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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.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Applying Acoustic Emission to Large Format Additive Manufacturing

Large format additive manufacturing (AM) is being adapted as a method of producing large structures in a short lead time and cost-effective way. With the growing advancement in AM techniques and application, machine monitoring and part qualification is highly needed. There has been leading research focused on the manufacturing development and feedstock material but minimum research on the structural health monitoring (SHM), defect detection, and nondestructive evaluation (NDE) for large format AM. Scanning large structure using conventional nondestructive testing (NDT) techniques, such as ultrasound or X-ray, and searching for potential defects can be very time consuming, challenging and cost prohibitive. Acoustic emission (AE) is a passive technique that can be used to monitor and locate defect progression in large structures by distributing group of sensors around the part. This research outlines the necessary procedure for implementing AE to AM as a reliability method. The topics this research will display are: (a) Wave propagation/velocity evaluation, (b) an AE attenuation characterization for the anisotropic printed structure and material, (c) background noise measurements of the extruder and gantry system, and (d) assist in optimal sensor selection and placement for monitoring large AM structures with demonstration. This work establishes the foundation for scaling up the SHM-AE system for the large additive platform.

Spencer, Ryan↗
DOE OSTI2021

ACCRUE—An Integral Index for Measuring Experimental Relevance in Support of Neutronic Model Validation

A key challenge for the introduction of any design changes, e.g., advanced fuel concepts, first-of-a-kind nuclear reactor designs, etc., is the cost of the associated experiments, which are required by law to validate the use of computer models for the various stages, starting from conceptual design, to deployment, licensing, operation, and safety. To achieve that, a criterion is needed to decide on whether a given experiment, past or planned, is relevant to the application of interest. This allows the analyst to select the best experiments for the given application leading to the highest measures of confidence for the computer model predictions. The state-of-the-art methods rely on the concept of similarity or representativity, which is a linear Gaussian-based inner-product metric measuring the angle—as weighted by a prior model parameters covariance matrix—between two gradients, one representing the application and the other a single validation experiment. This manuscript emphasizes the concept of experimental relevance which extends the basic similarity index to account for the value accrued from past experiments and the associated experimental uncertainties, both currently missing from the extant similarity methods. Accounting for multiple experiments is key to the overall experimental cost reduction by prescreening for redundant information from multiple equally-relevant experiments as measured by the basic similarity index. Accounting for experimental uncertainties is also important as it allows one to select between two different experimental setups, thus providing for a quantitative basis for sensor selection and optimization. The proposed metric is denoted by ACCRUE, short for Accumulative Correlation Coefficient for Relevance of Uncertainties in Experimental validation. Using a number of criticality experiments for highly enriched fast metal systems and low enriched thermal compound systems with accident tolerant fuel concept, the manuscript will compare the performance of the ACCRUE and basic similarity indices for prioritizing the relevance of a group of experiments to the given application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Quantitative and Predictive Genetic Parts for Plant Synthetic Biology

Plant synthetic biology aims to harness the natural abilities of plants and to turn them to new purposes. A primary goal of plant synthetic biology is to produce predictable and programmable genetic circuits from simple regulatory elements and well-characterized genetic components. The number of available DNA parts for plants is increasing, and the methods for rapid quantitative characterization are being developed, but the field of plant synthetic biology is still in its early stages. We here describe methods used to describe the quantitative properties of genetic components needed for plant synthetic biology. Once the quantitative properties and transfer function of a variety of genetic parts are known, computers can select the optimal components to assemble into functional devices, such as toggle switches and positive feedback circuits. However, while the variety of circuits and traits that can be put into plants are limitless, doing synthetic biology in plants poses unique challenges. Plants are composed of differentiated cells and tissues, each representing potentially unique regulatory or developmental contexts to introduced synthetic genetic circuits. Further, plants have evolved to be highly sensitive to environmental influences, such as light or temperature, any of which can affect the quantitative function of individual parts or whole circuits. Measuring the function of plant components within the context of a plant cell and, ideally, in a living plant, will be essential to using these components in gene circuits with predictable function. Mathematical modeling will be needed to account for the variety of contexts a genetic part will experience in different plant tissues or environments. With such understanding in hand, it may be possible to redesign plant traits to serve human and environmental needs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The Effects of Herbarium Specimen Characteristics on Short-Read NGS Sequencing Success in Nearly 8000 Specimens: Old, Degraded Samples Have Lower DNA Yields but Consistent Sequencing Success

Phylogenetic datasets are now commonly generated using short-read sequencing technologies unhampered by degraded DNA, such as that often extracted from herbarium specimens. The compatibility of these methods with herbarium specimens has precipitated an increase in broad sampling of herbarium specimens for inclusion in phylogenetic studies. Understanding which sample characteristics are predictive of sequencing success can guide researchers in the selection of tissues and specimens most likely to yield good results. Multiple recent studies have considered the relationship between sample characteristics and DNA yield and sequence capture success. Here we report an analysis of the relationship between sample characteristics and sequencing success for nearly 8,000 herbarium specimens. This study, the largest of its kind, is also the first to include a measure of specimen quality (“greenness”) as a predictor of DNA sequencing success. We found that taxonomic group and source herbarium are strong predictors of both DNA yield and sequencing success and that the most important specimen characteristics for predicting success differ for DNA yield and sequencing: greenness was the strongest predictor of DNA yield, and age was the strongest predictor of proportion-on-target reads recovered. Surprisingly, the relationship between age and proportion-on-target reads is the inverse of expectations; older specimens performed slightly better in our capture-based protocols. We also found that DNA yield itself is not a strong predictor of sequencing success. Most literature on DNA sequencing from herbarium specimens considers specimen selection for optimal DNA extraction success, which we find to be an inappropriate metric for predicting success using next-generation sequencing technologies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability

Tracking vital signs accurately is critical for triaging a patient and ensuring timely therapeutic intervention. The patient’s status is often clouded by compensatory mechanisms that can mask injury severity. The compensatory reserve measurement (CRM) is a triaging tool derived from an arterial waveform that has been shown to allow for earlier detection of hemorrhagic shock. However, the deep-learning artificial neural networks developed for its estimation do not explain how specific arterial waveform elements lead to predicting CRM due to the large number of parameters needed to tune these models. Alternatively, we investigate how classical machine-learning models driven by specific features extracted from the arterial waveform can be used to estimate CRM. More than 50 features were extracted from human arterial blood pressure data sets collected during simulated hypovolemic shock resulting from exposure to progressive levels of lower body negative pressure. A bagged decision tree design using the ten most significant features was selected as optimal for CRM estimation. This resulted in an average root mean squared error in all test data of 0.171, similar to the error for a deep-learning CRM algorithm at 0.159. By separating the dataset into sub-groups based on the severity of simulated hypovolemic shock withstood, large subject variability was observed, and the key features identified for these sub-groups differed. This methodology could allow for the identification of unique features and machine-learning models to differentiate individuals with good compensatory mechanisms against hypovolemia from those that might be poor compensators, leading to improved triage of trauma patients and ultimately enhancing military and emergency medicine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Spatiotemporal Variability in Wind Turbine Blade Leading Edge Erosion

Wind turbine blade leading edge erosion (LEE) reduces energy production and increases wind energy operation and maintenance costs. Degradation of the blade coating and ultimately damage to the underlying blade structure are caused by collisions of falling hydrometeors with rotating blades. The selection of optimal methods to mitigate/reduce LEE are critically dependent on the rates of coating fatigue accumulation at a given location and the time variance in the accumulation of material stresses. However, no such assessment currently exists for the United States of America (USA). To address this research gap, blade coating lifetimes at 883 sites across the USA are generated based on high-frequency (5-min) estimates of material fatigue derived using a mechanistic model and robust meteorological measurements. Results indicate blade coating failure at some sites in as few as 4 years, and that the frequency and intensity of material stresses are both highly episodic and spatially varying. Time series analyses indicate that up to one-third of blade coating lifetime is exhausted in just 360 5-min periods in the Southern Great Plains (SGP). Conversely, sites in the Pacific Northwest (PNW) exhibit the same level of coating lifetime depletion in over three times as many time periods. Thus, it may be more cost-effective to use wind turbine deregulation (erosion-safe mode) for damage reduction and blade lifetime extension in the SGP, while the application of blade leading edge protective measures may be more appropriate in the PNW. Annual total precipitation and mean wind speed are shown to be poor predictors of blade coating lifetime, re-emphasizing the need for detailed modeling studies such as that presented herein.

Pryor, Sara C. (ORCID:0000000348473440)↗
DOE OSTI2025

Time Synchronization Techniques in the Modern Smart Grid: A Comprehensive Survey

In modern smart grids, accurate and synchronized time signals are essential for effective monitoring, protection, and control. Various time synchronization methods exist, each tailored to specific application needs. Widely adopted solutions, such as GPS, however, are vulnerable to challenges such as signal loss and cyber-attacks, underscoring the need for reliable backup or supplementary solutions. This paper examines the timing requirements across different power grid applications and provides a comprehensive review of available time synchronization mechanisms. Through a comparative analysis of timing methods based on accuracy, flexibility, reliability, and security, this study offers insights to guide the selection of optimal solutions for seamless grid integration.

comparison↗
DOE OSTI2024

Investigation of Fe-Ni Battery/Module for Grid Service Duty Cycles

Iron–nickel (Fe-Ni) batteries are renowned for their durability and resilience against overcharging and operating temperatures. However, they encounter challenges in achieving widespread adoption for energy storage applications due to their low efficiency and the need for regular maintenance and electrolyte replacement, which adds to maintenance costs. This study evaluates and demonstrates the capabilities of Fe-Ni batteries for participating in grid energy storage applications. Stable performance was observed frequency regulation (FR) testing at 100% and 50% state of charge (SOC)s, while at 50% SOC, there was a 14% increase in efficiency compared to 100% SOC. Although 25% SOC achieved higher efficiency, limited cyclability was observed due to reaching the discharge cutoff voltage. Optimal SOC selection, battery monitoring, maintenance, and appropriate charging strategies of Fe-Ni batteries seem to be crucial for their FR applications. Fe-Ni batteries exhibit stable peak shaving (PS) results, indicating their suitability and reliability under various load conditions for PS testing. Extended cycling tests confirm their potential for long-term grid-scale energy storage, enhancing their appeal for PS and FR applications.

25 ENERGY STORAGE↗
DOE OSTI2021

Studying Corrosion Using Miniaturized Particle Attached Working Electrodes and the Nafion Membrane

We developed a new approach to attach particles onto a conductive layer as a working electrode (WE) in a microfluidic electrochemical cell with three electrodes. Nafion, an efficient proton transfer molecule, is used to form a thin protection layer to secure particle electrodes. Spin coating is used to develop a thin and even layer of Nafion membrane. The effects of Nafion (5 wt% 20 wt%) and spinning rates were evaluated using multiple sets of replicates. The electrochemical performance of various devices was demonstrated. Additionally, the electrochemical performance of the devices is used to select and optimize fabrication conditions. The results show that a higher spinning rate and a lower Nafion concentration (5 wt%) induce a better performance, using cerium oxide (CeO2) particles as a testing model. The WE surfaces were characterized using atomic force microscopy (AFM), scanning electron microscopy-focused ion beam (SEM-FIB), time-of-flight secondary ion mass spectrometry (ToF-SIMS), and X-ray photoelectron spectroscopy (XPS). The comparison between the pristine and corroded WE surfaces shows that Nafion is redistributed after potential is applied. Our results verify that Nafion membrane offers a reliable means to secure particles onto electrodes. Furthermore, the electrochemical performance is reliable and reproducible. Thus, this approach provides a new way to study more complex and challenging particles, such as uranium oxide, in the future.

42 ENGINEERING↗
DOE OSTI2023

Development of a Machine-Learned Cruise Guide Indicator for Rotorcraft

This paper presents a machine-learned virtual cruise guide indicator (vCGI) for Chinook helicopters. Two temporal neural networks were trained and evaluated on measured data from 55 flight tests, one for the fore rotor and another for the aft rotor, to predict a vCGI value, which protects 23 components from fatigue damage during steady-state conditions. Three different classes of machine learning architectures were evaluated for prediction of the vCGI from time sequences: a temporal convolutional neural network with 1D dilated causal convolutions, a long short-term memory recurrent neural network, and an attention-based transformer architecture. The final average model accuracy on unseen flight data is currently greater than 93% for CGI values which could result in fatigue damage and 90% for normal operation CGI values. Model accuracy was improved through a series of advancements in:(1) selection of optimal training data using temporal collective variables and unsupervised learning, (2) dataset augmentation with maximum-entropy temporal collective variables, and (3) implementation of a mixture-of-experts classification- regression approach using an adversarial classification approach to assign maneuver labels. The results are presented for each advancement in model development along with lessons learned in training machine learning models on real- world, time-dependent rotorcraft data.

Boyer, Mathew↗
DOE OSTI2025

Correlating Superconducting Qubit Performance Losses to Sidewall Near-Field Scattering via Terahertz Nanophotonics

Elucidating dielectric losses, structural heterogeneity, and interface imperfections is critical for improving coherence in superconducting qubits. However, most diagnostics rely on destructive electron microscopy or low-throughput millikelvin quantum measurements. Here, we demonstrate noninvasive terahertz (THz) nano-imaging/-spectroscopy of encapsulated niobium transmon qubits, revealing sidewall near-field scattering that correlates with qubit coherence. We further employ a THz hyperspectral line scan to probe dielectric responses and field participation at Al junction interfaces. These findings highlight the promise of THz near-field methods as a high-throughput proxy characterization tool for guiding material selection and optimizing processing protocols to improve qubit and quantum circuit performance.

Kim, Richard H.J. [Ames Lab]↗
DOE OSTI2019

Bayesian performance evaluation of evapotranspiration models based on eddy covariance systems in an arid region

Abstract. Evapotranspiration (ET) is a major component of the land surface processinvolved in energy fluxes and energy balance, especially in the hydrologicalcycle of agricultural ecosystems. While many models have been developed aspowerful tools to simulate ET, there is no agreement on which model bestdescribes the loss of water to the atmosphere. This study focuses on twoaspects, evaluating the performance of four widely used ET models andidentifying parameters, and the physical mechanisms that havesignificant impacts on the model performance. The four tested models arethe Shuttleworth–Wallace (SW) model, Penman–Monteith (PM) model,Priestley–Taylor and Flint–Childs (PT–FC) model, and advection–aridity (AA)model. By incorporating the mathematically rigorous thermodynamicintegration algorithm, the Bayesian model evidence (BME) approach is adoptedto select the optimal model with half-hourly ET observations obtained at aspring maize field in an arid region. Our results reveal that the SW model has thebest performance, and the extinction coefficient is not merely partitioningthe total available energy into the canopy and surface but also includingthe energy imbalance correction. The extinction coefficient is wellconstrained in the SW model and poorly constrained in the PM model but notconsidered in PT–FC and AA models. This is one of the main reasons that theSW model outperforms the other models. Meanwhile, the good fitting of SWmodel to observations can counterbalance its higher complexity. In addition,the detailed analysis of the discrepancies between observations and modelsimulations during the crop growth season indicate that explicit treatmentof energy imbalance and energy interaction will be the primary way offurther improving ET model performance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Search for heavy resonances decaying into two Higgs bosons or into a Higgs boson and a W or Z boson in proton-proton collisions at 13 TeV

A search is presented for massive narrow resonances decaying either into two Higgs bosons, or into a Higgs boson and a W or Z boson. The decay channels considered are HH$\to \mathrm{b\overline{b}}\tau^{+}\tau^{-}$ and VH$ \to \mathrm{q\overline{q}}\tau^{+}\tau^{-}$, where H denotes the Higgs boson, and V denotes the W or Z boson. This analysis is based on a data sample of proton-proton collisions collected at a center-of-mass energy of 13 TeV by the CMS Collaboration, corresponding to an integrated luminosity of 35.9 fb$^{-1}$. For the TeV-scale mass resonances considered, substructure techniques provide ways to differentiate among the hadronization products from vector boson decays to quarks, Higgs boson decays to bottom quarks, and quark- or gluon-induced jets. Reconstruction techniques are used that have been specifically optimized to select events in which the tau lepton pair is highly boosted. The observed data are consistent with standard model expectations and upper limits are set at 95% confidence level on the product of cross section and branching fraction for resonance masses between 0.9 and 4.0 TeV. Exclusion limits are set in the context of bulk radion and graviton models: spin-0 radion resonances are excluded below a mass of 2.7 TeV at 95% confidence level. In the spin-1 heavy vector triplet framework, mass-degenerate W' and Z' resonances with dominant couplings to the standard model gauge bosons are excluded below a mass of 2.8 TeV at 95% confidence level. There are the first limits for these decay channels at $\sqrt{s}=$ 13 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

PERFORMANCE MODELING OF A NOVEL “SMART” MAGNETIC PARTICLE-EMBEDDED PCM LAYER FOR THERMAL MANAGEMENT SYSTEMS

Developing stable and environmentally friendly phase change materials (PCM) has been an active area of research due to many applications, such as industrial energy storage system, cooling/heating applications in buildings, and thermal management for electronics equipment as well as for batteries and photovoltaic modules. However, previous studies confirmed that most PCMs suffer a serious disadvantage of low thermal conductivity. A novel design of PCM layer is investigated here for thermal management application. The novel PCM layer is comprised of a PCM and magnetic particles coated on the shell. When a magnetic field is applied in the thermal management system, due to the magnetic of the particles, PCM layer are attached to the heat source to absorb heat, which significantly improves the heat transfer between PCM and the heat source. The melting temperature of the PCM and Curie temperature of the magnetic particles are carefully selected to optimize the performance and to ensure materials compatibility. A numerical study is conducted to reveal the heat transfer and performance improvement of the PCM layer comparing to the conventional PCMs.

Zhang, Mingkan↗
DOE OSTI2018

CRITERIA FOR COMPARATIVE EVALUATIONS OF TREATY VERIFICATION MONITORING SYSTEMS

In 2017, a team of subject matter experts from across the U.S. Department of Energy (DOE) national laboratory developed a framework to assess and compare monitoring systems implemented to support treaty verification. Drawing on principles and techniques from multi-criteria decision making, the project team developed a set of evaluation criteria to serve as a decision support tool to understand and evaluate competing options. These criteria, which focus on monitoring systems designed to maintain chain of custody, were developed to be unambiguous, independent from each other, collectively exhaustive, measurable (whether this is quantitative or by a systematic subjective evaluation) and to help identify and prioritize factors of importance considering the perspectives of both a Host and Monitor. When used in the evaluation of options, criteria help to create a consistent framework that can assist in selecting the optimal solution among a set of competing alternatives.

decision making, Arms Control, decision analysis, ↗
DOE OSTI2018

Performance of Wavelength-Shifting Fibers for the Mu2e Cosmic Ray Veto Detector

The cosmic-ray-veto detector (CRV) for the Mu2e experiment consists of four layers of plastic scintillating counters read out by silicon photo-multipliers (SiPM) through wavelength-shifting fibers. This paper reports the light properties of several wavelength-shifting fiber samples with diameters of 1.0 mm, 1.4 mm, and 1.8 mm that were considered for the CRV system. A fiber diameter of 1.4 mm was selected as optimal for the CRV, and measurements of the prototype and production fiber of this diameter are presented. Fiber performance was found to exceed the CRV requirements for >99% of the spools. The measurements are performed using a scanner designed to ensure the fiber quality for the CRV.

Dukes, E. C.↗
DOE OSTI2023

Control of matrix converters using machine learning

A method of controlling a matrix converter system is provided. The method includes receiving an operating condition and consulting a trained Q-data structure for reward values associated with respective switching states of the switching matrix for an operating state that corresponds to the operating condition. The Q-data structure is trained using Q-learning to map a reward value predicted for respective switching states to respective discrete operating states. The method further includes sorting the reward values predicted for the respective switching states mapped to the operating state that corresponds to the operating condition, selecting a subset of the set of the mappings as a function of a result of sorting the reward values associated with the switching states of the operating state, evaluating each switching state included in the subset, and selecting an optimal switching state for the operating condition based on a result of evaluating the switching states of the subset.

Chamie, Mahmoud El↗
DOE OSTI2020

Development of an In-Situ Leaching Technology for Extracting Residual Uranium from Remediated Soil - 20099

Site-specific chemical solutions for extracting uranium were developed and evaluated for treating previously remediated soil at a former thorium mill tailings site, known as the Former Rare Earths Facility (REF), in West Chicago, Illinois. Prior remediation efforts had resulted in residual sand and gravel aggregate that met the soil cleanup standards. The target soil contains residual levels of uranium, which continues to leach into the site groundwater at levels exceeding groundwater protection standards (GWPS). A series of bench-scale tests were conducted to evaluate the efficacy and viability of in-situ leaching (ISL) technology to treat the target soil for the purposes of attaining uranium GWPS at the REF. Specific objectives of the bench-scale tests entailed identification and selection of optimal leaching, quantification of the extent and rate of uranium released as a function of chemical composition, chemical concentrations, chemical residence times, and obtaining critical data to estimate treatment costs. A combination of sodium bicarbonate and sodium carbonate reagent was the most effective leaching solution. In general, leaching solutions containing a higher concentration of sodium carbonate demonstrated superior uranium leaching capabilities. Removal of 50% of the uranium mass from the soil matrix was adequate for achieving compliance with the site-specific GWPS. After six to seven pore volume flushes (PVFs), the uranium leaching effectiveness of all leaching solutions was similar. The amount of initial uranium removed with each subsequent PVF was minimal, suggesting limited solubility of the remaining mass of uranium. The effects of leaching duration were significant and persisted through at least the first five consecutive PVFs. Leaching of uranium also resulted in leaching of several non-uranium constituents, many of which exceeded applicable National Pollutant Discharge Elimination System (NPDES) standards. Given historical operations and waste disposal practices at the site, leaching of non-uranium constituents was expected. Hydrochloric acid was used to stabilize treated soil. Savings of approximately $148 million in direct and indirect remediation costs are expected with an ISL alternative compared to the excavation and landfill disposal remediation option. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗