3,903 research outputs found

    Information and treatment of unknown correlations in the combination of measurements using the BLUE method

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    We discuss the effect of large positive correlations in the combinations of several measurements of a single physical quantity using the Best Linear Unbiased Estimate (BLUE) method. We suggest a new approach for comparing the relative weights of the different measurements in their contributions to the combined knowledge about the unknown parameter, using the well-established concept of Fisher information. We argue, in particular, that one We discuss the effect of large positive correlations in the combinations of several measurements of a single physical quantity using the Best Linear Unbiased Estimate (BLUE) method. We suggest a new approach for comparing the relative weights of the different measurements in their contributions to the combined knowledge about the unknown parameter, using the well-established concept of Fisher information. We argue, in particular, that one contribution to information comes from the collective interplay of the measurements through their correlations and that this contribution cannot be attributed to any of the individual measurements alone. We show that negative coefficients in the BLUE weighted average invariably indicate the presence of a regime of high correlations, where the effect of further increasing some of these correlations is that of reducing the error on the combined estimate. In these regimes, we stress that assuming fully correlated systematic uncertainties is not a truly conservative choice, and that the correlations provided as input to BLUE combinations need to be assessed with extreme care instead. In situations where the precise evaluation of these correlations is impractical, or even impossible, we provide tools to help experimental physicists perform more conservative combinations

    A low-cost radiation detection system to monitor radioactive environments by unmanned vehicles

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    AbstractUnconventional scenarios with hazardous radioactive levels are expected as consequences of accidents in the industrial sector of the nuclear energy production or following intentional releases of radioactive materials for terrorist purposes (dirty bombs, indoor contaminations, etc.). Nowadays, the need to balance the high standards of safety and security through an effective detection network is a matter of paramount importance. In this work, the authors' challenge has been to design, realize and test a low-cost gamma detection and spectroscopy system which may be used in unmanned vehicles in general and/or drones with low payload capabilities. The designed platform may be used to carry out mapping or localization operations in order to reduce the risk factor for first responders or for the population affected by radiological and nuclear events. In this paper, the design process of a gamma ray detection and spectroscopy system based on affordable and commercially available technologies is presented along with the results of our ongoing characterization of the prototype

    Drones and Sensors Ecosystem to Maximise the “Storm Effects” in Case of CBRNe Dispersion in Large Geographic Areas

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    The advancements in the field of robotics, specifically in the aerial robotics, combined with technological improvements of the capability of drones, have increased dramatically the use of these devices as a valuable tool in a wide range of applications. From civil to commercial and military area, the requirements in the emerging application for monitoring complex scenarios that are potentially dangerous for operators give rise to the need of a more powerful and sophisticated approach. This work aims at proposing the use of swarm drones to increase plume detection, tracking and source declaration for chemical releases. The several advantages which this technology may lead to this research and application fields are investigated, as well as the research and technological activities to be performed to make swarm drones efficient, reliable, and accurate

    changing the batch system in a tier 1 computing center why and how

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    At the Italian Tierl Center at CNAF we are evaluating the possibility to change the current production batch system. This activity is motivated mainly because we are looking for a more flexible licensing model as well as to avoid vendor lock-in. We performed a technology tracking exercise and among many possible solutions we chose to evaluate Grid Engine as an alternative because its adoption is increasing in the HEPiX community and because it's supported by the EMI middleware that we currently use on our computing farm. Another INFN site evaluated Slurm and we will compare our results in order to understand pros and cons of the two solutions. We will present the results of our evaluation of Grid Engine, in order to understand if it can fit the requirements of a Tier 1 center, compared to the solution we adopted long ago. We performed a survey and a critical re-evaluation of our farming infrastructure: many production softwares (accounting and monitoring on top of all) rely on our current solution and changing it required us to write new wrappers and adapt the infrastructure to the new system. We believe the results of this investigation can be very useful to other Tier-ls and Tier-2s centers in a similar situation, where the effort of switching may appear too hard to stand. We will provide guidelines in order to understand how difficult this operation can be and how long the change may take

    The HotSpot Code as a Tool to Improve Risk Analysis During Emergencies: Predicting I-131 and CS-137 Dispersion in the Fukushima Nuclear Accident

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    Conventional and non-conventional emergencies are among the most important safety and security concerns of the new millennium. Nuclear power and research plants, high-energy particle accelerators, radioactive substances for industrial and medical uses are all considered credible sources of threats both in warfare and in terror scenarios. Estimates of potential radiation releases of radioactive contamination related to these threats are therefore essential in order to prepare and respond to such scenarios. The goal of this paper is to demonstrate that computational modeling codes to simulate transport of radioactivity are extremely valuable to assess expected radiation levels and to improve risk analysis during emergencies helping the emergency planner and the first responders in the first hours of an occurring emergency

    Development and performance testing of a miniaturized multi-sensor system combining MOX and PID for potential UAV application in TIC, VOC and CWA dispersion scenarios

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    The development of a tool to reduce the exposure of personnel in case of inten- tional or accidental toxic chemicals dispersion scenarios opens the field to new operational perspectives in the domain of operator safety and of critical infrastructure monitoring. The use of two sensors with different operating principles, metal oxide and photo-ionization detector, allows to confirm the presence of specific classes of chemicals in a contaminated area. All instruments are expected to be integrated into the payload of an unmanned aerial vehicle (UAV) and used for different purposes such as critical infrastructure surveillance focused on the volatile organic chemical and chemical warfare agents (CWA) detection and the post-incident of contamination level monitoring. In this paper, the authors presented the hardware set-up implemented and the test realized with CWAs simulants and will discuss the results obtained presenting advantages and disadvantages of this system in an application such as a UAV for the detection of chemical substances

    Design of Miniaturized Sensors for a Mission-Oriented UAV Application: A New Pathway for Early Warning

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    In recent decades, the increasing threats associated with Chemical and Radiological (CR) agents prompted the development of new tools to detect and collect samples without putting in danger first responders inside contaminated areas. A particularly promising branch of these technological developments relates to the integration of different detectors and sampling systems with Unmanned Aerial Vehicles (UAV). The adoption of this equipment may bring significant benefits for both military and civilian implementations. For instance, instrumented UAVs could be used in support of specialist military teams such as Sampling and Identification of Biological, Chemical and Radiological Agents (SIBCRA) team, tasked to perform sampling in contaminated areas, detecting the presence of CR substances in field and then confirming, collecting and evaluating the effective threats. Furthermore, instrumented UAVs may find dual-use application in the civil world in support of emergency teams during industrial accidents and in the monitoring activities of critical infrastructures. Small size drones equipped with different instruments for detection and collection of samples may enable, indeed, several applications, becoming a tool versatile and easy to use in different fields, and even featuring equipment normally utilized in manual operation. The authors hereby present the design of miniaturized sensors for a mission-oriented UAV application and the preliminary results from an experimental campaign performed in 2020

    Long-Term Results at 10 Years of Pouch Resizing for Roux-en-Y Gastric Bypass Failure

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    Background: Roux-en-Y gastric bypass (RYGB) is currently one of the most performed bariatric procedures and it is associated with rapid weight loss. However, weight loss failure and weight regain after RYGB occurs in approximately 30% and 3-5% of patients, respectively, and represent a serious issue. RYGB pouch resizing is a surgical option that may be offered to selected patients with RYGB failure. The aim of this study is to assess long-term results of pouch resizing for RYGB failure. Materials and Methods: From February 2009 to November 2011, 20 consecutive patients underwent gastric pouch resizing for RYGB failure in our tertiary bariatric center. The primary outcome was the rate of failure (%EWL < 50% with at least one metabolic comorbidity) after at least 10 years from pouch resizing. Gastroesophageal Reflux Disease (GERD) was also assessed. Results: Twenty patients (18 women (90%)) were included and seventeen (85%) joined the study. The failure rate of pouch resizing was 47%. Mean %EWL and mean BMI were 47%, and 35.1 kg/m(2), respectively. Some of the persistent co-morbidities further improved or resolved after pouch resizing. Seven patients (41%) presented GERD requiring daily PPI with a significantly lower GERD-HQRL questionnaire score after pouch resizing (p < 0.001). Conclusion: Pouch resizing after RYGB results in a failure rate of 47% at the 10-year follow-up while the resolution of comorbidities is maintained over time despite a significant weight regain

    An Adjoint Method for the Optimal Boundary Control of Turbulent Flows Modeled with the Rans System

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    In recent years, the optimal control in fluid dynamics has gained attention for the design and the optimization of engineering devices. One of the main challenges concerns the application of the optimal control theory to turbulent flows modeled by the Reynolds averaging Navier-Stokes equations. In this work we propose the implementation of an optimal boundary control problem for the ReynoldsAveraged Navier-Stokes system closed with a two-equations turbulence model. The optimal boundary velocity is sought in order to achieve several objectives such as the enhancement of turbulence or the matching of the velocity field over a well defined domain region. The boundary where the control acts can be the main inlet section or additional injection holes placed along the domain. By minimizing the augmented Lagrangian functional we obtain the optimality system comprising the state, the adjoint, and the control equations. Furthermore, we propose numerical strategies that allow to solve the optimality system in a robust way for such a large number of unknowns

    Thermal-hydraulic and neutronic codes coupling for the analysis of a Lead Fast Reactor

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    In this work the thermal-hydraulics and neutronics behavior of a Lead Fast Reactor (LFR) core is investigated evaluating the power generation distribution taking into account the local temperature field. The temperature field is evaluated using the CFD finite element code FEMuS and exchanged with the multiscale neutron code DONJON-DRAGON, which interpolates the macroscopic cross-sections according to the local temperature field and local lead density distribution. As a result, the neutron flux changes and defines a new power density distribution which is used to update the temperature field into the CFD code. The coupling between neutron and CFD codes is achieved through their inclusion into the numerical platform SALOME. The numerical libraries MED, included into the SALOME platform, are used to exchange data run-time between FEMuS and DONJON
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