The Lewis number is the ratio of thermal diffusivity to molecular diffusion coefficient, and its influence on premixed-flame propagation has been a topic of extensive combustion research. Diffusive-thermal model, which neglects density variation caused by temperature increase due to combustion, has been frequently used to examine the effect of the Lewis number. Major advantages of the diffusive-thermal model are that it allows computation with a given flow field and that the sole effect of the Lewis number can be investigated. The diffusive-thermal model includes a dimensionless parameter, hereafter denoted by Λ, which corresponds to the pre-exponential factor of reaction rate constant. Its value must be determined such that the correct burning velocity can be reproduced. Although a number of studies use the lowest-order asymptotic expression for evaluating the value of Λ, the expression causes errors as much as several tens of percent depending on the condition. In this study, the value of Λ is numerically determined by seeking a traveling wave solution in a one-dimensional moving coordinate system. The method is simple enough to be implemented in Microsoft Excel using its solver add-in. It was found that even two-term asymptotic expansion of Λ resulted in errors more than 10% in some cases. It is therefore recommended to numerically evaluate the value of Λ under every condition of interest. As an alternative means, this paper proposes an empirical formula that yields the value of Λ with errors less than 1% in most cases (less than 2% in all the cases) tested in this study.
Baby carriage vibrations cause unpleasant sensations for both the babies and carriage operators. This study analyzed the baby carriage vibration generated by passing over a level difference on a road surface because this situation introduces a large physical burden and significant stress. The purpose of this study is to develop simulation models in order to improve the performances of baby carriages under operating conditions efficiently. Furthermore, experiments were conducted using a real baby carriage to verify the accuracy of the simulation models. We focused on vibrations in the front leg because characteristic vibrations were generated in this part. Baby carriage models, such as the rigid body model (modeled as a rigid body other than the elastic deformation of suspension) and the elastic connection model (modeled the movement of joints around the legs), have been developed. However, the accuracy of these models are insufficient because these are not able to model high-frequency vibrations and the trend in the vibration peaks when the baby carriage passes over the level difference. Additionally, we developed the front leg elastic body model considered the elastic deformation of front legs based on the finite segment method. In the front leg elastic body model, front legs were divided into fifths, which were connected by translational and rotational springs because the time is required for analysis using the general finite element method. This model was able to provide the trend similar to the experimental result. Finally, the vibration reduction design for a baby carriage was considered by using the developed simulation model.
A method to conserve the volume of dispersed components (e.g. bubbles and droplets) in a viscous fluid is proposed for the front-tracking method (Unverdi and Tryggvason, 1992; Tryggvason et al., 2001). The method adjusts the coordinates of each nodal points on the interface (or Lagrangian markers) along the velocity vector. A simplified algorithm determines the new position of the marker independently from those of the surrounding nodes, which allows the volume correction to be accomplished efficiently. The results show that the volume of a deformed fluid particle is kept constant within errors of O(10−7) ～ O(10−6). The effects of the time step size and the frequency of the volume correction are investigated. The method is applicable to enclosed structures of non-spherical geometry (e.g. oblate/prolate/spherical-cap fluid particles).
In a High-Temperature Gas-cooled Reactor (HTGR), radiation is the dominant form of heat transfer due to the high temperature environment. Therefore, the emissivity of the core materials (mainly nuclear grade graphite) is important for reactor safety assessment. In this paper, the emissivity of nuclear grade graphite IG-110 was measured in the temperature range from 500 °C to 1000 °C by using an infrared thermometer. Besides, the impact of the graphite oxidation, which may take place in a postulated air ingress accident, was also evaluated. As a result, it was found that the emissivity of IG-110 grade graphite decreases slightly as the temperature increase. Moreover, a relatively high emissivity was detected in the pre-oxidized specimen. Based on the measurement data, two experimental correlations were suggested for the engineering applications. It could also be concluded that the commonly used value of the graphite emissivity (0.8), is conservative for engineering judgment.
In finite element analysis, small fillets make mesh generation difficult and accurate evaluation of stress concentration at fillets requires refined meshes. Simplified analysis is often performed using a corner model where the fillets are removed. In the analysis using a corner model, mesh division becomes easier and the number of elements is reduced, which shortens the calculation time. However, the stress concentrations cannot be evaluated, and stress singularities occur at corners. We have developed a method for predicting the stress at a fillet based on the simulation of a simplified corner model and the use of a neural network. We use the stress distribution at a corner as the neural network input such that the method can be applied to arbitrary object shapes, loading, and boundary conditions. We trained and validated the neural network using simple corner and fillet models. It was shown that stress distribution at a corner can express the difference in loading conditions. In addition, we found that the method can predict stress at fillets of models that were not used for the neural network training. These results show the possibility that the method enables efficient stress concentration evaluation in finite element analysis.
In this study, we proposed a sterilization technique for cutting fluids using plasma treatment under atmospheric pressure and in-liquid and investigated the characteristics of sterilization and the fluids’ surface properties (e.g., wear resistance and wettability). The results show that the number of bacterial colonies in the fluid sterilized by atmospheric-pressure plasma and in-liquid plasma was reduced by more than 90% compared with the number in the untreated fluid. The lubricating properties of the plasma-treated cutting fluids were well improved compared with those of the untreated fluid, as determined from a comparison of the results of specific wear rate tests. The adhesive energy of the plasma-treated cutting fluids was greater than that of the untreated fluid, as revealed by the results of sliding angle measurements. However, the adhesive energy decreased over time; that is, the duration of the effect was limited. The results of this study demonstrate that the life of a cutting fluid can be prolonged by plasma treatment, with an associated improvement in the fluid’s tribological properties. This research can help reduce the frequency of maintenance required for coolants used in cutting applications.
Radioactive aerosols are strongly diffusive and migratory and thus have presented one of the greatest challenges during the decommissioning of the Fukushima Daiichi Nuclear Power Plant (NPP). Although cutting through debris underwater can suppress the generation of radioactive aerosols from pool scrubbing to some extent, the removal efficiency of bubble columns can be influenced by many factors. In this study, fine bubbles (microbubbles and nanobubbles) with large specific surface areas were introduced into a simple scrubber; nanobubbles, in particular, are known to have long residence times in water. The effects of fine bubbles on the aerosol removal efficiency during pool scrubbing were studied for TiO2 (around 100 nm) and ZrO2 (around 100 nm) aerosols. Due to the fact that TiO2 (4.23g/cm3) has similar density with CsOH (3.68g/cm3) and CsI (4.51g/cm3). On the other hand, ZrO2 was found in the fuel debris (Zirconium-Water Reaction). To clarify the effects of fine bubbles, three kinds of water were prepared (i.e., distilled water, nanobubble water, and microbubble water). As a result, the removal efficiency of fine bubbles for TiO2 aerosols decreased, while that observed for ZrO2 aerosols improved in some cases. The improved removal efficiency achieved using fine bubbles may provide a new method for suppressing the generation of radioactive aerosols in the decommissioning of the Fukushima Daiichi NPP.
The objective of this study is to quantify the influence of higher orders of expansion in the formulation of stochastic finite elements method on the linear elastic response in 2-dimensional problems with random physical parameters in the left hand side term. Neumann expansion was used to get an explicit expression of the result. Young’s modulus was considered as a random variable following normal distribution. The coefficient of variance (COV) of this input parameter ranged in this study up to 0.3 (30%), and mainly 20% of COV was analyzed. The displacement was selected as the quantity of interest. The difference in distribution function of the displacement for different orders of expansion was observed in the tail distribution. A fundamental example revealed the limitation of the applicability of first, second and third orders being approximately 3%, 12% and 20% of COV of input parameter. In the analysis of 2-phase composite material, the influence of geometrical random morphology was larger than that of physical parameter, but the latter was not negligible in the microscopic response.