Heat Transfer Performance and Piping Strategy Study for Chilled Water Systems at Low Cooling Loads

The temperature differential of chilled water is an important factor used for evaluating the performance of a chilled water system. A low delta-T may increase the pumping energy consumption and increase the chiller energy consumption. The system studied in this thesis is the chilled water system at the Dallas/Fort Worth International Airport (DFW Airport). This system has the problem of low delta-T under low cooling loads. When the chilled water flow is much lower than the design conditions at low cooling loads, it may lead to the laminar flow of the chilled water in the cooling coils. The main objective of this thesis is to explain the heat transfer performance of the cooling coils under low cooling loads. The water side and air side heat transfer coefficients at different water and air flow rates are calculated. The coefficients are used to analyze the heat transfer performance of the cooling coils at conditions ranging from very low loads to design conditions. The effectiveness-number of transfer units (NTU) method is utilized to analyze the cooling coil performance under different flow conditions, which also helps to obtain the cooling coil chilled water temperature differential under full load and partial load conditions. When the water flow rate drops to 1ft/s, laminar flow occurs; this further decreases the heat transfer rate on the water side. However, the cooling coil effectiveness increases with the drop of water flow rate, which compensates for the influence of the heat transfer performance under laminar flow conditions. Consequently, the delta-T in the cooling coil decreases in the transitional flow regime but increases in the laminar flow regime. Results of this thesis show that the laminar flow for the chilled water at low flow rate is not the main cause of the low delta-T syndrome in the chilled water system. Possible causes for the piping strategy of the low delta-T syndrome existing in the chilled water system under low flow conditions are studied in this thesis: (1) use of two way control valves; and (2) improper tertiary pump piping strategy

High-pressure pool boiling and physical insight of engineered surfaces

Doctor of PhilosophyDepartment of Mechanical and Nuclear EngineeringAmy R. BetzBoiling is a very effective way of heat transfer due to the latent heat of vaporization. Large amount of heat can be removed as bubbles form and leave the heated surface. Boiling heat transfer has lots of applications both in our daily lives and in the industry. The performance of boiling can be described with two important parameters, i.e. the heat transfer coefficient (HTC) and the critical heat flux (CHF). Enhancing the performance of boiling will greatly increase the efficiency of thermal systems, decrease the size of heat exchangers, and improve the safety of thermal facilities. Boiling heat transfer is an extremely complex process. After over a century of research, the mechanism for the HTC and CHF enhancement is still elusive. Previous research has demonstrated that fluid properties, system pressures, surface properties, and heater properties etc. have huge impact on the performance of boiling. Numerous methods, both active and passive, have been developed to enhance boiling heat transfer. In this work, the effect of pressure was investigated on a plain copper substrate from atmospheric pressure to 45 psig. Boiling heat transfer performance enhancement was then investigated on Teflon© coated copper surfaces, and graphene oxide coated copper surfaces under various system pressures. It was found that both HTC and CHF increases with the system pressure on all three types of surfaces. Enhancement of HTC on the Teflon© coated copper surface is contributed by the decrease in wettability. It is also hypothesized that the enhancement in both HTC and CHF on the graphene oxide coated surface is due to pinning from micro and nanostructures in the graphene oxide coating or non-homogeneous wettability. Condensation and freezing experiments were conducted on engineered surfaces in order to further characterize the pinning effect of non-homogeneous wettability and micro/nano structure of the surface

LIVE, ATTENUATED VACCINES AND METHODS OF MAKING AND USING

A live, attenuated HIV vaccine is provided, and methods of making a atenuated HIV vaccine are provided

Sum-Rate Maximization for Movable Antenna Enabled Multiuser Communications

A novel multiuser communication system with movable antennas (MAs) is proposed, where the antenna position optimization is exploited to enhance the downlink sum-rate. The joint optimization of the transmit beamforming vector and transmit MA positions is studied for a multiuser multiple-input single-input system. An efficient algorithm is proposed to tackle the formulated non-convex problem via capitalizing on fractional programming, alternating optimization, and gradient descent methods. To strike a better performance-complexity trade-off, a zero-forcing beamforming-based design is also proposed as an alternative. Numerical investigations are presented to verify the efficiency of the proposed algorithms and their superior performance compared with the benchmark relying on conventional fixed-position antennas (FPAs).Comment: 11 page

High-Q-factor Al [subscript 2]O[subscript 3] micro-trench cavities integrated with silicon nitride waveguides on silicon

We report on the design and performance of high-Q integrated optical micro-trench cavities on silicon. The microcavities are co-integrated with silicon nitride bus waveguides and fabricated using wafer-scale silicon-photonics-compatible processing steps. The amorphous aluminum oxide resonator material is deposited via sputtering in a single straightforward post-processing step. We examine the theoretical and experimental optical properties of the aluminum oxide micro-trench cavities for different bend radii, film thicknesses and near-infrared wavelengths and demonstrate experimental Q factors of > 10[superscript 6]. We propose that this high-Q micro-trench cavity design can be applied to incorporate a wide variety of novel microcavity materials, including rare-earth-doped films for microlasers, into wafer-scale silicon photonics platforms

Movable Antenna-Empowered AirComp

A novel over-the-air computation (AirComp) framework, empowered by the incorporation of movable antennas (MAs), is proposed to significantly enhance computation accuracy. Within this framework, the joint optimization of transmit power control, antenna positioning, and receive combining is investigated. An efficient method is proposed to tackle the problem of computation mean-squared error (MSE) minimization, capitalizing on the approach of alternating optimization. Numerical results are provided to substantiate the superior MSE performance of the proposed framework, which establish its clear advantage over benchmark systems employing conventional fixed-position antennas (FPAs)

Genomic Prediction of Breeding Values Using a Subset of SNPs Identified by Three Machine Learning Methods

The analysis of large genomic data is hampered by issues such as a small number of observations and a large number of predictive variables (commonly known as “large P small N”), high dimensionality or highly correlated data structures. Machine learning methods are renowned for dealing with these problems. To date machine learning methods have been applied in Genome-Wide Association Studies for identification of candidate genes, epistasis detection, gene network pathway analyses and genomic prediction of phenotypic values. However, the utility of two machine learning methods, Gradient Boosting Machine (GBM) and Extreme Gradient Boosting Method (XgBoost), in identifying a subset of SNP makers for genomic prediction of breeding values has never been explored before. In this study, using 38,082 SNP markers and body weight phenotypes from 2,093 Brahman cattle (1,097 bulls as a discovery population and 996 cows as a validation population), we examined the efficiency of three machine learning methods, namely Random Forests (RF), GBM and XgBoost, in (a) the identification of top 400, 1,000, and 3,000 ranked SNPs; (b) using the subsets of SNPs to construct genomic relationship matrices (GRMs) for the estimation of genomic breeding values (GEBVs). For comparison purposes, we also calculated the GEBVs from (1) 400, 1,000, and 3,000 SNPs that were randomly selected and evenly spaced across the genome, and (2) from all the SNPs. We found that RF and especially GBM are efficient methods in identifying a subset of SNPs with direct links to candidate genes affecting the growth trait. In comparison to the estimate of prediction accuracy of GEBVs from using all SNPs (0.43), the 3,000 top SNPs identified by RF (0.42) and GBM (0.46) had similar values to those of the whole SNP panel. The performance of the subsets of SNPs from RF and GBM was substantially better than that of evenly spaced subsets across the genome (0.18–0.29). Of the three methods, RF and GBM consistently outperformed the XgBoost in genomic prediction accuracy

Probiotic Lactobacillus rhamnosus GR-1 supplementation attenuates Pb-induced learning and memory deficits by reshaping the gut microbiota

Lead (Pb) exposure during early life has been associated with an increased risk of neurodevelopmental disorders, including learning and memory deficits. The intestinal flora, via the microbiome–gut–brain axis, could play a significant role in the nervous system. However, the effects of probiotics on ameliorating Pb-induced learning and memory deficits are still unclear. In this study, we showed that adolescent Pb exposure (150 ppm) for 2 months impaired spatial learning and memory ability, accompanied by the decreasing diversity of gut microbiota, and the decreasing abundance of Lactobacillus at the genus level. Surprisingly, administration of the Lactobacillus rhamnosus GR-1 (1010 organisms/rat/day), not L. rhamnosus LGG or Lactobacillus reuteri RC-14, reversed learning and memory deficits induced by Pb exposure. Meanwhile, administration of the L. rhamnosus GR-1 increased the diversity of the gut microbiota composition and partially normalized the genus level of Lactobacillus, Parabacteroides, Enterococcus, and Akkermansia in Pb-exposed rats. Notably, supplementation of L. rhamnosus GR-1 decreased the gut permeability of Pb-exposed rats, reduced proinflammatory cytokines [interleukin-1β (IL-1β) and IL-6] expression, and promoted anti-inflammatory cytokines [granulocyte colony-stimulating factor (G-CSF)] expression. Interestingly, neural cell treatment with G-CSF rescued Pb-induced neurotoxicity. In general, L. rhamnosus GR-1 supplementation recovered the Pb-induced loss of intestinal bacteria (Lactobacillus), which may have reversed the damage to learning and memory ability. Collectively, our findings demonstrate an unexpectedly pivotal role of L. rhamnosus GR-1 in Pb-induced cognitive deficits and identify a potential probiotic therapy for cognitive dysfunction during early life