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S.L. Lemanski

Researcher at Coventry University

Publications -  23
Citations -  648

S.L. Lemanski is an academic researcher from Coventry University. The author has contributed to research in topics: Stiffness & Finite element method. The author has an hindex of 11, co-authored 23 publications receiving 539 citations. Previous affiliations of S.L. Lemanski include University of Cambridge & University of Bristol.

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Behaviour of fibre–metal laminates subjected to localised blast loading: Part I—Experimental observations

TL;DR: In this paper, the authors examined the behavior of aluminium alloy-glass fiber-reinforced polypropylene-based fiber-metal laminates (FMLs) subjected to localised explosive blast loading.
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Behaviour of fibre metal laminates subjected to localised blast loading—Part II: Quantitative analysis

TL;DR: In this paper, the authors examined the behaviour of fiber-metal laminates subjected to localised explosive blast loading and found that the threshold impulse for the onset of tearing increases linearly with panel thickness.
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Measurement of fibre waviness in industrial composite components

TL;DR: In this article, the authors measured the length and width of the waviness region along and transverse to the fibres using autocorrelation and found that the length is in the range 1.1-4.4mm, being significantly greater in the prepreg than in the RTM component.
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Failure characterisation of blast-loaded fibre–metal laminate panels based on aluminium and glass–fibre reinforced polypropylene

TL;DR: In this paper, failure characterisation of the blast-loaded square fiber-metal laminate panels, identifying trends and failure modes for each panel type, including debonding, large plastic displacement, fibre fracture and matrix cracking are identified as damage mechanisms within the panels.
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Modelling failure of composite specimens with defects under compression loading

TL;DR: In this article, the authors used finite element models of composite failure to predict failure in situations where the failure mechanism was not known in advance, and the model predictions correlate well with experimental results, both qualitatively (location of failure and shape of failed specimen) and quantitatively (failure load).