Neill C. Renton

Reliability of complex chemical engineering processes

Abstract This paper presents a stochastic performance modelling approach that can be used to optimise design and operational reliability of complex chemical engineering processes. The framework can be applied to processes comprising multiple units, including the cases where closed form process performance functions are unavailable or difficult to derive from first principles, which is often the case in practice. An interface that facilitates automated two-way communication between Matlab® and process simulation environment is used to generate large process responses. The resulting constrained optimisation problem is solved using both Monte Carlo Simulation (MCS) and First Order Reliability Method (FORM); providing a wide range of stochastic process performance measures. Adding such capabilities to traditional deterministic process simulators provides a more informed basis for selecting optimum design factors; giving a simple way of enhancing overall process reliability and cost-efficiency. Two case study systems are considered to highlight the applicability and benefits of the approach.

A Hybrid Method for Stochastic Performance Modeling and Optimization of Chemical Engineering Processes

As chemical engineers seek to improve plant safety, reliability, and financial performance, a wide range of uncertaintyladen decisions need to be made. It is widely agreed that probabilistic approaches provide a rational framework to quantify such uncertainties and can result in improved decision making and performance when compared with deterministic approaches. This article proposes a novel method for design and performance analysis of chemical engineering processes under uncertainty. The framework combines process simulation tools, response surface techniques, and numerical integration schemes applied in structural reliability problems to determine the probability of a process achieving a performance function of interest. The approach can be used to model processes in the presence or absence of performance function(s), with or without parameter interactions, at both design and operational phases. With this, process behavior can be quantified in terms of stochastic performance measures such as reliability indices and the associated most probable process design/operating conditions, providing a simple way to analyze a wide range of decisions. To validate the applicability of the proposed framework, three case study systems are considered: a plug flow reactor, a heat exchanger, and finally a pump system. In each case, performance criteria based on the original physical model and the surrogate model are set up. Reliability analysis is then carried out based on these two models and the results are assessed. The results show that the proposed framework can be successfully applied in chemical engineering analysis with additional benefits over the traditional deterministic methods.

Influence of microstructure changes on corrosion resistance of super duplex stainless steel

Effect of microstructure on pitting corrosion of super duplex was investigated in 3.5% NaCl solution at 90°C. The microstructures were controlled by applying two different cooling rates of water quench and air from the heat treatment temperatures of 1,000°C and 1,300°C. The amount of ferrite and austenite and other precipitates were measured using optical and image analyser. The results revealed that the ferrite percentage increased as the heating temperature increased to 1300°C. Metallographic results showed the presence of intermetallic phases. Back scattering analysis revealed presence of sigma (σ) and chi (χ) phase. The volume fraction of ferrite to austenite as well as the precipitation of harmful intermetallic phase during cooling process affected the corrosion resistance. Reformation of austenite during slow cooling from 1,300°C enhanced corrosion resistance while intermetallic precipitates promoted pitting damage and decreased pitting potential to more active values.

Hydrogen Embrittlement Enhanced by Plastic Deformation of Super Duplex Stainless Steel

The effect of variations in plastic deformation percentage on hydrogen embrittlement of super duplex stainless steel alloy was investigated. Samples were strained to 4%, 8%, 12%, and 16% of plastic strain prior to hydrogen charging. Sufficient hydrogen for embrittlement was achieved by cathodic charging in 0.1 M H2SO4 for 48 h at a current density of 30 mA/cm2. Hydrogen embrittlement susceptibility was highly dependent on the amount of plastic deformation. Experimental results showed that prestraining of super duplex stainless steel and hydrogen charging affected the elongation and the values of the strain required to failure. The total elongation for the samples with no prestraining deformation and tested in air was 29%. This elongation reduced to 25% when the same sample condition (no prestraining) charged with hydrogen. Further reduction in elongation and strain to failure was observed when the prestraining samples were charged with hydrogen prior to tensile testing. Load—displacement results showed that as the percentage of the plastic deformation increased, the elongation and strain to failure decreased. Comparison between the prestrained samples, charged and uncharged with hydrogen, showed a noticeable difference in strain at failure in the hydrogen charged specimens.