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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Optimizing photonic ring-resonator filters for OH-suppressed near-infrared astronomy

Near-infrared wavelength observations are crucial for understanding numerous fields of astrophysics, such as supernova cosmology and positronium annihilation detection. However, current ground-based observations suffer from an enormous background due to OH emission in the upper atmosphere. One promising way to solve this problem is to use ring-resonator filters to suppress OH emission lines. Here, we discuss our optimization of ring-resonator filter performance from five perspectives: resonance wavelength matching, polarization-independent operation, low insertion loss, low-loss coupling to astronomical instruments, and broadband operation. In the end, we discuss next steps needed for reliable supernova and positronium observations, thus providing a roadmap for future advances in near-infrared astronomy.

42 ENGINEERING↗
DOE OSTI2023

High-bandwidth image-based predictive laser stabilization via optimized Fourier filters

Controlling the delivery of kHz-class pulsed lasers is of interest in a variety of industrial and scientific applications, from next-generation laser-plasma acceleration to laser-based x-ray emission and high-precision manufacturing. The transverse position of the laser pulse train on the application target is often subject to fluctuations by external drivers (e.g., room cooling and heating systems, motorized optics stages and mounts, vacuum systems, chillers, and/or ground vibrations). For typical situations where the disturbance spectrum exhibits discrete peaks on top of a broad-bandwidth lower-frequency background, traditional PID (proportional-integral-derivative) controllers may struggle, since as a general rule PID controllers can be used to suppress vibrations up to only about 5%–10% of the sampling frequency. Here, a predictive feed-forward algorithm is presented that significantly enhances the stabilization bandwidth in such laser systems (up to the Nyquist limit at half the sampling frequency) by online identification and filtering of one or a few discrete frequencies using optimized Fourier filters. Furthermore, the system architecture demonstrated here uses off-the-shelf CMOS cameras and piezo-electric actuated mirrors connected to a standard PC to process the alignment images and implement the algorithm. To avoid high-end, high-cost components, a machine-learning-based model of the piezo mirror’s dynamics was integrated into the system, which enables high-precision positioning by compensating for hysteresis and other hardware-induced effects. A successful demonstration of the method was performed on a 1 kHz laser pulse train, where externally-induced vibrations of up to 400 Hz were attenuated by a factor of five, far exceeding what could be done with a standard PID scheme.

Natal, Joseph↗
DOE OSTI2020

Evaluation of the Tenti S6 model for hydrocarbon fuels at elevated temperatures using filtered Rayleigh scattering measurements

This Letter targets the assessment of the well-known Tenti S6 model for predicting the Rayleigh–Brillouin scattering (RBS) spectra of select gas–phase hydrocarbon fuels (CH 4 , C 2 H 2 , C 2 H 4 , C 3 H 8 , and C 4 H 10 ) over a temperature range of 300 to 700 K. The Tenti S6 model is evaluated by comparing filtered Rayleigh scattering (FRS) measurements to synthetic FRS signals generated from the combination of the Tenti S6 output and an accurate iodine absorption filter model. Here, the experimental and synthetic FRS results agree very well (<3% difference) over the full temperature range for CH 4 , C 2 H 2 , and C 2 H 4 , indicating accurate calculation of the RBS spectra. For C 3 H 8 and C 4 H 10 , there are some large differences between the experimental and synthetic FRS results which cannot be resolved through tuning of bulk viscosity, internal heat capacity, or inclusion of vibrational degrees of freedom, suggesting the need for detailed measurements of the Rayleigh–Brillouin spectra.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Polarization-independent photonic Bragg grating filter with cladding asymmetry

A photonic Bragg grating is a fundamental building block that reflects the direction of wave propagation through spatial phase modulation and can be implemented using sidewall corrugation. However, due to the asymmetric aspect ratio of a waveguide cross section, typical Bragg gratings exhibit a strong polarization sensitivity. Here, we show that photonic Bragg gratings with cladding asymmetry can enable polarization-independent notch filters by rotating input polarizations. Such Bragg gratings strongly couple transverse electric (TE) and transverse magnetic (TM) modes propagating in opposite directions, filtering the input signal and reflecting the rotated mode. We analyzed this polarization-rotating Bragg grating using the coupled-mode theory and experimentally demonstrated it on a silicon-on-insulator platform. Our device concept is simple to implement and compatible with other platforms, readily available as polarization transparent Bragg components.

Pimbi, Daniel (ORCID:000000025933203X)↗
DOE OSTI2024

Optical filters made from random metasurfaces using Bayesian optimization

Abstract We theoretically investigate the ability to design optical filters from a single material and a single layer of randomly dispersed resonant dielectric particles, defining a random metasurface. Using a Bayesian and generalized Mie inverse-design approach, we design particle radii distributions that give rise to longpass, shortpass, bandpass, and bandstop spectral bands in the infrared. The optical response is shown to be directly related to electric and magnetic multipole scattering of the constituent particles and their near field coupling. We discuss the effect of the particle size distribution and particle–particle coupling interactions on filter design in random systems lacking long-range order.

Materials Science↗
DOE OSTI2020

Time-Resolved Aerosol Filter Sampler Instrument Handbook

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s aerosol counting, composition, extinction, and sizing system (ACCESS) includes a base module (9400), a filter sampler (9401), an advanced mixing condensation particle counter (MCPC, 9403), a miniaturized optical particle counter (MOPC, 9405), and a single-channel tricolor absorption photometer (STAP, 9406). This handbook describes the principles and operations of the filter sampler.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

GraphAlign: Graph-Enabled Machine Learning for Seismic Event Filtering

This report summarizes results from a 2 year effort to improve the current automated seismic event processing system by leveraging machine learning models that can operated over the inherent graph data structure of a seismic sensor network. Specifically, the GraphAlign project seeks to utilize prior information on which stations are more likely to detect signals originating from particular geographic regions to inform event filtering. To date, the GraphAlign team has developed a Graphical Neural Network (GNN) model to filter out false events generated by the Global Associator (GA) algorithm. The algorithm operates directly on waveform data that has been associated to an event by building a variable sized graph of station waveforms nodes with edge relations to an event location node. This builds off of previous work where random forest models were used to do the same task using hand crafted features. The GNN model performance was analyzed using an 8 week IMS/IDC dataset, and it was demonstrated that the GNN outperforms the random forest baseline. We provide additional error analysis of which events the GNN model performs well and poorly against concluded by future directions for improvements.

58 GEOSCIENCES↗
DOE OSTI2025

Parametric Analysis of Holdup in HEPA Filters

This technical document (TECH) contains an analysis of several conditions deemed credible for plutonium oxide buildup in high-efficiency air particulate (HEPA) filters to determine the effect of holdup inside the filter on reactivity. This document is performed in accordance with NCS-AP-005, R3 [Ref. (1)].

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Broadband and filter radiometers at Ross Island, Antarctica: detection of cloud ice phase versus liquid water influences on shortwave and longwave radiation

Abstract. Surface radiometer data from Ross Island, Antarctica, collected during the austral summer 2015–2016 by the US Department of Energy Atmospheric Radiation Measurement (ARM) program West Antarctic Radiation Experiment (AWARE), are used to evaluate how shortwave and longwave irradiance respond to changing cloud properties as governed by contrasting meteorological regimes. Shortwave atmospheric transmittance is derived from pyranometer measurements, and cloud conservative-scattering optical depth is derived from filter radiometer measurements at 870 nm. With onshore flow associated with marine air masses, clouds contain mostly liquid water. With southerly flow over the Transantarctic Mountains, orographic forcing induces substantial cloud ice water content. These ice and mixed-phase clouds attenuate more surface shortwave irradiance than the maritime-influenced clouds and also emit less longwave irradiance due to colder cloud base temperature. These detected irradiance changes are in a range that can mean onset or inhibition of surface melt over ice shelves. This study demonstrates how basic and relatively low-cost broadband and filter radiometers can be used to detect subtle climatological influences of contrasting cloud microphysical properties at very remote locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Tunable coherent light filter for optical sensing and imaging

Systems and methods are provided for filtering coherent infrared light from a thermal background for protection of infrared (IR) imaging arrays and detection systems. A Michelson interferometer is used for coherent light filtering. In an implementation, a system includes a fixed mirror, a beam splitter, and a moving mirror which can be controlled translationally, as well as tip/tilt. The Michelson interferometer may be used as an imaging system. For imaging applications, a system may comprise a tunable array of micro-electromechanical systems (MEMS) mirrors. A mid-wave IR interferometer with electronic feedback and MEMS mirror array is provided.

Wasserman, David↗
DOE OSTI2023

Branch target filtering based on memory region access count

A branch predictor of a processor includes one or more prediction structures, including a predicted branch address and predicted branch direction, that identify predicted branches. To reduce power consumption, the branch predictor selects one or more of the prediction structures that are not expected to provide useful branch prediction information and filters the selected structures such that the filtered structures are not used for branch prediction. The branch predictor thereby reduces the amount of power used for branch prediction without substantially reducing the accuracy of the predicted branches.

Kalamatianos, John↗
DOE OSTI2020

Radioactive Source Localization via Bayesian Particle Filter

In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Wiener Filter Deconvolution for Analog Signals

This project explores the use of Wiener deconvolution to recover an original signal that has been distorted by a known transfer function and by noise. A simulated Gaussian pulse was used as the test signal, and a transfer function was applied in the frequency domain to model the system distortion. Controlled noise was then introduced to approximate real-world signal degradation. A Wiener filter was implemented to reverse the effects of the transfer function while minimizing the influence of noise. The recovered signal was compared with the original pulse to evaluate the effectiveness of the filter. The results demonstrate that Wiener deconvolution offers a stable and effective approach to signal recovery, balancing complete transfer function inversion and noise suppression.

Campbell, Savanna [Fermilab]↗
DOE OSTI2023

Generalized filtered lifting line theory for arbitrary chord lengths and application to wind turbine blades

Abstract The filtered lifting line theory is an analytical approach used to solve the equations of flow subjected to body forces with a Gaussian distribution, such as used in the actuator line model. In the original formulation, the changes in chord length along the blade were assumed to be small. This assumption can lead to errors in the induced velocities predicted by the theory compared to full solutions of the equations. In this work, we revisit the original derivation and provide a more general formulation that can account for significant changes in chord along the blade. The revised formulation can be applied to wings with significant changes in chord along the span, such as wind turbine blades.

17 WIND ENERGY↗
DOE OSTI2023

Applying the Kalman filter particle method to strange and open charm hadron reconstruction in the STAR experiment

Here, we apply KF Particle, a Kalman Filter package for secondary vertex finding and fitting, to strange and open charm hadron reconstruction in heavy-ion collisions in the STAR experiment. Compared to the conventional helix swimming method used in STAR, the KF Particle method improves the reconstructed Λ, Ω and $D$ 0 significance considerably. At the same time, we demonstrate that Monte Carlo simulation with the STAR detector responses can well reproduce the topological variable distributions reconstructed in real data using the KF Particle method, therefore retaining good control on the reconstruction efficiency uncertainties for strange and open charm hadrons measurements in heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Dynamic Performance Enhancement for Nonlinear Stochastic Systems Using RBF Driven Nonlinear Compensation with Extended Kalman Filter

In this paper, a novel hybrid control method is proposed to enhance the control performance of the PI based control system for a class of nonlinear and non-Gaussian stochastic dynamic processes with unmeasurable states. Firstly, to enhance the tracking performance of the PI controller where the PI parameters are fixed in many actual control systems, the compensative signal is formed using the extended Kalman filter(EKF) based state estimator and driven by the radial basis function (RBF) neural network based compensator. In addition, the weights of RBF is trained to minimize the entropy criterion of tracking error as the process is subjected to non-Gaussian disturbances. Meanwhile, since the precise statistical property of noises is hard to obtain for many industrial processes, the kernel density estimation (KDE) technique is employed in this paper to estimate the entropy. The convergence of RBF network is discussed and the stability of the resulted closed-loop hybrid control system is analyzed in mean square sense. Finally, a numerical example and a practical system testing are given to illustrate the effectiveness of the proposed control method.

stochastic systems, PI Controller, Entropy, Extend↗
DOE OSTI2022

Kernel learning backward SDE filter for data assimilation

In this paper, we develop a kernel learning backward SDE filter method to estimate the state of a stochastic dynamical system based on its partial noisy observations. A system of forward backward stochastic differential equations is used to propagate the state of the target dynamical model, and Bayesian inference is applied to incorporate the observational information. Further, to characterize the dynamical model in the entire state space, we introduce a kernel learning method to learn a continuous global approximation for the conditional probability density function of the target state by using discrete approximated density values as training data. Numerical experiments demonstrate that the kernel learning backward SDE is highly effective.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Large-Eddy Simulation of a wind turbine using a Filtered Actuator Line Model

When dealing with multirotor devices such as quadcopters or wind farms, the cost of blade-resolved large-eddy simulation (LES) becomes prohibitive. Combining LES with a family of lower-fidelity models, called actuator line models (ALMs), has grown in popularity in the past decade. ALM replaces full blade resolution with an array of actuator points or lines parameterized by aerodynamic lift/drag polar plots along the blades. Body forces computed based on these actuator points are then projected onto the LES flow mesh, mimicking the effect of rotating blades on the flow. However, the optimal projection radius and the associated LES grid size is often too restrictive for multirotor simulations. Recently, a new tip-correction-based filtered ALM (F-ALM) was proposed by Martinez-Tossas and Meneveau (2019), which allows coarser-than-optimal grids by avoiding the associated overprediction of thrust. In this work, F-ALM is implemented into a high-order, in-house LES code to simulate National Renewable Energy Laboratory Phase VI wind turbine. It is then followed by a comparison between the baseline ALM and the newly implemented F-ALM in terms of instantaneous and time-averaged flow fields and blade loads, revealing the advantages of F-ALM in preventing the overprediction of power on coarse grids. Finally, this encourages accurate and affordable simulations of multirotor devices in the future.

17 WIND ENERGY↗