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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Maturing Rational Design Methodologies and Industry Consensus Engineering Standards: Critical Fastened Joints - Solar PV Industry

Critical structural joints can be seen throughout a solar array and are called upon to secure modules and keep racking assembled and able to resist large demands from winds and snow loads. In the relatively new and fast-growing solar PV industry, the important role these hardware assemblies (e.g. clips, clamps, bolts, nuts, washers) play is not well understood by product designers. Failures with critical structural joints are surprisingly common and point to the need for maturing the engineering and assembly of these joints. The wide variety of design concepts (Figure 2&2) demonstrate interesting and innovative ideas but are lacking the basics of fastener engineering seen in matured industries (e.g. transportation, buildings). Complicating the maturing process for critical structural joints is that they are one component in rack supporting structures that exhibits a systems behavior; each component will affect the other and play a key role in maintaining structural integrity. When wind loads the surface of a module, the underlying racking members deflect and twist which in turn imparts forces back into the joints and into the mounted modules. Often, these supporting rack structures exhibit high deflections and low natural frequencies which amplify the demands placed into the joints even in moderate winds. Current engineering practices and associated structural conventions view solar racking support structures as they would a high mass building that exhibit more static behaviors in wind events. Solar structures are unique from high mass buildings and require the development of solar specific industry engineering consensus standards.

14 SOLAR ENERGY↗
DOE OSTI2021

High Force Spring Clamp System

This is the Final Technical Report for the work by Hyperboloid LLC using SBIR Grant # DE-SC0019579. The work responded to US DOE SBIR Topics FY2019, Phase 1, Release 1, August 13 2018, Topic: 30. a. (2) SRF cavity joining techniques that create vacuum seals without resorting to the use of bolted flanges in order to minimize particulates. Hyperboloid LLC designed, developed and tested the High Force Spring Clamp System characterized in Patent US 9756715 that is aimed at solving this topic. The patent is held by Thomas Jefferson National Accelerator Facility. The flange bolts are substituted with exceptionally high force, binder-clip-like “C” Clamps. The clamps are opened and applied by hydraulic based tooling called “Clamp Openers” using particle minimization methods. Model 1 Clamp reached the goal of sealing the SRF industry standard hexagonal section, aluminum alloy gasket, leak-free on a research cavity as determined by a superfluid helium challenge, at 2 K for 2 assembly cycles. Descriptions include the ANSYS calculations that determine the size and shape of the clamp, the details of the Clamp Opener construction, particle counts from sealing flanges using both bolts and clamps. Model 2 Clamp, at half the size, needing a softer metallic gasket to be successful, is more readily adaptable to Cryomodule designs. It was tested, but a needs soft gasket development to be successful.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Deep Learning Systems for Increased Safeguards Surveillance Review Productivity

Nuclear safeguards inspectors expend significant time and maintain intense focus in reviewing video surveillance for safeguards relevant events. To increase efficiency and reduce the time burden of safeguards inspectors performing surveillance data review, this paper presents a novel deep learning (DL) systems concept to integrate generalized DL models into the safeguards surveillance review workflow. The Agency is investigating several DL algorithms for object recognition, localization, tracking, and flagging relevant activities. The project team is working closely with nuclear safeguards inspectors to identify review use cases (based on specific safeguards objectives) and collect their associated requirements. We focused on CANDU and LWR Nuclear Power Plants (NPPs) and their associated dry storage areas as these present a particularly heavy burden on the inspector surveillance review process due to the number of these facilities under safeguards worldwide. Initial DL algorithm results on safeguards data are promising. Using a convolutional neural network, the team attained a mean average precision (mAP) of 92.9% identifying and localizing spent fuel (SF) casks from a 475 surveillance image dataset. Further, the team had initial success in training a recurrent neural network to identify reactor area activities in video clips, successfully indicating when SF casks enter or exit a pool. We discuss how such DL algorithms would be integrated into the Next Generation Surveillance Review (NGSR) software application. Another issue impacting review productivity is the long time inspectors may have to wait when running these algorithms in NGSR. We present a concept to pre-process remotely collected surveillance data with DL models as the data arrives to IAEA headquarters so that results are already available when starting a new review in NGSR. The proposed DL system concept shows a pathway and workflow for increasing an inspector’s surveillance review productivity by quickly and accurately identifying declared and undeclared safeguards relevant objects and activities in large quantities of surveillance imagery data.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Tailored Fiber Placement for Complex Preforms

Tailored Fiber Placement (TFP) offers a novel approach to optimize fiber architecture for the fabrication of complex, structural parts not traditionally suitable for advanced composites. This technology not only offers new routes for weight reduction via metal substitution, it also offers cost reduction through minimization of material scrap and reduced labor. This reduction in component weight leads to increased fuel efficiency, and reduced production energy consumption, thereby, helping to achieve the stated IACMI technical goals. This technology leverages centuries of manufacturing development in support of the textile and embroidery industry. One major drawback to this technology is the lack of commercial or non- proprietary structural performance data and robust analytical tools used to optimize fiber architecture and predict performance. This project was structured to utilize common sub-element features to validate analytical performance tools, generate performance data, and gather cost and performance data on components of interest. This project was designed to give industry sponsors the confidence and ability to take full advantage of TFP to fabricate primary, highly loaded structure and integrate features such as metallic fasteners. The project focused principally on the use of high strength carbon fiber, such as T700, and the use of aerospace epoxy resin matrix to primarily support development of new composite applications in vehicle, aerospace, and industrial markets. This project applied previously developed analytical tools to predict the performance of TFP produced parts. This work focused on developing the pipeline to characterize material in order to accurately predict component performance when modifying the TFP print paths and stitch density. This focused on experimental characterization via standardized ASTM testing, alongside experimental testing of more representative service components by testing curved beam strength, beam shear performance, a large scale TFP lug, and ultimately designing a fully TFP clip bracket that reduced weight and cost compared to a traditional metallic component. The new knowledge gained from this program included: 1) development and demonstration of novel analytical tools applied to analysis of TFP preforms; 2) development and demonstration of a building block approach using coupons and sub-elements to optimize the design of a more complex component; 3) demonstration that optimized fiber orientation using TFP can exceed performance of conventional textile composite materials and can open new applications currently limited to metallic components; 4) Demonstration of performance and cost benefits of the TFP process as compared to metallic and conventional textile composites. Recommendations for follow-on work include development of design allowables to assess the impact of high temperature/moisture exposure or saturation during loading, tracking the impact of stitching needle wear on the performance of parts and ability to stitch thicker preforms, using TFP preforms as local reinforcement at areas of bearing or complex loading, and topology optimization of components by tow steering. The expertise developed during the course of this project can be leveraged to provide commercial engineering design and fabrication services using TFP. UDRI is in the process of formalizing their partnership with Spintech, who will serve as the commercialization partner for this technology and provide molding services and deliver finished components to the end user. UDRI will continue to produce the preforms until the economics allow Spintech to procure its own TFP equipment or lease UDRI equipment, at which point UDRI will step away from manufacture and serve as the engineering and design lead on product development.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep Learning for Fish Identification from Sonar Data: CRADA 481 [Abstract only]

To help solve the challenges of hydropower energy production related to the potential for eel injury and mortality from passage through hydropower turbines, we will develop a deep learning method for identifying migrating eels from imaging sonar. This project continues with a prior project conducted by the Pacific Northwest National Laboratory (PNNL) and the Electric Power Research Institute (EPRI) in FY2018-2019. The proposed method employs Convolution Neural Network (CNN), a powerful deep learning method for image classification, to distinguish between images of eels and non-eel moving objects. We propose to collect more laboratory data and add more existing field data to train a powerful deep learning model. In addition to eels and sticks as classified in previous studies, we will add images containing several non-eel fish species and macrophyte mats to the training data. A multi-class classification model will be developed to distinguish these objects. Object detection algorithm will be explored and developed to locate and identify multiple objects in each sonar frame. Motion analysis will be performed to track the movement of objects in sonar video clips. We will also improve the data conversion algorithm so that it can read in both DIDSON and ARIS (both are imaging sonars developed by Sound Metrics Corp) data files and convert them to images with comparably high resolution, regardless of the varying detection ranges in different environments. The developed algorithms will be packaged as a software with a graphic user interface. The software will be evaluated by external collaborators in the field. The developed framework can be generalized for automatic monitoring of fish passage and migration using other imaging sonars like ARIS and will benefit the design and operation of ecologically friendly hydroelectric projects. The developed wavelet and CNN model configuration parameters can potentially be transferred to lamprey detection in similar riverine environments.

13 HYDRO ENERGY↗
DOE OSTI2022

The Roles and Impacts of PV-Battery Hybrids in a Decarbonized U.S. Electricity Supply

In this paper, we explore the potential impacts of growing industry interest in hybrid systems comprising PV and battery technologies on the results and findings of the Solar Futures Study (DOE 2021). We employ similar scenario definitions in the same ReEDS capacity expansion model, but we perform two versions of each scenario: one in which PV and battery technologies must be deployed separately (No Hybrids), and one in which the model has the option of deploying them together as PVB hybrids (With Hybrids). By comparing the No Hybrids and With Hybrids versions of each scenario, we isolate the impacts of hybridization on the outcomes and findings of the Solar Futures Study. We find that PVB hybrid configurations capture a sizable share of PV deployment, and the highest-net-value PVB hybrid configuration depends strongly on policy conditions. A power sector decarbonization policy generally increases the value proposition of a more forward-looking PVB hybrid configuration that involves significant oversizing of the PV arrays, a larger battery (which facilitates greater recovery and utilization of otherwise clipped energy), and a higher capacity factor. The growing deployment of PVB hybrid configurations primarily displaces standalone PV capacity, such that total installed PV capacity is largely unaffected by the availability of PVB hybrid configurations. However, the higher capacity factors associated with PVB hybrid configurations drive a modest (1-2 percentage point) increase in PV's share of U.S. electricity supply in 2050. Finally, introducing the PVB hybrid configurations influences the future role and makeup of battery storage technologies, and it reduces the required transmission expansion, particularly under scenarios that involve a power sector decarbonization policy.

14 SOLAR ENERGY↗
DOE OSTI2022

Coastal Acoustic Buoy for Offshore Wind: Project Synthesis

The population of North Atlantic right whales is critically endangered and their habitat overlaps with offshore windfarm leases. It is therefore imperative that effective mitigation strategies be used to avoid impacts on right whales during the construction of offshore windfarms. The Department of Energy issued FOA Number DE-FOA-0001924 to encourage the development of technology that could monitor large exclusion zones for right whales in order to mitigate potential impact of construction noise on right whales. This report summarizes the past two years of the development and evaluation of the Coastal Acoustic Buoy for Offshore Wind (CABOW) project which aimed to develop technology to monitor large exclusion zones for North Atlantic right whales. Over the course of the project SMRU Consulting have implemented a rigorous design process including comparison of different approaches (e.g., single sensor vs multiple sensors), as well as consideration of placement and timing of acoustic monitoring. We have evaluated critical components of the CABOW system including, reliability, detection range, and bearing accuracy in areas adjacent to offshore windfarm leases in Maryland by conducting 3,536 playbacks of simulated right whale upcalls. The maximum call detection range was 7.5 km when noise was 99 dB re 1µPa rms (50-225 Hz), but this reduced to < 1 km when ambient noise levels were high. Our detection probability in the field was measured as a function of range as well as the source-to-noise level ratio allowing us to build a model to predict the probability of detection under various scenarios (sample size: 3,536 calls x 5 buoys = 17,680). The median bearing error was -0.25° but this is likely an underestimate of error due to experimental design. Using the published recall and precision of the two detectors we implemented in the CABOW system, we estimate that at a recall of 80%, our precision was > 80%, within the range of what we were aiming for in this project. To estimate our exclusion zone false negative and false positive rates, we built a simulation model using the empirical data from our field trial. We modelled three to nine CABOW units placed on the 10 km exclusion zone and estimated our false negative rate to be 1% or less (which was our project goal) and our false positive rate to be between seven and nine percent, slightly above our goal of 5%. However, we also modelled an equivalent PAM system that does not have bearing capabilities and found the false positive rates for that system to be six to eight times higher than the CABOW rate. This higher false positive rate of PAM systems with low spatial information could have significant cost repercussions for offshore wind developers by adding work shutdowns or delays without providing additional protection for right whales. The model we built allows us to explore the placement of PAM systems under various scenarios and will thus help facilitate planning of PAM mitigation systems to meet NOAA Incidental Harassment Authorizations for specific windfarms. We achieved an average system uptime of 98.3%, just below our goal of 99%. The issues that caused these short losses of data have been identified and fixed. Right whale detections and audio clips were typically transferred via radio from the buoys to the base station in two to four seconds. We therefore believe we have developed a highly robust real-time PAM system. Based on the above, we feel we have achieved the stated funding goal of developing a cost-effective and robust real-time PAM system that enables the monitoring of large exclusion zones for right whales during the constructions of offshore windfarms. This should lead to decreased costs and risks for the offshore wind sector while providing robust mitigation for right whales. It is important to state that PAM mitigation will need to be implemented with other mitigation strategies (e.g., visual observers) to provide a complete mitigation strategy to ensure that any effects on right whales from offshore windfarm construction is minimized.

17 WIND ENERGY↗
DOE OSTI2023

Performance of Windows in Walls With Continuous Insulation

Window openings in walls are a significant contributor to poor thermal performance because of thermal bridging through the framing members (e.g., studs, joists, plates, bracing) and because windows lack the thermal properties of insulation. Window installation guidance for walls with continuous insulation (CI) is critical for continued market growth of this energy efficiency technology. This research project offers window manufacturers a starting point and a potential path toward developing installation instructions for windows over CI. The objectives of the research include evaluating the common method for installing windows in walls with CI, as well as establishing acceptance criteria for evaluating the performance of windows installed in walls with and without CI. The research measures: 1. The performance characteristics (e.g., water management, structural integrity) of windows in walls without CI. 2. The performance of different thicknesses and types of CI used in walls. 3. The performance of different types of window assemblies (e.g., double-hung windows, mulled double-hung windows, mulled casement windows, and slider windows) installed over CI. 4. The performance of window flange types (e.g., rigid mounting and less robust flanges) installed over CI. 5. Installing windows over CI using baseline installation instructions versus window manufacturer installation instructions. The project’s sequential testing protocol consists of the following: • A water penetration resistance testing adapted from two ASTM standards: E331 (uniform static air pressure in four steps) and E547 (cyclic static air pressure) • A temperature cycling adapted from ASTM E2264 Method B (convective hot air) • A service condition wind loading test adapted from ASTM E330 • A six-month vertical displacement observation phase prior to the structural performance testing • A final water penetration resistance test after vertical displacement observation • A structural performance test adapted from ASTM E330. Key research findings include: • The criterion for passing a water penetration resistance test is that there is no water overflowing at the interior face of the studs. If there is any bubbling or slight pooling of water at the sill, then it must recede after the pressure is removed. Excessive leakage and/or water leaking to the interior face of the framing around the window constitutes a failure. • All single double-hung windows installed directly to lumber or over oriented strand board passed all test protocols. • For most wall specimens, the test results showed that the use of foam sheathing did not affect the performance of the window for water leakage. • All wall specimens underwent temperature cycling. The results indicated that temperature cycling had little to no effect on windows installed over foam sheathing. • For wall specimens that underwent six-month vertical displacement monitoring, the results showed that windows installed over foam sheathing do not sag over time. • The single-hung and double-hung windows installed using window manufacturer installation instructions passed the structural performance test, compared to failures observed in windows that were installed using generic installation instructions. The generic and manufacturer installation methods differed on the following construction details: type of fasteners, fastening patterns on the flanges, and window shimming details. • Additional testing is required to determine methods to improve structural pressure performance of slider windows. Potential solutions that would require additional testing may include fastener spacing, different types of fasteners, masonry window clips, construction adhesive, foam sealant, stronger window flange material, and/or straps.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Generating Synthetic Time Series Photovoltaic Data with Real-World Physical Challenges and Noise for Use in Algorithm Test and Validation

The PV Fleet Data Initiative and other projects seek the develop algorithms for automated analysis of PV time series data for extraction of statistical information and other parameters of the data such as degradation rates, soiling loss information, tracker performance, clipping or curtailment, system availability and other valuable information. While there is a vast body of PV data available for application of said extraction algorithms it is difficult to validate these algorithms because the true parameters to be extracted are not known. There has been a wide use of synthetic data in the literature for algorithm validation but this synthetic data is typically very bounded by the problem or topic at hand. The PV Fleet Data Initiative project has demonstrated that real time series PV data almost always includes a host of data quality and physical problems that, in reality, any automated PV abstraction algorithm must handle appropriately. For this reason, this work describes the development of a complex synthetic PV times series data set that includes data quality and physical problems that have been experienced in real world PV data. The various quality and physical problems are documented in the synthetic data so that users can test the validity of various PV extraction algorithms as well as develop new algorithms to solve problems this data set can support.

14 SOLAR ENERGY↗
DOE OSTI2024

Modeling Flow and Particle Deposition in a Spent Nuclear Fuel Assembly

CFD (Computational Fluid Dynamic) simulation of aerosol-laden natural convective flow and particle deposition in a spent fuel storage canister with 37 assemblies is currently computationally prohibitive. PWR (Pressurized Water Reactor) assemblies have up to 289 pins or tubes with several spacer grids to align the pins. Spacer grids with mixing vanes induce swirling during operation to increase heat transfer. Each spacer grid contains hundreds of small structures such as retaining clips, channel walls, and openings. The largest canisters store 37 PWR assemblies thus, there are numerous pins, tubes, and spacer grids for which the flow region between and around these structures needs to be determined along with the movement and deposition of aerosol particles. Because of the complicated geometry, modeling the intricate flow even for just one assembly is currently impractical. Nonetheless, we are developing techniques for a practical model to assess the natural aerosol particle deposition process in a canister in the event that a release occurs from one or more fuel pins. In the previous work it was demonstrated that CFD can model the flow through a PWR spacer grid with mixing vanes, including particle deposition, in a reasonable amount of time on a personal computer. In this work, the analysis is extended to include the bypass region between an assembly and the canister basket walls. It is shown that the flow velocity in the bypass region is about three times that of the interstitial region between the pins. The lengths before and after the spacer grid are also extended to determine when the flow becomes fully developed. In addition, the approach of computationally “stitching together” segments of an assembly is demonstrated with the plan to ultimately model a full assembly. The fraction of particles that are deposited in a segment with a spacer grid is determined as a function of particle size and flow velocity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

The VIBES Are Shifting: Assessing Emergent Capabilities in Multi-Modal Models

Researchers assessing open-source domains such as the internet, and particularly those studying information conflict, often have no single prescribed workflow. In the course of their research, they may need to perform a diverse array of tasks far beyond simply identifying an ever-changing set of objects. These analytical tasks can include ascertaining the provenance of images, understand an image in the context of accompanying text-based data, or identifying indicators of digital image manipulation. They must further be able to do this at the scale of tens of thousands of images or more. Traditional machine vision models have typically lacked the flexibility and breadth of performance sufficient for these needs. The research team from Pacific Northwest National Laboratory assessed the performance of a single baseline CLIP ViT-L model against a series of analytical tasks relevant for the study of online information conflict.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Optimizing 4d Emittance Measurements Using the Pinhole Scan Technique

Accurate measurement of electron beam emittance is essential for optimizing high-brightness electron sources. The Pinhole Scan Technique measures the 4D phase space and hence the emittance by measuring the beam profile after clipping the beam using a pinhole followed by a drift section and then scanning the beam over the pinhole. This technique has been implemented in low energy (< 200 keV) beamlines at both Cornell University and Arizona State University. However, the technique poses several practical challenges. In this work, we analyze and address key issues affecting the 4D phase space and emittance measurements using this technique. We identify and investigate sources of inaccuracies like the pinhole aspect ratio, beam divergence, position-momentum correlations in the phase space, and the point-spread-function of the detector and suggest techniques to minimize them. Our findings offer a pathway to more accurate 4D phase space characterization in advanced electron beam systems.

42 ENGINEERING↗
DOE OSTI2025

Development of a reliable Potting process for Photoconductive Semiconductor Switches (PCSS)

Electrical potting is an important process to protect semiconductor devices from damaging external elements (mechanical stress, moisture, high voltage, etc.) and provides structural support for delicate devices for electrical connectivity to a larger platform. This internship will focus on the development of a universal potting jig for photoconductive semiconductor switches (PCSS). The goal is to design a reliable compression jig that is cross compatible with various PCSS designs that allow for easy potting of devices with a high dielectric breakdown strength material. The challenge with the current potting jig is that the design is only compatible with one style of PCSS and applies uneven pressure that can lead to leakage of potting material. Our approach is to move from a design that applies pressure by binder clip to utilizing a micrometer based compressing jig for a reliable packaging process that can pot a variety of devices without having to have a unique compressing jig for each of style of PCSS. Possible roadblocks with the new design include epoxy leakage into the optical path and misalignment of the electrode – metal contact bond.

42 ENGINEERING↗
DOE OSTI2025

Modeling and Analysis of Clean Energy and Storage Technologies (CRADA Final Report, Project 1)

The goal of this project is to provide Southern Company Services, Inc. ("Participant") with custom scripts that can be used to create an average PV energy production profile, calculate lifetime energy value, calculate capacity value, and calculate the resultant financial metrics considering those value streams. Secondly, a fuel-cell model will be added to the public version of System Advisor Model (SAM). This standalone technology will incorporate PV and battery storage, allowing the participant to model the interaction of these three technologies. By adding this capability to a public version of SAM, a broad audience will be able to consider the system performance and financial benefits of installing a fuel cell as a baseline generator with PV. Thirdly, automated dispatch algorithms will be developed and added to SAM. These algorithms will enable Southern Company to dispatch a DC-connected front-of-the-meter battery system while considering price signals and PV clipping behavior. By adding these capabilities to a public version of SAM, users will be able to consider more complex and realistic ways of dispatching a battery system.

14 SOLAR ENERGY↗
DOE OSTI2026

Fermilab 2025 Summer Internship: Repairing Pre-Amplifiers with Mu2e Electronics Installation Team

The author spent nine weeks over summer 2025 working on the tracker electronics installation team for the Mu2e experiment. One of her main responsibilities was repairing high voltage (HV) and calibration (Cal) pre-amplifiers (pre-amps). During installation, the fragile wires connecting the two sockets to the pre-amp board must be bent, often leading to breakage. During production, the sockets and wires were initially soldered to the board at UC Berkely, then the whole pre-amp was coated in parylene before transport to Fermilab. The interns were able to expedite the repairs, and thus whole installation process, by using an alternative method on-site with epoxy. Another task they were responsible for, not included in the original project specifications, was attaching copper clips to specific vias on the Cals to reduce noise. The talk will give listeners insight into the daily problem-solving required by the novel technologies in the Mu2e project. The author would like to acknowledge her fellow Monmouth College undergraduate interns, Lizzie Durfee and Gianna Maughan, advisor and PI of the DOE RENEW Grant Dr. Christopher G. Fasano, and the Mu2e team lead by co-spokesperson Dr. Bob Bernstein and tracker L2 manager Dr. Brendan Kiburg.

de Zwart, Bronte [Monmouth Coll.]↗
DOE OSTI2023

KBase Narrative - Complete Genome Sequence of Acidovorax temperans strain LMJ

We have isolated a new strain of Acidovorax temperans strain LMJ (hereafter called strain LMJ) from a contaminated Tris-Acetate-Phosphate (TAP) medium plate of a green micro-alga Chlamydomonas reinhardtii strain LMJ.SG0182 (a Chlamydomonas Library project (CLiP) strain). We sequenced the whole genome of the strain LMJ using the PacBio Sequel II technology and have submitted it to NCBI along with the SRA and PacBio methylation motif data. We present the whole genome sequence of this strain that offer insights into its coding and non-coding genes and its nearest taxonomic neighbors.

Mitra, Mautusi↗
DOE OSTI2024

KBase Narrative - Complete genome sequence of a novel Microbacterium sp. strain Clip185.

We have isolated a new species of Microbacterium, an Actinobacterium. We have temporarily named this bacterium as Microbacterium sp. strain Clip185 (hereafter called strain Clip185) from a contaminated Tris-Acetate-Phosphate (TAP) medium culture plate of a green micro-alga Chlamydomonas reinhardtii strain LMJ.RY0402.185141 (a Chlamydomonas Library project CLiP strain). We sequenced the whole genome of strain Clip185 using the PacBio Sequel II Continuous Long Read technology and have submitted it to NCBI along with the SRA and PacBio methylation motif data. Additionally, we have submitted the PacBio methylome to REBASE, Ref#35996. We present the whole genome sequence of this new Microbacterium species that offers insights into its coding and non-coding genes and its nearest taxonomic neighbors.

Mitra, Mautusi↗
DOE OSTI2024

Deep learning models for interpretation of point of care ultrasound in military working dogs

Introduction: Military working dogs (MWDs) are essential for military operations in a wide range of missions. With this pivotal role, MWDs can become casualties requiring specialized veterinary care that may not always be available far forward on the battlefield. Some injuries such as pneumothorax, hemothorax, or abdominal hemorrhage can be diagnosed using point of care ultrasound (POCUS) such as the Global FAST® exam. This presents a unique opportunity for artificial intelligence (AI) to aid in the interpretation of ultrasound images. In this article, deep learning classification neural networks were developed for POCUS assessment in MWDs. Methods: Images were collected in five MWDs under general anesthesia or deep sedation for all scan points in the Global FAST® exam. For representative injuries, a cadaver model was used from which positive and negative injury images were captured. A total of 327 ultrasound clips were captured and split across scan points for training three different AI network architectures: MobileNetV2, DarkNet-19, and ShrapML. Gradient class activation mapping (GradCAM) overlays were generated for representative images to better explain AI predictions. Results: Performance of AI models reached over 82% accuracy for all scan points. The model with the highest performance was trained with the MobileNetV2 network for the cystocolic scan point achieving 99.8% accuracy. Across all trained networks the diaphragmatic hepatorenal scan point had the best overall performance. However, GradCAM overlays showed that the models with highest accuracy, like MobileNetV2, were not always identifying relevant features. Conversely, the GradCAM heatmaps for ShrapML show general agreement with regions most indicative of fluid accumulation. Discussion: Overall, the AI models developed can automate POCUS predictions in MWDs. Preliminarily, ShrapML had the strongest performance and prediction rate paired with accurately tracking fluid accumulation sites, making it the most suitable option for eventual real-time deployment with ultrasound systems. Further integration of this technology with imaging technologies will expand use of POCUS-based triage of MWDs.

59 BASIC BIOLOGICAL SCIENCES↗