RISK ASSESSMENT OF MALICIOUS ATTACKS AGAINST POWER SYSTEMS

The new scenarios of malicious attack prompt for their deeper consideration and mainly when critical systems are at stake. In this framework, infrastructural systems, including power systems, represent a possible target due to the huge impact they can have on society. Malicious attacks are different in their nature from other more traditional cause of threats to power system, since they embed a strategic interaction between the attacker and the defender (characteristics that cannot be found in natural events or systemic failures). This difference has not been systematically analyzed by the existent literature. In this respect, new approaches and tools are needed. This paper presents a mixed-strategy game-theory model able to capture the strategic interactions between malicious agents that may be willing to attack power systems and the system operators, with its related bodies, that are in charge of defending them. At the game equilibrium, the different strategies of the two players, in terms of attacking/protecting the critical elements of the systems, can be obtained. The information about the attack probability to various elements can be used to assess the risk associated with each of them, and the efficiency of defense resource allocation is evidenced in terms of the corresponding risk. Reference defense plans related to the online defense action and the defense action with a time delay can be obtained according to their respective various time constraints. Moreover, risk sensitivity to the defense/attack-resource variation is also analyzed. The model is applied to a standard IEEE RTS-96 test system for illustrative purpose and, on the basis of that system, some peculiar aspects of the malicious attacks are pointed ou

Combustion characteristics of cottonseed biodiesel and chicken fat biodiesel mixture in a multi-cylinder compression ignition engine

Although waste animal fats such as chicken fat are promising alternative energy sources, biodiesels produced from these type of feedstocks hardly satisfies the EN14214 biodiesel standards. In this study, biomixtures were prepared by blending cottonseed biodiesel and chicken rendering fat biodiesel which were produced via transesterification method. Biodiesels were blended with each other at 60/40, 50/50 and 30/70 volume ratios to produce CO60CH40, CO50CH50 and CO30CH70 fuels. First, fuel properties of the neat biodiesels and novel biomixtures were measured and compared to European biodiesel standards and diesel. Then, the engine performance, combustion characteristics and exhaust emissions of these novel biomixture fuels were measured in a three-cylinder indirect injection diesel engine under various engine loads and at constant speed of 1500 rpm. The fuel characterisation showed that CO60CH40 and CO50CH50 biomixtures met the European standards. The Brake Specific Energy Consumption (BSEC) and Brake Thermal Efficiency (BTE) of all biomixtures were comparable with CO100, CH100 and diesel at the full engine load. The combustion results revealed that the maximum in-cylinder pressure and energy release values of the CO50CH50 were 4.2% and 4.4% higher than the diesel at full engine load because of optimised fuel properties of biomixture such as molecular structure, viscosity, cetane number and iodine value. CO50CH50 had 2.9% reduced CO 2 and comparable CO emission compared to diesel, which were also 5.6% and 13% lower than cottonseed biodiesel respectively. However, NO emission of CO50CH50 was found 3.8% and 5.8% higher than diesel and cottonseed biodiesel. A 6.5% reduction on NO emission was observed when CO60CH40 biomixture fuel was used instead of diesel. To conclude, this research showed that blending of cottonseed and chicken fat biodiesels is a promising approach to meet the EN14214 standards, improve in-cylinder pressure, optimise energy release and reduce exhaust emissions. Blending of different biodiesels will be tested as a future work

Modified Selective Non-Catalytic Reduction System to Reduce NOx Gas Emission in Biodiesel Powered Engines

Biodiesel is considered as one of the attractive alternatives to fossil diesel fuel. Although biodiesels reduces most of the harmful gas emissions, they normally releases higher NOx emissions compared to fossil diesel. The Selective Catalytic Reduction (SCR) is a well-known technique used in the OEM industry to mitigate NOx emission. However, this technique may not be suitable for application in low power density engines due to back pressure and clogging issues. On the other hand, Selective Non-Catalytic Reduction (SNCR) is used in relatively large combustion operations ie. boilers and incinerators. The main disadvantage of SNCR technique is the high temperature window for diesel engine exhaust temperature. This study introduces a new design concept, which is a combination of SCR and SNCR systems, for low power density diesel engines. The developed after-treatment system composed of two main parts, injection-expansion pipe and swirl chamber. The working principle is providing maximum mixing of the injected fluid and exhaust gas in the expansion chamber, then creating a maximum turbulence in the swirl chamber. In this regard, NOx emission can be reduced at relatively lower exhaust temperatures without using any catalyst. The CFD models of three design candidates were examined in terms of velocity magnitudes, turbulence intensity and particle residence time to select the optimum physical dimensions. The selected design was manufactured and installed to exhaust system of a 1.3 litre diesel engine. Two fluids distilled water and urea-water solution were injected separately at the same flow rate of 375 ml/min. Exhaust gas emissions of fossil diesel, sheep fat biodiesel – waste cooking oil biodiesel blend and chicken fat – cottonseed biodiesel blend were tested. No significant changes in CO2 and HC emissions were observed. However, it was found that distilled water injection reduced CO and NO emissions by about 10% and 6% for fossil diesel; and by about 9% and 7% for biodiesels operation respectively. The urea-water injection led to reductions in CO and NO emissions by about 60% and 13% for fossil diesel; and by about 45% and 15% for biodiesels respectively

Production, Characterisation and Assessment of Biomixture Fuels for Compression Ignition Engine Application

Hardly any neat biodiesel satisfies the European EN14214 standard for compression ignition engine application. To satisfy the EN14214 standard, various additives are doped into biodiesel; however, biodiesel additives might cause other problems such as increase in the particular emission and increased specific fuel consumption. In addition, the additives could be expensive. Considering the increasing level of greenhouse gas GHG emissions and fossil fuel depletion, it is forecasted that the use of biodiesel will be higher in the near future. Hence, the negative aspects of the biodiesel additives will likely to gain much more importance and need to be replaced with better solutions. This study aims to satisfy the European standard EN14214 by blending the biodiesels derived from sustainable feedstocks. Waste Cooking Oil (WCO) and Animal Fat Oil (AFO) are two sustainable feedstocks in the EU (including the UK) for producing biodiesels. In the first stage of the study, these oils were transesterified separately and neat biodiesels (W100 & A100) were produced. Secondly, the biodiesels were blended together in various ratios: 80% WCO biodiesel and 20% AFO biodiesel (W80A20), 60% WCO biodiesel and 40% AFO biodiesel (W60A40), 50% WCO biodiesel and 50% AFO biodiesel (W50A50), 30% WCO biodiesel and 70% AFO biodiesel (W30A70), 10% WCO biodiesel and 90% AFO biodiesel (W10A90). The prepared samples were analysed using Thermo Scientific Trace 1300 Gas Chromatograph and ISQ LT Mass Spectrometer (GC-MS). The GSMS analysis gave Fatty Acid Methyl Ester (FAME) breakdowns of the fuel samples. It was found that total saturation degree of the samples was linearly increasing (from 15% for W100 to 54% for A100) as the percentage of the AFO biodiesel was increased. Furthermore, it was found that WCO biodiesel was mainly (82%) composed of polyunsaturated FAMEs. Cetane numbers, iodine numbers, calorific values, lower heating values and the densities (at 15 oC) of the samples were estimated by using the mass percentages data of the FAMEs. Besides, kinematic viscosities (at 40 °C and 20°C), densities (at 15 °C), heating values and flash point temperatures of the biomixture samples were measured in the lab. It was found that estimated and measured characterisation results were comparable. The current study concluded that biomixture fuel samples W60A40 and W50A50 were perfectly satisfying the European EN 14214 norms without any need of additives. Investigation on engine performance, exhaust emission and combustion characteristics will be conducted to assess the full feasibility of the proposed biomixture fuels

On chip interconnects for multiprocessor turbo decoding architectures

International audienc

Combining learning and constraints for genome-wide protein annotation

BackgroundThe advent of high-throughput experimental techniques paved the way to genome-wide computational analysis and predictive annotation studies. When considering the joint annotation of a large set of related entities, like all proteins of a certain genome, many candidate annotations could be inconsistent, or very unlikely, given the existing knowledge. A sound predictive framework capable of accounting for this type of constraints in making predictions could substantially contribute to the quality of machine-generated annotations at a genomic scale.ResultsWe present Ocelot, a predictive pipeline which simultaneously addresses functional and interaction annotation of all proteins of a given genome. The system combines sequence-based predictors for functional and protein-protein interaction (PPI) prediction with a consistency layer enforcing (soft) constraints as fuzzy logic rules. The enforced rules represent the available prior knowledge about the classification task, including taxonomic constraints over each GO hierarchy (e.g. a protein labeled with a GO term should also be labeled with all ancestor terms) as well as rules combining interaction and function prediction. An extensive experimental evaluation on the Yeast genome shows that the integration of prior knowledge via rules substantially improves the quality of the predictions. The system largely outperforms GoFDR, the only high-ranking system at the last CAFA challenge with a readily available implementation, when GoFDR is given access to intra-genome information only (as Ocelot), and has comparable or better results (depending on the hierarchy and performance measure) when GoFDR is allowed to use information from other genomes. Our system also compares favorably to recent methods based on deep learning

Vertex reconstruction for proton-proton collisions in ALICE

Reconstructing the interaction vertex is a challenging task in the low multiplicity environment of pp collisions at the LHC. The two innermost layers of the Inner Tracking System (ITS), made of pixels, allow to obtain a first estimate of the vertex position, which can be provided also in a quasi-online mode, since only the local reconstruction is used. The optimal vertex measurement is obtained after the full event processing, using the tracks reconstructed in the ALICE barrel detectors. We present the methods for primary vertex reconstruction in pp collisions using pixels and tracks reconstructed in the ITS+TPC or in the TPC only. We also show the performance of the vertex finder in reconstructing displaced vertices originated by short-lived particles like charmed mesons

Multi-site European framework for real-time co-simulation of power systems

© The Institution of Engineering and Technology. The framework for virtual integration of laboratories enables co-simulation and joint experiments that include hardware and software resources hosted at geographically distributed laboratories. The underlying concept of such framework is geographically distributed real-time (RT) co-simulation. To this end, digital RT simulators are interfaced over long distances via shared communication network such as the Internet. This study proposes an architecture for a modular framework supporting virtual integration of laboratories that enable flexible integration of digital RT simulators across Europe. In addition, the framework includes an interface that enables access for third parties via a web browser. A co-simulation interface algorithm adopted in this study is based on representation of interface quantities in form of dynamic phasors. Time delay between RT digital simulators is compensated by means of phase shift that enables simulation fidelity for slow transients. The proposed architecture is realised for the integration of laboratories across Europe that are located at RWTH Aachen University in Germany, Politecnico di Torino in Italy and at European Commission Joint Research Centres in Petten, Netherland and in Ispra, Italy. The framework for virtual integration of laboratories presented in this study is applied for co-simulation of transmission and distribution systems

A BIM-enabled Decision Support System to support large-scale energy retrofitting processes and off-site solutions for envelope insulation

The urgency of renewing the Architecture, Engineering and Construction related processes to increase quality standards and performances while reducing costs and operations time is widely discussed in literature. In this scenario, increasing the energy renovation rate of the existing European building stock is a key priority to support the EU's 2050 decarbonisation targets through innovative solutions. The introduction of prefabricated panels for building renovation – incorporating insulation, mechanical systems, and finishing – can provide the existing buildings with improved structural, thermal, acoustic, and architectural features. The higher quality and safety for the off-site activities, the faster on-site application and the reduction of waste are some advantages of this typology of Modern Methods of Construction (MMC). Several digital and informative tools have been introduced over the last years to customize and integrate the design of prefabricated panels on existing building envelopes (i.e. panelisation tools). However, the comparison of technological alternatives is left to the intuition of designers and managed through the use of several tools that are not interconnected and often downstream the design process. This paper presents a Panelisation Design Tool, which is a Decision Support System (DSS) to help decision-makers in the choice of technological solutions for retrofitting operations during the Early Design Stage. Thanks to BIM integration, some indicators related to different aspects (n Dimensions) are extracted from the model of the panelised building to compare different technologies in a systematic way. The Panelisation Design Tool is tested on a case study building located in the city of Monza, in Northern Italy, used as a pilot in the BIM4EEB European Project. The test aimed at demonstrating the effectiveness of the chosen parameters to evaluate multiple technological solutions in an integrated BIM approach

Parallel H.264/AVC Fast Rate-Distortion Optimized Motion Estimation using Graphics Processing Unit and Dedicated Hardware

Heterogeneous systems on a single chip composed of CPU, Graphical Processing Unit (GPU), and Field Programmable Gate Array (FPGA) are expected to emerge in near future. In this context, the System on Chip (SoC) can be dynamically adapted to employ different architectures for execution of data-intensive applications. Motion estimation is one such task that can be accelerated using FPGA and GPU for high performance H.264/AVC encoder implementation. In most of works on parallel implementation of motion estimation, the bit rate cost of motion vectors is generally ignored. On the contrary, this paper presents a fast rate-distortion optimized parallel motion estimation algorithm implemented on GPU using OpenCL and FPGA/ASIC using VHDL. The predicted motion vectors are estimated from temporally preceding motion vectors and used for evaluating the bit rate cost of the motion vectors simultaneously. The experimental results show that the proposed scheme achieves significant speedup on GPU and FPGA, and has comparable ratedistortion performance with respect to sequential fast motion estimation algorithm