1,569 research outputs found

    Carbon Black Reinforcement of Tyre Tread Compounds

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    The tyre industry is the leading consumer of rubber materials, accounting for approximately 70% of annual natural rubber production. The inherent properties and strength of rubber makes it suitable for engineering applications. However, to have useful lifetimes, rubber needs to be reinforced with fillers such as carbon black or silica. Fillers account for approximately 30% of materials by weight used in tyre tread compounds with CB being the most widely used reinforcing filler in tyres and engineering rubber materials. Various studies have shown that CB generally enhances properties such as modulus, tensile and tear strength, crack growth and abrasion resistance. For tyre tread applications, CB also influences other properties such as rolling resistance and grip. Less understood though, is how the morphological properties of CB influence fatigue and fracture properties of the rubber composite. The aim of this thesis is to conduct a systematic study to understand how these CB morphological properties including the structure and surface area affect reinforcement in tyre tread compounds. Eight different CB fillers varying widely in their structure and surface area were examined. The wide variation of CBs allows quantitative correlations to be drawn to understand the extent the CB properties affect these parameters. The CBs had an equivalent loading of 50 parts per hundred (phr) in natural rubber. An unfilled equivalent was also included. A series of experiments including conventional static and dynamic mechanical tests, strain induced crystallisation estimations, heat build-up and energy dissipation characterisation, fatigue crack growth resistance measurements, intrinsic and critical tear strength tests were conducted. Abrasion resistance as well as cut and chip resistance experiments were also performed. The results show the controlling CB morphological property is influenced by parameters such as the applied strain level, strain rate, severity of loading and the predominant deformation type (strain-, energy- or stress- controlled) in the test or application. Increasing CB surface area generally increases heat build-up and energy dissipation while CB structure affects crystallinity due to strain amplification effects. There is a step change in crack growth resistance below certain tearing energies which is attributed to the kinetics of strain induced crystallisation. There is a flip in ranking of cut and chip damage, with high structure CB compounds preferred at low impact forces and low structure CB compounds preferred at high impact forces. Abrasion tests show the formation of smear wear causes better abrasion resistance. The formation of smear wear is a factor of both the CB structure and surface area. Overall, the results highlight the difficulty to simultaneously optimise different parameters in tyre tread design. However, this work provides the tyre design engineer greater clarity on which CB to use to obtain a desired performance

    Temperature Reduction Technologies Meet Asphalt Pavement: Green and Sustainability

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    This Special Issue, "Temperature Reduction Technologies Meet Asphalt Pavement: Green and Sustainability", covers various subjects related to advanced temperature reduction technologies in bituminous materials. It can help civil engineers and material scientists better identify underlying views for sustainable pavement constructions

    Designing LMPA-Based Smart Materials for Soft Robotics Applications

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    This doctoral research, Designing LMPA (Low Melting Point Alloy) Based Smart Materials for Soft Robotics Applications, includes the following topics: (1) Introduction; (2) Robust Bicontinuous Metal-Elastomer Foam Composites with Highly Tunable Mechanical Stiffness; (3) Actively Morphing Drone Wing Design Enabled by Smart Materials for Green Unmanned Aerial Vehicles; (4) Dynamically Tunable Friction via Subsurface Stiffness Modulation; (5) LMPA Wool Sponge Based Smart Materials with Tunable Electrical Conductivity and Tunable Mechanical Stiffness for Soft Robotics; and (6) Contributions and Future Work.Soft robots are developed to interact safely with environments. Smart composites with tunable properties have found use in many soft robotics applications including robotic manipulators, locomotors, and haptics. The purpose of this work is to develop new smart materials with tunable properties (most importantly, mechanical stiffness) upon external stimuli, and integrate these novel smart materials in relevant soft robots. Stiffness tunable composites developed in previous studies have many drawbacks. For example, there is not enough stiffness change, or they are not robust enough. Here, we explore soft robotic mechanisms integrating stiffness tunable materials and innovate smart materials as needed to develop better versions of such soft robotic mechanisms. First, we develop a bicontinuous metal-elastomer foam composites with highly tunable mechanical stiffness. Second, we design and fabricate an actively morphing drone wing enabled by this smart composite, which is used as smart joints in the drone wing. Third, we explore composite pad-like structures with dynamically tunable friction achieved via subsurface stiffness modulation (SSM). We demonstrate that when these composite structures are properly integrated into soft crawling robots, the differences in friction of the two ends of these robots through SSM can be used to generate translational locomotion for untethered crawling robots. Also, we further develop a new class of smart composite based on LMPA wool sponge with tunable electrical conductivity and tunable stiffness for soft robotics applications. The implications of these studies on novel smart materials design are also discussed

    Systemic Circular Economy Solutions for Fiber Reinforced Composites

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    This open access book provides an overview of the work undertaken within the FiberEUse project, which developed solutions enhancing the profitability of composite recycling and reuse in value-added products, with a cross-sectorial approach. Glass and carbon fiber reinforced polymers, or composites, are increasingly used as structural materials in many manufacturing sectors like transport, constructions and energy due to their better lightweight and corrosion resistance compared to metals. However, composite recycling is still a challenge since no significant added value in the recycling and reprocessing of composites is demonstrated. FiberEUse developed innovative solutions and business models towards sustainable Circular Economy solutions for post-use composite-made products. Three strategies are presented, namely mechanical recycling of short fibers, thermal recycling of long fibers and modular car parts design for sustainable disassembly and remanufacturing. The validation of the FiberEUse approach within eight industrial demonstrators shows the potentials towards new Circular Economy value-chains for composite materials

    The Global Riverine Hydrokinetic Resource

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    Polymer-based 3-D printing of G-band metal-pipe rectangular waveguide components

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    The objective of this thesis is to investigate the use of low-cost polymer-based 3-D printing for G-band (140 to 220 GHz) metal-pipe rectangular waveguide (MPRWG) components. First, various preliminary designs are investigated. Then, a successful ‘trough-and-lid’ assembly is demonstrated, which mitigates against the main design challenges for split-block waveguide construction at upper-millimeter-wave frequencies (ca. 100 GHz to 300 GHz), and can be realized using low-cost 3-D printing and conventional metal plating techniques. With this assembly, inexpensive masked stereolithographic apparatus (MSLA) 3-D printers and a standard commercial copper electroplating service are used. The trough-and-lid assembly is expected to provide a standard solution for the low-cost and low loss realization of most MPRWG implementations above 100 GHz; previously, this was infeasible without the use of high-cost, state-of-the-art 3-D printing and/or custom-developed metal plating techniques. Three different component types are successfully demonstrated: (i) straight thru lines; (ii) 90° twists; and (iii) bandpass filters (BPFs). Along with frequency-domain S-parameter measurements, a detailed time-domain reflectometry analysis is also included. For the more accurate characterization of these components, the additional insertion loss due to conductor surface roughness is investigated. Finally, the integration of an MPRWG component into a millimeter-wave subsystem, which is based on the design of a radiometer front-end, is presented.Open Acces

    Ensemble Machine Learning Model Generalizability and its Application to Indirect Tool Condition Monitoring

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    A practical, accurate, robust, and generalizable system for monitoring tool condition during a machining process would enable advancements in manufacturing process automation, cost reduction, and efficiency improvement. Previously proposed systems using various individual machine learning (ML) models and other analysis techniques have struggled with low generalizability to new machining and environmental conditions, as well as a common reliance on expensive or intrusive sensory equipment which hinders their industry adoption. While ensemble ML techniques offer significant advantages over individual models in terms of performance, overfitting reduction, and generalizability improvement, they have only begun to see limited applications within the field of tool condition monitoring (TCM). To address the research gaps which currently surround TCM system generalizability and optimal ensemble model configuration for this application, nine ML model types, including five heterogeneous and homogeneous ensemble models, are employed for tool wear classification. Sound, spindle power, and axial load signals are utilized through the sensor fusion of practical external and internal machine sensors. This original experimental process data is collected through tool wear experiments using a variety of machining conditions. Four feature selection methods and multiple tool wear classification resolution values are compared for this application, and the performance of the ML models is compared across metrics including k-fold cross validation and leave-one-group-out cross validation. The generalizability of the models to data from unseen experiments and machining conditions is evaluated, and a method of improving the generalizability levels using noisy training data is examined. T-tests are used to measure the significance of model performance differences. The extra-trees ensemble ML method, which had never before been applied to signal-based TCM, shows the best performance of the nine models.M.S

    Analysis, Design and Fabrication of Micromixers, Volume II

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    Micromixers are an important component in micrototal analysis systems and lab-on-a-chip platforms which are widely used for sample preparation and analysis, drug delivery, and biological and chemical synthesis. The Special Issue "Analysis, Design and Fabrication of Micromixers II" published in Micromachines covers new mechanisms, numerical and/or experimental mixing analysis, design, and fabrication of various micromixers. This reprint includes an editorial, two review papers, and eleven research papers reporting on five active and six passive micromixers. Three of the active micromixers have electrokinetic driving force, but the other two are activated by mechanical mechanism and acoustic streaming. Three studies employs non-Newtonian working fluids, one of which deals with nano-non-Newtonian fluids. Most of the cases investigated micromixer design
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