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Conserved Macromolecular Architecture of Poplar Secondary Cell Walls Revealed by ssNMR and Atomistic Modeling

The macromolecular architecture of plant secondary cell walls governs wood's mechanical and biochemical properties, yet its natural intra-species variability remains poorly characterized. Here, we combined 13C solid-state NMR (ssNMR), multivariate statistical analysis, and molecular modeling to profile nanoscale structure across 13 genetically diverse Populus trichocarpa genotypes grown in 13C-enriched atmospheres. SsNMR-derived phenotypes spanning composition, structure, mobility, and inter-polymer proximities reveal a conserved architecture, with a subtle yet coordinated variation organizing into dominant structural and secondary mobility axes. A representative atomistic model captures these features and reproduces experimental metrics. Molecular dynamics simulations support a weak but consistent positive correlation between cellulose abundance and crystalline-like order, with interior cellulose chains enriched in tg (trans-gauche) conformations without expanding crystalline cores. Together, experiment and simulation reveal a genetically buffered, broadly conserved nanoscale architecture across genotypes, where subtle fine-tuning of cellulose bundling and matrix packing balances mechanical performance with biological function.

09 BIOMASS FUELS

Studies of Flame Structure in Microgravity

The present research endeavor is concerned with gaining fundamental understanding of the configuration, structure, and dynamics of laminar premixed and diffusion flames under conditions of negligible effects of gravity. Of particular interest is the potential to establish and hence study the properties of spherically- and cylindrically-symmetric flames and their response to external forces not related to gravity. For example, in an earlier experimental study of the burner-stabilized cylindrical premixed flames, the possibility of flame stabilization through flow divergence was established, while the resulting one-dimensional, adiabatic, stretchless flame also allowed an accurate means of determining the laminar flame speeds of combustible mixtures. We have recently extended our studies of the flame structure in microgravity along the following directions: (1) Analysis of the dynamics of spherical premixed flames; (2) Analysis of the spreading of cylindrical diffusion flames; (3) Experimental observation of an interesting dual luminous zone structure of a steady-state, microbuoyancy, spherical diffusion flame of air burning in a hydrogen/methane mixture environment, and its subsequent quantification through computational simulation with detailed chemistry and transport; (4) Experimental quantification of the unsteady growth of a spherical diffusion flame; and (5) Computational simulation of stretched, diffusionally-imbalanced premixed flames near and beyond the conventional limits of flammability, and the substantiation of the concept of extended limits of flammability. Motivation and results of these investigations are individually discussed.

C K Law

Behavior of 2-Cell CPV Ni-H2 Battery During Pulse Discharge

A study was carried out to determine the transient voltage behavior of the 2-cell CPV nickel-hydrogen battery with the objective of using the results as a basis for mathematical modeling. The 2-cell CPV battery which is manufactured by Eagle Picher, Inc. for the GOES program yields 18.5 Ah at C/2 rate of discharge at 10 C with a mid-discharge voltage of 2.514 V. The capacity increased with decrease of temperature and a maximum capacity of 22 Ah was obtained at -5 C. The pulse tests consisted of obtaining the voltage profile in the first 20 milliseconds of the one minute pulse discharge at 37 A and pulse discharge was repeated as a function of state-of-charge. The pulse test at 10 C and 20 C provided voltage profiles with the expected decrease in voltage as the pulse was applied. The end of pulse voltage decreased with the state-of-charge. The battery voltage was above 2V at the end of the one-minute pulse at 8 % state-of-charge at 10 C. The voltage profile during the 37 A pulse discharge consists of an initial drop in voltage which was independent of the state of charge. The invariability in the value for the initial drop in voltage with state of charge is a very important observation. The results show that towards the end of discharge the dominant resistance is not ohmic in nature. It could be hypothesized from the nature of the voltage transients that the dominant mechanism towards the end of discharge is proton diffusion. The study also shows that the dominant resistance in the voltage plateau during discharge is activation polarization.

Vaidyanathan, Hari

Mechanisms of Alkali Ionic Transport in Amorphous Oxyhalides Solid State Conductors

Amorphous oxyhalides have attracted significant attention due to their relatively high ionic conductivity (1 mS cm –1 ), excellent chemical stability, mechanical softness, and facile synthesis routes via standard solid‐state reactions. These materials exhibit an ionic conductivity that is almost independent of the underlying chemistry, in stark contrast to what occurs in crystalline conductors. In this work, we employ machine learning interatomic potentials to construct large‐scale molecular dynamics trajectories encompassing hundreds of nanoseconds to obtain statistically converged transport properties. We find that the amorphous state consists of chain fragments of metal‐anion tetrahedra of various lengths. By analyzing the residence time of alkali cations migrating around tetrahedrally‐coordinated metals, we find that oxygen anions limit alkali diffusion. By computing the full Einstein expression of the ionic conductivity, we demonstrate that the alkali transference number of these materials is strongly influenced by distinct‐particles correlations, while alkali transport is dictated by uncorrelated self‐diffusion. By extending this analysis to chemical compositions AMX 2.5 O 0.75 , spanning different alkaline (A = Li, Na, K), metallic (M = Al, Ga, In), and halogen (X = Cl, Br, I) species, we clarify why the diffusion properties of these materials remain largely insensitive to variations in atomic isovalent chemistry.

amorphous materials

Polarized target nuclear magnetic resonance measurements with deep neural networks

Continuous-wave Nuclear Magnetic Resonance (CW-NMR) operated in constant-current mode has served as a foundational technique for polarization measurement in solid-state dynamically polarized targets within nuclear and high-energy physics experiments for several decades, and it remains an essential tool. Conventional Q-meter-based phase-sensitive detection is critical for precise real-time determination of target polarization during scattering runs. However, the accuracy and reliability of these measurements are frequently compromised by elevated noise levels, baseline drift, and systematic uncertainties arising from signal isolation and fitting, ultimately degrading the overall experimental figure of merit. In this work, we report the first successful application of neural network architectures to continuous-wave NMR polarization metrology. By leveraging advanced machine learning techniques for signal extraction and denoising, we achieve a substantial reduction of fitting uncertainties under a variety of realistic simulated and experimental conditions. These improvements translate directly into more robust real-time (online) polarization monitoring and higher precision in subsequent offline analysis. By reducing analysis-induced uncertainty, the resulting methodology can improve the effective figure of merit for scattering experiments employing dynamically polarized targets and provides a new toolset for NMR-based polarimetry in high-energy and nuclear physics.

Metrology

Fluid-Thermal-Structural Interactions Induced by an Asymmetric Shock-Wave/Boundary-Layer Interaction in a Mach-6 Compression Corner

An experimental study is conducted of the fluid-thermal-structural interaction of a clamped compliant panel exposed to a three dimensional shock-wave/boundary-layer interaction (SWBLI) induced by a Mach-6 compression ramp with a spanwise nonuniform incoming boundary layer. The nonuniform boundary layer was produced by placing trips on one side of the upstream flat plate, resulting in largely turbulent flow on the tripped side and transitional flow on the untripped side. Measurements of the flowfield confirmed that the tripped boundary layer contained elevated levels of unsteadiness, and the SWBLI was observed to vary from attached to fully separated as the ramp angle was increased from 10◦ to 38◦; the separation region on the tripped side of the panel was noticeably smaller, showing the elevated turbulence levels of the tripped-side flow to remain relatively localized rather than diffusing across the whole model. Full-field, time-resolved panel deformations were measured using high-speed photogrammetry and the vibrational response at each compression angle was characterized. Although the measured modes conformed largely to those from classical clamped-plate theory, some skewing of the mode shapes was observed. IR thermography highlighted regions of the compliant region where elevated temperatures were likely to promote thermal softening effects to the transient panel response. The quasi-static deformation and stress field was used to characterize the internal stress factor of each mode and showed a meaningful relationship between transient panel response and stress contained within each mode: modes with antinodes lying in high-stress areas of the plate tended to exhibit increases in vibrational frequency and decreases in vibrational power, whereas the opposite was true for modes with antinodes in low-stress areas.

Spectral Proper Orthogonal Decomposition

High-Order Methods in NASA’s Next Generation of Computational Fluid Dynamics Tools

The missions of the National Aeronautics and Space Administration (NASA) routinely produce unique requirements and challenges for development and application of Computational Fluid Dynamics (CFD) methods. NASA presently embodies four distinct Mission Directorates: Aeronautics Research, Exploration Systems, Science, and Space Operations. These missions generate requirements for systems that operate in a wide variety of environments. They range from the high-speed flight of aerodynamically optimized vehicles operating in the earth’s atmosphere to spacecraft designed for missions that don’t favor aerodynamic optimization, some operating in the atmosphere of planets and planetary moons such as Mars and Venus or Saturn’s moon Titan. Systems supporting these vehicles, such as rocket and jet propulsion, reaction control systems, fluid and thermal transfer systems, etc. can also generate their own unique set of flow phenomena that challenge today’s CFD methodology. Through the NASA Engineering and Safety Center (NESC), NASA annually conducts state-of-the-discipline assessments in fifteen distinct engineering disciplines. These assessments are performed by the NASA Technical Fellows that lead Technical Discipline Teams (TDT) of recognized experts in these fifteen areas. In the Aerosciences discipline, three topics have been identified as the top challenges for the discipline: aero-plume interaction prediction, unsteady separated flows, and aerothermodynamic prediction. These challenge areas are defined by the Agency’s high-risk projects and problems on which the NESC is requested to perform independent testing, analysis, and assessments. When viewed as a whole, these tests, analyses, and assessments provide a clear view of the recurring technical challenges facing Agency engineers and researchers and can be used to guide future research and technology development. The present state-of-the-art in the application of CFD at NASA is the use of Reynolds-Averaged Navier- Stokes (RANS) solvers, primarily executed in a steady-state mode of operation. In isolated cases, Unsteady RANS (URANS) solvers have been employed when steady RANS solutions produce poorly converging or oscillating results or in cases, such as aeroelastic analysis, which require unsteady aerodynamic simulation. For most traditional external and internal aerodynamic flows, structured overset grids or unstructured grids are employed to minimize geometric modeling and grid generation times. Grid adaptation, primarily as a series of coarse-grain intermediate processing steps is also seeing use on particularly complex flow problems and configurations. In the case of aerothermodynamic flows, engineers have been forced to continue to employ structured grid techniques as the present unstructured grid methodology has proven inadequate in the prediction of surface heating. In the area of aero-plume interaction modeling, two-gas, frozen chemistry simulation is generally the state-of-the- art, with some production solvers capable of predicting flows with only a single gas component. Prediction of flows falling into the afore-mentioned top Aerosciences technical challenges have severely stressed the present state-of-the-art in CFD prediction and for some problems, such as unsteady separated flows and aero-plume interaction cases, engineers have begun employing Large Eddy Simulation (LES) and Hybrid RANS/LES techniques. In some isolated aero-propulsion interaction cases, chemically reacting flow simulations have been applied. These methods are highly evolutionary and engineers have little experience in their application, so they cannot be heavily relied upon in today’s application environment. Therefore, this leads one to muse over which numerical technologies will be included in the CFD tools that will be employed 30 years in the future. This presentation will describe specific technical problems that have stressed NASA’s traditional CFD methods to their breaking point and will link these issues to the Agency’s top Aerosciences technical challenges. The discussion will then shift to the characteristics of future CFD solvers that will be required to attack these challenges and how these characteristics differ from the present state-of-the- art. High-order methods certainly appear to have a place in the development of future CFD tools and some of the physical characteristics of our most challenging problems suggest that high-order methods are the only way to effectively solve them. But there are some relatively severe implementation issues that face these methods, particularly in the area of general applicability and robust operation as an engineering tool. Desired characteristics of next-generation CFD solvers will be discussed and the author’s view of which emerging numerical technologies might be employed to address these attributes will also be presented

David M Schuster

Research on battery-operated electric road vehicles

Mathematical analysis of battery-operated electric vehicles is presented. Attention is focused on assessing the influence of the battery on the mechanical and dynamical characteristics of dc electric motors with series and parallel excitation, as well as on evaluating the influence of the excitation mode and speed control system on the performance of the battery. The superiority of series excitation over parallel excitation with respect to vehicle performance is demonstrated. It is also shown that pulsed control of the electric motor, as compared to potentiometric control, provides a more effective use of the battery and decreases the cost of recharging.

Varpetian, V. S.

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an

An Efficient Approach to Collect Inlet Characterization Data

This report considers a novel process to acquire performance data for supersonic mixed compression inlets that is faster, and therefore less costly, than the previous one. In the previous process, measurements were recorded in discrete increments. The backpressuring actuator was advanced, there was a pause to allow for airflow fluctuations to diminish, and then the measurements were recorded. While this process was methodical, reliable and accurate, it consumed significant wind-on time. In general, high-speed wind tunnels are expensive to operate considering maintenance, energy and human resource requirements. Furthermore, many facilities, such as blowdown wind tunnels, are limited in the duration that they can maintain the desired test condition. Consequently, a quick method to collect the measurements is desired. A favored approach has the actuator moving in a continuous fashion with measurements recorded as the actuator continuously progresses through the increment points. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. While faster, continuous movement adds dynamic effects to the data. To better understand these dynamic effects and other potential influences, a study was undertaken to compare wind tunnel measurements taken at discrete actuator position points with data gathered during continuous actuator movement. Specially, plots of inlet pressure recovery versus mass capture ratio, or total pressure characteristic curves, were examined. The data were measured during experiments in the NASA Glenn Research Center Abe Silverstein 10- by 10-Foot Supersonic Wind Tunnel (SWT) with an inlet propulsion test article. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data and for analysis are explained. A discussion of the results along with features noted in the data is given. Finally, conclusions from this study that may be used to guide future wind tunnel experiment planning are presented.

Inlet

An Efficient Approach to Collect Inlet Characterization Data

This report considers a novel process to acquire performance data for supersonic mixed compression inlets that is faster, and therefore less costly, than the previous one. In the previous process, measurements were recorded in discrete increments. The backpressuring actuator was advanced, there was a pause to allow for airflow fluctuations to diminish, and then the measurements were recorded. While this process was methodical, reliable and accurate, it consumed significant wind-on time. In general, high-speed wind tunnels are expensive to operate considering maintenance, energy and human resource requirements. Furthermore, many facilities, such as blowdown wind tunnels, are limited in the duration that they can maintain the desired test condition. Consequently, a quick method to collect the measurements is desired. A favored approach has the actuator moving in a continuous fashion with measurements recorded as the actuator continuously progresses through the increment points. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. While faster, continuous movement adds dynamic effects to the data. To better understand these dynamic effects and other potential influences, a study was undertaken to compare wind tunnel measurements taken at discrete actuator position points with data gathered during continuous actuator movement. Specially, plots of inlet pressure recovery versus mass capture ratio, or total pressure characteristic curves, were examined. The data were measured during experiments in the NASA Glenn Research Center Abe Silverstein 10- by 10-Foot Supersonic Wind Tunnel (SWT) with an inlet propulsion test article. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data and for analysis are explained. A discussion of the results along with features noted in the data is given. Finally, conclusions from this study that may be used to guide future wind tunnel experiment planning are presented.

Data Acquisition

Vapor Transport Crystal Growth of Mercury-Cadmium-Telluride in Microgravity

Two epitaxial growth experiments of Hg 1-x Cd x Te layers on (100) CdTe substrates in closed ampoules using HgI 2 as a transport agent have been performed during the USML-1 mission. The characterization results to date demonstrate a considerable improvement of the space-grown epitaxial layers relative to ground-control specimens in terms of morphology, compositional uniformity, and structural micro homogeneity. These results show the effects of microgravity and fluid dynamic disturbances on-ground on the deposition and growth processes. The continued analysis of this technologically important system is designed to further elucidate the observed crystallographic improvements and their relation to mass flow.

Heribert Wiedemeier

BLEECAM™ (Benchmarking Life Cycle Environmental, Economic, and Social Metrics for Critical and Advanced Minerals and Materials) [SWR-25-125]

The National Laboratory of the Rockies' (NLR) Benchmarking Life Cycle Environmental, Economic, and Social Metrics for Critical and Advanced Minerals and Materials (BLEECAM™) is an open-source, integrated decision-support tool for evaluating the impacts, risks, and trade-offs across U.S. and global materials supply chains. Funded by the U.S. Department of Energy, BLEECAM supports supply chain and market analysis. The tool integrates multi-objective supply chain optimization, system dynamics, network design, lifecycle assessment, techno-economic modeling, and social impact assessment methods to evaluate how supply chains evolve over time, geography, and deployment scenarios. BLEECAM also supports analysis related to energy infrastructure, data centers and digital infrastructure, advanced manufacturing, and other sectors that depend on critical materials.

Khalifa, SherifA. [National Laboratory of the Rock

Performance Evaluation of Intravehicular Activity Spacesuit Without the Use of a Liquid Cooling Garment

The Orion Crew Survival Systems (OCSS) suit is equipped with safety technology that protects the crew during launch and re-entry and Intravehicular Activities (IVA). It was designed to be used with a Liquid Cooling Garment (LCG), an undergarment with tubes that circulate water to remove excess heat from a crew member. The objective of this study is to determine if the Modified Advanced Crew Escape Suit (MACES), which has very similar material, assembly, and pressure characteristics as the OCSS suit, can be used without the LCG to maintain the crew within their heat storage requirements where exceedances can lead to cognitive and physiological impairment. Testing was completed for both hot and cold environments where test subjects wore varying configurations of the MACES suit ensemble without the LCG. The tests were conducted in a temperature and humidity-controlled chamber with four test subjects ranging from extra small to large. Target metabolic rates were reached using an arm ergometer. To represent the different suit configurations seen in the concept of operations, the suit was tested with visor-down, visor-up, and without helmet and gloves. The test data was analyzed to determine how the environment, test subject size, metabolic rate, and suit configuration affected heat storage. Furthermore, the test data was used to correlate the METMAN model, a transient metabolic man program that simulates the heat transfer within a crew member’s body and from a crew member to the surrounding environment. The METMAN correlation showed good agreement between predicted heat storage and test data at the end of the test duration, with a coefficient of determination (R 2 ) value of 0.8999 for visor-down cases and R 2 of 0.8902 for visor-up and helmet off cases. A correlated METMAN model allows for the analysis and prediction of IVA suit performance without an LCG in additional scenarios.

Spacesuit

Performance Evaluation of Intravehicular Activity Spacesuit Without the Use of a Liquid Cooling Garment

The Orion Crew Survival Systems (OCSS) suit is equipped with safety technology that protects the crew during launch and re-entry and Intravehicular Activities (IVA). It was designed to be used with a Liquid Cooling Garment (LCG), an undergarment with tubes that circulate water to remove excess heat from a crew member. The objective of this study is to determine if the Modified Advanced Crew Escape Suit (MACES), which has very similar material, assembly, and pressure characteristics as the OCSS suit, can be used without the LCG to maintain the crew within their heat storage requirements where exceedances can lead to cognitive and physiological impairment. Testing was completed for both hot and cold environments where test subjects wore varying configurations of the MACES suit ensemble without the LCG. The tests were conducted in a temperature and humidity-controlled chamber with four test subjects ranging from extra small to large. Target metabolic rates were reached using an arm ergometer. To represent the different suit configurations seen in the concept of operations, the suit was tested with visor-down, visor-up, and without helmet and gloves. The test data was analyzed to determine how the environment, test subject size, metabolic rate, and suit configuration affected heat storage. Furthermore, the test data was used to correlate the METMAN model, a transient metabolic man program that simulates the heat transfer within a crew member’s body and from a crew member to the surrounding environment. The METMAN correlation showed good agreement between predicted heat storage and test data at the end of the test duration, with a coefficient of determination (R 2 ) value of 0.8999 for visor-down cases and R 2 of 0.8902 for visor-up and helmet off cases. A correlated METMAN model allows for the analysis and prediction of IVA suit performance without an LCG in additional scenarios.

Human Thermal Modeling

Black-hole powered quantum coherent amplifier

Abstract Atoms falling into a black hole (BH) through a cavity are shown to enable coherent amplification of light quanta powered by the BH-gravitational vacuum energy. This process can harness the BH energy towards useful purposes, such as propelling a spaceship trapped by the BH. The process can occur via transient amplification of a signal field by falling atoms that are partly excited by Hawking radiation reflected by an orbiting mirror. In the steady-state regime of thermally equilibrated atoms that weakly couple to the field, this amplifier constitutes a BH-powered quantum heat engine. The envisaged effects substantiate the thermodynamic approach to BH acceleration radiation.

Physics

A multiscale packed-bed reactor model for sustainable ethylene production via chemical looping oxidative coupling of methane

The rising global warming concerns and shale gas discovery have prompted research in the direction of greenhouse gas (GHG), such as methane, reduction and conversion. Oxidative coupling of methane (OCM) offers a pathway to low carbon-intense valorization of methane while producing ethylene, a chemical regarded as central to the petrochemical industry. Even after decades of OCM discovery, researchers keep understanding the process and underlying chemical reactions in a pursuit to achieve industrial viability for OCM. Here, in general, OCM suffers from low C 2 selectivity, yield and reactor temperature runaways due to highly exothermic nature of its reactions. Computational Fluid Dynamics (CFD) tools help analyze spatial gradients within the reactor to deeply understand the diffusion of species, mass and heat transfer phenomena. Furthermore, challenges associated with scaling up such as hot spot formation and parametric sensitivity can be addressed without having to expend on costly experiments. The current paper presents a multiscale packed-bed reactor CFD model coupled with a chemical kinetic model for the chemical looping OCM. The CFD model includes two scales i.e., macroscale for catalyst bed and microscale for individual pellets. Moreover, a chemical kinetic model based on 10 gas-phase reactions is integrated with the CFD model. An additional surface reaction for the formation of gas-phase oxygen from catalyst surface is added to account for the absence of feed oxygen. The model is calibrated against experimental results. The calibrated model captures trends in CH 4 conversion, C 2 selectivity and C 2 yield within a ± 4.35 % range across a temperature range of 700-900 °C. Moreover, model fidelity is evaluated by varying key computational parameters such as mesh resolution and time step size. The model is also verified by varying the inlet methane concentration and the gas hourly space velocity (GHSV) and comparing the results with literature. A sensitivity analysis and scale-up of the current model is undergoing.

Chemical looping

LES-Based Analysis of Film Cooling in a High-Pressure Turbine Rotor Including Effects of Purge and Tip Flow

Accurate modeling of coolant airflows, which form protective films over turbine blades, is essential for designing fuel-efficient and environmentally sustainable gas turbine engines. Excessive coolant reduces thermal efficiency, while insufficient coolant leads to blade overheating and causes damage. Therefore, precise prediction of flow field interactions with cooling air is critical for optimizing turbine performance. This study numerically investigates the cooling effectiveness of purge and film cooling flows within a high-pressure turbine (HPT) rotor using Large Eddy Simulation (LES). The study utilizes NASA Glenn Research Center’s Glenn-HT solver. The simulation models ethe conditions of the Penn State University START rotating rig. A high-fidelity structured mesh comprising up to 800 million cells is employed to resolve high-Reynolds number flow (Re ≈ 350,000) and to capture intricate secondary flow structures, including tip leakage and purge-induced vortices. Film cooling effectiveness computations are highly sensitive to boundary conditions at the cooling holes and to grid resolution. Even with well-resolved grids and included plena, strong mixing challenges traditional eddy viscosity models. To address this, a simplified configuration is simulated: a truncated row of shaped holes on the suction side near the leading edge and a row on the pressure side, both fed from internal plena while the purge slot and tip clearance are also modeled. Two isothermal LES cases are conducted at two distinct wall temperatures, which yield the adiabatic wall temperature and the heat transfer coefficient. The definition and means of computation of the effectiveness is discussed in this paper. The simulations reveal detailed three-dimensional unsteady flow features, including coherent vortical structures and secondary flows originating from the purge cavity. Film cooling effectiveness and Nusselt number distributions are presented for both the blade surface and tip, highlighting regions of elevated heat transfer and complex thermal behavior. These findings underscore the importance of high-resolution LES and realistic boundary conditions in capturing the dynamics of purge and film cooling, offering valuable insights for improving turbine blade design and thermal management strategies.

Secondary Flows