AQUANRG CONSULTING INC. — Department of Energy SBIR Phase I: 15a

Description

Current computational predictive tools are not benefited from state-of-the-art algorithms and hardware to simulate complex physical-chemical processes which occur in various material and energy systems- These simulation software: 1) simplify complex geometries, 2) model either physical or chemical processes, 3) are incapable of capturing physical and chemical properties which span vast length scales, and 4) are expensive premise-based tools- AquaNRG’s multiscale reactive transport modeling tool i-e- rtmApp combines novel mathematical methods and cloud hosting to: 1) capture exact and complex geometry of materials which are obtained from high- resolution imaging tools such as microCT or scanning electron microscope (SEM), 2) solve physical and chemical equations simultaneously, 3) account for nanometer to kilometer processes, and 4) provide a cost-effective SaaS solution- Reactive transport models (RTMs) have been previously used to analyze the interaction between physical, chemical, and biological processes in natural and man-made porous and fractured media- RTMs are used by engineers and scientists from various academic and industrial disciplines such as oil and gas (e-g- chemical enhanced oil recovery processes), nuclear waste management (e-g- concrete degradation in engineered barrier systems), environmental consulting (e-g- contaminant fate and transport), mining (e-g- acid mine drainage), automotive (e-g-, fuel cell control and modeling), additive manufacturing (e-g-, precise machining of parts and the manufacturing of arbitrary components and devices), and biomedical (e-g- physiologic mineralization in defective bones)- Existing RTM tools, however, can only delineate processes and material characteristics in a single length scale (e-g- nanometer or kilometer)- With engineers and scientists pursuing online technologies to support their work, web- based applications have been emerged as primary tools in various fields of science and engineering- Worldwide access to data anytime and with any mobile device as well as offering flexible and cost-effective on-demand and pay-as-you-go model while decreasing upfront and maintenance costs of hardware and software for large-scale computational research have led to increased demand for SaaS (Software as a Service) applications- However, RTMs have not been benefited immensely from SaaS advancements-