Hot-plug Based Activation and Deactivation of ATCA FRU Devices

Abstract: One of the most important features of the Advanced Telecommunications Computing Architecture (ATCA) contributing to its exceptional reliability and availability is its hot-swap functionality. In order for the user to be able to add and remove the components of an ATCA shelf without the necessity of switching the power on and off the PCI Industrial Computer Manufacturers Group (PICMG) specification clearly enumerates the stages a Field Replaceable Unit (FRU) has to go through upon insertion into and extraction from the shelf. These stages form the activation and deactivation processes that occur every time an element is changed in the ATCA system. This paper focuses on these processes placing the emphasis on the Electronic Keying (EK) implementation in the Intelligent Platform Management Controller (IPMC) software developed for the self-designed ATCA Carrier Board for FLASH. This Carrier Board utilizes the standard-defined PCI Express (PCIe) interface as well as introduces proprietary protocols in form of Rocket IO (RIO) and Low Latency Links (LLL)

A Prototype of a Decision Support System for River Basin Water Quality Management in Central and Eastern Europe

This Working Paper documents the implementation of a prototype of a Decision Support System (DSS) for regional water quality management applied to a case study of the Nitra River in Slovakia. With the goals of flexibility and simplicity in mind, two different approaches and tools have been implemented and tested. First, the object-oriented development tool ORVAN was used for fast prototyping of the mathematical programming model and for scenario analysis. Second, a problem-specific generator was implemented to generate various single criterion and multiple criteria optimization problems useful in examining the water quality problem. The resulting mixed-integer optimization problems were solved by the MOMIP package. Provided in the paper are the following: a complete formulation of the mathematical model, a detailed discussion of the data used, documentation of the developed software, an overview of interesting results, and recommendations for future work. Since only preliminary data were available at the time of performing the reported research, results are given merely as illustration of the methodology and software and should not he considered policy recommendations. For the latter task a verified data set and water quality model will be required

Multiple Criteria Analysis for Regional Water Quality Management: The Nitra River Case

This Working Paper documents the implementation of an element of a Decision Support System (DSS) for regional water quality management, applied in cooperation with the Water Research Institute (VUVH, Bratislava) and the Vah River Basin Authority to the Nitra River case study in Slovakia. Several re-usable, modular software tools have been developed and implemented -- a problem-specific generator to produce the core part of the mathematical programming model, tools for the generation and interactive modification of multicriteria problems, and a solver for the resulting mixed-integer optimization problem. Provided in the paper are the following: a complete formulation of the mathematical model (including the applied well-known dissolved oxygen model), a detailed discussion of the data used, documentation of the developed software, an overview of results which might be of interest, and recommendations for future work. Emphasis is placed on the advantages of multicriteria analysis for the regional water quality management problem

Distributed Radiation Monitoring System for Linear Accelerators based on CAN Bus

Abstract—Gamma and neutron radiation is produced during the normal operation of linear accelerators like Free-Electron Laser in Hamburg (FLASH) or X-ray Free Electron Laser (X-FEL). Gamma radiation cause general degeneration of electronics devices and neutron fluence can be a reason of soft error in memories and microcontrollers. X-FEL accelerator will be built only in one tunnel, therefore most of electronic control systems will be placed in radiation environment. Exposing control systems to radiation may lead to many errors and unexpected failure of the whole accelerator system. Thus, the radiation monitoring system able to monitor radiation doses produced near controlling systems is crucial. Knowledge of produced radiation doses allows to detect errors caused by radiation, make plans of essential exchange of control systems and prevent accelerator from serious damages. The paper presents the project of radiation monitoring system able to monitor radiation environment in real time

Bayesian calibration of the nitrous oxide emission module of an agro-ecosystem model

Nitrous oxide (N2O) is the main biogenic greenhouse gas contributing to the global warming potential (GWP) of agro-ecosystems. Evaluating the impact of agriculture on climate therefore requires a capacity to predict N2O emissions in relation to environmental conditions and crop management. Biophysical models simulating the dynamics of carbon and nitrogen in agro-ecosystems have a unique potential to explore these relationships, but are fraught with high uncertainties in their parameters due to their variations over time and space. Here, we used a Bayesian approach to calibrate the parameters of the N2O submodel of the agro-ecosystem model CERES-EGC. The submodel simulates N2O emissions from the nitrification and denitrification processes, which are modelled as the product of a potential rate with three dimensionless factors related to soil water content, nitrogen content and temperature. These equations involve a total set of 15 parameters, four of which are site-specific and should be measured on site, while the other 11 are considered global, i.e. invariant over time and space. We first gathered prior information on the model parameters based on the literature review, and assigned them uniform probability distributions. A Bayesian method based on the Metropolis–Hastings algorithm was subsequently developed to update the parameter distributions against a database of seven different field-sites in France. Three parallel Markov chains were run to ensure a convergence of the algorithm. This site-specific calibration significantly reduced the spread in parameter distribution, and the uncertainty in the N2O simulations. The model’s root mean square error (RMSE) was also abated by 73% across the field sites compared to the prior parameterization. The Bayesian calibration was subsequently applied simultaneously to all data sets, to obtain better global estimates for the parameters initially deemed universal. This made it possible to reduce the RMSE by 33% on average, compared to the uncalibrated model. These global parameter values may be used to obtain more realistic estimates of N2O emissions from arable soils at regional or continental scales