Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Performance Tuning”

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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Sentiment analysis of the United States public support of nuclear power on social media using large language models

This study utilized large language models (LLMs) to analyze public sentiment in the United States (US) regarding nuclear power on social media, focusing on X/Twitter, considering climate change challenges and advancements in nuclear power technology. Approximately, 1.26 million nuclear tweets from 2008–2023 were examined to fine-tune LLMs for sentiment classification. We found the crucial role of accurate data labeling for model performance, with potential implications for a 15% improvement, achieved through high-confidence labels. LLMs demonstrated better performance compared to traditional machine learning classifiers, with reduced susceptibility to overfitting and up to 96% classification accuracy. LLMs are used to segment the US public tweets into policy and energy-related categories, revealing that 68% are politically themed. Policy tweets tended to convey negative sentiment, often reflecting opposing political perspectives and focusing on nuclear deals and international relations. Energy-related tweets covered diverse topics with predominantly neutral to positive sentiment, indicating broad support for nuclear power in 48 out of 50 US states. The US public positive sentiments toward nuclear power stemmed from its high power density, reliability regardless of weather conditions, environmental benefits, application versatility, and recent innovations and advancements in both fission and fusion technologies. Negative sentiments primarily focused on waste management, high capital costs, and safety concerns. The neutral campaign highlighted global nuclear facts and advancements, with varying tones leaning towards positivity or negativity. An interesting neutral theme was the advocacy for the combined use of renewable and nuclear energy to attain net-zero goals.

Energy & Fuels↗
DOE OSTI2024

On the evaluation and selection of network-level traffic control policies: Perimeter control, TUC, and their combination

Perimeter control (PC) of urban traffic networks can be effective in increasing network-wide efficiency. PC operates on the border of a protected region of a traffic network. Most studies thus far considered fixed-time plans for the inner part of these regions. A few studies have shown that combining PC with locally actuated or decentralized traffic control systems may have positive effects on traffic performance, including better-defined Network Macroscopic Fundamental Diagrams (NMFDs), increased network throughput, and reduced delays. The Traffic-responsive Urban Control (TUC) is a real-time network-wide traffic control system with particular design characteristics, such as the balancing of link's occupancies and an inherent gating feature. These characteristics suggest that TUC may enhance the traffic network performance when combined with PC whilst improving the resulting NMFDs and network throughput and delays. Here, in this work, we investigate the effect of feedback perimeter control (FPC), TUC, and their combination on the NMFD and on the traffic conditions of general traffic and public transport in the microsimulation of a realistic model of the Christchurch Central Business District in New Zealand. We perform a thorough investigation of practical aspects of both control strategies and their combination, including parameter tuning and infrastructure requirements, and how they may affect the control system choice. Results show higher throughput and less hysteresis on the NMFDs, particularly when TUC is involved. PC provides benefits concentrated in the protected region which can greatly benefit public transportation if there is an overlap with the transit network. The combination of TUC and FPC boosts network-wide throughput.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Towards an astronomical foundation model for stars with a transformer-based model

ABSTRACT Rapid strides are currently being made in the field of artificial intelligence using transformer-based models like Large Language Models (LLMs). The potential of these methods for creating a single, large, versatile model in astronomy has not yet been explored. In this work, we propose a framework for data-driven astronomy that uses the same core techniques and architecture as used by LLMs. Using a variety of observations and labels of stars as an example, we build a transformer-based model and train it in a self-supervised manner with cross-survey data sets to perform a variety of inference tasks. In particular, we demonstrate that a single model can perform both discriminative and generative tasks even if the model was not trained or fine-tuned to do any specific task. For example, on the discriminative task of deriving stellar parameters from Gaia XP spectra, we achieve an accuracy of 47 K in Teff, 0.11 dex in log g, and 0.07 dex in [M/H], outperforming an expert XGBoost model in the same setting. But the same model can also generate XP spectra from stellar parameters, inpaint unobserved spectral regions, extract empirical stellar loci, and even determine the interstellar extinction curve. Our framework demonstrates that building and training a single foundation model without fine-tuning using data and parameters from multiple surveys to predict unmeasured observations and parameters is well within reach. Such ‘Large Astronomy Models’ trained on large quantities of observational data will play a large role in the analysis of current and future large surveys.

Leung, Henry W. (ORCID:0000000200362752)↗
DOE OSTI2021

Phase coexistence at the first-order Mott transition revealed by pressure-dependent dielectric spectroscopy of κ - (BEDT-TTF) 2 - Cu 2 (CN) 3

The dimer Mott insulator kappa - (BEDT-TTF) 2 - Cu 2 (CN) 3 can be tuned into metallic and superconducting states on applying pressure of 1.5 kbar and more. We have performed dielectric measurements (7.5 kHz to 5 MHz) on kappa - (BEDT-TTF) 2 - Cu 2 (CN) 3 single crystals as a function of temperature (down to T = 8 K) and pressure (up to p = 4.3 kbar). In addition to the relaxor-like dielectric behavior seen below 50 K at p = 0, that moves toward lower temperatures with pressure, a second peak emerges in ε 1 (T) around T = 15 K. When approaching the insulator-metal boundary, this peak diverges rapidly reaching ε 1 ≈ 10 5 . Our dynamical mean-field theory calculations substantiate that the dielectric catastrophe at the Mott transition is not caused by closing the energy gap, but due to the spatial coexistence of correlated metallic and insulating regions. We discuss the percolative nature of the first-order Mott insulator-to-metal transition in all details.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Field Harmonic Measurement of High-Gradient Permanent Magnet Quadrupoles for NSLS- II Upgrade

The National Synchrotron Light Source II (NSLS-II) is preparing for a major upgrade based on a new lattice concept, known as “Complex Bend,” to replace its existing double bend achromat (DBA) lattice. Here, this novel lattice will use high-gradient permanent magnet quadrupoles (PMQs) with small apertures in the range of 16–22 mm. A prototype complex bend branch with PMQs has been installed in the NSLS-II linac to evaluate the lattice's performance. An accurate and precise magnetic measurement system is required for field harmonic characterization and magnetic tuning of these PMQs. As part of this project a Rotating-Coil bench, based on a Printed Circuit Board (PCB) coil with a 12 mm diameter, has been configured to measure nine PMQs with bore diameter of 12.7 mm. This PCB coil has an active length of 270 mm, and is able to measure fields up to the 15th harmonic of the main field at a reference radius of 5 mm, while maintaining field quality levels within 10 ppm of the main field. This article presents the PCB coil setup, the harmonic measurement results and their temperature dependencies and repeatability. Simulation results on compensation of undesired multipoles using “IDBuilder”, a genetic algorithm-based optimizer code for magnetic tuning is included for field harmonic corrections.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An Applied Strategy for Using Empirical and Hybrid Models in Online Monitoring

The monitoring of plant equipment for failure prediction is one of the key contributors to operation and maintenance (O&M) costs for a nuclear power plant (NPP) because O&M monitoring depends on labor-intensive activities that are required to meet high equipment reliability standards. These activities rely primarily on humans for information gathering, condition diagnosis, and predictive analysis. Online monitoring aims to automate these activities by relying on sensors to replace human information gathering and machine learning to replace human analysis and decision making. To facilitate automated monitoring, a systematic strategy for anomaly detection is needed to optimally use the available sensor data, empirical models, and physics-supported models. This strategy is essential to provide credible reasoning on why and when an empirical (i.e., purely data-driven) versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. The extant methods usually adopt an ad hoc trial-and-error approach that, in addition to being time-consuming and costly, is also highly subjective; it is impacted by the background and the skill set of the personnel making the decisions. Thus, such an approach cannot guarantee an optimum outcome. This represents the motivation of the current research effort, which is focused on devising a scientifically supported strategy for the optimum selection of anomaly detection methods. This report presents a detailed assessment of the main anomaly detection techniques within the empirical or hybrid method streams. Empirical methods include pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The listed techniques within these two streams represent the vast majority of techniques performed for anomaly detection. Using the techniques as outcomes, a strategy was developed to enable a systematic decision-making process to lead to one of these techniques. The strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability and suitability for training and testing, cause-effect, entropy inference, and model fitting. Each of these decision points in the strategy is explained in detail in this report with examples, along with the scientific basis behind the decisions and outcomes in common and simplified terminology. The strategy is developed for use by any NPP staff with basic engineering or science knowledge. A user-friendly graphical state flow diagram was also developed as a visual presentation of the strategy. The strategy was tested and demonstrated through two pilot projects for the application of anomaly detection at an NPP. Each pilot had two use cases: an initial case in which certain decisions were made that resulted in one or more empirical techniques and a revised use case where one or more key decisions were modified resulting in using a set of hybrid methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1985

The superconducting cavity stability ruby maser oscillator

Analysis of an application of the rudy maser to a superconducting Cavity Stabilized oscillator shows many attractive features. These derive from the mechancial stability inherent in an all-cryogenic design and from the properties of the ruby maser itself. A multiple-cavity design has been developed to allow physical separation of the high-Q superconducting cavity and the ruby element with its requried applied magnetic field. Mode selection is accomplished in this design by tuning the ruby by means of the applied field. We conclude that such an oscillator would perform well, even with cavity Q's as low as 10 to the 8th power allowing the use of a superconductor-on-sapphire resonator with its greater rigidity and lower thermal expansion. A first test of the Superconducting Cavity Stabilized Maser Oscillator (SCSMO) confirms the efficacy of the multiple-cavity design and the applicability of the ruby maser. Frequency variation less than 4x10 to the minus 11th power was measured in the stabilized mode and is attributed to the reference oscillator and to instabilities in the pump source. Variation of 10 to the minus 10th power was observed in the low-Q unstabilized mode, again attributable to pump fluctuations. Even so, direct scaling to a Q of 10 the 9th power predicts a stability better than 10 to the minus 15th power. Together with results showing the lowest losses to date in sapphire at microwave frequencies, and preliminary experiments on superconductor-on-sapphire resonators, frequency stability, levels as low as 10 to the minus 17th power are indicated.

Dick, G. J.↗
NASA NTRS1984

A simplified GPS C/A reciever front end with low noise performance

A redesign of the antenna electronics package for the NBS/GPS C/A receiver has resulted in significantly reduced cost and improved performance. Major improvements include a simplified and more reliable multiplier/mixer, elimination of all twelve piston trimmer tuning capacitors in the original design, elimination of expensive bandpass filters, less expensive antenna and a simplified packaging scheme.

Davis, D. D.↗
NASA NTRS2004

Theoretical Evaluation of Electroactive Polymer Based Micropump Diaphragm for Air Flow Control

An electroactive polymer (EAP), high energy electron irradiated poly(vinylidene fluoride-trifluoroethylene) [P(VDFTrFE)] copolymer, based actuation micropump diaphragm (PAMPD) have been developed for air flow control. The displacement strokes and profiles as a function of amplifier and frequency of electric field have been characterized. The volume stroke rates (volume rate) as function of electric field, driving frequency have been theoretically evaluated, too. The PAMPD exhibits high volume rate. It is easily tuned with varying of either amplitude or frequency of the applied electric field. In addition, the performance of the diaphragms were modeled and the agreement between the modeling results and experimental data confirms that the response of the diaphragms follow the design parameters. The results demonstrated that the diaphragm can fit some future aerospace applications to replace the traditional complex mechanical systems, increase the control capability and reduce the weight of the future air dynamic control systems. KEYWORDS: Electroactive polymer (EAP), micropump, diaphragm, actuation, displacement, volume rate, pumping speed, clamping ratio.

Xu, Tian-Bing↗
NASA NTRS2009

Request for Information Response for the Flight Validation of Adaptive Control to Prevent Loss-of-Control Events. Overview of RFI Responses

Adaptive control should be integrated with a baseline controller and only used when necessary (5 responses). Implementation as an emergency system. Immediately re-stabilize and return to controlled flight. Forced perturbation (excitation) for fine-tuning system a) Check margins; b) Develop requirements for amplitude of excitation. Adaptive system can improve performance by eating into margin constraints imposed on the non-adaptive system. Nonlinear effects due to multi-string voting.

Bosworth, John T.↗
NASA NTRS2015

NASA Space Laser Technology

Over the next two decades, the number of space based laser missions for mapping, spectroscopy, remote sensing and other scientific investigations will increase several fold. The demand for high wall-plug efficiency, low noise, narrow linewidth laser systems to meet different systems requirements that can reliably operate over the life of a mission will be high. The general trends will be for spatial quality very close to the diffraction limit, improved spectral performance, increased wall-plug efficiency and multi-beam processing. Improved spectral performance will include narrower spectral width (very near the transform limit), increased wavelength stability and or tuning (depending on application) and lasers reaching a wider range of wavelengths stretching into the mid-infrared and the near ultraviolet. We are actively developing high efficiency laser transmitter and high-sensitivity laser receiver systems that are suitable for spaceborne applications.

Electro-Optics↗
DOE OSTI2020

A Learning-based Supervisory Control Architecture for Electric Vehicle Charging System Paired with Energy Storages

A Machine Learning-based predictive model is developed for optimal dispatching energy storage system integrated with Electric Vehicle battery charger. The model is effectively trained using transfer learning algorithm and successfully validated via measurement data to achieve high fidelity and accuracy. The study findings provide possibilities for future development of the presented approach to implement computational heavy predictive algorithms with multi-step predictions in emerging modular bidirectional charger topologies to realize vehicle-to-grid (V2G) technology. The online tuning can be explored using the new measurements obtained during the operation, henceforth, enhancing the controller performance for integrating multiple DERs into distribution power networks that shows huge interest for the utilities and regulatory agencies. Multiple operation scenatios have been evaluated and simulation results are discussed to verify intended performance of the proposed control solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding

Quantum computing calibration depends on interpreting experimental data, and calibration plots provide the most universal human-readable representation for this task, yet no systematic evaluation exists of how well vision-language models (VLMs) interpret them. We introduce QCalEval, the first VLM benchmark for quantum calibration plots: 243 samples across 87 scenario types from 22 experiment families, spanning superconducting qubits and neutral atoms, evaluated on six question types in both zero-shot and in-context learning settings. The best general-purpose zero-shot model reaches a mean score of 72.3, and many open-weight models degrade under multi-image in-context learning, whereas frontier closed models improve substantially. A supervised fine-tuning ablation at the 9-billion-parameter scale shows that SFT improves zero-shot performance but cannot close the multimodal in-context learning gap. As a reference case study, we release NVIDIA Ising Calibration 1, an open-weight model based on Qwen3.5-35B-A3B that reaches 74.7 zero-shot average score.

Cao, Shuxiang↗
DOE OSTI2020

The effect of lighting environment on task performance in buildings – A review

The effects of indoor environmental conditions on human health, satisfaction, and performance have been the focal point of research for decades. This paper reviews and summarizes the impact of lighting environment on task performance, specifically for the built environment audience. Existing studies included a variety of performance tests on cognitive performance and perception, visual acuity and reaction, memory, reasoning, and labor productivity. Illuminance, luminance ratio and correlated color temperature were found to affect performance in different ways, reflecting the impact of experimental techniques, conditions, performance evaluation methods used and data analysis methods. These were reviewed and categorized, with discussion on limitations related to sample size, modeling approach, carryover effects and other factors affecting individual differences in performance, with recommendations for future improvement. Although no universal conclusions can be made, in general, task performance seems to improve with higher illuminances, contrast ratios in the range of 7–11:1 (while always making sure that glare will not occur in the space) and higher correlated color temperature, while spectral tuning in the red or blue wavelengths has also shown positive effects. To obtain more generic evidence, future studies should be more consistent in terms of experimental procedures and overall light conditions, and also consider the effects of vertical illuminance, daylight provision/control, and outside views on task performance. Finally, studying performance with multi-factorial designs in a human-centered optimized manner (such as deploying variable lighting scenarios optimized for various tasks) can lead to deeper understanding of lighting effects on task performance, and ultimately to improved lighting design and operation in buildings overall.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Approaching the Strain-Free Limit in Ultrathin Nanomechanical Resonators

Ultrathin mechanical structures are ideal building platforms to pursue the ultimate limit of nanomechanical resonators for applications in sensing, signal processing, and quantum physics. Unfortunately, as the thickness of the vibrating structures is reduced, the built-in strain of the structural materials plays an increased role in determining the mechanical performance of the devices. As a consequence, it is very challenging to fabricate resonators working in the modulus-dominant regime, where their dynamic behavior is exclusively determined by the device geometry. In this Letter, we report ultrathin doubly clamped nanomechanical resonators with aspect ratios as large as L/t similar to 5000 and working in the modulus-dominant regime. Here, we observed room temperature thermomechanically induced motion of multiple vibration modes with resonant frequencies closely matching the predicted values of Euler-Bernoulli beam theory under an axial strain of 6.3 x 10 -8 . The low strain of the devices enables a record frequency tuning ratio of more than 50 times. These results illustrate a new strategy for the quantitative design of nanomechanical resonators with unprecedented performance.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRSDate not supplied

Maximum-Likelihood Parameter Estimation for High-Contrast Wavefront Sensing & Control

Stellar coronagraphs use closed-loop focal-plane wavefront sensing and control algorithms to create high-contrast dark zones suitable for imaging exoplanets and exozodiacal dust clouds around nearby stars. At present, the deepest contrast has been achieved using model-based algorithms, which use the predicted focal-plane influence of the coronagraph's deformable mirrors to drive diffracted starlight toward zero over time in an optimal control framework. However, model-based algorithms are susceptible to model mismatch, wherein a departure of the coronagraph's true optical characteristics from the model predictions causes reduced control loop performance. Here, we report on a technique for maximum-likelihood estimation of the wavefront control Jacobian matrix and noise statistics of the coronagraph focal-plane electric field from data acquired in situ during closed-loop wavefront control operations. By empirically tuning the Jacobian and noise properties in a statistically rigorous fashion, the maximum-likelihood approach mitigates model mismatch and recovers near-optimal control loop performance.

coronagraphy↗
DOE OSTI2026

Electrochemical dynamics of imidazolium ionic liquids at graphene electrodes for energy storage applications

Electric double layer capacitors (EDLCs) are prominent energy storage systems that constitute the foundation of more reliable and sustainable energy infrastructures. Modern EDLCs often incorporate ionic liquids (ILs) as a key component in their electrolytes, leveraging the high electrochemical stability of ILs to enhance device performance. The performance and functionality of these capacitors also hinge on the interfacial behavior of ILs at electrode surfaces, which remain insufficiently understood. Here, we performed synchrotron infrared nanospectroscopy (SINS) in combination with density functional theory (DFT) calculations to investigate the electric double layers (EDLs) of three imidazolium-based ILs in a custom-designed graphene liquid cell. This approach revealed new insights into the dynamics of IL EDLs and the underpinning factors originating from the IL structures. Variations in anion size and structure were found to tune the ILs’ ability to form EDLs with compact and closely-correlated ion arrangements, which are critical for enhancing their capacitive performance. These findings highlight the intricate interactions between ions governed by their structures and charge behaviors, which underscores the opportunities for targeted design of IL-based electrolytes to optimize EDLC functionality.

Electric double layers↗