Author

Tom F. Hansen

Observed names: Hansen, Tom Frode, Tom Frode Hansen

Institution: Norwegian Geotechnical Institute

Observed institutions: Norwegian Geotechnical Institute, University of Oslo

ORCID: 0000-0002-1020-7537

Observed ORCID: 0000-0002-1020-7537

OpenAlex ID: A5083847659

Reinforcement learning based process optimization and strategy development in conventional tunneling

2021 · Georg H. Erharter, Tom F. Hansen, et al. · Automation in Construction · 44

A comparative study on machine learning approaches for rock mass classification using drilling data

2024 · Tom F. Hansen, Georg H. Erharter, et al. · Applied Computing and Geosciences · 31

International Distribution and Development of Rock Mass Classification: A Review

2024 · Georg H. Erharter, Neil Bar, et al. · Rock Mechanics and Rock Engineering · 26

Predicting rock type from MWD tunnel data using a reproducible ML-modelling process

2024 · Tom F. Hansen, Zhongqiang Liu, et al. · Tunnelling and Underground Space Technology · 26

Towards reinforcement learning - driven TBM cutter changing policies

2024 · Tom F. Hansen, Georg H. Erharter, et al. · Automation in Construction · 18

Unsupervised Machine Learning for Data-Driven Rock Mass Classification: Addressing Limitations in Existing Systems Using Drilling Data

2024 · Tom F. Hansen, Arnstein Aarset · Rock Mechanics and Rock Engineering · 17

Analysis of water ingress, grouting effort, and pore pressure reduction caused by hard rock tunnels in the Oslo region

2022 · Jenny Langford, Kristin H. Holmøy, et al. · Tunnelling and Underground Space Technology · 12

Improving face decisions in tunnelling by machine learning‐based MWD analysis

2022 · Tom F. Hansen, Georg H. Erharter, et al. · Geomechanics and Tunnelling · 10

Towards optimized TBM cutter changing policies with reinforcement learning

2022 · Georg H. Erharter, Tom F. Hansen · Geomechanics and Tunnelling · 9

Norwegian tunnel excavation: Increasing digitalisation in all operations

2022 · Jessica Ka Yi Chiu, Tom F. Hansen, et al. · Geomechanics and Tunnelling · 6

Building and Analysing a Labelled Measure While Drilling Dataset from 15 Hard Rock Tunnels in Norway

2024 · Tom Frode Hansen, Zhongqiang Liu, et al. · SSRN Electronic Journal · 4

Can We Trust the Machine Learning Based Geotechnical Model?

2024 · Tom F. Hansen · Springer series in geomechanics and geoengineering · 3

Toward machine learning based decision support for pre‐grouting in hard rock

2024 · Ida Rongved, Tom F. Hansen, et al. · Civil Engineering Design · 2

Dataset for image-based rock joint trace mapping

2026 · Chiu, Jessica Ka Yi, Hansen, Tom Frode, et al. · Zenodo (CERN European Organization for Nuclear Research)

Best performing models for rock joint segmentation

2026 · Chiu, Jessica Ka Yi, Hansen, Tom Frode, et al. · Zenodo (CERN European Organization for Nuclear Research)

Real-world box dataset

2026 · Chiu, Jessica Ka Yi, Hansen, Tom Frode, et al. · Zenodo (CERN European Organization for Nuclear Research)

Real-world box dataset

2026 · Chiu, Jessica Ka Yi, Hansen, Tom Frode, et al. · Zenodo (CERN European Organization for Nuclear Research)

Dataset for image-based rock joint trace mapping

2026 · Chiu, Jessica Ka Yi, Hansen, Tom Frode, et al. · Zenodo (CERN European Organization for Nuclear Research)

Best performing models for rock joint segmentation

2026 · Chiu, Jessica Ka Yi, Hansen, Tom Frode, et al. · Zenodo (CERN European Organization for Nuclear Research)

Automated rock joint trace mapping using a supervised learning model trained on synthetic data generated by parametric modelling

2026 · Chiu, Jessica Ka Yi, Hansen, Tom Frode, et al. · arXiv (Cornell University)

Predicting Rock Type and Quality from MWD Data in Exploratory Drillholes - Focusing on Geologic Transition Zones and Uncertainty Assessments

2024 · Tom F. Hansen, Zhongqiang Liu · European Regional Conference of the International Association for Engineering Geology and the Environment (EUROENGEO)

Works count: 24

Citation count: 210

H-index: 9

I10-index: 8