Chemical hydrodynamics of a downward microbubble flow for intensification of gas‐fed bioreactors

Ansari, Manizheh; Turney, Damon E.; Yakobov, Roman; Kalaga, Dinesh V.; Kleinbart, Simon; Banerjee, Sanjoy; Joshi, Jyeshtharaj B.

doi:10.1002/aic.16002

Cited by 19 publications

(26 citation statements)

References 77 publications

(91 reference statements)

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“…liquid superficial velocity) causes a decrease in k L a by 81%, which is also explained by the fact that a doubling of jet velocity causes a 61% reduction in gas fraction. Note that the value of k L is known to be only weakly dependent on liquid velocity (i.e.,

k_{L} \propto v_{t}^{1 / 4}

) via turbulence . Therefore, an important finding is that the strong connection between k L a and reactor operating parameters is mediated mainly through the bubble surface area ( a ) term, that is, not through the k L term.…”

Section: Resultsmentioning

confidence: 99%

“…The mixture exits the bottom of the reactor to a gas–liquid separation chamber, wherein the gas is discarded and the liquid is recirculated. The experimental system is the same as our previous reports …”

Section: Methodsmentioning

confidence: 99%

“…Measurements of liquid or gas velocity inside the reactor were made by PIV of photographs from a high‐speed camera (Photron FASTCAM Mini UX 100), based on software described in Turney and Banerjee, which employs established PIV methods . Our previous report on this reactor describes the PIV methods in detail …”

Section: Methodsmentioning

confidence: 99%

“…Liquid RTD in the reactor was calculated by measuring the concentration time series of a salt pulse at different locations after a sharp pulse of salty solution was injected into the top of the reactor . The RTD salt concentration time series (C) allowed the following calculations of mean residence time

\overset{t}{true} = \frac{\int_{0}^{\infty} italictCdt}{\int_{0}^{\infty} italicCdt} = \frac{\sum t_{i} C_{i} Δ t_{i}}{\sum C_{i} Δ t_{i}}

and variance

σ^{2} = \frac{\int_{0}^{\infty} {(t - \overset{false¯}{t})}^{2} italicCdt}{\int_{0}^{\infty} italicCdt} = \frac{\sum {(t_{i} - \overset{false¯}{t})}^{2} C_{i} Δ t_{i}}{\sum C_{i} Δ t_{i}}

…”

Section: Methodsmentioning

confidence: 99%

“…The typical capital cost of corn‐to‐ethanol reactors is $60,000 per barrel‐per‐day capacity . Therefore, bioreactors for GTL are under active research and development …”

Section: Introductionmentioning

confidence: 99%

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A micro‐jet array for economic intensification of gas transfer in bioreactors

Turney

Ansari

Kalaga

et al. 2018

Biotechnology Progress

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Bioreactors are of interest for gas‐to‐liquid conversion of stranded or waste industrial gases, such as CO, CH4, or syngas. Process economics requires reduction of bioreactor cost and size while maintaining intense production via rapid delivery of gases to the liquid phase (i.e., high kLa). Here, we show a novel bioreactor design that outperforms all known technology in terms of gas transfer energy efficiency (kLa per power density) while operating at high kLa (i.e., near 0.8 s−1). The reactor design uses a micro‐jet array to break feedstock gas into a downward microbubble flow. Hydrodynamic and surfactant measurements show the reactor's advanced performance arises from its bubble breakage mechanism, which limits fluid shear to a thin plane located at an optimal location for bubble breakage. Power dissipation and kL are shown to scale with micro‐jet diameter rather than reactor diameter, and the micro‐jet array achieves improved performance compared to classical impinging‐jets, ejector, or U‐loop reactors. The hydrodynamic mechanism by which the micro‐jets break bubbles apart is shown to be shearing the bubbles into filaments then fragmentation by surface tension rather than “cutting in half” of bubbles. Guided by these hydrodynamic insights, strategies for industrial design are given. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2710, 2019

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k_{L} \propto v_{t}^{1 / 4}

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

\overset{t}{true} = \frac{\int_{0}^{\infty} italictCdt}{\int_{0}^{\infty} italicCdt} = \frac{\sum t_{i} C_{i} Δ t_{i}}{\sum C_{i} Δ t_{i}}

and variance

σ^{2} = \frac{\int_{0}^{\infty} {(t - \overset{false¯}{t})}^{2} italicCdt}{\int_{0}^{\infty} italicCdt} = \frac{\sum {(t_{i} - \overset{false¯}{t})}^{2} C_{i} Δ t_{i}}{\sum C_{i} Δ t_{i}}

…”

Section: Methodsmentioning

confidence: 99%

“…The typical capital cost of corn‐to‐ethanol reactors is $60,000 per barrel‐per‐day capacity . Therefore, bioreactors for GTL are under active research and development …”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A micro‐jet array for economic intensification of gas transfer in bioreactors

Turney

Ansari

Kalaga

et al. 2018

Biotechnology Progress

Self Cite

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Towards enhancement of gas–liquid mass transfer in bioelectrochemical systems: Validation of a robust CFD model

Karimi

Widén

Nygård

et al. 2021

Biotech & Bioengineering

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Mass transfer has been identified as a major bottleneck in gas fermentation and microbial conversion of carbon dioxide to chemicals. We present a pragmatic and validated Computational Fluid Dynamics (CFD) model for mass transfer in bioelectrochemical systems. Experiments were conducted to measure mixing times and mass transfer in a Duran bottle and an H‐cell. An Eulerian–Eulerian framework with a simplified model for the bubble size distribution (BSD) was developed that utilized only one additional equation for the bubble number density while including the breakup and coalescence. Validations of the CFD model for mixing times showed that the predictions were within the confidence intervals of the measurements, verifying the model's capability in simulating the hydrodynamics. Further validations were performed using constant and varying bubble diameters for the mass transfer. The results showed the benefits of a simplified BSD model, as it yielded improvements of seven and four times in accuracy when assessed against the experimental data for the Duran bottle and H‐cell, respectively. Modeling of the H‐cell predicted that a lower stirring rate improves mass transfer compared with higher stirring rates, which is of great importance when designing microbial cultivation processes. The model offers a feasible framework for advanced modeling of gas fermentation and microbial electrosynthesis.

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Performance of a Degassing Cyclone with Main and Subsidiary Chambers

Wang

Yang

2021

Chem Eng & Technol

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Based on the premise that large bubbles are removed in larger cyclones and small bubbles in smaller cyclones, a combined degassing cyclone with main and subsidiary chambers was designed to enhance liquid degassing. The pressure loss, liquid flow rate at the gas outlet, split ratio, gas flow rate at the liquid outlet, and degassing efficiency of the degassing cyclone were measured and calculated. Pressure loss correlations were established which relates the Euler number to the gas and liquid Reynolds numbers in the main chamber. Most cases exhibit a degassing efficiency greater than 0.998 when the liquid flow rate is more than 0.7 m 3 h -1 . The contours of pressure loss, split ratio, and degassing efficiency provide an effective guidance for designing a degassing cyclone.

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Chemical hydrodynamics of a downward microbubble flow for intensification of gas‐fed bioreactors

Cited by 19 publications

References 77 publications

A micro‐jet array for economic intensification of gas transfer in bioreactors

A micro‐jet array for economic intensification of gas transfer in bioreactors

Towards enhancement of gas–liquid mass transfer in bioelectrochemical systems: Validation of a robust CFD model

Performance of a Degassing Cyclone with Main and Subsidiary Chambers

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