JOURNAL OF ADHESION - Journal - Bridge of Knowledge

Search

JOURNAL OF ADHESION

ISSN:

0021-8464

eISSN:

1545-5823

Disciplines
(Field of Science):

  • automation, electronics, electrical engineering and space technologies (Engineering and Technology)
  • biomedical engineering (Engineering and Technology)
  • chemical engineering (Engineering and Technology)
  • civil engineering, geodesy and transport (Engineering and Technology)
  • materials engineering (Engineering and Technology)
  • mechanical engineering (Engineering and Technology)
  • environmental engineering, mining and energy (Engineering and Technology)
  • pharmacology and pharmacy (Medical and Health Sciences )
  • forestry (Agricultural sciences)
  • agriculture and horticulture (Agricultural sciences)
  • chemical sciences (Natural sciences)

Ministry points: Help

Ministry points - current year
Year Points List
Year 2024 100 Ministry scored journals list 2024
Ministry points - previous years
Year Points List
2024 100 Ministry scored journals list 2024
2023 100 Ministry Scored Journals List
2022 100 Ministry Scored Journals List 2019-2022
2021 100 Ministry Scored Journals List 2019-2022
2020 100 Ministry Scored Journals List 2019-2022
2019 100 Ministry Scored Journals List 2019-2022
2018 25 A
2017 25 A
2016 25 A
2015 25 A
2014 20 A
2013 20 A
2012 25 A
2011 25 A
2010 27 A

Model:

Hybrid

Points CiteScore:

Points CiteScore - current year
Year Points
Year 2023 5.3
Points CiteScore - previous years
Year Points
2023 5.3
2022 4.4
2021 4.9
2020 4.9
2019 4.3
2018 3.4
2017 3.3
2016 2.7
2015 2.5
2014 2.1
2013 1.9
2012 2
2011 1.7

Impact Factor:

Log in to see the Impact Factor.

Filters

total: 6

  • Category
  • Year
  • Options

clear Chosen catalog filters disabled

Catalog Journals

Year 2023
  • A Bayesian regularization-backpropagation neural network model for peeling computations
    Publication
    • S. Gouravaraju
    • J. Narayan
    • R. Sauer
    • S. S. Gautam

    - JOURNAL OF ADHESION - Year 2023

    A Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...

    Full text available to download

Year 2020
Year 2012
  • Impact of interface heterogeneity on joint fracture
    Publication
    • M. Budzik
    • J. Jumel
    • M. Shanahan

    - JOURNAL OF ADHESION - Year 2012

    The effects of heterogeneities (weak zones in particular) inadhesive joints and their importance on overall fracture propertiesare relatively unknown, but doubtlessly they may be crucial inmany applications. Using a model heterogeneous adhesive bond,represented by a given mixture of regions of strong and weakadhesion, we have studied the influence of interface variabilityon overall fracture energy (global energy release rate)....

    Full text to download in external service

Year 2011
Year 2009
  • Fracture in composite/aluminium joints of variable adhesive properties
    Publication

    - JOURNAL OF ADHESION - Year 2009

    A strain gauge technique recently developed with the wedge test, for estimating crack length and, thus, the fracture energy of structural adhesive bonding, has been employed on a system in which one adherend had two types of surface treatment. Simple polishing and polishing with subsequent sandblasting were the treatments used, with a distinct straight line, perpendicular to the sample edges, separating the two. Despite the clear-cut...

    Full text to download in external service

seen 1402 times