Development of Dynamic Constraint Models for a Model Based Transient Calibration Process

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.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

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.

Scale Up of PLA Nanoparticle Synthesis by Solvent Displacement and Functionalization of the Particles with a Silica Shell for Targeted Drug Delivery Applications

Biodegradable polymer nanoparticles have the properties necessary to address many of the issues associated with current drug delivery techniques including targeted and controlled delivery. A novel drug delivery vehicle is proposed consisting of a poly(lactic acid) nanoparticle core, with a functionalized, mesoporous silica shell. In this study, the production of PLA nanoparticles is investigated using solvent displacement in both a batch and continuous manner, and the effects of various system parameters are examined. Using Pluronic F-127 as the stabilization agent throughout the study, PLA nanoparticles are produced through solvent displacement with diameters ranging from 200 to 250 nm using two different methods: dropwise addition and in an impinging jet mixer. The impinging jet mixer allows for easy scale-up of particle production. The concentration of surfactant and volume of quench solution is found to have minimal impact on particle diameter; however, the concentration of PLA is found to significantly impact the diameter mean and polydispersity. In addition, the stability of the PLA nanoparticles is observed to increase as residual THF is evaporated. Lastly, the isolated PLA nanoparticles are coated with a silica shell using the Stöber Process. It is found that functionalizing the silica with a phosphonic silane in the presence of excess Pluronic F-127 decreases coalescence of the particles during the coating process. Future work should be conducted to fine-tune the PLA nanoparticle synthesis process by understanding the effect of other system parameters and in synthesizing mesoporous silica shells.

Corrosion Characteristics And Mechanical Properties Of Aluminum Coatings Applied By The Cold Spray Process

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.

Effects Of The Flash Welding Process On Mechanical And Microstructural Properties Of Structural Steel Joints Assessed Using Dest

ASTM A529 carbon¿manganese steel angle specimens were joined by flash butt welding and the effects of varying process parameter settings on the resulting welds were investigated. The weld metal and heat affected zones were examined and tested using tensile testing, ultrasonic scanning, Rockwell hardness testing, optical microscopy, and scanning electron microscopy with energy dispersive spectroscopy in order to quantify the effect of process variables on weld quality. Statistical analysis of experimental tensile and ultrasonic scanning data highlighted the sensitivity of weld strength and the presence of weld zone inclusions and interfacial defects to the process factors of upset current, flashing time duration, and upset dimension. Subsequent microstructural analysis revealed various phases within the weld and heat affected zone, including acicular ferrite, Widmanstätten or side-plate ferrite, and grain boundary ferrite. Inspection of the fracture surfaces of multiple tensile specimens, with scanning electron microscopy, displayed evidence of brittle cleavage fracture within the weld zone for certain factor combinations. Test results also indicated that hardness was increased in the weld zone for all specimens, which can be attributed to the extensive deformation of the upset operation. The significance of weld process factor levels on microstructure, fracture characteristics, and weld zone strength was analyzed. The relationships between significant flash welding process variables and weld quality metrics as applied to ASTM A529-Grade 50 steel angle were formalized in empirical process models.

The Supreme Court Confirmation Process and Its Implications

In recent history, there has been a trend of increasing partisan polarization throughout most of the American political system. Some of the impacts of this polarization are obvious; however, there is reason to believe that we miss some of the indirect effects of polarization. Accompanying the trend of increased polarization has been an increase in the contentiousness of the Supreme Court confirmation process. I believe that these two trends are related. Furthermore, I argue that these trends have an impact on judicial behavior. This is an issue worth exploring, since the Supreme Court is the most isolated branch of the federal government. The Constitution structured the Supreme Court to ensure that it was as isolated as possible from short-term political pressures and interests. This study attempts to show how it may be possible that those goals are no longer being fully achieved. My first hypothesis in this study is that increases in partisan polarization are a direct cause of the increase in the level of contention during the confirmation process. I then hypothesize that the more contention a justice faces during his or her confirmation process, the more ideologically extreme that justice will then vote on the bench. This means that a nominee appointed by a Republican president will tend to vote even more conservatively than was anticipated following a contentious confirmation process, and vice versa for Democratic appointees. In order to test these hypotheses, I developed a data set for every Supreme Court nominee dating back to President Franklin D. Roosevelt¿s appointments (1937). With this data set, I ran a series of regression models to analyze these relationships. Statistically speaking, the results support my first hypothesis in a fairly robust manner. My regression results for my second hypothesis indicate that the trend I am looking for is present for Republican nominees. For Democratic nominees, the impacts are less robust. Nonetheless, as the results will show, contention during the confirmation process does seem to have some impact on judicial behavior. Following my quantitative analysis, I analyze a series of case studies. These case studies serve to provide tangible examples of these statistical trends as well as to explore what else may be going on during the confirmation process and subsequent judicial decision-making. I use Justices Stevens, Rehnquist, and Alito as the subjects for these case studies. These cases will show that the trends described above do seem to be identifiable at the level of an individual case. These studies further help to indicate other potential impacts on judicial behavior. For example, following Justice Rehnquist¿s move from Associate to Chief Justice, we see a marked change in his behavior. Overall, this study serves as a means of analyzing some of the more indirect impacts of partisan polarization in modern politics. Further, the study offers a means of exploring some of the possible constraints (both conscious and subconscious) that Supreme Court justices may feel while they decide how to cast a vote in a particular case. Given the wide-reaching implications of Supreme Court decisions, it is important to try to grasp a full view of how these decisions are made.