Search

The static and dynamic characteristics of the spindle system significantly influence machining accuracy and efficiency. High static and dynamic stiffnesses and thermal stability are required for high-precision and high-efficiency machining. The dynamics of spindle systems are affected by centrifugal forces and thermal expansion in response to spindle rotation. A noncontact electromagnetic loading (EML) system has great potential for measuring spindle characteristics under rotational conditions. This study presents a state-of-the-art design and performance of the EML system, which is an improvement on the system used in previous studies. Detailed experimental design and signal processing are shown for static and dynamic performance measurements, including advanced hardware-in-the-loop simulation of the intermittent milling process using the developed EML system. Some of the representative results of each test are presented, and future research questions are discussed. [ABSTRACT FROM AUTHOR]

In the continuous mining face environment, the drum rotation speed of the continuous mining machine significantly influences dust dispersal patterns. This study utilized a dynamic mesh approach to assess the impact of four drum rotation speeds—0.5, 1.0, 1.5, and 2.0 r/s—on dust diffusion. The result shows that dust concentration in the sidewalk breathing zones at 0–30 m from the working face escalates with increasing rotation speed, with each 1.0 r/s increment in drum speed, dust concentration rises by 230.21 mg/m³ on average. The polynomial fitting curves correlating the average dust concentration in the breathing zones of continuous mining machine and shuttle car drivers to the drum's rotation speed, with respective equations Y = 543X3-1575X2+1134X+450 and Y = -442X3+1807X2-2104X+1170, and the drivers' dust concentration was lower (400–600 mg/m3) at drum speeds of 0.84–1.46 r/s. With the implementation of the on-board external spray device, achieving an average dust reduction rate of 90.62 % for total dust and 90.32 % for respiratory dust. Our research is directed towards optimizing the drum rotation speed for the operator's environment and inventing the on-board external spray device to further safeguard workers' health. • Simulation difference between dynamic and static mesh is obtained. • The optimum drum rotation speed for the driver is determined. • The simulation accuracy is improved. • Link between the drum speed and dust concentration in the breathing zone is obtained. • A spray dust removal device has been developed. [ABSTRACT FROM AUTHOR]

This work develops a novel basis-adaptive method for constructing anisotropic polynomial chaos expansions of multidimensional (vector-valued, multi-output) model responses. The adaptive basis selection is based on multivariate sensitivity analysis metrics that can be estimated by post-processing the polynomial chaos expansion and results in a common anisotropic polynomial basis for the vector-valued response. This allows the application of the method to problems with up to moderately high-dimensional model inputs (in the order of tens) and up to very high-dimensional model responses (in the order of thousands). The method is applied to different engineering test cases for surrogate modeling and uncertainty quantification, including use cases related to electric machine and power grid modeling and simulation, and is found to produce highly accurate results with comparatively low data and computational demand. • Novel basis-adaptive method for anisotropic polynomial chaos expansions of multivariate (vector-valued) model responses. • Basis adaptivity guided by multivariate sensitivity analysis metrics. • Method able to address up to moderately high-dimensional model inputs and up to very high-dimensional model responses. • Method applied to different engineering test cases for surrogate modeling and uncertainty quantification. [ABSTRACT FROM AUTHOR]

• A probabilistic risk assessment model is proposed to evaluate the impact of machining-induced residual stresses. • The residual stress dispersion is quantified using a scaling parameter. • Quantify residual stress dispersion by measurements and orthogonal cutting simulations. • Establish crack life database under varying residual stresses for efficient probability calculations. • Failure probability with compressive residual stress is lower than that without. The aero-engine disks inevitably have manufacturing-induced anomalies and machining-induced random residual stress (RS) in localized and critical areas, which cause a severe threat to the safety of the aircraft. Traditional structural design of the disks fails to establish a quantitative correlation between the machining process and the failure risk. Therefore, this paper proposes a probabilistic model considering random RS to quantify the influence of machining RS subjected to low-cycle fatigue. The RS dispersion is quantified using a scaling parameter, obtained by X-ray diffraction measurements and orthogonal cutting simulations. The crack life database under varying RSs is established for efficient probability calculations. Results show that the coefficient of variation (COV) of the RS on the same machined surface with the same processing parameters is 7.62 % in the local area and 13.74 % in the whole machined surface. The risk results show that the probability of failure (POF) considering the deterministic RS is 2–4 % lower than the POF without RS, owing to the extension of fatigue life by compressive RS. Furthermore, the POF considering the random RS is almost the same (difference <0.6 %) as the POF considering the deterministic RS because the depth of the machining RS is around 0.2 mm. The proposed method predicts the POF more accurately and is thus valuable for the safety assessment of an aero-engine titanium disk. [Display omitted] [ABSTRACT FROM AUTHOR]

Because of exclusive characteristics of Switched Reluctance Motor (SRM) particularly simple and robust structure and high reliability, it can be a good choice for many industrial applications. In terms of structure and performance principles, the Linear Switched Reluctance Motor (LSRM) is similar to rotary SRM (RSRM) and therefore their advantages are identical. The Segmental Translator Linear Switched Reluctance Motor (STLSRM) is a special type of LSRMs that can produce a higher thrust density in comparison to the simple type of LSRM. One of the most important models for predicting the characteristics of electric machines is the model based on the Magnetic Equivalent Circuit (MEC), which can be used to predict the performance characteristics of machines. Although the STLSRM has significant advantages, no MEC model has been introduced for it so far. With the aim of predicting the static and dynamic characteristics of this motor, a new analytical model based on MEC method is developed in the present paper. In addition to simplicity, the developed model has acceptable accuracy and speed. The proposed model is utilized for a three-phase STLSRM and different static and dynamic characteristics of the motor including static flux-linkage, static force, instantaneous current waveform and instantaneous thrust waveform are predicted. To validate these obtained simulation results, they are compared with those derived from the Finite Element Method (FEM). [ABSTRACT FROM AUTHOR]