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Journal articles on the topic 'Start modelling'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

de Jesus, Karla, Helon V. H. Ayala, Kelly de Jesus, Leandro dos S. Coelho, Alexandre I. A. Medeiros, José A. Abraldes, Mário A. P. Vaz, Ricardo J. Fernandes, and João Paulo Vilas-Boas. "Modelling and Predicting Backstroke Start Performance Using Non-Linear And Linear Models." Journal of Human Kinetics 61, no. 1 (March 23, 2018): 29–38. http://dx.doi.org/10.1515/hukin-2017-0133.

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AbstractOur aim was to compare non-linear and linear mathematical model responses for backstroke start performance prediction. Ten swimmers randomly completed eight 15 m backstroke starts with feet over the wedge, four with hands on the highest horizontal and four on the vertical handgrip. Swimmers were videotaped using a dual media camera set-up, with the starts being performed over an instrumented block with four force plates. Artificial neural networks were applied to predict 5 m start time using kinematic and kinetic variables and to determine the accuracy of the mean absolute percentage error. Artificial neural networks predicted start time more robustly than the linear model with respect to changing training to the validation dataset for the vertical handgrip (3.95 ± 1.67 vs. 5.92 ± 3.27%). Artificial neural networks obtained a smaller mean absolute percentage error than the linear model in the horizontal (0.43 ± 0.19 vs. 0.98 ± 0.19%) and vertical handgrip (0.45 ± 0.19 vs. 1.38 ± 0.30%) using all input data. The best artificial neural network validation revealed a smaller mean absolute error than the linear model for the horizontal (0.007 vs. 0.04 s) and vertical handgrip (0.01 vs. 0.03 s). Artificial neural networks should be used for backstroke 5 m start time prediction due to the quite small differences among the elite level performances.

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2

Pillsbury, R. D., and J. H. Schultz. "Modelling of plasma start-up in ITER." IEEE Transactions on Magnetics 28, no. 2 (March 1992): 1462–65. http://dx.doi.org/10.1109/20.123971.

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3

Keynejad, Farzad, and Chris Manzie. "Cold start modelling of spark ignition engines." Control Engineering Practice 19, no. 8 (August 2011): 912–25. http://dx.doi.org/10.1016/j.conengprac.2011.05.005.

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4

Samuel, Revelation J., and Haroun Mahgerefteh. "Transient Flow Modelling of Start-up CO2 Injection into Highly-Depleted Oil/Gas Fields." International Journal of Chemical Engineering and Applications 8, no. 5 (October 2017): 319–26. http://dx.doi.org/10.18178/ijcea.2017.8.5.677.

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5

Wu, Chenyi, and Andrew Travers. "Modelling and DNA topology of compact 2-start and 1-start chromatin fibres." Nucleic Acids Research 47, no. 18 (June 20, 2019): 9902–24. http://dx.doi.org/10.1093/nar/gkz495.

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Abstract We have investigated the structure of the most compact 30-nm chromatin fibres by modelling those with 2-start or 1-start crossed-linker organisations. Using an iterative procedure we obtained possible structural solutions for fibres of the highest possible compaction permitted by physical constraints, including the helical repeat of linker DNA. We find that this procedure predicts a quantized nucleosome repeat length (NRL) and that only fibres with longer NRLs (≥197 bp) can more likely adopt the 1-start organisation. The transition from 2-start to 1-start fibres is consistent with reported differing binding modes of the linker histone. We also calculate that in 1-start fibres the DNA constrains more torsion (as writhe) than 2-start fibres with the same NRL and that the maximum constraint obtained is in accord with previous experimental results. We posit that the coiling of the fibre is driven by overtwisting of linker DNA which, in the most compact forms - for example, in echinoderm sperm and avian erythrocytes - could adopt a helical repeat of ∼10 bp/turn. We argue that in vivo the total twist of linker DNA could be modulated by interaction with other abundant chromatin-associated proteins and by epigenetic modifications of the C-terminal tail of linker histones.

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6

Popovic, Dragana. "Modelling the marketing of high-tech start-ups." Journal of Targeting, Measurement and Analysis for Marketing 14, no. 3 (April 2006): 260–76. http://dx.doi.org/10.1057/palgrave.jt.5740186.

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7

Roach, C. M. "Modelling ohmic confinement experiments on the START tokamak." Plasma Physics and Controlled Fusion 38, no. 12 (December 1, 1996): 2187–203. http://dx.doi.org/10.1088/0741-3335/38/12/011.

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8

Pillsbury, R. D. "An Eigenexpansion Technique for Modelling Plasma Start-Up." Fusion Technology 15, no. 2P2B (March 1989): 933–37. http://dx.doi.org/10.13182/fst89-a39813.

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9

Laskowski, Piotr, Damian Zasina, Magdalena Zimakowska-Laskowska, and Piotr Orliński. "Modelling Hydrocarbons Cold-Start Emission from Passenger Cars." Advances in Science and Technology Research Journal 15, no. 3 (September 1, 2021): 117–25. http://dx.doi.org/10.12913/22998624/138764.

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10

Kiryushina, Maria Alexandrovna, and Tatiana Gennadyevna Elizarova. "Modelling of nozzle start-up for underexpanded jet generation." Keldysh Institute Preprints, no. 59 (2021): 1–30. http://dx.doi.org/10.20948/prepr-2021-59.

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A numerical simulation of hydrogen jet in the micronozzle is carried out, which is used as the main element in the experimental installation to study the properties of rarefied gases at high speeds and low temperatures. The features of the transient jet flow - pressure gradients, velocities and the complex geometry of the problem are uniformly described within the framework of the quasi-gas dynamic algorithm included in the open platform OpenFOAM.

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11

Cosenz, Federico. "Supporting start-up business model design through system dynamics modelling." Management Decision 55, no. 1 (February 13, 2017): 57–80. http://dx.doi.org/10.1108/md-06-2016-0395.

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Purpose The purpose of this paper is to explore how system dynamics (SD) modelling can provide a methodological support to business model (BM) design with the intent to better communicate business strategy and manage performance. Design/methodology/approach After a literature review of the field and an analysis of the strengths and limitations of conventional BM frameworks, the paper illustrates and discusses an approach that combines such a framework with SD modelling. A single-case study design was selected to explore the implications and limitations of using this combined approach to business modelling. Findings The methodological support provided by SD to BM design may effectively improve business strategy communication and performance management through both the adoption of a systemic and flexible perspective able to identify and analyse the main cause-and-effect relationships between the key-elements of the business strategy, and the use of a simulation technique that contributes in understanding how a firm operates, and its prospective performance over time. Originality/value Growing interest for BMs appears in the recent strategic management literature with research highlighting strengths and shortcomings. However, few attempts have been produced to overcome such limitations, while the adoption of SD is relatively new in supporting BM design.

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12

Ziegel, Eric R., John Sall, and Ann Lehman (SAS Institute). "JMP Start Statistics." Technometrics 41, no. 1 (February 1999): 84. http://dx.doi.org/10.2307/1271018.

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13

Serie, Eric, and Robert Joumard. "Modelling of pollutant emissions during cold start for road vehicles." International Journal of Vehicle Design 20, no. 1/2/3/4 (1998): 172. http://dx.doi.org/10.1504/ijvd.1998.001840.

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14

Park, Ji-Sang, Young-Kwang Jung, Keith T. Butler, and Aron Walsh. "Quick-start guide for first-principles modelling of semiconductor interfaces." Journal of Physics: Energy 1, no. 1 (November 20, 2018): 016001. http://dx.doi.org/10.1088/2515-7655/aad928.

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15

Ghahfarokhi, Mohammadreza M., Aliakbar Damaki Aliabad, Samad Taghipour Boroujeni, Ebrahim Amiri, and Vahid Zamani Faradonbeh. "Analytical modelling and optimisation of line start LSPM synchronous motors." IET Electric Power Applications 14, no. 3 (February 14, 2020): 398–408. http://dx.doi.org/10.1049/iet-epa.2019.0644.

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16

Kuntz, Ludwig, and Felix Müsgens. "Modelling start-up costs of multiple technologies in electricity markets." Mathematical Methods of Operations Research 66, no. 1 (February 16, 2007): 21–32. http://dx.doi.org/10.1007/s00186-007-0148-y.

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17

Malinský, Jan, and Jiří Novák. "Verification of Flexray Start-Up Mechanism by Timed Automata." Metrology and Measurement Systems 17, no. 3 (January 1, 2010): 461–80. http://dx.doi.org/10.2478/v10178-010-0039-z.

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Verification of Flexray Start-Up Mechanism by Timed AutomataThis contribution deals with the modelling of a selected part of a new automotive communication standard called FlexRay. In particular, it focuses on the mechanism ensuring the start-up of a FlexRay network. The model has been created with the use of timed automata and verified. For this purpose the UPPAAL software tool has been used that allows the modelling of discrete event systems with the use of timed automata, and subsequently the verification of the model with the use of suitable queries compiled in the so called computation tree logic. This model can be used to look for incorrect settings of time parameters of communication nodes in the network that prevent network start-up and subsequently the start of the car. The existence of this model also opens the way for finding possible errors in the standard. On the basis of the model, the work gives a case study of the start-up mechanism behaviour verification in a FlexRay network consisting of three communication nodes.

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18

Brzozowski, Krzysztof. "Multipoint source method in air pollution modelling of cold start emission." Environmental Modeling & Assessment 11, no. 4 (July 8, 2006): 371–80. http://dx.doi.org/10.1007/s10666-005-9027-1.

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19

Balakrishnan, S. R., and S. Santhakumar. "Fuzzy modelling considerations in an aero gas turbine engine start cycle." Fuzzy Sets and Systems 78, no. 1 (February 1996): 1–4. http://dx.doi.org/10.1016/0165-0114(95)00195-6.

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20

Sacconi, Andrea, and Haroun Mahgerefteh. "Modelling start-up injection of CO2 into highly-depleted gas fields." Energy 191 (January 2020): 116530. http://dx.doi.org/10.1016/j.energy.2019.116530.

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21

Novara, Cristina, Simone Falzoi, Valentina La Morgia, Federico Spanna, and Consolata Siniscalco. "Modelling the pollen season start in Corylus avellana and Alnus glutinosa." Aerobiologia 32, no. 3 (February 27, 2016): 555–69. http://dx.doi.org/10.1007/s10453-016-9432-8.

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22

Ross, M. D. "Modelling a with-profits life office." Journal of the Institute of Actuaries 116, no. 3 (December 1989): 691–715. http://dx.doi.org/10.1017/s0020268100036775.

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1.1 In this paper I intend to concentrate on the application of mathematics and the problems faced and (sometimes) solved by such application, rather than on the mathematics itself. That is not to belittle the mathematics in any way, and I would like to acknowledge at the start that the stochastic financial model which underlies the results given in this talk is based on Professor Wilkie's model as detailed in T.F.A.39, 341.

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23

Lippert, A. M., D. W. Stanton, C. J. Rutland, W. L. H. Hallett, and R. D. Reitz. "Multidimensional simulation of diesel engine cold start with advanced physical submodels." International Journal of Engine Research 1, no. 1 (February 1, 2000): 1–27. http://dx.doi.org/10.1177/146808740000100101.

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The complex physical processes occurring during cold starting of diesel engines mandate the use of advanced physical submodels in computations. The present study utilizes a continuous probability density function to represent more fully the range of compositions of commercial fuels. The model was applied to singledroplet calculations to validate the predictions against experimental results. Analysis of a high-pressure diesel spray showed axial composition gradients within the spray. Previous wall-film modelling was extended to include the continuous multicomponent fuel representation. Using these models, the cold-start behaviour of a heavy-duty diesel engine was analysed. The predictions show that multicomponent fuel modelling is critical to capturing realistic vaporization trends. In addition, the spray-film interaction modelling is crucial to capturing the spray impingement and subsequent secondary atomization. Heating the intake air temperature was shown to result in reduced ignition delay and accelerated vaporization. Increasing the fuel temperature increased vaporization prior to and away from the initial heat release. Increasing the injection pressure increased vaporization without much change in the ignition delay. Split injections, with 75 per cent of the fuel contained in the second pulse, displayed a substantial reduction in ignition delay due to ignition of the first pulse. The timing of the first injection was found to be an important parameter due to differences in the spray impingement behaviour with different timings.

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24

Ma, Fengying, Yankai Yin, and Min Li. "Start-Up Process Modelling of Sediment Microbial Fuel Cells Based on Data Driven." Mathematical Problems in Engineering 2019 (January 10, 2019): 1–10. http://dx.doi.org/10.1155/2019/7403732.

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Sediment microbial fuel cells (SMFCs) are a typical microbial fuel cell without membranes. They are a device developed on the basis of electrochemistry and use microbes as catalysts to convert chemical energy stored in organic matter into electrical energy. This study selected a single-chamber SMFC as a research object, using online monitoring technology to accurately measure the temperature, pH, and voltage of the microbial fuel cell during the start-up process. In the process of microbial fuel cell start-up, the relationship between temperature, pH, and voltage was analysed in detail, and the correlation between them was calculated using SPSS software. The experimental results show that, at the initial stage of SMFC, the purpose of rapid growth of power production can be achieved by a large increase in temperature, but once the temperature is reduced, the power production of SMFC will soon recover to the state before the temperature change. At the beginning of SMFC, when the temperature changes drastically, pH will change the same first, and then there will be a certain degree of rebound. In the middle stage of SMFC start-up, even if the temperature will return to normal after the change, a continuous temperature drop in a short time will lead to a continuous decrease in pH value. The RBF neural network and ELM neural network were used to perform nonlinear system regression in the later stage of SMFC start-up and using the regression network to forecast part of the data. The experimental results show that the ELM neural network is more excellent in forecasting SMFC system. This article will provide important guidance for shortening start-up time and increasing power output.

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25

Djordjevic, Marko. "Integrating Sequence Analysis with Biophysical Modelling for Accurate Transcription Start Site Prediction." Journal of Integrative Bioinformatics 11, no. 2 (June 1, 2014): 58–67. http://dx.doi.org/10.1515/jib-2014-240.

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Summary Promoter prediction in bacteria is a classical bioinformatics problem, where available methods for regulatory element detection exhibit a very high number of false positives. We here argue that accurate transcription start site (TSS) prediction is a complex problem, where available methods for sequence motif discovery are not in itself well adopted for solving the problem. We here instead propose that the problem requires integration of quantitative understanding of transcription initiation with careful description of promoter sequence specificity. We review evidence for this viewpoint, and discuss a current progress on these issues on the example of sigma70 transcription start sites in E. coli.

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26

Hierholtzer, A., and J. C. Akunna. "Modelling start-up performance of anaerobic digestion of saline-rich macro-algae." Water Science and Technology 69, no. 10 (March 7, 2014): 2059–65. http://dx.doi.org/10.2166/wst.2014.100.

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Some of the key factors affecting the adaptation of anaerobic digestion processes to increasing levels of salinity were determined in batch tests using brown seaweed as a feedstock. It was found that cultures seeded with non-saline anaerobic inoculum required an adaptation period of up to two months to reach the same level of methane production rate as in those cultures seeded with saline-adapted inoculum. The Anaerobic Digestion Model No.1 (ADM1) was modified to include an extra inhibition function to account for the effect of salinity, and calibrated using a set of experimental data obtained from batch biochemical methane potential tests. After calibration, the model was able to accurately predict methane production rates. Thus, the results show that, in the absence of saline-adapted inoculum, non-saline inoculum can be used for the start-up of anaerobic digestion systems treating saline-rich feedstocks.

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Garcı́a-Mozo, H., C. Galán, M. J. Aira, J. Belmonte, C. Dı́az de la Guardia, D. Fernández, A. M. Gutierrez, F. J. Rodriguez, M. M. Trigo, and E. Dominguez-Vilches. "Modelling start of oak pollen season in different climatic zones in Spain." Agricultural and Forest Meteorology 110, no. 4 (February 28, 2002): 247–57. http://dx.doi.org/10.1016/s0168-1923(02)00003-5.

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28

Ozdemir, Abdulehad, and Ata Mugan. "Stop/Start System Integration to Diesel Engine and System Modelling & Validation." IFAC Proceedings Volumes 46, no. 25 (2013): 95–100. http://dx.doi.org/10.3182/20130916-2-tr-4042.00008.

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29

Gudin, Dariusz, Omar Mian, and Steve Sanders. "Experimental measurement and modelling of plain bearing wear in start–stop applications." Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology 227, no. 5 (January 8, 2013): 433–46. http://dx.doi.org/10.1177/1350650112471287.

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30

Singdeo, Debanand, Tapobrata Dey, and Prakash C. Ghosh. "Modelling of start-up time for high temperature polymer electrolyte fuel cells." Energy 36, no. 10 (October 2011): 6081–89. http://dx.doi.org/10.1016/j.energy.2011.08.007.

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31

Mannina, Giorgio, and Gaetano Di Bella. "Comparing two start-up strategies for MBRs: Experimental study and mathematical modelling." Biochemical Engineering Journal 68 (October 2012): 91–103. http://dx.doi.org/10.1016/j.bej.2012.07.011.

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32

DE ANGELIS, E., and L. MESIN. "MODELLING OF THE IMMUNE RESPONSE: CONCEPTUAL FRAMEWORKS AND APPLICATIONS." Mathematical Models and Methods in Applied Sciences 11, no. 09 (December 2001): 1609–30. http://dx.doi.org/10.1142/s0218202501001501.

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This paper deals with the modelling of the immune response to the evolution of the progression of endothelial cells which have lost their differentiation and start their evolution toward methastatic states. The aim of this paper is to design a general mathematical framework toward modelling the so-called kinetic cellular theory. Some specific models are proposed within the above framework and suitable simulations are developed with special attention to bifurcation analysis.

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33

Wearden, John H. "Modelling Chronometric Counting." Timing & Time Perception 4, no. 3 (October 20, 2016): 271–98. http://dx.doi.org/10.1163/22134468-00002070.

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Participants performed on a temporal generalization task with standard durations being either 4 or 8 s, and comparison durations ranging from 2.5 to 5.5, or 5 to 11 s. They were required to count during all stimulus presentations, and counts were recorded as spacebar presses. Generalization gradients around both standard values peaked at the standard, but the gradient from the 8-s condition was steeper. Measured counts had low variance, both within trials and between trials, and a start process, which was different from the counting sequence, could also be identified in data. A computer model assuming that a comparison duration was identified as the standard when the count value for the comparison was one that had previously occurred for a standard fitted the temporal generalization gradients well. The model was also applied to some published data on temporal reproduction with counting, and generally fitted data adequately. The model makes a distinction between the variance of the count unit from one trial to another, and the counts within the trial, and this distinction was related to the overall variance of behaviours resulting from counting, and the ways in which variability of timing measures change with the duration timed.

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34

Louda, Petr, Jaromír Příhoda, and Karel Kozel. "Numerical modelling of turbulent transition in complex geometries." EPJ Web of Conferences 180 (2018): 02057. http://dx.doi.org/10.1051/epjconf/201818002057.

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The work deals with numerical simulation of laminar-turbulent transition in transonic flows in turbine cas-cades. The 3D cascade geometry as well as 2D model cascade in a wind tunnel is simulated. The γ-ζ transition model is based on empirical criteria for start of the transition. The implementation of the model is discussed including re-formulation of the criterion for transition on separation bubble.

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35

Ambrosi, D., N. Bellomo, and L. Preziosi. "Modelling Tumor Progression, Heterogeneity, and Immune Competition." Journal of Theoretical Medicine 4, no. 1 (2002): 51–65. http://dx.doi.org/10.1080/10273660290015206.

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This paper deals with the modeling of the immune response to the evolution of the progression of endothelial cells which have lost the differentiation and start their evolution towards metastatic states. The modeling is developed in the framework of the so-called kinetic cellular theory. The model is critically analyzed on the basis of analytic solutions, asymptotic behaviors and numerical simulations that illustrate the scenarios predicted by the model. Finally, possible developments and generalizations that could describe other known phenomena are pointed out.

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36

Barquero, Berta, and Britta Eyrich Jessen. "Impact of theoretical perspectives on the design of mathematical modelling tasks." Avances de Investigación en Educación Matemática, no. 17 (May 1, 2020): 98–113. http://dx.doi.org/10.35763/aiem.v0i17.317.

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In this paper, we discuss how the adoption of a particular theoretical framework affects task design in the research field of modelling and applications. With this purpose, we start by referring to the existence of different reference epistemological models about mathematical modelling to analyse better the consequences they have for decision making concerning designing modelling tasks and their implementation. In particular, we present the analysis of three case studies, which have been selected as representatives of different theoretical perspectives to modelling. We discuss the impact of the chosen reference epistemological model on the task design process of mathematical modelling and the local ecologies suited for their implementation.

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37

Ferguson, Teresa, and Amy Brown. "Implementation of Clinical Simulation–Where to Start?" Clinical Simulation in Nursing 5, no. 3 (May 2009): e138. http://dx.doi.org/10.1016/j.ecns.2009.04.032.

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38

HARROUZ, Abdelkader, Fadila TAHIRI, Fatiha BEKRAOUI, and Ibrahim BOUSSAID. "Modelling and Simulation of Synchronous Inductor Machines." Algerian Journal of Renewable Energy and Sustainable Development 01, no. 01 (June 15, 2019): 8–23. http://dx.doi.org/10.46657/ajresd.2019.1.1.2.

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This study focuses on the study of the compartment of the synchronous inductor machine with variable speed, fed by a threephase inverter. Several transients were treated by simulation (start unloading, introducing a torque load, reversing and speed setpoint change). Then engine cushion at both loss and when starting without the damper. In addition, robustness tests on the parametric variation of (MSRB) were also performed. Based on the results of simulations, the control technique studied makes it possible to obtain good dynamic and static performances and has a robustness with respect to the external perturbation and the parametric variation.

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39

Aliabad, A. D., and M. Mirsalim. "Analytic modelling and dynamic analysis of pole-changing line-start permanent-magnet motors." IET Electric Power Applications 6, no. 3 (2012): 149. http://dx.doi.org/10.1049/iet-epa.2011.0146.

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40

Azari, Niaz Milad, and Mojtaba Mirsalim. "Analytic modelling of a line‐start permanent‐magnet motor with slotted solid rotor." IET Electric Power Applications 8, no. 7 (August 2014): 278–85. http://dx.doi.org/10.1049/iet-epa.2014.0018.

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41

Cema, Grzegorz, Adam Sochacki, Jakub Kubiatowicz, Piotr Gutwiński, and Joanna Surmacz-Górska. "Start-Up, Modelling and Simulation of the Anammox Process in a Membrane Bioreactor." Chemical and Process Engineering 33, no. 4 (December 1, 2012): 639–50. http://dx.doi.org/10.2478/v10176-012-0054-6.

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There are certain well-known methods of diminishing concentrations of nitrogen compounds, but they are ineffective in case of nitrogen-rich wastewater with a low content of biodegradable carbon. Partial nitritation followed by anaerobic ammonium oxidation (Anammox) process appear to be an excellent alternative for traditional nitrification and denitrification. This paper presents the feasibility of successful start-up of Anammox process in a laboratory-scale membrane bioreactor (MBR). It was shown that the combination of membrane technology and Anammox process allowed to create a new highly efficient and compact system for nitrogen removal. It was possible to achieve average nitrogen removal efficiency equal to 76.7 ± 8.3%. It was shown that the start-up period of 6 months was needed to obtain high nitrogen removal efficiency. The applied biochemical model of the Anammox process was based on the state-of-the-art Activated Sludge Model No.1 (ASM 1) which was modified for accounting activity of autotrophs (nitrite-oxidising bacteria and nitrateoxidising bacteria) and anammox bacteria. In order to increase the predictive power of the simulation selected parameters of the model were adjusted during model calibration. Readjustment of the model parameters based on the critically evaluated data of the reactor resulted in a satisfactory match between the model predictions and the actual observations.

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Yerezhep, D., A. Aldiyarov, D. Sokolov, A. Nurmukan, B. Krutskikh, and Zh Amangeldieva. "Mathematical modelling of the cryogenic-dynamic start-up process in a pneumatic installation." Journal of Physics: Conference Series 1661 (November 2020): 012092. http://dx.doi.org/10.1088/1742-6596/1661/1/012092.

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43

Kim, Sunghyun, Samantha N. Hood, Ji-Sang Park, Lucy D. Whalley, and Aron Walsh. "Quick-start guide for first-principles modelling of point defects in crystalline materials." Journal of Physics: Energy 2, no. 3 (July 31, 2020): 036001. http://dx.doi.org/10.1088/2515-7655/aba081.

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44

Lakshmanan, Chittur Chandrsekharan, and Owen Edward Potter. "Dynamic simulation of a countercurrent heat exchanger modelling-start-up and frequency response." International Communications in Heat and Mass Transfer 21, no. 3 (May 1994): 421–34. http://dx.doi.org/10.1016/0735-1933(94)90010-8.

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45

Hübel, Moritz, Sebastian Meinke, Marcus T. Andrén, Christoffer Wedding, Jürgen Nocke, Conrad Gierow, Egon Hassel, and Jonas Funkquist. "Modelling and simulation of a coal-fired power plant for start-up optimisation." Applied Energy 208 (December 2017): 319–31. http://dx.doi.org/10.1016/j.apenergy.2017.10.033.

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46

Maroli, C., and V. Petrillo. "Modelling of start-up assist by electron cyclotron waves for large-size tokamaks." Il Nuovo Cimento D 10, no. 6 (June 1988): 677–91. http://dx.doi.org/10.1007/bf02451106.

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Operacz, Agnieszka, Bartosz Szeląg, and Mads Grahl-Madsen. "Possibility of the modelling of electricity production from hydropower." E3S Web of Conferences 86 (2019): 00008. http://dx.doi.org/10.1051/e3sconf/20198600008.

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In hydropower plants benefits depends on available flow. The paper presents a hybrid model for forecasting the operation of a hydropower plant, including the production of electricity. The possibility of mathematical modeling was chosen to show connections between observed in the past hydrological conditions (available flow) and energy deliver in the future. The available flow which is not enough for start turbines was forecasting by logistic regression model. The opposite situation when the flow starts turbine to produce energy, regression models (the support vector machines SVM, random forest RF, k nearest neighbour k-NN) were used. Results from hybrid model were compared with chosen data-mining methods. The possibility of forecasting of the length of periods when hydropower plant will be working could be very useful. It provides the prognosis of energy value which could be produced from hydropower plant. From the investors’ point of view the economic justification for the execution of the project based on the future energy producing could be a main criteria to realize or buy/sell hydropower plant. Also the secondary importance could be a possibility of planning review and maintenance work. Knowledge of power plant working periods could be a base for assessing a potential production from hydropower plant.

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48

Khalilikhah, O., and M. Shalchian. "Modelling and Fuzzy-Threshold Control of SI Engine for Emission Reduction during Cold Start Phase." International Journal of Automotive and Mechanical Engineering 16, no. 4 (December 30, 2019): 7225–42. http://dx.doi.org/10.15282/ijame.16.4.2019.05.0539.

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We present a controllable model of an internal combustion engine that captures the overlapping of the cylinder valves as a controllable parameter and its effect on engine efficiency and EGR rates. The model parameters have been calibrated for the EF7 engine and validated with experimental data. This model successfully estimates the performance and HC and NOx emissions concentration of the engine under cold start operating condition. A model-based fuzzy-threshold control strategy has been proposed in cold start operating condition. This strategy uses the overlapping angle of the cylinder inlet and outlet valves as an extra degree of freedom in comparison to the regular PID strategy in order to accelerate the warm-up duration the catalyst converter while reduces the exhaust harmful emissions during the warm-up phase. The proposed controller model has been verified in MATLAB Simulink environment and simulation results indicates 8.6% reduction of the start-up time of the catalyst converter and reduction of 3.5%, 8.5% and 7% of HC, NO and fuel consumption respectively during the catalyst warm-up phase.

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Smith, D. E. "The Case for Durative Actions: A Commentary on PDDL2.1." Journal of Artificial Intelligence Research 20 (December 1, 2003): 149–54. http://dx.doi.org/10.1613/jair.1997.

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The addition of durative actions to PDDL2.1 sparked some controversy. Fox and Long argued that actions should be considered as instantaneous, but can start and stop processes. Ultimately, a limited notion of durative actions was incorporated into the language. I argue that this notion is still impoverished, and that the underlying philosophical position of regarding durative actions as being a shorthand for a start action, process, and stop action ignores the realities of modelling and execution for complex systems.

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Sansom, Clare. "Modelling the Virtual Physiological Human." Biochemist 33, no. 1 (February 1, 2011): 50–51. http://dx.doi.org/10.1042/bio03301050.

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Systems biology – the theme of this issue of The Biochemist – can be thought of as more a philosophy of biology than a distinct set of techniques. It arose out of, but is distinct from, the genome projects and associated initiatives. The ‘catalogues’ of genes and proteins produced in recent years have generated enormous advances, but they do not tell the whole story. Nobel Laureate Sydney Brenner said in 2001 that “I know one approach that will fail, which is to start with genes, make proteins from them and try to build things bottom-up”1. In contrast with the reductionism of genomics, systems biology is ‘integrative’: as another Nobel Laureate, David Baltimore, writes, “it seeks to understand the integration of the pieces to form biological systems”2. Thus a typical systems biology study will involve both experimental analysis and computational modelling of a biological system at a number of levels: theoretically, at least, including the molecule, the pathway, the organelle, the cell, the tissue or organ, and the organism.

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