Browsing by Subject "uncertainty analysis"
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Item Design and performance of an ammonia measurement system(Texas A&M University, 2007-04-25) Boriack, Cale NolanAmmonia emissions from animal feeding operations (AFOs) have recently come under increased scrutiny. The US Environmental Protection Agency (EPA) has come under increased pressure from special interest groups to regulate ammonia. Regulation of ammonia is very difficult because every facility has different manure management practices. Different management practices lead to different emissions for every facility. Researchers have been tasked by industry to find best management practices to reduce emissions. The task cannot be completed without equipment that can efficiently and accurately compare emissions. To complete this task, a measurement system was developed and performance tested to measure ammonia. Performance tests included uncertainty analysis, system response, and adsorption kinetics. A measurement system was designed for measurement of gaseous emissions from ground level area sources (GLAS) in order to sample multiple receptors with a single sensor. This multiplexer may be used in both local and remote measurement systems to increase the sampling rate of gaseous emissions. The increased data collection capacity with the multiplexer allows for nearly three times as many samples to be taken in the same amount of time while using the same protocol for sampling. System response analysis was performed on an ammonia analyzer, a hydrogen sulfide analyzer, and tubing used with flux chamber measurement. System responses were measured and evaluated using transfer functions. The system responses for the analyzers were found to be first order with delay in auto mode. The tubing response was found to be a first order response with delay. Uncertainty analysis was performed on an ammonia sampling and analyzing system. The system included an analyzer, mass flow controllers, calibration gases, and analog outputs. The standard uncertainty was found to be 443 ppb when measuring a 16 ppm ammonia stream with a 20 ppm span. A laboratory study dealing with the adsorption kinetics of ammonia on a flux chamber was performed to determine if adsorption onto the chamber walls was significant. The study found that the adsorption would not significantly change the concentration of the output flow 30 minutes after a clean chamber was exposed to ammonia concentrations for concentrations above 2.5 ppm.Item Estimating uncertainties in integrated reservoir studies(Texas A&M University, 2004-09-30) Zhang, GuohongTo make sound investment decisions, decision makers need accurate estimates of the uncertainties present in forecasts of reservoir performance. In this work I propose a method, the integrated mismatch method, that incorporates the misfit in the history match into the estimation of uncertainty in the prediction. I applied the integrated mismatch method, which overcomes some deficiencies of existing methods, to uncertainty estimation in two reservoir studies and compared results to estimations from existing methods. The integrated mismatch method tends to generate smaller ranges of uncertainty than many existing methods. When starting from nonoptimal reservoir models, in some cases the integrated mismatch method is able to bracket the true reserves value while other methods fail to bracket it. The results show that even starting from a nonoptimal reservoir model, but as long as the experimental designs encompass the true case parameters, the integrated mismatch method brackets the true reserves value. If the experimental designs do not encompass all the true case parameters, but the true reserves value is covered by the experiments, the integrated mismatch method may still bracket the true case. This applies if there is a strong correlation between mismatch and closeness to the true reserves value. The integrated mismatch method does not need a large number of simulation runs for the uncertainty analysis, while some other methods need hundreds of runs.Item Evaluating and developing parameter optimization and uncertainty analysis methods for a computationally intensive distributed hydrological model(2009-05-15) Zhang, XuesongThis study focuses on developing and evaluating efficient and effective parameter calibration and uncertainty methods for hydrologic modeling. Five single objective optimization algorithms and six multi-objective optimization algorithms were tested for automatic parameter calibration of the SWAT model. A new multi-objective optimization method (Multi-objective Particle Swarm and Optimization & Genetic Algorithms) that combines the strengths of different optimization algorithms was proposed. Based on the evaluation of the performances of different algorithms on three test cases, the new method consistently performed better than or close to the other algorithms. In order to save efforts of running the computationally intensive SWAT model, support vector machine (SVM) was used as a surrogate to approximate the behavior of SWAT. It was illustrated that combining SVM with Particle Swarm and Optimization can save efforts for parameter calibration of SWAT. Further, SVM was used as a surrogate to implement parameter uncertainty analysis fo SWAT. The results show that SVM helped save more than 50% of runs of the computationally intensive SWAT model The effect of model structure on the uncertainty estimation of streamflow simulation was examined through applying SWAT and Neural Network models. The 95% uncertainty intervals estimated by SWAT only include 20% of the observed data, while Neural Networks include more than 70%. This indicates the model structure is an important source of uncertainty of hydrologic modeling and needs to be evaluated carefully. Further exploitation of the effect of different treatments of the uncertainties of model structures on hydrologic modeling was conducted through applying four types of Bayesian Neural Networks. By considering uncertainty associated with model structure, the Bayesian Neural Networks can provide more reasonable quantification of the uncertainty of streamflow simulation. This study stresses the need for improving understanding and quantifying methods of different uncertainty sources for effective estimation of uncertainty of hydrologic simulation.