Ulrike Dackermann

1.8k total citations · 1 hit paper
58 papers, 1.2k citations indexed

About

Ulrike Dackermann is a scholar working on Civil and Structural Engineering, Mechanics of Materials and Building and Construction. According to data from OpenAlex, Ulrike Dackermann has authored 58 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Civil and Structural Engineering, 22 papers in Mechanics of Materials and 21 papers in Building and Construction. Recurrent topics in Ulrike Dackermann's work include Structural Health Monitoring Techniques (41 papers), Ultrasonics and Acoustic Wave Propagation (20 papers) and Wood Treatment and Properties (18 papers). Ulrike Dackermann is often cited by papers focused on Structural Health Monitoring Techniques (41 papers), Ultrasonics and Acoustic Wave Propagation (20 papers) and Wood Treatment and Properties (18 papers). Ulrike Dackermann collaborates with scholars based in Australia, Iran and Germany. Ulrike Dackermann's co-authors include Jianchun Li, Sahar Hassani, Bijan Samali, Sahar Hassani, Mohsen Mousavi, Yang Yu, Robert B. Randall, Keith Crews, Wade A. Smith and You Lin Xu and has published in prestigious journals such as Construction and Building Materials, Sensors and Journal of Sound and Vibration.

In The Last Decade

Ulrike Dackermann

54 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

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 Systematic Review of Advanced Sensor Technologies for Non-Destructive Testing and Structural Health Monitoring

2023 201 citations Sahar Hassani, Ulrike Dackermann Sensors profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ulrike Dackermann Australia	19	847	388	294	273	98	58	1.2k
Gholamreza Gholipour China	16	1.1k 1.3×	289 0.7×	313 1.1×	343 1.3×	53 0.5×	24	1.5k
Devin K. Harris United States	22	1.5k 1.7×	181 0.5×	238 0.8×	479 1.8×	44 0.4×	87	1.7k
Mazdak Tootkaboni United States	18	763 0.9×	324 0.8×	194 0.7×	109 0.4×	60 0.6×	46	1.2k
Mayank Mishra India	21	837 1.0×	151 0.4×	152 0.5×	135 0.5×	59 0.6×	44	1.3k
Gökhan Pekcan United States	23	2.0k 2.4×	228 0.6×	305 1.0×	315 1.2×	49 0.5×	58	2.3k
Asma Alsadat Mousavi China	13	964 1.1×	251 0.6×	266 0.9×	301 1.1×	48 0.5×	14	1.3k
Shunlong Li China	20	1.3k 1.5×	315 0.8×	304 1.0×	79 0.3×	124 1.3×	69	1.5k
Jin‐Hak Yi South Korea	22	1.3k 1.5×	462 1.2×	332 1.1×	92 0.3×	209 2.1×	115	1.7k
Brent Phares United States	18	1.1k 1.4×	143 0.4×	182 0.6×	276 1.0×	93 0.9×	131	1.3k
Yunlai Zhou China	20	956 1.1×	436 1.1×	484 1.6×	70 0.3×	69 0.7×	104	1.4k

Countries citing papers authored by Ulrike Dackermann

Since Specialization

Citations

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

Fields of papers citing papers by Ulrike Dackermann

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ulrike Dackermann

This figure shows the co-authorship network connecting the top 25 collaborators of Ulrike Dackermann. A scholar is included among the top collaborators of Ulrike Dackermann 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 Ulrike Dackermann. Ulrike Dackermann 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

Hassani, Sahar, Samir Mustapha, Mohsen Mousavi, et al.. (2025). Enhancing structural condition assessment in steel pipelines via a WGAN-AAE data fusion methodology. Information Fusion. 129. 103970–103970. 1 indexed citations

Hassani, Sahar, Samir Mustapha, Jianchun Li, Mohsen Mousavi, & Ulrike Dackermann. (2025). Next-generation coupled structure-human sensing technology: Enhanced pedestrian-bridge interaction analysis using data fusion and machine learning. Information Fusion. 118. 102983–102983. 3 indexed citations

Dackermann, Ulrike, et al.. (2024). Machine learning (ML) algorithms for seismic vulnerability assessment of school buildings in high-intensity seismic zones. Structures. 70. 107639–107639. 15 indexed citations

Mousavi, Mohsen, Ulrike Dackermann, Sahar Hassani, Mahbube Subhani, & Amir H. Gandomi. (2024). Raw sensor data fusion using Johansen cointegration for condition assessment of concrete poles. Journal of Sound and Vibration. 599. 118909–118909.

Mousavi, Mohsen, et al.. (2024). Enhancing load prediction for structures with concrete overlay using transfer learning of time–frequency feature-based deep models. Engineering Structures. 305. 117734–117734. 3 indexed citations

Hassani, Sahar, Mohsen Mousavi, & Ulrike Dackermann. (2023). Johansen cointegration of frequency response functions contaminated with nonstationary colored noise for structural damage detection. Journal of Sound and Vibration. 552. 117641–117641. 22 indexed citations

Hassani, Sahar & Ulrike Dackermann. (2023). A Systematic Review of Advanced Sensor Technologies for Non-Destructive Testing and Structural Health Monitoring. Sensors. 23(4). 2204–2204. 201 indexed citations breakdown →

Hassani, Sahar & Ulrike Dackermann. (2023). A Systematic Review of Optimization Algorithms for Structural Health Monitoring and Optimal Sensor Placement. Sensors. 23(6). 3293–3293. 63 indexed citations

Dackermann, Ulrike, Wade A. Smith, Mehrisadat Makki Alamdari, Jianchun Li, & Robert B. Randall. (2018). Cepstrum-based damage identification in structures with progressive damage. Structural Health Monitoring. 18(1). 87–102. 20 indexed citations

10.

Dackermann, Ulrike, et al.. (2015). A new non-destructive testing system based on narrow-band frequency excitation for the condition assessment of pole structures using frequency response functions and principle component analysis. UTS ePRESS (University of Technology Sydney). 3 indexed citations

11.

Mustapha, Samir, et al.. (2015). Pattern Recognition Based on Time Series Analysis Using Vibration Data for Structural Health Monitoring in Civil Structures. Electronic Journal of Structural Engineering. 14(1). 106–115. 9 indexed citations

12.

Yu, Yang, Ulrike Dackermann, & Jianchun Li. (2015). A novel damage evaluation method for timber utility poles based on wavelet packet transform and support vector machine. UTS ePRESS (University of Technology Sydney). 1 indexed citations

13.

Krause, Martín, Ulrike Dackermann, & Jianchun Li. (2014). Elastic wave modes for the assessment of structural timber: ultrasonic echo for building elements and guided waves for pole and pile structures. Journal of Civil Structural Health Monitoring. 5(2). 221–249. 31 indexed citations

14.

Dackermann, Ulrike, et al.. (2014). On the use of the cepstrum and artificial neural networks to identify structural mass changes from response-only measurements. UTS ePRESS (University of Technology Sydney). 5 indexed citations

15.

Li, Jianchun, et al.. (2014). A numerical investigation on the damage identification of timber utility poles based on wavelet packet energy. ePublications@SCU (Southern Cross University). 1185–1190.

16.

Dackermann, Ulrike, Wade A. Smith, & Robert B. Randall. (2013). APPLICATION OF CEPSTRUM ANALYSIS AND ARTIFICIAL NEURAL NETWORKS FOR THE DAMAGE IDENTIFICATION OF A TWO-STOREY FRAMED STRUCTURE BASED ON RESPONSE-ONLY MEASUREMENTS. 7 indexed citations

17.

Dackermann, Ulrike, et al.. (2013). A Vibration-Based Approach for the Estimation of the Loss of Composite Action in Timber Composite Systems. Advanced materials research. 778. 462–469.

18.

Dackermann, Ulrike, et al.. (2013). Experimental Investigations of Material Properties of Timber Utility Poles Using Various Material Testing Approaches. Advanced materials research. 778. 265–272. 1 indexed citations

19.

Samali, Bijan, et al.. (2005). Experimental Modal Analysis of U-Shaped Adobe-Mudbrick Wall Units. UTS ePRESS (University of Technology Sydney). 1 indexed citations

20.

Samali, Bijan, et al.. (2005). Damage Identification of Timber Bridges Using Vibration Based Methods. 6 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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