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Articles 1 - 6 of 6
Full-Text Articles in Mechanical Engineering
Estimating Smart Wi-Fi Thermostat-Enabled Thermal Comfort Control Savings For Any Residence, Abdulelah D. Alhamayani, Qiancheng Sun, Kevin Hallinan
Estimating Smart Wi-Fi Thermostat-Enabled Thermal Comfort Control Savings For Any Residence, Abdulelah D. Alhamayani, Qiancheng Sun, Kevin Hallinan
Mechanical and Aerospace Engineering Faculty Publications
Nowadays, most indoor cooling control strategies are based solely on the dry-bulb temperature, which is not close to a guarantee of thermal comfort of occupants. Prior research has shown cooling energy savings from use of a thermal comfort control methodology ranging from 10 to 85%. The present research advances prior research to enable thermal comfort control in residential buildings using a smart Wi-Fi thermostat. "Fanger's Predicted Mean Vote model" is used to define thermal comfort. A machine learning model leveraging historical smart Wi-Fi thermostat data and outdoor temperature is trained to predict indoor temperature. A Long Short-Term-Memory neural network algorithm …
Toward Cost-Effective Residential Energy Reduction And Community Impacts: A Data-Based Machine Learning Approach, Adel Naji, Badr Al Tarhuni, Jun-Ki Choi, Salahaldin Alshatshati, Seraj Ajena
Toward Cost-Effective Residential Energy Reduction And Community Impacts: A Data-Based Machine Learning Approach, Adel Naji, Badr Al Tarhuni, Jun-Ki Choi, Salahaldin Alshatshati, Seraj Ajena
Mechanical and Aerospace Engineering Faculty Publications
Many U.S. utilities incentivize residential energy reduction through rebates, often in response to state mandates for energy reduction or from a desire to reduce demand to mitigate the need to grow generating assets. The assumption built into incentive programs is that the least efficient residences will be more likely take advantage of the rebates. This, however, is not always the case. The main goal of this study was to determine the potential for prioritized incentivization, i.e., prioritizing incentives that deliver the greatest energy savings per investment through an entire community. It uses a data mining approach that leverages known building …
Propeller And Propeller-In-Wing Thrust Vectoring, Grace G. Culpepper
Propeller And Propeller-In-Wing Thrust Vectoring, Grace G. Culpepper
Honors Theses
This research investigates the efficiency of a vane-based thrust vectoring system set in the wake of a propeller, supporting forward force at a minimum loss in net thrust. The vectoring system itself is placed in both a standalone propeller configuration and a propeller-in-wing configuration. Both static and wind-on force-based experiments are conducted at the University of Dayton Low Speed Wind Tunnel (UD-LSWT) with off-the-shelf R/C propellers. Sensitivity analysis determines both the effect of vane deflection angle on thrust vectoring and the effect of propeller placement with respect to the upper surface of the integrated wing on system performance. Static test …
Development Of A Computational Framework For Estimating Knee Joint Contact Forces In Running, Sean W. Kapp
Development Of A Computational Framework For Estimating Knee Joint Contact Forces In Running, Sean W. Kapp
Honors Theses
The prevalence of running as a form of exercise and the necessity of walking for simple locomotion obscure massive forces and moments within the body. An especial area of concern is the knee, as common among these injuries is knee pain as a result from high impact on the ground or ground reaction forces. These forces are altered by the foot strike pattern of the individual; in this study, either rearfoot strike (RFS) or forefoot strike (FFS). This alteration will impact internal forces conducted upward through the body. Given the complexity of the motion of running and the forces involved, …
Automated Residential Energy Audits Using A Smart Wifi Thermostat-Enabled Data Mining Approach, Abdulrahman Alanezi, Kevin Hallinan, Kefan Huang
Automated Residential Energy Audits Using A Smart Wifi Thermostat-Enabled Data Mining Approach, Abdulrahman Alanezi, Kevin Hallinan, Kefan Huang
Mechanical and Aerospace Engineering Faculty Publications
Smart WiFi thermostats, when they first reached the market, were touted as a means for achieving substantial heating and cooling energy cost savings. These savings did not materialize until additional features, such as geofencing, were added. Today, average savings from these thermostats of 10–12% in heating and 15% in cooling for a single-family residence have been reported. This research aims to demonstrate additional potential benefit of these thermostats, namely as a potential instrument for conducting virtual energy audits on residences. In this study, archived smart WiFi thermostat measured temperature data in the form of a power spectrum, corresponding historical weather …
Using Smart-Wifi Thermostat Data To Improve Prediction Of Residential Energy Consumption And Estimation Of Savings, Abdulrahman Alanezi, Kevin P. Hallinan, Rodwan Elhashmi
Using Smart-Wifi Thermostat Data To Improve Prediction Of Residential Energy Consumption And Estimation Of Savings, Abdulrahman Alanezi, Kevin P. Hallinan, Rodwan Elhashmi
Mechanical and Aerospace Engineering Faculty Publications
Energy savings based upon use of smart WiFi thermostats ranging from 10 to 15% have been documented, as new features such as geofencing have been added. Here, a new benefit of smart WiFi thermostats is identified and investigated; namely, as a tool to improve the estimation accuracy of residential energy consumption and, as a result, estimation of energy savings from energy system upgrades, when only monthly energy consumption is metered. This is made possible from the higher sampling frequency of smart WiFi thermostats. In this study, collected smart WiFi data are combined with outdoor temperature data and known residential geometrical …