Journal articles: 'Semi-empirical'

1

Murrell, John N. "Semi-empirical electronic structure methods." Journal of Molecular Structure: THEOCHEM 424, no. 1-2 (February 1998): 93–99. http://dx.doi.org/10.1016/s0166-1280(97)00234-0.

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2

Chudnovsky, A., and M. Ben Ouezdon. "Semi-empirical crack tip analysis." International Journal of Fracture 37, no. 1 (May 1988): 3–11. http://dx.doi.org/10.1007/bf00017819.

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3

Xu, Zhichen, Xiaodong Zhang, and Lin Sun. "Semi-empirical Multiprocessor Performance Predictions." Journal of Parallel and Distributed Computing 39, no. 1 (November 1996): 14–28. http://dx.doi.org/10.1006/jpdc.1996.0151.

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4

Bilous, Andrii, Viktor Myroniuk, Viktor Svynchuk, Oleksandr Soshenskyi, Oleksandr Lesnik, and Yaroslav Kovbasa. "Semi-empirical estimation of log taper using stem profile equations." Journal of Forest Science 67, No. 7 (July 20, 2021): 318–27. http://dx.doi.org/10.17221/209/2020-jfs.

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In January 2019 the forest industry in Ukraine adopted European standards for measuring and grading of round wood based on mid-point diameters, which caused major discrepancies from traditionally used estimates of timber volume using top diameters. To compare methods of merchantable wood volume estimation, we investigated the stem form inside bark for two dominant tree species in Ukraine, i.e. Scots pine (Pinus sylvestris L.) and common oak (Quercus robur L.). We used tree stem measurements to fit stem profile equations, whereas simulation was applied to derive log taper. We found that Newnham's (1992) variable-exponent taper equation performed well for predicting stem taper for both tree species. Then, we simulated the structure of harvested wood, so that it replicated annual distribution of logs by their length and diameters. As a result, the average log taper was estimated at 0.836 ÷ 0.855 cm·m<sup>–1</sup> and 1.180 ÷ 0.121 cm·m<sup>–1</sup> for pine and oak, respectively. The study also indicated that log taper varied along stems. The higher rates of diameter decrease were found for butt logs, for which the taper was 2.5–3.5 times higher than its average for the whole stem. The results of our study ensure the stacked round wood volume conversion between estimates obtained using top and mid-point diameters.

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5

Joshi, A., Pushpa Kumari, and M. L. Sharma. "Synthesis of Strong Ground Motion Using Modified Semi-Empirical Technique." International Journal of Engineering and Technology 4, no. 4 (2012): 424–26. http://dx.doi.org/10.7763/ijet.2012.v4.401.

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6

Traub, Lance. "Semi-Empirical Prediction of Airfoil Hysteresis." Aerospace 3, no. 2 (March 24, 2016): 9. http://dx.doi.org/10.3390/aerospace3020009.

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7

Kollár, Mojmír, and Evangelos Hristoforou. "Semi-empirical magnetostrictive delay line modelling." Journal of Magnetism and Magnetic Materials 320, no. 20 (October 2008): e1057-e1060. http://dx.doi.org/10.1016/j.jmmm.2008.04.108.

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8

Gibson, John K., Richard G. Haire, and Toru Ogawa. "Semi-empirical models of actinide alloying." Journal of Nuclear Materials 273, no. 2 (July 1999): 139–45. http://dx.doi.org/10.1016/s0022-3115(99)00038-0.

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9

Javanainen, Arto, Veronique Ferlet-Cavrois, Jukka Jaatinen, Heikki Kettunen, Michele Muschitiello, Francesco Pintacuda, Mikko Rossi, James R. Schwank, Marty R. Shaneyfelt, and Ari Virtanen. "Semi-Empirical Model for SEGR Prediction." IEEE Transactions on Nuclear Science 60, no. 4 (August 2013): 2660–65. http://dx.doi.org/10.1109/tns.2012.2236105.

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10

Zudin, Yu B. "Semi-empirical model for intense evaporation." Thermophysics and Aeromechanics 24, no. 4 (July 2017): 523–36. http://dx.doi.org/10.1134/s0869864317040035.

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11

Nelson, P. G. "Semi-empirical Methods of Quantum Chemistry." Analytica Chimica Acta 186 (1986): 340–41. http://dx.doi.org/10.1016/s0003-2670(00)81812-7.

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12

Pan, Wei, and Thomas A. Louis. "Two semi-parametric empirical Bayes estimators." Computational Statistics & Data Analysis 30, no. 2 (April 1999): 185–96. http://dx.doi.org/10.1016/s0167-9473(98)00086-3.

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13

Hart, J. Pirie, and Andrew W. Shogan. "Semi-greedy heuristics: An empirical study." Operations Research Letters 6, no. 3 (July 1987): 107–14. http://dx.doi.org/10.1016/0167-6377(87)90021-6.

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14

Bell, Stephen. "Semi-empirical methods of quantum chemistry." Endeavour 10, no. 1 (January 1986): 52–53. http://dx.doi.org/10.1016/0160-9327(86)90065-7.

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15

Fang, Cheng, Mingde Ding, J. C. Hénoux, and W. C. Livingston. "Semi-empirical model of solar plages." Science in China Series A: Mathematics 44, no. 4 (April 2001): 528–35. http://dx.doi.org/10.1007/bf02881890.

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16

Orville-Thomas, W. J. "Semi-empirical methods of quantum chemistry." Journal of Molecular Structure: THEOCHEM 136, no. 3-4 (April 1986): 396. http://dx.doi.org/10.1016/0166-1280(86)80155-5.

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17

Albert, Richard, and William M. Malone. "Semi-empirical calculation of reactivity ratios." Journal of Polymer Science: Polymer Symposia 42, no. 1 (March 8, 2007): 245–55. http://dx.doi.org/10.1002/polc.5070420127.

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18

Leishman, J. G., and T. S. Beddoes. "A Semi-Empirical Model for Dynamic Stall." Journal of the American Helicopter Society 34, no. 3 (July 1, 1989): 3–17. http://dx.doi.org/10.4050/jahs.34.3.

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19

Leishman, J. G., and T. S. Beddoes. "A Semi‐Empirical Model for Dynamic Stall." Journal of the American Helicopter Society 34, no. 3 (July 1, 1989): 3–17. http://dx.doi.org/10.4050/jahs.34.3.3.

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20

Amenabar, Juan P. "Semi-Empirical Approach for Missile Seeker Sizing." Journal of Spacecraft and Rockets 49, no. 3 (May 2012): 529–34. http://dx.doi.org/10.2514/1.a32075.

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21

Giannelli, Robert Anthony, Ryan Stubleski, and Anthony Saunders. "Semi-empirical Analysis of Cold Start Emissions." SAE International Journal of Fuels and Lubricants 7, no. 2 (April 1, 2014): 591–99. http://dx.doi.org/10.4271/2014-01-1619.

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22

Guimbard, Sébastien, Jérôme Gourrion, Marcos Portabella, Antonio Turiel, Carolina Gabarro, and Jordi Font. "SMOS Semi-Empirical Ocean Forward Model Adjustment." IEEE Transactions on Geoscience and Remote Sensing 50, no. 5 (May 2012): 1676–87. http://dx.doi.org/10.1109/tgrs.2012.2188410.

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23

HUANG, LIN CHUN, JUN JIE HU, and BING RUI LI. "SEMI-EMPIRICAL STUDY OF A SUPRAMOLECULE SWITCH." Journal of Theoretical and Computational Chemistry 08, no. 04 (August 2009): 575–85. http://dx.doi.org/10.1142/s0219633609004927.

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Semi-empirical (PM6) electronic structure calculations are reported on a newly synthesized supramolecule. The supramolecule possesses two different states, with different location of the arm under the external stimulus. The computational results capture the two states, the key switch-like character of the supramolecule.

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24

Mazzone, A. M. "Bonding in metallic superlattices: semi-empirical calculations." Modelling and Simulation in Materials Science and Engineering 8, no. 1 (January 1, 2000): 13–23. http://dx.doi.org/10.1088/0965-0393/8/1/302.

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25

Seenappa, L., H. C. Manjunatha, K. N. Sridhar, and Chikka Hanumantharayappa. "Semi empirical formula for exposure buildup factors." Radiation Effects and Defects in Solids 172, no. 9-10 (October 3, 2017): 790–98. http://dx.doi.org/10.1080/10420150.2017.1393426.

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26

Miller, J. H., W. E. Wilson, and S. T. Manson. "Secondary Electron Spectra: A Semi-Empirical Model." Radiation Protection Dosimetry 13, no. 1-4 (December 1, 1985): 27–30. http://dx.doi.org/10.1093/rpd/13.1-4.27.

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27

Miller, J. H., W. E. Wilson, and S. T. Manson. "Secondary Electron Spectra: A Semi-Empirical Model." Radiation Protection Dosimetry 13, no. 1-4 (December 1, 1985): 27–30. http://dx.doi.org/10.1093/oxfordjournals.rpd.a079541.

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28

Kazakov, V. E., H. C. Budnikov, and Y. N. Polyakov. "Semi-Empirical Simulation of Mercury Surface formation." Instrumentation Science & Technology 24, no. 2 (May 1996): 115–30. http://dx.doi.org/10.1080/10739149608000473.

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29

DiGiuseppe, Gianfranco, and Li Sun. "Semi-Empirical Equations to Estimate SOFC Lifetime." ECS Transactions 25, no. 2 (December 17, 2019): 801–10. http://dx.doi.org/10.1149/1.3205598.

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30

Anderson, David N., Michael Mendillo, and Bruce Herniter. "A semi-empirical low-latitude ionospheric model." Radio Science 22, no. 2 (March 1987): 292–306. http://dx.doi.org/10.1029/rs022i002p00292.

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31

Namazi-Rad, Mohammad-Reza, Pascal Perez, Matthew Berryman, and Rohan Wickramasuriya. "A Semi-Empirical Determination of Perceived Liveability." Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique 129, no. 1 (December 30, 2015): 5–24. http://dx.doi.org/10.1177/0759106315615510.

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32

Kurz, David, Jitendra Sharma, Marolo Alfaro, and Jim Graham. "Semi-empirical elastic–thermoviscoplastic model for clay." Canadian Geotechnical Journal 53, no. 10 (October 2016): 1583–99. http://dx.doi.org/10.1139/cgj-2015-0598.

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Clays exhibit creep in compression and shear. In one-dimensional compression, creep is commonly known as “secondary compression” even though it is also a significant component of deformations resulting from shear straining. It reflects viscous behaviour in clays and therefore depends on load duration, stress level, the ratio of shear stress to compression stress, strain rate, and temperature. Research described in the paper partitions strains into elastic (recoverable) and plastic (nonrecoverable) components. The plastic component includes viscous strains defined by a creep rate coefficient ψ that varies with plasticity index and temperature (T), but not with stress level or overconsolidation ratio (OCR). Earlier elastic–viscoplastic (EVP) models have been modified so that ψ = ψ(T) in a new elastic–thermoviscoplastic (ETVP) model. The paper provides a sensitivity analysis of simulated results from undrained (CIŪ) triaxial compression tests for normally consolidated and lightly overconsolidated clays. Axial strain rates range from 0.15%/day to 15%/day, and temperatures from 28 to 100 °C.

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33

Valio, Adriana. "Semi-empirical modelling of stellar magnetic activity." Proceedings of the International Astronomical Union 7, S286 (October 2011): 307–16. http://dx.doi.org/10.1017/s1743921312005017.

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AbstractSince Galileo, for four hundred years, dark spots have been observed systematically on the surface of the Sun. The monitoring of the sunspot number has shown that their number varies periodically every 11 years. This is the well-known solar activity cycle that is caused by the periodic changes of the magnetic field of the Sun. Not only do spots vary in number on a timescale of a decade, but the total luminosity and other signatures of activity such as flares and coronal mass ejections also increase and decrease with the 11-year cycle. Still unexplained to the present date are periods of decades with almost an absence of activity, where the best known example is the Maunder Minimum. Other stars also exhibit signs of cyclic activity, however the level of activity is usually thousand times higher than the solar one. Obviously, this is due to the difficulty of observing activity at the solar level on most stars. Presently, a method has been developed to detect and study individual solar like spots on the surface of planet-harbouring stars. As the planet eclipses dark patches on the surface of the star, a detectable signature can be observed in the light curve of the star during the transit. The study of a different variety of stars allows for a better understanding of magnetic cycles and the evolution of stars.

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34

Erceg, Sandro, and Sören Ehlers. "Semi-empirical level ice resistance prediction methods." Ship Technology Research 64, no. 1 (January 2, 2017): 1–14. http://dx.doi.org/10.1080/09377255.2016.1277839.

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35

Ding, Ming-de, and Cheng Fang. "A semi-empirical model of sunspot umbra." Chinese Astronomy and Astrophysics 15, no. 1 (March 1991): 28–36. http://dx.doi.org/10.1016/0275-1062(91)90005-i.

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36

Shapira, A., and A. Du Plessis. "A semi-empirical analysis of hypocenter mislocations." Tectonophysics 157, no. 4 (February 1989): 301–13. http://dx.doi.org/10.1016/0040-1951(89)90146-7.

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37

Di Benedetto, A., E. Salzano, and G. Russo. "Predicting pressure piling by semi-empirical correlations." Fire Safety Journal 40, no. 3 (April 2005): 282–98. http://dx.doi.org/10.1016/j.firesaf.2005.01.003.

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38

Singer, C. E., M. H. Redi, D. A. Boyd, A. J. Cavallo, B. Grek, D. B. Heifetz, R. A. Hulse, et al. "Semi-empirical models of H-mode discharges." Nuclear Fusion 25, no. 11 (November 1, 1985): 1555–73. http://dx.doi.org/10.1088/0029-5515/25/11/004.

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39

Raghurama, G., R. Narayan, and S. Ramaseshan. "A semi-empirical theory of molten salts." Journal of Physics C: Solid State Physics 18, no. 12 (April 30, 1985): 2401–9. http://dx.doi.org/10.1088/0022-3719/18/12/004.

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40

Cameron, R. H., L. Gizon, H. Schunker, and A. Pietarila. "Constructing Semi-Empirical Sunspot Models for Helioseismology." Solar Physics 268, no. 2 (September 22, 2010): 293–308. http://dx.doi.org/10.1007/s11207-010-9631-3.

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41

Korol, AV, AG Lyalin, AS Shulakov, and AV Solovy'ov. "Semi-empirical method for polarizational bremsstrahlung calculation." Journal of Electron Spectroscopy and Related Phenomena 79 (May 1996): 323–26. http://dx.doi.org/10.1016/0368-2048(96)02864-2.

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42

Zhang, Xiaodong, and Zhichen Xu. "A semi-empirical approach to scalability study." ACM SIGMETRICS Performance Evaluation Review 23, no. 1 (May 1995): 307–8. http://dx.doi.org/10.1145/223586.223624.

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43

Lee, Ki-Ho, Dong Hyun Song, Bong Jun Park, In-Joo Chin, and Hyoung Jin Choi. "Structures of Polyaniline Bases: Semi-Empirical Computations." Macromolecular Theory and Simulations 18, no. 4-5 (June 15, 2009): 287–98. http://dx.doi.org/10.1002/mats.200900010.

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44

Bozzolo, Guillermo, John Ferrante, and Rodrigo Ibañez-Meier. "Semi-empirical analysis of surface alloy formation." Surface Science 352-354 (May 1996): 577–82. http://dx.doi.org/10.1016/0039-6028(95)01201-x.

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45

Capitani, J. F. "Tetraethynylmethane: a semi-empirical molecular orbital study." Journal of Molecular Structure: THEOCHEM 332, no. 1-2 (February 1995): 21–23. http://dx.doi.org/10.1016/0166-1280(94)03916-9.

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46

FUJITA, Hiroshi, Yoshiyuki EINAGA, and Kaye HAMADA. "A Semi-Empirical Approach to the Viscosity of Semi-Dilute Polymer Solutions." Nihon Reoroji Gakkaishi(Journal of the Society of Rheology, Japan) 14, no. 1 (1986): 43–48. http://dx.doi.org/10.1678/rheology1973.14.1_43.

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47

Salahou, Mohamed Khaled, Xiyun Jiao, and Haishen Lü. "Assessment of Empirical and Semi-Empirical Models for Estimating a Soil Infiltration Function." Transactions of the ASABE 63, no. 4 (2020): 833–45. http://dx.doi.org/10.13031/trans.13639.

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HighlightsThe hydraulic performance computed with the KE or GA model is nearly the same, as long the models are calibrated using the same observation data.The GA model with the soil hydraulic parameters obtained from the pedotransfer functions adequately represented the soil infiltration function.The particle size distribution or the soil texture are recommended to estimate soil hydraulic parameters with the VG-ROSETTA model. Abstract. Field-scale estimation of a soil infiltration function is important for the design, simulation, and/or evaluation of surface irrigation systems. Semi-empirical and empirical infiltration models are used to estimate the infiltration function. Semi-empirical infiltration models have substantial computational and parameterization complexities, e.g., soil hydraulic parameters are needed to estimate the infiltration function. In contrast, empirical infiltration models are generally not considered to have specific initial and boundary conditions. The objectives of this study were to compare a semi-empirical infiltration model and an empirical infiltration model. The Green-Ampt model (GA) and the Kostiakov model (KE) were used as semi-empirical and empirical infiltration models, respectively. The soil hydraulic parameters for the GA model were estimated using various pedotransfer functions (PTFs), and in an additional assessment, the measured water content data were used to calibrate and validate the soil hydraulic parameters using the HYDRUS-1D model. The results show that the hydraulic performance computed with the KE or GA model is nearly the same, as long as they are calibrated using the same observation data. Additionally, the results indicate that the GA model with the soil hydraulic parameters obtained from the PTFs adequately represented the soil infiltration function in the borders. Keywords: Empirical infiltration model, Green-Ampt model, Infiltration model, Kostiakov model, Semi-empirical infiltration model, Soil hydraulic properties.

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48

Schenker, Benedikt, and Mukul Agarwal. "Online-optimized feed switching in semi-batch reactors using semi-empirical dynamic models." Control Engineering Practice 8, no. 12 (December 2000): 1393–403. http://dx.doi.org/10.1016/s0967-0661(00)00077-0.

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49

Wang, Yanzhao, Fengzhu Xing, Yang Xiao, and Jianzhong Gu. "An improved semi-empirical relationship for cluster radioactivity *." Chinese Physics C 45, no. 4 (April 1, 2021): 044111. http://dx.doi.org/10.1088/1674-1137/abe112.

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50

Li, Shao-Ming, Kai-Shing Yang, and Chi-Chuan Wang. "A Semi-Empirical Model for Predicting Frost Properties." Processes 9, no. 3 (February 25, 2021): 412. http://dx.doi.org/10.3390/pr9030412.

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In this study, a quantitative method for classifying the frost geometry is first proposed to substantiate a numerical model in predicting frost properties like density, thickness, and thermal conductivity. This method can recognize the crystal shape via linear programming of the existing map for frost morphology. By using this method, the frost conditions can be taken into account in a model to obtain the corresponding frost properties like thermal conductivity, frost thickness, and density for specific frost crystal. It is found that the developed model can predict the frost properties more accurately than the existing correlations. Specifically, the proposed model can identify the corresponding frost shape by a dimensionless temperature and the surface temperature. Moreover, by adopting the frost identification into the numerical model, the frost thickness can also be predicted satisfactorily. The proposed calculation method not only shows better predictive ability with thermal conductivities, but also gives good predictions for density and is especially accurate when the frost density is lower than 125 kg/m3. Yet, the predictive ability for frost density is improved by 24% when compared to the most accurate correlation available.

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Journal articles on the topic 'Semi-empirical'

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