Series-1 Nov. – Dec. 2021 Issue Statistics
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Abstract: This study involves a pre-construction investigation to characterise the subsurface lithology and recommend an appropriate foundation design for a one-storey building in a marginal land of the south-western Niger Delta. The soil investigation results indicate a dark-grey peat layer existing from top to a depth of 4.5 m, followed by a soft-greyish organic clay occurs to a depth of 12 m. This clay has an undrained shear strength between 21.17 – 22.52 KN/m2, coefficient of permeability between 1.2 x 10-6 - 1.85 x 10-8 cm/sec, coefficient of compressibility between 24.34 – 25.28 m2/MN, and the coefficient of consolidation 0.94 – 1.45 m2/yr indicating low permeability and moderately to low compressibility........
Keyword: Southwestern Niger Delta, Marginal Lands, Pile Foundation Design, Building Load, Vertical Stress, Bearing Capacities, Total Settlement, Rate of Settlement
[1]. Abam TKS, Okogbue CO (1993) Utilisation of marginal lands for construction in the Niger Delta. Bulletin of the International Association of Engineering Geology 48: 5-14
[2]. Amadi, A.N. (2009) A review of the causes of building failure in Nigeria with emphasis on the role of a Geologist. NMGS 45Th Annual international conference, Owerri, book of Abstract, p 101.
[3]. Amadi AN, Eze CJ, Igwe CO, Okunlola IA, Okoye NO (2012) Architect's and geologist's view on the causes of building failures in Nigeria. Mod Appl Sci 6: 31-38.
[4]. American Society for Testing of Materials (1997). Annualbook of ASTM standards, Vol. 04.08, Conshoshocken, Pa.
[5]. Bowles, J.E. (1977), Foundation Analysis and Design. 2nd Edition. McGraw-Hill Book Company, New York., 750 pages.
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Abstract: Geophysical survey using two dimensional resistivity methods was undertaken to investigate the causes of pavement failure along the Ikot Ekpene - Umuahia road. The study was centered on some perennial failed parts of the road namely Ariam, Awomnkwu, Ekebedi Oboro, Ogbubule Oboro, Okwe-ukwu Oboro, Ndoro Oboro, Umudike,Ahiaeke Ndume, Ehimiri using subsurface electrical method, which reveals the subsurface geology( lithology) at each location after interpretation. Abem Terrameter SAS 1000 was employed and the apparent resistivity values were used. The lithology of the subsurface reveals that their resistivity falls between >83Ωm to 103Ω. The geoelectric zones constructed from the VES resistivity structures shows that the pavement segments were founded on a shallow basement near low resistive layer bereft of vital geological features. This made it impossible for the pavement to withstand stress as a result of load from road users.
Keywords :- Geophysical survey, Pavement failure, ABEM Terrameter, Lithology, Thickly low resistivity layer.
[1]. Adegoke - Anthony, W.C. and Agada, O.A. 1980. Geotechnical characteristics of some residual soils and their implications on road design in Nigeria. Technical Lecture. Lagos, Nigeria. P. 1 – 16.
[2]. Adeyemo, I.A. and Omosuyi, G.A. 2012. Geophysical Investigation of Road Pavement Instability along Akure Owo express way, South Western Nigeria. American Journal of Research. 3(4), P.191-197.
[3]. Agwae, G. O., Geology, geochemistry and industrial potentials of marble deposits in Igarra Area, Southwestern Nige- ria 2011.University of Nigeria Nsukka, An Unpublished M.Sc Thesis.
[4]. Aigbedion, I. 2007. Geophysical Investigation of Road Failure Using Electromagne-tic Profile along Opoji Uwelench and Illeh in Ekpoma, Nigeria.
[5]. Aigbedion, I., "Geological and geophysical evidence for the road failures in Edo state, Nigeria". Environmental Geology, 2007. Berlin, pp 101- 103
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Abstract: The spectral signatures of various igneous rocks were studied using histograms of satellite images and digital photographs of hand specimen of rocks. Comparison of histogram of digital image of hand specimen of a known rock was done with satellite image of a terrain of known geographical location and the igneous rocks were identified on the basis of similarity of image histograms. It was found on the basis of study of histograms of gabbro, granite, basalt and rhyolite that the shape of histogram of images cropped from Google Earth and those from images of hand specimens of known rocks and photographs of glazed rocks taken from internet were showing high degree of resemblance.
Keywords : Image histogram, Digital image histogram, Igneous rock, Identification of Rocks
[1]. Blaschke, T., 2010: Object based image analysis for remote sensing. ISPRS journal of photogrammetry and remote sensing, 65 (1), 2-16.
[2]. Burger, W. & Burge, M.(2008) Digital Image Processing ~ Processing – An Algorithmic Introduction using Java Springer-Verlag, New York
[3]. Guangpeng Fan, FeixiangChen,Danyu Chen, Yan Li,and Yanqi Dong.(2020).A Deep Learning Model for Quick and Accurate Rock Recognition with Smartphones.Mobile Information Systems Volume 2020, Article ID 7462524, 14 pages https://doi.org/10.1155/2020/7462524.
[4]. https://crisp.nus.edu.sg/~research/tutorial/tmp/image.htm
[5]. https://geology.com/rocks/basalt.shtml
