Phillip Paevere

1.3k total citations
26 papers, 992 citations indexed

About

Phillip Paevere is a scholar working on Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment and Building and Construction. According to data from OpenAlex, Phillip Paevere has authored 26 papers receiving a total of 992 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Electrical and Electronic Engineering, 10 papers in Renewable Energy, Sustainability and the Environment and 9 papers in Building and Construction. Recurrent topics in Phillip Paevere's work include Electric Vehicles and Infrastructure (7 papers), Energy, Environment, and Transportation Policies (5 papers) and Building Energy and Comfort Optimization (4 papers). Phillip Paevere is often cited by papers focused on Electric Vehicles and Infrastructure (7 papers), Energy, Environment, and Transportation Policies (5 papers) and Building Energy and Comfort Optimization (4 papers). Phillip Paevere collaborates with scholars based in Australia, United States and Malaysia. Phillip Paevere's co-authors include Greg Foliente, Fai Ma, H. Zhang, Zhengen Ren, Bohumil Kasal, Andrew Higgins, Stephen K. Brown, George Grozev, John M. Gardner and Andrew Higgins and has published in prestigious journals such as Applied Energy, Energy Policy and Journal of Applied Mechanics.

In The Last Decade

Phillip Paevere

25 papers receiving 938 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Phillip Paevere Australia 17 299 284 275 170 144 26 992
Joshua D. Rhodes United States 18 497 1.7× 133 0.5× 1.1k 3.9× 137 0.8× 362 2.5× 40 1.6k
Pablo Eguía Spain 21 534 1.8× 78 0.3× 200 0.7× 316 1.9× 236 1.6× 68 1.2k
Tullio de Rubeis Italy 21 732 2.4× 103 0.4× 222 0.8× 295 1.7× 208 1.4× 56 1.2k
Nuno Simões Portugal 21 819 2.7× 159 0.6× 72 0.3× 366 2.2× 116 0.8× 100 1.4k
Deng Zhang China 20 538 1.8× 94 0.3× 440 1.6× 322 1.9× 137 1.0× 65 1.3k
Kristen Cetin United States 26 1.0k 3.4× 288 1.0× 378 1.4× 510 3.0× 244 1.7× 108 1.7k
Bin Hao China 13 254 0.8× 31 0.1× 170 0.6× 136 0.8× 113 0.8× 56 738
Giuseppe Oliveti Italy 25 638 2.1× 64 0.2× 419 1.5× 397 2.3× 366 2.5× 51 1.6k
Jian Lin China 19 98 0.3× 189 0.7× 612 2.2× 88 0.5× 294 2.0× 37 1.2k

Countries citing papers authored by Phillip Paevere

Since Specialization
Citations

This map shows the geographic impact of Phillip Paevere'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 Phillip Paevere with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phillip Paevere more than expected).

Fields of papers citing papers by Phillip Paevere

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Phillip Paevere. 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 Phillip Paevere. The network helps show where Phillip Paevere may publish in the future.

Co-authorship network of co-authors of Phillip Paevere

This figure shows the co-authorship network connecting the top 25 collaborators of Phillip Paevere. A scholar is included among the top collaborators of Phillip Paevere 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 Phillip Paevere. Phillip Paevere is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Goodman, Nigel, Amanda J. Wheeler, Phillip Paevere, et al.. (2018). Indoor volatile organic compounds at an Australian university. Building and Environment. 135. 344–351. 34 indexed citations
2.
Goodman, Nigel, et al.. (2018). Emissions from dryer vents during use of fragranced and fragrance-free laundry products. Air Quality Atmosphere & Health. 12(3). 289–295. 16 indexed citations
3.
Goodman, Nigel, Anne Steinemann, Amanda J. Wheeler, et al.. (2017). Volatile organic compounds within indoor environments in Australia. Building and Environment. 122. 116–125. 64 indexed citations
4.
Usher, John M., et al.. (2015). Impacts of policy on electric vehicle diffusion. UTS ePRESS (University of Technology Sydney). 1 indexed citations
5.
Motlagh, O., Phillip Paevere, Tang Sai Hong, & George Grozev. (2015). Analysis of household electricity consumption behaviours: Impact of domestic electricity generation. Applied Mathematics and Computation. 270. 165–178. 36 indexed citations
6.
Wang, Chi‐Hsiang, et al.. (2014). Statistical modeling of Electric Vehicle electricity consumption in the Victorian EV Trial, Australia. Transportation Research Part D Transport and Environment. 32. 263–277. 67 indexed citations
7.
Ren, Zhengen, et al.. (2013). A model for predicting household end-use energy consumption and greenhouse gas emissions in Australia. International Journal of Sustainable Building Technology and Urban Development. 4(3). 210–228. 55 indexed citations
8.
Paevere, Phillip, et al.. (2013). Spatio-temporal modelling of electric vehicle charging demand and impacts on peak household electrical load. Sustainability Science. 9(1). 61–76. 53 indexed citations
9.
Ren, Zhengen, et al.. (2013). Assessment of end-use electricity consumption and peak demand by Townsville's housing stock. Energy Policy. 61. 888–893. 14 indexed citations
10.
Ren, Zhengen, et al.. (2012). A local-community-level, physically-based model of end-use energy consumption by Australian housing stock. Energy Policy. 49. 586–596. 47 indexed citations
11.
Higgins, Andrew, et al.. (2012). Combining choice modelling and multi-criteria analysis for technology diffusion: An application to the uptake of electric vehicles. Technological Forecasting and Social Change. 79(8). 1399–1412. 85 indexed citations
12.
Paevere, Phillip, Andrew Higgins, Zhengen Ren, et al.. (2012). Spatial Modelling of Electric Vehicle Charging Demand and Impacts on Peak Household Electrical Load in Victoria, Australia. 8 indexed citations
13.
Paevere, Phillip, Andrew Higgins, George Grozev, Zhengen Ren, & Mark Horn. (2012). Electric Vehicles and the Smart Grid: Spatial Modelling of Impacts and Opportunities. World Electric Vehicle Journal. 5(3). 739–747. 1 indexed citations
14.
Paevere, Phillip & Stephen K. Brown. (2008). Indoor Environment Quality and Occupant Productivity in the CH2 Building: Post-Occupancy Summary. 22 indexed citations
15.
Collins, Michael, Bohumil Kasal, Phillip Paevere, & Greg Foliente. (2005). Three-Dimensional Model of Light Frame Wood Buildings. II: Experimental Investigation and Validation of Analytical Model. Journal of Structural Engineering. 131(4). 684–692. 28 indexed citations
16.
Kasal, Bohumil, et al.. (2005). Three-Dimensional Model of Light Frame Wood Buildings. I: Model Description. Journal of Structural Engineering. 131(4). 676–683. 56 indexed citations
17.
Ma, Fai, et al.. (2004). Parameter Analysis of the Differential Model of Hysteresis. Journal of Applied Mechanics. 71(3). 342–349. 267 indexed citations
18.
Kasal, Bohumil, et al.. (2004). Design Models of Light Frame Wood Buildings under Lateral Loads. Journal of Structural Engineering. 130(8). 1263–1271. 23 indexed citations
19.
Paevere, Phillip, Greg Foliente, & Bohumil Kasal. (2003). Load-Sharing and Redistribution in a One-Story Woodframe Building. Journal of Structural Engineering. 129(9). 1275–1284. 27 indexed citations
20.
Paevere, Phillip, N Haritos, & Greg Foliente. (1998). A Hysteretic MDOF Model For Dynamic Analysis of Offshore Towers. 4. 513–517. 1 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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