scholarly journals Development of an arc root model for studying the electrode vaporization and its influence on arc dynamics

AIP Advances ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 085324 ◽  
Author(s):  
Jindong Huo ◽  
JoAnne Ronzello ◽  
Alex Rontey ◽  
Yifei Wang ◽  
Linda Jacobs ◽  
...  
Keyword(s):  
Root Model ◽  
Arc Root

scholarly journals Towards an Efficient Arc Simulation Framework

2017 ◽  
Vol 4 (1) ◽  
pp. 79-82 ◽  
Author(s):  
R. Fuchs ◽  
M. Mürmann ◽  
H. Nordborg
Keyword(s):  
Reference Data ◽  
Low Voltage ◽  
Circuit Breaker ◽  
Test Case ◽  
Simulation Framework ◽  
Root Model ◽  
Coupled Solution ◽  
And Control ◽  
Arc Root

Arc simulations require a coupled solution of the flow and electromagnetic equations. Despite of industrial interest, there is no established simulation framework available yet. We assess the usability of STAR-CCM+ for low voltage circuit breaker simulations using a test case of a model arc chamber, since this toolkit allows to define and control the simulation in a single environment. In spite of a partially implemented arc root model, the results agree well with reference data of previous publications.

scholarly journals Lie-Algebraic Approach for Pricing Zero-Coupon Bonds in Single-Factor Interest Rate Models

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
C. F. Lo
Keyword(s):  
Interest Rate ◽  
Algebraic Approach ◽  
Dynamical Symmetry ◽  
Bond Pricing ◽  
Model Parameters ◽  
Time Varying ◽  
Single Factor ◽  
Bond Price ◽  
Interest Rate Models ◽  
Root Model

The Lie-algebraic approach has been applied to solve the bond pricing problem in single-factor interest rate models. Four of the popular single-factor models, namely, the Vasicek model, Cox-Ingersoll-Ross model, double square-root model, and Ahn-Gao model, are investigated. By exploiting the dynamical symmetry of their bond pricing equations, analytical closed-form pricing formulae can be derived in a straightfoward manner. Time-varying model parameters could also be incorporated into the derivation of the bond price formulae, and this has the added advantage of allowing yield curves to be fitted. Furthermore, the Lie-algebraic approach can be easily extended to formulate new analytically tractable single-factor interest rate models.

scholarly journals Predictive Modeling for the Growth of Salmonella spp. in Liquid Egg White and Application of Scenario-Based Risk Estimation

2021 ◽  
Vol 9 (3) ◽  
pp. 486
Author(s):  
Mi Seon Kang ◽  
Jin Hwa Park ◽  
Hyun Jung Kim
Keyword(s):  
Predictive Model ◽  
Scenario Analysis ◽  
Specific Growth ◽  
Risk Estimation ◽  
Egg White ◽  
Lag Phase ◽  
Salmonella Spp ◽  
Baseline Model ◽  
Phase Duration ◽  
Root Model

The objective of the study was to develop a predictive model of Salmonella spp. growth in pasteurized liquid egg white (LEW) and to estimate the salmonellosis risk using the baseline model and scenario analysis. Samples were inoculated with six strains of Salmonella, and bacterial growth was observed during storage at 10–37 °C. The primary models were developed using the Baranyi model for LEW. For the secondary models, the obtained specific growth rate (μmax) and lag phase duration were fitted to a square root model and Davey model, respectively, as functions of temperature (R2 ≥ 0.98). For μmax, the values were satisfied within an acceptable range (Af, Bf: 0.70–1.15). The probability of infection (Pinf) due to the consumption of LEW was zero in the baseline model. However, scenario analysis suggested possible salmonellosis for the consumption of LEW. Because Salmonella spp. proliferated much faster in LEW than in egg white (EW) during storage at 20 and 30 °C (p < 0.01), greater Pinf may be obtained for LEW when these products are stored at the same conditions. The developed predictive model can be applied to the risk management of Salmonella spp. along the food chain, including during product storage and distribution.

Modeling the Growth of Salmonella in Raw Poultry Stored under Aerobic Conditions

2008 ◽  
Vol 71 (12) ◽  
pp. 2429-2435 ◽  
Author(s):  
SILVIA A. DOMINGUEZ ◽  
DONALD W. SCHAFFNER
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Storage Temperature ◽  
Inoculum Size ◽  
Antibiotic Resistant ◽  
Aerobic Conditions ◽  
Root Model ◽  
Fail Safe ◽  
Spoilage Microflora ◽  
Raw Poultry

The presence of Salmonella in raw poultry is a well-recognized risk factor for foodborne illness. The objective of this study was to develop and validate a mathematical model that predicts the growth of Salmonella in raw poultry stored under aerobic conditions at a variety of temperatures. One hundred twelve Salmonella growth rates were extracted from 12 previously published studies. These growth rates were used to develop a square-root model relating the growth rate of Salmonella to storage temperature. Model predictions were compared to growth rate measurements collected in our laboratory for four poultry-specific Salmonella strains (two antibiotic-resistant and two nonresistant strains) inoculated onto raw chicken tender-loins. Chicken was inoculated at two levels (103 CFU/cm2 and ≤ 10 CFU/cm2) and incubated at temperatures ranging from 10 to 37°C. Visual inspection of the data, bias and accuracy factors, and comparison with two other published models were used to analyze the performance of the new model. Neither antibiotic resistance nor inoculum size affected Salmonella growth rates. The presence of spoilage microflora did not appear to slow the growth of Salmonella. Our model provided intermediate predicted growth rates when compared with the two other published models. Our model predicted slightly faster growth rates than those observed in inoculated chicken in the temperature range of 10 to 28°C but slightly slower growth rates than those observed between 30 and 37°C. Slightly negative bias factors were obtained in every case (−5to −3%); however, application of the model may be considered fail-safe for storage temperatures below 28°C.

Sign in / Sign up

Export Citation Format

Share Document