Computation of incompressible viscous flows through turbopump components

Flow through pump components, such as an inducer and an impeller, is efficiently simulated by solving the incompressible Navier-Stokes equations. The solution method is based on the pseudocompressibility approach and uses an implicit-upwind differencing scheme together with the Gauss-Seidel line relaxation method. the equations are solved in steadily rotating reference frames and the centrifugal force and the Coriolis force are added to the equation of motion. Current computations use a one-equation Baldwin-Barth turbulence model which is derived from a simplified form of the standard k-epsilon model equations. The resulting computer code is applied to the flow analysis inside a generic rocket engine pump inducer, a fuel pump impeller, and SSME high pressure fuel turbopump impeller. Numerical results of inducer flow are compared with experimental measurements. In the fuel pump impeller, the effect of downstream boundary conditions is investigated. Flow analyses at 80 percent, 100 percent, and 120 percent of design conditions are presented

Gene expression and metabolism in malignant hyperthermia susceptible and normal skeletal muscle

Malignant hyperthermia (MH) is an autosomal dominant, pharmacogenetic disorder primarily caused by RYR1 mutations which result in calcium dysregulation within skeletal muscle. Genetically susceptible individuals are at risk of potentially fatal hypermetabolic reactions when exposed to volatile anaesthetics and the muscle relaxant succinylcholine. MH susceptibility is diagnosed through the in vitro contracture test (IVCT) by challenging muscle biopsies with triggering agents, or by genetic screening for known familial mutations. Genome-wide gene expression was compared before and after IVCT, from MH-susceptible (MHS) and non-susceptible (MHN) skeletal muscle by RNA sequencing. A downregulation of genes related to oxidative phosphorylation (OXPHOS) was observed in MHS samples at baseline, suggesting a metabolic defect. Mitochondrial function was assessed by high resolution respirometry, measuring oxygen consumption rates in permeabilised muscle fibres. Results showed evidence of reduced OXPHOS capacity, complex II deficiency and increased mitochondrial content in MHS muscle at baseline. Exposure to halothane triggered a hypermetabolic response in MHS mitochondria which significantly increased oxygen consumption rates in several respiratory states, whilst MHN samples were unaltered. Genome-wide gene expression and mitochondrial function was also studied at baseline and after halothane challenge, using transgenic mouse models of MH to investigate RYR1 variant-specific effects. At baseline, fatty acid oxidation and mitochondria-related gene expression was downregulated in mice homozygous (HOM) for G2435R-RYR1 and heterozygous (HET) for T4826I-RYR1. In comparison to wild-type, mitochondria from G2435R-RYR1 HOM mice showed an increase in complex I-facilitated OXPHOS and reduced mitochondrial content at baseline. Mitochondria from transgenic mice also showed evidence of increased sensitivity to both halothane and calcium in comparison to wild-type. This study presents evidence of mitochondrial dysfunction in human and mouse MHS skeletal muscle, which is correlated with gene expression changes associated with oxidative metabolism. Functional defects in mitochondria are therefore potential contributors to phenotypic variability observed in MH

Adaptive Complex Contagions and Threshold Dynamical Systems

A broad range of nonlinear processes over networks are governed by threshold dynamics. So far, existing mathematical theory characterizing the behavior of such systems has largely been concerned with the case where the thresholds are static. In this paper we extend current theory of finite dynamical systems to cover dynamic thresholds. Three classes of parallel and sequential dynamic threshold systems are introduced and analyzed. Our main result, which is a complete characterization of their attractor structures, show that sequential systems may only have fixed points as limit sets whereas parallel systems may only have period orbits of size at most two as limit sets. The attractor states are characterized for general graphs and enumerated in the special case of paths and cycle graphs; a computational algorithm is outlined for determining the number of fixed points over a tree. We expect our results to be relevant for modeling a broad class of biological, behavioral and socio-technical systems where adaptive behavior is central.Comment: Submitted for publicatio

Floating architecture for a dynamic society: water as a media to explore flexibility

Qualificació obtinguda: 9 Màster universitari en Disseny -- Contemporary Desig

Stimulating Critical Thinking in U.S Business Students through the Inclusion of International Students

Students enroll in college with different expectations, aptitudes, and cultural backgrounds. Research supports the need for faculty to create an atmosphere where students feel comfortable discussing cultural sensitive issues. As the business world is becoming more global, critical thinking and the ability to form and articulate thoughts proficiently have become essential competencies for effective communication in all avenues of life. Discussion and Multicultural Education as methods of teaching have the potential in aiding the development of critical thinking skills of students. Moreover, students’ intellectual progress by means of the discussions enhances from critically evaluating views from global perspectives. This paper provides an argument as to the importance of faculty being knowledgeable of the cultural and sociopolitical history of international students to better foster a classroom climate of respect to ensure that the discussion perspectives from all students are inclusive and value

Functional characterization and discovery of modulators of SbMATE, the agronomically important aluminium tolerance transporter from Sorghum bicolor.

About 50% of the world's arable land is strongly acidic (pH ≤ 5). The low pH solubilizes root-toxic ionic aluminium (Al3+) species from clay minerals, driving the evolution of counteractive adaptations in cultivated crops. The food crop Sorghum bicolor upregulates the membrane-embedded transporter protein SbMATE in its roots. SbMATE mediates efflux of the anionic form of the organic acid, citrate, into the soil rhizosphere, chelating Al3+ ions and thereby imparting Al-resistance based on excluding Al+3 from the growing root tip. Here, we use electrophysiological, radiolabeled, and fluorescence-based transport assays in two heterologous expression systems to establish a broad substrate recognition profile of SbMATE, showing the proton and/or sodium-driven transport of 14C-citrate anion, as well as the organic monovalent cation, ethidium, but not its divalent analog, propidium. We further complement our transport assays by measuring substrate binding to detergent-purified SbMATE protein. Finally, we use the purified membrane protein as an antigen to discover native conformation-binding and transport function-altering nanobodies using an animal-free, mRNA/cDNA display technology. Our results demonstrate the utility of using Pichia pastoris as an efficient eukaryotic host to express large quantities of functional plant transporter proteins. The nanobody discovery approach is applicable to other non-immunogenic plant proteins

Incompressible Navier-Stokes Calculations in Pump Flows

Flow through pump components, such as the SSME-HPFTP Impeller and an advanced rocket pump impeller, is efficiently simulated by solving the incompressible Navier-Stokes equations. The solution method is based on the pseudo compressibility approach and uses an implicit-upwind differencing scheme together with the Gauss-Seidel line relaxation method. The equations are solved in steadily rotating reference frames and the centrifugal force and the Coriolis force are added to the equation of motion. Current computations use one-equation Baldwin-Barth turbulence model which is derived from a simplified form of the standard k-epsilon model equations. The resulting computer code is applied to the flow analysis inside an 11-inch SSME High Pressure Fuel Turbopump impeller, and an advanced rocket pump impeller. Numerical results of SSME-HPFTP impeller flow are compared with experimental measurements. In the advanced pump impeller, the effects of exit and shroud cavities are investigated. Flow analyses at design conditions will be presented

Tracking specialized T cell subsets Following Immunization Based on Fluorescent Reporter Protein

The intestine relies upon T regulatory and effector cells to regulate immune response to multiple antigens. A full understanding of this phenomenon would be significant in the treatment of food intolerance and inflammatory bowel diseases (IBDs). The role of Retinoic Acid (RA) in T-cell migration to the gut is well documented. However, the distribution of tissues where this exposure to RA occurs has not been extensively mapped. In order to determine this, the cre-lox system was used to engineer a RA-responsive reporter gene that expresses the fluorescent protein tdTomato following RA exposure. The tissues were then imaged and analyzed using histo-cytometry to determine distribution of cells with RA exposure. RA exposure in various tissue microenvironments was characterized using flow cytometry, PCR, and confocal microscopy imaging to determine the changes in lymphoid expression of tdTomato during immune activation. It was found that intestinal and lymphoid tissues had greater concentrations of cells with prior RA exposure, particularly the Peyer’s Patch, MLN, and Spleen. The preliminary results of these experiments indicate that immune activation leads to a higher density of tdTomato expressing cells in the intestine and lymphoid tissues, but lower in peripheral organs. These results indicate that immunization causes T-cells to be drawn out of peripheral tissues and into gut-associated lymphoid tissues. It is worth looking into the composition of these T-cells as compared to the base population

A Deep Learning Based Model for Driving Risk Assessment

In this paper a novel multilayer model is proposed for assessing driving risk. Studying aggressive behavior via massive driving data is essential for protecting road traffic safety and reducing losses of human life and property in smart city context. In particular, identifying aggressive behavior and driving risk are multi-factors combined evaluation process, which must be processed with time and environment. For instance, improper time and environment may facilitate abnormal driving behavior. The proposed Dynamic Multilayer Model consists of identifying instant aggressive driving behavior that can be visited within specific time windows and calculating individual driving risk via Deep Neural Networks based classification algorithms. Validation results show that the proposed methods are particularly effective for identifying driving aggressiveness and risk level via real dataset of 2129 drivers’ driving behavior