scholarly journals Development of Multi-physics (Multiphase CFD + MCNP) simulation for generic solution vessel power calculation

2017 ◽  
Author(s):  
Seung Jun Kim ◽  
Cynthia Eileen Buechler
Keyword(s):  
Power Calculation ◽  
Mcnp Simulation ◽  
Generic Solution ◽  
Multiphase Cfd

Stopping-power determination for compound by EELS

1994 ◽  
Vol 52 ◽  
pp. 948-949 ◽  
Author(s):  
David C. Joy ◽  
Suichu Luo ◽  
John R. Dunlap ◽  
Dick Williams ◽  
Siqi Cao
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Materials Science ◽  
Average Energy ◽  
Stopping Power ◽  
Accurate Information ◽  
Power Calculation ◽  
Coulomb Collisions ◽  
Electron Energy Loss

In Physics, Chemistry, Materials Science, Biology and Medicine, it is very important to have accurate information about the stopping power of various media for electrons, that is the average energy loss per unit pathlength due to inelastic Coulomb collisions with atomic electrons of the specimen along their trajectories. Techniques such as photoemission spectroscopy, Auger electron spectroscopy, and electron energy loss spectroscopy have been used in the measurements of electron-solid interaction. In this paper we present a comprehensive technique which combines experimental and theoretical work to determine the electron stopping power for various materials by electron energy loss spectroscopy (EELS ). As an example, we measured stopping power for Si, C, and their compound SiC. The method, results and discussion are described briefly as below.The stopping power calculation is based on the modified Bethe formula at low energy:where Neff and Ieff are the effective values of the mean ionization potential, and the number of electrons participating in the process respectively. Neff and Ieff can be obtained from the sum rule relations as we discussed before3 using the energy loss function Im(−1/ε).

Comparison of iol optic power calculation refractive results using fourth-generation formulas after radial keratotomy

Reflection ◽  
2018 ◽  
Vol 7 (2) ◽  
pp. 45-49
Author(s):  
O. V. Shilovskih ◽  
◽  
A. N. Ulyanov ◽  
M. V. Kremeshkov ◽  
E. M. Titarenko ◽  
...  
Keyword(s):  
Fourth Generation ◽  
Power Calculation ◽  
Radial Keratotomy

Scalable Processing Ultrathin Polymer Dielectric Films with a Generic Solution Based Approach for Wearable Soft Electronics

2019 ◽  
Vol 4 (7) ◽  
pp. 1800681 ◽  
Author(s):  
Sujie Chen ◽  
Sai Peng ◽  
Wenjian Sun ◽  
Guoying Gu ◽  
Qing Zhang ◽  
...  
Keyword(s):  
Dielectric Films ◽  
Polymer Dielectric ◽  
Generic Solution ◽  
Soft Electronics

scholarly journals Prediction accuracy of standard and total keratometry by swept-source optical biometer for multifocal intraocular lens power calculation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hun Lee ◽  
Jae Lim Chung ◽  
Young Jun Kim ◽  
Jae Yong Kim ◽  
Hungwon Tchah
Keyword(s):  
Cataract Surgery ◽  
Case Series ◽  
Intraocular Lenses ◽  
Power Calculation ◽  
Neutral Position ◽  
Swept Source ◽  
Refractive Outcomes ◽  
Case Series Study ◽  
Significant Difference ◽  
Optical Biometer

AbstractWe aimed to compare the refractive outcomes of cataract surgery with diffractive multifocal intraocular lenses (IOLs) using standard keratometry (K) and total keratometry (TK). In this retrospective observational case series study, a total of 302 patients who underwent cataract surgery with multifocal IOL implantation were included. Predicted refractive outcomes were calculated based on the current standard formulas and a new formula developed for TK using K and TK, which were obtained from a swept-source optical biometer. At 2-month postoperatively, median absolute prediction errors (MedAEs) and proportion of eyes within ± 0.50 diopters (D) of predicted postoperative spherical equivalent (SE) refraction were analyzed. There was no significant difference between MedAEs or proportion of eyes within ± 0.50D of predicted refraction from K and TK in each formula. In TFNT00 and 839MP IOL cases, there was no difference between MedAEs from K and TK using any formula. In 829MP IOL cases, MedAE from TK was significantly larger than that from K in Barrett Universal II/Barrett TK Universal II (P = 0.033). In 677MY IOL cases, MedAE from TK was significantly larger than that from K in Haigis (P = 0.020) and Holladay 2 (P = 0.006) formulas. In the subgroup analysis for IOL, there was no difference between the proportion of eyes within ± 0.50 D of predicted refraction from K and TK using any formula. TFNT00 and 839MP IOLs were favorable with TK, with 677MY IOL with K and 829MP IOL being in a neutral position, which necessitates the study that investigates the accuracy of the new TK technology.

scholarly journals Model for Predicting the Operating Temperature of Stratospheric Airship Solar Cells with a Support Vector Machine

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1228
Author(s):  
Xuwei Wang ◽  
Zhaojie Li ◽  
Yanlei Zhang
Keyword(s):  
Support Vector Machine ◽  
Solar Cell ◽  
Energy Balance ◽  
Output Power ◽  
Operating Temperature ◽  
Support Vector ◽  
Power Calculation ◽  
Pv System ◽  
Stratospheric Airship ◽  
Cell Modules

The stratospheric airship is a kind of aircraft that completely relies on the cycle of photovoltaic energy systems to achieve long duration flight. The accurate estimation of the operating temperature of solar cell modules on stratospheric airship is extremely important for the design of photovoltaics system (PV system), the output power calculation of PV system, and the calculation of energy balance. However, the related study has been rarely reported. A support vector machine prediction method based on particle swarm optimization algorithm (PSO-SVM) was established to predict the operating temperature of solar cell modules on stratospheric airship. The PSO algorithm was used to dynamically optimize the SVM’s parameters between the operating temperature of the solar cell modules and the measured data such as atmospheric pressure, solar radiation intensity, flight speed, and ambient temperature. The operating temperature data of the two sets of solar cell modules measured in the flight test were used to verify the accuracy of the temperature prediction model, and the prediction results were compared with a back propagation neural network (BPNN) method and the simulation results calculated by COMSOL Multiphysics of COMSOL, Inc., Columbus, MA, USA. The results shown that the PSO-SVM model realized the accurate prediction of the operating temperature of solar cell modules on stratospheric airship, which can guide the design of PV system, the output power calculation of PV system, and the calculation of energy balance.

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