Abstract

ITT Industries Space Systems Division (Space Systems) has developed an airborne natural gas leak detection system designed to detect, image, quantify, and precisely locate leaks from natural gas transmission pipelines. This system is called the Airborne Natural Gas Emission Lidar (ANGEL) system. The ANGEL system uses a highly sensitive differential absorption Lidar technology to remotely detect pipeline leaks. The ANGEL System is operated from a fixed wing aircraft and includes automatic scanning, pointing system, and pilot guidance systems. During a pipeline inspection, the ANGEL system aircraft flies at an elevation of 1000 feet above the ground at speeds of between 100 and 150 mph. Under this contract with DOE/NETL, Space Systems was funded to integrate the ANGEL sensor into a test aircraft and conduct a series of flight tests over a variety of test targets including simulated natural gas pipeline leaks. Following early tests in upstate New York in the summer of 2004, the ANGEL system was deployed to Casper, Wyoming to participate in a set of DOE-sponsored field tests at the Rocky Mountain Oilfield Testing Center (RMOTC). At RMOTC the Space Systems team completed integration of the system and flew an operational system for the first time. The ANGELmore » system flew 2 missions/day for the duration for the 5-day test. Over the course of the week the ANGEL System detected leaks ranging from 100 to 5,000 scfh.« le Document type: Report

Abstract

Accurate and reliable global positioning system (GPS)-based vehicle use data are highly valuable for many transportation, analysis, and automotive considerations. Model-based design, real-world fuel economy analysis, and the growing field of autonomous and connected technologies (including predictive powertrain control and self-driving cars) all have a vested interest in high-fidelity estimation of powertrain loads and vehicle usage profiles. Unfortunately, road grade can be a difficult property to extract from GPS data with consistency. In this report, we present a methodology for appending high-resolution elevation data to GPS speed traces via a static digital elevation model. Anomalous data points in the digital elevation model are addressed during a filtration/smoothing routine, resulting in an elevation profile that can be used to calculate road grade. This process is evaluated against a large, commercially available height/slope dataset from the Navteq/Nokia/HERE Advanced Driver Assistance Systems product. Results will show good agreement with the Advanced Driver Assistance Systems data in the ability to estimate road grade between any two consecutive points in the contiguous United States. Document type: Report