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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 145 records · Page 8

Overview of the fusion nuclear science facility, a credible break-in step on the path to fusion energy

Here the Fusion Nuclear Science Facility (FNSF) is examined as part of a two step program from ITER to commercial power plants. This first step is considered mandatory to establish the materials and component database in the real fusion in-service environment before proceeding to larger electricity producing facilities. The FNSF can be shown to make tremendous advances beyond ITER, toward a power plant, particularly in plasma duration and fusion nuclear environment. A moderate FNSF is studied in detail, which does not generate net electricity, but does reach the power plant blanket operating temperatures. The full poloidal Dual Coolant Lead Lithium (DCLL) blanket is chosen, with alternates being the Helium Cooled Lead Lithium (HCLL) and Helium Cooled Ceramic Breeder/Pebble Bed (HCCB/PB). Several power plant relevant choices are made in order to follow the philosophy of targeted technologies. Any fusion core component must be qualified by fusion relevant neutron testing and highly integrated non-nuclear testing before it can be installed on the FNSF in order to avoid the high probability of constant failures in a plasma-vacuum system. A range of missions for the FNSF, or any fusion nuclear facility on the path toward fusion power plants, are established and characterized by several metrics. A conservative physics strategy is pursued to accommodate the transition to ultra-long plasma pulses, and parameters are chosen to represent the power plant regime to the extent possible. An operating space is identified, and from this, one point is chosen for further detailed analysis, with R = 4.8 m, a = 1.2 m, I P = 7.9 MA, B T = 7.5 T, β N < 2.7, n/n Gr = 0.9, f BS = 0.52, q95 = 6.0, H 98 ~1.0, and Q = 4.0. The operating space is shown to be robust to parameter variations. A program is established for the FNSF to show how the missions for the facility are met, with a He/H, a DD and 5 DT phases. The facility requires ~25 years to complete its DT operation, including 7.8 years of neutron production, and the remaining spent on inspections and maintenance. The DD phase is critical to establish the ultra-long plasma pulse lengths. The blanket testing strategy is examined, and shows that many sectors have penetrations for heating and current drive (H/CD), diagnostics, or Test Blanket Modules (TBMs). The hot cell is a critical facility element in order for the FNSF to perform its function of developing the in-service material and component database. The pre-FNSF R&D is laid out in terms of priority topics, with the FNSF phases driving the time-lines for R&D completion. A series of detailed technical assessments of the FNSF operating point are reported in this issue, showing the credibility of such a step, and more detailed emphasis on R&D items to pursue. These include nuclear analysis, thermo-mechanics and thermal-hydraulics, liquid metal thermal hydraulics, transient thermo-mechanics, tritium analysis, maintenance assessment, magnet specification and analysis, materials assessments, core and scrape-off layer (SOL)/divertor plasma examinations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Influence of PV Module Materials and Design on Solder Joint Thermal Fatigue Durability

Finite element model (FEM) simulations have been performed to elucidate the effect of flat plate photovoltaic (PV) module materials and design on PbSn eutectic solder joint thermal fatigue durability. The statistical method of Latin Hypercube sampling was employed to investigate the sensitivity of simulated damage to each input variable. Variables of laminate material properties and their thicknesses were investigated. Using analysis of variance, we determined that the rate of solder fatigue was most sensitive to solder layer thickness, with copper ribbon and silicon thickness being the next two most sensitive variables. By simulating both accelerated thermal cycles (ATCs) and PV cell temperature histories through two characteristic days of service, we determined that the acceleration factor between the ATC and outdoor service was independent of the variables sampled in this study. This result implies that an ATC test will represent a similar time of outdoor exposure for a wide range of module designs. This is an encouraging result for the standard ATC that must be universally applied across all modules.

14 SOLAR ENERGY↗

FARM User Guidance and Instructions

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, the general workflow and the software requirements of FARM module are summarized, and the detailed instructions for installing FARM software, running built-in example cases, deriving Linear Parameter-Varying (LPV) state-space models, and using FARM for user-defined power dispatch problems are provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

FARM supervisory capabilities for thermal energy storage

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, an overview of the major capabilities of the latest release of FARM is provided, along with a summary of the tool demonstration campaign conducted at the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility. These results assess the performance of the control system architecture embedding FARM both as a Validator of the HERON power dispatcher and as a real time Supervisory control scheme. Additionally, the report outlines the areas that FARM might benefit from, along with proposed solutions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Multi-rate OCDMA system BER performance evaluations for different ML-code sequences

This paper analyzes Bit Error Rate (BER) of Optical Code Division Multiple Access (OCDMA) networks for different class of services which are data, voice, and video; whereas Multi-Length Weighted Modified Prime Code (ML-WMPC) sequences are utilized as a spreading code in with respect to previously used ML-Optical Orthogonal codes. Due to variations in bit rates between the mentioned services, each of them assigns a different WMPC sequence length. In addition, the shot noise, thermal noise, and the Multiple Access Interference (MAI) are included and considered as sources of noise in the BER performance analysis. Furthermore, Pulse Position Modulation, Manchester encoding and MAI cancellation (MAIC) technique are utilized to improve the network performance at a higher number of active users. For analysis, the BER performance calculations are investigated for three types of OCDMA receivers such as simple receiver, receiver with MAIC technique, and receiver with MAIC and Manchester encoding. Moreover, the BER mathematical models have been introduced for different bit rates according to the type of service in the presence of the ML-WMPC and the last of three mentioned OCDMA receivers. Finally, these models and their results are compared with the other existing models, where the results show an improvement in BER performance in the proposed approach.

42 ENGINEERING↗

A Siamese CNN + KNN-Based Classification Framework for Non-intrusive Load Monitoring

Through the development of smart grids, programs such as demand side response, have been presented as auxiliary services to the real-time operation of distributed networks. In order to provide consumers information on their energy consumption, so that a modulation in consumption is possible, non-intrusive load monitoring has been introduced as an solution to this pattern recognition problem. Non-intrusive load monitoring enables the modeling of electrical loads connected to the low-voltage system, considering only a single measurement point. Presented state-of-the-art solutions though, consider availability of data as well as representation of all possible classes of the environment. This is of course a most conservative hypothesis, since in real-life applications availability of such data is much difficult, as well as the dynamic behavior of models is implicitly evolving in time. Here, a framework that uses neural Siamese networks with k-nearest neighbor clustering is presented toward non-intrusive load monitoring. Online learning feature is implemented, which relaxes the hypothesis of data requirements as well addresses the evolving nature of load profile. k-nearest clustering allows nonlinear characteristic space modelling. Test results using synthetics and real-life data show that the solution, besides obtaining a good generalizability in the classification, also obtained results with an accuracy of 95.77%.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Power Electronics Based Self-Monitoring and Diagnosing for Photovoltaic Systems

Faults in photovoltaic (PV) systems can seriously affect the efficiency, energy yield, cost, safety, and reliability of PV plants. Condition monitoring of PV plants is, therefore, a very important approach to estimating the health condition of PV modules and power electronics in the system. However, additional hardware for PV system monitoring adds cost to the system's operation; delayed maintenance service also causes additional energy production loss. The Center for Power Electronics Systems (CPES) at the Virginia Polytechnic Institute and State University and Siemens Cooperate Research developed the online impedance measurement for a PV panel self-monitoring and diagnosing technology using the DC-DC converter connected to the panel. Small-signal impedances of a monocrystalline silicon PV panel were modeled and simulated to reflect fault conditions such as the short-circuit, hot-spot, and junction box faults. Modeling and simulation results were validated firstly using a test setup consisting of a solar simulator, a network analyzer, small-signal injectors, and a monocrystalline PV panel rated at 300 W.

14 SOLAR ENERGY↗

An efficient hybrid visible light communication/radio frequency system for vehicular applications

This paper focuses on improving the traffic system for Intelligent Transportation System (ITS) by using an imaging receiver instead of photodiode as a single receiver. Here, two simple traffic models have been proposed and analyzed in order to optimize the design characteristics such as signal to noise ratio, required power, received information, bit error rate, and modulation technique. First, a standalone visible light communication (VLC) with different modulation techniques is considered. The On–OFF Keying, L-Pulse Position Modulation (L-PPM), and Inverse L-Pulse Position Modulation (I-L-PPM) are investigated. Then, a hybrid communication system utilizing VLC and radio frequency (RF) is proposed for position-based services. The VLC/RF system combines the benefits of both systems and offers long distance transmission which is an important concern in ITS and in order to improve the link reliability in infrastructure to vehicle communications. This means that the probability of having a communication link between the transmitter and receiver is maintained without interruption. Then, the performance is finally evaluated. The obtained simulation results show a considerable increase in the received information using the proposed hybrid VLC/RF system compared to a VLC system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Future SDN-HPON Control Plane Architecture and Protocol for On-Demand Terabit End-to-End Extreme-Scale Science Applications

The UC Davis team conducted architecture, algorithm and experimental studies for next generation ultra-high-bandwidth optical networks in support of extreme-scale science applications. In particular, over the course of this 3-year project, the UC Davis team achieved the following main accomplishments: Designed a network architecture for automated multi-domain service provisioning: Designed information exchange schemes between autonomous systems (domains) Designed application programming interfaces to orchestrate resource reservation in data centers, high performance computation facilities, and communication networks belonging to different autonomous systems Experimentally assessed the multi-domain network architecture in a distributed field trial set-up connecting premises in three continents Designed a broker-based orchestrated multi-domain optical networking framework supporting observe-analyze-act cycle based cognitive inter-domain service provisioning: Designed an inter-domain operation mechanism, e.g., topology abstraction, for the broker plane and domain managers to collaboratively accomplish inter-domain service provisioning while respecting the autonomy of each administrative domain Designed an alien wavelength monitoring scheme and an artificial neural network based optical signal-to-noise ratio estimator for quality-of-transmission aware inter-domain service provisioning Developed a deep neural network based multi-domain traffic predictor and a cognitive routing and spectrum assignment algorithm to realize knowledge-based autonomous traffic engineering in multi-domain networks Implemented an optical signal-to-noise ratio estimator and traffic predictor with Google’s Tensor flow and assessed their performance using experimental and synthetic data Demonstrated the benefits of the proposed cognitive schemes with experiments ona two-domain elastic optical network testbed and evaluations on a six-domain simulation framework Built a two-domain software-defined networking control plane testbed using the ONOS platform and demonstrated the workflow of broker and domain manager cooperation, including hierarchical performance monitoring, topology abstraction and cognitive resource allocation. Designed self-learning cognitive service provisioning schemes using advanced machine learning technologies: Designed a self-taught anomaly detection framework for optical networks, including an unsupervised data clustering module for pattern recognition, a supervised data regression and classification module for online anomaly detection, and the system operation principle Experimentally validated the effectiveness of the self-taught anomaly detection framework with various failure/anomaly scenarios. Designed a self-learning autonomic routing, modulation and spectrum assignment (RMSA) provisioning framework for elastic optical networks with deep reinforcement learning. Designed effective modeling and training mechanisms for the self-learning RMSA framework Conducted extensive numerical simulations with various traffic patterns and topologies to verify the advantage of the self-learning RMSA framework.

42 ENGINEERING↗

Autonomic Intelligent Cyber Sensor (AICS) Version 1.0.1

The Autonomic Intelligent Cyber Sensor (AICS) provides cyber security and industrial network state awareness for Ethernet based control network implementations. The AICS utilizes collaborative mechanisms based on Autonomic Research and a Service Oriented Architecture (SOA) to: 1) identify anomalous network traffic; 2) discover network entity information; 3) deploy deceptive virtual hosts; and 4) implement self-configuring modules. AICS achieves these goals by dynamically reacting to the industrial human-digital ecosystem in which it resides. Information is transported internally and externally on a standards based, flexible two-level communication structure.

Vollmer, DenisTodd↗

SIW21-95: Hybridizing Synchronous Condensers with Grid-Forming Battery Energy Storage Systems

One of the main challenges associated with deployment of high shares of inverter-based resources (IBRs) in power grid is not only reduced system inertia but also degrading system strength that may cause severe stability impacts. A minimum level of system strength is needed for the power system to remain stable under normal conditions and to return to a steady state condition following a system disturbance. Significant system strength reduction is expected in almost all planned areas for solar and wind generation deployment. Synchronous condensers (SC) have been considered as one main technology to address the system strength issues for the areas with high levels of IBRs. SCs can help improving reliability and resiliency of power system but they do not provide the full range of services needed by power systems for reliable and economic integration of high shares of inverter-coupled variable generation such as PV generation. Services related to active power controls cannot be provided by SCs due to lack of prime mover. Even for provision of reactive power SCs have certain constraints based on their thermal and stability limits. NREL has been conducting research on a hybridized concept that combines SCs with grid forming (GFM) battery energy storage systems (BESS). This super flexible AC transmission system (SuperFACTS) that combines these two technologies in a single plant under the same controller offers a unique scalable set of services to the power system at all levels (transmission, sub-transmission, distribution, islands and isolated microgrids). Depending on use cases, SuperFACTS can be controlled to provide fully dispatchable and flexible operation using energy storage component, provide a full range of existing and future ancillary and reliability services to the grid (similar or better than conventional sources), maintain adequate levels of grid strength and inertia, and provide fault current for proper operation of protection systems. Therefore, this economic and easy to commercialize solution has potential for significant impacts on certain segments of global energy sector. All types of gird services (market based, reliability and resiliency) can be provided by SuperFACTS plants. GFM BESS can act as a self-black start source for each SuperFACTS module, which in turn can act a black start resource for co-located PV and wind power plants, segments of transmission and distribution networks, for conventional power plants, etc. The issue of in-rush currents during black start is addressed by overcurrent capability of SCs. In this paper we describe the results of modeling for SuperFACTS concept.

grid forming↗

Design, Manufacture, and Experimental Serviceability Validation of ITER Blanket Components

In 2014, the Russian Federation and the ITER International Organization signed two Procurement Arrangements (PAs) for ITER blanket components: 1.6.P1ARF.01 “Blanket First Wall” of February 14, 2014, and 1.6.P3.RF.01 “Blanket Module Connections” of December 19, 2014. The first PA stipulates development, manufacture, testing, and delivery to the ITER site of 179 Enhanced Heat Flux (EHF) First Wall (FW) Panels intended for withstanding the heat flux from the plasma up to 4.7MW/m{sup 2}. Two Russian institutions, NIIEFA (Efremov Institute) and NIKIET, are responsible for the implementation of this PA. NIIEFA manufactures plasma-facing components (PFCs) of the EHF FW panels and performs the final assembly and testing of the panels, and NIKIET manufactures FW beam structures, load-bearing structures of PFCs, and all elements of the panel attachment system. As for the second PA, NIKIET is the sole official supplier of flexible blanket supports, electrical insulation key pads (EIKPs), and blanket module/vacuum vessel electrical connectors. Joint activities of NIKIET and NIIEFA for implementing PA 1.6.P1ARF.01 are briefly described, and information on implementation of PA 1.6.P3.RF.01 is given. Results of the engineering design and research efforts in the scope of the above PAs in 2015–2016 are reported, and results of developing the technology for manufacturing ITER blanket components are presented.

42 ENGINEERING↗

Historical and Future Learning for the New Era of Multi-Terawatt Photovoltaics

Solar photovoltaics (PV) is entering a new era of multi-terawatt deployment, with 2 TW already in service and more than 75 TW predicted in many scenarios by 2050. This next era has been enabled by over five decades of cumulative advances in PV module cost reduction, performance and reliability. The current scale of deployment also introduces new needs, opportunities and challenges. In this Perspective we frame a path forwards based on learning, broadly defined as a combination of expansion of knowledge and advances through research and development, experience and collaboration. We discuss historical topics where learning has driven PV deployment until now, and emerging areas that are required to sustain high levels of future deployment. We expect progress to continue in terms of module price, performance and reliability, driven by advances in PV cell and module design, the emergence of tandem devices and increased focus on extending module lifetimes. Large-scale deployment also means large-scale sustainability and responsibility. We therefore posit that additional metrics, such as the impact on global CO2 emissions, resource consumption and design for reuse and recycling, will become increasingly important to the PV industry and provide opportunities for further learning.

14 SOLAR ENERGY↗

Highly Available Nuclear Power for Mission-Critical Applications

Some energy consumers require power on an anytime, all-year-round basis with a high level of certainty, including defense installations, isolated communities, and some industrial processes. For these customers, interruptions in electricity or heat can mean substantial financial loss or even loss of life. In the absence of grid-scale energy storage, a high level of power availability can be accomplished only through the robustness and redundancy of power generators. The NuScale small modular reactor design is well suited to provide highly available power because of several features related to both the nuclear steam supply system and the overall plant design. In analogy to Redundant Array of Independent Disks (RAID) systems used to provide highly reliable data storage, a NuScale plant can assure sustained power generation by virtue of its Redundant Array of Integral Reactors (RAIR).This paper describes the NuScale RAIR plant features and summarizes the results of a rigorous analysis of RAIR availability as a function of power or, conversely, the RAIR plant output power as a function of power availability. The analysis utilized the Matrix Laboratory code (MATLAB) and included probability distributions for the frequency and duration of module outages due to planned and unplanned events. Further, the study evaluated the impact of implementing turbine bypass rather than module shutdown and using one or more modules to supply house loads in the case of loss of off-site power (LOOP). Availability results are presented for a 12-module RAIR plant with and without turbine bypass enabled during a LOOP and for different possible connections to the off-site power distribution grid and dedicated service loads. Results indicate that a very high level of availability can be achieved at relatively high power output levels, regardless of turbine bypass and dedicated load connection, compared to the operating fleet.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

An agent-based deployment decision-support system for electric vehicle services

METS-R ADDSEVS simulator is a high fidelity, parallel, agent-based evacuation simulator for multi-modal energy-optimal trip scheduling in real-time (METS-R) at transportation hubs. It consists of two modules. The first one is the traffic simulator module; the second one is the high-performance computing (HPC) module. More details can be found at https://umnilab.github.io/METS-R_doc/.

Lei, Zengxiang↗

Durability of Polymeric Encapsulation Materials for Concentrating Photovoltaic Systems (Presentation)

Many concentrating photovoltaic (CPV) systems use a polymeric encapsulant to couple and optical component and/or coverglass to the cell. In that location, the encapsulation improves the transmission of concentrated optical flux through interface(s), while protecting the cell from the environment. The durability of encapsulation materials, however, is not well established relative to the desired service life of 30 years. Therefore, we have initiated a screen test to identify the field-induced failure modes for a variety of popular PV encapsulation materials. An existing CPV module (with no PV cells present) was modified to accommodate encapsulation specimens. The module (where nominal concentration of solar flux is 500x for the domed-Fresnel design) has been mounted on a tracker in Golden, CO (elevation 1.79 km). Initial results are reported here for 18 months cumulative exposure, including the hottest and coldest months of the past year. Characteristics observed at intervals during that time include: visual appearance, direct and hemispherical transmittance, and mass. Degradation may be assessed from subsequent analysis (including yellowness index and cut-on frequency) relative to the ambient conditions present during field exposure. The fluorescence signature observed of all the silicone specimens is examined here, including possible factors of causation -- the platinum catalyst used in the addition cured materials as well as the primer used to promote adhesion to the quartz substrate and superstrate.

14 SOLAR ENERGY↗

Characterization of mechanical properties and deformation behavior of highly irradiated 316L stainless steel from target modules at the Spallation Neutron Source using digital image correlation analysis

Tensile specimens with irradiation doses ranging from approximately 0.7 to 7.6 displacements per atom (dpa) were fabricated from 316L samples removed from Spallation Neutron Source (SNS) target vessels after service. Tensile tests were performed in conjunction with digital image correlation (DIC) characterization, which permitted detailed analysis of the strain distribution and deformation behavior of the specimen gauge sections during testing. The results show, while considerable hardening (500–700 MPa increase in yield strength) occurred in the 316L SNS target material with increasing dose, appreciable ductility (19–23% total elongation) remained in the material after irradiation to 7.6 dpa in the mixed neutron/proton environment of the SNS target region. The DIC data showed the strain distribution and deformation behavior of all irradiated specimens were nonuniform during testing. Strain localization in the form of deformation bands or “hotspots” was observed during testing, and in some specimens, the bands propagated as deformation waves along the gauge section. The “traveling wave” deformation behavior affected the amount of elongation each specimen achieved, and the scatter in the elongation data was attributed to the large variation in deformation behavior observed among different specimens. Bands of localized strain, or deformation bands, oriented at specific angles were observed in two-dimensional plots of the strain distribution in the gauge sections of some specimens. Overall, this paper describes the experimental procedures, results, and deformation behavior of tensile specimens from SNS targets after service and illustrates the value of DIC characterization during tensile testing of irradiated materials.

36 MATERIALS SCIENCE↗