双尺度二阶矩颗粒湍流模型和提升管内稠密两相流动的模拟

稠密气固两相流动是当前国际上的研究热点,常常采用将颗粒湍流模型和反映颗粒碰撞作用的动力学模型叠加的办法来构造稠密两相流动的湍流模型。但是，对颗粒湍流模型，国内外尚没有进行双尺度湍流模型的研究。该文基于将颗粒脉动分成湍流引起的大尺度脉动和颗粒间碰撞产生的小尺度脉动的概念，建立了一种新的双尺度二阶矩颗粒湍流模型，并对提升管内的稠密气固两相流动进行了模拟。所得颗粒浓度及速度分布和实验数据吻合较好，能揭示出提升管内的环-核流动结构。该模型的结果比单尺度二阶矩两相湍流模型的结果有所改进。     

Internet域内组播路由协议的分析与比较

本文主要对组播路由协议中域内组播协议部分进行了综述。首先从域内协议设计的思想出 发,分别讨论了五种现行协议的实现过程及其特性,并介绍了正在研究中的MIP协议,最后给出了几种协议 性能比较。     

Marginal quality‐based long‐term incentive mechanisms for crowd sensing

Crowd sensing is a new paradigm that leverages pervasive sensor‐equipped mobile devices to provide sensing services like forensic analysis, documenting public spaces, and collaboratively constructing statistical models. Extensive user participation is indispensable for achieving good service quality. Nowadays, most of existing mechanisms focus on guaranteeing good service quality based on instantaneous extensive user participation for crowd sensing applications. Little attention has been dedicated to maximizing long‐term service quality for crowd sensing applications due to their heterogeneous interests, preferences, selfish behaviors, and so on. To fill these gaps, a closed‐form expression of the marginal sensing data quality based on the monopoly aggregation in economics is derived in this paper. Furthermore, we design marginal quality‐based incentive mechanisms for long‐term crowd sensing applications not only to enhance extensive user participation by maximizing the expected total profits of mobile users but also to stimulate mobile users to produce high‐quality contents by applying the marginal quality. Finally, simulation results show that our mechanisms outperform the existing solutions. Copyright © 2015 John Wiley & Sons, Ltd.     

Trajectory segment selection with limited budget in mobile crowd sensing

Mobile Crowd Sensing is an emerging paradigm, in which a large number of participants are involved to complete a sensing task under a certain incentive mechanism. Hence, when the budget used to pay participants is limited, how to choose the most appropriate participants becomes a critical problem. Most of existing works aim to select a subset of participants to maximize the coverage, without considering redundancy. There are two kinds of redundancy in the existing literature, one is brought by the incomplete coverage assessment, while the other one is brought by the traditional participant selection process. Since paying for redundant data leads to budget waste, existing works cannot solve the participant selection problem commendably under limited budget. To address such issues, we first propose a coverage assessment considering both uniform coverage and maximum coverage, then design a trajectory segment selection scheme. Rather than choosing the whole trajectory of a participant, our scheme selects certain segments. Both offline and online algorithms are proposed in this paper. Two benchmarks are implemented and we carry out extensive experiments based on a real dataset. The evaluation results prove the effectiveness and the advantage of our algorithms in terms of the coverage quality.     

A mobile crowd sensing ecosystem enabled by CUPUS: Cloud-based publish/subscribe middleware for the Internet of Things

Mobile crowd sensing (MCS) is a novel class of mobile Internet of Things (IoT) applications for community sensing where sensors and mobile devices jointly collect and share data of interest to observe phenomena over a large geographic area. The inherent device mobility and high sensing frequency has the capacity to produce dense and rich spatiotemporal information about our environment, but also creates new challenges due to device dynamicity and energy constraints, as well as large volumes of generated raw sensor data which need to be processed and analyzed to extract useful information for end users. The paper presents an ecosystem for mobile crowd sensing which relies on the CloUd-based PUblish/Subscribe middleware (CUPUS) to acquire sensor data from mobile devices in a flexible and energy-efficient manner and to perform near real-time processing of Big Data streams. CUPUS has unique features compared to other MCS platforms: It enables management of mobile sensor resources within the cloud, supports filtering and aggregation of sensor data on mobile devices prior to its transmission into the cloud based on global data requirements, and can push information of interest from the cloud to user devices in near real-time. We present our experience with implementation and deployment of an MCS application for air quality monitoring built on top of the CUPUS middleware. Our experimental evaluation shows that CUPUS offers scalable processing performance, both on mobile devices and within the cloud, while its data propagation delay is mainly affected by transmission delay on wireless links.     

Space‐Time Warp Curve for Synthesizing Multi‐character Motions

This paper introduces a new motion‐synthesis technique for animating multiple characters. At a high level, we introduce a hub‐sub‐control‐point scheme that automatically generates many different spline curves from a user scribble. Then, each spline curve becomes a trajectory along which a 3D character moves. Based on the given curves, our algorithm synthesizes motions using a cyclic motion. In this process, space‐time warp curves, which are time‐warp curves, are embedded in the 3D environment to control the speed of the motions. Since the space‐time warp curve represents a trajectory over the time domain, it enables us to verify whether the trajectory causes any collisions between characters by simply checking whether two space‐time warp curves intersect. In addition, it is possible to edit space‐time warp curves at run time to change the speed of the characters. We use several experiments to demonstrate that the proposed algorithm can efficiently synthesize a group of character motions. Our method creates collision‐avoiding trajectories ten times faster than those created manually.     

Industrial Multi-Plug Conveying Analysis

Single-plug conveying systems have the advantage of being easy to handle and highly controllable. In industry, however, multi-plug conveying systems are the most common choice due to their high transporting capacity. In order to study a multi-plug industrial conveying system, the system parameters were varied along with the materials being conveyed. The responses obtained were compared to the single-plug laboratory system, noting differences and similarities. The pneumatic conveying system at an industrial facility consisted of a 0.01 m Schedule 10 aluminum pipe, approximately 100 m long. To measure the pressure at different points along the system, a total of seven transducers were installed, four air transducers and three flush transducers. This study also used a high-speed video camera to view the plugs as they passed through the transparent viewing port, providing more detailed information on the multi-plug conveying process. Three materials were tested at different superficial air velocities and solid mass flows. In each experiment all transducers took data with a sample rate of 1,000 Hz, giving a highly detailed overview of the conveying process. The analysis included plug velocity and plug size with respect to the superficial air velocity. The Mi model for plug-flow pressure drops was found to yield agreement with the data within ±25%. For this type of industrial operation, this agreement is considered acceptable. The visual observations recorded with the camera showed that there were conditions of stable plug formation as well as varying degrees of plug stability and integrity depending on the operational conditions.     

Analysis of the Stakeholder Engagement in the Deployment of Renewables and Smart Grid Technologies

The implementation of higher shares of renewables in a global energy mix has to be accompanied by simultaneous deployment of enabling smart grid technologies (SGTs). This combination will inevitably lead to a revolutionary change in a conventional energy system, particularly, the shifting role of consumers to prosumers. But resistance may arise from such a dramatic shift, since it is associated with high uncertainty in conjunction with increasing responsibilities of all stakeholders, the urgent need of effective control, and the development of a process. To ensure the positive influence, coherent actions of all players, and appropriate treatment of the spots of resistance, the analysis of the interplay between key stakeholders has been done. The paper introduces the framework for stakeholders' analysis, applies it on the European Union (EU) example, and provides recommendations to reduce the resistance of SGTs deployment.     

Generating a multiplicity of policies for agent steering in crowd simulation

Pedestrian steering algorithms range from completely procedural to entirely data‐driven, but the former grossly generalize across possible human behaviors and suffer computationally, whereas the latter are limited by the burden of ever‐increasing data samples. Our approach seeks the balanced middle ground by deriving a collection of machine‐learned policies based on the behavior of a procedural steering algorithm through the decomposition of the space of possible steering scenarios into steering contexts. The resulting algorithm scales well in the number of contexts, the use of new data sets to create new policies, and in the number of controlled agents as the policies become a simple evaluation of the rules asserted by the machine‐learning process. We also explore the use of synthetic data from an “oracle algorithm” that serves as an as‐needed source of samples, which can be stochastically polled for effective coverage. We observe that our approach produces pedestrian steering similar to that of the oracle steering algorithm, but with a significant performance boost. Runtime was reduced from hours under the oracle algorithm with 10 agents to on the order of 10 frames per second (FPS) with 3000 agents. We also analyze the nature of collisions in such a framework with no explicit collision avoidance. Copyright © 2014 John Wiley & Sons, Ltd.     

基于 BIM 与 Pathfinder 的楼梯间堆积物对高层住宅建筑人群疏散影响研究

高层住宅建筑发生火灾时,楼梯间作为主要逃生通道,保证其畅通性尤为重要,但楼梯间堆积物却是人群疏散的主要阻碍。利用 BIM 与 Pathfinder 软件相结合,建立应急疏散仿真模型,设定 574 名不同年龄阶段的疏散人员参与模拟,在Steering 行为模式下进行仿真,分别研究堆积物摆放面积、摆放形状及摆放位置对高层住宅建筑人群疏散时间、疏散速度及拥堵情况产生的影响,并以此为高层住宅建筑楼梯间的规范管理提供理论依据。