A Research Framework for the Multidisciplinary Design and Optimization of Wind Turbines

The design of very large wind turbines is a complex task which requires the development of dedicated tools and techniques. In this chapter, we present a system-level design procedure based on the combination of multi-body numerical models of the turbine and a multilevel optimization scheme. The overall design aims at the minimization of the cost of energy (COE) through the optimization of all the characteristics of the turbine, and the procedure automatically manages all the simulations required to compute relevant loads and displacements. This unique setup allows the designer to conduct trade-off studies in a highly realistic virtual environment and is an ideal test bench for advanced research studies in which it is important to assess the economic impact of specific design choices. Examples of such studies include the impact of stall-induced vibrations on fatigue, the development of active/passive control laws for large rotors, and the complete definition of 10–20 MW reference turbines

Setup of cryogenic front-end electronic systems for germanium detectors read-out

Front-end electronic devices for the read-out of ionizing radiation detectors must operate in many cases at cryogenic temperatures. In this work we focus in particular on front-end read-out systems for High-Purity Germanium (HPGe) detectors, which are usually operated at Liquid Nitrogen (LN) temperature. We analyze the strong effects that the changed characteristics of the electronic active and passive devices have on the charge preamplifier performance when operated in LN, while taking into account the particularly challenging requirements that the circuit has to meet: radio-purity, physical reliability under thermal cycling, low noise (0.1–0.2% resolutions) and fast rise time (~20 ns) needed for pulse shape analysis applications. The developed circuit consists of an external silicon JFET (Junction Field Effect Transistor), an external feedback network, and an ASIC (Application Specific Integrated Circuit) realized in a 5V 0.8μm CMOS technology. This work has been carried on in the framework of the GERDA experiment (GERmanium Detector Array). We will focus in particular on the effects that this challenging cryogenic setup has on the preamplifier performances

Low-dose Oral Imatinib in the treatment of systemic sclerosis interstitial lung disease unresponsive to cyclophosphamide. A phase II pilot study

none16noFraticelli P, Gabrielli B; Pomponio, G; Valentini, G; Bosello, S; Riboldi, P; Gerosa, M; Faggioli, P; Giacomelli, R; Del Papa, N; Gerli, R; Lunardi, C; Bombardieri, S; Malorni, W; Corvetta, A; Moroncini, G; Gabrielli, A.Fraticelli P, Gabrielli B; Pomponio, G; Valentini, G; Bosello, S; Riboldi, P; Gerosa, M; Faggioli, P; Giacomelli, R; Del Papa, N; Gerli, R; Lunardi, C; Bombardieri, S; Malorni, W; Corvetta, A; Moroncini, Gianluca; Gabrielli, Armand

Epidemiological patterns of asbestos exposure and spatial clusters of incident cases of malignant mesothelioma from the Italian national registry

Abstract BACKGROUND: Previous ecological spatial studies of malignant mesothelioma cases, mostly based on mortality data, lack reliable data on individual exposure to asbestos, thus failing to assess the contribution of different occupational and environmental sources in the determination of risk excess in specific areas. This study aims to identify territorial clusters of malignant mesothelioma through a Bayesian spatial analysis and to characterize them by the integrated use of asbestos exposure information retrieved from the Italian national mesothelioma registry (ReNaM). METHODS: In the period 1993 to 2008, 15,322 incident cases of all-site malignant mesothelioma were recorded and 11,852 occupational, residential and familial histories were obtained by individual interviews. Observed cases were assigned to the municipality of residence at the time of diagnosis and compared to those expected based on the age-specific rates of the respective geographical area. A spatial cluster analysis was performed for each area applying a Bayesian hierarchical model. Information about modalities and economic sectors of asbestos exposure was analyzed for each cluster. RESULTS: Thirty-two clusters of malignant mesothelioma were identified and characterized using the exposure data. Asbestos cement manufacturing industries and shipbuilding and repair facilities represented the main sources of asbestos exposure, but a major contribution to asbestos exposure was also provided by sectors with no direct use of asbestos, such as non-asbestos textile industries, metal engineering and construction. A high proportion of cases with environmental exposure was found in clusters where asbestos cement plants were located or a natural source of asbestos (or asbestos-like) fibers was identifiable. Differences in type and sources of exposure can also explain the varying percentage of cases occurring in women among clusters. CONCLUSIONS: Our study demonstrates shared exposure patterns in territorial clusters of malignant mesothelioma due to single or multiple industrial sources, with major implications for public health policies, health surveillance, compensation procedures and site remediation programs

Modeling of GERDA Phase II data

The GERmanium Detector Array (GERDA) experiment at the Gran Sasso underground laboratory (LNGS) of INFN is searching for neutrinoless double-beta ($0\nu\beta\beta$) decay of $^{76}$Ge. The technological challenge of GERDA is to operate in a "background-free" regime in the region of interest (ROI) after analysis cuts for the full 100$\,$kg$\cdot$yr target exposure of the experiment. A careful modeling and decomposition of the full-range energy spectrum is essential to predict the shape and composition of events in the ROI around $Q_{\beta\beta}$ for the $0\nu\beta\beta$ search, to extract a precise measurement of the half-life of the double-beta decay mode with neutrinos ($2\nu\beta\beta$) and in order to identify the location of residual impurities. The latter will permit future experiments to build strategies in order to further lower the background and achieve even better sensitivities. In this article the background decomposition prior to analysis cuts is presented for GERDA Phase II. The background model fit yields a flat spectrum in the ROI with a background index (BI) of $16.04^{+0.78}_{-0.85} \cdot 10^{-3}\,$cts/(kg$\cdot$keV$\cdot$yr) for the enriched BEGe data set and $14.68^{+0.47}_{-0.52} \cdot 10^{-3}\,$cts/(kg$\cdot$keV$\cdot$yr) for the enriched coaxial data set. These values are similar to the one of Gerda Phase I despite a much larger number of detectors and hence radioactive hardware components

Modeling of GERDA Phase II data

The GERmanium Detector Array (Gerda) experiment at the Gran Sasso underground laboratory (LNGS) of INFN is searching for neutrinoless double-beta (0νββ) decay of 76Ge. The technological challenge of Gerda is to operate in a “background-free” regime in the region of interest (ROI) after analysis cuts for the full 100 kg·yr target exposure of the experiment. A careful modeling and decomposition of the full-range energy spectrum is essential to predict the shape and composition of events in the ROI around Qββ for the 0νββ search, to extract a precise measurement of the half-life of the double-beta decay mode with neutrinos (2νββ) and in order to identify the location of residual impurities. The latter will permit future experiments to build strategies in order to further lower the background and achieve even better sensitivities. In this article the background decomposition prior to analysis cuts is presented for Gerda Phase II. The background model fit yields a flat spectrum in the ROI with a background index (BI) of 16.04+0.78−0.85⋅10−3 cts/(keV·kg·yr) for the enriched BEGe data set and 14.68+0.47−0.52⋅10−3 cts/(keV·kg·yr) for the enriched coaxial data set. These values are similar to the one of Phase I despite a much larger number of detectors and hence radioactive hardware components

Three-Surface Model with Redundant Longitudinal Control: Modeling, Trim Optimization and Control in a Preliminary Design Perspective

Notwithstanding the interest in the three-surface concept shown by aircraft designers, this configuration was not thoroughly investigated in conjunction with the adoption of two-elevator surfaces, on both canard and tail. In fact, the inclusion of an additional elevator produces a redundant longitudinal control which can be specifically exploited to target trim optimization. The same redundancy can be also employed to improve the flying qualities of the three-surface aircraft. In this paper, after introducing a simple flight mechanics model, ideal for preliminary design and analyses, the advantages of this configuration are explored. Firstly, the problem of finding the elevator deflections of canard and tail for minimum drag in trim is formulated and solved. Secondarily, the updating of a two-surface back-tailed airplane into an equivalent three-surface one is demonstrated, showing the potential improvement in cruise performance. Finally, the controls are employed through a smart control law for achieving better flying qualities

Equalizing aerodynamic blade loads through individual pitch control via multiblade multilag transformation

Control algorithms for rotor load mitigation are today generally adopted by industry. Most of them are based on the Coleman transformation, which is easy to implement and bears satisfactory results when the rotor is balanced. A multitude of causes, e.g., blade erosion, dirt, and especially pitch misalignment, may create significant imbalances. This gives birth to undesirable vibrations and reduced control performance in terms of load mitigation. In this paper, an alternative transformation is introduced, able to detect and quantify the rotor load harmonics due to aerodynamic imbalance. Next, a control algorithm, capable of targeting rotor imbalance itself and simultaneously lowering rotor loads, is presented. The effectiveness of the proposed solution is confirmed through simulations in virtual environment