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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Tuning circuitry for a wireless power system

A wireless power supply power supply including first tuning circuitry coupled directly to a transmitter, the first tuning circuitry including an LCC configuration. The wireless power supply may include second tuning circuitry coupled directly to switching circuitry (e.g., an inverter) of the power supply, where the second tuning circuitry may be operable to direct power from the switching circuitry to the first tuning circuitry for supply to the transmitter, and where the second tuning circuitry includes a reactance operable to establish inductive operation of the switching circuitry at the switching frequency of the switching circuitry.

Pries, Jason L.↗
DOE OSTI2023

Experimental Validation of Models of a Hull-Based Tuned Mass Damper System for a Semisubmersible Floating Offshore Wind Turbine Platform

Floating offshore wind turbine designs can be further optimized if the controller and remaining systems are designed together, known as control co-design. To effectively perform control co-design, modeling tools predicting the influence of the control systems on the response of a system must be validated. This article presents an experimental validation that utilizes a scale model of a semisubmersible platform for an offshore wind turbine that is fitted with adjustable tuned mass dampers. These dampers can be tuned to attenuate either the hull-pitch resonance or the tower-bending resonance. The data from the experiment are used to validate state-of-the-art modeling tools. It is shown that the models capture the overall effects of the tuned mass dampers; however, some models overpredict the reduction in platform pitch motion when the dampers are tuned to the pitch resonance. The relative reduction in the tower-base bending moment is more consistently captured by the models when the dampers are tuned to the tower-bending resonance. However, there are significant differences in the absolute level of tower-base bending moment between the models and the experiment. Much of the differences observed are a consequence of the challenge with accurately predicting the baseline platform resonance motion and the tower-bending moment, which should be addressed in future modeling efforts.

17 WIND ENERGY↗
DOE OSTI2024

Assessment of fine-tuned large language models for real-world chemistry and material science applications

The current generation of large language models (LLMs) has limited chemical knowledge. Recently, it has been shown that these LLMs can learn and predict chemical properties through fine-tuning. Using natural language to train machine learning models opens doors to a wider chemical audience, as field-specific featurization techniques can be omitted. In this work, we explore the potential and limitations of this approach. We studied the performance of fine-tuning three open-source LLMs (GPT-J-6B, Llama-3.1-8B, and Mistral-7B) for a range of different chemical questions. We benchmark their performances against “traditional” machine learning models and find that, in most cases, the fine-tuning approach is superior for a simple classification problem. Depending on the size of the dataset and the type of questions, we also successfully address more sophisticated problems. The most important conclusions of this work are that, for all datasets considered, their conversion into an LLM fine-tuning training set is straightforward and that fine-tuning with even relatively small datasets leads to predictive models. These results suggest that the systematic use of LLMs to guide experiments and simulations will be a powerful technique in any research study, significantly reducing unnecessary experiments or computations.

Van Herck, Joren↗
DOE OSTI2021

Development and validation of HERWIG 7 tunes from CMS underlying-event measurements

This paper presents new sets of parameters (“tunes”) for the underlying-event model of the ${\textsc {herwig}} \,7$ event generator. These parameters control the description of multiple-parton interactions (MPI) and colour reconnection in ${\textsc {herwig}} \,7$, and are obtained from a fit to minimum-bias data collected by the CMS experiment at $\sqrt{s}=0.9$, 7, and $13 \,\text {Te}\text {V} $. The tunes are based on the NNPDF 3.1 next-to-next-to-leading-order parton distribution function (PDF) set for the parton shower, and either a leading-order or next-to-next-to-leading-order PDF set for the simulation of MPI and the beam remnants. Predictions utilizing the tunes are produced for event shape observables in electron-positron collisions, and for minimum-bias, inclusive jet, top quark pair, and Z and W boson events in proton-proton collisions, and are compared with data. Each of the new tunes describes the data at a reasonable level, and the tunes using a leading-order PDF for the simulation of MPI provide the best description of the data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

BROOD: Bilevel and Robust Optimization and Outlier Detection for Efficient Tuning of High-Energy Physics Event Generators

The parameters in Monte Carlo (MC) event generators are tuned on experimental measurements by evaluating the goodness of fit between the data and the MC predictions. The relative importance of each measurement is adjusted manually in an often time-consuming, iterative process to meet different experimental needs. In this work, we introduce several optimization formulations and algorithms with new decision criteria for streamlining and automating this process. These algorithms are designed for two formulations: bilevel optimization and robust optimization. Both formulations are applied to the datasets used in the ATLAS A14 tune and to the dedicated hadronization datasets generated by the SHERPA generator, respectively. The corresponding tuned generator parameters are compared using three metrics. We compare the quality of our automatic tunes to the published ATLAS A14 tune. Moreover, we analyze the impact of a pre-processing step that excludes data that cannot be described by the physics models used in the MC event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Paraxial, Thin-Lens Analysis of Fixed-Tune, Non-Scaling FFAs with Two Magnets per Cell

Fixed-field accelerators (FFAs) have closed orbits that change as a function of beam momentum. It is sometimes useful to avoid various resonances by keeping the tunes constant as these orbits change. A well-known example is the scaling FFA where the entire beam orbit and optics are geometrically scaled as a function of momentum. However, this is stricter than necessary: cells with three or more lenses can have fixed tunes even when the focussing strengths in the lenses change. Recently, Dejan Trbojevic has found a pair of nonlinear magnets that produce fixed tunes and fixed beta functions while not being a scaling FFA. This improves on a more approximate solution in. Notably a scaling FFA would require one magnet to be entirely reverse-bending, whereas the Trbojevic solution does not do this and instead resembles an intermediate point between the traditional scaling field profiles and the nonscaling profiles centred around a momentum with equal and positive fields. This suggests there are at least three levels of stringency that one can apply to a fixed-tune FFA design: 1. Fixed cell tunes (in both planes) as a function of momentum; 2. Fixed optics (beta functions) as a function of momentum; 3. Similarity of all orbits via a scaling symmetry law ↔ traditional scaling FFA. This note studies the interesting case #2 above (#3 being fully characterised by the orbit at a single energy) in the simplest possible example: a cell of two thin lenses in the small angle (paraxial) approximation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Accuracy optimized neural networks do not effectively model optic flow tuning in brain area MSTd

Accuracy-optimized convolutional neural networks (CNNs) have emerged as highly effective models at predicting neural responses in brain areas along the primate ventral stream, but it is largely unknown whether they effectively model neurons in the complementary primate dorsal stream. We explored how well CNNs model the optic flow tuning properties of neurons in dorsal area MSTd and we compared our results with the Non-Negative Matrix Factorization (NNMF) model, which successfully models many tuning properties of MSTd neurons. To better understand the role of computational properties in the NNMF model that give rise to optic flow tuning that resembles that of MSTd neurons, we created additional CNN model variants that implement key NNMF constraints – non-negative weights and sparse coding of optic flow. While the CNNs and NNMF models both accurately estimate the observer's self-motion from purely translational or rotational optic flow, NNMF and the CNNs with nonnegative weights yield substantially less accurate estimates than the other CNNs when tested on more complex optic flow that combines observer translation and rotation. Despite its poor accuracy, NNMF gives rise to tuning properties that align more closely with those observed in primate MSTd than any of the accuracy-optimized CNNs. This work offers a step toward a deeper understanding of the computational properties and constraints that describe the optic flow tuning of primate area MSTd.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Broad frequency tuning of a Nb$_{3}$Sn superconducting microwave cavity for dark matter searches

We demonstrate a novel broad-frequency tuning mechanism for superconducting microwave cavities designed for dark matter searches. Using a Nb$_3$Sn-coated cigar-shaped cavity operating at approximately 9 GHz, we achieve continuous frequency tuning exceeding 1 GHz by mechanically separating the two cavity halves: a "tuning-by-opening" technique. Finite-element method simulations predict that radiative losses do not degrade the quality factor even for large openings, as a closed cavity with an intrinsic quality factor of $10^7$ maintains this value for apertures up to 9 mm, corresponding to a tuning range from 9.0 to 7.5 GHz. Experimental validation using both copper ring spacers and a continuous sliding mechanism confirms $Q_0$ values exceeding the dark matter quality factor across the entire explored frequency range, despite mechanical imperfections and film non-uniformities. This tuning approach avoids inserting elements into the resonant volume, making it particularly suitable for high-Q superconducting cavities in axion haloscope experiments and readily applicable to REBCO-based implementations capable of operating in multi-tesla magnetic fields.

Maiello, D. [Padua U.; INFN, Padua] (ORCID:0009000↗
DOE OSTI2022

Chemical Tuning Meets 2D Molecular Magnets

Two-dimensional (2D) magnets provoke a surge of interest in large anisotropy in reduced dimensions and are promising for next-generation information technology where dynamic magnetic tuning is essential. Until recently, the crucial metal-organic magnet Cr(pyz) 2 ∙xLiCl∙yTHF with considerable high coercivity and high-temperature magnetic order opens up a new platform to control magnetism in metal-organic materials at room temperature. Here we report an in-situ chemical tuning route to realize the controllable transformation of low-temperature magnetic order into room-temperature hard magnetism in Cr(pyz) 2 ∙xLiCl∙yTHF. The chemical tuning via electrochemical lithiation and solvation/desolvation exhibits continuously variable magnetic features from cryogenic magnetism to the room-temperature optimum performance of coercivity (H c ) of 8500 Oe and energy product of 0.6 MGOe. Such chemically flexible tunability of room-temperature magnetism is ascribed to the different degrees of lithiation and solvation that modify the stoichiometry and Cr-pyrazine coordination framework. Furthermore, the additively manufactured hybrid magnets show air stability and electromagnetic induction, providing potential applications. Our findings here suggest chemical tuning as a universal approach to control the anisotropy and magnetism of 2D hybrid magnets at room temperature, promising for data storage, magnetic refrigeration, and spintronics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bayesian optimization of PYTHIA 8 tunes

A new tune (set of model parameters) is found for the six most important parameters of the PYTHIA 8 final state parton shower and hadronization model using Bayesian optimization. The tune fits the Large Electron-Positron collider (LEPI) data from ALEPH better than the default tune in PYTHIA 8. To the best of our knowledge, we present the most comprehensive application of Bayesian optimization to the tuning of a parton shower and hadronization model using the LEPI data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Dynamic Modeling of a Kaplan Hydroturbine Using Optimal Parametric Tuning and Real Plant Operational Data

To address grid variability caused by renewable energy integration and to maintain grid reliability and resilience, hydropower must quickly adjust its power generation over short time periods. This changing energy generation landscape requires advance technology integration and adaptive parameter optimization for hydropower systems via digital twin effort. However, this is difficult owing to the lack of characterization and modeling for the nonlinear nature of hydroturbines. To solve this issue, this paper first formulates a six-coefficient Kaplan hydroturbine model and then proposes a parametric optimization tuning framework based on the Nelder–Mead algorithm for adaptive dynamic learning of the six-coefficients so as to build models that describe the turbine. To assess the performance of the proposed optimal parametric tuning technique, operational data from a real-world Kaplan hydroturbine unit are collected and used to model the relationship between the gate opening and the generated power production. The findings show that the proposed technique can effectively and adaptively learn the unknown dynamics of the Kaplan hydroturbine while optimally tune the unknown coefficients to match the generated power output from the real hydroturbine unit with an inaccuracy of less than 5%. The method can be used to provides optimal tuning of parameters critical for controller design, operational optimization and daily maintenance for hydroturbines in general.

13 HYDRO ENERGY↗
DOE OSTI2020

Building Tune-Up Accelerator Program (Final Technical Report)

In 2016, the City of Seattle passed a mandatory Building Tune-Up requirement for all commercial buildings 50,000 square feet (SF) and larger as part of its Climate Action strategy. The requirement is phased in by size with large buildings (greater than 200,000 SF) required first. This allowed Seattle’s Office of Sustainability & Environment (OSE) to offer the Building Tune-Up Accelerator (TUA) Program to the “mid-size” building market (less than 100,000 SF) to meet the requirements early. With funding from the US DOE, a package of technical and financial support was developed for building owners and energy service providers to encourage this hard-to-reach market to participate in the tune-up—and even go beyond requirements for greater energy savings. Seattle City Light, the municipal electric utility, offered participants a simple per square foot financial incentive. Partners at the University of Washington Integrated Design Lab, Smart Buildings Center and Pacific Northwest National Lab (PNNL) offered service provider trainings, analytical tools and technical support. This final technical report summarizes the program, projected energy and emissions savings and lessons learned from program development to implementation to final evaluation for the 102 buildings that participated.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Active Tuning of Optical Constants in the Visible–UV: Praseodymium-Doped Ceria—a Model Mixed Ionic–Electronic Conductor

Mixed ionic-electronic conductors offer chemical and electrical means for active tuning of their optical constants, e.g. with variations in oxygen non-stoichiometry in Pr 0.1 Ce 0.9 O 2-δ , enabling implementation of adaptive thin film optical devices. Here, we demonstrate in-situ chemo-tuning of the extinction coefficient in Pr 0.1 Ce 0.9 O 2-δ at elevated temperatures and provide a tuning model that treats the interdependence of mobile oxygen vacancies and small polarons coupled to variations in optically active praseodymium ions. Further, a new means for electro-tuning of the optical constants of mixed ionic-electronic conductors was demonstrated experimentally and modeled for Pr 0.1 Ce 0.9 O 2-δ thin films deposited on grid-like electrode structures. Modeling of non-steady state optical transmittance modulations in the latter allows for estimation of oxygen vacancy mobility that determines the switching speed of the device. Quenched-in values of nr and k to room temperature become nonvolatile, providing a modulation range in the extinction coefficient of Δk ~0.1 (change of ~800%) and in the refractive index of Δn r ~0.1 (relative to initial n r of ~2.35). Key figures of merit including, transmission optical modulation of ~0.04 per 1 mV nm -1 , switching energy per area of 670 pJ μm -2 and switching times of seconds, were demonstrated, with further improvements possible.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Automated workflow for non-empirical Wannier-localized optimal tuning of range-separated hybrid functionals

Here, we introduce an automated workflow for generating non-empirical Wannier-localized optimally-tuned screened range-separated hybrid (WOT-SRSH) functionals. WOT-SRSH functionals have been shown to yield highly accurate fundamental band gaps, band structures, and optical spectra for bulk and 2D semiconductors and insulators. Our workflow automatically and efficiently determines the WOT-SRSH functional parameters for a given crystal structure and composition, approximately enforcing the correct screened long-range Coulomb interaction and an ionization potential ansatz. In contrast to previous manual tuning approaches, our tuning procedure relies on a new search algorithm that only requires a few hybrid functional calculations with minimal user input. We demonstrate our workflow on 23 previously studied semiconductors and insulators, reporting the same high level of accuracy. By automating the tuning process and improving its computational efficiency, the approach outlined here enables applications of the WOT-SRSH functional to compute spectroscopic and optoelectronic properties for a wide range of materials.

Gant, Stephen E. [University of California, Berkel↗
DOE OSTI2022

Short-Range Order Tunes Optical Properties in Long-Range Disordered ZnSnN2-ZnO Alloy

Local site ordering offers a new paradigm for property control in functional materials. However, systems that exhibit a propensity for local order and global disorder are often challenging to characterize, and demonstrations of ordering-induced property tuning are few and far between. Here, we demonstrate that short-range ordering tunes the optical absorption edge in the long-range disordered alloy system (ZnSnN2)1-x(ZnO)2x at x = 0.25. We use combinatorial cosputtering to synthesize a set of thin-film samples spanning this alloy space. X-ray diffraction demonstrates lattice contraction as a function of alloy composition, confirming that a mixed-anion and -cation alloy has been synthesized. Using N and O K-edge X-ray absorption near-edge structure in conjunction with simulations of cation-disordered supercell structures, we find that samples exhibit octet-rule-breaking motifs around both anions. Upon annealing at an alloy composition of x = 0.25, X-ray absorption analysis suggests that local motif structure shifts toward octet-rule-conserving while long-range disorder is maintained. Spectroscopic ellipsometry reveals that local ordering increases the absorption edge energy at constant composition. Additionally, alloy-induced optical absorption edge tuning is demonstrated. This work paves the way toward property tuning with short-range ordering in (ZnSnN2)1-x(ZnO)2x and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Custom tuning of Rieske oxygenase reactivity

Rieske oxygenases use a Rieske-type [2Fe-2S] cluster and a mononuclear iron center to initiate a range of chemical transformations. However, few details exist regarding how this catalytic scaffold can be predictively tuned to catalyze divergent reactions. Therefore, in this work, using a combination of structural analyses, as well as substrate and rational protein-based engineering campaigns, we elucidate the architectural trends that govern catalytic outcome in the Rieske monooxygenase TsaM. We identify structural features that permit a substrate to be functionalized by TsaM and pinpoint active-site residues that can be targeted to manipulate reactivity. Exploiting these findings allowed for custom tuning of TsaM reactivity: substrates are identified that support divergent TsaM-catalyzed reactions and variants are created that exclusively catalyze dioxygenation or sequential monooxygenation chemistry. Importantly, we further leverage these trends to tune the reactivity of additional monooxygenase and dioxygenase enzymes, and thereby provide strategies to custom tune Rieske oxygenase reaction outcomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Alkali-induced catalytic tuning at metal and metal oxide interfaces

Alkali metals have been recognized as effective promoters in heterogeneous catalysis, capable of enhancing catalytic activity and tuning product distributions. Over the past few decades, significant efforts have been made aiming to reveal the mechanisms underlying the promoting effect of alkalis. However, the roles that alkali metals play in the catalytic process remain elusive due to challenges in capturing their catalytic behaviours upon exposure to reactive environments. This review summarizes recent surface science and theoretical studies of alkali (potassium, cesium)-decorated metal and metal oxide model catalysts, revealing the crucial tuning by alkalis of activity and selectivity for CO 2 hydrogenation. The analysis of electronic structures identifies the selective binding mechanism of the positively charged alkali ions on the surface, being able to reduce the surface work function and lead to strong electron polarization on the surfaces. Depending on the alkali–support interaction, the deposition of alkalis can selectively modify the bindings of reaction intermediates involved in CO 2 hydrogenation via the interplay among the ionic, covalent and electrostatic tunings. As a result, CO 2 can be effectively activated and converted into diverse products at the alkali–support interface, ranging from formic acid to methanol and ethanol. The identified selective bond-tuning advances the application of alkalis in promoting catalytic activity and controlling catalytic selectivity at alkali–support interfaces.

03 NATURAL GAS↗
DOE OSTI2021

Simplified tuning of long-range corrected density functionals for use in symmetry-adapted perturbation theory

Long considered a failure, second-order symmetry-adapted perturbation theory (SAPT) based on Kohn–Sham orbitals, or SAPT0(KS), can be resurrected for semiquantitative purposes using long-range corrected density functionals whose asymptotic behavior is adjusted separately for each monomer. Here, as in other contexts, correct asymptotic behavior can be enforced via “optimal tuning” based on the ionization energy theorem of density functional theory, but the tuning procedure is tedious, expensive for large systems, and comes with a troubling dependence on system size. Here, we show that essentially identical results are obtained using a fast, convenient, and automated tuning procedure based on the size of the exchange hole. In conjunction with “extended” (X)SAPT methods that improve the description of dispersion, this procedure achieves benchmark-quality interaction energies, along with the usual SAPT energy decomposition, without the hassle of system-specific tuning.

74 ATOMIC AND MOLECULAR PHYSICS↗