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At least 1,117 records · Page 62

Aeroelastic Analysis of a Flexible Wing Wind Tunnel Model with Variable Camber Continuous Trailing Edge Flap Design

This paper presents data analysis of a flexible wing wind tunnel model with a variable camber continuous trailing edge flap (VCCTEF) design for drag minimization tested at the University of Washington Aeronautical Laboratory (UWAL). The wind tunnel test was designed to explore the relative merit of the VCCTEF concept for improved cruise efficiency through the use of low-cost aeroelastic model test techniques. The flexible wing model is a 10%-scale model of a typical transport wing and is constructed of woven fabric composites and foam core. The wing structural stiffness in bending is tailored to be half of the stiffness of a Boeing 757-era transport wing while the torsional stiffness is about the same. This stiffness reduction results in a wing tip deflection of about 10% of the wing semi-span. The VCCTEF is a multi-segment flap design having three chordwise camber segments and five spanwise flap sections for a total of 15 individual flap elements. The three chordwise camber segments can be positioned appropriately to create a desired trailing edge camber. Elastomeric material is used to cover the gaps in between the spanwise flap sections, thereby creating a continuous trailing edge. Wind tunnel data analysis conducted previously shows that the VCCTEF can achieve a drag reduction of up to 6.31% and an improvement in the lift-to-drag ratio (L=D) of up to 4.85%. A method for estimating the bending and torsional stiffnesses of the flexible wingUWAL wind tunnel model from static load test data is presented. The resulting estimation indicates that the stiffness of the flexible wing is significantly stiffer in torsion than in bending by as much as 9 to 1. The lift prediction for the flexible wing is computed by a coupled aerodynamic-structural model. The coupled model is developed by coupling a conceptual aerodynamic tool Vorlax with a finite-element model of the flexible wing via an automated geometry deformation tool. Based on the comparison of the lift curve slope, the lift prediction for the rigid wing is in good agreement with the estimated lift coefficients derived from the wind tunnel test data. Due to the movement of the VCCTEF during the wind tunnel test, uncertainty in the lift prediction due to the indicated variations of the VCCTEF deflection is studied. The results show a significant spread in the lift prediction which contradicts the consistency in the aerodynamic measurements, thus suggesting that the indicated variations as measured by the VICON system may not be reliable. The lift prediction of the flexible wing agrees very well with the measured lift curve for the baseline configuration. The computed bending deflection and wash-out twist of the flexible wing also match reasonably well with the aeroelastic deflection measurements. The results demonstrate the validity of the aerodynamic-structural tool for use to analyze aerodynamic performance of flexible wings.

Wind Tunnel↗

Toward quantum Monte Carlo forces on heavier ions: Scaling properties

Quantum Monte Carlo (QMC) forces have been studied extensively in recent decades because of their importance with spectroscopic observables and geometry optimization. Here, we benchmark the accuracy and computational cost of QMC forces. The zero-variance zero-bias (ZVZB) force estimator is used in standard variational and diffusion Monte Carlo simulations with mean-field based trial wavefunctions and atomic pseudopotentials. Statistical force uncertainties are obtained with a recently developed regression technique for heavy tailed QMC data [P. Lopez Rios and G. J. Conduit, Phys. Rev. E 99, 063312 (2019)]. By considering selected atoms and dimers with elements ranging from H to Zn (1 ≤ Z eff ≤ 20), we assess the accuracy and the computational cost of ZVZB forces as the effective pseudopotential valence charge, Z eff , increases. We find that the costs of QMC energies and forces approximately follow simple power laws in Zeff. The force uncertainty grows more rapidly, leading to a best case cost scaling relationship of approximately Z e ff 6.5 ( 3 ) for diffusion Monte Carlo. We find that the accessible system size at fixed computational cost scales as Z e ff − 2 , insensitive to model assumptions or the use of the “space warp” variance-reduction technique. Our results predict the practical cost of obtaining forces for a range of materials, such as transition metal oxides where QMC forces have yet to be applied, and underscore the importance of further developing force variance-reduction techniques, particularly for atoms with high Z eff .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Incremental k-core decomposition: Algorithms and evaluation

A k-core of a graph is a maximal connected subgraph in which every vertex is connected to at least k vertices in the subgraph. k-core decomposition is often used in large-scale network analysis, such as community detection, protein function prediction, visualization, and solving NP-hard problems on real networks efficiently, like maximal clique finding. In many real-world applications, networks change over time. As a result, it is essential to develop efficient incremental algorithms for dynamic graph data. In this paper, we propose a suite of incremental k-core decomposition algorithms for dynamic graph data. These algorithms locate a small subgraph that is guaranteed to contain the list of vertices whose maximum k-core values have changed and efficiently process this subgraph to update the k-core decomposition. We present incremental algorithms for both insertion and deletion operations, and propose auxiliary vertex state maintenance techniques that can further accelerate these operations. Our results show a significant reduction in runtime compared to non-incremental alternatives. We illustrate the efficiency of our algorithms on different types of real and synthetic graphs, at varying scales. Furthermore, for a graph of 16 million vertices, we observe relative throughputs reaching a million times, relative to the non-incremental algorithms.

97 MATHEMATICS AND COMPUTING↗

Predicting Local Material Thickness from Steady-State Ultrasonic Wavefield Measurements Using a Convolutional Neural Network

Acoustic steady-state excitation spatial spectroscopy (ASSESS) is a full-field, ultrasonic non-destructive evaluation (NDE) technique used to locate and characterize defects in plate-like structures. ASSESS generates a steady-state, single-tone ultrasonic excitation in a structure and a scanning laser Doppler Vibrometer (LDV) measures the resulting full-field surface velocity response. Traditional processing techniques for ASSESS data rely on wavenumber domain analysis. This paper presents the alternative use of a convolutional neural network (CNN), trained using simulated ASSESS data, to predict the local plate thickness at every pixel in the wavefield measurement directly. The defect detection accuracy of CNN-based thickness predictions are shown to improve for defects of greater size, and for defects with higher thickness reductions. The CNN demonstrates the ability to predict thickness accurately in regions where Lamb wave dispersion relations are complex or unknown, such as near the boundaries of a test specimen, so long as the CNN is trained on data that accounts for these regions. The CNN also shows generalizability to ASSESS experimental data, despite an entirely simulated training dataset.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SPECTROSCOPIC SUBSYSTEMS IN NEARBY WIDE BINARIES

Radial velocity (RV) monitoring of solar-type visual binaries has been conducted at the CTIO/SMARTS 1.5 m telescope to study short-period systems. The data reduction is described, and mean and individual RVs of 163 observed objects are given. New spectroscopic binaries are discovered or suspected in 17 objects, and for some of them the orbital periods could be determined. Subsystems are efficiently detected even in a single observation by double lines and/or by the RV difference between the components of visual binaries. The potential of this detection technique is quantified by simulation and used for statistical assessment of 96 wide binaries within 67 pc. It is found that 43 binaries contain at least one subsystem, and the occurrence of subsystems is equally probable in either primary or secondary components. The frequency of subsystems and their periods matches the simple prescription proposed by the author. The remaining 53 simple wide binaries with a median projected separation of 1300 AU have an RV difference distribution between their components that is not compatible with the thermal eccentricity distribution f (e) = 2e but rather matches the uniform eccentricity distribution.

79 ASTRONOMY AND ASTROPHYSICS↗

TH-CD-207A-04: Optimized Respiratory Gating for Abnormal Breathers in Pancreatic SBRT

Purpose: Pancreatic SBRT is uniquely challenging due to both the erratic/unstable motion of the pancreas and the close proximity of the radiosensitive small bowel. Respiratory gating can mitigate this effect, but the irregularity of motion severely affects traditional phase-based gating. The purpose of this study was to analyze real-time motion data of pancreatic tumors to optimize the efficacy and accuracy of respiratory gating, with the overall goal of enabling dose escalated pancreatic SBRT. Methods: Fifteen pancreatic SBRT patients received 30–33 Gy in 5 fractions on a Varian TrueBeam STx unit. Abdominal compression was used to reduce the amplitude of tumor motion, and daily cone-beam computed tomography (CBCT) scans were acquired prior to each treatment for target localization purposes. For this study, breathing data (phase and amplitude) were collected during each CBCT scan using Varian’s Real-Time Position Management system. An in-house template matching technique was used to track the superior-inferior motion of implanted fiducial markers in CBCT projection images. Using tumor motion and breathing data, phase-based or amplitude-based respiratory gating was simulated for all 75 fractions, targeting either end-exhalation or end-inhalation phases of breathing. Results: For the average patient, gating at end-exhalation offered the best reductions in effective motion for equal duty cycles. However, optimal central phase angle varied widely (range: 0–92%, mean±SD: 49±12%), and phase-based gating windows typically associated with end-exhalation (i.e., “30–70%”) were rarely ideal. Amplitude-based gating significantly outperformed phase-based gating, with average effective ranges for amplitude-based gating 25% lower than phase-based gating ranges (as much as 73% lower). Amplitude-based gating was consistently better suited to accommodate abnormal breathing patterns. For both phase-based and amplitude-based gating, end-exhalation provided significantly better results than end-inhalation. Conclusion: Amplitude-based gating reliably outperformed phase-based gating, and end-exhalation was more suitable than end-inhalation. These results will be used to guide future dose-escalation trials. Research funding provided by Varian Medical Systems to Miften and Jones.

60 APPLIED LIFE SCIENCES↗

A Hybrid Reduced-Order Model of Fine-Resolution Hydrologic Simulations at a Polygonal Tundra Site

High-resolution predictions of land surface hydrological dynamics are desirable for improved investigations of regional- and watershed-scale processes. Direct deterministic simulations of fine-resolution land surface variables present many challenges, including high computational cost. We therefore propose the use of reduced-order modeling techniques to facilitate emulation of fine-resolution simulations. We use an emulator, Gaussian process regression, to approximate fine-resolution four-dimensional soil moisture fields predicted using a three-dimensional surface-subsurface hydrological simulator (PFLOTRAN). A dimension-reduction technique known as “proper orthogonal decomposition” is further used to improve the efficiency of the resulting reduced-order model (ROM). The ROM reduces simulation computational demand to negligible levels compared to the underlying fine-resolution model. In addition, the ROM that we constructed is equipped with an uncertainty estimate, allowing modelers to construct a ROM consistent with uncertainty in the measured data. The ROM is also capable of constructing statistically equivalent analogs that can be used in uncertainty and sensitivity analyses. We apply the technique to four polygonal tundra sites near Barrow, Alaska that are part of the Department of Energy’s Next-Generation Ecosystem Experiments (NGEE)-Arctic project. The ROM is trained for each site using simulated soil moisture from 1998-2000 and validated using the simulated data for 2002 and 2006. The average relative RMSEs of the ROMs are under 1%.

58 GEOSCIENCES↗

Experimental modal analysis of the fuselage panels of an Aero Commander aircraft

The reduction of interior noise in light aircraft was investigated with emphasis the thin fuselage sidewall. The approach used is theoretical and involves modeling of the sidewall panels and stiffeners. Experimental data obtained from tests investigating the effects of mass and stiffness treatments to the sidewalls are presented. The dynamic characteristics of treated panels are contrasted with the untreated sidewall panels using experimental modal analysis techniques. The results include the natural frequencies, modal dampling, and mode shapes of selected panels. Frequency response functions, data relating to the global fuselage response, and acoustic response are also presented.

Geisler, D.↗

Some comments on particle image displacement velocimetry

Laser speckle velocimetry (LSV) or particle image displacement velocimetry, is introduced. This technique provides the simultaneous visualization of the two-dimensional streamline pattern in unsteady flows as well as the quantification of the velocity field over an entire plane. The advantage of this technique is that the velocity field can be measured over an entire plane of the flow field simultaneously, with accuracy and spatial resolution. From this the instantaneous vorticity field can be easily obtained. This constitutes a great asset for the study of a variety of flows that evolve stochastically in both space and time. The basic concept of LSV; methods of data acquisition and reduction, examples of its use, and parameters that affect its utilization are described.

Lourenco, L. M.↗

Recent improvements in Geosat altimeter data

Techniques are described for enhancing the accuracy of the geophysical data records derived from Geosat altimeter observations with treatments for water-vapor correction and satellite orbit. The TOVS/Special Sensor Microwave Imager (SSMI) water vapor data and T2 ephemeris are used to effectively adjust tide-gauge records. The T2 orbit is found to be effective for the study of large-scale phenomena with reductions in the radial orbit error.

Cheney, Robert E.↗

Control of unsteady separated flow associated with the dynamic stall of airfoils

An effort to understand and control the unsteady separated flow associated with the dynamic stall of airfoils was funded for three years through the NASA cooperative agreement program. As part of this effort a substantial data base was compiled detailing the effects various parameters have on the development of the dynamic stall flow field. Parameters studied include Mach number, pitch rate, and pitch history, as well as Reynolds number (through two different model chord lengths) and the condition of the boundary layer at the leading edge of the airfoil (through application of surface roughness). It was found for free stream Mach numbers as low as 0.4 that a region of supersonic flow forms on the leading edge of the suction surface of the airfoil at moderate angles of attack. The shocks which form in this supersonic region induce boundary-layer separation and advance the dynamic stall process. Under such conditions a supercritical airfoil profile is called for to produce a flow field having a weaker leading-edge pressure gradient and no leading-edge shocks. An airfoil having an adaptive-geometry, or dynamically deformable leading edge (DDLE), is under development as a unique active flow-control device. The DDLE, formed of carbon-fiber composite and fiberglass, can be flexed between a NACA 0012 profile and a supercritical profile in a controllable fashion while the airfoil is executing an angle-of-attack pitch-up maneuver. The dynamic stall data were recorded using point diffraction interferometry (PDI), a noninvasive measurement technique. A new high-speed cinematography system was developed for recording interferometric images. The system is capable of phase-locking with the pitching airfoil motion for real-time documentation of the development of the dynamic stall flow field. Computer-aided image analysis algorithms were developed for fast and accurate reduction of the images, improving interpretation of the results.

Wilder, M. C.↗

Extension of mutation testing for the requirements and design faults - 322

Mutation Testing is a fault-based software testing technique that is considered to be the most efficient in detecting faults. It focuses on the software code level and follows a set of rules which are called mutation operators to systematically seed faults into the source code. Each seeded fault results is a new version of the software, which is called a mutant. Mutation testing promises to be effective in identifying adequate test data which can be used to find faults in the source code. However, traditional mutation testing is not geared towards the detection of requirements and design faults. To cover the full spectrum of possible faults, the mutation framework has been extended from the code level to the requirements and design level. Twenty-nine defects that appear in requirements and design documents were identified to define appropriate mutants. Then corresponding mutation operators that model the defects were developed. For each mutation operator, the strategy to generate a mutant and the evaluation of the number of possible mutants were defined. Existing code level cost reduction techniques were tailored for requirements and design mutation operators that result in a large number of mutants. With the extended mutation testing framework, the full spectrum of possible faults will be tested and identified to ensure the safety and functionality of the software. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Acceleration and Stabilization of Electron Transfer Products with Improved Quantum Yields upon Cation Binding to a Fused Bis-Zinc Porphyrin-Quinone Donor–Acceptor Conjugate

The role of metal ions in promoting electron transfer processes in biological coenzymes is of great significance not only to understand their mechanistic details but also due to their direct utilization in a number of chemical and biochemical processes. Here, we demonstrate an increased rate of forward electron transfer with improved reaction quantum yield, and an enhanced lifetime of electron transfer products upon cation binding to the acceptor entity in a donor-acceptor conjugate. Selective binding of cations such as Mg 2+ or Sc 3+ to the electron acceptor, quinone, in a fused, bis-zinc porphyrin-quinone donor-acceptor conjugate leads to facile reduction of the quinone making the electron transfer process thermodynamically highly feasible. Furthermore, the binding of metal ions to the electron transfer product, quinone anion, decelerates the reverse electron transfer process due to ion-pairing interactions, resulting in improving both the lifetime and quantum yields of the electron transfer products. Furthermore, systematic studies including spectral, electrochemical, computational, spectroelectrochemical, and transient absorption techniques, coupled with data analysis by Global Target Analysis (GloTarAn), are performed to demonstrate these novel findings that are relevant to further our understanding of electron transfer processes occurring in biological coenzymes and pertinent energy harvesting schemes.

Charge transfer↗

Leveraging unlabeled SEM datasets with self-supervised learning for enhanced particle segmentation

Scanning Electron Microscopes (SEMs) are widely used in experimental science laboratories, often requiring cumbersome and repetitive user analysis. Automating SEM image analysis processes is highly desirable to address this challenge. In particle sample analysis, Machine Learning (ML) has emerged as the most effective approach for particle segmentation. However, the time-intensive process of manually annotating thousands of SEM images limits the applicability of supervised learning approaches. Self-Supervised Learning (SSL) offers a promising alternative by enabling knowledge extraction from raw, unlabeled data. This study presents a framework for evaluating SSL techniques in SEM image analysis, focusing on novel methods leveraging the ConvNeXtV2 architecture for particle detection. A dataset comprising 25,000 SEM images is curated to benchmark these proposed SSL methods. The results demonstrate that ConvNeXtV2 models, with varying parameter counts, consistently outperform other techniques in particle detection across different length scales, achieving up to a 34% reduction in relative error compared to established SSL methods. Furthermore, an ablation study explores the relationship between dataset size and SSL performance, providing actionable insights for practitioners regarding model selection and resource efficiency. This research advances the integration of SSL into autonomous analysis pipelines and supports its application in accelerating materials science discovery.

Rettenberger, Luca↗

Origin and mitigation of wind noise on balloon-borne infrasound microbarometers

High-altitude monitoring of low-frequency acoustic waves (infrasound) on Earth has regained prominence in recent years, primarily driven by improvements in light-weight sensor technology and advances in scientific ballooning techniques. Balloon-borne infrasound monitoring is also being proposed as a remote sensing technique for planetary exploration. Contrary to ground-based infrasound monitoring, the infrasound noise background in the stratosphere as measured by a balloon remains uncharacterized and the efficacy of wind noise mitigation filters has not been investigated. In this study, an analysis of pressure data collected using infrasound microbarometers during the flight of a long-duration zero pressure balloon is presented. Here, a dramatic reduction of background noise in the stratosphere is demonstrated and it is shown that wind noise mitigation filters are not effective at reducing wind noise under these conditions. Results from this study demonstrate stratospheric balloons as a low-noise platform for infrasound monitoring and motivate the development of improved noise mitigation tools.

47 OTHER INSTRUMENTATION↗

Applying artificial intelligence to astronomical databases - A survey of applicable technology

AI technologies which are relevant to astronomical data bases are reviewed, including intelligent interfaces, internal representations, and data analysis. The natural language query system developed for the Hubble Space Telescope and the technique of goal directed queries are considered. Two technologies which might lead to the development of pictorial interfaces are presented: one based on Bayesian probabilities, the other on associative memories. The development of a data analysis system which can discover classes of data within a data base without any information other than the data itself is examined. A prototype data analysis assistant to automatically develop and implement plans for data reduction is described.

Rosenthal, Donald A.↗

Efficient development and processing of thermal math models of very large space truss structures

As the spacecraft moves along the orbit, the truss members are subjected to direct and reflected solar, albedo and planetary infra-red (IR) heating rates, as well as IR heating and shadowing from other spacecraft components. This is a transient process with continuously changing heating loads and the shadowing effects. The resulting nonuniform temperature distribution may cause nonuniform thermal expansion, deflection and stress in the truss elements, truss warping and thermal distortions. There are three challenges in the thermal-structural analysis of the large truss structures. The first is the development of the thermal and structural math models, the second - model processing, and the third - the data transfer between the models. All three tasks require considerable time and computer resources to be done because of a very large number of components involved. To address these challenges a series of techniques of automated thermal math modeling and efficient processing of very large space truss structures were developed. In the process the finite element and finite difference methods are interfaced. A very substantial reduction of the quantity of computations was achieved while assuring a desired accuracy of the results. The techniques are illustrated on the thermal analysis of a segment of the Space Station main truss.

Warren, Andrew H.↗