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Safitri A.,Mary Kay onnor Process Safety Center | Gao X.,Texas A&M University | Mannan M.S.,Texas A&M University
AIChE Annual Meeting, Conference Proceedings | Year: 2010

Infrared imaging technique is used in industry as a method to detect fugitive leaks from equipment and pipeline systems. Optical imaging is considered as a smart LDAR (Leak Detection and Repair) because it can scan a large number of equipment in relatively short time compared to detection using Total Vapor Analyzer (TVA) or 'gas sniffer'. In addition, the ability of infrared optical imaging system to visualize the gas plume which is not visible to naked eyes offers another advantage. However, this novel technique poses a lot of challenges in its application due to many uncertainties related to the sensitivity of the camera and factors which may affect measurement. Infrared imaging technique has been used in this research to detect methane gas leak from pipelines and monitor LNG plume from LNG spill. In this work, some significant factors affecting measurement such as gas emissivity, atmospheric attenuation, and stimulated radiation from other objects than the target are being evaluated. Furthermore, potential use of infrared imaging technique for methane gas emissions estimation is proposed in this research. This is carried out by assessing the sensitivity of the infrared camera during monitoring the gas release in order to obtain the minimum detectable gas concentration that still can be observed by the camera under real meteorological conditions. From this test, the correlation of mass flow rate and distance to minimum detectable concentration will be withdrawn. Prior to the test, discharge and dispersion simulation of methane gas at various pressures, temperatures and leak sizes is performed to calculate the gas release rate and predict the downwind concentration of methane gas. Several types of infrared imaging technique also have the capability as a non-contact temperature measurement and thus they can provide a spatial temperature distribution of a target object. This facility is used in this research to demonstrate the temperature profile of LNG gas plume in case of accidental spill of LNG on the ground. However, there is a high discrepancy of the cloud temperature measured using infrared camera to the thermocouple reading. This research has been able to identify the most significant uncertainty which comes from unspecified emissivity of the LNG cloud. The methane gas emissivity is not included in the detector's algorithm and therefore the apparent target temperature shows much higher value than the actual one. In this study, the methane gas emissivity as a function of temperature at different optical depth is analyzed using band absorption model. Source

Skjold T.,GexCon AS | Skjold T.,University of Bergen | Castellanos D.,Mary Kay onnor Process Safety Center | Castellanos D.,Texas A&M University | And 3 more authors.
Journal of Loss Prevention in the Process Industries | Year: 2014

This paper describes an experimental investigation of turbulent flame propagation in propane-air mixtures, and in mechanical suspensions of maize starch dispersed in air, in a closed vessel of length 3.6m and internal cross-section 0.27m×0.27m. The primary motivation for the work is to gain improved understanding of turbulent flame propagation in dust clouds, with a view to develop improved models and methods for assessing explosion risks in the process and mining industries. The study includes computational fluid dynamics (CFD) simulations with FLACS and DESC, for gas and dust explosions respectively. For initially quiescent propane-air mixtures, FLACS over-predicts the rate of combustion for fuel-lean mixtures, and under-predicts for fuel-rich mixtures. The simulations tend to be in better agreement with the experimental results for initially turbulent gaseous mixtures. The experimental results for maize starch vary significantly between repeated tests, but the subset of tests that yields the highest explosion pressures are in reasonable agreement with CFD simulations with DESC. © 2014 Elsevier Ltd. Source

Alfi M.,Texas A&M University | Nasrabadi H.,Texas A&M University | Banerjee D.,Mary Kay onnor Process Safety Center
Fluid Phase Equilibria | Year: 2016

The study of phase behavior of hydrocarbons inside shale rock has garnered significant attention in contemporary literature. The present work focused on experimental techniques for addressing this challenge. To this end, lab-on-a-chip technology was integrated with high-resolution imaging techniques (inverse confocal microscopy equipment) for investigating the phase behavior of hydrocarbons inside nanoscale capillaries (nanochannels). Experiments were performed to measure the bubble point temperature of pure Hexane, Heptane, and Octane inside nanochannels to study the confinement effect. The novel method of employing a nanofluidic chip enabled the visualization of fluid behavior inside nanoscale channels. The method was found to be highly promising for experimental investigation of the phase behavior in nano-scale pores, which has always been one of the biggest research challenges. The experimental results revealed that for nanochannel depth of 50 nm, the confinement effect in the form of wall-molecule interactions is almost negligible. Additionally, the Peng-Robinson equation of state (PR-EOS) with and without capillary pressure was used for modeling the hydrocarbon phase behavior. Experimental validation of numerical predictions obtained from these thermo-physical models describing the effect of phase behavior for confined fluids were performed in this study. © 2016 . Source

Licari F.A.,Pipeline and Hazardous Materials Safety Administration | Licari F.A.,Mary Kay onnor Process Safety Center
Journal of Loss Prevention in the Process Industries | Year: 2010

New performance metrics are necessary to quantify the inherent margins of safety. 11In this paper, margin of safety is an occupational safety phrase, and it is expressed as a ratio. in vapor dispersion models for liquefied natural gas (LNG) spills. Currently, vapor dispersion model calculations in the 49 Code of Federal Regulations, Part 193 as well as Standard 59A of the National Fire Protection Association (2001 edition) reduce the lower flammability limit (LFL) of methane in air by a safety factor of two (to 50% LFL) to ensure that flammable vapors do not extend beyond an LNG facility's property line during an LNG spill. Yet, neither document explicitly states the additional distance or the additional confidence level this existing safety standard creates to separate the public from LNG vapors at 100 percent LFL within the facility vs. 50 percent LFL at the facility property line.Although researchers have successfully validated how vapor dispersion models calculate conservative buffer (exclusion) zones, their collective work did not readily explain to the general public the inherent margins of safety in these models. Havens and Spicer developed correlations to demonstrate how well DEGADIS. 22DEGADIS is a dense gas, vapor dispersion model that was developed in collaboration with the Gas Research Institute and the University of Arkansas. The United States Department of Transportation adopted DEGADIS in its LNG facility siting regulations within Part 193 of the 49 Code of Federal Regulations. predictions compared with field testing measurements in the late 80s (Havens & Spicer, 1985). Their research also confirmed that peak gas concentrations exceeded time averaged measurements during some field trials as well as DEGADIS predictions. Then Hanna, Chang, and Strimaitis (1993) explained how several vapor dispersion models could be compared by calculating geometric mean bias and geometric variance and shared these validation results with the public. The works of the Havens and Hanna teams were also influential in explaining why the maximum concentration of methane in air at the property limits of an LNG facility should be 50 percent of its lower flammability limit during an LNG spill. Eleven years later, Chang and Hanna discussed how the relationships between fractional bias, geometric mean bias, geometric variance, and normalized mean square error could explain vapor dispersion model over and under prediction (Chang & Hanna, 2004). Despite these successful efforts, there has been reluctance to embrace vapor dispersion model results, because exclusion zones are not described as creating margins of safety (i.e. additional separation distance) or higher confidence levels (i.e. a likelihood of being correct) that protect the public.This paper proposes an improved performance metric to evaluate the validity of vapor dispersion models and a statistical methodology to determine the confidence level and the inherent margin of safety in calculating vapor dispersion exclusion zones. Descriptions of the new metric and methodology are presented in this document for the DEGADIS vapor dispersion model, together with example calculations. © 2010. Source

Yang X.,Mary Kay onnor Process Safety Center | Laird C.D.,Texas A&M University | Mannan M.S.,Mary Kay oConnor Process Safety Center
10AIChE - 2010 AIChE Spring Meeting and 6th Global Congress on Process Safety | Year: 2010

A discussion covers component inspection interval optimization of an oil/gas separation system in offshore plants; mathematical modeling developed for assessing the operational risk focusing on overflow scenario in oil/gas separation system; optimizing component inspection interval; a numerical Pareto optimization technique based on an evolutionary algorism and a technique using a scaling factor to represent the weights of trade-off objectives; Pareto optimal solutions generated to represent the optimal inspection budget and scheduling of pump, control valve, and level transmitter in the system; and choice of component inspection interval sets for whatever relative weighting is considered as the most appropriate one for the actual design problem. This is an abstract of a paper presented at the AIChE 2010 Spring National Meeting (San Antonio, TX 3/21-25/2010). Source

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