Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/43006
Full metadata record
DC FieldValueLanguage
dc.coverage.spatialParametric studies on the strength of bolted lap joints of hybrid fiber reinforced polymer compositesen_US
dc.date.accessioned2015-06-15T05:53:18Z-
dc.date.available2015-06-15T05:53:18Z-
dc.date.issued2015-06-15-
dc.identifier.urihttp://hdl.handle.net/10603/43006-
dc.description.abstractIn the present work investigation of the mechanical properties of oven cured hybrid fiber reinforced polymer composites laminates and its bolted joint is carried out The modeling of the properties using Artificial Neural Network ANN has been done newlineThe composite are reinforced with alkali treated woven jute natural fiber and woven glass fiber The hybrid fiber jute glass polymer matrix composites were made from 5 plies and fabricated by manual hand layup method Three different Stacking sequence were chosen for the study C1 Glass Jute Jute Jute Glass C2 Glass Jute Glass Jute Glass C3 Jute Glass Jute Glass Jute The composites laminates are post cured in hot air oven to maximize the fiber and matrix interface newlineThe optimization of these composites parameters are analyzed using analysis of variance ANOVA The behavior of fabricated composites has been assessed under different process parameter such as treatment of natural fiber in hours NaOH concentration stacking sequencing of jute and glass fiber laminas edge to hole diameter width to hole diameter and oven curing time to maximize the composite laminates strength and its joint strength Each parameter modeled with three levels L27 orthogonal array was implemented to minimize the no of experiments Contribution of each parameter and their optimum levels are analyzed newline newlineen_US
dc.format.extentxii, 116p.en_US
dc.languageEnglishen_US
dc.relationp109-115.en_US
dc.rightsuniversityen_US
dc.titleParametric studies on the strength of bolted lap joints of hybrid fiber reinforced polymer compositesen_US
dc.title.alternativeen_US
dc.creator.researcherSutharson Ben_US
dc.subject.keywordArtificial Neural Networken_US
dc.subject.keywordGlass Jute Jute Jute Glassen_US
dc.description.notereference p109-115.en_US
dc.contributor.guideRajendran Men_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Mechanical Engineeringen_US
dc.date.registeredn.d,en_US
dc.date.completed01/10/2014en_US
dc.date.awarded30/10/2014en_US
dc.format.dimensions23cm.en_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Mechanical Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File29.11 kBAdobe PDFView/Open
02_certificate.pdf1.54 MBAdobe PDFView/Open
03_abstract.pdf8.28 kBAdobe PDFView/Open
04_acknowledgement.pdf5.85 kBAdobe PDFView/Open
05_content.pdf23.4 kBAdobe PDFView/Open
06_chapter1.pdf255.57 kBAdobe PDFView/Open
07_chapter2.pdf273.97 kBAdobe PDFView/Open
08_chapter3.pdf759.76 kBAdobe PDFView/Open
09_chapter4.pdf2 MBAdobe PDFView/Open
10_chapter5.pdf10.31 kBAdobe PDFView/Open
11_reference.pdf342.42 kBAdobe PDFView/Open
12_publication.pdf32.15 kBAdobe PDFView/Open


Items in Shodhganga are licensed under Creative Commons Licence Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

Altmetric Badge: