Experimental Investigation for Tensile Performance of GFRP-Steel Hybridized Rebar

Tensile performance of the recently developed “FRP Hybrid Bar” at Korea Institute of Civil Engineering and Building Technology (KICT) is experimentally evaluated by the authors. FRP Hybrid Bar is introduced to overcome the low elastic modulus of the existing GFRP bars to be used as a structural member in reinforced concrete structures. The concept of material hybridization is applied to increase elastic modulus of GFRP bars by using steel. This hybridized GFRP bar can be used in concrete structures as a flexural reinforcement with a sufficient level of elastic modulus. In order to verify the effect of material hybridization on tensile properties, tensile tests are conducted. The test results for both FRP Hybrid Bar and the existing GFRP bars are compared. The results indicate that the elastic modulus of FRP Hybrid Bar can be enhanced by up to approximately 250 percent by the material hybridization with a sufficient tensile strength. To ensure the long-term durability of FRP Hybrid Bar to corrosion resistance, the individual and combined effects of environmental conditions on FRP Hybrid Bar itself as well as on the interface between rebar and concrete are currently under investigation

Causal Graph Discovery For Hydrological Time Series Knowledge Discovery

Causal inference or causal relationship discovery is an important task in hydrological study to explore the causes of abnormal hydrology phenomena such as drought and flood, which will help improving our prediction and response ability to natural disasters. Different from generic causality study where causalrelation discovery is sufficient, for extreme hydrological situation prediction and modeling, we need not only to construct a causal graph to reveal the contributing factors, but also to provide the lead time of each cause to its effect. Lead time is the time difference between the occurrence of lead and effect. Though causal inference or causal relationship discovery has been a major topic in many science problems, majority of the work has been focused on the validity of such relationship with no knowledge on cause-effect time lead information. Such insight is critical for hydrological modeling and prediction, in which time lead information is desired for knowing how long different factors will affect certain extreme situations such as flood or drought. The most commonly used computational algorithms for causality discovered can be categorized as using regression approaches or Bayesian approaches. Regression based approaches such as Granger\u27s causality assume linear causality and first order causal relationship. Bayesian approaches, such as the PC algorithm from Pearl\u27s causality definition, have exponential runtime complexity which makes it difficult to be applied to hydrological systems with a high number of variables. Furthermore, no existing approaches incorporate the lead time concept in the discovery of causal relationship. In this paper, we propose a new approach, mutual information causal (MI-Causal), for causal relationship discovery, which embodies the advantages of existing approaches and overcomes the limitations to satisfy the hydrologic need. The experimental results from both synthetic and real time hydrological data show that our proposed method outperforms regression approaches and Bayesian based approaches

Probablistic Rainfall Forecasting Using Single-Valued Rainfall Forecasts for Risk-Based Water Management at the South Florida Water Management District

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Breakdown of the interlayer coherence in twisted bilayer graphene

Coherent motion of the electrons in the Bloch states is one of the fundamental concepts of the charge conduction in solid state physics. In layered materials, however, such a condition often breaks down for the interlayer conduction, when the interlayer coupling is significantly reduced by e.g. large interlayer separation. We report that complete suppression of coherent conduction is realized even in an atomic length scale of layer separation in twisted bilayer graphene. The interlayer resistivity of twisted bilayer graphene is much higher than the c-axis resistivity of Bernal-stacked graphite, and exhibits strong dependence on temperature as well as on external electric fields. These results suggest that the graphene layers are significantly decoupled by rotation and incoherent conduction is a main transport channel between the layers of twisted bilayer graphene.Comment: 5 pages, 3 figure

Real-Time Early Detection and Monitoring of Flooding Using Low-Cost Highly Sensitive Ultrasound Sensing of Water Level

Flooding poses safety hazards to motorists, emergency and maintenance crews and may cause costly damage to transportation infrastructure and its operation. Flash flooding, in particular, causes the most flood-related deaths According to NOAA, in 2017 alone, flash flooding also caused $60.7 billion worth of economic damage. Low-water crossings are among the first places where deaths and significant damages to vehicles occur during flooding. With flash flooding, when a critical corridor is blocked by a high level of water, it affects the safety of the general public. To keep the critical corridors open as long as possible, and to minimize losses from flooding, accurate early detection of the rising water level is essential. The flood level detection system has to have flood stage maps in the geographic information system for the street-, roadway-, and critical-freight corridors. This area encompasses public roads in urbanized areas that provide access and connection to the primary roads for ports, public transportation or other transportation facilities. The main goal of this project is to develop cost-effective and high efficient solar-powered water level detection units and implement real-time water level monitoring for water both pavement and river stream. The project was performed with three objectives: to develop the low cost reliable real-time data of the ultrasound water level detection system, increasing its data reliability and resolution; 2) to improve an energy-saving processing system; and to deploy the ultrasound water level detection system and real-time monitoring system for water both pavement and river stream for safety measures. The obtained results and findings imply the developed monitoring system can present reliable water level data with efficient power and data transmission system

Development of an approximate construction duration prediction model during the project planning phase for general office buildings

Accurate prediction of the construction duration is imperative to the reliable cash flow analysis during the project planning phase when feasibility analysis is carried out. However, lack of information and frequent changes that occur as a result of a negotiation process between the owner and the designer in defining the project scope make it difficult to compute real-time construction duration. Domestic and foreign models for calculating the construction durations cannot be readily applied to computation of construction duration for general office buildings in Korea specifically during the project planning phase as there is a limit in its applicability due to numerous restrictions. Moreover, there are no preceding studies suggesting different computational approaches to predict the entire construction duration for office buildings with the approximate construction duration concept during planning phase. Therefore, based on the collected performance data, this study proposes a multiple linear regression model that facilitates reliable prediction of approximate construction duration for office buildings in the project planning phase. The model will allow the owner and other stakeholders to predict the real-time construction duration using the basic information on office buildings and to assess the construction durations incorporating frequent changes during the project planning phase

Heuristic Incremental Theory of Diffraction for a Wedge with Impedance Surfaces

This paper proposes a novel incremental theory of diffraction (ITD) formulation to calculate the fringe field from a wedge characterized by impedance surfaces and arbitrary exterior angles. The ITD formula was originally based on the Fourier transform pair relationship between the solution for the canonical wedge problem and incremental field contribution. However, this procedure can be utilized to report the ITD formula only for planar and half-planar impedance surfaces. Therefore, this paper develops a heuristic ITD formula by conceptually deriving the incremental diffracted field contribution from the uniform theory of diffraction coefficient and inferring the physical optics edge-diffracted field contribution from the terms related to the incidence shadow and reflection shadow boundaries. The proposed formula is applied to simple triangular impedance cylinder and disk models with impedance surfaces, and the results are compared with those of the method-of-moment and VIRAF’s ITD solver to show that is performs similar to the former and better than the latter