Patricia E. Gharagozloo

Analysis and modeling of Nannochloropsis growth in lab, greenhouse, and raceway experiments

Efficient production of algal biofuels could reduce dependence on foreign oil by providing a domestic renewable energy source. Moreover, algae-based biofuels are attractive for their large oil yield potential despite decreased land use and natural resource (e.g., water and nutrients) requirements compared to terrestrial energy crops. Important factors controlling algal lipid productivity include temperature, nutrient availability, salinity, pH, and the light-to-biomass conversion rate. Computational approaches allow for inexpensive predictions of algae growth kinetics for various bioreactor sizes and geometries without the need for multiple, expensive measurement systems. Parametric studies of algal species include serial experiments that use off-line monitoring of growth and lipid levels. Such approaches are time consuming and usually incomplete, and studies on the effect of the interaction between various parameters on algal growth are currently lacking. However, these are the necessary precursors for computational models, which currently lack the data necessary to accurately simulate and predict algae growth. In this work, we conduct a lab-scale parametric study of the marine alga Nannochloropsis salina and apply the findings to our physics-based computational algae growth model. We then compare results from the model with experiments conducted in a greenhouse tank and an outdoor, open-channel raceway pond. Results show that the computational model effectively predicts algae growth in systems across varying scale and identifies the causes for reductions in algal productivities. Applying the model facilitates optimization of pond designs and improvements in strain selection.

Rapid hydrogen gas generation using reactive thermal decomposition of uranium hydride.

Oxygen gas injection has been studied as one method for rapidly generating hydrogen gas from a uranium hydride storage system. Small scale reactors, 2.9 g UH{sub 3}, were used to study the process experimentally. Complimentary numerical simulations were used to better characterize and understand the strongly coupled chemical and thermal transport processes controlling hydrogen gas liberation. The results indicate that UH{sub 3} and O{sub 2} are sufficiently reactive to enable a well designed system to release gram quantities of hydrogen in {approx} 2 seconds over a broad temperature range. The major system-design challenge appears to be heat management. In addition to the oxidation tests, H/D isotope exchange experiments were performed. The rate limiting step in the overall gas-to-particle exchange process was found to be hydrogen diffusion in the {approx}0.5 {mu}m hydride particles. The experiments generated a set of high quality experimental data; from which effective intra-particle diffusion coefficients can be inferred.

From benchtop to raceway : spectroscopic signatures of dynamic biological processes in algal communities.

The search is on for new renewable energy and algal-derived biofuel is a critical piece in the multi-faceted renewable energy puzzle. It has 30x more oil than any terrestrial oilseed crop, ideal composition for biodiesel, no competition with food crops, can be grown in waste water, and is cleaner than petroleum based fuels. This project discusses these three goals: (1) Conduct fundamental research into the effects that dynamic biotic and abiotic stressors have on algal growth and lipid production - Genomics/Transcriptomics, Bioanalytical spectroscopy/Chemical imaging; (2) Discover spectral signatures for algal health at the benchtop and greenhouse scale - Remote sensing, Bioanalytical spectroscopy; and (3) Develop computational model for algal growth and productivity at the raceway scale - Computational modeling.

A Coupled Transport and Solid Mechanics Formulation for Modeling Oxidation and Decomposition in a Uranium Hydride Bed

Modeling of reacting flows in porous media has become particularly important with the increased interest in hydrogen solid-storage beds. It is important for design applications to have an accurate, but relatively simple model for system analysis. We are interested in simulating the reaction of uranium hydride and oxygen gas in a hydrogen storage bed using multiphysics finite element modeling. Our model considers chemical reactions, heat transport, and mass transport within a hydride bed. Previously, the time-varying permeability and porosity were considered uniform. This led to discrepancies between the simulated results and experimental measurements. In this work, we account for the effects of non-uniform changes in permeability and porosity due to phase and thermal expansion. These expansions result in mechanical stresses which lead to bed deformation. To describe this, we develop a simplified solid mechanics model for the local variation of permeability and porosity as a function of the local bed deformation. We find that, by using this solid mechanics model, we improve the agreement between our reacting bed model and the experimental data.Copyright

Multiphysics Model of Palladium Hydride Isotope Exchange Accounting for Higher Dimensionality

This report summarizes computational model development and simulations results for a series of isotope exchange dynamics experiments including long and thin isothermal beds similar to the Foltz and Melius beds and a larger non-isothermal experiment on the NENG7 test bed. The multiphysics 2D axi-symmetric model simulates the temperature and pressure dependent exchange reaction kinetics, pressure and isotope dependent stoichiometry, heat generation from the reaction, reacting gas flow through porous media, and non-uniformities in the bed permeability. The new model is now able to replicate the curved reaction front and asymmetry of the exit gas mass fractions over time. The improved understanding of the exchange process and its dependence on the non-uniform bed properties and temperatures in these larger systems is critical to the future design of such systems.