Processing math: 100%
Research article Special Issues

Utilizing the Box-Behnken method on modeling of ternary-Casson nanofluid with variable density and heat sink across a vertical jet

  • Received: 18 January 2025 Revised: 26 March 2025 Accepted: 03 April 2025 Published: 28 April 2025
  • In this paper, the thermal performance of Casson fluid is discussed with variable density while the vertical jet is taken out. The correlation of tri-hybrid nanofluid was utilized whereas base fluid was addressed as ethylene glycol, and suspension of CuO,GO and aluminum oxide were considered because of their superior heat transfer capabilities, such as electronic cooling and heat exchangers. For increased energy efficiency, these nanofluids were also utilized in industrial cooling systems, solar collectors, and automobile radiators. Darcy's law was used with heat sink and viscous dissipation. The development of the mathematical model was visualized in terms of PDEs. The finite element method was used for numerical procedures. The novel aspect included using the Box-Behnken design for optimization and the finite element method to analyze tri-hybrid nanofluid flow over a vertical jet with Darcy-Forchheimer effects, heat source, and viscous dissipation. It was claimed that highly novelty work is discussed. The Box Behnken design was employed for calculating Nusselt number and divergent velocity. We concluded that the motion of nanofluid is enhanced when Forchiermer number and B are enhanced. The temperature profile is boosted when heat sink and Eckert number, D, and the power law index number are enhanced. Ternary hybrid nano-fluid has remarkable achievement in heat transfer rate and divergent velocity than hybrid nanofluid and nanofluid.

    Citation: Umar Nazir, Abdelaziz Nasr. Utilizing the Box-Behnken method on modeling of ternary-Casson nanofluid with variable density and heat sink across a vertical jet[J]. AIMS Mathematics, 2025, 10(4): 10093-10123. doi: 10.3934/math.2025460

    Related Papers:

    [1] Oluwafolajimi Adesanya, Tolulope Oduselu, Oluwawapelumi Akin-Ajani, Olubusuyi M. Adewumi, Olusegun G. Ademowo . An exegesis of bacteriophage therapy: An emerging player in the fight against anti-microbial resistance. AIMS Microbiology, 2020, 6(3): 204-230. doi: 10.3934/microbiol.2020014
    [2] Ashrafus Safa, Jinath Sultana Jime, Farishta Shahel . Cholera toxin phage: structural and functional diversity between Vibrio cholerae biotypes. AIMS Microbiology, 2020, 6(2): 144-151. doi: 10.3934/microbiol.2020009
    [3] Abdullahi Yusuf Muhammad, Malik Amonov, Chandrika Murugaiah, Atif Amin Baig, Marina Yusoff . Intestinal colonization against Vibrio cholerae: host and microbial resistance mechanisms. AIMS Microbiology, 2023, 9(2): 346-374. doi: 10.3934/microbiol.2023019
    [4] Rochelle Keet, Diane Rip . Listeria monocytogenes isolates from Western Cape, South Africa exhibit resistance to multiple antibiotics and contradicts certain global resistance patterns. AIMS Microbiology, 2021, 7(1): 40-58. doi: 10.3934/microbiol.2021004
    [5] Ogueri Nwaiwu, Chiugo Claret Aduba . An in silico analysis of acquired antimicrobial resistance genes in Aeromonas plasmids. AIMS Microbiology, 2020, 6(1): 75-91. doi: 10.3934/microbiol.2020005
    [6] Chioma Lilian Ozoaduche, Katalin Posta, Balázs Libisch, Ferenc Olasz . Acquired antibiotic resistance of Pseudomonas spp., Escherichia coli and Acinetobacter spp. in the Western Balkans and Hungary with a One Health outlook. AIMS Microbiology, 2025, 11(2): 436-461. doi: 10.3934/microbiol.2025020
    [7] Philip Serwer . Restoring logic and data to phage-cures for infectious disease. AIMS Microbiology, 2017, 3(4): 706-712. doi: 10.3934/microbiol.2017.4.706
    [8] Rosette Mansour, Mohammad H. El-Dakdouki, Sara Mina . Phylogenetic group distribution and antibiotic resistance of Escherichia coli isolates in aquatic environments of a highly populated area. AIMS Microbiology, 2024, 10(2): 340-362. doi: 10.3934/microbiol.2024018
    [9] Neda Askari, Hassan Momtaz, Elahe Tajbakhsh . Acinetobacter baumannii in sheep, goat, and camel raw meat: virulence and antibiotic resistance pattern. AIMS Microbiology, 2019, 5(3): 272-284. doi: 10.3934/microbiol.2019.3.272
    [10] Mohammad Abu-Sini, Mohammad A. Al-Kafaween, Rania M. Al-Groom, Abu Bakar Mohd Hilmi . Comparative in vitro activity of various antibiotic against planktonic and biofilm and the gene expression profile in Pseudomonas aeruginosa. AIMS Microbiology, 2023, 9(2): 313-331. doi: 10.3934/microbiol.2023017
  • In this paper, the thermal performance of Casson fluid is discussed with variable density while the vertical jet is taken out. The correlation of tri-hybrid nanofluid was utilized whereas base fluid was addressed as ethylene glycol, and suspension of CuO,GO and aluminum oxide were considered because of their superior heat transfer capabilities, such as electronic cooling and heat exchangers. For increased energy efficiency, these nanofluids were also utilized in industrial cooling systems, solar collectors, and automobile radiators. Darcy's law was used with heat sink and viscous dissipation. The development of the mathematical model was visualized in terms of PDEs. The finite element method was used for numerical procedures. The novel aspect included using the Box-Behnken design for optimization and the finite element method to analyze tri-hybrid nanofluid flow over a vertical jet with Darcy-Forchheimer effects, heat source, and viscous dissipation. It was claimed that highly novelty work is discussed. The Box Behnken design was employed for calculating Nusselt number and divergent velocity. We concluded that the motion of nanofluid is enhanced when Forchiermer number and B are enhanced. The temperature profile is boosted when heat sink and Eckert number, D, and the power law index number are enhanced. Ternary hybrid nano-fluid has remarkable achievement in heat transfer rate and divergent velocity than hybrid nanofluid and nanofluid.



    V. cholera is a gram-negative, facultative, motile anaerobe that secrets a diarrhoeagenic protein called cholera toxin [1]. The organism has over 200 serogroups, but only the O1 and O139 serogroups have been linked to the diarrheal disease commonly known as cholera [2]. In third world countries, the organism typically transmits by drinking contaminated surface water [3], whereas, in developed countries, transmissions are associated with raw or undercooked shellfish consumption [4]. Cholera is a frequent occurrence in Bangladesh, with seasonal outbreaks occurring annually [5]. Since V. cholera is predominantly an aquatic organism, the propagation and epidemiology of these outbreaks are highly influenced by contaminated water sources and flooding. In most rural areas of Bangladesh, access to potable clean drinking water is minimal, especially during annual flooding. A vast majority of the population still drinks untreated surface water in rural areas of the country and most of these annual outbreak buds in those populations.

    Furthermore, underground water sources like tube wells are often submerged and contaminated by flood water during annual flooding. Thus, it is crucial to perform a comparative study of V. cholera contamination among different surface and underground water sources as a part of consistent surveillance operation. Besides, annual cholera outbreaks are often treated with the same group of antibiotics, resulting in a high antibiotic resistance in V. cholera strains against commonly used antibiotics. A yearly evaluation of the antibiotic resistance profile of field strains is necessary for the effective therapeutic use of available antibiotics. Therefore, this research aimed at quantifying V. spp. in different water sources of Bangladesh and evaluating the antibiotic resistance profile of V. cholera to estimate and mitigate the risk of the annual cholera outbreak.

    A total of 45 environmental water samples were aseptically collected from pond, river and tube-well of different designated areas of Gazipur district, Bangladesh (Benupur, Chandabaha, Kaliakoir, Sutrapur and Begunbari). Following collection 4 samples are then serially diluted in alkaline peptone water and streak on selective media of Thiosulfate Citrate Bile Salts Sucrose (TCBS) agar, (Hi media, India) and incubated 37 °C for 24 hours. Following incubation, colonies with shiny yellow color and smooth, convex, and slightly flattened texture with opaque centers (Figure 1A, 1B) were used in viable count of V. spp. [6]. For bacteria isolation 1 mL of buffer peptone solution (1:10 dilution) was enriched in nutrient broth at 37 °C for 16 hours and then transferred in selective media (TCBS agar plate) for incubation (37 °C for 24 hours). Then one colony was randomly selected from each plate for biochemical analysis and hemolysis test (Figure 1C, 1D).

    Table 1.  Concentration (µg /disc) of antibiotic disc used for antimicrobial resistance test.
    Antibiotics Symbol Disc concentration (µg /disc)
    Ciprofloxacin (CIP) 5
    Gentamycin (GEN) 10
    Penicillin (P) 10
    Vancomycin (VA) 30
    Cephalexin (CN) 30
    Chloramphenicol (C) 30
    Tetracycline (TE) 30
    Erythromycin (E) 15
    Sulfamethoxazole (SXT) 25
    Nalidixic Acid (NA) 30
    Azithromycin (AZ) 15

     | Show Table
    DownLoad: CSV

    V. spp. isolated in selective media were confirmed as V. cholera by different biochemical tests Catalase, Oxidase, MR, VP, Indole, glucose, maltose, mannitol and sucrose fermentation) according to the methodology described in [7].

    Table 2.  Bacterial concentration in different sources collected from 5 different locations.
    Sample type Bacterial conc. (Log CFU/mL)
    10−3 DF1 10−4 DF1 10−5 DF1
    River 4.96A 5.89A 6.79a
    Pond 4.98A 5.92A 6.80a
    Tube well 4.86B 5.73B 6.06b
    SEM2 0.028 0.035 0.500
    P value <0.0001 <0.0001 <0.0001

     | Show Table
    DownLoad: CSV

    Antibiotic sensitivity test was performed according to Kriby-Bauer disc diffusion method [9] and following the guideline of Clinical and Laboratory Standards Institute [8]. A total of 11 commercially available antibiotics were used (Table 1) in this research to assess drug susceptibility and resistance of isolated species (Mast diagnostics Mersey side, UK). A single colony of pure culture isolated from the samples was incubated in nutrient broth at 37 °C for 16 hours. Then 0.1 ml of broth was spread on Mueller-Hinton agar plate using a cell spreader and an antibiotic disc was placed on top. The plates were then incubated in 37 °C for 24 hours. After incubation, the zone of inhibition near the discs was measured using a millimeter scale and categorized as resistant or sensitive according to the manufacturer's recommendation (Table 1).

    Table 3.  V. spp. concentration in water samples of 5 different location (Benupur, Chandabadha, Kaliakoir, Sutrapur and Begunbari).
    Sample type DF1 Bacterial concentration in each location (Log CFU/mL)
    Benupur Chandabaha Kaliakoir Sutrapur Begunbari
    River Burigonga 10−3 4.95 5.00 4.93 4.99 4.94
    10−4 5.88 5.93 5.87 5.90 5.88
    10−5 6.79 6.80 6.81 6.81 6.79
    Pond 10−3 4.94 4.99 5.00 4.99 5.00
    10−4 5.90 5.89 5.93 5.90 5.87
    10−5 6.80 6.79 6.80 6.77 6.72
    Tube-well 10−3 4.91 4.86 4.86 4.83 5.00
    10−4 5.81 5.76 5.71 5.68 5.89
    10−5 6.62 6.52 6.46 6.57 7.00

    Average 5.84 5.83 5.82 5.83 5.90
    SEM2 0.261 0.257 0.261 0.259 0.247

    P-value 0.996

    *Note: CFU= colony forming unite, 1DF = Dilution factor, 2SEM= Standard error of mean

     | Show Table
    DownLoad: CSV

    A total of 5 replicate samples were randomly collected from each of the 5 different locations (Benupur, Chandabaha, Kaliakoir, Sutrapur, Begunbari) of each 3 water sources (river, pond and tube-well). Bacterial concentration in samples were log transformed and subjected to Shapiro-Wilk test for normality analysis. Bartlett's Test was performed to ensure the homogeneity of variance among the collected samples. The bacterial concentration in different water sources and at different locations were analyzed with one-way ANOVA using the GLM procedure of SAS software (version 9.2) under the following model. Yij = µ + Ti + δL + ϵij. Where, Yij = Bacterial concentration in each sample; µ = Overall mean bacterial concentration; Ti = Effect of water source; δL = Blocking effect of location and ϵij = random error. We assumed that the variation within the model, caused by from sampling location are normally distributed with a mean of 0 and a variance of σL2. Random error ϵij of the model is also normally distributed with a mean of 0 and a variance of σ2. Both variances σL2 and σ2 are independent of each other. For data analysis, P < 0.05 was considered statistically significant and when a significant difference is detected, the were subjected to the least significant difference test (LSD) for mean separation.

    Figure 1.  V. spp. on Nutrient's Agar (A), TCBS Agar left the yellow colony and green colony right (B), blood agar hemolytic colony (C), and non-hemolytic colony on blood agar (D).
    Figure 2.  Biochemical test results. Indole test (A), Methyl red test (B), Voges-Proskauer test (C), Simmons citrate test (D), KIA test (E), and MIU test (F).
    Table 4.  Biochemical tests result of 12 isolated strains of V. cholera.
    Tests Results
    R1 R3 R5 R6 R7 P1 P3 P5 P6 T3 T4 T7
    Nit + + + + + + + + + + + +
    Ox + + + + + + - + + + - +
    Ind + + + + - + + + + + + +
    Ci + + + + + + + + + + + +
    MR - - - + - - - + - - - -
    VP + + + + + + + + + + + +
    MIU + + + + + + + - + + + +
    Urease - - - - - - + - - - - -
    KIA Yb, Ys, G= -H2S= - Yb, Ys, G= -H2S= - Yb, Ys, G= -H2S= - Yb, Ys, G= -H2S= - Yb, Ys, G= -H2S= - Yb Ys, G= -H2S= - Yb, Ys, G= -H2S= - Yb, Ys, G= -H2S= - Yb, Ys, G= -H2S= - Yb, Ys, G= -H2S= - Yb, Ys, G= -H2S= - Yb, Ys, G= -H2S= -
    Glucose + + + - + + - + + + - +
    Maltose + + + + + + + + + - + +
    Mannitol + + + + + + + + + + + +
    Sucrose + + + + - + + + + + + +
    Gelatin hydrolysis + + + + + + - + + + + +

    *Note: Legends: SL No.: Serial Number, Nit: Nitrate utilization test, Ox: Oxidase test, In: Indole test, Ci: Citrate test, MR: Methyl Red test, VP: Voges-Proskauer test, MIU: Motility indole urease, KIA: Kinglar iron agar +: positive, -: Negative, Y: Yellow, B: Butt, S: Slant, G: Gas.

     | Show Table
    DownLoad: CSV

    Viable counts were performed on TCBS agar plate which selects V. spp. based on their sucrose fermentation characteristics and the result is presented in Table 2. There was significantly higher V. spp. in pond and river water than tube-well water (P < 0.001) at all 3 dilution levels (dilution factor: 103, 104 and 105). Bacterial concentration did not vary significantly based on the location of sample collection (P > 0.05) (Table 3).

    Table 5.  Comparative prevalence of V. cholera among the V. spp. isolated from different water sources.
    Bacterial isolate River water Pond water Tube well water Total isolates Percentage (%)
    V. cholera 5 (41.67%) 4 (40%) 3(37.5%) 12 40
    V. parahimulyticus 7 (58.33%) 6 (60%) 5 (62.5%) 18 60
    Total isolates 12 10 8 30

     | Show Table
    DownLoad: CSV

    Total of 14 biochemical tests were performed on isolates of different samples and the result of those tests are presented in Table 4. Out of the 30 isolates, 12 isolates were positive in nitrate, oxidase, indole, citrate utilization, MR, motility, glucose, sucrose, mannitol, maltose, and gelatin hydrolysis agar test (Figure 2A, 2F). V. spp. were also found to be negative in MR, urease, and kingler iron agar test. Hemolytic characteristics of the isolates were also evaluated to differentiate between V. cholera and V. parahaemolyticus (Figure 1C, 1D). V. cholera are known to cause β-hemolysis whereas V. parahaemolyticus causes α-hemolysis. Based on this characteristic 12 of the initial isolates were classified as V. cholera and remaining 18 was classified as V. parahaemolyticus.

    The comparative prevalence of V. cholera among the V. spp. isolated from different water sources are presented in Table 5. River water had the highest prevalence of V. cholera (5 out of 12 isolates; 41.67%) whereas, tube-well water had the lowest prevalence (3 out of 8; 37.5%).

    Table 6.  Outcome of antibiotic sensitivity test of 12 V. cholera isolates obtained from different water samples.
    Isolate GEN CIP CN VA P C TE E NA AZ SXT
    R1 S S S R R S S I I S S
    R3 S S S R R S S R R S S
    R5 S S S I R S I R R S S
    R6 S S S R R S I I R R S
    R7 S S S R R R R R R S S
    P1 S S S R R S R R R S S
    P3 S S S R R S R R R S M
    P5 S S S R R I I R R S S
    P6 S S I I I S I R R R S
    T3 S S I R R S S I R S S
    T4 S S R R R S S I R S S
    T7 S S R I R S I R R S S

    *Note: GEN: Gentamycin, CIP: Ciprofloxacin, CN: Cephalexin, VA: Vancomycin, P: Penicillin, C: Chloramphenicol, TE: Tetracycline, E: Erythromycin, NA: Nalidixic Acid, AZ: Azithromycin, SXT: Sulfamethoxazole, R: River, P; Pond; T; Tap, s: Sensitive and r: Resistance. R1, R3, R5, R6, R7 are the V. cholera isolates collected from rivers, P1, P3, P5 and P6 are the V. cholera isolates collected from pond, T3, T4 and T7 are the V. cholera isolates collected from tube-well.

     | Show Table
    DownLoad: CSV

    The results of antibiotic sensitivity test performed on 12 V. cholera isolates are presented in Table 6. The antibiotic sensitivity profiles of those isolates have been compiled in Table 7. All 12 isolates showed 100% sensitivity toward Gentamicin and ciprofloxacin. All the isolates showed multidrug resistance (Table 6). However, these isolates were susceptible to Chloramphenicol (91.67%), and Sulfamethoxazole (91.67%). Azithromycin (66.67%). Tetracycline (33.33%), and Cephalexin (16.67%) had moderate to low sensitivity. All 12 isolates showed 100% resistance toward Penicillin, Vancomycin, Erythromycin, and Nalidixic Acid. This result is congruent with the study of [10] performed in neighboring country Nepal, where they found their isolates sensitive to Ciprofloxacin, Ampicillin, and resistant to Nalidixic acid. However, unlike this study, their isolates also showed higher sensitivity toward Erythromycin and Tetracycline. The majority of resistance in environmental species are thought to have originated from historically resistant organisms. As a result, it's essential to keep track of both the frequency and the antimicrobial resistance profile of V. cholera to identify the high-risk water sources. To minimize the risk of cholera transmission through contaminated water, we recommend screening various water sources against this pathogenic bacteria before using it for washing, drinking and irrigation. Vulnerable populations, especially farmers in rural areas, should take appropriate precautions to avoid cholera transmission through water [11]. There were some limitations to our research. Due to the funding constrain, a limited number of samples were collected, which might not be sufficient to draw a precise conclusion. Our analysis still lacks molecular characterization of the isolates, which might have strengthened our conclusion.

    Table 7.  Antibiotic sensitivity profile of 12 isolates V. spp. obtained from different water samples.
    Organism Antibiotics Susceptibility (%) Resistance (%)
    V. cholera Gentamycin (GEN) 12(100%) 0(0%)
    Ciprofloxacin (CIP) 12(100%) 0(0%)
    Cephalexin (CN) 2(16.67%) 10(83.33%)
    Vancomycin (VA) 0(0%) 12(100%)
    Penicillin (P) 0(0%) 12(100%)
    Chloramphenicol (C) 11(91.67%) 1(8.33%)
    Tetracycline (TE) 4(33.33%) 8(66.67%)
    Erythromycin (E) 0(0%) 12(100%)
    Sulfamethoxazole (SXT) 11(91.67%) 1(8.33%)
    Nalidixic Acid (NA) 0(0%) 12(100%)
    Azithromycin (AZ) 8(66.67%) 4(33.33%)

     | Show Table
    DownLoad: CSV

    Based on the data of our experiment we conclude that V. cholera is endemic to the surface water sources like pond and river in Gazipur region of Bangladesh. Underground water like tube well has comparatively lower concentration of V. cholera Antibiotics like, Gentamicin, Ciprofloxacin, Chloramphenicol, Sulfamethoxazole and Azithromycin are highly effective against the V. cholera isolates collected in this study. We suggest the application of these antibiotics in therapeutics of annual cholera outbreak. Furthermore, we highly recommend prioritizing underground water over surface water as drinking water source.



    [1] M. Sohail, U. Nazir, A. Singh, A. Tulu, M. J. Khan, Finite element analysis of cross fluid model over a vertical disk suspended to a tetra hybrid nanoparticles mixture, Sci. Rep. , 14 (2024), 1520. https://doi.org/10.1038/s41598-024-51262-w doi: 10.1038/s41598-024-51262-w
    [2] M. D. Shamshuddin, N. Akkurt, A. Saeed, P. Kumam, Radiation mechanism on dissipative ternary hybrid nanoliquid flow through rotating disk encountered by Hall currents: HAM solution, Alex. Eng. J. , 65 (2023), 543–559. https://doi.org/10.1016/j.aej.2022.10.021 doi: 10.1016/j.aej.2022.10.021
    [3] M. D. Shamshuddin, Z. Raizah, N. Akkurt, V. S. Patil, S. M. Eldin, Case study of thermal and solutal aspects on non-Newtonian Prandtl hybrid nanofluid flowing via stretchable sheet: Multiple slip solution, Case Stud. Therm. Eng. , 49 (2023), 103186. https://doi.org/10.1016/j.csite.2023.103186 doi: 10.1016/j.csite.2023.103186
    [4] M. D. Shamshuddin, S. O. Salawu, S. Panda, S. R. Mishra, A. Alanazy, M. R. Eid, Thermal case exploration of electromagnetic radiative tri-hybrid nanofluid flow in Bi-directional stretching device in absorbent medium: SQLM analysis, Case Stud. Therm. Eng. , 60 (2024), 104734. https://doi.org/10.1016/j.csite.2024.104734 doi: 10.1016/j.csite.2024.104734
    [5] A. Ali, Z. Khan, M. Sun, T. Muhammad, K. A. M. Alharbi, Numerical investigation of heat and mass transfer in micropolar nanofluid flows over an inclined surface with stochastic numerical approach, Eur. Phys. J. Plus, 139 (2024), 957. https://doi.org/10.1140/epjp/s13360-024-05676-0 doi: 10.1140/epjp/s13360-024-05676-0
    [6] Z. Khan, W. F. Alfwzan, A. Ali, N. Innab, S. Zuhra, S. Islam, Intelligent computing for electromagnetohydrodynamic bioconvection flow of micropolar nanofluid with thermal radiation and stratification: Levenberg–Marquardt backpropagation algorithm, AIP Adv. , 14 (2024), 035101. https://doi.org/10.1063/5.0187124 doi: 10.1063/5.0187124
    [7] A. M. Alqahtani, M. Bilal, F. A. A. Elsebaee, S. M. Eldin, T. R. Alsenani, A. Ali, Energy transmission through carreau yasuda fluid influenced by ethylene glycol with activation energy and ternary hybrid nanocomposites by using a mathematical model, Heliyon, 9 (2023), e15074. https://doi.org/10.1016/j.heliyon.2023.e14740 doi: 10.1016/j.heliyon.2023.e14740
    [8] K. U. Rahman, Z. Mahmood, S. U. Khan, A. Ali, Z. Li, I. Tlili, Enhanced thermal study in hybrid nanofluid flow in a channel motivated by graphene/Fe3O4 and Newtonian heating, Results Eng. , 21 (2024), 101772. https://doi.org/10.1016/j.rineng.2024.101772 doi: 10.1016/j.rineng.2024.101772
    [9] A. Jan, M. Mushtaq, M. Hussain, Heat transfer enhancement of forced convection magnetized cross model ternary hybrid nanofluid flow over a stretching cylinder: non-similar analysis, Int. J. Heat Fluid Flow, 106 (2024), 109302. https://doi.org/10.1016/j.ijheatfluidflow.2024.109302
    [10] M. Rahman, H. Waheed, M. Turkyilmazoglu, M. S. Siddiqui, Darcy–Brinkman porous medium for dusty fluid flow with steady boundary layer flow in the presence of slip effect, Int. J. Mod. Phys. B, 38 (2024), 2450152. https://doi.org/10.1142/S0217979224501522 doi: 10.1142/S0217979224501522
    [11] A. Rehman, M. S. Al-Buriahi, H. E. Ali, R. Jan, I. A. Khan, Analytical simulation of Darcy–Forchheimer nanofluid flow over a curved expanding permeable surface, Fluid Dyn. Res. , 56 (2024), 065503. https://doi.org/10.1088/1873-7005/ad8b67 doi: 10.1088/1873-7005/ad8b67
    [12] I. Khan, R. Zulkifli, T. Chinyoka, Z. Ling, M. A. Shah, Numerical analysis of radiative MHD gravity-driven thin film third-grade fluid flow with exothermic reaction and modified Darcy's law on an inclined plane, Mech. Time-Depend. Mater. , 29 (2025), 12. https://doi.org/10.1007/s11043-024-09744-x doi: 10.1007/s11043-024-09744-x
    [13] T. Hayat, M. Shafique, A. Tanveer, A. Alsaedi, Magnetohydrodynamic effects on peristaltic flow of hyperbolic tangent nanofluid with slip conditions and Joule heating in an inclined channel, Int. J. Heat Mass Transf. , 102 (2016), 54–63. https://doi.org/10.1016/j.ijheatmasstransfer.2016.05.105 doi: 10.1016/j.ijheatmasstransfer.2016.05.105
    [14] H. Adun, M. Abid, D. Kavaz, Y. Hu, J. H. Zaini, Optimizing the thermophysical behavior of a novel ternary hybrid nanofluid for energy applications through experimental research, Heliyon, 10 (2024), e32728. https://doi.org/10.1016/j.heliyon.2024.e32728 doi: 10.1016/j.heliyon.2024.e32728
    [15] S. A. Lone, Z. Raizah, H. Alrabaiah, S. Shahab, A. Saeed, A. Khan, Exploring convective conditions in three-dimensional rotating ternary hybrid nanofluid flow over an extending sheet: A numerical analysis, J. Therm. Anal. Calorim., 2024. https://doi.org/10.1007/s10973-024-13070-2
    [16] I. Khan, M. W. Ahmed Khan, Artificial neural networking for computational assessment of ternary hybrid nanofluid flow caused by a stretching sheet: Implications of machine-learning approach, Eng. Appl. Comput. Fluid Mech. , 18 (2024), 2411786. https://doi.org/10.1080/19942060.2024.2411786 doi: 10.1080/19942060.2024.2411786
    [17] T. N. Tanuja, S. Manjunatha, H. S. Migdadi, R. Saadeh, A. Qazza, U. Khan, et al., Leveraging artificial neural networks approach for thermal conductivity evaluation in porous rectangular wetted fins filled with ternary hybrid nanofluid, J. Radiat. Res. Appl. Sci. , 17 (2024), 101125. https://doi.org/10.1016/j.jrras.2024.101125 doi: 10.1016/j.jrras.2024.101125
    [18] H. Kim, Y. Do, S. Ramachandran, M. Sankar, K. Thirumalaisamy, Computational analysis of magnetohydrodynamic ternary-hybrid nanofluid flow and heat transfer inside a porous cavity with shape effects, Phys. Fluids, 36 (2024), 082008. https://doi.org/10.1063/5.0222802 doi: 10.1063/5.0222802
    [19] D. Mohanty, G. Mahanta, S. Shaw, Irreversibility and thermal performance of nonlinear radiative cross-ternary hybrid nanofluid flow about a stretching cylinder with industrial applications, Powder Technol. , 433 (2024), 119255. https://doi.org/10.1016/j.powtec.2023.119255 doi: 10.1016/j.powtec.2023.119255
    [20] A. Z. Ullah, X. Guo, T. Gul, I. Ali, A. Saeed, A. M. Galal, Thin film flow of the ternary hybrid nanofluid over a rotating disk under the influence of magnetic field due to nonlinear convection, J. Magn. Magn. Mater. , 573 (2023), 170673. https://doi.org/10.1016/j.jmmm.2023.170673 doi: 10.1016/j.jmmm.2023.170673
    [21] D. Mohanty, G. Mahanta, S. Shaw, R. Katta, Entropy and thermal performance on shape-based 3D tri-hybrid nanofluid flow due to a rotating disk with statistical analysis, J. Therm. Anal. Calorim. , 149 (2024), 12285–12306. https://doi.org/10.1007/s10973-024-13592-9 doi: 10.1007/s10973-024-13592-9
    [22] M. Faizan, M. Ajithkumar, M. V. Reddy, M. A. Jamal, B. Almutairi, N. A. Shah, J. D. Chung, A theoretical analysis of the ternary hybrid nano-fluid with Williamson fluid model, Ain Shams Eng. J. , 15 (2024), 102839. https://doi.org/10.1016/j.asej.2024.102839 doi: 10.1016/j.asej.2024.102839
    [23] M. Ramzan, F. Ali, N. Akkurt, A. Saeed, P. Kumam, A. M. Galal, Computational assessment of Carreau ternary hybrid nanofluid influenced by MHD flow for entropy generation, J. Magn. Magn. Mater. , 567 (2023), 170353. https://doi.org/10.1016/j.jmmm.2023.170353 doi: 10.1016/j.jmmm.2023.170353
    [24] A. Mishra, S. K. Rawat, M. Yaseen, M. Pant, Development of machine learning algorithm for assessment of heat transfer of ternary hybrid nanofluid flow towards three different geometries: Case of artificial neural network, Heliyon, 9 (2023), e21436. https://doi.org/10.1016/j.heliyon.2023.e21453 doi: 10.1016/j.heliyon.2023.e21453
    [25] A. Mishra, Analysis of waste discharge concentration in radiative hybrid nanofluid flow over a stretching/shrinking sheet with chemical reaction, Mech. Time-Depend. Mater. , 29 (2025), 7. https://doi.org/10.1007/s11043-024-09752-x doi: 10.1007/s11043-024-09752-x
    [26] A. Mishra, Significance of Thompson and Troian slip effects on Fe3O4-CoFe2O4 ethylene glycol-water hybrid nanofluid flow over a permeable plate, Hybrid Adv. , 6 (2024), 100262. https://doi.org/10.1016/j.hybadv.2024.100262 doi: 10.1016/j.hybadv.2024.100262
    [27] A. Mishra, Hydrothermal performance of hybrid nanofluid flow over an exponentially stretching sheet influenced by gyrotactic microorganisms: A comparative evaluation of Yamada-Ota and Xue models, Numer. Heat Transf. Part A Appl., 2024, 1–30. https://doi.org/10.1080/10407782.2024.2363496
    [28] G. Ramasekhar, F. Mebarek-Oudina, S. Suneetha, H. Vaidya, P. D. Selvi, Computational simulation of Casson hybrid nanofluid flow with Rosseland approximation and uneven heat source/sink, Int. J. Thermofluids, 24 (2024), 100893. https://doi.org/10.1016/j.ijft.2024.100893 doi: 10.1016/j.ijft.2024.100893
    [29] N. Z. Basha, F. Mebarek-Oudina, R. Choudhari, H. Vaidya, B. Hadimani, K. V. Prasad, et al., Thermal radiation effect on mixed convective Casson fluid flow over a porous stretching sheet with variable fluid properties, J. Adv. Res. Fluid Mech. Therm. Sci. , 111 (2023), 1. https://doi.org/10.37934/arfmts.111.1.127 doi: 10.37934/arfmts.111.1.127
    [30] I. Chabani, F. Mebarek-Oudina, Convection with Cu-MgO/Water hybrid nanofluid and discrete heating, In: Mathematical Modelling of Fluid Dynamics and Nanofluids, CRC Press, 2023,495–510.
    [31] A. Mezaache, F. Mebarek-Oudina, H. Vaidya, Y. Fouad, Heat transfer analysis of nanofluid flow with entropy generation in a corrugated heat exchanger channel partially filled with porous medium, Heat Trans. , 53 (2024), 4625–4647. https://doi.org/10.1002/htj.23149 doi: 10.1002/htj.23149
    [32] L. S. Sundar, E. V. Ramana, M. K. Singh, A. C. Sousa, Thermal conductivity and viscosity of stabilized ethylene glycol and water mixture Al2O3 nanofluids for heat transfer applications: An experimental study, Int. Commun. Heat Mass Trans. , 56 (2014), 86–95. https://doi.org/10.1016/j.icheatmasstransfer.2014.06.009 doi: 10.1016/j.icheatmasstransfer.2014.06.009
    [33] Y. Zhang, N. Shahmir, M. Ramzan, H. A. S. Ghazwani, M. Y. Malik, Comparative analysis of Maxwell and Xue models for a hybrid nanofluid film flow on an inclined moving substrate, Case Stud. Therm. Eng. , 28 (2021), 101598. https://doi.org/10.1016/j.csite.2021.101598 doi: 10.1016/j.csite.2021.101598
    [34] Y. Zhang, N. Shahmir, M. Ramzan, H. A. S. Ghazwani, M. Y. Malik, Comparative analysis of Maxwell and Xue models for a hybrid nanofluid film flow on an inclined moving substrate, Case Stud. Therm. Eng. , 28 (2021), 101598. https://doi.org/10.1016/j.csite.2021.101598 doi: 10.1016/j.csite.2021.101598
    [35] A. M. Galal, A. Akgül, S. A. Idris, S. Formanova, T. K. Ibrahim, M. K. Hassani, et al, , The performance evolution of Xue and Yamada-Ota models for local thermal non equilibrium effects on 3D radiative Casson trihybrid nanofluid, Sci. Rep. , 15 (2025), 7325. https://doi.org/10.1038/s41598-025-87257-4 doi: 10.1038/s41598-025-87257-4
    [36] M. Y. Rafiq, A. Sabeen, A. U. Rehman, Z. Abbas, Comparative study of Yamada-Ota and Xue models for MHD hybrid nanofluid flow past a rotating stretchable disk: Stability analysis, Int. J. Numer. Methods Heat Fluid Flow, 34 (2024), 3793–3819. https://doi.org/10.1108/HFF-01-2024-0060 doi: 10.1108/HFF-01-2024-0060
    [37] T. Maryam, U. Ahmad, G. Rasool, M. Ashraf, T. Sun, I. Razzaq, Numerical study of the thermal performance of the combined effect of solar energy and variable density around a laminar vertical jet, Case Stud. Therm. Eng. , 56 (2024), 104275. https://doi.org/10.1016/j.csite.2024.104275 doi: 10.1016/j.csite.2024.104275
    [38] J. C. Mollendorf, B. Gebhart, Thermal buoyancy in round laminar vertical jets, Int. J. Heat Mass Trans. , 16 (1973), 735–745. https://doi.org/10.1016/0017-9310(73)90087-2 doi: 10.1016/0017-9310(73)90087-2
    [39] T. Mogi, S. Horiguchi, Experimental study on the hazards of high-pressure hydrogen jet diffusion flames, J. Loss Prev. Proc. Ind. , 22 (2009), 45–51. https://doi.org/10.1016/j.jlp.2008.08.006 doi: 10.1016/j.jlp.2008.08.006
    [40] S. Siddiqa, S. Asghar, M. A. Hossain, Radiation effects in mixed convection flow of a viscous fluid having temperature-dependent density along a permeable vertical plate, J. Eng. Phys. Thermophy. , 85 (2012), 339–348. https://doi.org/10.1007/s10891-012-0658-1 doi: 10.1007/s10891-012-0658-1
    [41] H. Maurer, C. Kessler, Identification and quantification of ethylene glycol and diethylene glycol in plasma using gas chromatography-mass spectrometry, Arch. Toxicol. , 62 (1988), 66–69. https://doi.org/10.1007/BF00316260 doi: 10.1007/BF00316260
    [42] A. Mariano, M. J. Pastoriza-Gallego, L. Lugo, A. Camacho, S. Canzonieri, M. M. Piñeiro, Thermal conductivity, rheological behaviour and density of non-Newtonian ethylene glycol-based SnO2 nanofluids, Fluid Phase Equilib. , 337 (2013), 119–124. https://doi.org/10.1016/j.fluid.2012.09.029 doi: 10.1016/j.fluid.2012.09.029
    [43] S. Mukhopadhyay, P. R. De, K. Bhattacharyya, G. C. Layek, Casson fluid flow over an unsteady stretching surface, Ain Shams Eng. J. , 4 (2013), 933–938. https://doi.org/10.1016/j.asej.2013.04.004 doi: 10.1016/j.asej.2013.04.004
    [44] M. Y. Rafiq, A. Sabeen, A. U. Rehman, Z. Abbas, Comparative study of Yamada-Ota and Xue models for MHD hybrid nanofluid flow past a rotating stretchable disk: stability analysis, Int. J. Numer. Methods Heat Fluid Flow, 34 (2024), 3793–3819. https://doi.org/10.1108/HFF-01-2024-0060 doi: 10.1108/HFF-01-2024-0060
  • This article has been cited by:

    1. Prasanga Madhushani Kumarage, Liyana Arachchilage Dinithi Sandunika De Silva, Gang-Joon Heo, Aquatic environments: A potential source of antimicrobial-resistant Vibrio spp., 2022, 133, 1365-2672, 2267, 10.1111/jam.15702
    2. Raquiba Sultana, Al Mahmud, Sayad Mahmud Koli, Jannatul Nayema, Aboni Ghosh, Susmita Banik Sushree, Pranta Shom, Tanvir Ahmed Siddiqui, Kamal Kanta Das, Mrityunjoy Acharjee, Isolation and Identification of Vibrio Species from Different Types of Water Sources Along with Their Drug Susceptible Pattern, 2024, 8, 2588-9834, 207, 10.4103/bbrj.bbrj_138_24
    3. Aaron Awere‐Duodu, Onyansaniba K. Ntim, Eric S. Donkor, Vibrio cholerae in Water Environments: A Systematic Review and Meta‐Analysis, 2025, 17, 1758-2229, 10.1111/1758-2229.70103
    4. Bright E IGERE, ONOHUEAN Hope, P.O Adomi, T Bashiru Abeni, Phenicol antibiotic resistance status amongst environmental non-O1/non-O139 Vibrio cholerae and Clinical O1/O139 Vibrio cholerae strains: a systematic review and meta-synthesis, 2025, 29501946, 100474, 10.1016/j.microb.2025.100474
  • Reader Comments
  • © 2025 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(447) PDF downloads(34) Cited by(1)

Figures and Tables

Figures(22)  /  Tables(10)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog