On the Need to Reparametrize the OVATION Prime (2010) Auroral Precipitation Model

2021 ◽  
Vol 46 (3) ◽  
pp. 194-199
Author(s):  
A. V. Nikolaev
Keyword(s):  
Precipitation Model

Effect of Strain Rate on Nb(C,N) Precipitation in Micro Alloy Steel Slab

2012 ◽  
Vol 535-537 ◽  
pp. 633-638 ◽  
Author(s):  
Zheng Hai Zhu ◽  
Sheng Tao Qiu
Keyword(s):  
Continuous Casting ◽  
Strain Rate ◽  
Alloy Steel ◽  
Casting Speed ◽  
Casting Process ◽  
Continuous Casting Process ◽  
Precipitation Model ◽  
Strain And Strain Rate ◽  
Steel Slab

It was analyzed by strain-induced precipitation model that Nb(C,N) precipitation in micro alloy steel slab was effected by strain rate during continuous casting process. The results are as follows: The changing of casting speed could effect the time for 5%precipitation of Nb(C,N), which was decreasing with increasing casting speed at certain temperature and strain rate. Slab strain and strain rate were too small in bending zone and leveling zone. The effect of slab strain rate on Nb(C,N) precipitation could be ignore when Nb(C,N) precipitation in continuous casting process was studied.

scholarly journals Stochastic daily precipitation model with a heavy-tailed component

2014 ◽  
Vol 14 (9) ◽  
pp. 2321-2335 ◽  
Author(s):  
N. M. Neykov ◽  
P. N. Neytchev ◽  
W. Zucchini
Keyword(s):  
Linear Models ◽  
Daily Precipitation ◽  
Daily Rainfall ◽  
Binary Logistic Regression ◽  
Skewed Distribution ◽  
Generalized Pareto ◽  
Precipitation Model ◽  
Standard Models ◽  
Heavy Tailed ◽  
Standard Software

Abstract. Stochastic daily precipitation models are commonly used to generate scenarios of climate variability or change on a daily timescale. The standard models consist of two components describing the occurrence and intensity series, respectively. Binary logistic regression is used to fit the occurrence data, and the intensity series is modeled using a continuous-valued right-skewed distribution, such as gamma, Weibull or lognormal. The precipitation series is then modeled using the joint density, and standard software for generalized linear models can be used to perform the computations. A drawback of these precipitation models is that they do not produce a sufficiently heavy upper tail for the distribution of daily precipitation amounts; they tend to underestimate the frequency of large storms. In this study, we adapted the approach of Furrer and Katz (2008) based on hybrid distributions in order to correct for this shortcoming. In particular, we applied hybrid gamma–generalized Pareto (GP) and hybrid Weibull–GP distributions to develop a stochastic precipitation model for daily rainfall at Ihtiman in western Bulgaria. We report the results of simulations designed to compare the models based on the hybrid distributions and those based on the standard distributions. Some potential difficulties are outlined.

scholarly journals Toward a next generation particle precipitation model: Mesoscale prediction through machine learning (a case study and framework for progress)

Space Weather ◽  
2021 ◽  
Author(s):  
Ryan M. McGranaghan ◽  
Jack Ziegler ◽  
Téo Bloch ◽  
Spencer Hatch ◽  
Enrico Camporeale ◽  
...  
Keyword(s):  
Machine Learning ◽  
Next Generation ◽  
Particle Precipitation ◽  
Precipitation Model

scholarly journals An Explanation of Microstructures in the Tantalum-Carbon System

1963 ◽  
Vol 7 ◽  
pp. 126-135 ◽  
Author(s):  
G. Santoro ◽  
H. B. Probst
Keyword(s):  
Chemical Analysis ◽  
High Purity ◽  
Unknown Origin ◽  
Conclusive Evidence ◽  
X Ray Diffraction ◽  
X Ray ◽  
Characteristic Appearance ◽  
Precipitation Model ◽  
Micro Structures ◽  
Carbon System

AbstractCompositions in the tantalum-carbon system were prepared by carburizing high-purity tantalum wires. The microstructures so produced exhibit regions of a characteristic striated structure identical to those observed by earlier investigators. There are disparities in the literature as to the origin of such structures in the tantalum—carbon system. They have been variously described as “twins,” “striated structure,” “precipitate,” and “structure of unknown origin.” This paper presents conclusive evidence that the structures in question are the result of precipitation on cooling. In addition, a coherent precipitation model is applied in which it is shown that the lattice relationship {0001}Ta2C‖{Klll}TaC can exist with less than 0.5% misfit. This relationship is shown to completely explain the occurrence and characteristic appearance of the observed micro structures. Correlations between chemical analysis, X-ray diffraction results, metallography, and microhardness measurements confirm the proposed precipitation model.

Chemical phosphorus removal model based on equilibrium chemistry

2005 ◽  
Vol 52 (10-11) ◽  
pp. 549-555 ◽  
Author(s):  
I. Takács ◽  
S. Murthy ◽  
P.M. Fairlamb
Keyword(s):  
Phosphorus Removal ◽  
Dissociation Constants ◽  
Chemical Precipitation ◽  
Weak Acid ◽  
Chemical Mechanisms ◽  
Model Based ◽  
Precipitation Model ◽  
Physico Chemical ◽  
Ph Range ◽  
Biological Methods

Regulations in many regions of the world require total phosphorus (TP) levels lower than 0.10mgP/L (100μgP/L) in effluents, resulting in the need to achieve very low ortho-phosphate (OP) concentrations. Chemical precipitation is a widely used technology for controlling effluent OP discharge, either on its own or supplementing biological methods. The various chemical and physico-chemical mechanisms that result in extremely low residual OP levels are complex and depend on pH. In practice, engineering calculations frequently use an empirical precipitation model. This model requires pH as input and predicts the lowest achievable OP residual of 35μgP/L at a narrow optimum pH of 6.9 – 7.0, when an excess of ferric is added. The model has been combined with a biokinetic and weak acid/base chemistry based pH model, to allow accurate prediction of pH, OP residuals and chemical sludge production. Analysis of effluent data from the Blue Plains plant shows that residuals as low as 10μgP/L OP can be achieved regularly, over a wider pH range. The precipitation model was recalibrated to match the newly available data. Subsequently it was compared with a new, mechanistic precipitation model based on solubility and dissociation constants for actual chemical compounds. The need for more accurate measurement of extremely low OP concentrations and considering the role of organics, adsorption and coagulation in chemical phosphorus removal is demonstrated.

Do you only have yourself to blame? A meta‐analytic test of the victim precipitation model

2019 ◽  
Vol 41 (8) ◽  
pp. 706-721 ◽  
Author(s):  
Lindsay Y. Dhanani ◽  
Amanda M. Main ◽  
Andrew Pueschel
Keyword(s):  
Precipitation Model

scholarly journals Regional Precipitation Model Based on Geographically and Temporally Weighted Regression Kriging

2020 ◽  
Vol 12 (16) ◽  
pp. 2547 ◽  
Author(s):  
Wei Zhang ◽  
Dan Liu ◽  
Shengjie Zheng ◽  
Shuya Liu ◽  
Hugo A. Loáiciga ◽  
...  
Keyword(s):  
Temporal Distribution ◽  
Absolute Error ◽  
Weighted Regression ◽  
Distribution Model ◽  
Monthly Precipitation ◽  
Regression Kriging ◽  
Time Step ◽  
Predictive Skill ◽  
Precipitation Model ◽  
Meteorological Modeling

High-resolution precipitation field has been widely used in hydrological and meteorological modeling. This paper establishes the spatial and temporal distribution model of precipitation in Hubei Province from 2006 through 2014, based on the data of 75 meteorological stations. This paper applies a geographically and temporally weighted regression kriging (GTWRK) model to precipitation and assesses the effects of timescales and a time-weighted function on precipitation interpolation. This work’s results indicate that: (1) the optimal timescale of the geographically and temporally weighted regression (GTWR) precipitation model is daily. The fitting accuracy is improved when the timescale is converted from months and years to days. The average mean absolute error (MAE), mean relative error (MRE), and the root mean square error (RMSE) decrease with scaling from monthly to daily time steps by 36%, 56%, and 35%, respectively, and the same statistical indexes decrease by 13%, 15%, and 14%, respectively, when scaling from annual to daily steps; (2) the time weight function based on an exponential function improves the predictive skill of the GTWR model by 3% when compared to geographically weighted regression (GWR) using a monthly time step; and (3) the GTWRK has the highest accuracy, and improves the MAE, MRE and RMSE by 3%, 10% and 1% with respect to monthly precipitation predictions, respectively, and by 3%, 10% and 5% concerning annual precipitation predictions, respectively, compared with the GWR results.

scholarly journals Hard X-Ray Imaging Observations by Yohkoh of the 15 November, 1991 Flare

1993 ◽  
Vol 141 ◽  
pp. 258-262
Author(s):  
Taro Sakao
Keyword(s):  
Magnetic Fields ◽  
Energy Release ◽  
Impulsive Phase ◽  
Time Profile ◽  
X Rays ◽  
X Ray ◽  
Precipitation Model ◽  
X Ray Imaging ◽  
Coronal Magnetic Fields ◽  
The Individual

AbstractWe present hard X-ray imaging observations by Yohkoh of the 15 November, 1991 flare. The pre-impulsive and the impulsive phase observations are summarized as follows: (1) Hard X-ray sources in the precursor (or pre–impulsive) phase appear in a much wider area compared with the impulsive phase sources and they show clear evolution just before the onset of the impulsive phase. This suggests that some global re-structuring of coronal magnetic fields led to the impulsive energy release. (2) In the impulsive phase, at the peaks of the individual spikes of the time profile, the bulk of the hard X-ray emission (above 20 keV) originates from the footpoints of the flaring loop. At the valleys between the spikes, X-rays below 30 keV are emitted from near the loop top, while higher energy ones (above 30 keV) are still emitted from the footpoints. Such behavior of hard X-ray sources can be explained by the partial precipitation model.

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