Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A review of methods to match building energy simulation models to measured data
2014639 citationsDaniel Coakley, Paul Raftery et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Daniel Coakley
Since
Specialization
Citations
This map shows the geographic impact of Daniel Coakley'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 Daniel Coakley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Coakley more than expected).
This network shows the impact of papers produced by Daniel Coakley. 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 Daniel Coakley. The network helps show where Daniel Coakley may publish in the future.
Co-authorship network of co-authors of Daniel Coakley
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Coakley.
A scholar is included among the top collaborators of Daniel Coakley 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 Daniel Coakley. Daniel Coakley is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Olesen, Bjarne W., Dragos‐Ioan Bogatu, Ongun Berk Kazanci, & Daniel Coakley. (2021). The use of CO2 as an indicator for indoor air quality and control of ventilation according to EN16798-1 and TR16798-2.2 indexed citations
Bogatu, Dragos‐Ioan, Ongun Berk Kazanci, Daniel Coakley, & Bjarne W. Olesen. (2020). Long-term IEQ Evaluation Metrics Based on Standards and Certification Schemes. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU).1 indexed citations
5.
Olesen, Bjarne W., et al.. (2020). Whole year evaluation of thermal comfort using international standards EN16798-1 and TR16798-2. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 20–33.3 indexed citations
Kazanci, Ongun Berk, Daniel Coakley, & Bjarne W. Olesen. (2019). A Review of Adaptive Thermal Comfort Implementation in International Thermal Comfort Standards. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU).8 indexed citations
Corry, Edward, Daniel Coakley, James O’Donnell, Pieter Pauwels, & Marcus Keane. (2013). The role of linked data and the semantic web in building operation. Ghent University Academic Bibliography (Ghent University).5 indexed citations
18.
Bruton, Ken, Daniel Coakley, Peter O’Donovan, Marcus Keane, & Dominic O’Sullivan. (2013). Development of an Online Expert Rule Based Automated fault Detection and Diagnostic (AFDD) Tool for Air Handling Units: Beta Test Results. OAKTRUST (Texas A&M University).3 indexed citations
Coakley, Daniel, et al.. (2011). CALIBRATION OF A DETAILED BES MODEL TO MEASURED DATA USING AN EVIDENCE-BASED ANALYTICAL OPTIMISATION APPROACH.34 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.