The integrity of the containment will be challenged during a severe accident due to pressurization caused by the accumulation of steam and other gases and possible ignition of hydrogen and carbon monoxide. Installation of a passive filtered venting system and passive autocatalytic recombiners allows control of the pressure, radioactive releases, and concentration of flammable gases. Thermal hydraulic analysis of the containment equipped with dedicated passive safety systems after a hypothetical station blackout event is performed for a two-loop pressurized water reactor NPP with three integral severe accident codes: ASTEC, MELCOR, and MAAP. MELCOR and MAAP are two major US codes for severe accident analyses, and the ASTEC code is the European code, joint property of Institut de Radioprotection et de Sûreté Nucléaire (IRSN, France) and Gesellschaft für Anlagen und Reaktorsicherheit (GRS, Germany). Codes’ overall characteristics, physics models, and the analysis results are compared herein. Despite considerable differences between the codes’ modelling features, the general trends of the NPP behaviour are found to be similar, although discrepancies related to simulation of the processes in the containment cavity are also observed and discussed in the paper.

Making cities smart represents a major potential for sustainable development, where both the quality of life and the economy improve. Implementing new and efficient solutions in a smart city involves a large spectrum of uncertainties related to the size and project complexity. Characterization and assessment of the variables uncertainty in planning methodology seem necessary to reach the best decision about the best approach to achieve favorable realization outcomes for planned projects. By including uncertainties in the planning, assessment makes it possible to calculate result uncertainties for all expectations, and project cost-effectiveness. In this way, planning can be improved, if the most important parameters of result uncertainties are identified, better defined, and controlled. This study describes a parameter uncertainty characterization methodology applied on the cost-benefit analysis of smart city development with a case study, focused on smart metering infrastructure. Parameter uncertainty characterization is performed based on its variable nature (epistemic and aleatory), time-dependency, and the available information. Cost-benefit analysis results are given as both point value and as uncertainties. Uncertainty is considered for 25 variables of investment and operating costs, and benefits estimation. The presented methodology in smart city planning provides a way to better identify the critical parameters for achieving the defined objectives.