Development and Validation of a Model-Based Combustion Controller for Water Injection Management

This manuscript reports the overall development of a Ph.D. research project during the “Mechanics and advanced engineering sciences” course at the Department of Industrial Engineering of the University of Bologna. The project is focused on the development of a combustion control system for an innovative Spark Ignited engine layout. In details, the controller is oriented to manage a prototypal engine equipped with a Port Water Injection system. The water injection technology allows an increment of combustion efficiency due to the knock mitigation effect that permits to keep the combustion phasing closer to the optimal position with respect to the traditional layout. At the beginning of the project, the effects and the possible benefits achievable by water injection have been investigated by a focused experimental campaign. Then the data obtained by combustion analysis have been processed to design a control-oriented combustion model. The model identifies the correlation between Spark Advance, combustion phasing and injected water mass, and two different strategies are presented, both based on an analytic and semi-empirical approach and therefore compatible with a real-time application. The model has been implemented in a combustion controller that manages water injection to reach the best achievable combustion efficiency while keeping knock levels under a pre-established threshold. Three different versions of the algorithm are described in detail. This controller has been designed and pre-calibrated in a software-in-the-loop environment and later an experimental validation has been performed with a rapid control prototyping approach to highlight the performance of the system on real set-up. To further make the strategy implementable on an onboard application, an estimation algorithm of combustion phasing, necessary for the controller, has been developed during the last phase of the PhD Course, based on accelerometric signals.

Optimal bidding strategies of an electric vehicle aggregator in an electricity market

In recent years Electric Vehicles (EVs) are getting more importance as future transport systems, due to the increase of the concerns relevant to the greenhouse gases emission and the use fossil fuel. The management of the charging and discharging process of EVs could provide new business model for participating in the electricity markets. Moreover, vehicle to grid systems have the potential of increasing utility system flexibility. This thesis develops some models for the optimal integration of the EVs in the electricity market. In particular, the thesis focuses on the optimal bidding strategy of an EV aggregator participating to both the day ahead market and the secondary reserve market. The aggregator profit is maximized taking into account the energy balance equation, as well as the technical constraints of energy settlement, power supply and state of charge of the EVs. The results obtained by using the GAMS (General Algebraic Modelling System) environment are presented and discussed.

Development of a numerical platform for the modeling and optimal control of liquid metal flows

The main purpose of this work is to develop a numerical platform for the turbulence modeling and optimal control of liquid metal flows. Thanks to their interesting thermal properties, liquid metals are widely studied as coolants for heat transfer applications in the nuclear context. However, due to their low Prandtl numbers, the standard turbulence models commonly used for coolants as air or water are inadequate. Advanced turbulence models able to capture the anisotropy in the flow and heat transfer are then necessary. In this thesis, a new anisotropic four-parameter turbulence model is presented and validated. The proposed model is based on explicit algebraic models and solves four additional transport equations for dynamical and thermal turbulent variables. For the validation of the model, several flow configurations are considered for different Reynolds and Prandtl numbers, namely fully developed flows in a plane channel and cylindrical pipe, and forced and mixed convection in a backward-facing step geometry. Since buoyancy effects cannot be neglected in liquid metals-cooled fast reactors, the second aim of this work is to provide mathematical and numerical tools for the simulation and optimization of liquid metals in mixed and natural convection. Optimal control problems for turbulent buoyant flows are studied and analyzed with the Lagrange multipliers method. Numerical algorithms for optimal control problems are integrated into the numerical platform and several simulations are performed to show the robustness, consistency, and feasibility of the method.

Longitudinal Micro CT-driven biomarkers as a tool to evaluate lung fibrosis progression and antifibrotic efficacy in a refined Bleomycin mouse model

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive disease with no curative pharmacological treatment. Animal models play an essential role in revealing molecular mechanisms involved in the pathogenesis of the disease. Bleomycin (BLM)-induced lung fibrosis is the most widely used and characterized model for anti-fibrotic drugs screening. However, several issues have been reported, such as the identification of an optimal BLM dose and administration scheme as well as gender-specificity. Moreover, the balance between disease resolution, an appropriate time window for therapeutic intervention and animal welfare remains critical aspects yet to be fully elucidated. In this thesis, Micro CT imaging has been used as a tool to identify the ideal BLM dose regimen to induce sustained lung fibrosis in mice as well as to assess the anti-fibrotic effect of Nintedanib (NINT) treatment upon this BLM administration regimen. In order to select the optimal BLM dose scheme, C57bl/6 male mice were treated with BLM via oropharyngeal aspiration (OA), following either double or triple BLM administration. The triple BLM administration resulted in the most promising scheme, able to balance disease resolution, appropriate time-window for therapeutic intervention and animal welfare. The fibrosis progression was longitudinally assessed by micro-CT every 7 days for 5 weeks after BLM administration and 5 animals were sacrificed at each timepoint for the BALF and histological evaluation. The antifibrotic effect of NINT was assessed following different treatment regimens in this model. Herein, we have developed an optimized mouse model of pulmonary fibrosis, enabling three weeks of the therapeutic window to screen putative anti-fibrotic drugs. micro-CT scanning, allowed us to monitor the progression of lung fibrosis and the therapeutical response longitudinally in the same subject, drastically reducing the number of animals involved in the experiment.

Modeling and Model Predictive Control of an Industrial Hydraulic System

This thesis aims to illustrate the construction of a mathematical model of a hydraulic system, oriented to the design of a model predictive control (MPC) algorithm. The modeling procedure starts with the basic formulation of a piston-servovalve system. The latter is a complex non linear system with some unknown and not measurable effects that constitute a challenging problem for the modeling procedure. The first level of approximation for system parameters is obtained basing on datasheet informations, provided workbench tests and other data from the company. Then, to validate and refine the model, open-loop simulations have been made for data matching with the characteristics obtained from real acquisitions. The final developed set of ODEs captures all the main peculiarities of the system despite some characteristics due to highly varying and unknown hydraulic effects, like the unmodeled resistive elements of the pipes. After an accurate analysis, since the model presents many internal complexities, a simplified version is presented. The latter is used to linearize and discretize correctly the non linear model. Basing on that, a MPC algorithm for reference tracking with linear constraints is implemented. The results obtained show the potential of MPC in this kind of industrial applications, thus a high quality tracking performances while satisfying state and input constraints. The increased robustness and flexibility are evident with respect to the standard control techniques, such as PID controllers, adopted for these systems. The simulations for model validation and the controlled system have been carried out in a Python code environment.

Circumplex Model to analyze the impact of emotions on decision-making processes in innovation management

Group work allows participants to pool their thoughts and examine difficulties from several angles. In these settings, it is possible to attempt things that an individual could not achieve, combining a variety of abilities and knowledge to tackle more complicated and large-scale challenges. That’s why nowadays collaborative work is becoming more and more widespread to solve complex innovation dilemmas. Since innovation isn’t a tangible thing, most innovation teams used to take decisions based on performance KPIs such as forecasted engagement, projected profitability, investments required, cultural impacts etc. Have you ever wondered the reason why sometimes innovation group processes come out with decisions which are not the optimal meeting point of all the KPIs? Has this decision been influenced by other factors? Some researchers account part of this phenomenon to the emotions in group-based interaction between participants. I will develop a literature review that is split into three parts: first, I will consider some emotions theories from an individual perspective; secondly, a wider view of collective interactions theories will be provided; lastly, I will supply some recent collective interaction empirical studies. After the theoretical and empirical gaps have been tackled, the study will additionally move forward with a methodological point of view, about the Circumplex Model, which is the model I used to evaluate emotions in my research. This model has been applied to SUGAR project, which is the biggest design thinking academy worldwide.

An optimal control tool for trajectory generation of autonomous drones

In the recent years, autonomous aerial vehicles gained large popularity in a variety of applications in the field of automation. To accomplish various and challenging tasks the capability of generating trajectories has assumed a key role. As higher performances are sought, traditional, flatness-based trajectory generation schemes present their limitations. In these approaches the highly nonlinear dynamics of the quadrotor is, indeed, neglected. Therefore, strategies based on optimal control principles turn out to be beneficial, since in the trajectory generation process they allow the control unit to best exploit the actual dynamics, and enable the drone to perform quite aggressive maneuvers. This dissertation is then concerned with the development of an optimal control technique to generate trajectories for autonomous drones. The algorithm adopted to this end is a second-order iterative method working directly in continuous-time, which, under proper initialization, guarantees quadratic convergence to a locally optimal trajectory. At each iteration a quadratic approximation of the cost functional is minimized and a decreasing direction is then obtained as a linear-affine control law, after solving a differential Riccati equation. The algorithm has been implemented and its effectiveness has been tested on the vectored-thrust dynamical model of a quadrotor in a realistic simulative setup.

A deep learning model for controlling the galvanizing process in a production line

In the industry of steelmaking, the process of galvanizing is a treatment which is applied to protect the steel from corrosion. The air knife effect (AKE) occurs when nozzles emit a steam of air on the surfaces of a steel strip to remove excess zinc from it. In our work we formalized the problem to control the AKE and we implemented, with the R&D dept.of MarcegagliaSPA, a DL model able to drive the AKE. We call it controller. It takes as input the tuple : a tuple of the physical conditions of the process line (t,h,s) with the target value of the zinc coating (c); and generates the expected tuple of (pres and dist) to drive the mechanical nozzles towards the (c). According to the requirements we designed the structure of the network. We collected and explored the data set of the historical data of the smart factory. Finally, we designed the loss function as sum of three components: the minimization between the coating addressed by the network and the target value we want to reach; and two weighted minimization components for both pressure and distance. In our solution we construct a second module, named coating net, to predict the coating of zinc resulting from the AKE when the conditions are applied to the prod. line. Its structure is made by a linear and a deep nonlinear “residual” component learned by empirical observations. The predictions made by the coating nets are used as ground truth in the loss function of the controller. By tuning the weights of the different components of the loss function, it is possible to train models with slightly different optimization purposes. In the tests we compared the regularization of different strategies with the standard one in condition of optimal estimation for both; the overall accuracy is ± 3 g/m^2 dal target for all of them. Lastly, we analyze how the controller modeled the current solutions with the new logic: the sub-optimal values of pres and dist can be optimize of 50% and 20%.

Integrated Proteomics Identified Up-regulated Focal Adhesion-mediated Proteins In Human Squamous Cell Carcinoma In An Orthotopic Murine Model.

Understanding the molecular mechanisms of oral carcinogenesis will yield important advances in diagnostics, prognostics, effective treatment, and outcome of oral cancer. Hence, in this study we have investigated the proteomic and peptidomic profiles by combining an orthotopic murine model of oral squamous cell carcinoma (OSCC), mass spectrometry-based proteomics and biological network analysis. Our results indicated the up-regulation of proteins involved in actin cytoskeleton organization and cell-cell junction assembly events and their expression was validated in human OSCC tissues. In addition, the functional relevance of talin-1 in OSCC adhesion, migration and invasion was demonstrated. Taken together, this study identified specific processes deregulated in oral cancer and provided novel refined OSCC-targeting molecules.

Electronic And Structural Study Of Pt-modified Au Vicinal Surfaces: A Model System For Pt-au Catalysts.

Two single crystalline surfaces of Au vicinal to the (111) plane were modified with Pt and studied using scanning tunneling microscopy (STM) and X-ray photoemission spectroscopy (XPS) in ultra-high vacuum environment. The vicinal surfaces studied are Au(332) and Au(887) and different Pt coverage (θPt) were deposited on each surface. From STM images we determine that Pt deposits on both surfaces as nanoislands with heights ranging from 1 ML to 3 ML depending on θPt. On both surfaces the early growth of Pt ad-islands occurs at the lower part of the step edge, with Pt ad-atoms being incorporated into the steps in some cases. XPS results indicate that partial alloying of Pt occurs at the interface at room temperature and at all coverage, as suggested by the negative chemical shift of Pt 4f core line, indicating an upward shift of the d-band center of the alloyed Pt. Also, the existence of a segregated Pt phase especially at higher coverage is detected by XPS. Sample annealing indicates that the temperature rise promotes a further incorporation of Pt atoms into the Au substrate as supported by STM and XPS results. Additionally, the catalytic activity of different PtAu systems reported in the literature for some electrochemical reactions is discussed considering our findings.

Doehlert Design-desirability Function Multi-criteria Optimal Separation Of 17 Phenolic Compounds From Extra-virgin Olive Oil By Capillary Zone Electrophoresis.

In Brazil, the consumption of extra-virgin olive oil (EVOO) is increasing annually, but there are no experimental studies concerning the phenolic compound contents of commercial EVOO. The aim of this work was to optimise the separation of 17 phenolic compounds already detected in EVOO. A Doehlert matrix experimental design was used, evaluating the effects of pH and electrolyte concentration. Resolution, runtime and migration time relative standard deviation values were evaluated. Derringer's desirability function was used to simultaneously optimise all 37 responses. The 17 peaks were separated in 19min using a fused-silica capillary (50μm internal diameter, 72cm of effective length) with an extended light path and 101.3mmolL(-1) of boric acid electrolyte (pH 9.15, 30kV). The method was validated and applied to 15 EVOO samples found in Brazilian supermarkets.

The Soluble Guanylyl Cyclase Activator Bay 60-2770 Potently Relaxes The Pulmonary Artery On Congenital Diaphragmatic Hernia Rabbit Model.

Congenital diaphragmatic hernia (CDH) is associated with pulmonary hypertension which is often difficult to manage, and a significant cause of morbidity and mortality. In this study, we have used a rabbit model of CDH to evaluate the effects of BAY 60-2770 on the in vitro reactivity of left pulmonary artery. CDH was performed in New Zealand rabbit fetuses (n = 10 per group) and compared to controls. Measurements of body, total and left lung weights (BW, TLW, LLW) were done. Pulmonary artery rings were pre-contracted with phenylephrine (10 μM), after which cumulative concentration-response curves to glyceryl trinitrate (GTN; NO donor), tadalafil (PDE5 inhibitor) and BAY 60-2770 (sGC activator) were obtained as well as the levels of NO (NO3/NO2). LLW, TLW and LBR were decreased in CDH (p < 0.05). In left pulmonary artery, the potency (pEC50) for GTN was markedly lower in CDH (8.25 ± 0.02 versus 9.27 ± 0.03; p < 0.01). In contrast, the potency for BAY 60-2770 was markedly greater in CDH (11.7 ± 0.03 versus 10.5 ± 0.06; p < 0.01). The NO2/NO3 levels were 62 % higher in CDH (p < 0.05). BAY 60-2770 exhibits a greater potency to relax the pulmonary artery in CDH, indicating a potential use for pulmonary hypertension in this disease.

Bay 41-2272, A Soluble Guanylate Cyclase Stimulator, Relaxes Isolated Human Ureter In A Standardized In Vitro Model.

To characterize the relaxation induced by BAY 41-2272 in human ureteral segments. Ureter specimens (n = 17) from multiple organ human deceased donors (mean age 40 ± 3.2 years, male/female ratio 2:1) were used to characterize the relaxing response of BAY 41-2272. Immunohistochemical analysis for endothelial and neuronal nitric oxide synthase, guanylate cyclase stimulator (sGC) and type 5 phosphodiesterase was also performed. The potency values were determined as the negative log of the molar to produce 50% of the maximal relaxation in potassium chloride-precontracted specimens. The unpaired Student t test was used for the comparisons. Immunohistochemistry revealed the presence of endothelial nitric oxide synthase in vessel endothelia and neuronal nitric oxide synthase in urothelium and nerve structures. sGC was expressed in the smooth muscle and urothelium layer, and type 5 phosphodiesterase was present in the smooth muscle only. BAY 41-2272 (0.001-100 μM) relaxed the isolated ureter in a concentration dependent manner, with a potency and maximal relaxation value of 5.82 ± 0.14 and 84% ± 5%, respectively. The addition of nitric oxide synthase and sGC inhibitors reduced the maximal relaxation values by 21% and 45%, respectively. However, the presence of sildenafil (100 nM) significantly potentiated (6.47 ± 0.10, P <.05) this response. Neither glibenclamide or tetraethylammonium nor ureteral urothelium removal influenced the relaxation response by BAY 41-2272. BAY 41-2272 relaxes the human isolated ureter in a concentration-dependent manner, mainly by activating the sGC enzyme in smooth muscle cells rather than in the urothelium, although a cyclic guanosine monophosphate-independent mechanism might have a role. The potassium channels do not seem to be involved.

Atomic Charge Transfer-counter Polarization Effects Determine Infrared Ch Intensities Of Hydrocarbons: A Quantum Theory Of Atoms In Molecules Model.

Atomic charge transfer-counter polarization effects determine most of the infrared fundamental CH intensities of simple hydrocarbons, methane, ethylene, ethane, propyne, cyclopropane and allene. The quantum theory of atoms in molecules/charge-charge flux-dipole flux model predicted the values of 30 CH intensities ranging from 0 to 123 km mol(-1) with a root mean square (rms) error of only 4.2 km mol(-1) without including a specific equilibrium atomic charge term. Sums of the contributions from terms involving charge flux and/or dipole flux averaged 20.3 km mol(-1), about ten times larger than the average charge contribution of 2.0 km mol(-1). The only notable exceptions are the CH stretching and bending intensities of acetylene and two of the propyne vibrations for hydrogens bound to sp hybridized carbon atoms. Calculations were carried out at four quantum levels, MP2/6-311++G(3d,3p), MP2/cc-pVTZ, QCISD/6-311++G(3d,3p) and QCISD/cc-pVTZ. The results calculated at the QCISD level are the most accurate among the four with root mean square errors of 4.7 and 5.0 km mol(-1) for the 6-311++G(3d,3p) and cc-pVTZ basis sets. These values are close to the estimated aggregate experimental error of the hydrocarbon intensities, 4.0 km mol(-1). The atomic charge transfer-counter polarization effect is much larger than the charge effect for the results of all four quantum levels. Charge transfer-counter polarization effects are expected to also be important in vibrations of more polar molecules for which equilibrium charge contributions can be large.

Mesenchymal Stromal Cells From Adipose Tissue Attached To Suture Material Enhance The Closure Of Enterocutaneous Fistulas In A Rat Model.

Surgical treatment for enterocutaneous fistulas (EF) frequently fails. Cell therapy may represent a new approach to treatment. Mesenchymal stromal cells (MSCs) have high proliferative and differentiation capacity. This study aimed to investigate whether MSCs could adhere to suture filament (SF), promoting better EF healing. MSCs, 1 × 10(6), from adipose tissue (ATMSCs) were adhered to a Polyvicryl SF by adding a specific fibrin glue formulation. Adhesion was confirmed by confocal and scanning electron microscopy (SEM). A cecal fistula was created in 22 Wistar rats by incising the cecum and suturing the opening to the surgical wound subcutaneously with four separate stitches. The animals were randomly allocated to three groups: control (CG)-five animals, EF performed; injection (IG)-eight animals 1 × 10(6) ATMSCs injected around EF borders; and suture filament (SG): nine animals, sutured with 1 × 10(6) ATMSCs attached to the filaments with fibrin glue. Fistulas were photographed on the operation day and every 3 days until the 21st day and analyzed by two observers using ImageJ Software. Confocal and SEM results demonstrated ATMSCs adhered to SF (ATMSCs-SF). The average reduction size of the fistula area at 21st day was greater for the SG group (90.34%, P < 0.05) than the IG (71.80%) and CG (46.54%) groups. ATMSCs adhered to SF maintain viability and proliferative capacity. EF submitted to ATMSCs-SF procedure showed greater recovery and healing. This approach might be a new and effective tool for EF treatment.