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    <title>BURA Collection:</title>
    <link>https://bura.brunel.ac.uk/handle/2438/8625</link>
    <description />
    <items>
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        <rdf:li rdf:resource="https://bura.brunel.ac.uk/handle/2438/33703" />
        <rdf:li rdf:resource="https://bura.brunel.ac.uk/handle/2438/33678" />
        <rdf:li rdf:resource="https://bura.brunel.ac.uk/handle/2438/33655" />
        <rdf:li rdf:resource="https://bura.brunel.ac.uk/handle/2438/33633" />
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    <dc:date>2026-08-18T03:30:54Z</dc:date>
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  <item rdf:about="https://bura.brunel.ac.uk/handle/2438/33703">
    <title>Intelligent Monitoring of Machining Processes using Gaussian Process Regression and On-Machine Comparator Measurement</title>
    <link>https://bura.brunel.ac.uk/handle/2438/33703</link>
    <description>Title: Intelligent Monitoring of Machining Processes using Gaussian Process Regression and On-Machine Comparator Measurement
Authors: Papananias, Moschos; Noh, Yohan; Cheng, Kai
Abstract: This paper presents an intelligent machining process monitoring approach with emphasis on On-Machine Comparator Measurement (OMCM) and the effect of remastering on dimensional accuracy. Comparator measurement applies the comparator principle by referencing each measurement to a calibrated master part. In this approach, a mastering procedure is first performed by measuring the calibrated master part to establish a reference. By directly comparing the test part with the master part under repeatability conditions, constant systematic errors in the measurement system are effectively cancelled when determining deviations from the master part. However, the accuracy of this method depends on the time interval between mastering and subsequent production measurements. An experimental study is conducted on a vertical milling centre using non-intrusive sensing. Gaussian Process Regression (GPR) is employed to model Coordinate Measuring Machine (CMM) measured diameter deviations and the associated uncertainty. OMCM is implemented, and the effect of remastering is discussed. The results demonstrate that measurement accuracy deteriorates when remastering is not performed prior to significant system drift, whereas timely remastering improves accuracy and reduces uncertainty, highlighting the critical role of remastering in maintaining measurement reliability with OMCM.</description>
    <dc:date>2026-06-26T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://bura.brunel.ac.uk/handle/2438/33678">
    <title>Molecular dynamics simulation of high slip flow of water confined between graphene nanochannels at experimentally accessible shear rates</title>
    <link>https://bura.brunel.ac.uk/handle/2438/33678</link>
    <description>Title: Molecular dynamics simulation of high slip flow of water confined between graphene nanochannels at experimentally accessible shear rates
Authors: Civello, Carmelo Riccardo; Maffioli, Luca; Smith, Edward R; Ewen, James P; Daivis, Peter J; Dini, Daniele; Todd, BD
Abstract: The transient time correlation function (TTCF) method has emerged as a powerful methodology for accurately probing systems at low shear rates. In the present study, TTCF was used to evaluate the shear rate dependence of the slip length in a high-slip system consisting of water confined between graphene walls at experimentally accessible shear rates, for which classical nonequilibrium molecular dynamics (NEMD) is unfeasible. The corresponding Navier friction coefficient was computed for all shear rates spanning six orders of magnitude and compared with the equilibrium limit. We report for the first time NEMD results obtained at experimentally accessible shear rates using the TTCF approach for a system that has attracted significant interest over the past decades. The slip length calculated with TTCF is in good agreement with previous equilibrium molecular dynamics simulations and experiments. Our aim here is to highlight the extraordinary power of TTCF, particularly for high-slip (low effective shear rate) systems, and to verify that equilibrium methods directly match NEMD measurements at experimentally accessible shear rates.
Description: Data Availability: &#xD;
The data that support the findings of this study are available within the article and its supplementary material: https://ndownloader.figstatic.com/files/65223213 .</description>
    <dc:date>2026-06-17T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://bura.brunel.ac.uk/handle/2438/33655">
    <title>Extraction and linking of motivation, specification and structure of inventions for early design use</title>
    <link>https://bura.brunel.ac.uk/handle/2438/33655</link>
    <description>Title: Extraction and linking of motivation, specification and structure of inventions for early design use
Authors: Jiang, Pingfei; Atherton, Mark; Sorce, Salvatore
Abstract: Novel design creations often exist in the form of patents. It is well acknowledged that patents are a great source of design inspiration, therefore designers are encouraged to engage patents early in the design process. Studies of patent analysis have been carried out to benefit engineering design activities such as patent classification, technology forecasting, idea generation and emerging design-prior art comparison. However, the design intent behind inventions has received little attention in patent analysis. Designers can gain better design insight by looking at a patent from a systematic perspective starting from design intent to principal solutions. In this paper, an approach is proposed to extract and link the knowledge conveyed within patent descriptive sections to typical early engineering design stages, namely Motivation, Specification and Structure. This knowledge is then conceptualised into TRIZ engineering parameters and reconciled functional basis to enable cross-patent analysis. When compared to expert analysis, the proposed approach achieves an average of 63% accuracy with respect to Motivation, 56% with respect to Specification function and 44% with respect to Specification flow. Potential applications of such linking for early design use are then demonstrated through a prototype knowledge network.</description>
    <dc:date>2023-06-23T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://bura.brunel.ac.uk/handle/2438/33633">
    <title>Toward ultra-low emissions combustion in a dual fuel diesel-hydrogen engine under low load condition: a 3D-CFD study</title>
    <link>https://bura.brunel.ac.uk/handle/2438/33633</link>
    <description>Title: Toward ultra-low emissions combustion in a dual fuel diesel-hydrogen engine under low load condition: a 3D-CFD study
Authors: Pisapia, Alfredo Maria; Rinaldini, Carlo Alberto; Scrignoli, Francesco; Wang, Xinyan; Zhao, Hua
Abstract: Decarbonising Compression Ignition (CI) engines remains critical in marine, heavy-duty and off-road sectors with long asset lifetimes favouring retrofit solutions. Hydrogen can displace Diesel, yet ultra-high Hydrogen Energy Share (HES) is limited by rapid heat release, NOₓ formation and excessive pressure rise. This study employs a 3D-CFD model, calibrated against nine experimental operating points, to numerically explore ultra-high HES in a dual fuel Diesel–hydrogen engine at low load (1200 rpm, IMEP = 6 bar). A single-pilot Reactivity Controlled Compression Ignition (RCCI) strategy, with advanced Diesel injection promoting distributed ignition of an ultra-lean H₂–air mixture, extends hydrogen utilization without violating mechanical or emissions constraints. Two configurations emerge: HES = 96% (SOI = 660°CA) delivers +4.4% gross indicated efficiency, −88.6% CO₂ and −98% NOₓ; HES = 98% (SOI = 655°CA) achieves −94% CO₂ and −99.7% NOₓ. In both cases the peak in-cylinder pressure and the Peak Pressure Rise Rate stay within the structural design limits of the single-cylinder research engine used in this study (180 bar and 20 bar/°CA respectively).</description>
    <dc:date>2026-07-31T00:00:00Z</dc:date>
  </item>
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