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Artificial intelligence and machine learning are revolutionising fields of science and engineering. In recent years, process engineering has widely benefited from this novel modelling and optimisation approach. The open literature can offer several examples of their applications to chemical engineering problems. Increasing investments are devoted to these techniques from different industrial areas, but insufficient information on a structured course covering these topics in a chemical engineering curriculum could be found. The course in this paper intends to reduce this gap. We introduce one of the first courses on artificial intelligence applications in a chemical engineering curriculum. The course targets Master's students with a chemical engineering background and insufficient knowledge of statistical approaches. It covers the main aspects by utilising frontal lectures and hands-on exercises with active learning methods. This paper shows the methodology we adapted to introduce students to machine learning techniques and how they responded to each class. The student performances for each test are shown, as well as the survey results based on student feedback and suggestions. This work contains essential guidelines for educators who will provide an artificial intelligence course in a chemical engineering curriculum. • An AI course for chemical engineers is given as one of the first attempts in Europe. • The course is structured into frontal and hands-on lessons. • Modelling and optimisation techniques via AI were shown to the students. • Applications of developed models were explained to the students. • Students can apply basic AI in chemical engineering tasks after this course. [ABSTRACT FROM AUTHOR]

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]

Abstract: Background: Vascular support structures are important devices for treating valve stenosis. Large population of patients are treated for valvular disease and the principal mode of treatment is the use of percutaneous valvuloplasty. Stent devices are proving to be an improved technology in minimal invasive cardiac surgery. This technology now accounts for 20% of treatments in Europe. This new technology provides highly effective results at minimal cost and short duration of hospitalization. Methods: This paper discusses the design and finite element analysis (FEA) of a percutaneous aortic valve stent. The stent design was modeled and subjected to FEA. The improved model design was carried out to meet the functional and surgical requirements. Analysis was done with different materials with loads ranging from 50 to 73 kgf/mm2. These forces were selected because these values are far greater than the normal human blood pressure which ranges from 10 to 16 kPa. It was also to understand the mechanical behavior of different stent materials under such high pressures. Results: A stent model was generated and its physical, mechanical, and behavioral properties were studied. Finite element analysis and simulation of the model help the designer to optimize the geometry suitable for performance during and after implantation. The design objective for the stent is to have long-term durability, low thrombogenicity, and resistance to migration and paravalvular leak. Conclusion: The analysis performed in this paper may aid in understanding the stent''s tolerable pressure ranges in comparison with the physiological pressures exerted by the heart and cardiac blood flow during abnormal cardiovascular conditions. It may also help in finding the material that will best suit the stent. [Copyright &y& Elsevier]

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]

Abstract: Hydrogen has a wide range of applications. In view of the environmental benefits, hydrogen can be produced by decarbonized means. When alkaline electrolysis is the selected process, extra value is offered by flexible operation that could bring both; an opportunity to reduce the cost of hydrogen produced (by consuming electricity during off-peak hours, and stopping the process during peak hours) and also a complementary tool to help balancing of the electric system. This paper assesses the profitability of market-driven operation for three different markets: France, Germany and Spain, with an analysis on the spot market. The market that exhibits the biggest potential in terms of profitability thanks to flexible operation is the French one, for each studied year. France is also the country that has the smallest installed renewable capacity amongst three considered countries. The gain on the hydrogen production cost allowed by the optimization is less than 3%. Hence, market-driven operation does not seem highly favourable to valorize fluctuating hydrogen production, when only the market price opportunities are considered. The balancing tool provided by the electrolysis system needs to be specifically valorized, in order to make flexible operation profitable. [Copyright &y& Elsevier]

Abstract: In the course of discussing different target types for their suitability in the European Spallation Source (ESS) one main focus was on neutronics'' performance. Diverse concepts have been assessed baselining some preliminary engineering and geometrical details and including some optimization. With the restrictions and resulting uncertainty imposed by the lack of detailed designs optimizations at the time of compiling this paper, the conclusion drawn is basically that there is a little difference in the neutronic yield of the investigated targets. Other criteria like safety, environmental compatibility, reliability and cost will thus dominate the choice of an ESS target. [Copyright &y& Elsevier]

Abstract: In transmission and distribution systems, the high number of installed transformers, a loss source in networks, suggests a good potential for energy savings. This paper presents how the Spanish Distribution regulation policy, Royal Decree 222/2008, affects the overall energy efficiency in distribution transformers. The objective of a utility is the maximization of the benefit, and in case of failures, to install a chosen transformer in order to maximize the profit. Here, a novel method to optimize energy efficiency, considering the constraints set by the Spanish Distribution regulation policy, is presented; its aim is to achieve the objectives of the utility when installing new transformers. The overall energy efficiency increase is a clear result that can help in meeting the requirements of European environmental plans, such as the ‘20–20–20’ action plan. [ABSTRACT FROM AUTHOR]

Abstract: In many European countries, municipalities offer their inhabitants a wide variety of social services. In this paper we will focus on efficiently scheduling home care, transportation of the elderly, and home meal delivery. These so-called municipal or communal routing problems can be modeled as different variants of the vehicle routing problem, a well-known optimization problem from the literature. We present a focused literature review and report on case studies using Finnish data. The computational results show that there is a significant potential for cost savings for all applications considered. [Copyright &y& Elsevier]

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]