Relevant bibliographies by topics / Physical and mathematical model

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Physical and mathematical model'

Author: Grafiati
Published: 5 June 2025
Last updated: 24 June 2025

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Journal articles on the topic "Physical and mathematical model"

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Rajić, Dušan. "Mathematical-physical model of solving inventive problems." FME Transactions 49, no. 3 (2021): 726–33. http://dx.doi.org/10.5937/fme2103726r.

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The spatial-temporal LT-contradiction matrix is an inventology tool that enables exact calculations of certain parameters in an engineering system through mathematical-physical modeling. It objectifies the decision-making process and creates the preconditions to finding an adequate resource (X-element) with a higher probability, and thus to reach a higher degree of ideality solution (HDIS) of an inventive problem as well. Any engineering system that generates an inventive problem can be described using the LT-contradiction matrix. By crossing the appropriate parameters in the LT-contradiction matrix, with the help of the differential geometry of the tensor, a qualitative-quantitative analysis and calculation of relevant degree all contradictions that exist in the inventive problem can be performed. After that, the path to finding the physical characteristics of the X-element in the mathematical-physical model is facilitated, i.e. finding a real resource that will enable a HDIS of the inventive problem in an engineering system.
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Kézi, Csaba. "Teaching the Analysis of Newton’s Cooling Model to Engineering Students." International Journal of Engineering and Management Sciences 8, no. 2 (2023): 63–68. http://dx.doi.org/10.21791/ijems.2023.2.7.

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To apply mathematical methods to physical or other real life problem, we have to formulate the problem in mathematical terms. It means that, we have to construct the mathematical model for the problem. Many physical problems shows the relationships between changing quantities. The rates of change are represented mathematically by derivatives. In this case the mathematical models involve equations relating an unknown function and one or more of its derivatives. These equations are the differential equations. In this article, teaching the analysis of Newton's cooling model to engineering students is presented as one of the applications of separable differential equations.
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Gumnitsky, Jaroslav, Lubov Venger, Vira Sabadash, Dmytro Symak, Anna Hyvlud, and Zoriana Gnativ. "Physical and Mathematical Models of Target Component Extraction from Rectlinear Capillaries." Chemistry & Chemical Technology 16, no. 1 (2022): 112–17. http://dx.doi.org/10.23939/chcht16.01.112.

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The extraction of the solid component from the rectilinear capillary has been investigated. The presence of two extraction zones (convective and molecular diffusion) was confirmed. The effect of the system vacuumizing on the extraction rate has been studied. The convection zone during vacuumizing was found to be increased due to the appearance of the vapor phase bubbles. The mass transfer coefficients for the convective zone have been determined. A mathematical model of the molecular diffusion stage is given, taking into account the nonlinear change in the component concentration in the liquid due to the displacement of the extraction boundary. The molecular diffusion coefficients in the capillary have been determined.
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Kwaghkor, Lubem M., A. Mohammed, and E. V. Nyamtswam. "A MATHEMATICAL MODEL FOR DIABETES MANAGEMENT." FUDMA JOURNAL OF SCIENCES 6, no. 5 (2022): 36–40. http://dx.doi.org/10.33003/fjs-2022-0605-1091.

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Treating and controlling of diabetes is called diabetes management. The management of diabetes can be done through improvement of the patient dietary knowledge, attitudes, and practices. This research work is aimed at introducing dietary (diet restriction) to an earlier model for the detection and control of diabetes: to study the effect of physical exercise and dietary on excess glucose, insulin and epinephrine concentrations in the blood in managing diabetes. The resulting model is found to be uniformly and asymptotically stable. The result shows that when physical exercise is combined with recommended dietary in the management of diabetes, the excess glucose, insulin and epinephrine concentrations returns to their normal level faster with time compared to when only physical exercise is used as a control measure. Hence, it is recommended that in the management of diabetes, both physical exercise and dietary should be used as control measures
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Pankratova, Nataliya, and Igor Golinko. "Electric heater mathematical model for cyber-physical systems." System research and information technologies, no. 2 (September 14, 2021): 7–17. http://dx.doi.org/10.20535/srit.2308-8893.2021.2.01.

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The article discusses the heat and mass transfer dynamic model for an electric heater with lumped parameters, which allows transient processes simulation for the main influences. The proposed model is recommended to be used in cyber-physical systems for forecasting and evaluating the effectiveness of control systems integrated into a single information management system. The developed model can be used by specialists for the analysis and synthesis of control systems for balanced ventilation systems or industrial air conditioners. As an example, a numerical simulation of transient processes along the action main channels for an electric heater HE 36/2 manufactured by VTS CLIMA was carried out. The significant advantage of the proposed model is the possibility for using it for the synthesis and analysis of multidimensional control systems.
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Bergamasco, A., L. Cavaleri, and P. Sguazzero. "Physical and mathematical analysis of a wind model." Il Nuovo Cimento C 9, no. 1 (1986): 1–16. http://dx.doi.org/10.1007/bf02508048.

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Feofanova, S. S., and E. Yu Zaykova. "Territorial physical and mathematical model of stormwater management." E3S Web of Conferences 403 (2023): 04003. http://dx.doi.org/10.1051/e3sconf/202340304003.

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Climate change reduction and adaptation policies are being implemented worldwide through stormwater management in urban areas. Rational use of stormwater could influence the decrease of the "heat island" effect and "cool down" cities. The authors plan to analyze the features of green spaces in the city and demonstrate by a concrete example the opportunity to implement elements of green infrastructure. For widespread use in urban areas, the authors created physical and mathematical model of the territory and recommend variants with four main types of green structures: soil, biotope, shrub, tree. The authors' research proves that with correct analysis of the terrain from the point of view of the terrain from the point of view of urban planning, engineering and landscape, with responsible selection of plants of local flora, bio-drainage systems can work well even in regions with a cold climate, such as Russia.
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Kandic, Aleksandar. "Mathematical model of explanation of the world’s structure in Plato’s Timaeus." Theoria, Beograd 62, no. 2 (2019): 163–88. http://dx.doi.org/10.2298/theo1902163k.

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Plato?s cosmological dialogue The Timaeus initiates, among other things, the question of the status of mathematical entities: do they exist completely independently of the physical world whose structure they supposedly explain, are they present in a certain sense within the physical world, or are they, perhaps, exclusively psychological in nature. The author of the paper critically examines Johansen?s interpretation according to which the inherent structure of the human psyche, in the case of Plato?s Timaeus, is already mathematically ideal. Although Johansen?s interpretation is pervasive and well-grounded, the relationship between mathematical and sensory entities is considered mainly in the context of astronomy, disregarding Plato?s theory of micro-structures (the so-called geometric atomism). Thus, the author confronts Johansen?s interpretation with the opinions of other influential researchers of ancient philosophy, such as Cornford, Vlastos, Popper, Lloyd, Brisson, as well as the philosophers of the ancient era, Proclus, Aristotle, and others, in an effort to develop an interpretation that is as close as possible to the whole of Plato?s text. It seems that, when it comes to Plato?s Timaeus, one cannot discuss about the psychological origin of the mathematical model of explanation of natural phenomena without realizing that, in a quite complicated way, such mathematical model possesses a physical aspect as well. Plato himself, at the end of The Timaeus, claims that psychological disorders are caused by disruptions of the mathematically ideal proportions of bodily parts of the human organism (86b), which is only one of his claims that points to the psychophysical nature of mathematical entities.
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Vsevolod Horyachko, Vsevolod, Oksana Hoholyuk, Taras Ryzhyi, and Serhiy Rendzinyak. "Mathematical model of electrical activity of biological network areas." Computational Problems of Electrical Engineering 9, no. 2 (2019): 8–12. http://dx.doi.org/10.23939/jcpee2019.02.008.

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In the paper, the mathematical model describing the generation of action potential and propagation of an impulse in the neuron's filaments on the basis of the analysis of parametric electriс circuits with distributed parameters and the mathematical model of synaptic interneuron connections are proposed. Developed models allow taking into account the influence of such factors as geometric, physical and chemical parameters of the neuron's filaments and the presence of different neurotransmitters in chemical synapses on transmitting a neural impulse. Further, such models can be used for investigating the conditions of neuron firing at spatial and time integration of input signals, as well as for the simulation of neuromuscular junctions.
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Šumarac, D., Z. Perović, D. Vatić, T. Curić, I. Nurković, and M. Cao. "Preisach Mathematical Model of Hysteresis." Scientific Publications of the State University of Novi Pazar Series A: Applied Mathematics, Informatics and mechanics 15, no. 2 (2023): 61–72. http://dx.doi.org/10.46793/spsunp2302.061s.

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Hysteretic nonlinear phenomena occur in many physical processes: ferromagnetism, adsorption, cyclic plasticity in mechanics, phase transformations, economics, etc. It is characterized by the fact that the same instantaneous values of input can give different outputs depending on the history of the input applied. It means that the relationship is not only nonlinear but also multivalued making it very difficult to model and control. In this paper, accent was given to the application to mechanics i.e. to cyclic plasticity of trusses.
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Dissertations / Theses on the topic "Physical and mathematical model"

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Zhou, Xiaobin. "Mathematical and Physical Simulations of BOF Converters." Doctoral thesis, KTH, Tillämpad processmetallurgi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-175462.

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The purpose of this study is to develop mathematical models to explore the mixing and its related phenomena in converter bath. Specifically, first, a mathematical model of a physical model converter, which was scaled down to 1/6th of a 30 t vessel, was developed in this study. A number of parameters were studied and their effects on the mixing time were recorded in a top blown converter. Second, a mathematical model for a combined top-bottom blown was built to investigate the optimization process. Then, a side tuyere was introduced in the combined top-bottom blown converter and its effects on the mixing and wall shear stress were studied. Moreover, based on the above results, the kinetic energy transfer phenomena in a real converter were investigated by applying the mathematical models. A simplified model, in which the calculation region was reduced to save calculation compared to simulations of the whole region of the converter, was used in the mathematical simulation. In addition, this method was also used in the simulation of real converters. This approach makes it possible to simulate the Laval nozzle flow jet and the cavity separately when using different turbulence models. In the top blown converter model, a comparison between the physical model and the mathematical model showed a good relative difference of 2.5% and 6.1% for the cavity depth and radius, respectively. In addition, the predicted mixing time showed a good relative difference of 2.8% in comparison to the experimental data. In an optimization of a combined top-bottom blown converter, a new bottom tuyere scheme with an asymmetrical configuration was found to be one of the best cases with respect to a decreased mixing time in the bath. An industrial investigation showed that the application effects of the new tuyere scheme yield a better stirring condition in the bath compared to the original case. Furthermore, the results indicated that the mixing time for a combined top-bottom-side blown converter was decreased profoundly compared to a conventional combined top-bottom blown converter. It was found that the side wall shear stress is increased by introducing side blowing, especially in the region near the side blowing plume. For a 100 t converter in real, the fundamental aspects of kinetic energy transfer from a top and bottom gas to the bath were explored. The analyses revealed that the energy transfer is less efficient when the top lance height is lowered or the flowrate is increased in the top blowing operations. However, an inverse trend was found. Namely, that the kinetic energy transfer is increased when the bottom flowrate is increased in the current bottom blowing operations. In addition, the slag on top of the bath is found to dissipate 6.6%, 9.4% and 11.2% for the slag masses 5, 9 and 15 t compared to the case without slag on top of the surface of the bath, respectively.<br><p>QC 20151015</p>
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Machekhin, Yu P. "Measurement of non physical quantities." Thesis, XXI IMEKO World Congress, Prague, Czech Republic, 2015. http://openarchive.nure.ua/handle/document/8669.

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The work focused on the development of measurement methods in non-physical areas of human activity. Analyzed not technical activities of a person lying in the fields of social, biological, economic and other areas where no standards or measurement procedures, built on mathematical and physical models. It is shown that for measuring physical quantities it is necessary to use methods that provide measurements and processing of measurement results. Implementation of measurements of physical quantities for which there are no reference values, is possible only in the case when a connection is established between the test value and operating parameters, which is in the nature of the scales. The basis of these scales are measured intervals of time during which the dynamic system is returned to a stable state.
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Böhm, Ulrike, Gesche Pospiech, Hermann Körndle, and Susanne Narciss. "Physicists use mathematics to describe physical principles an mathematicians use physical phenomena to illustrate mathematical formula - Do they really mean the same?" Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-82341.

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Matthews, Amanda. "A Mathematical Model for Anti-Malarial Drug Resistance." VCU Scholars Compass, 2009. http://scholarscompass.vcu.edu/etd/1721.

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Despite the array of medical advances of our modern day society, infectious diseases still plague millions of people worldwide. Malaria, in particular, causes substantial suffering and death throughout both developed and developing countries. Aside from the socioeconomic challenges presented by the disease's prevalence in impoverished nations, one of the major difficulties scientists have encountered while attempting to eradicate the disease is the parasite's ability to become resistant to new drugs and methods of treatment. In an effort to better understand the dynamics of malaria, we analyze a mathematical model that accounts for both the treatment aspect as well as the drug resistance that accompanies it. Simulations demonstrating the effects of treatment rates and the level of resistance are studied and discussed in hopes of shedding additional light on the characteristics of this devastating epidemic.
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Paul-Michael, Salomonsky. "A Mathematical System for Human Implantable Wound Model Studies." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/3187.

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Dermal wound healing involves a myriad of highly regulated and sophisticated mechanisms, which are coordinated and carried out via several specialized cell types. The dominant players involved in this process include platelets, neutrophils, macrophages and fibroblasts. These cells play a vital role in the repair of the wound by orchestrating tasks such as forming a fibrin clot to stanch blood flow, removing foreign organisms and cellular debris, depositing new collagen matrix and establishing the contractile forces which eventually bridge the void caused by the initial infraction.\\[5pt] \indent Our current understanding of these mechanisms has been primarily based upon animal models. Unfortunately, these models lack insight into pathologic conditions, which plague human beings, such as keloid scar or chronic ulcer formation. Consequently, investigators have proposed a number of {\it in vivo} techniques to study wound repair in humans in order to overcome this barrier. One approach, which has been devised to increase our level of understanding of these chronic conditions, involves the cutaneous placement of a small cylindrical structure within the appendage of a human test subject.\\[5pt] \indent Researches have designed a variety of these implantable structures to examine different aspects of wound healing in both healthy subjects and individuals that experience some trauma related condition. In each case, several implants are surgically positioned at multiple locations under sterile conditions. These structures are later removed at distinct time intervals at which point they are histologically analyzed and biochemically assayed to deduce the presence of biological markers involved in the repair process. Implantable structures used in this way are often referred to as Human Implantable Models or Systems.\\[5pt] \indent Clinical studies with implantable models open up tremendous opportunities in fields such as biomathematics because they provide an experimentally controlled setting that aids in the development and validation of mathematical models. Furthermore, experiments carried out with implants greatly simplify the mathematics required to describe the repair process because they minimize the modeling of complex features associated with healing such as wound geometry and the evolution of contractile forces.\\[5pt] \indent In this work, we present a notional mathematical model, which accounts for two fundamental processes involved in the repair of an acute dermal wound. These processes include the inflammatory response and fibroplasia. Our system describes each of these events through the time evolution of four primary species or variables. These include the density of initial damage, inflammatory cells, fibroblasts and deposition of new collagen matrix. Since it is difficult to populate the equations of our model with coefficients that have been empirically derived, we fit these constants by carrying out a large number of simulations until there is reasonable agreement between the time response of the variables of our system and those reported by the literature for normal healing. Once a suitable choice of parameters has been made, we then compare simulation results with data obtained from clinical investigations. While more data is desired, we have a promising first step toward describing the primary events of wound repair within the confines of an implantable system.
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Sen, Sagar. "A model-driven approach to design engineered physical systems /." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=101173.

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The constant growth in complexity of engineered physical (electrical, mechanical etc.) systems has led to the development of software tools to store and reuse design knowledge to simplify the creation of such systems. Models that encode structure and behaviour of components in the system are currently being developed based on the techniques prescribed by Model Driven Engineering (MDE). We use MDE concepts to develop appropriate modelling formalisms to allow creation of models of a target Engineered Physical System ( EPS) at different levels of abstraction. Each level of abstraction presents a certain view of the EPS to a domain expert in the development team. For instance, a high-level view is suitable for a person in a managerial role. An engineer who deals with the same system at a lower level of abstraction develops a model using idealized physical components. A physicist's concern is the physical meaningfulness of the model. The physicist's model verifies if the model prescribed by the manager via the engineer adheres to the laws of conservation of energy and momentum. Finally, a mathematician or a computer scientist obtains a solution to the constrained equations imposed by the dynamical system by solving it analytically or numerically. This model usually takes the form of a set of Differential Algebraic Equations provided by the physicist.<br>We design model transformations to transform models from a high-level modelling language to lower-level language. We present visual Graph Grammar rules to perform these transformations. We start with a high-level representation of the physical system which is a model in the High-level Physical System Model modelling language. This model is transformed in subsequent steps to a set of trajectories that describe the state of the physical system over time. We show that this hierarchy of transformations to encode knowledge about physical systems drastically reduces design space size at the high-level of abstraction. We search the space of an example EPS using a design heuristic based randomized algorithm to determine the speedup in search due to reduction in the number of design variables.
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Sumner, Neil R. "Calibration of a conceptual rainfall-runoff model using simulated annealing." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 1995. https://ro.ecu.edu.au/theses/1169.

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Simulated annealing (Kirkpatrick et al, 1983) is used to estimate the parameters of a mathematical model that predicts the water yield from a catchment. The calibration problem involves finding the global minimum of a multivariate function that has many extraneous local minima, a situation in which conventional optimisation methods are ineffective. The objective function which quantifies discrepancies between the computed and observed streamflows must be carefully selected to satisfy the least square assumptions. Several published simulated annealing algorithms have been implemented, tested and evaluated using standard test functions. Appropriate cooling schedules are found for each algorithm and test function investigated. The number of function evaluations required to find the minimum is compared to published results for the test functions using either simulated annealing and other global optimisation methods. A new simulated annealing algorithm based on the Hooke and Jeeves (1961) pattern search method is developed and compared with existing algorithms from the literature.
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Bhaskar, Ankush. "Physical understanding and mathematical modeling of geomagnetic field variations during disturbed magnetosphere-ionosphere system." Thesis, Indian Institute of Geomagnetism (IIG), 2016. http://localhost:8080/xmlui/handle/123456789/885.

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A thesis submitted to the University of Mumbai for the Ph.D.(Science) degree in physics under the guidance of Dr. Geeta Vichare<br>The thesis concludes with the following list of major conclusions drawn from the entire study. • The effect of IMF Bz turnings observed in the equatorial geomagnetic field vari ations indicates that the magnitude of northward Bz does not have the influence on the equatorial ionosphere whereas, the response signatures are mainly con trolled by the magnitudes of southward Bz during both northward and southward turnings. • The equivalent current vectors reveal a clockwise (anticlockwise) ionospheric cur rent loop in the afternoon (morning) sector during the main impulse (MI) of the negative pressure impulse (SI−). This indicates an ionospheric twin-cell-vortex current system (DP2) due to field-aligned currents (FACs) associated with the dusk-to-dawn convection electric field during the MI of the SI−. • The stochastic variations of EEJ and Sq are in a cross-talk with a net flow of information from EEJ to Sq station for data having time resolutions between 30-120 min. This suggests that the variations in the magnetic field of EEJ are reflected in Sq, indicating EEJ and Sq are coupled systems. • The physical processes responsible for the geomagnetic storms and Forbush de creases are different, even though they originate due to common interplanetary disturbance like ICMEs and CIRs. For geomagnetic storms, reconnection is the major process whereas, FDs are mainly caused by inhibited diffusion of cosmic rays into the ICMEs due to enhanced IMF and Vsw. It is observed that expan sion of ICME contributes in early recovery phase whereas the gradual variation of solar wind speed beyond ICME boundaries is responsible for the long duration of FD recovery. • The developed artificial neural networks are capable in forecasting global SYMH, ASYH indices and locally observed geomagnetic field variations in Indian sector about an hour before, provided the real-time upstream solar wind data is available.
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Anderson, Evelyn Carole. "Anumerical model for the estimation of solar radiation on rugged terrain /." The Ohio State University, 1985. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487259125218402.

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Brook, Sapoty, and mikewood@deakin edu au. "A physical theory of organisation and consequent neural model of spatio-temporal pattern acquisition." Deakin University. School of Architecture and Engineering, 1987. http://tux.lib.deakin.edu.au./adt-VDU/public/adt-VDU20050825.121850.

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A neurone model (the FORMON) is proposed which provides a mathematical explanation for a range of psychological phenomena and has potential in Artificial Intelligence applications. A general definition of organisation in terms of entropy and information is formulated. The concept of microcodes is introduced to describe the physical nature of organisation. Spatio-temporal pattern acquisition and processing functions attributable to individual neurones are reviewed. The criterion for self-organisation in a neurone is determined as the maximisation of mutual organisation. A feedback control system is proposed to satisfy this criterion and provide an integrated long-term memory of spatio-temporal pattern. This pattern acquisition system is shown to be applicable to dendritic pattern recognition and axonal pattern generation. Provision is also made for adaptation, short-term memory and operant learning. An electro-chemical model of transmission and processing of neural signals is outlined to provide the pattern acquisition functions of the Formon model. A transverse magnetic mode of electrotonic propagation is postulated in addition to the transverse electromagnetic mode. Configurations of the Formon are categorised in terms of possible pattern processing functions. Connective architectures are proposed as self-organising models of acquisitive semantic and syntactic networks.
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Books on the topic "Physical and mathematical model"

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Boldyreva, L. B. A model of superfluid physical vacuum. Fond parapsikhologii im. L.L. Vasilʹeva, 1992.

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Shabetnik, Basil D. Fractal physics: Introduction to a new physical model. A. Gylys, 1994.

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Schroeder, P. R. Verification of the lateral drainage component of the (HELP) model using physical models. U.S. Environmental Protection Agency, Hazardous Waste Engineering Research Laboratory, 1988.

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Paul, Gilman, and National Renewable Energy Laboratory (U.S.), eds. Technical manual for the SAM Physical Trough model. National Renewable Energy Laboratory, 2011.

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Freerks, Marshall C. The vortex model of matter. s.n.], 1993.

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Larsen, Ryan J. New developments in the standard model. Nova Science Publishers, 2011.

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Nomura, Kosuke. Interacting Boson Model from Energy Density Functionals. Springer Japan, 2013.

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Molenaar, J., and E. W. C. van Groesen. Continuum modeling in the physical sciences. Society for Industrial and Applied Mathematics, 2007.

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Szekely, Julian. The physical and mathematical modeling of Tundish operations. Springer-Verlag, 1989.

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Szekely, Julian. The physical and mathematical modeling of Tundish operations. Springer-Verlag, 1989.

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Book chapters on the topic "Physical and mathematical model"

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Augustin, Matthias Albert. "Physical and Mathematical Foundation." In A Method of Fundamental Solutions in Poroelasticity to Model the Stress Field in Geothermal Reservoirs. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17079-4_3.

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Aspri, Andrea. "From the Physical to the Mathematical Model." In An Elastic Model for Volcanology. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31475-0_1.

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van der Schaft, Arjan. "Physical Network Systems and Model Reduction." In Mathematical Control Theory II. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21003-2_11.

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Davies, A. M. "Mathematical Formulation of a Spectral Tidal Model." In Advanced Physical Oceanographic Numerical Modelling. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-017-0627-8_21.

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Davies, A. M. "Mathematical Formulation of a Spectral Circulation Model." In Advanced Physical Oceanographic Numerical Modelling. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-017-0627-8_22.

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Assous, Franck, Patrick Ciarlet, and Simon Labrunie. "Physical Framework and Models." In Applied Mathematical Sciences. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-70842-3_1.

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Iqbal, Kamran. "Mathematical Models of Physical Systems." In A First Course in Control System Design, 2nd ed. River Publishers, 2022. http://dx.doi.org/10.1201/9781003336907-1.

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Shang, De-Yi, and Liang-Cai Zhong. "Mathematical Model of Variable Physical Properties of Nanofluids." In Heat and Mass Transfer. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94403-6_5.

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Borrelli, Arianna. "The Great Yogurt Project: Models and Symmetry Principles in Early Particle Physics." In Model and Mathematics: From the 19th to the 21st Century. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97833-4_6.

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AbstractAccording to the received view of the development of particle physics, mathematics, and more specifically group theory, provided the key which, between the late 1950s and the early 1960s, allowed scientists to achieve both a deeper physical understanding and an empirically successful modeling of particle phenomena. Indeed, a posteriori it has even been suggested that just by looking at diagrams of observed particle properties (see Fig. 1) one could have recognized in them the structures of specific groups (see Fig. 2). However, a closer look at theoretical practices of the 1950s and early 1960s reveals a tension between the employment of advanced mathematical tools and the “modeling” of observation, if the term “model” is understood as a construction allowing for the fitting and predicting of phenomena. As we shall see, the most empirically successful schemes, such as the “Gell-Mann and Nishijima model” or the “eightfold way”, were mathematically very simple, made no use of group-theoretical notions and for quite a time resisted all attempts to transform them into more refined mathematical constructs. Indeed, the theorists who proposed them had little or no interest in abstract approaches to mathematical practice. On the other hand, there were a number of particle theorists who did care about and employ group-theoretical notions, yet not primarily as tools to fit phenomena, but rather as a guide to uncover the fundamental principles of particle interactions. Moreover, these theorists did not regard all groups as epistemically equivalent, and instead clearly preferred those transformations related to space-time invariances over all others. These authors also often made a distinction between purely descriptive “models” and the “theories” they were (unsuccessfully) trying to build and which in their opinion would provide a deeper understanding of nature. Nonetheless, they expected their “theories”, too, to be empirically successful in describing observation, and thus to also function as “models”. In this sense, like their less mathematically-inclined colleagues, they also saw no clear-cut distinction between “modeling” and “theorizing” particle phenomena. In my paper I will discuss the development of these theoretical practices between the 1950s and the early 1960s as examples of the complex relationship between mathematics and the conceptualization of physical phenomena, arguing that, at least in this case, no general statements are possible on the relationship of mathematics and models. At that time, very different mathematical practices coexisted and the epistemic attitudes of physicists towards theoretical constructs could depend both on the assumptions and goals of the individual authors and on the specific mathematical methods and concepts linked to the constructs.
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Prodan, Emil. "Electron Dynamics: Concrete Physical Models." In SpringerBriefs in Mathematical Physics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55023-7_2.

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Conference papers on the topic "Physical and mathematical model"

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Lansberg, Alexander Alexandrovich, Vadim Yevgenyevich Bolshev, and Alexander Alexandrovich Panfilov. "Study of Reverse Transformation Mode in 0.4/10 kV Electric Network on Physical Model." In 2024 6th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA). IEEE, 2024. https://doi.org/10.1109/summa64428.2024.10803844.

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Hou, Guolian, Furong Huang, Tongyue Sun, and Jianhua Zhang. "Mathematical model for ultra-supercritical unit by physical principles." In 2014 IEEE 9th Conference on Industrial Electronics and Applications (ICIEA). IEEE, 2014. http://dx.doi.org/10.1109/iciea.2014.6931268.

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Si, Weixin, Zhaoliang Duan, Cheng Liu, Xiangyun Liao, Zhiyong Yuan, and Jianhui Zhao. "Simulation of Acupuncture Skin Deformation Using Mathematical-Physical Model." In 2010 International Conference on Biomedical Engineering and Computer Science (ICBECS). IEEE, 2010. http://dx.doi.org/10.1109/icbecs.2010.5462402.

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Constantinescu, Radu, Fanel Iacobescu, and Alina Pauna. "Nonlinear mathematical models for physical phenomena." In 10th Jubilee International Conference of the Balkan Physical Union. Author(s), 2019. http://dx.doi.org/10.1063/1.5091249.

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BIASE, FRANCISCO DI. "A Holoinformational Model of the Physical Observer." In Proceedings of the 8th Symposium Honoring Mathematical Physicist Jean-Pierre Vigier. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814504782_0050.

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ROSSI, ARCANGELO. "MATHEMATICAL MODELS AND PHYSICAL REALITY FROM CLASSICAL TO QUANTUM PHYSICS." In Historical Analysis and Open Questions — Cesena 2004. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812773258_0025.

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Enevoldsen, Marie S., Ove Skovgaard, and Peter E. Andersen. "A Combined Mathematical-Physical Model of Laser-Induced Thermotherapy (LITT)." In European Conference on Biomedical Optics. OSA, 2009. http://dx.doi.org/10.1364/ecbo.2009.7373_15.

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Enevoldsen, Marie S., Ove Skovgaard, and Peter E. Andersen. "A combined mathematical-physical model of laser-induced thermotherapy (LITT)." In European Conferences on Biomedical Optics, edited by Ronald Sroka and Lothar D. Lilge. SPIE, 2009. http://dx.doi.org/10.1117/12.831933.

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Kozlovska, Tetyana I., Peter F. Kolisnik, Sergey M. Zlepko, et al. "Physical-mathematical model of optical radiation interaction with biological tissues." In Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2017, edited by Ryszard S. Romaniuk and Maciej Linczuk. SPIE, 2017. http://dx.doi.org/10.1117/12.2280928.

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Kucheriuk, Victor. "Physical and mathematical models in experimental methods." In Photomechanics '95, edited by M. Kh Akhmetzyanov, S. I. Gerasimov, and K. L. Komarov. SPIE, 1996. http://dx.doi.org/10.1117/12.242105.

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Reports on the topic "Physical and mathematical model"

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Kuropiatnyk, D. I. Actuality of the problem of parametric identification of a mathematical model. [б. в.], 2018. http://dx.doi.org/10.31812/123456789/2885.

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The purpose of the article is to study the possibilities of increasing the efficiency of a mathematical model by identifying the parameters of an object. A key factor for parametrization can be called the consideration of properties of the values of the model at a specific time point, which allows a deeper analysis of data dependencies and correlation between them. However, such a technique does not always work, because in advance it is impossible to predict that the parameters can be substantially optimized. In addition, it is necessary to take into account the fact that minimization reduces the values of parameters without taking into account their real physical properties. The correctness of the final values will be based on dynamically selected parameters, which allows you to modify the terms of use of the system in real time. In the development process, the values of experimentally obtained data with the model are compared, which allows you to understand the accuracy of minimization. When choosing the most relevant parameters, various minimization functions are used, which provides an opportunity to cover a wide range of theoretical initial situations. Verification of the correctness of the decision is carried out with the help of a quality function, which can identify the accuracy and correctness of the optimized parameters. It is possible to choose different types of functional quality, depending on the characteristics of the initial data. The presence of such tools during parametrization allows for varied analysis of the model, testing it on various algorithms, data volumes and conditions of guaranteed convergence of functional methods.
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Perdigão, Rui A. P. Earth System Dynamic Intelligence - ESDI. Meteoceanics, 2021. http://dx.doi.org/10.46337/esdi.210414.

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Earth System Dynamic Intelligence (ESDI) entails developing and making innovative use of emerging concepts and pathways in mathematical geophysics, Earth System Dynamics, and information technologies to sense, monitor, harness, analyze, model and fundamentally unveil dynamic understanding across the natural, social and technical geosciences, including the associated manifold multiscale multidomain processes, interactions and complexity, along with the associated predictability and uncertainty dynamics. The ESDI Flagship initiative ignites the development, discussion and cross-fertilization of novel theoretical insights, methodological developments and geophysical applications across interdisciplinary mathematical, geophysical and information technological approaches towards a cross-cutting, mathematically sound, physically consistent, socially conscious and operationally effective Earth System Dynamic Intelligence. Going beyond the well established stochastic-dynamic, information-theoretic, artificial intelligence, mechanistic and hybrid techniques, ESDI paves the way to exploratory and disruptive developments along emerging information physical intelligence pathways, and bridges fundamental and operational complex problem solving across frontier natural, social and technical geosciences. Overall, the ESDI Flagship breeds a nascent field and community where methodological ingenuity and natural process understanding come together to shed light onto fundamental theoretical aspects to build innovative methodologies, products and services to tackle real-world challenges facing our planet.
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Pasupuleti, Murali Krishna. Mathematical Modeling for Machine Learning: Theory, Simulation, and Scientific Computing. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv125.

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Abstract Mathematical modeling serves as a fundamental framework for advancing machine learning (ML) and artificial intelligence (AI) by integrating theoretical, computational, and simulation-based approaches. This research explores how numerical optimization, differential equations, variational inference, and scientific computing contribute to the development of scalable, interpretable, and efficient AI systems. Key topics include convex and non-convex optimization, physics-informed machine learning (PIML), partial differential equation (PDE)-constrained AI, and Bayesian modeling for uncertainty quantification. By leveraging finite element methods (FEM), computational fluid dynamics (CFD), and reinforcement learning (RL), this study demonstrates how mathematical modeling enhances AI-driven scientific discovery, engineering simulations, climate modeling, and drug discovery. The findings highlight the importance of high-performance computing (HPC), parallelized ML training, and hybrid AI approaches that integrate data-driven and model-based learning for solving complex real-world problems. Keywords Mathematical modeling, machine learning, scientific computing, numerical optimization, differential equations, PDE-constrained AI, variational inference, Bayesian modeling, convex optimization, non-convex optimization, reinforcement learning, high-performance computing, hybrid AI, physics-informed machine learning, finite element methods, computational fluid dynamics, uncertainty quantification, simulation-based AI, interpretable AI, scalable AI.
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Rumynin, V. G., V. A. Mironenko, L. N. Sindalovsky, A. V. Boronina, P. K. Konosavsky, and S. P. Pozdniakov. Evaluation of conceptual, mathematical and physical-and-chemical models for describing subsurface radionuclide transport at the Lake Karachai Waste Disposal Site. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/6513.

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Perdigão, Rui A. P., and Julia Hall. Empowering Next-Generation Synergies among Models and Data with Information Physical Quantum Technological Intelligence. Synergistic Manifolds, 2024. https://doi.org/10.46337/241209.

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We present and deploy our methodological and technological framework of Information Physical Quantum Technological Intelligence (IPQuTI), to empower next-generation mathematically robust, physically consistent, computationally efficient and operationally scalable synergies among models and data across multisectoral theoretical and applied workflows. Going beyond digital computing platforms, IPQuTI encompasses a richer basis alphabet of fundamental quantum states (information building blocks) and a high-order set of superposition and entanglement functionals (grammar) beyond the state of the art in quantum information itself. These are foundational core underneath our increased ability to encode, analyze, generate and simulate a broader physical language: one that is able to seamlessly treat complex high-dimensional data and model structures, interactions and operations with faster computational speed, higher robustness, physical consistency, information fidelity, spatiotemporal resolution and lead. For example, in the setting of ensemble operations, IPQuTI encapsulates an entire spatiotemporal system of events into a block operation as a coherent universe. Turning lengthy intense computational churning of approximate equations and massive datasets into a post-quantum spatiotemporal pulse of rich spatiotemporal diversity, spanning deterministic and stochastic synergies among models and data into a unified solution. With nonlinear geophysical applications in mind, IPQuTI is explored in key contexts of Data Assimilation, Data Fusion, Machine Learning, Predictability Investigation and Uncertainty Quantification. Firstly, to further optimize gold-standard state-of-art (SoA) solutions, providing them with a new efficient and robust platform to operate. Second, to overcome known SoA challenges, thereby contributing towards their methodological and practical upgrade. Third, to unveil novel features adding methodological and applied value to these areas, including handling sparse records, perturbations and extremes.
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Clausen, Jay, Christopher Felt, Michael Musty, et al. Modernizing environmental signature physics for target detection—Phase 3. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/43442.

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The present effort (Phase 3) builds on our previously published prior efforts (Phases 1 and 2), which examined methods of determining the probability of detection and false alarm rates using thermal infrared for buried object detection. Environmental phenomenological effects are often represented in weather forecasts in a relatively coarse, hourly resolution, which introduces concerns such as exclusion or misrepresentation of ephemera or lags in timing when using this data as an input for the Army’s Tactical Assault Kit software system. Additionally, the direct application of observed temperature data with weather model data may not be the best approach because metadata associated with the observations are not included. As a result, there is a need to explore mathematical methods such as Bayesian statistics to incorporate observations into models. To better address this concern, the initial analysis in Phase 2 data is expanded in this report to include (1) multivariate analyses for detecting objects in soil, (2) a moving box analysis of object visibility with alternative methods for converting FLIR radiance values to thermal temperature values, (3) a calibrated thermal model of soil temperature using thermal IR imagery, and (4) a simple classifier method for automating buried object detection.
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Svobodny, Thomas P. Mathematical Modeling, Simulation, and Control of Physical Processes. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada455803.

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Frauenfelder, H., P. Hagan, J. Sobehart, and Tetsuji Ueda. Applications of mathematical analysis of nonlinear physical systems. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/258142.

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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, 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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Bruno, Oscar P. Mathematical Prediction of the Physical Properties of Materials and Media. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada368323.

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