Simulation is a powerful and efficient tool for studying wireless networks. Despite the widespread use of simulation, particularly in the study of IEEE 802.11-style networks (e.g., WLAN, mesh, and ad hoc networks), doubts about the credibility of simulation results still persist in the research community. These concerns stem, in part, from a lack of trust in some of the models used in simulation as they do not always accurately reflect reality. Models of the physical layer (PHY), in particular, are a key source of concern. The behavior of the physical layer varies greatly depending on the specifics of the wireless environment, making it difficult to characterize. Validation is the primary means of establishing trust in such models. We present an approach to validating physical layer models using the direct execution of a real PHY implementation inside the wireless simulation environment. This approach leverages the credibility inherent to testbeds, while maintaining the scalability and repeatability associated with simulation. Specifically, we use the PHY implementation from Hydra, a software-defined radio testbed, to validate the sophisticated physical layer model of a new wireless network simulator, called WiNS. This PHY model is also employed in other state-of-the-art network simulators, including ns-3. As such, this validation study also provides insight into the fidelity of other wireless network simulators using this model. This physical layer model is especially important because it is used to represent the physical layer for systems in 802.11-style networks. Network simulation is a particularly popular method for studying these kinds of wireless networks. We use direct-execution to evaluate the accuracy of our PHY model from the perspectives of different protocol layers. First, we characterize the link-level behavior of the physical layer under different wireless channels and impairments. We identify operating regimes where the model is accurate and show accountable difference where it is not. We then use direct-execution to evaluate the accuracy of the PHY model in the presence of interference. We develop "error-maps" that provide guidance to model users in evaluating the potential impact of model inaccuracy in terms of the interference in their own simulation scenarios. This part of our study helps to develop a better understanding of the fidelity of our model from a physical layer perspective. We also demonstrate the efficacy of direct-execution in evaluating the accuracy of our PHY model from the perspectives of the MAC and network layers. Specifically, we use direct-execution to investigate a rate-adaptive MAC protocol and an ad hoc routing protocol. This part of our study demonstrates how the semantics and policies of such protocols can influence the impact that a PHY model has on network simulations. We also show that direct-execution helps us to identify when a model that is inaccurate from the perspective of the PHY can still be used to generate trustworthy simulation results. The results of this study show that the leading physical layer model employed by WiNS and other state-of-the-art network simulators, including ns-3, is accurate under a limited set of wireless conditions. Moreover, our validation study demonstrates that direct-execution is an effective means of evaluating the accuracy of a PHY model and allows us to identify the operating conditions and protocol configurations where the model can be used to generate trustworthy simulation results. / text

Thunderstorms have been identified as an important component of the hydrological cycle on the Canadian Prairies, a region that is postulated to have the potential to exert a detectable influence on convective precipitation in the summer. However, very little work has been undertaken exploring and elucidating those aspects of biophysical forcing on the Canadian Prairies that affect lightning activity during the summer months, the constraints under which any linkages operate, and the mechanisms by which surface anomalies modify the structure and moisture content of the convective boundary layer (CBL) so as to modulate lightning activity. Evapotranspiration (ET) from the soil and vegetation canopy is known to be important for modulating the moisture content in the CBL, and this in turn has important implications for the initiation and intensity of deep, moist convection. The Second Generation Prairie Agrometeorological Model (PAMII) of Raddatz (1993) has been used extensively for the purpose of quantifying the evolution of soil moisture and ET in response to atmospheric drivers on the Canadian Prairies. However, the ability of PAMII to simulate the evolution of root-zone soil moisture and ET during the growing season has yet to be verified against a comprehensive set of in-situ observations. In this thesis, we address the above knowledge gaps using unique datasets comprising observed lightning flash data, satellite-derived Normalized Difference Vegetation Index (NDVI) data, observed atmospheric soundings, in-situ soil moisture observations and estimates of daily ET from eddy-covariance systems. A thorough quantitative validation of simulations of root-zone soil moisture and ET from PAMII was undertaken against in-situ soil moisture measurements and ET from eddy-covariance systems at sites on the Canadian Prairies. Our analysis demonstrates that PAMII shows skill in simulating the evolution of bulk root-zone soil moisture content and ET during the growing season, and for contrasting summer conditions (i.e., wet versus dry). As part of the soil moisture validation, a novel multi-model pedotransfer function ensemble technique was developed to quantify the uncertainty in soil moisture simulations arising from errors in the specified soil texture and associated soil hydraulic properties. An innovative approach was used to explore linkages between the terrestrial surface and deep, moist convection on the Canadian Prairies, using datasets which avoid many of the problems encountered when studying linkages between soil moisture and thunderstorm activity. This was achieved using lightning flash data in unison with remotely sensed NDVI data. Specifically, statistical analysis of the data over 38 Census Agricultural Regions (CARs) on the Canadian Prairies for 10 summers from 1999 to 2008 provided evidence for a surface-convection feedback on the Canadian Prairies, in which drought tends to perpetuate drought with respect to deep, moist convection. The constraints in which such a feedback operates (e.g., areal extent and magnitude of the NDVI anomalies) were also identified. For example, our data suggest that NDVI anomalies and lightning duration are asymmetric, with the relationship between NDVI and lightning duration strengthening as the area and amplitude of the negative NDVI anomaly (less vegetation vigour) increases. Finally, we focused on how surface anomalies over the Canadian Prairies can condition the CBL so as to inhibit or facilitate thunderstorm activity, while also considering the role of synoptic-scale forcing on modulating summer thunderstorm activity. We focused on a CAR located over central Alberta for which observed lightning flash data, NDVI data, and in-situ sounding data were available for 11 summers from 1999 to 2009. Our analysis suggests that storms over this region are more likely to develop and are longer-lived or more widespread when they develop in an environment in which the surface and upper-air synoptic-scale forcings are synchronized. On days when a surface or upper-air feature is present, storms are more likely to be triggered when NDVI is much above average, compared to when NDVI is much below average. We propose a conceptual model, based almost entirely on observations, which integrates our findings to describe how a reduction in vegetation vigour modulates the partitioning of available energy into sensible and latent heat fluxes at the surface, thereby modulating the lifting condensation level heights, which in turn affect lightning duration.

A systematic approach of testing and validating transition models is developed and employed in testing of a recently developed transition model. The testing methodology uses efficient computational tools and a wide range of test cases. The computational tools include a boundary layer code, single zone Navier Stokes solver, and a multi-block Navier Stokes solver which uses MPI and is capable of handling complex geometries and moving grids. Test cases include simple flat plate experiments, cascade experiments, and unsteady wake/blade interaction experiments. The test cases are used to test the predicting capabilities of the transition model under various effects such as free stream turbulence intensity, Reynolds number variations, pressure gradient, flow separation, and unsteady wake/blade interaction. Using the above test cases and computational tools a method is developed to validate transition models. The transition model is first implemented in boundary layer code and tested for simple flat plate cases. Then the transition model is implemented in single zone Navier Stokes solver and tested for hysteresis effects for flat plate cases. Finally the transition model is implemented in multi zone Navier Stokes solver and tested for compressor and turbine cascade cases followed by unsteady wake/blade interaction experiments. Using the method developed a new correlation based transition model (Menter et al. 2004) which uses local variables is tested and validated. The new model predicted good results for high free stream turbulence and high Reynolds number cases. For low free stream turbulence and low Reynolds number cases, the results were satisfactory.

Thunderstorms have been identified as an important component of the hydrological cycle on the Canadian Prairies, a region that is postulated to have the potential to exert a detectable influence on convective precipitation in the summer. However, very little work has been undertaken exploring and elucidating those aspects of biophysical forcing on the Canadian Prairies that affect lightning activity during the summer months, the constraints under which any linkages operate, and the mechanisms by which surface anomalies modify the structure and moisture content of the convective boundary layer (CBL) so as to modulate lightning activity. Evapotranspiration (ET) from the soil and vegetation canopy is known to be important for modulating the moisture content in the CBL, and this in turn has important implications for the initiation and intensity of deep, moist convection. The Second Generation Prairie Agrometeorological Model (PAMII) of Raddatz (1993) has been used extensively for the purpose of quantifying the evolution of soil moisture and ET in response to atmospheric drivers on the Canadian Prairies. However, the ability of PAMII to simulate the evolution of root-zone soil moisture and ET during the growing season has yet to be verified against a comprehensive set of in-situ observations. In this thesis, we address the above knowledge gaps using unique datasets comprising observed lightning flash data, satellite-derived Normalized Difference Vegetation Index (NDVI) data, observed atmospheric soundings, in-situ soil moisture observations and estimates of daily ET from eddy-covariance systems. A thorough quantitative validation of simulations of root-zone soil moisture and ET from PAMII was undertaken against in-situ soil moisture measurements and ET from eddy-covariance systems at sites on the Canadian Prairies. Our analysis demonstrates that PAMII shows skill in simulating the evolution of bulk root-zone soil moisture content and ET during the growing season, and for contrasting summer conditions (i.e., wet versus dry). As part of the soil moisture validation, a novel multi-model pedotransfer function ensemble technique was developed to quantify the uncertainty in soil moisture simulations arising from errors in the specified soil texture and associated soil hydraulic properties. An innovative approach was used to explore linkages between the terrestrial surface and deep, moist convection on the Canadian Prairies, using datasets which avoid many of the problems encountered when studying linkages between soil moisture and thunderstorm activity. This was achieved using lightning flash data in unison with remotely sensed NDVI data. Specifically, statistical analysis of the data over 38 Census Agricultural Regions (CARs) on the Canadian Prairies for 10 summers from 1999 to 2008 provided evidence for a surface-convection feedback on the Canadian Prairies, in which drought tends to perpetuate drought with respect to deep, moist convection. The constraints in which such a feedback operates (e.g., areal extent and magnitude of the NDVI anomalies) were also identified. For example, our data suggest that NDVI anomalies and lightning duration are asymmetric, with the relationship between NDVI and lightning duration strengthening as the area and amplitude of the negative NDVI anomaly (less vegetation vigour) increases. Finally, we focused on how surface anomalies over the Canadian Prairies can condition the CBL so as to inhibit or facilitate thunderstorm activity, while also considering the role of synoptic-scale forcing on modulating summer thunderstorm activity. We focused on a CAR located over central Alberta for which observed lightning flash data, NDVI data, and in-situ sounding data were available for 11 summers from 1999 to 2009. Our analysis suggests that storms over this region are more likely to develop and are longer-lived or more widespread when they develop in an environment in which the surface and upper-air synoptic-scale forcings are synchronized. On days when a surface or upper-air feature is present, storms are more likely to be triggered when NDVI is much above average, compared to when NDVI is much below average. We propose a conceptual model, based almost entirely on observations, which integrates our findings to describe how a reduction in vegetation vigour modulates the partitioning of available energy into sensible and latent heat fluxes at the surface, thereby modulating the lifting condensation level heights, which in turn affect lightning duration.

Flexible carbon capture and storage (CCS) has the potential to play a significant part in the decarbonisation of electricity generation portfolios which have significant penetration from intermittent renewable sources. Post-combustion capture (PCC) with amine solvents is a mature technology and is currently the state-of-the-art for CO2 emissions reduction from power stations. However, knowledge of the dynamic capture process is currently limited due to a dearth of dynamic datasets which reflect real plant operation, lack of a robust in-situ solvent analysis method for plant control and uncertainty about how changing plant design affects the response to dynamic operations. In addition, the nature of interfacial gas-liquid dynamics inside the absorber column are not well known and rely on correlations for effective mass transfer area and liquid holdup which may have uncertainties of up to +/- 13%. This could result in absorption columns being improperly sized for CCS operations. Two pilot-scale test campaigns are implemented in order to gain an understanding of how the capture plant responds to dynamic operations, the first on natural gas combined cycle (NGCC)-equivalent flue gas, the second on pulverised coal (PC)-equivalent. Changes in flue gas flow rates and steam supply which are designed to be representative of PCC operation on real NGCC and PC plant are implemented, using 30%wt monoethanolamine (MEA) as absorbent in both cases. Dynamic datasets are obtained for 5 scenarios with NGCC and 8 with PC flue gas. The test campaigns are carried out using two separate pilot-scale facilities and highlight the effect of plant design on hydrodynamics and hence, the response of the capture plant to dynamic operations. Finally, a novel solvent sensor is used to demonstrate, for the first time, control of the capture facility using in-situ measurements of solvent composition, combined with knowledge of test facility hydrodynamics and response times. Results from the pilot-scale test campaign are then used along with a mathematical NGCC capture plant scale up to investigate the potential effects of dynamic operations on total yearly CO2 emissions and the associated environmental penalties, depending on CO2 price. Manufacturers of column internals for CCS often rely on computational fluid dynamic (CFD) software tools for design, but existing commercial codes are unable to handle complex two-phase flows such as those encountered in the absorber column of a CO2 capture plant. An open-source direct numerical simulation (DNS) tool which will be capable of rigorously modelling two-phase flow with turbulence and mass transfer has been developed and could eventually replace the empirical methods currently used in packing design. The DNS code requires validation by experiment. For the purpose of validation a dual-purpose wetted-wall column is constructed, which in addition to mass transfer measurements can be used to determine liquid film thickness using an optical method. Measurements of average film thickness, wave amplitude, frequency, velocity and growth rate are provided for three liquid flow rates of fresh 30%wt MEA solution. Wave measurements are made with quiescent, laminar and turbulent gas flow, with and without mass transfer. These measurements can be used to validate the DNS code at its existing level of complexity, and in the future when turbulence and mass transfer are added.

The design and development of process-aware information systems is often supported by specifying requirements as business process models. Although this approach is generally accepted as an effective strategy, it remains a fundamental challenge to adequately validate these models given the diverging skill set of domain experts and system analysts. As domain experts often do not feel confident in judging the correctness and completeness of process models that system analysts create, the validation often has to regress to a discourse using natural language. In order to support such a discourse appropriately, so-called verbalization techniques have been defined for different types of conceptual models. However, there is currently no sophisticated technique available that is capable of generating natural-looking text from process models. In this paper, we address this research gap and propose a technique for generating natural language texts from business process models. A comparison with manually created process descriptions demonstrates that the generated texts are superior in terms of completeness, structure, and linguistic complexity. An evaluation with users further demonstrates that the texts are very understandable and effectively allow the reader to infer the process model semantics. Hence, the generated texts represent a useful input for process model validation.

No description available.

Phase change material (PCM)-based ocean thermal energy harvesting is a relatively new method, which extracts the thermal energy from the temperature gradient in the ocean thermocline. Its basic idea is to utilize the temperature variation along the ocean water depth to cyclically freeze and melt a specific kind of PCM. The volume expansion, which happens in the melting process, is used to do useful work (e.g., drive a turbine generator), thereby converting a fraction of the absorbed thermal energy into mechanical energy or electrical energy. Compared to other ocean energy technologies (e.g., wave energy converters, tidal current turbines, and ocean thermal energy conversion), the proposed PCM-based approach can be easily implemented at a small scale with a relatively simple structural system, which makes it a promising method to extend the range and service life of battery-powered devices, e.g, autonomous underwater vehicles (AUVs). This dissertation presents a combined theoretical and experimental study of the PCM-based ocean thermal energy harvesting approach, which aims at demonstrating the feasibility of the proposed approach and investigating possible methods to improve the overall performance of prototypical systems. First, a solid/liquid phase change thermodynamic model is developed, based on which a specific upperbound of the thermal efficiency is derived for the PCM-based approach. Next, a prototypical PCM-based ocean thermal energy harvesting system is designed, fabricated, and tested. To predict the performance of specific systems, a thermo-mechanical model, which couples the thermodynamic behaviors of the fluid materials and the elastic behavior of the structural system, is developed and validated based on the comparison with the experimental measurement. For the purpose of design optimization, the validated thermo-mechanical model is employed to conduct a parametric study. Based on the results of the parametric study, a new scalable and portable PCM-based ocean thermal energy harvesting system is developed and tested. In addition, the thermo-mechanical model is modified to account for the design changes. However, a combined analysis of the results from both the prototypical system and the model reveals that achieving a good performance requires maintaining a high internal pressure, which will complicate the structural design. To mitigate this issue, the idea of using a hydraulic accumulator to regulate the internal pressure is proposed, and experimentally and theoretically examined. Finally, a spatial-varying Robin transmission condition for fluid-structure coupled problems with strong added-mass effect is proposed and investigated using fluid structure interaction (FSI) model problems. This can be a potential method for the future research on the fluid-structure coupled numerical analysis of AUVs, which are integrated with and powered by the PCM-based thermal energy harvesting devices. / Doctor of Philosophy / The global ocean, which covers about 71% of the Earth’s surface, absorbs a great amount of heat from the sunshine everyday, making it a reliable and renewable source of thermal energy. Also, the temperature of the ocean water varies with depth, which provides a necessary condition (i.e, a temperature gradient) to extract the thermal energy. If harvested and converted into electrical energy using small scale portable devices, the ocean thermal energy can be a potential energy resource to provide power for autonomous underwater vehicles (AUVs), which are conventionally powered by on-board rechargeable batteries. To this end, this dissertation presents a study of using solid/liquid phase change materials (PCMs) to extract thermal energy from the temperature gradient in the ocean. The basic idea is to use the warm surface water and deep cold water to melt and freeze the PCM cyclically. In the meantime, the volume of PCM will expand and contract accordingly. Therefore, a turbine generator can be driven by the volume expansion in the melting process, thereby converting a fraction of the absorbed thermal energy into electrical energy. This study includes four key aspects. First, to evaluate the theoretical full potential of the PCM-based approach, a solid/liquid phase change thermodynamic model – which represents an idealized energy harvester – is developed. Based on the thermodynamic model, an upperbound of the thermal efficiency is derived. Secondly, two prototypical systems, as well as a thermo-mechanical model which can predict the performance of specific designs, are developed. Third, for the purposes of performance improvement and pressure regulation, the latter of which is associated with the structural safety, a hydraulic accumulator is added to the existing system and its effects are examined using both experimental and theoretical methods. Finally, a computational method is proposed and demonstrated, which can be a potential tool for the design of PCM-based ocean thermal energy harvesting systems when they are integrated with exiting AUVs.

The research detailed in this study focuses on the determination of an appropriate objective function to aid parameter estimation when simulating areas influenced by tidally varying flows. Three objective functions that are measures of how well the model results match field data at several locations and times were tested. A set of test cases is developed to represent tidally influenced systems and allow for the testing of the objective functions. These objective functions were tested by computing their values and comparing them for the various estimated parameters. Based on results of the first method of testing a further analysis was performed using PEST, an automatic parameter estimation tool. A weighted least squares of the velocity and water surface values with a weight function on the velocity term based on the shallow water equations is found to be a reasonable objective function at this point in the research.

No description available.