Courses
Risk Assessment
This short course provides an overview of the methods used for risk assessment, management and reduction. This will be accomplished using descriptions of methods with examples and exercises. This short course is designed to aid the practicing engineer who has responsibilities for risk assessment, management and reduction in chemical plants and petroleum refineries. Three hours continuing professional development credit. Send a critique to pike@lsu.edu for certificate of completion.
On-Line Optimization
This short course provides an overview of the On-Line Optimization. It includes three nonlinear optimization problems, which are gross error detection and data reconciliation, parameter estimation, and economic optimization. This short course also provides steps to use the On-Line Optimization program. One hour continuing professional development credit. Send a critique to pike@lsu.edu for certificate of completion.
Process Safety
This short course provides an overview of several aspects of process safety. It contains PowerPoint presentations from the SACHE 2003 Workshop on Designing for Safe and Reliable Process Operations held at the ExxonMobil Chemical Plant in Baton Rouge. One hour continuing professional development credit for each PowerPoint presentation reviewed. Send a critique to pike@lsu.edu for certificate of completion.
Process Optimization
This short course provides an overview of industrial optimization including optimization of operations and design. Operations optimization goes from on- line optimization to multi-plant optimization. Sophisticated computer programs are required that incorporate elaborate mathematical programming algorithms and plant models with thousands of material and energy balance constraints that mesh with distributed control systems. Mathematical programming theory is the basis for these methods and has led to thousands of algorithms which required numerical experimentation to determine the ones that gave the best performance on industrial systems. Important algorithms are described for large, nonlinear and mixed-integer problems. On-line optimization presented unique challenges in gross error detection and data reconciliation. Optimization of multi-plant chemical production complexes such as those on the Houston ship channel and the lower Mississippi River corridor required solutions of multi-criteria, mixed-integer, nonlinear programming problems with sensitivity analysis using Monte Carlo simulation to give cumulative probability distributions at Pareto optimal point. Send a critique to pike@lsu.edu for certificate of completion.