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Go to Editorial ManagerPipelines are one of the most convenient and effective ways of transporting petrol over a long distance. The environment applies, beyond extremely high external pressures, low temperatures and intensive corrosive process, the occurrence of defects on the pipe body, which compromises the structural integrity of pipelines leading to catastrophic failures. The main modifications concern the mechanical resistance, toughness at low temperatures weld ability and resistance to embrittlement related to hydrogen. Among mechanical characteristics, the fracture toughness is very important for pipeline steels in design and safe assessment. Aiming to enhance the reliability and operation of complex pipelines system, a study based on the mechanics of the elastoplastic fracture in order to determine better prediction of the fatigue life. The materials tested here are API 5L X42 and X52 micro alloyed steels, as well as to evidence the toughness resistance of these materials. Results indicated that both X42 and X52 steel behave in a similar way and in all cases a slight increase of the transition temperature was found. The characteristic toughness value shows an evident loss in mechanical performances if compared to the uncharged one.
In this paper, Weibull uni-axial and multi-axial distribution function is applied to evaluate the reliability of the fracture strength of rotating turbine rotor wheel manufactured from ceramic material and have inner surface crack. Three cases are considered, first taking only the effect of rotational stresses, second taking the effect of rotational and thermal stresses in ceramic disc, and third taking the effect of rotational and thermal loading in ceramic blade. It was found that there is a convergence between results gotten from uni-axial and multi-axial distribution function, but multi-axial distribution function give small large in values result compared to uni-axial distribution function. The expected values of rupture strength of ceramic blade is higher than of that of disc material, therefore the failure occurs in blade first than in disc material in service survival.
Monitoring the health of rotating machinery is essential to ensure system safety, achieve cost savings, and enhance overall reliability. The requirement for a reliable and clear method of identifying defects has prompted the development of several monitoring techniques. They utilize vibration, measurement of the motor's current signature, and acoustic emission data in the process of condition monitoring. The MFS (machinery fault simulator) equipment was used to determine bearing faults using vibration signal analysis. MFS conducts simulations and investigations of many bearing issues, including those occurring in the inner race, outer race, and balls. An accelerometer (type B & K 4366) was connected to a data acquisition device (IDAC-6C) to record vibration signals under different operating conditions. Furthermore, a tachometer equipped with an LCD display is employed to measure the rotational speed. Four types of defects in ball bearing (Koyo 1205C3 type) were studied, the slot in outer race with size 0.196 mm, the slot in inner race with size 0.191 mm, in ball with size 0.196 mm in additional to compound defect. In this paper, spectral correlation technique was employed to detect defects in ball bearings running at varying speed, along with spectral coherence and the corresponding Enhanced Envelope Spectrum (EES) in frequency-order domain and order-order domain. The results show that the adopted methods, that are used to analyze the real vibration signals for diagnosis the defected ball bearings, are suitable, accurate and less processing time for varying speed. The processing time of the FastACP method used to analyze the signals in order- order domain is less than that of the adopted method in the frequency-order domain for any defect type. Overall, using the FastACP method in the order-order domain significantly reduced processing time by approximately 27% compared to the adopted method in the frequency- order domain under varying speed conditions.
Bearing fault diagnosis is essential for the maintenance, durability, and reliability of rotating machines. It can minimize economic losses by removing unplanned downtime in the industry due to the failure of rotary machines. In bearing fault detection, developing fault features extraction techniques that can successfully applicable for various fault severity and different operating conditions is still a critical issue. In the current work, the feature extraction technique is a combination between pre-processing algorithms and envelope analysis method. In the pre- processing stage, the autoregressive (AR) model is used to filter the original signal and remove the deterministic vibration sources, as well as maintain the signal representing the condition of the bearing without contaminating noises. Then, the most suitable frequency band is selected based on the spectral kurtosis (SK) analysis. This band contains the signature frequencies of the roller bearing. After that, envelope analysis is employed for detecting faults at different severity. Finally, the features represented the peaks at fundamental fault frequencies are automatically selected from the envelope spectrum. By analyzing all diagnoses results, it is found that the presented method effectively extracts the features at calculated resonance bearing frequencies and proves the significance of the enhancements in a pre-filtering stage in the overall detection performance. Also, it can benefit from these features in the fault classification fields at different speeds because it is independent of speed variation.
This work uses different shapes of intake manifold for study the effect on a single cylinder four stroke gasoline engine. A numerical simulation of the flow achieved through five intake manifold designs, using 3D Computational Fluid Dynamic (CFD) software package FLUINT (6.3.). Accordingly, the three-dimensional resolution of Navier-Stokes equations in conjunction with the standard k-ε turbulence model is undertaken to provide knowledge of the air movement nature and examining the intake manifold optimal geometry. Five cases of intake manifold are examined experimentally in order to produce a comprehensive and realistic data set. These data are in the form of engine performance, exhaust gas products and relative AFR for each case separately under different engine speeds. Exhaust gas analyzer type (Infragas-209) is used in the present work to measure exhaust gas concentrations and relative air/fuel ratio ( ). The results were obtained in this investigation showed that a Simulate numerically and experimentally is capable to select the optimized intake system geometry with reliability. Velocity is highest near the outer wall at increased the curvature ratio and pressure is highest near the inner wall at increased the curvature ratio. The secondary flow increases when the engine speeds and curvature ratio increase because of increasing the pressure difference between the inner wall and the outer wall. The effect of these parameters explained on the swirl air movement and tumble inside the cylinder are increasing by increase the engine speed and γ respectively. The increasing in the engine speed and the optimum selection of the manifold which designed enhanced the mixing of the fuel with air. The results showed that the optimized manifold 135º- NE (case 5) due to enhance AFR, fuel consumption and exhaust emissions are improved.