Application and optimization of a thermal energy storage on a cruise ship

The thesis, developed in collaboration between the team Systems and Equipment for Energy and Environment of Bologna University and Chalmers University of Technology in Goteborg, aims to study the benefits resulting from the adoption of a thermal storage system for marine application. To that purpose a chruis ship has been considered. To reach the purpose has been used the software EGO (Energy Greed Optimization) developed by University of Bologna.

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.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Characterization and optimization of antigen-specific T cell responses during ex vivo expansion of melanoma tumor-infiltrating lymphocytes

Treatment of metastatic melanoma with tumor reactive T cells (adoptive T cell therapy, ACT) is a promising approach associated with a high clinical response rate. However, further optimization of this treatment modality is required to increase the clinical response after this therapy. ACT in melanoma involves an initial phase (pre-REP) of tumor-infiltrating lymphocyte (TIL) expansion ex vivo from tumor isolates followed by a second phase, “rapid expansion protocol” (REP) generating the billions of cells used as the TIL infusion product. The main question addressed in this thesis was how the currently used REP affected the responsiveness of the CD8+ T cells to defined melanoma antigens. We hypothesized that the REP drives the TIL to further differentiate and become hyporesponsive to antigen restimulation, therefore, proper cytokine treatment or other ways to expand TIL is required to improve upon this outcome. We evaluated the response of CD8+ TIL to melanoma antigen restimulation using MART-1 peptide-pulsed mature DC in vitro. Post-REP TILs were mostly hypo-responsive with poor proliferation and higher apoptosis. Phenotypic analysis revealed that the expression of CD28 was significantly reduced in post-REP TILs. By sorting experiment and microarray analysis, we confirmed that the few CD28+ post-REP TILs had superior survival capacity and proliferated after restimulation. We then went on to investigate methods to maintain CD28 expression during the REP and improve TIL responsiveness. Firstly, IL-15 and IL-21 were found to synergize in maintaining TIL CD28 expression and antigenic responsiveness during REP. Secondly, we found IL-15 was superior as compared to IL-2 in supporting the long-term expansion of antigen-specific CD8+ TIL after restimulation. These results suggest that current expansion protocols used for adoptive T-cell therapy in melanoma yield largely hyporesponsive products containing CD8+ T cells unable to respond in vivo to re-stimulation with antigen. A modification of our current approaches by using IL-15+IL-21 as supporting cytokines in the REP, or/and administration of IL-15 instead of IL-2 after TIL infusion, may enhance the anti-tumor efficacy and long-term persistence of infused T cells in vivo.

Preparation and optimization of calcium fluoride particles for dental applications.

Fluorides are used in dental care due to their beneficial effect in tooth enamel de-/remineralization cycles. To achieve a desired constant supply of soluble fluorides in the oral cavity, different approaches have been followed. Here we present results on the preparation of CaF2 particles and their characterization with respect to a potential application as enamel associated fluoride releasing reservoirs. CaF2 particles were synthesized by precipitation from soluble NaF and CaCl2 salt solutions of defined concentrations and their morphology analyzed by scanning electron microscopy. CaF2 particles with defined sizes and shapes could be synthesized by adjusting the concentrations of the precursor salt solutions. Such particles interacted with enamel surfaces when applied at fluoride concentrations correlating to typical dental care products. Fluoride release from the synthesized CaF2 particles was observed to be largely influenced by the concentration of phosphate in the solution. Physiological solutions with phosphate concentration similar to saliva (3.5 mM) reduced the fluoride release from pure CaF2 particles by a factor of 10-20 × as compared to phosphate free buffer solutions. Fluoride release was even lower in human saliva. The fluoride release could be increased by the addition of phosphate in substoichiometric amounts during CaF2 particle synthesis. The presented results demonstrate that the morphology and fluoride release characteristics of CaF2 particles can be tuned and provide evidence of the suitability of synthetic CaF2 particles as enamel associated fluoride reservoirs.

Regulating a Benzodifuran Single Molecule Redox Switch via Electrochemical Gating and Optimization of Molecule/Electrode Coupling

We report a novel strategy for the regulation of charge transport through single molecule junctions via the combination of external stimuli of electrode potential, internal modulation of molecular structures, and optimization of anchoring groups. We have designed redox-active benzodifuran (BDF) compounds as functional electronic units to fabricate metal–molecule–metal (m–M–m) junction devices by scanning tunneling microscopy (STM) and mechanically controllable break junctions (MCBJ). The conductance of thiol-terminated BDF can be tuned by changing the electrode potentials showing clearly an off/on/off single molecule redox switching effect. To optimize the response, a BDF molecule tailored with carbodithioate (−CS2–) anchoring groups was synthesized. Our studies show that replacement of thiol by carbodithioate not only enhances the junction conductance but also substantially improves the switching effect by enhancing the on/off ratio from 2.5 to 8.

Generation of an hTERT-restricted, CMV-augmented oncolytic adenovirus capable of tumor-specific transgene expression: Development, characterization, and optimization

Current shortcomings in cancer therapy require the generation of new, broadly applicable, potent, targeted treatments. Here, an adenovirus is engineered to replicate specifically in cells with active human telomerase promotion using a modified hTERT promoter, fused to a CMV promoter element. The virus was also modified to contain a visible reporter transgene, GFP. The virus, Ad/hTC-GFP-E1 was characterized in vitro and demonstrated tumor specific activity both by dose and over time course experiments in a variety of cell lines. In vivo, Ad/hTC-GFP-E1 was affected at suppressing tumor growth and providing a survival benefit without causing any measurable toxicity. To increase the host range of the vector, the fiber region was modified to contain an RGD-motif. The vector, AdRGD/hTC-GFP-E1, was recharacterized in vitro, revealing heightened levels of infectivity and toxicity however maintaining a therapeutic window between cancer and normal cell toxicity. AdRGD/hTC-GFP-E1 was administered in vivo by limb perfusion and was observed to be tumor specific both in expression and replication. To further enhance the efficacy of viral vectors in lung delivery, asthma medications were investigated for their abilities to enhance transgene delivery and expression. A combination of bronchodilators, mast cell inhibitors, and mucolytic agents was devised which demonstrated fold increases in expression in immunocompetent mouse lungs as single agents and more homogenous, intense levels of expression when done in combination of all agents. To characterize the methods in which some cancers are resistant or may become resistant to oncolytic treatments, several small molecule inhibitors of metabolic pathways were applied in combination with oncolytic infection in vitro. SP600125 and PD 98059, respective JNK and ERK inhibitors, successfully suppressed oncolytic toxicity, however did not affect infectivity or transgene expression of Ad/hTC-GFP-E1. JNK and ERK inhibition did significantly suppress viral replication, however, as analyzed by lysate transfer and titration assays. In contrast, SB 203580, an inhibitor for p38, did not demonstrate any protective effects with infected cells. Flow cytometric analysis indicated a possible correlation with G1 arrest and suppressed viral production, however more compounds must be investigated to clarify this observation. ^

Design and Optimization of Four-dimensional Cone-beam Computed Tomography in Image-guided Radiation Therapy

The influence of respiratory motion on patient anatomy poses a challenge to accurate radiation therapy, especially in lung cancer treatment. Modern radiation therapy planning uses models of tumor respiratory motion to account for target motion in targeting. The tumor motion model can be verified on a per-treatment session basis with four-dimensional cone-beam computed tomography (4D-CBCT), which acquires an image set of the dynamic target throughout the respiratory cycle during the therapy session. 4D-CBCT is undersampled if the scan time is too short. However, short scan time is desirable in clinical practice to reduce patient setup time. This dissertation presents the design and optimization of 4D-CBCT to reduce the impact of undersampling artifacts with short scan times. This work measures the impact of undersampling artifacts on the accuracy of target motion measurement under different sampling conditions and for various object sizes and motions. The results provide a minimum scan time such that the target tracking error is less than a specified tolerance. This work also presents new image reconstruction algorithms for reducing undersampling artifacts in undersampled datasets by taking advantage of the assumption that the relevant motion of interest is contained within a volume-of-interest (VOI). It is shown that the VOI-based reconstruction provides more accurate image intensity than standard reconstruction. The VOI-based reconstruction produced 43% fewer least-squares error inside the VOI and 84% fewer error throughout the image in a study designed to simulate target motion. The VOI-based reconstruction approach can reduce acquisition time and improve image quality in 4D-CBCT.

Design and Optimization of Power Delivery and Distribution Systems Using Evolutionary Computation Techniques

Nowadays computing platforms consist of a very large number of components that require to be supplied with diferent voltage levels and power requirements. Even a very small platform, like a handheld computer, may contain more than twenty diferent loads and voltage regulators. The power delivery designers of these systems are required to provide, in a very short time, the right power architecture that optimizes the performance, meets electrical specifications plus cost and size targets. The appropriate selection of the architecture and converters directly defines the performance of a given solution. Therefore, the designer needs to be able to evaluate a significant number of options in order to know with good certainty whether the selected solutions meet the size, energy eficiency and cost targets. The design dificulties of selecting the right solution arise due to the wide range of power conversion products provided by diferent manufacturers. These products range from discrete components (to build converters) to complete power conversion modules that employ diferent manufacturing technologies. Consequently, in most cases it is not possible to analyze all the alternatives (combinations of power architectures and converters) that can be built. The designer has to select a limited number of converters in order to simplify the analysis. In this thesis, in order to overcome the mentioned dificulties, a new design methodology for power supply systems is proposed. This methodology integrates evolutionary computation techniques in order to make possible analyzing a large number of possibilities. This exhaustive analysis helps the designer to quickly define a set of feasible solutions and select the best trade-off in performance according to each application. The proposed approach consists of two key steps, one for the automatic generation of architectures and other for the optimized selection of components. In this thesis are detailed the implementation of these two steps. The usefulness of the methodology is corroborated by contrasting the results using real problems and experiments designed to test the limits of the algorithms.

Integrated program debugging, verification, and optimization using abstract interpretation (and the Ciao system preprocessor)

The technique of Abstract Interpretation has allowed the development of very sophisticated global program analyses which are at the same time provably correct and practical. We present in a tutorial fashion a novel program development framework which uses abstract interpretation as a fundamental tool. The framework uses modular, incremental abstract interpretation to obtain information about the program. This information is used to validate programs, to detect bugs with respect to partial specifications written using assertions (in the program itself and/or in system libraries), to generate and simplify run-time tests, and to perform high-level program transformations such as multiple abstract specialization, parallelization, and resource usage control, all in a provably correct way. In the case of validation and debugging, the assertions can refer to a variety of program points such as procedure entry, procedure exit, points within procedures, or global computations. The system can reason with much richer information than, for example, traditional types. This includes data structure shape (including pointer sharing), bounds on data structure sizes, and other operational variable instantiation properties, as well as procedure-level properties such as determinacy, termination, nonfailure, and bounds on resource consumption (time or space cost). CiaoPP, the preprocessor of the Ciao multi-paradigm programming system, which implements the described functionality, will be used to illustrate the fundamental ideas.

A graph-based approach for latency modeling and optimization in multiview video encoding

We present a novel framework for encoding latency analysis of arbitrary multiview video coding prediction structures. This framework avoids the need to consider an specific encoder architecture for encoding latency analysis by assuming an unlimited processing capacity on the multiview encoder. Under this assumption, only the influence of the prediction structure and the processing times have to be considered, and the encoding latency is solved systematically by means of a graph model. The results obtained with this model are valid for a multiview encoder with sufficient processing capacity and serve as a lower bound otherwise. Furthermore, with the objective of low latency encoder design with low penalty on rate-distortion performance, the graph model allows us to identify the prediction relationships that add higher encoding latency to the encoder. Experimental results for JMVM prediction structures illustrate how low latency prediction structures with a low rate-distortion penalty can be derived in a systematic manner using the new model.

Adverse aerodynamics effects of a high speed train under the influence of cross winds, analysis and optimization of wind fence

The research work that here is summarized, it is classed on the area of dynamics and measures of railway safety, specifically in the study of the influence of the cross wind on the high-speed trains as well as the study of new mitigation measures like wind breaking structures or wind fences, with optimized shapes. The work has been developed in the Research Center in Rail Technology (CITEF), and supported by the Universidad Politécnica de Madrid, Spain.

Analysis and optimization of propagation losses in LiNbO3 optical waveguides produced by swift heavy-ion irradiation

The propagation losses (PL) of lithium niobate optical planar waveguides fabricated by swift heavy-ion irradiation (SHI), an alternative to conventional ion implantation, have been investigated and optimized. For waveguide fabrication, congruently melting LiNbO3 substrates were irradiated with F ions at 20 MeV or 30 MeV and fluences in the range 1013–1014 cm−2. The influence of the temperature and time of post-irradiation annealing treatments has been systematically studied. Optimum propagation losses lower than 0.5 dB/cm have been obtained for both TE and TM modes, after a two-stage annealing treatment at 350 and 375∘C. Possible loss mechanisms are discussed.