Characterization of the Ejector Pump Performance for the Assisted Bidirectional Glenn Procedure

This study introduces an algebraic model informed by computational fluid dynamics (CFD) simulations to investigate the performance of the assisted bidirectional Glenn (ABG) operation on a broad range of conditions. The performance of this operation, as measured by the superior vena cava (SVC) pressure, depends on the nozzle area in its ejector pump and the patient’s pulmonary vascular resistance (PVR). Using the developed algebraic model to explore this two-dimensional parameter space shows that the ejector pump can create a pressure difference between the pulmonary artery and the SVC as high as 5 mmHg. The lowest SVC pressure is produced at a nozzle area that decreases linearly with the PVR such that, at PVR =4.2 (Wood units-m2), there is no added benefit in utilizing the ejector pump effect (optimal nozzle area is zero, corresponding to the bidirectional Glenn circulation). At PVR =2 (Wood units-m2), the SVC pressure can be lowered to less than 4 mmHg by using an optimal nozzle area of ≈2.5 mm2. Regardless of the PVR, adding a 2 mm2 nozzle to the baseline bidirectional Glenn boosts the oxygen saturation and delivery by at least 15%. The SVC pressure for that 2 mm2 nozzle remains below 14 mmHg for all PVRs less than 7 Wood units-m2. The mechanical efficiency of the optimal designs consistently remains below 30%, indicating the potential for improvement in the future. A good agreement is observed between the algebraic model and high-fidelity CFD simulations.

Markov chains to determine the probability of climate change for planting selection in the city of Caxias do Sul

ABSTRACT: The Markov stochastic chain model and the analytical hierarchy process (AHP) were used as tools to support decision-making for the best crop-planting choice in the city of Caxias do Sul, Brazil. Temperature and precipitation information were collected from the Meteorological Database for Teaching and Research of the National Institute of Meteorology of Brazil for the period 1997-2017. The stochastic model was applied to obtain the probability of transition between a range of variations for temperature and precipitation. In the second phase of the study, an algebraic model was developed, making it possible to link the probability of the Markov chain transition matrix to the AHP judgment matrix. In the third phase, the AHP was applied as a tool to determine the most beneficial crop that could be planted for the studied city, considering the evaluated criteria: temperature, precipitation, and soil pH. The alternatives for crop planting were carrots, tomatoes, apples, and grapes. These were chosen because they are the most-planted crops in the city of Caxias do Sul. The ranking of the benefit-force results of applying the model for spring was carrots (0.297), apples (0.259), grapes (0.228), and tomatoes (0.215); for summer: grapes (0.261), tomatoes (0.261), apples (0.238), and carrots (0.230); for autumn: carrots (0.316), grapes (0.243), tomatoes (0.228), and apples (0.213); and for winter: carrots (0.327), tomatoes (0.235), apples (0.222), and grapes (0.216). Thus, it was concluded that farmers would have a better chance of success if they planted carrots during the spring, autumn, and winter, and grapes during the summer.

Overtone Frequencies of NO2 using Lie algebraic model

In this paper, we used the one dimensional unitatry Lie algebraic model to compute the vibrational frequencies of nitrogen dioxide (NO2) molecule in the gas phase up to the sixth overtone. In this model, the Hamiltonian operator describes the stretching and bending vibrations with algebraic parameters. The calculated fundamental vibrational frequencies are compared with experimental values and results consistent with the reference values.

Quantum protocols at presence of nonabelian superselection rules in the framework of algebraic model

In this paper, we study the influence of nonabelian superselection rules on the transfer of quantum information with the help of qubits on the base of an algebraic model and formulate quantum protocols. We pay the main attention to the superselection structure of the algebra of observables [Formula: see text] defined by the Cuntz algebra [Formula: see text] (a field algebra) that contains [Formula: see text] as a pointwise fixed subalgebra with respect to the action of the gauge group [Formula: see text]. We prove that it is possible to code information only with the help of states such that projectors on them belong to the algebra of observables. These projectors commute with the elements of the representation of the group [Formula: see text], and therefore allow the recipient to restore the obtained information.

Numerical Infeasibilities of Nanofibrous Mats Process Design

A new computer-aided method to design electrospun, nanofibrous mats was implemented and tested. In this work, the standard nonlinear algebraic model led to the terminal fiber diameter FD being examined in detail. The analysis was performed in terms of numerical feasibility. The study specified the limit value of the axial length scale, parameter χ, that determined valid solutions. The presented approach has vast practical potential (i.e., biomedical applications, air/water purification systems, fire protection and solar industries).

Dynamic Nonlinear Algebraic Models With Scale-Similarity Dynamic Procedure For Large-Eddy Simulation of Turbulence

A dynamic nonlinear algebraic model with scale-similarity dynamic procedure (DNAM-SSD) is proposed for subgrid-scale (SGS) stress in large-eddy simulation of turbulence. The model coefficients of the DNAM-SSD model are adaptively calculated through the scale-similarity relation, which greatly simplifies the conventional Germano-identity based dynamic procedure (GID). The a priori study shows that the DNAM-SSD model predicts the SGS stress considerably better than the conventional velocity gradient model (VGM), dynamic Smagorinsky model (DSM), dynamic mixed model (DMM) and DNAM-GID model at a variety of filter widths ranging from inertial to viscous ranges. The correlation coefficients of the SGS stress predicted by the DNAM-SSD model can be larger than 95% with the relative errors lower than 30%. In the a posteriori testings of LES, the DNAM-SSD model outperforms the implicit LES (ILES), DSM, DMM and DNAM-GID models without increasing computational costs, which only takes up half the time of the DNAM-GID model. The DNAM-SSD model accurately predicts plenty of turbulent statistics and instantaneous spatial structures in reasonable agreement with the filtered DNS data. These results indicate that the current DNAM-SSD model is attractive for the development of highly accurate SGS models for LES of turbulence.