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Estimated Outlet Temperatures in Shell-and-Tube Heat Exchanger Using Artificial Neural Network Approach Based on Practical Data

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

150 sets of data were generated in different days by the reference heat exchanger model to training the network. Regression between desired target and prediction ANN output for training , validation, testing and all samples show reasonably values are equal to one (R=1) . 50 sets of data were generated to test the network and compare between desired and predicated exit temperature (water temp. and air temp.) show a good agreement ( ).

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Publication Date
Sat Sep 02 2023
Journal Name
Al-khwarizmi Engineering Journal (alkej)
Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Key Exchange Management by using Neural Network Synchronization

The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev

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Publication Date
Mon Aug 01 2022
Journal Name
Journal Of Engineering
Mechanical Integrity of Printed Circuit Heat Exchanger

The printed circuit heat exchanger is a plate type heat exchanger with a high performance and compact size. Heat exchangers such as this need a unique form of bonding and other techniques to be used in their construction. In this study, the process of joining plates, diffusion bonding, was performed and studied. A special furnace was manufactured for bonding purposes. The bonding process of copper metal was carried out under specific conditions of a high temperature up to 700 oC, high pressure of 3.45 MPa, and in an inert environment (Argon gas) to make tensile samples. The tensile samples are cylindrical shapes containing groves representing the flow channels in the printed circuit heat exchanger and checking their tensile st

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Publication Date
Tue Dec 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Performance Evaluation of Three Phase Spray Direct Contact Heat Exchanger

 

The present investigation deals with experimental study of three-phase direct-contact heat exchanger, for water-Freon R11 system, where water is the continuous phase (liquid) and Freon R11 (liquid-gas) is the dispersed phase. The test section consisted of a cylindrical Perspex column with inner diameter 8cm and 1.2m long, in which, water was to be confined. Liquid Freon R11 drops were injected into the hot water filled column, through a special design of distributors at the bottom of the column. The liquid Freon R11 drops rose on their way up and evaporated into two-phase bubbles at atmospheric pressure. The study was devoted to express the effect of process variables such as c

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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Intrusion detection method for internet of things based on the spiking neural network and decision tree method

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Intrusion detection method for internet of things based on the spiking neural network and decision tree method

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Pose Invariant Palm Vein Identification System using Convolutional Neural Network

Palm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main

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Scopus (18)
Crossref (2)
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Publication Date
Tue Oct 08 2002
Journal Name
Iraqi Journal Of Laser
Design Considerations of Laser Source in a Ring Network Based on Fiber Distributed Data Interface (FDDI)

This work presents the use of laser diode in the fiber distributed data interface FDDI networks. FDDI uses optical fiber as a transmission media. This solves the problems resulted from the EMI, and noise. In addition it increases the security of transmission. A network with a ring topology consists of three computers was designed and implemented. The timed token protocol was used to achieve and control the process of communication over the ring. Nonreturn to zero inversion (NRZI) modulation was carried out as a part of the physical (PHY) sublayer. The optical system consists of a laser diode with wavelength of 820 nm and 2.5 mW maximum output power as a source, optical fiber as a channel, and positive intrinsic negative (PIN) photodiode

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Publication Date
Mon Dec 01 2008
Journal Name
Journal Of Economics And Administrative Sciences
Neural Networks as a Discriminant Purposes

Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.

In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.  

 

 

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Publication Date
Thu Feb 29 2024
Journal Name
International Journal Of Design & Nature And Ecodynamics
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