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2024 (submitted)
- Köse G, Zamora JDS, Osmancevic E, Janotte F, Oladyshkin S, Nowak W. Bayesian failure localization identifies inconsistencies between water distribution network models and real-world conditions. Journal of Water Resources Planning and Management - ASCE.
2024
- Kröker I, Nißler E, Oladyshkin S, Nowak W, Haslauer C. Data-driven surrogate-based Bayesian model calibration for predicting vadose zone temperatures in drinking water supply pipes. In: Geophys Res Abstr. Vienna: EGU General Assembly 2024; 2024. (Geophys. Res. Abstr.; Bde. 25, EGU2024-7820).
- Morales Oreamuno MF, Oladyshkin S, Nowak W. Training surrogate models using input dimension reduction and Bayesian active learning techniques for inverse modelling in heterogeneous media applications. In: geoENV2024 Book of Abstracts. Chania, Crete, GR: Creative Commons Licence BY-NC-ND 4.0; 2024. S. 191--192. (geoENV2024 Book of Abstracts).
- Chen Q, Boxberg MS, Menzel N, Morales Oreamuno MF, Nowak W, Oladyshkin S, u. a. The site selection data hub: a data-centric approach for integrated simulation workflow management in radioactive waste disposal site selection. In: Geophys Res Abstr. Vienna: EGU General Assembly 2024; 2024. (Geophys. Res. Abstr.; Bde. 26, EGU24-12859).
- Kröker I, Brünnette T, Wildt N, Oreamuno MFM, Kohlhaas R, Oladyshkin S, u. a. Bayesian Active Learning for Regularized Multi-Resolution Arbitrary Polynomial Chaos using Information Theory. International Journal for Uncertainty Quantification. September 2024;
- Kurgyis K, Achtziger-Zupančič P, Bjorge M, Boxberg MS, Broggi M, Buchwald J, u. a. Uncertainties and robustness with regard to the safety of a repository for high-level radioactive waste: Introduction of a research initiative. Environmental Earth Sciences. Januar 2024;83(2).
- Morales Oreamuno MF, Oladyshkin S, Nowak W. Error-aware surrogate modelling with input dimension reduction for groundwater modelling in heterogenous media. In: Geophys Res Abstr. Vienna: EGU General Assembly 2024; 2024. (Geophys. Res. Abstr.; Bde. 26, EGU24-12586).
2023
- Köse G, Oladyshkin S, Nowak W. Optimizing Pressure Monitoring in a Water Distribution Network through Bayesian Calibration. In: 18th Pipeline Technology Conference 2023 [Internet]. Berlin, Germany: EITEP Institute; 2023. (18th Pipeline Technology Conference 2023). Verfügbar unter: https://www.pipeline-conference.com/abstracts/optimizing-pressure-monitoring-water-distribution-network-through-bayesian-calibration
- Kohlhaas R, Kröker I, Oladyshkin S, Nowak W. Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator: concept for bias correction, assessment of surrogate reliability and its application to the carbon dioxide benchmark. Computational Geosciences. 2023;27(3):1–21.
- Oladyshkin S, Praditia T, Kroeker I, Mohammadi F, Nowak W, Otte S. The Deep Arbitrary Polynomial Chaos Neural Network or how Deep Artificial Neural Networks could benefit from Data-Driven Homogeneous Chaos Theory. Neural Networks. 2023;166:85–104.
- Horuz CC, Karlbauer M, Praditia T, Butz MV, Oladyshkin S, Nowak W, u. a. Physical Domain Reconstruction with Finite Volume Neural Networks. Applied Artificial Intelligence. 2023;37(1):2204261.
- Mohammadi F, Eggenweiler E, Flemisch B, Oladyshkin S, Rybak I, Schneider M, u. a. A surrogate-assisted uncertainty-aware Bayesian validation framework and its application to coupling free flow and porous-medium flow. Computational Geosciences. Juli 2023;27(4):663--686.
- Bürkner PC, Kröker I, Oladyshkin S, Nowak W. The sparse Polynomial Chaos expansion: a fully Bayesian approach with joint priors on the coefficients and global selection of terms. Journal of Computational Physics. 2023;112210.
- Morales Oreamuno MF, Oladyshkin S, Nowak W. Information-Theoretic Scores for Bayesian Model Selection and Similarity Analysis: Concept and Application to a Groundwater Problem. Water Resources Research. Juli 2023;59(7):e2022WR033711.
- Kröker I, Oladyshkin S, Rybak I. Global sensitivity analysis using multi-resolution polynomial chaos expansion for coupled Stokes-Darcy flow problems. Computational Geosciences [Internet]. 2023; Verfügbar unter: https://rdcu.be/dhL31
- Zhang L, Nowak W, Oladyshkin S, Wang Y, Cai J. Opportunities and challenges in CO2 geologic utilization and storage. Advances in Geo-Energy Research. Juli 2023;8(3):141–5.
- Schwindt S, Medrano SC, Mouris K, Beckers F, Haun S, Nowak W, u. a. Bayesian calibration points to misconceptions in three-dimensional hydrodynamic reservoir modelling. Water Resources Research. 2023;59:e2022WR033660.
- Mouris K, Acuna Espinoza E, Schwindt S, Mohammadi F, Haun S, Wieprecht S, u. a. Stability criteria for Bayesian calibration of reservoir sedimentation models. Modeling Earth Systems and Environment [Internet]. 2023; Verfügbar unter: https://doi.org/10.1007/s40808-023-01712-7
2022
- Cheng K, Z L, Xiao S, Oladyshkin S, Nowak W. Mixed covariance function Kriging model for uncertainty quantification. International Journal for Uncertainty Quantification. 2022;12(3):17–30.
- Horuz CC, Karlbauer M, Praditia T, Butz MV, Oladyshkin S, Nowak W, u. a. Inferring Boundary Conditions in Finite Volume Neural Networks. In: Pimenidis E, Angelov P, Jayne C, Papaleonidas A, Aydin M, Herausgeber. International Conference on Artificial Neural Networks and Machine Learning -- ICANN 2022. Cham: Springer International Publishing; 2022. S. 538–49. (Pimenidis E, Angelov P, Jayne C, Papaleonidas A, Aydin M, Reihenherausgeber. International Conference on Artificial Neural Networks and Machine Learning -- ICANN 2022).
- Kröker I, Oladyshkin S. Arbitrary Multi-Resolution Multi-Wavelet-based Polynomial Chaos Expansion for Data-Driven Uncertainty Quantification. Reliability Engineering & System Safety. 2022;222:108376.
- Praditia T, Karlbauer M, Otte S, Oladyshkin S, Butz MV, Nowak W. Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network. Water Resources Research. 2022;58(12).
- Karlbauer M, Praditia T, Otte S, Oladyshkin S, Nowak W, Butz MV. Composing Partial Differential Equations with Physics-Aware Neural Networks. In: Proceedings of the 39th International Conference on Machine Learning. Baltimore, USA; 2022. S. 10773--10801. (Proceedings of the 39th International Conference on Machine Learning).
2021 (submitted)
- Cheng K, Lu Z, Xiao S, Oladyshkin S, Nowak W. Unified Bayesian inference framework for surrogate modelling: connection between existing techniques and their common fundamentals. Reliability Engineering and System Safety.
2021
- Praditia T, Oladyshkin S, Nowak W. Finite Volume Neural Networks: a Hybrid Modeling Strategy for Subsurface Contaminant Transport. In: AGU Fall Meeting 2021. 2021. (AGU Fall Meeting 2021).
- Cheng K, Xiao S, Zhang X, Oladyshkin S, Nowak W. Resampling method for reliability-based design optimization based on thermodynamic integration and parallel tempering. Mechanical Systems and Signal Processing. 2021;156:107630.
- Praditia T, Karlbauer M, Otte S, Oladyshkin S, Butz M, Nowak W. Finite Volume Neural Network: Modeling Subsurface Contaminant Transport. In: Deep Learning for Simulation ICLR Workshop 2021 [Internet]. 2021. (Deep Learning for Simulation ICLR Workshop 2021). Verfügbar unter: https://arxiv.org/abs/2104.06010
- Scheurer S, Schäfer Rodrigues Silva A, Mohammadi F, Hommel J, Oladyshkin S, Flemisch B, u. a. Surrogate-based Bayesian Comparison of Computationally Expensive Models: Application to Microbially Induced Calcite Precipitation. Computational Geosciences. 2021;25:1899–917.
- Praditia T, Oladyshkin S, Nowak W. Physics Informed Neural Network for porous media modelling. In Stuttgart, Germany: InterPore German Chapter Meeting 2021; 2021.
- Praditia T, Oladyshkin S, Nowak W. Universal Differential Equation for Diffusion-Sorption Problem in Porous Media Flow. In online: EGU General Assembly 2021; 2021.
- Flaig S, Praditia T, Kissinger A, Lang U, Oladyshkin S, Nowak W. Prognosis of water levels in a moor groundwater system influenced by hydrology and water extraction using an artificial neural network. In online: EGU General Assembly 2021; 2021.
- Xiao S, Praditia T, Oladyshkin S, Nowak W. Global sensitivity analysis of a CaO/Ca(OH)2 thermochemical energy storage model for parametric effect analysis. Applied Energy [Internet]. 2021;285:116456. Verfügbar unter: https://www.sciencedirect.com/science/article/pii/S0306261921000222
2020
- Xiao S, Oladyshkin S, Nowak W. Forward-reverse switch between density-based and regional sensitivity analysis. Applied Mathematical Modelling. 2020;84:377–92.
- Xiao S, Oladyshkin S, Nowak W. Reliability analysis with stratified importance sampling based on adaptive Kriging. Reliability Engineering & System Safety. 2020;197:106852.
- Beckers F, Heredia A, Noack M, Nowak W, Wieprecht S, Oladyshkin S. Bayesian Calibration and Validation of a Large-scale and Time-demanding Sediment Transport Model. Water Resources Research. 2020;56(7):e2019WR026966.
- Manguang G, Zhang L, Miao X, Oladyshkin S, Cheng X, Wang Y, u. a. Application of computed tomography (CT) in geologic CO_2 storage research: a critical review. Journal of Natural Gas Science and Engineering. 2020;103591.
- Oladyshkin S, Beckers F, Kroeker I, Mohammadi F, Heredia A, Noack M, u. a. Uncertainty quantification using Bayesian arbitrary polynomial chaos for computationally demanding environmental modelling: conventional, sparse and adaptive strategy. In: Computational Methods in Water Resources (CMWR). 2020. (Computational Methods in Water Resources (CMWR)).
- Oladyshkin S, Mohammadi F, Kröker I, Nowak W. Bayesian3 active learning for Gaussian process emulator using information theory. Entropy. 2020;22(0890):1–27.
- Guthke A, Bakhshipour AE, de Barros F, Class H, Daniell JE, Dittmer U, u. a. A unified framework for quantitative interdisciplinary flood risk assessment. In online: AGU Fall Meeting 2020; 2020.
- Praditia T, Walser T, Oladyshkin S, Nowak W. Improving Thermochemical Energy Storage dynamics forecast with Physics-Inspired Neural Network architecture. Energies [Internet]. 2020;13(15):3873. Verfügbar unter: https://www.mdpi.com/1996-1073/13/15/3873
2019
- Köppel M, Franzelin F, Kröker I, Oladyshkin S, Santin G, Wittwar D, u. a. Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario. Computational Geosciences. 2019;23(2):339–54.
- J. Salgado, Oladyshkin S, Osmancevic E, Janotte F. Kalibrierung von Rechennetzmodellen anhand probabilistischer Bayes‘scher Verfahren. DWGV energie wasser-praxis. 2019;2:16–21.
- Xiao S, Reuschen S, Köse G, Oladyshkin S, Nowak W. Estimation of small failure probabilities based on thermodynamic integration and parallel tempering. Mechanical Systems and Signal Processing. 2019;133:106248.
- Xiao S, Oladyshkin S, Nowak W. Reliability sensitivity analysis with subset simulation: application to a carbon dioxide storage problem. In: International Conference of Euro Asia Civil Engineering Forum. Stuttgart, Germany: International Conference of Euro Asia Civil Engineering Forum; 2019. (International Conference of Euro Asia Civil Engineering Forum).
- Praditia T, Walser T, Oladyshkin S, Nowak W. Using physics-based regularization in Artificial Neural Networks to predict thermochemical energy storage systems. In: Fall Meeting 2019, Abstract: IN32B-15. San Francisco, CA, USA: American Geophysical Union (AGU); 2019. (Fall Meeting 2019, Abstract: IN32B-15).
- Oladyshkin S, Nowak W. The connection between Bayesian Inference and Information Theory for model selection, information gain and experimental design. Entropy. 2019;21:1081.
2018
- Oladyshkin S, Guthke A, Mohamadi F, Kopmann R, Nowak W. Model selection under computational time constraints: application to river engineering. In Saint-Malo, France: XXII. International Conference on Computational Methods in Water Resources (CMWR); 2018.
- Mohammadi F, Kopmann R, Guthke A, Oladyshkin S, Nowak W. Bayesian selection of hydro-morphodynamic models under computational time constraints. Advances in Water Resources [Internet]. 2018;117:53–64. Verfügbar unter: http://www.sciencedirect.com/science/article/pii/S0309170817311909
- Oladyshkin S, Nowak W. Incomplete statistical information limits the utility of higher-order polynomial chaos expansions. Reliability Engineering & System Safety. 2018;169:137–48.
- Guthke A, Oladyshkin S, Mohammadi F, Kopmann R, Nowak W. Bayesian model selection under computational time constraints: application to river modeling. In: Fall Meeting 2018. Washington, D.C., USA: American Geophysical Union (AGU); 2018. (Fall Meeting 2018).
2017
- Namhata A, Zhang L, Dilmore RM, Oladyshkin S, Nakles DV. Modeling Pressure Changes due to Migration of Fluids into the Above Zone Monitoring Interval of a Geologic Carbon Storage Site. International Journal of Greenhouse Gas Control. 2017;56:30–42.
- Agada SS, Geiger S, ElSheikh A, Oladyshkin S. Data-driven surrogates for rapid simulation and optimization of WAG injection in fractured carbonate reservoirs. Petroleum Geoscience. 2017;23(2):270–83.
- Fernandez B, Kopmann R, Oladyshkin S. Automated Calibration For Numerical Models Of Riverflow. In: General Assembly 2017, Geophysical Research Abstracts 19: EGU2017-1026-3, 2017. Vienna, Austria: European Geosciences Union (EGU); 2017. (General Assembly 2017, Geophysical Research Abstracts 19: EGU2017-1026-3, 2017).
2016
- Oladyshkin S, Nowak W. Incomplete statistical information limits the utility of higher-order polynomial chaos expansions. In Lausanne Switzerland: SIAM Conference on Uncertainty Quantification; 2016.
- T. H. Mai, W. Nowak RK, Oladyshkin S. Uncertainty quantification for a hydro-morphodynamic model of river Rhine. In: General Assembly 2016, Geophysical Research Abstracts 18: EGU2016-5701-3, 2016. Vienna, Austria: European Geosciences Union (EGU); 2016. (General Assembly 2016, Geophysical Research Abstracts 18: EGU2016-5701-3, 2016).
- Schulte DO, Rühaak W, Oladyshkin S, Welsch B, Sass I. Optimization of Medium Deep Borehole Thermal Energy Storages. Energy Technology. 2016;(4):104–13.
- Namhata A, Oladyshkin S, Dilmore RM, Zhang L, Nakles DV. Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site. Scientific Reports. 2016;6:39536.
- Zhang Y, Liu Y, Pau G, Oladyshkin S, Finsterle S. Evaluation of multiple reduced-order models to enhance confidence in global sensitivity analyses. International Journal of Greenhouse Gas Control. 2016;49:217–26.
- Schulte D, Rühaak W, Welsch B, Oladyshkin S, Sass I. Optimization of borehole heat exchanger arrays. Energy Storages. In: General Assembly 2016, Geophysical Research Abstracts 18: EGU2016-8405-1, 2016. Vienna, Austria: European Geosciences Union (EGU); 2016. (General Assembly 2016, Geophysical Research Abstracts 18: EGU2016-8405-1, 2016).
2015
- Hlawatsch M, Oladyshkin S, Weiskopf D. Employing Model Reduction for Uncertainty Visualization in the Context of CO$_2$ Storage Simulation. Visualization for Decision Making Under Uncertainty. In: SPE Reservoir Simulation Symposium. Chicago, IL, USA: IEEE VIS 2015 Conference; 2015. (SPE Reservoir Simulation Symposium).
- Agada S, Geiger S, Elsheikh AH, Mackay E, Oladyshkin S. Reduced Order Models for Rapid EOR Simulation in Fractured Carbonate Reservoirs. In: SPE Reservoir Simulation Symposium. Society of Petroleum Engineers; 2015. S. SPE-173205. (SPE Reservoir Simulation Symposium).
- A. Namhata, S. Oladyshkin RD, Nakles DV. Leakage Characterization through Above Zone Monitoring Interval: Uncertainty Quantification and Sensitivity Analysis. In Pittsburgh, PA, USA: The 14th Annual Conference on Carbon Capture Utilization and Storage; 2015.
- Namhata A, Dilmore R, Oladyshkin S, Zhang L, Nakles DV. Modeling, Uncertainty Quantification and Sensitivity Analysis of Subsurface Fluid Migration in the Above Zone Monitoring Interval of a Geologic Carbon Storage Site. In: Fall Meeting 2015, Abstract: H51U-05. San Francisco, CA, USA: American Geophysical Union (AGU); 2015. (Fall Meeting 2015, Abstract: H51U-05).
2014
- Oladyshkin S, Schröder P, Class H, Nowak W. Stochastic model calibration for large-scale applications via Bayesian updating combined with arbitrary polynomial chaos. In Stuttgart, Germany: XX. International Conference on Computational Methods in Water Resources (CMWR); 2014.
- Zhang Y, Oladyshkin S, Y YL, Pau GSH. Comparison of four reduced order models for uncertainty quantification in subsurface flow and transport problems. In Stuttgart, Germany: XX. International Conference on Computational Methods in Water Resources (CMWR); 2014.
- Elsheikh AH, Oladyshkin S, Nowak W, Christie M. Estimating the probability of CO_2 leakage using rare event simulation. In: ECMOR XIV-14th European conference on the mathematics of oil recovery. 2014. S. We B25. (ECMOR XIV-14th European conference on the mathematics of oil recovery).
- Oladyshkin S, de Barros HCRHWNFPJ, Ashraf M. Data-driven polynomial response surfaces as efficient tool for applied tasks under uncertainty. In Research Triangle Park, NC, USA: SAMSI Geosciences Applications Opening Workshop; 2014.
- Zhang Y, Oladyshkin S, Y YL, Pau GSH. Comparison of Applying four Reduced Order Models to a Global Sensitivity Analysis. In: Fall Meeting 2014, Abstract: H31J-0761. San Francisco, CA, USA: American Geophysical Union (AGU); 2014. (Fall Meeting 2014, Abstract: H31J-0761).
- Oladyshkin S, Nowak W. Analyzing the expansion order for polynomial chaos expansions in the light of imprecise information on statistical input distributions. In Boulder, CO, USA: 1st International Conference on Frontiers in Computational Physics: Modeling the Earth System; 2014.
- Karajan N, Otto D, Oladyshkin S, Ehlers M. Application of the polynomial chaos expansion to approximate the homogenised response of the intervertebral disc. Biomechanics and modeling in mechanobiology. 2014;13(5):1065–80.
- Franzelin F, Pflüger D, Oladyshkin S. Uncertainty quantification with adaptive sparse grids and its application to CO$_2$ storage. In Stuttgart, Germany: XX. International Conference on Computational Methods in Water Resources (CMWR); 2014.
- Namhata A, Oladyshkin S, Dilmore R, Nakles DV. Leakage Characterization through Above Zone Monitoring Interval: Uncertainty Quantification and Sensitivity Analysis. In Pittsburgh, PA, USA: The 14th Annual Conference on Carbon Capture Utilization and Storage; 2014.
- Oladyshkin S. Efficient Modeling of Environmental Systems in the Face of Complexity and Uncertainty [Internet]. Habilitationsschrift Nr. 231, Mitteilungsheft des Instituts für Wasserbau Nr. 231 (Habilitationsschrift) Institut für Wasserbau, Universität Stuttgart, 2014. ISBN: 978-3-942036-35-1; 2014. Verfügbar unter: http://elib.uni-stuttgart.de/opus/volltexte/2015/9523/
2013
- Oladyshkin S, Class H, Nowak W. Bayesian updating via bootstrap filtering combined with data-driven polynomial chaos expansions:methodology and application to history matching for carbon dioxide storage in geological formations. Computational Geosciences. 2013;17(4):671–87.
- Oladyshkin S, Nowak W. On polynomial chaos expansions under incomplete statistical input information. In München, Germany: Euromech colloquium 543; 2013.
- Oladyshkin S, Schröder P, Class H, Nowak W. Chaos Expansion based Bootstrap Filter to Calibrate CO2 Injection Models. Energy Procedia. 2013;40:398–407.
- Ashraf M, Oladyshkin S, Nowak W. Geological storage of CO2: global sensitivity analysis and risk assessment using arbitrary polynomial chaos expansion. International Journal of Greenhouse Gas Control. 2013;19:704–19.
- Flemisch B, Class H, Darcis M, Faigle B, Hommel J, Kissinger A, u. a. Coupling Approaches, Risk Assessment and History Matching for CO$_2$ Storage Modeling. In Granada, Spain: Plenary lecture; 2013.
2012
- Oladyshkin S, Nowak W. Analyzing the expansion order for polynomial chaos expansions in the light of imprecise information on statistical input distributions. In Boulder, CO, USA: 1st International Conference on Frontiers in Computational Physics: Modeling the Earth System; 2012.
- Oladyshkin S, Panfilov M. Open thermodynamic model for compressible multicomponent two-phase flow in porous media. Journal of Petroleum Science and Engineering. 2012;81:41–8.
- Walter L, Binning PJ, Oladyshkin S, Flemisch B, Class H. Brine migration resulting from CO$_2$ injection into saline aquifers - An approach to risk estimation including various levels of uncertainty. International Journal of Greenhouse Gas Control. 2012;9:495–506.
- Walter L, Binning PJ, Oladyshkin S, Flemisch B, Class H. Modeling concepts to address risk of brine infiltration into shallow groundwater resources. In Urbana-Champaign, IL, USA: XIX. International Conference on Computational Methods in Water Resources (CMWR); 2012.
- Oladyshkin S, Nowak W. Polynomial Response Surfaces for Probabilistic Risk Assessment and Risk Control via Robust Design (Book). Luo Y, Herausgeber. Novel Approaches and Their Applications in Risk Assessment, ISBN: 978-953-51-0519-0 [Internet]. 2012; Verfügbar unter: /brokenurl#www.intechopen.com/books/
- Ashraf M, Oladyshkin S, Nowak W. Geological storage of CO$_2$: sensitivity analysis and risk assessment using arbitrary polynomial chaos expansion. In: General Assembly 2012, Geophysical Research Abstracts 14: EGU2012-9243, 2012. Vienna, Austria: European Geosciences Union (EGU); 2012. (General Assembly 2012, Geophysical Research Abstracts 14: EGU2012-9243, 2012).
- Oladyshkin S, Nowak W. Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion. Reliability Engineering and System Safety. 2012;106:179–90.
- Oladyshkin S, de Barros FPJ, Nowak W. Global sensitivity analysis: a flexible and efficient framework with an example from stochastic hydrogeology. Advances in Water Resources. 2012;37:10–22.
- Walter L, Kissinger A, Oladyshkin S, Helmig R. Methods for evaluating competitive use of the subsurface - for example, the influence of CCS in groundwater. In TU, München, Germany: Keynote lecture, Exploratory Workshop: An integrated approach to water research and technology development; 2012.
2011
- Oladyshkin S, Class H, Helmig R, Nowak W. Efficient Bayesian updating with PCE-based particle filters based on polynomial chaos expansion and CO$_2$ storage. In: Fall Meeting 2011, Abstract: GC51A-0928. San Francisco, CA, USA: American Geophysical Union (AGU); 2011. (Fall Meeting 2011, Abstract: GC51A-0928).
- de Barros FPJ, Oladyshkin S, Nowak W. An integrative data-adaptive approach for global sensitivity analysis: application to subsurface flow and transport. In: General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-11206, 2011. Vienna, Austria: European Geosciences Union (EGU); 2011. (General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-11206, 2011).
- Enzenhöfer R, Geiges A, Koch J, Leube P, Mehne J, Oladyshkin S, u. a. Zurück in die Unsicherheit - Stochastische Modellierung von Hydrosystemen. In Stuttgart, Germany: LH2-Kolloquium; 2011.
- Oladyshkin S, Class H, Helmig R, Nowak W. An Integrative Approach to Robust Design and Probabilistic Risk Assessment for CO$_2$ Storage in Geological Formations. Computer Geosciences. 2011;15(3):565–77.
- Oladyshkin S, Panfilov M. Hydrogen penetration in water through porous medium: application to a radioactive waste storage site. Environmental Earth Sciences. 2011;64(4):989–99.
- Oladyshkin S, Class H, Helmig R, Nowak W. A concept for data-driven probabilistic risk assessment and application to carbon dioxide storage in geological formations. Advances in Water Resources. 2011;34:1508–18.
- Oladyshkin S, Class H, Helmig R, Nowak W. Bayesian updating on arbitrary polynomial chaos expansion: application to carbon dioxide storage in geological formations. In Poitiers, France: Invited lecture: Pprime CNRS, CEAT; 2011.
- Walter A, Binning PJ, Class H, Flemisch B, Oladyshkin S. Brine migration due to CO2 injection into saline aquifers? A consistent approach to risk estimation including different levels of uncertainty. In Bergen, Norway: Workshop: IGeMS; 2011.
- Walter L, Class H, Oladyshkin S, Flemisch B, Helmig R. Influence of Dirichlet boundary conditions on risk assessment for CO$_2$ storage in geological formations. In Urbana-Champaign, IL, USA: SimTech 2011 - International Conference on Simulation Technology 2011; 2011.
- Oladyshkin S, Class H, Helmig R, Nowak W. Data-driven framework for history matching: application to carbon dioxide storage in geological formations. In: General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-11137, 2011. Vienna, Austria: European Geosciences Union (EGU); 2011. (General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-11137, 2011).
- Oladyshkin S, Class H, Helmig R, Nowak W. Modeling of underground carbon dioxide storage: data-driven robust design and probabilistic risk assessment. In Stuttgart, Germany: SimTech 2011 - International Conference on Simulation Technology 2011; 2011.
- Walter L, Oladyshkin S, Class H, Darcis M, Helmig R. A study on pressure evolution in a channel system during CO$_2$ injection. Energy Procedia. 2011;4:3722–9.
2010
- Oladyshkin S, Class H, Helmig R, Nowak W. Probabilistic risk assessment for $CO_2$ storage in geological formations: robust design and support for decision making under uncertainty. In: General Assembly 2010, Geophysical Research Abstracts 12: EGU2010-3559, 2010. Vienna, Austria: European Geosciences Union (EGU); 2010. (General Assembly 2010, Geophysical Research Abstracts 12: EGU2010-3559, 2010).
- Oladyshkin S, Class H, Helmig R, Nowak W. Data-driven framework for modeling of CO$_2$ storage: probabilistic risk assessment, robust design and history matching. In Princeton, NJ, USA: Workshop: Scale of resolution, model complexity and solution approaches for CO2 storage problems; 2010.
- Walter L, Oladyshkin S, Class H, Darcis M, Helmig R. A study on pressure evolution in a sand channel system during CO$_2$ injection. In Amsterdam, The Netherlands: Greenhouse Gas Control Technologies (GHGT10); 2010.
- Oladyshkin S, Class H, Helmig R, Nowak W. Chaos expansion for uncertainty quantification of multiphase flow in CO$_2$ storage reservoirs. In Nancy, France: JEMP 2010; 2010.
- Oladyshkin S, Class H, Hofmann R, Nowak W. Highly efficient tool for probabilistic risk assessment of CCS joint with injection design. In Barcelone, Spain: XVIII. International Conference on Computational Methods in Water Resources (CMWR); 2010.
- Oladyshkin S, Class H, Helmig R, Nowak W. Data-driven robust design and probabilistic risk assessment: application to underground carbon dioxide storage. In: Fall Meeting 2010, Abstract: H41L-03. San Francisco, CA, USA: American Geophysical Union (AGU); 2010. (Fall Meeting 2010, Abstract: H41L-03).
- Oladyshkin S, Class H, Helmig R, Nowak W, de Barros FPJ, Ashraf M. Data-driven polynomial response surfaces as efficient tool for applied tasks under uncertainty. In Research Triangle Park, NC, USA: SAMSI Geosciences Applications Opening Workshop; 2010.
2009
- Oladyshkin S, Nowak W, Helmig R. Joint design and probabilistic risk assessment for CO$_2$ storage by integral probabilistic collocation method. In Stuttgart, Germany: International conference on Non-linearities and Upscaling in Porous Media (NUPUS); 2009.
2008
- Oladyshkin S, Royer JJ, Panfilov M. Effective solution through the streamline technique and HT-splitting for the $3$D dynamic analysis of the compositional flows in oil reservoirs. Transport in Porous Media. 2008;74(3):311–29.
- Oladyshkin S. HT-splitting and open thermodynamic model for compressible multicomponent two-phase flow in porous media. In Nancy, France: EUROMECH Colloquium 499, Nonlinear Mechanics of Multiphase Flow in Porous Media: Phase Transitions, Instability, Non equilibrium, Modelling; 2008.
- Oladyshkin S, Panfilov M. Differential split thermodyamic model for gasliquid compositional flow. In Lyon, France: MoMaS Journ’ees Multiphasiques; 2008.
2007
- S. Oladyshkin JJR, Panfilov M. Modelling Compositional Flows in Oil Reservoirs using gOcad Streamline Simulator and HT-Splitting Technique. In: 27th Gocad Meeting. Nancy, France; 2007. (27th Gocad Meeting).
- Oladyshkin S, Panfilov M. Limit thermodynamic model for compositional gas-liquid systems moving in a porous medium. Transport in Porous Media. 2007;70(2):147–65.
- Oladyshkin S, Panfilov M. Hydro-thermodynamics of multi-compositional flow in porous media: modelling of hydrogen-water flow with mass exchange in an underground storage. In St-Raphael, France: Mini-cours. GdR MoMaS, Modélisation Numérique d’Écoulements Multiphasiques en Milieux Poreux : Application au Transfert des Gaz autour du Stockage de Déchets Radioactifs; 2007.
- Oladyshkin S, Skachkov S, Panfilova I, Panfilov M. Upscaling fractured media and streamline HT-splitting in compositional reservoir simulation. Oil & Gas Science and Technology. 2007;62(2):137–46.
- Oladyshkin S, Panfilov M. Streamline splitting between thermodynamics and hydrodynamics in compositional gas-liquid flow through porous media. Comptes rendus de l’Academie des sciences Mecanique. 2007;335(1):7–12.
2006
- Oladyshkin S, Panfilov M. Gas-liquid flow in porous media, HT-splitting and asymptotic solutions. In Nancy, France: The 4th Seminar “Sciences and Engineering of Resources, Techniques, Produced, Environment”; 2006.
- Oladyshkin S, Panfilova I, Panfilov M. Non-Equlibrium Two-Velocity Effects in Gas-Condensate Flow through Porous Media. In: ECMOR-X :10th European Conference on the Mathematics of Oil Recovery P B029. Amsterdam, Netherlands; 2006. S. 10. (ECMOR-X :10th European Conference on the Mathematics of Oil Recovery P. B029).
- Oladyshkin S, M. Panfilov IP, Skachkov S. Streamline splitting the thermo- and hydrodynamics in compositional gas-liquid flow through porous media and application to hydrogen - water behaviour in radioactive waste deposits. In Pau, France: GdR MoMaS, Modélisation Numérique d’Écoulements Multiphasiques en Milieux Poreux : Application au Transfert des Gaz autour du Stockage de Déchets Radioactifs; 2006.
- Oladyshkin S, Panfilov M. Splitting the Thermodynamics and Hydrodynamics in Compositional Gas-Liquid Flow through Porous Reservoirs. In: ECMOR-X :10th European Conference on the Mathematics of Oil Recovery P B030. Amsterdam, Netherlands; 2006. S. 10. (ECMOR-X :10th European Conference on the Mathematics of Oil Recovery. P. B030).
- S. Oladyshkin, M. Panfilov IP, Shandrygin A. Two-phase flow of a retrograde mixture in the porous media: non-equlibrium effects and splitting the thermodynamlics and hydrodynamics. In: IX Russian Congress of Theoretical and Applied Mechanics. Nizhniy Novgorod, Russia; 2006. S. 140. (IX Russian Congress of Theoretical and Applied Mechanics; Bd. 2).
- Oladyshkin S, M. Panfilov IP, Skachkov S. Upscaling the macro-fractures in compositional reservoir simulation: streamline HT-splitting and analytical boundary method. In Rueil-Malmaison, France: Int. Conf. Quantitative Methods for Reservoir Characterization. IFP,; 2006.
2005
- Oladyshkin S, Panfilov M. Asymptotic semi-stationary contrast model of gas-liquid flow with phase transitions in porous media. In Avignon, France: Int. Conference SIAM : Society for Industrial and Applied Mathematics, “Mathematical and Computational Issues in the Geosciences”; 2005. S. 35.
- Oladyshkin S, Panfilov M. Asymptotic analytical model of gas-condensate flow in porous media. In: 3rd Seminar “Sciences and Engineering of Resources, Techniques, Production, Environment". Nancy, France; 2005. S. 276–83. (3rd Seminar “Sciences and Engineering of Resources, Techniques, Production, Environment").
- S. Oladyshkin MP. Modeling of two-phase macroflow with phase transitions and contract properties. Transactions of the Russian Academy of Engineering Sciences. 2005;5:34–6.
- Oladyshkin S, Panfilov M. Two-phase flow with phase transitions in porous media: instability of stationary solutions and a semi-stationary model. In: Third Biot Conference on Poromechanics. Norman, OK, USA; 2005. S. 529–35. (Third Biot Conference on Poromechanics; Bd. Procs POROMECHANICS-3, ISBN: 0415380413).
2003
- S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. Invariant immersing method applied to the problem to thermocapillary convection a viscous fluid in the plane channel. Transactions of the Russian Academy of Engineering Sciences Ser Applied Mathematics and Mechanics. 2003;4:26–31.
- S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. Influence of the Marangoni thermocapillary effect on thermal distribution in the modelling environment with space conditions. In Ekaterinbourg, Russia: UrO RAN; 2003. S. 52.
- S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. Influence of Marangoni forces on distribution of temperature in the viscous fluid filling a two-sided corner. In Moscow-Izhevsk, Russia: The 3 international conference “Mathematics. Computer. Education”; 2003. S. 90.
2002
- S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. Temperature crisis in the viscous fluid of finite thermoconductivity, which motion under the action of Marangoni forces. In Sarov, Russia: The VII N. Novgorod session of young scientists (section of mathematics and mathematical modelling); 2002. S. 58–9.
- S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. Algorithm of invariant immersing as applied to thermocapillary convection a viscous liquid in a plane channel. In N. Novgorod, Russia: The VII computer-based conference «Information technologies in science, designing and manufacture»; 2002. S. 9.
- S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. The simulation of viscous fluid convection in the plane channel under the thermocapillary forces action. In Moscow-Dubna, Russia: The 3 international conference “Mathematics. Computer. Education”; 2002. S. 121.
- S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. Modeling of temperature and velocity field inside viscous fluid of finite thermoconductivity, moving inside a corner with free surface, under the action of Marangoni forces. Transactions of the Russian Academy of Engineering Sciences Ser Applied Mathematics and Mechanics. 2002;79–88.
2001
- S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. The simulation of viscous fluid convection in the plane channel under the thermocapillary forces action. In N. Novgorod, Russia: The 3 international scientific-practical conference on graphic information technologies and systems (COGRAPH); 2001. S. 13.
- S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. Marangoni effect, when the surface tension coefficient depends non-linearly on the temperature. In Ekaterinburg, Russia: 3 All-Russian congress on theoretical and applied mechanics. Ural department of Russian Academy of Sciences; 2001. S. 15.
- S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. The numerical algorithm development in the problem of thermocapillary convection under the Marangoni forces action. Transactions of the Russian Academy of Engineering Sciences. 2001;2:28–39.
07/2002 Angewandte Mathematik (Dipl.), Lobachevsky Staatliche Universität zu
Nizhny Novgorod, Russland
10/2003 - 12/2008 Wissenschaftlicher Mitarbeiter, Universität Lorraine, Nancy,
Frankreich
10/2006 Promotion, Universität Lorraine, Nancy, Frankreich
02/2009-02/2014 Wissenschaftlicher Mitarbeiter, Institut für Wasser- und
Umweltsystemmodellierung, Universität Stuttgart
02/2014 Habilitation, Universität Stuttgart
Since 09/2014 stellvertretender Leiter der Abteilung Stochastische Simulation und
Sicherheitsforschung für Hydrosysteme, Institut für Wasser- und Umweltsystemmodellierung,
Universität Stuttgart
Seit 09/2020 apl. Professor, Institut für Wasser- und Umweltsystemmodellierung,
Universität Stuttgart
Seit 10/2021 Studiendekan “Water Resources Engineering and Management”,
Universität Stuttgart
Umwelttechnik: Kohlendioxidspeicherung, unterirdische Lagerstätten, Lagerung radioaktiver
Abfälle
Unterirdische Strömung: Strömung in porösen Medien, mehrphasige Strömung, Strömung in der
Zusammensetzung
Quantifizierung von Unsicherheiten und maschinelles Lernen: Polynomiale Chaos-Erweiterung,
Gauß-Prozess-Emulator, Sensitivitätsanalyse, Risikobewertung, Modellkalibrierung, Modellauswahl,
Bayes'sche Inferenz, Informationstheorie
Projekte: