Assessing One-minute Diffuse Fraction Models Based on Worldwide Climate Features

2021 ◽  
Author(s):  
Allan R. Starke ◽  
Leonardo F.L. Lemos ◽  
Cristian M. Barni ◽  
Rubinei D. Machado ◽  
José M. Cardemil ◽  
...  
Keyword(s):  
Diffuse Fraction ◽  
Fraction Models

A Comparative Assessment of Diffuse Fraction Models

2016 ◽  
Vol 861 ◽  
pp. 509-515
Author(s):  
Ehsan Vazifeh ◽  
Matthias Schuss ◽  
Ardeshir Mahdavi
Keyword(s):  
Energy Use ◽  
Critical Issue ◽  
Comparative Assessment ◽  
Building Performance ◽  
Solar Altitude ◽  
Diffuse Fraction ◽  
Calculation Results ◽  
Irradiance Data ◽  
Relative Errors ◽  
Fraction Models

Many building performance applications (energy use, solar gains, thermal comfort, renewable energy systems, daylight, etc.) require information about both direct and diffuse components of the incident solar radiation. However, most meteorological stations only monitor global horizontal irradiance. Consequently, multiple methods have been proposed in the past to derive from measured global horizontal irradiance data the diffuse fraction. Thereby, additional data regarding other parameters such as clearness index, solar altitude, air mass, and turbidity are used. Given the importance of this procedure for the down the line tools, its reliability represents a critical issue. To address this point, we pursued an empirical approach. A number of existing methods for the computation of the diffuse fraction were selected. Actual measurements of global and diffuse irradiance were obtained for seven locations in USA and one location in Austria. The measured global irradiance data for these locations were fed to the aforementioned diffuse fraction models. The calculation results were then compared with the corresponding empirical data. The comparative assessment yielded a number of findings. The relative performance ("ranking") of the models was found to be more or less consistent across the different locations. However, none of the models can be said to be performing wholly satisfactory. For instance, the best performing model displayed only in 45 to 65 percentage of the cases relative errors less than 20%. In case of the worst performing model, the percentage of the cases for which relative errors were less than 20% was even smaller, namely 30% to 60%.

Two-Phase Friction Factor Obtained From Various Void Fraction Models During Condensation of R134A in Vertical Downward Flow at High Mass Flux

2008 ◽  
Author(s):  
Ahmet Selim Dalkilic ◽  
Suriyan Laohalertdecha ◽  
Somchai Wongwises
Keyword(s):  
Void Fraction ◽  
Annular Flow ◽  
Smooth Tube ◽  
High Mass ◽  
Two Phase ◽  
Void Fractions ◽  
Mass Fluxes ◽  
Friction Factors ◽  
Flow Void ◽  
Fraction Models

Void fractions are determined in vertical downward annular two-phase flow of R134a inside 8.1 mm i.d. smooth tube. The experiments are done at average saturated condensing temperatures of 40 and 50°C. The average qualities are between 0.84–0.94. The mass fluxes are around 515 kg m−2s−1. The experimental setup is explained elaborately. Comparisons between the void fraction determined from 35 void fraction correlations are done. According to the use of various horizontal and vertical annular flow void fraction models together with the present experimental condensation heat transfer data, similar void fraction results were obtained mostly for the smooth tube. The experimental friction factors obtained from void fraction correlations are compared with the friction factors determined from graphical information provided by Bergelin et. al. Effect of void fraction alteration on the momentum pressure drop is also presented.

Evaluation of the tail of the probability distribution of daily and sub-daily precipitation in CMIP6 models

2021 ◽  
pp. 1-61
Author(s):  
Jesse Norris ◽  
Alex Hall ◽  
J. David Neelin ◽  
Chad W. Thackeray ◽  
Di Chen
Keyword(s):  
General Circulation ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
Coupled Model ◽  
Lower Troposphere ◽  
General Circulation Models ◽  
Intercomparison Project ◽  
Cloud Tops ◽  
The Tropics ◽  
Fraction Models

AbstractDaily and sub-daily precipitation extremes in historical Coupled-Model-Intercomparison-Project-Phase-6 (CMIP6) simulations are evaluated against satellite-based observational estimates. Extremes are defined as the precipitation amount exceeded every x years, ranging from 0.01–10, encompassing the rarest events that are detectable in the observational record without noisy results. With increasing temporal resolution there is an increased discrepancy between models and observations: for daily extremes the multi-model median underestimates the highest percentiles by about a third, and for 3-hourly extremes by about 75% in the tropics. The novelty of the current study is that, to understand the model spread, we evaluate the 3-D structure of the atmosphere when extremes occur. In midlatitudes, where extremes are simulated predominantly explicitly, the intuitive relationship exists whereby higher-resolution models produce larger extremes (r=–0.49), via greater vertical velocity. In the tropics, the convective fraction (the fraction of precipitation simulated directly from the convective scheme) is more relevant. For models below 60% convective fraction, precipitation amount decreases with convective fraction (r=–0.63), but above 75% convective fraction, this relationship breaks down. In the lower-convective-fraction models, there is more moisture in the lower troposphere, closer to saturation. In the higher-convective-fraction models, there is deeper convection and higher cloud tops, which appears to be more physical. Thus, the low-convective models are mostly closer to the observations of extreme precipitation in the tropics, but likely for the wrong reasons. These inter-model differences in the environment in which extremes are simulated hold clues into how parameterizations could be modified in general circulation models to produce more credible 21st-Century projections.

scholarly journals Adaptive Neuro-Fuzzy Inference System and a Multilayer Perceptron Model Trained with Grey Wolf Optimizer for Predicting Solar Diffuse Fraction

Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1192
Author(s):  
Randall Claywell ◽  
Laszlo Nadai ◽  
Imre Felde ◽  
Sina Ardabili ◽  
Amirhosein Mosavi
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Evaluation Criteria ◽  
Absolute Error ◽  
Grey Wolf Optimizer ◽  
Multi Layer Perceptron ◽  
Grey Wolf ◽  
Inference System ◽  
Diffuse Fraction ◽  
Testing Procedures

The accurate prediction of the solar diffuse fraction (DF), sometimes called the diffuse ratio, is an important topic for solar energy research. In the present study, the current state of Diffuse irradiance research is discussed and then three robust, machine learning (ML) models are examined using a large dataset (almost eight years) of hourly readings from Almeria, Spain. The ML models used herein, are a hybrid adaptive network-based fuzzy inference system (ANFIS), a single multi-layer perceptron (MLP) and a hybrid multi-layer perceptron grey wolf optimizer (MLP-GWO). These models were evaluated for their predictive precision, using various solar and DF irradiance data, from Spain. The results were then evaluated using frequently used evaluation criteria, the mean absolute error (MAE), mean error (ME) and the root mean square error (RMSE). The results showed that the MLP-GWO model, followed by the ANFIS model, provided a higher performance in both the training and the testing procedures.

Bivariate lifetime modelling using copula functions in presence of mixture and non-mixture cure fraction models, censored data and covariates

2016 ◽  
Vol 11 (4) ◽  
pp. 261-276 ◽  
Author(s):  
Jorge Alberto Achcar ◽  
Edson Zangiacomi Martinez ◽  
José Rafael Tovar Cuevas
Keyword(s):  
Censored Data ◽  
Copula Functions ◽  
Cure Fraction ◽  
Fraction Models

scholarly journals Modeling the erythemal surface diffuse irradiance fraction for Badajoz, Spain

2017 ◽  
Vol 17 (20) ◽  
pp. 12697-12708 ◽  
Author(s):  
Guadalupe Sanchez ◽  
Antonio Serrano ◽  
María Luisa Cancillo
Keyword(s):  
Empirical Models ◽  
Experimental Measurements ◽  
Strong Impact ◽  
Diffuse Fraction ◽  
Additional Information ◽  
Mathematical Expressions ◽  
Physically Based ◽  
Physically Based Models ◽  
Ultraviolet Irradiance ◽  
Semi Empirical

Abstract. Despite its important role on the human health and numerous biological processes, the diffuse component of the erythemal ultraviolet irradiance (UVER) is scarcely measured at standard radiometric stations and therefore needs to be estimated. This study proposes and compares 10 empirical models to estimate the UVER diffuse fraction. These models are inspired from mathematical expressions originally used to estimate total diffuse fraction, but, in this study, they are applied to the UVER case and tested against experimental measurements. In addition to adapting to the UVER range the various independent variables involved in these models, the total ozone column has been added in order to account for its strong impact on the attenuation of ultraviolet radiation. The proposed models are fitted to experimental measurements and validated against an independent subset. The best-performing model (RAU3) is based on a model proposed by Ruiz-Arias et al. (2010) and shows values of r2 equal to 0.91 and relative root-mean-square error (rRMSE) equal to 6.1 %. The performance achieved by this entirely empirical model is better than those obtained by previous semi-empirical approaches and therefore needs no additional information from other physically based models. This study expands on previous research to the ultraviolet range and provides reliable empirical models to accurately estimate the UVER diffuse fraction.

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