Simple Breaker Index Formula Using Linear Model

Breaking waves generated by wave shoaling in coastal areas have a close relationship with various physical phenomena in coastal regions. Therefore, it is crucial to accurately predict breaker indexes such as breaking wave height and breaking depth when designing coastal structures. Many studies on wave breaking have been carried out, and many experimental data have been documented. Representative studies on wave breaking provide many empirical formulas for the prediction of breaking index, mainly through hydraulic model experiments. However, the existing empirical formulas for breaking index determine the coefficients of the assumed equation through statistical analysis of data under the assumption of a specific equation. This study presents an alternative method to estimate breaker index using representative linear-based supervised machine learning algorithms that show high predictive performance in various research fields related to regression or classification problems. Based on the used machine learning methods, a new simple linear equation for the prediction of breaker index is presented. The newly proposed breaker index formula showed similar predictive performance compared to the existing empirical formula, although it was a simple linear equation.

Evaluation of TEM specimen quality prepared by focused ion beam using symmetry breaking index of convergent-beam electron diffraction

Degradation of the crystalline quality of transmission electron microscopy specimens in silicon prepared with different conditions has been examined using convergent-beam electron diffraction (CBED). The specimens are prepared using focused ion beam (FIB) with different accelerating voltages, Ar-ion milling and crushing method. Symmetry breaking of CBED patterns was quantitatively evaluated by symmetry breaking index S, which has been previously reported. The degradation and inhomogeneity of the FIB specimen were suppressed by decreasing the accelerating voltages of the FIB fabrication in the final process.

Optimization of Basecutter Structural Parameters for Under-the-Ground Sugarcane Basecutting

HighlightsAn under-the-ground basecutting mode was employed, which is different from the typical above-the-ground basecutting mode.A series of field experiments were carried out using the response surface methodology (RSM).The complicated effect of critical parameters on three indicators (stubble breaking index, stubble uprooting index, and power consumption) was explored.The optimal values of critical parameters were determined using a multi-objective optimization method.Abstract. Basecutting is an important process in mechanical sugarcane harvesting, thus, it’s necessary to develop a high-efficient basecutter. The previous research about basecutting has mainly focused on the above-the-ground basecutting instead of under-the-ground basecutting. Therefore, the objective of this study was to analyze how the critical structural parameters, such as blade number (BN), oblique angle and bevel angle of blades (OA, BA), affect the cutting performance of a sugarcane harvester with an under-the-ground basecutting mode. A series of field tests were carried out using Liugong sugarcane harvester. The experimental indexes were determined as stubble breaking index (BI), stubble uprooting index (UI), and power consumption (PC). The ANOVA results indicated that three regression models of indicators were significant, and were in agreement with the test data. Additionally, it was concluded that OA and BN were the two most important factors when optimizing BI, UI, and PC. BA was the last factor to be considered although it had significant effect on BI and UI. The multi-objective optimization results showed that the optimal parameter combination was 3 of BN, 10° of OA, and 20° of BA, and the corresponding BI, UI, and PC reached the minimum. For sugarcane growers, reduced stubble damage and power consumption could increase the sugarcane germination and decrease the harvesting cost, respectively. For sugarcane mills, this cutting mode might cause potential decrease in sugar quality, specifically sediment levels. However, this disadvantage could be overcome by optimizing basecutter parameters. Keywords: Basecutter, Cutting mode, Power consumption, Stubble breaking, Stubble uprooting, Under-the-ground basecutting.