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Gabriel Lodewijks

Researcher at University of New South Wales

Publications -  251
Citations -  3819

Gabriel Lodewijks is an academic researcher from University of New South Wales. The author has contributed to research in topics: Container (abstract data type) & Ultimate tensile strength. The author has an hindex of 28, co-authored 242 publications receiving 2846 citations. Previous affiliations of Gabriel Lodewijks include Wuhan University of Technology & University of Science and Technology Beijing.

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DEM speedup: Stiffness effects on behavior of bulk material

TL;DR: In this paper, the authors investigated the effect of particle stiffness reduction on bulk behavior by examining three case studies and showed that particle stiffness can be reduced without affecting the bulk material behavior, whereas the third test showed that a stiffness reduction influenced the bulk behavior.
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Physical properties of solid biomass

TL;DR: In this article, the physical material properties of three types of solid biomass fuels: wood pellets, wood chips and torrefied pellets are studied. And the experimental setup as well as relevant standards (e.g. ASTM and CEN) are described.
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Micro–macro properties of quartz sand: Experimental investigation and DEM simulation

TL;DR: In this paper, the authors used a slice of a domain instead of the whole domain where the material slice represents the realistic mechanical behavior of materials and used it to calibrate the microscopic properties of granular materials by discrete element method (DEM).
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Detecting fatigue in car drivers and aircraft pilots by using non-invasive measures: the value of differentiation of sleepiness and mental fatigue

TL;DR: This paper aims to give psychological insight of the existing non-invasive measures for driver and pilot fatigue by differentiating sleepiness and mental fatigue, and discusses on the future directions in terms of methodology of conducting operator fatigue research and fatigue analysis by using eye-related parameters.
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Condition monitoring approaches for the detection of railway wheel defects

TL;DR: The existing data acquisition techniques for the monitoring of railway wheel condition are reviewed, and the state-of-the-art methods and required research are discussed.