도심지에 시공된 아스팔트 포장은 교통량 증가와 중차량의 가감속으로 인해 포트홀 및 소성변형 등의 파손이 흔히 발생하고 있다. 이러한 아스팔트 포장의 파손을 최소화하기 위해 콘크리트 포장으로 전환하는 공법인 초속경 시멘트 콘크리트 포장 공법과 프리캐스 트 콘크리트 포장 공법이 있으나 고비용으로 인해 널리 적용하기에는 한계가 있는 실정이다. 최근 서울시에서는 신설 중앙버스정류장 에 현장타설 방식으로 연속철근 콘크리트 포장(CRCP)을 시공하였다. 본 연구에서는 인력포설 방식으로 시공한 중앙버스정류장의 CRCP에 대한 공용성을 분석하고자 온도계, 균열유도장치, 철근 변형률계, 콘크리트 변형률계, 변위계, 균열계 등을 포함하는 계측시스 템을 구축하였으며 본 논문에서는 이러한 계측시스템에 대하여 기술한다.

PURPOSES : In this study, a numerical clogging model that can be used to realistically visualize the movement of particles in cylindrical permeability test equipment was proposed based on the system coupling of computational fluid dynamics with the discrete element method and experimental permeability test results. This model can also be used to simulate the interaction of dust particles with bedding particles. METHODS: A 4-way system coupling method with multiphase volumes of the fluid model and porous media model was proposed. The proposed model needs to consider the influence of flow on the dust particles, interaction between the dust particles, and interaction between the dust particles and bedding layer particles. The permeability coefficient of the bedding layer in cylindrical permeability test equipment was not calculated by using the permeability test result, but was estimated by using the particle packing model and Ergun model. RESULTS : The numerical simulation demonstrated a good agreement with the experimental test results in terms of permeability and drain time. Additionally, the initial movement of particles due to the sudden drain hole opening was successfully captured by the numerical model. CONCLUSIONS : A 4-way coupling model was sufficient to simulate the water flow and particle movement in cylindrical permeability test equipment. However, additional tests and simulation are required to utilize the model for more realistic block pavement systems.

PURPOSES : In this study, a series of fundamental falling head permeability tests were conducted on a binary particle mix bedding to determine the minimum water level, bedding layer thickness, and amount of dust that can result in the stable permeability with high repeatability. The determined condition is used to develop a CFD-DEM coupled clogging model that can explain the movement of dust particles in flowing water of a block pavement system. METHODS: A binary particle mixture is utilized to experimentally simulate an ideal bedding layer of a block pavement system. To obtain a bedding layer with maximum packing degree, the well-known particle packing degree model, i.e., the modified Toufar model, was utilized. The permeability of the bedding layer for various water levels, bedding layer thicknesses, and amounts of dust was calculated. The permeability for a small water level drop was also plotted to evaluate the effect of dust on the bedding layer clogging. RESULTS: It was observed that a water level of 100 mm, bedding depth of 70 mm, and dust amount of 0.3 g result in a stable permeability condition with high repeatability. The relationship between the minimum dust amount and surface clogging of the bedding layer was suggested based on the evaluation of the volumetric calculation of the particle and void and the permeability change in the test. CONCLUSIONS: The test procedure to determine the minimum water level, bedding thickness, and dust amount was successfully proposed. The mechanism of clogging on the surface of the bedding layer was examined by relating the volumetric characteristics of dust to the clogging surface.

Asphalt pavement overlay method is one of widely chosen construction methods for remodelling existing aged concrete pavement layer. However, in this case reflective cracking is a challenging issue due to movement of transverse joints: built in existing concrete pavement layer with constant interval length. In this paper, collecting field data: collection of displacement and temperature data on existing concrete pavement layer for further complicated pavement performance analysis, was performed. To fulfil this objective, various types of thermometer were embedded into concrete layer with different depth level. Then, movement of existing concrete layer was measured numerically. Each Displacement Measuring Gauge (DMG) along with thermometer was embedded with depth of 3cm and 15cm, respectively. Additional thermometers were embedded at the middle depth of overlaid asphalt pavement layer for further extensive analysis and data collection. Total four testing sites were considered based on different asphalt mixture type and construction method. The 1st site was constructed with conventional construction approach, the 2nd site was constructed with a new pavement equipment contains simultaneous tack-coating function, the 3rd site was similar to 1st site but Guss-asphalt was constructed as a binder course, and in 4th site Noise-Reduction Porous Asphalt (NRPA) was constructed as a surface course and regular Dense Grade Asphalt (DGA) was constructed as a binder course. A field asphalt pavement layer sample coring works: along with basic material property tests, were also performed to acquire not only overlaid asphalt but also existing concrete pavement materials. This gauge measuring work in this study is an initial step therefore, long-term movement data of each pavement layer was not able to be collected, unfortunately. However through collecting and analysing initial data on each test site, two crucial findings were acquired. First, in all four tested site highest temperature variations were observed at the upper asphalt pavement layer and the variation trends decreased with increase of pavement depth (in case of concrete pavement layer, temperature and movement variations also decreased with increase of pavement depth). Secondly, when Guss-asphalt was applied as a binder course temperature variations of existing concrete pavement layer was crucially smaller than those of other comparison cases. These current findings and collected data set can provide successful input information for further pavement structure analysis such as 2D (and/or 3D) Finite Element Method (FEM) analysis as a future study.