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Adiabatic flame temperature

The adiabatic flame temperature is the maximum that combustion products can theoretically reach during the complete of a and oxidizer under ideal adiabatic conditions, where no heat is lost to the surroundings, no work is performed, and the process occurs at constant without of products. This represents an upper for temperatures in practical and is calculated by conserving the total of the , equating the of the reactants (at their initial ) to that of the products at the final equilibrium . Key factors influencing the adiabatic flame temperature include the type of and oxidizer, the stoichiometric (with the highest value at exact ), initial temperature and pressure of the reactants, and the presence of excess air or diluents, which lower the temperature by absorbing . For common fuels burning in air at standard conditions (298 and 1 atm), values range from about 2230 for to 2480 for , while using pure oxygen as the oxidizer can exceed 3000 due to the absence of dilution. In reality, actual temperatures are lower due to losses, incomplete , and of species like CO₂ and H₂O at high temperatures, which absorbs energy. The concept is fundamental in combustion engineering for designing efficient and safe systems, such as gas turbines, rocket engines, and industrial furnaces, where it guides material selection to withstand thermal stresses and predicts pollutant formation like NOx, which increases with higher temperatures. Tools like NASA's Chemical Equilibrium with Applications (CEA) software compute these temperatures by minimizing Gibbs free energy to find equilibrium compositions under specified constraints.

Fundamentals

Definition

The adiabatic flame temperature represents the theoretical maximum temperature achieved during the complete combustion of a and oxidizer in an , where no is transferred to or from the surroundings. itself is an exothermic in which a combines with an oxidizer, typically oxygen from air, converting energy into through rapid oxidation. Under ideal conditions, all the released raises the temperature of the combustion products, assuming a reversible with no work other than flow work in constant-pressure scenarios. This temperature serves as an upper limit for combustion processes and is calculated based on the energy balance where the of the reactants equals that of the products at the final state. In an , the absence of exchange ensures that the system's change is solely due to the reaction's heat release. Unlike the adiabatic flame temperature, actual flame temperatures observed in real-world applications are significantly lower because of non-ideal effects, including losses to the , incomplete fuel oxidation, and dissociation of high-temperature species like and into atoms or radicals, which absorb energy. These deviations highlight the idealized nature of the adiabatic assumption, providing a benchmark for evaluating in devices such as engines and burners.

Types of Adiabatic Processes

In the context of adiabatic flame temperature, processes are categorized into constant volume (isochoric) and constant pressure (isobaric) types, each reflecting distinct thermodynamic constraints on during the reaction. These classifications build on the core concept of adiabatic flame temperature as the maximum achievable product temperature with no heat loss to the surroundings. Constant volume adiabatic flame temperature applies to scenarios where the volume remains fixed, preventing any work from being done by the . All released is thus directed toward raising the of the combustion products, yielding a higher temperature. This condition is commonly simulated in closed bomb apparatuses during laboratory experiments, which provide a confined environment to study fundamental behaviors such as and rise without external influences. Conversely, constant pressure adiabatic flame temperature describes processes where pressure is held constant, allowing the products to expand and perform work on the surroundings. This dissipates a portion of the released as mechanical work, resulting in a lower product than in the isochoric case. Such conditions are prevalent in practical applications like open flames and gas burners, where combustion gases vent freely into the atmosphere, mimicking steady-flow systems in furnaces or engines. Typically, the constant volume adiabatic flame temperature exceeds the constant value by 200–500 , depending on fuel composition and initial conditions; for instance, stoichiometric methane-air at 298 yields about 2890 at constant volume versus 2320 at constant .

Thermodynamic Principles

Energy Balance in

The first law of thermodynamics, which expresses the conservation of energy, is fundamental to understanding the energy balance in combustion processes. It states that the change in the internal energy of a system equals the heat added to the system minus the work done by the system: \Delta U = Q - W. In the context of adiabatic combustion, where no heat is exchanged with the surroundings (Q = 0), this simplifies to \Delta U = -W. For processes at constant volume, the work term W is zero, leading to \Delta U = 0, meaning the internal energy of the products equals that of the reactants. At constant pressure, the work done is W = P \Delta V, and the balance shifts to the enthalpy change \Delta H = \Delta U + P \Delta V = 0, establishing that the enthalpy of the products matches the enthalpy of the reactants under adiabatic conditions. In adiabatic combustion, the chemical energy stored in the reactants is released during the reaction and fully converted into thermal energy of the combustion products, without any dissipation to the environment. This heat release, often denoted as Q, represents the exothermic nature of the combustion reaction, where the bond energies in the products are lower than those in the reactants, liberating energy that raises the temperature of the system. The adiabatic assumption ensures that all this released energy contributes to the internal or enthalpic state of the products, providing the basis for calculating the maximum achievable flame temperature. This conversion is idealized as complete, with the energy balance capturing the transformation from chemical potential to sensible heat. Combustion systems can be analyzed as either closed or open systems, and the adiabatic condition simplifies the energy balance in both by eliminating heat transfer terms. In a closed system, such as a batch reactor, the fixed mass confines the analysis to internal energy changes, with the adiabatic constraint preventing thermal losses and focusing the balance on reaction-induced variations within the volume. For open systems, like continuous-flow combustors, the steady-state energy balance incorporates mass flows, but the adiabatic assumption removes boundary heat fluxes, reducing the equation to equate inlet and outlet enthalpies adjusted for any shaft work. This simplification highlights how the no-heat-transfer idealization streamlines conservation principles across system types. The energy balance for adiabatic flame temperature assumes a reversible , implying no generation from irreversibilities such as mixing or finite-rate . In this ideal reversible case, the occurs quasistatically, preserving the maximum work potential and ensuring that the temperature rise reflects pure without dissipative losses. This assumption underpins the theoretical framework, allowing to directly link reactant and product states without additional terms complicating the balance.

Role of Enthalpy and Internal Energy

In adiabatic combustion, (H) and (U) function as key thermodynamic state functions that enable the precise quantification of without external exchange. Internal energy U encapsulates the total kinetic and potential energies of the molecules within the system, excluding contributions from bulk motion or external work potentials. H extends this by accounting for flow work in open systems, defined as H = U + PV, where P is and V is volume; this formulation is particularly apt for processes involving steady flow, such as in where reactants and products may enter and exit control volumes. For constant-volume adiabatic combustion, the absence of expansion work simplifies the energy balance to Uproducts = Ureactants, directly linking the internal energies of the initial mixture and final products to determine the flame temperature. This equality holds because no is lost and no work is performed, conserving the system's intrinsic content. In contrast, constant-pressure adiabatic processes, common in open-flame configurations, employ the balance Hproducts = Hreactants, as the term accommodates the pressure-volume interactions without altering the total . These balances underscore how U governs closed, rigid systems, while H is indispensable for flow-dominated scenarios. The increase (ΔT) in adiabatic flames emerges from the temperature-dependent contributions, integrated via the specific heats at constant volume (Cv) for changes and at constant pressure (Cp) for changes. Specifically, variations in U and H with are captured by ΔU = ∫ Cv dT and ΔH = ∫ Cp dT, where Cp and Cv are functions of , often modeled using fits for accuracy across flame conditions. To establish a consistent reference, enthalpies of formation (ΔHf) are standardized at 298 K and 1 atm, serving as the baseline for calculating absolute enthalpies in both U and H balances; for instance, elements like H2, O2, N2, and solid carbon are assigned zero ΔHf at this state.

Calculation Methods

Theoretical Approach

The theoretical approach to calculating the adiabatic flame temperature centers on achieving in an adiabatic combustion process, where the total of the reactants equals that of the products at the final . The methodology starts by specifying the initial conditions of the reactants, including their composition, , and pressure, from which their enthalpies are determined using standard thermodynamic data. The products' composition is then estimated assuming complete or equilibrium reaction, and an initial guess for the product is made; the enthalpies of the products at this guessed are computed and compared to the reactants' . If they do not match, the guess is adjusted iteratively—typically using methods like successive substitution or Newton-Raphson—until the energy balance is satisfied within a specified tolerance. This iteration is essential due to the temperature dependence of key properties, such as molar heat capacities at constant pressure C_p(T) and standard enthalpies of formation \Delta H_f^\circ(T), which vary nonlinearly and affect the overall enthalpy calculations. Thermodynamic data for these properties are sourced from established databases or tables, often derived from statistical mechanics or experimental measurements, providing polynomial expressions (e.g., NASA polynomials) valid over wide temperature ranges for common combustion species like CO_2, H_2O, and radicals. These sources ensure accurate representation of real gas behavior and dissociation effects at high temperatures. A core assumption in this approach is that the combustion products achieve chemical equilibrium instantaneously, determined by minimizing the Gibbs free energy or solving for equilibrium constants, while disregarding finite-rate kinetics that might limit actual reaction progress. This equilibrium composition is recalculated at each iteration step to account for species shifts, such as dissociation of CO_2 into CO and O, which absorb energy and lower the predicted temperature. The method thus prioritizes thermodynamic limits over kinetic constraints, providing an upper bound on achievable temperatures. To streamline the iterative process, especially for complex mixtures, computational tools have become standard. The Chemical Equilibrium with Applications (CEA) program, developed by and McBride, with a modernized open-source version (CEA2022) released in 2024, automates the equilibrium solving and property lookups using a vast species database. Similarly, open-source libraries such as implement the same principles via stiff ODE solvers for equilibrium, enabling rapid computation for parametric studies across fuel types and conditions. These tools have supplanted manual methods, enhancing accuracy and accessibility for engineering applications.

Key Equations and Assumptions

The at constant volume is derived from of thermodynamics for an , where the change in is zero, leading to the condition that the of the products at T_{ad} equals the of the reactants: U_p(T_{ad}) = U_r. This can be expressed approximately as \int_{T_r}^{T_{ad}} C_{v,p}(T) \, dT \approx -\frac{\sum n_i \Delta H_{f,i}^\circ}{n_p} (neglecting the \Delta n_g RT term), where C_{v,p} is the specific heat at constant volume of the products, T_r is the reactant temperature, n_i are stoichiometric coefficients, and \Delta H_{f,i}^\circ are standard heats of formation (with \Delta U_f \approx \Delta H_f). For the constant pressure case, which is more common in open combustion systems, the enthalpy balance applies: H_p(T_{ad}) = H_r, or equivalently \int_{T_r}^{T_{ad}} C_{p,p}(T) \, dT = -\frac{\sum n_i \Delta H_{f,i}^\circ}{n_p}, with C_{p,p} as the specific heat at constant pressure of the products. This formulation assumes no work beyond the boundary . The full expression for solving T_{ad} at constant pressure incorporates species-specific temperature-dependent heat capacities and formation enthalpies: \sum_i n_{p,i} \left( \int_{T_0}^{T_{ad}} C_{p,i}(T) \, dT + \Delta H_{f,i}^\circ \right) = \sum_j n_{r,j} \left( \int_{T_0}^{T_r} C_{p,j}(T) \, dT + \Delta H_{f,j}^\circ \right), where the left sum is over product species i with moles n_{p,i}, the right over reactants j with moles n_{r,j}, T_0 is a reference temperature (often 298 K), and the integrals account for sensible enthalpy changes. This nonlinear equation is typically solved iteratively using polynomial fits for C_p(T). A similar formulation applies for constant volume using C_v and \Delta U_f^\circ. Key assumptions underlying these equations include ideal gas behavior for all species, where enthalpy and internal energy depend solely on temperature; complete combustion to stable products without dissociation; and a stoichiometric fuel-oxidizer ratio with initial reactant temperature T_r. These simplifications enable analytical or numerical solution but idealize real flames. Dissociation at high temperatures, such as \ce{CO2 ⇌ CO + 1/2 O2}, consumes energy through endothermic reactions, lowering the actual T_{ad} from the no-dissociation prediction by 200–500 K depending on conditions. This effect is corrected by iteratively solving the energy balance coupled with chemical equilibrium constants from the law of mass action, adjusting product compositions until consistency is achieved.

Influencing Factors

Reactant Composition

The adiabatic flame temperature is fundamentally influenced by the of the reactants, as it determines the total released during and how that is distributed among the products. Fuels with higher heating values (HHV) generally yield higher adiabatic flame temperatures because they release more per unit upon complete oxidation. For instance, fuel achieves a higher adiabatic flame temperature compared to due to its superior HHV of approximately 142 MJ/kg versus 55.5 MJ/kg for , resulting in temperatures around 2,425 for stoichiometric hydrogen-air mixtures versus about 2,230 for methane-air. Similarly, fuels like exhibit even higher temperatures owing to their elevated content, though practical applications often favor hydrocarbons for stability. The choice of oxidizer also plays a critical role, primarily through its impact on dilution effects in the combustion products. When air serves as the oxidizer, its 21% oxygen content and 79% nitrogen dilute the reaction zone, absorbing heat and lowering the adiabatic flame temperature; in contrast, pure oxygen eliminates this nitrogen ballast, enabling significantly higher temperatures. For example, stoichiometric hydrogen-oxygen combustion reaches approximately 3,509 K, compared to 2,230 K with air, highlighting the dilution's suppressive effect. This principle extends to other fuels, where oxygen-enriched environments can boost temperatures by 500–1,000 K, enhancing energy efficiency in applications like rocket propulsion. The equivalence ratio (φ), defined as the fuel-to-oxidizer ratio relative to stoichiometric conditions, optimizes the adiabatic flame temperature at φ = 1, where complete maximizes energy release without excess reactants. Deviations from reduce the temperature: mixtures (φ < 1) introduce excess oxidizer that absorbs heat, while rich mixtures (φ > 1) leave unburned that limits oxidation. Calculations for methane-air flames show a peak of about 2,200 K at φ = 1, dropping to around 1,800 K at φ = 0.8 and 1,900 K at φ = 1.2 under standard conditions. This bell-shaped curve is consistent across fuels like , where higher fractions in the shift the peak slightly but maintain the stoichiometric maximum. Impurities and diluents in the reactants further modulate the adiabatic flame temperature by parasitically consuming reaction energy. , for example, acts as a through and , reducing temperatures; in methane-air at φ = 1.2 and 322 initial , 100% relative lowers the flame from 2,269 to 2,045 . Similarly, inert diluents like excess or decrease the effective , with effects akin to leaning the —e.g., adding 200% theoretical air to octane halves the temperature from 2,200°C to 1,100°C. These reductions are particularly relevant in real-world fuels containing trace water or additives, underscoring the need for purified reactants in high-temperature processes.

Environmental Conditions

The adiabatic flame temperature is influenced by environmental conditions such as pressure and initial temperature of the reactants, which modify the energy balance during . Higher pressure slightly increases the adiabatic flame temperature, typically by about 50 K for a rise from 1 to 30 bar in methane-air mixtures, due to the suppression of molecular dissociation according to . This occurs because elevated pressure shifts the toward products with fewer moles of gas, reducing the energy required for dissociation and thereby raising the temperature; the modification PV = nRT reflects this through a decrease in the effective number of moles n. In high-pressure environments, such as those in advanced engine designs, this effect becomes relevant for optimizing performance, though the increase remains modest compared to other factors. The initial temperature of the reactants, denoted T_0, also affects the adiabatic flame temperature T_{ad}, where T_{ad} = T_0 + \Delta T and \Delta T (the temperature rise) decreases with higher T_0 due to reduced change, yet the overall T_{ad} still rises. For instance, in ammonia-methane-air mixtures, increasing T_0 from 300 to 500 elevates T_{ad} nonlinearly, enhancing reaction rates and propagation. This linear contribution of T_0 to T_{ad} is fundamental in thermodynamic models for varying ambient conditions. Humidity in the intake air, primarily as , acts as a that lowers the adiabatic flame temperature by absorbing heat through its high , typically reducing it by approximately 40–50 K (or 1.7–2.3%) for humidity levels from 0 to 120 grains of water per pound of dry air. In humidified systems, dissociates endothermically, further cooling the flame and altering concentrations, which can decrease peak temperatures by 1.7-2.3% depending on burner design. Similar effects occur with other s like excess , emphasizing the role of environmental in real-world flame behavior. Under non-stoichiometric conditions, the equivalence ratio interacts with these environmental parameters, where weakly amplifies the temperature peak near stoichiometric ratios (φ ≈ 1) while exacerbates reductions in lean mixtures by enhancing heat dilution. This interplay, observed in premixed flames, underscores how external conditions modulate compositional effects without altering core .

Practical Examples

Hydrocarbon Flames

Hydrocarbon flames, particularly those involving common fuels such as , , and , achieve theoretical adiabatic flame temperatures under stoichiometric conditions that reflect the energy release from complete without heat loss. These temperatures are calculated assuming constant processes at 1 atm, with reactants entering at 298 . For instance, stoichiometric of in air yields an adiabatic flame temperature of 2226 , while in pure oxygen reaches 3087 . , often approximated as a mixture similar to (C₈H₁₈), has a stoichiometric adiabatic flame temperature in air of approximately 2260 . Recent data incorporating biofuels highlight in air at 2238 under the same conditions. The following table summarizes theoretical adiabatic flame temperatures for selected hydrocarbon fuels under stoichiometric conditions (constant pressure, 1 atm, initial temperature 298 ): Values sourced from chemical equilibrium calculations using mechanisms like GRI-Mech 3.0 and CEA. A key variation arises from the choice of oxidizer: pure oxygen produces adiabatic flame temperatures over 1000 K higher than air for the same , primarily because air's content absorbs without participating in the , lowering the peak . For example, propane's rises by approximately 837 K when switching from air to oxygen. This difference underscores the role of reactant in influencing flame energetics, as discussed in prior sections on influencing factors.

Non-Hydrocarbon Flames

Non-hydrocarbon flames encompass combustions involving fuels such as , , , , and metals, which exhibit distinct behaviors compared to hydrocarbon counterparts due to their or synthetic compositions. These flames often achieve high temperatures driven by strong bond energies in products like or metal oxides, but they can produce solid residues or exhibit rapid propagation rates that influence practical applications. For instance, 's high leads to flammability limits and elevated reactivity, while metal combustions generate oxides that retain heat. Representative adiabatic flame temperatures for select non-hydrocarbon fuels under stoichiometric conditions at standard initial and (25°C, 1 atm) are summarized below. These values assume complete without , highlighting the potential for temperatures exceeding 3000 in oxygen-rich environments, though actual flames may deviate due to incomplete reactions or heat losses. Values are from calculations using tools like CEA.
FuelOxidizerAdiabatic Flame Temperature ()Notes
(H₂)Air2395High ; calculations yield ~2378 .
(CO)Air2394Produces CO₂ and H₂O; temperature sensitive to excess air.
(H₂/CO mix)AirUp to 2500Varies with H₂:CO ratio (e.g., 50:50 ~2200 ); common in processes.
(NH₃)Air2073Lower than hydrocarbons; stoichiometric peak 1800°C, relevant for carbon-free green energy transitions.
Aluminum (Al)O₂3730Forms solid Al₂O₃; high exothermicity leads to and vapor-phase flames.
Metal combustions, such as those of aluminum or magnesium in , demonstrate unique behaviors including intense luminosity and solid product formation that sustains high local temperatures despite radiative losses. Aluminum's reaction with oxygen yields an adiabatic temperature around 3730 K, promoting particle vaporization and subsequent oxide condensation, which is leveraged in energetic materials for controlled energy release. Syngas flames from processes, typically comprising H₂, , and diluents like CO₂, reach up to 2500 K depending on composition, with higher H₂ content elevating temperatures due to its endothermic limits. In contrast, emerges as a promising non-carbon in 2025 green energy contexts, offering ~2073 K in air under lean conditions, though its low necessitates blending for . These flames underscore the diversity in non-hydrocarbon systems, where product phases and profoundly affect thermal profiles.

Applications and Limitations

Industrial Uses

In internal combustion engines and gas turbines, the adiabatic flame temperature serves as a critical for predicting maximum temperatures, enabling engineers to optimize designs for while mitigating emissions through strategies like fuel dilution or that limit peak temperatures. For instance, in gas turbines, maintaining the adiabatic flame temperature below certain thresholds reduces thermal formation by controlling the temperature-dependent Zeldovich mechanism, as demonstrated in emission control models where steam injection lowers the temperature to suppress oxide production. Similarly, in reciprocating engines, operations are designed based on adiabatic flame temperature calculations to achieve lower peak cylinder temperatures, enhancing fuel economy and reducing emissions in combined and power applications. In , adiabatic flame temperature calculations are essential for designing high-temperature furnaces and oxy-fuel torches used in and reheating processes, where elevated temperatures facilitate efficient material processing. Oxy-fuel systems, which replace air with pure oxygen, achieve significantly higher adiabatic temperatures to improve and reduce fuel consumption in reheating furnaces, allowing precise control of zones for uniform heating. These designs rely on temperature predictions to select materials capable of withstanding localized hot spots without degradation. Rocket systems select fuel-oxidizer combinations based on their adiabatic flame temperatures, often targeting values exceeding 3000 K to maximize and efficiency while balancing nozzle and chamber material constraints. For example, bipropellant combinations like with or are evaluated using adiabatic flame temperature as a key metric in preliminary , ensuring complete release under isentropic expansion conditions. Recent advancements in sustainable modeling, as of 2025, incorporate adiabatic flame temperature into frameworks for net-zero emission goals, particularly for -blended fuels in industrial and applications. Models for ultra-lean premixed use adiabatic flame temperature to predict flame stability and low-NOx regimes, supporting decarbonization in gas turbines and supporting the transition to carbon-free fuels. In systems, these models aid in designing cryogenic heat exchangers for by estimating maximum temperatures to size components and select durable materials like nickel-based superalloys.

Real-World Deviations

In real-world processes, the actual often falls significantly below the predicted adiabatic value due to various non-ideal effects that violate the assumptions of a perfectly insulated, system. losses primarily through and to surrounding surfaces and fluids represent a major deviation, as no environment is truly adiabatic. These losses can extract substantial energy from the zone, reducing the observed by several hundred kelvin depending on the enclosure geometry and flow conditions. For instance, in enclosed combustors like gas turbines, radiative to walls dominates at high temperatures, while becomes prominent in turbulent flows, collectively diminishing the peak achievable. Incomplete combustion further exacerbates these discrepancies by limiting the to reach full , primarily due to finite and mixing limitations in practical flames. In reality, rapid combustion timescales—often less than one second—prevent complete conversion of reactants to products, resulting in unburned hydrocarbons, , or formation, which reduces the effective heat release and thus lowers the flame temperature compared to the adiabatic prediction. This kinetic constraint is particularly evident in lean or stratified mixtures, where local fuel-air ratios deviate from , leading to suboptimal extraction. Advanced kinetic models, such as those incorporating detailed mechanisms, are essential to quantify this shortfall, which can decrease temperatures by 10-20% in diffusion flames. Dissociation of combustion products, such as the breakdown of H₂O and CO₂ into atomic or radical species at elevated temperatures, is another critical factor more pronounced in actual flames than in simplistic adiabatic models. This endothermic process absorbs thermal energy that would otherwise raise the product temperature, effectively capping the peak at lower values; for example, in stoichiometric hydrogen-oxygen combustion at ambient pressure, dissociation can reduce the temperature from approximately 5,000 K (without dissociation) to around 3,000 K when accounting for equilibrium species like H, OH, and O. In real scenarios, non-uniform temperature profiles and pressure variations amplify this effect, necessitating advanced thermodynamic models that include multi-species equilibrium calculations to predict deviations accurately. Higher pressures, as in rocket engines, mitigate dissociation somewhat, but turbulent mixing in practical systems often enhances it beyond ideal predictions. Measuring flame temperatures in operational environments poses additional challenges, particularly when comparing experimental data to theoretical adiabatic values, as techniques like optical pyrometry must contend with variations, interference, and non-graybody radiation assumptions. Two-color pyrometry, which infers temperature from ratios at selected wavelengths (e.g., 694 and 768 ), offers non-intrusive measurements but introduces uncertainties up to 3-4% due to errors and nonlinear detector responses at high temperatures above 1,000°C. These methods often yield values 5-10% lower than adiabatic predictions even under controlled conditions, highlighting the need for hybrid approaches combining pyrometry with diagnostics to validate theoretical models against real heterogeneities. To bridge these gaps, (CFD) simulations have emerged as vital tools in the 2020s for correcting adiabatic predictions by incorporating , , and in detailed and models. For example, the Fire Dynamics Simulator (FDS) version 6.8.0 enables analysis of deviations during transient phases like fire decay, accounting for smoke-induced radiation attenuation and variable convective coefficients, which can cause adiabatic surface temperatures to differ by up to 50°C from readings in smoky environments. Such simulations, validated against experimental data, provide corrections for industrial applications by integrating multi-physics effects, improving accuracy over traditional equilibrium assumptions and addressing limitations in earlier models.

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    (PDF) CFD-based analysis of thermocouple measurements in the ...
    Jun 27, 2024 · CFD-based analysis of thermocouple measurements in the fire decay and cooling phases in relation to the adiabatic surface temperature. June 2024.