CEEC CoE

Calibration of Analytical Suction Bucket Installation Models Using Grain-Scale LBM-DEM Simulations
2026-06-11 08:10 - 08:30 (Asia/Tokyo)
If you’re at the 45th International Conference on Ocean, Offshore & Arctic Engineering (OMAE2026) in Tokyo this June, don’t miss the presentation from our own Samual Kemmler on “Calibration of Analytical Suction Bucket Installation Models Using Grain-Scale LBM-DEM Simulations.”
Suction bucket foundations offer significant advantages for offshore wind applications, enabling fast and cost-efficient installation. However, installation failures due to piping erosion remain a critical challenge, particularly in loose or highly permeable seabeds. Understanding the interplay between seepage flow, soil properties, and foundation geometry during suction installation is essential for improving design guidelines and installation strategies.
In this contribution, fully-resolved numerical simulations are provided, that allow a detailed, grain-scale view of the suction installation process. A coupled Lattice Boltzmann-Discrete Element Method (LBM-DEM) framework is employed, in which fluid flow is resolved at a scale significantly finer than the particle size. This allows to capture pore-scale flow effects, particle rearrangements, and evolving soil resistance during installation, offering a higher level of detail compared to unresolved or continuum methods.
The modeling approach is used to explore how soil characteristics and installation parameters influence the development of piping erosion and the resulting installation performance. By systematically varying key parameters, conditions are identified that promote either stable penetration or the onset of piping erosion, highlighting the critical role of seepage near the skirt tip. Beyond identifying failure envelopes, the simulations provide micromechanical insight into how local forces, flow paths, and soil resistance evolve as erosion initiates and progresses. These insights enable the critical examination of common assumptions regarding resistance distribution inside and outside the bucket during suction-driven installation.
Additionally, the fully resolved simulation data can serve as a reference for calibrating and improving continuum-based models, bridging the gap between particle-scale mechanisms and engineering-scale predictive tools. The results illustrate how fully resolved LBM-DEM modeling can complement experimental and field studies, providing a powerful tool for developing more robust suction bucket installation strategies in challenging seabed conditions.

Mixed-Precision and Energy-Efficiency in SEM Codes
2026-06-24 15:45 - 17:15 (Europe/Paris) | Congress Center Hamburg, Congressplatz 1, Hamburg, 20355, Germany
If you’re going to be at ISC26 in Hamburg this year, take a break and visit our own Yanxiang Chen and his poster “Poster: Mixed-Precision and Energy-Efficiency in SEM Codes.”
Mixed-precision computing has emerged as a key strategy to improve performance and energy efficiency on current and future high-performance computing (HPC) systems. However, integrating mixed-precision into large, production-level scientific applications remains challenging due to concerns about numerical stability, accuracy, and the complexity of identifying which computations can safely tolerate reduced precision. In this work, we propose a systematic and practical methodology for enabling mixed-precision in spectral element codes by combining insights from computer arithmetic tools, performance modeling, and targeted algorithmic analysis.
Our approach leverages three complementary components: first, computer arithmetic tools, such as Verificarlo, to instrument and analyze floating-point behavior throughout an application; second, a roofline performance model to quantify the potential computational benefits of lower-precision arithmetic; and third, precision-aware numerical techniques to mitigate or eliminate instabilities introduced when reducing precision in critical algorithmic kernels. Together, these elements form a repeatable framework that guides developers in deciding where and how to apply mixed precision without compromising scientific correctness.
To demonstrate the effectiveness of our methodology, we apply it to two representative spectral element codes widely used in computational fluid dynamics (CFD): Nekbone and Neko. Nekbone is a mini-application proxy for the spectral element CFD code Nek5000, while Neko is a modern spectral element code used for solving incompressible Navier–Stokes equations. For each code, we perform a detailed precision analysis, identify precision-sensitive and precision-robust regions, and design mixed-precision variants accordingly.
In the Nekbone case study, our analysis reveals that mixed precision can significantly accelerate the Conjugate Gradient (CG) solver without adversely affecting convergence or solution quality. We address stagnation phenomena often observed in reduced-precision CG by integrating arithmetic verification with adaptive precision controls, effectively preserving numerical stability. When executed on the MareNostrum 5 supercomputer, the mixed-precision Nekbone achieves a 1.62x speedup in time-to-solution and a 2.43x reduction in energy-to-solution relative to the double-precision baseline, demonstrating substantial gains in both performance and energy efficiency.
For the full Neko application, we extend our precision strategy to a broader set of computational kernels, leveraging the insights gained from Nekbone and applying them within the context of the momentum solver in the Navier-Stokes equation on the Poisson example. The mixed-precision Neko implementation attains up to ~1.3x improvement in both execution time and energy consumption compared to the double-precision version, while maintaining the solution accuracy.
These results confirm that mixed-precision approaches, when carefully designed and guided by arithmetic and performance analysis, can yield significant improvements on HPC platforms for real-world scientific applications. Our methodology provides a general blueprint for HPC developers to adopt mixed precision in other spectral element and iterative methods, ultimately contributing to more efficient utilization of future exascale systems.
