seyed ashkan moosavian

The importance of the effect of geographic climate on the performance parameters of cars requires comprehensive studies and research in this field, especially in Iran, where the diversity of climatic conditions is clearly evident. The factor scores of each of the influential components in determining the climate divide Iran into four climatic categories, which are: (1) dry, (2) humid with heavy rainfall, (3) semi-humid, semi-dry and (4) humid with little rainfall. Therefore, in this research, the effect of geographic climate on the characteristics of statistical data and driving cycle has been investigated. For this purpose, four cities of Arak (semi-arid to semi-humid), Tehran (dry), Ahvaz (humid with low rainfall) and Rasht (humid with high rainfall) were selected as representatives of their climate. Then, by reducing the dimensions of the data from 12 to 2 statistical data characteristics, using PCA analysis, and then by clustering the data using the chemical mean method, and extracting the driving cycles of each city under different climatic conditions, the effect of the geographic climate on the characteristics of the statistical data and the driving cycles of the case was investigated, and also the data of the city of Rasht on rainy and non-rainy days were separated and analyzed, and in the results of the investigations, it was observed that climatic conditions can have significant effects on the average driving speed (about 21 percent), travel time ( about 18 percent) as well as average travel speed (about 22 percent) and car stopping percentage (about 84.4 percent). As a result, it can be said that geographical climate is one of the most influential factors on driving cycles.

Driving cycles represent the vehicle speed as a function of time and are used in vehicle design, fuel management, and the improvement of standard indicators. In this study, four combined driving cycles were extracted using real data. The data was collected from a passenger car with a gasoline engine under real driving conditions while driven from Tehran to Amol based on the car chasing method. A code was generated in MATLAB software to create the desired cycle using support vector machine and K-means algorithms considering mid-range and mean values as group centers. The characteristic parameters of the cycles such as the average speed and the percentage of the car travel time at idle, cruise, accelerating, and decelerating conditions were also calculated. These cycles were compared based on the mean relative error, the root-mean-square error, and the Chi-square test. The results showed that the cycles extracted by the support vector machine were closer to the allowable time interval (less than 1800 seconds); however, the cycle extracted by the K-means algorithm with the mean value as the centers of the generated categories, recorded the least errors. This cycle, in addition to spending most of its time in accelerated motion, represented a greater amplitude of acceleration and velocity fluctuations than other cycles.

In recent decades, rising greenhouse gas emissions have become a major challenge and concern. Environmental pollution is one of the greatest human challenges of the 21st century. Improving the performance of internal combustion engines and reducing the amount of pollutant emissions has always been a concern for researchers. The use of alternative fuels and the control and adjustment of the lambda coefficient are known as the most effective ways to increase fuel efficiency, reduce pollution and improve engine mobility. Therefore, in this study, the relationship between air-to-fuel equilibrium ratio or lambda coefficient with engine performance and exhaust emissions of a diesel engine using diesel-ethanol fuel blends as an alternative fuel at 1700, 1800 and 1900 rpm engine speeds has been investigated. The results showed that increasing the percentage of ethanol in the diesel-ethanol fuel blend increased the lambda coefficient. This increase reduced engine power and torque. The highest power reduction was achieved at 1900 rpm at the rate of 1.18 kW and the maximum torque reduction at 1800 rpm at the rate of 5.94 N.m. As the lambda coefficient increased, the exhaust oxygen output increased by 42.89% at 1700 rpm. The increase in lambda also reduced the emissions of unburned hydrocarbons and carbon monoxide. Thus, the highest reduction of these pollutants was 23.8% at 1800 rpm and 38.75% at 1900 rpm, respectively. Also, increasing the lambda coefficient slightly increased the nitrogen oxides. Finally, due to the use of diesel-ethanol fuel blends and as a result of increasing the lambda coefficient, a significant reduction in the amount of emissions of exhaust gases was achieved.

In this article, different defects in the carbon fiber reinforced polymer matrix laminated composite under tensile loading have been detected by the vibration analysis. For this objective, the tensile test on open-hole composite standard specimens was performed based on the ASTM-D5766 standard. The tensile loading was considered as 2 mm/min, based on the mentioned standard. Acceleration sensors was installed on standard specimens and vibration signals were acquired during tensile loading. In order to detect different defects, in addition to composite standard samples, pure resin and pure fiber specimens were also tested under tensile loading. Signals for pure resin and pure fiber samples were analyzed by the Fourier transform method and signals for open-hole composite standard specimens were analyzed by the wavelet transform approach. Obtained results from the signal analysis showed that the vibration analysis could be a proper method to detect three types of defects in the carbon fiber reinforced polymer matrix laminated composite, including the fiber breakage, matrix cracking and other failures. These other failures were debonding, the delamination and the pull-out. Then also, the maximum percentage of failure mechanisms in the open-hole composite standard samples was due to debonding of fibers from the matrix, the delamination and the pull-out failure. Such these results had an agreement with images from the scanning electron microscopy, which obtained from the fracture surface of standard specimens, after tensile testing.

Pistons are always exposed to scuffing fault in an internal combustion engine. This fault can seriously damage piston and cylinder so that engine performance decreases drastically. The objective of this research is to investigate the effects of piston scuffing fault on the engine vibration in order to the usage of vibrations for detecting this fault. To this end، horizontal and vertical vibration signals of the engine were captured for healthy condition and scuffed piston and cylinder state. In this research، time-domain، frequency-domain and time-frequency domain analyses were used for the engine vibrations. In time-domain analysis، two parameters of root mean square and impulse factor were extracted from the vibration signals. Fast Fourier transform and short-time Fourier transform were employed for frequency-domain and time-frequency domain analyses، respectively. Moreover، two features of mean and energy were used in time-frequency domain analysis. The results showed that the piston scuffing fault generates significant vibrations in horizontal and vertical directions of the engine. Also based on the obtained results، the piston scuffing fault produced substantial vibrations in the frequency band of 2 to 6 kHz in the horizontal direction، whereas for the vertical vibrations of the engine، the frequency band of 4 to 6 kHz was affected. The obtained results demonstrated that the engine vibrations are capable of identifying the pistion scuffing fault، and can be used for its detection in engine.