Applied Mechanics and Materials Vols. 764-765

Abstract: The ANFIS algorithm was first applied to calibration modeling of the multi-hole pitot tube in this study. Owing to its capability of efficient learning, easy implementation and excellent explanation through fuzzy rules, ANFIS can help identify the dominant parameters and construct fuzzy learning system. After determination of the ANFIS structure from the calibration data, the network of pitot tube calibration parameters was established and the correlation among non-dimensional pressure coefficients, flow angle and flow velocity were constructed as well. Meanwhile, the air velocity can be predicted based on the measurements of flow angles and flow angle coefficients. It can reach to a high consistency of 0.0068 with the original data after iteration. Eventually, ANFIS can be integrated with real-time data acquisition system and wind tunnel due to its programmability. A large database consisting of flow properties, flow angles and the non-dimensional pressure coefficients can be efficiently established and will be helpful for shortening the calibration procedures.

Abstract: This paper describes a novel device, a wet cell, used for observation in the wet environment inside the scanning electron microscope (SEM). A Wet cell is composed of three counterparts, which are flow control system, thermal system and Wet cell body. The flow system provides continuous buffer liquid to wet cell and maintains cells living at the vacuum environment. It can control different flowrates and switch to different fluidics. Additionally, the thermal system can control the temperature inside the wet cell and maintain at 37 °C. It also offers preheating thermal module to lower the fluctuated of wet cell inside temperature. The wet cell body contains a silicon nitride film based observation window and provides a wet environment for observation between vacuum and anti-vacuum status. In this paper, we introduce the structure and experimental data of flow control and thermal system in Wet cell to let SEM easily provide lots of live imaging information such as dynamics of nano-materials and biological samples in the liquid state.

Abstract: Nonlinear magneto-electric response characteristics of giant magnetostrictive-piezoelectric composite sensors in harmonic and stochastic magnetic fields were studied in this paper. Van der Pol nonlinear difference items were introduced to interpret the hysteresis phenomena of both giant magnetostrictive material and piezoelectric ceramics. The nonlinear dynamic model of giant magnetostrictive-piezoelectric composite sensors in harmonic and stochastic magnetic fields was developed. The expression of dynamic response of the system was obtained, and the bifurcation characteristics of the system were analyzed. The magneto-electric coefficient of the composite sensors was determined, and the effects of system parameters on the dynamic characteristics and magneto-electric coefficient of the system were analyzed. The simulation results show that there are stochastic Hopf bifurcation and jump phenomena of vibration amplitude in the system, and both of that can be avoided through adjusting parameters. The experimental results show that the system’s motion becomes chaotic when stochastic excitation is extremely large. The results of this paper are helpful for optimal design and improvement of giant magnetostrictive-piezoelectric composite sensors.

Abstract: This research proposes a wireless non-floating type thermal convection accelerometer, in which the heaters and the thermal sensors were made on the surface of a flexible substrate with a stacking material (such as aluminum nitride with thickness 1mm), this new device is different from those of the traditional floating structures with a grooved chamber in the silicon substrate. Thus one can integrate both a thermal convection accelerometer and a wireless RFID antenna on the same substrate, and this accelerometer is a wireless one and very convenient for fabrication and usage. Besides, the filling gas was changed as xenon to avoid the oxidizing effect that will be produced by the previously used CO₂ or air. Thus not only the reliability but the life cycle of the heater can be increased. The performances by using the traditional rectangular chamber for either xenon or CO₂ without stacking material had nonlinear effects. But the cases by using a stacking layer and xenon gas are always better. Comparisons with the previous accelerometer with rectangular chamber, stacking material and filled by CO₂ are also made (with sensitivity 0.182°C/G), the sensitivity for the new one with hemi-cylindrical chamber, xenon gas and stacking material is better (0.227°C/G) and without nonlinear effect in larger accelerations. The new device can be used in the applications of air bags and munition industry.

Abstract: Moodle is one of the most popular Learning Management System (LMS) in the world. However, this kind of system always suffer the burden of large amount of user connections in a short period of time, such that the front end web servers and the rear end database servers became the bottleneck of the whole system. In the LMS system, the most challenges are to provide the rapid response, the system stability, the system flexibility, the system scalability, and the fault tolerance. Currently, the problems of system overloading are solved by the load balancing scheme, which still have a lot of limitations. In this paper, the proposed scheme, based on the load balancing scheme, combines the mercy of Moodle network scheme and the separate of database in order to improve the performance both on the level of systems and applications for the situation of large amount users. From the performance evaluation, the proposed scheme is superior to the existing system model.

Abstract: For most traffic engineering studies, traffic flows are usually analyzed and evaluated on hourly basis. However few studies have been performed that estimate the number of traffic volumes made to an airport as a function of air passengers by time of day. The objective of this paper is to develop a mathematical model which forecasts hourly traffic volume by using hourly airport operation data along with airport user characteristics data. An analytical model was developed. This model can be used to (1) predict the number of vehicles queued at airport entrances intersection or toll plaza, (2) predict optimum toll lane staffing, and (3) analyze the level of congestion on the roadway for different levels of air passenger demand in future.

Abstract: This paper addressed a new lane departure warning system (LDWS). We used the side-view cameras to promote Advanced Driver Assistance Systems (ADAS). A left side-view camera detected the right lane next to vehicle, and a right side-view camera detected the right lane. Two cameras processed in their algorithm and gave warning message, independently and separately. Our algorithm combined those warning messages to analyze environment situations. At the end, we used the LUXGEN MPV to test and showed results of verifications and tests.

Abstract: Identifying hazardous locations on highways is an essential step for safety improvement programs and projects since it provides decision makers with a logical and scientific basis for the allocation of resources in a cost-effective manner. There have been numerous studies conducted to develop suitable methodologies for identifying hazardous locations; however, most of them have not considered spatial interactions which are inherent in traffic accidents. In this paper, we use the GIS-based geographically weighted regression (GWR) that can model crash outcomes and identify hazardous locations on expressways while reflecting the effect of spatial dependency and heterogeneity on the outbreak of traffic accidents. This method has been applied to a case study at Gyeongbu Expressway in Korea with 3-year crash data. Koenker's studentized Bruesch-Pagan and Moran’s I tests confirm the spatial relationship among crash data. The findings indicate that it is proper to model crash frequency with GWR for identifying hazardous locations.

Abstract: Elevators are the essential transportation tools in high buildings so that Elevator Group Control System (EGCS) is developed to dynamically layout the schedule of elevators in a group. In this study, a fuzzy cognitive map (FCM) based computation approach by using particle swarm optimization (PSO) has been applied for estimating the minimum required elevators in EGCS so as to minimize the power consumption with predefined service quality. In literature, most of the studies were mostly focused on the scheduling strategy in order to have more efficient elevator dispatching or energy saving. However, the minimum numbers of elevators should be activated to sustain the required service quality. In other words, the maximum average waiting time for customers should be less than the predefined length of time while the minimum numbers of elevators are working in EGCS. The experimental results show that the performance of the proposed FCM based approach is feasible to estimate the required power consumption and average waiting time so as to decide the optimal numbers of elevators in EGCS.

Abstract: This paper aims at presenting a simple approach utilizing a Kinect-based scanner to create models available for 3D printing or other digital manufacturing machines. The outputs of Kinect-based scanners are a depth map and they usually need complicated computational processes to prepare them ready for a digital fabrication. The necessary processes include noise filtering, point cloud alignment and surface reconstruction. Each process may require several functions and algorithms to accomplish these specific tasks. For instance, the Iterative Closest Point (ICP) is frequently used in a 3D registration and the bilateral filter is often used in a noise point filtering process. This paper attempts to develop a simple Kinect-based scanner and its specific modeling approach without involving the above complicated processes.The developed scanner consists of an ASUS’s Xtion Pro and rotation table. A set of organized point cloud can be generated by the scanner. Those organized point clouds can be aligned precisely by a simple transformation matrix instead of the ICP. The surface quality of raw point clouds captured by Kinect are usually rough. For this drawback, this paper introduces a solution to obtain a smooth surface model. Inaddition, those processes have been efficiently developed by free open libraries, VTK, Point Cloud Library and OpenNI.