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Numerical Optimization (numerical + optimization)
Selected AbstractsStochastic Cost Optimization of Multistrategy DNAPL Site RemediationGROUND WATER MONITORING & REMEDIATION, Issue 3 2010Jack 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 numerical optimization of the triple-pressure steam-reheat gas-reheat gas-recuperated combined power cycle that uses steam for cooling the first GTINTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 15 2008A. M. Bassily Abstract Optimization is an important method for improving the efficiency and power of the combined cycle. In this paper, the triple-pressure steam-reheat gas-reheat gas-recuperated combined cycle that uses steam for cooling the first gas turbine (the regular steam-cooled cycle) was optimized relative to its operating parameters. The optimized cycle generates more power and consumes more fuel than the regular steam-cooled 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 heat recovery steam generator (HRSG) and the costs of the additional operation and maintenance, installation, and fuel. Constraints were set on many operating parameters such as air compression ratio, the minimum temperature difference for pinch points (,Tppm), the dryness fraction at steam turbine outlet, and stack temperature. The net additional revenue and cycle efficiency were optimized at 11 different maximum values of turbine inlet temperature (TIT) using two different methods: the direct search and the variable metric. The optima were found at the boundaries of many constraints such as the maximum values of air compression ratio, turbine outlet temperature (TOT), and the minimum value of stack temperature. The performance of the optimized cycles was compared with that for the regular steam-cooled cycle. The results indicate that the optimized cycles are 1.7,1.8 percentage points higher in efficiency and 4.4,7.1% higher in total specific work than the regular steam-cooled 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 21 million U.S. dollars for a 439,MW power plant. Increasing the maximum TOT to 1000°C and replacing the stainless steel recuperator heat exchanger of the optimized cycle with a super-alloys-recuperated heat exchanger could result in an additional efficiency increase of 1.1 percentage point and a specific work increase of 4.8,7.1%. The optimized cycles were about 3.3 percentage points higher in efficiency than the most efficient commercially available H-system combined cycle when compared at the same value of TIT. Copyright © 2008 John Wiley & Sons, Ltd. [source] Seasonal patterns of growth, expenditure and assimilation in juvenile Atlantic salmonJOURNAL OF ANIMAL ECOLOGY, Issue 6 2002Wayne Jones Summary 1We report a modelling study of a data-set describing the growth of individual Atlantic salmon (Salmo salar L.) parr in the Girnock Burn (Scotland). A development of the compensatory growth model due to Broekhusien et al. (1994) was fitted to these data by numerical optimization. 2The model uses carbon mass as a surrogate for an energy currency. This mass is divided into structure and reserve components, so as to describe decoupled changes in length and wet-weight. 3Using the same parameters for all fish, our model explained 83% of the variability in length and weight at age. Adding a single additional parameter for each individual enabled the model to explain over 96% of length and weight variability. 4Weak negative correlation between size at first capture and within-study growth argues against genetic causality of observed growth variability. 5The energetic basis of our model enables us to infer time-series of net assimilation and basal maintenance rates for the observed individuals. Maximal growth occurs early in the season when high assimilation is accompanied by low temperatures and maintenance rates. In late season, continuing high assimilation is balanced by high maintenance rates consequent on summer temperatures. [source] Analysis of the fluid,structure interaction in the optimization-based design of polymer sheeting diesJOURNAL OF APPLIED POLYMER SCIENCE, Issue 6 2007Qi Wang Abstract A polymer-sheeting-die-design methodology is presented that integrates a simulation of the polymer melt flow and die-cavity deformation with numerical optimization to compute a die-cavity geometry capable of giving a nearly uniform exit flow rate. Both the polymer melt flow and sheeting-die deformation are analyzed with a general-purpose finite-element program. The approach includes a user-defined element that is used to evaluate the purely viscous non-Newtonian flow in a flat die. The flow analysis, which is simplified with the Hele,Shaw approximation, is coupled to a three-dimensional finite-element simulation for die deformation. In addition, shape optimization of a polymer sheeting die is performed by the incorporation of the coupled analyses in our constrained optimization algorithm. A sample problem is discussed to illustrate the die-design methodology. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 3994,4004, 2007 [source] Optimal control of innate immune responseOPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 2 2002Robert F. Stengel Abstract Treatment of a pathogenic disease process is interpreted as the optimal control of a dynamic system. Evolution of the disease is characterized by a non-linear, fourth-order ordinary differential equation that describes concentrations of pathogens, plasma cells, and antibodies, as well as a numerical indication of patient health. Without control, the dynamic model evidences sub-clinical or clinical decay, chronic stabilization, or unrestrained lethal growth of the pathogen, depending on the initial conditions for the infection. The dynamic equations are controlled by therapeutic agents that affect the rate of change of system variables. Control histories that minimize a quadratic cost function are generated by numerical optimization over a fixed time interval, given otherwise lethal initial conditions. Tradeoffs between cost function weighting of pathogens, organ health, and use of therapeutics are evaluated. Optimal control solutions that defeat the pathogen and preserve organ health are demonstrated for four different approaches to therapy. It is shown that control theory can point the way toward new protocols for treatment and remediation of human diseases. Copyright © 2002 John Wiley & Sons, Ltd. [source] | ||||||||||