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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 OSTI2025

eMosaic: Electrification Mosaic Platform for Grid Informed Smart Charging Management (Final Scientific/Technical Report)

ABB (Prime Contractor), in collaboration with its partners at the Utah State University (USU), Idaho National Laboratory, Rocky Mountain Power (RMP), and Electric Power Engineers (EPE), have performed research, development, and wide scale demonstration of a scalable and resilient Electrification Mosaic (eMosaic) platform for Smart Charge Management (SCM) for Electric Vehicle Infrastructure. Work was completed under DE EE0009194, titled “eMosaic Electrification Mosaic Platform for Grid Informed Smart Charging Management”, funded by the US Department of Energy. The project members developed algorithms that provide localized and bulk grid services and that reduce and stabilize costs all the way down the supply chain to the PEV owner through SCM. This platform aggregates telemetry from multiple data sources as pieces of the larger picture including personal, private fleet or transportation EVs, fast chargers and other supply equipment, weather service information, and geographically distributed charging sites such as public lots, garage and retail, and private or shared usage depots. ABB and the project team designed, tested, and improved a charging management system at local/edge and cloud levels. The ultimate objective of the project was to convincingly demonstrate that the developed secure eMosaic plat-form can be readily and favorably adopted by diverse utilities and site owners at scale. This was achieved through a demonstration plan with field deployment at several physical sites across 4 states and additional scalable simulation from high fidelity charging models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Recommendations for Secure Transport: Material Conveyance Physical Protection Technology

Nuclear material is at higher risk of theft and sabotage during transport than during any other phase of the nuclear fuel lifecycle. Nuclear materials are transported in the public domain where adversaries have an upper hand by taking advantage of the time and location of the theft or sabotage attempt. As such, even modest threat profiles for transport of nuclear and radioactive material can require substantial detection and delay measures to support timely response. Conveyance tracking augmented with technology that improves on-the-scene situational awareness at a remote monitoring center has been adopted as a de-facto standard approach for transportation security. At present, the extended tracking and situational awareness capabilities needed for a nuclear material shipment, as is provided by the purpose designed, Transportation – Security, Tracking and Reporting (T-STAR) System, do not exist in a single commercial off-the-shelf (COTS) solution. Typically, the COTS systems that excel in one area are deficient in other areas, presenting challenges to designing well-rounded, robust systems. Still, COTS solutions can offer the basic set of tracking and situational awareness capabilities by indicating last update time, current location, and route taken. By incorporating vehicle and driver performance measures via the vehicle’s controller area network (CAN bus) and video alongside other data streams allows telemetry and other shipment information to be assessed in novel ways.This paper describes the operation, capabilities and features of various conveyance protection systems and approaches, assesses emerging technologies and how they could be used through a unified interface, and enumerates additional ways to provide early detection using vehicle, onboard technologies, effective delay technologies and approaches and simple equipment to improve protection during transport.

Shannon, Michael↗
DOE OSTI2022

Microbial sensor system for monitoring the environment and surfaces

A microbial sensor, system and method that can be used to determine the biochemical conditions of waters, saturated sediments, unsaturated soils, rhizosphere and other environments is disclosed. The flexibility of the microbial sensor design allows for the monitoring of surfaces (skin, ventilation conduits, etc.). An electrochemical microbial sensor system is composed of an indicator electrode(s) and a reference electrode. The reference electrode employs a hydrogen permeable membrane. The electrochemical system is interfaced into a signal/communication module allowing the manual or automated collection of data from field deployments and laboratory investigations. The data is transmitted using various communication technologies including Bluetooth™, cellular, satellite and radio telemetry to cloud-based data management systems. The stored data may be downloaded by users using open-source dashboard and visualization software to image the various environments and/or surfaces investigated.

Burge, Scott R.↗
DOE OSTI2024

Tracking animal movements via collaborative acoustic telemetry networks: Multiscale habitat use, phenology, and management insights

Abstract Estuaries support diverse fish and invertebrate communities, including resident species that rely on estuarine habitats year‐round and transient migratory species. The unique movement patterns of these animals connect habitats within and far beyond the estuary and are integrally linked to fisheries management objectives. With a focus on Chesapeake Bay, this study leveraged data from collaborative acoustic telemetry networks in the northwest Atlantic to assess habitat use and phenology of movements for seven species of fish (cownose rays, dusky sharks, smooth dogfish, alewife, striped bass, common carp, and blue catfish) and one invertebrate (horseshoe crabs). A total of 288 acoustically tagged individuals were detected >3.2 million times (6,743 to 2,095,717 detections per species) on receivers across ~20.5 degrees of latitude spanning the North American Atlantic seaboard from Florida, USA, to New Brunswick, Canada. Common metrics of movement and phenology grouped these species as resident (common carp, blue catfish, horseshoe crabs), primarily resident in estuaries (juvenile striped bass), and coastal migrant (cownose rays, dusky sharks, smooth dogfish, alewife); maximum distance traveled varied by three orders of magnitude among these species. Further analysis of phenology for coastal migrants elucidated the timing and duration of these species' use of Chesapeake Bay. Collectively, movements linked habitats within Chesapeake Bay and connected the estuary to coastal ecosystems both to the north (e.g., alewife) and south (e.g., cownose rays), creating networks of fisheries management jurisdictions that varied in complexity and identified opportunities for enhancement to current management or co‐management of some species. Our results elucidate the importance of estuaries to species with diverse movement behaviors, identify scales and pathways of habitat connectivity via animal movements, and highlight the utility of collaborative acoustic telemetry networks for quantifying movements relevant to both ecological research and fisheries management.

Livernois, Mariah C.↗
DOE OSTI2018

Stochastic correlation analysis to rank the impact of intermittent wind generation on unreliability margins of power systems

Power systems are vulnerable to extreme contingencies (like an outage of a major generating substation or transmission line) that can cause significant generation and load loss and can lead to further cascading outages of other transmission facilities and generators in the system. Power systems operators take time-ahead actions (real time to day ahead) actions based on forecasted data as well as telemetry. However, there is a probability of extreme swings in wind generation that can push the power system that is already close to system boundaries into unreliable states. Increasing penetration on wind generation and uncertainties in short term forecast can move the system into operational states that can violate N-1 reliability criteria. While the power system planning accounts for worst case analyses to mitigate such emergencies, it is necessary to understand the spatial and temporal correlation of load buses with intermittent wind generation. The ranking of wind generators based on stochastic correlation to unreliability margins of load buses provides an insight of system vulnerabilities that can be corrected by appropriate emergency controls. A Monte-Carlo simulation of wind uncertainty forecast is performed to identify the probability distributions of unreliability margins. Ranking of wind generators is performed based on stochastic correlation analysis of the wind power generated and the load losses at the buses. This helps in not only identifying weak buses in the power system but also in identifying the vulnerable wind locations to plan for system reinforcements. Power system modeling and hybrid simulation to calculate unreliability margins are performed using DCAT and demonstrated on the 32-bus Nordic test system.

generators, wind forecasting, wind power generatio↗
DOE OSTI2013

Statistical Characterization of School Bus Drive Cycles Collected via Onboard Logging Systems

In an effort to characterize the dynamics typical of school bus operation, National Renewable Energy Laboratory (NREL) researchers set out to gather in-use duty cycle data from school bus fleets operating across the country. Employing a combination of Isaac Instruments GPS/CAN data loggers in conjunction with existing onboard telemetric systems resulted in the capture of operating information for more than 200 individual vehicles in three geographically unique domestic locations. In total, over 1,500 individual operational route shifts from Washington, New York, and Colorado were collected. Upon completing the collection of in-use field data using either NREL-installed data acquisition devices or existing onboard telemetry systems, large-scale duty-cycle statistical analyses were performed to examine underlying vehicle dynamics trends within the data and to explore vehicle operation variations between fleet locations. Based on the results of these analyses, high, low, and average vehicle dynamics requirements were determined, resulting in the selection of representative standard chassis dynamometer test cycles for each condition. In this paper, the methodology and accompanying results of the large-scale duty-cycle statistical analysis are presented, including graphical and tabular representations of a number of relationships between key duty-cycle metrics observed within the larger data set. In addition to presenting the results of this analysis, conclusions are drawn and presented regarding potential applications of advanced vehicle technology as it relates specifically to school buses.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Fast DR: Controlling Small Loads over the Internet

Current state-of-the-art demand response systems are expensive due to extreme reliability constraints in telemetry, control, and metering. The typical cost of enabling a site for regulation services is between $50k and $80k. These costs are orders of magnitude too high for small loads to participate in high-value grid services. Traditional demand response (DR) schedules events in advance and provides basic on/off control. We developed fast DR measurement and communication technologies, which are scalable cost-effective demand response systems with sufficient reliability for real-time control and monitoring of loads over the internet, and we demonstrated an example system for under $100. We installed FastDR systems for lighting, motor, and thermostat control along with power metering at a total of 10 sites, including 6 commercial buildings and 4 residential buildings. This demonstration addressed the following important methodological questions: 1) Can we reliably control loads simultaneously and with low latency across multiple sites within a specified response time; 2) How reliable is using the internet or 4G cellular network as the mode of control and metering; and 3) Can existing Smart Meters provide data for real-time telemetry services. Testing shows fast DR is capable of control to response in 4 seconds and loads complete transition in seconds to less than one minute depending on load type. We demonstrated 4s regulation services and synchronized load control, and we successfully met specifications for ancillary services across the US. Telemetry via the 4G cellular network demonstrated 94.5% success rate, and residential Internet demonstrated a 98% success rate.

Kiliccote, Sila↗
DOE OSTI2014

Flexible and Scalable Data Fusion using Proactive Schemaless Information Services

Exascale data environments are fast approaching, driven by diverse structured and unstructured data such as system and application telemetry streams, open-source information capture, and on-demand simulation output. Storage costs having plummeted, the question is now one of converting vast stores of data to actionable information. Complicating this problem are the low degrees of awareness across domain boundaries about what potentially useful data may exist, and write-once- read-never issues (data generation/collection rates outpacing data analysis and integration rates). Increasingly, technologists and researchers need to correlate previously unrelated data sources and artifacts to produce fused data views for domain-specific purposes. New tools and approaches for creating such views from vast amounts of data are vitally important to maintaining research and operational momentum. We propose to research and develop tools and services to assist in the creation, refinement, discovery and reuse of fused data views over large, diverse collections of heterogeneously structured data. We innovate in the following ways. First, we enable and encourage end-users to introduce customized index methods selected for local benefit rather than for global interaction (flexible multi-indexing). We envision rich combinations of such views on application data: views that span backing stores with different semantics, that introduce analytic methods of indexing, and that define multiple views on individual data items. We specifically decline to build a big fused database of everything providing a centralized index over all data, or to export a rigid schema to all comers as in federated query approaches. Second, we proactively advertise these application-specific views so that they may be programmatically reused and extended (data proactivity). Through this mechanism, both changes in state (new data in existing view collected) and changes in structure (new or derived view exists) are made known. Lastly, we embrace found data heterogeneity by coupling multi-indexing to backing stores with appropriate semantics (as opposed to a single store or schema).

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2014

Flexible and Scalable Data Fusion using Proactive, Schemaless Information Services

Exascale data environments are fast approaching, driven by diverse structured and unstructured data such as system and application telemetry streams, open-source information capture, and on-demand simulation output. Storage costs having plummeted, the question is now one of converting vast stores of data to actionable information. Complicating this problem are the low degrees of awareness across domain boundaries about what potentially useful data may exist, and write-once-read- never issues (data generation/collection rates outpacing data analysis and integration rates). Increasingly, technologists and researchers need to correlate previously unrelated data sources and artifacts to produce fused data views for domain-specific purposes. New tools and approaches for creating such views from vast amounts of data are vitally important to maintaining research and operational momentum. We propose to research and develop tools and services to assist in the creation, refinement, discovery and reuse of fused data views over large, diverse collections of heterogeneously structured data. We innovate in the following ways. First, we enable and encourage end-users to introduce customized index methods selected for local benefit rather than for global interaction (flexible multi-indexing). We envision rich combinations of such views on application data: views that span backing stores with different semantics, that introduce analytic methods of indexing, and that define multiple views on individual data items. We specifically decline to build a big fused database of everything providing a centralized index over all data, or to export a rigid schema to all comers as in federated query approaches. Second, we proactively advertise these application-specific views so that they may be programmatically reused and extended (data proactivity). Through this mechanism, both changes in state (new data in existing view collected) and changes in structure (new or derived view exists) are made known. Lastly, we embrace found data heterogeneity by coupling multi-indexing to backing stores with appropriate semantics (as opposed to a single store or schema).

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

Real-Time Monitoring of Gas-Phase and Dissolved CO 2 Using a Mixed-Matrix Composite Integrated Fiber Optic Sensor for Carbon Storage Application

Novel chemical sensors that improve detection and quantification of CO 2 are critical to ensuring safe and cost-effective monitoring of carbon storage sites. Fiber optic (FO) based chemical sensor systems are promising field-deployable systems for real-time monitoring of CO 2 in geological formations for long-range distributed sensing. Here, a mixed-matrix composite integrated FO sensor system was developed with a purely optical readout that reliably operates as a detector for gas-phase and dissolved CO 2 . A mixed-matrix composite sensor coating consisting of plasmonic nanocrystals and hydrophobic zeolite embedded in a polymer matrix was integrated on the FO sensor. The mixed-matrix composite FO sensor showed excellent reversibility/stability in a high humidity environment and sensitivity to gas-phase CO 2 over a large concentration range. This remarkable sensing performance was enabled by using plasmonic nanocrystals to significantly enhance the sensitivity and a hydrophobic zeolite to effectively mitigate interference from water vapor. The sensor exhibited the ability to sense CO 2 in the presence of other geologically relevant gases, which is of importance for applications in geological formations. A prototype FO sensor configuration which possesses a robust sensing capability for monitoring dissolved CO 2 in natural water was demonstrated. Reproducibility was confirmed over many cycles, both in a laboratory setting and in the field. More importantly, we demonstrated on-line monitoring capabilities with a wireless telemetry system, which transferred the data from the field to a website. The combination of outstanding CO 2 sensing properties and facile coating processability makes this mixed-matrix composite FO sensor a good candidate suitable for practical carbon storage applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Datasets for characterizing extreme events relevant to hydrologic design over the conterminous United States

Despite the close linkage between extreme floods and snowmelt, particularly through rain-on-snow (ROS), hydrologic infrastructure is mostly designed based on standard precipitation Intensity-Duration-Frequency curves (PREC-IDF) that neglect snow processes in runoff generation. For snow-dominated regions, such simplification could result in substantial errors in estimating extreme events and infrastructure design risk. To address this long-standing problem, we applied the Next Generation IDF (NG-IDF) technique to estimate design basis extreme events for different durations and return periods in the conterminous United States (CONUS) to distinctly represent the contribution of rain, snowmelt, and ROS events to the amount of water reaching the land surface. A suite of datasets were developed to characterize the magnitude, trend, seasonality, and dominant mechanism of extreme events for over 200,000 locations. Infrastructure design risk associated with the use of PREC-IDF was estimated. Accuracy of the model simulations used in the analyses was confirmed by long-term snow data at over 200 Snowpack Telemetry stations. The presented spatially continuous datasets are readily usable and instrumental for supporting site-specific infrastructure design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Streaming Analytics for Anomaly Detection in Large-Scale Data

Anomalous behavior poses serious risks to assured performance and reliability of complex, high-consequence systems. For spaceborne assets and their state-of-health (SOH) telemetry, the challenges of high-dimensional data of varying data types are compounded by computational limitations from size, weight, and power (SWaP) constraints as well as data availability. Automated anomaly detection methods tend to perform poorly under these constraints, while current operational approaches can introduce delays in response time due to the manual, retrospective processes for understanding system failures. As a result, presently deployed space systems, and those deployed in the near future, face situations where mission operations might be delayed or only be able to operate under degraded capabilities. Here, we examine a near-term lightweight solution that provides real-time detection capabilities for rare events and assess state-of-the-art anomaly detection techniques against real SOH telemetry from space platforms. This report describes our methodology and research, which could support more automated capabilities for comprehensive space operations as well as for other resource-constrained edge applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Dynamic Line Rating Oncor Electric Delivery Smart Grid Program

Electric transmission lines are the lifeline of the electric utility industry, delivering its product from source to consumer. This critical infrastructure is often constrained such that there is inadequate capacity on existing transmission lines to efficiently deliver the power to meet demand in certain areas or to transport energy from high-generation areas to high-consumption regions. When this happens, the cost of the energy rises; more costly sources of power are used to meet the demand or the system operates less reliably. These economic impacts are known as congestion, and they can amount to substantial dollars for any time frame of reference: hour, day or year. There are several solutions to the transmission constraint problem, including: construction of new generation, construction of new transmission facilities, rebuilding and reconductoring of existing transmission assets, and Dynamic Line Rating (DLR). All of these options except DLR are capital intensive, have long lead times and often experience strong public and regulatory opposition. The Smart Grid Demonstration Program (SGDP) project co-funded by the Department of Energy (DOE) and Oncor Electric Delivery Company developed and deployed the most extensive and advanced DLR installation to demonstrate that DLR technology is capable of resolving many transmission capacity constraint problems with a system that is reliable, safe and very cost competitive. The SGDP DLR deployment is the first application of DLR technology to feed transmission line real-time dynamic ratings directly into the system operation’s State Estimator and load dispatch program, which optimizes the matching of generation with load demand on a security, reliability and economic basis. The integrated Dynamic Line Rating (iDLR)1 collects transmission line parameters at remote locations on the lines, calculates the real-time line rating based on the equivalent conductor temperature, ambient temperature and influence of wind and solar radiation on the stringing section, transmits the data to the Transmission Energy Management System, validates its integrity and passes it on to Oncor and ERCOT (Electric Reliability Council of Texas) respective system operations. The iDLR system is automatic and transparent to ERCOT System Operations, i.e., it operates in parallel with all other system status telemetry collected through Supervisory Control and Data Acquisition (SCADA) employed across the company.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Glass Additive and Subtractive Manufacturing of a Fiber Optic Rotary Encoder for Downhole Pressure Sensing

This article presents a fiber optic rotary encoder-based pressure sensor for downhole applications. The rotary encoder, which is composed of an encoding pad and an all-glass optical fiber sensing head, converts the rotation angles of a pressure transducer to digital codes. The optical fiber only serves as the telemetry channel to directly transmit the data in digital format such that the environmental temperature influence and the long-time drift are minimized. The glass additive and subtractive manufacturing (ASM) techniques are used to embed the multichannel optical fibers into a bulk-fused silica glass substrate. Because the fused silica glass shares a similar material property to the optical fiber (e.g., thermal expansion coefficient), the optical fiber sensing head is well sealed and fixed even at an elevated temperature. The picosecond laser blackening technique is used to fabricate the high reflectivity contrast encoding pad with high accuracy. Here, the proposed pressure sensor was manufactured and experimentally verified to have a signal-to-noise ratio (SNR) of 23 dB and a linear pressure response with a root-mean-square error (RMSE) of 0.37. During the 400-h 250 °C long-term stability test, there was no digital code variation. In addition, a mathematical model to study the relationships between the sensor’s performances and design parameters was established. According to the model, a 12-bit encoder (0.02% pressure sensitivity) can be achieved with a radius of 20 mm.

02 PETROLEUM↗
DOE OSTI2014

Artificial Retina Project: Electromagnetic and Thermal Effects

This award supported the investigation on electromagnetic and thermal effects associated with the artificial retina, designed in collaboration with national laboratories, universities, and private companies. Our work over the two years of support under this award has focused mainly on 1) Design of new telemetry coils for optimal power and data transfer between the implant and the external device while achieving a significant size reduction with respect to currently used coils; 2) feasibility study of the virtual electrode configuration 3) study the effect of pulse shape and duration on the stimulation efficacy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Costs to Automate Demand Response - Taxonomy and Results from Field Studies and Programs

During the past decade, the technology to automate demand response (DR) in buildings and industrial facilities has advanced significantly. Automation allows rapid, repeatable, reliable operation. This study focuses on costs for DR automation in commercial buildings with some discussion on residential buildings and industrial facilities. DR automation technology relies on numerous components, including communication systems, hardware and software gateways, standards-based messaging protocols, controls and integration platforms, and measurement and telemetry systems. This report compares cost data from several DR automation programs and pilot projects, evaluates trends in the cost per unit of DR and kilowatts (kW) available from automated systems, and applies a standard naming convention and classification or taxonomy for system elements. Median costs for the 56 installed automated DR systems studied here are about $200/kW. The deviation around this median is large with costs in some cases being an order of magnitude great or less than the median. This wide range is a result of variations in system age, size of load reduction, sophistication, and type of equipment included in cost analysis. The costs to automate fast DR systems for ancillary services are not fully analyzed in this report because additional research is needed to determine the total cost to install, operate, and maintain these systems. However, recent research suggests that they could be developed at costs similar to those of existing hot-summer DR automation systems. This report considers installation and configuration costs and does include the costs of owning and operating DR automation systems. Future analysis of the latter costs should include the costs to the building or facility manager costs as well as utility or third party program manager cost.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Rapidly Deployable Acoustic Monitoring and Localization System Based on a Low-Cost Wave Buoy Platform

The primary objective of this project is to develop a cost-effective, fit-for-purpose environmental monitoring system, “NoiseSpotter®,” that characterizes, classifies, and provides accurate location information for anthropogenic and natural sounds in near real-time. NoiseSpotter was developed to support the evaluation of potential acoustic effects of marine energy (ME) projects. By utilizing a compact array of three acoustic particle motion sensors, NoiseSpotter triangulates individual bearings to provide sound source localization to within 5% accuracy, allowing the ability to discern ME device sounds relative to other confounding sounds in the environment, while providing location estimates to nearby marine mammals for environmental mitigation purposes. The ME industry needs proven solutions to meet environmental impact assessment needs. The NoiseSpotter® includes off-the-shelf, modular components that are easy to assemble and disassemble. Its acoustic particle motion sensors are commercially available and the data logger and real-time telemetry system is designed to be plug-and-play. The entire system is relatively compact and can be deployed from small vessels. NoiseSpotter’s near real-time capability enables operational monitoring of ME sounds, particularly during early stages of technology adoption to facilitate mitigation of potential noise effects. Widespread adoption of the technology for acoustic monitoring of ME devices requires that it be cost effective; hence the anticipated commercial cost of system hardware is $35,000. This project contributes to reducing barriers to ME testing through support of scientific research focused on reducing or mitigating environmental risks and lowering costs and complexity of environmental monitoring. This project has developed an acoustic monitoring system, NoiseSpotter® (U.S. Patent No. 11,156,734 and U.S. Registered Trademark No. 6,442,313), to detect and characterize baseline noise and sounds from ME operations and support geolocation of detected sounds. The intended outcome of the project is to mitigate concerns about the potential for ME device noise to alter marine mammal or fish behavior. NoiseSpotter® enables cost-effective, near real-time acoustic monitoring of an operational ME device relative to ambient environmental noise and provides a technical basis for ME developers seeking to navigate the permitting process in an efficient manner.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Electrically Engaged UnduLation (EEL) Marine Energy System

Current technologies at the forefront of instrumentation for ocean observation through acoustic mapping are powered by batteries that cannot achieve the lasting durations required for high-resolution measurements. Pyro-E has designed an Electrically Engaged unduLation (EEL) system capable of in situ energy harvest and deployment in sub-sea configurations. By extracting kinetic energy from the ocean, EEL proposes to provide power output ranging from 1 mW to 1,000 mW. Such a magnitude of power can sustain active instrumentation with onboard processing of data and over-the-horizon telemetry. Pyro-E and Oak Ridge National Laboratory have utilized software tools and powerful computing resources to develop a techno-economic design of the EEL capable of harvesting 5 W. The material response of the EEL under simulated hydromechanical loads is described through time-accurate predictions. All physical tests were conducted by Pyro-E to guide simulations at Oak Ridge National Laboratory.

16 TIDAL AND WAVE POWER↗