arXiv subjects

Ioannis Stefanou

Publications and source records attributed to Ioannis Stefanou.

At least 19 recordsLinked to original sources

arXiv2026

Modular Sign Compensation for MIMO Systems with Unknown Control Direction: An Exact Nominal Recovery Approach

This paper addresses stabilization of MIMO systems with uncertain time-varying diagonal input direction. We propose a modular switching sign-compensation layer acting as an outer wrapper around a nominal controller. Unlike Nussbaum-type gains, monitoring functions, or binary adaptive mechanisms, the method uses only bounded sign changes that preserve the nominal control magnitude and its properties. The compensation layer uses adaptive variables built from nominal Lyapunov quantities to search for the unknown input-sign configuration based on schedulers. Two schedulers are developed: a vector scheduler, where each input channel explores its own sign compensation and admits an online trapping certificate, and a scalar pattern scheduler, where one variable visits all diagonal sign matrices and gives a design-time recovery guarantee on sufficiently long constant-sign intervals. Once the correct sign configuration is set, the actual closed loop coincides with the nominal closed loop and the original nominal stability property is recovered. The approach is illustrated on a flight roll-reversal problem, a visual-servoing benchmark, and an underground-reservoir control example motivated by human induced-seismicity mitigation.

eess.SY↗

arXiv2026

A Control Framework for Induced Seismicity Mitigation in Groningen Gas Reservoir

Induced seismicity associated with gas production poses major operational and societal challenges, as illustrated by the Groningen field in the Netherlands. While many studies have focused on forecasting seismicity under prescribed production scenarios, fewer works address the inverse problem: designing operational strategies that minimize seismicity while maintaining production objectives. In this paper, we propose a control-oriented methodology for operating Groningen under induced-seismicity mitigation constraints. We employ a cascade model coupling pore-pressure diffusion with seismicity rate (SR) dynamics, and complement it with a stochastic event-generation procedure to convert the continuous SR field into a synthetic earthquake catalog with event times, locations, and magnitudes. From this catalog, we estimate regional SR measurements and design a robust feedback controller that computes well-rate commands to regulate the SR toward a desired reference while satisfying operational requirements, including prescribed production constraints. The proposed control architecture explicitly accounts for injection and extraction flux limits (actuator saturation). The well fluxes generated by the controller are updated at discrete-time intervals (digital control). We validate the modeling components against Groningen data and illustrate the approach through numerical experiments under different scenarios, including various control update periods and gain selections, as well as combined production with compensating injection (e.g., reinjection of nitrogen). The results illustrate how the proposed framework can reduce seismicity levels in a controlled manner while maximizing production targets.

eess.SY↗

arXiv2026

A shifted interface approach for internal discontinuities in poroelastic media

Porous media containing cracks, fractures, or internal discontinuities arise throughout subsurface geomechanics, biomechanics, and materials science. Numerical simulation of the coupled hydromechanical response is inherently challenging because the pressure and displacement fields are tightly coupled through the Biot equations, requiring stable mixed formulations. These difficulties are compounded when cracks are present, because standard mesh-conforming approaches require costly, labor-intensive, body-fitted meshing, while unfitted methods often require cut-cell integration, enrichment functions, or additional stabilization. In this work, we use an alternative approach, we adapt the shifted interface method to coupled transient poroelasticity with embedded interfaces. The method replaces the true crack by a surrogate approximation where interface conditions are transferred through local expansions. A unified derivation yields shifted forms for both hydraulic transmission and mechanical traction coupling. Two enforcement strategies are extensively compared: a weak (integral) enforcement and a strong (pointwise) enforcement. Four test cases of increasing geometric complexity (offset mesh-aligned, boundary-intersecting angled, embedded angled, and multi-crack configurations) validate the formulation. Away from crack tips, interface residuals converge as O(h); near tips, localized post-processing artifacts degrade the global rate, but first-order convergence is recovered when a small tip region is excluded. A multi-crack demonstration with four simultaneously embedded cracks of distinct geometry and interface properties confirms the practical applicability of the framework. These results support the shifted interface method as a practical framework for poroelastic crack modeling on non-body-fitted meshes with geometrically complex embedded interfaces.

cs.CE↗

arXiv2026

Control of Human-Induced Seismicity in Underground Reservoirs Governed by a Nonlinear 3D PDE-ODE System

Induced seismicity caused by fluid extraction or injection in underground reservoirs is a major challenge for safe energy production and storage. This paper presents a robust output-feedback controller for induced seismicity mitigation in geological reservoirs described by a coupled 3D PDE-ODE model. The controller is nonlinear and robust (MIMO Super-Twisting design), producing a continuous control signal and requiring minimal model information, while accommodating parameter uncertainties and spatial heterogeneity. Two operational outputs are regulated simultaneously: regional pressures and seismicity rates computed over reservoir sub-regions. Closed-loop properties are established via explicit bounds on the solution and its time derivative for both the infinite-dimensional dynamics and the nonlinear ODE system, yielding finite-time or exponential convergence of the tracking errors. The method is evaluated on the Groningen gas-field case study in two scenarios: gas production while not exceeding the intrinsic seismicity of the region, and combined production with CO$_2$ injection toward net-zero carbon operation. Simulations demonstrate accurate tracking of pressure and seismicity targets across regions under significant parameter uncertainty, supporting safer reservoir operation while preserving production objectives.

eess.SY↗

arXiv2025

Reinforcement learning-based adaptive time-integration for nonsmooth dynamics

Numerical time integration is fundamental to the simulation of initial and boundary value problems. Traditionally, time integration schemes require adaptive time-stepping to ensure computational speed and sufficient accuracy. Although these methods are based on mathematical derivations related to the order of accuracy for the chosen integrator, they also rely on heuristic development to determine optimal time steps. In this work, we use an alternative approach based on Reinforcement Learning (RL) to select the optimal time step for any time integrator method, balancing computational speed and accuracy. To explore the potential of our RL-based adaptive time-stepping approach, we choose a challenging model problem involving set-valued frictional instabilities at various spatiotemporal scales. This problem demonstrates the robustness of our strategy in handling nonsmooth problems, which present a demanding scenario for numerical integration. Specifically, we apply RL to the simulation of a seismic fault with Coulomb friction. Our findings indicate that RL can learn an optimal strategy for time integration, achieving up to a fourfold speed-up. Our RL-based adaptive integrator offers a new approach for time integration in various other problems in mechanics.

physics.comp-ph↗

arXiv2025

Slip, Differentiate, Observe: State and Parameter Estimation for Rate and State Friction from Noisy Data

Quantifying frictional properties of interfaces remains a major challenge in both terrestrial and extraterrestrial geomechanics, where available samples, laboratory apparatuses, and geophysical observations are inherently limited. We introduce an analytic and numerical framework, grounded in nonlinear control theory, to infer the emergent frictional behavior of seismic faults. From noisy slip measurements, we first reconstruct the slip rate and frictional response in finite time using a Robust Exact Filtering Differentiator (REFD) that attenuates measurement noise. Building on these reconstructions, we design an exponentially convergent adaptive-gain observer that estimates the internal state variable and the key parameters (a - b) and dc of the rate-and-state friction (RSF) law, widely used in fault mechanics. Numerical experiments show that, in fast slip regimes where data are sufficiently rich, the method recovers RSF parameters with errors on the order of 20% and accurately tracks the RSF state variable despite noise contamination, whereas slowly varying sliding periods lack the observability required for reliable estimation. We also establish observability and identifiability conditions for the extended system, enabling the determination of additional parameters and outlining pathways for more advanced control-theoretic approaches to friction and state identification in fault systems. Although we apply the approach to a reduced spring-slider analogue, it improves on classical RSF calibration methods that depend on laboratory access to shear and normal stress. It also offers convergence guarantees and explicit error bounds, and it can further support model-based inversions that embed RSF in forward simulations.

physics.geo-ph↗

arXiv2024

Measurement, self-similarity, and TNT equivalence of blasts from exploding wires

Reduced-scale experiments offer a controlled and safe environment for studying the effects of blasts on structures. Traditionally, these experiments rely on the detonation of solid or gaseous explosive mixtures, with only limited understanding of alternative explosive sources. This paper presents a detailed investigation of the blasts produced by exploding aluminum wires for generating shock waves of controlled energy levels. We meticulously design the experiments to ensure a precise quantification of the underlying uncertainties and conduct comprehensive parametric studies. We draw practical relationships of the blast intensity with respect to the stand-off distance and the stored energy levels. The analysis demonstrates self-similarity of blasts with respect to the conventional concept of the scaled distance, a desirable degree of sphericity of the generated shock waves, and high repeatability. Finally, we quantify the equivalence of the reduced-scale blasts from exploding wires with high explosives, including TNT. The present experimental setup and study demonstrate the high degree of robustness and effectiveness of exploding aluminum wires as a tool for controlled blast generation and reduced-scale structural testing.

physics.class-ph↗

arXiv2024

AI-Driven approach for sustainable extraction of earth's subsurface renewable energy while minimizing seismic activity

Deep Geothermal Energy, Carbon Capture and Storage, and Hydrogen Storage hold considerable promise for meeting the energy sector's large-scale requirements and reducing CO$_2$ emissions. However, the injection of fluids into the Earth's crust, essential for these activities, can induce or trigger earthquakes. In this paper, we highlight a new approach based on Reinforcement Learning for the control of human-induced seismicity in the highly complex environment of an underground reservoir. This complex system poses significant challenges in the control design due to parameter uncertainties and unmodeled dynamics. We show that the reinforcement learning algorithm can interact efficiently with a robust controller, by choosing the controller parameters in real-time, reducing human-induced seismicity and allowing the consideration of further production objectives, \textit{e.g.}, minimal control power. Simulations are presented for a simplified underground reservoir under various energy demand scenarios, demonstrating the reliability and effectiveness of the proposed control-reinforcement learning approach.

cs.LG↗

arXiv2024

A POD-TANN approach for the multiscale modeling of materials and macroelement derivation in geomechanics

This paper introduces a novel approach that combines Proper Orthogonal Decomposition (POD) with Thermodynamics-based Artificial Neural Networks (TANN) to capture the macroscopic behavior of complex inelastic systems and derive macroelements in geomechanics. The methodology leverages POD to extract macroscopic Internal State Variables from microscopic state information, thereby enriching the macroscopic state description used to train an energy potential network within the TANN framework. The thermodynamic consistency provided by TANN, combined with the hierarchical nature of POD, allows to reproduce complex, non-linear inelastic material behaviors as well as macroscopic geomechanical systems responses. The approach is validated through applications of increasing complexity, demonstrating its capability to reproduce high-fidelity simulation data. The applications proposed include the homogenization of continuous inelastic representative unit cells and the derivation of a macroelement for a geotechnical system involving a monopile in a clay layer subjected to horizontal loading. Eventually, the projection operators directly obtained via POD, are exploit to easily reconstruct the microscopic fields. The results indicate that the POD-TANN approach not only offers accuracy in reproducing the studied constitutive responses, but also reduces computational costs, making it a practical tool for the multiscale modeling of heterogeneous inelastic geomechanical systems.

cs.LG↗

arXiv2024

Scaling laws for the rigid-body response of masonry structures under blast loads

The response of masonry structures to explosions can be hardly investigated relying only on numerical and analytical tools. Experimental tests are of paramount importance for improving the current comprehension and validate existing models. However, experiments involving blast scenarios are, at present, partial and limited in number, compared to tests under different dynamic conditions, such as earthquakes. The reason lies on the fact that full-scale blast experiments present many difficulties, mainly due to the nature of the loading action. Experiments in reduced-scale offer instead greater flexibility. Nevertheless, appropriate scaling laws for the response of masonry structures under blast excitations are needed before performing such tests. We propose here new scaling laws for the dynamic, rigid-body response and failure modes of masonry structures under blast loads. This work takes its roots from previous studies, where closed-form solutions for the rocking response of slender blocks due to explosions have been derived and validated against numerical and experimental tests. The proposed scaling laws are here validated with detailed numerical simulations accounting for combined rocking, up-lifting, and sliding mechanisms of monolithic structures. Then, the application to multi-drum stone columns is considered. In particular, we show that, whilst the presence of complex behaviors, such as wobbling and impacts, similarity is assured. The developments demonstrate their applicability in the design of reduced-scale experiments of masonry structures.

math.NA↗

arXiv2024

miniBLAST: a novel experimental setup for laboratory testing of structures under blast loads

We present a novel experimental setup called miniBLAST, which enables systematic and repeatable laboratory tests of structures subjected to blast loads. The explosive source is based on the discharge of high electrical loads on a thin conductor, producing repeatable blast-type shock waves of controlled intensity. Conducting blast experiments under safe laboratory conditions offers significant advantages over large-scale experiments, which are expensive, require specialized personnel, are limited in number, and face repeatability issues. In this work, we provide a comprehensive description of the setup's design rationale and technical characteristics. Moreover, we place particular emphasis on the installation phases, safety, and metrology. The explosive source is analyzed and the signature of blast shock waves is retrieved. Finally, we present an example of a masonry wall subjected to blast loads of varying intensity. We then report its dynamic response in three dimensions and at different time instances. This new experimental setup offers a cost-effective, safe, and repeatable method to study structural dynamics under blast loads, with results that can be upscaled to real structures. It also aids in evaluating numerical models and lays the groundwork for further investigations into blast effects and mitigation.

physics.class-ph↗

arXiv2024

Insights of using Control Theory for minimizing Induced Seismicity in Underground Reservoirs

Deep Geothermal Energy, Carbon Capture, and Storage and Hydrogen Storage have significant potential to meet the large-scale needs of the energy sector and reduce the CO$_2$ emissions. However, the injection of fluids into the earth's crust, upon which these activities rely, can lead to the formation of new seismogenic faults or the reactivation of existing ones, thereby causing earthquakes. In this study, we propose a novel approach based on control theory to address this issue. First, we obtain a simplified model of induced seismicity due to fluid injections in an underground reservoir using a diffusion equation in three dimensions. Then, we design a robust tracking control approach to force the seismicity rate to follow desired references. In this way, the induced seismicity is minimized while ensuring fluid circulation for the needs of renewable energy production and storage. The designed control guarantees the achievement of the control objectives even in the presence of system uncertainties and unknown dynamics. Finally, we present simulations of a simplified geothermal reservoir under different scenarios of energy demand to show the reliability and performance of the control approach, opening new perspectives for field experiments based on real-time regulators.

eess.SY↗

arXiv2023

Passivity-based control of underactuated mechanical systems with Coulomb friction: Application to earthquake prevention

Passivity property gives a sense of energy balance. The classical definitions and theorems of passivity in dynamical systems require time invariance and locally Lipschitz functions. However, these conditions are not met in many systems. A characteristic example is nonautonomous and discontinuous systems due to presence of Coulomb friction. This paper presents an extended result for the negative feedback connection of two passive nonautonomous systems with set-valued right-hand side based on an invariance-like principle. Such extension is the base of a structural passivity-based control synthesis for underactuated mechanical systems with Coulomb friction. The first step consists in designing the control able to restore the passivity in the considered friction law, achieving stabilization of the system trajectories to a domain with zero velocities. Then, an integral action is included to improve the latter result and perform a tracking over a constant reference (regulation). At last, the control is designed considering dynamics in the actuation. These control objectives are obtained using fewer control inputs than degrees of freedom, as a result of the underactuated nature of the plant. The presented control strategy is implemented in an earthquake prevention scenario, where a mature seismogenic fault represents the considered frictional underactuated mechanical system. Simulations are performed to show how the seismic energy can be slowly dissipated by tracking a slow reference, thanks to fluid injection far from the fault, accounting also for the slow dynamics of the fluid's diffusion.

eess.SY↗

arXiv2023

Evolution TANN and the identification of internal variables and evolution equations in solid mechanics

Data-driven and deep learning approaches have demonstrated to have the potential of replacing classical constitutive models for complex materials. Yet, the necessity of structuring constitutive models with an incremental formulation has given rise to data-driven approaches where physical quantities, e.g. deformation, blend with artificial, non-physical ones, such as the increments in deformation and time. Neural networks and the consequent constitutive models depend, thus, on the particular incremental formulation, fail in identifying material representations locally in time, and suffer from poor generalization. Herein, we propose a new approach which allows, for the first time, to decouple the material representation from the incremental formulation. Inspired by the Thermodynamics-based Artificial Neural Networks (TANN) and the theory of the internal variables, the evolution TANN (eTANN) are continuous-time and, therefore, independent of the aforementioned artificial quantities. Key feature of the proposed approach is the identification of the evolution equations of the internal variables in the form of ordinary differential equations, rather than in an incremental discrete-time form. In this work, we focus attention to juxtapose and show how the various general notions of solid mechanics are implemented in eTANN. The capabilities as well as the scalability of the proposed approach are demonstrated through several applications involving a broad spectrum of complex material behaviors, from plasticity to damage and viscosity (and combination of them). Finally, we show that the proposed approach can be used to speed-up multiscale analyses, by virtue of asymptotic homogenization. eTANN provide excellent results compared to detailed fine-scale simulations and offer the possibility not only to describe the average macroscopic material behavior, but also micromechanical, complex mechanisms.

cs.CE↗

arXiv2023

Earthquake Control: An Emerging Application for Robust Control. Theory and Experimental Tests

This paper addresses the possibility of using robust control theory for preventing earthquakes through fluid injections in the earth's crust. The designed robust controllers drive aseismically a fault system to a new equilibrium point of lower energy by tracking a slow reference signal. The control design is based on a reduced-order nonlinear model able to reproduce earthquake-like instabilities. Uncertainties related to the frictional and mechanical properties of the underlying physical process and external perturbations are considered. Two types of controllers are derived. The first one is based on sliding-mode theory and leads to local finite-time convergence of the tracking error and rejection of Lipschitz w.r.t. time perturbations. The second controller is based on LQR control and presents global exponential stability of the tracking error and rejection of Lipschitz w.r.t. states perturbations. Both controllers generate a continuous control signal, attenuating the chattering effect in the case of the sliding-mode algorithms. The developed controllers are tested extensively and compared on the basis of numerical simulations and experiments in the laboratory. The present work opens new perspectives for the application of robust nonlinear control theory to complex geosystems, earthquakes and sustainable energy production.

math.OC↗

arXiv2022

Multiscale modeling of inelastic materials with Thermodynamics-based Artificial Neural Networks (TANN)

The mechanical behavior of inelastic materials with microstructure is very complex and hard to grasp with heuristic, empirical constitutive models. For this purpose, multiscale, homogenization approaches are often used for performing reliable, accurate predictions of the macroscopic mechanical behavior of solids and structures. Nevertheless, the calculation cost of such approaches is extremely high and prohibitive for real-scale applications involving inelastic materials. Here, we propose the so-called Thermodynamics-based Artificial Neural Networks (TANN) for the constitutive modeling of materials with inelastic and complex microstructure. Our approach integrates thermodynamics-aware dimensionality reduction techniques and thermodynamics-based deep neural networks to identify, in an autonomous way, the constitutive laws and discover the internal state variables of complex inelastic materials. The efficiency and accuracy of TANN in predicting the average and local stress-strain response, the free-energy and the dissipation rate is demonstrated for both regular and perturbed two- and three-dimensional lattice microstructures in inelasticity. TANN manage to identify the internal state variables that characterize the inelastic deformation of the complex microstructural fields. These internal state variables are then used to reconstruct the microdeformation fields of the microstructure at a given state. Finally, a double-scale homogenization scheme (FEMxTANN) is used to solve a large scale boundary value problem. The high performance of the homogenized model using TANN is illustrated through detailed comparisons with microstructural calculations at large scale. An excellent agreement is shown for a variety of monotonous and cyclic stress-strain paths.

cond-mat.mtrl-sci↗

arXiv2022

Fault friction under thermal pressurization during large coseismic-slip Part I: Numerical analyses

In this paper, we study the role of thermal pressurization in the frictional response of a fault under large coseismic slip. We investigate the role of the seismic slip velocity, mixture compressibility, characteristic grain size and viscosity parameter in the frictional response of the coupled thermo-hydro-mechanical problem, taking into account the fault's microstructure. Starting from the mass, energy and momentum balance for Cosserat continua we derive the equations of our model. We complete the mathematical description using perfect plasticity and Perzyna viscoplasticity in the material constitutive behavior. We investigate both the rate independent as well as the rate dependent frictional response and compare with existing models found in literature, namely the rate and state friction law (Dieterich (1992),Ruina(1983a)). We show that our model is capable of predicting strain rate hardening and velocity softening without the assumption of a state variable. We observe traveling instabilities inside the layer that lead to oscillations in the fault's frictional response, like in the case of Portevin Le Chatelier (PLC) effect. This behavior is not captured by existing numerical analyses presented in Rattez et al. (2018c,b,a) and go beyond the established models of uniform shear (Lachenbruch (1980)) and shear on a mathematical plane (Rice (2006a)), which predict a strictly monotonous behavior during shearing. Recent experimental analyses, which have managed to insulate thermal pressurization from other weakening mechanisms (Badt et al. (2020)), corroborate our numerical results.

physics.geo-ph↗

arXiv2022

Fault friction under thermal pressurization during large coseismic-slip Part II: Expansion to the model of frictional slip

In Stathas and Stefanou (2022) we presented the frictional response of a bounded fault gouge under largecoseismic slip. We did so by taking into account the evolution of the Principal Slip Zone (PSZ) thickness using a Cosserat micromorphic continuum model for the description of the fault's mechanical response. The numerical results obtained differ significantly from those predicted by the established model of thermal pressurization during slip on a mathematical plane (see Mase and Smith (1987); Rice (2006a); Platt et al. (2014a) among others). These differences prompt us to reconsider the basic assumptions of a stationary strain localization on an unbounded domain present in the original model. We depart from these assumptions, extending the model to incorporate different strain localization modes, temperature and pore fluid pressure boundary conditions. The new model allows us to gain significant understanding of the detailed numerical results of Part I. We investigate the influence of a traveling strain localization inside the fault gouge considering isothermal, drained boundary conditions for the bounded and unbounded domain respectively. Our results establish that when a stationary strain localization profile is applied on a bounded domain, the boundary conditions lead to a steady state, where total strength regain is achieved. In the case of a traveling instability such a steady state is not possible and the fault only regains part of its frictional strength, depending on the seismic slip velocity and the traveling velocity of the shear band. In this case frictional oscillations increasing the frequency content of the earthquake are also developed. Our results indicate a reappraisal of the role of thermal pressurization as a frictional weakening mechanism.

physics.geo-ph↗