Our research is highly multidisciplinary in the process safety area with intent to resolve the most critical safety problem in the industries, which is to prevent and mitigate hazardous phenomena including fire, explosion, and toxic release, from a molecular level to an enterprise scale.
Major Research Equipment: Process 11 Parallel Twin-Screw Extruder by Thermo Fisher Scientific, Cone Calorimeter and Oxygen Index by Fire Testing Technology, and RC1 Reaction Calorimeter with FTIR by Mettler Toledo
1. Molecular Level
Principles of chemistry, such as quantum chemistry and physical chemistry are used to predict hazardous properties and inhibit hazardous reactions at a molecular level.
Molecular modeling can also be combined with quantitative structure–property relationship (QSPR) models to predict flammability of hydrocarbons. Two PhD students have been working on QSPR and graduated. Minimum ignition energy (MIE) is one of the most important parameters when characterizing probability of ignition. For the first time, my research group has proposed two QSPR models based on limited existing experimental data. Both models are validated to have excellent performances and hence are qualified to predict MIE values for chemicals with no experimental data available. These two validated models can also help gain a better understanding of effects of molecular structures on ignition properties of hydrocarbon fuels. This research provides general guideline and methodology of establishing QSPR models to predict hazardous properties of chemicals. The preliminary result was published in Industrial & Engineering Chemistry Research and was featured by the magazine Advances in Engineering.
(1) Review of Recent Developments of Quantitative Structure-Property Relationship Models on Fire and Explosion Related Properties, Process Safety and Environmental Protection, 2019, 129, 280-290.
(2) Prediction of Minimum Ignition Energy from Molecular Structure Using Quantitative Structure-Property Relationship (QSPR) Models, Industrial & Engineering Chemistry Research 2017, 56 (1), 47–51
(3) Thermal decomposition pathways of hydroxylamine: theoretical investigation on the initial steps, Journal of Physical Chemistry A 2010, 114 (34), 9262-9269
Principles of physics, such as thermodynamics, heat transfer and mass transfer are applied to study fire retardant and fire suppression at a macroscale level.
Fire has long been a major hazard in our lives. According to the NFPA 2011 statistics data, 35% of the fires that occurred in the US were structure fires, of which 84% were homes. Polymeric materials have been used almost everywhere in buildings, manufacturing, and chemical processes but most of these materials are highly combustible. When it is used as films, coatings and foams, those thin objects are even more combustible than bulk materials. To control those polymeric fires, flame retardant technology is becoming increasingly important. In general, flame retardant additives are incorporated in the polymer matrix to increase the time to ignition, improve self-extinguishing properties, decrease the heat release rate and prevent the formation of flammable drops. The FTT cone calorimeter (ASTM E1354) and limiting oxygen index (ASTM D2863) are available in our lab for fire retardant testing.
Unlike fire consequence modeling, fire suppression modeling is still primitive. Water suppresses fire through primary physical effects, such as water vapor displaces oxygen, cooling of solid fuel surface and flame zone, high latent heat of vaporization. Not many agents have a suppression capability better than water. However, the suppression capabilities of water could be even improved with chemical additives. Water can serve as transporting media for some agents, which makes it the ideal medium to deliver some chemical additives to the fire site. We believe the combining chemical effects with physical effects of water will increase suppression efficiency significantly.
(1) Cone calorimeter analysis of flame retardant poly (methyl methacrylate)-silica nanocomposites, Journal of Thermal Analysis and Calorimetry 2017, 128 (3), 1443-1451
(2) Thermal degradation and flammability of nanocomposites composed of silica cross-linked to poly(methyl methacrylate), Plastics, Rubber and Composites: Macromolecular Engineering 2016, 45 (9), 375-381
(3) Optimization of Water Mist Droplet Size by Using CFD Modeling for Fire Suppressions, Journal of Loss Prevention in the Process Industries 2016, 44, 626–632
3. Plant Level
Principles of transport and sensor network are used to study chemical release/dispersion and vice versa to estimate emission source terms at a plant level.
One challenge of Carbon Capture and Storage (CCS) is how to identify CO2 leak locations in order to aid decision makers in emergency response. In the event of a release, it is important to know the current and future spatial extent of CO2 as well as its location. Relevant concentration sensors are required to detect the chemical where they can form a network of static sensors on the ground to estimate the source term. A benefit of this approach lies in early detection near places of strategic importance. The source term estimation from these sensor measurements is a problem in inverse modelling which is highly nonlinear. A hybrid algorithm with particle swarm optimization (PSO) was proposed to identify the source parameters including source strength and location. This is a good method for hazardous emission source estimation.
(1) Location of contaminant emission source in atmosphere based on optimal correlated matching of concentration distribution, Process Safety and Environmental Protection 2018, 117, 498-510
(2) Failure probability analysis of the urban buried gas pipelines using Bayesian networks, Process Safety and Environmental Protection 2017, 111, 678-686
(3) Consequence analysis of accidental release of supercritical carbon dioxide from high pressure pipelines, International Journal of Greenhouse Gas Control 2016, 55, 166–176
4. Enterprise Level
Principles of management, psychology, and human behaviors are combined with technical knowledge to address safety issues at an enterprise level.
There are different challenges at this level: technological, personnel, procedures, management, culture, and regulatory. Also, safety at this level is dynamic and evolves in structure and behavior over time. More precisely, human and management aspects of safety should be studied through the concepts of safety culture and safety climate. We have performed a human error analysis of the Macondo well blowout which has caused the largest non-intentional oil spill in history. The situation stemmed from a series of human errors through all stages of the project leading up to the blowout and subsequent explosion. An integrative framework to improve safety includes the environment, person, and behavior.
(1) Human error analysis of the macondo well blowout, Process Safety Progress 2013, 32 (2), 217-221