Research Areas

Sustainable methods for cooling tower water treatment
Cooling towers are typically incorporated into air conditioning systems of large buildings and industrial facilities. To reduce contaminants, precipitation of inorganic elements, and bacterial growth that build up in the system, cooling tower water is both treated with harsh chemicals and routinely purged to a municipal sewer system and replaced with make-up water. Potable water is often used for make-up water. We are developing a passive system that eliminates blow down water as well as the need to use harsh chemicals, thereby resulting in a cost-effective, environmentally friendly, innovative alternative to current technology.

Energy harvesting in shallow and deep water

Unmanned Underwater Vehicles (UUVs) are equipped with a number of sensors usually powered by heavy rechargeable batteries. The average battery stack on a 52 kilogram sea-glider weighs about 18 kilograms. The weight and capacity of these rechargeable batteries are of concern, especially if an UUV is on a mission that requires a longer uninterrupted/unattended operation than battery life allows. By harvesting energy from ambient sources like vibrations, heat, wind, or wave energy then using this energy to generate power, we may enable remote sensor systems, small electronic devices, and/or microelectromechanical systems (MEMs) to operate indefinitely.

Utilization of waste products in green building construction

Currently, construction-related materials comprise one-fourth of landfill space in the U.S. A small percentage is diverted from landfills and reused or recycled. For example, in the construction industry, concrete and asphalt are sometimes reused for base course or backfill.

Contractors are reluctant to use waste and by-products. Using reclaimed materials in the construction industry often imposes added costs to a construction budget. That mechanical and chemical properties of these materials are not well documented or understood further discourages use. We are identifying commonly available waste products and their mechanical properties for green building construction.

Energy savings predictions from building equipment retrofits

The main challenge in predicting the energy savings from equipment retrofits lies in identifying comparative data post replacement/retrofit. Variations in weather, building internal loads, and HVAC equipment operation schedules does not allow direct comparison of building energy measurements in the pre-retrofit period to actual post-retrofit energy use. These variations, along with limitations of commonly used linear regression methods for data processing, result in inaccurate energy savings predictions.

We are developing a model that estimates potential energy savings using Artificial Intelligence (AI) methods including neural networks, fuzzy logic, and genetic algorithms. The model integrates variables to the pre-retrofit energy usage pattern then provides energy savings estimates for the post-retrofit period by using statistically averaged weather data for the building location.

Energy benchmarking model

Energy benchmarking is an important step in evaluating the energy use of a building to compare with similar buildings in similar climates. Depending on benchmarking results, extra measures can be taken to reduce energy consumption when the subject building has been assessed to consume more than other similar buildings. Benchmarking aids in the prediction of potential energy savings from equipment upgrades. We are developing a benchmarking model using Artificial Neural Networks (ANN). The model specifically focuses on predicting a weighted EUI by taking various building variables into consideration.

Use of radiant cooling in hot and humid climates

Radiant cooling panels are composed of tubes in a panel configuration. Cold water flows through the tubes and removes heat from the surrounding air primarily by radiation heat transfer. Cooling panels can be embedded into a building structure permanently or mounted to the ceiling or floor. Advantages of radiant cooling panels include simple mechanisms, low maintenance expenses, and lower electrical energy consumption rate when compared to existing mechanical cooling equipment. While radiant cooling panels can effectively remove sensible heat from a room, they do not effectively remove latent heat. In hot and humid climates like Hawaii, radiant cooling panels can be integrated with mechanical cooling methods to create an energy-conserving, cost-effective building air conditioning system.

Development of a wind power forecasting model

The intermittent nature of wind energy makes forecasting tools desirable in order to predict power fluctuations that affect the reliability of power generation and transmission. Extensive research efforts of European and American research groups favor the use of neural networks in forecasting, especially for medium term forecasting. However, short term wind power forecasting has not been successfully modeled. We are developing a tool to forecast short term wind power. Our forecasting method will improve predictions, particularly after the second hour which has been a major challenge with the currently applied moving average statistical method.