Table 2.

Material properties used in the predictive modelling

MaterialKh (m²)Kv (m²)Thermal conductivity (W m−1 °C−1)Heat capacity (J kg−1 °C−1)Pore compressibility (Pa−1)Expansion coefficient (°C−1)Initial porosityInitial degree of water saturation
WetDry
OPA2.5 × 10−207.5 × 10−211.90
1.87* (1.6–2.2)
1.0
1.0
946.5
800.0* (800–1100)
1.7 × 10−91.7 × 10−50.1370.0
EDZ2.5 × 10−202.5 × 10−201.51.010681.7 × 10−93.47 × 10−50.1370.0
GBM3.5 × 10−203.5 × 10−201.00 0.96* (0.7–1.3)0.30
0.26* (0.25–0.35)
817.0
989.5* (500–1200)
3.7 × 10−91.5 × 10−50.450.11
Bentonite blocks3.5 × 10−203.5 × 10−201.00 0.96* (0.7–1.3)0.30
0.26* (0.25–0.35)
1520.0
900.0* (900–2000)
3.0 × 10−91.5 × 10−50.330.94
Heater1.0 × 10−501.0 × 10−505252440
135* (100–500)
1.5 × 10−50.010.2
Liner1.0 × 10−191.0 × 10−191.350.49646.7 × 10−101.5 × 10−50.20.75
  • EDZ, excavation disturbed zone; GBM, granulated bentonite mixture; OPA, Opalinus Clay; Kh, permeability parallel to bedding; Kv, permeability perpendicular to bedding.

  • * Values determined with inverse model are given in italic. Values in parentheses indicate the range used for the calibration

  • Linear relationship between thermal conductivity and degree of water saturation.

  • Initial values are taken from Gaus et al. (2014) and Senger (2013).