A Multi-Timescale Two-Stage Robust Grid-Friendly Dispatch Model for Microgrid Operation
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97 MATHEMATICS AND COMPUTING↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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A python package for analyzing Resilience of Complex Systems (pyRoCS) v.0.0
SAND2024-01040O PyRoCS software synthesizes mathematical equations from several domains—including information theory, ecology, and engineering sciences—to support resilience analysis for complex systems. Resilience is the ability of the complex system being analyzed to withstand, operate through, and recover from a disruption. The complex system can be a physical system such as an electric grid, an organization such as a company, or even a subfunction of an organization. Existing mathematical equations for resilience analysis are found within multiple domains including information theory, biological sciences, and complex systems. This package synthesizes and refactors equations from these various domains to make them more generalizable for application across different types of complex systems relevant for resilience analysis. Users will be able to apply these equations to characterize different components of complex systems based on available data. 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.
Verzi, Stephen↗
An Integrated Hydroclimatic Assessment of Future Reservoir and Hydropower Operations in the U.S.
The engineering of rivers by dams is a formative feature of human-nature systems and the interconnectivity of water, energy, and the climate. Sufficient and broad-based representations of dams in large-scale hydrological models prove essential to mapping their extensive regulation of river flow and biogeochemistry and gauging climate-linked provisions, including freshwater supply and hydropower. We present an integrated modeling framework to investigate future streamflow and hydropower generation in the Contiguous U.S. (1990–2075), leveraging an ensemble of six downscaled and bias-corrected General Circulation Models (GCMs) from the high-end SSP585 scenario of the CMIP6. To achieve this, we develop a reservoir operations and parameterization scheme for 1,384 dams in a high-resolution river network, including simulated hydropower generation for 326 dams. For the GCM ensemble mean, we simulate a widespread increase in regulated streamflow into the late-century (11% annual and 17% in winter for the dam median) with region-specific changes in summer streamflow that feature prominent declines in the Northwest (−7%). Mediation by reservoirs is shown to dampen intra-annual streamflow changes, delivering additional summer releases that partially mitigate declining flows. Total hydropower generation is projected to increase modestly (+3%), with boosted generation in the winter (+9%) and spring (+5%) offsetting declined summer generation (−3.4%), suggesting strong adaptation potential for hydropower in the future energy portfolio. Further analysis reveals that the choice of GCM, particularly in western regions, has significant bearing on projected streamflow and hydropower changes.
13 HYDRO ENERGY↗
HQ-Tracer
HQ-Tracer is a software plugin related to the open-source project Ghidra. It is used for taking an emulation instruction trace from open source platforms and displaying inside of Ghidra. It allows for software debugging, reverse engineering, and enables interactive forward and backward stepping and searching through the execution traces. 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. SAND2021-4552 O
Wright, ChristopherM.↗
Cylinder block casting slab core cast geometry for sawcut entrance enhancement
An automobile vehicle engine includes multiple water jackets individually formed in a cast engine block proximate to successive ones of multiple cylinder bores. Multiple cast-in place transition regions are individually formed during a casting operation of the cast engine block at entrances to individual ones of the multiple water jackets. Individual ones of multiple sawcuts open into individual ones of the multiple cast-in place transition regions.
Petrus, Ronald John↗
Neural operator prediction of linear instability waves in high-speed boundary layers
Here, we investigate if neural operators can predict the linear evolution of instability waves in high-speed boundary layers. To this end, we extend the design of the DeepOnet to ensure accurate and robust predictions, and also to perform data assimilation. In particular, we train DeepONet to take as inputs an upstream disturbance and a downstream location of interest, and to provide as output the perturbation field downstream in the boundary layer. DeepONet thus approximates the linearized and parabolized Navier-Stokes operator for this flow. For successful application to the high-speed boundary layer problem, we add sample weighting and Fourier input features to the regular DeepONet formulation. Once trained, the DeepOnet can perform fast and accurate predictions of the downstream disturbances within the range of training frequencies (inside the distribution). In addition, we show that DeepONet can solve the inverse problem, where downstream wall measurements are adopted as input, and a trained network can predict the upstream disturbances that led to these observations. This capability, along with the forward predictions, allows us to perform a full data assimilation cycle efficiently: starting from wall-pressure data, we predict the upstream disturbance using the inverse DeepONet and its evolution using the forward DeepONet. Finally, we introduce three new metrics to benchmark the training, evaluation and break-even cost of neural operators.
42 ENGINEERING↗
Integrated system to reduce emissions from natural gas-fired reciprocating engines
Natural gas-fired reciprocating engines (NGFRE), which are naturally aspirated are used in the oil and gas industry for the production, storage, processing, and transmission of natural gas extracted from wells. These stationary, lean-burn engines exhibit increased combustion instability and higher emissions of methane (CH 4 ) and Volatile Organic Compounds (VOCs) at lower loads, resulting in restrictions on the operational envelope of such engines. Here, in this paper, some of the emission reduction technologies for NGFREs are reviewed. Also, an experimental investigation of an integrated system to reduce emissions and improve the combustion performance of an NGFRE is presented. The integrated system consists of an air management package and integrated sensors including an amperometric NOx/O 2 sensor, exhaust temperature thermocouple, pressure transducers and vibration sensors. Experiments were carried out using natural gas and natural gas/propane blends at different load steps, and combustion performance, as well as emissions, were analyzed. For natural gas fuel, the results show that the standard deviation of peak pressure and indicated thermal efficiency (ITE) improved by 67.4 psi and 4.2% respectively, at 40% load. Similarly, CH 4 and Nitrogen Oxides (NOx) emissions reduced considerably by 84% and 63% respectively. However, CO emissions increased from 8 ppm to 152 ppm. At 60% load, the ITE improved by 3.8% and the CH 4 emissions were reduced by 68%. The reduction in VOCs emissions was 63% at 40% load and 69% at 60% load. The findings of this research provide evidence of the effectiveness of the integrated air management system in improving the sustainability of NGFREs. In general, this technology can be implemented on air-assisted combustion applications to improve combustion performance and, consequently, reduce emissions.
33 ADVANCED PROPULSION SYSTEMS↗
Gear Test Assembly – Experimental Testing and Gear Analysis (FY2021 Year End Report)
The Gear Test Assembly (GTA) is an experimental apparatus designed to test mechanical components used in fuel handling systems of liquid-sodium cooled fast-spectrum nuclear reactors. The performance and lifetime of gears, bearings, and dynamic seals are the primary focus of study. Three experimental campaigns have been completed since the start of operation in 2019, and the GTA is currently assembled and ready to begin the fourth experimental campaign. Sodium operations at the Mechanisms Engineering Test Loop (METL) have been paused while repairs are made to the Building 308 Alkali Metal Scrubber. This work is nearly complete, and once METL is brought back into operation the GTA will begin sodium testing immediately.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Release-to-Birth Ratios for AGR-5/6/7 Operating Cycles 162B–168A
This engineering calculations and analysis report (ECAR) documents the release-to-birth ratios of the Advanced Gas Reactor (AGR) experiment, AGR-5/6/7, which was irradiated in the Advanced Test Reactor (ATR) Northeast Flux Trap from February 16, 2018 to July 22, 2020.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
WeightedAFL
WeightedAFL (WAFL) is an improvement to open source fuzzer, American Fuzzy Lop (AFL). Fuzzers modify input to target programs in order to produce crashes and other unintended output in those target programs. WAFL integrates directly with AFL to determine offsets within a buffer that will improve performance metrics. WAFL uses various machine learning techniques to learn these offsets. WAFL also provides a novel software engineering solution to integrate with AFL and allows contributors to quickly write and test algorithms in python. SAND2020-12546 O 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.
Kincher-Winoto, Kina↗
Hydrogen Extremely Low Probability of Rupture Version 1
SAND2024-08511O The Hydrogen Extremely Low Probability of Rupture (HELPR) software toolkit provides probabilistic fracture assessments of natural gas infrastructure for transporting hydrogen. Using probabilistic sampling and sensitivity analysis—along with engineering fatigue and fracture mechanics— the software develops models that can predict structural integrity measures for natural gas pipelines under stress. 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.
Schroeder, Benjamin↗
Palo Verde Water Cycle Model
SAND2022-12901 O The Palo Verde Water Cycle Model (PVWCM) is a dynamic multi-physics and economics code that allows managers and engineers to assess the economic benefit of potential water-saving technologies and water sources before money is invested in them. 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.
Middleton, Bobby↗
Operation-adversarial scenario generation
This paper proposes a modified conditional generative adversarial network (cGAN) model to generate net load scenarios for power systems that are statistically credible, conditioned by given labels (e.g., seasons), and, at the same time, “stressful” to the system operations and dispatch decisions. The measure of stress used in this paper is based on the operating cost increases due to net load changes. The proposed operation-adversarial cGAN (OA-cGAN) internalizes a DC optimal power flow model and seeks to maximize the operating cost and achieve a worst-case data generation. The training and testing stages employed in the proposed OA-cGAN use historical day-ahead net load forecast errors and has been implemented for the realistic NYISO 11-zone system. In conclusion, our numerical experiments demonstrate that the generated operation-adversarial forecast errors lead to more cost-effective and reliable dispatch decisions.
42 ENGINEERING↗
Probabilistic Grid Reliability Analysis with Energy Storage Systems
SAND2025-12025O The Probabilistic Grid Reliability Analysis with Energy Storage Systems (ProGRESS) software tool is an open-source tool for assessing the resource adequacy of the evolving electric power grid integrated with energy storage systems (ESS). This tool uses a simulation engine to create diverse scenarios that test the limits of the modern power grid consisting of a high-volume ESS and variable energy resources (VER). 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.
Nguyen, Tu↗
Rancor-HUNTER: Using a Simulator Engine for Realistic Human Performance Modeling of Nuclear Power Operations
The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a software system to simulate human performance in support of human reliability analysis (HRA) in nuclear power plants. This paper summarizes recent work to integrate HUNTER with a plant simulator, namely the Rancor Microworld Simulator. Rancor is an offshoot of earlier work at Idaho National Laboratory (INL) to support plant modernization. The graphical software tools used to mimic digital human-system interface upgrades at INL’s Human Systems Simulation Laboratory were linked to the Rancor Microworld Simulator, an INL-developed simplified plant model. HUNTER becomes a “virtual operator” coupled to the Rancor simulator, thereby allowing a tight coupling between a digital human twin and a digital twin of the plant. Rancor-HUNTER may be run through Monte Carlo iterations across a dynamic range of performance shaping factors, thereby producing distributions of human performance in terms of procedure paths, errors instantiations, and task durations. This paper overviews the various unique features of Rancor-HUNTER and presents an example run of Rancor-HUNTER for a startup scenario.
99 - GENERAL AND MISCELLANEOUS↗
DieselGen.jl
SAND2026-22947O DieselGen.jl is a Julia tool for diesel-engine generator sizing and performance simulation. It provides a standalone implementation of FASTSim-style diesel fuel-converter behavior with differentiable efficiency and fuel-consumption calculations. 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.
Michelen Strofer, Carlos [Sandia National Lab. (SN↗
Calculating topological properties of artificial graphene in B-field
SAND2025-03258O Calculating topological properties of artificial graphene in B-field is a user-friendly tool designed to analyze artificial graphene systems influenced by magnetic fields. It helps researchers understand the unique properties of these materials by calculating the local Chern marker, a key indicator of their behavior. With just one file, this software runs easily on any device with Matlab, making it accessible for scientists and engineers. It provides valuable insights into the electronic characteristics of artificial graphene, which supports advancements in material science and technology, paving the way for innovative applications in electronics and beyond. 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.
Spataru, Dan [Sandia National Lab. (SNL-CA), Liver↗
2020 Annual Site Environmental Report for Sandia National Laboratories, Tonopah Test Range, Nevada, and Kaua'i Test Facility, Hawai'i
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. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, Tonopah Test Range (SNL/TTR) in Nevada and Sandia National Laboratories, Kaua‘i Test Facility (SNL/KTF) in Hawai‘i. Activities at SNL/TTR are conducted in support of U.S. Department of Energy weapons programs and have operated at the site since 1957. SNL/KTF has operated as a rocket preparation launching and tracking facility since 1962. The U.S. Department of Energy and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this Annual Site Environmental Report. This report summarizes the environmental protection, restoration, and monitoring programs in place at SNL/TTR and SNL/KTF during calendar year 2020. Environmental topics include air quality, ecology, environmental restoration, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety and Health Reporting , and has been approved for public distribution.
54 ENVIRONMENTAL SCIENCES↗