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This dataset contains survey, navigation, and platform-design data supporting instrument deployment and positioning during the 2016-2017 RODEO field operations at Block Island. It includes an acoustic localization software toolkit and its Block Island position solutions, R/V Tioga ship navigation and underway data, CTD casts, ship-track charts, and engineering designs for the deployed moorings and arrays.
Integrated instrumentation packages are an attractive option for environmental and ecological monitoring at marine energy sites, as they can support a range of sensors in a form factor compact enough for the operational constraints posed by energetic waves and currents. Here we present details of the architecture and performance for one such system—the Adaptable Monitoring Package—which supports active acoustic, passive acoustic, and optical sensing to quantify the physical environment and animal presence at marine energy sites. we describe cabled and autonomous deployments and contrast the relatively limited system capabilities in an autonomous operating mode with more expansive capabilities, including real-time data processing, afforded by shore power or in situ power harvesting from waves. Across these deployments, we describe sensor performance, outcomes for biological target classification algorithms using data from multibeam sonars and optical cameras, and the effectiveness of measures to limit biofouling and corrosion. On the basis of these experiences, we discuss the demonstrated requirements for integrated instrumentation, possible operational concepts for monitoring the environmental and ecological effects of marine energy converters using such systems, and the engineering trade-offs inherent in their development. Overall, we find that integrated instrumentation can provide powerful capabilities for observing rare events, managing the volume of data collected, and mitigating potential bias to marine animal behavior. These capabilities may be as relevant to the broader oceanographic community as they are to the emerging marine energy sector.
We present field deployment results of a portable optical absorption spectrometer for localization and quantification of fugitive methane (CH 4 ) emissions. Our near-infrared sensor targets the 2$ν_3$ R(4) CH 4 transition at 6057.1 cm −1 (1651 nm) via line-scanned tunable diode-laser absorption spectroscopy (TDLAS), with Allan deviation analysis yielding a normalized 2.0 ppmv∙Hz −1/2 sensitivity (4.5 × 10 −6 Hz −1/2 noise-equivalent absorption) over 5 cm open-path length. Controlled CH 4 leak experiments are performed at the METEC CSU engineering facility, where concurrent deployment of our TDLAS and a customized volatile organic compound (VOC) sensor demonstrates good linear correlation (R 2 = 0.74) over high-flow (>60 SCFH) CH 4 releases spanning 4.4 h. In conjunction with simultaneous wind velocity measurements, the leak angle-of-arrival (AOA) is ascertained via correlation of CH 4 concentration and wind angle, demonstrating the efficacy of single-sensor line-of-sight (LOS) determination of leak sources. Finally, source magnitude estimation based on a Gaussian plume model is demonstrated, with good correspondence (R 2 = 0.74) between calculated and measured release rates.
Camera-based wildlife monitoring is often overwhelmed by non-target triggers and slowed by manual review or cloud-dependent inference, which can prevent timely intervention for high stakes human–wildlife conflicts. Our key contribution is a deployable, fully offline edge vision sensor that achieves near-real-time, highly accurate wildlife event classification by combining detector-based empty-image suppression with a lightweight classifier trained with a staged transfer-learning curriculum. Specifically, Stage 1 uses a pretrained You Only Look Once (YOLO)-family detector for permissive animal localization and empty-trigger suppression, and Stage 2 uses a lightweight EfficientNet-based binary classifier to confirm puma on detector crops and gate downstream actions. Our design is robust to low-quality nighttime monochrome imagery (motion blur, low contrast, illumination artifacts, and partial-body captures) and operates using commercially available components in connectivity-limited settings. In field deployments running since May 2025, end-to-end latency from camera trigger to action command is approximately 4 s. Ablation studies using a dataset of labeled wildlife images (pumas, not pumas) show that the two-stage approach substantially reduces false alarms in identifying pumas relative to a full-image classifier while maintaining high recall. On the held-out test set (N = 1434 events), the proposed two-stage cascade achieves precision 0.983, recall 0.975, F1 0.979, accuracy 0.986, and balanced accuracy 0.983, with only 8 false positives and 12 false negatives. The system can be easily adapted for other species, as demonstrated by rapid retraining of the second stage to classify ringtails. Downstream responses (e.g., notifications and optional audio/light outputs) provide flexible actuation capabilities that can be configured to support intervention.
Global interest in mitigating climate change effects is a driver for the development of renewable energy sources. In-stream tidal power, a type of marine hydrokinetic (MHK) energy uses tidal currents to generate electricity and is one example of developing a renewable energy industry. Effects and impacts on fishes in areas of tidal power development are a consideration, and presently there are many unanswered questions in this field of research. Knowledge of how fish use these areas before and after device installation is essential to informing regulators for decision-making. We attempted a Before-After-Control-Impact (BACI) study design to compare an index of fish density near and away from an MHK tidal energy device deployed in Cobscook Bay, Maine. The index was mean volume backscattering strength (Sv) obtained from 24-hour stationary, down-looking hydroacoustic surveys. Data were collected several times per year at an “impact” site within 50–75 m of a device and at a “control” site approximately 1.6 km away, both before and after turbine installation in August 2012. Fish density was lowest in March surveys and highest in May surveys at both sites. One of four comparisons (August 2011/before vs. 2012/after) indicated an interaction of fish density with turbine installation. Operational status of the installed turbine and on-water activity disturbances (e.g., industry vessel and diving activities) varied at the impact site and possibly influenced results. Lower fish densities were observed during installation and maintenance periods than during normal device operation. The effects of construction activities must be separated from the effects of a deployed device to effectively implement a statistically rigorous assessment that could separate the effects of these different activities. This parsimonious approach and results were used for permit licensing by federal and state regulatory bodies at this site and others and can be used to consider regulatory adjustments during different phases of device operation and maintenance.
Abstract We present a scalable, cloud-based science platform solution designed to enable next-to-the-data analyses of terabyte-scale astronomical tabular data sets. The presented platform is built on Amazon Web Services (over Kubernetes and S3 abstraction layers), utilizes Apache Spark and the Astronomy eXtensions for Spark for parallel data analysis and manipulation, and provides the familiar JupyterHub web-accessible front end for user access. We outline the architecture of the analysis platform, provide implementation details and rationale for (and against) technology choices, verify scalability through strong and weak scaling tests, and demonstrate usability through an example science analysis of data from the Zwicky Transient Facility’s 1Bn+ light-curve catalog. Furthermore, we show how this system enables an end user to iteratively build analyses (in Python) that transparently scale processing with no need for end-user interaction. The system is designed to be deployable by astronomers with moderate cloud engineering knowledge, or (ideally) IT groups. Over the past 3 yr, it has been utilized to build science platforms for the DiRAC Institute, the ZTF partnership, the LSST Solar System Science Collaboration, and the LSST Interdisciplinary Network for Collaboration and Computing, as well as for numerous short-term events (with over 100 simultaneous users). In a live demo instance, the deployment scripts, source code, and cost calculators are accessible. 4 4 http://hub.astronomycommons.org/
The disparate characteristics between conventional (CVs) and battery electric vehicles (BEVs) in terms of driving range, refill/recharge time, and availability of refuel/recharge infrastructure inherently limit the relative utility of BEVs when benchmarked against traditional driver travel patterns. However, given a high penetration of high-power public charging combined with driver tolerance for rerouting travel to facilitate charging on long-distance trips, the difference in utility between CVs and BEVs could be marginalized. We quantify the relationships between BEV utility, the deployment of fast chargers, and driver tolerance for rerouting travel and extending travel durations by simulating BEVs operated over real-world travel patterns using the National Renewable Energy Laboratory's Battery Lifetime Analysis and Simulation Tool for Vehicles (BLAST-V). With support from the U.S. Department of Energy's Vehicle Technologies Office, BLAST-V has been developed to include algorithms for estimating the available range of BEVs prior to the start of trips, for rerouting baseline travel to utilize public charging infrastructure when necessary, and for making driver travel decisions for those trips in the presence of available public charging infrastructure, all while conducting advanced vehicle simulations that account for battery electrical, thermal, and degradation response. Results from BLAST-V simulations on vehicle utility, frequency of inserted stops, duration of charging events, and additional time and distance necessary for rerouting travel are presented to illustrate how BEV utility and travel patterns can be affected by various fast charge deployments.
ObjectiveOur goal is to develop deployable strategies for infectious disease diagnosis at the point-of-care that are applicable to multiple hosts of infection - conforming to the global One Health Strategy for diagnostics. We aim to develop methods that do not require prior knowledge of the pathogen in question, and can facilitate rapid and effective decision-making and situational awareness.IntroductionThere is an urgent need for diagnostic strategies for infections which are host-independent, so as to effectively track zoonotic spread, monitor animal carriers of pathogens, and evaluate transmission dynamics. Infection of a host - pathogen or human- by an animal results in recognition by the immune response, which consequently causes release of inflammatory mediators. Many scientists have explored the use of cytokines as diagnostic indicators of disease, but the conserved nature of the immune response in humans and animals results in cross-reactivity among many pathogens, making evaluation of the results difficult, especially in high disease burden populations. Measuring the pathogen-specific signature, however, is advantageous - as it offers discrete identification of active infection, and discrimination from exposure. It also offers a universal strategy that can be applied to human and animal hosts of infection - allowing for One Health Biosurveillance. Achieving this, however, requires the development of a) tailored strategies for the measurement of biochemically disparate pathogen signatures in clinical samples and b) ultra-sensitive detection of such signatures in the host. The sensor team at Los Alamos National Laboratory is working on both of these aspects, and the development of One Health Diagnostic platforms, the focus of the work presented here.MethodsMany of the biomarkers secreted by bacterial pathogens and recognized by innate immune receptors elicit host cytokine responses that are amphiphilic (largely glycolipids, lipoproteins or lipoglycans). Based on such, our team has developed tailored methods – membrane insertion and lipoprotein capture for the capture and detection of these greasy and stealthy molecules in infected blood. Sensitivity and specificity, assay optimization, alinearity associated with lipidic molecules and assay parameter development for biomarkers associated with bacterial pathogens will be presented. Considerations for clinical sampling for amphiphile detection in blood, and clinical study design will be demonstrated. Our team has developed an ultra-sensitive biosensor for detection of biomarkers in complex matrices based on the evanescent field properties of single mode planar optical waveguides. Detection of amphiphilic biomarkers in clinical samples, using the waveguide-based biosensor and tailored methods for the detection of such molecules has allowed for the diagnosis of infection in both human and animals hosts. Herein, we present two examples of the same; 1) diagnosis of tuberculosis in humans, cattle and badgers using pathogen-based diagnostic strategies; and 2) detection of Gram-negative Lipopolysacharides in beef and in patients with Salmonella-induced sepsis.ResultsWe have developed tailored ultra-sensitive waveguide-biosensor assays for the detection of Lipoarabinomannan (and other biomarkers) from Mycobacteria and demonstrated feasibility in blinded clinical studies in humans and cattle, demonstrating one -health compatibility.We have also demonstrated detection of lipopolysacharides from eight different serotypes of Shiga-toxin carrying E. coli in beef, and Salmonella Typhimurium in pediatric patients using the same approach.ConclusionsWe have demonstrated clinical feasibility of a One Health Strategy for point-of-care diagnostics of bacterial infections in blood for tuberculosis and Gram-negative pathogens in clinical samples. The results will be demonstrated with several discussion points on the consideration of unconventional biochemistry of pathogens for diagnostics, factors influencing point-of-care deployment and integration of diagnostic platforms for biosurveillance. One Health Considerations and challenges therein will also merit discussion.ReferencesSakamuri, R; et al. Accurate Tracking of Bovine Tuberculosis Biomarkers in Infected Cattle using a Novel Biomarker Capture Strategy, Analytical Sciences, 33(4): 457-460, 2017.Noormohammed A et al. Detection of Salmonella LPS in Patient blood by Lipoprotein Capture. Proc. SPIE 10072, Optical Diagnostics and Sensing XVII: Toward Point-of-Care Diagnostics, 100720A , 2017. doi:10.1117/12.2253506Stromberg L et al. Membrane Insertion for the Detection of Lipopolysaccharides: Exploring the Dynamics of Amphiphile-in-Lipid Assays, PloS One, April 2016.Sakamuri RM et al. Association of lipoarabinomannan with high density lipoprotein in blood: implications for diagnostics.Tuberculosis (Edinb). 2013 May;93(3):301-7. doi: 10.1016/j.tube.2013.02.015. Epub 2013 Mar 16Mukundan H et al. Understanding the interaction of Lipoarabinomannan with membrane mimetic architectures. Tuberculosis, 92(1) 32-47, 2012.Mukundan H et al., Waveguide-based Sensors for Pathogen Detection, Invited Review, Sensors, 9(7), 5783-5809.
Electricity load forecasting for buildings and campuses is becoming increasingly important as the penetration of distributed energy resources (DERs) grows. Efficient operation and dispatch of DERs require reasonably accurate predictions of future energy consumption in order to conduct near-real-time optimized dispatch of on-site generation and storage assets. Electric utilities have traditionally performed load forecasting for load pockets spanning large geographic areas, and therefore, forecasting has not been a common practice by buildings and campus operators. Given the growing trends of research and prototyping in the grid-interactive efficient buildings domain, characteristics beyond simple algorithm forecast accuracy are important in determining the algorithm's true utility for smart buildings. Other characteristics include the overall design of the deployed architecture and the operational efficiency of the forecasting system. In this work, we present a deep-learning-based load forecasting system that predicts the building load at 1-hour intervals for 18 hours in the future. We also discuss challenges associated with the real-time deployment of such systems as well as the research opportunities presented by a fully functional forecasting system that has been developed within the National Renewable Energy Laboratory's Intelligent Campus program.
The Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC) was developed by the National Laboratory of the Rockies as a modular platform for advancing wave-powered desalination technologies. Designed to operate in either a hydraulic or electric configuration, the system enables direct comparison of mechanical-to-water and electrical-to-water conversion pathways using a single hardware architecture. Deployments in 2022 and 2024 at the Jennette's Pier test site in North Carolina demonstrated freshwater production between 60 and 300 gallons per day, including successful operation in wave heights as low as 0.25 m. A structured evaluation approach combining numerical modeling of hydrodynamic and power take-off response, controlled laboratory testing, and in-ocean field deployments has been used to characterize and refine system performance. Specifically, insights from these efforts are now informing the second-generation HERO WEC (V2) to increase robustness and overall survivability. Changes from the original prototype include improved drivetrain components, refined geometry, enhanced control systems, and design. The HERO WEC platform continues to serve as an open-access research asset supporting broader marine energy and desalination development.
Developing methods for rapid, large-scale deployment of carbon capture systems is critical for meeting climate change goals. Optimization-based decisions can be employed at the design and manufacturing phases to minimize costs of deployment and operation. Manufacturing standardization results in significant cost savings due to economies of numbers. Building off previous work, we present a process family design approach to design a set of carbon capture systems while explicitly including economies of numbers savings within the formulation. Our formulation optimizes both the number and characteristics of the common components in the platform and simultaneously designs the resulting set of carbon capture systems. Savings from economies of numbers are explicitly included in the formulation to determine the number of components in the platform. We show and discuss the savings we gain from economies of numbers.
Deployment studies of a dynamically and elastically scaled model of an inflatable parawing, deployed from a capsule mounted with rotational freedom in a wind tunnel
An apparatus was developed for thermal distortion measurements on deployable boom structures. The calibration procedure and thermal static bending plus twist measurements are considered. The thermal mechanics test facility is described. A table is presented for several examples of spacecraft applications of thermal static distortion measurements on 3-m deployable booms.
Quantitative analyses were developed to the point where numerical results can be easily obtained in the optimal transfer trajectory problem. Analyses of deployment dynamics and control of the paired satellite concept are progressing. Automatic control in space, optimal retrieval transfer trajectories, deployment attitude dynamics and control, and automatic control systems for retrieval are also considered.
A unique deployable boom developed for accurately positioning magnetometers 6 meters (19.7 feet) from a spacecraft is described. Weight, mounting system, magnetic cleanliness, thermal dimensional stability, and natural frequency were critical constraints that were met. The boom was flown on Mariner 10 and deployed flawlessly. The design, development, and testing of the boom and optical alignment of the sensors are described. Design trades and problem solutions are discussed.
Meaningful magnetic field vector measurements in space require accurate placement of a magnetometer beyond the magnetic fields of a spacecraft. The design and development of a deployable boom is described which ensures accurate deployment of an instrument package and maintains high stability after extension.
An experiment designed to use the Space Shuttle in tests of the mechanical and electrical properties of spaceborne deployable antennas under zero-gravity conditions is outlined. Space-erectable 20-meter diameter phased arrays or reflector/feed systems, and self-deploying mechanisms, are to be tested. Reflector surface integrity will be tested by an AM laser technique, and electrical behavior will be tested by a spin-stabilized RF beacon injected into orbit prior to unfurlment of the antenna. Focusing and gain measurements, static pattern measurements, dynamic RF gain measurements, and measurements of cross-polarized signals will be conducted, and the reflector will be illuminated by separate feeds for the S-, X-, and K-bands. Mechanical features of the mesh-wrapped rib furlable antenna design are described.
Theoretical analysis and experimental investigations are presented for two deployment concepts of the drogue parachute deployment for the space shuttle solid rocket booster. The analysis represents the motion of three coupled rigid bodies, with one of the bodies having variable mass and moment of inertia. The unfurling process of the parachute from the bag is idealized as the flow of a continuum out of a control surface. The pilot parachute or tethered nose cap is modeled as a flexible pendulum with a nonlinear spring and a moving support. Measured wind tunnel test data compare reasonably well with the theory.