Mass-ratio and Magnetic Flux Dependence of Modulated Accretion from Circumbinary Disks

Accreting supermassive binary black holes (SMBBHs) are potential multimessenger sources because they emit both gravitational-wave and electromagnetic (EM) radiation. Past work has shown that their EM output may be periodically modulated by an asymmetric density distribution in the circumbinary disk, often called an “overdensity” or “lump;” this modulation could possibly be used to identify a source as a binary. We explore the sensitivity of the overdensity to SMBBH mass ratio and magnetic flux through the accretion disk. We find that the relative amplitude of the overdensity and its associated EM periodic signal both degrade with diminishing mass ratio, vanishing altogether somewhere between 1:2 and 1:5. Greater magnetization also weakens the lump and any modulation of the light output. We develop a model to describe how lump formation results from internal stress degrading faster in the lump region than it can be rejuvenated through accretion inflow, and predicts a threshold value in specific internal stress below which lump formation should occur and which all our lump-forming simulations satisfy. Thus, detection of such a modulation would provide a constraint on both mass ratio and magnetic flux piercing the accretion flow.

A study on using image-based machine learning methods to develop surrogate models of stamp forming simulations

In design for forming, it is becoming increasingly significant to develop surrogate models of high-fidelity finite element analysis (FEA) simulations of forming processes, to achieve effective component feasibility assessment as well as process and component optimizations. However, surrogate models using traditional scalar-based machine learning methods (SBMLMs) fall short on accuracy and generalizability. This is because SBMLMs fail to harness the location information available from the simulations. To overcome this shortcoming, the theoretical feasibility and practical advantages of innovatively applying image-based machine learning methods (IBMLMs) in developing surrogate models of sheet stamp forming simulations are explored in this study. To demonstrate the advantages of IBMLMs, the effect of the location information on both design variables and simulated physical fields is firstly proposed and analyzed. Based on a sheet steel stamping case study, a Res-SE-U-Net IBMLM surrogate model of stamping simulations is then developed and compared with a baseline multi-layer perceptron (MLP) SBMLM surrogate model. The results show that the IBMLM model is advantageous over the MLP SBMLM model in accuracy, generalizability, robustness, and informativeness. This paper presents a promising methodology in leveraging IBMLMs as surrogate models to make maximum use of information from stamp forming FEA results. Future prospective studies that are inspired by this paper are also discussed.

Potential and challenges of a solid-shell element for the macroscopic forming simulation of engineering textiles

Finite element (FE) forming simulation offers the possibility of a detailed analysis of the deformation behaviour of engineering textiles during forming processes, to predict possible manufacturing effects such as wrinkling or local changes in fibre volume content. The majority of macroscopic simulations are based on conventional two-dimensional shell elements with large aspect ratios to model the membrane and bending behaviour of thin fabrics efficiently. However, a three-dimensional element approach is necessary to account for stresses and strains in thickness direction accurately, which is required for processes with a significant influence of the fabric’s compaction behaviour, e.g. wet compression moulding. Conventional linear 3D-solid elements that would be commercially available for this purpose are rarely suitable for high aspect ratio forming simulations. They are often subjected to several locking phenomena under bending deformation, which leads to a strong dependence of the element formulation on the forming behaviour [1]. Therefore, in the present work a 3D hexahedral solid-shell element, based on the initial work of Schwarze and Reese [2,3], which has shown promising results for the forming of thin isotropic materials [1], is extended for highly anisotropic materials. The advantages of a locking-free element formulation are shown through a comparison to commercially available solid and shell elements in forming simulations of a generic geometry. Additionally, first ideas for an approach of a membrane-bending-decoupling based on a Taylor approximation of the strain are discussed, which is necessary for an accurate description of the deformation behaviour of thin fabrics.