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The new reactor concepts proposed in the Generation IV International Forum require the development and validation of computational tools able to assess their safety performance. In the first part of this paper the models of the ESFR design developed by several organisations in the framework of the CP-ESFR project were presented and their reliability validated via a benchmarking exercise. This second part of the paper includes the application of those tools for the analysis of design basis accident (DBC) scenarios of the reference design. Further, this paper also introduces the main features of the core optimisation process carried out within the project with the objective to enhance the core safety performance through the reduction of the positive coolant density reactivity effect. The influence of this optimised core design on the reactor safety performance during the previously analysed transients is also discussed. The conclusion provides an overview of the work performed by the partners involved in the project towards the development and enhancement of computational tools specifically tailored to the evaluation of the safety performance of the Generation IV innovative nuclear reactor designs. [ABSTRACT FROM AUTHOR]

Background Agri-food is one of the most important sectors of the industry in Europe and potentially a major contributor to the global warming. Sustainability issues in this context pose a huge challenge for several reasons: the variety of considered scales, the number of disciplines involved, the uncertainties, the out-of-equilibrium states, the complex quantitative and qualitative factors, the normative issues and the availability of data. Although important insight and breakthroughs have been attained in different scientific domains, an overarching and integrated analysis of these complex problems have yet to be realized. Scope and Approach This context creates huge opportunities for research in interaction with mathematical programming, integrative models and decision-support tools. The paper propose a computational viewpoint including questions of holistic approach, multiscale reconstruction and optimization. Some directions are discussed. Key Findings and Conclusions Several research questions based on a mathematical programming framework are emerging: how can such a framework manage uncertainty, cope with complex qualitative and quantitative information essential for social and environmental considerations, encompass diverse scales in space and time, cope with a multivariable dynamic environment and with scarcity of data. Moreover, how can it deal with different perspectives, types of models, research goals and data produced by conceptually disjoint scientific disciplines, ranging from physics and physiology to sociology and ethics? Building models is essential, but highly difficult; it will need a strong iterative interaction combining computational intensive methods, formal reasoning and the experts of the different fields. Some future research directions are proposed, involving all those dimensions: mathematical resilience, human-machine interactive learning and optimization techniques. [ABSTRACT FROM AUTHOR]

Numerous Life Cycle Analysis of bread pointed out that wheat production and transportation have important impacts on the environment. But wheat is grown all around the world and it is not always consumed where it is produced. In this paper an analysis of the wheat movements around Europe is done, taking special attention on the Spanish situation. An optimization of wheat exchanges is done eliminating the import–export overlapping. This optimization entails a reduction of the number of trips by 34% and the CO 2 emissions reduction due to transportation is calculated to be 121.175 tones. Consequently less trips, fewer trucks, less traffic and lower emissions that brings economic, social and environmental benefits. [ABSTRACT FROM AUTHOR]

Involving residential actors in the energy transition is crucial for its success. Local energy generation, consumption and trading are identified as desirable forms of involvement, especially in energy communities. The potentials for energy communities in the residential building stock are high but are largely untapped in multi-family buildings. In many countries, rapidly evolving legal frameworks aim at overcoming related barriers, e.g. ownership structures, principal–agent problems and system complexity. But academic literature is scarce regarding the techno-economic and environmental implications of such complex frameworks. This paper develops a mixed-integer linear program (MILP) optimisation model for assessing the implementation of multi-energy systems in an energy community in multi-family buildings with a special distinction between investor and user; the model is applied to the German Tenant Electricity Law. Based on hourly demands from appliances, heating and electric vehicles, the optimal energy system layout and dispatch are determined. The results contain a rich set of performance indicators that demonstrate how the legal framework affects the technologies' interdependencies and economic viability of energy communities with multi-energy systems. Certain economic technology combinations may fail to support national emissions mitigation goals and lead to lock-ins in Europe's largest residential building stock. The subsidies do not lead to the utilisation of a battery storage. Despite this, self-sufficiency ratios of more than 90% are observable for systems with combined heat and power plants and heat pumps. Social C O 2 mitigation costs range between 147.5–272.8 € / t CO 2 . Finally, the results show the strong influence of the heat demand on the system layout. • System optimisation of distinct operators and consumers in multi-family buildings. • Inclusion of Tenant Electricity Law leads to complex investment and dispatch decisions. • Highest profitability combining photovoltaic, combined heat and power and heat pump. • Combined heat and power is favoured, but profits depend on building's heating demand. • Legislation incentivises energy communities but may offset national CO 2 mitigation. [ABSTRACT FROM AUTHOR]

In Europe, most of the district heat is produced from fossil energy sources such as coal or natural gas. Together with the intention to divert municipal waste from landfill, which is still the main way of treatment in approximately half of the EU countries, there is a potential for the construction of waste-to-energy plants (WtEP) that can partially replace fossil fuels. An important factor in planning the construction of new WtE plants is the assessment of the project's economy. However, the ecological aspect of the project, namely the greenhouse-gas (GHG) savings, is becoming a topic of discussion nowadays. In terms of GHG savings, WtE plant integration into an existing district heating system (DHS) has a positive impact, but its level is often only roughly estimated. The paper presents a comprehensive mathematical optimization tool working on a daily time interval that is able to evaluate the impact of changing current technology or WtE plant construction on global warming potential. The technical parameters such as boiler output range, energy efficiency, etc. are considered. The tool also allows to put in the context the GHG savings and economic benefits of the project. These two factors are very difficult to compare. The study answers the question of how to deal with this issue and presents the possibility of comparison, which is generally transferable to any two parameters. Due to two poorly comparable criteria, the result does not include a single optimal solution, but clearly illustrates the view of the overall issue and gives a good basis for the final decision. The method used are illustrated in real-world DHS with various parameters where the relationship between GHG savings and the economic benefits of the integration of a WtE plant is evaluated. The whole problem is the task of linear integer programming and is implemented in the GAMS programming environment. • A multi-criteria optimization tool for WtE plant integration is introduced. • Economic and environmental aspects are put into context. • The optimal capacity is determined depending on the emphasis on both aspects. • The cost of removing a tonne of CO 2 by WtE in a particular location is calculated. [ABSTRACT FROM AUTHOR]