Geopathic Stress: A Possible Cause for Pavement Distresses and Road Accidents
Salgude Rohit1, Pimplikar Sunil2, Sonawane Gaurav3
1Salgude Rohit*, Rsearch Scholar, Civil Engineering Department, MIT, Pune, Savitribai Phule Pune University, Pune, India.
2Pimplikar Sunil Professor and Head of Civil Engg. Department, MIT, Pune, Savitribai Phule Pune University, Pune, India.
3Sonawane Gaurav, Master of Technology (Civil and Environmental Technology) student at Department of Technology, Savitribai Phule Pune University, Pune, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 30, 2020. | Manuscript published on April 10, 2020. | PP: 850-854 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3991049620/2020©BEIESP | DOI: 10.35940/ijitee.F3991.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: India loses 3% of its GDP due to road accidents. Significance of Geopathic stress as a causative factor of road accidents has been studied by few researchers; however its effect on Pavement distresses and hence road accident is yet unexplored. The aim of this research is to determine the correlation between average number of accidents, Pavement Condition Index (PCI) values and Geopathic stress. Accident data was collected from Pune traffic department for 3 years period from 2015-16 to 2017-18. Based on the number of accidents during this period accident blackspots were found. On each black spot pavement distresses survey was carried out and its condition was analyzed by Indian Road Congress (IRC) 82:2015 code method. At these accident blackspots detection of geopathic stress was done by using 2 copper L-rods, lecher antenna. Intensity was measured in terms of electrical and magnetic field. Electrical field reading was measured using Esmog-spion and magnetic field reading was measured by magnetometer. Data was analyzed using Karl Pearson’s correlation coefficient and a linear regression model is developed for average number of road accidents (Ā) with Pavement Condition Index (PCI). Utility of the equation is for forecasting the number of fatal accidents at similar black spots based on their pavement distress condition. A further attempt is to investigate the effect of electric and magnetic characteristics of geopathic stress on road accidents.
Keywords: Accident Blackspots, Geopathic Stress, Magnetic Field, Electrical Field, Pavement Distresses, Pavement Condition Index.
Scope of the Article: Refrigeration and Air Conditioning