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Lin, Mark, and Periklis Papadopoulos. "ANumerical Uncertainty in Parallel Processing Using Computational Fluid Dynamics as Example." Athens Journal of Τechnology & Engineering 8, no. 2 (April 29, 2021): 169–80. http://dx.doi.org/10.30958/ajte.8-2-3.
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Computational methods such as Computational Fluid Dynamics (CFD) traditionally yield a single output – a single number that is much like the result one would get if one were to perform a theoretical hand calculation. However, this paper will show that computation methods have inherent uncertainty which can also be reported statistically. In numerical computation, because many factors affect the data collected, the data can be quoted in terms of standard deviations (error bars) along with a mean value to make data comparison meaningful. In cases where two data sets are obscured by uncertainty, the two data sets are said to be indistinguishable. A sample CFD problem pertaining to external aerodynamics is copied and ran on 29 identical computers in a university computer lab. The expectation is that all 29 runs should return exactly the same result; unfortunately, in a few cases the result turns out to be different. This is attributed to the parallelization scheme which partitions the mesh to run in parallel on multiple cores of the computer. The distribution of the computational load is hardware-driven depending on the available resource of each computer at the time. Things, such as load-balancing among multiple Central Processing Unit (CPU) cores using Message Passing Interface (MPI) are transparent to the user. Software algorithm such as METIS or JOSTLE is used to automatically divide up the load between different processors. As such, the user has no control over the outcome of the CFD calculation even when the same problem is computed. Because of this, numerical uncertainty arises from parallel (multicore) computing. One way to resolve this issue is to compute problems using a single core, without mesh repartitioning. However, as this paper demonstrates even this is not straight forward. Keywords: numerical uncertainty, parallelization, load-balancing, automotive aerodynamics
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Ricci, Stefano, and Valentino Meacci. "Data-Adaptive Coherent Demodulator for High Dynamics Pulse-Wave Ultrasound Applications." Electronics 7, no. 12 (December 14, 2018): 434. http://dx.doi.org/10.3390/electronics7120434.
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Pulse-Wave Doppler (PWD) ultrasound has been applied to the detection of blood flow for a long time; recently the same method was also proven effective in the monitoring of industrial fluids and suspensions flowing in pipes. In a PWD investigation, bursts of ultrasounds at 0.5–10 MHz are periodically transmitted in the medium under test. The received signal is amplified, sampled at tens of MHz, and digitally processed in a Field Programmable Gate Array (FPGA). First processing step is a coherent demodulation. Unfortunately, the weak echoes reflected from the fluid particles are received together with the echoes from the high-reflective pipe walls, whose amplitude can be 30–40 dB higher. This represents a challenge for the input dynamics of the system and the demodulator, which should clearly detect the weak fluid signal while not saturating at the pipe wall components. In this paper, a numerical demodulator architecture is presented capable of auto-tuning its internal dynamics to adapt to the feature of the actual input signal. The proposed demodulator is integrated into a system for the detection of the velocity profile of fluids flowing in pipes. Simulations and experiments with the system connected to a flow-rig show that the data-adaptive demodulator produces a noise reduction of at least of 20 dB with respect to different approaches, and recovers a correct velocity profile even when the input data are sampled at 8 bits only instead of the typical 12–16 bits.
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Horta, A. A., L. O. S. Ferreira, E. L. Martinez, and R. Maciel Filho. "SIMULATION OF THE ALCOHOL-OIL MIXTURE IN A T-SHAPED MICROCHANNEL USING THE DISSIPATIVE PARTICLE DYNAMICS METHOD ON GPU DEVICES." Revista de Engenharia Térmica 13, no. 1 (June 30, 2014): 65. http://dx.doi.org/10.5380/reterm.v13i1.62072.
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Multiphase fluid motion in microchannnels involves complicated fluid dynamics and is fundamentally important to diverse practical engineering applications. Among several applications, the alcohol-oil mixture is particularly important due to its application for biodiesel production. In this work, the mixture of immiscible fluids alcohol-oil in a square T-shaped microchannel was investigated using the Dissipative Particle Dynamics (DPD) method available in the HOOMD simulator, which runs on a single graphic processing unit (GPU). The immiscible fluids were achieved by increasing the repulsive force between species. The fluid properties and hydrodynamic behavior were discussed in function of model parameters. The simulation results agree with data published in the literature showing that the DPD is appropriate for simulation of mass transport on complex geometries in microscale on a single GPU.
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NISHIDA, Hidetoshi. "Velocity Correction Technique for Incompressible Velocity with Noises Using Data-processing Fluid Dynamics (DFD)." Transactions of the Japan Society of Mechanical Engineers Series B 74, no. 738 (2008): 261–66. http://dx.doi.org/10.1299/kikaib.74.261.
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Barber, T. J., G. Doig, C. Beves, I. Watson, and S. Diasinos. "Synergistic integration of computational fluid dynamics and experimental fluid dynamics for ground effect aerodynamics studies." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 226, no. 6 (June 2012): 602–19. http://dx.doi.org/10.1177/0954410011414321.
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This article highlights the ‘synergistic’ use of experimental fluid dynamics (EFD) and computational fluid dynamics (CFD), where the two sets of simulations are performed concurrently and by the same researcher. In particular, examples from the area of ground effect aerodynamics are discussed, where the major facility used was also designed through a combination of CFD and EFD. Three examples are than outlined, to demonstrate the insight that can be obtained from the integration of CFD and EFD studies. The case studies are the study of dimple flow (to enhance aerodynamic performance), the analysis of a Formula-style front wing and wheel, and the study of compressible flow ground effect aerodynamics. In many instances, CFD has been used to not only provide complementary information to an experimental study, but to design the experiments. Laser-based, non-intrusive experimental techniques were used to provide an excellent complement to CFD. The large datasets found from both experimental and numerical simulations have required a new methodology to correlate the information; a new post-processing method has been developed, making use of the kriging and co-kriging estimators, to develop correlations between the often disparate data types.
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San, Omer, Suraj Pawar, and Adil Rasheed. "Prospects of federated machine learning in fluid dynamics." AIP Advances 12, no. 9 (September 1, 2022): 095212. http://dx.doi.org/10.1063/5.0104344.
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Physics-based models have been mainstream in fluid dynamics for developing predictive models. In recent years, machine learning has offered a renaissance to the fluid community due to the rapid developments in data science, processing units, neural network based technologies, and sensor adaptations. So far in many applications in fluid dynamics, machine learning approaches have been mostly focused on a standard process that requires centralizing the training data on a designated machine or in a data center. In this article, we present a federated machine learning approach that enables localized clients to collaboratively learn an aggregated and shared predictive model while keeping all the training data on each edge device. We demonstrate the feasibility and prospects of such a decentralized learning approach with an effort to forge a deep learning surrogate model for reconstructing spatiotemporal fields. Our results indicate that federated machine learning might be a viable tool for designing highly accurate predictive decentralized digital twins relevant to fluid dynamics.
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Rambo, Jeffrey, and Yogendra Joshi. "Thermal Performance Metrics for Arranging Forced Air Cooled Servers in a Data Processing Cabinet." Journal of Electronic Packaging 127, no. 4 (February 11, 2005): 452–59. http://dx.doi.org/10.1115/1.2056575.
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The optimal arrangement of various components in a standard data processing cabinet layout is investigated through computational fluid dynamics and heat transfer. Relevant heat transfer performance of candidate designs is measured by newly proposed metrics for systems level electronics cooling. The results are then extended to define a favorable power dissipation profile, the most favorable of which was found to be one where the power dissipation increases in the vertical direction.
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Mayinger, F. "The 1991 Max Jakob Memorial Award Lecture: Image-Forming Optical Techniques in Heat Transfer: Revival by Computer-Aided Data Processing." Journal of Heat Transfer 115, no. 4 (November 1, 1993): 824–34. http://dx.doi.org/10.1115/1.2911376.
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Increasing possibilities of computer-aided data processing have fostered a revival of image-forming optical techniques in heat and mass transfer as well as in fluid dynamics. Optical measuring techniques can provide comprehensive and detailed information on the formation of phase interfaces, particle movement, or the size distribution of droplet swarms. Holographic interferograms contain full information, not only about boundary layers restricting transport processes, but also on local coefficients of heat and mass transfer. Laser-induced fluorescence promotes a better understanding of combustion processes by conveying insights into the concentration and the temperature in and around a flame. For describing complicated phenomena in fluid dynamics or in heat transfer by computer programs, global experimental information is not sufficient. Optical techniques provide local data without disturbing the process and with a high temporal resolution. By using the results of optical measuring techniques, it is possible to improve computer programs that describe physical processes. Optical techniques are also very sensitive touchstones for checking the quality of such programs.
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Marinho, Daniel Almeida, Victor Machado Reis, João Paulo Vilas-Boas, Francisco Bessone Alves, Leandro Machado, Abel Ilah Rouboa, and António José Silva. "Design of a three-dimensional hand/forearm model to apply computational fluid dynamics." Brazilian Archives of Biology and Technology 53, no. 2 (April 2010): 436–42. http://dx.doi.org/10.1590/s1516-89132010000200024.
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The purpose of this study was to develop a three-dimensional digital model of a human hand and forearm to apply Computational Fluid Dynamics to propulsion analysis in swimming. Computer tomography scans of the hand and forearm of an Olympic swimmer were applied. The data were converted, using image processing techniques, into relevant coordinate input, which could be used in Computational Fluid Dynamics software. From that analysis, it was possible to verify an almost perfect agreement between the true human segment and the digital model. This technique could be used as a means to overcome the difficulties in developing a true three-dimensional model of a specific segment of the human body. Additionally, it could be used to improve the use of Computational Fluid Dynamics generally in sports and specifically in swimming studies, decreasing the gap between the experimental and the computational data.
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Jin, Zhihao. "Advancement of Liquid Immersion Cooling for Data Centers." Highlights in Science, Engineering and Technology 97 (May 28, 2024): 321–27. http://dx.doi.org/10.54097/4fbbk041.
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With the increasing processing capabilities of data centers, the demand for advanced cooling has been increased, positioning liquid immersion cooling systems as a focal point due to their effectiveness and environmental benefits. This paper reviews the current state and prospects of liquid immersion cooling technologies for data centers by paper analyzing. The research spans the optimization of cooling technology parameters, material and coolant performance, as well as system level integration and thermal management. The characteristics analysis of liquids and supercritical fluids underscores the significance of coolant selection Innovative cooling network designs have been shown to initiate failures and improve thermal distribution, enhancing data center performance and reliability. Additionally, the interplay between cooling systems and IT systems has been explored for its overall energy efficiency impact. Liquid immersion cooling technology demonstrates vast potential in ensuring safety, enhancing heat exchange efficiency, and meeting the growing needs of future data center development. Nonetheless, a deep understanding of complex fluid dynamics and heat transfer mechanisms remains key to driving technological advantages.
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Atkinson, H. V. "Experimental Determination of the Parameters for Modelling Semi-Solid Processing." Solid State Phenomena 116-117 (October 2006): 16–23. http://dx.doi.org/10.4028/www.scientific.net/ssp.116-117.16.
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The numerical modeling of semi-solid processing requires data on the rheological properties of materials. This data is often obtained by rheometry but there are difficulties with characterizing high solid fractions, where the torque which can be exerted with the rheometer is insufficient. A number of other methods for measuring the flow parameters, including compression between platens, have been utilized. The various methods will be reviewed in this paper. Computational fluid dynamics modelers have often used data from steady state experiments but it is the behaviour during rapid transients which is more relevant to the actual semi-solid processing route.
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Sulastri, Jennifer, Yoga Satria Putra, and Yudha Arman. "Pemodelan Pencampuran Dua Cairan dalam Lid-Driven Cavity Menggunakan Pendekatan Computational Fluid Dynamics." PRISMA FISIKA 10, no. 3 (February 26, 2023): 402. http://dx.doi.org/10.26418/pf.v10i3.60379.
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Lid-driven cavity adalah aliran dalam rongga dengan tutup yang bergerak. Proses pencampuran dalam lid-driven cavity merupakan kajian yang menarik untuk dilakukan. Tujuan dari penelitian ini adalah untuk memodelkan proses pencampuran dua fluida cair dalam lid-driven cavity menggunakan perangkat lunak open source OpenFOAM dengan menerapkan model turbulen RANS k-epsilon. Penelitian dilakukan melalui tiga tahap, yaitu pre-processing, solving dan post-processing. Validasi hasil simulasi dilakukan setelah semua proses simulasi selesai. Hasil penelitian menunjukan bahwa konsentrasi dua cairan fluida sesuai dengan data eksperimen. Sudut geometri yang diuji terdiri dari 0°, 5°, 10°, 15°, 20° dan 25°. Hasil simulasi pencampuran pada nilai 0°, 5°, 10°, 15° memiliki waktu yang lebih singkat dan menghasilkan konsentrasi sebesar 0.247, 0.255, 0.270, dan 0.295. Pencampuran dua fluida dengan ° dan 25° telah menghasilkan konsentrasi sebesar 0.342 dan 0.400. Pencampuran pada kondisi ini memerlukan waktu perhitungan yang lebih lama.
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Gupta, Nikita, Nishant Bhardwaj, Gulam Muhammad Khan, and Vivek Dave. "Global Trends of Computational Fluid Dynamics to Resolve Real World Problems in the Contemporary Era." Current Biochemical Engineering 6, no. 3 (December 28, 2020): 136–55. http://dx.doi.org/10.2174/2212711906999200601121232.
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Background: Computational fluid dynamics (CFD) came into existence with great success, thereby replacing the traditional methods used to simulate the problems related to the flow of fluid. First CFD utilitarian was introduced to the world in 1957, which was developed by a team at Los Alamos National Lab. For tremendous performance and to meet the expected results with ease for modern process conditions, engineers are now more inclined towards the use of simulation software rather than traditional methods. Hence, in the current scenario with the advancement of computer technologies, “CFD is recognized as an excellent tool for engineers to resolve real-world problems.” Introduction: CFD is defined as a branch of fluid dynamics which involves the use of numerical analysis and data structure to solve complications related to the flow of fluids (gasses or liquids). CFD is based on three major principles that are mass conservation, Newton's second law, and energy conservation. CFD has extended to a number of applications at an alarming rate in every field such as in aerospace, sports, food industry, engineering, hydraulics, HVAC (Heating, Ventilating, and Air conditioning), automotive, environmental, power generation, biomedical, pharmaceutical, and many more. Hence, a number of software like ANSYS, Open Foam, SimScale, Gerris, Auto desk simulation, Code_Saturne, etc, are beneficial in order to execute the operations, and to find the solution of realworld problems within a fraction of seconds. Methods: CFD analysis involves three major steps; pre-processing, solution, and post-processing. Preprocessing deals with defining model goals, identification of domain, designing, and creating the grid. Solution involves setting up the numerical model, computing, and monitoring the solution; whereas, post-processing includes results of the examination and revision of the model. Results: The review includes current challenges about the computational fluid dynamics. It is relevant in different areas of engineering to find answers for the problems occurring globally with the aid of a number of simulation-based software hereby, making the world free from complex problems in order to have a non-complicated scenario. Conclusion: Computational fluid dynamics are relevant in each, and every kind of problem related to the fluid flow, either existing in the human body or anywhere. In the contemporary era, there are enormous numbers of simulation-based software, which provide excellent results with just one click, thereby resolving the problems within microseconds. Hence, we cannot imagine our present and upcoming future without CFD, which has ultimately made the execution of work easier, leaving behind non-complicating scenarios. Lastly, we can conclude that “CFD is a faster, smarter, and lighter way in designing process.”
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Edlin, Joy, Justin Nowell, Christopher Arthurs, Alberto Figueroa, and Marjan Jahangiri. "Assessing the methodology used to study the ascending aorta haemodynamics in bicuspid aortic valve." European Heart Journal - Digital Health 2, no. 2 (June 1, 2021): 271–78. http://dx.doi.org/10.1093/ehjdh/ztab022.
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Abstract Aims Modern imaging techniques provide evermore-detailed anatomical and physiological information for use in computational fluid dynamics to predict the behaviour of physiological phenomena. Computer modelling can help plan suitable interventions. Our group used magnetic resonance imaging and computational fluid dynamics to study the haemodynamic variables in the ascending aorta in patients with bicuspid aortic valve before and after isolated tissue aortic valve replacement. Computer modelling requires turning a physiological model into a mathematical one, solvable by equations that undergo multiple iterations in four dimensions. Creating these models involves several steps with manual inputs, making the process prone to errors and limiting its inter- and intra-operator reproducibility. Despite these challenges, we created computational models for each patient to study ascending aorta blood flow before and after surgery. Methods and results Magnetic resonance imaging provided the anatomical and velocity data required for the blood flow simulation. Patient-specific in- and outflow boundary conditions were used for the computational fluid dynamics analysis. Haemodynamic variables pertaining to blood flow pattern and derived from the magnetic resonance imaging data were calculated. However, we encountered problems in our multi-step methodology, most notably processing the flow data. This meant that other variables requiring computation with computational fluid dynamics could not be calculated. Conclusion Creating a model for computational fluid dynamics analysis is as complex as the physiology under scrutiny. We discuss some of the difficulties associated with creating such models, along with suggestions for improvements in order to yield reliable and beneficial results.
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Filipovic, Nenad, and Milos Kojic. "Computer simulations of blood flow with mass transport through the carotid artery bifurcation." Theoretical and Applied Mechanics 31, no. 1 (2004): 1–33. http://dx.doi.org/10.2298/tam0401001f.
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The current paradigm for clinical diagnostic for the treatment of vascular disease relies exclusively on diagnostic imaging data to define the present state of the patient, empirical data to evaluate the efficacy of prior treatments for similar patients. These techniques are insufficient to predict the outcome of a given treatment for an individual patient. We here propose a new paradigm of predictive medicine where physician could use computational simulation to construct and evaluate a specific geometrical/anatomical model to predict the outcome for an individual patient. For this purpose it is necessary to develop a complex software system which combines user friendly interface, automatic solid modeling, automatic finite mesh generation, computational fluid dynamics and post-processing visualization. The flow dynamics is defined according to the incompressible Navier-Stokes equations for Newtonian and non-Newtonian fluids. Mass transport of oxygen and macromolecules is modeled by the convection diffusion equation and coupled with flow dynamics. The computer simulations are based upon finite element analysis where the new computer methods for coupling oxygen transport and fluid flow are described. The comparison results shows a good agreement between clinical observation for critical zones of flow separation, flow recirculation, low wall shear stresses which may contribute to the development of atherosclerotic diseases.
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Podichetty, Jagdeep T., Md Waliul Islam, David Van, Gary L. Foutch, and A. H. Johannes. "Viscous heating analysis of simulant feces by computational fluid dynamics and experimentation." Journal of Water, Sanitation and Hygiene for Development 4, no. 1 (October 21, 2013): 62–71. http://dx.doi.org/10.2166/washdev.2013.070.
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Highly viscous substances, such as feces, produce significant heat when layer deformation occurs. We describe the use of viscous heating sufficient to destroy disease-causing microorganisms and whipworms in feces. Computational fluid dynamics (CFD) was used to evaluate preliminary design and provide initial geometric specifications for a laboratory-scale unit. The laboratory device has a rotating core separated from a fixed shell wall by a defined space. Data were obtained over a range of operating conditions with simulant materials. The CFD model was validated with the experimental results. The temperature observed with the smallest spacing was 190 °C. Alternative geometries are considered for high-volume sludge processing. Potential design modifications include enhancing efficient water evaporation and recovery.
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Long, Yun, Xi’an Guo, and Tianbai Xiao. "Research, Application and Future Prospect of Mode Decomposition in Fluid Mechanics." Symmetry 16, no. 2 (January 29, 2024): 155. http://dx.doi.org/10.3390/sym16020155.
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In fluid mechanics, modal decomposition, deeply intertwined with the concept of symmetry, is an essential data analysis method. It facilitates the segmentation of parameters such as flow, velocity, and pressure fields into distinct modes, each exhibiting symmetrical or asymmetrical characteristics in terms of amplitudes, frequencies, and phases. This technique, emphasizing the role of symmetry, is pivotal in both theoretical research and practical engineering applications. This paper delves into two dominant modal decomposition methods, infused with symmetry considerations: Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD). POD excels in dissecting flow fields with clear periodic structures, often showcasing symmetrical patterns. It utilizes basis functions and time coefficients to delineate spatial modes and their evolution, highlighting symmetrical or asymmetrical transitions. In contrast, DMD effectively analyzes more complex, often asymmetrical structures like turbulent flows. By performing iterative analyses on the flow field, DMD discerns symmetrical or asymmetrical statistical structures, assembling modal functions and coefficients for decomposition. This method is adapted to extracting symmetrical patterns in vibration frequencies, growth rates, and intermodal coupling. The integration of modal decomposition with symmetry concepts in fluid mechanics enables the effective extraction of fluid flow features, such as symmetrically or asymmetrically arranged vortex configurations and trace evolutions. It enhances the post-processing analysis of numerical simulations and machine learning approaches in flow field simulations. In engineering, understanding the symmetrical aspects of complex flow dynamics is crucial. The dynamics assist in flow control, noise suppression, and optimization measures, thus improving the symmetry in system efficiency and energy consumption. Overall, modal decomposition methods, especially POD and DMD, provide significant insights into the symmetrical and asymmetrical analysis of fluid flow. These techniques underpin the study of fluid mechanics, offering crucial tools for fluid flow control, optimization, and the investigation of nonlinear phenomena and propagation modes in fluid dynamics, all through the lens of symmetry.
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Borghi, M., G. Cantore, M. Milani, and R. Paoluzzi. "Analysis of hydraulic components using computational fluid dynamics models." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 212, no. 7 (July 1, 1998): 619–29. http://dx.doi.org/10.1243/0954406981521583.
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This paper presents some results obtained during the computational fluid dynamics (CFD) analysis of internal flows inside a hydraulic component, using a scaling technique applied to numerical pre- and post-processing. The main aim of the work is to demonstrate the reduction of computational work needed for a complete analysis of component behaviour over a wide range of operating conditions. This result is achieved through the adoption of a methodology aimed at giving the highest level of generality to a non-dimensional solution, thereby overcoming the two major limitations encountered in the use of CFD in fluid power design: computer resources and time. In the case study, the technique was applied to a hydraulic distributor and computations were performed with a commercial computational fluid dynamics code. The key factor of this technique is the evaluation, for a given distributor opening, of the Reynolds number of the flow in the metering region. Provided that this number is high enough to ensure that the discharge coefficient has reached its asymptotic value, the characterization of the flow by a single non-dimensional numerical run can be shown. The theoretical contents of the analysis of the re-scaling technique, which focuses on the engineering information necessary in component design, are described in detail. The bases for its subsequent application to actual cases are then outlined. Finally, a fairly close correlation between numerical results and experimental data is presented.
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Lyakhovets, M. V., G. V. Makarov, and A. S. Salamatin. "Data generation for digital simulators of metallurgical process operators." Izvestiya. Ferrous Metallurgy 66, no. 2 (June 6, 2023): 236–43. http://dx.doi.org/10.17073/0368-0797-2023-2-236-243.
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The article deals with the formation of model implementations of time series of data (based on in-situ data) of controlled and uncontrolled impacts in simulator-training and digital modeling systems. Such simulators are becoming increasingly widespread due to the development of information and computer technologies, automated research systems, training systems, digital modeling technologies (APM modeling), as well as digital counterparts and advanced control systems. The formed implementations of impacts can characterize situations of normal process flow, emergency and pre-emergency states, or specific representative situations for training operators and technological personnel, software testing, research and tuning of algorithms and search for optimal control actions. Using examples from the metallurgical industry, the possibility of forming several interrelated impacts based on models of nonlinear dynamics and multivariate dynamic databases is shown. The Lorentz system describing the thermal convection of a fluid medium is considered as a model of the impacts formation. The model parameters for the low- and high-frequency components are determined separately, by processing in-situ data. Next, a training sample is formed using normalization and relay-exponential smoothing operations. The implementations of the actions are formed taking into account the mutual correlation of data based on models of chemical dynamics and are adjusted to the specified properties on a limited sample of a given volume with the required accuracy using a generator in the form of a closed dynamic system. The generator in form of a closed dynamic system is built on the basis of a multidimensional generating autoregressive model with adjustable coefficients. An example of the formation of data series on technological parameters of a blast furnace (the degree of wear of the furnace lining, temperature sensor readings and heat flux density) is shown.
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Reynolds, Quinn G., Oliver F. Oxtoby, Markus W. Erwee, and Pieter J. A. Bezuidenhout. "An extension of the multiple marker algorithm for study of phase separation problems at the mesoscale." MATEC Web of Conferences 347 (2021): 00025. http://dx.doi.org/10.1051/matecconf/202134700025.
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Multiphase fluid flow is an active field of research in numerous branches of science and technology. An interesting subset of multiphase flow problems involves the dispersion of one phase into another in the form of many small bubbles or droplets, and their subsequent separation back into bulk phases after this has occurred. Phase dispersion may be a desirable effect, for example in the production of emulsions of otherwise immiscible liquids or to increase interfacial surface area for chemical reactions, or an undesirable one, for example in the intermixing of waste and product phases during processing or the generation of foams preventing gas-liquid decoupling. The present paper describes a computational fluid dynamics method based on the multiple marker front-capturing algorithm – itself an extension of the volume-of-fluids method for multiphase flow – which is capable of scaling to mesoscale systems involving thousands of droplets or bubbles. The method includes sub-grid models for solution of the Reynolds equation to account for thin film dynamics and rupture. The method is demonstrated with an implementation in the OpenFOAM® computational mechanics framework. Comparisons against empirical data are presented, together with a performance benchmarking study and example applications.
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Bhoite, Kiran, S. M. Bhosle, Riddhi Mirajkar, Rahul More, and Sachin Kolekar. "Machine Learning Based Fluid-Transportation Monitoring and Controlling." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9s (August 31, 2023): 446–52. http://dx.doi.org/10.17762/ijritcc.v11i9s.7455.
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The discipline of fluid mechanics is developing quickly, propelled by previously unheard-of data volumes from experiments, field measurements, and expansive simulations at various spatiotemporal scales. The field of machine learning (ML) provides a plethora of methods for gleaning insights from data that can be used to inform our understanding of the fluid dynamics at play. As an added bonus, ML algorithms can be used to automate duties associated with flow control and optimization, while also enhancing domain expertise. This article provides a review of the background, current state, and potential future applications of ML in fluid mechanics. We provide an introduction to the most fundamental ML approaches and describe their applications to the study, modelling, optimization, and management of fluid flows. From the standpoint of scientific inquiry, which treats data as an integral aspect of modelling, experiments, and simulations, the benefits and drawbacks of these approaches are discussed. Since ML provides a robust information-processing framework, it can supplement and potentially revolutionize conventional approaches to fluid mechanics study and industrial applications.
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Iman Fitri Ismail, Akmal Nizam Mohammed, Bambang Basuno, Siti Aisyah Alimuddin, and Mustafa Alas. "Evaluation of CFD Computing Performance on Multi-Core Processors for Flow Simulations." Journal of Advanced Research in Applied Sciences and Engineering Technology 28, no. 1 (September 11, 2022): 67–80. http://dx.doi.org/10.37934/araset.28.1.6780.
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Previous parallel computing implementations for Computational Fluid Dynamics (CFD) focused extensively on Complex Instruction Set Computer (CISC). Parallel programming was incorporated into the previous generation of the Raspberry Pi Reduced Instruction Set Computer (RISC). However, it yielded poor computing performance due to the processing power limits of the time. This research focuses on utilising two Raspberry Pi 3 B+ with increased processing capability compared to its previous generation to tackle fluid flow problems using numerical analysis and CFD. Parallel computing elements such as Secure Shell (SSH) and the Message Passing Interface (MPI) protocol were implemented for Advanced RISC Machine (ARM) processors. The parallel network was then validated by a processor call attempt and core execution test. Parallelisation of the processors enables the study of fluid flow and computational fluid dynamics (CFD) problems, such as validation of the NACA 0012 airfoil and an additional case of the Laplace equation for computing the temperature distribution via the parallel system. The experimental NACA 0012 data was validated using the parallel system, which can simulate the airfoil's physics. Each core was enabled and tested to determine the system's performance in parallelising the execution of various programming algorithms such as pi calculation. A comparison of the execution time for the NACA 0012 validation case yielded a parallelisation efficiency above 50%. The case studies confirmed the Raspberry Pi 3 B+'s successful parallelisation independent of external software and machines, making it a self-sustaining compact demonstration cluster of parallel computers for CFD.
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Madiba, Gislain B., and George A. McMechan. "Processing, inversion, and interpretation of a 2D seismic data set from the North Viking Graben, North Sea." GEOPHYSICS 68, no. 3 (May 2003): 837–48. http://dx.doi.org/10.1190/1.1581036.
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Simultaneous elastic impedance inversion is performed on the 2D North Viking Graben seismic data set used at the 1994 SEG workshop on amplitude variation with offset and inversion. P‐velocity (Vp), S‐velocity (Vs), density logs, and seismic data are input to the inversion. The inverted P‐impedance and S‐impedance sections are used to generate an approximate compressional‐to‐shear velocity ratio (Vp/Vs) section which, in turn, is used along with water‐filled porosity (Swv) derived from the logs from two wells, to generate fluid estimate sections. This is possible as the reservoir sands have fairly constant total porosity of approximately 28 ± 4%, so the hydrocarbon filled porosity is the total porosity minus the water‐filled porosity. To enhance the separation of lithologies and of fluid content, we map Vp/Vs into Swv using an empirical crossplot‐derived relation. This mapping expands the dynamic range of the low end of the Vp/Vs values. The different lithologies and fluids are generally well separated in the Vp/Vs–Swv domain. Potential hydrocarbon reservoirs (as calibrated by the well data) are identified throughout the seismic section and are consistent with the fluid content estimations obtained from alternative computations. The Vp/Vs–Swv plane still does not produce unique interpretation in many situations. However, the critical distinction, which is between hydrocarbon‐bearing sands and all other geologic/reservoir configurations, is defined. Swv ≤ 0.17 and Vp/Vs ≤ 1.8 are the criteria that delineate potential reservoirs in this area, with decreasing Swv indicating a higher gas/oil ratio, and decreasing Vp/Vs indicating a higher sand/shale ratio. As these criteria are locally calibrated, they appear to be valid locally; they should not be applied to other data sets, which may exhibit significantly different relationships. However, the overall procedure should be generally applicable.
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Psota, Pavel, Gramoz Çubreli, Jindřich Hála, David Šimurda, Petr Šidlof, Jan Kredba, Marek Stašík, et al. "Characterization of Supersonic Compressible Fluid Flow Using High-Speed Interferometry." Sensors 21, no. 23 (December 6, 2021): 8158. http://dx.doi.org/10.3390/s21238158.
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This paper presents a very effective interference technique for the sensing and researching of compressible fluid flow in a wind tunnel facility. The developed technique is very sensitive and accurate, yet easy to use under conditions typical for aerodynamic labs, and will be used for the nonintrusive investigation of flutter in blade cascades. The interferometer employs a high-speed camera, fiber optics, and available “of-the-shelf” optics and optomechanics. The construction of the interferometer together with the fiber optics ensures the high compactness and portability of the system. Moreover, single-shot quantitative data processing based on introducing a spatial carrier frequency and Fourier analysis allows for almost real-time quantitative processing. As a validation case, the interferometric system was successfully applied in the research of supersonic compressible fluid discharge from a narrow channel in a wind tunnel. Density distributions were quantitatively analyzed with the spatial resolution of about 50 μm. The results of the measurement revealed important features of the flow pattern. Moreover, the measurement results were compared with Computational Fluid Dynamics (CFD) simulations with a good agreement.
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Blandy Berenice Pamplona Solis, Julio César Cruz Argüello, Isaias May Canche, Leopoldo Gómez Barba, and Mayra Polett Gurrola. "CFD Analysis in the Mesh Modified Gas Diffusion Layer of a Proton Exchange Membrane Fuel Cell (PEMFC)." CFD Letters 16, no. 1 (November 29, 2023): 55–67. http://dx.doi.org/10.37934/cfdl.16.1.5567.
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Computational Fluid Dynamics (CFD) software is well known for its application feasibility as well as reliable results in modeling electrochemical, thermal, and fluid transport processes. CFD has been used to investigate the phenomena involved in the operation of fuel cells, providing a large amount of data that must be analyzed to improve cell efficiency. This paper aims to demonstrate that programming can be used in the post-processing phase, using scripts in Python language to automate data analysis, based on the results of the simulation of oxygen transport in Polymer Electrolyte Membrane Fuel Cell (PEMFC). The OpenFOAM open-source CFD tool solved the fluid governing equations through the SIMPLE algorithm of three proposed Gas Diffusion Layer (GDL) case studies. In this work, an algorithm is presented to extract, compute and visualize the post-process results, supporting the GDL selection.
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Boby Rachmat, Kristi Agust, Nur Indri Rahayu, M Muktiarni, and Tomoliyus. "Concept of Computational Fluid Dynamics and Its Application in Sport Science: Bibliometric Analysis of Modelling Thermal Comfort in Sport Hall." CFD Letters 16, no. 1 (November 29, 2023): 1–21. http://dx.doi.org/10.37934/cfdl.16.1.121.
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Computational Fluid Dynamics (CFD) has become a very effective tool in modeling and analyzing various complex phenomena, including being an integral part of analyzing thermal comfort phenomena. Therefore, this research was carried out to identify developments in the scientific literature related to research on sports science to carry out initial identification of sports hall thermal comfort modeling using dynamic computing concepts, analyzing trends and research focus in this field through bibliometrics. In addition, this research provides a comprehensive insight into the latest scientific contributions and developments in the field of sports science as an initial identification of sports hall thermal comfort modeling using a dynamic computing approach. Bibliometric analysis and theoretical analysis were chosen as research methods. This research also consists of five steps, namely (i) determining the theme and sources of research data; (ii) article data collection; (iii) data processing, (iv) bibliometric analysis, and (v) report preparation. "Computational Fluid Dynamics Design (CFD) in Sport Science" was used as a keyword in this research. Based on the search results, 823 documents were obtained from 1996 to 2023. Research on CFD in sports science will increase in 2022. Many countries, affiliates, and authors have contributed to increasing the number of publications on CFD in sports science, such as the United States with a total of 103 publications. With this research, it is hoped that it will provide insight to researchers, practitioners, and policymakers regarding research directions that may not have been fully explored in the application of CFD in the field of sports in particular, as well as other fields.
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Xu, Bin, Liwen Zhang, Weibin Zhang, Yilin Deng, and Teck Neng Wong. "Data-Driven Modal Decomposition Methods as Feature Detection Techniques for Flow Fields in Hydraulic Machinery: A Mini Review." Journal of Marine Science and Engineering 12, no. 5 (May 13, 2024): 813. http://dx.doi.org/10.3390/jmse12050813.
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Cavitation is a quasi-periodic process, and its non-stationarity leads to increasingly complex flow field structures. On the other hand, characterizing the flow field with greater precision has become increasingly feasible. However, accurately and effectively extracting the most representative vibration modes and spatial structures from these vast amounts of data has become a significant challenge. Researchers have proposed data-driven modal decomposition techniques to extract flow field information, which have been widely applied in various fields such as signal processing and fluid dynamics. This paper addresses the application of modal decomposition methods, such as dynamic mode decomposition (DMD), Proper Orthogonal Decomposition (POD), and Spectral Proper Orthogonal Decomposition (SPOD), in cavitation feature detection in hydraulic machinery. It reviews the mathematical principles of these three algorithms and a series of improvements made by researchers since their inception. It also provides examples of the applications of these three algorithms in different hydraulic machinery. Based on this, the future development trends and possible directions for the improvement of modal decomposition methods are discussed.
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Hashifatunnisa and S. Panggabean. "Study of Biodiesel Production Fluid Flow Patterns in LPD Type Static Mixing Reactors Using CFD Simulation for Sustainable Energy." IOP Conference Series: Earth and Environmental Science 977, no. 1 (June 1, 2022): 012064. http://dx.doi.org/10.1088/1755-1315/977/1/012064.
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Abstract Flow patterns can be analyzed accurately using a computational fluid dynamics model approach or CFD. The purpose of this study was to examine the pattern of fluid flow, pressure drop, fluid viscosity and FAME results in biodiesel production in a low pressure drop (LPD) static mixing reactor. The CFD method has three important stages, namely pre-processing (experimental data), solution search (boundary conditions and calculations) and post-processing (data presentation and validation). The simulation results show that the flow pattern occurred in turbulent flow with Reynolds number in each reactor above 3000 (Re > 3000). This research also produces a scenario that can reduce the pressure drop in the flow by performing a hole addition scenario, that successfully reduces the pressure drop by 5.13% compared to conventional LPD. Observations also show a decrease in viscosity in the hollow scenario with a decrease of 9.8% better than conventional LPD and an increase of 0.33% FAME in the scenario of adding holes. This study on biodiesel production can help increase the yield of better biodiesel with high quality and for the future can reduce or replace the use of non-renewable fossil fuels with renewable fuels so that the environment will remain sustainable.
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Lee, Yejee, and Hayoung Byun. "L-rCBF: Learning-Based Key–Value Data Structure for Dynamic Data Processing." Applied Sciences 13, no. 22 (November 7, 2023): 12116. http://dx.doi.org/10.3390/app132212116.
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Learning-based data structures, such as a learned Bloom filter and a learned functional Bloom filter (L-FBF), have recently been proposed to replace traditional structures. However, using these structures for dynamic data processing is difficult because a specific element cannot be deleted from a trained model. A counting Bloom filter with return values (rCBF) is a more efficient key–value structure than a functional Bloom filter (FBF) for repetitive insertions and deletions. In this study, we propose a learned rCBF (L-rCBF) comprising a model, a Bloom filter, and an rCBF and the deletion algorithm for the L-rCBF. To delete a specific element from the L-rCBF, two different operations are performed according to four different cases. In the experiments, the proposed L-rCBF is compared with a single rCBF and an L-FBF in terms of undeletables and search failures, and this comparison is conducted using two different models. In addition, we present a theoretical analysis of the rCBF with experimental results to demonstrate that a structure with an rCBF is more suitable for dynamic data than a structure with an FBF.
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Suwardana, R., A. P. Nugroho, Y. D. Prasetyatama, M. A. F. Falah, L. Sutiarso, and T. Okayasu. "Analysis of airflow distribution on urban mini plant factory using computational fluid dynamics." IOP Conference Series: Earth and Environmental Science 1116, no. 1 (December 1, 2022): 012029. http://dx.doi.org/10.1088/1755-1315/1116/1/012029.
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Abstract Limited land for agricultural cultivation in urban areas makes it difficult to fulfill for healthy and sustainable food. Mini Plant Factory is an alternative to produce food, especially vegetables. In the Mini Plant Factory, the distribution of air flow is one thing that must be considered because the air flow will affect the growth of the plants in it so it is necessary to do an analysis to determine the good air flow in the mini plant factory using Computational Fluid Dynamics (CFD) software. The purpose of this study was to analyse the aeration of the air flow in the mini plant factory using Computational Fluid Dynamics. This research was carried out at smart agriculture UGM, in this study using a mini plant factory measuring 70 x 40 x 150 cm, which is equipped with a temperature sensor (DHT 22) of 1 units in each shelf and 1 unit on the outside for measure environmental conditions, with a total number of 4 temperature sensors,, the mini plant factory is also equipped with an automatic nutrition system that is integrated with the cloud, and is equipped with artificial lighting. CFD analysis was carried out using the Ansys 2022 software, the laptop specifications used were AMD Ryzen 7 4800 H, NVIDIA GeForce RTX 3050. Temperature data was measured during the observation period. The analysis method in CFD has several stages, namely preparation, meshing workflow, mesh, models, materials, boundary conditions, solution and post-processing. The last part is data validation, namely by making a comparison between the CFD results and the actual data, then calculating the error value using MAPE. The expected result are visualisation various distribution of aeration temperatures inside mini plant factory, optimum aeration design for mini plant factory.
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Al-Kharusi, Ibrahim, and David W. Walker. "Locality properties of 3D data orderings with application to parallel molecular dynamics simulations." International Journal of High Performance Computing Applications 33, no. 5 (May 19, 2019): 998–1018. http://dx.doi.org/10.1177/1094342019846282.
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Application performance on graphical processing units (GPUs), in terms of execution speed and memory usage, depends on the efficient use of hierarchical memory. It is expected that enhancing data locality in molecular dynamic simulations will lower the cost of data movement across the GPU memory hierarchy. The work presented in this article analyses the spatial data locality and data reuse characteristics for row-major, Hilbert and Morton orderings and the impact these have on the performance of molecular dynamics simulations. A simple cache model is presented, and this is found to give results that are consistent with the timing results for the particle force computation obtained on NVidia GeForce GTX960 and Tesla P100 GPUs. Further analysis of the observed memory use, in terms of cache hits and the number of memory transactions, provides a more detailed explanation of execution behaviour for the different orderings. To the best of our knowledge, this is the first study to investigate memory analysis and data locality issues for molecular dynamics simulations of Lennard-Jones fluids on NVidia’s Maxwell and Tesla architectures.
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Pratiwi, Dian, and Agung Wiyono. "PEMANTAUAN PROSES INJEKSI AIR PADA LAPANGAN “SMR” CEKUNGAN SUMATERA TENGAH BERDASARKAN DATA ANOMALI TIME-LAPSE MICROGRAVITY." Jurnal Geofisika Eksplorasi 4, no. 1 (January 17, 2020): 112–25. http://dx.doi.org/10.23960/jge.v4i1.10.
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There had been done a regional research about monitoring of injection process in "SMR" field of Central Sumatera Basin using microgravity method. The time-lapse microgravity method is the development of the gravity method (x, y, z) by adding the fourth dimension of time (t). Monitoring is carried out on production fields that have performed EOR (Enchanced Oil Recovery) ie the process of injecting water into the reservoir to push and drain the remnants of oil in the pores of the reservoir rock to the production well. The microgravity data processing is done by finding the difference between observed gravity values between the first and the second measurements, then performing the spectral analysis to separate the anomaly at reservoir depth and noise. The time-lapse microgravity anomaly has a value of -132.28 μGal to 54.89 μGal. Positive anomalies are related to the injection process, whereas the negative anomalies are related to the production process in the study area. Filtering analysis shows that there are two zones of fluid dynamics, which is due to the process of surface water dynamics (groundwater above reservoir) and that occurs in the reservoir. Fluid reduction zones occur in areas with more production wells than injection wells. Density reduction occurs in the reservoir layer at a depth of 600 m to 1000 m with a maximum reduction value of -3.1x10-3 gr / cm3. The gravity time-lapse inversion model shows the existence of several injection wells that are less effective and therefore need to be stopped injecting.
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M Muktiarni, Nur Indri Rahayu, Ai Nurhayati, Andika Dutha Bachari, and Affero Ismail. "Concept of Computational Fluid Dynamics Design and Analysis Tool for Food Industry: A Bibliometric." CFD Letters 16, no. 2 (November 30, 2023): 1–23. http://dx.doi.org/10.37934/cfdl.16.2.123.
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Technology that is currently in demand is CFD. By simulating fluid flow around a product on a computer, the computational fluid dynamics (CFD) technique allows designers of new products to be tested. This research aims to analyze the bibliometrics of CFD publications as a design tool in the food industry to determine concepts, trends, and contributions of previous research. Computational Fluid Dynamics (CFD) is a technology used to test product designs through computer simulations of fluid flow around the product. The use of technology in various industries, such as the food industry, is essential to create better products or services. This research uses a bibliometric analysis method supported by theoretical analysis. This research consists of 5 steps, namely (i) determining the research theme for formulating keywords, (ii) collecting publication documents, (iii) data processing, (iv) bibliometric analysis, and (v) preparing a report. The keywords used in this research are "Computational Fluid Dynamics Design (CFD) in Food Industry." The results of the publication search found a total of 211 documents from 1992 to 2023. The average number of publications was 6.59. The trend of CFD publications in the food industry was first carried out in 1992. The development of this publication has been fluctuating, and there has been an increase in publications in the last five years (2019 - 2023). Research publications regarding CFD in the food industry are grouped into 20 subject areas. Contributions to this research consisted of 159 authors, 160 affiliates, and 51 countries. Completing this research will likely provide information regarding publication sources and contributions made by several scientists from various affiliates and countries worldwide.
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Nelson, Christopher C., Alan B. Cain, Robert Dougherty, Kenneth S. Brentner, and Philip J. Morris. "Application of synthetic array techniques for improved simulations of hot supersonic jet noise." International Journal of Aeroacoustics 16, no. 4-5 (July 2017): 382–402. http://dx.doi.org/10.1177/1475472x17718734.
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The synthetic array technique has previously been used to provide insight for developing improved microphone array data processing techniques. In recent work, however, it has also been successfully applied to diagnose the source of unexpected (and nonphysical) tones which arose in unsteady computational fluid dynamics (CFD) simulations of hot supersonic jets. The insight obtained from this method has allowed the authors to rapidly arrive at a strategy that greatly improves the results. This success opens up additional areas where the synthetic array technique can find application.
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VAN GENNIP, YVES, and CAROLA-BIBIANE SCHÖNLIEB. "Introduction: Big data and partial differential equations." European Journal of Applied Mathematics 28, no. 6 (November 7, 2017): 877–85. http://dx.doi.org/10.1017/s0956792517000304.
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Partial differential equations (PDEs) are expressions involving an unknown function in many independent variables and their partial derivatives up to a certain order. Since PDEs express continuous change, they have long been used to formulate a myriad of dynamical physical and biological phenomena: heat flow, optics, electrostatics and -dynamics, elasticity, fluid flow and many more. Many of these PDEs can be derived in a variational way, i.e. via minimization of an ‘energy’ functional. In this globalised and technologically advanced age, PDEs are also extensively used for modelling social situations (e.g. models for opinion formation, mathematical finance, crowd motion) and tasks in engineering (such as models for semiconductors, networks, and signal and image processing tasks). In particular, in recent years, there has been increasing interest from applied analysts in applying the models and techniques from variational methods and PDEs to tackle problems in data science. This issue of the European Journal of Applied Mathematics highlights some recent developments in this young and growing area. It gives a taste of endeavours in this realm in two exemplary contributions on PDEs on graphs [1, 2] and one on probabilistic domain decomposition for numerically solving large-scale PDEs [3].
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Franchetta, M., K. O. Suen, and T. G. Bancroft. "Pseudo-transient computational fluid dynamics analysis of an underbonnet compartment during thermal soak." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 221, no. 10 (October 1, 2007): 1209–20. http://dx.doi.org/10.1243/09544070jauto555.
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Underbonnet simulations are proving to be crucially important within a vehicle development programme, reducing test work and time-to-market. While computational fluid dynamics (CFD) simulations of steady forced flows have been demonstrated to be reliable, studies of transient convective flows in engine compartments are not yet carried out owing to high computing demands and lack of validated work. The present work assesses the practical feasibility of applying the CFD tool at the initial stage of a vehicle development programme for investigating the thermally driven flow in an engine bay under thermal soak. A computation procedure that enables pseudo time-marching CFD simulations to be performed with significantly reduced central processing unit (CPU) time usage is proposed. The methodology was initially tested on simple geometries and then implemented for investigating a simplified half-scale underbonnet compartment. The numerical results are compared with experimental data taken with thermocouples and with particle image velocimetry (PIV). The novel computation methodology is successful in efficiently providing detailed and time-accurate time-dependent thermal and flow predictions. Its application will extend the use of the CFD tool for transient investigations, enabling improvements to the component packaging of engine bays and the refinement of thermal management strategies with reduced need for in-territory testing.
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Collins, M. W. "Holographic techniques for whole-field thermal and fluid measurements." Aeronautical Journal 95, no. 949 (November 1991): 313–23. http://dx.doi.org/10.1017/s0001924000024192.
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SummaryMeasurement methods using holography are non-invasive, whole-field and can be applied in real-time. They are particularly appropriate for experimental validation of current CFD (computational fluid dynamics) codes which have 3-dimensional, transient, irregular geometry capabilities.In holographic interferometry, the fringes formed by refractive index changes represent lines of constant Mach number in isentropic compressible flows and isotherms in convection. Examples are given of two-dimensional inter-ferograms in these areas, and their quantitative interpretation.Automatic fringe and data processing is a necessity, and the method is extendable to three dimensions using tomographical reconstruction. These issues are discussed, together with the general question of comparison with flow predictions.Fluid fields may also be treated on a three-dimensional time-dependent basis, using HCV (holocinematographic velocimetry), a holographic extension of PIV (particle image velocimetry). It is proposeds to run an experiment to measure both fluid and thermal fields, and surface temperatures simultaneously, using HCV or PIV, holographic interferometry and liquid crystal methods respectively.
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Lu, Yu Liang, Yun Feng Zhao, and Bo Liang. "Performance Analysis of Centrifugal Compressor under Different Operation Conditions." Applied Mechanics and Materials 779 (July 2015): 133–40. http://dx.doi.org/10.4028/www.scientific.net/amm.779.133.
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Centrifugal compressor in bootstrap turbine cooler was studied to build computational model of flow domain for compressor component. The relationship between pressure ratio πc, efficiency ηc, flow rate G and rotational speed N was calculated by 3D numerical method. Experimental data were compared with the calculated results and good agreement was achieved. It indicated that performance characteristics of centrifugal compressor under off-Design condition could be predicted by computational fluid dynamics (CFD) technology. Furthermore, internal flow characteristics and load distribution could be visualized directly by CFD post processing graph.
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Begovic, Ermina, Carlo Bertorello, Raffaele Ponzini, and Francesco Salvadore. "Planing Hull Hydrodynamic Performance Prediction Using LincoSim Virtual Towing Tank." Journal of Marine Science and Engineering 12, no. 5 (May 9, 2024): 794. http://dx.doi.org/10.3390/jmse12050794.
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This work shows the performance of LincoSim, a web-based virtual towing tank enabling automated and standardized calm water computational fluid dynamics (CFD) data sampling, extending previous published applications to the case of a high-speed hull. The calculations are performed for a 1:10 scale model of a 43 ft powerboat hull form in the Froude number range from 0.3 to 2.0. The counterpart physical model is the experimental fluid dynamics (EFD) campaign performed at the University of Naples Federico II, where the resistance, sinkage and trim data have been measured. The EFD/CFD data comparison is performed and shown with a discussion of the spotted differences. The average percentage differences between the EFD and CFD data for the whole speed range are 1.84, 6.87 and 6.94 for the resistance, dynamic trim, and sinkage, respectively. These results confirm the maturity of the standardized and automated CFD modeling for calm water hydrodynamic analysis included in LincoSim, even at very high Froude numbers. The wetted length of the keel and chine and the wetted surface are calculated from numerical data using the advanced post-processing. Finally, as a work in progress, we test a first comparison for the same hull of the EFD and CFD data, considering two seakeeping conditions for head waves at a given wavelength for two velocity conditions. Also, this kind of analysis confirms the tight correlation between the measured and computed outcomes. This synergic interplay of EFD and CFD can link the advantages of both methods to support hull design but also requires experiment planning and final data analysis to obtain physical parameters not easily measurable in laboratory, such as the wetted surface, wetted lengths, proper viscous contribution, and pressure distribution both in calm water and in waves.
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Kubík, M., K. Šebesta, Z. Strecker, F. Jeniš, J. Goldasz, and I. Mazůrek. "Hydrodynamic response time of magnetorheological fluid in valve mode: model and experimental verification." Smart Materials and Structures 30, no. 12 (November 11, 2021): 125020. http://dx.doi.org/10.1088/1361-665x/ac3437.
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Abstract The transient behaviour of magnetorheological (MR) actuators affects their performance in progressive semiactive control suspension systems. The two sources of the time delay between the control signal and damping force are (a) dynamics of MR damper hardware and (b) the MR fluid dynamics. The significant part of the MR fluid response time is the so-called hydrodynamic response time which is connected with the transient flow. Due to the above, the main aim of this paper is to experimentally determine the hydrodynamic response time of MR fluid and present systematic means for characterizing it via computational fluid dynamics (CFD) or analytical tools. The unique measurement method using an in-house patented slit flow rheometer is presented. The essence of the method relies on determining the pressure drop variation with the time spent by the fluid in the MR gap. The experimental determined hydrodynamic response time of MR fluid ranges from 0.4 to 1 ms for a selected gap size and a range of magnetic field stimuli. The results show that the higher the magnetic field, the lower the hydrodynamic response time is. Both CFD and analytical models exhibit similar trends as the experimental data. Moreover, the impact of temperature and gap size was determined. Here, the higher the gap size and temperature of MR fluid, the longer the response time is.
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Dreier, Christian, and Michael Vorländer. "Sound source modelling by nonnegative matrix factorization for virtual reality applications." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 5 (August 1, 2021): 1053–61. http://dx.doi.org/10.3397/in-2021-1742.
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Auralization is a suitable method for subjective noise evaluation of virtual prototypes. A basic requirement is the accurate modelling of the sound sources. This includes a dynamic and parametric description at multiple operating conditions. In the case of wave propagation including flow, such as aircraft or vehicle noise, aeroacoustics or fluid dynamics simulations are practically limited to the acoustic near field due to high computational costs. Especially challenging are simulations of rotating systems, such as fan noise radiation. For better applicability, the proposed method is based on in-situ recordings of flyovers. The processing chain compensates for source position and movement as well as atmospheric and soil damping effects on recorded data. The compensated source signal is decomposed into partial sources in spectro-temporal domain with nonnegative matrix factorization (NMF) and can optionally be enhanced by physically-based source information. The format of the source model obtained is ready to use for dynamic sound synthesis in real-time virtual reality applications.
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Williams, Kyle, Stephen Rudin, Daniel Bednarek, Ammad Baig, Adnan Hussain Siddiqui, Elad I. Levy, and Ciprian Ionita. "226 Advancing Neurovascular Diagnostics for Abnormal Hemodynamic Conditions Through AI-Driven Physics-informed Neural Networks." Neurosurgery 70, Supplement_1 (April 2024): 61. http://dx.doi.org/10.1227/neu.0000000000002809_226.
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INTRODUCTION: Many studies have explored the application of machine learning and neural networks in extracting critical diagnostic information from structural and functional medical imaging. While these methods show potential for improving efficiency, concerns arise when interpreting subtle imaging features, especially when training data is limited. Physics-informed neural networks (PINNs) address these issues by incorporating governing equations from physical and mechanical models into the analysis. METHODS: We examined the use of a PINN that enforces the convection equation, relating contrast media propagation to blood velocity, the Navier-Stokes equations for velocity and pressure distributions, and the conservation of mass requirement to calculate velocity and pressure distributions within patient-specific blood vessels. We also implemented a boundary condition that accounts for real contrast-media propagation from 1000 fps high-speed angiographic (HSA) image sequences, allowing for an assumption-free problem space within a medical imaging framework. Velocity fields and pressure gradients were calculated for flow in aneurysms and carotid bifurcations. RESULTS: Our method demonstrates comparable results to computational fluid dynamics (CFD) without requiring manual data processing, significantly improving the efficiency of calculating high-resolution velocity and pressure fields. By integrating AI with physics modeling, this novel approach holds the potential for advancing neurovascular diagnostics and providing more accurate, personalized treatment plans for patients with neurovascular pathologies. CONCLUSIONS: This innovative approach, integrating physics modeling and artificial intelligence, offers more accurate and personalized diagnostics for patients with neurovascular pathologies. The PINN method not only achieves results comparable to computational fluid dynamics without the need for manual data processing but also greatly enhances the efficiency of calculating high-resolution velocity and pressure fields.
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Alvarenga, Nuno, João Martins, José Caeiro, João Garcia, João Pássaro, Luis Coelho, Maria Teresa Santos, Célia Lampreia, António Martins, and João Dias. "Applying Computational Fluid Dynamics in the Development of Smart Ripening Rooms for Traditional Cheeses." Foods 10, no. 8 (July 23, 2021): 1716. http://dx.doi.org/10.3390/foods10081716.
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Traditional ewe’s cheese producers face certain challenges caused by fluctuating environmental parameters inside the ripening room, which lead to lack of homogeneity in the final product. The present research discusses the application of computer fluid dynamics for simulating the distribution of environmental parameters, predicting the airflow pattern, and identifying critical areas where such parameters could cause reduced cheese quality. A new monitoring system was developed including presence sensors, temperature and humidity dataloggers, pneumatic actuators, microcontrollers, and microcomputers connected remotely for control, data visualization, and processing. The validation of the computer simulation and monitoring system was made with a batch of 40 ewe’s cheeses distributed in three different zones inside a prototype ripening room and ripened for 35 days. At 35 days, a physical, chemical, and microbiological characterization of cheeses was made for evaluation of the influence of environmental conditions on cheese quality. The comparison between simulated and local measurements showed close agreement, especially concerning air velocity inside the stacks of cheese. The results of Pearson’s correlation analysis and PCA concluded that temperature affected the appearance of the rind, hardness, number and area occupied by holes. Humidity affected aw and mFeret. Air velocity affected pH and the circularity of gas holes.
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Luo, Robert K., Ping Lou, Weidong Wang, and Naizheng Guo. "Natural Frequency Region – Fluid-Structural-Interaction approach for dynamic impact predictions and experimental verification of rubber–metal bonded systems with fluid." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 233, no. 2 (July 22, 2018): 211–19. http://dx.doi.org/10.1177/0954409718788902.
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This paper presents an integrated procedure for dynamic impact predictions and an experimental verification of rubber–metal bonded components with fluid to be used as a potential application in rail vehicle suspensions. There are three steps involved in the procedure. First, a quasi-static analysis was performed to verify the elastic properties of the rubber material using hyperelastic models. Second, a dynamic impact evaluation on selected hydro-mounts without fluid was conducted using the Natural Frequency Region (NFR) approach. Finally, a coupled NFR (with Fluid-Structural-Interaction) approach, different from the usual viscoelastic methods, was initiated to predict the dynamic impact responses of these components with the fluid in time domain. All the analyses have been validated with experimental data. The first two stages have been briefly described and the third stage is detailed in this paper. It should be noted that a powerful computer with multi-central processing units is essential to obtain a reasonable result within an acceptable time frame. It took approximately 40 h wall-clock time to complete the analysis using a workstation with 10 central processing units. It has been suggested that the natural frequency region–fluid–structure interaction methodology is reliable and could be used at the design stage and for engineering applications.
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Turiel, Antonio, Jordi Isern-Fontanet, and Emilio García-Ladona. "Wavelet Filtering to Extract Coherent Vortices from Altimetric Data." Journal of Atmospheric and Oceanic Technology 24, no. 12 (December 1, 2007): 2103–19. http://dx.doi.org/10.1175/2007jtecho434.1.
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Abstract Because of the optimal features of wavelet processing, the use of wavelets for describing and analyzing signals in 2D turbulence has been generalized since a decade ago. In spite of the close analogy between 2D turbulence and geophysical fluid dynamics, few works have tried to generalize the rich framework of wavelet techniques to the study of experimental signals in oceanography. In this paper, the authors extend a prominent wavelet technique designed for the study of direct numerical simulations (DNSs) on 2D turbulence, the coherent vortex simulation, and analyze with it ocean velocity fields obtained from sea surface height maps derived from satellite altimetry. The authors demonstrate the pertinence of this technique to describe altimetry data, resulting in a description of oceanic flows with a reduced number of degrees of freedom. In particular, it is shown that the western Mediterranean circulation is well approximated by a field of extracted coherent vortices when an appropriate wavelet basis is employed as a filter; however, about one-third of the energy is lost in this description, evidencing important differences between results obtained on the frame of 2D turbulence and oceanic data.
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Ishiwatari, M., E. Toyoda, Y. Morikawa, S. Takehiro, Y. Sasaki, S. Nishizawa, M. Odaka, et al. ""Gtool5": a Fortran90 library of input/output interfaces for self-descriptive multi-dimensional numerical data." Geoscientific Model Development 5, no. 2 (April 3, 2012): 449–55. http://dx.doi.org/10.5194/gmd-5-449-2012.
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Abstract. A Fortran90 input/output library, "gtool5", is developed for use with numerical simulation models in the fields of Earth and planetary sciences. The use of this library will simplify implementation of input/output operations into program code in a consolidated form independent of the size and complexity of the software and data. The library also enables simple specification of the metadata needed for post-processing and visualization of the data. These aspects improve the readability of simulation code, which facilitates the simultaneous performance of multiple numerical experiments with different software and efficiency in examining and comparing the numerical results. The library is expected to provide a common software platform to reinforce research on, for instance, the atmosphere and ocean, where a close combination of multiple simulation models with a wide variety of complexity of physics implementations from massive climate models to simple geophysical fluid dynamics models is required.
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Ishiwatari, M., E. Toyoda, Y. Morikawa, S. Takehiro, Y. Sasaki, S. Nishizawa, M. Odaka, et al. ""Gtool5": a Fortran90 library of input/output interfaces for self-descriptive multi-dimensional numerical data." Geoscientific Model Development Discussions 4, no. 4 (December 19, 2011): 3691–707. http://dx.doi.org/10.5194/gmdd-4-3691-2011.
Full textAbstract:
Abstract. A Fortran90 input/output library, "gtool5", is developed for use with numerical simulation models in the fields of Earth and planetary sciences. The use of this library will simplify implementation of input/output operations into program code in a consolidated form independent of the size and complexity of the software and data. The library also enables simple specification of the metadata needed for post-processing and visualization of the data. These aspects improve the readability of simulation code, which facilitates the simultaneous performance of multiple numerical experiments with different software and efficiency in examining and comparing the numerical results. The library is expected to provide a common software platform to reinforce research on, for instance, the atmosphere and ocean, where a close combination of multiple simulation models with a wide variety of complexity of physics implementations from massive climate models to simple geophysical fluid dynamics models is required.
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Suárez , Gustavo, and Juan David Velásquez. "Distributed Consensus for Global Matrix Formation in the Principal Component Pursuit Scenario." Applied Sciences 14, no. 9 (April 25, 2024): 3619. http://dx.doi.org/10.3390/app14093619.
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The aim behind principal component pursuit is to recover a low-rank matrix and a sparse matrix from a noisy signal which is the sum of both matrices. This optimization problem is a priori and non-convex and is useful in signal processing, data compression, image processing, machine learning, fluid dynamics, and more. Here, a distributed scheme described by a static undirected graph, where each agent only observes part of the noisy or corrupted matrix, is applied to achieve a consensus; then, a robust approach that can also handle missing values is applied using alternating directions to solve the convex relaxation problem, which actually solves the non-convex problem under some weak assumptions. Some examples of image recovery are shown, where the network of agents achieves consensus exponentially fast.
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Cioroiu, Doinita Roxana, Oana Cristina Parvulescu, Claudia Irina Koncsag, Tanase Dobre, and Cristian Raducanu. "Rheological Characterization of Algal Suspensions for Bioethanol Processing." Revista de Chimie 68, no. 10 (November 15, 2017): 2311–16. http://dx.doi.org/10.37358/rc.17.10.5875.
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The paper has aimed at studying the rheology of macroalgae aqueous suspensions in the presence of cellulase enzyme relevant to bioethanol processing by a subsequent fermentation. Rheological measurements of aqueous suspensions of Ceramium virgatum and Cladophora vagabunda macroalgae species were performed using a Couette geometry rotational viscosimeter. The effects of operation temperature (t=25, 50 �C), cellulase/dried algae ratio (R=0, 16 U/mgda), and algal suspension mass concentration (c=5-15%) on rheological behaviour and parameters were evaluated. Algal suspensions behaved as non-Newtonian fluids obeying either a Bingham plastic linear relationship or an Ostwald-de Waele power law corresponding to a pseudoplastic fluid. Characteristic dynamic viscosity of Bingham plastic fluids were in the range 0.045-0.115 Pa�s for C. virgatum suspensions and 0.021-0.114 Pa�s for C. vagabunda ones, whereas apparent viscosity varied from 0.138 Pa�s to 43.551 Pa�s for C. virgatum and from 0.181 Pa�s to 45.417 Pa�s for C. vagabunda. Data obtained in 8 rheological tests corresponding to a Bingham plastic behaviour of C. vagabunda suspensions, which were processed according to a 23 factorial experiment, emphasized an increase in suspension viscosity with all process factors. The results could be useful for optimization of enzymatic hydrolysis process in order to develop efficient and cost effective saccharification and fermentation strategies.
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Oleynik, Andrey G., Valeri V. Birukov, and Roman N. Nikitin. "Initial stage of a mathematical model development for real-time control of magnetic-gravitational separation." Transactions of the Kоla Science Centre of RAS. Series: Engineering Sciences 14, no. 7/2023 (February 27, 2024): 102–11. http://dx.doi.org/10.37614/2949-1215.2023.14.7.011.
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The initial stage of the mathematical model development designed to control in real time the enrichment of magnetite ores in magnetic gravity separators is presented the article. A significantly lower computational complexity in comparison with models using computational fluid dynamics tools is a main requirement for the created model. The study uses physical modeling and applies similarity criteria which well-known in hydrodynamics. As a result of processing of the laboratory experiments data, the structure of the model was established, the values of its parameters for boundary cases were obtained and the directions of further research on improving the model were determined.