Data Reconciliation of the Turbine Section: Evaluation of Estimation Uncertainty

2014 ◽  
Author(s):  
Olli Saarela ◽  
Emil Wingstedt
Keyword(s):  
First Principles ◽  
Nuclear Power ◽  
Process Model ◽  
A Priori ◽  
Data Reconciliation ◽  
Estimation Uncertainty ◽  
Data Driven Approach ◽  
Multiple Measurements ◽  
Energy Balances ◽  
Mass And Energy Balances

Data reconciliation is technique for reducing measurement uncertainty by adjusting measured data to comply with a first-principles process model, most importantly with mass and energy balances. It also provides estimates for modelled unmeasurable process variables and estimates for the uncertainties of the computed values. For computing these estimates the process model has to include estimates of measurement uncertainties defined a priori. A priori consideration of all potential sources of uncertainty is far from trivial. This paper discusses a data-driven approach of uncertainty evaluation, based on identifying and subtracting variability modes affecting multiple measurements. Possible bias in the measurements is not considered. The approach is applied to evaluate the uncertainties of estimates computed with a data reconciliation model of a turbine section of a nuclear power plant.

Data Reconciliation Applied in a Transfer and Storage Terminal

2006 ◽  
Author(s):  
Rafael Noac Feldman ◽  
Elcio Cruz de Oliveira
Keyword(s):  
Diesel Oil ◽  
Data Reconciliation ◽  
Systematic Bias ◽  
Random Errors ◽  
Single Measure ◽  
Gross Error ◽  
Energy Balances ◽  
And Storage ◽  
Mass And Energy Balances

In a simply manner, data reconciliation is a mathematic treatment with propose of a better quality of the data in a process. Industrial processes typically have a large number of measured variables, which presents some degree of random errors and, less frequently, gross errors. In this text, in order to simplify the notation and terminology we classify all instrument and process errors in these two categories. Any significant systematic bias is included in the gross error category. Data reconciliation allows the measurements to be adjusted (“reconciled”) to satisfy process restrictions (mass and energy balances) and improve measurements quality. The results obtained by data reconciliation can also provide benefits in custody transfer issues. Custody transfer is the responsibility transfer during the storage and transportation of a measured refined product volume. Any loss or gain resulting in a non-trustful measurement is considered as the transportation company responsibility. Therefore, the work objective is to propose a data reconciliation methodology, in a process involving diesel oil custody transfer in a Transpetro’s terminal (Terminal of Sao Caetano do Sul), in order to evaluate and correct possible inconsistencies, besides to know a single measure that represents better the measurement system. In this study we will use data from static measurement in tanks, dynamic measurement in turbine and ultra-sonic device. A database will be obtained in two basic steps: process modeling and data reconciliation to consolidate the mass balance. The reconciled value shows us that there is a bias in the ultra-sonic meter and the turbine meter measurement is more reliable, as expected.

Innovative energy and mass balance of a continuous evaporating crystallizer

2019 ◽  
pp. 646-654
Author(s):  
Jan Iciek ◽  
Kornel Hulak ◽  
Radosław Gruska
Keyword(s):  
Energy Balance ◽  
Mass Balance ◽  
Working Conditions ◽  
Crystallization Process ◽  
Heat Losses ◽  
Inert Gas ◽  
Gas Removal ◽  
Energy Balances ◽  
Heat Released ◽  
Mass And Energy Balances

The article presents the mass and energy balances of the sucrose crystallization process in a continuous evaporating crystallizer. The developed algorithm allows to assess the working conditions of the continuous evaporating crystallizers and the technological and energy parameters. The energy balance algorithm takes into account the heat released during the crystallization of sucrose, which was analyzed in this study, heat losses to the environment and heat losses due the vapor used for inert gas removal.

Mass and energy balances of an autothermal pilot carbonization unit

2019 ◽  
Vol 120 ◽  
pp. 144-155 ◽  
Author(s):  
Andrea Maria Rizzo ◽  
Marco Pettorali ◽  
Renato Nistri ◽  
David Chiaramonti
Keyword(s):  
Energy Balances ◽  
Mass And Energy Balances

scholarly journals A continuum model for meltwater flow through compacting snow

2017 ◽  
Vol 11 (6) ◽  
pp. 2799-2813 ◽  
Author(s):  
Colin R. Meyer ◽  
Ian J. Hewitt
Keyword(s):  
Continuum Model ◽  
Pore Space ◽  
Water Storage ◽  
Greenland Ice Sheet ◽  
Percolation Process ◽  
Surface Mass ◽  
Run Off ◽  
Flow Through ◽  
Energy Balances ◽  
Mass And Energy Balances

Abstract. Meltwater is produced on the surface of glaciers and ice sheets when the seasonal energy forcing warms the snow to its melting temperature. This meltwater percolates into the snow and subsequently runs off laterally in streams, is stored as liquid water, or refreezes, thus warming the subsurface through the release of latent heat. We present a continuum model for the percolation process that includes heat conduction, meltwater percolation and refreezing, as well as mechanical compaction. The model is forced by surface mass and energy balances, and the percolation process is described using Darcy's law, allowing for both partially and fully saturated pore space. Water is allowed to run off from the surface if the snow is fully saturated. The model outputs include the temperature, density, and water-content profiles and the surface runoff and water storage. We compare the propagation of freezing fronts that occur in the model to observations from the Greenland Ice Sheet. We show that the model applies to both accumulation and ablation areas and allows for a transition between the two as the surface energy forcing varies. The largest average firn temperatures occur at intermediate values of the surface forcing when perennial water storage is predicted.

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