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Department of Mechanical Engineering

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These digital collections include theses, dissertations, faculty publications, and datasets from the Department of Mechanical Engineering.

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Browsing Department of Mechanical Engineering by Author "Alciatore, David G., committee member"

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    Anticipation enhanced behavior-based robotics using integrated system dynamics
    (Colorado State University. Libraries, 2017) Hopper, Douglas A., author; Troxell, Wade O., advisor; Alciatore, David G., committee member; Heyliger, Paul R., committee member; Bjostad, Lou B., committee member
    Behavior-based robotics specifies behavior as the interaction between the task, environment, and agent with specific capabilities that creates a successful behavior to attain task achievement. Observed task achieving behavior is confirmed and validated by a prespecified performance criteria. For behavior-based robotics, conditions in the niche environment are directly matched to and cue behavior choice that yields task achievement by the robot agent. A minimalist approach attains this behavior choice from only a few possible scenarios for the niche environment and a simple associated response. Previous work in behavior-based robotics has been generally limited to a reactive response to environmental conditions, with little or no notion of looking ahead to potential successful future outcomes. Focus on the notion of anticipation provides a novel addition to the task achieving behavior-based robotics approach. Anticipation is the formulation of suitable processes to manifest behavior from a small set of feasible scenarios in the near future before the outcome is certain. Anticipation results in successful behavior beyond mere reactions to niche conditions that leads to desired task achievement with expected perceived immediate or later reward based on suitable fitness matched to the niche. The approach to add anticipation developed a formal system dynamics model to represent previously known behavior archetypes, extended them with the notion of anticipation, and enhanced the system dynamics operation. Simulation of a robot instance using anticipation for wall following, called the TOURIST, was conducted to gain insight into behaviors that would be observable in a real world natural system. Simulation of the TOURIST robot with anticipation built into the archetype programming illustrated the advantages of including the notion of anticipation. Anticipation allows a TOURIST robot agent to travel a smoother path and make choice of small increments in behavior change that produce more desired longer term responses. With anticipation, numerous small adjustments are made that require less energy than large spins of the SEEK behavior, so only one third of the SEEK behaviors occur, and thus wastes less energy and time. Also with anticipation, the TOURIST makes twice as many cycles of the area at the same speed and in the same time, so a broader range of area is covered and can more readily perceive any dynamic changes in the overall arena. The methods and insights were added to a real world robot instance, and the benefits of anticipation were observed to occur. A specific metric, ANNum, was developed for describing operation of the TOURIST robot. Greater metric values were found with anticipation on, reflecting more behavior responsiveness to the niche per unit time when anticipation was used. In conclusion, anticipation enhances robotic performance by manifesting task achieving behavior that is properly matched to a specific niche condition. Anticipation extends beyond the merely reactive behavior previously used in behavior-based robotics by acting like a funnel or channel to guide the behavior choice to match a specific niche. The observed behavior choice is manifest before the outcome is realized and certain to occur. As a practical result, the robot agent is able to make many smaller adjustments earlier and faster with better chance for desired outcome than would be observed without anticipation. It circumvents repeated larger adjustments that waste more resources and take more time for task achievement. Such enhanced anticipation behavior avoids obstructions and potential destructive paths or motion, and is more able to achieve tasks such as to find objects and move along walls with minimal effort. Thus, anticipation that is added to robot architecture improves behavior choices to realize desired task achievement. Future work could add anticipation to real world practical automation and robotics to further test the improved operation with anticipation. In summary, anticipation observed in a robot agent should act before the outcome is known, make timely small adjustments toward a goal, and appear as if the future were known ahead of time.
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    Application of structural health monitoring for damage identification in an industrial fan rotor using in-situ modal analysis testing
    (Colorado State University. Libraries, 2014) Wilcox, Chad M., author; Willson, Bryan D., advisor; Alciatore, David G., committee member; Bienkiewicz, Bogusz J., committee member
    A testing procedure is desired which can be applied in manufacturing environments to determine the structural integrity of rotating components within a machine. Current non-destructive evaluation (NDE) of components includes visual inspection, dye penetrant, and x-ray testing. Each of these NDE techniques have limitations in manufacturing plants given very limited time frames and access to rotating components. Vibration condition monitoring is widely used and accepted as a beneficial way to determine faults in rotating equipment. Current vibration condition monitoring practices rely on measurement and analysis of response data. The response data is affected by both changing forces and structural parameters of the system being measured. Therefore, determining whether forces have changed or the structure has been compromised is not readily determined from vibration condition monitoring data. Structural health monitoring (SHM) has been implemented for a variety of structural faults including: cracking and breaking, loosening of assembled parts, flaws and voids caused by manufacturing, and improper assembly of parts (Wolff & Richardson, 1989). Many studies in the area of SHM have focused on idealized test setups and have used only simulated data. This study focuses on implementation of SHM on the rotating assembly of an industrial fan. The data and results from SHM are used to validate whether or not the structure has been compromised.
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    The bids-evaluation decision model development and application for PPP transport projects: a project risks modeling framework
    (Colorado State University. Libraries, 2010) Jang, Guan-wei, author; Duff, William S., advisor; Alciatore, David G., committee member; Labadie, John W., committee member; Puttlitz, Christian Matthew, committee member
    Public-private partnership (PPP) infrastructure projects play a key role in economic growth. Value for money (VFM), a core objective when conducting PPP projects, is defined as the optimal combination of whole life costs and benefits of the project to meet user requirements. The PPP infrastructure projects are generally very complex and have highly dynamic, interdependent risks and uncertainties that occur over the life cycle of a project. By using PPP arrangements, experts transfer and allocate risks to the party who is most capable of managing them in a cost effective manner. This requires the optimization of risk allocation between the public and private sectors in order to achieve the best VFM. Risk assessment is a critical element when selecting a project partner and examining projected VFM performance. Unfortunately, the current contractor selection methods used in the industry do not address interdependently dynamic and non-linear risk interactions. Such methods are unable to address unstructured or even semi-structured real world problems. By using these methods, experts often lack the global perspectives of project life cycles and ignore the uncertainty of project performance outcomes. This researcher developed a theoretical approach which applied hybrid techniques to a bidding proposal selection model from the public perspective. Using System Dynamics modeling and relevant statistical techniques, the dynamic risk interactions and interdependencies over project construction and operation phases were addressed and quantified. By employing Monte Carlo simulation, this researcher estimated the probability distribution of the overall project net present value (NPV) with compounding both downside and beneficial effects over project construction and operation phases. By applying appropriate decision making methods to compare the probability distribution of NPV among the bidding proposals, a capable contractor can be selected.