Sensitivity of modeled microphysics to stochastically perturbed parameters

2021 ◽  
Author(s):  
Tomislava Vukicevic ◽  
Aleksa Stankovic ◽  
Derek Posselt
Keyword(s):  
Parameter Uncertainty ◽  
Squall Line ◽  
Physical Parameters ◽  
Test Case ◽  
Modeling Framework ◽  
Water Path ◽  
Second Moment ◽  
Ensemble Simulations ◽  
Parameter Perturbations ◽  
Stochastically Perturbed

<p>This study investigates sensitivity of  cloud and precipitation parameterized microphysics  to stochastic representation of parameter uncertainty as formulated by the stochastically perturbed parameterization (SPP) scheme.  SPP is applied to multiple microphysical parameters within a lagrangian column model, used in several prior published studies to characterize  parameter uncertainty by means of multivariate nonlinear inversions using remote sensing observations. The 1D column microphysics model is forced with prescribed time-varying profiles of temperature, humidity and vertical velocity.  This modeling framework allows for investigation of the effect of changes in model physics parameters on the model output in isolation from any feedback to the cloud-scale dynamics.</p><p>The test case selected in this study of an idealized representation of mid-latitude squall-line convection is the same as in the prior studies. This enabled using the estimates of multi-parameter distributions from the inversions in the prior studies as the basis for setting the second-moment statistics in the SPP scheme implementation. Additionally impacts of the non-stochastic and stochastic multi-parameter representation of parameterization uncertainty on the microphysics model solution could be directly compared.</p><p>The sensitivity experiments with the SPP scheme involve ensemble simulations where each member is evolved with a different stochastic sequence of parameter perturbations, as is done in the standard practice with this scheme.  The experiments explore impacts of using different decorrelation times and different estimates of second moment statistics for the parameter perturbations.  These include uncorrelated perturbations between the parameters for several values of variance for each parameter and correlated perturbations based on multi-parameter empirical statistical distributions from the prior studies.  The selection of physical parameters for the perturbations is based on the significance of their impacts derived from the prior studies . </p><p>The results are evaluated in terms of changes to the ensemble mean and variance of time evolving profiles of hydrometeor mass quantities, the microphysics processes within the model as well as in terms of the simulated column integral microphysics-sensitive satellite-based  observables. The latter include PR (Precipitation Rate) , LWP (Liquid Water Path), IWP (Ice water path), TOA-LW and TOA-SW (-Long and -Short Wave, respectively).  In each experiment six parameters were perturbed.</p><p>The analyses performed so far indicate a high sensitivity of the microphysics model to the SPP scheme. The ensemble simulations with the standard uncorrelated parameter perturbations exhibit a significant bias relative to the control simulation which uses the unperturbed parameters.  For the selected test case the skewness toward small parameter values in the SPP sampling based on the underlying log-normal distributions leads to less precipitating ice and more precipitating liquid and accumulated precipitation. The response is due to nonlinear relationships between the parameters and modeled microphysics output. The changes in microphysics output result in large mean changes in PR, LWP, IWP, TOA- LW and SW, suggesting a potential for using these and other microphysics sensitive satellite observations to evaluate and if needed correct properties of the underlying sampling distribution in the stochastic scheme.  Further analyses will be presented at the conference.</p>

scholarly journals NETWORK MODELLING AND SEMANTIC 3D CITY MODELS: TESTING THE MATURITY OF THE UTILITY NETWORK ADE FOR CITYGML WITH A WATER NETWORK TEST CASE

2018 ◽  
Vol IV-4 ◽  
pp. 13-20 ◽  
Author(s):  
I. Boates ◽  
G. Agugiaro ◽  
A. Nichersu
Keyword(s):  
Relational Database ◽  
Data Model ◽  
Database Schema ◽  
Future Research ◽  
Physical Parameters ◽  
Test Case ◽  
Network Modelling ◽  
Complex Development ◽  
Relational Database Schema ◽  
Utility Network

<p><strong>Abstract.</strong> Recent advances in semantic 3D city modelling and a demand from utility network operators for multi-utility data models integration have contributed to the emergence of an open Application Domain Extension (ADE) of the CityGML data model tailored to multiple types of utility networks. This extension, called the Utility Network ADE, is still in active development. However, work is already well underway to create data samples and to develop methods of modelling thereupon. In this paper, a mapping of the Utility Network ADE data model to a relational database schema is introduced. A sample of a freshwater network using the Utility Network ADE and based on data from the city of Nanaimo, Canada, is also presented. This sample has also been imported into a relational database schema built upon the 3DCityDB (a database implementation of CityGML) extended with a schema of the Utility Network ADE. Further to this, a series of basic network analysis functions have been defined and implemented in SQL to interact with the database so as to carry out sample atomic processes involved in network modelling, such as reading semantic properties of elements, calculating composite physical parameters of the network as a whole, and performing simple topological routing to serve as a guiding example for further and more complex development. A brief outlook is also presented, suggesting areas with high potential for future research and development of this nascent data model.</p>

Polymer Solution with Very Low Relaxation Time: A Combined Numerical-Experimental Determination Strategy

2021 ◽  
Author(s):  
Guillaume Maîtrejean ◽  
Denis C D Roux ◽  
Maxime Rosello ◽  
Pascal Jay ◽  
Jean Xing ◽  
...  
Keyword(s):  
Relaxation Time ◽  
Experimental Determination ◽  
Polymer Solution ◽  
Mixed Strategy ◽  
Numerical Approach ◽  
Physical Parameters ◽  
Test Case ◽  
Ink Jet ◽  
Elastic Polymer ◽  
Numerical Strategy

Abstract For very low relaxation time (i.e. lesser than a microsecond) viscoelastic fluid experimental determination is difficult, if not impossible. In the present work the relaxation time measurement of a weakly elastic polymer solution, too low to be measured using classical rheometry techniques, is assessed using a mixed experimental-numerical strategy. First the fluid is rheologically assessed, by measuring its shear viscosity, surface tension and density. Then the relaxation time is determined by comparing the jetting of polymer solution from a Continuous Ink-Jet (CIJ) device experimentally and numerically. The numerical approach is first validated using test case and a viscoelastic Oldroyd-B model is then used to model the experimental solution. The relaxation time is then a parameter allowing us to fit numerical simulation onto experimental results. This mixed strategy is particularly convenient for weakly elastic solution for which physical parameters can not be measured using experimental rheometry setup.

scholarly journals Tree-based fitted Q-iteration for multi-objective Markov decision processes in water resource management

2013 ◽  
Vol 15 (2) ◽  
pp. 258-270 ◽  
Author(s):  
F. Pianosi ◽  
A. Castelletti ◽  
M. Restelli
Keyword(s):  
Markov Decision Processes ◽  
Decision Processes ◽  
Test Case ◽  
Modeling Framework ◽  
Multi Objective ◽  
Markov Decision ◽  
Operating Policies ◽  
Single Objective ◽  
Hoa Binh

Multi-objective Markov decision processes (MOMDPs) provide an effective modeling framework for decision-making problems involving water systems. The traditional approach is to define many single-objective problems (resulting from different combinations of the objectives), each solvable by standard optimization. This paper presents an approach based on reinforcement learning (RL) that can learn the operating policies for all combinations of objectives in a single training process. The key idea is to enlarge the approximation of the action-value function, which is performed by single-objective RL over the state-action space, to the space of the objectives' weights. The batch-mode nature of the algorithm allows for enriching the training dataset without further interaction with the controlled system. The approach is demonstrated on a numerical test case study and evaluated on a real-world application, the Hoa Binh reservoir, Vietnam. Experimental results on the test case show that the proposed approach (multi-objective fitted Q-iteration; MOFQI) becomes computationally preferable over the repeated application of its single-objective version (fitted Q-iteration; FQI) when evaluating more than five weight combinations. In the Hoa Binh case study, the operating policies computed with MOFQI and FQI have comparable efficiency, while MOFQI provides a continuous approximation of the Pareto frontier with no additional computing costs.

scholarly journals Regional impacts of ultrafine particle emissions from the surface of the Great Lakes

2011 ◽  
Vol 11 (5) ◽  
pp. 16207-16244
Author(s):  
S. H. Chung ◽  
B. M. Basarab ◽  
T. M. VanReken
Keyword(s):  
Great Lakes ◽  
Ultrafine Particles ◽  
Ultrafine Particle ◽  
Breaking Waves ◽  
Base Case ◽  
Test Case ◽  
Detailed Knowledge ◽  
Freshwater Lakes ◽  
Lake Surface ◽  
Modeling Framework

Abstract. Quantifying the impacts of aerosols on climate requires a detailed knowledge of both the anthropogenic and the natural contributions to the aerosol population. Recent work has suggested a previously unrecognized natural source of ultrafine particles resulting from breaking waves at the surface of large freshwater lakes. This work is the first modeling study to investigate the potential for this newly discovered source to affect the aerosol number concentrations on regional scales. Using the WRF-Chem modeling framework, the impacts of wind-driven aerosol production from the surface of the Great Lakes were studied for a July 2004 test case. Simulations were performed for a base case with no lake surface emissions, a case with lake surface emissions included, and a default case wherein large freshwater lakes emit marine particles as if they were oceans. Results indicate that the lake surface emissions can enhance the surface level aerosol number concentration by ∼20 % over the remote northern Great Lakes and by ∼5 % over other parts of the Great Lakes. These results were highly sensitive the nucleation parameterization within WRF-Chem; when the nucleation process was deactivated, surface-layer enhancements from the lake emissions increased to as much as 200 %. The results reported here have significant uncertainties associated with the lake emission parameterization and the way ultrafine particles are modeled within WRF-Chem. Nevertheless, the magnitude of the impacts found in this study suggest that further study of this phenomena is merited.

scholarly journals Constitutive equations with pressure-dependent rheological parameters for describing ice creep

2019 ◽  
Vol 65 (252) ◽  
pp. 557-564
Author(s):  
MARTINA ARCANGIOLI ◽  
ANGIOLO FARINA ◽  
LORENZO FUSI ◽  
GIUSEPPE SACCOMANDI
Keyword(s):  
Experimental Data ◽  
Hydrostatic Pressure ◽  
Implicit Theories ◽  
Constitutive Models ◽  
Elongational Flow ◽  
Rheological Parameters ◽  
Physical Parameters ◽  
Creep Tests ◽  
Modeling Framework ◽  
Polycrystalline Ice

ABSTRACTExperimental data from creep tests on polycrystalline ice samples highlight not only the non-Newtonian behavior of ice but also suggest a critical dependence of the various rheological parameters upon the applied hydrostatic pressure. We propose a new modeling framework, based on implicit theories of continuum mechanics, that generalizes two well-known constitutive models by taking into account the effect of the pressure in the description of ice in creep. To ascertain the validity of the proposed models, we fit the physical parameters with experimental data for the elongational flow of ice samples. The results show good agreement with the experimental creep curves. In particular, the proposed generalized models reproduce the increase of the creep rate due to the presence of hydrostatic pressure.

Numerically Efficient Solution Techniques for Computational Fluid Dynamics and Heat Transfer Problems

2004 ◽  
Author(s):  
Marc Garbey ◽  
Wei Shyy ◽  
Bilel Hadri ◽  
Edouard Rougetet
Keyword(s):  
Heat Transfer ◽  
Broad Class ◽  
Systematic Investigation ◽  
Bioheat Transfer ◽  
Navier Stokes ◽  
Physical Parameters ◽  
Test Case ◽  
Krylov Method ◽  
Software Interface ◽  
Intelligent Software

We present a numerical software interface that can be integrated easily in a CFD or Heat transfer code and allows the systematic investigation of the efficiency of a broad class of solvers to optimize the code. We consider three classes of solvers that are respectively direct solver with LU decomposition, Krylov method with incomplete LU preconditionner and algebraic multigrid that have been implemented in Lapack, Sparskit, and Hypre. We systematically investigate the performance of these solvers with four test cases in ground flow, multiphase flow, bioheat transfer, and pressure solve in an Incompressible Navier Stokes code for flow in pipe with overset composite meshes. We show for each test case that the choice of the best solver may depend critically on the grid size, the aspect ratio of the grid, and further the physical parameters of the problem and the architecture of the processor. We have constructed an interface that allows to easily include in an existing CFD or heat transfer code any of the elliptic solvers available in Lapack, Sparskit and Hypre. This interface has the simplicity of Matlab command but keeps the efficiency of the original Fortran or C library. This interface can help us to investigate what would be the best solver as a preprocessing procedure. This work is a first step to construct intelligent software that will optimize an existing code automatically using the best algorithm for the application.

scholarly journals Generating effective models and parameters for RNA genetic circuits

2015 ◽  
Author(s):  
Chelsea Y Hu ◽  
Jeffrey D Varner ◽  
Julius B Lucks
Keyword(s):  
Gene Expression ◽  
Circuit Design ◽  
Core Gene ◽  
Equation Model ◽  
Genetic Circuit ◽  
Test Case ◽  
Genetic Circuits ◽  
Modeling Framework ◽  
Broad Array ◽  
Effective Models

RNA genetic circuitry is emerging as a powerful tool to control gene expression. However, little work has been done to create a theoretical foundation for RNA circuit design. A prerequisite to this is a quantitative modeling framework that accurately describes the dynamics of RNA circuits. In this work, we develop an ordinary differential equation model of transcriptional RNA genetic circuitry, using an RNA cascade as a test case. We show that parameter sensitivity analysis can be used to design a set of four simple experiments that can be performed in parallel using rapid cell-free transcription-translation (TX-TL) reactions to determine the thirteen parameters of the model. The resulting model accurately recapitulates the dynamic behavior of the cascade, and can be easily extended to predict the function of new cascade variants that utilize new elements with limited additional characterization experiments. Interestingly, we show that inconsistencies between model predictions and experiments led to the model-guided discovery of a previously unknown maturation step required for RNA regulator function. We also determine circuit parameters in two different batches of TX-TL, and show that batch-to-batch variation can be attributed to differences in parameters that are directly related to the concentrations of core gene expression machinery. We anticipate the RNA circuit models developed here will inform the creation of computer aided genetic circuit design tools that can incorporate the growing number of RNA regulators, and that the parameterization method will find use in determining functional parameters of a broad array of natural and synthetic regulatory systems.

scholarly journals Development of an openEHR Template for COVID-19 Based on Clinical Guidelines

10.2196/20239 ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. e20239 ◽  
Author(s):  
Mengyang Li ◽  
Heather Leslie ◽  
Bin Qi ◽  
Shan Nan ◽  
Hongshuo Feng ◽  
...  
Keyword(s):  
Decision Support ◽  
Data Model ◽  
Data Exchange ◽  
Disease Diagnosis ◽  
Information Modeling ◽  
Diagnosis And Treatment ◽  
Data Repository ◽  
Test Case ◽  
Modeling Framework ◽  
Shared Data

Background The coronavirus disease (COVID-19) was discovered in China in December 2019. It has developed into a threatening international public health emergency. With the exception of China, the number of cases continues to increase worldwide. A number of studies about disease diagnosis and treatment have been carried out, and many clinically proven effective results have been achieved. Although information technology can improve the transferring of such knowledge to clinical practice rapidly, data interoperability is still a challenge due to the heterogeneous nature of hospital information systems. This issue becomes even more serious if the knowledge for diagnosis and treatment is updated rapidly as is the case for COVID-19. An open, semantic-sharing, and collaborative-information modeling framework is needed to rapidly develop a shared data model for exchanging data among systems. openEHR is such a framework and is supported by many open software packages that help to promote information sharing and interoperability. Objective This study aims to develop a shared data model based on the openEHR modeling approach to improve the interoperability among systems for the diagnosis and treatment of COVID-19. Methods The latest Guideline of COVID-19 Diagnosis and Treatment in China was selected as the knowledge source for modeling. First, the guideline was analyzed and the data items used for diagnosis and treatment, and management were extracted. Second, the data items were classified and further organized into domain concepts with a mind map. Third, searching was executed in the international openEHR Clinical Knowledge Manager (CKM) to find the existing archetypes that could represent the concepts. New archetypes were developed for those concepts that could not be found. Fourth, these archetypes were further organized into a template using Ocean Template Editor. Fifth, a test case of data exchanging between the clinical data repository and clinical decision support system based on the template was conducted to verify the feasibility of the study. Results A total of 203 data items were extracted from the guideline in China, and 16 domain concepts (16 leaf nodes in the mind map) were organized. There were 22 archetypes used to develop the template for all data items extracted from the guideline. All of them could be found in the CKM and reused directly. The archetypes and templates were reviewed and finally released in a public project within the CKM. The test case showed that the template can facilitate the data exchange and meet the requirements of decision support. Conclusions This study has developed the openEHR template for COVID-19 based on the latest guideline from China using openEHR modeling methodology. It represented the capability of the methodology for rapidly modeling and sharing knowledge through reusing the existing archetypes, which is especially useful in a new and fast-changing area such as with COVID-19.

A Comparison Between the Use of Physical Parameters and Correction Factors in Dynamic Model Updating

1995 ◽  
Author(s):  
Walter D’Ambrogio ◽  
Annalisa Fregolent
Keyword(s):  
Elasticity Modulus ◽  
Model Updating ◽  
Mass Density ◽  
Physical Parameters ◽  
Test Case ◽  
Correction Factors ◽  
Scale Factors ◽  
Updating Procedure ◽  
Geometrical Dimensions ◽  
Selection Of

Abstract The selection of quantities and/or variables that have to be corrected during the updating process is addressed in this paper. Among quantities, the major alternative is the choice between correction factors and physical parameters. The former represent scale factors used to adjust mass and stiffness submatrices of the analytical model, while the latter include parameters such as the elasticity modulus, mass density, geometrical dimensions, etc. Advantages and limitations in the process of updating physical parameters instead of correction factors are highlighted: it can be shown that only a limited number of physical parameters can be simultaneously updated for each element. The two approaches are compared using a previously developed updating procedure to solve an experimental test case.

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