Search NASA⌕ Search

SEARCH · Search NASA

Results for “tuning technique”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7

Use of the Charge/Discharge (C/D) ratio to aument voltage limit (V sub T) charge control in the ERBS spacecraft

A 50-ampere hour nickel cadmium cell test pack was operated in a power profile simulating the orbit of the Earth Radiation Budget Satellite (ERBS). The objective was to determine the ability of the temperature compensated voltage limit (V sub T) charge control system to maintain energy balance in the half sine wave-type current profile expected of this mission. The four-cell pack (50 E) was tested at the Naval Weapons Support Center (NWSC) at Crane, Indiana. The ERBS evaluation test consisted of two distinct operating sequences, each having a specific purpose. The first phase was a parametric test involving the effect of V sub T level, temperature, and Beta angle on the charge/discharge (C/D) ratio, an indicator of the amount of overcharge. The second phase of testing made use of the C/D ratio limit to augment the V sub T charge limit control. When the C/D limit was reached, the current was switched from the taper mode to a C/67 (0.75 A) trickle charge. The use of an ampere hour integrator limiting the overcharge to a C/67 rate provided a fine tuning of the charge control technique which eliminated the sensitivity problems noted in the initial operating sequence.

Halpert, G.↗

Internal Water Vapor Photoacoustic Calibration

Water vapor absorption is ubiquitous in the infrared wavelength range where photoacoustic trace gas detectors operate. This technique allows for discontinuous wavelength tuning by temperature-jumping a laser diode from one range to another within a time span suitable for photoacoustic calibration. The use of an internal calibration eliminates the need for external calibrated reference gases. Commercial applications include an improvement of photoacoustic spectrometers in all fields of use.

Pilgrim, Jeffrey S.↗

Laser Frequency Stabilization and Control through Offset Sideband Locking to Optical Cavities

We describe a class of techniques whereby a laser frequency can be stabilized to a fixed optical cavity resonance with an adjustable offset, providing a wide tuning range for the central frequency. These techniques require only minor modifications to the standard Pound-Drever-Hall locking techniques and have the advantage of not altering the intrinsic stability of the frequency reference. In a laboratory investigation the sideband techniques were found to perform equally well as the standard, non-tunable Pound-Drever-Hall technique, each providing more than four decades of frequency noise suppression over the free-running noise. An application of a tunable system as a pre-stabilization stage in a phase-lock loop is also presented with the combined system achieving a frequency noise suppression of nearly twelve orders of magnitude.

Thorpe, James I.↗

Self-Tuning of Design Variables for Generalized Predictive Control

Three techniques are introduced to determine the order and control weighting for the design of a generalized predictive controller. These techniques are based on the application of fuzzy logic, genetic algorithms, and simulated annealing to conduct an optimal search on specific performance indexes or objective functions. Fuzzy logic is found to be feasible for real-time and on-line implementation due to its smooth and quick convergence. On the other hand, genetic algorithms and simulated annealing are applicable for initial estimation of the model order and control weighting, and final fine-tuning within a small region of the solution space, Several numerical simulations for a multiple-input and multiple-output system are given to illustrate the techniques developed in this paper.

Lin, Chaung↗

Tuned oscillator atomic force microscopy methods and apparatus

Techniques for operating an atomic force microscope, the atomic force microscope comprising a cantilever and configured to image a surface of a sample using a probe tip coupled to the cantilever, the techniques comprising using a controller to perform: obtaining, based on at least one intrinsic parameter of the cantilever, a first quality factor and a first free oscillation amplitude, wherein the cantilever exhibits only one stable oscillation state when oscillating at the first free oscillation amplitude and operating at the first quality factor; and controlling the cantilever to exhibit the only one stable oscillation state by controlling the cantilever to oscillate at a fixed frequency at or near a resonance frequency of the cantilever, oscillate at the first free oscillation amplitude, and operate at the first quality factor.

Schwarz, Udo↗

Tunable rainbow light trapping in ultrathin resonator arrays

Abstract Rainbow light trapping in plasmonic devices allows for field enhancement of multiple wavelengths within a single device. However, many of these devices lack precise control over spatial and spectral enhancement profiles and cannot provide extremely high localised field strengths. Here we present a versatile, analytical design paradigm for rainbow trapping in nanogroove arrays by utilising both the groove-width and groove-length as tuning parameters. We couple this design technique with fabrication through multilayer thin-film deposition and focused ion beam milling, which enables the realisation of unprecedented feature sizes down to 5 nm and corresponding extreme normalised local field enhancements up to 10 3 . We demonstrate rainbow trapping within the devices through hyperspectral microscopy and show agreement between the experimental results and simulation. The combination of expeditious design and precise fabrication underpins the implementation of these nanogroove arrays for manifold applications in sensing and nanoscale optics.

42 ENGINEERING↗

Gas-phase fragmentation of single heteroatom-incorporated Co 5 MS 8 (PEt 3 ) 6 + (M = Mn, Fe, Co, Ni) nanoclusters

Functionalization of metal-chalcogenide clusters by either replacing core atoms or by tuning the ligand is a powerful technique to tailor their properties. Central to this approach is understanding the competition between the strength of the metal-ligand and metal-metal interactions. Here, using collision-induced dissociation of atomically precise metal sulfide nanoclusters, Co 5 MS 8 L 6 + (L = PEt 3 , M = Mn, Fe, Co, Ni) and Co 5-x Fe x S 8 L 6 + (x = 1–3), we study the effect of a heteroatom incorporation on the core-ligand interactions and relative stability towards fragmentation. Sequential ligand loss is the dominant dissociation pathway that competes with ligand sulfide (LS) loss. Because the ligands are attached to metal atoms, LS loss is an unusual dissociation pathway, indicating significant rearrangement of the core prior to fragmentation. Both experiments and theoretical calculations indicate the reduced stability of Co 5 MnS 8 L 6 + and Co 5 FeS 8 L 6 + towards the first ligand loss in comparison with their Co 6 S 8 L 6 + and Co 5 NiS 8 L 6 + counterparts and provide insights into the core-ligand interaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Remote detection of OH

This is a remote measurement technique utilizing a XeCl excimer laser tuned to the Q sub 21 1 rotational transition of the 0-0, A-X band at 307.847 nm. A wavemeter is under development to monitor, on a pulse-to-pulse basis, both the laser lineshape and absolute wavelength. Fluorescence is detected with a multiple Fabry-Perot type filter with a spectral resolution on the order of 0.001 nm. This is tuned to the overlapping Q sub 2 2, Q sub 12 2, Q sub 2 3, and Q sub 12 3 rotational transitions at 308.986 nm. The fringe pattern from this filter is imaged using a discrete, multi-anode detector which has a photon gain of 10 to the 8th power. This permits the simultaneous monitoring of OH fluorescence, N2 and/or O2 rotational Raman scattering and broadband background levels. The use of three etalons in series provides sufficient rejection, approx. greater than 10 to the 10th power, against the laser radiation only 1.2 nm away.

Mcdermid, I. Stuart↗

On-orbit system identification overview

Parameter identification and modeling are key elements of a design and operational flight strategy for control of flexible space structures. The emphasis of the identification program is on on-orbit applications to spacecraft control. High performance robust controllers will result from advanced design synthesis techniques and on-orbit identification/system tuning. Near term goals for the program include development of an integrated on-line processing capability for flexible body parameter identification, and validation with physical structure experiments.

Mettler, Edward↗

A Validation Study of Merging and Spacing Techniques in a NAS-Wide Simulation

In November 2010, Intelligent Automation, Inc. (IAI) delivered an M&S software tool to that allows system level studies of the complex terminal airspace with the ACES simulation. The software was evaluated against current day arrivals in the Atlanta TRACON using Atlanta's Hartsfield-Jackson International Airport (KATL) arrival schedules. Results of this validation effort are presented describing data sets, traffic flow assumptions and techniques, and arrival rate comparisons between reported landings at Atlanta versus simulated arrivals using the same traffic sets in ACES equipped with M&S. Initial results showed the simulated system capacity to be significantly below arrival capacity seen at KATL. Data was gathered for Atlanta using commercial airport and flight tracking websites (like FlightAware.com), and analyzed to insure compatible techniques were used for result reporting and comparison. TFM operators for Atlanta were consulted for tuning final simulation parameters and for guidance in flow management techniques during high volume operations. Using these modified parameters and incorporating TFM guidance for efficiencies in flowing aircraft, arrival capacity for KATL was matched for the simulation. Following this validation effort, a sensitivity study was conducted to measure the impact of variations in system parameters on the Atlanta airport arrival capacity.

Glaab, Patricia C.↗

A geometric framework for momentum-based optimizers for low-rank training

Low-rank pre-training and fine-tuning have recently emerged as promising techniques for reducing the computational and storage costs of large neural networks. Training low-rank parameterizations typically relies on conventional optimizers such as heavy ball momentum methods or Adam. In this work, we identify and analyze potential difficulties that these training methods encounter when used to train low-rank parameterizations of weights. In particular, we show that classical momentum methods can struggle to converge to a local optimum due to the geometry of the underlying optimization landscape. To address this, we introduce novel training strategies derived from dynamical low-rank approximation, which explicitly account for the underlying geometric structure. Our approach leverages and combines tools from dynamical low-rank approximation and momentum-based optimization to design optimizers that respect the intrinsic geometry of the parameter space. We validate our methods through numerical experiments, demonstrating faster convergence, and stronger validation metrics at given parameter budgets.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗

Detection of gaseous oxygen using temperature tuned laser diodes

The development of an optical differential absorption technique using laser diodes is discussed. The technique is being developed as a solution to overcome the difficulties imposed by conventional liquid rocket propulsion system leak detection such as damage to the engine, cumbersome equipment, and excessive amounts of time. The detection of O2 at atmospheric pressure and temperature using laser diodes is demonstrated. Also, it is shown that, by temperature tuning the laser diode, the wavelength was shifted to a level where the oxygen absorption peaks are found. The levels of transmission determined via experimental means and those calculated from spectral data are found to be in close agreement.

Fox, Curtis W.↗

An adjustable RF tuning element for microwave, millimeter wave, and submillimeter wave integrated circuits

Planar RF circuits are used in a wide range of applications from 1 GHz to 300 GHz, including radar, communications, commercial RF test instruments, and remote sensing radiometers. These circuits, however, provide only fixed tuning elements. This lack of adjustability puts severe demands on circuit design procedures and materials parameters. We have developed a novel tuning element which can be incorporated into the design of a planar circuit in order to allow active, post-fabrication tuning by varying the electrical length of a coplanar strip transmission line. It consists of a series of thin plates which can slide in unison along the transmission line, and the size and spacing of the plates are designed to provide a large reflection of RF power over a useful frequency bandwidth. Tests of this structure at 1 GHz to 3 Ghz showed that it produced a reflection coefficient greater than 0.90 over a 20 percent bandwidth. A 2 GHz circuit incorporating this tuning element was also tested to demonstrate practical tuning ranges. This structure can be fabricated for frequencies as high as 1000 GHz using existing micromachining techniques. Many commercial applications can benefit from this micromechanical RF tuning element, as it will aid in extending microwave integrated circuit technology into the high millimeter wave and submillimeter wave bands by easing constraints on circuit technology.

Lubecke, Victor M.↗

Automated tuning of airframe vibration by structural optimization

Numerical optimization techniques are used to modify the dynamic response at a specified point(s) of a helicopter airframe structure due to a steady state narrow band excitation. Calculation of steady state vibration amplitude is reduced to the solution of linear equations with complex coefficients. The sensitivity of the dynamic amplitudes with respect to the structural parameter perturbations can be computed with the same technique as the one used in the static displacement sensitivity without requiring eigenvector sensitivity. Approximate models for critical structural responses are created based on the sensitivity data to reduce the amount of computational effort and to enable the design of structures of practical scale and complexity. This approach is general in that it accommodates static, dynamic, and frequency constraints simultaneously as long as their computational models are available. It can be used in optimizing mass distribution as well as stiffness modifications of practical structures.

Miura, H.↗

MapsTorch : automatic differentiation for X-ray fluorescence data analysis

X-ray fluorescence (XRF) is a popular spectroscopy technique for elemental analysis. Spectrum fitting and parameter tuning are at the core of XRF analysis and are conventionally manually intensive, especially for synchrotron experiments involving large amounts of diverse samples. This work introduces the automatic differentiation (AD) technique to XRF and an open-source package called MapsTorch. By transforming an analytical model of the XRF spectrum into a differentiable computation graph with AD, MapsTorch enables robust optimization of parameters and elemental intensities. We evaluate MapsTorch by conducting computational experiments on a large number of historical synchrotron XRF datasets and compare its performance with the currently practiced fitting tool NLopt. The results show that MapsTorch consistently achieves high-quality fits and often leads to better fitting quality than NLopt, particularly in tasks such as initial spectrum fitting and elemental intensity refinement. The robust performance of MapsTorch paves the way for developing automated and high-throughput XRF data analysis workflows to handle the increasing data volumes expected from next-generation synchrotron facilities.

X-ray fluorescence↗

Constructing an Efficient Self-Tuning Aircraft Engine Model for Control and Health Management Applications

Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulations.Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulatns.

Armstrong, Jeffrey B.↗

Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation

An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation applications such as model-based diagnostic, controls, and life usage calculations. The advantage of the innovation is the significant reduction in estimation errors that it can provide relative to the conventional approach of selecting a subset of health parameters to serve as the model tuning parameter vector. Because this technique needs only to be performed during the system design process, it places no additional computation burden on the onboard Kalman filter implementation. The technique has been developed for aircraft engine onboard estimation applications, as this application typically presents an under-determined estimation problem. However, this generic technique could be applied to other industries using gas turbine engine technology.

Simon, Donald L.↗

Explaining machine-learning models for gamma-ray detection and identification

As more complex predictive models are used for gamma-ray spectral analysis, methods are needed to probe and understand their predictions and behavior. Recent work has begun to bring the latest techniques from the field of Explainable Artificial Intelligence (XAI) into the applications of gamma-ray spectroscopy, including the introduction of gradient-based methods like saliency mapping and Gradient-weighted Class Activation Mapping (Grad-CAM), and black box methods like Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP). In addition, new sources of synthetic radiological data are becoming available, and these new data sets present opportunities to train models using more data than ever before. In this work, we use a neural network model trained on synthetic NaI(Tl) urban search data to compare some of these explanation methods and identify modifications that need to be applied to adapt the methods to gamma-ray spectral data. We find that the black box methods LIME and SHAP are especially accurate in their results, and recommend SHAP since it requires little hyperparameter tuning. We also propose and demonstrate a technique for generating counterfactual explanations using orthogonal projections of LIME and SHAP explanations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗