Smoothed particle hydrodynamics (SPH) is a mesh-free Lagrangian method for obtaining approximate numerical solutions of the equations of fluid dynamics; which has been widely applied to weakly- and strongly compressible turbulence in astrophysics and engineering applications. We present a learn-able hierarchy of parameterized and "physics-explainable" SPH informed fluid simulators using …

Infrastructure is critical for enabling society to function and the economy to thrive, but there is an increasing mismatch between the need for infrastructure investments and available capital, which is in consequence of constraints on public resources and limited capacity to leverage the private sector co-financing under the current system. …

Spurred by the emerging blockchain technology and increased interest in tokenization, this forecasting research built on extensive literature and aggregated expertise to explore the potential implementation of blockchain-enabled tokenization in infrastructure investment and development. The Delphi-based scenario analysis approach was applied to gather long-term forecasts and assessments of a research …

Turbulent flows are ubiquitous, and obtaining efficient, accurate and generalizable reduced order models remains a challenging problem. This manuscript develops a hierarchy of reduced Lagrangian models for turbulent flows in order to investigate and compare the effects of enforcing Smoothed Particle Hydrodynamics (SPH) structure versus embedding neural networks (NN)s within …