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At least 217 records · Page 12

Pressure distribution on the nose of an airship in circling flight

In recent tests on the pressures occurring on the envelope and control surfaces of the naval airship C-7, it was noted that the pressures on the nose of the airship, while flying in level circling flight, were symmetrically distributed. Such a condition can only occur when the nose of the airship is pointed directly into the wind, and to accomplish this in circling flight, the axis of the airship must then be parallel to the direction of the motion of the nose. The question was raised as to whether the same conditions occur generally on all airships in circling flight. It appears that airships flying in a constant, level, circling flight path will generally head very closely into the wind, and any deviation will be so slight that the distribution of pressure over the nose will be but slightly, if at all, changed from a symmetrical distribution.

Fairbanks, Karl J↗

Mesoscale simulation of granular materials under weak shock compaction–pore size distribution effects

This research established a systematic method to generate various pore-size distributions (PSDs) and studied the effect of PSDs on the shock compaction response of granular materials using two-dimensional mesoscale simulations under identical porosity. Simulations utilized various PSDs for three particle shapes (circle, ellipse, and square). Contacting particle configurations using three PSDs, characterized by spatially uniform distributed pores to heterogeneous distributed pores, and non-contacting particle configurations under a single case of PSD were tested. The PSD of generated particle sets was characterized using coordination number, mean diameter, and bimodality coefficient as statistical metrics. Mesoscale simulations showed that regardless of the conditions of pore distributions, shock compaction of granular materials consistently demonstrates a precursor, shock compaction front, and end. However, the shock compaction velocity of contacting particles was dependent on the PSDs despite the constant initial porosity. The compaction velocity was faster in particle configurations with relatively uniform pore distributions than in heterogeneous pore distributions, which our study demonstrated can be attributed to particle rearrangement during compaction. Circular-shaped particles had high sensitivity in shock compaction response to the various PSDs. Furthermore, a contacting particle configuration tended to propagate the shock compaction wave relatively faster than particles that were in a non-contact configuration. This study established the relative importance of considering PSD as a metric over the coordination number in studies of the shock compaction response of granular materials. Further, insights are provided on the evolving shock substructure to characterize the shock compaction response of granular materials.

36 MATERIALS SCIENCE↗

Distributed automatic control of technological processes in conditions of weightlessness

Some problems associated with the automatic control of liquid metal and plasma systems under conditions of weightlessness are examined, with particular reference to the problem of stability of liquid equilibrium configurations. The theoretical fundamentals of automatic control of processes in electrically conducting continuous media are outlined, and means of using electromagnetic fields for simulating technological processes in a space environment are discussed.

Kukhtenko, A. I.↗

Wall Shear Stress, Wall Pressure and Near Wall Velocity Field Relationships in a Whirling Annular Seal

The mean and phase averaged pressure and wall shear stress distributions were measured on the stator wall of a 50% eccentric annular seal which was whirling in a circular orbit at the same speed as the shaft rotation. The shear stresses were measured using flush mounted hot-film probes. Four different operating conditions were considered consisting of Reynolds numbers of 12,000 and 24,000 and Taylor numbers of 3,300 and 6,600. At each of the operating conditions the axial distribution (from Z/L = -0.2 to 1.2) of the mean pressure, shear stress magnitude, and shear stress direction on the stator wall were measured. Also measured were the phase averaged pressure and shear stress. These data were combined to calculate the force distributions along the seal length. Integration of the force distributions result in the net forces and moments generated by the pressure and shear stresses. The flow field inside the seal operating at a Reynolds number of 24,000 and a Taylor number of 6,600 has been measured using a 3-D laser Doppler anemometer system. Phase averaged wall pressure and wall shear stress are presented along with phase averaged mean velocity and turbulence kinetic energy distributions located 0.16c from the stator wall where c is the seal clearance. The relationships between the velocity, turbulence, wall pressure and wall shear stress are very complex and do not follow simple bulk flow predictions.

Morrison, Gerald L.↗

Joint Modeling of Wind Speed and Wind Direction Through a Conditional Approach

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. In this work, we develop a conditional approach to model these two variables, where the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. To accommodate the circular nature of wind direction, a von Mises mixture model is used; the conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the dependence of the Weibull parameters on wind direction. A Monte Carlo simulation study indicates that our method outperforms two other approaches in estimation efficiency: one that utilizes periodic spline quantile regression and another that generates data from the commonly used Abe-Ley distribution for cylindrical data. We illustrate our method by using the output from a regional climate model to investigate how the joint distribution of wind speed and direction may change under some future climate scenarios. Our method indicates significant changes in the variation of wind speed with respect to some directions.

17 WIND ENERGY↗

Investigation at Mach Numbers of 0.60 to 3.50 of Blended Wing-Body Combinations with Cambered and Twisted Wings with Diamond, Delta and Arrow Plan Forms

This investigation is a continuation of the experimental and theoretical evaluation of blended wing-body combinations. The basic diamond, delta, and arrow plan forms which had an aspect ratio of 2 with leading-edge sweeps of 45.00 deg., 59.04 deg., and 70.82 deg. and trailing edge of -45.00 deg., -18.43 deg., and 41.19 deg., respectively, are used herein as standards for evaluating the effects of camber and warp. The wing thickness distributions were computed by varying the section shape along with the body radii (blending process) to match the prescribed area distribution and wing plan form. The wing camber and warp were computed to try to obtain nearly elliptical spanwise and chordwise load distributions for each plan form and thus to obtain low drag due to lift for a range of Mach numbers for which the velocities normal to the wing leading edge are subsonic. Elliptical chordwise load distributions were not possible for the plan forms and design conditions selected, so these distributions were somewhat different for each plan form. The models were tested with transition fixed at Mach numbers from 0.60 to 3.50 and at Reynolds numbers, based on the mean aerodynamic chord of the wing, of roughly 4,000,000 to 9,000,000. At speeds where the velocities normal to the wing leading edges were supersonic, an increase in the experimental wave-drag coefficients due to camber and twist was evident, but this penalty decreased with increased sweep. Thus the minimum wave-drag coefficients for the cambered arrow model were almost identical with the zero-lift wave- drag coefficients for the uncambered arrow model at all test Mach numbers.

Holdaway, George H.↗

A Three-Dimensional Solution of Flows over Wings with Leading-Edge Vortex Separation. Part 1: Engineering Document

A method of predicting forces, moments, and detailed surface pressures on thin, sharp-edged wings with leading-edge vortex separation in incompressible flow is presented. The method employs an inviscid flow model in which the wing and the rolled-up vortex sheets are represented by piecewise, continuous quadratic doublet sheet distributions. The Kutta condition is imposed on all wing edges. Computed results are compared with experimental data and with the predictions of the leading-edge suction analogy for a selected number of wing planforms over a wide range of angle of attack. These comparisons show the method to be very promising, capable of producing not only force predictions, but also accurate predictions of detailed surface pressure distributions, loads, and moments.

Brune, G. W.↗

Pressure distributions from high Reynolds number transonic tests of an NACA 0012 airfoil in the Langley 0.3-meter transonic cryogenic tunnel

Tests were conducted in the 2-D test section of the Langley 0.3-meter Transonic Cryogenic Tunnel on a NACA 0012 airfoil to obtain aerodynamic data as a part of the Advanced Technology Airfoil Test (ATAT) program. The test program covered a Mach number range of 0.30 to 0.82 and a Reynolds number range of 3.0 to 45.0 x 10 to the 6th power. The stagnation pressure was varied between 1.2 and 6.0 atmospheres and the stagnation temperature was varied between 300 K and 90 K to obtain these test conditions. Tabulated pressure distributions and integrated force and moment coefficients are presented as well as plots of the surface pressure distributions. The data are presented uncorrected for wall interference effects and without analysis.

Ladson, Charles L.↗

Multiscale Modeling of Nanoparticle Precipitation in Oxide Dispersion-Strengthened Steels Produced by Laser Powder Bed Fusion

Laser Powder Bed Fusion (LPBF) enables the efficient production of near-net-shape oxide dispersion-strengthened (ODS) alloys, which possess superior mechanical properties due to oxide nanoparticles (e.g., yttrium oxide, Y-O, and yttrium-titanium oxide, Y-Ti-O) embedded in the alloy matrix. To better understand the precipitation mechanisms of the oxide nanoparticles and predict their size distribution under LPBF conditions, we developed an innovative physics-based multiscale modeling strategy that incorporates multiple computational approaches. These include a finite volume method model (Flow3D) to analyze the temperature field and cooling rate of the melt pool during the LPBF process, a density functional theory model to calculate the binding energy of Y-O particles and the temperature-dependent diffusivities of Y and O in molten 316L stainless steel (SS), and a cluster dynamics model to evaluate the kinetic evolution and size distribution of Y-O nanoparticles in as-fabricated 316L SS ODS alloys. The model-predicted particle sizes exhibit good agreement with experimental measurements across various LPBF process parameters, i.e., laser power (110–220 W) and scanning speed (150–900 mm/s), demonstrating the reliability and predictive power of the modeling approach. The multiscale approach can be used to guide the future design of experimental process parameters to control oxide nanoparticle characteristics in LPBF-manufactured ODS alloys. Additionally, our approach introduces a novel strategy for understanding and modeling the thermodynamics and kinetics of precipitation in high-temperature systems, particularly molten alloys.

Wang, Zhengming (ORCID:0000000241627112)↗

The Application of Nonstandard Analysis to the Study of Inviscid Shock Wave Jump Conditions

The use of conservation laws in nonconservative form for deriving shock jump conditions by Schwartz distribution theory leads to ambiguous products of generalized functions. Nonstandard analysis is used to define a class of Heaviside functions where the jump from zero to one occurs on an infinitesimal interval. These Heaviside functions differ by their microstructure near x = 0, i.e., by the nature of the rise within the infinitesimal interval it is shown that the conservation laws in nonconservative form can relate the different Heaviside functions used to define jumps in different flow parameters. There are no mathematical or logical ambiguities in the derivation of the jump conditions. An important result is that the microstructure of the Heaviside function of the jump in entropy has a positive peak greater than one within the infinitesimal interval where the jump occurs. This phenomena is known from more sophisticated studies of the structure of shock waves using viscous fluid assumption. However, the present analysis is simpler and more direct.

Farassat, F.↗

Computationally efficient and error aware surrogate construction for numerical solutions of subsurface flow through porous media

Limiting the injection rate to restrict the pressure below a threshold at a critical location can be an important goal of simulations that model the subsurface pressure between injection and extraction wells. The pressure is approximated by the solution of Darcy’s partial differential equation for a given permeability field. The subsurface permeability is modeled as a random field since it is known only up to statistical properties. This induces uncertainty in the computed pressure. Solving the partial differential equation for an ensemble of random permeability simulations enables estimating a probability distribution for the pressure at the critical location. These simulations are computationally expensive, and practitioners often need rapid online guidance for real-time pressure management. An ensemble of numerical partial differential equation solutions is used to construct a Gaussian process regression model that can quickly predict the pressure at the critical location as a function of the extraction rate and permeability realization. The Gaussian process surrogate analyzes the ensemble of numerical pressure solutions at the critical location as noisy observations of the true pressure solution, enabling robust inference using the conditional Gaussian process distribution. Our first novel contribution is to identify a sampling methodology for the random environment and matching kernel technology for which fitting the Gaussian process regression model scales as O ( n log n ) instead of the typical O ( n 3 ) rate in the number of samples n used to fit the surrogate. The surrogate model allows almost instantaneous predictions for the pressure at the critical location as a function of the extraction rate and permeability realization. Our second contribution is a novel algorithm to calibrate the uncertainty in the surrogate model to the discrepancy between the true pressure solution of Darcy’s equation and the numerical solution. Finally, although our method is derived for building a surrogate for the solution of Darcy’s equation with a random permeability field, the framework broadly applies to solutions of other partial differential equations with random coefficients.

54 ENVIRONMENTAL SCIENCES↗

Investigation of multispectral remote sensing of snow cover using a solar radiation model

A solar radiation model is described which is able to calculate, for given atmospheric and topographic input conditions, the spectral distributions of the direct and diffuse components of the total irradiance incident upon a target surface. The irradiance includes both upwelling radiation backscattered toward the earth's surface and radiation reflected toward the target from other terrain surfaces. Spectral reflectance data for two dissimilar snow types are fed into the model, along with a geometric description of the topography of the snow covered terrain. These data permit the calculation of the exitance of the target over the wavelength limits of a given sensor and, hence, the apparent contrast between the two snow types for the given input conditions. The results show that the contrast between the two snow types, all other factors being constant, is greatest in the near infrared wavelengths.

Waterman, S. E.↗

A comparative analysis of residual stresses from friction stir processing of aluminum cast 380 and wrought 7075 alloy sheets: experimental characterization and modeling

Residual stresses are often overlooked in friction stir processing (FSP), but their significant impact on fatigue performance necessitates their consideration in optimizing processing parameters. The first step in this effort is understanding how process conditions influence residual stress distributions, especially across different alloys. This study focuses on determining and explaining the through-thickness residual stress variations and the effect of process temperature on the residual stress magnitude in wrought AA7075 and cast AA380.0 alloys. Additionally, for AA380.0, the impact of a second FSP pass was investigated. To achieve this, hole-drilling electronic speckle pattern interferometry (ESPI) and the thermal pseudo-mechanical (TPM) model within finite element analysis were employed to study the 3D distributions of in-plane residual stresses in processed samples under various conditions. A key finding was the varying impact of process temperatures on residual stress magnitudes. Higher process temperatures reduced stresses in AA380.0 but increased them in AA7075. Additionally, the through-thickness stress distributions differed between the two alloys. Further analysis revealed that yield stresses are crucial in explaining these phenomena and the effects of additional FSP passes. Further, this fundamental understanding will be vital in guiding the efforts to mitigate residual stresses and assess their impact on the performance of FSP aluminum alloys.

36 MATERIALS SCIENCE↗

Electron Beam Welding of Pure Tungsten Hex Cans for Nuclear Thermal Propulsion Engines

Nuclear thermal propulsion (NTP) is an in-space propulsion method currently being developed at the NASA Marshall Space Flight Center (MSFC). NTP systems are a high specific impulse (750–1,100 s), high thrust (15,000–250,000 lbf ) method of propulsion which have the potential to allow for faster transit times when optimizing for high ΔV. In the nuclear rocket engine, the heat from the nuclear fission reaction is transferred to a low molecular mass propellant (such as hydrogen). Hot propellant is expanded through a nozzle to generate thrust. Development of ceramic metal (cermet) fuel systems for NTP applications is currently ongoing at MSFC. In cermet fuel systems, ceramic fissile fuel particles such as uranium nitride or uranium dioxide are dispersed within a net-shaped, high-density structural matrix. The composite material is cladded by a protective metal structure to make up an NTP fuel element. Cladding materials must be able to withstand the demanding operating conditions required of the engine as well as retain a hermetic seal to allow for retention of fuel element structural integrity, prevent hydrogen attack or migration of the ceramic fuel, and limit release of fission products during operation. For NTP applications, tungsten is a prime material for both the metal matrix and cladding in cermet fuel systems because of its high melting point, high temperature strength, and compatibility with hot hydrogen. If a weld in tungsten with the capability of holding a hermetic seal is achievable, tungsten becomes a strong candidate for NTP applications. This Technical Memorandum focuses on determining the weldability of pure tungsten using electron beam welding (EBW). Tungsten appears well suited for NTP applications, but it has a high ductile to brittle transition temperature (DBTT) dependent upon chemical composition, structure/stress distribution, and mechanical conditions. Therefore, it is highly subject to brittle fracture. Because of its high susceptibility to brittle fracture, it is very difficult to weld. EBW was chosen for joining pure tungsten because of its low heat input compared to gas tungsten arc welding. Reduced heat input can be directly correlated with an increase in ductility of a tungsten weld. EBW is a high energy density welding process in which a stream of electrons penetrates a weld joint in a deep, narrow spike in contrast to a broad gas tungsten arc weld pool. The investigation initially focused on EBW of tungsten plates of both 0.01 in and 0.03 in thickness to determine if EBW could weld pure tungsten without the presence of visual defects—particularly cracking—in the welds. Variation in the weld procedure and post-weld heat treatment (PWHT) was used to improve the surface appearance of flat EBWs on a pure tungsten sheet. The investigation moved on to weld 0.05-in-thick hexagonal tungsten cans with a weld joint thickness of 0.025 in. The goal for welding the pure tungsten hex cans was to avoid any visual surface defects and generate a weld capable of a hermetic seal. This proved difficult. Cold welds commonly exhibited porosity that leaked air. Hot welds exhibited cracks, typically observed immediately after welding. Later welds were preheated to increase ductility and decrease the likelihood of through-thickness cracking. PWHT was used to arrest microcrack growth both in the flat weld samples and hexagonal weld samples.

Courtright, Z. S.↗

Numerical Simulation of No Vent Chill and Fill of a Large Liquid Hydrogen Tank

On orbit transfer of cryogenic liquids is necessary for many future space missions. The techniques required to transfer cryogens in micro gravity are quite different from ground system applications. In normal gravity, cryogenic tanks are usually filled from the bottom at nearly atmospheric pressure. The vapor generated due to heat transfer from warm tank walls, is allowed to vent from the top of the tank while the tank is being filled. If the normal gravity technique is used on orbit, the uncertainty of liquid and vapor distributions in unsettled condition may result in dumping of large amounts of liquid propellant overboard. The Vented Chill and No Vent Fill (VCNVF) process is a methodology [1] used to reduce propellant loss by holding the vent valve open during initial wall chilldown, preventing over-pressurization of the tank and stalling of the incoming flow, but closing the tank vent valve after chilling the tank wall sufficiently. An accurate simulation of no vent tank chill and fill is necessary to estimate the amount of propellant necessary to chill the tank, determine the maximum sustainable flowrate to fill the tank without stalling, and establish a timeline for the filling process. Numerical modeling of filling a cryogenic tank is complex because the flow is two-phase and the process involves both boiling and condensation with heat transfer between solid and fluid. In recent years, progress has been made to develop a numerical modeling technique [2,3,4] that has been verified by comparing with the test data from a small flight tank using liquid nitrogen [5]. The purpose of the present paper is to apply this technique in a larger tank with liquid hydrogen and compare with the test data of Chato [1]. The K-site Test Facility [1], shown in Figure 1, consists of a Test Tank, spray system, instrumentation, and the vacuum chamber. The test tank selected was ellipsoidal with an 87 inch major diameter and a 1.2 to 1 major to minor axis ratio. The two ends are joined by a short 1.5 inch cylindrical section. The tank is made of 2219 aluminum chemically milled to a nominal thickness of 0.087 inches. The tank weighs 329.25 pounds, and the tank volume is 175 ft 3 . The GFSSP model of the Test Tank is shown in Figure 2. Node 13 is a boundary node that represents the supply tank which is supplying liquid hydrogen at a given pressure and temperature. The total measured flowrate is evenly distributed through Branches 131 through 139. Nodes 1 through 9 represent the test tank and they are connected with metal solid nodes 14 through 22 through fluid-to-solid conductors that allow convective heat transfer between the solid and fluid nodes. The predicted tank pressure, filling rate, wall temperature and fluid temperature will be compared with test data.

Alok Majumdar↗

Probing the Effect of Electrode Thermodynamics on Reaction Heterogeneity in Thick Battery Electrodes

Thick electrodes present a viable strategy for enhancing energy density and reducing manufacturing costs of lithium-ion batteries. However, reaction heterogeneity during cycling compromises their rate capability and cycle life. While this nonuniformity is commonly attributed to sluggish charge transport, it is demonstrated here that the thermodynamic properties of the electrode material play an equally critical role. Through combined X-ray fluorescence microscopy and absorption near-edge structure spectroscopy, reaction distributions in LiFePO 4 (LFP) and LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC) thick electrodes with matched porosity and tortuosity are compared. LFP electrodes develop pronounced depth-oriented state-of-charge (SOC) gradients that worsen with increasing discharge rates, whereas NMC maintains much more uniform SOC distributions under such conditions. This difference originates from their distinct SOC dependence of equilibrium potentials and is quantifiable through a dimensionless “reaction uniformity” number. Intriguingly, LFP thick electrodes also exhibit lateral SOC variations that strengthen during slow discharge. In conclusion, the enhanced reaction uniformity in NMC correlates with better active material utilization and slower capacity fade than LFP, highlighting electrode thermodynamics as a key design consideration for thick electrodes.

36 MATERIALS SCIENCE↗

SDYN-GANs: Adversarial learning methods for multistep generative models for general order stochastic dynamics

We introduce adversarial learning methods for data-driven generative modeling of dynamics of nth-order stochastic systems. Our approach builds on Generative Adversarial Networks (GANs) with generative model classes based on stable m-step stochastic numerical integrators. From observations of trajectory samples, we introduce methods for learning long-time predictors and stable representations of the dynamics. Our approaches use discriminators based on Maximum Mean Discrepancy (MMD), training protocols using both conditional and marginal distributions, and methods for learning dynamic responses over different time-scales. We show how our approaches can be used for modeling physical systems to learn force-laws, damping coefficients, and noise-related parameters. Our adversarial learning approaches provide methods for obtaining stable generative models for dynamic tasks including long-time prediction and developing simulations for stochastic systems.

• Artificial intelligence (AI) / machine learning ↗