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Sensor Placement Optimization Software Applied to Site-Scale Methane-Emissions Monitoring

Journal Article · · Journal of Environmental Engineering
 [1];  [1];  [1];  [2];  [2]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  2. Stanford Univ., CA (United States)
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Advances in sensor technology have increased our ability to monitor a wide range of environments. However, even as the cost of sensors decline, only a limited number of sensors can be installed at any given site. The physical placement of sensors, along with the sensor technology and operating conditions, can have a large impact on our ability to adequately monitor environmental change. This paper introduces a new open-source Python package, called Chama, that determines optimal sensor placement and technology to improve a sensor network’s detection capabilities. Additionally, the methods are demonstrated using site-specific methane emission scenarios that capture uncertainty in wind conditions and emission characteristics. Mixed-integer linear programming formulations are used to determine sensor locations and detection thresholds that maximize detection of the emission scenarios. The optimized sensor networks consistently increase the ability to detect leaks, as compared to sensors placed near each potential emission source or along the perimeter of the site.
Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC04-94AL85000; NA0003525
OSTI ID:
1778069
Report Number(s):
SAND--2021-4105J; 695375
Journal Information:
Journal of Environmental Engineering, Journal Name: Journal of Environmental Engineering Journal Issue: 7 Vol. 146; ISSN 0733-9372
Publisher:
American Society of Civil Engineers (ASCE)Copyright Statement
Country of Publication:
United States
Language:
English

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