Synthesis and lanthanide coordination chemistry of CMPO-decorated dibenzothiophene and dibenzothiophene sulfone platforms
Not Available
Rosario-Amorin, Daniel↗
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1:50 Scale Testing of Three Floating Wind Turbines at MARIN and Numerical Model Validation Against Test Data
The primary goal of the basin model test program discussed herein is to properly scale and accurately capture physical data of the rigid body motions, accelerations and loads for different floating wind turbine platform technologies. The intended use for this data is for performing comparisons with predictions from various aero-hydro-servo-elastic floating wind turbine simulators for calibration and validation. Of particular interest is validating the floating offshore wind turbine simulation capabilities of NREL’s FAST open-source simulation tool. Once the validation process is complete, coupled simulators such as FAST can be used with a much greater degree of confidence in design processes for commercial development of floating offshore wind turbines. The test program subsequently described in this report was performed at MARIN (Maritime Research Institute Netherlands) in Wageningen, the Netherlands. The models considered consisted of the horizontal axis, NREL 5 MW Reference Wind Turbine (Jonkman et al., 2009) with a flexible tower affixed atop three distinct platforms: a tension leg platform (TLP), a spar-buoy modeled after the OC3 Hywind (Jonkman, 2010) and a semi-submersible. The three generic platform designs were intended to cover the spectrum of currently investigated concepts, each based on proven floating offshore structure technology. The models were tested under Froude scale wind and wave loads. The high-quality wind environments, unique to these tests, were realized in the offshore basin via a novel wind machine which exhibits negligible swirl and low turbulence intensity in the flow field. Recorded data from the floating wind turbine models included rotor torque and position, tower top and base forces and moments, mooring line tensions, six-axis platform motions and accelerations at key locations on the nacelle, tower, and platform. A large number of tests were performed ranging from simple free-decay tests to complex operating conditions with irregular sea states and dynamic winds.
17 WIND ENERGY↗
SMALL UNMANNED MARINE HYDROKINETIC PLATFORMS FOR POWER GENERATION IN COASTAL AND TIDAL WATERS
The feasibility and optimization of small unmanned mobile marine hydrokinetic (MHK) energy platforms for harvesting marine current energy in coastal and tidal waters are examined. A case study of a platform based on the use of a free-surface waterwheel (FSWW) mounted on an autonomous unmanned surface vehicle (USV) was conducted. Such platforms can serve as recharging stations for aerial drones (UAVs), enabling extension of the UAVs’ autonomous operating time. An unmanned MHK platform potentially meets this need with sustainable power harvested from water currents. For the case study, six different waterwheel configurations were field-tested in the Intracoastal Waterway of South Florida in support of determining the configuration that produced the most power. Required technologies for unmanned operations of the MHK platform were developed and tested. The data from the field-testing were analyzed to develop an empirical relation between the wheel’s theoretical hydrokinetic power produced and the mechanical power harnessed by the MHK platform with various waterwheel configurations during field-testing. The field data was also used to determine the electrical power generated by the FSWW configurations during field-testing. The study has led to the development of standardized testing procedures. The empirical relation is used to examine predicted power production through scaling up different physical aspects of the waterwheel.
McKinney, Adriana↗
BEAM: A Computational Workflow System for Managing and Modeling Material Characterization Data in HPC Environments
Improvements in scientific instrumentation allow imaging at mesoscopic to atomic length scales, many spectroscopic modes, and now—with the rise of multimodal acquisition systems and the associated processing capability—the era of multidimensional, informationally dense data sets has arrived. Technical issues in these combinatorial scientific fields are exacerbated by computational challenges best summarized as a necessity for drastic improvement in the capability to transfer, store, and analyze large volumes of data. The Bellerophon Environment for Analysis of Materials (BEAM) platform provides material scientists the capability to directly leverage the integrated computational and analytical power of High Performance Computing (HPC) to perform scalable data analysis and simulation via an intuitive, cross-platform client user interface. This framework delivers authenticated, “push-button” execution of complex user workflows that deploy data analysis algorithms and computational simulations utilizing the converged compute-and-data infrastructure at Oak Ridge National Laboratory's (ORNL) Compute and Data Environment for Science (CADES) and HPC environments like Titan at the Oak Ridge Leadership Computing Facility (OLCF). In this work we address the underlying HPC needs for characterization in the material science community, elaborate how BEAM's design and infrastructure tackle those needs, and present a small sub-set of user cases where scientists utilized BEAM across a broad range of analytical techniques and analysis modes.
96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
Novel Analysis and Visualization of Chemical Events for Public Health Surveillance
Pacific Northwest National Laboratory hosted an intern-based web application development contest in the summer of 2016 centered around developing novel chemical surveillance applications to aid in health situational awareness. Making up the three teams were three graduate students (n=9) from various US schools majoring in non-public health domains, such as computer science and user design. The interns successfully developed three applications that demonstrated a value-add to chemical surveillance—ChemAnalyzer (text analytics), RetroSpect (retrospective analysis of chemical events),and ToxicBusters (geo-based trend analytics). These applications will be the basis for the first chemical surveillance application to be incorporated into the DTRA Biosurveillance Ecosystem (BSVE).Pacific Northwest National Laboratory (PNNL), on behalf the Defense Threat Reduction Agency (DTRA; project number CB10190), hosts an annual intern- based web app development contest. Previous competitions have focused on mobile biosurveillance. The 2016 competition pivoted away from biosurveillance to focus on addressing challenges within the field of chemical surveillance and increasing public health chemical situational awareness. The result of the app will be integrated within the DTRA BSVE. PNNL hosted nine graduate interns for a 10-week period in the summer of 2016 as participants in a summer web application development contest. Students were drawn from such fields as software engineering and user experience and design and placed into three teams of three students. The challenge presented to the interns was to design and develop a fully-functional web application that would address a critical need within the chemical surveillance community. The interns developed their own ideas (vetted by PNNL and DTRA), discovered and integrated their own data sources, and produced their own visualizations and analytics, independent of any assistance outside of that provided in an advisory capacity. The competition end with a judging event with a panel of subject matter experts and cash awards were distributed to the teams. Each team produced a unique application. Although there was mild overlap between some of the ideas, the applications were developed independently and each reflected the unique contributions of the teams. ChemAnalyzer is a text-analytics platform designed to facilitate more data-driven decision, given a corpus of text data about a chemical event. Their platform provided the ability to automatically identify and highlight key words in documents related to chemical events. The keywords are drawn from an ontology installed with the system, as well as any user-identified keywords. The ChemAnalyzer team finished in third place. The RetroSpect team developed a visual analytic tool for performing retrospective analysis and monitoring of chemical events. Their app provided the ability to search and analyze past events, as well as visualization of state and county information for the recorded chemical events. The RetroSpect team finished in second place. The Toxic busters team - the winners of the competition - created a geo-based situational awareness tool for tracking chemical events. Their app featured an updateable map overlay, search functionality for finding specific or related events, incident and city/state/national-level statistics and trends, as well as news and social media integration based on keywords related to chemical surveillance. Each of the apps developed by the teams provides value to an analyst tasked with monitoring chemical events. The apps integrated unique data sources to provides a full picture of a chemical event, and its effects upon the surrounding population. This integrated analytics provides a valuable benefit over existing workflows, where analysts must monitor news, social, and other information sources manually for real-time information. The apps developed by these interns are designed to enable identification and analysis of the incident as quickly as possible, allowing for more timely assessments of the incident and its impacts. The web app development contest provided a unique opportunity for students to learn about the emerging needs in chemical surveillance as it relates to health situational awareness. Students were drawn from a variety of fields and were tasked with developing novel web apps addressing some of the most pressing challenges in the field of chemical surveillance. The ideas generated by the students will help form the basis for future chemical surveillance application development to be integrated with the DTRABSVE.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Slycat™ User Manual
Slycat™ is a web-based system for performing data analysis and visualization of potentially large quantities of remote, high-dimensional data. Slycat™ specializes in working with ensemble data. An ensemble is a group of related data sets, which typically consists of a set of simulation runs exploring the same problem space. An ensemble can be thought of as a set of samples within a multi-variate domain, where each sample is a vector whose value defines a point in high-dimensional space. To understand and describe the underlying problem being modeled in the simulations, ensemble analysis looks for shared behaviors and common features across the group of runs. Additionally, ensemble analysis tries to quantify differences found in any members that deviate from the rest of the group. The Slycat™ system integrates data management, scalable analysis, and visualization. Results are viewed remotely on a user’s desktop via commodity web clients using a multi-tiered hierarchy of computation and data storage, as shown in Figure 1. Our goal is to operate on data as close to the source as possible, thereby reducing time and storage costs associated with data movement. Consequently, we are working to develop parallel analysis capabilities that operate on High Performance Computing (HPC) platforms, to explore approaches for reducing data size, and to implement strategies for staging computation across the Slycat™ hierarchy. Within Slycat™, data and visual analysis are organized around projects, which are shared by a project team. Project members are explicitly added, each with a designated set of permissions. Although users sign-in to access Slycat™, individual accounts are not maintained. Instead, authentication is used to determine project access. Within projects, Slycat™ models capture analysis results and enable data exploration through various visual representations. Although for scientists each simulation run is a model of real-world phenomena given certain conditions, we use the term model to refer to our modeling of the ensemble data, not the physics. Different model types often provide complementary perspectives on data features when analyzing the same data set. Each model visualizes data at several levels of abstraction, allowing the user to range from viewing the ensemble holistically to accessing numeric parameter values for a single run. Bookmarks provide a mechanism for sharing results, enabling interesting model states to be labeled and saved.
97 MATHEMATICS AND COMPUTING↗
Pixel multiplexing technique for real-time three-dimensional-imaging laser detection and ranging system using four linear-mode avalanche photodiodes
The avalanche-photodiode-array (APD-array) laser detection and ranging (LADAR) system has been continually developed owing to its superiority of nonscanning, large field of view, high sensitivity, and high precision. However, how to achieve higher-efficient detection and better integration of the LADAR system for real-time three-dimensional (3D) imaging continues to be a problem. In this study, a novel LADAR system using four linear mode APDs (LmAPDs) is developed for high-efficient detection by adopting a modulation and multiplexing technique. Furthermore, an automatic control system for the array LADAR system is proposed and designed by applying the virtual instrumentation technique. The control system aims to achieve four functions: synchronization of laser emission and rotating platform, multi-channel synchronous data acquisition, real-time Ethernet upper monitoring, and real-time signal processing and 3D visualization. The structure and principle of the complete system are described in the paper. The experimental results demonstrate that the LADAR system is capable of achieving real-time 3D imaging on an omnidirectional rotating platform under the control of the virtual instrumentation system. The automatic imaging LADAR system utilized only 4 LmAPDs to achieve 256-pixel-per-frame detection with by employing 64-bit demodulator. Moreover, the lateral resolution is ∼15 cm and range accuracy is ∼4 cm root-mean-square error at a distance of ∼40 m.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
A digital twin platform for building performance monitoring and optimization: Performance simulation and case studies
Advancements in sensor technology, data analytics, affordable compute, and communication infrastructure have paved the way for Digital Twin technology in optimizing building operations and controls. This study presents the development of an open and interoperable web-based Digital Twin platform for integrating diverse data streams and facilitating effective user interactions. The platform utilizes modern technologies for the web framework and time-series data management, ensuring scalability and responsiveness. The backend supports seamless integration of diverse data sources and emulators, incorporating data from building sensors and meters, external weather Application Programming Interfaces, and advanced EnergyPlus simulation models of the building and its energy systems including the Distributed Energy Resources that are formulated in Functional Mockup Units. A simulation case study was conducted with FlexLab, a test facility on Lawrence Berkeley National Laboratory campus. The case study includes normal operations, Distributed Energy Resource integration, and power outage scenarios, to illustrate the Digital Twin’s ability to provide critical insights into energy performance and thermal resilience. The results demonstrated the platform’s potential as a decision-support tool for optimizing building energy performance and enhancing resilience against extreme weather events. Future work will focus on deploying the Digital Twin platform to a real building for field validation, extending its capabilities to cover more scenarios such as bidirectional Electric Vehicle interactions, and enhancing user engagement.
EnergyPlus↗
Cross-platform validation and analysis environment for particle physics
Not Available
Chekanov, S. V.↗
TestDose: A nuclear medicine software based on Monte Carlo modeling for generating gamma camera acquisitions and dosimetry
Purpose: The TestDose platform was developed to generate scintigraphic imaging protocols and associated dosimetry by Monte Carlo modeling. TestDose is part of a broader project (www.dositest.com) whose aim is to identify the biases induced by different clinical dosimetry protocols. Methods: The TestDose software allows handling the whole pipeline from virtual patient generation to resulting planar and SPECT images and dosimetry calculations. The originality of their approach relies on the implementation of functional segmentation for the anthropomorphic model representing a virtual patient. Two anthropomorphic models are currently available: 4D XCAT and ICRP 110. A pharmacokinetic model describes the biodistribution of a given radiopharmaceutical in each defined compartment at various time-points. The Monte Carlo simulation toolkit GATE offers the possibility to accurately simulate scintigraphic images and absorbed doses in volumes of interest. The TestDose platform relies on GATE to reproduce precisely any imaging protocol and to provide reference dosimetry. For image generation, TestDose stores user’s imaging requirements and generates automatically command files used as input for GATE. Each compartment is simulated only once and the resulting output is weighted using pharmacokinetic data. Resulting compartment projections are aggregated to obtain the final image. For dosimetry computation, emission data are stored in the platform database and relevant GATE input files are generated for the virtual patient model and associated pharmacokinetics. Results: Two samples of software runs are given to demonstrate the potential of TestDose. A clinical imaging protocol for the Octreoscan™ therapeutical treatment was implemented using the 4D XCAT model. Whole-body “step and shoot” acquisitions at different times postinjection and one SPECT acquisition were generated within reasonable computation times. Based on the same Octreoscan™ kinetics, a dosimetry computation performed on the ICRP 110 model is also presented. Conclusions: The proposed platform offers a generic framework to implement any scintigraphic imaging protocols and voxel/organ-based dosimetry computation. Thanks to the modular nature of TestDose, other imaging modalities could be supported in the future such as positron emission tomography.
60 APPLIED LIFE SCIENCES↗
A Modularized Urban Scale Building Energy Modeling Framework Designed with An Open Mind
In recent years, physics-based building energy modeling (BEM) has started being used to evaluate the performance of buildings in the context of connected communities and on an urban scale to study their aggregated energy use, interactions, and impacts on the energy supply infrastructure and environment. The development of urban-scale BEM solutions needs extensive effort. Existing attempts tend to focus on different aspects of BEM on an urban scale, such as collecting as-built building data from different information sources, integrating geometry modeling with geographic information systems (GISs), representing operational and occupancy profiles, automating workflow, processing and visualizing the results, and conducting large-scale simulations. Urban-scale BEM development would benefit from multi-disciplinary research areas and from an open platform to adopt advancements on data sources and tools. For these purposes, this research proposes a modularized bottom-up model creation and simulation framework that is built on the state-of-the-art BEM tools and can accommodate different building stock data. This framework uses a standardized schema to describe building design and operational characteristics, and it can be instantiated from different building survey datasets with heterogeneous structures. The paper demonstrates how thousands of surveyed buildings from the 2012 U.S. Energy Information Administration’s Commercial Buildings Energy Consumption Survey (CBECS) were one-to-one converted to EnergyPlus models through the schema and the model generation process, then simulated with distributed computing, and their results are summarized.
Lei, Xuechen↗
An analysis of alcohol compression ignition strategies on different engine platforms
Strategies that enable ignition of the low cetane alcohol fuels (methanol and ethanol) include intake heating (direct or via hot residual trapping), increased compression ratio (CR), multi-injection strategies, ignition enhancers, and active prechambers. The literature consistently shows alcohol compression ignition (CI) is more efficient than diesel at high loads irrespective of ignition strategy but shows contradictory results at low loads. To understand this, this work combines data from four different engine platforms ranging from a displaced volume of 0.4 to 2.1 L/cyl. using different alcohol CI ignition strategies. Using modeling to support experimental analysis, alcohol-specific efficiency penalties are highlighted to inform alcohol combustion system development. The alcohols’ lower energy density means more fuel must be injected near top dead center to achieve a given load, increasing the relative penalty of sensible/latent heating. Pilot injections help reduce this penalty. Intake heating incurs both a heat transfer penalty and a thermodynamic penalty due to a reduced ratio of specific heats during compression. A strategy that combines elevated CR, large pilot injections, and ignition enhancers can avoid this penalty. Alternatively, a prechamber strategy can achieve this without changing the CR, nor needing ignition enhancers in the fuel. At low loads, diesel burns in a partially premixed mode characterized by high burn rates and low heat losses, reducing alcohol-specific combustion benefits. Alcohol CI on the light-duty platform showed abnormally high heat transfer over diesel compared to other platforms, favoring a more premixed/partially premixed strategy despite a combustion efficiency tradeoff.
33 ADVANCED PROPULSION SYSTEMS↗
MapReduce SVM Game
Despite technological advances making computing devices faster, smaller, and more prevalent in today's age, data generation and collection has outpaced data processing capabilities. Simply having more compute platforms does not provide a means of addressing challenging problems in the big data era. Rather, alternative processing approaches are needed and the application of machine learning to big data is hugely important. The MapReduce programming paradigm is an alternative to conventional supercomputing approaches, and requires less stringent data passing constrained problem decompositions. Rather, MapReduce relies upon defining a means of partitioning the desired problem so that subsets may be computed independently and recom- bined to yield the net desired result. However, not all machine learning algorithms are amenable to such an approach. Game-theoretic algorithms are often innately distributed, consisting of local interactions between players without requiring a central authority and are iterative by nature rather than requiring extensive retraining. Effectively, a game-theoretic approach to machine learning is well suited for the MapReduce paradigm and provides a novel, alternative new perspective to addressing the big data problem. In this paper we present a variant of our Support Vector Machine (SVM) Game classifier which may be used in a distributed manner, and show an illustrative example of applying this algorithm.
97 MATHEMATICS AND COMPUTING↗
Selective stress-based microcantilever sensors for enhanced surveillance
Assessment of component aging and degradation in weapon systems remains a considerable challenge for the Integrated Stockpile Evaluation program. Analysis of weapon atmospheres can provide degradation signatures and indicate the presence of corrosive vapors. However, a critical need exists for compatible in-situ sensors to detect moisture and other gases over stockpile lifetimes. This inhibits development of both “self-aware weapons” and fully instrumented weapon test platforms that could provide in-situ data to validate high-fidelity models for gases within weapons. We developed platforms for on-demand weapon atmosphere surveillance based on static microcantilevers (SMC) and surface accoustic wave (SAW) devices coated with nanoporous metal organic frameworks (MOFs) to provide selectivity.
Allendorf, Mark D.↗
Savannah River Site H-Canyon Collaborative Advanced Technology Demonstration (ATD) - 18313
In support of the Department of Energy's Environmental Management Office of Technology Development (DOE-EM TD) Robotics Technology thrust to pull innovative commercial off the shelf (COTS) and near ready technologies to the field to expedite remaining EM mission clean up and enhance worker safety, the required FY19 Savannah River Site (SRS) H-Canyon Air Exhaust (HCAEX) tunnel inspection task will be used to demonstrate and evaluate the benefit of pulling advanced technology solutions to EM facilities. Presently a biannual visual inspection of the SRS HCAEX tunnel is required to evaluate the structural integrity of the tunnel. While the ability to see inside the tunnel in recent years has been highly invaluable, it is desirable to have a better understanding of the tunnel environment to support a more thorough structural integrity analysis and for long term planning purposes. This higher order of understanding can be accomplished through state of the art COTS sensors and those currently in development and near ready. The ATD will identify and develop for deployment advanced technologies to be hosted on the FY19 inspection platform to acquire high value data desired by the stakeholder. This presentation will include an overview of the ATD mission, background on the tunnel and harsh remote environment in which the inspection robot will work and the high priority inspection needs identified by the H-Canyon facility stakeholders. Discussion will include previous and planned robotic platform modifications to facilitate work in the tunnel and a discussion on the advanced technologies identified to be implemented for the inspection. The ATD will be completed over approximately a 2-year period and has already begun in the form of planning, identification of stakeholder needs, specification of a robust platform and identification of the high priority sensor needs to be pursued. This presentation will be a status of the ATD at approximately the 7-month mark. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
dlmcfpt.c1
The DLMC VAP uses inertial data from the ARM NAV system to transform the Doppler lidar beam angles (az and el) from the lidar's frame of reference to an Earth-fixed frame such the azimuth angle is measured clockwise from true north and the elevation angle is measured from the local horizon. Additionally, the VAP compensates the observed radial (air) velocity data for the effects of the platform velocity (i.e. corrected_radial_velocity = observed_radial_velocity-platform_radial_velocity). The VAP was developed specifically for MOSAiC. The dlmcfpt.c1 product contains the fixed point, or staring data. The dlmcusr.c1 product contains a user defined scan which is anything the operator wants it to be.
54 ENVIRONMENTAL SCIENCES↗
dlmcusr.c1
The DLMC VAP uses inertial data from the ARM NAV system to transform the Doppler lidar beam angles (az and el) from the lidar's frame of reference to an Earth-fixed frame such the azimuth angle is measured clockwise from true north and the elevation angle is measured from the local horizon. Additionally, the VAP compensates the observed radial (air) velocity data for the effects of the platform velocity (i.e. corrected_radial_velocity = observed_radial_velocity-platform_radial_velocity). The VAP was developed specifically for MOSAiC. The dlmcfpt.c1 product contains the fixed point, or staring data. The dlmcusr.c1 product contains a user defined scan which is anything the operator wants it to be.
54 ENVIRONMENTAL SCIENCES↗
Integrating Data Centers and Grid Technologies at Scale
This presentation focuses on the challenge of integrating AI-driven data centers with the power grid at scale. It examines the AI data center capacity challenge and the role of new Medium Voltage Direct Current (MVDC) and other grid-enhancing technologies in enabling efficient and reliable power delivery. The session will highlight the National Laboratory of the Rockies' ARIES capabilities and planning tools, along with collaborative examples involving Verrus, Compass, and Schneider through the Agora test bed for grid-friendly data center evaluations, and ON. Energy for UPS evaluation. It will showcase the NLR Stable Grid Platform for studying oscillations caused by large-scale data centers, along with planning tools to assess grid security and reliability. Additionally, the presentation covers reconductoring strategies to increase grid capacity and explores innovative data center architectures, including the Advanced DC Architectures with Power-electronic Transformers (ADAPT) platform, which enables testing of complete DC architectures for data centers.
24 POWER TRANSMISSION AND DISTRIBUTION↗