Applications of Computer Science in Environmental Models

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Computation is now regarded as an equal and indispensable partner, along with theory and experiment, in the advance of scientific knowledge and engineering practice. Numerical simulation enables the study of complex systems and natural phenomena that would be too expensive or dangerous, or even impossible, to study by direct experimentation. The quest for ever higher levels of detail and realism in such simulations requires enormous computational capacity, and has provided the impetus for dramatic breakthroughs in computer algorithms and architectures. Due to these advances, computational scientists and engineers can now solve large-scale problems that were once thought intractable. Computational science and engineering (CSE) is a rapidly growing multidisciplinary area with connections to the sciences, engineering, and mathematics and computer science. CSE focuses on the development of problemsolving methodologies and robust tools for the solution of scientific and engineering problems. We believe that CSE will play an important if not dominating role for the future of the scientific discovery process and engineering design. The computation science is now being used widely for environmental engineering calculations. The behavior of environmental engineering systems and processes can be studied with the help of computation science and understanding as well as better solutions to environmental engineering problems can be obtained.

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International Journal of Latest Technology in Engineering Management Applied Science IJLTEMAS Volume VI Issue III March 2017 | ISSN 2278-2540 www.ijltemas.in Page 94 Applications of Computer Science in Environmental Models S. V. Khedkar 1 Dr. N. W. Ingole 2 1 Department Of Chemical Engineering College Of Engineering and Technology NH-6 Murtizapur Road Babhulgaon Jh Akola 444104 Maharashtra State 2 Professor and Dean R D PRMIT R Bandera Amravati. Abstract: - Computation is now regarded as an equal and indispensable partner along with theory and experiment in the advance of scientific knowledge and engineering practice. Numerical simulation enables the study of complex systems and natural phenomena that would be too expensive or dangerous or even impossible to study by direct experimentation. The quest for ever higher levels of detail and realism in such simulations requires enormous computational capacity and has provided the impetus for dramatic breakthroughs in computer algorithms and architectures. Due to these advances computational scientists and engineers can now solve large-scale problems that were once thought intractable. Computational science and engineering CSE is a rapidly growing multidisciplinary area with connections to the sciences engineering and mathematics and computer science. CSE focuses on the development of problem- solving methodologies and robust tools for the solution of scientific and engineering problems. We believe that CSE will play an important if not dominating role for the future of the scientific discovery process and engineering design. The computation science is now being used widely for environmental engineering calculations. The behavior of environmental engineering systems and processes can be studied with the help of computation science and understanding as well as better solutions to environmental engineering problems can be obtained. Key Words: algorithms computation environmental engineering simulation. I. INTRODUCTION hemistry. Computational chemistry CC is widely used in academic and industrial research. Computed molecular structures e.g. very often are more reliable than experimentally determined ones. According to "Chemical Engineering News" the newsletter of the American Chemical Society Computational Chemistry has developed from a "nice to have" to a "must-have" tool . The main incentive of CC is the prediction of chemical phenomena based on models which relate either to first principles theory "rigorous models" to statistical ensembles governed by the laws of classical physics or thermodynamics or simply to empirical knowledge. In real problem solving situations these models are often combined to form "hybrid models" where only the critical part of the problem is treated at the rigorous level of theory. Rigorous theory in the molecular context is synonymous with quantum mechanics i.e. solving the Schrödinger equation for a molecular complex with or without the presence of external perturbation photons electric fields etc.. There are a number of methods available which provide approximate solutions to the Schrödinger equation Hartree - Fock and Density Functional theory e.g.. Simulation is used to predict properties of large and complex entities such as a liquid the folding of a protein in solution or the elasticity of a polymer. Finally empirical models most often try to establish correlations between the structure of a molecule and its pharmaceutical activity. Simulations and quantum chemical calculations on the other hand very often are extremely compute-intensive due to the number of degrees of freedom and the complexity of the terms to be evaluated. The high accuracy required in these calculations sets restrictions with regard to the method used to solve the partial differential equations PDEs involved. Further information is available at the website for the International Union of Pure and Applied Chemistry. Bio engineering. Historically engineers have used chemistry thermodynamics and transport to design chemical processes. Now these fundamental processes are applied to the understanding of complex biological phenomena that are governed by the same physical laws. Computer models are being used to understand and to develop treatments for glaucoma to understand and to fabricate bio artificial materials for example bio artificial arteries and for studying the normal and pathologic response of soft hydrated tissues in the human musculoskeletal system. II. APPLICATION OF COMPUTATIONAL SCIENCE IN ENVIRONMENTAL ENGINEERING Computational science as mentioned above can be used in multiple areas for the inter conversion of data to obtain a final software program. This has been shown in detail with a case study below. A. Materials and Methods C

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International Journal of Latest Technology in Engineering Management Applied Science IJLTEMAS Volume VI Issue III March 2017 | ISSN 2278-2540 www.ijltemas.in Page 95 Fig 1 Batch sonication process Sonication is a process of advanced oxidation in which the sample solution is irradiated with the ultrasonic waves A.S. Stasinakis2005 Mira Petrovic 2011 . The reactor used in this case is the probe reactor. The irradiation causes physical chemical and biological changes in the water. K. S. Gandhi and R. Kumar 1994 Kenneth S. Suslick 1999 L. H. Thompson and L.K.Doraiswamy 1999 Uma Mukherji 2003. It is seen that the process also affects the Chemical Oxygen Demand which was verified using standard method APHA 2005. The solution of aspirin having concentration of 700 mg/L was prepared by adding two disprin tablets to 1000 ml deionised water of laboratory grade. The single tablet of aspirin contains 350 mg aspirin by weight. The tablet is self dispersible and dissolves by itself. A slight stirring may be done at the end with a glass rod if required. The detailed pre-sonication observations for this concentration have been reported in table 1 below. Royal Society of Chemistry 2003 R.K. Maheswari et al. 2010 B Observations Table 1 Presonication sample parameters observed S. No Parameter Observed Observed Value 1. pH 3.1 2. Total Dissolved Solids TDS 152 ppm 3. Conductivity 200 µS/cm 4. Sample Volume 500 ml 5. Sonication Frequency 20 kHz 6. Sonication Mode Continuous 7. Initial Concentration of Sample 700 mg/L Table 2 postsonication sample parameters observed S. No Amplitude of Sonication in Time of sonication In mints in minutes End point of titration for non sonicated sample in ml End point of titration for sonicated sample in ml Aspirin at start of sonication 700 mg/L Aspirin Degraded at the end of sonication 1. 10 05 2.3 1.2 100 47.83 2. 20 05 2.3 0.8 100 65.22 3. 30 05 2.3 0.7 100 69.57 4. 40 05 2.3 0.7 100 69.57 5. 50 05 2.3 0.6 100 73.92 6. 60 05 2.3 0.5 100 78.27 7. 70 05 2.3 0.4 100 82.61 8. 80 05 2.3 0.4 100 82.61 9. 90 05 2.3 0.4 100 82.61 10 100 05 2.3 0.3 100 86.96 11. 10 10 2.3 0.5 100 78.27 12. 20 10 2.3 0.5 100 78.27 13. 30 10 2.3 0.5 100 78.27 14. 40 10 2.3 0.4 100 82.61 15. 50 10 2.3 0.4 100 82.61 16. 60 10 2.3 0.4 100 82.61 17. 70 10 2.3 0.3 100 86.96 18. 80 10 2.3 0.3 100 86.96 19. 90 10 2.3 0.2 100 91.30 20 100 10 2.3 0.2 100 91.30 21. 10 15 2.3 0.4 100 82.61 22. 20 15 2.3 0.2 100 91.30 23. 30 15 2.3 0.2 100 91.30 24. 40 15 2.3 0.2 100 91.30 25. 50 15 2.3 0.2 100 91.30 26. 60 15 2.3 0.2 100 91.30 27. 70 15 2.3 0.2 100 91.30 28. 80 15 2.3 0.2 100 91.30 29. 90 15 2.3 0.2 100 91.30 30. 100 15 2.3 0.2 100 91.30

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International Journal of Latest Technology in Engineering Management Applied Science IJLTEMAS Volume VI Issue III March 2017 | ISSN 2278-2540 www.ijltemas.in Page 96 C Program development in C++ If a value for biodegradation was reported as the BOD Biochemical Oxygen Demand or as the percentage of chemical degraded then this information can be converted to a half-life estimate. Assuming first order decay from an initial quantity C 0 to C a in time t gives Jon Arnot et al. 2005 P. C. Jain 2013 Charles G hill Jr. Thatcher Root 2003 Salil K. Ghoshal 1997 C a C 0 exp. -kt 1 Where k is the reaction rate constant. The percent loss or BOD is then BOD 100 x C 0 -C a /C 0 100 x 1- exp. - kt 2 From which k can be calculated as k -1/t ln 100 - BOD/100 3 The half life t 1/2 is then 0.693/k or t 1/2 - 0.693 t/ln 100 - BOD / 100 4 This is the case for kinetic modeling Catherine A. Peters 2001 Yanhui Hu 2011 D Sample data C++ Program includeiostream includemath.h includestdlib.h include fstream includestring include iomanip using namespace std int mainint argc char argv ifargcatoiargv1+3 cout"Enter appropriate arguments" exit1 else int ia double k15t15x15h15pc15 a atoiargv2 cout"Amplitude is "aendl cout"The value of time are\n" fori0iatoiargv1i++ ti5+i5 coutti"\t" coutendl cout"The input values are"endl fori0iatoiargv1i++ xi atofargvi+3 coutxi"\t" coutendl fori0iatoiargv1i++ cilog100/100-xi ki1/tici hi0.693/ki cout"The value of constant are\n" fori0iatoiargv1i++ coutci"\t" coutendl cout"The rate constant k is\n" fori0iatoiargv1i++ coutki"\t" coutendl cout"The half life time t0.5 is\n" fori0iatoiargv1i++ couthi"\t" coutendl paa/double210001500 cout"The value of intensity is "scientificpendl ofstream outdata outdata.open"readings.csv" ios::app outdata"Table for amplitude "aendlendl outdata"Time of Sonication""" fori0iatoiargv1i++ outdata ti outdata "" outdataendl outdata" Aspirin at end of Sonication""" fori0iatoiargv1i++ outdata xi outdata "" outdataendl outdata"Value of lnC0/Ca""" fori0iatoiargv1i++ outdata ci

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International Journal of Latest Technology in Engineering Management Applied Science IJLTEMAS Volume VI Issue III March 2017 | ISSN 2278-2540 www.ijltemas.in Page 97 outdata "" outdataendl outdata"Value of constant k""" fori0iatoiargv1i++ outdata ki outdata "" outdataendl outdata"Value of half life t0.5""" fori0iatoiargv1i++ outdata hi outdata "" outdataendlendl outdata"Values of intensity"scientificpendlendlendlendl outdata.close return 0 Data obtained in terms of rate constant k and half life t1/2 using above program in C++ Data obtained for rate constant k and half life t1/2 for different amplitudes of sonication. III. CONCLUSIONS The program in C++ was successfully developed and utilized for calculations relating to both Chemical Engineering and Civil Engineering Environmental Engineering. It did not only simplify the work but this progam can now be used to make any number of calculations. The data thus obtained can be modeled and validated. REFERENCES 1. A.S. Stasinakis “Use Of Selected Advanced Oxidation Processes Aops For Wastewater Treatment – A Mini Review” Global Nest Journal Vol 10 No 3 pp 376-385 2008 2. APHA “Standard Methods for the Examination of Water and Wastewater” Washington DC 21 st Centennial Edition 2005. 3. “aspirin”- A Curriculum Resource For Post-16 Chemistry And Science CoursesCompiled by David Lewis Edited by Colin Osborne and Maria Pack second edition Printed by the Royal Society of Chemistry 2003ISBN 0–85404–388–8pp 1-31 4. Charles G hill Jr. Thatcher Root Introduction To Chemical Engineering Kinetics And Reactor Design second edition 2003 published by John Wiley Sons Inc. Hoboken New Jersey second editionISBN no 979-1-118-36825pp-30-53. 5. Catherine A. Peters 2001 “Statistics for Analysis of Experimental Data” Environmental Engineering Processes Laboratory Manual pp 1-25. 6. Jain P.C. 2013 “Engineering Chemistry” published by DhanpatRai Publishing Company P Ltd. 15 th Edition P-3. 7. Jon Arnot Todd Gowin Don Mackay 2005 Canadian Environment Report On Development And Application Of Models Of Chemical Fate In Canada practical methods for estimating environmental biodegradation ratespp 2-48. 8. Kenneth S. Suslick 1999 “Acoustic cavitation and its chemical consequences Phil. Trans.R. Soc. Lond.” A 1999 357 pp 335- 353.

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International Journal of Latest Technology in Engineering Management Applied Science IJLTEMAS Volume VI Issue III March 2017 | ISSN 2278-2540 www.ijltemas.in Page 98 9. K. S. Gandhi and R. Kumar 1994 “Sonochemical Reaction Engineering” Sadhana Vol 19 part 6 December 1994 pp 1055- 1076. 10. L. H. Thompson and L.K.Doraiswamy 1999 “Sonochemistry: Science and Engineering”Ind. Eng. Chem. Res.199938 pp 1215- 1249. 11. Mira Petrovic 2011 Advanced Oxidation Processes Aops “Applied For Wastewater and Drinking Water Treatment. Elimination of Pharmaceuticals the Holistic Approach to Environment” 120112 pp 63-74. 12. R.K. Maheswari Harish K Chandrawanshi Neerja Gupta 2010 “Quantitative Estimation Of Aspirin In Tablets And Bulk Sample Using Metformin Hydrochloride As Hydrotropic” Vol 2 Issue 1 2010pp 20-23. 13. Salil K. Ghoshal Shyamlal K. Sanyal Siddhatha Datta 1997 Introduction to Chemical Engineering 1993 Tata Macgraw-Hill Publishing Limited ISBN no. 0-07-460140-7pp 318319. 14. T.J. Mason andJ.P.Lorimer 2002 “Applied Sonochemistry: Uses Of Power Ultrasound in Chemistry and Processing”. Wiley – VCH Verlag GmbH Co. KGaA. ISBNs: 3-527-30205-0 Hardback 3- 527-60054-xElectronic. 15. Yanhui Hu 2011“Linear Regression 101” Journal of Validation Technology Spring 2011pp 15-22. 16. Uma Mukherji 2003 “Engineering Physics” Narosa Publishing House ISBN 81-7319-240-5 pp 69-84. 17. Chemical and Engineering News May 1997. 18. International Union of Pure and Applied Chemistry IUPAC http://www.chem.qmw.ac.uk/iupac/.

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