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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Visible Light Communications: A Survey on Recent High-Capacity Demonstrations and Digital Modulation Techniques

In order to deal with the increasing number of mobile devices and with their demand for Internet services, particularly social media platforms, streaming video, and online gaming, Radio-Frequency (RF) wireless networks have been pushed to their capacity limits. In addition to this, 80% of the total data traffic is carried out by users inside buildings. Therefore, new technologies have started to be considered for indoor wireless communications. Visible Light Communications (VLC) can provide both illumination and communications, appearing as an alternative or complement to RF wireless networks. VLC offers high bandwidth and immunity to interference from electromagnetic sources. This manuscript reviews recent high-capacity VLC demonstrations. The main focus of this work is to present digital-signal-processing techniques used in VLC systems. Different modulation formats are analyzed, which can be divided into two large groups, namely single-carrier and multi-carrier modulation schemes. Finally, some recently proposed capacity-achieving strategies are presented. We discuss how to implement these techniques and how they will be useful for the continued development of VLC systems.

Loureiro, Pedro A. (ORCID:0000000283546185)↗
DOE OSTI2023

PyFLEXTRKR: a flexible feature tracking Python software for convective cloud analysis

Abstract. This paper describes the new open-source framework PyFLEXTRKR (Python FLEXible object TRacKeR), a flexible atmospheric feature tracking software package with specific capabilities to track convective clouds from a variety of observations and model simulations. This software can track any atmospheric 2D objects and handle merging and splitting explicitly. The package has a collection of multi-object identification algorithms, scalable parallelization options, and has been optimized for large datasets including global high-resolution data. We demonstrate applications of PyFLEXTRKR on tracking individual deep convective cells and mesoscale convective systems from observations and model simulations ranging from large-eddy resolving (∼100s m) to mesoscale (∼10s km) resolutions. Visualization, post-processing, and statistical analysis tools are included in the package. New Lagrangian analyses of convective clouds produced by PyFLEXTRKR applicable to a wide range of datasets and scales facilitate advanced model evaluation and development efforts as well as scientific discovery.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Interdisciplinary Research Collaborative Trains Students to See Through Turbulent Systems

Despite the availability of interdisciplinary academic training programs, the practice of environmental science is often hampered by a lack of convergence across diverse disciplines. This gap is particularly salient in settings characterized by complex environmental issues, such as multiple-use coastal ecosystems. In response, we developed and implemented a training, research, and communication framework to provide undergraduates with an authentic operative experience working at the interface of interdisciplinary science and public decision-making within a case study of marine renewable energy. In our program, students gained hands-on experience with the scientific process and learned how to make information relevant, useful, and accessible to diverse stakeholder groups. Application of this framework demonstrates that the process of integrating data from biological (visual and acoustic monitoring of fish and marine mammals), physical (hydrodynamics), and social (local ecological knowledge) sciences can provide a more complete understanding of complex and turbulent ecosystems for better informed decision-making. We offer several recommendations to facilitate the adaptation and implementation of our interdisciplinary framework to diverse research contexts, with a focus on interdisciplinary training for the next generation of marine scientists.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

D and D Research on KM-IT Platform - 20494

The Knowledge Management Information Tool (KM-IT) is a web-based system developed to maintain and preserve the Department of Energy's (DoE's) knowledge base. The system was developed by Florida International University's Applied Research Center (FIU-ARC) with the support of the D and D community including the DOE Office of Environmental Management, and with the collaboration and support of the DoE's Energy Facility Contractors Group (EFCOG) and the former ALARA Centers at Hanford and Savannah. The KM-IT system is a community driven system tailored to serve the technical issues faced by the workforce across the DOE Complex. This KM-IT web-based interactive system is operational and available for use at www.dndkm.org and is currently comprised of the following modules: Web Crawler, Hotline, Technology, Hanford's ALARA Center Reports, Specialist Directory, Lessons Learned, Best Practices, Video/Picture Library, Vendors and Industry News. The Web Crawler dynamically searches through the KM-IT repository as well as the web and displays search results based on the search criteria. The Hotline allows registered users to post questions/problems related to D and D and to receive solutions from a subject-matter specialist. The Technology module serves as repository of D and D technologies and contains technology/ demonstration fact sheets and vendor information. D and D community members can add Lessons Learned, Best Practices, and Pictures/Videos to the D and D repository, after a formal approval process. The Vendor module provides a directory of commercial vendors who provide D and D related technologies, supplies, and services. KM-IT makes an excellent use of the knowledge that exists within the D and D community by allowing D and D project managers around the DOE complex to collaborate by sharing innovative ideas, past experiences, and practices and by maintaining a directory of subject matter specialists. FIU has developed the dedicated module on KM-IT platform to publish D and D research being performed at FIU. This module highlights current EM research efforts and activities in support of D and D being performed at FIU/SRNL associated with fixatives and intumescent products. FIU will expand this module to include the recent and current D and D research being performed across multiple DOE EM sites, national labs and universities. FIU will collaborate with SRNL, INL, ANL and other universities to explore and publish D and D research activities on KM-IT. As a result, the user community will have a centralized location to review new D and D related research across the DOE EM complex. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Simultaneously characterization of tumoral angiogenesis and vasculogenesis in stem cell-derived teratomas

Highlights: • CAM supports the growth and differentiation of embryonic stem cells into teratomas. • In teratomas, parenchymal Embryonic stem cell-derived endothelial cells form chimeric vessels with stromal endothelial cells. • CAM allows the simultaneously characterization of vasculogenesis and angiogenesis processes. Tumor neovascularization may occur via both angiogenic and vasculogenic events. In order to investigate the vessel formation during tumor growth, we developed a novel experimental model that takes into account the differentiative and tumorigenic properties of Embryonic Stem cells (ESCs). Leukemia Inhibitory Factor-deprived murine ESCs were grafted on the top of the chick embryo chorionallantoic membrane (CAM) in ovo. Cell grafts progressively grew, forming a vascularized mass within 10 days. At this stage, the grafts are formed by cells with differentiative features representative of all three germ layers, thus originating teratomas, a germinal cell tumor. In addition, ESC supports neovascular events by recruiting host capillaries from surrounding tissue that infiltrates the tumor mass. Moreover, immunofluorescence studies demonstrate that perfused active blood vessels within the tumor are of both avian and murine origin because of the simultaneous occurrence of angiogenic and vasculogenic events. In conclusion, the chick embryo ESC/CAM-derived teratoma model may represent a useful approach to investigate both vasculogenic and angiogenic events during tumor growth and for the study of natural and synthetic modulators of the two processes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Development of Enabling Technologies for Chemical Looping Combustion and Chemical Looping with Oxygen Uncoupling (Final Report)

This report summarizes results from the project, “Development of Enabling Technologies for Chemical Looping Combustion and Chemical Looping with Oxygen Uncoupling,” which evaluated several aspects of dual fluidized bed chemical looping combustion and chemical looping with oxygen uncoupling (CLOU). The objective was to provide tools and enabling technologies to help advance fluidized bed chemical looping technology to pilot, demonstration and commercial scale. One focus area is oxygen carriers, which are key to chemical looping combustion. The copper oxygen carrier-coal ash system was systematically evaluated through a combination of thermodynamic modeling and lab-scale experiments, taking into consideration different oxygen carrier support materials and coal types. A method of mapping “safe” and “risk” zones for different combinations was established, and recommendations for target conditions are provided. In addition, a simple solution for limiting negative influence of some coal ashes, namely adding small amounts of calcium to the system, is proposed. In addition, a novel process for recovering and recycling copper from spent oxygen carriers is proposed. A new approach for design and operation of loop seals in a CLOU system was developed, and involves distinct gas injection points and a short horizontal section to help control the fate of the fluidizing gases. For the air-to-fuel reactor loop seal, the upstream side is fluidized with air, ideally input into the side rather than into the bottom, which prevents uncoupling (reduction) of the oxygen carrier before entering the fuel reactor. Also, alternative for separating oxygen carrier particles and gas in circulating fluidized bed-based chemical looping system is proposed. A new reduced reaction scheme for conversion of coal in copper-based CLOU was developed and implemented into CPFD Software’s Barracuda VR package. The resulting model provides higher fidelity than the baseline, especially when it comes to minor reactions that are part of the overall combustion environment. For in-reactor heat extraction, it was determined in this project that the best way to do that in a dual circulating fluidized-bed system is through heat exchange low in the air reactor. The air reactor is the hotter of the two and for a fast-fluidized circulating bed, the lower, more dense section has a higher heat transfer coefficient and offers more consistent particle-wall contact since it doesn’t have the splashing behavior the top of the bed does. It was determined that just the wall surface area in the lower quarter to third of the air reactor is sufficient to control temperatures in both reactors. Finally, consideration was given to a new concept for CLC, which involves a staged fuel reactor with a different type of oxygen carrier in each stage.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Processability and Material Behavior of NiTi Shape Memory Alloys Using Wire Laser-Directed Energy Deposition (WL-DED)

Utilizing additive manufacturing (AM) techniques with shape memory alloys (SMAs) like NiTi shows great promise for fabricating highly flexible and functionally superior 3D metallic structures. Compared to methods relying on powder feedstocks, wire-based additive manufacturing processes provide a viable alternative, addressing challenges such as chemical composition instability, material availability, higher feedstock costs, and limitations on part size while simplifying process development. This study presented a novel approach by thoroughly assessing the printability of Ni-rich Ni55.94Ti (Wt. %) SMA using the wire laser-directed energy deposition (WL-DED) technique, addressing the existing knowledge gap regarding the laser wire-feed metal additive manufacturing of NiTi alloys. For the first time, the impact of processing parameters—specifically laser power (400–1000 W) and transverse speed (300–900 mm/min)—on single-track fabrication using NiTi wires in the WL-DED process was examined. An optimal range of process parameters was determined to achieve high-quality prints with minimal defects, such as wire dripping, stubbing, and overfilling. Building upon these findings, we printed five distinct cubes, demonstrating the feasibility of producing nearly porosity-free specimens. Notably, this study investigated the effect of energy density on the printed part density, impurity pick-up, transformation temperature, and hardness of the manufactured NiTi cubes. The results from the cube study demonstrated that varying energy densities (46.66–70 J/mm3) significantly affected the quality of the deposits. Lower to intermediate energy densities achieved high relative densities (>99%) and favorable phase transformation temperatures. In contrast, higher energy densities led to instability in melt pool shape, increased porosity, and discrepancies in phase transformation temperatures. These findings highlighted the critical role of precise parameter control in achieving functional NiTi parts and offer valuable insights for advancing AM techniques in fabricating larger high-quality NiTi components. Additionally, our research highlighted important considerations for civil engineering applications, particularly in the development of seismic dampers for energy dissipation in structures, offering a promising solution for enhancing structural performance and energy management in critical infrastructure.

Dabbaghi, Hediyeh↗
DOE OSTI2025

Energy-Efficient Capacitive Deionization through Electrode Modification and Process Development

Electrochemical separation technologies, such as capacitive deionization (CDI), are promising for addressing global energy and water challenges. However, there is a need to improve the performance, better understand property-performance relationships, and evaluate the longevity of CDI electrodes. This study explores the chemical modification of electrodes and the adjustment of CDI operating parameters. Results indicate that nitric acid (HNO3) conditioning of activated carbon cloth (ACC) electrodes removes metal oxides, introduces oxygen and nitrogen functionalities, and increases the specific capacitance (16% at 1 mV/s). Moreover, these changes in electrode properties positively impact device-level CDI performance. Through HNO3-conditioning of the ACC and tuning of the operational parameters, this work demonstrates higher electrosorption capacity (4.0x), greater charge efficiency (90% vs 24%), and lower energy consumption (3.8x). Despite these enhancements, limitations of the HNO 3 -conditioned ACC include decreased desorption kinetics and a 32% loss in electrosorption capacity after 200 cycles. Overall, this work provides guidance on using oxidative pretreatment via HNO 3 to modify ACC electrodes for CDI and evaluates the trade-offs associated with varying operational parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Atomic Layer Deposition for Improved Biomass Conversion Catalysts

Heterogeneous catalysts are a key enabler of the transition towards a sustainable, bio-based economy for fuels and chemicals. However, the harsh conditions in many biomass conversion processes lead to nanoparticle sintering, support collapse, and metal leaching in conventional PGM catalysts. Next-generation catalysts must be developed to address these stability challenges. This presentation will discuss ongoing work between the Catalytic Carbon Transformation and Scale-Up Center at NREL and various industrial partners to develop scalable and cost-effective atomic layer deposition (ALD) coatings for improving the performance of biomass conversion catalysts. The substantial focus will be devoted to the benefits of TiO2 ALD coatings on supported Pd hydrogenation catalysts. Ten cycles of TiO2 ALD were found to dramatically improve the activity of a conventional Pd/Al2O3 catalyst towards aromatic hydrogenation, despite partial coverage of the Pd sites by the ALD layer. Subsequent advanced characterization and atomic-scale computational modeling revealed that the ALD coating weakened the adsorption strength of hydrogenation surface intermediates, leading to higher reaction rates. Reaction testing after exposure to sulfur impurities, high temperature oxidation, and hydrothermal treatment demonstrated the improved stability of the ALD-coated catalyst. Additionally, the ALD synthesis process was found to be scalable over two orders of magnitude with minimal deviation in synthesized catalyst properties. These results were contextualized with cost models of industrial ALD coating and aromatic hydrogenation processes to further refine the value proposition of ALD coatings. Given the demonstrated improvements in hydrogenation, TiO2 ALD coatings have also been applied to supported Pt catalysts for use in other biomass conversion reactions, such as hydrodeoxygenation for the production of sustainable aviation fuel (SAF) and the oxidation of glucose to bio-derived gluconic acid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Spatiotemporal and Statistical Mapping of Transition Metal Equilibria in Alkaline Media

Transition metal dissolution and redeposition (D/R) kinetics in alkaline media play a critical role in various chemical and electrochemical processes. Competitive reaction kinetics between different transition metals can modulate individual metal behavior in these processes. To date, these phenomena have remained largely unmeasured, and even when captured, they are difficult to statistically characterize due to their dynamic nature, simultaneous occurrence, and spatially heterogeneous nature. Here, in this study, we develop a statistical analysis framework based on in situ and operando X-ray fluorescence microscopy (XFM) to investigate the relative D/R kinetics of multiple transition metals in alkaline media. By employing statistical analysis, we quantify the spatial distribution of D/R species and assess the rate at which the system reaches equilibrium under varying reaction conditions. We show that pH does not simply change the rate of dissolution and redeposition, but reorganizes the cross-element kinetic correlations among Ni, Fe, and Mn and accelerates the spatial equilibration of D/R events, as quantified through correlation analysis, reaction-rate estimation, probability function distributions, and texture-based monitoring statistics. Additionally, we demonstrate how modifying the solvent environment can influence D/R kinetics, providing a pathway for tuning materials synthesis and process optimization. Our study offers valuable insights into the complex interplay between different transition metals and provides a reliable statistical framework for spatial analysis of diverse imaging data sets, enabling deeper extraction of latent information across multiple modalities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Incorporation of market signals for the optimal design of post combustion carbon capture systems

Recent studies have shown that fossil generators equipped with post-combustion carbon capture (PCC) systems are needed to reduce the cost of deep decarbonization. Such generators need to be flexible and responsive to grid conditions, particularly in a high variable renewable energy (VRE) environment. In this work, we evaluate the net present value (NPV) of retrofitting an existing natural gas combined cycle (NGCC) unit with a flexible PCC system while incorporating market signals from a high VRE grid. We use our industrial partner’s NGCC configuration as representative of existing NGCC units and Svante’s rapid-temperature swing adsorption (TSA) for PCC. Because of its ability to rapidly startup/shutdown and ramp-up/ramp-down, the chosen capture technology is very attractive for load-following operations. For a given set of market signals, we formulate a two-stage stochastic multi-period optimization problem, under the price-taker assumption, to simultaneously optimize the design of the capture system and operation of the entire plant. Rigorous models for the NGCC unit, PCC system, and compression system are developed using commercial process simulators and validated with either plant or vendor data. For computational tractability, we develop surrogate/reduced-order models for use in the optimization problem. The surrogate model for the NGCC plant is constructed by linearizing the rigorous dynamic model at 75% load, while data-driven nonlinear surrogate models for the capture and compression systems are constructed using simulation data from the rigorous models. The optimization problem, formulated as a mixed integer bilinear program, is implemented in the IDAES® integrated platform and solved to global optimality using Gurobi 9.5. Using this formulation, we determine the profitability of retrofitting an existing NGCC unit with the chosen capture system for multiple regions in the U.S. under two scenarios with different carbon prices. Importantly, the results show that the optimal decision strongly depends on the region and on the carbon price, thereby demonstrating the importance of the inclusion of market signals in the design process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Development of transparent, particle‐loaded photoresins for volumetric additive manufacturing of silica glass

Abstract Additive manufacturing of glass aims to change the paradigm of glass manufacturing by allowing for improved customization coupled with lower energy and post‐processing needs. Fabrication of glass via volumetric additive manufacturing (VAM) involves printing in a silica‐loaded photopolymer resin with subsequent thermal processing and adds additional advantages by allowing for rapid printing of parts with smooth surfaces and no supports. Previous work in glass VAM has demonstrated fabrication of optical quality microoptics with overall dimensions on the scale of tens of cubic millimeters. For applications requiring glass printed on the scale of cubic centimeters the rheology, scattering, and green part strength must be controlled via resin formulation. Here, we present insight into a novel glass photopolymer resin suitable for VAM and in the effect of tuning formulation on the ability to produce dense glass parts with volumes on the scale of cubic centimeters.

Myers, Luke A.↗
DOE OSTI2022

Selective Sulfidation for Rare Earth Element Separation

Rare earth metals and compounds are critical components of advanced materials for energy, structural alloys, and transportation. These low-tonnage elements are sourced together as by- and co-products, and presently require complete hydrometallurgical dissolution followed by liquid–liquid separation for their isola- tion and production. There is great interest in developing alternatives to those hydrometallurgical processes in order to limit the environmental impact of rare earth element supply. Herein, we present selective sulfidation as a novel, high- temperature alternative to facilitate physical separation of rare earth by- and co- product elements. We explore the thermodynamics of rare earth oxide sulfidation with elemental sulfur, and discuss the role of carbon in controlling sulfidation selectivity. We apply these findings to the demonstration of selective sulfidation for iron-rare earth and lanthanide-lanthanide separations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A guide to diagnosing colored resonances at hadron colliders

We present a comprehensive study on how to distinguish the properties of heavy dijet resonances at hadron colliders. A variety of spins, chiral couplings, charges, and QCD color representations are considered. Distinguishing the different color representations is particularly difficult at hadron colliders. To determine the QCD color structure, we consider a third jet radiated in a resonant dijet event. We show that the relative rates of three-jet versus two-jet processes are sensitive to the color representation of the resonance. We also show analytically that the antennae radiation pattern of soft radiation depends on the color structure of dijet events and develops an observable that is sensitive to the antennae patterns. Finally, we exploit a Convolutional Neural Network with Machine Learning techniques to differentiate the radiation patterns from different colored resonances and find encouraging results to discriminate them. We demonstrate our results numerically at a 14 TeV LHC, and the methodology presented here should be applicable to other future hadron colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

CO 2 electroreduction favors carbon isotope 12 C over 13 C and facilitates isotope separation

We discovered that CO 2 electroreduction strongly favors the conversion of the dominant isotope of carbon ( 12 C) and discriminates against the less abundant, stable carbon 13 C isotope. Both absorption of CO 2 in the alkaline electrolyte and CO 2 electrochemical reduction favor the lighter isotopologue. As a result, the stream of unreacted CO 2 leaving the electrolyzer has an increased 13 C content, and the depletion of 13 C in the product is several times greater than that of photosynthesis. Using a natural abundance feed, we demonstrate enriching of the 13 C fraction to ~1.3% (i.e., +18%) in a single-pass reactor and propose a scalable and economically attractive process to yield isotopes of a commercial purity. Our finding opens pathways to both cheaper and less energy-intensive production of stable isotopes ( 13 C, 15 N) essential to the healthcare and chemistry research, and to an economically viable, disruptive application of electrolysis technologies developed in the context of sustainability transition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Plasma image classification using cosine similarity constrained convolutional neural network

Plasma jets are widely investigated both in the laboratory and in nature. Astrophysical objects such as black holes, active galactic nuclei and young stellar objects commonly emit plasma jets in various forms. With the availability of data from plasma jet experiments resembling astrophysical plasma jets, classification of such data would potentially aid in not only investigating the underlying physics of the experiments but also the study of astrophysical jets. In this work we use deep learning to process all of the laboratory plasma images from the Caltech Spheromak Experiment spanning two decades. We found that cosine similarity can aid in feature selection, classify images through comparison of feature vector direction and be used as a loss function for the training of AlexNet for plasma image classification. We also develop a simple vector direction comparison algorithm for binary and multi-class classification. Using our algorithm we demonstrate 93 % accurate binary classification to distinguish unstable columns from stable columns and 92 % accurate five-way classification of a small, labelled data set which includes three classes corresponding to varying levels of kink instability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Multi-Area Model-Free State Estimation via Distributed Tensor Decomposition

This paper proposes a model-free method for distribution system state estimation based on tensor completion using canonical polyadic decomposition. In particular, we consider a setting where the network is divided into multiple areas. The measured physical quantities at buses located in the same area are processed by an area controller. A third-order tensor is constructed to collect these measured quantities. The measurements are analyzed locally to recover the full state information of the network. A closed-form iterative algorithm based on the alternating direction method of multipliers is developed to obtain the low-rank factors of the whole network state tensor where information exchange happens only between neighboring areas. To demonstrate the efficacy of the developed algorithm, numerical simulations are carried out using an IEEE test system.

alternating direction method of multipliers↗