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At least 919 records · Page 51

Geometric Scale-up Experiments on Fluidization of Geldart B Glass Beads

The objective of this work is to provide a valuable database from controlled experiments for validating computational models. Recently, coarse-grained techniques such as particle-in-cell (PIC) or coarse-grained discrete element modeling (DEM) have gained popularity due to their computational efficiency while modeling large-scale systems; however, the influence of model parameters and their sensitivities at different geometric scales and flow conditions remain to be analyzed. These datasets are critical for the multiphase flow research community to assess predictive capability of modeling techniques as well as elucidate the hydrodynamic behavior in these systems. This study performed fluidization experiments using three different test sections with internal diameters of 2.5, 4, and 6 in. The operating conditions, bed material, and range of flow velocities at the inlet were constant in all the units, which were not hydrodynamically scaled. Glass beads having a Sauter Mean Diameter of 332 μm were used. Superficial velocity was varied from 2.97 to 5.35 times the minimum fluidization velocity and the initial static bed height was 0.1524 m. The order in which the experiments were performed was randomized and replicates were included to provide uncertainty in measurements. Statistics of differential pressure and bed height from these tests were reported. Future plans include validating PIC methodology in the open-source software, MFiX (Multiphase Flow with Interphase Exchanges) using results from this study. This could further be extended to determine optimal model parameters using inverse techniques such as deterministic calibration or Bayesian inference.

20 FOSSIL-FUELED POWER PLANTS↗

Wireless System Development for GaN-Based Transmitters for Advanced Nuclear Reactor Environments

The market for consumer electronics is dominated by Si-based electronics. Many Si-based complementary metal–oxide–semiconductor (CMOS) devices are reaching their limitations in terms of switching frequencies, voltages, currents, and temperatures. Furthermore, these devices are widely known to be susceptible to ionizing radiation and neutrons. Advanced nuclear reactors, especially microreactors and small modular reactors, require wireless electronics that can survive larger neutron and gamma doses than Si CMOS. Because of their size, electronics will need to be placed closer to the reactor cores, and cabling capabilities may be limited. However, GaN high-electron-mobility transistors (HEMTs) have been shown to switch faster with higher gains, and they can achieve current and voltage limits beyond traditional Si CMOS. However, they have less market maturity and have undergone less testing. These GaN HEMTs have been shown to survive ionizing radiation with little effects, but the effects of neutron radiation remain widely unknown. In this report, a wireless electronic system capable of supporting multiple radiation-hardened (rad-hard) sensors is presented. The proposed transmission scheme was designed to be simple to increase the likelihood of success in the immature GaN HEMT process and in high-radiation environments. The transmission system was tested using software-defined radios to emulate the transmission scheme before the transmitter circuitry in the GaN process was developed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Electrochemically Engineered, Highly Energy-Efficient Conversion of Ethane to Ethylene and Hydrogen below 550 °C in a Protonic Ceramic Electrochemical Cell

Ethylene is one of the largest building blocks in the petrochemical industry, mainly produced by steam cracking of ethane derived from naphtha or shale gas at high temperatures (>800 °C). Despite its technical maturity and economic competitiveness, the thermal steam cracking of ethane is highly energy-intensive. In this work, an electrochemically engineered direct conversion process of ethane to produce hydrogen and ethylene using a planar protonic ceramic membrane reactor with a bi-functional three-dimensional catalytic electrode is reported, with a single-pass ethane conversion of 40% and ethylene yield of 26.7% at 550 °C. Compared with the industrial ethane steam cracking, this method saves process energy input by 45.1% and improves process energy efficiency by 50.6%, based on comprehensive process simulation using Aspen Plus software. Further, steam electrolysis treatment under the solid oxide electrolysis cell mode can regenerate the system’s catalytic performance and significantly alleviate catalytic degradation by 74%, demonstrating high techno-economic viability.

bi-functional electrode↗

Generic Data Display (GD2)

SAND2023-11967O Generic Data Display (GD2) is a real-time data visualization application that can display user-defined input data. The open-source software is comprised of a back end system written in Python, and a front end user interface written in JavaScript. The back end system collects data from a variety of input sources, such as message queue, HTTP, XML, JSON, and others. The front end displays data in an Open MCT web interface, and users can configure the system by providing JSON formatted configuration files. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Figueroa, Benjamin↗

Operational Energy Life Cycle Data Development for the National Institute of Standards And Technology (NIST) Building Industry Reporting and Design for Sustainability (BIRDS) Neutral Environmental Software Tool (NEST)

For this analysis, regionalized life cycle assessment (LCA) results for environmental impacts (using the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts [TRACI] 2.1) and cumulative energy demand (using the Federal Life Cycle Analysis Commons Elementary Flow List [FEDEFL] Inventory Methods v1.0.0) were evaluated for the production and utilization of electricity, natural gas, fuel oil, and propane as commodities within residential and commercial buildings. These results can used as a framework for future research into net zero, high-performance buildings, such as done here for the Building Industry Reporting and Design for Sustainability (BIRDS) database by the National Institute of Standards and Technology (NIST) Engineering Laboratory. The geographical results were assigned to each United States (U.S.) Zone Improvement Plan (ZIP) code based on the ZIP code location and corresponding Balancing Authority Area, natural gas basin, and Petroleum Administration for Defense Districts (PADDs). Additionally, previously developed models were utilized to develop future life cycle profiles. Projections were based on data available from the U.S. Energy Information Administration Annual Energy Outlook 2022 through 2050 (AEO 2022). Electricity LCA models were updated based on AEO 2022 projected annual generation mixes, while the natural gas baseline model was updated based on projected shares of natural gas types (conventional, shale, tight, and coalbed methane). Projections of crude oil production rates and export rates were applied to the petroleum baseline model in five-year increments to investigate their effects on the life cycle profile of fuel oil and propane. While only 100-year Global Warming Potential (GWP-100) with climate carbon feedback (CC-FB) and Cumulative Energy Demand are shown in Section 4: Results, the complete results, including Acidification Potential, Eutrophication Potential, Freshwater Ecotoxicity Potential, GWP-100 without inclusion of CC-FB, Human Health Impacts Potentials (Cancer, Non-Cancer), Ozone Depletion Potential, Particulate Matter Formation Potential, and Photochemical Smog Formation Potential, are tabulated for each ZIP code in the Excel worksheets that accompany this analysis. For the Excel spreadsheet tools associated with this report, please go to https://www.netl.doe.gov/energy-analysis/details?id=f8890fac-be55-44ac-aaa9-e2888bfabe93

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Integrated system failure analysis software toolchain (IS-FAST)

Systems and methods are provided for generating faults and analyzing fault propagation and its effects. Starting from the ontologies of components, functions, flows, and faults, systems and methods are provided that describe, generate and track faults in a computer system across multiple domains throughout design and/or development. In order to construct the system and fault models, a series of concepts is introduced in the form of ontologies and their dependencies. An investigation is performed into the faults, including their type, cause, life-cycle aspects, and effect. Principles and rules are created to generate various faults based on system configurations. After the modeling process, a simulation engine is described to execute actions and simulate the process of fault generation and propagation. As a result, fault paths that impact components and functions can be obtained.

Diao, Xiaoxu↗

Formulation and calibration of two-dimensional constitutive models for composite structures based on panel tests

Steel Plate Concrete (SC) composite members have been widely adopted because of its cost-efficiency and enhanced structural behavior. While researchers have attempted to study its in-plane shear behavior in the past twenty years, very limited number of large-scale pure shear tests were performed due to the challenge of experimental set-up and the availability of facilities. In this paper, a series of uniaxial loading tests and two full-scale pure shear panel tests of SC members were reported, on which the “mechanics-based Membrane Model of SC elements (MM-SC)” is developed. The MM-SC model is based on the fixed-angle crack formulation and the smeared-crack formulation, in which the experimental-based uniaxial constitutive models are implemented, considering the local buckling of faceplate, the tension stiffening of steel plate, the strength degradation of cracked concrete and the confinement effect of concrete. The proposed MM-SC model is subsequently incorporated into the object-oriented software OpenSEES. Finally, the simulation results of proposed model well predict the SC test observations in terms of critical branch points and structural behaviors, including initial stiffness, cracking strength, post-crack stiffness, yield strength, maximum strength, and failure modes.

42 ENGINEERING↗

Results From Invoking Artificial Neural Networks to Measure Insider Threat Detection & Mitigation

Advances on differentiating between malicious intent and natural “organizational evolution” to explain observed anomalies in operational workplace patterns suggest benefit from evaluating collective behaviors observed in the facilities to improve insider threat detection and mitigation (ITDM). Advances in artificial neural networks (ANN) provide more robust pathways for capturing, analyzing, and collating disparate data signals into quantitative descriptions of operational workplace patterns. In response, a joint study by Sandia National Laboratories and the University of Texas at Austin explored the effectiveness of commercial artificial neural network (ANN) software to improve ITDM. Overall, this research demonstrates the benefit of learning patterns of organizational behaviors, detecting off-normal (or anomalous) deviations from these patterns, and alerting when certain types, frequencies, or quantities of deviations emerge for improving ITDM. Evaluating nearly 33,000 access control data points and over 1,600 intrusion sensor data points collected over a nearly twelve-month period, this study's results demonstrated the ANN could recognize operational patterns at the Nuclear Engineering Teaching Laboratory (NETL) and detect off-normal behaviors—suggesting that ANNs can be used to support a data-analytic approach to ITDM. Several representative experiments were conducted to further evaluate these conclusions, with the resultant insights supporting collective behavior-based analytical approaches to quantitatively describe insider threat detection and mitigation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Clustering Algorithm for AM Parts using GSH and EDT with Autoencoder

SAND2025-10103O The Clustering Algorithm for AM Parts Using GSH and (EDT With Autoencoder is a software tool. It uses a clustering algorithm for additive manufacturing (AM) parts using generalized spherical harmonics (GSH) and Euclidean distance transform (EDT) with an autoencoder to quantify material microstructure. The tool offers improved sensitivity to microstructural changes compared to traditional approaches. The tool integrates multiple microstructural properties, such as grain morphology, crystallographic orientation, and material phase information, to provide a comprehensive analysis of material microstructures. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Rodgers, Theron [Sandia National Lab. (SNL-CA), Li↗

pyTriBeam

SAND2025-01899O pyTriBeam is a software tool that creates automated processes for a scanning electron microscope including workflows for 3D serial sectioning dataset collection, high-res image montaging, and support for custom script use. This includes integration for 3D chemical mapping (EDS) and crystallographic (EBSD) data collection with select supported detectors. The application allows end users to setup and run customizable data collection workflows without requiring expertise in programming. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hovey, Chad↗

Discrete Element Method Analysis for Metal Powders Used in Additive Manufacturing, and DEM Simulation Tutorial Using LIGGGHTS-PUBLIC [PowerPoint and paper]

Discrete Element Method (DEM) is a method of analysis to evaluate the dynamic interactions between granular particles. This method has been used in the pharmaceutical industry to improve the powder compaction process for tablet manufacturing. There are also applications in agriculture, food industry, and manufacturing. Direct energy deposition is an additive manufacturing technique which uses metallic powders fed through a nozzle, melted using a directed laser, and transformed into a solid object layer by layer. One way of feeding metal particles into the system involves the use of a vibrating hopper. Given a specified amplitude and frequency input, the hopper will enable the powder to travel up a path, and inject through the system with assistance from a stream of gas. The mechanical properties of a printed object can vary, depending on the characteristics of the powder flow and the particles’ as-received properties. Improved understanding of dynamic interactions of flowing powders could enable additive manufacturing components with 2D or 3D variations in mechanical properties, e.g., density. This work uses DEM simulation software to investigate the effects of particle cohesion, friction, and density on the quality of the flow by performing an angle of repose simulation, which is often used as a metric to evaluate the flowability of powders.

36 MATERIALS SCIENCE↗

Document Management: A Focused Analysis on the Configuration Management Process at Y-12 National Security Complex

The configuration management process at Y-12 is a crucial process to ensure safe operations and compliance with Department of Energy (DOE) regulations and requirements. This process is evaluated utilizing systems-thinking methodology in order to understand the current operational flow, with the ultimate goal of building an easily understandable, representative model. This model offers insights on key areas of waste and provides a potential solution by modernizing rate limiting steps: a software implementation to update the traditional document management system and make it paperless. Stakeholders of the software implementation are identified in order to define characteristic requirements of an effective product and the anticipated benefit is evaluated. Ultimately, this project is an effort to increase the quality of life for all stakeholders, while improving the capacity, throughput, and effectiveness of a necessary process at Y-12.

42 ENGINEERING↗

Evaluation of the Barracuda Software Package for Simulating Bubble Motion in Vibrating Liquid-Filled Containers

The commercial software package Barracuda, developed by CPFD Software for simulating particle-laden fluid flows, is evaluated as a means to simulate the motion of bubbles in vibrating liquid-filled containers. Demonstration simulations of bubbles rising due to buoyancy forces in a cylinder filled with silicone oil and angled at 0, 30, 45, and 60 degrees from the vertical were performed by CPFD Software. The results of these simulations are discussed, and the capabilities of Barracuda for simulating bubble motion are assessed. It was determined that at present Barracuda does not meet the needs of the desired application. Further developments that would enable its use for this application are highlighted.

42 ENGINEERING↗

Evaluation of Guardbanding Methods for Calibration and Product Acceptance

The Primary Standards Lab employs guardbanding methods to reduce risk of false acceptance in calibration when test uncertainty ratios are low. Similarly, production agencies guardband their requirements to reduce false accept rates in product acceptance. The root-sum-square guardbanding method is recommended by PSL, but many other guardbanding methods have been proposed in literature or implemented in commercial software. This report analyzes the false accept and reject rates resulting from the most common guardbanding methods. It is shown that the root-sum-square method and the Dobbert Managed Guardband strategy are similar and both are suitable for calibration and product acceptance work in the NSE.

42 ENGINEERING↗

Integrated Methane Monitoring Platform Design (Final Report)

As the urgency for understanding methane emissions and the number of methane monitoring technologies being deployed have increased in the last two decades, there is an opportunity and a need to integrate the numerous disparate data sources to enable the detection, quantification, contextualization, and reporting of methane emissions along the oil and gas supply chain. Such an integration would enable emissions reductions through early detection of super emitters, data-driven mitigation strategies, and improved greenhouse gas inventories. The GTI Energy (“GTI”) project team (“the team”) worked with a multitude of industry experts, stakeholders, and subject matter experts (SMEs) to collect guidance, insights, and information to inform the requirements and subsequent engineering, design, deployment, and operations of an integrated methane monitoring platform (IMMP). This final report describes the results of the team’s effort to execute the Integrated Methane Monitoring Platform Design project, ultimately providing an engineering, design, deployment, and operating plan (EDDOP) for the IMMP. This final report summarizes and integrates the project tasks' results and outputs.

03 NATURAL GAS↗

Grid Utility Asset Vulnerability Assessment (GUAVA) Software Tool

Increasing demand and changes in generation portfolios is pushing power grid to operate towards the limit. However, due to lack of analytical tools for understanding various scales of impact on grid, it is becoming more vulnerable to wide scale power outages and blackouts. A vulnerable grid operating at its limit can be easily disrupted by asset failures caused by devastating hurricanes which has been known to damage transmission and distribution lines along its track. In this direction, researchers have focused on determining these assets by conducting Monte Carlo simulations of hurricanes with uncertainties and collected a large set of simulation data. To determine the infrastructure updates necessary for mitigating wide scale impact of hurricanes on the grid, we propose a software tool named “Grid Utility Asset Vulnerability Analysis” (GUAVA) framework. GUAVA presents a novel data-driven probabilistic analytical approach to (1) post-process hurricane failure scenarios, (2) identify/rank assets that are most vulnerable and critical to failing and are associated with highest impact/risk, and (3) to inform system upgrade decisions & prioritization. Based on the observed results and employed data-driven methodology, it is expected GUAVA can be adapted to provide power system planners with a recommendation engine for making informed decisions to improve resilience of grid.

Mahapatra, Kaveri↗

Code for BALDR Study 07.04

SAND2024-11256O The Code for BALDR Study 07.04 software reproduces results from the BALDR study concerning "Multilabel Proportion Prediction and Out-of-Distribution Detection on Gamma Spectra of Short-Lived Fission Products." This code can reproduce a scientific study following the step numbers present in the file names. The scientific study uses synthetic and measured data to find the best model for the radioisotope proportion estimation task of interest and generates results. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Morrow, Tyler↗

GenConfig

SAND2025-04091O GenConfig converts a build name into a set of configuration flags or CMake fragment files for use with CMake. This is accomplished using ConfigKeywordParser and two configuration files. GenConfig is the main tool in a set of software libraries used for generating and configuring an environment and configuration flags. The tool uses other modules within the GenConfig family to ultimately parse and enable an environment that is ready for development from a given build name string. The unique algorithms used in GenConfig mainly pertain to validating the format and checking the existence of the given build string in the expected configuration .ini files. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Gates, Jason↗