{"data":{"activities":[{"__typename":"IntellectualContribution","id":"325988012032","description":"

Xu, S., Emami, A., & Khaleghian, S. (2025). Controlled Dry Adhesion of Bio-Inspired Fibrillar Polymers: Mechanics, Strategies, and Recent Advances. Materials, 18(7), 1620. Retrieved from https://doi.org/10.3390/ma18071620

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Xu, S., De, S., Khaleghian, S., & Emami, A. (2025). Wear Resistance of Additively Manufactured Footwear Soles. Lubricants, 13(2), 89. https://doi.org/10.3390/lubricants13020089

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Xu, S., De, S., Khaleghian, S., & Emami, A. (2025). Comparative tribological and drainage performance of additively manufactured outsoles tread designs. Friction. https://doi.org/10.26599/frict.2025.9441024

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Uddin, M. J., Sherrell, J., Emami, A., & Khaleghian, S. (2024). Application of Artificial Intelligence and Sensor Fusion for Soil Organic Matter Prediction. Sensors, 24(7), 2357. https://doi.org/10.3390/s24072357

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Xu, S., Khan, M. J. I., Khaleghian, S., & Emami, A. (2023). Slip Risk Prediction Using Intelligent Insoles and a Slip Simulator. Electronics, 12(21), 4393. https://doi.org/10.3390/electronics12214393

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De, S., Xu, S., Emami, A., & Khaleghian, S. (n.d.). Gecko-Inspired Microscale Structures for Friction and Deformation Control in Zero-Gravity Environments.

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Kim, E., Khaleghian, S., & Emami, A. (2023). Behavior of 3D Printed Stretchable Structured Sensors. Electronics, 12(1). https://doi.org/10.3390/electronics12010018

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Emami, A., Sah, H. N., Aguayo, F., & Khaleghian, S. (2023). Experimental investigations and empirical modeling of rubber wear on concrete pavement. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 237(1), 149–162. https://doi.org/10.1177/13506501221104290

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Khan, M. J. I., Khaleghian, S., & Emami, A. (2022). Design of a Versatile Slip Resistance Tester Mimicking Foot Kinematics and Kinetics During Human Slip.

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Banks, J. D., Khaleghian, S., & Emami, A. (2022). Effects of Infill on the Additive Manufacturing of Piezoresistive Pressure Sensors. Retrieved from https://imece.secure-platform.com/a/solicitations/182/sessiongallery/11799/application/91749

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Uddin, M. J., Basutkar, R. K., Emami, A., & Khaleghian, S. (2022). Development of AI-Based Algorithms for the Estimation of Soil Organic Matter from the Integration of UAV & In-Ground Soil Sensor.

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Nguyen, K., Bryant, M., Song, I.-H., You, B.-H., & Khaleghian, S. (2022). The Application of PVDF-Based Piezoelectric Patches in Energy Harvesting from Tire Deformation. Sensors, 22(24), 9995. https://doi.org/10.3390/s22249995

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Ashouri, M., Khaleghian, S., & Emami, A. (2022). A data-driven model for pressure distribution measurements by a four-electrode polymer sensor. Sensors and Actuators A: Physical, 342, 113663. https://doi.org/10.1016/j.sna.2022.113663

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Ashouri, M., Khaleghian, S., & Emami, A. (2022). Reduced-order modeling of conductive polymer pressure sensors using finite element simulations and deep neural networks. Structural and Multidisciplinary Optimization, 65(5). https://doi.org/10.1007/s00158-022-03237-6

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Banks, J. D., Khaleghian, S., & Emami, A. (2022). Flexible Piezoresistive Nanocomposite Sensors: Materials Selection, Processing, and Performance.

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Emami, A., Gnidehoue, H. H. C., & Khaleghian, S. (2021). Estimation of Rubber Wear Rate Using Three Different Machine Learning Algorithms.

\n","time_range":"2021MMDD2021MMDD"},{"__typename":"IntellectualContribution","id":"226298333184","description":"

Emami, A., Gnidehoue, H. H., & Khaleghian, S. (2021). Estimation of Rubber Wear Rate Using Three Different Machine Learning Algorithms.

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Basutkar, R. K., & Khaleghian, S. (2021). Design and development of an automated system for precision agriculture.

\n","time_range":"202108DD202108DD"},{"__typename":"IntellectualContribution","id":"215049670656","description":"

Gnidehoue, H. H. C., Emami, A., & Khaleghian, S. (2020). Application of Machine Learning Algorithms in Wear Rate Estimation of Rubbers.

\n","time_range":"2020MMDD2020MMDD"},{"__typename":"IntellectualContribution","id":"215936292864","description":"

Ghahremani-Moghadam, D., & Khaleghian, S. (2020). Microstructure and Mechanical Properties of Friction Stir Welded and Processed Joints with the Addition of Nanoparticles: A Review. Current Biochemical Engineering, 6(2), 82--90.

\n","time_range":"2020MMDD2020MMDD"},{"__typename":"IntellectualContribution","id":"215936282624","description":"

Maurya, D., Khaleghian, S., Sriramdas, R., Kumar, P., Kishore, R. A., Kang, M. G., … Priya, S. (2020). 3D printed graphene-based self-powered strain sensors for smart tires in autonomous vehicles. Nature Communications, 11(1). https://doi.org/10.1038/s41467-020-19088-y

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Emami, A., Khaleghian, S., Bezek, T., & Taheri, S. (2020). Design and development of a new portable test setup to study friction and wear. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 234(5), 730–742. https://doi.org/10.1177/1350650119867795

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Behroozinia, P., Khaleghian, S., Taheri, S., & Mirzaeifar, R. (2020). An investigation towards intelligent tyres using finite element analysis. International Journal of Pavement Engineering, 21(3), 311–321. https://doi.org/10.1080/10298436.2018.1475664

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Emami, A., & Khaleghian, S. (2019). Investigation of tribological behavior of Styrene-Butadiene Rubber compound on asphalt-like surfaces. Tribology International, 136, 487–495. https://doi.org/10.1016/j.triboint.2019.04.002

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Khaleghian, S., Ghasemalizadeh, O., Taheri, S., & Flintsch, G. (2019). A Combination of Intelligent Tire and Vehicle Dynamic Based Algorithm to Estimate the Tire-Road Friction. SAE International Journal of Passenger Cars - Mechanical Systems, 12(2). https://doi.org/10.4271/06-12-02-0007

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Najafi, S., Flintsch, G. W., & Khaleghian, S. (2019). Pavement friction management – artificial neural network approach. International Journal of Pavement Engineering, 20(2), 125–135. https://doi.org/10.1080/10298436.2016.1264221

\n","time_range":"201902DD201902DD"},{"__typename":"IntellectualContribution","id":"172177514496","description":"

Behroozinia, P., Khaleghian, S., Taheri, S., & Mirzaeifar, R. (2019). Damage diagnosis in intelligent tires using time-domain and frequency-domain analysis. Mechanics Based Design of Structures and Machines, 47(1), 54–66. https://doi.org/10.1080/15397734.2018.1496842

\n","time_range":"2019010220190102"},{"__typename":"IntellectualContribution","id":"172177516544","description":"

Maurya, D., Kumar, P., Khaleghian, S., Sriramdas, R., Kang, M. G., Kishore, R. A., … Priya, S. (2018). Energy harvesting and strain sensing in smart tire for next generation autonomous vehicles. Applied Energy, 232, 312–322. https://doi.org/10.1016/j.apenergy.2018.09.183

\n","time_range":"201812DD201812DD"},{"__typename":"IntellectualContribution","id":"208685617152","description":"

Emami, A., Khaleghian, S., Su, C., & Taheri, S. (2017). Comparison of multiscale analytical model of friction and wear of viscoelastic materials with experiments. In ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE) (Vol. 9). https://doi.org/10.1115/IMECE2017-71537

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Khaleghian, S., & Taheri, S. (2017). Intelligent Tire Based Pressure Monitoring Algorithm. In Volume 12: Transportation Systems. American Society of Mechanical Engineers. https://doi.org/10.1115/imece2017-71048

\n","time_range":"2017110320171103"},{"__typename":"IntellectualContribution","id":"321416624128","description":"

Emami, A., Khaleghian, S., Su, C., & Taheri, S. (2017). Physics-Based Friction Model With Potential Application in Numerical Models for Tire-Road Traction. In Volume 3: Vibration in Mechanical Systems; Modeling and Validation; Dynamic Systems and Control Education; Vibrations and Control of Systems; Modeling and Estimation for Vehicle Safety and Integrity; Modeling and Control of IC Engines and Aftertreatment Systems; Unmanned Aerial Vehicles (UAVs) and Their Applications; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Control of Smart Buildings and Microgrids; Energy Systems. American Society of Mechanical Engineers. https://doi.org/10.1115/dscc2017-5335

\n","time_range":"2017101120171011"},{"__typename":"IntellectualContribution","id":"172177526784","description":"

Khaleghian, S., & Taheri, S. (2017). Terrain classification using intelligent tire. Journal of Terramechanics, 71, 15–24. https://doi.org/10.1016/j.jterra.2017.01.005

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Khaleghian, S., Emami, A., & Taheri, S. (2017). A technical survey on tire-road friction estimation. Friction, 5(2), 123–146. https://doi.org/10.1007/s40544-017-0151-0

\n","time_range":"201706DD201706DD"},{"__typename":"IntellectualContribution","id":"172177520640","description":"

Khaleghian, S., Ghasemalizadeh, O., & Taheri, S. (2016). Estimation of the Tire Contact Patch Length and Normal Load Using Intelligent Tires and Its Application in Small Ground Robot to Estimate the Tire-Road Friction. Tire Science and Technology, 44(4), 248–261. https://doi.org/10.2346/tire.16.440402

\n","time_range":"2016100120161001"},{"__typename":"IntellectualContribution","id":"172177522688","description":"

Najafi, S., Flintsch, G. W., & Khaleghian, S. (2016). Fuzzy logic inference-based Pavement Friction Management and real-time slippery warning systems: A proof of concept study. Accident Analysis & Prevention, 90, 41–49. https://doi.org/10.1016/j.aap.2016.02.007

\n","time_range":"201605DD201605DD"},{"__typename":"IntellectualContribution","id":"215936280576","description":"

Khaleghian, S., Ghasemalizadeh, O., & Taheri, S. (2015). Estimation of the Contact Patch Length and Normal Load using Intelligent Tires. In 34th annual Meeting and Conference on Tire Science and Technology.

\n","time_range":"2015MMDD2015MMDD"},{"__typename":"IntellectualContribution","id":"321416753152","description":"

Dehnavi, M. Y., Khaleghian, S., Emami, A., Tehrani, M., & Soltani, N. (2014). Utilizing digital image correlation to determine stress intensity factors. Polymer Testing, 37, 28–35. https://doi.org/10.1016/j.polymertesting.2014.04.005

\n","time_range":"201408DD201408DD"},{"__typename":"IntellectualContribution","id":"321416663040","description":"

Khaleghian, S., Emami, A., Tehrani, M., & Soltani, N. (2013). Analysis of effective parameters for stress intensity factors in the contact problem between an asymmetric wedge and a half-plane using an experimental method of photoelasticity. Materials & Design, 43, 447–453. https://doi.org/10.1016/j.matdes.2012.07.038

\n","time_range":"201301DD201301DD"},{"__typename":"IntellectualContribution","id":"215050379264","description":"

Khaleghian, S., Emami, A., Tehrani, M., & Soltani, N. (2012). Study of Stress Intensity Factors in a Contact Problem for an Asymmetric Elastic Wedge and a Half-Plane Containing an Edge Crack Using the Experimental Method of Photoelasticity.

\n","time_range":"2012MMDD2012MMDD"},{"__typename":"IntellectualContribution","id":"172177518592","description":"

Ghasemi, M., Khaleghian, S., & Soltani, N. (2010). Errors Estimation for Evaluating Mixed-Mode Stress Intensity Factors for Cracks Emanating from Sharp Notches Using Simulated Photo elasticity. World Applied Sciences Journal, 4(11), 733--736.

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Dr. Meysam Khaleghian

Biography

Research Interests