121 research outputs found
Numerical approximation of phase field based shape and topology optimization for fluids
We consider the problem of finding optimal shapes of fluid domains. The fluid
obeys the Navier--Stokes equations. Inside a holdall container we use a phase
field approach using diffuse interfaces to describe the domain of free flow. We
formulate a corresponding optimization problem where flow outside the fluid
domain is penalized. The resulting formulation of the shape optimization
problem is shown to be well-posed, hence there exists a minimizer, and first
order optimality conditions are derived.
For the numerical realization we introduce a mass conserving gradient flow
and obtain a Cahn--Hilliard type system, which is integrated numerically using
the finite element method. An adaptive concept using reliable, residual based
error estimation is exploited for the resolution of the spatial mesh.
The overall concept is numerically investigated and comparison values are
provided
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Stability of infinite dimensional control problems with pointwise state constraints
A general class of nonlinear infinite dimensional optimization problems
is considered that covers semi-linear elliptic control problems with
distributed control as well as boundary control. Moreover, pointwise
inequality constraints on the control and the state are incorporated. The
general optimization problem is perturbed by a certain class of
perturbations, and we establish convergence of local solutions of the
perturbed problems to a local solution of the unperturbed optimal control
problem. These class of perturbations include finite element discretization
as well as data perturbation such that the theory implies convergence of
finite element approximation and stability w.r.t. noisy data
Numerical analysis of Lavrentiev-regularized state constrained elliptic control problems
In the present work, we apply semi-discretization proposed by the first author in [13] to Lavrentiev-regularized state constrained elliptic control problems. We extend the results of [17] and prove weak convergence of the adjoint states and multipliers of the regularized problems to their counterparts of the original problem. Further, we prove error estimates for finite element discretizations of the regularized problem and investigate the overall error imposed by the finite element discretization of the regularized problem compared to the continuous solution of the original problem. Finally we present numerical results which confirm our analytical findings
Numerical analysis of Lavrentiev-regularized state constrained elliptic control problems
In the present work, we apply semi-discretization proposed by the first author in [13] to Lavrentiev-regularized state constrained elliptic control problems. We extend the results of [17] and prove weak convergence of the adjoint states and multipliers of the regularized problems to their
counterparts of the original problem. Further, we prove error estimates for finite element discretizations of the regularized problem and investigate the overall error imposed by the finite element discretization of the regularized problem compared to the continuous solution of the original problem. Finally we present numerical results which confirm our analytical findings
Shape optimization for surface functionals in Navier--Stokes flow using a phase field approach
We consider shape and topology optimization for fluids which are governed by
the Navier--Stokes equations. Shapes are modelled with the help of a phase
field approach and the solid body is relaxed to be a porous medium. The phase
field method uses a Ginzburg--Landau functional in order to approximate a
perimeter penalization. We focus on surface functionals and carefully introduce
a new modelling variant, show existence of minimizers and derive first order
necessary conditions. These conditions are related to classical shape
derivatives by identifying the sharp interface limit with the help of formally
matched asymptotic expansions. Finally, we present numerical computations based
on a Cahn--Hilliard type gradient descent which demonstrate that the method can
be used to solve shape optimization problems for fluids with the help of the
new approach
Limited utility of qPCR-based detection of tumor-specific circulating mRNAs in whole blood from clear cell renal cell carcinoma patients
BACKGROUND:
RNA sequencing data is providing abundant information about the levels of dysregulation of genes in various tumors. These data, as well as data based on older microarray technologies have enabled the identification of many genes which are upregulated in clear cell renal cell carcinoma (ccRCC) compared to matched normal tissue. Here we use RNA sequencing data in order to construct a panel of highly overexpressed genes in ccRCC so as to evaluate their RNA levels in whole blood and determine any diagnostic potential of these levels for renal cell carcinoma patients.
METHODS:
A bioinformatics analysis with Python was performed using TCGA, GEO and other databases to identify genes which are upregulated in ccRCC while being absent in the blood of healthy individuals. Quantitative Real Time PCR (RT-qPCR) was subsequently used to measure the levels of candidate genes in whole blood (PAX gene) of 16 ccRCC patients versus 11 healthy individuals. PCR results were processed in qBase and GraphPadPrism and statistics was done with Mann-Whitney U test.
RESULTS:
While most analyzed genes were either undetectable or did not show any dysregulated expression, two genes, CDK18 and CCND1, were paradoxically downregulated in the blood of ccRCC patients compared to healthy controls. Furthermore, LOX showed a tendency towards upregulation in metastatic ccRCC samples compared to non-metastatic.
CONCLUSIONS:
This analysis illustrates the difficulty of detecting tumor regulated genes in blood and the possible influence of interference from expression in blood cells even for genes conditionally absent in normal blood. Testing in plasma samples indicated that tumor specific mRNAs were not detectable. While CDK18, CCND1 and LOX mRNAs might carry biomarker potential, this would require validation in an independent, larger patient cohort
A goal-oriented dual-weighted adaptive finite element approach for the optimal control of a nonsmooth Cahn--Hilliard--Navier--Stokes system
This paper is concerned with the development and implementation of an adaptive solution algorithm for the optimal control of a time-discrete Cahn--Hilliard--Navier--Stokes system with variable densities. The free energy density associated to the Cahn--Hilliard system incorporates the double-obstacle potential which yields an optimal control problem for a family of coupled systems in each time instant of a variational inequality of fourth order and the Navier--Stokes equation. A dual-weighed residual approach for goal-oriented adaptive finite elements is presented which is based on the concept of C-stationarity. The overall error representation depends on primal residual weighted by approximate dual quantities and vice versa as well as various complementary mismatch errors. Details on the numerical realization of the adaptive concept and a report on numerical tests are given
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A goal-oriented dual-weighted adaptive finite element approach for the optimal control of a nonsmooth Cahn-Hilliard-Navier-Stokes system
This paper is concerned with the development and implementation of an
adaptive solution algorithm for the optimal control of a time-discrete
Cahn-Hilliard-Navier-Stokes system with variable densities. The free energy
density associated to the Cahn-Hilliard system incorporates the
double-obstacle potential which yields an optimal control problem for a
family of coupled systems in each time instant of a variational inequality of
fourth order and the Navier-Stokes equation. A dual-weighted residual
approach for goal-oriented adaptive finite elements is presented which is
based on the concept of C-stationarity. The overall error representation
depends on primal residuals weighted by approximate dual quantities and vice
versa as well as various complementarity mismatch errors. Details on the
numerical realization of the adaptive concept and a report on numerical tests
are given
Biochemical Frequency Control by Synchronisation of Coupled Repressilators: An In Silico Study of Modules for Circadian Clock Systems
Exploration of chronobiological systems emerges as a growing research field within bioinformatics focusing on various applications in medicine, agriculture, and material sciences. From a systems biological perspective, the question arises whether biological control systems for regulation of oscillatory signals and their technical counterparts utilise similar mechanisms. If so, modelling approaches and parameterisation adopted from building blocks can help to identify general components for frequency control in circadian clocks along with gaining insight into mechanisms of clock synchronisation to external stimuli like the daily rhythm of sunlight and darkness. Phase-locked loops could be an interesting candidate in this context. Both, biology and engineering, can benefit from a unified view resulting from systems modularisation. In a first experimental study, we analyse a model of coupled repressilators. We demonstrate its ability to synchronise clock signals in a monofrequential manner. Several oscillators initially deviate in phase difference and frequency with respect to explicit reaction and diffusion rates. Accordingly, the duration of the synchronisation process depends on dedicated reaction and diffusion parameters whose settings still lack to be sufficiently captured analytically
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