Laser transformation hardening of a tool steel: Simulation-based parameter optimization and experimental results

2006 ◽  
Vol 200 (22-23) ◽  
pp. 6362-6367 ◽  
Author(s):  
M.J. Tobar ◽  
C. Álvarez ◽  
J.M. Amado ◽  
A. Ramil ◽  
E. Saavedra ◽  
...  
Keyword(s):  
Tool Steel ◽  
Parameter Optimization ◽  
Experimental Results ◽  
Simulation Based ◽  
Laser Transformation Hardening

scholarly journals Fault diagnosis of bearing based on relevance vector machine classifier with improved binary bat algorithm for feature selection and parameter optimization

2017 ◽  
Vol 9 (1) ◽  
pp. 168781401668529 ◽  
Author(s):  
Sheng-wei Fei
Keyword(s):  
Feature Selection ◽  
Fault Diagnosis ◽  
Parameter Optimization ◽  
Bat Algorithm ◽  
Relevance Vector Machine ◽  
Experimental Results ◽  
Machine Method ◽  
Training Samples ◽  
Kernel Parameter

In this article, fault diagnosis of bearing based on relevance vector machine classifier with improved binary bat algorithm is proposed, and the improved binary bat algorithm is used to select the appropriate features and kernel parameter of relevance vector machine. In the improved binary bat algorithm, the new velocities updating method of the bats is presented in order to ensure the decreasing of the probabilities of changing their position vectors’ elements when the position vectors’ elements of the bats are equal to the current best location’s element, and the increasing of the probabilities of changing their position vectors’ elements when the position vectors’ elements of the bats are unequal to the current best location’s element, which are helpful to strengthen the optimization ability of binary bat algorithm. The traditional relevance vector machine trained by the training samples with the unreduced features can be used to compare with the proposed improved binary bat algorithm–relevance vector machine method. The experimental results indicate that improved binary bat algorithm–relevance vector machine has a stronger fault diagnosis ability of bearing than the traditional relevance vector machine trained by the training samples with the unreduced features, and fault diagnosis of bearing based on improved binary bat algorithm–relevance vector machine is feasible.

Optimizing Dressing Conditions for Minimum Flatness Tolerance when Grinding SKD11 Tool Steel

2021 ◽  
Vol 1020 ◽  
pp. 83-90
Author(s):  
Thi Hong Tran ◽  
Tran Ngoc Giang ◽  
Ngoc Vu Ngo ◽  
Thanh Danh Bui ◽  
Thanh Tu Nguyen ◽  
...  
Keyword(s):  
Tool Steel ◽  
Feed Rate ◽  
Input Parameter ◽  
Experimental Results ◽  
Grinding Wheel ◽  
Input Parameters

This study is to determine effects of the dressing parameters to the flatness tolerance (Fl) when grinding SKD11 steel using HaiDuong grinding wheel and also propose the suitable dressing parameters to obtain the smallest flatness tolerance. In this paper, the effects of the six input parameters including feed rate (S), depth of rough dressing cut (ar), rough dressing times (nr), depth of finish dressing cut (af), finish dressing times (nf) and non-feeding dressing (nnon) to the flatness tolerance were investigated. To find out the influence of each input parameter on output results, the S/N ratio was analysized. Evaluated experimental results show that, the average flatness tolerance was 4.05μm and deviation of this value was 11.38% compared with the predicted value.

scholarly journals Experimental Analysis and Simulation of Novel Technical Textile Reinforced Composite of Banana Fibre

Materials ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1134 ◽  
Author(s):  
Mario Monzón ◽  
Rubén Paz ◽  
Martí Verdaguer ◽  
Luis Suárez ◽  
Pere Badalló ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Predictive Modelling ◽  
Experimental Results ◽  
Average Error ◽  
Acceptable Error ◽  
Simulation Based ◽  
Banana Fibre ◽  
The One ◽  
Textile Reinforced Composite ◽  
Definition Of

The use of natural fibres allows reducing environmental impact, due to their natural renewable origin and the lower energy needed for their production and processing. This work presents the mechanical characterization of a newly developed technical textile, with banana fibre treated by enzymes, comparing experimental results with numerical simulation based on the definition of the unit cell at micromechanical level. The experimental test shows that the composite with the fabric of banana fibre presents worse mechanical behaviour than the one with commercial flax fibre. The presence of wool, necessary for producing the yarn, reduces the mechanical properties of the banana textile. The numerical simulation had an acceptable error compared with the experimental results, with a global average error of 9%, showing that the predictive modelling based on the multiscale method is suitable for the design process of this kind of composite.

Efficient container stacking approach to improve handling: efficiency in Chinese rail–truck transshipment terminals

SIMULATION ◽  
2019 ◽  
Vol 96 (1) ◽  
pp. 3-15 ◽  
Author(s):  
Wang Li ◽  
Zhu Xiaoning ◽  
Xie Zhengyu
Keyword(s):  
Optimization Model ◽  
Experimental Results ◽  
Computational Experiments ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Container Stacking ◽  
Simulation Based ◽  
Allocation Preferences

An efficient container stacking approach is vital to the handling efficiency of container transshipment terminals. In this paper, by considering container allocation preferences and operation distance, the container stacking problem in rail–truck transshipment terminals has been formulated as a multi-objective optimization model to minimize container overlapping amounts and crane moving distance. A simulation-based algorithm implementing process has been developed to stack containers to the optimum positions. Computational experiments on data from a rail–truck transshipment terminal in China are conducted to test the efficiency of the proposed approach. Experimental results demonstrate that the container stacking approach is efficient and significant for improving handling efficiency in rail–truck transshipment terminals.

Study of the Non-Dominated Sorting Genetic Algorithm for the Optimal Structural Parameter of the Tooth-Arrangement Multi-Fingered Dextrous Hand

2013 ◽  
Vol 756-759 ◽  
pp. 4082-4089
Author(s):  
Zhan Li Li ◽  
Xiang Ting He
Keyword(s):  
Genetic Algorithm ◽  
Parameter Optimization ◽  
Experimental Results ◽  
Structural Parameter ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Multi Objective ◽  
Dextrous Hand

Firstly, the structural parameter optimization of the tooth-arrangement multi-fingered dextrous hand is studied. Secondly, as to the shortcomings that the Pareto solution of multi-objective optimization was distributed unevenly in NSGA-II, a non-dominated sorting genetic algorithm based on immune principle is proposed. Lastly, the structural parameter of the medical tooth-arrangement multi-fingered dextrous hand is optimized using the proposed algorithm. The experimental results show that this algorithm can optimize structural parameter of tooth-arrangement multi-fingered dextrous hand very well.

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