Case Study of an Aerosol Explosion and a Method to Determine Explosion Temperatures

A failure analysis case study is presented for a two-piece aerosol containing tetrafluoroethane, commonly referred to as Refrigerant 134a. A gentleman was preparing to recharge the air conditioning system of an automobile when the bottom exploded off the aerosol container, propelling the body of the aerosol container like a rocket, which hit the man in the eye and blinded him in that eye. The aerosol was never connected to the air conditioner, therefore backpressure from the air conditioner (AC) compressor was ruled out as a cause for the explosion. The objective of the study was to determine why the aerosol exploded. Several recently developed test methods were used, including two types of heat-to-burst tests and a puncture chamber to measure the pressure-versus-temperature behavior of aerosols. More common test methods were also used, such as water bath pressure tests, hydro pressure burst tests, pneumatic pressure burst tests, hardness measurements, weight measurements, metallography, scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and an accident scenario recreation. A semi-empirical correlation between the hardness and weights of the container bottoms was used to determine the explosion temperature and/or pressure. This semi-empirical correlation agrees in principle with an analysis of the explosion pressures using finite-element analysis (FEA). The root cause for the explosion was determined to be a lack of strength of the bottom of the two-piece aerosol coupled with heating the aerosol to temperatures significantly above room temperature.     

Prediction of Undrained Sinkhole Collapse

Sinkholes are surface depressions or shafts resulting from the collapse of a submerged cavity in soil. The cavities that lead to sinkholes form as a result of underlying geology in limestone areas, or as a result of human activity such as mining or leakage from a sewer. The formation of sinkholes is often sudden and can lead to extensive damage and loss of life, especially in urban areas. Much of the literature on the subject of sinkhole formation is empirical in nature, often being associated with specific locations. This paper presents the results of a study, using numerical modeling, of the undrained stability of the submerged cavities that lead to sinkhole formation. Finite-element limit analysis techniques (using programs developed at the University of Newcastle) are used to obtain upper and lower bound values of a suitable load parameter, which bracket the exact solution. The results are compared to analytical solutions, both from literature and derived independently.     

A Finite Element Computational Method for Gas Hydrate. Part I: Theory

A finite element scheme is presented to model the dissociation of gas hydrates in porous media by hot water injection. We show a complete derivation of the finite element formulation, including the associated mass and energy conservation equations capable of performing transient analysis of both conductive and convective heat transfer for gas and liquid flow in porous media. The scheme also includes the latent heat effect to accommodate the change of phase due to melting of hydrate. In the companion paper, Part II, this method is successfully applied to hydrate reservoirs.     

The Challenge of the Market

Identifying markets for new or improved products for minor crops threatened with extinction is one critical component of any strategy intended to enhance prospects for sustainable production and use. Typically, however, activities linked to the sustainability of these commodities avoid addressing questions associated with assessing their commercial potential. After a brief review of this avoidance syndrome, this article presents a sample of practical, low-cost procedures to help evaluate the market prospects and procedures for crops like quinoa, while citing references to other methodological materials covering similar topics.     

A neural network model for the wire bonding process

A crucial step in manufacturing microcircuits is the wire bonding process in which a very thin gold wire must be formed to connect two surfaces in the microcircuit. The quality of the wire bond can be measured by visual inspection and a pull test—both of which are high-reliability, high-cost approaches to statistical process control. Westinghouse wanted to develop a high-reliability, low-cost quality assurance system. In this paper, we report on a year-long study to construct a neural network model that is capable of predicting the quality of wire bonds. The results of our modeling efforts reveal that neural networks are useful tools for statistical process control problems.