11 research outputs found
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On flames established with air jet in cross flow of fuel-rich combustion products
Advances in combustor technologies are driving aircraft gas turbine engines to operate at higher pressures, temperatures and equivalence ratios. A viable approach for protecting the combustor from the high-temperature environment is to inject air through the holes drilled on the surfaces. However, it is possible that the air intended for cooling purposes may react with fuel-rich combustion products and may increase heat flux. Air Force Research Laboratory (AFRL) has developed an experimental rig for studying the flames formed between the injected cold air and the cross flow of combustion products. Laser-based OH measurements revealed an upstream shift for the flames when the air injection velocity was increased and downstream shift when the fuel content in the cross flow was increased. As conventional understanding of the flame stability does not explain such shifts in flame anchoring location, a time-dependent, detailed-chemistry computational-fluid-dynamics model is used for identifying the mechanisms that are responsible. Combustion of propane fuel with air is modeled using a chemical-kinetics mechanism involving 52 species and 544 reactions. Calculations reveled that the flames in the film-cooling experiment are formed through autoignition process. Simulations have reproduced the various flame characteristics observed in the experiments. Numerical results are used for explaining the non-intuitive shifts in flame anchoring location to the changes in blowing ratio and equivalence ratio. The higher diffusive mass transfer rate of hydrogen in comparison to the local heat transport enhances H₂–O₂ mixing compared to thermal dissipation rate, which, in turn, affects the autoignition process. While increasing the blowing ratio abates the differences resulting from non-equal mass and heat transport rates, higher concentrations of hydrogen in the fuel-rich cross flows accelerate those differences.KEYWORDS: Autoignition, Diffusion flame, Film-cooling, Preferential diffusion, Jet-in-cross-flowThis is the publisher’s final pdf. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/fue
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Characterization of inverse diffusion flames in vitiated cross flows via two-photon planar laser-induced fluorescence of CO and 2-D thermometry
Two-photon, planar laser-induced fluorescence (PLIF) of carbon-monoxide (CO) and two-dimensional thermometry employing two-color, hydroxyl radical (OH) PLIF are used to characterize atmospheric-pressure inverse diffusion flames. These flames are important tools to aid the understanding of secondary reaction zones that may form in gas turbine engines when film-cooling air reacts with fuel-rich packets from the combustor. For the experiments performed in the present study, exhaust from a propane–air well-stirred reactor is channeled to a test section where three different film-cooling geometries are used to create inverse diffusion flames: (1) a single row of normal cooling holes, (2) a slot cut at an angle of 30° with respect to the wall, and (3) an 5 × 11 array of cooling holes. It is found that CO and H₂ concentrations of a few percent can lead to secondary reaction zones and that different cooling-hole geometries can produce dramatically different secondary reaction-zone shapes. These secondary reaction zone flames have Damköhler numbers greater than unity and are diffusion limited. The PLIF measurements show regions where CO is consumed, OH produced, and the temperature perturbed. For film-cooling flows that remain attached to the wall, the secondary reaction zone is also close to the wall and can cover a relatively long axial length. For film-cooling flows that separate from the wall, the secondary reaction zones protrude farther into the cross flow then quickly mix with the cross flow. By comparing the CO, OH, and temperature fields, three characteristic regions of flows with secondary reaction zones are identified: the injection region where cooling air displaces the vitiated cross flow, the secondary reaction zone region, and the mix-out region where all of the oxygen has been consumed and mixing with the vitiated cross flow controls the local composition and temperature.Keywords: Film cooling, Inverse diffusion flames, Two-photon CO-PLIF, Laser diagnostic
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BlunckDavidMIMEOnFlamesEstablished.pdf
Advances in combustor technologies are driving aircraft gas turbine engines to operate at higher pressures,
temperatures and equivalence ratios. A viable approach for protecting the combustor from the
high-temperature environment is to inject air through the holes drilled on the surfaces. However, it is
possible that the air intended for cooling purposes may react with fuel-rich combustion products and
may increase heat flux. Air Force Research Laboratory (AFRL) has developed an experimental rig for
studying the flames formed between the injected cold air and the cross flow of combustion products.
Laser-based OH measurements revealed an upstream shift for the flames when the air injection velocity
was increased and downstream shift when the fuel content in the cross flow was increased. As conventional
understanding of the flame stability does not explain such shifts in flame anchoring location, a
time-dependent, detailed-chemistry computational-fluid-dynamics model is used for identifying the
mechanisms that are responsible. Combustion of propane fuel with air is modeled using a chemical-kinetics
mechanism involving 52 species and 544 reactions. Calculations reveled that the flames in the
film-cooling experiment are formed through autoignition process. Simulations have reproduced the various
flame characteristics observed in the experiments. Numerical results are used for explaining the
non-intuitive shifts in flame anchoring location to the changes in blowing ratio and equivalence ratio.
The higher diffusive mass transfer rate of hydrogen in comparison to the local heat transport enhances
H₂–O₂ mixing compared to thermal dissipation rate, which, in turn, affects the autoignition process.
While increasing the blowing ratio abates the differences resulting from non-equal mass and heat transport
rates, higher concentrations of hydrogen in the fuel-rich cross flows accelerate those differences.Keywords: Jet-in-cross-flow, Autoignition, Diffusion flame, Film-cooling, Preferential diffusio
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BlunckDavidMIMEOnFlamesEstablished_SupplementaryData.txt
Advances in combustor technologies are driving aircraft gas turbine engines to operate at higher pressures,
temperatures and equivalence ratios. A viable approach for protecting the combustor from the
high-temperature environment is to inject air through the holes drilled on the surfaces. However, it is
possible that the air intended for cooling purposes may react with fuel-rich combustion products and
may increase heat flux. Air Force Research Laboratory (AFRL) has developed an experimental rig for
studying the flames formed between the injected cold air and the cross flow of combustion products.
Laser-based OH measurements revealed an upstream shift for the flames when the air injection velocity
was increased and downstream shift when the fuel content in the cross flow was increased. As conventional
understanding of the flame stability does not explain such shifts in flame anchoring location, a
time-dependent, detailed-chemistry computational-fluid-dynamics model is used for identifying the
mechanisms that are responsible. Combustion of propane fuel with air is modeled using a chemical-kinetics
mechanism involving 52 species and 544 reactions. Calculations reveled that the flames in the
film-cooling experiment are formed through autoignition process. Simulations have reproduced the various
flame characteristics observed in the experiments. Numerical results are used for explaining the
non-intuitive shifts in flame anchoring location to the changes in blowing ratio and equivalence ratio.
The higher diffusive mass transfer rate of hydrogen in comparison to the local heat transport enhances
H₂–O₂ mixing compared to thermal dissipation rate, which, in turn, affects the autoignition process.
While increasing the blowing ratio abates the differences resulting from non-equal mass and heat transport
rates, higher concentrations of hydrogen in the fuel-rich cross flows accelerate those differences.Keywords: Preferential diffusion, Diffusion flame, Film-cooling, Jet-in-cross-flow, Autoignitio
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Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction
Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community
Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction
Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community