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Journal articles on the topic 'Mathematical models of plants'

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Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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1

Sukhova, Ekaterina, Elena Akinchits, and Vladimir Sukhov. "Mathematical Models of Electrical Activity in Plants." Journal of Membrane Biology 250, no. 5 (July 15, 2017): 407–23. http://dx.doi.org/10.1007/s00232-017-9969-7.

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2

Abagyan, A. A., A. E. Kroshilin, V. E. Kroshilin, V. N. Maidanik, E. F. Seleznev, and R. L. Fuks. "Dynamical mathematical models of nuclear power plants." Atomic Energy 88, no. 6 (June 2000): 431–42. http://dx.doi.org/10.1007/bf02673465.

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3

Roose, Tiina, and Andrea Schnepf. "Mathematical models of plant–soil interaction." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 366, no. 1885 (September 25, 2008): 4597–611. http://dx.doi.org/10.1098/rsta.2008.0198.

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In this paper, we set out to illustrate and discuss how mathematical modelling could and should be applied to aid our understanding of plants and, in particular, plant–soil interactions. Our aim is to persuade members of both the biological and mathematical communities of the need to collaborate in developing quantitative mechanistic models. We believe that such models will lead to a more profound understanding of the fundamental science of plants and may help us with managing real-world problems such as food shortages and global warming. We start the paper by reviewing mathematical models that have been developed to describe nutrient and water uptake by a single root. We discuss briefly the mathematical techniques involved in analysing these models and present some of the analytical results of these models. Then, we describe how the information gained from the single-root scale models can be translated to root system and field scales. We discuss the advantages and disadvantages of different mathematical approaches and make a case that mechanistic rather than phenomenological models will in the end be more trustworthy. We also discuss the need for a considerable amount of effort on the fundamental mathematics of upscaling and homogenization methods specialized for branched networks such as roots. Finally, we discuss different future avenues of research and how we believe these should be approached so that in the long term it will be possible to develop a valid, quantitative whole-plant model.
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4

Gallego, Antonio J., Manuel Macías, Fernando de de Castilla, and Eduardo F. Camacho. "Mathematical modeling of the Mojave Solar Plants." Energies 12, no. 21 (November 3, 2019): 4197. http://dx.doi.org/10.3390/en12214197.

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Competitiveness of solar energy is one of current main research topics. Overall efficiency of solar plants can be improved by using advanced control strategies. To design and tuning properly advanced control strategies, a mathematical model of the plant is needed. The model has to fulfill two important points: (1) It has to reproduce accurately the dynamics of the real system; and (2) since the model is used to test advanced control strategies, its computational burden has to be as low as possible. This trade-off is essential to optimize the tuning process of the controller and minimize the commissioning time. In this paper, the modeling of the large-scale commercial solar trough plants Mojave Beta and Mojave Alpha is presented. These two models were used to test advanced control strategies to operate the plants.
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5

Provorov, Nikolay A., and Nikolay I. Vorobyov. "Evolution of micro-symbionts of cultured plants: experimental and mathematical models." Ecological genetics 9, no. 3 (September 15, 2011): 20–22. http://dx.doi.org/10.17816/ecogen9320-22.

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Formation of the cultured flora resulted in a decrease of plant symbiotic potential based on interactions with beneficial microorganisms. This decrease leads to transformation of plant micro-symbionts into the non-adaptive forms caused by: а) blocking the selection in favor of mutualistic strains; б) horizontal gene transfer in the microbial communities resulted in formation of virulent “symbiotic cheaters”. Mathematical simulation suggests that these tendencies may be overcome by formation of the optimal population structures in symbiotic system which should possess a high integrity and specificity of partners’ interactions as well as by a tolerance to the invasions of non-active aboriginal strains from the local soil populations.
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6

Cherednichenko, Oleksandr, Serhiy Serbin, Mykhaylo Tkach, Jerzy Kowalski, and Daifen Chen. "Mathematical Modelling of Marine Power Plants with Thermochemical Fuel Treatment." Polish Maritime Research 29, no. 3 (September 1, 2022): 99–108. http://dx.doi.org/10.2478/pomr-2022-0030.

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Abstract The article considers the methodological aspects of the theoretical investigation of marine power plants with thermochemical fuel treatment. The results of the study of the complex influence of temperature, pressure, and the ratio of steam / base fuel on the thermochemical treatment efficiency are presented. The adequacy of the obtained regression dependences was confirmed by the physical modelling of thermochemical fuel treatment processes. For a gas turbine power complex with a thermochemical fuel treatment system, the characteristics of the power equipment were determined separately with further merging of the obtained results and a combination of material and energy flow models. Algorithms, which provide settings for the mathematical models of structural and functional blocks, the optimisation of thermochemical energy transformations, and verification of developed models according to the indicators of existing gas turbine engines, were created. The influence of mechanical energy consumption during the organisation of thermochemical processing of fuel on the efficiency of thermochemical recuperation is analysed.
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7

Bruce, David M. "Mathematical modelling of the cellular mechanics of plants." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 358, no. 1437 (July 30, 2003): 1437–44. http://dx.doi.org/10.1098/rstb.2003.1337.

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The complex mechanical behaviour of plant tissues reflects the complexity of their structure and material properties. Modelling has been widely used in studies of how cell walls, single cells and tissue respond to loading, both externally applied loading and loads on the cell wall resulting from changes in the pressure within fluid–filled cells. This paper reviews what approaches have been taken to modelling and simulation of cell wall, cell and tissue mechanics, and to what extent models have been successful in predicting mechanical behaviour. Advances in understanding of cell wall ultrastructure and the control of cell growth present opportunities for modelling to clarify how growth–related mechanical properties arise from wall polymeric structure and biochemistry.
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8

Pruteanu, Augustina, Valentin Vladut, Petru Cardei, and Despina Bordean. "General Tendencies of the Behaviour of Vegetables Developed in a Soil Contaminated with Heavy Metals." Revista de Chimie 71, no. 2 (March 3, 2020): 85–90. http://dx.doi.org/10.37358/rc.20.2.7897.

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The paper presents experimental results obtained in the study of heavy metals transfer from soil to vegetables. The experiments for which the raw and statistically processed data are presented in this paper are preliminary experiments within an extensive research program of plant behaviour in soils contaminated with heavy metals. These experiments underlie the development of primary statistical mathematical models that are also presented in the paper. These experiments will also form the basis for far more consistent experiments that follow plants throughout the life cycle. The statistical mathematical models presented in this paper facilitate extracting important conclusions about how plants accumulate heavy metals as well as about the accumulation rate behaviour during experiments. Both experiments and mathematical models will form the basis of complex experiments and dynamic mathematical models in the next stage of research.
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9

Carpinelli, G., F. Gagliardi, M. Russo, and A. Sturchio. "Steady-state mathematical models of battery storage plants with line-commutated converters." IEEE Transactions on Power Delivery 8, no. 2 (April 1993): 494–503. http://dx.doi.org/10.1109/61.216851.

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10

Bykova, Ya P., and B. V. Ermolenko. "Economic-mathematical models for designing a wastewater purification system for electroplating plants." Theoretical Foundations of Chemical Engineering 45, no. 4 (August 2011): 542–49. http://dx.doi.org/10.1134/s0040579510051069.

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11

Griguletsky, V. G. "Approximate digital models of plant growth and productivity." Oil Crops 3, no. 191 (November 25, 2022): 79–108. http://dx.doi.org/10.25230/2412-608x-2022-3-191-79-108.

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The article presents a brief review and analysis of existing mathematical models for calculating the growth and productivity of agricultural plants. Much attention is paid to the analysis of the first models of plant growth by T.B. Robertson, F.F. Blackman, E.A. Mitcherlich and other famous researchers. Important theoretical works by I.A. Poletaeva, T.I. Eman, Yu.I. Gilderman, G.P. Kareva et al., who established and for the first time took into account the competition of plants for the amount of energy received during pho-tosynthesis on the mechanism of plant growth and their productivity. In total, more than 30 mathematical models of famous authors are indicated. The article describes a new approximate digital model of growth and productivity of agricultural plants, taking into account the main provisions and results of the cellular theory of the structure and growth of plants, obtained in the fundamental works of D.A. Sabinina, R.O. Erickson, V.B. Ivanov and other researchers. For the first time in a new growth model, it is taken into account that the relative length of a plant cell and the relative increase in this length are proportional to the difference between the maximum length and the actual value of the cell length, and the relative number of plant cells and the relative increase in this number of cells are proportional to the difference between the maximum number of cells and the actual number of cells. For the first time a mathematical model of plant growth under the combined action of light, mineral nutrition and respiration was described. Examples of calculations are considered that show a good agreement between the actual and calculated values of plant height, productivity of different crops for different climatic and soil conditions.
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12

Ladanyuk, Anatoliy P., and Natalya N. Lutskaya. "Problems Features of the Robust Control of Process Plants. Part I. Process Plants and their Mathematical Models." Journal of Automation and Information Sciences 48, no. 9 (2016): 75–83. http://dx.doi.org/10.1615/jautomatinfscien.v48.i9.60.

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13

Vitória, Edney L. da, Ismael L. de J. Freitas, Tamara Locatelli, Elcio das G. Lacerda, Juliana M. Valle, Raphaela C. Pereira, Paloma F. P. de Almeida, Rafael Z. da Vitória, Carla da P. Simon, and Adriano A. Fernandes. "Mathematical Models for Leaf Area Estimates of Guava." Journal of Agricultural Science 10, no. 12 (November 15, 2018): 272. http://dx.doi.org/10.5539/jas.v10n12p272.

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The aim of this work was to compare methods of determining the leaf area of guava (leaf discs and scanned images) and to model leaf area as a function of linear dimensions. Four areas of guava ‘Paluma’ were selected (12, 15, 20 and 24 months of age) for the experiment in the municipality of Pedro Canário, ES, Brazil. We randomly collected samples from 15 plants in each area. Ten leaves were chosen among the lower, middle and upper thirds of each plant to ensure that leaves of all sizes were collected, for a total of 600 leaves. Subsequently, we determined the leaf area by the methods of digital imaging and leaf discs. Linear regression analysis and correlation analysis were used to compare the methods. Linear, quadratic and power models of leaf area, as a function of the length or width and/or the product of length and width were adjusted. The methods of leaf discs and scanned images are discordant. The method of digitised images was a better fit to the width of the leaf, while the method of leaf discs was a better fit for length.
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14

Torres, M., S. Perez-Boada, and J. M. Duran. "Growth analysis by different mathematical models of barley plants after u.v.-A irradiation." Environmental and Experimental Botany 28, no. 4 (October 1988): 315–21. http://dx.doi.org/10.1016/0098-8472(88)90055-x.

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15

Novotny, V., H. Jones, X. Feng, and A. Capodaglio. "Time Series Analysis Models of Activated Sludge Plants." Water Science and Technology 23, no. 4-6 (February 1, 1991): 1107–16. http://dx.doi.org/10.2166/wst.1991.0562.

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Time series models of the activated sludge process are very useful in design and real time operation of wastewater treatment systems which deal with variable influent flows and pollution loads. In contrast to common deterministic dynamic mathematical models which require knowledge of a large number of coefficients, the time series models can be developed from input and output monitoring data series. In order to avoid “black box” approaches, time series models can be made compatible and identical in principle, with their dynamic mass balance model equivalents. In fact, these two types of models may differ only in nomenclature. ARMA-Transfer Function models can be used for systems which are linear or can be linearized such as typical BOD or suspended solids influent-effluent relationships for which the type of model is known. For systems which are highly nonlinear, and/or the input-output model is unknown, neural network models can be used. Both ARMA-TF models and neural network models can be made self-learning, that is, the performance of the model can be periodically improved manually or in an automated mode as new information is collected by monitoring. Application examples are included.
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16

Sahoo, Jyoti Prakash, Upasana Mohapatra, and Priyadarshini Mishra. "An outlook on metabolic pathway engineering in crop plants." Archives of Agriculture and Environmental Science 5, no. 3 (September 25, 2020): 431–34. http://dx.doi.org/10.26832/24566632.2020.0503027.

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To produce the essential secondary metabolites, plants are the major and important target source materials for conducting the high-profile metabolic engineering studies. Metabolic pathway engineering of both microorganism targets and plants target contribute towards important drug discovery. In order to efficiently work out in advanced plant metabolic pathway engineering techniques, a detailed knowledge and expertise is essentially needed regarding the plant cell physiology and the mechanics of plant metabolism. Mathematical and statistical models to scale and map the genome for integrative metabolic pathway activity, signal transduction mechanism in the genome, gene regulation and the networks of protein-protein interaction can provide the in-depth knowledge to work efficiently on plant metabolic pathway engineering studies. Incorporation of omics data into these statistical and mathematical models is crucial in the case of drug discovery using the plant system. Recently, artificial intelligence concept and approaches are experimentally applied for efficient and accurate metabolic engineering in plants.
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17

Bulatov, Yuri, Andrey Kryukov, and Aleksandr Cherepanov. "Mathematical models for determining limit operating modes in electrical networks with distributed generation plants." Science Bulletin of the Novosibirsk State Technical University, no. 4 (December 18, 2020): 17–36. http://dx.doi.org/10.17212/1814-1196-2020-4-17-36.

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Decentralization of electricity generation based on distributed generation plants is an important segment of the new technology platform for the power industry. On the basis of this approach, significant positive effects can be obtained, which consist in reducing financial costs of energy supply, increasing the uninterrupted power supply, improving the quality of electricity and stimulating the use of renewable energy sources. Effective use of distributed generation in electric power systems requires the development of methods and tools that provide coordinated management of normal, emergency and post-emergency modes. Of particular relevance is the problem of determining the limit operating modes of networks, at the nodal points of which relatively low power generators are connected. In some situations, for example, when using small hydraulic stations, groups of such generators can be located at significant distances for 6-10-20 kV distribution networks from consumption centers. In this case there will be a noticeable limitation of the regions of static aperiodic stability. The article presents the results of developments aimed at implementing methods for determining the limit operating modes by static aperiodic stability in networks with distributed generation plants. The proposed approach is based on the limit modes equations which provide the formation of effective algorithms for the operational finding of points belonging to the boundaries of stability regions. The results of the construction of the indicated areas for a 6 kV electric network with distributed generation plants based on low-power hydraulic stations are presented. Additionally, the transient processes in the studied electric power system were simulated in the Matlab system for various space points of the controlled mode parameters.
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18

BENJAMIN, L. R. "SIMULATING COMPETITION BETWEEN PLANTS USING MATHEMATICAL MODELS AND THE PROSPECT OF PREDICTING MARKETABLE YIELD." Acta Horticulturae, no. 267 (April 1990): 395–400. http://dx.doi.org/10.17660/actahortic.1990.267.46.

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19

PINEDA PÉREZ, CÉSAR AUGUSTO. "MODELO MATEMÁTICO DE INTEGRACIÓN DE PRODUCCIÓN E INVENTARIOS EN UNA RED LOGÍSTICA PLANTAS, DISTRIBUIDORES Y DETALLISTAS." Revista Ingeniería, Matemáticas y Ciencias de la Información 9, no. 18 (July 31, 2022): 89–115. http://dx.doi.org/10.21017/rimci.2022.v9.n18.a122.

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This article presents a nonlinear programming mathematical model that coordinates inventories and production in a logistics network made up of plants, distributors, and retailers. The procedure for formulating and solving the mathematical model uses nonlinear programming, linear programming, heuristics, and Lagrangian relaxation in stages.
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20

Flores-Alsina, Xavier, Krist V. Gernaey, and Ulf Jeppsson. "Benchmarking biological nutrient removal in wastewater treatment plants: influence of mathematical model assumptions." Water Science and Technology 65, no. 8 (April 1, 2012): 1496–505. http://dx.doi.org/10.2166/wst.2012.039.

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This paper examines the effect of different model assumptions when describing biological nutrient removal (BNR) by the activated sludge models (ASM) 1, 2d & 3. The performance of a nitrogen removal (WWTP1) and a combined nitrogen and phosphorus removal (WWTP2) benchmark wastewater treatment plant was compared for a series of model assumptions. Three different model approaches describing BNR are considered. In the reference case, the original model implementations are used to simulate WWTP1 (ASM1 & 3) and WWTP2 (ASM2d). The second set of models includes a reactive settler, which extends the description of the non-reactive TSS sedimentation and transport in the reference case with the full set of ASM processes. Finally, the third set of models is based on including electron acceptor dependency of biomass decay rates for ASM1 (WWTP1) and ASM2d (WWTP2). The results show that incorporation of a reactive settler: (1) increases the hydrolysis of particulates; (2) increases the overall plant's denitrification efficiency by reducing the SNOx concentration at the bottom of the clarifier; (3) increases the oxidation of COD compounds; (4) increases XOHO and XANO decay; and, finally, (5) increases the growth of XPAO and formation of XPHA,Stor for ASM2d, which has a major impact on the whole P removal system. Introduction of electron acceptor dependent decay leads to a substantial increase of the concentration of XANO, XOHO and XPAO in the bottom of the clarifier. The paper ends with a critical discussion of the influence of the different model assumptions, and emphasizes the need for a model user to understand the significant differences in simulation results that are obtained when applying different combinations of ‘standard’ models.
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21

Amelia, Rika, Nursanti Anggriani, Asep K. Supriatna, and Noor Istifadah. "Mathematical Model for Analyzing the Dynamics of Tungro Virus Disease in Rice: A Systematic Literature Review." Mathematics 10, no. 16 (August 15, 2022): 2944. http://dx.doi.org/10.3390/math10162944.

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One of the main obstacles in rice cultivation is the tungro virus disease caused by Rice tungro spherical virus (RTSV) and Rice tungro bacilliform virus (RTBV). These viruses are transmitted by green leafhopper (Nephotettix virescens) vector, semi-persistently after sucking infected plants. Subsequently, the vectors migrate and suck susceptible plants, but they can be controlled chemically and biologically. Mathematical modeling is one of the tools that can be used to analyze the spread of disease in plants. A literature review was conducted regarding the mathematical model of the spread of tungro virus disease in rice plants with the data sourced from scholarly references available in the dimension database, Google Scholar, and Scopus in 2012–2021. The steps followed include conducting a literature analysis and examining the mathematical model of the transmission of tungro virus disease in rice plants to identify gaps for future research. The results show that since 2016, few studies have analyzed mathematical models of the spread of tungro virus disease in rice plants. This is evident from the data search results, which show that only four articles were acquired through the option of duplication and visualization using VOSviewer software.
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22

Olena, Solona, Melnyk Oleksandr, and Hryshchenko Volodymyr. "SIMULATION OF THE SYSTEM OF MINERAL NUTRITION OF PLANTS IN CLOSED SOIL." Vibrations in engineering and technology, no. 3(106) (December 23, 2022): 72–77. http://dx.doi.org/10.37128/2306-8744-2022-3-10.

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One of the important factors in the high productivity of growing vegetable crops by the method of small volume of this system of vegetable production is the accurate and timely supply of mineral nutrition to their root system. During hydroponic cultivation, all mineral substances of plants are obtained from their aqueous solutions. In closed soil, the water regime should be regulated taking into account the biological characteristics of the culture, the growth phase and the intensity of light. To successfully implement the plant nutrition process, it is necessary to formulate a mathematical model of the process and equivalent transfer functions. This will make it possible to choose a rational way of management and determine the parameters of management systems. The analysis of the latest researches in the field of automation of processes of nutrition of plants grown in closed soil shows that for each specific case, a scheme of automation of this process was proposed, which led to different results of the implementation of the process of nutrition. To generalize the principles of regulating the supply of nutrient solutions to plants in closed soil, it is necessary to develop real mathematical models of processes and equivalent transfer functions that will allow choosing a rational method of management. The specificity of the object of research determines the need to use the analytical method of obtaining dynamic models as the main one. The mathematical description of the dynamics of mass transfer during drip irrigation includes the value of the evaporative capacity of plants. This value significantly depends on the parameters of the microclimate in the building. To determine the influence of these parameters on the dynamics of liquid transpiration, a mathematical model was obtained in the form of differential equations of heat and material balances. The obtained mathematical models and the structural schemes built on their basis will serve as the basis for creating a system of mineral nutrition of plants in closed soil.
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23

Mednikov, Aleksandr, Alexey Maksimov, and Elina Tyurina. "Mathematical modeling of mini-CHP based on biomass." E3S Web of Conferences 69 (2018): 02005. http://dx.doi.org/10.1051/e3sconf/20186902005.

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One of the promising directions of small-scale distributed power generation for Russia is the use of biomass. The present work is devoted to studies of an mini-CHP based on multi-stage biomass gasification. Mathematical models of elements and mini-CHP in general based on technological schemes were constructed. The mathematical models were constructed with the software developed at Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences. The calculations were made for two sizes of internal combustion engines. Thus, we obtained the values of flow rates, temperatures of heat carriers at various points of flow charts of the plants.
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24

Chew, Yin Hoon, Robert W. Smith, Harriet J. Jones, Daniel D. Seaton, Ramon Grima, and Karen J. Halliday. "Mathematical Models Light Up Plant Signaling." Plant Cell 26, no. 1 (January 2014): 5–20. http://dx.doi.org/10.1105/tpc.113.120006.

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25

A.D. SAPARBAEV, A. T. MAKULOVA, and A. A. ELEUSOV. "MODELS OF GRAIN TRANSPORTATION IN A COMPLEX SYSTEM OF GRAIN PROCESSING PLANTS." Bulletin of the National Engineering Academy of the Republic of Kazakhstan 3, no. 77 (October 15, 2020): 26–31. http://dx.doi.org/10.47533/2020.1606-146x.03.

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The purpose of the scientific article is to determine the optimal options for attaching grain farms to grain receiving enterprises. When writing the work were used methods for studying bibliographic sources and the principles of economic and mathematical modeling, systematization, synthesis, comparison, quantitative and qualitative analysis. Results of the study – the optimal options for attaching grain farms to grain receiving enterprises were determined on the basis of the effective use of their technical ability in operations of receiving, processing, placing, forming batches of grain and the optimal scheme for linking grain receiving enterprises to processing plants taking into account the distance of transportation for the intended purpose, as well as the annual needs.
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Диордиев, В. Т., А. А. Кашкарёв, and А. А. Диордиев. "DEVELOPMENT OF THE INTEGRATED MATHEMATICAL MODELS FOR THE DESCRIPTION OF THE DYNAMIC ELECTRIC POWER PLANTS." Proceedings of the Tavria State Agrotechnological University 19, no. 2 (2019): 200–207. http://dx.doi.org/10.31388/2078-0877-19-2-200-207.

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27

Hvala, Nadja, Darko Vrečko, Meta Levstek, and Cirila Bordon. "The Use of Dynamic Mathematical Models for Improving the Designs of Upgraded Wastewater Treatment Plants." Journal of Sustainable Development of Energy, Water and Environment Systems 5, no. 1 (March 2017): 15–31. http://dx.doi.org/10.13044/j.sdewes.d5.0130.

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28

Jean, R. "Application of Two Mathematical Models to the Araceae, a Family of Plants with Enigmatic Phyllotaxis." Annals of Botany 88, no. 2 (August 2001): 173–86. http://dx.doi.org/10.1006/anbo.2001.1411.

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29

Kulagin, V. A. "Development of a complex of mathematical models of a vehicle suspension for fatigue life analysis." Izvestiya MGTU MAMI 15, no. 4 (December 15, 2021): 33–42. http://dx.doi.org/10.31992/2074-0530-2021-50-4-33-42.

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The reduction in the duration of the development of new vehicles and the associated desire to reduce the costs of automotive plants contribute to a more active application of mathematical modeling to solve engineering problems. The tasks, which are analyzing and predicting the fatigue life of vehicle components and assemblies, can be solved using a set of methods and tools of mathematical modeling. This article discusses the development of a complex of mathematical models of the front and rear suspensions of a passenger automobile, which have the properties necessary for accurate reproduction of wheel loads and dynamic behavior of the suspension as a mechanical system. The complex of mathematical models is implemented in a multi-link modeling environment. The models are designed to carry out a subsequent validation study of the loading of individual suspension components during forced service life tests. In the future, this complex of mathematical models can be used for simulation of semi-natural forced resource tests of the suspension module, as well as a sample for the development of suspension models of other automobiles. The purpose of this work is to form sufficient requirements for mathematical models for the implementation of fatigue durability studies using mathematical modeling methods and obtaining reliable calculation results. Research engineers will be able to follow these requirements to determine and collect initial data for the development of their own mathematical models.
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Zayed, Tarek M., and Ibrahim A. Nosair. "Cost management for concrete batch plant using stochastic mathematical models." Canadian Journal of Civil Engineering 33, no. 8 (August 1, 2006): 1065–74. http://dx.doi.org/10.1139/l06-051.

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Assessing productivity, cost, and delays are essential to manage any construction operation, particularly the concrete batch plant (CBP) operation. This paper focuses on assessing the above-mentioned items for the CBP using stochastic mathematical models. It aims at (i) identifying the potential sources of delay in the CBP operation; (ii) assessing their influence on production, efficiency, time, and cost; and (iii) determining each factor share in inflating the CBP concrete unit expense. Stochastic mathematical models were designed to accomplish the aforementioned objectives. Data were collected from five CBP sites in Indiana, USA, to implement and verify the designed models. Results show that delays due to management conditions have the highest probability of occurrence (0.43), expected value of delay percent (62.54% out of total delays), and relative delay percent. The expected value of efficiency for all plants is 86.53%; however, the average total expense is US$15.56/m3 (all currency are in US$). In addition, the expected value of effective expenses (EE) is $18.03/m3, resulting in extra expenses (XE) of $2.47/m3. This research is relevant to both industry practitioners and researchers. It develops models to determine the effect of delays on concrete unit cost. They are also beneficial to the CBP management.Key words: concrete batch plant, delays, management conditions, cost models, cost management, stochastic mathematical models.
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Wang, Qing Cheng, Xiao Dong Yang, Guang Rui Shang, Zhuo Juan Yang, Guo Hua Cao, and Hong Ji Xu. "Research on Supporting Force of Several Models of Hydrophobic Plant Leaves." Applied Mechanics and Materials 152-154 (January 2012): 1112–17. http://dx.doi.org/10.4028/www.scientific.net/amm.152-154.1112.

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In this paper, the leaves of 5 kinds of hydrophobic plants including lotus, canna, green poplar, grape and pumpkin were selected, whose contact angles were 150.6º, 135.5 º, 110.4 º, 101.3 º and 94.8 º respectively by contact angle instrument measuring. These plant leaves were adhered to rectangular box by double-sided adhesive tape, as experimental model.The maximum supporting force of these models on water surface were measured by analytical balance, and the supporting force increases as contact angle, the dimple pressed by the model on water surface can increase its supporting force. Through mechanical analysis, the mathematical model of the supporting force was established, the relationship between depth of dimple and contact angle was analyzed by the mathematical model.
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Pérez, Maria del Carmen, Alejandro López, and Pablo Padilla. "Space-time dynamics of Stem Cell Niches: a unified approach for Plants." Journal of Integrative Bioinformatics 10, no. 2 (June 1, 2013): 48–57. http://dx.doi.org/10.1515/jib-2013-219.

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Summary Many complex systems cannot be analyzed using traditional mathematical tools, due to their irreducible nature. This makes it necessary to develop models that can be implemented computationally to simulate their evolution. Examples of these models are cellular automata, evolutionary algorithms, complex networks, agent-based models, symbolic dynamics and dynamical systems techniques.We review some representative approaches to model the stem cell niche in Arabidopsis thaliana and the basic biological mechanisms that underlie its formation and maintenance. We propose a mathematical model based on cellular automata for describing the space-time dynamics of the stem cell niche in the root. By making minimal assumptions on the cell communication process documented in experiments, we classify the basic developmental features of the stem-cell niche, including the basic structural architecture, and suggest that they could be understood as the result of generic mechanisms given by short and long range signals. This could be a first step in understanding why different stem cell niches share similar topologies, not only in plants. Also the fact that this organization is a robust consequence of the way information is being processed by the cells and to some extent independent of the detailed features of the signaling mechanism.
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De Clercq, Bob, Filip Coen, Bart Vanderhaegen, and Peter A. Vanrolleghem. "Calibrating simple models for mixing and flow propagation in waste water treatment plants." Water Science and Technology 39, no. 4 (February 1, 1999): 61–69. http://dx.doi.org/10.2166/wst.1999.0190.

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Mathematical models are useful tools in the prediction of system responses to operational changes in waste water treatment plants (WWTPs). The tanks-in-series model is one of the widespread hydraulic models in waste water treatment. This study shows the applicability of the mentioned model. Next to the mixing of substrate in a conventional activated sludge system, an oxidation ditch and a trickling filter, also the flow propagation in a waste water treatment plant was modelled. These different full-scale examples taken from waste water treatment demonstrate the relative ease of model configuration and calibration. Difficulties like experimental design, modelling the diffusion in biofilms and transients in flow rate were encountered.
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Zhang, Tongqian, Xinzhu Meng, Yi Song, and Zhenqing Li. "Dynamical Analysis of Delayed Plant Disease Models with Continuous or Impulsive Cultural Control Strategies." Abstract and Applied Analysis 2012 (2012): 1–25. http://dx.doi.org/10.1155/2012/428453.

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Delayed plant disease mathematical models including continuous cultural control strategy and impulsive cultural control strategy are presented and investigated. Firstly, we consider continuous cultural control strategy in which continuous replanting of healthy plants is taken. The existence and local stability of disease-free equilibrium and positive equilibrium are studied by analyzing the associated characteristic transcendental equation. And then, plant disease model with impulsive replanting of healthy plants is also considered; the sufficient condition under which the infected plant-free periodic solution is globally attritive is obtained. Moreover, permanence of the system is studied. Some numerical simulations are also given to illustrate our results.
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BILIAIEV, M. M., V. A. KOZACHYNA, P. B. MASHYKHINA, and V. V. TSURKAN. "MATHEMATICAL MODELING IN WATER TREATMENT PROBLEMS." Ukrainian Journal of Civil Engineering and Architecture, no. 4 (October 22, 2022): 13–19. http://dx.doi.org/10.30838/j.bpsacea.2312.250822.13.872.

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Problem statement. Analysis of the treatment facilities efficiency in sewerage at the stage of their design is great importance. Also, at the stage of structures’ reconstruction or their operation adjustment under different load conditions, it is necessary to know the efficiency of water treatment in different areas of treatment facilities. Such information makes it possible to rationally operate facilities. For solving problems of this class, the most effective tool is the use of the numerical modeling method. The work considers development of numerical models set for solving problems of this class. Methodology. Two fundamental models are used to solve the velocity field determination of the wastewater flow in the sewage treatment plant. The first is a model of the vortex-free motion for an incompressible fluid. The second model is the Navier-Stokes equations written in Helmholtz variables. The mass transfer equation is used to determine impurity concentration fields in sewage treatment plants, which takes into account flow velocity, diffusion and the presence of impurity emission sources. Material balance equations for the substrate and activated sludge are used to calculate the process of biological wastewater treatment. Finite-difference schemes are used to build numerical models that allow calculating the hydrodynamics of the flow and the distribution of the impurity concentration in the facility. The Euler method is used for the numerical solution of the material balance equations. Results. Numerical models were built, which were used to develop a complex of computer programs. These computer programs allow real-time analysis of the water treatment efficiency in the facility. Scientific novelty. Numerical models have been developed that allow investigating the process of water treatment in facilities of the «settler» type and in aeration tanks, that is, for a significant class of treatment facilities used in practice. Practical value. The calculation time of the velocity field and the impurity concentration field in a water treatment plant with a complex geometric shape is few seconds. This allows usinge the developed numerical models for serial calculations in project organizations in daily work.
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Zhang, Shu, Hu Jun Ling, Zhen Lin Zhang, Meng Jie Hu, and Yang Pang. "The Application of Fuzzy Neural Network Generalized Predictive Control in Unit Plant Coordinated Control System." Applied Mechanics and Materials 602-605 (August 2014): 1329–31. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.1329.

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The characteristic of unit coordinated control in thermal power plants having complex, nonlinear, larger time delay, and establishing mathematical models are very difficult. In the paper establish mathematical models of using fuzzy neural network system, make full use of the ability of fuzzy logic reasoning and neural network self-learning; using multivariable generalized predictive control strategy, Simulation results show that the use of fuzzy neural network generalized predictive control for good stability of main steam pressure , strong effectiveness of tracking the power grid load, and little fluctuation of different load conversion.
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Jacobsen, Bo Neergaard, Georg Becher, Bjorn K. Jensen, Silvano Monarca, Heidrun Scholz-Muramatsu, and Jaap Struijs. "Fate prediction of specific organic compounds in bioreactors." Water Science and Technology 33, no. 6 (March 1, 1996): 289–96. http://dx.doi.org/10.2166/wst.1996.0108.

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A systematic review of significant removal processes for specific organic compounds (SOCs) in bioreactors was conducted. The processes were quantified in terms of mathematical equations for removal rates and dependent parameters using a notation consistent with IAWQ nomenclature. Six SOCs, known to be frequent groundwater pollutants, were selected for further evaluation. Model simulations for the fate of these compounds in urban wastewater treatment plants (WWTPs) were performed and compared with the observed removal in the corresponding plants. A good agreement within ±15% was found for both the two different mathematical models used. Model parameters for process rate constants and partition coefficients were obtained, separately, from literature data; no fitting of the data to the monitoring data was performed. Several mathematical models for simulation of SOCs in WWTPs are available. The limiting step for further progress in this field is considered to be the lack of process rates under typical field conditions, in particular for biodegradation. It is recommended to initiate a systematic collection, organization and filing of such data within a European or international framework.
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Maryati, Ati, Nursanti Anggriani, and Ema Carnia. "STABILITY ANALYSIS OF TUNGRO DISEASE SPREAD MODEL IN RICE PLANT USING MATRIX METHOD." BAREKENG: Jurnal Ilmu Matematika dan Terapan 16, no. 1 (March 21, 2022): 217–28. http://dx.doi.org/10.30598/barekengvol16iss1pp215-226.

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Rice is one of the staple foods produced from the rice plant. Rice productivity is increased by carrying out efforts to control diseases that usually attack rice plants. Tungro is one of the most destructive diseases of rice plants. Mathematical models can help solve problems in the spread of plant diseases. In this paper, the development of a mathematical model for the spread of tungro disease in rice plants with 6 compartments is developed involving rice in the vegetative and generative phases. Furthermore, stability analysis is carried out on the obtained model by using the Basic Reproduction Number ( ) search through the matrix method, especially through the search for transition matrices and transmission matrices. The analytical results show that when 1 the non-endemic equilibrium point is stable and when >1 the endemic equilibrium point is stable. Numerical results showed that rice plants in the generative phase were more infected than rice plants in the vegetative phase.
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Petrochenkov, Anton, Aleksandr Romodin, Vladimir Kazantsev, Aleksey Sal’nikov, Sergey Bochkarev, Yuri Gagarin, Ruslan Shapranov, and Pavel Brusnitcin. "Principles of Imitation for the Loading of the Test Bench for Gas Turbines of Gas Pumping Units, Adequate to Real Conditions." Sustainability 13, no. 24 (December 10, 2021): 13678. http://dx.doi.org/10.3390/su132413678.

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The purpose of the study is to analyze the prospects for the development of loading methods for gas turbines as well as to develop a mathematical model that adequately describes the real operating conditions of the loading system at various loads and rotation speeds. A comparative analysis of the most common methods and technical means of loading the shafts of a free turbine at gas turbine plants intended for operation as part of gas pumping units is presented. Based on the results of the analysis, the expediency of using the loading model “Free Power Turbine Rotor–Hydraulic Brake” as a load simulation is shown. Recommendations for the creation of an automation system for the load testing of power plants have been developed. Mathematical models and Hardware-in-the-Loop simulation models of power plants have been developed and tested. One of the most important factors that predetermine the effectiveness of the loading principle is the possibility of software implementation of the loading means using software control systems that provide the specified loading parameters of the gas turbine.
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Andreeva, P. I., S. I. Zavalishin, and G. E. Shablinskiy. "Dynamic characteristics investigations of nuclear power plants containment shells using physicaland mathematical models and real projects." Vestnik MGSU, no. 11 (November 2013): 114–22. http://dx.doi.org/10.22227/1997-0935.2013.11.114-122.

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Kler, A. M., A. S. Maksimov, and E. L. Stepanova. "High-speed mathematical models of cogeneration steam turbines: Optimization of operation at heat and power plants." Thermophysics and Aeromechanics 13, no. 1 (January 2006): 141–48. http://dx.doi.org/10.1134/s1531869906010175.

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Leydon, Alexander R., Hardik P. Gala, Sarah Guiziou, and Jennifer L. Nemhauser. "Engineering Synthetic Signaling in Plants." Annual Review of Plant Biology 71, no. 1 (April 29, 2020): 767–88. http://dx.doi.org/10.1146/annurev-arplant-081519-035852.

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Synthetic signaling is a branch of synthetic biology that aims to understand native genetic regulatory mechanisms and to use these insights to engineer interventions and devices that achieve specified design parameters. Applying synthetic signaling approaches to plants offers the promise of mitigating the worst effects of climate change and providing a means to engineer crops for entirely novel environments, such as those in space travel. The ability to engineer new traits using synthetic signaling methods will require standardized libraries of biological parts and methods to assemble them; the decoupling of complex processes into simpler subsystems; and mathematical models that can accelerate the design-build-test-learn cycle. The field of plant synthetic signaling is relatively new, but it is poised for rapid advancement. Translation from the laboratory to the field is likely to be slowed, however, by the lack of constructive dialogue between researchers and other stakeholders.
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43

Bussell, E. H., C. E. Dangerfield, C. A. Gilligan, and N. J. Cunniffe. "Applying optimal control theory to complex epidemiological models to inform real-world disease management." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1776 (May 20, 2019): 20180284. http://dx.doi.org/10.1098/rstb.2018.0284.

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Mathematical models provide a rational basis to inform how, where and when to control disease. Assuming an accurate spatially explicit simulation model can be fitted to spread data, it is straightforward to use it to test the performance of a range of management strategies. However, the typical complexity of simulation models and the vast set of possible controls mean that only a small subset of all possible strategies can ever be tested. An alternative approach—optimal control theory—allows the best control to be identified unambiguously. However, the complexity of the underpinning mathematics means that disease models used to identify this optimum must be very simple. We highlight two frameworks for bridging the gap between detailed epidemic simulations and optimal control theory: open-loop and model predictive control. Both these frameworks approximate a simulation model with a simpler model more amenable to mathematical analysis. Using an illustrative example model, we show the benefits of using feedback control, in which the approximation and control are updated as the epidemic progresses. Our work illustrates a new methodology to allow the insights of optimal control theory to inform practical disease management strategies, with the potential for application to diseases of humans, animals and plants. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.
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44

López, Andrés Robalino, and Ángel Mena-Nieto. "Meteorological Forecasting for renewable energy plants. A case study of two energy plants in Spain." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 2 (June 17, 2015): 181. http://dx.doi.org/10.17770/etr2015vol2.262.

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<p class="R-AbstractKeywords"><span lang="EN-US">Energy resources are the engines that drive every economy [1], [4], [14], Therefore, it is necessary to develop their exploitation in a friendlier, environmentally and sustainable way indeed it is a critically needed nowadays. Then, it is necessary to improve efficiency and optimize renewable energy in order that replace polluting energy sources. This work aims to relate the use of forecasting on meteorological variables such as wind speed, wind direction, solar radiation, among others, obtained by mathematical models implemented on computer to forecast energy production in renewable energies plants. It has been implemented and automated one of the most used models by the scientific community in this field, WRF (Weather Research and Forecasting Model). WRF is a next generation mesoscale model, designed to serve as a tool for meteorological research in addition to provide forecasts in operational regime. This research introduce the topic of energy forecast, mainly of renewable energy, focusing on wind and solar energy, basing the study on a better forecasting of meteorological variables in order to use as income in energy production forecast. A case study in two Spanish renewable energy plants is exposed</span><span lang="EN-US">. </span></p>
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45

Zhuravleva, V. V., A. S. Manicheva, and A. A. Martynova. "Analysis of the Mathematical Model of Photosynthesis in Protected Ground." Izvestiya of Altai State University, no. 4(114) (September 9, 2020): 86–91. http://dx.doi.org/10.14258/izvasu(2020)4-13.

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The problem of predicting changes in the intensity of photosynthesis associated with changes in the lighting mode, atmospheric carbon dioxide concentration, and the temperature is urgent. Appropriate models can help choose the optimal mode of growing plants in protected soil, as well as serve as a basis for predicting the consequences of global climate change. It is noted that in the conditions of protected soil, the most significant factor is the illumination of plants. The aim of the research is to construct an algorithm for additional illumination of plants in protected ground conditions based on a mathematical model of photosynthesis. The authors introduced the value of the efficiency of additional illumination and studied its dependence on the coefficient of light transmission of the roof. The solution of the main task of the study is achieved by the fact that the light mode in protected ground structures is carried out on the basis of additional illumination to the ideal (optimal) for this type of plant. The entered value of the efficiency of additional illumination shows what energy costs will be for the production of photosynthesis products and, as a result, allows estimation of the economic costs. The considered method of artificial lighting of plants makes it possible to effectively use both sunlight and artificial lighting, providing an optimal lighting mode all year round, and allows to increase the intensity of photosynthesis by 50-80 %.
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46

Belonosov, Mikhail, and Vladimir Kishkin. "Verification on application program generation and loading for safety systems of nuclear power plants based on the reverse engineering method." Nuclear Energy and Technology 4, no. 4 (December 13, 2018): 223–28. http://dx.doi.org/10.3897/nucet.4.31868.

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The article describes an automated verification method used for application software of control safety systems based on the TPTS-SB equipment. Verification is performed by comparing two mathematical models (oriented graphs): one obtained by processing the original design data, i.e., graphical functional diagrams, and the other formed by reversing the program code loaded from the controller. The vertices in both graphs are functional blocks of mathematical and logical operations; the edges are connections between them. The constructed mathematical models undergo a comparison, covering the vertices and edges of the graphs as well as the memory cells and values of constants. The equivalence of mathematical models proves the correspondence between the program code and the initial set of design functional diagrams. The proposed automated verification method makes it possible to prove that no distortion is introduced into the program during the process of converting graphical functional diagrams into the program code with its subsequent translation and loading into the controller. It is postulated that any distortions will be detected during the verification procedure, which is performed every time after loading the code into the controller. The solution provides an acceptable speed when large volumes of vector graphics stored in a relational database are processed, and makes it possible to visualize the verification results. The proposed method is implemented in the GET-R1 instrumentation tools for TPTS-SB and is used in designing and verifying the application software of the safety systems at the Belarusian NPP.
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Barbi, Silvia, Francesco Barbieri, Alessandro Bertacchini, and Monia Montorsi. "Statistical Optimization of a Hyper Red, Deep Blue, and White LEDs Light Combination for Controlled Basil Horticulture." Applied Sciences 11, no. 19 (October 6, 2021): 9279. http://dx.doi.org/10.3390/app11199279.

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This study aims to optimize artificial LEDs light conditions, for “Genovese” basil germination and growth in an indoor environment suitable for horticulture. Following a previous study on the synergic effect of LEDs light and a tailored fertilizer, in this study, the effect of white LED in combination with hyper red and deep blue, as well the plants–lights distance, was correlated to 14 growth and germination parameters, such as height, number of plants, etc. A design of experiments approach was implemented, aiming to derive mathematical models with predictive power, employing a restrained number of tests. Results demonstrated that for the germination phase, it is not possible to derive reliable mathematical models because almost the same results were found for all the experiments in terms of a fruitful germination. On the contrary, for the growth phase, the statistical analysis indicates that the distance among plants and lights is the most significant parameter. Nevertheless, correlations with LED light type emerged, indicating that white LEDs should be employed only to enhance specific growth parameters (e.g., to reduce water consumption). The tailored models derived in this study can be exploited to further enhance the desired property of interest in the growth of basil in horticulture.
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Voronin, K. P., V. S. Kotov, and A. Y. Lapidus. "The quality indicator model of the functioning on ship gas turbine plants." Transactions of the Krylov State Research Centre S-I, no. 1 (December 8, 2021): 134–36. http://dx.doi.org/10.24937/2542-2324-2021-1-s-i-134-136.

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Special mathematical models are described for predicting plant failures on the basis of multivariate statistical analysis of operational information by using factor analysis. The considered process of assessing changes in the technical state of a gas turbine engine in operation on the basis of factor analysis can be applied to various energy facilities for which the parameters of the working process are periodically recorded.
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Oyewo, Toyese, Odunayo Magret Olarewaju, Melanie Bernice Cloete, and Olukorede Tijani Adenuga. "Environmental costs estimation and mathematical model of marginal social cost: A case study of coal power plants." Environmental Economics 12, no. 1 (August 20, 2021): 90–102. http://dx.doi.org/10.21511/ee.12(1).2021.08.

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An increase in electricity production is proportional to environmental risks due to continuous energy production. The paper aims to quantitatively estimate the environmental costs and mathematically model the marginal social cost associated with the lifespan of the coal power plants. Results revealed South Africa Tier 1 company optimum level of electricity production per annum at around 2.15 gigawatts, considering the emission costs and reasonable profit. 85% of the total emissions during the combustion phase average cost of the C02 emission discharged by coal is calculated as 0.23c/KWh, 0.085c/kWh is calculated for NO2, while SO2 is 0.035c/KWh. Total emission cost represents 69.2% of the total cost of producing 1 MGW of electricity. The results confirmed the company losses to be insignificantly considerable to the evaluated environmental costs and capital investment. However, the use of this newly developed mathematical model depends on the source of energy production to confirm the feasibility and profitability of investment in coal-powered stations using environmental management accounting and marginal social cost approaches. AcknowledgmentThe authors would like to acknowledge the National Research Foundation and Durban University of Technology for financial support.
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Portes, Tomás Aquino. "Estimating the interconversion between CO2 and organic matter in the environment using mathematical models and some considerations." Revista de Biologia Neotropical / Journal of Neotropical Biology 17, no. 1 (June 27, 2020): 56–67. http://dx.doi.org/10.5216/rbn.v17i1.61889.

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The aims was to use mathematical models to analyze the interconversion between the amount of organic matter produced and the consequent variation in the concentration of CO2 in the atmosphere and to discuss, supported by the data presented and the literature, possible changes in the Earth's environment. Scientific findings and evidence indicate that the concentrations of CO2 and O2 varied throughout the existence of the Earth. These variations were a consequence of the existing environment in different Eras, resulting in changes in all other processes that depended on these gases. Chemical reactions occurred and organic products such as petroleum arose abiotically. These products gave origin to organic chemistry and drastically reduced the concentration of CO2 and elevated O2 in the atmosphere. In the current plants, for each O2 produced in the photochemical step of photosynthesis, one CO2 is assimilated in the biochemical step. Supported by this relationship and by the results presented in this work, it can be inferred that the first photosynthetic organisms originated on Earth when the concentration of CO2 was possibly at a concentration below 1000 ppm. Biochemistry started with these organisms. The results suggest that the reduction in CO2 concentration was linear in relation to the age of the Earth, before the origin of photosynthetic organisms. This relationship changed with origin of these organisms, due to the major changes that occurred in the environment. There is evidence that in certain periods, CO2 concentrations have been reduced below the CO2 compensation point for certain plants resulting in the extinction of these plants and the organisms that depended on them.
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