DERIVING THE NONLINEAR RISK-BENEFIT ALGORITHM FOR RESERVOIRS1

ABSTRACT: The Nonlinear Risk-Benefit (NRB) Algorithm includes risk as one of the objectives in a multiple-objective optimization problem. The NRB Algorithm is derived by extending the Surrogate Worth Trade-Off method to quadratic programming. This category of problem is common in water resources planning and design, especially multipurpose reservoir systems. Consequently, an example is given using the algorithm for optimally operating a multipurpose reservoir.     

Factors affecting degradation of dimethyl sulfoxide (DMSO) by fluidized-bed Fenton process

In this study, the target compound is dimethyl sulfoxide (DMSO), which is used as a photoresist stripping solvent in the semiconductor and thin-film transistor liquid crystal display (TFT-LCD) manufacturing processes. The effects of the operating parameters (pH, Fe²⁺ and H₂O₂ concentrations) on the degradation of DMSO in the fluidized-bed Fenton process were examined. This study used the Box-Behnken design (BBD) to investigate the optimum conditions of DMSO degradation. The highest DMSO removal was 98 % for pH 3, when the H₂O₂ to Fe²⁺ molar ratio was 12. At pH 2 and 4, the highest DMSO removal was 82 %, when the H₂O₂ to Fe²⁺ molar ratio was 6.5. The correlation of DMSO removal showed that the effect of the parameters on DMSO removal followed the order Fe²⁺?>?H₂O₂?>?pH. From the BBD prediction, the optimum conditions were pH 3, 5 mM of Fe²⁺, and 60 mM of H₂O₂. The difference between the experimental value (98 %) and the predicted value (96 %) was not significant. The removal efficiencies of DMSO, chemical oxygen demand (COD), total organic carbon (TOC), and iron in the fluidized-bed Fenton process were higher than those in the traditional Fenton process.