06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7
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Item Open Access Modeling freezing and BioGeoChemical processes in Antarctic sea ice(2024) Pathak, Raghav; Seyedpour, Seyed Morteza; Kutschan, Bernd; Thom, Andrea; Thoms, Silke; Ricken, TimThe Antarctic sea ice, which undergoes annual freezing and melting, plays a significant role in the global climate cycle. Since satellite observations in the Antarctic region began, 2023 saw a historically unprecedented decrease in the extent of sea ice. Further ocean warming and future environmental conditions in the Southern Ocean will influence the extent and amount of ice in the Marginal Ice Zones (MIZ), the BioGeoChemical (BGC) cycles, and their interconnected relationships. The so‐called pancake floes are a composition of a porous sea ice matrix with interstitial brine, nutrients, and biological communities inside the pores. The ice formation and salinity are both dependent on the ambient temperature. To realistically model these multiphasic and multicomponent coupled processes, the extended Theory of Porous Media (eTPM) is used to develop Partial Differential Equations (PDEs) based high‐fidelity models capable of simulating the different seasonal variations in the region. All critical variables like salinity, ice volume fraction, and temperature, among others, are considered and have their equations of state. The phase transition phenomenon is approached through a micro‐macro linking scheme. In this paper, a phase‐field solidification model [4] coupled with salinity is used to model the microscale freezing processes and up‐scaled to the macroscale eTPM model. The evolution equations for the phase field model are derived following Landau‐Ginzburg order parameter gradient dynamics and mass conservation of salt allowing to model the salt trapped inside the pores. A BGC flux model for sea ice is set up to simulate the algal species present in the sea ice matrix. Ordinary differential equations (ODE) are employed to represent the diverse environmental factors involved in the growth and loss of distinct BGC components. Processes like photosynthesis are dependent on temperature and salinity, which are derived through an ODE‐PDE coupling with the eTPM model. Academic simulations and results are presented as validation for the mathematical model. These high‐fidelity models eventually lead to their incorporation into large‐scale global climate models.Item Open Access Optimization of the groundwater remediation process using a coupled genetic algorithm-finite difference method(2021) Seyedpour, Seyed Morteza; Valizadeh, Iman; Kirmizakis, Panagiotis; Doherty, Rory; Ricken, TimIn situ chemical oxidation using permanganate as an oxidant is a remediation technique often used to treat contaminated groundwater. In this paper, groundwater flow with a full hydraulic conductivity tensor and remediation process through in situ chemical oxidation are simulated. The numerical approach was verified with a physical sandbox experiment and analytical solution for 2D advection-diffusion with a first-order decay rate constant. The numerical results were in good agreement with the results of physical sandbox model and the analytical solution. The developed model was applied to two different studies, using multi-objective genetic algorithm to optimise remediation design. In order to reach the optimised design, three objectives considering three constraints were defined. The time to reach the desired concentration and remediation cost regarding the number of required oxidant sources in the optimised design was less than any arbitrary design.Item Open Access Transient high-frequency spherical wave propagation in porous medium using fractional calculus technique(2023) Soltani, Kamran; Seyedpour, Seyed Morteza; Ricken, Tim; Rezazadeh, GhaderTransient high-frequency spherical wave propagation in the porous medium is studied using the Biot-JKD theory. The porous media is considered to be a composed of deformable solid skeleton and viscous incompressible fluid inside the pores. In order to treat the fractional proportionality of the dynamic tortuosity to the frequency (or equivalently, to time) due to the viscous interaction between solid and fluid phases, the fractional calculus theory along with the Laplace and Fourier transforms are used to solve the coupled governing partial differential equations of the scaler and vector potential functions obtained from the Helmholtz’s decomposition in the Laplace domain. Both the longitudinal and transverse waves, additionally the reflection and transmission kernels are determined in detail at the Laplace domain. For the Laplace-to-time inversion transform, Durbin’s numerical formula is used and the independence of the results from the involved tuning and accuracy parameters is checked. The effects of the porosity, dynamic tortuosity, characteristics length, etc. on the reflected pressure and stress are investigated. The general pattern of the results is similar to our previous knowledge of wave propagation. Further works and experiments may be conducted in future works for various applications.Item Open Access The effect of Caspian Sea water on mechanical properties and durability of concrete containing rice husk ash, nano SiO2, and nano Al2O3(2022) Arasteh-Khoshbin, Omolbanin; Seyedpour, Seyed Morteza; Ricken, TimVarious studies have been recently conducted aiming at developing more sustainable cementitious systems so that concrete structures may not have a negative effect on the environment and are decomposed. It has been attempted to build sustainable binders by substituting silica fume, cement with fly ash, nano-silica, nano-alumina, and rice husk ash. In this paper, a series of experiments on concrete with different contents of rice husk ash (10%, 15%, and 20%), nano SiO2(1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%), and nano Al2O3(1%, 2%, 3%, 4%) are performed to analyze the durability and mechanical properties of samples under the curing condition of Caspian seawater. The workability, density, water penetration, chloride ion penetration, and compressive strength (at 7, 14, 28, and 90 day) of the samples were determined. The experimental results showed that workability decreased gradually with increasing additives content, while the compressive gradually increased. Among the additives, adding 8% of the nano SiO2had the most significant effect on the improvement of compressive strength. Adding 8% nano SiO2and 4% nano Al2O3 reduced the depth of water permeability by 53% and 30%, respectively. Furthermore, adding 8% nanoSiO2 reduced chloride ion penetration by 85%.Item Open Access Affine transformations accelerate the training of physics-informed neural networks of a one-dimensional consolidation problem(2023) Mandl, Luis; Mielke, André; Seyedpour, Seyed Morteza; Ricken, TimPhysics-informed neural networks (PINNs) leverage data and knowledge about a problem. They provide a nonnumerical pathway to solving partial differential equations by expressing the field solution as an artificial neural network. This approach has been applied successfully to various types of differential equations. A major area of research on PINNs is the application to coupled partial differential equations in particular, and a general breakthrough is still lacking. In coupled equations, the optimization operates in a critical conflict between boundary conditions and the underlying equations, which often requires either many iterations or complex schemes to avoid trivial solutions and to achieve convergence. We provide empirical evidence for the mitigation of bad initial conditioning in PINNs for solving one-dimensional consolidation problems of porous media through the introduction of affine transformations after the classical output layer of artificial neural network architectures, effectively accelerating the training process. These affine physics-informed neural networks (AfPINNs) then produce nontrivial and accurate field solutions even in parameter spaces with diverging orders of magnitude. On average, AfPINNs show the ability to improve the L2relative error by 64.84%after 25,000 epochs for a one-dimensional consolidation problem based on Biot’s theory, and an average improvement by 58.80%with a transfer approach to the theory of porous media.Item Open Access Uncertainty with varying subsurface permeabilities reduced using coupled Random Field and extended Theory of Porous Media contaminant transport models(2022) Seyedpour, Seyed Morteza; Henning, Carla; Kirmizakis, Panagiotis; Herbrandt, Swetlana; Ickstadt, Katja; Doherty, Rory; Ricken, TimTo maximize the usefulness of groundwater flow models for the protection of aquifers and abstraction wells, it is necessary to identify and decrease the uncertainty associated with the major parameters such as permeability. To do this, there is a need to develop set of estimates representing subsurface heterogeneity or representative soil permeability estimates. Here, we use a coupled Random Field and extended Theory of Porous Media (eTPM) simulation to develop a robust model with a good predictive ability that reduces uncertainty. The coupled model is then validated with a physical sandbox experiment. Uncertainty is reduced by using 500 realisations of the permeability parameter using the eTPM approach. A multi-layer contaminant transport scenario with varying permeabilities, similar to what could be expected with shallow alluvial sediments, is simulated. The results show that the contaminant arrival time could be strongly affected by random field realizations of permeability compared with a modelled homogenous permeability parameter. The breakthrough time for heterogeneous permeabilities is shorter than the homogeneous condition. Using the 75% confidence interval (CI), the average contaminant concentration shows 4.4% variation from the average values of the considered area and 8.9% variation in the case of a 95% confidence interval.Item Open Access Phase transition in porous materials : effects of material parameters and deformation regime on mass conservativity(2024) Brodbeck, Maximilian; Suditsch, Marlon; Seyedpour, Seyed Morteza; Ricken, TimPhase transition in porous materials is relevant within different engineering applications, such as freezing in saturated soil or pancake sea ice. Mathematical descriptions of such processes can be derived based on Biot’s consolidation theory or the Theory of Porous Media. Depending on parameters such as density ratio, permeability or compressibility of the solid matrix, either small or finite deformations occur. Numerical solution procedures for the general, finite deformation case, suffers from instabilities and high computational costs. Simplifications, assuming small deformations, increases stability and computational efficiency. Within this work shortcomings of simplified theories based on Biot and linearisations of the Theory of Porous Media (TPM) are systematically studied. In order to determine the interaction of the different model parameters a non-dimensional model for poro-elasticity is presented. Based on a characteristic test-case including phase-transition and consolidation, the simplified models are compared to the fully non-linear TPM, focusing on mass errors as well as the time behaviour of the solution. Taking further into account the efficiency of discretisation based on different primal variables and finite-element-spaces, a guideline for selecting an appropriate combination of model, kinematic assumption and discretisation scheme is presented.Item Open Access On effects of freezing and thawing cycles of concrete containing nano-SiO2 : experimental study of material properties and crack simulation(2023) Arasteh-Khoshbin, Omolbanin; Seyedpour, Seyed Morteza; Brodbeck, Maximilian; Lambers, Lena; Ricken, TimConstruction during cold weather can lead to freezing accidents in concrete, causing significant hidden threats to the project’s performance and safety by affecting the mechanical properties and durability reduction. This study aims to deduce the compressive strength and durability of the concrete containing nano- SiO2under freezing-thawing cycles with the Caspian seawater curing condition. The specimens were subjected to freezing-thawing cycles according to ASTM C666. Furthermore, crack propagation in the concrete after freezing-thawing cycles is simulated. The results reveal that adding until nano- SiO2until 6% improved compressive strength before and after freezing-thaw cycles. The water permeability experiences a substantial reduction as the amount of nano- SiO2increases. Furthermore, the water permeability exhibits a positive correlation with the number of cycles, resulting in significantly higher values after 150 cycles compared to the initial sample. Moreover, adding 8% nano- SiO2reduced the depth of water permeability and chloride ion penetration after 150 cycles by 57% and 86%, respectively. The crack simulation results indicate that concrete containing 6% nano- SiO2shows an optimal resistance against crack formation. Concrete with 6% nano- SiO2requires 13.88% less force for crack initialization after 150 freezing and thawing cycles. Among different nano- SiO2percentages, 6% shows the best crack resistance and 8% the minimum water permeability and chloride ion penetration.Item Open Access Simulation of contaminant transport through the vadose zone : a continuum mechanical approach within the framework of the extended Theory of Porous Media (eTPM)(2023) Seyedpour, Seyed Morteza; Thom, Andrea; Ricken, TimThe simulation of contaminant transport through the vadose zone enjoys high significance for decision makers and contaminated site planners since the vadose zone can serve as a filter, but many contaminants can be transported from this region to aquifers. The intention of this paper is to utilize the extended Theory of Porous Media (eTPM) to develop a ternary model for the simulation of contaminant transport in the vadose zone whose application is subsequently shown via a numerical example. The simulation was conducted for 140 days, during which the contamination source was removed after 25 days. The results indicate that the contaminant reached the water table after 76 days. The concentration of the contaminant reaching the groundwater was 17% less than that of the contaminant source.Item Open Access Comparing durability and compressive strength predictions of hyperoptimized random forests and artificial neural networks on a small dataset of concrete containing nano SiO2 and RHA(2024) Arasteh-Khoshbin, Omolbanin; Seyedpour, Seyed Morteza; Mandl, Luis; Lambers, Lena; Ricken, Tim