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Unit operation

In chemical engineering, a unit operation is a fundamental physical process that transforms materials through changes in their physical state, properties, or form without involving chemical reactions, such as separation, mixing, or heat transfer.^[1]^[2] The concept was introduced in 1915 by Arthur D. Little, who proposed that complex industrial processes could be analyzed and designed by decomposing them into these standardized, equipment-based steps, enabling engineers to apply universal principles across diverse applications.^[3]^[4] Unit operations distinguish themselves from unit processes, which involve chemical reactions that alter molecular structure, though the two are often integrated in sequence for complete manufacturing workflows.^[2] Key categories of unit operations include mass transfer (e.g., distillation for separating liquid mixtures based on volatility differences, absorption for capturing gases in liquids), heat transfer (e.g., evaporation to concentrate solutions by vaporizing solvents, heat exchangers for transferring thermal energy between fluids), and mechanical operations (e.g., filtration to remove solids from liquids, size reduction via crushing or grinding).^[5]^[1] These operations rely on scientific principles like fluid dynamics, thermodynamics, and transport phenomena to optimize efficiency, energy use, and product quality in industries ranging from pharmaceuticals and petrochemicals to food processing and water treatment.^[5] By standardizing these steps, unit operations facilitate scalable process design, predictive modeling, and innovation in equipment like distillation columns, pumps, and membrane separators.^[1]

Fundamentals

Definition

A unit operation refers to a fundamental physical transformation or manipulation of materials in chemical engineering processes, independent of their specific chemical composition, that alters properties such as temperature, pressure, phase state, or concentration through mechanical, thermal, or other physical means rather than chemical reactions. This concept emphasizes the commonality of such transformations across diverse industries, enabling engineers to analyze and design processes by breaking them down into repeatable, standardized steps. The term was coined by Arthur D. Little in 1915, who proposed that "any chemical process, on whatever scale conducted, may be resolved into unit operations," providing a framework for systematic study and application beyond particular substances or reactions.^[6] At its core, the unit operation principle highlights generality, modularity, and grounding in transport phenomena. Generality arises because these operations apply universally to any material—solids, liquids, or gases—focusing on physical behaviors rather than molecular specifics, which allows knowledge transfer across sectors like pharmaceuticals, petroleum refining, and food processing. Modularity enables the assembly of complex processes by linking individual unit operations, facilitating scalable design and optimization through standardized equipment and procedures. Fundamentally, unit operations rely on the principles of transport phenomena, encompassing momentum transfer (fluid flow and mechanics), heat transfer, and mass transfer, which provide the quantitative foundation for predicting and controlling material behavior.^[6] Key characteristics of unit operations include their implementation via dedicated equipment, such as pumps, heat exchangers, or separators, which perform the physical changes efficiently at industrial scales. Most require energy input to drive transformations, often in the form of mechanical work, heat, or electrical power, contributing to overall process efficiency considerations. Additionally, many unit operations involve inherent irreversibility, particularly those generating entropy through mixing or friction, which impacts thermodynamic efficiency and design choices.

Classification

Unit operations are primarily classified according to the underlying transport phenomena that govern their behavior, encompassing momentum transfer, heat transfer, and mass transfer. Momentum transfer operations involve the movement and mixing of fluids or solids, such as fluid flow through pipes and agitation in reactors, which are analyzed using principles of fluid dynamics to describe velocity profiles and shear stresses. Heat transfer operations focus on the exchange of thermal energy, including processes like heating, cooling, and condensation, where temperature gradients drive conductive, convective, or radiative mechanisms. Mass transfer operations deal with the diffusion or convection of species between phases, exemplified by distillation for vapor-liquid separation and extraction for solute transfer between immiscible liquids, relying on concentration differences to achieve separation. Secondary classification schemes organize unit operations by the phases involved or their functional roles in a process. Phase-based categorization distinguishes operations by interacting states of matter, such as gas-liquid contacts in absorption towers, solid-liquid interactions in leaching, or gas-solid processes in drying, which influence equipment design and efficiency. Functional classification groups operations by purpose, including preparation steps like size reduction and blending, separation techniques such as filtration and centrifugation, and purification methods like crystallization and adsorption, providing a practical framework for process synthesis.^[7] Within these schemes, detailed subgroups emerge, such as mechanical separations, which form a key category relying on physical forces rather than chemical affinities or diffusional mechanisms. Mechanical separations include filtration to remove solids from liquids via porous media and sedimentation to settle particles by gravity in settling tanks, both minimizing energy input while achieving phase disengagement.^[8] These subgroups highlight how transport principles unify diverse equipment, avoiding process-specific silos. The classification of unit operations has evolved from empirical methods, which relied on trial-and-error scaling from laboratory data in the early 20th century, to phenomenological approaches post-1930s that emphasize fundamental physical laws. This shift, accelerated by the 1960 publication of Transport Phenomena by Bird, Stewart, and Lightfoot, integrated molecular-level analyses of transport rates, enabling predictive modeling over ad-hoc correlations and fostering a more scientific foundation for chemical engineering.^[9]

Historical Development

Origins

The roots of unit operations trace back to 19th-century industrial practices in the chemical sector, where physical transformations were routinely applied without a unified theoretical framework. In alcohol production, distillation emerged as a key operation during this period, with urban distilleries in the United States adopting pot stills and later column stills invented by Aeneas Coffey in 1830 to process grains on a large scale, enabling high-proof spirits through vaporization and condensation.^[10] Similarly, sugar refining relied on filtration to purify raw syrup into crystallized products; at facilities like the Pennsylvania Sugar Refining Company, raw sugar was melted into syrup, filtered to remove impurities, and then piped for further evaporation and drying, all handled empirically by skilled workers.^[11] These operations, drawn from disparate industries including dyeing and pharmacy, highlighted recurring physical steps—such as evaporation, filtration, and distillation—that transcended specific chemical recipes but lacked systematic study.^[12] The formal conceptualization of unit operations arose from the need to professionalize chemical engineering by generalizing these physical processes beyond ad-hoc organic syntheses prevalent in pharmacy and dye-making. In the late 19th and early 20th centuries, the explosive growth of the synthetic dye industry, particularly in Germany and Britain, demanded scalable methods for handling reactions and separations, influencing educators to seek a broader curriculum that emphasized transferable engineering principles over narrow chemical knowledge.^[13] This motivation culminated in 1915 when Arthur D. Little, a prominent consultant and MIT affiliate, introduced the term "unit operations" in a report to MIT's president, stating: "Any chemical process, on whatever scale conducted, may be resolved into a coordinated series of what may be termed 'unit operations.'"^[14] Little's framework posited that common physical operations, like mixing, heating, and separating, could be taught and researched independently of the underlying chemistry, providing a foundation for a distinct engineering discipline.^[15] Initial adoption of this approach occurred rapidly in U.S. university curricula during the 1920s, as institutions sought to train engineers for expanding industries. At MIT, where Little's ideas originated, the chemical engineering program—established in 1888—integrated unit operations by 1916 through practical "plant-based stations" that simulated industrial processes, with the 1923 textbook Principles of Chemical Engineering by William H. Walker, Warren K. Lewis, and William H. McAdams solidifying it as a core pedagogy.^[14] Penn State University followed suit, launching its four-year chemical engineering curriculum in 1924, which emphasized unit operations to bridge chemistry and mechanical engineering, reflecting the growing consensus on this educational model across American academia.^[16]

Evolution in Chemical Engineering

The theoretical advancement of unit operations in chemical engineering during the 1930s and 1950s marked a pivotal shift toward integration with transport phenomena, providing rigorous mathematical descriptions of momentum, heat, and mass transfer balances that unified disparate physical processes underlying unit operations. Building on Arthur D. Little's early 20th-century framework of unit operations as standardized physical steps in chemical processes, researchers at the University of Wisconsin-Madison, including R. Byron Bird, Warren E. Stewart, and Edwin N. Lightfoot, developed a comprehensive approach emphasizing conservation laws and analogous transport equations. This integration transformed unit operations from empirical practices into a scientifically grounded discipline, enabling predictive modeling of phenomena like fluid flow and diffusion across scales.^[17]^[18] A landmark in this evolution was the 1960 publication of Transport Phenomena by Bird, Stewart, and Lightfoot, which formalized the mathematical unification of unit operations through transport equations, becoming the foundational text for chemical engineering curricula worldwide. The book presented momentum, energy, and mass transport as interconnected phenomena governed by similar differential equations, such as the Navier-Stokes equations for fluid momentum and Fourier's law for heat conduction, thereby shifting focus from operation-specific correlations to fundamental principles. Its influence extended beyond academia, informing process design and optimization in industries reliant on separation and reaction systems.^[19]^[20] Post-World War II institutional growth within the American Institute of Chemical Engineers (AIChE) bolstered this theoretical progress, with the chartering of the first technical division—the Nuclear Engineering Division—in 1954, followed by expansions into areas like environmental and transport processes that supported unit operations research. This organizational development facilitated specialized programming and knowledge exchange, enhancing the discipline's professional infrastructure. Concurrently, the concepts of unit operations and transport phenomena spread internationally to Europe and Asia, driven by U.S. educational models, multinational collaborations, and postwar reconstruction efforts; for instance, new chemical engineering departments emerged in British universities like Cambridge and Leeds in the 1950s, while France established institutions such as the École Supérieure des Industries Chimiques in 1887, and Japan's programs at Kyoto and Tokyo Institute of Technology expanded amid industrial recovery.^[21]^[22]^[23] Since the 1980s, the evolution has incorporated computational modeling, particularly computational fluid dynamics (CFD), to simulate complex transport processes in unit operations, addressing limitations of analytical solutions in non-ideal geometries and multiphase flows. Enabled by advances in computing power and numerical methods like finite volume discretization, CFD tools such as Fluent—pioneered in the early 1980s—allowed engineers to predict velocity profiles, heat transfer coefficients, and mass dispersion in reactors and separators with greater accuracy, reducing reliance on physical prototypes. This digital integration has since become standard in process design, exemplified by applications in optimizing distillation columns and fluidized beds, and continues to evolve with multiphysics simulations for sustainable engineering.^[24]^[25]

Key Examples

Separation Operations

Separation operations encompass a range of unit operations that exploit physical differences in phase equilibria, densities, or solubilities to isolate components from mixtures without inducing chemical reactions, forming a core subset of mass transfer-based unit operations. These methods are essential in chemical engineering for purifying liquids, gases, and solids, often achieving high selectivity through controlled energy inputs or mechanical forces. Representative examples include distillation for vapor-liquid systems, filtration and sedimentation for solid-liquid dispersions, and extraction for liquid-liquid partitions, each leveraging equilibrium or kinetic principles to drive separation efficiency.^[26] Distillation relies on the principles of vapor-liquid equilibrium (VLE), where components with differing volatilities are separated by repeated vaporization and condensation cycles. In a typical setup, a feed mixture is heated in a reboiler to generate vapor that rises through a column packed with trays or structured packing, allowing intimate contact between ascending vapor and descending liquid reflux. Equilibrium stages are determined using methods like the McCabe-Thiele graphical technique for binary systems, which plots VLE data (y-x diagram) alongside operating lines representing material balances. The rectifying section operating line follows the equation y = \frac{R}{R+1} x + \frac{x_D}{R+1}, where y is the vapor mole fraction, x is the liquid mole fraction, R is the reflux ratio, and x_D is the distillate composition; the stripping section line is y = \frac{\bar{L}}{\bar{V}} x - \frac{B x_B}{\bar{V}}, assuming constant molal overflow for energy balance simplification. This approach enables calculation of minimum reflux and theoretical stages, optimizing column height and energy use.^[27] Filtration and sedimentation achieve solid-liquid separation through mechanical retention or gravitational settling, respectively, with filtration forming a porous cake that impedes further flow while sedimentation exploits density differences for clarification. In filtration, the process follows Darcy's law, describing the superficial velocity v of filtrate through the cake as v = -\frac{k}{\mu} \nabla P, where k is the permeability, \mu is the fluid viscosity, and \nabla P is the pressure gradient; cake formation progressively reduces permeability, requiring pressure buildup for constant-rate operation. Sedimentation, often batch or continuous in settlers, relies on hindered settling where particle velocity decreases with solids concentration, modeled by Stokes' law for dilute suspensions but adjusted for compression zones in thicker slurries. Common equipment includes plate-and-frame presses or rotary vacuum filters for filtration, and centrifuges—such as tubular-bowl types—for enhanced sedimentation, where centrifugal acceleration (up to 10,000g) replaces gravity to separate emulsions or clarify broths rapidly.^[28]^[29] Liquid-liquid extraction partitions solutes between two immiscible solvents based on relative solubilities, typically involving a feed dissolved in one phase contacted with a solvent-rich extractant in mixer-settlers or column extractors. Solvent selection prioritizes high distribution coefficients (e.g., favoring non-polar solvents for organic solutes from aqueous feeds), low mutual solubility to minimize entrainment, and favorable physical properties like density difference for phase disengagement; common choices include hexane for hydrocarbons or tributyl phosphate for metals. Stage-wise calculations employ equilibrium data in a triangular diagram or Kremser equation for countercurrent cascades, where the number of theoretical stages N is given by N = \frac{\ln \left[ \frac{E_{N+1} - E_1^*}{E_1 - E_1^*} \left(1 - \frac{1}{m S}\right) + \frac{1}{m S} \right]}{\ln (m S)}, with m as the slope of the equilibrium line, S as the solvent-to-feed ratio, and E as extraction factors, enabling prediction of outlet compositions and solvent economy.^[30]^[31] Among these, energy efficiency varies significantly: distillation is highly energy-intensive due to latent heat requirements (often 70-80% of process energy in refineries), while filtration and sedimentation consume primarily mechanical power (e.g., pumps or centrifuges at typically 0.5-5 kWh/m³ filtrate, depending on slurry solids content and equipment), and extraction balances moderate agitation energy with solvent recovery distillation, achieving up to 50% lower overall consumption than pure distillation routes through hybrid designs. These operations collectively underscore the trade-offs in capital, operating costs, and throughput, with centrifuges enabling compact, high-g separations in space-constrained applications like pharmaceuticals.^[26]^[32]

Heat Transfer Operations

Heat transfer operations involve the exchange of thermal energy between fluids or between a fluid and a solid surface without changing the chemical composition, relying on conduction, convection, and radiation principles. These are crucial for heating, cooling, concentration, and phase changes in process streams. Key examples include heat exchangers for sensible heat transfer and evaporation for latent heat removal via vaporization. Shell-and-tube heat exchangers are widely used, where one fluid flows through tubes and another across the shell, transferring heat through tube walls. Design follows the log mean temperature difference (LMTD) method: Q = U A \Delta T_{lm}, where Q is heat duty, U is overall heat transfer coefficient (typically 200-1000 W/m²K for liquids), A is area, and \Delta T_{lm} = \frac{\Delta T_1 - \Delta T_2}{\ln(\Delta T_1 / \Delta T_2)} for countercurrent flow. Fouling factors adjust U, and pressure drop calculations ensure flow rates.^[33] Evaporation concentrates solutions by boiling off solvents, often in multiple-effect evaporators to recover heat from vapor. Single-effect energy use is high (~600-1000 kJ/kg water evaporated), but multiple effects reduce it to 100-200 kJ/kg by reusing steam. Boiling point elevation in non-volatile solutes affects vacuum operation to lower temperatures, preventing degradation in food or pharma applications.^[34]

Reaction and Mixing Operations

Mixing operations are fundamental unit operations that achieve physical blending of materials to ensure uniformity, often enhancing contact in processes involving chemical reactions (unit processes). These rely on mechanical agitation or fluid dynamics to overcome diffusion limitations, improving efficiency in reactors, blenders, and separators. In stirred tanks, mixing ensures homogeneity for consistent reaction rates or product quality. Mechanisms vary by flow regime: laminar mixing (low Reynolds number Re_i < 10) depends on shear and diffusion, suitable for viscous fluids; turbulent mixing (Re_i > 10^4) uses eddies for rapid blending in low-viscosity systems. Power consumption is given by P = N_p \rho N^3 D^5, where N_p is the power number (e.g., ~5 for Rushton turbines in turbulent flow), \rho density, N speed, D impeller diameter; in turbulent conditions, N_p is constant. Baffled vessels and impeller designs (e.g., propellers for axial flow) optimize energy, with mixing times of 10-100 seconds in industrial scales up to 100 m³.^[35] Mixing integrates with heat transfer via jackets or coils to control temperatures during exothermic or endothermic reactions, preventing hotspots or maintaining kinetics. In multifunctional setups, mixing enhances transport, achieving uniform profiles and higher yields. Residence time distribution (RTD) analysis, via tracers, quantifies mixing quality; ideal mixing minimizes variance for consistent processing. Poor mixing can reduce selectivity by 20-50% in multiphase systems.^[36]

Applications and Design

Role in Process Engineering

Unit operations form the foundational elements of process engineering, enabling the design and optimization of chemical processes by breaking down complex systems into modular, interconnected steps. In process flowsheeting, these operations are sequenced to transform raw materials into products through logical progression, such as initiating with mixing or heating to prepare feedstocks, followed by separation via distillation or extraction, and concluding with purification operations like filtration to meet specifications.^[37] This modular approach, depicted in process flow diagrams (PFDs), facilitates material and energy balances across the entire flowsheet, ensuring efficient resource utilization and process viability.^[37] Economic considerations in assembling unit operations emphasize capital and operating cost estimation to evaluate process feasibility. The Lang factor method provides a rapid assessment by multiplying the total purchased equipment cost by a plant-specific multiplier to approximate fixed capital investment (FCI) and total capital investment (TCI); for fluid processing plants typical in chemical engineering, this factor is approximately 5.0 for FCI.^[38] Safety evaluations integrate Hazard and Operability (HAZOP) studies, which systematically examine each unit operation for deviations in parameters like flow or pressure, identifying potential hazards and recommending safeguards to mitigate risks such as equipment failure or overpressure.^[39] The integration of unit operations draws on multidisciplinary principles, linking thermodynamics for phase equilibria and energy transfers, kinetics for reaction rate modeling in reactors, and control systems for dynamic regulation of process variables.^[40] This holistic approach ensures that individual operations align with overarching process dynamics, as seen in courses combining these fields for reactor design and process control.^[40] An illustrative case is the generic petroleum refining process, where modularity allows sequential assembly of unit operations and unit processes: crude oil first enters an atmospheric distillation unit for initial separation into fractions by boiling point, followed by conversion processes like catalytic cracking to produce lighter hydrocarbons such as gasoline, and concluding with treatment unit operations for blending and impurity removal.^[41] This configuration highlights the adaptability of unit operations, enabling refineries to reconfigure modules based on market demands for specific fuels while maintaining overall process integrity.^[41]

Scale-up Considerations

Scale-up of unit operations involves transitioning processes from laboratory or pilot scales to full production while maintaining performance, safety, and efficiency. This enlargement often introduces complexities due to changes in physical dimensions, flow regimes, and transport phenomena, requiring systematic approaches to predict and mitigate deviations from small-scale behavior.^[42] Fundamental scale-up principles rely on achieving similarity between scales to ensure comparable process outcomes. Geometric similarity maintains proportional linear dimensions, such as tank diameter to height ratios, minimizing uncertainties in flow patterns. Kinematic similarity preserves velocity profiles and flow trajectories, while dynamic similarity equates force ratios, including inertial, viscous, and gravitational forces, to replicate stress distributions. These similarities are essential for operations like mixing and heat transfer, where deviations can alter efficiency.^[43]^[44] In mixing operations, rules of thumb guide scale-up by targeting key parameters. For turbulent blending, constant power per unit volume (P/V) ensures adequate agitation intensity, as power input scales with the cube of impeller diameter while volume scales with its cube, leading to higher absolute power needs at larger scales. This approach, often combined with constant impeller tip speed (π n D), balances blending time and shear forces, with dimensionless mixing time (n t_m) approximately 39 for standard geometries like a tank diameter three times the impeller diameter.^[42] Common challenges arise from altered transport rates and fluid dynamics during scale-up. Heat and mass transfer limitations intensify because surface area scales with the square of linear dimensions while volume scales cubically, reducing the area-to-volume (A/V) ratio and potentially causing hotspots or incomplete mixing in larger vessels. Fluid dynamics changes are pronounced via Reynolds number effects, defined as Re = ρ v D / μ, where ρ is density, v is velocity, D is characteristic length, and μ is viscosity; low Re in small scales favors laminar flow, but high Re in production promotes turbulence, altering mixing uniformity and transfer coefficients.^[42]^[45] Strategies to address these include dimensional analysis via the Buckingham Pi theorem, which reduces variables to dimensionless groups like Re, Prandtl (Pr), and Nusselt (Nu) numbers for predicting scale effects without full prototyping. This theorem states that if a problem involves n variables with k fundamental dimensions, it can be reformulated into n-k dimensionless π terms, enabling extrapolation of lab data to larger scales. Pilot plant testing validates these predictions by operating intermediate-scale units (e.g., 1/10th production size) to measure real-world deviations in heat transfer or residence time distributions.^[46]^[47] Modern tools enhance scale-up accuracy through computational simulation. Software like Aspen Plus facilitates modeling of unit operations, incorporating custom blocks for reactions, separations, and heat exchangers to simulate scale transitions and optimize parameters such as flow rates or energy inputs. Its recipe-based scale-up features integrate economic and safety analyses, allowing rapid iteration from conceptual design to production feasibility without extensive physical testing. As of 2025, advancements include AI and machine learning for predictive modeling and process intensification techniques to enhance efficiency in scaling unit operations.^[48]^[49]

Unit Processes

Unit processes in chemical engineering encompass the chemical transformations and reactions that alter the molecular structure of substances, such as breaking and forming chemical bonds, in contrast to the physical manipulations of unit operations. These processes are inherently dependent on the specific molecular composition and reactivity of the materials involved, making them distinct from more universal physical principles. For instance, oxidation involves the addition of oxygen or removal of hydrogen from a compound, while hydrogenation adds hydrogen across double bonds, both critical in synthesizing intermediates like alcohols or pharmaceuticals.^[50] Key examples of unit processes include polymerization, where monomers link to form long-chain polymers like polyethylene, and fermentation, a biological-chemical reaction where microorganisms convert sugars into products such as ethanol or antibiotics. These processes rely on detailed reaction mechanisms to understand pathways, such as stepwise addition in polymerization or enzymatic catalysis in fermentation, alongside stoichiometric balances that dictate reactant and product ratios. The kinetics of these reactions are often modeled using rate laws.^[50] In distinction from unit operations, which apply general physical laws like heat and mass transfer across diverse substances, unit processes are chemistry-specific, requiring tailored conditions such as catalysts or pH control to achieve desired transformations. This specificity arises because chemical changes depend on electronic structures and reaction pathways unique to each system, rather than scalable physical phenomena. Historically, unit processes co-evolved with unit operations in the formative years of chemical engineering curricula during the early 20th century, with educational debates in the 1930s—such as those advocating for balanced training in both—solidifying their complementary roles in process design. Unit operations often enable these chemical processes by providing the necessary physical environments, like mixing or heating in reactors.^[50]^[51]

Integration with Unit Operations

In chemical engineering, the integration of unit operations with unit processes often manifests in hybrid systems that combine reaction and separation functionalities within a single apparatus, such as reactive distillation, where chemical reactions occur simultaneously with vapor-liquid separation to enhance product yields and reduce byproducts.^[52] This approach leverages the removal of reaction products in situ to shift equilibrium-limited reactions toward completion, as demonstrated in industrial applications for esterification and etherification processes.^[53] Process synthesis tools facilitate such integrations through structured design paradigms, notably the hierarchical decomposition method proposed by J.M. Douglas, which breaks down the synthesis problem into sequential levels starting from the batch process and progressing to detailed utility systems, enabling systematic evaluation of integrated alternatives.^[54] This methodology promotes the identification of multifunctional units by addressing mass and energy balances at progressively finer scales, avoiding exhaustive enumeration of options.^[55] The primary benefits of these integrations include substantial efficiency gains, such as significant reductions in energy consumption and capital costs compared to sequential processes, with reported savings of 25-40% in energy and up to 30% in capital for certain configurations, due to minimized equipment and streamlined material flows.^[52]^[56] However, challenges arise from increased complexity in control, particularly the coupled mass-energy balances that demand advanced modeling to manage interactions between reaction kinetics and separation dynamics, potentially leading to operational instabilities if not properly addressed.^[57] Emerging trends in bioprocesses highlight the integration of fermentation—a unit process for microbial growth and product formation—with filtration operations for continuous cell recycle and product recovery, as seen in membrane-integrated bioreactors that maintain high cell densities while enabling real-time separation.^[58] This synergy supports scalable production of biologics like monoclonal antibodies, with integrated continuous bioprocessing achieving significantly higher productivities than traditional batch methods, including cell densities up to threefold higher, by reducing downtime and contamination risks.^[59]

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Mar 5, 2005 · We consider scaling of flow within a stirred tank with increasing Reynolds number. Experimental results obtained from two different tanks of ...
[44]
A generalization of the Π-theorem and dimensional analysis - PNAS
Dimensional analysis reduces a problem's degrees of freedom to the minimum and thus suggests the most economical scaling laws. It can be particularly useful in ...
[45]
Pilot Plant Testing for Liquid-Liquid Extraction - AIChE
When designing a liquid-liquid extraction column, pilot plant testing generates the data necessary for accurate scaleup to the production rate.
[46]
Aspen Plus | Leading Process Simulation Software - AspenTech
Optimize design and support operational decisions with quick and easy-to-build custom unit operations models. ... Recipe Based Process Scale Up. Develop and ...
[47]
(PDF) Units of Chemical Engineering Operations - ResearchGate
Dec 20, 2022 · The concepts of unit operations, rate processes and thermodynamic equilibrium have provided a framework to design the process equipment.
[48]
Some aspects of fermentation as an unit process in chemical ...
There are described possibilities of scale up in stirred tank fermenters being based on known relations of mass-, energy-and heat transfer.
[49]
https://www.aiche.org/resources/publications/cep/2024/march/advanced-manufacturing-progress-process-scale-learnings-rapid
[50]
Reactive Distillation: Stepping Up to the Next Level of Process ...
Reactive distillation (RD) is an efficient process intensification technique that integrates chemical reaction and distillation in a single apparatus.
[51]
Designing reactive distillation processes: present and future
This paper will focus on the available design issues and techniques for reactive distillation (RD) processes. Industrial relevance requires design issues not to ...
[52]
A hierarchical decision procedure for process synthesis - Douglas
The procedure is evolutionary, using a hierarchy of decision levels, adding structure at each level, and using heuristics and generating alternatives.Missing: 1988 | Show results with:1988
[53]
[PDF] A generalized superstructure-based framework for process synthesis
... hierarchical approaches for process synthesis is the method discussed in Douglas (Douglas, 1985, 1988) where the synthesis problem is decomposed into five ...
[54]
Opportunities and challenges for process control in process ...
Reactive distillation can be considered as reaction and distillation combined into one new unit operation and this integrated separation process is a good ...Missing: benefits | Show results with:benefits
[55]
Integration of Fermentation and Membrane Processes - SpringerLink
It is the purpose of this paper to discuss the operation of cell recycle systems by membrane filtration and membrane downstream processes for “in-situ” product ...
[56]
Integrated continuous bioprocessing: Economic, operational ... - NIH
This paper presents a systems approach to evaluating the potential of integrated continuous bioprocessing for monoclonal antibody (mAb) manufacture.