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Cost Optimization (cost + optimization)

Distribution by Scientific Domains

Engineering	100%

Selected Abstracts

Stochastic Cost Optimization of Multistrategy DNAPL Site Remediation

GROUND WATER MONITORING & REMEDIATION, Issue 3 2010
Jack Parker
This paper investigates numerical optimization of dense nonaqueous phase liquid (DNAPL) site remediation design considering effects of prediction and measurement uncertainty. Results are presented for a hypothetical problem involving remediation using thermal source reduction (TSR) and bioremediation with electron donor (ED) injection. Pump-and-treat is utilized as a backup measure if compliance criteria are not met. Remediation system design variables are optimized to minimize expected net present value (ENPV) cost. Adaptive criteria are assumed for real-time control of TSR and ED duration. Source zone dissolved concentration data enabled more reliable and lower cost operation of TSR than soil concentration data, but using both soil and dissolved data improved results sufficiently to more than offset the additional cost. Decisions to terminate remediation and monitoring or to initiate pump-and-treat are complicated by measurement noise. Simultaneous optimization of monitoring frequency, averaging period, and lookback periods to confirm decisions, in addition to remediation design variables, reduced ENPV cost. Results indicate that remediation design under conditions of uncertainty is affected by subtle interactions and tradeoffs between design variables, compliance rules, site characteristics, and uncertainty in model predictions and monitoring data. Optimized designs yielded cost savings of up to approximately 50% compared with a nonoptimized design based on common engineering practices. Significant improvements in accuracy and reductions in cost were achieved by recalibrating the model to data collected during remediation and re-optimizing design variables. Repeating this process periodically is advisable to minimize total costs and maximize reliability. [source]

Cost optimization of composite floors using neural dynamics model

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING, Issue 11 2001
Hojjat Adeli
Abstract The design of composite beams is complicated and highly iterative. Depending on the design parameters a beam can be fully composite or partially composite. In the case of design on the basis of the American Institute of Steel Construction (AISC) Load and Resistance Factor Design (LRFD) one has to consider the plastic deformations. As pointed out by Lorenz, the real advantage of the LRFD code can be realized in the minimum cost design. In this article, we present a general formulation for the cost optimization of composite beams based on the AISC LRFD specifications by including the costs of (a) concrete, (b) steel beam, and (c) shear studs. The problem is formulated as a mixed integer-discrete non-linear programming problem and solved by the recently patented neural dynamics model of Adeli and Park (U.S. patent 5,815,394 issued on September 29, 1998). It is shown that use of the cost optimization algorithm presented in this article results in substantial cost savings. Copyright © 2001 John Wiley & Sons, Ltd. [source]

Analysis and cost optimization of the triple-pressure steam-reheat gas-reheat gas-recuperated combined power cycle

INTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 2 2008
A. M. Bassily
Abstract Increasing the inlet temperature of gas turbine (TIT) and optimization are important methods for improving the efficiency and power of the combined cycle. In this paper, the triple-pressure steam-reheat gas-reheat recuperated combined cycle (the Regular Gas-Reheat cycle) was optimized relative to its operating parameters, including the temperature differences for pinch points (,TPP). The optimized triple-pressure steam-reheat gas-reheat recuperated combined cycle (the Optimized cycle) had much lower ,TPP than that for the Regular Gas-Reheat cycle so that the area of heat transfer of the heat recovery steam generator (HRSG) of the Optimized cycle had to be increased to keep the same rate of heat transfer. For the same mass flow rate of air, the Optimized cycle generates more power and consumes more fuel than the Regular Gas-Reheat cycle. An objective function of the net additional revenue (the saving of the optimization process) was defined in terms of the revenue of the additional generated power and the costs of replacing the HRSG and the additional fuel. Constraints were set on many operating parameters such as the minimum temperature difference for pinch points (,TPPm), the steam turbines inlet temperatures and pressures, and the dryness fraction at steam turbine outlet. The net additional revenue was optimized at 11 different maximum values of TIT using two different methods: the direct search and variable metric. The performance of the Optimized cycle was compared with that for the Regular Gas-Reheat cycle and the triple-pressure steam-reheat gas-reheat recuperated reduced-irreversibility combined cycle (the Reduced-Irreversibility cycle). The results indicate that the Optimized cycle is 0.17,0.35 percentage point higher in efficiency and 5.3,6.8% higher in specific work than the Reduced-Irreversibility cycle, which is 2.84,2.91 percentage points higher in efficiency and 4.7% higher in specific work than the Regular Gas-Reheat cycle when all cycles are compared at the same values of TIT and ,TPPm. Optimizing the net additional revenue could result in an annual saving of 33.7 million US dollars for a 481 MW power plant. The Optimized cycle was 3.62 percentage points higher in efficiency than the most efficient commercially available H-system combined cycle when compared at the same value of TIT. Copyright © 2007 John Wiley & Sons, Ltd. [source]