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At least 1,711 records · Page 95

Modeling of Sound Transmission through Shell Structures with Turbulent Boundary Layer Excitation

The turbulent boundary layer (TBL) pressure field is an important source of cabin noise during cruise of high subsonic and supersonic commercial aircraft. The broadband character of this excitation field results in an interior noise spectrum that dominates the overall sound pressure level (SPL) and speech interference metrics in the forward and midcabins of many aircraft. In the authors' previous study, sound transmission through an aircraft fuselage, modeled by two concentric cylindrical sandwich shells and excited by a TBL statistical model was investigated analytically. An assessment of point and global structural vibration levels and resulting interior noise levels was obtained for different TBL models, flight conditions and fuselage structural designs. However, due to the complication of the shell structure, the important noise transmission mechanisms were difficult to discern. Previous experience has demonstrated that a fundamental understanding of the range of modes (or wavenumbers) generated by the TBL source both in the structure and the acoustic cavity is key to the development of both active and passive control technologies. In an initial effort to provide this insight, the objective of this paper is to develop an analytical model of sound transmission through a simple unstiffened cylindrical aluminum shell excited by a TBL pressure field. The description of the turbulent pressure field is based on the Corcos formulation for the cross-spectral density (CSD) of the pressure fluctuations. The coupled shell and interior and exterior acoustic equations are solved for the structural displacement and the interior acoustic response using a Galerkin approach to obtain analytical solutions. Specifically, this study compares the real part of the normalized CSD of the TBL excitation field, the structural displacement and the interior acoustic field. Further the modal compositions of the structural and cavity response are examined and some inference of the dominant mechanism of noise transmission is made.

Tang, Yvette Y.↗

First-Principles Modeling of IAT-Driven Anomalous Resistivity in Hollow Cathode Discharges I: Theory

Self-consistent expressions are derived for the impact of ion acoustic turbulence (IAT) on the fluid properties of electrons and ions in the plume of a hollow cathode. This instability is believed to have a dominant role in the plasmadynamics in this region. The random phase approximation is applied to the perturbed Boltzmann equation to determine the effective drag and heating of the plasma species induced by the IAT. These driving terms are then incorporated into momentum and energy fluid equations for the ions and electrons. A fluid-like relation governing the evolution of the total IAT wave energy density is also presented. The physical significance of the IAT-based terms is discussed in the context of energy and momentum conservation, and a path forward is outlined for implementing the effects of IAT in the fluid-based model in Part II.

Jorns, Benjamin A.↗

Machine learning the spectral function of a hole in a quantum antiferromagnet

Understanding charge motion in a background of interacting quantum spins is a fundamental problem in quantum many-body physics. The most extensively studied model for this problem is the so-called t-t'-t''-J model, where the determination of the parameter t' in the context of cuprate superconductors is challenging. Here we present a theoretical study of the spectral functions of a mobile hole in the t-t'-t''-J model using two machine-learning techniques: K-nearest neighbor regression (KNN) and a feed-forward neural network (FFNN). We employ the self-consistent Born approximation to generate a dataset of about 1.3 x 10 5 spectral functions. Here we show that, for the forward problem, both methods allow for the accurate and efficient prediction of spectral functions, allowing, e.g., rapid searches through parameter space. Furthermore, we find that for the inverse problem (inferring Hamiltonian parameters from spectra), the FFNN can, but the KNN cannot, accurately predict the model parameters using merely the density of states. Our results suggest that it may be possible to use deep-learning methods to predict materials parameters from experimentally measured spectral functions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Power Management and Distribution (PMAD) Model Development: Final Report

Power management and distribution (PMAD) models were developed in the early 1990's to model candidate architectures for various Space Exploration Initiative (SEI) missions. They were used to generate "ballpark" component mass estimates to support conceptual PMAD system design studies. The initial set of models was provided to NASA Lewis Research Center (since renamed Glenn Research Center) in 1992. They were developed to estimate the characteristics of power conditioning components predicted to be available in the 2005 timeframe. Early 90's component and device designs and material technologies were projected forward to the 2005 timeframe, and algorithms reflecting those design and material improvements were incorporated into the models to generate mass, volume, and efficiency estimates for circa 2005 components. The models are about ten years old now and NASA GRC requested a review of them to determine if they should be updated to bring them into agreement with current performance projections or to incorporate unforeseen design or technology advances. This report documents the results of this review and the updated power conditioning models and new transmission line models generated to estimate post 2005 PMAD system masses and sizes. This effort continues the expansion and enhancement of a library of PMAD models developed to allow system designers to assess future power system architectures and distribution techniques quickly and consistently.

Metcalf, Kenneth J.↗

Parametric Study of SANSMIC Input and Resulting Impact on Predicted Cavern Geometry and Leaching Efficiency

The Sandia Solution Mining Code (SANSMIC) has been used for many years to examine the development of salt cavern geometry, both in a confirmatory manner with comparisons made to real-world sonar data and in a predictive manner when updated sonar data are not available. SANSMIC models require some modeling choices in order to incorporate real-world data. Key modeling choices include the vertical resolution of cavern geometry to implement, as well as how to incorporate daily raw water injection data into the SANSMIC model. This report documents five studies that address the impact of the modeling choices on the predicted cavern geometries and calculated leaching efficiencies. In most cases, hypothetical cylindrical initial cavern geometries are used to provide a common baseline against which to test the systematic variation of input variables including cavern radius, oil-brine-interface (OBI) depth, vertical cell size, raw water injection rate, raw water injection duration, workover time, and number of leaching stages. The use of smaller cell sizes is recommended moving forward to provide a better one-to-one relationship between sonar data and the modeled cavern. A new methodology for incorporating raw water injection data is also recommended, in order to more closely model real-world injection and workover times. Overall, the systematic studies performed here have increased our confidence in previous SANSMIC model results, as well future use of the code for predicting leaching effects on cavern geometries. Some minor changes to modeling choices are recommended, which can easily be applied with the version of SANSMIC currently under development.

42 ENGINEERING↗

Improving Computational Efficiency of Prognostics Algorithms in Resource-Constrained Settings

In engineering and aerospace applications, it is vital to operational success to have insight into the expected performance and health of physical systems. The field of prognostics and health management provides quantitative methods for monitoring, predicting, and managing system health. Prognostics algorithms can be employed to assess the current state of a system, propagate the system throughout time, and predict potential anomalies or failures that may occur. While they can provide accurate prediction results, effective prognostics algorithms can be challenging to use in resource-constrained settings due to computational limitations and high computational latency, leading to obsolete predictions. Thus, computationally efficient and accurate algorithms are necessary for future remaining useful life predictions. In this work, we implement new algorithmic approaches for prediction, quantitatively compare them via a battery degradation use-case, and provide recommendations of potential improvements to a prognostics framework. One approach to prediction is through sampling, whereby the current state of a physical system is sampled many times and each sample is propagated forward until failure is reached, resulting in a distribution of failure values. To improve the efficiency of this process, we implemented five new algorithmic approaches to prediction, including three distinct sampling methods (standard Monte Carlo, Quasi-Monte Carlo, and Latin Hypercube Sampling), a variable time step algorithm, and a variable sample size algorithm. To compare the algorithms, we employ a variety of metrics designed specifically to analyze both computational efficiency and model accuracy. Our metrics include accuracy to compare the average predicted value to ground truth, mean absolute deviation to illustrate dispersion, specific percentile error to describe accuracy within a user-defined risk tolerance, and code run-time. To quantitatively analyze our results, we employ a use-case of degradation of a Lithium-ion battery. We use an electrochemistry-based model to describe the current health state of the battery, and implement our prediction algorithms to propagate forward in time until end-of-discharge (EOD) is reached. Notably, through this work it was found that none of our sampling approaches had a significant impact on computational efficiency or model accuracy in predicting EOD of the battery. We find that while the sampling methods are unique, the distributions they generate are similar, ultimately producing final predictions that are nearly identical. In exploring the effect of the time step within the prediction algorithm, we found that prediction accuracy was highly dependent on the time step used, and that implementing a variable time step within a particular prediction may provide an increase in computational efficiency while also maintaining prediction accuracy. Finally, implementing a variable sample size also affected prediction, and our results show that tuning both the magnitude and timing of the sample size adjustment can result in improved computation speed and maintained prediction accuracy. Taken together, our findings highlight the challenge of performing prognostics in resource-constrained settings, and illustrate the potential of developing new prediction algorithms to improve computational efficiency.

prognostics↗

FACET: a new long-lived particle detector in the very forward region of the CMS experiment

We describe a proposal to add a set of very forward detectors to the CMS experiment for the high-luminosity era of the Large Hadron Collider to search for beyond the standard model long-lived particles, such as dark photons, heavy neutral leptons, axion-like particles, and dark Higgs bosons. The proposed subsystem is called FACET for Forward-Aperture CMS ExTension, and will be sensitive to any particles that can penetrate at least 50 m of magnetized iron and decay in an 18 m long, 1 m diameter vacuum pipe. The decay products will be measured in detectors using identical technology to the planned CMS Phase-2 upgrade.

Particle and Resonance Production↗

Instantiation of HCML Demonstrating Bayesian Predictive Modeling for Attentional Control

The research team developed models of Attentional Control (AC) that are unique to existing modeling approaches in the literature. The goal was to enable the research team to (1) make predictions about AC and human performance in real-world scenarios and (2) to make predictions about individual characteristics based on human data. First, the team developed a proof-of-concept approach for representing an experimental design and human subjects data in a Bayesian model, then demonstrated an ability to draw inferences about conditions of interest relevant to real-world scenarios. Ultimately, this effort was successful, and we were able to make reasonable (meaning supported by behavioral data) inferences about conditions of interest to develop a risk model for AC (where risk is defined as a mismatch between AC and attentional demand). The team additionally defined a path forward for a human-constrained machine learning (HCML) approach to make predictions about an individual's state based on performance data. The effort represents a successful first step in both modeling efforts and serves as a basis for future work activities. Numerous opportunities for future work have been defined.

97 MATHEMATICS AND COMPUTING↗

Inlet Noise Reduction by Shielding for the Blended-Wing-Body Airplane

Noise shielding benefits associated with an advanced unconventional subsonic transport concept, the Blended-Wing-Body, were studied using a 4- percent scale, 3-engine nacelle model. The study was conducted in the Anechoic Noise Research Facility at NASA Langley Research Center. A high- frequency, wideband point source was placed inside the nacelles of the center engine and one of the side engines in order to simulate broadband engine noise. The sound field of the model was measured with a rotating microphone array that was moved to various stations along the model axis and with a fixed array of microphones that was erected behind the model. Ten rotating microphones were traversed a total of 22 degrees in 2-degree increments. Seven fixed microphones covered an arc that extended from a point in the exhaust exit plane of the center engine (and directly below its centerline) to a point 30 degrees above the jet centerline. While no attempt was made to simulate the noise emission characteristics of an aircraft engine, the model source was intended to radiate sound in a frequency range encompassing 1, 2, and 3 times the blade passage of a typical full-scale engine. In this study, the Blended-Wing-Body model was found to provide significant shielding of inlet noise. In particular, noise radiated downward into the forward sector was reduced by 20 to 25 dB overall in the full-scale frequencies from 2000 to 4000 Hz, decreasing to 10 dB or less at the lower frequencies. Also, it was observed that noise associated with the exhaust radiates into the sector directly below the model downstream to reduce shielding efficiency.

Clark, Lorenzo R.↗

Aeroelastic stability of complete rotors with application to a teetering rotor in forward flight

The derivation of a set of nonlinear coupled flap-lag-torsion equations of motion for moderately large deflections of an elastic, two bladed teetering helicopter rotor in forward flight is concisely outlined. The following degrees of freedom are included in the mathematical model: rigid body flapping, rigid body lead lag, elastic bending in flap and lead-lag blade root torsion and shaft torsion. Quasi-steady aerodynamic loads are considered and the effects of reversed flow are included. The aeroelastic stability of the complete rotor is investigated using a linearized system of equations of motion. The equilibrium position about which the equations are linearized is obtained by considering the trim state of the helicopter, in true or simulated forward flight conditions. The sensitivity of the aeroelastic stability boundaries to interblade structural and mechanical coupling is illustrated by comparing the complete rotor stability boundaries with those obtained from a single blade analysis for a number of hover and forward flight cases.

Shamie, J.↗

Kinematic modeling of a double octahedral Variable Geometry Truss (VGT) as an extensible gimbal

This paper presents the complete forward and inverse kinematics solutions for control of the three degree-of-freedom (DOF) double octahedral variable geometry truss (VGT) module as an extensible gimbal. A VGT is a truss structure partially comprised of linearly actuated members. A VGT can be used as joints in a large, lightweight, high load-bearing manipulator for earth- and space-based remote operations, plus industrial applications. The results have been used to control the NASA VGT hardware as an extensible gimbal, demonstrating the capability of this device to be a joint in a VGT-based manipulator. This work is an integral part of a VGT-based manipulator design, simulation, and control tool.

Williams, Robert L., II↗

Aeroelastic stability of complete rotors with application to a teetering rotor in forward flight

The derivation of a set of non-linear coupled flap-lag-torsion equations of motion for moderately large deflections of an elastic, two-bladed teetering helicopter rotor in forward flight is concisely outlined. The following degrees of freedom are included in the mathematical model: rigid body flapping, rigid body lead-lag, elastic bending in flap and lead-lag, blade root torsion, and shaft torsion. Quasi-steady aerodynamic loads are considered and the effects of reversed flow are included. The aeroelastic stability of the complete rotor is investigated by using a linearized system of equations of motion. The equilibrium position about which the equations are linearized is obtained by considering the trim state of the helicopter, in true or simulated forward flight conditions. The sensitivity of the aeroelastic stability boundaries to interblade structural and mechanical coupling is illustrated by comparing the complete rotor stability boundaries with those obtained from a single blade analysis for a number of hover and forward flight cases.

Shamie, J.↗

Dark Energy Survey Year 6 Results: Point-Spread Function Modeling

We present the point-spread function (PSF) modeling for weak lensing shear measurement using the full six years of the Dark Energy Survey (DES Y6) data. We review the PSF estimation procedure using the PIFF (PSFs In the Full FOV) software package and describe the key improvements made to PIFF and modeling diagnostics since the DES year three (Y3) analysis: (i) use of external Gaia and infrared photometry catalogs to ensure higher purity of the stellar sample used for model fitting, (ii) addition of color-dependent PSF modeling, the first for any weak lensing analysis, and (iii) inclusion of model diagnostics inspecting fourth-order moments, which can bias weak lensing measurements to a similar degree as second-order modeling errors. Through a comprehensive set of diagnostic tests, we demonstrate the improved accuracy of the Y6 models evident in significantly smaller systematic errors than those of the Y3 analysis, in which all g band data were excluded due to insufficiently accurate PSF models. For the Y6 weak lensing analysis, we include g band photometry data in addition to the riz bands, providing a fourth band for photometric redshift estimation. Looking forward to the next generation of wide-field surveys, we describe several ongoing improvements to PIFF, which will be the default PSF modeling software for weak lensing analyses for the Vera C. Rubin Observatory’s Legacy Survey of Space and Time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Precipitation Estimates for Hydroelectricity

Hydroelectric plants require precise and timely estimates of rain, snow and other hydrometeors for operations. However, it is far from being a trivial task to measure and predict precipitation. This paper presents the linkages between precipitation science and hydroelectricity, and in doing so it provides insight into current research directions that are relevant for this renewable energy. Methods described include radars, disdrometers, satellites and numerical models. Two recent advances that have the potential of being highly beneficial for hydropower operations are featured: the Global Precipitation Measuring (GPM) mission, which represents an important leap forward in precipitation observations from space, and high performance computing (HPC) and grid technology, that allows building ensembles of numerical weather and climate models.

Tapiador, Francisco J.↗

PLANETARY DEFENSE: FINDINGS AND RECOMMENDATIONS FROM THE NATIONAL ACADEMIES PLANETARY SCIENCE AND ASTROBIOLOGY DECADAL SURVEY 2023 - 2032

The National Academies of Sciences, Engineering, and Medicine was chartered by the NASA Science Mission Directorate (SMD), with support from the National Science Foundation, to conduct a new decadal survey to develop a comprehensive science and mission strategy for planetary science (1). The survey was tasked to determine the current state of knowledge and to identify the most important scientific questions to be addressed in astrobiology and planetary science during the upcoming decade of 2023 - 2032. For the first time, the decadal survey also included and addressed the topic of planetary defense, now recognized as a key element of NASA’s planetary science activities under the direction of NASA’s SMD Planetary Defense Coordination Office. The topic of planetary defense was included in the decadal survey as a dedicated chapter, divided into five sections based on the framework from the U.S. National NEO Preparedness Strategy and Action Plan (2). These sections discussed: NEO Detection, Tracking, and Characterization NEO Modelling, Prediction, and Integration NEO Deflection and Disruption Missions International Cooperation on NEO Preparation NEO Impact Emergency Procedures and Action Protocols Content of these sections included identifying the activities, ground- and space-based assets, facilities, resources, technologies, and missions that should be considered to enable NEO preparedness over the next decade. Supporting inputs to this chapter involved contributions from submitted white papers authored by many members of the NEO science and planetary defense communities. In addition, a planetary defense rapid mission architecture study commissioned by the decadal survey small bodies panel and led by the Jet Propulsion Laboratory examined several different types of in-situ characterization and mitigation demonstration missions. All of this input contributed to the formulation of 42 findings and 11 recommendations that suggest a path forward for increasing our understanding of the NEO population and their associated physical characteristics, modelling the impact probabilities and hazard potential of these objects, and implementing plans to develop and test NEO impact mitigation capabilities. Including planetary defense in the decadal survey has helped sharpen the focus on this international issue and provided key inputs for stakeholders and decision makers to consider when developing future planetary defense-related activities. Such information is vital for developing a long-term integrated planetary defense capability able to protect humanity in the decades to come.

NEO Detection and Characterization↗

The predicted effect of aerodynamic detuning on coupled bending-torsion unstalled supersonic flutter

A mathematical model is developed to predict the enhanced coupled bending-torsion unstalled supersonic flutter stability due to alternate circumferential spacing aerodynamic detuning of a turbomachine rotor. The translational and torsional unsteady aerodynamic coefficients are developed in terms of influence coefficients, with the coupled bending-torsion stability analysis developed by considering the coupled equations of motion together with the unsteady aerodynamic loading. The effect of this aerodynamic detuning on coupled bending-torsion unstalled supersonic flutter as well as the verification of the modeling are then demonstrated by considering an unstable 12 bladed rotor, with Verdon's uniformly spaced Cascade B flow geometry as a baseline. However, with the elastic axis and center of gravity at 60 percent of the chord, this type of aerodynamic detuning has a minimal effect on stability. For both uniform and nonuniform circumferentially space rotors, a single degree of freedom torsion mode analysis was shown to be appropriate for values of the bending-torsion natural frequency ratio lower than 0.6 and higher 1.2. When the elastic axis and center of gravity are not coincident, the effect of detuning on cascade stability was found to be very sensitive to the location of the center of gravity with respect to the elastic axis. In addition, it was determined that when the center of gravity was forward of an elastic axis located at midchord, a single degree of freedom torsion model did not accurately predict cascade stability.

Hoyniak, D.↗

The effect of circumferential aerodynamic detuning on coupled bending-torsion unstalled supersonic flutter

A mathematical model developed to predict the enhanced coupled bending-torsion unstalled supersonic flutter stability due to alternate circumferential spacing aerodynamic detuning of a turbomachine rotor. The translational and torsional unsteady aerodynamic coefficients are developed in terms of influence coefficients, with the coupled bending-torsion stability analysis developed by considering the coupled equations of this aerodynamic detuning on coupled bending-torsion unstalled supersonic flutter as well as the verification of the modeling are then demonstrated by considering an unstable 12 bladed rotor, with Verdon's uniformly spaced Cascade B flow geometry as a baseline. However, with the elastic axis and center of gravity at 60 percent of the chord, this type of aerodynamic detuning has a minimal effect on stability. For both uniform and nonuniform circumferentially space rotors, a single degree of freedom torsion mode analysis was shown to be appropriate for values of the bending-torsion natural frequency ratio lower than 0.6 and higher 1.2. When the elastic axis and center of gravity are not coincident, the effect of detuning on cascade stability was found to be very sensitive to the location of the center of gravity with respect to the elastic axis. In addition, it was determined that when the center of gravity was forward of an elastic axis located at midchord, a single degree of freedom torsion model did not accurately predict cascade stability.

Hoyniak, D.↗

Application of unsupervised deep learning to image segmentation and in-situ contact angle measurements in a CO 2 -water-rock system

Rock surface wettability is a critical property that regulates multiphase flows in porous media, which can be quantified using the surface contact angle (CA). X-ray micro-computed tomography (μCT) provides an effective approach to in-situ measurements of surface CAs. However, the CA measurement accuracy depends significantly on the quality of CT image segmentation, which is the clustering of CT pixels into separate phases. Inspired by this, we developed a deep learning (DL)-based CA measurement workflow. Motivated by the recent tremendous progress in unsupervised learning techniques and aiming to avoid expensive manual data annotations, an unsupervised DL pipeline for CT image segmentation was proposed and implemented, which includes unsupervised model training and post-processing. The unsupervised model training was driven by a novel loss function constrained with feature similarity and spatial continuity and implemented by iterative forward and backward paths; the former clustered the pixel-wise feature vectors extracted by convolution neural networks, whereas the latter updated the parameters using gradient descent. An over-segmentation strategy was adopted for model training. The post-processing steps based on agglomerative hierarchical clustering (AHC) were implemented to further merge the over-segmented model output to the desired cluster number, which is intended to improve the efficiency of image segmentation. The developed unsupervised DL pipeline was compared with other commonly-used image segmentation methods using pixel-wise and physics-based evaluation metrics on a synthetic raw-image dataset, which had a known ground truth. The unsupervised DL pipeline showed the best performance. Next, the segmented images were input to an automatic CA measurement tool, and the results were validated by comparisons with manual measurements. The CA values from the manual and automatic measurements showed similar distributions and statistical properties. The automatic measurement demonstrated a wider spectrum because of the much larger number of measurement data points. The primary novelty of the unsupervised DL pipeline developed in this study lies in the novel loss function and the over-segmentation strategy associated with AHC post-processing. Finally, the workflow has been proven an efficient tool for pore-scale wettability characterization, which has a wide range of applications in fundamental studies of multiphase flows in natural porous media, which have critical implications to geological carbon sequestration, hydrocarbon energy recovery, and contaminant transport in groundwater.

42 ENGINEERING↗