柳州绕城高速公路沥青混合料目标配合比设计

文章介绍柳州绕城高速公路沥青混合料目标配合比设计实例,为沥青混凝土路面的设计与施工提供借鉴。     

SMA沥青混合料配合比设计与施工控制

SMA沥青混合料尽管具有众多优越的路用性能,但其施工难度较大、要求较高。为此,详细介绍了SMA混合料中原材料的选择及配合比的设计过程,并提出施工中的质量控制要点,以促进SMA沥青混凝土在我国的进一步推广应用。     

沥青混合料设计与施工质量

阐述了高等级公路沥青混合料配合比设计、施工和质量控制。     

青南地区沥青混合料配合比设计研究

青南地区沥青路面施工需综合考虑低温高寒、雨热同期等高寒地区特殊的环境因素。文章结合G214线结古至巴塘机场公路建设,从沥青混合料配合比设计入手,探讨高寒地区沥青混合料配合比设计方法。     

沥青路面冷再生沥青混合料配合比设计研究

冷再生沥青混合料施工技术是一种节能环保的公路路面修复技术,不但可以有效减少石料、沥青、水泥的需求量,降低工程成本,减少了资源浪费,并且与热再生技术相比可以有效降低CO2排放量。配合比设计是影响冷再生沥青混合料质量的关键因素,本文以某公路沥青路面修复工程为例,对沥青路面冷再生沥青混合料配合比进行研究,以加强冷再生沥青混合料质量控制。     

温拌沥青混合料配合比设计与施工控制

结合工程实践介绍了温拌沥青混合料的工艺原理、配合比设计,并对温拌沥青混合料路面的施工工艺过程以及控制措施进行了阐述。     

沥青混合料配合比组成设计对路面施工质量的影响分析

为了提高沥青路面的舒适性和安全性,首先对沥青混合料各指标进行阐述,再对沥青混合料原材料质量和配合比设计过程进行总结,最后对沥青混合料拌和过程控制进行分析,旨在为今后道路施工提供借鉴。     

再生沥青混合料理论最大相对密度确定方法研究

再生沥青混合料内部孔隙较多,掺入的旧料为沥青与集料裹合物,依据规范现有的计算法与试验法难以确定其理论最大相对密度。基于沥青混合料理论最大相对密度计算法和实测法测定原理,通过新拌不同级配类型的沥青混合料,建立理密计算值与实测值关系系数,以再生沥青混合料实测值计算真实值,修正再生沥青混合料理密计算和试验公式。     

高模量沥青混合料在G205示范工程的应用

在G205示范工程(淄博段)中,采用了HM AC-25高模量沥青混合料施工。     

抗永久变形性能的沥青混合料配合比设计方法研究

沥青路面永久变形主要是沥青面层在高温、重载作用下出现的高温剪切流动变形。提高沥青混合料的高温抗永久变形可以采用改性沥青、添加抗永久变形剂,也可以从混合料配合比组成方面进行优化,主要研究沥青混合料配合比设计方法。     

沥青玛蹄脂碎石混合料在路面施工中的应用

结合济南二环东路高架桥工程沥青路面的铺筑技术,研究了沥青马蹄脂碎石混合料(SMA)技术性能及施工特点。结果表明沥青玛蹄脂碎石混合料弥补了传统沥青混合料的缺陷,使其使用性能更加全面,而改性沥青马蹄脂碎石混合料又在此基础上提高了沥青混凝土路面的高温稳定性、低温抗裂性及水稳性。     

不同RAP掺量下就地热再生沥青混合料空隙率优选分析

依托福建省某高速路面预防性养护工程,采用最大理论密度线理论设计了再生沥青混合料级配,通过马歇尔试验研究了RAP料在86%、90%、94%掺量下再生沥青混合料空隙率的变化,并基于二次回归方程建立了不同RAP掺量与再生沥青混合料空隙率之间的回归方程,说明了不同RAP掺量与空隙率之间的变化趋势。研究结果表明:随着RAP料掺量增加,再生沥青混合料空隙率在逐渐降低;当再生沥青混合料空隙率控制在4%时,RAP料掺量约为89%。     

U型槽结构钢筋混凝土配合比设计及应用

结合S351砀定路定陶京九铁路下穿立交封闭式路堑U型槽结构施工,介绍了该结构混凝土配合比设计的基本思路、方法及步骤;阐述了施工工艺要点。     

Mathematical characterization of spatiotemporal congested traffic patterns: mixed speed data analysis in the greater Toronto and Hamilton area,Canada

This paper formulates a comprehensive methodology for analyzing, quantifying and identifying congestion characteristics based on speed distribution. Utilizing vehicle speed data, a mathematical approach is applied, in order to characterize roadway segments, in terms of travel reliability, congestion severity and duration. We argue that the Gaussian mixture model (GMM) and its parameter combination is the appropriate tool if we are to obtain quantitative congestion measures and rank roadway performance. A significant contribution of our approach is that it is based on assumptions regarding mixed components as well as speed distribution and can be applied to large databases. We test our framework on the greater Toronto and Hamilton area in Ontario, Canada, and conclude that congestion quantification through the application of the GMM can be successfully accomplished. Results indicate that speed patterns differ significantly between counties as well as days of the week.     

Real options and flexibility analysis in design and management of one-way mobility on-demand systems using decision rules

This study explores the concepts of real options and flexibility analysis as an approach to address uncertain demand growth in mobility on-demand (MoD) vehicle-sharing systems, with the goal of improving expected lifecycle performance. As MoD systems are gaining popularity worldwide, they inevitably face significant uncertainty in terms of needs and customer demands. Designing, planning capacity deployment, and operating such system can be challenging, and require significant capital investments for companies and cities. Two distinct real options analysis (ROA) models are developed to evaluate and optimize flexible strategies for these systems, relying on a novel methodological approach to value flexibility based on decision rules. The decision-rule-based approach differs from standard ROA approaches used to quantify the value of flexibility in irreversible investment projects, typically based on dynamic programming. It emulates the decision-making process by capturing mathematically a triggering mechanism that determines when it is best to exercise the flexibilities embedded in the system design. Two prevalent types of MoD systems are studied in this paper as demonstration of the methodological framework: a station-based system where customers must pick up and return the vehicle at specific locations, and a free-floating system, where customers may pick up and drop the car anywhere within a certain area. A simulation-based approach is used to analyze the station-based system, which models the rebalancing operations from a micro-level perspective. The approach consists of a discrete event simulator for performance estimation, and an optimization algorithm for design space exploration that integrates a population-based search algorithm with Optimal Computing Budget Allocation (OCBA). For the free-floating system, an analytical model is developed where the decision rule is formulated into and solved using stochastic mixed integer programming (MIP). The study provides guidance to system operators on potential strategies for deploying MoD systems, considering explicitly uncertainty and flexibility as a value enhancing mechanism.