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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Development of a Convolutional Neural Network Classifier for Data Starved Spectra - 20199

The Institute for Clean Energy Technology (ICET) at Mississippi State University is exploring the utility of machine learning in augmenting its mobile radiation surveying platforms, which are currently being developed as means to survey depleted uranium contaminated areas in support of remediation and decommissioning efforts. Mobile survey platforms provide a means to efficiently scan large areas of interest while reducing human exposure to radiation and other hazards. The survey platforms can also be used for scanning for any gamma emitting isotope in addition to depleted uranium. The spectral data that the platforms collect may be data starved with relatively low counts and poorly defined spectral features depending on the speed of the platforms and scintillation detector selection. Such data-starved spectra are difficult to use for isotope identification, requiring advanced knowledge of the possible radionuclides that could be present and environmental factors that could attenuate signals or introduce background noise. These factors in combination with the volume of survey data increases the time it takes to perform analysis of survey data when the source type is unknown. There are a number of algorithms in the field of machine learning that can be used to classify data that would be challenging and time-consuming for a human to identify. Supervised machine learning algorithms train models based on extensive amounts of human-labeled training data. Once sufficiently trained, these models can be used to quickly make high-fidelity predictions on new data. Convolutional neural networks are machine learning algorithms that excel in learning representations of 'shapes'. They do this by taking numerical input data and convolving them with spatial feature detectors referred to as filters. These filters are incrementally adjusted to reduce the prediction error on the data during the backpropagation step of training. Discussed in this paper is the development of a convolutional neural network classifier (CNNC) that can utilize spectral survey data for source discrimination and isotope identification. Bench-top laboratory experiments data using LaBr{sub 3}(Ce) scintillation detectors were used to train and evaluate the performance of the developed CNNC. The CNNC is capable of discriminating a variety of gamma emitting source types, differentiating different forms of uranium (depleted vs. natural), and estimating the amount of uranium for a known geometry. The discussed CNNC may be useful in scenarios where survey systems are deployed in situations where hazardous radioactive material maybe present, but the type is unknown. When used in remediation applications the CNNC can be used to screen-out false positives, helping reduce remediation costs. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2017

The Future of EPA's Waste Estimation Support Tool - 17227

The Environmental Protection Agency's (EPA's) Waste Estimation Support Tool (WEST) is a GIS-based decision support tool for estimating the characteristics, amount, and residual radioactivity of waste generated from remediation and cleanup activities after a radiological incident, including those involving radiological dispersal devices, improvised nuclear devices, and nuclear power plants. WEST has been released to the public and has been used in numerous national level exercises and planning scenarios; however, it continues to be improved and refined to add additional functionality and performance. Since its inception, WEST has undergone a myriad of updates, routinely ensuring compatibility with ESRI's ArcGIS and FEMA's Hazus, a tool for estimating potential losses from earthquakes, wind, and flood events. Furthermore, recent enhancements have added reporting and mapping features and multi-state support. Over time, this progress has strained WEST's Microsoft{sup C} Excel based platform. The inherent limitations of Excel have limited the capacity of WEST and narrowed the scope of potential enhancements. Recent collaborative efforts between the Department of Homeland Security's (DHS's) Science and Technology Directorate (S and T) and EPA will see the introduction of a new software platform for easing memory limitations and new and innovative features for improving the accuracy of waste estimates. The planned enhancements include: 1) Systems approach: measure or predict the outcome of decisions associated with disaster response (e.g., decontamination efficacy vs. waste) and to a greater extent, the overall resource demand (e.g., cost, time, etc.); 2) Custom infrastructure data and international support: accommodate non-US building information where available and also add new data and information on recently used decontamination technologies as applied in a real-world incident; 3) Additional waste factors: addition of waste factors that are unique to wide area scenarios such as vehicles and trees as they will likely contribute in a significant manner to the overall waste stream;4) Site analysis and logistics: apply spatial information and analysis technologies to locate and prioritize potential waste staging or storage sites; and use GIS-based logistics planning to better organize, route, and estimate the cost, time, and logistical requirements (i.e., resource demand) associated with transporting large volumes of waste from a disaster-stricken area to waste staging or storage sites; 5) Decontamination technologies: introduce new decontamination technologies, better understand the feasibility and efficacy of new and preexisting decontamination technologies when applied to a wide area incident, and use historical incidents to ground truth waste results; and 6) Resource demand: ability to estimate resource demand information associated with decontamination technologies, waste staging and storage, and logistical information for transporting waste. This paper will describe the next version of WEST (WEST 4.0), and how the aforementioned enhancements will contribute to improving the planning and response capabilities of the tool. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Virtual Design Studio (VDS) - Development of an Integrated Computer Simulation Environment for Performance Based Design of Very-Low Energy and High IEQ Buildings

Executive Summary The objective of this study was to develop a “Virtual Design Studio (VDS)”: a software platform for integrated, coordinated and optimized design of green building systems with low energy consumption, high indoor environmental quality (IEQ), and high level of sustainability. This VDS is intended to assist collaborating architects, engineers and project management team members throughout from the early phases to the detailed building design stages. It can be used to plan design tasks and workflow, and evaluate the potential impacts of various green building strategies on the building performance by using the state of the art simulation tools as well as industrial/professional standards and guidelines for green building system design. Engaged in the development of VDS was a multi-disciplinary research team that included architects, engineers, and software developers. Based on the review and analysis of how existing professional practices in building systems design operate, particularly those used in the U.S., Germany and UK, a generic process for performance-based building design, construction and operation was proposed. It distinguishes the whole process into five distinct stages: Assess, Define, Design, Apply, and Monitoring (ADDAM). The current VDS is focused on the first three stages. The VDS considers building design as a multi-dimensional process, involving multiple design teams, design factors, and design stages. The intersection among these three dimensions defines a specific design task in terms of “who”, “what” and “when”. It also considers building design as a multi-objective process that aims to enhance the five aspects of performance for green building systems: site sustainability, materials and resource efficiency, water utilization efficiency, energy efficiency and impacts to the atmospheric environment, and IEQ. The current VDS development has been limited to energy efficiency and IEQ performance, with particular focus on evaluating thermal performance, air quality and lighting environmental quality because of their strong interaction with the energy performance of buildings. The VDS software framework contains four major functions: 1) Design coordination: It enables users to define tasks using the Input-Process-Output flow approach, which specifies the anticipated activities (i.e., the process), required input and output information, and anticipated interactions with other tasks. It also allows task scheduling to define the work flow, and sharing of the design data and information via the internet. 2) Modeling and simulation: It enables users to perform building simulations to predict the energy consumption and IEQ conditions at any of the design stages by using EnergyPlus and a combined heat, air, moisture and pollutant simulation (CHAMPS) model. A method for co-simulation was developed to allow the use of both models at the same time step for the combined energy and indoor air quality analysis. 3) Results visualization: It enables users to display a 3-D geometric design of the building by reading BIM (building information model) file generated by design software such as SketchUp, and the predicted results of heat, air, moisture, pollutant and light distributions in the building. 4) Performance evaluation: It enables the users to compare the performance of a proposed building design against a reference building that is defined for the same type of buildings under the same climate condition, and predicts the percent of improvements over the minimum requirements specified in ASHRAE Standard 55-2010, 62.1-2010 and 90.1-2010. An approach was developed to estimate the potential impact of a design factor on the whole building performance, and hence can assist the user to identify areas that have most pay back for investment. The VDS software was developed by using C++ with the conventional Model, View and Control (MVC) software architecture. The software has been verified by using a simple 3-zone case building. The application of the VDS concepts and framework for building design and performance analysis has been illustrated by using a medium-sized, five story office building that received LEED Platinum Certification from USGBC.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

PhytoOracle: Scalable, modular phenomics data processing pipelines

As phenomics data volume and dimensionality increase due to advancements in sensor technology, there is an urgent need to develop and implement scalable data processing pipelines. Current phenomics data processing pipelines lack modularity, extensibility, and processing distribution across sensor modalities and phenotyping platforms. To address these challenges, we developed PhytoOracle (PO), a suite of modular, scalable pipelines for processing large volumes of field phenomics RGB, thermal, PSII chlorophyll fluorescence 2D images, and 3D point clouds. PhytoOracle aims to ( i ) improve data processing efficiency; ( ii ) provide an extensible, reproducible computing framework; and ( iii ) enable data fusion of multi-modal phenomics data. PhytoOracle integrates open-source distributed computing frameworks for parallel processing on high-performance computing, cloud, and local computing environments. Each pipeline component is available as a standalone container, providing transferability, extensibility, and reproducibility. The PO pipeline extracts and associates individual plant traits across sensor modalities and collection time points, representing a unique multi-system approach to addressing the genotype-phenotype gap. To date, PO supports lettuce and sorghum phenotypic trait extraction, with a goal of widening the range of supported species in the future. At the maximum number of cores tested in this study (1,024 cores), PO processing times were: 235 minutes for 9,270 RGB images (140.7 GB), 235 minutes for 9,270 thermal images (5.4 GB), and 13 minutes for 39,678 PSII images (86.2 GB). These processing times represent end-to-end processing, from raw data to fully processed numerical phenotypic trait data. Repeatability values of 0.39-0.95 (bounding area), 0.81-0.95 (axis-aligned bounding volume), 0.79-0.94 (oriented bounding volume), 0.83-0.95 (plant height), and 0.81-0.95 (number of points) were observed in Field Scanalyzer data. We also show the ability of PO to process drone data with a repeatability of 0.55-0.95 (bounding area).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

PoE Lighting System Energy Reporting Study, Part 1

The replacement of today’s lighting infrastructure with LED products offers the potential for future connected lighting systems (CLS) that could become a data-collection platform that enables greater energy savings in buildings and cities. Such connected lighting systems can not only drastically improve the energy performance of lighting and other building systems, but also enable a wide array of services, benefits, and revenue streams that would enhance the value of lighting systems. As LED technology matures, maximizing the energy savings from connected LED lighting systems will become increasingly dependent on successful integration into the built environment. That’s why the DOE SSL Program is working closely with industry to identify and collaboratively address the technology development needs of CLS. For several years now, a growing number of wired and wireless network communication technologies have been integrated into commercially available lighting devices. While most commercially available lighting devices continue to require line-voltage AC power, a few new low-voltage DC technologies have also been introduced into the market as options for powering LED devices. More recently, a technology that has long supported non-lighting applications has become increasingly viable for LED lighting. This approach, whereby a single Ethernet cable is used to both provide low-voltage DC power and enable network communication, is generally referred to as Power over Ethernet (PoE). Whereas wireless solutions offer reduced control system installation cost relative to traditional low-voltage alternatives, PoE technology can offer additional cost savings by transmitting power and communications over the same low-voltage cable, while also reducing demand for wireless bandwidth. Although PoE technology was introduced at the start of this century, it was initially of limited applicability to lighting systems to power transmission limits for available Ethernet cabling. However, PoE has become increasingly viable for lighting applications in recent years as Ethernet cabling technology has evolved and relevant standards and specifications have adapted. These gains have been compounded by ongoing improvements to the luminous efficacy of LED technologies, increasing the number of LED luminaires suitable for use with Ethernet switches capable of sourcing PoE. As a result, a growing number of manufacturers have introduced PoE lighting systems in recent years. Connected lighting systems that can report their own energy consumption can deliver increased energy savings over conventional lighting solutions by facilitating data-driven energy management. PoE technology has the potential to be key in bringing this capability to mainstream lighting applications. This study is the first of a multi-part effort to explore the energy reporting capability of commercially-marketed PoE connected lighting systems. It first provides a brief background on the development of the various PoE technologies, ranging from standards-based to proprietary, and illustrates the convergence of PoE power sourcing capabilities and LED luminaire power requirements. It then classifies PoE system devices in relationship to how they are used in systems—introducing new terminology as needed—and briefly describes different PoE system architectures implemented by various lighting manufacturers. A discussion of existing standards and specifications that address energy reporting is provided, and existing test setups and methods germane to characterizing PoE system energy reporting performance are reviewed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

WBS 4.2.1.31 Integrated Life Cycle Sustainability Analysis

The main objective of this project (following the 2017 BETO Program Peer-Review) is to provide BETO with a coherent methodology and modeling framework based on life cycle (LCA) and economic input-output analysis, tested and vetted with stakeholders, to better understand the effects of an expanding U.S. bioeconomy at specific levels including economic dimensions such as jobs, gross domestic product (value added), and environmental criteria such as air pollutant emissions, water and land use, ecotoxicity, and others. This supports a 2019 milestone in the BETO MYP and simultaneously addresses a gap previously identified in the BETO program and highlighted, e.g., by BETO Program Peer Reviewers in 2015 and 2017. To fill in this gap, NREL started collaborating with developers of the national level U.S. Environmentally-Extended Input-Output (USEEIO) model in FY18. This peer-reviewed, open source model is based on publicly available data, and developed and maintained by U.S. EPA where it has been the basis for EPA's Sustainable Material Management analyses and program. Also, USEEIO was initially designed for use with EPA's Tool for the Reduction and Assessment of Chemicals and Other Environmental Impacts (TRACI). It aligns well with similar efforts including the Federal LCA Commons and the Sustainable Acquisition Program at the Department of Defense (DoD). In FY18, NREL convened stakeholders from federal agencies, universities, and private sector entities to identify and form a common understanding of (1) models describing the U.S. economy and how to build off of them, (2) a bioeconomy definition for the next modeling steps, (3) the (sub)sectors that can/should be used in the framework, and (4) opportunities for collaboration and data sharing. NREL then created a first order model by disaggregating, i.e., separating the economic activities associated with and attributed to a selected product of the bioeconomy: corn ethanol. Corn ethanol is well studied and has a significant amount of public, validated economic industry information. This is important as disaggregation is a critical step in creating a representative and accurate framework. Corn ethanol served as a validation test case for the method and framework. By the end of FY18, the team was able to generate several scenarios for corn ethanol on national and selected regional levels providing results on the absolute and relative (Megajoule) effects in several environmental and economic impact categories. A second objective of the project is to inform BETO's strategic decision making, specifically its sustainability research portfolio, by engaging in, evaluating, and synthesizing selected global multi-year activities from the perspectives of a variety of complex multilateral and multi-stakeholder processes that pertain to bioenergy. This helps to (1) identify gaps, barriers, and critical areas for future BETO bioenergy and sustainability assessments; (2) identify opportunities and challenges to a sustainable U.S. bioeconomy; and (3) contribute to and disseminate BETO information to and from major global bioenergy and sustainability efforts. This project's work with multilateral organizations ensures that U.S. science-based viewpoints are considered and helps to balance the influence of the large number of countries with the same centralized philosophy. This engagement builds a more solid foundation for sustainable biomass and bioenergy systems in the U.S. and in the world. Working with multi-lateral, international platforms including IEA Bioenergy, Global Bio-Energy Partnership (GBEP), and their partner organizations also allows engagement with important stakeholders including policy makers, industry, NGOs, and academia.

09 BIOMASS FUELS↗
DOE OSTI2019

Scalable and efficient learning from crowds with Gaussian processes

Over the last few years, multiply-annotated data has become a very popular source of information. Online platforms such as Amazon Mechanical Turk have revolutionized the labelling process needed for any classification task, sharing the effort between a number of annotators (instead of the classical single expert). This crowdsourcing approach has introduced new challenging problems, such as handling disagreements on the annotated samples or combining the unknown expertise of the annotators. Probabilistic methods, such as Gaussian Processes (GP), have proven successful to model this new crowdsourcing scenario. However, GPs do not scale up well with the training set size, which makes them prohibitive for medium-to-large datasets (beyond 10K training instances). This constitutes a serious limitation for current real-world applications. In this work, we introduce two scalable and efficient GP-based crowdsourcing methods that allow for processing previously-prohibitive datasets. The first one is an efficient and fast approximation to GP with squared exponential (SE) kernel. The second allows for learning a more flexible kernel at the expense of a heavier training (but still scalable to large datasets). Since the latter is not a GP-SE approximation, it can be also considered as a whole new scalable and efficient crowdsourcing method, useful for any dataset size. Both methods use Fourier features and variational inference, can predict the class of new samples, and estimate the expertise of the involved annotators. A complete experimentation compares them with state-of-the-art probabilistic approaches in synthetic and real crowdsourcing datasets of different sizes. Finally, they stand out as the best performing approach for large scale problems. Moreover, the second method is competitive with the current state-of-the-art for small datasets.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Certifying the Performance of Fixative Technologies under Open Air Demolition Activities for D and D - 20096

Department of Energy (DOE) facilities undergoing deactivation and decommissioning (D and D) activities struggle with safety concerns of residual radioactive contamination leftover after gross decontamination efforts have concluded. The positive effects of implementing fixative technologies for decommissioning and maintenance is known across the DOE complex. However, there is no standardized metric in place that quantifies the performance of these technologies such as incombustible fixative platforms that immobilize the contamination in a solid polymer material under normal operating conditions or when exposed to stressors. The primary focus of this research is to provide the empirical data necessary to properly characterize the effects of implementing fixative technologies on mitigating the release of contamination. In addition, this effort has been used to identify and establish uniform testing protocols to quantify operational parameters of fixating platforms and properly credit such systems under a variety of operational conditions and stressors that can arise during open air demolition efforts (e.g. impact, water, thermal, etc.). The established protocols will be provided to the ASTM International E10.03 Subcommittee on Radiological Protection for Decontamination and Decommissioning of Nuclear Facilities and Components for the potential of formal standardization. Attributes to be addressed during testing are material compromise from impact stress, thermal stress for incombustible fixative materials, and immobilization factors (how well an immobilizing platform is capable of retaining fixated material during thermal and impact stressors). In developing these test methods, a greater understanding of the material's behavior under anticipated and unanticipated events, such as decommissioning activities and contingency events as outlined in the Basis of Interim Operations (BIO), can be successfully characterized. There are several key components of the experimental methodology that is essential in empirically certifying fixative technologies. A surrogate contaminant with a unique signature has been utilized with the implementation of a uniform contamination process of test coupons that is quantifiable and replicable for direct fixative comparisons. A modular test chamber has also been used to apply the various stressors of interest. Collection of released contamination that includes airborne and resettled contaminant particles and analyzed using mass spectrometry. This research directly supports DOE complex-wide concerns in terms of final disposition of nuclear facilities and the considerations made during their time between ceasing facility operation and final disposition. The results of this effort aims to provide a standardized road map and logical decision flow to better facilitate fixative technologies into D and D activities required to achieve the desired facility end state. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2018

GPM Mission's Best Practices: PERP

Similar to other missions, the Global Precipitation Measurement (GPM) Core Observatory's Command and Data Handling (C&DH) subsystem is critical for operations of the spacecraft. The onboard C&DH system comprises of two fully redundant boxes - a primary and a cold backup. Within each box, amongst other components, is a Single Board Computer (SBC) that hosts the flight software (FSW) system. In the event of an SBC reset, the Flight Operations Team (FOT) is poised with a lengthy task of restoring the SBC to nominal configuration. Due to the complexity of the C&DH system, this may take many days at a time to complete. The spacecraft's FSW applications are located in Electronically Erasable Programmable Read-Only Memory (EEPROM) and are copied into Random Access Memory (RAM) upon SBC initialization/reset. Each SBC has two banks of EEPROM, with each bank containing a copy of the FSW. Since launch, there have been many configuration changes to tables and applications that have been loaded into just RAM. Unfortunately, these changes are vulnerable to being wiped during a SBC initialization/reset, when the RAM is overwritten by the EEPROM. Although the EEPROM loads the default FSW configurations, the process to command non-default individual table and application changes is very cumbersome and time consuming. This consequentially increases the time until the spacecraft is back into nominal Mission Science Mode (MSM) drastically. The GPM Power-On Reset (POR) Expedited Recovery Process (PERP) Design introduces a method of consolidating commands into a single file load which the SBC can process independently of the ground - decreasing recovery time, the level of TDRS support reliance, and human error. This tested design can be implemented across many other missions that utilize a similar core Flight Executive (cFE) platform; hence providing an easy-to-follow, safe, and efficient process that can be applied across the board.

recovery↗
DOE OSTI2023

Small Reactors in Microgrids: Technology Modeling and Selection (Net-Zero Microgrid Program Project Report)

This report demonstrates the capabilities of the net-zero microgrid (NZM) Xendee platform for modeling an SR module with electricity, heat extraction and thermal storage in microgrids configurations. The model effectively captures the most important technical and economic considerations for SR technology specific analysis: cost and operational characteristics of SR technology and financial costs and incentives. The model can analyze multiple scenarios to establish metrics for cost-competitive and zero-carbon microgrids connected to the grid or completely isolated. The model is fully integrated within the Xendee platform for modeling and analysis of clean energy microgrids with storage and generation from renewable energy sources. The model captures the capabilities, constraints, and nuances of SR by incorporating parameters related to plant economics, design efficiency and performance, plant operation and component and fuel lifespan. The cost and operational parameters modeled in the SR module are specific to the technology selected for integration in the microgrid. Cost parameters recognize advanced nuclear technology for modular production and installation based on economies of scale from factory manufacture and related commissioning, and cost reduction through technology maturation—first-of-a-kind (FOAK) and nth-of-a-Kind (NOAK). The cost parameters include installation, operations and maintenance (O&M), fuel refueling cycle, and reactor life. Installation cost reflects economies of scale due to unit sizing at scale and colocation. O&M economies of scale for both fixed- and variable-cost fuel life-cycle costs are incurred at every refueling interval, with separate front- and back-end fuel costs, as well as waste-handling and disposition costs. This report investigates key characteristics of different SR technologies suitable for microgrid applications, including design principles, sizing, coolant properties, temperature ratings, fuel structures, and life-cycle considerations. This also includes fuel technologies applicable to these SR systems, alongside strategies for nuclear-waste and spent-fuel management and approaches to address safety, security, and proliferation challenges. Four primary groups of SR technologies are examined: water-cooled, liquid-metal-cooled, high-temperature gas-cooled, and molten-salt-cooled systems. In this report, an initial guideline for technology selection is established, aligning the characteristics of the technologies with the requirements of microgrids. The selection of technology in a microgrid is influenced by various factors, including financial capacity, location and accessibility, demand type and characteristics, reliability and resilience requirements, area constraints, and the lifespan of the microgrid. The types of electrical and non-electrical applications within the microgrid also play a significant role in technology selection. The characteristics of SRs, such as their smaller size, modularity, transportability, long refueling interval, improved safety features, ability to operate in autonomous or semi-autonomous mode, and provision of high-grade heat, are particularly appealing for microgrids. Furthermore, a list of considerations for implementing SRs in microgrids is outlined. The SR model is created to be continuously improved with the acquisition of actual data on investment and operational costs, experience with supply chains, production at scale, and field deployments. In the near term, performance data on applications in microgrids will become available from lessons learned from laboratory tests, such as those planned for the Microreactor Applications Research Validation and Evaluation Project (MARVEL), led by Idaho National Laboratory (INL). The SR model incorporates scenario data and known SR design specifications, enabling technoeconomic analysis for SR deployment in microgrids. It specifically considers the distinctive attributes of SRs as generators in technoeconomic studies. SRs can be modeled and analyzed with generation from renewable-energy sources, energy storage, and flexible loads over a range of functionality and applications. This offers a comprehensive tool for feasibility studies, scenario development, and sensitivity analysis for “what-if” consideration of any range of assumptions about SRs in microgrids and other aggregations of distributed-energy resources, including virtual power plants.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

IMG-ABC. A knowledge base to fuel discovery of biosynthetic gene clusters and novel secondary metabolites

In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG’s comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC’s focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in lphaproteobacteria . IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG’s extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Evaluation of Engineered Barrier Systems in the Disposition of Spent Nuclear Fuel

This document is a summary of the R&D activities associated with the Engineered Barrier Systems Work Package. Multiple facets of Engineered Barrier Systems (EBS) research were examined in the course of FY18 activities. This report is focused on delivering an update on the status and progress of modelling tools and experimental methods, both of which are essential to understanding and predicting long-term repository performance as part of the safety case. Specifically, the work described herein aims to improve understanding of EBS component evolution and interactions. Utlimately, the EBS Work Package is working towards producing process models for distinct processes that can either be incorporated into performance assessment (PA), or provide critical information for implementing better constraints on barrier performance The main objective of this work is that the models being developed and refined will either be implemented directly into the Generic Disposal System Analysis platform (GDSA), or can otherwise be indirectly linked to the performance assessment by providing improved bounding conditions. In either the case, the expectation is that validated modelling tools will be developed that provide critical input to the safety case. This report covers a range of topics — modelling topics include: thermal-hydrologic-mechanical-chemical coupling (THMC) in buffer materials, comparisons of modelling approaches to optimize computational efficiency, thermal analysis for EBS/repository design, benchmarking of thermal analysis tools, and a preliminary study of buffer re-saturation processes. Experimental work reported, includes: chemical evolution and sorption behavior of clay-based buffer materials and high-pressure, high temperature studies of EBS material interactions. The work leverages international collaborations to ensure that the DOE program is active and abreast of the latest advances in nuclear waste disposal. This includes participation in the HotBENT Field Test, aimed at understanding near-field effects on EBS materials at temperatures above 100 °C, and the analysis of data and characterization of samples from the FEBEX Field Test. Both the FEBEX and HotBENT Field Tests utilize/utilized the Grimsel Test Site in Switzerland, which is situated in a granite host rock. These tests offer the opportunity to understand near field evolution of bentonite buffer at in situ conditions for either a relatively long timescale (18 years for FEBEX) or temperature above 100 °C (HotBENT). Overall, this report provides in depth descriptions of tools and capabilities to investigate nearfield performance of EBS materials (esp. bentonite buffer), as well as tools for drift-scale thermal and thermal-hydrologic analysis critical to EBS and repository design. For a more detailed description of work contained herein, please see Section 10 ("Conclusions") of this document.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Development of a SPARK Training Dataset

In its first five years, the National Nuclear Security Administration’s (NNSA) Next Generation Safeguards Initiative (NGSI) sponsored more than 400 undergraduate, graduate, and post-doctoral students in internships and research positions (Wyse 2012). In the past seven years, the NGSI program has, and continues to produce a large body of scientific, technical, and policy work in targeted core safeguards capabilities and human capital development activities. Not only does the NGSI program carry out activities across multiple disciplines, but also across all U.S. Department of Energy (DOE)/NNSA locations in the United States. However, products are not readily shared among disciplines and across locations, nor are they archived in a comprehensive library. Rather, knowledge of NGSI-produced literature is localized to the researchers, clients, and internal laboratory/facility publication systems such as the Electronic Records and Information Capture Architecture (ERICA) at the Pacific Northwest National Laboratory (PNNL). There is also no incorporated way of analyzing existing NGSI literature to determine whether the larger NGSI program is achieving its core safeguards capabilities and activities. A complete library of NGSI literature could prove beneficial to a cohesive, sustainable, and more economical NGSI program. The Safeguards Platform for Automated Retrieval of Knowledge (SPARK) has been developed to be a knowledge storage, retrieval, and analysis capability to capture safeguards knowledge to exist beyond the lifespan of NGSI. During the development process, it was necessary to build a SPARK training dataset (a corpus of documents) for initial entry into the system and for demonstration purposes. We manipulated these data to gain new information about the breadth of NGSI publications, and they evaluated the science-policy interface at PNNL as a practical demonstration of SPARK’s intended analysis capability. The analysis demonstration sought to answer the question, “Who leads research and development at PNNL, scientists or policy researchers?” The analysis was inconclusive as to whether policy researchers or scientists are primary drivers for research at PNNL. However, the dataset development and analysis activity did demonstrate the utility and usability of the SPARK dataset. After the initiation of the NGSI program there is a clear increase in the number of publications of safeguards products. Employing the natural language analysis tool IN SPIRE™ showed the presence of vocation- and topic-specific vernacular within NGSI sub-topics. The methodology developed to define the scope of the dataset was useful in describing safeguards applications, but may be applicable for research on other topics beyond safeguards. The analysis emphasized the need for an expanded dataset to fully understand the scope of safeguards publications and research both nationally and internationally. As the SPARK dataset grows to include publications outside PNNL, topics crosscutting disciplines and DOE/NNSA locations should become more apparent. NGSI was established in 2008 to cultivate the next generation of safeguards professionals and support the development of core safeguards capabilities (NNSA 2012). Now a robust system to preserve and share institutional memory such as SPARK is needed to inspire and equip the next generation of safeguards experts, technologies, and policies.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2017

Open V2X at ESIF: June 2015 - February 2017 (Final Report)

The University of Delaware (UD), and their industrial partners, have carried out testing, documentation, and standards development at ESIF. These activities are intended to help meet the objective of NREL's INTEGRATE program, to enable clean energy technologies to increase the hosting capacity of the grid, by providing grid services in a holistic manner using an open source, interoperable platform. In particular, the 'Open V2X at ESIF' project worked to facilitate standardization and interoperability for Electric Vehicle technologies, including battery electric vehicles and plug-in hybrid vehicles (hence EV) to provide grid services. This was done by interconnecting and testing EV and EVSE (charging station) hardware from different manufacturers, by developing standards and test protocols for standards, and by documenting new protocols to be proposed as standards. Contractor-supplied equipment used in the testing included Vehicle Smart Links (VSLs) installed in an EV and School Bus, single-phase and three-phase charging stations, and an optimizing aggregator (software running on a server, hence just 'Aggregator'). The Aggregator software was developed by U of Delaware and is now licensed to Nuvve Corp for commercial development, and licensed to NRG/EVgo for demonstrations. The Aggregator monitors capacity and operations of the EVs and EVSEs, dispatches them in response to requests, and reports their operations and metered power flow. In operation, as vehicles move, plug-in and unplug, the aggregator tracks the total capacity available within a defined jurisdiction or RTO (Regional Transmission Organization, synonym for ISO or TSO), and dispatches part or all of that capacity based on market or direct dispatch signals from a grid entity. The VSL is the data acquisition and control module in the resource itself (EVSE or EV), with rich communication between a single Optimizing Aggregator and many VSL (one in each resource). All requests and dispatch events are also logged by the aggregator to make the provision of grid power auditable. For these tests, the dispatch was typically a recorded signal, the VSL was in the EV or EVSE, and the recording of experimental performance was often carried out by the normal logging functions of the aggregator.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2019

Orbital Debris Ontology, Terminology, and Knowledge Modeling

The looming threat orbital debris poses to assets in orbit demands solutions. As the orbital population grows, so does this hazard, but so does the sea of data. The problem is also an opportunity for interdisciplinary innovation and cooperation. This paper focuses on the data and information management aspect of developing solutions for a sustainable and safe orbital space environment. The corresponding author’s in-progress work to develop an orbital debris domain ontology is summarized in order to discuss knowledge modeling for this domain. Methodological approaches of this effort can also contribute to standards efforts and address terminological and policy questions. Leveraging the growing volumes of orbital debris and space situational awareness (SSA) data will create a more complete picture of the orbital space environment. Part of the solution will be: consistent and correct data interpretation, sharing orbital debris and SSA data in one form or another, terminology development & harmonization, and knowledge or domain modeling. To facilitate this, [Rovetto, 2015/16] discussed ontology development for the orbital debris domain. This paper lists concepts from that paper, and subsequently developed concepts [2-9]. Ontology engineering is an interdisciplinary field related to knowledge representation and reasoning in artificial intelligence, semantic technologies and the so-called semantic web. An ontology is effectively a computable and semantically rich terminology that presents a knowledge or domain model for a topic area. Expressions of knowledge or assertions are stored using formally defined term. This knowledge base is reasoned over to yield answers to queries, among other things. Ontologies have been developed in knowledge-based projects across various disciplines, and used for such things as search engines, chatbots, enterprise knowledge graphs, etc. Ontologies support: interoperability, automated reasoning, data sharing and integration, data search and retrieval, and communicating the meaning of data. The Orbital Debris Ontology (ODO), and related ontologies [Rovetto & Kelso 2016] [Rovetto 2016, 2017], were proposed to help achieve this. ODO, for instance, is intended as a domain ontology that can be used across federated databases, offering an explicitly specified set of concepts describing the orbital debris domain. Its meaning-rich taxonomy will provide a sharable semantics for orbital debris data to, in part, consistently communicate the meaning of data to both humans and machines, and tag data elements in space object catalogs to help afford inference tasks, decision support, knowledge discovery, and information integration. ODO and the SSA ontology (SSAO) is part of the overall Orbital Space Domain Ontology concept, which is conceived as a broader domain reference ontology. It aims to provide a knowledge representation structure of the orbital space environment, a common semantic model, and develop a sharable terminology. Collectively this will provide common meaning for datasets, a high-level taxonomy or classification for orbital space objects, and thus means to characterize space objects. Ongoing efforts have included using visualizations, R, JSON-LD, and contemporary semantic technologies. Potential applications and interdisciplinary partnerships include web-based platforms, web apps, visualizations, and academia projects. Community input and participation may yield a more widely understood domain model as well as facilitate terminological standards. For example, the proposed conceptual, terminological and ontological analysis may contribute to such efforts as the Space Debris Mitigation Requirements in the International Standards Organization by developing more precise, consistent and coherent terms and definitions. Projects that seek to develop in-house ontologies can use ODO and related ontologies as domain reference ontologies. This paper was developed independent of author affiliations. Readers are encouraged to contact corresponding author(1) with general interest and potential opportunities to support or realize the described project.

Robert J. Rovetto↗
DOE OSTI2019

R and DE Robotic Sensor Intern Team: Sensor Suite Mock Up Testing

Assess sensor suite performance: - Mounted on crawler typical to what would be used in tunnel; - In test bed simulating the tunnel environment. The SuperDroid fiber tethered LT-F crawler is a general-purpose surveillance robot that our team has refurbished as a testing platform for the sensor suite. This crawler was selected because its dimensions are similar to the actual crawler that will be deployed in the field. Crawler preparation included: - Communicating with vendor to resolve software and platform issues; - Configuring a laptop with the crawler control software; - Reconfiguration of communication protocol between computer and crawler; - Resolution of control board checksum errors; - Installation of a mounting fixture on the base; - In progress: addition of lighting needed for total darkness. A solution for hosting the selected sensors onto a single unit that could function standalone or be mounted on the crawler was needed. Sensor mount requirements included: - Host Lidar, panospheric cameras and IMU sensors; - Cable management for rotating Lidar; - House on-board crawler computer; - Method for affixing to crawler; - Robust and vibration proof. The Lidar sensor required a sturdy mount that ensured the axis of rotation be centered with the LiDAR's desired laser path and included a slender profile in order to not block the scanning FOV. The mounting plate holds two 180-degree cameras on either side and the servo on the center. The servo mount is located so the axis of rotation is in the center of the plate. The mount features a set of guides that hold the wires and ensure they wrap around the spool area properly. The sensor box design features thick walls for added strength, holes for mounting the sensor suite to the crawler, notches on the bottom for the different components and holes for cable routing and management. The sensor mounts were designed using CREO and printed in the R and DE Additive Manufacturing Lab. To test the performance of the sensor suite for our application it was desired to design and build a test bed simulating the H-Canyon tunnel environment. Requirements included: - Dimensions similar to the tunnel; - Wall surfaces simulating the eroded tunnel walls; - Complete darkness; - Even and uneven crawler path; - Ability to change the tunnel width to simulate erosion. The HCAEX tunnel changes in height and includes several bends ranging from approximately 30 to 80 degrees, for that reason a test bed capable of easily being changed was needed. The final design includes two sections that can be connected to provide a 16' tunnel or placed at an angle to create a tunnel bend. The test bed features caster wheels for easy movement and has a sliding inner wall that enables tunnel width to be controlled. In order to simulate the tunnel walls without adding a lot of weight to the test bed, sheets of faux stone are to be used on the inner walls. To create a completely dark tunnel, 100% black-out film will be draped over the tunnel structure. Carpet remnants in the lab will enable folds to be introduced in the floor to generate uneven surface data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2004

Evaluation of Open-Source Hard Real Time Software Packages

Reliable software is, at times, hard to find. No piece of software can be guaranteed to work in every situation that may arise during its use here at Glenn Research Center or in space. The job of the Software Assurance (SA) group in the Risk Management Office is to rigorously test the software in an effort to ensure it matches the contract specifications. In some cases the SA team also researches new alternatives for selected software packages. This testing and research is an integral part of the department of Safety and Mission Assurance. Real Time operation in reference to a computer system is a particular style of handing the timing and manner with which inputs and outputs are handled. A real time system executes these commands and appropriate processing within a defined timing constraint. Within this definition there are two other classifications of real time systems: hard and soft. A soft real time system is one in which if the particular timing constraints are not rigidly met there will be no critical results. On the other hand, a hard real time system is one in which if the timing constraints are not met the results could be catastrophic. An example of a soft real time system is a DVD decoder. If the particular piece of data from the input is not decoded and displayed to the screen at exactly the correct moment nothing critical will become of it, the user may not even notice it. However, a hard real time system is needed to control the timing of fuel injections or steering on the Space Shuttle; a delay of even a fraction of a second could be catastrophic in such a complex system. The current real time system employed by most NASA projects is Wind River's VxWorks operating system. This is a proprietary operating system that can be configured to work with many of NASA s needs and it provides very accurate and reliable hard real time performance. The down side is that since it is a proprietary operating system it is also costly to implement. The prospect of replacing this somewhat costly implementation is the focus of one of the SA group s current research projects. The explosion of open source software in the last ten years has led to the development of a multitude of software solutions which were once only produced by major corporations. The benefits of these open projects include faster release and bug patching cycles as well as inexpensive if not free software solutions. The main packages for hard real time solutions under Linux are Real Time Application Interface (RTAI) and two varieties of Real Time Linux (RTL), RTLFree and RTLPro. During my time here at NASA I have been testing various hard real time solutions operating as layers on the Linux Operating System. All testing is being run on an Intel SBC 2590 which is a common embedded hardware platform. The test plan was provided to me by the Software Assurance group at the start of my internship and my job has been to test the systems by developing and executing the test cases on the hardware. These tests are constructed so that the Software Assurance group can get hard test data for a comparison between the open source and proprietary implementations of hard real time solutions.

Mattei, Nicholas S.↗