Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"data reconciliation"”.
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Data reconciliation in bioprocess development
Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1997.
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Extensions to the data reconciliation procedure
Data reconciliation is a method of improving the quality of data obtained from automated measurements in chemical plants. All measuring instruments are subject to error. These measurement errors degrade the quality of the data, resulting in inconsistencies in the material and energy balance …
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Application of process data reconciliation in power plants
… is vital to have reliable and accurate process data to achieve process optimization. However, process measurements are inevitably subject to measurement errors. These measurement errors are classified as random and gross errors. Data reconciliation technique is an effective data treatment method …
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Optimisation techniques for advanced process supervision and control
… namely model predictive control and dynamic data reconciliation. A model predictive control scheme is implemented and used to simulate the control of a coal gasification plant. Static as well as dynamic data reconciliation techniques are developed and used in conjunction with steady-state …
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Development of a heuristic methodology for designing measurement networks for precise metal accounting
… errors are an inherent property of measured data and they can only be minimised. Two types of rules for designing measurement networks were considered. The first type of rules referred to as 'expert heuristics' consists of (i) Code of Practice Guidelines from the AMIRA P754 Code, and (ii) …
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Issues in on-line optimisation
… Techniques for steady-state detection, static data reconciliation, gross error detection and steady-state optimisation are presented and implemented separately and within an on-line optimisation methodology. It has been acknowledged for some time now that the estimation of derivative …
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Improved tracking of phosphorus in wastewater treatment works through anaerobic digestion of p-rich sludge
… but the failure of these models to achieve data reconciliation when modelling the anaerobic digestion of PAOs show that they are still incomplete. Ikumi and Ekama (2019) generated stoichiometry to help model PAO intracellular processes and hypothesised that an energy transfer between the …
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Bayesian Methods for Mineral Processing Operations
… model parameters and predictions given a set of data and a prior distribution and model parameter prior distributions. The uncertainty quantification possible with Bayesian methods lend well to statistical simulation, model selection, and sensitivity analysis. Moreover, Bayesian models utilizing …
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A new diagnostics tool for water injected gas turbines - emissions monitoring and modeling
… Water injection is used to help lower emissions. Data reconciliation and gross error detection are performed to adjust measured variables and determine efficiency. A continuous emission monitoring system (CEMS) has been recently installed to measure both the NOx and O2 concentrations in the …
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Computer-Aided Design and Simulation of Chemical Plants: PEETPACK, a Non-Proprietary Flowsheeting Program
… library of unit models and physical property data, or contains an efficient calculation order finder. Many programs suffer also from a poor data interface with the users which makes teaching or learning process difficult and time-consuming. PEETPACK (Process Engineering Evaluation Techniques …
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Resource Efficiency in the Chemical Industry
… to process designers, based on simulated, static data. So the second step involved applying this methodology to real, dynamic data from an ammonia site. Two years of data from 311 at minute-level frequency are collected. This thesis develops boundary definition and data reconciliation methods for …