A Method for Assessing the Sustainability of Design in Developing World Projects

Projects for the developing world usually find themselves at the bottom of an engineer’s priority list. There is often very little engineering effort placed on creating new products for the poorest people in the world. This trend is beginning to change now as people begin to recognize the potential for these projects. Engineers are beginning to try and solve some of the direst issues in the developing world and many are having positive impacts. However, the conditions needed to support these projects can only be maintained in the short term. There is now a need for greater sustainability. Sustainability has a wide variety of definitions in both business and engineering. These concepts are analyzed and synthesized to develop a broad meaning of sustainability in the developing world. This primarily stems from the “triple bottom line” concept of economic, social, and environmental sustainability. Using this model and several international standards, this thesis develops a metric for guiding and evaluating the sustainability of engineering projects. The metric contains qualitative questions that investigate the sustainability of a project. It is used to assess several existing projects in order to determine flaws. Specifically, three projects seeking to deliver eyeglasses are analyzed for weaknesses to help define a new design approach for achieving better results. Using the metric as a guiding tool, teams designed two pieces of optometry equipment: one to cut lenses for eyeglasses and the other to diagnose refractive error, or prescription. These designs are created and prototyped in the developed and developing worlds in order to determine general feasibility. Although there is a recognized need for eventual design iterations, the whole project is evaluated using the developed metric and compared to the existing projects. Overall, the success demonstrates the improvements made to the long-term sustainability of the project resulting from the use of the sustainability metric.

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.

Static and Dynamic Error Correction of a Computer-Aided Mechanical Navigation Linkage for Arthroscopic Hip Surgery

While beneficially decreasing the necessary incision size, arthroscopic hip surgery increases the surgical complexity due to loss of joint visibility. To ease such difficulty, a computer-aided mechanical navigation system was developed to present the location of the surgical tool relative to the patient¿s hip joint. A preliminary study reduced the position error of the tracking linkage with limited static testing trials. In this study, a correction method, including a rotational correction factor and a length correction function, was developed through more in-depth static testing. The developed correction method was then applied to additional static and dynamic testing trials to evaluate its effectiveness. For static testing, the position error decreased from an average of 0.384 inches to 0.153 inches, with an error reduction of 60.5%. Three parameters utilized to quantify error reduction of dynamic testing did not show consistent results. The vertex coordinates achieved 29.4% of error reduction, yet with large variation in the upper vertex. The triangular area error was reduced by 5.37%, however inconsistent among all five dynamic trials. Error of vertex angles increased, indicating a shape torsion using the developed correction method. While the established correction method effectively and consistently reduced position error in static testing, it did not present consistent results in dynamic trials. More dynamic paramters should be explored to quantify error reduction of dynamic testing, and more in-depth dynamic testing methodology should be conducted to further improve the accuracy of the computer-aided nagivation system.