A neural network simulator of a gas turbine with a waste heat recovery section

The objective of the paper is to assess the feasibility of the neural network (NN) approach in power plant process evaluations. A "feed-forward'' technique with a back propagation algorithm was applied to a gas turbine equipped with waste heat boiler and water heater. Data from physical ol empirical simulators of plant components were used to train such a NN model. Results obtained using a conventional computing technique are compared with those of the direct method based on a NN approach. The NN simulator was able to perform calculations in a really short computing time with a high degree of accuracy, predicting various steady-state operating conditions on the basis of inputs that can be easily obtained,vith existing plant instrumentation. The optimization of NN parameters like number of hidden neurons, training sample size, and learning I ate is discussed in the paper

Urban green spaces assessment approach to health, safety and environment

The city is alive with dynamic systems, where parks and urban green spaces have high strategic importance which help to improve living conditions. Urban parks are used as visual landscape with so many benefits such as reducing stress, reducing air pollution and producing oxygen, creating opportunities for people to participate in physical activities, optimal environment for children and decreasing noise pollution. The importance of parks is such extent that are discussed as an indicator of urban development. Hereupon the design and maintenance of urban green spaces requires integrated management system based on international standards of health, safety and the environment. In this study, Nezami Ganjavi Park (District 6 of Tehran) with the approach to integrated management systems have been analyzed. In order to identify the status of the park in terms of the requirements of the management system based on previous studies and all Tehran Municipality’s considerations, a check list has been prepared and completed by park survey and interview with green space experts. The results showed that the utility of health indicators were 92.33 % (the highest) and environmental and safety indicators were 72 %, 84 % respectively. According to SWOT analysis in Nezami Ganjavi Park some of strength points are fire extinguishers, first aid box, annual testing of drinking water and important weakness is using unseparated trash bins also as an opportunities, there are some interesting factors for children and parents to spend free times. Finally, the most important threat is unsuitable park facilities for disabled

A simple transformation method in skewness reduction

Statistical analysis of non-normal data is usually more complicated than that for normal distribution. In this paper, a simple root/power transformation technique developed by Niaki, et al [1] is extended to transform right and left skewed distributions to nearly normal. The value of the root/power is explored such that the skewness of the transformed data becomes almost zero with an acceptable error. The proposed method is then compared to the well-known and complicated Box, et al [2] transformation method for different left and right skewed distributions using Monte Carlo simulation. While the proposed procedure is easy to understand and to implement, the results of the simulation study show that it works as good as the Box-Cox method

A neural network simulator of a gas turbine with a waste heat recovery section

The objective of the paper is to assess the feasibility of the neural network (NN) approach in power plant process evaluations. A "feed-forward'' technique with a back propagation algorithm was applied to a gas turbine equipped with waste heat boiler and water heater. Data from physical ol empirical simulators of plant components were used to train such a NN model. Results obtained using a conventional computing technique are compared with those of the direct method based on a NN approach. The NN simulator was able to perform calculations in a really short computing time with a high degree of accuracy, predicting various steady-state operating conditions on the basis of inputs that can be easily obtained,vith existing plant instrumentation. The optimization of NN parameters like number of hidden neurons, training sample size, and learning I ate is discussed in the paper

Implementation of child safety and health management system by means of FMEA method

Every year, many accidents leading to physical injuries in kindergartens, indicates that a very large percentage of them are related to the safety concerns and lack of hygiene in these places. Families, due to their busy life style and working hours and also children needs of preschool education, are searching to find most suitable kindergartens for their children. Selecting a kindergarten with various suitable training programs, although very important criteria for selection, but is not sufficient. Indicators such as health, safety and environment issues in these places must be crucial factors in this decision making. Child safety and health management system is an integrated system, derived from health, safety and environmental management regulations which helps the kindergartens complies with relevant regulations to reduce the number of accidents occurrence. The present case study has tried, by using failure modes and effects analysis method and child safety and health management system to find the best practicable indicators to assess the relative impact of different failures in order to identify the parts of the process that are most in need of change. In this regards, 10 semi-governmental kindergartens located in Tehran District 6 of Tehran Municipality, which are supervised by municipality of Tehran were selected and evaluated. The results showed that according to the child safety and health management system and failure modes and effects analysis, all these places need massive infrastructural changes according to the preventive action list in order to be considered a safe and hygienic place for the children