6 resultados para Approximat Model (scheme)
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
This thesis deals with a novel control approach based on the extension of the well-known Internal Model Principle to the case of periodic switched linear exosystems. This extension, inspired by power electronics applications, aims to provide an effective design method to robustly achieve the asymptotic tracking of periodic references with an infinite number of harmonics. In the first part of the thesis the basic components of the novel control scheme are described and preliminary results on stabilization are provided. In the second part, advanced control methods for two applications coming from the world high energy physics are presented.
Resumo:
Different tools have been used to set up and adopt the model for the fulfillment of the objective of this research. 1. The Model The base model that has been used is the Analytical Hierarchy Process (AHP) adapted with the aim to perform a Benefit Cost Analysis. The AHP developed by Thomas Saaty is a multicriteria decision - making technique which decomposes a complex problem into a hierarchy. It is used to derive ratio scales from both discreet and continuous paired comparisons in multilevel hierarchic structures. These comparisons may be taken from actual measurements or from a fundamental scale that reflects the relative strength of preferences and feelings. 2. Tools and methods 2.1. The Expert Choice Software The software Expert Choice is a tool that allows each operator to easily implement the AHP model in every stage of the problem. 2.2. Personal Interviews to the farms For this research, the farms of the region Emilia Romagna certified EMAS have been detected. Information has been given by EMAS center in Wien. Personal interviews have been carried out to each farm in order to have a complete and realistic judgment of each criteria of the hierarchy. 2.3. Questionnaire A supporting questionnaire has also been delivered and used for the interviews . 3. Elaboration of the data After data collection, the data elaboration has taken place. The software support Expert Choice has been used . 4. Results of the Analysis The result of the figures above (vedere altro documento) gives a series of numbers which are fractions of the unit. This has to be interpreted as the relative contribution of each element to the fulfillment of the relative objective. So calculating the Benefits/costs ratio for each alternative the following will be obtained: Alternative One: Implement EMAS Benefits ratio: 0, 877 Costs ratio: 0, 815 Benfit/Cost ratio: 0,877/0,815=1,08 Alternative Two: Not Implement EMAS Benefits ratio: 0,123 Costs ration: 0,185 Benefit/Cost ratio: 0,123/0,185=0,66 As stated above, the alternative with the highest ratio will be the best solution for the organization. This means that the research carried out and the model implemented suggests that EMAS adoption in the agricultural sector is the best alternative. It has to be noted that the ratio is 1,08 which is a relatively low positive value. This shows the fragility of this conclusion and suggests a careful exam of the benefits and costs for each farm before adopting the scheme. On the other part, the result needs to be taken in consideration by the policy makers in order to enhance their intervention regarding the scheme adoption on the agricultural sector. According to the AHP elaboration of judgments we have the following main considerations on Benefits: - Legal compliance seems to be the most important benefit for the agricultural sector since its rank is 0,471 - The next two most important benefits are Improved internal organization (ranking 0,230) followed by Competitive advantage (ranking 0, 221) mostly due to the sub-element Improved image (ranking 0,743) Finally, even though Incentives are not ranked among the most important elements, the financial ones seem to have been decisive on the decision making process. According to the AHP elaboration of judgments we have the following main considerations on Costs: - External costs seem to be largely more important than the internal ones (ranking 0, 857 over 0,143) suggesting that Emas costs over consultancy and verification remain the biggest obstacle. - The implementation of the EMS is the most challenging element regarding the internal costs (ranking 0,750).
Resumo:
In the last few years the resolution of numerical weather prediction (nwp) became higher and higher with the progresses of technology and knowledge. As a consequence, a great number of initial data became fundamental for a correct initialization of the models. The potential of radar observations has long been recognized for improving the initial conditions of high-resolution nwp models, while operational application becomes more frequent. The fact that many nwp centres have recently taken into operations convection-permitting forecast models, many of which assimilate radar data, emphasizes the need for an approach to providing quality information which is needed in order to avoid that radar errors degrade the model's initial conditions and, therefore, its forecasts. Environmental risks can can be related with various causes: meteorological, seismical, hydrological/hydraulic. Flash floods have horizontal dimension of 1-20 Km and can be inserted in mesoscale gamma subscale, this scale can be modeled only with nwp model with the highest resolution as the COSMO-2 model. One of the problems of modeling extreme convective events is related with the atmospheric initial conditions, in fact the scale dimension for the assimilation of atmospheric condition in an high resolution model is about 10 Km, a value too high for a correct representation of convection initial conditions. Assimilation of radar data with his resolution of about of Km every 5 or 10 minutes can be a solution for this problem. In this contribution a pragmatic and empirical approach to deriving a radar data quality description is proposed to be used in radar data assimilation and more specifically for the latent heat nudging (lhn) scheme. Later the the nvective capabilities of the cosmo-2 model are investigated through some case studies. Finally, this work shows some preliminary experiments of coupling of a high resolution meteorological model with an Hydrological one.
Resumo:
The development of a multibody model of a motorbike engine cranktrain is presented in this work, with an emphasis on flexible component model reduction. A modelling methodology based upon the adoption of non-ideal joints at interface locations, and the inclusion of component flexibility, is developed: both are necessary tasks if one wants to capture dynamic effects which arise in lightweight, high-speed applications. With regard to the first topic, both a ball bearing model and a journal bearing model are implemented, in order to properly capture the dynamic effects of the main connections in the system: angular contact ball bearings are modelled according to a five-DOF nonlinear scheme in order to grasp the crankshaft main bearings behaviour, while an impedance-based hydrodynamic bearing model is implemented providing an enhanced operation prediction at the conrod big end locations. Concerning the second matter, flexible models of the crankshaft and the connecting rod are produced. The well-established Craig-Bampton reduction technique is adopted as a general framework to obtain reduced model representations which are suitable for the subsequent multibody analyses. A particular component mode selection procedure is implemented, based on the concept of Effective Interface Mass, allowing an assessment of the accuracy of the reduced models prior to the nonlinear simulation phase. In addition, a procedure to alleviate the effects of modal truncation, based on the Modal Truncation Augmentation approach, is developed. In order to assess the performances of the proposed modal reduction schemes, numerical tests are performed onto the crankshaft and the conrod models in both frequency and modal domains. A multibody model of the cranktrain is eventually assembled and simulated using a commercial software. Numerical results are presented, demonstrating the effectiveness of the implemented flexible model reduction techniques. The advantages over the conventional frequency-based truncation approach are discussed.
Resumo:
Idiopathic pulmonary fibrosis (IPF) is a chronic progressive disease with no curative pharmacological treatment. Animal models play an essential role in revealing molecular mechanisms involved in the pathogenesis of the disease. Bleomycin (BLM)-induced lung fibrosis is the most widely used and characterized model for anti-fibrotic drugs screening. However, several issues have been reported, such as the identification of an optimal BLM dose and administration scheme as well as gender-specificity. Moreover, the balance between disease resolution, an appropriate time window for therapeutic intervention and animal welfare remains critical aspects yet to be fully elucidated. In this thesis, Micro CT imaging has been used as a tool to identify the ideal BLM dose regimen to induce sustained lung fibrosis in mice as well as to assess the anti-fibrotic effect of Nintedanib (NINT) treatment upon this BLM administration regimen. In order to select the optimal BLM dose scheme, C57bl/6 male mice were treated with BLM via oropharyngeal aspiration (OA), following either double or triple BLM administration. The triple BLM administration resulted in the most promising scheme, able to balance disease resolution, appropriate time-window for therapeutic intervention and animal welfare. The fibrosis progression was longitudinally assessed by micro-CT every 7 days for 5 weeks after BLM administration and 5 animals were sacrificed at each timepoint for the BALF and histological evaluation. The antifibrotic effect of NINT was assessed following different treatment regimens in this model. Herein, we have developed an optimized mouse model of pulmonary fibrosis, enabling three weeks of the therapeutic window to screen putative anti-fibrotic drugs. micro-CT scanning, allowed us to monitor the progression of lung fibrosis and the therapeutical response longitudinally in the same subject, drastically reducing the number of animals involved in the experiment.
Resumo:
We start in Chapter 2 to investigate linear matrix-valued SDEs and the Itô-stochastic Magnus expansion. The Itô-stochastic Magnus expansion provides an efficient numerical scheme to solve matrix-valued SDEs. We show convergence of the expansion up to a stopping time τ and provide an asymptotic estimate of the cumulative distribution function of τ. Moreover, we show how to apply it to solve SPDEs with one and two spatial dimensions by combining it with the method of lines with high accuracy. We will see that the Magnus expansion allows us to use GPU techniques leading to major performance improvements compared to a standard Euler-Maruyama scheme. In Chapter 3, we study a short-rate model in a Cox-Ingersoll-Ross (CIR) framework for negative interest rates. We define the short rate as the difference of two independent CIR processes and add a deterministic shift to guarantee a perfect fit to the market term structure. We show how to use the Gram-Charlier expansion to efficiently calibrate the model to the market swaption surface and price Bermudan swaptions with good accuracy. We are taking two different perspectives for rating transition modelling. In Section 4.4, we study inhomogeneous continuous-time Markov chains (ICTMC) as a candidate for a rating model with deterministic rating transitions. We extend this model by taking a Lie group perspective in Section 4.5, to allow for stochastic rating transitions. In both cases, we will compare the most popular choices for a change of measure technique and show how to efficiently calibrate both models to the available historical rating data and market default probabilities. At the very end, we apply the techniques shown in this thesis to minimize the collateral-inclusive Credit/ Debit Valuation Adjustments under the constraint of small collateral postings by using a collateral account dependent on rating trigger.