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In this paper, the steady-state and transient heat transfer processes of functionally graded materials (FGMs) are analyzed using a coupled thermo-mechanical model in a GPU parallel multiphysics finite–discrete element software, namely MultiFracS. First, the coupled model to handle the heat transfer problem of heterogeneous materials is verified. Then, the advantages and disadvantages of FGMs and composite materials in response to thermal shock loads are compared and the results indicate that FGMs can overcome extreme environments better than composite materials. Finally, the influence of the geometric distribution characteristics of the double-edge cracks in the gradient material plate on the crack propagation is analyzed. The simulation results show that the interaction between the cracks affects the crack propagation path under the thermal load. The inclination angle and spacing of double-edge cracks greatly influence crack propagation. Specifically, a larger inclination angle and spacing can lead to a smaller crack propagation angle. The approach in this paper provides a new quantitative tool for investigating the thermal, elastic, and cracking of functionally graded materials.

Cycle-to-cycle variations during the combustion phase should be comprehensively investigated because these variations are among the most serious causes of higher emissions and lower efficiency. The main objective of this study was to evaluate the relationship between cyclic variations and combustion parameters. The combustion and cyclic variation characteristics were investigated using a diesel engine operating on Fischer−Tropsch (F−T) fuel synthesized from coal. Experiments were conducted under full load conditions at three engine speeds of 1200, 2000, and 2800 rpm. The results revealed that cyclic variations of F−T diesel were lower than those of 0# diesel, acquired the minimum value at the speed of 2000 rpm, and reached the maximum at the speed of 2800 rpm. The mean fluctuation intensity of F−T diesel was 0.185, 0.189, and 0.205 at speeds of 1200, 2000, and 2800 rpm, respectively, smaller than that of 0# diesel under the corresponding conditions. The relationships between cyclic variations and combustion parameters were analyzed by correlation methods. Maximum in-cylinder pressure (Pmax) increased linearly with increased ignition delay, while it decreased linearly with increased combustion duration. The Pearson’s correlations between Pmax and ignition delay were 0.75, 0.78, and 0.73; however, the corresponding values between Pmax and combustion duration were 0.61, 067, and 0.65 when fueled with F−T diesel at speeds of 1200, 2000, and 2800 rpm, respectively. Moreover, the Pearson’s correlations of 0# diesel were higher than those of F−T diesel at the same operating loads. Compared with combustion duration, the ignition delay had more important effects on cyclic variations with a higher Pearson’s correlation. Furthermore, the ignition delay significantly influenced cyclic variation under a high speed load, while the combustion duration had a marked effect under low speed conditions. Overall, the results revealed the importance of combustion parameters on cyclic variation, which has great significance for controlled cyclic variation in diesel engines.

This paper proposes a fault identification method based on an improved stochastic subspace modal identification algorithm to achieve high-performance fault identification of dump truck suspension. The sensitivity of modal parameters to suspension faults is evaluated, and a fault diagnosis method based on modal energy difference is established. The feasibility of the proposed method is validated by numerical simulation and full-scale vehicle tests. The result shows that the proposed average correlation signal based stochastic subspace identification (ACS-SSI) method can identify the fluctuation of vehicle modal parameters effectively with respect to different spring stiffness and damping ratio conditions, and then fault identification of the suspension system can be realized by the variation of the modal energy difference (MED).

The paper presents a study of the relationship between the combustion behavior and vibration response of internal combustion (IC) engines fueled with biodiesel based on finite element modelling along with experimental evaluation. An improved finite element (FE) model is established and validated to predict the dynamic responses of cylinder liners with respect to two main sources: combustion shock and piston side thrust. Based on the validated FE model, the response characteristics of the cylinder liner in an IC engine fueled with biodiesel and its causal relationship with excitation sources have been predicted. Due to the lower calorific value of biodiesel, a greater amount of fuel is injected into the combustion chamber to maintain power outputs, which results in a prolonged combustion duration and subsequent higher overall vibration levels, compared with that of diesel. The advanced ignition of biodiesel is the main cause to the compound effect on the coupling of piston side-thrust force, thereby resulting in a nonlinear increase in the root mean square (RMS) of local vibration response close to the combustion top dead center (TDC). These key findings provides insight understandings for not only biodiesel combustion diagnostics but also more accurate diagnostics of fossil diesel based on nonintrusive vibrations.

As one of the most common gear failure modes, tooth wear can produce nonlinear modulation sidebands in the vibration frequency spectrum. However, limited research has been reported in monitoring the gear wear based on vibration due to the lack of tools which can effectively extract the small sidebands. In order to accurately monitor gear wear progression in a timely fashion, this paper presents a gear wear condition monitoring approach based on vibration signal analysis using the modulation signal bispectrum-based sideband estimator (MSB-SE) method. The vibration signals are collected using a run-to-failure test of gearbox under an accelerated test process. MSB analysis was performed on the vibration signals to extract the sideband information. Using a combination of the peak value of MSB-SE and the coherence of MSB-SE, the overall information of gear transmission system can be obtained. Based on the amplitude of MSB-SE peaks, a dimensionless indicator is proposed to assess the effects of gear tooth wear. The results demonstrated that the proposed indicator can be used to accurately and reliably monitor gear tooth wear and evaluate the wear severity.