Study of carbon nanotube film and shape memory alloys treatment for sensing and structural vibration control

Structural vibration control is of great importance. Current active and passive vibration control strategies usually employ individual elements to fulfill this task, such as viscoelastic patches for providing damping, transducers for picking up signals and actuators for inputting actuating forces. The goal of this dissertation work is to design, manufacture, investigate and apply a new type of multifunctional composite material for structural vibration control. This new composite, which is based on multi-walled carbon nanotube (MWCNT) film, is potentially to function as free layer damping treatment and strain sensor simultaneously. That is, the new material integrates the transducer and the damping patch into one element. The multifunctional composite was prepared by sandwiching the MWCNT film between two adhesive layers. Static sensing test indicated that the MWCNT film sensor resistance changes almost linearly with the applied load. Sensor sensitivity factors were comparable to those of the foil strain gauges. Dynamic test indicated that the MWCNT film sensor can outperform the foil strain gage in high frequency ranges. Temperature test indicated the MWCNT sensor had good temperature stability over the range of 237 K-363 K. The Young’s modulus and shear modulus of the MWCNT film composite were acquired by nanoindentation test and direct shear test, respectively. A free vibration damping test indicated that the MWCNT composite sensor can also provide good damping without adding excessive weight to the base structure. A new model for sandwich structural vibration control was then proposed. In this new configuration, a cantilever beam covered with MWCNT composite on top and one layer of shape memory alloy (SMA) on the bottom was used to illustrate this concept. The MWCNT composite simultaneously serves as free layer damping and strain sensor, and the SMA acts as actuator. Simple on-off controller was designed for controlling the temperature of the SMA so as to control the SMA recovery stress as input and the system stiffness. Both free and forced vibrations were analyzed. Simulation work showed that this new configuration for sandwich structural vibration control was successful especially for low frequency system.

A middleware to support services delivery in a domain-specific virtual machine

The increasing use of model-driven software development has renewed emphasis on using domain-specific models during application development. More specifically, there has been emphasis on using domain-specific modeling languages (DSMLs) to capture user-specified requirements when creating applications. The current approach to realizing these applications is to translate DSML models into source code using several model-to-model and model-to-code transformations. This approach is still dependent on the underlying source code representation and only raises the level of abstraction during development. Experience has shown that developers will many times be required to manually modify the generated source code, which can be error-prone and time consuming. ^ An alternative to the aforementioned approach involves using an interpreted domain-specific modeling language (i-DSML) whose models can be directly executed using a Domain Specific Virtual Machine (DSVM). Direct execution of i-DSML models require a semantically rich platform that reduces the gap between the application models and the underlying services required to realize the application. One layer in this platform is the domain-specific middleware that is responsible for the management and delivery of services in the specific domain. ^ In this dissertation, we investigated the problem of designing the domain-specific middleware of the DSVM to facilitate the bifurcation of the semantics of the domain and the model of execution (MoE) while supporting runtime adaptation and validation. We approached our investigation by seeking solutions to the following sub-problems: (1) How can the domain-specific knowledge (DSK) semantics be separated from the MoE for a given domain? (2) How do we define a generic model of execution (GMoE) of the middleware so that it is adaptable and realizes DSK operations to support delivery of services? (3) How do we validate the realization of DSK operations at runtime? ^ Our research into the domain-specific middleware was done using an i-DSML for the user-centric communication domain, Communication Modeling Language (CML), and for microgrid energy management domain, Microgrid Modeling Language (MGridML). We have successfully developed a methodology to separate the DSK and GMoE of the middleware of a DSVM that supports specialization for a given domain, and is able to perform adaptation and validation at runtime. ^

Modeling of shape memory alloys with plasticity

Shape memory alloys are a special class of metals that can undergo large deformation yet still be able to recover their original shape through the mechanism of phase transformations. However, when they experience plastic slip, their ability to recover their original shape is reduced. This is due to the presence of dislocations generated by plastic flow that interfere with shape recovery through the shape memory effect and the superelastic effect. A one-dimensional model that captures the coupling between shape memory effect, the superelastic effect and plastic deformation is introduced. The shape memory alloy is assumed to have only 3 phases: austenite, positive variant martensite and negative variant martensite. If the SMA flows plastically, each phase will exhibit a dislocation field that permanently prevents a portion of it from being transformed back to other phases. Hence, less of the phase is available for subsequent phase transformations. A constitutive model was developed to depict this phenomena and simulate the effect of plasticity on both the shape memory effect and the superelastic effect in shape memory alloys. In addition, experimental tests were conducted to characterize the phenomenon in shape memory wire and superelastic wire. ^ The constitutive model was then implemented in within a finite element context as UMAT (User MATerial Subroutine) for the commercial finite element package ABAQUS. The model is phenomenological in nature and is based on the construction of stress-temperature phase diagram. ^ The model has been shown to be capable of capturing the qualitative and quantitative aspects of the coupling between plasticity and the shape memory effect and plasticity and the super elastic effect within acceptable limits. As a verification case a simple truss structure was built and tested and then simulated using the FEA constitutive model. The results where found to be close the experimental data. ^

Life history trade-offs and community dynamics of small fishes in a seasonally pulsed wetland

We used a one-dimensional, spatially explicit model to simulate the community of small fishes in the freshwater wetlands of southern Florida, USA. The seasonality of rainfall in these wetlands causes annual fluctuations in the amount of flooded area. We modeled fish populations that differed from each other only in efficiency of resource utilization and dispersal ability. The simulations showed that these trade-offs, along with the spatial and temporal variability of the environment, allow coexistence of several species competing exploitatively for a common resource type. This mechanism, while sharing some characteristics with other mechanisms proposed for coexistence of competing species, is novel in detail. Simulated fish densities resembled patterns observed in Everglades empirical data. Cells with hydroperiods less than 6 months accumulated negligible fish biomass. One unique model result was that, when multiple species coexisted, it was possible for one of the coexisting species to have both lower local resource utilization efficiency and lower dispersal ability than one of the other species. This counterintuitive result is a consequence of stronger effects of other competitors on the superior species.

Time orientation in organizations: Polychronicity and multitasking

This dissertation consists of four studies examining two constructs related to time orientation in organizations: polychronicity and multitasking. The first study investigates the internal structure of polychronicity and its external correlates in a sample of undergraduate students (N = 732). Results converge to support a one-factor model and finds measures of polychronicity to be significantly related to extraversion, agreeableness, and openness to experience. The second study quantitatively reviews the existing research examining the relationship between polychronicity and the Big Five factors of personality. Results reveal a significant relationship between extraversion and openness to experience across studies. Studies three and four examine the usefulness of multitasking ability in the prediction of work related criteria using two organizational samples (N = 175 and 119, respectively). Multitasking ability demonstrated predictive validity, however the incremental validity over that of traditional predictors (i.e., cognitive ability and the Big Five factors of personality) was minimal. The relationships between multitasking ability, polychronicity, and other individual differences were also investigated. Polychronicity and multitasking ability proved to be distinct constructs demonstrating differential relationships with cognitive ability, personality, and performance. Results provided support for multitasking performance as a mediator in the relationship between multitasking ability and overall job performance. Additionally, polychronicity moderated the relationship between multitasking ability and both ratings of multitasking performance and overall job performance in Study four. Clarification of the factor structure of polychronicity and its correlates will facilitate future research in the time orientation literature. Results from two organizational samples point to work related measures of multitasking ability as a worthwhile tool for predicting the performance of job applicants.

A Case Study in Crisis Management: Le Petit Gourmet Catering

The skills of crisis management are more and more valuable in the food service industry. How a manager handles a crisis can spell the difference between success and failure. Finding a good model for crisis management is difficult. The author offers a case study to introduce one such model.

The Next Generation of Scientists: Examining the Experiences of Graduate Students in Network-Level Social-Ecological Science

By integrating the research and resources of hundreds of scientists from dozens of institutions, network-level science is fast becoming one scientific model of choice to address complex problems. In the pursuit to confront pressing environmental issues such as climate change, many scientists, practitioners, policy makers, and institutions are promoting network-level research that integrates the social and ecological sciences. To understand how this scientific trend is unfolding among rising scientists, we examined how graduate students experienced one such emergent social-ecological research initiative, Integrated Science for Society and Environment, within the large-scale, geographically distributed Long Term Ecological Research (LTER) Network. Through workshops, surveys, and interviews, we found that graduate students faced challenges in how they conceptualized and practiced social-ecological research within the LTER Network. We have presented these conceptual challenges at three scales: the individual/project, the LTER site, and the LTER Network. The level of student engagement with and knowledge of the LTER Network was varied, and students faced different institutional, cultural, and logistic barriers to practicing social-ecological research. These types of challenges are unlikely to be unique to LTER graduate students; thus, our findings are relevant to other scientific networks implementing new social-ecological research initiatives.

Ethnic and American identity development: A developmental systems approach

Given the role ethnic identity has as a protective factor against the effects of marginalization and discrimination (Umaña-Taylor, 2011), research longitudinally examining ethnic identity has become of increased importance. However, successful identity development must incorporate elements from both one's ethnic group and from the United States (Berry, 1980). Despite this, relatively few studies have jointly evaluated ethnic and American identity (Schwartz et al., 2012). The current dissertation, guided by three objectives, sought to address this and several other gaps in the literature. First, psychometric properties of the Multigroup Ethnic Identity Measure (MEIM) and the American Identity Measure (AIM) were evaluated. Secondly, the dissertation examined growth trends in recently immigrated Hispanic adolescents' and their caregivers' ethnic and American identity. Lastly, the relationship between adolescents' and caregivers' ethnic and American identity was evaluated. The study used an archival sample consisting of 301 recently immigrated Hispanic families collected from Miami (N = 151) and Los Angeles (N = 150). Consistent with previous research, results in Study 1 indicated a two-factor model reliably provided better fit than a one-factor model and established longitudinal invariance for the MEIM and the AIM. Results from Study 2 found significant growth in adolescents' American identity. While some differences were found across site and nationality, evidence suggested recently immigrated Hispanic adolescents were becoming more bicultural. Counterintuitively, results found a significant decline in caregivers' ethnic identity which future studies should further examine. Finally, results from Study 3, found several significant positive relationships between adolescents' and their caregivers' ethnic and American identity. Findings provided preliminary evidence for the importance of examining identity development within a systemic lens. Despite several limitations, these three studies represented a step forward in addressing the current gaps in the cultural identity literature. Implications for future investigation are discussed.

Time Orientation in Organizations: Polychronicity and Multitasking

This dissertation consists of four studies examining two constructs related to time orientation in organizations: polychronicity and multitasking. The first study investigates the internal structure of polychronicity and its external correlates in a sample of undergraduate students (N = 732). Results converge to support a one-factor model and finds measures of polychronicity to be significantly related to extraversion, agreeableness, and openness to experience. The second study quantitatively reviews the existing research examining the relationship between polychronicity and the Big Five factors of personality. Results reveal a significant relationship between extraversion and openness to experience across studies. Studies three and four examine the usefulness of multitasking ability in the prediction of work related criteria using two organizational samples (N = 175 and 119, respectively). Multitasking ability demonstrated predictive validity, however the incremental validity over that of traditional predictors (i.e., cognitive ability and the Big Five factors of personality) was minimal. The relationships between multitasking ability, polychronicity, and other individual differences were also investigated. Polychronicity and multitasking ability proved to be distinct constructs demonstrating differential relationships with cognitive ability, personality, and performance. Results provided support for multitasking performance as a mediator in the relationship between multitasking ability and overall job performance. Additionally, polychronicity moderated the relationship between multitasking ability and both ratings of multitasking performance and overall job performance in Study four. Clarification of the factor structure of polychronicity and its correlates will facilitate future research in the time orientation literature. Results from two organizational samples point to work related measures of multitasking ability as a worthwhile tool for predicting the performance of job applicants.

A generic model of execution for synthesizing domain-specific models

Software engineering researchers are challenged to provide increasingly more powerful levels of abstractions to address the rising complexity inherent in software solutions. One new development paradigm that places models as abstraction at the forefront of the development process is Model-Driven Software Development (MDSD). MDSD considers models as first class artifacts, extending the capability for engineers to use concepts from the problem domain of discourse to specify apropos solutions. A key component in MDSD is domain-specific modeling languages (DSMLs) which are languages with focused expressiveness, targeting a specific taxonomy of problems. The de facto approach used is to first transform DSML models to an intermediate artifact in a HLL e.g., Java or C++, then execute that resulting code.^ Our research group has developed a class of DSMLs, referred to as interpreted DSMLs (i-DSMLs), where models are directly interpreted by a specialized execution engine with semantics based on model changes at runtime. This execution engine uses a layered architecture and is referred to as a domain-specific virtual machine (DSVM). As the domain-specific model being executed descends the layers of the DSVM the semantic gap between the user-defined model and the services being provided by the underlying infrastructure is closed. The focus of this research is the synthesis engine, the layer in the DSVM which transforms i-DSML models into executable scripts for the next lower layer to process.^ The appeal of an i-DSML is constrained as it possesses unique semantics contained within the DSVM. Existing DSVMs for i-DSMLs exhibit tight coupling between the implicit model of execution and the semantics of the domain, making it difficult to develop DSVMs for new i-DSMLs without a significant investment in resources.^ At the onset of this research only one i-DSML had been created for the user- centric communication domain using the aforementioned approach. This i-DSML is the Communication Modeling Language (CML) and its DSVM is the Communication Virtual machine (CVM). A major problem with the CVM's synthesis engine is that the domain-specific knowledge (DSK) and the model of execution (MoE) are tightly interwoven consequently subsequent DSVMs would need to be developed from inception with no reuse of expertise.^ This dissertation investigates how to decouple the DSK from the MoE and subsequently producing a generic model of execution (GMoE) from the remaining application logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis component of i-DSML interpreters utilizes a reusable framework loosely coupled to DSK as swappable framework extensions.^ This approach involves first creating an i-DSML and its DSVM for a second do- main, demand-side smartgrid, or microgrid energy management, and designing the synthesis engine so that the DSK and MoE are easily decoupled. To validate the utility of the approach, the SEs are instantiated using the GMoE and DSKs of the two aforementioned domains and an empirical study to support our claim of reduced developmental effort is performed.^

A Generic Model of Execution for Synthesizing Domain-Specific Models

Software engineering researchers are challenged to provide increasingly more pow- erful levels of abstractions to address the rising complexity inherent in software solu- tions. One new development paradigm that places models as abstraction at the fore- front of the development process is Model-Driven Software Development (MDSD). MDSD considers models as first class artifacts, extending the capability for engineers to use concepts from the problem domain of discourse to specify apropos solutions. A key component in MDSD is domain-specific modeling languages (DSMLs) which are languages with focused expressiveness, targeting a specific taxonomy of problems. The de facto approach used is to first transform DSML models to an intermediate artifact in a HLL e.g., Java or C++, then execute that resulting code. Our research group has developed a class of DSMLs, referred to as interpreted DSMLs (i-DSMLs), where models are directly interpreted by a specialized execution engine with semantics based on model changes at runtime. This execution engine uses a layered architecture and is referred to as a domain-specific virtual machine (DSVM). As the domain-specific model being executed descends the layers of the DSVM the semantic gap between the user-defined model and the services being provided by the underlying infrastructure is closed. The focus of this research is the synthesis engine, the layer in the DSVM which transforms i-DSML models into executable scripts for the next lower layer to process. The appeal of an i-DSML is constrained as it possesses unique semantics contained within the DSVM. Existing DSVMs for i-DSMLs exhibit tight coupling between the implicit model of execution and the semantics of the domain, making it difficult to develop DSVMs for new i-DSMLs without a significant investment in resources. At the onset of this research only one i-DSML had been created for the user- centric communication domain using the aforementioned approach. This i-DSML is the Communication Modeling Language (CML) and its DSVM is the Communication Virtual machine (CVM). A major problem with the CVM’s synthesis engine is that the domain-specific knowledge (DSK) and the model of execution (MoE) are tightly interwoven consequently subsequent DSVMs would need to be developed from inception with no reuse of expertise. This dissertation investigates how to decouple the DSK from the MoE and sub- sequently producing a generic model of execution (GMoE) from the remaining appli- cation logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis com- ponent of i-DSML interpreters utilizes a reusable framework loosely coupled to DSK as swappable framework extensions. This approach involves first creating an i-DSML and its DSVM for a second do- main, demand-side smartgrid, or microgrid energy management, and designing the synthesis engine so that the DSK and MoE are easily decoupled. To validate the utility of the approach, the SEs are instantiated using the GMoE and DSKs of the two aforementioned domains and an empirical study to support our claim of reduced developmental effort is performed.