Position-varying surface roughness prediction method considering compensated acceleration in milling of thin-walled workpiece

Machined surface roughness will affect parts’ service performance. Thus, predicting it in the machining is important to avoid rejects. Surface roughness will be affected by system position dependent vibration even under constant parameter with certain toolpath processing in the finishing. Aiming at surface roughness prediction in the machining process, this paper proposes a position-varying surface roughness prediction method based on compensated acceleration by using regression analysis. To reduce the stochastic error of measuring the machined surface profile height, the surface area is repeatedly measured three times, and Pauta criterion is adopted to eliminate abnormal points. The actual vibration state at any processing position is obtained through the single-point monitoring acceleration compensation model. Seven acceleration features are extracted, and valley, which has the highest R-square proving the effectiveness of the filtering features, is selected as the input of the prediction model by mutual information coefficients. Finally, by comparing the measured and predicted surface roughness curves, they have the same trends, with the average error of 16.28% and the minimum error of 0.16%. Moreover, the prediction curve matches and agrees well with the actual surface state, which verifies the accuracy and reliability of the model.     

Effect of Ni and SAPO-34 co-additive on enhancing hydrogen storage performance of MgH2

The hydrogen storage performances of MgH₂ improved by the addition of Ni and SAPO-34 were studied in detail. The mixture of MgH₂ with Ni and SAPO-34 was a physical reaction as shown by the X-ray diffraction (XRD) results. The SAPO-34 and Ni were uniformly distributed on the surface of MgH₂. The thermodynamic and kinetic properties of 90MgH₂/5Ni/5SAPO-34 were investigated by differential scanning calorimetry (DSC) and pressure-composition-isothermal (PCI) methods. The results showed that the dehydrogenation activation energy of 90MgH₂/5Ni/5SAPO-34 decreased by 64.3 kJ/mol compared with that of MgH₂. In addition, the relationship between the value of dehydrogenation heat and hydrogen content was also investigated by in-situ calorimetry. The enthalpy value of each sample in the dehydrogenation processes were calculated by in-situ calorimetry measurement. The dehydrogenation enthalpies of as-milled MgH₂ and 90MgH₂/5Ni/5SAPO-34 were 63.2 kJ/mol H₂ and 53.6 kJ/mol H₂, respectively. Thus, the co-doping of Ni and SAPO-34 contributed significantly to decrease the thermodynamic stability and improve the hydrogen sorption kinetic properties of MgH₂.     

Nonlinear optimization strategy based on multivariate prediction capability ratios: Analytical schemes and model validation for duplex stainless steel end milling

Given the complex nature of their phenomena and interactions, industrial processes often have multiple variables of interest, usually grouped into critical-to-quality and critical-to-performance characteristics. These variables often have significant correlations, which make engineering problems multivariate. For this reason, Response Surface Methodology, coupled with multivariate techniques, has been widely used as a logical roadmap for modeling and optimization of the characteristics of interest. However, the variability and prediction capability of the numerical solutions obtained are almost always neglected, reducing the likelihood that numerical results are indeed compatible with observable process improvements. To fill this gap, this paper proposes a nonlinear multiobjective optimization strategy based on multivariate prediction capability ratios. For this, rotated Factor Analysis is used as the multivariate technique for grouping process characteristics and composing capability ratios, so that the prediction variance is taken as the natural variability of the process modeled and the expected value distances to the nadir solutions of the latent variables are taken as the allowed variability. Normal Boundary Intersection method, combined with Generalized Reduced Gradient algorithm, is used as the numerical scheme to maximize the prediction capability of Pareto optimal solutions. To illustrate the feasibility of the proposed strategy, we present a case study of end milling without cutting fluids of duplex stainless steel UNS S32205. Rotatable Central Composite Design, with three cutting parameters, was employed for data collection. Traditional multivariate and proposed approaches were compared. The results demonstrate that the proposed optimization strategy is able to provide solutions with satisfactory prediction capability for all variables analyzed, regardless of their convexities, optimization directions, and correlation structure. In addition, while critical-to-quality characteristics are more difficult to control, they have been favored by the proposed optimization regarding prediction capability, which was a desirable result.     

Corrosion of pure and milled Mg17Al12 in “model” seawater solution

The corrosion behavior of pure Mg₁₇Al₁₂ and the effect of ball milling in presence of additives (i.e. graphite (G) and magnesium chloride (MgCl₂)) are evaluated in 3.5 wt% NaCl aqueous solution using electrochemical polarization and impedance measurements. Pure Mg₁₇Al₁₂ and milled Mg₁₇Al₁₂ without additives and with MgCl₂ present an open current potential (OCP) of −1.2 V/SCE while Mg₁₇Al₁₂ + G shows a slightly higher OCP (+10% maximum). Mg₁₇Al₁₂ corrodes with low kinetics and an increase of corrosion rate for the milled Mg₁₇Al₁₂ is observed. The corrosion current densities (J_corr) derived from the Tafel plots, exhibit their corrosion reactivity as follow: Mg₁₇Al₁₂ < Mg₁₇Al₁₂ 5h < Mg₁₇Al₁₂ + G 5h < Mg₁₇Al₁₂ + MgCl₂ 5h. Electrochemical impedance spectroscopy (EIS) results are in good agreement with the measured J_corr. Randles circuit models are established for all samples to explain their surface behavior in the aqueous NaCl solution. The variation of the fitted parameters is attributed either to the effect of ball milling or to the effect of the additive. Our results are helpful in elucidating the effect of ball milling and the additives.     

大型球磨机订购（制造）设计联络中零部件结构优化的探讨

针对大型球磨机使用中存在的问题，对球磨机主要零部件结构缺陷进行分析并提出解决方案。通过设计联络，提前对球磨机主要零部件结构进行优化，消除设备缺陷。大型球磨机设计联络中对主要零部件结构进行优化，对提高球磨机的运转率有着事半功倍的作用。     

Stochastic modelling of abrasive waterjet footprints using finite element analysis

The proposal of erosion models to predict the jet footprint during abrasive waterjet machining is a key element for the development of this technology, but it is very challenging because of the inherent fluctuations of the process. This issue becomes critical when the size of the cutting systems is reduced, since the relative size of these deviations increases. The present paper considers for the first time a modelling framework capable of predicting the average shape of AWJM footprints and, of great novelty, the variability along the trench, combining finite element analysis and Monte Carlo methods, and verifying the model using different feed speeds and tilt angles. For that purpose, the relevance of each random parameter, such as shape (sharpness), size and relative orientation of the abrasive particles, has been investigated through parametric studies on these variables. Multiple particle simulations with randomly generated input were performed to determine the effect of operating parameters in the overall variability of the jet footprint. The process was simulated using Abaqus 6.14 as multiple garnet particles hitting a target of Ti–6Al–4V at very high velocity, eroding the target by plastic deformation and material removal. The model shows successfully the influence of single particle parameters, such as the shape, on the surface variability. The results for the footprint variability show that stochastic methods are suitable to model these fluctuations, and it is also shown that this approach yields accurate estimates of the average profile after multiple jet passes with error less than 5%.     

A physically-based model for global collision avoidance in 5-axis point milling

Although 5-axis free form surface machining is commonly proposed in CAD/CAM software, several issues still need to be addressed and especially collision avoidance between the tool and the part. Indeed, advanced user skills are often required to define smooth tool axis orientations along the tool path in high speed machining. In the literature, the problem of collision avoidance is mainly treated as an iterative process based on local and global collision tests with a geometrical method. In this paper, an innovative method based on physical modeling is used to generate 5-axis collision-free smooth tool paths. In the proposed approach, the ball-end tool is considered as a rigid body moving in the 3D space on which repulsive forces, deriving from a scalar potential field attached to the check surfaces, and attractive forces are acting. A study of the check surface tessellation is carried out to ensure smooth variations of the tool axis orientation. The proposed algorithm is applied to open pocket parts such as an impeller to emphasize the effectiveness of this method to avoid collision.     

Alloying behavior and novel properties of CoCrFeNiMn high-entropy alloy fabricated by mechanical alloying and spark plasma sintering

An equiatomic CoCrFeNiMn high-entropy alloy was synthesized by mechanical alloying (MA) and spark plasma sintering (SPS). During MA, a solid solution with refined microstructure of 10 nm which consists of a FCC phase and a BCC phase was formed. After SPS consolidation, only one FCC phase can be detected in the HEA bulks. The as-sintered bulks exhibit high compressive strength of 1987 MPa. An interesting magnetic transition associated with the structure coarsening and phase transformation was observed during SPS process.     

Analysis of specific discharge rate functions in industrial scale cement grinding multi-compartment ball mills to assist ball mill modeling

Specific discharge rates in industrial scale multi-compartment cement grinding ball mills were determined using industrial scale data to assist modeling of multi-compartment ball mills. Multi-compartment ball mill model structures were proposed to estimate normalized specific discharge rate functions. Multi-compartment mills were divided into perfectly mixed mill segments to describe material transport mechanism in the mill. Specific discharge rate functions were determined by using the estimated mill hold-up for perfectly mixed mill segments at the steady state condition of the cement grinding circuits. Estimated normalized discharge rate functions were found to be different than the basic pattern observed in semi-autogenous mills due to the differences in design and operational conditions of the mills. Coarse particle accumulation was found to have a significant effect on discharge rate function pattern. Estimated normalized discharge rate functions could be used in modeling of multi-compartment ball mills.     

A specific energy-based size reduction model for batch grinding ball mill

A particle size reduction model has been developed as the first component of an upgraded ball mill model. The model is based on a specific energy-size reduction function, which calculates the particle breakage index, t₁₀, according to the size-specific energy, and then calculates the full product size distribution using the t₁₀–t_n relationships and the mass-size balance approach. The model employs an ore-specific and size-dependent breakage function, whose parameters are independently measured with a fine particle breakage characterisation device, the JKFBC. This has effectively overcome the limitation of using a default breakage appearance function for all ores in the perfect mixing ball mill model. Since the ore-specific characteristics and the machine-related specific energy parameters are mechanistically incorporated in the size reduction model, it has the capability to predict size reduction in response to changes in the ball mill feed breakage characteristics and the operation-related specific energy.