Modeling of burden distribution in the blast furnace

The blast furnace is the main ironmaking production unit in the world which converts iron ore with coke and hot blast into liquid iron, hot metal, which is used for steelmaking. The furnace acts as a counter-current reactor charged with layers of raw material of very different gas permeability. The arrangement of these layers, or burden distribution, is the most important factor influencing the gas flow conditions inside the furnace, which dictate the efficiency of the heat transfer and reduction processes. For proper control the furnace operators should know the overall conditions in the furnace and be able to predict how control actions affect the state of the furnace. However, due to high temperatures and pressure, hostile atmosphere and mechanical wear it is very difficult to measure internal variables. Instead, the operators have to rely extensively on measurements obtained at the boundaries of the furnace and make their decisions on the basis of heuristic rules and results from mathematical models. It is particularly difficult to understand the distribution of the burden materials because of the complex behavior of the particulate materials during charging. The aim of this doctoral thesis is to clarify some aspects of burden distribution and to develop tools that can aid the decision-making process in the control of the burden and gas distribution in the blast furnace. A relatively simple mathematical model was created for simulation of the distribution of the burden material with a bell-less top charging system. The model developed is fast and it can therefore be used by the operators to gain understanding of the formation of layers for different charging programs. The results were verified by findings from charging experiments using a small-scale charging rig at the laboratory. A basic gas flow model was developed which utilized the results of the burden distribution model to estimate the gas permeability of the upper part of the blast furnace. This combined formulation for gas and burden distribution made it possible to implement a search for the best combination of charging parameters to achieve a target gas temperature distribution. As this mathematical task is discontinuous and non-differentiable, a genetic algorithm was applied to solve the optimization problem. It was demonstrated that the method was able to evolve optimal charging programs that fulfilled the target conditions. Even though the burden distribution model provides information about the layer structure, it neglects some effects which influence the results, such as mixed layer formation and coke collapse. A more accurate numerical method for studying particle mechanics, the Discrete Element Method (DEM), was used to study some aspects of the charging process more closely. Model charging programs were simulated using DEM and compared with the results from small-scale experiments. The mixed layer was defined and the voidage of mixed layers was estimated. The mixed layer was found to have about 12% less voidage than layers of the individual burden components. Finally, a model for predicting the extent of coke collapse when heavier pellets are charged over a layer of lighter coke particles was formulated based on slope stability theory, and was used to update the coke layer distribution after charging in the mathematical model. In designing this revision, results from DEM simulations and charging experiments for some charging programs were used. The findings from the coke collapse analysis can be used to design charging programs with more stable coke layers.

All-regime Lagrangian-Remap numerical schemes for the gas dynamics equations. Applications to the large friction and low Mach coefficients

In this talk, we propose an all regime Lagrange-Projection like numerical scheme for the gas dynamics equations. By all regime, we mean that the numerical scheme is able to compute accurate approximate solutions with an under-resolved discretization with respect to the Mach number M, i.e. such that the ratio between the Mach number M and the mesh size or the time step is small with respect to 1. The key idea is to decouple acoustic and transport phenomenon and then alter the numerical flux in the acoustic approximation to obtain a uniform truncation error in term of M. This modified scheme is conservative and endowed with good stability properties with respect to the positivity of the density and the internal energy. A discrete entropy inequality under a condition on the modification is obtained thanks to a reinterpretation of the modified scheme in the Harten Lax and van Leer formalism. A natural extension to multi-dimensional problems discretized over unstructured mesh is proposed. Then a simple and efficient semi implicit scheme is also proposed. The resulting scheme is stable under a CFL condition driven by the (slow) material waves and not by the (fast) acoustic waves and so verifies the all regime property. Numerical evidences are proposed and show the ability of the scheme to deal with tests where the flow regime may vary from low to high Mach values.

Estudo paramétrico da segregação gravitacional na injeção contínua de vapor

Steam injection is the most used method of additional recovery for the extraction of heavy oil. In this type procedure is common to happen gravitational segregation and this phenomenon can affect the production of oil and therefore, it shoulds be considered in the projects of continuous steam injection. For many years, the gravitational segregation was not adequately considered in the calculation procedures in Reservoir Engineering. The effect of the gravity causes the segregation of fluids inside the porous media according to their densities. The results of simulation arising from reservoirs could provide the ability to deal with the gravity, and it became apparent that the effects of the gravity could significantly affect the performance of the reservoir. It know that the gravitational segregation can happen in almost every case where there is injection of light fluid, specially the steam, and occurs with greater intensity for viscous oil reservoirs. This work discusses the influence of some parameters of the rock-reservoir in segregation as viscosity, permeability, thickness, cover gas, porosity. From a model that shows the phenomenon with greater intensity, optimized some operational parameters as the rate flow rate steam, distance between the wells injector-producer, and interval of completion which contributed to the reduction in gravity override, thus increasing the oil recovery. It was shown a greater technical-economic viability for the model of distance between the wells 100 m. The analysis was performed using the simulator of CMG (Computer Modeling Group-Stars 2007.11, in which was observed by iterating between studied variables in heavy oil reservoirs with similar characteristics to Brazilian Northeast

Estudo paramétrico da recuperação de petróleo pesado por aquecimento eletromagnético resistivo

Electrical resistive heating (ERH) is a thermal method used to improve oil recovery. It can increase oil rate and oil recovery due to temperature increase caused by electrical current passage through oil zone. ERH has some advantage compared with well-known thermal methods such as continuous steam flood, presenting low-water production. This method can be applied to reservoirs with different characteristics and initial reservoir conditions. Commercial software was used to test several cases using a semi-synthetic homogeneous reservoir with some characteristics as found in northeast Brazilian basins. It was realized a sensitivity analysis of some reservoir parameters, such as: oil zone, aquifer presence, gas cap presence and oil saturation on oil recovery and energy consumption. Then it was tested several cases studying the electrical variables considered more important in the process, such as: voltage, electrical configurations and electrodes positions. Energy optimization by electrodes voltage levels changes and electrical settings modify the intensity and the electrical current distribution in oil zone and, consequently, their influences in reservoir temperature reached at some regions. Results show which reservoir parameters were significant in order to improve oil recovery and energy requirement in for each reservoir. Most significant parameters on oil recovery and electrical energy delivered were oil thickness, presence of aquifer, presence of gas cap, voltage, electrical configuration and electrodes positions. Factors such as: connate water, water salinity and relative permeability to water at irreducible oil saturation had low influence on oil recovery but had some influence in energy requirements. It was possible to optimize energy consumption and oil recovery by electrical variables. Energy requirements can decrease by changing electrodes voltages during the process. This application can be extended to heavy oil reservoirs of high depth, such as offshore fields, where nowadays it is not applicable any conventional thermal process such as steam flooding

Modeling the Effect of Vapor Wall Deposition on the Formation of Secondary Organic Aerosol in Chamber Studies

Laboratory chamber experiments are used to investigate formation of secondary organic aerosol (SOA) from biogenic and anthropogenic precursors under a variety of environmental conditions. Simulations of these experiments test our understanding of the prevailing chemistry of SOA formation as well as the dynamic processes occurring in the chamber itself. One dynamic process occurring in the chamber that was only recently recognized is the deposition of vapor species to the Teflon walls of the chamber. Low-volatility products formed from the oxidation of volatile organic compounds (VOCs) deposit on the walls rather than forming SOA, decreasing the amount of SOA formed (quantified as the SOA yield: mass of SOA formed per mass of VOC reacted). In this work, several modeling studies are presented that address the effect of vapor wall deposition on SOA formation in chambers.

A coupled vapor-particle dynamics model is used to examine the competition among the rates of gas-phase oxidation to low volatility products, wall deposition of these products, and mass transfer to the particle phase. The relative time scales of these rates control the amount of SOA formed by affecting the influence of vapor wall deposition. Simulations show that an effect on SOA yield of changing the vapor-particle mass transfer rate is only observed when SOA formation is kinetically limited. For systems with kinetically limited SOA formation, increasing the rate of vapor-particle mass transfer by increasing the concentration of seed particles is an effective way to minimize the effect of vapor wall deposition.

This coupled vapor-particle dynamics model is then applied to α-pinene ozonolysis SOA experiments. Experiments show that the SOA yield is affected when changing the oxidation rate but not when changing the rate of gas-particle mass transfer by changing the concentration of seed particles. Model simulations show that the absence of an effect of changing the seed particle concentration is consistent with SOA formation being governed by quasi-equilibrium growth, in which gas-particle equilibrium is established much faster than the rate of change of the gas-phase concentration. The observed effect of oxidation rate on SOA yield arises due to the presence of vapor wall deposition: gas-phase oxidation products are produced more quickly and condense preferentially onto seed particles before being lost to the walls. Therefore, for α-pinene ozonolysis, increasing the oxidation rate is the most effective way to mitigate the influence of vapor wall deposition.

Finally, the detailed model GECKO-A (Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere) is used to simulate α-pinene photooxidation SOA experiments. Unexpectedly, α-pinene OH oxidation experiments show no effect when changing either the oxidation rate or the vapor-particle mass transfer rate, whereas GECKO-A predicts that changing the oxidation rate should drastically affect the SOA yield. Sensitivity studies show that the assumed magnitude of the vapor wall deposition rate can greatly affect conclusions drawn from comparisons between simulations and experiments. If vapor wall loss in the Caltech chamber is of order 10^-5 s^-1, GECKO-A greatly overpredicts SOA during high UV experiments, likely due to an overprediction of second-generation products. However, if instead vapor wall loss in the Caltech chamber is of order 10^-3 s^-1, GECKO-A greatly underpredicts SOA during low UV experiments, possibly due to missing autoxidation pathways in the α-pinene mechanism.

MODELING AND EXPERIMENTAL SETUP OF AN HCCI ENGINE

For the past three decades the automotive industry is facing two main conflicting challenges to improve fuel economy and meet emissions standards. This has driven the engineers and researchers around the world to develop engines and powertrain which can meet these two daunting challenges. Focusing on the internal combustion engines there are very few options to enhance their performance beyond the current standards without increasing the price considerably. The Homogeneous Charge Compression Ignition (HCCI) engine technology is one of the combustion techniques which has the potential to partially meet the current critical challenges including CAFE standards and stringent EPA emissions standards. HCCI works on very lean mixtures compared to current SI engines, resulting in very low combustion temperatures and ultra-low NOx emissions. These engines when controlled accurately result in ultra-low soot formation. On the other hand HCCI engines face a problem of high unburnt hydrocarbon and carbon monoxide emissions. This technology also faces acute combustion controls problem, which if not dealt properly with yields highly unfavorable operating conditions and exhaust emissions. This thesis contains two main parts. One part deals in developing an HCCI experimental setup and the other focusses on developing a grey box modelling technique to control HCCI exhaust gas emissions. The experimental part gives the complete details on modification made on the stock engine to run in HCCI mode. This part also comprises details and specifications of all the sensors, actuators and other auxiliary parts attached to the conventional SI engine in order to run and monitor the engine in SI mode and future SI-HCCI mode switching studies. In the latter part around 600 data points from two different HCCI setups for two different engines are studied. A grey-box model for emission prediction is developed. The grey box model is trained with the use of 75% data and the remaining data is used for validation purpose. An average of 70% increase in accuracy for predicting engine performance is found while using the grey-box over an empirical (black box) model during this study. The grey-box model provides a solution for the difficulty faced for real time control of an HCCI engine. The grey-box model in this thesis is the first study in literature to develop a control oriented model for predicting HCCI engine emissions for control.

ADVANCED COMPUTATIONAL MODELING OF THE INTERNAL STRUCTURE OF SMART WIND-TURBINE BLADES

Implementation of stable aeroelastic models with the ability to capture the complex features of Multi concept smartblades is a prime step in reducing the uncertainties that come along with blade dynamics. The numerical simulations of fluid structure interaction can thus be used to test a realistic scenarios comprising of full-scale blades at a reasonably low computational cost. A code which was a combination of two advanced numerical models was designed and was run with the help of paralell HPC supercomputer platform. The first model was based on a variation of dimensional reduction technique proposed by Hodges and Yu. This model was the one to record the structural response of heterogenous composite blades. This technique reduces the geometrical complexities of the heterogenous blade section into a stiffness matrix for an equivalent beam. This derived equivalent 1-D strain energy matrix is similar to the actual 3-D strain energy matrix in an asymptotic sense. As this 1-D matrix helps in accurately modeling the blade structure as a 1-D finite element problem, this substantially redues the computational effort and subsequently the computational cost that are required to model the structural dynamics at each step. Second model comprises of implementation of the Blade Element Momentum Theory. In this approach we map all the velocities and the forces with the help of orthogonal matrices that help in capturing the large deformations and the effects of rotations in calculating the aerodynamic forces. This ultimately helps us to take into account the complex flexo torsional deformations. In this thesis we have succesfully tested these computayinal tools developed by MTU’s research team lead by for the aero elastic analysis of wind-turbine blades. The validation in this thesis is majorly based on several experiments done on NREL-5MW blade, as this is widely accepted as a benchmark blade in the wind industry. Along with the use of this innovative model the internal blade structure was also changed to add up to the existing benefits of the already advanced numerical models.

Physics-Based Modeling of Power System Components for the Evaluation of Low-Frequency Radiated Electromagnetic Fields

The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system’s EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter’s components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled

Modeling, Simulation, and Characterization of Space Debris in low-Earth Orbit

Every space launch increases the overall amount of space debris. Satellites have limited awareness of nearby objects that might pose a collision hazard. Astrometric, radiometric, and thermal models for the study of space debris in low-Earth orbit have been developed. This modeled approach proposes analysis methods that provide increased Local Area Awareness for satellites in low-Earth and geostationary orbit. Local Area Awareness is defined as the ability to detect, characterize, and extract useful information regarding resident space objects as they move through the space environment surrounding a spacecraft. The study of space debris is of critical importance to all space-faring nations. Characterization efforts are proposed using long-wave infrared sensors for space-based observations of debris objects in low-Earth orbit. Long-wave infrared sensors are commercially available and do not require solar illumination to be observed, as their received signal is temperature dependent. The characterization of debris objects through means of passive imaging techniques allows for further studies into the origination, specifications, and future trajectory of debris objects. Conclusions are made regarding the aforementioned thermal analysis as a function of debris orbit, geometry, orientation with respect to time, and material properties. Development of a thermal model permits the characterization of debris objects based upon their received long-wave infrared signals. Information regarding the material type, size, and tumble-rate of the observed debris objects are extracted. This investigation proposes the utilization of long-wave infrared radiometric models of typical debris to develop techniques for the detection and characterization of debris objects via signal analysis of unresolved imagery. Knowledge regarding the orbital type and semi-major axis of the observed debris object are extracted via astrometric analysis. This knowledge may aid in the constraint of the admissible region for the initial orbit determination process. The resultant orbital information is then fused with the radiometric characterization analysis enabling further characterization efforts of the observed debris object. This fused analysis, yielding orbital, material, and thermal properties, significantly increases a satellite’s Local Area Awareness via an intimate understanding of the debris environment surrounding the spacecraft.

Modeling, control and field tests on an experimental irrigation canal

Irrigation canals are complex hydraulic systems difficult to control. Many models and control strategies have already been developed using linear control theory. In the present study, a PI controller is developed and implemented in a brand new prototype canal and its features evaluated experimentally. The base model relies on the linearized Saint-Venant equations which is compared with a reservoir model to check its accuracy. This technique will prove its capability and versatility in tuning properly a controller for this kind of systems.

Large scale underground energy storage for renewables integration: general criteria for reservoir identification and viable technologies.

The increasing integration of renewable energies in the electricity grid contributes considerably to achieve the European Union goals on energy and Greenhouse Gases (GHG) emissions reduction. However, it also brings problems to grid management. Large scale energy storage can provide the means for a better integration of the renewable energy sources, for balancing supply and demand, to increase energy security, to enhance a better management of the grid and also to converge towards a low carbon economy. Geological formations have the potential to store large volumes of fluids with minimal impact to environment and society. One of the ways to ensure a large scale energy storage is to use the storage capacity in geological reservoir. In fact, there are several viable technologies for underground energy storage, as well as several types of underground reservoirs that can be considered. The geological energy storage technologies considered in this research were: Underground Gas Storage (UGS), Hydrogen Storage (HS), Compressed Air Energy Storage (CAES), Underground Pumped Hydro Storage (UPHS) and Thermal Energy Storage (TES). For these different types of underground energy storage technologies there are several types of geological reservoirs that can be suitable, namely: depleted hydrocarbon reservoirs, aquifers, salt formations and caverns, engineered rock caverns and abandoned mines. Specific site screening criteria are applicable to each of these reservoir types and technologies, which determines the viability of the reservoir itself, and of the technology for any particular site. This paper presents a review of the criteria applied in the scope of the Portuguese contribution to the EU funded project ESTMAP – Energy Storage Mapping and Planning.

Thermal and air quality modeling of an electric vehicle cabin with low-cost sensors and reinforcement learning

The design process of any electric vehicle system has to be oriented towards the best energy efficiency, together with the constraint of maintaining comfort in the vehicle cabin. Main aim of this study is to research the best thermal management solution in terms of HVAC efficiency without compromising occupant’s comfort and internal air quality. An Arduino controlled Low Cost System of Sensors was developed and compared against reference instrumentation (average R-squared of 0.92) and then used to characterise the vehicle cabin in real parking and driving conditions trials. Data on the energy use of the HVAC was retrieved from the car On-Board Diagnostic port. Energy savings using recirculation can reach 30 %, but pollutants concentration in the cabin builds up in this operating mode. Moreover, the temperature profile appeared strongly nonuniform with air temperature differences up to 10° C. Optimisation methods often require a high number of runs to find the optimal configuration of the system. Fast models proved to be beneficial for these task, while CFD-1D model are usually slower despite the higher level of detail provided. In this work, the collected dataset was used to train a fast ML model of both cabin and HVAC using linear regression. Average scaled RMSE over all trials is 0.4 %, while computation time is 0.0077 ms for each second of simulated time on a laptop computer. Finally, a reinforcement learning environment was built in OpenAI and Stable-Baselines3 using the built-in Proximal Policy Optimisation algorithm to update the policy and seek for the best compromise between comfort, air quality and energy reward terms. The learning curves show an oscillating behaviour overall, with only 2 experiments behaving as expected even if too slow. This result leaves large room for improvement, ranging from the reward function engineering to the expansion of the ML model.

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.

Short-term Physiological Changes In Roots And Leaves Of Sugarcane Varieties Exposed To H2o2 In Root Medium.

The aim of this study was to evaluate the differential sensitivity of sugarcane genotypes to H2O2 in root medium. As a hypothesis, the drought tolerant genotype would be able to minimize the oxidative damage and maintain the water transport from roots to shoots, reducing the negative effects on photosynthesis. The sugarcane genotypes IACSP94-2094 (drought tolerant) and IACSP94-2101 (drought sensitive) were grown in a growth chamber and exposed to three levels of H2O2 in nutrient solution: control; 3mmolL(-1) and 80mmolL(-1). Leaf gas exchange, photochemical activity, root hydraulic conductance (Lr) and antioxidant metabolism in both roots and leaves were evaluated after 15min of treatment with H2O2. Although, root hydraulic conductance, stomatal aperture, apparent electron transport rate and instantaneous carboxylation efficiency have been reduced by H2O2 in both genotypes, IACSP94-2094 presented higher values of those variables as compared to IACSP94-2101. There was a significant genotypic variation in relation to the physiological responses of sugarcane to increasing H2O2 in root tissues, being root changes associated with modifications in plant shoots. IACSP94-2094 presented a root antioxidant system more effective against H2O2 in root medium, regardless H2O2 concentration. Under low H2O2 concentration, water transport and leaf gas exchange of IACSP94-2094 were less affected as compared to IACSP94-2101. Under high H2O2 concentration, the lower sensitivity of IACSP94-2094 was associated with increases in superoxide dismutase activity in roots and leaves and increases in catalase activity in roots. In conclusion, we propose a general model of sugarcane reaction to H2O2, linking root and shoot physiological responses.

Effect of propolis gel on the in vitro reduction of dentin permeability

OBJECTIVE: The aim of this study was to evaluate the capacity of potassium oxalate, fluoride gel and two kinds of propolis gel to reduce the hydraulic conductance of dentin, in vitro. MATERIAL AND METHODS: The methodology used for the measurement of hydraulic conductance of dentin in the present study was based on a model proposed in literature. Thirty-six 1-mm-thick dentin discs, obtained from extracted human third molars were divided into 4 groups (n=9). The groups corresponded to the following experimental materials: GI-10% propolis gel, pH 4.1; GII-30% propolis gel; GIII-3% potassium oxalate gel, pH 4,1; and GIV-1.23% fluoride gel, pH 4.1, applied to the dentin under the following surface conditions: after 37% phosphoric acid and before 6% citric acid application. The occluding capacity of the dentin tubules was evaluated using scanning electron microscopy (SEM) at ×500, ×1,000 and ×2,000 magnifications. Data were analyzed statistically by two-way ANOVA and Tukey's test at 5% significance level. RESULTS: Groups I, II, III, IV did not differ significantly from the others in any conditions by reducing in hydraulic conductance. The active agents reduced dentin permeability; however they produced the smallest reduction in hydraulic conductance when compared to the presence of smear layer (P<0.05). The effectiveness in reducing dentin permeability did not differ significantly from 10% or 30% propolis gels. SEM micrographs revealed that dentin tubules were partially occluded after treatment with propolis. CONCLUSIONS: Under the conditions of this study, the application of 10% and 30% propolis gels did not seem to reduce the hydraulic conductance of dentin in vitro, but it showed capacity of partially obliterating the dentin tubules. Propolis is used in the treatment of different oral problems without causing significant great collateral effects, and can be a good option in the treatment of patients with dentin sensitivity.