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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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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Perspectives of Open-Air Processing to Enable Perovskite Solar Cell Manufacturing

We report high throughput open-air processing techniques for the scalable production of all device and barrier layers for perovskite photovoltaics (PV). This work discusses and resolves some of the most formidable barriers to module-level scaling that the perovskite community has been facing. Our advanced technoeconomic manufacturing analysis indicates that vacuum-based processes with high capital expenditures (CapEx) and low throughputs dominate the cost of production. Open-air fabrication methods offer low CapEx routes to manufacturing, but achieving reproducibility in ambient conditions with varying relative humidity has been a persistent challenge. The use of rapid processing methods with plasma curing to convert films from the solution-state enables reproducibility, moisture immunity, and the highest perovskite PV efficiency produced in open-air. These methods are readily translatable to in-line processing where layers are sequentially deposited without the need for lengthy post-annealing steps that reduce throughput and involve additional equipment. Significant progress is demonstrated in reduced manufacturing costs as perovskites contend as a commercially viable next-generation thin film PV technology.

14 SOLAR ENERGY↗
DOE OSTI2020

Scaling Global Warming Impacts on Ocean Ecosystems: Lessons From a Suite of Earth System Models

An important technique used by climate modelers to isolate the impacts of increasing greenhouse gasses on Earth System processes is to simulate the impact of an abrupt increase in carbon dioxide. The spatial pattern of change provides a “fingerprint” that is generally much larger than natural variability. Insofar as the response to radiative forcing is linear (the impact of quadrupling CO 2 is twice the impact of doubling CO 2 ) this fingerprint can then be used to estimate the impact of historical greenhouse gas forcing. However, the degree to which biogeochemical cycles respond linearly to radiative forcing has rarely been tested. In this paper, we evaluate which ocean biogeochemical fields are likely to respond linearly to changing radiative forcing, which ones do not, and where linearity breaks down. We also demonstrate that the representation of lateral mixing by mesoscale eddies, which varies significantly across climate models, plays an important role in modulating the breakdown of linearity. Globally integrated surface rates of biogeochemical cycling (primary productivity, particulate export) respond in a relatively linear fashion and are only moderately sensitive to mixing. By contrast, the habitability of the interior ocean (as determined by hypoxia and calcite supersaturation) behaves non-linearly and is very sensitive to mixing. This is because the deep ocean, as well as certain regions in the surface ocean, are very sensitive to the magnitude of deep wintertime convection. The cessation of convection under global warming is strongly modulated by the representation of eddy mixing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Hydrodynamic and frictional modulation of deformations in switchable colloidal crystallites

Displacive transformations in colloidal crystals may offer a pathway for increasing the diversity of accessible configurations without the need to engineer particle shape or interaction complexity. To date, binary crystals composed of spherically symmetric particles at specific size ratios have been formed that exhibit floppiness and facile routes for transformation into more rigid structures that are otherwise not accessible by direct nucleation and growth. There is evidence that such transformations, at least at the micrometer scale, are kinetically influenced by concomitant solvent motion that effectively induces hydrodynamic correlations between particles. Here, we study quantitatively the impact of such interactions on the transformation of binary bcc-CsCl analog crystals into close-packed configurations. We first employ principal-component analysis to stratify the explorations of a bcc-CsCl crystallite into orthogonal directions according to displacement. We then compute diffusion coefficients along the different directions using several dynamical models and find that hydrodynamic correlations, depending on their range, can either enhance or dampen collective particle motions. These two distinct effects work synergistically to bias crystallite deformations toward a subset of the available outcomes.

42 ENGINEERING↗
DOE OSTI2025

PV Degradation Modeling: Applying Geospatial Workflows with "PVDeg"

Accurate degradation modeling is essential for predicting photovoltaic (PV) module performance, estimating longevity and informing design decisions. With degradation rates varying significantly by location, geospatial analysis is critical for PV and broader applications, such as agrivoltaics, weathering and environmental data analysis. This work presents PVDeg, an open-source tool designed for geospatial degradation analysis. PVDeg integrates meteorological data from global sources, including the National Solar Radiation Database (NSRDB) and Photovoltaic Geographical Information System (PVGIS), with degradation models. The toolkit enables users to customize geospatial workflows by integrating weather data, material parameters, and user-defined Python functions. It facilitates accelerated downloads of NSRDB and PVGIS datasets and optimizes geospatial point selection to preserve data density in regions of interest. Additionally, PVDeg provides a local database for storage and spatial queries, supporting large-scale analyses without the need for high-performance computing (HPC) resources. PVDeg provides a foundational workflow that extends its utility beyond PV applications, enabling researchers to analyze geospatial processes across discipline.

14 SOLAR ENERGY↗
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 OSTI2025

Atomic-scale imaging of frequency-dependent phonon anisotropy

Directly visualizing vibrational anisotropy in individual phonon modes is essential for understanding a wide range of intriguing optical, thermal and elastic phenomena in materials. Although conventional optical and diffraction techniques have been used to estimate vibrational anisotropies, they fall short in achieving the spatial and energy resolution necessary to provide detailed information. Here, we introduce a new form of momentum-selective electron energy-loss spectroscopy, which enables the element-resolved imaging of frequency- and symmetry-dependent vibrational anisotropies with atomic resolution. Vibrational anisotropies manifest in different norms of orthogonal atomic displacements, known as thermal ellipsoids. Using the centrosymmetric strontium titanate as a model system, we observed two distinct types of oxygen vibrations with contrasting anisotropies: oblate thermal ellipsoids below 60 meV and prolate ones above 60 meV. In non-centrosymmetric barium titanate, our approach can detect subtle distortions of the oxygen octahedra by observing the unexpected modulation of q-selective signals between apical and equatorial oxygen sites near 55 meV, which originates from reduced crystal symmetry and may also be linked to ferroelectric polarization. These observations are quantitatively supported by theoretical modelling, which demonstrates the reliability of our approach. The measured frequency-dependent vibrational anisotropies shed new light on the dielectric and thermal behaviours governed by acoustic and optical phonons. Furthermore, the ability to visualize phonon eigenvectors at specific crystallographic sites with unprecedented spatial and energy resolution opens new avenues for exploring dielectric, optical, thermal and superconducting properties.

Ferroelectrics and multiferroics↗
DOE OSTI2019

Multi-Scale Modeling of Thermal-Fluid Phenomena Related to Loss of Forced Circulation Transient in HTGRs

Under the support of DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS), an effort had been pursued to support High Temperature Gas-cooled Reactors (HTGR) technology development and its modeling and simulation needs. There was a particular need for advanced modeling & simulation tools to predict thermal-fluid behavior in the nuclear reactor primary system, especially the core and lower and upper plena, during safety-related transients. In this report, two main such activities were presented: 1) system level HTGR simulations using system analysis code SAM for both normal operating and accident conditions; and 2) three-dimensional (3D) computational fluid dynamics (CFD) simulations on Deteriorated Turbulent Heat Transfer (DTHT) of interest to HTGR transients, including code benchmark and closure correlation development. In this work, Modular High Temperature Gas-cooled Reactor (MHTGR) full loop simulations were performed using System Analysis Module (SAM) code. Two approaches were used to model the reactor core; (i) unit-cell or lumped parameter model, and (ii) detailed ring model, to address the different needs under different reactor conditions. Aside from the core model changes other reactor components in the primary system, such as upper/lower plenum, heat exchanger and blower etc, were kept the same. In the unit-cell core model, the lumped parameter approach was used to model the coolant channels and the heat structures using 1-D and 2-D components, respectively. The fuel assembly heat structure was modeled based on unit-cell thickness approximation. In normal and controlled operating conditions, the calculated maximum temperatures for both coolant and heat structures were within the designed limits. The unit-cell model is, however, not able to capture the radial heat conduction through fuel assemblies, which is the dominant heat transfer mechanism during accident transients, such as pressurized conduction cooldown (PCC) event. To address this modeling challenge, ring models were developed. A simplified ring model was developed first. In this simplified model, the active core was simulated with 9 circular rings consists of 6 rings for homogenized fuel heat structure and 3 rings for gas coolant. It was quickly found that this model gives rather large simulation error as it was not able to correctly capture the solid structure representative geometries. A detailed ring model was developed to address this issue. The active core was simulated with 99 circular rings consists of 66 rings for homogenized fuel heat structure and 33 rings for gas coolant. In both ring models, six additional rings were included to represent inner reflector, outer reflector, core barrel, Reactor Pressure Vessel (RPV), RPV coolant channel, and Reactive Cavity Cooling System (RCCS). The detailed ring model was applied in two different SAM simulations; (i) normal operating conditions, and (ii) accident scenarios (more specifically, PCC event), for MHTGR design. In both simulations, the SAM calculated results for coolant and heat structure temperatures were within the reactor designed limits. The newly proposed detailed ring model approach in this work has proved to be a promising method to address the challenging modeling and simulation needs in the MHTGR design. As demonstrated in this work, this model was suitable for MHTGR simulations under both normal and accident conditions. Apart from the SAM model development for gas-cooled reactors, 3D Computational Fluid Dynamics (CFD) models were developed and validated with relaminarized Deteriorated Turbulent Heat Transfer (DTHT) MIT benchmark test. Two different CFD codes, Nek5000 and STAR-CCM+, were used for this benchmark activity. Compared with MIT data, Nek5000 shows very good agreement between its simulated and experimentally measured wall temperatures. In contrast, STAR-CCM+ under-predicted wall temperature due to over predicted turbulence in the wall region. The Nek5000 code was also used to develop wall-heat transfer correlations for laminar flow in cylindrical tube. Several simulations were performed for various Reynolds flow and wall heat fluxes. Significant deviations were found when compared the predicted heat transfer coefficient and the Sieder-Tate correlation. A new set of heat transfer correlation was proposed for laminar flow which is valid for 400<Re<2000.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Enabling Staged Pressurized Oxy-Combustion: Improving Flexibility and Performance at Reduced Cost

Introduction: The staged pressurized oxy-combustion (SPOC) process, developed by Washington University in St. Louis (WUSTL), is an oxy-combustion carbon capture technology that employs a steam power cycle to generate electricity. As with atmospheric-pressure oxy-combustion processes, carbon dioxide (CO 2 ) capture rates of 90% or higher can be achieved. The staged-combustion approach of the SPOC process, when operated at elevated gas pressure, allows for near elimination of flue gas recycle (FGR) and leads to significant improvements in efficiency and reduced costs. The primary goal of this project was to investigate the potential for SPOC for flexible operation beyond the capabilities of conventional coal-fired power plants, particularly those employing carbon capture and storage (CCS). Oxy-combustion differs from conventional coal combustion in that the combustion of coal is carried out using oxygen as opposed to air. The resultant flue gas is a mixture of primarily CO 2 and water, greatly simplifying CO 2 capture. As SPOC does the oxy-combustion process under pressure, it is higher efficiency and lower cost than atmospheric oxy-combustion. The project was led by the Electric Power Research Institute, Inc., with the assistance of WUSTL, Doosan Babcock (DBL – boiler plant original equipment manufacturer), and Air Liquide (AL – air separation experts). The specific objectives of the project were to: (1) Evaluate the SPOC concept and develop a risk-based approach to the heating surface layout ensuring that performance (gas and steam side), manufacturing, transportation, and plant erection considerations were fully accounted for in the system design. (2) Improve the technology to ensure its performance and cost potential are substantially better than today’s baseline pulverized coal power plant with post-combustion capture (PCC) or atmospheric oxy-combustion, and show progress toward performance commensurate with projected commercial operation, including 90% or more CO 2 capture. (3) Address critical technology gaps and improving overall system performance for the technology. (4) Perform combustion tests at scale under commensurate pressure to the commercial operating system validate combustor and advance the SPOC combustion modeling tools that will facilitate full-scale design. Combustion Testing: Testing was initially carried out at atmospheric pressure with methane to ensure that all systems were correctly operating. Following this, the testing then proceeded to moderate pressure operation at 4 bara, where different stoichiometric conditions were used across an extended heat input range, showing that a stable flame could be maintained. Testing then proceeded at 10 and 15 bara where it was shown that the ignition system needed to be replaced at these operating conditions. When testing recommenced, a similar stable flame shape was achieved, without any methane support, and the full 100 kWth coal oxy-combustion was demonstrated. Heat flux measurements showed 400 kW/m 2 (0.126 MMBtu/hr-ft 2 ) from the flame, within the 450 kW/m 2 (0.142 MMBtu/hr-ft 2 ) preferred limit defined by DBL for the full-scale design case. Carbon monoxide and carbon-in-ash measurements showed that complete combustion was possible with ultra-low excess oxygen at 1 vol % in the product flue gas. This allowed the full-scale models to be calculated based on this level of excess oxygen, improving the performance of the system as lower feed oxygen is produced in the air separation unit (ASU), saving auxiliary power. Full-Scale Design: The full-scale design is sized to deliver 550 MWe net electrical power output to allow direct comparison with the National Energy Technology Laboratory (NETL) baseline cases using the same Montana Powder River Basin (PRB) fuel. The cases used for direct comparison are: Case S12A (supercritical [SC] coal without CO 2 capture), Case S12B (SC coal with PCC at 90% CO 2 capture, and Case S12F (atmospheric oxy-combustion SC coal with 90% CO 2 capture). The SPOC stages were configured to be identical arrangements, allowing for a more straightforward design, construction, and control strategy. Each stage consists of two PVs, the first being the combustor PV module and the second being the convective PV module. The combustor module is the tallest vessel, with local coal feeding equipment and the burner FGR and oxygen plenums at the top and ash management at the bottom. The combustor module is effectively an open cross section with membrane tubes around the circumference – this unobstructed slender profile ensures that the relatively slower burnout mechanism needed for the low-speed turbulent mixing burner can proceed unimpeded and that molten ash will not attach to any surfaces at an angle to the predominant flue gas flow. The steam turbine used in the SPOC design is essentially the same unit utilized in the atmospheric oxy-combustion case except the degree of heat recovery possible allows the low-pressure (LP) feedwater heater train to be eliminated. This is a result of being able to capture the latent heat of evaporation of the moisture produced in the combustion (normally lost to the stack). The SPOC system outperforms the NETL atmospheric oxy-combustion baseline case by 3.3% points and the PCC case by 7.5% points. This performance increase is mainly a result of the improved heat recovery possible from the product flue gas and from the reduced auxiliary power consumption from the ASU and the CO 2 compression and purification unit over the atmospheric equivalent. The combined improvement in boiler efficiency and reduction in the steam turbine heat rate resulted in a net improvement in the overall plant efficiency by 0.61%, to 35.6% on a HHV basis. This relatively small improvement in plant efficiency between sub-bituminous and bituminous coals shows the value of useful moisture latent heat recovery offered by the SPOC system when using low rank fuels. Flexibility and Turndown: The SPOC system has inherent high turndown capabilities because of a demonstrated high range of combustion stability and the ability to bypass stages, thereby reducing steam generation rates proportionally without altering firing rates in operating stages. ASU units do not generally offer significant turndown opportunities as they are limited by the performance of the compression plant. The baseline SPOC design has a 2-train ASU configuration, needed to be able to meet the 10,500 tonnes per day duty, that can deliver efficient turndown points between 85–100% load with both trains operating, and at 45–50% load with a single train operating. Outside these operating points, the flexibility and efficiency are limited and may be uncompetitive at loads below 45% as the ASU systems are unable to turndown beyond 85% for the base case and 70% for the flexible case. The ASU cold box for the flexible case was designed to operate at loads between 40-100%, below this operating range the purity of the produced oxygen cannot be guaranteed, resulting in additional load for the CPU equipment. The additional power consumption of these cases yields an uneconomic operating condition with poor efficiency when operating at low loads such as 25% and 12%. To address this flexibility constraint, AL evaluated how the ASU configuration could be altered to deliver efficient oxygen supply over the load range. This involved integrating the compressor duties across both ASU trains into a shared duty arrangement with multiple compressors, strategically sized to deliver the duty required across all load ranges between 40–100% by enabling different combinations of the main air compressors and the booster air compressors. The oxygen purity cannot be guaranteed below 40% load for each train – the power consumption at 25% and 12% loads were estimated based on the multi-compressor configuration at maximum turndown as these load cases were not considered in the flexible ASU design. With a different cold box configuration, i.e. number of trains, the entire load range could be delivered within oxygen purity specifications. Although there is a small efficiency reduction at full load, there are significant improvements in overall plant performance during low-load operation. The exact ASU configuration needed will therefore be dependent on the expected operating profile of the unit. Economic Analysis: Cost estimates for the baseline and the flexible cases were developed using NETL baseline case data for common BOP items and an Association for the Advancement of Cost Engineering International Class 5 (conceptual/screening study) assessment of key components unique to the SPOC system. The capital, operating, and maintenance costs were assessed along with the first-year power cost, levelized cost of electricity, and CO 2 captured and avoided cost for the SPOC cases were compared against the relevant NETL baseline cases in January 2019 dollars. Both SPOC cases achieve a lower cost that the alternative NETL baseline cases (with the flexible SPOC case being slightly higher than the baseline SPOC case due to the compounded impact of higher capital costs and lower efficiency at full load). The SPOC cases deliver a lower cost of CO 2 avoided than the NETL baseline cases due to greater efficiency in generating low-carbon power. However, the cost of CO 2 captured is higher because the higher efficiency of the SPOC process generates less CO 2 , hence less needs to be captured, resulting in a high capital cost being shared over a reduced CO 2 quantity. The flexible ASU adds 1.6% overall to the plant cost in comparison to the baseline case, but the efficiency improvements at loads below 50% are significant. Subsequently, depending on the plant load-profile expectation, the flexible ASU would be beneficial if the plant spends a significant portion of its operating life below 50% load. This kind of operating profile is likely to be required for all fossil plants when more renewable electricity generators are installed on the local grid, particularly solar power that can be predicted ahead of time, allowing for appropriate pricing signals to be incorporated into the diurnal cycle. R&D Recommendations: SPOC, while a promising technology, is a relatively recent concept and, as such, operability issues of combustor design and steam-side integration for such systems at a scale relevant to commercial deployment have not been evaluated. WUSTL has conducted extensive small pilot-scale (100 kWth) research to understand and advance pressurized oxy-combustion processes, including investigation of combustion and flame characteristics, radiative heat flux, burner operability, turn down, char burnout, ash characteristics, water-wash column operation, etc. for pressurized oxy-combustion systems. Nonetheless, at this stage in the development of the SPOC process, what is needed is a large-scale pilot plant that can serve to study pressurized oxy-combustion systems and components at a scale commensurate with the maturity of the technology. A scale of 10 MWth, which includes steam-side integration and two stages would yield essential information with respect to heat transfer characteristics both in the radiative and convective sections of the pressure vessels, and the ability to operate the fuel staging process. In addition, while modeling results indicate that combustion and flame characteristics improve with scale, direct studies of the combustor at this scale will ensure that the models can be relied upon for scale up to commercial scale. Furthermore, a detailed analysis must be performed to understand the scaling aspects of key components and systems.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Neural network model of the multi-mode anomalous transport module for accelerated transport simulations

Here, a neural network version of the Multi-Mode Anomalous Transport Module, known as MMMnet, has been developed to calculate plasma turbulent diffusivities in DIII-D with a calculation time suitable for control applications. MMMnet uses a simple artificial neural network structure to predict the ion thermal, electron thermal, and toroidal momentum diffusivities while reproducing Multi-Mode Model (MMM) data with good accuracy and keeping the calculation time as a fraction of that associated with MMM. Model-based control techniques require models with fast calculation times, making many existing physics-oriented predictive codes unsuitable. The control-oriented predictive code COTSIM (Control Oriented Transport SIMulator) calculates the most significant plasma dynamics in response to the different actuators while running at a speed useful for control design. In order to achieve this calculation speed, COTSIM often relies on scaling laws and control-level models. Replacing some of these scaling laws and control-level models with neural network versions of more complex physics-level models has the potential of increasing the range of validity and the level of accuracy of COTSIM without compromising its computational speed. In this work, MMMnet is integrated into COTSIM to improve the turbulent diffusivity predictions, which will in turn improve the prediction accuracy associated with the dynamics of many plasma properties.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗
DOE OSTI2022

Leafweb: Dataset in Support of Coupled Modeling of Photophysics, Photochemistry, and Biochemistry of Photosynthesis, December 2022 Release

This data set contains measurements of leaf gas exchange and Pulse-Amplitude Modulated (PAM) fluorometry of light, carbon dioxide (CO2), oxygen (O2), and temperature responses from 26 C3 photosynthetic and four C4 photosynthetic species measured by independent researchers in Canada, China, Finland, Netherlands, and United States in the field, garden, or greenhouse. Data were collected between 1987 and 2021, however data for individual species only provide coverage over a few hours to one year. Species include three lianas, three shrubs, two boreal deciduous trees, two boreal evergreen needle-leaf tree, three temperate deciduous trees, four tropical deciduous trees, three tropical evergreen trees, one C3 grass, three C4 grasses, and six crop varieties. These measurements are conducted according to standard protocols in gas exchange (Long and Bernacchi 2003) and PAM fluorometry (Baker 2008). The Scots pine (Pinus sylvestris) dataset contains one-year continuous fluorometry observations made at intervals of 10 or 30 minutes in the field under natural environments using Walz monitoring PAM. Measurements from all other 29 species include simultaneous PAM fluorometry and gas exchange observations. Among these 29 species, seven species were measured with light response curves only (i.e., light intensity varied systematically with ambient CO2 concentration controlled at a constant level, e.g., 400 ppm). All the other 22 species were measured with both the light response and CO2 response (i.e., ambient CO2 concentration varied systematically with light intensity controlled at a constant level, e.g., 1200 µmolm-2s-1). For most species, measurements were made with temperature controlled at ~ 25 degrees Celsius (C) with the exceptions of Scots pine (natural diurnal and seasonal variations), tomato cultivar Basket Vee (~ 21 degrees C), and cotton which contained temperature stress experiments (9 to 40 degrees C). All measurements were made at ambient O2 concentration except for the tomato cultivar Basket Vee and cotton which used two O2 levels (2 and 21%) and rice and tomato cultivar Growdena which used five O2 levels (2, 10, 21, 35, and 50%). This dataset supports the complete modeling of photosynthesis at the leaf scale, including photophysical, photochemical, and biochemical reactions. It will support research in the applications of remotely sensed solar induced chlorophyll fluorescence and the responses of energy dissipation pathways to environmental variations across species and climates. This dataset contains 260 data files in comma separate (.csv) format contained inside 11 compressed (*.zip) files. Additional metadata are provided: one data dictionary, a species information table, and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

air temperature↗
DOE OSTI2021

Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions

Abstract Wetland methane (CH 4 ) emissions ( $${F}_{{{CH}}_{4}}$$ F C H 4 ) are important in global carbon budgets and climate change assessments. Currently, $${F}_{{{CH}}_{4}}$$ F C H 4 projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent $${F}_{{{CH}}_{4}}$$ F C H 4 temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that $${F}_{{{CH}}_{4}}$$ F C H 4 are often controlled by factors beyond temperature. Here, we evaluate the relationship between $${F}_{{{CH}}_{4}}$$ F C H 4 and temperature using observations from the FLUXNET-CH 4 database. Measurements collected across the globe show substantial seasonal hysteresis between $${F}_{{{CH}}_{4}}$$ F C H 4 and temperature, suggesting larger $${F}_{{{CH}}_{4}}$$ F C H 4 sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH 4 production are thus needed to improve global CH 4 budget assessments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Toroidal modeling of runaway electron loss due to 3-D fields in DIII-D and COMPASS

The 3-D field induced relativistic runaway electron (RE) loss has been simulated for DIII-D, COMPASS and ITER plasmas, utilizing the MARS-F code incorporated with the recently developed and updated RE orbit module (REORBIT). Modeling shows effectively 100% loss of a post-disruption, high-current runaway beam in DIII-D, due to the 1 kG level of magnetic field perturbation produced by a fast growing n = 1 resistive kink instability. The RE loss is shown to be independent of the particle energy or the initial location of particles in the configuration space. Applied resonant magnetic perturbation (RMP) fields from in-vessel coils are not effective for RE beam mitigation in DIII-D, but do produce finite (>10%) RE loss in COMPASS, consistent with experimental observations in above two devices. The major reasons for this difference in RE control by RMP between these two devices are (i) the coil proximity to the RE beam and (ii) the effective coil current scaling versus the machine size and the toroidal magnetic field. About 10% RE loss fraction is also predicted for an ITER 15 MA scenario with pre-disruption plasma, highlighting the role of the plasma response. Up to 30% loss is computed, however, by artificially scaling the equilibrium pressure to zero. This is due to the more resistive plasma response and stronger resulting field line stochasticity. Distributions of the lost REs to the limiting surface show poloidally peaked profile near the high-field-side in both DIII-D and COMPASS, covering about 100o poloidal angle. Higher perturbation field level and/or higher particle energy also result in REs being lost to the low-field-side of the limiting surface of these two devices, increasing the effective wetted area. Finally, for the modeled ITER plasmas, the applied RMP field, with optimal poloidal spectrum that maximizes the edge localized mode control, leads to REs being lost to the lower divertor region of the limiting surface within a narrow poloidal band.

3-D field↗
DOE OSTI2019

Prediction of divertor heat flux width for ITER using BOUT++ transport and turbulence module

Investigation of turbulent transport dynamics in scrape-off-layer (SOL) and divertor heat flux width prediction is performed for ITER. Both BOUT++ transport and BOUT++ turbulence codes are applied to capture the physics on different temporal scales. Simulations start with an ITER 15MA baseline scenario profile generated by CORSICA (Kim et al 2015 Paper ITER_D_R9T8J9 v1.1). In BOUT++ transport code, the plasma parameters ( n i , T i , T e ) and radial electric () profiles are evolved to steady state. Here, the initial plasma profiles inside the separatrix are taken from CORSICA scenario studies. Transport coefficients are calculated by inverting the plasma profiles inside the separatrix.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Thermal performance and energy consumption validation of an occupied local government office building outfitted with ceiling tile phase change materials

Buildings present an opportunity for energy conservation and the modulation of peak energy demand through controlled Heating, Ventilation, and Air Conditioning (HVAC) energy use. The administrative and office building stock in the United States holds potential to achieve energy and demand savings through retrofits such as insulation, weatherization, and thermal energy storage. Specifically, there is a need to validate passive phase change material (PCM) applications in full scale in aging administrative buildings in the US to evaluate the energy benefits. Aim of this study was to conduct a whole building level thermal and energy validation of an operational building and explore an alternative method for evaluating energy efficiency. To accomplish this, the study employed PCMs in the drop ceiling and carry out an energy audit and on-site measurement of HVAC systems' energy demand and consumption. A full-scale EnergyPlus energy model, modeled by the authors, served as a baseline for evaluation. The results show that calibrated model's envelope temperature measures fall within the accepted errors. HVAC energy simulation results also fall within the accepted errors for monthly and hourly pre- and post- PCM retrofit electricity and natural gas data. The novelty of this study is that it employees energy scales per Heating Degree Hour and Cooling Degree Hour, in contrast to the commonly used Heating Degree Days and Cooling Degree Days as reported in the literature to analyze energy savings. These findings underscore the pivotal role of a calibrated model in assessing the efficacy of a singular energy measure, like a PCM-retrofitted ceiling, in an occupied office building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

The two radiative states of the Arctic atmosphere and their impacts on the surface energy budget of sea ice

The surface energy budget (SEB) is a central regulator of Arctic climate and sea ice evolution, yet its processes remain poorly constrained due to sparse observations and complex, coupled surface-atmosphere interactions. This study leverages year-long measurements from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) to provide the most comprehensive assessment to date of the central Arctic SEB and its modulation by atmospheric variability. Ship- and ice-based observations from October 2019 to September 2020 were used to directly measure or tightly constrain each term of the SEB, leading to exceptional energetic closure with the seasonal snow and ice mass balance. The analysis reveals strong seasonal transitions in atmosphere-surface energy transfer that are modulated by the atmospheric state and constrained by the ability of the surface temperature to respond. Classification of the atmosphere into its two dominant radiative states—the semi-transparent (ST) and opaque (OP)—highlights the central role of synoptic-scale variability in clouds. The ST atmospheric state dominated the long winter ice growth season, with limited cloudiness supporting persistent surface radiative cooling and ice growth. The OP state, associated with liquid-containing or thick ice clouds, became dominant in spring, with the combination of increased solar heating and cloud surface longwave warming driving ice and snow melt. Eddy covariance versus bulk approaches for deriving surface turbulent heat fluxes provide vastly different perspectives on the role of turbulence in modulating the SEB. These results establish a high-quality benchmark dataset for Arctic SEB studies and demonstrate how the balance of atmospheric radiative states exerts a first-order control on the annual evolution of the sea ice. The findings have broad implications for advancing observing technologies, understanding Arctic amplification, improving climate models, and predicting future sea ice change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Pattern-enhanced Resonant Soft X-ray Scattering for Operando monitoring of electrochemical solid-liquid interfaces

Unveiling interfaces at sub-nanometer scales is essential for advancing the understanding of complex chemical transformations. However, characterizing solid-liquid interfaces with high dimensional sensitivity and temporal resolution remains challenging, due to their dynamic nature and inaccessibility by conventional probes. Here we present an approach, Pattern-enhanced Resonant Soft X-ray Scattering, to overcome the challenges. Rooted in a “sample-as-optics” philosophy, this technique utilizes precisely engineered line-grating nanopatterns to modulate near-field X-ray illumination, coherently enhancing scattering signals from the line-gratings. We implement the method using Ni line-grating nanopatterns in electrochemical water oxidation. The periodic nanostructures serve as diffractive optical elements to reveal the Ni oxidation gradients and structural dynamics at the electrode-electrolyte interfaces. Finite-element simulations corroborate the observed trends by modeling variations in compositions and structures during electrocatalysis. Through integrating advanced sample design with coherent wave nature of soft X-rays, our approach opens accessible pathways to operando exploring chemical evolution and sub-nanometer dimensional variations simultaneously in electrochemical systems. This non-destructive method is efficient and element-specific, making it valuable for probing chemical and dimensional dynamics with appropriate modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Background-Aware 3-D Point Cloud Segmentation With Dynamic Point Feature Aggregation

With the proliferation of LiDAR sensors and 3-D vision cameras, 3-D point cloud analysis has attracted significant attention in recent years. In this article, we propose a novel 3-D point cloud learning network, referred to as dynamic point feature aggregation network (DPFA-Net), by selectively performing the neighborhood feature aggregation (FA) with dynamic pooling and an attention mechanism. DPFA-Net has two variants for semantic segmentation and classification of 3-D point clouds. As the core module of the DPFA-Net, we propose an FA layer, in which features of the dynamic neighborhood of each point are aggregated via a self-attention mechanism. In contrast to other segmentation models, which aggregate features from fixed neighborhoods, our approach can aggregate features from different neighbors in different layers providing a more selective and broader view to the query points and focusing more on the relevant features in a local neighborhood. In addition, to further improve the performance of semantic segmentation, we exploit the background–foreground (BF) information and present two novel approaches, namely, two-stage BF-Net and BF regularization. Experimental results show that the proposed DPFA-Net achieves the state-of-the-art overall accuracy score of 89.22% for semantic segmentation on the Stanford large-scale 3-D Indoor Spaces (S3DIS) dataset and provides consistently satisfactory performance across different tasks of semantic segmentation, part segmentation, and 3-D object classification. Furthermore, our model achieves 93.1% accuracy on the ModelNet40 dataset and provides a mean shape intersection-over-union (IoU) value of 85.5% for part segmentation on the ShapeNet-Part dataset. It is a also computationally more efficient compared to other methods.

3-D↗