Miriam B. Dodt
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View article: Near-real-time online process control using grey-box models
Near-real-time online process control using grey-box models Open
Conference paper for 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), 2023, Dublin, Ireland. A scheme is presented with the goal to enable near-real time reliable and robust proces…
View article: A self-learning Digital Twin for Process Control of fast processes under Uncertainty
A self-learning Digital Twin for Process Control of fast processes under Uncertainty Open
Conference paper for the 5th International Conference on Uncertainty Quantification in Computational Science and Engineering (UNCECOMP 2023), Athens, Greece. Methodology to perform reliable process control for fast and highly complex proce…
View article: A SELF-LEARNING DIGITAL TWIN FOR PROCESS CONTROL OF FAST PROCESSES UNDER UNCERTAINTY
A SELF-LEARNING DIGITAL TWIN FOR PROCESS CONTROL OF FAST PROCESSES UNDER UNCERTAINTY Open
With the recent developments of sensor technologies appear new opportunities for conducting increasingly efficient and close control of industrial processes.This paper proposes a new scheme for near real-time process control of extremely f…
View article: Active learning in grey-box models for near-real-time online monitoring of dynamic processes
Active learning in grey-box models for near-real-time online monitoring of dynamic processes Open
Near-real-time monitoring of dynamical processes in a production line can aid greatly in increasing the products quality and reliability, leading to an overall extended lifetime and reduced costs. It enables timely intervention in case of …
View article: Active learning in grey-box models for near-real-time online monitoring of dynamic processes
Active learning in grey-box models for near-real-time online monitoring of dynamic processes Open
Near-real-time monitoring of dynamical processes in a production line can aid greatly in increasing the products quality and reliability, leading to an overall extended lifetime and reduced costs. It enables timely intervention in case of …
View article: Comparison of state of the art sampling-based Bayesian Updating techniques
Comparison of state of the art sampling-based Bayesian Updating techniques Open
Nowadays, model updating has an increasing importance in many areas of interest for engineering applications such as structural\nhealth monitoring or risk and reliability assessment. As a matter of fact, it allows for solving a plethora of…