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DOE OSTI2024

Countering Weapons of Mass Destruction Office (CWMD) Data Categorization Study: Chemical, Biological, Radiological, and Nuclear (CBRN) Detection Device Data

Pacific Northwest National Laboratory (PNNL) seeks to address critical questions related to chemical, biological, radiological, and nuclear (CBRN) detection devices. This research aims to enhance the security and understanding of these devices by investigating various aspects of their identification, communication, and functionality. The primary focus is on network security, malware detection, device identification, and intelligence gathering. CBRN data can be categorized in various ways depending on the purpose of CBRN detection devices and the specific context of the applications for analysis. Criteria that can be used to assist in this effort include but are not limited to data type, data protocol, source/destination, application, time, security, and content. This study will inform additional paths for data classification, data profiling, data mapping, and data modeling. This will help the Countering Weapons of Mass Destruction Office (CWMD) better understand their data and make informed decisions based on the insights gained from this study and their application. The CBRN Data Categorization study will include the identification of 5–10 different CBRN detection devices with unique characteristics for assessing and analyzing the data that is being produced by and transmitted from these devices.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2025

Probing Curved Spacetime with a Distributed Atomic Processor Clock

Quantum dynamics on curved spacetime has never been directly probed beyond the Newtonian limit. Although we can describe such dynamics theoretically, experiments would provide empirical evidence that quantum theory holds even in this extreme limit. The practical challenge is the minute spacetime curvature difference over the length scale of the typical extent of quantum effects. Here, we propose a quantum network of alkaline earth (like) atomic processors for constructing a distributed quantum state that is sensitive to the differential proper time between its constituent atomic processor nodes, implementing a quantum observable that is affected by post-Newtonian curved spacetime. Conceptually, we propose to delocalize one clock between three locations by encoding the presence or absence of a clock into the state of the local atoms. By separating three atomic nodes over approximately kilometer-scale elevation differences and distributing one clock between them via a 𝑊 state, we demonstrate that the curvature of spacetime is manifest in the interference of the three different proper times that give rise to three distinct beat notes in our nonlocal observable. We further demonstrate that 𝑁-atom entanglement within each node enhances the interrogation bandwidth by a factor of 𝑁. We discuss how our proposed system can probe new facets of fundamental physics, such as the linearity, unitarity, and probabilistic nature of quantum theory on curved spacetime. Our protocol combines several recent advances with neutral atom and trapped ions to realize a novel quantum probe of gravity uniquely enabled by quantum networks.

Covey, Jacob P. [Univ. of Illinois at Urbana-Champ↗

DOE OSTI2022

Sample-Efficient Adaptive Calibration of Quantum Networks Using Bayesian Optimization

All physical systems employed for quantum information tasks must act as unbiased carriers of encoded quantum states. Ensuring such indistinguishability of information carriers is a major challenge in many quantum information applications, including advanced quantum communication protocols. For photons, the workhorses of quantum communication networks, it is difficult to obtain and maintain their indistinguishability because of environment-induced transformations and loss imparted by communication channels, especially in noisy scenarios. Conventional strategies to mitigate these transformations often require hardware or software overhead that is restrictive (e.g., adding noise), infeasible (e.g., on a satellite), or time-consuming for deployed networks. In this work we propose and develop resource-efficient Bayesian optimization techniques to rapidly and adaptively calibrate the indistinguishability of individual photons for quantum networks using only information derived from their measurement. To experimentally validate our approach, we demonstrate the optimization of Hong-Ou-Mandel interference between two photons-a central task in quantum networking- finding rapid, efficient, and reliable convergence towards maximal photon indistinguishability in the presence of high loss and shot noise. We expect our resource-optimized and experimentally friendly methodology will allow fast and reliable calibration of indistinguishable quanta, a necessary task in distributed quantum computing, communications, and sensing, as well as for fundamental investigations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Gravitational waves from global cosmic strings and cosmic archaeology

Global cosmic strings are predicted in many motivated extensions to the Standard Model of particle physics, with close connections to axion dark matter physics. Recent studies suggest that, although subdominant relative to Goldstone emission, gravitational wave (GW) signals from global strings can be detectable with current and planned GW detectors such as LIGO, LISA, DECIGO/BBO, ET/CE and AEDGE/AION, as well as pulsar timing arrays such as PPTA, NANOGrav and SKA. This work is an extensive, updated study on GWs from a global cosmic string network, taking into account of the most recent developments related to the subject. The main analysis is based on the analytical Velocity-dependent One-Scale (VOS) model calibrated with recent simulation results, which provides a generic protocol for such calculations with details given. We also demonstrate how the GW signal can be influenced with variations to the baseline model: this includes considering the uncertainties of model parameters and the potential deviation from the conventional VOS model prediction (i.e. the scaling behavior) as suggested by some of the recent simulation results. Furthermore, we investigated in detail the effect of a non-standard cosmology (e.g. early matter domination or kination) or new particle species on the GW signals from global strings. We demonstrate that the frequency spectrum of GW background from global cosmic strings can be used to probe the cosmic history prior to the Big Bang nucleosynthesis (BBN) (i.e. the primordial dark age) up to a temperature of T ~ 10 8 GeV.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Remote Hardware-in-the-Loop Approach for Microgrid Controller Evaluation

Utilities have been installing microgrids because of the increased resilience and reliability advantages they may provide to the distribution system. A microgrid controller is a critical component in microgrids. It is of great benefit to derisk the installation of microgrid controllers before field deployment. Hardware-in-the-loop (HIL) testing is used by controller developers and utilities to evaluate the controllers under stressful conditions. In this work, a microgrid control function developed by the Synchrophasor Grid Monitoring and Automation (SyGMA) laboratory at the University of California, San Diego is tested in a remote HIL (RHIL) setup. The digital real-time simulation of the detailed microgrid system was operated at the National Renewable Energy Laboratory's Energy Systems Integration Facility. Under such RHIL setup, successful controller operation is contingent on understanding and characterizing the communications channel and in particular network latencies. The novelty of this paper is the proposed use of a RHIL setup that leverages existing power system communications protocols to evaluate the controller in conjunction with the simulation capabilities of a remote facility. The work presented here will provide the complete setup of the HIL evaluation platform, the details of the communications protocols used by the setup for data transfer between the two organizations, test cases developed to evaluate the controller, and the results from the experiments.

controller hardware-in-the-loop↗

DOE OSTI2020

Remote Hardware-in-the-Loop Approach for Microgrid Controller Evaluation

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

SARS-CoV-2 wastewater variant surveillance: pandemic response leveraging FDA’s GenomeTrakr network

ABSTRACT Wastewater surveillance has emerged as a crucial public health tool for population-level pathogen surveillance. Supported by funding from the American Rescue Plan Act of 2021, the FDA‘s genomic epidemiology program, GenomeTrakr, was leveraged to sequence SARS-CoV-2 from wastewater sites across the United States. This initiative required the evaluation, optimization, development, and publication of new methods and analytical tools spanning sample collection through variant analyses. Version-controlled protocols for each step of the process were developed and published on protocols.io. A custom data analysis tool and a publicly accessible dashboard were built to facilitate real-time visualization of the collected data, focusing on the relative abundance of SARS-CoV-2 variants and sub-lineages across different samples and sites throughout the project. From September 2021 through June 2023, a total of 3,389 wastewater samples were collected, with 2,517 undergoing sequencing and submission to NCBI under the umbrella BioProject,PRJNA757291. Sequence data were released with explicit quality control (QC) tags on all sequence records, communicating our confidence in the quality of data. Variant analysis revealed wide circulation of Delta in the fall of 2021 and captured the sweep of Omicron and subsequent diversification of this lineage through the end of the sampling period. This project successfully achieved two important goals for the FDA’s GenomeTrakr program: first, contributing timely genomic data for the SARS-CoV-2 pandemic response, and second, establishing both capacity and best practices for culture-independent, population-level environmental surveillance for other pathogens of interest to the FDA. IMPORTANCE This paper serves two primary objectives. First, it summarizes the genomic and contextual data collected during a Covid-19 pandemic response project, which utilized the FDA’s laboratory network, traditionally employed for sequencing foodborne pathogens, for sequencing SARS-CoV-2 from wastewater samples. Second, it outlines best practices for gathering and organizing population-level next generation sequencing (NGS) data collected for culture-free, surveillance of pathogens sourced from environmental samples.

Microbiology↗

DOE OSTI2020

Distributed Intrusion Detection System using Semantic-based Rules for SCADA in Smart Grid

Cyber-physical system (CPS) security for the smart grid enables secure communication for the SCADA and wide-area measurement system data. Power utilities world-wide use various SCADA protocols, namely DNP3, Modbus, and IEC 61850, for the data exchanges across substation field devices, remote terminal units (RTUs), and control center applications. Adversaries may exploit compromised SCADA protocols for the reconnaissance, data exfiltration, vulnerability assessment, and injection of stealthy cyberattacks to affect power system operation. In this paper, we propose an efficient algorithm to generate robust rule sets. We integrate the rule sets into an intrusion detection system (IDS), which continuously monitors the DNP3 data traffic at a substation network and detects intrusions and anomalies in real-time. To enable CPS-aware wide-area situational awareness, we integrated the methodology into an open-source distributed-IDS (D-IDS) framework. The D-IDS facilitates central monitoring of the detected anomalies from the geographically distributed substations and to the control center. The proposed algorithm provides an optimal solution to detect network intrusions and abnormal behavior. Different types of IDS rules based on packet payload, packet flow, and time threshold are generated. Further, IDS testing and evaluation is performed with a set of rules in different sequences. The detection time is measured for different IDS rules, and the results are plotted. All the experiments are conducted at Power Cyber Lab, Iowa State University, for multiple power grid models. After successful testing and evaluation, knowledge and implementation are transferred to field deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Emergency Voltage Regulation in Power Systems via Ripple-Type Control: Preprint

With increasing penetration of volatile renewable generation and cyber-physical disruptions, ensuring safe operation of bulk power systems has become unprecedentedly challenging. Since communication and computational costs restrict centralized system dispatch to be called upon every few minutes; and purely local schemes are shown to be insufficient, distributed controls have been advocated for handling unanticipated system conditions in real time. However, the applicability of distributed control schemes is fundamentally limited by their need for widespread communication and model cognizance. In this con-text, we put forth a hybrid low-communication saturation-driven protocol for the coordination of control agents that are distributed over a physical system and are allowed to communicate with peers over a ‘hotline’ communication network. Under this protocol, when agents observe a constraint violation based on local measurements, they respond locally until their control resources saturate, in which case they send a beacon for assistance to peer agents. The scheme ensures that minor violations are efficiently mitigated via fast local controls, while severe violations may be handled by a collaboration of a relatively small set of agents. We evaluate the performance of this scheme via extensive numerical tests on the IEEE 14-bus test feeder, where agents act upon noisy measurements under diverse scenarios of random load variations and severe low/high voltage events.

distributed control↗

DOE OSTI2021

From CAN to ROS: A Monitoring and Data Recording Bridge

The Controller Area Network (CAN) bus protocol is used in modern vehicles for sharing messages between several control units within a vehicle. CAN bus messages are encoded with unknown scheme and decoding these messages provide unlimited access to valuable information that is used in many autonomous vehicles applications. This paper proposes a ROS based package (CAN-to-ROS) for monitoring, recording, and real-time and offline decoding of CAN bus messages. The package is developed in the ROS framework to add modularity and ease of integration with other software, and it is written in C++ to guarantee speed of the execution during run-time. For realtime decoding of CAN bus data, CAN-to-ROS package used in conjunction with other library called Libpanda that provide access to CAN bus message from a vehicle. The package was evaluated and tested on a Raspberry Pi with real CAN bus data from a Toyota RAV4. The results confirm the capabilities of CAN-to-ROS package and resulted in using the package in other research projects.

Elmadani, Safwan↗

DOE OSTI2023

Chemical abrasion: the mechanics of zircon dissolution

Chemical abrasion is a technique that combines thermal annealing and partial dissolution in hydrofluoric acid (HF) to selectively remove radiation-damaged portions of zircon crystals prior to U–Pb isotopic analysis, and it is applied ubiquitously to zircon prior to U–Pb isotope dilution thermal ionization mass spectrometry (ID-TIMS). The mechanics of zircon dissolution in HF and the impact of different leaching conditions on the zircon structure, however, are poorly resolved. We present a microstructural investigation that integrates microscale X-ray computed tomography (µCT), scanning electron microscopy, and Raman spectroscopy to evaluate zircon dissolution in HF. We show that µCT is an effective tool for imaging metamictization and complex dissolution networks in three dimensions. Acid frequently reaches crystal interiors via fractures spatially associated with radiation damage zoning and inclusions to dissolve soluble high-U zones, some inclusions, and material around fractures, leaving behind a more crystalline zircon residue. Other acid paths to crystal cores include the dissolution of surface-reaching inclusions and the percolation of acid across zones with high defect densities. In highly crystalline samples dissolution is crystallographically controlled with dissolution proceeding almost exclusively along the c axis. Increasing the leaching temperature from 180 to 210 °C results in deeper etching textures, wider acid paths, more complex internal dissolution networks, and greater volume losses. How a grain dissolves strongly depends on its initial radiation damage content and defect distribution as well as the size and position of inclusions. As such, the effectiveness of any chemical abrasion protocol for ID-TIMS U–Pb geochronology is likely sample-dependent. We also briefly discuss the implications of our findings for deep-time (U-Th)/He thermochronology.

58 GEOSCIENCES↗

DOE OSTI2024

PSInet: a new global water potential network

Abstract Given the pressing challenges posed by climate change, it is crucial to develop a deeper understanding of the impacts of escalating drought and heat stress on terrestrial ecosystems and the vital services they offer. Soil and plant water potential play a pivotal role in governing the dynamics of water within ecosystems and exert direct control over plant function and mortality risk during periods of ecological stress. However, existing observations of water potential suffer from significant limitations, including their sporadic and discontinuous nature, inconsistent representation of relevant spatio-temporal scales and numerous methodological challenges. These limitations hinder the comprehensive and synthetic research needed to enhance our conceptual understanding and predictive models of plant function and survival under limited moisture availability. In this article, we present PSInet (PSI—for the Greek letter Ψ used to denote water potential), a novel collaborative network of researchers and data, designed to bridge the current critical information gap in water potential data. The primary objectives of PSInet are as follows. (i) Establishing the first openly accessible global database for time series of plant and soil water potential measurements, while providing important linkages with other relevant observation networks. (ii) Fostering an inclusive and diverse collaborative environment for all scientists studying water potential in various stages of their careers. (iii) Standardizing methodologies, processing and interpretation of water potential data through the engagement of a global community of scientists, facilitated by the dissemination of standardized protocols, best practices and early career training opportunities. (iv) Facilitating the use of the PSInet database for synthesizing knowledge and addressing prominent gaps in our understanding of plants’ physiological responses to various environmental stressors. The PSInet initiative is integral to meeting the fundamental research challenge of discerning which plant species will thrive and which will be vulnerable in a world undergoing rapid warming and increasing aridification.

Forestry↗

DOE OSTI2022

Entanglement Purification and Protection in a Superconducting Quantum Network

High-fidelity quantum entanglement is a key resource for quantum communication and distributed quantum computing, enabling quantum state teleportation, dense coding, and quantum encryption. Any sources of decoherence in the communication channel, however, degrade entanglement fidelity, thereby increasing the error rates of entangled state protocols. Entanglement purification provides a method to alleviate these nonidealities by distilling impure states into higher-fidelity entangled states. In this work, we demonstrate the entanglement purification of Bell pairs shared between two remote superconducting quantum nodes connected by a moderately lossy, 1-meter long superconducting communication cable. We use a purification process to correct the dominant amplitude damping errors caused by transmission through the cable, with fractional increases in fidelity as large as 25%, achieved for higher damping errors. The best final fidelity the purification achieves is 94.09 ± 0.98%. In addition, we use both dynamical decoupling and Rabi driving to protect the entangled states from local noise, increasing the effective qubit dephasing time by a factor of 4, from 3 to 12 μs. These methods demonstrate the potential for the generation and preservation of very high-fidelity entanglement in a superconducting quantum communication network.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Light storage, retrieval, and controllable interference in an atomic tripod system

Highly efficient quantum memories are essential for advancing quantum information processing technologies, including scalable quantum computing and quantum networks. We experimentally demonstrate a light storage and retrieval protocol in a tripod system using an ensemble of laser-cooled 87 Rb atoms. The tripod system, which consists of three ground states and an excited state, offers rich dynamics: its use to coherently store and retrieve a weak probe pulse in the 87 Rb 𝐹 = 1 ground-state manifold leads to the interference of two spin-wave excitations during storage time that translate to an interference in the peak intensity of the retrieved probe pulse. Our work shows that these interferences, which manifest when varying the pulse sequence or energy level structure, can be controlled experimentally by varying the storage time, optical phase, and magnetic field strength. Theoretical simulations exhibit excellent agreement with the experimental results. In conclusion, this work demonstrates the rich dynamics and versatile capabilities of atomic tripod systems for light storage and retrieval, with key advantages over conventional Λ systems, highlighting the potential of atomic tripod systems for applications in quantum information processing, quantum synchronization, and atomic memory protocols.

Coherent control↗

DOE OSTI2025

MSU IETC ML for Modbus (AN EDGE)

This study explores machine learning for decoding Modbus RTU data using K-Nearest Neighbors (KNN) models. An initial KNN model trained on 8,000 packets achieved 95.15% accuracy. Although ML improves generalization, accuracy still falls short of deterministic methods. These findings have implications for Modbus traffic analysis, intrusion detection in industrial networks, and adaptive error correction in real-time monitoring systems. By refining ML-based decoding, future work could enable more efficient anomaly detection and predictive maintenance in industrial automation and cybersecurity applications.

Communication Protocol↗

DOE OSTI2022

Optimization of Water-Alternating-CO2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

Summary This paper will present a robust workflow to address multiobjective optimization (MOO) of carbon dioxide (CO2)-enhanced oil recovery (EOR)-sequestration projects with a large number of operational control parameters. Farnsworth unit (FWU) field, a mature oil reservoir undergoing CO2 alternating water injection (CO2-WAG) EOR, will be used as a field case to validate the proposed optimization protocol. The expected outcome of this work would be a repository of Pareto-optimal solutions of multiple objective functions, including oil recovery, carbon storage volume, and project economics. FWU’s numerical model is used to demonstrate the proposed optimization workflow. Because using MOO requires computationally intensive procedures, machine-learning-based proxies are introduced to substitute for the high-fidelity model, thus reducing the total computation overhead. The vector machine regression combined with the Gaussian kernel (Gaussian-SVR) is used to construct proxies. An iterative self-adjusting process prepares the training knowledge base to develop robust proxies and minimizes computational time. The proxies’ hyperparameters will be optimally designed using Bayesian optimization to achieve better generalization performance. Trained proxies will be coupled with multiobjective particle swarm Optimization (MOPSO) protocol to construct the Pareto-front solution repository. The outcomes of this workflow will be a repository containing Pareto-optimal solutions of multiple objectives considered in the CO2-WAG project. The proposed optimization workflow will be compared with another established methodology using a multilayer neural network (MLNN) to validate its feasibility in handling MOO with a large number of parameters to control. Optimization parameters used include operational variables that might be used to control the CO2-WAG process, such as the duration of the water/gas injection period, producer bottomhole pressure (BHP) control, and water injection rate of each well included in the numerical model. It is proved that the workflow coupling Gaussian-SVR proxies and the iterative self-adjusting protocol is more computationally efficient. The MOO process is made more rapid by squeezing the size of the required training knowledge base while maintaining the high accuracy of the optimized results. The outcomes of the optimization study show promising results in successfully establishing the solution repository considering multiple objective functions. Results are also verified by validating the Pareto fronts with simulation results using obtained optimized control parameters. The outcome from this work could provide field operators an opportunity to design a CO2-WAG project using as many inputs as possible from the reservoir models. The proposed work introduces a novel concept that couples Gaussian-SVR proxies with a self-adjusting protocol to increase the computational efficiency of the proposed workflow and to guarantee the high accuracy of the obtained optimized results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO2-WAG process, which greatly extends its utility in solving large-scale MOO problems in various projects with similar desired outcomes.

Energy & Fuels↗

DOE OSTI2025

Optimized V1G and V2G Electric Vehicle Fleet Management and Grid Transaction at Marine Corps Air Station Miramar in San Diego, CA

The overall technical goal of the project was to demonstrate an all-electric bi-directional non-tactical fleet at Marine Corps Air Station (MCAS) Miramar that was integrated and controlled with other distributed energy resources (DERs) (i.e., PV, stationary battery, and building loads) to provide resilience to critical electric loads in the event of grid outages, to minimize charging costs, and to provide economic energy resources to electricity markets. In this project, the specific, technical objectives were: 1. Demonstrate that bi-directional electric vehicles can provide critical complementary services to fixed storage batteries in microgrid applications while performing function as non-tactical vehicles. 2. Demonstrate participation of bi-directional (V2G) and unidirectional (V1G) PEVs for demand management and minimization of charging costs. 3. Demonstrate integration of multiple DERs for grid service participation. US Marine Corps Air Station (MCAS) Miramar in San Diego was the site of this electric vehicle-to-microgrid-utility grid test and demonstration project. Existing microgrid assets in this study included (1) a public works building; (2) a 30-kW rooftop photovoltaic (PV) system and (3) a separate 250 kW carport PV system. In this project, six bi-directional V2G vans were located at the MCAS Miramar’s showcase building-scale microgrid to develop and test technical capabilities that V2G can provide in microgrid applications (e.g., cost reduction and resiliency). These resources provided aggregated demand management and simulated participation in current retail DR programs. The vehicles used in this demonstration were selected because they provided functionality that MCAS Miramar needed, 15 passenger transport and facilities work cargo carrying capacity, and bi-directional charging capability that the research project required. All vehicles in this study were manufactured and distributed by VIA Motors, Inc. There were six vehicles total and each was VIA’s VTRUX eREV V2G model, a modified General Motors Chevrolet 2500 2WD van. Three of the vans were configured as passenger vans and the other three were configured as cargo vans. Each van had an on-board bi-direcrtional inverter/charger, Bel Power Solutions model 350INVCHGT150-120-240-8G nominally rated at +/-15 kW. The VIA van’s charging connector follows the J1772 charging protocol. The bi-directional EVSEs demonstrated in this study were manufactured by Coritech, Inc. Each VGI-80-AC charging station enabled enhanced V2G charging capability to a Clipper Creek CS-100 charging module. The enhanced capabilities included ethernet communication following the SEP2.0 protocol with a distributed energy resource function set and an operator screen displaying real-time SOC, voltage, and current. The VGI-80-AC charging stations are classified as level 2 with a maximum current output of 80 A or effectively 19 kW. The VIA van’s onboard charger limited the charging and discharging power to 15 kW in each direction. A control computer was installed in the EWOC and connected to an existing monitor. The V2G control communication network was a completely stand-alone closed system that did not have any connection to any other networks on the base. A cybersecure remote communication connection was created with a cellular modem, firewall hardware, and a virtual private network configuration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Sap Velocity Data for Urban Trees in Chicago, Illinois (2024-2025)

This dataset contains uncorrected sap velocity measurements using the heat ratio method (HRM) collected using ICT International SFM1x sensors at five urban sites in Chicago, Illinois, as part of the DOE CROCUS project. The data includes continuous monitoring of sap velocity from various tree species, including Maples (Acer spp.): Sugar Maple (Acer saccharum), Silver Maple (Acer saccharinum), and Red Maple (Acer rubrum); Oaks (Quercus spp.): Swamp White Oak (Quercus bicolor); American Elm (Ulmus americana); Honey Locust (Gleditsia triacanthos); Cottonwood (Populus deltoides); and Tree of Heaven (Ailanthus altissima) across Chicago State University (CSU), Northeastern Illinois University (NEIU), Northwestern University (NU), University of Illinois Chicago (UIC), and West Woodlawn "Blacks in Green" (BIG). These include both street trees and those in urban park locations. Measurements were collected at 15-20 minute intervals, depending on the sensor, and transmitted via Long Range Wide Area Network (LoRaWAN) protocols. The wireless data was collected by Sage Network (https://sagecontinuum.org/) nodes. The dataset includes sensor ID, Global Positioning System (GPS) coordinates, tree species (common and scientific names), tree identification number, diameter at breast height (DBH in cm), uncorrected sap velocity measurements (cm/hr) from both inner and outer probes, and Sage Node identifiers so the data can be mapped to related variables such as air quality and wind speed that were collected on the Sage nodes. All timestamps are in local Chicago time (CDT/CST). Quality control flags are provided using a 3-bit binary system indicating physical range violations (< -10 or > 60 cm/hr), step spikes (absolute difference > 36 cm/hr), and stuck sensor conditions (> 10 consecutive identical values). These are raw data, not corrected for wood anatomy or species-specific characteristics. Data is provided in comma separated (CSV) format. This dataset is part of a larger collection of CROCUS environmental monitoring data, including linked datasets from Air Quality Transmitter (AQT) sensors, Weather Transmitter (WXT) sensors, and Multi-Function Research LoRaWAN (MFR) Nodes. DOIs for the supporting data are provided as part of this data package.

Chicago↗