Mechanical Engineering Journal
Online ISSN : 2187-9745
ISSN-L : 2187-9745
Current issue
Displaying 1-8 of 8 articles from this issue
Solid Mechanics and Materials Engineering (Original Paper)
  • Masaki WATANABE, Shinya MATSUDA
    2024 Volume 11 Issue 5 Pages 24-00203
    Published: 2024
    Released on J-STAGE: October 15, 2024
    Advance online publication: September 01, 2024
    JOURNAL OPEN ACCESS

    Structures assembled using profiles and bolts made of aluminum (Al) alloy can be recycled without dismantling, as loosening and electrical corrosion of the bolts are prevented by fastening them between homogeneous materials. However, reports on practical applications are scarce. This study analyzes the breakage of Al bolts in a structure used for an extended period in a farm growing cloud-ear mushrooms under a water-sprinkled environment. The site investigation revealed that the fracture surface of bolts was inclined and that the farm water had a weakly basic pH value. Mechanical, chemical, and crystallographic properties were measured through tensile testing, fractography, X-ray diffraction, Fourier transform infrared spectroscopy, and electron back-scatter diffraction analysis on both broken and unbroken Al bolts recovered from the site. The results showed brittle mechanical properties due to stress-corrosion cracking from aluminum hydroxide formation caused by prolonged water exposure. Failure analysis was conducted using maximum principal stress and Mises stress-failure criteria based on actual, tightening-torque values. The bolts were judged to fail based on the maximum principal-stress criterion. These findings suggest that optimizing the environment and tightening torque is crucial for the effective use of structures fastened with Al bolts.

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  • Masayuki ARAI, Kaito MASUI
    2024 Volume 11 Issue 5 Pages 24-00255
    Published: 2024
    Released on J-STAGE: October 15, 2024
    Advance online publication: September 27, 2024
    JOURNAL OPEN ACCESS

    Mathematically, the well-known heat conduction equation is a parabolic partial differential equation, which defines the temperature at a point as proportional to the difference in the average of the surrounding temperatures. Marin indicated that the associated equation assumes that heat propagates at an infinite speed, which does not satisfy Einstein's special theory of relativity. Later, Landau discovered the existence of heat waves in liquid Helium II by observing the anomalous thermal conductivity at certain temperatures. Recently, it was reported that heat waves also occur in carbon nanotubes. To eliminate such physical inconsistencies, researchers have attempted to improve the associated equation in various ways, such as by introducing a relaxation time. In this study, we focused on the heat conduction equation, in which two relaxation times were introduced by Tzou, and attempted to couple it with the dynamic thermoelastic equation so that heat and stress waves could be generated and propagated simultaneously, but at different speeds. As a simple example, a one-dimensional bar problem was investigated and solved numerically using the Laplace transform technique. The results showed that in the conventional heat conduction equation, the temperature was diffusely distributed from the heating point in the depth direction, whereas the spike-shaped compressive stress propagated at a constant speed. However, in the heat conduction equation with relaxation times, the temperature distribution has discontinuities propagating at a constant speed, confirming that the heat wave can be simulated. However, the compressive stress results showed that the thermoelastic coupling effect increased the period of stress occurrence and reduced the peak stress.

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Dynamics & Control, Robotics & Mechatronics (Original Paper)
  • Yura WATANABE, Toshihiko SHIRAISHI
    2024 Volume 11 Issue 5 Pages 24-00102
    Published: 2024
    Released on J-STAGE: October 15, 2024
    Advance online publication: August 17, 2024
    JOURNAL OPEN ACCESS

    Cartilage regenerative medicine requires time and effort to regenerate thick hyaline cartilage. In this study, we investigated the effects of mechanical vibrations on chondrocyte proliferation and cartilage matrix production to simplify the regenerative medicine procedure. Chondrocytes were harvested from the metatarsophalangeal joints of pigs. Isolated chondrocytes were cultured in a monolayer without a scaffold for up to 26 days. Mechanical vibrations at 12.5, 25, and 50 Hz of 0.5 G were applied to a culture plate. Cell morphology, cell counting, tissue staining of proteoglycan and type II collagen, and real-time reverse transcription polymerase chain reaction were performed. The target genes were type II collagen, aggrecan, SOX9, type I collagen, and fibronectin. No significant difference in cell counts was observed at any of the measurement dates. Tissue staining showed that the cultured cartilage tissue contained hyaline cartilage matrices. The 25 Hz and 0.5 G mechanical vibration significantly increased the gene expression levels of type II collagen, aggrecan, fibronectin, and type I collagen by approximately 4.4, 3.4, 3.2, and 4.8 folds, respectively, compared to the static state. This suggests that the 25 Hz and 0.5 G mechanical vibration is beneficial for cultured cartilage transplantation in a simple procedure, providing the cultured cartilage with more hyaline cartilage characteristics, higher adhesion to cartilage defects, and greater strength than in the static state. Additionally, the gene expression levels of type I and II collagens at 25 Hz were significantly higher than those at 12.5 Hz and 50 Hz under the 0.5 G mechanical vibrations. This indicates that mechanical vibrations have a frequency-dependent effect on the gene expression of type I and II collagens.

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  • Yuta KONNO, Takahiro TOMIOKA
    2024 Volume 11 Issue 5 Pages 24-00222
    Published: 2024
    Released on J-STAGE: October 15, 2024
    Advance online publication: September 10, 2024
    JOURNAL OPEN ACCESS

    Periodic structures are known to have specific frequency ranges called band gaps, where the transmission of elastic waves is suppressed. Research on band gap formation in mechanical structures has recently gained considerable attention, and there is a need for analytically versatile and cost-effective methods to address the band gap effect in various structural elements. In this paper, we investigate band gap characteristics and frequency response analysis of periodic beams using an energy method that allows for easy extension to plates and shells. In using the energy method for vibration problems with non-uniform systems like periodic structures, the selection of admissible functions becomes crucial, and the treatment of boundary and connecting conditions is also essential. This study focuses on those subjects by employing elastic beams with a periodic structure of unit cells; a unit cell consists of two parts with different structural characteristics. Since band gaps can be determined by dispersion curves, the analytical process for obtaining dispersion curves by the energy method is described in detail in this paper. Three treatments to express a unit cell and three admissible functions are tested. Calculated dispersion curves are compared with those obtained by the differential quadrature method (DQM), which is widely used in band gap research. The frequency response analysis is also carried out using the energy method and compared with the results by finite element analysis using ANSYS and experimental results, and good agreement has been demonstrated among them. No resonant peaks exist in the frequency range corresponding to the band gap in the dispersion curves for both experimental and numerical results, and this shows that the formation of the band gap in the actual periodic beam and the validity of the numerical approach using the energy method for dispersion analysis and FRF calculation of periodic beams.

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  • Kazuya YOKOTA, Masataka OGURA, Masajiro ABE
    2024 Volume 11 Issue 5 Pages 24-00228
    Published: 2024
    Released on J-STAGE: October 15, 2024
    Advance online publication: October 04, 2024
    JOURNAL OPEN ACCESS

    Physics-informed Neural Networks (PINNs) is a method for numerical simulation by introducing a loss function with respect to the governing equations into a neural network. Although PINNs has been studied for its usefulness in the field of inverse analysis, but there are few examples of PINNs applied to acoustic analysis. In this study, we report a method for identifying loss parameters in acoustic tubes using PINNs. We set the energy loss parameters within the acoustic tube as trainable parameters of the neural network. The problem of identifying the loss parameters was then formulated as an optimization problem for the neural network, and the physical properties were identified. The neural network structure used in this process was based on our previously proposed ResoNet, which is a PINNs to analyze acoustic resonance. The validity of the proposed method is evaluated by forward and inverse analysis (identification of loss parameters). The results showed that when the parameters to be identified have multiple local solutions, the parameters converge to one of these solutions, and not necessarily to the true value. However, in problem settings where there are no local solutions, the parameters can be identified with high accuracy. This method can be applied to various sound fields by simply changing the governing equations in the loss function, and is expected to have a wide range of applications.

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Computational Mechanics (Original Paper)
  • Yuhi TSUCHIYAMA, Yusuke SUNAOKA, Hiroshi OKADA, Yuto OTOGURO
    2024 Volume 11 Issue 5 Pages 24-00173
    Published: 2024
    Released on J-STAGE: October 15, 2024
    Advance online publication: September 01, 2024
    JOURNAL OPEN ACCESS

    In the present investigation, a method of overlaying models of isogeometric analysis (IGA) is proposed. We call this technique s-version IGA (S-IGA). In S-IGA, a local IGA model representing the localized features of structures such as holes, cracks, notches, etc. is superimposed on a global IGA model that represents the structure as a whole. Although IGA is known as a highly accurate analysis methodology which has a potential to replace the finite element method, building analysis models for IGA is a quite troublesome task. That is because IGA is based on B-Spline or NURBS volume represented by the multiplication of B-Spline or NURBS basis functions in three-natural coordinates for three-dimensional space. In this paper, S-IGA is proposed for the purpose of reducing analysis model generation task in IGA and is critically examined for its accuracy. Discussions are extended to a modeling of mixed mode crack problem.

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Transportation and Logistics (Original Paper)
  • Byung hyun KIM, Kakeru TAKAHASHI, Hiroshi YOSHITAKE, Tomoya MURAKI, Yo ...
    2024 Volume 11 Issue 5 Pages 24-00151
    Published: 2024
    Released on J-STAGE: October 15, 2024
    Advance online publication: September 01, 2024
    JOURNAL OPEN ACCESS

    To reduce unsafe driving among older drivers, clarifying the process and factors leading to such behaviors is essential. In this study, we proposed a method to express the process and factors leading to unsafe driving using Bayesian networks. In the proposed method, the flow leading to unsafe driving is divided into three stages: driver characteristics, driving behavior, and driving unsafeness. Driver age, various driving behaviors, traffic violation and collision risk were selected as indices of driver characteristics, driving behavior, and driving unsafeness. By organizing and layering these indices in the order of cause, behavior and result, the indices were set to align with the timeline. With the proposed structuring method, we constructed models of deceleration and intersection-passing behaviors based on the driving data of older drivers at stop-sign intersections. The results revealed that driving characteristics and environmental factors influence indices related to the position and speed at intersection entry, capturing relationships leading to violations at stop lines and collision risk with crossing vehicles at intersections. Moreover, it was confirmed through probability inference that the association shown in the structured results was identical to the known driving characteristics of older drivers. According to this result of probability inference, the validity of the proposed structuring method was confirmed.

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  • Vili MILKOVIĆ, Krešimir OSMAN, Dennis JANKOVICH
    2024 Volume 11 Issue 5 Pages 24-00070
    Published: 2024
    Released on J-STAGE: October 15, 2024
    Advance online publication: September 10, 2024
    JOURNAL OPEN ACCESS

    Railway vehicles, due to a large number of hours spent in service operation, have a high frequency of breakdowns, thus, maintenance planning can be complex and expensive. The concept of maintenance is certainly connected to the concept of reliability, and the consequences of neglect can cause enormous resources losses. This research develop tool to optimize the required stocks of spare parts / materials and required number of employees for a given level of vehicle reliability. In the first phase of the research, data for the total fleet of 216 passenger wagons divided into 36 different technical groups were structured and analyzed according to the criteria defined by domestic regulations and international standards. In the second phase, reliability dependences on resource costs for all groups were modelled with using of regression analysis and enhanced by neural networks. Furthermore, goal and constraint functions were set and optimization algorithms were used in order to obtain optimal resources depending on the given system reliability. All the results of the applied algorithms were compared. The new model in practice serve as a tool to support the management of passenger car maintenance in making strategic decisions about resource planning with regard to available financial resources or the required reliability of the entire rolling stock.

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