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Статті в журналах з теми "Hydrodynamic and biokinetic modeling"

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Автор: Grafiati

Опубліковано: 6 вересня 2023

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1

Huang, Chenfu, Anika Kuczynski, Martin T. Auer, David M. O’Donnell, and Pengfei Xue. "Management Transition to the Great Lakes Nearshore: Insights from Hydrodynamic Modeling." Journal of Marine Science and Engineering 7, no. 5 (May 4, 2019): 129. http://dx.doi.org/10.3390/jmse7050129.

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The emerging shift in Great Lakes management from offshore to nearshore waters will require attention to complexities of coastal hydrodynamics and biogeochemical transformations. Emphasizing hydrodynamics, this work resolves transport processes in quantifying discharge plume and pollutant of concern (POC) footprint dimensions, the latter being the portion of the plume where water quality standards are not met. A generic approach, isolated from pollutant-specific biokinetics, provides first-approximation estimates of the footprint area. A high-resolution, linked hydrodynamic-tracer model is applied at a site in the Greater Toronto Area on Lake Ontario. Model results agree with observed meteorological and hydrodynamic conditions and satisfactorily simulate plume dimensions. Footprints are examined in the context of guidelines for regulatory mixing zone size and attendant loss of beneficial use. We demonstrate that the ratio of the water quality standard to the POC concentration at discharge is a key determinant of footprint dimensions. Footprint size for traditional pollutants (ammonia, total phosphorus) meets regulatory guidelines; however, that for soluble reactive phosphorus, a presently unattended pollutant, is ~1–2 orders of magnitude larger. This suggests that it may be necessary to upgrade treatment technologies to maintain consistency with regulatory guidelines and mitigate manifestations of the eutrophication-related soluble reactive phosphorus POC.

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2

Ortiz, Antonio, Rubén Díez-Montero, Joan García, Nadeem Khalil, and Enrica Uggetti. "Advanced biokinetic and hydrodynamic modelling to support and optimize the design of full-scale high rate algal ponds." Computational and Structural Biotechnology Journal 20 (2022): 386–98. http://dx.doi.org/10.1016/j.csbj.2021.12.034.

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3

Zeng, Ming, Audrey Soric, and Nicolas Roche. "Calibration of hydrodynamic behavior and biokinetics for TOC removal modeling in biofilm reactors under different hydraulic conditions." Bioresource Technology 144 (September 2013): 202–9. http://dx.doi.org/10.1016/j.biortech.2013.06.111.

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4

Xu, Qi, Yanlei Wan, Qiongxiang Wu, Keke Xiao, Wenbo Yu, Sha Liang, Yuwei Zhu, et al. "An efficient hydrodynamic-biokinetic model for the optimization of operational strategy applied in a full-scale oxidation ditch by CFD integrated with ASM2." Water Research 193 (April 2021): 116888. http://dx.doi.org/10.1016/j.watres.2021.116888.

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5

Boltz, Joshua P., Bruce R. Johnson, Imre Takács, Glen T. Daigger, Eberhard Morgenroth, Doris Brockmann, Róbert Kovács, Jason M. Calhoun, Jean-Marc Choubert, and Nicolas Derlon. "Biofilm carrier migration model describes reactor performance." Water Science and Technology 75, no. 12 (March 17, 2017): 2818–28. http://dx.doi.org/10.2166/wst.2017.160.

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The accuracy of a biofilm reactor model depends on the extent to which physical system conditions (particularly bulk-liquid hydrodynamics and their influence on biofilm dynamics) deviate from the ideal conditions upon which the model is based. It follows that an improved capacity to model a biofilm reactor does not necessarily rely on an improved biofilm model, but does rely on an improved mathematical description of the biofilm reactor and its components. Existing biofilm reactor models typically include a one-dimensional biofilm model, a process (biokinetic and stoichiometric) model, and a continuous flow stirred tank reactor (CFSTR) mass balance that [when organizing CFSTRs in series] creates a pseudo two-dimensional (2-D) model of bulk-liquid hydrodynamics approaching plug flow. In such a biofilm reactor model, the user-defined biofilm area is specified for each CFSTR; thereby, Xcarrier does not exit the boundaries of the CFSTR to which they are assigned or exchange boundaries with other CFSTRs in the series. The error introduced by this pseudo 2-D biofilm reactor modeling approach may adversely affect model results and limit model-user capacity to accurately calibrate a model. This paper presents a new sub-model that describes the migration of Xcarrier and associated biofilms, and evaluates the impact that Xcarrier migration and axial dispersion has on simulated system performance. Relevance of the new biofilm reactor model to engineering situations is discussed by applying it to known biofilm reactor types and operational conditions.

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6

Yang, Jixiang, Yanqing Yang, Xin Ji, Youpeng Chen, Jinsong Guo, and Fang Fang. "Three-Dimensional Modeling of Hydrodynamics and Biokinetics in EGSB Reactor." Journal of Chemistry 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/635281.

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A three-dimensional model integrating computational fluid dynamics (CFD) and biokinetics was established to model an expanded granular sludge bed (EGSB) reactor in this study. The EGSB reactor treating synthesized municipal wastewater was operated at ambient temperature. The model provided satisfactory modeling results regarding hydrodynamics and biokinetics. The model shows that influent distribution was evenly distributed. In addition, butyrate and propionate degradation rates linearly decreased along the flow direction in the reactor. However, acetate degradation rate increased first and decreased later. VFA degradation rate distributions were different at each reactor cross section. VFA degradation rates near reactor wall were lower than VFA degradation rates at reactor axis. Moreover, a pulse high influent COD concentration had a tiny impact on effluent quality, which indicates that the reactor was stable while treating synthesized wastewater at adopted conditions.

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7

Meister, Michael, Daniel Winkler, Massoud Rezavand, and Wolfgang Rauch. "Integrating hydrodynamics and biokinetics in wastewater treatment modelling by using smoothed particle hydrodynamics." Computers & Chemical Engineering 99 (April 2017): 1–12. http://dx.doi.org/10.1016/j.compchemeng.2016.12.020.

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8

Meister, Michael, and Wolfgang Rauch. "Modelling aerated flows with smoothed particle hydrodynamics." Journal of Hydroinformatics 17, no. 4 (March 9, 2015): 493–504. http://dx.doi.org/10.2166/hydro.2015.132.

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Modelling aerated flows is a complex application of computational fluid dynamics (CFD) since the interfaces between air and water change rapidly. In this work, the simulation of aerated flows with the smoothed particle hydrodynamics (SPH) method is investigated with a focus towards the application in engineering practice. To prove the accuracy of the method, the processes of air entrainment and rising air bubbles are studied. Through monitoring the evolution of the bubble contours it is shown that the novel approach of adding artificial repulsion forces at the interface does not alter the dynamics but stabilizes the flow. Building on these fundamental processes we extend the discussion to practical applications with a special focus on forced aeration. Since the employment of a detailed SPH model to practical problems remains out of bounds due to the high computational demand, we propose a combined experimental and numerical study where experimental bubble characteristics are imposed on the numerical simulation. Based on the data of the conducted bubble column experiment, the computational demand is significantly decreased such that the oxygen consumption due to biokinetic processes can be modelled. The future perspective is to apply SPH to urban water systems, e.g., for simulating detailed processes in wastewater treatment and sewer hydraulics.

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9

Prades, L., A. D. Dorado, J. Climent, X. Guimerà, S. Chiva, and X. Gamisans. "CFD modeling of a fixed-bed biofilm reactor coupling hydrodynamics and biokinetics." Chemical Engineering Journal 313 (April 2017): 680–92. http://dx.doi.org/10.1016/j.cej.2016.12.107.

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10

Blaauboer, Bas J. "Biokinetic Modeling andin Vitro–in VivoExtrapolations." Journal of Toxicology and Environmental Health, Part B 13, no. 2-4 (June 17, 2010): 242–52. http://dx.doi.org/10.1080/10937404.2010.483940.

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11

Escudié, Renaud, Thierry Conte, Jean Philippe Steyer, and Jean Philippe Delgenès. "Hydrodynamic and biokinetic models of an anaerobic fixed-bed reactor." Process Biochemistry 40, no. 7 (June 2005): 2311–23. http://dx.doi.org/10.1016/j.procbio.2004.09.004.

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12

Sharma, Vishal, Ramakant Sharma, and Shanta Satyanarayan. "Biokinetic modeling of heavy metals in earthworms." Toxicological & Environmental Chemistry 93, no. 3 (February 10, 2011): 474–86. http://dx.doi.org/10.1080/02772248.2010.545210.

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13

Schoefs, O., D. Dochain, M. Perrier, and R. Samson. "Estimation of the Hydrodynamic and Biokinetic Models of Soil Bioremediation Processes." Chemical Engineering Research and Design 81, no. 9 (October 2003): 1279–88. http://dx.doi.org/10.1205/026387603770866506.

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14

Miller, Guthrie, John A. Klumpp, Dunstana Melo, and Deepesh Poudel. "The Role Of Extracellular Fluid in Biokinetic Modeling." Health Physics 113, no. 6 (December 2017): 519–26. http://dx.doi.org/10.1097/hp.0000000000000722.

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15

Farrokhi, Mehrdad, Mostafa Mahdavianpour, Mehdi Shirzad-Siboni, Mohammad Naimi-Joubani, and Hamzeh Ali Jamali. "Intrinsic kinetics for fixed bed bioreactor in hospital wastewater treatment." Water Science and Technology 74, no. 8 (August 26, 2016): 1992–98. http://dx.doi.org/10.2166/wst.2016.399.

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Variation in hospital wastewater (HWW) pollutants and differences with municipal wastewater (MWW), make the use of biokinetic coefficients obtained from activated sludge in the MWW treatment unprofitable for designing, modeling and evaluation of biological processes for HWW treatment. Since this study was conducted to evaluate the performance and biokinetic coefficients of a fixed bed bioreactor (FBBR) using rice husks as fixed media in HWW treatment, a new modified method was also proposed for biokinetic estimation in FBBR processes. For these purposes, five hydraulic retention times along with five sludge retention times were introduced to a pilot setup and the required data were attained. The performance process for chemical oxygen demand (COD) removal was significant (87.8–97.5%) in different conditions. The values of biokinetic coefficients k, Ks, Y and Kd were obtained as 2.42 (day−1), 55.5 (mgCOD/L), 0.2929 (mgBiomass/mgCOD) and 0.0164 (day−1), respectively. The rice husks with high surface area and high affinity for biomass accumulation on its surface are promising media for a green and environmentally friendly FBBR process. The kinetics parameters values are utilizable for modeling of FBBR using rice husks as fixed media in HWW treatment.

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16

Rehman, Usman, Wim Audenaert, Youri Amerlinck, Thomas Maere, Marina Arnaldos, and Ingmar Nopens. "How well-mixed is well mixed? Hydrodynamic-biokinetic model integration in an aerated tank of a full-scale water resource recovery facility." Water Science and Technology 76, no. 8 (June 1, 2017): 1950–65. http://dx.doi.org/10.2166/wst.2017.330.

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Current water resource recovery facility (WRRF) models only consider local concentration variations caused by inadequate mixing to a very limited extent, which often leads to a need for (rigorous) calibration. The main objective of this study is to visualize local impacts of mixing by developing an integrated hydrodynamic-biokinetic model for an aeration compartment of a full-scale WRRF. Such a model is able to predict local variations in concentrations and thus allows judging their importance at a process level. In order to achieve this, full-scale hydrodynamics have been simulated using computational fluid dynamics (CFD) through a detailed description of the gas and liquid phases and validated experimentally. In a second step, full ASM1 biokinetic model was integrated with the CFD model to account for the impact of mixing at the process level. The integrated model was subsequently used to evaluate effects of changing influent and aeration flows on process performance. Regions of poor mixing resulting in non-uniform substrate distributions were observed even in areas commonly assumed to be well-mixed. The concept of concentration distribution plots was introduced to quantify and clearly present spatial variations in local process concentrations. Moreover, the results of the CFD-biokinetic model were concisely compared with a conventional tanks-in-series (TIS) approach. It was found that TIS model needs calibration and a single parameter set does not suffice to describe the system under both dry and wet weather conditions. Finally, it was concluded that local mixing conditions have significant consequences in terms of optimal sensor location, control system design and process evaluation.

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17

Kumar, P. S., and A. B. Pandit. "Modeling Hydrodynamic Cavitation." Chemical Engineering & Technology 22, no. 12 (December 1999): 1017–27. http://dx.doi.org/10.1002/(sici)1521-4125(199912)22:12<1017::aid-ceat1017>3.0.co;2-l.

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18

Spengel, Douglas B., and David A. Dzombak. "Biokinetic modeling and scale-up considerations for rotating biological contactors." Water Environment Research 64, no. 3 (May 1992): 223–35. http://dx.doi.org/10.2175/wer.64.3.6.

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19

Areberg, Johan, H. Jönsson, and S. Mattsson. "Population Biokinetic Modeling of Thyroid Uptake and Retention of Radioiodine." Cancer Biotherapy and Radiopharmaceuticals 20, no. 1 (February 2005): 1–10. http://dx.doi.org/10.1089/cbr.2005.20.1.

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20

Breustedt, Bastian, Eric Blanchardon, Philippe Bérard, Paul Fritsch, Augusto Giussani, Maria Antonia Lopez, Andrea Luciani, et al. "THE CONRAD APPROACH TO BIOKINETIC MODELING OF DTPA DECORPORATION THERAPY." Health Physics 99, no. 4 (October 2010): 547–52. http://dx.doi.org/10.1097/hp.0b013e3181bfba02.

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21

Mašić, Alma, Kai M. Udert, and Kris Villez. "Global parameter optimization for biokinetic modeling of simple batch experiments." Environmental Modelling & Software 85 (November 2016): 356–73. http://dx.doi.org/10.1016/j.envsoft.2016.06.015.

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22

Li, Wei Bo, Paul Roth, Wolfgang Wahl, Uwe Oeh, Vera Höllriegl, and Herwig G. Paretzke. "Biokinetic modeling of uranium in man after injection and ingestion." Radiation and Environmental Biophysics 44, no. 1 (April 14, 2005): 29–40. http://dx.doi.org/10.1007/s00411-005-0272-0.

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23

Ganesan, SP, K. Saravanakumar, and L. Rajendran. "Mathematical Modeling of Multienzyme Biosensor System." International Journal of Computational Mathematics 2014 (October 1, 2014): 1–15. http://dx.doi.org/10.1155/2014/694037.

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A mathematical model of hybrid inhibitor biosensor system is discussed. This model consists of five nonlinear partial differential equations for bisubstrate sensitive amperometric system. Simple and closed form of analytical expressions for concentration of glucose-6-phosphate (substrate), potassium dihydrogen phosphate (inhibitor), oxygen (co-substrate), glucose (product 1), and hydrogen peroxide (product 3) is obtained in terms of rate constant using modified Adomian decomposition method (MADM). In this study, behavior of biokinetic parameters is analyzed using this theoretical result. The obtained analytical results (concentrations) are compared with the numerical results and are found to be in satisfactory agreement.

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24

Triantafyllidou, Simoni, Daniel Gallagher, and Marc Edwards. "Assessing risk with increasingly stringent public health goals: the case of water lead and blood lead in children." Journal of Water and Health 12, no. 1 (October 26, 2013): 57–68. http://dx.doi.org/10.2166/wh.2013.067.

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Previous predictions of children's blood lead levels (BLLs) through biokinetic models conclude that lead in tap water is not a primary health risk for a typical child under scenarios representative of chronic exposure, when applying a 10 μg/dL BLL of concern. Use of the US Environmental Protection Agency Integrated Exposure Uptake Biokinetic (IEUBK) model and of the International Commission on Radiological Protection (ICRP) biokinetic model to simulate children's exposure to water lead at home and at school was re-examined by expanding the scope of previous modeling efforts to consider new public health goals and improved methodology. Specifically, explicit consideration of the more sensitive population groups (e.g., young children and, particularly, formula-fed infants), the variability in BLLs amongst exposed individuals within those groups (e.g., more sensitive children at the upper tail of the BLL distribution), more conservative BLL reference values (e.g., 5 and 2 μg/dL versus 10 μg/dL) and concerns of acute exposure revealed situations where relatively low water lead levels were predicted to pose a human health concern.

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25

Bába, Barnabás, and Tamás Karches. "Sizing of a decentralized wastewater treatment unit supported by biokinetic modeling." Pollack Periodica 15, no. 1 (April 2020): 103–11. http://dx.doi.org/10.1556/606.2020.15.1.10.

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Abstract Decentralized wastewater systems treat, dispose and reuse the wastewater in the vicinity of source, reducing the sewage transportation cost to minimal. As an alternative to centralized systems it can function as a satellite system or an individual wastewater treatment unit. Design an onsite facility applies the same sizing procedure compared the conventional large scale systems, whereas the input flow data and its variability, the model parameters could differ. In this study a small size treatment unit was designed by biokinetic modeling, where the model parameters were estimated using analytical methods. As a result of the calculation the biomass build-up and the quality of the treated effluent was predicted and the operation parameters were determined in summer and winter operation.

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26

Zhou, Yanyan, Fangsan Wei, Wei Zhang, Zhiqiang Guo, and Li Zhang. "Copper bioaccumulation and biokinetic modeling in marine herbivorous fish Siganus oramin." Aquatic Toxicology 196 (March 2018): 61–69. http://dx.doi.org/10.1016/j.aquatox.2018.01.009.

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27

Gujer, Willi. "Is modeling of biological wastewater treatment a mature technology?" Water Science and Technology 63, no. 8 (April 1, 2011): 1739–43. http://dx.doi.org/10.2166/wst.2011.323.

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Based on three case studies it is demonstrated that the application of mathematical models in biological wastewater treatment has not yet reached its full potential. Model structure uncertainty and correlation of uncertain parameter values make up the first case. The combination of biokinetic and hydraulic models relates to the second case. The evolution of a full scale plant over its life expectancy is the frame for the third case. This paper was initially presented as a discussion starter and thus is raising questions rather than providing answers.

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28

Poirazi, Panayiota, Frï¿½dï¿½ric Leroy, Marina D. Georgalaki, Anastassios Aktypis, Luc De Vuyst, and Effie Tsakalidou. "Use of Artificial Neural Networks and a Gamma-Concept-Based Approach To Model Growth of and Bacteriocin Production by Streptococcus macedonicus ACA-DC 198 under Simulated Conditions of Kasseri Cheese Production." Applied and Environmental Microbiology 73, no. 3 (December 8, 2006): 768–76. http://dx.doi.org/10.1128/aem.01721-06.

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ABSTRACT Growth of and bacteriocin production by Streptococcus macedonicus ACA-DC 198 were assessed and modeled under conditions simulating Kasseri cheese production. Controlled fermentations were performed in milk supplemented with yeast extract at different combinations of temperature (25, 40, and 55ï¿½C), constant pH (pHs 5 and 6), and added NaCl (at concentrations of 0, 2, and 4%, wt/vol). The data obtained were used to construct two types of predictive models, namely, a modeling approach based on the gamma concept, as well as a model based on artificial neural networks (ANNs). The latter computational methods were used on 36 control fermentations to quantify the complex relationships between the conditions applied (temperature, pH, and NaCl) and population behavior and to calculate the associated biokinetic parameters, i.e., maximum specific growth and cell count decrease rates and specific bacteriocin production. The functions obtained were able to estimate these biokinetic parameters for four validation fermentation experiments and obtained good agreement between modeled and experimental values. Overall, these experiments show that both methods can be successfully used to unravel complex kinetic patterns within biological data of this kind and to predict population kinetics. Whereas ANNs yield a better correlation between experimental and predicted results, the gamma-concept-based model is more suitable for biological interpretation. Also, while the gamma-concept-based model has not been designed for modeling of other biokinetic parameters than the specific growth rate, ANNs are able to deal with any parameter of relevance, including specific bacteriocin production.

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29

B, Nwokoma Darlington, Dagde Kenneth K, Akpa Jackson G, and Ehirim Emmanuel. "Biokinetic Study of Microbial Decontamination of Oilfield Produced Water." International Journal of Chemical and Process Engineering Research 9, no. 1 (September 19, 2022): 11–20. http://dx.doi.org/10.18488/65.v9i1.3129.

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This work was aimed at identifying microbials and determining the biokinetic parameters for bio-decontamination of oilfield produced water. An extant physical treatment unit for produced water was re-engineered and retrofit with a discontinuous aerobic bioreactor (Bio-Unit) system. The Bio-Unit was operated in a fill-and-draw sequence and the rates of total organic carbon (TOC) removal and biomass growth were monitored. The isolated microbial strains were identified as Bacillus, Pseudomonas and Chryseobacterium spp. The biokinetic parameters of the bio-detoxification process were determined by fitting experimental data into the Monod Equation. The maximum specific substrate utilization rate (k_m), maximum specific growth rate (μ(m,h )), substrate half saturation coefficient (K(STOC )), yield (Y), and endogenous decay rate (b_h), were found to be 0.20 day-1, 0.31 day-1, 2.7 mg TOC/l, 1.6 mg MLSS/mg TOC, and 0.23 day-1, respectively. These values are within the range published in literatures for oilfield produced water, thus will suffice for designing, modeling and control of biological treatment systems, since biokinetic parameters for real oilfield produced water treatment using discontinuous biological configuration is scanty.

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30

Zhou, Xin, Zeqian Zhang, and Yaxin Li. "Four-stage biofilm anaerobic–anoxic–oxic–oxic system for strengthening the biological treatment of coking wastewater: COD removal behaviors and biokinetic modeling." RSC Advances 7, no. 38 (2017): 23714–26. http://dx.doi.org/10.1039/c7ra00277g.

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Biokinetic models of high-strength coking wastewater with a high chemical oxygen demand (COD) was efficiently treated by a novel pilot-scale four-stage biofilm anaerobic–anoxic–oxic–oxic (FB-A²/O²) system.

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31

Osawa, Norihito, Pujirahajo Alwafi, Yusuke Fukushima, and Tokuzo Hosoyamada. "Hydrodynamic Modeling of Pyroclastic Flows." Journal of applied mechanics 10 (2007): 855–64. http://dx.doi.org/10.2208/journalam.10.855.

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32

Singh, Vivekanand, and S. Murty Bhallamudi. "Hydrodynamic Modeling of Basin Irrigation." Journal of Irrigation and Drainage Engineering 123, no. 6 (November 1997): 407–14. http://dx.doi.org/10.1061/(asce)0733-9437(1997)123:6(407).

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33

Molin, B. "Hydrodynamic modeling of perforated structures." Applied Ocean Research 33, no. 1 (February 2011): 1–11. http://dx.doi.org/10.1016/j.apor.2010.11.003.

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34

Tang, P. K. "Modeling Hydrodynamic Behaviors in Detonation." Propellants, Explosives, Pyrotechnics 16, no. 5 (October 1991): 240–44. http://dx.doi.org/10.1002/prep.19910160508.

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35

Palm, S., T. Back, B. Haraldsson, L. Jacobsson, S. Lindegren, and P. Albertsson. "Biokinetic Modeling and Dosimetry for Optimizing Intraperitoneal Radioimmunotherapy of Ovarian Cancer Microtumors." Journal of Nuclear Medicine 57, no. 4 (January 14, 2016): 594–600. http://dx.doi.org/10.2967/jnumed.115.167825.

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36

Alavi, Alireza Nazari, Mohammad Mirzai, Ali Akbar Sajadi, and Hamed Hasanian. "Biokinetic modeling for aerobic treatment of aqueous phase of oil-water emulsion." Bioscience Biotechnology Research Communications 9, no. 4 (December 25, 2016): 625–32. http://dx.doi.org/10.21786/bbrc/9.4/9.

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37

Martati, Erryana, Marelle Boersma, Albertus Spenkelink, Dambar Khadka, Peter van Bladeren, Ivonne Rietjens, and Ans Punt. "Physiologically based biokinetic modeling of safrole in humans as compared with rats." Toxicology Letters 211 (June 2012): S139. http://dx.doi.org/10.1016/j.toxlet.2012.03.508.

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38

Li, Wei Bo, Udo Gerstmann, Augusto Giussani, Uwe Oeh, and Herwig G. Paretzke. "Internal dose assessment of 210Po using biokinetic modeling and urinary excretion measurement." Radiation and Environmental Biophysics 47, no. 1 (September 25, 2007): 101–10. http://dx.doi.org/10.1007/s00411-007-0133-0.

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39

Yuan, Zhigou, Peter A. Vanrolleghem, and Ghislain C. Vansteenkiste. "Modeling error identification of activated sludge models." Water Science and Technology 36, no. 5 (September 1, 1997): 81–88. http://dx.doi.org/10.2166/wst.1997.0170.

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Information about the location of modeling erros is crucial for the efficient improvement of an invalid model. This article discusses how to pinpoint modeling errors through comparison of experimental data with data obtained through simulation of the invalid model. An observer-based approach is presented. By designing a dedicated observer for the system using the invalid model, a signal vector is generated, on which each modeling error imposes an easily identifiable feature. An algorithm to analyze the featured signal is then presented. With this algorithm, the features of each of the modeling errors are extracted. The approach is illustrated for a denitrification reactor model in which errors in the dimension of the state vector, in the structure of the biokinetic relationship and in the values of the parameters could be identified.

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40

GALE, CHARLES, SANGYONG JEON, and BJÖRN SCHENKE. "HYDRODYNAMIC MODELING OF HEAVY-ION COLLISIONS." International Journal of Modern Physics A 28, no. 11 (April 25, 2013): 1340011. http://dx.doi.org/10.1142/s0217751x13400113.

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We review progress in the hydrodynamic description of heavy-ion collisions, focusing on recent developments in modeling the fluctuating initial state and event-by-event viscous hydrodynamic simulations. We discuss how hydrodynamics can be used to extract information on fundamental properties of quantum chromodynamics from experimental data, and review successes and challenges of the hydrodynamic framework.

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41

Gungor, Arif Can, Stefan M. Koepfli, Michael Baumann, Hande Ibili, Jasmin Smajic, and Juerg Leuthold. "Modeling Hydrodynamic Charge Transport in Graphene." Materials 15, no. 12 (June 10, 2022): 4141. http://dx.doi.org/10.3390/ma15124141.

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Анотація:

Graphene has exceptional electronic properties, such as zero band gap, massless carriers, and high mobility. These exotic carrier properties enable the design and development of unique graphene devices. However, traditional semiconductor solvers based on drift-diffusion equations are not capable of modeling and simulating the charge distribution and transport in graphene, accurately, to its full extent. The effects of charge inertia, viscosity, collective charge movement, contact doping, etc., cannot be accounted for by the conventional Poisson-drift-diffusion models, due to the underlying assumptions and simplifications. Therefore, this article proposes two mathematical models to analyze and simulate graphene-based devices. The first model is based on a modified nonlinear Poisson’s equation, which solves for the Fermi level and charge distribution electrostatically on graphene, by considering gating and contact doping. The second proposed solver focuses on the transport of the carriers by solving a hydrodynamic model. Furthermore, this model is applied to a Tesla-valve structure, where the viscosity and collective motion of the carriers play an important role, giving rise to rectification. These two models allow us to model unique electronic properties of graphene that could be paramount for the design of future graphene devices.

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42

McCreanor, P. T., and D. R. Reinhart. "Hydrodynamic modeling of leachate recirculating landfills." Water Science and Technology 34, no. 7-8 (October 1, 1996): 463–70. http://dx.doi.org/10.2166/wst.1996.0655.

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Анотація:

Leachate recirculation is an emerging technology for the enhanced stabilization of active landfills and in-situ treatment of problematic landfills. A variety of researcher have documented the benefits of increasing landfill moisture content and liquid movement through the fill. However, little work has addressed the hydrodynamic characteristics of the recirculating landfill, specifically the effect of leachate flow rate and waste characteristics upon leachate routing. This paper presents the results of mathematical modeling of the horizontal infiltration trench and vertical infiltration well, two commonly employed leachate application methods. The results of transient unsaturated flow modeling are detailed.

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43

McCreanor, Philip T., and Debra R. Reinhart. "Hydrodynamic modeling of leachate recirculating landfills." Waste Management & Research 17, no. 6 (December 1999): 465–69. http://dx.doi.org/10.1177/0734242x9901700610.

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44

Chevrier, P., M. Barrault, and C. Fievet. "Hydrodynamic Model for Electrical Arc Modeling." IEEE Power Engineering Review 16, no. 10 (October 1996): 53–54. http://dx.doi.org/10.1109/mper.1996.4311024.

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45

Chen, Yongliang, and S. D. Heister. "Modeling Hydrodynamic Nonequilibrium in Cavitating Flows." Journal of Fluids Engineering 118, no. 1 (March 1, 1996): 172–78. http://dx.doi.org/10.1115/1.2817497.

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Анотація:

A nonlinear numerical model has been developed to assess nonequilibrium effects in cavitating flows. The numerical implementation involves a two-phase treatment with the use of a pseudo-density which varies between the liquid and gas/vapor extremes. A new constitutive equation for the pseudo-density is derived based on the bubble response described by a modified form of the Rayleigh-Plesset equation. Use of this constitutive equation in a numerical procedure permits the assessment of nonequilibrium effects. This scheme provides a quantitative description of scaling effects in cavitated flows. With minimal modifications, the model can also be used for bubbly two-phase flows.

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46

Low, D. K. Y., L. Li, and P. J. Byrd. "Hydrodynamic Physical Modeling of Laser Drilling." Journal of Manufacturing Science and Engineering 124, no. 4 (October 23, 2002): 852–62. http://dx.doi.org/10.1115/1.1510518.

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Анотація:

Laser drilling is a complex process that involves material removal through both vaporization and hydrodynamic melt ejection. The process is further complicated when an assist gas is incorporated, which is often the case under most practical drilling conditions. It is the intent of this article to investigate these effects through both experiments and theoretical analysis. The analysis accounts for conduction in the solid, vaporization, vaporization-induced recoil pressure melt ejection, convection due to the melt flow as well as the effects of using an O2 assist gas, which includes the effective assist gas pressure exerted on the melt surface, the forced convection cooling and the additional energy generated due to the oxidation of the melt surface by O2. The effects of the absorbed laser intensity on the melt surface temperature, melt ejection velocity and drilling velocity were studied for both cases of laser drilling with and without O2 assist gas and compared to experimental results obtained for EN3 low carbon steel. The dependence of threshold time on the absorbed laser intensity for either vaporization-dominated or melt ejection-dominated (hydrodynamic-dominated) material removal was studied and subsequently related to the threshold conditions for spatter formation. The model was subsequently optimized by examining the significance of the O2 effects considered.

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47

Manukovskiy, Andrey, and D. Makarov. "Modeling of hydrodynamic processes «Brake-stabilizers»." Актуальные направления научных исследований XXI века: теория и практика 2, no. 5 (July 25, 2016): 195–203. http://dx.doi.org/10.12737/6786.

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48

Wang, Wei-Chen, and Ke-Jung Chen. "Magneto-Hydrodynamic simulations on galaxy modeling." Proceedings of the International Astronomical Union 15, S341 (November 2019): 320–22. http://dx.doi.org/10.1017/s174392131900231x.

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AbstractMagnetic field plays an important role in star formation and galaxy evolution. Previous studies discussed about the origin of magnetic field and its effect to the environment. With the recent advancement of supercomputers, adding the magnetic field to a cosmological hydrodynamic simulations only become feasible. In this proceeding, we present the results of high-resolution magneto-hydrodynamic simulation with GIZMO and compare our simulation result with the previous literature and the observations.

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49

Yan, Li. "Hydrodynamic modeling of heavy-ion collisions." Nuclear Physics A 967 (November 2017): 89–96. http://dx.doi.org/10.1016/j.nuclphysa.2017.04.022.

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50

Aragon, Sergio R. "Recent advances in macromolecular hydrodynamic modeling." Methods 54, no. 1 (May 2011): 101–14. http://dx.doi.org/10.1016/j.ymeth.2010.10.005.

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