Simulation of Snow Covers Area by a Physical based Model

Snow cover is an important phenomenon in hydrology, hence modeling the snow accumulation and melting is an important issue in places where snowmelt significantly contributes to runoff and has significant effect on water balance. The physics-based models are invariably distributed, with the basin disaggregated into zones or grid cells. Satellites images provide valuable data to verify the accuracy of spatially distributed model outputs. In this study a spatially distributed physically based model (WetSpa) was applied to predict snow cover and melting in the Latyan dam watershed in Iran. Snowmelt is simulated based on an energy balance approach. The model is applied and calibrated with one year of observed daily precipitation, air temperature, windspeed, and daily potential evaporation. The predicted snow-covered area is compared with remotely sensed images (MODIS). The results show that simulated snow cover area SCA has a good agreement with satellite image snow cover area SCA from MODIS images. The model performance is also tested by statistical and graphical comparison of simulated and measured discharges entering the Latyan dam reservoir.

Simulation of Water Droplet on Horizontally Smooth and Rough Surfaces Using Quasi-Molecular Modelling

We developed a method based on quasi-molecular modelling to simulate the fall of water drops on horizontally smooth and rough surfaces. Each quasi-molecule was a group of particles that interacted in a fashion entirely analogous to classical Newtonian molecular interactions. When a falling water droplet was simulated at low impact velocity on both smooth and rough surfaces, the droplets moved periodically (i.e. the droplets moved up and down for a certain period, finally they stopped moving and reached a steady state), spreading and recoiling without splash or break-up. Spreading rates of falling water droplets increased rapidly as time increased until the spreading rate reached its steady state at time t ~ 0.25 s for rough surface and t ~ 0.40 s for smooth surface. The droplet height above both surfaces decreased as time increased, remained constant after the droplet diameter attained a maximum value and reached its steady state at time t ~ 0.4 s. However, rough surface had higher spreading rates of falling water droplets and lower height on the surface than smooth one.

Prediction of Compressive Strength of SCC Containing Bottom Ash using Artificial Neural Networks

The paper presents a comparative performance of the models developed to predict 28 days compressive strengths using neural network techniques for data taken from literature (ANN-I) and data developed experimentally for SCC containing bottom ash as partial replacement of fine aggregates (ANN-II). The data used in the models are arranged in the format of six and eight input parameters that cover the contents of cement, sand, coarse aggregate, fly ash as partial replacement of cement, bottom ash as partial replacement of sand, water and water/powder ratio, superplasticizer dosage and an output parameter that is 28-days compressive strength and compressive strengths at 7 days, 28 days, 90 days and 365 days, respectively for ANN-I and ANN-II. The importance of different input parameters is also given for predicting the strengths at various ages using neural network. The model developed from literature data could be easily extended to the experimental data, with bottom ash as partial replacement of sand with some modifications.

An Investigation of the Effect of the Different Mix Constituents on Concrete Electric Resistivity

Steel corrosion in concrete is considered as a main engineering problems for many countries and lots of expenses has been paid for their repair and maintenance annually. This problem may occur in all engineering structures whether in coastal and offshore or other areas. Hence, concrete structures should be able to withstand corrosion factors existing in water or soil. Reinforcing steel corrosion enhancement can be measured by use of concrete electrical resistance; and maintaining high electric resistivity in concrete is necessary for steel corrosion prevention. Lots of studies devoted to different aspects of the subjects worldwide. In this paper, an evaluation of the effects of W/C ratio, cementitious materials, and percent increase in silica fume were investigated on electric resistivity of high strength concrete. To do that, sixteen mix design with one aggregate grading was planned. Five of them had varying amount of W/C ratio and other eleven mixes was prepared with constant W/C ratio but different amount of cementitious materials. Silica fume and super plasticizer were used with different proportions in all specimens. Specimens were tested after moist curing for 28 days. A total of 80 cube specimens (50 mm) were tested for concrete electrical resistance. Results show that concrete electric resistivity can be increased with increasing amount of cementitious materials and silica fume.

Sustainable and Ecological Designs of the Built Environment

This paper reviews designs of the built environment from a sustainability perspective, emphasizing their importance in achieving ecological and sustainable economic objectives. The built environment has traditionally resulted in loss of biodiversity, extinction of some species, climate change, excessive water use, land degradation, space depletion, waste accumulation, energy consumption and environmental pollution. Materials used like plastics, metals, bricks, concrete, cement, natural aggregates, glass and plaster have wreaked havoc on the earth´s resources, since they have high levels of embodied energy hence not sustainable. Additional resources are consumed during use and disposal phases. Proposed designs for sustainability solutions include: ecological sanitation and eco-efficiency systems that ensure social, economic, environmental and technical sustainability. Renewable materials and energy systems, passive cooling and heating systems and material and energy reduction, reuse and recycling can improve the sector. These ideas are intended to inform the field of ecological design of the built environment.

Packing Theory for Natural and Crushed Aggregate to Obtain the Best Mix of Aggregate: Research and Development

Concrete performance is strongly affected by the particle packing degree since it determines the distribution of the cementitious component and the interaction of mineral particles. By using packing theory designers will be able to select optimal aggregate materials for preparing concrete with low cement content, which is beneficial from the point of cost. Optimum particle packing implies minimizing porosity and thereby reducing the amount of cement paste needed to fill the voids between the aggregate particles, taking also the rheology of the concrete into consideration. For reaching good fluidity superplasticizers are required. The results from pilot tests at Luleå University of Technology (LTU) show various forms of the proposed theoretical models, and the empirical approach taken in the study seems to provide a safer basis for developing new, improved packing models.

The Effect of Fine Aggregate Properties on the Fatigue Behavior of the Conventional and Polymer Modified Bituminous Mixtures Using Two Types of Sand as Fine Aggregate

Fatigue cracking continues to be the main challenges in improving the performance of bituminous mixture pavements. The purpose of this paper is to look at some aspects of the effects of fine aggregate properties on the fatigue behaviour of hot mixture asphalt. Two types of sand (quarry and mining sand) with two conventional bitumen (PEN 50/60 & PEN 80/100) and four polymers modified bitumen PMB (PM1_82, PM1_76, PM2_82 and PM2_76) were used. Physical, chemical and mechanical tests were performed on the sands to determine their effect when incorporated with a bituminous mixture. According to the beam fatigue results, quarry sand that has more angularity, rougher, higher shear strength and a higher percentage of Aluminium oxide presented higher resistance to fatigue. Also a PMB mixture gives better fatigue results than conventional mixtures, this is due to the PMB having better viscosity property than that of the conventional bitumen.

Beneficial Use of Coal Combustion By-products in the Rehabilitation of Failed Asphalt Pavements

This study demonstrates the use of Class F fly ash in combination with lime or lime kiln dust in the full depth reclamation (FDR) of asphalt pavements. FDR, in the context of this paper, is a process of pulverizing a predetermined amount of flexible pavement that is structurally deficient, blending it with chemical additives and water, and compacting it in place to construct a new stabilized base course. Test sections of two structurally deficient asphalt pavements were reclaimed using Class F fly ash in combination with lime and lime kiln dust. In addition, control sections were constructed using cement, cement and emulsion, lime kiln dust and emulsion, and mill and fill. The service performance and structural behavior of the FDR pavement test sections were monitored to determine how the fly ash sections compared to other more traditional pavement rehabilitation techniques. Service performance and structural behavior were determined with the use of sensors embedded in the road and Falling Weight Deflectometer (FWD) tests. Monitoring results of the FWD tests conducted up to 2 years after reclamation show that the cement, fly ash+LKD, and fly ash+lime sections exhibited two year resilient modulus values comparable to open graded cement stabilized aggregates (more than 750 ksi). The cement treatment resulted in a significant increase in resilient modulus within 3 weeks of construction and beyond this curing time, the stiffness increase was slow. On the other hand, the fly ash+LKD and fly ash+lime test sections indicated slower shorter-term increase in stiffness. The fly ash+LKD and fly ash+lime section average resilient modulus values at two years after construction were in excess of 800 ksi. Additional longer-term testing data will be available from ongoing pavement performance and environmental condition data collection at the two pavement sites.

New Device for Enhancement of Liposomal Magnetofection Efficiency of Cancer Cells

Liposomal magnetofection is the most powerful nonviral method for the nucleic acid delivery into the cultured cancer cells and widely used for in vitro applications. Use of the static magnetic field condition may result in non-uniform distribution of aggregate complexes on the surface of cultured cells. To prevent this, we developed the new device which allows to concentrate aggregate complexes under dynamic magnetic field, assisting more contact of these complexes with cellular membrane and, possibly, stimulating endocytosis. Newly developed device for magnetofection under dynamic gradient magnetic field, “DynaFECTOR", was used to compare transfection efficiency of human liver hepatocellular carcinoma cell line HepG2 with that obtained by lipofection and magnetofection. The effect of two parameters on transfection efficiency, incubation time under dynamic magnetic field and rotation frequency of magnet, was estimated. Liposomal magnetofection under dynamic gradient magnetic field showed the highest transfection efficiency for HepG2 cells.

Spatial Mapping of Dengue Incidence: A Case Study in Hulu Langat District, Selangor, Malaysia

Dengue is a mosquito-borne infection that has peaked to an alarming rate in recent decades. It can be found in tropical and sub-tropical climate. In Malaysia, dengue has been declared as one of the national health threat to the public. This study aimed to map the spatial distributions of dengue cases in the district of Hulu Langat, Selangor via a combination of Geographic Information System (GIS) and spatial statistic tools. Data related to dengue was gathered from the various government health agencies. The location of dengue cases was geocoded using a handheld GPS Juno SB Trimble. A total of 197 dengue cases occurring in 2003 were used in this study. Those data then was aggregated into sub-district level and then converted into GIS format. The study also used population or demographic data as well as the boundary of Hulu Langat. To assess the spatial distribution of dengue cases three spatial statistics method (Moran-s I, average nearest neighborhood (ANN) and kernel density estimation) were applied together with spatial analysis in the GIS environment. Those three indices were used to analyze the spatial distribution and average distance of dengue incidence and to locate the hot spot of dengue cases. The results indicated that the dengue cases was clustered (p < 0.01) when analyze using Moran-s I with z scores 5.03. The results from ANN analysis showed that the average nearest neighbor ratio is less than 1 which is 0.518755 (p < 0.0001). From this result, we can expect the dengue cases pattern in Hulu Langat district is exhibiting a cluster pattern. The z-score for dengue incidence within the district is -13.0525 (p < 0.0001). It was also found that the significant spatial autocorrelation of dengue incidences occurs at an average distance of 380.81 meters (p < 0.0001). Several locations especially residential area also had been identified as the hot spots of dengue cases in the district.

A Materialized View Approach to Support Aggregation Operations over Long Periods in Sensor Networks

The increasing interest on processing data created by sensor networks has evolved into approaches to implement sensor networks as databases. The aggregation operator, which calculates a value from a large group of data such as computing averages or sums, etc. is an essential function that needs to be provided when implementing such sensor network databases. This work proposes to add the DURING clause into TinySQL to calculate values during a specific long period and suggests a way to implement the aggregation service in sensor networks by applying materialized view and incremental view maintenance techniques that is used in data warehouses. In sensor networks, data values are passed from child nodes to parent nodes and an aggregation value is computed at the root node. As such root nodes need to be memory efficient and low powered, it becomes a problem to recompute aggregate values from all past and current data. Therefore, applying incremental view maintenance techniques can reduce the memory consumption and support fast computation of aggregate values.