Search NASA⌕ Search

SEARCH · Search NASA

Results for “leakage detection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Threshold Helium Leakage Detection Switch with Ultra Low Power Operation

Detecting helium leakage is important in many applications, such as in dry cask nuclear waste storage systems. This work develops a helium detection system based on the relative permittivity (dielectric constant) difference between air and helium. This difference changes the status of an electrostatic microelectromechanical system (MEMS) switch. The switch is a capacitive-based device and requires a very negligible amount of power. Exciting the switch’s electrical resonance enhances the MEMS switch sensitivity to detect low helium concentration. This work simulates two different MEMS switch configurations: a cantilever-based MEMS modeled as a single-degree-freedom model and a clamped-clamped beam MEMS molded using the COMSOL Multiphysics finite-element software. While both configurations demonstrate the switch’s simple operation concept, the clamped-clamped beam was selected for detailed parametric characterization due to its comprehensive modeling approach. The beam detects at least 5% helium concentration levels when excited at 3.8 MHz, near electrical resonance. The switch performance decreases at lower excitation frequencies or increases the circuit resistance. The MEMS sensor detection level was relatively immune to beam thickness and parasitic capacitance changes. However, higher parasitic capacitance increases the switch’s susceptibility to errors, fluctuations, and uncertainties.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Leakage detection using smart field technology

Various examples are provided for gas leakage detection from geologic storage sites. In one example, a system for detection of gas leakage from a geologic storage site includes permanent down-hole gauges (PDGs) disposed at different depths within a well and an evaluation system that can determine a three-dimensional (3D) location of the gas leakage from the geologic storage site and a leakage indicator. The 3D location and leakage indicator can be determined using pressure data provided by the PDGs. The geologic storage site can store, e.g., CO2, natural gas or other type of gas. In another example, a method for detecting gas leakage from a geologic storage site includes receiving pressure data provided by PDGs disposed within one or more wells associated with the geologic storage site, determining key performance indicators using the pressure data and determining a 3D location and a leakage indicator using the key performance indicators.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Underground hydrogen storage leakage detection and characterization based on machine learning of sparse seismic data

Underground hydrogen storage (UHS) is considered as a scalable approach for massive storage and seasonal extraction of hydrogen (H 2 ). Although conventional leakage detection and characterization methods based on time-lapse seismic imaging and inversion generally apply to H 2 leakage detection problem, a high-fidelity yet cost effective geophysics approach is still missing to reliably inform leakage location and properties based on very sparse data. In response, we develop a novel supervised machine learning method to detect and characterize H 2 leakage from UHS. The input to our neural network are sparse time-lapse seismic waveforms, while the output from the neural network includes the spatial location and physical properties of a H 2 leakage. Here, we generate high-quality time-lapse waveforms using the elastic-wave equations to train the neural network. We train and validate our machine learning model and find that it attains high accuracy in using extremely sparse time-lapse seismic data to detect and characterize H 2 leakage. Our investigation is the first systematic study that focuses on applying machine learning to subsurface H 2 leakage detection and characterization and could potentially serve as a cost-effective geophysical tool for underground hydrogen leakage detection and characterization with high fidelity.

08 HYDROGEN↗
NASA NTRS1994

The development of a solid-state hydrogen sensor for rocket engine leakage detection

Hydrogen propellant leakage poses significant operational problems in the rocket propulsion industry as well as for space exploratory applications. Vigorous efforts have been devoted to minimizing hydrogen leakage in assembly, test, and launch operations related to hydrogen propellant. The objective has been to reduce the operational cost of assembling and maintaining hydrogen delivery systems. Specifically, efforts have been made to develop a hydrogen leak detection system for point-contact measurement. Under the auspices of Lewis Research Center, the Electronics Design Center at Case Western Reserve University, Cleveland, Ohio, has undertaken the development of a point-contact hydrogen gas sensor with potential applications to the hydrogen propellant industry. We envision a sensor array consisting of numbers of discrete hydrogen sensors that can be located in potential leak sites. Silicon-based microfabrication and micromachining techniques are used in the fabrication of these sensor prototypes. Evaluations of the sensor are carried out in-house at Case Western Reserve University as well as at Lewis Research Center and GenCorp Aerojet, Sacramento, California. The hydrogen gas sensor is not only applicable in a hydrogen propulsion system, but also usable in many other civilian and industrial settings. This includes vehicles or facility use, or in the production of hydrogen gas. Dual space and commercial uses of these point-contacted hydrogen sensors are feasible and will directly meet the needs and objectives of NASA as well as various industrial segments.

Liu, Chung-Chiun↗
DOE OSTI2024

A novel transient infrared imaging method for non-intrusive, low-cost, fast, and accurate air leakage detection in building envelopes

Air leakage through the building envelope in the U.S. accounts for about four quads of energy annually, costing approximately $40 billion per year. However, a high-fidelity and non-intrusive method to detect air leakage has not been demonstrated to date. Here, in this paper, we propose a novel non-intrusive and low-cost method called Transient Infrared (IR) Imaging (TIRI) that can rapidly and accurately identify air leakage locations and relative rates on building envelopes. When the interior and exterior temperatures are different, and a small internal pressure pulse is created by HVAC, the temperature at locations with air leakages will change rapidly, while the areas without a leakage do not change. Based on a heat transfer model, we have derived the temperature change as a function of time after the HVAC is turned on. By tracking the temperature change, which depends on leakage rate and size, we have obtained the air leakage map in the case studies. Using an exterior door as an example, we took transient IR images in different seasons and different times of the day, and successfully obtained the leakage map in all the scenarios. Successfully obtained the air leakage map even when the indoor-outdoor air temperature difference is as small as 2 °C. We have also realized a detection speed of 10s and demonstrated that this method also worked for windows, which have mirror-like IR reflections. Our TIRI method will accelerate the improvement of airtightness in buildings, save building energy, and help reduce greenhouse gas emissions.

42 ENGINEERING↗
DOE OSTI2020

Fluorescent air leakage detection system for enclosures

Provided is a Fluorescent Air Leakage Detection (FALD) system and method for locating a defect in an enclosure that uses a nontoxic fluorescent solution as a marker. The solution is aerosolized with an atomizing device and guided to defects by a gas pressure modifying device. Defects are visually located by surveying the enclosure with an ultraviolet or visible light source and identifying a location where accumulated solution fluoresces.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Normal or abnormal? Machine learning for the leakage detection in carbon sequestration projects using pressure field data

The international commitments for atmospheric carbon reduction will require a rapid increase in carbon capture and storage (CCS) projects. The key to any successful CCS project lies in the long term storage and prevention of leakage of stored carbon dioxide (CO 2 ). In addition to being a greenhouse gas, CO 2 leaks reaching the surface can accumulate in low-lying areas resulting in a serious health risk. Among several alternatives, some of the more promising CCS storage formations are depleted oil and gas reservoirs, where the reservoirs had good geological seals prior to hydrocarbon extraction. With more CCS wells coming online, it is imperative to implement permanent, automated monitoring tools. We apply machine learning models to automate the leakage detection process in carbon storage reservoirs using rates of (CO 2 ) injection and pressure data measured by simple harmonic pulse testing (HPT). To validate the feasibility of this machine learning based workflow, we use data from HPT experiments carried out in the Cranfield oil field, Mississippi, USA. The data consist of a series of pulse tests conducted with baseline parameters and with an artificially introduced leak. Here, in this study, we pose the leakage detection task as an anomaly detection problem where deviation from the predicted behavior indicates leaks in the reservoir. Results show that different machine learning architectures such as multi-layer feed forward network, Long Short-Term Memory, and convolutional neural network are able to identify leakages and can provide early warning. These warnings can then be used to take remedial measures.

58 GEOSCIENCES↗
DOE OSTI2023

Surface acoustic wave sensor for refrigerant leakage detection

A SAW sensor is optimized for detection of refrigerant leakage in a refrigerant system or other gases, vapors, explosives or chemicals of interest. The SAW sensor includes a piezoelectric substrate; an interdigitated transducer deposited on the piezoelectric substrate, the interdigitated transducer having an input portion that receives input surface acoustic waves and an output portion that emits output surface acoustic waves; and a refrigerant sensor film located between the input portion and the output portion of the interdigitated transducer, the refrigerant sensor film including a sorbent material that is selected for preferential adsorption of a target refrigerant over atmospheric gases. Adsorption of the target refrigerant by the sorbent material results in a frequency shift of a frequency of the output surface acoustic waves relative to a frequency of the input surface acoustic waves. The sorbent material may be a metal organic framework (MOF) material, a covalent organic framework (COF) material, a porous organic cage or organic macrocyles such as calix [n] arene and its related derivatives.

Kunapuli, Raghuit Prasad↗
NASA NTRS1971

Study to develop improved methods to detect leakage in fluid systems, phase 2

An ultrasonic contact sensor engineering prototype leak detection system was developed and its capabilities under cryogenic operations demonstrated. The results from tests indicate that the transducer performed well on liquid hydrogen plumbing, that flow and valve actuation could be monitored, and that the phase change from gaseous to liquid hydrogen could be detected by the externally mounted transducers. Tests also demonstrate the ability of the system to detect internal leaks past valve seats and to function as a flow meter. Such a system demonstrates that it is not necessary to break into welded systems to locate internal leaks.

Janus, J. C.↗
NASA NTRS1972

Study to develop improved methods to detect leakage in fluid systems, phase 3

Research was undertaken to design and fabricate a prototype flight weight ultrasonic contact sensor leak detection system and to perform the necessary testing to collect enough data to establish design parameters and develop necessary baseline operating characteristics. The prototype system consists of five channels and is capable for monitoring frequencies from 1 KHz to 110 KHz.

Janus, J. C.↗