6 resultados para Engineering Process
em Bucknell University Digital Commons - Pensilvania - USA
Resumo:
Model based calibration has gained popularity in recent years as a method to optimize increasingly complex engine systems. However virtually all model based techniques are applied to steady state calibration. Transient calibration is by and large an emerging technology. An important piece of any transient calibration process is the ability to constrain the optimizer to treat the problem as a dynamic one and not as a quasi-static process. The optimized air-handling parameters corresponding to any instant of time must be achievable in a transient sense; this in turn depends on the trajectory of the same parameters over previous time instances. In this work dynamic constraint models have been proposed to translate commanded to actually achieved air-handling parameters. These models enable the optimization to be realistic in a transient sense. The air handling system has been treated as a linear second order system with PD control. Parameters for this second order system have been extracted from real transient data. The model has been shown to be the best choice relative to a list of appropriate candidates such as neural networks and first order models. The selected second order model was used in conjunction with transient emission models to predict emissions over the FTP cycle. It has been shown that emission predictions based on air-handing parameters predicted by the dynamic constraint model do not differ significantly from corresponding emissions based on measured air-handling parameters.
Resumo:
This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.
Resumo:
This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.
Resumo:
A new concept for a solar thermal electrolytic process was developed for the production of H-2 from water. A metal oxide is reduced to a lower oxidation state in air with concentrated solar energy. The reduced oxide is then used either as an anode or solute for the electrolytic production of H-2 in either an aqueous acid or base solution. The presence of the reduced metal oxide as part of the electrolytic cell decreases the potential required for water electrolysis below the ideal 1.23 V required when H-2 and O-2 evolve at 1 bar and 298 K. During electrolysis, H-2 evolves at the cathode at 1 bar while the reduced metal oxide is returned to its original oxidation state, thus completing the H-2 production cycle. Ideal sunlight-to-hydrogen thermal efficiencies were established for three oxide systems: Fe2O3-Fe3O4, Co3O4-CoO, and Mn2O3-Mn3O4. The ideal efficiencies that include radiation heat loss are as high or higher than corresponding ideal values reported in the solar thermal chemistry literature. An exploratory experimental study for the iron oxide system confirmed that the electrolytic and thermal reduction steps occur in a laboratory scale environment.
Resumo:
The curriculum of the Bucknell University Chemical Engineering Department includes a required senior year capstone course titled Process Engineering, with an emphasis on process design. For the past ten years library research has been a significant component of the coursework, and students working in teams meet with the librarian throughout the semester to explore a wide variety of information resources required for their project. The assignment has been the same from 1989 to 1999. Teams of students are responsible for designing a safe, efficient, and profitable process for the dehydrogenation of ethylbenzene to styrene monomer. A series of written reports on their chosen process design is a significant course outcome. While the assignment and the specific chemical technology have not changed radically in the past decade, the process of research and discovery has evolved considerably. This paper describes the solutions offered in 1989 to meet the information needs of the chemical engineering students at Bucknell University, and the evolution in research brought about by online databases, electronic journals, and the Internet, making the process of discovery a completely different experience in 1999.
Resumo:
Aluminum coatings were applied to 2024-T3 and 7075-T6 aluminum alloys via the Cold Spray process. The coatings were applied to substrateswith various surface preparation and Cold Spray carrier gas combinations. Some samples were coated with an additional sealant with and without a chromate conversion layer. An exhaustive corrosion analysis was then performed which utilized a number of long termand accelerated tests in order to characterize the corrosion protection of the coatings.