MKOPSC Theses and Dissertations

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Investigating Microbiologically Influenced Corrosion Using Co-culture Biofilms
(2018-11-19) Kotu, Susmitha Purnima; Jayaraman, Arul; Mannan, Sam; Mashuga, Chad; Han, Arum
A holistic understanding of microbiologically influenced corrosion (MIC) requires investigation of the underlying microbiological, metallurgical and electrochemical mechanisms. MIC studies are typically conducted using batch reactors or large scale flow loops that are nutrient-limited and have buildup of waste products. To overcome these disadvantages, we developed a continuous-flow, microfluidic microbiologically influenced corrosion model, M-MIC-1, comprising of carbon steel coated glass slide bonded to a microchannel imprinted in a polymer. Using M-MIC1, we investigated the effect of two biocides on short-term and long-term, single-species and co-culture biofilms of Shewanella oneidensis and Vibrio natriegens. We found that biocide resistance was impacted by biofilm type, biofilm growth time and the type of biocide. These results show the importance of conducting biocide screening studies with process fluids for effective MIC mitigation. Our studies illustrate that M-MIC1 flow model provides an ideal platform. To effectively comprehend MIC mechanisms, we developed M-MIC2 flow model that is amenable to dynamic and integrated measurements of biofilm dynamics and electrochemical impedance. M-MIC2 comprises of a two-metal electrode system with carbon steel and titanium bonded to a microchannel. Preliminary static and continuous-flow studies with single-species and co-culture biofilms of S. oneidensis and V. natriegens in M-MIC2 indicated some correlation of the variations in biofilm biomass to impedance spectra for S. oneidensis biofilms. We also hypothesized that a systems-level understanding of the microbial community and their metabolism can enhance the understanding of underlying mechanisms. Produced water from a MIC-impacted oil field was exposed to carbon steel coupons to mimic the corrosion environment in the laboratory. We observed an increased abundance (using 16S rRNA sequencing) of the genera, Nitratireductor and Desulfovibrio and unclassified genera of Rhodobacteraceae, Deltaproteobacteria, and Desulfobacteraceace. Based on the metagenome, we predicted an increased abundance of several genes related to energy, carbohydrate, lipid, and xenobiotic metabolism. This correlated to the increased abundance of measured metabolites (using untargeted metabolomics analysis) such as carboxylic acids, fatty acids, and amino acids that were earlier associated with MIC. These analyses can be repeated for multiple MIC-impacted field locations to delineate common features and identify metabolite biomarkers for MIC detection.
Surface-Active Nanoplate for Oil Recovery
(2020-03-23) Zhang, Lecheng; Cheng, Zhengdong; Akbulut, Mustafa; Hill, A. Daniel; Wang, Qingsheng
Janus colloidal surfactants with opposing wettability on two structural parts are receiving attention for their intriguing structural and practical application in various industries. Combining the advantages of molecular surfactants and particle-stabilized Pickering emulsions, Janus colloidal surfactants generate remarkably stable emulsions. This dissertation developed a straightforward and cost-efficient strategy to develop Janus nanoplate surfactants (JNPS) from aluminosilicate nanoclays materials, including Kaoinite and Halloysite, by stepwise surface modifications, including an innovative selective surface modification step. Such colloidal surfactants are found to be able to stabilize Pickering emulsions of different oil/water systems. The microstructural characterization of solidified polystyrene emulsions indicates that the emulsion interface is evenly covered by JNPS. The phase behaviors of water/oil emulsion generated by these novel platelet surfactants were also investigated. Furthermore, this dissertation demonstrated the application of JNPS for enhanced oil recovery with a microfluidic flooding test, showing a dramatic increase of oil recovery ratio. This research provides important insights for the design and synthesis of two-dimensional Janus colloidal surfactants, which could be utilized in biomedical, food and mining industries, especially for circumstances where high salinity and high temperature are involved.
The Effects of Advice-Giving and Advice-Taking on Safety Behavior: A Social Network Perspective
(2020-04-16) He, Yimin; Payne, Stephanie C; Bergman, Mindy E; Arthur, Jr., Winfred; Kwok, Oi-Man
Previous research suggests that safety behavior is an important antecedent of workplace safety that can be influenced by coworkers within the employee’s network. Drawing on the social network perspective, both advice and trust network structures (centrality and density) are proposed to influence resource exchanges among employees and thus impact their safety behaviors. The objective of the current study is to examine the extent to which: 1) advice-giving (indegree centrality) and advice-taking (outdegree centrality) impact safety behavior, 2) cognitive and affective trustworthiness (indegree centrality) and trust in coworkers (outdegree centrality) are related to advice-giving and advice-taking behaviors which in turn are expected to be related to safety behavior, and 3) advice network density relates to safety behavior. Four hundred sixteen nurses in 42 workgroups and their respective supervisors from a hospital in China each completed a survey. Data were analyzed using social network analysis and hierarchical linear modeling. Advice-giving was positively associated with safety behavior and this relationship was stronger when corresponding group members reported more advice-giving and advice-taking behaviors within the group. Further, cognitive and affective trustworthiness were positively related to advice-giving and subsequent safety behavior; whereas cognitive trust in coworkers was positively related to advice-taking. Both cognitive and affective trust in coworkers were not related to safety behavior. These findings highlight the relevance of the advice social network to safety behavior revealing in part the value of measuring social network variables to understanding workplace safety.
Develop a Hazard Index Using Machine Learning Approach for the Hazard Identification of Chemical Logistic Warehouses
(2019-11-04) Zhang, Zhuoran; Wang, Qingsheng; El-Halwagi, Mahmoud; Sasangohar, Farzan
With the rapid development of chemical process plants, the safe storage of hazardous chemicals become an essential topic. Several chemical warehouse incidents related to fire and explosion have been reported recently. Therefore, an accurate hazard identification method for the logistic warehouse is needed not only for the facility to develop a proper emergency response plan but also for the residents who live near the facility to have an effective hazard communication. Furthermore, the government can better allocate the resources for first responders to make fire protection strategies, and the stakeholders can lead to improved risk management. The storage of hazardous chemicals in a warehouse is a complex problem. The potential hazards include flammability, reactivity, and interaction among different types of hazardous chemicals. Hazard index is a helpful tool to identify and quantify the hazard in a facility or a process unit. Various hazard indices are developed in history. However, the challenge for this research is to improve the current method with the novel technique to implement our purpose. The first objective of this research is to develop a “Storage Hazard Factor” (SHF) to evaluate and rank the inherent hazards of chemicals stored in logistic warehouses. In the factor calculation, the inherent hazard of chemicals is determined by various parameters (e.g., the NFPA rating, the flammability limit, and the protective action criteria values, etc.) and validated by the comparison with other indices. The current criteria for flammable hazard ratings are based on flash point, which is proved to be insufficient. Two machine learning based methods will be used for the classification of liquid flammability considering aerosolization based on DIPPR 801 database. Subsequently, SHF and other warehouse safety penalty factors (e.g., the quantity of the chemicals, the distance to the nearest fire department, etc.) are utilized to identify the Logistic Warehouse Hazard Index (LWHI) of the facilities. In the last chapter, LWHI is applied to an actual case from Houston Chronicle, and several statistical analyses are used to prove that the LWHI is helpful for hazard identification to emergency responders and hazard communication to the public.
Process Hazard Evaluation and Safer Design for Oxidation of Secondary Alcohols to Ketones Using Hydrogen Peroxide
(2019-11-08) Sun, Yue; Wilhite, Benjamin; Mashuga, Chad; El-Halwagi, Mahmoud; Banerjee, Debjyoti
Ketones are industrially produced in large quantities. They find application as solvents and polymer and pharmaceuticals precursors. Substantial efforts have been put towards a green oxidation of alcohols to ketones with aqueous hydrogen peroxide as an oxidant including research for identifying appropriate reaction conditions and employed catalysts. Because of the use of hydrogen peroxide, the study of this reaction from a safety point of view prior to its scale-up is of preponderant importance. Herein, the purpose of this work is to conduct process hazard evaluation of this catalytic reaction and to propose safe process design. Various calorimetric and analytical techniques are used to study the thermal and kinetic behavior, helping identify reaction pathways and safety issues associated with the reaction. Differential scanning calorimetry (DSC) is used to gain insight into the potential reactivity hazards related to the process; Phi-TEC II adiabatic calorimetry measurements is performed to obtain detailed information of the worst reaction runaway scenarios; 100 ml reactor with oil jacket is used to assess the reaction behavior close to normal conditions at minor scale; RC1e heat-flow isothermal calorimetric measurements is conducted for assessing conditions relevant to normal process operations (e.g. stirring rate and heat release) and to evaluate the effect of solvent vaporization on reaction temperature. Gas chromatography-mass spectrometry (GC-MS) were used to analyze the final products. DSC results for 2-octanol and 2-butanol reaction systems were presented, and two highly exothermic reactions are found for both. Especially, for 2-octanol oxidative reaction, Phi-TEC II results again reveal two highly exothermic reactions occurred during testing process. Besides, GC-MS data verify that both exothermic peaks were owing to the alcohol oxidation, thus indicating that in the conditions of the reaction and with the employed catalysts, hydrogen peroxide did not fully decompose at lower temperatures. Non-condensable gas generation measurements through Phi-TEC II validated this argument. The RC1e results verified that 2-octanol conversion was higher at higher stirring rates, while evaporative cooling of solvents tempered the reaction by removing the heat generated, thus improving safety. These findings can be further used to propose safer operating measures for design and scale-up of this reaction process to avert a potential runaway and to probe in the reaction pathways to increase inherently safer conditions for its performance.
Cumulative Risk Assessment to Analyze Increased Risk Due to Impaired Barriers in Offshore Facilities
(2019-04-09) Halim, Syeda Zohra; El-Halwagi, Mahmoud; Mashuga, Chad; Karim, Nazmul; Schubert, Jerome
Investigation of past incidents always reveal deficiencies that are not directly equipment-related, but may be non-technical in nature, such as procedural deviation, inadequate communication etc. Past risk assessment models only provide semi-quantitative approaches to incorporate such learning from past incidents and cannot capture their dynamic nature and dependency within a single model. Current research takes up the challenge of developing a novel approach and step-by-step methodology for quantitatively merging technical, operational, human and organizational factors contributing to the cumulative risk of barrier failure. It also addresses their dynamic changes with time, considers interactions among each other and incorporates uncertainty of parameter estimation to assess the total risk. First, a methodology is developed and implemented for extracting statistical data of contributing factors behind past incidents from investigation reports. The study produces a generic dataset of contributing factors in 137 fire incidents from the US Outer Continental Shelf (OCS). Analysis shows that failures rates of contributors are non-constant and can be modelled as non-homogenous Poisson process with Power Law distribution. Hierarchical Bayesian Analysis is utilized to predict probability of failure within a time period and next time of occurrence from the generic data. Results show reliability growth for contributors related to ‘design flaw’ and ‘inadequate job safety analysis’ in the OCS, although a majority of other contributors show deterioration. In the next stage, near-miss data from a particular facility is incorporated to obtain plant- specific understanding of how and when their next critical failure may occur. Interaction among contributing factors are measured from the analysis of investigation reports. Finally, a cumulative risk assessment model for an offshore unit with safety instruments is developed, where the contributing factors are mapped onto Bayesian Network to provide probability distributions of barrier failure and subsequent incidents. A case study is adopted to show how extracted information from investigations can be utilized to update generic data and obtain probability distributions of individual barrier failure. This research will aid management to identify key organizational issues that contribute to an increased risk of barrier failure, so that better resource allocation can be ensured.
LNG Suppression Foam Stabilized By Zirconium Phosphate Nanoplatelets
(2015-04-14) Zhang, Lecheng; Cheng, Zhengdong; Zhu, Ding; Mannan, Sam M
In this work, a zirconium phosphate based universal foam stabilizer was developed to stabilize and improve performance of firefighting foam and high expansion liquid natural gas (LNG) suppression foam. With the world’s increasing demand for natural gas, a large quantity of natural gas is transported in liquid natural gas form. The safety issues related to LNG are of critical concern in LNG process safety. High expansion LNG suppression foam was developed to mitigate accidental LNG spillage. Particle stabilized Pickering emulsion, which mainly the mixture of oil and water, was studied in detail for application in the chemical and oil industries. The advantage of the particle surfactant compared to the conventional surfactant is well understood. A particle stabilized gas-liquid mixture, Pickering foam, is still an emerging topic in soft matter. Pickering foam is studied in this work. Different foam formulas were mixed with propylamine exfoliated ZrP nanoplatelets. Foam stabilities were tested under different conditions, including high salinity and extreme temperatures. We found reduced drainage rate and extra surface stability induced by platelets were two factors which contributed to the excellent stability of our Pickering foam. LN2 was used to simulate the evaporation process of LNG suppressed by different foam formulas. Experimental results proved LN2 evaporation rate in the ZrP-PA added foam was modestly lower than conventional foam.
Thermal Hazard Analysis of Nitroaromatic Compounds
(2019-07-18) Zhu, Wen; Mashuga, Chad; Holste, James; Wilhite, Benjamin; Banerjee, Debjyoti
Nitroaromatic compounds are among the largest group of industry chemicals. Due to the high bond-association energy (BDE) of the C-NO2 in nitroaromatic compounds (297 ± 17 kJ/mole), once the runaway reaction is triggered, the compounds will release massive heat and gases that accelerate the system temperature and pressure increase that lead to an explosion instantly. Mononitrotoluenes (MNT) is among most important nitroaromatic compounds used as intermediates for the synthetic pharmaceuticals, agrochemicals and precursors for TNT. However, in the past 30 years, serious incidents, owing to its thermal decomposition, have killed 88 people and injured more than 900. To help prevent future thermal runaway behavior of the nitroaromatic compounds, this work presents using both the experimental and simulation methodologies to figure out the thermochemistry and thermodynamics starting from MNT. The understanding of the thermal behaviors and mechanisms can yield safer handling and storage of the reactive chemicals. To investigate the mechanisms that cause the ortho-nitrotoluene (2-NT, isomer of MNT) decomposition reactions, the effects of different incompatible substances and surrounding conditions, such as confinement, heating rate, induction effect and sample sizes, were studied using three types of calorimetry – DSC, ARSST and APTAC. Experimental results suggest that: 2-NT is the most hazardous reactive chemical among the three isomers of MNT with the much higher pressure rise rate than the others. It is an autocatalytic reaction follows three stages: induction phase, acceleration phase and decay phase. The induction phase follows the zero order reaction with activation energy (170-174 kJ mol-1 ) and preexponential factor (1011.6 -1011.7 s -1 ). The main decomposition pathway during reduction phase is the generation of anthranil and water. The six common contaminants (NaOH, Na2SO4, CaCl2, NaCl, Na2CO3 and Fe2O3) that exist in the manufacturing process of MNT lower the thermal stability of 2-NT with the three proposed mechanisms (generation of OH- , impact of chloride ions and Iron (III) oxide catalyzed nitroarenes reduction). This work demonstrates the complexity and the multiple studies required for making MNT safer, providing suggestions to the nitroaromatics industry. It can also serve as an example for comprehensive studies on various reactive chemicals.
Effect of Dust Dispersion and Morphology on Dust Deflagration Hazard
(2019-04-05) Bagaria, Pranav; Mashuga, Chad V; Holste, James C; Cheng, Zhengdong; Petersen, Eric L
Dust explosions have led to numerous fatalities, injuries and property loss. Standards (ASTM, ISO etc.) mention a 20 L or a 1 m^3 apparatus to measure explosion parameters. These standards assume the dust particle size distribution remains unaltered post-dispersion in these apparatus. Recent studies have shown that dispersion in the standard 20 L apparatus, widely used for dust explosion properties measurement, leads to significant particle breakage. Reduction in particle size distribution due to dispersion can lead to erroneous risk assessment due to association of explosion parameters with pre-dispersion particle size distribution. This research investigates various factors that affect dust particle size reduction during dispersion and studies the effect of dust particle shape on minimum ignition energy (MIE). First, we explored the role of outlet valve, dispersion nozzle, cloud turbulence, and dust concentration on particle breakage. Also, the behavior of nanomaterial post-dispersion was analyzed. Results show significant particle breakage occurs due to outlet valve, nozzle, and cloud turbulence. An inverse relation between dust concentration and particle breakage was found. Nanomaterial de-agglomerates post-dispersion generating large surface area, thereby increasing explosion hazard. Second, we analyzed particle breakage due to dispersion in the MIE apparatus. Results show that MIE apparatus does not cause particle breakage but it alters the size distribution of electrostatic dusts significantly, which can affect ignition energy measurement of electrostatic dusts. Third, consequence of particle breakage due to dispersion on MIE was studied. Results show significant reduction in the MIE value of the dust post-dispersion, highlighting increased risk. Fourth, dependence of size reduction due to dust dispersion on different materials was studied. A sigmoidal correlation between particle breakage due to dispersion and the mechanical properties (brittleness index) of materials was established allowing process industries to identify dusts susceptible to breakage during explosion testing. Finally, we examined the effect of particle morphology on MIE of dusts. By testing spherical and irregular shaped material with similar size distribution, we demonstrated that morphology significantly impacts the MIE of dusts and should be included as a factor in risk assessment. This research will result in improved ASTM testing standards and accurate risk assessment for better safety measures.
Experimental and Theoretical Study on Stability of High Expansion Foam Used for LNG Vapor Risk Mitigation
(2019-02-28) Krishnan, Pratik; Cheng, Zhengdong; El-Halwagi, Mahmoud; Anand, Nagamangala; Wu, Hung-Jen
Liquefaction of natural gas is an effective way to easily store and transport natural gas. A spill of liquefied natural gas (LNG) can result in the formation of a vapor cloud, which can migrate downwind near the ground because of a density greater than air. This cloud has the potential to ignite, and presents an asphyxiation hazard as well. The National Fire Protection Association (NFPA) recommends the use of high expansion (HEX) foam to mitigate the vapor risk due to cryogenic LNG. This dissertation studies the effects of forced convection and thermal radiation on HEX foam breakage. A lab-scale foam generator was used to produce HEX foam and carry out experiments to evaluate the rate of foam breakage, the amount of liquid drained from foam, the vaporization rate of the cryogenic liquid, and the temperature profile in the foam. In addition, zirconium phosphate (ZrP) nanoplates were utilized to improve the stability of HEX foam. A heat transfer model was also developed to estimate HEX foam height that should be applied. The results indicated that forced convection and thermal radiation can significantly affect foam breakage rates. Therefore, accounting for these effects provides a better estimate for the amount of foam that needs to be applied for effective vapor risk mitigation. Nanoplates could be used to improve HEX foam stability and showed lower foam breakage rates. The heat transfer model predicted the height of the HEX foam that needs to be applied for outgoing vapors to be naturally buoyant.
Developing Leading Indicators Framework for Predicting Kicks and Preventing Blowouts
(2019-02-08) Tamim, Md Nafiz Ekram; Karim, M. Nazmul; Hasan, A. Rashid; El-Halwagi, Mahmoud M; Holste, James C
Due to the operational complexities of drilling, completion and well intervention activities, it is often quite challenging to predict a potential blowout scenario timely and efficiently. In drilling operations, blowouts are usually preceded by kicks and predicting kicks early is crucial for regaining control of the well and preventing major incident. Kicks and blowouts happen due to failure of well control barriers and leading indicators could be very effective in identify vulnerabilities in such systems. For assessing integrity of well control barriers with appropriate sets of leading indicators, a robust framework was proposed and sets of probabilistic models were developed in this work. By following a systematic cause-based methodology proposed in this work, sets of leading indicators were identified for monitoring barrier performances while drilling, completion and well intervention activities. Analyses of Montara and Deepwater Horizon blowout incidents demonstrated applicability of leading indicators framework in revealing system weaknesses prior to major incidents. Using the real-time kick indicators, decision support algorithms were developed in this work which would help to understand a kick progression scenario and actions required to confirm a kick. Leading indicators-based probabilistic models were developed for evaluating the relative importance of different organizational and operational factors, and assessing their impacts on the key causal factors of well control barrier failure events. These models were constructed for hydrostatic head failure events which can be caused by abnormal pore pressure and swabbing, and cementing failure during drilling and completion activities. An integrated iii model for assessing well control failure events during wireline operations was also constructed. These models represent realistic scenario of barrier health and could be very useful for determining barrier failure probabilities from observed data. Addition to these, efficiencies of kick detection parameters to detect potential influxes and factors impacting their performances can also be assessed with the developed models. These functions enable informed decision-making for preventing kicks and blowouts while drilling or intervening a well, by providing real-time status of the well control system.
Study of Cryogenic Vaporization Source-Term Due to Heat Transfer from the Solid Substrate
(2017-04-10) Ahammad, Monir; Mannan, Sam; Vechot, Luc; Holste, Jame; Petersen, Eric
U.S. regulation requires LNG facilities to demonstrate a safe exclusion zone for public safety. European safety case also requires that the facility will demonstrate their risk level within a tolerable limit. Thus, cryogenic liquids (i.e., LNG) release scenarios needs to be modeled to determine consequence severity and perceived risk level. The existing models and tools are very sensitive to the inputs, also known as source-terms. Inaccurate inputs might result in an amplified or subdued consequence severity and may change the estimated risk level and/or safety exclusion zone. Accurate prediction of the source-terms is complex due to the presence of boiling regimes and requires validated models of boiling regimes. A CFD-based approach is taken to model film boiling using Rayleigh-Taylor instability and volume of fluid (VOF) methods. Film boiling simulations for LN2, LO2, and LNG are conducted with a various degree of wall superheat. The simulated results were compared with Berenson and Klimenko correlations to demonstrate that CFD model overcomes the limitations of these correlations. To extend the applicability of these simulations, a first principle model is proposed to enable a faster calculation of heat transfer to cryogenic pool boiling. Medium-scale cryogenic spill experiments have been conducted on an instrumented concrete substrate where LN2, LO2, and liquid air are used. The vaporization rate, temperature, and heat flux profiles are recorded during the experiments. It is found that the effect of the mixture on the LN2 vaporization rate is not significant and the heat conduction inside the concrete substrate is unidirectional. The proposed CFD-based film boiling models for LN2 and LO2 are validated using medium-scale experimental data and are in agreement for higher wall superheats but slightly deviates for the lower wall superheats. The deviation in experimental data can be attributed to the surface roughness and change in boiling regime from film to nucleate. The model for LNG is validated against the experimental data reported in the literature. It is found that the model can capture the vaporization rate reported from the Maplin Sands experiments and other laboratory tests on film boiling.
Safer Operational Conditions for Natural Gas Processing in Transmission Line to LNG Plants
(2018-11-21) Napaporn, Wongwaran Andrew; El-Halwagi, Mahmoud; Hilaly, Ahmad; Sasangohar, Farzan
Carbon dioxide must be removed from natural gas before liquefying the gas because it freezes in pipelines and corrodes process equipment. There are several processes that can be used to remove CO2 from natural gas. The most common processes are chemical and physical absorption. Implementation of other processes such as adsorption, membrane separations and cryogenic distillations are also found all over the world. However, only chemical absorption and physical absorption processes meet the specification of COv2 to be less than the required specification in the United States for preventing corrosion in transmission lines. Therefore, the current study focuses on these two processes. In each process, there are various ways to operate. The objective of this work is to find the optimal process and operating conditions, which cost us the least between the two given where the specification of the natural gas is achieved. Aspen HYSYS was used to simulate all the processes mentioned and Aspen Economic Evaluation was used to calculate the expenses of the processes. Corrosion rate and pipeline cost were evaluated using the NORSOK corrosion model. The process operational cost and pipeline cost have been evaluated and compared to find the suitable COv2 removal process and optimal condition for various pipeline distance.
Process Resilience Analysis Framework for Design and Operations
(2018-11-27) Jain, Prerna; Karim, Nazmul; Pistikopoulos, Stratos; El-Halwagi, Mahmoud; Ferris, Thomas
Process plants are complex socio-technical systems that degrade gradually and change with advancing technology. This research deals with exploring and answering questions related to the uncertainties involved in the process systems, and their complexity. It aims to systematically integrate resilience in process design and operations through three different phases of prediction, survival, and recovery using a novel framework called Process Resilience Analysis Framework (PRAF). The analysis relies on simulation, data-driven models and optimization approach employing the resilience metrics developed in this research. In particular, an integrated method incorporating aspects of process operations, equipment maintenance, and process safety is developed for the following three phases: •Prediction: to find the feasible operating region under changing conditions using Bayesian approach, global sensitivity analysis, and robust simulation methods, •Survival: to determine optimal operations and maintenance strategies using simulation, Bayesian regression analysis, and optimization, and •Recovery: to develop a strategy for emergency barriers in abnormal situations using dynamic simulation, Bayesian analysis, and optimization. Examples of a batch reactor, and cooling tower operations process unit are used to illustrate the application of PRAF. The results demonstrate that PRAF is successful in capturing the interactions between the process operability characteristics, maintenance, and safety policy. The prediction phase analysis leads to good dynamic response and stability of operations. The survival phase helps in the reduction of unplanned shutdown and downtime. The recovery phase results in in reduced severity of consequences, and response time and overall enhanced recovery. Overall, PRAF achieves flexibility, controllability and reliability of the system, supports more informed decision-making and profitable process systems.
Phase Equilibrium Studies on N-Oxidation Systems to Determine Homogeneous Mixture Conditions
(2018-10-24) Sunder Janardanan, .; Holste, James; Jeong, Hae-Kwon; Wilhite, Benjamin; Banerjee, Debjyoti
The N-oxidation of alkylpyridines is used in the pharmaceutical industries to synthesize alkylpyridine N-oxides that are involved in the production of analgesic and anti-inflammatory drugs. The synthesis process involves continuous addition of aqueous hydrogen peroxide (35% w/w) solution to a mixture of alkylpyridine and phosphotungstic acid catalyst. The oxidation is accompanied by undesired decomposition of hydrogen peroxide, which produces large amounts of oxygen and water vapor. This reaction introduces a series of hazards during the operation including the potential to over pressurize an improperly vented reactor and generation of an oxygen-rich atmosphere in an alkyl pyridine flammable environment. The decomposition is accelerated during the N-oxidation of higher order alkylpyridines (lutidines, collidines) due to mass transfer limitations caused by the separation of the liquid into organic and aqueous phase. Also, the presence of phosphotungstic acid (catalyst) in the aqueous phase further intensifies the peroxide decomposition reducing the safety and efficiency of the process. It is thus essential to identify homogeneous reaction conditions and operate the reactor in a regime where phase separation is prevented. The immiscibility between the alkylpyridine and water is primarily responsible for the liquid phase heterogeneity during the N-oxidation. The current work addresses this research gap by investigating the influence of the alkylpyridine N-oxide on the phase separation since the N-oxide is known for its increased reactivity. Experimental and theoretical studies were conducted on 2,6-lutidine/2,6-lutidineN-oxide/water mixtures at different temperatures. The phase equilibrium experiments were conducted at 110 °C in lab-scale calorimeters wherein the ternary mixtures were analyzed with the help of in-situ FTIR spectroscopy. It was found that the extent of heterogeneity between 2,6-lutidine and water is reduced dramatically by the presence of 2,6-lutidine-N-oxide as indicated by the phase diagram. In order to support the experimental work, the UNIQUAC thermodynamic model was used to estimate the biphasic compositions and predict the LLE curve for the ternary mixture. The energy parameters used in the equations, which describe the intermolecular interactions were calculated based on molecular dynamics simulations. Apart from this, the molecular parameters for N-oxide were obtained by following a quantum mechanical approach, which utilized a surface building algorithm for constructing the molecular surface. The results predicted by the model provide a satisfactory representation of the experimental data at T = 110 °C. In addition to this, the influence of temperature on the phase behavior was studied by generating phase equilibrium data at T = 100 and 125 °C. The findings from this research study can be used to implement the inherent safety concept – “Hybridization” to the N-oxidation system wherein the concentration of product N-oxide can be controlled to maintain a less hazardous environment.
Flammability Characteristics of Light Hydrocarbons and Their Mixtures at Elevated Conditions
(2018-11-01) Gan, Ning; Karim, Nazmul M.; Bukur, Dragomir B.; El-Halwagi, Mahmoud M.; Petersen, Eric L.
Accurate data of flammability limits for flammable gases and vapors are needed to prevent fires and explosions. The flammability limit is the maximum or minimum fuel concentration at which a gas mixture is flammable in a given atmosphere. Even though investigations of flammability limit have been carried out for decades, data are still scarce and sometimes unavailable. Through years of study, people have developed estimation and approximation methods for the prediction of flammability limit. However, these methods exhibit significant variations, especially at elevated temperatures and pressures. This research focuses on the flammability limits of light hydrocarbons (methane, propane, and ethylene) and their binary mixtures at normal and elevated conditions. The flammability limits of pure light hydrocarbons, and binary mixtures were determined experimentally at the temperature up to 300ºC and initial pressure up to 2atm. The experiments were conducted in a closed cylindrical stainless steel vessel with upward flame propagation. The combustion behavior and different flammability criteria were compared and the 7% pressure increment was determined as the most appropriate criterion for the test. Experimentally measured pure hydrocarbon flammability limits are compared with existing data in the literature to study the influence of temperature, pressure, and apparatus set. An estimation model was developed for the prediction of pure light hydrocarbon flammability limit at elevated conditions. For binary mixtures, experiment data were compared with predictions from Le Chatelier’s Rule to validate its application at elevated conditions. It was discovered that Le Chatelier’s rule works fairly well for the lower flammability limit of mixtures only. The explanation of the difference between upper flammability limit predictions with experimental data was investigated through the reaction pathway analysis using ANSYS CHEMKIN software. It was proved that for the upper flammability limit test, ethylene was more reactive than methane and propane in the combustion process. Finally, a modified Le Chatelier’s rule model was developed and validated using experimental data.
Risk Analysis Including Organizational Aspects In Process Industries
(2015-07-09) Park, Younggil; Mannan, Sam; El-Halwagi, Mahmoud; Wortman, Martin
The lack of management of organizational change has been found to be a contributing factor in a number of accidents. Proper management of organizational change considering the possible process safety incidents is essential to solve this problem. The key to successfully managing organizational change is to effectively assess the associated risks. In this research an Organizational Change Risk (OCR) model is developed for the purpose of a quantitative risk assessment that includes organizational change aspects. This model quantitatively assesses the effect of various organizational changes on the risk of process safety incidents and shows how and how much organizational change influences the risk. The OCR model starts from identifying the major incident scenario and developed Bow-Tie (BT) diagram which illustrate a scenario from causes to effects. Then Organizational Change Factors (OCFs), which show the status of change in an organization in comparison to its previous condition and determined by survey and indicator metric, are incorporated into the Bow-tie. Finally, the Bayesian Network (BN) model is applied for the sake of dynamic analysis to calculate the frequency of the incidents and consequences. In order to demonstrate the applicability, the model is tested using a hypothetical case of a company that made organizational change by divesting one of their plants to another company. The results of the case study show that the model is useful in identifying the organizational factors that predominantly affect the risk, quantifying the change of frequency of process safety incidents due to organizational change, evaluating the impact on the safety barriers that mitigate and prevent incidents, and determining how much organizational factors have to be improved to decrease process safety incidents.
Pipeline Risk Assessment Using Dynamic Bayesian Network (DBN) for Internal Corrosion
(2018-08-03) Palaniappan, Visalatchi; Mannan, Sam; Banerjee, Debjyoti; Schubert, Jerome
Pipelines are the most efficient mode of transportation for various chemicals and are considered as safe, yet pipeline incidents remain occurring. Corrosion is one of the main reasons for incidents especially in subsea pipelines due to the harsh corrosive environment that prevails. Corrosion can be attributed to 36% amongst all the causes of subsea pipeline failure. Internal corrosion being an incoherent process, one can never forecast exact occurrences inside a pipeline resulting in highly unpredictable risk. Therefore, this paper focuses on risk assessment of internal corrosion in subsea pipelines. Corrosion is time-dependent phenomena, and conventional risk assessment tools have limited capabilities of quantifying risk in terms of time dependency. Hence, this paper presents a Dynamic Bayesian Network (DBN) model to assess and manage the risk of internal corrosion in subsea. DBN possesses certain advantages such as representation of temporal dependence between variable, ability to handle missing data, ability to deal with continuous data, time- based risk update, observation of the change of variables with time and better representation of cause and effect relationship. This model aims to find the cause of internal corrosion and predict the consequence in case of pipeline failure given the reliability of safety barrier in place at each time step. It also demonstrates the variation of corrosion promoting agents, corrosion rate and safety barriers with time.
DEVELOPMENT AND APPLICATION OF PROCESS SAFETY INDICES IN EARLY DESIGN PHASE OF CHEMICAL SUPPLY CHAIN
(2018-08-06) Roy, Nitin; Mannan, M Sam; Hasan, MM Faruque; El-Halwagi, Mahmoud; El-Jack, Fadwa; Butenko, Sergiy
Supply chain network design and optimization are very important in decision making, which gives the ability to stakeholders to assess the massive supply chains to increase profit while minimizing risks. Risks in supply chains arise from various sources such as demand, supply and manufacturing. One of the significant sources is the supply chain disruptions caused by chemical and process hazards during the transportation, manufacturing and storage of chemicals. Process safety engineering is the study of hazards and risks in the chemical process industry and deals with the prevention and mitigation of the risks. The concept of process safety has grown exponentially during the last two decades. Risk analysis techniques such as Hazard and Operability (HazOp) Analysis and Layer of Protection Analysis (LOPA) are well-established. However, they need large amounts of information that is not available during early design. Several quantitative and semi-quantitative safety indices such as Inherent Safety Index and Dow Fire and Explosion Index have been published which can be used at early design. But, there is a need for classification and critical analyses of these indices for correct usage. This study presents a critical discussion of published indices which includes classification into categories such as application industry, input type, and model aggregation; and lists advantages and disadvantages of each index. This will help researchers and engineers select correct safety index for their application. Supply chain is a part of product life-cycle. Often, supply chain analysis overlooks the hazards at consumer level. Several of the products used every day such as propane grills, batteries, and spot removers are hazardous if not used properly. This study shows a systematic way of analyzing injuries due to hazardous consumer products. A brief introduction of propane supply chain is presented. NEISS database has been analyzed for consumer propane injuries and several recommendations have been derived for the consumer propane market. It was inferred that there is a lack of awareness of hazards of propane products at home, which result in high number of injuries to face due to flash burns. Quantification of chemical and process hazard is necessary in decision making and is one of the challenges faced by the chemical process industry. Moreover, due to the complexities of the process and limited understanding of the chemicals, the risk and hazards posed are uncertain in nature. This study develops a novel framework of holistically analyzing supply chain network design and process safety. This work shows how the hazards in the supply chain drive the upper bounds on the flow for each entity in the supply chain. Secondly, the general supply chain formulation has been revised to integrate these bounds. The supply chain formulation described here is a non-linear mixed integer programming (MINLP) model with a case study in ammonia supply chain. The results show that in a chemical supply chain profit is an increasing function of hazard bounds.
Towards The Development of Biosensors for the Detection of Microbiologically Influenced Corrosion (MIC)
(2018-08-07) Kannan, Pranav; Vaddiraju, Sreeram; Mannan, M. Sam; Jayaraman, Arul; Castaneda, Homero; Wortman, Martin A
Corrosion is one of the biggest concerns for mechanical integrity of infrastructure and infrastructural components, such as oil refineries, bridges and roads. The economic cost of corrosion is typically estimated to be between 1 to 5 % of the gross national product (GNP) of countries, of which the contribution of microbiologically influenced corrosion (MIC) is estimated to be between 10% and 50%. Current state-of-the-art approaches for detecting MIC primarily rely on ex-situ tests, including bacterial test kits (bug bottles); corrosion coupons, pigging deposits analysis and destructive analysis of MIC affected sites using SEM, TEM, and XRD. These ex-situ measurements do not capture the complexities and time sensitivities underlying MIC. This is owed to the fact that the proliferation of the microbial contamination is a dynamic and rapid process, and any delay can prove expensive as it is estimated that once the biofilm formation takes place the amount of biocides needed is magnitude of orders more as compared to when the bacteria are in planktonic form. Additionally, the field environment is a complex biotic and abiotic environment which is often difficult to replicate even in high fidelity laboratory models. Hence a real-time/pseudo real-time method of detection would greatly help reduce the costs and optimize biocide-based mitigation of MIC. To overcome the above-mentioned shortcomings associated with the state-of-the-art; this work is aimed at the development of a sensor substrate whereby highly specific detection can be carried out in the environment where the corrosion exists, in a real-time/pseudo real-time basis. More specifically, the research is aimed at the development of sensors based on a nanowire matrix functionalized with biomolecules which can perform this specific and real-time detection of MIC in the pipeline environment. Here, the detection of MIC is based on the binding of specific biomolecules causing MIC to organic molecules anchored on top of the nanowires. These sensors also need to be inexpensive (made of low-cost, earth abundant materials), have low power consumption, and robustly deployable. The primary component of the detection platforms are copper oxide nanowire arrays (CuONWs with lengths of 25 to 30 m, 50 to 100 nm in diameter) and silicon nanowires arrays (SiNWs with lengths of 5 to 8 m, 45 to 100 nm in diameter). They are synthesized using facile and scalable techniques and are selected for their robust electrical and mechanical properties. Electrochemical degradation studies of the NWs were performed in 3.5 wt. % NaCl solution and simulated produced water using polarization and electrochemical impedance spectroscopy (EIS). The NWs systems showed robust resistance to degradation despite higher surface area (as compared to bulk counterparts), and both diffusion limitations and charge transfer resistance was observed on the analysis of the impedance response. The ability to immobilize a variety of moieties on the nanowire platforms gives them the ability to detecting a wide variety of MIC biomarkers. The Biotin-Streptavidin (SA) complex was used as a proof of concept to test the viability of the NW arrays as a substrate for sensing. A custom test bed was built for the functionalized NW thin films, and cyclic voltammetry studies revealed a stable current response with time for 10nM and 10,000 nM SA concentrations. The use of different probes such as aptamers to larger immunoglobulin probes provides the flexibility to detect the full spectrum of biomarkers. The development of these next generation sensor platforms along with the methodologies employed to stabilize them and assemble them into functional devices are explored in detail in this dissertation.

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