Random vibration fatigue loading occurs in automotive, aerospace, offshore and indeed in many structural and machine components. The analysis of these types of problems is often carried out using either time domain or frequency domain methods. Time domain rainflow counting together with Miner's linear damage accumulation assumption is widely accepted as a method of rationalising stress amplitude and mean stress from random fatigue loading and the damage caused to the component. Frequency domain methods provide a faster alternative for the analysis of the same problem but the results are generally conservative compared to those obtained using time domain methods. This paper presents an artificial neural network (ANN) machine learning approach for the prediction of damage caused by random fatigue loading. The results obtained for ergodic Gaussian stationary stochastic loading is very encouraging. The method embodies rapid analysis as well as better agreement with rainflow counting method than existing frequency domain methods.
Current diesel engine after-treatment systems such as Selective Catalyst Reduction (SCR) use ammonia (NH3) to reduce Nitrogen Oxides (NOx) into Nitrogen (N2) and water. However, if the reaction between NH3 and NOx is unbalanced, it can lead either to NH3 or NOx being released into the environment. As NH3 is classified as a hazardous compound on the environment, its accurate measurement is essential.
Fourier Transform Infrared (FTIR) and Tuneable Diode Laser (TDL) spectroscopy are two of the methods that can measure raw emissions from engine exhaust pipes, especially NH3. However, it is difficult to suggest which method is the right one for measuring NH3 from engine exhausts.
This paper compares the effectiveness of FTIR and TDL methods for NH3 measurement from diesel engine exhausts, based on tests conducted under well-controlled laboratory conditions. The concentration of NH3 from a diesel engine was measured under both a steady-state test cycle and a transient test cycle. The NH3 readings from FTIR and TDL were analysed, for comparison of precision, response time and their accuracy. It was shown that both techniques were suitable with attention to the different sampling procedures to avoid absorption.
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