Measures of Model Performance Based On the Log Accuracy Ratio

Morley, S.; Brito, Thiago; Welling, D. T.

doi:10.1002/2017sw001669

Cited by 208 publications

(236 citation statements)

References 63 publications

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“…Median symmetric accuracy error metric (Morley et al, ) of the simulated and the observed electron flux values presented in Figure during the March 2015 (left) and 2013 (right) magnetic storms. Other error metrics are presented in supporting information, Figures S7 and S8.…”

Section: Resultsmentioning

confidence: 99%

Rapid Outer Radiation Belt Flux Dropouts and Fast Acceleration During the March 2015 and 2013 Storms: The Role of Ultra‐Low Frequency Wave Transport From a Dynamic Outer Boundary

et al. 2020

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We present simulations of the outer radiation belt electron flux during the March 2015 and 2013 storms using a radial diffusion model. Despite differences in disturbance short‐time intensity between the two storms, the response of the ultra‐relativistic electrons in the outer radiation belt was remarkably similar, both showing a sudden drop in the electron flux followed by a rapid enhancement in the outer belt flux to levels over an order of magnitude higher than those observed during the pre‐storm interval. Simulations of the ultra‐relativistic electron flux during the March 2015 storm show that outward radial diffusion can explain the flux dropout down to L*~4. However, in order to reproduce, the observed flux dropout at L* < 4 requires the addition of a loss process characterized by an electron lifetime of around 1 hr operating below L*~3.5 during the flux dropout interval. Nonetheless, during the pre‐storm and recovery phase of both storms, the radial diffusion simulation reproduces the observed flux dynamics. For the March 2013 storm, the flux dropout across all L‐shells is reproduced by outward radial diffusion activity alone. However, during the flux enhancement interval at relativistic energies, there is evidence of a growing local peak in the electron phase space density at L*~3.8, consistent with local acceleration such as by very low frequency chorus waves. Overall, the simulation results for both storms can accurately reproduce the observed electron flux only when event specific radial diffusion coefficients are used, instead of the empirical diffusion coefficients derived from ultra‐low frequency wave statistics.

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Section: Resultsmentioning

confidence: 99%

Rapid Outer Radiation Belt Flux Dropouts and Fast Acceleration During the March 2015 and 2013 Storms: The Role of Ultra‐Low Frequency Wave Transport From a Dynamic Outer Boundary

et al. 2020

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“…The third metric is the median symmetric accuracy (MdSA), defined as (Morley, 2016;Morley et al, 2018) The MdAPE has the drawback of penalizing over-prediction compared with under-predictions, and thus favors under-forecasting models.…”

Section: Error Metrics Definitionmentioning

confidence: 99%

“…The fourth metric is the median log accuracy ratio (MdLQ), given by (Morley, 2016;Morley et al, 2018) MdLQ = Med(log 10 (Q)). The fourth metric is the median log accuracy ratio (MdLQ), given by (Morley, 2016;Morley et al, 2018) MdLQ = Med(log 10 (Q)).…”

Section: Error Metrics Definitionmentioning

confidence: 99%

On the Use of Different Magnetic Field Models for Simulating the Dynamics of the Outer Radiation Belt Electrons During the October 1990 Storm

Loridan

Ripoll

et al. 2019

JGR Space Physics

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During geomagnetic storms, the magnetic field in the outer belt is known to be significantly distorted by the solar wind, such that the outer belt dynamics can be greatly impacted by the magnetic field topology. In this context, we develop a reduced Fokker‐Planck code that includes the effects related to realistic magnetic field models (by using the existing dedicated LANLGeoMag library) through the steps of preprocessing, postprocessing, and, for the first time, during the computation of the reduced Fokker‐Planck diffusion equation itself. We perform the solutions of the reduced Fokker‐Planck equation in the framework of the geomagnetic storm that occurred from 9 October to 15 October 1990. With the use of Combined Release and Radiation Effects Satellite observations, the magnetic field model is shown to strongly affect the way of conciliating theory with observations (processing steps). More specifically, we explain analytically and numerically why the use of a dipole field can lead to misleading interpretations on the local enhancements (attributed to local acceleration) displayed by the electron distribution function, resulting in inaccurate simulations results at large L‐shells. The consideration of a realistic field does not produce any artificial peaks. With such corrected data sets, a great part of the dynamics can be described by radial transport and is thus better reproduced by the simulations. This crucial importance of the field geometry is further emphasized with the calculation of unidirectional, omnidirectional, and integral electron fluxes, and their accuracy is quantified thanks to dedicated metrics.

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“…However, as mentioned by Tofallis, this method is no longer feasible for the investigation of error propagation with respect to the crack length in a single test due to its biased characteristics. Therefore, logarithmic accuracy ratio (AR) is implemented for the analysis of error propagation within a single test, and the formulation is expressed as

{AR}_{f} = log ((), \frac{N_{f}}{{(N_{gt})}_{f}})

where AR f is the logarithmic AR when crack length is a f while the predicted fatigue cycle is ( N gt ) f . Because the predicted data are strictly positive, this method is well suited in the current study; it provides quantitative information of error propagation with respect to crack length, as well as a distinguishable visualization of both underprediction and overprediction.…”

Section: Online‐offline Prognosis Modelmentioning

confidence: 99%

An online‐offline prognosis model for fatigue life prediction under biaxial cyclic loading with overloads

Datta

Chattopadhyay

et al. 2019

Fatigue Fract Eng Mat Struct

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This paper presents a robust online‐offline model for the prediction of crack propagation under complex in‐phase biaxial fatigue loading in the presence of overloads of different magnitudes. The online prognosis model comprises a combination of finite element analysis and data‐driven regression to predict the crack propagation under constant loading, while the offline model is trained using experimental data to inform the post‐overload crack growth retardation behavior to the online model. The developed methodology is validated by conducting biaxial fatigue experiments using aluminum AA7075‐T651 alloy cruciform specimens. A close correlation is observed between the experimental results and model predictions. The results show that the model successfully predicts the crack retardation behavior under the influence of overloads with different magnitudes occurring at different stages of fatigue crack growth. Error analysis is conducted to investigate the sensitivities of the number of training points and crack increments to the prediction accuracy. In addition, the error propagation with respect to the crack length is studied, which provides constructive suggestions for further model improvement.

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Measures of Model Performance Based On the Log Accuracy Ratio

Cited by 208 publications

References 63 publications

Rapid Outer Radiation Belt Flux Dropouts and Fast Acceleration During the March 2015 and 2013 Storms: The Role of Ultra‐Low Frequency Wave Transport From a Dynamic Outer Boundary

Rapid Outer Radiation Belt Flux Dropouts and Fast Acceleration During the March 2015 and 2013 Storms: The Role of Ultra‐Low Frequency Wave Transport From a Dynamic Outer Boundary

On the Use of Different Magnetic Field Models for Simulating the Dynamics of the Outer Radiation Belt Electrons During the October 1990 Storm

An online‐offline prognosis model for fatigue life prediction under biaxial cyclic loading with overloads

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