3-D Design Method of Gear Cutting Tool Profile Base...

Jo Aug 29, 2025

Cutting tools have a decisive influence on the quality of machined parts and the efficiency of machining. Especially, the precision of cutting tools often leads to the precision of the gear class components.

There are two gear cutting methods; by forming and by generation. Because the gear cutting by forming has low machining accuracy and productivity, the gear cutting by generation is in common use. For gear generating, cutting tools such as a hob and a gear shaper cutter should be designed and manufactured precisely enough to increase the machining accuracy of gears.

The profile of a gear cutter is determined by the envelope equation of the instantaneous trajectory of the gear tooth profile. Therefore, the profile of the cutter can be determined only on the condition that the profile equation of the gear tooth to be machined is known. If the gear tooth profile is given as the measurement data or is a complex transcendental function, it is impossible to determine the profile of the cutter.

Choe Myong Chol, an institute head at the Faculty of Mechanical Science and Technology, has proposed a new method for 3D design of the toothed tool profile from the measurement data of a sample gear without any complex calculations in the way of reverse engineering.

This method can be applied to all generating cutters ranging from 2D to 3D tools.

For further details, please refer to his paper “3-D Design Method of the Gear Cutting Tool Profile Based on Reverse Engineering” in “Transactions of the Indian National Academy of Engineering” (SCI).

Performance of Steam-treated SAPO-18

Jo Aug 28, 2025

Silicoaluminophosphate (SAPO) molecular sieves have opened new perspectives in the conversion process of dimethyl ether to olefins (DTO) and recently, SAPO-18 catalysts with enhanced stability have been reported as catalysts for DTO reactions.

SAPO-18 is a microporous crystal of the AEI-type framework, in which only dimethyl ether (DME), light olefins and linear hydrocarbons can pass through the pores, while aromatic intermediates formed inside the pores cannot. This leads to coke deposition by the growth of aromatic intermediates during reactions, and the deposited coke blocks the pore entrance of the catalyst, leading to deactivation.

Therefore, it is necessary to improve the performance of catalysts that can delay their deactivation in the DTO reaction using the SAPO-18 catalyst.

Ho Yu Gyong, a researcher at the Institute of Nano Science and Technology, has steam-treated the hydrothermally synthesized SAPO-18 catalyst to investigate the catalytic performance in dimethyl ether to olefins (DTO) reactions.

After steam treatment, micropores and mesopores were created on the SAPO-18 catalyst.

To evaluate the catalytic activity of steamed SAPO-18, she carried out a DTO reaction at 673K with weight hourly space velocity (WHSV) of 3.546h^-1. The result showed that the steamed SAPO-18 (S-773) steamed at 773K exhibited excellent DTO conversion performance.

You can find the details in her paper “Steam-treated SAPO-18 with well-regulated acidity and excellent DTO performance” in “Journal of the Indian Chemical Society” (SCI).

Efficient Scheduling Scheme for Semi-On-Demand Char...

Jo Aug 27, 2025

In a wireless rechargeable sensor network (WRSN), energy supply to the sensor nodes is performed by a wireless charging vehicle (WCV). Due to charging capability constraint such as WCV’s battery capacity, however, determining an efficient order in which sensor nodes should be charged, is a challenging problem to be solved. It means it is necessary to improve charging efficiency by making an effective use of charging capability of wireless charging vehicles (WCVs).

Proactive charging-enabled on-demand charging scheme (semi-on-demand charging scheme) has been developed to solve this problem. While replying to on-demand charging requests (CRs) preferentially, semi-on-demand charging (SoC) scheme includes proactive charging for the potential Bottleneck Nodes (pBNs), although sensor nodes do not generate CRs, so long as WCV has redundant capability.

The existing scheme, however, not only fails to exactly predict the pBNs owing to the use of a fixed deadline threshold, but also selects the proactive charging nodes randomly among the predicted pBNs, thus leaving space for further improving charging and network performance.

In order to solve this problem, Jong Nam Jun, a student at the Faculty of Communications, has proposed a new SoC scheduling algorithm using FAHP-VWA and Q-Learning, with the help of Ri Man Gun, an institute head of the same faculty.

The extensive simulations demonstrated that the proposed algorithm can improve the whole charging and network performance, in comparison to other existing schemes.

For more information, you can refer to his paper “An Efficient Scheduling Scheme for Semi-On-Demand Charging in Wireless Rechargeable Sensor Networks” in “Iranian Journal of Science and Technology, Transactions of Electrical Engineering” (SCI).