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Preliminary Workforce Development and Environmental and Co-use Management Plans for a Floating Offshore Wind Platform - CRADA 609 (Final Report)

Pacific Northwest National Laboratory (PNNL) provided technical assistance to Glosten, Inc. and its affiliate, PelaStar, LLC to advance the development of their floating offshore wind (FOSW) platform. PNNL provided guidance and assessment in two areas that are important to address in the development of FOSW platforms: (1) workforce development and (2) environmental impacts and ocean co-use considerations. This work was funded by the U.S. Department of Energy’s (DOE) Wind Energy Technologies Office (WETO) through Phase 2 of the FLoating Offshore Wind ReadINess (FLOWIN) Prize. It should be noted that the Plans presented in this report are specific to the PelaStar tension-leg platform (TLP) and may not be applicable to all FOSW platforms. Workforce development and environmental/co-use impacts are highly dependent on the geographical region in which activities take place. At the request of PelaStar, PNNL focused on two regions where development may take place: the Gulf of Maine and Northern California. PNNL generated a preliminary Workforce Development Plan for PelaStar, which includes estimated job numbers and skillsets required to establish a workforce to manufacture, install, and operate their platform as part of FOSW projects. The Plan offers methods to increase diversity, equity, and inclusion practices when developing a new workforce and includes colleges and training centers for potential recruitment. Both positive and negative impacts to communities are evaluated, with potential mitigation strategies for reducing negative impacts. The structure of Community Benefit Agreements and Project Labor Agreements are discussed, noting the limitations of the role of a platform manufacturer versus the offshore wind developer. PNNL also drafted a preliminary Environmental and Co-Use Management Plan that serves as a guide to preparing an environmental assessment related to the installation and operation of PelaStar’s unique TLP design, including its potential ecological, socioeconomic, and emissions impacts. The Plan summarizes information on relevant regulatory requirements, potential impact producing factors, monitoring and mitigation measures, and physical and biological resources in the Gulf of Maine and Northern California. One of the primary perceived benefits of the PelaStar TLP is its reduced footprint due to its tensioned tendons versus catenary or taut moorings, but more research must be done as there are no studies on PelaStar’s TLP system to-date. The section also highlights ocean co-use considerations for PelaStar’s TLP system, specifically for fisheries, including existing perspectives, methods, examples, and limitations. The PNNL team established through this preliminary work and review of available literature and resources that there is not yet much research or planning around FOSW. With FOSW being a new industry, many of the findings and planning are adapted from fixed bottom offshore wind, which itself is only just taking off in the United States. More research is needed to establish best practices for workforce development and to assess environmental and ocean co-use impacts and mitigation approaches.

17 WIND ENERGY↗

Aerodynamic Characterization and Improved Testing Methods for the Space Launch System Liftoff and Transition Environment

Low-speed wind tunnel testing for the liftoff and transition environment of the Space Launch System (SLS) was recently completed in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel using 1.75%-scale models of three SLS vehicle configurations. During the liftoff testing, the primary objective was to evaluate the aerodynamic forces and moments on the SLS launch vehicles, as the vehicle, launch tower, and mobile launch platform were subjected to ground winds from all directions at varying heights for the vehicle off the launch pad. Additionally, aerodynamic forces and moments were acquired for all three SLS vehicles during the transition phase from liftoff to ascent that covered a wide range of angles of attack and angles of side slip. Details of the experimental setup including improved testing methods and a stiffer sting-balance system based on lessons learned from previous test entries are presented. Also, a new force measurement technique was applied during the test where two subminiature six-component load cells were installed in each Solid Rocket Booster (SRB) to acquire forces and moments for each SRB separately from the full vehicle forces and moments measured by the main strain gauge balance. Finally, sample results from the experiment are presented including improved overall data coverage, evaluation of the new SRB data, and smoke flow visualization photos.

Chan, David T.↗

Rancor-HUNTER: A Virtual Plant and Operator Environment for Predicting Human Performance

Advances in simulation capabilities to model physical systems have outpaced the development of simulations for humans using those physical systems. There is an argument that the infinite span of potential human behaviors inherently render human modeling more challenging than physical systems. Despite this challenge, the need for modeling humans interacting with these complex systems is paramount. As technologies have improved, many of the failure modes originating from the physical systems have been solved. This means the overall proportion of human errors has increased, such that it is not uncommon to be the primary driver of system failure in modern complex systems. Moreover, technologies such as automated systems may introduce emerging contexts that can cause new, unanticipated modes of human error. Therefore, it is now more important than ever to develop models of human behavior to realize overall system error reductions and achieve established safety margins. To support new and novel concepts of operations for the anticipated wave of advanced nuclear reactor deployments, human factors and human reliability analysis researchers need to develop advanced simulation-based approaches. This talk presents a simulation environment suitable to both collect data and then perform Monte Carlo simulations to evaluate human performance and develop better models of human behavior. Specifically, the Rancor Microworld Simulator models a complex energy production system in a simplified manner. Rancor includes computer-based procedures, which serve as a framework to automatically classify human behaviors without manual, subjective experimenter coding during scenarios. This method supports a detailed level of analysis at the task level. It is feasible for collecting large sample sizes required to develop quantitative modelling elements that have historically challenged traditional full-scope simulator study approaches. Additionally, the other portion of this experimental platform, the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), is presented to show how the collected data can be used to evaluate novel scenarios based on the contextual factors, or performance shaping factors, derived from Rancor simulations. Rancor-HUNTER is being used to predict operator performance with new procedures, such as results from control room modernization or new-build situations. Rancor-HUNTER is also proving a useful surrogate platform to model human performance for other complex systems.

99 GENERAL AND MISCELLANEOUS↗

Bhutan Water Resources Tech Paper: Comparing Precipitation, Temperature, and Phenology Data Trends in Bhutan to Assist the Himalayan Environmental Rhythm Observation and Evaluation System (HEROES) Project

Himalayan countries, including Bhutan, have become vulnerable to warming trends which result in increasing temperature and variable rainfall and snowfall. By combining phenological and meteorological data, Earth observation platforms and sensors were used to assess trends in precipitation, temperature, and vegetation phenology in Bhutan from 1996 through 2017. This project studied precipitation using Climate Hazards Center Infrared Precipitation with Station data, analyzed temperature using the Famine Early Warning System Network Land Data Assimilation System, incorporated elevation data from the Shuttle Radar Topography Mission, and assessed vegetation phenology using Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) to evaluate climate variability and its effects on Bhutan. In situ temperature and precipitation data were also collected from the Himalayan Environmental Rhythm Observation and Evaluation System (HEROES) project and Bhutan’s National Center for Hydrology and Meterology. Modeled and in situ data showed similar trends in precipitation and temperature for the Thimpu, Chhukha, and Gasa regions. Aqua and Terra MODIS phenology data were variable from year to year. However, the data suggested a late onset of spring green up. Partners at the Bhutan Foundation and locally in Bhutan can use this information to better understand and monitor climate variability and replicate these methods for future analysis.

Kinley Dorji↗

Bhutan Water Resources Project Summary - Comparing Precipitation, Temperature, and Phenology Data Trends in Bhutan to Assist the Himalayan Environmental Rhythm Observation and Evaluation System (HEROES) Project

Himalayan countries, including Bhutan, have become vulnerable to warming trends which result in increasing temperature and variable rainfall and snowfall. By combining phenological and meteorological data, Earth observation platforms and sensors were used to assess trends in precipitation, temperature, and vegetation phenology in Bhutan from 1996 through 2017. This project studied precipitation using Climate Hazards Center Infrared Precipitation with Station data, analyzed temperature using the Famine Early Warning System Network Land Data Assimilation System, incorporated elevation data from the Shuttle Radar Topography Mission, and assessed vegetation phenology using Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) to evaluate climate variability and its effects on Bhutan. In situ temperature and precipitation data were also collected from the Himalayan Environmental Rhythm Observation and Evaluation System (HEROES) project and Bhutan’s National Center for Hydrology and Meterology. Modeled and in situ data showed similar trends in precipitation and temperature for the Thimpu, Chhukha, and Gasa regions. Aqua and Terra MODIS phenology data were variable from year to year. However, the data suggested a late onset of spring green up. Partners at the Bhutan Foundation and locally in Bhutan can use this information to better understand and monitor climate variability and replicate these methods for future analysis.

DEVELOP Project Summary↗

Self‐Standing Carbon Nanofibers@Carbon Felt Electrodes to Boost Electrolyzer Productivity: Application to the Electro‐Manufacturing of trans ‐3‐Hexenedioic Acid and Adipic Acid

The industrial implementation of electrosynthesis for chemical manufacturing remains constrained by the limited surface area of conventional electrodes. Herein, this challenge is addressed by designing a carbon nanofiber@carbon felt (CNF@CF) electrode platform that combines the high conductivity, flexibility, and ease of handling of commercial carbon felts (CF) with the large surface area and tunable surface chemistry of carbon nanofibers (CNFs). CNFs are deliberately grown onto the CF scaffold to form a sword-in-sheath structure, where entangled nanofibers wrap the felt macrofibers to provide excellent mechanical stability and electrical conductivity without binders. CNF@CF is evaluated both as an electrode and as a catalyst support for the electrochemical hydrogenation of cis,cis-muconic acid (ccMA), a biobased platform molecule key to the production of performance polyamides and renewable Nylon 6,6. As a noncatalytic electrode for the partial hydrogenation to trans-3-hexenedioic acid, CNF@CF achieves a threefold increase in both cumulative productivity and Faradaic efficiency (FE) compared to bare CF. A similar boost in catalytic activity and energy efficiency is observed using Pd/CNF@CF for the hydrogenation of ccMA to adipic acid. These results highlight the opportunities of the CNF@CF platform for electro-organic synthesis and sustainable chemical manufacturing.

electrochemical hydrogenation↗

Spatially Resolved Proteome Profiling of <200 Cells from Tomato Fruit Pericarp by Integrating Laser-Capture Microdissection with Nanodroplet Sample Preparation

Due to sensitivity limitations, global proteome measurements generally require large amounts of biological starting material, which masks heterogeneity within the samples and differential protein expression among constituent cell types. Methods for spatially-resolved proteomics are being developed to resolve protein expression for distinct single cell types among highly heterogeneous tissues, but have primarily been applied to mammalian systems. Here we evaluate the performance of cell-type-specific proteome analysis of tomato fruit pericarp tissues by a platform integrating laser capture microdissection (LCM) and a recently developed automated sample preparation system (nanoPOTS, Nanodroplet processing in One pot for Trace Samples). Tomato fruits were cryosectioned prior to LCM, and tissues were dissected and captured directly into nanoPOTS chips for processing. Following processing, samples were analyzed by nanoLC-MS/MS. Approximately 1900 unique peptides and 422 proteins were identified on average from ~0.04 mm2 tissues comprising ~ 8-15 parenchyma cells. Spatially-resolved proteome analyses were performed using cells of outer epidermis, collenchyma, and parenchyma. Using =200 cells, a total of 1,870 protein groups were identified and the various tissues were easily resolved. The results provide spatial and tissue-specific insights into key enzymes and pathways involved in carbohydrate transport and source-sink relationships in tomato fruit. Of note, at the time of fruit ripening studied here, we identified differentially abundant proteins throughout the pericarp related to chlorophyll biogenesis, photosynthesis, and especially transport.

Liang, Yiran↗

De Novo Design of Proteins That Bind Naphthalenediimides, Powerful Photooxidants with Tunable Photophysical Properties

De novo protein design provides a framework to test our understanding of protein function and build proteins with cofactors and functions not found in nature. Here, we report the design of proteins designed to bind powerful photooxidants and the evaluation of the use of these proteins to generate diffusible small-molecule reactive species. Because excited-state dynamics are influenced by the dynamics and hydration of a photooxidant’s environment, it was important to not only design a binding site but also to evaluate its dynamic properties. Thus, we used computational design in conjunction with molecular dynamics (MD) simulations to design a protein, designated NBP (NDI Binding Protein), that held a naphthalenediimide (NDI), a powerful photooxidant, in a programmable molecular environment. Solution NMR confirmed the structure of the complex. We evaluated two NDI cofactors in this de novo protein using ultrafast pump–probe spectroscopy to evaluate light-triggered intra- and intermolecular electron transfer function. Moreover, we demonstrated the utility of this platform to activate multiple molecular probes for protein labeling.

carbonyls↗

An Analysis Workflow-Aware Storage System for Multi-Core Active Flash Arrays

Here, the need for novel data analysis is urgent in the face of a data deluge from modern applications. Traditional approaches to data analysis incur significant data movement costs, moving data back and forth between the storage system and the processor. Emerging Active Flash devices enable processing on the flash, where the data already resides. An array of such Active Flash devices allows us to revisit how analysis workflows interact with storage systems. By seamlessly blending together the flash storage and data analysis, we create an analysis workflow-aware storage system, AnalyzeThis. Our guiding principle is that analysis-awareness be deeply ingrained in each and every layer of the storage, elevating data analyses as first-class citizens, and transforming AnalyzeThis into a potent analytics-aware appliance. To evaluate the AnalyzeThis system, we have adopted both emulation and simulation approaches. In particular, we have evaluated AnalyzeThis by implementing the AnalyzeThis storage system on top of the Active Flash Array's emulation platform. We have also implemented an event-driven AnalyzeThis simulator, called AnalyzeThisSim, which allows us to address the limitations of the emulation platform, e.g., performance impact of using multi-core SSDs. The results from our emulation and simulation platforms indicate that AnalyzeThis is a viable approach for expediting workflow execution and minimizing data movement.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

SU-E-P-22: AAPM Task Group 263 Tackling Standardization of Nomenclature for Radiation Therapy

Purpose: There is growing recognition of need for increased clarity and consistency in the nomenclatures used for body and organ structures, DVH metrics, toxicity, dose and volume units, etc. Standardization has multiple benefits; e.g. facilitating data collection for clinical trials, enabling the pooling of data between institutions, making transfers (i.e. hand-offs) between centers safer, and enabling vendors to define “default” settings. Towards this goal, the American Association of Physicists in Medicine (AAPM) formed a task group (TG263) in July of 2014, operating under the Work Group on Clinical Trials to develop consensus statements. Guiding principles derived from the investigation and example nomenclatures will be presented for public feedback. Methods: We formed a multi-institutional and multi-vendor collaborative group of 39 physicists, physicians and others involved in clinical use and electronic transfer of information. Members include individuals from IROC, NRG, IHE-RO, DICOM WG-7, ASTRO and EORTC groups with overlapping interests to maximize the quality of the consensus and increase the likelihood of adoption. Surveys of group and NRG members were used to define current nomenclatures and requirements. Technical requirements of vendor systems and the proposed DICOM standards were examined. Results: There is a marked degree of inter and intra institutional variation in current approaches, resulting from inter-vendor differences in capabilities, clinic specific conceptualizations and inconsistencies. Using a consensus approach, the group defined optimal formats for the naming of targets and normal structures. A formal objective assessment of 13 existing clinically-used software packages show that all had capabilities to accommodate these recommended nomenclatures. Conclusions: A multi-stakeholder effort is making significant steps forward in developing a standard nomenclature that will work across platforms. Our current working list includes > 550 structures. Outreach efforts are ongoing to ensure broader participation in evaluating and testing the principles as they are developed by TG263.

60 APPLIED LIFE SCIENCES↗

SU-F-T-346: Dose Mimicking Inverse Planning Based On Helical Delivery Treatment Plans for Head and Neck Patients

Purpose: We aim to evaluate a new commercial dose mimicking inverse-planning application that was designed to provide cross-platform treatment planning, for its dosimetric quality and efficiency. The clinical benefit of this application allows patients treated on O-shaped linac to receive an equivalent plan on conventional L-shaped linac as needed for workflow or machine downtime. Methods: The dose mimicking optimization process seeks to create a similar DVH of an O-shaped linac-based plans with an alternative treatment technique (IMRT or VMAT), by maintaining target conformity, and penalizing dose falloff outside the target. Ten head and neck (HN) helical delivery plans, including simple and complex cases were selected for re-planning with the dose mimicking application. All plans were generated for a 6 MV beam model, using 7-field/ 9-field IMRT and VMAT techniques. PTV coverage (D1, D99 and homogeneity index [HI]), and OARs avoidance (Dmean / Dmax) were compared. Results: The resulting dose mimicked HN plans achieved acceptable PTV coverage for HI (VMAT 7.0±2.3, 7-fld 7.3±2.4, and 9-fld 7.0±2.4), D99 (98.0%±0.7%, 97.8%±0.7%, and 98.0%±0.7%), as well as D1 (106.4%±2.1%, 106.5%±2.2%, and 106.4%±2.1%), respectively. The OAR dose discrepancy varied: brainstem (2% to 4%), cord (3% to 6%), esophagus (−4% to −8%), larynx (−4% to 2%), and parotid (4% to 14%). Mimicked plans would typically be needed for 1–5 fractions of a treatment course, and we estimate <1% variance would be introduced in target coverage while maintaining comparable low dose to OARs. All mimicked plans were approved by independent physician and passed patient specific QA within our established tolerance. Conclusion: Dose mimicked plans provide a practical alternative for responding to clinical workflow issues, and provide reliability for patient treatment. The quality of dose mimicking for HN patients highly depends on the delivery technique, field numbers and angles, as well as user selection of structures.

60 APPLIED LIFE SCIENCES↗

A HPC “Cyber Wind Facility” Incorporating Fully-Coupled CFD/CSD for Turbine-Platform-Wake Interactions with the Atmosphere and Ocean

The central aims of the DOE-supported “Cyber Wind Facility” project center on the recognition that wind turbines over land and ocean generate power from atmospheric winds that are inherently turbulent and strongly varying, both spatially over the rotor disk and in temporally as the rotating blades pass through atmospheric eddies embedded within the mean wind. The daytime unstable atmospheric boundary layer (ABL) is particularly variable in space time as solar heating generates buoyancy-driven motions that interact with strong mean shear in the ABL “surface layer,” the lowest 200 - 300 m where wind turbines reside in farms. With the “Cyber Wind Facility” (CWF) program we initiate a research and technology direction in which “cyber data” are generated from “computational experiments” within a “facility” akin to a wind tunnel, but with true space-time atmospheric turbulence that drive utility-scale wind turbines at full-scale Reynolds numbers. With DOE support we generated the key “modules” within a computational framework to create a first generation Cyber Wind Facility (CWF) for single wind turbines in the daytime ABL---both over land where the ABL globally unstable and over water with closer-to-neutral atmospheric conditions but with time response strongly affected by wave-induced forcing of the wind turbine platform (here a buoy configuration). The CWF program has significantly improved the accuracy of actuator line models, evaluated with the Cyber Wind Facility in full blade-boundary-layer-resolved mode. The application of the CWF made in this program showed the existence of important ramp-like response events that likely contribute to bearing fatigue failure on the main shaft and that the advanced ALM method developed here captures the primary nonsteady response characteristics. Long-time analysis uncovered distinctive key dynamics that explain primary mechanisms that underlie potentially deleterious load transients. We also showed that blade bend-twist coupling plays a central role in the elastic responses of the blades to atmospheric turbulence, impacting turbine power.

17 WIND ENERGY↗

ExaTN: Scalable GPU-Accelerated High-Performance Processing of General Tensor Networks at Exascale

We present ExaTN (Exascale Tensor Networks), a scalable GPU-accelerated C++ library which can express and process tensor networks on shared- as well as distributed-memory high-performance computing platforms, including those equipped with GPU accelerators. Specifically, ExaTN provides the ability to build, transform, and numerically evaluate tensor networks with arbitrary graph structures and complexity. It also provides algorithmic primitives for the optimization of tensor factors inside a given tensor network in order to find an extremum of a chosen tensor network functional, which is one of the key numerical procedures in quantum many-body theory and quantum-inspired machine learning. Numerical primitives exposed by ExaTN provide the foundation for composing rather complex tensor network algorithms. We enumerate multiple application domains which can benefit from the capabilities of our library, including condensed matter physics, quantum chemistry, quantum circuit simulations, as well as quantum and classical machine learning, for some of which we provide preliminary demonstrations and performance benchmarks just to emphasize a broad utility of our library.

97 MATHEMATICS AND COMPUTING↗

Far-infrared radiometer to map OH in the middle atmosphere

A baseline design is evaluated for a far-infrared radiometer to map global concentration profiles of OH from a satellite platform. The instrument performance is modeled using the spectral database and radiative transfer models developed from recent balloon-based studies of the upper atmosphere. The results indicate that the OH concentration can be measured by limb sounding with 10-percent accuracy in the region of its peak concentration near 40 km, but with useful data for the altitude range between 25 and 120 km. The resolution is 3.5 km in the vertical and 500 km in the horizontal direction. The same technique in principle can be expanded in a multichannel mode to address other related species, e.g. H2O, O3, and HO2, which have accessible rotational emission features in the far-infrared spectral region.

Nolt, I. G.↗

Laser transmitter module for NASA lidar in space technology experiment (LITE)

NASA's lidar in Space Technology Experiment (LITE) is a multimission Space Transportation System (STS) program to evaluate the capability of a lidar experiment to measure aerosols and other atmospheric parameters from a space platform. The measurements will be made at three wavelengths (1.06, 0.532 and 0.355 microns). This paper presents the results to date of the program to produce the space-qualified laser transmitter module (LTM) for this mission.

Chang, J. H.↗

An Asynchronous Task-based Fan-Both Sparse Cholesky Solver

Systems of linear equations arise at the heart of many scientific and engineering applications. Many of these linear systems are sparse; i.e., most of the elements in the coefficient matrix are zero. Direct methods based on matrix factorizations are sometimes needed to ensure accurate solutions. For example, accurate solution of sparse linear systems is needed in shift-invert Lanczos to compute interior eigenvalues. The performance and resource usage of sparse matrix factorizations are critical to time-to-solution and maximum problem size solvable on a given platform. In many applications, the coefficient matrices are symmetric, and exploiting symmetry will reduce both the amount of work and storage cost required for factorization. When the factorization is performed on large-scale distributed memory platforms, communication cost is critical to the performance of the algorithm. At the same time, network topologies have become increasingly complex, so that modern platforms exhibit a high level of performance variability. This makes scheduling of computations an intricate and performance-critical task. In this paper, we investigate the use of an asynchronous task paradigm, one-sided communication and dynamic scheduling in implementing sparse Cholesky factorization (symPACK) on large-scale distributed memory platforms. Our solver symPACK relies on efficient and flexible communication primitives provided by the UPC++ library. Performance evaluation shows good scalability and that symPACK outperforms state-of-the-art parallel distributed memory factorization packages, validating our approach on practical cases.

Jacquelin, Mathias↗

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗