Selected publications

Damasceno & Svanström 2025
EAGE GET

Validates a thermodynamic model for the Skallen LRC using field data.
Shows circulation systems mitigate freezing and overheating, reducing thermal extremes.
Model provides foundation for LRC optimization and hydrogen storage applications.

Damasceno et al. 2024
Georisk 46(1)

Develops a reliability-based design tool using the ADIS method and 3D FE modeling for hydrogen storage in LRCs.
Good quality rock mass is essential for safety with geological and steel lining uncertainties.
Sensitivity analysis reveals significant effects of corrosion and hydrogen embrittlement.

Damasceno et al. 2023
J Rock Mech Geotech Eng

Uses coupled FE analysis to study steel strain concentration from rock joint opening under gas pressure.
Models concrete crack initiation and component interactions in LRC systems.
Rock mass quality and joint spacing are critical factors, with largest effects in good quality rock.

Damasceno et al. 2023
J Rock Mech Geotech Eng

Compares analytical and FE models (2D/3D) for predicting rock mass response under high pressure.
Validates against Skallen field measurements and analyses under different stress conditions.
Analytical models suitable for isotropic stresses; 3D FE models superior for anisotropic conditions.

Damasceno 2022
KTH Doctoral Thesis

Integrates advanced FE models with ADIS method to develop a reliability-based design tool for LRCs.
Models account for component interactions including rock joint effects on steel lining strain.
ADIS efficiently evaluates small failure probabilities using a relatively small number of samples.

Damasceno et al. 2020
ISRM EUROCK

Develops reliability-based methodology for LRC depth using Response Surface method.
Analyzes uplift resistance with overburden using correlated uncertain variables.
Shows computational efficiency and applicability to combine with time demanding FE model problems.

Damasceno et al. 2019
ICASP13

Evaluates Subset Simulation (SuS) for calculating fatigue failure probability in LRCs.
SuS uses fewer samples compared with Monte Carlo.
Increased samples per level and conditional probability improve precision.

Johansson et al. 2018
HYBRIT RP1 WP2.3

Identifies research needs for adapting Skallen LRC technology to hydrogen storage in HYBRIT initiative.
Risk-based design frameworks and hydrogen embrittlement are critical challenges.
Additional areas: concrete optimization and rock mass property spatial variation effects.