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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CRAGE-mediated insertion of fluorescent chromosomal markers for accurate and scalable measurement of co-culture dynamics in Escherichia coli

Monitoring population dynamics in co-culture is necessary in engineering microbial consortia involved in distributed metabolic processes or biosensing applications. However, it remains difficult to measure strain-specific growth dynamics in high-throughput formats. This is especially vexing in plate-based functional screens leveraging whole-cell biosensors to detect specific metabolic signals. Here, we develop an experimental high-throughput co-culture system to measure and model the relationship between fluorescence and cell abundance, combining chassis-independent recombinase-assisted genome engineering (CRAGE) and whole-cell biosensing with a PemrR-green fluorescent protein (GFP) monoaromatic reporter used in plate-based functional screening. CRAGE was used to construct Escherichia coli EPI300 strains constitutively expressing red fluorescent protein (RFP) and the relationship between RFP expression and optical density (OD600) was determined throughout the EPI300 growth cycle. A linear equation describing the increase of normalized RFP fluorescence during deceleration phase was derived and used to predict biosensor strain dynamics in co-culture. Measured and predicted values were compared using flow cytometric detection methods. Induction of the biosensor lead to increased GFP fluorescence normalized to biosensor cell abundance, as expected, but a significant decrease in relative abundance of the biosensor strain in co-culture and a decrease in bulk GFP fluorescence. Taken together, these results highlight sensitivity of population dynamics to variations in metabolic activity in co-culture and the potential effect of these dynamics on the performance of functional screens in plate-based formats. The engineered strains and model used to evaluate these dynamics provide a framework for optimizing growth of synthetic co-cultures used in screening, testing and pathway engineering applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Microstructural Transitions during Powder Metallurgical Processing of Solute Stabilized Nanostructured Tungsten Alloys

Exploiting grain boundary engineering in the design of alloys for extreme environments provides a promising pathway for enhancing performance relative to coarse-grained counterparts. Due to its attractive properties as a plasma facing material for fusion devices, tungsten presents an opportunity to exploit this approach in addressing the significant materials challenges imposed by the fusion environment. Here, we employ a ternary alloy design approach for stabilizing W against recrystallization and grain growth while simultaneously enhancing its manufacturability through powder metallurgical processing. Mechanical alloying and grain refinement in W-10 at.% Ti-(10,20) at.% Cr alloys are accomplished through high-energy ball milling with transitions in the microstructure mapped as a function of milling time. We demonstrate the multi-modal nature of the resulting nanocrystalline grain structure and its stability up to 1300 °C with the coarser grain size population correlated to transitions in crystallographic texture that result from the preferred slip systems in BCC W. Field-assisted sintering is employed to consolidate the alloy powders into bulk samples, which, due to the deliberately designed compositional features, are shown to retain ultrafine grain structures despite the presence of minor carbides formed during sintering due to carbon impurities in the ball-milled powders.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Storage-Induced Collapse of Lignin Macromolecular Structure and Its Impacts on the Biorefinery

Lignin plays a vital role in the economics of biorefineries, serving as a source of process energy and a feedstock for sustainable fuels and chemical production. While understanding lignin’s chemical composition is crucial, emerging evidence suggests that a more comprehensive understanding of its macromolecular structure is critical to explaining its complex behavior in the biorefinery. This study investigated the partial collapse of the lignin network in corn stover feedstock after harvest and storage as a result of the microbial digestion of hemicellulose. Fluorescence microscopy was used to detect the collapse of lignin in terms of lignin’s inter-molecular interaction and the re-orientation of lignin’s chromophores, by the changes in lignin’s fluorescence lifetime, anisotropy, and the number of effective emitters. With minimal sample perturbation, our in-situ microscopic results revealed lignin's coil-globule transition phenomena, which was only previously predicted by molecular dynamics modeling extracted lignin in solvent. This collapse of lignin macromolecular structure was confirmed by results from NMR, IR, Raman, and powder X-ray diffraction. We also investigated the impact of this storage-induced collapse on the downstream biorefinery processes. Our study revealed that the two major approaches for lignin valorization in the lignin-first biorefinery model, namely monomer extraction and milled wood lignin extraction, were negatively impacted by the lignin collapse. As changes during storage are a source of feedstock variability, our study highlights the importance of understanding the effect of feedstock handling on biorefinery operations and economics.

09 BIOMASS FUELS↗
DOE OSTI2020

Accelerating nuclear fuel development and qualification: Modeling and simulation integrated with separate-effects testing

In this work, an approach to transform and accelerate nuclear fuel development and qualification is outlined. The approach exploits advanced modeling and simulation at the outset to inform constituent and system selection and to enable integral fuel performance analyses. Analyses using these tools identify and prioritize the most important fuel performance parameters and phenomena for subsequent targeted characterization with separate-effects tests. Separate-effects testing spans out-of-pile and in-pile tests and is meant to iterate with and inform engineering-scale integral fuel performance analyses throughout the development process. Exercising this cycle in an agile fashion will increase confidence in the integral fuel performance predictions while reducing uncertainties. This process sets the stage for executing a much more limited set of well-defined integral irradiation tests designed to validate engineering-scale fuel performance codes and to confirm the performance and safety of the fuel system under prototypic conditions. This approach will reduce the time for development and qualification of a new fuel system, and it will also reduce associated costs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Sparsity Facilitates Chemical-Reaction Selection for Engine Simulations

Analysis of large-scale, realistic models incorporating detailed chemistry can be challenging because each simulation is computationally expensive, and a complete analysis may require many simulations. This paper addresses one such problem of this type, chemical-reaction selection in engine simulations. In this computationally challenging case, it is demonstrated how the important concept of sparsity can facilitate chemical-reaction selection, which is the process of finding the most important chemical reactions for modeling a chemical process. It is difficult to perform accurate reaction selection for engine simulations using realistic models of the chemistry, as each simulation takes processor weeks to complete. We developed a procedure to efficiently accomplish this selection process with a relatively small number of simulations using a form of global sensitivity analysis based on sparse regression. The chemical-reaction selection leads to an analysis of the ignition chemistry as it evolves within the compression-ignition engine simulations and allows for the spatial development of the selected chemical reactions to be studied in detail.

Magnotti, Gina M.↗
DOE OSTI2021

3D-printable engineered cementitious composites (3DP-ECC): Fresh and hardened properties

3D printing (3DP) is an emerging digital construction method for concrete materials. A major impediment to efficient 3D concrete printing (3DCP) is the need for steel reinforcement, the placement of which is incompatible with the 3DP process. Unlike plain concrete, ductile self-reinforced engineered cementitious composite (ECC) holds promise to remove the dependence on steel reinforcement. The objective of this research is to develop a 3D-printable ECC (3DP-ECC). The fresh rheological and hardened mechanical properties of 3DP-ECC are investigated. The robotically printed tensile specimens demonstrated the familiar multiple microcracking and strain-hardening behavior of conventionally cast ECC. Significant orthotropy is revealed in the compressive properties. The interface between printed layers is found to be toughened by a printed groove-tongue joint. The developed 3DP-ECC was used to print a twisted column with 150 layers, reaching a height of 1.5 m. This research lays the groundwork for efficient robotically 3D-printed structures of complex shapes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Machine-learning based prediction of injection rate and solenoid voltage characteristics in GDI injectors

We report that current state-of-the-art gasoline direct-injection (GDI) engines use multiple injections as one of the key technologies to improve exhaust emissions and fuel efficiency. For this technology to be successful, secured adequate control of fuel quantity for each injection is mandatory. However, nonlinearity and variations in the injection quantity can deteriorate the accuracy of fuel control, especially with small fuel injections. Therefore, it is necessary to understand the complex injection behavior and to develop a predictive model to be utilized in the development process. This study presents a methodology for rate of injection (ROI) and solenoid voltage modeling using artificial neural networks (ANNs) constructed from a set of Zeuch-style hydraulic experimental measurements conducted over a wide range of conditions. A quantitative comparison between the ANN model and the experimental data shows that the model is capable of predicting not only general features of the ROI trend, but also transient and non-linear behaviors at particular conditions. In addition, the end of injection (EOI) could be detected precisely with a virtually generated solenoid voltage signal and the signal processing method, which applies to an actual engine control unit. A correlation between the detected EOI timings calculated from the modeled signal and the measurement results showed a high coefficient of determination.

42 ENGINEERING↗
DOE OSTI2023

Regulatory response to a hybrid ancestral nitrogenase in Azotobacter vinelandii

Biological nitrogen fixation, the microbial reduction of atmospheric nitrogen to bioavailable ammonia, represents both a major limitation on biological productivity and a highly desirable engineering target for synthetic biology. However, the engineering of nitrogen fixation requires an integrated understanding of how the gene regulatory dynamics of host diazotrophs respond across sequence-function space of its central catalytic metalloenzyme, nitrogenase. Here, we interrogate this relationship by analyzing the transcriptome of Azotobacter vinelandii engineered with a phylogenetically inferred ancestral nitrogenase protein variant. The engineered strain exhibits reduced cellular nitrogenase activity but recovers wild-type growth rates following an extended lag period. We find that expression of genes within the immediate nitrogen fixation network is resilient to the introduced nitrogenase sequence-level perturbations. Rather the sustained physiological compatibility with the ancestral nitrogenase variant is accompanied by reduced expression of genes that support trace metal and electron resource allocation to nitrogenase. Our results spotlight gene expression changes in cellular processes adjacent to nitrogen fixation as productive engineering considerations to improve compatibility between remodeled nitrogenase proteins and engineered host diazotrophs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Fourier heat conduction as a phenomenon described within the scope of the second law

The historical development of the Carnot cycle necessitated the construction of isothermal and adiabatic pathways within the cycle that were also mechanically 'reversible' which lead eventually to the Kelvin-Clausius development of the entropy function S where for any reversible closed path C, ∮{sub C} dS = 0 based on an infinite number of concatenated Carnot engines that approximated the said path and where for each engine ΔQ{sub 1}/T{sub 1}+ΔQ{sub 2}/T{sub 2} = 0 where the Q's and T's are the heat absorption increments and temperature respectively with the subscripts indicating the isothermal paths (1;2) where for the Carnot engine, the heat absorption is for the diathermal (isothermal) paths of the cycle only. Since 'heat' has been defined as that form of energy that is transferred as a result of a temperature difference and a corollary of the Clausius statement of the Second law is that it is impossible for heat to be transferred from a cold to a hot reservoir with no other effect on the environment, these statements suggested that the local mode of transfer of 'heat' in the isothermal segments of the pathway does imply a Fourier heat conduction mechanism (to conform to the definition of 'heat') albeit of a 'reversible' kind, but on the other hand, the Fourier mechanism is apparently irreversible, leading to an increase in entropy of the combined reservoirs at either end of the material involved in the conveyance of the heat energy. These and several other considerations lead Benofy and Quay (BQ) to postulate the Fourier heat conduction phenomenon to be an ancillary principle in thermodynamics, with this principle being strictly local in nature, where the global Second law statements could not be applied to this local process. Here we present equations that model heat conduction as a thermodynamically reversible but mechanically irreversible process where due to the belief in mechanical time reversible symmetry, thermodynamical reversibility has been unfortunately linked to mechanical reversibility, that has discouraged such an association. The modeling is based on an application of a 'recoverable transition', defined and developed earlier on ideas derived from thermal desorption of particles from a surface where the Fourier heat conduction process is approximated as a series of such desorption processes. We recall that the original Carnot engine required both adiabatic and isothermal steps to complete the zero entropy cycle, and this construct lead to the consequent deduction that any Second law statement that refers to heat-work conversion processes are only globally relevant. Here, on the other hand, we examine Fourier heat conduction from MD simulation and model this process as a zero-entropy forward scattering process relative to each of the atoms in the lattice chain being treated as a system where the Carnot cycle can be applied individually. The equations developed predicts the 'work' done to be equal to the energy transfer rate. The MD simulations conducted shows excellent agreement with the theory. Such views and results as these, if developed to a successful conclusion could imply that the Carnot cycle be viewed as describing a local process of energy-work conversion and that irreversible local processes might be brought within the scope of this cycle, implying a unified treatment of thermodynamically (i) irreversible, (ii) reversible, (iii) isothermal and (iv) adiabatic processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Biocompatible surface functionalization architecture for a diamond quantum sensor

Significance Diamond-based quantum sensing enables nanoscale measurements of biological systems with unprecedented sensitivity. Potential applications of this emerging technology range from the investigation of fundamental biological processes to the development of next-generation medical diagnostics devices. One of the main challenges faced by bioquantum sensing is the need to interface quantum sensors with biological target systems. Specifically, such an interface needs to maintain the highly fragile quantum states of our sensor and at the same time be able to fish intact biomolecules out of solution and immobilize them on our quantum sensor surface. Our work overcomes these challenges by combining tools from quantum engineering, single-molecule biophysics, and material processing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Respiratory energy demands and scope for demand expansion and destruction

Photosynthesis is the primary energy input to plants, but most plant metabolic processes are powered much or all of the time by ATP and NAD(P)H that come from respiratory oxidation of photosynthetically produced carbohydrates, that is, “dark respiration” (Amthor, 1994). The processes of growth, nutrient uptake and assimilation, active transport, and maintenance are thus all clients of respiration and compete for their share of a respiratory energy budget that is capped by photosynthate income. The economic principle of opportunity cost applies to these clients’ competing demands: spending respiratory energy on process A means missing the benefit of investing that energy in process B (Mahmoudabadi et al., 2019). This principle is key to assessing prospects for crop improvement by metabolic engineering. As de Lorenzo (2015) put it: “metabolism…frames and ultimately resolves whether a given genetic program (existing…or engineered) can be deployed or not.” Foreign or reconfigured native processes bolted on to a crop-plant’s metabolic chassis must compete for respiratory energy with native ones without crashing the energy economy. A proviso on plant carbon budgets is that photosynthetic carbon fixation (“source activity”) can in certain cases increase to meet increased carbon demand (“sink activity”), that is, budget envelopes are not always fixed (Smith et al., 2018). However, as there is some consensus that productivity is most often limited or co-limited by carbon supply (Ainsworth and Long, 2005; Körner, 2015; Sonnewald and Fernie, 2018), we make this our basal assumption in the analyses below.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

MODEL BASED BIOMASS SYSTEM DESIGN OF FEEDSTOCK SUPPLY SYSTEMS FOR BIOENERGY PRODUCTION

Engineering feedstock supply systems that deliver affordable, high-quality biomass remains a challenge for the emerging bioenergy industry. Cellulosic biomass is geographically distributed and has diverse physical and chemical properties. Because of this feedstock supply systems that deliver cellulosic biomass resources to biorefineries require integration of a broad set of engineered unit operations. These unit operations include harvest and collection, storage, preprocessing, and transportation processes. Design decisions for each feedstock supply system unit operation impact the engineering design and performance of the other system elements. These interdependencies are further complicated by spatial and temporal variances such as climate conditions and biomass characteristics. This paper develops an integrated model that couples a SQL-based data management engine and systems dynamics models to design and evaluate biomass feedstock supply systems. The integrated model, called the Biomass Logistics Model (BLM), includes a suite of databases that provide 1) engineering performance data for hundreds of equipment systems, 2) spatially explicit labor cost datasets, and 3) local tax and regulation data. The BLM analytic engine is built in the systems dynamics software package PowersimTM. The BLM is designed to work with thermochemical and biochemical based biofuel conversion platforms and accommodates a range of cellulosic biomass types (i.e., herbaceous residues, short- rotation woody and herbaceous energy crops, woody residues, algae, etc.). The BLM simulates the flow of biomass through the entire supply chain, tracking changes in feedstock characteristics (i.e., moisture content, dry matter, ash content, and dry bulk density) as influenced by the various operations in the supply chain. By accounting for all of the equipment that comes into contact with biomass from the point of harvest to the throat of the conversion facility and the change in characteristics, the BLM evaluates economic performance of the engineered system, as well as determining energy consumption and green house gas performance of the design. This paper presents a BLM case study delivering corn stover to produce cellulosic ethanol. The case study utilizes the BLM to model the performance of several feedstock supply system designs. The case study also explores the impact of temporal variations in climate conditions to test the sensitivity of the engineering designs. Results from the case study show that under certain conditions corn stover can be delivered to the cellulosic ethanol biorefinery for $35/dry ton.

09 BIOMASS FUELS↗
DOE OSTI2020

Performance of Public Film Cooling Geometries Produced Through Additive Manufacturing

Abstract Film cooling is an essential cooling technology to allow modern gas turbines to operate at high temperatures. For years, researchers in this community have worked to improve the effectiveness of film cooling configurations by maximizing the coolant coverage and minimizing the heat flux from the hot gas into the part. Working toward this goal has generated many promising film cooling concepts with unique shapes and configurations. However, until recently, many of these designs were challenging to manufacture in actual turbine hardware due to limitations with legacy manufacturing methods. Now, with the advances in additive manufacturing, it is possible to create turbine parts using high-temperature nickel alloys that feature detailed and unique geometry features. Armed with this new manufacturing power, this study aims to build and test the promising designs from the public literature that were previously difficult or impossible to implement. In this study, different cooling hole designs were manufactured in test coupons using a laser powder bed fusion process. Each nickel alloy coupon featured a single row of engine scale cooling holes, fed by a microchannel. To evaluate performance, the overall cooling effectiveness of each coupon was measured using a matched Biot test at engine relevant conditions. The results showed that certain hole shapes are better suited for additive manufacturing than others and that the manufacturing process can cause significant deviations from the performance reported in the literature.

Engineering↗
DOE OSTI2018

Prospects for enhancing leaf photosynthetic capacity by manipulating mesophyll cell morphology

Leaves are beautifully specialized organs designed to maximize the use of light and CO 2 for photosynthesis. Engineering leaf anatomy therefore holds great potential to enhance photosynthetic capacity. In this work, we review the effect of the dominant leaf anatomical traits on leaf photosynthesis and confirm that a high chloroplast surface area exposed to intercellular airspace per unit leaf area (S c ) is critical for efficient photosynthesis. The possibility of improving S c through appropriately increasing mesophyll cell density is further analyzed. The potential influences of modifying mesophyll cell morphology on CO 2 diffusion, light distribution within the leaf, and other physiological processes are also discussed. Some potential target genes regulating leaf mesophyll cell proliferation and expansion are explored. Indeed, more comprehensive research is needed to understand how manipulating mesophyll cell morphology through editing the potential target genes impacts leaf photosynthetic capacity and related physiological processes. This will pinpoint the targets for engineering leaf anatomy to maximize photosynthetic capacity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Spatiotemporal flame propagations, combustion and solid particle emissions from lean and stoichiometric gasoline direct injection engine operation

Increased particle number and mass emissions in gasoline direct injection (GDI) engines should require to investigate in-cylinder flame and combustion characteristics associated with primary source of particle emissions. In this article, in-cylinder spatiotemporal flame luminosity is quantitatively characterized to features combustion process and solid particle emissions from a GDI engine operating in two lean and one stoichiometric modes. Low- and high-steady state operating points were used to compare combustion strategies on flame development and emission characteristics. A fiber-optic sensor composed of eight measurement channels detected the flame front and the direction of the flame propagation in the combustion chamber. Solid particle emissions in the exhaust were measured using an engine exhaust particle sizer and a micro soot sensor. Results of the experiments showed that two lean combustion modes by injection strategies resulted in distinct combustion and flame development. Lean combustion modes generated high diffusion flame by burning stratified rich-mixture. Although the lean cases resulted in strong diffusion flames, the lean-homogeneous produced similar particle size distributions with the stoichiometric mode with high ash particles. Piston pool fires on the piston surface in the lean-stratified mode induced a large accumulation mode with high particle mass concentrations.

42 ENGINEERING↗
DOE OSTI2023

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $ \$ $6B annually (at $ \$ $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year), and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE) missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

42 ENGINEERING↗
DOE OSTI2023

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $6B annually (at $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year),and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE)missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

99 GENERAL AND MISCELLANEOUS↗