Challenges in applying Process Safety Management at a University Laboratories

PresentationRisks associated with academic research are often perceived as being much lower than risks within large-scale process industry operations. While the inventories of hazardous materials are generally lower within an academic environment and the number of other hazards may be lower, factors such as materials of construction typically used in laboratories, and the proximity of researchers to their equipment push risks to the individual disproportionately higher. The number of reported lab accidents worldwide that have resulted in fatalities, severe personnel injury, and financial loss demonstrates that there is a need to better risk management practices within academic teaching and experimental research labs. This need was very strongly emphasized by the US Chemical Safety Board following their investigation of major fatal laboratory accidents in the previous years. Risk management within academic laboratories starts with developing a solid understanding of the concepts of Hazard and Risk. For people outside the safety and process safety industry, there is a lack of distinction between these two terms. While Hazard corresponds to the potential for harm (usually independent of scale), Risk is related to the combination of the likelihood of a hazard scenario occurring and the severity of the consequence, should the scenario occur and is typically expressed in terms of impacts to People, Assets, Environment, and Company Reputation. The more layers of protection (controls, prevention measures and mitigations methods) in place to prevent and manage the hazard scenario and the higher the reliability of each layer, the lower the likelihood, and / or severity and thus the lower the risk. A variety of different hazards exist within university academic and research laboratories, and the risks associated with the experiments being undertaken within these labs can be significant if not properly managed. Yet, the misperception that university labs are “low risks” and “inherently safer” still remains within and outside academia, in part due to a lack of hazard awareness. This work discusses a proven approach to applying the principles of process safety management, widely used in the process industry, to teaching and research laboratories within an academic environment through selected challenges and examples

Building Process Safety Culture at Texas A&M University at Qatar: A Case Study on Experimental Research

PresentationOver the last few years, the importance of establishing and maintaining a positive safety culture in the process industry and its impact on the safety performances of a company have strongly been emphasized by regulatory institutions, academia and very importantly by the process industry itself. A strong safety culture, when everyone in a company feels responsible for safety and acts accordingly, is not achieved overnight as it requires changing behaviors and instilling safety values to individuals. The challenge is there for existing employees of a company but also for new recruits. In the particular case of freshly graduated engineers, it is often only when joining a company that the individual discovers the concept of safety culture and has to buy into it. Academia could play a much better role in training engineers who, not only understand the process safety challenges faced by the industry, but genuinely join the industry with a pre- established positive safety culture developed during the years of their education. Instilling a process safety culture to future engineers is an area that still requires major efforts from academia. Experimental research at university or college often involves the handling of hazardous substances and processes, with an associated level of risk that need to be minimized. Incidents (major and minor) do happen in university laboratories. It is very common that only major incidents are reported and investigated. Operational deviations, minor incidents, near misses almost never see the light of discussion, although they are opportunities to instill a process safety culture to students, as they are in the process industry. The objective of this paper is to provide a case study on building process safety culture in a research environment by applying different key aspects of process safety principles. In this study, a series of experiments were analyzed to show how process safety principles starting from inherently safer design and management program can be learnt while performing experimental research. The authors have found that investigating the root causes of near misses have multiple benefits. During the actual experiments no injuries have occurred and even the potential of having injuries was relatively low. However, in the context of this study, selected issues were investigated as accidents, which referred to not being able to successfully perform the experiments or near miss referred to delay of a planned / scheduled experiment. As the matter of fact, all these issues may be treated as time and financial losses. Different aspects of failures such as human factor, process design or inherently safer design and standard operating procedures were discussed via case studies. It was found that having students discussing and presenting the investigation results to other students has greatly improved not only the safety aspects of research but also the productivity and safety culture of the involved researchers

KINETICS OF SLURRY PHASE FISCHER-TROPSCH SYNTHESIS

This report covers the fourth year of a research project conducted under the University Coal Research Program. The overall objective of this project is to develop a comprehensive kinetic model for slurry-phase Fischer-Tropsch synthesis (FTS) employing iron-based catalysts. This model will be validated with experimental data obtained in a stirred-tank slurry reactor (STSR) over a wide range of process conditions. The model will be able to predict molar flow rates and concentrations of all reactants and major product species (water, carbon dioxide, linear 1- and 2-olefins, and linear paraffins) as a function of reaction conditions in the STSR. During the fourth year of the project, an analysis of experimental data collected during the second year of this project was performed. Kinetic parameters were estimated utilizing product distributions from 27 mass balances. During the reporting period two kinetic models were employed: a comprehensive kinetic model of Dr. Li and co-workers (Yang et al., 2003) and a hydrocarbon selectivity model of Van der Laan and Beenackers (1998, 1999) The kinetic model of Yang et al. (2003) has 24 parameters (20 parameters for hydrocarbon formation, and 4 parameters for the water-gas-shift (WGS) reaction). Kinetic parameters for the WGS reaction and FTS synthesis were estimated first separately, and then simultaneously. The estimation of these kinetic parameters employed the Levenberg-Marquardt (LM) method and the trust-region reflective Newton large-scale (LS) method. A genetic algorithm (GA) was incorporated into estimation of parameters for FTS reaction to provide initial estimates of model parameters. All reaction rate constants and activation energies were found to be positive, but at the 95% confidence level the intervals were large. Agreement between predicted and experimental reaction rates has been fair to good. Light hydrocarbons are predicted fairly accurately, whereas the model underpredicts values of higher molecular weight hydrocarbons. Van der Laan and Beenackers hydrocarbon selectivity model provides a very good fit of the experimental data for hydrocarbons up to about C{sub 20}. However, the experimental data shows higher paraffin formation rates in C{sub 12}-C{sub 25} region which is likely due to hydrocracking or other secondary reactions. The model accurately captures the observed experimental trends of decreasing olefin to paraffin ratio and increasing {alpha} (chain growth length) with increase in chain length

KINETICS OF SLURRY PHASE FISCHER-TROPSCH SYSTHESIS

This report covers the third year of this research grant under the University Coal Research program. The overall objective of this project is to develop a comprehensive kinetic model for slurry phase Fischer-Tropsch synthesis (FTS) on iron catalysts. This model will be validated with experimental data obtained in a stirred tank slurry reactor (STSR) over a wide range of process conditions. The model will be able to predict molar flow rates and concentrations of all reactants and major product species (H{sub 2}O, CO{sub 2}, linear 1- and 2-olefins, and linear paraffins) as a function of reaction conditions in the STSR. During the reporting period we utilized experimental data from the STSR, that were obtained during the first two years of the project, to perform vapor-liquid equilibrium (VLE) calculations and estimate kinetic parameters. We used a modified Peng-Robinson (PR) equation of state (EOS) with estimated values of binary interaction coefficients for the VLE calculations. Calculated vapor phase compositions were in excellent agreement with experimental values from the STSR under reaction conditions. Occasional discrepancies (for some of the experimental data) between calculated and experimental values of the liquid phase composition were ascribed to experimental errors. The VLE calculations show that the vapor and the liquid are in thermodynamic equilibrium under reaction conditions. Also, we have successfully applied the Levenberg-Marquardt method (Marquardt, 1963) to estimate parameters of a kinetic model proposed earlier by Lox and Froment (1993b) for FTS on an iron catalyst. This kinetic model is well suited for initial studies where the main goal is to learn techniques for parameter estimation and statistical analysis of estimated values of model parameters. It predicts that the chain growth parameter ({alpha}) and olefin to paraffin ratio are independent of carbon number, whereas our experimental data show that they vary with the carbon number. Predicted molar flow rates of inorganic species, n-paraffins and total olefins were generally not in good agreement with the corresponding experimental values. In the future we'll use kinetic models based on non-constant value of {alpha}

Kinetics of Slurry Phase Fischer-Tropsch Synthesis

The overall objective of this project is to develop a comprehensive kinetic model for slurry-phase Fischer-Tropsch synthesis (FTS) employing iron-based catalysts. This model will be validated with experimental data obtained in a stirred-tank slurry reactor (STSR) over a wide range of process conditions. Three STSR tests of the Ruhrchemie LP 33/81 catalyst were conducted to collect data on catalyst activity and selectivity under 25 different sets of process conditions. The observed decrease in 1-olefin content and increase in 2-olefin and n-paraffin contents with the increase in conversion are consistent with a concept that 1-olefins participate in secondary reactions (e.g. 1-olefin hydrogenation, isomerization and readsorption), whereas 2-olefins and n-paraffins are formed in these reactions. Carbon number product distribution showed an increase in chain growth probability with increase in chain length. Vapor-liquid equilibrium calculations were made to check validity of the assumption that the gas and liquid phases are in equilibrium during FTS in the STSR. Calculated vapor phase compositions were in excellent agreement with experimental values from the STSR under reaction conditions. Discrepancies between the calculated and experimental values for the liquid-phase composition (for some of the experimental data) are ascribed to experimental errors in the amount of wax collected from the reactor, and the relative amounts of hydrocarbon wax and Durasyn 164 oil (start-up fluid) in the liquid samples. Kinetic parameters of four kinetic models (Lox and Froment, 1993b; Yang et al., 2003; Van der Laan and Beenackers, 1998, 1999; and an extended kinetic model of Van der Laan and Beenackers) were estimated from experimental data in the STSR tests. Two of these kinetic models (Lox and Froment, 1993b; Yang et al., 2003) can predict a complete product distribution (inorganic species and hydrocarbons), whereas the kinetic model of Van der Laan and Beenackers (1998, 1999) can be used only to fit product distribution of total olefins and n-paraffins. The kinetic model of Van der Laan and Beenackers was extended to account separately for formation of 1- and 2-olefins, as well as n-paraffins. A simplified form of the kinetic model of Lox and Froment (1993b) has only five parameters at isothermal conditions. Because of its relative simplicity, this model is well suited for initial studies where the main goal is to learn techniques for parameter estimation and statistical analysis of estimated values of model parameters. The same techniques and computer codes were used in the analysis of other kinetic models. The Levenberg-Marquardt (LM) method was employed for minimization of the objective function and kinetic parameter estimation. Predicted reaction rates of inorganic and hydrocarbon species were not in good agreement with experimental data. All reaction rate constants and activation energies (24 parameters) of the Yang et al. (2003) model were found to be positive, but the corresponding 95% confidence intervals were large. Agreement between predicted and experimental reaction rates has been fair to good. Light hydrocarbons were predicted fairly accurately, whereas the model predictions of higher molecular weight hydrocarbons values were lower than the experimental ones. The Van der Laan and Beenackers kinetic model (known as olefin readsorption product distribution model = ORPDM) provided a very good fit of the experimental data for hydrocarbons (total olefins and n-paraffins) up to about C{sub 20} (with the exception of experimental data that showed higher paraffin formation rates in C{sub 12}-C{sub 25} region, due to hydrocracking or other secondary reactions). Estimated values of all model parameters (true and pseudo-kinetic parameters) had high statistical significance after combining parameters related to olefin termination and readsorption into one (total of 7 model parameters). The original ORPDM was extended to account separately for formation of 1- and 2-olefins, and successfully employed to fit experimental data of three major groups of hydrocarbon products (n-paraffins, 1-olefins and 2-olefins). This model is referred to as an extended ORPDM (8 model parameters in its final form). In general, all three groups of products were fitted well, and the estimated model parameters were all positive and the corresponding 95% confidence intervals were small. Even though the extended ORPDM provided a very good fit of experimental data, it can not be used for the prediction of product distributions for a given set of process conditions. This model has several pseudo-kinetic parameters whose values vary with process conditions. Additional work is needed to expand capabilities of the model to predict molar flow rates of all inorganic species and major hydrocarbon products in terms of true kinetic (temperature dependent) constants

A Medium-Scale Cryogenic Spill Study to Estimate Vapor Formation on Concrete Substrate

PresentationThis paper presents the findings of medium-scale (5 - 15 kg) cryogenic liquid experiments on a concrete substrate which may represent an industrial grade diking material. The temperature varying thermal characteristics, i.e. the conductivity (k) and heat capacity (Cp) of the concrete substrate were measured in the range of -160°C to 50°C using guarded hot plate and DSC, respectively. Vaporization rate of liquid nitrogen (LN2), liquid oxygen (LO2) and a mixture of 80% LN2 and 20% LO2, (i.e. liquid air) were studied on the same concrete substrate. It was found that conductive heat transfer from the concrete substrate has the greatest contribution in the vaporization of cryogenic liquids. The evidence of phase change from film boiling to nucleate boiling was observed during the pool vaporization of LO2. The effect of preferential boiling on the temperature and heat flux profiles inside the concrete substrate was also observed. The change of heat fluxes due to the preferential boiling after each refill of mixture liquids were found to vary from 3% to 15%. Finally, the recorded heat flux during the early and later stages of pool vaporization were 12.4 kW/m2 and 3.7 kW/m2 for LN2 and 12.9 kW/m2 and 2.96 kW/m2 for LO2

Use of a two-parameter Weibull distribution for the description of the particle size effect on dust minimum explosible concentration

Combustible dust explosion properties, like Minimum Explosible Concentration (MEC) and Minimum Ignition Energy (or Temperature), have a strong dependency on the particle surface area to mass ratio which varies with the particle size distribution. Unfortunately, the comparison of the dust explosion properties reported in the literature for a given dust material is often difficult because of the lack of description of the particle size distribution which is usually limited only to scattered information about the median (d50), mean, or one, two, or maximum three percentiles (e.g., d10, d50, and d90). This approach often gives conflicted conclusions or observations of no trend with measured independent parameters. It seems that a different approach is necessary to comprehensively describe the dependency of dust explosion properties on the particle size distribution. Such improvement could be achieved using a continuous probability distribution of which an example is a two-parameter normal distribution. However, the normal probability density function can only represent a symmetrical bell-shaped distribution which does not apply to the dust particle size analysis that often results in a skewed bell-shaped histogram. This study explored the use of a two-parameter (shape and scale) Weibull probability density function to describe a particle size distribution. A series of experimental data on the Minimum Explosible Concentration (MEC) of sulfur and polyethylene dust samples for which the particle distribution is measured were used to estimate the Weibull's scale and shape parameters. Two- and three-dimensional plots were generated to demonstrate the correlations of these parameters with MEC. The results show that as the scale and shape parameters increase, the MEC increases with higher dependence on the scale parameter (b). This is consistent with the initial conclusion where the MEC increases with increasing particle size. The paper discusses the advantages of using such an approach to describe the effect of particle size distribution on dust explosion properties but also shows that using only a median or mean of a particle size distribution to describe MEC may be misleading, especially if a sample represented by d50 as a coarse distribution contains a long tail of fine particles.Other InformationPublished in: Journal of Loss Prevention in the Process IndustriesLicense: http://creativecommons.org/licenses/by/4.0/See article on publisher's website: https://dx.doi.org/10.1016/j.jlp.2024.105269</p

Modeling of Fischer-Tropsch Product Distribution over Fe-based Catalyst

The kinetic models of Fischer-Tropsch synthesis (FTS) product distribution can be classified into two major groups: hydrocarbon selectivity models and detailed Langmuir-Hinshelwood-Hougen-Watson (LHHW) kinetic models. In this study the two approaches to FTS product distribution modeling are presented and compared using the experimental data obtained in a stirred tank slurry reactor with promoted iron catalyst over a wide range of process conditions. Positive deviations from the classical Anderson-Schulz-Flory distribution and an exponential decrease in olefin-to-paraffin ratio with carbon number are predicted by the inclusion of solubility-enhanced 1-olefin readsorption and/or chain length dependent 1-olefin desorption concepts. In general the agreement between the model predictions and experimental data was very good, and modeling approaches are discussed in terms of fit quality, physical meaningfulness and practical utility

Hydrocarbon selectivity models for iron-based Fischer-Tropsch catalyst

Two kinetic models of Fischer-Tropsch product selectivity have been developed based on reaction networks from the literature. The models were fitted to experimental data obtained using commercial iron-based catalyst in a stirred tank slurry reactor and under a wide range of process conditions. Results showed that both of the rival models were able to provide a satisfactory prediction of the experimental product distribution for n-paraffin, 1- and 2-olefin. The simpler of the two models, a reaction network with a single type of active sites and solubility enhanced 1-olefin readsorption term, was chosen as more adequate for practical use