Experimental results on gravity driven fully condensing flows in vertical tubes, their agreement with theory, and their differences with shear driven flows' boundary-condition sensitivities

This doctoral thesis presents the experimental results along with a suitable synthesis with computational/theoretical results towards development of a reliable heat transfer correlation for a specific annular condensation flow regime inside a vertical tube. For fully condensing flows of pure vapor (FC-72) inside a vertical cylindrical tube of 6.6 mm diameter and 0.7 m length, the experimental measurements are shown to yield values of average heat transfer co-efficient, and approximate length of full condensation. The experimental conditions cover: mass flux G over a range of 2.9 kg/m2-s ≤ G ≤ 87.7 kg/m2-s, temperature difference ∆T (saturation temperature at the inlet pressure minus the mean condensing surface temperature) of 5 ºC to 45 ºC, and cases for which the length of full condensation xFC is in the range of 0 < xFC < 0.7 m. The range of flow conditions over which there is good agreement (within 15%) with the theory and its modeling assumptions has been identified. Additionally, the ranges of flow conditions for which there are significant discrepancies (between 15 -30% and greater than 30%) with theory have also been identified. The paper also refers to a brief set of key experimental results with regard to sensitivity of the flow to time-varying or quasi-steady (i.e. steady in the mean) impositions of pressure at both the inlet and the outlet. The experimental results support the updated theoretical/computational results that gravity dominated condensing flows do not allow such elliptic impositions.

Analyzing the effects of vertical acceleration and deceleration in multi-phase, debris-flow sediment-column experiments / by Christine Marie Williams.

Water-saturated debris flows are among some of the most destructive mass movements. Their complex nature presents a challenge for quantitative description and modeling. In order to improve understanding of the dynamics of these flows, it is important to seek a simplified dynamic system underlying their behavior. Models currently in use to describe the motion of debris flows employ depth-averaged equations of motion, typically assuming negligible effects from vertical acceleration. However, in many cases debris flows experience significant vertical acceleration as they move across irregular surfaces, and it has been proposed that friction associated with vertical forces and liquefaction merit inclusion in any comprehensive mechanical model. The intent of this work is to determine the effect of vertical acceleration through a series of laboratory experiments designed to simulate debris flows, testing a recent model for debris flows experimentally. In the experiments, a mass of water-saturated sediment is released suddenly from a holding container, and parameters including rate of collapse, pore-fluid pressure, and bed load are monitored. Experiments are simplified to axial geometry so that variables act solely in the vertical dimension. Steady state equations to infer motion of the moving sediment mass are not sufficient to model accurately the independent solid and fluid constituents in these experiments. The model developed in this work more accurately predicts the bed-normal stress of a saturated sediment mass in motion and illustrates the importance of acceleration and deceleration.

Mechanisms contributing to the deep chlorophyll maximum in Lake Superior

The seasonal appearance of a deep chlorophyll maximum (DCM) in Lake Superior is a striking phenomenon that is widely observed; however its mechanisms of formation and maintenance are not well understood. As this phenomenon may be the reflection of an ecological driver, or a driver itself, a lack of understanding its driving forces limits the ability to accurately predict and manage changes in this ecosystem. Key mechanisms generally associated with DCM dynamics (i.e. ecological, physiological and physical phenomena) are examined individually and in concert to establish their role. First the prevailing paradigm, “the DCM is a great place to live”, is analyzed through an integration of the results of laboratory experiments and field measurements. The analysis indicates that growth at this depth is severely restricted and thus not able to explain the full magnitude of this phenomenon. Additional contributing mechanisms like photoadaptation, settling and grazing are reviewed with a one-dimensional mathematical model of chlorophyll and particulate organic carbon. Settling has the strongest impact on the formation and maintenance of the DCM, transporting biomass to the metalimnion and resulting in the accumulation of algae, i.e. a peak in the particulate organic carbon profile. Subsequently, shade adaptation becomes manifest as a chlorophyll maximum deeper in the water column where light conditions particularly favor the process. Shade adaptation mediates the magnitude, shape and vertical position of the chlorophyll peak. Growth at DCM depth shows only a marginal contribution, while grazing has an adverse effect on the extent of the DCM. The observed separation of the carbon biomass and chlorophyll maximum should caution scientists to equate the DCM with a large nutrient pool that is available to higher trophic levels. The ecological significance of the DCM should not be separated from the underlying carbon dynamics. When evaluated in its entirety, the DCM becomes the projected image of a structure that remains elusive to measure but represents the foundation of all higher trophic levels. These results also offer guidance in examine ecosystem perturbations such as climate change. For example, warming would be expected to prolong the period of thermal stratification, extending the late summer period of suboptimal (phosphorus-limited) growth and attendant transport of phytoplankton to the metalimnion. This reduction in epilimnetic algal production would decrease the supply of algae to the metalimnion, possibly reducing the supply of prey to the grazer community. This work demonstrates the value of modeling to challenge and advance our understanding of ecosystem dynamics, steps vital to reliable testing of management alternatives.

Multi-software modeling technique for field distribution propagation through an optical vertical interconnect assembly

Embedded siloxane polymer waveguides have shown promising results for use in optical backplanes. They exhibit high temperature stability, low optical absorption, and require common processing techniques. A challenging aspect of this technology is out-of-plane coupling of the waveguides. A multi-software approach to modeling an optical vertical interconnect (via) is proposed. This approach utilizes the beam propagation method to generate varied modal field distribution structures which are then propagated through a via model using the angular spectrum propagation technique. Simulation results show average losses between 2.5 and 4.5 dB for different initial input conditions. Certain configurations show losses of less than 3 dB and it is shown that in an input/output pair of vias, average losses per via may be lower than the targeted 3 dB.

Estimation of vertical groundwater fluxes into a streambed through continuous temperature profile monitoring and the relationship of groundwater fluxes to coaster brook trout spawning habitat

We hypothesized that the spatial distribution of groundwater inflows through river bottom sediments is a critical factor associated with the selection of coaster brook trout (a life history variant of Salvelinus fontinalis,) spawning sites. An 80-m reach of the Salmon Trout River, in the Huron Mountains of the upper peninsula of Michigan, was selected to test the hypothesis based on long-term documentation of coaster brook trout spawning at this site. Throughout this site, the river is relatively similar along its length with regard to stream channel and substrate features. A monitoring well system consisting of an array of 27 wells was installed to measure subsurface temperatures underneath the riverbed over a 13-month period. The monitoring well locations were separated into areas where spawning has and has not been observed. Over 200,000 total temperature measurements were collected from 5 depths within each of the 27 monitoring wells. Temperatures within the substrate at the spawning area were generally cooler and less variable than river temperatures. Substrate temperatures in the non-spawning area were generally warmer, more variable, and closely tracked temporal variations in river temperatures. Temperature data were inverted to obtain subsurface groundwater velocities using a numerical approximation of the heat transfer equation. Approximately 45,000 estimates of groundwater velocities were obtained. Estimated velocities in the spawning and non-spawning areas confirmed that groundwater velocities in the spawning area were primarily in the upward direction, and were generally greater in magnitude than velocities in the non-spawning area. In the non-spawning area there was a greater occurrence of velocities in the downward direction, and velocity estimates were generally lesser in magnitude than in the spawning area. Both the temperature and velocity results confirm the hypothesis that spawning sites correspond to areas of significant groundwater influx to the river bed.

Genetic association studies under the population stratification, family pedigree and application to genome-wide association studies

This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.