Model Matematika Penyebaran Penyakit Demam Berdarah

Di dalam paper ini dibahas model matematika deterministik untuk penyebaranpenyakit demam berdarah. Ambang batas epidemik dapat ditentukan sebagaifungsi dari pertumbuhan nyamuk Aedes aegypti. Pertumbuhan nyamuk ini jugamenentukan kestabilan dari state bebas demam berdarah dan state endemikdemam berdarah. Analisis selanjutnya memperlihatkan bahwa pengontrolanepidemik yang efektif adalah dengan cara mengontrol pertumbuhan nyamuktersebut secara periodik

Cost Minimization Model of Gas Transmission Line for Indonesian SIJ Pipeline Network

Optimization of Indonesian SIJ gas pipeline network is being discussed here. Optimum pipe diameters together with the corresponding pressure distribution are obtained from minimization of total cost function consisting of investment and operating costs and subjects to some physical (Panhandle A and Panhandle B equations) constraints. Iteration technique based on Generalized Steepest-Descent and fourth order Runge-Kutta method are used here. The resulting diameters from this continuous optimization are then rounded to the closest available discrete sizes. We have also calculated toll fee along each segment and safety factor of the network by determining the pipe wall thickness, using ANSI B31.8 standard. Sensitivity analysis of toll fee for variation of flow rates is shown here. The result will gives the diameter and compressor size and compressor location that feasible to use for the SIJ pipeline project. The Result also indicates that the east route cost relatively less expensive than the west cost

Optimization of Vertical Well Placement for Oil Field Development Based on Basic Reservoir Rock Properties Using a Genetic Algorithm

Comparing the quality of basic reservoir rock properties is a common practice to locate new infill or development wells for optimizing oil field development using reservoir simulation. The conventional technique employs a manual trial-and-error process to find new well locations, which proves to be time-consuming, especially for large fields. Concerning this practical matter, an alternative in the form of a robust technique is introduced in order to reduce time and effort in finding new well locations capable of producing the highest oil recovery. The objective of this research was to apply a genetic algorithm (GA) for determining well locations using reservoir simulation, in order to avoid the conventional manual trial-and-error method. This GA involved the basic rock properties, i.e. porosity, permeability, and oil saturation, of each grid block obtained from a reservoir simulation model, to which a newly generated fitness function was applied, formulated by translating common engineering practice in reservoir simulation into a mathematical equation and then into a computer program. The maximum fitness value indicates the best grid location for a new well. In order to validate the proposed GA method and evaluate the performance of the program, two fields with different production profile characteristics were used, fields X and Y. The proposed method proved to be a robust and accurate method to find the best new well locations for oil field development. The key to the success of the proposed GA method lies in the formulation of the objective functions