Joseph H. Morrison

1.3k total citations
35 papers, 1.0k citations indexed

About

Joseph H. Morrison is a scholar working on Computational Mechanics, Aerospace Engineering and Applied Mathematics. According to data from OpenAlex, Joseph H. Morrison has authored 35 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computational Mechanics, 18 papers in Aerospace Engineering and 8 papers in Applied Mathematics. Recurrent topics in Joseph H. Morrison's work include Computational Fluid Dynamics and Aerodynamics (28 papers), Fluid Dynamics and Turbulent Flows (27 papers) and Aerodynamics and Acoustics in Jet Flows (12 papers). Joseph H. Morrison is often cited by papers focused on Computational Fluid Dynamics and Aerodynamics (28 papers), Fluid Dynamics and Turbulent Flows (27 papers) and Aerodynamics and Acoustics in Jet Flows (12 papers). Joseph H. Morrison collaborates with scholars based in United States, Japan and Germany. Joseph H. Morrison's co-authors include John Vassberg, Olaf Brodersen, Richard A. Wahls, Edward N. Tinoco, Christopher L. Rumsey, Kelly Laflin, Dimitri J. Mavriplis, Thomas B. Gatski, Mori Mani and Mitsuhiro Murayama and has published in prestigious journals such as AIAA Journal, Physics of Fluids and SAE technical papers on CD-ROM/SAE technical paper series.

In The Last Decade

Joseph H. Morrison

35 papers receiving 964 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Joseph H. Morrison United States	14	916	501	208	149	78	35	1.0k
Mori Mani United States	16	963 1.1×	582 1.2×	225 1.1×	138 0.9×	91 1.2×	33	1.1k
D. Schwamborn Germany	13	642 0.7×	437 0.9×	106 0.5×	119 0.8×	35 0.4×	30	759
Melissa B. Rivers United States	14	998 1.1×	764 1.5×	248 1.2×	121 0.8×	160 2.1×	29	1.3k
Cord-Christian Rossow Germany	15	723 0.8×	415 0.8×	169 0.8×	87 0.6×	95 1.2×	43	829
Neal T. Frink United States	23	1.6k 1.7×	970 1.9×	410 2.0×	114 0.8×	85 1.1×	78	1.7k
Daryl L. Bonhaus United States	11	1.2k 1.4×	501 1.0×	293 1.4×	87 0.6×	23 0.3×	21	1.4k
Joseph Morrison United States	15	838 0.9×	482 1.0×	278 1.3×	82 0.6×	37 0.5×	35	954
Mark DeHaan Australia	10	691 0.8×	559 1.1×	147 0.7×	65 0.4×	129 1.7×	12	902
Khaled S. Abdol-Hamid United States	18	1.1k 1.2×	791 1.6×	223 1.1×	184 1.2×	23 0.3×	93	1.2k
Edwin van der Weide United States	17	821 0.9×	395 0.8×	143 0.7×	44 0.3×	97 1.2×	46	1.0k

Countries citing papers authored by Joseph H. Morrison

Since Specialization

Citations

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

Fields of papers citing papers by Joseph H. Morrison

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joseph H. Morrison. 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 Joseph H. Morrison. The network helps show where Joseph H. Morrison may publish in the future.

Co-authorship network of co-authors of Joseph H. Morrison

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

All Works

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20 of 20 papers shown

Derlaga, Joseph M. & Joseph H. Morrison. (2018). Statistical Analysis of the Sixth AIAA Drag Prediction Workshop Solutions. Journal of Aircraft. 55(4). 1388–1400. 6 indexed citations

Morrison, Joseph H., et al.. (2016). Comprehensive Digital Transformation NASA Langley Research Center. NASA STI Repository (National Aeronautics and Space Administration). 2 indexed citations

Morrison, Joseph H., William L. Kleb, & John Vassberg. (2014). Observations on CFD Verification and Validation from the AIAA Drag Prediction Workshops. 52nd Aerospace Sciences Meeting. 12 indexed citations

Mavriplis, Dimitri J., John Vassberg, Edward N. Tinoco, et al.. (2009). Grid Quality and Resolution Issues from the Drag Prediction Workshop Series. Journal of Aircraft. 46(3). 935–950. 80 indexed citations

Vassberg, John, Edward N. Tinoco, Mortaza Mani, et al.. (2008). Abridged Summary of the Third AIAA Computational Fluid Dynamics Drag Prediction Workshop. Journal of Aircraft. 45(3). 781–798. 114 indexed citations

Sclafani, Anthony, et al.. (2008). CFL3D/OVERFLOW Results for DLR-F6 Wing/Body and Drag Prediction Workshop Wing. Journal of Aircraft. 45(3). 762–780. 27 indexed citations

Morrison, Joseph H. & Michael J. Hemsch. (2007). Statistical Analysis of the AIAA Drag Prediction Workshop CFD Solutions. NASA Technical Reports Server (NASA). 2 indexed citations

Laflin, Kelly, John Vassberg, Richard A. Wahls, et al.. (2005). Data Summary from Second AIAA Computational Fluid Dynamics Drag Prediction Workshop. Journal of Aircraft. 42(5). 1165–1178. 162 indexed citations

Mendenhall, Michael R., Robert E. Childs, & Joseph H. Morrison. (2003). Best Practices for Reduction of Uncertainty in CFD Results. NASA Technical Reports Server (NASA). 6 indexed citations

10.

Rumsey, Christopher L., et al.. (2001). CFD Sensitivity Analysis of a Modern Civil Transport Near Buffet-Onset Conditions. 27 indexed citations

11.

Rumsey, Christopher L., Thomas B. Gatski, & Joseph H. Morrison. (2000). Turbulence model predictions of strongly curved flow in a U-duct. AIAA Journal. 38. 1394–1402. 1 indexed citations

12.

Rumsey, Christopher L., Thomas B. Gatski, & Joseph H. Morrison. (2000). Turbulence Model Predictions of Strongly Curved Flow in a U-Duct. AIAA Journal. 38(8). 1394–1402. 85 indexed citations

13.

White, J. A. & Joseph H. Morrison. (1999). A Psuedo-Temporal Multi-Grid Relaxation Scheme for Solving the Parabolized Navier-Stokes Equations. NASA Technical Reports Server (NASA). 39 indexed citations

14.

Abid, Ridha, Joseph H. Morrison, Thomas B. Gatski, & Charles G. Speziale. (1996). Prediction of aerodynamic flows with a new explicit algebraic stress model. AIAA Journal. 34(12). 2632–2635. 37 indexed citations

15.

Abid, Ridha, Thomas B. Gatski, & Joseph H. Morrison. (1995). Assessment of pressure-strain models in predicting compressible, turbulent ramp flows. AIAA Journal. 33(1). 156–159. 2 indexed citations

16.

Morrison, Joseph H.. (1992). A Compressible Navier-Stokes Solver With Two-Equation and Reynolds Stress Turbulence Closure Models. NASA Technical Reports Server (NASA). 24 indexed citations

17.

Parlette, Edward B., et al.. (1990). Comparison Between Experimental and Numerical Results for a Research Hypersonic Aircraft. Journal of Aircraft. 27. 7 indexed citations

18.

Parlette, Edward B., et al.. (1990). Comparison between experimental and numerical results for a researchhypersonic aircraft. Journal of Aircraft. 27(4). 300–305. 6 indexed citations

19.

McClinton, Charles R., et al.. (1989). Hypersonic CFD Applications for the National Aero-Space Plane. SAE technical papers on CD-ROM/SAE technical paper series. 1. 2 indexed citations

20.

Morrison, Joseph H. & M. Napolitano. (1988). Efficient solutions of two-dimensional incompressible steady viscous flows. Computers & Fluids. 16(2). 119–132. 12 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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