Journal articles on the topic 'Soil temperature – Mathematical models'
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Dessureault-Rompré, Jacynthe, Bernie J. Zebarth, Alex Georgallas, David L. Burton, Cynthia A. Grant, and Craig F. Drury. "Temperature dependence of soil nitrogen mineralization rate: Comparison of mathematical models, reference temperatures and origin of the soils." Geoderma 157, no. 3-4 (July 2010): 97–108. http://dx.doi.org/10.1016/j.geoderma.2010.04.001.
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Ryabkov, A. V., E. P. Martynenko, A. F. Zakuraev, and B. A. Ashabokov. "DEVELOPMENT OF MATHEMATICAL MODELS FOR STUDYOF GEOTECHNICAL PROPERTIES OF MARSHES." Oil and Gas Studies, no. 4 (September 1, 2016): 93–97. http://dx.doi.org/10.31660/0445-0108-2016-4-93-97.
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It is shown that failures at normal operation of pipeline transport occur largely due to the cyclical nature of degradation processes that are inherent in the system with various soil and swamp covers and are accompanied by sharp negative temperature gradients. A model of methane liberation processes was generated. The method of molecular beam epitaxy was analyzed, which permitted to capture the volume and cyclicity of methane liberation, to measure all noises and signals in different frequency ranges.
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Park, Keunbo, Heekwon Yang, Bang Lee, and Dongwook Kim. "Development of Shallow-Depth Soil Temperature Estimation Model Based on Thermal Response in Permafrost Area." Applied Sciences 8, no. 10 (October 11, 2018): 1886. http://dx.doi.org/10.3390/app8101886.
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A soil temperature estimation model for increasing depth in a permafrost area in Alaska near the Bering Sea is proposed based on a thermal response concept. Thermal response is a measure of the internal physical heat transfer of soil due to transferred heat into the soil. Soil temperature data at different depths from late spring to the early autumn period at multiple permafrost sites were collected using automatic sensor measurements. From the analysis results, a model was established based on the relationship between the normalized cumulative soil temperatures (CRCST*i,m and CST*ud,m) of two different depths. CST*ud,m is the parameter of the soil temperature measurement at a depth of 5 cm, and CRCST*i,m is the parameter of the soil temperature measured at deeper depths of i cm (i = 10, 15, 20, and 30). Additionally, the fitting parameters of the mathematical models of the CRCST*i,m–CST*ud,m relationship were determined. The measured soil temperature depth profiles at a different site were compared with their predicted soil temperatures using the developed model for the model validation purpose. Consequently, the predicted soil temperatures at different soil depths using the soil temperature measurement of the uppermost depth (5 cm) were in good agreement with the measured results.
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Shein, Ye V., A. G. Bolotov, and A. V. Dembovetskii. "Soil Hydrology of Agricultural Landscapes: Quantitative Description, Research Methods, and Availability of Soil Water." Eurasian Soil Science 54, no. 9 (September 2021): 1367–74. http://dx.doi.org/10.1134/s1064229321090076.
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Abstract Soil hydrology has deep Russian roots, which are primarily related to the theory of soil hydrological constants and their practical application. These constants have been used to assess the hydrological soil conditions in stationary observations, for which attempts to arrange regular hydrological observations in the landscape faced impracticable complexity of work and calculations and provided unreliable quantitative predictions. At present, there are new opportunities for experimental research, digital analysis, and prediction of hydrological indicators of soils in the landscape. A new quantitative approach to the use of digital technologies for monitoring soil water and temperature in the soils of agricultural landscapes, their dynamics, and their probabilistic calculations has been developed. Based on the soil map, it is proposed to create an information and measurement system with the studied thermal and hydrophysical characteristics of soils using mathematical models to calculate the dynamics of moisture and temperature for given periods and conditions of different availability of heat and precipitation, which allows us to quantify the availability of moisture reserves in the soils of the agricultural landscape. This system of observations, assessment, and forecast includes the use of modern technologies for determining soil water content and temperature, the adaptation of predictive physically based models for calculating the dynamics of moisture reserves depending on the availability of precipitation and conditions at the lower boundary of soil profiles. The paper deals with the hydrological analysis of soils by the example of the agricultural landscape of the Zelenograd station of the Dokuchaev Soil Science Institute in the village of El’digino, Pushkino district, Moscow oblast.
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Shishkin, K. V., A. A. Belik, A. A. Kokoreva, and Z. S. Ezhelev. "Adequateness assessement of percolate and temperature model using MSU Large lysimeters." Dokuchaev Soil Bulletin, no. 99 (December 9, 2019): 76–91. http://dx.doi.org/10.19047/0136-1694-2019-99-76-91.
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The assessement of PEARL model adequateness was carried out on the basis of temperature and percolate data obtained by means of MSU Large Lysimeters. Lysimeters are used in experimental soil science mostly for investigating water balance and substance or ions transport from observed horizons or full soil profile. PEARL 4 model, the water prediction block of which is built on the basis of classical SWAP model, uses preferential water flow describing mechanism. Systematical observation of experimental soils in MSU Large lysimeters allowed obtaining extensive data on temperature and soil moisture dynamics, as well as percolate from bottom border. Thеsе measurements are unique and can become the basis for adaptation, verification and setting of mass and energy transfer models. It was shown, that mathematical parametric model requires adjustment for reaching reliable values of percolate from bottom border, moisture and temperature profiles. It can be achieved by selection of water retention curve (WTC) approximation parameters. It was noticed that the error for all predicted parameters increases in winter period. Thereby, the use of such matter transfer models in soil are problematic for long-term prognosis. For example, due to the annual error accumulation before the spring season such models cannot be applied for estimation of the risk of ground water pollution with agrochemicals.
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Palamarchuk, Vitalii, and Oleksii Alieksieiev. "MATHEMATICAL MODELS OF HIGH-STARCH MAIZE HYBRIDS OF DIFFERENT GROUND GROUPS." Agriculture and Forestry, no. 1 (April 28, 2020): 28–47. http://dx.doi.org/10.37128/2707-5826-2020-1-3.
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The article presents the results of mathematical modeling based on the construction and usage of different images of an object, process or system. The research expected to study the dependence of the productivity level and the economically valuable features of corn hybrids in the form of mathematical models. Field studies were carried out during 2011-2017 at the field of research of the Department of Plant, Selection and Bioenergy Crops of SE EF “Kordelivske” of IP NAASU of Vinnytsia National Agrarian University under the conditions of the Forest-Steppe of the Right-Bank, in accordance with the recommendations presented in the Methodology Of The Maize Field Study. The soils in the study variants are represented by black earth soil of deep medium loamy on the loessial soil. The humus content (according to Tiurin) in the tilth soil was 4.60%. Soil reaction - pH (salt) 5.7. The soils contain lightly hydrolyzed nitrogen (according to Kornfield) 106 mg per 1 kg of soil, mobile phosphorus and exchangeable potassium (according to Chirikov) 186 and 160 mg per 1 kg of soil, respectively. The experiments established the economic and biological evaluation of corn hybrids depending on the sowing period, the size of the fraction and the depth of seed wrapping, foliar fertilizers by micro fertilizers. The plot area for hybrids was 10.5 m2. Repeatability in experiments for hybrids is 3 times. Placement of plots is by the method of randomized blocks. An ecological-genetic model of quantitative features was used to study the phenotypic productivity of maize hybrids and to establish the influence on the formation of their traits. The model construction is based on the hierarchy of production traits demonstration in ontogeny and the correspondence of their manifestation in organogenesis. The model consists of three modules of features, i.e. the resultant and two components which reflecting the phenotypic implementation of the genetic formula. Resulting features are those that have an environmentally stable relationships and the highest total contribution to the intended property, yield. As a result of the conducted research, the mathematical models of the duration of the growing season of early-maturing maize hybrids allowed us to determine that the biggest influence does sums of effective temperatures (≥ + 10° C) for May, June, August and September over correlation rate at r = -0.62 and r = -0.51, r = 0.59 and r = 0.39, respectively. Also precipitation amount significantly influenced on the duration of the growing season and the correlation coefficient was r = -0.44, and the influence of the HTI was at the level of r = -0.34. For middle-early hybrids the sum of effective temperatures (≥ + 10° C) in May and June r = -0.46 and r = -0.28, respectively, and also the sum of effective temperatures (≥ + 10° C) in August – r = 0.18 had a strong effect. However, for medium-maturing maize hybrids, the duration of the growing season was determined by the sum of effective temperatures (≥ + 10° C) for May, June and July – r = -0.37, r = -0.34 and r = -0.28, and the sum of effective temperatures (≥ + 10° C) in August – r = 0,18. It is also possible to note the influence and the total sum of effective temperatures (≥ + 10° C) during vegetation at the level of correlation coefficient r = -0.51. According to the research results of mathematical models of the influence of weather conditions on the formation of phenotypic productivity of maize hybrids of different maturity groups both general biological regularities and group differences of features formation were established. Thus, if we analyze the differences between groups of early-ripening and middle-early corn hybrids, their growth and development in general are influenced by the sum of the effective temperatures, rainfall and HTI. In fact, the studied groups of ripeness differ slightly and the main differences are observed only in the variability of the studied features or their close relationship with each other. However, middle-aged hybrids respond somewhat differently to environmental factors, which allow developing the elements of adaptive growing technology for each of the maturity groups. Key words: corn, hybrid, phenotype, mathematical model, productivity, economic and valuable features.
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Wilson, David J., and Kanji Tamamushi. "Low-Temperature Thermal Treatment of Contaminated Soils: Simple Mathematical Models." Separation Science and Technology 28, no. 15-16 (November 1993): 2351–75. http://dx.doi.org/10.1080/01496399308019742.
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Van, Sin'tun, Aleksey Kolos, and Andrey Petryaev. "Mathematical Modeling of the Process of Soil Freezing of Railway Subgrade in Cold Climate Con-ditions." Proceedings of Petersburg Transport University 19, no. 4 (December 20, 2022): 820–31. http://dx.doi.org/10.20295/1815-588x-2022-4-820-831.
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Purpose: Mathematical model for studying the process of soil freezing given moisture migration is developed. Numerical modeling of temperature mode of railway subgrade at non-stationary pro-cess in cold climate conditions is performed. Methods: Numerical implementation of the model is performed by mathematical module processing in COMSOL Multiphysics program, which’s based on partial differential equations (PDE), with finite element method. The model reliability is con-firmed by the comparison with previous experimental data and the results of simulation by other authors. Results: Calculation results on the developed model basis show the best correlation with experimental data in comparison with the results for other models. Calculation example and calcu-lation results for subgrade temperature mode in freezing-thawing fifth cycle are presented. The analysis of soil freezing depth change and soil temperature fluctuation change by depth by fifth year are carried out. Practical significance: The developed mathematical model makes it possible to predict soil freezing depth, taking into account moisture migration, including freezing and thawing depth changes caused by climate warming. The developed model can be used both, to study the mechanism of subgrade temperature mode distribution at freezing and thawing, and to improve subgrade construction for to protect it from soil frost heaving.
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Tarnawski, Vlodek R., and Bernhard Wagner. "On the prediction of hydraulic conductivity of frozen soils." Canadian Geotechnical Journal 33, no. 1 (March 25, 1996): 176–80. http://dx.doi.org/10.1139/t96-033.
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This paper describes a mathematical model for predicting the hydraulic conductivity of partially frozen soils on the basis of limited input data such as grain size distribution and bulk density or porosity. A new model is based on an analogy for the hydraulic conductivity of frozen and unfrozen soils and models for the estimation of hydraulic properties of soils and unfrozen water content. Campbell's model was used for prediction of soil-water characteristics from limited data, while unfrozen water content was obtained from two models (by P.J. Williams and D.M. Anderson) applied to two different temperature ranges. The new model can be used for the rapid estimation of the hydraulic conductivity of practically any freezing soil having log-normal grain size distribution and for computer simulation of moisture migration in soils below the freezing point. An acceptable conformity between the model prediction and measured data for pure sand has been achieved. The computer program developed requires the following input data: grain size distribution, bulk density or porosity, and soil temperature. Key words: frozen soils, hydraulic conductivity, bulk density, grain size distribution, unfrozen water content.
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Tong, Bing, Zhiqiu Gao, Robert Horton, and Linlin Wang. "Soil Apparent Thermal Diffusivity Estimated by Conduction and by Conduction–Convection Heat Transfer Models." Journal of Hydrometeorology 18, no. 1 (December 27, 2016): 109–18. http://dx.doi.org/10.1175/jhm-d-16-0086.1.
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Abstract Soil heat transfer is complex, and conduction-alone models may not always perform well in estimating soil apparent thermal diffusivity. Soil apparent thermal diffusivity is related to soil temperature change propagation rates. Soil temperature data collected at the Tazhong station in China were used to examine the characteristics of soil apparent thermal diffusivity determined by three different algorithms and the sum of vertical gradient of soil apparent thermal diffusivity and apparent water flux density . The results showed that 1) soil apparent thermal diffusivity obtained with a conduction–convection algorithm had a better agreement with soil apparent thermal diffusivity obtained with a phase algorithm than with soil apparent thermal diffusivity obtained with an amplitude algorithm except for the case of = 0; 2) when > 0, , and when < 0, ; 3) for a given soil temperature phase shift, increased (decreased) with increasing logarithmic amplitude attenuation when the phase shift was larger (smaller) than the logarithmic amplitude attenuation, reached a maximum value when the phase shift equaled the logarithmic amplitude attenuation, and increased with increasing logarithmic amplitude attenuation; and 4) for a given logarithmic amplitude attenuation, decreased with increasing phase shift and increased (decreased) with increasing phase shift when the phase shift was larger (smaller) than times the logarithmic amplitude attenuation. These mathematical conclusions were also confirmed with field data.
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Vincent, C. D. "Recent Advances in Modelling Crop Response to Temperature." Outlook on Agriculture 18, no. 2 (June 1989): 54–57. http://dx.doi.org/10.1177/003072708901800202.
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Mathematical models to predict the effect of altering various parameters in real-life situations are now widely used. The complexity of the factors that control the growth of crops makes such modelling very difficult in the context of agriculture, but nevertheless some useful results have been obtained. This article reviews the progress that has been made in predicting the effect of air and soil temperature on the growth of plants.
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Zhang, Li, Zhi Kai Chang, and Shang Feng Du. "Measurement Model and Simulation of Soil Nitrate Nitrogen Based on Ion Selective Electrode." Advanced Materials Research 718-720 (July 2013): 657–62. http://dx.doi.org/10.4028/www.scientific.net/amr.718-720.657.
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The existing conventional detection methods ofnitrate nitrogenmostly consume time, cost a lot of moneyand need professionals. This limits the application of soil testing and fertilization technology at the grass-roots level. Therefore, a kind of fast, low-cost and simple operated method of soil nitrate nitrogen is in urgent need. The research of measurement models based on electrochemical principles of soil nitrate nitrogen is carried out in this paper to the issue ofquick access to the information of soil nitrate nitrogen. The linear regression equation is used to establish the mathematical model of electrodes and the binary quadratic regression model is used to study the temperature correction mathematical model of electrodes and finally matlab is used for datasimulation.
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Barrett, Damian J., and Luigi J. Renzullo. "On the Efficacy of Combining Thermal and Microwave Satellite Data as Observational Constraints for Root-Zone Soil Moisture Estimation." Journal of Hydrometeorology 10, no. 5 (October 1, 2009): 1109–27. http://dx.doi.org/10.1175/2009jhm1043.1.
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Abstract Data assimilation applications require the development of appropriate mathematical operators to relate model states to satellite observations. Two such “observation” operators were developed and used to examine the conditions under which satellite microwave and thermal observations provide effective constraints on estimated soil moisture. The first operator uses a two-layer surface energy balance (SEB) model to relate root-zone moisture with top-of-canopy temperature. The second couples SEB and microwave radiative transfer models to yield top-of-atmosphere brightness temperature from surface layer moisture content. Tangent linear models for these operators were developed to examine the sensitivity of modeled observations to variations in soil moisture. Assuming a standard deviation in the observed surface temperature of 0.5 K and maximal model sensitivity, the error in the analysis moisture content decreased by 11% for a background error of 0.025 m3 m−3 and by 29% for a background error of 0.05 m3 m−3. As the observation error approached 2 K, the assimilation of individual surface temperature observations provided virtually no constraint on estimates of soil moisture. Given the range of published errors on brightness temperature, microwave satellite observations were always a strong constraint on soil moisture, except under dense forest and in relatively dry soils. Under contrasting vegetation cover and soil moisture conditions, orthogonal information contained in thermal and microwave observations can be used to improve soil moisture estimation because limited constraint afforded by one data type is compensated by strong constraint from the other data type.
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ZHARNITSKIY, V. YA, P. A. KORNIENKO, and A. P. SMIRNOV. "Mathematical modeling of thermal processes in the «Concrete-soil» system." Prirodoobustrojstvo, no. 3 (2022): 71–76. http://dx.doi.org/10.26897/1997-6011-2022-3-71-76.
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The calculation of concrete curing modes and the development of mathematical models are greatly influenced by the temperature field in the concrete of channel linings. The problem is reduced to solving a nonlinear heat equation that takes into account the exothermic heat release of concrete and the phase transformation of moisture, and time-varying boundary conditions that allow taking into account the impact on concrete of the external environment during laying and maintenance. Variable thermophysical coefficients make it possible to take into account the inhomogeneity of the medium (in the case of laying concrete on the ground) and the change in the aggregate state of the substance when the phase transformation temperature is reached. Since it is impossible to obtain an analytical solution in a general form, a numerical solution method is used, based on a combination of a finite-difference solution with a method for calculating heat release and concrete strength from the corresponding fields of isothermal curves obtained experimentally. When constructing a difference scheme, an integro-interpolation method (balance method) is used, based on the law of conservation of heat. For an extended body of sufficiently large dimensions, the process of heat transfer in it is assumed to be linear, and the coordinate system with the center is taken to be on the axis of the body. The presented mathematical model of thermal processes in the “concrete-soil” system makes it possible to predict the modes of holding monolithic concrete to achieve the necessary technological requirements, as well as to apply the most economical modes.
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Brusturean, Gabriela-Alina, Jean Carré, Delia Perju, and Teodor Todinca. "Study of the influence of temperature the venting depollution process of soils contaminated with volatile organic compounds." Journal of the Serbian Chemical Society 71, no. 12 (2006): 1353–61. http://dx.doi.org/10.2298/jsc0612353b.
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Venting is one of the most used in situ remediation methods for unsaturated soils contaminated with volatile organic compounds (VOC). The development of mathematical models and their validation by means of experimental results allowed the identification of the main parameters which influence the soil depollution process. The influence of temperature on the venting depollution process of soils polluted with volatile organic compounds was studied in this investigation. It was found that the depollution efficiency is strongly influenced by the vapour pressure of the pollutants. The conclusions, derived from the performed experimental determinations allowed characterization of the depollution process by using an "equilibrium" model. This model considers the existence of equilibrium between the four pollution phases (vapour, aqueous, "solid" and non-aqueous phase organic liquids) at any moment in time. In order to calculate the vapour pressure, a modified equation of the Antoine model was used in the model. Application of the mathematical model indicates that a 10 ?C temperature rise leads to a two-fold increase in the vapor pressure of a compound. Comparison of the modeled and experimental curves, as well as the values of the obtained performance critterions, verified that the chosen mathematical model describes the influence of temperature on the depollution process very well. .
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Sidnyaev, Nikolay Ivanovich, Vasilii Ivanovich Vasiliev, and Yuliya Sergeevna Ilina. "Calculation methods of non-stationary temperature fields influence on foundation in cryolithozone." Арктика и Антарктика, no. 2 (February 2020): 106–25. http://dx.doi.org/10.7256/2453-8922.2020.2.32405.
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This article is devoted to the mathematical modeling and computing experiment in problems of temperature fields forecast in continuous foundations in cryolithozone, which will provide a qualitative approach to non-stationary thermal calculations for making design decisions to ensure the stability and reliability of bases and foundations of buildings in the Arctic zone. The article formulates the problem of forecasting by determining changes in the temperature, areal distribution, thickness, and vertical structure of permafrost, seasonal and perennial freezing of the soil, their temperature strength state, and properties in connection with the construction of buildings. Presented mathematical calculations are based mainly on the assumption of a non-stationary process of heat exchange. Mathematical models for determining depth of thawing are considered. The problem of determining the temperature in the basement of the foundation, limited on the one side, in which the temperature depends on only one coordinate with the condition that the surface temperature of the permafrost soil undergoes periodic fluctuations around zero value under the influence of external influences, has been solved. It is demonstrated that the two-dimensional problem of permafrost ground with a semi-infinite foundation thickness can be generalized even more. The problem is formulated in the form of a differential equation of heat balance taking into account the heat flux, which varies according to the Fourier’s law.
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Cârdei, Petru, Cătălina Tudora, Valentin Vlăduț, Mirabela Augustina Pruteanu, Iuliana Găgeanu, Dan Cujbescu, Despina-Maria Bordean, Nicoleta Ungureanu, George Ipate, and Oana Diana Cristea. "Mathematical Model to Simulate the Transfer of Heavy Metals from Soil to Plant." Sustainability 13, no. 11 (May 30, 2021): 6157. http://dx.doi.org/10.3390/su13116157.
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Heavy metals are naturally occurring elements, but their various applications have led to their wide circulation in the environment, raising concerns over their latent effects on the environment and human health. Their toxicity depends on numerous factors, including chemical species, concentration of heavy metal ions, environmental factors, etc. Experimental studies on the single or cumulative effects of heavy metals on plants are complex, time consuming and difficult to conduct. An alternative is mathematical modeling, which can include different factors into an integrated system and can predict plant and environmental behavior under multiple stressors. This paper presents a mathematical model that simulates the dependence of temperature, concentration of Zn in the soil and the subsequent bioaccumulation in lettuce (Lactuca sativa L.); respectively, the reaction of lettuce to Zn contamination. The main results consist of three mathematical models, based on systems of ordinary differential equations and checking their predictions with available experimental data. The models are applied to predict an optimal harvest time of lettuce with low concentration of Zn, in identifying the availability of the analyzed species to phytoremediation operations and the possibility of maneuvering certain control factors to reduce or increase the intensity of the bioaccumulation process.
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Pospelova, Irina G., Ivan V. Vozmishchev, and Anatoliy M. Niyazov. "Soil Disinfection Methods in Protected Ground." Elektrotekhnologii i elektrooborudovanie v APK, no. 3 (September 20, 2020): 45–49. http://dx.doi.org/10.22314/2658-4859-2020-67-3-45-49.
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Soil is a favorable environment for many microorganisms, pathogenic bacteria, fungal spores, insect eggs due to the presence of nutrients and moisture in it. Soil treatment from pests and pathogens of agricultural crops for disinfection can be carried out by chemical, energy, thermal, biological methods. The most common method is thermal. This is because many pests and pathogens have a protein structure that is easily destroyed when the temperature increases, and the thermal effect can be obtained from various heat carriers. (Research purpose) The research purpose is in developing an energy-efficient method of soil disinfection using infrared radiation. (Materials and methods) The article shows the relation between the spectral thermoradiation characteristics of soil with characteristics of infrared emitters, namely the amount of applied heat, temperature, conductivity, soil moisture, and exposure time, to justify the rational mode of operation for decontamination of the soil. The article presents a mathematical model for this purpose based on known laws that determine the relationship between the necessary parameters. (Results and discussion) Authors offered a plant for soil disinfection with infrared radiation. It was found that the high energy efficiency of the installation is achieved by a high efficiency of infrared burners and infrared radiation affects directly the object of treatment, the soil. The article presents structural-logical and mathematical models of infrared power supply. (Conclusions) Analysis of the heating kinetics equation showed that the maximum permissible speeds for the process of infrared heating of the soil depend on its thermophysical properties, the maximum permissible temperature, the area and the required depth of warming of the soil. It was found that infrared heating and a device for disinfecting the soil in this way will allow energy-efficient, convenient and fast processing.
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Magda, Waldemar. "Comparison of Soil Models in the Thermodynamic Analysis of a Submarine Pipeline Buried in Seabed Sediments." Polish Maritime Research 24, no. 4 (December 20, 2017): 124–30. http://dx.doi.org/10.1515/pomr-2017-0144.
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Abstract This paper deals with mathematical modelling of a seabed layer in the thermodynamic analysis of a submarine pipeline buried in seabed sediments. The existing seabed soil models: a “soil ring” and a semi-infinite soil layer are discussed in a comparative analysis of the shape factor of a surrounding soil layer. The meaning of differences in the heat transfer coefficient of a soil layer is illustrated based on a computational example of the longitudinal temperaturę profile of a -kilometer long crude oil pipeline buried in seabed sediments.
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Zhalko, M. E., and K. A. Cherny. "INFLUENCE OF THE ROAD BASEMENT WATER AND THERMAL REGIME ON THE PAVEMENT CONDITION." Construction and Geotechnics 10, no. 3 (December 15, 2019): 97–103. http://dx.doi.org/10.15593/2224-9826/2019.3.10.
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A article is devoted to study of the roads pavement condition influence with improved surface on the road traffic safety. The topicality of the issue is confirmed traffic police statistics and a significant list of scientific papers dealing with issues of water and heat balance of soil mass. The article deals with the road, located in the city and suburban areas. The work shows the temperature and humidity influence on the process of soil freezing and on the road surface integrity directly. Mathematical models of temperature distribution processes and filtration fluid movement in the ground are presented. In article offered option to improve the technical and operational characteristics of roads. It will have a positive impact on the traffic safety and smoothness.
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Rudov, S. E., V. Ya Shapiro, O. I. Grigoreva, I. V. Grigorev, and O. A. Kunitskaya. "A Predictive Model of the Impact of the Skidding System on Forest Soil in Severe Climatic Conditions." Lesnoy Zhurnal (Forestry Journal), no. 5 (November 5, 2020): 131–44. http://dx.doi.org/10.37482/0536-1036-2020-5-131-144.
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In the Russian Federation logging operations are traditionally carried out in winter. This is due to the predominance of areas with swamped and water-logged (class III and IV) soils in the forest fund, where work of forestry equipment is difficult, and sometimes impossible in the warm season. The work of logging companies in the forests of the cryolithozone, characterized by a sharply continental climate, with severe frosts in winter, is hampered by the fact that forest machines are not recommended to operate at temperatures below –40 °C due to the high probability of breaking of metal structures and hydraulic system. At the same time, in the warm season, most of the cutting areas on cryosolic soils become difficult to pass for heavy forest machines. It turns out that the convenient period for logging in the forests of the cryolithozone is quite small. This results in the need of work in the so-called off-season period, when the air temperature becomes positive, and the thawing processes of the soil top layer begin. The same applies to the logging companies not operating in the conditions of cryosolic soils, for instance, in the Leningrad, Novgorod, Pskov, Vologda regions, etc. The observed climate warming has led to a significant reduction in the sustained period of winter logging. Frequent temperature transitions around 0 °C in winter, autumn and spring necessitate to work during the off-season too, while cutting areas thaw. In bad seasonal and climatic conditions, which primarily include off-season periods in general and permafrost in particular, it is very difficult to take into account in mathematical models features of soil freezing and thawing and their effect on the destruction nature. The article shows that the development of long-term predictive models of indicators of cyclic interaction between the skidding system and forest soil in adverse climatic conditions of off-season logging operations in order to improve their reliability requires rapid adjustment of the calculated parameters based on the actual experimental data at a given step of the cycles.
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Schlentner, Robert E., and Keith Van Cleve. "Relationships between CO2 evolution from soil, substrate temperature, and substrate moisture in four mature forest types in interior Alaska." Canadian Journal of Forest Research 15, no. 1 (February 1, 1985): 97–106. http://dx.doi.org/10.1139/x85-018.
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A soda lime technique was used to measure CO2 evolution at the soil surface in four mature forest types (aspen (Populustremuloides Michx.), paper birch (Betulapapyrifera Marsh.), black spruce (Piceamariana (Mill.) B.S.P.), and white spruce (Piceaglauca (Moeneh) Voss)) in interior Alaska. Surface temperature, 15-cm depth temperature, and soil moisture were measured concurrently with CO2 evolution. Accumulated CO2 evolution ranged from 1315 to 1654 g CO2•m−2 for the period May 1 – September 30 in 1981 and 1982 in the four stands. Data were used to develop three-dimensional response surfaces and test mathematical models of respiration in relation to substrate temperature and moisture. GRESP, a biologically based model, provided a fairly accurate simulation of the seasonal course of respiration as a function of substrate temperature and moisture. In an attempt to better define the observed response surface trends, a best-fit equation model, BRESP, was formulated. BRESP includes the moisture portion of the GRESP equation, and an altered temperature equation which more adequately defines the upper and lower thresholds of respiration in relation to substrate temperature. GRESP and BRESP each produced similar r2 values; however, higher order polynomial equations gave a better-fit model. The weakest area of all models for simulating seasonal trends was during the periods of peak respiration in June.
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Li, Cong, Yaonan Zhang, and Xupeng Ren. "Modeling Hourly Soil Temperature Using Deep BiLSTM Neural Network." Algorithms 13, no. 7 (July 17, 2020): 173. http://dx.doi.org/10.3390/a13070173.
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Soil temperature (ST) plays a key role in the processes and functions of almost all ecosystems, and is also an essential parameter for various applications such as agricultural production, geothermal development, and their utilization. Although numerous machine learning models have been used in the prediction of ST, and good results have been obtained, most of the current studies have focused on daily or monthly ST predictions, while hourly ST predictions are scarce. This paper presents a novel scheme for forecasting the hourly ST using weather forecast data. The method considers the hourly ST prediction to be the superposition of two parts, namely, the daily average ST prediction and the ST amplitude (the difference between the hourly ST and the daily average ST) prediction. According to the results of correlation analysis, we selected nine meteorological parameters and combined two temporal parameters as the input vectors for predicting the daily average ST. For the task of predicting the ST amplitude, seven meteorological parameters and one temporal parameter were selected as the inputs. Two submodels were constructed using a deep bidirectional long short-term memory network (BiLSTM). For the task of hourly ST prediction at five different soil depths at 30 sites, which are located in 5 common climates in the United States, the results showed the method proposed in this paper performs best at all depths for 30 stations (100% of all) for the root mean square error (RMSE), 27 stations (90% of all) for the mean absolute error (MAE), and 30 stations (100% of all) for the coefficient of determination (R2), respectively. Moreover, the method adopted in this study displays a stronger ST prediction ability than the traditional methods under all climate types involved in the experiment, the hourly ST produced by it can be used as a driving parameter for high-resolution biogeochemical models, land surface models and hydrological models and can provide ideas for an analysis of other time series data.
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Zhang, Haijing, Xiang Zhang, Yao Yin, Gaojie Liu, Yu Zhu, Xuejun Tan, and Yuan Huang. "Comparison of Three Energy-Saving Strategies Based on Models Established for In Situ Gas Thermal Remediation of Contaminated Soil." Geofluids 2022 (January 17, 2022): 1–12. http://dx.doi.org/10.1155/2022/5447682.
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Soil pollution has become an issue of concern with the development of industrialization. In situ gas thermal remediation is a suitable remediation technology for heavily organic contaminated soil, yet its high energy consumption limits the application. In this study, three energy-saving strategies, off-gas burn-back mode, heat-returning mode, and air-preheating mode, were proposed, and their natural gas consumption and energy utilization ratio were analysed. A mathematical model was established for the heat and mass transfer in unsaturated soil by employing conjugate heat transfer. The temperature of the soil and flue gas, and the concentration of components in the soil and off-gas were simulated, which indicated the thermal behavior of the contaminated soil and the timing for operation control. Models of burners were also developed under different energy-saving modes for energy analysis. By comparing the basic method, adopting the off-gas burn-back mode obtained an energy-saving effect of 3.37%, which relied on the content and calorific value of the pollutant in the off-gas. Under combustion air-preheating ratios of 0.5 and 1.0, natural gas could only be saved by 13.56% and 18.88%, respectively. In general, the most effective energy-saving measure was the heat-returning mode, by which 21.44% of natural gas could be saved when the reflux ratio of the flue gas was 0.5.
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Krams, M., and A. Ziverts. "Experiments of Conceptual Mathematical Groundwater Dynamics and Runoff Modelling in Latvia." Hydrology Research 24, no. 4 (August 1, 1993): 243–62. http://dx.doi.org/10.2166/nh.1993.0006.
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A mathematical model METUL for estimating the daily groundwater level and drainage, surface and subsurface runoff in small areas is described. Input data for the model are daily mean values of air temperature, precipitation and vapour pressure deficit, as well as the occurrence and disappearance of snow cover. Questions about the determination of the model's parameters are discussed, and the results of the model's application to experimental areas in two drainages are analyzed. The model's usefulness in objectively determining the soil water regime of small areas after only short-term groundwater level observations is shown.
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Xie, Hua W., Adriana L. Romero-Olivares, Michele Guindani, and Steven D. Allison. "A Bayesian approach to evaluation of soil biogeochemical models." Biogeosciences 17, no. 15 (August 10, 2020): 4043–57. http://dx.doi.org/10.5194/bg-17-4043-2020.
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Abstract. To make predictions about the carbon cycling consequences of rising global surface temperatures, Earth system scientists rely on mathematical soil biogeochemical models (SBMs). However, it is not clear which models have better predictive accuracy, and a rigorous quantitative approach for comparing and validating the predictions has yet to be established. In this study, we present a Bayesian approach to SBM comparison that can be incorporated into a statistical model selection framework. We compared the fits of linear and nonlinear SBMs to soil respiration data compiled in a recent meta-analysis of soil warming field experiments. Fit quality was quantified using Bayesian goodness-of-fit metrics, including the widely applicable information criterion (WAIC) and leave-one-out cross validation (LOO). We found that the linear model generally outperformed the nonlinear model at fitting the meta-analysis data set. Both WAIC and LOO computed higher overfitting risk and effective numbers of parameters for the nonlinear model compared to the linear model, conditional on the data set. Goodness of fit for both models generally improved when they were initialized with lower and more realistic steady-state soil organic carbon densities. Still, testing whether linear models offer definitively superior predictive performance over nonlinear models on a global scale will require comparisons with additional site-specific data sets of suitable size and dimensionality. Such comparisons can build upon the approach defined in this study to make more rigorous statistical determinations about model accuracy while leveraging emerging data sets, such as those from long-term ecological research experiments.
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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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Prakash, Bhagwati, and Terry J. Siebenmorgen. "Mathematical Modeling of a Cross-Flow Rice Dryer with Grain Inverters." Transactions of the ASABE 61, no. 5 (2018): 1757–65. http://dx.doi.org/10.13031/trans.12927.
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Abstract. Industrial-scale cross-flow dryers are commonly equipped with grain inverters to improve the uniformity of drying across the column thickness. While a few mathematical models have been reported that include the operation of grain inverters, such models were rarely validated with experiments comprising grain inversions. In this study, a mathematical model was developed to evaluate the impact of grain inverters on the uniformity of grain moisture content (MC) across the column in cross-flow dryers. To improve the accuracy of model predictions, the impact of using two thin-layer drying equations, the Newton and modified Page equations, in the model was also investigated. An experimental setup was fabricated to simulate grain inversion, and drying experiments were performed to measure rice MC and air temperature across the column thickness, which were then compared with model-predicted values. When the modified Page equation was used in the model, the model predictions matched the experimental observations more closely than when using the Newton equation. The model successfully predicted grain and air properties when 0, 1, and 2 grain inversions were used; the root mean square error between predicted and measured values of rice MC and air temperature were within 0.1 to 0.2 percentage points and 1°C to 4°C, respectively. Grain inversions were shown to improve the uniformity of drying in rice kernels; in the tested drying conditions, a single grain inversion produced more uniform drying than two or more grain inversions in the column. The presented results demonstrate the usefulness of the developed model in investigating the role of grain inversion in cross-flow drying of rice. As such, the model could be readily used to improve dryer design, particularly the number and arrangement of grain inverters, and optimize rice drying operations. Keywords: Deep-bed drying, Grain inverters, Mathematical modeling, Reversed airflow, Thin-layer drying.
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Zhang, Shu, and Mao Yu Zheng. "Sustainability Study on GCHP Heating System in Severe Cold Area of China." Applied Mechanics and Materials 411-414 (September 2013): 3084–87. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.3084.
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In this paper, the mathematical models of a GCHP system and a Ground-couple heat pump system with air-soil thermal storage (GCHPASTS) were developed, and the 20-year performances of the two systems were simulated in severe cold area of china, respectively. The results show that the soil temperature declines gradually during the operation of a GCHP system, which leads to the decrease of the coefficient of performance (COP) and the heating effect of the heat pump year after year. On the contrary, the balance of ground thermal load can be realized during the operation of a GCHPASTS system, and the heating performance of heat pump is stable and efficient for long time. So, it can be proved that a GCHP system cant be used for heating alone, while a GCHPASTS system is feasibility.
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Yang, Jun, Zhenguo Yan, Zhengwei Zhang, and Shu Zeng. "Analytical solution and process analysis of energy pile’s heat transfer rate." E3S Web of Conferences 205 (2020): 05026. http://dx.doi.org/10.1051/e3sconf/202020505026.
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With the ever-increasing energy demand and implications of climate change, the use of energy piles to absorb shallow geothermal energy to regulate room temperature of buildings is considered the best sustainable energy technology, especially in China, and the use of this technology is becoming increasingly popular. At present, studies generally uses the temperature field to analyze the heat transfer performance of the energy pile, which cannot represent the heat transfer rate distribution intuitively. In this study, we used mathematical models to provide an analytical solution to determine the heat transfer rate distribution between the energy pile and surrounding soil. Analysis of the heat transfer process of concrete piles in clay showed that the difference in thermal properties between the energy pile and the surrounding soil affected the whole heat transfer process, especially in the initial stage. The time required to reach the quasi-steady state mainly depended on the pile’s volume heat capacity, the thermal diffusivity of the pile and the surrounding soil. In engineering practice, to enhance the heat transfer performance of energy piles, the following measures can be taken: reduce the difference in thermal properties between the energy pile and surrounding soil and increase the distance between energy piles to improve the heat transfer conditions.
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Mao, Qian Jun. "Transfer Heat Mechanism of Oil-Gas-Water Three-Phase Flow in Pipeline." Advanced Materials Research 199-200 (February 2011): 1609–12. http://dx.doi.org/10.4028/www.scientific.net/amr.199-200.1609.
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It is well known that the oil-gas-water three-phase flow belongs to the field of multiphase flow,transfer heat mechanism of which is very complicated.Transfer heat mechanism is affected not only by different buries in oil gathering pipeline, but also by soil temperature periodicity change. Both domestic and oversea scholars have already studied on the transfer heat mechanisms of oil-gas-water three phase,but they are still in the level of fundamental theory and laboratory.This paper establishes transfer heat models of the oil-gas-water three-phase flow in buried oil gathering pipeline, including the physical model and the mathematical model,and testing in experiment .The purpose of this paper is to analyze value between the calculation and the testing . The results show that the mathematical model of this paper is accurate , and the relative error is ≤ 10%.
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TALAMUCCI, F. "FREEZING PROCESSES IN SATURATED SOILS." Mathematical Models and Methods in Applied Sciences 08, no. 01 (February 1998): 107–38. http://dx.doi.org/10.1142/s0218202598000068.
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When a soil saturated with water is subject to freezing, a volume expansion can generally be observed. The increase in volume is due not only to the different densities of water and ice, but mainly to a water migration process that is transported from the base of the soil up to an intermediate region where the change of phase occurs. It is generally accepted that a transition region, called frozen fringe, where ice and water coexist in the porous space, separates the unfrozen from the frozen part of the soil. Immediately over the frozen fringe a pure segregated layer of ice (ice lens) can form. If the freezing process is too fast or the weight acting on the soil (overburden pressure) is relevant, the porous matrix does not separate and the shifting of the frozen fringe towards the base of the soil (frost penetration) is observed. Many mathematical models have been proposed for the frost heave process. The main features of the one-dimensional model we are considering are summarized in Sec. 1. In Ref. 9 the case of assignment of the boundary thermal fluxes (at the base and on top of the soil) is studied. In practical cases, sometime the boundary temperatures, instead of the thermal fluxes, can be registered or imposed: in this paper we will investigate the model in such case. The main purpose is to detect which are the boundary values for temperature that determine the process of lens formation or frost penetration, once the properties of the soil are known.
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Sunmonu, Musliu Olushola. "Prediction and Determination of Weight and Lycopene Contents of Stored Tomatoes (Lycopersicon esculentum)." International Journal of Engineering Research in Africa 15 (April 2015): 141–49. http://dx.doi.org/10.4028/www.scientific.net/jera.15.141.
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The need to develop empirical model equations that describe the changes in the nutritional compositions of stored tomatoes under different environmental conditionsA study was carried out to predict and determine the weight and lycopene contents of stored tomatoes. Three sets of four different types of passive evaporative cooling structures made of clay and aluminium were designed and constructed as part of the study. One set consists of four separate cooling chambers. Two cooling chambers were made with aluminium container (cylindrical and square shapes) and the other two were made of clay container (cylindrical and square). These four containers were separately inserted inside a bigger clay pot inter-spaced with clay soil of 5 cm (to form tin-in-pot, pot-in-pot, tin-in-wall and wall-in wall) with the outside structure wrapped with jute sack. The other two sets followed the same pattern with interspacing of 7 cm and 10 cm, respectively. The set with 7 cm interspace served as the control in which the interspace soil and the jute sacks were constantly wetted at intervals of between 2 to 4 hours depending on the rate of evaporation with water at room temperature. The 5 cm and 10 cm interspaced soil were constantly wetted with salt solution (sodium chloride) at the same interval to keep the soil in moist condition. Freshly harvested matured tomatoes (globe variety) were used for the experiments and the temperature and relative humidity inside the cooling chambers were monitored daily . The weight, lycopene contents, bacterial and fungal counts of these produce were determined at intervals of three days for a period of sixteen days. Mathematical models (using essential regression software package) were developed to predict the weight and lycopene contents of the stored produce at various conditions considered in the study. By substituting different values of predictor variables into the model equations, the expected values of weight and lycopene contents of stored tomatoes were predicted. Further analysis was done using a paired sample t-test using SPSS 16.0 computer software package to show the level of significance between the mean of observed and the predicted values for all the models developed. The mathematical models developed are reasonably accurate to predict the storability of fruits and vegetables in passive evaporative cooling structures.
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Barone, F. S., E. K. Yanful, R. M. Quigley, and R. K. Rowe. "Effect of multiple contaminant migration on diffusion and adsorption of some domestic waste contaminants in a natural clayey soil." Canadian Geotechnical Journal 26, no. 2 (May 1, 1989): 189–98. http://dx.doi.org/10.1139/t89-028.
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This paper describes laboratory model tests involving the placement of domestic landfill leachate on top of a layer of saturated undisturbed clayey soil and allowing chemical constituents to migrate into the soil by diffusion only. During the testing period (15 days), samples from the overlying leachate were regularly collected and analyzed for the chemical constituents of interest (i.e., Cl−, Na+, K+, Mg++, and Ca++). At the end of the test, the soil layer was sectioned to determine the pore-water and adsorbed concentration variations with depth for each species. Mathematical model POLLUTE was then used to back-figure both the diffusion coefficient (D) and the adsorption term (ρK). The measured diffusion coefficients at a temperature of 10 °C were determined to be [Formula: see text], [Formula: see text], and [Formula: see text]. The corresponding adsorption terms were [Formula: see text], [Formula: see text], and [Formula: see text].Ca++ and Mg++, originally predominant on the clay exchange sites, were heavily desorbed to accommodate the adsorption of migrating Na+, K+, and possibly NH4+, causing hardness halo effects that the model could not fit. This behaviour corresponds to that commonly observed at domestic waste sites in southern Ontario.The importance of multiple contaminant migration on diffusion rates was assessed by comparing the leachate models with similar models using a variety of single salts dissolved in distilled water as the source solutions. For the single-salt models, all species considered, including Ca++ and Mg++, behaved in a way that could be described by conventional Fickian theory. A comparison of the diffusion and adsorption parameters obtained from the two types of models indicated that for both Na+ and K+, the measured D and ρK from the leachate models were 20 and 60% lower, respectively, than the values obtained from the single-salt models. For Cl−, the diffusion coefficient obtained from the leachate models was 25% higher than that obtained from the single-salt models.For the Sarnia grey soil used, both D and ρK are significantly influenced by the types and amounts of co-diffusing species present in the initial source solutions. Laboratory tests conducted to determine diffusion parameters for use in design should be run with soils and source solutions chemically identical to those expected in the field. Key words: domestic waste leachate, multiple contaminant migration, clayey soil, diffusion, adsorption, laboratory study.
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Shesteperov, A. A., and E. A. Lukyanova. "Foundations and methods of modeling of projected growth potato globoderosis on agrometeorological conditions." Russian Journal of Parasitology 12, no. 2 (June 28, 2018): 95–103. http://dx.doi.org/10.31016/1998-8435-2018-12-2-95-103.
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The purpose of the research: to develop verbal, analogous, mathematical models of projected growth of potato globoderosis depending on agrometeorological conditions. Materials and methods. Analysis of national and foreign literature regarding epiphytotiology, modeling was performed, as well as available literature data and personal supervision about influence of meteorological conditions on the potato globoderosis development were generalized. A database received in Kondrovo of Kaluga Region was used in order to develop verbal, analogous, mathematical model. One experimental field was chosen out of 40 experimental fields and plots of land where Sineglazka vulnerable variety was grown during 1979-1993. On the field with average soil quality the population density of nematodes varied from 14,900 to 27,300 (average 20,600) ovicells and larvas at the 100 cubic cm of soil. Globoderosis development was evaluated according to the scale for at-ground visual appraisal of defeat potato plants by globoderosis in points annually in July. Phenological, phytosanitary and phytohelminthological metering and supervision at the experimental field were conducted during vegetational season. Correlation and regression analysis of collected material was conducted using software application Microsoft Excel. Results and discussion. Сorrelation coefficient for meteorological factors closely related to globoderosis development over 15 years were calculated with the help of correlation analysis. Predictors (average daily temperature, quantity and amount of rainfall) for short period forecast of globoderosis development while planting of potatoes with average level of fertility were determined. As the result of regression analysis mathematic models of projected growth globoderosis depending on agrometeorological factors were received. Confidence of a mathematical model, i.e. differences of expectancy record from retrospective average 3.6%. Correspondence of mathematic model was checked by historical data using correlation coefficient between the result of projected growth globoderosis and measurement data. It is 0.83. Accuracy of forecast varied from -36.8 to 36.5%.
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Prakash, Bhagwati, Sangeeta Mukhopadhyay, and Terry J. Siebenmorgen. "Mathematical Modeling of a Cross-Flow Rice Dryer." Transactions of the ASABE 60, no. 3 (2017): 999–1009. http://dx.doi.org/10.13031/trans.12155.
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Abstract. Cross-flow dryers are the most popular industrial-scale rice dryers used in the U.S., yet few mathematical models have been developed and rigorously validated for such dryers. In addition, the glass transition states of rice kernels have never been predicted using a deep-bed drying model. In this study, a mathematical model was developed that describes the distribution of grain and air properties throughout a cross-flow dryer column. The model was validated by performing experiments in a lab dryer that was fabricated to simulate cross-flow drying. The model predictions of grain and air properties were observed to be very close to the measured values in the drying experiments; the root mean square error between the predicted and measured values of rice MC, air temperature, and air RH were less than one percentage point, 5°C, and ten percentage points, respectively. The model was then used to predict the glass transition state of starch present in rice kernels throughout the dryer column. The impact of initial MC on the glass transition states of rice kernels during cross-flow drying was also illustrated. Such predictions of rice kernel material states allow the model to be used for rice fissuring research. Additionally, the model could be applied to optimize drying operation parameters as well as improve dryer design, so as to achieve greater drying capacity, milling quality, and energy efficiency in a commercial drying operation. Keywords: Cross-flow drying, Glass transition, Mathematical model, Rice drying.
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Koven, C. D., E. A. G. Schuur, C. Schädel, T. J. Bohn, E. J. Burke, G. Chen, X. Chen, et al. "A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 373, no. 2054 (November 13, 2015): 20140423. http://dx.doi.org/10.1098/rsta.2014.0423.
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We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change ( γ sensitivity) of −14 to −19 Pg C °C −1 on a 100 year time scale. For CH 4 emissions, our approach assumes a fixed saturated area and that increases in CH 4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH 4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.
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Lima, Elizeu de Souza, Zigomar Menezes de Souza, Rafael Montanari, Stanley Robson de Medeiros Oliveira, Lenon Henrique Lovera, and Camila Viana Vieira Farhate. "CLASSIFICATION OF THE INITIAL DEVELOPMENT OF EUCALIPTUS USING DATA MINING TECHNIQUES." CERNE 23, no. 2 (June 2017): 201–8. http://dx.doi.org/10.1590/01047760201723022296.
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ABSTRACT Eucalyptus plantation has expanded considerably in Brazil, especially in regions where soils have low fertility, such as in Brazilian Cerrados. To achieve greater productivity, it is essential to know the needs of the soil and the right moment to correct it. Mathematical and computational models have been used as a promising alternative to help in this decision-making process. The aim of this study was to model the influence of climate and physico-chemical attributes in the development of Eucalyptus urograndis in Entisol quartzipsamment soil using the decision tree induction technique. To do so, we used 30 attributes, 29 of them are predictive and one is the target-attribute or response variable regarding the height of the eucalyptus. We defined four approaches to select these features: no selection, Correlation-based Feature Selection (CFS), Chi-square test (χ2) and Wrapper. To classify the data, we used the decision tree induction technique available in the Weka software 3.6. This data mining technique allowed us to create a classification model for the initial development of eucalyptus. From this model, one can predict new cases in different production classes, in which the individual wood volume (IWV) and the diameter at breast height (DBH) are crucial features to predict the growth of Eucalyptus urograndis, in addition to the presence of chemical soil components such as: magnesium (Mg+2), phosphorus (P), aluminum (Al+3), potassium (K+), potential acidity (H + Al), hydrogen potential (pH), and physical attributes such as soil resistance to penetration and related to climate, such as minimum temperature.
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Bragov, Anatoly, Sergey Isaev, Sergey Kapustin, Alexander Konstantinov, and Andrey Lomunov. "Creation of database for strength calculation of constructions." EPJ Web of Conferences 183 (2018): 01024. http://dx.doi.org/10.1051/epjconf/201818301024.
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The problems of creation of an automated system for obtaining, processing and storing experimental information on the physical and mechanical properties of structural materials, building materials and various soil media used to provide information support for automated computing systems for analysis of strength and design of structures are discussed. The developed database is focused on studying the effects of the behavior of structural materials under highly parametric influences of force, temperature and other physical fields, as well as on equipping and experimental substantiation of mathematical models describing these effects. In the proposed variant, the database is implemented as a client-server application executed on the Microsoft.Net Framework using a powerful database management system MS SQL Server. The content of the created bank is made up of sections of primary information, material properties and material models. In order to automate the processing of data at all stages of information conversion, a special “Desktop” subsystem is included in the bank, which allows aggregating data obtained from several different experiments, correcting the selected data, processing and converting it. Processing and transformation of data in the subsystem “Desktop” can be carried out either in manual mode or on the basis of special algorithms using appropriate mathematical methods.
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Barneze, Arlete S., Mohamed Abdalla, Jeanette Whitaker, Niall P. McNamara, and Nicholas J. Ostle. "Predicted Soil Greenhouse Gas Emissions from Climate × Management Interactions in Temperate Grassland." Agronomy 12, no. 12 (December 2, 2022): 3055. http://dx.doi.org/10.3390/agronomy12123055.
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Grassland management practices and their interactions with climatic variables have significant impacts on soil greenhouse gas (GHG) emissions. Mathematical models can be used to simulate the impacts of management and potential changes in climate beyond the temporal extent of short-term field experiments. In this study, field measurements of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) emissions from grassland soils were used to test and validate the DNDC (DeNitrification-DeComposition) model. The model was then applied to predict changes in GHG emissions due to interactions between climate warming and grassland management in a 30-year simulation. Sensitivity analysis showed that the DNDC model was susceptible to changes in temperature, rainfall, soil carbon and N-fertiliser rate for predicting N2O and CO2 emissions, but not for net CH4 emissions. Validation of the model suggests that N2O emissions were well described by N-fertilised treatments (relative variation of 2%), while non-fertilised treatments showed higher variations between measured and simulated values (relative variation of 26%). CO2 emissions (plant and soil respiration) were well described by the model prior to hay meadow cutting but afterwards measured emissions were higher than those simulated. Emissions of CH4 were on average negative and largely negligible for both simulated and measured values. Long-term scenario projections suggest that net GHG emissions would increase over time under all treatments and interactions. Overall, this study confirms that GHG emissions from intensively managed, fertilised grasslands are at greater risk of being amplified through climate warming, and represent a greater risk of climate feedbacks.
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Батюк, Л. В., and Н. М. Кізілова. "Monitoring system of biophysical properties of the red blood cells of patients for medical diagnosis purposes." Системи обробки інформації, no. 3(162), (September 30, 2020): 13–20. http://dx.doi.org/10.30748/soi.2020.162.02.
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Modern medical diagnostics is impossible without high-tech means of collecting information about the patient's condition, in particular, the biochemical properties of blood and other tissues, physiological signals in the format of time series, and medical images as well. Extensive use of automatic methods of information processing and decision-making based on mathematical models, expert systems, and artificial intelligence is an integral part of the tomorrow’s medicine. Such approaches significantly increase the accuracy of diagnosis and the effectiveness of the prescribed treatment, but this requires the availability of properly structured databases with the results of both successful / unsuccessful treatments, and a complete set of necessary analyses and tests for each patient. This paper discusses the most important components of such database and public health monitoring system. The main issues are the standardization of data format, approaches, methods and laboratory equipment used to unify monitoring, diagnosis and control over the treatment. The importance of using additional physical parameters of blood cells and tissues to increase the efficiency of medical diagnostics with artificial intelligence is shown. The sedimentation curves corresponding to stable normal, stable increased and unstable erythrocyte aggregation rate are given. It is shown that the time to reach the maximum cell sedimentation rate can be calculated on a 2-phase model of blood suspension, indicators of which could be accumulated in the database, which will allow the extraction of additional diagnostic information using novel statistical and mathematical methods. Typical dependences of erythrocyte dielectric constant curves on temperature for oncology patients are given. It is shown that storage in the database the values of dielectric permittivity of red blood cells measured at different temperature and frequencies of electromagnetic fields applied in the dielectrometer, provides significant material for a more detailed study of the patterns of development of various diseases and finding the most sensitive indices for their timely detection.
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Fraters, Menno, Cedric Thieulot, Arie van den Berg, and Wim Spakman. "The Geodynamic World Builder: a solution for complex initial conditions in numerical modeling." Solid Earth 10, no. 5 (October 29, 2019): 1785–807. http://dx.doi.org/10.5194/se-10-1785-2019.
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Abstract. The Geodynamic World Builder is an open-source code library intended to set up initial conditions for computational geodynamic models in both Cartesian and spherical geometries. The inputs for the JavaScript Object Notation (JSON)-style parameter file are not mathematical but rather a structured nested list describing tectonic features, e.g., a continental, an oceanic or a subducting plate. Each of these tectonic features can be assigned a specific temperature profile (e.g., plate model) or composition label (e.g., uniform). For each point in space, the Geodynamic World Builder can return the composition and/or temperature. It is written in C++ but can be used in almost any language through its C and Fortran wrappers. Various examples of 2-D and 3-D subduction settings are presented. The Geodynamic World Builder comes with an extensive online user manual.
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Robertson, Andy D., Keith Paustian, Stephen Ogle, Matthew D. Wallenstein, Emanuele Lugato, and M. Francesca Cotrufo. "Unifying soil organic matter formation and persistence frameworks: the MEMS model." Biogeosciences 16, no. 6 (March 25, 2019): 1225–48. http://dx.doi.org/10.5194/bg-16-1225-2019.
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Abstract. Soil organic matter (SOM) dynamics in ecosystem-scale biogeochemical models have traditionally been simulated as immeasurable fluxes between conceptually defined pools. This greatly limits how empirical data can be used to improve model performance and reduce the uncertainty associated with their predictions of carbon (C) cycling. Recent advances in our understanding of the biogeochemical processes that govern SOM formation and persistence demand a new mathematical model with a structure built around key mechanisms and biogeochemically relevant pools. Here, we present one approach that aims to address this need. Our new model (MEMS v1.0) is developed from the Microbial Efficiency-Matrix Stabilization framework, which emphasizes the importance of linking the chemistry of organic matter inputs with efficiency of microbial processing and ultimately with the soil mineral matrix, when studying SOM formation and stabilization. Building on this framework, MEMS v1.0 is also capable of simulating the concept of C saturation and represents decomposition processes and mechanisms of physico-chemical stabilization to define SOM formation into four primary fractions. After describing the model in detail, we optimize four key parameters identified through a variance-based sensitivity analysis. Optimization employed soil fractionation data from 154 sites with diverse environmental conditions, directly equating mineral-associated organic matter and particulate organic matter fractions with corresponding model pools. Finally, model performance was evaluated using total topsoil (0–20 cm) C data from 8192 forest and grassland sites across Europe. Despite the relative simplicity of the model, it was able to accurately capture general trends in soil C stocks across extensive gradients of temperature, precipitation, annual C inputs and soil texture. The novel approach that MEMS v1.0 takes to simulate SOM dynamics has the potential to improve our forecasts of how soils respond to management and environmental perturbation. Ensuring these forecasts are accurate is key to effectively informing policy that can address the sustainability of ecosystem services and help mitigate climate change.
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Čiegis, Raimondas, Gerda Jankevičiūtė, and Natalija Tumanov. "ON EFFICIENT NUMERICAL ALGORITHMS FOR SIMULATION OF HIGH POWER ELECTRICAL CABLES." Mathematical Modelling and Analysis 20, no. 6 (November 23, 2015): 701–14. http://dx.doi.org/10.3846/13926292.2015.1108250.
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The new virtual modelling tool is constructed, which is used for optimal design of power transmission lines and cables. The construction of such lines should meet the latest power transmission network technical and economical requirements. The solver is is based on classical and modified mathematical models describing main heat conduction processes: diffusion, convection and radiation in various materials and environments. In basic heat conduction equation, we take into account a linear dependence of the resistance on temperature. Multi-physic and multi-scale models are required to simulate industrial cases of power transmission lines. The velocity of convective transport of the heat in air regions is simulated by solving a coupled thermo-convection problem including the heat conduction problem and the standard Navier-Stokes model of the heat flow in air. Another multi-physic model is used to describe changes of material heat conduction coefficients in soil due to influence of heating. This process is described by by solving a simplified mass balance equation for flows in porous media. The multi-scale and homogenization analysis is required to to formulate simple and accurate mathematical describing heat conduction process is metal region which consists of a bundle of tightly coupled metal wires. The FVM is used to solve the obtained systems of differential equations. Discretization of the domain is done by applying “aCute” mesh generator, which is a modification of the well-known Triangle mesh generator. The discrete schemes are implemented by using the OpenFOAM tool.
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Zhang, Wenbing, Zhenzhong Shen, Jie Ren, Wanlin Zhang, Liqun Xu, and Guanyun Chen. "A Hydrothermal Coupling Model for Estimating Temperature Variations in the Riparian Zone." Mathematical Problems in Engineering 2020 (September 26, 2020): 1–12. http://dx.doi.org/10.1155/2020/3484109.
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In research using heat tracing technology to investigate the lateral hyporheic exchange in the shallow geological body of the riparian zone, the accurate estimation of temperature changes can provide a scientific basis for quantifying the process of lateral hyporheic exchange. To improve the accuracy of estimating temperature changes in the riparian zone, a hydrothermal coupling model considering parameter heterogeneity was established based on existing models of the relationship between thermal conductivity and saturation. The model was verified by temperature data from laboratory experiments, and the effect of the thermal conductivity prediction models was compared with that of the partial differential equation (PDE) modeling approach. The results show that the established hydrothermal coupling model can effectively characterize the temperature changes observed in a generalized laboratory model of the riparian zone, and the model simulation effects vary with the equivalent thermal conductivity models. In addition, several thermal conductivity empirical models are suggested for further application. The model parameter sensitivity analysis indicated that the hydraulic conductivity ks, VG model parameters (α and β) and heat capacity of soil Cs have a relatively large effect on the temperature output of the model. The results of this study will provide reference for the selection of equivalent thermal conductivity model for simulating temperature variations in the riparian zone.
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Kutumov, Yu D., V. E. Mizonov, A. I. Tikhonov, and T. Yu Shadrikova. "Development of digital twin model of underground electric cable: thermal part of the problem." Vestnik IGEU, no. 3 (June 30, 2021): 59–65. http://dx.doi.org/10.17588/2072-2672.2021.3.059-065.
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Innovative technologies of generative design using the concept of digital twins of the designed objects play an important role in growing digitalization trend of project activities. The digital twin of an object is the object simulation model with high accuracy of mathematical description. It is used to solve the problems of regime and structural optimization of the object. Usually, generative design technologies are implemented using 3D models of physical fields. And specialized packages which have high requirements for computer resources and user skills are used. At the same time, quite often the object for which the digital twin model is developed consists of several subsystems that allow relatively independent modeling. A one-dimensional model of the thermal process cannot provide the required accuracy, but a 2D-model is quite sufficient for this purpose. The development of such a model that combines the required accuracy, and low cost of machine time is currently topical scientific and practical problem. The method of mathematical modeling is used to solve this problem. The model uses the mathematical apparatus of the Markov chain theory. The model is two-dimensional and is adapted to the multi-layer environment representing the soil, in a separate cell of which a non-stationary heat source may be found. Heat passage through the surrounding soil is described in terms of thermal conductivity, and the heat exchange with the environment is described in terms of heat transfer. The influence of the parameters on the process flow is studied by numerical methods. At this stage of the study, experimental verification of the model is not expected. A mathematical two-dimensional model of digital twin of underground electric cable has been developed. It allows us to predict the cable temperature and its distribution in the surrounding soil. The assessment of thermal state of the power transmission line is given according to the power and the depth of the heat source location. It is found that the results of simulation modeling are consistent with the physical concepts of the process. The results obtained are of scientific novelty, since they are based on a universal modeling algorithm and allow us to describe the transients in the object under study, which is a part of the digital twin of the underground cable. The model is easy to use and requires little machine time. It can be easily used in generative design practice.
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Oliveira, Matias Marchesan de, Arlei Coldebella, Paulo Belli Filho, and Paulo Armando Victória de Oliveira. "Aeration frequency on accelerated composting of animal carcasses." Ciência e Agrotecnologia 42, no. 6 (December 2018): 653–65. http://dx.doi.org/10.1590/1413-70542018426021818.
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ABSTRACT Rotary drum reactors (RDRs) for accelerated carcass composting are being installed in animal production units as an alternative for the disposal of pig and poultry carcasses in Brazil. The aim of the present study was to investigate the influence of aeration frequency on gas emissions (CO2-C, CH4-C, NH3-N and N2O-N) during composting of pig and poultry carcasses in RDRs. RDRs with a volume of 3.6 m3 (50% useful volume) were used. Aeration time was 24 minutes. Four intervals between aeration periods were tested (treatments) as follows: 1 hour (T1), 2 hours (T2), 3 hours (T3) and 4 hours (T4). Gas emissions were continuously monitored using a photoacoustic gas monitor (INNOVA 1412). Temperature was monitored using iButtons mixed with the biomass. Mathematical models of CO2-C and NH3-N emissions relative to the observed biomass temperature were proposed. Biomass temperature was affected by the treatments. The highest aeration frequency had the shortest thermophilic phase (>50 °C). No significant differences in total gas emissions were observed between treatments (p>0.05). CO2-C and NH3-N emissions were better fitted by non-linear models (R2=0.75 and R2=0.78, respectively). A minimum 2-hour interval should be adopted between aeration periods of 24 minutes to guarantee a longer thermophilic phase and elimination of possible pathogenic contaminants.
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Funahashi, Fumiaki, and Jennifer L. Parke. "Thermal Inactivation of Inoculum of Two Phytophthora Species by Intermittent Versus Constant Heat." Phytopathology® 108, no. 7 (July 2018): 829–36. http://dx.doi.org/10.1094/phyto-06-17-0205-r.
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Research on solarization efficacy has examined the critical temperature and minimum exposure time to inactivate soilborne pathogens. Most mathematical models focus on survival of inoculum subjected to a constant heat regime rather than an intermittent heat regime that better simulates field conditions. To develop a more accurate predictive model, we conducted controlled lab experiments with rhododendron leaf disks infested with Phytophthora ramorum and P. pini. Focused in vitro experiments with P. ramorum showed significantly longer survival of inoculum exposed to intermittent versus constant heat, indicating that intermittent heat is less damaging. A similar trend was observed in soil. Damage was evaluated by comparing the reduction in subsequent survival time of inoculum subjected to different intensities of sublethal heat treatments. Inoculum exposure to continuous heat reflected an increasing rate of damage accumulation. Multiple sublethal heat events resulted in a constant rate of damage accumulation which allowed us to calculate total damage as the sum of damage from each heat event. A model including a correction for an intermittent heat regime significantly improved the prediction of thermal inactivation under a temperature regime that simulated field conditions.
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HAN, Z. W., X. MENG, M. LIN, Y. H. ZHANG, J. YANG, and Y. R. WANG. "SIMULATION ON OPERATION CHARACTERISTICS OF HYBRID GROUND-AIR SOURCE HEAT PUMP SYSTEM WITH NATURAL COLD STORAGE." International Journal of Air-Conditioning and Refrigeration 22, no. 02 (April 29, 2014): 1440004. http://dx.doi.org/10.1142/s2010132514400045.
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To solve the problem of the coefficient of performance (COP) decrease and power crunch in cooling dominated South China associated with the long-term usage of ground-source heat pump system (GSHPS), a hybrid ground-air source heat pump system (HGASHPS) with natural cold storage is presented in this paper. The system consists of a GSHP system and compound air-cooled chillers (CACC), which can be operated according to the vapor compression refrigeration cycle or separate type heat pipe natural cycle. The mathematical models of each part of the system were set up and the conversion conditions between operation modes for the system were determined. The transient simulation for HGASHPS with natural cold storage in Nanjing was carried out. The operation characteristics of the systems in operational life were comparatively analyzed. The simulation results indicated that the HGASHPS with natural cold storage could retain the thermal balance of soil temperature field in one year cycle and increase the COP and reliability of the system.
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Grenfell, B. T., G. Smith, and R. M. Anderson. "Maximum-likelihood estimates of the mortality and migration rates of the infective larvae of Ostertagia ostertagi and Cooperia oncophora." Parasitology 92, no. 3 (June 1986): 643–52. http://dx.doi.org/10.1017/s0031182000065501.
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SUMMARYWe present an analysis of the survival and migration rates of the infective (L3) stages of Oslertagia ostertagi and Cooperia oncophora. Although the majority of laboratory studies show that the survival of the L3 stage depends upon temperature, moisture and the age of the larvae, a simple mathematical model of larval demography, in which their mortality and migration rates are held constant, provides as good agreement between observed and predicted larval counts as models in which these rate processes are made explicit functions of larval age and microclimate. Maximum-likelihood estimates of larval mortality rates in the faeces and on the herbage are 0·0284/day and 0·00887/day respectively. The average migration rate from faeces to herbage under temperate Northern European conditions is estimated as 0·00884/day. Finally, we discuss the probable scale of L3 larval losses due to desiccation and lavage (active or passsive migration into the soil).