Records with Subject: Numerical Methods and Statistics
Showing records 1 to 25 of 31. [First] Page: 1 2 Last
Application of Transformation Matrices to the Solution of Population Balance Equations
Vasyl Skorych, Nilima Das, Maksym Dosta, Jitendra Kumar, Stefan Heinrich
November 5, 2019 (v1)
Keywords: agglomeration, dynamic flowsheet simulation, milling, multidimensional distributed parameters, population balance equation, process modelling, solids, transformation matrix
The development of algorithms and methods for modelling flowsheets in the field of granular materials has a number of challenges. The difficulties are mainly related to the inhomogeneity of solid materials, requiring a description of granular materials using distributed parameters. To overcome some of these problems, an approach with transformation matrices can be used. This allows one to quantitatively describe the material transitions between different classes in a multidimensional distributed set of parameters, making it possible to properly handle dependent distributions. This contribution proposes a new method for formulating transformation matrices using population balance equations (PBE) for agglomeration and milling processes. The finite volume method for spatial discretization and the second-order Runge−Kutta method were used to obtain the complete discretized form of the PBE and to calculate the transformation matrices. The proposed method was implemented in the flowsheet mod... [more]
A Numerical Approach to Solve Volume-Based Batch Crystallization Model with Fines Dissolution Unit
Safyan Mukhtar, Muhammad Sohaib, Ishfaq Ahmad
September 23, 2019 (v1)
Keywords: orthogonal polynomials, quadrature method of moments, volume-based population balance model with fines dissolution
In this article, a numerical study of a one-dimensional, volume-based batch crystallization model (PBM) is presented that is used in numerous industries and chemical engineering sciences. A numerical approximation of the underlying model is discussed by using an alternative Quadrature Method of Moments (QMOM). Fines dissolution term is also incorporated in the governing equation for improvement of product quality and removal of undesirable particles. The moment-generating function is introduced in order to apply the QMOM. To find the quadrature abscissas, an orthogonal polynomial of degree three is derived. To verify the efficiency and accuracy of the proposed technique, two test problems are discussed. The numerical results obtained by the proposed scheme are plotted versus the analytical solutions. Thus, these findings line up well with the analytical findings.
Simulating Stochastic Populations. Direct Averaging Methods
Vu Tran, Doraiswami Ramkrishna
July 11, 2019 (v1)
Keywords: direct averaging, drug resistance, stochastic simulation, transfer
A method of directly computing the average behavior of stochastic populations is established, which obviates the time-consuming process of generating detailed sample paths. The method relies on suitably discretized time intervals in which nonlinearities are quasi-linearized to produce random variables with known expectations and variances. The pair of equations is directly solved to obtain the average behavior of the system at the end of a time interval based on its knowledge at the beginning of the interval. The sample path requirement for this process is considerably lower than that for the process over the entire simulation period. The efficiency of the method is demonstrated on the transfer of antibiotics resistance between two bacterial species which is a problem of mounting concern in fighting disease.
Discrete Element Method Model Optimization of Cylindrical Pellet Size
Jiri Rozbroj, Jiri Zegzulka, Jan Necas, Lucie Jezerska
June 10, 2019 (v1)
Keywords: DEM, friction coefficient, hopper discharge, particle image velocimetry, pellets
The DEM (Discrete Element Method) is one option for studying the kinematic behaviour of cylindrical pellets. The DEM experiments attempted to optimize the numerical model parameters that affected time and velocity as a cylindrical vessel emptied. This vessel was filled with cylindrical pellets. Optimization was accomplished by changing the coefficient of friction between particles and selecting the length accuracy grade of the sample cylindrical pellets. The initial state was a series of ten vessel-discharge experiments evaluated using PIV (Particle Image Velocimetry). The cylindrical pellet test samples were described according to their length in three accuracy grades. These cylindrical pellet length accuracy grades were subsequently used in the DEM simulations. The article discusses a comparison of the influence of the length accuracy grade of cylindrical pellets on optimal calibration of time and velocity when the cylindrical vessel is emptied. The accuracy grade of cylindrical pell... [more]
On the Boundary Conditions in a Non-Linear Dissipative Observer for Tubular Reactors
Irandi Gutierrez-Carmona, Jaime A. Moreno, H.F. Abundis-Fong
April 9, 2019 (v1)
Keywords: distributed observers, PDE, perturbation estimation, sensor position
The modal injection mechanism ensures the exponential convergence of an observer in a continuous tubular reactor in dependence with the system parameters, the sensor location, and the observer gains. In this paper, it is shown that by simple considerations in the boundary conditions, the observer convergence is improved regardless of the presence of perturbations, the sensor locations acquire a meaningful physical meaning, and by simple numerical manipulations, the perturbations in the inflow can be numerically estimated.
Numerical Models for Viscoelastic Liquid Atomization Spray
Lijuan Qian, Jianzhong Lin, Fubing Bao
February 27, 2019 (v1)
Keywords: atomization spray, numerical modeling, viscoelastic fluid
Atomization spray of non-Newtonian liquid plays a pivotal role in various engineering applications, especially for the energy utilization. To operate spray systems efficiently and well understand the effects of liquid rheological properties on the whole spray process, a comprehensive model using Euler-Lagrangian approaches was established to simulate the evolution of the atomization spray for viscoelastic liquid. Based on the Oldroyd model, the viscoelastic linear dispersion relation was introduced into the primary atomization; an extended viscoelastic version of Taylor analogy breakup (TAB) model was proposed; and the coalescence criteria was modified by rheological parameters, such as the relaxation time, the retardation time and the zero shear viscosity. The predicted results are validated with experimental data varying air-liquid mass flow ratio (ALR). Then, numerical calculations are conducted to investigate the characteristics of viscoelastic liquid atomization process. Results s... [more]
Assessing Steady-State, Multivariate Experimental Data Using Gaussian Processes: The GPExp Open-Source Library
Sylvain Quoilin, Jessica Schrouff
November 28, 2018 (v1)
Keywords: experimental data, feature selection, Gaussian processes, kriging, outlier, regression, surface response
Experimental data are subject to different sources of disturbance and errors, whose importance should be assessed. The level of noise, the presence of outliers or a measure of the “explainability” of the key variables with respect to the externally-imposed operating condition are important indicators, but are not straightforward to obtain, especially if the data are sparse and multivariate. This paper proposes a methodology and a suite of tools implementing Gaussian processes for quality assessment of steady-state experimental data. The aim of the proposed tool is to: (1) provide a smooth (de-noised) multivariate operating map of the measured variable with respect to the inputs; (2) determine which inputs are relevant to predict a selected output; (3) provide a sensitivity analysis of the measured variables with respect to the inputs; (4) provide a measure of the accuracy (confidence intervals) for the prediction of the data; (5) detect the observations that are likely to be outliers.... [more]
Comparison of Moving Boundary and Finite-Volume Heat Exchanger Models in the Modelica Language
Adriano Desideri, Bertrand Dechesne, Jorrit Wronski, Martijn van den Broek, Sergei Gusev, Vincent Lemort, Sylvain Quoilin
November 27, 2018 (v1)
Keywords: Dynamic Modelling, dynamic validation, Modelica, organic Rankine cycle (ORC)
When modeling low capacity energy systems, such as a small size (5⁻150 kWel) organic Rankine cycle unit, the governing dynamics are mainly concentrated in the heat exchangers. As a consequence, the accuracy and simulation speed of the higher level system model mainly depend on the heat exchanger model formulation. In particular, the modeling of thermo-flow systems characterized by evaporation or condensation requires heat exchanger models capable of handling phase transitions. To this aim, the finite volume (FV) and the moving boundary (MB) approaches are the most widely used. The two models are developed and included in the open-source ThermoCycle Modelica library. In this contribution, a comparison between the two approaches is presented. An integrity and accuracy test is designed to evaluate the performance of the FV and MB models during transient conditions. In order to analyze how the two modeling approaches perform when integrated at a system level, two organic Rankine cycle (ORC... [more]
Constant Jacobian Matrix-Based Stochastic Galerkin Method for Probabilistic Load Flow
Yingyun Sun, Rui Mao, Zuyi Li, Wei Tian
November 27, 2018 (v1)
Keywords: generalized polynomial chaos, Nataf transformation, probabilistic load flow, stochastic Galerkin method, uncertainty quantification
An intrusive spectral method of probabilistic load flow (PLF) is proposed in the paper, which can handle the uncertainties arising from renewable energy integration. Generalized polynomial chaos (gPC) expansions of dependent random variables are utilized to build a spectral stochastic representation of PLF model. Instead of solving the coupled PLF model with a traditional, cumbersome method, a modified stochastic Galerkin (SG) method is proposed based on the P-Q decoupling properties of load flow in power system. By introducing two pre-calculated constant sparse Jacobian matrices, the computational burden of the SG method is significantly reduced. Two cases, IEEE 14-bus and IEEE 118-bus systems, are used to verify the computation speed and efficiency of the proposed method.
Implementing a Novel Hybrid Maximum Power Point Tracking Technique in DSP via Simulink/MATLAB under Partially Shaded Conditions
Shahrooz Hajighorbani, Mohd Amran Mohd Radzi, Mohd Zainal Abidin Ab Kadir, Suhaidi Shafie, Muhammad Ammirrul Atiqi Mohd Zainuri
November 16, 2018 (v1)
Keywords: digital signal processing (DSP), global maximum power point (GMPP), O), partial shadow (PS), perturb and observation (P&, photovoltaic (PV), Simulink/MATLAB
This paper presents a hybrid maximum power point tracking (MPPT) method to detect the global maximum power point (GMPP) under partially shaded conditions (PSCs), which have more complex characteristics with multiple peak power points. The hybrid method can track the GMPP when a partial shadow occurs either before or after acquiring the MPP under uniform conditions. When PS occurs after obtaining the MPP during uniform conditions, the new operating point should be specified by the modified linear function, which reduces the searching zone of the GMPP and has a significant effect on reducing the reaching time of the GMPP. Simultaneously, the possible MPPs are scanned and stored when shifting the operating point to a new reference voltage. Finally, after determining the possible location of the GMPP, the GMPP is obtained using the modified P&O. Conversely, when PS occurs before obtaining the MPP, the referenced MPP should be specified. Thus, after recognizing the possible location of... [more]
A Novel Computational Approach for Harmonic Mitigation in PV Systems with Single-Phase Five-Level CHBMI
Rosario Miceli, Giuseppe Schettino, Fabio Viola
September 21, 2018 (v1)
Keywords: multilevel power converter, phase shifted, photovoltaic systems, selective harmonic mitigation, soft switching, voltage cancellation
In this paper, a novel approach to low order harmonic mitigation in fundamental switching frequency modulation is proposed for high power photovoltaic (PV) applications, without trying to solve the cumbersome non-linear transcendental equations. The proposed method allows for mitigation of the first-five harmonics (third, fifth, seventh, ninth, and eleventh harmonics), to reduce the complexity of the required procedure and to allocate few computational resource in the Field Programmable Gate Array (FPGA) based control board. Therefore, the voltage waveform taken into account is different respect traditional voltage waveform. The same concept, known as “voltage cancelation„, used for single-phase cascaded H-bridge inverters, has been applied at a single-phase five-level cascaded H-bridge multilevel inverter (CHBMI). Through a very basic methodology, the polynomial equations that drive the control angles were detected for a single-phase five-level CHBMI. The acquired polynomial equations... [more]
Periodic Steady State Assessment of Microgrids with Photovoltaic Generation Using Limit Cycle Extrapolation and Cubic Splines
Marcolino Díaz-Araujo, Aurelio Medina, Rafael Cisneros-Magaña, Amner Ramírez
September 21, 2018 (v1)
Keywords: cubic splines, limit cycle, numerical differentiation method, periodic steady state, photovoltaic energy sources, time domain
This paper proposes a fast and accurate time domain (TD) methodology for the assessment of the dynamic and periodic steady state operation of microgrids with photovoltaic (PV) energy sources. The proposed methodology uses the trapezoidal rule (TR) technique to integrate the set of first-order differential algebraic equations (DAE), generated by the entire electrical system. The Numerical Differentiation (ND) method is used to significantly speed-up the process of convergence of the state variables to the limit cycle with the fewest number of possible time steps per cycle. After that, the cubic spline interpolation (CSI) algorithm is used to reconstruct the steady state waveform obtained from the ND method and to increase the efficiency of the conventional TR method. This curve-fitting algorithm is used only once at the end part of the algorithm. The ND-CSI can be used to assess stability, power quality, dynamic and periodic steady state operation, fault and transient conditions, among... [more]
BiPAD: Binomial Point Process Based Energy-Aware Data Dissemination in Opportunistic D2D Networks
Seho Han, Kisong Lee, Hyun-Ho Choi, Howon Lee
September 21, 2018 (v1)
Keywords: binomial point process (BPP), data dissemination, device-to-device (D2D) communication, k-th furthest distance, relay selection
In opportunistic device-to-device (D2D) networks, the epidemic routing protocol can be used to optimize the message delivery ratio. However, it has the disadvantage that it causes excessive coverage overlaps and wastes energy in message transmissions because devices are more likely to receive duplicates from neighbors. We therefore propose an efficient data dissemination algorithm that can reduce undesired transmission overlap with little performance degradation in the message delivery ratio. The proposed algorithm allows devices further away than the k-th furthest distance from the source device to forward a message to their neighbors. These relay devices are determined by analysis based on a binomial point process (BPP). Using a set of intensive simulations, we present the resulting network performances with respect to the total number of received messages, the forwarding efficiency and the actual number of relays. In particular, we find the optimal number of relays to achieve almost... [more]
Identification of the Heat Equation Parameters for Estimation of a Bare Overhead Conductor’s Temperature by the Differential Evolution Algorithm
Mirza Sarajlić, Jože Pihler, Nermin Sarajlić, Gorazd Štumberger
September 21, 2018 (v1)
Keywords: conductor temperature, measurement, Optimization, overhead transmission line, parameter identification, Simulation
This paper deals with the Differential Evolution (DE) based method for identification of the heat equation parameters applied for the estimation of a bare overhead conductor`s temperature. The parameters are determined in the optimization process using a dynamic model of the conductor; the measured environmental temperature, solar radiation and wind velocity; the current and temperature measured on the tested overhead conductor; and the DE, which is applied as the optimization tool. The main task of the DE is to minimise the difference between the measured and model-calculated conductor temperatures. The conductor model is relevant and suitable for the prediction of the conductor temperature, as the agreement between measured and model-calculated conductor temperatures is exceptional, where the deviation between mean and maximum measured and model-calculated conductor temperatures is less than 0.03 °C.
Parameter Estimation of Electromechanical Oscillation Based on a Constrained EKF with C&I-PSO
Yonghui Sun, Yi Wang, Linquan Bai, Yinlong Hu, Denis Sidorov, Daniil Panasetsky
September 21, 2018 (v1)
Keywords: C&, constrained parameter estimation, extended Kalman filter, I particle swarm optimization, power systems, ringdown detection
By combining together the extended Kalman filter with a newly developed C&I particle swarm optimization algorithm (C&I-PSO), a novel estimation method is proposed for parameter estimation of electromechanical oscillation, in which critical physical constraints on the parameters are taken into account. Based on the extended Kalman filtering algorithm, the constrained parameter estimation problem is formulated via the projection method. Then, by utilizing the penalty function method, the obtained constrained optimization problem could be converted into an equivalent unconstrained optimization problem; finally, the C&I-PSO algorithm is developed to address the unconstrained optimization problem. Therefore, the parameters of electromechanical oscillation with physical constraints can be successfully estimated and better performed. Finally, the effectiveness of the obtained results has been illustrated by several test systems.
Choosing the Optimal Multi-Point Iterative Method for the Colebrook Flow Friction Equation
Pavel Praks, Dejan Brkić
August 28, 2018 (v1)
Keywords: Colebrook equation, Colebrook–White, explicit approximations, hydraulic resistances, iterative methods, pipes, three-point methods, turbulent flow
The Colebrook equation is implicitly given in respect to the unknown flow friction factor λ; λ = ζ ( R e , ε * , λ ) which cannot be expressed explicitly in exact way without simplifications and use of approximate calculus. A common approach to solve it is through the Newton⁻Raphson iterative procedure or through the fixed-point iterative procedure. Both require in some cases, up to seven iterations. On the other hand, numerous more powerful iterative methods such as three- or two-point methods, etc. are available. The purpose is to choose optimal iterative method in order to solve the implicit Colebrook equation for flow friction accurately using the least possible number of iterations. The methods are thoroughly tested and those which require the least possible number of iterations to reach the accurate solution are identified. The most powerful three-point methods require, in the worst case, only two iterations to reach the final solution. The recommended representativ... [more]
A Coupled Thermal-Hydraulic-Mechanical Nonlinear Model for Fault Water Inrush
Weitao Liu, Jiyuan Zhao, Ruiai Nie, Yuben Liu, Yanhui Du
August 28, 2018 (v1)
Keywords: coupled THM model, fault water inrush, nonlinear flow in fractured porous media, numerical model, warning levels of fault water inrush
A coupled thermal-nonlinear hydraulic-mechanical (THM) model for fault water inrush was carried out in this paper to study the water-rock-temperature interactions and predict the fault water inrush. First, the governing equations of the coupled THM model were established by coupling the particle transport equation, nonlinear flow equation, mechanical equation, and the heat transfer equation. Second, by setting different boundary conditions, the mechanical model, nonlinear hydraulic-mechanical (HM) coupling model, and the thermal-nonlinear hydraulic-mechanical (THM) coupling model were established, respectively. Finally, a numerical simulation of these models was established by using COMSOL Multiphysics. Results indicate that the nonlinear water flow equation could describe the nonlinear water flow process in the fractured zone of the fault. The mining stress and the water velocity had a great influence on the temperature of the fault zone. The temperature change of the fault zone can r... [more]
A High-Order Numerical Manifold Method for Darcy Flow in Heterogeneous Porous Media
Lingfeng Zhou, Yuan Wang, Di Feng
August 28, 2018 (v1)
Keywords: Darcy flow, heterogeneity, high-order, numerical manifold method, refraction law
One major challenge in modeling Darcy flow in heterogeneous porous media is simulating the material interfaces accurately. To overcome this defect, the refraction law is fully introduced into the numerical manifold method (NMM) as an a posteriori condition. To achieve a better accuracy of the Darcy velocity and continuous nodal velocity, a high-order weight function with a continuous nodal gradient is adopted. NMM is an advanced method with two independent cover systems, which can easily solve both continuous and discontinuous problems in a unified form. Moreover, a regular mathematical mesh, independent of the physical domain, is used in the NMM model. Compared to the conforming mesh of other numerical methods, it is more efficient and flexible. A number of numerical examples were simulated by the new NMM model, comparing the results with the original NMM model and the analytical solutions. Thereby, it is proven that the proposed method is accurate, efficient, and robust for modeling... [more]
Underground Risk Index Assessment and Prediction Using a Simplified Hierarchical Fuzzy Logic Model and Kalman Filter
Muhammad Fayaz, Israr Ullah, Do-Hyeun Kim
August 28, 2018 (v1)
Keywords: fuzzy inference system, hierarchical fuzzy logic (HFL), membership functions (MFs), risk assessment, simplified hierarchical fuzzy logic (SHFL), underground risk
Normally, most of the accidents that occur in underground facilities are not instantaneous; rather, hazards build up gradually behind the scenes and are invisible due to the inherent structure of these facilities. An efficient inference system is highly desirable to monitor these facilities to avoid such accidents beforehand. A fuzzy inference system is a significant risk assessment method, but there are three critical challenges associated with fuzzy inference-based systems, i.e., rules determination, membership functions (MFs) distribution determination, and rules reduction to deal with the problem of dimensionality. In this paper, a simplified hierarchical fuzzy logic (SHFL) model has been suggested to assess underground risk while addressing the associated challenges. For rule determination, two new rule-designing and determination methods are introduced, namely average rules-based (ARB) and max rules-based (MRB). To determine efficient membership functions (MFs), a module named th... [more]
A Blended Risk Index Modeling and Visualization Based on Hierarchical Fuzzy Logic for Water Supply Pipelines Assessment and Management
Muhammad Fayaz, Shabir Ahmad, Israr Ullah, DoHyeun Kim
July 31, 2018 (v1)
Keywords: blended model, hierarchical fuzzy logic, risk index, visualization, water supply pipelines
Critical infrastructure such as power and water delivery is growing rapidly in the developing world and there are developed assets that must be maintained in developed nations. One underground component that is difficult to inspect is water supply pipelines. Most of the water line accidents occur in buildings is due to pipeline damage. To minimize accidental loss, a risk assessment method is needed to continuously assess risk and report any abnormality for preventative maintenance. In this work, a blended hierarchical fuzzy logic model for water supply pipeline risk index assessment is proposed. Four important parameters are inputs to the proposed blended hierarchical fuzzy logic model. The blended hierarchical fuzzy logic model dramatically reduces the number of conditions in the rule base. Rule reduction is important because the transparency and interpretation are compromised by an overly large set. Further, it is challenging to accurately design a large number of rules because rule... [more]
The Impact of Global Sensitivities and Design Measures in Model-Based Optimal Experimental Design
René Schenkendorf, Xiangzhong Xie, Moritz Rehbein, Stephan Scholl, Ulrike Krewer
July 31, 2018 (v1)
Keywords: global parameter sensitivities, optimal design measures, optimal experimental design, point estimate method, robustification
In the field of chemical engineering, mathematical models have been proven to be an indispensable tool for process analysis, process design, and condition monitoring. To gain the most benefit from model-based approaches, the implemented mathematical models have to be based on sound principles, and they need to be calibrated to the process under study with suitable model parameter estimates. Often, the model parameters identified by experimental data, however, pose severe uncertainties leading to incorrect or biased inferences. This applies in particular in the field of pharmaceutical manufacturing, where usually the measurement data are limited in quantity and quality when analyzing novel active pharmaceutical ingredients. Optimally designed experiments, in turn, aim to increase the quality of the gathered data in the most efficient way. Any improvement in data quality results in more precise parameter estimates and more reliable model candidates. The applied methods for parameter sens... [more]
Predicting the Operating States of Grinding Circuits by Use of Recurrence Texture Analysis of Time Series Data
Jason P. Bardinas, Chris Aldrich, Lara F. A. Napier
July 31, 2018 (v1)
Keywords: AlexNet, comminution, grinding, multivariate image analysis, nonlinear time series analysis, textons, texture analysis, VGG16
Grinding circuits typically contribute disproportionately to the overall cost of ore beneficiation and their optimal operation is therefore of critical importance in the cost-effective operation of mineral processing plants. This can be challenging, as these circuits can also exhibit complex, nonlinear behavior that can be difficult to model. In this paper, it is shown that key time series variables of grinding circuits can be recast into sets of descriptor variables that can be used in advanced modelling and control of the mill. Two real-world case studies are considered. In the first, it is shown that the controller states of an autogenous mill can be identified from the load measurements of the mill by using a support vector machine and the abovementioned descriptor variables as predictors. In the second case study, it is shown that power and temperature measurements in a horizontally stirred mill can be used for online estimation of the particle size of the mill product.
RadViz Deluxe: An Attribute-Aware Display for Multivariate Data
Shenghui Cheng, Wei Xu, Klaus Mueller
July 31, 2018 (v1)
Keywords: generalized barycentric interpolation, multi-objective layout, multivariate data, RadViz
Modern data, such as occurring in chemical engineering, typically entail large collections of samples with numerous dimensional components (or attributes). Visualizing the samples in relation of these components can bring valuable insight. For example, one may be able to see how a certain chemical property is expressed in the samples taken. This could reveal if there are clusters and outliers that have specific distinguishing properties. Current multivariate visualization methods lack the ability to reveal these types of information at a sufficient degree of fidelity since they are not optimized to simultaneously present the relations of the samples as well as the relations of the samples to their attributes. We propose a display that is designed to reveal these multiple relations. Our scheme is based on the concept of RadViz, but enhances the layout with three stages of iterative refinement. These refinements reduce the layout error in terms of three essential relationships—sample to... [more]
How to Generate Economic and Sustainability Reports from Big Data? Qualifications of Process Industry
Esa Hämäläinen, Tommi Inkinen
July 31, 2018 (v1)
Keywords: Big Data, economic efficiency, economic geography, process industry, sustainability
Big Data may introduce new opportunities, and for this reason it has become a mantra among most industries. This paper focuses on examining how to develop cost and sustainable reporting by utilizing Big Data that covers economic values, production volumes, and emission information. We assume strongly that this use supports cleaner production, while at the same time offers more information for revenue and profitability development. We argue that Big Data brings company-wide business benefits if data queries and interfaces are built to be interactive, intuitive, and user-friendly. The amount of information related to operations, costs, emissions, and the supply chain would increase enormously if Big Data was used in various manufacturing industries. It is essential to expose the relevant correlations between different attributes and data fields. Proper algorithm design and programming are key to making the most of Big Data. This paper introduces ideas on how to refine raw data into valua... [more]
Numerical Aspects of Data Reconciliation in Industrial Applications
Maurício M. Câmara, Rafael M. Soares, Thiago Feital, Thiago K. Anzai, Fabio C. Diehl, Pedro H. Thompson, José Carlos Pinto
July 31, 2018 (v1)
Keywords: industrial data reconciliation, nonlinear programming, offshore oil production, process monitoring
Data reconciliation is a model-based technique that reduces measurement errors by making use of redundancies in process data. It is largely applied in modern process industries, being commercially available in software tools. Based on industrial applications reported in the literature, we have identified and tested different configuration settings providing a numerical assessment on the performance of several important aspects involved in the solution of nonlinear steady-state data reconciliation that are generally overlooked. The discussed items are comprised of problem formulation, regarding the presence of estimated parameters in the objective function; solution approach when applying nonlinear programming solvers; methods for estimating objective function gradients; initial guess; and optimization algorithm. The study is based on simulations of a rigorous and validated model of a real offshore oil production system. The assessment includes evaluations of solution robustness, constr... [more]
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