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At least 181 records · Page 10

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NASA NTRS1993

Optimization of actuator arrays for aircraft interior noise control

A numerical procedure for grouping actuators in order to reduce the number of degrees of freedom in an active noise control system is evaluated using experimental data. Piezoceramic actuators for reducing aircraft interior noise are arranged into groups using a nonlinear optimization routine and clustering algorithm. An actuator group is created when two or more actuators are driven with the same control input. This procedure is suitable for active control applications where actuators are already mounted on a structure. The feasibility of this technique is demonstrated using measured data from the aft cabin of a Douglas DC-9 fuselage. The measured data include transfer functions between 34 piezoceramic actuators and 29 interior microphones and microphone responses due to the primary noise produced by external speakers. Control inputs for the grouped actuators were calculated so that a cost function, defined as a quadratic pressure term and a penalty term, was a minimum. The measured transfer functions and microphone responses are checked by comparing calculated noise reductions with measured noise reductions for four frequencies. The grouping procedure is then used to determine actuator groups that improve overall interior noise reductions by 5.3 to 15 dB, compared to the baseline experimental configuration.

Cabell, R. H.↗

NASA NTRS2010

Compact, High Energy 2-micron Coherent Doppler Wind Lidar Development for NASA's Future 3-D Winds Measurement from Space

This paper presents an overview of 2-micron laser transmitter development at NASA Langley Research Center for coherent-detection lidar profiling of winds. The novel high-energy, 2-micron, Ho:Tm:LuLiF laser technology developed at NASA Langley was employed to study laser technology currently envisioned by NASA for future global coherent Doppler lidar winds measurement. The 250 mJ, 10 Hz laser was designed as an integral part of a compact lidar transceiver developed for future aircraft flight. Ground-based wind profiles made with this transceiver will be presented. NASA Langley is currently funded to build complete Doppler lidar systems using this transceiver for the DC-8 aircraft in autonomous operation. Recently, LaRC 2-micron coherent Doppler wind lidar system was selected to contribute to the NASA Science Mission Directorate (SMD) Earth Science Division (ESD) hurricane field experiment in 2010 titled Genesis and Rapid Intensification Processes (GRIP). The Doppler lidar system will measure vertical profiles of horizontal vector winds from the DC-8 aircraft using NASA Langley s existing 2-micron, pulsed, coherent detection, Doppler wind lidar system that is ready for DC-8 integration. The measurements will typically extend from the DC-8 to the earth s surface. They will be highly accurate in both wind magnitude and direction. Displays of the data will be provided in real time on the DC-8. The pulsed Doppler wind lidar of NASA Langley Research Center is much more powerful than past Doppler lidars. The operating range, accuracy, range resolution, and time resolution will be unprecedented. We expect the data to play a key role, combined with the other sensors, in improving understanding and predictive algorithms for hurricane strength and track. 1

Singh, Upendra N.↗

NASA NTRS2015

Real-Time On-Board Airborne Demonstration of High-Speed On-Board Data Processing for Science Instruments (HOPS)

The project called High-Speed On-Board Data Processing for Science Instruments (HOPS) has been funded by NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) program since April, 2012. The HOPS team recently completed two flight campaigns during the summer of 2014 on two different aircrafts with two different science instruments. The first flight campaign was in July, 2014 based at NASA Langley Research Center (LaRC) in Hampton, VA on the NASA's HU-25 aircraft. The science instrument that flew with HOPS was Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) CarbonHawk Experiment Simulator (ACES) funded by NASA's Instrument Incubator Program (IIP). The second campaign was in August, 2014 based at NASA Armstrong Flight Research Center (AFRC) in Palmdale, CA on the NASA's DC-8 aircraft. HOPS flew with the Multifunctional Fiber Laser Lidar (MFLL) instrument developed by Excelis Inc. The goal of the campaigns was to perform an end-to-end demonstration of the capabilities of the HOPS prototype system (HOPS COTS) while running the most computationally intensive part of the ASCENDS algorithm real-time on-board. The comparison of the two flight campaigns and the results of the functionality tests of the HOPS COTS are presented in this paper.

Beyon, Jeffrey Y.↗

NASA NTRS1990

Fault analysis of multichannel spacecraft power systems

The NASA Marshall Space Flight Center proposes to implement computer-controlled fault injection into an electrical power system breadboard to study the reactions of the various control elements of this breadboard. Elements under study include the remote power controllers, the algorithms in the control computers, and the artificially intelligent control programs resident in this breadboard. To this end, a study of electrical power system faults is being performed to yield a list of the most common power system faults. The results of this study will be applied to a multichannel high-voltage DC spacecraft power system called the large autonomous spacecraft electrical power system (LASEPS) breadboard. The results of the power system fault study and the planned implementation of these faults into the LASEPS breadboard are described.

Dugal-Whitehead, Norma R.↗

NASA NTRS1988

Near UV atmospheric absorption measurements from the DC-8 aircraft during the 1987 airborne Antarctic ozone experiment

During the Airborne Antarctic Ozone Experiment from 28 August to 30 September 1987 near UV zenith scattered sky measurements were made over Antarctic from the NASA DC-8 aircraft using a one third m spectrograph equipped with a diode-array detector. Scattered sky light data in the wavelength range 348 nm to 388 nm was spectrally analyzed for O3, NO2, OClO, and BrO column abundances. Slant column abudances of O3, NO2, OClO and BrO were determined, using a computer algorithm of non-linear and linear least square correlation of Antarctic scattered sky spectra to laboratory absorption cross section data. Using measured vertical electrochemical sonde ozone profiles from Palmer, Halley Bay, and the South Pole Stations the slant columns of O3 were converted into vertical column abundances. The vertical column amounts of NO2, OClO, and BrO were derived using vertical profiles calculated by a chemical model appropriate for Antarctica. NO2 vertical column abundances show steep latitudinal decrease with increasing latitude for all 13 flights carried out during the mission. In the regions where NO2 abudances are low, OClO and BrO were observed. The spatial and temporal vertical column abundances of these species are discussed in the context of the chemistry and dynamics in the antarctic polar vortex during the austral spring.

Wahner, A.↗

DOE OSTI2017

Control of MMC-HVDC in low-inertia weak grids

With the inherent benefits of high-voltage direct current (HVDC) transmission systems like long-distance high-power transmission with lesser losses and costs, easy integration of renewables, and others, increased presence of DC-AC grids is expected. One of the consequences of increased presence of power electronics is the reduced inertia in the grid, which is an emerging concern. Moreover, the long length of AC transmission lines result in the presence of weak grids (with low short-circuit ratio). To address these concerns, an advanced control algorithm is proposed to control the modular multilevel converter (MMC) based HVDC substation that is connected to a low-inertia weak-grid. The algorithm is based on optimization of control states like frequency, capacitor voltages, active power, and currents in the MMC. The performance of the proposed algorithm is validated in PSCAD/EMTDC to show the effectiveness of the proposed strategy.

Debnath, Suman↗

NASA NTRS1986

Novel measurement techniques (development and analysis of silicon solar cells near 20% effciency)

Work in identifying, developing, and analyzing techniques for measuring bulk recombination rates, and surface recombination velocities and rates in all regions of high-efficiency silicon solar cells is presented. The accuracy of the previously developed DC measurement system was improved by adding blocked interference filters. The system was further automated by writing software that completely samples the unkown solar cell regions with data of numerous recombination velocity and lifetime pairs. The results can be displayed in three dimensions and the best fit can be found numerically using the simplex minimization algorithm. Also described is a theoretical methodology to analyze and compare existing dynamic measurement techniques.

Wolf, M.↗

NASA NTRS1996

Application of Phase Shifted, Laser Feedback Interferometry to Fluid Physics

We have combined the principles of phase-shifting interferometry (PSI) and laser-feedback interferometry (LFI) to produce a new instrument that can measure both optical path length (OPL) changes and discern sample reflectivity variations. In LFI, coherent feedback of the incident light either reflected directly from a surface or reflected after transmission through a region of interest will modulate the output intensity of the laser. LFI can yield a high signal-to-noise ratio even for low reflectivity samples. By combining PSI and LFI, we have produced a robust instrument, based upon a HeNe laser, with high dynamic range that can be used to measure either static (dc) or oscillatory changes along the optical path. As with other forms of interferometry, large changes in OPL require phase unwrapping. Conversely, small phase changes are limited by the fraction of a fringe that can be measured. We introduce the phase shifts with an electro-optic modulator (EOM) and use either the Carre or Hariharan algorithms to determine the phase and visibility. We have determined the accuracy and precision of our technique by measuring both the bending of a cantilevered piezoelectric bimorph and linear ramps to the EOM. Using PSI, sub-nanometer displacements can be measured. We have combined our interferometer with a commercial microscope and scanning piezoelectric stage and have measured the variation in OPL and visibility for drops of PDMS (silicone oil) on coated single crystal silicon. Our measurement of the static contact angle agrees with the value of 68 deg stated in the literature.

Ovryn, Ben↗

NASA NTRS1991

Description of real-time Ada software implementation of a power system monitor for the Space Station Freedom PMAD DC testbed

The authors describe the Ada language software developed to perform the electrical power system monitoring functions for the NASA Lewis Research Center's Power Management and Distribution (PMAD) DC testbed. The results of the effort to implement this monitor are presented. The PMAD DC testbed is a reduced-scale prototype of the electric power system to be used in Space Station Freedom. The power is controlled by smart switches known as power control components (or switchgear). The power control components are currently coordinated by five Compaq 386/20e computers connected through an 802.4 local area network. The power system monitor algorithm comprises several functions, including periodic data acquisition, data smoothing, system performance analysis, and status reporting. Data are collected from the switchgear sensors every 100 ms, then passed through a 2-Hz digital filter. System performance analysis includes power interruption and overcurrent detection. The system monitor required a hardware timer interrupt to activate the data acquisition function. The execution time of the code was optimized by using an assembly language routine. The routine allows direct vectoring of the processor to Ada language procedures that perform periodic control activities.

Ludwig, Kimberly↗

DOE OSTI2017

Report of the HPC Correctness Summit, January 25-26, 2017, Washington, DC

Technologies for verification and debugging have made significant strides in the context of general systems software. An investment in such technologies to make them applicable for High Performance Computing (HPC) could lead to substantial improvements in the productivity and sustainability of HPC software development. Such improvements will be essential to fully exploit new exascale computer architectures. Without such investment, there is the possibility of a substantial crisis in our ability to advance the field of HPC, as the complexity of our architectures, algorithms, and applications is moving beyond the ability of our developers. As HPC is of strategic importance to our nation, forming the bedrock of its scientific and technological capabilities, such investment is highly warranted.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Design and Analysis of an Integral MPPT Control Law for Wave Energy Conversion Systems

In this paper, we propose an integral-based maximum power point tracking (MPPT) algorithm for point absorber wave energy conversion (WEC) systems. A permanent magnet synchronous generator (PMSG) is coupled to the point absorber and its drive implements the proposed MPPT control. While the rotating frame of reference of the PMSG implements power control, the slower mechanical frequency of the incident waves are processed with an additional transformation that yields another set of dc dynamics. The computed dc power in the new reference frame, which is focused on slow wave dynamics, is input to the MPPT control law that tunes the emulated resistance of the machine drive to extract peak power from the wave absorber device. We derive a stability condition for the proposed controller and validate our control design on a simulated 10kW system.

wave energy, maximum power point tracking (MPPT), ↗

DOE OSTI2026

Leveraging machine learning to enhance aerosol classification using Single-Particle Mass Spectrometry

Advancing automated classification of atmospheric aerosols from Single-Particle Mass Spectrometry (SPMS) data remains challenging due to overlapping ion signatures, compositional diversity, and limited labeled data. This study evaluates supervised and semi-supervised learning frameworks to enhance aerosol identification by jointly leveraging labeled and unlabeled spectra. Four models were compared: a supervised Support Vector Machine (SVM), a self-training SVM, a stacked autoencoder classifier, and a stacked autoencoder trained using a temporal-ensembling Mean Teacher approach. All models achieved high and stable accuracies (90.0 %–91.1 %), surpassing previous results on the same dataset (87 %) and matching the performance of state-of-the-art deep learning methods. Despite small global metric differences (≤ 1 %), semi-supervised variants yielded up to 5 %–10 % improvements for compositionally rare particle types – such as soot (0.77 % of spectra, F1-score: 0.93–0.97) and hazelnut pollen (0.98 % of spectra, F1-score: 0.97–1.00) – equating to roughly ∼ 187 additional correctly classified spectra. These gains are scientifically significant, as such rare particles exert disproportionate influence on radiative absorption and ice nucleation processes; their improved detection reduces modeled uncertainties in aerosol absorption optical depth and mixed-phase cloud ice nucleation rates. The models' residual misclassifications (≈ 9 %) largely arise from true spectral overlap among chemically adjacent species (e.g., Na- vs. K-feldspar, coated vs. uncoated feldspars), reflecting physical compositional continuity rather than algorithmic error. Collectively, these findings demonstrate that leveraging unlabeled data to learn robust spectral representations and refine classification enhances both fidelity and interpretability, bridging data-driven analysis with aerosol–climate process understanding.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1994

Design, characterization and control of the Unique Mobility Corporation robot

Space and mass are at a premium on any space mission, and thus any machinery designed for space use should be lightweight and compact, without sacrificing strength. It is for this reason that NASA/LeRC contracted Unique Mobility Corporation to exploit their novel actuator designs to build a robot that would advance the present state of technology with respect to these requirements. Custom-designed motors are the key feature of this robot. They are compact, high-performance dc brushless servo motors with a high pole count and low inductance, thus permitting high torque generation and rapid phase commutation. Using a custom-designed digital signal processor-based controller board, the pulse width modulation power amplifiers regulate the fast dynamics of the motor currents. In addition, the programmable digital signal processor (DSP) controller permits implementation of nonlinear compensation algorithms to account for motoring vs. regeneration, torque ripple, and back-EMF. As a result, the motors produce a high torque relative to their size and weight, and can do so with good torque regulation and acceptably high velocity saturation limits. This paper presents the Unique Mobility Corporation robot prototype: its actuators, its kinematic design, its control system, and its experimental characterization. Performance results, including saturation torques, saturation velocities and tracking accuracy tests are included.

Velasco, Virgilio B., Jr.↗

NASA NTRS2012

Prognostics of Power Electronics, Methods and Validation Experiments

Abstract Failure of electronic devices is a concern for future electric aircrafts that will see an increase of electronics to drive and control safety-critical equipment throughout the aircraft. As a result, investigation of precursors to failure in electronics and prediction of remaining life of electronic components is of key importance. DC-DC power converters are power electronics systems employed typically as sourcing elements for avionics equipment. Current research efforts in prognostics for these power systems focuses on the identification of failure mechanisms and the development of accelerated aging methodologies and systems to accelerate the aging process of test devices, while continuously measuring key electrical and thermal parameters. Preliminary model-based prognostics algorithms have been developed making use of empirical degradation models and physics-inspired degradation model with focus on key components like electrolytic capacitors and power MOSFETs (metal-oxide-semiconductor-field-effect-transistor). This paper presents current results on the development of validation methods for prognostics algorithms of power electrolytic capacitors. Particularly, in the use of accelerated aging systems for algorithm validation. Validation of prognostics algorithms present difficulties in practice due to the lack of run-to-failure experiments in deployed systems. By using accelerated experiments, we circumvent this problem in order to define initial validation activities.

Kulkarni, Chetan S.↗

NASA NTRS2019

Microphysical Retrievals from Simultaneous Measurements by Airborne and Ground Radars during OLYMPEX

The OLYMPEX field campaign took place over the Olympic Peninsula of Washington during winter 2015-2016. During the intensive observing period, several aircraft flights obtained multi-frequency airborne radar measurements at X-, Ku-, Ka, and W-band from radars aboard the ER-2 and DC-8 aircraft. In addition, ground radars at S- and X-band performed RHI scans under the aircraft ground tracks. These coincident datasets provide a wealth of complementary information about the hydrometeor particle sizes, shapes, and orientations.In order to synthesize these measurements and test the robustness of scattering models, an optimal estimation retrieval based upon a Hitschfeld-Bordan profiling algorithm has been developed. This algorithm retrieves profiles of the particle size distribution parameters Nw and Dm, and, in the ice phase, relative proportions of aggregate, pristine, and rimed particles, using scattering models with different size-density and size-aspect ratio relationships. Under this formulation, only the pristine particles are horizontally aligned and capable of producing non-zero ZDR and KDP.From the nadir-looking airborne multifrequency radars, we find that aggregates may be readily distinguished from rimed and pristine particles owing to their uniqueness in triple-frequency space. However, rimed and pristine particles occupy a similar region in this space and thus polarimetric measurements greatly enhance their identification in our retrieval framework. With these capabilities we will present analyses of three-dimensional hydrometeor mapping obtained during various OLYMPEX cases. Some features retrieved in these cases include a layer of enhanced aggregation about 2km above the melting layer, hypothesized to be maintained by orographic uplift. This layer is often situated above a layer of denser, aligned particles. Regions of riming and supercooled liquid water beneath generating cells are also identified by our retrieval algorithm. Comparisons to in-situ observations and evaluation of scattering models will be presented.

Munchak, S. Joseph↗

DOE OSTI2020

Enabling Seamless Integration of EV Charging Infrastructure with Weak Electric Grids

Widespread adoption of Electric Vehicles (EVs) for light, medium, and heavy-duty applications has gained significant interest. Based on ownership and user preferences, light duty and local delivery medium-duty EVs are typically connected to grid distribution networks whereas larger medium duty and heavy-duty EVs are typically connected to distribution or even sub-transmission networks. Challenges with at-scale EVs and charging infrastructure supporting them include interoperability, distribution network upgrades, surge in demand charges, power quality issues, voltage stability, etc. Based on real-world data, steady-state and dynamic assessments of light-duty EV charging with a focus on DC Fast Charging (DCFC) for weak distribution grids is presented. Three main areas of contributions in this paper include - steady state and dynamic power quality measurements and assessments using real world data, transient assessments of light duty EV integration with weak distribution networks (IEEE 13 node feeder system) under grid-connected and microgrid modes, and formulation of an intelligent charging decision algorithm to enable an impact-minimal charging.

actionable intelligence↗

DOE OSTI2021

Optimization of a High Bunch Charge ERL Injection Merger for PERLE

Delivery of high charge electron bunches into the main loop of an ERL (energy recovery linac) while preserving the emittance is challenging. This is because at the typical injection momentum, space charge forces still have a significant effect on the beam dynamics. In this work we consider the design of the merger for PERLE, an ERL test facility to be based at IJCLab in France. Previous simulations have shown that the baseline DC gun based injector can achieve the required emittance at the booster linac exit. The quality of the 500 pC bunches must then be preserved with space charge through the merger at total beam energy of 7 MeV keeping the emittance below 6 mm mrad. The beam dynamics in the merger were simulated using the code OPAL and optimised using a genetic algorithm. Three possible merger schemes were investigated. The goal of the optimisation was to minimise the emittance growth while also achieving the required Twiss parameters to match onto the spreader at the main linac exit. A three dipole solution is then examined in more detail.

Hounsell, B.↗

DOE OSTI2022

A deep learning-enhanced framework for multiphysics joint inversion

Joint inversion has drawn considerable attention due to the availability of multiple geophysical data sets, ever-increasing computational resources, the development of advanced algorithms, and its ability to reduce inversion uncertainty. A key issue of joint inversion is to develop effective strategies to link different geophysical data in a unified mathematical framework, in which the information obtained from different models can complement each other. We have developed a deep learning-enhanced joint inversion framework to simultaneously reconstruct different physical models by fusing different types of geophysical data. Traditionally, structure similarity constraints are pursued by joint inversion algorithms using manually crafted formulations (e.g., cross gradient). The constraint is constructed by a deep neural network (DNN) during the learning process. The framework is designed to combine the DNN and a traditional independent inversion workflow and improve the joint inversion result iteratively. The network can be easily extended to incorporate multiphysics without structural changes. Numerical experiments on the joint inversion of 2D DC resistivity data and seismic traveltime are used to validate our method. In addition, this learning-based framework demonstrates excellent generalization abilities when tested on data sets using different geologic structures. It also can handle different sensing configurations and nonconforming discretization.

Geochemistry & Geophysics↗