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1

Bhattacharjee, Binita, Douglas A. Schwer, Paul I. Barton, and William H. Green. "Optimally-reduced kinetic models: reaction elimination in large-scale kinetic mechanisms." Combustion and Flame 135, no. 3 (2003): 191–208. http://dx.doi.org/10.1016/s0010-2180(03)00159-7.

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Nikolaev, Evgeni V., Priti Pharkya, Costas D. Maranas, and Antonios Armaou. "OPTIMAL SELECTION OF ENZYME LEVELS USING LARGE-SCALE KINETIC MODELS." IFAC Proceedings Volumes 38, no. 1 (2005): 25–30. http://dx.doi.org/10.3182/20050703-6-cz-1902.02208.

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Herty, Michael, and Christian Ringhofer. "Large time behavior of averaged kinetic models on networks." Mathematical Models and Methods in Applied Sciences 25, no. 05 (2015): 875–904. http://dx.doi.org/10.1142/s0218202515500219.

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We are interested in flows on general networks and derive a kinetic equation describing general production, social or transportation networks. Corresponding macroscopic transport equations for large time and homogenized behavior are obtained and studied numerically. This work continues a recent discussion [Averaged kinetic models for flows on unstructured networks, Kinetic Related Models 4 (2011) 1081–1096] and provides additionally explicit equilibrium solutions, second-order macroscopic approximations as well as numerical simulations on a large scale homogenized network.
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Zhang, Lei, Xiao Han, Xinbin Zhang, and Jihong Yan. "Door-Triggering Mechanism for Large-Scale Rapid-Decompression Experiments." International Journal of Aerospace Engineering 2020 (August 1, 2020): 1–9. http://dx.doi.org/10.1155/2020/6841651.

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For large-scale rapid-decompression experiments, a new door-triggering mechanism is proposed for a 750 mm diameter pressure relief channel. Quick opening of the door is realized by utilizing a spring-based release mechanism to instantly convert large amounts of elastic potential energy into kinetic energy. To counteract the significant inertial effect of the high-speed door on the chamber, a flywheel-based cushioning mechanism is designed to absorb the kinetic energy of the door after opening. This carefully designed mechanism consists of the closing mechanism, energy storage unit, locking/rel
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Berkemeier, Thomas, Matteo Krüger, Aryeh Feinberg, Marcel Müller, Ulrich Pöschl, and Ulrich K. Krieger. "Accelerating models for multiphase chemical kinetics through machine learning with polynomial chaos expansion and neural networks." Geoscientific Model Development 16, no. 7 (2023): 2037–54. http://dx.doi.org/10.5194/gmd-16-2037-2023.

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Abstract. The heterogeneous chemistry of atmospheric aerosols involves multiphase chemical kinetics that can be described by kinetic multi-layer models (KMs) that explicitly resolve mass transport and chemical reactions. However, KMs are computationally too expensive to be used as sub-modules in large-scale atmospheric models, and the computational costs also limit their utility in inverse-modeling approaches commonly used to infer aerosol kinetic parameters from laboratory studies. In this study, we show how machine learning methods can generate inexpensive surrogate models for the kinetic mu
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Gábor, Attila, Alejandro F. Villaverde, and Julio R. Banga. "Parameter identifiability analysis and visualization in large-scale kinetic models of biosystems." BMC Systems Biology 11, no. 1 (2017): 54. https://doi.org/10.1186/s12918-017-0428-y.

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<strong>Background: </strong>Kinetic models of biochemical systems usually consist of ordinary differential equations that have many unknown parameters. Some of these parameters are often practically unidentifiable, that is, their values cannot be uniquely determined from the available data. Possible causes are lack of influence on the measured outputs, interdependence among parameters, and poor data quality. Uncorrelated parameters can be seen as the key tuning knobs of a predictive model. Therefore, before attempting to perform parameter estimation (model calibration) it is important to char
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Adiamah, Delali A., Julia Handl, and Jean-Marc Schwartz. "Streamlining the construction of large-scale dynamic models using generic kinetic equations." Bioinformatics 26, no. 10 (2010): 1324–31. http://dx.doi.org/10.1093/bioinformatics/btq136.

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Li, Kuijun, Priyadarshi Mahapatra, K. Sham Bhat, David C. Miller, and David S. Mebane. "Multi-scale modeling of an amine sorbent fluidized bed adsorber with dynamic discrepancy reduced modeling." Reaction Chemistry & Engineering 2, no. 4 (2017): 550–60. http://dx.doi.org/10.1039/c7re00040e.

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van Lent, Paul, Olga Bunkova, Bálint Magyar, Léon Planken, Joep Schmitz, and Thomas Abeel. "Jaxkineticmodel: Neural ordinary differential equations inspired parameterization of kinetic models." PLOS Computational Biology 21, no. 7 (2025): e1012733. https://doi.org/10.1371/journal.pcbi.1012733.

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Motivation: Metabolic kinetic models are widely used to model biological systems. Despite their widespread use, it remains challenging to parameterize these Ordinary Differential Equations (ODE) for large scale kinetic models. Recent work on neural ODEs has shown the potential for modeling time-series data using neural networks, and many methodological developments in this field can similarly be applied to kinetic models. Results: We have implemented a simulation and training framework for Systems Biology Markup Language (SBML) models using JAX/Diffrax, which we named jaxkineticmodel. JAX allo
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Cancellieri, Dominique, Valérie Leroy-Cancellieri, Xavier Silvani, and Frédéric Morandini. "New experimental diagnostics in combustion of forest fuels: microscale appreciation for a macroscale approach." Natural Hazards and Earth System Sciences 18, no. 7 (2018): 1957–68. http://dx.doi.org/10.5194/nhess-18-1957-2018.

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Abstract. In modelling the wildfire behaviour, good knowledge of the mechanisms and the kinetic parameters controlling the thermal decomposition of forest fuel is of great importance. The kinetic modelling is based on the mass-loss rate, which defines the mass-source term of combustible gases that supply the flames and influences the propagation of wildland fires. In this work, we investigated the thermal degradation of three different fuels using a multi-scale approach. Lab-scale experimental diagnostics such as thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), use of
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LU, HAO, CHRISTOPHER J. RUTLAND, and LESLIE M. SMITH. "A POSTERIORI TESTS OF ONE-EQUATION LES MODELING OF ROTATING TURBULENCE." International Journal of Modern Physics C 19, no. 12 (2008): 1949–64. http://dx.doi.org/10.1142/s0129183108013394.

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Eight subgrid-scale (SGS) models were evaluated using two flow configurations: homogeneous decaying turbulence, and rotating turbulence forced at large or intermediate scales. Testing was performed for the first configuration through a systematic comparison between direct numerical simulation results and large eddy simulation results of many characteristics, including resolved kinetic energy, SGS energy production, molecular dissipation, and kinetic energy spectrum. The new models, which are based on dynamic structure model and satisfy the consistency of material frame indifference with the SG
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12

Samira, Hotić, Matijašić Gordana, and Perviz Osman. "Kinetics of dolomite grinding in a laboratory ball mill." Technologica Acta 15, no. 1 (2022): 29–37. https://doi.org/10.5281/zenodo.6918933.

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Grinding is one of the most widely used methods of obtaining solid particles of controled/ desired distribution systems in all branches of industry. Enlargement of this process is often based on experience and on trial and error methods that requires a large number of experiments. The development of mathematical models enabled the transfer of results to a larger scale in similar systems. The proposed researches were conducted in a laboratory scale. The modeling of the grinding process by the population balance included a description of the kinetics of dolomite grinding by kinetic parameters an
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Miskovic, Ljubisa, Susanne Alff-Tuomala, Keng Cher Soh, et al. "A design–build–test cycle using modeling and experiments reveals interdependencies between upper glycolysis and xylose uptake in recombinant S. cerevisiae and improves predictive capabilities of large-scale kinetic models." Biotechnology for Biofuels 10, no. 1 (2017): 166. https://doi.org/10.1186/s13068-017-0838-5.

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<strong>Background: </strong>Recent advancements in omics measurement technologies have led to an ever-increasing amount of available experimental data that necessitate systems-oriented methodologies for efficient and systematic integration of data into consistent large-scale kinetic models. These models can help us to uncover new insights into cellular physiology and also to assist in the rational design of bioreactor or fermentation processes. Optimization and Risk Analysis of Complex Living Entities (ORACLE) framework for the construction of large-scale kinetic models can be used as guidanc
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14

Remli, Muhammad Akmal, Mohd Saberi Mohamad, Safaai Deris, Richard Sinnott, and Suhaimi Napis. "An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems." Current Proteomics 16, no. 5 (2019): 427–38. http://dx.doi.org/10.2174/1570164616666190401203128.

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Background: Mathematical models play a central role in facilitating researchers to better understand and comprehensively analyze various processes in biochemical systems. Their usage is beneficial in metabolic engineering as they help predict and improve desired products. However, one of the primary challenges in model building is parameter estimation. It is the process to find nearoptimal values of kinetic parameters which may culminate in the best fit of model prediction to experimental data. Methods: This paper proposes an improved scatter search algorithm to address the challenging paramet
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15

Yang, Qian, Carlos A. Sing-Long, and Evan J. Reed. "Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics." Chemical Science 8, no. 8 (2017): 5781–96. http://dx.doi.org/10.1039/c7sc01052d.

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We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD).
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Schofield, Keith. "Large Scale Chemical Kinetic Models of Fossil Fuel Combustion: Adequate as Engineering Models—No More, No Less." Energy & Fuels 26, no. 9 (2012): 5468–80. http://dx.doi.org/10.1021/ef300858s.

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Ramon, Charlotte, Mattia G. Gollub, and Jörg Stelling. "Integrating –omics data into genome-scale metabolic network models: principles and challenges." Essays in Biochemistry 62, no. 4 (2018): 563–74. http://dx.doi.org/10.1042/ebc20180011.

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At genome scale, it is not yet possible to devise detailed kinetic models for metabolism because data on the in vivo biochemistry are too sparse. Predictive large-scale models for metabolism most commonly use the constraint-based framework, in which network structures constrain possible metabolic phenotypes at steady state. However, these models commonly leave many possibilities open, making them less predictive than desired. With increasingly available –omics data, it is appealing to increase the predictive power of constraint-based models (CBMs) through data integration. Many corresponding m
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18

Nguyen Dang Binh, Thanh, Dung Nguyen Trung, and Duc Hong Ta. "MODELING OF ESSENTIAL OIL EXTRACTION PROCESS: APPLICATION FOR ORANGE, POMELO, AND LEMONGRASS." Vietnam Journal of Science and Technology 56, no. 4A (2018): 182. http://dx.doi.org/10.15625/2525-2518/56/4a/12811.

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ABSTRACT - HCTN - 44In this study, the kinetic models of steam distillation of orange (Citrus Sinensis (L.) Osbeck), pomelo (Citrus grandis L.), and lemongrass (Cymbopogon Citratus) for the recovery of essential oils were developed. The model parameters were estimated based on experimental data and comprehensive kinetic mechanisms of the solid-liquid extraction process. Numerical results showed that, the extraction mechanism of the three materials were best fit to the Patricelli two-stage model in which the diffusion of the oil was followed by the washing step. Moreover, the model parameters o
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19

Burini, D., and N. Chouhad. "Hilbert method toward a multiscale analysis from kinetic to macroscopic models for active particles." Mathematical Models and Methods in Applied Sciences 27, no. 07 (2017): 1327–53. http://dx.doi.org/10.1142/s0218202517400176.

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This paper develops a Hilbert type method to derive models at the macroscopic scale for large systems of several interacting living entities whose statistical dynamics at the microscopic scale is delivered by kinetic theory methods. The presentation is in three steps, where the first one presents the structures of the kinetic theory approach used toward the aforementioned analysis; the second step presents the mathematical method; while the third step provides a number of specific applications. The approach is focused on a simple system and with a binary mixture, where different time-space sca
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Azorakos, Georgios, Bjarke Eltard Larsen, and David R. Fuhrman. "NEW METHODS FOR STABILIZING RANS TURBULENCE MODELS WITH APPLICATION TO LARGE SCALE BREAKING WAVES." Coastal Engineering Proceedings, no. 36v (December 28, 2020): 19. http://dx.doi.org/10.9753/icce.v36v.waves.19.

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Recently, Larsen and Fuhrman (2018) have shown that seemingly all commonly used (both k-omega and k-epsilon variants) two-equation RANS turbulence closure models are unconditionally unstable in the potential flow beneath surface waves, helping to explain the wide-spread over-production of turbulent kinetic energy in CFD simulations, relative to measurements. They devised and tested a new formally stabilized formulation of the widely used k-omega turbulence model, making use of a modified eddy viscosity. In the present work, three new formally-stable k-omega turbulence model formulations are de
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21

Bellomo, N., A. Bellouquid, and N. Chouhad. "From a multiscale derivation of nonlinear cross-diffusion models to Keller–Segel models in a Navier–Stokes fluid." Mathematical Models and Methods in Applied Sciences 26, no. 11 (2016): 2041–69. http://dx.doi.org/10.1142/s0218202516400078.

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This paper deals with a micro–macro derivation of a variety of cross-diffusion models for a large system of active particles. Some of the models at the macroscopic scale can be viewed as developments of the classical Keller–Segel model. The first part of the presentation focuses on a survey and a critical analysis of some phenomenological models known in the literature. The second part is devoted to the design of the micro–macro general framework, where methods of the kinetic theory are used to model the dynamics of the system including the case of coupling with a fluid. The third part deals w
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22

Pererva, Yehor, Charles D. Miller, and Ronald C. Sims. "Existing Empirical Kinetic Models in Biochemical Methane Potential (BMP) Testing, Their Selection and Numerical Solution." Water 12, no. 6 (2020): 1831. http://dx.doi.org/10.3390/w12061831.

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Biochemical Methane Potential (BMP) tests are a crucial part of feasibility studies to estimate energy recovery opportunities from organic wastes and wastewater. Despite the large number of publications dedicated to BMP testing and numerous attempts to standardize procedures, there is no “one size fits all” mathematical model to describe biomethane formation kinetic precisely. Importantly, the kinetics models are utilized for treatability estimation and modeling processes for the purpose of scale-up. A numerical computation approach is a widely used method to determine model coefficients, as a
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23

Winkler, C. M., and Sarma L. Rani. "Evaluation of subgrid scale kinetic energy models in large eddy simulations of turbulent channel flow." International Journal of Numerical Methods for Heat & Fluid Flow 16, no. 2 (2006): 226–39. http://dx.doi.org/10.1108/09615530610644280.

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Di Maggio, Jimena, Cecilia Paulo, Vanina Estrada, Nora Perotti, Juan C. Diaz Ricci, and M. Soledad Diaz. "Parameter estimation in kinetic models for large scale biotechnological systems with advanced mathematical programming techniques." Biochemical Engineering Journal 83 (February 2014): 104–15. http://dx.doi.org/10.1016/j.bej.2013.12.012.

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Zhang, Chao, Zelong Yuan, Yunpeng Wang, Ruibo Zhang, and Jianchun Wang. "Density-unweighted subgrid-scale models for large-eddy simulations of compressible turbulence." Physics of Fluids 34, no. 6 (2022): 065137. http://dx.doi.org/10.1063/5.0095726.

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Density-unweighted methods in large-eddy simulations (LES) of turbulence have received little attention, and the modeling of unclosed terms using density-unweighted methods even less. We investigate the density-unweighted subgrid-scale (SGS) closure problem for LES of decaying compressible isotropic turbulence at initial turbulent Mach numbers 0.4 and 0.8. Compared to the LES with Favre (density-weighted) filtering, there are more unclosed SGS terms for density-unweighted LES, which can be reconstructed using different SGS models, including the gradient model (GM), approximate deconvolution mo
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Clark, Teresa J., Longyun Guo, John Morgan, and Jorg Schwender. "Modeling Plant Metabolism: From Network Reconstruction to Mechanistic Models." Annual Review of Plant Biology 71, no. 1 (2020): 303–26. http://dx.doi.org/10.1146/annurev-arplant-050718-100221.

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Mathematical modeling of plant metabolism enables the plant science community to understand the organization of plant metabolism, obtain quantitative insights into metabolic functions, and derive engineering strategies for manipulation of metabolism. Among the various modeling approaches, metabolic pathway analysis can dissect the basic functional modes of subsections of core metabolism, such as photorespiration, and reveal how classical definitions of metabolic pathways have overlapping functionality. In the many studies using constraint-based modeling in plants, numerous computational tools
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Laperre, B., J. Amaya, S. Jamal, and G. Lapenta. "Identification of high order closure terms from fully kinetic simulations using machine learning." Physics of Plasmas 29, no. 3 (2022): 032706. http://dx.doi.org/10.1063/5.0066397.

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Simulations of large-scale plasma systems are typically based on a fluid approximation approach. These models construct a moment-based system of equations that approximate the particle-based physics as a fluid, but as a result, they lack the small-scale physical processes available to fully kinetic models. Traditionally, empirical closure relations are used to close the moment-based system of equations, which typically approximate the pressure tensor or heat flux. The more accurate the closure relation, the stronger the simulation approaches kinetic-based results. In this paper, new closure te
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Dai, Qiang, Jingxuan Zhu, Shuliang Zhang, Shaonan Zhu, Dawei Han, and Guonian Lv. "Estimation of rainfall erosivity based on WRF-derived raindrop size distributions." Hydrology and Earth System Sciences 24, no. 11 (2020): 5407–22. http://dx.doi.org/10.5194/hess-24-5407-2020.

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Abstract. Soil erosion can cause various ecological problems, such as land degradation, soil fertility loss, and river siltation. Rainfall is the primary water-driven force for soil erosion, and its potential effect on soil erosion is reflected by rainfall erosivity that relates to the raindrop kinetic energy. As it is difficult to observe large-scale dynamic characteristics of raindrops, all the current rainfall erosivity models use the function based on rainfall amount to represent the raindrops' kinetic energy. With the development of global atmospheric re-analysis data, numerical weather p
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Santoni, Christian, Fotis Sotiropoulos, and Ali Khosronejad. "A Comparative Analysis of Actuator-Based Turbine Structure Parametrizations for High-Fidelity Modeling of Utility-Scale Wind Turbines under Neutral Atmospheric Conditions." Energies 17, no. 3 (2024): 753. http://dx.doi.org/10.3390/en17030753.

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This study compared the efficacy of the actuator line and actuator surface models in carrying out large-eddy simulations of a utility-scale wind turbine. A large-eddy simulation with the actuator surface and line models was employed to study the wake flow and power production of the turbine. While both the actuator models were employed for the blade representation, the nacelle was modeled using the actuator surface approach. Both of the actuator models demonstrated agreement in the mean velocity field, power production, and turbulence kinetic energy of the wake flow. Comparing the wake flow, p
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Sun, Dong Gou, Bing Huang, Wen Gang Zuo, Huai Yuan Zhao, Wen Wei, and Jing Deng. "Kinetic Models of Hydrogen Production Process by Batch Anaerobic Fermentation from Contained Sugar Wastewater." Advanced Materials Research 634-638 (January 2013): 981–86. http://dx.doi.org/10.4028/www.scientific.net/amr.634-638.981.

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The processes of biomass growth, hydrogen production and sucrose degradation were systemically investigated about batch anaerobic fermentation which is based on activated sludge for a basic strain and the simulating sucrose wastewater for a substrate. The kinetics of microbial growth, hydrogen production and sucrose degradation were proposed according to the Compertz equation and the Luedeking-Piret equation. The relationship between the biomass, hydrogen and substrate were also evaluated. The results shown that the hydrogen is a main produce of the formation process which is a growth-associat
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31

Smith, Robert W., Rosmalen Rik P. van, dos Santos Vitor A. P. Martins, and Christian Fleck. "DMPy: a Python package for automated mathematical model construction of large-scale metabolic systems." BMC Systems Biology 12, no. 1 (2018): 72. https://doi.org/10.1186/s12918-018-0584-8.

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<strong>Background: </strong>Models of metabolism are often used in biotechnology and pharmaceutical research to identify drug targets or increase the direct production of valuable compounds. Due to the complexity of large metabolic systems, a number of conclusions have been drawn using mathematical methods with simplifying assumptions. For example, constraint-based models describe changes of internal concentrations that occur much quicker than alterations in cell physiology. Thus, metabolite concentrations and reaction fluxes are fixed to constant values. This greatly reduces the mathematical
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Gent, Frederick A., Mordecai-Mark Mac Low, and Maarit J. Korpi-Lagg. "Transition from Small-scale to Large-scale Dynamo in a Supernova-driven, Multiphase Medium." Astrophysical Journal 961, no. 1 (2024): 7. http://dx.doi.org/10.3847/1538-4357/ad0da0.

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Abstract Magnetic fields are now widely recognized as critical at many scales to galactic dynamics and structure, including multiphase pressure balance, dust processing, and star formation. Using imposed magnetic fields cannot reliably model the interstellar medium's (ISM) dynamical structure nor phase interactions. Dynamos must be modeled. ISM models exist of turbulent magnetic fields using small-scale dynamo (SSD). Others model the large-scale dynamo (LSD) organizing magnetic fields at the scale of the disk or spiral arms. Separately, neither can fully describe the galactic magnetic field dy
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Ali Eshtewy, Neveen, and Lena Scholz. "Model Reduction for Kinetic Models of Biological Systems." Symmetry 12, no. 5 (2020): 863. http://dx.doi.org/10.3390/sym12050863.

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High dimensionality continues to be a challenge in computational systems biology. The kinetic models of many phenomena of interest are high-dimensional and complex, resulting in large computational effort in the simulation. Model order reduction (MOR) is a mathematical technique that is used to reduce the computational complexity of high-dimensional systems by approximation with lower dimensional systems, while retaining the important information and properties of the full order system. Proper orthogonal decomposition (POD) is a method based on Galerkin projection that can be used for reducing
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Liu, Yongfeng, Yi Liu, and Duolong Di. "Adsorption behaviors of (–)-epigallocatechin gallate and caffeine on macroporous adsorption resins functionalized with carbazole and N-methylimidazole." Pigment & Resin Technology 49, no. 3 (2020): 197–205. http://dx.doi.org/10.1108/prt-06-2019-0055.

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Purpose The purpose of this study is to focus on the preparation of macroporous adsorption resins (MARs) functionalized with carbazole and N-methylimidazole, and adsorption behaviors of (–)-epigallocatechin gallate (EGCG) and caffeine (CAF) on the functionalized MARs. Design/methodology/approach Based on the Friedel–Crafts and amination reactions, novel MARs functionalized with carbazole and N-methylimidazole were synthesized and characterized by the BET method. Accordingly, adsorption behaviors and structure-activity relationships for EGCG and CAF were studied in detail. Findings The results
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Bengtsson, Lisa, Heiner Körnich, Erland Källén, and Gunilla Svensson. "Large-Scale Dynamical Response to Subgrid-Scale Organization Provided by Cellular Automata." Journal of the Atmospheric Sciences 68, no. 12 (2011): 3132–44. http://dx.doi.org/10.1175/jas-d-10-05028.1.

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Abstract Because of the limited resolution of numerical weather prediction (NWP) models, subgrid-scale physical processes are parameterized and represented by gridbox means. However, some physical processes are better represented by a mean and its variance; a typical example is deep convection, with scales varying from individual updrafts to organized mesoscale systems. This study investigates, in an idealized setting, whether a cellular automaton (CA) can be used to enhance subgrid-scale organization by forming clusters representative of the convective scales and thus yield a stochastic repre
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Avissar, Roni, and Fei Chen. "Development and Analysis of Prognostic Equations for Mesoscale Kinetic Energy and Mesoscale (Subgrid Scale) Fluxes for Large-Scale Atmospheric Models." Journal of the Atmospheric Sciences 50, no. 22 (1993): 3751–74. http://dx.doi.org/10.1175/1520-0469(1993)050<3751:daaope>2.0.co;2.

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Michael, A. T., M. Opher, G. Tóth, V. Tenishev, and D. Borovikov. "The Solar Wind with Hydrogen Ion Exchange and Large-scale Dynamics (SHIELD) Code: A Self-consistent Kinetic–Magnetohydrodynamic Model of the Outer Heliosphere." Astrophysical Journal 924, no. 2 (2022): 105. http://dx.doi.org/10.3847/1538-4357/ac35eb.

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Abstract Neutral hydrogen has been shown to greatly impact the plasma flow in the heliosphere and the location of the heliospheric boundaries. We present the results of the Solar Wind with Hydrogen Ion Exchange and Large-scale Dynamics (SHIELD) model, a new, self-consistent, kinetic–MHD model of the outer heliosphere within the Space Weather Modeling Framework. The charge exchange mean free path is on the order of the size of the heliosphere; therefore, the neutral atoms cannot be described as a fluid. The numerical code SHIELD couples the MHD solution for a single plasma fluid to the kinetic
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38

Schaeffer, D. B., F. D. Cruz, R. S. Dorst, et al. "Laser-driven, ion-scale magnetospheres in laboratory plasmas. I. Experimental platform and first results." Physics of Plasmas 29, no. 4 (2022): 042901. http://dx.doi.org/10.1063/5.0084353.

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Magnetospheres are a ubiquitous feature of magnetized bodies embedded in a plasma flow. While large planetary magnetospheres have been studied for decades by spacecraft, ion-scale “mini” magnetospheres can provide a unique environment to study kinetic-scale, collisionless plasma physics in the laboratory to help validate models of larger systems. In this work, we present preliminary experiments of ion-scale magnetospheres performed on a unique high-repetition-rate platform developed for the Large Plasma Device at the University of California, Los Angeles. The experiments utilize a high-repetit
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39

Calkins, Michael A., Keith Julien, Steven M. Tobias, and Jonathan M. Aurnou. "A multiscale dynamo model driven by quasi-geostrophic convection." Journal of Fluid Mechanics 780 (September 2, 2015): 143–66. http://dx.doi.org/10.1017/jfm.2015.464.

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A convection-driven multiscale dynamo model is developed in the limit of low Rossby number for the plane layer geometry in which the gravity and rotation vectors are aligned. The small-scale fluctuating dynamics are described by a magnetically modified quasi-geostrophic equation set, and the large-scale mean dynamics are governed by a diagnostic thermal wind balance. The model utilizes three time scales that respectively characterize the convective time scale, the large-scale magnetic evolution time scale and the large-scale thermal evolution time scale. Distinct equations are derived for the
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40

Iwata, Naoyuki, Hiroki Suzuki, and Shinsuke Mochizuki. "Numerical simulation of viscosity/implicit large-eddy steady turbulence with the Reynolds number dependency." Journal of Physics: Conference Series 2047, no. 1 (2021): 012007. http://dx.doi.org/10.1088/1742-6596/2047/1/012007.

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Abstract This study presents a numerical analysis that models small scale turbulence using numerical viscosity or implicit large-eddy simulation (LES). The motivation for focusing on these models is that the sub-grid scale components of LES are assumed to have a sufficiently high Reynolds number turbulence. The Reynolds number dependence of steady isotropic turbulence is used to validate the present analysis. Here, this dependency ranges from low to high Reynolds numbers. The results of this analysis are validated by comparing them with those of direct numerical simulation. The donor cell meth
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Boscheri, Walter, Giacomo Dimarco, and Lorenzo Pareschi. "Modeling and simulating the spatial spread of an epidemic through multiscale kinetic transport equations." Mathematical Models and Methods in Applied Sciences 31, no. 06 (2021): 1059–97. http://dx.doi.org/10.1142/s0218202521400017.

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In this paper, we propose a novel space-dependent multiscale model for the spread of infectious diseases in a two-dimensional spatial context on realistic geographical scenarios. The model couples a system of kinetic transport equations describing a population of commuters moving on a large scale (extra-urban) with a system of diffusion equations characterizing the non-commuting population acting over a small scale (urban). The modeling approach permits to avoid unrealistic effects of traditional diffusion models in epidemiology, like infinite propagation speed on large scales and mass migrati
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Chen, Junjie, Baofang Liu, Xuhui Gao, and Deguang Xu. "Computational Fluid Dynamics Simulations of Lean Premixed Methane-Air Flame in a Micro-Channel Reactor Using Different Chemical Kinetics." International Journal of Chemical Reactor Engineering 14, no. 5 (2016): 1003–15. http://dx.doi.org/10.1515/ijcre-2015-0174.

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Abstract Flame temperature and structure are a useful tool for describing flame dynamics and flame stability, especially at the micro-scale. The objective of this study is to examine the effect of different kinetic models (that have been proven to accurately predict the macro-combustion behavior of hydrocarbons) on the combustion characteristics and the flame stability in microreactors, and to explore the applicability of these kinetic models at the micro-scale. Computational fluid dynamics (CFD) simulations of lean premixed methane-air flame in micro-channel reactors were carried out to exami
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43

Li, Dion, Yuxi Chen, Chuanfei Dong, Liang Wang, and Gabor Toth. "Numerical study of magnetic island coalescence using magnetohydrodynamics with adaptively embedded particle-in-cell model." AIP Advances 13, no. 1 (2023): 015126. http://dx.doi.org/10.1063/5.0122087.

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Collisionless magnetic reconnection typically requires kinetic treatment that is, in general, computationally expensive compared to fluid-based models. In this study, we use the magnetohydrodynamics with an adaptively embedded particle-in-cell (MHD-AEPIC) model to study the interaction of two magnetic flux ropes. This innovative model embeds one or more adaptive PIC regions into a global MHD simulation domain such that the kinetic treatment is only applied in regions where the kinetic physics is prominent. We compare the simulation results among three cases: (1) MHD with adaptively embedded PI
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44

Vinnett, Luis, Alex Esteban, Francisca Orellana, Marcelo Rivera, and Matías Benítez. "On the Sensitivity of Kinetic Modeling to the Selection of Flotation Intervals in Batch Tests." Minerals 15, no. 6 (2025): 583. https://doi.org/10.3390/min15060583.

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Batch tests were conducted to recover copper minerals by flotation. Seven intervals (cumulative flotation times) were chosen to characterize flotation kinetics in terms of maximum recoveries, R∞, and flotation rate distributions, f(k). The responses were subsampled, removing one datapoint at a time to obtain seven datasets with six time-recovery datapoints. The main objective of this subsampling procedure was to assess the sensitivity of the R∞–f(k) estimates to moderate changes and arbitrary selection of flotation intervals in batch tests. These datasets were fitted to the Single Flotation Ra
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Chaudhari, Ashvinkumar, Antti Hellsten, and Jari Hämäläinen. "Full-Scale Experimental Validation of Large-Eddy Simulation of Wind Flows over Complex Terrain: The Bolund Hill." Advances in Meteorology 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/9232759.

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Numerical simulation of local atmospheric flows around a complex topography is important for many wind energy applications, as it can help in locating and optimizing wind farms. The aim of this paper is to simulate the atmospheric flows over the challenging and complex site of Bolund Hill (in Denmark) using Large-Eddy Simulations (LES) and to validate the simulation methodology against full-scale measurements. Wind prediction over a potential inland wind park is the main application of the validated LES methodology. For the first time, LES-based results from more than one wind direction of the
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46

Pham, Duy-Tan J., and Jean-Marie C. Bouteiller. "Experimentally Constrained Mechanistic and Data-Driven Models for Simulating NMDA Receptor Dynamics." Biomedicines 13, no. 7 (2025): 1674. https://doi.org/10.3390/biomedicines13071674.

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Background: The N-methyl-d-aspartate receptor (NMDA-R) is a glutamate ionotropic receptor in the brain that is crucial for synaptic plasticity, which underlies learning and memory formation. Dysfunction of NMDA receptors is implicated in various neurological diseases due to their roles in both normal cognition and excitotoxicity. However, their dynamics are challenging to capture accurately due to their high complexity and non-linear behavior. Methods: This article presents the elaboration and calibration of experimentally constrained computational models of GluN1/GluN2A NMDA-R dynamics: (1) a
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47

Moeng, C. H., P. P. Sullivan, M. F. Khairoutdinov, and D. A. Randall. "A Mixed Scheme for Subgrid-Scale Fluxes in Cloud-Resolving Models." Journal of the Atmospheric Sciences 67, no. 11 (2010): 3692–705. http://dx.doi.org/10.1175/2010jas3565.1.

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Abstract A large-domain large-eddy simulation of a tropical deep convection system is used as a benchmark to derive and test a mixed subgrid-scale (SGS) scheme for scalar and momentum fluxes in cloud-resolving models (CRMs). The benchmark simulation resolves a broad range of scales ranging from mesoscale organizations, through gravity waves and individual clouds, down to energy-containing turbulent eddies. A spectral analysis shows that the vertical-velocity kinetic energy peaks at scales from hundreds of meters in the lower cloud layer to several kilometers higher up; these scales are typical
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48

Kamieniecki, Jan A., Maarten H. P. Ambaum, Robert S. Plant, and Steven J. Woolnough. "The Implications of an Idealized Large-Scale Circulation for Mechanical Work Done by Tropical Convection." Journal of the Atmospheric Sciences 75, no. 8 (2018): 2533–47. http://dx.doi.org/10.1175/jas-d-17-0314.1.

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Abstract A thermodynamic analysis is presented of an overturning circulation simulated by two cloud-resolving models, coupled by a weak temperature gradient parameterization. Taken together, they represent two separated regions over different sea surface temperatures, and the coupling represents an idealized large-scale circulation such as the Walker circulation. It is demonstrated that a thermodynamic budget linking net heat input to the generation of mechanical energy can be partitioned into contributions from the large-scale interaction between the two regions, as represented by the weak te
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Tochi, Nkwocha Stephen, Isaac Adebayo Akinbulu, Oke Temidayo Joseph, and Medubi Kayode Michelle. "Kinetics and Equilibrium Studies of the Detoxification of Aqueous Solutions of Phenolic Derivatives using Activated Carbon." International Research Journal of Pure and Applied Chemistry 25, no. 4 (2024): 99–115. http://dx.doi.org/10.9734/irjpac/2024/v25i4869.

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This study investigates the kinetics and equilibrium of phenolic derivative detoxification from aqueous solutions using activated carbon derived from coconut husk (CHAC). Phenolic compounds, prevalent in industrial wastewater, are highly toxic to humans and aquatic life. The removal efficiency of 4-Nitrophenol (PNP) and 4-Chlorophenol (PCP) was examined using batch adsorption experiments under varying conditions including adsorbent dose, contact time, initial concentration, and temperature. Coconut husk was chemically activated and characterized for its adsorption properties. The optimal adsor
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50

Mahadevan, A., J. Lu, S. P. Meacham, and P. Malanotte-Rizzoli. "The predictability of large-scale wind-driven flows." Nonlinear Processes in Geophysics 8, no. 6 (2001): 449–65. http://dx.doi.org/10.5194/npg-8-449-2001.

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Abstract. The singular values associated with optimally growing perturbations to stationary and time-dependent solutions for the general circulation in an ocean basin provide a measure of the rate at which solutions with nearby initial conditions begin to diverge, and hence, a measure of the predictability of the flow. In this paper, the singular vectors and singular values of stationary and evolving examples of wind-driven, double-gyre circulations in different flow regimes are explored. By changing the Reynolds number in simple quasi-geostrophic models of the wind-driven circulation, steady,
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