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Destructive diseases of the lung like lung cancer or fibrosis are still often lethal. Also in case of fibrosis in the liver, the only possible cure is transplantation.
In this thesis, we investigate 3D micro computed synchrotron radiation (SR\( \mu \)CT) images of capillary blood vessels in mouse lungs and livers. The specimen show so-called compensatory lung growth as well as different states of pulmonary and hepatic fibrosis.
During compensatory lung growth, after resecting part of the lung, the remaining part compensates for this loss by extending into the empty space. This process is accompanied by an active vessel growing.
In general, the human lung can not compensate for such a loss. Thus, understanding this process in mice is important to improve treatment options in case of diseases like lung cancer.
In case of fibrosis, the formation of scars within the organ's tissue forces the capillary vessels to grow to ensure blood supply.
Thus, the process of fibrosis as well as compensatory lung growth can be accessed by considering the capillary architecture.
As preparation of 2D microscopic images is faster, easier, and cheaper compared to SR\( \mu \)CT images, they currently form the basis of medical investigation. Yet, characteristics like direction and shape of objects can only properly be analyzed using 3D imaging techniques. Hence, analyzing SR\( \mu \)CT data provides valuable additional information.
For the fibrotic specimen, we apply image analysis methods well-known from material science. We measure the vessel diameter using the granulometry distribution function and describe the inter-vessel distance by the spherical contact distribution. Moreover, we estimate the directional distribution of the capillary structure. All features turn out to be useful to characterize fibrosis based on the deformation of capillary vessels.
It is already known that the most efficient mechanism of vessel growing forms small torus-shaped holes within the capillary structure, so-called intussusceptive pillars. Analyzing their location and number strongly contributes to the characterization of vessel growing. Hence, for all three applications, this is of great interest. This thesis provides the first algorithm to detect intussusceptive pillars in SR\( \mu \)CT images. After segmentation of raw image data, our algorithm works automatically and allows for a quantitative evaluation of a large amount of data.
The analysis of SR\( \mu \)CT data using our pillar algorithm as well as the granulometry, spherical contact distribution, and directional analysis extends the current state-of-the-art in medical studies. Although it is not possible to replace certain 3D features by 2D features without losing information, our results could be used to examine 2D features approximating the 3D findings reasonably well.
The various uses of fiber-reinforced composites, for example in the enclosures of planes, boats and cars, generates the demand for a detailed analysis of these materials. The final goal is to optimize fibrous materials by the means of “virtual material design”. New fibrous materials are virtually created as realizations of a stochastic model and evaluated with physical simulations. In that way, materials can be optimized for specific use cases, without constructing expensive prototypes or performing mechanical experiments. In order to design a practically fabricable material, the stochastic model is first adapted to an existing material and then slightly modified. The virtual reconstruction of the existing material requires a precise knowledge of the geometry of its microstructure. The first part of this thesis describes a fiber quantification method by the means of local measurements of the fiber radius and orientation. The combination of a sparse chord length transform and inertia moments leads to an efficient and precise new algorithm. It outperforms existing approaches with the possibility to treat different fiber radii within one sample, with high precision in continuous space and comparably fast computing time. This local quantification method can be directly applied on gray value images by adapting the directional distance transforms on gray values. In this work, several approaches of this kind are developed and evaluated. Further characterization of the fiber system requires a segmentation of each single fiber. Using basic morphological operators with specific structuring elements, it is possible to derive a probability for each pixel describing if the pixel belongs to a fiber core in a region without overlapping fibers. Tracking high probabilities leads to a partly reconstruction of the fiber cores in non crossing regions. These core parts are then reconnected over critical regions, if they fulfill certain conditions ensuring the affiliation to the same fiber. In the second part of this work, we develop a new stochastic model for dense systems of non overlapping fibers with a controllable level of bending. Existing approaches in the literature have at least one weakness in either achieving high volume fractions, producing non overlapping fibers, or controlling the bending or the orientation distribution. This gap can be bridged by our stochastic model, which operates in two steps. Firstly, a random walk with the multivariate von Mises-Fisher orientation distribution defines bent fibers. Secondly, a force-biased packing approach arranges them in a non overlapping configuration. Furthermore, we provide the estimation of all parameters needed for the fitting of this model to a real microstructure. Finally, we simulate the macroscopic behavior of different microstructures to derive their mechanical and thermal properties. This part is mostly supported by existing software and serves as a summary of physical simulation applied to random fiber systems. The application on a glass fiber reinforced polymer proves the quality of the reconstruction by our stochastic model, as the effective properties match for both the real microstructure and the realizations of the fitted model. This thesis includes all steps to successfully perform virtual material design on various data sets. With novel and efficient algorithms it contributes to the science of analysis and modeling of fiber reinforced materials.
The fifth-generation (5G) of wireless networks promises to bring new advances, such as a huge increase in mobile data rates, a plunge in communications latency, and an increase in the quality of experience perceived by users that can cope with the ever-increasing demand in Internet traffic. However, the high cost of capital and operational expenditure (CAPEX/OPEX) of the new 5G network and the lack of a killer application hinder its rapid adoption. In this context, Mobile Network Operators (MNOs) have turned their attention to the following idea: opening up their infrastructure so that vertical businesses can leverage the new 5G network to improve their primary businesses and develop new ones. However, deploying multiple isolated vertical applications on top of the same infrastructure poses unique challenges that must be addressed. In this thesis, we provide critical contributions to developing 5G networks to accommodate different vertical applications in an isolated, flexible, and automated manner. This thesis contributions spawn on three main areas: (i) the development of an integrated fronthaul and backhaul network, (ii) the development of a network slicing overbooking algorithm, and (iii) the development of a method to mitigate the noisy neighbors' problem in a vRAN deployment.
A building-block model reveals new insights into the biogenesis of yeast mitochondrial ribosomes
(2020)
Most of the mitochondrial proteins in yeast are encoded in the nuclear genome, get synthesized by cytosolic ribosomes and are imported via TOM and TIM23 into the matrix or other subcompartments of mitochondria. The mitochondrial DNA in yeast however also encodes a small set of 8 proteins from which most are hydrophobic membrane proteins and build core components of the OXPHOS complexes. They get synthesized by mitochondrial ribosomes which are descendants of bacterial ribosomes and still have some similarities to them. On the other hand, mitochondrial ribosomes experienced various structural and functional changes during evolution that specialized them for the synthesis of the mitochondrial encoded membrane proteins. The mitoribosome contains mitochondria-specific ribosomal proteins and replaced the bacterial 5S rRNA by mitochondria-specific proteins and rRNA extensions. Furthermore, the mitoribosome is tethered to the inner mitochondrial membrane to facilitate a co-translational insertion of newly synthesized proteins. Thus, also the assembly process of mitoribosomes differs from that of bacteria and is to date not well understood.
Therefore, the biogenesis of mitochondrial ribosomes in yeast should be investigated. To this end, a strain was generated in which the gene of the mitochondrial RNA-polymerase RPO41 is under control of an inducible GAL10-promoter. Since the scaffold of ribosomes is built by ribosomal RNAs, the depletion of the RNA-polymerase subsequently leads to a loss of mitochondrial ribosomes. Reinduction of Rpo41 initiates the assembly of new mitoribosomes, which makes this strain an attractive model to study mitoribosome biogenesis.
Initially, the effects of Rpo41 depletion on cellular and mitochondrial physiology was investigated. Upon Rpo41 depletion, growth on respiratory glycerol medium was inhibited. Furthermore, mitochondrial ribosomal 21S and 15S rRNA was diminished and mitochondrial translation was almost completely absent. Also, mitochondrial DNA was strongly reduced due to the fact that mtDNA replication requires RNA primers that get synthesized by Rpo41.
Next, the effect of reinduction of Rpo41 on mitochondria was tested. Time course experiments showed that mitochondrial translation can partially recover from 48h Rpo41 depletion within a timeframe of 4.5h. Sucrose gradient sedimentation experiments further showed that the mitoribosomal constitution was comparable to wildtype control samples during the time course of 4.5h of reinduction, suggesting that the ribosome assembly is not fundamentally altered in Gal-Rpo41 mitochondria. In addition, the depletion time was found to be critical for recovery of mitochondrial translation and mitochondrial RNA levels. It was observed that after 36h of Rpo41 depletion, the rRNA levels and mitochondrial translation recovered to almost 100%, but only within a time course of 10h.
Finally, mitochondria from Gal-Rpo41 cells isolated after different timepoints of reinduction were used to perform complexome profiling and the assembly of mitochondrial protein complexes was investigated. First, the steady state conditions and the assembly process of mitochondrial respiratory chain complexes were monitored. The individual respiratory chain complexes and the super-complexes of complex III, complex IV and complex V were observed. Furthermore, it was seen that they recovered from Rpo41 depletion within 4.5h of reinduction. Complexome profiles of the mitoribosomal small and large subunit discovered subcomplexes of mitoribosomal proteins that were assumed to form prior to their incorporation into assembly intermediates. The complexome profiles after reinduction indeed showed the formation of these subcomplexes before formation of the fully assembled subunit. In the mitochondrial LSU one subcomplex builds the membrane facing protuberance and a second subcomplex forms the central protuberance. In contrast to the preassembled subcomplexes, proteins that were involved in early assembly steps were exclusively found in the fully assembled subunit. Proteins that assemble at the periphery of the mitoribosome during intermediate and late assembly steps where found in soluble form suggesting a pool of unassembled proteins that supply assembly intermediates with proteins.
Taken together, the findings of this thesis suggest a so far unknow building-block model for mitoribosome assembly in which characteristic structures of the yeast mitochondrial ribosome form preassembled subcomplexes prior to their incorporation into the mitoribosome.
A Consistent Large Eddy Approach for Lattice Boltzmann Methods and its Application to Complex Flows
(2015)
Lattice Boltzmann Methods have shown to be promising tools for solving fluid flow problems. This is related to the advantages of these methods, which are among others, the simplicity in handling complex geometries and the high efficiency in calculating transient flows. Lattice Boltzmann Methods are mesoscopic methods, based on discrete particle dynamics. This is in contrast to conventional Computational Fluid Dynamics methods, which are based on the solution of the continuum equations. Calculations of turbulent flows in engineering depend in general on modeling, since resolving of all turbulent scales is and will be in near future far beyond the computational possibilities. One of the most auspicious modeling approaches is the large eddy simulation, in which the large, inhomogeneous turbulence structures are directly computed and the smaller, more homogeneous structures are modeled.
In this thesis, a consistent large eddy approach for the Lattice Boltzmann Method is introduced. This large eddy model includes, besides a subgrid scale model, appropriate boundary conditions for wall resolved and wall modeled calculations. It also provides conditions for turbulent domain inlets. For the case of wall modeled simulations, a two layer wall model is derived in the Lattice Boltzmann context. Turbulent inlet conditions are achieved by means of a synthetic turbulence technique within the Lattice Boltzmann Method.
The proposed approach is implemented in the Lattice Boltzmann based CFD package SAM-Lattice, which has been created in the course of this work. SAM-Lattice is feasible of the calculation of incompressible or weakly compressible, isothermal flows of engineering interest in complex three dimensional domains. Special design targets of SAM-Lattice are high automatization and high performance.
Validation of the suggested large eddy Lattice Boltzmann scheme is performed for pump intake flows, which have not yet been treated by LBM. Even though, this numerical method is very suitable for this kind of vortical flows in complicated domains. In general, applications of LBM to hydrodynamic engineering problems are rare. The results of the pump intake validation cases reveal that the proposed numerical approach is able to represent qualitatively and quantitatively the very complex flows in the intakes. The findings provided in this thesis can serve as the basis for a broader application of LBM in hydrodynamic engineering problems.
Beamforming performs spatial filtering to preserve the signal from given directions of interest while suppressing interfering signals and noise arriving from other directions.
For example, a microphone array equipped with beamforming algorithm could preserve the sound coming from a target speaker and suppress sounds coming from other speakers.
Beamformer has been widely used in many applications such as radar, sonar, communication, and acoustic systems.
A data-independent beamformer is the beamformer whose coefficients are independent on sensor signals, it normally uses less computation since the coefficients are computed once. Moreover, its coefficients are derived from the well-defined statistical models, then it produces less artifacts. The major drawback of this beamforming class is its limitation to the interference suppression.
On the other hand, an adaptive beamformer is a beamformer whose coefficients depend on or adapt to sensor signals. It is capable of suppressing the interference better than a data-independent beamforming but it suffers from either too much distortion of the signal of interest or less noise reduction when the updating rate of coefficients does not synchronize with the changing rate of the noise model. Besides, it is computationally intensive since the coefficients need to be updated frequently.
In acoustic applications, the bandwidth of signals of interest extends over several octaves, but we always expect that the characteristic of the beamformer is invariant with regard to the bandwidth of interest. This can be achieved by the so-called broadband beamforming.
Since the beam pattern of conventional beamformers depends on the frequency of the signal, it is common to use a dense and uniform array for the broadband beamforming to guarantee some essential performances together, such as frequency-independence, less sensitive to white noise, high directivity factor or high front-to-back ratio. In this dissertation, we mainly focus on the sparse array of which the aim is to use fewer sensors in the array,
while simultaneously assuring several important performances of the beamformer.
In the past few decades, many design methodologies for sparse arrays have been proposed and were applied in a variety of practical applications.
Although good results were presented, there are still some restrictions, such as the number of sensors is large, the designed beam pattern must be fixed, the steering ability is limited and the computational complexity is high.
In this work, two novel approaches for the sparse array design taking a hypothesized uniform array as a basis are proposed, that is, one for data-independent beamformers and the another for adaptive beamformers.
As an underlying component of the proposed methods, the dissertation introduces some new insights into the uniform array with broadband beamforming. In this context, a function formulating the relations between the sensor coefficients and its beam pattern over frequency is proposed. The function mainly contains the coordinate transform and inverse Fourier transform.
Furthermore, from the bijection of the function and broadband beamforming perspective, we propose the lower and upper bounds for the inter-distance of sensors. Within these bounds, the function is a bijective function that can be utilized to design the uniform array with broadband beamforming.
For data-independent beamforming, many studies have focused on optimization procedures to seek the sparse array deployment. This dissertation presents an alternative approach to determine the location of sensors.
Starting with a weight spectrum of a virtual dense and uniform array, some techniques are used, such as analyzing a weight spectrum to determine the critical sensors, applying the clustering technique to group the sensors into different groups and selecting representative sensors for each group.
After the sparse array deployment is specified, the optimization technique is applied to find the beamformer coefficients. The proposed method helps to save the computation time in the design phase and its beamformer performance outperforms other state-of-the-art methods in several aspects such as the higher white noise gain, higher directivity factor or more frequency-independence.
For adaptive beamforming, the dissertation attempts to design a versatile sparse microphone array that can be used for different beam patterns.
Furthermore, we aim to reduce the number of microphones in the sparse array while ensuring that its performance can continue to compete with a highly dense and uniform array in terms of broadband beamforming.
An irregular microphone array in a planar surface with the maximum number of distinct distances between the microphones is proposed.
It is demonstrated that the irregular microphone array is well-suited to sparse recovery algorithms that are used to solve underdetermined systems with subject to sparse solutions. Here, a sparse solution is the sound source's spatial spectrum that need to be reconstructed from microphone signals.
From the reconstructed sound sources, a method for array interpolation is presented to obtain an interpolated dense and uniform microphone array that performs well with broadband beamforming.
In addition, two alternative approaches for generalized sidelobe canceler (GSC) beamformer are proposed. One is the data-independent beamforming variant, the other is the adaptive beamforming variant. The GSC decomposes beamforming into two paths: The upper path is to preserve the desired signal, the lower path is to suppress the desired signal. From a beam pattern viewpoint, we propose an improvement for GSC, that is, instead of using the blocking matrix in the lower path to suppress the desired signal, we design a beamformer that contains the nulls at the look direction and at some other directions. Both approaches are simple beamforming design methods and they can be applied to either sparse array or uniform array.
Lastly, a new technique for direction-of-arrival (DOA) estimation based on the annihilating filter is also presented in this dissertation.
It is based on the idea of finite rate of innovation to reconstruct the stream of Diracs, that is, identifying an annihilating filter/locator filter for a few uniform samples and the position of the Diracs are then related to the roots of the filter. Here, an annihilating filter is the filter that suppresses the signal, since its coefficient vector is always orthogonal to every frame of signal.
In the DOA context, we regard an active source as a Dirac associated with the arrival direction, then the directions of active sources can be derived from the roots of the annihilating filter. However,
the DOA obtained by this method is sensitive to noise and the number of DOAs is limited.
To address these issues, the dissertation proposes a robust method to design the annihilating filter and to increase the degree-of-freedom of the measurement system (more active sources can be detected) via observing multiple data frames.
Furthermore, we also analyze the performance of DOA with diffuse noise and propose an extended multiple signal classification algorithm that takes diffuse noise into account. In the simulation,
it shows, that in the case of diffuse noise, only the extended multiple signal classification algorithm can estimate the DOAs properly.
The growing computational power enables the establishment of the Population Balance Equation (PBE)
to model the steady state and dynamic behavior of multiphase flow unit operations. Accordingly, the twophase
flow
behavior inside liquid-liquid extraction equipment is characterized by different factors. These
factors include: interactions among droplets (breakage and coalescence), different time scales due to the
size distribution of the dispersed phase, and micro time scales of the interphase diffusional mass transfer
process. As a result of this, the general PBE has no well known analytical solution and therefore robust
numerical solution methods with low computational cost are highly admired.
In this work, the Sectional Quadrature Method of Moments (SQMOM) (Attarakih, M. M., Drumm, C.,
Bart, H.-J. (2009). Solution of the population balance equation using the Sectional Quadrature Method of
Moments (SQMOM). Chem. Eng. Sci. 64, 742-752) is extended to take into account the continuous flow
systems in spatial domain. In this regard, the SQMOM is extended to solve the spatially distributed
nonhomogeneous bivariate PBE to model the hydrodynamics and physical/reactive mass transfer
behavior of liquid-liquid extraction equipment. Based on the extended SQMOM, two different steady
state and dynamic simulation algorithms for hydrodynamics and mass transfer behavior of liquid-liquid
extraction equipment are developed and efficiently implemented. At the steady state modeling level, a
Spatially-Mixed SQMOM (SM-SQMOM) algorithm is developed and successfully implemented in a onedimensional
physical spatial domain. The integral spatial numerical flux is closed using the mean mass
droplet diameter based on the One Primary and One Secondary Particle Method (OPOSPM which is the
simplest case of the SQMOM). On the other hand the hydrodynamics integral source terms are closed
using the analytical Two-Equal Weight Quadrature (TEqWQ). To avoid the numerical solution of the
droplet rise velocity, an analytical solution based on the algebraic velocity model is derived for the
particular case of unit velocity exponent appearing in the droplet swarm model. In addition to this, the
source term due to mass transport is closed using OPOSPM. The resulting system of ordinary differential
equations with respect to space is solved using the MATLAB adaptive Runge–Kutta method (ODE45). At
the dynamic modeling level, the SQMOM is extended to a one-dimensional physical spatial domain and
resolved using the finite volume method. To close the mathematical model, the required quadrature nodes
and weights are calculated using the analytical solution based on the Two Unequal Weights Quadrature
(TUEWQ) formula. By applying the finite volume method to the spatial domain, a semi-discreet ordinary
differential equation system is obtained and solved. Both steady state and dynamic algorithms are
extensively validated at analytical, numerical, and experimental levels. At the numerical level, the
predictions of both algorithms are validated using the extended fixed pivot technique as implemented in
PPBLab software (Attarakih, M., Alzyod, S., Abu-Khader, M., Bart, H.-J. (2012). PPBLAB: A new
multivariate population balance environment for particulate system modeling and simulation. Procedia
Eng. 42, pp. 144-562). At the experimental validation level, the extended SQMOM is successfully used
to model the steady state hydrodynamics and physical and reactive mass transfer behavior of agitated
liquid-liquid extraction columns under different operating conditions. In this regard, both models are
found efficient and able to follow liquid extraction column behavior during column scale-up, where three
column diameters were investigated (DN32, DN80, and DN150). To shed more light on the local
interactions among the contacted phases, a reduced coupled PBE and CFD framework is used to model
the hydrodynamic behavior of pulsed sieve plate columns. In this regard, OPOSPM is utilized and
implemented in FLUENT 18.2 commercial software as a special case of the SQMOM. The dropletdroplet
interactions
(breakage
and
coalescence)
are
taken
into
account
using
OPOSPM,
while
the
required
information
about
the
velocity
field
and
energy
dissipation
is
calculated
by
the
CFD
model.
In
addition
to
this,
the proposed coupled OPOSPM-CFD framework is extended to include the mass transfer. The
proposed framework is numerically tested and the results are compared with the published experimental
data. The required breakage and coalescence parameters to perform the 2D-CFD simulation are estimated
using PPBLab software, where a 1D-CFD simulation using a multi-sectional gird is performed. A very
good agreement is obtained at the experimental and the numerical validation levels.
The present thesis describes the development and the evaluation of a design procedure of inducer with arbitrary meridional and blade shape. This special type of pump impeller, which is usually mounted upstream of a main pump impeller, is employed in many applications demanding the realization of low NPSH values. An inducer basically increases suction performance by producing mostly a small pressure rise while allowing for a greater degree of cavitation, that is the formation of vapor bubbles, at its inlet than a conventional pump impeller. This is achieved by specially designed blade channels promoting the collapse of the produced vapor bubbles.
The main focus of the present thesis is the description of the design method, which enables the generation of the three-dimensional blade geometry. The method is based on a parametric representation of the geometry considering the particular requirements for inducers and the publicly available design practice. Within this approach the sequence of design steps is adapted from the classical design process of mixed flow and radial impellers. As a consequence leading and trailing edge blade angles are determined based on simplifications and certain empirical assumptions for multiple blade sections and are used to design the blade camber curves. Along the camber curves the blade profile is generated following a thickness distribution that has to be prescribed. A special feature of the newly developed method is that arbitrary shaped, asymmetric thickness distributions can be realized.
Due to the detailed description of the design and calculation steps a fully comprehensible procedure is outlined, which covers the development of inducer bladings from an initial set of duty parameters to the final three-dimensional blade geometry.
The components involved in the design procedure are tested by designing two exemplary inducers and they are assessed by comparison with numerical simulations. Functioning of these inducers in the real application is finally demonstrated with water tests.
The main result of this dissertation is a design software for inducers allowing for the design of three-dimensional, asymmetrically profiled bladings. The developed software is free of commercial third-party libraries. As a consequence a program is available that can be modified and extended as desired. As potential future development goals inducers with splitter and tandem blades as well as an integrated design of inducer and impeller are proposed.
Medical cyber-physical systems (MCPS) emerged as an evolution of the relations between connected health systems, healthcare providers, and modern medical devices. Such systems combine independent medical devices at runtime in order to render new patient monitoring/control functionalities, such as physiological closed loops for controlling drug infusion or optimization of alarms. Despite the advances regarding alarm precision, healthcare providers still struggle with alarm flooding caused by the limited risk assessment models. Furthermore, these limitations also impose severe barriers on the adoption of automated supervision through autonomous actions, such as safety interlocks for avoiding overdosage. The literature has focused on the verification of safety parameters to assure the safety of treatment at runtime and thus optimize alarms and automated actions. Such solutions have relied on the definition of actuation ranges based on thresholds for a few monitored parameters. Given the very dynamic nature of the relevant context conditions (e.g., the patient’s condition, treatment details, system configurations, etc.), fixed thresholds are a weak means for assessing the current risk. This thesis presents an approach for enabling dynamic risk assessment for cooperative MCPS based on an adaptive Bayesian Networks (BN) model. The main aim of the approach is to support continuous runtime risk assessment of the current situation based on relevant context and system information. The presented approach comprises (i) a dynamic risk analysis constituent, which corresponds to the elicitation of relevant risk parameters, risk metric building, and risk metric management; and (ii) a runtime risk classification constituent, which aims to analyze the current situation risk, establish risk classes, and identify and deploy mitigation measures. The proposed approach was evaluated and its feasibility proved by means of simulated experiments guided by an international team of medical experts with a focus on the requirements of efficacy, efficiency, and availability of patient treatment.
This work deals with the simulation of the micro-cutting process of titanium. For this
purpose, a suitable crystal-plastic material model is developed and efficient implemen-
tations are investigated to simulate the micro-cutting process. Several challenges arise
for the material model. On the one hand, the low symmetry hexagonal close-packed
crystal structure of titanium has to be considered. On the other hand, large defor-
mations and strains occur during the machining process. Another important part is
the algorithm for the determination of the active slip systems, which has a significant
influence on the stability of the simulation. In order to obtain a robust implemen-
tation, different aspects, such as the algorithm for the determination of the active
slip systems, the method for mesh separation between chip and workpiece as well as
the hardening process are investigated, and different approaches are compared. The
developed crystal-plastic material model and the selected implementations are first
validated and investigated using illustrative examples. The presented simulations of
the micro-cutting process show the influence of different machining parameters on the
process. Finally, the influence of a real microstructure on the plastic deformation and
the cutting force during the process is shown.