Numerical simulations of a three-dimensional model of impingement and film cooling on a flat plate are presented and validated with the available experimental data. Four different turbulence models were utilized for simulation, in which SST  had the highest precision, resulting in less than 4% maximum error in temperature estimation. A simplified geometry with periodic boundary conditions is de...

the spatial distribution of petrophysical properties within the reservoirs is one of the most importantfactors in reservoir characterization. flow units are the continuous body over a specific reservoirvolume within which the geological and petrophysical properties are the same. accordingly, anaccurate prediction of flow units is a major task to achieve a reliable petrophysical description of a...

abstract the present study was carried out for developing and evaluating of the optimization model of cropping pattern in irrigation networks using analytical hierarchy process (ahp). the model was programmed into two sub-models. the objective of the first sub-model was ranking of crop appropriately, and the objective of the second sub-model was ranking of cropping area of each crop. ten criter...

background: one of the key issues in determining the quality of water in rivers is to create a water quality control network with a suitable performance. the measured qualitative variables at stations should be representative of all the changes in water quality in water systems. since the increase in water quality monitoring stations increases annual monitoring costs, recognition of the station...

‎linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints‎. ‎in this paper‎, ‎to solve this problem‎, ‎we combine a discretization method and a neural network method‎. ‎by a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problem‎. ‎then‎, ‎we use...

The main objective of this paper is to introduce a new intelligent optimization technique that uses a predictioncorrectionstrategy supported by a recurrent neural network for finding a near optimal solution of a givenobjective function. Recently there have been attempts for using artificial neural networks (ANNs) in optimizationproblems and some types of ANNs such as Hopfield network and Boltzm...

Deep learning is one of the subsets of machine learning that is widely used in Artificial Intelligence (AI) field such as natural language processing and machine vision. The learning algorithms require optimization in multiple aspects. Generally, model-based inferences need to solve an optimized problem. In deep learning, the most important problem that can be solved by optimization is neural n...

the main objective of this study is the modelling and optimization of an industrial hydrocracker unit (hu) by means of adaptive neuro fuzzy inference system (anfis) model. in this case, some data were collected from an industrial hydrocracker plant. inputs of an anfis include flow rate of fresh feed and recycle hydrogen, temperature of reactors, mole percentage of h2 and h2s, feed flow rate and...