Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data

Analysis of compressible turbulent flows is essential for applications related to propulsion, energy generation, and the environment. Here, we present BLASTNet 2.0, a 2.2 TB network-of-datasets containing 744 full-domain samples from 34 high-fidelity direct numerical simulations, which addresses the current limited availability of 3D high-fidelity reacting and non-reacting compressible turbulent flow simulation data. With this data, we benchmark a total of 49 variations of five deep learning approaches for 3D super-resolution - which can be applied for improving scientific imaging, simulations, turbulence models, as well as in computer vision applications. We perform neural scaling analysis on these models to examine the performance of different machine learning (ML) approaches, including two scientific ML techniques. We demonstrate that (i) predictive performance can scale with model size and cost, (ii) architecture matters significantly, especially for smaller models, and (iii) the benefits of physics-based losses can persist with increasing model size. The outcomes of this benchmark study are anticipated to offer insights that can aid the design of 3D super-resolution models, especially for turbulence models, while this data is expected to foster ML methods for a broad range of flow physics applications. This data is publicly available with download links and browsing tools consolidated at https://blastnet.github.io.Comment: Accepted in Advances in Neural Information Processing Systems 36 (NeurIPS 2023). 55 pages, 21 figures. v2: Corrected co-author name. Keywords: Super-resolution, 3D, Neural Scaling, Physics-informed Loss, Computational Fluid Dynamics, Partial Differential Equations, Turbulent Reacting Flows, Direct Numerical Simulation, Fluid Mechanics, Combustio

Simulation of the marine environment using bioreactor for investigation of 2507 duplex stainless steel corrosion in the presence of marine isolated Bacillus Vietnamensis bacterium

The effect of marine B. vietnamensis, isolated from East Sea, China, on the corrosion behavior of SAF 2507 duplex stainless steel (DSS) was studied. A flat plate bioreactor was used to simulate the marine environment. And the environmental parameters such as temperature, pH, flow rate and oxygen content were controlled in bioreactor which operated aerobically for 30 days with either inoculated or sterile artificial seawater. Electrochemical studies demonstrated a noticeable decrease in open circuit potential and an increase in current density in solutions containing B. vietnamensis compared to the sterile artificial seawater which confirmed the enhancement of corrosion rate of 2507 DSS in the presence of bacterium. FESEM images showed the presence of porous and heterogeneous biofllm and oxide layer on the 2507 DSS surface in the presence of bacterium. The heterogeneity of biofllm and different thicknesses of biofllm made the oxygen concentration cells on the 2507 DSS surface and induced localized corrosion at longer exposure times. The biofllm composition also identified by FTIR. (C) 2018 Elsevier B.V. All rights reserved