Sensitivity Constrained Nonlinear Programming: A General Approach for Planning and Design Under Parameter Uncertainty and an Application to Treatment Plant Design

One important problem with using mathematical models is that parameter values, and thus the model results, are often uncertain. A general approach, Sensitivity Constrained Nonlinear Programming (SCNLP), was developed for extending nonlinear optimization models, to include functions that depend on the system sensitivity to changes in parameter values. Such sensitivity-based functions include first-order measures of variance, reliability, and robustness. Thus SCNLP can be used to generate solutions or designs that are good with respect to modeled objectives, and that also reflect concerns about uncertainty in parameter values. A solution procedure and an implementation based on an existing nonlinear programming code are presented. SCNLP was applied to a complex activated sludge wastewater treatment plant design problem. The alternative designs generated represent the tradeoff between cost and system robustness, where robustness is related inversely to the sensitivity of effluent quality to changes in 55 parameter values. The results show a significant tradeoff between cost and robustness and significant design trends associated with improvements in robustness. These design trends are generally more consistent with recommended design practice than is the minimum cost design. SCNLP should be applicable to many problems where parameter value uncertainty is important, e.g., the design of contaminated groundwater remediation schemes.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Environmental Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Uber, James Gregory

Contributors dc:contributor

• Brill, E. Downey, Jr.,

• Engineering, Civil
• Engineering, Industrial
• Engineering, Sanitary and Municipal

Identifier

(UMI)AAI8823270

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/69978