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At least 19 records

Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems

In this work, we present Lift & Learn, a physics-informed method for learning low-dimensional models for large-scale dynamical systems. The method exploits knowledge of a system’s governing equations to identify a coordinate transformation in which the system dynamics have quadratic structure. This transformation is called a lifting map because it often adds auxiliary variables to the system state. The lifting map is applied to data obtained by evaluating a model for the original nonlinear system. This lifted data is projected onto its leading principal components, and low-dimensional linear and quadratic matrix operators are fit to the lifted reduced data using a least-squares operator inference procedure. Analysis of our method shows that the Lift & Learn models are able to capture the system physics in the lifted coordinates at least as accurately as traditional intrusive model reduction approaches. This preservation of system physics makes the Lift & Learn models robust to changes in inputs. Numerical experiments on the FitzHugh–Nagumo neuron activation model and the compressible Euler equations demonstrate the generalizability of our model.

97 MATHEMATICS AND COMPUTING↗

Learning the boundary-to-domain mapping using Lifting Product Fourier Neural Operators for partial differential equations

Neural operators such as the Fourier Neural Operator (FNO) have been shown to provide resolution-independent deep learning models that can learn mappings between function spaces. For example, an initial condition can be mapped to the solution of a partial differential equation (PDE) at a future time-step using a neural operator. Despite the popularity of neural operators, their use to predict solution functions over a domain given only data over the boundary (such as a spatially varying Dirichlet boundary condition) remains unexplored. In this paper, we refer to such problems as boundary-to-domain problems; they have a wide range of applications in areas such as fluid mechanics, solid mechanics, heat transfer etc. We present a novel FNO-based architecture, named Lifting Product FNO (or LP-FNO) which can map arbitrary boundary functions defined on the lower-dimensional boundary to a solution in the entire domain. Specifically, two FNOs defined on the lower-dimensional boundary are lifted into the higher dimensional domain using our proposed lifting product layer. We demonstrate the efficacy and resolution independence of the proposed LP-FNO for the 2D Poisson equation.

Kashi, Aditya↗

Approaches to high aspect ratio triangulations

In aerospace computational fluid dynamics calculations, high aspect ratio, or stretched, triangulations are necessary to adequately resolve the features of a viscous flow around bodies. In this paper, we explore alternatives to the Delaunay triangulation which can be used to generate high aspect ratio triangulations of point sets. The method is based on a variation of the lifting map concept which derives Delaunay triangulations from convex hull calculations.

Posenau, M.-A.↗

Chemical Interaction of Palladium in Uranium Oxycarbide Nuclear Fuel Kernel

Chemical Interaction of Palladium in Uranium Oxycarbide Nuclear Fuel Kernel Jana Howard1,3, Guang Yang3, Haiyan Zhao1*, Patrick Warren4, Tiankai Yao3, Steven Cavazos4 Elizabeth Sooby Wood4*, Ching-heng Shiau2 1 University of Idaho, Environmental Science, Idaho Falls, Idaho, USA 2 Boise State University, Microscopy and Characterization Suite, Idaho Falls, Idaho, USA 3 Idaho National Laboratory, Idaho Falls, Idaho, USA 4 University of Texas San Antonio, Department of Physics and Astronomy, San Antonio, Texas, USA *Corresponding author: haiyanz@uidaho.edu; elizabeth.soobywood@utsa.edu Tri-structural Isotropic (TRISO) particle fuel is the preferred choice for the newest and next-generation high-temperature nuclear reactors due to its robust construction [1]. The fuel design effectively contains fission products inside the particle at extremely high temperatures [2]. However, the effect of transition metal fission products on fuel performance and structural integrity remains largely unknown, creating uncertainties in predicting fuel performance and potential failure mechanisms [2]. For example, palladium (Pd) has a strong tendency to form intermetallic phases with uranium (U). These new phases tend to be hard and brittle which could lead to fracture of fuel kernel during irradiation [3,4]. Pd is not normally produced in high concentrations in normal fission reactions however, driving the production of Pd into the locality of a Uranium Oxycarbide (UCO) nuclear fuel provides an opportunity to closely observe the diffusion and chemical interactions. This study focuses on detailed transmission electron microscopy characterization of the intermetallic phases formed by the interaction between a UCO kernel and a Pd bar after annealing at 1100 °C for 100 hours. Figure 1 provides an overview of the UCO kernel in contact with the Pd bar. The UCO-Pd sample surface was examined using a Focused Ion Beam (FIB) Quanta 3D FEG FEI in VCD detector mode at 10kV, 83pA to reveal surface features. Several key surface features in the interaction region were observed including: (1) a small area with dendritic microstructure, (2) color contrast near the UCO kernel and Pd boundary, and (3) darker and lighter regions throughout the sample surface. To analyze diffusion behavior, FIB was used to prepare lamellae from five different areas of the UCO-Pd sample, as well as one for the as-received sample. These lamellae were examined using a Scanning Transmission Electron Microscope ThermoFisher Spectra 300 (STEM-Spectra). Energy Dispersive Spectroscopy results confirmed the diffusion between the UCO fuel and Pd bar. Figure 2 shows the identified phases of UC, UO2, and Pd dispersed throughout the interaction region. It was also found that the Pd concentration decreases as the radial distance from the UCO-Pd interface increases. The Pd concentration was 36.93% atomic fraction 11µm from the interaction region then decreased to 7.51% atomic fraction at 257 µm away from the interaction region. Figure 3 shows how concentrations of U and Pd vary across the interaction zone, highlighting the extent of diffusion. This study confirms that Pd interacts with surrounding material to form U-Pd phase and diffusion zones. These diffusion zones vary in composition depending on its radial distance from the point of contact with the Pd bar. These findings contribute to a deeper understanding of the fission product behavior in high temperature nuclear fuels, aiding in the prediction and mitigation of potential fuel degradation mechanisms. A B C Fig. 1. SEM micrographs of UCO fuel kernel in contact with solid Pd bar and the lift out locations. Figure 1A shows UCO fuel kernel in contact with solid Pd bar. Figure 1B shows a higher magnification image of the UCO fuel-Pd interaction zone. Figure 1C shows lift out sites for the lamellae. A B C Fig 2. EDS maps reveal the distribution of U, O, and Pd in location 3. Figure 2A shows the distribution of uranium. Figure 2B shows the distribution of oxygen. Figure 2C shows the distribution of palladium. A B C Fig 3. Palladium and uranium concentration across interaction zone in location 2. Figure 3A shows EDS map of lift out number 2. Figure 3B shows a zoomed in EDS map taken from the interaction zone. Figure 3C shows a line graph of uranium and palladium concentrations across the interaction zone. References: 1. B.E. Wells, N.R. Phillips, K.J. Geelhood. Pacific West Laboratory. (2021). TRISO Fuel: Properties and Failure Modes. https://www.nrc.gov/docs/ML2117/ML21175A152.pdf (Accessed January 16, 2025). 2. American Nuclear Society. TRISO Fuel Development Progresses in INL, ORNL. https://www.gen-4.org/gif/upload/docs/application/pdf/2014-03/nov13nn_fuel_reprint.pdf (Accessed January 16, 2025) 3. Clark R.A., M.A. Con

36 - MATERIALS SCIENCE↗

Chemical Interaction of Palladium in Uranium Oxycarbide Nuclear Fuel Kernel

Chemical Interaction of Palladium in Uranium Oxycarbide Nuclear Fuel Kernel Jana Howard1,3, Guang Yang3, Haiyan Zhao1*, Patrick Warren4, Tiankai Yao3, Steven Cavazos4 Elizabeth Sooby Wood4*, Ching-heng Shiau2 1 University of Idaho, Environmental Science, Idaho Falls, Idaho, USA 2 Boise State University, Microscopy and Characterization Suite, Idaho Falls, Idaho, USA 3 Idaho National Laboratory, Idaho Falls, Idaho, USA 4 University of Texas San Antonio, Department of Physics and Astronomy, San Antonio, Texas, USA *Corresponding author: haiyanz@uidaho.edu; elizabeth.soobywood@utsa.edu Tri-structural Isotropic (TRISO) particle fuel is the preferred choice for the newest and next-generation high-temperature nuclear reactors due to its robust construction [1]. The fuel design effectively contains fission products inside the particle at extremely high temperatures [2]. However, the effect of transition metal fission products on fuel performance and structural integrity remains largely unknown, creating uncertainties in predicting fuel performance and potential failure mechanisms [2]. For example, palladium (Pd) has a strong tendency to form intermetallic phases with uranium (U). These new phases tend to be hard and brittle which could lead to fracture of fuel kernel during irradiation [3,4]. Pd is not normally produced in high concentrations in normal fission reactions however, driving the production of Pd into the locality of a Uranium Oxycarbide (UCO) nuclear fuel provides an opportunity to closely observe the diffusion and chemical interactions. This study focuses on detailed transmission electron microscopy characterization of the intermetallic phases formed by the interaction between a UCO kernel and a Pd bar after annealing at 1100 °C for 100 hours. Figure 1 provides an overview of the UCO kernel in contact with the Pd bar. The UCO-Pd sample surface was examined using a Focused Ion Beam (FIB) Quanta 3D FEG FEI in VCD detector mode at 10kV, 83pA to reveal surface features. Several key surface features in the interaction region were observed including: (1) a small area with dendritic microstructure, (2) color contrast near the UCO kernel and Pd boundary, and (3) darker and lighter regions throughout the sample surface. To analyze diffusion behavior, FIB was used to prepare lamellae from five different areas of the UCO-Pd sample, as well as one for the as-received sample. These lamellae were examined using a Scanning Transmission Electron Microscope ThermoFisher Spectra 300 (STEM-Spectra). Energy Dispersive Spectroscopy results confirmed the diffusion between the UCO fuel and Pd bar. Figure 2 shows the identified phases of UC, UO2, and Pd dispersed throughout the interaction region. It was also found that the Pd concentration decreases as the radial distance from the UCO-Pd interface increases. The Pd concentration was 36.93% atomic fraction 11µm from the interaction region then decreased to 7.51% atomic fraction at 257 µm away from the interaction region. Figure 3 shows how concentrations of U and Pd vary across the interaction zone, highlighting the extent of diffusion. This study confirms that Pd interacts with surrounding material to form U-Pd phase and diffusion zones. These diffusion zones vary in composition depending on its radial distance from the point of contact with the Pd bar. These findings contribute to a deeper understanding of the fission product behavior in high temperature nuclear fuels, aiding in the prediction and mitigation of potential fuel degradation mechanisms. A B C Fig. 1. SEM micrographs of UCO fuel kernel in contact with solid Pd bar and the lift out locations. Figure 1A shows UCO fuel kernel in contact with solid Pd bar. Figure 1B shows a higher magnification image of the UCO fuel-Pd interaction zone. Figure 1C shows lift out sites for the lamellae. A B C Fig 2. EDS maps reveal the distribution of U, O, and Pd in location 3. Figure 2A shows the distribution of uranium. Figure 2B shows the distribution of oxygen. Figure 2C shows the distribution of palladium. A B C Fig 3. Palladium and uranium concentration across interaction zone in location 2. Figure 3A shows EDS map of lift out number 2. Figure 3B shows a zoomed in EDS map taken from the interaction zone. Figure 3C shows a line graph of uranium and palladium concentrations across the interaction zone. References: 1. B.E. Wells, N.R. Phillips, K.J. Geelhood. Pacific West Laboratory. (2021). TRISO Fuel: Properties and Failure Modes. https://www.nrc.gov/docs/ML2117/ML21175A152.pdf (Accessed January 16, 2025). 2. American Nuclear Society. TRISO Fuel Development Progresses in INL, ORNL. https://www.gen-4.org/gif/upload/docs/application/pdf/2014-03/nov13nn_fuel_reprint.pdf (Accessed January 16, 2025) 3. Clark R.A., M.A. Con

36 - MATERIALS SCIENCE↗

Enabling probabilistic learning on manifolds through double diffusion maps

Here, we present a generative learning framework for probabilistic sampling that extends Probabilistic Learning on Manifolds (PLoM), which is designed to generate statistically consistent realizations of a random vector in a finite-dimensional Euclidean space, informed by a (representative) set of observations. In its original form, PLoM constructs a reduced-order probabilistic model by combining three main components: (a) kernel density estimation to approximate the underlying probability measure, (b) Diffusion Maps to characterize the manifold of the data, and (c) a reduced-order Itô Stochastic Differential Equation (ISDE) to sample from the learned distribution. However, its sampling dynamics are posed in the ambient space and the retained number of reduced coordinates is chosen by projection-reconstruction error. In practice, this often (i) requires more coordinates than the data’s intrinsic dimension to achieve stable sampling and (ii) lacks a smooth, basis-independent lifting back to the data domain; moreover, standard Diffusion Maps emphasize harmonic eigenfunctions and can miss non-harmonic latent structure. We address these limitations by decoupling geometry learning from sampling: a first Diffusion Maps pass identifies non-harmonic coordinates on which we formulate a full-order ISDE directly in the latent space, while Double Diffusion Maps captures multiscale geometric features and Geometric Harmonics (GH) learns a smooth lifting map to the ambient variables that is independent of the particular diffusion basis. This hybrid design preserves the system’s dynamical richness with a compact geometric representation and enables principled out-of-sample inference. The effectiveness and robustness of the proposed method are illustrated through two numerical studies: one based on data generated from two-dimensional Hermite polynomial functions and another based on high-fidelity simulations of a detonation wave in a reactive flow.

Double diffusion maps↗

Influence of Buoyant Convection on the Stability of Enclosed Laminar Flames

An investigation of the stability limits of Enclosed Laminar Flames (ELF) was conducted in the Middeck Glovebox (MGBX) facility on the STS-87 Space Shuttle mission (November to December 1997). The primary objective of the ELF glovebox investigation is to determine the effect of buoyancy on the stability of round, laminar, gas-jet diffusion flames in a co-flow air duct. Comparison tests were conducted in normal gravity to allow isolation and identification of the influence of buoyancy. The results were used to map the lift-off and blow-out stability limits as a function of the fuel and air velocities for the two buoyancy conditions. Approximately 50 tests were conducted during the Space Shuttle mission, using a 50/50 mixture (volume basis) of methane and nitrogen as the fuel. The experimental results verified the hypothesis that substantially greater velocities are required to destabilize the flame in microgravity. The increase in air velocity required to induce lift off in microgravity (compared to normal gravity) was nearly equal to the increase required to induce blow out. Furthermore, the air velocity increase was relatively independent of the fuel flow, except at low fuel flows. At high fuel flows, it was found that the microgravity flames tend to immediately blow out after lift off. This is in agreement with the free-jet theory which suggests that stable lifted flames are not possible for fuels with a Schmidt number of 0.5<Sc<l, such as the diluted methane used in this study. However, stable lifted flames were observed in microgravity at low fuel flows, and in normal gravity, despite the fuel's low Schmidt number. The discrepancy between the experimental data and the theory of Chung and Lee is presumably due to the differences in the flow condition; namely, the ducted flow versus a free jet, and a non-similar velocity profile versus a self-similar profile.

Brooker, John E.↗

Control law system for X-Wing aircraft

Control law system for the collective axis, as well as pitch and roll axes, of an X-Wing aircraft and for the pneumatic valving controlling circulation control blowing for the rotor. As to the collective axis, the system gives the pilot single-lever direct lift control and insures that maximum cyclic blowing control power is available in transition. Angle-of-attach de-coupling is provided in rotary wing flight, and mechanical collective is used to augment pneumatic roll control when appropriate. Automatic gain variations with airspeed and rotor speed are provided, so a unitary set of control laws works in all three X-Wing flight modes. As to pitch and roll axes, the system produces essentially the same aircraft response regardless of flight mode or condition. Undesirable cross-couplings are compensated for in a manner unnoticeable to the pilot without requiring pilot action, as flight mode or condition is changed. A hub moment feedback scheme is implemented, utilizing a P+I controller, significantly improving bandwidth. Limits protect aircraft structure from inadvertent damage. As to pneumatic valving, the system automatically provides the pressure required at each valve azimuth location, as dictated by collective, cyclic and higher harmonic blowing commands. Variations in the required control phase angle are automatically introduced, and variations in plenum pressure are compensated for. The required switching for leading, trailing and dual edge blowing is automated, using a simple table look-up procedure. Non-linearities due to valve characteristics of circulation control lift are linearized by map look-ups.

Lawrence, Thomas H.↗

Multi-level optimization with the koopman operator for data-driven, domain-aware, and dynamic system security

Cyber-Physical Systems (CPSs) like the power grid are critically important but also increasingly vulnerable; ensuring reliable system operation in the face of disruptions is becoming more and more challenging. Multi-Level Optimization (MLO) is a powerful way to model adversarial interactions, which naturally makes it applicable to studying CPS security. However, MLO typically does not address underlying system dynamics, and incorporating nonlinear dynamics is generally infeasible. In this paper, we show how to combine MLO with the Koopman Operator (KO) to remedy this. The KO maps nonlinear dynamics to a lifted space in which those dynamics are linear, thus making it ideal for use with MLO. Moreover, the structure of the KO also provides convenient ways to incorporate domain knowledge into the data-driven process of learning the KO representation of a given system. Here we then demonstrate the use of MLO-KO on a small example problem taken from the power grid domain, discuss the scalability and computational cost of MLO-KO, and identify future research directions for this work.

42 ENGINEERING↗

Patterns of vortex shedding from an oscillating circular cylinder

Vortex shedding from an oscillating circular cylinder was numerically investigated at Re = 100 with the Navier-Stokes equations and the new boundary conditions. The detailed shedding patterns are characterized by means of streakline plotting and lift-coefficient curves. A parameter map is presented which distinguishes the synchronized shedding from the asynchronous and the double vortices shedding from the single vortex shedding. The computational result is in good agreement with earlier experimental results.

Chang, Keun-Shik↗

Lift on a bent, flat plate

The lift on a bent, flat plate is calculated exactly by the use of conformal mapping. Results are presented in terms permitting direct determination of the angle of zero lift, the lift coefficient, and the lift-curve slope for any flap-chord ratio, flap-deflection angle, and angle of attack.

WING FLAPS - DEFLECTION↗

Investigation of Aerodynamic Matching Sensitivities for Conceptual Design

A methodology for aerodynamic matching was implemented in the Higher fidelity Conceptual Design and structural optimization (HCDstruct) tool to support transonic flutter simulations. The Enhanced Factor Correction Technique was implemented in HCDstruct to correct the Nastran doublet lattice method using data from corresponding computational fluid dynamics simulations. In this paper, sensitivities associated with this aerodynamic matching technique were investigated using HCDstruct and a Boeing 737-200-like aircraft configuration. Specifically, sensitivities of the aerodynamic matching method were investigated with respect to changes in flight conditions, such as changes in Mach number and angle of attack, and also in key design variables for the main wing, such as changes in aspect ratio and sweep angle. The variations in flight conditions and design parameters were mapped to estimated prediction error in sectional lift for the main wing, which helps to demonstrate the extent to which a user may expect a given aerodynamic correction matrix to provide suitable aerodynamic predictions for a realistic aircraft wing.

Jesse R. Quinlan↗

Investigation of Aerodynamic Matching Sensitivities for Conceptual Design

A methodology for aerodynamic matching was implemented in the Higher fidelity Conceptual Design and structural optimization (HCDstruct) tool to support transonic flutter simulations. The Enhanced Factor Correction Technique was implemented in HCDstruct to correct the Nastran doublet lattice method using data from corresponding computational fluid dynamics simulations. In this paper, sensitivities associated with this aerodynamic matching technique were investigated using HCDstruct and a Boeing 737-200-like aircraft configuration. Specifically, sensitivities of the aerodynamic matching method were investigated with respect to changes in flight conditions, such as changes in Mach number and angle of attack, and also in key design variables for the main wing, such as changes in aspect ratio and sweep angle. The variations in flight conditions and design parameters were mapped to estimated prediction error in sectional lift for the main wing, which helps to demonstrate the extent to which a user may expect a given aerodynamic correction matrix to provide suitable aerodynamic predictions for a realistic aircraft wing.

Jesse Ray Quinlan↗

Aeroacoustic Study of a Subscale Large Civil Transport (STAR) Model – Part 2: Validation of Simulated Results

Aeroacoustic measurements of the 26%-scale, semispan Boeing 777-200 Subsonic Transport Aeroacoustic Research (STAR) model tested in the NASA Ames Research Center 40- by 80-foot wind tunnel were used to ascertain the efficacy of high-fidelity simulations to accurately predict noise from the landing gear of large commercial transports. The simulations, conducted with the lattice Boltzmann solver PowerFLOW®, used a digital replica of the STAR model with or without main landing gear deployed and slats and flaps set to their highest deflection angles to represent aircraft during landing. The computations were performed at a Mach number of 0.21, Reynolds number of 8.2 million based on the model mean aerodynamic chord, and other conditions prevalent during the STAR model test. Measured and computed surface pressures were in very good agreement at most port locations on the model, as were global force coefficients, indicating that the simulations captured the impact of main gear deployment on inboard flap loading. Noise sources produced by the main landing gear and high-lift devices were determined via source localization maps generated with CLEAN from synthetic and experimental data. In general, very good agreement between predicted and measured acoustic source location and relative strength was observed in the maps. Comparisons of far-field noise spectra obtained from the CLEAN deconvolution maps showed remarkable agreement between synthetic and experimental broadband noise at low and medium frequencies. Main landing gear sources for model-scale frequencies above 7,000 Hz could not be resolved with the spatial resolution used during the simulations.

airframe noise↗

Evidence of lithium mobility under neutron irradiation

Understanding the evolution of intermetallic materials in high-radiation environments is of great importance for fusion science and national security. Tritium ( 3 H) and lithium ( 6 Li, 7 Li) transport within neutron irradiated claddings coated with aluminide (FeAl3) has been investigated using state-of-the-art multimodal imaging. Specifically, scanning electron microscopy – focused ion beam (SEM-FIB) was used to prepare irradiated coating lift-out samples for follow-on microanalysis. Here, scanning transmission electron microscopy (STEM) was used to acquire atomic-scale information on the carbonaceous structure and elemental mapping. Atomic force microscopy (AFM) was used to determine lift-out dimensions nondestructively. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) spectral and depth profiling show unexpected lithium isotopic distributions in the irradiated cladding, raising an important evidence of possible light isotope mobility within the cladding under elevated temperature and irradiation. ToF-SIMS three-dimensional chemical mappings of mid- and bottom-cladding coatings show light isotopic (e.g., 3 H, 6 Li, 7 Li) distributions in the irradiated coating and give new insights into the fundamental mechanism related to transport mechanisms within the cladding. Multimodal imaging is power to link microstructure, chemistry, and nanoscale defects that impact reliability of these materials. Furthermore, chemical mapping offers observations of the microstructural evolution due to irradiation and provides insights into unexpected material transport under extreme conditions.

36 MATERIALS SCIENCE↗

AI‐Driven Robot Enables Synthesis‐Property Relation Prediction for Metal Halide Perovskites in Humid Atmosphere

Materials Acceleration Platforms (MAPs) – also known as self-driving laboratories– present a new paradigm for materials science and promise an order of magnitude accelerated materials discovery compared to the traditional trial-and-error approach. Metal halide perovskites (MHPs) are an emerging class of materials for optoelectronic applications but are plagued by irreproducible optoelectronic quality, particularly for films fabricated in a humid atmosphere. Here, in this work, a machine learning (ML)-guided closed-loop platform is developed with a multimodal data fusion approach to predict synthesis–property relations for the optical quality of MHP thin films in relative humidities (RHs) ranging from 5–55%. The efficiency of this approach is confirmed by the fast-dropping learning rate to 2% after experimentally sampling less than 1% of the possible 5,000+ combinations. The prediction of synthesis–property relations is done by optical and imaging characterizations. In situ photoluminescence characterization revealed the origin of thin film quality variation at different RH. These insights provide an avenue for controlling the MHP crystallization by fine-tuning the synthesis parameters and RH for a given chemistry, thus lifting the need for stringent atmosphere control. The MAP enables an accelerated screening and understanding of the synthesis design space, facilitating rational synthesis recipe choice for a wide range of materials.

AI-driven robot↗

Spin-orbit enabled quantum transport channels in a two-hole double quantum dot

We analyze experimentally and theoretically the transport spectra of a gated lateral GaAs double quantum dot containing two holes. The strong spin-orbit interaction present in the hole subband lifts the Pauli spin blockade and allows to map out the complete spectra of the two-hole system. By performing measurements in both source-drain voltage directions, at different detunings and magnetic fields, we carry out quantitative fitting to a Hubbard two-site model accounting for the tunnel coupling to the leads and the spin-flip relaxation process. We extract the singlet-triplet gap and the magnetic field corresponding to the singlet-triplet transition in the double-hole ground state. Additionally, at the singlet-triplet transition we find a resonant enhancement (in the blockaded direction) and suppression of current (in the conduction direction). The current enhancement stems from the multiple resonance of two-hole levels, opening several conduction channels at once. The current suppression arises from the quantum interference of spin-conserving and spin-flipping tunneling processes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Design of high lift airfoils with a Stratford distribution by the Eppler method

Airfoils having a Stratford pressure distribution, which has zero skin friction in the pressure recovery area, were investigated in an effort to develop high lift airfoils. The Eppler program, an inverse conformal mapping technique where the x and y coordinates of the airfoil are developed from a given velocity distribution, was used.

Thomson, W. G.↗