Almost all commuter trains in Japan are equipped with cross-flow fans in order to circulate the air in a cabin and provide beneficial cooling to passengers, especially during the hot and humid summer seasons. The purpose of this study is to propose a method for predicting the passengers’ thermal comfort in non-steady state thermal environments with airflow from cross-flow fans in commuter trains in summer. The proposed method is composed of two calculation parts: a part for calculating sensory temperature based on a human thermoregulation model applicable to non-steady state thermal environments, and a part for calculating the percentage of passengers dissatisfied with the thermal environment based on a statistical model derived from the results of experiments conducted in commuter trains in summer. In order to evaluate the thermal comfort with a cyclic wind from cross-flow fans, the proposed method converts the cyclic wind to a constant wind speed equal to the total amount of heat loss from the whole-body calculated by human thermoregulation model. Applying the proposed method to our previous research where fan-off/fan-on conditions and the congestion rates of below 100%, 120% and 180% had been performed, we examined the prediction accuracy of it. As a result, the mean absolute prediction errors of the proposed method in the congestion rates of below 100%, 120% and 180% under fan-off condition were 9.4pt, 8.2pt and 7.3pt, respectively, and those under fan-on condition were 4.5pt, 10.0pt and 13.2pt, respectively.
Real drive emissions (RDE) regulation were introduced from Euro6-d regulation. In order to achieve the regulation value of PM(Particulate Matter) emission in the RDE regulation, it is effective to install GPF(Gasoline Particulate Filter) system. To prevent GPF corruption , GPF system needs “PM emission amount estimation model” that estimates PM emission amount from direct injection gasoline engine to estimate PM corrected amount. Some models, for example packet model and map-based model, have been proposed as PM emission amount estimation model. However, these models have problems in terms of calculation load and accuracy for On-board calculation. Purpose of this research is to study On-board PM emission amount estimation model . We proposed a new model method of physical quantities that dominate PM production. Developed model uses probability density function of mixture fraction space so that mixture and fuel adhesion can be treated uniformly as a fuel distribution in cylinder. Also, variance of mixture-derived probability density function and fuel adhesion ratio are functionalized by a second-order polynomial of engine control parameters, and can be applied to multiple operating conditions. The developed model was verified by comparison with measurement data. Under 25 degC of coolant temperature(19 operation points), the estimated error was during 0% and 59% and average estimated error was 19%.
We propose a method for solving differential equations implicitly using iterative calculations in spreadsheet software. This method uses difference equations by discretizing the coordinates of the independent variables with cells of spreadsheet for analysis. Thus, the equations are embedded in the cells performing substitution of grid point. In addition, the embedded equations are solved by Newton’s method, and the iterative function of the spreadsheet software is used in the calculation. This method can be applied even when the differential equation is discretized by an implicit solution method. Therefore, it can be applied to ordinary and partial differential equations of different types. The advantages of discretization using the implicit method (high computational accuracy, large time increments) are also presented in this paper. The analysis procedure is almost the same regardless of the type of equation. In this paper, as an example, a simple differential equation was analyzed using Microsoft Excel, a typical spreadsheet software, to illustrate the method. The results are also shown by the analysis of the gas lubrication equation.
In this study, the water absorption behavior of a film adhesive for aircraft use was experimentally investigated, and the formula of weight gain of the adhesive with water immersion was proposed and evaluated, comprised of a Fickian diffusion term and a dissolution term. A gravimetric analysis by immersing the thin plate adhesive specimens in water revealed the weight of the specimens increased linearly with the square root of time in the initial phase of water absorption, and then the weight decreased after passing a peak. That means Fickian diffusion was dominant in the initial phase but was not after the initial phase, which may be caused by dissoluting the adhesive. For the purpose of considering dissolution, a Nernst-Noyes-Whitney equation was introduced, and the model of dissolvable area decreasing of specimen surfaces was considered, then those and Fick’s law of diffusion were integrated as the formula of the weight gain of the adhesive with water immersion. The proposed formula was evaluated by the least-squares fitting using experimental data. As a result, the fitting curves were almost consistent with experimental data and successfully simulated the behavior, that is, Fickian diffusion was dominant in the initial stage of water absorption, and the weight of the specimens decreased after the initial stage.
In recent years, the deterioration of many bridges built during the period of rapid economic growth has become a problem. As a solution of it, preventive measures such as visual inspections and repairs by humans have been taken, but these methods have problems in terms of cost and safety. If inspection by robots becomes possible, both of these problems will be improved and it is expected to contribute greatly to the maintenance and management of bridges. Therefore, a number of robots have been developed for the purpose of bridge inspection. The among such inspection robots, wire-driven robots, which have less risk of falling and can perform close proximity or contact inspection, are attracting attention. However, one of the problems with this type of robot is that it is difficult to place the wire under the bridge when there is a river or road underneath it, or when it is very high. Thus, in this study, a shooting device for shooting arrows with attached strings was developed to solve this problem. We then conducted a shooting experiment and confirmed that the device aimed at the target automatically and shot the arrow. In addition, we created a simulation model of an arrow with a string attached to it to obtain information such as the shooting angle of the arrow in advance. Then, the flight trajectory and horizontal flight distance of the arrows were compared between the actual and simulated data, and the consistency was confirmed.
This paper presents an improved calculation method of fatigue damage in spacecraft equipment under wideband random vibration. The method is based on principle of linear fatigue damage theory (Miner’s rule) to calculate accumulated fatigue damage, where the calculation of stress cycles is improved by more general Rice distribution instead of conventional Rayleigh distribution, which has been commonly used for decades. Examples of numerical simulation and test data of spacecraft equipment are used to demonstrate the accuracy of these two different statistical distributions and show that the generated stress of the equipment subject to wideband random vibration excitation would be filtered into a narrowband random stress response due to resonance of equipment. However, the statistical distribution of peak value of the narrowband random stress response can vary depending on the spectrum of excitation and resonance frequency and differs from the conventional Rayleigh distribution assumption. This paper, through the numerical and test examples, demonstrates that the improved method is a more feasible method which can create more accurate and less conservative accumulated fatigue damage than the conventional Rayleigh distribution.
Peristaltic crawling robots inspired by the earthworm's motion have been attracting attention as robots for working in hazardous environments or confined spaces. The peristaltic crawling robots need turning motion to move in winding piping or in spaces with obstacles. In this study, we propose a model-based motion generation method for peristaltic crawling robots to realize a turning motion suitable for the robot’s dynamics and the friction characteristics of the environment. For realizing the motion generation, a two-dimensional dynamic model is constructed by combining the robot’s kinematics and a dynamic friction model, and motion patterns are generated by applying numerical optimization based on the particle optimization method. The contributions of this study are the construction of the model that enables detailed motion analysis on two-dimensional plane and the realization of the model-based method for generating efficient turning motions and turning movements at specified angles for peristaltic crawling robots. As a result of generating the turning motions, it was confirmed that the turning angle was increased by combining the stretching and bending motion. In addition, the validities of the constructed a two-dimensional dynamic model and motion generation method were confirmed from experimental verifications.
Since the noise generated by mechanical structures affects the merchantability, it is important to predict it at the design stage. Statistical energy analysis (SEA), which solves the energy equilibrium equation between subsystems, is widely used to predict structural noise. However, due to the assumption that eigenmodes are treated statistically, SEA is limited to application in the high-frequency range with high mode density, so it is the challenge to develop vibration power flow analysis method for the low- and mid-frequency range. In this study, we propose a modal energy propagation analysis method to evaluate the vibration power flow between the eigenmodes of a subsystem. In this paper, the validity of the theory and the countermeasures to reduce the vibration by controlling the transmitted power between the eigenmodes are verified using a simple test apparatus. As a result, it was shown that the transmitted power between subsystems can be approximated by the summation of the transmitted powers of individual eigenmodes, confirming the validity of the calculation theory. In addition, it was confirmed that the mean square velocity of the subsystem can be reduced by identifying and controlling the transmitted power of individual eigenmodes using this method.
In the problem of cylinder rolling without slipping on a horizontal floor, both the cylinder and floor are generally treated as rigid bodies in normal textbooks. When the air resistance is ignored, the equation of motion has a solution with a constant velocity. However, in the real world, permanent motion does not occur. The difficulty can be solved by taking account of vertical force. Two main origins of vertical force are described. 1) Both a cylinder and a floor are not perfect circle and not perfect plane, but have uneven surfaces. The micro bumps on the surface yield small collisions in the direction perpendicular to the floor. The collisions generate rolling friction torque around the center. 2) A strong force acts on the contact part which is deformed. The high-speed deformation produces a history effect on the relationship between stress and strain, because the compressed wave in the contact part diffuses to the outside at the speed of sound. Then rolling friction torque is also generated. Both are originated by the forces perpendicular to the floor. The rolling friction torque derives velocity decrease of the cylinder. To solve the simultaneous differential equations of rotation and translation is important. This method is useful for studying rolling systems such as trains and cars.
This study describes a method for probabilistically predicting the acoustic properties of porous sound-absorbing materials. Porous materials consist of complex microstructures, and homogenization methods can predict their dynamic properties. However, it is difficult to consider the randomness of the microstructure as in actual porous materials. This randomness affects the acoustic characteristics of the sound-absorbing material. Therefore, we propose a method to consider randomness in the homogenization unit cell and calculate the probability distribution of the sound absorption characteristics. The balance of computational cost with prediction accuracy is essential in predicting stochastic behavior in the multiscale simulation. Thus, we propose a Bayesian approach to achieve both computational cost and prediction accuracy. Random variables are assumed to be the microstructure shape parameters. The product of these probability density functions and the sound absorption coefficient is integrated to calculate the probability distribution of the sound absorption coefficient. The function of the sound absorption coefficient is approximated to calculate this integral by Gaussian process regression. This integral value follows a gauss distribution, and its variance is evaluated as the correctness of the approximation of the integral value. We define this variance as an acquisition function and adaptively obtain additional sampling points where it is minimized. Then, the sound absorption coefficient is recalculated with multiscale simulation at additional points to update the approximate model. Repeating these processes allows the probability distribution to be approximated with reasonable accuracy.
This paper presents a cooperative people tracking using networked light detection and rangings (LiDARs) allocated in an environment. Each LiDAR detects people from the LiDAR-scan data using a background subtraction method and sends the people positions to the adjacent LiDARs. It estimates the people poses (positions and velocities), and the estimates are exchanged among the adjacent LiDARs. A distributed interacting-multimodel (DIMM)-based method is utilized to accurately estimate poses of people under various motion modes, such as stopping, walking, and suddenly rushing out, in a distributed manner without a central server. A global nearest neighbor (GNN)-based data asscosiation as well as a rule-based detection and track management is implemented to reduce false tracking in environments with people close to each other. The DIMM-based method works in any LiDAR network topologies, and therefore, this may provide a degree of scalability that cannot be achieved by conventional centralized interacting-multimodel (CIMM)-based method with a central server. Simulation results of people tracking by three LiDARs in an intersection environment reveal the tracking performance of the proposed DIMM-based method by comparison of conventional CIMM and Kalman filter-based methods.