Eulerian-Lagrangian two phase debris flow model

The main objective of this work is to develop a quasi three-dimensional numerical model to simulate stony debris flows, considering a continuum fluid phase, composed by water and fine sediments, and a non-continuum phase including large particles, such as pebbles and boulders. Large particles are treated in a Lagrangian frame of reference using the Discrete Element Method, the fluid phase is based on the Eulerian approach, using the Finite Element Method to solve the depth-averaged Navier-Stokes equations in two horizontal dimensions. The particle’s equations of motion are in three dimensions. The model simulates particle-particle collisions and wall-particle collisions, taking into account that particles are immersed in a fluid. Bingham and Cross rheological models are used for the continuum phase. Both formulations provide very stable results, even in the range of very low shear rates. Bingham formulation is better able to simulate the stopping stage of the fluid when applied shear stresses are low. Results of numerical simulations have been compared with data from laboratory experiments on a flume-fan prototype. Results show that the model is capable of simulating the motion of big particles moving in the fluid flow, handling dense particulate flows and avoiding overlap among particles. An application to simulate debris flow events that occurred in Northern Venezuela in 1999 shows that the model could replicate the main boulder accumulation areas that were surveyed by the USGS. Uniqueness of this research is the integration of mud flow and stony debris movement in a single modeling tool that can be used for planning and management of debris flow prone areas.

Eulerian-Lagrangian Two Phase Debris Flow Model

The main objective of this work is to develop a quasi three-dimensional numerical model to simulate stony debris flows, considering a continuum fluid phase, composed by water and fine sediments, and a non-continuum phase including large particles, such as pebbles and boulders. Large particles are treated in a Lagrangian frame of reference using the Discrete Element Method, the fluid phase is based on the Eulerian approach, using the Finite Element Method to solve the depth-averaged Navier–Stokes equations in two horizontal dimensions. The particle’s equations of motion are in three dimensions. The model simulates particle-particle collisions and wall-particle collisions, taking into account that particles are immersed in a fluid. Bingham and Cross rheological models are used for the continuum phase. Both formulations provide very stable results, even in the range of very low shear rates. Bingham formulation is better able to simulate the stopping stage of the fluid when applied shear stresses are low. Results of numerical simulations have been compared with data from laboratory experiments on a flume-fan prototype. Results show that the model is capable of simulating the motion of big particles moving in the fluid flow, handling dense particulate flows and avoiding overlap among particles. An application to simulate debris flow events that occurred in Northern Venezuela in 1999 shows that the model could replicate the main boulder accumulation areas that were surveyed by the USGS. Uniqueness of this research is the integration of mud flow and stony debris movement in a single modeling tool that can be used for planning and management of debris flow prone areas.

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.

Numerical investigation on the heat transfer enhancement using micro/nano phase-change particulate flow

The introduction of phase change material fluid and nanofluid in micro-channel heat sink design can significantly increase the cooling capacity of the heat sink because of the unique features of these two kinds of fluids. To better assist the design of a high performance micro-channel heat sink using phase change fluid and nanofluid, the heat transfer enhancement mechanism behind the flow with such fluids must be completely understood. ^ A detailed parametric study is conducted to further investigate the heat transfer enhancement of the phase change material particle suspension flow, by using the two-phase non-thermal-equilibrium model developed by Hao and Tao (2004). The parametric study is conducted under normal conditions with Reynolds numbers of Re = 90–600 and phase change material particle concentrations of ϵp ≤ 0.25, as well as extreme conditions of very low Reynolds numbers (Re < 50) and high phase change material particle concentration (ϵp = 50%–70%) slurry flow. By using the two newly-defined parameters, named effectiveness factor ϵeff and performance index PI, respectively, it is found that there exists an optimal relation between the channel design parameters L and D, particle volume fraction ϵp, Reynolds number Re, and the wall heat flux qw. The influence of the particle volume fraction ϵp, particle size dp, and the particle viscosity μ p, to the phase change material suspension flow, are investigated and discussed. The model was validated by available experimental data. The conclusions will assist designers in making their decisions that relate to the design or selection of a micro-pump suitable for micro or mini scale heat transfer devices. ^ To understand the heat transfer enhancement mechanism of the nanofluid flow from the particle level, the lattice Boltzmann method is used because of its mesoscopic feature and its many numerical advantages. By using a two-component lattice Boltzmann model, the heat transfer enhancement of the nanofluid is analyzed, through incorporating the different forces acting on the nanoparticles to the two-component lattice Boltzmann model. It is found that the nanofluid has better heat transfer enhancement at low Reynolds numbers, and the Brownian motion effect of the nanoparticles will be weakened by the increase of flow speed. ^

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.

How do partnerships lead to a competitive advantage? Applying the resource based view to nascent social ventures

This dissertation is one of the earliest to systematically apply and empirically test the resource-based view (RBV) in the context of nascent social ventures in a large scale study. Social ventures are entrepreneurial ventures organized as nonprofit, for-profit, or hybrid organizations whose primary purpose is to address unmet social needs and create social value. Nascent social ventures face resource gaps and engage in partnerships or alliances as one means to access external resources. These partnerships with different sectors facilitate social venture innovative and earned income strategies, and assist in the development of adequate heterogeneous resource conditions that impact competitive advantage. Competitive advantage in the context of nascent social ventures is achieved through the creation of value and the achievement of venture development activities and launching. The relationships between partnerships, heterogeneous resource conditions, strategies, and competitive advantage are analyzed in the context of nascent social ventures that participated in business plan competitions. A content analysis of 179 social venture business plans and an exploratory follow-up survey of 72 of these ventures are used to analyze these relationships using regression, ANOVA, correlations, t-tests, and non-parametric statistics. The findings suggest a significant positive relationship between competitive advantage and partnership diversity, heterogeneous resource conditions, social innovation, and earned income. Social capital is the type of resource most significantly related to competitive advantage. Founder previous start-up experience, client location, and business plan completeness are also found to be significant in the relationship between partnership diversity and competitive advantage. Finally the findings suggest that hybrid social ventures create a greater competitive advantage than nonprofit or for-profit social ventures. Consequently, this dissertation not only provides academics further insight into the factors that impact nascent social value creation, venture development, and ability to launch, but also offers practitioners guidance on how best to organize certain processes to create a competitive advantage. As a result more insight is gained into the nascent social venture creation process and how these ventures can have a greater impact on society.

Three essays on a longitudinal analysis of business start-ups using the Kauffman Firm Survey

This dissertation focused on the longitudinal analysis of business start-ups using three waves of data from the Kauffman Firm Survey. ^ The first essay used the data from years 2004-2008, and examined the simultaneous relationship between a firm's capital structure, human resource policies, and its impact on the level of innovation. The firm leverage was calculated as, debt divided by total financial resources. Index of employee well-being was determined by a set of nine dichotomous questions asked in the survey. A negative binomial fixed effects model was used to analyze the effect of employee well-being and leverage on the count data of patents and copyrights, which were used as a proxy for innovation. The paper demonstrated that employee well-being positively affects the firm's innovation, while a higher leverage ratio had a negative impact on the innovation. No significant relation was found between leverage and employee well-being.^ The second essay used the data from years 2004-2009, and inquired whether a higher entrepreneurial speed of learning is desirable, and whether there is a linkage between the speed of learning and growth rate of the firm. The change in the speed of learning was measured using a pooled OLS estimator in repeated cross-sections. There was evidence of a declining speed of learning over time, and it was concluded that a higher speed of learning is not necessarily a good thing, because speed of learning is contingent on the entrepreneur's initial knowledge, and the precision of the signals he receives from the market. Also, there was no reason to expect speed of learning to be related to the growth of the firm in one direction over another.^ The third essay used the data from years 2004-2010, and determined the timing of diversification activities by the business start-ups. It captured when a start-up diversified for the first time, and explored the association between an early diversification strategy adopted by a firm, and its survival rate. A semi-parametric Cox proportional hazard model was used to examine the survival pattern. The results demonstrated that firms diversifying at an early stage in their lives show a higher survival rate; however, this effect fades over time.^

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.^

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.

Numerical Investigation on the Heat Transfer Enhancement Using Micro/Nano Phase-Change Particulate Flow

The introduction of phase change material fluid and nanofluid in micro-channel heat sink design can significantly increase the cooling capacity of the heat sink because of the unique features of these two kinds of fluids. To better assist the design of a high performance micro-channel heat sink using phase change fluid and nanofluid, the heat transfer enhancement mechanism behind the flow with such fluids must be completely understood. A detailed parametric study is conducted to further investigate the heat transfer enhancement of the phase change material particle suspension flow, by using the two-phase non-thermal-equilibrium model developed by Hao and Tao (2004). The parametric study is conducted under normal conditions with Reynolds numbers of Re=600-900 and phase change material particle concentrations ¡Ü0.25 , as well as extreme conditions of very low Reynolds numbers (Re < 50) and high phase change material particle concentration (0.5-0.7) slurry flow. By using the two newly-defined parameters, named effectiveness factor and performance index, respectively, it is found that there exists an optimal relation between the channel design parameters, particle volume fraction, Reynolds number, and the wall heat flux. The influence of the particle volume fraction, particle size, and the particle viscosity, to the phase change material suspension flow, are investigated and discussed. The model was validated by available experimental data. The conclusions will assist designers in making their decisions that relate to the design or selection of a micro-pump suitable for micro or mini scale heat transfer devices. To understand the heat transfer enhancement mechanism of the nanofluid flow from the particle level, the lattice Boltzmann method is used because of its mesoscopic feature and its many numerical advantages. By using a two-component lattice Boltzmann model, the heat transfer enhancement of the nanofluid is analyzed, through incorporating the different forces acting on the nanoparticles to the two-component lattice Boltzmann model. It is found that the nanofluid has better heat transfer enhancement at low Reynolds numbers, and the Brownian motion effect of the nanoparticles will be weakened by the increase of flow speed.

Three Essays on a Longitudinal Analysis of Business Start-ups using the Kauffman Firm Survey

This dissertation focused on the longitudinal analysis of business start-ups using three waves of data from the Kauffman Firm Survey. The first essay used the data from years 2004-2008, and examined the simultaneous relationship between a firm’s capital structure, human resource policies, and its impact on the level of innovation. The firm leverage was calculated as, debt divided by total financial resources. Index of employee well-being was determined by a set of nine dichotomous questions asked in the survey. A negative binomial fixed effects model was used to analyze the effect of employee well-being and leverage on the count data of patents and copyrights, which were used as a proxy for innovation. The paper demonstrated that employee well-being positively affects the firm's innovation, while a higher leverage ratio had a negative impact on the innovation. No significant relation was found between leverage and employee well-being. The second essay used the data from years 2004-2009, and inquired whether a higher entrepreneurial speed of learning is desirable, and whether there is a linkage between the speed of learning and growth rate of the firm. The change in the speed of learning was measured using a pooled OLS estimator in repeated cross-sections. There was evidence of a declining speed of learning over time, and it was concluded that a higher speed of learning is not necessarily a good thing, because speed of learning is contingent on the entrepreneur's initial knowledge, and the precision of the signals he receives from the market. Also, there was no reason to expect speed of learning to be related to the growth of the firm in one direction over another. The third essay used the data from years 2004-2010, and determined the timing of diversification activities by the business start-ups. It captured when a start-up diversified for the first time, and explored the association between an early diversification strategy adopted by a firm, and its survival rate. A semi-parametric Cox proportional hazard model was used to examine the survival pattern. The results demonstrated that firms diversifying at an early stage in their lives show a higher survival rate; however, this effect fades over time.

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 (BH3NH3), 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 Pmn21 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.