@inproceedings{daSilveria2021_PHM,

title = {Data Selection Criteria for the Application of Predictive Maintenance to Centrifugal Pumps},

author = {Nubia Nale Alves Silveira and Richard Loendersloot and Annemieke Angelique Meghoe and Tiedo Tinga},

url = {https://phm-europe.org/},

year  = {2021},

date = {2021-06-01},

urldate = {2021-06-01},

booktitle = {Proceedings of the 6th European Conference of the Prognostics and Health Management Societ},

number = {1},

pages = {372–380},

series = {Archives of the PHM Society European Conference},

abstract = {The maintenance of vehicles and components is present in most people's daily lives, ranging from changing a private vehicle's oil to the failure prediction of an aircraft component during flight. Usually, the manufacturer's maintenance recommendation is a good solution when the cost is not too high, and the real application is used as indicated by the manufacturer. However, this recommendation can turn unfeasible when there is a significant variation in operational conditions or high maintenance costs. In these cases, the manufacturer's suggestion is typically conservative, leading to unnecessarily high costs. Therefore, the challenge is to find the best approach for optimizing a component's maintenance, given the system in which it is integrated and the associated operational and environmental conditions. Nevertheless, the available information on the loads on the component also plays a role in that choice. This paper proposes to combine case-specific information with generic degradation prediction models to obtain an acceptable but also affordable approach. The objective is to develop data selection criteria to indicate the parameters that have a high impact on the failure prediction, in this case, of a generic impeller pump. Subsequently, the approach delivers to the user an indication of the component remaining useful life using different operational scenarios.},

note = {6th European Conference of the Prognostics and Health Management Society, PHME 2021, PHME 2021 ; Conference date: 28-06-2021 Through 02-07-2021},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Badings2021NFM,

title = {Balancing Wind and Batteries: Towards Predictive Verification of Smart  Grids},

author = {Thom S. Badings and Arnd Hartmanns and Nils Jansen and Marnix Suilen},

url = {https://arxiv.org/abs/2101.12496},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {13th NASA Formal Methods Symposium},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Simao2021alwayssafe,

title = {AlwaysSafe: Reinforcement Learning Without Safety Constraint Violations During Training},

author = {Thiago D. Simão and Nils Jansen and Matthijs T. J. Spaan},

url = {https://ifaamas.org/Proceedings/aamas2021/pdfs/p1226.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS)},

pages = {1226-1235},

publisher = {IFAAMAS},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}