parametric optimization mahua oil von kolakoti aditya (10 Ergebnisse)

Zustand: New.

Zustand: New. In.

PF. Zustand: New.

Taschenbuch. Zustand: Neu. Neuware -In this present investigation, four important process parameters of catalyst concentration, molar ratio, reaction time, and reaction temperature were studied and optimized using Box Behnken assisted response surface method (RSM) and Genetic Algorithm (GA) to achieve the maximum mahua oil biodiesel yield. For this purpose, 27 experiments were conducted randomly based on the design matrix using statistical software MiniTab®2019. A maximum yield of 91.32% is achieved in RSM, catalyst concentration and reaction time are identified as influence parameters in biodiesel yield. GA modelling show an improvement of 4.96% in biodiesel yield compared to RSM approach. Both techniques are successfully tested in prediction and modelling the biodiesel yield from mahua oil. The obtained biodiesel from the transesterification process is blended with standard diesel fuel at various proportions (B10 to B90) and tested for different fuel properties. All the biodiesel blends are observed within the limits of international standards of ASTMD-6751 and EN-14214. The results indicate that the chosen models are highly accurate in achieving maximum biodiesel yield.Books on Demand GmbH, Überseering 33, 22297 Hamburg 80 pp. Englisch.

Taschenbuch. Zustand: Neu. Parametric optimization of mahua oil biodiesel production | RSM and GA approach | Aditya Kolakoti (u. a.) | Taschenbuch | 80 S. | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202513197 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

PAP. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this present investigation, four important process parameters of catalyst concentration, molar ratio, reaction time, and reaction temperature were studied and optimized using Box Behnken assisted response surface method (RSM) and Genetic Algorithm (GA) to achieve the maximum mahua oil biodiesel yield. For this purpose, 27 experiments were conducted randomly based on the design matrix using statistical software MiniTab®2019. A maximum yield of 91.32% is achieved in RSM, catalyst concentration and reaction time are identified as influence parameters in biodiesel yield. GA modelling show an improvement of 4.96% in biodiesel yield compared to RSM approach. Both techniques are successfully tested in prediction and modelling the biodiesel yield from mahua oil. The obtained biodiesel from the transesterification process is blended with standard diesel fuel at various proportions (B10 to B90) and tested for different fuel properties. All the biodiesel blends are observed within the limits of international standards of ASTMD-6751 and EN-14214. The results indicate that the chosen models are highly accurate in achieving maximum biodiesel yield. 80 pp. Englisch.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kolakoti AdityaDr. Aditya Kolakoti is currently working as an Assistant Professor in the Department of Mechanical Engineering, Raghu Engineering College (A), Visakhapatnam, India. Mr. Prakasa Rao Mosa and Mr. Tulasi Ganesh Kotaru are.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this present investigation, four important process parameters of catalyst concentration, molar ratio, reaction time, and reaction temperature were studied and optimized using Box Behnken assisted response surface method (RSM) and Genetic Algorithm (GA) to achieve the maximum mahua oil biodiesel yield. For this purpose, 27 experiments were conducted randomly based on the design matrix using statistical software MiniTab®2019. A maximum yield of 91.32% is achieved in RSM, catalyst concentration and reaction time are identified as influence parameters in biodiesel yield. GA modelling show an improvement of 4.96% in biodiesel yield compared to RSM approach. Both techniques are successfully tested in prediction and modelling the biodiesel yield from mahua oil. The obtained biodiesel from the transesterification process is blended with standard diesel fuel at various proportions (B10 to B90) and tested for different fuel properties. All the biodiesel blends are observed within the limits of international standards of ASTMD-6751 and EN-14214. The results indicate that the chosen models are highly accurate in achieving maximum biodiesel yield.