Dong Van Dao

1.7k total citations · 2 hit papers
19 papers, 1.4k citations indexed

About

Dong Van Dao is a scholar working on Civil and Structural Engineering, Building and Construction and Management, Monitoring, Policy and Law. According to data from OpenAlex, Dong Van Dao has authored 19 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Civil and Structural Engineering, 4 papers in Building and Construction and 3 papers in Management, Monitoring, Policy and Law. Recurrent topics in Dong Van Dao's work include Infrastructure Maintenance and Monitoring (9 papers), Innovative concrete reinforcement materials (7 papers) and Asphalt Pavement Performance Evaluation (6 papers). Dong Van Dao is often cited by papers focused on Infrastructure Maintenance and Monitoring (9 papers), Innovative concrete reinforcement materials (7 papers) and Asphalt Pavement Performance Evaluation (6 papers). Dong Van Dao collaborates with scholars based in Vietnam, United States and Japan. Dong Van Dao's co-authors include Binh Thai Pham, Hai‐Bang Ly, Tien-Thinh Le, Son Hoang Trinh, Lei Lü, Vuong Minh Le, Tran Van Phong, Chinh Luu, Indra Prakash and Hojjat Adeli and has published in prestigious journals such as The Science of The Total Environment, Construction and Building Materials and Sustainability.

In The Last Decade

Dong Van Dao

18 papers receiving 1.3k 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.

Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete

2019 281 citations Dong Van Dao, Hai‐Bang Ly et al. Materials profile →
A spatially explicit deep learning neural network model for the prediction of landslide susceptibility

2020 264 citations Dong Van Dao, Mahmoud Bayat et al. CATENA profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dong Van Dao Vietnam	12	808	278	276	259	147	19	1.4k
Mohammad Mehrabi Iran	11	208 0.3×	360 1.3×	128 0.5×	396 1.5×	135 0.9×	13	871
Dagang Lü China	27	1.9k 2.3×	174 0.6×	924 3.3×	71 0.3×	174 1.2×	147	2.6k
Vuong Minh Le Vietnam	13	649 0.8×	94 0.3×	207 0.8×	46 0.2×	122 0.8×	14	1.1k
Mansour Mosallanezhad Iran	17	724 0.9×	104 0.4×	71 0.3×	209 0.8×	117 0.8×	28	1.1k
Luc Chouinard Canada	22	850 1.1×	86 0.3×	175 0.6×	175 0.7×	108 0.7×	107	1.3k
Enrico Tubaldi United Kingdom	33	2.6k 3.2×	212 0.8×	478 1.7×	61 0.2×	117 0.8×	114	2.9k
Abdullahi M. Salman United States	20	758 0.9×	194 0.7×	110 0.4×	31 0.1×	146 1.0×	39	1.2k
Abdolreza Osouli United States	15	597 0.7×	97 0.3×	68 0.2×	152 0.6×	87 0.6×	86	985
M. Dolores Esteban Spain	21	589 0.7×	125 0.4×	103 0.4×	114 0.4×	131 0.9×	83	1.8k

Countries citing papers authored by Dong Van Dao

Since Specialization

Citations

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

Fields of papers citing papers by Dong Van Dao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dong Van Dao. 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 Dong Van Dao. The network helps show where Dong Van Dao may publish in the future.

Co-authorship network of co-authors of Dong Van Dao

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

All Works

Sort: Min cites: Since: Top N: Style:

19 of 19 papers shown

Dao, Dong Van, et al.. (2024). Effects of rejuvenators and aging conditions on the properties of blended bitumen and the cracking behavior of hot asphalt mixtures with a high RAP content. Proceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design and Applications. 238(7). 1368–1390.

Nguyen, May Huu, et al.. (2023). Effect of curing regimes on the dynamic modulus of entirely RAP cold recycled asphalt mixture. Proceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design and Applications. 237(9). 1975–1989. 3 indexed citations

Dao, Dong Van, et al.. (2022). Calibration of a stress-strain response for geopolymer concrete under axial compressive load. Proceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design and Applications. 236(8). 1623–1636. 4 indexed citations

Dao, Dong Van, et al.. (2022). Evaluation of cracking resistance of warm mix asphalt incorporating high reclaimed asphalt pavement content. Proceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design and Applications. 236(12). 2550–2560. 2 indexed citations

Dao, Dong Van, et al.. (2022). Prediction of interlayer shear strength of double-layer asphalt using novel hybrid artificial intelligence models of ANFIS and metaheuristic optimizations. Construction and Building Materials. 323. 126595–126595. 15 indexed citations

Pham, Binh Thai, Dong Van Dao, Tri Dev Acharya, et al.. (2021). Performance assessment of artificial neural network using chi-square and backward elimination feature selection methods for landslide susceptibility analysis. Environmental Earth Sciences. 80(20). 25 indexed citations

Pham, Binh Thai, Chinh Luu, Dong Van Dao, et al.. (2021). Flood risk assessment using deep learning integrated with multi-criteria decision analysis. Knowledge-Based Systems. 219. 106899–106899. 113 indexed citations

Dao, Dong Van, Mahmoud Bayat, Davood Mafi-Gholami, et al.. (2020). A spatially explicit deep learning neural network model for the prediction of landslide susceptibility. CATENA. 188. 104451–104451. 264 indexed citations breakdown →

Dao, Dong Van, Hojjat Adeli, Hai‐Bang Ly, et al.. (2020). A Sensitivity and Robustness Analysis of GPR and ANN for High-Performance Concrete Compressive Strength Prediction Using a Monte Carlo Simulation. Sustainability. 12(3). 830–830. 173 indexed citations

10.

Dao, Dong Van, Hai‐Bang Ly, Huong-Lan Thi Vu, Tien-Thinh Le, & Binh Thai Pham. (2020). Investigation and Optimization of the C-ANN Structure in Predicting the Compressive Strength of Foamed Concrete. Materials. 13(5). 1072–1072. 84 indexed citations

11.

Dao, Dong Van, et al.. (2020). Cost-Effective Approaches Based on Machine Learning to Predict Dynamic Modulus of Warm Mix Asphalt with High Reclaimed Asphalt Pavement. Materials. 13(15). 3272–3272. 22 indexed citations

12.

Dao, Dong Van, Son Hoang Trinh, Hai‐Bang Ly, & Binh Thai Pham. (2019). Prediction of Compressive Strength of Geopolymer Concrete Using Entirely Steel Slag Aggregates: Novel Hybrid Artificial Intelligence Approaches. Applied Sciences. 9(6). 1113–1113. 127 indexed citations

13.

Ly, Hai‐Bang, Binh Thai Pham, Dong Van Dao, et al.. (2019). Improvement of ANFIS Model for Prediction of Compressive Strength of Manufactured Sand Concrete. Applied Sciences. 9(18). 3841–3841. 85 indexed citations

14.

Dao, Dong Van, Hai‐Bang Ly, Son Hoang Trinh, Tien-Thinh Le, & Binh Thai Pham. (2019). Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete. Materials. 12(6). 983–983. 281 indexed citations breakdown →

15.

Pham, Binh Thai, Manh Duc Nguyen, Dong Van Dao, et al.. (2019). Development of artificial intelligence models for the prediction of Compression Coefficient of soil: An application of Monte Carlo sensitivity analysis. The Science of The Total Environment. 679. 172–184. 140 indexed citations

16.

Tran, Van Quan, et al.. (2019). Effect of temperature on the chloride binding capacity of cementitious materials. Magazine of Concrete Research. 73(15). 771–784. 18 indexed citations

17.

Forth, John P., et al.. (2013). The use of optimisation for enhancing the development of a novel sustainable masonry unit. Applied Mathematical Modelling. 38(3). 853–863. 3 indexed citations

18.

Forth, John P., Dong Van Dao, & S E Zoorob. (2010). Investigating the Effects of Curing Methods on the Compressive Strength of Bitublock. Journal of Materials in Civil Engineering. 22(3). 207–213. 1 indexed citations

19.

Dao, Dong Van, John P. Forth, & S E Zoorob. (2006). Bitumen bound construction units utilising only recycled and waste materials as aggregates. 1 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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