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.

A microstructure based model of the deformation mechanisms and flow stress during elevated temperature straining of a magnesium alloy

We show that the variation of flow stress with strain rate and grain size in a magnesium alloy deformed at a constant strain rate and 450 °C can be predicted by a crystal plasticity model that includes grain boundary sliding and diffusion. The model predicts the grain size dependence of the critical strain rate that will cause a transition in deformation mechanism from dislocation creep to grain boundary sliding, and yields estimates for grain boundary fluidity and diffusivity.

Adsorption behavior of redox-active suppressor additives: Combined electrochemical and STM studies

The redox chemistry and the related surface phase behavior of Safranine (SAF) and Janus Green B (JGB) have been studied by means of cyclic voltammetry in combination with in situ Scanning Tunneling Microscopy using HOPG (Highly Oriented Pyrolytic Graphite) and single crystalline Cu(1 0 0) as model substrates, both revealing different widths of the accessible potential windows. JGB and SAF serve as prototypical heterocyclic suppressor/leveler additives that are used for the metallization of 3D-TSVs (3D Through Silicon Vias) following a classical "leveling" concept. SAF can be considered as the reductive decomposition product of JGB that is formed at the copper/electrolyte interface upon electroplating. Both additives reveal a pronounced pH-dependent redox-chemistry with redox-transitions lying close to or even beyond the anodic limit of the copper potential window. Affected by these redox-processes are in particular the aromatic cores of those heterocycles that can be (quasi)reversibly reduced by a two electron transfer process within the potential window of copper. Therefore we identify the reduced form of those dyes as the active components for the suppressing/leveling effect in copper plating. STM data clearly shows a dye surface phase behavior that is crucially determined by its potential-dependent redox-chemistry. This will be exemplarily discussed for the SAF dye. On chloride-modified Cu(1 0 0) mono-reduced SAF forms a structurally well-defined monolayer of cationic stacking polymers. However, this coupled anion/cation layer reveals only minor suppressing capabilities with respect to the copper dissolution and deposition processes. Complete reduction of the aromatic heterocycle finally leads to the 3D precipitation of hydrophobic reaction products. 3D clusters of this SAF precipitate are discussed as the active structural motif for the suppressing effect of these dyes. (C) 2011 Elsevier Ltd. All rights reserved.

Underneath the cerclage: an ex vivo study on the cerclage-bone interface mechanics

Cerclages regain interest due to a rising number of periprosthetic fractures. The contact distribution at the circumferential cerclage-bone interface is still unknown. Local interface pressure depends on the amount of contact area. Cortical damage at the interface would provoke cerclage loosening. Therefore, the contact area, the bone pressure along the interface and the cortical resistance underneath loaded cerclages were determined in an ex vivo model.

Diagnostic microchip to assay 3D colony-growth potential of captured circulating tumor cells

Microfluidic technology has been successfully applied to isolate very rare tumor-derived epithelial cells (circulating tumor cells, CTCs) from blood with relatively high yield and purity, opening up exciting prospects for early detection of cancer. However, a major limitation of state-of-the-art CTC-chips is their inability to characterize the behavior and function of captured CTCs, for example to obtain information on proliferative and invasive properties or, ultimately, tumor re-initiating potential. Although CTCs can be efficiently immunostained with markers reporting phenotype or fate (e.g. apoptosis, proliferation), it has not yet been possible to reliably grow captured CTCs over long periods of time and at single cell level. It is challenging to remove CTCs from a microchip after capture, therefore such analyses should ideally be performed directly on-chip. To address this challenge, we merged CTC capture with three-dimensional (3D) tumor cell culture on the same microfluidic platform. PC3 prostate cancer cells were isolated from spiked blood on a transparent PDMS CTC-chip, encapsulated on-chip in a biomimetic hydrogel matrix (QGel™) that was formed in situ, and their clonal 3D spheroid growth potential was assessed by microscopy over one week in culture. The possibility to clonally expand a subset of captured CTCs in a near-physiological in vitro model adds an important element to the expanding CTC-chip toolbox that ultimately should improve prediction of treatment responses and disease progression.

Monte Carlo source model for photon beam radiotherapy: photon source characteristics

A major barrier to widespread clinical implementation of Monte Carlo dose calculation is the difficulty in characterizing the radiation source within a generalized source model. This work aims to develop a generalized three-component source model (target, primary collimator, flattening filter) for 6- and 18-MV photon beams that match full phase-space data (PSD). Subsource by subsource comparison of dose distributions, using either source PSD or the source model as input, allows accurate source characterization and has the potential to ease the commissioning procedure, since it is possible to obtain information about which subsource needs to be tuned. This source model is unique in that, compared to previous source models, it retains additional correlations among PS variables, which improves accuracy at nonstandard source-to-surface distances (SSDs). In our study, three-dimensional (3D) dose calculations were performed for SSDs ranging from 50 to 200 cm and for field sizes from 1 x 1 to 30 x 30 cm2 as well as a 10 x 10 cm2 field 5 cm off axis in each direction. The 3D dose distributions, using either full PSD or the source model as input, were compared in terms of dose-difference and distance-to-agreement. With this model, over 99% of the voxels agreed within +/-1% or 1 mm for the target, within 2% or 2 mm for the primary collimator, and within +/-2.5% or 2 mm for the flattening filter in all cases studied. For the dose distributions, 99% of the dose voxels agreed within 1% or 1 mm when the combined source model-including a charged particle source and the full PSD as input-was used. The accurate and general characterization of each photon source and knowledge of the subsource dose distributions should facilitate source model commissioning procedures by allowing scaling the histogram distributions representing the subsources to be tuned.

Hip2Norm: an object-oriented cross-platform program for 3D analysis of hip joint morphology using 2D pelvic radiographs

We developed an object-oriented cross-platform program to perform three-dimensional (3D) analysis of hip joint morphology using two-dimensional (2D) anteroposterior (AP) pelvic radiographs. Landmarks extracted from 2D AP pelvic radiographs and optionally an additional lateral pelvic X-ray were combined with a cone beam projection model to reconstruct 3D hip joints. Since individual pelvic orientation can vary considerably, a method for standardizing pelvic orientation was implemented to determine the absolute tilt/rotation. The evaluation of anatomically morphologic differences was achieved by reconstructing the projected acetabular rim and the measured hip parameters as if obtained in a standardized neutral orientation. The program had been successfully used to interactively objectify acetabular version in hips with femoro-acetabular impingement or developmental dysplasia. Hip(2)Norm is written in object-oriented programming language C++ using cross-platform software Qt (TrollTech, Oslo, Norway) for graphical user interface (GUI) and is transportable to any platform.

Development of the premature infant nose throat-model (PrINT-Model): an upper airway replica of a premature neonate for the study of aerosol delivery

Clinical efficacy of aerosol therapy in premature newborns depends on the efficiency of delivery of aerosolized drug to the bronchial tree. To study the influence of various anatomical, physical, and physiological factors on aerosol delivery in preterm newborns, it is crucial to have appropriate in vitro models, which are currently not available. We therefore constructed the premature infant nose throat-model (PrINT-Model), an upper airway model corresponding to a premature infant of 32-wk gestational age by three-dimensional (3D) reconstruction of a three-planar magnetic resonance imaging scan and subsequent 3D-printing. Validation was realized by visual comparison and comparison of total airway volume. To study the feasibility of measuring aerosol deposition, budesonide was aerosolized through the cast and lung dose was expressed as percentage of nominal dose. The airway volumes of the initial magnetic resonance imaging and validation computed tomography scan showed a relative deviation of 0.94%. Lung dose at low flow (1 L/min) was 61.84% and 9.00% at high flow (10 L/min), p < 0.0001. 3D-reconstruction provided an anatomically accurate surrogate of the upper airways of a 32-wk-old premature infant, making the model suitable for future in vitro testing.

Use of a 3D perfusion bioreactor with osteoblasts and osteoblast/endothelial cell co-cultures to improve tissue-engineered bone

The delivery of oxygen, nutrients, and the removal of waste are essential for cellular survival. Culture systems for 3D bone tissue engineering have addressed this issue by utilizing perfusion flow bioreactors that stimulate osteogenic activity through the delivery of oxygen and nutrients by low-shear fluid flow. It is also well established that bone responds to mechanical stimulation, but may desensitize under continuous loading. While perfusion flow and mechanical stimulation are used to increase cellular survival in vitro, 3D tissue-engineered constructs face additional limitations upon in vivo implantation. As it requires significant amounts of time for vascular infiltration by the host, implants are subject to an increased risk of necrosis. One solution is to introduce tissue-engineered bone that has been pre-vascularized through the co-culture of osteoblasts and endothelial cells on 3D constructs. It is unclear from previous studies: 1) how 3D bone tissue constructs will respond to partitioned mechanical stimulation, 2) how gene expression compares in 2D and in 3D, 3) how co-cultures will affect osteoblast activity, and 4) how perfusion flow will affect co-cultures of osteoblasts and endothelial cells. We have used an integrated approach to address these questions by utilizing mechanical stimulation, perfusion flow, and a co-culture technique to increase the success of 3D bone tissue engineering. We measured gene expression of several osteogenic and angiogenic genes in both 2D and 3D (static culture and mechanical stimulation), as well as in 3D cultures subjected to perfusion flow, mechanical stimulation and partitioned mechanical stimulation. Finally, we co-cultured osteoblasts and endothelial cells on 3D scaffolds and subjected them to long-term incubation in either static culture or under perfusion flow to determine changes in gene expression as well as histological measures of osteogenic and angiogenic activity. We discovered that 2D and 3D osteoblast cultures react differently to shear stress, and that partitioning mechanical stimulation does not affect gene expression in our model. Furthermore, our results suggest that perfusion flow may rescue 3D tissue-engineered constructs from hypoxic-like conditions by reducing hypoxia-specific gene expression and increasing histological indices of both osteogenic and angiogenic activity. Future research to elucidate the mechanisms behind these results may contribute to a more mature bone-like structure that integrates more quickly into host tissue, increasing the potential of bone tissue engineering.

Discrete element methods for asphalt concrete : development and application of user-defined microstructural models and a viscoelastic micromechanical model

As an important Civil Engineering material, asphalt concrete (AC) is commonly used to build road surfaces, airports, and parking lots. With traditional laboratory tests and theoretical equations, it is a challenge to fully understand such a random composite material. Based on the discrete element method (DEM), this research seeks to develop and implement computer models as research approaches for improving understandings of AC microstructure-based mechanics. In this research, three categories of approaches were developed or employed to simulate microstructures of AC materials, namely the randomly-generated models, the idealized models, and image-based models. The image-based models were recommended for accurately predicting AC performance, while the other models were recommended as research tools to obtain deep insight into the AC microstructure-based mechanics. A viscoelastic micromechanical model was developed to capture viscoelastic interactions within the AC microstructure. Four types of constitutive models were built to address the four categories of interactions within an AC specimen. Each of the constitutive models consists of three parts which represent three different interaction behaviors: a stiffness model (force-displace relation), a bonding model (shear and tensile strengths), and a slip model (frictional property). Three techniques were developed to reduce the computational time for AC viscoelastic simulations. It was found that the computational time was significantly reduced to days or hours from years or months for typical three-dimensional models. Dynamic modulus and creep stiffness tests were simulated and methodologies were developed to determine the viscoelastic parameters. It was found that the DE models could successfully predict dynamic modulus, phase angles, and creep stiffness in a wide range of frequencies, temperatures, and time spans. Mineral aggregate morphology characteristics (sphericity, orientation, and angularity) were studied to investigate their impacts on AC creep stiffness. It was found that aggregate characteristics significantly impact creep stiffness. Pavement responses and pavement-vehicle interactions were investigated by simulating pavement sections under a rolling wheel. It was found that wheel acceleration, steadily moving, and deceleration significantly impact contact forces. Additionally, summary and recommendations were provided in the last chapter and part of computer programming codes wree provided in the appendixes.

A system for 3-D reconstruction of a patient-specific surface model from calibrated X-ray images

This paper presents a system for 3-D reconstruction of a patient-specific surface model from calibrated X-ray images. Our system requires two X-ray images of a patient with one acquired from the anterior-posterior direction and the other from the axial direction. A custom-designed cage is utilized in our system to calibrate both images. Starting from bone contours that are interactively identified from the X-ray images, our system constructs a patient-specific surface model of the proximal femur based on a statistical model based 2D/3D reconstruction algorithm. In this paper, we present the design and validation of the system with 25 bones. An average reconstruction error of 0.95 mm was observed.

Algorithms For Automatic And Robust Registration Of 3D Head Scans

wo methods for registering laser-scans of human heads and transforming them to a new semantically consistent topology defined by a user-provided template mesh are described. Both algorithms are stated within the Iterative Closest Point framework. The first method is based on finding landmark correspondences by iteratively registering the vicinity of a landmark with a re-weighted error function. Thin-plate spline interpolation is then used to deform the template mesh and finally the scan is resampled in the topology of the deformed template. The second algorithm employs a morphable shape model, which can be computed from a database of laser-scans using the first algorithm. It directly optimizes pose and shape of the morphable model. The use of the algorithm with PCA mixture models, where the shape is split up into regions each described by an individual subspace, is addressed. Mixture models require either blending or regularization strategies, both of which are described in detail. For both algorithms, strategies for filling in missing geometry for incomplete laser-scans are described. While an interpolation-based approach can be used to fill in small or smooth regions, the model-driven algorithm is capable of fitting a plausible complete head mesh to arbitrarily small geometry, which is known as "shape completion". The importance of regularization in the case of extreme shape completion is shown.