Effective cooling is required in power generation, processing, and distribution to avoid failure that could occur during operations. As heat loads continue to increase, manufacturers of wind turbines are turning to improve the cooling system to remove high intensity heat loads from many active parts particularly in the generator part. Wind generators need an effective cooling system due to the large amount of heat that is released during power production. Many large wind turbines (more than 5MW rated power) particularly offshore wind turbines where the water is available, heat exchangers with water-air cooling system is used, in which the water is utilized to cool the hot air. This type of heat exchangers are desired, since they are more efficient and reliable than the air-air heat exchangers, which are used in small wind turbines. Because of the growing number of failures that occurred in wind turbine generators due to high generator’s temperatures owing to power losses of generator, applying condition monitoring system on wind generators depending on heat transfer analysis through the heat exchangers of wind generators plays an effective role. This helps avoid failures and maintain wind turbines to be protected. In this paper new methodology has been applied by considering the heat transfer and fluid mechanics analysis through a heat exchanger of wind generator, which uses water to air cooling system. Case study based on data collected from actual measurements demonstrates the adequacy of the proposed model. 

The building projects are differentiated, each building project is unique in terms of size, the level of complexity, procurement systems required. The characteristics of building projects could have major influence on overall project performance. Building projects that incorporate green designs, which are complicated to understand or manage adequately and are more complex compared with typical building projects. Therefore, To achieve high-green design performance, understand crucial characteristics of building projects that may have affect performance level of green design is required. The propose of this study to identify key project characteristics of building projects influencing green design performance. To achieve mentioned aim a questionnaire survey was conducted to collect dada required. A sample of 274 respondents has been covered under the study, including architects and engineers practicing design and consultancy building sectors. Prior to analysis of data WINSTEPS software were used to determine validity and reliability of date. Descriptive analysis data includes quantitative and qualitative. The results revealed that the Project Size can influence the Green Design Performance. The type of Building and size of the project are the key factors influencing Green Design Performance. The Availability of Design Information was moderate. The Reused and Recycled Materials were hard to find, while Regional Materials were available in the market.

Progressive building collapse occurs when failure of a structural component leads to the failure and collapse of surrounding members, possibly promoting additional collapse. Global system collapse will occur if the damaged system is unable to reach a new static equilibrium configuration. The objective of this research is to identify and investigate the importance of issues related to the unexpected collapse resulting from the loss of key elements of the structure (a column or columns, for example). In this research study there are examined on the entire frame including details of the column loss scenario and also the influence of the ductility and strength of beam-to-column joints adjacent to the location of such as incident. The study also includes catenary action in beams resulting from collapse and its impact on the adjacent joints and reports on the comparison of negative and positive moments in joints. In addition, it records the important notes associated with the state of collapse and parts of this research include the conformity of numerical and analytical results, the ratio of credibility and conformity of results and the test. This thesis reports in detail on the experimental and numerical investigations of the behaviour of steel and composite joints, which aim to develop common solutions with regard to the joint semi-rigid and partial strength properties that might allow for significant rotations and the redistribution of internal forces in structural system when there was a damage to its key element such as a column. Investigations of steel and composite joints with regard to their ductile behaviour are presented. Thereby special attention is paid to shaping of …

The development and implementation of condition monitoring system become very important for wind industry with the increasing number of failures in wind turbine generators due to over temperature especially in offshore wind turbines where higher maintenance costs than onshore wind farms have to be paid due to their farthest locations. Monitoring the wind generators temperatures is significant and plays a remarkable role in an effective condition monitoring system. Moreover, they can be easily measured and recorded automatically by the Supervisory Control and Data Acquisition (SCADA) which gives more clarification about their behavior trend. An unexpected increase in component temperature may indicate overload, poor lubrication, or possibly ineffective passive or active cooling. Many techniques are used to reliably predict generator's temperatures to avoid occurrence of failures in wind turbine generators. Multiple Linear Regression Model (MLRM) is a model that can be used to construct the normal operating model for the wind turbine generator temperature and then at each time step the model is used to predict the generator temperature by measuring the correlation between the observed values and the predicted values of criterion variables. Then standard errors of the estimate can be found. The standard error of the estimate indicates how close the actual observations fall to the predicted values on the regression line. In this paper, a new condition-monitoring method based on applying Multiple Linear Regression Model for a wind turbine generator is proposed. The technique is used to construct the normal behavior model of an electrical generator temperatures based on the historical generator temperatures data. Case study built on a data collected from actual measurements demonstrates the adequacy of the proposed model.

Current and future applications of small gas turbine engines annular type combustors have requirements presenting difficult disputes to the combustor designer. Reduced cost and fuel consumption and improved durability and reliability as well as higher temperatures and pressures for such application are forecast. Coupled with these performance requirements; irrespective of the engine size; is the demand to control the pollutant emissions, namely the oxides of nitrogen, carbon monoxide, smoke and unburned hydrocarbons. These technical and environmental challenges have made the design of small size combustion system a very hard task. Thus, the main target of this work is to generalize a calculation method of annular type combustors for small gas turbine engines that enables to understand the fundamental concepts of the coupled processes and to identify the proper procedure that formulate and solve the problems in combustion fields in as much simplified and accurate manner as possible. The combustion chamber in task is designed with central vaporizing unit and to deliver 516.3 KW of power. The geometrical constraints are 142 mm & 140 mm overall length and casing diameter, respectively, while the airflow rate is 0.8 kg/sec and the fuel flow rate is 0.012 kg/sec. The relevant design equations are programmed by using MathCAD language for ease and speed up of the calculation process.

Pavement distress is an indication of pavement layer deterioration. There are many types of

deteriorations; however, rutting, defined as the permanent deformation forming longitudinal

surface depressions in the wheel paths, is one of the most important kind of distress that affect

the safety and the ride quality of flexible pavement. The main objective of this study was to

develop an empirical pavement rutting model for the wet freeze zone, which is one of the four

long term pavement performance (LTPP) climate zones, to predict the depth of pavement rutting

on granular bases. Using the LTPP database, the study aimed at a better understanding of the

pavement rutting phenomena and the factors that may affect pavement rutting. Multiple

regression analysis was performed to develop a flexible pavement rutting model. The proposed

model was developed based on the relationship between the response variable rut depth, and

predictor variables of traffic loads, structural number, Marshall stiffness, air voids in the total

mix, and voids in the mineral aggregate. It was found that traffic loads was the predominant

factor that have a significant effect on pavement rutting, which agrees with the existing

literature, as well as engineering knowledge and practice. Following the traffic loads, structural

number was the most significant secondary factor, followed by percent of voids in the total mix,

• voids in the mineral aggregate, and Marshall stiffness.

neural network is considered as a nonlinear dynamic system consisting of a large number of simple processing elements interconnected in some manner with adjustable weighted strength. Neural networks provide qualitative and quantitative (analog, digital or logical) knowledge through information coding and decoding, and have powerful functions in learning and selforganization. These properties make neural networks considered to be more powerful in dealing with numerical data than other artificial intelligent systems like expert systems. However, the performance of neural networks depends deeply in number of factors including transfer function, number of hidden layers, number of nodes in hidden layers, input function, and weight function. In this article we present a comparative study of these factors and how they influence the performance of a system. 

The influence of physical (external added weight) and neurophysiological (fatigue) factors on static and dynamic balance in sport related activities was typified statically by the Romberg test (one foot flat, eyes open) and dynamically by jumping and hopping in both horizontal and vertical directions. Twenty healthy males were participated in this study. In Static condition, added weight increased body-s inertia and therefore decreased body sway in AP direction though not significantly. Dynamically, added weight significantly increased body sway in both ML and AP directions, indicating instability, and the use of the counter rotating segments mechanism to maintain balance was demonstrated. Fatigue on the other hand significantly increased body sway during static balance as a neurophysiological adaptation primarily to the inverted pendulum mechanism. Dynamically, fatigue significantly increased body sway in both ML and AP directions again indicating instability but with a greater use of counter rotating segments mechanism. Differential adaptations for each of the two balance mechanisms (inverted pendulum and counter rotating segments) were found between one foot flat and two feet flat dynamic conditions, as participants relied more heavily on the first in the one foot flat conditions and relied more on the second in the two feet flat conditions.

The Muslim faith requires individuals to fast between the hours of sunrise and sunset during the month of Ramadan. Our recent work has concentrated on some of the changes that take place during the daytime when fasting. A questionnaire was developed to assess subjective estimates of physical, mental and social activities, and fatigue. Four days were studied: in the weeks before and after Ramadan (control days) and during the first and last weeks of Ramadan (experimental days). On each of these four days, this questionnaire was given several times during the daytime and once after the fast had been broken and just before individuals retired at night. During Ramadan, daytime mental, physical and social activities all decreased below control values but then increased to abovecontrol values in the evening. The desires to perform physical and mental activities showed very similar patterns. That is, individuals tried to conserve energy during the daytime in preparation for the evenings when they ate and drank, often with friends. During Ramadan also, individuals were more fatigued in the daytime and napped more often than on control days. This extra fatigue probably reflected decreased sleep, individuals often having risen earlier (before sunrise, to prepare for fasting) and retired later (to enable recovery from the fast). Some physiological measures and objective measures of performance (including the response to a bout of exercise) have also been investigated. Urine osmolality fell during the daytime on control days as subjects drank, but rose in Ramadan to reach values at sunset indicative of dehydration. Exercise performance was also compromised, particularly late in the afternoon when the fast had lasted several hours. Self-chosen exercise work-rates fell and a set amount of exercise felt more arduous. There were also changes in heart rate and lactate accumulation in the blood, indicative of greater cardiovascular and metabolic stress caused by the exercise in subjects who had been fasting. Daytime fasting in Ramadan produces widespread effects which probably reflect combined effects of sleep loss and restrictions to intakes of water and food.