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At least 127 records · Page 7

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.

03 NATURAL GAS↗

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↗

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: Run in real-time on the edge (≥ 12 Hz), Classification: Achieve less than 5% false positive detection, Classification: Achieve ≥ 95% methane plume detection rate, 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↗

In-situ gloveport glove leak tester

The invention provides a system for detecting leaks in glovebox gloves, the system having a first seal within a glovebox aperture; a second seal contacting exterior surfaces of a glovebox, wherein the exterior surfaces define a periphery of the aperture; a first fluid supply for circumferentially expanding the first seal against center facing surfaces of the aperture to a first pressure; a second fluid supply for inflating the glove to a second pressure; and a pressure gauge for detecting a pressure decrease of the second pressure. Also provided is an in situ method for detecting leaks in glove box gloves, the method having the steps of applying a radially directed force to inside surfaces of cuffs of the gloves to hermetically seal the gloves from the exterior of the glovebox, thereby establishing a seal; inflating the gloves to a pressure; and monitoring the pressure for any decrease in pressure.

42 ENGINEERING↗

NASA Hydrogen Research for Spaceport and Space Based Applications

The activities presented are a broad based approach to advancing key hydrogen related technologies in areas such as hydrogen production, distributed sensors for hydrogen-leak detection, laser instrumentation for hydrogen-leak detection, and cryogenic transport and storage. Presented are the results form 15 research projects, education, and outreach activities, system and trade studies, and project management. The work will aid in advancing the state-of-the-art for several critical technologies related to the implementation of a hydrogen infrastructure. Activities conducted are relevant to a number of propulsion and power systems for terrestrial, aeronautics, and aerospace applications.

Anderson, Tim↗

Hydrogen Research for Spaceport and Space-Based Applications: Hydrogen Production, Storage, and Transport

The activities presented are a broad based approach to advancing key hydrogen related technologies in areas such as fuel cells, hydrogen production, and distributed sensors for hydrogen-leak detection, laser instrumentation for hydrogen-leak detection, and cryogenic transport and storage. Presented are the results from research projects, education and outreach activities, system and trade studies. The work will aid in advancing the state-of-the-art for several critical technologies related to the implementation of a hydrogen infrastructure. Activities conducted are relevant to a number of propulsion and power systems for terrestrial, aeronautics and aerospace applications. Hydrogen storage and in-space hydrogen transport research focused on developing and verifying design concepts for efficient, safe, lightweight liquid hydrogen cryogenic storage systems. Research into hydrogen production had a specific goal of further advancing proton conducting membrane technology in the laboratory at a larger scale. System and process trade studies evaluated the proton conducting membrane technology, specifically, scale-up issues.

Anderson, Tim↗

Hydrogen Research for Spaceport and Space-Based Applications: Fuel Cell Projects

The activities presented are a broad based approach to advancing key hydrogen related technologies in areas such as fuel cells, hydrogen production, and distributed sensors for hydrogen-leak detection, laser instrumentation for hydrogen-leak detection, and cryogenic transport and storage. Presented are the results from research projects, education and outreach activities, system and trade studies. The work will aid in advancing the state-of-the-art for several critical technologies related to the implementation of a hydrogen infrastructure. Activities conducted are relevant to a number of propulsion and power systems for terrestrial, aeronautics and aerospace applications. Fuel cell research focused on proton exchange membranes (PEM), solid oxide fuel cells (SOFC). Specific technologies included aircraft fuel cell reformers, new and improved electrodes, electrolytes, interconnect, and seals, modeling of fuel cells including CFD coupled with impedance spectroscopy. Research was conducted on new materials and designs for fuel cells, along with using embedded sensors with power management electronics to improve the power density delivered by fuel cells. Fuel cell applications considered were in-space operations, aviation, and ground-based fuel cells such as; powering auxiliary power units (APUs) in aircraft; high power density, long duration power supplies for interplanetary missions (space science probes and planetary rovers); regenerative capabilities for high altitude aircraft; and power supplies for reusable launch vehicles.

Anderson, Tim↗

Gas-mapping 3D imager measurement techniques and method of data processing

Measurement approaches and data analysis methods are disclosed for combining 3D topographic data with spatially-registered gas concentration data to increase the efficiency of gas monitoring and leak detection tasks. Here, the metric for efficiency is defined as reducing the measurement time required to achieve the detection, or non-detection, of a gas leak with a desired confidence level. Methods are presented for localizing and quantifying detected gas leaks. Particular attention is paid to the combination of 3D spatial data with path-integrated gas concentration measurements acquired using remote gas sensing technologies, as this data can be used to determine the path-averaged gas concentration between the sensor and points in the measurement scene. Path-averaged gas concentration data is useful for finding and quantifying localized regions of elevated (or anomalous) gas concentration making it ideal for a variety of applications including: oil and gas pipeline monitoring, facility leak and emissions monitoring, and environmental monitoring.

Thorpe, Michael↗

Chemical Microsensor Development for Aerospace Applications

Numerous aerospace applications, including low-false-alarm fire detection, environmental monitoring, fuel leak detection, and engine emission monitoring, would benefit greatly from robust and low weight, cost, and power consumption chemical microsensors. NASA Glenn Research Center has been working to develop a variety of chemical microsensors with these attributes to address the aforementioned applications. Chemical microsensors using different material platforms and sensing mechanisms have been produced. Approaches using electrochemical cells, resistors, and Schottky diode platforms, combined with nano-based materials, high temperature solid electrolytes, and room temperature polymer electrolytes have been realized to enable different types of microsensors. By understanding the application needs and chemical gas species to be detected, sensing materials and unique microfabrication processes were selected and applied. The chemical microsensors were designed utilizing simple structures and the least number of microfabrication processes possible, while maintaining high yield and low cost. In this presentation, an overview of carbon dioxide (CO2), oxygen (O2), and hydrogen/hydrocarbons (H2/CxHy) microsensors and their fabrication, testing results, and applications will be described. Particular challenges associated with improving the H2/CxHy microsensor contact wire-bonding pad will be discussed. These microsensors represent our research approach and serve as major tools as we expand our sensor development toolbox. Our ultimate goal is to develop robust chemical microsensor systems for aerospace and commercial applications.

hydrogen sensors↗

A sonic transducer to detect fluid leaks

Ultrasonic detector utilizes set of contact transducers and bandpass filters to detect and analyze sonic energy produced by flow or leakage. Detector covers wide frequency range and is operable at cryogenic temperatures and in vacuum.

Cimerman, I.↗

Total hydrocarbon analysis by ion mobility spectrometry

Astronauts must be alerted quickly to chemical leaks that compromise their health and the success of their missions. An ideal leak detector would be equally sensitive to all compounds that might constitute a hazard and insensitive to nontoxic compounds. No ideal sensor exists; thus, selection of a methodology is a series of compromises. The commonly used methods are either insensitive at the low exposure levels set by OSHA, NASA, and other organizations or are selectively insensitive to important classes of chemicals such as Freons. After extensive study and experience, the Toxicology Group at JSC has selected ion mobility spectrometry (IMS) for development into a broad range, sensitive detector. In addition to the sensing method, signal processing is important leak detection because a background signal can be expected at all times. The leak-detecting instrument must be programmed to discriminate between authentic leaks and background fluctuations caused by routine operations. The results of an evaluation of the prototype THA is presented in terms related to spacecraft operations. The evaluation included determination of instrumental parameters such as stability and response times. We also included responses to some common components of spacecraft atmospheres in pure form and in binary and ternary mixtures. The output of the four algorithms to the mixtures was found to be noticeably different. These responses are compared on the basis of their utility for signaling a chemical leak. As a means of evaluating its resistance to a falsely positive response, the THA was challenged with carbon dioxide and methane, compounds whose concentrations normally increase in spacecraft air during human habitation. The instrument showed virtually no response to these interferences. Although the prototype THA is designed for space flight, this detector is expected to be useful for field screening at chemical waste dumps and other environmentally sensitive locations.

Cross, John H.↗

Calibration and field deployment of low-cost sensor network to monitor underground pipeline leakage

Recent technological advances in methane detection have improved leak detection and repair. However, current methods to reliably measure methane concentrations rely on expensive instruments or demand significant labor input. There is interest in using affordable methane sensors that are responsive to ppmv level changes in methane concentrations in both urban and rural environments for monitoring underground natural gas pipeline leaks. This is especially relevant for situations where potentially significant leaks cannot be repaired immediately or smaller leaks that require long-term monitoring and further evaluation. In this work, a low-cost sensor unit, equipped with a metal oxide sensor, was designed, built, and calibrated over a wide range of methane concentrations and environmental conditions in preparation for field application. A network of these sensors was then installed at the test site and used to measure methane concentrations at ground level above known sub-surface natural gas emissions which emulated underground gas pipeline leaks. This low-cost sensor network measured over 4 days total for the two different known leakage rates. Results demonstrate that the sensors can continuously measure relative methane variability for extended periods but require calibration for a wide range of temperature and humidity conditions to properly determine absolute gas (i.e., methane) concentrations. Furthermore, when a regression analysis was conducted to evaluate the effects of meteorological parameters on methane concentration, air temperature and wind speed have strong impacts on the concentration. Overall, the network approach allows improved identification of leak location and monitoring of underground natural gas leaks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Test program, helium II orbital resupply coupling

The full scope of this program was to have included development tests, design and production of custom test equipment and acceptance and qualification testing of prototype and protoflight coupling hardware. This program was performed by Ball Aerospace Systems Division, Boulder, Colorado until its premature termination in May 1991. Development tests were performed on cryogenic face seals and flow control devices at superfluid helium (He II) conditions. Special equipment was developed to allow quantified leak detection at large leak rates up to 8.4 x 10(exp -4) SCCS. Two major fixtures were developed and characterized: The Cryogenic Test Fixture (CTF) and the Thermal Mismatch Fixture (Glovebox). The CTF allows the coupling hardware to be filled with liquid nitrogen (LN2), liquid helium (LHe) or sub-cooled liquid helium when hardware flow control valves are either open or closed. Heat leak measurements, internal and external helium leakage measurements, cryogenic proof pressure tests and external load applications are performed in this fixture. Special reusable MLI closures were developed to provide repeatable installations in the CTF. The Thermal Mismatch Fixture allows all design configurations of coupling hardware to be engaged and disengaged while measuring applied forces and torques. Any two hardware components may be individually thermally preconditioned within the range of 117 deg K to 350 deg K prior to engage/disengage cycling. This verifies dimensional compatibility and operation when thermally mismatched. A clean, dry GN2 atmosphere is maintained in the fixture at all times. The first shipset of hardware was received, inspected and cycled at room temperature just prior to program termination.

Hyatt, William S.↗

A Leak Monitor for Industry

GenCorp Aerojet Industrial Products, Lewis Research Center, Marshall Space Flight Center, and Case Western Reserve University developed a gas leak detection system, originally for use with the Space Shuttle propulsion system and reusable launch vehicles. The Model HG200 Automated Gas Leak Detection System has miniaturized sensors that can identify extremely low concentrations of hydrogen without requiring oxygen. A microprocessor-based hardware/software system monitors the sensors and displays the source and magnitude of hydrogen leaks in real time. The system detects trace hydrogen around pipes, connectors, flanges and pressure tanks, and has been used by Ford Motor Company in the production of a natural gas-powered car.

Source record↗

Assessing the Value of Seismic Amplitude Versus Offset (AVO) Attributes for CO2 Storage Project Using a Bayesian Network Model for Decision Support

Attributes versus offset (AVO) are a set of measurements to analyze how the characteristics of reflected seismic waves change as a function of the offset. It can be useful for monitoring CO2 storage sites because the presence of leaked CO2 into the overlying aquifer can change the properties of the rocks and pore fluids composition that can alter the way seismic waves reflect and their amplitudes. The time-lapse changes in AVO attributes derived from repeat seismic surveys can help identify anomalies or shifts in the subsurface that could potentially be used as an indicator for CO2 leak detection. Our study leverages multiple seismic attributes derived from synthetic seismic data and Bayesian network model to quantify the probability of leak detection in the overlying aquifer above the storage reservoir. It helps to quantify the value of individual seismic attributes at multiple monitoring periods based upon their sensitivities.

Kumar, Abhash↗

Heuristic based analytics for gas leak source identification

Heuristic-based techniques for gas leak source identification are provided. In one aspect, a method for identifying a location of a gas leak source includes: obtaining gas sensor data and wind data synchronously from a gas leak detection system having a network of interconnected motes comprising gas sensors and wind sensors, with the gas sensors arranged around possible gas leak sources in a given area of interest; identifying the location of the gas leak source using the gas sensor data and wind data; and determining a magnitude of gas leak from the gas leak source using the location of the gas leak source and a distance d between the location of the gas leak source and a select one of the gas sensors from which the gas sensor data was obtained. A gas leak detection system is also provided.

03 NATURAL GAS↗