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Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial voids ratio. Multi-layer perceptron training by the backpropagation algorithm was used in creating the network. It was found that both models can predict shear strength parameters for gypseous soils with good reliability. Sensitivity analysis of the first model indicated that dry unit weight and plasticity index have the most significant effect on the predicted cohesion. While in the second model, the results indicated that the gypsum content and plasticity index have the most significant effect on the predicted angle of internal friction.

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
The Effects of Different Water Types on the Dissolution, Physical Appearance, and Compressive Strength of Gypsum Rock
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Dissolution of gypsum rock in water is significant, which may result in hydrocarbon reservoir formation and evaporate deposits. However, the complexity of the gypsum dissolution process is still of interest because of its uncleanness that requires more critical analysis. The objectives of this experimental study are emphasis on the dissolution characteristics of gypsum rock under room temperature and by various types of water; namely: deionized, tap, fresh, acidic, well, and normal rainwatre. In addition, the influences of dissolution on gypsum rock's mechanical and physical characteristics. Gypsum rock was obtained from Agjalar area, in the southwest of Sulaymaniyah city, Northern Iraq. Experimental results show that we

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Publication Date
Mon Jan 01 2018
Journal Name
Surface And Coatings Technology
Effect of new zirconia surface coatings on the surface properties and bonding strength of veneering zirconia substrate
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Publication Date
Sun Oct 01 2017
Journal Name
International Journal Of Science And Research (ijsr)
Effect of Elevated Temperature on the Compressive Strength of Reactive Powder Concrete (RPC) Containing Polyvinyl Chloride (PVC)
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Fire is the most sever environmental condition affecting on concrete structures, thus investigating for fire safet, IJSR, Call for Papers, Online Journal

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Assessing the Influence of Moisture Damage under Repeated Load on Multilayer Interface Bond Strength of Asphalt Concrete
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The performance and durability of the asphalt pavement structure mainly depend on the strength of the bonding between the layers. Such a bond is achieved through the use of an adhesive material (tack coat) to bond the asphalt layers. The main objective of this study is to evaluate the effect of moisture in conjunction with repeated traffic loads on the strength of the bonding between asphalt layers using two types of tack coats with different application rates. Using the nominal maximum size of aggregate (NMAS), the layers were graded (25/19) and (19/9.5) mm. The slabs of multilayer asphalt concrete were prepared using a roller compactor using two types of tack coats to bond between layers, namely rapid curing cut back a

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Publication Date
Fri Jun 15 2018
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of phosphate ester addition on transverse strength and hardness of heat cured acrylic denture base material
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Background: acrylic resin denture base consider a common denture base material for its acceptable cost, aesthetic and easy processing but still has disadvantages including easy of fracture and low impact strength. Material and method: The experimental group was prepared by addition of 15% phosphoric acid 2-hydroxyethyl methacrylate ester (PA2HEME) with polymethyl methacrylate monomer; the experimental groups was compared with the control one. The specimens were prepared according to ADA specification No. 12 with dimension 65 mm x 10 mm x2.5 mm (length x width x thickness respectively). The prepared specimens were tested by three-point flexural strength utilizing Instron Universal Testing Machine (WDW, Layree Technology Co.), Shore D hard

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Publication Date
Wed Oct 11 2017
Journal Name
International Journal Of Science And Research
Effect of Elevated Temperature on the Compressive Strength of Reactive Powder Concrete (RPC) Containing Polyvinyl Chloride (PVC)
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Fire is the most sever environmental condition affecting on concrete structures, thus investigating for fire safety in structural concrete is important for building construction. The slow heat transfer and strength loss enables concrete to be effective for fire resistance. Concrete structures withstand when exposed to fire according to: their thermal properties, rate of heating, characteristic properties of concrete mixes and their composition and on the duration of fire, and concerned as thermal property with other factors such as loss of mass which affected by aggregate type, moisture content, and composition of concrete mix. The present research goal is to study the effect of rising temperature on the compressive strength of the rea

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Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
A new Cumulative Damage Model for Fatigue Life Prediction under Shot Peening Treatment
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 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

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Publication Date
Mon Apr 09 2018
Journal Name
Al-khwarizmi Engineering Journal
Neural Network Modeling of Cutting Force and Chip Thickness Ratio for Turning Aluminum Alloy 7075-T6
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The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T

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Publication Date
Fri Sep 01 2017
Journal Name
2017 9th Computer Science And Electronic Engineering (ceec)
Modelling the power cost and trade-off of live migration the virtual machines in cloud-radio access networks
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Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
The Influence of NMI against Modularity in Community Detection Problem: A Case Study for Unsigned and Signed Networks
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Community detection is useful for better understanding the structure of complex networks. It aids in the extraction of the required information from such networks and has a vital role in different fields that range from healthcare to regional geography, economics, human interactions, and mobility. The method for detecting the structure of communities involves the partitioning of complex networks into groups of nodes, with extensive connections within community and sparse connections with other communities. In the literature, two main measures, namely the Modularity (Q) and Normalized Mutual Information (NMI) have been used for evaluating the validation and quality of the detected community structures. Although many optimization algo

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