养护施工总承包模式下业主与承包商的博弈分析

文章以博弈论为理论基础,分析了养护施工总承包模式下业主与总承包商的博弈关系,提出了引导双方采用合理的策略以获得最大利益及保证工程产品达到较高质量水平的博弈对策,为养护施工总承包工程的管理和施工提供方法借鉴。     

结构分割转换工法在地下空间开发中的应用及设想

为了更加快速、安全、高效地完成城市地下空间开发,以结构分割转换工法（CC工法）为研究内容,从工法内涵、工程实践和应用推广3个角度展开研究。首先,基于ＣＣ工法的最新研究成果,从结构分割、建造方案及节点处理3个方面详细介绍CC工法的核心内容;然后,结合工程实践对该工法进行验证性研究,重点比较跨中设缝与柱顶设缝方案的优缺点,介绍该工程地下结构分割、转换的过程,最终证实CC工法建造地下空间的合理性、灵活性及适用性;最后,进行CC工法在富水地层中应用的可行性研究,通过对CC工法与明挖法、暗挖法、型钢混凝土、地面预制装配式结构等技术进行结合应用研究,得出在特定的工程条件下,CC工法也具有与其他先进工法结合应用的价值。     

凿岩台车臂定位系统与液压臂结构不匹配问题研究

为解决凿岩台车臂定位系统与液压臂结构不匹配而出现液压臂下降时抖动、平动速度慢、泵压过高等问题,系统分析液压臂下降时抖动的原因,指出液压臂下降时抖动是由于液压臂下部液压缸平衡阀的先导油源压力不稳引起的,并通过试验证实,如果下降过程中下部液压缸平衡阀的先导油源压力一直大于其开启压力,液压臂能够平缓下降。可以通过提高液压臂油源压力和增大下部液压缸回油背压来解决液压臂下降抖动问题。     

卵石层小净距隧道关键参数研究

针对卵石地层小净距隧道围岩整体性与稳定性差、施工中易坍塌、围岩相互扰动大的问题,通过FLAC 3D数值模拟和现场监测,对卵石层小净距隧道左右洞合理净距和先后行洞掌子面安全纵向间距进行了研究。得到如下结论： 1）当净距不大于6 m时,隧道地表沉降槽呈“V形”,沉降最大点位于中夹岩顶部;随着净距大于6 m,隧道拱顶部位地表沉降逐渐超过中夹岩顶部,地表沉降槽呈 “W形”。2）当2洞间净距不大于6 m（约1倍洞跨）时,2洞开挖后围岩压力叠加效应明显,极易发生失稳;当隧道净距大于18 m时,可按分离式隧道进行设计; 3）随着先后行洞间掌子面纵向距离的增加,后行洞施工对先行洞的影响逐渐减少,当纵向间距达到30 m（4.6倍洞跨）时,这种影响基本可以不予考虑。     

基于气动效应的特长隧道断面优化探讨

铁路隧道净空面积的确定,不仅应考虑隧道建筑限界和机车车辆限界,还要考虑列车通过隧道时诱发的空气动力学效应。基于一维、可压缩、非定常的流动假设,推导得到车内瞬变压力、洞口微气压波和空气阻力计算公式,并结合这3个指标对现有城际铁路、高速铁路隧道设计规范进行论证和优化。结果表明： 针对大于10 km的特长隧道,在一定长度范围内,且在提高列车密封水平、增加洞口微气压波缓冲结构的情况下,可对特长隧道净空断面进行优化。     

地下叠合墙接触面形式的设计研究

为解决地下工程中叠合结构接触面采用常规凿毛等方式进行预处理时存在的施工难度大、剪力槽设置参差不齐等难题,提出一种便于施工的预制叠合结构形式,然后运用ANSYS有限元软件对波浪形、三角形以及梯形波纹结构面进行受力对比分析,结果表明梯形结构面在结构应力、接触面压力以及接触面滑移方面更有优势,并确定梯形结构面作为静力荷载试验方案。通过静力荷载试验对比分析整体现浇梁和梯形结构面叠合梁在各级荷载作用下的挠度、水平位移以及裂缝开展形态,结合实测数据表明： 在受到相同荷载作用下,叠合梁的挠度增量小于整体现浇梁,同时叠合梁在裂缝开展阶段存在停滞现象,能够减缓裂缝穿过叠合面,从而提高结构的整体承载力。     

大型地下空间的结构分割转换工法研究

为解决当下地下空间开发难题,依托中铁工程装备集团地下停车场项目,提出建造大型地下空间的结构分割转换工法（CC工法）,并成功应用。文章从传统各工法的特点出发,阐述CC工法的设想。基于工程实践过程,首先,从地下结构的分割与转换2个角度,重点介绍大型地下空间的形成过程、型钢和钢筋混凝土组合结构管节、节点处理措施等创新内容; 然后,针对B类节点的处理措施、整体背土现象等工程问题进行解决与优化; 最后,探讨该工法拓展应用的可能性,分别介绍多层、曲线、长距离、装配式结构大型地下空间的初步方案。CC工法的成功研发,旨在为城市大型地下空间开发提供一套新的解决思路。     

Incorporating the extended theory of planned behavior in a school travel mode choice model: a case study of Shaoxing,China

Travel to and from school can have social, economic, and environmental implications for students and their parents. Therefore, understanding school travel mode choice behavior is essential to find policy-oriented approaches to optimizing school travel mode share. Recent research suggests that psychological factors of parents play a significant role in school travel mode choice behavior and the Multiple Indicators and Multiple Causes (MIMIC) model has been used to test the effect of psychological constructs on mode choice behavior. However, little research has used a systematic framework of behavioral theory to organize these psychological factors and investigate their internal relationships. This paper proposes an extended theory of planned behavior (ETPB) to delve into the psychological factors caused by the effects of adults’ cognition and behavioral habits and explores the factors’ relationship paradigm. A theoretical framework of travel mode choice behavior for students in China is constructed. We established the MIMIC model that accommodates latent variables from ETPB. We found that not all the psychological latent variables have significant effects on school travel mode choice behavior, but habit can play an essential role. The results provide theoretical support for demand policies for school travel.     

A Pareto-improving hybrid rationing and pricing policy with multiclass network equilibria

This paper extends the work on Pareto-improving hybrid rationing and pricing policy for general road networks by considering heterogeneous users with different values of time. Mathematical programming models are proposed to find a multiclass Pareto-improving pure road space rationing scheme (MPI-PR) and multiclass hybrid rationing and pricing schemes (MHPI and MHPI-S). A numerical example with a multimodal network is provided for comparing both the efficiency and equity of the three proposed policies. We discover that MHPI-S can achieve the largest reduction in total system delay, MHPI can induce the least spatial inequity and MHPI-S is a progressive policy which is appealing to policy makers. Furthermore, numerical results reveal that different classes of users react differently to the same hybrid policies and multiclass Pareto-improving hybrid schemes yield less delay reduction when compared to their single-class counterparts.     

Shaping the Coast with Permits: Making the State Regulatory Permitting Process Transparent with Text Mining

This paper examines the California Coastal Commission's permitting process. Using several text mining techniques, including web scraping, information extraction, and supervised classification, I demonstrate how to retrieve empirical data from unstructured texts, namely public meeting agendas and staff reports. Contrary to the concern that the Commission routinely delays or rejects permitting requests, the data reveal that outright rejection of permit applications is rare. On average, eight of ten applications were approved. Single-family homes and commercial development projects were approved about 80% of the time; the rates were about 70% for seawalls and retaining walls, and 60% for land-use changes. Most applications were processed swiftly, with a median application length of 3 months. The agency's influence comes primarily from negotiating each application. Qualitative study of 50 cases pertaining to single-family home construction reveals that the agency adopts a “managed development” approach, that is, allowing development but scrupulously managing various aspects of development. These case studies illustrate how the agency interprets the broad, abstract state laws and translates the mandates into enforceable actions as permitting conditions. In areas where the state mandates conflict, particularly over development in receding shorelines, the agency has the largest leverage in creating and implementing its preferred policies. The text mining techniques demonstrated in this paper can be applied to study any governmental agency. These techniques help to extract information from a massive volume of papers and organize them into a database for analyses. The empirical data extracted from texts can significantly increase bureaucratic transparency.