Mathematical properties and constraints representation for bottom-up approaches to the evaluation of GHG mitigation policies

Bottom-up models, including MARKAL, MESSAGE and AIM, are widely used when analyzing the effect of greenhouse gas (GHG) abatement policies. These bottom-up models are mostly formulated as a linear programming (LP) optimization model to find both the minimal cost combination of abatement technologies and energy flows while satisfying demands. It is not unusual that the bottom-up modeling involves a great number of technical, industrial, socioeconomic and environmental constraints. Investigating representative constraints needed for analyzing GHG abatement policies, this study proposes how to implement these constraints in bottom-up modeling.     

大跨径人行桥人致振动舒适性研究

国内对大跨径人行桥人致振动舒适性研究较少，以某大跨径人行斜拉桥为例，采用强迫振动法和全桥连续行人流荷载模型，结合德国人行桥设计指南EN03(2007)，阐述了大跨径人行桥人致振动舒适性的评价过程，并采取了在桥上安装调频质量阻尼器(TMD)系统的减振措施设计。结果表明，通过减振措施，该桥的人致振动舒适性评价从“差”提高到了“最佳”。     

客运专线无砟轨道系统设计

根据我国客运专线的工程特点,无砟轨道结构选型应遵循施工性、维护性、动力性、适应性和经济性的5个基本原则,并给出2类无砟轨道的性能.在研究确定无砟轨道设计理论和原则的基础上,建议设计轮重取静轮重的3倍、疲劳检算轮重取静轮重的1.5倍.板式无砟轨道不同弹性模量的砂浆垫层对轨下基础刚度的影响不同,建议研发新型填充层材料.合理确定无砟轨道的弹性,建议轨下基础刚度的合理范围为20～30kN·mm-1.通过定期打磨钢轨和钢轨无缝化,降低噪音;通过降低轨道刚度、提高轨道参振质量,降低线路下部结构物的振动.无砟轨道的设计寿命应为60年,为此应制定相应的维修标准和管理办法.     

Experimental study on seismic vibration control of an offshore wind turbine with TMD considering soil liquefaction effect

Wind energy is clean and sustainable. Taiwan is establishing offshore wind farms using wind turbines in the Taiwan Strait. However, these are located in an earthquake-prone area with sandy seabed conditions. To ensure their safety and reliability, the turbines’ support structure must be protected against wind, waves, and seismic loads. Tuned mass dampers (TMDs) are commonly employed to reduce structural vibrations. A TMD is more simply incorporated into turbine structures than are other energy dissipation devices. In this study, a 1:25-scale test model with a TMD was constructed and subjected to shaking table tests to experimentally simulate the dynamic behavior of a typical 5-MW wind turbine with a jacket-type support structure and pile foundation. The scaled-down wind turbine model has a nacelle without rotating blades; therefore, the aerodynamic and rotational effects due to the rotating blades were ignored in this study. A large laminar shear box filled with saturated sandy ground was used to simulate the typical seabed conditions of Taiwanese offshore wind farms. The TMD system was designed to be tuned the first-mode frequency of the test model. Two ground accelerations, selected by considering wind farm site condition and near-fault characteristics, were used for excitation in the test. The responses of the test model with and without the TMD system were compared, and the influence of soil liquefaction on the effectiveness of TMD vibration control was addressed.     

北京地铁5号线地下线减振措施现场测试与分析

为满足沿途多处敏感点的环境振动要求,北京地铁5号线采用了多种减振措施.其中地下线在一般减振、较高减振和特殊减振要求的地段分别安装了普通扣件、Ⅲ型轨道减振器扣件和钢弹簧浮置板轨道.采用高灵敏度加速度传感器,对北京地铁5号线地下线一般减振、较高减振和特殊减振地段进行了现场测试.在时域和频域内,比较了各测试断面钢轨、道床和隧...     

公轨双层高架中道路桥梁形式对轨道噪声分布影响研究

高架独立轨道交通具有建设、运营成本低的优势,但其对周边居民产生的环境噪声污染问题突出,道路与轨道双层合建高架的上层道路桥梁可起到屏蔽作用,减小由轨道交通引起的道路上部区域噪声。为分析不同道路桥梁形式对轨道噪声传播规律的影响,根据实测钢轨振动加速度,建立二维声学模型进行轨道噪声传播规律预测研究。首先采用现场噪声实测结果验证方法的准确性,然后对比分析独立双U梁轨道、空心板梁道路桥+双U梁轨道、小箱梁道路桥+双U梁轨道的噪声传播与分布规律,揭示双层高架桥梁的降噪机理。结果表明,上层道路桥改变了噪声的传播途径,在增大桥下噪声的同时可以使得一部分区域(道路桥侧上方)的噪声减小;进而,在道路以上区域,小箱梁道路桥+双U梁轨道形式相比空心板梁道路桥+双U梁轨道显著降低了噪声级,大部分降幅在6～11 dB(A)之间,最大降幅约21 dB(A);与空心板梁结构形式相比,底面凹凸不平的小箱梁结构能将声能量更好地限制在道路桥梁以下范围内,从而对道路上方区域取得更大的降噪效果。提出的噪声预测方法可为公轨合建双层高架的轨道噪声快速预测与评估提供参考,计算结果可为双层高架的道路桥梁选型提供声学性能依据。     

软弱围岩隧道抗震设防措施

隧道的抗震设防一直只注重结构的强度,而忽视了结构的变形能力和软弱围岩的抗震能力.对软弱围岩隧道震害机理和抗震设防措施的分析表明:锚杆(锚管)和围岩注浆加固措施能提高软弱围岩的抗震性;合理的结构刚度、高性能的建筑材料和高阻尼结构能改善衬砌结构适应地震位移的能力;减震层、抗震缝和预留错台能减轻震害影响.     

Light Rail Rapid Transit systems for more sustainable ground accessibility of airports

This paper investigates the potential of Light Rail Rapid Transit (LRRT) to mitigate the environmental and social burden of ground access systems of an airport. This implies, on the one hand, LRRT's capability in mitigating externalities in terms of noise, air pollution/climate change, traffic incidents/accidents and congestion of airport ground access systems and, on the other, the provision of sufficient capacity to accommodate generally increasing volumes of both air passenger and airport employee demand by connecting the airport to its core catchment area. A methodology for assessing the capability of LRRT operating as an airport ground access system is developed. This methodology consists of models to analyze and predict demand and capacity for an LRRT system and models to quantify the externalities of particular airport ground access systems as well as assessing their prospective savings thanks to the introduction of an LRRT system. The methodology is applied to a large European airport – Amsterdam Schiphol (the Netherlands) – using a ‘what-if?’ scenario approach.     

峡谷底斜拉桥抗风性能改善试验研究

采用节段模型风洞试验的方法对某峡谷底斜拉桥---西藏迫龙沟斜拉桥的抗风性能进行了改善研究。首先,借助于地形风洞试验结果获得了桥位处风攻角和风偏角大小,并确定了大桥颤振检验风速和颤振试验的风攻角范围;然后,考察了大桥原方案的颤振稳定性并通过气动措施改善了原方案的颤振性能;最后检验了施加气动措施前后大桥涡激共振特性。研究结果表明：峡谷底大跨度桥梁的设计基准高度可参照桥面高度确定,但有必要进行地形试验确定桥位处风攻角和风偏角的实际情况;迫龙沟大桥颤振稳定性出现了＆#177;3＆#176;和0＆#176;风攻角下满足要求而5＆#176;风攻角下不满足要求的现象,因此峡谷底大跨度桥梁颤振稳定性检验只进行《规范》建议的风攻角试验可能存在安全隐患;颤振性能改善措施选取时,应考虑斜风的不利影响,确保大桥有足够的颤振稳定性安全储备。     

A hybrid Bayesian Network approach to detect driver cognitive distraction

Driver cognitive distraction (e.g., hand-free cell phone conversation) can lead to unapparent, but detrimental, impairment to driving safety. Detecting cognitive distraction represents an important function for driver distraction mitigation systems. We developed a layered algorithm that integrated two data mining methods—Dynamic Bayesian Network (DBN) and supervised clustering—to detect cognitive distraction using eye movement and driving performance measures. In this study, the algorithm was trained and tested with the data collected in a simulator-based study, where drivers drove either with or without an auditory secondary task. We calculated 19 distraction indicators and defined cognitive distraction using the experimental condition (i.e., “distraction” as in the drives with the secondary task, and “no distraction” as in the drives without the secondary task). We compared the layered algorithm with previously developed DBN and Support Vector Machine (SVM) algorithms. The results showed that the layered algorithm achieved comparable prediction performance as the two alternatives. Nonetheless, the layered algorithm shortened training and prediction time compared to the original DBN because supervised clustering improved computational efficiency by reducing the number of inputs for DBNs. Moreover, the supervised clustering of the layered algorithm revealed rich information on the relationship between driver cognitive state and performance. This study demonstrates that the layered algorithm can capitalize on the best attributes of component data mining methods and can identify human cognitive state efficiently. The study also shows the value in considering the supervised clustering method as an approach to feature reduction in data mining applications.