Sensitivity analysis was performed on a soot model using a partially stirred reactor (PaSR) in order to determine the effects of mixing model parameters on soot scalar values. The sensitivities of the mixture fraction zeta and progress variable C to the mixing model constant C_phi were calculated; these values were used to compute the sensitivity of water mass fraction Y_H2O to C_phi and several soot quantities to soot moments. Results were validated by evaluating the mean mixture fraction sensitivity and a long simulation time case. From the baseline case, it was noted that soot moment sensitivities tended to peak on the rich side of the stoichiometric mixture fraction zeta_st. Timestep, number of notional particles, mixing timescale tau_mix, and residence time tau_res were varied independently. Choices for timestep and notional particle count were shown to be sufficient to capture relevant scalar profiles, and did not greatly affect sensitivity calculations. Altering tau_mix or tau_res was shown to affect sensitivity to mixing, and it was concluded that the soot model is more heavily influenced by the chemistry than mixing. / text

Assuming a set of variates are independent and normally distributed is commonplace in statistics. In this thesis, we consider the consequences of these assumptions as they pertain to global sensitivity analysis. We begin by illustrating how the notion of sensitivity becomes distorted in the presence of codependent model inputs. This observation motivates us to develop a new methodology which accommodates for input codependencies. Our methodology can be summarized through three points: First, a new form of sensitivity is presented which performs as well as the classical form but can be obtained at a fraction of the computational cost. Second, we define a measure which quantifies the extent of distortion caused by codependent inputs. The third point is regarding the modelling of said codependencies. The multivariate normal distribution is a natural choice for modelling codependent inputs; however, our methodology uses a copula-based approach instead. Copulas are a contemporary strategy for constructing multivariate distributions whereby the marginal and joint behaviours are treated separately. As a result, a practitioner has more flexibility when modelling inputs. / Thesis (Master, Chemical Engineering) -- Queen's University, 2013-12-05 10:16:26.81

UA Open Access Publishing Fund / Background Missing outcome data is a threat to the validity of treatment effect estimates in randomized controlled trials. We aimed to evaluate the extent, handling, and sensitivity analysis of missing data and intention-to-treat (ITT) analysis of randomized controlled trials (RCTs) in top tier medical journals, and compare our findings with previous reviews related to missing data and ITT in RCTs. Methods Review of RCTs published between July and December 2013 in the BMJ, JAMA, Lancet, and New England Journal of Medicine, excluding cluster randomized trials and trials whose primary outcome was survival. Results Of the 77 identified eligible articles, 73 (95%) reported some missing outcome data. The median percentage of participants with a missing outcome was 9% (range 0 – 70%). The most commonly used method to handle missing data in the primary analysis was complete case analysis (33, 45%), while 20 (27%) performed simple imputation, 15 (19%) used model based methods, and 6 (8%) used multiple imputation. 27 (35%) trials with missing data reported a sensitivity analysis. However, most did not alter the assumptions of missing data from the primary analysis. Reports of ITT or modified ITT were found in 52 (85%) trials, with 21 (40%) of them including all randomized participants. A comparison to a review of trials reported in 2001 showed that missing data rates and approaches are similar, but the use of the term ITT has increased, as has the report of sensitivity analysis. Conclusions Missing outcome data continues to be a common problem in RCTs. Definitions of the ITT approach remain inconsistent across trials. A large gap is apparent between statistical methods research related to missing data and use of these methods in application settings, including RCTs in top medical journals.

Tapeng Bay is the second largest lagoon in Taiwan. The biological and ecological environments are an autotrophic system and are influenced by seasonal variability, terrestrial pollutant inputs and the exchange rates with seawater. There¡¦re intense oyster culture and fish farming activities in the bay before July, 2002. The oyster was the most important spineless member in the lagoon. They would filtrate microplankton and detritus; they would also excrete nutrient and consume dissolved oxygen. Therefore, oyster played a very crucial role in the Tapeng Bay. This study combines the biological responses of the oysters with the complicated interaction among microplankton, nutrient, detritus and dissolved oxygen to establish the relationship of dynamical mechanisms between variables by applying the system dynamics simulation software STELLA. Model results clearly reveal that the oysters are the main species of filtration. The factors which affect the biomass of oysters include microplankton concentration, temperature and individual mass; the connection between oysters and other biological variables is closely tied. The study has also shown that the removing of oysters may cause significant increases of plankton and detritus during the eutrophication condition. Although the simulated water quality variables show higher than those obtained from sampling experiments in the literatures, the trend corresponds well with the relative studies. Despite the fact that oysters excrete much nutrient and nutrient is mostly taken up by microplankton, the condition of nutrient limitation has never happened, which is in correspondence with the result. In the sensitivity analysis, the parameters of oyster filtration rate and the autotroph nitrogen to carbon ratio are important factors which have influence on oysters biomass, and the concentration of microplankton and ammonium. Oyster excretion rate and the proportion of oyster feces and pseudofeces also have significant influences on the concentration of ammonium. The oyster culture racks in the Bay have already been torn down, but the Bay is still eutrophic. This is a clear indication of the importance of the oysters in the lagoon. Properly culture some oysters in the area where exist high concentrations of microplankton or organic input. By applying the oyster abundant filtration, planktons and suspended solids, mostly detritus and organic matters, can probably be controlled and the water quality in the bay can thus be improved. Although the STELLA has its limitation on broader applications, the model developed by this study can be combined with the features of social or economic fields. A decision supporting system can be developed for the management of ecological environment policies.

Due to the difficulty of reinforcement in power network and the interconnection of more distributed generators, fault current level has become a serious problem in transmission and distribution system operations. The utilization of fault current limiters (FCLs) in power system provides an effective way to suppress the fault currents. In this thesis the sensitivity of impedance matrix due to changes in the branch parameters is derived and used to choose the candidates for FCL installation in a complex power system. The proposed method also considers the effect on power system transient stability due to the installation of FCL. The Extended Equal Area Criterion (EEAC) is used to simplify the multi-machine transient stability problem to a simple equivalent modal and to simplify the transient stability evaluation. A fuzzy logic approach considering impedance of FCL, transient stability and voltage sag effects is used to choose good FCL installation locations in loop transmission systems.

Depletion calculations for nuclear reactors model the dynamic coupling between the material composition and neutron flux and help predict reactor performance and safety characteristics. In order to be trusted as reliable predictive tools and inputs to licensing and operational decisions, the simulations must include an accurate and holistic quantification of errors and uncertainties in its outputs. Uncertainty quantification is a formidable challenge in large, realistic reactor models because of the large number of unknowns and myriad sources of uncertainty and error. We present a framework for performing efficient uncertainty quantification in depletion problems using an adjoint approach, with emphasis on high-fidelity calculations using advanced massively parallel computing architectures. This approach calls for a solution to two systems of equations: (a) the forward, engineering system that models the reactor, and (b) the adjoint system, which is mathematically related to but different from the forward system. We use the solutions of these systems to produce sensitivity and error estimates at a cost that does not grow rapidly with the number of uncertain inputs. We present the framework in a general fashion and apply it to both the source-driven and k-eigenvalue forms of the depletion equations. We describe the implementation and verification of solvers for the forward and ad- joint equations in the PDT code, and we test the algorithms on realistic reactor analysis problems. We demonstrate a new approach for reducing the memory and I/O demands on the host machine, which can be overwhelming for typical adjoint algorithms. Our conclusion is that adjoint depletion calculations using full transport solutions are not only computationally tractable, they are the most attractive option for performing uncertainty quantification on high-fidelity reactor analysis problems.

No description available.

Wind is the main abiotic cause of disturbance to forests in large parts of the world, particularly at temperate and boreal latitudes. In the past few decades the consequences of large wind-induced losses have been experienced at various levels, from small forest owners to large-scale, whole-society level. This is particularly relevant for areas, such as Europe, where forests are intensively managed, and the assets exposed to wind hazard are substantial. To better manage forests and commercial tree plantations to reduce the risk of wind damage, process-based, semi-mechanistic mathematical models such as ForestGALES are used. This model has been parameterised and evaluated for numerous conifer species, which constitute the major plantation types in temperate and boreal biomes. However, the geographical extent and economic importance of fast-growing broadleaved species, such as those of the Eucalyptus genus, and the lack of detailed historical data on wind damage to these species, require that tools for the estimation of the risk of wind damage to these species are developed and evaluated. This is particularly relevant in light of the projected increases of surface temperature due to climate change, and of the frequency and severity of extreme windstorms, that are expected as a consequence of climate change. Fieldwork was conducted in a semi-natural Eucalyptus globulus (Labill.) forest in the Asturias region in Northern Spain to acquire data for the parameterisation of ForestGALES for E. globulus, using a tree-pulling experiment. The behaviour of the parameterisation was investigated for different stocking densities to evaluate whether the effects of tree height, stocking density, and presence of a fresh upwind gap are consistent with the literature. This parameterisation was then used to compare the vulnerability to wind damage between E. globulus and Pinus pinaster (Ait.), the predominant plantation species in the Aquitaine region of SW France where extensive damage was experienced from storms Martin (1999) and Klaus (2009). The effects of rooting depth (2x), growth rate (2x), presence/absence of a recently created windward gap, and of the predominant wind climate in Aquitaine were investigated in this comparison. In order to aid forest managers with optimal resource allocation for practical applications of ForestGALES, and to provide forest modellers with invaluable insights for the development of robust wind damage risk models, ForestGALES was subjected to a sensitivity analysis. A generalisation of the variance-based method of Sobol’ for the case of correlated variables was used to investigate the sensitivity of the outputs of ForestGALES (the critical wind speeds for stem breakage and uprooting, and the associated probabilities of damage) to variation in its input variables. Almost all the E. globulus trees pulled in Asturias failed by overturning rather than breakage, which allowed for good confidence in the calculations of the overturning moments required for the empirical component of ForestGALES. Resistance to overturning was not significantly influenced by the presence of a tap-root. Modelling the shape of the tree crowns with an ellipsoid provided a good approximation of the geometry of the canopy, but required additional fieldwork as crown width in the four cardinal directions had to be estimated visually prior to the tests. The scarcity of detailed published data on wind damage to E. globulus made evaluating the parameterisation particularly challenging. This impediment was obviated by investigating the behaviour of the parameterisation with regards to the well-known effects of tree height, stocking density, and presence of a fresh upwind gap. The simulations showed that the parameterisation behaved as expected, with vulnerability of E. globulus stands increasing with tree height, stocking density, and the presence of a gap. High initial planting densities, an early thinning, and a final harvesting before the trees have reached a height of 20 – 25m are recommended to reduce the risk of wind damage to E. globulus. The comparison with P. pinaster showed that E. globulus trees are particularly susceptible to the presence of a recently created windward gap. Therefore, harvesting at neighbouring sites should be minimised, and preferentially performed when the neighbouring stands are still at a young age to take advantage of the fast growth rates of E. globulus. These practices would ensure that in case of wind damage any losses are recovered in a short time. These procedures can reduce the cumulative risk through the rotation, while maintaining competitive yields. The ForestGALES simulations have also highlighted that the silvicultural practices currently in place in Aquitaine expose P. pinaster trees to high levels of cumulative risk (> 20%). The sensitivity analysis of ForestGALES has highlighted the strengths of the model and the areas that require substantial improvement. The results of the analysis show that ForestGALES is able to simulate very effectively the dynamics of wind damage to forest stands, as the model architecture reflects the significant influences of tree height, stocking density, dbh, and size of an upwind gap, on the calculations of the critical wind speeds of damage. Similarly, in ForestGALES the wind climate of a site is the main driver of variation of the probabilities of damage, as it is for real forests affected by extreme storms. Conversely, when the windiness of a site is moderate, ForestGALES accounts for the larger role of tree and stand variables. The sensitivity analysis has shown that ForestGALES is particularly efficient at simulating not only the effect of the size of windward gaps on the vulnerability of a stand, but also at differentiating between recently formed stand edges and edges that have been in place since the establishment of a stand. Therefore, for practical applications of the model, tree height, dbh, stocking density, the size and nature of an upwind gap, and the local wind climate, are the variables that need to be known with a high accuracy in order to maximally reduce the uncertainty of the model predictions. The section of the model that requires further attention and research is the one dedicated to the calculation of the trees’ resistance to overturning. The sensitivity analysis has shown that rooting depth and soil type, the model input variables on which the empirical component of ForestGALES that describes the resistance to overturning is based, contribute only marginally to the variation in the outputs. This finding unequivocally identifies that efforts for future research should be aimed at studying the mechanics of root-soil interactions with regards to tree stability. The results of the sensitivity analysis have also shown that the variance-based method used in this research project is equally sensitive to the accurate description of the probability distribution functions of the scrutinised variables, as it is to their correlation structure.

DRASTIC model is the most widely used method for aquifer vulnerability mapping which consists of seven hydrogeological parameters. Despite of its popularity, this technique disregards the effect of regional characteristics and there is no specific validation method to demonstrate the accuracy of this method. The main goal of this research was developing an integrated GIS-based DRASTIC model using Depth to water, Net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and Hydraulic Conductivity (DRASTIC). In order to obtain a more reliable and accurate assessment, the rates and weights of original DRASTIC were modified using Wilcoxon rank-sum non-parametric statistical test and Single Parameter Sensitivity Analysis (SPSA). The methodology was implemented for the Shahrekord plain in the southwestern region of Iran. Two different sets of measured nitrate concentrations from two monitoring events were used, one for modification and other for validation purposes. Validation nitrate values were compared to the calculated DRASTIC index to assess the efficacy of the DRASTIC model. The validation results obtained from Pearson's correlation and chi-square values, revealed that the modified DRASTIC is more efficient than original DRASTIC. The modified rate/weight DRASTIC (spline) model showed the highest correlation coefficient and chi square value as 0.88 and 72.93, respectively, compared to -0.3 and 25.2 for the original DRASTIC (spline) model. The integrated vulnerability map showed the high risk imposed on the southeastern part of the Shahrekord aquifer. In addition, sensitivity analysis indicated that the removal of net recharge parameter from the modified model caused larger variation in vulnerability index showing that this parameter has more impact on the DRASTIC vulnerability of the aquifer. Moreover, Aquifer media (A), Topography (T) and Impact of vadose zone (I) were found to have less effect and importance compared to other variables as expected. Therefore, reduced modified DRASTIC model was proposed by eliminating A, T and I parameters. Pearson's correlation coefficient and chi-square value for the reduced model were calculated as 0.88 and 100.38, respectively, which was found to be as reliable as full modified DRASTIC model.

No description available.