Study of Gas Drying by Adsorption on Composite Materials Using Neural Networks

نویسندگان

  • RODICA DIACONESCU
  • MARIUS SEBASTIAN SECULA
  • STELIAN PETRESCU
چکیده

An artificial neural network study of gas drying by adsorption in fixed bed of composite materials is presented in this paper. The experimental investigations were carried out at two values of relative humidity and three values of air flow rate respectively. The experimental data were employed in the design of the feed forward neural networks for modeling the evolution in time of some adsorption parameters, such as adsorption rate, water concentration in the bed, water vapor concentration in air at the exit from the fixed bed, drying degree and rate respectively. Based on these adsorption parameters, two composite adsorbent materials having porous matrices were compared

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Ann Modeling And Simulation Of Gas Drying By Adsorption On Composite Materials

An artificial neural network (ANN) modeling of gas drying by adsorption in fixed bed of composite materials is presented in this paper. The experimental investigations were carried out at two values of relative humidity and three values of air flow rate respectively. The experimental data were employed in the design of the feed forward neural networks for modeling the evolution in time of some ...

متن کامل

Removal of Bisphenol-A by NaP Zeolite/Hydroxyapatite Composite: Adsorption Experiments and Modeling by Artificial Neural Networks

In this paper, we have reported removal of Bisphenol A (BPA) by Hydroxyapatite/NaP zeolite (HAp: Zeolite ) nanocomposite which synthesized in previous our work and characterized by using different methods such as X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscope, Energy Dispersive X-ray analysis, surface area, and thermogravimetric analysis. To investigate...

متن کامل

Modeling and Optimization of Roll-bonding Parameters for Bond Strength of Ti/Cu/Ti Clad Composites by Artificial Neural Networks and Genetic Algorithm

This paper deals with modeling and optimization of the roll-bonding process of Ti/Cu/Ti composite for determination of the best roll-bonding parameters leading to the maximum Ti/Cu bond strength by combination of neural network and genetic algorithm. An artificial neural network (ANN) program has been proposed to determine the effect of practical parameters, i.e., rolling temperature, reduction...

متن کامل

A Robust Method to Predict Equilibrium and Kinetics of Sulfur and Nitrogen Compounds Adsorption from Liquid Fuel on Mesoporous Material

This study presents a robust and rigorous method based on intelligent models, namely radial basis function networks optimized by particle swarm optimization (PSO-RBF), multilayer perceptron neural networks (MLP-NNs), and adaptive neuro-fuzzy inference system optimized by particle swarm optimization methods (PSO-ANFIS), for predicting the equilibrium and kinetics of the adsorption of sulfur and ...

متن کامل

Photocatalytic Removal of NOx Gas from Air by TiO2/Polymer Composite Nanofibers

Nitrogen oxides (NOx) released in atmosphere by fuels combustion lead to photochemical smog and acidic rains and have negative effects on human`s nervous system. In this research nanocomposite membranes of Poly Vinylidene Fluoride (PVDF)/ Poly Dimethylsiloxane (PDMS) and Titanium Dioxide nanoparticles (TiO2) with different weight percentage of TiO2 (0.5 and 1) for adsorption of NOx were prepare...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009