Wind Input, Surface Dissipation and Directional Properties of Shoaling Waves

A spherical wave measurement buoy capable of detecting breaking waves has been designed and built. The buoy is 16 inches in diameter and houses a 9 degree of freedom inertial measurement unit (IMU). The orientation and acceleration of the buoy is continuously logged at frequencies up to 200 Hz providing a high fidelity description of the motion of the buoy as it is impacted by breaking waves. The buoy was deployed several times throughout the winter of 2013–2014. Both moored and free-drifting data were acquired in near-shore shoaling waves off the coast of Newport, OR. Almost 200 breaking waves of varying type and intensity were measured over the course of multiple deployments. The characteristic signature of spilling and plunging breakers was identified in the IMU data.

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3D B-Rep meshing for real-time data-based geometric parametric analysis

Advanced Modeling and Simulation in Engineering Sciences ◽

10.1186/s40323-021-00194-5 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Tristan Maquart ◽

Thomas Elguedj ◽

Anthony Gravouil ◽

Michel Rochette

Keyword(s):

Real Time ◽

Surface Topology ◽

Time Data ◽

Standard Data ◽

Input Surface ◽

Cad Models ◽

Pants Decomposition ◽

Parametric Studies ◽

Geometry Feature ◽

Complicated Geometry

AbstractThis paper presents an effective framework to automatically construct 3D quadrilateral meshes of complicated geometry and arbitrary topology adapted for parametric studies. The input is a triangulation of the solid 3D model’s boundary provided from B-Rep CAD models or scanned geometry. The triangulated mesh is decomposed into a set of cuboids in two steps: pants decomposition and cuboid decomposition. This workflow includes an integration of a geometry-feature-aware pants-to-cuboids decomposition algorithm. This set of cuboids perfectly replicates the input surface topology. Using aligned global parameterization, patches are re-positioned on the surface in a way to achieve low overall distortion, and alignment to principal curvature directions and sharp features. Based on the cuboid decomposition and global parameterization, a 3D quadrilateral mesh is extracted. For different parametric instances with the same topology but different geometries, the MEG-IsoQuad method allows to have the same representation: isotopological meshes holding the same connectivity where each point on a mesh has an analogous one into all other meshes. Faithful 3D numerical charts of parametric geometries are then built using standard data-based techniques. Geometries are then evaluated in real-time. The efficiency and the robustness of the proposed approach are illustrated through a few parametric examples.

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Modeling Low Intensity Fires: Lessons Learned from 2012 RxCADRE

Atmosphere ◽

10.3390/atmos12020139 ◽

2021 ◽

Vol 12 (2) ◽

pp. 139

Author(s):

Rodman R. Linn ◽

Judith L. Winterkamp ◽

James H. Furman ◽

Brett Williams ◽

J. Kevin Hiers ◽

...

Keyword(s):

Prescribed Fire ◽

Fire Spread ◽

Lessons Learned ◽

Field Sampling ◽

Wind Fields ◽

Low Intensity ◽

Novel Method ◽

Wind Input ◽

Variable Wind ◽

Local Variability

Coupled fire-atmosphere models are increasingly being used to study low-intensity fires, such as those that are used in prescribed fire applications. Thus, the need arises to evaluate these models for their ability to accurately represent fire spread in marginal burning conditions. In this study, wind and fuel data collected during the Prescribed Fire Combustion and Atmospheric Dynamics Research Experiments (RxCADRE) fire campaign were used to generate initial and boundary conditions for coupled fire-atmosphere simulations. We present a novel method to obtain fuels representation at the model grid scale using a combination of imagery, machine learning, and field sampling. Several methods to generate wind input conditions for the model from eight different anemometer measurements are explored. We find a strong sensitivity of fire outcomes to wind inputs. This result highlights the critical need to include variable wind fields as inputs in modeling marginal fire conditions. This work highlights the complexities of comparing physics-based model results against observations, which are more acute in marginal burning conditions, where stronger sensitivities to local variability in wind and fuels drive fire outcomes.

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Shoaling waves simulator

Proceedings of the 1998 ACM symposium on Applied Computing - SAC '98 ◽

10.1145/330560.331017 ◽

1998 ◽

Cited By ~ 1

Author(s):

Suzanne M. Lea ◽

Matthew Lybanon ◽

Peter M. Smith

Keyword(s):

Shoaling Waves

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