189,387 research outputs found
Effects of porous substrates on the structure of turbulent boundary layers
Get PDFThree different porous substrates (with different pore sizes, s, and
permeabilities, K) are used to examine their effect on the structure of
boundary layer flow over them. The flow is characterised with single-point
hot-wire measurements as well as planar Particle Image Velocimetry. In order to
elucidate differences in shallow and deep flows past porous substrate, foams
with two different thickness (h) are used (for all three substrates). A wide
range of Friction Reynolds number (2000< Retau < 15000) and Permeability based
Reynolds number (1<ReK< 50) are attained. For substrates with ReK=1, the flow
behaviour remains similar to flow over impermeable smooth walls and as such
Townsend's hypothesis remains valid. In contrast, a substantial reduction in
velocity disturbances and associated length scales is achieved for permeable
(ReK>1) and dense (relative to viscous scales) foam at the thick substrate
limit (h/s>10), which leads to the breakdown of outer-layer similarity. As
porosity is increased, a thin substrate limit is reached (h/s), and the foam
becomes sparse relative to viscous scales (s+ > 100). For such foams, the flow
conforms to outer-layer similarity and is more akin to flow over rough
surfaces. Such substrates are unable to attenuate velocity disturbances and the
dependence of substrate thickness (h/s) on spectral energy content of turbulent
fluctuations ceases to exist. The present study shows that transition from
thick to thin substrate flow behavior depends not only on thickness-to-pore
ratio (h/s) but also on substrate density relative to viscous scales of the
flow.Comment: 29 pages, 14 figure
On the use of two-point velocity correlation in wall-pressure models for turbulent flow past a trailing edge under adverse pressure gradient
Get PDFTwo-point velocity statistics near the trailing edge of a controlled diffusion airfoil are obtained, both experimentally and analytically, by decomposing Poisson's equation for pressure into the mean-shear (MS) and turbulence-turbulence (TT) interaction terms. The study focuses on the modeling of each interaction term, in order to allow for the reconstruction of the wall-pressure spectra from tomographic velocimetry data, without numerically solving for pressure. The two-point correlation of the wall-normal velocity that describes the magnitude of the MS source term is found to be influenced by various competing factors such as blocking, mean-shear, and the adverse mean pressure gradient. The blocking term is found to supersede the other interaction terms close to the wall, making the two-point velocity correlation self-similar. The most dominant TT term that contributes to far-field noise for an observer located perpendicular to the airfoil chord at the mid-span is shown to be the one that quantifies the variation of the wall-normal velocity fluctuations in the longitudinal direction because of the statistical homogeneity of turbulence in planes parallel to the wall. A model to determine the contribution of the TT interaction term is proposed where the fourth-order two-point correlation can be modeled using Lighthill's approximation. However, its contribution toward wall-pressure spectra is found to be substantially lower than the MS term in the present case. Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Wind Energ
Towards decoupling the effects of permeability and roughness on turbulent boundary layers
Get PDFBoundary layer flow over a realistic porous wall might contain both the
effects of wall-permeability and wall-roughness. These two effects are
typically examined in the context of a rough-wall flow, i.e., by defining a
``roughness'' length or equivalent to capture the effect of the surface on
momentum deficit/drag. In this work, we examine the hypothesis of Esteban et
al. (2022), that a turbulent boundary layer over a porous wall could be
modelled as a superposition of the roughness effects on the permeability
effects by using independently obtained information on permeability and
roughness. We carry out wind tunnel experiments at high Reynolds number () on various combinations of porous walls where
different roughnesses are overlaid over a given permeable wall. Measurements
are also conducted on the permeable wall as well as the rough walls
independently to obtain the corresponding lengthscales. Analysis of mean flow
data across all these measurements suggests that an empirical formulation can
be obtained where the momentum deficit () is modelled as a
combination of independently obtained roughness and permeability lengthscales.
This formulation assumes the presence of outer-layer similarity across these
different surfaces, which is shown to be valid at high Reynolds numbers.
Finally, this decoupling approach is equivalent to the area-weighted power-mean
of the respective permeability and roughness lengthscales, consistent with the
approach recently suggested by Hutchins et al. (2023) to capture the effects of
heterogeneous rough surfaces.Comment: Under review for publication in JFM Rapid
“The Impact Of Ownership Structure On Corporate Social Responsibility: An Empirical Evidence For European Firms”
No full textIn this paper we supplement existent research on the relation between Corporate Social Performance and Corporate Financial Performance by studying the link between corporate social responsibility and ownership structure in Europe.
Neither theory nor empirical studies seem to agree to what effect is more likely to emerge or under what conditions large shareholders are beneficial or not to the firm’s other stakeholders.
To our knowledge there are very few empirical studies on corporate social responsibility that take into account the firm’s ownership structure and there is no empirical evidence for Europe.
We examine a sample of 646 European firms during the period 2001-2003, and we frame the research question within a comprehensive typology of possible relationships between corporate social responsibility and ownership, which accommodates all of the arguments and empirical findings presented in the literature
sj-docx-1-imj-10.1177_10815589221140589 – Supplemental material for Comparison of outcome among type 2 vs type 1 myocardial infarction: a systematic review and meta-analysis
No full textSupplemental material, sj-docx-1-imj-10.1177_10815589221140589 for Comparison of outcome among type 2 vs type 1 myocardial infarction: a systematic review and meta-analysis by Vikash Jaiswal, Song Peng Ang, Angela Ishak, Yusra Minahil Nasir, Jia Ee Chia, Sidra Naz and Akash Jaiswal in Journal of Investigative Medicine</p
Correction: Gupta, P.; Jaiswal, P. Transcriptional Modulation During Photomorphogenesis in Rice Seedlings. Genes 2024, 15, 1072
No full textIn the original publication [...
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Influence of mechanical surface treatment on the strength of mixed adhesive joint
No full textAdhesive bonding is a promising joining technique in modern transport industries which provides for lightweight connection of dissimilar materials. However, available adhesive types have reached their limits in terms of durability and strength. A potential solution to this problem is the utilization of mixed adhesives. However, the influence of the surface preparation method on the performance of mixed adhesive joints has not been investigated thoroughly yet. The objective of this study is therefore to analyze such influence on the strength of mixed adhesive single lap joints. In this regard, five mechanical surface treatment methods were examined on aluminium alloy AA6082 using combinations of three different types of adhesives by means of static tensile tests. The results show significant increase in joint strength and ductility for DP 8005-AV138 compared to AV138 alone for sanding surface preparation. The roughness value in the range of Ra=1.7 to 3.1μm and Rm=36.5 to 44.60μm provide the highest shear strength
Effects of pressure gradient histories on skin friction and mean flow of high Reynolds number turbulent boundary layers over smooth and rough walls
No full textExperiments are conducted over smooth and rough walls to explore the influence of pressure gradient histories on skin friction and mean flow of turbulent boundary layers. Different pressure gradient histories are imposed on the boundary layer through an aerofoil mounted in the freestream. Hot-wire measurements are taken at different freestream velocities downstream of theaerofoil where the flow has locally recovered to zero pressure gradient but retains the history effects. Direct skin friction measurements are also made using oil film interferometry for smooth walls and a floating element drag balance for rough walls. The friction Reynolds number
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