Analysis and Prediction of Transient Opacity Spikes Using Dimensional Modeling

Dimensional modeling, GT-Power in particular, has been used for two related purposes-to quantify and understand the inaccuracies of transient engine flow estimates that cause transient smoke spikes and to improve empirical models of opacity or particulate matter used for engine calibration. It has been proposed by dimensional modeling that exhaust gas recirculation flow rate was significantly underestimated and volumetric efficiency was overestimated by the electronic control module during the turbocharger lag period of an electronically controlled heavy duty diesel engine. Factoring in cylinder-to-cylinder variation, it has been shown that the electronic control module estimated fuel-Oxygen ratio was lower than actual by up to 35% during the turbocharger lag period but within 2% of actual elsewhere, thus hindering fuel-Oxygen ratio limit-based smoke control. The dimensional modeling of transient flow was enabled with a new method of simulating transient data in which the manifold pressures and exhaust gas recirculation system flow resistance, characterized as a function of exhaust gas recirculation valve position at each measured transient data point, were replicated by quasi-static or transient simulation to predict engine flows. Dimensional modeling was also used to transform the engine operating parameter model input space to a more fundamental lower dimensional space so that a nearest neighbor approach could be used to predict smoke emissions. This new approach, intended for engine calibration and control modeling, was termed the "nonparametric reduced dimensionality" approach. It was used to predict federal test procedure cumulative particulate matter within 7% of measured value, based solely on steady-state training data. Very little correlation between the model inputs in the transformed space was observed as compared to the engine operating parameter space. This more uniform, smaller, shrunken model input space might explain how the nonparametric reduced dimensionality approach model could successfully predict federal test procedure emissions when roughly 40% of all transient points were classified as outliers as per the steady-state training data.

Multiscale Characterization of Acrylic Bone Cement Modified with Functionalized Mesoporous Silica Nanoparticles

Acrylic bone cement is widely used to anchor orthopedic implants to bone and mechanical failure of the cement mantle surrounding an implant can contribute to aseptic loosening. In an effort to enhance the mechanical properties of bone cement, a variety of nanoparticles and fibers can be incorporated into the cement matrix. Mesoporous silica nanoparticles (MSNs) are a class of particles that display high potential for use as reinforcement within bone cement. Therefore, the purpose of this study was to quantify the impact of modifying an acrylic cement with various low-loadings of mesoporous silica. Three types of MSNs (one plain variety and two modified with functional groups) at two loading ratios (0.1 and 0.2 wt/wt) were incorporated into a commercially available bone cement. The mechanical properties were characterized using four-point bending, microindentation and nanoindentation (static, stress relaxation, and creep) while material properties were assessed through dynamic mechanical analysis, differential scanning calorimetry, thermogravimetric analysis, FTIR spectroscopy, and scanning electron microscopy. Four-point flexural testing and nanoindentation revealed minimal impact on the properties of the cements, except for several changes in the nano-level static mechanical properties. Conversely, microindentation testing demonstrated that the addition of MSNs significantly increased the microhardness. The stress relaxation and creep properties of the cements measured with nanoindentation displayed no effect resulting from the addition of MSNs. The measured material properties were consistent among all cements. Analysis of scanning electron micrographs images revealed that surface functionalization enhanced particle dispersion within the cement matrix and resulted in fewer particle agglomerates. These results suggest that the loading ratios of mesoporous silica used in this study were not an effective reinforcement material. Future work should be conducted to determine the impact of higher MSN loading ratios and alternative functional groups. (C) 2014 Elsevier Ltd. All rights reserved.