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At least 199 records · Page 11

All sources NASA NTRS DOE OSTI

NASA NTRS2004

Antenna LQG Controllers: Properties, Limits of Performance, and Tuning Procedure

The LQG controllers significantly improve antenna tracking precision, but their tuning is a trial-and-error process. A control engineer has two tools to tune an LQG controller: the choice of coordinate system of the controller, and the selection of weights of the LQG performance index. The paper selects the coordinates of the open-loop model that simplify the shaping of the closed-loop performance and analyzes the impact of the weights on the antenna closed-loop bandwidth, disturbance rejection properties, and antenna acceleration. Finally, it presents the LQG controller tuning procedure that rationally shapes the closed-loop performance.

antennas↗

NASA NTRS2011

A Tuned Single Parameter for Representing Conjunction Risk

Satellite conjunction assessment risk analysis is a subjective enterprise that can benefit from quantitative aids and, to this end, NASA/GSFC has developed a fuzzy logic construct - called the F-value - to attempt to provide a statement of conjunction risk that amalgamates multiple indices and yields a more stable intra-event assessment. This construct has now sustained an extended tuning procedure against heuristic analyst assessment of event risk. The tuning effort has resulted in modifications to the calculation procedure and the adjustment of tuning coefficients, producing a construct with both more predictive force and a better statement of its error.

Plakaloic, D.↗

NASA NTRS2016

A-Priori Tuning of Modified Magnussen Combustion Model

In the application of CFD to turbulent reacting flows, one of the main limitations to predictive accuracy is the chemistry model. Using a full or skeletal kinetics model may provide good predictive ability, however, at considerable computational cost. Adding the ability to account for the interaction between turbulence and chemistry improves the overall fidelity of a simulation but adds to this cost. An alternative is the use of simple models, such as the Magnussen model, which has negligible computational overhead, but lacks general predictive ability except for cases that can be tuned to the flow being solved. In this paper, a technique will be described that allows the tuning of the Magnussen model for an arbitrary fuel and flow geometry without the need to have experimental data for that particular case. The tuning is based on comparing the results of the Magnussen model and full finite-rate chemistry when applied to perfectly and partially stirred reactor simulations. In addition, a modification to the Magnussen model is proposed that allows the upper kinetic limit for the reaction rate to be set, giving better physical agreement with full kinetic mechanisms. This procedure allows a simple reacting model to be used in a predictive manner, and affords significant savings in computational costs for simulations.

Norris, A. T.↗

NASA NTRS2016

Tuned Chamber Core Panel Acoustic Test Results

This report documents acoustic testing of tuned chamber core panels, which can be used to supplement the low-frequency performance of conventional acoustic treatment. The tuned chamber core concept incorporates low-frequency noise control directly within the primary structure and is applicable to sandwich constructions with a directional core, including corrugated-, truss-, and fluted-core designs. These types of sandwich structures have long, hollow channels (or chambers) in the core. By adding small holes through one of the facesheets, the hollow chambers can be utilized as an array of low-frequency acoustic resonators. These resonators can then be used to attenuate low-frequency noise (below 400 Hz) inside a vehicle compartment without increasing the weight or size of the structure. The results of this test program demonstrate that the tuned chamber core concept is effective when used in isolation or combined with acoustic foam treatments. Specifically, an array of acoustic resonators integrated within the core of the panels was shown to improve both the low-frequency absorption and transmission loss of the structure in targeted one-third octave bands.

Schiller, Noah H.↗

NASA NTRS2018

Tuning Process for the Modified Magnussen Combustion Model

In the application of CFD to turbulent reacting flows, one of the main limitations to predictive accuracy is the chemistry model. Using a full or skeletal kinetics model may provide good predictive ability, however, at considerable computational cost. Adding the ability to account for the interaction between turbulence and chemistry improves the overall fidelity of a simulation but adds to this cost. An alternative is the use of simple models, such as the Magnussen model, which has negligible computational overhead, but lacks general predictive ability except for cases that can be tuned to the flow being solved. In this paper, a technique will be described that allows the tuning of the Magnussen model for an arbitrary fuel and flow geometry without the need to have experimental data for a particular case. The tuning is based on comparing the results of the Magnussen model and full finite-rate chemistry when applied to perfectly and partially stirred reactor sim- ulations. In addition, a modification to the Magnussen model is proposed that allows the upper kinetic limit for the reaction rate to be set, giving better physical agreement with full kinetic mechanisms. In order to improve the agreement with flame temperatures, the thermal properties of the product species is adjusted to better match the mixture proper- ties of the full mechanism. The combustion model is then applied to the simulation of a representative scramjet flowpath, and the results compared to experimental data and other kinetic models. This procedure allows a simple reacting model to be used in a predictive manner, and affords significant savings in computational costs for CFD simulations.

Norris, A. T.↗

NASA NTRSDate not supplied

Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning

Multi-model Monte Carlo methods have been demonstrated to be an efficient and accurate alternative to standard Monte Carlo (MC) in the model-based propagation of uncertainty in entry, descent, and landing (EDL) applications. These multi-model MC methods fuse predictions from low-fidelity models with the high-fidelity EDL model of interest to produce unbiased statistics with a fraction of the computational cost. The accuracy and efficiency of the multi-model MC methods are dependent upon the magnitude of correlations of the low-fidelity models with the high-fidelity model, but also upon the correlation amongst the low-fidelity models, and their relative computational cost. Because of this layer of complexity, the question of how to optimally select the set of low-fidelity models has remained open. In this work, methods for optimal model construction and tuning are investigated as a means to increase the speed and precision of trajectory simulation for EDL. Specifically, the focus is on the inclusion of low-fidelity model tuning within the sample allocation optimization that accompanies multi-model MC methods. Preliminary results indicate that low-fidelity model tuning can significantly improve efficiency and precision of trajectory simulations and provide an increased edge to multi-model MC methods when compared to standard MC. The challenges and potential benefits to exploring a fully iterative and comprehensive optimization strategy in future work are highlighted.

uncertainty quantification↗

NASA NTRSDate not supplied

Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning

Multi-model Monte Carlo methods have been demonstrated to be an efficient and accurate alternative to standard Monte Carlo (MC) in the model-based propagation of uncertainty in entry, descent, and landing (EDL) applications. These multi-model MC methods fuse predictions from low-fidelity models with the high-fidelity EDL model of interest to produce unbiased statistics with a fraction of the computational cost. The accuracy and efficiency of the multi-model MC methods are dependent upon the magnitude of correlations of the low-fidelity models with the high-fidelity model, but also upon the correlation among the low-fidelity models, and their relative computational cost. Because of this layer of complexity, the question of how to optimally select the set of low-fidelity models has remained open. In this work, methods for optimal model construction and tuning are investigated as a means to increase the speed and precision of trajectory simulation for EDL. Specifically, the focus is on the inclusion of low-fidelity model tuning within the sample allocation optimization that accompanies multi-model MC methods. Preliminary results indicate that low-fidelity model tuning can significantly improve efficiency and precision of trajectory simulations and provide an increased edge to multi-model MC methods when compared to standard MC. The challenges and potential benefits to exploring a fully iterative and comprehensive optimization strategy in future work are highlighted.

uncertainty quantification↗

NASA NTRS2020

Structural Model Tuning Tool: User's Reference Manual

This report presents an efficient approach for tuning finite element models to match the measured ground vibration test and static test data. Frequencies, mode shapes, total weight, location of the center of gravity, and static deformation computed from the finite element model are matched to the measured data. The model tuning procedure used in this work is based on solving an optimization problem in which the errors for the considered metrics, between the finite element prediction and the measured data, are minimized. Analytical sensitivity values of performance indices are computed using the NASTRAN-generated sensitivity values together with the in-house computer codes, which allow for faster computational time and the use of gradient-based optimizers. The method is applied to the Aerostructures Test Wing IV model. The study shows that the military standard and the National Aeronautics and Space Administration standard for comparing analytical and experimental modal data are all satisfied. The final finite element model correlates well with the test data. The flutter speed decreases by 8.91 percent after model tuning compared with the original Aerostructures Test Wing IV design.

Chan-gi Pak↗

DOE OSTI2020

Impact of Tuned Lighting on Skilled Nursing Center Residents' Sleep

The Problem: Sleep disturbance is common among nursing center residents and places them at risk for poor health outcomes. Lighting that changes in color and intensity over the course of the day and night may improve sleep and other outcomes, like dementia behaviors, but has has not been rigorously evaluated under real-world conditions. The Resolution: This single-facility study establishes that facility-level tuned lighting is feasible to implement and evaluate in a nursing center. Researchers randomly-assigned three corridors to one of two lighting conditions, then the other. Residents experienced half as many sleep disturbances while exposed to tuned vs. static lighting. There was no effect on behaviors. Tips for Success: Tuned lighting is a low-risk intervention that could be employed in new construction or when retrofitting fixtures into existing buildings. Key Words: Nursing home, long-term care, lighting, sleep, behaviors

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Systems, methods and computer program products for self-tuning sensor data processing

Systems and methods are disclosed that include tools that utilize Dynamic Detector Tuning (DDT) software that identifies near-optimal parameter settings for each sensor using a neuro-dynamic programming (reinforcement learning) paradigm. DDT adapts parameter values to the current state of the environment by leveraging cooperation within a neighborhood of sensors. The key metric that guides the dynamic tuning is consistency of each sensor with its nearest neighbors: parameters are automatically adjusted on a per station basis to be more or less sensitive to produce consistent agreement of detections in its neighborhood. The DDT algorithm adapts in near real-time to changing conditions in an attempt to automatically self-tune a signal detector to identify (detect) only signals from events of interest. The disclosed systems and methods reduce the number of missed legitimate detections and the number of false detections, resulting in improved event detection.

Draelos, Timothy J.↗

DOE OSTI2021

Apprentice for Event Generator Tuning

Apprentice is a tool developed for event generator tuning. It contains a range of conceptual improvements and extensions over the tuning tool Professor. Its core functionality remains the construction of a multivariate analytic surrogate model to computationally expensive Monte-Carlo event generator predictions. The surrogate model is used for numerical optimization in chi-square minimization and likelihood evaluation. Apprentice also introduces algorithms to automate the selection of observable weights to minimize the effect of mis-modeling in the event generators. We illustrate our improvements for the task of MC-generator tuning and limit setting.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Two-DoF Model-Informed Controller Gain Tuning for Several Floating Wind Platforms

Much effort has recently been put into the development of collective blade pitch controllers for floating offshore wind turbines, with the aim of overcoming negative damping issues that arise with traditional control methods. One proposed approach to this challenge involves using a two-degree-of-freedom model to inform the gain schedule of a nacelle velocity feedback term in an otherwise conventional proportional-integral controller. The model uses tower-top fore-aft and rotor angular displacements, and is used to calculate a nacelle velocity feedback gain that results in a specified increase in platform pitch damping. Earlier performance evaluations of this tuning method were favorable, suggesting its potential as an easy way for researchers to obtain an adequate controller. This paper expands on those previous results by examining the performance of the tuning method relative to baseline controllers for several hull configurations, and for several prescribed increases in platform pitch damping. Simulations were run in OpenFAST for several load cases above rated wind speed and show results consistent with trends in the earlier study. The tuning method is thus shown to be adaptable to many different types of hulls, making it useful for the evaluation of prototype designs.

artificial intelligence↗

DOE OSTI2024

Validation of the NOνA experiment 2023-tuning on simulated neutrino-matter interactions

NOνA is a long-baseline neutrino oscillation experiment that utilizes a two-detector design to study the oscillations of muon neutrinos into electron neutrinos over a baseline of 810 km. The Near Detector (ND) measures the neutrino beam spectrum and composition before oscillation, which is then compared to the oscillated neutrino energy spectrum observed in the Far Detector (FD). In the ND, the neutrinos are detected through their interactions with the heavy target nuclei within the detector. NOνA employs the GENIE neutrino event generator for simulating these neutrino-nucleus interactions. However, the default GENIE prediction does not adequately reproduce the ND data. To address this, NOνA developed a tune of the neutrino interaction models within GENIE version 3:0:6 to minimize discrepancies between the simulated predictions and the observed data in the ND. This dissertation tests the NOνA’s 2023 tune of the GENIE neutrino cross-section simulations by performing a data/simulations comparison for the ND. The analysis employed datasets comprising $2.55\times10^{21}$ protons-on-target (POT) in neutrino beam mode and $1.14\times10^{21}$ POT in antineutrino beam mode. The NOνA tuning of neutrino-matter interaction simulations matches with ND data within the $1\sigma$ error band, overestimating muon neutrino and antineutrino charged current interactions by approximately 6 % and 9 %, respectively. Discrepancies were observed in the energy region dominated by Quasi-Elastic-like interactions. Systematic uncertainties associated with the modeling of the neutrino cross-section, particularly those pertaining Quasi-Elastic like interactions, contributed considerably to the overall error in the simulations. Furthermore, the reconstruction algorithm used in NOνA for particle classification demonstrated significant misidentifications between charged pions and protons, as well as a tendency to overlook additional pions or protons in multi-particle simulated events.

Cortés Parra, Camilo Andrés↗

DOE OSTI2026

Test cavity and Iris-to-Coax transition for tuning and high-power verification of SNS DTL iris couplers

The Spallation Neutron Source (SNS) Drift Tube Linac (DTL) employs iris couplers to efficiently deliver RF power into the accelerating structure. To support the development, tuning, and high‑power conditioning of these couplers prior to installation in the actual DTLs, a dedicated test cavity and an iris‑to‑coaxial transition structure have been designed. This work presents the electromagnetic design, simulation, and optimization of the test setup, enabling precise characterization of the iris coupler’s performance. The transition structure allows for tuning of the iris opening dimensions without requiring a waveguide taper or full‑size waveguide transitions, while maintaining impedance matching between the coaxial feed and the iris geometry to minimize reflection and power loss. During low‑power tests, the iris opening di-mensions can be evaluated using the iris‑to‑coax transi-tion attached to the test cavity. For high‑power condi-tioning, full‑size waveguides with ceramic vacuum win-dows are connected to the test cavity to replicate opera-tional conditions. Key design parameters were optimized using computer-aided simulation, and sensitivity studies were conducted to assess the impact of mechanical toler-ances on RF performance. The resulting test platform provides a reliable and efficient means for tuning and validating iris couplers, contributing to improved opera-tional stability in the SNS DTL.

Lee, Sung-Woo [ORNL] (ORCID:000000030915835X)↗

DOE OSTI2026

Axion dark matter search with a photonic bandgap cavity haloscope and dielectric tuning rod over 10.25-10.45 GHz

We report the development of a new widely tunable cavity and demonstrate its use in a search for dark matter axions. We achieve unloaded quality factors above $10^{5}$, roughly $25\times$ larger than a bare copper cavity at the same frequency, using concentric sapphire shells to reduce Ohmic losses on the cavity barrel. A rotating sapphire rod tunes our cavity mode over the $10.1-11.7$ GHz range, approximately $16\%$ of its resonant frequency. Using an amplified receiver chain, we demonstrate sensitivity to new axion parameter space by tuning the cavity over the $200$ MHz range between $10.25-10.45$ GHz (42.4 - 43.2, $μ$eV) to constrain the axion-to-photon coupling to $|g_{aγγ}|$$\leq$ 1 $\times$$10^{-12}$${GeV}^{-1}$. This cavity can scan its tuning range about $9$ times faster compared to a bare copper cavity when paired with a photon counting device, laying the groundwork for a definitive search for the QCD axion over $10.1-11.7$ GHz.

Lynn, Morgan [Chicago U.]↗

DOE OSTI2024

Colossal Strain Tuning of Ferroelectric Transitions in KNbO 3 Thin Films

Strong coupling between polarization ( P ) and strain (ɛ) in ferroelectric complex oxides offers unique opportunities to dramatically tune their properties. Here colossal strain tuning of ferroelectricity in epitaxial KNbO 3 thin films grown by sub‐oxide molecular beam epitaxy is demonstrated. While bulk KNbO 3 exhibits three ferroelectric transitions and a Curie temperature ( T c ) of ≈676 K, phase‐field modeling predicts that a biaxial strain of as little as −0.6% pushes its T c > 975 K, its decomposition temperature in air, and for −1.4% strain, to T c > 1325 K, its melting point. Furthermore, a strain of −1.5% can stabilize a single phase throughout the entire temperature range of its stability. A combination of temperature‐dependent second harmonic generation measurements, synchrotron‐based X‐ray reciprocal space mapping, ferroelectric measurements, and transmission electron microscopy reveal a single tetragonal phase from 10 K to 975 K, an enhancement of ≈46% in the tetragonal phase remanent polarization ( P r ), and a ≈200% enhancement in its optical second harmonic generation coefficients over bulk values. These properties in a lead‐free system, but with properties comparable or superior to lead‐based systems, make it an attractive candidate for applications ranging from high‐temperature ferroelectric memory to cryogenic temperature quantum computing.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Reconfigurable Magnetotransport in MnBi 2 Te 4 via Gate and Magnetic Field Tuning

The intrinsic magnetic topological insulator MnBi 2 Te 4 is a promising platform for exploring quantum phases with nontrivial band topology and for enabling electrical control over coupled magnetic and electronic phase transitions. In-plane magnetic fields, in particular, offer a distinct means of tuning these properties by strengthening quantized Hall effects, enhancing surface energy gaps, and driving spin reorientation transitions. However, a systematic understanding of how such fields affect magnetotransport is limited. Here, the magnetotransport behavior of few-layer MnBi 2 Te 4 as a function of gate voltage, temperature, and magnetic field angle, with a primary focus on in-plane field effects, are investigated. A gate-tunable crossover in magnetoresistance is observed from positive to negative values under in-plane magnetic fields as the gate voltage is swept below the charge neutrality point at temperatures below the Néel temperature. The in-plane field drives a transition from the antiferromagnetic ground state to a ferromagnetic configuration with spins aligned in-plane, while simultaneously altering the electronic structure, as revealed by gate-dependent transport features. The angle-dependent measurements reveal strongly gate-tunable magnetotransport anisotropy. These results establish in-plane magnetic fields as an effective tuning parameter for modulating spin and charge transport in MnBi 2 Te 4 , advancing prospects for reconfigurable spintronic and topological devices.

MnBi 2 Te 4↗

DOE OSTI2023

Linker-Based Bandgap Tuning in Conductive MOF Solid Solutions

Herein, the synthesis of Cu 3 (HAB) x (TATHB) 2-x (HAB: hexaaminobenzene, TATHB: triaminotrihydroxybenzene) is reported. Synthetic improvement of Cu 3 (TATHB) 2 leads to a more crystalline framework with higher electrical conductivity value than previously reported. The improved crystallinity and analogous structure between TATHB and HAB enable the synthesis of Cu 3 (HAB) x (TATHB) 2-x with ligand compositions precisely controlled by precursor ratios. The electrical conductivity is tuned from 4.2 × 10 -8 to 2.9 × 10 -5 S cm -1 by simply increasing the nitrogen content in the crystal lattice. Furthermore, computational calculation supports that the solid solution facilitates the band structure tuning. In conclusion, it is envisioned that the findings not only shed light on the ligand-dependent structure–property relationship but create new prospects in synthesizing multicomponent electrically conductive metal-organic frameworks (MOFs) for tailoring optoelectronic device applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗