Sensitivity Analysis and Parameter Optimization of a Hydrodynamic Model for the Aeration Chamber in a Water-Lifting Aerator

2013 ◽  
Vol 663 ◽  
pp. 888-893
Author(s):  
Xin Sun ◽  
Fei Fei Duan ◽  
Ting Lin Huang
Keyword(s):  
Sensitivity Analysis ◽  
Hydrodynamic Model ◽  
Flow Resistance ◽  
Water Velocity ◽  
Force Balance ◽  
Model Parameters ◽  
Total Force ◽  
Two Phase ◽  
Optimized Model ◽  
Resistance Coefficients

A one-dimensional hydrodynamic model for the aeration chamber in the water-lifting aerator was developed on the basis of the total force balance between the driving force and flow resistance acting on the gas-liquid two-phase flow. Water velocity in the aeration chamber was predicted under different combinations of flow resistance coefficients at the top (KT) and the entrance and exit (KE), the results of sensitivity analysis showed that both KT and KE have significant effect on the predicted water velocity and gas holdup in the riser of the aeration chamber. Taking the water velocity as the main objective, flow resistance coefficients of KT and KE were optimized as and , where Ulr is the superficial water velocity. Using optimized model parameters, the water velocities were well predicted within ±7% of the measured ones respectively.

Development and Sensitivity Analysis of Model for Aeration Chamber in Water-Circulating Aerator

2012 ◽  
Vol 260-261 ◽  
pp. 663-668
Author(s):  
Xin Sun ◽  
Fei Fei Duan ◽  
Ting Lin Huang ◽  
Meng Dan Zhang
Keyword(s):  
Sensitivity Analysis ◽  
Flow Resistance ◽  
Mathematic Model ◽  
Resistance Coefficient ◽  
Water Velocity ◽  
Force Balance ◽  
Model Parameters ◽  
Prediction Errors ◽  
Two Phase ◽  
One Dimensional

Based on the force balance between the driving force and drag force acting on the gas-liquid two-phase flow in the aeration chamber, a one-dimensional mathematic model of water velocity for the aeration chamber was developed and solved with METLAB. Sensitivity analysis of the model parameters showed that the prediction results were greatly dependant on the flow resistance coefficient at the top (KT) and the coefficient due to local disturbances at the entrance and exit (KE). Using optimized parameters, under air flow rates higher than 0.055m³/s, prediction errors of gas holdup and water velocity can both be further decreased within ± 9%. Developed model of water velocity can be used to design and optimize the aeration chamber in the water-circulating aerator.

Systematic Parameter Estimation and Sensitivity Analysis Using a Multidimensional PEMFC Model Coupled With DAKOTA

2010 ◽  
Author(s):  
Brian Carnes ◽  
Ken S. Chen ◽  
Fangming Jiang ◽  
Gang Luo ◽  
Chao-Yang Wang
Keyword(s):  
Sensitivity Analysis ◽  
Parameter Estimation ◽  
Proton Exchange Membrane ◽  
Computational Models ◽  
Proton Exchange ◽  
Operating Conditions ◽  
Critical Parameters ◽  
Model Parameters ◽  
Two Phase ◽  
Manual Adjustment

Current computational models for proton exchange membrane fuel cells (PEMFCs) include a large number of parameters such as boundary conditions, material properties, and numerous parameters used in sub-models for membrane transport, two-phase flow and electrochemistry. In order to successfully use a computational PEMFC model in design and optimization, it is important to identify critical parameters under a wide variety of operating conditions, such as relative humidity, current load, temperature, etc. Moreover, when experimental data is available in the form of polarization curves or local distribution of current and reactant/product species (e.g., O2, H2O concentrations), critical parameters can be estimated in order to enable the model to better fit the data. Sensitivity analysis and parameter estimation are typically performed using manual adjustment of parameters, which is also common in parameter studies. We present work to demonstrate a systematic approach based on using a widely available toolkit developed at Sandia called DAKOTA that supports many kinds of design studies, such as sensitivity analysis as well as optimization and uncertainty quantification. In the present work, we couple a multidimensional PEMFC model (which is being developed, tested and later validated in a joint effort by a team from Penn State Univ. and Sandia National Laboratories) with DAKOTA through the mapping of model parameters to system responses. Using this interface, we demonstrate the efficiency of performing simple parameter studies as well as identifying critical parameters using sensitivity analysis. Finally, we show examples of optimization and parameter estimation using the automated capability in DAKOTA.

scholarly journals Advanced sensitivity analysis of the impact of the temporal distribution and intensity in a rainfall event on hydrograph parameters in urban catchments: a case study

2021 ◽  
Author(s):  
Francesco Fatone ◽  
Bartosz Szelag ◽  
Adam Kiczko ◽  
Darek Majerek ◽  
Monika Majewska ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Hydrodynamic Model ◽  
Estimation Method ◽  
Temporal Distribution ◽  
Rainfall Event ◽  
Model Parameters ◽  
Rainfall Distribution ◽  
Urban Catchments ◽  
Outflow Hydrograph ◽  
The Impact

Abstract. Knowledge of the variability of the hydrograph of outflow from urban catchments is highly important for measurements and evaluation of the operation of sewer networks. Currently, hydrodynamic models are most frequently used for hydrograph modeling. Since a large number of their parameters have to be identified, there may be problems at the calibration stage. Hence, the sensitivity analysis is used to limit the number of parameters. However, the current sensitivity analysis methods ignore the effect of the temporal distribution and intensity of precipitation in a rainfall event on the catchment outflow hydrograph. The article presents the methodology of construction of a simulator of catchment outflow hydrograph parameters (volume, maximum flow). For this purpose, uncertainty analysis results obtained with the use of the GLUE (Generalized Likelihood Uncertainty Estimation) method were used. An innovative sensitivity coefficient has been proposed to study the impact of the variability of hydrodynamic model parameters depending on rainfall distribution, rainfall genesis (in the Chomicz scale), and uncertainty of estimated simulator coefficients on the parameters of the outflow hydrograph. The results indicated a considerable influence of rainfall distribution and intensity on the sensitivity factors. The greater the intensity and temporal distribution of rainfall, the lower the impact of the identified hydrodynamic model parameters on the hydrograph parameters. Additionally, the calculations confirmed the significant impact of the uncertainty of the estimated coefficient in the simulator on the sensitivity coefficients, which has a significant effect on the interpretation of the relationships obtained. The approach presented in the study can be widely applied at the model calibration stage and for appropriate selection of hydrographs for identification and validation of model parameters.

Simulation of mechanically stirred two-phase liquid-gas flow

1986 ◽  
Vol 51 (5) ◽  
pp. 1001-1015 ◽  
Author(s):  
Ivan Fořt ◽  
Vladimír Rogalewicz ◽  
Miroslav Richter
Keyword(s):  
Spatial Distribution ◽  
Velocity Field ◽  
Gas Flow ◽  
Liquid Velocity ◽  
Model Parameters ◽  
Two Phase ◽  
Mean Velocity ◽  
Rushton Turbine ◽  
Low Viscosity ◽  
Volumetric Gas Flow Rate

The study describes simulation of the motion of bubbles in gas, dispersed by a mechanical impeller in a turbulent low-viscosity liquid flow. The model employs the Monte Carlo method and it is based both on the knowledge of the mean velocity field of mixed liquid (mean motion) and of the spatial distribution of turbulence intensity ( fluctuating motion) in the investigated system - a cylindrical tank with radial baffles at the wall and with a standard (Rushton) turbine impeller in the vessel axis. Motion of the liquid is then superimposed with that of the bubbles in a still environment (ascending motion). The computation of the simulation includes determination of the spatial distribution of the gas holds-up (volumetric concentrations) in the agitated charge as well as of the total gas hold-up system depending on the impeller size and its frequency of revolutions, on the volumetric gas flow rate and the physical properties of gas and liquid. As model parameters, both liquid velocity field and normal gas bubbles distribution characteristics are considered, assuming that the bubbles in the system do not coalesce.

scholarly journals A Sensitivity Analysis of the SPACSYS Model

Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 624
Author(s):  
Yan Shan ◽  
Mingbin Huang ◽  
Paul Harris ◽  
Lianhai Wu
Keyword(s):  
Sensitivity Analysis ◽  
Wheat Yield ◽  
Climatic Conditions ◽  
Water Dynamics ◽  
Ecological Modelling ◽  
Soil Conditions ◽  
Model Parameters ◽  
Nutrient Inputs ◽  
Nutrient Pool ◽  
Wheat Field

A sensitivity analysis is critical for determining the relative importance of model parameters to their influence on the simulated outputs from a process-based model. In this study, a sensitivity analysis for the SPACSYS model, first published in Ecological Modelling (Wu, et al., 2007), was conducted with respect to changes in 61 input parameters and their influence on 27 output variables. Parameter sensitivity was conducted in a ‘one at a time’ manner and objectively assessed through a single statistical diagnostic (normalized root mean square deviation) which ranked parameters according to their influence of each output variable in turn. A winter wheat field experiment provided the case study data. Two sets of weather elements to represent different climatic conditions and four different soil types were specified, where results indicated little influence on these specifications for the identification of the most sensitive parameters. Soil conditions and management were found to affect the ranking of parameter sensitivities more strongly than weather conditions for the selected outputs. Parameters related to drainage were strongly influential for simulations of soil water dynamics, yield and biomass of wheat, runoff, and leaching from soil during individual and consecutive growing years. Wheat yield and biomass simulations were sensitive to the ‘ammonium immobilised fraction’ parameter that related to soil mineralization and immobilisation. Simulations of CO2 release from the soil and soil nutrient pool changes were most sensitive to external nutrient inputs and the process of denitrification, mineralization, and decomposition. This study provides important evidence of which SPACSYS parameters require the most care in their specification. Moving forward, this evidence can help direct efficient sampling and lab analyses for increased accuracy of such parameters. Results provide a useful reference for model users on which parameters are most influential for different simulation goals, which in turn provides better informed decision making for farmers and government policy alike.

scholarly journals Global Sensitivity Analysis of a Homogenized Constrained Mixture Model of Arterial Growth and Remodeling

2021 ◽  
Author(s):  
Sebastian Brandstaeter ◽  
Sebastian L. Fuchs ◽  
Jonas Biehler ◽  
Roland C. Aydin ◽  
Wolfgang A. Wall ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Model Parameters ◽  
Computational Studies ◽  
Growth And Remodeling ◽  
Global Sensitivity ◽  
Output Variability ◽  
Constrained Mixture ◽  
The One ◽  
Influential Parameters

AbstractGrowth and remodeling in arterial tissue have attracted considerable attention over the last decade. Mathematical models have been proposed, and computational studies with these have helped to understand the role of the different model parameters. So far it remains, however, poorly understood how much of the model output variability can be attributed to the individual input parameters and their interactions. To clarify this, we propose herein a global sensitivity analysis, based on Sobol indices, for a homogenized constrained mixture model of aortic growth and remodeling. In two representative examples, we found that 54–80% of the long term output variability resulted from only three model parameters. In our study, the two most influential parameters were the one characterizing the ability of the tissue to increase collagen production under increased stress and the one characterizing the collagen half-life time. The third most influential parameter was the one characterizing the strain-stiffening of collagen under large deformation. Our results suggest that in future computational studies it may - at least in scenarios similar to the ones studied herein - suffice to use population average values for the other parameters. Moreover, our results suggest that developing methods to measure the said three most influential parameters may be an important step towards reliable patient-specific predictions of the enlargement of abdominal aortic aneurysms in clinical practice.

scholarly journals Gaussian Processes Proxy Model with Latent Variable Models and Variogram-Based Sensitivity Analysis for Assisted History Matching

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4290
Author(s):  
Dongmei Zhang ◽  
Yuyang Zhang ◽  
Bohou Jiang ◽  
Xinwei Jiang ◽  
Zhijiang Kang
Keyword(s):  
Sensitivity Analysis ◽  
Gaussian Processes ◽  
Latent Variable ◽  
History Matching ◽  
Latent Variable Models ◽  
High Dimensional ◽  
Model Parameters ◽  
Variable Model ◽  
Assisted History Matching ◽  
Proxy Models

Reservoir history matching is a well-known inverse problem for production prediction where enormous uncertain reservoir parameters of a reservoir numerical model are optimized by minimizing the misfit between the simulated and history production data. Gaussian Process (GP) has shown promising performance for assisted history matching due to the efficient nonparametric and nonlinear model with few model parameters to be tuned automatically. Recently introduced Gaussian Processes proxy models and Variogram Analysis of Response Surface-based sensitivity analysis (GP-VARS) uses forward and inverse Gaussian Processes (GP) based proxy models with the VARS-based sensitivity analysis to optimize the high-dimensional reservoir parameters. However, the inverse GP solution (GPIS) in GP-VARS are unsatisfactory especially for enormous reservoir parameters where the mapping from low-dimensional misfits to high-dimensional uncertain reservoir parameters could be poorly modeled by GP. To improve the performance of GP-VARS, in this paper we propose the Gaussian Processes proxy models with Latent Variable Models and VARS-based sensitivity analysis (GPLVM-VARS) where Gaussian Processes Latent Variable Model (GPLVM)-based inverse solution (GPLVMIS) instead of GP-based GPIS is provided with the inputs and outputs of GPIS reversed. The experimental results demonstrate the effectiveness of the proposed GPLVM-VARS in terms of accuracy and complexity. The source code of the proposed GPLVM-VARS is available at https://github.com/XinweiJiang/GPLVM-VARS.

scholarly journals Cost-effectiveness of TAS-102 plus bevacizumab versus TAS-102 monotherapy in patients with metastatic colorectal cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kiyoaki Sugiura ◽  
Yuki Seo ◽  
Takayuki Takahashi ◽  
Hideyuki Tokura ◽  
Yasuhiro Ito ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Health Care ◽  
Sensitivity Analysis ◽  
Cost Effectiveness ◽  
Combination Therapy ◽  
Metastatic Colorectal Cancer ◽  
Cost Effective ◽  
Model Parameters ◽  
Combination Regimen ◽  
The Cost

Abstract Background TAS-102 plus bevacizumab is an anticipated combination regimen for patients who have metastatic colorectal cancer. However, evidence supporting its use for this indication is limited. We compared the cost-effectiveness of TAS-102 plus bevacizumab combination therapy with TAS-102 monotherapy for patients with chemorefractory metastatic colorectal cancer. Method Markov decision modeling using treatment costs, disease-free survival, and overall survival was performed to examine the cost-effectiveness of TAS-102 plus bevacizumab combination therapy and TAS-102 monotherapy. The Japanese health care payer’s perspective was adopted. The outcomes were modeled on the basis of published literature. The incremental cost-effectiveness ratio (ICER) between the two treatment regimens was the primary outcome. Sensitivity analysis was performed and the effect of uncertainty on the model parameters were investigated. Results TAS-102 plus bevacizumab had an ICER of $21,534 per quality-adjusted life-year (QALY) gained compared with TAS-102 monotherapy. Sensitivity analysis demonstrated that TAS-102 monotherapy was more cost-effective than TAS-102 and bevacizumab combination therapy at a willingness-to-pay of under $50,000 per QALY gained. Conclusions TAS-102 and bevacizumab combination therapy is a cost-effective option for patients who have metastatic colorectal cancer in the Japanese health care system.

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