## Fraunhofer (ITWM)

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#### Fachbereich / Organisatorische Einheit

- Fraunhofer (ITWM) (222)
- Fachbereich Mathematik (2)

#### Erscheinungsjahr

#### Dokumenttyp

- Bericht (198)
- Preprint (19)
- Dissertation (4)
- Arbeitspapier (1)

#### Schlagworte

- numerical upscaling (6)
- Darcy’s law (3)
- effective heat conductivity (3)
- facility location (3)
- non-Newtonian flow in porous media (3)
- poroelasticity (3)
- virtual material design (3)
- American options (2)
- Bartlett spectrum (2)
- HJB equation (2)

- Simulation of Degradation Processes in Lithium-Ion Batteries (2015)
- Lithium-ion batteries are increasingly becoming an ubiquitous part of our everyday life - they are present in mobile phones, laptops, tools, cars, etc. However, there are still many concerns about their longevity and their safety. In this work we focus on the simulation of several degradation mechanisms on the microscopic scale, where one can resolve the active materials inside the electrodes of the lithium-ion batteries as porous structures. We mainly study two aspects - heat generation and mechanical stress. For the former we consider an electrochemical non-isothermal model on the spatially resolved porous scale to observe the temperature increase inside a battery cell, as well as to observe the individual heat sources to assess their contributions to the total heat generation. As a result from our experiments, we determined that the temperature has very small spatial variance for our test cases and thus allows for an ODE formulation of the heat equation. The second aspect that we consider is the generation of mechanical stress as a result of the insertion of lithium ions in the electrode materials. We study two approaches - using small strain models and finite strain models. For the small strain models, the initial geometry and the current geometry coincide. The model considers a diffusion equation for the lithium ions and equilibrium equation for the mechanical stress. First, we test a single perforated cylindrical particle using different boundary conditions for the displacement and with Neumann boundary conditions for the diffusion equation. We also test for cylindrical particles, but with boundary conditions for the diffusion equation in the electrodes coming from an isothermal electrochemical model for the whole battery cell. For the finite strain models we take in consideration the deformation of the initial geometry as a result of the intercalation and the mechanical stress. We compare two elastic models to study the sensitivity of the predicted elastic behavior on the specific model used. We also consider a softening of the active material dependent on the concentration of the lithium ions and using data for silicon electrodes. We recover the general behavior of the stress from known physical experiments. Some models, like the mechanical models we use, depend on the local values of the concentration to predict the mechanical stress. In that sense we perform a short comparative study between the Finite Element Method with tetrahedral elements and the Finite Volume Method with voxel volumes for an isothermal electrochemical model. The spatial discretizations of the PDEs are done using the Finite Element Method. For some models we have discontinuous quantities where we adapt the FEM accordingly. The time derivatives are discretized using the implicit Backward Euler method. The nonlinear systems are linearized using the Newton method. All of the discretized models are implemented in a C++ framework developed during the thesis.

- Upscaling Approaches for Nonlinear Processes in Lithium-Ion Batteries (2015)
- Lithium-ion batteries are broadly used nowadays in all kinds of portable electronics, such as laptops, cell phones, tablets, e-book readers, digital cameras, etc. They are preferred to other types of rechargeable batteries due to their superior characteristics, such as light weight and high energy density, no memory effect, and a big number of charge/discharge cycles. The high demand and applicability of Li-ion batteries naturally give rise to the unceasing necessity of developing better batteries in terms of performance and lifetime. The aim of the mathematical modelling of Li-ion batteries is to help engineers test different battery configurations and electrode materials faster and cheaper. Lithium-ion batteries are multiscale systems. A typical Li-ion battery consists of multiple connected electrochemical battery cells. Each cell has two electrodes - anode and cathode, as well as a separator between them that prevents a short circuit. Both electrodes have porous structure composed of two phases - solid and electrolyte. We call macroscale the lengthscale of the whole electrode and microscale - the lengthscale at which we can distinguish the complex porous structure of the electrodes. We start from a Li-ion battery model derived on the microscale. The model is based on nonlinear diffusion type of equations for the transport of Lithium ions and charges in the electrolyte and in the active material. Electrochemical reactions on the solid-electrolyte interface couple the two phases. The interface kinetics is modelled by the highly nonlinear Butler-Volmer interface conditions. Direct numerical simulations with standard methods, such as the Finite Element Method or Finite Volume Method, lead to ill-conditioned problems with a huge number of degrees of freedom which are difficult to solve. Therefore, the aim of this work is to derive upscaled models on the lengthscale of the whole electrode so that we do not have to resolve all the small-scale features of the porous microstructure thus reducing the computational time and cost. We do this by applying two different upscaling techniques - the Asymptotic Homogenization Method and the Multiscale Finite Element Method (MsFEM). We consider the electrolyte and the solid as two self-complementary perforated domains and we exploit this idea with both upscaling methods. The first method is restricted only to periodic media and periodically oscillating solutions while the second method can be applied to randomly oscillating solutions and is based on the Finite Element Method framework. We apply the Asymptotic Homogenization Method to derive a coupled macro-micro upscaled model under the assumption of periodic electrode microstructure. A crucial step in the homogenization procedure is the upscaling of the Butler-Volmer interface conditions. We rigorously determine the asymptotic order of the interface exchange current densities and we perform a comprehensive numerical study in order to validate the derived homogenized Li-ion battery model. In order to upscale the microscale battery problem in the case of random electrode microstructure we apply the MsFEM, extended to problems in perforated domains with Neumann boundary conditions on the holes. We conduct a detailed numerical investigation of the proposed algorithm and we show numerical convergence of the method that we design. We also apply the developed technique to a simplified two-dimensional Li-ion battery problem and we show numerical convergence of the solution obtained with the MsFEM to the reference microscale one.

- Image based characterization and geometric modeling of 3d materials microstructures (2015)
- It is well known that the structure at a microscopic point of view strongly influences the macroscopic properties of materials. Moreover, the advancement in imaging technologies allows to capture the complexity of the structures at always decreasing scales. Therefore, more sophisticated image analysis techniques are needed. This thesis provides tools to geometrically characterize different types of three-dimensional structures with applications to industrial production and to materials science. Our goal is to enhance methods that allow the extraction of geometric features from images and the automatic processing of the information. In particular, we investigate which characteristics are sufficient and necessary to infer the desired information, such as particles classification for technical cleanliness and fitting of stochastic models in materials science. In the production line of automotive industry, dirt particles collect on the surface of mechanical components. Residual dirt might reduce the performance and durability of assembled products. Geometric characterization of these particles allows to identify their potential danger. While the current standards are based on 2d microscopic images, we extend the characterization to 3d. In particular, we provide a collection of parameters that exhaustively describe size and shape of three-dimensional objects and can be efficiently estimated from binary images. Furthermore, we show that only a few features are sufficient to classify particles according to the standards of technical cleanliness. In the context of materials science, we consider two types of microstructures: fiber systems and foams. Stochastic geometry grants the fundamentals for versatile models able to encompass the geometry observed in the samples. To allow automatic model fitting, we need rules stating which parameters of the model yield the best-fitting characteristics. However, the validity of such rules strongly depends on the properties of the structures and on the choice of the model. For instance, isotropic orientation distribution yields the best theoretical results for Boolean models and Poisson processes of cylinders with circular cross sections. Nevertheless, fiber systems in composites are often anisotropic. Starting from analytical results from the literature, we derive formulae for anisotropic Poisson processes of cylinders with polygonal cross sections that can be directly used in applications. We apply this procedure to a sample of medium density fiber board. Even if image resolution does not allow to estimate reliably characteristics of the singles fibers, we can fit Boolean models and Poisson cylinder processes. In particular, we show the complete model fitting and validation procedure with cylinders with circular and squared cross sections. Different problems arise when modeling cellular materials. Motivated by the physics of foams, random Laguerre tessellations are a good choice to model the pore system of foams. Considering tessellations generated by systems of non-overlapping spheres allows to control the cell size distribution, but yields the loss of an analytical description of the model. Nevertheless, automatic model fitting can still be obtained by approximating the characteristics of the tessellation depending on the parameters of the model. We investigate how to improve the choice of the model parameters. Angles between facets and between edges were never considered so far. We show that the distributions of angles in Laguerre tessellations depend on the model parameters. Thus, including the moments of the angles still allows automatic model fitting. Moreover, we propose an algorithm to estimate angles from images of real foams. We observe that angles are matched well in random Laguerre tessellations also when they are not employed to choose the model parameters. Then, we concentrate on the edge length distribution. In Laguerre tessellations occur many more short edges than in real foams. To deal with this problem, we consider relaxed models. Relaxation refers to topological and structural modifications of a tessellation in order to make it comply with Plateau's laws of mechanical equilibrium. We inspect samples of different types of foams, closed and open cell foams, polymeric and metallic. By comparing the geometric characteristics of the model and of the relaxed tessellations, we conclude that whether the relaxation improves the edge length distribution strongly depends on the type of foam.

- Test rig optimization (2014)
- Designing good test rigs for fatigue life tests is a common task in the auto- motive industry. The problem to find an optimal test rig configuration and actuator load signals can be formulated as a mathematical program. We in- troduce a new optimization model that includes multi-criteria, discrete and continuous aspects. At the same time we manage to avoid the necessity to deal with the rainflow-counting (RFC) method. RFC is an algorithm, which extracts load cycles from an irregular time signal. As a mathematical func- tion it is non-convex and non-differentiable and, hence, makes optimization of the test rig intractable. The block structure of the load signals is assumed from the beginning. It highly reduces complexity of the problem without decreasing the feasible set. Also, we optimize with respect to the actuators’ positions, which makes it possible to take torques into account and thus extend the feasible set. As a result, the new model gives significantly better results, compared with the other approaches in the test rig optimization. Under certain conditions, the non-convex test rig problem is a union of convex problems on cones. Numerical methods for optimization usually need constraints and a starting point. We describe an algorithm that detects each cone and its interior point in a polynomial time. The test rig problem belongs to the class of bilevel programs. For every instance of the state vector, the sum of functions has to be maximized. We propose a new branch and bound technique that uses local maxima of every summand.

- Residual Demand Modeling and Application to Electricity Pricing (2012)
- Worldwide the installed capacity of renewable technologies for electricity production is rising tremendously. The German market is particularly progressive and its regulatory rules imply that production from renewables is decoupled from market prices and electricity demand. Conventional generation technologies are to cover the residual demand (defined as total demand minus production from renewables) but set the price at the exchange. Existing electricity price models do not account for the new risks introduced by the volatile production of renewables and their effects on the conventional demand curve. A model for residual demand is proposed, which is used as an extension of supply/demand electricity price models to account for renewable infeed in the market. Infeed from wind and solar (photovoltaics) is modeled explicitly and withdrawn from total demand. The methodology separates the impact of weather and capacity. Efficiency is transformed on the real line using the logit-transformation and modeled as a stochastic process. Installed capacity is assumed a deterministic function of time. In a case study the residual demand model is applied to the German day-ahead market using a supply/demand model with a deterministic supply-side representation. Price trajectories are simulated and the results are compared to market future and option prices. The trajectories show typical features seen in market prices in recent years and the model is able to closely reproduce the structure and magnitude of market prices. Using the simulated prices it is found that renewable infeed increases the volatility of forward prices in times of low demand, but can reduce volatility in peak hours. Prices for different scenarios of installed wind and solar capacity are compared and the meritorder effect of increased wind and solar capacity is calculated. It is found that wind has a stronger overall effect than solar, but both are even in peak hours.

- Integration of nonlinear models of flexible body deformation in Multibody System Dynamics (2012)
- A simple transformation of the Equation of Motion (EoM) allows us to directly integrate nonlinear structural models into the recursive Multibody System (MBS) formalism of SIMPACK. This contribution describes how the integration is performed for a discrete Cosserat rod model which has been developed at the ITWM. As a practical example, the run-up of a simplified three-bladed wind turbine is studied where the dynamic deformations of the three blades are calculated by the Cosserat rod model.

- Constitutive models for static granular systems and focus to the Jiang-Liu hyperelastic law (2012)
- Granular systems in solid-like state exhibit properties like stiffness dependence on stress, dilatancy, yield or incremental non-linearity that can be described within the continuum mechanical framework. Different constitutive models have been proposed in the literature either based on relations between some components of the stress tensor or on a quasi-elastic description. After a brief description of these models, the hyperelastic law recently proposed by Jiang and Liu [1] will be investigated. In this framework, the stress-strain relation is derived from an elastic strain energy density where the stable proper- ties are linked to a Drucker-Prager yield criteria. Further, a numerical method based on the finite element discretization and Newton- Raphson iterations is presented to solve the force balance equation. The 2D numerical examples presented in this work show that the stress distributions can be computed not only for triangular domains, as previoulsy done in the literature, but also for more complex geometries. If the slope of the heap is greater than a critical value, numerical instabilities appear and no elastic solution can be found, as predicted by the theory. As main result, the dependence of the material parameter Xi on the maximum angle of repose is established.

- Construction of discrete shell models by geometric finite differences (2012)
- In the presented work, we make use of the strong reciprocity between kinematics and geometry to build a geometrically nonlinear, shearable low order discrete shell model of Cosserat type defined on triangular meshes, from which we deduce a rotation–free Kirchhoff type model with the triangle vertex positions as degrees of freedom. Both models behave physically plausible already on very coarse meshes, and show good convergence properties on regular meshes. Moreover, from the theoretical side, this deduction provides a common geometric framework for several existing models.

- Geometrically exact Cosserat rods with Kelvin-Voigt type viscous damping (2012)
- We present the derivation of a simple viscous damping model of Kelvin–Voigt type for geometrically exact Cosserat rods from three–dimensional continuum theory. Assuming a homogeneous and isotropic material, we obtain explicit formulas for the damping parameters of the model in terms of the well known stiffness parameters of the rod and the retardation time constants defined as the ratios of bulk and shear viscosities to the respective elastic moduli. We briefly discuss the range of validity of our damping model and illustrate its behaviour with a numerical example.

- Multi-level Monte Carlo methods using ensemble level mixed MsFEM for two-phase flow and transport simulations (2012)
- In this paper, we propose multi-level Monte Carlo(MLMC) methods that use ensemble level mixed multiscale methods in the simulations of multi-phase flow and transport. The main idea of ensemble level multiscale methods is to construct local multiscale basis functions that can be used for any member of the ensemble. We consider two types of ensemble level mixed multiscale finite element methods, (1) the no-local-solve-online ensemble level method (NLSO) and (2) the local-solve-online ensemble level method (LSO). Both mixed multiscale methods use a number of snapshots of the permeability media to generate a multiscale basis. As a result, in the offline stage, we construct multiple basis functions for each coarse region where basis functions correspond to different realizations. In the no-local-solve-online ensemble level method one uses the whole set of pre-computed basis functions to approximate the solution for an arbitrary realization. In the local-solve-online ensemble level method one uses the pre-computed functions to construct a multiscale basis for a particular realization. With this basis the solution corresponding to this particular realization is approximated in LSO mixed MsFEM. In both approaches the accuracy of the method is related to the number of snapshots computed based on different realizations that one uses to pre-compute a multiscale basis. We note that LSO approaches share similarities with reduced basis methods [11, 21, 22]. In multi-level Monte Carlo methods ([14, 13]), more accurate (and expensive) forward simulations are run with fewer samples while less accurate(and inexpensive) forward simulations are run with a larger number of samples. Selecting the number of expensive and inexpensive simulations carefully, one can show that MLMC methods can provide better accuracy at the same cost as MC methods. In our simulations, our goal is twofold. First, we would like to compare NLSO and LSO mixed MsFEMs. In particular, we show that NLSO mixed MsFEM is more accurate compared to LSO mixed MsFEM. Further, we use both approaches in the context of MLMC to speed-up MC calculations. We present basic aspects of the algorithm and numerical results for coupled flow and transport in heterogeneous porous media.