15 resultados para energy simulation

em AMS Tesi di Laurea - Alm@DL - Università di Bologna


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The following research thesis is about a retrofit project made in Denmark, Copenhagen, and carried out on one of the buildings belonging to the Royal Danish Academy. The key assumption and base of the entire research process is that, up to now, the standard procedure in retrofit cases like this provides as comparative method between de facto and design, the use of Energy Simulation software. These programs generally divide the space into different thermal zones, assigning to each of them different levels of employment, activities, set-point temperatures set for cooling and heating analysis and so on, but always providing average and constant values, usually taken in the middle point of the single thermal zone. Therefore, the project and its research path stems from the attempt to investigate the potentialities of this kind of designing for retrofit process, as previously anticipated not antithetical but complementary to that classic energy-based retrofit, thus passing from the building scale, and all its thermal zones, to the users' scale, related to humans and microclimates. The main software used in this process is Autodesk Simulation CFD. The idea behind the project is that in certain situations, for example, it will not be necessary to add throughout insulation layers (previously parameterized and optimized with Design Builder), and that even in Winter conditions, due maybe to the users' activities, the increased level of clothing (clo) and the heat produced by equipments, thermal comfort could be achieved also in areas characterized by considerably lower MRT. After the analysis of the State of Art and its simulations, the project has still been supported by the tool itself, the CFD Software, in an iterative process aimed at achieving visible improvements in terms of MRT, on spaces with different needs and characteristics, both in Winter and Summer regimes.

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In this thesis, we propose a novel approach to model the diffusion of residential PV systems. For this purpose, we use an agent-based model where agents are the families living in the area of interest. The case study is the Emilia-Romagna Regional Energy plan, which aims to increase the produc- tion of electricity from renewable energy. So, we study the microdata from the Survey on Household Income and Wealth (SHIW) provided by Bank of Italy in order to obtain the characteristics of families living in Emilia-Romagna. These data have allowed us to artificial generate families and reproduce the socio-economic aspects of the region. The families generated by means of a software are placed on the virtual world by associating them with the buildings. These buildings are acquired by analysing the vector data of regional buildings made available by the region. Each year, the model determines the level of diffusion by simulating the installed capacity. The adoption behaviour is influenced by social interactions, household’s economic situation, the environmental benefits arising from the adoption and the payback period of the investment.

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Hybrid vehicles represent the future for automakers, since they allow to improve the fuel economy and to reduce the pollutant emissions. A key component of the hybrid powertrain is the Energy Storage System, that determines the ability of the vehicle to store and reuse energy. Though electrified Energy Storage Systems (ESS), based on batteries and ultracapacitors, are a proven technology, Alternative Energy Storage Systems (AESS), based on mechanical, hydraulic and pneumatic devices, are gaining interest because they give the possibility of realizing low-cost mild-hybrid vehicles. Currently, most literature of design methodologies focuses on electric ESS, which are not suitable for AESS design. In this contest, The Ohio State University has developed an Alternative Energy Storage System design methodology. This work focuses on the development of driving cycle analysis methodology that is a key component of Alternative Energy Storage System design procedure. The proposed methodology is based on a statistical approach to analyzing driving schedules that represent the vehicle typical use. Driving data are broken up into power events sequence, namely traction and braking events, and for each of them, energy-related and dynamic metrics are calculated. By means of a clustering process and statistical synthesis methods, statistically-relevant metrics are determined. These metrics define cycle representative braking events. By using these events as inputs for the Alternative Energy Storage System design methodology, different system designs are obtained. Each of them is characterized by attributes, namely system volume and weight. In the last part the work, the designs are evaluated in simulation by introducing and calculating a metric related to the energy conversion efficiency. Finally, the designs are compared accounting for attributes and efficiency values. In order to automate the driving data extraction and synthesis process, a specific script Matlab based has been developed. Results show that the driving cycle analysis methodology, based on the statistical approach, allows to extract and synthesize cycle representative data. The designs based on cycle statistically-relevant metrics are properly sized and have satisfying efficiency values with respect to the expectations. An exception is the design based on the cycle worst-case scenario, corresponding to same approach adopted by the conventional electric ESS design methodologies. In this case, a heavy system with poor efficiency is produced. The proposed new methodology seems to be a valid and consistent support for Alternative Energy Storage System design.

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This dissertation deals with the development of a project concerning a demonstration in the scope of the Supply Chain 6 of the Internet of Energy (IoE) project: the Remote Monitoring Emulator, which bears my personal contribution in several sections. IoE is a project of international relevance, that means to establish an interoperability standard as regards the electric power production and utilization infrastructure, using Smart Space platforms. The future perspectives of IoE have to do with a platform for electrical power trade-of, the Smart Grid, whose energy is produced by decentralized renewable sources and whose services are exploited primarily according to the Internet of Things philosophy. The main consumers of this kind of smart technology will be Smart Houses (that is to say, buildings controlled by an autonomous system for electrical energy management that is interoperable with the Smart Grid) and Electric Mobility, that is a smart and automated management regarding movement and, overall, recharging of electrical vehicles. It is precisely in the latter case study that the project Remote Monitoring Emulator takes place. It consists in the development of a simulated platform for the management of an electrical vehicle recharging in a city. My personal contribution to this project lies in development and modeling of the simulation platform, of its counterpart in a mobile application and implementation of a city service prototype. This platform shall, ultimately, make up a demonstrator system exploiting the same device which a real user, inside his vehicle, would use. The main requirements that this platform shall satisfy will be interoperability, expandability and relevance to standards, as it needs to communicate with other development groups and to effectively respond to internal changes that can affect IoE.

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Laser shock peening is a technique similar to shot peening that imparts compressive residual stresses in materials for improving fatigue resistance. The ability to use a high energy laser pulse to generate shock waves, inducing a compressive residual stress field in metallic materials, has applications in multiple fields such as turbo-machinery, airframe structures, and medical appliances. The transient nature of the LSP phenomenon and the high rate of the laser's dynamic make real time in-situ measurement of laser/material interaction very challenging. For this reason and for the high cost of the experimental tests, reliable analytical methods for predicting detailed effects of LSP are needed to understand the potential of the process. Aim of this work has been the prediction of residual stress field after Laser Peening process by means of Finite Element Modeling. The work has been carried out in the Stress Methods department of Airbus Operations GmbH (Hamburg) and it includes investigation on compressive residual stresses induced by Laser Shock Peening, study on mesh sensitivity, optimization and tuning of the model by using physical and numerical parameters, validation of the model by comparing it with experimental results. The model has been realized with Abaqus/Explicit commercial software starting from considerations done on previous works. FE analyses are “Mesh Sensitive”: by increasing the number of elements and by decreasing their size, the software is able to probe even the details of the real phenomenon. However, these details, could be only an amplification of real phenomenon. For this reason it was necessary to optimize the mesh elements' size and number. A new model has been created with a more fine mesh in the trough thickness direction because it is the most involved in the process deformations. This increment of the global number of elements has been paid with an "in plane" size reduction of the elements far from the peened area in order to avoid too high computational costs. Efficiency and stability of the analyses has been improved by using bulk viscosity coefficients, a merely numerical parameter available in Abaqus/Explicit. A plastic rate sensitivity study has been also carried out and a new set of Johnson Cook's model coefficient has been chosen. These investigations led to a more controllable and reliable model, valid even for more complex geometries. Moreover the study about the material properties highlighted a gap of the model about the simulation of the surface conditions. Modeling of the ablative layer employed during the real process has been used to fill this gap. In the real process ablative layer is a super thin sheet of pure aluminum stuck on the masterpiece. In the simulation it has been simply reproduced as a 100µm layer made by a material with a yield point of 10MPa. All those new settings has been applied to a set of analyses made with different geometry models to verify the robustness of the model. The calibration of the model with the experimental results was based on stress and displacement measurements carried out on the surface and in depth as well. The good correlation between the simulation and experimental tests results proved this model to be reliable.

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Constant developments in the field of offshore wind energy have increased the range of water depths at which wind farms are planned to be installed. Therefore, in addition to monopile support structures suitable in shallow waters (up to 30 m), different types of support structures, able to withstand severe sea conditions at the greater water depths, have been developed. For water depths above 30 m, the jacket is one of the preferred support types. Jacket represents a lightweight support structure, which, in combination with complex nature of environmental loads, is prone to highly dynamic behavior. As a consequence, high stresses with great variability in time can be observed in all structural members. The highest concentration of stresses occurs in joints due to their nature (structural discontinuities) and due to the existence of notches along the welds present in the joints. This makes them the weakest elements of the jacket in terms of fatigue. In the numerical modeling of jackets for offshore wind turbines, a reduction of local stresses at the chord-brace joints, and consequently an optimization of the model, can be achieved by implementing joint flexibility in the chord-brace joints. Therefore, in this work, the influence of joint flexibility on the fatigue damage in chord-brace joints of a numerical jacket model, subjected to advanced load simulations, is studied.

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The rapid development in the field of lighting and illumination allows low energy consumption and a rapid growth in the use, and development of solid-state sources. As the efficiency of these devices increases and their cost decreases there are predictions that they will become the dominant source for general illumination in the short term. The objective of this thesis is to study, through extensive simulations in realistic scenarios, the feasibility and exploitation of visible light communication (VLC) for vehicular ad hoc networks (VANETs) applications. A brief introduction will introduce the new scenario of smart cities in which visible light communication will become a fundamental enabling technology for the future communication systems. Specifically, this thesis focus on the acquisition of several, frequent, and small data packets from vehicles, exploited as sensors of the environment. The use of vehicles as sensors is a new paradigm to enable an efficient environment monitoring and an improved traffic management. In most cases, the sensed information must be collected at a remote control centre and one of the most challenging aspects is the uplink acquisition of data from vehicles. My thesis discusses the opportunity to take advantage of short range vehicle-to-vehicle (V2V) and vehicle-to-roadside (V2R) communications to offload the cellular networks. More specifically, it discusses the system design and assesses the obtainable cellular resource saving, by considering the impact of the percentage of vehicles equipped with short range communication devices, of the number of deployed road side units, and of the adopted routing protocol. When short range communications are concerned, WAVE/IEEE 802.11p is considered as standard for VANETs. Its use together with VLC will be considered in urban vehicular scenarios to let vehicles communicate without involving the cellular network. The study is conducted by simulation, considering both a simulation platform (SHINE, simulation platform for heterogeneous interworking networks) developed within the Wireless communication Laboratory (Wilab) of the University of Bologna and CNR, and network simulator (NS3). trying to realistically represent all the wireless network communication aspects. Specifically, simulation of vehicular system was performed and introduced in ns-3, creating a new module for the simulator. This module will help to study VLC applications in VANETs. Final observations would enhance and encourage potential research in the area and optimize performance of VLC systems applications in the future.

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Since its discovery, top quark has represented one of the most investigated field in particle physics. The aim of this thesis is the reconstruction of hadronic top with high transverse momentum (boosted) with the Template Overlap Method (TOM). Because of the high energy, the decay products of boosted tops are partially or totally overlapped and thus they are contained in a single large radius jet (fat-jet). TOM compares the internal energy distributions of the candidate fat-jet to a sample of tops obtained by a MC simulation (template). The algorithm is based on the definition of an overlap function, which quantifies the level of agreement between the fat-jet and the template, allowing an efficient discrimination of signal from the background contributions. A working point has been decided in order to obtain a signal efficiency close to 90% and a corresponding background rejection at 70%. TOM performances have been tested on MC samples in the muon channel and compared with the previous methods present in literature. All the methods will be merged in a multivariate analysis to give a global top tagging which will be included in ttbar production differential cross section performed on the data acquired in 2012 at sqrt(s)=8 TeV in high phase space region, where new physics processes could be possible. Due to its peculiarity to increase the pT, the Template Overlap Method will play a crucial role in the next data taking at sqrt(s)=13 TeV, where the almost totality of the tops will be produced at high energy, making the standard reconstruction methods inefficient.

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This dissertation document deals with the development of a project, over a span of more than two years, carried out within the scope of the Arrowhead Framework and which bears my personal contribution in several sections. The final part of the project took place during a visiting period at the university of Luleå. The Arrowhead Project is an European project, belonging to the ARTEMIS association, which aims to foster new technologies and unify the access to them into an unique framework. Such technologies include the Internet of Things phe- nomenon, Smart Houses, Electrical Mobility and renewable energy production. An application is considered compliant with such framework when it respects the Service Oriented Architecture paradigm and it is able to interact with a set of defined components called Arrowhead Core Services. My personal contribution to this project is given by the development of several user-friendly API, published in the project's main repository, and the integration of a legacy system within the Arrowhead Framework. The implementation of this legacy system was initiated by me in 2012 and, after many improvements carried out by several developers in UniBO, it has been again significantly modified this year in order to achieve compatibility. The system consists of a simulation of an urban scenario where a certain amount of electrical vehicles are traveling along their specified routes. The vehicles are con-suming their battery and, thus, need to recharge at the charging stations. The electrical vehicles need to use a reservation mechanism to be able to recharge and avoid waiting lines, due to the long recharge process. The integration with the above mentioned framework consists in the publication of the services that the system provides to the end users through the instantiation of several Arrowhead Service Producers, together with a demo Arrowhead- compliant client application able to consume such services.

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This thesis is based on two studies that are related to floating wave energy conversion (WEC) devices and turbulent fountains. The ability of the open-source CFD software OpenFOAM® has been studied to simulate these phenomena. The CFD model has been compared with the physical experimental results. The first study presents a model of a WEC device, called MoonWEC, which is patented by the University of Bologna. The CFD model of the MoonWEC under the action of waves has been simulated using OpenFOAM and the results are promising. The reliability of the CFD model is confirmed by the laboratory experiments, conducted at the University of Bologna, for which a small-scale prototype of the MoonWEC was made from wood and brass. The second part of the thesis is related to the turbulent fountains which are formed when a heavier source fluid is injected upward into a lighter ambient fluid, or else a lighter source fluid is injected downward into a heavier ambient fluid. For this study, the first case is considered for laboratory experiments and the corresponding CFD model. The vertical releases of the source fluids into a quiescent, uniform ambient fluid, from a circular source, were studied with different densities in the laboratory experiments, conducted at the University of Parma. The CFD model has been set up for these experiments. Favourable results have been observed from the OpenFOAM simulations for the turbulent fountains as well, indicating that it can be a reliable tool for the simulation of such phenomena.

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The voltage profile of the catenary between traction substations (TSSs) is affected by the trolleybus current intake and by its position with respect to the TSSs: the higher the current requested by the bus and the further the bus from the TSSs, the deeper the voltage drop. When the voltage drops below 500V, the trolleybus is forced to decrease its consumption by reducing its input current. This thesis deals with the analysis of the improvements that the installation of an BESS produces in the operation of a particularly loaded FS of the DC trolleybus network of the city of Bologna. The stationary BESS is charged by the TSSs during off-peak times and delivers the stored energy when the catenary is overloaded alleviating the load on the TSSs and reducing the voltage drops. Only IMC buses are considered in the prospect of a future disposal of all internal combustion engine vehicles. These trolleybuses cause deeper voltage drops because they absorb enough current to power their traction motor and recharge the on board battery. The control of the BESS aims to keep the catenary voltage within the admissible voltage range and makes sure that all physical limitations are met. A model of FS Marconi Trento Trieste is implemented in Simulink environment to simulate its daily operation and compare the behavior of the trolleybus network with and without BESS. From the simulation without BESS, the best location of the energy storage system is deduced, and the battery control is tuned. Furthermore, from the knowledge of the load curve and the battery control trans-characteristic, it is formulated a prediction of the voltage distribution at BESS connection point. The prediction is then compared with the simulation results to validate the Simulink model. The BESS allows to decrease the voltage drops along the catenary, the Joule losses and the current delivered by the TSSs, indicating that the BESS can be a solution to improve the operation of the trolleybus network.

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The scientific success of the LHC experiments at CERN highly depends on the availability of computing resources which efficiently store, process, and analyse the amount of data collected every year. This is ensured by the Worldwide LHC Computing Grid infrastructure that connect computing centres distributed all over the world with high performance network. LHC has an ambitious experimental program for the coming years, which includes large investments and improvements both for the hardware of the detectors and for the software and computing systems, in order to deal with the huge increase in the event rate expected from the High Luminosity LHC (HL-LHC) phase and consequently with the huge amount of data that will be produced. Since few years the role of Artificial Intelligence has become relevant in the High Energy Physics (HEP) world. Machine Learning (ML) and Deep Learning algorithms have been successfully used in many areas of HEP, like online and offline reconstruction programs, detector simulation, object reconstruction, identification, Monte Carlo generation, and surely they will be crucial in the HL-LHC phase. This thesis aims at contributing to a CMS R&D project, regarding a ML "as a Service" solution for HEP needs (MLaaS4HEP). It consists in a data-service able to perform an entire ML pipeline (in terms of reading data, processing data, training ML models, serving predictions) in a completely model-agnostic fashion, directly using ROOT files of arbitrary size from local or distributed data sources. This framework has been updated adding new features in the data preprocessing phase, allowing more flexibility to the user. Since the MLaaS4HEP framework is experiment agnostic, the ATLAS Higgs Boson ML challenge has been chosen as physics use case, with the aim to test MLaaS4HEP and the contribution done with this work.

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In recent years, developed countries have turned their attention to clean and renewable energy, such as wind energy and wave energy that can be converted to electrical power. Companies and academic groups worldwide are investigating several wave energy ideas today. Accordingly, this thesis studies the numerical simulation of the dynamic response of the wave energy converters (WECs) subjected to the ocean waves. This study considers a two-body point absorber (2BPA) and an oscillating surge wave energy converter (OSWEC). The first aim is to mesh the bodies of the earlier mentioned WECs to calculate their hydrostatic properties using axiMesh.m and Mesh.m functions provided by NEMOH. The second aim is to calculate the first-order hydrodynamic coefficients of the WECs using the NEMOH BEM solver and to study the ability of this method to eliminate irregular frequencies. The third is to generate a *.h5 file for 2BPA and OSWEC devices, in which all the hydrodynamic data are included. The BEMIO, a pre-and post-processing tool developed by WEC-Sim, is used in this study to create *.h5 files. The primary and final goal is to run the wave energy converter Simulator (WEC-Sim) to simulate the dynamic responses of WECs studied in this thesis and estimate their power performance at different sites located in the Mediterranean Sea and the North Sea. The hydrodynamic data obtained by the NEMOH BEM solver for the 2BPA and OSWEC devices studied in this thesis is imported to WEC-Sim using BEMIO. Lastly, the power matrices and annual energy production (AEP) of WECs are estimated for different sites located in the Sea of Sicily, Sea of Sardinia, Adriatic Sea, Tyrrhenian Sea, and the North Sea. To this end, the NEMOH and WEC-Sim are still the most practical tools to estimate the power generation of WECs numerically.

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The work presented in this thesis aims to contribute to innovation in the Urban Air Mobility and Delivery sector and represents a solid starting point for air logistics and its future scenarios. The dissertation focuses on modeling, simulation, and control of a formation of multirotor aircraft for cooperative load transportation, with particular attention to environmental sustainability. First, a simulation and test environment is developed to assess technologies for suspended load stabilization. Starting from the mathematical model of two identical multirotors, formation-flight-keeping and collision-avoidance algorithms are analyzed. This approach guarantees both the safety of the vehicles within the formation and that of the payload, which may be made of people in the very near future. Afterwards, a mathematical model for the suspended load is implemented, as well as an active controller for its stabilization. The key focus of this part is represented by both analysis and control of payload oscillatory motion, by thoroughly investigating load kinetic energy decay. At this point, several test cases were introduced, in order to understand which strategy is the most effective and safe in terms of future applications in the field of air logistics.

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Modern High-Performance Computing HPC systems are gradually increasing in size and complexity due to the correspondent demand of larger simulations requiring more complicated tasks and higher accuracy. However, as side effects of the Dennard’s scaling approaching its ultimate power limit, the efficiency of software plays also an important role in increasing the overall performance of a computation. Tools to measure application performance in these increasingly complex environments provide insights into the intricate ways in which software and hardware interact. The monitoring of the power consumption in order to save energy is possible through processors interfaces like Intel Running Average Power Limit RAPL. Given the low level of these interfaces, they are often paired with an application-level tool like Performance Application Programming Interface PAPI. Since several problems in many heterogeneous fields can be represented as a complex linear system, an optimized and scalable linear system solver algorithm can decrease significantly the time spent to compute its resolution. One of the most widely used algorithms deployed for the resolution of large simulation is the Gaussian Elimination, which has its most popular implementation for HPC systems in the Scalable Linear Algebra PACKage ScaLAPACK library. However, another relevant algorithm, which is increasing in popularity in the academic field, is the Inhibition Method. This thesis compares the energy consumption of the Inhibition Method and Gaussian Elimination from ScaLAPACK to profile their execution during the resolution of linear systems above the HPC architecture offered by CINECA. Moreover, it also collates the energy and power values for different ranks, nodes, and sockets configurations. The monitoring tools employed to track the energy consumption of these algorithms are PAPI and RAPL, that will be integrated with the parallel execution of the algorithms managed with the Message Passing Interface MPI.