The members of MSAL are active in several research projects. Brief descriptions of these are described below.
Thermal Property and Performance Predictions of Nanoenhanced Phase Change Materials (PCMs)
Funded by the Chemical, Bioengineering, Environmental, and Transport Systems Division of the Engineering Directorate of the National Science Foundation
A number of projects are focused on a holistic prediction of the thermal conductivity of phase change materials containing highly-conducting nanoparticles such as graphene sheets and graphite nanofibers. These investigations are important as the efficiency of phase change materials for energy storage is limited by their low thermal conductivity. Aspects of this effort include the following:
- Determination of the correct approach for performing equilibirum molecular dynamics (EMD) for thermal conductivity prediction of graphitic materials.
- Equilibrium molecular dynamics (EMD) and nonequilibrium molecular dynamics (NEMD) simulations of graphene, graphite, and graphite nanofibers for evaluation of their thermal conductivity tensors.
- Development and application of a theoretical treatment for percolated networks of nanoparticles.
- Examination the influence of the structure of single-layer and multi-layer graphene on thermal conductivity.
Additional work examines the behavior and performance of PCMs through the analysis of PCM energy storage performance for specific applications using multiphysics modeling. This work is part of a larger overall effort that includes members of the NovaTherm Laboratory at Villanova. The project web site is located here.
The molecular dynamics simulations were performed using the in-house Molecular Dynamics for Arbitrary Geometries (MDAG) code. This software is a parallel classical molecular dynamics (MD) tool for investigation of a wide variety of nanoscale systems. The code is developed using a simple keyword format with zone-based molecular initialization that allows for implementation of a MD simulation of thousands of molecules with a few lines of input deck. Some features of the code are as follows:
- Trivial parallel implementation
- Traditional or linked-cell force calculation
- Electrostatic force calculation via Ewald summation
- Trivial simulation restart capability
- System visualization via opendx software
- Hexahedral zone-based initialization (input deck creation via a hexahedral mesh generation code like TrueGrid)
MDAG is developed in structured C. Parallel implementation is through MPI and CUDA (GPU processing).
Energy Efficient Buildings and Data Centers
Funded in part by (1) the Industrial Innovation and Partnerships Division of the Engineering Directorate of the National Science Foundation, (2) the US Environmental Protection Agency, and (3) the Office of Naval Research.
Building HVAC systems comprise a large portion of overall energy costs. Therefore, improvements in the energy efficiency of building systems can potentially save customers large sums of money annually. This fact is particularly true for data centers, where the amount of power required for cooling the IT equipment is as much as the power used by the IT equipment themselves. Therefore, MSAL is a partner in the NSF I/UCRC in Energy-Smart Electronic Systems (ES2).
Specific projects under investigation in this field are as follows:
- Exergy analysis and modeling of data center cooling systems (partnership with the Laboratory for Advanced Thermal and Fluid Systems at Villanova University)
- Modeling and experiments of the efficiency of air cooling systems in a 1U server.
- Holistic calibration of PID coefficients for building HVAC systems for energy conservation.
- Application of supervisory control techniques in building HVAC systems for energy conservation.
The final two listed efforts were performed using the in-house Lumped HVAC (L-HVAC) software. L-HVAC is a lumped parameter code used to predict moist airflow thermodynamic properties in a heating, ventilating, and air conditioning system (HVAC). The code performs nonlinear implicit coupled calculations of flow resistance, absolute humidity, coil calculations, psychrometrics, and energy transfer to obtain predictions of system air properties for both transient and steady-state systems. Some features of this code include:
- Virtual controls: thermostats and flow regulators connected to output devices (control dampers, chiller work input, fan speed/power)
- Energy use calculations by the entire HVAC system: chiller work input and fan/pump work input
- Trivial simulation restart capability
- Adaptability to nearly any HVAC system
The data center modeling work is performed using the multiphysics flow network modeling tool Villanova Thermodynamic Analysis of Systems (VTAS). VTAS contains the capability to model the energy and mass flows throughout a data center, and also calculates second-law efficiencies using exergetic analysis. This tool can be used to aid in optimizing data center cooling systems and to determine bottlenecks in energy efficiency. Further information and VTAS components can be found in the VTAS component library.
A new area has emerged in improving the energy efficiency of industrial kitchens. The energy assessment will be done by extending life cycle analysis theory towards food storage, cooking, display, and storage. This work, funded by the Environmental Protection Agency, is in partnership with Villanova Dining Services.
Molecular-Based Predictions of Material and System Properties
The ability to predict the properties of materials based on molecular information provides a powerful means to tailor the molecular structure of materials to achieve the desired macroscopic behavior. This approach involves incorporating the molecular interactions into a known theoretical framework to achieve the desired result. Projects related to this category are listed below:
- Effective Thermal Conductivity Prediction of Composite Materials Containing Percolated Cylindrical Inclusions: A method has been developed that allows for the prediction of the effective thermal conductivity in a bulk composite material containing a percolated network of randomly-distributed cylindrical inclusions. If conduction through a background matrix material is ignored, then the result of the theory is a simple closed-form solution. This work enables the ability to predict difficult-to-measure microscale properties based on data from macroscale experiments.
- Extension of the Neoclassical Theory of Capillarity: J. D. van der Waals originally developed a theoretical approach to interfacial tension prediction using excess free energy generation due to the presence of a finite-sized transition region between bulk liquid and vapor phases of a fluid. In his analysis, he applied the van der Waals equation of state to obtain his results. The predictions were recently improved by V. P. Carey at UC Berkeley by applying the Redlich-Kwong fluid model to this analysis. At MSAL, we applied the two most advanced cubic equations of state known - Soave-Redlich-Kwong and Peng-Robinson - to the theory of capillarity but found out that the increased complexity in the latter two models provided worse predictions. Further investigation into this issue found that the reason is that all models overpredict vapor density, and these overpredictions act to adjust the calculated surface tension to a reasonable value. The better vapor density predictions by the advanced models reduce this adjustment and therefore provide less accurate predictions of surface tension. In addition, relations were created that allow for reasonable estimates of surface tension using the advanced models.
- Size Dependence on Nanoscale Drag: a simple approach has been developed to predict the drag on an infinite circular cylinder. The approach suggests that the Stokes formula dramatically overestimates the drag on the cylinder when a macroscopic approach is applied for cylinders with radii on the order of nm.
- Phase Change Material Evaluation: A number of empirical and statistical thermodynamic approaches have been proposed for evaluation of the thermal properties of phase change materials. We have determined which combinations of methods provide the most accurate predictions of important PCM thermal properties for a given class of organic PCMs. The goal of this work is to establish a predictive means for tailoring a PCM molecule to optimize PCM performance.
- Nano-droplet Impingement Heat Transfer: the unique aspects of nano-droplet impingement on a solid surface were explored using MD simulations. We discovered that an energy gain is seen by the surface even when the droplet temperature is below the substrate temperature. This represents an inherent limitation in the viability of spray cooling at the nanoscale.