Dr. David  Santillan
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Dr. David Santillan

Lecturer
Universidad Politecnica de Madrid, Spain


Highest Degree
Ph.D. in Civil Engineering from Technical University of Madrid, Spain

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Area of Interest:

Physical Science Engineering
100%
Thermal Engineering
62%
Thermal Analysis
90%
Hydrodynamics
75%
Geophysics
55%

Research Publications in Numbers

Books
0
Chapters
0
Articles
0
Abstracts
0

Selected Publications

  1. Santillan, D.,J.C. Mosquera and L. Cueto-Felgueroso, 2017. Phase-field model for brittle fracture. validation with experimental results and extension to dam engineering problems. Eng. Fract. Mech., 178: 109-125.
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  2. Santillan, D., R. Juanes and L. Cueto-Felgueroso, 2017. Phase field model of fluid-driven fracture in elastic media: Immersed-fracture formulation and validation with analytical solutions. J. Geophys. Res.Solid Earth, 122: 2565-2589.
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  3. Cueto-Felgueroso, L., D. Santillan and J.C. Mosquera, 2017. Stick-Slip dynamics of flow-induced seismicity on rate and state faults. Geophys. Res. Lett., 44: 4098-4106.
    CrossRef  |  Direct Link  |  
  4. Vicente, D.J., L. Garrote, R. Sanchez and D. Santillan, 2015. Pressure management in water distribution systems: current status, proposals, and future trends J. Water Resour. Plann. Manag., .
    Direct Link  |  
  5. Santillan, D.,E. Salete and M.A. Toledo, 2015. A methodology for the assessment of the effect of climate change on the thermal-strain–stress behaviour of structures. Eng. Struct., 92: 123-141.
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  6. Santillan, D., E. Salete, M.A. Toledo and A. Granados, 2015. An improved 1D-model for computing the thermal behaviour of concrete dams during operation. Comparison with other approaches. Comput. Concr., 15: 103-126.
    CrossRef  |  
  7. Santillan, D., E. Salete and M.A. Toledo, 2015. A new 1D analytical model for computing the thermal field of concrete dams due to the environmental actions. Appl. Thermal Eng., 85: 160-171.
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  8. Santillan, D., L. Mediero and L. Garrote, 2014. Modelling uncertainty of flood quantile estimations at ungauged sites by Bayesian networks. J. Hydroinf., 16: 822-838.
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  9. Santillan, D., J. Fraile-Ardanuy and M.A. Toledo, 2014. Seepage prediction in arch dams by means of artificial neural networks. Tecnol. Ciencias del Agua, 5: 81-96.
  10. Santillan, D., E. Salete, D.J. Vicente and M.A. Toledo, 2014. Treatment of solar radiation by spatial and temporal discretization for modeling the thermal response of arch dams. J. Eng. Mech., .
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  11. Mediero, L., D. Santillan, L. Garrote and A. Granados, 2014. Detection and attribution of trends in magnitude, frequency and timing of floods in Spain. J. Hydrol., 517: 1072-1088.
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