Inovação e gerenciamento de programa sincronizado e colaborativo para novos programas
Founded in 1973, UES, Inc. is an innovative science and technology company that provides government and industry customers with superior research and development expertise and world-class support. UES takes great pride in developing products and services from its technologies for commercialization and transition.
UES, Inc. was founded with a vision to become a renowned scientific research and development organization and is proud to be a partner with the Air Force Research Laboratory for over four decades. One specific area of research is focused on the needs of the Air Force Research Laboratory’s 711th Human Performance Wing (HPW). The areas of focus include advancing marker discovery in air and biofluids, developing sensors, and evaluating microbiomes for health and performance, as well as toxicology, industrial hygiene, and high throughput screening for genetic and chemical exposure.
For this specific program, government researchers in collaboration with UES contractors led the research structure, design and implementation to identify credible simulation models and data characterization for airflow movement within Air Force cargo aircraft. A better understanding of airflow movement could be used to identify hot spots where bioaerosol contaminants are likely to accumulate, which would inform various strategies for decontamination.
To develop the needed computational fluid dynamics (CFD) simulations, government researchers in the 711th HPW and UES contractors assigned to the 711th HPW partnered with Simcenter™ Engineering and Consulting services and used Siemens multiphysics CFD simulation software, Simcenter™ STAR-CCM+™, part of the Xcelerator™ portfolio, the comprehensive and integrated portfolio of software and services from Siemens Digital Industries Software.
The model used in the study was a C-130 Hercules, which has been a workhorse of the U.S. Air Force aeromedical evacuation capability since the 1960s. The C-130’s design allows the aircraft to quickly switch from a cargo and personnel transport configuration to an aeromedical evacuation platform for up to 74 litter patients. The aircraft is outfitted with electrical and oxygen systems for aeromedical evacuation.
The objective of the study was to model the injection of bioaerosols (simulated cough) and track the particles throughout the aircraft cabin. A typical scenario involves multiple passengers lying flat on beds. A cough from an infected passenger is then simulated by modeling the jet of cough air carrying droplets of different sizes in Simcenter STAR-CCM+. Engineers at UES used a geometric model of the C-130 to set up the initial steady-state flow field inside the cabin. Simcenter Engineering consultants took the models and prepared them for the transient multiphase particle tracking simulations. The simulations were run on 200 CPUs on a high-performance computing (HPC) cluster. In just a few days, Simcenter Engineering consultants were able to deliver the analysis of different sizes and transfer the knowledge to UES and the Air Force.
To simulate such complex biological agent transport scenarios, the fidelity of the simulation is crucial. Simcenter STAR-CCM+ uses a multiphase functionality that accurately predicts the paths of solid particles dispersed in airflows. Simcenter STAR-CCM+ can track the particles in time and predict where different sized particles land, how much particle mass accumulates on the interior surfaces and the residence times of the particles (how long they linger in the air). In addition, the streamlined simulation workflow is set up to easily go from evaluating just one cough scenario to hundreds of different scenarios.
The results from the analysis will help the US Air Force make critical decisions regarding the transport of infectious patients.
The results of the simulation aid in the design of the cabin ventilation system and aircrew safety procedures when transporting sick passengers. Design optimizations can be done with additional simulations that vary the number of patients, the ventilation system air flow conditions or the aircraft geometry.
The results of this study demonstrate a proof-of-concept simulation for the distribution of aerosols of biologically relevant size and density aboard a cargo aircraft. Follow-on studies are required to validate these computational predictions.
The developed knowledge regarding bioaerosol transport and deposition in cargo aircraft will be useful to guide improved procedures and sampling strategies for bioaerosol detection and surface decontamination based on suspected points of introduction into the aircraft. This data enables in-patient transfer and overall Air Force personnel transport safer for all involved.