Thermal Design, Diagnostics, and Inverse Modeling
Heat Transfer in Metal Foams and Metamaterials for Thermal Management
This research focuses on enhancing heat transfer performance in metal foams embedded with phase change materials (PCMs) and thermal metamaterials, aiming to develop next-generation thermal management solutions. It investigates how the geometry of structured porous materials influences the melting behavior, temperature distribution, and overall thermal response of PCM systems. This approach combines advanced computational fluid dynamics (CFD) simulations with experimental validation to ensure accuracy and practical relevance. This work seeks to uncover design strategies that maximize thermal conductivity in PCM-integrated porous structures.
Application of Inverse Problems in Flow Rate Measurement
Low-cost, non-intrusive flow measurement and diagnostic techniques are developed by combining experimental heat transfer methods, inverse heat conduction modeling, and machine learning. They characterize thermal systems, such as heated pipes, by applying inverse models (e.g., using Green’s functions and Tikhonov regularization) to reconstruct heat fluxes from surface temperature data. This thermal response is then used to estimate fluid flow rates and detect faults like leaks or blockages. Their work integrates analytical modeling, laboratory experiments with band heaters and thermocouples, and data-driven approaches to enable accurate, real-time diagnostics without interrupting system operation.
Smart and Sustainable Building Systems
Building Energy Performance Forecasting
The objective of this project is to critically analyze existing methods used for forecasting building energy performance, focusing on data-driven, physics-based, and hybrid modeling approaches. This project aims at identifying research trends, challenges in dataset availability, and gaps in generalization across building types. At the end, an AI model will be developed to predict building energy.
A Comparative Case Study on the Performance of Building Integrated Photovoltaic (BIPV) Systems Installed on Rooftops and Facades of a Commercial Building
This project uses EnergyPlus and OpenStudio to compare the performance, energy yield, and cost-effectiveness of BIPV installations on rooftops versus façades, and windows in a real commercial building setting. Rooftop installations have shown higher efficiency due to solar exposure; façade BIPVs had aesthetic and shading benefits. The results of this project will be applied to building energy performance forecasting.
Solar Water Heating System for Energy-Efficient Buildings
This project involves designing and analyzing a solar water heating system integrated into residential and commercial buildings. The system uses solar thermal collectors and insulated storage tanks, combined with advanced heat exchanger designs to optimize energy transfer. The research aims to improve energy savings and reduce reliance on fossil fuels, contributing to the decarbonization of water heating systems in buildings.
Energy-Efficient HVAC Systems for Net-Zero Buildings
This project focuses on optimizing HVAC system configurations and control strategies to improve energy efficiency in green buildings. This includes envelope design, heat recovery, and integration with renewable energy sources for reduced emissions. The project also investigates the use of nanoparticles and PCMs for better heat absorption and thermal storage.
Renewable Energy Planning and Optimization
Optimal Site Selection for Solar Farms in the USA Using Fuzzy Logic, AHP, and GIS
This research focuses on identifying the most suitable locations for photovoltaic (PV) solar farms across the United States. As solar energy becomes more essential for reducing emissions and ensuring clean energy supply, it is increasingly important to make careful decisions about where to build solar farms. This decision is complex because it involves many different environmental, technical, and legal factors. To solve this, a spatial decision support model was developed that combines Geographic Information Systems (GIS), Fuzzy Logic, and the Analytic Hierarchy Process (AHP).
In the model, five main groups of criteria are used: (1) Climate, including solar radiation (GHI, DNI, DHI), effective sunshine hours, and temperature; (2) Environmental, such as land cover, water bodies, and protected areas; (3) Orography, including slope, aspect, and elevation; (4) Location, which measures distances to roads, power grids, and cities; and (5) Regulation Constraints, such as legal rules about how far solar farms should be from natural gas lines, fault zones, or mining sites.
Each sub-criterion is standardized using Fuzzy Membership Functions like linear, triangular, or trapezoidal shapes. These functions allow the model to assign scores between 0 and 1 based on how suitable each location is, instead of just using a “yes” or “no” approach. Areas that are completely restricted—like steep slopes, flood zones, or ecological reserves—are removed using Boolean masking. AHP is also applied to determine the weights of each criterion based on expert opinions.
The result of this analysis is a set of high-resolution maps that classify land across the U.S. into five levels of suitability, ranging from “very suitable” to “not suitable.” These maps provide useful guidance for investors, engineers, and policymakers who are planning solar energy projects. By combining legal, environmental, and physical data in one flexible framework, the model supports more accurate and sustainable site selection compared to traditional binary methods. This research intends to help speed up the clean energy transition by supporting long-term, data-driven energy planning.
Sustainable Water and Thermal Technologies
Membrane Distillation for Water Purification
This study investigates membrane distillation (MD) technology for high-efficiency water purification. The work emphasizes optimizing membrane performance and system design for treating saline or wastewater streams. By improving energy efficiency and thermal integration, this research supports sustainable water treatment solutions aligned with global clean water goals.