Engineering Commons^™

A Bi-Invariant Approach To Approximate Motion Synthesis Of Planar Four-Bar Linkage, Tianze Xu, David H. Myszka, Andrew P. Murray

Mechanical and Aerospace Engineering Faculty Publications

This paper presents a planar four-bar approximate motion synthesis technique that uses only pole locations. Synthesis for rigid-body guidance determines the linkage dimensions that guide a body in a desired manner. The desired motion is specified with task positions including a location and orientation angle. Approximation motion synthesis is necessary when an exact match to the task positions cannot be obtained. A linkage that achieves the task positions as closely as possible becomes desired. Structural error refers to the deviations between the task positions and the linkage's generated positions. A challenge in approximate motion synthesis is that structural error involves …

Characterization Of Upper Extremity Kinematics Using Virtual Reality Movement Tasks And Wearable Imu Technology, Skyler A. Barclay, Lanna N. Klausing, Tessa M. Hill, Allison L. Kinney, Timothy Reissman, Megan E. Reissman

Mechanical and Aerospace Engineering Faculty Publications

Task-specific training has been shown to be an effective neuromotor rehabilitation intervention, however, this repetitive approach is not always very engaging. Virtual reality (VR) systems are becoming increasingly popular in therapy due to their ability to encourage movement through customizable and immersive environments. Additionally, VR can allow for a standardization of tasks that is often lacking in upper extremity research. Here, 16 healthy participants performed upper extremity movement tasks synced to music, using a commercially available VR game known as Beat Saber. VR tasks were customized to characterize participants' joint angles with respect to each task's specified cardinal direction (inward, …

Utilizing Machine Learning Models To Estimate Energy Savings From An Industrial Energy System, Eva Mclaughlin, Jun-Ki Choi

Mechanical and Aerospace Engineering Faculty Publications

Energy audits are an important part of reducing energy usage, costs, and carbon emissions, but there have been discrepancies in the quality of audits depending upon the auditor, which can negatively affect the impacts and credibility of the energy assessment. In this paper, historical energy auditing data from a U.S. Department of Energy sponsored research program was gathered and analyzed with a machine-learning algorithm to predict demand savings from a compressed air system assessment recommendation in industrial manufacturing facilities. Different energy auditors calculate savings for repairing leaks in compressed air systems in various ways, so the energy demand savings have …

Smart Wifi Thermostat-Enabled Thermal Comfort Control In Residences, Robert Lou, Kevin P. Hallinan, Kefan Huang, Timothy Reissman

Mechanical and Aerospace Engineering Faculty Publications

The present research leverages prior works to automatically estimate wall and ceiling R-values using a combination of a smart WiFi thermostat, building geometry, and historical energy consumption data to improve the calculation of the mean radiant temperature (MRT), which is integral to the determination of thermal comfort in buildings. To assess the potential of this approach for realizing energy savings in any residence, machine learning predictive models of indoor temperature and humidity, based upon a nonlinear autoregressive exogenous model (NARX), were developed. The developed models were used to calculate the temperature and humidity set-points needed to achieve minimum thermal comfort …

Predicting Industrial Building Energy Consumption With Statistical And Machine-Learning Models Informed By Physical System Parameters, Sean Kapp, Jun-Ki Choi, Taehoon Hong

Mechanical and Aerospace Engineering Faculty Publications

The industrial sector consumes about one-third of global energy, making them a frequent target for energy use reduction. Variation in energy usage is observed with weather conditions, as space conditioning needs to change seasonally, and with production, energy-using equipment is directly tied to production rate. Previous models were based on engineering analyses of equipment and relied on site-specific details. Others consisted of single -variable regressors that did not capture all contributions to energy consumption. New modeling techniques could be applied to rectify these weaknesses. Applying data from 45 different manufacturing plants obtained from industrial energy audits, a supervised machine-learning model …

Predicting The Impact Of Utility Lighting Rebate Programs On Promoting Industrial Energy Efficiency: A Machine Learning Approach, Phillip Shook, Jun-Ki Choi

Mechanical and Aerospace Engineering Faculty Publications

Implementation costs are a major factor in manufacturers' decisions to invest in energy-efficient technologies. Emerging technologies in lighting systems, however, typically require small investment costs and offer short, simple payback periods, due, in part, to federal, state, and utility incentive programs. Recently, however, certain state and federal mandates have reduced the support for and efficacy of electricity utility incentivizing programs. To determine the impact of such support programs, this study examined historical data regarding lighting retrofit savings, implementation costs, and utility rebates gathered from 13 years of industrial energy audits by a U.S. Department of Energy Industrial Assessment Center in …

An Improved Method To Estimate Savings From Thermal Comfort Control In Residences From Smart Wi-Fi Thermostat Data, Abdulelah D. Alhamayani, Qiancheng Sun, Kevin P. Hallinan

Mechanical and Aerospace Engineering Faculty Publications

The net-zero global carbon target for 2050 needs both expansion of renewable energy and substantive energy consumption reduction. Many of the solutions needed are expensive. Controlling HVAC systems in buildings based upon thermal comfort, not just temperature, uniquely offers a means for deep savings at virtually no cost. In this study, a more accurate means to quantify the savings potential in any building in which smart WiFi thermostats are present is developed. Prior research by Alhamayani et al. leveraging such data for individual residences predicted cooling energy savings in the range from 33 to 47%, but this research was based …

Six-Bar Linkage Models Of A Recumbent Tricycle Mechanism To Increase Power Throughput In Fes Cycling, Nicholas A. Lanese, David H. Myszka, Anthony L. Bazler, Andrew P. Murray

Mechanical and Aerospace Engineering Faculty Publications

This paper presents the kinematic and static analysis of two mechanisms to improve power throughput for persons with tetra- or paraplegia pedaling a performance tricycle via FES. FES, or functional electrical stimulation, activates muscles by passing small electrical currents through the muscle creating a contraction. The use of FES can build muscle in patients, relieve soreness, and promote cardiovascular health. Compared to an able-bodied rider, a cyclist stimulated via FES produces an order of magnitude less power creating some notable pedaling difficulties especially pertaining to inactive zones. An inactive zone occurs when the leg position is unable to produce enough …

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

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 …

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

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 …

Self-Learning Algorithm To Predict Indoor Temperature And Cooling Demand From Smart Wifi Thermostat In A Residential Building, Kefan Huang, Kevin Hallinan, Robert Lou, Abdulrahman Alanezi, Salahaldin Alshatshati, Qiancheng Sun

Mechanical and Aerospace Engineering Faculty Publications

Smart WiFi thermostats have moved well beyond the function they were originally designed for; namely, controlling heating and cooling comfort in buildings. They are now also learning from occupant behaviors and permit occupants to control their comfort remotely. This research seeks to go beyond this state of the art by utilizing smart WiFi thermostat data in residences to develop dynamic predictive models for room temperature and cooling/heating demand. These models can then be used to estimate the energy savings from new thermostat temperature schedules and estimate peak load reduction achievable from maintaining a residence in a minimum thermal comfort condition. …

A Machine Learning Framework For Drop-In Volume Swell Characteristics Of Sustainable Aviation Fuel, Shane Kosir, Joshua Heyne, John Graham

Mechanical and Aerospace Engineering Faculty Publications

A machine learning framework has been developed to predict volume swell for 10 non-metallic materials submerged in neat compounds. The non-metallic materials included nitrile rubber, extracted nitrile rubber, fluorosilicone, low temp fluorocarbon, lightweight polysulfide, polythioether, epoxy (0.2 mm), epoxy (0.04 mm), nylon, and Kapton. Volume swell, a material compatibility concern, serves as a significant impediment for the minimization of the greenhouse gas emissions of aviation. Sustainable aviation fuels, the only near and mid-term solution to mitigating greenhouse gas emissions, are limited to low blend limits with conventional fuel due to material compatibility issues (i.e. O-ring swell). A neural network was …

Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey Wagner, Clay Koschnick, Steven Schuldt, Jada Williams, Kevin Hallinan

Mechanical and Aerospace Engineering Faculty Publications

Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal solar panels using 14 months of data collected from 12 northern-hemisphere locations. We performed our data collection and analysis in the absence of irradiation data-an approach not commonly found in prior literature. Using latitude, month, hour, ambient temperature, pressure, humidity, wind speed, and cloud ceiling as independent variables, a distributed random forest regression algorithm modeled the combined …

Sustainable Aviation Fuels Approval Streamlining: Auxiliary Power Unit Lean Blowout Testing, Erin E. Peiffer, Joshua S. Heyne, Meredith Colket

Mechanical and Aerospace Engineering Faculty Publications

An underpinning hindrance in the market penetration of sustainable aviation fuel is the approval process for alternative jet fuels. One solution to this is to develop low-cost screening tools that can be implemented earlier in the approval process. Auxiliary power unit combustors historically show the most sensitivity to physical and volatile fuel properties, making it a useful tool in assessing potential alternative jet fuel effects at test conditions representative of operability stability limits. It is hypothesized that these observations can be explained via timescale analysis considering fuel droplet breakup and evaporation, combustor mixing, and chemical reactivity timescales on the progression …

Special Issue: Selected Papers From Idetc 2017, Andreas Mueller, Andrew Murray, Venkat N. Krovi

Mechanical and Aerospace Engineering Faculty Publications

The Mechanisms and Robotics Conference has traditionally provided a vigorous and stimulating international forum for the exchange of technical and scientific information on the theory and practice of mechanical systems. The topical coverage has span areas central to mechanical systems including design (novel mechanisms and robots, synthesis), analysis (kinematics, dynamics, computational approaches, and software systems), applications (from micro-air vehicles, modular robotics, origami applications, medical robotics, to exoskeleton-assistive systems), and educational practices.

Special Issue: Selected Papers From Idetc 2015, Venkat N. Krovi, Andrew P. Murray, James Schmiedeler

Mechanical and Aerospace Engineering Faculty Publications

This second IDETC Special Issue, containing 19 papers from researchers in seven countries on three continents, seeks to cap- ture the current interest topics and latest results from the 39th ASME Mechanisms and Robotics (M&R) conference. The topics span the synthesis and analysis of novel mechanisms and robots as well as their validation in a variety of applications. The papers are organized with contributions to the core theoretical methodol- ogies of M&R (five papers) appearing first. The application areas that follow are micro air vehicles (MAVs) (two papers), modular robotics (three papers), origami applications (three papers), medi- cal robotics (three …

Simulation Model Of An Automatic Commercial Ice Machine, Haithem Murgham, David Myszka, Vijay Bahel, Rajan Rajendran, Kurt Knapke, Suresh Shivashankar, Kyaw Wynn

Mechanical and Aerospace Engineering Faculty Publications

Automatic commercial ice-making machines that produce a batch of cube ice at regular intervals are known as “cubers." Such machines are commonly used in food service, food preservation, hotel, and health service industries. The machines are typically rated for the weight of ice produced over a 24-hour period at ambient air temperatures of 90°F and water inlet temperature of 70°F.

These cubers typically utilize an air-cooled, vapor-compression cycle to freeze circulating water flowing over an evaporator grid. Once a sufficient amount ice is formed, a valve switches to enable a harvest mode, where the compressor’s discharge gas is routed into …

Evaluation Of Different Optimal Control Problem Formulations For Solving The Muscle Redundancy Problem, Friedl De Groote, Allison Kinney, Anil Rao, Benjamin J. Fregly

Mechanical and Aerospace Engineering Faculty Publications

This study evaluates several possible optimal control problem formulations for solving the muscle redundancy problem with the goal of identifying the most efficient and robust formulation. One novel formulation involves the introduction of additional controls that equal the time derivative of the states, resulting in very simple dynamic equations. The nonlinear equations describing muscle dynamics are then imposed as algebraic constraints in their implicit form, simplifying their evaluation. By comparing different problem formulations for computing muscle controls that can reproduce inverse dynamic joint torques during gait, we demonstrate the efficiency and robustness of the proposed novel formulation.

Synergies Controls Improve Prediction Of Knee Contact Forces And Muscle Excitations During Gait, Benjamin J. Fregly, Jonathan P. Walter, Allison Kinney, Scott A. Banks, Darryl D. D'Lima, Thor F. Besier, David G. Lloyd

Mechanical and Aerospace Engineering Faculty Publications

This study investigates whether use of muscle excitation controls constructed from subjectspecific muscle synergy information can improve optimization prediction of knee contact forces and muscle excitations during walking. Muscle synergies quantify how a large number of experimental muscle electromyographic (EMG) signals can be reconstructed by linearly mixing a much smaller number of neural commands generated by the nervous system. Our hypothesis was that controlling all muscle excitations with a small set of experimentally calculated neural commands would improve prediction of knee contact forces and leg muscle excitations compared to using independently controlled muscle excitations.

End-Of-Life Management Of Crystalline Silicon Photovoltaic Module, Jun-Ki Choi

Mechanical and Aerospace Engineering Faculty Publications

PV manufacturing has been growing over the past 10 years and further annual growth of 15% is expected until 2020. A study on positioning a grand plan for solar power shows how vast PV arrays and other renewable energies can provide significant amount of electricity and total energy needs by 2050. Various new PV technologies have been introduced in the market and existing technologies have undergone further development. How all these developments will affect the fate of the end-of-life PV modules is uncertain. In addition, the market price of some rare earth materials utilized in the manufacturing of the various …

Muscle Synergies Improve Estimation Of Knee Contact Forces During Walking, Benjamin J. Fregly, Jonathan P. Walter, Allison Kinney, Scott A. Banks, Darryl D. D'Lima, Thor F. Besier, David G. Lloyd

Mechanical and Aerospace Engineering Faculty Publications

This study investigates whether use of subject-specific muscle synergies can improve optimization predictions of muscle excitation patterns and knee contact forces during walking. Muscle synergies describe how a small number of neural commands generated by the nervous system can be linearly combined to produce the broad range of muscle electromyographic (EMG) signals measured experimentally. By quantifying the interdependence of individual EMG signals, muscle synergies provide dimensionality reduction for the neural control redundancy problem. Our hypothesis was that use of subjectspecific muscle synergies to limit muscle excitation patterns would improve prediction of muscle EMG patterns at the hip, knee, and ankle …

Engineering Innovation And Design For Stem Teachers And The Stem Quality Framework, James Rowley, Sandi Preiss, Margaret Pinnell, Suzanne Franco

Mechanical and Aerospace Engineering Faculty Publications

The backbone of economic growth in the United States relies on engineering innovation. However, engineering innovation cannot occur without engineers and scientists. Unfortunately however, many K-12 students do not have a good understanding of the engineering design process or the vast field of engineering. As a result, many students lose interest in math and science and do not pursue Science, Technology, Engineering and Math (STEM) fields. This paper will describe a unique partnership among the Teacher Education Program and School of Engineering at the University of Dayton (UD) and the Dayton Regional STEM Center (DRSC). This partnership initiated with the …

The Key Ideas Of Mdw Viii: A Summary, Aaron Altman, Clive L. Dym, Ray Hurwitz, John W. Wesner

Mechanical and Aerospace Engineering Faculty Publications

This paper summarizes and highlights the presentations and discussions that took place during Mudd Design Workshop VIII, ‘Design Education: Innovation and Entrepreneurship,’ at Harvey Mudd College. This paper also describes both the key ideas that emerged from the presentations and discussions of the participating engineering design educators, practitioners and researchers, and the methodology used to capture and retain those ideas. Additionally, this paper proposes a framework of design competencies that were created and evolved by the workshop’s participants as a response to a question posed at one of the workshop sessions: ‘What are the minimum design competencies students should learn …

Encyclopedia Of Mathematics And Society: 'Engineering Design', Kimberly Edginton Bigelow

Mechanical and Aerospace Engineering Faculty Publications

Engineers design everything from automobiles and bridges to prosthetic limbs and sporting equipment. Designing is different from simply building in that it requires the adherence to a very systematic, yet iterative, process known as the “engineering design process.” This process is to engineers what the scientific method is to scientists-guiding steps that help ensure that the end result is the best it can be. When a new product is created without following the steps of the engineering design process, there is a higher likelihood that the product designed will lack some important aspect: the end product may not appropriately account …

In Search Of Something More: My Path Towards International Service-Learning In Engineering Education, Margaret Pinnell

Mechanical and Aerospace Engineering Faculty Publications

My personal and professional travels led me toward global education, in particular the University of Dayton (UD) program Engineers in Technical Humanitarian Opportunities for Service-Learning (ETHOS). I do not believe I ever intended to become part of an international engineering education program. In fact, I think the international piece was just a bonus. What really drew me to the ETHOS program was what initially draws our students to the program - a desire to "help" people. In order for the reader to understand how I ended up being involved in global education through the ETHOS program, I must first explain …

Results Of An Interlaboratory Study Of The Astm Standard Test Method For Tensile Properties Of Polymer Matrix Composites D 3039, Margaret Pinnell, Richard Fields, Ronald Zabora

Mechanical and Aerospace Engineering Faculty Publications

An investigation was conducted on the ASTM Standard Test Method for Tensile Properties of Polymer Matrix Composites (D 3039). This investigation consisted of both preliminary testing and an interlaboratory test program. Information generated from preliminary testing was used to determine the effects of various parameters and to optimize the interlaboratory test plan and test protocol. The interlaboratory study portion of this investigation was conducted on six composite material systems in a variety of lay-up configurations. The number of participating labs ranged from five to nine depending on the material type. Precision statistics were determined for the ASTM D 3039 standard …

Microstructural Study Of Nanoprecipitates In Rra Treated Al-7075 T6 Using Afm/Ufm/Stem, Samuel J.M. Kuhr, Margaret Pinnell, Daniel Eylon

Mechanical and Aerospace Engineering Faculty Publications

7075 T651 aluminum alloy is frequently used in aircraft applications for its high strength to weight ratio. However, aircraft parts made of this alloy have been plagued by stress corrosion cracking (SCC). Retrogression and re-aging (RRA) is a post T651 two-stage heat treatment that provides improved SCC resistance with minimal loss in tensile strength. In this study, various forms of microscopy and mechanical testing are used to investigate how the RRA process affects the microstructure.

The microscopic observations in this paper show that the precipitates in the aluminum alloy coarsen and that the grain boundary regions are depleted of copper …

Electro-Hydrodynamic Pumped Hydraulic Actuation With Application To Active Vibration Control, Ahmad Reza Kashani, Sung Kang, Kevin P. Hallinan

Mechanical and Aerospace Engineering Faculty Publications

A new type of actuation device has been conceptualized that meets the needs of both large displacement, force and bandwidth within a package more compact than currently available magnetostrictive and stack-type piezoelectric actuators of similar rating. This concept relies on micro-scale electrohydrodynamic (EHD) pumping of a dielectric liquid within small channels. Configured as an actuator, the EHD pump(s) would be used to move fluid between two reservoirs—each having a compliant membrane that interfaces to the world to provide the means to achieve vibration cancellation or micro actuation.

Ordinarily limited to generating flow in macroscale applications, the EHD pump, when operating …