Showing 4 results for Spatial Variation
Volume 1, Issue 3 (9-2023)
Abstract
This study focuses on determining the concentration of fluoride ions in selected hand-dug wells and investigating its health implications in Gwagwalada Area Council, Federal Capital Territory, Abuja. The necessity for this investigation arose from observed health issues, including dental and skeletal fluorosis among the residents in the area. Fifteen sampling points (well water sources) were chosen in the study area, and a total of forty-five samples (three per sampling point) were collected. The calorimetric water quality analysis method was employed to analyze these samples in the laboratory. Additionally, the Inverse Distance Weighting (IDW) interpolation method was used to generate a spatial variation map for fluoride ion concentration using ArcMap. The results indicate a concentration range of 0.122 mg/L to 1.910 mg/L across the study area. When compared with the recommendations for fluoride ion concentration in the Nigeria Industrial Standard (NIS) for drinking water (0.1 – 1.0 mg/L), approximately 67% of the sampling points (10 out of 15) fall within the recommended values, while 33% fall outside. The areas with higher fluoride ion concentrations include Dupa 1, Dupa 2, Tunga Maje 1, Tunga Maje 2, and Old Kutunku 2. The study concludes that the observed dental and skeletal fluorosis in these areas can be attributed to the consumption of water with high fluoride concentrations. Consequently, the study recommends increased attention from both local and federal authorities to provide potable water for human consumption in these areas to address the associated health challenges.
Nematollah Mahmoudi, Mohammadreza Ahmadi, Manochehr Babanezhad, Jafar Seyfabadi, Aboulghasem Roohi,
Volume 2, Issue 2 (9-2013)
Abstract
Factors affecting the spatial variations of water quality of the Mazandaran coastal ecosystem was determined in summer 2012. For this purpose, water quality parameters (nutrients, temperature, conductivity, salinity, dissolved oxygen, pH, chlorophyll α and turbidity) were evaluated along 4 transects (Amirabad, Babolsar, Noshahr and Ramsar) in the depths of 5, 10, 20 and 50m, using multivariate analysis methods. Based on the cluster analysis of data, the sampling sites could be classified into 5 distinct groups, including 35-50m water layer of station 50m in all transects, 0-5m layer in station 5m in all transects, Ramsar transect and the majority of surface and bottom layers of 3 transects including Noshahr, Babolsar and Amirabad. Based on discriminant analysis, 86.40% of the sampling sites were correctly classified. Factor analysis explained 87.53% of the total variance, the five principal components of which (viz. temperature, turbidity, nitrate, silica and ammonium) were considered as the most effective parameters on the spatial variation of water quality. This study suggests that the number of sampling locations can be reduced to two transects. Thermocline, transport of nutrients (specially phosphorus and ammonium) from rivers, sea floor, cage culture and the ctenophore, M. leidyi, were the most effective sources on spatial variations of water quality. Moreover, the multivariate statistical methods were found to be useful tools to recognize the spatial variations pattern along the Mazandaran coasts in summer.
Volume 11, Issue 4 (12-2011)
Abstract
One of the main distinctions between geomaterials and other engineering materials is the
spatial variation of their properties in different directions inside them. This characteristic of
geomaterials (so- called as heterogeneity) is studied herewith. Almost all natural soils are
highly variable in their properties and rarely homogeneous. Soil heterogeneity can be
classified into two main categories. The first is lithological heterogeneity, which can be
manifested in the form of thin soft/stiff layers embedded in a stiffer/softer media or the
inclusion of pockets of different lithology within a more uniform soil mass. The second
source of heterogeneity can be attributed to inherent spatial soil variability, which is the
variation of soil properties from one point to another in space due to different deposition
conditions and different loading histories. Inherent spatial variability of geomaterials is itself
devided into the random component, which is attributed to different depositioaln conditions,
and the deterministic trends, which are attributed to the variation in soil properties, such as
increase in soil strength with depth due to increase in confining pressure.
Different elements of soil inherent spatial variability such as mean, variance, and spatial
correlation characteristics were introduced with the main focus on the importance of spatial
correlation distane and the way to handle it. Several spatial distributions introduced to
describe the probabilistic variation of geotechnical properties of soils. Among all, absolute
normal distribution was adopted as appropriate distribution, which best presents these
properties in horizontal direction.
Variation of geotechnical parameters in vertical direction is, however, conceived to follow a
deterministic trend. Using random field theory, local average subdivisions (LAS) formulation
and MATLAB Mathworks, virtual data with different correlations was produced, and by
employing autocorrelation function, a trend for this function was invoked for different
predetermined values of the scale of fluctuations. It was found that autocorrelation function
has a deterministic trend as far as the scale of fluctuation has not been exceeded. It is clearly
concluded that, for distances farther than the specific scale of fluctuation, the behavior is
chaotic and this can be an index to calculate the scale of fluctuation of the experimental data.
Volume 21, Issue 5 (11-2021)
Abstract
It is vital to consider the spatial variations of ground motions in the design of extended structures and long bridges. In this paper, the effect of spatial variations of ground motions and local site conditions on the response of
non-uniform column heights bridge is studied. To generate non-uniform accelerometers of ground motion, a simulated algorithm based on the spectrum design with unstable multivariate random process functions and a spectral density matrix is used. Accelerometers were generated with a coherence function including the effect of wave propagation and the duration of the earthquake that is consistent with the selected response spectrum. In addition, the simulation is performed in 800 time intervals with a time step of 0.025 seconds. The maximum ground acceleration is assumed 0.35 g. The response of the bridge with a length of about 242 m with 5 spans under the effect of uniform and non-uniform accelerometers was investigated by nonlinear time history analysis in OpenSees program. The local site effect was assumed by changing soil type (soil under the two piers is softer than the other piers) and apparent wave velocity under different bridge piers. The apparent velocity of the wave propagation of the soft soil assumed 1000 m/s and for the hard soil 2000 m/s. To verify the acceleration of the generated accelerograms, the generated spectrum is compared with the Eurocode design spectrum, and to validate the analysis performed on the bridge, the ratio of M/
calculated and compared with ratio that calculated by Shinozaka and Deodatis. In this paper variations of axial force, shear force and bending moments in bridge piers in different positions were studied as comparison criteria. The results showed that the simultaneity of spatial variations of ground motions and changes in the soil conditions causes a significant increase in the bridge response. Comparison of the results in the two input cases of uniform and non-uniform spatial variations of ground motions shows that the properties of spatial variations of earthquake motions can affect the response of the bridge. The results are compared based on the ratio of the maximum stress created at the base in the non-uniform excitation state to the maximum created in the uniform excitation state or the ratio of the maximum stress created at the base in the variable soil to the same soil. Based on the presented results, it was observed that the maximum bending moments in variable soil conditions can be increased to about
2.5 times to the maximum created in the same soil condition in the piers and also the maximum axial force created in the two shorter piers in the non-uniform excitation state is up to 2 times larger than in the uniform excitation state, and if the effect of different soils is applied to the two middle piers, the axial force in the middle two piers can be increased up to 3 times. Based on the obtained results, it is observed that the maximum shear force created in the direction of the transverse axis in the two middle piers occurred in a situation where non-uniform excitation coincides with the change of soil conditions under the piers and the bending moment in the direction of the transverse axis in the piers in this case has increased up to 120%.
