D.L. Ermak

4.6k total citations · 1 hit paper
31 papers, 3.2k citations indexed

About

D.L. Ermak is a scholar working on Environmental Engineering, Atmospheric Science and Pollution. According to data from OpenAlex, D.L. Ermak has authored 31 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Environmental Engineering, 8 papers in Atmospheric Science and 7 papers in Pollution. Recurrent topics in D.L. Ermak's work include Wind and Air Flow Studies (18 papers), Oil Spill Detection and Mitigation (7 papers) and Atmospheric chemistry and aerosols (6 papers). D.L. Ermak is often cited by papers focused on Wind and Air Flow Studies (18 papers), Oil Spill Detection and Mitigation (7 papers) and Atmospheric chemistry and aerosols (6 papers). D.L. Ermak collaborates with scholars based in United States. D.L. Ermak's co-authors include J. Andrew McCammon, R.P. Koopman, Anay Luketa-Hanlin, S.T. Chan, Yin Yeh, David L. Morgan, Howard C. Rodean, Stevens T. Chan, William J. Hogan and R.T. Cederwall and has published in prestigious journals such as The Journal of Chemical Physics, Journal of Hazardous Materials and Journal of Computational Physics.

In The Last Decade

D.L. Ermak

29 papers receiving 3.1k citations

Hit Papers

Brownian dynamics with hydrodynamic interactions 1978 2026 1994 2010 1978 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D.L. Ermak United States 15 965 819 690 639 460 31 3.2k
A. Bellemans Belgium 29 1.4k 1.4× 406 0.5× 1.3k 1.8× 937 1.5× 311 0.7× 111 4.0k
D.J. Evans Australia 25 1.7k 1.8× 811 1.0× 1.2k 1.7× 887 1.4× 196 0.4× 59 4.6k
R. Aris United States 38 1.1k 1.1× 693 0.8× 2.0k 2.8× 530 0.8× 242 0.5× 136 6.8k
Rutherford Aris United States 31 996 1.0× 485 0.6× 851 1.2× 187 0.3× 186 0.4× 125 5.2k
Stephen Prager United States 31 1.1k 1.1× 370 0.5× 810 1.2× 478 0.7× 317 0.7× 64 3.7k
Robert I. Cukier United States 36 1.3k 1.4× 1.7k 2.1× 392 0.6× 1.8k 2.9× 1.6k 3.5× 182 6.5k
Kenji Yasuoka Japan 44 1.4k 1.5× 806 1.0× 1.1k 1.6× 1.3k 2.0× 152 0.3× 244 5.9k
G. S. Kell Canada 19 793 0.8× 311 0.4× 1.5k 2.2× 946 1.5× 191 0.4× 36 4.1k
H. Brenner United States 36 1.1k 1.1× 387 0.5× 2.0k 2.9× 519 0.8× 702 1.5× 123 6.3k
E. Guyon France 38 879 0.9× 360 0.4× 659 1.0× 1.2k 1.9× 106 0.2× 180 4.6k

Countries citing papers authored by D.L. Ermak

Since Specialization
Citations

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

Fields of papers citing papers by D.L. Ermak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D.L. Ermak. 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 D.L. Ermak. The network helps show where D.L. Ermak may publish in the future.

Co-authorship network of co-authors of D.L. Ermak

This figure shows the co-authorship network connecting the top 25 collaborators of D.L. Ermak. A scholar is included among the top collaborators of D.L. Ermak 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 D.L. Ermak. D.L. Ermak 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.
Luketa-Hanlin, Anay, R.P. Koopman, & D.L. Ermak. (2006). On the application of computational fluid dynamics codes for liquefied natural gas dispersion. Journal of Hazardous Materials. 140(3). 504–517. 84 indexed citations
2.
Koopman, R.P. & D.L. Ermak. (2006). Lessons learned from LNG safety research. Journal of Hazardous Materials. 140(3). 412–428. 67 indexed citations
3.
Nasstrom, John S. & D.L. Ermak. (1999). A Homogeneous Langevin Equation Model, Part i: Simulation of Particle Trajectories in Turbulence with a Skewed Velocity Distribution. Boundary-Layer Meteorology. 92(3). 343–369. 3 indexed citations
4.
Nasstrom, John S. & D.L. Ermak. (1999). A Homogeneous Langevin Equation Model, Part ii: Simulation of Dispersion in the Convective Boundary Layer. Boundary-Layer Meteorology. 92(3). 371–405. 4 indexed citations
5.
Albritton, J. R., et al.. (1997). Computational fluid dynamics modeling for emergency preparedness and response. Environmental Modelling & Software. 12(1). 43–50. 10 indexed citations
6.
Ermak, D.L., et al.. (1989). Heavy Gas Dispersion Test Summary Report. Defense Technical Information Center (DTIC). 17 indexed citations
7.
Koopman, R.P., D.L. Ermak, & Stevens T. Chan. (1989). A review of recent field tests and mathematical modelling of atmospheric dispersion of large spills of Denser-than-air gases. Atmospheric Environment (1967). 23(4). 731–745. 28 indexed citations
8.
Koopman, R.P., D.L. Ermak, & S.T. Chan. (1988). A review of recent work in atmospheric dispersion of large spills. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
9.
Ermak, D.L., et al.. (1986). Recent developments on the FEM3 and SLAB atmospheric dispersion models. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 8 indexed citations
10.
Chan, S.T. & D.L. Ermak. (1985). Further assessment of FEM3: a numerical model for the dispersion of heavy gases over complex terrain. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 3 indexed citations
11.
Morgan, David L., S.T. Chan, D.L. Ermak, et al.. (1984). Phenomenology and modeling of liquefied natural gas vapor dispersion. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 4 indexed citations
12.
Kansa, E.J., et al.. (1983). Atmospheric dispersion of ammonia: an ammonia fog model. 1 indexed citations
13.
Koopman, R.P., R.T. Cederwall, D.L. Ermak, et al.. (1982). Analysis of Burro series 40-m3 lng spill experiments. Journal of Hazardous Materials. 6(1-2). 43–83. 82 indexed citations
14.
Ermak, D.L., et al.. (1982). A comparison of dense gas dispersion model simulations with burro series LNG spill test results. Journal of Hazardous Materials. 6(1-2). 129–160. 54 indexed citations
15.
Chan, S.T., Philip Gresho, & D.L. Ermak. (1981). Three-dimensional, conservation equation model for simulating LNG vapor dispersion in the atmosphere. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 2 indexed citations
16.
Ermak, D.L., et al.. (1980). Numerical integration of the Langevin equation: Monte Carlo simulation. Journal of Computational Physics. 35(2). 169–182. 290 indexed citations
17.
Koopman, R.P., B. Bowman, & D.L. Ermak. (1979). Data and calculations of dispersion on 5 m/sup 3/ LNG spill tests. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1 indexed citations
18.
Ermak, D.L.. (1978). A scenario for geothermal electric power development in Imperial Valley. Energy. 3(2). 203–217. 3 indexed citations
19.
Gudiksen, P.H., et al.. (1977). Methodology for assessing the potential impact on air quality resulting from geothermal resource development in the Imperial Valley. University of North Texas Digital Library (University of North Texas). 78. 28655. 1 indexed citations
20.
Ermak, D.L. & Yin Yeh. (1974). Equilibrium electrostatic effects on the behavior of polyions in solution: polyion-mobile ion interaction. Chemical Physics Letters. 24(2). 243–248. 48 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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