Daniel C. Kammer

2.9k total citations · 1 hit paper
65 papers, 2.0k citations indexed

About

Daniel C. Kammer is a scholar working on Civil and Structural Engineering, Statistics, Probability and Uncertainty and Mechanics of Materials. According to data from OpenAlex, Daniel C. Kammer has authored 65 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Civil and Structural Engineering, 25 papers in Statistics, Probability and Uncertainty and 13 papers in Mechanics of Materials. Recurrent topics in Daniel C. Kammer's work include Structural Health Monitoring Techniques (42 papers), Probabilistic and Robust Engineering Design (25 papers) and Bladed Disk Vibration Dynamics (15 papers). Daniel C. Kammer is often cited by papers focused on Structural Health Monitoring Techniques (42 papers), Probabilistic and Robust Engineering Design (25 papers) and Bladed Disk Vibration Dynamics (15 papers). Daniel C. Kammer collaborates with scholars based in United States and Sweden. Daniel C. Kammer's co-authors include Leehter Yao, Michael Tinker, William A. Sethares, Adam Steltzner, Gary L. Gray, Ian Dobson, Thomas Abrahamsson, Matthew S. Allen, Randall L. Mayes and Paul Milenkovic and has published in prestigious journals such as Computer Methods in Applied Mechanics and Engineering, Journal of Applied Mechanics and AIAA Journal.

In The Last Decade

Daniel C. Kammer

63 papers receiving 1.8k citations

Hit Papers

Sensor placement for on-orbit modal identification and co... 1991 2026 2002 2014 1991 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel C. Kammer United States 18 1.7k 541 409 358 306 65 2.0k
A. G. Chassiakos United States 18 2.9k 1.7× 237 0.4× 262 0.6× 500 1.4× 777 2.5× 37 3.2k
Valder Steffen Brazil 26 862 0.5× 411 0.8× 470 1.1× 716 2.0× 724 2.4× 160 2.2k
Laurent Mevel France 24 1.7k 1.0× 574 1.1× 483 1.2× 298 0.8× 545 1.8× 125 2.0k
Nikolaos Dervilis United Kingdom 30 1.4k 0.8× 245 0.5× 473 1.2× 514 1.4× 441 1.4× 109 2.1k
Saeed Eftekhar Azam United States 21 1.2k 0.7× 215 0.4× 270 0.7× 391 1.1× 448 1.5× 67 1.5k
Zhong-Rong Lu China 25 1.7k 1.0× 357 0.7× 670 1.6× 391 1.1× 293 1.0× 134 2.1k
Cristinel Mares United Kingdom 17 762 0.5× 256 0.5× 286 0.7× 379 1.1× 147 0.5× 63 1.1k
A. Rama Mohan Rao India 22 1.0k 0.6× 113 0.2× 593 1.4× 284 0.8× 152 0.5× 98 1.3k
Dmitri Tcherniak Denmark 20 801 0.5× 106 0.2× 380 0.9× 256 0.7× 336 1.1× 59 1.1k
Zhiyi Tang China 11 1.1k 0.7× 70 0.1× 261 0.6× 246 0.7× 158 0.5× 29 1.5k

Countries citing papers authored by Daniel C. Kammer

Since Specialization
Citations

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

Fields of papers citing papers by Daniel C. Kammer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel C. Kammer. 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 C. Kammer. The network helps show where Daniel C. Kammer may publish in the future.

Co-authorship network of co-authors of Daniel C. Kammer

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel C. Kammer. A scholar is included among the top collaborators of Daniel C. Kammer 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 C. Kammer. Daniel C. Kammer 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.
Kammer, Daniel C., et al.. (2018). An Examination of Launch Vehicle Loads Reanalysis Techniques. NASA Technical Reports Server (NASA). 1 indexed citations
2.
Kammer, Daniel C., et al.. (2013). Correcting indefinite mass matrices due to substructure uncoupling. Journal of Sound and Vibration. 332(22). 5856–5866. 5 indexed citations
3.
Allen, Matthew S., Daniel C. Kammer, & Randall L. Mayes. (2012). Metrics for diagnosing negative mass and stiffness when uncoupling experimental and analytical substructures. Journal of Sound and Vibration. 331(25). 5435–5448. 6 indexed citations
4.
Kammer, Daniel C., et al.. (2009). Frequency Band Averaging of Spectral Densities for Updating Finite Element Models. Journal of vibration and acoustics. 131(4). 10 indexed citations
5.
Kammer, Daniel C., et al.. (2008). Mass-weighting methods for sensor placement using sensor set expansion techniques. Mechanical Systems and Signal Processing. 22(7). 1515–1525. 18 indexed citations
6.
Kammer, Daniel C. & Adam Steltzner. (2000). Structural Identification Using Inverse System Dynamics. Journal of Guidance Control and Dynamics. 23(5). 819–825. 9 indexed citations
7.
Steltzner, Adam & Daniel C. Kammer. (1999). Input force estimation using an inverse structural filter. 3727. 954–960. 23 indexed citations
8.
Kammer, Daniel C. & Adam Steltzner. (1999). Structural Identification Using Inverse System Dynamics, #224. SPIE eBooks. 3727. 1880–1886. 3 indexed citations
9.
Kammer, Daniel C.. (1998). Model Reduction Using Modal, SEREP, and Hybrid. 3243. 177. 1 indexed citations
10.
Kammer, Daniel C.. (1997). Estimation of Structural Response Using Remote Sensor Locations. Proceedings of SPIE, the International Society for Optical Engineering. 3089. 1379–1385. 1 indexed citations
11.
Gray, Gary L., Ian Dobson, & Daniel C. Kammer. (1996). Chaos in a Spacecraft Attitude Maneuver Due to Time-Periodic Perturbations. Journal of Applied Mechanics. 63(2). 501–508. 12 indexed citations
12.
Kammer, Daniel C.. (1996). Input force reconstruction using a time domain technique. Dynamics Specialists Conference. 11 indexed citations
13.
Kammer, Daniel C., et al.. (1994). Optimal sensor placement for modal identification using system-realization methods. 4 indexed citations
14.
Kammer, Daniel C. & Gary L. Gray. (1993). A nonlinear control design for energy sink simulation in the Euler-Poinsot problem. The Journal of the Astronautical Sciences. 41(1). 111–132. 3 indexed citations
15.
Gray, Gary L., Daniel C. Kammer, & Ian Dobson. (1993). Detection of chaotic saddles in an attitude maneuver of a spacecraft containing a viscous damper. 95. 167–184. 6 indexed citations
16.
Kammer, Daniel C.. (1992). Effect of model error on sensor placement for on-orbit modal identification of large space structures. Journal of Guidance Control and Dynamics. 15(2). 334–341. 68 indexed citations
17.
Gray, Gary L., Daniel C. Kammer, & Ian Dobson. (1992). Chaos in an attitude maneuver of a damped satellite due to time-periodic perturbations. 593–612. 4 indexed citations
18.
Kammer, Daniel C.. (1992). Effects of Noise on Sensor Placement for On-Orbit Modal Identification of Large Space Structures. Journal of Dynamic Systems Measurement and Control. 114(3). 436–443. 56 indexed citations
19.
Kammer, Daniel C.. (1992). Reply by Author to W. L. Poston and R. H. Tolson. Journal of Guidance Control and Dynamics. 15(6). 1514–1514. 2 indexed citations
20.
Kammer, Daniel C., et al.. (1986). Shock and Vibration Analysis of a Communication System Subject to Nuclear Blast. 30.2.1–30.2.5. 3 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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