M. MacDonald

559 total citations
19 papers, 405 citations indexed

About

M. MacDonald is a scholar working on Computational Mechanics, Environmental Engineering and Aerospace Engineering. According to data from OpenAlex, M. MacDonald has authored 19 papers receiving a total of 405 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computational Mechanics, 7 papers in Environmental Engineering and 6 papers in Aerospace Engineering. Recurrent topics in M. MacDonald's work include Fluid Dynamics and Turbulent Flows (16 papers), Wind and Air Flow Studies (7 papers) and Aerodynamics and Acoustics in Jet Flows (6 papers). M. MacDonald is often cited by papers focused on Fluid Dynamics and Turbulent Flows (16 papers), Wind and Air Flow Studies (7 papers) and Aerodynamics and Acoustics in Jet Flows (6 papers). M. MacDonald collaborates with scholars based in Australia, New Zealand and United Kingdom. M. MacDonald's co-authors include Daniel Chung, Nicholas Hutchins, Leon Chan, Andrew Ooi, Ricardo García-Mayoral, Davide Modesti, Richard Clarke, João Teixeira, John Cater and Wai Yie Leong and has published in prestigious journals such as Journal of Fluid Mechanics, Boundary-Layer Meteorology and Ocean Engineering.

In The Last Decade

M. MacDonald

17 papers receiving 393 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
M. MacDonald Australia	7	355	157	138	120	89	19	405
Thomas O. Jelly Australia	10	356 1.0×	179 1.1×	88 0.6×	110 0.9×	50 0.6×	26	422
Jinyul Hwang South Korea	12	416 1.2×	153 1.0×	146 1.1×	62 0.5×	135 1.5×	25	428
Alireza Ashrafian Norway	7	388 1.1×	228 1.5×	142 1.0×	82 0.7×	87 1.0×	10	432
Leon Chan Australia	12	456 1.3×	136 0.9×	170 1.2×	140 1.2×	74 0.8×	41	552
El‐Sayed Zanoun Germany	10	352 1.0×	186 1.2×	130 0.9×	86 0.7×	62 0.7×	27	428
Amirreza Rouhi Australia	9	271 0.8×	91 0.6×	93 0.7×	60 0.5×	53 0.6×	17	311
Caleb Morrill-Winter Australia	9	331 0.9×	88 0.6×	217 1.6×	71 0.6×	133 1.5×	16	350
Eda Doğan United Kingdom	10	250 0.7×	84 0.5×	158 1.1×	103 0.9×	67 0.8×	14	313
William Hambleton United States	6	498 1.4×	102 0.6×	275 2.0×	78 0.7×	175 2.0×	9	541
Krishna M. Talluru Australia	12	410 1.2×	104 0.7×	308 2.2×	62 0.5×	128 1.4×	29	480

Countries citing papers authored by M. MacDonald

Since Specialization

Citations

This map shows the geographic impact of M. MacDonald's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by M. MacDonald with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. MacDonald more than expected).

Fields of papers citing papers by M. MacDonald

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. MacDonald. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by M. MacDonald. The network helps show where M. MacDonald may publish in the future.

Co-authorship network of co-authors of M. MacDonald

This figure shows the co-authorship network connecting the top 25 collaborators of M. MacDonald. A scholar is included among the top collaborators of M. MacDonald based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with M. MacDonald. M. MacDonald is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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19 of 19 papers shown

MacDonald, M., et al.. (2025). Unraveling the drag crisis of large spheres in vertical turbulent pipe flow for deep-sea mining: a 6-DOF CFD investigation. Ocean Engineering. 340. 122292–122292. 1 indexed citations

Cater, John, et al.. (2025). Direct Numerical Simulation of Fog Formation with Turbulence and Longwave Radiation. Boundary-Layer Meteorology. 191(7).

Armfield, S.W., et al.. (2024). Universal relative scaling of longitudinal structure functions in shear-dominated turbulence. Journal of Fluid Mechanics. 984.

MacDonald, M.. (2024). Direct numerical simulation of momentum and scalar internal boundary layers. International Journal of Heat and Fluid Flow. 106. 109285–109285. 2 indexed citations

Wang, Zhongwei, et al.. (2023). Experimental investigation on the dynamics of buoyancy-induced vortices. International Journal of Heat and Fluid Flow. 105. 109265–109265. 1 indexed citations

Leong, Wai Yie, M. MacDonald, John Cater, & Richard G.J. Flay. (2022). A review of atmospheric vortex engines for power generation. Journal of Wind Engineering and Industrial Aerodynamics. 230. 105200–105200. 2 indexed citations

Modesti, Davide, et al.. (2020). Direct Numerical Simulations of Turbulent Flow Over Various Riblet Shapes in Minimal-Span Channels. Flow Turbulence and Combustion. 107(1). 1–29. 24 indexed citations

MacDonald, M., et al.. (2020). Numerical Simulations of Laboratory–Scale Buoyancy Vortices. ResearchSpace (University of Auckland). 1 indexed citations

MacDonald, M., Marcin J. Kurowski, & João Teixeira. (2020). Direct Numerical Simulation of the Moist Stably Stratified Surface Layer: Turbulence and Fog Formation. Boundary-Layer Meteorology. 175(3). 343–368. 4 indexed citations

10.

Flay, Richard G.J., et al.. (2020). Scaling of Experimental Buoyancy Vortex Structures with Respect to Power Generation. Journal of Physics Conference Series. 1618(3). 32008–32008. 2 indexed citations

11.

MacDonald, M., Nicholas Hutchins, & Daniel Chung. (2018). Roughness effects in turbulent forced convection. Journal of Fluid Mechanics. 861. 138–162. 56 indexed citations

12.

Chan, Leon, M. MacDonald, Daniel Chung, Nicholas Hutchins, & Andrew Ooi. (2018). Secondary motion in turbulent pipe flow with three-dimensional roughness. Journal of Fluid Mechanics. 854. 5–33. 64 indexed citations

13.

MacDonald, M., et al.. (2018). Manipulation of near-wall turbulence by surface slip and permeability. Journal of Physics Conference Series. 1001. 12011–12011. 15 indexed citations

14.

MacDonald, M., Daniel Chung, Nicholas Hutchins, et al.. (2017). The minimal-span channel for rough-wall turbulent flows. Journal of Fluid Mechanics. 816. 5–42. 60 indexed citations

15.

Chan, Leon, M. MacDonald, Daniel Chung, Nicholas Hutchins, & Andrew Ooi. (2017). Analysis of the coherent and turbulent stresses of a numerically simulated rough wall pipe. Journal of Physics Conference Series. 822. 12011–12011. 1 indexed citations

16.

MacDonald, M., Daniel Chung, Nicholas Hutchins, et al.. (2016). The minimal channel: a fast and direct method for characterising roughness. Journal of Physics Conference Series. 708. 12010–12010. 8 indexed citations

17.

Chan, Leon, M. MacDonald, Daniel Chung, Nicholas Hutchins, & Andrew Ooi. (2015). A systematic investigation of roughness height and wavelength in turbulent pipe flow in the transitionally rough regime. Journal of Fluid Mechanics. 771. 743–777. 157 indexed citations

18.

Chan, Leon, M. MacDonald, Daniel Chung, Nicholas Hutchins, & Andrew Ooi. (2014). Numerical simulation of a rough-wall pipe from the transitionally rough regime to the fully rough regime. 1 indexed citations

19.

Clarke, Richard, et al.. (2014). Hydrodynamic persistence within very dilute two-dimensional suspensions of squirmers. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 470(2167). 20130508–20130508. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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