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alkej-199
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 conservative prediction of fatigue life in comparison with CD and CDM methods. The prediction of the present model gave slightly below the experimental data while the CDM gave overestimate prediction and CD showed strongly underestimates the life of specimens.

 

Keywords: Cumulative fatigue damage, Shot peening, Non-linear model.

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Publication Date
Fri Mar 01 2013
Journal Name
مجلة ميسان لعلوم التربية البدنية
Consistent determinants of post-stroke health-related quality of life across diverse cultures: Berlin-Ibadan study
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Publication Date
Sun Sep 06 2015
Journal Name
Baghdad Science Journal
The age-specific fecundity life tables of Planococcus citri Risso and important predators attack in Baghdad
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Reproduction potential and age –specific fecundity of the Mealybug Planococcus citri Risso were studied in the laboratories of Biological control research unit,college of Agriculture –Baghdad university at 25± 2Cº and 60-70% R.H.with 16 light:8 dark photo period.The results showed that the survival ratio began to decline at the 38th day, the average female age was 20 days ,while the average age was 8 days at the first reproduction . Net reproduction rate ( Ro ) was 58.59 female female generation which prove that the population of the mealybug was of the unstable kind , intrinsic rate of increase (rm) was 0.118 femalefemale and the average length period of generation ( T ) was 34.30 days . Many local predators attack the mealybug

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Publication Date
Sun Apr 03 2011
Journal Name
Journal Of Educational And Psychological Researches
Satisfy of life and it's relationship; with the bige factors of character in the university student
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This research aim to recognize
satisfy of life in the university's student and balance in satisfy of life
according to two type aveirable sex specific and find type and
relationship's director between satisfy of life and character big factors.
and known hom much that Factors in satisfy of life, the research sample
consist of (401) student male and female and from both specified in
Baghdad's University, researcher bult scale of Costa &McCrae Fore the
fire big Factors to Personality, research result That the university's
student low level of satisfy of life and there are no different statically if
they are scientific or human in their study. And there is positive and there
is positive and indicate relation

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Publication Date
Sat Mar 26 2022
Journal Name
Nasaq Journal
An analytical study of the science textbook of the intermediate 1st grade according to life skills
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The aim of this study is to develop the science textbook for the 1st intermediate grade by analyzing it according to life skills. Its core areas were mental skills, environmental skills, and health skills. The analysis tool was used after verifying its validity and stability in analyzing the science textbook for the 1st intermediate grade, and the results of the study resulted in the inclusion of mental skills on a high percentage of repetitions, while we find that this percentage is low in the inclusion of environmental and health skills. The study recommended the importance of achieving balance and justice in including skills in the science textbook for the 1st intermediate grade, by emphasizing the environmental and health skills by incr

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Publication Date
Tue Jan 01 2019
Journal Name
Iraqi Journal Of Agricultural Sciences
Extend the shelf life and improving sensory properties of white soft cheese by adding celery... leaves
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This study was aime to investigate the effect of addition different concentration of celery leaves to white soft cheese ,Treated cheese between 2018-2019, ,The finely Celery (Apium graveolens) leaves were adding to crude white cheese after texturizing in three leveles included (A,B,C) in addition of control antimicrobial activity of celery treated cheese against total account bacteria and coliform bacteria was estimated during (0, 5, 10, 15, 20) days. The results were shown that the higher concentration of celery in treated cheese, had a lower concentration of protein, lipid and ash content ( 16.81,15.13 and 4.30% respectively, but it had a higher moisture content 59.50%.also the total bacteria counts were decreasing significantly (0.05 P)w

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Scopus (13)
Scopus
Publication Date
Mon Jan 01 2018
Journal Name
Communications In Computer And Information Science
Automatically Recognizing Emotions in Text Using Prediction by Partial Matching (PPM) Text Compression Method
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

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Publication Date
Wed Nov 01 2023
Journal Name
Journal Of King Saud University - Engineering Sciences
Particle swarm optimization technique-based prediction of peak ground acceleration of Iraq’s tectonic regions
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Peak ground acceleration (PGA) is one of the critical factors that affect the determination of earthquake intensity. PGA is generally utilized to describe ground motion in a particular zone and is able to efficiently predict the parameters of site ground motion for the design of engineering structures. Therefore, novel models are developed to forecast PGA in the case of the Iraqi database, which utilizes the particle swarm optimization (PSO) approach. A data set of 187 historical ground-motion recordings in Iraq’s tectonic regions was used to build the explicit proposed models. The proposed PGA models relate to different seismic parameters, including the magnitude of the earthquake (Mw), average shear-wave velocity (VS30), focal depth (FD

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Publication Date
Tue Dec 19 2017
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm
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In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad.  One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process.

The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and a

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Publication Date
Fri Dec 23 2011
Journal Name
International Journal Of The Physical Sciences
Fast prediction of power transfer stability index based on radial basis function neural network
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Scopus (16)
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Publication Date
Wed May 03 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Enhancing smart home energy efficiency through accurate load prediction using deep convolutional neural networks
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The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

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