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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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1,091 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CyDER: A Cyber Physical Co-simulation Platform for Distributed Energy Resources in Smartgrids

The CyDER project aimed at developing an open-source, modular and scalable co-simulation platform for power grids with large shares of Distributed Energy Resources (DERs). The project partners are the Lawrence Berkeley National Lab (LBNL), Lawrence Livermore National Lab (LLNL), PG&E, SolarCity, and ChargePoint. The prime recipient is LBNL; SolarCity and ChargePoint were partners for the project’s first two years. Increased DER integration introduces a number of challenges in power grid operation including a more dynamic interaction between the transmission grid and distribution grids, and increased modeling complexity. Although specialized software exists to precisely model different components of the power system, it is far from trivial to integrate all various models and perform a holistic simulation. Instead of replicating all models in a common simulation program, a commonly accepted approach to tackle this model diversity is to couple third-party simulators and models through a co-simulation platform that coordinates information exchange among the various components. Following this line of research, this project’s objective was to develop a co-simulation platform based on a widely accepted industrial standard called Functional Mockup Interface (FMI). Within this process, the project developed models compliant with the FMI standard, called Functional Mockup Units (FMUs), and used them to perform various operational and planning power system analyses. Relying and building upon an industrial standard is the main differentiation of this project compared with previous or parallel efforts in the co-simulation area. Particular emphasis was put on delivering software utilities to facilitate setting up and running co-simulations by end-users. Furthermore, a strong aspect of this project is demonstrating that co-simulation techniques can be used to perform Hardware-in-the-Loop (HIL) simulations that couple software components (e.g., simulated models) with hardware components (e.g., real devices such PV systems and batteries). The long-term goal of CyDER project is to help establish FMI as a powerful standard for co-simulation and promote adoption by electric utilities and other interested stakeholders. The main accomplishments of the project include the development of several FMUs including distribution and transmission grid models, PV inverters with Volt/Var/Watt controllers, batteries, and predictive optimal controllers. Additionally, a unique software package was developed, called SimulatorToFMU, which is capable of exporting any Python-driven simulator or Python script as an FMU. This is an important contribution towards establishing FMI as one of the main co-simulation standards, because more and more third-party programs for sub-system modeling and simulation are delivered with Python APIs. The CyDER platform was used to perform PV hosting capacity analyses in real utility feeders with and without smart inverter controls, battery storage, and EV charging. Smart inverter controls include conventional Volt/Var/Watt controls for reactive power support and active power curtailment, but also predictive controls that optimize the charging and discharging profile of the battery connected on the DC side in order to minimize the customer’s economic benefit. Finally, an important result of this project is delivering an experimental setup that consists of residential-scale PV inverters with battery storage, a real-time grid simulator with an ideal voltage source as grid emulator, and micro Phasor Measurement Units (PMUs). All these components and additional software modules are coupled to one another using the FMI standard and can be co-simulated with the CyDER platform.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Airfoil Computational Fluid Dynamics - 2k shapes, 25 AoA's, 3 Re numbers

This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) - for 1,830 airfoil shapes computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes were designed using the separable shape tensor parameterization that encodes two-dimensional shapes as elements of the Grassmann manifold. This data-driven approach learns two independent spaces of parameter from a collection of sample airfoils. The first captures large-scale, linear perturbations, and the second defines small-scale, higher-order perturbations. For this dataset, we used the G2Aero database of over 19,000 airfoil shapes to learn a parameter space that captured a wide array of shape characteristics. We sampled airfoil designs over both parameter spaces to explore the full range of possible shape variations. The aerodynamic quantities for the generated airfoil were obtained using the HAM2D code, which is a finite-volume Reynolds-averaged Navier-Stokes (RANS) flow solver. We employ a fifth-order WENO scheme for spatial reconstruction with Roe's flux difference scheme for inviscid flux and second-order central differencing for viscous flux. A preconditioned GMRES method is applied for implicit integration. The Spalart-Allmaras 1-eq turbulence model is used for the turbulence closure, and the Medida-Baeder 2-eq transition model is applied to account for the effects of laminar turbulent transition. The airfoil grid is generated with a total of 400 points on the airfoil surface, the initial wall-normal spacing of y+ = 1, and an outer boundary located at 300 chord lengths away from the wall. The CFD simulations are performed at a freestream Mach number of 0.1, for or three different Reynolds' numbers (3M, 6M, and 9M), and for 25 angles of attack from -4 deg. to 20 deg. with 1 degree increments. Across all these various parameters, this dataset includes the results from over 250,000 CFD simulations. The simulations were performed using the Bridges-2 system at the Pittsburgh Supercomputing Center in February 2023 as part of the INTEGRATE project funded by the Advanced Research Projects Agency - Energy, in the U.S. Department of Energy. The data was collected, reformatted, and preprocessed for this OEDI submission in July 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub Repository resource under explore_airfoil_2k_data.ipynb.

2k↗
DOE OSTI2023

Airfoil Computational Fluid Dynamics - 9k shapes, 2 AoA's

This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) - for 8,996 airfoil shapes, computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes were designed using the separable shape tensor parameterization that encodes two-dimensional shapes as elements of the Grassmann manifold. This data-driven approach learns two independent spaces of parameter from a collection of sample airfoils. The first captures large-scale, linear perturbations, and the second defines small-scale, higher-order perturbations. For this data, we used the G2Aero database of over 19,000 airfoil shapes to learn a parameter space that captured a wide array of shape characteristics. We fixed the linear deformations to be the mean over the database and sampled new shapes over a four-dimensional parameter space of higher-order perturbation. This sampling approaches allows for isolated analysis of non-linear airfoil shape deformations while holding other aspects (e.g., airfoil thickness) approximately constant. The aerodynamic quantities for the generated airfoil were obtained using the HAM2D code, which is a finite-volume Reynolds-averaged Navier-Stokes (RANS) flow solver. We employ a fifth-order WENO scheme for spatial reconstruction with Roe's flux difference scheme for inviscid flux and second-order central differencing for viscous flux. A preconditioned GMRES method is applied for implicit integration. The Spalart-Allmaras 1-eq turbulence model is used for the turbulence closure, and the Medida-Baeder 2-eq transition model is applied to account for the effects of laminar turbulent transition. The airfoil grid is generated with a total of 400 points on the airfoil surface, the initial wall-normal spacing of y+ = 1, and an outer boundary located at 300 chord lengths away from the wall. The CFD simulations are performed at a freestream Mach number of 0.1, Reynolds number of 9M, and at two angles of attack, 4 deg. and 12 deg. The simulations were performed using the Bridges-2 system at the Pittsburgh Supercomputing Center in February 2023 as part of the INTEGRATE project funded by the Advanced Research Projects Agency - Energy in the U.S. Department of Energy. The data was collected, reformatted, and preprocessed for this OEDI submission in July 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub Repository resource under explore_airfoil_9k_data.ipynb.

9k↗
DOE OSTI2026

TDCOSMO XXIII. Measurement of the Hubble constant from the doubly lensed quasar HE 1104−1805

Time-delay cosmography leverages strongly lensed quasars to measure the Universe’s current expansion rate, H 0 , independently from other methods. The latest TDCOSMO milestone measurement primarily used quadruply lensed quasars for their mass profile constraints. However, doubly lensed quasars, being more abundant and offering precise time delays, could expand the sample by a factor of 5, significantly advancing towards a 1% precision measurement of H 0 . We present the first TDCOSMO analysis of a doubly imaged source, HE 1104−1805, including the measurement of the four necessary ingredients. First, by combining 17 years of data from the SMARTS, Euler, and WFI telescopes, we measured a time delay of 176.3 +11.4 −10.3 days. Second, using MUSE data, we extracted stellar velocity dispersion measurements in three radial bins with 5% to 13% precision. Third, employing F160W HST imaging for lens modelling and marginalising over various modelling choices, we measured the Fermat potential difference between the images. Fourth, using wide-field imaging, we measured the convergence added by objects not included in the lens modelling. By combining these four ingredients, we measured the time delay distance and the angular diameter distance to the deflector, favouring a power-law mass model over a baryonic and dark matter composite model. The measurement was performed blindly to prevent experimenter bias and resulted in a Hubble constant of H 0 = +5.8 −5.0 × λ int km s −1 Mpc −1 , where λ int is the internal mass sheet degeneracy parameter. This is in agreement with the TDCOSMO-2025 milestone and its precision for λ int = 1 is comparable to that obtained with the best-observed quadruply lensed quasars (4–6%). This work is a stepping stone towards a precise measurement of H 0 using a large sample of doubly lensed quasars, supplementing the current sample. The next TDCOSMO milestone paper will include this system in its hierarchical analysis, constraining λ int and H 0 jointly with multiple lenses.

cosmological parameters↗
DOE OSTI2023

Optical/X-ray/radio view of Abell 1213: A galaxy cluster with anomalous diffuse radio emission

Context. Abell 1213, a low-richness galaxy system, is known to host an anomalous radio halo detected in data of the Very Large Array (VLA). It is an outlier with regard to the relation between the radio halo power and the X-ray luminosity of the parent clusters. Aims. Our aim is to analyze the cluster in the optical, X-ray, and radio bands to characterize the environment of its diffuse radio emission and to shed new light on its nature. Methods. We used optical data from the Sloan Digital Sky Survey to study the internal dynamics of the cluster. We also analyzed archival XMM-Newton X-ray data to unveil the properties of its hot intracluster medium. Finally, we used recent data from the LOw Frequency ARray (LOFAR) at 144 MHz, together with VLA data at 1.4 GHz, to study the spectral behavior of the diffuse radio source. Results. Both our optical and X-ray analysis reveal that this low-mass cluster exhibits disturbed dynamics. In fact, it is composed of several galaxy groups in the peripheral regions and, in particular, in the core, where we find evidence of substructures oriented in the NE–SW direction, with hints of a merger nearly along the line of sight. The analysis of the X-ray emission adds further evidence that the cluster is in an unrelaxed dynamical state. At radio wavelengths, the LOFAR data show that the diffuse emission is ~510 kpc in size. Moreover, there are hints of low-surface-brightness emission permeating the cluster center. Conclusions. The environment of the diffuse radio emission is not what we would expect for a classical halo. The spectral index map of the radio source is compatible with a relic interpretation, possibly due to a merger in the N–S or NE–SW directions, in agreement with the substructures detected through the optical analysis. The fragmented, diffuse radio emissions at the cluster center could be attributed to the surface brightness peaks of a faint central radio halo.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

STRIDES: automated uniform models for 30 quadruply imaged quasars

ABSTRACT Gravitational time delays provide a powerful one-step measurement of H0, independent of all other probes. One key ingredient in time-delay cosmography are high-accuracy lens models. Those are currently expensive to obtain, both, in terms of computing and investigator time (105–106 CPU hours and ∼0.5–1 yr, respectively). Major improvements in modelling speed are therefore necessary to exploit the large number of lenses that are forecast to be discovered over the current decade. In order to bypass this roadblock, we develop an automated modelling pipeline and apply it to a sample of 31 lens systems, observed by the Hubble Space Telescope in multiple bands. Our automated pipeline can derive models for 30/31 lenses with few hours of human time and <100 CPU hours of computing time for a typical system. For each lens, we provide measurements of key parameters and predictions of magnification as well as time delays for the multiple images. We characterize the cosmography-readiness of our models using the stability of differences in the Fermat potential (proportional to time delay) with respect to modelling choices. We find that for 10/30 lenses, our models are cosmography or nearly cosmography grade (<3 per cent and 3–5 per cent variations). For 6/30 lenses, the models are close to cosmography grade (5–10 per cent). These results utilize informative priors and will need to be confirmed by further analysis. However, they are also likely to improve by extending the pipeline modelling sequence and options. In conclusion, we show that uniform cosmography grade modelling of large strong lens samples is within reach.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Higher Efficiency, Demand Flexible Refrigerator with On-Demand Micro-Vibrational De-icing Technology

Refrigerator technology has advanced significantly over the last couple of decades. Today’s refrigerators use only about 25% of the energy that was required to power models built in 1975. Even as they continually improve efficiency to meet standards, refrigerators have increased in size by almost 20%, added energy-consuming features such as through-the-door ice, and provide more benefits than ever before. However, a few challenges and technology gaps are preventing further improvement of the demand responsiveness and efficiency of the refrigerators. One of the major technology gaps in existing refrigerators is their outdated de-icing process. When the evaporator generates frost, an old-fashioned resistive heating element melts the ice. Most refrigerators have a timed defrost cycle, rather than an active system that could monitor the state of the frost. In these systems, not only is the precious electricity used at its least efficient form of conversion (direct conversion of electricity to heat), but also all the latent heat associated with the ice is wasted during the melting process. On top of that, the refrigerator needs to work harder to pull the temperature down after defrosting, and, last but not least, the food quality is severely impacted by the temperature swings during the defrost cycle. According to a study, the EU alone wastes 89 million tons of food in the supply chain every year. Any temperature swing during defrosting (about 6F according to Emerson for low-temperature cases) can negatively impact the shelf life of meat and other products for multiple days. All these issues can happen during the peak demand time of the electric grid. Unlike the conventional systems, the proposed novel advanced micro-vibrational deicing process uses no heat for defrosting. Instead, it uses the micro vibrations generated by a piezoelectric or vibration-generating module to mechanically break ice from the heat exchanger almost instantaneously. The project titled “Higher Efficiency, Demand Flexible Refrigerator with On-Demand Micro-Vibrational De-icing Technology, performed by Ultrasonic Technology Solutions, LLC (UTS) of Knoxville, TN, in collaboration with Emerson (now Copeland), represents the final phase of a multi-year effort funded under the U.S. Department of Energy’s Building Technologies Office (BTO) BENEFIT FOA 2020. Initiated on October 1, 2021, and completed after a nine-month no-cost extension ending September 30, 2025, this project aimed to develop and validate a novel micro-vibrational mechanical defrosting system, achieving more than 25% improvement in defrosting energy efficiency over conventional baseline defrosting technologies. Over sixteen quarters, the project advanced from fundamental ice-mechanical characterization and prototype development to full-scale system integration and validation. Initial efforts established project management infrastructure and characterized ice adhesion properties, followed by the design and fabrication of early aluminum-based prototypes for resonance frequency testing. Subsequent quarters saw rapid technical progression, including the identification of optimal piezoelectric and motor-based vibration mechanisms, the demonstration of effective de-icing over 6x6-inch aluminum surfaces. The team achieved its Go/No-Go milestone by exceeding the 25% energy-efficiency improvement target—reaching up to 3,340% under optimized conditions—and later confirmed that motor-driven systems offered superior performance and energy efficiency compared to piezoelectric alternatives. Continued refinement led to the development of amplifier systems on printed circuit boards, improved control and instrumentation hardware, and integration into full-scale heat exchanger (HX) prototypes at both UTS and Copeland facilities. Multiple vibration-mounting studies and frost-growth experiments guided mechanical optimization and noise-mitigation strategies, achieving a 17.5 dB reduction in sound pressure level and verifying robust mechanical performance. Advanced analyses, including modal and harmonic simulations, established a quantitative understanding of vibrational behavior and de-icing efficiency across >1000 cm² systems. The final project phase successfully demonstrated scalable integration within reach-in and chest freezer prototypes, confirmed >25% efficiency improvements in large-area systems, and completed a comprehensive business model and scale-up strategy identifying electric defrost systems as the primary beachhead market. The culmination of this DOE-supported effort establishes micro-vibrational defrosting as a viable, high-efficiency, low-noise, and demand-flexible de-icing technology, paving the way for commercial deployment and broader application in next-generation refrigeration systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Transportation in net-zero emissions futures: Insights from the EMF-37 model intercomparison study

Transportation is currently the largest source of U.S. anthropogenic CO 2 emissions, at about a third of the total. Achieving net-zero emissions by mid-century will require substantial reductions in transportation emissions across passenger and freight travel. Here we leverage a model intercomparison study to explore the role of transportation in scenarios achieving net-zero economy-wide CO 2 emissions by 2050. We find the transport sector is poised to play the most significant role in reducing demand-side emissions, mostly driven by technology substitution, as modeling results suggest a limited role for mode shifting and for reduced use of personal car travel in the U.S. Among various technology solutions, models show agreement that passenger on-road vehicles will largely transition to electric vehicles (EVs), while solutions to decarbonize heavier travel modes are more diverse and include greater use of liquid biofuels and hydrogen. Research should continue to investigate the evolution of on-road electrification, the role of biofuels and hydrogen across heavier travel modes, and the role of mode shifting and travel behavior change to support personal transportation decarbonization at national and regional scales to temper the rapid growth in clean fuel and electricity demand.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Adaptive Protection and Validated Models to Enable Deployment of High Penetrations of Solar PV (PV-MOD)

The availability and validation of various PV models in commercial tools differ, with some models not yet thoroughly validated for advanced inverter functionalities and reliable performance under weak system conditions. Many existing models do not fully incorporate new inverter control functions, which can affect system stability. The increasing deployment of solar PV and other inverter-based resources (IBRs), including distributed energy resources (DERs), is influencing the reliable operation of protection schemes in distribution systems and microgrids. Emerging adaptive protection schemes (APS) offer new opportunities for protecting these systems during varying configurations and DER operating conditions, though their demonstration and validation remain limited. Adaptive protection schemes face similar challenges, as they are typically designed for specific configurations. There is a growing need for tools and methodologies to streamline the deployment of adaptive protection for safe and reliable DER integration. The project main objective was to develop and validate high-fidelity generic models of solar PV facilities for stability, protection, EMT, and QSTS analyses. This objective was achieved, and these models can now be integrated into commercial software tools, enabling utilities, vendors, and developers to study high-penetration PV systems more confidently. The project also demonstrated advanced applications of these models, including the design and deployment of adaptive protection schemes in high-penetration field applications and microgrids, supporting grid safety and reliability. Several milestones were reached by the end of the project. A sophisticated inverter test plan was developed, and inverters representative of the North American marketplace were selected. EPRI and NREL tested various inverters, conforming to IEEE standards. Improvements were made to existing generic models of IBR units, IBR plants, and aggregated feeders for various analyses. The first generic electromagnetic transient (EMT) model for a solar PV plant was developed, conforming to IEEE Std 2800™-2022 and validated against laboratory measurements of a 2.2 MVA large-scale battery energy storage system (BESS) inverter. That model was then used to produce reference responses illustrating examples of validated and verified IBR plant models that pass or fail tests for technical minimum capability and performance as specified in the IEEE standard. The developed, tested, and validated generic models can be used for transmission planning, stability assessments, expansion planning, and evaluating potential future IBR interconnection requirements. They can also support interconnection screens and conformity assessments of IBR plants, including solar PV. The project significantly contributed to the ongoing standardization and model-based representation and verification of IBR responses. The project further addressed challenges of common distribution protection schemes with increasing deployment of DER by developing, validating, and demonstrating adaptive protection schemes (APS) that can improve the reliable and safe integration of DER into distribution systems. New APS were designed using improved DER models for three common distribution systems: a radial feeder, a meshed network, and a microgrid. Modeling and hardware-in-the-loop (HIL) testing of the APS were conducted, successfully showing their effectiveness and selectivity. Proof-of-concept field demonstration was achieved for two APS, i.e., one on a radial feeder and another one in a microgrid. Field demonstration could not be achieved for the APS on a meshed network, primarily due apprehension of one utility partner and also due to limited access to the protective algorithms in the network protectors. Guidelines developed from the lessons learned in the project lay out the general process followed in the design, installation, and commissioning of APS for various distribution systems. Distribution utility partners’ apprehension about field demonstration of the new APS were addressed—with varying success—by taking a stepped risk-management approach of modeling of a wide range of sensitivities first, performing in-depth proof-of-concept testing in the laboratory including HIL next, and finally deliberately implementing and commissioning the actual protection equipment and algorithms into parts of—or in parallel operation to—the three real distribution systems. Future work should include pilot projects that further show the acceptable performance of the developed APS before these schemes be rolled out more widely. Inclusion of both utility and original equipment manufacturers (OEMs) in future projects could increase chances of successful field demonstration. Despite challenges in achieving the field demonstration goal of the project for all three APS, the research significantly contributed to the innovation of adaptive protection solutions for scalable and reliable DER integration into distribution systems. This project significantly enhances the understanding of the impact of using appropriate inverter models on distribution and transmission (T&D) systems. By addressing the limitations of existing generic models, the project introduces high-fidelity models for stability, protection, electromagnetic transient (EMT), and quasi-static time series (QSTS) analyses. These models, integrated into commercial software tools, enable utilities, vendors, and developers to confidently study high-penetration PV systems. The project also demonstrates advanced applications, including adaptive protection schemes (APS) for distribution systems and microgrids, ensuring grid safety and reliability. The technical effectiveness and economic feasibility of the methods are evident through the development and validation of sophisticated inverter test plans and the selection of representative inverters. Testing by EPRI and NREL on retail, commercial, and utility-scale inverters, conforming to IEEE standards, underscores the robustness of the models. Improvements to existing generic models for various analyses further enhance their validity and applicability. The project also identifies gaps in common distribution protection schemes and designed new APS using improved DER models, demonstrating their effectiveness through modeling and hardware-in-the-loop (HIL) testing. The project’s benefits to the public are manifold. By advancing the standardization and model-based representation of IBR response, it supports transmission planning, stability assessments, and future IBR interconnection requirements. The generic models can facilitate better communication between transmission planners and developers, supporting expected IBR plant capability and performance. Additionally, the development of APS for radial feeders, meshed networks, and microgrids supports the integration of distributed energy resources (DERs) into distribution systems, enhancing grid reliability and safety. The project’s emphasis on thorough testing and simplicity in design ensures practical and scalable solutions for DER integration.

14 SOLAR ENERGY↗
DOE OSTI2023

Tracking Aerosol Convection Interactions Experiment (TRACER) Field Campaign Report

Convective clouds serve a critical role in the Earth’s energy and water cycles through their transport of heat, moisture, momentum, and chemical species through the troposphere driving the global circulation (e.g., Hartmann et al. 1984, Del Genio et al. 2012, Su et al. 2014). On more local scales, convective clouds impact the atmospheric heating profile through diabatic heating effects, removal of water from the atmospheric column through precipitation, and conditioning of the local environment impacting further development of clouds (e.g., Sullivan and Voigt 2021). These critical roles underscore the importance of realistic representation of convective processes across scales of models from large-eddy simulation (LES), to convection-permitting models (CPM; e.g., Kendon et al. 2020, Marinescu et al. 2021), to numerical weather prediction (NWP) models used for operational weather forecasting, to Earth system models used to predict climate sensitivity (Sanderson et al. 2011, Sherwood et al. 2014, Tomassini et al. 2014, Zhao et al. 2016, Cronin et al. 2017). A key component of improving model representation of convective clouds is better quantification and parameterization of updraft microphysics and dynamics, including their interactions with the surrounding environment and storm organization (Bony et al. 2015, Hagos and Houze 2016, Donner et al. 2016, Morrison et al. 2020). Aerosol is an important environmental factor that could affect convective clouds and precipitation since cloud droplet and ice formation processes are initiated by it. Andrae et al. (2004) hypothesized that aerosols associated with increased biomass burning particles acting as cloud condensation nuclei (CCN) result in smaller and more monodisperse cloud droplets leading to suppression of warm rain formation, ultimately leading to more cloud water being lofted above the freezing level based on observations in the Amazon region. The subsequent increase in latent heat release increases the buoyancy of rising convective parcels invigorating the deep convection. This work was followed by a description of the theoretical basis for this “cold-phase invigoration” by Rosenfeld et al. (2008), who argued that it could have a significant effect for deep convective clouds with warm cloud-bases. Several modeling studies (e.g., Khain et al. 2005, 2009, van den Heever et al. 2006, Fan et al. 2007, 2009, 2012, Lee et al. 2008, Storer et al. 2010, Lebo et al. 2012, Storer and van den Heever 2013, Chen et al. 2020, Dagan et al. 2022) have investigated these aerosol-convection interactions and the environmental factors that influence their relative importance and magnitude. More recently, several studies have indicated that “warm-phase invigoration”, the enhancement of convection through condensational heating, also appears to play a role in enhancing both shallow cumuli (Seiki and Nakajima 2014, Saleeby et al 2015) and deeper tropical convection (Lebo and Seinfeld 2011, Khain et al. 2012, Sheffield et al 2015, Fan et al. 2018, Igel and van den Heever 2021), as well as Houston thunderstorms (Fan et al. 2007, 2020). However, still other studies have provided additional evidence of systematic biases in simulated convective outflow ice size distribution properties, which are consistent with a lack of poorly understood secondary ice production within convective updrafts (e.g., Fridlind et al. 2017). To help address these critical gaps in our understanding of cloud processes, aerosol processes and aerosol-cloud interactions, the Tracking Aerosol Convection Interactions Experiment was designed building upon efforts by the Aerosol, Cloud, Precipitation and Climate (ACPC) Initiative (http://acpcintiative.org/), a joint effort of the International Geosphere-Biosphere Programme (IGBP) and the World Climate Research Program (WCRP) that focused on resolving uncertainties in the interactions between aerosol and clouds towards better understanding the role that these interactions play in the climate system. The TRACER campaign was motivated by recommendations from a number of pilot studies undertaken by ACPC (van den Heever et al. 2017, Fridlind et al. 2019, Hu et al. 2019, Fan et al. 2020, Marinescu et al. 2021, Hernandez-Deckers et al. 2022) that pointed towards the southeastern Texas region as a locale where aerosol-convection interactions could be studied owing to the copious occurrence of isolated convection during the summer months accompanied by diverse and significant sources of aerosols from both anthropogenic and natural sources. The TRACER campaign began on 01 October 2021 and extended through 30 September 2022 with an intensive operational period (IOP) during June-September 2022. Three main sites (Table 1) were managed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

PipeSight: A High-Performance Computing Platform for Pipeline Integrity Management

The Phase I feasibility study completed as part of this project has led to a number of innovative technologies being developed and has laid the foundation for a successful Phase II effort to commercialize a platform for managing the integrity of pipelines for the damage mechanisms of the new, hybrid-energy based economy. To ground the development efforts and direction of the project, an extensive market research and customer discovery effort was undertaken early in Phase I. Through this effort, a number of pipeline owners and operators were interviewed, and the following key findings were discovered about the pipeline industry: • Small pipeline operators do not have the central engineering groups necessary to perform their own independent analysis of inspection data, but instead rely on summarized tally sheets provided to them by inspection service providers. • The time it takes to go from an inspection to a completed engineering assessment, even for small segments of pipeline, can take anywhere from 30-120 days. During this delay, critical threats can (and have been known to) cause failures. • Uncertainty is often not accounted for in the assessment of pipeline integrity. The tally sheets provided by third-party service providers are almost always deterministic in nature, identifying threats that present a concern only to the current (not the future) integrity of the pipeline. • It is uncommon to apply the latest technologies to perform advanced assessments of damaged pipelines. There is a desire to use more advanced analysis capabilities to assess threats. Many pipeline operators indicated that they would often excavate a pipeline to perform an inspection and find that the damage was not as bad as they anticipated, thus using limited resources unnecessarily. Companies are not consistent in their use of inspection data to determine corrosion rates, and those that do only calculate deterministic corrosion rates. • The industry has prominently relied on time-based inspections but has recently started to transition to risk-based inspections. However, there appears to be no uniform guidance on how to do so while properly accounting for all sources of uncertainty. • Companies are not storing inspection data in a manner that allows for the ready determination of temporal trends. • Predictive maintenance principles and practices are beginning to be used by early adopters • Some pipelines are being re-purposed to transport different process fluids than they were designed for, e.g., H 2 and CO 2 rich process streams to serve the new hybrid-energy based economy, which are presenting new integrity concerns for the existing pipeline network that crisscrosses the United States. As a result of these discoveries, we were able to target the development efforts in Phase I to best serve the needs of the industry. In Phase I, we developed a way to correlate multiple large-scale scans of the pipeline to determine a probabilistic corrosion rate that accounts for all sources of error and uncertainty in the inspection process. This probabilistic corrosion rate can be used to predict the future thickness distribution of the pipe wall. We demonstrate how this analysis may be performed in an analytical fashion and has been implemented in such a manner that it can be readily distributed using GPU computing through integration of the Kokkos programming model. We also make a very novel extension of the analytical corrosion rate model to Bayesian Networks (an explainable AI technique) that can account for non-parametric distributions of corrosion rates. With the predictions made above for the probabilistic corrosion rate and corresponding future distribution of the pipe wall thickness, we can assess the integrity of the pipeline through the use of a probabilistic engineering assessment. We developed a novel screening data analysis approach that can rapidly identify ‘hotspots’ (local thin areas) where the integrity of the pipeline is a concern. Once more, we implemented this screening approach in C++ to leverage GPU computing via the Kokkos programming model. After the critical hotspots are identified, we developed a program that can automatically generate an advanced finite element model of the damaged regions. Since the number of damaged regions that require advanced analysis can number in the thousands, we integrated an open-source container-native workflow engine for orchestrating parallel jobs on the cloud. Initially, these advanced numerical models were only designed to account for loading due to internal pressure. However, in a slight pivot from the initial Phase I proposal, we developed a complete pipe stress analysis program (called Simflex) which can simulate the complete pipeline and its response to thermal expansion, pressure, thermal bowing, weight, wind, earthquake, support displacement, support friction and external forces. This pipe stress analysis program was written generically, to handle any piping system, but contains the features needed to model long pipelines (i.e., it incorporates a model for soil mechanics and can account for the nonlinear boundary conditions necessary to simulate long underground pipelines). This pipe stress analysis program can simulate any segment of the pipeline (simple or complex) under any set of conditions and loads, to determine the supplemental loads (axial forces and bending moments) at the location of damage. This enables the most accurate state of stress to be accounted for in the pipeline, which can prove critical when evaluating the integrity of a damaged region. In the process of developing the technologies to perform the integrity assessment of the pipeline, we also extended one of the industry standard approaches for performing the assessment of local thin areas that extend more in the circumferential direction than the longitudinal direction of the pipeline. This approach was presented to the API 579-1/AS ME FFS-1 steering committee in November 2021 for consideration in the next edition of the industry standard for Fitness-For-Service (expected to be released in 2023). To help pipeline operators make decisions with the results on any integrity assessment, we developed a new approach to the life-cycle management of pipelines which uses a Bayesian Decision Network. The network is designed to help pipeline operators plan and prioritize inspection activities and ultimately make smarter, more cost-effective decisions. The Bayesian approach accounts for all sources of uncertainty and carries them through to the final optimal decisions, providing a probabilistic framework for optimizing inspection intervals. The proof-of-concept networks developed in the feasibility study are complete, verified, and are focused on a subset of the pipeline. To expand this novel approach to the scale necessary for an entire network of pipelines in Phase II, we will leverage the DOE-funded Bengi solver for industrial-scale decision making with Bayesian Networks [22]. Once implemented, we will be able to provide the pipeline industry with a much-needed tool for optimal inspection planning using truly explainable artificial intelligence (XAI). To handle all of these advanced capabilities into a cloud-based platform, the architecture of the Equity Engineering Cloud (EEC) was extended to include Argo Workflows, a framework capable of distributing and managing a massive number of jobs that consume their own resources, such that thousands of serial finite element simulations can be run in parallel. As part of this substantial undertaking, we also integrated Argo Continuous Delivery (CD) into the EEC, to aid with the rapid prototyping and iterations that will be imperative to the success of the PipeSight platform’s Agile development process in Phase II. As part of the pipe stress analysis program, we also developed a custom visualizer that leverages the DOE-funded VTK visualization library. We added custom contouring capabilities and a means for interacting visually with both the inputs and outputs of the pipe stress analysis program. We also developed routines for automating the post-processing of the finite element simulations to determine if any failure criteria are met and to visualize the deformations, stresses and strains in ParaView using the exodus II file format (a subset of netCDF).

24 POWER TRANSMISSION AND DISTRIBUTION↗