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DOE OSTI2022

Molecular qubits based on photogenerated spin-correlated radical pairs for quantum sensing

Photogenerated spin-correlated radical pairs (SCRPs) in electron donor–bridge–acceptor (D–B–A) molecules can act as molecular qubits and inherently spin qubit pairs. SCRPs can take singlet and triplet spin states, comprising the quantum superposition state. Their synthetic accessibility and well-defined structures, together with their ability to be prepared in an initially pure, entangled spin state and optical addressability, make them one of the promising avenues for advancing quantum information science. Coherence between two spin states and spin selective electron transfer reactions form the foundation of using SCRPs as qubits for sensing. We can exploit the unique sensitivity of the spin dynamics of SCRPs to external magnetic fields for sensing applications including resolution-enhanced imaging, magnetometers, and magnetic switch. Molecular quantum sensors, if realized, can provide new technological developments beyond what is possible with classical counterparts. While the community of spin chemistry has actively investigated magnetic field effects on chemical reactions via SCRPs for several decades, we have not yet fully exploited the synthetic tunability of molecular systems to our advantage. This review offers an introduction to the photogenerated SCRPs-based molecular qubits for quantum sensing, aiming to lay the foundation for researchers new to the field and provide a basic reference for researchers active in the field. We focus on the basic principles necessary to construct molecular qubits based on SCRPs and the examples in quantum sensing explored to date from the perspective of the experimentalist.

Mani, Tomoyasu (ORCID:0000000241255195)↗

DOE OSTI2018

Fluid Stratification Separate Effects Analysis, Testing and Benchmarking

High Temperature Gas Reactors (HTGRs) are positioned to disrupt local and global markets via their unique ability to produce carbon-free process heat, high efficiency power generation, and passively safe operational features. However, significant impediments still exist to delay deployment of this particular technology, including a lack of experimental data, verified code application, and lack of consensus with regards to severe accident progression. In particular, air ingress accidents represent a particular challenge to designers and engineers, as they represent low probability, but highly complex, accident scenarios. Including phenomena such as molecular diffusion, free convection, and complex heat and mass transfer paths, experimental and traceable data is essential to maturing the state of the industry. Therefore, this work presents an experimental investigation of the transition to natural convection in HTGR applications using the Stratified Flow Separate Effects Test Facility, housed at Oregon State University. In particular, this work will present data that challenges the assumption that molecular diffusion is a significant factor in this severe accident in the reference facility of the General Atomic 600 MW th Gas Turbine-Modular Helium Reactor (GT-MHR). Rather, experimentally produced data shows a statistically suggestive retardant effect of cross duct orientation, indicating that ingress mechanics may be fundamentally altered via facility geometry. Experimentally, this is achieved using a simplified cross duct that may be positioned in one of two ways so as to provide either horizontal or vertical access to the lower plenum area. Onset of natural convection (ONC) is measured using an oxygen sensor probe, immersed in the helium working fluid, so as to provide direct indication of air presence in the upper plenum. This document will present the doctoral dissertation produced by this work, along with its analysis, experimental data, observations, and conclusions, in addition to select documents that will highlight critical changes during the development process. Those documents will include the quality assurance plan, all subsequent change requests, and the engineering transfer from Harris Thermal in order to establish the most complete quality record possible.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

Selection of Components for the Remote, Canister-Monitoring System

This report documents the selection of components as part of the efforts initiated to develop a remote, canister-monitoring system (RCMS) for determining and monitoring environmental conditions within dry fuel storage canisters containing aluminum clad spent nuclear fuel (ASNF) at the Idaho National Laboratory (INL). These efforts are in support of Department of Energy Office of Environmental Management (DOE-EM) investigations into technical issues associated with extended dry storage (50+ years) of ASNF. The capability to establish and monitor the performance of ASNF in situ provides the opportunity to (1) evaluate the appropriate technologies for monitoring, (2) collect canister environment conditions as soon as possible, (3) verify and validate current laboratory-based study results and analytic modeling approaches, and (4) potentially identify additional dry storage options for ASNF at the INL site. The improved understanding of ASNF behavior gained by performing this work would also contribute to the safety basis for extended dry storage in current and future configurations as well as to provide information for future transportation, conditioning, and disposal of ASNF. The parameters to be monitored by the RCMS include temperature, relative humidity, hydrogen gas concentration and radiation environment (dose). Components are selected based on the expected environmental conditions within the canister and fuel storage area, and the desired performance of the RCMS. Several of these components have been purchased and received. Future activities include component testing and calibration, software development for operation of the integrated sensor module and fabrication of a representative test volume. The results of these tests and changes to desired performance characteristics will inform subsequent activities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

OSCA1 is an osmotic specific sensor: a method to distinguish Ca 2+ -mediated osmotic and ionic perception

Genetic mutants defective in stimulus-induced Ca 2+ increases have been gradually isolated, allowing the identification of cell-surface sensors/receptors, such as the osmosensor OSCA1. However, determining the Ca 2+ -signaling specificity to various stimuli in these mutants remains a challenge. For instance, less is known about the exact selectivity between osmotic and ionic stresses in the osca1 mutant. Here, we have developed a method to distinguish the osmotic and ionic effects by analyzing Ca 2+ increases, and demonstrated that osca1 is impaired primarily in Ca 2+ increases induced by the osmotic but not ionic stress. We recorded Ca 2+ increases induced by sorbitol (osmotic effect, OE) and NaCl/CaCl 2 (OE + ionic effect, IE) in Arabidopsis wild-type and osca1 seedlings. Here we assumed the NaCl/CaCl 2 total effect (TE) = OE + IE, then developed procedures for Ca 2+ imaging, image analysis and mathematic fitting/modeling, and found osca1 defects mainly in OE. The osmotic specificity of osca1 suggests that osmotic and ionic perceptions are independent. The precise estimation of these two stress effects is applicable not only to new Ca 2+ -signaling mutants with distinct stimulus specificity but also the complex Ca 2+ signaling crosstalk among multiple concurrent stresses that occur naturally, and will enable us to specifically fine tune multiple signal pathways to improve crop yields.

Arabidopsis↗

DOE OSTI2016

Experimental Design for Evaluating Selected Nondestructive Measurement Technologies - Advanced Reactor Technology Milestone: M3AT-16PN2301043

The harsh environments in advanced reactors (AdvRx) increase the possibility of degradation of safety-critical passive components, and therefore pose a particular challenge for deployment and extended operation of these concepts. Nondestructive evaluation technologies are an essential element for obtaining information on passive component condition in AdvRx, with the development of sensor technologies for nondestructively inspecting AdvRx passive components identified as a key need. Given the challenges posed by AdvRx environments and the potential needs for reducing the burden posed by periodic in-service inspection of hard-to-access and hard-to-replace components, a viable solution may be provided by online condition monitoring of components. This report identifies the key challenges that will need to be overcome for sensor development in this context, and documents an experimental plan for sensor development, test, and evaluation. The focus of initial research and development is on sodium fast reactors, with the eventual goal of the research being developing the necessary sensor technology, quantifying sensor survivability and long-term measurement reliability for nondestructively inspecting critical components. Materials for sensor development that are likely to withstand the harsh environments are described, along with a status on the fabrication of reference specimens, and the planned approach for design and evaluation of the sensor and measurement technology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys

Data Challenge 1 (DC1) is the first synthetic data set produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST data set. DC1 is comprised of r -band observations of 40 deg 2 to 10 yr LSST depth. In this paper, we present each stage of the simulation and analysis process: (a) generation, by synthesizing sources from cosmological N -body simulations in individual sensor-visit images with different observing conditions; (b) reduction using a development version of the LSST Science Pipelines; and (c) matching to the input cosmological catalogue for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star–galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: (i) survey properties have an impact of 50 per cent of the statistical uncertainty for the scales and models used in DC1; (ii) a selection to eliminate artefacts in the catalogues is necessary to avoid biases in the measured clustering; and (iii) the presence of bright objects has a significant impact (2σ–6σ) in the estimated power spectra at small scales (ℓ > 1200), highlighting the impact of blending in studies at small angular scales in LSST.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

GeoPlace v. 1.0

GeoPlace software solves several problems related to efficient sensor placement for remote sensing. It consists of several components. “GeoFoot” finds efficient locations for centering a set of camera images, in order to ensure that the collection of images contains an entire region. It is built on a modified version of “Simple MPS”. GeoSubFoot selects non-overlapping rectangular subregions of a single camera image, in order to devote more resources for higher-fidelity sub-images of those regions. The goal is for the rectangular subregions to contain many user-specified pixels of interest. Simple MPS is a generic program that produces point-sample distributions with blue noise characteristics over arbitrary-dimensional squares. GeoFoot includes an extension of it to sampling from polygons in 2d, including both the inside of the polygon and slightly outside it.

Ebeida, MohamedS.↗

DOE OSTI2016

GeoPlace v. 1.0

Ebeida, Mohamed S.↗

DOE OSTI2018

On-board Radiation Sensor and Low-Altitude Contour Mapping of Radiation Fields using UAS Swarm - 18239

This paper addresses the design of light weight radiation sensors for the small-scale unmanned aerial system (UAS), and its implementation for low-altitude radiation source localization and contour mapping. The compact, high-resolution gamma-ray CZT sensors were integrated to UAS platforms as plug-and-play components using Robot Operation System (ROS). In this work, the UAS swarm consists of three platforms positioned in circular formation. The onboard data analysis provides time and position stamped intensities of gamma-ray peaks for each UAS-based sensor that are used as the input data for the swarm flight control algorithm. Each UAS measures radiation simultaneously for estimating gradient of radiation to compute a bulk heading angle of the swarm for contour mapping, which can provide relatively precise boundary of the safe area for potential human exploration. The UAS radiation sensors allow measurements from just few meters up to hundreds of meters thus filling the gap between land- and helicopter- based platforms. The swarm of UAS has advantages over a single agent based approach in detecting radiative sources and effectively mapping the area. The proposed method can locate sources of radiation as well as mapping the contaminated area for enhancing situation awareness capabilities for first responders. Computer simulation is presented for UAS swarm based source localization and contour mapping in the simulated radiation fields created by the MCNP code. Selected key gradient estimation and contour mapping algorithms are validated experimentally with small scale multicopter UAS in the indoor flight test bed. (authors)

42 ENGINEERING↗

DOE OSTI2021

An overview of data tools for representing and managing building information and performance data

Building information modeling (BIM) has been widely adopted for representing and exchanging building data across disciplines during building design and construction. However, BIM's use in the building operation phase is limited. With the increasing deployment of low-cost sensors and meters, as well as affordable digital storage and computing technologies, growing volumes of data have been collected from buildings, their energy services systems, and occupants. Such data are crucial to help decision makers understand what, how, and when energy is consumed in buildings—a critical step to improving building performance for energy efficiency, demand flexibility, and resilience. However, practical analyses and use of the collected data are very limited due to various reasons, including poor data quality, ad-hoc representation of data, and lack of data science skills. To unlock value from building data, there is a strong need for a toolchain to curate and represent building information and performance data in common standardized terminologies and schemas, to enable interoperability between tools and applications. This study selected and reviewed 24 data tools based on common use cases of data across the building life cycle, from design to construction, commissioning, operation, and retrofits. The selected data tools are grouped into three categories: (1) data dictionary or terminology, (2) data ontology and schemas, and (3) data platforms. The data are grouped into ten typologies covering most types of data collected in buildings. This study resulted in five main findings: (1) most data representation tools can represent their intended data typologies well, such as Green Button for smart meter data and Brick schema for metadata of sensors in buildings and HVAC systems, but none of the tools cover all ten types of data; (2) there is a need for data schemas to represent the basis of design data and metadata of occupant data; (3) standard terminologies such as those defined in BEDES are only adopted in a few data tools; (4) integrating data across various stages in the building life cycle remains a challenge; and (5) most data tools were developed and maintained by different parties for different purposes, their flexibility and interoperability can be improved to support broader use cases. Finally, recommendations for future research on building data tools are provided for the data and buildings community based on the FAIR principles to make data Findable, Accessible, Interoperable, and Reusable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Large Area Transfer of Bismuth‐Based Layered Oxide Thin Films Using a Flexible Polymer Transfer Method

Magnetic and ferroelectric oxide thin films have long been studied for their applications in electronics, optics, and sensors. The properties of these oxide thin films are highly dependent on the film growth quality and conditions. To maximize the film quality, epitaxial oxide thin films are frequently grown on single-crystal oxide substrates such as strontium titanate (SrTiO 3 ) and lanthanum aluminate (LaAlO 3 ) to satisfy lattice matching and minimize defect formation. However, these single-crystal oxide substrates cannot readily be used in practical applications due to their high cost, limited availability, and small wafer sizes. One leading solution to this challenge is film transfer. In this demonstration, a material from a new class of multiferroic oxides is selected, namely bismuth-based layered oxides, for the transfer. A water-soluble sacrificial layer of Sr 3 Al 2 O 6 is inserted between the oxide substrate and the film, enabling the release of the film from the original substrate onto a polymer support layer. The films are transferred onto new substrates of silicon and lithium niobate (LiNbO 3 ) and the polymer layer is removed. These substrates allow for the future design of electronic and optical devices as well as sensors using this new group of multiferroic layered oxide films.

36 MATERIALS SCIENCE↗

DOE OSTI2012

AIRE-induced apoptosis is associated with nuclear translocation of stress sensor protein GAPDH

Highlights: Black-Right-Pointing-Pointer AIRE induces apoptosis in epithelial cells. Black-Right-Pointing-Pointer CARD domain of AIRE is sufficient for apoptosis induction. Black-Right-Pointing-Pointer AIRE induced apoptosis involves GAPDH translocation to the nuclei. Black-Right-Pointing-Pointer Deprenyl inhibits AIRE induced apoptosis. -- Abstract: AIRE (Autoimmune Regulator) has a central role in the transcriptional regulation of self-antigens in medullary thymic epithelial cells, which is necessary for negative selection of autoreactive T cells. Recent data have shown that AIRE can also induce apoptosis, which may be linked to cross-presentation of these self-antigens. Here we studied AIRE-induced apoptosis using AIRE over-expression in a thymic epithelial cell line as well as doxycycline-inducible HEK293 cells. We show that the HSR/CARD domain in AIRE together with a nuclear localization signal is sufficient to induce apoptosis. In the nuclei of AIRE-positive cells, we also found an increased accumulation of a glycolytic enzyme, glyceraldehyde-3-phosphate (GAPDH) reflecting cellular stress and apoptosis. Additionally, AIRE-induced apoptosis was inhibited with an anti-apoptotic agent deprenyl that blocks GAPDH nitrosylation and nuclear translocation. We propose that the AIRE-induced apoptosis pathway is associated with GAPDH nuclear translocation and induction of NO-induced cellular stress in AIRE-expressing cells.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Overview of Quantum Sensing Materials and Techniques for Energy Sector Applications

The energy sector has become increasingly dependent upon highly sensitive sensing devices for a wide range of applications. Variables such as temperature, pH, electromagnetic fields, ions, and pressure must be measured with high precision, often in harsh conditions (e.g. highly corrosive environments due to high temperature, pressure and humidity). These sensors are deployed in infrastructure such as transformers, pipelines, mines, nuclear power plants, and other areas to ensure safe operating conditions and uninterrupted, optimized service. Moreover, new opportunities for sensors have emerged due to the expansion of smart grids/meters, driverless vehicles, and the discovery of new oil, gas, and critical mineral deposits. The continued maturation of quantum sensing technologies offers exciting opportunities for quantum-enhanced measurements within the energy sector that may provide significant improvements in sensitivity beyond the classical limit. Here, an overview of established and emerging quantum materials for sensing applications will be provided, from trapped ions to color centers in diamond and silicon carbide. Associated quantum sensing methods for these materials will be discussed, with an emphasis on platforms that are nearing commercial viability. Specific application opportunities within the energy sector for quantum sensors will then be analyzed, including oil/gas discovery, greenhouse gas emission monitoring, pH and ion sensing, current measurement in electric vehicle batteries, and quantum-enhanced spectroscopy. Remaining barriers, such as quantum sensor platform miniaturization and ruggedization, will also be analyzed. A specific project at the National Energy Technology Laboratory involving the functionalization of qubits using metal-organic frameworks for enhanced quantum sensing will also be highlighted. Here, nitrogen vacancy centers (NV) in nanodiamonds, a commercially available qubit with long coherence times and utilizable quantum properties at room temperature, are encapsulated in a controlled way using the metal-organic framework ZIF-8. The ZIF-8 provides a well-defined, porous scaffold that can be controlled to promote the selective uptake of specific target analytes, such as gas molecules or ions. The quantum sensing performance of this composite material is either preserved or enhanced following ZIF-8 encapsulation; the optically detected magnetic resonance response of the NV nanodiamonds with and without the ZIF-8 coating are identical, while the ZIF-8 coating increases the longitudinal spin relaxation lifetime (T1) of the NV centers, an important parameter for spin relaxometry-based quantum sensing experiments. Taken together, these results demonstrate the importance of qubit functionalization as a crucial step for rationally designing high performance quantum sensors.

Crawford, Scott↗

DOE OSTI2017

Design and performance of SiPM-based readout of PbF 2 crystals for high-rate, precision timing applications

Here, we have developed a custom amplifier board coupled to a large-format 16-channel Hamamatsu silicon photomultiplier device for use as the light sensor for the electromagnetic calorimeters in the Muon g-2 experiment at Fermilab. The calorimeter absorber is an array of lead-fluoride crystals, which produces short-duration Cherenkov light. The detector sits in the high magnetic field of the muon storage ring. The SiPMs selected, and their accompanying custom electronics, must preserve the short pulse shape, have high quantum efficiency, be non-magnetic, exhibit gain stability under varying rate conditions, and cover a fairly large fraction of the crystal exit surface area. We describe an optimized design that employs the new-generation of thru-silicon via devices. As a result, the performance is documented in a series of bench and beam tests.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Detection of Cyber Attacks in Grid-tied PV Systems Using Dynamic Watermarking

This paper presents of an active detection scheme for detecting cyber attacks on sensors controlling a grid-tied PV systems. Several cyber vulnerabilities in Grid tied PV Systems are discussed. The defense mechanism introduces a private (secret) watermarking signal into the control inputs of the grid-tied inverter system. This will enable the detection of any malicious manipulation of sensor measurements. Based on the measured data, two statistical tests are conducted to identify anomalies in the system using the presence of the watermarking signal. It shown that when a sensor data is compromised and/or replaced by a pre-recorded healthy signal, both test 1 and 2 exhibit high values indicating a possible malicious activity. The robustness of the proposed algorithm is tested and validated with several attack scenarios on a grid tied PV system. Select results from an experimental setup are discussed.

Ibrahim, Hasan↗

DOE OSTI2022

A Review: PFAS Adsorption, Sensing, and Remediation with Engineered Nanoporous Materials

Per- and polyfluoroalkyl substances (PFAS) are among the most abundant environmental contaminant species. They are widespread due to uncontrolled industrial and commercial use and have been linked to health risks such as cancer. With rising global concerns about the public health effects of PFAS, there is an incentive to develop strategies for reliable monitoring and effective PFAS removal, particularly in drinking water. Traditional PFAS sensing techniques are inefficient due to long measurement times, high labor input, high costs, and limitations to ex situ analysis. Current commercially available sorbents for PFAS removal generally lack the ability to capture PFAS components rapidly and quantitatively. Furthermore, existing sorbents are notably inefficient in removing the more toxic, smaller PFAS chemical chains. Large-scale applications of these methods tend to be costly and resource-intensive. Pacific Northwest National Laboratory has developed unique strategies for PFAS sensing and removal with capture probe technology that has an affinity for fluorocarbons, including PFAS. For both sensing and removal, the customizable capture probes can target specific PFAS compounds since they used a metal-organic framework (MOF)-based technology that can be fine-tuned and molecularly tailored. This tailoring of the materials enables high PFAS sensitivity, selectivity, and faster uptake. PNNL’s capture probe materials have been developed into a sensing technique based on the interactions of the capture probes with PFAS at the molecular level and further transduced that to a quantifiable electrochemical response. The materials have been integrated into a sensor platform developed by New Jersey Institute of Technology (NJIT). Tunable capture probes with a range of detection sensitivities allow for faster and more sensitive PFAS detection limits as low as what appears to be 0.5 ng/L (compared to the U.S. Environmental Protection Agency health advisory level of 70 ng/L). Customization of the capture probe results in improved sorption capacities (fast kinetics and high capacities) compared to commercial granular activated carbons. This research applied various experimental and modeling tools to improve understanding the molecular level interactions between the sorbents towards PFAS adsorption properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Continuous Emulation and Multiscale Visualization of Traffic Flow Using Stationary Roadside Sensor Data

With the advent of the next-generation traffic monitoring systems, there has been a significant increase in the spatial-temporal resolution of vehicle mobility data in many cities. Effective analysis and visualization of such data can provide transportation planners with data-driven insights, which can facilitate the understanding of multiscale traffic dynamics. In this paper, we present a web-based traffic emulator for emulating and visualizing near-real-time and historical traffic flows on highways using data from road-side sensors. To construct a continuous traffic flow, the emulator adopts an analytical pipeline that can (a) integrate traffic data collected from discrete road-side radar detection sensors, (b) interpolate traffic conditions (vehicle speed and volume) on unmeasured road segments based on traffic flow theory, and (c) generate lane-specific vehicle trajectories and movements using a mathematically optimized representation of the road network. Our app also provides an integrated visual workflow that allows users to explore the interconnected traffic dynamics using an appropriate traffic flow visualization selected based on the level of detail. We devise two innovative geo-visualization techniques that utilize an animated strips-network representation and a lane usage matrix to visualize lane performances. To ensure a smooth emulation of large-scale traffic flow in an easy-to-access web environment, we implement the emulator using client-side GPU-accelerated techniques. Lastly, we close with a case study that visualizes traffic dynamics of two scenarios - an afternoon peak hour and a traffic accident - in Chattanooga, Tennessee. Our app visualizes the responses of traffic dynamics during different traffic conditions, and to the presence of the traffic accident at different spatial scales.

42 ENGINEERING↗

DOE OSTI2011

Observation Targeting for the Tehachapi Pass and Mid-Columbia Basin: WindSENSE Phase III Project Summary Report

The overall goal of this multi-phased research project known as WindSENSE is to develop an observation system deployment strategy that would improve wind power generation forecasts. The objective of the deployment strategy is to produce the maximum benefit for 1- to 6-hour ahead forecasts of wind speed at hub-height (~80 m). In Phase III of the project, the focus was on the Mid-Columbia Basin region which encompasses the Bonneville Power Administration (BPA) wind generation area shown in Figure 1 that includes Klondike, Stateline, and Hopkins Ridge wind plants. The typical hub height of a wind turbine is approximately 80-m above ground level (AGL). So it would seem that building meteorological towers in the region upwind of a wind generation facility would provide data necessary to improve the short-term forecasts for the 80-m AGL wind speed. However, this additional meteorological information typically does not significantly improve the accuracy of the 0- to 6-hour ahead wind power forecasts because processes controlling wind variability change from day-to-day and, at times, from hour-to-hour. It is also important to note that some processes causing significant changes in wind power production function principally in the vertical direction. These processes will not be detected by meteorological towers at off-site locations. For these reasons, it is quite challenging to determine the best type of sensors and deployment locations. To address the measurement deployment problem, Ensemble Sensitivity Analysis (ESA) was applied in the Phase I portion of the WindSENSE project. The ESA approach was initially designed to produce spatial fields that depict the sensitivity of a forecast metric to a set of prior state variables selected by the user. The best combination of variables and locations to improve the forecast was determined using the Multiple Observation Optimization Algorithm (MOOA) developed in Phase I. In Zack et al. (2010a), the ESA-MOOA approach was applied and evaluated for the wind plants in the Tehachapi Pass region for a period during the warm season. That research demonstrated that forecast sensitivity derived from the dataset was characterized by well-defined, localized patterns for a number of state variables such as the 80-m wind and the 25-m to 1-km temperature difference prior to the forecast time. The sensitivity patterns produced as part of the Tehachapi Pass study were coherent and consistent with the basic physical processes that drive wind patterns in the Tehachapi area. In Phase II of the WindSENSE project, the ESA-MOOA approach was extended and applied to the wind plants located in the Mid-Columbia Basin wind generation area of Washington-Oregon during the summer and to the Tehachapi Pass region during the winter. The objective of this study was to identify measurement locations and variables that have the greatest positive impact on the accuracy of wind forecasts in the 0- to 6-hour look-ahead periods for the two regions and to establish a higher level of confidence in ESA-MOOA for mesoscale applications. The detailed methodology and results are provided in separate technical reports listed in the publications section below. Ideally, the data assimilation scheme used in the Phase III experiments would have been based upon an ensemble Kalman filter (EnKF) that was similar to the ESA method used to diagnose the Mid-Columbia Basin sensitivity patterns in the previous studies. However, running an EnKF system at high resolution is impractical because of the very high computational cost. Thus, it was decided to use a three-dimensional variational (3DVAR) analysis scheme that is less computationally intensive. The objective of this task is to develop an observation system deployment strategy for the mid Columbia Basin (i.e. the BPA wind generation region) that is designed to produce the maximum benefit for 1- to 6-hour ahead forecasts of hub-height (~80 m) wind speed with a focus on periods of large changes in wind speed. There are two tasks in the current project effort designed to validate the ESA observational system deployment approach in order to move closer to the overall goal: (1) Perform an Observing System Experiment (OSE) using a data denial approach. (2) Conduct a set of Observing System Simulation Experiments (OSSE) for the Mid-Columbia basin region.

17 WIND ENERGY↗