A complex network perspective for characterizing urban travel demand patterns: graph theoretical analysis of large-scale origin–destination demand networks

Urban travel demand, consisting of thousands or millions of origin–destination trips, can be viewed as a large-scale weighted directed graph. The paper applies a complex network-motivated approach to understand and characterize urban travel demand patterns through analysis of statistical properties of origin–destination demand networks. We compare selected network characteristics of travel demand patterns in two cities, presenting a comparative network-theoretic analysis of Chicago and Melbourne. The proposed approach develops an interdisciplinary and quantitative framework to understand mobility characteristics in urban areas. The paper explores statistical properties of the complex weighted network of urban trips of the selected cities. We show that travel demand networks exhibit similar properties despite their differences in topography and urban structure. Results provide a quantitative characterization of the network structure of origin–destination demand in cities, suggesting that the underlying dynamical processes in travel demand networks are similar and evolved by the distribution of activities and interaction between places in cities.     

Application of fuel-saving strategies onboard high-speed passenger ships

Strategies of fuel consumption onboard ships are of one of the crucial issues in marine shipping industry. Many of the relevant authorities maritime domain gave great interesting to that issue, either through research that discussed the impact of marine fuel consumption on the environment and economy of ships or through practical experiments’ that are made by marine engine manufacturers. Over the years, many solutions have been put forward to overcome this problem while maintaining the amount of goods transported globally at the same transfer rate and ship speed. The present paper sheds light on many of the methods used currently to reach this purpose. It is explained that applying a certain fuel-saving strategy will rely on some of the factors, especially the type of ship. Mainly two methods including: shore-side power and cold out of heat strategies have been investigated regarding adaption, economic, and environmental issues in case of applying onboard high-speed passenger ships.     

Design of ferrite magnet CFSM to improve speed response of EPS system

This paper deals with the speed response characteristic of the concentrated flux synchronous motor (CFSM) using ferrite magnets for the electric power steering (EPS) system. To analyze the response characteristic of the CFSM, an analytical method using the electromechanical undamped natural frequency and damping ratio based on the transfer function is proposed. By using the method, the speed response according to the variations of the shape of the permanent magnets (PMs) and rotor core is analyzed. It was analyzed under the conditions of the constant volume of the PMs as well as the constant diameter of the rotor. By using the proposed analysis method, the improved model is desgined based on the initial model fulfilling the required specifications. Finally, the torque and speed response characteristics of two motors are simulated through the finite element analysis (FEA) and MATLAB Simulink.     

Lifting Capability and Stress Analyses of the Crane System for a Large-Sized Tactical Wrecker

A large-sized tactical wrecker is a special-purpose vehicle that lifts and tows tactical vehicles and heavy loads. It consists of a crane, a post structure, outriggers and a suitable chassis truck, and during its initial design, the structural safety and tipping stability should be preemptively examined in terms of the layout of these components. This paper proposes computer-aided engineering (CAE) methods to evaluate the maximum lifting capacity of the wrecker and the structural safety of its crane during the initial design. The analytical model for the large-sized wrecker is constructed with 236 degrees of freedom by combining the crane system developed using the ADAMS macros with the dynamic model of large chassis truck with an axle suspension. The design parameters for the wrecker model that influence the tipping stability are selected, and then the maximum lifting loads with the corresponding changes are calculated. This parametric study shows that the characteristics of the boom and the layout of the outriggers greatly affect the maximum lifting capacity. Finite element (FE) analyses of the 1st stage boom and the 3rd stage boom show the stresses under the maximum overturning moment condition are within the allowable strength.     

Ontology-based approach for legal provision retrieval

In this paper, we present an ontology-based approach for legal provision retrieval. The approach aims at assisting the man who knows little about legal knowledge to inquire appropriate provisions. Legal ontology and legal concept probability model are main functional components in our approach. Legal ontology is extracted from Chinese laws by the natural language processing (NLP) techniques. Legal concept probability model is built from corpus, and the model is used to bridge the gap between legal ontology and natural language inquiries.     

Mining evolving association rules for e-business recommendation

Association analysis is an effective data mining approach capable of unveiling interesting associations within a large dataset. Although widely adopted in e-business areas, it still has many difficulties when applied in practice. For instance, there is a mismatch between the static rules discovered and the drifting nature of the user interests, and it is difficult to detect associations from a huge volume of raw user data. This paper presents an effective approach to mine evolving association rules in order to tackle these problems. It is followed by a recommendation model based on the evolving association rules unveiled. Experimental results on an online toggery show that it can effectively unveil people’s shifting interests and make better recommendations accordingly.     

Effects of Injection Timing on Transient Performance of A Regulated Two-Stage Turbocharged Diesel Engine with Turbine Bypass Valve

The object of this paper is to reduce soot emissions under typical 5s transient conditions of constant speed and increasing torque. And effects of fuel injection timing on combustion and emissions parameters were experimentally and numerically studied in a regulated two-stage turbocharged diesel engine with a turbine bypass valve (TBV). The test results indicated that: the smaller TBV opening could improve deterioration of smoke emissions and BSFC at medium and heavy loads. Afterward, the full-stage injection timing (FSIT) strategies (delaying injection timing during the entire transient process) could reduce soot and NO_X emissions simultaneously. However, when TBV opening became larger, smoke emissions and BSFC were deteriorated gradually. Moreover, the sectional-stage injection timing (SSIT) strategies (advancing injection timing from 10 % load to a preset load and delaying injection timing from the preset load to 100 % load) could markedly reduce soot emissions by 75.8 % with TBV opening 20 %; the degradation of fuel consumption could be effectively suppressed. Finally, coupling the SSIT strategies with the TBV control strategies could significantly improve the transient performance.     

Vehicle stability control based on driver’s emergency alignment intention recognition

In this work, the reference model modification strategy for vehicle stability control based on driver's intention recognition under emergent obstacle avoidance situation was proposed. First the conflicts between the driver's emergency alignment (EA) intention and vehicle response characteristics were analyzed in critical emergent obstacle avoidance situation. Second combining steering wheel angle and its speed, the driver's EA intention was recognized. The reference model modification strategy based on steering operation index (SOI) was presented. Then a LQR model following controller with tire cornering stiffness adaption was used to generate direct yaw moment for tracking modified reference yaw rate and reference sideslip angle. Finally based on the four-in-wheel-motor-drive (FIWMD) electric vehicles (EV), double lane change and slalom tests were conducted to compare the results using modified reference model with the results using normal reference model. The experimental tests have proved the effectiveness of the reference model modification strategy based on driver's intention recognition.     

Hydraulic retarders for heavy vehicles: Analysis of fluid mechanics and computational fluid dynamics on braking torque and temperature rise

Hydraulic retarders are auxiliary braking devices that reduce the velocity of a vehicle, particularly when a vehicle is driven downhill. Such velocity reduction could reduce the potential risk caused by brake failure caused by the service brake working for a long time and the temperature of the brake shoe becomes extremely high. This paper introduces the construction of the hydraulic retarder and proposes two mathematical models for the hydraulic retarder. The first mathematical model is deduced by using fluid mechanics, which is used to analyze the mechanism of how braking torque is produced and the key factors that can influence the value of the braking torque. The second mathematical model is deduced by using thermodynamics, which is used to quantify the heat produced by the hydraulic retarder. This research emphasizes that the flow rate and the average velocity of the working fluid in the working chamber mainly determine the braking torque of the hydraulic retarder. The flow rate into and out of the working chamber determines the temperature rise of the working fluid. Computational fluid dynamics (CFD) simulations are conducted with the Reynolds-averaged Navier-Stokes (RANS) and Shear Stress Transport (SST) turbulent models. Experiments are carried out to justify the two mathematical models and the CFD simulations. The results show that the mathematical models are capable of describing the force analysis and energy conversion of the hydraulic retarder and SST is more accurate for CFD simulation and the error is within 6 %.     

Iterative Learning Control Algorithm for Feedforward Controller of EGR and VGT Systems in a CRDI Diesel Engine

The modern diesel engines equip the exhaust gas recirculation (EGR) system to suppress the NOx emissions. In addition, the variable geometric turbocharger (VGT) system is installed to improve the drivability and fuel efficiency. These EGR and VGT systems have cross-coupled behavior because they interact with the intake and the exhaust manifolds. Furthermore, the turbocharger time delay, gas flow dynamics through EGR pipe cause the nonlinearity characteristics. These nonlinear multi-input-multi-output characteristics cause the degradation of control accuracy, especially during the transient condition. In order to improve the control accuracy, this study proposes an iterative learning control (ILC) algorithm for feedforward controller of EGR and VGT systems. The feedforward controller obtains the values about EGR and VGT actuators using the previous control results in predefined transient states. The ILC algorithm consists of a PD-type learning function and a low-pass filter. The control gains of learning function are determined to guarantee the convergence of learning results. In addition, the low-pass filter is designed for robustness against plant disturbance. The proposed control algorithm was validated by engine experiment which repeated predefined transient states. The error was reduced by 15 % according to the gain. As a result, the proposed algorithm is affordable for improving the transient control performance.