• Energy Research

Abstract This study presents a mathematical model and experimental verification of factors influencing thermal runaway propagation of NCM811/C lithium-ion battery module after fast charging operation. The key factors considered for the thermal runaway propagation include charging C-rate, battery spacing, triggering temperature, speed, and interval of the thermal runaway propagation. The analysis of the 3D model shows that increasing the spacing and triggering temperature of the battery will reduce the risk of thermal runaway propagation of the battery module and change the order of thermal runaway propagation. Further, the thermal runaway propagation speed increases gradually with the propagation process; however, it is inhibited by increasing triggering temperature and battery spacing and the decrease of charging C-rate. These observations play a critical role in the lithium-ion battery pack design.

Abstract This study presents a mathematical model and experimental verification of factors influencing thermal runaway propagation of NCM811/C lithium-ion battery module after fast charging operation. The key factors considered for the thermal runaway propagation include charging C-rate, battery spacing, triggering temperature, speed, and interval of the thermal runaway propagation. The analysis of the 3D model shows that increasing the spacing and triggering temperature of the battery will reduce the risk of thermal runaway propagation of the battery module and change the order of thermal runaway propagation. Further, the thermal runaway propagation speed increases gradually with the propagation process; however, it is inhibited by increasing triggering temperature and battery spacing and the decrease of charging C-rate. These observations play a critical role in the lithium-ion battery pack design.

Darcy’s law has long been used to describe the flow in porous media. Despite the progress that took place in oil production industry research, it became clear that there is a loss of pressure, especially in the area near the wellbore region, where Darcy’s law is not applicable. For this reason, Forchheimer presented his equation in 1910, where he added a new term to Darcy’s law dealing with pressure loss due to inertial forces by introducing a new term, the β coefficient, into the equation. This paper presents a study of fluid flow through porous media, where water was used as a working fluid. Furthermore, the characteristics of the non-Darcy flow were analyzed by presenting the corresponding pressure and velocity gradient curves for each pressure. Extensive analysis indicates that many of the correlations available in the literature either have defective units or are the product of a small number of experiments. In this study, we benefit from relatively large samples, the radial flow, and the perforation in the middle of the samples. The properties of the samples were measured using mercury intrusion porosimetry. It was found that there is a direct relationship between the porosity and the grain’s size; the greater the size of the grains, the greater the porosity, and vice versa. The non-Darcy coefficient term, β, is found to be inversely proportional to the porosity and permeability. In a previous study, the β was investigated for compressible flow scenarios; however, this study calculated it for an incompressible flow. Finally, by analyzing the β values of both studies, we could deduce new novelty correlations for the β coefficient term, where the permeability, porosity, and tortuosity are included.

Darcy’s law has long been used to describe the flow in porous media. Despite the progress that took place in oil production industry research, it became clear that there is a loss of pressure, especially in the area near the wellbore region, where Darcy’s law is not applicable. For this reason, Forchheimer presented his equation in 1910, where he added a new term to Darcy’s law dealing with pressure loss due to inertial forces by introducing a new term, the β coefficient, into the equation. This paper presents a study of fluid flow through porous media, where water was used as a working fluid. Furthermore, the characteristics of the non-Darcy flow were analyzed by presenting the corresponding pressure and velocity gradient curves for each pressure. Extensive analysis indicates that many of the correlations available in the literature either have defective units or are the product of a small number of experiments. In this study, we benefit from relatively large samples, the radial flow, and the perforation in the middle of the samples. The properties of the samples were measured using mercury intrusion porosimetry. It was found that there is a direct relationship between the porosity and the grain’s size; the greater the size of the grains, the greater the porosity, and vice versa. The non-Darcy coefficient term, β, is found to be inversely proportional to the porosity and permeability. In a previous study, the β was investigated for compressible flow scenarios; however, this study calculated it for an incompressible flow. Finally, by analyzing the β values of both studies, we could deduce new novelty correlations for the β coefficient term, where the permeability, porosity, and tortuosity are included.

Pitting corrosion is a localized corrosion that often causes leak and failure of process components. The aim of this work is to present a new fitness-for-service (FFS) assessment methodology for process equipment to track and predict pitting corrosion. In this methodology, pit density is modeled using a non-homogenous Poisson process and induction time for pit initiation is simulated as the realization of a Weibull process. The non-homogenous Markov process is used to estimate maximum pit depth, considering that only the current state of the damage influences its future development. Subsequently, the distributions of the operating pressure and the estimated burst pressure of the defected component are integrated with Monte Carlo simulations and First Order Second Moment (FOSM) method to calculate the reliability index and probability of failure. This methodology provides a more realistic failure assessment and enables consideration of uncertainty associated with estimating pit characteristics. The practical application of the proposed model is demonstrated using a piping case study.

Pitting corrosion is a localized corrosion that often causes leak and failure of process components. The aim of this work is to present a new fitness-for-service (FFS) assessment methodology for process equipment to track and predict pitting corrosion. In this methodology, pit density is modeled using a non-homogenous Poisson process and induction time for pit initiation is simulated as the realization of a Weibull process. The non-homogenous Markov process is used to estimate maximum pit depth, considering that only the current state of the damage influences its future development. Subsequently, the distributions of the operating pressure and the estimated burst pressure of the defected component are integrated with Monte Carlo simulations and First Order Second Moment (FOSM) method to calculate the reliability index and probability of failure. This methodology provides a more realistic failure assessment and enables consideration of uncertainty associated with estimating pit characteristics. The practical application of the proposed model is demonstrated using a piping case study.

Abstract Deepwater drilling is one of the high-risk operations in the oil and gas sector due to large uncertainties and extreme operating conditions. In the last few decades Managed Pressure Drilling Operations (MPD) and Underbalanced Drilling (UBD) have become increasingly used as alternatives to conventional drilling operations such as Overbalanced Drilling (OVD) technology. These newer techniques provide several advantages however the blowout risk during these operations is still not fully understood. Blowout is regarded as one of the most catastrophic events in offshore drilling operations; therefore implementation and maintenance of safety measures is essential to maintain risk below the acceptance criteria. This study is aimed at applying the Bayesian Network (BN) to conduct a dynamic safety analysis of deepwater MPD and UBD operations. It investigates different risk factors associated with MPD and UBD technologies, which could lead to a blowout accident. Blowout accident scenarios are investigated and the BNs are developed for MPD and UBD technologies in order to predict the probability of blowout occurrence. The main objective of this paper is to understand MPD and UBD technologies, to identify hazardous events during MPD and UBD operations, to perform failure analysis (modelling) of blowout events and to evaluate plus compare risk. Importance factor analysis in drilling operations is performed to assess contribution of each root cause to the potential accident; the results show that UBD has a higher occurrence probability of kick and blowout compared to MPD technology. The Rotating Control Devices (RCD) failure in MPD technology and increase in flow-through annulus in UBD technology are the most critical situations for kick and blowout.

Abstract Deepwater drilling is one of the high-risk operations in the oil and gas sector due to large uncertainties and extreme operating conditions. In the last few decades Managed Pressure Drilling Operations (MPD) and Underbalanced Drilling (UBD) have become increasingly used as alternatives to conventional drilling operations such as Overbalanced Drilling (OVD) technology. These newer techniques provide several advantages however the blowout risk during these operations is still not fully understood. Blowout is regarded as one of the most catastrophic events in offshore drilling operations; therefore implementation and maintenance of safety measures is essential to maintain risk below the acceptance criteria. This study is aimed at applying the Bayesian Network (BN) to conduct a dynamic safety analysis of deepwater MPD and UBD operations. It investigates different risk factors associated with MPD and UBD technologies, which could lead to a blowout accident. Blowout accident scenarios are investigated and the BNs are developed for MPD and UBD technologies in order to predict the probability of blowout occurrence. The main objective of this paper is to understand MPD and UBD technologies, to identify hazardous events during MPD and UBD operations, to perform failure analysis (modelling) of blowout events and to evaluate plus compare risk. Importance factor analysis in drilling operations is performed to assess contribution of each root cause to the potential accident; the results show that UBD has a higher occurrence probability of kick and blowout compared to MPD technology. The Rotating Control Devices (RCD) failure in MPD technology and increase in flow-through annulus in UBD technology are the most critical situations for kick and blowout.

Corrosion under insulation (CUI) is a serious issue in harsh marine environments. Corrosion damage can have catastrophic effects on health and safety, asset integrity, the environment, and productivity if it is not detected and managed early. Limited information is available for CUI in marine environments. To overcome this issue, three types of corrosion tests are proposed: Determination of the effect of environmental factors on CUI using laboratory simulation, field testing, and accelerated marine atmosphere testing for CUI. This paper describes the methodology for developing statistically significant data to evaluate CUI in harsh marine field conditions, develop an accelerated laboratory test procedure to simulate CUI, develop a model of CUI rate, and develop risk-based remaining life assessment model for assets under CUI attack.