A passive-active dynamic insulation system for all climates

Peer reviewedPublisher PD

ANALYSIS OF ENGINE CHARACTERISTICS AND EMISSIONS FUELED BY IN-SITU MIXING OF SMALL AMOUNT OF HYDROGEN IN COMPRESSED NATURAL GAS

The use of gaseous fuels in internal combustion engines has long been observed as a possible method of reducing emissions while maintaining engine performance and efficiency. Most of the research interests is focused on the use of compressed natural gas as alternative fuel, mainly due to its wide availability, high thermal efficiency and lower exhaust emissions compared to other hydrocarbon fuels. But compressed natural gas has the penalty of slow burning velocity and poor lean burn ability. One effective way to solve this problem is to mix the compressed natural gas with a fuel that possesses the high burning velocity. Hydrogen is the best additive candidate to natural gas due to its unique characteristics in promoting flame propagation speed, which stabilizes the combustion process. This research investigated the engine characteristics and emissions of a CNG-DI engine fueled by low levels of hydrogen enrichment (lower than 10%) in CNG utilizing an in-situ mixing system. Prior to the main experiment, two pre-experiments were conducted to determine the best and most suitable parameters for optimization of engine performance, combustion as well as emissions. The first experiment was to determine the suitable injector type to be used, and it was found that the wide cone angle injector of 70o was better for the applications. The second experiment was to determine the suitable injection timing, and it was discovered that the earlier injection timing was the best for this work. In this research, the engine used was a 4-stroke single cylinder, with a swept volume of 399.25 cc and a compression ratio of 14:1. The injection timing was set to 300o crank angle before top dead center as determined in the pre-experiment; the engine speed from 2000 to 4000 rpm and the spark timing for all the operating conditions were set to maximum brake torque. All the experiments were conducted at full load and relative air-fuel ratio λ =1.0. The injection pressure was fixed at 14 bar for all the cases. The findings revealed that the brake torque, brake power and brake mean effective pressure increased with the increase of hydrogen fraction at low and medium engine speeds. The brake specific energy consumption decreased and brake thermal efficiency increased with the increase of hydrogen percentage. In general, significant changes have been observed with the engine characteristics at low engine speed but the rate of increase/decrease of the parameters decreased was less significant with the addition of higher percentages of hydrogen as well as with the increase in engine speeds. For all the cases, the cylinder pressure and the heat release rate increased while the flame developement and rapid combustion duration decreased with the increase in the amount of hydrogen in the blends. The phenomenon was more obvious at the low engine speed, suggesting that the effect of hydrogen addition in the enhancement of burning velocity plays more important role at relatively low cylinder air motion. Exhaust THC, CO and CO2 concentrations decreased with the increase of hydrogen fraction due to the increase in hydrogen to carbon ratio (H/C). However, the variation in the NOx emissions was found to be negligible with the addition of hydrogen

Dynamics of Stochastic Systems with Memory (Mathematics and Statistics Colloquium, Wright State University)

We describe an approach to the dynamics of stochastic systems with finite memory using multiplicative cocycles in Hilbert space. We introduce the notion of hyperbolicity for stationary solutions of the stochastic differential system. We then establish the existence of smooth stable and unstable manifolds in a neighborhood of a hyperbolic stationary solution. The stable and unstable manifolds are stationary and asymptotically invariant under the stochastic semiflow. The proof uses ideas from infinite-dimensional multiplicative ergodic theory and interpolation arguments

The Stable Manifold Theorem for SDE\u27s (Probability Seminar, University of California, Irvine)

In this talk, we formulate a local stable manifold theorem for stochastic differential equations in Euclidean space, driven by multi-dimensional Brownian motion. We introduce the concept of hyperbolicity for stationary trajectories of a SDE. This is done using the Oseledec muliplicative ergodic theorem on the linearized SDE along the stationary solution. Using methods of (non-linear ergodic theory), we construct a stationary family of stable and unstable manifolds in a stationary neighborhood around the hyperbolic stationary trajectory of the non-linear SDE. The stable/unstable manifolds are dynamically characterized using anticipative stochastic calculus

On the Dynamics of Stochastic Differential Equations (Ellis B. Stouffer Colloquium, University of Kansas)

We formulate and outline a proof of the Local Stable Manifold Theorem for stochastic differential equations (SDE\u27s) in Euclidean space (joint work with M. Scheutzow). This is a central result in dynamical systems with noise. Starting with the existence of a stochastic flow for an SDE, we introduce the notion of a hyperbolic stationary trajectory. We prove the existence of invariant random stable and unstable manifolds in the neighborhood of a hyperbolic stationary solution. For Stratonovich noise, the stable and unstable manifolds are dynamically characterized using forward and backward solutions of the anticipating SDE

The Stable Manifold Theorem for Stochastic Systems with Memory (Probability Seminar, Université Henri Poincaré Nancy 1)

We state and prove a Local Stable Manifold Theorem for nonlinear stochastic differential systems with finite memory (viz. stochastic functional differential equations (sfde\u27s)). We introduce the notion of hyperbolicity for stationary solutions of sfde\u27s. We then establish the existence of smooth stable and unstable manifolds in a neighborhood of a hyperbolic stationary solution. The stable and unstable manifolds are stationary and asymptotically invariant under the stochastic semiflow. The proof uses infinite-dimensional multiplicative ergodic theory techniques and interpolation arguments

Stochastic Dynamics of Infinite-Dimensional Systems (Stochastic and Non-linear Analysis Seminar, University of Illinois)

We describe an approach to the dynamics of non-linear stochastic differential systems with finite memory using multiplicative cocycles in Hilbert space. We introduce the notion of hyperbolicity for stationary solutions of stochastic systems with memory. We then establish the existence of smooth stable and unstable manifolds in a neighborhood of a hyperbolic stationary solution. The stable and unstable manifolds are stationary and asymptotically invariant under the stochastic semiflow. The proof uses ideas from infinite-dimensional multiplicative ergodic theory and interpolation arguments