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At least 1,783 records · Page 99

eSHIVA in IOTA: Experiment on Stochasticity in High Intensity Variable Accelerators

Nonlinear integrable optics, the basis of IOTA, is a very special form of Hamiltonian system, called completely integrable. The consequences are many, most importantly the absence of fixed points that are in one-to-one correspondence with (overlapping) resonances. This, in turn, does not limit the dynamic aperture and allows large amplitude dependent tune shifts without adverse effects. In fact, it helps significantly in alleviating issues with collective instabilities. We developed and tested different numerical methods to give a more complete picture of the dynamics of integrable and near-integrable nonlinear Hamiltonian systems consisting of motion of charged particles in electromagnetic fields. Comparison of the results allowed us to discern real phenomena from numerical artifacts and come up with conclusions that will facilitate pushing the intensity frontier in beam dynamics even further for the benefit of the accelerator community as a whole and society as the consequence of the science and technological advancements it will make possible. We concluded that, while novel structure preserving integrators would be ideal, symplectic methods under mild restrictions offer adequate invariant preservation. We especially highlighted the very good performance of the Stormer-Verlet method at low accuracy and a modified Lobatto method at high accuracy for the Integrable Optics Test Accelerator (IOTA). However, we showed that symplectic integrators are limited by numerically induced resonances, which make interpretation of some simulation results challenging. These limitations and workarounds have been addressed.The nonlinear integrable optics test accelerator IOTA at Fermilab -- a very special experimental accelerator designed to investigate nonlinear optics under severe space-charge conditions – has recently completed its construction and initial commissioning of the ring has begun. We report first, under 2 (a) below: the progress on the nonlinear tune-shift measurements for various values of the nonlinear strength potential and their comparison with theoretical expectations, thus benchmarking the nonlinear characteristics of the ring; then, under 2 (b) below: the progress on simulation and design of a gas-jet monitor to measure beam profile and in particular its diffusive halo, expected to develop during stochastic diffusion of large amplitude particles under nonlinear forces of the magnetic lattice and Coulomb space-charge. Since the development of a proton beam source in IOTA is delayed and to be completed only in the future pending financial support, the gas-jet monitor is planned for testing with real proton beams elsewhere at Fermilab (e.g. in the Main Injector or PIP-II source possibly). Once proton beams are available in IOTA, the understanding of the nonlinear properties of IOTA combined with the developed gas-jet monitor, will enable a thorough experimental analysis of nonlinear stochastic diffusion in IOTA nonlinear ring, and boosted by proper theoretical understanding of the same.

43 PARTICLE ACCELERATORS↗

Wildlife Management Plan for the Oak Ridge Reservation

This document outlines a plan for management of the wildlife resources on the US Department of Energy’s (DOE’s) Oak Ridge Reservation. Management includes wildlife population control through restoration of wildlife species; preservation, management, and enhancement of wildlife habitats; coordination of wildlife studies and characterization of areas, hunting, trapping, removal, and habitat manipulation; wildlife damage control; and law enforcement. Wildlife resources are divided into several categories, each with a specific set of objectives and procedures to attain the goals. These objectives are management of (1) wildlife habitats to ensure that all resident wildlife species exist on the Reservation in viable numbers; (2) focal species to promote healthy populations on designated land units; (3) game species for research, education, recreation, and public safety; (4) the Three Bend Scenic and Wildlife Management Refuge Area; (5) nuisance wildlife, including nonnative species, to achieve adequate population control for the maintenance of health and safety on the Reservation; (6) sensitive species (i.e., state or federally listed as Endangered, Threatened, Of Special Concern, or In Need of Management) through preservation and protection of both the species and habitats critical to the survival of those species; and (7) wildlife disease. Achievement of the objectives is a joint effort between Oak Ridge National Laboratory and the Tennessee Wildlife Resources Agency (TWRA) through agreements between DOE and the University of Tennessee (UT)-Battelle LLC, between TWRA and DOE, and between Tennessee Department of Environment and Conservation (TDEC) and DOE. Implementation of objectives is to be informed by leading-edge research and a strong collaborative approach between UT-Battelle and TWRA.

54 ENVIRONMENTAL SCIENCES↗

Status and Availability of OPTD, the Out-of-Pile Transient Database

The DOE Advanced Reactor Technology program has supported knowledge preservation efforts to recover and preserve fuel data from the US sodium cooled fast reactor (SFR) program. Databases have been established containing experimental data generated during the Integral Fast Reactor program (from in-pile experiments at EBR-II, FFTF, and TREAT) and during related outof-pile examinations of EBR-II-irradiated fuels. The information in these databases is essential to support further development and licensing activities for advanced fast reactor designs. OPTD, the Out-of-Pile Transient Database, is an organized, searchable archive of records describing out-ofpile furnace transient tests conducted on metallic fuels. It includes records of over 150 tests on irradiated fuel pins conducted in furnace apparatuses constructed in the Alpha-Gamma Hot Cell Facility at ANL. This report presents the content, functions, and accessibility of the Out-of-Pile Transient Database (OPTD). It describes the information presently available in the database, the web interface created to provide access to this information, the activities undertaken to build OPTD, and the enabling of online access to the database for DOE users. Plans for FY2021 and beyond are also included.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Preliminary Study of Potential Utilization of Triassic Rift Basins for Long-Term Carbon Sequestration

Triassic rift basins of the eastern United States present a potential option for long–term carbon dioxide (CO 2 ) sequestration. Exposed and buried basins are located near large point CO 2 sources. Because of their similar origins, comparable fill successions indicate a level of reproducibility that can be conveyed between basins. The thick rock successions of the exposed Culpeper and Gettysburg basins served as proxies for understanding of the basin sequences. Their study allowed recognition of five mappable assemblages of rock types, herein termed lithofacies associations. These lithofacies associations were formed by alluvial fan, braided and meandering streams and marginal and distal lake depositional processes.Stratigraphic architecture of the lithofacies associations within exposed basins suggests a vertical succession that consists of an initial coarse-grained fluvial succession that is progressively replaced upward and basinward by finer grained lacustrine deposits. Along the faulted margins of the basins alluvial fans transitioning to fluvial delta deposits reflect lateral progradation and contemporaneous lateral components of the basin filling.To test the model devised in exposed basins, facies associations were developed for the buried Taylorsville Basin. This basin preserves over 8,000 feet of Triassic rocks that are concealed beneath more than 2,000 feet of Cretaceous and Tertiary Coastal Plain sediments. Composition and stratigraphic architecture of these rocks are similar to those observed in exposed basins. Infilling of the basin was the result of vertical aggradation and lateral progradation of coarse-grained to fine-grained facies. Based upon study of outcrops in the Culpeper and Gettysburg basins, groups of recurring lithologic facies were identified as the fundamental constructs of the basin’s sediment infilling. These groups of facies, termed lithofacies associations, represent an amalgamation of lithologic components from broadly similar depositional systems. These lithologic associations were then extrapolated into the exposed and buried portions of the Taylorsville basins. This effort determined that Triassic rift basins provide several avenues for potential study of geologic sequestration of carbon. The characteristic rift basin succession in the basins presents possible reservoir targets within the marginal fluvial deposits. Furthermore, intrusive and extrusive mafic bodies present a potential source of fracture porosity that could serve as CO 2 reservoirs. Porosity values from thin section analysis of exposed basin samples are higher in alluvial fan and braided fluvial lithofacies. Porosity is highest in samples that show less compaction, due to a lack of ductile lithic fragments and/or higher stratigraphic position. Log data from the Taylorsville Basin indicates that porosity and permeability values in basin marginal fluvial strata are elevated. Near the center of the basin, porosity and permeability values are greatly reduced, primarily owing to the fine-grained character of the lacustrine deposits. Some Triassic basins also contain thick intervals of concordant extrusive and intrusive mafic igneous rocks. These igneous bodies are potential CO 2 reservoirs for several reasons. Firstly, extrusive lava flows provide potential storage in the layers of primary porosity that occur in the vesicules formed at the top of lava flows. Secondly, both lava flows and subsurface igneous sills exhibit extensive fracture porosity produced by the rapid cooling of the flows and intrusions. Thirdly, these igneous rocks are mafic in composition, and studies have shown that iron- and magnesium-rich mafic rocks provide sequestration opportunities through carbonate remineralization. Lastly, extrusive and intrusive igneous rocks are invariably preserved within fine-grained lake deposits. These lacustrine sediments can serve as a fine-grained confining layer that encases the igneous rocks both above and below.

01 COAL, LIGNITE, AND PEAT↗

U.S. Industry Opportunities for Advanced Nuclear Technology Development Phase II (Final Report)

This limited scope study aims at preserving the results of experimental programs for the safety of light water cooled and advanced reactors by locating and documenting, to the extent possible, where the experimental test information for these programs has been archived. The Light Water Reactor Data Preservation Activity Team initially identified seven (7) experimental programs, exceeding the required five (5) in the scope of work, which were determined to be “at risk” of potentially losing valuable data. The seven (7) experimental programs/subject areas identified are (descriptions of each experiment/experience are provided in Section 3.0): 1. FERMI-1 Reactor Accident 2. Fission Product Behavior During the In-Pile Severe Fuel Damage Test SFD I-4 3. Containment Iodine Computer Code Exercise Based on Radioiodine Test Facility (RTF) Experiment 4. Wide Range Piping Integrity Demonstration (WIND) Project 5. Iodine Chemical Research in Canada 6. High Temperature Fission Product Chemistry and Transport in Steam 7. Anything related to radioactive Methyl Iodide.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Summary Report for Out-of-Pile Transient Testing Database Development

The DOE Advanced Reactor Technology program has supported knowledge preservation efforts to recover and preserve fuel data from the US sodium cooled fast reactor (SFR) program. Efforts have focused on establishing databases of experimental data generated during the Integral Fast Reactor program (at EBR-II, FFTF, and TREAT) as well as during related out-of-pile examinations of the fuel irradiated at EBR-II. The information in these databases is essential to support further development and licensing activities for advanced fast reactor designs. OPTD is a database of out-of-pile furnace transient tests on metallic fuel. It includes records of 62 tests on irradiated fuel pins conducted in furnace apparatuses constructed in the Alpha-Gamma Hot Cell Facility at ANL. This report describes efforts during FY19 to improve visibility and access, expand the content of, and improve the user experience with the FIPD and OPTD databases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Real-time data reduction at 100 Tbps: Challenge and opportunity for AI-based data reduction for next-generation large-scale nuclear physics collider experiment

The modern large-scale nuclear physics (NP) experiments in high-energy particle colliders utilize streaming-readout electronics to digitize detector response at O(100) Tbps bandwidth. Prominent examples at Brookhaven National Lab (BNL) include the sPHENIX experiment at Relativistic Heavy Ion Collider (RHIC), which is under construction, and the experiments proposed for the Electron-Ion Collider (EIC), planned for the 2030s . One of the main challenges for these streaming readout systems is to manage the data rate with sufficient data reduction in real time so the end-data fit persistent storage for offline analysis, which is typically at O(1000) times smaller and O(100) Gbps. Such data reduction traditionally is achieved via real-time high level triggers, which select and save a small subset of collisions of interest. Although triggering is applicable to high energy collider experiments such as those at the Large Hardron Collider at CERN, it is insufficient for these nuclear physics experiments which study diverse collision topologies. And traditional triggering approach is inefficient to preserve the max information harvested from the operation of colliders that costs O(100)M per year to DOE. Meanwhile, in recent years, ML-based high-throughput data reduction has emerged as a promising approach to efficiently preserve max information for a given space of persistent storage, e.g. via AI data compression, feature extraction, and noise filtering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Universal Monte Carlo Event Generator

With the Jefferson Lab 12 GeV physics program underway and plans for the future Electron-Ion Collider (EIC), the nuclear physics community is entering a new era of exploration of QCD phenomena involving extensive data taking and event-level processing. This brings with it the potential for unprecedented access to multidimensional particle momentum distributions (PMDs) that can be connected to various theoretical frameworks by unfolding the emergent quantum mechanical properties of QCD using the PMDs. In practice, the PMDs are rendered as discretized histograms (typically one- or two-dimensional projections), and detector effects must be taken into account to unfold the pure detector effect-free PMDs that can be connected with theory. One of the challenges in this new era is obtaining faithful reconstructions of the multidimensional PMDs that preserve all of the inherent particle correlations. In this LDRD project we developed a novel approach using machine learning (ML) that solves this challenge, by avoiding entirely the need to use histograms as the main numerical technique to obtain the detector effect-free PMDs. The new approach is, moreover, scalable to higher dimensional PMDs. The central idea involves training neural networks (NNs) to generate synthetic event-level data (momenta 4-vectors of final state particles) to preserve all correlations among the particles. This is achieved by converting the trial synthetic vertex-level events to detector-level events using detector simulators. The NNs are then tuned using a specialized distance metric between the synthetic detector events and the real detector events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Position Papers for the ASCR Workshop on Cybersecurity and Privacy for Scientific Computing Ecosystems

At the request of the Department of Energy's (DOE) Office of Advanced Scientific Computing Research (ASCR), this program committee has been tasked with organizing a workshop to identify basic research needs in cybersecurity and privacy to better support DOE's science and energy mission. As part of the process, the program committee is soliciting community input in the form of position papers to help identify significant use cases, facility issues, and other barriers to enabling verifiably trustworthy computational science while preserving data confidentiality as appropriate for scientific workflows of interest to DOE. The program committee will review these position papers and based on the fit of their area of expertise and interest, selected contributors will have the opportunity to participate in the workshop currently planned as a virtual event November 3-5th, 2021. The thrust areas that will be explored by this workshop are the following: (1) Algorithms for secure, scalable, privacy-enhancing technologies and frameworks, including: Federated AI/ML, Differential privacy, Randomized algorithms, Adversarial modeling & simulation, Graph algorithms, and Formal methods; (2) Platforms to support the entire scientific-computing ecosystem, including edge computing for large-scale experiments, focusing on heterogeneous systems and distributed systems, including: Heterogeneous computing systems, Distributed computing systems, and Secure data architectures; and (3) Data workflows to allow agile use of data while preserving integrity and privacy, making the important properties verifiable either at runtime or post-computation, including: Integrity and provenance and Data management infrastructure. Topics that are out-of-scope for the workshop include discussing specific proposed solutions or areas that are clearly out of DOE's fundamental and applied-sciences mission scope, e.g., cryptography, enterprise security, and general-operations technology.

97 MATHEMATICS AND COMPUTING↗

Mitigate: An Adaptive Network Data Anonymization Tool Using Condensation-Based Differential Privacy

Modern network devices collect a large amount of data that can be analyzed to identify bottlenecks, anomalies, cyber-attacks, etc. Therefore, there is often a need to analyze such collections of network data quite often by an external expert or by the research community. However, these collections of data contain sensitive, proprietary information. In order for the network data to be shared, it must first be anonymized. The overall objective of this project is to develop an innovative privacy management tool to anonymize network data and achieve sufficient privacy, acceptable data utility, and efficient data analysis at the same time. No existing anonymization methods can achieve all of these at the same time. The core of this technology is a differential private clustering algorithm that provides strong privacy protection, preserves data properties important for subsequent analysis, and allows the party receiving the anonymized data to conduct analysis directly on anonymized data without the need of decryption or any extra processing. The research carried out was to design, implement and verify a solution to this problem by completing the following tasks: 1) developing the core technology; 2) developing a context based method that automatically recommends fields that must be anonymized; 3) conducted experiments showing superior results using our approach compared to existing tools, and 4) developed an intuitive but basic user interface. The research that was conducted generated novel algorithmic techniques that utilize state-of-the-art methods such as condensation, differential privacy preservation, clustering, automated tuning based on contextual awareness, and recommendation techniques to specify columns to users for anonymization leading to optimal privacy that allows research analysis on the dataset. Experiments were conducted to evaluate the efficacy of these novel algorithmic techniques by performing analysis on original non-anonymized datasets, then conducting analysis on the same yet anonymized datasets and comparing the results of the analyses. Overall, the anonymized analysis results were within 1% of the original results, verifying that the generated technology not only guarantees a high level of privacy but also enables research analysis as if it were conducted on the original dataset. Potential applications of this technology include anonymization of any type of structured network datasets that contain sensitive identifiers, such as IP addresses, that can be used in multiple applications. For example, to create an AI or machine learning model for cyber security, e.g., to detect attacks, or for performance analysis, e.g., identify bottlenecks or predict performance. In addition, a market analysis that was conducted for potential applications of this technology identified a broader range of applications of our anonymization technology beyond the network sector that includes healthcare, banking, insurance, securities, finance (FISB), data brokering, cloud services, ad sales, and government.

97 MATHEMATICS AND COMPUTING↗

Highlights for DOE ASCR Applied Math Office [Slides]

An efficient Picard-based solver is proposed for a novel energy conserving particle integrator preserving all first-order guiding center drifts and correct gyroradius for large time steps in arbitrary (non-uniform) magnetic fields. This research enables the efficient deployment of the novel asymptotic preserving (AP) particle orbit integrator into modern energy-conserving, implicit particle-in-cell codes, delivering a truly multiscale simulation capability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Towards Z-Next: The Integration of Theory, Experiments, and Computational Simulation in a Bayesian Data Assimilation Framework

Making reliable predictions in the presence of uncertainty is critical to high-consequence modeling and simulation activities, such as those encountered at Sandia National Laboratories. Surrogate or reduced-order models are often used to mitigate the expense of performing quality uncertainty analyses with high-fidelity, physics-based codes. However, phenomenological surrogate models do not always adhere to important physics and system properties. This project develops surrogate models that integrate physical theory with experimental data through a maximally-informative framework that accounts for the many uncertainties present in computational modeling problems. Correlations between relevant outputs are preserved through the use of multi-output or co-predictive surrogate models; known physical properties (specifically monotoncity) are also preserved; and unknown physics and phenomena are detected using a causal analysis. By endowing surrogate models with key properties of the physical system being studied, their predictive power is arguably enhanced, allowing for reliable simulations and analyses at a reduced computational cost.

97 MATHEMATICS AND COMPUTING↗

Surveillance of Site A and Plot M: Report for 2021

The results of the environmental surveillance program conducted at Site A/Plot M for calendar year 2021 are presented within this document. Site A/Plot M is in the Palos Area Preserves, operated by the Forest Preserve District of Cook County. The surveillance program consists of the collection and analysis of surface and groundwater samples to determine the amount of hydrogen-3 and strontium-90 present in the environment within and surrounding the site of the former research facility (Site A) and waste burial site (Plot M).

54 ENVIRONMENTAL SCIENCES↗

Indoor Occupant Counting by RF Backscattering

Building HVAC (heating, ventilation and air conditioning) consumes approximately 13% of all energy consumption in USA. Motion detectors, cameras and user programmable thermostats have been shown to be ineffective for HVAC controls to save energy, mostly due to the user concerns of comfort, reliability and privacy. A new HVAC control system based on real-time occupant counting that is fully automated, highly accurate, economically sensible and preserving privacy and aesthetics can thus bring forth a disruptive impact to this large energy sector. Our indoor occupant monitoring technology is based on the radio-frequency identification system (RFID), deployed in the room, not on the occupants. One reader with four antennas can be deployed on the ceiling or behind the ceiling panels for every thousand square feet in home, office and assisted living, with or without room partitions. The sticker-like passive tag, 10 cents each and maintenance-free, are profusely hidden on the wall or inside the furniture at arbitrary position, preserving privacy and aesthetics. The large number of tags can realize diverse observation points to accommodate arbitrary room layouts, which is impractical by other active units of camera, infrared, radar or lidar. With 20 tags, the system can reliably detect the number of occupants. For 100 tags, occupant posture and location can be known. The technology has been verified in the research labs and test buildings with very high accuracy. When the real-time occupant number can be accurately known without assuming devices on occupants or occupant motion, the building HVAC system can be automated to achieve building energy saving without sacrificing occupant comfort. According to our limited testing in a few types of building models and the simplified cost calculation, the RFID system has low overall cost in production, deployment, operation and maintenance. The signal processing algorithm based on machine learning requires very small number of training cases as most learning is transferrable for various layouts, and very low computational needs during operation, according to our testing in four different room sizes and layouts. In our preliminary estimate from HVAC saving alone, the RFID system can potentially pay for itself within 1.5 years, in addition to the other enhancement in building automation systems (BAS). Our commercialization strategy and business pitch deck focus on venturing this Cornell occupant monitoring technology into BAS and energy management markets. We have identified three broad BAS market segments of senior living, residential buildings, and office buildings. We have put together the minimum viable product characteristics for these identified segments, including analyses on total cost and competing technologies, as well as the fit and technical gaps for these market segments. We intend to bring the technology to market by licensing or partnering with existing BAS vendors. A list of potential collaborators and licensing partner candidates was assembled for different aspects of integrating our technology into a potential product that can be used with BAS.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Waste Isolation Pilot Plant Annual Site Environmental Report for 2016

The purpose of the Waste Isolation Pilot Plant (WIPP) Annual Site Environmental Report for 2016 (ASER) is to provide the information required by U.S. Department of Energy (DOE) Order 231.1B, Environment, Safety, and Health Reporting. The DOE Carlsbad Field Office (CBFO) and the management and operating contractor (MOC) maintain and preserve the environmental resources at the WIPP facility. DOE Order 231.1B; DOE Order 436.1, Departmental Sustainability; and DOE Order 458.1, Radiation Protection of the Public and the Environment, require that the affected environment at and near DOE facilities be monitored to ensure the safety and health of the public and workers, and preservation of the environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Small Angle X-Ray Scattering and Polymers

Polymers are some of the most versatile and useful materials on this planet. Properties of polymers are a result of their processing history, chemical makeup, and physical structure. Therefore, characterization is necessary to develop new polymer formulations and processes. Many established techniques for polymer characterization are destructive, and alternative methods that don’t destroy samples are in high demand. Thermal analysis techniques such as differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) yield important characteristic information for polymer samples while destroying the sample. Non-destructive strategies such as X ray diffraction (XRD) or small angle X-ray scattering (SAXS) can also find polymer characteristics while preserving a sample’s attributes. Sample preservation is desirable when investigating novel formulation and processing methods. SAXS analysis will be done on two different polymers: polyethylene, and a triblock copolymer. Using these two polymers allows for confidence between tests as polyethylene is very common, and well understood. Polyethylene analysis will be done first, and when methods have been refined so that the SAXS data matches accepted thermal analysis values for HDPE, there will be confidence to use the same analysis on block copolymers. Block copolymers remain relatively unexplored, so SAXS data will yield valuable information on their characteristics. Understanding the mechanical properties of these polymers is paramount to their application in upcycling, a process by which waste plastic can be converted into a higher value commodity. For this project, the upcycling process will be done via 3-dimensional (3d) printing.

36 MATERIALS SCIENCE↗

Cultural Resource Management Plan for Brookhaven National Laboratory

The Cultural Resource Management Plan (CRMP) for Brookhaven National Laboratory (BNL) provides an organized guide that describes or references the facets and interrelationships of cultural resources at BNL. Management strategies included within this CRMP are designed to adequately identify the cultural resources that BNL and DOE consider significant and to acknowledge associated management actions. A principal objective of the CRMP is to reduce the need for additional regulatory documents and to serve as the basis for a formal agreement between the DOE and the New York State Historic Preservation Officer (NYSHPO). The BNL CRMP is designed to be a “living document.” Each section includes identified gaps in the management plan, with proposed goals and actions for addressing each gap. The plan will be periodically revised to incorporate new documentation. The current (2023) update incorporates new findings and/or updated text based on completed or ongoing projects related to cultural resources at BNL since inception of the last updated CRMP in 2013. Historically, Brookhaven National Laboratory had little need for cultural resource management because many of its buildings were less than 50 years old. Most of the features that are potentially eligible for inclusion in the National Register of Historic Places were protected simply by avoiding the features. Compliance with cultural resource laws and regulations has included archeological surveys, such as those associated with the 1977 Final Environmental Impact Statement for Brookhaven National Laboratory and the 1978 Final Environmental Impact Statement for the Proton-Proton Storage Accelerator Facility (ISABELLE). In 1979, World War I trenches associated with the former Camp Upton and located near ISABELLE were determined to be eligible for inclusion in the National Register of Historic Places; however, many of these trenches had been destroyed by construction work. In 1991, the NYSHPO provided BNL with a letter indicating that only three structures and features were likely to be eligible for inclusion in the National Register of Historic Places. Between 1991 and 1999, little work associated with cultural resource management was accomplished. Beginning in 1999, awareness for the need of a program to manage cultural resources grew out of the realization that over half of the buildings at BNL were either 50 years old or were reaching that age and were, therefore, subject to the requirements in Section 106 of the National Historic Preservation Act. This fact, concomitant with the decontamination and decommissioning of the Brookhaven Graphite Research Reactor (BGRR) and the subsequent determination of BGRR’s eligibility for listing as an historical site, fueled the need for developing and implementing a more structured program for managing cultural resources at BNL.

54 ENVIRONMENTAL SCIENCES↗

Rays for Roots - Integrating Backscatter X-Ray Phenotyping, Modeling and Genetics to Increase Carbon Sequestration and Switchgrass Resource Use (Final Report)

To increase carbon (C) deposition in the soil and enhance crop resource use efficiency, characterizing root form and function is essential. Several root and soil traits have been linked to increased root-to-soil C transfer. Technology that could provide high-resolution characterization of many of these traits in field conditions would revolutionize our ability to study and understand how to increase C sequestration. In this effort, we developed an initial early prototype backscatter X-ray system for non-destructive imaging of root traits. We collected initial backscatter X-ray data in field and lab settings and carried out early analysis of these data. Along with this prototype, we also developed a suite of root phenotyping approaches including advanced minirhizotron image analysis, soil core imaging, and mesocosm imaging. Minirhizotron (MR) tubes are clear tubes inserted into the soil in the field and used to image roots and the surrounding soil. Our team has developed deep learning-based methods that can segment roots from soil that can learn from imprecise image-level labels. The ability to learn or fine-tune our deep learning algorithms from image-level labels allows easier and faster application of these approaches to new locations and new plant species. We have successfully implemented and applied our MR analysis approaches to thousands of switchgrass MR images collected across geographical regions. An advantage of MR imaging is the ability to collect root and soil images over time. Our soil core analysis included collecting hundreds of soil core samples from harvested switchgrass fields and imaging these cores with both X-ray CT and backscatter X-ray imaging. Initial segmentation approaches for the X-ray CT images of these cores have been developed and applied. An advantage of soil core analysis is that it preserves the three-dimensional structures of the roots and soil in the core collected. Our group also developed photogrammetry-based mesocosm root imaging and phenotyping approaches. In this approach, a plant was grown in a large mesocosm with a three-dimensional grid of thin supporting lines inserted throughout the mesocosm. After the plant (and, correspondingly, the root architecture is grown and established) the soil media was removed and the supporting lines approximately preserved the three-dimensional root architecture. Then, we applied photogrammetry techniques to create a three-dimensional digital representation of the root architecture for which we developed analysis algorithms including skeletonization. We carried out our phenotyping development with powerful switchgrass resources and physiological and agroecosystem modeling to deliver novel technology. This project contributes to multiple ARPA-E missions including reduction of foreign imports of energy, reduction of energy-related emissions including greenhouse gases, and ensuring that the United States maintains a technological lead in developing and deploying advanced energy technology. Furthermore, the developed tools could transform public and private plant breeding and could be broadly applicable to other crops and, potentially, other application areas. Our team of engineers, plant and soil scientists, and modelers i) developed an early prototype backscatter X-ray platform that can operate in field conditions; ii) developed a suite of root phenotyping and characterization approaches as described above; iii) developed and carried out plant biology and physiology roots studies and; iv) developed and implemented mechanistic physiological modeling.

42 ENGINEERING↗