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i-manager's Journal on Future Engineering and Technology (JFET)

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Biomaterial Strategies for Immune System Enhancement and Tissue Healing
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Volume 14 Issue 1 August - October 2018

Article

The Evolution of 3D printing and Industry 4.0

Gisli Thorsteinsson* , Tom page**

* Professor, Department of Design and Craft Education, University of Iceland, Iceland.

** Associate Professor, Department of Product Design, Nottingham Trent University, England.

Thorsteinsson, G. and Page, T. (2018). The Evolution of 3D printing and Industry 4.0.i-manager’s Journal on Future Engineering and Technology,14(1), 1-15.
https://doi.org/10.26634/jfet.14.1.14600

Abstract

3D printing is increasingly gaining public interest. As its popularity rises, more stories are released in support of the technology with many predicting that it will revolutionise the way people work and live. However, there is an argument that its future may be over exaggerated. The purpose of this paper is to assess a hypothetical future dominated by 3D printing. To achieve this, various areas are considered. Firstly, the implications of Industry 4.0 are discussed, this being integral to the rise of 3D printing. It is hoped that, through understanding Industry 4.0, more accurate predictions can be made on 3D printing's future. In this essay 3D printing is examined through assessing the limitations and applications that the technology currently possesses, as well as, the future applications many predict. This, combined with detailed interviews with various members of the design community, helps to highlight any weaknesses in the technology giving a more accurate portrayal of the true future of 3D printing.

References

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[2]. Atkeson, A., & Kehoe, P. J. (2001). The Transition to a New Economy after the Second Industrial Revolution. Working Paper No. 8676. Cambridge, MA: National Bureau of Economic Research, 2001.

[3]. Birtchnell, T. (2016). A New Industrial Future? Abingdon: Routledge.

[4]. Blackman, J. (2014). The 1^stAmendment, 2^nd Amendment and 3D Printed Guns. Tennessee Law Review, 81(2), 479-929.

[5]. Brynjolfsson, E. (2013a). Labour Productivity in Two Erras [digital image]. TED. [Accessed 19 January 2018].

[6]. Brynjolfsson, E. (2013b). The Great Decoupling. New Perspectives Quarterly, 30(1), 61-63.

[7]. Brynjolfsson, E., & McAfee. A. (2012). Race Against the Machine: How the Digital Revolution is Driving Productivity, Accelerating Innovation, and Irreversibly Changing Employment and the Economy. Lexington: Digital Frontier Press.

[8]. Brynjolfsson, E., McAfee, A., & Manyika, J. (2016). Will Your Job Disappear? New Perspectives Quarterly, 31(2), 74-77.

[9]. Courtland, R. (2013). MakerBot's founder is on the edge of the 3-D printing revolution. IEEE Spectrum [online], 50(7), pp. 21-22.

[10]. Formlabs. (2018). Form2 3D Printer [digital image]. Formlabs. [Accessed 2 February 2018].

[11]. Goldstein T. A., Epstein, C. J., Schwartz, J., Krush, A., Lagalante, D. J., Mercadante, K. P., Zeltsman, D., Smith, L. P., & Grande, D. A. (2016). Feasibility of Bio-printing with a Modified Desktop 3D Printer. Tissue Engineering, 22(12), 1071-1076.

[12]. Goldstein, T., Smith, L., Grande, D., & Zeltsman, D. (2014). 286Integrating Biodegradable 3D-Bio-Printing Technology into Tracheal Reconstruction. Interactive Cardio Vascular and Thoracic Surgery, 19(1), S86.

[13]. Gordan, R. J. (2016a). The Rise and Fall of American Growth: The U.S. Standard of Living since the Civil War. New Jersey: Princeton University Press.

[14]. Gordon, R. J. (2016b). Perspectives on the Rise and Fall of American Growth. American Economic Review, 106(5), pp. 72-76.

[15]. Graham, A. D., Olof, S. N., Burke, M. J., Armstrong, J. P., Mikhailova, E. A., Nicholson, J. G., Box, S. J., Szele, F. G., Perriman, A. W., & Bayley, H. (2017). High-Resolution Patterned Cellular Constructs by Droplet-Based 3D Printing. Scientific Reports, 7(1), 1-11.

[16]. Hanson, M. (2018). The 10 best 3D printers of 2018 [online]. TechRadar News: TechRadar. [Accessed 1 February 2018].

[17]. Home, R., & Hausman, K. (2017). 3D Printing for Dummies. New York: John Wiley & Sons, Inc.

[18]. Kennedy, E. J., & Giampetro-Meyer, A. (2015). Gearing up for the next industrial revolution: 3d printing, home-based factories, and modes of social control. Chicago Law Journal, 46(4), 955-988.

[19]. Kirkpatrick, K. (2017). 3D-Printing Human Body Parts. Association for Computing Machinery, 60(10), 15-17.

[20]. Lasi, H., Fettke, P., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering,6(4), 239-242.

[21]. Lipson, H., & Kurman, M. (2013). Fabricated: The New World of 3D Printing. Indianapolis: John Wiley & Sons, Inc.

[22]. Little, R. K. (2014). Guns don't kill people, 3D printing does? Hasting Law Journal, 65(6), 1505-1513.

[23]. Murphy, S. V., & Atala, A. (2014). 3D bio-printing of tissues and organs. Nature Biotechnology, 32(8), 773-786.

[24]. Noorani, R. (2017). 3D Printing: Technology, Applications, and Selection. Florida: CRC Press.

[25]. O'Connor, A. (2013). Don't shun 3D printers – they might save your life one day. Manufacturers Monthly [online], (July). [Accessed 1 February 2018]

[26]. Pettis, B., France, A. K., & Shergill, J. (2012). Getting Started with MakerBot. New York: O'Reilly Media, Inc.

[27]. Popescu, A. (2016). Cody Wilson: The man who wants Americans to print their own 3D guns. The Guardian [online], 12 June. [Accessed 1 February 2018]

[28]. Roopavath, U. K., & Kalaskar, D. M. (2017). 3D Printing in Medicine. London: Woodhead Publishing.

[29]. Russman, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P., & Harnisch, M. (2015b). Industry 4.0: How Intelligent Machines will Transform Everything we Know. Boston: Boston Consulting Group.

[30]. Russmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P., & Harnisch, M. (2015a). Industry 4.0: The future of productivity and Growth in Manufacturing Industries. Boston Consulting Group.

[31]. Savini, A., & Savini, G. G. (2015). A short history of 3D printing, a technological revolution just started. In History of High-Technologies and their Socio-Cultural Contexts Conference (HISTELCON), 2015 ICOHTEC/IEEE International (pp. 1-8). IEEE.

[32]. Shewbridge, R., Hurst, A., & Kane, S. K. (2014). Everyday making: Identifying future uses for 3D Printing in the Home. Proceedings of the 2014 Conference on Designing Interactive Systems, ACM (pp. 815-824).

[33]. Stratasys, (2018). MakerBot Replicator [digital image]. MakerBot. [Accessed 2 February 2018].

[34]. Todd, I. (2017). Metallurgy: No more tears for metal 3D printing. Nature [online], 549 (7672), pp. 342-343. [Accessed 31 January 2018]

[35]. Wang, S., Zhang, D. Li, D., & Zhangm, C. (2016). Towards smart factory for industry 4.0: A self-organized multi-agent system with big data based feedback and coordination. Computer Networks, 101(1), 158-168.

[36]. Zontek, T. L., Ogle, B. R., Jankovic, J. T., & Hollenbeck, S. M. (2017). An exposure assessment of desktop 3D printing. Journal of Chemical Health and Safety, 24(2), 15-25.

[37]. Zusha, E. (2018). U.S News: Market Emerges for 'Ghost th Guns'. Wall Street Journal, 4 of January. [Accessed 1 February 2018]

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Research Paper

Performance Analysis of Humidification-Dehumidification Desalination Processes

Giuma M. Fellah*

*Professor, Department of Mechanical and Industrial Engineering, Faculty of Engineering, University of Tripoli, Libya.

Fellah, G. (2018). Performance analysis of humidification-dehumidification desalination processes.i-manager’s Journal on Future Engineering and Technology,14(1), 16-25. https://doi.org/10.26634/jfet.14.1.14596

Abstract

The processes of humidification and dehumidification (HD) are based on the fact that air can be mixed with quantities of vapor. When airflow is in contact with salt water, air extracts a certain quantity of vapor. On the other hand, the distilled water is recovered by maintaining the humid air in contact with cooling surfaces. A wide range of thermal energy including solar, geothermal, exhaust gases, and fossil fuel may be used to operate HD desalination systems. These systems are suitable for arid areas, and when the demand for fresh water is decentralized. In the present work, the influence of the feed salinity and air flow rate on the thermodynamic performance is analyzed. It is found that both the performance ratio and the productivity decreases with the increase in the salinity of the feed water. A parametric study is performed to find the effect of the air flow rate on the productivity and the performance ratio of the system. It is found that both the productivity and the performance ratio decreases with the increase in the air flow rate.

References

[1]. Ahmed, H. A., Ismail, I. M., Saleh, W. F., & Ahmed, M. (2017). Experimental investigation of humidification- dehumidification desalination system with corrugated packing in the humidifier. Desalination, 410, 19-29.

[2]. Akhatov, Z. S., Khalimov, A. S., & Saidov, K. K. (2016). A study of the influence of inlet air flow humidity and temperature on thermal efficiency of an evaporation chamber of a solar desalination plant. Applied Solar Energy, 52(2), 109-114.

[3]. Bourouni, K., Chaibi, M. T., & Tadrist, L. (2001). Water desalination by humidification and dehumidification of air: State of the art. Desalination, 137(1-3), 167-176.

[4]. Cheng, H., & Shichang, W. A. N. G. (2007). Modelling and experimental investigation of humidification-dehumidification desalination using a carbon-filled-plastic shell-tube column. Chinese Journal of Chemical Engineering, 15(4), 478-485.

[5]. El-Haroun, A. A. (2013). Desalination system with Humidification-Dehumidification of air. International Journal of Pure and Applied Sciences and Technology, 14(1), 44-52.

[6]. Elhenawy, Y., Elkader, M. A., & Moustafa, G. H. (2015). A Theoretical Model for a Humidification Dehumidification (HD) Solar Desalination Unit. World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, 9(6), 646-655.

[7]. ElKader, M. A., Aref, A., Moustafa, G. H., & ElHenawy, Y. (2014). A theoretical and experimental study for a Humidification-Dehumidification (HD) solar desalination unit. International Journal of Water Resources and Arid Environments, 3(2), 108-120.

[8]. Ghalavand, Y., Hatamipour, M. S., & Rahimi, A. (2014). Humidification compression desalination. Desalination, 341, 120-125.

[9]. Ghalavand, Y., Hatamipour, M. S., & Rahimi, A. (2016). Performance evaluation of humidification-compression desalination. Desalination and Water Treatment, 57(33), 15285-15292.

[10]. Gude, V. G., & Nirmalakhandan, N. (2008). Desalination using low-grade heat sources. Journal of Energy Engineering, 134(3), 95-101.

[11]. Hamad, A., & Abdul-Karim, M. (2005). Desalination using ambient air: Simulation and energy optimization. Desalination, 175(3), 247-257.

[12]. Kabeel, A. E., Hamed, M. H., Omara, Z. M., & Sharshir, S. W. (2013). Water desalination using a humidification-dehumidification technique—a detailed review. Natural Resources, 4(03), 286-305.

[13]. Karhe, Y. B., & Ahmad, M. A. N. (2014). A review of solar-driven desalination system using Humidification- Dehumidification process. IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE), 71-75.

[14]. Parekh, S., Farid, M. M., Selman, J. R., & Al-Hallaj, S. (2004). Solar desalination with a humidification-dehumidification technique—a comprehensive technical review. Desalination, 160(2), 167-186.

[15]. Perret, J. S., Al-Ismaili, A. M., & Sablani, S. S. (2005). Humidification-dehumidification system in a greenhouse for sustainable crop production. In Proc., Ninth International Water Technology Conference (pp. 849-862).

[16]. Rajaseenivasan, T., & Srithar, K. (2017). Potential of a dual purpose solar collector on humidification dehumidification desalination system. Desalination, 404, 35-40.

[17]. Shalaby, S. M., Bek, M. A., & Kabeel, A. E. (2017). Design recommendations for humidification- dehumidification solar water desalination systems. Energy Procedia, 107, 270-274.

[18]. Sharshir, S. W., Peng, G., Yang, N., El-Samadony, M. O. A., & Kabeel, A. E. (2016a). A continuous desalination system using humidification–dehumidification and a solar still with an evacuated solar water heater. Applied Thermal Engineering, 104, 734-742.

[19]. Sharshir, S. W., Peng, G., Yang, N., Eltawil, M. A., Ali, M. K. A., & Kabeel, A. E. (2016 b). A hybrid desalination system using humidification-dehumidification and solar stills integrated with evacuated solar water heater. Energy Conversion and Management, 124, 287-296.

[20]. Siddiqui, F. R., Elminshawy, N. A., & Addas, M. F. (2016). Design and performance improvement of a solar desalination system by using solar air heater: Experimental and theoretical approach. Desalination, 399, 78-87.

[21]. Yassin, J. S. & Sawalem, M. M. (2015). Performance evaluation of a solar Humidification – Dehumidification Desalination Unit. The International Journal of Engineering and Information Technology (IJEIT), 1(2), 15-22.

[22]. Zhang, L., & Cheng, G. (2009, March). A new process of solar desalination based on humidificationdehumidification cycle. In Proceedings of the International Multi Conference of Engineers and Computer Scientists (Vol. 2, pp. 18-20).

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Research Paper

Design of Optimum Number of Rain Gauge Network Over Sabarmati River Basin

Anant D. Patel*

*Assistant Professor, Department of Civil Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India.

Patel, A. D. (2018). Design of Optimum Number of Rain Gauge Network Over Sabarmati River Basin.i-manager’s Journal on Future Engineering and Technology,14(1), 26-31. https://doi.org/10.26634/jfet.14.1.14207

Abstract

Rainfall is the most important and an essential natural source of water, which is utilized for different purposes.Hydrological analysis and modelling becomes very popular in the field of water resources management. Rain gauge is a common instrument that is used to measure the amount of rainfall and it also provides the rainfall distribution pattern.These data prove to be very useful and can be used for different purposes, such as design of hydraulic structures, flood control, irrigation canal design, etc. Thus, rainfall data are prime input parameter and it is most critical for a river basin to have an optimum number of rain gauges in catchment area of the river. This paper has basically analyzed whether the Sabarmati River basin has an optimum number of rain gauges or not. If not then design of optimum number of rain gauge is an important task in the river basin. Thus, according to IS:4987-1994, Optimum number of rain gauges in Sabarmati river basin is 37, while existing rain gauges are 31. So, Additional 6 rain gauges are required in basin and their location is also proposed in this paper based on Thiessen polygon method, which is used for equal areal rainfall distribution in the basin.

References

[1]. Adhikary, S. K., Yilmaz, A. G., & Muttil, N. (2015). Optimal design of rain gauge network in the Middle Yarra River catchment, Australia. Hydrological Processes, 29(11), 2582-2599.

[2]. Al-Aboodi, A. H. D., & Al-Abadi, A. M. (2014). Optimum rain-gauges network design of some cities in Iraq. Journal of University of Babylon, 22(4), 946-958.

[3]. Bureau of Indian Standards. (1994). Recommendations for establishing net work of rain-gauge stations (IS 4987:1994). New Delhi, India.

[4]. Cheng, K. S., Lin, Y. C., & Liou, J. J. (2008). Rain-gauge network evaluation and augmentation using geostatistics. Hydrologic Process, 22(14), 2554-2564.

[5]. Patel, A. D., Dholakia, M. B., Patel, D. P., Prakash, I., & Mahmood, K. (2016). Analysis of optimum number of rain gauge in Shetrunji River Basin, Gujarat-India. International Journal of Science Technology & Engineering, 2(11), 380- 384.

[6]. Putthividhya, A., & Tanaka, K. (2012). Optimal rain gauge network design and spatial precipitation mapping based on geostatistical analysis from colocated elevation and humidity data. International Journal of Environmental Science and Development, 3(2), 124-129.

[7]. Sen, D. (2013). Real-time rainfall monitoring and flood inundation forecasting for the city of Kolkata. ISH Journal of Hydraulic Engineering, 19(2), 137-144.

[8]. Tsintikidis, D., Georgakakos, K. P., Sperfslage, J. A., Smith, D. E., & Carpenter, T. M. (2002). Precipitation uncertainty and rain-gauge network design within Folsom Lake watershed. Journal of Hydrologic Engineering, 7(2), 175-184.

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Research Paper

Clustering Technique to Threshold Vegetation Indices and Gap Detection in Hazaribagh Wildlife Sanctuary, Jharkhand (India)

Saurabh Kumar Gupta* , A. C. Pandey**

* PhD Scholar, Center for Land Resource Management, Central University of Jharkhand, India.

** Professor, Center for Land Resource Management, Central University of Jharkhand, India.

Gupta, S. K. and Pandey, A. C.(2018). Clustering Technique to Threshold Vegetation Indices and Gap Detection In Hazaribagh Wildlife Sanctuary, Jharkhand (India).i-manager’s Journal on Future Engineering and Technology,14(1), 32-41. https://doi.org/10.26634/jfet.14.1.15257

Abstract

The K means clustering was processed for threshold vegetation indices and gap detection. It was processed for retrieving the vegetation index value that represents forest land cover, percentage vegetation coverage, and canopy density. The method was further used for finding the probability distribution of forest canopy gaps in the forest. The result was tested in the Hazaribagh Wildlife Sanctuary, Jharkhand, India. The percentage vegetation cover was calculated in the new SNAP software. The canopy density was mapped through FCD model. From the analysis, it was estimated that the dense forest having greater than 70% of canopy density comprises 64-100% of vegetation cover; moderately dense forest having 40-70% canopy density includes 21-64% of vegetation cover, and open forest having less than 40% canopy density have 7-21% of vegetation cover. The Normalized Vegetation Index (NDVI) and Transformed Vegetation Index (TVI) considered being more efficient and Difference Vegetation Index (DVI) was less efficient for forest vegetation cover and density measurement. Inversely, it was observed that DVI was more efficient in finding gaps in the forest. The method was also functional for finding the probability distribution of canopy gaps in the forest. This clustering technique can be applied in other means for forest landscape level assessment.

References

[1]. Addabbo, P., Focareta, M., Marcuccio, S., Votto, C., & Ullo, S. L. (2016). Contribution of Sentinel-2 data for applications in vegetation monitoring. Acta Imeko, 5(2), 44-54.

[2]. Baret, E., Guyot, G., Begue, A., Morel, P., & Podaire, A. (1986). Etude de la complémentarité du moyen infrarouge avec le visible et le proche infrarouge pour le suivi de la végétation. Spectral Signatures of Objects in Remote Sensing, 409-412.

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[5]. Conrad, O., Bechtel, B., Bock, M., Dietrich, H., Fischer, E., Gerlitz, L., ... & Böhner, J. (2015). System for automated geoscientific analyses (SAGA) v. 2.1. 4. Geoscientific Model Development, 8(7), 1991-2007.

[6]. Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., ... & Meygret, A. (2012). Sentinel-2: ESA's optical high-resolution mission for GMES operational services. Remote Sensing of Environment, 120, 25-36.

[7]. Hartigan, J. A., & Wong, M. A. (1979). Algorithm AS 136: A k-means clustering algorithm. Journal of the Royal Statistical Society. Series C (Applied Statistics), 28(1), 100- 108.

[8]. Lv, Z., Hu, Y., Zhong, H., Wu, J., Li, B., & Zhao, H. (2010, October). Parallel K-means clustering of remote sensing images based on MapReduce. In International Conference on Web Information Systems and Mining (pp. 162-170). Springer, Berlin, Heidelberg.

[9]. Matsuyama, T. (1987). Knowledge-based aerial image understanding systems and expert systems for image processing. IEEE Transactions on Geoscience and Remote Sensing, (3), 305-316.

[10]. Ostertag, R. (1998). Belowground effects of canopy gaps in a tropical wet forest. Ecology, 79(4), 1294-1304.

[11]. Rikimaru, A. (1997). Development of forest canopy density mapping and monitoring model using indices of vegetation, bare soil and shadow. Presented Paper for the 18^th ACRS.

[12]. Rikimaru, A., Roy, P. S., & Miyatake, S. (2002). Tropical forest cover density mapping. Tropical Ecology, 43(1), 39- 47.

[13]. Silvertown, J., & Smith, B. (1988). Gaps in the canopy: The missing dimension in vegetation dynamics. Vegetatio, 77(1-3), 57-60.

[14]. Van der Meer, F. D., Van der Werff, H. M. A., & Van Ruitenbeek, F. J. A. (2014). Potential of ESA's Sentinel-2 for geological applications. Remote Sensing of Environment, 148, 124-133.

[15]. Wang, J., Wang, J., Ke, Q., Zeng, G., & Li, S. (2015). Fast Approximate K-Means via Cluster Closures. In Multimedia Data Mining and Analytics (pp. 373-395). Springer, Cham.

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Research Paper

Studies on Continuous Adsorption of Acetic Acid from Aqueous Solution Using Rice Husk Adsorbent

Dr. S.V.A.R. Sastry* , Anusha Sri Adibatla, S. Varun*

* Associate Professor, Department of Chemical Engineering, MVGR College of Engineering (A), Vizianagaram, Andhra Pradesh, India.

-* UG Scholar, Department of Chemical Engineering, MVGR College of Engineering (A), Vizianagaram, Andhra Pradesh, India.

Sastry, S. V. A. R., Adibatla, A. S., and Varun, S. (2018). Studies on Continuous Adsorption of Acetic Acid from Aqueous Solution Using Rice Husk Adsorbent. i-manager’s Journal on Future Engineering and Technology, 14(1), 42-47. https://doi.org/10.26634/jfet.14.1.14692

Abstract

Acetic acid is widely used as an industrial chemical due to its very good solvency and miscibility. It is also used as a reagent in the production of many industrial chemicals. The major use of acetic acid is in the manufacture of vinyl acetate monomer, narrowly followed by acetic anhydride and ester. The total worldwide production of acetic acid is expected to reach 15.5 Mt/a (million tons per year) by 2020. Waste Acetic acid with pH of 5 or lower is termed as a dangerous waste. There are many methods used for removal of acetic acid from aqueous solutions; however these are also energy and cost intensive. Adsorption is one of the alternate methods which can be used for the removal of acetic acid. Considering the economics, there is increasing research interest in using alternate low cost adsorbents. In this work, adsorption of acetic acid from aqueous solutions by using Rice husk has been explored. The adsorption of Acetic acid in continuous mode has been studied with two variables (adsorbent dosage, adsorbate dosage), keeping one constant at a time. Breakthrough curves were obtained. The results showed that the proposed adsorbent is very useful for removing Acetic acid from industrial wastewater.

References

[1]. Chen, S., Yue, Q., Gao, B., Li, Q., Xu, X., & Fu, K. (2012). Adsorption of hexavalent chromium from aqueous solution by modified corn stalk: A fixed-bed column study. Bioresource Technology, 113, 114-120.

[2]. Dwivedi, C. P., Sahu, J. N., Mohanty, C. R., Mohan, B. R., & Meikap, B. C. (2008). Column performance of granular activated carbon packed bed for Pb (II) removal. Journal of Hazardous Materials, 156(1-3), 596-603.

[3]. Goel, J., Kadirvelu, K., Rajagopal, C., & Garg, V. K. (2005). Removal of lead (II) by adsorption using treated granular activated carbon: Batch and column studies. Journal of Hazardous Materials, 125 (1-3), 211-220.

[4]. Guyo, U., Mhonyera, J., & Moyo, M. (2015). Pb (II) adsorption from aqueous solutions by raw and treated biomass of maize stover–A comparative study. Process Safety and Environmental Protection, 93, 192-200.

[5]. Han, R., Zou, W., Li, H., Li, Y., & Shi, J. (2006). Copper (II) and lead (II) removal from aqueous solution in fixed-bed columns by manganese oxide coated zeolite. Journal of Hazardous Materials, 137(2), 934-942.

[6]. Long, Y., Lei, D., Ni, J., Ren, Z., Chen, C., & Xu, H. (2014). Packed bed column studies on lead (II) removal from industrial wastewater by modified Agaricus bisporus. Bioresource Technology, 152, 457-463.

[7]. Mondal, M. K. (2009). Removal of Pb (II) ions from aqueous solution using activated tea waste: Adsorption on a fixed-bed column. Journal of Environmental Management, 90(11), 3266-3271.

[8]. Özer, A. (2007). Removal of Pb (II) ions from aqueous solutions by sulphuric acid-treated wheat bran. Journal of Hazardous Materials, 141(3), 753-761.

[9]. Qaiser, S., Saleemi, A. R., & Umar, M. (2009). Biosorption of lead from aqueous solution by Ficus religiosa leaves: Batch and column study. Journal of Hazardous Materials, 166(2-3), 998-1005.

[10]. Sastry, S. V. A. R., & Rao, B. (2017). Determination of adsorption kinetics for removal of copper from waste water using Spent Tea Extract (STE). i-manager's Journal on Future Engineering and Technology, 12(4), 27-32.

[11]. Sastry, S. V. A. R., & Rao, S. (2016). Studies on adsorption of Cu (II) using spent tea extract (STE) from industrial wastewater. i-manager's Journal on Future Engineering and Technology, 11(3), 31-35.

[12]. Sousa, F. W., Oliveira, A. G., Ribeiro, J. P., Rosa, M. F., Keukeleire, D., & Nascimento, R. F. (2010). Green coconut shells applied as adsorbent for removal of toxic metal ions using fixed-bed column technology. Journal of Environmental Management, 91(8), 1634-1640.

[13]. Tchobanoglous, G., Burton, F. L., & Stensel, H. D. (2003). Wastewater Engineering: Treatment and Reuse. Tata McGraw-Hill, New Delhi, India.

[14]. Velazquez-Jimenez, L. H., Pavlick, A., & Rangel- Mendez, J. R. (2013). Chemical characterization of raw and treated agave bagasse and its potential as adsorbent of metal cations from water. Industrial Crops and Products, 43(1), 200-206.

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Research Paper

Remote Sensing and GIS Based Groundwater Prospects and Quality Assessment in Fatehabad District, Haryana

Surender Kumar*

*Faculty, Department of Geography, DNPG College, Hisar, Haryana, India.

Kumar, S. (2018). Remote Sensing and Gis Based Groundwater Prospects and Quality Assessment in Fatehabad District, Haryana.i-manager’s Journal on Future Engineering and Technology,14(1), 48-54. https://doi.org/10.26634/jfet.14.1.15255

Abstract

In modern period of urbanization, industrialization, agriculture, and increasing population have great affect on quantity and quality of groundwater. Haryana is an agriculture dominated state so water is a major requirement for irrigation. Fatehabad district is also an agriculture dominated district, which lies between 28^o48'15” to 29^o17'10” N and 76^o28'40” to 77^o12'45” E covering an area of 2538 km². In this present study, remote sensing satellite IRS-P6-LISS-III 2006 has been used to assess the groundwater prospects and quality by preparing various thematic layers in Arc Map Arc Info 9.3 GIS software. Field visits have been done to collect GPS points to verify delineated unit and inventory data. Post field correction has been made in prospects and quality map. In the district, Older Alluvial Plain, Aeolian plain, Sand Dune, Sand Dune Complex, Palaeochannel, and Older Flood Plain have been demarcated. Older Alluvial covers the largest area of 1498.94 sq. km² (59.09%) having good to very good groundwater prospects, which is 59.09% of total area. After that Aeolian plain covers 411.8 km² (16.22%) having moderate to good, sand dune and dune complex covers 30.86 km² (1.21) and 70.04 km²(2.77%), respectively having poor groundwater prospects. Older flood plain covers 368.84 km²(14.53%) having good to very good groundwater prospects. Palaeochannel covers 86.68 km²(3.41%) having very good to excellent groundwater prospects. For ground water quality, data has been collected from Groundwater Cell, Hisar. The major constituents, such as TDS, Cl, Ca+Mg, EC (μmho/cm), pH, and TH are used to assess the groundwater quality from pre monsoon and post monsoon data. Based on Indian Drinking Water Standards (BIS Guideline–IS: 10500:1991), ground water quality has been categorized into desirable and permissible limit and non-potable limit. In the integrated groundwater quality map, only two categories have same permissible and non potable limit. Permissible limit covers an area of 1703.67 sq.km (67.13%) and non-potable area covers an area of 834.33 sq.km (32.87%). The study presented is highly useful for giving a glance view of prospects and quality in the district which will be helpful in further development and management.

References

[1]. Bureau of Indian Standards. (1991). Drinking Water Characteristics (IS 10500:1991). New Delhi, India.

[2]. Khan, M. A., Narain, P., & Moharana, P. C. (2006). Prospecting groundwater resources using RS-GIS—A case study from arid western rajasthan of India. Journal of the Indian Society of Remote Sensing, 34(2), 171.

[3]. Kumar, B., & Kumar, U. (2010). Integrated approach using RS and GIS techniques for mapping of groundwater prospects in Lower Sanjai Watershed, Jharkhand. International Journal of Geomatics and Geosciences, 1(3), 587-598.

[4]. Roy, S. P. (2008). A Book of National Remote Sensing Centre and Indian Space Research Organization.

[5]. Qureshi, A. S., McCornick, P. G., Sarwar, A., & Sharma, B. R. (2010). Challenges and prospects of sustainable groundwater management in the Indus Basin, Pakistan. Water Resources Management, 24(8), 1551-1569.

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Review Paper

Water Balance Assessment Using Geospatial Techniques: A Review

Abanish Kumar* , Shruti Kanga, Sudhanshu*

* Research Scholar, Geoinformatics at Suresh Gyan Vihar University, Jaipur, India.

Assistant Professor and Coordinator, Centre for Climate Change & Water Research, Suresh Gyan Vihar University, Jaipur, India.

* Chief Mentor & Professor, Suresh Gyan Vihar University, Jaipur, India.

Kumar, A.,Kanga, S. and Sudhanshu. (2018). Water Balance Assessment Using Geospatial Techniques: A Review. i-manager’s Journal on Future Engineering and Technology, 14(1), 55-63. https://doi.org/10.26634/jfet.14.1.15254

Abstract

Water balance analysis for estimation of the supply/demand scenario utilizes geospatial approach that plays a very important role in worldwide research. Water balance is based on the law of conservation of mass, which states that any change in the water content of a given soil volume during a specified period must be equal to the difference between the amount of water added to the soil volume and the amount of water withdrawn from it. It helps to quantify the relationships between precipitation, surface and groundwater runoff, evaporation, evapotranspiration and aquifer drafts, and provide a framework for future planning of sustainable exploitation of the available water resources. This paper has discussed about the review of literatures in the field of water balance assessment. The water balance assessment of any area, an agricultural land, watershed, or a continent can be estimated by calculating the input, output, and storage changes of water components at the Earth's surface. From the review of research papers it is evident that a lot of research has been carried out and lot of models, such as SWAT, TM, GRACE, MIKE SHE, etc., have been developed for the evaluation of water balance assessment. Their analysis could be used for the study area to assess the water balance analysis for estimation of the supply/demand scenario, viz. evaporation, evapotransipiration, surface runoff, crop water requirement, inflow, outflow, and change in water storage as it requires exploring water balance components to overcome overexploitation or water scarcity in the study area.

References

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[2]. Azarderakhsh, M., Rossow, W. B., Papa, F., Norouzi, H., & Khanbilvardi, R. (2011). Integrating Terrestrial Water Balance in the Amazon Basin using Remote Sensing Data. Journal of Geophysical Research, 116, 148-227.

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[11]. Jain, S. K., Jain, S. K., Hariprasad, V., & Choudhry, A. (2011). Water balance study for a basin integrating remote sensing data and GIS. Journal of the Indian Society of Remote Sensing, 39(2), 259-270.

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[22]. Panagopoulos, A., Arampatzis, G., Kuhr, P., Kunkel, R., Tziritis, E., & Wendland, F. (2015). Area-differentiated modeling of water balance in Pinios river Basin, central Greece. Global NEST Journal, 17(2), 221-235.

[23]. Raghavendra, R. K., & Cholke, S. (2017). Assessment of watershed based water balance for Irrigation Scheduling through Geospatial Technique. International Journal of Engineering Technology Science and Research (IJETSR), 4(8), 1128-1134.

[24]. Shen, H., Leblanc, M., Frappart, F., Seoane, L., O'grady, D., Olioso, A., & Tweed, S. (2017). A comparative study of GRACE with continental evapotranspiration estimates in Australian semi-arid and arid basins: Sensitivity to climate variability and extremes. Water, 9(9), 614.

[25]. Singh, S. K., Mishra, S. K., & Kanga, S. (2017). Delineation of groundwater potential zone using geospatial techniques for Shimla city, Himachal Pradesh (India). International Journal for Scientific Research and Development, 5(4), 225-234.

[26]. Singh, S. K., Saklani, B., Prakash, S., Chauhan, R., & Gupta, H. (2014). Geospatial Approach for Decentralised Planning at Rajhana Panchayat, Himachal Pradesh. International Journal of Advancement in Remote Sensing, GIS and Geography, 2(2), 27-43.

[27]. Thapa, B. R., Ishidaira, H., Pandey, V. P., & Shakya, N. M. (2017). A multi-model approach for analyzing water balance dynamics in Kathmandu Valley, Nepal. Journal of Hydrology: Regional Studies, 9, 149-162.

[28]. Thompson, S. E., Harman, C. J., Troch, P. A., Brooks, P. D., & Sivapalan, M. (2011). Spatial scale dependence of ecohydrologically mediated water balance partitioning: A synthesis framework for catchment ecohydrology. Water Resources Research, 47(10),143-158.

[29]. Uniyal, B., Jha, M. K., & Verma, A. K. (2015). Assessing climate change impact on water balance components of a river basin using SWAT model. Water Resources Management, 29(13), 4767-4785.

[30]. Usmanov, S., Mitani, Y., & Kusuda, T. (2016). An integrated hydrological model for water balance estimation in the Chirchik River Basin, Northern Uzbekistan. Computational Water, Energy, and Environmental Engineering, 5(3), 87-97.

[31]. White, E. D., Easton, Z. M., Fuka, D. R., Collick, A. S., Adgo, E., McCartney, M., & Steenhuis, T. S. (2011). Development and application of a physically based landscape water balance in the SWAT model. Hydrological Processes, 25(6), 915-925.

[32]. Yang, Y., Liu, Y., Cao, S., & Cheng, Y. (2017). A method of evaluating water resource assets and liabilities: A case study of Jinan City, Shandong Province. Water, 9(8), 575.

[33]. Yin, Z., Feng, Q., Zou, S., & Yang, L. (2016). Assessing variation in water balance components in mountainous inland river basin experiencing climate change. Water, 8(10), 472.

[34]. Zhang, D., Chen, X., Yao, H., & Lin, B. (2015). Improved calibration scheme of SWAT by separating wet and dry seasons. Ecological Modelling, 301, 54-61.

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Case Study

Multi-Criteria Analysis for Flood Risk Assessment Using Remote Sensing & GIS Technique-A Case Study of Damodar River Basin

Surajit Bera* , Mobin Ahmad , Alisha Prasad *

- Natural Resource Modelling and Environment Management, CSIR- Central Institute of Mining & Fuel Research, Dhanbad, Jharkhand, India.

Center for Land Resource Management, Central University of Jharkhand, Ranchi, Jharkhand, India.

Bera, S., Ahmad, M. and Prasad, A.(2018). Multi-Criteria Analysis for Flood Risk Assessment Using Remote Sensing & Gis Technique-A Case Study of Damodar River Basin.i-manager’s Journal on Future Engineering and Technology, 14(1), 55-74. https://doi.org/10.26634/jfet.14.1.15256

Abstract

Flood is a natural hazard occurring on the Earth's surface when water overflows the bank and spreads over the flood plain causing harm to the residents, crops, and vegetation. GIS, Remote Sensing, and Modelling technology are used in formulating models for flood hazard monitoring, risk analysis, and identification of flood risk zones for the planning and management of this natural hazard. The flood risk assessment of Damodar River Basin lying in districts of Jharkhand, Bihar and West Bengal in India, was prepared using multi-criteria analysis involving the weighted overlay of LU/LC, drainage density, soil, rainfall, slope, and geological parameters. The total area of 23,370.98 sq.km is divided into four flood risk zones, namely no flood risk, low flood risk, moderate flood risk, and high flood risk zone. According to the final output flood risk map no risk zone covers 6,472.19 sq.km (27.69%), low risk zone covers 3,341.02 sq.km (14.30%), moderate risk zone covers 12,647.48 sq.km (54.12%), and high risk zone covers 910.29 sq.km (3.89%) of area. According to the evaluated statistics 40% of the total area of Bihar in the study area comes under no risk zone. A major area of low flood risk zone is present in Jharkhand, which is 15.80% of the total area of Jharkhand in the study area, whereas in Bihar it comprises 6.23% of its total area in the study area and in West Bengal it covers 11.02% of its total area in the study area. In West Bengal, 68.63% and 20.35% of the total area of West Bengal in the study area comes under moderate flood risk and high flood risk zone, respectively.

References

[1]. Ali, K., Bajracharya, R. M., & Koirala, H. L. (2016). A review of flood risk assessment. International Journal of Environment, Agriculture and Biotechnology, 1(4), 1065- 1077.

[2]. Balabanova, S., & Vassilev, V. (2010). Creation of flood hazard maps. Water Obs. Inf. Syst. Balk. Ctries. BALWOIS.

[3]. Choudhury, J. (1995). Barddhaman Jelar Itihash o Smanskriti (History and Culture of Burdwan District). Kolkata: Pustak Biponi.

[4]. Dhar, O. N., & Nandargi, S. (2003). Hydrometeorological aspects of floods in India. Natural Hazards, 28(1), 1-33.

[5]. Ghosh, S. (2013). Estimation of flash flood magnitude and flood risk in the lower segment of Damodar River basin, India. Int. J. Geol. Earth Environ. Sci., 3(2), 97-114.

[6]. Jeb, D. N., & Aggarwal, S. P. (2008). Flood inundation hazard modeling of the River Kaduna using remote sensing and geographic information systems. Journal of Applied Sciences Research, 4(12), 1822-1833.

[7]. Kale, V. S. (1998). Monsoon floods in India: A hydro-geomorphic perspective. Memoirs-Geological Society of India, 229-259.

[8]. Lingadevaru, D. C., & Govindaraju, J. P. D. Assessment using Remote Sensing and GIS Techniques: A Karnataka, India. International Journal of Current Research.

[9]. Renyi, L., & Nan, L. (2002). Flood area and damage estimation in Zhejiang, China. Journal of Environmental Management, 66(1), 1-8.

[10]. Saha, M. K. (2005). River flood forecasting and preparedness-Lower Damodar Valley in West Bengal. River Floods-A Socio-Technical Approach, 244-249.

[11]. Singh, A. K., & Sharma, A. K. (2009). GIS and a remote sensing-based approach for urban flood-plain mapping for the Tapi catchment, India. IAHS Publication, 331, 389.

i-manager's Journal on Future Engineering and Technology (JFET)

Current Issue Vol. 20 Issue 1

Most Read

Most Cited

Volume 14 Issue 1 August - October 2018

Gisli Thorsteinsson* , Tom page**

* Professor, Department of Design and Craft Education, University of Iceland, Iceland. ** Associate Professor, Department of Product Design, Nottingham Trent University, England.

Thorsteinsson, G. and Page, T. (2018). The Evolution of 3D printing and Industry 4.0.i-manager’s Journal on Future Engineering and Technology,14(1), 1-15. https://doi.org/10.26634/jfet.14.1.14600

Abstract

References

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Giuma M. Fellah*

*Professor, Department of Mechanical and Industrial Engineering, Faculty of Engineering, University of Tripoli, Libya.

Fellah, G. (2018). Performance analysis of humidification-dehumidification desalination processes.i-manager’s Journal on Future Engineering and Technology,14(1), 16-25. https://doi.org/10.26634/jfet.14.1.14596

Abstract

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Anant D. Patel*

*Assistant Professor, Department of Civil Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India.

Patel, A. D. (2018). Design of Optimum Number of Rain Gauge Network Over Sabarmati River Basin.i-manager’s Journal on Future Engineering and Technology,14(1), 26-31. https://doi.org/10.26634/jfet.14.1.14207

Abstract

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Saurabh Kumar Gupta* , A. C. Pandey**

* PhD Scholar, Center for Land Resource Management, Central University of Jharkhand, India. ** Professor, Center for Land Resource Management, Central University of Jharkhand, India.

Gupta, S. K. and Pandey, A. C.(2018). Clustering Technique to Threshold Vegetation Indices and Gap Detection In Hazaribagh Wildlife Sanctuary, Jharkhand (India).i-manager’s Journal on Future Engineering and Technology,14(1), 32-41. https://doi.org/10.26634/jfet.14.1.15257

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Dr. S.V.A.R. Sastry* , Anusha Sri Adibatla**, S. Varun***

* Associate Professor, Department of Chemical Engineering, MVGR College of Engineering (A), Vizianagaram, Andhra Pradesh, India. **-*** UG Scholar, Department of Chemical Engineering, MVGR College of Engineering (A), Vizianagaram, Andhra Pradesh, India.

Sastry, S. V. A. R., Adibatla, A. S., and Varun, S. (2018). Studies on Continuous Adsorption of Acetic Acid from Aqueous Solution Using Rice Husk Adsorbent. i-manager’s Journal on Future Engineering and Technology, 14(1), 42-47. https://doi.org/10.26634/jfet.14.1.14692

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Surender Kumar*

*Faculty, Department of Geography, DNPG College, Hisar, Haryana, India.

Kumar, S. (2018). Remote Sensing and Gis Based Groundwater Prospects and Quality Assessment in Fatehabad District, Haryana.i-manager’s Journal on Future Engineering and Technology,14(1), 48-54. https://doi.org/10.26634/jfet.14.1.15255

Abstract

References

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Abanish Kumar* , Shruti Kanga**, Sudhanshu***

* Research Scholar, Geoinformatics at Suresh Gyan Vihar University, Jaipur, India. ** Assistant Professor and Coordinator, Centre for Climate Change & Water Research, Suresh Gyan Vihar University, Jaipur, India. *** Chief Mentor & Professor, Suresh Gyan Vihar University, Jaipur, India.

Kumar, A.,Kanga, S. and Sudhanshu. (2018). Water Balance Assessment Using Geospatial Techniques: A Review. i-manager’s Journal on Future Engineering and Technology, 14(1), 55-63. https://doi.org/10.26634/jfet.14.1.15254

Abstract

References

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Surajit Bera* , Mobin Ahmad **, Alisha Prasad ***

*-** Natural Resource Modelling and Environment Management, CSIR- Central Institute of Mining & Fuel Research, Dhanbad, Jharkhand, India. *** Center for Land Resource Management, Central University of Jharkhand, Ranchi, Jharkhand, India.

Bera, S., Ahmad, M. and Prasad, A.(2018). Multi-Criteria Analysis for Flood Risk Assessment Using Remote Sensing & Gis Technique-A Case Study of Damodar River Basin.i-manager’s Journal on Future Engineering and Technology, 14(1), 55-74. https://doi.org/10.26634/jfet.14.1.15256

Abstract

References

Full Article (HTML)

Pdf

* Professor, Department of Design and Craft Education, University of Iceland, Iceland.

** Associate Professor, Department of Product Design, Nottingham Trent University, England.

Thorsteinsson, G. and Page, T. (2018). The Evolution of 3D printing and Industry 4.0.i-manager’s Journal on Future Engineering and Technology,14(1), 1-15.
https://doi.org/10.26634/jfet.14.1.14600

* PhD Scholar, Center for Land Resource Management, Central University of Jharkhand, India.

** Professor, Center for Land Resource Management, Central University of Jharkhand, India.

Dr. S.V.A.R. Sastry* , Anusha Sri Adibatla, S. Varun*

* Associate Professor, Department of Chemical Engineering, MVGR College of Engineering (A), Vizianagaram, Andhra Pradesh, India.

-* UG Scholar, Department of Chemical Engineering, MVGR College of Engineering (A), Vizianagaram, Andhra Pradesh, India.

Abanish Kumar* , Shruti Kanga, Sudhanshu*

* Research Scholar, Geoinformatics at Suresh Gyan Vihar University, Jaipur, India.

Assistant Professor and Coordinator, Centre for Climate Change & Water Research, Suresh Gyan Vihar University, Jaipur, India.

* Chief Mentor & Professor, Suresh Gyan Vihar University, Jaipur, India.

Surajit Bera* , Mobin Ahmad , Alisha Prasad *

- Natural Resource Modelling and Environment Management, CSIR- Central Institute of Mining & Fuel Research, Dhanbad, Jharkhand, India.

Center for Land Resource Management, Central University of Jharkhand, Ranchi, Jharkhand, India.