Publications & Presentations

A second-generation tunable diode laser absorption spectroscopy (TDLAS)ebased sensor was used to measure dm/dt. In addition, a new approach to calculate drying heterogeneity in a batch during primary drying is described. The TDLAS dm/dt measurements were found to be within 5%-10% of gravimetric measurement for laboratory- and pilot-scale lyophilizers. Intersupplier variability in Kv was high for the same “type” of vials, which can lead to erroneous product temperature prediction if “one value” of vial heat transfer coefficient is used for “all vial types” from different suppliers. Studies conducted in both a laboratory- and a pilot-scale lyophilizer showed TDLAS product temperature to be within ±1 C of average thermocouple temperature during primary drying. Using TDLAS data and calculations to estimate drying heterogeneity (number of vials undergoing primary drying), good agreement was obtained between theoretical and experimental results, demonstrating usefulness of the new approach.

The full article is available at: https://www.sciencedirect.com/science/article/pii/S0022354918305008?dgcid=author

To provide an affordable sensing system enabling more effective methane mitigation programs, we have adapted the backscatter-TDLAS technology embedded in the Remote Methane Leak Detector (RMLD) for mounting on PSI’s two-foot-wide quadrotor Unmanned Aerial Vehicle (UAV) featuring highly advanced autonomy.

The principal purpose of developing rapid and remote leak rate measurement techniques is to rank leaks based not only on the current practice of measuring local concentration (which can be very high for a small leak in a no wind condition), but also on measuring leak rate. No current leak survey tool directly images gas leak plumes quantitatively, much less quantifies emission rate, a technology gap that this sensor development addresses. The technology under development, which we call “RMLD-QGI” (Quantitative Gas Imager), combines low-cost laser scanner, visible camera, and near-IR tunable diode laser absorption spectroscopy (TDLAS) gas detection to answer this need.

The system was found throughout the trials to reliably distinguish between cases with and without a methane release down to 2 standard cubic feet per hour (0.011 g/s). Among several methods evaluated for horizontal localization, the location corresponding to the maximum path-integrated methane reading performed best with a mean absolute error of 1.2 m if the results from several flights are spatially averaged. Additionally, a method of rotating the data around the estimated leak location according to the wind is developed, with the leak magnitude calculated from the average crosswind integrated flux in the region near the source location. The system is initially applied at the well pad scale (100–1000 m² area). Validation of these methods is presented including tests with unknown leak locations. Sources of error, including GPS uncertainty, meteorological variables, data averaging, and flight pattern coverage, are discussed. The techniques described here are important for surveys of small facilities where the scales for dispersion-based approaches are not readily applicable.

The system is composed of three major technologies: miniaturized RMLD (mini-RMLD) based on Backscatter Tunable Diode Laser Absorption Spectroscopy (TDLAS), an autonomous quadrotor UAV and simplified quantification and localization algorithms. With a miniaturized, downward-facing RMLD on a small UAV, the system measures the column-integrated CH₄ mixing ratio and can semi-autonomously monitor CH₄ leakage from sites associated with natural gas production, providing an advanced capability in detecting leaks at hard-to-access sites compared to traditional manual methods. Automated leak characterization algorithms combined with a wireless data link implement real-time leak quantification and reporting. This study placed particular emphasis on the RMLD-UAV system description and the quantification algorithm development based on a mass balance approach. Early data were gathered to test the prototype system and to evaluate the algorithm performance. The quantification algorithm derived in this study tended to underestimate the gas leak rates and yielded unreliable estimations in detecting leaks under 7 x 10^-66 m³/s (~1 Standard Cubic Feet per Hour (SCFH)). Zero-leak cases can be ascertained via a skewness indicator, which is unique and promising. The influence of the systematic error was investigated by introducing simulated noises, of which Global Positioning System (GPS) noise presented the greatest impact on leak rate errors. The correlation between estimated leak rates and wind conditions were investigated, and steady winds with higher wind speeds were preferred to get better leak rate estimations, which was accurate to approximately 50% during several field trials. High precision coordinate information from the GPS, accurate wind measurements and preferred wind conditions, appropriate flight strategy and the relative steady survey height of the system are the crucial factors to optimize the leak rate estimations.