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Results for “plug-flow model”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1995

VRA Modeling, phase 1

The destruction of organic contaminants in waste water for closed systems, such as that of Space Station, is crucial due to the need for recycling the waste water. A co-current upflow bubble column using oxygen as the gas phase oxidant and packed with catalyst particles consisting of a noble metal on an alumina substrate is being developed for this process. The objective of this study is to develop a plug-flow model that will predict the performance of this three phase reactor system in destroying a multicomponent mixture of organic contaminants in water. Mass balances on a series of contaminants and oxygen in both the liquid and gas phases are used to develop this model. These mass balances incorporate the gas-to-liquid and liquid-to-particle mass transfer coefficients, the catalyst effectiveness factor, and intrinsic reaction rate. To validate this model, a bench scale reactor has been tested at Michigan Technological University at elevated pressures (50-83 psig,) and a temperature range of 200 to 290 F. Feeds consisting of five dilute solutions of ethanol (approx. 10 ppm), chlorobenzene (approx. 20 ppb), formaldehyde (approx. 100 ppb), dimethyl sulfoxide (DMSO approx. 300 ppb), and urea (approx. 20 ppm) in water were tested individually with an oxygen mass flow rate of 0.009 lb/h. The results from these individual tests were used to develop the kinetic parameter inputs necessary for the computer model. The computer simulated results are compared to the experimental data obtained for all 5 components run in a mixture on the differential test column for a range of reactor contact times.

Kindt, Louis M.↗
NASA NTRS1973

A stochastic model of turbulent mixing with chemical reaction: Nitric oxide formulation in a plug-flow burner

A stochastic model of turbulent mixing was developed for a reactor in which mixing is represented by n-body fluid particle interactions. The model was used to justify the assumption (made in previous investigations of the role of turbulent mixing on burner generated thermal nitric oxide and carbon monoxide emissions) that for a simple plug flow reactor, composition nonuniformities can be described by a Gaussian distribution function in the local fuel:air equivalence ratio. Recent extensions of this stochastic model to include the combined effects of turbulent mixing and secondary air entrainment on thermal generation of nitric oxide in gas turbine combustors are discussed. Finally, rate limited upper and lower bounds of the nitric oxide produced by thermal fixation of molecular nitrogen and oxidation of organically bound fuel nitrogen are estimated on the basis of the stochastic model for a plug flow burner; these are compared with experimental measurements obtained using a laboratory burner operated over a wide range of test conditions; good agreement is obtained.

Flagan, R. C.↗
NASA NTRS2023

Multiphysics Modeling of Electrode Dissolution under Hydrodynamic Conditions in Low Conductivity Water

Efficient plug-flow electrochemical reactors are characterized by their ability to effectively convert species with significant ionic strength and/or with the assistance of a well-behaved electrolyte. Because of the classic electroconductivity requirement, electrochemical reactors are not particularly attractive options for applications with low-conductivity conditions, especially for low-pressure feeds. However, these reactors can still find application in dedicated processes such as ultra-clean water conditioning and biological-coupled separation systems. Consequently, a multi-physics model was developed using COMSOL Multiphysics to characterize different reactor-design conditions based on the Tertiary Current Distribution which accounts for the effects of expected variations in electrolyte composition and ionic strength on the electrochemical process, as well as solution resistance and electrode kinetics. The modelling framework presented here employs single-phase laminar fluid flow, the Nernst-Planck equation, the water-based electroneutrality condition, and concentration-dependent overpotentials. This investigation particularly explores the electrolysis process of “anodic dissolution,” in which elemental species dissociate from the solid matrix of the electrode and enter the liquid phase of the electrolyte as soluble ions. The reactor configuration of interest has a rectangular parallel-electrode design and is operated galvanostatically. A series of parametric studies are carried out to inspect the response of the system when hydrodynamic, kinetic, and geometric conditions are changed. The parametric sweep resulted in variable effluent concentrations and system voltage, which reveal underlaying optimization patterns for electrode dissolution in low conductivity water.

Multiphysics↗
NASA NTRS1995

Velocity Fields of Axisymmetric Hydrogen-Air Counterflow Diffusion Flames from LDV, PIV, and Numerical Computation

Laminar fuel-air counterflow diffusion flames (CFDFs) were studied using axisymmetric convergent-nozzle and straight-tube opposed jet burners (OJBs). The subject diagnostics were used to probe a systematic set of H2/N2-air CFDFs over wide ranges of fuel input (22 to 100% Ha), and input axial strain rate (130 to 1700 Us) just upstream of the airside edge, for both plug-flow and parabolic input velocity profiles. Laser Doppler Velocimetry (LDV) was applied along the centerline of seeded air flows from a convergent nozzle OJB (7.2 mm i.d.), and Particle Imaging Velocimetry (PIV) was applied on the entire airside of both nozzle and tube OJBs (7 and 5 mm i.d.) to characterize global velocity structure. Data are compared to numerical results from a one-dimensional (1-D) CFDF code based on a stream function solution for a potential flow input boundary condition. Axial strain rate inputs at the airside edge of nozzle-OJB flows, using LDV and PIV, were consistent with 1-D impingement theory, and supported earlier diagnostic studies. The LDV results also characterized a heat-release hump. Radial strain rates in the flame substantially exceeded 1-D numerical predictions. Whereas the 1-D model closely predicted the max I min axial velocity ratio in the hot layer, it overpredicted its thickness. The results also support previously measured effects of plug-flow and parabolic input strain rates on CFDF extinction limits. Finally, the submillimeter-scale LDV and PIV diagnostics were tested under severe conditions, which reinforced their use with subcentimeter OJB tools to assess effects of aerodynamic strain, and fueVair composition, on laminar CFDF properties, including extinction.

Pellett, Gerald L.↗
NASA NTRS2005

Updated Chemical Kinetics and Sensitivity Analysis Code

An updated version of the General Chemical Kinetics and Sensitivity Analysis (LSENS) computer code has become available. A prior version of LSENS was described in "Program Helps to Determine Chemical-Reaction Mechanisms" (LEW-15758), NASA Tech Briefs, Vol. 19, No. 5 (May 1995), page 66. To recapitulate: LSENS solves complex, homogeneous, gas-phase, chemical-kinetics problems (e.g., combustion of fuels) that are represented by sets of many coupled, nonlinear, first-order ordinary differential equations. LSENS has been designed for flexibility, convenience, and computational efficiency. The present version of LSENS incorporates mathematical models for (1) a static system; (2) steady, one-dimensional inviscid flow; (3) reaction behind an incident shock wave, including boundary layer correction; (4) a perfectly stirred reactor; and (5) a perfectly stirred reactor followed by a plug-flow reactor. In addition, LSENS can compute equilibrium properties for the following assigned states: enthalpy and pressure, temperature and pressure, internal energy and volume, and temperature and volume. For static and one-dimensional-flow problems, including those behind an incident shock wave and following a perfectly stirred reactor calculation, LSENS can compute sensitivity coefficients of dependent variables and their derivatives, with respect to the initial values of dependent variables and/or the rate-coefficient parameters of the chemical reactions.

Radhakrishnan, Krishnan↗