The influence of processing parameters on aluminium alloy A357 manufactured by Selective Laser Melting

A comparative study of the mechanical properties of 20 experimental alloys has been carried out. The effect of different contents of Si, Cu, Mg, Fe and Mn, as well as solidification rate, has been assessed using a strength-ductility chart and a quality index-strength chart developed for the alloys.The charts show that the strength generally increases and the ductility decreases with an increasing content of Cu and Mg. Increased Fe (at Fe/Mn ratio 0.5) dramatically lowers the ductility and strength of low Si alloys. Increased Si content generally increases the strength and the ductility. The increase in ductility with increased Si is particularly significant when the Fe content is high. The charts are used to show that the cracking of second phase particles imposes a limit to the maximum achievable strength by limiting the ductility of strong alloys. The (Cu + Mg) content (at.%), which determines the precipitation strengthening and the volume fraction of Cu-rich and Mg-rich intermetallics, can be used to s...

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Strength-ductility behaviour of Al-Si-Cu-Mg casting alloys in T6 temper

Damage initiation in model metallic materials: X-ray tomography and modelling

https://www.cavs.msstate.edu/publications/docs/2003/01/754Cyclic%20plasticity.pdf

Cyclic plasticity at pores and inclusions in cast Al-Si alloys

https://www.cavs.msstate.edu/publications/docs/2000/01/825Finite%20element.pdf

Finite element analysis of the stress distributions near damaged Si particle clusters in cast Al–Si alloys

The cracking of Si particles in an A357 Al alloy has been investigated over a spectrum of stress and strain by varying aging strength and applying different tensile strains. The variation of the fraction of broken Si particles with stress, strain, and cleavage plane orientation has been obtained. The features of cracking reveal that cracking of Si particles is a very localized event. A dislocation pileup mechanism is the most probable one among all crack-initiation theories for explaining the behavior. Based on this mechanism, further deduction has been made to obtain the relationship between the fraction of broken particles and metallurgical factors. The present data, along with Gurlandrss and that of Lowet al., have been found to verify this relationship for the effect of stress, strain, and cleavage plane orientation.

The cracking mechanism of silicon particles in an A357 aluminum alloy

In recent years, many studies on variational mode decomposition (VMD) have mainly focused on choosing the number of modes and balancing parameter, while less research focuses on the internal properties of VMD. This paper proposes an adaptive single-mode VMD (ASMVMD) method based on the convergence characteristics of VMD and the adaptivity of particle swarm optimization (PSO). Firstly, we study the convergence characteristics of single-mode VMD and find that the U-shaped convergence region related to fault impact is very wide in the whole frequency domain. Secondly, based on the characteristics of the U-shaped convergence region, a new population position initialization strategy is proposed. Finally, the improved PSO is used to optimize the initial center frequency and balancing parameter of single-mode VMD. The effectiveness of the proposed method is verified by analyzing the simulated signal and wheelset bearing fault signals. Compared with the fast kurtogram and Autogram, it is shown that ASMVMD has a stronger capability of fault feature extraction.

Adaptive single-mode variational mode decomposition and its applications in wheelset bearing fault diagnosis

Aiming at the difficulty of accurate diagnosis of wheelset-bearing system composite faults, a multi-fault feature extraction method based on self-adaptive variational mode extraction (SAVME) was proposed. Variational mode extraction (VME) can extract a specific sub-signal from a multi-component signal. The key to the success of this algorithm is to determine appropriate initial parameters in advance, including initial center frequency (ICF) and penalty factor. To determine the key parameters of VME adaptively, the convergence characteristics of VME are analyzed deeply, and the VME convergence tendency diagram is proposed creatively according to the trend of the iterative curve of the center frequency of the desired mode. By analyzing the test signal with the VME convergence tendency diagram, the number of main latent sub-signals in the test signal and the ICF of each sub-signal corresponding to the VME can be determined efficiently. Then, according to the position of the ICF of each sub-signal in the frequency domain, the empirical formula of the penalty factor is used to quickly obtain the appropriate penalty factor. The proposed SAVME method not only improves the parameter selection adaptability of the traditional VME algorithm but also extends the VME algorithm to the field of multi-fault diagnosis. By analyzing the simulated signal and two experimental signals, the effectiveness of the SAVME algorithm is verified. Compared with the fast kurtogram method and the adaptive variational mode decomposition method, the proposed method is more accurate and superior in the multi-fault feature extraction of the wheelset-bearing system.

A new fault diagnosis method for wheelset-bearing system based on VME convergence tendency diagram

The physical and mechanical properties of the reservoir bank slope deteriorate under the fluctuation of water level, causing bank debonding and slippage, which can produce different degrees of damage to the bridge foundation, piers, and superstructure, a condition that is difficult to treat. In this paper, for a Yangtze River Bridge bank slope instability problem in the Three Gorges reservoir area, a numerical model of the bank slope and bridge was established using the finite element-SPH conversion coupling algorithm, and the pile pier damage development law and damage mode (deformation and stress–strain curves of the bank slope and pile foundation) were obtained according to the geological conditions of the bridge location. Additionally, combined with the characteristics of bank destabilization in the reservoir area of the Three Gorges Yangtze River Bridge, landslide management is proposed by using soil drainage and anti-slip pile reinforcement measures. In addition, for the characteristics of bridge pier deflection, a comprehensive deflection correction reinforcement method of pushing deflection correction, adding pile foundation, expanding pile bearing, and increasing pier cross-sectional area is proposed, so as to provide a theoretical basis for the prevention and control of reservoir bank landslides, the service life of pile structure, and the disposal of diseases.

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Study on the Damage Mechanism of Bank Slope-Bridge Pile Foundation Interaction under Reservoir Water Level Cycle


 The hardness and high abrasiveness of shale formations pose great challenges for improving drilling performance with deeper and more complex unconventional gas-reservoir formations explored and developed in the Sichuan Basin of China. The work discussed a workflow of data-driven drilling-parameter optimization based on machine learning. The algorithm was used to construct the correlation among drilling parameters, lithology change, vibration, bit wear, and hole cleaning, dynamically optimize rock-breaking efficiency, and integrate with the rig control system.
 The data-driven drilling optimization workflow consisted of exploration mode, learning mode, and application mode. The exploration phase trained a linear model at a certain frequency during data collection and updates the increasing trend of rate of penetration (ROP) in real time after starting the workflow. Based on the trend, the direction for further exploration was given. The system entered the learning mode after sufficient exploration to learn the exact functional relationship between ROP/MSE (mechanical specific energy) and operation parameters in the current explored data queue. Current optimal operation parameters were presented based on the function relationship. Then the workflow entered the application mode, maintained the current optimal operating parameters, and kept the efficient rock-breaking state. The workflow constantly monitored the micro-interval ROP and bit energy output in the application mode. When drilling performance was under expectation, the workflow automatically evaluated new conditions (e.g., formation change, Bottom hole assembly (BHA) vibration, and cuttings bed) and switched to the learning mode or exploration mode to adapt to changes in the current drilling state.
 The algorithm has been integrated with the rig control system, and the field test was carried out in well Ning 209H71-3, a shale-gas horizontal well in the Sichuan Basin. The test showed that the random forest and support vector machine algorithm could fit the nonlinear function relationship among drilling parameters, hole cleaning, and bit working performance, with properly optimized parameters presented. Besides, the workflow could evaluate the trends of ROP, MSE, depth of cutting (DOC), and stick-slips (SS) to capture the limiters for drilling performance, such as bit wear and lithology changes. Two modes integrated with global and local recommendations, and the optimal parameters have been provided to drillers in time. The field performance showed about 20% of ROP improvement with the recommended parameters along the horizontal section, and a 3,100-m horizontal section has been achieved.
 Machine learning algorithms were applied to drilling parameter recommendations with lower manual intervention. The novel workflow is not limited to bit type, downhole tools, rig equipment, etc. It has shown an outstanding drilling improvement in complex unconventional gas wells, which led the conventional drilling process to the automated era.

Wen-Pin Liu

Papers

The cracking mechanism of silicon particles in an A357 aluminum alloy

Adaptive single-mode variational mode decomposition and its applications in wheelset bearing fault diagnosis

A new fault diagnosis method for wheelset-bearing system based on VME convergence tendency diagram

Study on the Damage Mechanism of Bank Slope-Bridge Pile Foundation Interaction under Reservoir Water Level Cycle

Maximising Drilling Rates with Real-Time Data-Driven Drilling Parameters Optimisation