Extension of moment projection method to the fragmentation process
The method of moments is a simple but efficient method of solving the population balance equation which describes particle dynamics. Recently, the moment projection method (MPM) was proposed and validated for particle inception, coagulation, growth and, more importantly, shrinkage; here the method i...
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| Veröffentlicht in: | Journal of computational physics 2017-04, Vol.335, p.516-534 |
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| container_title | Journal of computational physics |
| container_volume | 335 |
| creator | Wu, Shaohua Yapp, Edward K.Y. Akroyd, Jethro Mosbach, Sebastian Xu, Rong Yang, Wenming Kraft, Markus |
| description | The method of moments is a simple but efficient method of solving the population balance equation which describes particle dynamics. Recently, the moment projection method (MPM) was proposed and validated for particle inception, coagulation, growth and, more importantly, shrinkage; here the method is extended to include the fragmentation process. The performance of MPM is tested for 13 different test cases for different fragmentation kernels, fragment distribution functions and initial conditions. Comparisons are made with the quadrature method of moments (QMOM), hybrid method of moments (HMOM) and a high-precision stochastic solution calculated using the established direct simulation algorithm (DSA) and advantages of MPM are drawn. |
| doi_str_mv | 10.1016/j.jcp.2017.01.045 |
| format | Article |
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Recently, the moment projection method (MPM) was proposed and validated for particle inception, coagulation, growth and, more importantly, shrinkage; here the method is extended to include the fragmentation process. The performance of MPM is tested for 13 different test cases for different fragmentation kernels, fragment distribution functions and initial conditions. Comparisons are made with the quadrature method of moments (QMOM), hybrid method of moments (HMOM) and a high-precision stochastic solution calculated using the established direct simulation algorithm (DSA) and advantages of MPM are drawn.</description><identifier>ISSN: 0021-9991</identifier><identifier>EISSN: 1090-2716</identifier><identifier>DOI: 10.1016/j.jcp.2017.01.045</identifier><language>eng</language><publisher>Cambridge: Elsevier Inc</publisher><subject>ACCURACY ; ALGORITHMS ; BALANCES ; Breakage ; CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS ; COMPARATIVE EVALUATIONS ; Computational physics ; Computer simulation ; COMPUTERIZED SIMULATION ; DISTRIBUTION ; DISTRIBUTION FUNCTIONS ; EQUATIONS ; FRAGMENTATION ; Initial conditions ; MATHEMATICAL SOLUTIONS ; Method of moments ; Moment projection method ; MOMENTS METHOD ; Particulate systems ; PARTICULATES ; Population balance ; QUADRATURES ; SHRINKAGE ; Stochastic models ; STOCHASTIC PROCESSES ; Studies</subject><ispartof>Journal of computational physics, 2017-04, Vol.335, p.516-534</ispartof><rights>2017 Elsevier Inc.</rights><rights>Copyright Elsevier Science Ltd. 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Recently, the moment projection method (MPM) was proposed and validated for particle inception, coagulation, growth and, more importantly, shrinkage; here the method is extended to include the fragmentation process. The performance of MPM is tested for 13 different test cases for different fragmentation kernels, fragment distribution functions and initial conditions. 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| ispartof | Journal of computational physics, 2017-04, Vol.335, p.516-534 |
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| subjects | ACCURACY ALGORITHMS BALANCES Breakage CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS COMPARATIVE EVALUATIONS Computational physics Computer simulation COMPUTERIZED SIMULATION DISTRIBUTION DISTRIBUTION FUNCTIONS EQUATIONS FRAGMENTATION Initial conditions MATHEMATICAL SOLUTIONS Method of moments Moment projection method MOMENTS METHOD Particulate systems PARTICULATES Population balance QUADRATURES SHRINKAGE Stochastic models STOCHASTIC PROCESSES Studies |
| title | Extension of moment projection method to the fragmentation process |
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