Distributed optimization in transportation and logistics networks

Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimization of cost functions. In general, these can be complex optimization problems involving many variables. However, physicists noted that in a network, a node variable (such as the amount of resources of the nodes) is connected to a set of link variables (such as the flow connecting the node), and similarly each link variable is connected to a number of (usually two) node variables. This enables one to break the problem into local components, often arriving at distributive algorithms to solve the problems. Compared with centralized algorithms, distributed algorithms have the advantages of lower computational complexity, and lower communication overhead. Since they have a faster response to local changes of the environment, they are especially useful for networks with evolving conditions. This review will cover message-passing algorithms in applications such as resource allocation, transportation networks, facility location, traffic routing, and stability of power grids.

Power spectrum model of visual masking: simulations and empirical data

In the study of the spatial characteristics of the visual channels, the power spectrum model of visual masking is one of the most widely used. When the task is to detect a signal masked by visual noise, this classical model assumes that the signal and the noise are previously processed by a bank of linear channels and that the power of the signal at threshold is proportional to the power of the noise passing through the visual channel that mediates detection. The model also assumes that this visual channel will have the highest ratio of signal power to noise power at its output. According to this, there are masking conditions where the highest signal-to-noise ratio (SNR) occurs in a channel centered in a spatial frequency different from the spatial frequency of the signal (off-frequency looking). Under these conditions the channel mediating detection could vary with the type of noise used in the masking experiment and this could affect the estimation of the shape and the bandwidth of the visual channels. It is generally believed that notched noise, white noise and double bandpass noise prevent off-frequency looking, and high-pass, low-pass and bandpass noises can promote it independently of the channel's shape. In this study, by means of a procedure that finds the channel that maximizes the SNR at its output, we performed numerical simulations using the power spectrum model to study the characteristics of masking caused by six types of one-dimensional noise (white, high-pass, low-pass, bandpass, notched, and double bandpass) for two types of channel's shape (symmetric and asymmetric). Our simulations confirm that (1) high-pass, low-pass, and bandpass noises do not prevent the off-frequency looking, (2) white noise satisfactorily prevents the off-frequency looking independently of the shape and bandwidth of the visual channel, and interestingly we proved for the first time that (3) notched and double bandpass noises prevent off-frequency looking only when the noise cutoffs around the spatial frequency of the signal match the shape of the visual channel (symmetric or asymmetric) involved in the detection. In order to test the explanatory power of the model with empirical data, we performed six visual masking experiments. We show that this model, with only two free parameters, fits the empirical masking data with high precision. Finally, we provide equations of the power spectrum model for six masking noises used in the simulations and in the experiments.

A NEW DC UPS FOR DC POWER DISTRIBUTION SYSTEM IN DATA CENTER

In recent years, the 380V DC and 48V DC distribution systems have been extensively studied for the latest data centers. It is widely believed that the 380V DC system is a very promising candidate because of its lower cable cost compared to the 48V DC system. However, previous studies have not adequately addressed the low reliability issue with the 380V DC systems due to large amount of series connected batteries. In this thesis, a quantitative comparison for the two systems has been presented in terms of efficiency, reliability and cost. A new multi-port DC UPS with both high voltage output and low voltage output is proposed. When utility ac is available, it delivers power to the load through its high voltage output and charges the battery through its low voltage output. When utility ac is off, it boosts the low battery voltage and delivers power to the load form the battery. Thus, the advantages of both systems are combined and the disadvantages of them are avoided. High efficiency is also achieved as only one converter is working in either situation. Details about the design and analysis of the new UPS are presented. For the main AC-DC part of the new UPS, a novel bridgeless three-level single-stage AC-DC converter is proposed. It eliminates the auxiliary circuit for balancing the capacitor voltages and the two bridge rectifier diodes in previous topology. Zero voltage switching, high power factor, and low component stresses are achieved with this topology. Compared to previous topologies, the proposed converter has a lower cost, higher reliability, and higher efficiency. The steady state operation of the converter is analyzed and a decoupled model is proposed for the converter. For the battery side converter as a part of the new UPS, a ZVS bidirectional DC-DC converter based on self-sustained oscillation control is proposed. Frequency control is used to ensure the ZVS operation of all four switches and phase shift control is employed to regulate the converter output power. Detailed analysis of the steady state operation and design of the converter are presented. Theoretical, simulation, and experimental results are presented to verify the effectiveness of the proposed concepts.

Reproductive biology of the blackmouth catshark, Galeus melastomus (Chondrichthyes : Scyliorhinidae) off the south coast of Portugal

The reproductive biology of 1045 female (9.5-67 cm (total length(TL)) and 1007 male (9.4-64.3 cm TL) blackmouth catsharks, Galeus melastomus, was investigated. The sharks were caught off southern Portugal by bottom crustacean trawlers at depths from 209 to 754 m. The sex ratio was 1:1, and this species is sexually dimorphic with males approaching maturity at smaller size than females. Sexual segregation appears to be given for the stork within the study area. Sexual maturity was reached at a total length above 49 cm in males and above 56 cm in females. Mating and egg-deposition take place all year round, with two reproductive peaks of activity, in winter and summer. Egg capsules are, on average, 54 mm long and 21 mm wide, with a maximum of 63 x 25 mm encountered. Morphometric measurements of claspers, testes, ovaries, and oviducal glands were suitable for determining sexual maturity of blackmouth catshark.

Imaginarios sociales de adolescentes y docentes en torno al cuerpo, la corporalidad y la actividad física. Estudio cualitativo en un colegio de Bogotá, 2014-2015.

Problema. Esta investigación se aproxima al entorno escolar con el propósito de avanzar en la comprensión de los imaginarios de los adolescentes y docentes en torno al cuerpo, la corporalidad y la AF, como un elemento relevante en el diseño de programas y planes efectivos para fomento de la práctica de AF. Objetivo. Analizar los imaginarios sociales de docentes y adolescentes en torno a los conceptos de cuerpo, corporalidad y AF. Métodos. Investigación de corte cualitativo, descriptivo e interpretativo. Se realizaron entrevistas semi-estructuradas a docentes y a estudiantes entre los 12 y 18 años de un colegio público de Bogotá. Se realizó análisis de contenido. Se compararon los resultados de estudiantes por grupos de edades y género. Resultados. Docentes y estudiantes definen el cuerpo a partir de las características biológicas, las diferencias sexuales y las funciones vitales. La definición de corporalidad en los estudiantes se encuentra ligada con la imagen y la apariencia física; los docentes la entienden como la posibilidad de interactuar con el entorno y como la materialización de la existencia. La AF en los estudiantes se asocia con la práctica de ejercicio y deporte, en los docentes se comprende como una práctica de autocuidado que permite el mantenimiento de la salud. Conclusiones. Para promover la AF tempranamente como una experiencia vital es necesario intervenir los espacios escolares. Hay que vincular al cuerpo a los procesos formativos con el propósito de desarrollar la autonomía corporal, este aspecto implica cambios en los currículos.

El modelo de negocio en el desarrollo de una organización: un estudio de la compañía Southwest Airlines

El presente trabajo constituye una investigación acerca del rol del modelo de negocio en el desarrollo de las organizaciones. Esto se hace, en particular, a través del estudio detallado de la compañía Southwest Airlines. Se identifican para esta empresa, entre otros asuntos, las relaciones entre los recursos y los elementos que ofrece su entorno. Esto, en lo fundamental, para determinar el funcionamiento que ha llevado a la organización a la creación de un modelo de negocio adecuado y exitoso y el poder del mismo para evolucionar en un medio cambiante y aprovechar las oportunidades que este brinda. El presente documento presenta el origen, el desarrollo y los resultados de un estudio realizado a la empresa Southwest Airlines. En este se presentan sus políticas y estructura de procesos en relación con sus clientes —tanto internos como externos Esta se evidencia, al final, en la eficiencia, el compromiso de los empleados y otra serie de elementos que contribuyen al buen funcionamiento de la organización. El aporte de esta investigación está,en generar resultados a partir de un estudio a uno de los modelos de negocio de la industria aérea, específicamente el modelo de bajo costo (low cost). El propósito del trabajo fue desarrollar un análisis de las variables que consolidan todo el proceso de gestión en esta herramienta (business model) para ofrecerle al lector las pautas para fomentar la creación de modelos de negocio en las organizaciones y brindar así una estructura que contribuya a alcanzar el éxito en el mismo.

Bidding and Optimization Strategies for Wind-PV Systems in Electricity Markets

The variability in non-dispatchable power generation raises important challenges to the integration of renewable energy sources into the electricity power grid. This paper provides the coordinated trading of wind and photovoltaic energy to mitigate risks due to the wind and solar power variability, electricity prices, and financial penalties arising out the generation shortfall and surplus. The problem of wind-photovoltaic coordinated trading is formulated as a linear programming problem. The goal is to obtain the optimal bidding strategy that maximizes the total profit. The wind-photovoltaic coordinated operation is modeled and compared with the uncoordinated operation. A comparison of the models and relevant conclusions are drawn from an illustrative case study of the Iberian day-ahead electricity market.

Bidding and Optimization Strategies for Wind-PV Systems in Electricity Markets Assisted by CPS

The variability in non-dispatchable power generation raises important challenges to the integration of renewable energy sources into the electricity power grid. This paper provides the coordinated trading of wind and photovoltaic energy assisted by a cyber-physical system for supporting management decisions to mitigate risks due to the wind and solar power variability, electricity prices, and financial penalties arising out the generation shortfall and surplus. The problem of wind-photovoltaic coordinated trading is formulated as a stochastic linear programming problem. The goal is to obtain the optimal bidding strategy that maximizes the total profit. The wind-photovoltaic coordinated operation is modelled and compared with the uncoordinated operation. A comparison of the models and relevant conclusions are drawn from an illustrative case study of the Iberian day-ahead electricity market.

“The Landscape of wheat - A landscape of power” pp: 66-70

Portugal in the end of the 19 th century was characterized by a huge economic and political instability. This situation led to the publication of the Hunger Law (1899), which is identified as the critical breaking point since it imposed a political ideology over a vernacular landscape. The Alentejo (south of Portugal), between (1889-1929) emerges as a paradigmatic landscapes where an abrupt transformation take place: an ancient landscape with the loss of their ecological memory was lost and a false identities was created. The diversity and ecological richness of the vernacular landscape gave way to the monotony of the cereal and the ecological and social system that for centuries had built up and evolved was abruptly compromised. To analyze and understand the important transformation that happened in the ancestral countryside of Alentejo, the research was based on the concept of landscape as a system, and that the landscape represents the relationship between the natural system and the cultural.

Modeling, Component Selection and Optimization of Servo-controlled Automatic Machinery

A servo-controlled automatic machine can perform tasks that involve synchronized actuation of a significant number of servo-axes, namely one degree-of-freedom (DoF) electromechanical actuators. Each servo-axis comprises a servo-motor, a mechanical transmission and an end-effector, and is responsible for generating the desired motion profile and providing the power required to achieve the overall task. The design of a such a machine must involve a detailed study from a mechatronic viewpoint, due to its electric and mechanical nature. The first objective of this thesis is the development of an overarching electromechanical model for a servo-axis. Every loss source is taken into account, be it mechanical or electrical. The mechanical transmission is modeled by means of a sequence of lumped-parameter blocks. The electric model of the motor and the inverter takes into account winding losses, iron losses and controller switching losses. No experimental characterizations are needed to implement the electric model, since the parameters are inferred from the data available in commercial catalogs. With the global model at disposal, a second objective of this work is to perform the optimization analysis, in particular, the selection of the motor-reducer unit. The optimal transmission ratios that minimize several objective functions are found. An optimization process is carried out and repeated for each candidate motor. Then, we present a novel method where the discrete set of available motor is extended to a continuous domain, by fitting manufacturer data. The problem becomes a two-dimensional nonlinear optimization subject to nonlinear constraints, and the solution gives the optimal choice for the motor-reducer system. The presented electromechanical model, along with the implementation of optimization algorithms, forms a complete and powerful simulation tool for servo-controlled automatic machines. The tool allows for determining a wide range of electric and mechanical parameters and the behavior of the system in different operating conditions.

Development and optimization of fibre-shaped dye-sensitized solar cells employing an innovative fully organic sensitizer

The quality of human life depends to a large degree on the availability of energy. In recent years, photovoltaic technology has been growing extraordinarily as a suitable source of energy, as a consequence of the increasing concern over the impact of fossil fuels on climate change. Developing affordable and highly efficiently photovoltaic technologies is the ultimate goal in this direction. Dye-sensitized solar cells (DSSCs) offer an efficient and easily implementing technology for future energy supply. Compared to conventional silicon solar cells, they provide comparable power conversion efficiency at low material and manufacturing costs. In addition, DSSCs are able to harvest low-intensity light in diffuse illumination conditions and then represent one of the most promising alternatives to the traditional photovoltaic technology, even more when trying to move towards flexible and transparent portable devices. Among these, considering the increasing demand of modern electronics for small, portable and wearable integrated optoelectronic devices, Fibre Dye-Sensitized Solar Cells (FDSSCs) have gained increasing interest as suitable energy provision systems for the development of the next-generation of smart products, namely “electronic textiles” or “e-textiles”. In this thesis, several key parameters towards the optimization of FDSSCs based on inexpensive and abundant TiO2 as photoanode and a new innovative fully organic sensitizer were studied. In particular, the effect of various FDSSCs components on the device properties pertaining to the cell architecture in terms of photoanode oxide layer thickness, electrolytic system, cell length and electrodes substrates were examined. The photovoltaic performances of the as obtained FDSSCs were fully characterized. Finally, the metal part of the devices (wire substrate) was substituted with substrates suitable for the textile industry as a fundamental step towards commercial exploitation.

Optimization and development of low environmental impact propulsion systems

The aim of the Ph.D. research project was to explore Dual Fuel combustion and hybridization. Natural gas-diesel Dual Fuel combustion was experimentally investigated on a 4-Stroke, 2.8 L, turbocharged, light-duty Diesel engine, considering four operating points in the range between low to medium-high loads at 3000 rpm. Then, a numerical analysis was carried out using a customized version of the KIVA-3V code, in order to optimize the diesel injection strategy of the highest investigated load. A second KIVA-3V model was used to analyse the interchangeability between natural gas and biogas on an intermediate operating point. Since natural gas-diesel Dual Fuel combustion suffers from poor combustion efficiency at low loads, the effects of hydrogen enriched natural gas on Dual Fuel combustion were investigated using a validated Ansys Forte model, followed by an optimization of the diesel injection strategy and a sensitivity analysis to the swirl ratio, on the lowest investigated load. Since one of the main issues of Low Temperature Combustion engines is the low power density, 2-Stroke engines, thanks to the double frequency compared to 4-Stroke engines, may be more suitable to operate in Dual Fuel mode. Therefore, the application of gasoline-diesel Dual Fuel combustion to a modern 2-Stroke Diesel engine was analysed, starting from the investigation of gasoline injection and mixture formation. As far as hybridization is concerned, a MATLAB-Simulink model was built to compare a conventional (combustion) and a parallel-hybrid powertrain applied to a Formula SAE race car.

Methods for integrating machine learning and constrained optimization

In the framework of industrial problems, the application of Constrained Optimization is known to have overall very good modeling capability and performance and stands as one of the most powerful, explored, and exploited tool to address prescriptive tasks. The number of applications is huge, ranging from logistics to transportation, packing, production, telecommunication, scheduling, and much more. The main reason behind this success is to be found in the remarkable effort put in the last decades by the OR community to develop realistic models and devise exact or approximate methods to solve the largest variety of constrained or combinatorial optimization problems, together with the spread of computational power and easily accessible OR software and resources. On the other hand, the technological advancements lead to a data wealth never seen before and increasingly push towards methods able to extract useful knowledge from them; among the data-driven methods, Machine Learning techniques appear to be one of the most promising, thanks to its successes in domains like Image Recognition, Natural Language Processes and playing games, but also the amount of research involved. The purpose of the present research is to study how Machine Learning and Constrained Optimization can be used together to achieve systems able to leverage the strengths of both methods: this would open the way to exploiting decades of research on resolution techniques for COPs and constructing models able to adapt and learn from available data. In the first part of this work, we survey the existing techniques and classify them according to the type, method, or scope of the integration; subsequently, we introduce a novel and general algorithm devised to inject knowledge into learning models through constraints, Moving Target. In the last part of the thesis, two applications stemming from real-world projects and done in collaboration with Optit will be presented.

RF energy harvesting solutions for electromagnetic harsh environments: from industrial plants to wearable/implantable devices

The presented Thesis describes the design of RF-energy harvesting systems with applications on different environments, from the biomedical side to the industrial one, tackling the common thread problem which is the design of complete energy autonomous tags each of them with its dedicated purpose. This Thesis gathers a work of three years in the field of energy harvesting system design, a combination of full-wave electromagnetic designs to optimize not only the antenna performance but also to fulfill the requirements given by each case study such as dimensions, insensitivity from the surrounding environment, flexibility and compliance with regulations. The research activity has been based on the development of highly-demanded ideas and real-case necessities which are in line with the environment in which modern IoT applications can really make a positive contribution. The Thesis is organized as follows: the first application, described in Chapter 2, regards the design and experimental validations of a rotation-insensitive WPT system for implantable devices. Chapter 3 presents the design of a wearable energy autonomous detector to identify the presence of ethanol on the body surface. Chapter 4 describes investigations in the use of Bessel Beam launchers for creating a highly-focused energy harvesting link for wearable applications. Reduced dimensions, high focusing and decoupling from the human body are the key points to be addressed during the full-wave design and nonlinear optimization of the receiver antenna. Finally, Chapter 5 presents an energy autonomous system exploiting LoRa (Long Range) nodes for tracking trailers in industrial plants. The novelty behind this design lies on the aim of obtaining a perfectly scalable system that exploits not only EH basic operating system but embeds a seamless solution for collecting a certain amount of power that varies with respect the received power level on the antenna, without the need of additional off-the-shelf components.

Optimization of an innovative T6 heat treatment for the AlSi10Mg alloy processed by Laser-based Powder Bed Fusion: effect on microstructure, mechanical properties, and tribological behavior

Laser-based Powder Bed Fusion (L-PBF) technology is one of the most commonly used metal Additive Manufacturing (AM) techniques to produce highly customized and value-added parts. The AlSi10Mg alloy has received more attention in the L-PBF process due to its good printability, high strength/weight ratio, corrosion resistance, and relatively low cost. However, a deep understanding of the effect of heat treatments on this alloy's metastable microstructure is still required for developing tailored heat treatments for the L-PBF AlSi10Mg alloy to overcome the limits of the as-built condition. Several authors have already investigated the effects of conventional heat treatment on the microstructure and mechanical behavior of the L-PBF AlSi10Mg alloy but often overlooked the peculiarities of the starting supersatured and ultrafine microstructure induced by rapid solidification. For this reason, the effects of innovative T6 heat treatment (T6R) on the microstructure and mechanical behavior of the L-PBF AlSi10Mg alloy were assessed. The short solution soaking time (10 min) and the relatively low temperature (510 °C) reduced the typical porosity growth at high temperatures and led to a homogeneous distribution of fine globular Si particles in the Al matrix. In addition, it increased the amount of Mg and Si in the solid solution available for precipitation hardening during the aging step. The mechanical (at room temperature and 200 °C) and tribological properties of the T6R alloy were evaluated and compared with other solutions, especially with an optimized direct-aged alloy (T5 alloy). Results showed that the innovative T6R alloy exhibits the best mechanical trade-off between strength and ductility, the highest fatigue strength among the analyzed conditions, and interesting tribological behavior. Furthermore, the high-temperature mechanical performances of the heat-treated L-PBF AlSi10Mg alloy make it suitable for structural components operating in mild service conditions at 200 °C.