Home | People | Lisa Maria Ringel, MEng

Lisa Maria Ringel, MEng

MEng Lisa Maria Ringel

+49 345 / 55 – 26076

Room 4.23
von-Seckendorff-Platz 3
06120 Halle (Saale)

Lisa Maria Ringel, MEng

+49 345 / 55 – 26076

Room 4.23
von-Seckendorff-Platz 3
06120 Halle (Saale)

About Me

My research focuses on the stochastic characterization of discrete fracture networks (DFNs). I use data from tomographic experiments to infer the properties of DFNs. For this purpose, I work on the  implementation of fast forward models by suitable numerical methods and I compare different inversion approaches (especially Markov chain Monte Carlo) by their efficiency and performance.

Research Interests

■  Numerical Methods
■  Inversion
■  Bayesian statistics
■  Hydraulic and Tracer Tomography

CV

2019 – today | PhD student
Martin Luther University Halle-Wittenberg,
Applied Geology

2018 – 2019 | Research Assistant
Ingolstadt University of Applied Sciences, Institute of New Energy Systems (InES)

2018 | Master‘s thesis
German Aerospace Center, Institute of Aeroelasticity
Title: Preliminary design of a wind tunnel experiment for transient shock boundary layer interaction

2017 – 2018 | M. Eng. Technical Development in Mechanical Engineering
Ingolstadt University of Applied Sciences

2015 – 2018 | Scholarship holder
Max Weber-Program

2013 – 2017 | B. Eng. Renewable Energy Technologies
Ingolstadt University of Applied Sciences

Publications

Ringel, L. M., Jalali, M., Bayer, P. 2021. Stochastic Inversion of Three-Dimensional Discrete Fracture Network Structure With Hydraulic Tomography. Water Resources Research. 57(12), e2021WR030401.

Ringel, L. M., Jalali, M. & Bayer, P.(2020). Inversion of three-dimensional discrete fracture networks using hydraulic tomography. Paper presented at the AGU Fall Meeting, virtual.

Ringel, L. M., Somogyvari, M., Jalali, M. & Bayer, P.(2020). Characterization of discrete fracture networks by invasive tomographic methods. Paper presented at Computational Methods in Water Resources, virtual.

Bayer, P., Afshari Moein, M. J., Somogyvári, M., Ringel, L. M., & Jalali, M. (2020). Stress-based tomography: potential, open-questions and future developments. Paper presented at the EGU General Assembly, virtual.

Ringel, L. M., Somogyvari, M., Jalali, M., & Bayer, P. (2020). A fast and robust approach for simulating the pressure diffusion in three-dimensional discrete fracture networks applied to inversion problems. Paper presented at the EGU General Assembly, virtual.

Englert, A., Bayer, P., Ringel, L. M., Jalali, M., & Somogyvari, M. (2019). Discrete Fracture Network reconstruction using a tomographic approach. AGU Fall Meeting, H32A-01.

Ringel, L. M., Somogyvári, M., Jalali, M., & Bayer, P. (2019). Comparison of Hydraulic and Tracer Tomography for Discrete Fracture Network Inversion. Geosciences, 9(6), 274.

Ringel, L. M., Somogyvári, M., Jalali, M., & Bayer, P. (2019). Inversion of discrete fracture networks by hydraulic and tracer tomography. Paper presented at the EGU General Assembly, Vienna.

Logo applied geoology
Daniela Rothe
Daniela Rothe

Secretary

Tel.: +49 345 / 55 – 26151
Fax: +49 345 / 55 – 27068

Room H3 1.30
von-Seckendorff-Platz 3
06120 Halle (Saale)