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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Leveraging inter-firm influence in the diffusion of energy efficiency technologies: An agent-based model

Energy efficiency technologies (EETs) are crucial for saving energy and reducing carbon dioxide emissions. However, the diffusion of EETs in small and medium-sized enterprises is rather slow. Literature shows the interactions between innovation adopters and potential adopters have significant impacts on innovation diffusion. Enterprises lack the motivation to share information, and EETs usually lack observability, which suppress the inter-firm influence. Thus, an information platform, together with proper policies encouraging or forcing enterprises to disclose EET-related information, should help harness inter-firm influence to accelerate EETs' diffusion. To explore whether and how such an information platform affects EETs' diffusion in small and medium-sized enterprises, this report builds an agent-based model to mimic EET diffusion processes. Based on a series of controlled numerical experiments, some counter-intuitive phenomena are discovered and explained. The results show that the information platform is a double-edged sword that notably accelerates EETs' diffusion by approximately 47% but may also boost negative information to diffuse even faster and delay massive adoption of EETs. Increasing network density and the intensity of inter-firm influence are effective to speed EET diffusion, but their impacts diminish drastically after reaching some critical values (0.05 and 0.15 respectively) and eventually harm the stability of the system. Ultimately, the findings implicate that EET suppliers should carefully launch their promising but immature products; policies that can reduce the perceived risk by enterprises and the effort to maintain an informative rather than judgmental information platform can prominently mitigate the negative side effects brought by high fluidity of information.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Analysis of mobility data to build contact networks for COVID-19

As social distancing policies and recommendations went into effect in response to COVID-19, people made rapid changes to the places they visit. These changes are clearly seen in mobility data, which records foot traffic using location trackers in cell phones. While mobility data is often used to extract the number of customers that visit a particular business or business type, it is the frequency and duration of concurrent occupancy at those sites that governs transmission. Understanding the way people interact at different locations can help target policies and inform contact tracing and prevention strategies. This paper outlines methods to extract interactions from mobility data and build networks that can be used in epidemiological models. Several measures of interaction are extracted: interactions between people, the cumulative interactions for a single person, and cumulative interactions that occur at particular businesses. Network metrics are computed to identify structural trends which show clear changes based on the timing of stay-at-home orders. Measures of interaction and structural trends in the resulting networks can be used to better understand potential spreading events, the percent of interactions that can be classified as close contacts, and the impact of policy choices to control transmission.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Artificial Intelligence-Aided Wind Plant Optimization for Nationwide Evaluation of Land Use and Economic Benefits of Wake Steering

If clean energy pathways are to harness massive increases in wind power, innovations with broad geographic viability will be needed to support buildout in diverse locations. However, geodiversity in impact potential is seldom captured in technology assessment. Here we propose a scalable approach to plant-level optimization using artificial intelligence to evaluate land sparing and economic benefits of wake steering at more than 6,800 plausible onshore wind locations in the USA. This emerging controls strategy optimizes plant energy production by directing turbine wakes. On the basis of estimates from our artificial intelligence model trained on engineering wind flow simulations, co-optimizing plant layouts with wake steering can reduce land requirements by an average of 18% per plant (site-specific benefits range from 2% to 34%), subject to errors and uncertainties in the flow model, wind resource estimates, buildout scenario and geographic factors. According to model estimates, wake steering is predicted to increase power production during high-value (relatively low wind) periods, boosting the annual revenue of individual plants by up to US$3.7 million (equivalent to US$13,000 MW-1 yr-1) but producing negligible gains in some settings. Consideration of wake steering’s geographic potential reveals divergent nationwide prospects for improved economics and siting flexibility.

deployment↗
DOE OSTI2020

Real-time power management technique for microgrid with flexible boundaries

In order to diminish the impacts brought by high penetration of renewable energy on the reliability of distribution systems, some distribution networks (e.g. Chattanooga electric power board system) have deployed smart switches (SSs) to island some areas to mitigate outage losses. However, due to intermittency and sharply changing rate of renewable energy, it is likely to experience insufficient or excessive power for islanded areas. Therefore, a microgrid controller featured with flexible boundaries is proposed. With proposed microgrid controller, the microgrid can not only shrink or expand its boundaries according to current renewable energy supply, but also disconnect/connect to the main grid with a designated SS. Furthermore, to ensure the microgrid controller could obtain suitable boundaries on the time scale of seconds, a real-time power management technique with alternative generating algorithm is designed to generate all possible alternative boundaries and choose the optimal one, which is scalable to any topology. In addition, in order to maintain state of charge of batteries within a desirable range, anti-overcharge/discharge strategies are designed. Four comprehensive experiments verify that the implementation of the microgrid controllers can realise flexible boundaries and deal with sharply changing rate of renewable generation or load on the time scale of seconds.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Comparison of machine learning systems trained to detect Alfvén eigenmodes using the CO 2 interferometer on DIII-D

Abstract A Machine-Learning (ML) based detection scheme that automatically detects Alfvén Eigenmodes (AE) in a labelled DIII-D database is presented here. Controlling AEs is important for the success of planned burning plasma devices such as ITER, since resonant fast ions can drive AEs unstable and degrade the performance of the plasma or damage the first walls of the machine vessel. Artificial Intelligence could be useful for real-time detection and control of AEs in steady-state plasma scenarios by implementing ML-based models into control algorithms that drive actuators for mitigation of AE impacts. Thus, the objective is to compare differences in performance between using two different recurrent neural network systems (Reservoir Computing Network and Long Short Term Memory Network) and two different representations of the C O 2 phase data (simple and crosspower spectrograms). All C O 2 interferometer chords are used to train both models, but only one is processed during each training step. The results from the model and data comparison show higher performance for the RCN model (True Positive Rate = 90% and False Positive Rate = 14%), and that using simple magnitude spectrograms is sufficient to detect AEs. Also, the vertical C O 2 interferometer chord passing near the center is better for ML-based detection of AEs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Hidden frustration in the triangular-lattice antiferromagnet NdCd 3 ⁢P 3

We report a study of the magnetic ground state and crystal electric field (CEF) scheme in the triangular-lattice antiferromagnet NdCd 3 ⁢P 3 . Combined neutron scattering, magnetization, and heat capacity measurements demonstrate that the Nd 3+ moments occupying the triangular lattice in this material harbor hidden signs of frustration not detected in typical Curie-Weiss-based parametrization of the frustration index (𝑓 = Θ 𝐶⁢𝑊 /𝑇 𝑁 ). This is evidenced by a zero-field splitting of the Kramers' ground state and first excited state doublets at temperatures far in excess of 𝑇 𝑁 as well as signatures of low-energy fluctuations for 𝑇 ≫ 𝑇 𝑁 . As a result, a suppression of the zero-field ordered moment relative to its field saturation value is observed, and the impacts of this magnetic frustration as well as the coexisting bond frustration in the CdP honeycomb network on the physical properties of NdCd 3 ⁢P3 are discussed.

Frustrated magnetism↗
DOE OSTI2021

Few-shot Learning for Post-disaster Structure Damage Assessment

Automating post-disaster damage assessment with remote sensing data is critical for faster surveys of structures impacted by natural disasters. One significant obstacle to training state-of-the-art deep neural networks to support this automation is that large quantities of labelled data are often required. However, obtaining those labels is particularly unrealistic to support post-disaster damage assessment in a timely manner. Few-shot learning methods could help to mitigate this by reducing the amount of labelled data required to successfully train a model while achieving satisfactory results. To this end, we explore a feature reweighting method to the YOLOv3 object detection architecture to achieve few-shot learning of damage assessment models on the xBD dataset. Our results show that the feature reweighting approach yield improved mAP over the baseline with significantly fewer labelled samples. In addition, we use t-SNE to analyze the class-specific reweighting vectors generated by the reweighting module in order to evaluate their inter-class and intra-class similarity. We find that the vectors form clusters based on class, and that these clusters overlap with visually similar classes. Those results show the potential to employ this few-shot learning strategy for rapid damage assessment with post-event remote sensing images.

Bowman, Jordan↗
DOE OSTI2021

Locating Seismic Events with Local-Distance Data

As the seismic monitoring community advances toward detecting, identifying, and locating ever-smaller natural and anthropogenic events, the need is constantly increasing for higher resolution, higher fidelity data, models, and methods for accurately characterizing events. Local-distance seismic data provide robust constraints on event locations, but also introduce complexity due to the significant geologic heterogeneity of the Earth’s crust and upper mantle, and the relative sparsity of data that often occurs with small events recorded on regional seismic networks. Identifying the critical characteristics for improving local-scale event locations and the factors that impact location accuracy and reliability is an ongoing challenge for the seismic community. Using Utah as a test case, we examine three data sets of varying duration, finesse, and magnitude to investigate the effects of local earth structure and modeling parameters on local-distance event location precision and accuracy. We observe that the most critical elements controlling relocation precision are azimuthal coverage and local-scale velocity structure, with tradeoffs based on event depth, type, location, and range.

42 ENGINEERING↗
NASA NTRS1990

The Cable and Wireless approach to network synchronization

The philosophy adopted by Cable and Wireless for the synchronization of its world-wide network is presented. The architectures of some clock systems already deployed and how network synchronization had been implemented at selected locations are discussed. This includes some innovative designs as the network spans both first and third world countries with a combination of North Amercan and European hierarchy equipment. Different parts of the global network are linked together by a combination of terrestrial microwave, submarine cable and satellite technology. The impact of synchronization on Intelsat Intermediate Data Rate (IDR) operation and the restoration of submarine cable systems are addressed.

Calvert, Robert D.↗
NASA NTRS2001

The Conference Proceedings of the 2001 Air Transport Research Society (ATRS) of the WCTR Society

The ATRS held its 5th Annual conference at the City University of Hong Kong Campus in July 2001. The conference was a success with nearly 140 participants including 70 presenters. Titles that comprise Volume 2 include: Intelligent Airport Gate Assignment System; A Study on the Effects of the Personality Compatibility to the Job Performance; ITS/CVO Application for Air cargo Transportation in Korea; An Airport as a Logistics and Economic Hub: The Case of Incheon International Airport; The Impact Of Aviation Safety over the Consumer's Behavior; The Integration of China and Taiwan Air Networks for Direct Air Cargo Services; Quality perception and carrier choice in Civil Aviation; Future Trends in Business Travel Decision Making; Cooperation Among German Airports in Europe; Inbound and Outbound Air Passenger Traffic Forecasting between the United States and Selected Asian countries; An Evaluation of Alternative Facilities for Airport Redevelopment using Fuzzy Linguistic Approach; Economic Analysis of Airline Alliances; The Aviation Cooperation between the two Koreas Preparing for the Reunification of the Peninsula; and A Study on the Air Transport Cooperation in Northeast Asia between China, Japan and Korea.

Lee, Yeong-Heok↗
NASA NTRS2004

Networking Technologies Enable Advances in Earth Science

This paper describes an experiment to prototype a new way of conducting science by applying networking and distributed computing technologies to an Earth Science application. A combination of satellite, wireless, and terrestrial networking provided geologists at a remote field site with interactive access to supercomputer facilities at two NASA centers, thus enabling them to validate and calibrate remotely sensed geological data in near-real time. This represents a fundamental shift in the way that Earth scientists analyze remotely sensed data. In this paper we describe the experiment and the network infrastructure that enabled it, analyze the data flow during the experiment, and discuss the scientific impact of the results.

Johnson, Marjory↗
NASA NTRS2004

Biomass-Burning Aerosols in South East-Asia: Smoke Impact Assessment (BASE-ASIA)

Biomass burning has been a regular practice for land clearing and land conversion in many countries, especially those in Africa, South America, and Southeast Asia. However, the unique climatology of Southeast Asia is very different than that of Africa and South America, such that large-scale biomass burning causes smoke to interact extensively with clouds during the peak-burning season of March to April. Significant global sources of greenhouse gases (e.g., CO2, CH4), chemically active gases (e.g., NO, CO, HC, CH3Br), and atmospheric aerosols are produced by biomass burning processes. These gases influence the Earth- atmosphere system, impacting both global climate and tropospheric chemistry. Some aerosols can serve as cloud condensation nuclei, which play an important role in determining cloud lifetime and precipitation, hence, altering the earth s radiation and water budget. Analyses from satellite measurements reveal the reflected solar (emitted thermal) radiation from clouds due to smoke aerosols can be reduced (enhanced) by 100 (20) Watts per square meter over the month of March 2000. In addition, the reduction in cloud spectral reflectance is large enough to lead to significant errors in satellite retrievals of cloud properties (e.g., optical thickness and effective radius). The fresh water distribution in this region is highly dependent on monsoon rainfall; in fact, the predictability of the tropical climate system is much reduced during the boreal spring. Therefore, to accurately assess the impact of smoke aerosols in this region requires continuous observations from satellites, aircraft, ground-based networks and dedicated field experiments. BASE-ASIA initiative has been proposed and will be discussed.

Tsay, S.-C.↗
NASA NTRS2008

Geologic Evolution of the Martian Highlands: MTMs -20002, -20007, -25002, and -25007

As part of a continuing study to understand the relationship between valleys and highland resurfacing through geologic mapping, the authors are continuing to map seven 1:500,000-scale MTM quads in portions of the Margaritifer, Arabia, and Noachis Terrae. Results from this mapping will also help constrain the role and extent of past water in the region. The MTMs are grouped in two different areas within the region and compliment previous mapping in adjacent areas. Three western quads focus on Jones crater and the Himera, Samara, and Loire Valles systems. This abstract focuses on the four eastern quads wherein a large, ancient impact structure, Noachis basin, is flanked on its south and east by a series of valley networks. A solitary valley drains this basin and stretches north-northeast for approximately 450 km, transporting materials into Arabia Terra. Pertinent raster and vector data have been imported and registered using ESRI's ArcMap GIS software. To inspect and quantify stratigraphic relations, crater counts are being compiled in ESRI's ArcView GIS software to make use of crater counting tools specifically developed for planetary mappers. New datasets from the Mars Reconnaissance Orbiter including 4 CTX images, 31 CRISM multi-spectral pushbroom images, and 4 HiRISE images were incorporated into the project during the third year. The CRISM dataset uses summary parameters with thresholds to select targets for the high-resolution datasets. The befit for mappers is the extensive coverage and general compositional information. Results of a cursory analysis show strong mafic absorptions on the floors of Peta crater and Noachis basin. LCP absorptions occur more often than olivine, however, olivine tends to be denser than both pyroxenes. Olivine and HCP mat indicate relatively younger rocks, which is supported by the occurrence of wrinkle ridges associated with high olivine and HCP absorptions in the Peta crater and Noachis basin floors.

Fortezzo, C. M.↗
NASA NTRS2022

Climate Change-Induced Peatland Drying in Southeast Asia

When organic peat soils are sufficiently dry, they become flammable. In Southeast Asian peatlands, widespread deforestation and associated drainage create dry conditions that, when coupled with El Niño-driven drought, result in catastrophic fire events that release large amounts of carbon and deadly smoke to the atmosphere. While the effects of anthropogenic degradation on peat moisture and fire risk have been extensively demonstrated, climate change impacts to peat flammability are poorly understood. These impacts are likely to be mediated primarily through changes in soil moisture. Here, we used neural networks (trained on data from the NASA Soil Moisture Active Passive satellite) to model soil moisture as a function of climate, degradation, and location. The neural networks were forced with regional climate model projections for 1985–2005 and 2040–2060 climate under RCP8.5 forcing to predict changes in soil moisture. We find that reduced precipitation and increased evaporative demand will lead to median soil moisture decreases about half as strong as those observed during recent El Niño droughts in 2015 and 2019. Based on previous studies, such reductions may be expected to accelerate peat carbon emissions. Our results also suggest that soil moisture in degraded areas with less tree cover may be more sensitive to climate change than in other land use types, motivating urgent peatland restoration. Climate change may play an important role in future soil moisture regimes and by extension, future peat fire in Southeast Asian peatlands.

VIIRS↗
DOE OSTI2025

A Graph-Net with Node Embeddings to Detect False Data Injection Attacks in Photovoltaic Systems

Distributed energy resources (DER) contribute to the operational stability of the larger power grid both at utility-scale as well as commercial and residential scales in aggregated forms. These DER in-turn are susceptible to increasing cyber threats. An adversary can plug into the same local network that a field photovoltaic (PV) system uses to interconnect its data loggers and inverters and manipulate certain measurements collected from the network or trick existing irradiance and inverter readings through false data injection attacks (FDIA). Control routines that rely on these measurements can propagate the false data, impacting critical decisions that result in a suboptimal operation or even cause intentional harm leading to inverter-tripping or unscheduled loads that need to be shed. To detect FDIA in PV systems, the paper introduces an attention-based graph neural network with node embeddings and applied it to a simple prototypical DC-coupled microgrid with PV, energy storage, and load. The algorithm shows a detection accuracy of up to 98.95%. The proposed FDIA detection technique will provide micro-grid operators with an effective method to safeguard their systems, guaranteeing the secure and reliable operation.

Parvez, Imtiaz [Utah Valley University]↗
DOE OSTI2023

Performance of hybrid Innegra-carbon fiber composites

Abstract In this work material synergy with high stiffness carbon fiber with ductile high strength polypropylene fiber (Innegra S), (referred to as Innegra, herein) have been evaluated in a range of laminate designs. Both woven and discontinuous carbon fiber have been considered. The discontinuous fibers are based on three-dimensional deposition (3DEP) (referred to as 3DEP, herein) carbon fiber preform process. Eleven (11) variants of Innegra-carbon fiber hybrid laminates were investigated for tensile, flexure, compression, in-plane shear and low velocity impact response. The effect of position of Innegra within the laminate was studied and found to influence strength and stiffness properties. In terms of overall trends, Innegra provides upward of 18% improvement in strain (ductility) to the composite and eliminates brittle fracture of carbon fiber. The moduli trends follow the proportionality of Innegra fiber to carbon fiber plies. However, the strength is controlled by the interface between Innegra and carbon fiber. The primary failure mode in tension and compression is via onset of debonding between Innegra and carbon fiber. The 3DEP carbon fiber constituents provided highest values of in-plane shear indicating that three-dimensional (3D) network of carbon fiber provides higher shear resistance. The Innegra intensive variants exhibited superior energy absorption under low velocity impact, at energy levels 15–60 J. This work provides insight for designers to incorporate Innegra and carbon fiber hybrids in composite structures.

36 MATERIALS SCIENCE↗
NASA NTRS2006

CCSDS Time-Critical Onboard Networking Service

The Consultative Committee for Space Data Systems (CCSDS) is developing recommendations for communication services onboard spacecraft. Today many different communication buses are used on spacecraft requiring software with the same basic functionality to be rewritten for each type of bus. This impacts on the application software resulting in custom software for almost every new mission. The Spacecraft Onboard Interface Services (SOIS) working group aims to provide a consistent interface to various onboard buses and sub-networks, enabling a common interface to the application software. The eventual goal is reusable software that can be easily ported to new missions and run on a range of onboard buses without substantial modification. The system engineer will then be able to select a bus based on its performance, power, etc and be confident that a particular choice of bus will not place excessive demands on software development. This paper describes the SOIS Intra-Networking Service which is designed to enable data transfer and multiplexing of a variety of internetworking protocols with a range of quality of service support, over underlying heterogeneous data links. The Intra-network service interface provides users with a common Quality of Service interface when transporting data across a variety of underlying data links. Supported Quality of Service (QoS) elements include: Priority, Resource Reservation and Retry/Redundancy. These three QoS elements combine and map into four TCONS services for onboard data communications: Best Effort, Assured, Reserved, and Guaranteed. Data to be transported is passed to the Intra-network service with a requested QoS. The requested QoS includes the type of service, priority and where appropriate, a channel identifier. The data is de-multiplexed, prioritized, and the required resources for transport are allocated. The data is then passed to the appropriate data link for transfer across the bus. The SOIS supported data links may inherently provide the quality of service support requested by the intra-network layer. In the case where the data link does not have the required level of support, the missing functionality is added by SOIS. As a result of this architecture, re-usable software applications can be designed and used across missions thereby promoting common mission operations. In addition, the protocol multiplexing function enables the blending of multiple onboard networks. This paper starts by giving an overview of the SOIS architecture in section 11, illustrating where the TCONS services fit into the overall architecture. It then describes the quality of service approach adopted, in section III. The prototyping efforts that have been going on are introduced in section JY. Finally, in section V the current status of the CCSDS recommendations is summarized.

Parkes, Steve↗
NASA NTRS2023

The Impact and Estimation of Uncertainty Correlation for Multi-Angle Polarimetric Remote Sensing of Aerosols and Ocean Color

Multi-angle polarimetric (MAP) measurements contain rich information for characterization of aerosol microphysical and optical properties that can be used to improve atmospheric correction in ocean color remote sensing. Advanced retrieval algorithms have been developed to obtain multiple geophysical parameters in the atmosphere-ocean system, although uncertainty correlation among measurements is generally ignored due to lack of knowledge on its strength and characterization. In this work, we provide a practical framework to evaluate the impact of the angular uncertainty correlation from retrieval results and a method to estimate correlation strength from retrieval fitting residuals. The Fast Multi-Angular Polarimetric Ocean coLor (FastMAPOL) retrieval algorithm, based on neural network forward models, is used to conduct the retrievals and uncertainty quantification. In addition, we also discuss a flexible approach to include a correlated uncertainty model in the retrieval algorithm. The impact of angular correlation on retrieval uncertainties is discussed based on synthetic AirHARP and HARP2 measurements using a Monte Carlo uncertainty estimation method. Correlation properties are estimated using auto-correlation functions based on the fitting residuals from both synthetic AirHARP and HARP2 data and real AirHARP measurement, with the resulting angular correlation parameters found to be larger than 0.9 and 0.8 for reflectance and DoLP, respectively, which correspond to correlation angles of 10° and 5°. Although this study focuses on angular correlation from HARP instruments, the methodology to study and quantify uncertainty correlation is also applicable to other instruments with angular, spectral, or spatial correlations, and can help inform laboratory calibration and characterization of the instrument uncertainty structure.

PACE↗