There is an optimal load and corresponding velocity at which peak power output occurs. It is reasonable to expect that these conditions will change as a result of fatigue during 30 s of all-out cycling. This study evaluated optimal velocity after 30 s of maximal isokinetic cycle ergometer exercise and tested the hypothesis that progressive adjustment of velocity (optimized) during 30 s of all-out cycling would permit greater short-term work capacity (STWC). Non-fatigued optimal cadence [NF(OC), 109.6 (2.5) rpm] was determined for ten males on an SRM ergometer using regression analysis of the torque-angular velocity relation during a 7-s maximal acceleration. Fatigued optimal cadence [73.4 (2.4) rpm] was determined in the same way, immediately after a 30-s isokinetic test at NF(OC). A subsequent trial with cadence decreasing in steps from NF(OC) to a conservative estimate of fatigued optimal cadence [83.9 (2.8) rpm] was completed to see if more work could be done with a more optimal cadence during the test. STWC was not different ( P=0.50) between the constant [23,681 (764) J] and optimized [23,679 (708) J] conditions. Another more radical progressive change in cadence with four subjects yielded the same result (no increase in STWC). Extraneous factors apparently contribute more to variability in STWC than differences between constant and adjusted optimization of conditions.

A systematic approach is proposed to find optimal operational conditions for nitrogen and phosphorus (N, P) removal in a biological nutrient removal process. The approach is a dual optimization strategy using modeling, variable selection, design of experiments, and optimization with multiple response surface methodology. The study focused on determining interactive effects between independent variables for N and P removal, which were selected through a new sensitivity analysis considering the effluent quality index. After selecting key operational variables, a multiple response surface model based on a new desirability function was used for the dual optimization of both N and P removal. The proposed method was applied to a standard A 2 O process and obtained the optimized removal efficiencies of 78.0% and 80.0% for N and P, respectively. This study confirmed that the proposed dual optimization method was useful to systematically optimize N and P removal in a biological nutrient removal process and also can be applied to any other biological processes.

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