52 Maschinenbau, Energietechnik, Fertigungstechnik
Refine
Document Type
- Doctoral Thesis (14)
- Article (3)
Institute
Keywords
- Finite-Elemente-Methode (4)
- Isogeometric Analysis (3)
- Batterie (2)
- Machine learning (2)
- Maschinelles Lernen (2)
- Optimierung (2)
- Phasenfeldmodell (2)
- Strukturdynamik (2)
- Abaqus (1)
- Akkumulator (1)
- Auswirkung (1)
- Battery (1)
- Battery development (1)
- Berechnung (1)
- Continuum Mechnics (1)
- Electrochemical properties (1)
- Elektrochemische Eigenschaft (1)
- Elektrode (1)
- Elektrodenmaterial (1)
- Energiespeichersystem (1)
- Energiewirtschaft (1)
- Erdbeben (1)
- Fiber Reinforced Composite (1)
- Finite Element Method (1)
- Finite Element Model (1)
- Flexoelectricity (1)
- Fracture (1)
- Geometric Partial Differential Equations (1)
- Grauguss (1)
- Hydrodynamik (1)
- Impact (1)
- Inverse problems (1)
- Isogeometrische Analyse (1)
- Lebensdauerabschätzung (1)
- Maschinenbau (1)
- Mechanical properties (1)
- Mechanische Eigenschaft (1)
- Modellbildung (1)
- Modellierung (1)
- Molecular Dynamics Simulation (1)
- Molekulardynamik (1)
- Multi-scale modeling (1)
- Multiphysics (1)
- Nachhaltigkeit (1)
- Nachhaltigkeitsbewertung (1)
- Nanomaterial (1)
- Nanostructures (1)
- Nanostrukturiertes Material (1)
- Neuronales Netz (1)
- Numerische Berechnung (1)
- OA-Publikationsfonds2018 (1)
- Optimization (1)
- Optimization problems (1)
- PDEs (1)
- Peridynamik (1)
- Phase field model (1)
- Phase-field modeling (1)
- Physics informed neural network (1)
- Piezoelectricity (1)
- Polymer compound (1)
- Polymerverbindung (1)
- Primärenergie (1)
- Primärenergiefaktor (1)
- Residual-based variational multiscale method (1)
- Risikomanagement (1)
- Schwingung (1)
- Schwingungsanalyse (1)
- Simulation (1)
- Simulationsprozess (1)
- Sprödbruch (1)
- Strukturmechanik (1)
- Strömungsmechanik (1)
- Surface effects (1)
- Thermoelastic damping (1)
- Umweltleistung (1)
- Variational principle (1)
- Vesicle dynamics (1)
- Vesikel (1)
- Wechselwirkung (1)
- Werkstoffdämpfung (1)
- Werkstoffprüfung (1)
- Wärmebedarf (1)
- XFEM (1)
- brittle fracture (1)
- buildings (1)
- decay experiments (1)
- deep neural network (1)
- demand response programs (1)
- earthquake (1)
- earthquake safety assessment (1)
- energy dissipation (1)
- erneuerbare Energie (1)
- extreme events (1)
- extreme pressure (1)
- forward contracts (1)
- gradient elasticity (1)
- hydraulic jump (1)
- level set method (1)
- mathematical modeling (1)
- mitigation (1)
- modal damping (1)
- natural hazard (1)
- numerical methods (1)
- phase field (1)
- phase field fracture method (1)
- rapid visual screening (1)
- retailer (1)
- risk management (1)
- seismic assessment (1)
- smoothed particle hydrodynamics (1)
- standard deviation of pressure fluctuations (1)
- statistical coeffcient of the probability distribution (1)
- stilling basin (1)
- stochastic programming (1)
- weighted residual method (1)
- Ökobilanz (1)
- Ökoeffizienz (1)
Rechargeable lithium ion batteries (LIBs) play a very significant role in power supply and storage. In recent decades, LIBs have caught tremendous attention in mobile communication, portable electronics, and electric vehicles. Furthermore, global warming has become a worldwide issue due to the ongoing production of greenhouse gases. It motivates solutions such as renewable sources of energy. Solar and wind energies are the most important ones in renewable energy sources. By technology progress, they will definitely require batteries to store the produced power to make a balance between power generation and consumption. Nowadays,rechargeable batteries such as LIBs are considered as one of the best solutions. They provide high specific energy and high rate performance while their rate of self-discharge is low.
Performance of LIBs can be improved through the modification of battery characteristics. The size of solid particles in electrodes can impact the specific energy and the cyclability of batteries. It can improve the amount of lithium content in the electrode which is a vital parameter in capacity and capability of a battery. There exist diferent sources of heat generation in LIBs such as heat produced during electrochemical reactions, internal resistance in battery. The size of electrode's electroactive particles can directly affect the produced heat in battery. It will be shown that the smaller size of solid particle enhance the thermal characteristics of LIBs.
Thermal issues such as overheating, temperature maldistribution in the battery, and thermal runaway have confined applications of LIBs. Such thermal challenges reduce the Life cycle of LIBs. As well, they may lead to dangerous conditions such as fire or even explosion in batteries. However, recent advances in fabrication of advanced materials such as graphene and carbon nanotubes with extraordinary thermal conductivity and electrical properties propose new opportunities to enhance their performance. Since experimental works are expensive, our objective is to use computational methods to investigate the thermal issues in LIBS. Dissipation of the heat produced in the battery can improve the cyclability and specific capacity of LIBs. In real applications, packs of LIB consist several battery cells that are used as the power source. Therefore, it is worth to investigate thermal characteristic of battery packs under their cycles of charging/discharging operations at different applied current rates. To remove the produced heat in batteries, they can be surrounded by materials with high thermal conductivity. Parafin wax absorbs high energy since it has a high latent heat. Absorption high amounts of energy occurs at constant temperature without phase change. As well, thermal conductivity of parafin can be magnified with nano-materials such as graphene, CNT, and fullerene to form a nano-composite medium. Improving the thermal conductivity of LIBs increase the heat dissipation from batteries which is a vital issue in systems of battery thermal management. The application of two-dimensional (2D) materials has been on the rise since exfoliation the graphene from bulk graphite. 2D materials are single-layered in an order of nanosizes which show superior thermal, mechanical, and optoelectronic properties. They are potential candidates for energy storage and supply, particularly in lithium ion batteries as electrode material. The high thermal conductivity of graphene and graphene-like materials can play a significant role in thermal management of batteries. However, defects always exist in nano-materials since there is no ideal fabrication process. One of the most important defects in materials are nano-crack which can dramatically weaken the mechanical properties of the materials. Newly synthesized crystalline carbon nitride with the stoichiometry of C3N have attracted many attentions due to its extraordinary mechanical and thermal properties. The other nano-material is phagraphene which shows anisotropic mechanical characteristics which is ideal in production of nanocomposite.
It shows ductile fracture behavior when subjected under uniaxial loadings. It is worth to investigate their thermo-mechanical properties in its pristine and defective states. We hope that the findings of our work not only be useful for both experimental and theoretical researches but also help to design advanced electrodes for LIBs.
Turbomachinery plays an important role in many cases of energy generation or conversion. Therefore, turbomachinery is a promising approaching point for optimization in order to increase the efficiency of energy use. In recent years, the use of automated optimization strategies in combination with numerical simulation has become increasingly popular in many fields of engineering. The complex interactions between fluid and solid mechanics encountered in turbomachines on the one hand and the high computational expense needed to calculate the performance on the other hand, have, however, prevented a widespread use of these techniques in this field of engineering. The objective of this work was the development of a strategy for efficient metamodel based optimization of centrifugal compressor impellers. In this context, the main focus is the reduction of the required numerical expense. The central idea followed in this research was the incorporation of preliminary information acquired from low-fidelity computation methods and empirical correlations into the sampling process to identify promising regions of the parameter space. This information was then used to concentrate the numerically expensive high-fidelity computations of the fluid dynamic and structure mechanic performance of the impeller in these regions while still maintaining a good coverage of the whole parameter space. The development of the optimization strategy can be divided into three main tasks. Firstly, the available preliminary information had to be researched and rated. This research identified loss models based on one dimensional flow physics and empirical correlations as the best suited method to predict the aerodynamic performance. The loss models were calibrated using available performance data to obtain a high prediction quality. As no sufficiently exact models for the prediction of the mechanical loading of the impellercould be identified, a metamodel based on finite element computations was chosen for this estimation. The second task was the development of a sampling method which concentrates samples in regions of the parameter space where high quality designs are predicted by the preliminary information while maintaining a good overall coverage. As available methods like rejection sampling or Markov-chain Monte-Carlo methods did not meet the requirements in terms of sample distribution and input correlation, a new multi-fidelity sampling method called “Filtered Sampling“has been developed. The last task was the development of an automated computational workflow. This workflow encompasses geometry parametrization, geometry generation, grid generation and computation of the aerodynamic performance and the structure mechanic loading. Special emphasis was put into the development of a geometry parametrization strategy based on fluid mechanic considerations to prevent the generation of physically inexpedient designs. Finally, the optimization strategy, which utilizes the previously developed tools, was successfully employed to carry out three optimization tasks. The efficiency of the method was proven by the first and second testcase where an existing compressor design was optimized by the presented method. The results were comparable to optimizations which did not take preliminary information into account, while the required computational expense cloud be halved. In the third testcase, the method was applied to generate a new impeller design. In contrast to the previous examples, this optimization featuredlargervariationsoftheimpellerdesigns. Therefore, theapplicability of the method to parameter spaces with significantly varying designs could be proven, too.
Following restructuring of power industry, electricity supply to end-use customers has undergone fundamental changes. In the restructured power system, some of the responsibilities of the vertically integrated distribution companies have been assigned to network managers and retailers. Under the new situation, retailers are in charge of providing electrical energy to electricity consumers who have already signed contract with them. Retailers usually provide the required energy at a variable price, from wholesale electricity markets, forward contracts with energy producers, or distributed energy generators, and sell it at a fixed retail price to its clients. Different strategies are implemented by retailers to reduce the potential financial losses and risks associated with the uncertain nature of wholesale spot electricity market prices and electrical load of the consumers. In this paper, the strategic behavior of retailers in implementing forward contracts, distributed energy sources, and demand-response programs with the aim of increasing their profit and reducing their risk, while keeping their retail prices as low as possible, is investigated. For this purpose, risk management problem of the retailer companies collaborating with wholesale electricity markets, is modeled through bi-level programming approach and a comprehensive framework for retail electricity pricing, considering customers’ constraints, is provided in this paper. In the first level of the proposed bi-level optimization problem, the retailer maximizes its expected profit for a given risk level of profit variability, while in the second level, the customers minimize their consumption costs. The proposed programming problem is modeled as Mixed Integer programming (MIP) problem and can be efficiently solved using available commercial solvers. The simulation results on a test case approve the effectiveness of the proposed demand-response program based on dynamic pricing approach on reducing the retailer’s risk and increasing its profit.
In this paper, the decision-making problem of the retailers under dynamic pricing approach for demand response integration have been investigated. The retailer was supposed to rely on forward contracts, DGs, and spot electricity market to supply the required active and reactive power of its customers. To verify the effectiveness of the proposed model, four schemes for retailer’s scheduling problem are considered and the resulted profit under each scheme are analyzed and compared. The simulation results on a test case indicate that providing more options for the retailer to buy the required power of its customers and increase its flexibility in buying energy from spot electricity market reduces the retailers’ risk and increases its profit. From the customers’ perspective also the retailers’accesstodifferentpowersupplysourcesmayleadtoareductionintheretailelectricityprices. Since the retailer would be able to decrease its electricity selling price to the customers without losing its profitability, with the aim of attracting more customers. Inthiswork,theconditionalvalueatrisk(CVaR)measureisusedforconsideringandquantifying riskinthedecision-makingproblems. Amongallthepossibleoptioninfrontoftheretailertooptimize its profit and risk, demand response programs are the most beneficial option for both retailer and its customers. The simulation results on the case study prove that implementing dynamic pricing approach on retail electricity prices to integrate demand response programs can successfully provoke customers to shift their flexible demand from peak-load hours to mid-load and low-load hours. Comparing the simulation results of the third and fourth schemes evidences the impact of DRPs and customers’ load shifting on the reduction of retailer’s risk, as well as the reduction of retailer’s payment to contract holders, DG owners, and spot electricity market. Furthermore, the numerical results imply on the potential of reducing average retail prices up to 8%, under demand response activation. Consequently, it provides a win–win solution for both retailer and its customers.
Phase Field Modeling for Fracture with Applications to Homogeneous and Heterogeneous Materials
(2017)
The thesis presents an implementation including different applications of a variational-based approach for gradient type standard dissipative solids. Phase field model for brittle fracture is an application of the variational-based framework for gradient type solids. This model allows the prediction of different crack topologies and states. Of significant concern is the application of theoretical and numerical formulation of the phase field modeling into the commercial finite element software Abaqus in 2D and 3D. The fully coupled incremental variational formulation of phase field method is implemented by using the UEL and UMAT subroutines of Abaqus. The phase field method
considerably reduces the implementation complexity of fracture problems as it removes the need for numerical tracking of discontinuities in the displacement field that are characteristic of discrete crack methods. This is accomplished by replacing the sharp discontinuities with a scalar damage phase field representing the diffuse crack topology wherein the amount of diffusion is controlled by a regularization parameter. The nonlinear coupled system consisting of the linear momentum equation and a diffusion type equation governing the phase field evolution is solved simultaneously via a Newton-
Raphson approach. Post-processing of simulation results to be used as visualization
module is performed via an additional UMAT subroutine implemented in the standard Abaqus viewer.
In the same context, we propose a simple yet effective algorithm to initiate and propagate cracks in 2D geometries which is independent of both particular constitutive laws and specific element technology and dimension. It consists of a localization limiter in the form of the screened Poisson equation with, optionally, local mesh refinement. A staggered scheme for standard equilibrium and screened Cauchy equations is used. The remeshing part of the algorithm consists of a sequence of mesh subdivision and element erosion steps. Element subdivision is based on edge split operations using a
given constitutive quantity (either damage or void fraction). Mesh smoothing makes use of edge contraction as function of a given constitutive quantity such as the principal stress or void fraction. To assess the robustness and accuracy of this algorithm, we use both quasi-brittle benchmarks and ductile tests.
Furthermore, we introduce a computational approach regarding mechanical loading in microscale on an inelastically deforming composite material. The nanocomposites material of fully exfoliated clay/epoxy is shaped to predict macroscopic elastic and fracture related material parameters based on their fine–scale features. Two different configurations of polymer nanocomposites material (PNCs) have been studied. These configurations are fully bonded PNCs and PNCs with an interphase zone formation between the matrix and the clay reinforcement. The representative volume element of PNCs specimens with different clay weight contents, different aspect ratios, and different
interphase zone thicknesses are generated by adopting Python scripting. Different constitutive models are employed for the matrix, the clay platelets, and the interphase zones. The brittle fracture behavior of the epoxy matrix and the interphase zones material are modeled using the phase field approach, whereas the stiff silicate clay platelets of the composite are designated as a linear elastic material. The comprehensive study investigates the elastic and fracture behavior of PNCs composites, in addition to predict Young’s modulus, tensile strength, fracture toughness, surface energy dissipation, and cracks surface area in the composite for different material parameters, geometry, and interphase zones properties and thicknesses.
The thesis investigates at the computer aided simulation process for operational vibration analysis of complex coupled systems. As part of the internal methods project “Absolute Values” of the BMW Group, the thesis deals with the analysis of the structural dynamic interactions and excitation interactions. The overarching aim of the methods project is to predict the operational vibrations of engines.
Simulations are usually used to analyze technical aspects (e. g. operational vibrations, strength, ...) of single components in the industrial development. The boundary conditions of submodels are mostly based on experiences. So the interactions with neighboring components and systems are neglected. To get physically more realistic results but still efficient simulations, this work wants to support the engineer during the preprocessing phase by useful criteria.
At first suitable abstraction levels based on the existing literature are defined to identify structural dynamic interactions and excitation interactions of coupled systems. So it is possible to separate different effects of the coupled subsystems. On this basis, criteria are derived to assess the influence of interactions between the considered systems. These criteria can be used during the preprocessing phase and help the engineer to build up efficient models with respect to the interactions with neighboring systems. The method was developed by using several models with different complexity levels. Furthermore, the method is proved for the application in the industrial environment by using the example of a current combustion engine.
Piezoelectric materials are used in several applications as sensors and actuators where they experience high stress and electric field concentrations as a result of which they may fail due to fracture. Though there are many analytical and experimental works on piezoelectric fracture mechanics. There are very few studies about damage detection, which is an interesting way to prevent the failure of these ceramics.
An iterative method to treat the inverse problem of detecting cracks and voids in piezoelectric structures is proposed. Extended finite element method (XFEM) is employed for solving the inverse problem as it allows the use of a single regular mesh for large number of iterations with different flaw geometries.
Firstly, minimization of cost function is performed by Multilevel Coordinate Search (MCS) method. The XFEM-MCS methodology is applied to two dimensional electromechanical problems where flaws considered are straight cracks and elliptical voids. Then a numerical method based on combination of classical shape derivative and level set method for front propagation used in structural optimization is utilized to minimize the cost function. The results obtained show that the XFEM-level set methodology is effectively able to determine the number of voids in a piezoelectric structure and its corresponding locations.
The XFEM-level set methodology is improved to solve the inverse problem of detecting inclusion interfaces in a piezoelectric structure. The material interfaces are implicitly represented by level sets which are identified by applying regularisation using total variation penalty terms. The formulation is presented for three dimensional structures and inclusions made of different materials are detected by using multiple level sets. The results obtained prove that the iterative procedure proposed can determine the location and approximate shape of material subdomains in the presence of higher noise levels.
Piezoelectric nanostructures exhibit size dependent properties because of surface elasticity and surface piezoelectricity. Initially a study to understand the influence of surface elasticity on optimization of nano elastic beams is performed. The boundary of the nano structure is implicitly represented by a level set function, which is considered as the design variable in the optimization process. Two objective functions, minimizing the total potential energy of a nanostructure subjected to a material volume constraint and minimizing the least square error compared to a target
displacement, are chosen for the numerical examples. The numerical examples demonstrate the importance of size and aspect ratio in determining how surface effects impact the optimized topology of nanobeams.
Finally a conventional cantilever energy harvester with a piezoelectric nano layer is analysed. The presence of surface piezoelectricity in nano beams and nano plates leads to increase in electromechanical coupling coefficient. Topology optimization of these piezoelectric structures in an energy harvesting device to further increase energy conversion using appropriately modified XFEM-level set algorithm is performed .
Briefly, the two basic questions that this research is supposed to answer are:
1. Howmuch fiber is needed and how fibers should be distributed through a fiber reinforced composite (FRC) structure in order to obtain the optimal and reliable structural response?
2. How do uncertainties influence the optimization results and reliability of the structure?
Giving answer to the above questions a double stage sequential optimization algorithm for finding the optimal content of short fiber reinforcements and their distribution in the composite structure, considering uncertain design parameters, is presented. In the first stage, the optimal amount of short fibers in a FRC structure with uniformly distributed fibers is conducted in the framework of a Reliability Based Design Optimization (RBDO) problem. Presented model considers material, structural and modeling uncertainties. In the second stage, the fiber distribution optimization (with the aim to further increase in structural reliability) is performed by defining a fiber distribution function through a Non-Uniform Rational BSpline (NURBS) surface. The advantages of using the NURBS surface as a fiber distribution function include: using the same data set for the optimization and analysis; high convergence rate due to the smoothness of the NURBS; mesh independency of the optimal layout; no need for any post processing technique and its non-heuristic nature. The output of stage 1 (the optimal fiber content for homogeneously distributed fibers) is considered as the input of stage 2. The output of stage 2 is the Reliability Index (b ) of the structure with the optimal fiber content and distribution.
First order reliability method (in order to approximate the limit state function) as well as different material models including Rule of Mixtures, Mori-Tanaka, energy-based approach and stochastic multi-scales are implemented in different examples. The proposed combined model is able to capture the role of available uncertainties in FRC structures through a computationally efficient algorithm using all sequential, NURBS and sensitivity based techniques. The methodology is successfully implemented for interfacial shear stress optimization in sandwich beams and also for optimization of the internal cooling channels in a ceramic matrix composite.
Finally, after some changes and modifications by combining Isogeometric Analysis, level set and point wise density mapping techniques, the computational framework is extended for topology optimization of piezoelectric / flexoelectric materials.