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At least 397 records · Page 22

Molten Sodium Penetration in NaSICON Electrolytes at 0.1 A cm –2

High-conductivity solid electrolytes, such as the Na superionic conductor, NaSICON, are poised to play an increasingly important role in safe, reliable battery-based energy storage, enabling advanced sodium-based batteries. Coupled demands of increased current density (≥0.1 A cm –2 ) and low-temperature (<200 °C) operation, combined with increased discharge times for long-duration storage (>12 h), challenge the limitations of solid electrolytes. Here, we explore the penetration of molten sodium into NaSICON at high current densities. Previous studies of β"-alumina proposed that Poiseuille pressure-driven cracking (mode I) and recombination of ions and electrons within the solid electrolyte (mode II) are the two main mechanisms for Na penetration, but a comprehensive study of Na penetration in NaSICON is necessary, particularly at high current density. To further understand these modes, this work employs unidirectional galvanostatic testing of Na|NaSICON|Na symmetric cells at 0.1 A cm –2 over 23 h at 110 °C. Further, while galvanostatic testing shows a relatively constant yet increasingly noisy voltage profile, electrochemical impedance spectroscopy (EIS) reveals a significant decrease in cell impedance correlated with significant sodium penetration, as observed in scanning electron microscopy (SEM). Further SEM analysis of sodium accumulation within NaSICON suggests that mode II failure may be far more prevalent than previously considered. Further, these findings suggest that total (dis)charge density (mAh cm –2 ), as opposed to current density (mA cm –2 ), may be a more critical parameter when examining solid electrolyte failure, highlighting the challenge of achieving long discharge times in batteries using solid electrolytes. Together, these results provide a better understanding of the limitations of NaSICON solid electrolytes under high current and emphasize the need for improved electrode–electrolyte interfaces.

25 ENERGY STORAGE↗

Uniform Mechanical Loading Can Test for Nonuniform Loading Durability

In this work, we present a method to evaluate the equivalency between any module mechanical loading conditions. The method is developed to address the specific failure mode of glass fracture and is based on Weibull analysis and weakest link theory. It considers the varying stress profile across the module to calculate the probability of glass fracture, which is used as the metric of equivalency. An idealized nonuniform loading scheme is employed to demonstrate the method and introduce the concept of the equivalent uniform load factor: a factor applied to the maximum pressure of the nonuniform load to obtain the equivalent uniform load value. It is demonstrated that this factor is less than unity for all nonuniform load cases considered, including snow and various characters of wind loading. These significant results suggest that uniform loading may be reliably, and practically, employed to evaluate photovoltaic module glass for nonuniform loading durability.

14 SOLAR ENERGY↗

To Fail or not to Fail: An Exploration of Machine Learning Techniques for Predictive Maintenance

Predictive maintenance refers to the ability to predict when machinery or systems need to be maintained. Making an accurate prediction is quite challenging given the costs for both over-estimating (unnecessary maintenance and reduction in availability of assets) and under-estimating (untimely breakdowns and possible loss of equipment or lives). To address these challenges researchers were able to develop new approaches for analyzing oil samples taken extracting samples from oil-wetted machinery that may provide information critical to developing predictive capabilities. We consider the problem from both supervised (though data limited) and unsupervised approaches and provide a first look into a data driven approach for identification of condition indicators. Through this work we identify a collection of candidate features that can form the basis of condition indicators for both a high level discrimination of failure vs. normal operation as well as a set for potential failure mode identification. Finally, we present an anomaly detection framework for detecting failures which can be a viable solution for an onboard analysis tool in deployed systems.

predictive maintenance, anomaly detection, Laserne↗

DISTRI: Distributed Multi-Facility HPC Simulator (DISTRI) v2.1

DISTRI is an advanced network simulator designed for multi-facility computational infrastructures with agentic behavior. It simulates HPC facilities where computational resources act as autonomous agents, making intelligent decisions about job scheduling, load balancing, and resource allocation. The simulator focuses on developing and testing decentralized algorithms that promote resilience and efficiency in multi-facility environments. Key Features: - Agentic Resource Behavior: Processors and DTNs act as autonomous agents with decision-making capabilities - Pheromone-Based Load Balancing: Decentralized load balancing inspired by ant colony optimization - Dual Topology Support: Mesh (normal operations) and Dumbell (network testing) topologies - Comprehensive TCP Simulation: Realistic TCP implementations with multiple congestion control algorithms - Failure Resilience Testing: Processor failure simulation with automatic job reassignment - Extensive Visualization: Detailed performance analysis and metrics collection - Research-Ready: Designed for algorithm development and benchmarking

Bez, Jean Luca [Lawrence Berkeley National Laborat↗

An Integrated Framework for Risk Assessment of Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology Refinement and Exploration

This report documents activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2023 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective, and secure DI&C technologies for digital upgrades/designs. A risk assessment-informed framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk informed capability to quantitatively estimate the safety margin obtained from plant modernization, especially for safety-related DI&C systems, (2) support and supplement existing risk informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of safety-related DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals, the LWRS-developed framework provides a means to address relevant technical issues by: (1) defining a risk informed analysis process for DI&C upgrade that integrates hazard analysis, reliability analysis, and consequence analysis, (2) applying risk informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development and deployment of advanced DI&C technologies in nuclear power plants (NPPs). Adding diversity within a system or components is the primary means to eliminate and mitigate CCFs, but diversity also increases system complexity and may not address all sources of systematic failures. Optimization of diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in safety-related DI&C systems of NPPs and supporting relevant design optimization, the proposed framework provides: (a) A best-estimate, risk informed capability to address new technical digital issues quantitatively, focusing on software CCFs in safety-related DI&C systems of NPPs; (b) A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to predict and prevent risk in the early design stage of DI&C systems; (c) Technical bases and risk informed insights to assist users address the risk informed alternatives for evaluation of CCFs in safety-related DI&C systems of NPPs; and (d) A risk informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The research and development efforts of this project in FY 2023 are focused on refining current methods on software CCF modeling and estimation and exploring additional innovative approaches to risk assessment of DI&C systems to enable a more comprehensive and complete assessment of various safety-related DI&C design architectures. The primary audience of this report are DI&C designers, engineers, and probabilistic risk assessment (PRA) practitioners. This includes stakeholders, such as the nuclear utilities and regulators who consider the deployment and upgrade of DI&C systems, DI&C software developers and reviewers, and cybersecurity specialists. It should be noted that all the analyses are performed for the demonstration of the methodology, not for the evaluation of an actual digital control system. Results are obtained based on limited design information and testing data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Correlation between Sensor Performance, Autonomy Performance and Fuel-Efficiency in Semi-Truck Platoons

Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each n close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces green- house gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel. This is especially an issue if deceleration is applied in response to a bad measurement. In this study, a faulty radar was shown to cause a greater than 5% increase in fuel consumption. The mechanism of this fuel consumption increase is investigated and applied to other types of sensor failures to indicate their potential effects on fuel economy. This analysis indicates that poor GPS signals over short time can be largely filtered out, with no real gain or loss of fuel economy. V2V communications were intentionally limited by causing interference, which resulted in dropped communication packets over a small physical area, but not an appreciable impact on fuel economy.

vehicle platooning, sensor performance, semi-auton↗

An Integrated Risk Assessment Process of Safety-Related Digital I&C Systems in Nuclear Power Plants

Upgrading the existing analog instrumentation and control (I&C) systems to state-of-the-art digital I&C (DI&C) systems will greatly benefit existing light water reactors. However, the issue of software common cause failure (CCF) remains an obstacle in terms of qualification for digital technologies. Existing analyses of CCFs in I&C systems mainly focus on hardware failures. With the application and upgrading of new DI&C systems, design flaws could cause software CCFs to become a potential threat to plant safety, considering that most redundancy designs use similar digital platforms or software in their operating and application systems. With complex multilayer redundancy designs to meet the single failure criterion, these I&C safety systems are of particular concern in U.S. Nuclear Regulatory Commission licensing procedures. In Fiscal Year 2019, the Risk-Informed Systems Analysis (RISA) Pathway of the U.S. Department of Energy’s Light Water Reactor Sustainability Program initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades and designs. An integrated risk assessment for the DI&C process was proposed for this strategy to identify potential key digital-induced failures, implement reliability analyses of related digital safety I&C systems, and evaluate the unanalyzed sequences introduced by these failures (particularly software CCFs) at the plant level. Here this paper summarizes these RISA efforts in the risk analysis of safety-related DI&C systems at Idaho National Laboratory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Vitality models found useful in modeling tag-failure times in acoustic-tag survival studies

Abstract Acoustic telemetry studies often rely on the assumption that premature tag failure does not affect the validity of inferences. However, in some cases this assumption is possibly or likely invalid and it is necessary to apply a correction to estimation procedures. The question of which approaches and specific models are best suited to modeling acoustic tag failures has received little research attention. In this short communication, we present a meta-analysis of 42 acoustic tag-life studies, originally used to correct survival studies involving outmigrating juvenile salmonids in the Columbia/Snake river basin. We compare the performance of nine alternative parametric models including common failure–time/survival models and the vitality models of Li and Anderson Theor Popul Biol 76:118–131, (2009) and Demogr Res 28:341–372, (2013). The tag-life studies used acoustic tags from three different tag manufacturers, had expected lifetimes between 12 and 61 days, and had dry weights ranging from 0.22 to 1.65 g. In 57% of the cases, the vitality models of Li and Anderson Theor Popul Biol 76:118–131, (2009) and Demogr Res 28:341–372, (2013) fit the tag-failure times best. The vitality models were also the second-best choices in 17% of the cases. Together, the vitality models, log-logistic, (19%), and gamma models (14%) accounted for 90% of the models selected. Unlike more traditional failure–time models (e.g., Weibull, Gompertz, gamma, and log-logistic), the vitality models are capable of characterizing both the early onset of tag failure due to manufacturing errors and the anticipated battery life. We provide further guidance on appropriate sample sizes (50–100 tags) and procedures to be considered when applying precise tag-life corrections in release–recapture survival studies.

Skalski, John R. (ORCID:0000000270702505)↗

MDPCT1 Quench Data and Performance Analysis

MDPCT1 is a four-layer cos-theta Nb3Sn dipole demonstrator developed and tested at FNAL in the framework of the U.S. Magnet Development Program. The magnet reached record fields for accelerator magnets of 14.1 T at 4.5 K in the first test and 14.5 T at 1.9 K in the second test and then showed large degradation. While its inner coils performed exceptionally well with only two quenches up to 14.5 T and no evidence of degradation, the outer coils degraded over the course of testing. By adopting new measurement and analysis techniques at FNAL we are discussing in detail what happened. Both success and failure in our diagnostics are discussed. The evolution of techniques over the course of two tests (and three thermal cycles) shows the path to address challenges brought by the first four-layer magnet tested at FNAL. This paper presents the analysis of quench data along with diagnostic features and complementary measurements taken in support of the magnet performance analysis.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Review of the Mechanical Properties of Materials Used in Nb 3 Sn Magnets for Particle Accelerators

Superconducting magnets experience significant thermo-mechanical loads throughout their life cycle. These are introduced by the electro-magnetic forces during powering, but also by the prestress applied in many magnet designs. Further to this, the large thermal excursion that components of different materials experience can generate significant internal forces. The loads are also experienced by the superconducting coils, whose critical current can decrease as a consequence of the applied strain. It is then crucial to predict the overall mechanical behavior and conservatively design a magnet, avoiding failure of the mechanical components and of the superconducting coils. Finite Element Analysis (FEA) is generally used to perform these tasks, but its results rely heavily on the material properties and models used. This is in particular true for the coil composite, which is simplified to allow reasonable model sizes in full magnet models. Here we present the state-of-art knowledge of the mechanical properties of the materials mostly used in superconducting magnet construction. We review elastic and plastic properties at room and cryogenic temperature, thermal contraction, and summarize the state-of-art failure criteria for these materials. Finally, the paper summarizes the present understanding of the mechanical behavior and limits of Nb3Sn coils. For the first time, an orthotropic failure criteria is proposed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Component Failure R&D

This presentation is to establish a scientific basis for risk and reliability analysis through integrated work with data collection, model development, and stakeholder engagement.

availability↗

Long-Term Toxicity and Health-Related Quality of Life After Adjuvant Chemoradiation Therapy or Radiation Therapy Alone for High-Risk Endometrial Cancer in the Randomized PORTEC-3 Trial

The survival results of the PORTEC-3 trial showed a significant improvement in both overall and failure-free survival with chemoradiation therapy versus pelvic radiation therapy alone. The present analysis was performed to compare long-term adverse events (AE) and health-related quality of life (HRQOL).

62 RADIOLOGY AND NUCLEAR MEDICINE↗

AGR 5/6/7 Data Qualification Report for ATR Cycles 162B through 168A

This report provides the qualification status of experimental data for the Advanced Gas Reactor (AGR) 5/6/7 fuel irradiation. AGR-5/6/7 was conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) in support of development and qualification of tri-structural isotropic (TRISO) low-enriched fuel for use in high temperature gas-cooled reactors. The objectives of the AGR-5/6/7 experiments are to: (i) irradiate reference-design fuel particles to support fuel qualification, (ii) establish operating margins for the fuel beyond normal operating conditions, and (iii) provide irradiated-fuel performance data and irradiated-fuel samples for post-irradiation examination (PIE) and safety testing. The test train contains five separate capsules that were independently controlled and monitored. Each capsule contains multiple 12.51-mm-long compacts filled with low enriched uranium carbide/oxide (UCO) TRISO fuel particles. The primary objective of the AGR-5/6 test (Capsules 1, 2, 4, and 5) is to verify successful performance of the reference-design fuel under normal operating conditions. The AGR-7 test (Capsule 3) was designed to explore fuel performance at higher temperatures to demonstrate the capability of the fuel to withstand conditions beyond normal operating conditions in support of plant design and licensing. AGR 5/6/7 will also provide irradiated-fuel performance data on fission-gas release from failed particles during irradiation. The AGR-5/6/7 capsules were irradiated in the ATR northeast flux trap location. The experiment began on February 16, 2018 and ended on July 22, 2020, spanning nine ATR cycles over two and a half years. Thus, the AGR-5/6/7 fuel compacts were irradiated for a total of 360.9 effective full power days. The AGR 5/6/7 experiment was able to remain in the reactor core during all three Powered Axial Locator Mechanism (PALM) cycles (163A, 165A, and 167A) without overheating its fuel compacts. This report includes irradiation monitoring data from nine ATR Cycles: 162B, 163A, 164A, 164B, 165A, 166A, 166B, 167A, and 168A, as stored in the Nuclear Data Management and Analysis System (NDMAS). During irradiation, data records consisted of instantaneous measurements recorded every minute and provided by text files automatically every 2 hours. The AGR 5/6/7 data streams addressed in this report include thermocouple (TC) temperatures, sweep gas data (flow rates [capsule inlet, outlet, and downstream at detector], pressure, and moisture content), and Fission Product Monitoring System (FPMS) data (release rates and release to birth rate ratios [R/Bs]) for each of the five capsules. A total of 94,989,908 TC temperature and sweep gas data records were received and processed by NDMAS for AGR 5/6/7 irradiation. Of these records, 41,593,387 (or 43.7% of the total) met data collection and accuracy requirements and are labeled as Qualified. A total of 57,746,693 TC temperature readings were captured from 54 installed TCs. Among them, 10,034,676 TC temperature records (only 17.4%) were Qualified and 47,701,371 TC temperatures (or 82.6%) are Failed due to 48 TC failures (63.5%) and due to missing values (19.1%). To assess performance of the operational TCs, analysis of daily correlations between TCs found no evidence of virtual junction failure for any TCs. Analyses on control charts of TC temperature differences revealed trending in TC readings for TC2, 4, 5, and 13 in Capsule 3, but there is no conclusive indication of TC drift failure that caused those trends. Therefore, TC control charts are not used to disqualify TC data, but only for users’ consideration. For sweep gas flow rates, a total of 31,519,747 gas flow records (84.4%) are Qualified for use for AGR-5/6/7 experiment; 5,723,468 gas flow records (15.4%) are Failed due mostly to missing values; and 74,641 high sweep gas flow rates (0.2 %) are Trend. A large number of Failed missing TC temperature and gas flow values were caused by an error in the data output script that outputted a ‘NULL’ value when values were unchanged. This problem was fixed during the outage of Cycle 166B, which led to a substantially decreased number of missing values during the last three cycles. Nonetheless, a large amount of non-missing data remained because of the high data acquisition frequency (1-minute) and still provided sufficient data to effectively monitor the experiment as designed. For FPMS data, NDMAS received and processed fission product release and R/B data for nine ATR cycles, when ATR core reached full power during AGR 5/6/7 irradiation. These data consist of 110,388 release rate records and 110,388 R/B records for the twelve radionuclides (Kr 85m, Kr 87, Kr 88, Kr 89, Kr 90, Xe 131m, Xe 133, Xe 135, Xe 135m, Xe 137, Xe 138, and Xe 139) for each of the five capsules. Equivalent numbers of uncertainty records associated the release rates and R/B values were provided. To date, qualification status of the FPMS data stored in the NDMAS dat

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Void coalescence and ductile failure in IN718 investigated via high-energy synchrotron X-ray tomography and diffraction

Ductile failure through the growth and coalescence of voids is of particular relevance for many engineering materials. Yet, the lack of experimental measurements of the mechanical state of the material at an appropriate length scale has limited further understanding of the regime of ductile failure. In this study, local grain-scale experimental measurements are used to determine their relevance for describing and predicting ductile failure. Additive manufactured materials, due to the presence of inherent porosity, as well as the ability to tailor internal porosity, provides a promising avenue to study ductile failure. Selective laser melting is used to manufacture a specially designed specimen with two large, internal voids, in addition to the natural porosity, which is characteristic to the production process. The initial porosity and its evolution upon tensile loading are characterized via micro tomography. Several locations of void coalescence are captured in the sample, revealing activity of multiple modes of failure. Finite element simulations, with a simplified J2 plasticity model, instantiated with the initial void structure, is deployed, in which geometric localizations of stress concentration corresponded with experimentally observed sites of coalescence but was inadequate in capturing the appropriate failure mechanism. Furthermore, from the experimental results of the far-field high-energy diffraction microscopy, the heterogeneous micromechanical state is identified and tracked around voids due to the local grain interactions. These experiments determine narrow bands of low stress triaxiality, at the onset of failure, which highlight the path of coalescence through intervoid shearing. Diffraction spot spreading analysis aided characterization of intragranular plasticity and strain heterogeneity, which can be coupled with high triaxiality to form the conditions inducive for coalescence through intervoid necking. In this study, the experimentally determined grain-scale description of the micromechanical state provides a physical basis that can accurately capture both the sites and the mechanism of void coalescence at the onset of ductile failure.

36 MATERIALS SCIENCE↗

Theoretical Analysis and Experimental Validation of Flying-Capacitor Multilevel Converters Under Short-Circuit Fault Conditions

Addressing the increasing demand for high- efficiency and high-power-density converters, the flying-capacitor multilevel converter has shown itself as a promising topology. A key advantage of this topology is the reduced voltage rating of the switches, though also makes it vulnerable to device failure during short-circuit conditions. Despite large interest in fault-tolerant operation of these converters, alongside detailed descriptions of flying capacitor balancing, little research has focused on the converter short-circuit fault analysis, which may cause a switch failure if not properly designed for. Therefore, this work presents a comprehensive model describing the large- signal short-circuit switching behavior of a general N -level flying- capacitor multilevel converter. Highly simplified models used to predict the evolution of the switch current and voltage stress during the fault are proposed, targeted at practicing engineers for conservative design guidelines. These models are used to determine the critical time for remedial action of the converter before reaching some predefined maximum conditions. A 2-to-10- level fully-configurable flying-capacitor multilevel converter and a fault circuit hardware prototype are used to experimentally perform different short-circuit tests that show a good match to the measured behavior.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Numerical Simulation and Experimental Validation of Joint Performance in Aluminum-Steel Lap Welds Formed by Friction Stir Dovetailing

Friction stir dovetailing (FSD) is a new dissimilar material joining process that simultaneously forms a mechanical interlock and metallurgical bond at the dissimilar material interface. This work presents development of a modeling and simulation approach to predict mechanical performance of FSD thick section aluminum to steel joints. A finite element analysis (FEA) was carried out in order to predict the load-carrying capacity and failure location for aluminum thicknesses between 12.7 mm and 50.8 mm with different numbers of dovetails. The numerical results and corresponding experimental investigation are in agreement and suggest that the developed methods can be used effectively for design and analysis of FSD joints using standard FEA tools.

Friction stir dovetailing, Friction stir welding, ↗

Structure and mechanical properties of grain boundaries in molybdenum disulfide (MoS 2 )

Molybdenum disulfide (MoS 2 ) is a two-dimensional material widely used as a lubricant in many applications involving mechanical loading under a wide range of operating temperatures. Since many synthesis and processing techniques yield MoS 2 in its polycrystalline form, establishing grain boundary (GB) structure–property relations is key to designing MoS 2 microstructures with tailored properties. Here, we employ classical, reactive atomistic simulations to investigate the structure and mechanical behavior of a wide range of GBs in MoS 2 as a function of temperature. Using a bicrystal MoS 2 geometry, we characterize the atomic structure and calculate the energy of several low-angle GBs. Then, we simulate the tensile deformation behavior of MoS 2 bicrystals at several temperatures. Our results reveal that at temperatures above 100 K, the deformation of MoS 2 bicrystals is characterized by the nucleation of shear bands from GBs that grow, with subsequent loading, into the MoS 2 crystals. At low temperatures, the tensile deformation is characterized by the nucleation and propagation of deformation fronts, resulting in altered bond angles and bond lengths. Quantitative analysis reveals a decrease in the ultimate tensile stress and ultimate failure strain of MoS 2 bicrystals with the increase in temperature. Furthermore, our simulations of the mechanical behavior of metastable GBs reveal that the strength and ductility decrease with the increase in energy of these boundary structures. In broad terms, our work provides future avenues to employ GB engineering as a strategy to tailor the properties of MoS 2 microstructures.

Moore, Robert D. [Lehigh Univ., Bethlehem, PA (Uni↗

Deep-Lynx-ML-Adapter

The Deep Lynx Machine Learning (ML) Adapter is a generic adapter that programmatically runs the ML as continuous data is received. Then, Jupyter Notebooks can be customized according to the project for pre-processing the data, building the machine learning models, prediction analysis of incoming data using an existing model, and forecasting anomalies / failures of the physical asset.

Wilsdon, KatherineN↗