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This paper presents a method to automatically improve simulation model accuracy by using a stochastic gradient descent algorithm. The proposed algorithm updates models' parameters based on data collected from the actual domain under investigation. Collected data and feedback are fed into the simulation model to get predictions. In a linear prediction model, this data, along with the predictions, would form a typical regression problem; however, the stochastic gradient descent algorithm was modified to update the simulation model parameters. A tunneling case study is presented here, and the results show that the proposed algorithm can decrease simulation error by more than 50%, even in the case of incomplete simulation models or a missing inter-relationship between elements. Besides improving initial models, this paper provides a new approach for achieving data-driven simulation models that are updated in real time based on feedback from the actual domain. • Proposing a data-driven approach to enhance simulation performance. • Using stochastic gradient descent algorithm to update simulation parameters. • Deriving mathematical model to calculate error rate from a simulation model. • Applying the proposed method in a real case study of a tunneling project. • Suggesting a new approach for fitting data to model a simulation. [ABSTRACT FROM AUTHOR]

In this paper, we address modelling and simulation of dynamics involved in docking of large marine vessels with aid of tugboats, with the aim of providing a tool for improved design of control algorithms for autonomous docking operations. Mathematical models of the docking vessel and tugboats in 3DOF are derived, with a special focus on realistic interactions through towline, contact and friction forces with stick–slip dynamics and time delays, which are typically not considered in previous publications on the topic. We also present the implementation of the developed models in the first step towards a Simulink simulator in which considers the special case of tugboat-assisted docking operations in the Narvik harbour. The developed simulator is available on GitHub (see Ørke et al. (2023)) and encompasses model dynamics, tugboat control and vessel control and guidance, although the scope of this paper is model dynamics. We present simulation results that show that we are indeed able to capture interaction dynamics in a realistic way. Finally, we include a discussion of our results and some ideas for further development, as well as some concluding remarks. [Display omitted] • Mathematical modelling of docking vessel and tugboats in 3DOF. • Modelling of interaction forces in pushing/pulling operations. • Model implementation in Simulink-developed simulator. • Simulation and discussion of interaction forces, and ideas for future work. [ABSTRACT FROM AUTHOR]