Planning and Design of Engineering Systems

Introduction - historical background to engineering, nature of engineering work, differences between engineering, science and mathematics, engineering as problem solving, relationship between engineering work and societal needs and values, the work of the engineer in relation to the work of other professionals; engineering methodology - steps in the methodology - problem formulation, feasibility study, preliminary design, detailed design, implementation; basic systems concepts - modelling of engineering systems, systems and subsystems - input, output and state concepts, optimization and suboptimization, black box systems, application of concepts to civil engineering projects; creative aspects of planning and design - the need for innovative and creative solutions to engineering problems, lateral thinking and creative problem solving, factors which influence creative thinking, techniques for stimulating ideas - attribute listing, systematic search, brain storming, the nominal group technique; economic evaluation - differences between public sector and private sector projects, time value of money, discounting formulae, economic criteria for comparing projects - net present value, internal rate of return, benefit-cost ratio, the effects of inflation on economic analysis, estimation of project benefits and costs, choice of discount rate and project life; social and environmental evaluation of engineering projects - the need to consider multiple objectives, complexity of natural systems, environmental impact assessment, environmental indices, the Leopold Matrix, the Battelle System and other methods, social effects - income redistribution, social disruption, safety; optimization - linear programming - the role of optimization, linear programming and engineering applications, duality; non-linear optimization and dynamic programmes - non-linear optimization methods including calculus, lagrange multipliers and separable programming, dynamic programming, applications to engineering planning and design; decision theory - decisions under risk and uncertainty, the use of the various decision criteria - minimax, regret and Laplace, decision trees and the expected value approach, utility functions and attitudes towards risk, Bayes theorem and applications in engineering decision making.