A Comparison Between Recent Experimental Results and Existing Correlations for Microfin Tubes for Refrigerant and Nanolubricants Mixtures Two Phase Flow Boiling

Driven by higher energy efficiency targets, there is critical need for major heat transfer enhancements in heat exchangers. Nanolubricants, that is, nanoparticles dispersed in the non-volatile component of a mixture, have the potential to increase the heat transfer coefficient by 20% or more for two-phase flow boiling with small or no penalization on the two-phase flow pressure drop. The present work builds upon these intriguing yet unexplained findings, which were documented in the experiments of the present study for one type of nanolubricant, but for which a theory still does not exist. This paper presents a comparison between existing models in the literature and recent new experimental data for two phase flow boiling in a microfin tube of refrigerant R410A and nanolubricants mixtures. Alumina Oxide (g-Al2O3) based nanolubricants with 40 nominal particle diameter of approximately spherical shape were investigated. The nanoparticles concentration in the lubricant varied from 10 to about 20 in mass percentage, and the lubricant concentration varied from 0 up to 3% in mass percentage. The models available in the open domain literature were not able to capture the effects of the nanoparticles on the two-phase flow heat transfer coefficient. The augmented thermal conductivity of the lubricant due to the addition of highly conductive nanoparticles was not the main mechanism responsible for the heat transfer enhancements. The discrepancy between the simulation results and the experimental data was postulated to be due to non-Newtonian behaviors due to the presence of nanoparticles and surfactants. The flow development of the liquid phase of the mixture and the localized thickening and thinning of the liquid film thickness around the inner walls of the tube can alter the film local convective thermal resistance.

Stimulation of phosphoinositide hydrolysis via class I antigen-specific recognition in murine cardiac tissue

AbstractInduction of polyphosphoinositide hydrolysis in cardiac tissue by specific recognition of class I histocompatibility antigens was assayed. C3H (H-2k) mice auricles were labelled with myo-3H]inositol precursor and inositol phosphate production in the presence or absence of anti-class I k products was measured. Anti-class I, but not anti-class II products specifically increased phosphoinositide turnover. This increment was partially blocked by muscarinic cholinergic and α-adrenergic blockers and even more so by the phospholipase C inhibitor NCDC. Alloantibodies specifically directed against class I antigens could then exert stimulation of phospholipase C-mediated phosphoinositide hydrolysis through the interaction with muscarinic cholinergic and/or α-adrenergic receptors. The induction of intracellular second messengers by class I antigens and hormone-receptor interactions is discussed

Hyperbolicity of link complements in Seifert-fibered spaces

Let (gamma) over bar be a link in a Seifert-fibered space M over a hyperbolic 2 -orbifold O that projects injectively to a filling multicurve of closed geodesics gamma in O. We prove that the complement M-(gamma) over bar of (gamma) over bar in M admits a hyperbolic structure of finite volume, and we give combinatorial bounds of its volume.Peer reviewe

Bayesian modeling and clustering for spatio-temporal areal data: an application to Italian unemployment

Spatio-temporal areal data can be seen as a collection of time series which are spatially correlated according to a specific neighboring structure. Incorporating the temporal and spatial dimension into a statistical model poses challenges regarding the underlying theoretical framework as well as the implementation of efficient computational methods. We propose to include spatio-temporal random effects using a conditional autoregressive prior, where the temporal correlation is modeled through an autoregressive mean decomposition and the spatial correlation by the precision matrix inheriting the neighboring structure. Their joint distribution constitutes a Gaussian Markov random field, whose sparse precision matrix enables the usage of efficient sampling algorithms. We cluster the areal units using a nonparametric prior, thereby learning latent partitions of the areal units. The performance of the model is assessed via an application to study regional unemployment patterns in Italy. When compared to other spatial and spatio-temporal competitors, the proposed model shows more precise estimates and the additional information obtained from the clustering allows for an extended economic interpretation of the unemployment rates of the Italian provinces

Thermodynamic and Heat Transfer Properties of Al2O3 Nanolubricants

In vapor compression cycles, a small portion of the oil circulates with the refrigerant throughout the system components, while most of the oil stays in the compressors. In heat exchangers, the lubricant in excess penalizes the heat transfer and increases the pressure losses: both effects are highly undesired but yet unavoidable. Nanoparticles dispersed in the excess lubricant are expected to provide enhancements in heat transfer. While solubility and miscibility of refrigerants in polyolesters (POE) lubricant are well established knowledge there is a lack of information regarding if and how nanoparticles dispersed in the lubricant affect these two properties. This paper presents experimental data of solubility and miscibility of three types of Al2O3 nanolubricants with refrigerant R410A. The nanoparticles were dispersed in POE lubricant by using different surfactants and dispersion methods and the nanolubricants showed lower refrigerant R410A solubility than that of POE oil. High viscosity suspensions are expected to stabilize the nanoparticles and avoid clustering. This aspect was verified in the present paper for the Al2O3 nanolubricants and long term stability and the degree of agglomeration, when present, were measured. The data identified optimum combinations of surfactants to achieve stable and uniform nanolubricant dispersions for several months. Surfactants affected slightly the thermal conductivity, specific heat, viscosity, and solubility properties of the nanolubricants. The specific heats of the nanolubricants were lower than that of POE oil at temperatures from 0 to 20°C while they were similar at 40°C. Thermal conductivity ranged from 1.1 times higher at 5°C to 1.4 times higher at 40°C than that of POE lubricant. The viscosity was about 2.6 times higher at 5°C while it was similar to that of POE lubricant at 40°C. The thermal and transport properties data for three nanolubricants provided in this paper advance the basic understanding of nanoparticles interaction with R410A refrigerant and POE lubricant mixtures

Modeling of Lubricant Effects in a Microchannel Type Condenser

In HVAC and refrigeration systems, a small portion of the oil circulates with the refrigerant flow through the cycle components, while most of the oil stays in the compressor. The circulating oil can form a fairly homogeneous mixture with the liquid refrigerant, or it can exist as a separate oil-rich film inside the small tubes and headers of a microchannel heat exchanger; the amount of oil held up is affected by the system conditions. The oil retention in the microchannel type condenser is of particular interest as the amount of oil in excess in this component affects the heat transfer capacity and increases the frictional pressure losses. This paper presents a new physics-based model of the oil retention in microchannel-type condensers. The model calculates the local thermodynamic properties in each section for the refrigerant R-410A and Polyester (POE) oil mixture based on the local oil concentration, pressure, temperature, and mass flux. Then the model, which was experimentally validated, predicts the refrigerant-side heat transfer coefficient and pressure drop. The simulation results indicated that the pressure losses increased by over 20% when the oil mass flow rate fraction increased up to 5 weight percent. The augmented mixture viscosity resulted in high frictional pressure drops and shear stress during the two phase flow condensation. The refrigerant side correlations were validated against literature data for in-tube two-phase flow condensation but further investigation is needed for the single-phase annular type flow in microchannel with refrigerant vapor and oil. At low degree of superheat the heat transfer coefficient of the refrigerant and oil mixture was basically unaffected by the oil mass fraction up to 3 weight percent. When the oil mass fraction was higher than 3 weight percent, then the heat transfer capacity of the condenser decreased. At high degree of superheat, the heat transfer coefficient of the oil and refrigerant mixture was penalized when the Oil Mass Fraction (OMF) was higher than 2 weight percent. Further investigation is needed on the suitability and accuracy of the heat transfer coefficients correlations to be adopted with superheated vapor refrigerant and lubricant film in annular flow at the inlet section of the microchannel type condenser

STILTool: a Semantic Table Interpretation evaLuation Tool

This paper describes STILTool, an open-source tool for the automatic evaluation of the quality of semantic annotations computed by semantic table interpretation approaches. STILTool provides a graphical interface allowing users to analyse the correctness of the annotations of tabular data. The tool also provides a set of statistics in order to identify the most common error patterns

Building on an oasis in Garamantian times: geoarchaeological investigation on mud architectural elements from the excavation of Fewet (Central Sahara, SW Libya)

The paper describes the micromorphological and mineralogical properties of earthen architectural elements from the excavation of the Garamantian compound of Fewet (Central Sahara, SW Libya), settled between the 2nd century BC and the 1st century AD, and compares this evidence with a set of samples from historical to modern context of Saharan and Sub-Saharan Africa. At Fewet, the production of mud bricks, plasters, and mortars employed in the building of the compound required raw materials available near the settlement. The earthen elements lack almost completely clay and organic temper, and their main components are quartz grains (sandy to silty) and a calcareous and slightly organic mud, available beside former springs. Only plaster and mortars show the addition (in limited quantity) of finely subdivided vegetal remains to the mixture. The technology for earthen elements used in Garamantian times resembles those today applied at many localities in Sub-Saharan Africa. Finally, our analyses showed that in the last millennia archaeological sediments underwent limited postdepositional weathering, mostly related to solute redistribution after occasional rainfalls. Today, the same process affects traditional mud brick buildings

Bayesian clustering of multiple zero-inflated outcomes

Several applications involving counts present a large proportion of zeros (excess-of-zeros data). A popular model for such data is the hurdle model, which explicitly models the probability of a zero count, while assuming a sampling distribution on the positive integers. We consider data from multiple count processes. In this context, it is of interest to study the patterns of counts and cluster the subjects accordingly. We introduce a novel Bayesian approach to cluster multiple, possibly related, zero-inflated processes. We propose a joint model for zero-inflated counts, specifying a hurdle model for each process with a shifted Negative Binomial sampling distribution. Conditionally on the model parameters, the different processes are assumed independent, leading to a substantial reduction in the number of parameters as compared with traditional multivariate approaches. The subject-specific probabilities of zero-inflation and the parameters of the sampling distribution are flexibly modelled via an enriched finite mixture with random number of components. This induces a two-level clustering of the subjects based on the zero/non-zero patterns (outer clustering) and on the sampling distribution (inner clustering). Posterior inference is performed through tailored Markov chain Monte Carlo schemes. We demonstrate the proposed approach on an application involving the use of the messaging service WhatsApp. This article is part of the theme issue 'Bayesian inference: challenges, perspectives, and prospects'