Comparative Evaluation of the Flexural Strength of Concrete and Colcrete

Colcrete is a construction material resulting from grouting of prep laced coarse aggregates with colgrout. Colcrete is more economical to use than concrete. If the performance of colcrete in service is favourably comparable to that of concrete, some construction costs could be saved in the use of colcrete in place of concrete. This paper reports the findings of a study carried out to compare the flexural strength of colcrete to that of concrete. Concrete beams of 750 mm × 150 mm × 150 mm were cast in accordance to BS 1881: Part 118: 1983 using 1:2:4 and 1:3:6 nominal mix ratios, with water-cement ratios of 0.56 and 0.58, respectively. Similar colcrete beams were cast using 1:2 and 1:3 colgrout with 0.56 and 0.58 water cement ratios, respectively. Three different sizes - 47 mm, 50 mm, and 55 mm - of coarse aggregates were used. The beams were tested for flexural strength after 28 days of casting and curing in water. Flexural strength results for the concrete and colcrete were compared. Results show that for the two mix ratios investigated, and the three types of coarse aggregates used, the flexural strength of colcrete is higher than that of concrete. On the basis of this study, it is concluded that colcrete performs better in flexure than concrete. The use of colcrete is, therefore, recommended in structures, especially members predominantly loaded in flexure, so as to reap the benefits of better performance and cost savings in construction projects

The development and use of off-shore mineral exploration techniques

Imperial Users onl

Migrant workers in the East Midlands labour market 2007

This report provides a profile of international migrants in the East Midlands and their role in the regional labour marke

Identification of patterns in long-term observations of the cloudy boundary layer

Understanding atmospheric boundary layer (ABL) processes is a key aspect in improving parameterizations in weather forecast and climate prediction models, but also for renewable energy and air quality studies. The ABL, as the lowest part of the atmosphere, can be directly affected by heterogeneities in land surface properties like soil, vegetation and topography, creating patterns at different temporal and spatial scales. In this context, turbulent mixing plays an important role in connecting the atmosphere to the Earth's surface. The turbulent motions are responsible for the thermodynamic structure of the ABL by redistributing heat and moisture and the transport of constituents like aerosols and pollutants away from the surface. These processes are the main drivers for the development of ABL clouds, which in turn feed back to the ABL and surface through interaction with solar radiation, coupling to the large-scale circulation and precipitation formation. This links back to the aim of model improvement, since clouds are one of the largest source of uncertainty in global models. Therefore interdisciplinary research is required to capture the interplay between the different compartments of the Earth. The Transregional Collaborative Research Centre 32 (TR32) in its third phase is dedicated to find these patterns in the soil-vegetation-atmosphere system by a monitoring, modelling and data assimilation approach. Within the TR32 project D2 special emphasis is on measuring, modelling and understanding the spatio-temporal structures in land surface-atmosphere exchange at the Jülich ObservatorY for Cloud Evolution (JOYCE). For the typical ABL process scales of seconds to hours and meters to kilometers, ground-based remote sensing observations are well suited to continuously gather comprehensive information on the atmospheric state in a long-term perspective. With additional model simulations the conceptual process understanding can be improved. This study focuses on the long-term characterisation of the cloudy boundary layer to identify patterns that can be further linked to surface properties at JOYCE. For this purpose, a classification for characterizing ABL turbulence is developed (Publication I). The classification, based on Doppler wind lidar (DWL) data, identifies turbulence regions in the ABL and assigns a mixing source using multiple DWL quantities. In this way, convective, wind shear and cloud driven turbulence can be distinguished under most atmospheric conditions. The method is applied at two research sites, showing a distinct behavior for different climate regimes in terms of the diurnal and seasonal cycle of ABL development. In the analysis of the long-term data sets, nocturnal low-level jets (LLJ) are identified as an important source of shear generated mixing. Therefore, a long-term record of LLJ periods, compiled with DWL observations, is investigated in Publication II. The high frequency of occurrence and wind speeds, associated with significant turbulence close to the surface, reveal the relevance of LLJs for wind energy applications. In addition, a strong interaction of the wind field with the surrounding topography can be seen in the DWL measurements, as well as in the results of a high-resolution large-eddy simulation (LES). Also during the day, when the buoyancy production represents the main factor of convective ABL mixing, the interaction between the land surface and the atmosphere is strongly influenced by surface properties. In particular, the local transport of water vapor in moist thermals is a key mechanism for the coupling of clouds to the underlying land surface and a spatially heterogeneous distribution of land use types can lead to patterns in atmospheric water vapor fields (Publication III). Besides a scanning microwave radiometer (MWR), also satellite and LES data are taken into account, showing a good agreement in identifying the direction of water vapor sources. Convective clouds, that are frequently forming in the ABL due to this convective humidity transport, often contain small amounts of liquid water. These thin liquid water clouds, with a low liquid water path (LWP), are important in terms of their interaction with radiation. In the range of low LWP values, the radiative fluxes are very sensitive to small changes in the amount liquid water contained in the clouds. For a correct representation of the cloud microphysical and optical properties, statistical retrievals using a neural network approach are developed in Publication IV. The retrievals with low computational demand are derived from ground-based observations and make use of the distinct sensitivities in different spectral regimes. While the microwave regime suffers from high uncertainties in low LWP situations, the infrared regime reveals saturation effects for higher LWP. A combination of both spectral regimes yields the best results for the whole range of LWP values

Present values of lifetime earnings of college occupations

Economic returns analysis for some occupations entered by college graduates and applications to engineering and scientific labor marke