Relevant bibliographies by topics / Research, Industrial – Mathematical models

Academic literature on the topic 'Research, Industrial – Mathematical models'

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Published: 10 March 2023

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Journal articles on the topic "Research, Industrial – Mathematical models"

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Turlakova, Svitlana. "Research of mathematical methods and models of long-term industrial development." Economy of Industry 4, no. 100 (December 1, 2022): 53–77. http://dx.doi.org/10.15407/econindustry2022.04.053.

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The importance of the study of relevant mathematical methods and models of long-term development of the national industry is substantiated. It has been proven that causal econometric models of production are relatively simple and convenient to use in practice, as well as the most common tools for researching the long-term economic future. It was defined that the production functions, adapted to individual circumstances, proved their ability to solve the assigned tasks. However, the problem of more accurate adjustment to the features of the simulated object of research is particularly relevant in the current conditions of development of Ukraine, in the conditions of concentration of attention on certain sectors, on particular branch of industry, and in connection with the revolutionary transformations of production forces and relations, in accordance with the spread of cyber-physical technologies of the Fourth Industrial revolution.In such specific circumstances, it makes sense to ask for more sophisticated models. On the one hand, they are better, as they allow more accurate tuning of the modeled object, including by adding important factors that are outside the production system. On the other hand, they are worse because they complicate the analysis and significantly increase the number of variables needed to describe the dynamics of economic growth. In this connection, expert research methods cannot be neglected. Choosing the type of model, the range of influencing factors, possible development scenarios, etc., usually requires expert assessments (often implicit). Therefore, when analyzing long-term factors and development trends, it is important to adhere to the main methodological message of expert approaches in the construction of foresights: for long time horizons in conditions of significant uncertainty, it is appropriate to ask questions not about the calculation of the "correct future", but about the assessment of the spectrum of probable scenarios of development, expansion and rethinking its new opportunities and challenges, in particular – to avoid potentially harmful ideas and expectations, embedded in the current policy.
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Alieva, N. "Economic and Mathematical Modeling of the Innovation Process in the Agro-Industrial Sector." Economic Herald of the Donbas, no. 4 (66) (2021): 29–32. http://dx.doi.org/10.12958/1817-3772-2021-4(66)-29-32.

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Modern scientific research in the field of agriculture is increasingly based on various mathematical calculations. In practice, it is the economic and mathematical models that are of particular importance. These methods and approaches are particularly valuable and widespread in the production environment, but in the modern conditions of production and economic activity, more and more industrial economic entities are faced with the application of mathematical models in order to improve the efficiency of investment resource management.
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Aliyeva, Nailya Rauf kyzy. "Economic and Mathematical Modeling of the Innovation Process in the Agro-Industrial Sector." Economic Herald of the Donbas, no. 2 (64) (2021): 118–22. http://dx.doi.org/10.12958/1817-3772-2021-2(64)-118-122.

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Modern scientific research in the agro-industrial sphere is increasingly based on various mathematical calculations. In practice, it is economic and mathematical models that are of particular importance. These methods and approaches have gained particular value and distribution in the production environment, but in modern conditions of production and economic activity, more and more sectoral economic entities are faced with the application of mathematical models in order to improve the efficiency of investment resource management.
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Zhao, Yu Qing, and Zhi Yong Li. "Evaporation Tower Heat and Mass Transfer Research in Saline Water Evaporation System." Advanced Materials Research 838-841 (November 2013): 1923–27. http://dx.doi.org/10.4028/www.scientific.net/amr.838-841.1923.

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In order to recycle the salt in industrial waste water, non-filler evaporation tower is used to evaporate and concentrate saline water. Based on the heat and mass transfer theory, developed a mathematical model of evaporation tower. Experiment results showed that difference of the export air dry bulb temperature values between models calculated and tested is within 5%. It is proves the correctness of the mathematical model.
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Cong, Jing. "Research on the Factors Affecting Carbon Emissions Based on Multivariate Regression Models." Scientific and Social Research 4, no. 3 (March 16, 2022): 102–7. http://dx.doi.org/10.26689/ssr.v4i3.3664.

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Carbon peak and carbon neutrality are two new terms that are being mentioned more frequently, and the measurement of carbon emissions has become an important research topic. Based on relevant data, this paper studies the relationship and evolution law of the driving factors of carbon emissions from energy structure and industrial structure as well as the result factors of carbon emissions from energy consumption, and then establishes corresponding mathematical models. The driving factors, result factors, and relationship attributes that are difficult to measure in the carbon emissions from energy structure and industrial structure are analyzed to fathom the evolution law of carbon emissions and absorption. Based on the results, phased and global suggestions for carbon neutrality have been suggested, taking into account the characteristics of different industries and regions.
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Mehta, U., R. Prasad, and K. Kothari. "VARIOUS ANALYTICAL MODELS FOR SUPERCAPACITORS: A MATHEMATICAL STUDY." Resource-Efficient Technologies, no. 1 (May 9, 2020): 1–15. http://dx.doi.org/10.18799/24056537/2020/1/218.

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Supercapacitors (SCs) are used extensively in high-power potential energy applications like renewable energy systems, electric vehicles, power electronics, and many other industrial applications. This is due to SCs containing high-power density and the ability to respond spontaneously with fast charging and discharging demands. Advancements in material and fabrication techniques have induced a scope for research to improve the application of SCs. Many researchers have studied various SC properties and their effects on energy storage and management performance. In this paper, various fractional calculus-based SC models are summarized, with emphasis on analytical studies from derived classical SC models. Study prevails such parameterized resistor–capacitor networks have simplified the representation of electrical behavior of SCs to deal with the complicated internal structure. Fractional calculus has been used to develop SC models with the aim of understanding their complicated structure. Finally, the properties of different SC models utilized by various researchers to understand the behavior of SCs are listed using an equivalent circuit.
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Fechete, Flavia, and Anișor Nedelcu. "Modeling the Economic Performance of Industrial Systems Using Mathematical Programming." Applied Mechanics and Materials 809-810 (November 2015): 1553–58. http://dx.doi.org/10.4028/www.scientific.net/amm.809-810.1553.

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Mathematical programming models and especially their subclass - linear programming models - plays an extremely important role, both in theory and in economic practice. Linear programming, through its results, brought a considerable contribution to improving management methods in economics and it has boosted theoretical research in modeling complex economic systems, study and interpretation of laws and economic processes. Developing and designing a model for achieving the economic performance of the industrial system allows managers making optimal decision and ensures the improvement of their activity. This paper aim is to determine an optimal manufacturing program for an industrial system, so that, by its implementation, to achieve economic performance. The manufacturing program conducted using a computer software will allow this entity to optimize their management decision process by providing information related to physical production that must be executed on each of their the products, or about the unused or overloaded capacity, in order to maximize their profits.
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Polozhaenko, Serhii, Fedir Garaschenko, and Ludmila Prokofieva. "Mathematical Models of Technological Processes of Oil Refining and Their Qualitative Analysis Based on the General Concept Of Models." Mathematical and computer modelling. Series: Technical sciences 23 (December 6, 2022): 107–15. http://dx.doi.org/10.32626/2308-5916.2022-23.107-115.

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Theorems of existence and uniqueness of the decision of system of the equations in the private derivatives, representing the generalized mathematical model of processes and devices of preprocessing of crude hydrocarbons are formulated and proved. Generalization gives the chance to apply the principle of unification and typification when de-veloping a method of numerical realization of mathematical models of a class of processes (devices) of preprocessing of crude hydrocarbons, and the proof of the corresponding theorems (an essence —the qua-litative analysis) provides a correctness of application of the generalized model in applied problems of mathematical modeling of studied pro-cesses (devices). Proofs of the formulated theorems are strict, logically true and are consistently executed within terms of the functional ana-lysis. Practical applicability of theorems of existence and uniqueness of the decision as component of the qualitative analysis, is defined by pos-sibility of research on their basis of adequacy of algorithmic means of mathematical modeling of a studied class of processes (devices).
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Kostyuchenko, Mikhail, Volodymyr Gogo, Boris Kobilyansky, Oleg Kruzhilko, Ihor Yefremov, Kyrylo Hriadushchyi, and Oleksandr Tkachuk. "ANALYSIS OF PRODUCTION RISK ON EXAMPLES OF MINERS ‘LABOR." JOURNAL of Donetsk Mining Institute, no. 2 (2021): 159–75. http://dx.doi.org/10.31474/1999-981x-2021-2-159-175.

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Objective: Based on the review of the array of publications to analyze the methods and models of general risk assessment, the nature of industrial risks and management processes on the examples of labor of coal miners. Propose a classification of mathematical models of industrial risk and identify the most appropriate model for the work of miners in the stochastic system “man-machine-environment”. Methodology: Applied to the use of situational analysis, qualimetry, probability theory and risk theory, methods of classification of occupational risks. Results: Based on a systematic analysis of multifactorial risks of emergency situations, the essence of industrial risks and management processes on the examples of coal miners, the dominant causes of industrial risk in the ergatic system (“man – machine – environment”), models and methods of risk research. Scientific novelty: For the first time on the basis of the analysis of the reasons, dynamics and consequences of industrial risks the classification of mathematical models of risks which are adapted to ergatic systems of mine production is offered. Practical value: The need for adequate practical application of risk methods and models for the assessment and measurement of industrial hazards has been proven.
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Hvozd, Viktor, Eugene Tishchenko, Andriy Berezovskyi, and Stanislav Sidnei. "Research of Fire Resistance of Elements of Steel Frames of Industrial Buildings." Materials Science Forum 1038 (July 13, 2021): 506–13. http://dx.doi.org/10.4028/www.scientific.net/msf.1038.506.

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The article considers and analyses the methods by which it is possible to carry out research to determine the fire resistance of elements of steel frames of industrial buildings. It is determined that it is expedient to use the means of computational fluid dynamics, which has no limitations due to the high cost, complexity, environmental friendliness and complexity in comparison with real experiments. In order to conduct the most reliable computational experiments, mathematical models of temperature and mechanical reaction to the thermal effect of fire were created, taking into account the equations of thermal conductivity, systems of differential equations of stress-strain state of solids in their numerical implementation based on the finite element method. The solution of mathematical models was carried out using computational fluid dynamics, which describes the process of heat and mass transfer in test fire furnaces during the determination of fire resistance of steel structures. According to the results of computational experiments it is shown that the limiting state of loss of bearing capacity of vertical and horizontal structures occurs due to the formation of a zone of plastic deformations taking into account the associative theory of plasticity. According to the results of computational experiments, the dependence of the limit of fire resistance on the level of applied load to structures, which is close to linear, was revealed. Based on the obtained dependences and the corresponding graphs, a technique is developed based on the use of maximum deformations of the elements with the corresponding fixation of the limit state on the loss of fire resistance in terms of bearing capacity by bending this curve.
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Dissertations / Theses on the topic "Research, Industrial – Mathematical models"

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Mitwasi, Mousa George. "Mathematical models for the deterministic, capacitated, single kanban system." Diss., The University of Arizona, 1991. http://hdl.handle.net/10150/185523.

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The kanban system is the most popular technique for implementing the Just-In-Time philosophy. In this dissertation we develop mathematical models for the deterministic, capacitated, single kanban system. Three different production structures are studied. The models are used to analyze the system, understand the need and behavior of kanbans, and compute good solutions for the number of kanbans to allocate for each part. The first model applies to the single-stage, single-item system. Optimal solutions for the number of kanbans for this system are developed. The second and third models are built for the multi-stage, single-item system and the single-stage, multi-item system respectively. Necessary and sufficient conditions for the feasibility of a set of kanbans are developed for the last two models. The conditions are used to develop heuristic and optimal solution procedures. The heuristic procedures are tested over randomly generated problems and are shown to perform very well compared to the optimal solution procedures.
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Lin, Lebin. "Data Mining and Mathematical Models for Direct Market Campaign Optimization for Fred Meyer Jewelers." Wright State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=wright1483558398637535.

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Wang, Shuai. "Data mining techniques and mathematical models for the optimal scholarship allocation problem for a state university." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1515618183686262.

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Malik, Shadan A. "Optimization model for product mix and capacity management with activity-based information." Thesis, This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-02022010-020435/.

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Abbas, Mustafa Sulaiman. "Consistency Analysis for Judgment Quantification in Hierarchical Decision Model." PDXScholar, 2016. https://pdxscholar.library.pdx.edu/open_access_etds/2699.

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The objective of this research is to establish consistency thresholds linked to alpha (α) levels for HDM’s (Hierarchical Decision Model) judgment quantification method. Measuring consistency in order to control it is a crucial and inseparable part of any AHP/HDM experiment. The researchers on the subject recommend establishing thresholds that are statistically based on hypothesis testing, and are linked to the number of decision variables and (α) level. Such thresholds provide the means with which to evaluate the soundness and validity of an AHP/HDM decision. The linkage of thresholds to (α) levels allows the decision makers to set an appropriate inconsistency tolerance compatible with the situation at hand. The measurements of judgments are unreliable in the absence of an inconsistency measure that includes acceptable limits. All of this is essential to the credibility of the entire decision making process and hence is extremely useful for practitioners and researchers alike. This research includes distribution fitting for the inconsistencies. It is a valuable and interesting part of the research results and adds usefulness, practicality and insight. The superb fits obtained give confidence that all the statistical inferences based on the fitted distributions accurately reflect the HDM’s inconsistency measure.
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Athawale, Samita. "Chemotherapy Appointment Scheduling and Operations Planning." University of Akron / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=akron1428951061.

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Fatollahzadeh, Kianoush. "A laboratory vehicle mock-up research work on truck driver’s selected seat position and posture : A mathematical model approach with respect to anthropometry, body landmark locations and discomfort." Doctoral thesis, KTH, Industriell ekonomi och organisation (Inst.), 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4028.

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Professional truck drivers are highly exposed to fatigue and work related injuries. Truck drivers are common victims of musculoskeletal disorders, frequently suffering from pain symptoms particularly in the neck, shoulder and lower back. This situation is believed to be a contributor to the high absenteeism in this job category. A high percentage of this problem is due to the adoption of an unhealthy driving posture resulting from inappropriate seat design. This incorrect and poor design is owing to the insufficient and obsolete anthropometrical data which has been used for decades for arranging and positioning components in the driver environment. The main objective of the present study was to create and construct a mathematical model which clarifies and predicts the drivers’ comfortable sitting posture and position. It was hypothesized that the length and height characteristics of some body segments as well as the body weight and waist circumference of the driver have a great impact on the selection of a specific sitting posture. The steering wheel positions as well as the pedal/floor locations were hypothesized to be highly correlated to the driver’s selected posture and the corresponding comfort. The effect of the seat position on posture selection and related comfort assessments constituted the other hypothesis of the study which received extra attention. A laboratory experiment on a Scania truck cab mock-up was conducted. The seat track travel along a vertical as well as horizontal forward-backward path was obtained by mounting the seat on the motorized rigid frame which allowed unrestricted vertical and fore-aft travel. The seat cushion angle and backrest angle were adjusted by pivoting the entire seat and backrest around a lateral axis and independently. The pedal components were mounted on a motorized platform, thus allowing unrestricted fore-aft and height travel without any changes in the pedal angles. The steering wheel was mounted on the instrument panel by two independent pneumatic axes which allowed a wide range of adjustments including tilting and moving along the sagittal plane for adjusting the height and distance. The test plan called for 55 international highly experienced heavy truck drivers. The drivers were recruited to span a large range of body weight and stature, in particular to ensure adequate representation of both the extreme as well as the normal group of drivers. The drivers filled in a general information questionnaire before undergoing the anthropometrical measurements and thereafter the test trials. The experiment contained a subset of test conditions with five different trials using random selection sampling procedure. Drivers were asked to adjust the components in a wide range of trajectory according to a written protocol. A sparse set of threedimensional body landmark locations and the corresponding comfort assessments were recorded. As the main part of the result, the mathematical models using multiple regression analyses on selected body landmarks as well as anthropometrical measures were developed which proposed a linear correlation between parameters. The differences between the observed data and the corresponding predicted data using the model were found to be minimal and almost dispensable. Additionally, the drivers preferred to sit in the rearmost position and at a rather high level relative to the rest of the available and adjustable area. Considering the normal adjustable seat area of the cab, only a very small part of the observed Hpoint data lies within this area while a large remaining amount of data lies outside of it. Moreover, the difference between the observation (plotted H-point data) and the neutral H-point was found to be significant. Furthermore, and since some of the data lies almost on the border of the adjustable area, it may indicate a reasonable tendency for even more seat adjustment in the backward direction. A conceptual model consisting of four different parameters was developed and presented in the end. These parameters of the model suggest being as key factors which play a central role on process of decision making regarding the selection of a desirable sitting posture. Any eventual modifications and adjustments for elimination or minimizing discrepancies, biases or obscured factors affecting the quality of the mathematical model would be a case for future study. The investigation of a complete assessment of comfort should be supplemented with an analysis of how many truck drivers are satisfied with the comfort in the end.
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Vijayakumar, Bharathwaj. "SCHEDULING SURGICAL CASES IN A CONSTRAINED ENVIRONMENT." Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1303093820.

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Roychowdhury, Sayak. "Investigation of Flash-free Die Casting by Overflow Design Optimization." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1406121850.

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Lim, Dong-Joon. "Technological Forecasting Based on Segmented Rate of Change." PDXScholar, 2015. https://pdxscholar.library.pdx.edu/open_access_etds/2220.

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Consider the following questions in the early stage of new product development. What should be the target market for proposed design concepts? Who will be the competitors and how fast are they moving forward in terms of performance improvements? Ultimately, is the current design concept and targeted launch date feasible and competitive? To answer these questions, there is a need to integrate the product benchmarking with the assessment of performance improvement so that analysts can have a risk measure for their R&D target setting practices. Consequently, this study presents how time series benchmarking analysis can be used to assist scheduling new product releases. Specifically, the proposed model attempts to estimate the "auspicious" time by which proposed design concepts will be available as competitive products by taking into account the rate of performance improvement expected in a target segment. The empirical illustration of commercial airplane development has shown that this new method provides valuable information such as dominating designs, distinct segments, and the potential rate of performance improvement, which can be utilized in the early stage of new product development. In particular, six dominant airplanes are identified with corresponding local RoCs and, inter alia, technological advancement toward long-range and wide-body airplanes represents very competitive segments of the market with rapid changes. The resulting individualized RoCs are able to estimate the arrivals of four different design concepts, which is consistent with what has happened since 2007 in commercial airplane industry. In addition, the case study of the Exascale supercomputer development is presented to demonstrate the predictive use of the new method. The results indicate that the current development target of 2020 might entail technical risks considering the rate of change emphasizing power efficiency observed in the past. It is forecasted that either a Cray-built hybrid system using Intel processors or an IBM-built Blue Gene architecture system using PowerPC processors will likely achieve the goal between early 2021 and late 2022. This indicates that the challenge to improve the power efficiency by a factor of 23 would require the maximum delay of 4 years to reach the Exascale supercomputer compared to the existing performance curve.
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Books on the topic "Research, Industrial – Mathematical models"

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A, Ciriani Tito, ed. Operational research in industry. Houndmills, Basingstoke, Hampshire: Macmillan Press, 1999.

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Cassady, C. Richard. Probability models in operations research. Boca Raton, FL: Taylor & Francis, 2008.

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Joseph, Geunes, Pardalos P. M. 1954-, and Romeijn H. Edwin, eds. Supply chain management: Models, applications, and research directions. Dordrecht: Kluwer Academic, 2002.

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Lach, Saul. R&D, investment and industry dynamics. Cambridge, MA (1050 Massachusetts Avenue, Cambridge, MA 02138): National Bureau of Economic Research, 1992.

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Kropachev, S. V. Programmno-t͡s︡elevoe upravlenie resheniem nauchno-tekhnicheskikh problem. Novosibirsk: "Nauka," Sibirskoe otd-nie, 1989.

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Kropachev, S. V. Programmno-tselevoe upravlenie resheniem nauchno-tekhnicheskikh problem. Novosibirsk: Nauka, Sibirskoe otd-nie, 1989.

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Levin, Richard C. Cost-reducing and demand-creating R&D with spillovers. Cambridge, Mass: National Bureau of Economic Research, 1989.

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Forschungs- und Entwicklungskooperationen: Eine wettbewerbstheoretische und wettbewerbspolitische Untersuchung. Frankfurt am Main: P. Lang, 1997.

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A, Ottjes Jaap, and Lodewijks Gabriël, eds. The Delft systems approach: Analysis and design of industrial systems. London: Springer, 2008.

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Heinz, Schättler, Friedman Avner, Kashdan Eugene, and SpringerLink (Online service), eds. Mathematical Methods and Models in Biomedicine. New York, NY: Springer New York, 2013.

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Book chapters on the topic "Research, Industrial – Mathematical models"

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Shkaberina, Guzel Sh, Viktor I. Orlov, Elena M. Tovbis, and Lev A. Kazakovtsev. "On the Optimization Models for Automatic Grouping of Industrial Products by Homogeneous Production Batches." In Mathematical Optimization Theory and Operations Research, 421–36. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58657-7_33.

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Bermúdez, Alfredo. "Some Case Studies in Environmental and Industrial Mathematics." In SEMA SIMAI Springer Series, 19–38. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86236-7_2.

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AbstractThis presentation deals with four case studies in environmental and industrial mathematics developed by the mathematical engineering research group (mat+i) from the University of Santiago de Compostela and the Technological Institute for Industrial Mathematics (ITMATI). The first case involves environmental fluid mechanics: optimizing the location of submarine outfalls on the coast. This work, related to shallow water equations with variable depth, led us to develop a theory for numerical treatment of source terms in nonlinear first order hyperbolic balance laws. More recently, these techniques have been applied to solve Euler equations with source terms arising from numerical simulation of gas transportation networks when topography via gravity force is considered in the model. The last two problems concerns electromagnetism. One of them is related to nondestructive testing of car parts by using magnetic nanoparticles (the so-called magnetic particle inspection, MPI): mathematical modelling of magnetic hysteresis to simulate demagnetization. Finally, we present a mathematical procedure to reduce the computing time needed to achieve the stationary state of an induction electric machine when using transient numerical simulation.
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Biesinger, Andreas, Ruben Pesch, Mariela Cotrado, and Dirk Pietruschka. "Increased Efficiency Through Intelligent Networking of Producers and Consumers in Commercial Areas Using the Example of Robert Bosch GmbH." In iCity. Transformative Research for the Livable, Intelligent, and Sustainable City, 105–43. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92096-8_9.

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AbstractEnergy-efficient heating and cooling systems as well as intelligent systems for energy distribution are urgently required in order to be able to meet the ambitious goals of the European Union to reduce greenhouse gas emissions. The present article is intended to show that intelligent system extensions for the area of heating, cooling and electricity production for the industrial sector can lead to significant increase in efficiency. For this purpose, a simulation study for the expansion of a combined heat and power (CHP) plant with 2 MW thermal output using a 1.4 MW absorption chiller has been carried out. This shows that a heat-controlled CHP unit can significantly increase its running time. A system model was created for the initial situation and validated with existing measurement data. In the second step, this model was expanded to include the ACM module. The simulation was able to prove that in the event of a system expansion, the run time of the CHP unit can be increased by 35%. In addition to then increase of energy efficiency in the supply system, the analysis also focuses on the efficiency of the energy distribution via thermal networks in an industrial environment. The presented paper therefore also highlights the optimization potentials in the operation of thermal supply networks for industrial applications. For this purpose, a mathematical model has been developed which in addition to the components of the thermal network itself also comprises the producers and consumers. The specific construction of thermal networks for the supply of industrial properties requires adapted solutions for the simulation of such systems. Therefore, amongst other things, in the paper, solutions are shown for the modelling of direct flow local heating networks as well as for the operation of a cascade-controlled pump group.
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Wu, Bowei, Yanyan Jiang, and Hanzhi Liu. "Research on the Impact of China's Artificial Intelligence on the Transformation and Upgrading of Industrial Structure Based on Dynamic Panel Data Model." In Proceedings of the 2022 International Conference on Mathematical Statistics and Economic Analysis (MSEA 2022), 366–74. Dordrecht: Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-042-8_54.

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Zemitis, Aivars. "Mathematical Models for Impinging Jets." In Progress in Industrial Mathematics at ECMI 2002, 399–403. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-09510-2_55.

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Wacker, Hj, T. Kronberger, A. Ortner, and L. Peer. "Mathematical Models in Chemical Engineering." In Operations Research Proceedings, 570–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77254-2_66.

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Terzopoulos, Demetri. "On Deformable Models." In Mathematical Sciences Research Institute Publications, 181–92. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4613-9711-3_20.

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Langenberg, H. "Mathematical Models in Environmental Research." In GKSS School of Environmental Research, 89–107. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-59563-9_5.

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Göttlich, S., and A. Klar. "Minisymposium Mathematical Models for Supply Chains." In Progress in Industrial Mathematics at ECMI 2008, 513–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12110-4_80.

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Tan, Raymond R., Kathleen B. Aviso, Michael Angelo B. Promentilla, Krista Danielle S. Yu, and Joost R. Santos. "Mathematical Foundations of Input–Output Models." In Lecture Notes in Management and Industrial Engineering, 9–28. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1873-3_2.

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Conference papers on the topic "Research, Industrial – Mathematical models"

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Jin, Ying-Lei, Ai-Hong Tang, Yong Huang, Xu Zheng, and Qiu-Shi Xu. "Research for Equivalent Mathematical Model of MMC-DPFC." In 2017 International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII). IEEE, 2017. http://dx.doi.org/10.1109/iciicii.2017.46.

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Long, Hua, and Baoan Li. "Research on Document Content Classification on Mathematical Regression Model." In 2015 3rd International Conference on Mechatronics and Industrial Informatics. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/icmii-15.2015.120.

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Benedikt, Ondřej, Přemysl Šůcha, and Zdeněk Hanzálek. "On Idle Energy Consumption Minimization in Production: Industrial Example and Mathematical Model." In 9th International Conference on Operations Research and Enterprise Systems. SCITEPRESS - Science and Technology Publications, 2020. http://dx.doi.org/10.5220/0008877400350046.

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Afshari, Hamid, Romain Farel, Jean-Paul Gourlia, and Qingjin Peng. "Energy Symbioses in Eco-Industrial Parks: Models and Perspectives." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59965.

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Design and implementation of Eco-Industrial Parks (EIPs) is a practical and scientific solution to achieve sustainable industries. Specifically, energy exchange networks can significantly contribute to the pollution reduction by recovering and sharing wasted heat generated in industrial processes. Despite this perceived fact, the existing research seems mainly looking for one to one relation and lacks in methods for modeling and optimizing multi-synergy symbioses that is essential for EIPs. This paper reviews main concepts in designing industrial symbioses and proposes an optimization model to exchange the residual energy between individual industries in an EIP. Using mathematical programming, the model decides the best set of connections between energy suppliers and users to minimize the total cost and maximize energy symbioses. The presented models analyze perspectives to potential symbioses for individual industries and EIP managers. A detailed discussion clarifies how these perspectives can affect the optimized symbioses. The model is validated using anonymized data of a real case. The result shows that various perspectives to the model provide different energy network topographies.
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Chimmalee, Benjamas, and Anuchit Anupan. "Simulation of Network Model on Cloud Technology based on Mathematical Framework." In 2021 6th International Conference on Business and Industrial Research (ICBIR). IEEE, 2021. http://dx.doi.org/10.1109/icbir52339.2021.9465875.

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Xiaobin Zhang and Yanru Zhong. "Research on the mathematical model and DC-voltage of static var generator." In 2009 4th IEEE Conference on Industrial Electronics and Applications (ICIEA). IEEE, 2009. http://dx.doi.org/10.1109/iciea.2009.5138812.

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Liu, Xuehang. "Research on Contribution of China’s Marine Industrial Structure Change to Ocean Economic Growth base on Mathematical Model." In 2020 2nd International Conference on Economic Management and Model Engineering (ICEMME). IEEE, 2020. http://dx.doi.org/10.1109/icemme51517.2020.00118.

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Elliott, Novak S. J. "Cerebrospinal Fluid-Structure Interactions: The Development of Mathematical Models Accessible to Clinicians." In ASME 2014 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/pvp2014-29096.

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Physical scientists work with clinicians on biomechanical problems, yet the predictive capabilities of mathematical models often remain elusive to clinical collaborators. This is due to both conceptual differences in the research methodologies of each discipline, and the perceived complexity of even simple models. This limits expert medical input, affecting the applicability of the results. Moreover, a lack of understanding undermines the medical practitioner’s confidence in modeling predictions, hampering its clinical application. In this paper we consider the disease syringomyelia, which involves the fluid-structure interaction of pressure vessels and pipes, as a paradigm of the nexus between the modeling approaches of physical scientists and clinicians. The observations made are broadly applicable to cross-disciplinary research between engineers and non-technical specialists, such as may occur in academic-industrial collaborations.
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Statnikov, I. N., and G. I. Firsov. "Processing of the Results of the Planned Mathematical Experiment in Solving Problems of Research of Dynamics Machines and Mechanisms." In 2018 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon). IEEE, 2018. http://dx.doi.org/10.1109/fareastcon.2018.8602481.

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Hu, Tingjia. "Research on the Social Financing Method of college sports Based on Multivariate Optimization Mathematical Model and BOT Financing Mode." In 2nd International Conference on Management Science and Industrial Engineering (MSIE 2013). Paris, France: Atlantis Press, 2013. http://dx.doi.org/10.2991/msie-13.2013.83.

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Reports on the topic "Research, Industrial – Mathematical models"

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Iisa, Kristiina. Development of Kinetics and Mathematical Models for High-Pressure Gasification of Lignite-Switchgrass Blends: Cooperative Research and Development Final Report, CRADA Number CRD-11-447. Office of Scientific and Technical Information (OSTI), April 2016. http://dx.doi.org/10.2172/1247124.

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Markova, Oksana M., Serhiy O. Semerikov, Andrii M. Striuk, Hanna M. Shalatska, Pavlo P. Nechypurenko, and Vitaliy V. Tron. Implementation of cloud service models in training of future information technology specialists. [б. в.], September 2019. http://dx.doi.org/10.31812/123456789/3270.

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Leading research directions are defined on the basis of self-analysis of the study results on the use of cloud technologies in training by employees of joint research laboratory “Сloud technologies in education” of Kryvyi Rih National University and Institute of Information Technology and Learning Aids of the NAES of Ukraine in 2009-2018: cloud learning technologies, cloud technologies of blended learning, cloud-oriented learning environments, cloud-oriented methodological systems of training, the provision of cloud-based educational services. The ways of implementation SaaS, PaaS, IaaS cloud services models which are appropriate to use in the process of studying the academic disciplines of the cycles of mathematical, natural science and professional and practical training of future specialists in information technology are shown, based on the example of software engineering, computer science and computer engineering. The most significant advantages of using cloud technologies in training of future information technology specialists are definite, namely, the possibility of using modern parallel programming tools as the basis of cloud technologies. Conclusions are drawn; the direction of further research is indicated: designing a cloud-oriented learning environment for future specialists in computer engineering, identifying trends in the development of cloud technologies in the professional training and retraining of information technology specialists, developing a methodology for building the research competencies of future software engineering specialists by using cloud technologies.
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Shokaliuk, Svitlana V., Yelyzaveta Yu Bohunenko, Iryna V. Lovianova, and Mariya P. Shyshkina. Technologies of distance learning for programming basics lessons on the principles of integrated development of key competences. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3888.

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In the era of the fourth industrial revolution – Industry 4.0 – developing key competences (digital, multilingual and mathematical competences in particular) is of paramount importance. The purpose of this work is to investigate the content of key competences of a secondary school student and to develop a method of teaching for the integrated development of multilingual and mathematical competences in the process of teaching Programming Basics with the help of distant technologies. The objectives of the research include generalizing and systematizing theoretical data on the structure and the content of key competences and the potential of informatics lessons for the development of separate components of multilingual and mathematical competences; generalizing and systematizing theoretical data on the ways of arranging distant support for informatics learning, Programming Basics in particular; to investigate the content and the methods of teaching Programming Basics in 7th-11th grades; to develop the e-learning Moodle course using Python for Programming Basics on the principles of integrated approach to developing separate components of multilingual and mathematical competence with determining some methodical special features while using it. The object of the study is to teach informatics to junior high school and high school students. The subject of the study is the means and the methods of realizing distant support in the process of teaching Programming Basics using Python on the principles of an integrated approach to developing multilingual and mathematical competences.
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Hlushak, Oksana M., Svetlana O. Semenyaka, Volodymyr V. Proshkin, Stanislav V. Sapozhnykov, and Oksana S. Lytvyn. The usage of digital technologies in the university training of future bachelors (having been based on the data of mathematical subjects). [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3860.

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This article demonstrates that mathematics in the system of higher education has outgrown the status of the general education subject and should become an integral part of the professional training of future bachelors, including economists, on the basis of intersubject connection with special subjects. Such aspects as the importance of improving the scientific and methodological support of mathematical training of students by means of digital technologies are revealed. It is specified that in order to implement the task of qualified training of students learning econometrics and economic and mathematical modeling, it is necessary to use digital technologies in two directions: for the organization of electronic educational space and in the process of solving applied problems at the junction of the branches of economics and mathematics. The advantages of using e-learning courses in the educational process are presented (such as providing individualization of the educational process in accordance with the needs, characteristics and capabilities of students; improving the quality and efficiency of the educational process; ensuring systematic monitoring of the educational quality). The unified structures of “Econometrics”, “Economic and mathematical modeling” based on the Moodle platform are the following ones. The article presents the results of the pedagogical experiment on the attitude of students to the use of e-learning course (ELC) in the educational process of Borys Grinchenko Kyiv University and Alfred Nobel University (Dnipro city). We found that the following metrics need improvement: availability of time-appropriate mathematical materials; individual approach in training; students’ self-expression and the development of their creativity in the e-learning process. The following opportunities are brought to light the possibilities of digital technologies for the construction and research of econometric models (based on the problem of dependence of the level of the Ukrainian population employment). Various stages of building and testing of the econometric model are characterized: identification of variables, specification of the model, parameterization and verification of the statistical significance of the obtained results.
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Semerikov, Serhiy O., Illia O. Teplytskyi, Yuliia V. Yechkalo, and Arnold E. Kiv. Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot. [б. в.], November 2018. http://dx.doi.org/10.31812/123456789/2648.

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The article substantiates the necessity to develop training methods of computer simulation of neural networks in the spreadsheet environment. The systematic review of their application to simulating artificial neural networks is performed. The authors distinguish basic approaches to solving the problem of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools of neural network simulation, application of third-party add-ins to spreadsheets, development of macros using the embedded languages of spreadsheets; use of standard spreadsheet add-ins for non-linear optimization, creation of neural networks in the spreadsheet environment without add-ins and macros. After analyzing a collection of writings of 1890-1950, the research determines the role of the scientific journal “Bulletin of Mathematical Biophysics”, its founder Nicolas Rashevsky and the scientific community around the journal in creating and developing models and methods of computational neuroscience. There are identified psychophysical basics of creating neural networks, mathematical foundations of neural computing and methods of neuroengineering (image recognition, in particular). The role of Walter Pitts in combining the descriptive and quantitative theories of training is discussed. It is shown that to acquire neural simulation competences in the spreadsheet environment, one should master the models based on the historical and genetic approach. It is indicated that there are three groups of models, which are promising in terms of developing corresponding methods – the continuous two-factor model of Rashevsky, the discrete model of McCulloch and Pitts, and the discrete-continuous models of Householder and Landahl.
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Mathew, Sonu, Srinivas S. Pulugurtha, and Sarvani Duvvuri. Modeling and Predicting Geospatial Teen Crash Frequency. Mineta Transportation Institute, June 2022. http://dx.doi.org/10.31979/mti.2022.2119.

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This research project 1) evaluates the effect of road network, demographic, and land use characteristics on road crashes involving teen drivers, and, 2) develops and compares the predictability of local and global regression models in estimating teen crash frequency. The team considered data for 201 spatially distributed road segments in Mecklenburg County, North Carolina, USA for the evaluation and obtained data related to teen crashes from the Highway Safety Information System (HSIS) database. The team extracted demographic and land use characteristics using two different buffer widths (0.25 miles and 0.5 miles) at each selected road segment, with the number of crashes on each road segment used as the dependent variable. The generalized linear models with negative binomial distribution (GLM-based NB model) as well as the geographically weighted negative binomial regression (GWNBR) and geographically weighted negative binomial regression model with global dispersion (GWNBRg) were developed and compared. This research relied on data for 147 geographically distributed road segments for modeling and data for 49 segments for validation. The annual average daily traffic (AADT), light commercial land use, light industrial land use, number of household units, and number of pupils enrolled in public or private high schools are significant explanatory variables influencing the teen crash frequency. Both methods have good predictive capabilities and can be used to estimate the teen crash frequency. However, the GWNBR and GWNBRg better capture the spatial dependency and spatial heterogeneity among road teen crashes and the associated risk factors.
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Kim, Changmo, Ghazan Khan, Brent Nguyen, and Emily L. Hoang. Development of a Statistical Model to Predict Materials’ Unit Prices for Future Maintenance and Rehabilitation in Highway Life Cycle Cost Analysis. Mineta Transportation Institute, December 2020. http://dx.doi.org/10.31979/mti.2020.1806.

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The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting pavement materials’ unit price. Additionally, the unit price records of the popular pavement materials were categorized by project size (small, medium, large, and extra-large). The critical variables were chosen after identifying their correlations, and the future values of each variable were predicted through time-series analysis. Multiple regression models using selected socio-economic variables were developed to predict the future values of pavement materials’ unit price. A case study was used to compare the results between the uniform unit prices in the current LCCA procedures and the unit prices predicted in this study. In LCCA, long-term prediction involves uncertainties due to unexpected economic trends and industrial demand and supply conditions. Economic recessions and a global pandemic are examples of unexpected events which can have a significant influence on variations in material unit prices and project costs. Nevertheless, the data-driven scientific approach as described in this research reduces risk caused by such uncertainties and enables reasonable predictions for the future. The statistical models developed to predict the future unit prices of the pavement materials through this research can be implemented to enhance the current LCCA procedure and predict more realistic unit prices and project costs for the future M&R activities, thus promoting the most cost-effective alternative in LCCA.
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Lieth, J. Heiner, Michael Raviv, and David W. Burger. Effects of root zone temperature, oxygen concentration, and moisture content on actual vs. potential growth of greenhouse crops. United States Department of Agriculture, January 2006. http://dx.doi.org/10.32747/2006.7586547.bard.

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Soilless crop production in protected cultivation requires optimization of many environmental and plant variables. Variables of the root zone (rhizosphere) have always been difficult to characterize but have been studied extensively. In soilless production the opportunity exists to optimize these variables in relation to crop production. The project objectives were to model the relationship between biomass production and the rhizosphere variables: temperature, dissolved oxygen concentration and water availability by characterizing potential growth and how this translates to actual growth. As part of this we sought to improve of our understanding of root growth and rhizosphere processes by generating data on the effect of rhizosphere water status, temperature and dissolved oxygen on root growth, modeling potential and actual growth and by developing and calibrating models for various physical and chemical properties in soilless production systems. In particular we sought to use calorimetry to identify potential growth of the plants in relation to these rhizosphere variables. While we did experimental work on various crops, our main model system for the mathematical modeling work was greenhouse cut-flower rose production in soil-less cultivation. In support of this, our objective was the development of a Rose crop model. Specific to this project we sought to create submodels for the rhizosphere processes, integrate these into the rose crop simulation model which we had begun developing prior to the start of this project. We also sought to verify and validate any such models and where feasible create tools that growers could be used for production management. We made significant progress with regard to the use of microcalorimetry. At both locations (Israel and US) we demonstrated that specific growth rate for root and flower stem biomass production were sensitive to dissolved oxygen. Our work also identified that it is possible to identify optimal potential growth scenarios and that for greenhouse-grown rose the optimal root zone temperature for potential growth is around 17 C (substantially lower than is common in commercial greenhouses) while flower production growth potential was indifferent to a range as wide as 17-26C in the root zone. We had several set-backs that highlighted to us the fact that work needs to be done to identify when microcalorimetric research relates to instantaneous plant responses to the environment and when it relates to plant acclimation. One outcome of this research has been our determination that irrigation technology in soilless production systems needs to explicitly include optimization of oxygen in the root zone. Simply structuring the root zone to be “well aerated” is not the most optimal approach, but rather a minimum level. Our future work will focus on implementing direct control over dissolved oxygen in the root zone of soilless production systems.
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Guidati, Gianfranco, and Domenico Giardini. Joint synthesis “Geothermal Energy” of the NRP “Energy”. Swiss National Science Foundation (SNSF), February 2020. http://dx.doi.org/10.46446/publication_nrp70_nrp71.2020.4.en.

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Near-to-surface geothermal energy with heat pumps is state of the art and is already widespread in Switzerland. In the future energy system, medium-deep to deep geothermal energy (1 to 6 kilometres) will, in addition, play an important role. To the forefront is the supply of heat for buildings and industrial processes. This form of geothermal energy utilisation requires a highly permeable underground area that allows a fluid – usually water – to absorb the naturally existing rock heat and then transport it to the surface. Sedimentary rocks are usually permeable by nature, whereas for granites and gneisses permeability must be artificially induced by injecting water. The heat gained in this way increases in line with the drilling depth: at a depth of 1 kilometre, the underground temperature is approximately 40°C, while at a depth of 3 kilometres it is around 100°C. To drive a steam turbine for the production of electricity, temperatures of over 100°C are required. As this requires greater depths of 3 to 6 kilometres, the risk of seismicity induced by the drilling also increases. Underground zones are also suitable for storing heat and gases, such as hydrogen or methane, and for the definitive storage of CO2. For this purpose, such zones need to fulfil similar requirements to those applicable to heat generation. In addition, however, a dense top layer is required above the reservoir so that the gas cannot escape. The joint project “Hydropower and geo-energy” of the NRP “Energy” focused on the question of where suitable ground layers can be found in Switzerland that optimally meet the requirements for the various uses. A second research priority concerned measures to reduce seismicity induced by deep drilling and the resulting damage to buildings. Models and simulations were also developed which contribute to a better understanding of the underground processes involved in the development and use of geothermal resources. In summary, the research results show that there are good conditions in Switzerland for the use of medium-deep geothermal energy (1 to 3 kilometres) – both for the building stock and for industrial processes. There are also grounds for optimism concerning the seasonal storage of heat and gases. In contrast, the potential for the definitive storage of CO2 in relevant quantities is rather limited. With respect to electricity production using deep geothermal energy (> 3 kilometres), the extent to which there is potential to exploit the underground economically is still not absolutely certain. In this regard, industrially operated demonstration plants are urgently needed in order to boost acceptance among the population and investors.
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Zhang, Renduo, and David Russo. Scale-dependency and spatial variability of soil hydraulic properties. United States Department of Agriculture, November 2004. http://dx.doi.org/10.32747/2004.7587220.bard.

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Water resources assessment and protection requires quantitative descriptions of field-scale water flow and contaminant transport through the subsurface, which, in turn, require reliable information about soil hydraulic properties. However, much is still unknown concerning hydraulic properties and flow behavior in heterogeneous soils. Especially, relationships of hydraulic properties changing with measured scales are poorly understood. Soil hydraulic properties are usually measured at a small scale and used for quantifying flow and transport in large scales, which causes misleading results. Therefore, determination of scale-dependent and spatial variability of soil hydraulic properties provides the essential information for quantifying water flow and chemical transport through the subsurface, which are the key processes for detection of potential agricultural/industrial contaminants, reduction of agricultural chemical movement, improvement of soil and water quality, and increase of agricultural productivity. The original research objectives of this project were: 1. to measure soil hydraulic properties at different locations and different scales at large fields; 2. to develop scale-dependent relationships of soil hydraulic properties; and 3. to determine spatial variability and heterogeneity of soil hydraulic properties as a function of measurement scales. The US investigators conducted field and lab experiments to measure soil hydraulic properties at different locations and different scales. Based on the field and lab experiments, a well-structured database of soil physical and hydraulic properties was developed. The database was used to study scale-dependency, spatial variability, and heterogeneity of soil hydraulic properties. An improved method was developed for calculating hydraulic properties based on infiltration data from the disc infiltrometer. Compared with the other methods, the proposed method provided more accurate and stable estimations of the hydraulic conductivity and macroscopic capillary length, using infiltration data collected atshort experiment periods. We also developed scale-dependent relationships of soil hydraulic properties using the fractal and geostatistical characterization. The research effort of the Israeli research team concentrates on tasks along the second objective. The main accomplishment of this effort is that we succeed to derive first-order, upscaled (block effective) conductivity tensor, K'ᵢⱼ, and time-dependent dispersion tensor, D'ᵢⱼ, i,j=1,2,3, for steady-state flow in three-dimensional, partially saturated, heterogeneous formations, for length-scales comparable with those of the formation heterogeneity. Numerical simulations designed to test the applicability of the upscaling methodology to more general situations involving complex, transient flow regimes originating from periodic rain/irrigation events and water uptake by plant roots suggested that even in this complicated case, the upscaling methodology essentially compensated for the loss of sub-grid-scale variations of the velocity field caused by coarse discretization of the flow domain. These results have significant implications with respect to the development of field-scale solute transport models capable of simulating complex real-world scenarios in the subsurface, and, in turn, are essential for the assessment of the threat posed by contamination from agricultural and/or industrial sources.
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