We propose two enhancements of quasi-Newton methods used to accelerate coupling iterations for partitioned fluid-structure interaction. Quasi-Newton methods have been established as flexible, yet robust, efficient and accurate coupling methods of multi-physics simulations in general. The coupling library preCICE provides several variants, the so-called IQN-ILS method being the most commonly used. It uses input and output differences of the coupled solvers collected in previous iterations and time steps to approximate Newton iterations. To make quasi-Newton methods both applicable for parallel coupling (where these differences contain data from different physical fields) and to provide a robust approach for re-using information, a combination of information filtering and scaling for the different physical fields is typically required. This leads to good convergence, but increases the cost per iteration. We propose two new approaches—pre-scaling weight monitoring and a new, so-called QR3 filter, to substantially improve runtime while not affecting convergence quality. We evaluate these for a variety of fluid-structure interaction examples. Results show that we achieve drastic speedups for the pure quasi-Newton update steps. In the future, we intend to apply the methods also to volume-coupled scenarios, where these gains can be decisive for the feasibility of the coupling approach.
preCICE is a free/open-source coupling library. It enables creating partitioned multi-physics simulations by gluing together separate software packages. This paper summarizes the development efforts in preCICE of the past five years. During this time span, we have turned the software from a working prototype -- sophisticated numerical coupling methods and scalability on ten thousands of compute cores -- to a sustainable and user-friendly software project with a steadily-growing community. Today, we know through forum discussions, conferences, workshops, and publications of more than 100 research groups using preCICE. We cover the fundamentals of the software alongside a performance and accuracy analysis of different data mapping methods. Afterwards, we describe ready-to-use integration with widely-used external simulation software packages, tests, and continuous integration from unit to system level, and community building measures, drawing an overview of the current preCICE ecosystem.
preCICE is a free/open-source coupling library. It enables creating partitioned multi-physics simulations by gluing together separate software packages. This paper summarizes the development efforts in preCICE of the past five years. During this time span, we have turned the software from a working prototype -- sophisticated numerical coupling methods and scalability on ten thousands of compute cores -- to a sustainable and user-friendly software project with a steadily-growing community. Today, we know through forum discussions, conferences, workshops, and publications of more than 100 research groups using preCICE. We cover the fundamentals of the software alongside a performance and accuracy analysis of different data mapping methods. Afterwards, we describe ready-to-use integration with widely-used external simulation software packages, tests, and continuous integration from unit to system level, and community building measures, drawing an overview of the current preCICE ecosystem.
<p>Shallow geothermal energy can contribute to a regenerative supply of urban heating and cooling loads and hence, reduce primary energy consumption and greenhouse gas emissions. In the city of Munich, which hosts a very productive shallow aquifer, conditions are outstanding for the thermal use of groundwater. Therefore, already more than 2800 shallow geothermal systems are installed and due to better economic incentives, numbers are rising. Thus, the future development of this already intensely used urban aquifer holds challenges to avoid conflicting uses, but also opportunities to build synergies and balance the energy budget.</p><p>However, fostering a sustainable development is only possible with knowledge about the dynamic hydraulic and thermal behaviour of the groundwater and its anthropogenic and natural influences. Currently, this information is missing on a city scale as a decision basis for the responsible growth of thermal groundwater use. As a consequence, water authorities have to become increasingly restrictive when granting licenses to cope with preventive drinking water protection. Therefore, tools for the thermal management of aquifers are needed to enable resilient decision making.</p><p>The project GEO.KW (2019-2021), funded by the German Ministry for Economic Affairs and Energy, took up this challenge and develops a flexible management and optimisation tool for the thermal use of groundwater. As pilot area for an implementation, Munich offers a dynamic and well-monitored hydrogeology. The tool&#8217;s core element is the coupling between a thermal-hydraulic groundwater model and a linear optimisation model for distributed energy systems. This interdisciplinary approach, allows us to include the heat storage potential of the aquifer and study the coverable heating and cooling demand depending on the thermal resource at high temporal and spatial resolution. The optimisation integrates all regulatory restrictions of water resource management, like temperature or extraction limits, and comparatively analyses conventional heating and cooling systems alongside with thermal groundwater use. As cost factor in the optimisation, greenhouse gas emissions and economic cost is evaluated.</p><p>The development focuses on using highly parallelised open-source codes and efficient code coupling. The numerical groundwater simulation is performed with <em>PFLOTRAN</em>, a code specifically built for scalability on supercomputers. It is coupled to the linear optimiser <em>urbs </em>through the minimally invasive coupling library <em>preCICE </em>and the simulations are performed on the <em>SuperMUC-NG</em> in Garching, Germany. Since the parallelisation of optimisation problems is not straightforward, a decomposition procedure is introduced to assure performance with high resolution models.</p><p>The optimisation tool and associated methods will also be applicable to other urban areas. Thus, it will offer the decision support for an optimised growth of thermal groundwater use to assure its contribution to emission-free and decarbonised heating and cooling of cities.</p>
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