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A Mathematical Model of a Thermally Activated Roof (TAR) Cooling System Using a Simplified RC-Thermal Model with Time Dependent Supply Water Temperature
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This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time dependent with the variation of the ambient wet bulb temperature. Results from RC-thermal modeling were compared with experimental measurements for a second story room measuring 5.5 m x 4 m x 3 m at Amarah city/ Iraq (31.865 ˚N, 47.128 ˚E) for 21 July, 2013. The roof was constructed of 200 mm concrete slab, 150 mm turf and 50 mm insulation. Galvanized 13 mm steel pipe coils were buried in the roof slab with a pipe occupation ratio of 0.12. The walls were constructed of 240 mm common brick with 10mm cement plaster on the inside and outside surfaces and 20 mm Styrofoam insulation on the inside surface and covered with PVC panel. Thermistors were used to measure the indoor and outdoor temperatures, TAR system water inlet and outlet temperatures and temperature distribution inside the concrete slab. The effect of pipe spacing and water mass flow rate were evaluated. Agreement was good between the experimental and RC-thermal model. Concrete core temperature reaches the supply water temperature faster for lower pipe spacing. Heat extracted from the space increased with water mass flow rate to an optimum of 0.0088 kg/s.m².

 

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Publication Date
Thu Dec 16 2021
Journal Name
Translational Vision Science & Technology
A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps
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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Energy management and storage systems on electric vehicles: A comprehensive review
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Sat Aug 21 2021
Journal Name
Engineering, Technology & Applied Science Research
A Comparison between Static and Repeated Load Test to Predict Asphalt Concrete Rut Depth
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Rutting has a significant impact on the pavements' performance. Rutting depth is often used as a parameter to assess the quality of pavements. The Asphalt Institute (AI) design method prescribes a maximum allowable rutting depth of 13mm, whereas the AASHTO design method stipulates a critical serviceability index of 2.5 which is equivalent to an average rutting depth of 15mm. In this research, static and repeated compression tests were performed to evaluate the permanent strain based on (1) the relationship between mix properties (asphalt content and type), and (2) testing temperature. The results indicated that the accumulated plastic strain was higher during the repeated load test than that during the static load tests. Notably, temperatur

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Publication Date
Tue Dec 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of SO2 over Modified Activated Carbon in Fixed Bed Reactor: I, Effect of Metal Oxide Loadings and Acid Treatment
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The removal of SO2 from simulated gas stream (SO2 + air) in a fixed bed reactor using Modified Activated Carbon (MAC) catalysts was investigated. All the experiments were conducted at atmospheric pressure, initial SO2 concentration of 2500 ppm and bed temperature of 90oC. MAC was prepared by loading a series of nickel and copper oxides 1, 3, 5, 7, and 10 w

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Improving Thermal Performance in the University Classrooms
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Universities are among spaces where it's important to ensure thermal comfort in indoor spaces, improving the occupants' well-being and productivity. The problem of the research was to study appropriate glazing systems for the spaces of the University of Baghdad because glazing systems are one of the most important elements of the indoor environments, and it has a major impact on the thermal performance of buildings. Glass is one of the most seasoned materials that are most utilized in the design. Since it is a diaphanous material, it allows sunlight to enter the building, increasing the space's temperature, cooling loads, and energy consumption in summer. The research followed the experimental method by studying and

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
A noval SVR estimation of figarch modal and forecasting for white oil data in Iraq
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The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

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Scopus
Publication Date
Mon Jan 01 2018
Journal Name
Rehabend
Prediction of impact force-time history in sandy soils
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Publication Date
Sun May 11 2025
Journal Name
Iraqi Statisticians Journal
Nonparametric Estimation for Nonstationary Time Series Models
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Publication Date
Sun Mar 06 2016
Journal Name
Baghdad Science Journal
Isolation and Purification of a Cyclooxygenase-2 from the Blood of a Patient Suffering from Rheumatoid Arthritis and Studying the Effect of Natural Products of the Soapwort on the Activity of Purified Enzyme
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In this paper to isolate and study the properties of the cyclooxygenase-2 (EC: 1.14.99.1) enzyme in the blood of a patient suffering from rheumatoid arthritis and study the effect of natural products of the Soapwort on the activity of purified enzyme. The study involves taking 30 ml of blood from an adult woman 40 years old, who suffers from rheumatoid arthritis disease for 13 years. Serum is separated and subjected to a series of purification processes including: precipitation by ammonium sulfate, filtration by centrifugation radiator, dialysis in presence of ammonium bicarbonate, separation using the technology of ion exchange, lipholization and then estimating approximate molecular weight of the enzyme using gel filtration techni

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