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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Raman Microscopy Analysis of Wyoming CarbonSAFE Pilot Well Thin Sections for Mineralogy and Organic Matter Characterization

Scanning confocal Raman microspectroscopy (RMS) was used to analyze thin sections for inorganic mineral content and for evaluation of organic material (OM). Thin sections were selected from a stratigraphic test well core in the Powder River Basin, Wyoming under the Wyoming CarbonSAFE project. The well was analyzed with a variety of rock and fluid characterization techniques to determine the feasibility of a commercial-scale CO2 storage site. RMS complements other analyses, including traditional petrography, SEM, porosity and permeability, and XRD For this aspect of the study, RMS is especially important in the evaluation of OM in sealing lithologies. At prospective geologic CO2 storage sites, it is imperative to assess the unconventional oil and gas potential of seals to ensure that any future development would not compromise the integrity of the seals. Whole-slide mineralogical surveys were performed on thin sections from various shale and sandstone formations. Surveys were analyzed with Direct Classical Least Squares to identify and quantify minerals. The location and concentration of minerals was color-coded and overlaid on optical images for visualization of the distribution of minerals. Dense hyperspectral Raman mapping of OM was performed on five thin sections. Eleven spectral parameters diagnostic of organic type and thermal maturity were used to train a Partial Least Squares (PLS) calibration against a set of artificially matured samples spanning the pre- to mid-oil window. The PLS was applied to the study set and a post-mature set. Additionally, the PLS was applied to each point in hyperspectral maps for visualization of trends in maturity across sample sets and discrimination of organic matter types within a given map. In inorganic surveys on thin sections, a total of 14 unique inorganic minerals were identified in Raman spectra including quartz, dolomite, calcite, hematite and anhydrite. Shale thin sections tended to be dominated by organic material. OM was often observed mixed with inorganic minerals. Sand- and mudstones were dominated by inorganic minerals. The PLS extrapolated the post-mature set to reflectances >1.2%. The study set ranged from very immature to postmature in the median of map fit-peak parameters. However, point maturity maps indicate that matrix OM in all study samples is immature and that discreet organic particles selected for mapping, which may be inertinites, bias medians towards more-mature. The work demonstrates the capabilities of RMS to perform both whole-slide mineralogy and OM analysis with applications to formation evaluation in oil & gas, carbon sequestration and mining. Here, analysis of sealing formations in the well indicates high levels of immature organic matter that would not be a viable target for future oil production that could compromise the CO2 storage site. The work brings together diverse disciplines from geology and petrography to analytical chemistry, big data and microscopy.

Myers, Grant↗
DOE OSTI2020

Analytic Modeling of a Deep Shielding Problem

Previous generations of scientists would make tremendous efforts to simplify non-tractable problems and generate simpler models that preserved the fundamental physics. This process involved applying assumptions and simplifications to reduce the complexity of the problem until it reached a solvable form. Each assumption and simplification was chosen and applied with the intent to preserve the essential physics of the problem, since, if the core physics of the problem were eliminated, the simplified model served no purpose. Moreover, if done correctly, solutions to the reduced model would serve as useful approximations to the original problem. In a sense, solving the simple models laid the ground-work for and provided insight into the more complex problem. Today, however, the affordability of high performance computing has essentially replaced the process for analyzing complex problems. Rather than "building up" a problem by understanding smaller, simpler models, a user generally relies on powerful computational tools to directly arrive at solutions to complex problems. As computational resources grow, users continue trying to simulate new, more complex, or more detailed problems, resulting in continual stress on both the code and computational resources. When these resources are limited, the user will have to make concessions by simplifying the problem while trying to preserve important details. In the context of the Monte Carlo N-Particle radiation transport simulation tool, simplifications typically come as reductions in geometry, or by using variance reduction techniques. Both approaches can influence the physics of the problem, leading to potentially inaccurate or non-physical results. Errors can also be introduced as a result of faulty input into a computational tool: something as simple as transposing numbers in a tally input can result in incorrect answers. In this paradigm, reduced complexity computational and analytical models still have an important purpose. The explicit form of an analytic solution is arguably the best way to understand the qualitative properties of simple models. In contrast to "building up" a complex problem through understanding simpler problems, results from detailed computational scenarios can be better explained by "building down" the complex model through simple models rooted in the fundamental or essential phenomenology. Simplified analytic and computational models can be used to 1) increase a user's confidence in the computational solution of a complex model, 2) confirm there are no user input errors, and 3) ensure essential assumptions of the simulation tool are preserved. This process of using analytic models to develop a more valuable analysis of simulation results is named the results assessment methodology. The utility of the results assessment methodology and a complimentary sensitivity analysis is exemplified through the analysis of the neutron flux in a dry used fuel storage cask. This application was chosen due to current scientific interest in used nuclear fuel storage.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Analytic Modeling of a Deep Shielding Problem

Previous generations of scientists would make tremendous efforts to simplify non-tractable problems and generate simpler models that preserved the fundamental physics. This process involved applying assumptions and simplifications to reduce the complexity of the problem until it reached a solvable form. Each assumption and simplification was chosen and applied with the intent to preserve the essential physics of the problem, since, if the core physics of the problem were eliminated, the simplified model served no purpose. Moreover, if done correctly, solutions to the reduced model would serve as useful approximations to the original problem. In a sense, solving the simple models laid the ground-work for and provided insight into the more complex problem. Today, however, the affordability of high performance computing has essentially replaced the process for analyzing complex problems. Rather than "building up" a problem by understanding smaller, simpler models, a user generally relies on powerful computational tools to directly arrive at solutions to complex problems. As computational resources grow, users continue trying to simulate new, more complex, or more detailed problems, resulting in continual stress on both the code and computational resources. When these resources are limited, the user will have to make concessions by simplifying the problem while trying to preserve important details. In the context of the Monte Carlo N-Particle radiation transport simulation tool, simplifications typically come as reductions in geometry, or by using variance reduction techniques. Both approaches can influence the physics of the problem, leading to potentially inaccurate or non-physical results. Errors can also be introduced as a result of faulty input into a computational tool: something as simple as transposing numbers in a tally input can result in incorrect answers. In this paradigm, reduced complexity computational and analytical models still have an important purpose. The explicit form of an analytic solution is arguably the best way to understand the qualitative properties of simple models. In contrast to "building up" a complex problem through understanding simpler problems, results from detailed computational scenarios can be better explained by "building down" the complex model through simple models rooted in the fundamental or essential phenomenology. Simplified analytic and computational models can be used to 1) increase a user's confidence in the computational solution of a complex model, 2) con firm there are no user input errors, and 3) ensure essential assumptions of the simulation tool are preserved. This process of using analytic models to develop a more valuable analysis of simulation results is named the results assessment methodology. The utility of the results assessment methodology and a complimentary sensitivity analysis is exempli fied through the analysis of the neutron flux in a dry used fuel storage cask. This application was chosen due to current scientific interest in used nuclear fuel storage.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Challenges Associated with In-Situ Calibration of Load Cells in Force Limited Vibration Testing

The difference in mounting configuration between flight and test can significantly impact the effectiveness of the test in environmental vibration testing. Many tests are performed with large electrodynamic shakers, which utilize interfaces that seek to replicate a fixed base, such as slip tables and head expanders. This fixed base configuration is rarely seen in flight configurations; rather a more realistic configuration would include a flexible mounting structure with its own compliance and dynamics. This causes significant over and under tests in various frequency bands depending on the differences between the test article and fixture dynamics. The traditional way of avoiding these high loads is to limit the acceleration responses at multiple locations on the test article. However, the effectiveness of this approach is highly dependent upon the validity of the test article’s analytical in order to derive accurate acceleration response limit specifications. Also this technique requires limiting the acceleration responses at many locations throughout the test article, which may not be implementable due to such things as access and cleanliness issues An improved environmental vibration testing technique known as force limiting incorporates measurements of the forces between the test article and shaker system interface and limiting them to a specification that more accurately replicates the interface impedance of the structure the test article will be mounted to in flight. In effect this transforms the high mechanical impedance at the test article to shaker interface to more closely match the mechanical impedance of the flight interface, which avoids producing the unrealistically high interface loads. Typically force gauges or load cells are used to measure these interface forces. However, utilizing load cells can present a multitude of challenges depending upon such things as their installation method, geometric layout, and test fixture setup. Regardless, it is extremely important to perform an in-situ calibration of the load cells prior to vibration testing at any significant levels. This paper will discuss the challenges associated with utilizing load cells during the NASA Evolutionary Xenon Thruster – Commercial (NEXT-C) gridded ion thruster proto-flight vibration test performed at the NASA Glenn Research Center’s Structural Dynamics Laboratory.

Kenneth J Pederson↗
NASA NTRSDate not supplied

Challenges Associated with In-Situ Calibration of Load Cells in Force Limited Vibration Testing

The difference in mounting configuration between flight and test can significantly impact the effectiveness of the test in environmental vibration testing. Many tests are performed with large electrodynamic shakers, which utilize interfaces that seek to replicate a fixed base, such as slip tables and head expanders. This fixed base configuration is rarely seen in flight configurations; rather a more realistic configuration would include a flexible mounting structure with its own compliance and dynamics. This causes significant over and under tests in various frequency bands depending on the differences between the test article and fixture dynamics. The traditional way of avoiding these high loads is to limit the acceleration responses at multiple locations on the test article. However, the effectiveness of this approach is highly dependent upon the validity of the test article’s analytical in order to derive accurate acceleration response limit specifications. Also this technique requires limiting the acceleration responses at many locations throughout the test article, which may not be implementable due to such things as access and cleanliness issues An improved environmental vibration testing technique known as force limiting incorporates measurements of the forces between the test article and shaker system interface and limiting them to a specification that more accurately replicates the interface impedance of the structure the test article will be mounted to in flight. In effect this transforms the high mechanical impedance at the test article to shaker interface to more closely match the mechanical impedance of the flight interface, which avoids producing the unrealistically high interface loads. Typically force gauges or load cells are used to measure these interface forces. However, utilizing load cells can present a multitude of challenges depending upon such things as their installation method, geometric layout, and test fixture setup. Regardless, it is extremely important to perform an in-situ calibration of the load cells prior to vibration testing at any significant levels. This paper will discuss the challenges associated with utilizing load cells during the NASA Evolutionary Xenon Thruster – Commercial (NEXT-C) gridded ion thruster proto-flight vibration test performed at the NASA Glenn Research Center’s Structural Dynamics Laboratory.

K. J. Pederson↗
DOE OSTI2022

Multiscale Electrochemomechanics Interaction and Degradation Analytics of Sn Electrodes for Sodium-Ion Batteries

Sodium-ion batteries have emerged as a strong contender among the beyond lithium-ion chemistries due to elemental abundance and the low cost of sodium. Tin (Sn) is a promising alloying electrode with high capacity, redox reversibility, and earth abundance. Tin electrodes, however, undergo a series of intermediate reactions exhibiting multiple voltage plateaus upon sodiation/desodiation. Phase transformations related to incomplete sodiation in tin during cycling, in the presence of a frail solid electrolyte interphase layer, can quickly weaken the structural stability. The structural dynamics and reactivity of the electrode/electrolyte interface, being further dependent on the size and morphology of the active material particle in the presence of different electrolytes, dictate the electrode degradation and survivability during cycling. Here, we paint a comprehensive picture of the underpinnings of the electrochemical and mechanics coupling and electrode/electrolyte interfacial interactions in alloying Sn electrodes. We elicit the fundamental role of electrode/electrolyte complexations in the Sn electrode structure-property-performance relationship based on multimodal analytics, including electrochemical, microscopy, and tomography analyses.

25 ENERGY STORAGE↗
DOE OSTI2023

Robust scalable initialization for Bayesian variational inference with multi-modal Laplace approximations

Predictive modeling typically relies on Bayesian model calibration to provide uncertainty quantification. Variational inference utilizing fully independent (“mean-field”) Gaussian distributions are often used as approximate probability density functions. This simplification is attractive since the number of variational parameters grows only linearly with the number of unknown model parameters. However, the resulting diagonal covariance structure and unimodal behavior can be too restrictive to provide useful approximations of intractable Bayesian posteriors that exhibit highly non-Gaussian behavior, including multimodality. High-fidelity surrogate posteriors for these problems can be obtained by considering the family of Gaussian mixtures. Gaussian mixtures are capable of capturing multiple modes and approximating any distribution to an arbitrary degree of accuracy, while maintaining some analytical tractability. Unfortunately, variational inference using Gaussian mixtures with full-covariance structures suffers from a quadratic growth in variational parameters with the number of model parameters. The existence of multiple local minima due to strong nonconvex trends in the loss functions often associated with variational inference present additional complications, These challenges motivate the need for robust initialization procedures to improve the performance and computational scalability of variational inference with mixture models. In this work, we propose a method for constructing an initial Gaussian mixture model approximation that can be used to warm-start the iterative solvers for variational inference. The procedure begins with a global optimization stage in model parameter space. In this step, local gradient-based optimization, globalized through multistart, is used to determine a set of local maxima, which we take to approximate the mixture component centers. Around each mode, a local Gaussian approximation is constructed via the Laplace approximation. Finally, the mixture weights are determined through constrained least squares regression. The robustness and scalability of the proposed methodology is demonstrated through application to an ensemble of synthetic tests using high-dimensional, multimodal probability density functions. Here, the practical aspects of the approach are demonstrated with inversion problems in structural dynamics.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Optimal Force Control of Vibro-Impact Systems for Autonomous Drilling Applications

The need to maintain optimal energy efficiency is critical during the drilling operations performed on future and current planetary rover missions (see figure). Specifically, this innovation seeks to solve the following problem. Given a spring-loaded percussive drill driven by a voice-coil motor, one needs to determine the optimal input voltage waveform (periodic function) and the optimal hammering period that minimizes the dissipated energy, while ensuring that the hammer-to-rock impacts are made with sufficient (user-defined) impact velocity (or impact energy). To solve this problem, it was first observed that when voice-coil-actuated percussive drills are driven at high power, it is of paramount importance to ensure that the electrical current of the device remains in phase with the velocity of the hammer. Otherwise, negative work is performed and the drill experiences a loss of performance (i.e., reduced impact energy) and an increase in Joule heating (i.e., reduction in energy efficiency). This observation has motivated many drilling products to incorporate the standard bang-bang control approach for driving their percussive drills. However, the bang-bang control approach is significantly less efficient than the optimal energy-efficient control approach solved herein. To obtain this solution, the standard tools of classical optimal control theory were applied. It is worth noting that these tools inherently require the solution of a two-point boundary value problem (TPBVP), i.e., a system of differential equations where half the equations have unknown boundary conditions. Typically, the TPBVP is impossible to solve analytically for high-dimensional dynamic systems. However, for the case of the spring-loaded vibro-impactor, this approach yields the exact optimal control solution as the sum of four analytic functions whose coefficients are determined using a simple, easy-to-implement algorithm. Once the optimal control waveform is determined, it can be used optimally in the context of both open-loop and closed-loop control modes (using standard realtime control hardware).

Aldrich, Jack B.↗
DOE OSTI2022

Deep Convolutional Neural Networks Exploit High-Spatial- and -Temporal-Resolution Aerial Imagery to Phenotype Key Traits in Miscanthus

Miscanthus is one of the most promising perennial crops for bioenergy production, with high yield potential and a low environmental footprint. The increasing interest in this crop requires accelerated selection and the development of new screening techniques. New analytical methods that are more accurate and less labor-intensive are needed to better characterize the effects of genetics and the environment on key traits under field conditions. We used persistent multispectral and photogrammetric UAV time-series imagery collected 10 times over the season, together with ground-truth data for thousands of Miscanthus genotypes, to determine the flowering time, culm length, and biomass yield traits. We compared the performance of convolutional neural network (CNN) architectures that used image data from single dates (2D-spatial) versus the integration of multiple dates by 3D-spatiotemporal architectures. The ability of UAV-based remote sensing to rapidly and non-destructively assess large-scale genetic variation in flowering time, height, and biomass production was improved through the use of 3D-spatiotemporal CNN architectures versus 2D-spatial CNN architectures. The performance gains of the best 3D-spatiotemporal analyses compared to the best 2D-spatial architectures manifested in up to 23% improvements in R2, 17% reductions in RMSE, and 20% reductions in MAE. The integration of photogrammetric and spectral features with 3D architectures was crucial to the improved assessment of all traits. In conclusion, our findings demonstrate that the integration of high-spatiotemporal-resolution UAV imagery with 3D-CNNs enables more accurate monitoring of the dynamics of key phenological and yield-related crop traits. This is especially valuable in highly productive, perennial grass crops such as Miscanthus, where in-field phenotyping is especially challenging and traditionally limits the rate of crop improvement through breeding.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Manifold Learning-Based Polynomial Chaos Expansions for High-Dimensional Surrogate Models

In this work we introduce a manifold learning-based method for uncertainty quantification (UQ) in systems describing complex spatiotemporal processes. Our first objective is to identify the embedding of a set of high-dimensional data representing quantities of interest of the computational or analytical model. For this purpose, we employ Grassmannian diffusion maps, a two-step nonlinear dimension reduction technique which allows us to reduce the dimensionality of the data and identify meaningful geometric descriptions in a parsimonious and inexpensive manner. Polynomial chaos expansion is then used to construct a mapping between the stochastic input parameters and the diffusion coordinates of the reduced space. An adaptive clustering technique is proposed to identify an optimal number of clusters of points in the latent space. The similarity of points allows us to construct a number of geometric harmonic emulators which are finally utilized as a set of inexpensive pretrained models to perform an inverse map of realizations of latent features to the ambient space and thus perform accurate out-of-sample predictions. Thus, the proposed method acts as an encoder-decoder system which is able to automatically handle very high-dimensional data while simultaneously operating successfully in the small-data regime. The method is demonstrated on two benchmark problems and on a system of advection-diffusion-reaction equations which model a first-order chemical reaction between two species. In all test cases, the proposed method is able to achieve highly accurate approximations which ultimately lead to the significant acceleration of UQ tasks.

42 ENGINEERING↗
DOE OSTI2022

Understanding the Role of Order in Y‐Series Non‐Fullerene Solar Cells to Realize High Open‐Circuit Voltages

Abstract Non‐fullerene acceptors (NFAs) as used in state‐of‐the‐art organic solar cells feature highly crystalline layers that go along with low energetic disorder. Here, the crucial role of energetic disorder in blends of the donor polymer PM6 with two Y‐series NFAs, Y6, and N4 is studied. By performing temperature‐dependent charge transport and recombination studies, a consistent picture of the shape of the density of state distributions for free charges in the two blends is developed, allowing an analytical description of the dependence of the open‐circuit voltage V OC on temperature and illumination intensity. Disorder is found to influence the value of the V OC at room temperature, but also its progression with temperature. Here, the PM6:Y6 blend benefits substantially from its narrower state distributions. The analysis also shows that the energy of the equilibrated free charge population is well below the energy of the NFA singlet excitons for both blends and possibly below the energy of the populated charge transfer manifold, indicating a down‐hill driving force for free charge formation. It is concluded that energetic disorder of charge‐separated states has to be considered in the analysis of the photovoltaic properties, even for the more ordered PM6:Y6 blend.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Self-supported MoO 2 /MoS 2 nano-sheets embedded in a carbon cloth as a binder-free substrate for high-energy lithium–sulfur batteries

As one of the most prospective candidates for next-generation rechargeable batteries, lithium-sulfur (Li-S) batteries currently still encounter great challenges associated with the low conductivity, severe shuttle effects, and sluggish redox kinetics. Herein, a self-supported sulfur host is fabricated by an in-situ growth of MoO 2 /MoS 2 nano-sheets on a carbon cloth (CC). First, carbon cloth serves as a good template for the morphology-controlled synthesis of nanostructured materials, which not only alleviates the agglomeration of MoO2/MoS2, but also enhances the flexibility and mechanical strengthen of the hybrid architecture as a free-standing host. Second, the polysulfide-trapping ability can be greatly enhanced by both physical and chemical adsorption from the MoO 2 /MoS 2 -anchored carbon cloth. Moreover, the partially sulfurized MoO 2 /MoS 2 nano-sheets integrate the benefits of conductive MoO 2 and sulfiphilic MoS 2 , thus facilitating fast charge transfer and redox kinetics of polysulfide conversion. As a result, these attributes enable the host to hold a high sulfur loading (up to 7.6 mg cm -2 ), which exceeds most of the reported carbon cloth-related cathode work in the literature. Furthermore, the Li-S cells can achieve a high peak capacity of 1350 mA h g -1 , excellent rate capability (C/20 - 2C rate), impressive areal capacity (up to 6.3 mA h cm -2 ), and a high capacity retention of 85% after 100 cycles.

25 ENERGY STORAGE↗
DOE OSTI2024

Data Analytics for Catalysis Predictions: Are We Ready Yet?

Catalysis informatics has received tremendous attention in recent years as a tool to design catalysts and discover unique descriptors that capture the relationships between chemical properties and catalytic performance. One of the stop-gaps in understanding catalytic effects, which is often ignored and limits the deployment of data science tools, relates to the lack of uniform data. The catalytic cleavage of C–X (X= H, C, N, and O) bonds is relevant to many fundamental catalytic processes. In this Perspective, we performed data analytics on four groups of C–X cleavage reactions that are common in production, upcycling, or reactive separation: the C–C cleavage in cyclopropyl alcohol, the C–H cleavage in hydroacylation reactions, the C–O cleavage in β-O-4 linkages, and the C–N cleavage in amides, using experimental data collected from the literature to understand their underlying correlations. Experimental variables of high impact are identified for each reaction by dimensionality reduction methods. We highlight the urgent need for experimental data sets that include full details on the reaction conditions, such as reagent concentration, reaction temperature, or time in machine-readable forms. We discuss the potential improvement of the data of these reactions and promising approaches such as autonomous experiments to fill the gaps in unbiased experimental data. Finally, we also address the early stage consideration of separation aspects in the experimental design of efficient catalytic systems for these fundamental examples of chemical reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Uranium Bed Design Parameters for Tritium Plants Supporting Fusion Reactors

Uranium hydride is commonly used to store hydrogen or its isotopes in a solid state. The Self-Assaying Tritium Accountancy and Containment Unit for ITER (STACI) is a 5.2-kg bed of depleted uranium (dU) capable of holding up to 33 mol of hydrogen or its isotopes. Here we summarize the data analysis of past experimental campaigns with STACI, with the aim of describing the kinetics and thermodynamics of the hydriding process. Computed tomography imaging was performed on STACI both before and after its experimental campaign, and a high degree of swelling was observed in the dU. Literature on studies in regard to the swelling of large (multikilogram) quantities of uranium hydride for storage applications was not identified during this study. Data from the experimental campaign, as well as data on the formation reaction, are presented. The authors hope to create an analytical model of STACI based on these data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1972

Study of low gravity propellant transfer

The results are presented of a program to perform an analytical assessment of potential methods for replenishing the auxiliary propulsion, fuel cell and life support cryogens which may be aboard an orbiting space station. The fluids involved are cryogenic H2, O2, and N2. A complete transfer system was taken to consist of supply storage, transfer, and receiver tank fluid conditioning (pressure and temperature control). In terms of supply storage, the basic systems considered were high pressure (greater than critical), intermediate pressure (less than critical), and modular (transfer of the tanks). Significant findings are included.

Source record↗
NASA NTRS1977

Cost analysis of advanced turbine blade manufacturing processes

A rigorous analysis was conducted to estimate relative manufacturing costs for high technology gas turbine blades prepared by three candidate materials process systems. The manufacturing costs for the same turbine blade configuration of directionally solidified eutectic alloy, an oxide dispersion strengthened superalloy, and a fiber reinforced superalloy were compared on a relative basis to the costs of the same blade currently in production utilizing the directional solidification process. An analytical process cost model was developed to quantitatively perform the cost comparisons. The impact of individual process yield factors on costs was also assessed as well as effects of process parameters, raw materials, labor rates and consumable items.

Barth, C. F.↗
NASA NTRS1984

Summary of recent NASA propeller research

Advanced high-speed propellers offer large performance improvements for aircraft that cruise in the Mach 0.7 to 0.8 speed regime. At these speeds, studies indicate that there is a 15 to near 40 percent block fuel savings and associated operating cost benefits for advanced turboprops compared to equivalent technology turbofan powered aircraft. Recent wind tunnel results for five eight to ten blade advanced models are compared with analytical predictions. Test results show that blade sweep was important in achieving net efficiencies near 80 percent at Mach 0.8 and reducing nearfield cruise noise by about 6 dB. Lifting line and lifting surface aerodynamic analysis codes are under development and some results are compared with propeller force and probe data. Also, analytical predictions are compared with some initial laser velocimeter measurements of the flow field velocities of an eightbladed 45 swept propeller. Experimental aeroelastic results indicate that cascade effects and blade sweep strongly affect propeller aeroelastic characteristics. Comparisons of propeller near-field noise data with linear acoustic theory indicate that the theory adequately predicts near-field noise for subsonic tip speeds but overpredicts the noise for supersonic tip speeds.

Mikkelson, D. C.↗