Nonlinear Wave Evolution in Interaction With Currents and Viscoleastic Muds

A numerical model is extended to investigate the nonlinear dynamics of surface wave propagation over mud in the presence of currents. A phase-resolving frequency-domain model for wave-current interaction is improved to account for wave modulations due to viscoelastic mud of arbitrary thickness. The model compares well with published laboratory data and performs slightly better than the model with viscous mud-induced wave damping mechanism. Monochromatic and random wave simulations are conducted to examine the combined effect of currents, mud-induced wave dissipation and modulation, and nonlinear wave-wave interactions on surface wave spectra. Results indicate that current effects on wave damping over viscoelastic mud is not as straightforward as that over viscous mud. For example, while opposing currents consistently increase damping of random waves over viscous mud, they can decrease damping over viscoelastic mud due to high variations in frequency-dependent damping stemming from mud’s elasticity. It is shown that a model that assumes the mud layer to be thin for simplification can overestimate wave damping over thick mud layers

Towards an Uncertainty-Aware Adaptive Decision Engine for Self-Protecting Software: an POMDP-based Approach

The threats posed by evolving cyberattacks have led to increased research related to software systems that can self-protect. One topic in this domain is Moving Target Defense (MTD), which changes software characteristics in the protected system to make it harder for attackers to exploit vulnerabilities. However, MTD implementation and deployment are often impacted by run-time uncertainties, and existing MTD decision-making solutions have neglected uncertainty in model parameters and lack self-adaptation. This paper aims to address this gap by proposing an approach for an uncertainty-aware and self-adaptive MTD decision engine based on Partially Observable Markov Decision Process and Bayesian Learning techniques. The proposed approach considers uncertainty in both state and model parameters; thus, it has the potential to better capture environmental variability and improve defense strategies. A preliminary study is presented to highlight the potential effectiveness and challenges of the proposed approach

Book Review: Radiology in Global Health

This book review examines Mollura and Lungren’s (eds.) Radiology in Global Health: Strategies, Implementation, and Applications (2014). The contributors have attempted to investigate root causes for radiological service-related disparity that exists between prosperous economies and low- and middle-income countries. The book is clearly geared towards manufacturing consent among stakeholders through research-based evidence to amplify the role of radiology in global healthcare through initiation, implementation, amelioration, and developing sustainable solutions for rollout of essential diagnostic/therapeutic radiology services at population levels. This includes reducing access gaps for radiology/imaging services within industrialized countries as well

Modeling the Impacts of Sea Level Rise on Storm Surge Inundation in Flood-Prone Urban Areas of Hampton Roads, Virginia

Hampton Roads is a populated area in the United States Mid-Atlantic region that is highly affected by sea level rise (SLR). The transportation infrastructure in the region is increasingly disrupted by storm surge and even minor flooding events. The purpose of this study is to improve our understanding of SLR impacts on storm surge flooding in the region. We develop a hydrodynamic model to study the vulnerability of several critical flood-prone neighborhoods to storm surge flooding under several SLR projections. The hydrodynamic model is validated for tide prediction, and its performance in storm surge simulation is validated with the water level data from Hurricane Irene (2011). The developed model is then applied to three urban flooding hotspots located in Norfolk, Chesapeake, and the Isle of Wight. The extent, intensity, and duration of storm surge inundation under different SLR scenarios are estimated. Furthermore, the difference between the extent of flooding as predicted by the hydrodynamic model and the “bathtub” approach is highlighted

Characterizing Seagrass Effects on Hydrodynamics of Waves and Currents Through Field Measurements and Computational Modelling

Low-lying coastal and estuarine areas are among the most populated regions globally, have high economic significance, and are increasingly threatened by climate change, sea level rise, nuisance flooding, and extreme storms. Nature-based coastal protections are sustainable and sea-level resilient alternatives compared to traditional solutions such as dikes and seawalls. Submerged aquatic vegetation (SAV) or seagrasses can provide coastal flood and erosion protection by attenuating storm wave and current energy and stabilizing seabed sediments. However, more research is needed to understand the interactions between flow, SAVs, and sediments. These dynamic interactions affect flow at different scales and seagrass productivity. In this study, we present field measurements of current and wave evolution over a seagrass meadow in South Bay, Virginia. The high vertical resolution measurements show how currents change from above-canopy to in-canopy waters. Wave measurements indicate the dissipation and frequency modulation over the canopy. The results are compared with hydrodynamic simulations using a two-way coupled flow-vegetation interaction model that simulates nonlinear current and wave evolution as well as dynamics of highly flexible vegetation