6 citations · 8 across the 9 of their papers we have counts for
9 papers
Physics-Informed Framework for Impact Identification in Aerospace Composites
Natália Ribeiro Marinho, Richard Loendersloot, Jan Willem Wiegman +2
This paper introduces a novel physics-informed impact identification (Phy-ID) framework. The proposed method integrates observational, inductive, and learning biases to combine phy…
Defining Energy Indicators for Impact Identification on Aerospace Composites: A Structured Feature Selection Approach Guided by Domain Knowledge
Natália Ribeiro Marinho, Richard Loendersloot, Frank Grooteman +3
Energy estimation is critical to impact identification on aerospace composites, where low-velocity impacts can induce internal damage that is undetectable at the surface. Data spar…
Demonstrators for Industrial Cyber-Physical System Research: A Requirements Hierarchy Driven by Software-Intensive Design
Uraz Odyurt, Richard Loendersloot, Tiedo Tinga
One of the challenges apparent in the organisation of research projects is the uncertainties around the subject of demonstrators. A precise and detailed elicitation of the coverage…
InfoPos: A Design Support Framework for ML-Assisted Fault Detection and Identification in Industrial Cyber-Physical Systems
Uraz Odyurt, Richard Loendersloot, Tiedo Tinga
The variety of building blocks and algorithms incorporated in data-centric and ML-assisted fault detection and identification solutions is high, contributing to two challenges: sel…
A maturity framework for data driven maintenance
Chris Rijsdijk, Mike van de Wijnckel, Tiedo Tinga
Maintenance decisions range from the simple detection of faults to ultimately predicting future failures and solving the problem. These traditionally human decisions are nowadays i…
Maintenance Strategies for Sewer Pipes with Multi-State Degradation and Deep Reinforcement Learning
Lisandro A. Jimenez-Roa, Thiago D. Simão, Zaharah Bukhsh +4
Large-scale infrastructure systems are crucial for societal welfare, and their effective management requires strategic forecasting and intervention methods that account for various…
Comparing Homogeneous And Inhomogeneous Time Markov Chains For Modelling Degradation In Sewer Pipe Networks
Lisandro A. Jimenez-Roa, Tiedo Tinga, Tom Heskes +1
Sewer pipe systems are essential for social and economic welfare. Managing these systems requires robust predictive models for degradation behaviour. This study focuses on probabil…
Deterioration modeling of sewer pipes via discrete-time Markov chains: A large-scale case study in the Netherlands
L. A. Jimenez-Roa, T. Heskes, T. Tinga +2
Sewer pipe network systems are an important part of civil infrastructure, and in order to find a good trade-off between maintenance costs and system performance, reliable sewer pip…
Automatic inference of fault tree models via multi-objective evolutionary algorithms
Lisandro A. Jimenez-Roa, Tom Heskes, Tiedo Tinga +1
Fault tree analysis is a well-known technique in reliability engineering and risk assessment, which supports decision-making processes and the management of complex systems. Tradit…