This paper presents an application of a condition-monitoring system (CMS) based on a polynomial regression model (PRM) to study the influence of heat loss on a wind generator’s temperatures. Monitoring the wind generator temperatures is a significant for efficient operation, and plays a key role in an effective CMS. Many techniques, including prediction models can be utilized to reliably forecast a wind generator’s temperature during operation and avoid the occurrence of a failure. PRMs are widely used in situations when the relationship between the response and the independent variables are curve-linear. These techniques can be used to construct a normal behavior model of an electrical generator’s temperatures based on recorded data. Many independent variables affect a generator’s temperature; however, the degree of influence of each independent variable on the response is dissimilar. In many situations, adding a new independent variable to the model may cause unsatisfactory results ;therefore, the selection of the variables should be very accurate. A generator’s heat loss can be considered a significant independent variable that greatly influences the wind generator with respect to the other variables. A generator’s heat loss can be estimated in intervals by analyzing the exchange in the heat between the hot and cold fluid through the heat exchangers of wind generators. A case study built on data collected from actual measurements demonstrates the adequacy of the proposed model. 

Compiler writers have developed various techniques, such as constant folding, subexpression elimination, loop transformation and vectorization, to help compilers in code optimization for performance improvement. Yet, they have been far less successful in developing techniques or cost models that compilers can rely on to simplify parallel programming and tune the performance of parallel applications automatically. This paper is the first of two-phase study to develop an analytical model that can be used to estimate the cost for sequential and parallel execution of array expressions on multicore architectures. While this paper discuss the possibility of developing a cost model to estimate the sequential execution of array expressions on a single CPU, the second part of the investigation shall focus on developing a model to estimate parallel execution of arrays on multicore platforms. The model presented in this paper is expected to be used by programming language compilers as complement component with the other model to estimate and subsequently decide whether to parallelize individual array expressions or not. The preliminary results which are presented here show that this model can give a satisfactory evaluation and high-precision estimation for the cost of executing a regular array expression on a single core processor.

In this study, the production of ethylene and hydrogen is studied via the thermal cracking of ethylene in an ethylene plant based in Libya. During the process of thermal cracking, a mix of naphtha and steam is input into tubes that are directed to the naphtha main line. The utilization of steam is generally used because of the partial removal of coke which has undesirable effects on the process. The coke accumulation on the coils, or tubes, result in a decrease in pressure and also reduction in the yields produced. In this work, the naphtha thermal cracking process is both designed and solved numerically. A thorough comparison of the design results and the data extracted from the experiment reveal that the design may predict the overall process precisely. Also, the direct effects of CO2 are studied with regard to the accumulation of coke. Based on the results of two separate scenarios, the process of thermal cracking with the CO2 is beneficial to the overall process due to the higher yield of ethylene and propylene, and less accumulation of coke, and, in turn, less thickness on the coils inside the furnace. The results from the simulation show that the run time, or run length, of the furnace with the addition of CO2 becomes almost two times as the run time with adding steam. Based on these results, this study has proven to be worthy to explore, and the addition of CO2 has been observed to have noticeably positive results on the thermal cracking process.

Abstract—this work reports on a high speed flexible automation system based on Cartesian multi-axis coordinate system linear step motor developed, in the target application as a multi-use robot system. The task of this work is to constructs an interactive multimedia page for study and researches the principle’s work of drive of direct action linear step motor, Development the mathematical model and implementation of a closed loop control, based MATLAB/SIMULINK, Study the static and dynamic characteristics of the motor movement which is restricted to the trajectories accessible through the given commands.

Abstract—This work reports on the steady-state analysis and control strategies of switched reluctance motors (SRMs). For this purpose, a theoretical background is introduced and a mathematical model is derived. A Matlab code has been written to determine the motor magnetic characteristics. The inductance profile has also been determined and from which the induced voltage constant, which is used to find the electromagnetic torque, is obtained. A low-performance voltage control strategy is applied to the motor. Simulation results are given to evaluate the overall system performance

Abstract

There is much discussion in the scientific literature and concern in the wider community about climate

change, recent climate analyses indicate that the magnitude of 21st Century warming is likely to have been the

largest of any century for the last 1000 years over the northern hemisphere. All the IPCC's four reports between

1990 and 2007 concluded that we cannot expect stable climate in the future and we should prepare scenarios

and strategies for the survival of humankind under the conditions of forthcoming global change. In this study,

the applicability of the statistical downscaling model (SDSM) in downscaling temperature in Misurata area -

Libya, was investigated. The investigation includes the calibration of the SDSM model by using large-scale

atmospheric variables encompassing NCEP reanalysis data, the validation of the model were measured daily

temperature data (1961-1990) using independent period of the NCEP reanalysis data and the general circulation

model (GCM) outputs of scenarios A2 and B2 of the HadCM3 model. The model is calibrated and applied at a

daily time series, even though the output is monthly and the prediction of the future regional maximum and

minimum temperature scenarios for three time windows: 2011-2040, 2041-2070 and 2071-2099. The results showed

that: The statistical downscaling model (SDSM) was able to describe the basic statistical properties of daily

minimum and maximum temperature in the period of record, suggesting that it could be used to predict future

trends. Trend analysis in the study area showed an increase in average annual and monthly temperature,

compared to the baseline period for both HadCM3A2a and HadCM3B2a scenarios in both the dry and wet

seasons. However, this increase is higher in dry months than wet months for all future time horizons and for

both HadCM3A2a and HadCM3B2a scenarios. Thus there is likely to be a significant warming in local surface

temperature, which is enough for a significant change on the energy balance and is likely to impact water

availability.

Key words: Statistical downscaling model SDSM Intergovernmental Panel on Climate Change

IPCC General circulation model GCM Special Report on the Emission Scenarios SERS

Maximum and minimum temperature Misurata area Libya