Determination of fokker-planck equations from experimental data sets of complex systems

2008 ◽  
pp. 273-281
Author(s):  
Rudolf Friedrich ◽  
Silke Siegert ◽  
Joachim Peinke
Keyword(s):  
Experimental Data ◽  
Complex Systems ◽  
Data Sets ◽  
Fokker Planck Equations ◽  
Fokker Planck

scholarly journals Manning's roughness coefficient determination in laboratory experiments using 2D modeling and automatic calibration

2020 ◽  
pp. 22-33
Author(s):  
Basile Lavoie ◽  
Tew-Fik Mahdi
Keyword(s):  
Experimental Data ◽  
Laboratory Experiments ◽  
Numerical Models ◽  
Roughness Coefficient ◽  
Automatic Calibration ◽  
Test Cases ◽  
Data Sets ◽  
Step Method ◽  
Numerous Data

Reliable experimental data are essential for choosing and validating numerical models. Although numerous data sets have been presented in the literature, few have been made widely available to the scientific community. Additionally, these experimental data sets have generally given little attention to the determination of Manning's roughness coefficients. This paper addresses these two issues. Three channel configurations are studied: a flatbed channel, a channel with a triangular sill and a channel with a triangular abutment. Three increasing permanent discharges are used for each configuration, leading to nine test cases. The Manning's coefficients are determined using three methods: the traditional step method, automatic calibration, via a 2D hydrodynamic model, considering theoretical value intervals and automatic calibration ignoring these intervals. The results show that automatic calibration with theoretical value intervals is advantageous compared to the step method. Automatic calibration ignoring theoretical intervals yields low errors but unphysical values; therefore, it is not recommended.

Determination of the critical O2 delivery from experimental data: sensitivity to error

1988 ◽  
Vol 64 (5) ◽  
pp. 2074-2082 ◽  
Author(s):  
R. W. Samsel ◽  
P. T. Schumacker
Keyword(s):  
Experimental Data ◽  
Experimental Error ◽  
Polynomial Regression ◽  
Regression Line ◽  
Real Data ◽  
Data Sets ◽  
Regression Techniques ◽  
O2 Delivery ◽  
Single Regression

Normally, metabolic need determines tissue O2 consumption (VO2). In states of reduced supply, VO2 declines sharply below a critical level of O2 delivery (QO2 = blood flow X arterial O2 content). Although several investigators have measured a critical O2 delivery in whole animals or in isolated tissues, there is no general agreement over how to determine the critical point from a collection of real data. In this study, we compare three algorithms for finding the critical O2 delivery from a set of experimental data. We also present a technique for estimating the effect of experimental error on the precision of these algorithms. Using 16 data sets collected in normal dogs, we compare single-line, dual-line, and polynomial regression algorithms for identifying the critical O2 delivery. The dual-line and polynomial regression techniques fit the data better (mean residual square deviation 0.024 and 0.031, respectively) than the single-regression line approach (0.110). To investigate the influence of experimental error on the derived critical QO2, we used a Monte Carlo technique, repeatedly perturbing the experimental data to simulate experimental error. We then calculated the variance of the critical QO2 frequency distribution obtained when the three algorithms were applied to the perturbed data. By this analysis, the dual-line regression technique was less sensitive to experimental error than the polynomial technique.

Fokker–Planck equations in the simulation of complex systems

1994 ◽  
Vol 36 (1) ◽  
pp. 17-48 ◽  
Author(s):  
Antonio García-Olivares ◽  
Antonio Muñoz
Keyword(s):  
Complex Systems ◽  
Fokker Planck Equations ◽  
Fokker Planck

From Data to Assessment Models, Demonstrated through a Digital Twin of Marine Risers

2021 ◽  
Author(s):  
Ehsan Kharazmi ◽  
Zhicheng Wang ◽  
Dixia Fan ◽  
Samuel Rudy ◽  
Themis Sapsis ◽  
...  
Keyword(s):  
Machine Learning ◽  
Experimental Data ◽  
Complex Systems ◽  
Fatigue Damage ◽  
Complete Characterization ◽  
Sensor Data ◽  
Data Sets ◽  
Multiple Sources ◽  
Marine Risers ◽  
Vortex Induced Vibrations

Abstract Assessing the fatigue damage in marine risers due to vortex-induced vibrations (VIV) serves as a comprehensive example of using machine learning methods to derive assessment models of complex systems. A complete characterization of response of such complex systems is usually unavailable despite massive experimental data and computation results. These algorithms can use multi-fidelity data sets from multiple sources, including real-time sensor data from the field, systematic experimental data, and simulation data. Here we develop a three-pronged approach to demonstrate how tools in machine learning are employed to develop data-driven models that can be used for accurate and efficient fatigue damage predictions for marine risers subject to VIV.

Rule-Based Mamdani-Type Fuzzy Modeling of Heating and Cooling Performances of Counter Flow Ranque-Hilsch Vortex Tubes with Different Geometric Construction for Brass

2013 ◽  
Vol 372 ◽  
pp. 346-349
Author(s):  
Dilek Nur Ozen ◽  
Adnan Berber ◽  
Kevser Dincer
Keyword(s):  
Experimental Data ◽  
Vortex Tube ◽  
Modeling Technique ◽  
Data Sets ◽  
Geometric Constructions ◽  
Counter Flow ◽  
Rule Based ◽  
Heating And Cooling ◽  
Vortex Tubes

In this study, thermal performances of counter flow Ranque-Hilsch vortex tubes were experimentally investigated and modeled with a Rule Based Mamdani-Type Fuzzy (RBMTF) modeling technique. The vortex tubes were made of brass. Diameter of vortex tube (D) was 10 mm. Length of vortex tube (L) was 10D, 11D, 12D, 13D, 14D. Input parameters (ξ, L/D) and output parameters (ΔTh, ΔTc) were described by RBMTF if-then rules. 45 experimental data sets were used in the training step. R2 for the ΔTh was found to be 99.42 % and R2 for the ΔTc was 99.66 %. The actual values and RBMTF results demonstrated that RBMTF can be successfully used for the determination of heating and cooling performances of counter flow RHVT with different geometric constructions for brass.

Direct phase determination in electron crystallography: small organic molecules

1992 ◽  
Vol 50 (2) ◽  
pp. 1166-1167
Author(s):  
Douglas L. Dorset
Keyword(s):  
Organic Molecules ◽  
Data Sets ◽  
Temperature Structure ◽  
3D Analysis ◽  
Intensity Data ◽  
Electron Crystallography ◽  
Phase Determination ◽  
Measured Intensity ◽  
3D Data

The quantitative use of electron diffraction intensity data for the determination of crystal structures represents the pioneering achievement in the electron crystallography of organic molecules, an effort largely begun by B. K. Vainshtein and his co-workers. However, despite numerous representative structure analyses yielding results consistent with X-ray determination, this entire effort was viewed with considerable mistrust by many crystallographers. This was no doubt due to the rather high crystallographic R-factors reported for some structures and, more importantly, the failure to convince many skeptics that the measured intensity data were adequate for ab initio structure determinations.We have recently demonstrated the utility of these data sets for structure analyses by direct phase determination based on the probabilistic estimate of three- and four-phase structure invariant sums. Examples include the structure of diketopiperazine using Vainshtein's 3D data, a similar 3D analysis of the room temperature structure of thiourea, and a zonal determination of the urea structure, the latter also based on data collected by the Moscow group.

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