Transport properties of fluids in nanochannels: bridging nano to macro

This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the Makedonia Palace Hotel, Thessaloniki in Greece. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, Aristotle University of Thessaloniki, University of Thessaly, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute.A method of calculating transport properties in nanochannels is presented in this work. The Molecular Dynamics simulation of a system of liquid argon flowing in a nanochannel formed by krypton walls was the basis for our analysis concerning transport properties and specifically diffusion coefficient, shear viscosity and thermal conductivity. It is shown that for confined systems, such as nanochannels, if one of the transport properties is known, then the others can be estimated. The simulation results reveal that all properties approach bulk values at relatively small channel widths, at about 6-7nm. Below this critical point, the wall effect on fluid atoms is strong and the transport properties change dramatically. In order to extend the calculations over rough-wall nanochannels, we apply the relation extracted for flat wall channels to channels with walls consisted of successive rectangular protrusions and cavities

Transport properties and structure of fluids in hydrophobic/hydrophilic nanochannels

This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.When downsizing towards the nanoscale, system dimensions have been found to affect channel flows mainly because of the presence of the walls that interact strongly with fluid particles. Parameters which are not taken into account at the classical theory continuum theory at the macroscale, should be taken into account at the nano or even micro-scale where the surface to volume ratio increases significantly. Such property is the wall/fluid interaction which determines the wetting (hydrophilic behavior) or not (hydrophobic behavior) of a surface. We first investigate the effect of wall/fluid interaction on fluid atom distribution near the wall through the radial distribution function and, next, we calculate the three most important fluid transport properties, i.e., the diffusion coefficient, shear viscosity and thermal conductivity. Transport properties seem to be affected significantly in the channel region adjacent to the wall

Prototyping the BOPTEST framework for simulation-based testing of advanced control strategies in buildings

Advanced control strategies are becoming increasingly necessary in buildings in order to meet and balance requirements for energy efficiency, demand flexibility, and occupant comfort. Additional development and widespread adoption of emerging control strategies, however, ultimately require low implementation costs to reduce payback period and verified performance to gain control vendor, building owner, and operator trust. This is difficult in an already first-cost driven and risk-averse industry. Recent innovations in building simulation can significantly aid in meeting these requirements and spurring innovation at early stages of development by evaluating performance, comparing state-of-the-art to new strategies, providing installation experience, and testing controller implementations. This paper presents the development of a simulation framework consisting of test cases and software platform for the testing of advanced control strategies (BOPTEST - Building Optimization Performance Test). The objectives and requirements of the framework, components of a test case, and proposed software platform architecture are described, and the framework is demonstrated with a prototype implementation and example test case

Impact of dietary organic acids and botanicals on intestinal integrity and inflammation in weaned pigs

BACKGROUND: Organic acids, such as citric and sorbic acid, and pure plant-derived constituents, like monoterpens and aldehydes, have a long history of use in pig feeding as alternatives to antibiotic growth promoters. However, their effects on the intestinal barrier function and inflammation have never been investigated. Therefore, aim of this study was to assess the impact of a microencapsulated mixture of citric acid and sorbic acid (OA) and pure botanicals, namely thymol and vanillin, (PB) on the intestinal integrity and functionality of weaned pigs and in vitro on Caco-2 cells. In the first study 20 piglets were divided in 2 groups and received either a basal diet or the basal diet supplemented with OA + PB (5 g/kg) for 2 weeks post-weaning at the end of which ileum and jejunum samples were collected for Ussing chambers analysis of trans-epithelial electrical resistance (TER), intermittent short-circuit current (I(SC)), and dextran flux. Scrapings of ileum mucosa were also collected for cytokine analysis (n = 6). In the second study we measured the effect of these compounds directly on TER and permeability of Caco-2 monolayers treated with either 0.2 or 1 g/l of OA + PB. RESULTS: Pigs fed with OA + PB tended to have reduced I(SC) in the ileum (P = 0.07) and the ileal gene expression of IL-12, TGF-β, and IL-6 was down regulated. In the in vitro study on Caco-2 cells, TER was increased by the supplementation of 0.2 g/l at 4, 6, and 14 days of the experiment, whereas 1 g/l increased TER at 10 and 12 days of treatment (P < 0.05). Dextran flux was not significantly affected though a decrease was observed at 7 and 14 days (P = 0.10 and P = 0.09, respectively). CONCLUSIONS: Overall, considering the results from both experiments, OA + PB improved the maturation of the intestinal mucosa by modulating the local and systemic inflammatory pressure ultimately resulting in a less permeable intestine, and eventually improving the growth of piglets prematurely weaned

Molecular dynamics pre-simulations for nanoscale computational fluid dynamics

We present a procedure for using molecular dynamics (MD) simulations to provide essential fluid and interface properties for subsequent use in computational fluid dynamics (CFD) calculations of nanoscale fluid flows. The MD pre-simulations enable us to obtain an equation of state, constitutive relations, and boundary conditions for any given fluid/solid combination, in a form that can be conveniently implemented within an otherwise conventional Navier–Stokes solver. Our results demonstrate that these enhanced CFD simulations are then capable of providing good flow field results in a range of complex geometries at the nanoscale. Comparison for validation is with full-scale MD simulations here, but the computational cost of the enhanced CFD is negligible in comparison with the MD. Importantly, accurate predictions can be obtained in geometries that are more complex than the planar MD pre-simulation geometry that provides the nanoscale fluid properties. The robustness of the enhanced CFD is tested by application to water flow along a (15,15) carbon nanotube, and it is found that useful flow information can be obtained

A water/ion separation device: theoretical and numerical investigation

An array of ion separation cells is presented in this work, to propose a novel desalination device. Molecular Dynamics simulations have been incorporated to establish the theoretical back-ground and calculate all parameters that could lead the manufacturing step. The main system component is an ion separation cell, in which water/NaCl solution flows due to an external pressure difference and ions are directed towards the non‐permeable walls under the effect of an electric field, with direction perpendicular to the flow. Clean water is gathered from the output, while the remaining, high‐concentration water/ion solution is re‐cycled in the cells. The strength of the electric field, cell dimensions, and wall/fluid interactions are investigated over a wide range, and shear viscosity and the volumetric flow rate are calculated for each case. © 2021 by the author. Licensee MDPI, Basel, Switzerland

Machine learning techniques for fluid flows at the nanoscale

Simulations of fluid flows at the nanoscale feature massive data production and machine learning (ML) techniques have been developed during recent years to leverage them, presenting unique results. This work facilitates ML tools to provide an insight on properties among molecular dynamics (MD) simulations, covering missing data points and predicting states not previously located by the simulation. Taking the fluid flow of a simple Lennard-Jones liquid in nanoscale slits as a basis, ML regression-based algorithms are exploited to provide an alternative for the calculation of transport properties of fluids, e.g., the diffusion coefficient, shear viscosity and thermal conductivity and the average velocity across the nanochannels. Through appropriate training and testing, MLpredicted values can be extracted for various input variables, such as the geometrical characteristics of the slits, the interaction parameters between particles and the flow driving force. The proposed technique could act in parallel to simulation as a means of enriching the database of material properties, assisting in coupling between scales, and accelerating data-based scientific computations. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Nanoscale slip length prediction with machine learning tools

This work incorporates machine learning (ML) techniques, such as multivariate regression, the multi-layer perceptron, and random forest to predict the slip length at the nanoscale. Data points are collected both from our simulation data and data from the literature, and comprise Molecular Dynamics simulations of simple monoatomic, polar, and molecular liquids. Training and test points cover a wide range of input parameters which have been found to affect the slip length value, concerning dynamical and geometrical characteristics of the model, along with simulation parameters that constitute the simulation conditions. The aim of this work is to suggest an accurate and efficient procedure capable of reproducing physical properties, such as the slip length, acting parallel to simulation methods. Non-linear models, based on neural networks and decision trees, have been found to achieve better performance compared to linear regression methods. After the model is trained on representative simulation data, it is capable of accurately predicting the slip length values in regions between or in close proximity to the input data range, at the nanoscale. Results also reveal that, as channel dimensions increase, the slip length turns into a size-independent material property, affected mainly by wall roughness and wettability. © 2021, The Author(s)