• 338 Citations
  • 6 h-Index
20012019
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Fingerprint Dive into the research topics where Richard Loendersloot is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 21 Similar Profiles
Structural health monitoring Engineering & Materials Science
Composite structures Engineering & Materials Science
Composite materials Engineering & Materials Science
Strain energy Engineering & Materials Science
Monitoring Engineering & Materials Science
Delamination Engineering & Materials Science
Helicopters Engineering & Materials Science
Skin Engineering & Materials Science

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Research Output 2001 2019

22 Downloads (Pure)

A New Adaptive E-Learning Concept for Multidisciplinary Learning Environments

Loendersloot, R. & Martinetti, A., 25 Jun 2019, Proceedings of the 15th International CDIO conference. Bennedsen, J., Birkkjaer Lauritsen, A., Edstrom, K., Kuptasthien, N., Roslof, J. & Songer, R. (eds.). Aarhus: University of Aarhus, 11 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Open Access
File
learning environment
learning
student
electronic learning
learning objective

Artificial intelligence based condition monitoring of rail infrastructure

Ahmad, W., 24 Sep 2019, Enschede: University of Twente. 81 p.

Research output: ThesisPd Eng ThesisAcademic

Open Access
File
Condition monitoring
Artificial intelligence
Rails
Axles
Defects

Fatigue Damage Identification and Remaining Useful Life Estimation of Composite Structures using Piezo Wafer Active Transducers

Loendersloot, R., Ehsani Amoli, M. & Shamshirsaz, M., 2 Sep 2019. 12 p.

Research output: Contribution to conferencePaperAcademicpeer-review

Open Access
File
Fatigue damage
Composite structures
Transducers
Fatigue of materials
Glass fiber reinforced plastics

Physical Model-Based Prognostics and Health Monitoring to Enable Predictive Maintenance

Tinga, T. & Loendersloot, R., 1 Mar 2019, Predictive Maintenance in Dynamic Systems: Advanced Methods, Decision Support Tools and Real-World Applications. Lughofer, E. & Sayed-Mouchaweh, M. (eds.). Springer, p. 313-353

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Health
Monitoring
Structural health monitoring
Industry
27 Downloads (Pure)

Rail wear and remaining life prediction using meta-models

Meghoe, A., Loendersloot, R. & Tinga, T., 2 Jun 2019, In : International Journal of Rail Transportation. 26 p.

Research output: Contribution to journalArticleAcademicpeer-review

Open Access
File
Rails
Wear of materials
scenario
Regression analysis
Managers