Magnetic field tuning characteristics of bimodal ultrasonic motor stator

The magnetic field tuning characteristics of an ultrasonic motor (USM) stator are discussed. The stator consists of two piezoelectric ceramic transducer (PZT) plates and one sandwiched-in Terfenol-D plate. The dimensions of the stator are carefully adjusted to specifically discuss the influence of the magnetic field on the frequency difference between the longitudinal and bending modes of the stator. The frequency difference discussed in this paper is usually small and mainly caused by uneven materials, machining errors and changes in external conditions (temperature, pre-stress or load). The longitudinal and bending modes of the stator are simultaneously excited by an external electric field to generate the elliptic motion trajectories of the driving points. A direct current (DC) magnetic field is applied to decrease the difference between the two mode frequencies of the fabricated stator. In experiments, the dependences of the two mode frequencies and their difference on DC magnetic fields are all investigated. The experimental results indicate that the difference between the longitudinal and bending mode frequencies of the PZT/Terfenol-D/PZT composite stator can be tuned by changing the intensity of the external DC magnetic field.     

Sensorimotor self-learning model based on operant conditioning for two-wheeled robot

Traditional control methods of two-wheeled robot are usually model-based and require the robot’s precise mathematic model which is hard to get. A sensorimotor self-learning model named SMM TWR is presented in this paper to handle these problems. The model consists of seven elements: the discrete learning time set, the sensory state set, the motion set, the sensorimotor mapping, the state orientation unit, the learning mechanism and the model’s entropy. The learning mechanism for SMM TWR is designed based on the theory of operant conditioning (OC), and it adjusts the sensorimotor mapping at every learning step. This helps the robot to choose motions. The leaning direction of the mechanism is decided by the state orientation unit. Simulation results show that with the sensorimotor model designed, the robot is endowed the abilities of self-learning and self-organizing, and it can learn the skills to keep itself balance through interacting with the environment.     

Compensation of pressure enthalpy effects on temperature fields for throttling of high-pressure real gas

For the pressure enthalpy of high pressure pneumatics, the computational fluid dynamics (CFD) simulation based on ideal gas assumption fails to obtain the real temperature information. Therefore, we propose a method to compensate the pressure enthalpy of throttling for CFD simulation based on ideal gas assumption. Firstly, the pressure enthalpy is calculated for the pressure range of 0.101 to 30 MPa and the temperature range of 190 to 298 K based on Soave-Redlich-Kwong (S-R-K) equation. Then, a polynomial fitting equation is applied to practical application in the above mentioned range. The basic idea of the compensation method is to convert the pressure enthalpy difference between inlet air and nodes into the compensation temperature. In the above temperature and pressure range, the compensated temperature is close to the real one, and the relative temperature drop error is below 10%. This error is mainly caused by the velocity difference of the orifice between the real and ideal gas models. Finally, this compensation method performs an icing analysis for practical high pressure slide pilot valve.     

Approximate method for reliability assessment of complex phased mission systems

Phased-mission systems (PMSs) have wide applications in engineering practices, such as manmade satellites. Certain critical parts in the system, such as cold standby, hot standby and functional standby, are designed in redundancy architecture to achieve high reliability performance. State-space models such as Markov process have been used extensively in previous studies for reliability evaluation of PMSs with dynamic behaviors. The most popular way to deal with the dynamic behaviors is Markov process, but it is well known that Markov process is limited to exponential distribution. In practice, however, the lifetime of most machinery products can follow non-exponential distributions like the Weibull distribution which cannot be handled by the Markov process. In order to solve this kind of problem, we present a semi-Markov model combined with an approximation algorithm to analyze PMS reliability subjected to non-exponential failures. Furthermore, the accuracy of the approximation algorithm is investigated by comparing to an accurate solution, and a typical PMS (attitude and orbit control system) is analyzed to demonstrate the implementation of the method.     

Design of car battery protection device based on torsion spring

In recent years, electric vehicles are developing rapidly in automotive industry. When involved in accidents, if the batteries of electric cars break, it is likely to cause a short circuit and start a fire. Aimed at this issue, a car battery protection device based on torsion spring has been designed. The car battery protection device can deform in a particular pattern in a collision accident. Impact energy of the accident is absorbed by the deformation, which can significantly reduce impact force on the batteries. Meanwhile, based on the principle of maximum energy absorption, some crucial parameters of the device can be determined. Furthermore, an impact simulation conducted on ANSYS software shows that maximum safety factors can be obtained when the material of car battery protection device is carbon steel. The analysis of “safe space” in the car battery protection device shows that the device can prevent battery damage effectively in general circumstances, which means the reliability of the device has been verified. Therefore, when applied to electric vehicles, the car battery protection device, which can prevent secondary accidents, significantly improves the vehicle security in accidents.     

Calculation of strain amplification matrix for strain invariant failure theory based on representative volume element models with periodical boundary condition

Strain invariant failure theory (SIFT) is a micro-mechanics-based failure theory for multi-scale failure analysis of composite materials originally proposed by Gosse and Christensen. In this paper, the approach for obtaining strain amplification matrix which is a key step for the execution of SIFT is improved by adopting representative volume element (RVE) finite element models considering periodical boundary condition, based on which more actual deformation mode is reflected. The deformation modes and strain data at the characteristic points of the centroid cell of multi-cell RVE model are analyzed and taken as a reference. It can be concluded that more reasonable deformation mode and relationship between the micro-mechanical and macro-mechanical strain states are obtained by employing the new model. Finally, numerical examples are provided to illustrate the determination of strain amplification factors within the RVEs considering periodical boundary condition at the characteristic points.     

Gain and noise figure analysis of Er<Superscript>3+</Superscript>-doped YAG transparent ceramic microchip amplifier

The rate equations and the power evolution equations based on excited state absorption (ESA) and cooperative upconversion (CUC) of high concentration erbium-doped yttrium aluminum garnet (YAG) transparent ceramic waveguide amplifier are set up to analyze the effects of the pump power, active ion concentration and waveguide length on the amplifier gain and noise figure (NF). The numerical analysis predicts that with a pump power of 100mW, an active ion concentration of 1.0×10²⁶ ion/m³ and a waveguide length of 3 cm, a small-signal gain of 30 dB and an NF of 5 dB can be achieved in the micro-chip amplifier.     

Strava Metro data for bicycle monitoring: a literature review

ABSTRACT

Monitoring bicycle trips is no longer limited to traditional sources, such as travel surveys and counts. Strava, a popular fitness tracker, continuously collects human movement trajectories, and its commercial data service, Strava Metro, has enriched bicycle research opportunities over the last five years. Accrued knowledge from colleagues who have already utilised Strava Metro data can be valuable for those seeking expanded monitoring options. To convey such knowledge, this paper synthesises a data overview, extensive literature review on how the data have been applied to deal with drivers’ bicycle-related issues, and implications for future work. The review results indicate that Strava Metro data have the potential—although finite—to be used to identify various travel patterns, estimate travel demand, analyse route choice, control for exposure in crash models, and assess air pollution exposure. However, several challenges, such as the under-representativeness of the general population, bias towards and away from certain groups, and lack of demographic and trip details at the individual level, prevent researchers from depending entirely on the new data source. Cross-use with other sources and validation of reliability with official data could enhance the potentiality.     

Simulation of mixed gas formation for a spray-wall complex guided LPG direct injection engine

To obtain an ultralean air-fuel ratio and to reduce engine-out NOX and HC emissions induced by the richer mixture near the spark plug, a spray and wall complex guided combustion system has been developed by utilizing the fuel characteristics of LPG. The new combustion system configuration is optimized by using a commercial CFD code, FIRE V2013, and the reliability of the system has been experimentally demonstrated by Plane Laser-Induced Fluorescence (PLIF). The mixture formation in the new combustion system under part load (2,000 rpm) is numerically simulated. With an injection timing of 40°CA BTDC, the LPG spray which is injected from two upper holes, reaches the ignition point, and the other part of the LPG spray which is injected from the bottom hole, is directed to the ignition point through the vertical vortices at the same time. At the ignition timing of about 20°CA BTDC, the two-part mixtures have been shown to form a stable and richer stratified mixture around the ignition point, and the maximum global air-fuel ratio reaches to 60: 1.     

Integrated approach to an optimal automotive timing chain system design

Ensuring engine efficiency is a crucial issue for automotive manufacturers. Several manufacturers focus on reducing the time taken to develop and introduce brand new vehicles to the market. Thus, a synergic approach including various simulations is generally adopted to achieve a development schedule and to reduce the cost of physical tests. This study involved proposing a design process that is very useful in the preliminary development stage through effective support from simulations. This type of simulation-based design process is effective in developing timing chain drives; the use of this process, based on results from multiple trials, showed improvements in performance including low friction and vibration, improved durability, and cost-effective part design when compared to conventional processes. This study proposes an integrated approach to the preliminary design of an automotive timing chain system. The approach involves structural and dynamic analyses. The details of the design process are described by using the case of a virtual engine. This study conducted and summarized a dynamic and structural analysis as well as topological optimization to describe a process to obtain optimal results. The results of this study indicated the following improvements in overall performance factors: 12.1 % improvement in transmission error, 10.1 % reduction in chain tension, 46 % reduction in tensioner arm weight, and 11 % reduction in transversal displacement.