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    <title>OPUS Collection:</title>
    <link>http://hdl.handle.net/10453/35200</link>
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        <rdf:li rdf:resource="http://hdl.handle.net/10453/195073" />
        <rdf:li rdf:resource="http://hdl.handle.net/10453/195072" />
        <rdf:li rdf:resource="http://hdl.handle.net/10453/195071" />
        <rdf:li rdf:resource="http://hdl.handle.net/10453/195029" />
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    <dc:date>2026-05-21T06:10:07Z</dc:date>
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  <item rdf:about="http://hdl.handle.net/10453/195073">
    <title>Conceptual and Computational Perspectives of Sustainable Rail Geotechnics</title>
    <link>http://hdl.handle.net/10453/195073</link>
    <description>Title: Conceptual and Computational Perspectives of Sustainable Rail Geotechnics
Authors: Indraratna, B; Qi, Y; Ngo, T; Malisetty, R; Rujikiatkamjorn, C
Abstract: Given the rapidly evolving national policies of many countries which actively promote the socio-economic and environmental perspectives of circular economy, the Transport Research Centre at the University of Technology Sydney has launched innovative measures of adopting off-the-road rubber tyres, recycled rubber derivatives and granular by-products from mining and steel industry in novel track design. This paper presents some salient features evolving through mathematical formulations and numerical modelling of ballasted track components incorporating recycled wastes, with special reference to: (i) a coupled rheological and continuum mechanics approach to predict a more accurate track dynamic response to evaluate the most suitable speeds and axle loads for specific substructure conditions under the influence of rubber inclusions, (ii) hybrid Discrete-Finite Element Method (DEM-FEM) simulations to micro-mechanically characterize ballast behavior with and with-out recycled rubber mats with a particular focus on ballast breakage. These computational modelling processes were calibrated and validated through comprehensive laboratory and field tests. The research outcomes provide a deeper understanding of the geotechnical effectiveness and performance enhancement of novel ballast tracks that incorporate blended waste materials.</description>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
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  <item rdf:about="http://hdl.handle.net/10453/195072">
    <title>The Modified Critical-State Framework of a Waste Mixture Concerning the Addition of Rubber</title>
    <link>http://hdl.handle.net/10453/195072</link>
    <description>Title: The Modified Critical-State Framework of a Waste Mixture Concerning the Addition of Rubber
Authors: Qi, Y; Indraratna, B
Abstract: The practical application of recycled and marginal materials such as scrap tyres and mining by-products in railways is becoming more prevalent. This paper investigates the fundamental stress-strain behaviour of a granular waste matrix (steel furnace slags blended with coal wash and recycled rubber granules) to serve as the railway subballast. The findings indicate that the incorporation of rubber has a substantial impact on the geotechnical properties of the waste mixtures, especially the dilatancy response and the ability to attain the critical state. For the mixtures with a higher amount of rubber (20–40%) that could not achieve the critical state, extrapolation was adopted to obtain the critical state parameters. A critical state surface was developed by capturing the effect of rubber inclusions. Moreover, a semi-empirical model was established to predict the dilatancy response of the waste composites by modifying the critical state parameters and incorporating the energy input.</description>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
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  <item rdf:about="http://hdl.handle.net/10453/195071">
    <title>Use of Recycled Rubber Granulates in Railway Subballast for Improved Track Performance</title>
    <link>http://hdl.handle.net/10453/195071</link>
    <description>Title: Use of Recycled Rubber Granulates in Railway Subballast for Improved Track Performance
Authors: Qi, Y; Indraratna, B; Malisetty, R
Abstract: As current ballasted tracks are inadequate for supporting Australia’s faster, heavier freight trains, there is an urgent need to develop innovative and sustainable alternatives for transport infrastructure. This paper presents a novel solution for increasing the stability and resiliency of railways by developing a sustainable energy-absorbing subballast layer (SEAL) using recycled tire rubber granulates, steel furnace slag, and coal wash to replace traditional rockfill as subballast. The engineering properties of the track incorporating SEAL were investigated through large-scale laboratory tests (i.e., prototype cubic triaxial tests) and a rheological model. The test results and model simulation confirm that the inclusion of recycled rubber granulates actively increases the efficiency of dissipating energy, decreases ballast breakage, vibrations, and the propagation of dynamic loading within the substructure depth. Also, 10% by weight was found to be the optimal rubber content within SEAL to increase the energy-absorbing capacity of the track foundation and decrease the lateral displacements of the track, while reducing the amount of ballast breakage and maintaining an acceptable settlement.</description>
    <dc:date>2026-03-05T00:00:00Z</dc:date>
  </item>
  <item rdf:about="http://hdl.handle.net/10453/195029">
    <title>Reconstructing hysteresis behavior for magnetorheological elastomer base isolator using bi-fidelity transferring evolution</title>
    <link>http://hdl.handle.net/10453/195029</link>
    <description>Title: Reconstructing hysteresis behavior for magnetorheological elastomer base isolator using bi-fidelity transferring evolution
Authors: Ding, Z; Kuok, SC; Chen, Z; Noori, M; Yu, Y; Yuen, KV
Abstract: This study proposes a novel methodology to characterize and predict nonlinear hysteresis behavior of a magnetorheological elastomer (MRE) base isolator. A Maxwell nonlinear model is utilized to capture the force-displacement and force-velocity loops under varying input currents. To enable efficient and rapid reconstruction of nonlinear responses, a surrogate-assisted evolutionary algorithm (EA) is developed, incorporating a clustering-driven online learning model management mechanism for bi-fidelity optimization. Specifically, an incremental Kriging model is constructed to approximate the high-fidelity objective function, serving as a low-fidelity evaluation. Representative solutions, determined through K-means clustering and the Kriging model, are selectively transferred to high-fidelity evaluations, guiding the search for the global optimum. Experimental data of displacement, velocity, and force obtained from the MRE isolator are used to validate the proposed algorithm, demonstrating highly accurate predictions with exceptional computational efficiency.</description>
    <dc:date>2025-11-15T00:00:00Z</dc:date>
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