Evaluation of the Energy Balance of a Gasoline Engine Using Ethanol and n-Butanol as Additives

Energy supply is one of the most important current issues in the world. The most uses of fossil fuels are for providing power to internal combustion engines. The increase in the global price of fossil fuels and the environmental concerns have made researchers to look for alternate sources of energies, such as biofuels. The main disadvantage of biofuels is their low heating values. However, they can be used as gasoline additives. The aim of this study was to evaluate the energy balance of a four-cylinder gasoline engine with ethanol and n-butanol alcohols in different volume percentages at three different engine speed of 1000, 1500, 2000 rpm. The results showed that the engine brake power increased in fuel blends that contain bio-alcohols compared to pure gasoline fuel. Also, by increasing the engine speed, the engine brake power of the fuel blends increased so that at 2000 rpm, the G70E15B15 fuel blend had the highest brake power of 47.1 kW. Also, the exhaust heat loss in fuel blends containing ethanol and n-butanol increased compared to pure gasoline, and also increased with the increase in engine speed. The lowest exhaust heat loss of 3.98 kW related to pure gasoline at 1000 rpm and the highest exhaust heat loss of 6.38 kW for G70E15B15 fuel blend at 2000 rpm were obtained. Pure gasoline fuel had lower heat loss of cooling system than other fuel blends. Heat loss of cooling system decreased with increasing speed from 1000 to 2000 rpm. Therefore, the G70E15B15 fuel blend with 11.01 kW and pure gasoline with 2.89 kW had the highest and lowest heat loss of cooling system, respectively

Multidisciplinary Research and Practice for Information Systems: IFIP WG 8.4, 8.9/TC 5 International Cross-Domain Conference and Workshop on Availability, Reliability, and Security, CD-ARES 2012, Prague, Czech Republic, August 20-24, 2012. Proceedings

International audienceBook Front Matter of LNCS 746

Improving cyber security in industrial control system environment.

Integrating industrial control system (ICS) with information technology (IT) and internet technologies has made industrial control system environments (ICSEs) more vulnerable to cyber-attacks. Increased connectivity has brought about increased security threats, vulnerabilities, and risks in both technology and people (human) constituents of the ICSE. Regardless of existing security solutions which are chiefly tailored towards technical dimensions, cyber-attacks on ICSEs continue to increase with a proportionate level of consequences and impacts. These consequences include system failures or breakdowns, likewise affecting the operations of dependent systems. Impacts often include; marring physical safety, triggering loss of lives, causing huge economic damages, and thwarting the vital missions of productions and businesses. This thesis addresses uncharted solution paths to the above challenges by investigating both technical and human-factor security evaluations to improve cyber security in the ICSE. An ICS testbed, scenario-based, and expert opinion approaches are used to demonstrate and validate cyber-attack feasibility scenarios. To improve security of ICSs, the research provides: (i) an adaptive operational security metrics generation (OSMG) framework for generating suitable security metrics for security evaluations in ICSEs, and a list of good security metrics methodology characteristics (scope-definitive, objective-oriented, reliable, simple, adaptable, and repeatable), (ii) a technical multi-attribute vulnerability (and impact) assessment (MAVCA) methodology that considers and combines dynamic metrics (temporal and environmental) attributes of vulnerabilities with the functional dependency relationship attributes of the vulnerability host components, to achieve a better representation of exploitation impacts on ICSE networks, (iii) a quantitative human-factor security (capability and vulnerability) evaluation model based on human-agent security knowledge and skills, used to identify the most vulnerable human elements, identify the least security aspects of the general workforce, and prioritise security enhancement efforts, and (iv) security risk reduction through critical impact point assessment (S2R-CIPA) process model that demonstrates the combination of technical and human-factor security evaluations to mitigate risks and achieve ICSE-wide security enhancements. The approaches or models of cyber-attack feasibility testing, adaptive security metrication, multi-attribute impact analysis, and workforce security capability evaluations can support security auditors, analysts, managers, and system owners of ICSs to create security strategies and improve cyber incidence response, and thus effectively reduce security risk.PhD in Manufacturin

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

Assessing for the volatility of the Saudi, Dubai and Kuwait stock markets: time series analysis (2005-2016)

The Kuwait, UAE and Saudi stock markets, alongside five specific firms from the latter, provided the indicator data for analysing market volatility. Autoregressive integrated moving average (ARIMA), Bayesian and Akaike analysis, Ljung-Box Q test, Partial autocorrelation function (PAC) and autocorrelation were the unit root tests applied, alongside matrix error, in this quantitative research. The study aims were to: assess weak-natured efficiency; contrast stock markets’ efficiency; explore market efficiency changes as time progresses. Statistics regarding matrices errors enabled variables influencing market efficiency to be established. Agreement on market efficiency has not been reached by researchers, with one shortcoming of EMH being lack of acknowledgement that an explored time frame may be characterised by varying efficiency levels. Consequently, the EMH and financial conduct have been subject to historiography, yet the connection between EMH and the financial behaviour model has not been the focus of studies using historical data. Accordingly, this research shortcoming tackled through this study, with the company-linked variables influencing stock market efficiency being identified through a literature review. Further, this study prospects identified, with the ongoing development of market efficiency and acceptance of inefficiency and efficiency’s simultaneous presence being the outcome. Finally, liberalisation, financial crises and reform in the Middle East and North Africa (MENA) region is a focus lacking in the extant research, with this study offering a further contribution in this regard. The study reveals that, with five companies and all countries characterised by market inefficiencies, which also changed as time progressed. Foremost efficiency characterised DSM, with SSM second, based on contrasting the obtained data’s random walk. The overall index had less efficiency than the specific firms. Concerning variables, SSM mark efficiency was not enhanced via crises or liberalisation, although it was by reform. Further, the research explains the results’ implications