Shape optimization for drag reduction in linked bodies using evolution strategies

We present results from the shape optimization of linked bodies for drag reduction in simulations of incompressible flow at moderate Reynolds numbers. The optimization relies on the covariance matrix adaptation evolution strategy (CMA-ES) and the flow simulations use vortex methods with the Brinkman penalization to enforce boundary conditions in complex bodies. We exploit the inherent parallelism of CMA-ES, by implementing a multi-host framework which allows for the distribution of the expensive cost function evaluations across parallel architectures, without being limited to one computing facility. This study repeats in silico for the first time Ingo Rechenberg’s pioneering wind tunnel experiments for drag reduction that led to the inception of evolution strategies. The simulations confirm that the results of these experimental studies indicate a flat plate is not the optimal solution for drag reduction in linked bodies. We present the vorticity field of the flow and identify the governing mechanisms for this drag reduction by the slightly corrugated linked plate configuration.     

Enthalpy-entropy compensation in water sorption by various wood species

Tsuga heterophylla ), Douglas fir (Pseudotsuga menziesii), western red cedar (Thuja plicata), sitka spruce (Picea sitchensis), and lodgepole pine (Pinus contorta). Enthalpy and entropy show a strong negative relation to the moisture content, the absolute desorption values always being higher than the adsorption ones, but with no clear trend between and within the species. Furthermore, it is shown that the linear plot of compensation between enthalpy and entropy correlates well for water sorption in wood; that water adsorption or desorption are irreversible, and that both are enthalpy-driven mechanisms.

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Tsuga heterophyll , Pseudotsuga menziesi, Thuja plicata, Picea sitchensis), und Pinus contorta. Enthalpie und Entropie steigen mit fallender Feuchte. Die Desorptionswerte sind immer etwas h?her als die Adsorptionswerte. Zwischen den Holzarten gab es keine signifikanten Unterschiede. Die lineare Kompensation zwischen Enhalpie und Entropie korrelliert gut mit der Sorption. Absorption und Desorption sind irreversible, Enthalpie-getriebene Prozesse.

     

Non-periodic Molecular Dynamics simulations of coarse grained lipid bilayer in water

We present a multiscale algorithm that couples coarse grained molecular dynamics (CGMD) with continuum solver. The coupling requires the imposition of non-periodic boundary conditions on the coarse grained Molecular Dynamics which, when not properly enforced, may result in spurious fluctuations of the material properties of the system represented by CGMD. In this paper we extend a control algorithm originally developed for atomistic simulations [3], to conduct simulations involving coarse grained water molecules without periodic boundary conditions. We demonstrate the applicability of our method in simulating more complex systems by performing a non-periodic Molecular Dynamics simulation of a DPPC lipid in liquid coarse grained water.     

Self-organizing nets for optimization

Given some optimization problem and a series of typically expensive trials of solution candidates sampled from a search space, how can we efficiently select the next candidate? We address this fundamental problem by embedding simple optimization strategies in learning algorithms inspired by Kohonen's self-organizing maps and neural gas networks. Our adaptive nets or grids are used to identify and exploit search space regions that maximize the probability of generating points closer to the optima. Net nodes are attracted by candidates that lead to improved evaluations, thus, quickly biasing the active data selection process toward promising regions, without loss of ability to escape from local optima. On standard benchmark functions, our techniques perform more reliably than the widely used covariance matrix adaptation evolution strategy. The proposed algorithm is also applied to the problem of drag reduction in a flow past an actively controlled circular cylinder, leading to unprecedented drag reduction.     

Learning probability distributions in continuous evolutionary algorithms – a comparative review

We present a comparative review of Evolutionary Algorithms that generate new population members by sampling a probability distributionconstructed during the optimization process. We present a unifying formulation for five such algorithms that enables us to characterize them based on the parametrization of the probability distribution, the learning methodology, and the use of historical information.The algorithms are evaluated on a number of test functions in order to assess their relative strengths and weaknesses. This comparative reviewhelps to identify areas of applicability for the algorithms and to guidefuture algorithmic developments.     

Mesh-particle interpolations on graphics processing units and multicore central processing units

Particle-mesh interpolations are fundamental operations for particle-in-cell codes, as implemented in vortex methods, plasma dynamics and electrostatics simulations. In these simulations, the mesh is used to solve the field equations and the gradients of the fields are used in order to advance the particles. The time integration of particle trajectories is performed through an extensive resampling of the flow field at the particle locations. The computational performance of this resampling turns out to be limited by the memory bandwidth of the underlying computer architecture. We investigate how mesh-particle interpolation can be efficiently performed on graphics processing units (GPUs) and multicore central processing units (CPUs), and we present two implementation techniques. The single-precision results for the multicore CPU implementation show an acceleration of 45-70×, depending on system size, and an acceleration of 85-155× for the GPU implementation over an efficient single-threaded C++ implementation. In double precision, we observe a performance improvement of 30-40× for the multicore CPU implementation and 20-45× for the GPU implementation. With respect to the 16-threaded standard C++ implementation, the present CPU technique leads to a performance increase of roughly 2.8-3.7× in single precision and 1.7-2.4× in double precision, whereas the GPU technique leads to an improvement of 9× in single precision and 2.2-2.8× in double precision.     

Multiobjective evolutionary algorithm for the optimization of noisy combustion processes

This work introduces a multiobjective evolutionary algorithm capable of handling noisy problems with a particular emphasis on robustness against unexpected measurements (outliers). The algorithm is based on the Strength Pareto evolutionary algorithm of Zitzler and Thiele and includes the new concepts of domination dependent lifetime, re-evaluation of solutions and modifications in the update of the archive population. Several tests on prototypical functions underline the improvements in convergence speed and robustness of the extended algorithm. The proposed algorithm is implemented to the Pareto optimization of the combustion process of a stationary gas turbine in an industrial setup. The Pareto front is constructed for the objectives of minimization of NO/sub x/ emissions and reduction of the pressure fluctuations (pulsation) of the flame. Both objectives are conflicting affecting the environment and the lifetime of the turbine, respectively. The optimization leads a Pareto front corresponding to reduced emissions and pulsation of the burner. The physical implications of the solutions are discussed and the algorithm is evaluated.     

RADIO FREQUENCY VACUUM DRYING OF WOOD. I. MATHEMATICAL MODEL

A one-dimensional mathematical model to describe the transport phenomena during continuous radio frequency/vacuum (RF/V) drying of thick lumber was developed from general conservation equations. When drying at temperatures near the boiling point, as in RF/V drying, the effect of the gas phase pressure gradient on moisture transfer within the solid can be very important. The controlling resistances and transport mechanisms are discussed in detail. In addition, capillary transport in RF/V drying is discussed and its effect is compared with convective drying. The model provides a relatively fast and efficient way to simulate vacuum drying behavior assisted by dielectric heating. As an example, the governing heat and mass transfer equations, including consideration of internal heat generation and the effect of gas phase pressure gradient, are derived and solved in a one-dimensional system using a finite volume method. The effect of changes of the most important parameters on the predictions of the model is also presented.     

Covalently Bonded Graphene–Carbon Nanotube Hybrid for High‐Performance Thermal Interfaces

The remarkable thermal properties of graphene and carbon nanotubes (CNTs) have been the subject of intensive investigations for the thermal management of integrated circuits. However, the small contact area of CNTs and the large anisotropic heat conduction of graphene have hindered their applications as effective thermal interface materials (TIMs). Here, a covalently bonded graphene–CNT (G‐CNT) hybrid is presented that multiplies the axial heat transfer capability of individual CNTs through their parallel arrangement, while at the same time it provides a large contact area for efficient heat extraction. Through computer simulations, it is demonstrated that the G‐CNT outperforms few‐layer graphene by more than 2 orders of magnitude for the c‐axis heat transfer, while its thermal resistance is 3 orders of magnitude lower than the state‐of‐the‐art TIMs. We show that heat can be removed from the G‐CNT by immersing it in a liquid. The heat transfer characteristics of G‐CNT suggest that it has the potential to revolutionize the design of high‐performance TIMs.