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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

AE33 Aethalometer Records at RMBL [AMF2] from April 2022 to October 2023

The dataset presents atmospheric mass loadings of black carbon (BC) and brown carbon (BrC), during the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign that took place from 2021 – 2023 in Gothic, CO. A Magee Scientific aethalometer (model AE33) was deployed at the Rocky Mountain Biological Laboratory, 200 m north of AMF2 to monitor mass loadings of optically absorbing aerosols. The instrument inlet was equipped with a BGI SCC 1.829 ambient cyclone with a particle cutoff of 2.5 μm and placed 5 m above ground level. The dataset reports hour-resolved BC mass loadings at 370, 470, 520, 590, 660, 880, and 950 (BC370, BC470, BC 520, BC590, BC660, BC880, BC950 in ng/m3) reported by the instrument built-in algorithm, which calculates mass loadings from the rate of change of the attenuation of light transmitted through the aerosol-laden filter. BC880 is the operationally defined reference of the BC concentration. Hour-resolved absorbance at each wavelength were calculated from their respective mass absorption cross-section in inverse megameters (Mm-1). The absorption Angstrom exponent (AAE) for BrC and BC were calculated for each hour. BrC AAE (AAE_BrC) was calculated from the slope of Log(wavelength) versus Log(absorbance) based on the measurements at 370, 470, and 520 nm. BC AAE (AAE_BrC) was calculated from the slope of Log(wavelength) versus Log(absorbance) based on the measurements at 590, 660, 880, and 950 nm. The aethalometer record spans time periods of 4/5/2022 – 10/3/2022 and 12/8/2022 – 10/9/2023. The ambient CO2 concentration recorded by a Vaisala CARBOCAP carbon dioxide probe GMP343 is also reported in ppm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Contact Stress Sensor _ Proposal to the FY2020 Technology Tech Mat Grants Program

The technology to be advanced is a very small and thin Contact Stress Sensor (CSS) that measures the contact stress between two contacting surfaces. It will be used to monitor the internal condition of a weapon in the stockpile over periods of decades. Monitoring the load path of a complex weapon assembly offers an important verification of the weapon’s mechanical state in both quasi-static or dynamic environments. Concurrently, the sensor can be used to measure temperature. This is useful for sensor calibration while installed in a system, as well as thermal monitoring in regions of the system that are difficult to access. Thus, the CSS is one way to monitor the internal “health” of a weapon. A sensor is shown below with each sensor being less then 2mm in width and 125 microns in thickness.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

OCTOKV: An Agile Network-Based Key-Value Storage System with Robust Load Orchestration

In this paper, we propose OctoKV, an innovative network-based key-value storage system. OctoKV addresses the repetitive address translation overhead associated with traditional key-value stores running on file systems on the client side. To mitigate this overhead, we implemented the key-value store on the server side using NVMe-oF and a user-level NVMe driver. In particular, we employed fine-grained resource monitoring and load balancing based on heuristics to optimize I/O performance. OctoKV is deployed on a Linux cluster with Intel SPDK. The extensive evaluation shows that OctoKV achieves lower I/O response times in comparison to traditional approaches where key-value stores run on the client side. Also, the proposed load balancing strategies efficiently enhance I/O response times by equally distributing the workload from overloaded cores to other cores.

Khan, Awais↗
NASA NTRS1984

Knowledge-based fault monitoring and diagnosis in Space Shuttle propellant loading

The LOX Expert System (LES), now being developed as a tool for the constraint-based monitoring and analysis of propellant loading at the Kennedy Space Center (KSC), is discussed. The loading of LOX at the KSC and its control and monitoring by the Launch Processing System are summarized, and the relevant problem for LES is presented. The LES database is briefly described, and the interaction of LES with KNOBS, a constraint- and frame-oriented knowledge-based system developed as a demonstration system in aid of tactical air mission planning, is the context of launch processing is discussed in detail. The design and fault isolation techniques of LES are also discussed.

Scarl, E. A.↗
NASA NTRS1989

A detailed investigation of the micromechanisms of compressive failure in open hole composite laminates

Micromechanisms responsible for compressive failure in open-hole composite laminates were investigated. Specimens containing circular center holes were loaded in compression to failure at a slow rate, and the surface damage development during loading was monitored. Several coupon compression tests were interrupted prior to catastrophic failure to allow for the assessment of fiber shear crippling and/or fiber microbuckling by NDE techniques. From these sectioning studies, the extent and mode of failure were determined, and a three-dimensional schematic of the shear crippling zone was developed. Results show that the majority of the damage in compression-loaded open-hole composite laminates is shear crippled or microbuckled 0-deg fibers; in many cases, however, the shear crippling damage within the 0-deg plies produced shear strains and damage in the adjacent off-axis plies.

Guynn, E. Gail↗
NASA NTRS2006

Flight Test of an Adaptive Controller and Simulated Failure/Damage on the NASA NF-15B

The method of flight-testing the Intelligent Flight Control System (IFCS) Second Generation (Gen-2) project on the NASA NF-15B is herein described. The Gen-2 project objective includes flight-testing a dynamic inversion controller augmented by a direct adaptive neural network to demonstrate performance improvements in the presence of simulated failure/damage. The Gen-2 objectives as implemented on the NASA NF-15B created challenges for software design, structural loading limitations, and flight test operations. Simulated failure/damage is introduced by modifying control surface commands, therefore requiring structural loads measurements. Flight-testing began with the validation of a structural loads model. Flight-testing of the Gen-2 controller continued, using test maneuvers designed in a sequenced approach. Success would clear the new controller with respect to dynamic response, simulated failure/damage, and with adaptation on and off. A handling qualities evaluation was conducted on the capability of the Gen-2 controller to restore aircraft response in the presence of a simulated failure/damage. Control room monitoring of loads sensors, flight dynamics, and controller adaptation, in addition to postflight data comparison to the simulation, ensured a safe methodology of buildup testing. Flight-testing continued without major incident to accomplish the project objectives, successfully uncovering strengths and weaknesses of the Gen-2 control approach in flight.

Buschbacher, Mark↗
DOE OSTI2026

A Physics-Based Digital Twin for Wave Elevation and Seabed Moment Estimation of Offshore Monopiles: Preprint

In this work, we present a proof of concept of a physics-based digital twin for a monopile structure (with overhead inertia) subjected to wave loading. The digital twin is formulated using reduced-order models derived from first principles and combined with a Kalman filter for state estimation. The proposed framework estimates the monopile top motion, the wave elevation, and the section forces and moments along the pile using primarily acceleration measurements at the monopile top. Key innovations include the use of a hydrodynamic shape function to represent distributed wave loading in a compact and computationally efficient manner, and the introduction of a shaping filter to augment the state-space with wave kinematics. Synthetic measurement data are generated using OpenFAST and used as a reference to assess the performance of the digital twin. Results demonstrate that the wave elevation can be accurately reconstructed without direct sea-state measurements as long as the wave regime is inertia-dominated. Under the ideal tested conditions, the total hydrodynamic force and sea-bed bending moment are estimated with relative errors on the order of 1% and correlation coefficients exceeding 96%. Future work will evaluate the estimator's performance under operational uncertainties and more complex loading conditions.

17 WIND ENERGY↗
DOE OSTI2020

TRANSENSOR: Transformer Real-time Assessment INtelligent System with Embedded Network of Sensors and Optical Readout. Final Report

Utilities across the world are wrestling with evolving market dynamics, population growth and climate change. Distributed Energy Resources (DERs) such as solar photovoltaics, distributed generators and energy storage systems are becoming important parts of the U.S. energy mix. These factors are driving an increasing need for low-cost grid asset monitoring. Aside from being costly, traditional utility monitoring systems are not sufficiently robust and do not provide real-time visibility into the condition of grid assets such as transformers. Lack of accurate real-time measurements on performance has resulted in the use of lagging indicators, such as oil sample analysis. To address this need, an innovative embedded optical sensing technology, Transformer Real-time Assessment Intelligent System (TRANSENSOR) was developed, validated and demonstrated in this project. To date, TRANSENSOR has focused on transformers but is extendable to other grid assets. In addition to the technology being embedded into new transformers during manufacturing, a retrofit configuration that can be installed on existing transformers in the field was also developed. It is anticipated that the ability to retrofit existing transformers will help accelerate adoption of the underlying TRANSENSOR technology. Phase 1 of the project focused on laboratory development and qualification of the technology. Following iterations and exploration of relevant optical sensing modalities and multiplexed configurations of interest for the transformer environment, an effective candidate configuration was agreed upon, down-selected and custom-designed for embedding into General Electric (GE) network transformers. Two new GE 500 kilovolt ampere (kVA), 27 kilovolt (kV) distribution network transformers were built with embedded fiber-optic (FO) sensors and successfully qualified per industry standards at GE’s Shreveport, Louisiana facility during Phase 1 of the project. Following the successful completion of Phase 1, the team proceeded to Phase 2, which focused on a field demonstration of the technology. Over Phase 2, the first new GE transformer built with embedded fiber-optic sensors was installed in an above-ground cage and connected to the grid at Con Edison’s Astoria facility. A second transformer equipped with TRANSENSOR was installed in an underground vault. Additionally, an older (1982 year model) GE transformer in an above-ground cage was retrofitted with fiber- optic sensors and reconnected to the grid at ConEd’s facility. Analysis of data acquired from the sensors showed interesting correlations with transformer loading. Additionally, key events such as transformer low-voltage network connection, primary-side energizing, and a pressure loss event from an oil sampling were detected by the TRANSENSOR system. Online data processing/feature extraction algorithms for the second transformer in the underground vault detected key features and event alerts that were transmitted through a wireless 4G connection. The remote deployment concept showed promising results with data collection running for a total of 8 months across the three (3) GE transformers instrumented for the Phase 2 field demonstration. This sets the stage well for further development and commercialization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Phasor-Measurement-Unit-Based Data Analytics Using Digital Twin and PhasorAnalytics Software

A major objective of this project was to apply GE’s commercial machine learning and data analytics toolsets to large-scale, real-world, anonymized Phasor Measurement Unit (PMU) datasets in order to extract signatures, correlated and/or causal factors, and precursor patterns associated with significant power system phenomena. The project had a particular emphasis on extraction of insights relevant to asset health monitoring, real-time load modeling and cybersecurity monitoring. Additionally, the team was directed to undertake a comprehensive data quality analysis for the provided datasets and encouraged to estimate the ‘machine-learning readiness’ of the datasets by documenting any major obstacles to the application of commercial machine learning algorithms. To accomplish the aforementioned objectives, the project team’s work centered around the identification of key event signatures and application of the identified event signatures for event detection and event classification. The industry-validated, semi-supervised machine learning strategy employed for event signature identification involved several major tasks, including data-preprocessing, generation of an overabundance of features, normal data identification, normality modeling, and event signature identification through a methodical, quantitative ranking of features in order of relevance to each studied event type. Throughout the project, data quality issues and mitigation techniques were investigated. In this report, insights are provided regarding the readiness of the provided synchrophasor datasets for application of machine learning and data analytics. The methodologies employed for this technical strategy are summarized in this report. With regards to data preprocessing and feature generation, the provided Training and Test Datasets were ingested into GE’s big data environment. Subsequently, the team applied bad data cleansing and data imputation scripts, event detection scripts, and application programming interfaces (APIs) to the datasets for convenient data access. The project team completed development and validation of dozens of physics-based, statistics-based and transformation-based feature functions used for the extraction of over 60 synchrophasor features. Using a new parallel feature generation technology developed on this project, over 60 features have been rapidly generated for the full two years’ worth of Training and Test Dataset data associated with both the Eastern and Western interconnects. Even accommodating for temporal down-sampling inherent to the feature extraction procedure, this parallel feature generation activity resulted in a massive feature set with a storage requirement approximately equal to that of the raw training dataset itself. With regards to normal data identification and normality modeling, a normality model was built using the feature data extracted from the Training Dataset and iteratively refined subsequent to incremental adjustments and expansions of the Training Dataset feature data. With respect to event characterization and signature identification, an event signature identification pipeline was developed and used in conjunction with the normality model to identify over 15 event signatures for key event categories within the Training Dataset. The identified event signatures were used to characterize hundreds of key events in terms of relative severity, duration, and location of the event. An investigation was undertaken to identify correlated and causal factors involved in transformer events. A separate investigation into temporal trends in ring-down analysis results was undertaken to determine possible associations between system dynamics and various other factors such as loading, season or year. To validate the identified event signatures, additional work was undertaken to develop signature-based anomaly detection and classification tools suitable for convenient application to the synchrophasor datasets. The anomaly detection and classification tools, suitable for online application, were then applied to the entirety of the Eastern Interconnect Training and Test Datasets. Performance of the event detection and classification tools was evaluated upon receipt of the Test Dataset event logs (i.e., the labels for events contained in the Test Dataset), and promising results were obtained despite several challenges (documented herein) associated with application of supervised or semi-supervised machine learning methods to large-scale, anonymized datasets. Finally, the detection and classification tools were used to detect, classify, and characterize thousands of new events not included in the original event logs provided by the DOE within both the Training and Test Datasets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Development of a health monitoring framework: Application to a supercritical pulverized coal-fired boiler

In this study, this work details the development of a physics-based equipment health monitoring framework for a supercritical boiler, using first-principles models to estimate the remaining useful life (RUL) of its components. The framework accounts for fatigue and creep life consumption, generating spatio-temporal variations in mechanical and thermal stress. Analysis of the stress profile throughout the boiler highlights the finishing superheater inlet steam header as a vulnerable location susceptible to damage from cycling operation. The framework also yields quantified uncertainty in the RUL projection for specific locations, accounting for uncertainties in material properties and boiler operation. Results indicate that operational uncertainties (e.g., seasonal variation and operational strategy) and material properties (e.g., rupture time coefficients, Young’s modulus, yield strength, and coefficient of thermal expansion) significantly impact the RUL of the finishing superheater inlet steam header. Additionally, case studies demonstrate the use of the health monitoring framework as a predictive tool for operational planning under uncertainty, including scenarios with and without updates on the operation of the boiler.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Polymer-Stabilized Liquid Metal Nanoparticles as a Scalable Current Collector Engineering Approach Enabling Lithium Metal Anodes

Dendrites and dead lithium formation over prolonged cycling have long been challenges that hinder the safe implementation of metallic Li anodes. In this study, we employ polymer-stabilized liquid metal nanoparticles (LM-P NPs) of eutectic gallium indium (EGaIn) to create uniform Li nucleation sites enabling homogeneous lithium electrodeposition. Block copolymers of poly(ethylene oxide) and poly(acrylic acid) (PEO-b-PAA) were grafted onto the EGaIn surface, forming stabilized, well-dispersed NPs. Using a scalable spray coating approach, LM-P NPs were fabricated on copper current collectors, providing lithiophilic PEO sites and interactive carboxyl groups to guide Li deposition. The Li-EGaIn alloying process greatly reduced the Li + diffusion barrier, enabling fast Li transport through the coating layer, resulting in decreased nucleation overpotential. Therefore, about five times lower Li nucleation overpotential was obtained on the LM-P modified Cu with an optimal composition of the polymers than the bare Cu substrates. DFT computations was used to reveal the binding properties between the LM-P layer and Li. Due to the regulated Li plating/stripping process, as-obtained 30 μm Li anodes paired with LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM8 11 ) with a negative/positive electrode capacity (N/P) ratio ~ 10 exhibited stable cycling performance at 0.5C for over 250 cycles, with an average Coulombic efficiency of 99.55%. Ultrathin Li (1 μm) anodes with an N/P ratio ~ 0.6 were also demonstrated in Li|LiFePO 4 cells, which examined the stabilization of Li by LM-P NPs and monitored practical loadings of Li anodes that are close to anode-free systems.

25 ENERGY STORAGE↗
DOE OSTI2024

A Contextually Supervised Optimization-Based HVAC Load Disaggregation Methodology

This paper presents a novel contextually supervised optimization-based approach for disaggregating heating, ventilation, and air-conditioning (HVAC) loads using smart meter or Supervisory Control and Data Acquisition data. To disaggregate the load into HVAC loads, large and infrequently used loads (LIUL), and base loads, we formulate an optimization problem to minimize a set of five loss terms, consisting of the reconstruction errors of the overall load profile, the ramp rate losses, and three distinct loss functions linked with the HVAC load, base load, and LIUL, respectively. To enhance accuracy, we incorporate two forms of contextual information into the problem formulation. First, we utilize mutual information to estimate HVAC energy consumption. Second, we employ a base load dictionary to constrain HVAC load estimation errors. The obtained HVAC load profiles are fine-tuned by abnormal ramp detection followed by binary hypothesis testing. Here, the proposed method is developed and tested using sub-metered residential and commercial building data. Simulation results show that the proposed method outperforms existing methods across various data resolutions and load aggregation levels, showing excellent transferability and generalizability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Phased: Phase-Aware Submodularity-Based Energy Disaggregation

Energy disaggregation is the task of discerning the energy consumption of individual appliances from aggregated measurements, which holds promise for understanding and reducing energy usage. In this paper, we propose PHASED, an optimization approach for energy disaggregation that has two key features: PHASED (i) exploits the structure of power distribution systems to make use of readily available measurements that are neglected by existing methods, and (ii) poses the problem as a minimization of a difference of sub-modular functions. We leverage this form by applying a discrete optimization variant of the majorization-minimization algorithm to iteratively minimize a sequence of global upper bounds of the cost function to obtain high-quality approximate solutions. PHASED improves the disaggregation accuracy of state-of-the-art models by up to 61% and achieves better prediction on heavy load appliances.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2021

Flaming Moe

Current clamp measurements collected on various small electronic devices. Details on the data set can be found in J. M. Vann, T. P. Karnowski, R. Kerekes, C. D. Cooke and A. L. Anderson, A Dimensionally Aligned Signal Projection for Classification of Unintended Radiated Emissions, in IEEE Transactions on Electromagnetic Compatibility, vol. 60, no. 1, pp. 122-131, Feb. 2018, doi: 10.1109/TEMC.2017.2692962.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

QXF Cold Mass Friction Test

The purpose of this test is to determine the longitudinal force on the stainless steel shell that is required to break the friction between the stainless steel shell and the aluminum shell underneath. This is achieved by suspending the short magnet between two backing plates on the eight grade 8 threaded rods which replace the 8 stainless steel toke tie rods in the magnet assembly. Eight hydraulic cylinders are mounted to each backing plate. Six, 22" sections of the stainless steel shell are welded in place on the magnet, each of which has a slightly different developed length, starting from the baseline design, and becoming progressively looser. A pushing flange is mounted to the stainless steel shells via small tack welds. Four load cells are then attached to the flange at designated points, while additional tooling is attached to each of the cylinders to facilitate the transfer of force from the cylinders to the stainless steel shell During the test, the cylinders will be slowly energized to no more than 7000 psi, with a resultant, longitudinal force on the flange of no more than 125,400 lbf. For each set of shells, the test ends when the load cell monitoring software detects a sharp decrease in force. This will indicate that the friction has broken. The cullenders will then be de-energized and the cycle will repeat for the next test. Welding operations outlined in the procedure (US-HiLumi-doc-4200) are outside the scope of the HA as the work is occurring under a previously-issued burn permit by qualified welders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1982

Laboratory upwelled radiance and reflectance spectra of Kerr reservoir sediment waters

Reflectance, chromaticity, and several other physical and chemical properties were measured for various water mixtures of bottom sediments taken from two sites at Kerr Reservoir, Virginia. Mixture concentrations ranged from 5 to 1000 ppm by weight of total suspended solids (TSS) in filtered deionized tap water. The two sets of radiance and reflectance spectra obtained were similar in shape and magnitude for comparable values of TSS. Upwelled reflectance was observed to be a nonlinear function of TSS with the degree of curvature a function of wavelength. Sediment from the downstream site contained a greater amount of particulate organic carbon than from the upstream site. No strong conclusions can be made regarding the effects of this difference on the radiance and reflectance spectra. Near-infrared wavelengths appear useful for measuring highly turbid water with concentrations up to 1000 ppm or more. Chromaticity characteristics do not appear useful for monitoring sediment loads above 150 ppm.

Witte, W. G.↗
NASA NTRS1980

Behavior of damaged graphite/epoxy laminates under compression loading

The influence of three different resin systems on the damage tolerance of graphite/polymer laminates was evaluated. Testing consisted of both static compression and cyclic compression evaluation of 10.2 by 15.2 by 0.5 cm (4 by 6 by 0.2 in) laminates with circular holes, simulated delaminations, and low velocity impact. Damage growth under steadily increasing compression and cyclic compression loading was monitored. Damage size and impact-induced failures for the three materials were compared. Of the three material systems evaluated, the one most tolerant to impact damage exhibited the least delamination within the cross section due to impact, the highest transverse tension strain to failure, and the largest crack opening force, as determined from double cantilever beam tests.

Byers, B. A.↗
NASA NTRS1981

AD-1 oblique wing aircraft program

A NASA program for evaluation of the handling and flying characteristics of the AD-1 oblique wing aircraft is discussed. The vehicle was flown to compare wind tunnel predictions with aerodynamic data, explore the control system requirements, and obtain a preliminary assessment of the aeroelastic effects. The fiberglass sandwich skin aircraft is designed for 8 g positive and 4 g negative loading at 175 knots, while the wing pivot can withstand 25 g loading. Flight monitoring was accomplished with a 41 channel pulse code modulation system for telemetry and by averaging of pilot ratings. Maneuvering tests are outlined, noting that pilot ratings indicated acceptable handling at up to 50 deg sweep. It is concluded that acceptable flying qualities can be achieved with a 60 deg sweep, and that aeroelastic tailoring can be used to satisfy cruise design technology.

Mcmurtry, T. C.↗