Towards an algorithmic synthesis of thermofluid systems
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Towards an algorithmic synthesis of thermofluid systems Jonas B. Weber1 · Michael Hartisch1 · Alexander D. Herbst1 · Ulf Lorenz1 Received: 21 October 2019 / Revised: 9 September 2020 / Accepted: 9 September 2020 © The Author(s) 2020
Abstract Individual technical components are usually well optimized. However, the design process of entire technical systems, especially in its early stages, is still dominated by human intuition and the practical experience of engineers. In this context, our vision is the widespread availability of software tools to support the human-driven design process with the help of modern mathematical methods. As a contribution to this, we consider a selected class of technical systems, so-called thermofluid systems. From a technical point of view, these systems comprise fluid distribution as well as superimposed heat transfer. Based on models for simple fluid systems as extensively studied in literature, we develop model extensions and algorithmic methods directed towards the optimized synthesis of thermofluid systems to a practical extent. Concerning fluid systems, we propose a Branch-and-Bound framework, exploiting problem-specific characteristics. This framework is then further analyzed using the application example of booster stations for high-rise buildings. In addition, we demonstrate the application of Quantified Programs to meet possible resilience requirements with respect to the systems generated. In order to model basic thermofluid systems, we extend the existing formulation for fluid systems by including heat transfer. Since this consideration alone is not able to deal with dynamic system behavior, we face this challenge separately by providing a more sophisticated representation dealing with the temporal couplings that result from storage components. For the considered case, we further show the advantages of this special continuoustime representation compared to the more common representation using discrete time intervals. Keywords Engineering software tool · System synthesis problem · Thermofluid system · Mixed-integer linear programming · Resilience
* Jonas B. Weber jonas.weber@uni‑siegen.de Extended author information available on the last page of the article
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1 Introduction In light of the European Union’s (EU) greenhouse gas emission reduction goal and its commitment under the climate agreement reached at the COP21 climate conference in Paris, the heating and cooling sector holds great potential for achieving these objectives. According to a report prepared by the Executive Agency for Small and Medium-Sized Enterprises (2016), heating and cooling accounted the EU’s biggest energy use with 50% of final energy consumption in 2012, which corresponds to 546 Mtoe1 and it is expected to remain that way. In this regard, the ‘EU Heating and Cooling Strategy’ announced by the European Commission points out that demand reduction and the deployment of renewable energy and other sustainable sources can reduce fossil fuel import and guarante
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