigation Board: Development of On-Orbit IR Thermography

One of NASA's Space Shuttle Return-to-Flight (RTF) efforts has been to develop thermography for the on-orbit inspection of the Reinforced Carbon Carbon (RCC) portion of the Orbiter Wing Leading Edge (WLE). This paper addresses the capability of thermography to detect cracks in RCC by using in-plane thermal gradients that naturally occur on-orbit. Crack damage, which can result from launch debris impact, is a detection challenge for other on-orbit sensors under consideration for RTF, such as the Intensified Television Camera and Laser Dynamic Range Imager. We studied various cracks in RCC, both natural and simulated, along with material characteristics, such as emissivity uniformity, in steady-state thermography. Severity of crack, such as those likely and unlikely to cause burn through were tested, both in-air and in-vacuum, and the goal of this procedure was to assure crew and vehicle safety during reentry by identification and quantification of a damage condition while on-orbit. Expected thermal conditions are presented in typical shuttle orbits, and the expected damage signatures for each scenario are presented. Finally, through statistical signal detection, our results show that even at very low in-plane thermal gradients, we are able to detect damage at or below the threshold for fatality in the most critical sections of the WLE, with a confidence exceeding 1 in 10,000 probability of false negative.

Ottens, Brian P.↗
NASA NTRS2019

Networked Array Recorder (NeAR) Microphones for Field-Deployed Phased Arrays

An innovative edge-computing concept known as NeAR (Networked Array Recorder) has been developed to provide enhancements to existing field-deployable microphone phased arrays utilized for aeroacoustic flyover measurements of airframe and propulsive noise sources. The proposed system allows for the elimination of multiple miles of sensor wiring in an array installation, thereby improving the scalability of the overall system, increasing the fault-tolerance of the hardware, and reducing the effort needed to build-up and tear-down an array in the field. A demonstration of the NeAR concept was performed at Edwards Air Force Base in California in March – April, 2018, where twelve individual NeAR microphones were deployed as a piggyback on a conventional phased array system deployed for airframe noise flyover testing. The microphones operated successfully during the demonstration with good time history and spectral correlations shown between the NeAR units and conventional microphones located nearby in the array. The NeAR concept has spinoffs beyond its use for phased arrays, including applications in remote environmental sensing and noise monitoring.

Cull.iton, William G.↗
DOE OSTI2022

Design, Construction, and Field Validation of a Blown-In Fiberglass Wall System in a Cold, Wet, and Windy Climate

In the Native Village of Tununak, located on Nelson Island in Southwest Alaska,buildings are exposed to wind-driven rain and snow throughout the year. The Cold Climate Housing Research Center (CCHRC) and Knauf Insulation partnered with the community in 2018 to design a residence for a public safety officer. Construction began in fall 2021 and is scheduled to conclude in summer 2022. The house will use integrated trusses with floor, attic, and wall cavities filled with blown-in fiberglass insulation. Hygrothermal models of the building envelope system demonstrate that the high ambient moisture load will wet the outer edges of the insulation annually regardless of the extent and integrity of exterior weather sealing measures; blown-in fiberglass is expected to be more resilient to this wetting than blown-in cellulose. To verify this, researchers will embed temperature, relative humidity, and moisture sensors in the two windward walls of the house to monitor the ability of the blown-in fiberglass insulation to dry out after wetting events that may have occurred during the transport of the insulation to the building site, storage of the insulation on site, construction process, or after installation in the wall. Sensors will remain in place for two years,documenting the wall's performance over time and verifying the design's potential for use in buildings located in climates where the chance for moisture damage is high. Here, we describe the wall system , design criteria, and the results from the hygrothermal modeling. We share details on the monitoring system's components and the planned management and analysis of data. Finally, we explain how the experiences and data from this project will inform future builds in similar locations.

building design↗
DOE OSTI2012

The Institute of Geophysics and Planetary Physics adds Science of Signatures and a new Deputy to its portfolio

The Institute of Geophysics and Planetary Physics (IGPP) is adding the Science of Signatures to it’s portfolio. It’s new title, the Institute of Geophysics, Planetary Physics and Signatures (IGPPS) is in recognition that Science of Signatures is a LANL strategic science pillar, and is a natural fit with the IGPPS goal of promoting and supporting high quality, cutting-edge science in the areas of astrophysics, space physics, solid planetary geoscience, and climate science. IGPPS Director Dogliani states that, “One cannot fully understand natural phenomena without conducting field measurements of key events.” Beginning in FY13, IGPPS will consider proposals that investigate and develop signature and sensor science for potential use in understanding our evolving climate, geoscience, planetary space and cosmology phenomena.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Spatial Distribution of Resonance in the Velocity Field for Transonic Flow over a Rectangular Cavity

Pulse-burst particle image velocimetry (PIV) has been used to acquire time-resolved data at 37.5 kHz of the flow over a finite-width rectangular cavity at Mach 0.8. Power spectra of the PIV data reveal four resonance modes that match the frequencies detected simultaneously using high-frequency wall pressure sensors but whose magnitudes exhibit spatial dependence throughout the cavity. Spatio-temporal cross-correlations of velocity to pressure were calculated after bandpass filtering for specific resonance frequencies. Cross-correlation magnitudes express the distribution of resonance energy, revealing local maxima and minima at the edges of the shear layer attributable to wave interference between downstream- and upstream-propagating disturbances. Turbulence intensities were calculated using a triple decomposition and are greatest in the core of the shear layer for higher modes, where resonant energies ordinarily are lower. Most of the energy for the lowest mode lies in the recirculation region and results principally from turbulence rather than resonance. Together, the velocity-pressure cross-correlations and the triple-decomposition turbulence intensities explain the sources of energy identified in the spatial distributions of power spectra amplitudes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy’s National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI’s Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: 1. Run in real-time on the edge (≥ 12 Hz) 2. Classification: Achieve less than 5% false positive detection 3. Classification: Achieve ≥ 95% methane plume detection rate 4. Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗
DOE OSTI2022

Peak Prediction Using Multi Layer Perceptron (MLP) for Edge Computing ASICs Targeting Scientific Applications

High data rate detectors play an integral part in scientific research and their development is actively pursued at High Energy Physics (HEP) facilities around the world. Edge Machine Learning (ML) offers the ability to reduce data rates by integrating ML algorithms into Application Specific Integrated Circuits (ASICs) on the front end electronics. In this work, we explore a set of neural network architectures for predicting the peak amplitudes in the detector's sensor response. We have designed and synthesized several MLP based neural networks comparing their inference accuracy, power consumption, and area targeting for minimal latency. The neural networks are synthesized in a commercial 65nm process. The effect of quantizing the network's weights and biases on hardware performance and area is reported. We also conduct design space exploration to compare between design alternatives

47 OTHER INSTRUMENTATION↗
NASA NTRS1988

Millimeter-wave Sensor Image Enhancement

Images of an airborne scanning radiometer operating at a frequency of 98 GHz were analyzed. The mm wave images were obtained using the JPL mm wave imaging sensor. The goal was to enhance the information content of these images and make their interpretation easier for human analysis. A visual interpretative approach was used for information extraction from the images. This included application of nonlinear transform techniques for noise reduction and for color, contrast, and edge enhancement. Results of the techniques on selected mm wave images are shown.

Wilson, William J.↗
DOE OSTI2012

High resolution detection and excitation of resonant magnetic perturbations in a wall-stabilized tokamak

We report high-resolution detection of the 3D plasma magnetic response of wall-stabilized tokamak discharges in the High Beta Tokamak-Extended Pulse [T. H. Ivers et al., Phys. Plasmas 3, 1926 (1996)] device. A new adjustable conducting wall has been installed on HBT-EP made up of 20 independent, movable, wall segments instrumented with three distinct sets of 40 modular coils that can be independently driven to generate a wide variety of magnetic perturbations. High-resolution detection of the plasma response is made with 216 poloidal and radial magnetic sensors that have been located and calibrated with high-accuracy. Static and dynamic plasma responses to resonant and non-resonant magnetic perturbations are observed through measurement of the step-response following a rapid change in the toroidal phase of the applied perturbations. Biorthogonal decomposition of the full set of magnetic sensors clearly defines the structures of naturally occurring external kinks as being composed of independent m/n = 3/1 and 6/2 modes. Resonant magnetic perturbations were applied to discharges with pre-existing, saturated m/n = 3/1 external kink mode activity. This m/n = 3/1 kink mode was observed to lock to the applied perturbation field. During this kink mode locked period, the plasma resonant response is characterized by a linear, a saturated, and a disruptive plasma regime dependent on the magnitude of the applied field and value of the edge safety factor and plasma rotation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Development of a Freeze-Dried CRISPR-Cas12 Sensor for Detecting Wolbachia in the Secondary Science Classroom

Training the future synthetic biology workforce requires the opportunity for students to be exposed to biotechnology concepts and activities in secondary education. Detecting Wolbachia bacteria in arthropods using polymerase chain reaction (PCR) has become a common way for secondary students to investigate and apply recombinant DNA technology in the science classroom. Despite this important activity, cutting-edge biotechnologies such as clustered regularly interspaced short palindromic repeat (CRISPR)-based diagnostics have yet to be widely implemented in the classroom. To address this gap, we present a freeze-dried CRISPR-Cas12 sensing reaction to complement traditional recombinant DNA technology education and teach synthetic biology concepts. The reactions accurately detect Wolbachia from arthropod-derived PCR samples in under 2 h and can be stored at room temperature for over a month without appreciable degradation. Here, the reactions are easy-to-use and cost less than $40 to implement for a classroom of 22 students including the cost of reusable equipment. We see these freeze-dried CRISPR-Cas12 reactions as an accessible way to incorporate synthetic biology education into the existing biology curriculum, which will expand biology educational opportunities in science, technology, engineering, and mathematics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

A reversible strain-induced electrical conductivity in cup-stacked carbon nanotube

We have used in-situ current-voltage measurements of cup-stacked carbon nanotubes (CSCNTs) to establish a reversible strain induced (compressive bending) semiconducting to metallic behavior. The corresponding electrical resistance decreases by two orders of magnitude during the process, and reaches values comparable to those of highly crystalline multi-walled carbon nanotube (MWCNT) and graphite. Joule heating experiments on the same CSCNTs showed that the edges of individual cups merge to form loops induced by the heating process. The resistance of these looped CSCNTs was close to that of highly deformed CSCNTs (and crystalline MWCNTs), thus suggesting that a similar conduction mechanism took place in both cases. Using a combination of molecular dynamics and first-principles calculations based on density functional theory, we conclude that an edge-to-edge interlayer transport mechanism results in conduction channels at the compressed side of the CSCNTs due to electronic density overlap between individual cups, thus making CSCNT more conducting. This strain-induced CSCNT semiconductor to metal transition could potentially be applied to enabling functional composite materials (e.g. mechanical sensors) with enhanced and tunable conducting properties upon compression.

Hayashi, T↗
DOE OSTI2012

Multi-energy x-ray imaging and sensing for diagnostic and control of the burning plasma

New diagnostic and sensor designs are needed for future burning plasma (BP) fusion experiments, having good space and time resolution and capable of prolonged operation in the harsh BP environment. We evaluate the potential of multi-energy x-ray imaging with filtered detector arrays for BP diagnostic and control. Experimental studies show that this simple and robust technique enables measuring with good accuracy, speed, and spatial resolution the T{sub e} profile, impurity content, and MHD activity in a tokamak. Applied to the BP this diagnostic could also serve for non-magnetic sensing of the plasma position, centroid, ELM, and RWM instability. BP compatible x-ray sensors are proposed using 'optical array' or 'bi-cell' detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Waveform processing using neural network algorithms on the front-end electronics

In a multi-channel radiation detector readout system, waveform sampling, digitization, and raw data transmission to the data acquisition system constitute a conventional processing chain. The deposited energy on the sensor is estimated by extracting peak amplitudes, area under pulse envelopes from the raw data, and starting times of signals or time of arrivals. However, such quantities can be estimated using machine learning algorithms on the front-end Application-Specific Integrated Circuits (ASICs), often termed as “edge computing”. Edge computation offers enormous benefits, especially when the analytical forms are not fully known or the registered waveform suffers from noise and imperfections of practical implementations. In this work, we aim to predict peak amplitude from a single waveform snippet whose rising and falling edges containing only 3 to 4 samples. We thoroughly studied two well-accepted neural network algorithms, Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN) by varying their model sizes. Further, to better fit front-end electronics, neural network model reduction techniques, such as network pruning methods and variable-bit quantization approaches, were also studied. By combining pruning and quantization, our best performing model has the size of 1.5 KB, reduced from 16.6 KB of its full model counterpart. It can reach mean absolute error of 0.034 comparing to that of a naive baseline of 0.135. Such parameter-efficient and predictive neural network models established feasibility and practicality of their deployment on front-end ASICs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Development and Implementation of Fault-Correction Algorithms in Fault Detection and Diagnostics Tools

A fault detection and diagnostics (FDD) tool is a type of energy management and information system that continuously identifies the presence of faults and efficiency improvement opportunities through a one-way interface to the building automation system and the application of automated analytics. Building operators on the leading edge of technology adoption use FDD tools to enable median whole-building portfolio savings of 8%. Although FDD tools can inform operators of operational faults, currently an action is always required to correct the faults to generate energy savings. A subset of faults, however, such as biased sensors, can be addressed automatically, eliminating the need for staff intervention. Automating this fault “correction” can significantly increase the savings generated by FDD tools and reduce the reliance on human intervention. Doing so is expected to advance the usability and technical and economic performance of FDD technologies. This paper presents the development of nine innovative fault auto-correction algorithms for Heating, Ventilation, and Air Conditioning pi(HVAC) systems. When the auto-correction routine is triggered, it overwrites control setpoints or other variables to implement the intended changes. It also discusses the implementation of the auto-correction algorithms in commercial FDD software products, the integration of these strategies with building automation systems and their preliminary testing.

field testing↗
NASA NTRS1989

Millimeter-wave sensor image enhancement

Images from an airborne, scanning radiometer operating at a frequency of 98 GHz have been analyzed. The millimeter-wave images were obtained in 1985-1986 using the JPL millimeter-wave imaging sensor. The goal of this study was to enhance the information content of these images and make their interpretation easier. A visual-interpretative approach was used for information extraction from the images. This included application of nonlinear transform techniques for noise reduction and for color, contrast, and edge enhancement. Results of using the techniques on selected millimeter-wave images are discussed.

Wilson, William J.↗
NASA NTRS2016

Measurements in a Transitioning Cone Boundary Layer at Freestream Mach 3.5

An experimental study was conducted in the Supersonic Low-Disturbance Tunnel to investigate naturally-occurring instabilities in a supersonic boundary layer on a 7 deg half- angle cone. All tests were conducted with a nominal freestream Mach number of M(sub infinity) = 3:5, total temperature of T(sub 0) = 299:8 K, and unit Reynolds numbers of Re(sub infinity) x 10(exp -6) = 9:89, 13.85, 21.77, and 25.73 m(exp -1). Instability measurements were acquired under noisy- ow and quiet- ow conditions. Measurements were made to document the freestream and the boundary-layer edge environment, to document the cone baseline flow, and to establish the stability characteristics of the transitioning flow. Pitot pressure and hot-wire boundary- layer measurements were obtained using a model-integrated traverse system. All hot- wire results were single-point measurements and were acquired with a sensor calibrated to mass ux. For the noisy-flow conditions, excellent agreement for the growth rates and mode shapes was achieved between the measured results and linear stability theory (LST). The corresponding N factor at transition from LST is N 3:9. The stability measurements for the quiet-flow conditions were limited to the aft end of the cone. The most unstable first-mode instabilities as predicted by LST were successfully measured, but this unstable first mode was not the dominant instability measured in the boundary layer. Instead, the dominant instabilities were found to be the less-amplified, low-frequency disturbances predicted by linear stability theory, and these instabilities grew according to linear theory. These low-frequency unstable disturbances were initiated by freestream acoustic disturbances through a receptivity process that is believed to occur near the branch I locations of the cone. Under quiet-flow conditions, the boundary layer remained laminar up to the last measurement station for the largest Re1, implying a transition N factor of N greater than 8:5.

King, Rudolph A.↗