浅述重力式码头沉箱预制在连云港港赣榆港区一期工程中质量控制要点

由于深水泊位建造日趋增多,沉箱预制逐渐向高大发展。保证质量犹为重要。结合在连云港港赣榆港区一期工程中沉箱预制施工管理实践,介绍施工工艺流程。分析施工中存在的问题。阐述施工过程中主要工序的质量控制要点。     

某型船电网振荡的原因分析及对策

本文分析了某型船电力系统在电网振荡时各电气参数变化的特点及电网发生振荡的原因,阐述了处理电网振荡的方法,提出了一种新的处理方法,并提出了一些建议。     

内河船舶波浪载荷研究

利用内河波浪散布图和修订波浪谱对内河系列船舶进行了波浪载荷的计算预报,首次分析了内河船舶波浪载荷的规律和特点,并与俄罗斯内河登记局(RRR)和法国-德国船级社(B-G)的内河规范载荷对应的等效模数要求进行了比较分析。结合实船测试结果表明：波浪载荷变化规律与国外同类规范一致,预报波浪载荷水平与测试结果及国外同类规范要求相当。内河船舶波浪载荷预报应考虑航速和水深的影响,载荷预报结果可以作为制定内河波浪载荷公式的基础。     

沉管隧道穿越江河海湾的优越性

文章从工程的造价、质量、工期、安全、生态环境及社会效益等角度,通过对沉管隧道与桥梁、盾构隧道渡越方案的分析、对比和论证,着重指出采用沉管隧道方案穿越江河海湾的诸多优越性.     

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.     

苏家湾隧道初期支护变形侵限处理措施及施工工艺的研究

文章针对苏家湾隧道发生的初期支护变形侵限的病害,通过对隧道洞身地质条件的分析,并利用有限元软件MIDAS-GTS对隧道初期支护结构及二次衬砌进行了验算,确定出控制隧道初期支护变形的支护参数;并提出施工前加强对隧道中线顶部地表的地形地貌调查,完善排水系统、隧道内加强支护系统、适当加大预留变形量,并加强监控量测等施工工艺和处理措施。     

Safety modeling for two‐way left‐turn lanes and a procedure to identify two‐way left‐turn lane segments with safety concerns

In the past, two‐way left‐turn lane (TWLTL) median treatments have been frequently used in Florida to inexpensively improve traffic and safety performances. In order to identify factors that may have significant impacts on safety operations in TWLTL sections and to identify TWLTL locations that present existing and future safety concerns, a research project was carried out and results are summarized in the paper. In the research, a three‐year crash history database with crashes and section characteristics from a total of 1688 TWLTL sections all over Florida was developed and used. A negative binomial regression model was developed to determine the statistical relationship between the number of crashes per mile per year and several variables such as traffic volume, access density, posted speed, and number of lanes. In regard to the methodology, in order to identify locations with safety concerns, several steps are needed: development of real crash data distribution, determination of statistical distribution models that better represent the actual crash data, determination of percentile values for the average number of crashes, estimation of crash rates for sections with the same characteristics, estimation of critical values for the variables corresponding to the percentile values for average number of crashes, calculation of tables of critical average annual daily traffic values, and generation of a list of TWLTL locations with critical safety concerns. Results presented in the paper have been used in real applications. Copyright © 2012 John Wiley & Sons, Ltd.     

基于小波分析的隧道监测数据处理

基于小波分析理论,对一组隧道洞内水平收敛监测数据进行了去噪重构.实际分析结果表明,小波分析能够有效地去除监测数据的噪声,识别数据中的突变点;从去噪后的数据曲线分析,得出水平收敛量的发展趋势,可以有效地指导隧道的安全施工.     

Hybrid model for prediction of bus arrival times at next station

Effective prediction of bus arrival times is important to advanced traveler information systems (ATIS). Here a hybrid model, based on support vector machine (SVM) and Kalman filtering technique, is presented to predict bus arrival times. In the model, the SVM model predicts the baseline travel times on the basic of historical trips occurring data at given time‐of‐day, weather conditions, route segment, the travel times on the current segment, and the latest travel times on the predicted segment; the Kalman filtering‐based dynamic algorithm uses the latest bus arrival information, together with estimated baseline travel times, to predict arrival times at the next point. The predicted bus arrival times are examined by data of bus no. 7 in a satellite town of Dalian in China. Results show that the hybrid model proposed in this paper is feasible and applicable in bus arrival time forecasting area, and generally provides better performance than artificial neural network (ANN)–based methods. Copyright © 2010 John Wiley & Sons, Ltd.