Inverse Volume-of-Fluid Meshless Method for Efficient Non-Destructive Thermographic Evaluation

A novel computational tool based in the Localized Radial-basis Function (RBF) Collocation (LRC) Meshless method coupled with a Volume-of-Fluid (VoF) scheme capable of accurately and efficiently solving transient multi-dimensional heat conduction problems in composite and heterogeneous media is formulated and implemented. While the LRC Meshless method lends its inherent advantages of spectral convergence and ease of automation, the VoF scheme allows to effectively and efficiently simulate the location, size, and shape of cavities, voids, inclusions, defects, or de-attachments in the conducting media without the need to regenerate point distributions, boundaries, or interpolation matrices. To this end, the Inverse Geometric problem of Cavity Detection can be formulated as an optimization problem that minimizes an objective function that computes the deviation of measured temperatures at accessible locations to those generated by the LRC-VoF Meshless method. The LRC-VoF Meshless algorithms will be driven by an optimization code based on the Genetic Algorithms technique which can efficiently search for the optimal set of design parameters (location size, shape, etc.) within a predefined design space. Initial guesses to the search algorithm will be provided by the classical 1D semi-infinite composite analytical solution which can predict the approximate location of the cavity. The LRC-VoF formulation is tested and validated through a series of controlled numerical experiments. This approach will allow solving the onerous computational inverse problem in a very efficient and robust manner while affording its implementation in modest computational platforms, thereby realizing the disruptive potential of the multi-dimensional high-fidelity non-destructive evaluation (NDE) method

Biomass Characterization and Insulation Optimization Studies

This study indicates how biomass materials can be effectively used as naturally sustainable alternatives to insulation materials. Barley grains and oak leaves, straw, and jute are collected, and crushed into powders/ chopped pieces. The physical characteristics are measured to characterize each powder. The biomass powder reinforced composites are manufactured in varying weight ratios. The density and thermal conductivity of composite materials are measured. The properties of composites compared to those of commercial insulation materials are found to be close to them. Furthermore, genetic algorithms (GA) can be used to achieve multi-objective optimization entailing maximizing insulation (minimizing heat transfer) and simultaneously maximizing sustainability (minimizing carbon footprint) of a designed insulation structure. The two resulting nonlinear competing objective functions will be maximized by means of evolutionary optimization techniques within a defined design space. The multi-objective optimization is achieved by building a Pareto front and determining the points of best compromise between the two objectives

Effects of Physical Parameters of Natural Fibers on Thermal Conductivity of Biomass Composites

Effects of Physical Parameters of Natural Fibers on Thermal Conductivity of Biomass Composites Hussein Awad Kurdi Saad, Gustavo Villarroel, and Birce Dikici (Advisor). Department of Mechanical Engineering, College of Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL, USA Abstract Agricultural waste products can be utilized as naturally environmental alternatives to insulation materials. Biomass materials (barley seeds and oak leaves) are gathered from the nature and used to mill into powders. Measuring the bulk density of the biomass powders is done by using a density cup. A relative humidity meter apparatus is used to implement moisture examinations. The angle of repose and the angle of internal friction are determined to characterize the flow behavior of the powders. The biomass powder reinforced composites are produced in varying weight ratios. A density analyzer is used to measure composite material’s density. Oak leaf powders measured to have 36.4% more moisture compared to barley seed powders. Oak leaf powders measured to have better flowability due to lower angle of repose compared to barley seed powders. Oak and barley reinforced composites measured to have density between 0.6-0.9 g/cm3 and have thermal conductivity between 0.16-0.25 W/mK respectively. The properties measured are close to those of conventional insulation materials