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Andy Nichols   Dr.  University Lecturer 
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Andy Nichols published an article in September 2016.
Top co-authors See all
Janet Richardson

232 shared publications

Faculty of Health and Human Sciences, Plymouth University, Plymouth, UK

Shuai Shao

191 shared publications

Department of Mechanical and Industrial Engineering, Louisiana State University, Baton Rouge, LA, USA

Kirill V. Horoshenkov

110 shared publications

Department of Mechanical Engineering, The University of Sheffield, Sheffield S1 3JD, United Kingdom

S. Tait

106 shared publications

Professor of Water Engineering, Dept. of Civil and Structural Engineering, Univ. of Sheffield, Mappin St., Sheffield S1 3JD, UK

S. Shepherd

90 shared publications

The Laboratory of Neural Systems, The Rockefeller University, New York, NY 10065, USA

15
Publications
18
Reads
0
Downloads
20
Citations
Publication Record
Distribution of Articles published per year 
(2009 - 2016)
Publications See all
Article 2 Reads 0 Citations Finite difference time domain modelling of sound scattering by the dynamically rough surface of a turbulent open channel... Kirill V. Horoshenkov, Timothy Van Renterghem, Andrew Nichol... Published: 01 September 2016
Applied Acoustics, doi: 10.1016/j.apacoust.2016.03.009
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The problem of scattering of airborne sound by a dynamically rough surface of a turbulent, open channel flow is poorly understood. In this work, a laser-induced fluorescence (LIF) technique is used to capture accurately a representative number of the instantaneous elevations of the dynamically rough surface of 6 turbulent, subcritical flows in a rectangular flume with Reynolds numbers of 10,800⩽Re⩽47,30010,800⩽Re⩽47,300 and Froude numbers of 0.36⩽Fr⩽0.690.36⩽Fr⩽0.69. The surface elevation data were then used in a finite difference time domain (FDTD) model to predict the directivity pattern of the airborne sound pressure scattered by the dynamically rough flow surface. The predictions obtained with the FDTD model were compared against the sound pressure data measured in the flume and against that obtained with the Kirchhoff approximation. It is shown that the FDTD model agrees with the measured data within 22.3%. The agreement between the FDTD model and stationary phase approximation based on Kirchhoff integral is within 3%. The novelty of this work is in the direct use of the LIF data and FDTD model to predict the directivity pattern of the airborne sound pressure scattered by the flow surface. This work is aimed to inform the design of acoustic instrumentation for non-invasive measurements of hydraulic processes in rivers and in partially filled pipes.
Article 3 Reads 4 Citations A model of the free surface dynamics of shallow turbulent flows Andrew Nichols, Simon J. Tait, Kirill V. Horoshenkov, Simon ... Published: 16 May 2016
Journal of Hydraulic Research, doi: 10.1080/00221686.2016.1176607
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Article 6 Reads 1 Citation Achieving cost and carbon savings in neonatal practice: A review of the literature on sustainable waste management Andy Nichols, Jane Grose, Rumbidzai Mukonoweshuro Published: 01 April 2016
Journal of Neonatal Nursing, doi: 10.1016/j.jnn.2016.01.002
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BOOK-CHAPTER 2 Reads 0 Citations Potential Application of Mesh-Free SPH Method in Turbulent River Flows Ehsan Kazemi, Simon Tait, Songdong Shao, Andrew Nichols Published: 01 January 2016
GeoPlanet: Earth and Planetary Sciences, doi: 10.1007/978-3-319-27750-9_2
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Article 2 Reads 4 Citations A non-invasive acoustical method to measure the mean roughness height of the free surface of a turbulent shallow water f... A. Krynkin, Kirill Horoshenkov, Andrew Nichols, S. J. Tait Published: 01 November 2014
Review of Scientific Instruments, doi: 10.1063/1.4901932
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In this paper, the directivity of the airborne sound field scattered by a dynamically rough free flow surface in a flume is used to determine the mean roughness height for six hydraulic conditions in which the uniform depth of the turbulent flow. The nonlinear curve fitting method is used to minimize the error between the predicted directivity and directivity data. The data fitting algorithm is based on the averaged solution for the scattered sound pressure as a function of angle which is derived through the Kirchhoff integral and its approximations. This solution takes into account the directivity of the acoustic source. For the adopted source and receiver geometry and acoustic frequency it is shown that the contribution from the stationary phase point (single specular point on the rough surface) yields similar results to those which can be obtained through the full Kirchhoff's integral. The accuracy in the inverted mean roughness height is comparable to that achieved with an array of conductive wave probes. This method enables non-invasive estimation of the flow Reynolds number and uniform flow depth.
Article 3 Reads 0 Citations Physical space and its impact on waste management in the neonatal care setting Andrew Nichols, Sean Manzi Published: 01 July 2014
Journal of Infection Prevention, doi: 10.1177/1757177414531632
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