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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Low-Velocity Impact Response of Sandwich Beams with Functionally Graded Core

The problem of low-speed impact of a one-dimensional sandwich panel by a rigid cylindrical projectile is considered. The core of the sandwich panel is functionally graded such that the density, and hence its stiffness, vary through the thickness. The problem is a combination of static contact problem and dynamic response of the sandwich panel obtained via a simple nonlinear spring-mass model (quasi-static approximation). The variation of core Young's modulus is represented by a polynomial in the thickness coordinate, but the Poisson's ratio is kept constant. The two-dimensional elasticity equations for the plane sandwich structure are solved using a combination of Fourier series and Galerkin method. The contact problem is solved using the assumed contact stress distribution method. For the impact problem we used a simple dynamic model based on quasi-static behavior of the panel - the sandwich beam was modeled as a combination of two springs, a linear spring to account for the global deflection and a nonlinear spring to represent the local indentation effects. Results indicate that the contact stiffness of thc beam with graded core Increases causing the contact stresses and other stress components in the vicinity of contact to increase. However, the values of maximum strains corresponding to the maximum impact load arc reduced considerably due to grading of thc core properties. For a better comparison, the thickness of the functionally graded cores was chosen such that the flexural stiffness was equal to that of a beam with homogeneous core. The results indicate that functionally graded cores can be used effectively to mitigate or completely prevent impact damage in sandwich composites.

Apetre, N. A.↗
DOE OSTI2024

Multimodal, microspectroscopic speciation of legacy phosphorus in two US mid-Atlantic agricultural soils

To understand phosphorus (P) mobility in agricultural soils and its potential environmental risk, it is essential to directly measure solid phase P speciation. Often, bulk P K-edge X-ray absorption near edge structure (XANES) spectroscopy followed by linear combination fitting (LCF) is utilized to determine the solid P phases in soil. However, this method may limit results to only a few major phases. Additionally, XANES spectra for different P species may have very similar features, leading to an over- or underestimate of their contribution to LCF. Here, an improved P speciation by pairing multimodal microbeam-X-ray fluorescence (µ-XRF) mapping coupled with µ-XANES (microbeam-X-ray absorption near edge structure) analysis to directly speciate major and minor P phases on the micron scale is provided. We combined maps of both tender (P, sulfur, aluminum, and silicon) and hard energy (calcium, iron [Fe], and manganese) elements to evaluate the elemental co-locations with P. To better account for uncertainty assigning XANES peaks to individual compounds, a more quantitative fingerprinting by “spectral feature analysis” was completed. With this analysis, an R-factor is reported for the fit. These results were compared to traditional LCF. Pre-edge fitting results revealed the presence of a two-component pre-edge feature for phosphate adsorbed to ferrihydrite. Additionally, phytate co-precipitated with ferrihydrite (Phytate-Fe-Cop) had a pre-edge feature, indicating direct association with Fe. Lastly, a unique P species associated with manganese oxide was identified in the soil via multimodal mapping and µ-XANES. These results allow for better prediction of P dissolution and mobility.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Closures for Two-fluid Five-moment Equations for Magnetized Plasmas (Final Scientific Report)

In the proposed work, we will develop a complete set of closures for two-fluid five-moment equations for magnetized plasmas. Specifically, we propose to obtain explicit formulas for electrons and ions to express heat flow, viscosity, frictional force, and collisional heating in terms of density, and temperature, flow velocity. For this purpose, we solve a set of general moment equations for the relevant closure moments. An infinite hierarchy of general moment equations is completely equivalent to the original Landau-Fokker-Planck kinetic equation. In the small gyro-period expansion, the parallel components of the general moment equations agree with the moments of the drift-kinetic equation (DKE). The advantages of solving the moment equations include (i) an exact treatment of the collision operator, (ii) closure and transport relations with no flux-surface average, and (iii) a unified form of closures for general collisionality. Practically we solve a truncated set of moment equations and hence must verify the convergence of the solutions by increasing number of moments. The parallel integral (nonlocal) closures obtained by solving a set of linearized parallel moment equations are useful only when the nonlinear coupling of moments to the temperature and magnetic field gradient terms is negligible. When the nonlinear coupling terms are substantial, we propose a Fourier transform method to solve the parallel moment equations. By Fourier-expanding the magnetic field, we can convert the differential equations of parallel moments to linear algebraic equations for Fourier components of the moments. The convergence of the solutions can be confirmed by increasing the number of Fourier modes. Our preliminary study in axisymmetric circular magnetic geometry with a large aspect ratio shows that (i) the solutions for Fourier modes n=0 and n=1 converge when modes up to n=2 are included in the expansion, and (ii) lower collisionality requires more moments for convergent closures, as in the case of the integral closures. The proposed work will start from this simple magnetic geometry to find general parallel closures and then be generalized to explore a non-circular magnetic field with finite aspect-ratio. With parallel moments known, the perpendicular component of moment closures can be obtained by inverting the generalized cross product operator in the general moment equations. These efforts will be performed in conjunction with several multi-institutional projects, NIMROD, the Center for Extended MHD Modeling (CEMM), and the Plasma Science and Innovation (PSI) Center.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1951

Formulas for the Supersonic Loading, Lift, and Drag of Flat Swept-Back Wings with Leading Edges Behind the Mach Line

The method of superposition of linearized conical flows has been applied to the calculation of the aerodynamic properties, in supersonic flight, of thin flat, swept-back wings at an angle of attack. The wings are assumed to have rectilinear plan forms, with tips parallel to the stream, and to taper in the conventional sense. The investigation covers the moderately supersonic speed range where the Mach lines from the leading-edge apex lie ahead of the wing. The trailing edge may lie ahead of or behind the Mach lines from its apex. The case in which the Mach cone from one tip intersects the other tip is not treated. Formulas are obtained for the load distribution, the total lift, and the drag due to lift. For the cases in which the trailing edge is outside the Mach cone from its apex the formulas are complete. For wings with both leading and trailing edges behind their respective Mach lines, a degree of approximation is necessary. Charts of some of the functions derived are included to facilitate computing, and several examples are worked out in outline.

Cohen, Doris↗
NASA NTRS2006

Scheduling Aircraft Landings under Constrained Position Shifting

Optimal scheduling of airport runway operations can play an important role in improving the safety and efficiency of the National Airspace System (NAS). Methods that compute the optimal landing sequence and landing times of aircraft must accommodate practical issues that affect the implementation of the schedule. One such practical consideration, known as Constrained Position Shifting (CPS), is the restriction that each aircraft must land within a pre-specified number of positions of its place in the First-Come-First-Served (FCFS) sequence. We consider the problem of scheduling landings of aircraft in a CPS environment in order to maximize runway throughput (minimize the completion time of the landing sequence), subject to operational constraints such as FAA-specified minimum inter-arrival spacing restrictions, precedence relationships among aircraft that arise either from airline preferences or air traffic control procedures that prevent overtaking, and time windows (representing possible control actions) during which each aircraft landing can occur. We present a Dynamic Programming-based approach that scales linearly in the number of aircraft, and describe our computational experience with a prototype implementation on realistic data for Denver International Airport.

Balakrishnan, Hamsa↗
NASA NTRSDate not supplied

Blue-enriched Light Improves Alertness and Mood Following Abrupt Awakening from Slow Wave Sleep

INTRODUCTION: All crew on the International Space Station (ISS) have a sleep opportunity at the same time. Emergencies arising during this time require all crew members to be abruptly awoken from sleep and to be alert, ready to work as a team, and to perform safety-critical tasks soon after waking. However, crew may experience sleep inertia after waking, which is associated with reduced alertness, poor mood, and impaired performance, especially if woken from deep sleep (slow wave sleep, SWS). Light has been shown to improve alertness during sleep deprivation and circadian misalignment. In this study, we assessed the efficacy of blue-enriched light to improve alertness and mood immediately after waking from SWS, i.e., during the sleep inertia period. METHODS: Twelve participants kept a sleep schedule of 8.5 h for 5 nights and 5 h for one night prior to the overnight laboratory visit (confirmed by actigraphy). Participants went to bed at their scheduled habitual bedtime in the laboratory and were monitored by standard polysomnography. After at least 5 min of SWS, participants were awoken and exposed to either red ambient light (control) or blue-enriched light (light) for 1 h. During this time, participants completed a subjective scale of alertness (Karolinska Sleepiness Scale, KSS) and visual analogue scales (VAS) of mood at 2 min, 17 min, 32 min, and 47 min after waking. Following this sleep inertia measurement period, all lights were turned off and participants were allowed to return to sleep. They were then awoken again from their subsequent SWS period and exposed to the opposite condition (control or light). A linear mixed-effects model with fixed effects of condition, time, and condition*time and a random effect of participant was used to determine the impact of light across the testing period. An average of baseline responses (pre-sleep) was included as a covariate. RESULTS: Compared to the control condition, participants exposed to blue-enriched light reported feeling more alert (KSS: F1,77=4.955, p=.029; VASalert: F1,77=8.226, p=.005), more cheerful (VAScheerful: F1,77=8.615, p=.004), less depressed (VASdepressed: F1,77=4.649, p=.034), and less lethargic (VASlethargic: F1,77=5.652, p=.020). DISCUSSION: Exposure to blue-enriched light immediately after waking from SWS may help to improve subjective alertness and mood. Future analyses will explore whether these findings extend to effects on cognitive performance. This countermeasure to sleep inertia may be suitable for implementation to alert crew members during mid-sleep emergencies but requires further testing in field settings.

alertness↗
NASA NTRSDate not supplied

Rise and Shine: Using Light as a Countermeasure to Sleep Inertia

INTRODUCTION: Sleep inertia describes the phenomenon of sleepiness and poor performance experienced after waking from sleep. This period of impaired alertness and performance is of significant concern to workers who nap on shift, or work on-call and are required to perform safety-critical tasks soon after waking (e.g., emergency services, healthcare, military). Light has been shown to acutely improve alertness during sleep deprivation and circadian misalignment. In this study, we assessed the efficacy of blue-enriched light to improve alertness and mood immediately after waking from SWS, i.e., during the sleep inertia period. METHODS: Twelve participants kept a sleep schedule of 8.5 h for 5 nights and 5 h for one night prior to the overnight laboratory visit (confirmed by actigraphy). Participants went to bed at their scheduled habitual bedtime in the laboratory and were monitored by standard polysomnography. After at least 5 min of SWS, participants were awoken and exposed to either red ambient light (control) or blue-enriched light (light) for 1 h. During this time, participants completed a subjective scale of alertness (Karolinska Sleepiness Scale, KSS) and visual analogue scales (VAS) of mood at 2 min, 17 min, 32 min, and 47 min after waking. Following this sleep inertia measurement period, all lights were turned off and participants were allowed to return to sleep. They were then awoken again from their subsequent SWS period and exposed to the opposite condition (control or light). A linear mixed-effects model with fixed effects of condition, time, and condition*time and a random effect of participant was used to determine the impact of light across the testing period. An average of baseline responses (pre-sleep) was included as a covariate. RESULTS: Compared to the control condition, participants exposed to blue-enriched light reported feeling more alert (KSS: F1,77=4.955, p=.029; VASalert: F1,77=8.226, p=.005), more cheerful (VAScheerful: F1,77=8.615, p=.004), less depressed (VASdepressed: F1,77=4.649, p=.034), and less lethargic (VASlethargic: F1,77=5.652, p=.020). DISCUSSION: Exposure to blue-enriched light immediately after waking from SWS may help to improve subjective alertness and mood. Future analyses will explore whether these findings extend to effects on cognitive performance. This countermeasure to sleep inertia may be suitable for implementation to alert crew members during mid-sleep emergencies but requires further testing in field settings.

alertness↗
NASA NTRSDate not supplied

Light Improves Alertness and Mood during the Sleep Inertial Period following Slow Wave Sleep

Introduction: Waking from sleep, especially slow wave sleep (SWS), is associated with reduced alertness known as sleep inertia. Light improves alertness during sleep deprivation and circadian misalignment. In this study, we assessed the efficacy of light to improve alertness and mood immediately after waking from SWS. Methods: Twelve participants kept a sleep schedule of 8.5 h for 5 nights and 5 h for one night prior to the overnight laboratory visit (confirmed by actigraphy). Participants went to bed at their scheduled habitual bedtime in the laboratory and were monitored by standard polysomnography. After at least 5 min of SWS, participants were awoken and exposed to either red ambient light (control) or blue-enriched bright light (light) for 1 h. During this time, participants completed a subjective scale of alertness (Karolinska Sleepiness Scale, KSS) and visual analogue scales (VAS) of mood at 2 min, 17 min, 32 min, and 47 min after waking. Following this sleep inertia measurement period, all lights were turned off and participants were allowed to return to sleep. They were then awoken again from their subsequent SWS period and exposed to the opposite condition (control or light). A linear mixed-effects model with fixed effects of condition, time, and condition*time and a random effect of participant was used to determine the impact of light across the testing period. An average of baseline responses (pre-sleep) was included as a covariate. Results: Compared to the control condition, participants exposed to bright blue-enriched light reported feeling more alert (KSS: F1,77=4.955, p=.029; VASalert: F1,77=8.226, p=.005), more cheerful (VAScheerful: F1,77=8.615, p=.004), less depressed (VASdepressed: F1,77=4.649, p=.034), and less lethargic (VASlethargic: F1,77=5.652, p=.020). Discussion: Exposure to blue-enriched bright light immediately after waking from SWS may help to improve subjective alertness and mood. Future analyses will explore whether these findings extend to effects on cognitive performance.

alertness↗
NASA NTRSDate not supplied

Saccade-Pursuit Coordination during Ocular Tracking across Different Impairment Sources

Purpose: Sleep loss and alcohol have been shown to impair smooth pursuit and its underlying visual motion processing in humans. This study examines the saccadic compensation for this poor pursuit. Methods: Using an established behavioral ocular-tracking paradigm (Liston & Stone, 2014, doi:10.1167/14.14.12), we examined the dose-response of ground lost (pursuit deficit integrated across our 300-ms steady-state tracking interval) and ground gained (increased saccadic response harnessed to compensate)across three separate studies – acute low-dose alcohol administration (LDA; n = 16 subjects), acute sleep loss(ASL; n = 12), and chronic sleep restriction (CSR; n = 12). We computed dose-responses as the linear regression slopes of ground lost and gained across treatment dose (% blood alcohol concentration [BAC] or hours awake). For the CSR study, we computed the mean effect for a single dose (5-hours nightly sleep for 1week). Results: For LDA, there was significantly increased ground lost (P < 0.001) and gained (P < 0.001) with increased %BAC. In addition, the dose-responses were not significantly different (P = 0.35), indicating effectively complete saccadic compensation due to significant increases in both saccadic rate (P < 0.05) and amplitude (P < 0.001). For ASL, there was significantly increased ground lost with time awake (P < 0.01),however ground gained was significantly lower (P < 0.001), indicating, at best, incomplete compensation due to a significant increase in saccadic rate (P < 0.001) but not amplitude (P = 0.10). With CSR, pursuit was again significantly impaired (P < 0.05), with saccadic rate significantly increased (P < 0.05) but, surprisingly, amplitude was significantly decreased (P < 0.05), effectively eliminating ground gained (P = 0.90). Conclusions: Our analyses show that LDA, ASL, and CSR affect tracking differently, suggesting the involvement of different brain pathways. With LDA, the effect appears largely due to the cortical impairment of visual motion processing with largely healthy brainstem and mid-brain responses (driving effective saccadic compensation). ASL and CSR however appear to affect both cortical and sub-cortical pathways, with at best partial saccadic compensation. Lastly, CSR is associated with an additional compromise due to a maladaptive decrease in saccade amplitude.

saccade↗
DOE OSTI2021

Planetary normal mode computation: Parallel algorithms, performance and reproducibility

This report is an extension of work entitled “Computing planetary interior normal modes with a highly parallel polynomial filtering eigensolver.” by Shi et al., [1] originally presented at the SC18 conference. A highly parallel polynomial filtered eigensolver was developed and exploited to calculate the planetary normal modes. The proposed method is ideally suited for computing interior eigenpairs for large-scale eigenvalue problems as it greatly enhances memory and computational efficiency. In this article, the second-order finite element method is used to further improve the accuracy as only the first-order finite element method was deployed in the previous work. The parallel algorithm, its parallel performance up to 20k processors, and the great computational accuracy are illustrated. The reproducibility of the previous work was successfully performed on the Student Cluster Competition at the SC19 conference by several participant teams using a completely different Mars-model dataset on different clusters. Both weak and strong scaling performances of the reproducibility by the participant teams were impressive and encouraging. The analysis and reflection of their results are demonstrated and future direction is discussed.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2020

Convolutional Neural Network for Transition Modeling Based on Linear Stability Theory

Transition prediction is an important aspect of aerodynamic design because of its impact on skin friction and potential coupling with flow separation characteristics. Traditionally, the modeling of transition has relied on correlation-based empirical formulas based on integral quantities such as the shape factor of the boundary layer. However, in many applications of computational fluid dynamics, the shape factor is not straightforwardly available or not well-defined. We propose using the complete velocity profile along with other quantities (e.g., frequency, Reynolds number) to predict the perturbation amplification factor. While this can be achieved with regression models based on a classical fully connected neural network, such a model can be computationally more demanding. We propose a novel convolutional neural network inspired by the underlying physics as described by the stability equations. Specifically, convolutional layers are first used to extract integral quantities from the velocity profiles, and then fully connected layers are used to map the extracted integral quantities, along with frequency and Reynolds number, to the output (amplification ratio). Numerical tests on classical boundary layers clearly demonstrate the merits of the proposed method. More importantly, we demonstrate that, for Tollmien-Schlichting instabilities in two-dimensional, low-speed boundary layers, the proposed network encodes information in the boundary layer profiles into an integral quantity that is strongly correlated to a well-known, physically defined parameter – the shape factor.

Laminar-turbulent transition↗
DOE OSTI2022

Nuclear data covariances are critical input to determine upper sub-critical limits and to design experiments to increase it [Slides]

This presentation discusses how Upper Subcritical Limits (USL) are key parameters to determine operational limits in nuclear criticality safety evaluations. It also discusses an example of plutonium casting operation using tantalum at LANL PF-4. The Whisper tool at Los Alamos relies on many inputs, including covariance data, leading the presentation to ask if an existing benchmark data be used in Whisper to adjust nuclear data and covariances to justify a higher USL. If not, Whisper can be used to help design an optimal new benchmark experiment. The presentation also seeks to determine what the possible impacts are on USL and operational limits for plutonium casting. In conclusion, nuclear data covariances are used for by Whisper for: GSSL adjustment of nuclear data and covariances, identification of most similar existing benchmark experiments to application, simulation of Upper Subcritical Limit of application, and input to optimization techniques for designing most appropriate new benchmark experiment(s) to meet requirements. This requires a complete set of nuclear data covariances, benchmarks and k-effective sensitivity profiles (for both benchmarks and applications). The presentation concludes by asking if end users should trust results that depend on current covariance data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Towards Reconstruction of Complex Flow Fields Using Unit Flows

Many complex turbulent flows in nature and engineering can be qualitatively regarded as being constituted of multiple simpler unit flows. The objective of this work is to characterize the coherent structures in such complex flows as a combination of constituent unitary flow structures for the purpose of reduced-order representation. While turbulence is clearly a non-linear phenomenon, we aim to establish the degree to which the optimally weighted superposition of unitary flow structures can represent the complex flow structures. The rationale for investigating such superposition stems from the fact that the large-scale coherent structures are generated by underlying flow instabilities that may be reasonably described using linear analysis. Clearly, the degree of validity of superposition will depend on the flow under consideration. In this work, we take the first step toward establishing a procedure for investigating superposition. Experimental data of single and triple tandem jets in crossflow are used to demonstrate the procedure. A composite triple tandem jet flow field is generated from optimal superposition of single jet data and compared against ‘true’ triple jet data. Direct comparisons between the true and composite fields are made for spatial, temporal, and kinetic energy content. The large-scale features (obtained from proper orthogonal decomposition or POD) of true and composite tandem jet wakes exhibit nearly 70% agreement in terms of modal eigenvector correlation. Corresponding eigenvalues reveal that the kinetic energy of the flow is also emulated with only a slight overprediction. Temporal frequency features are also examined in an effort to completely characterize POD modes. The proposed method serves as a foundation for more rigorous and robust dimensional reduction in complex flows based on unit flow modes.

Kristo, Paul J.↗
NASA NTRS1998

Multi-Bandwidth Frequency Selective Surfaces for Near Infrared Filtering: Design and Optimization

Frequency selective surfaces are widely used in the microwave and millimeter wave regions of the spectrum for filtering signals. They are used in telecommunication systems for multi-frequency operation or in instrument detectors for spectroscopy. The frequency selective surface operation depends on a periodic array of elements resonating at prescribed wavelengths producing a filter response. The size of the elements is on the order of half the electrical wavelength, and the array period is typically less than a wavelength for efficient operation. When operating in the optical region, diffraction gratings are used for filtering. In this regime the period of the grating may be several wavelengths producing multiple orders of light in reflection or transmission. In regions between these bands (specifically in the infrared band) frequency selective filters consisting of patterned metal layers fabricated using electron beam lithography are beginning to be developed. The operation is completely analogous to surfaces made in the microwave and millimeter wave region except for the choice of materials used and the fabrication process. In addition, the lithography process allows an arbitrary distribution of patterns corresponding to resonances at various wavelengths to be produced. The design of sub-millimeter filters follows the design methods used in the microwave region. Exacting modal matching, integral equation or finite element methods can be used for design. A major difference though is the introduction of material parameters and thicknesses that may not be important in longer wavelength designs. This paper describes the design of multi- bandwidth filters operating in the 1-5 micrometer wavelength range. This work follows on a previous design. In this paper extensions based on further optimization and an examination of the specific shape of the element in the periodic cell will be reported. Results from the design, manufacture and test of linear wedge filters built using microlithographic techniques and used in spectral imaging applications will be presented.

Cwik, Tom↗
DOE OSTI2022

Sensor selection and tool wear prediction with data‐driven models for precision machining

Abstract Estimation of tool wear in precision machining is vital in the traditional subtractive machining industry to reduce processing cost, improve manufacturing efficiency and product quality. In this vein, fusion of time and frequency‐domain features of commonly sensed signals can provide an early indication of tool wear and improve its prediction accuracy for prognostics and health management. This paper presents a data‐driven methodology and a complete tool chain for the inference of precision machining tool wear from fused machine measurements, such as cutting force, power, audio and vibration signals, and quantify the usefulness of each measurement. Indicators of tool wear are extracted from time‐domain signal statistics, frequency‐domain analysis, and time‐frequency domain analysis. Correlation coefficients between the extracted features (indicators) and the tool wear are used to select the most informative features. Principal Component Analysis and Partial Least‐Squares are used to reduce the dimensionality of the feature space. Regression models, including linear regression, support vector regression, Decision tree regression, neural network regression and Gaussian process regression, are used to predict the tool wear using data from a Haas milling machine performing spiral boss face milling. The performance of the regression models based on subsets of sensors validates the preliminary estimates about the saliency of the sensors. The experimental results show that the proposed methods can predict the machine tool wear precisely, with readily available sensor measurements. Neural network and Gaussian process regression were able to achieve good estimates of tool wear at different machine operating conditions. The most informative signal in predicting tool wear was shown to be the vibration signal. Time‐frequency domain features were the most informative features among the combination of features of three domains. In addition, using partial least squares components extracted from the original features of signals led to higher prediction accuracy.

Han, Seulki↗
NASA NTRS2014

Elastic Model Transitions: a Hybrid Approach Utilizing Quadratic Inequality Constrained Least Squares (LSQI) and Direct Shape Mapping (DSM)

A method for transitioning linear time invariant (LTI) models in time varying simulation is proposed that utilizes both quadratically constrained least squares (LSQI) and Direct Shape Mapping (DSM) algorithms to determine physical displacements. This approach is applicable to the simulation of the elastic behavior of launch vehicles and other structures that utilize multiple LTI finite element model (FEM) derived mode sets that are propagated throughout time. The time invariant nature of the elastic data for discrete segments of the launch vehicle trajectory presents a problem of how to properly transition between models while preserving motion across the transition. In addition, energy may vary between flex models when using a truncated mode set. The LSQI-DSM algorithm can accommodate significant changes in energy between FEM models and carries elastic motion across FEM model transitions. Compared with previous approaches, the LSQI-DSM algorithm shows improvements ranging from a significant reduction to a complete removal of transients across FEM model transitions as well as maintaining elastic motion from the prior state.

Jurenko, Robert J.↗
NASA NTRS1999

Multi-Bandwidth Frequency Selective Surfaces for Near Infrared Filtering: Design and Optimization

Frequency selective surfaces are widely used in the microwave and millimeter wave regions of the spectrum for filtering signals. They are used in telecommunication systems for multi-frequency operation or in instrument detectors for spectroscopy. The frequency selective surface operation depends on a periodic array of elements resonating at prescribed wavelengths producing a filter response. The size of the elements is on the order of half the electrical wavelength, and the array period is typically less than a wavelength for efficient operation. When operating in the optical region, diffraction gratings are used for filtering. In this regime the period of the grating may be several wavelengths producing multiple orders of light in reflection or transmission. In regions between these bands (specifically in the infrared band) frequency selective filters consisting of patterned metal layers fabricated using electron beam lithography are beginning to be developed. The operation is completely analogous to surfaces made in the microwave and millimeter wave region except for the choice of materials used and the fabrication process. In addition, the lithography process allows an arbitrary distribution of patterns corresponding to resonances at various wavelengths to be produced. The design of sub-millimeter filters follows the design methods used in the microwave region. Exacting modal matching, integral equation or finite element methods can be used for design. A major difference though is the introduction of material parameters and thicknesses tha_ may not be important in longer wavelength designs. This paper describes the design of multi-bandwidth filters operating in the I-5 micrometer wavelength range. This work follows on previous design [1,2]. In this paper extensions based on further optimization and an examination of the specific shape of the element in the periodic cell will be reported. Results from the design, manufacture and test of linear wedge filters built using micro-lithographic techniques and used ir spectral imaging applications will be presented.

Cwik, Tom↗
DOE OSTI2020

Assessing Historical Variability of South Asian Monsoon Lows and Depressions With an Optimized Tracking Algorithm

Abstract Cyclonic low‐pressure systems (LPS) produce abundant rainfall in South Asia, where they are traditionally categorized as monsoon lows, monsoon depressions, and more intense cyclonic storms. The India Meteorological Department (IMD) has tracked monsoon depressions for over a century, finding a large decline in their number in recent decades, but their methods have changed over time and do not include monsoon lows. This study presents a fast, objective algorithm for identifying monsoon LPS and uses it to assess interannual variability and trends in reanalyses. Variables and thresholds used in the algorithm are selected to best match a subjectively analyzed LPS data set while minimizing disagreement between four reanalyses in a training period. The stream function of 850 hPa horizontal wind is found to be optimal in this sense; it is less noisy than vorticity and represents the complete nondivergent wind, even when flow is not geostrophic. Using this algorithm, LPS statistics are computed for five reanalyses, and none show a detectable trend in monsoon depression counts since 1979. Both the Japanese 55‐year Reanalysis (JRA‐55) and the IMD data set show a step‐like reduction in depression counts when they began using geostationary satellite data, in 1979 and 1982, respectively; the 1958–2018 linear trend in JRA‐55, however, is smaller than in the IMD data set, and its error bar includes 0. There are more LPS in seasons with above‐average monsoon rainfall and in La Niña years, but few other large‐scale modes of interannual variability are found to modulate LPS counts, lifetimes, or track length consistently across reanalyses.

54 ENVIRONMENTAL SCIENCES↗