Numerical heat transfer analysis of carbon-based foams for use in thermal protection system

The applicability of carbon-based foams as an insulating or active cooling material in thermal protection systems (TPSs) of space vehicles is considered using a computer modeling. This study focuses on numerical investigation of the performance of carbon foams for use in TPSs of space vehicles. Two kinds of carbon foams are considered in this study. For active cooling, the carbon foam that has a thermal conductivity of 100 W/m-k is used and for the insulation, the carbon foam having a thermal conductivity of 0.225 W/m-k is used. A 3D geometry is employed to simulate coolant flow and heat transfer through carbon foam model. Gambit has been used to model the 3D geometry and the numerical simulation is carried out in FLUENT. Numerical results from this thesis suggests that the use of CFOAM and HTC carbon foams in TPS's may effectively protect the aluminum structure of the space shuttle during reentry of the space vehicle.

Design and analysis of a folded meander dipole antenna using the MININEC program

The Mini-Numerical Electromagnetic Code (MININEC) program, a PC-Compatible version of the powerful NEC program, is used to design a new type of reduced-size antenna. The validity of the program to model simple well-known antennas, such as dipoles and monopoles, is first shown. More complex geometries such as folded dipoles, and meander dipole antennas are also analysed using the program. The final design geometry of a meander folded dipole is characterized with MININEC, yielding results that serve as the basis for the practical construction of the antenna. Finally, the laboratory work with a prototype antenna is described, and practical results are presented.

The development and analysis of a field project model curriculum and its impact on achievement and attitude toward science and the environment with at-risk eleventh and twelfth grade students

This study was an evaluation of a Field Project Model Curriculum and its impact on achievement, attitude toward science, attitude toward the environment, self-concept, and academic self-concept with at-risk eleventh and twelfth grade students. One hundred eight students were pretested and posttested on the Piers-Harris Children's Self-Concept Scale, PHCSC (1985); the Self-Concept as a Learner Scale, SCAL (1978); the Marine Science Test, MST (1987); the Science Attitude Inventory, SAI (1970); and the Environmental Attitude Scale, EAS (1972). Using a stratified random design, three groups of students were randomly assigned according to sex and stanine level, to three treatment groups. Group one received the field project method, group two received the field study method, and group three received the field trip method. All three groups followed the marine biology course content as specified by Florida Student Performance Objectives and Frameworks. The intervention occurred for ten months with each group participating in outside-of-classroom activities on a trimonthly basis. Analysis of covariance procedures were used to determine treatment effects. F-ratios, p-levels and t-tests at p $<$.0062 (.05/8) indicated that a significant difference existed among the three treatment groups. Findings indicated that groups one and two were significantly different from group three with group one displaying significantly higher results than group two. There were no significant differences between males and females in performance on the five dependent variables. The tenets underlying environmental education are congruent with the recommendations toward the reform of science education. These include a value analysis approach, inquiry methods, and critical thinking strategies that are applied to environmental issues. ^

A framework for specification and analysis of software architectures

Software architecture is the abstract design of a software system. It plays a key role as a bridge between requirements and implementation, and is a blueprint for development. The architecture represents a set of early design decisions that are crucial to a system. Mistakes in those decisions are very costly if they remain undetected until the system is implemented and deployed. This is where formal specification and analysis fits in. Formal specification makes sure that an architecture design is represented in a rigorous and unambiguous way. Furthermore, a formally specified model allows the use of different analysis techniques for verifying the correctness of those crucial design decisions. ^ This dissertation presented a framework, called SAM, for formal specification and analysis of software architectures. In terms of specification, formalisms and mechanisms were identified and chosen to specify software architecture based on different analysis needs. Formalisms for specifying properties were also explored, especially in the case of non-functional properties. In terms of analysis, the dissertation explored both the verification of functional properties and the evaluation of non-functional properties of software architecture. For the verification of functional property, methodologies were presented on how to apply existing model checking techniques on a SAM model. For the evaluation of non-functional properties, the dissertation first showed how to incorporate stochastic information into a SAM model, and then explained how to translate the model to existing tools and conducts the analysis using those tools. ^ To alleviate the analysis work, we also provided a tool to automatically translate a SAM model for model checking. All the techniques and methods described in the dissertation were illustrated by examples or case studies, which also served a purpose of advocating the use of formal methods in practice. ^

An approach for design and analysis of User-centric Communication Middleware

Today, the development of domain-specific communication applications is both time-consuming and error-prone because the low-level communication services provided by the existing systems and networks are primitive and often heterogeneous. Multimedia communication applications are typically built on top of low-level network abstractions such as TCP/UDP socket, SIP (Session Initiation Protocol) and RTP (Real-time Transport Protocol) APIs. The User-centric Communication Middleware (UCM) is proposed to encapsulate the networking complexity and heterogeneity of basic multimedia and multi-party communication for upper-layer communication applications. And UCM provides a unified user-centric communication service to diverse communication applications ranging from a simple phone call and video conferencing to specialized communication applications like disaster management and telemedicine. It makes it easier to the development of domain-specific communication applications. The UCM abstraction and API is proposed to achieve these goals. The dissertation also tries to integrate the formal method into UCM development process. The formal model is created for UCM using SAM methodology. Some design errors are found during model creation because the formal method forces to give the precise description of UCM. By using the SAM tool, formal UCM model is translated to Promela formula model. In the dissertation, some system properties are defined as temporal logic formulas. These temporal logic formulas are manually translated to promela formulas which are individually integrated with promela formula model of UCM and verified using SPIN tool. Formal analysis used here helps verify the system properties (for example multiparty multimedia protocol) and dig out the bugs of systems.

Dynamic modeling and analysis of single-stage boost inverters under normal and abnormal conditions

Inverters play key roles in connecting sustainable energy (SE) sources to the local loads and the ac grid. Although there has been a rapid expansion in the use of renewable sources in recent years, fundamental research, on the design of inverters that are specialized for use in these systems, is still needed. Recent advances in power electronics have led to proposing new topologies and switching patterns for single-stage power conversion, which are appropriate for SE sources and energy storage devices. The current source inverter (CSI) topology, along with a newly proposed switching pattern, is capable of converting the low dc voltage to the line ac in only one stage. Simple implementation and high reliability, together with the potential advantages of higher efficiency and lower cost, turns the so-called, single-stage boost inverter (SSBI), into a viable competitor to the existing SE-based power conversion technologies.^ The dynamic model is one of the most essential requirements for performance analysis and control design of any engineering system. Thus, in order to have satisfactory operation, it is necessary to derive a dynamic model for the SSBI system. However, because of the switching behavior and nonlinear elements involved, analysis of the SSBI is a complicated task.^ This research applies the state-space averaging technique to the SSBI to develop the state-space-averaged model of the SSBI under stand-alone and grid-connected modes of operation. Then, a small-signal model is derived by means of the perturbation and linearization method. An experimental hardware set-up, including a laboratory-scaled prototype SSBI, is built and the validity of the obtained models is verified through simulation and experiments. Finally, an eigenvalue sensitivity analysis is performed to investigate the stability and dynamic behavior of the SSBI system over a typical range of operation. ^

Investigating Race and Ethnicity on Data Collection and Analysis

This paper details the research methods an introductory qualitative research class used to both study an issue related to race and identity, and to familiarize themselves with data collection strategies. Throughout the paper the authors attempt to capture the challenges, disagreements, and consensus building that marked this unusual research endeavor.

Formal modeling and analysis techniques for high level Petri nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. ^ There are two issues in using HLPNs—modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. ^ For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. ^ For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. ^ The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.^

Design and analysis of micro-channel heat-exchanger embedded in Low Temperature Co-fire Ceramic (LTCC)

Increased device density, switching speeds of integrated circuits and decrease in package size is placing new demands for high power thermal-management. The convectional method of forced air cooling with passive heat sink can handle heat fluxes up-to 3-5W/cm2; however current microprocessors are operating at levels of 100W/cm2, This demands the usage of novel thermal-management systems. In this work, water-cooling systems with active heat sink are embedded in the substrate. The research involved fabricating LTCC substrates of various configurations - an open-duct substrate, the second with thermal vias and the third with thermal vias and free-standing metal columns and metal foil. Thermal testing was performed experimentally and these results are compared with CFD results. An overall thermal resistance for the base substrate is demonstrated to be 3.4oC/W-cm2. Addition of thermal vias reduces the effective resistance of the system by 7times and further addition of free standing columns reduced it by 20times.

Simulation and analysis of network traffic for efficient and reliable information transfer

With the growing commercial importance of the Internet and the development of new real-time, connection-oriented services like IP-telephony and electronic commerce resilience is becoming a key issue in the design of TP-based networks. Two emerging technologies, which can accomplish the task of efficient information transfer, are Multiprotocol Label Switching (MPLS) and Differentiated Services. A main benefit of MPLS is the ability to introduce traffic-engineering concepts due to its connection-oriented characteristic. With MPLS it is possible to assign different paths for packets through the network. Differentiated services divides traffic into different classes and treat them differently, especially when there is a shortage of network resources. In this thesis, a framework was proposed to integrate the above two technologies and its performance in providing load balancing and improving QoS was evaluated. Simulation and analysis of this framework demonstrated that the combination of MPLS and Differentiated services is a powerful tool for QoS provisioning in IP networks.

Formal Modeling and Analysis Techniques for High Level Petri Nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. There are two issues in using HLPNs - modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.

Analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

A qualitative analysis of the congruency of Jungian psychological preferences identified by the Myers-Briggs Type Indicator (MBTI) and the human resource development role of instructor/facilitator

The purpose of this ethnographic study was to describe and explain the congruency of psychological preferences identified by the Myers-Briggs Type Indicator (MBTI) and the human resource development (HRD) role of instructor/facilitator. This investigation was conducted with 23 HRD professionals who worked in the Miami, Florida area as instructors/facilitators with adult learners in job-related contexts.^ The study was conducted using qualitative strategies of data collection and analysis. The research participants were selected through a purposive sampling strategy. Data collection strategies included: (a) administration and scoring of the MBTI, Form G, (b) open-ended and semi-structured interviews, (c) participant observations of the research subjects at their respective work sites and while conducting training sessions, (d) field notes, and (e) contact summary sheets to record field research encounters. Data analysis was conducted with the use of a computer program for qualitative analysis called FolioViews 3.1 for Windows. This included: (a) coding of transcribed interviews and field notes, (b) theme analysis, (c) memoing, and (d) cross-case analysis.^ The three major themes that emerged in relation to the congruency of psychological preferences and the role of instructor/facilitator were: (1) designing and preparing instruction/facilitation, (2) conducting training and managing group process, and (3) interpersonal relations and perspectives among instructors/facilitators.^ The first two themes were analyzed through the combination of the four Jungian personality functions. These combinations are: sensing-thinking (ST), sensing-feeling (SF), intuition-thinking (NT), and intuition-feeling (NF). The third theme was analyzed through the combination of the attitudes or energy focus and the judgment function. These combinations are: extraversion-thinking (ET), extraversion-feeling (EF), introversion-thinking (IT), and introversion-feeling (IF).^ A last area uncovered by this ethnographic study was the influence exerted by a training and development culture on the instructor/facilitator role. This professional culture is described and explained in terms of the shared values and expectations reported by the study respondents. ^

Statistical analysis and meta-analysis of microarray data

The microarray technology provides a high-throughput technique to study gene expression. Microarrays can help us diagnose different types of cancers, understand biological processes, assess host responses to drugs and pathogens, find markers for specific diseases, and much more. Microarray experiments generate large amounts of data. Thus, effective data processing and analysis are critical for making reliable inferences from the data. ^ The first part of dissertation addresses the problem of finding an optimal set of genes (biomarkers) to classify a set of samples as diseased or normal. Three statistical gene selection methods (GS, GS-NR, and GS-PCA) were developed to identify a set of genes that best differentiate between samples. A comparative study on different classification tools was performed and the best combinations of gene selection and classifiers for multi-class cancer classification were identified. For most of the benchmarking cancer data sets, the gene selection method proposed in this dissertation, GS, outperformed other gene selection methods. The classifiers based on Random Forests, neural network ensembles, and K-nearest neighbor (KNN) showed consistently god performance. A striking commonality among these classifiers is that they all use a committee-based approach, suggesting that ensemble classification methods are superior. ^ The same biological problem may be studied at different research labs and/or performed using different lab protocols or samples. In such situations, it is important to combine results from these efforts. The second part of the dissertation addresses the problem of pooling the results from different independent experiments to obtain improved results. Four statistical pooling techniques (Fisher inverse chi-square method, Logit method. Stouffer's Z transform method, and Liptak-Stouffer weighted Z-method) were investigated in this dissertation. These pooling techniques were applied to the problem of identifying cell cycle-regulated genes in two different yeast species. As a result, improved sets of cell cycle-regulated genes were identified. The last part of dissertation explores the effectiveness of wavelet data transforms for the task of clustering. Discrete wavelet transforms, with an appropriate choice of wavelet bases, were shown to be effective in producing clusters that were biologically more meaningful. ^