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[Interview]: Alexandre Shvartsburg, Pacific Northwest National Laboratory, Richland, WA, USA

Q1. What are your main research activities in ion mobility mass spectrometry (past or present)? My early efforts focused on the structural characterization of atomic (carbon and semiconductor) clusters. After the production of bulk fullerenes, many hoped that other nanoclusters discovered in the gas phase could also coalesce into new materials. As these studies required accurate and robust mobility calculations for any ion geometry, I strived to build the needed theory and implement it in the Mobcal software widely employed today. Since 2004, I have been developing methods and novel applications of differential IMS (FAIMS) at PNNL. The principal achievement has been raising the resolving power by over tenfold (up to ~400 for multiply-charged peptides) using elevated fields, helium and hydrogen-rich buffers, and extended filtering times. This performance broadly allows previously unthinkable separations of very similar species, for example sequence inversions and post-translational modification localization isomers of peptides (including “middle-down” peptides such as histone tails), lipid regioisomers, and even isotopomers. Another major direction is investigating the dipole alignment of larger proteins, which creates an exceptionally strong FAIMS effect that is a potential tool for structural biology. Q2: What have been the most significant instrumentation or applications developments in the history of ion mobility - mass spectrometry? In 1995 when I started graduate research at Northwestern, only two groups worldwide worked with IMS/MS and “the literature” meant papers by Bowers (UCSB). Well-wishers counseled me to “learn something useful like HPLC, as IMS would never have real utility”. This booklet showcases the scale of change since. First, the practical IMS/ToF platforms for complex biological analyses demonstrated by Clemmer have turned IMS/MS from an esoteric physical chemistry technique into a powerful analytical tool. By commercializing the IMS/ToF technology in Synapt instruments, Waters has greatly increased its impact via expanded number and diversity of applications. Concurrently, Guevremont at Canadian NRC has perfected FAIMS coupled to MS, deployed it for real-world bio and environmental analyses, and widely distributed it in the Ionalytics Selectra system (subsequently installed on Thermo MS platforms). The latest breakthrough is ultra-FAIMS by Owlstone, where extreme fields allow numerous qualitatively new separations and operational modes that we just begin to explore. Q3: Where do you see ion mobility - mass spectrometry making the most impact in the next 5 years? Any predictions for where the field will go? Sciences dealing with perturbations in media (such as optics or acoustics) at some point shift from the linear to nonlinear paradigm, where propagation depends on the magnitude of perturbation or its driving force. While the linear part remains industrially important (e.g., eyewear and architectural glass for optics), frontline research moves to nonlinear phenomena. IMS is undergoing that transition now with the rise of FAIMS, which should continue as the fundamental understanding improves, new modalities and applications emerge, and more instrumentation is introduced by vendors. Modifying and augmenting FAIMS separations through vapor dopants that render ion mobilities less linear is becoming routine. I expect this area to advance, extending to more specific interactions and to complexation with solution additives. Another route to higher separation power is integrating FAIMS with conventional IMS; proliferation of both technologies would make such 2-D platforms common. Along with mass spectrometry and conventional IMS, FAIMS will address increasingly large macromolecules, including proteins and their complexes.

Shvartsburg, Alexandre A.↗

The Psyche Gamma-Ray and Neutron Spectrometer

A Gamma-Ray and Neutron Spectrometer (GRNS) instrument has been developed as part of the science payload for NASA’s Discovery Program Psyche mission to the M-class asteroid (16) Psyche. The GRNS instrument is designed to measure the elemental composition of Psyche with the goal to understand the origin of this mysterious, potentially metal-rich planetary body. The GRNS will measure the near-surface abundances for the elements Ni, Fe, Si, K, S, Al, and Ca, as well as the spatial distribution of Psyche’s metal-to-silicate fraction (or metal fraction). These measurements address three of the five Psyche mission science objectives: determine if Psyche is a core; determine whether small metal bodies incorporate light elements into the metal phase; and determine whether Psyche was formed under reducing conditions. The Gamma-Ray Spectrometer (GRS) uses a cryocooled, high-purity Ge (HPGe) sensor to detect cosmic-ray generated gamma rays in the 60 to 9000-keV energy range. The HPGe sensor is surrounded by a borated plastic anticoincidence shield that provides three functions: active background rejection from charged particle interactions in the HPGe sensor; fast neutron measurements; and direct measurements of the incident galactic cosmic ray flux. The Neutron Spectrometer (NS) uses three 3 He gas proportional sensors, each with different material wraps to measure thermal (<0.4 eV), low-energy epithermal (0.4 eV to 1 keV), and high-energy epithermal (up to 100 keV) neutrons. This paper provides an overview of the Psyche GRNS, including: its science and measurement objectives; the design of the instrument hardware, software, and operation; pre-launch performance measurements and its initial performance in space; and an overview of its data products and expected operation for different Psyche mission phases.

Engineering - Instrumentation related to nuclear s↗

Patient-Specific Monte Carlo-Based Dose-Kernel Approach for Inverse Planning in Afterloading Brachytherapy

Purpose: Brachytherapy planning software relies on the Task Group report 43 dosimetry formalism. This formalism, based on a water approximation, neglects various heterogeneous materials present during treatment. Various studies have suggested that these heterogeneities should be taken into account to improve the treatment quality. The present study sought to demonstrate the feasibility of incorporating Monte Carlo (MC) dosimetry within an inverse planning algorithm to improve the dose conformity and increase the treatment quality. Methods and Materials: The method was based on precalculated dose kernels in full patient geometries, representing the dose distribution of a brachytherapy source at a single dwell position using MC simulations and the Geant4 toolkit. These dose kernels are used by the inverse planning by simulated annealing tool to produce a fast MC-based plan. A test was performed for an interstitial brachytherapy breast treatment using two different high-dose-rate brachytherapy sources: the microSelectron iridium-192 source and the electronic brachytherapy source Axxent operating at 50 kVp. Results: A research version of the inverse planning by simulated annealing algorithm was combined with MC to provide a method to fully account for the heterogeneities in dose optimization, using the MC method. The effect of the water approximation was found to depend on photon energy, with greater dose attenuation for the lower energies of the Axxent source compared with iridium-192. For the latter, an underdosage of 5.1% for the dose received by 90% of the clinical target volume was found. Conclusion: A new method to optimize afterloading brachytherapy plans that uses MC dosimetric information was developed. Including computed tomography-based information in MC dosimetry in the inverse planning process was shown to take into account the full range of scatter and heterogeneity conditions. This led to significant dose differences compared with the Task Group report 43 approach for the Axxent source.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Ocean Thermal Extractable Energy Visualization (Final Technical Report)

The Ocean Thermal Extractable Energy Visualization (OTEEV) project focuses on assessing the Maximum Practicably Extractable Energy (MPEE) from the world's ocean thermal resources. MPEE is defined as being sustainable and technically feasible, given today's state-of-the-art ocean energy technology. Under this project the OTEEV team developed a comprehensive Geospatial Information System (GIS) dataset and software tool, and used the tool to provide a meaningful assessment of MPEE from the global and domestic U.S. ocean thermal resources. The OTEEV project leverages existing NREL renewable energy GIS technologies and integrates extractable energy estimated from quality-controlled data and projected optimal achievable energy conversion rates. Input data are synthesized from a broad range of existing in-situ measurements and ground-truthed numerical models with temporal and spatial resolutions sufficient to reflect the local resource. Energy production rates are calculated for regions based on conversion rates estimated for current technology, local energy density of the resource, and sustainable resource extraction. Plant spacing and maximum production rates are then estimated based on a default plant size and transmission mechanisms. The resulting data are organized, displayed, and accessed using a multi-layered GIS mapping tool, http://maps.nrel.gov/mhk_atlas with a user-friendly graphical user interface.

14 SOLAR ENERGY↗

IoT-Based Comfort Control and Fault Diagnostics System for Energy-Efficient Homes

This project studies an Internet of Things (IoT)-based comfort control and fault diagnostics system (referred as iComfort in this report) for energy-efficient homes. The system delivers an occupant-comfort-oriented thermal environment adaptive to fault scenarios and achieves HVAC energy savings in a cost-effective and straightforward way. This smart iComfort home system consists of the following key features. 1) Cost-effectiveness and scalability of the entire hardware and software system: The system includes low-cost temperature, humidity, and airflow sensors, and a Raspberry Pi-based local hub that interfaces with the cloud and IoT-enabled devices. The cost is low, not only for sensors, but also the costs associated with sensor installation, system setup and commissioning, data communication and storage, and data analytics (e.g., the development of automated fault detection and diagnosis (AFDD), as well as adaptive control strategies that are both computationally efficient and practical to implement). 2) Energy performance and user satisfaction: The system delivers user satisfaction and energy savings. This includes a) ease of use, b) optimal occupant thermal comfort, and c) accurate system feedback (e.g., low false alarm of AFDD strategies). 3) Favorable demonstrated prototype performance: The prototype tested at the Pacific Northwest National Laboratory (PNNL) Lab Homes demonstrates the accuracy of fault detections and diagnoses and shows thermal comfort improvement and energy savings through adaptive and optimal HVAC operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SAPHIRE 8 Volume 2 - Technical Reference

The Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) refers to a set of computer programs that were developed to create and analyze probabilistic risk assessment (PRAs). Herein information is provided on the principles used in the construction and operation of Version 8.0 of the SAPHIRE system. This report summarizes the fundamental mathematical concepts of sets and logic, fault trees, and probability. This volume then describes the algorithms used to construct a fault tree and to obtain the minimal cut sets. It gives the formulas used to obtain the probability of the top event from the minimal cut sets, and the formulas for probabilities that apply for various assumptions concerning reparability and mission time. It defines the measures of basic event importance that SAPHIRE can calculate. This volume gives an overview of uncertainty analysis using simple Monte Carlo sampling or Latin Hypercube sampling, and states the algorithms used by this program to generate random basic event probabilities from various distributions. Also covered are enhance capabilities such as seismic analysis, Workspace algorithms, cut set "recovery," end state manipulation, and use of "compound events."

97 MATHEMATICS AND COMPUTING↗

Implementations and Evaluations of Wind Turbine Inertial Controls With FAST and Digital Real-Time Simulations

This paper presents a novel simulation approach to evaluate new ancillary service controls in the context of large-scale wind power integration. We adopt and compare different types of turbine inertial control methods with the proposed modifications to cope with realistic wind conditions in the field. The simulation procedure is started with the software-based simulation, in which we employ the high-fidelity wind turbine simulator FAST that models a real three-bladed controls advanced research turbine (CART3). The advantages of using FAST are that it can provide convincing simulation results and address the interactions between turbine electrical and mechanical systems. The developed controller model is then rapidly prototyped for the real-time simulation with the hardware-in-the-loop scheme. CART3 will respond to a virtual frequency event triggered in the emulated electric grid modeled in a digital real-time simulator. The introduced simulation platform streamlines the procedure of designing turbine auxiliary controls, and these simulations results give insights on the turbine controls and their impacts on the interconnected power system, as well as the effects on turbine mechanical components. For example, the results indicate that the inertial controls tend to reduce the out-of-plane mechanical loadings in region 2, while such loadings are dominated by the pitch actions in region 3.

17 WIND ENERGY↗

Mapping Benthic Habitat Conditions and Seafloor Deposits using Sediment Profile Imaging and a Semiautomated Image Processing System

Objectives/Scope: Sediment profile imaging (SPI) technology characterizes in situ physical, geochemical, and biological seafloor features. SPI was required by Mexico’s Agency for Safety, Energy, and Environment in 2017 for environmental baseline surveys (EBS) of oil lease blocks in the southern Gulf of Mexico. Because of its ability to provide information on benthic community health and the distribution of very thin (down to the centimeter scale) layers of deposited materials, SPI technology is highly effective for mapping drill cuttings or drilling muds released around wellheads during exploration or production and documenting their ecological impacts. SPI technology has not been widely used in the oil and gas industry for EBS or other monitoring activities. A primary objective of this work is to improve the transparency and consistency of the SPI data generation and data management process. Methods, Procedures, Process: The SPI camera works like an inverted periscope and obtains an undisturbed 21x15-cm cross-sectional image of the upper sediment column. The camera is internally powered and can be deployed rapidly from a standard winch in depths to 4,000 m. Many stations can be sampled in a single day by “pogo-sticking” across a survey area. Sediment grain size, penetration depth, surface boundary roughness, natural and anthropogenic depositional layers, depth of the oxidized surface sediment layer, maximum biogenic mixing depth, and infaunal successional stage can be directly measured at sea or immediately following the cruise. Final SPI data sets can be provided within a few weeks of the survey. Results, Observations, Conclusions: Details on the features measured in SPI images and the underlying interpretive paradigms are presented. To standardize the SPI data generation process, Integral Consulting Inc. has developed 1) a semiautomated image analysis platform, and 2) a SPI data-specific database architecture that allows both numerical and non-numerical metrics to be incorporated into a standard database structure. An integrated, software-based SPI analysis platform has been developed that imports image files and metadata and provides a graphical user interface. The software automatically stores the data, which can then be reviewed for quality assurance, plotted, statistically analyzed, and mapped or exported to other platforms (e.g., Esri ArcGIS©) for further evaluation. Image processing algorithms have been developed using a combination of open-source and commercially available software packages (e.g., MATLAB® and OpenCV) to automatically quantify key parameters. Novel/Additive Information: SPI technology’s underutilization in the oil and gas industry may be in part due to a lack of standardization in the measurement of basic features in SPI images. A primary objective of this work is to develop a streamlined, standardized, and transparent process for generating and managing SPI data.

02 PETROLEUM↗

Learning Global Proliferation Expertise Evolution Using AI-Driven Analytics and Public Information

Detecting and anticipating global proliferation expertise and capability evolution from unstructured, noisy, and incomplete public data streams is a highly desired, but extremely challenging task. Here, in this article, we present our pioneering data-driven approach to support the non-proliferation mission to detect and explain the evolution of proliferation expertise and capability development globally from terabytes of publicly available information (PAI), focusing on our knowledge extraction pipeline and descriptive analytics. We first discuss how we fuse nine open-source data streams, including multilingual data, to convert 4 TB of unstructured data to structured knowledge and encode dynamically evolving proliferation expertise representations—content and context graphs. For this, we rely on natural language processing (NLP) and deep learning (DL) models to perform information extraction, topic modeling, and distributed text representation (aka embedding) learning. We then present interactive, usable, and explainable descriptive analytics to refine domain knowledge and present it in a human-understandable form. Finally, we introduce future work avenues that will leverage our dynamic knowledge representations and descriptive analytics to enable predictive and prescriptive inferences to achieve real-time domain understanding and contextual reasoning about global proliferation expertise and capability evolution.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Poster — Thur Eve — 46: Monte Carlo model of the Novalis Classic 6MV stereotactic linear accelerator using the GATE simulation platform

Monte Carlo (MC) simulation is accepted as the most accurate method to predict dose deposition when compared to other methods in radiation treatment planning. Current dose calculation algorithms used for treatment planning can become inaccurate when small radiation fields and tissue inhomogeneities are present. At our centre the Novalis Classic linear accelerator (linac) is used for Stereotactic Radiosurgery (SRS). The first MC model to date of the Novalis Classic linac was developed at our centre using the Geant4 Application for Tomographic Emission (GATE) simulation platform. GATE is relatively new, open source MC software built from CERN's Geometry and Tracking 4 (Geant4) toolkit. The linac geometry was modeled using manufacturer specifications, as well as in-house measurements of the micro MLC's. Among multiple model parameters, the initial electron beam was adjusted so that calculated depth dose curves agreed with measured values. Simulations were run on the European Grid Infrastructure through GateLab. Simulation time is approximately 8 hours on GateLab for a complete head model simulation to acquire a phase space file. Current results have a majority of points within 3% of the measured dose values for square field sizes ranging from 6×6 mm{sup 2} to 98×98 mm{sup 2} (maximum field size on the Novalis Classic linac) at 100 cm SSD. The x-ray spectrum was determined from the MC data as well. The model provides an investigation into GATE'S capabilities and has the potential to be used as a research tool and an independent dose calculation engine for clinical treatment plans.

60 APPLIED LIFE SCIENCES↗

A Mobile Automated Tomographic Gamma Scanning System - 13231

Canberra Industries have recently designed and built a new automated Tomographic Gamma Scanning (TGS) system for mobile deployment. The TGS technique combines high-resolution gamma spectroscopy with low spatial resolution 3-dimensional image reconstruction to provide increased accuracy over traditional approaches for the assay of non-uniform source distributions in low-to medium-density, non-heterogeneous matrices. Originally pioneered by R. Estep at Los Alamos National Laboratory (LANL), the TGS method has been further developed and commercialized by Canberra Industries in recent years. The present system advances the state of the art on several fronts: it is designed to be housed in a standard cargo transport container for ease of transport, allowing waste characterization at multiple facilities under the purview of a single operator. Conveyor feed, drum rotator, and detector and collimator positioning mechanisms operated by programmable logic control (PLC) allow automated batch mode operation. The variable geometry settings can accommodate a wide range of waste packaging, including but not limited to standard 220 liter drums, 380 liter overpack drums, and smaller 20 liter cans. A 20 mCi Eu-152 transmission source provides attenuation corrections for drum matrices up to 1 g/cm{sup 3} in TGS mode; the system can be operated in Segmented Gamma Scanning (SGS) mode to measure higher density drums. To support TGS assays at higher densities, the source shield is sufficient to house an alternate Co-60 transmission source of higher activity, up to 250 mCi. An automated shutter and attenuator assembly is provided for operating the system with a dual intensity transmission source. The system's 1500 kg capacity rotator turntable can handle heavy containers such as concrete lined 380 liter overpack drums. Finally, data acquisition utilizes Canberra's Broad Energy Germanium (BEGE) detector and Lynx MCA, with 32 k channels, providing better than 0.1 keV/channel resolution to support both isotopic analysis with the MGA/MGAU software and a wide 3 MeV dynamic range. The calibration and verification of the system is discussed, and quantitative results are presented for a variety of drum types and matrices. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NBIC Biofeeds: A Digital Tool for Open Source Biosurveillance across Federal Agencies

The National Biosurveillance Integration Center (NBIC) is developing a scalable, flexible open source data collection, analysis, and dissemination tool to support biosurveillance operations by the U.S. Department of Homeland Security (DHS) and its federal interagency partners. The NBIC integrates, analyzes, and distributes key information about health and disease events to help ensure the nation’s responses are well-informed, save lives, and minimize economic impact. NBIC serves as a bridge between Federal, State, Local, Territorial, and Tribal entities to conduct biosurveillance across human, animal, plant, and environmental domains. The integration of information enables early warning and shared situational awareness of biological events to inform critical decisions directing response and recovery efforts. To meet its mission objectives, NBIC utilizes a variety of datasets, including open source information, to provide comprehensive coverage of biological events occurring across the globe. NBIC Biofeeds is a digital tool designed to improve the efficiency of reviewing and analyzing large volumes of open source reporting by biosurveillance analysts on a daily basis; moreover, the system provides a mechanism to disseminate tailored feeds allowing NBIC to better meet the specific information needs of individual, interagency partners. The tool is currently under development by the Department of Energy (DOE), Pacific Northwest National Laboratory (PNNL)and it is in a testing and evaluation phase supported by NBIC biosurveillance subject matter experts. Integration with the Defense Threat Reduction Agency (DTRA), Biosurveillance Ecosystem(BSVE) is also underway. NBIC Biofeeds Version 1 is expected to be fully operational in Fiscal Year 2017. The PNNL is applying agile methodology to streamline the build of NBIC Biofeeds to specifications required for operational use by NBIC and its federal interagency partners. Biosurveillance, analytics, and system engineering subject matter experts provide guidance on the implementation of features in the tool to ensure functionality aligns with operational workflows and production support. PNNL is leveraging software from a previous government effort to repurpose the technology to meet NBIC needs. NBIC Biofeeds incorporates the open source, document-orientated MongoDB database to capture user- and system-generated metadata on hundreds of thousands of records, in part, to establish baselines to aid prospective and retrospective analysis on emerging biological events. NBIC Biofeeds integrates a biosurveillance taxonomy (uniquely developed by NBIC),which includes input from interagency partners to recognize critical characteristics of a biological event. In NBIC Biofeeds Version1, metadata capture of reported events is done manually by NBIC analysts; however, moving forward in Version 2, the tool will be further automated to flag significant reporting on biological events with a human remaining in the loop to confirm the validity of the system-generated tags. To serve as a one-stop tool for open source biosurveillance, NBIC Biofeeds automatically harvests information from thousands of websites, utilizing third party aggregators, paid subscriptions to data feeds, and scraping of high priority sources. Users can develop desired queries for automatic updating, leverage a unique review and curation mechanism, and further analyze data from topical, geographic, and temporal visualization features in the tool. To meet NBIC’s information sharing needs, the tool allows for design of tailored RSS feeds and electronic message-based delivery of analysis on biological events, intended for recipients in the government with unique missions around human, animal, plant, and environmental health. Through current testing and evaluation – underway by biosurveillance subject matter experts – NBIC Biofeeds is demonstrating value in supporting open source biosurveillance by the Center for more rapid recognition and sharing of key event characteristics. Centralizing access and analysis of this data set into a single system is increasing the efficiency of daily, global biosurveillance, while enhancing the value of information identified through use of the querying, curation, and production support features in the tool.

59 BASIC BIOLOGICAL SCIENCES↗

Phase II Nevada Water Resources Data, Modeling, and Visualization (DMV) Center (Final Report)

Water is unquestionably a critical resource throughout the United States. In the semi-arid west -- an area stressed by increase in human population and sprawl of the built environment -- water is the most important limiting resource. Crucially, science must understand factors that affect availability and distribution of water. To sustain growing consumptive demand, science needs to translate understanding into reliable and robust predictions of availability under weather conditions that could be average but might be extreme. These predictions are needed to support current and long-term planning. Similar to the role of weather forecast and climate prediction, water prediction over short and long temporal scales can contribute to resource strategy, governmental policy and municipal infrastructure decisions, which are arguably tied to the natural variability and unnatural change to climate. Change in seasonal and annual temperature, precipitation, snowmelt, and runoff affect the distribution of water over large temporal and spatial scales, which impact the risk of flooding and the groundwater recharge. Anthropogenic influences and impacts increase the complexity and urgency of the challenge. The goal of this project has been to develop a decision support framework of data acquisition, digital modeling, and 3D visualization. This integrated framework consists of tools for compiling, discovering and projecting our understanding of processes that control the availability and distribution of water. The framework is intended to support the analysis of the complex interactions between processes that affect water supply, from controlled availability to either scarcity or deluge. The developed framework enables DRI to promote excellence in water resource management, particularly within the Lake Tahoe basin. In principle, this framework could be replicated for other watersheds throughout the United States. Phase II of this project builds upon the research conducted during Phase I, in which the hydrologic framework was investigated and the development initiated. Phase II concentrates on practical implementation of the earlier work but emphasizes applications to the hydrology of the Lake Tahoe basin. Phase 1 efforts have been refined and extended by creating a toolset for geographic information systems (GIS) that is usable for disparate types of geospatial and geo-referenced data. The toolset is intended to serve multiple users for a variety of applications. The web portal for internet access to hydrologic and remotely sensed product data, prototyped in Phase I, has been significantly enhanced. The portal provides high performance access to LANDSAT-derived data using techniques developed during the course of the project. The portal is interactive, and supports the geo-referenced display of hydrologic information derived from remotely sensed data, such as various vegetative indices used to calculate water consumption. The platform can serve both internal and external constituencies using inter-operating infrastructure that spans both sides of the DRI firewall. The platform is intended grow its supported data assets and to serve as a template for replication to other geographic areas. An unanticipated development during the project was the use of ArcGIS software on a new computer system, called the IBM PureSytems, and the parallel use of the systems for faster, more efficient image processing. Additional data, independent of the portal, was collected within the Sagehen basin and provides detailed information regarding the processes that control hydrologic responses within mountain watersheds. The newly collected data include elevation, evapotranspiration, energy balance and remotely sensed snow-pack data. A Lake Tahoe basin hydrologic model has been developed, in part to help predict the hydrologic impacts of climate change. The model couples both the surface and subsurface hydrology, with the two components having been independently calibrated. Results from the coupled simulations involving both surface water and groundwater processes show that it is possible to fairly accurately simulate lake effects and water budget variables over a wide range of dry and wet cycles in the historical record. The Lake Tahoe basin is representative of the hydrology, topography and climate throughout the Sierra Nevada Range, and the entire model development is prototypical of the efforts required to replicate the decision support framework to other locales. The Lake Tahoe model in particular, could allow water managers to evaluate more accurately components of the water budget (ET, runoff, groundwater, etc) and to answer important questions regarding water resources in northern Nevada. This report discusses the geographic scale and the hydrologic complexity of the calibrated model developed as part of this project, as well as simulation results for historical and future climate projects To enable human-driven data exploration and discovery, de novo software for a globalized rendering module that extends the capability of our evolving custom visualization engine from Phase I (called SMEngine) has been developed. The new rendering component, called Horizon, supports terrain rendering capable of displaying and interrogating both remotely sensed and modeled data. The development of Horizon necessitated adaptation of the visualization engine to allow extensible integration of components such as the global rendering module and support for associated features. The resulting software is general in its GIS capability, but a specific Lake Tahoe visualization application suitable for immersive decision support in the DRIVE6 virtual reality facility has been developed. During the development, various features to enhance the value of the visualization experience were explored, including the use of hyperspectral image overlays. An over-arching goal of the visualization aspect of the project has been to develop and demonstrate the CAVE (CAVE Automatic Virtual Environment) as a practical tool for hydrologic research.

54 ENVIRONMENTAL SCIENCES↗

TU-CD-BRA-11: Application of Bone Suppression Technique to Inspiratory/expiratory Chest Radiography

Purpose: The bone suppression technique based on advanced image processing can suppress the conspicuity of bones on chest radiographs, creating soft tissue images normally obtained by the dual-energy subtraction technique. This study was performed to investigate the usefulness of bone suppression technique in quantitative analysis of pulmonary function in inspiratory/expiratory chest radiography. Methods: Commercial bone suppression image processing software (ClearRead; Riverain Technologies) was applied to paired inspiratory/expiratory chest radiographs of 107 patients (normal, 33; abnormal, 74) to create corresponding bone suppression images. The abnormal subjects had been diagnosed with pulmonary diseases, such as pneumothorax, pneumonia, emphysema, asthma, and lung cancer. After recognition of the lung area, the vectors of respiratory displacement were measured in all local lung areas using a cross-correlation technique. The measured displacement in each area was visualized as displacement color maps. The distribution pattern of respiratory displacement was assessed by comparison with the findings of lung scintigraphy. Results: Respiratory displacement of pulmonary markings (soft tissues) was able to be quantified separately from the rib movements on bone suppression images. The resulting displacement map showed a left-right symmetric distribution increasing from the lung apex to the bottom region of the lung in many cases. However, patients with ventilatory impairments showed a nonuniform distribution caused by decreased displacement of pulmonary markings, which were confirmed to correspond to area with ventilatory impairments found on the lung scintigrams. Conclusion: The bone suppression technique was useful for quantitative analysis of respiratory displacement of pulmonary markings without any interruption of the rib shadows. Abnormal areas could be detected as decreased displacement of pulmonary markings. Inspiratory/expiratory chest radiography combined with the bone suppression technique has potential for predicting local lung function on the basis of dynamic analysis of pulmonary markings. This work was partially supported by Nakatani Foundation, Grant-in-aid for Scientific Research (C) of Ministry of Education, Culture, Sports, Science and Technology, JAPAN (Grant number : 24601007), and Nakatani Foundation, Mitsubishi Foundation, and the he Mitani Foundation for Research and Development. Yasushi Kishitani is a staff of TOYO corporation.

60 APPLIED LIFE SCIENCES↗

Immersive Digital Twin Laboratory for Engineering Education (CRADA Final Report)

This project aimed to create an immersive digital twin laboratory that incorporates advanced tracking and visualization capabilities. In collaboration with Fort Lewis College, NREL designed a state-of-the-art physical visualization laboratory, developed a software platform to enable interaction with tracked physical objects in the laboratory, and provided proof-of-concept curricula that included manipulating these tracked objects. The project was initiated to address the growing need for innovative educational tools in engineering education. As renewable energy systems, particularly solar installations, become more complex, there is a pressing need to bridge the gap between theoretical knowledge and practical application. Traditional methods of teaching solar engineering concepts often fall short of providing students with a comprehensive, hands-on understanding. This immersive digital twin laboratory was conceived to fill that gap by creating a safe, non-energized setting where students can interact with augmented solar installation objects, gaining valuable insights into system performance, design, and maintenance. The project utilized extended reality (XR) technologies, including head-mounted displays (HMDs) and a whole-room optical motion tracking system, to connect physical objects with their digital twins in real time. The laboratory was equipped with MagicLeap 2 HMDs, supported by a Vicon Vero 2.2 Optical Tracking System, which provided precise 6-degrees-of-freedom (6-DOF) tracking. We developed a software platform to manage the interaction between the tracked physical objects and their virtual counterparts, enabling real-time data synchronization, object recognition, and virtual overlays. We designed the system to be flexible and extendable, allowing for future integration of additional objects and curriculum. This research advances the field of engineering education by demonstrating the potential of immersive digital twin environments. The laboratory provides a dynamic learning space where students can experiment, collaborate, and learn without the risks associated with live experimentation. The ability to simulate and manipulate solar installation objects under various conditions has broad implications for workforce development, particularly in renewable energy. The project also highlights the economic feasibility of using XR technologies in educational settings, offering a cost-effective solution for institutions looking to enhance their curriculum. By fostering a deeper understanding of solar energy systems, this work contributes to the broader goal of supporting the global energy transition and preparing the next generation of engineers and technicians.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cybersecurity for Electric Vehicle Charging Infrastructure

As the U.S. electrifies the transportation sector, cyberattacks targeting vehicle charging could impact several critical infrastructure sectors including power systems, manufacturing, medical services, and agriculture. This is a growing area of concern as charging stations increase power delivery capabilities and must communicate to authorize charging, sequence the charging process, and manage load (grid operators, vehicles, OEM vendors, charging network operators, etc.). The research challenges are numerous and complicated because there are many end users, stakeholders, and software and equipment vendors interests involved. Poorly implemented electric vehicle supply equipment (EVSE), electric vehicle (EV), or grid operator communication systems could be a significant risk to EV adoption because the political, social, and financial impact of cyberattacks — or public perception of such — would ripple across the industry and produce lasting effects. Unfortunately, there is currently no comprehensive EVSE cybersecurity approach and limited best practices have been adopted by the EV/EVSE industry. There is an incomplete industry understanding of the attack surface, interconnected assets, and unsecured inter faces. Comprehensive cybersecurity recommendations founded on sound research are necessary to secure EV charging infrastructure. This project provided the power, security, and automotive industry with a strong technical basis for securing this infrastructure by developing threat models, determining technology gaps, and identifying or developing effective countermeasures. Specifically, the team created a cybersecurity threat model and performed a technical risk assessment of EVSE assets across multiple manufacturers and vendors, so that automotive, charging, and utility stakeholders could better protect customers, vehicles, and power systems in the face of new cyber threats.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development of Application Function Blocks for Power-Hardware-in-the-Loop Testing of Grid-Connected Inverters: Preprint

Stability and accuracy of the PHIL platform has been a common problem and challenging issue for a long time, thus continuous efforts and research have been devoted to developing interface algorithms to improve upon this. Some of existing works exhibit promising solutions to compensate the errors in the PHIL platform. However, there is a need to harmonize various solutions into a standard framework that provides a general solution for various PHIL test beds and that can be reused with minimum modifications to avoid extra effort. A good way to do this is by using application function blocks (AFBs), which are model-based and can be developed as a standard library component, thus achieving satisfactory reusability and reconfigurability for various platforms. Since PHIL simulation has the flexibility of the software simulation, proper functions can be easily implemented in the digital real-time simulator (DRTS) to preprocess the reference signal before sending it to the power amplifier. Therefore, this paper aims to develop standard AFBs in DRTS for the PHIL interface to test grid-connected inverters. The PHIL interface algorithm is separated into five AFBs that will be presented in detail in this paper.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SEAS Communication Engine: An Extensible, Flexible Wrapper for Co-Simulation Agents

When modeling and analyzing the power grid and other large scale systems, researchers often express scenarios as optimization problems and feed them into advanced software solvers. In order to allow multiple solvers to communicate with each other and share data from different domains, the National Renewable Energy Laboratory (NREL) and associated Department of Energy (DOE) labs have developed a software framework called the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). HELICS allows cosimulation via a collection of client libraries for different languages that can be called from the appropriate optimization software. However, these client libraries do not provide a higher level of abstraction beyond reading and writing data off of the shared HELICS bus. In this paper, we describe a new software library called the SEAS Communication Engine that exposes a higher-level API for running cosimulation problems. The SEAS Engine provides a class-based abstraction on top of the Python HELICS client, in order to allow users to implement their domain-specific cosimulations without needing to interact with core HELICS primitives. This will make adoption of HELICS and cosimulation in general easier, by exposing a simpler API. In the second part of the paper, we validate our library on a collection of different simulation examples, including the canonical IEEE 13 Bus Feeder. Lastly, we demonstrate using the SEAS Engine to directly call domain-specific code written in the Julia programming language. Our hope is that this will serve as a template for easily calling software in different programming languages via the SEAS Engine, thereby avoiding code duplication and complexity.

co-simulation↗