Houman Hanachi

644 total citations
22 papers, 485 citations indexed

About

Houman Hanachi is a scholar working on Mechanical Engineering, Aerospace Engineering and Control and Systems Engineering. According to data from OpenAlex, Houman Hanachi has authored 22 papers receiving a total of 485 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Mechanical Engineering, 8 papers in Aerospace Engineering and 7 papers in Control and Systems Engineering. Recurrent topics in Houman Hanachi's work include Turbomachinery Performance and Optimization (8 papers), Refrigeration and Air Conditioning Technologies (7 papers) and Advanced Sensor Technologies Research (6 papers). Houman Hanachi is often cited by papers focused on Turbomachinery Performance and Optimization (8 papers), Refrigeration and Air Conditioning Technologies (7 papers) and Advanced Sensor Technologies Research (6 papers). Houman Hanachi collaborates with scholars based in Canada and China. Houman Hanachi's co-authors include Avisekh Banerjee, Jie Liu, Jie Liu, Chris K. Mechefske, Il Yong Kim, Jie Liu, Ying Chen, Ying Chen, Wennian Yu and Jie Liu and has published in prestigious journals such as Mechanical Systems and Signal Processing, The International Journal of Advanced Manufacturing Technology and Measurement Science and Technology.

In The Last Decade

Houman Hanachi

22 papers receiving 466 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Houman Hanachi Canada	10	239	159	117	83	75	22	485
Mohammadreza Tahan Malaysia	4	237 1.0×	102 0.6×	129 1.1×	69 0.8×	85 1.1×	8	479
Avisekh Banerjee Canada	10	174 0.7×	138 0.9×	90 0.8×	96 1.2×	65 0.9×	28	399
Yunpeng Cao China	11	218 0.9×	125 0.8×	118 1.0×	59 0.7×	66 0.9×	47	371
N. Aretakis Greece	16	239 1.0×	172 1.1×	108 0.9×	121 1.5×	225 3.0×	68	633
Hans DePold United States	7	268 1.1×	58 0.4×	118 1.0×	116 1.4×	44 0.6×	12	433
Jun Tao China	12	88 0.4×	82 0.5×	63 0.5×	48 0.6×	182 2.4×	27	563
Jonathan DeCastro United States	8	255 1.1×	55 0.3×	39 0.3×	35 0.4×	77 1.0×	15	421
Nadji Hadroug Algeria	12	198 0.8×	55 0.3×	122 1.0×	29 0.3×	23 0.3×	38	379
Behnoush Rezaeianjouybari United States	6	209 0.9×	338 2.1×	67 0.6×	240 2.9×	26 0.3×	7	612

Countries citing papers authored by Houman Hanachi

Since Specialization

Citations

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

Fields of papers citing papers by Houman Hanachi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Houman Hanachi

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

Zhang, Yu, Houman Hanachi, Jie Liu, & Chunsheng Yang. (2020). Model-based degradation inference for auxiliary power unit start system. Engineering Failure Analysis. 118. 104895–104895. 1 indexed citations

Ravichandran, T., et al.. (2020). Data-Driven Performance Prediction Using Gas Turbine Sensory Signals. 1–6. 4 indexed citations

Liu, Jie, et al.. (2020). A physics-based framework for online surface roughness assessment for high-pressure turbines. Chinese Journal of Aeronautics. 34(7). 135–156. 3 indexed citations

Hanachi, Houman, et al.. (2018). Performance-Based Gas Turbine Health Monitoring, Diagnostics, and Prognostics: A Survey. IEEE Transactions on Reliability. 67(3). 1340–1363. 113 indexed citations

Hanachi, Houman, Jie Liu, Il Yong Kim, & Chris K. Mechefske. (2018). Hybrid sequential fault estimation for multi-mode diagnosis of gas turbine engines. Mechanical Systems and Signal Processing. 115. 255–268. 24 indexed citations

Hanachi, Houman, et al.. (2018). Predictive Compressor Wash Optimization for Economic Operation of Gas Turbine. Journal of Engineering for Gas Turbines and Power. 140(12). 3 indexed citations

Hanachi, Houman, Wennian Yu, Il Yong Kim, Jie Liu, & Chris K. Mechefske. (2018). Hybrid data-driven physics-based model fusion framework for tool wear prediction. The International Journal of Advanced Manufacturing Technology. 101(9-12). 2861–2872. 101 indexed citations

Zhang, Yu, et al.. (2018). Physics-based Model and Neural Network Model for Monitoring Starter Degradation of APU. 1–7. 7 indexed citations

Hanachi, Houman, et al.. (2017). Enhancement of prognostic models for short-term degradation of gas turbines. 66–69. 11 indexed citations

10.

Hanachi, Houman, et al.. (2017). Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system. Chinese Journal of Aeronautics. 31(1). 1–9. 44 indexed citations

11.

Hanachi, Houman & Jie Liu. (2016). State Estimation for General Class of Dynamical Systems: An Extension to Particle Filters. 2 indexed citations

12.

Hanachi, Houman, Jie Liu, Avisekh Banerjee, & Ying Chen. (2016). Prediction of Compressor Fouling Rate Under Time Varying Operating Conditions. 12 indexed citations

13.

Hanachi, Houman, et al.. (2015). A framework with nonlinear system model and nonparametric noise for gas turbine degradation state estimation. Measurement Science and Technology. 26(6). 65604–65604. 20 indexed citations

14.

Hanachi, Houman, et al.. (2015). Effects of the Intake Air Humidity on the Gas Turbine Performance Monitoring. 10 indexed citations

15.

Hanachi, Houman, Jie Liu, Avisekh Banerjee, & Ying Chen. (2015). Sequential state estimation of nonlinear/non-Gaussian systems with stochastic input for turbine degradation estimation. Mechanical Systems and Signal Processing. 72-73. 32–45. 28 indexed citations

16.

Hanachi, Houman, Jie Liu, Avisekh Banerjee, & Ying Chen. (2015). Effects of Humidity Condensation on the Trend of Gas Turbine Performance Deterioration. Journal of Engineering for Gas Turbines and Power. 137(12). 5 indexed citations

17.

Hanachi, Houman, et al.. (2014). A Physics-Based Modeling Approach for Performance Monitoring in Gas Turbine Engines. IEEE Transactions on Reliability. 64(1). 197–205. 75 indexed citations

18.

Hanachi, Houman, et al.. (2014). A Physics-Based Performance Indicator for Gas Turbine Engines Under Variable Operating Conditions. 6 indexed citations

19.

Hanachi, Houman, et al.. (2012). Bladed disk crack detection through advanced analysis of blade time of arrival signal. 59. 1–4. 6 indexed citations

20.

Hanachi, Houman, et al.. (2012). Bladed disc crack diagnostics using blade passage signals. Measurement Science and Technology. 23(12). 125003–125003. 7 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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