Coupling of Chemical Kinetics with Computational Fluid Dynamics in a Three-Dimensional Engine Model

The role of computer modeling has grown recently to integrate itself as an inseparable tool to experimental studies for the optimization of automotive engines and the development of future fuels. Traditionally, computer models rely on simplified global reaction steps to simulate the combustion and pollutant formation inside the internal combustion engine. With the current interest in advanced combustion modes and injection strategies, this approach depends on arbitrary adjustment of model parameters that could reduce credibility of the predictions. The purpose of this study is to enhance the combustion model of KIVA, a computational fluid dynamics code, by coupling its fluid mechanics solution with detailed kinetic reactions solved by the chemistry solver, CHEMKIN. As a result, an engine-friendly reaction mechanism for n-heptane was selected to simulate diesel oxidation. Each cell in the computational domain is considered as a perfectly-stirred reactor which undergoes adiabatic constant- volume combustion. The model was applied to an ideally-prepared homogeneous- charge compression-ignition combustion (HCCI) and direct injection (DI) diesel combustion. Ignition and combustion results show that the code successfully simulates the premixed HCCI scenario when compared to traditional combustion models. Direct injection cases, on the other hand, do not offer a reliable prediction mainly due to the lack of turbulent-mixing model, inherent in the perfectly-stirred reactor formulation. In addition, the model is sensitive to intake conditions and experimental uncertainties which require implementation of enhanced predictive tools. It is recommended that future improvements consider turbulent-mixing effects as well as optimization techniques to accurately simulate actual in-cylinder process with reduced computational cost. Furthermore, the model requires the extension of existing fuel oxidation mechanisms to include pollutant formation kinetics for emission control studies.

Improving the stability of an oxime based electrochemical microsensor for organo-phosphate vapor detection

A micro gas sensor has been developed by our group for the detection of organo-phosphate vapors using an aqueous oxime solution. The analyte diffuses from the high flow rate gas stream through a porous membrane to the low flow rate aqueous phase. It reacts with the oxime PBO (1-Phenyl-1,2,3,-butanetrione 2-oxime) to produce cyanide ions, which are then detected electrochemically from the change in solution potential. Previous work on this oxime based electrochemistry indicated that the optimal buffer pH for the aqueous solution was approximately 10. A basic environment is needed for the oxime anion to form and the detection reaction to take place. At this specific pH, the potential response of the sensor to an analyte (such as acetic anhydride) is maximized. However, sensor response slowly decreases as the aqueous oxime solution ages, by as much as 80% in first 24 hours. The decrease in sensor response is due to cyanide which is produced during the oxime degradation process, as evidenced by the cyanide selective electrode. Solid phase micro-extraction carried out on the oxime solution found several other possible degradation products, including acetic acid, N-hydroxy benzamide, benzoic acid, benzoyl cyanide, 1-Phenyl 1,3-butadione, 2-isonitrosoacetophenone and an imine derived from the oxime. It was concluded that degradation occurred through nucleophilic attack by a hydroxide or oxime anion to produce cyanide, as well as a nitrogen atom rearrangement similar to Beckmann rearrangement. The stability of the oxime in organic solvents is most likely due to the lack of water, and specifically hydroxide ions. The reaction between oxime and organo-phosphate to produce cyanide ions requires hydroxide ions, and therefore pure organic solvents are not compatible with the current micro-sensor electrochemistry. By combining a concentrated organic oxime solution with the basic aqueous buffer just prior to being used in the detection process, oxime degradation can be avoided while preserving the original electrochemical detection scheme. Based on beaker cell experiments with selective cyanide sensitive electrodes, ethanol was chosen as the best organic solvent due to its stabilizing effect on the oxime, minimal interference with the aqueous electrochemistry, and compatibility with the current microsensor material (PMMA). Further studies showed that ethanol had a small effect on micro-sensor performance by reducing the rate of cyanide production and decreasing the overall response time. To avoid incomplete mixing of the aqueous and organic solutions, they were pre-mixed externally at a 10:1 ratio, respectively. To adapt the microsensor design to allow for mixing to take place within the device, a small serpentine channel component was fabricated with the same dimensions and material as the original sensor. This allowed for seamless integration of the microsensor with the serpentine mixing channel. Mixing in the serpentine microchannel takes place via diffusion. Both detector potential response and diffusional mixing improve with increased liquid residence time, and thus decreased liquid flowrate. Micromixer performance was studies at a 10:1 aqueous buffer to organic solution flow rate ratio, for a total rate of 5.5 μL/min. It was found that the sensor response utilizing the integrated micromixer was nearly identical to the response when the solutions were premixed and fed at the same rate.

Simulations of droplet dispersion in the wakes of cylinders and icing tunnel spray bars

Simulations of droplet dispersion behind cylinder wakes and downstream of icing tunnel spray bars were conducted. In both cases, a range of droplet sizes were investigated numerically with a Lagrangian particle trajectory approach while the turbulent air flow was investigated with a hybrid Reynolds-Averaged Navier-Stokes/Large-Eddy Simulations approach scheme. In the first study, droplets were injected downstream of a cylinder at sub-critical conditions (i.e. with laminar boundary layer separation). A stochastic continuous random walk (CRW) turbulence model was used to capture the effects of sub-grid turbulence. Small inertia droplets (characterized by small Stokes numbers) were affected by both the large-scale and small-scale vortex structures and closely followed the air flow, while exhibiting a dispersion consistent with that of a scalar flow field. Droplets with intermediate Stokes numbers were centrifuged by the vortices to the outer edges of the wake, yielding an increased dispersion. Large Stokes number droplets were found to be less responsive to the vortex structures and exhibited the least dispersion. Particle concentration was also correlated with vorticity distribution which yielded preferential bias effects as a function of different particle sizes. This trend was qualitatively similar to results seen in homogenous isotropic turbulence, though the influence of particle inertia was less pronounced for the cylinder wake case. A similar study was completed for droplet dispersion within the Icing Research Tunnel (IRT) at the NASA Glenn Research Center, where it is important to obtain a nearly uniform liquid water content (LWC) distribution in the test section (to recreate atmospheric icing conditions).. For this goal, droplets are diffused by the mean and turbulent flow generated from the nozzle air jets, from the upstream spray bars, and from the vertical strut wakes. To understand the influence of these three components, a set of simulations was conducted with a sequential inclusion of these components. Firstly, a jet in an otherwise quiescent airflow was simulated to capture the impact of the air jet on flow turbulence and droplet distribution, and the predictions compared well with experimental results. The effects of the spray bar wake and vertical strut wake were then included with two more simulation conditions, for which it was found that the air jets were the primary driving force for droplet dispersion, i.e. that the spray bar and vertical strut wake effects were secondary.

Cell-cell communication in three dimensional microenvironments

Cellular behavior is dependent on a variety of extracellular cues required for normal tissue function, wound healing, and activation of the immune system. Removed from their in vivo microenvironment and cultured in vitro, cells lose many environmental cues and that may result in abberant behavior, making it difficult to study cellular processes. In order to mimic native tissue environments, optical tweezer and microfluidic technologies were used to place cells within defined areas of the culture environment. To provide three dimensional supports found in natural tissues, hydrogel scaffolds of poly (ethylene glycol) diacrylate and the basement membrane matrix Matrigel were used. Optical tweezer technology allowed precision placement and formation of homotypic and heterotypic arrays of human U937, HEK 293, and porcine mesenchymal stem cells. Alternatively, two microfluidic devices were designed to pattern Matrigel scaffolds. The first microfluidic device utilized laminar flow to spatially pattern multiple cell types within the device. Gradients of soluble molecules were then be formed and manipulated across the Matrigel scaffolds. Patterning Matrigel using laminar flow techniques require microfluidic expertise and do not produce consistent patterning conditions, limiting their use difficult in most cell culture laboratories. Thus, a buried Matrigel polydimethylsiloxane (PDMS) device was developed for spatial patterning of biological scaffolds. Matrigel is injected into micron sized channels of PDMS fabricated by soft lithography and allowed to thermally cure. Following curing, a second PDMS device was placed on top of the buried Matrigel channels to support media flow. In order to validate these systems, a cell-cell communication model system was developed utilizing LPS and TNFα signaling with fluorescent reporter systems to monitor communication in real time. We demonstrated the utility of microfluidic devices to support the cell-cell communication model system by co culturing three cell types within Matrigel scaffolds and monitoring signaling activity via fluorescent reporters.