A comprehensive review is conducted on the application of Lagrangian mesh-free methods for simulating flows in various types of porous media, ranging from fixed structures like coastal breakwaters to deformable and transportable media. Deformable porous media refer to soil structures that may deform under the influence of currents and waves, while transportable media involve processes such as sediment transport and scour around hydraulic, coastal, and ocean structures. This review addresses problem dimensionality, governing equations, domain discretization schemes, interaction mechanisms, and applications. The literature analysis reveals that while various numerical techniques have been employed to model the complex interaction between fluid and solid phases, not all methods are physically or mathematically justifiable. However, some approaches have significantly advanced the modeling process over the past two decades. Based on these findings, a modeling framework is proposed to guide the construction of mesh-free models for simulating flow interactions with natural or engineered porous structures. It highlights two effective approaches: (i) Three-dimensional (3D) pore-scale microscopic modeling of flow through large-sized solid particles using coupled smoothed particle hydrodynamics (SPH) and discrete element method (DEM), and (ii) two-dimensional (2D) macroscopic modeling of flow in small-sized porous media using the mixture theory and SPH. The framework highlights the mixture-theory-based methods as particularly effective for large-scale simulations and the advanced SPH-DEM coupling techniques that enable precise simulations of complex fluid–solid interactions. The framework serves as a guide for researchers developing mesh-free numerical models to simulate fluid flows in porous media for hydraulic, coastal, and ocean engineering applications.

The present work concentrates on liquid sloshing in tanks under real seismic excitations with various frequency contents [the ratio of peak ground acceleration (PGA) to peak ground velocity (PGV)] by a finite-difference turbulent model. The turbulence is modeled by the large eddy simulation, and the fluid–structure interaction is resolved by the Virtual Boundary Force method. Thirteen seismic records, covering the low, intermediate and high frequency contents, are adopted to excite nonlinear sloshing waves. Both sloshing wave and hydrodynamic pressure are recorded, and their correlations with the filling level, PGA, PGV and frequency content have been identified. The findings suggest that (1) the sloshing responses are in general positively correlated with the filling level; (2) the sloshing height strongly relates to PGV and frequency content, and the seismic excitation of low frequency and meantime with a larger PGV can trigger more violent sloshing waves than others; and (3) the dynamic pressure along the tank sidewall decreases from the bottom up, which is dominated by PGA at the lower part but the stronger correlation is established with PGV and frequency content at the upper part. Finally, to damp severe sloshing waves, the horizontal, vertical and coupled horizontal and vertical baffles are introduced, and their inhibiting effects are discussed. The present work may guide the design of partially filled storage tanks under seismic excitations.

Regular expression denial of service (ReDoS)— which exploits the super-linear running time of matching regular expressions against carefully crafted inputs—is an emerging class of DoS attacks to web services. One challenging question for a victim web service under ReDoS attacks is how to quickly recover its normal operation after ReDoS attacks, especially these zero-day ones exploiting previously unknown vulnerabilities.In this paper, we present RegexNet, the first payload-based, automated, reactive ReDoS recovery system for web services. RegexNet adopts a learning model, which is updated constantly in a feedback loop during runtime, to classify payloads of upcoming requests including the request contents and database query responses. If detected as a cause leading to ReDoS, RegexNet migrates those requests to a sandbox and isolates their execution for a fast, first-measure recovery.We have implemented a RegexNet prototype and integrated it with HAProxy and Node.js. Evaluation results show that RegexNet is effective in recovering the performance of web services against zero-day ReDoS attacks, responsive on reacting to attacks in sub-minute, and resilient to different ReDoS attack types including adaptive ones that are designed to evade RegexNet on purpose.