Volume-6 , Issue-2 , Dec 2019, ISSN 2348-635X Go Back

• Open Access   Article

  Strength and Flexural Behavior of Concrete Made With Metakaolin, Copper Slag and Waste Glass Powder

  N. Guruvignesh, K. Priyanka

  Research Paper | Journal-Paper (WAJES)

  Vol.6 , Issue.2 , pp.1-5, Dec-2019

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  In construction industry, consumption of cement and sand is increasing day by day as well as cost is also increasing. So to reduce the consumption of cement and sand, there is a need to replace a part of cement by some pozzolanic material to reduce the consumption of cement and replace apart sand by some silica based materials to control the environmental pollution to some extent. The main focus of this project has been studied that flexural behaviour of concrete made with 15% metakaolin as replacement of cement,100% copper slag as replacement of fine aggregate and 100% waste glass as replacement as fine aggregate. In this project work, an attempt has been made to produce the strength using metakaolin as replacing materials and copper slag , waste glass are as alternate sand. The experimental work carried out and the results obtained are presented and discussed in this report.

  Key-Words / Index Term
  metakaolin,copper slag, pozzolanic, glass powder

  References
  [1].Sivakumar T and Sivaramakrishnan R using copper slag as partial replacement for fine aggregates for experimental investigation on the mechanical properties ofreinforced cement concrete in E-ISSN 2277 - 4106, P-ISSN 2347 – 5161
  [2]. Mali J.R, kirti Gajare, Mrunmayee Patil, Kajal Patil, Latika Pawar, Yashsvini Jadhav using copper slag as fine aggregate for construction materials.Research article vol.issue No.4.
  [3].Deepak.S, Vijay.G, Vinothkumar.R, Gokula kannan.P using glass powder andquartz powder as cement with steel fiber ISSN:0974- 4290,ISSN(Online):2455-9555
  [4].IS 12269.Recommended specification for 53 Grade Ordinary Portlandcement, Bureau ofIndianStandards, New Delhi, India, 1987.
  [5]. IS 383. Recommendedspecification for Coarse and Fine Aggregates from Natural Sourcesfor Concrete, Bureau of Indian Standards, New Delhi, India, 1970.
  [6].IS 10262.Recommended to Concrete Mix Proportions Guide Line, Bureau of Indian standards,New Delhi, India, 2009.
  

  Citation
  N. Guruvignesh, K. Priyanka, "Strength and Flexural Behavior of Concrete Made With Metakaolin, Copper Slag and Waste Glass Powder," World Academics Journal of Engineering Sciences, Vol.6, Issue.2, pp.1-5, 2019

• Open Access   Article

  Development of an Automated Home System with Infrared Sensors

  John Nwankwo Chijioke, Sadiq Thomas

  Research Paper | Journal-Paper (WAJES)

  Vol.6 , Issue.2 , pp.6-11, Dec-2019

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  Recent advances in the field of control systems and information and communications technology have led to the introduction of automation to our homes. This paper presents a simple and inexpensive electronic solution to the challenge of comfort, security and the frequent manual switching of home appliances. The design is broken into two: the first is a passive infrared-based system that triggers an audio visual alarm when motion is detected. The second is an infrared sensor-based system that increments a counter when a person makes an entrance into a room and decrements when an exit is made. The resulting number of people left in the room is displayed on a seven-segment display. As long as the count on the display is one or more, the appliances are turned on. Peripheral Interface Controller microcontroller drives the switching process, through a relay, by comparing the outputs of the infrared receiver pair. The passive infrared sensor used to add security feature to the home system was set to a 3-second delay and 2-meter range to achieve a faster and more efficient response. Costing only NGN 32,120 (about 88 USD), this design is not only comparatively cheaper than other home automation solutions reviewed in this paper but also the most power efficient, with an energy expenditure rate of only 1.41 watts

  Key-Words / Index Term
  Automation, Home Security, Internet of Things, People Counter, Infrared, Microcontroller

  References
  [1] W. Qidwai, "Advances in Information and Communication Technology (ICT):Issues, Challenges and Opportunities for Health Care Professionals," Journal of the College of Physicians and Surgeons Pakistan, vol. 21, no. 11, pp. 651-653, January 2011.
  [2] I. Kaur, "Microcontroller Based Home Automation System With Security," International Journal of Advanced Computer Science and and Application(IJACSA), vol. Vol. 1, no. No. 6, pp. 60 - 65, December 2010.
  [3] B. Faros, "The paradox of automation," Journal of Computing Sciences in Colleges, vol. 31, no. 5, pp. 120-121, May, 2016.
  [4] R. Harper, "Conceptions of the Homes," in Inside The Smart Homes, London, Springer-Verlag Limited, 2014, pp. 22-26.
  [5] Q. Chen, M. Gao, J. Ma, D. Zhang, L. M. Ni and Y. Liu, "MOCUS: moving object counting using ultrasonic," Int. J. Sensor Network, vol. 3, no. I, p. 56, 2008.
  [6] S. Nouwt, B. R. de Vries and D. van der Burgt, "Camera Surveillance in the Netherlands," in Reasonable Expectations of Privacy, The Hague, T.M.C. Asser Press, 2005, pp. 115-165.
  [7] O. F. Ogollah, "Room Occupancy Monitoring and Counting Device," University of Nairobi, Nairobi, 2015.
  [8] A. Choi, "Spirit: A Home Automation System," California Polytechnic State University, California, 2014.
  [9] B. Jaleleddine, "Advance Remote Control Home Appliance Switching System Using Radio Frequency and Bluetooth," International Journal of Scientific Research in Computer Science and Engineering, vol. 4, no. 6, pp. 21-27, 06 Dec, 2016.
  [10] M. M. H. B. A. RANI, "ACTIVE INFRARED MOTION DETECTOR FOR HOUSE SECURITY SYSTEM," UNIVERSITI MALAYSIA , PAHANG.
  [11] O. M. Olalekan, "Individual Control Home Automation System," Federal University of Technology, Akure, Akure, 2009.
  [12] D. Javale, M. Mohsin, S. Nandanwar and M. Shingate, "Home Automation and Security System Using Android ADK," International Journal of Electronics Communication and Computer Technology (IJECCT), vol. 3, no. 2, pp. 1 - 3, March 2013.
  [13] G. Waradkar, H. Ramina, V. Maitry, T. Ansurkar, A. Rawat and P. Das, "Automated Room Light Controller with Visitor Counter," International Journal of Engineering Science and Computing,, vol. Vol. 6, no. 3, pp. 2723 - 2725, March 2016.
  

  Citation
  John Nwankwo Chijioke, Sadiq Thomas, "Development of an Automated Home System with Infrared Sensors," World Academics Journal of Engineering Sciences, Vol.6, Issue.2, pp.6-11, 2019

• Open Access   Article

  Effect of Different Forms of Super Absorbent Polymers on Soil Physical & Chemical Properties in Orchard field

  S.H. Dahri, M.A. Mangrio, I.A. Shaikh, S.A. Dahri, F.V. Steenbergen

  Research Paper | Journal-Paper (WAJES)

  Vol.6 , Issue.2 , pp.12-20, Dec-2019

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  Abstract
  This research aimed to evaluate the effect of different forms of Super Absorbent Polymers (SAP) on soil physical and chemical properties under orchard field condition. Total area under the experiment was divided into twelve plant pits of size 0.46 m × 0.46 m having the depth of 0.60 m, with three replications and four treatments. The treatments were Control, Polymer Water pad, super absorbent polymers (SAP) in Powder form and super absorbent polymers (SAP) in Crystal form. The size of plant pit was set according to the size of polymer water pad. A plastic polythene sheet at a depth of 0.6 meters was given from all the four sides of pits, to prevent the seepage. Water absorbent polymers in powder as well as in crystal forms were mixed with the soil of pit at the rate of 3g/kg of soil. Lemon plants of one year old were transplanted in pits. The samples of soil were taken for physical and chemical properties, before and after applying the treatments. The results reveal that soil bulk density under SAP (Powder) and SAP (Crystal) treatment was reduced thereby soil porosity increased under both treatments while it was unchanged under control and water pad treatments. The field capacity of soil under both treatments was increased as compared to control and water pad treatment. The pH of soil under all treatments was decreased. EC of soil under water pad and SAP (Powder) was increased while there was a minimum increase in EC of soil under Control and SAP (Crystal) treatment. Under water pad and SAP (Powder) treatments, cations (K & Na) and minerals (Ca + Mg) were accumulated. The SAR and ESP of soil under all SAP treatments were increased as compared with control

  Key-Words / Index Term
  Super absorbent polymers, Water saving, Increasing irrigation interval, Increasing crop yield, Increasing soil fertility

  References
  [1] World Bank. “Pakistan: Water Economy Running Dry, Report No. 34081-PK, Agric. and Rural Dev. Unit”, The World Bank, Washington, D.C, 2006.
  [2] Govt. of Pakistan, “Agricultural Statistics of Pakistan 2005-06”, Ministry of Food Agric. and Livestock (Econ. Wing) Islamabad", 2007.
  [3] Wang H.X., C.M Liu, and L. Zhang., “Water-saving agriculture in China: an overview”. Advances in Agronomy, 75, 135–171, 2002.
  [4] Devine D.M. and C.L. Higginbotham, “Synthesis and characterization of chemically Cross linked N-vinyl pyrrolidione (NVP) based hydrogels”. European Polymer Journal, 41, 1272–1279, 2005.
  [5] Fernandez E., D. Lopez-Cabarcos, L.E. & C. Mijangos,. “Viscoelastic and swelling properties of glucose oxidase loaded polyacrylamide hydrogels and the evaluation of their properties as glucose sensors”. Polymer, 46, 2211–2217, 2005.
  [6] Buchholz, F.L, “The structure and properties of superabsorbents polyacrylates. In: F.L. Buchholz and A.T. Graham, editors, Modern superabsorbent polymer technology”. Wiley-VCH, New York. p. 167–221, 1998.
  [7] Burke, D.R., G. Akay, and P.E. Bilsborrow, “Development of novel polymeric materials for agroprocess intensification”. J. Appl. Polym. Sci. 118:3292–3299, 2010. doi:10.1002/app.32640.
  [8] Yu, J., I. Shainberg, Y.L. Yan, J.G. Shi, G.J. Levy, and A.I. Mamedov, “Superabsorbents and semiarid soil properties affecting water absorption”. Soil Sci. Soc. Am. J. 75:2305–2313, 2011. doi:10.2136/sssaj2010.0397.
  [9] Qu, G., and A. Varennes, “Use of hydrophilic insoluble polymers in the restoration of metal-contaminated soils”. Appl. Environ. Soil Sci. 2009:1–8, 2009. doi:10.1155/2009/790687.
  [10] Akhter, J., K. Mahmood, K.A. Malik, A. Mardan, M. Ahmad, and M.M. Iqbal, “Effects of hydro gel amendment on water storage of sandy loam and loam soils and seedling growth of barley, wheat and chickpea”. Plant Soil Environ. 50:463–469, 2004.
  [11] Bai W., H. Zhang, B. Liu, Y. Wu & J. Song, “Effects of super-absorbent polymers on the physical and chemical properties of soil following different wetting and drying cycles”, 2010.
  [12] Busscher, W.J., D.L. Bjorneberg, and R.E. Sojka, ”Field application of PAM as an amendment in deep-tilled US southeastern Coastal Plain soils”. Soil Tillage Res. 104(2):215–220, 2009. doi:10.1016/j.still.2009.02.009.
  [13] Han, Y.G., P.L. Yang, Y.P. Luo, S.M. Ren, L.X. Zhang, and L. Xu, “Porosity change model for watered superabsorbent polymer-treated soil. Environ”. Earth Sci. 61:1197–1205, 2010. doi:10.1007/s12665-009-0443-4.
  [14] Hüttermann, A., M. Zommorodi, and K. Reise, “Addition of hydrogels to soil for prolonging the survival of Pinus halepensis seedlings subjected to drought”. Soil Tillage Res. 50:295–304, 1999. doi:10.1016/S0167-1987(99)00023.
  [15] Abedi-Koupai, J., F. Sohrab, and G. Swarbrick, “Evaluation of hydrogel application on soil water retention characteristics. J. Plant Nutr. 31:317–331, 2008. doi:10.1080/01904160701853928.
  [16] Bhardwaj, A.K., I. Shainberg, D. Goldstein, D.N. Warrington, and G.J. Levy, “Water retention and hydraulic conductivity of cross-linked polyacrylamides in sandy soils”. Soil Sci. Soc. Am. J. 71:406–412, 2007. doi:10.2136/sssaj2006.0138.
  [17] Dorraji, S.S., A. Golchin, and S. Ahmadi, “The effects of hydrophilic polymer and soil salinity on corn growth in sandy and loamy soils”. Clean Soil Air Water 38(7):584–591, 2010.
  [18] Liu, M., R. Liang, F. Zhan, Z. Liu, and A. Niu. “Synthesis of a slow-release and superabsorbent nitrogen fertilizer and its properties”. Polym. Adv. Technol. 17:430–438, 2006. doi:10.1002/pat.720.
  [19] Teodorescu, M., A. Lungu, P.O. Stanescu, and C. Neamţu, “Preparation and properties of novel slow-release NPK agrochemical formulations based on poly (acrylic acid) hydrogels and liquid fertilizers”. Ind. Eng. Chem. Res. 48:6527–6534, 2009. doi:10.1021/ie900254b,
  [20] Agaba, H., L.J.B. Orikiriza, J.F.O. Esegu, J. Obua, J.D. Kabasa, and A. Huttermann, “Effects of Hydrogel Amendment to Different Soils on Plant Available Water and Survival of Trees under Drought Conditions”, Clean– Soil, Air. Water 38:328–335, 2010.
  [21] Banedjschafie, S., and W. Durner, “Water retention properties of a sandy soil with superabsorbent polymers as affected by aging and water quality”. J. Plant Nut. Soil Sci. 178:798–806, 2015.
  [22] Montesano, F.F., A. Parente, P. Santamaria, A. Sannino, and F. Serio, “Biodegradable superabsorbent hydrogel increaseswater retention properties of growing media and plant growth”. Agriculture and Agricultural Science Procedia 4:451–458, 2015. doi:10.1016/j.aaspro.2015.03.052.
  [23] Karimi, A., M. Noshadi, and M. Ahmadzadeh, “Effects of superabsorbent polymer (Igeta) on crop, soil water and irrigation interval”. J. Sci. Technol. Agric. Nat. Res. 12:415–420, 2009.
  [24] Baker, S.W. “The effect of polyacrylamide copolymer on the performance of Lolium perenne L. turf grown a sand root zone”. J. Sports Turf Research Institute 67:66–82, 1991.
  [25] Beniwal, R.S., R. Langenfeld-Heyser, and A. Polle, “Ectomycorrhiza and hydrogel protect hybrid poplar from water deficit and unravel plastic responses of xylem anatomy”. Environ. Exp. Bot. 69:189–197, 2010. doi:10.1016/j. envexpbot.2010.02.005.
  [26] El-Hady, O.A., M.Y. Tayel, and A.A. Lofty, “Super gel as a soil conditioner. II. Its effects on plant growth, enzyme activity, water use efficiency and nutrient uptake”. Acta Hortic. 19:257–266, 1981. doi:10.17660/ActaHortic.1981.119.22.
  [27] Silberbush, M., E. Adar, and Y. De Malach, “Use of a hydrophilic polymer to improve water storage and availability to crops grown in sand dunes I. Corn irrigated by trickling”. Agric. Water Manage. 23:303–313, 1993. doi:10.1016/0378- 3774(93)90042-9.
  [28] Singh, J., “Effect of Stockosorb polymers and potassium levels on potato and onion. J. Potassium Res. 14:78–82, 1998.
  [29] Han, Y.G., P.L. Yang, and L. Xu, “Experimental studies on increase of yield and soil moisture of fruit tree by using superabsorbent polymers”. Sci. Agric. Sin. 38:2486–2491, 2005.
  [30] Viero, P.W.M., K.E.A. Chiswell, and J.M. Theron “The effect of a soil amended hydrogel on the establishment of Eucalyptus grandis clone on a sandy clay loam soil in Zululand during winter”. Southern Afr. For. J. 193:65–75, 2002. doi:10.1080/ 20702620.2002.10433519.
  [31] Yu, J., Shi, J.G., Dang, P.F., Mamedov, A.I., Shainberg, I. and Levy, G.J., “Soil and polymer properties affecting water retention by superabsorbent polymers under drying conditions”. Soil Science Society of America Journal, 76(5), pp.1758-1767, 2012.
  [32] Kahlown M. A., and A. Majeed., "COMSATS 1st meeting on water resources in the south: present Scenario and future proposals", 2001.
  [33] US Salinity Laboratory Staff, “Diagnosis and improvement of saline and alkali soils”. Agric. Handbook No 60, USDA, US Govt Printing Office, Washington DC, 1954.
  [34] Schonfeld MA, Johnson RC, Carver BF, Mornhinweg DW, “Water relations in winter wheat as drought resistance indicator”. Crop Sci., 28: 526-531, 1988.
  [35] Bouyoucos, G.J., Hydrometer method improved for making particle size analyses of soils”. Agronomy journal, 54(5), pp.464-465, 1962.
  [36] Yang, H.S., Liu, R.F., Zhang, J.P. & Wang, A.Q, “Effects of poly (acrylic-acylamide) ⁄ attapulgite superabsorbent composite on soil water content and physical properties”. Journal of Soil and Water Conservation, 19, 38–41, 2005. (In Chinese, with English abstract),
  [37] Veihmeyer, F.J. and Hendrickson, A.H., “The moisture equivalent as a measure of the field capacity of soils”. Soil Science, 32(3), pp.181-194, 1931.
  [38] Cassel, D.K. & Nielsen, D.R.,” Field capacity and available water capacity. In: Methods of soil analysis”. Part 1, 2nd edn (ed.A. Klute), pp. 901–926. Agron. Monogr. 9. ASA and SSSA, Madison, WI, 1986.
  [39] Rowell, D.L., “The preparation of saturation extracts and the analysis of soil salinity and sodicity. soil science methods and applications”. Rowell, editor. UK: Longman Group, 1994.
  [40] Oster, J.D. and Sposito, G., “The Gapon Coefficient and the Exchangeable Sodium Percentage-Sodium Adsorption Ratio Relation”. Soil Science Society of America Journal, 44(2), pp.258-260, 1980.
  [41] Yazdani F., I. Allahdadi, G.A. Akbari, “Impact of superabsorbent polymer on yield and growth analysis of Soybean (Glycine max L.) under drought stress condition”. Pak. J. Biol. Sci., 10: 4190-4196, 2007.
  [42] Tohidi-Moghadam, H.R., Shirani-Rad, A.H., Nour-Mohammadi, G., Habibi, D., Modarres-Sanavy, S.A.M., Mashhadi-Akbar-Boojar, M. and Dolatabadian, A., “Response of six oilseed rape genotypes to water stress and hydrogel application”. Pesquisa Agropecuária Tropical, 39(3), 2009.
  [43] Darb A.M., “The hydraulic properties of a sandy soil treated with gel forming soil conditioner”. Soil Techno 1.9, 15-28, 1996.
  [44] Nazarli, H., Zardashti, M.R., Darvishzadeh, R. and Najafi, S., “The effect of water stress and polymer on water use efficiency, yield and several morphological traits of sunflower under greenhouse condition”. Notulae Scientia Biologicae, 2(4), pp.53-58, 2010.
  [45] Srivastava, R., Awasthi, K. and Tripathi, D., “Nanotechnology towards Sustainable Agriculture”. Nanotechnology, 6(6), pp.155-158, 2018.
  

  Citation
  S.H. Dahri, M.A. Mangrio, I.A. Shaikh, S.A. Dahri, F.V. Steenbergen, "Effect of Different Forms of Super Absorbent Polymers on Soil Physical & Chemical Properties in Orchard field," World Academics Journal of Engineering Sciences, Vol.6, Issue.2, pp.12-20, 2019

• Open Access   Article

  Spatial Variation of Rainfall for Upper Cauvery Karnataka

  Mohammed Badiuddin Parvez, M. Inayathulla

  Research Paper | Journal-Paper (WAJES)

  Vol.6 , Issue.2 , pp.21-29, Dec-2019

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  Abstract
  An attempt has been made to study the variability of seasonal and annual rainfall for a period of 25 years (1991-2015) for the upper Cauvery portion which has five districts. It can be observed that the average annual rainfall for every five years considered range from 800 to 1200mm for more than 45 percent of the area upto 2010 and from 2011-2015 it has been reduced to less than 35 percent and the percentage of area for which the rainfall range was less than 800mm was increased to 28.39 percent which was less than 14 percent from 1991-2010. The maximum portion of the area had average post monsoon rainfall between 100mm to 200mm has been from 1991 to 2010. And from 2011-2016 the maximum portion of the area has a average post monsoon rainfall less than 150mm. Some parts of Hassan, kodagu and chikkamangalore districts portions in the study area has average annual rainfall above 2000mm where as mandya district portion in the study area has annual rainfall less than 800mm and in mysore district average annual rainfall ranges from 800mm to 1500mm

  Key-Words / Index Term
  Average annual, Monsoon, Postmonsoon, Premonsoon, Rainfall variability and Raingauge

  References
  [1] Bell F. C., 1969, “Generalized rainfall-duration-frequency relationship”, ASCE J. Hydraulic Eng., 95, 311–327.
  [2] Bernard, M. M., (1932), “Formulas for rainfall intensities of long durations”. Trans. ASCE 6:592 - 624.
  [3] Chow V.T., D.R. Maidment and L.W.Mays, 1988, “Applied Hydrology”, McGraw- Hill, Chapter 10 – Probability, Risk and Uncertainty Analysis for Hydrologic and Hydraulic Design: 361 – 398.
  [4] M. M. Rashid, 1 S. B. Faruque and 2 J. B. Alam 2012, “Modeling of Short Duration Rainfall Intensity Duration Frequency (SDRIDF) Equation for Sylhet City in Bangladesh.
  [5] Mohammed Badiuddin Parvez, M Inayathulla “Generation Of Intensity Duration Frequency Curves For Different Return Period Using Short Duration Rainfall For Manvi Taluk Raichur District Karnataka”, International Research Journal of Engineering and Management Studies (IRJEMS), Volume: 03 Issue: 04 | April -2019.
  [6] Mohammed Badiuddin Parvez, M Inayathulla “Prioritization Of Subwatersheds of Cauvery Region Based on Morphometric Analysis Using GIS”, International Journal for Research in Engineering Application & Management (IJREAM), Volume: 05 Issue: 01, April -2019.
  [7] Mohammed Badiuddin Parvez, M Inayathulla “Modelling of Short Duration Isopluvial Map For Raichur District Karnataka”, International Journal for Science and Advance Research in Technology (IJSART), Volume: 05 Issue: 4, April -2019.
  [8] Mohammed Badiuddin Parvez, M Inayathulla, "Geomorphological Analysis of Landforms of Upper Cauvery Karnataka India", International Journal of Scientific Research in Multidisciplinary Studies , Vol.5, Issue.10, pp.33-38, 2019.
  [9] Mohammed Badiuddin Parvez, Chalapathi k, Amritha Thankachan, M Inayathulla, " Modelling of Intensity-Duration Frequency curves for Upper Cauvery Karnataka through Normal Distribution", IJITEE, Vol.9, Issue.1, pp.4480-4502, 2019.
  [10] Mohammed Badiuddin Parvez, M Inayathulla, "Multivariate Geomorphometric Approach to Prioritize Erosion Prone Watershed of Upper Cauvery Karnataka", World Academics Journal of Engineering Sciences, Vol.6, Issue.1, pp.7-17, 2019.
  [11] Mohammed Badiuddin Parvez, M Inayathulla, "Assesment of the Intensity Duration Frequency Curves for Storms in Upper Cauvery Karnataka Based on Pearson Type III Extreme Value", World Academics Journal of Engineering Sciences, Vol.6, Issue.1, pp.26-46, 2019.
  [12] Mohammed Badiuddin Parvez, Chalapathi k, Amritha Thankachan, M Inayathulla, " Isopluvial Maps of Daily Maximum Precipitation for Different Frequency for Upper Cauvery Karnataka", Praxis Science and Technology Journal, Vol.8, Issue.10, pp.20-38, 2019.
  [13] Mohammed Badiuddin Parvez, M Inayathulla, "Rainfall Analysis for Modelling of IDF Curves for Bangalore Rural, Karnataka", International Journal of Scientific Research in Multidisciplinary Studies , Vol.5, Issue.8, pp.114-132, 2019
  [14] Mohammed Badiuddin Parvez, and M Inayathulla. " Derivation Of Intensity Duration Frequency Curves Using Short Duration Rainfall For Yermarus Raingauge Station Raichur District Karnataka" International Journal of Innovative Research in Technology Volume 6 Issue 2 July 2019 Page 1-7
  [15] Sherman, C. W. (1931). Frequency and intensity of excessive rainfall at Boston, Massachusetts, Transactions of the American Society of Civil Engineers, 95, pp.951– 960.
  

  Citation
  Mohammed Badiuddin Parvez, M. Inayathulla, "Spatial Variation of Rainfall for Upper Cauvery Karnataka," World Academics Journal of Engineering Sciences, Vol.6, Issue.2, pp.21-29, 2019

• Open Access   Article

  Statical Analysis of Rainfall for Modelling of IDF curves for Upper Cauvery Karnataka by Gumbel’s Distribution

  Mohammed Badiuddin Parvez, M. Inayathulla

  Research Paper | Journal-Paper (WAJES)

  Vol.6 , Issue.2 , pp.30-52, Dec-2019

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  Abstract
  Intensity-duration-frequency (IDF) curves represent the relationship between storm intensity, storm duration and return period. The IDF curves available are mostly done by fitting series of annual maximum rainfall intensity to parametric distributions. Climate change is expected to exacerbate the extremes in the climate variables. Being prone to harsh climate impacts, it is very crucial to study extreme rainfall-induced flooding for short durations over regions that are rapidly growing. One way to study the extremes is by the application of the Intensity-Duration-Frequency (IDF) curves. The annual maximum rainfall intensity (AMRI) characteristics are often used to construct these IDF curves that are being used in several infrastructure designs for urban areas. Thus, there is a need to obtain high temporal and spatial resolution rainfall information. Many urban areas of developing countries lack long records of short-duration rainfall. The shortest duration obtained is normally at a daily scale/24 h. Thus, it is very crucial to find a methodology to construct IDF curves for short-duration rainfall (sub-daily) for these urban areas. The fast extension of urban area that does not have adequate preparedness to cope with climate change is certainly a big risk to life and economy. The study region is Upper Cauvery which lies in Karnataka India. The sub-daily IDF curves for current and future climate for Upper Cauvery were constructed from 1 to 24 h based on the Gumbel’s Distribution approach. Rainfall data of 23 (Twenty three) hydrological years of all stations were used. Maximum rainfall frequency analysis was made by Gumbel’s Distribution method. Finally Equations were developed for different return periods

  Key-Words / Index Term
  Climate change, Gumbel Distribution, Intensity Duration Frequency (IDF), Log Normal Distribution, Normal Distribution, Pearson Type III Distribution, Log Pearson Type III Distribution Rainfall Duration

  References
  [1] Bell F. C., 1969, “Generalized rainfall-duration-frequency relationship”, ASCE J. Hydraulic Eng., 95, 311–327.
  [2] Bernard, M. M., (1932), “Formulas for rainfall intensities of long durations”. Trans. ASCE 6:592 - 624.
  [3] Bhaskar, N. R.; Parida, B. P.; Nayak, A. K. 1997. Flood Estimation for Ungauged Catchments Using the GIUH. Journal of Water Resources Planning and Management., ASCE 123(4): 228-238.
  [4] Chow V.T., D.R. Maidment and L.W.Mays, 1988, “Applied Hydrology”, McGraw- Hill, Chapter 10 – Probability, Risk and Uncertainty Analysis for Hydrologic and Hydraulic Design: 361 – 398.
  [5] M. M. Rashid, 1 S. B. Faruque and 2 J. B. Alam 2012, “Modeling of Short Duration Rainfall Intensity Duration Frequency (SDRIDF) Equation for Sylhet City in Bangladesh.
  [6] Mohammed Badiuddin Parvez, M Inayathulla “Generation Of Intensity Duration Frequency Curves For Different Return Period Using Short Duration Rainfall For Manvi Taluk Raichur District Karnataka”, International Research Journal of Engineering and Management Studies (IRJEMS), Volume: 03 Issue: 04 | April -2019.
  [7] Mohammed Badiuddin Parvez, M Inayathulla “Prioritization Of Subwatersheds of Cauvery Region Based on Morphometric Analysis Using GIS”, International Journal for Research in Engineering Application & Management (IJREAM), Volume: 05 Issue: 01, April -2019.
  [8] Mohammed Badiuddin Parvez, M Inayathulla “Modelling of Short Duration Isopluvial Map For Raichur District Karnataka”, International Journal for Science and Advance Research in Technology (IJSART), Volume: 05 Issue: 4, April -2019.
  [9] Mohammed Badiuddin Parvez, and M .Inayathulla. "Morphometry, Hypsometry Analysis and Runoff Estimation of Aam Talab Watershed Raichur, Karnataka" International Journal Of Advance Research And Innovative Ideas In Education Volume 5 Issue 3 2019 Page 1713-1727
  [10] Mohammed Badiuddin Parvez, and M Inayathulla. "Generation of Short Duration Isohyetal Maps For Raichur District Karnataka" International Journal Of Advance Research And Innovative Ideas In Education Volume 5 Issue 2 2019 Page 3234-3242
  [11] Mohammed Badiuddin Parvez, and M Inayathulla. " Derivation Of Intensity Duration Frequency Curves Using Short Duration Rainfall For Yermarus Raingauge Station Raichur District Karnataka" International Journal of Innovative Research in Technology Volume 6 Issue 2 July 2019 Page 1-7
  [12] Mohammed Badiuddin Parvez, Chalapathi K and M Inayathulla. " Geomorphological Analysis of Two Mini-Watersheds in Raichur City Karnataka" International Research Journal of Engineering and Technology (IRJET) Volume 6 Issue 6 June 2019 Page 2896-2901
  [13] Mohammed Badiuddin Parvez, M Inayathulla, "Geomorphological Analysis of Landforms of Upper Cauvery Karnataka India", International Journal of Scientific Research in Multidisciplinary Studies , Vol.5, Issue.10, pp.33-38, 2019.
  [14] Mohammed Badiuddin Parvez, Chalapathi k, Amritha Thankachan, M Inayathulla, " Modelling of Intensity-Duration Frequency curves for Upper Cauvery Karnataka through Normal Distribution", IJITEE, Vol.9, Issue.1, pp.4480-4502, 2019.
  [15] Mohammed Badiuddin Parvez, M Inayathulla, "Multivariate Geomorphometric Approach to Prioritize Erosion Prone Watershed of Upper Cauvery Karnataka", World Academics Journal of Engineering Sciences, Vol.6, Issue.1, pp.7-17, 2019.
  [16] Mohammed Badiuddin Parvez, M Inayathulla, "Assesment of the Intensity Duration Frequency Curves for Storms in Upper Cauvery Karnataka Based on Pearson Type III Extreme Value", World Academics Journal of Engineering Sciences, Vol.6, Issue.1, pp.26-46, 2019.
  [17] Mohammed Badiuddin Parvez, Chalapathi k, Amritha Thankachan, M Inayathulla, " Isopluvial Maps of Daily Maximum Precipitation for Different Frequency for Upper Cauvery Karnataka", Praxis Science and Technology Journal, Vol.8, Issue.10, pp.20-38, 2019.
  [18] Sherman, C. W. (1931). Frequency and intensity of excessive rainfall at Boston, Massachusetts, Transactions of the American Society of Civil Engineers, 95, pp.951– 960.
  

  Citation
  Mohammed Badiuddin Parvez, M. Inayathulla, "Statical Analysis of Rainfall for Modelling of IDF curves for Upper Cauvery Karnataka by Gumbel’s Distribution," World Academics Journal of Engineering Sciences, Vol.6, Issue.2, pp.30-52, 2019

• Open Access   Article

  Estimation of Household Energy Consumption: A Survey

  R. Nigam, R. Jain, A. Sehgal, R. Maheshwari, P. S. Mehra

  Survey Paper | Journal-Paper (WAJES)

  Vol.6 , Issue.2 , pp.53-63, Dec-2019

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Now-a-days energy consumption has become one of the most studied topics, not just from a climate prospective, but also from technological view of point. The power consumed by millions of household, around the globe, comes majorly from non-renewable sources of energy, which are rapidly depleting. There is an urgent need generating to find ways to effectively consume energy for a sustainable environment. Many researchers have proposed model for Energy Consumption, especially Household sector, to gather different optimized patterns, thus to find solutions to various energy consumption problems. This paper considered various previous works done in the related field, from the year 2010 to 2019, to give a comprehensive study about models applied and dataset used, besides their optimization techniques and results.

  Key-Words / Index Term
  Energy Consumption; Household Energy Consumption; Optimization; Machine Learning Techniques; Survey

  References
  [1] Zhang W, Robinson C, Guhathakurta S, Garikapati VM, Dilkina B, Brown MA, et al. Estimating residential energy consumption in metropolitan areas: A microsimulation approach. Energy 2018;155:162–73. doi:10.1016/j.energy.2018.04.161.
  [2] Bansal A, Rompikuntla SK, Gopinadhan J, Kaur A, Kazi ZA. Energy Consumption Forecasting for Smart Meters 2015.
  [3] Gajowniczek K, Ząbkowski T. Electricity forecasting on the individual household level enhanced based on activity patterns. PLoS One 2017;12:e0174098. doi:10.1371/journal.pone.0174098.
  [4] Mehra PS, Doja MN, Alam B. Stable period enhancement for zonal (SPEZ)-based clustering in heterogeneous WSN. Smart Innov. Syst. Technol., vol. 79, Springer Science and Business Media Deutschland GmbH; 2018, p. 887–96. doi:10.1007/978-981-10-5828-8_83.
  [5] Zhou D, Balandat M, Tomlin C. Residential Demand Response Targeting Using Machine Learning with Observational Data 2016.
  [6] Nishida K, Takeda A, Iwata S, Kiho M, Nakayama I. Household energy consumption prediction by feature selection of lifestyle data. 2017 IEEE Int. Conf. Smart Grid Commun. SmartGridComm 2017, vol. 2018- Janua, Institute of Electrical and Electronics Engineers Inc.; 2018, p. 235–40. doi:10.1109/SmartGridComm.2017.8340676.
  [7] Ziel F. Forecasting Electricity Spot Prices Using Lasso: On Capturing the Autoregressive Intraday Structure. IEEE Trans Power Syst 2016;31:4977–87. doi:10.1109/TPWRS.2016.2521545.
  [8] Mirowski P, Chen S, Kam Ho T, Yu CN. Demand forecasting in smart grids. Bell Labs Tech J 2014;18:135–58. doi:10.1002/bltj.21650.
  [9] Tureczek A, Nielsen P, Madsen H. Electricity Consumption Clustering Using Smart Meter Data. Energies 2018;11:859. doi:10.3390/en11040859.
  [10] Zhou D, Balandat M, Tomlin C. A Bayesian Perspective on Residential Demand Response Using Smart Meter Data 2016.
  [11] Tureczek AM, Nielsen PS. Structured Literature Review of Electricity Consumption Classification Using Smart Meter Data. Citation 2017;10. doi:10.3390/en10050584.
  [12] McLoughlin F, Duffy A, Conlon M. A clustering approach to domestic electricity load profile characterisation using smart metering data. Appl Energy 2015;141:190–9. doi:10.1016/j.apenergy.2014.12.039.
  [13] Van Dam SS, Bakker CA, Van Hal JDM. Home energy monitors: Impact over the medium-term. Build Res Inf 2010;38:458–69. doi:10.1080/09613218.2010.494832.
  [14] Cheung LTO, Chow ASY, Fok L, Yu KM, Chou KL. The effect of self-determined motivation on household energy consumption behaviour in a metropolitan area in southern China. Energy Effic 2017;10:549–61. doi:10.1007/s12053-016-9472-5.
  [15] Anvari-Moghaddam A, Monsef H, Rahimi-Kian A. Optimal smart home energy management considering energy saving and a comfortable lifestyle. IEEE Trans Smart Grid 2015;6:324–32. doi:10.1109/TSG.2014.2349352.
  [16] Liu Y, Yuen C, Yu R, Zhang Y, Xie S. Queuing-Based Energy Consumption Management for Heterogeneous Residential Demands in Smart Grid. IEEE Trans Smart Grid 2016;7:1650–9. doi:10.1109/TSG.2015.2432571.
  [17] Xue J, Ye J, Wang D, Yang B, Zhai J, Liu H. Household energy efficiency management and optimization with energy storage. 2016 IEEE 2nd Annu. South. Power Electron. Conf. SPEC 2016, Institute of Electrical and Electronics Engineers Inc.; 2016. doi:10.1109/SPEC.2016.7846052.
  [18] Cerquitelli T, Chicco G, Di Corso E, Ventura F, Montesano G, Del Pizzo A, et al. Discovering electricity consumption over time for residential consumers through cluster analysis. 2018 14th Int. Conf. Dev. Appl. Syst. DAS 2018 - Proc., Institute of Electrical and Electronics Engineers Inc.; 2018, p. 164–9. doi:10.1109/DAAS.2018.8396090.
  [19] Al-Otaibi R, Jin N, Wilcox T, Flach P. Feature Construction and Calibration for Clustering Daily Load Curves from Smart-Meter Data. IEEE Trans Ind Informatics 2016;12:645–54. doi:10.1109/TII.2016.2528819.
  [20] Elattar EE, Goulermas J, Wu QH. Electric load forecasting based on locally weighted support vector regression. IEEE Trans Syst Man Cybern Part C Appl Rev 2010;40:438–47. doi:10.1109/TSMCC.2010.2040176.
  [21] Eseye AT, Lehtonen M, Tukia T, Uimonen S, John Millar R. Machine learning based integrated feature selection approach for improved electricity demand forecasting in decentralized energy systems. IEEE Access 2019;7:91463–75. doi:10.1109/ACCESS.2019.2924685.
  [22] Yoo SG, Myriam HÁ. Predicting residential electricity consumption using neural networks: A case study. J. Phys. Conf. Ser., vol. 1072, Institute of Physics Publishing; 2018. doi:10.1088/1742-6596/1072/1/012005.
  [23] Edwards RE, New J, Parker LE. Predicting future hourly residential electrical consumption: A machine learning case study. Energy Build 2012;49:591–603. doi:10.1016/j.enbuild.2012.03.010.
  [24] Ozoh P, Abd-Rahman S, Labadin J. Predicting electricity consumption: A comparative analysis of the accuracy of various computational techniques. 2015 9th Int. Conf. IT Asia Transform. Big Data into Knowledge, CITA 2015 - Proc., Institute of Electrical and Electronics Engineers Inc.; 2015. doi:10.1109/CITA.2015.7349819.
  [25] Sun C, Sun F, Moura SJ. Nonlinear predictive energy management of residential buildings with photovoltaics & batteries. J Power Sources 2016;325:723–31. doi:10.1016/j.jpowsour.2016.06.076.
  [26] Li K, Su H, Chu J. Forecasting building energy consumption using neural networks and hybrid neuro-fuzzy system: A comparative study. Energy Build 2011;43:2893–9. doi:10.1016/j.enbuild.2011.07.010.
  [27] Agnetis A, De Pascale G, Detti P, Vicino A. Load scheduling for household energy consumption optimization. IEEE Trans Smart Grid 2013;4:2364–73. doi:10.1109/TSG.2013.2254506.
  [28] Kwac J, Flora J, Rajagopal R. Household energy consumption segmentation using hourly data. IEEE Trans Smart Grid 2014;5:420–30. doi:10.1109/TSG.2013.2278477.
  [29] Zhang XM, Grolinger K, Capretz MAM, Seewald L. Forecasting Residential Energy Consumption: Single Household Perspective. Proc. - 17th IEEE Int. Conf. Mach. Learn. Appl. ICMLA 2018, Institute of Electrical and Electronics Engineers Inc.; 2019, p. 110–7. doi:10.1109/ICMLA.2018.00024.
  [30] Sharma VS, Pamnani RN. International Journal of Computer Science and Mobile Computing EFFECTIVE PREDICTION OF ELECTRICITY CONSUMPTION BASED ON EFFICIENT ANALYSIS OF HOUSEHOLD CHARACTERISTICS. vol. 6. 2017.
  [31] Iwafune Y, Yagita Y, Ogimoto K. Estimation of appliance electricity consumption by monitoring currents on residential distribution boards. 2010 Int. Conf. Power Syst. Technol. Technol. Innov. Mak. Power Grid Smarter, POWERCON2010, 2010. doi:10.1109/POWERCON.2010.5666076.
  [32] Ghofrani M, Hassanzadeh M, Etezadi-Amoli M, Fadali MS. Smart meter based short-term load forecasting for residential customers. NAPS 2011 - 43rd North Am. Power Symp., 2011. doi:10.1109/NAPS.2011.6025124.
  [33] Li Y, Ng BL, Trayer M, Liu L. Automated residential demand response: Algorithmic implications of pricing models. IEEE Trans Smart Grid 2012;3:1712–21. doi:10.1109/TSG.2012.2218262.
  [34] Mehra PS, Doja MN, Alam B. Enhanced Clustering Algorithm based on Fuzzy Logic (E-CAFL) for WSN. Scalable Comput Pract Exp 2019;20:41–54. doi:10.12694/scpe.v20i1.1443.
  [35] Cai H, Shen S, Lin Q, Li X, Xiao H. Predicting the Energy Consumption of Residential Buildings for Regional Electricity Supply-Side and Demand-Side Management. IEEE Access 2019;7:30386–97. doi:10.1109/ACCESS.2019.2901257.
  [36] Bhattacharjee S, Reichard G. Socio-economic factors affecting individual household energy consumption: A systematic review. ASME 2011 5th Int. Conf. Energy Sustain. ES 2011, 2011, p. 891–901. doi:10.1115/ES2011-54615.
  [37] Subbiah R, Pal A, Nordberg EK, Marathe A, Marathe M V. Energy Demand Model for Residential Sector: A First Principles Approach. IEEE Trans Sustain Energy 2017;8:1215–24. doi:10.1109/TSTE.2017.2669990.
  [38] Jain RK, Smith KM, Culligan PJ, Taylor JE. Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy. Appl Energy 2014;123:168–78. doi:10.1016/j.apenergy.2014.02.057.
  [39] Nagpal D, Srivastava R, Mehrotra D, Anuranjana. Feature selection approach for reducing the power consumption for a greener environment. 2nd Int. Conf. Telecommun. Networks, TEL-NET 2017, vol. 2018- January, Institute of Electrical and Electronics Engineers Inc.; 2018, p. 1–5. doi:10.1109/TEL-NET.2017.8343509.
  [40] Amara F, Agbossou K, Dube Y, Kelouwani S, Cardenas A. Estimation of temperature correlation with household electricity demand for forecasting application. IECON Proc. (Industrial Electron. Conf., IEEE Computer Society; 2016, p. 3960–5. doi:10.1109/IECON.2016.7793935.
  [41] Pirbazari AM, Chakravorty A, Rong C. Evaluating Feature Selection Methods for Short-Term Load Forecasting. 2019 IEEE Int. Conf. Big Data Smart Comput. BigComp 2019 - Proc., Institute of Electrical and Electronics Engineers Inc.; 2019. doi:10.1109/BIGCOMP.2019.8679188.
  [42] Masoodian M, Buchwald I, Luz S, André E. Temporal visualization of energy consumption loads using time-tone. Proc. - 2017 21st Int. Conf. Inf. Vis. iV 2017, Institute of Electrical and Electronics Engineers Inc.; 2017, p. 146–51. doi:10.1109/iV.2017.13
  

  Citation
  R. Nigam, R. Jain, A. Sehgal, R. Maheshwari, P. S. Mehra, "Estimation of Household Energy Consumption: A Survey," World Academics Journal of Engineering Sciences, Vol.6, Issue.2, pp.53-63, 2019