A detailed analysis of how an urban trail system affects cyclists’ travel

Transportation specialists, urban planners, and public health officials have been steadfast in encouraging active modes of transportation over the past decades. Conventional thinking, however, suggests that providing infrastructure for cycling and walking in the form of off-street trails is critically important. An outstanding question in the literature is how one’s travel is affected by the use of such facilities and specifically, the role of distance to the trail in using such facilities. This research describes a highly detailed analysis of use along an off-street facility in Minneapolis, Minnesota, USA. The core questions addressed in this investigation aim to understand relationships between: (1) the propensity of using the trail based on distance from the trip origin and destination, and (2) how far out of their way trail users travel for the benefit of using the trail and explanatory factors for doing so. The data used in the analysis for this research was collected as a human intercept survey along a section of an off-street facility. The analysis demonstrates that a cogent distance decay pattern exists and that the decay function varies by trip purpose. Furthermore, we find that bicyclists travel, on average, 67% longer in order to include the trail facility on their route. The paper concludes by explaining how the distance decay and shortest path versus taken path analysis can aid in the planning and analysis of new trail systems.

Component Sizing of Parallel Hybrid Electric Vehicle Using Optimal Search Algorithm

In designing a parallel hybrid electric vehicle, it is essential to select the optimal capacity of power sources and the optimal gear ratio of the torque coupler. The capacity of the power sources and the gear ratio of the torque coupler should be optimized simultaneously. However, since this process is excessively time-consuming, previous studies have selected the gear ratio of the torque coupler and then selected the capacity of power source. However, this approach cannot guarantee global optimization. In this paper, a feasible region is defined to satisfy the required performance of vehicle such as maximum speed, hill-climbing. and feasible points are selected inside the feasible region. In the conventional technique, the global optimal solution is obtained by simulating all feasible points. In the optimization technique, optimal points are simulated within the feasible region using several optimal search algorithms, such as the golden section search algorithm and the hillclimbing search algorithm. And using these algorithms, the number of simulations is reduced and the capacity of the power source and the gear ratio of the torque coupler are optimized simultaneously. Finally, the validity of the component sizing results is verified by comparing the global optimal solution obtained by applying the conventional technique with the solution obtained by applying the proposed optimization technique.     

Effect of absorption layer on interior sound field of sonar dome

Using the finite element method (FEM) and boundary element method (BEM) and considering the sound absorption layer which is covered on the backing of the sonar dome, the interior field in the dome which is excited by the incident plane wave has been studied. This method is validated by comparing numerical results with that of classic elastic theory. Then the effect of parameters of the sound absorption layer on interior sound field has been analyzed. The numerical calculation results show that uniformity of interior sound pressure is improved when the backing is covered with a sound absorption layer. The thicker the layer is, or the higher the loss factor of layer is, the more uniform the sound field is.     

How much can trip chaining reduce VMT? A simplified method

Trip chaining represents a way to reduce vehicle miles traveled (VMT) that does not require people to shift away from driving private automobiles. While the existing literature on trip chaining acknowledges this potential, little has been done by way of quantifying this. This research seeks to fill this gap by using a large travel survey from the San Francisco Bay area to model the VMT generated by automobile tours as a function of tour composition (i.e., the number and type of destinations on that tour). The model results indicate that many tours involving trips chains (i.e., those tours with more than one destination) generate significantly less VMT than would occur if the destinations in these tours were split into multiple tours with single destinations. Tours that combine a work and non-work destination (which are the most common types of trip chains) particularly demonstrate potential for VMT reduction. Adding a non-work destination to a work tour is usually (depending on the specific type of destination) predicted to result in a reduction of 6–11 VMT, or about 20–30 %. Adding two non-work destinations to a work tour is usually predicted to result in a reduction of 10–22 VMT, or about 25–50 %.     

Directed proxy signature in the standard model

A directed signature is a type of signature with restricted verification ability. Directed signatures allow only a designated verifier to check the validity of the signature issued to him, and at the time of trouble or if necessary, any third party can verify the signature with the help of the signer or the designated verifier. Directed signature schemes are widely used in situations where the receiver’s privacy should be protected. Proxy signatures allow an entity to delegate its signing capability to another entity in such a way that the latter can sign message on behalf of the former when the former is not available. Proxy signature schemes have found numerous practical applications such as distributed systems and mobile agent applications. In this paper, we firstly define the notion of the directed proxy signature by combining the proxy signature and directed signature. Then, we formalize its security model and present a concrete scheme in the standard model. Finally, we use the techniques from provable security to show that the proposed scheme is unforgeable under the gap Diffie-Hellman assumption, and invisible under the decisional Diffie-Hellman assumption.     

Guaranteed Cost Iterative Learning Control for Multi-Phase Batch Processes

Batch process is a typical multi-phase process. Due to the interaction between the phases of the batch process, high precision control in a single phase cannot guarantee high precision control of the whole batch process. In order to solve this problem, the guaranteed cost iterative learning control (ILC) of multi-phase batch processes is studied in this paper. Firstly, through introducing the output error, the state error and the extended information, the multi-phase batch process is transformed into an equivalent 2D switched system which has different dimensions. In addition, under the measurable condition, the guaranteed cost iterative learning control law with extended information is designed. The proposed control law ensures not only the stability of the system but also the optimal control performance. Next, in order to study the stability of the system and the minimum running time under the condition of stable running, the multi-Lyapunov function method is used. By means of the average dwell time method, the sufficient conditions ensuring system to be exponentially stable are given in the form of linear matrix inequality (LMI). Finally, the injection molding process is taken as an example to make simulation, which shows the feasibility and effectiveness of the proposed method.     

Trade-off in optimizing energy consumption and end user quality of experience in radio access network

To reduce network access latency, network traffic volume and server load, caching capacity has been proposed as a component of evolved Node B (eNodeB) in the ratio access network (RAN). These eNodeB caches reduce transport energy consumption but lead to additional energy cost by equipping every eNodeB with caching capacity. Existing researches focus on how to minimize total energy consumption, but often ignore the trade-off between energy efficiency and end user quality of experience, which may lead to undesired network performance degradation. In this paper, for the first time, we build an energy model to formulate the problem of minimizing total energy consumption at eNodeB caches by taking a trade-off between energy efficiency and end user quality of experience. Through coordinating all the eNodeB caches in the same RAN, the proposed model can take a good balance between caching energy and transport energy consumption while also guarantee end user quality of experience. The experimental results demonstrate the effectiveness of the proposed model. Compared with the existing works, our proposal significantly reduces the energy consumption by approximately 17% while keeps superior end user quality of experience performance.     

Thermal Transport in Nanoporous Yttria-Stabilized Zirconia by Molecular Dynamics Simulation

Yttria-stabilized zirconia (YSZ) is widely used as thermal barrier coatings (TBCs) to reduce heat transfer between hot gases and metallic components in gas-turbine engines. Porous structure can generally reduce the lattice thermal conductivity of bulk material, so porous YSZ can be potentially used as TBCs with better thermal performance. In this work, we investigate the thermal conductivity of nanoporous YSZ using the nonequilibrium molecular dynamics (NEMD) simulation, and comprehensively discuss the effects of cross-sectional area, pore size, structure length, porosity, Y₂O₃ concentration and temperature on the thermal conductivity. To compare with the results of the NEMD simulation, we solve the heat diffusion equation and the gray Boltzmann transport equation (BTE) to calculate the thermal conductivity of the same porous structure. From the results, we find that the thermal conductivity of YSZ has a weak dependence on the structure length at the length range from 10 to 26 nm, which indicates that the majority of heat carriers have very short mean free path (MFP) but there exists small percentage (about 3%) of phonons with longer MFP (larger than 10 nm) contributing to the thermal conductivity. The thermal conductivity predicted by NEMD simulation is smaller than that of solving heat diffusion equation (diffusive limit) with the same porous structure. It shows that the presence of pores affects phonon scattering and further affects the thermal conductivity of nanoporous YSZ. The results agree well with the solution of gray BTE with a average MFP of 0.6 nm. The thermal conductivity of nanoporous YSZ weakly depends on the Y₂O₃ concentration and temperature, which shows the phonons with very short MFP play the major contribution to the thermal conductivity. The results help to better understand the heat transfer in porous YSZ structure and develop better TBCs.     

Coordinated collision avoidance for connected vehicles using relative kinetic energy density

Vehicular collision often leads to serious casualties and traffic congestion, and the consequences are worse for multiple-vehicle collision. Many previous works on collision avoidance have only focused on the case for two consecutive vehicles using on-board sensors, which ignored the influence on upstream traffic flow. This paper proposes a novel coordinated collision avoidance (CCA) strategy for connected vehicles, which has potential to avoid collision and smooth the braking behaviors of multiple vehicles, leading to an improvement of traffic smoothness. Specifically, model predictive control (MPC) framework is used to formulate the CCA into an optimization problem, where the objective is to minimize the total relative kinetic energy density (RKED) among connected vehicles. Monte Carlo simulations are used to demonstrate the effectiveness of proposed CCA strategy by comparison with other two strategies. Among all the three control strategies, the RKED based control strategy shows the best performance of collision avoidance, including the best crash prevention rates (99.2 % on dry asphalt road and 90.5 % on wet asphalt road) and the best control of distance headways between vehicles.     

Research on reduction of Fe<Subscript>2</Subscript>O<Subscript>3</Subscript> by biomass sawdust

The research on biomass reduction of Fe₂O₃ was carried out by using sawdust as reductant. The direct reducing agents in the biomass magnetization process were determined by comparing various biomass pyrolysis products with the reduction degree (divalent iron content in total iron), reduction temperature range and valence change of Fe₂O₃ in the reduction process. The microstructure variation of Fe₂O₃ at different stages was also analyzed by scanning electron microscopy (SEM). Nonisothermal thermogravimetric analysis (TGA) was applied to explore the thermal reduction process. The results show that the direct reducing substances in the biomass reaction with Fe₂O₃ are H₂ and bio-oil, and the reduction process can be divided into two steps: biomass pyrolyzing to release H₂ and bio-oil, and reductive volatiles reacting with Fe₂O₃. The two steps are relatively independent. The kinetic of the reduction reaction follows a first-order reaction kinetic model, with 88.99 kJ/mol activation energy and 9.55 × 10⁸ min^?1 frequency factor.