The holy grail of microfluidics: sub-laminar drag by layout of periodically embedded microgrooves

The sub-laminar drag effect of microgroove surfaces was studied numerically in a steady two-dimensional channel flow at subcritical Reynolds numbers. Considerations are restricted to grooves of a few viscous length scales in depth, which are assumed not to promote the laminar to turbulent transition process. It was found that the drag reduction effect is due to the layout of grooves with respect to the flow direction and contour geometry. Results of computations show that for grooves of curved contour placed normal to the flow direction, drag arising from viscous and pressure forces is modulated due to the functional dependence of forces on the surface area projected in the flow direction. Such a groove layout leads to a large skin-friction reduction, but a comparable increase in pressure drag results in sub-laminar drag if drag over flat surface is considered as a reference. For a curved groove contour, the drag reduction increases with increasing Reynolds number and reaches about 5 % at Reynolds numbers approaching critical.     

Towards Automated Binding Affinity Prediction Using an Iterative Linear Interaction Energy Approach

Binding affinity prediction of potential drugs to target and off-target proteins is an essential asset in drug development. These predictions require the calculation of binding free energies. In such calculations, it is a major challenge to properly account for both the dynamic nature of the protein and the possible variety of ligand-binding orientations, while keeping computational costs tractable. Recently, an iterative Linear Interaction Energy (LIE) approach was introduced, in which results from multiple simulations of a protein-ligand complex are combined into a single binding free energy using a Boltzmann weighting-based scheme. This method was shown to reach experimental accuracy for flexible proteins while retaining the computational efficiency of the general LIE approach. Here, we show that the iterative LIE approach can be used to predict binding affinities in an automated way. A workflow was designed using preselected protein conformations, automated ligand docking and clustering, and a (semi-)automated molecular dynamics simulation setup. We show that using this workflow, binding affinities of aryloxypropanolamines to the malleable Cytochrome P450 2D6 enzyme can be predicted without a priori knowledge of dominant protein-ligand conformations. In addition, we provide an outlook for an approach to assess the quality of the LIE predictions, based on simulation outcomes only.     

NURBS based least‐squares finite element methods for fluid and solid mechanics

This contribution investigates the performance of a least‐squares finite element method based on non‐uniform rational B‐splines (NURBS) basis functions. The least‐squares functional is formulated directly in terms of the strong form of the governing equations and boundary conditions. Thus, the introduction of auxiliary variables is avoided, but the order of the basis functions must be higher or equal to the order of the highest spatial derivatives. The methodology is applied to the incompressible Navier–Stokes equations and to linear as well as nonlinear elastic solid mechanics. The numerical examples presented feature convective effects and incompressible or nearly incompressible material. The numerical results, which are obtained with equal‐order interpolation and without any stabilisation techniques, are smooth and accurate. It is shown that for p and h refinement, the theoretical rates of convergence are achieved. Copyright © 2014 John Wiley & Sons, Ltd.     

Vortex characteristics due to nozzle clogging in water caster mould: modelling and validation

In continuous slab casting, clogging in the submerged entry nozzle (SEN) ports leads to flow asymmetry and vortex formation in the mould. Knowledge of vortexing and its influence on product quality is fundamental for defect-free production. In this study, the interconnected effects of nozzle clogging and SEN submergence depth, variation on flow asymmetry and vortex characteristics in a 0.4 scale water caster have been characterised by CFD investigation and validated with experimental results from the authors’ previous work. Mean flow velocities at the sub-meniscus and near the port exit predicted by the computational model are compared with the time-averaged values of the impeller probe velocity measurements and found to be in reasonable agreement. Three different clogging conditions (0, 33 and 66% in the left port of the SEN) for SEN submergence depth of 60?mm are studied and the 66% clogging produced vortices having largest diameter, which is consistent with the experimental observations. The effects of SEN submergence depth on flow asymmetry and vortexing are investigated with three different conditions – 40, 60 and 80?mm. It is found that the shallow SEN submergence depth (40?mm) produces vortices of largest diameter and the flow is most stable for a SEN submergence depth of 60?mm among the three cases. Vortex bending towards the SEN as noticed in the experimental observations is also observed in the computational study. This work illustrates the possibility of capturing features of vortexing using validated CFD model.     

A novel SON2‐based similarity index and its application for the rationalization of river water quality monitoring network

In this paper, a novel self‐organizing network (SON) based similarity index and its application for the optimization of sampling locations in an existing river water quality monitoring network (WQMN) is presented. A rationalization of the River Danube WQMN on its stretch through Serbia was performed using the proposed SON²‐based similarity index. A high‐dimensional dataset was used, which is composed of 18 water quality parameters that were collected during the period 2002–2010 at 17 monitoring locations. The SON‐based seasonal classification that divides 12 months into the cold, moderate, and warm seasons was employed, whereas its second application on each seasonal class yielded subclasses that were used to compare the monitoring locations. The obtained SON²‐based similarity index can be utilized for analysing seasonal variations, as well as overall similarities among neighbouring sites. Based on the calculated similarities of locations and characteristics of the River Danube basin a rationalized WQMN, which uses 30% less monitoring sites, has been proposed.     

Sensitivity Analysis Methods to Design Optimal Ship Hulls

Automatic procedures for the design of ship hull geometries yielding minimal wave resistance and wave breaking are an attractive opportunity from both the economical and practical standpoints. Estimating the cost function gradient according to the Sensitivity Equation and Adjoint Methods (SEM, AM) instead of using the standard finite difference approximations has the potential of reducing the computational cost of the overall optimization procedure. Aim of this paper is to assess the actual extent of the cost reduction. Speed-up factors of up to 3.3 have been obtained in the evaluation of the cost function gradient and of about 1.6 in the overall optimization procedure applied to an optimal shape design problem of an existing tanker ship. The SEM and AM methods perform better than finite differences mainly because of (i) the smaller number of flow solutions needed to compute the cost function gradient and (ii) the opportunity of using the same LU factored matrix for both the flow solver and the SEM or AM equations, a circumstance arising as a consequence of having chosen a linearized potential flow model of the 3D free-surface problem.     

Hydroelastic optimization of a keel fin of a sailing boat: a multidisciplinary robust formulation for ship design

The paper presents a formulation for multidisciplinary design optimization of vessels, subject to uncertain operating conditions. The formulation couples the multidisciplinary design analysis with the Bayesian approach to decision problems affected by uncertainty. In the present context, the design specifications are no longer given in terms of a single operating design point, but in terms of probability density function of the operating scenario. The optimal configuration is that which maximizes the performance expectation over the uncertain parameters variation. In this sense, the optimal solution is “robust” within the stochastic scenario assumed. Theoretical and numerical issues are addressed and numerical results in the hydroelastic optimization of a keel fin of a sailing yacht are presented.     

A model for everyday experience of the built environment: the embodied perception of architecture

Architecture's daily impact on its users is the result of neither concentration nor focused attention. Preoccupied with everyday tasks, most people do not stop to observe the architectural object as a work of art. In this paper I investigate the content that may be present when architecture is experienced in the state Walter Benjamin calls 'distraction'. Using a phenomenological model of attention and my applied research, I propose a plausible model for the Lived Experience of the Built Environment (LEBEN). I further consider the possible components of the everyday experience of architecture and the urban surroundings, and suggest an integrative structure for it. Part I explains the need for the research and presents its objectives. Part II discusses the phenomenological model of attention and awareness. Parts III and IV present the LEBEN model, briefly describing its sources in the literature, and applied research, based on a workshop that examined multi-subjective perspectives. I note the research assumptions, methodology and the challenges facing such an investigation, eg, whether it is possible to study a phenomenon that exists beyond the realm of focal attention. Part V introduces the core-themes and categories distilled from my research (edge, depth, change, atmosphere and affordances) and positions them in the LEBEN model.     

Hydrolysis of pumpkin oil cake protein isolate and free radical scavenging activity of hydrolysates: Influence of temperature,enzyme/substrate ratio and time

The effect of hydrolysis parameters (temperature, initial enzyme/substrate ratio and time) on the hydrolysis of pumpkin oil cake protein isolate (PuOC PI) with acid protease from Aspergillus niger and the antioxidant potency of the obtained hydrolysates were studied by response surface methodology (RSM). The hydrolysis progress, measured by the degree of hydrolysis (DH), was described by a second-order polynomial model (R² = 0.77) and the conditions for optimum DH (42.94%) were found at temperature of 40 °C, enzyme/substrate ratio (E/S) 4.38 HUT/mg of substrate proteins and 85 min. The antiradical activity (AA) of the PuOC PI hydrolysates was examined by the 1,1-diphenyl-2-picryl-hydrazyl (DPPH) assay; all hydrolysates showed a concentration dependent scavenging activity against DPPH radicals. The AA of hydrolysates was influenced by process parameters and was presented also by a second-order polynomial model (R² = 0.7). The conditions to achieve the highest DH did not result hydrolysates with the optimum AA; the highest AA ranged from 34% to 40% and were found in hydrolysates obtained at 50 °C.