Journal of Mechanical Science and Technology最新文献

Multilayer ceramic capacitors (MLCCs) consist of multiple ceramic layers causing vibration owing to its piezoelectric characteristics. The vibrations are transmitted to the printed circuit board (PCB), causing acoustic noise. The mounting location and direction of the MLCC are crucial factors for reducing the acoustic noise. This paper presents a novel method for determining the optimal location and direction of MLCCs to reduce the acoustic noise. The excitation force of MLCC was simplified to calculate the vibroacoustic response of the PCB efficiently. Two design variables representing the MLCC location and direction were developed, and optimization problems were defined to minimize the acoustic noise. To validate the proposed method, the optimization problems were solved for an M.2 solid-state drive model under various scenarios. The results demonstrated that, on average, the overall sound power level was reduced by 4.59 dB for a single MLCC and 6.04 dB for multiple MLCCs.

The system parameters of the braking process of a rotary eddy current brake (RECB) exhibit time-varying characteristics and alternate transformations of the heat source (HS) and non-heat source (NHS) regions of the brake disc. A full-structure equivalent thermal network model for the RECB system is established, considering its physical structure. In addition, a calculation method is proposed to update the temperature of the rotating unit with a finite stepping distance. The method employs the transient process of electromagnetic thermal coupling on the brake disc, distinguishes between the thermal processes in the HS and NHS regions of the brake disc, and simulates the temperature distribution of the entire braking system. The proposed calculation method is verified via rig tests, and the effects of brake temperature rise on braking performance are assessed. The method can be used for optimal design, heat capacity analysis, and life analysis of brakes.

Cable-driven manipulators find applications in medical care, housekeeping services, and various other scenarios. However, the flexible joints of cable-driven manipulators exhibit rigid-flexible coupling characteristics, posing challenges for their modeling and accurate control. In this paper, a cable-driven serial-parallel manipulator is analyzed, and the rigidflexible coupling characteristics and dynamic modeling of its flexible joints are studied. Based on the coupling problem between joint flexibility deformation and end motion of the manipulator, a rigid-flexible coupling dynamics model was established. Through derivation of the coupling matrix, the coupling factor was defined to characterize the influence of flexible joint deformation on end motion of the manipulator. Finally, the dynamics coupling factor was simulated, and the influence of the joint cable-wheel reduction ratio and the end load on rigid-flexible characteristics of the manipulator was revealed, which lays a theoretical basis for the accurate control of cable-driven manipulators.

This study investigates the impact of key parameters in fused deposition modeling (FDM), i.e., infill density and bed temperature, on the shape memory properties of four-dimensional (4D) printed shape memory polymer (SMP). Two thermo-mechanical programming methodologies, namely programming during printing (PDP) and programming after printing (PAP), are used to examine their effects too. Increasing the infill percentage greatly improves the ability of the material to regain its original shape. This is achieved by increasing the amount of material and minimizing gaps between layers, which helps to build up the pre-strain, which causes shape morphing. On the other hand, higher bed temperatures decrease the shape recovery by slowing down cooling, decreasing residual strain, and minimizing thermal stresses. Compared to PAP samples, PDP samples show a significant 40 % increase in shape memory index (SMI), indicating the considerable influence of FDM printing rather than post-printing programming process.

The influence of design parameters on the thermal performance of a packed bed thermocline thermal energy storage (TES) system was analyzed. Both one-dimensional (1D) and two-dimensional (2D) in-house codes were developed in MATLAB environment. The diameter of solid filler, height of storage tank, and fluid velocity were varied. The thermal performance of the system, such as discharging time, thermocline thickness, and energy efficiency was calculated. As the diameter of the solid filler and fluid velocity increased, and the height of the storage tank decreased, the discharging time decreased. As the diameter of the solid filler and the height of storage tank increased, the thermocline generally became thicker. The thermocline thickness according to the fluid velocity showed non-monotonic behavior: initially increasing and then decreasing, since it affected heat transfer coefficient, fluid-solid contact time and discharging time, which affected thermocline expansion. The 2D model exhibited higher energy efficiency than the 1D model, due to the consideration of the additional wall heating to the fluid, resulting in extended discharging time except for very low flow velocities.

A newly developed and hand layup hybrid FRP of Basalt, Glass and Kevlar-29 was considered for the characterisation of Nd: YAG laser drilling and optimisation using stochastic methods. Laser current (LC), pulse width (PW), stand-off distance (SoD), and compressed air pressure (CAP) were the laser parameters. The Box-Behnken designed laser drilling experiments were completed to characterise through hole taper angle and average overcut. The grey relational grade (GRG) of the responses was considered for optimisation using a genetic algorithm (GA), teaching learning-based optimisation (TLBO) and golden jackal optimisation (GJO). The predicted optimum setting was LC of 180 A, SoD of 1 mm and CAP of 8 kg/cm². The GA & TLBO and GJO predicted PW of 3 ms with GRG of 0.9948 and 2.625 ms with GRG of 0.9203, respectively. The experimental verification of the predicted conditions acknowledges the predicted values of the responses with acceptable errors.

Wind turbines installed in regions with high altitudes and low temperatures on winter season, ice can accumulate on the blade surfaces during operating condition. A small amount of ice accretion on the blade surface can result in several crucial issues, such as AEP (annual energy production) reduction due to degrade aerodynamic performance, and safety concerns related to ice falling down. Predicting and elucidating icing accretion phenomena under various weather conditions are significantly essential in the aspect of operating and maintenance. The primary objective of this study was to assess the impact of ice accretion on the aerodynamic characteristics of wind turbine blades CFD (computational fluid dynamics) analysis, including ice thickness and shape, under varying weather conditions. Therefore, this study focused on identifying the aerodynamic characteristics affected by ice accretion, including ice thickness and shape under various weather conditions through Fensap. Through this methodology, the presence of ice accumulation on the blade surfaces was investigated, and its adverse impact on aerodynamic performance has been assessed.

In semiconductor production processes, controlling and inspecting contamination particle defects are extremely important because even a small particle within any stage of the process can remarkably affect the quality of the final products. Particle contamination can be critically detrimental in every process, thereby reducing production yield in semiconductor processes. In this study, we investigated the correlation between the actual defect rate and the probability of contamination particle defect observed by a commercially available automated visual inspection (AVI) system in semiconductor backend processes. During mass production, we observed that contamination particles produced in a thermal process were transported to various locations and caused defects. Particles sized 45 µm were observed most frequently compared with the actual contamination particles and AVI images. To effectively detect particle defect on wafer surfaces, particles smaller than 100 µm should also be considered. The hallmark of this study is that we effectively controlled particles larger than 50 µm using our AVI equipment after the die attach approach to reduce defects in the wire bonding process in advance. We provide monitoring methods for contamination control of particles present in the thermal process on the AVI system applied in mass production processes. Finally, we suggest a plausible entrainment pathway of the contamination particles and present visual images of actual contamination particles observed using an optical microscope.

Electrical energy saving was evaluated by taking advantage of PV and ESS in a community unit. An artificial neural network (ANN) and long short-term memory (LSTM) were employed to create a predictive model for PV generation. Annual demand data for residential buildings were estimated using EnergyPlus, while data for other buildings were collected from measurements in J Energy Town, Republic of Korea. Pearson correlation coefficients identified six crucial variables for the model. Comparative analysis of 310 cases revealed that the best-performing model was an ANN with three hidden layers and nodes of 14, 13 and 11. The model satisfied ASHRAE guidelines with a CV(RMSE) of 29.1 % and NMBE of −7.14 %. Evaluating electricity consumption in the community, case B (PV generation) showed a significant 46.3 % reduction compared to case A, while case D achieved a 5 % energy savings relative to case E over the year.

When a water drop is impinged upon a superhydrophobic surface with submillimetric surface structures, unconventional impact dynamics such as pancake-like bouncing and asymmetric drop spreading can occur. However, the fabrication of such surface structures often requires an unconventional fabrication approach, which is either time-consuming or costly. In this study, we propose a simple lithography-based approach to manufacture submillimetric cone-shaped pillars over a large area by taking advantage of a unique optical property of hydrogels: a change of refractive index after UV-curing. With an additional hydrophobic nanoparticle coating, we demonstrate that such structures can be used to reduce the contact time during drop impact and induce a drop rotation during rebound. Moreover, the flexibility of hydrogels enables the transfer of surface structures to non-planar substrates.