This study presents a parameterised finite element modelling approach to predict the temperature field evolution and crystallisation behaviour of short carbon fibre reinforced polyether-ether-ketone (SCF/PEEK) during ...
This study presents a parameterised finite element modelling approach to predict the temperature field evolution and crystallisation behaviour of short carbon fibre reinforced polyether-ether-ketone (SCF/PEEK) during laser-assisted fused filament fabrication (LAFFF). The model innovatively integrates dynamic laser-nozzle heat sources with the melting-crystallisation kinetics of materials, which effectively addresses the longstanding issues of thermal imbalance and non-uniform crystal distribution in composites additive manufacturing. Validated through thermocouple measurements, infrared monitoring, and differential scanning calorimetry, the framework achieves predictive accuracy within ± 5 % for average relative crystallinity and ± 20 % for crystal variance. This research uncovers the crucial role of laser induced through-thickness heat transfer, a characteristic that has not been previously evident in conventional FFF. The results show that optimised auxiliary heating parameters, with ambient temperatures ranging from 75–110 °C and laser power between 2–3 W, create a process window that balances crystallinity enhancement with defect mitigation. Laser preheating generates transient temperature cycles, prolonging the exposure of the material near the crystallisation peak temperature of 235 °C. Meanwhile, elevated ambient temperatures decrease thermal gradients, together expanding the crystallisation window. This synergistic effect boosts the average relative crystallinity by 60 %–82 % compared to conventional rapid - cooling FFF, reaching values similar to those of industrial - grade 3D printing systems. These insights pave the way for the optimisation of thermal conditions in LAFFF, reducing dependence on high-temperature equipment and expanding the applicability of SCF/PEEK 3D printing technology.
We present a differentiable formulation of rigid-body contact dynamics for objects and robots represented as compositions of convex primitives. Existing optimization-based approaches simulating contact between convex ...
This paper presents a new mechanics model for unidirectional notched-tube continuum wrists, a class of mechanisms frequently used to implement distal steering in needle-sized surgical robotic instruments. Existing kin...
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Hepatic vessels in computed tomography scans often suffer from image fragmentation and noise interference, making it difficult to maintain vessel integrity and posing significant challenges for vessel segmentation. To...
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This paper introduces a magneto-electroactive endoluminal soft (MEESo) robot concept, which could enable new classes of catheters, tethered capsule endoscopes, and other mesoscale soft robots designed to navigate the ...
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Rich haptic sensory feedback in response to user interactions is desirable for an effective, immersive virtual reality or teleoperation system. However, this feedback depends on material properties and user interactio...
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ISBN:
(数字)9781728173955
ISBN:
(纸本)9781728173962
Rich haptic sensory feedback in response to user interactions is desirable for an effective, immersive virtual reality or teleoperation system. However, this feedback depends on material properties and user interactions in a complex, non-linear manner. Therefore, it is challenging to model the mapping from material and user interactions to haptic feedback in a way that generalizes over many variations of the user's input. Current methodologies are typically conditioned on user interactions, but require a separate model for each material. In this paper, we present a learned action-conditional model that uses data from a vision-based tactile sensor (GelSight) and user's action as input. This model predicts an induced acceleration that could be used to provide haptic vibration feedback to a user. We trained our proposed model on a publicly available dataset (Penn Haptic Texture Toolkit) that we augmented with GelSight measurements of the different materials. We show that a unified model over all materials outperforms previous methods and generalizes to new actions and new instances of the material categories in the dataset.
In this paper, a kinematic calibration method is developed for a 3rRPS metamorphic parallel mechanism with respect to all unknown parameters. Each limb of the 3rRPS mechanism is composed of (rR), P, and S joints. Two ...
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