Modeling of Ultraviolet Optical Intensities in Agglomerates of Spores and Vegetative Cells Exposed to Sunlight
Abstract
An accurate model for predicting the photochemical degradation and transformation of bacterial spores and cells exposed to environmental conditions is of major importance to the Army, DOD and DHS. A key mechanism in the degradation process is damage of DNA due to absorption of UV radiation, and in this respect a predictive model will need reliable information on 1) the location of the DNA within spores and cells, 2) the UV solar spectrum under variable environmental conditions, and 3) the distribution of UV radiative intensity within the spore or cell. The work proposed here deals entirely with task 3. Specifically, the work will develop numerical codes, based on physical first principles, for predicting the spectral electromagnetic absorption rates within more realistically-modeled spores and cells, existing either individually, in clusters, or incorporated into droplets, and residing in the atmosphere or on a surface. The model developed in the proposed work will be based upon application of the macroscopic, frequency-domain Maxwell s equations (MEs) to detailed representations of the spore/cell system. The approach is basically that of a direct simulation, involving the three tasks of 1) generating a detailed realization of the refractive index distribution within a spore/cell system (individual or clustered), 2) solving the MEs for the system (either exactly or numerically to a length scale well shorter than the illuminating wavelength) and computing the sought quantities (local field intensity distribution and local absorption rates for the specific configuration, and 4) averaging over multiple randomly sampled configurations of the system, to obtain distribution statistics of the field intensity and absorption rates. This approach is computationally intensive and has become feasible only recently due to the widespread accessibility of parallel computational platforms.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 24, 2018
- Source ID
- W911NF1710392
Entities
People
- Daniel Mackowski
Organizations
- Army Contracting Command
- Auburn University
- United States Army