Modelling and Design of Advanced Reliable Circuits and Devices for Energy Efficiency

Reliable electronic systems, namely a set of reliable electronic devices connected to each other and working correctly together for the same functionality, represent an essential ingredient for the large-scale commercial implementation of any technological advancement. Microelectronics technologies and new powerful integrated circuits provide noticeable improvements in performance and cost-effectiveness, and allow introducing electronic systems in increasingly diversified contexts. On the other hand, opening of new fields of application leads to new, unexplored reliability issues. The development of semiconductor device and electrical models (such as the well known SPICE models) able to describe the electrical behavior of devices and circuits, is a useful means to simulate and analyze the functionality of new electronic architectures and new technologies. Moreover, it represents an effective way to point out the reliability issues due to the employment of advanced electronic systems in new application contexts. In this thesis modeling and design of both advanced reliable circuits for general-purpose applications and devices for energy efficiency are considered. More in details, the following activities have been carried out: first, reliability issues in terms of security of standard communication protocols in wireless sensor networks are discussed. A new communication protocol is introduced, allows increasing the network security. Second, a novel scheme for the on-die measurement of either clock jitter or process parameter variations is proposed. The developed scheme can be used for an evaluation of both jitter and process parameter variations at low costs. Then, reliability issues in the field of “energy scavenging systems” have been analyzed. An accurate analysis and modeling of the effects of faults affecting circuit for energy harvesting from mechanical vibrations is performed. Finally, the problem of modeling the electrical and thermal behavior of photovoltaic (PV) cells under hot-spot condition is addressed with the development of an electrical and thermal model.

Experimental Analysis and Numerical Simulation of Quench in Superconducting HTS Tapes and Coils

The quench characteristics of second generation (2 G) YBCO Coated Conductor (CC) tapes are of fundamental importance for the design and safe operation of superconducting cables and magnets based on this material. Their ability to transport high current densities at high temperature, up to 77 K, and at very high fields, over 20 T, together with the increasing knowledge in their manufacturing, which is reducing their cost, are pushing the use of this innovative material in numerous system applications, from high field magnets for research to motors and generators as well as for cables. The aim of this Ph. D. thesis is the experimental analysis and numerical simulations of quench in superconducting HTS tapes and coils. A measurements facility for the characterization of superconducting tapes and coils was designed, assembled and tested. The facility consist of a cryostat, a cryocooler, a vacuum system, resistive and superconducting current leads and signal feedthrough. Moreover, the data acquisition system and the software for critical current and quench measurements were developed. A 2D model was developed using the finite element code COMSOL Multiphysics R . The problem of modeling the high aspect ratio of the tape is tackled by multiplying the tape thickness by a constant factor, compensating the heat and electrical balance equations by introducing a material anisotropy. The model was then validated both with the results of a 1D quench model based on a non-linear electric circuit coupled to a thermal model of the tape, to literature measurements and to critical current and quench measurements made in the cryogenic facility. Finally the model was extended to the study of coils and windings with the definition of the tape and stack homogenized properties. The procedure allows the definition of a multi-scale hierarchical model, able to simulate the windings with different degrees of detail.

Fission track age determinations of rocks from north Greenland

Apatite fission track (FT) ages and length characteristics of samples obtained from Cambrian to Paleocene-aged sandstones collected along the margin of Nares Strait in Ellesmere Island in the Canadian Arctic Archipelago are dominated by a thermal history related to Paleogene relative plate movements between Greenland and Ellesmere Island. A preliminary inverse FT thermal model for a Cambrian (Archer Fiord Formation) sandstone in the hanging wall of the Rawlings Bay thrust at Cape Lawrence is consistent with Paleocene exhumational cooling, likely as a result of erosion of the thrust. This suggests that thrusting at Cape Lawrence occurred prior to the onset of Eocene compression, likely due to transpression during earlier strikeslip along the strait. Models for samples from volcaniclastic sandstones of the Late Paleocene Pavy Formation (from Cape Back and near Pavy River), and a sandstone from the Late Paleocene Mount Lawson Formation (at Split Lake, near Makinson Inlet) are also consistent with minor burial heating following known periods of basaltic volcanism in Baffin Bay and Davis Strait (c. 61-59 Ma), or related tholeiitic volcanism and intrusive activity (c. 55-54 Ma). Thermal models for samples from sea level dykes from around Smith Sound suggest a period of Late Cretaceous - Paleocene heating prior to final cooling during Paleocene time. These model results imply that Paleocene tectonic movements along Nares Strait were significant, and provide limited support for the former existence of the Wegener Fault. Apatite FT data from central Ellesmere Island suggest however, that cooling there occurred during Early Eocene time (c. 50 Ma), which was likely a result of erosion of thrusts during Eurekan compression. This diachronous cooling suggests that Eurekan deformation was partitioned at discrete intervals across Ellesmere Island, and thus it is likely that displacements along the strait were much less than the 150 km that has been previously suggested for the Wegener Fault.

Study of a-Si crystallization dependence on power and irradiation time using a CW green laser

An advantage of laser crystallization over conventional heating methods is its ability to limit rapid heating and cooling to thin surface layers. Laser energy is used to heat the a-Si thin film to change the microstructure to poly-Si. Thin film samples of a-Si were irradiated with a CW-green laser source. Laser irradiated spots were produced by using different laser powers and irradiation times. These parameters are identified as key variables in the crystallization process. The power threshold for crystallization is reduced as the irradiation time is increased. When this threshold is reached the crystalline fraction increases lineally with power for each irradiation time. The experimental results are analysed with the aid of a numerical thermal model and the presence of two crystallization mechanisms are observed: one due to melting and the other due to solid phase transformation.

Intelligence Algorithms for Increasing Navigation Systems Accuracy

Application of neural network algorithm for increasing the accuracy of navigation systems are showing. Various navigation systems, where a couple of sensors are used in the same device in different positions and the disturbances act equally on both sensors, the trained neural network can be advantageous for increasing the accuracy of system. The neural algorithm had used for determination the interconnection between the sensors errors in two channels to avoid the unobservation of navigation system. Representation of thermal error of two- component navigation sensors by time model, which coefficients depend only on parameters of the device, its orientations relative to disturbance vector allows to predict thermal errors change, measuring the current temperature and having identified preliminary parameters of the model for the set position. These properties of thermal model are used for training the neural network and compensation the errors of navigation system in non- stationary thermal fields.

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.

SIGNIFICANCE OF HEAT DISSIPATION IN THE CATHODE CATALYST LAYER ON THE LIFETIME AND RELIABILITY OF POLYMER ELECTROLYTE FUEL CELLS

To study the dissipation of heat generated due to the formation of pinholes that cause local hotspots in the catalyst layer of the Polymer Electrolyte Fuel Cell, a two-phase non-isothermal model has been developed by coupling Darcy’s law with heat transport. The domain under consideration is a section of the membrane electrode assembly with a half-channel and a half-rib. Five potential locations where a pinhole might form were analyzed: at the midplane of the channel, midway between the channel midplane and the channel wall, at the channel or rib wall, midway between the rib midplane and the channel wall, at the midplane of the rib. In the first part of this work, a preliminary thermal model was developed. The model was then refined to account for the two-phase effects. A sensitivity study was done to evaluate the effect of the following properties on the maximum temperature in the domain: Catalyst layer thermal conductivity, the Microporous layer thermal conductivity, the anisotropy factor of the Catalyst layer thermal conductivity, the Porous transport layer porosity, the liquid water distribution and the thickness of the membrane and porous layers. Accounting for the two-phase effects, a slight cooling effect was observed across all hotspot locations. The thermal properties of the catalyst layer were shown to have a limited impact on the maximum temperature in the catalyst layer of new fuel cells without pinhole. However, as hotspots start to appear, thermal properties play a more significant role in mitigating the thermal runaway.

Análise energética em central fixa de produção de massas asfálticas

O consumo energético nas indústrias é algo que tem de ser monitorizado, avaliado e orientado, visando a eficiência energética e sustentabilidade, de modo não só a reduzir o consumo de combustíveis fósseis, mas também a auxiliar a redução da fatura económica. O presente trabalho teve como principal objetivo uma análise energética, e incorpora a caracterização térmica dos materiais utilizados na indústria de produção de massas asfálticas, e o desenvolvimento de um modelo térmico que preveja o comportamento dos mesmos, na produção de massas asfálticas, em central fixa com incorporação de material reciclado a frio. Primariamente o estudo passou pela análise dos consumos energéticos da instalação, caracterizando-a segundo o Decretolei 71/2008, de 15 de Abril, tendo-se constatado, que o consumo de gás natural se evidencia como uma das principais fontes de energia e um dos principais responsáveis pela emissão de GEE (Gases de Efeito de Estufa). Posteriormente o consumo de gás natural foi distribuído pelos pontos consumidores, o cilindro exsicador e a caldeira de aquecimento de óleo térmico. O cilindro exsicador é o principal consumidor energético, com um consumo próximo de 90% do gás natural total. Seguidamente foi realizada uma caracterização dos materiais utilizados na produção de massas asfálticas segundo o DSC (Differential Scanning Calorimetry). Os materiais analisados foram o reciclado/fresado, o calcário, o pó de calcário, o seixo, a areia e o granito. Os resultados dos materiais secos demonstraram que o material com maior cp (calor específico) foi a areia e o menor o calcário. Nos resultados dos materiais saturados observou-se que o seixo apresenta maior facilidade de remoção de humidade e o reciclado/fresado apresenta menor. Por último, foi realizado um modelo térmico com utilização de um balanço mássico e energético ao processo de secagem e sobreaquecimento dos agregados no cilindro exsicador. Conclui-se que as principais influências no consumo de gás natural, na produção de massas asfálticas com inclusão de material reciclado a frio, são: a necessidade energética de aquecimento em função da temperatura a obter, e a energia necessária para remover o conteúdo em humidade presente nos diversos materiais (fresado e agregados).

Differences in grain growth of calcite: a field-based modeling approach

Normal grain growth of calcite was investigated by combining grain size analysis of calcite across the contact aureole of the Adamello pluton, and grain growth modeling based on a thermal model of the surroundings of the pluton. In an unbiased model system, i.e., location dependent variations in temperature-time path, 2/3 and 1/3 of grain growth occurs during pro- and retrograde metamorphism at all locations, respectively. In contrast to this idealized situation, in the field example three groups can be distinguished, which are characterized by variations in their grain size versus temperature relationships: Group I occurs at low temperatures and the grain size remains constant because nano-scale second phase particles of organic origin inhibit grain growth in the calcite aggregates under these conditions. In the presence of an aqueous fluid, these second phases decay at a temperature of about 350 °C enabling the onset of grain growth in calcite. In the following growth period, fluid-enhanced group II and slower group III growth occurs. For group II a continuous and intense grain size increase with T is typical while the grain growth decreases with T for group III. None of the observed trends correlate with experimentally based grain growth kinetics, probably due to differences between nature and experiment which have not yet been investigated (e.g., porosity, second phases). Therefore, grain growth modeling was used to iteratively improve the correlation between measured and modeled grain sizes by optimizing activation energy (Q), pre-exponential factor (k0) and grain size exponent (n). For n=2, Q of 350 kJ/mol, k0 of 1.7×1021 μmns−1 and Q of 35 kJ/mol, k0 of 2.5×10-5 μmns−1 were obtained for group II and III, respectively. With respect to future work, field-data based grain growth modeling might be a promising tool for investigating the influences of secondary effects like porosity and second phases on grain growth in nature, and to unravel differences between nature and experiment.

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.

Dry grinding technology for automotive gears manufacturing: process modeling and optimization

The following thesis focused on the dry grinding process modelling and optimization for automotive gears production. A FEM model was implemented with the aim at predicting process temperatures and preventing grinding thermal defects on the material surface. In particular, the model was conceived to facilitate the choice of the grinding parameters during the design and the execution of the dry-hard finishing process developed and patented by the company Samputensili Machine Tools (EMAG Group) on automotive gears. The proposed model allows to analyse the influence of the technological parameters, comprising the grinding wheel specifications. Automotive gears finished by dry-hard finishing process are supposed to reach the same quality target of the gears finished through the conventional wet grinding process with the advantage of reducing production costs and environmental pollution. But, the grinding process allows very high values of specific pressure and heat absorbed by the material, therefore, removing the lubricant increases the risk of thermal defects occurrence. An incorrect design of the process parameters set could cause grinding burns, which affect the mechanical performance of the ground component inevitably. Therefore, a modelling phase of the process could allow to enhance the mechanical characteristics of the components and avoid waste during production. A hierarchical FEM model was implemented to predict dry grinding temperatures and was represented by the interconnection of a microscopic and a macroscopic approach. A microscopic single grain grinding model was linked to a macroscopic thermal model to predict the dry grinding process temperatures and so to forecast the thermal cycle effect caused by the process parameters and the grinding wheel specification choice. Good agreement between the model and the experiments was achieved making the dry-hard finishing an efficient and reliable technology to implement in the gears automotive industry.

Novel methods of state estimation and parameter identification for high-performance motorcycles

This research activity aims at providing a reliable estimation of particular state variables or parameters concerning the dynamics and performance optimization of a MotoGP-class motorcycle, integrating the classical model-based approach with new methodologies involving artificial intelligence. The first topic of the research focuses on the estimation of the thermal behavior of the MotoGP carbon braking system. Numerical tools are developed to assess the instantaneous surface temperature distribution in the motorcycle's front brake discs. Within this application other important brake parameters are identified using Kalman filters, such as the disc convection coefficient and the power distribution in the disc-pads contact region. Subsequently, a physical model of the brake is built to estimate the instantaneous braking torque. However, the results obtained with this approach are highly limited by the knowledge of the friction coefficient (μ) between the disc rotor and the pads. Since the value of μ is a highly nonlinear function of many variables (namely temperature, pressure and angular velocity of the disc), an analytical model for the friction coefficient estimation appears impractical to establish. To overcome this challenge, an innovative hybrid solution is implemented, combining the benefit of artificial intelligence (AI) with classical model-based approach. Indeed, the disc temperature estimated through the thermal model previously implemented is processed by a machine learning algorithm that outputs the actual value of the friction coefficient thus improving the braking torque computation performed by the physical model of the brake. Finally, the last topic of this research activity regards the development of an AI algorithm to estimate the current sideslip angle of the motorcycle's front tire. While a single-track motorcycle kinematic model and IMU accelerometer signals theoretically enable sideslip calculation, the presence of accelerometer noise leads to a significant drift over time. To address this issue, a long short-term memory (LSTM) network is implemented.

Bilinear H 2-optimal Model Order-Reduction with applications to thermal parametric systems

Magdeburg, Univ., Fak. für Mathematik, Diss., 2015

Thermal tests on the LISA pathfinder engineering model

Report for the scientific sojourn carried out at Albert Einstein Institut in Germany, from April to July 2006.