Catalytic behavior of potassium containing compounds for diesel soot combustion

Alkali doped oxides were synthesized and tested as catalysts for diesel soot combustion using a combinatorial method. It has been found that potassium shows better promotion of the catalytic activity than other alkali elements, and most of the potassium-rich oxides showed similar catalytic behaviors when catalysts and soot were mixed in a slurry. The influence of different mixing methods, including loose contact, tight contact and slurry (wet) mixing with different soot suspensions, on the catalytic behavior of some transition metal oxides, alkali metal carbonates and potassium-containing oxides were studied through thermogravimetry and XRD. The high activity of potassium-containing catalysts is found to be due to the intimate contact between soot and potassium cations caused by polar solvents. Potassium containing catalysts degraded after repeated thermal cycles due to the loss of potassium. It was also found that the addition of transition elements can inhibit the loss of potassium.     

An energy-efficient multi-objective integrated process planning and scheduling for a flexible job-shop-type remanufacturing system

This study considers an energy-efficient multi-objective integrated process planning and scheduling (IPPS) problem for the remanufacturing system (RMS) integrating parallel disassembly, flexible job-shop-type reprocessing, and parallel reassembly shops with the goal of realizing the minimization of both energy cost and completion time. The multi-objective mixed-integer programming model is first constructed with consideration of operation, sequence, and process flexibilities in the RMS for identifying this scheduling issue mathematically. An improved spider monkey optimization algorithm (ISMO) with a global criterion multi-objective method is developed to address the proposed problem. By embedding dynamic adaptive inertia weight and various local neighborhood searching strategies in ISMO, its global and local search capabilities are improved significantly. A set of simulation experiments are systematically designed and conducted for evaluating ISMO’s performance. Finally, a case study from the real-world remanufacturing scenario is adopted to assess ISMO’s ability to handle the realistic remanufacturing IPPS problem. Simulation results demonstrate ISMO’s superiority compared to other baseline algorithms when tackling the energy-aware IPPS problem regarding solution accuracy, computing speed, solution stability, and convergence behavior. Meanwhile, the case study results validate ISMO’s supremacy in solving the real-world remanufacturing IPPS problem with relatively lower energy usage and time cost.     

Traffic accidents involving fatigue driving and their extent of casualties

The rapid progress of motorization has increased the number of traffic-related casualties. Although fatigue driving is a major cause of traffic accidents, the public remains not rather aware of its potential harmfulness. Fatigue driving has been termed as a “silent killer.” Thus, a thorough study of traffic accidents and the risk factors associated with fatigue-related casualties is of utmost importance. In this study, we analyze traffic accident data for the period 2006–2010 in Guangdong Province, China. The study data were extracted from the traffic accident database of China's Public Security Department. A logistic regression model is used to assess the effect of driver characteristics, type of vehicles, road conditions, and environmental factors on fatigue-related traffic accident occurrence and severity. On the one hand, male drivers, trucks, driving during midnight to dawn, and morning rush hours are identified as risk factors of fatigue-related crashes but do not necessarily result in severe casualties. Driving at night without street-lights contributes to fatigue-related crashes and severe casualties. On the other hand, while factors such as less experienced drivers, unsafe vehicle status, slippery roads, driving at night with street-lights, and weekends do not have significant effect on fatigue-related crashes, yet accidents associated with these factors are likely to have severe casualties. The empirical results of the present study have important policy implications on the reduction of fatigue-related crashes as well as their severity.     

Guaranteed cost control analysis and iterative design for constrained Takagi–Sugeno systems

This paper presents a novel control design technique in order to obtain a guaranteed cost fuzzy controller subject to constraints on the input channel. This guaranteed cost control law is obtained via multi-parametric quadratic programming. The result is a piecewise fuzzy control law where the state partition is defined by fuzzy inequalities. The parameters of the Lyapunov function can be obtained previously using Linear Matrix Inequalities optimization.     

Improved learning of I2C distance and accelerating the neighborhood search for image classification

Image-to-class (I2C) distance is a novel measure for image classification and has successfully handled datasets with large intra-class variances. However, due to the lack of a training phase, the performance of this distance is easily affected by irrelevant local features that may hurt the classification accuracy. Besides, the success of this I2C distance relies heavily on the large number of local features in the training set, which requires expensive computation cost for classifying test images. On the other hand, if there are small number of local features in the training set, it may result in poor performance.In this paper, we propose a distance learning method to improve the classification accuracy of this I2C distance as well as two strategies for accelerating its NN search. We first propose a large margin optimization framework to learn the I2C distance function, which is modeled as a weighted combination of the distance from every local feature in an image to its nearest-neighbor (NN) in a candidate class. We learn these weights associated with local features in the training set by constraining the optimization such that the I2C distance from image to its belonging class should be less than that to any other class. We evaluate the proposed method on several publicly available image datasets and show that the performance of I2C distance for classification can significantly be improved by learning a weighted I2C distance function. To improve the computation cost, we also propose two methods based on spatial division and hubness score to accelerate the NN search, which is able to largely reduce the on-line testing time while still preserving or even achieving a better classification accuracy.     

雨天环境下高速公路交通流特性及模型研究

降雨对高速公路交通流会产生一定的影响。为量化分析不同强度降雨对高速公路交通流微观和宏观特性的影响程度,根据实际观测的高速公路交通流和降雨量数据,确定了各种降雨类型下微观交通流特性参数(如速度、车头时距、车头间距等)的分布规律;对经典的宏观交通流模型进行了对比分析,选择Van Aerde模型作为雨天环境下高速公路交通流模型,运用启发式算法对各种类型降雨下的模型参数进行了标定,并给出了不同天气下交通流量-速度关系曲线和速度-密度关系曲线。结果表明,与无雨天气相比,小雨、中雨和大雨天气下高速公路平均速度分别下降4.7%、9.8%和16.1%,通行能力分别降低10.5%、17.4%和27.1%。     

Experimental and finite element studies on hot sizing process for L-shaped composite beams

This work aims at developing a hot sizing process on composite materials to correct the profiles of composite structures during manufacture. Hot sizing experiments were carried out at 150 °C with different sizing loads and hot sizing periods for L-shaped composite beams made of carbon fiber plain-weave fabric and epoxy resin. To predict the springback in hot sizing process, a corresponding finite element simulation method was developed using stress relaxation equations determined at the same temperature. Excellent agreements between the predicted and observed results were obtained. The effects of the component thickness and 45° ply percentage on the springback rate were investigated by simulation. Springback rate in hot sizing process on composite materials ranges from 60% to 95%. In conclusion hot sizing process is proved to be a valid method for compensation for the process-induced deformation (PID) of L-shaped composite beams.     

Using computational intelligence for large scale air route networks design

Due to the rapid development of air transportation, Air Route Networks (ARNs) need to be carefully designed to improve both efficiency and safety of air traffic service. The Crossing Waypoints Location Problem (CWLP) plays a crucial role in the design of an ARN. This paper investigates this problem in the context of designing the national ARN of China. Instead of adopting the single-objective formulation established in previous research, we propose to formulate CWLP as a bi-objective optimization problem. An algorithm named Memetic Algorithm with Pull–Push operator (MAPP) is proposed to tackle it. MAPP employs the Pull–Push operator, which is specifically designed for CWLP, for local search and the Comprehensive Learning Particle Swarm Optimizer for global search. Empirical studies using real data of the current national ARN of China showed that MAPP outperformed an existing approach to CWLP as well as three well-known Multi-Objective Evolutionary Algorithms (MOEAs). Moreover, MAPP not only managed to reduce the cost of the current ARN, but also improved the airspace safety. Hence, it has been implemented as a module in the software that is currently used for ARN planning in China. The data used in our experimental studies have been made available online and can be used as a benchmark problem for research on both ARN design and evolutionary multi-objective optimization.     

Discrepancy analysis of driving performance of taxi drivers and non-professional drivers for red-light running violation and crash avoidance at intersections

Due to comfort, convenience, and flexibility, taxis have become increasingly more prevalent in China, especially in large cities. However, many violations and road crashes that occurred frequently were related to taxi drivers. This study aimed to investigate differences in driving performance between taxi drivers and non-professional drivers from the perspectives of red-light running violation and potential crash involvement based on a driving simulation experiment. Two typical scenarios were established in a driving simulator, which includes the red-light running violation scenario and the crash avoidance scenario. There were 49 participants, including 23 taxi drivers (14 males and 9 females) and 26 non-professional drivers (13 males and 13 females) recruited for this experiment. The driving simulation experiment results indicated that non-professional drivers paid more attention to red-light running violations in comparison to taxi drivers who had a higher probability of red-light running violation. Furthermore, it was found that taxi drivers were more inclined to turn the steering wheel in an attempt to avoid a potential collision and non-professional drivers had more abrupt deceleration behaviors when facing a potential crash. Moreover, the experiment results showed that taxi drivers had a smaller crash rate compared to non-professional drivers and had a better performance in terms of crash avoidance at the intersection.     

Risk appraisal of passing zones on two-lane rural highways and policy applications

Passing on two-lane rural highways is associated with risks of head-on collision resulting from unsafe completion of passing maneuvers in the opposite traffic lane. In this paper, we explore the use of time-to-collision (TTC) as a surrogate safety measure of the risk associated with passing maneuvers. Logistic regression models to predict the probability to end the passing maneuver with TTC less than 2 or 3 s-threshold were developed with the time-gap from initiation of the maneuver to arrival of the opposite vehicle (effective accepted gap), and the passing duration as explanatory variables. The data used for model estimation was collected using stationary tripod-mounted camcorders at 19 passing zones in Uganda. Results showed that passing maneuvers completed with TTC less than 3 s are unsafe and often involved sudden speed reduction, flashing headlights, and lateral shift to shoulders. Model sensitivity analysis was conducted for observed passing durations involving passenger cars or short trucks (2–3 axles), and long trucks (4–7 axles) as the passed vehicles for 3 s TTC-threshold. Three risk levels were proposed based on the probability to complete passing maneuvers with TTC less than 3 s for a range of opposite direction traffic volumes. Applications of the results for safety improvements of two-lane rural highways are also discussed.