Modelling short crack growth behaviour in nickel-base superalloys

This paper provides a description of the features and mechanisms of facetted short crack growth in Ni-base superalloys, and briefly reviews existing short crack growth models in terms of their application to Ni-base alloys. The concept of “soft barriers” is introduced to produce a new two-phase model for local microstructural effects on short crack growth in Waspaloy. This is derived from detailed observations of crack growth through individual grains. The model differs from all previous approaches in highlighting the importance of crack path perturbations within grains. Potential applications of the model in alloy development are discussed.

Conceptual Information Compression and Efficient Pattern Search

This paper introduces an encoding of knowledge representation statements as regular languages and proposes a two-phase approach to processing of explicitly declared conceptual information. The idea is presented for the simple conceptual graphs where conceptual pattern search is implemented by the so called projection operation. Projection calculations are organised into off-line preprocessing and run-time computations. This enables fast run-time treatment of NP-complete problems, given that the intermediate results of the off-line phase are kept in suitable data structures. The experiments with randomly-generated, middle-size knowledge bases support the claim that the suggested approach radically improves the run-time conceptual pattern search.

A hybrid molecular dynamics/fluctuating hydrodynamics method for modelling liquids at multiple scales in space and time

A new 3D implementation of a hybrid model based on the analogy with two-phase hydrodynamics has been developed for the simulation of liquids at microscale. The idea of the method is to smoothly combine the atomistic description in the molecular dynamics zone with the Landau-Lifshitz fluctuating hydrodynamics representation in the rest of the system in the framework of macroscopic conservation laws through the use of a single "zoom-in" user-defined function s that has the meaning of a partial concentration in the two-phase analogy model. In comparison with our previous works, the implementation has been extended to full 3D simulations for a range of atomistic models in GROMACS from argon to water in equilibrium conditions with a constant or a spatially variable function s. Preliminary results of simulating the diffusion of a small peptide in water are also reported.

A novel algorithm of posture best fit based on key characteristics for large components assembly

Measurement and variation control of geometrical Key Characteristics (KCs), such as flatness and gap of joint faces, coaxiality of cabin sections, is the crucial issue in large components assembly from the aerospace industry. Aiming to control geometrical KCs and to attain the best fit of posture, an optimization algorithm based on KCs for large components assembly is proposed. This approach regards the posture best fit, which is a key activity in Measurement Aided Assembly (MAA), as a two-phase optimal problem. In the first phase, the global measurement coordinate system of digital model and shop floor is unified with minimum error based on singular value decomposition, and the current posture of components being assembly is optimally solved in terms of minimum variation of all reference points. In the second phase, the best posture of the movable component is optimally determined by minimizing multiple KCs' variation with the constraints that every KC respectively conforms to its product specification. The optimal models and the process procedures for these two-phase optimal problems based on Particle Swarm Optimization (PSO) are proposed. In each model, every posture to be calculated is modeled as a 6 dimensional particle (three movement and three rotation parameters). Finally, an example that two cabin sections of satellite mainframe structure are being assembled is selected to verify the effectiveness of the proposed approach, models and algorithms. The experiment result shows the approach is promising and will provide a foundation for further study and application. © 2013 The Authors.

Online sensorless position estimation for switched reluctance motors using one current sensor

This paper proposes an online sensorless rotor position estimation technique for switched reluctance motors (SRMs) using just one current sensor. It is achieved by first decoupling the excitation current from the bus current. Two phase-shifted pulse width modulation signals are injected into the relevant lower transistors in the asymmetrical half-bridge converter for short intervals during each current fundamental cycle. Analog-to-digital converters are triggered in the pause middles of the dual pulse to separate the bus current for excitation current recognition. Next, the rotor position is estimated from the excitation current, by a current-rise-time method in the current-chopping-control mode in a low-speed operation and a current-gradient method in the voltage-pulse-control mode in a high-speed operation. The proposed scheme requires only a bus current sensor and a minor change to the converter circuit, without a need for individual phase current sensors or additional detection devices, achieving a more compact and cost-effective drive. The performance of the sensorless SRM drive is fully investigated. The simulation and experiments on a 750-W three-phase 12/8-pole SRM are carried out to verify the effectiveness of the proposed scheme.

Fault diagnosis scheme for open-circuit faults in switched reluctance motor drives using fast Fourier transform algorithm with bus current detection

Reliability of power converters is of crucial importance in switched reluctance motor drives used for safety-critical applications. Open-circuit faults in power converters will cause the motor to run in unbalanced states, and if left untreated, they will lead to damage to the motor and power modules, and even cause a catastrophic failure of the whole drive system. This study is focused on using a single current sensor to detect open-circuit faults accurately. An asymmetrical half-bridge converter is considered in this study and the faults of single-phase open and two-phase open are analysed. Three different bus positions are defined. On the basis of a fast Fourier transform algorithm with Blackman window interpolation, the bus current spectrums before and after open-circuit faults are analysed in details. Their fault characteristics are extracted accurately by the normalisations of the phase fundamental frequency component and double phase fundamental frequency component, and the fault characteristics of the three bus detection schemes are also compared. The open-circuit faults can be located by finding the relationship between the bus current and rotor position. The effectiveness of the proposed diagnosis method is validated by the simulation results and experimental tests.

3D simulation of the effects of sphericity on char entrainment in fluidised beds

The paper presents a 3-dimensional simulation of the effect of particle shape on char entrainment in a bubbling fluidised bed reactor. Three char particles of 350 μm side length but of different shapes (cube, sphere, and tetrahedron) are injected into the fluidised bed and the momentum transport from the fluidising gas and fluidised sand is modelled. Due to the fluidising conditions, reactor design and particle shape the char particles will either be entrained from the reactor or remain inside the bubbling bed. The sphericity of the particles is the factor that differentiates the particle motion inside the reactor and their efficient entrainment out of it. The simulation has been performed with a completely revised momentum transport model for bubble three-phase flow, taking into account the sphericity factors, and has been applied as an extension to the commercial finite volume code FLUENT 6.3. © 2010 Elsevier B.V.All rights reserved.

Longitudinal effects of family factors on alcohol use and alcohol-related problems among males from pre-adolescence to adulthood

The goal of this study was to examine the longitudinal effects of five family factors on alcohol use among adolescent males. The family factors included familism (family pride, loyalty, and cohesion), parent derogation (being put down by parents), parent/child communication, family alcohol problems and family drug problems. The study focused on the effects of the family factors reported by a sample of 451 White-non-Hispanic and African American males during early and mid-adolescence on (1) the intensity of alcohol use in mid-adolescence, and (2) the number of problems associated with alcohol use during the transition to young adulthood. The study also explored racial differences in the effects of the family factors. The data for this study were derived from a two-phase longitudinal epidemiologic cohort study of male and female adolescents enrolled in middle schools in Miami, FL. Data were collected at four points between 1990 and 2001. Linear and logistical regressions were used to analyze the effects of the family variables on the dependent variables. ^ The results of the analyses indicated that all of the family variables except family drug problems were statistically significant predictors of the level of alcohol use and alcohol-related problems. Familism had a moderate influence on both of the dependent variables at all data points, while parent derogation, parent/child communication and family alcohol problems were weak predictors. While the family factors varied by race, their impact on the dependent variables did not vary substantially. ^ This study had methodological shortcomings related to measurement and design that may have contributed to the weak influence of the variables. Future studies should explore possible mediating effects of these variables, and should employ more sensitive measures that are culturally appropriate. The results suggest that, since early family factors have long-term effects on children's substance-using behaviors, the family environment should be addressed in prevention and intervention efforts. ^

Computational modeling of intermediate temperature proton exchange membrane (PEM) fuel cells

A two-phase three-dimensional computational model of an intermediate temperature (120--190°C) proton exchange membrane (PEM) fuel cell is presented. This represents the first attempt to model PEM fuel cells employing intermediate temperature membranes, in this case, phosphoric acid doped polybenzimidazole (PBI). To date, mathematical modeling of PEM fuel cells has been restricted to low temperature operation, especially to those employing Nafion ® membranes; while research on PBI as an intermediate temperature membrane has been solely at the experimental level. This work is an advancement in the state of the art of both these fields of research. With a growing trend toward higher temperature operation of PEM fuel cells, mathematical modeling of such systems is necessary to help hasten the development of the technology and highlight areas where research should be focused.^ This mathematical model accounted for all the major transport and polarization processes occurring inside the fuel cell, including the two phase phenomenon of gas dissolution in the polymer electrolyte. Results were presented for polarization performance, flux distributions, concentration variations in both the gaseous and aqueous phases, and temperature variations for various heat management strategies. The model predictions matched well with published experimental data, and were self-consistent.^ The major finding of this research was that, due to the transport limitations imposed by the use of phosphoric acid as a doping agent, namely low solubility and diffusivity of dissolved gases and anion adsorption onto catalyst sites, the catalyst utilization is very low (∼1--2%). Significant cost savings were predicted with the use of advanced catalyst deposition techniques that would greatly reduce the eventual thickness of the catalyst layer, and subsequently improve catalyst utilization. The model also predicted that an increase in power output in the order of 50% is expected if alternative doping agents to phosphoric acid can be found, which afford better transport properties of dissolved gases, reduced anion adsorption onto catalyst sites, and which maintain stability and conductive properties at elevated temperatures.^

Ensemble fuzzy belief intrusion detection design

With the rapid growth of the Internet, computer attacks are increasing at a fast pace and can easily cause millions of dollar in damage to an organization. Detecting these attacks is an important issue of computer security. There are many types of attacks and they fall into four main categories, Denial of Service (DoS) attacks, Probe, User to Root (U2R) attacks, and Remote to Local (R2L) attacks. Within these categories, DoS and Probe attacks continuously show up with greater frequency in a short period of time when they attack systems. They are different from the normal traffic data and can be easily separated from normal activities. On the contrary, U2R and R2L attacks are embedded in the data portions of the packets and normally involve only a single connection. It becomes difficult to achieve satisfactory detection accuracy for detecting these two attacks. Therefore, we focus on studying the ambiguity problem between normal activities and U2R/R2L attacks. The goal is to build a detection system that can accurately and quickly detect these two attacks. In this dissertation, we design a two-phase intrusion detection approach. In the first phase, a correlation-based feature selection algorithm is proposed to advance the speed of detection. Features with poor prediction ability for the signatures of attacks and features inter-correlated with one or more other features are considered redundant. Such features are removed and only indispensable information about the original feature space remains. In the second phase, we develop an ensemble intrusion detection system to achieve accurate detection performance. The proposed method includes multiple feature selecting intrusion detectors and a data mining intrusion detector. The former ones consist of a set of detectors, and each of them uses a fuzzy clustering technique and belief theory to solve the ambiguity problem. The latter one applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The final decision is a combination of the outputs of feature selecting and data mining detectors. The experimental results indicate that our ensemble approach not only significantly reduces the detection time but also effectively detect U2R and R2L attacks that contain degrees of ambiguous information.

Caring and being cared -for: Perceptions of adolescent males at -risk for school failure

This qualitative study used grounded theory methods and purposeful sampling to explore perceptions on caring and being cared-for. Twenty-four adolescent male participants, identified as at-risk for school failure, completed a two phase interview process exploring these phenomena within three relationships; the relationship with the friend, with the most caring person they knew and with the teacher they felt cared for them. ^ Each participant was asked a predetermined set of open questions in an initial semi-structured interview. In addition each participant was encouraged to explore his own reflections on caring. A second interview allowed for member checking and for the participant to continue sharing his meaning of caring and being cared-for. ^ Line by line analysis with open, axial and selective coding was applied to interview transcripts along with a constant comparative method. Results indicated that the core category integrating all other categories was attachment bonding. Participants' stories manifested characteristics of proximity seeking, secure base, safe haven and distress upon involuntary separation from an attachment figure. ^ Strategies facilitating attachment bonding were influenced by the power positions of the relational players. Participants responded positively to the one-caring when they felt cared-for. Results further indicated that participants did not need to feel a sense of belonging in order to feel cared-for. Teacher behaviors indicating openness for authentic connections with students were specific to teacher's friendliness and professional competence. Teachers who nurtured feelings of being cared-for were uncommon in the participants' educational experience. ^ The number of adolescent males leaving high school prematurely is both a personal problem and a social problem. Despite a “mask” of indifference often exhibited by adolescent males at-risk for school failure, teachers might consider the social/emotional needs of these students when implementing the curriculum. In addition, policy makers might consider the social/emotional needs of this vulnerable population when developing programs meant to foster psychological well-being and connectedness for adolescent males at-risk for school failure. ^

Teachers' experiences in and perceptions of their 12th-grade British literature classrooms

The purpose of this study was to understand the experiences and perceptions of 12th-grade literature teachers about curriculum, Post-Colonial literature, and students. Theories posed by Piaget (1995), Vygotsky (1995), and Rosenblatt (1995) formed the framework for this micro-ethnographic study. Seven teachers from public and private schools in South Florida participated in this two-phase study; three teachers in Phase I and four in Phase II. All participants completed individual semi-structured interviews and demographic surveys. In addition, four of the teachers were observed teaching. The analysis yielded three themes and two sub-themes: (a) knowledge concerned teachers' knowledge of British literature content and Post-Colonial authors and their literature; (b) freedom described teachers' freedom to choose how to teach their content. Included in this theme was dilemmas associated with 12th-grade classrooms which described issues that were pertinent to the 12th-grade teacher and classroom that were revealed by the study; and (c) thoughts about students described teachers' perceptions about students and how literature might affect the students. Two subthemes of knowledge were as follows:(1) text complexity described teacher responses to a Post-Colonial text's complexity and (2) student desirability/teachability described teachers' perception about how desirable Post-Colonial texts would be to students and whether teachers would be willing to teach these texts. The researcher offers recommendations for understanding factors associated with 12th-grade teachers perceptions and implications for enhancing the 12th-grade experience for teachers and curriculum, based on this study: (a) build teacher morale and capacity, (b) treat all students as integral components of the teaching and learning process; teachers in this study thought teaching disenfranchised learners was a form of punishment meted out by the administration, and (c) include more Post-Colonial authors in school curricula in colleges and schools as most teachers in this study did not study this type of literature nor knew how to teach it.

High pressure and low temperature study of ammonia borane and lithium amidoborane

Hydrogen has been considered as a potentially efficient and environmentally friendly alternative energy solution. However, one of the most important scientific and technical challenges that the "hydrogen economy" faces is the development of safe and economically viable on-board hydrogen storage for fuel cell applications, especially to the transportation sector. Ammonia borane (BH3NH 3), a solid state hydrogen storage material, possesses exceptionally high hydrogen content (19.6 wt%).However, a fairly high temperature is required to release all the hydrogen atoms, along with the emission of toxic borazine. Recently research interests are focusing on the improvement of H2 discharge from ammonia borane (AB) including lowering the dehydrogenation temperature and enhancing hydrogen release rate using different techniques. Till now the detailed information about the bonding characteristics of AB is not sufficient to understand details about its phases and structures. ^ Elemental substitution of ammonia borane produces metal amidoboranes. Introduction of metal atoms to the ammonia borane structure may alter the bonding characteristics. Lithium amidoborane is synthesized by ball milling of ammonia borane and lithium hydride. High pressure study of molecular crystal provides unique insight into the intermolecular bonding forces and phase stability. During this dissertation, Raman spectroscopic study of lithium amidoborane has been carried out at high pressure in a diamond anvil cell. It has been identified that there is no dihydrogen bond in the lithium amidoborane structure, whereas dihydrogen bond is the characteristic bond of the parent compound ammonia borane. It has also been identified that the B-H bond becomes weaker, whereas B-N and N-H bonds become stronger than those in the parent compound ammonia borane. At high pressure up to 15 GPa, Raman spectroscopic study indicates two phase transformations of lithium amidoborane, whereas synchrotron X-ray diffraction data indicates only one phase transformation of this material. ^ Pressure and temperature has a significant effect on the structural stability of ammonia borane. This dissertation explored the phase transformation behavior of ammonia borane at high pressure and low temperature using in situ Raman spectroscopy. The P-T phase boundary between the tetragonal (I4mm) and orthorhombic (Pmn21) phases of ammonia borane has been determined. The transition has a positive Clapeyron slope which indicates the transition is of exothermic in nature. Influence of nanoconfinemment on the I4mm to Pmn2 1 phase transition of ammonia borane was also investigated. Mesoporus silica scaffolds SBA-15 with pore size of ~8 nm and MCM-41 with pore size of 2.1-2.7 nm, were used to nanoconfine ammonia borane. During cooling down, the I4mm to Pmn21 phase transition was not observed in MCM-41 nanoconfined ammonia borane, whereas the SBA-15 nanocondfined ammonia borane shows the phase transition at ~195 K. Four new phases of ammonia borane were also identified at high pressure up to 15 GPa and low temperature down to 90 K.^

Assessing Organizational Image: Triangulation Across Different Applicant Perceptions, Website, and Facebook Features

This study examined the role of corporate websites and company Facebook profiles in shaping perceptions of organizational image in the recruitment context. A primary purpose of this research was to determine whether or not perceptions of organizational image vary across different web-based recruitment methods, specifically examining corporate websites and social networking (SNW) sites, such as company Facebook profiles. A secondary goal was to determine how these perceptions of image are shaped by the objective components of websites and Facebook profiles. Finally, this study sought to determine the most influential components of websites and Facebook profiles, in terms of impacting image, to better understand how organizations can maximize their web-based recruitment efforts. A total of 102 companies selected from Fortune Magazine’s 2011 top 500 were chosen for the study. Perceptions of organizational personality as well as objective assessments of personality were gathered for each organization in a two phase approach. Results indicate that exposure to corporate websites and company Facebook profiles do influence perceptions of image in different ways. Furthermore, individual components of the websites were identified as key drivers for influencing specific image dimensions, particularly for company Facebook pages. Findings are beneficial for advising practitioners on how to best manage their web-based recruitment sources in order to maximize efficiency. The present study serves to further our understanding of the process through which perceptions of organizational image are influenced by new recruitment sources.

Ensemble Fuzzy Belief Intrusion Detection Design

With the rapid growth of the Internet, computer attacks are increasing at a fast pace and can easily cause millions of dollar in damage to an organization. Detecting these attacks is an important issue of computer security. There are many types of attacks and they fall into four main categories, Denial of Service (DoS) attacks, Probe, User to Root (U2R) attacks, and Remote to Local (R2L) attacks. Within these categories, DoS and Probe attacks continuously show up with greater frequency in a short period of time when they attack systems. They are different from the normal traffic data and can be easily separated from normal activities. On the contrary, U2R and R2L attacks are embedded in the data portions of the packets and normally involve only a single connection. It becomes difficult to achieve satisfactory detection accuracy for detecting these two attacks. Therefore, we focus on studying the ambiguity problem between normal activities and U2R/R2L attacks. The goal is to build a detection system that can accurately and quickly detect these two attacks. In this dissertation, we design a two-phase intrusion detection approach. In the first phase, a correlation-based feature selection algorithm is proposed to advance the speed of detection. Features with poor prediction ability for the signatures of attacks and features inter-correlated with one or more other features are considered redundant. Such features are removed and only indispensable information about the original feature space remains. In the second phase, we develop an ensemble intrusion detection system to achieve accurate detection performance. The proposed method includes multiple feature selecting intrusion detectors and a data mining intrusion detector. The former ones consist of a set of detectors, and each of them uses a fuzzy clustering technique and belief theory to solve the ambiguity problem. The latter one applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The final decision is a combination of the outputs of feature selecting and data mining detectors. The experimental results indicate that our ensemble approach not only significantly reduces the detection time but also effectively detect U2R and R2L attacks that contain degrees of ambiguous information.