Optimization of fresh concrete pumping pressure loss with CFD-DEM approach

For remanufacturing truck cranes with the characteristic of single piece production, the coupling effect of multi-physical fields and the correlation of multi-defect modes are also faced in service. This causes that the safety of crane jib structures has great volatility and uncertainty and is difficult to be judged by fatigue test and damage test. To solve the above problems, an approach of fatigue remaining life evaluation based on random load spectrum is presented. By collecting operating cycle times corresponding to characteristic parameter values during the given time period, the small-sample measured load spectrum is acquired. Six probability distribution models are used to fit the lifting weight sample in characteristic parameters and the optimal distribution model based on Akaike's information criterion (AIC) is obtained. With the Latin hypercube sampling (LHS) method, a random sample of lifting weight is determined within the fixed inspection cycle. In addition, combining with the rated lifting weight table of truck crane, the corresponding jib length and working range are confirmed. Through defining random values of character parameters and matched operating cycle times, a random load spectrum is gained, thus enabling the extension of measured load spectrum. Depending on the remanufacturing information database, the remanufacturing information of truck crane are retrieved to determine fatigue dangerous cross sections and critical points of jib structures. In order to reflect the variation of structure stress level, the equivalent cross sections of dangerous cross sections are constructed. The first principal stress–time history simulation model for critical points is established, and the rain-flow counting technology is adopted to extract the two-dimensional stress spectrum from simulation results. Using the Paris formula combined with the greatest risk principle, the fatigue residual life of jib structure is estimated. Furthermore, the fatigue remaining life evaluation system for jib structure of remanufacturing truck crane is developed for easier application of the proposed method. Finally, as an illustrative example, jib structures of ZLJ5551JQZ110V remanufacturing truck crane are provided to demonstrate the validity and feasibility of this method and system.

Fatigue remaining life estimation for remanufacturing truck crane Jib structure based on random load spectrum

Fatigue residual life estimation of jib structure based on improved v‐SVR algorithm obtaining equivalent load spectrum

The purpose of this study is to present a new method for estimating the fatigue life of the screw blade in the screw sand washing machine. To ensure the accuracy of numerical simulation, the loading area and the value of load are determined by means of the theoretical analysis. To ascertain the location of the stress peak and stress range, the static analysis of the screw blade is executed via the finite element method. To reduce the research cost and ensure the feasibility of the research method, Markov chain Monte Carlo (MCMC) is employed to simulate the random load with the Gauss distribution on the screw blade. In addition, the Nondominated Sorting Genetic Algorithm (NSGA-II) is utilized to find out an optimum variation coefficient of the stress, aiming at guaranteeing the precision of the random load. The rainflow cycle extrapolation is adopted to generate the fatigue load spectrum closer to the real condition, taking account of the possibility of the extreme loads caused by overload occurrence. Subsequently, the rainflow matrix after extrapolation, the estimated P-S-N curve, Goodman stress correction method and Miner's rules are made use of assessing the service life of the screw blade. In particular, the effects of the surface roughness, residual stresses and fatigue notch factors on the fatigue life are taken into consideration. Ultimately, the non-linear surface fitting technique is used to obtain the equation concerning the fatigue life of the screw blade versus residual stresses and fatigue notch factors. The numerical results show that the stress peak is in the root of the screw blade and the service life of the screw blade declines exponentially with growing residual stresses and fatigue notch factors.

Yonghong Liu

Papers

Fatigue life prediction for boom structure of concrete pump truck