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ICAT: The Interactive Corpus Analysis Tool
The Interactive Corpus Analysis Tool (ICAT) is a Python library for creating dashboards to explore textual datasets and build simple binary classification models to help filter through them and focus on entries of interest. This tool uses a form of interactive machine learning (IML), a paradigm of “machine teaching” (Simard et al., 2017) that sits at the intersection of the fields of human computer interaction (HCI), visual analytics, and machine learning. The intent of ICAT is to allow subject matter experts (SME) with limited to no experience in machine learning to benefit from an iterative human-in-the-loop (HITL) approach to building their own model without needing to understand the details of the underlying algorithm. This interactivity is achieved by allowing the user to create features, label data points, and visually manipulate a representation of the features to manually cluster and investigate data, while a model is trained on the fly based on these actions. ICAT is built on top of the Panel (Holoviz, 2018) library, using a combination of Vega, a custom IPyWidget using D3, and ipyvuetify, and is intended to be used inside of a Jupyter environment.
A structural equation modeling approach to leveraging the power of extant sentiment analysis tools
Machine-derived sentiment analysis has become a pervasive and useful tool to address a wide array of issues in natural language processing. Leading technology companies such as Google now provide sentiment analysis tools (SATs) as readily accessible online products. Academic researchers develop and make available SATs to support the research enterprise. One of the major challenges with SATs is the inconsistencies in results among the various SATs. Consequently, the selection of a SAT for a specific purpose may significantly impact the application. This study addresses the foregoing problem by utilizing structural equation modeling to merge the outputs of SATs to develop a combined sentiment metric without the need for a labeled training dataset. This method is applicable to a wide range of text-based problems, is data-driven, and replicable. It was tested using three publicly available datasets and compared against seven different SATs. The results indicate that as a continous measure, the proposed method outperformed other SATs in the movie reviews and SemEval datasets, and achieved a tie for first place with IBM Watson on the Sentiment 140 dataset. Also, compared to the published major alternatives, the arithmetic mean solution, this approach performed better across these three datasets.
Cyber-informed Engineering Battery Analysis Tool
The Cyber-Informed Engineering Battery Analysis Tool (CIEBAT) leverages the Department of Energy’s Cyber-Informed Engineering to prompt engineering designers and operators through an analysis of the critical functions to be supported by a BESS installation, the criticality of those functions, the impacts of denial, disruption or misuse of those functions within the BESS system, and the mitigations which could best prevent impacts to those functions resulting from cyber attack. Through use of this tool, BESS designers and operators can quickly identify appropriate engineering mitigation opportunities to limit impacts from cyber attack and functions where engineering and operational staff can prioritize and guide the application of cybersecurity protections to best support the resiliency of the system.
Cyber-informed Engineering Microgrid Analysis Tool
The Cyber-Informed Engineering Microgrid Analysis Tool (CIEMAT) leverages the Department of Energy’s Cyber-Informed Engineering to prompt engineering designers and operators through an analysis of the critical functions to be supported by a microgrid installations, the criticality of those functions, the impacts of denial, disruption or misuse of those functions on the microgrid and dependent functions, and the mitigations which could best prevent impacts to those functions resulting from cyber attack. Through use of this tool, microgrid designers and operators can quickly identify appropriate engineering mitigations to limit impacts from cyber attack and functions where engineering and operational staff can prioritize and guide the application of cybersecurity protections to best support the resiliency of the system.
Flat and Level Analysis Tool (FLAT) for real-time automated segmentation and analysis of concrete slab point clouds
In the United States, the flatness and levelness of concrete floors during construction is traditionally specified by a maximum allowable gap under a 3 meter straightedge. However, the straightedge method is inexact and rarely representative of the entire floor since the technician is free to choose any location on the floor to perform the measurement. In cases requiring a higher degree of precision and repeatability, concrete floor flatness and levelness can be measured using the standard test method ASTM E1155. With the recent introduction of advanced surveying instruments such as robotic theodolites and terrestrial laser scanners (TLS), the means now exist to modernize and expedite the measurement of floor flatness and levelness. This paper details the development and demonstration of a digital tool, named the Flat and Level Analysis Tool (FLAT), to automate and expedite the segmentation and analysis of flatness and levelness from dense point cloud data of concrete floor slabs. Segmentation algorithms were developed using unsupervised machine learning to extract the set of points belonging to the concrete floor slab from a full 360 scan of a construction site. After segmentation, automated analysis algorithms report the results according to the standard method. The developed algorithms were demonstrated on a dense point cloud captured from a concrete slab-on-grade at a construction site. Results show that the digital tool can quickly provide estimates for floor flatness and levelness with minimal human involvement with comparable accuracy to manual methods.
Blending Pipeline Analysis Tool for Hydrogen (BlendPATH) Documentation and User Manual
The Blending Pipeline Analysis Tool for Hydrogen (BlendPATH) is a flexible, open-source Python tool designed to provide users with case-by-case analysis capabilities to identify the necessary modifications to repurpose existing natural gas transmission pipeline networks to transport hydrogen as a blend of a user-specified volume fraction of hydrogen or as a pure stream and to estimate the associated capital and operating expenditures resulting from those modifications. This tool is intended to be applied during the initial screening stage of a prospective project when pipeline developers compile transmission pipeline technical documentation and history but prior to performing detailed pipeline inspections. Performing analysis with BlendPATH during this initial screening stage can provide the user with an understanding of promising opportunities and probable economic outcomes of repurposing their pipeline network for hydrogen before proceeding with detailed pipeline materials testing and pipeline inspections. BlendPATH consists of multiple modules to simulate, assess, and modify existing natural gas transmission pipeline network designs to be compatible with hydrogen as a blend or pure stream. The tool employs an open-source gas network hydraulic model to simulate existing, user-specified transmission pipeline networks, and it applies ASME B31.12 to assess the pipe segments within these networks for compatibility with hydrogen and to modify the networks to achieve compatibility where the existing infrastructure is inadequate. Users can specify ASME B31.12 design options for pipeline assessment and can select from multiple methods for pipeline modification. This report details the functionalities of BlendPATH Version 2.0.2 and demonstrates an example of applying BlendPATH to a case study. Potential and intended users of this framework include natural gas pipeline developers and operators and researchers at both public and private institutions. BlendPATH is publicly available at https://github.com/NREL/BlendPATH.
HYPSTAT (Hydrogen Production, Storage, and Transmission Analysis Tool) [SWR-23-04]
The Hydrogen Production, Storage, and Transmission Analysis Tool (HYPSTAT) is a modeling framework developed by the National Renewable Energy Laboratory (NREL) to support the analysis of hydrogen systems. HYPSTAT focuses on key components of hydrogen infrastructure, particularly electrolytic hydrogen production, hydrogen storage, and hydrogen transmission, as part of the transition to decarbonized energy systems HYPSTAT operates as a supply-to-demand model, taking a fixed exogenous demand as input and optimizing the design and operation of the hydrogen system to meet that demand. It determines cost-optimal configurations based on specified technology options and system constraints.
Catalyst-Vision (PEM Catalyst Layer Image Analysis Tool) [SWR-25-100]
Catalyst-Vision (PEM Catalyst Layer Image Analysis Tool) provides an advanced Python-based tool, primarily designed for use in a Jupyter/Colab notebook, for the quantitative morphological analysis of pre-segmented shapes. While developed for analyzing PEM catalyst layers from microscopy, its methodology is suitable for characterizing any grayscale object provided on a uniform white background. The tool uses a robust computer vision pipeline based on the Euclidean Distance Transform and skeletonization to accurately measure local thickness and tortuosity, providing a comprehensive characterization of an object's geometry and internal texture. If you find this code useful, please cite our preprint as: Chan, Ai-Lin and Hayden, Steven and Harvey, Steven P. and Smeaton, Michelle and Okrucky, Caleb and Watt, John and Ulična, Soňa and Spurgeon, Steven and Jungjohann, Katherine and Alia, Shaun, Mechanism-informed breakdown: understanding degradation by controlling voltage hold patterns in PEM water electrolyzers. Preprint (2025).
CIEPAT (Cyber-Informed Engineering Photovoltaic Analysis Tool) [SWR-25-171]
The Cyber-Informed Engineering Photovoltaic Analysis Tool (CIEPAT) was developed in collaboration with the U.S. Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER). This tool is a energy source subcomponent integrated into the CIEMAT ecosystem and is developed to enhance the security and resilience of Photovoltaic installations by incorporating Cyber-Informed Engineering (CIE) principles into the deployment of PV systems.
Procurement Analysis Tool (PAT) Informational Webinar for Clean Energy States Alliance
This is a slide deck for the Procurement Analysis Tool and the deck published in August 2025. This webinar is a part of the PAT roadshow and we are presenting it in different forums and to different audience. https://research-hub.nrel.gov/en/publications/procurement-analysis-tool-pat-informational-webinar
CIECAT (Cyber-Informed Engineering Commercial Buildings Analysis Tool) [SWR-25-172]
The Cyber-Informed Engineering Commercial Buildings Analysis Tool (CIECAT) was developed in collaboration with the U.S. Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER). This tool is a energy source subcomponent integrated into the CIEMAT ecosystem and is developed to enhance the security and resilience of Commercial Buildings by incorporating Cyber-Informed Engineering (CIE) principles into the Commercial Buildings.
Sensitivity Analysis Tool for Electrochemical Conversion of CO2 to CO
Data presented in poster is sourced from the Electrochemical Catalyst Sensitivity Analysis Tool. This tool comprises a material balance model with cost estimation to estimate the levelized cost of product for CO production via CO2 electrolysis. A set of sensitivity analyses on key system and financial parameters is included with results so that users can test the impacts of these parameters on LCOP.
CO2_S_COM_Offshore: A Technoeconomic Analysis Tool for Offshore Saline Carbon Storage
Presentation for the FECM NETL Carbon Management Program Review Meeting 2024. This presentation details the development of CO2_S_COM_Offshore, a cost model and technoeconomic analysis tool for screening offshore saline carbon storage sites.
A LOCA Analysis Tool: Coupling RELAP5-3D to BISON
Experimental evidence illustrates that at burnups slightly above the current regulatory limit of a rod-averaged burnup of 62 MWd/kgU, the ceramic UO 2 inside light-water reactor fuel rods becomes susceptible to a phenomenon known as fuel fragmentation, relocation, and dispersal (FFRD) during a loss of coolant accident (LOCA) transient. The severity of FFRD is strongly influenced by the zirconium-based (Zircaloy) cladding behavior during the LOCA transient. A Technology Commercialization Fund (TCF) project was awarded to an Electric Power Research Institute (EPRI)/Idaho National Laboratory team to create a LOCA analysis tool that couples BISON to the systems/thermal-hydraulics code RELAP5-3D [1] for analysis of LOCA scenarios. In addition, further refinements to existing BISON models were identified as necessary to more accurately represent more recent experimental evidence from the Studsvik Cladding Integrity Project (SCIP) and other experimental programs.
Cross-Code Verification of Neutronics Analysis Tools at INL Applied for 238 Pu Production in the Advanced Test Reactor
Here, analyses are completed for experiments prior to experiment irradiation in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). Various codes are used to qualify all experiments planned for insertion in the reactor, thereby ensuring that all safety and programmatic requirements are satisfied preirradiation. Among the common experiment analysis tools at INL are MCNP5 coupled to ORIGEN2 (MOPY) and MC21. MOPY uses MCNP5 for transport calculations along with calculations for fluxes and select reaction rates, and then ORIGEN2 handles the step-by-step and postirradiation depletion. MC21 handles all in-reactor transport and step-by-step, during-irradiation, depletion calculations, and then ORIGEN (SCALE 6.2.3) is used for decay and dose calculations postirradiation. The MOPY results, along with those obtained via two variations of the MC21 model, were compared in terms of 238 Pu production in the ATR’s H10 position. For the MOPY model, the MC21 model utilizing the HELIOS-based fission product (FP) library, and the MC21 model utilizing the expanded 1300 FP library, the during-cycle irradiation in-core heating results were sufficiently equivalent; however, the MOPY model and the MC21 model with the HELIOS library showed some differences relating to the respective FP libraries. Ultimately, the MC21 model with a 1300 FP library produced the most consistent results throughout the cycle, whereas the MC21 model that utilized the (smaller) HELIOS library was able to handle during-irradiation analysis but lacked certain short-lived FPs that significantly contributed to the total decay heat at shutdown. MOPY, on the other hand, was found to overpredict fission gas production, as a result of limitations in the ORIGEN2 code.
Triso Analysis Tool For Predictive Source Terms
Source term modeling for TRi-structural ISOtropic (TRISO) fuel has been performed for previous reactor designs, but few are available in the open literature. Thus, there is a need to develop a simple, versatile, and mechanistic model of fission product release and transport in gas reactor cores that can be applied to a variety of reactors through user inputs and reactor-specific radionuclide inventories. To meet this need, the TRISO Analysis Tool for Predictive Source terms (TRISO-ATOPS) was developed. This model calculates the release of the key safety-important fission products by diffusion through the kernel, silicon carbide and graphite based on fuel and graphite temperatures in the reactor under normal operation. These releases from the fuel enter the coolant where they can plate-out on cooler surfaces. A clean-up model is included for designs with a coolant purification system for removing fission gases. This initial distribution of fission products in the reactor serves as an initial condition for potential releases under postulated accident conditions. From this initial condition, the model calculates the fission product release for any transient temperature profile, and the fission product releases can then be used to assess radiological dose to the workers and the public using conventional radiological dose tools. Data on the diffusion of fission products is based on historic German TRISO experiments and the more current Department of Energy Advanced Gas Reactor TRISO fuel development program. The example cases in this work demonstrate the flexibility of the model
Automated ToF-SIMS PCA Analysis Tool
Python software package for PCA analysis of ToF-SIMS spectra data