LES Subgrid Modeling of Liquid-Gas Phase Interface Dynamics

Project: Research project

Project Details

Description

Liquid/gas two-phase ows occur in almost every aspect of our daily lives. In those ows that involve topology changes, the atomization of the liquid is governed by the dynamics of the phase interface. Although atomization is crucial in many technical applications ranging from energy conversion to pharmaceutical sprays, no predictive models derived from rst principle currently exist. The development of such a predictive model for large eddy simulations (LES) of atomizing ows is the objective of the proposed research project. Since the phase interface dynamics during atomization do not appear to follow a cascade process, a novel approach is proposed to determine the unclosed terms in the LES formulation involving the phase interface dynamics. This approach, based on a multi-scale decomposition, combines features of direct numerical simulations (DNS) and LES in an ecient way inherently incorporating the interaction and competition between dierent forces and atomization mechanisms acting on multiple length and time scales. The intellectual merit of this proposal is that it will provide a novel way of treating non- cascade processes of interface dynamics in LES, where the idea of a cascade process is usually the prerequisite and foundation for the modeling approach. While the focus of this project is on liquid/gas phase interfaces the proposed methodology can be applied to other thin, interface-like structures that may or may not follow a cascade process, like for example premixed and partially premixed ame fronts. The resulting predictive LES model for phase interface dynamics will have a profound impact on a range of disciplines, such as energy systems, where the design of fuel-ecient and low-polluting engines hinges on the air/fuel mix for optimal combustion which depends critically on the quality of the liquid fuel atomization. All solvers and models developed in the project will be made freely and readily available. Being based on the CHIMPS paradigm, adaptation to other researcher's codes is straightforward, thus ensuring wide dissemination of the project's results. The transformative potential of this proposal is signicant. An incremental improvement design philosophy is currently prevalent in many engine applications in part due to experiments of radically new designs being very costly and the fact that numerical simulations lack a predictive model for atomization and thus require tuning with existing experimental data. The ecient, pre- dictive LES approach for atomization proposed here has the potential to initiate a transformative, bold new design philosophy that targets radically new designs, because the cost of pre-selection feasiblilty studies using the proposed LES approach is signicantly lower than experimental stud- ies. Radically new atomization concepts might result in signicantly improved engine performance to reduce pollutant formation, thus enabling environmentally sustainable energy conversion, and increased fuel eciency, hence decreasing the national dependency on fossil fuels. The broader impacts of this proposal include incorporating its results into a new cross- listed graduate/advanced undergraduate course to be developed by the PI on multiphase ows. Projects developed in the courses will be utilized to recruit undergraduates into REU projects that will focus on supporting and enhancing a high school outreach program. The high school program is a measurable, replicable, high-impact, engaging enrichment program designed to inspire and inform the high school community about STEM-related elds. The investigators will collaborate with the Scottsdale Unied School District to involve high school calculus students in experimental research by designing, testing, analyzing, and optimizing water hose nozzles to meet dierent goals. The best designs will then be analyzed experimentally in the Biopropulsion Laboratory at ASU, and will also be analyzed numeri
StatusFinished
Effective start/end date9/1/098/31/12

Funding

  • National Science Foundation (NSF): $155,000.00

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