A microstructure based model of the deformation mechanisms and flow stress during elevated temperature straining of a magnesium alloy

We show that the variation of flow stress with strain rate and grain size in a magnesium alloy deformed at a constant strain rate and 450 °C can be predicted by a crystal plasticity model that includes grain boundary sliding and diffusion. The model predicts the grain size dependence of the critical strain rate that will cause a transition in deformation mechanism from dislocation creep to grain boundary sliding, and yields estimates for grain boundary fluidity and diffusivity.

The Design of XML-Based Model and Experiment Description Languages for Network Simulation

The Simulation Automation Framework for Experiments (SAFE) is a project created to raise the level of abstraction in network simulation tools and thereby address issues that undermine credibility. SAFE incorporates best practices in network simulationto automate the experimental process and to guide users in the development of sound scientific studies using the popular ns-3 network simulator. My contributions to the SAFE project: the design of two XML-based languages called NEDL (ns-3 Experiment Description Language) and NSTL (ns-3 Script Templating Language), which facilitate the description of experiments and network simulationmodels, respectively. The languages provide a foundation for the construction of better interfaces between the user and the ns-3 simulator. They also provide input to a mechanism which automates the execution of network simulation experiments. Additionally,this thesis demonstrates that one can develop tools to generate ns-3 scripts in Python or C++ automatically from NSTL model descriptions.

A generalisation of the fractional Brownian field based on non-Euclidean norms

We explore a generalisation of the L´evy fractional Brownian field on the Euclidean space based on replacing the Euclidean norm with another norm. A characterisation result for admissible norms yields a complete description of all self-similar Gaussian random fields with stationary increments. Several integral representations of the introduced random fields are derived. In a similar vein, several non-Euclidean variants of the fractional Poisson field are introduced and it is shown that they share the covariance structure with the fractional Brownian field and converge to it. The shape parameters of the Poisson and Brownian variants are related by convex geometry transforms, namely the radial pth mean body and the polar projection transforms.

Field-Based Evaluations of Horizontal Flat-Plate Fish Screens

Diversions from streams are often screened to prevent the loss of or injury to fish. Hydraulic criteria meant to protect fish that encounter screens have been developed, but primarily for screens that are vertical to the water flow rather than horizontal. For this reason, we measured selected hydraulic variables and released wild rainbow trout Oncorhynchus mykiss over two types of horizontal flat-plate fish screens in the field. Our goal was to assess the efficacy of these screens under a variety of conditions in the field and provide information that could be used to develop criteria for safe fish passage. We evaluated three different inverted-weir screens over a range of strewn (0.24-1.77 m(3)/s) and diversion flows (0.10-0.31 m(3)/s). Approach velocities (AVs) ranged from 3 to 8 cm/s and sweeping velocities (SVs) from 69 to 143 cm/s. We also evaluated a simple backwatered screen over stream flows of 0.23-0.79 m(3)/s and diversion flows of 0.08-0.32 m(3)/s. The mean SVs for this screen ranged from 15 to 66 cm/s and the mean AVs from 1 to 5 cm/s. The survival rates of fish held for 24 h after passage over these screens exceeded 98%. Overall, the number of fish-screen contacts was low and the injuries related to passage were infrequent and consisted primarily of minor fin injuries. Our results indicate that screens of this type have great potential as safe and effective fish screens for small diversions. Care must be taken, however, to avoid operating conditions that produce shallow or no water over the screen surface, situations of high AVs and low SVs at backwatered screens, and situations producing a localized high AV with spiraling flow.

An individual based model spatial distribution, production and biomass for Calanus finmarchicus in the Norwegian Sea

The copepod Calanus finmarchicus is the dominant species of the meso-zooplankton in the Norwegian Sea, and constitutes an important link between the phytoplankton and the higher trophic levels in the Norwegian Sea food chain. An individualbased model for C. finmarchicus, based on super-individuals and evolving traits for behaviour, stages, etc., is two-way coupled to the NORWegian ECOlogical Model system (NORWECOM). One year of modelled C. finmarchicus spatial distribution, production and biomass are found to represent observations reasonably well. High C. finmarchicus abundance is found along the Norwegian shelf-break in the early summer, while the overwintering population is found along the slope and in the deeper Norwegian Sea basins. The timing of the spring bloom is generally later than in the observations. Annual Norwegian Sea production is found to be 29 million tonnes of carbon and a production to biomass (P/B) ratio of 4.3 emerges. Sensitivity tests show that the modelling system is robust to initial values of behavioural traits and with regards to the number of super-individuals simulated given that this is above about 50,000 individuals. Experiments with the model system indicate that it provides a valuable tool for studies of ecosystem responses to causative forces such as prey density or overwintering population size. For example, introducing C. finmarchicus food limitations reduces the stock dramatically, but on the other hand, a reduced stock may rebuild in one year under normal conditions. The NetCDF file contains model grid coordinates and bottom topography.

Knowledge pipeline in freight pipeline industry: competence- based model for open innovation

There is growing concern over the challenges for innovation in Freight Pipeline industry. Since the early works of Chesbrough a decade ago, we have learned a lot about the content, context and process of open innovation. However, much more research is needed in Freight Pipeline Industry. The reality is that few corporations have institutionalized open innovation practices in ways that have enabled substantial growth or industry leadership. Based on this, we pursue the following question: How does a firm’s integration into knowledge networks depend on its ability to manage knowledge? A competence-based model for freight pipeline organizations is analysed, this model should be understood by any organization in order to be successful in motivating professionals who carry out innovations and play a main role in collaborative knowledge creation processes. This paper aims to explain how can open innovation achieve its potential in most Freight Pipeline Industries.

A Satisfaction-based Model for Affect Recognition from Conversational Features in Spoken Dialog Systems

Detecting user affect automatically during real-time conversation is the main challenge towards our greater aim of infusing social intelligence into a natural-language mixed-initiative High-Fidelity (Hi-Fi) audio control spoken dialog agent. In recent years, studies on affect detection from voice have moved on to using realistic, non-acted data, which is subtler. However, it is more challenging to perceive subtler emotions and this is demonstrated in tasks such as labelling and machine prediction. This paper attempts to address part of this challenge by considering the role of user satisfaction ratings and also conversational/dialog features in discriminating contentment and frustration, two types of emotions that are known to be prevalent within spoken human-computer interaction. However, given the laboratory constraints, users might be positively biased when rating the system, indirectly making the reliability of the satisfaction data questionable. Machine learning experiments were conducted on two datasets, users and annotators, which were then compared in order to assess the reliability of these datasets. Our results indicated that standard classifiers were significantly more successful in discriminating the abovementioned emotions and their intensities (reflected by user satisfaction ratings) from annotator data than from user data. These results corroborated that: first, satisfaction data could be used directly as an alternative target variable to model affect, and that they could be predicted exclusively by dialog features. Second, these were only true when trying to predict the abovementioned emotions using annotator?s data, suggesting that user bias does exist in a laboratory-led evaluation.

Agent-based model for the effect of curing temperature on cement hydration

The agent-based model presented here, comprises an algorithm that computes the degree of hydration, the water consumption and the layer thickness of C-S-H gel as functions of time for different temperatures and different w/c ratios. The results are in agreement with reported experimental studies, demonstrating the applicability of the model. As the available experimental results regarding elevated curing temperature are scarce, the model could be recalibrated in the future. Combining the agent-based computational model with TGA analysis, a semiempirical method is achieved to be used for better understanding the microstructure development in ordinary cement pastes and to predict the influence of temperature on the hydration process.

Nationwide impact and vehicle to grid application of electric vehicles mobility using an activity based model

This paper describes the impact of electric mobility on the transmission grid in Flanders region (Belgium), using a micro-simulation activity based models. These models are used to provide temporal and spatial estimation of energy and power demanded by electric vehicles (EVs) in different mobility zones. The increment in the load demand due to electric mobility is added to the background load demand in these mobility areas and the effects over the transmission substations are analyzed. From this information, the total storage capacity per zone is evaluated and some strategies for EV aggregator are proposed, allowing the aggregator to fulfill bids on the electricity markets.

Phase Transitions in Disordered Systems: The Example of the Random-Field Ising Model in Four Dimensions

By performing a high-statistics simulation of the D = 4 random-field Ising model at zero temperature for different shapes of the random-field distribution, we show that the model is ruled by a single universality class. We compute to a high accuracy the complete set of critical exponents for this class, including the correction-to-scaling exponent. Our results indicate that in four dimensions (i) dimensional reduction as predicted by the perturbative renormalization group does not hold and (ii) three independent critical exponents are needed to describe the transition.

Development of a Strengths-Based Model for Insurance Automobile, Property, and Casualty Claims Operations

ABSTRACT \ Employers know that to have a successful organization, they must have the right people in the right jobs. But how will they know whom to place where? The development of a model based upon an individual's personality traits and strengths, and how to best use them, is a good place to start. Employees working in positions in which their traits and strengths are maximized enjoy work more, are more efficient, and are less apt to be absent or to look for work elsewhere. It is a mutually beneficial process of selection for both employers and employees. This model illustrates the process in an automobile and property insurance claims operation through utilization of the Myers-Briggs Type Indicators and the StrengthsFinder Profiles.