A Vortex Damping Outflow Forcing for Multiphase Flows with Sharp Interfacial Jumps

Outflow boundaries play an important role in multiphase fluid dynamics simulations involving low Weber numbers and large jump in physical variables. Inadequate treatment of these jumps at outflow generates undesirable fluid disturbances within the computational domain. We introduce a forcing term for incompressible Navier-Stokes equations that is coupled with a fixed pressure outflow boundary condition to enable stable exit of these disturbances from the domain boundary. The forcing term acts as a damping mechanism to control vortices that are generated by droplets/bubbles in multiphase flows, and is designed to be a general formulation that can be applied to a variety of fluid-flow simulations involving phase transition and sharp interfacial jumps. Validation cases are provided to demonstrate applicability of this formulation to pool and flow boiling problems, where bubble induced vortices during evaporation and condensation can lead to instabilities at outflow boundaries that eventually propagate downstream to corrupt numerical solution. Computational experiments are performed using \flashx, which is a composable open-source software instrument designed for multiscale fluid dynamics simulations on heterogenous architectures.Comment: Preprint Submitted to Journal of Computational Physic

BubbleML: A Multi-Physics Dataset and Benchmarks for Machine Learning

In the field of phase change phenomena, the lack of accessible and diverse datasets suitable for machine learning (ML) training poses a significant challenge. Existing experimental datasets are often restricted, with limited availability and sparse ground truth data, impeding our understanding of this complex multiphysics phenomena. To bridge this gap, we present the BubbleML Dataset \footnote{\label{git_dataset}\url{https://github.com/HPCForge/BubbleML}} which leverages physics-driven simulations to provide accurate ground truth information for various boiling scenarios, encompassing nucleate pool boiling, flow boiling, and sub-cooled boiling. This extensive dataset covers a wide range of parameters, including varying gravity conditions, flow rates, sub-cooling levels, and wall superheat, comprising 79 simulations. BubbleML is validated against experimental observations and trends, establishing it as an invaluable resource for ML research. Furthermore, we showcase its potential to facilitate exploration of diverse downstream tasks by introducing two benchmarks: (a) optical flow analysis to capture bubble dynamics, and (b) operator networks for learning temperature dynamics. The BubbleML dataset and its benchmarks serve as a catalyst for advancements in ML-driven research on multiphysics phase change phenomena, enabling the development and comparison of state-of-the-art techniques and models.Comment: Submitted to Neurips Datasets and Benchmarks Track 202

A Multiphase Solver for High-Fidelity Phase-Change Simulations over Complex Geometries

Complex interactions between solid, liquid and gas occur in many practical engineering applications, and are often difficult to quantify experimentally. A few examples include boiling over solid heaters, solidification melt-dynamics in metal casting, and convective cooling of electronic components. With the availability of scalable computational tools, high-fidelity simulations can provide new insight into these phenomena and answer open questions. In the present work, a multiphase solver is presented which can simulate problems involving phase transition over complex geometries. The dynamics of liquid-gas interface are modeled using a level-set technique, which utilizes Ghost Fluid Method (GFM) to account for sharp jump in pressure, velocity, and temperature across the multiphase boundary. The fluid-solid interactions are modeled using an Immersed Boundary Method (IBM) which uses a Moving Least Squared (MLS) reconstruction to calculate fluid-flow around the solid, along with an additional GFM forcing to model its effect on pressure, temperature and Conjugate Heat Transfer (CHT). The resulting three dimensional solver is fully explicit in time and uses a fractional step method for Navier-Stokes, energy, and mass transfer equations. Validation and verification cases are presented to demonstrate the accuracy of the solver in comparison to experimental and analytical problems, and results of high fidelity pool boiling simulations in varying gravity environments are discussed in detail

Eligibility for low-dose rivaroxaban based on the COMPASS trial: Insights from the veterans affairs healthcare system

Introduction: Low-dose rivaroxaban reduced major adverse cardiac and limb events among patients with stable atherosclerotic vascular disease (ASCVD) in the COMPASS trial. The objective of our study was to evaluate the eligibility and budgetary impact of the COMPASS trial in a real-world population.Methods: The VA administrative and clinical databases were utilized to conduct a cross-sectional study to identify patients eligible for low-dose rivaroxaban receiving care at all 141 facilities between October 1, 2014 and September 30, 2015. Proportion of patients with stable ASCVD eligible for low-dose rivaroxaban and prevalence of multiple risk enrichment criteria among eligible patients. Pharmaceutical budgetary impact using VA pharmacy pricing. Chi-squared and Student\u27s t tests were used to compare patients eligible versus ineligible patients.Results: From an initial cohort of 1,248,214 patients with ASCVD, 488,495 patients (39.1%) met trial eligibility criteria. Eligible patients were older (74.2 vs 64.5 years) with higher proportion of hypertension (84.1% vs 82.1%) and diabetes (46.2% vs 32.9) compared with ineligible patients (p \u3c 0.001 for all comparisons). A median of 38.7% (IQR 4.6%) of total ASCVD patients per facility were rivaroxaban eligible. Estimated annual VA pharmacy budgetary impact would range from $0.47 billion to$1.88 billion for 25% to 100% treatment penetration. Annual facility level pharmaceutical budgetary impact would be a median of $12.3 million (IQR$8.0-$16.3 million) for treatment of all eligible patients. Among eligible patients, age greater than 65 years was the most common risk enrichment factor (86.9%). Prevalence of eligible patients with multiple enrichment factors varied from 34.2% (one factor) to 6.2% (four or more).Conclusion: Over one third of patients with stable ASCVD may qualify for low-dose rivaroxaban within the VA. Additional studies are needed to understand eligibility in other populations and a formal cost-effectiveness analysis is warranted

Potential impact of the 2019 ACC/AHA guidelines on the primary prevention of cardiovascular disease recommendations on the inappropriate routine use of aspirin and aspirin use without a recommended indication for primary prevention of cardiovascular disease in cardiology practices: Insights from the NCDR pinnacle registry

Background: Aspirin is recommended in patients with atherosclerotic cardiovascular disease for secondary prevention. In patients without atherosclerotic cardiovascular disease and not at high 10-year risk, there is no evidence aspirin reduces adverse cardiovascular events and it could increase bleeding. The 2019 American College of Cardiology/American Heart Association Guidelines on Primary Prevention of Cardiovascular Disease state that aspirin may be considered for primary prevention (class IIb) in patients 40 to 70 years that are at higher risk of atherosclerotic cardiovascular disease and that routine use of aspirin should be avoided (class III:Harm) for patients \u3e70 years. We examined the frequency of patients on aspirin for primary prevention that would have been considered unindicated or potentially harmful per the recent guideline where aspirin discontinuation may be beneficial.Methods: To assess the potential impact, within the National Cardiovascular Disease Registry Practice Innovation and Clinical Excellence Registry, we assessed 855 366 patients from 400 practices with encounters between January 1, 2018 and March 31, 2019, that were receiving aspirin for primary prevention. We defined inappropriate use as the use of aspirin in patients \u3c40 or \u3e70 years and use without a recommended indication as use of aspirin in patients 40 to 70 years with low, borderline, or intermediate 10-year atherosclerotic cardiovascular disease risk. Frequency of inappropriate use and use without a recommended indication were calculated and practice-level variation was evaluated using the median rate ratio.Results: Inappropriate use occurred in 27.6% (193 674/701 975) and use without a recommended indication in 26.0% (31 810/122 507) with significant practice-level variation in inappropriate use (predicted median practice-level rate 33.5%, interquartile range, 24.1% to 40.8%; median rate ratio, 1.71 [95% CI, 1.67-1.76]).Conclusions: Immediately before the 2019 American College of Cardiology/American Heart Association Guidelines on Primary Prevention of Cardiovascular Disease, over one-fourth of patients in this national registry were receiving aspirin for primary prevention inappropriately or without a recommended indication with significant practice-level variation. These findings help to determine the potential impact of guideline recommendations on contemporary use of aspirin for primary prevention