Entries filed under “Visualization”

In this video, NASA uses state-of-the-art visualization to revisit Hurricane Katrina, which struck the Gulf Coast on August 28, 2005. Before and during the hurricane’s landfall, NASA provided data gathered from a series of Earth-observing satellites to help predict Katrina’s path and intensity. In its aftermath, NASA satellites also helped identify areas hardest hit.

Engineers have used Oasys GSA software to analyse the dynamic structure and resolve vibration patterns in order to understand the structural behaviour, and seemingly random variations of quadrangular and polygonal patterns, of a dragonfly wing. First presented at ASME, the International Mechanical Engineering Congress in Colorado, the work by Maria Mingallon, senior structural engineer at Arup, and Sakthivel Ramaswamy, director at KRR Engineering, revealed an intriguing feature, dubbed the nodus.

Acting as both reinforcement and shock absorber to the wing, the nodus copes with combined torsion and bending stress concentrations at the junction of the rigid leading-edge and the more flexible sections of the wing. The researchers concluded that the concentration of stresses and bending moments must have imposed strong selection pressure and that the nodus has evolved to combine a stress-absorbing strip of soft cuticle with strong, three-dimensional cross bars across the entire spar between the costal margin and the leading edge.

Oasys GSA Software’s ability to predict and resolve vibration issues is more commonly used in the design of buildings where the trend to use modern lighter materials creates potential vibration issues which must be resolved at the design stage. It has also recently been applied to the analysis of blast damage to human skeleton in war zones in a prize-winning post-graduate project at Imperial College in the UK.

This story originally appeared on HPC Projects. It appears here as part of a cross-publishing agreement with Scientific Computing World.

A Cleveland Clinic research team is developing computational representations of the human body in order to understand how movement patterns and loads on the joints deform the surrounding tissues and cells. Utilising the computing systems of the Ohio Supercomputer Center in the US, the team hopes the virtual models will someday be used to understand damage mechanisms caused by the aging process or by debilitating diseases, such as osteoarthritis.

Leading the team is Ahmet Erdemir, director of the Computational Biomodeling Core (CoBi) and a faculty member in the Department of Biomedical Engineering at the Lerner Research Institute (LRI) in Cleveland, Ohio. ‘The aging process and debilitating diseases affect many aspects of the mechanical function of the human body, from the way we move to how our muscles, joints, tissues, and cells accommodate the loading exerted on the body during daily activities,’ Erdemir explained. ‘Computational modelling techniques provide an avenue to obtain additional insights about mechanics at various spatial scales.’

While many macro-scale studies have looked at how the various components of a knee joint respond to weight and other external loads, Erdemir and colleague Scott C. Sibole wanted to better understand how those large mechanical forces correspond to the related deformation of individual cartilage cells – or chondrocytes – within the knee. Previous micro-scale studies of cartilage have not commonly been based on data from body-level scales, in particular, by the musculoskeletal mechanics of the knee joint. Furthermore, calculated deformations have typically been for a single cell at the centre of a 100-cubic-micrometre block of simulated tissue; Erdemir used an anatomically-based representation that calculated deformations for 11 cells distributed within the same volume.

Erdemir’s method proved to be highly scalable because of micro-scale model independence that allowed exploitation of distributed memory computing architecture. As a result, Sibole, a research engineer at LRI, was able to harness the 75 teraflops of computational power of OSC’s IBM 1350 Glenn Cluster. When engineers recently deployed the centre’s more powerful HP-Intel Xeon Oakley Cluster, the Glenn Cluster was partially decommissioned.

An article authored by Erdemir and Sibole, ‘Chondrocyte Deformations as a Function of Tibiofemoral Joint Loading Predicted by a Generalized High-Throughput Pipeline of Multi-Scale Simulations’, was recently published in PLoS ONE, an international, peer-reviewed, open-access, online journal. The article can be viewed at: http://dx.doi.org/10.1371/journal.pone.0037538. Grant funding from the National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health supported the study.

This story originally appeared on HPC Projects. It appears here as part of a cross-publishing agreement with Scientific Computing World.