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Why Terminology Matters for Successful Rollout of Carbon Dioxide Utilization Technologies

To realize their full sustainability potential, carbon dioxide utilization technologies (carbon capture and utilization/CCU) presently require policy support. Consequently, they require acceptance among a variety of stakeholders in industry, policy making, and in the public sphere alike. While CO 2 utilization is already a topic of discourse among these stakeholders, there is a lack of common terminology to describe such technologies. On the contrary: The present article shows that terminology in the field of CO 2 utilization technologies is currently used inconsistently, and that different designations such as CCU, CCUS, or CDR convey different meanings and contexts. These ambiguities may cause communication problems with regard to policy making, funding proposals, and especially in public discourse. In order to initiate and accompany a goal-oriented and knowledge-based debate on CO 2 utilization technologies in the future, actors in the field are asked to question their own choices of terminology and to assess its accuracy. Acronyms and technical abbreviations are the chief cause of potential misunderstandings, and so should be avoided whenever possible or else include a brief explanation. Consistent and precise use of terminology will facilitate transparent dialogue concerning CO 2 utilization in the future.

54 ENVIRONMENTAL SCIENCES↗

Compact fiber-coupled narrowband two-mode squeezed light source

Quantum correlated states of light, such as squeezed states, are a fundamental resource for the development of quantum technologies, as they are needed for applications in quantum metrology, quantum computation, and quantum communications. It is thus critical to develop compact, efficient, and robust sources to generate such states. Here, we report on a compact, narrowband, fiber-coupled source of two-mode squeezed states of light at 795 nm based on four-wave mixing (FWM) in an 85 Rb atomic vapor. The source is designed in a small modular form factor, with two input fiber-coupled beams, the seed and pump beams required for the FWM, and two output fibers, one for each of the modes of the squeezed state. The system is optimized for low pump power (135 mW) to achieve a maximum intensity-difference squeezing of 4.4 dB after the output of fibers at an analysis frequency of 1 MHz. Furthermore, the narrowband nature of the source makes it ideal for atomic-based quantum sensing and quantum networking configurations that rely on atomic quantum memories. Such a source paves the way for a versatile and portable platform for applications in quantum information science.

Jain, Umang [University of Oklahoma, Norman, OK (U↗

Moiré quantum chemistry: Charge transfer in transition metal dichalcogenide superlattices

Transition metal dichalcogenide (TMD) bilayers have recently emerged as a robust and tunable moiré system for studying and designing correlated electron physics. In this Rapid Communication, by combining a large-scale first-principles calculation and continuum model approach, we provide an electronic structure theory that maps long-period TMD heterobilayer superlattices onto diatomic crystals with cations and anions. We find that the interplay between the moiré potential and Coulomb interaction leads to filling-dependent charge transfer between different moiré superlattice regions. Further, we show that the insulating state at half filling found in recent experiments on WSe 2 /WS 2 is a charge-transfer insulator rather than a Mott-Hubbard insulator. Our work reveals the richness of simplicity in moiré quantum chemistry.

36 MATERIALS SCIENCE↗

Performance Audit Report: Automated Meteorological Monitoring Stations, Lawrence Livermore National Laboratory

The Waste and Air Quality Offices Group at the Lawrence Livermore National Laboratory operates two main meteorological monitoring sites near Livermore, California. The primary met tower (Site 200) is located in the northwest corner of the lab and consists of a fifty-two (52) meter tower with vertical wind speed sensors, horizontal wind speed and direction sensors and air temperature sensors at fifty-two (52) meters, twenty-three (23) meters and ten (10) meters. In addition, there is a temperature and humidity probe at ten (10) meters. At two (2) meters there are upward and downward facing solar and infrared radiation sensors, an air temperature sensor, barometric pressure sensor and a temperature and relative humidity probe. At ground level there is a tipping bucket rain gauge located to the southwest of the tower. The datalogger, communication peripherals and the barometric pressure sensor are housed in a small building near the tower. The Site 300 met site is located approximately 10 miles east of Livermore within the boundary of the LLNL blast test site. This site also consists of a 52-meter tower which is configured the same as the 52-meter tower at Site 200. There is also a building at this site that houses the datalogger, communication peripherals and the barometric pressure sensor. At both Site 200 and Site 300, data are collected by Ethernet with telephone modem collection as a backup. The data collection interval for both sites is fifteen (15) minutes via workstations running Loggernet software located at the main lab facility. The audits of the Lawrence Livermore National Laboratory’s two automated meteorological stations located near Livermore, California were performed on October 24 & 25, 2023. These audits were performed under the guidelines of the Quality Assurance Handbook for Air Pollution Measurement Systems, Volume IV, Version 2 and the On-Site Meteorological Program Guidance for Regulatory Modeling Applications, U.S. EPA.

54 ENVIRONMENTAL SCIENCES↗

ParFlow Sand Tank: A tool for groundwater exploration

The ParFlow Sand Tank model is an open source application designed to allow users to interactively simulate and visualize groundwater movement through the subsurface. The app is designed for both research and education; teaching hydrogeology concepts and making it easy explore and run sophisticated groundwater simulations. Our goal is to support increased accessibility and usability of research grade hydrology tools for research and teaching. The Sand Tank application simulates groundwater and surface water fluxes as well as contaminant transport in real time using the integrated physical hydrology model ParFlow (Kollet & Maxwell, 2006; Maxwell & Miller, 2005; Osei-Kuffuor et al., 2014) and the particle tracking code EcoSlim (Maxwell et al., 2019). ParFlow is a numerical hydrology model that simulates spatially distributed groundwater and surface water flow. It is a well established research tool with more than 90 publications documenting its development use to advance our understanding of groundwater dynamics and groundwater surface water interactions from the hillslope to the continental scale e.g. (Condon et al., 2020; Condon & Maxwell, 2019; Maxwell & Condon, 2016). It is designed for efficient parallel computation and has been run on many platforms spanning from laptops to supercomputers. However, one of the challenges of ParFlow is that it requires significant training and hydrologic expertise to develop simulations. The Sand Tank application makes this model accessible to anyone for education and exploration. Our application uses ParFlow for its simulation backend and ParaView for the data loading and processing. The communication infrastructure relies on the ParaViewWeb framework. We use model templates deployed in Docker images to setup the Sand Tank framework. Users can build the application locally or interact with it through our web deployment. When interacting with a template users can interactively change model parameters like subsurface processes or pump/inject water into the subsurface and watch the system respond to their changes in real time as the simulation runs. Additionally, our template setup will allow more advanced users to build custom templates of increasing complexity for both research and educational purposes.

54 ENVIRONMENTAL SCIENCES↗

DOE Challenges and Opportunities Associated with Accountable Nuclear Material Needs for Development and Commercialization of Fusion Nuclear Energy

Fusion energy represents a transformative opportunity to deliver a safe, plentiful, and carbon-free source of reliable primary power. In recent years, fusion research and development have accelerated significantly, particularly within the US, driven by decades of foundational public investment. Notably, in 2024 the US Department of Energy (DOE) established a comprehensive Fusion Energy Strategy aimed at collaborating with industry partners to enable the deployment of fusion power plants and grid integration by the 2030s. This strategy is chiefly implemented through the DOE Office of Science (SC) Fusion Energy Sciences program. This project was initiated to identify potential approaches for the Office of Environment, Safety, and Health (NA-ESH-12) within DOE’s National Nuclear Security Administration to begin engagement with the fusion community on future accountable material needs. The goal of the project is to inform and influence the supply of and demand for accountable nuclear materials as fusion energy is developed and commercialized. NA-ESH-12 must proactively engage with the fusion community regarding the production and management of accountable nuclear materials. Given the complexity and scale of materials required for research, pilot projects, and eventual commercial reactors, early coordination is vital. The project’s objective is to provide insights that will shape the supply and demand landscape for critical nuclear materials, ensuring that DOE is prepared to effectively support fusion energy development and commercialization. In FY 2025, an initial limited review was conducted to identify the status of the fusion energy community’s progress toward full-scale energy production and the need for accountable nuclear material. This included communications with SC, NA-ESH-12, Savannah River National Laboratory, and Oak Ridge National Laboratory, and attending the Rutgers University–sponsored Supply Chain Workshop: Scaling the Fusion Industry and the International Atomic Energy Agency’s Ninth DEMO Programme Workshop. The review to date indicates that the amounts of tritium, lithium-6, and deuterium required by the fusion industry will be dependent on fuel type, breeding technology, blankets, and R&D improvements. One concern is that the commercial sector does not have a sufficient supply chain to meet the demand for development and commercialization for fusion energy production. The supply and demand estimates for these materials should be routinely reviewed as fusion technologies mature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Leveraging generative AI for urban digital twins: a scoping review on the autonomous generation of urban data, scenarios, designs, and 3D city models for smart city advancement

The digital transformation of modern cities by integrating advanced information, communication, and computing technologies has marked the epoch of data-driven smart city applications for efficient and sustainable urban management. Despite their effectiveness, these applications often rely on massive amounts of high-dimensional and multi-domain data for monitoring and characterizing different urban sub-systems, presenting challenges in application areas that are limited by data quality and availability, as well as costly efforts for generating urban scenarios and design alternatives. As an emerging research area in deep learning, Generative Artificial Intelligence (GenAI) models have demonstrated their unique values in content generation. This paper aims to explore the innovative integration of GenAI techniques and urban digital twins to address challenges in the planning and management of built environments with focuses on various urban sub-systems, such as transportation, energy, water, and building and infrastructure. The survey starts with the introduction of cutting-edge generative AI models, such as the Generative Adversarial Networks (GAN), Variational Autoencoders (VAEs), Generative Pre-trained Transformer (GPT), followed by a scoping review of the existing urban science applications that leverage the intelligent and autonomous capability of these techniques to facilitate the research, operations, and management of critical urban subsystems, as well as the holistic planning and design of the built environment. Based on the review, we discuss potential opportunities and technical strategies that integrate GenAI models into the next-generation urban digital twins for more intelligent, scalable, and automated smart city development and management.

3D city modeling↗

Quantum networks based on color centers in diamond

With the ability to transfer and process quantum information, large-scale quantum networks will enable a suite of fundamentally new applications, from quantum communications to distributed sensing, metrology, and computing. This Perspective reviews requirements for quantum network nodes and color centers in diamond as suitable node candidates. We give a brief overview of state-of-the-art quantum network experiments employing color centers in diamond and discuss future research directions, focusing, in particular, on the control and coherence of qubits that distribute and store entangled states, and on efficient spin–photon interfaces. We discuss a route toward large-scale integrated devices combining color centers in diamond with other photonic materials and give an outlook toward realistic future quantum network protocol implementations and applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

OPEN leaf : an open‐source cloud‐based phenotyping system for tracking dynamic changes at leaf‐specific resolution in Arabidopsis

SUMMARY The first draft of the Arabidopsis genome was released more than 20 years ago and despite intensive molecular research, more than 30% of Arabidopsis genes remained uncharacterized or without an assigned function. This is in part due to gene redundancy within gene families or the essential nature of genes, where their deletion results in lethality (i.e., thedark genome). High‐throughput plant phenotyping (HTPP) offers an automated and unbiased approach to characterize subtle or transient phenotypes resulting from gene redundancy or inducible gene silencing; however, access to commercial HTPP platforms remains limited. Here we describe the design and implementation ofOPEN leaf, an open‐source phenotyping system with cloud connectivity and remote bilateral communication to facilitate data collection, sharing and processing.OPEN leaf, coupled with our SMART imaging processing pipeline was able to consistently document and quantify dynamic changes at the whole rosette level and leaf‐specific resolution when plants experienced changes in nutrient availability. Our data also demonstrate that VIS sensors remain underutilized and can be used in high‐throughput screens to identify and characterize previously unidentified phenotypes in a leaf‐specific time‐dependent manner. Moreover, the modular and open‐source design ofOPEN leafallows seamless integration of additional sensors based on users and experimental needs.

Plant Sciences↗

Pressurizer dynamic model and emulated programmable logic controllers for nuclear power plants cybersecurity investigations

This work demonstrates the functionality of the pressurizer using a fast-running three regions, non-equilibrium model and control programs of emulated PLCs. The state variables from an integrated model of primary loop in a representative PWR plant are communicated to the pressurizer’s emulated PLCs using a synchronized data transfer function. In turn, the PLCs communicate back instructions to the pressurizer model to adjust the pressure and water level to remain within preprogramed setpoints. Pressurizer model simultaneously solves the coupled mass and energy conservation equations in the saturated vapor and saturated and subcooled liquid regions using fixed step solver. Results demonstrate the response of the pressurizer model linked to an emulated pressure and water level PLCs in a simulated transient involving surge-in and surge-out events. The 50 ms response delay time for the emulated PLC insignificantly affects operation and predictions of the pressurizer model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Drone Video Platform—Collision Avoidance, Situational Awareness, and Communications

Small unmanned aerial systems are ideal for delivering sensors into areas that are inaccessible or too dangerous for human entry or manned aircraft over-flights. The systems can fly low and slow for enhanced sensitivity and in tight spaces where ordinary aircraft could never fit. We have configured and flown sensor payloads for radiation, chemical, and optical detection on small fixed-wing and rotary-wing aircraft. All the sensor packages provide telemetry, GPS coordinates, LIDAR distance ranging, and absolute time of day to microsecond accuracy. Payload weights range from less than 1 kg up to 5.5 kg. Currently, communications are over 2.4 GHz and 915 MHz radios, as well as over 4G LTE cellular data links. Real-time data feeds from the sensor payloads to web browser clients anywhere in the world are possible via a virtual EC2 server on the Amazon AWS cloud. In FY 2019, the Nevada National Security Site teamed with Virginia Tech, H3D Corp., and Unmanned Systems, Inc. to accomplish the four flight missions described in this report. A large part of this year’s mission goals were to demonstrate the ability to fly beyond visual line of sight (BVLOS).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The Role of Quantum Science Concepts in Enhancing Sensing and Imaging Technologies: Applications for Biology: Proceedings of a Workshop

Quantum concepts hold the potential to enable significant advances in sensing and imaging technologies that could be vital to the study of biological systems. The workshop Quantum Science Concepts in Enhancing Sensing and Imaging Technologies: Applications for Biology, held online March 8–10, 2021, was organized to examine the research and development needs to advance biological applications of quantum technology. Hosted by the National Academies of Sciences, Engineering, and Medicine, the event brought together experts working on state-of-the-art, quantum-enabled technologies and scientists who are interested in applying these technologies to biological systems. Through talks, panels, and discussions, the workshop facilitated a better understanding of the current and future biological applications of quantum-enabled technologies in fields such as microbiology, molecular biology, cell biology, plant science, mycology, and many others. The workshop was organized around three main themes. The first, quantum in biology, examined quantum concepts that are hypothesized to be important for life processes and that researchers are working to observe through biological imaging and sensing. The second, quantum for biology, addressed ways to use quantum concepts to enhance technologies for biological imaging and sensing. The third, biology for quantum, offered a wider discussion of how the frontiers of biological imaging and sensing could enable future study using quantum concepts, tools, or technologies. Throughout the workshop, participants identified a wide range of emerging approaches and opportunities at the intersection of quantum physics and biological sensing and imaging. During the workshop, there were some differences in how each speaker defined the term quantum. During one of the panels, Prem Kumar offered thoughts on what phenomena are classical versus quantum, explaining that techniques get progressively more quantum as you move from just having superposition to having superposition with measurement and entanglement. Another explanation from Clarice Aiello delineates the definition into several levels. This includes a base level of “quantum-ness,” which reflects that all matter is made of atoms, and when these particles are isolated they behave based on quantum mechanical principles. A second level is related to quantum coherence, where a single quantum object might be found in a coherent superposition state. A final level, which she described as the quantum-entangled level, involves multiple quantum systems which are entangled among themselves. Overall, the workshop touched on concepts such as superposition, entanglement, and squeezing and their potential implications for communication, computing, and simulation, in addition to the workshop’s main focal area, biological sensing and imaging. At the opening of the workshop, Thorsten Ritz of the University of California, Irvine, identified two questions at the heart of quantum biology: Is the machinery of life quantum mechanical, and can quantum mechanics be used to study the machinery of life in new ways? Participants highlighted systems in which researchers have explored these questions, from the vast array of molecular interactions involved in biological processes such as photosynthesis, to the mechanics involved in cellular functions such as differentiation and aggregation, to the role of oscillating magnetic fields in flight orientation among birds. Sensing and imaging technologies are crucial to biological research; these technologies could both enhance the study of quantum effects and be enhanced by quantum concepts. A critical challenge in biological research is to develop imaging and sensing tools that do not damage or interfere with the often fragile and fleeting systems being studied. Attendees discussed a variety of established and emerging technologies that could enhance noninvasive biological imaging, including single- and two-photon spectroscopy, single-molecule spectroscopy, quantum illumination, ghost imaging, and cryo-electron microscopy. One example came from Marlan Scully who gave a keynote address on the first day of the workshop. Scully emphasized the use of different laser technologies, which exhibit coherence and other quantum properties, in moving toward real-world biological applications, such as the detection of SARS-CoV-2. Both tools and theory will play an important role in advancing quantum biology research and applications. Several participants suggested theorists and experimentalists should work in tandem to understand and model biological processes. While physics often reduces systems to their simplest forms for fundamental insights, participants also noted the value of observing and understanding biological systems in all their “messiness,” capturing both the inner workings of biological systems and the complex interactions that occur within and between organisms. In discussions among participants, several attendees stressed the need to match emerging tools with the right scientific questions. Rather than developing quantum technologies as “a hammer looking for a nail,” participants emphasized a focus on exploring the problems these technologies are best suited to address. For example, it is important to consider the size of the phenomenon being studied, the timescales that are important in answering the scientific question, and other relevant considerations. Every tool along the spectrum from classical to quantum involves its own set of trade-offs. For example, Ted Laurence of the Lawrence Livermore National Laboratory said that quantum measurements, such as single photon counting, fluorescence transitions, and lasers, can take longer to produce the same results as classical measurements. These quantum measurements, however, do not require calibration and can enable new research questions to be answered. Prem Kumar, Northwestern University, noted that, despite their promise, quantum approaches should not be used simply for the sake of using quantum, especially in situations where classical approaches better meet the needs of the researcher. Understanding and applying quantum concepts could enable advances in a wide range of application areas including energy, synthetic biology, medicine, and sustainability. For example, Michelle O’Malley, University of California, Santa Barbara, described how improved noninvasive imaging approaches could help capture the complex interactions and functions involved in the breakdown of organic matter by microbial communities and lead to new technologies for capturing valuable products from plant waste. Several other participants discussed needs in tracking the movement of metabolites and molecules in microbial communities for insights into nutrient cycling in environments such as soil. Margaret Ahmad, Sorbonne University, discussed potential opportunities to leverage the magnetic properties of cryptochromes to advance new treatment approaches for diseases such as COVID-19 and cancer. Looking toward the future development of the field, participants discussed challenges to advancing quantum biology that arise from disciplinary disconnects between physicists and biologists. The siloing of academic research disciplines represents a significant barrier to progress. Disconnects in terminology, motivations and priorities, and structural barriers to collaborative work underscore the need for concerted efforts to bridge these divides. Attendees and speakers offered suggestions for resolving these divergences, establishing a shared language, moving the field forward, and fostering meaningful feedback between disciplines. Overall, participants stressed a need for balance, open communication, collaboration, unity, and clear dialogue on trade-offs between quantum and classical approaches. Keiko Torii, The University of Texas at Austin, said that the best collaborations happen when the project provides mutual advantages that can show off everyone’s talents, each team finds the work interesting, and partners develop a camaraderie to pursue new knowledge. To enable near- and long-term opportunities in this space, participants suggested that exploratory, high-risk funding could improve existing instrumentation to explore quantum enhancement collaboratively. They also emphasized the need for collaboration between quantum physicists and sensing/imaging scientists, which could be advanced through a dedicated quantum biology investigator program. People, even more than technology, will be crucial to the future of quantum biology. Participants explored training, education, and workforce needs to further develop this burgeoning field and cultivate the next generation of scientists. While many programs are still in their nascent stages, participants highlighted examples of approaches and programs being developed at various types of institutions to engage students and professional scientists in quantum biology research. Several participants stressed the need for an inclusive approach, spanning disciplines as well as communities to foster a diverse field fueled by the intellectual contributions of a wide range of people, including historically under-resourced schools and students. To increase awareness and excitement about quantum physics and related areas of biology, attendees suggested capitalizing on the “buzz” around quantum. Several participants emphasized the need to start early, introducing students to quantum concepts and their appealing “weirdness” in K–12 education. Engaging students early—before they become entrenched in traditional disciplinary siloes as typically happens in graduate school—could help to galvanize interest in the area and foster a generation of scientists with the interdisciplinary mindset and skills needed to advance this interdisciplinary field. While these efforts could be advanced at many levels and across multiple sectors, several participants suggested a national quantum biology center could be a valuable hub to coordinate and support quantum biology education and workforce development across academia, industry, and government.

59 BASIC BIOLOGICAL SCIENCES↗

Brief communication: Monitoring snow depth using small, cheap, and easy-to-deploy snow–ground interface temperature sensors

Abstract. Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. We trained a random forest machine learning model to predict snow depth from variability in snow–ground interface temperature. The model performed well on Alaska's Seward Peninsula where it was trained and at Arctic evaluation sites (RMSE ≤ 0.15 m). It performed poorly at temperate sites with deeper snowpacks, partially due to training data limitations. Small temperature sensors are cheap and easy to deploy, so this technique enables spatially distributed and temporally continuous snowpack monitoring at high latitudes to an extent previously infeasible.

54 ENVIRONMENTAL SCIENCES↗

Communication-efficient certificate revocation management for Advanced Metering Infrastructure and IoT Integration

Advanced Metering Infrastructure forms a communication network for the collection of power data from smart meters in Smart Grid. As the communication between smart meters could be secured utilizing public-key cryptography, however, public-key cryptography still has certain challenges in terms of certificate revocation and management particularly related distribution and storage overhead of revoked certificates. To address this challenge, in this work, we propose a novel revocation management approach by utilizing cryptographic accumulators which reduces the space requirements for revocation information significantly and thus enables efficient distribution of such information to all smart meters. We implemented the proposed approach on both ns-3 network simulator and a testbed. We demonstrated its superior performance with respect to traditional methods for revocation management.

97 MATHEMATICS AND COMPUTING↗

A proteomic meta-analysis refinement of plasma extracellular vesicles

Extracellular vesicles play major roles in cell-to-cell communication and are excellent biomarker candidates. However, studying plasma extracellular vesicles is challenging due to contaminants. Here, we performed a proteomics meta-analysis of public data to refine the plasma EV composition by separating EV proteins and contaminants into different clusters. We obtained two clusters with a total of 1717 proteins that were depleted of known contaminants and enriched in EV markers with independently validated 71% true-positive. These clusters had 133 clusters of differentiation (CD) antigens and were enriched with proteins from cell-to-cell communication and signaling. We compared our data with the proteins deposited in PeptideAtlas, making our refined EV protein list a resource for mechanistic and biomarker studies. As a use case example for this resource, we validated the type 1 diabetes biomarker proplatelet basic protein in EVs and showed that it regulates apoptosis of β cells and macrophages, two key players in the disease development. Our approach provides a refinement of the EV composition and a resource for the scientific community.

59 BASIC BIOLOGICAL SCIENCES↗

Strong spin–orbit quenching via the product Jahn–Teller effect in neutral group IV qubits in diamond

Abstract Artificial atom qubits in diamond have emerged as leading candidates for a range of solid-state quantum systems, from quantum sensors to repeater nodes in memory-enhanced quantum communication. Inversion-symmetric group IV vacancy centers, comprised of Si, Ge, Sn, and Pb dopants, hold particular promise as their neutrally charged electronic configuration results in a ground-state spin triplet, enabling long spin coherence above cryogenic temperatures. However, despite the tremendous interest in these defects, a theoretical understanding of the electronic and spin structure of these centers remains elusive. In this context, we predict the ground-state and excited-state properties of the neutral group IV color centers from first principles. We capture the product Jahn–Teller effect found in the excited state manifold to second order in electron–phonon coupling, and present a nonperturbative treatment of the effect of spin–orbit coupling. Importantly, we find that spin–orbit splitting is strongly quenched due to the dominant Jahn–Teller effect, with the lowest optically-active 3 E u state weakly split into m s -resolved states. The predicted complex vibronic spectra of the neutral group IV color centers are essential for their experimental identification and have key implications for use of these systems in quantum information science.

Materials Science↗

Deep Learning for Automated Identification of Eels in Sonar Data

Freshwater eels, such as the American eel (Anguilla rostrata) present numerous challenges related to safe downstream fish passage at hydroelectric facilities. One of those challenges is effective monitoring of their abundance, movements, and behavior to facilitate design and operation of eel protection and passage facilities. A previous EPRI study documented the ability of human analysts to reliably identify American eels in data obtained with a 1100/1800 kHz, multibeam sonar. This report describes a project to develop deep learning (a subset of artificial intelligence) tools to automate the time-consuming, subjective process of eel identification in multibeam sonar data. The project exploited new data collected in the laboratory and the existing data from the prior EPRI field study to develop and test deep learning and other data analytic tools, including wavelet filtering, differencing for static object removal, and convolutional neural network analysis. The analysis of the laboratory data demonstrated feasibility of the approach, revealed object characteristics observed with the sonar that distinguish eels from similarly sized and shaped acoustic targets, and provided additional data for algorithm selection and training. Deep learning algorithms trained and tested on the laboratory data alone achieved accuracy rates of greater than 98% when classifying acoustic images of eels and similar-sized neutrally buoyant sticks. The algorithm trained and tested on the pre-existing field data alone, and yielded classification accuracy of 9.3% false positives and 13.3% false negatives when distinguishing between eels and sticks/PVC pipes based on video clips (i.e., multiple, consecutive images). This performance is comparable to the classification accuracy achieved by human analysts in the prior study. The deep learning algorithm trained on a combination of video clips obtained in the laboratory and the field and tested on video clips from the field, was able to distinguish eels from sticks and PVC pipes (a river debris analog) of similar size with 100% accuracy. Outreach to the hardware, software, and end-user communities early in the project helped to identify needs and specify the application space. Outreach to those communities at the end of the project communicated project results and opportunities for further development. The project achieved proof of concept for automated identification of eel in multibeam sonar data. Future work should focus on acquisition of additional data for more robust algorithm training and testing; modification of the software tools to accommodate multiple acoustic targets in the acoustic field at a given time; identification of additional object classes; incorporation of motion in the object identification and classification algorithms; operationalizing the software tools, including integration with other existing sonar data analysis tools; and partnering with hardware and software providers for distribution of the software tools with their commercial products.

13 HYDRO ENERGY↗

Summer 2021 Internship Report

The Library Research and Prototyping team (Proto Team) under the research library explores aspects of scholarly communication, covering aspects of infrastructure, interoperability, and persistence. One of the key contributions of the team is the contribution in standardizing and forming the infrastructure for Mementos in web archiving. The Memento framework in web archiving enables access to digital resources in prior versions serving both persistence and the interoperability of the information. During the internship program, I worked on improving the Memento infrastructure by updating the memento validator. The Memento validator provides the functionality of testing the compliance of the web resources to the Memento specification. The application is intended to be used by the community at large such as web archives, researchers, librarians, and general users, with different levels of technical expertise.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗