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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 73 records · Page 4

On the oceanic origin for the enhanced seasonal cycle of SST in the midlatitudes under global warming

Climate models project an enhancement in SST seasonal cycle over the midlatitude oceans under global warming. However, the maintaining mechanism for this enhancement is still under debate. This study investigates the SST seasonal cycle enhancement under quadrupling CO2 using a set of partially coupled experiments, in which the contribution from direct CO2 forcing (without the effect of wind changes) and wind effects can be isolated. Results indicate that both the direct CO2 and total wind effects contribute to the enhancement in the SST seasonal cycle, with the former (latter) effect being more important in the Northern Hemisphere (Southern Hemisphere). Further decomposition of the wind effect into the wind stress feedback and wind-evaporation-SST (WES) feedback through the change of wind speed reveals the importance of the wind stress-driven ocean response in the change of SST seasonal cycle, a result in contrast to a previous study that ascribed the midlatitude SST seasonal cycle change to the thermodynamic WES feedback. The direct CO2 effect regulates SST seasonal cycle mainly through the mediating effects of the ocean mixed layer depth (MLD): i) the CO2 induced warming leads to MLD shoaling, thus reducing its effective heat capacity; ii) the climatological MLD is greater in winter than summer, given the same amount of energy flux from the surface, SST warming in winter should be smaller. Notably, the surface wind seasonal cycle change due solely to the direct CO2 effect is found to bear a great resemblance to the full wind response, implicating that the direct CO2 effect is the root source for the enhancement of the midlatitude SST seasonal cycle. This is further supported by an ocean-alone experiment that replicates the SST seasonal cycle enhancement under a spatially and temporally homogeneous surface thermal forcing into the ocean.

Liu, Fukai↗

Ducted fuel injection with Low-Net-Carbon fuels as a solution for meeting future emissions regulations

Several studies have proven how ducted fuel injection (DFI) reduces soot emissions for compression-ignition engines. Nevertheless, no comprehensive study has investigated how DFI performs over a load range in combination with low-net-carbon fuels. In this study, optical-engine experiments were performed with four different fuels—conventional diesel and three low-net-carbon fuels—at low and moderate load, to measure emissions levels and performance. The 1.7-liter single-cylinder optical engine was equipped with a high-speed camera to capture natural luminosity images of the combustion event. Conventional diesel and DFI combustion were investigated at four different dilution levels (to simulate exhaust-gas recirculation effects), from 14 to 21 mol% oxygen in the intake. At a given dilution level, with commercial diesel fuel, DFI reduced soot by 82% at medium load, and 75% at low load without increasing NO x . The results further show how DFI with dilution reduces soot and NO x without compromising engine performance or other emission types, especially when combined with low-net-carbon fuels. DFI with the oxygenated low-net-carbon blend HEA67 simultaneously reduced soot and NO x by as much as 93 % and 82 %, respectively, relative to conventional diesel combustion with commercial diesel fuel. These soot and NO x reductions occurred while lifecycle CO 2 was reduced by at least 70 % when using low-net-carbon fuels instead of conventional diesel. All emissions changes were compared with future emissions regulations for different vehicle sectors to investigate how DFI can be used to facilitate achievement of the regulations. Finally, the results show how the DFI cases fall below several future emissions regulation levels, rendering less need for aftertreatment systems and giving a possible lower cost of ownership.

33 ADVANCED PROPULSION SYSTEMS↗

Aerosol hygroscopicity over the South-East Atlantic Ocean during the biomass burning season – Part 2: Influence of sea salt and burning conditions on CCN hygroscopicity

Biomass burning (BB) significantly influences cloud condensation nuclei (CCN) concentrations over the southeastern Atlantic; however, aerosol hygroscopicity (κ) – a key factor for CCN activation – remains poorly constrained during the BB season. This study investigates κ variability using in situ measurements from Ascension Island during the 2016 and 2017 BB seasons. Results show substantial monthly variability, with κ values lowest in August and increasing through October. On average, κ was significantly higher in 2017 (∼ 0.55) than in 2016 (∼ 0.33), suggesting that the aerosols in 2017 were more hygroscopic and more easily activated as CCN. Sulfate and sea salt were the two dominant contributors to κ and the primary drivers of its interannual variability. During the 2017 BB season, sulfate – the major inorganic component – accounted for ∼ 34 % of the submicron aerosol mass, while sea salt, estimated via κ-closure analysis, contributed ∼ 17 %. The higher κ in 2017 was largely attributed to increased sea salt, likely driven by stronger marine winds. Approximately 67 % of sulfate was linked to BB emissions. Variations in BB combustion efficiency, modulated by regional meteorology, influenced sulfate fraction and thus κ values. Specifically, higher relative humidity and lower wind speeds over BB source regions in 2017 favored smoldering combustion, explaining the higher sulfate fraction. Overall, the observed interannual differences in aerosol hygroscopicity reflect the combined impacts of BB combustion characteristics and sea salt emissions, underscoring the critical roles of both BB and marine aerosol sources in regulating aerosol-cloud interactions over the southeastern Atlantic.

54 ENVIRONMENTAL SCIENCES↗

Evaluating ecosystem water use efficiency and recovery dynamics during flash droughts: insights from observations and model simulations

Flash droughts (FD), rapidly emerging in a warming future, disrupt ecosystems, agriculture, and water security. Ecosystem water use efficiency (WUE), the ratio of gross primary production (GPP) to actual evapotranspiration (AET), balances carbon assimilation and water loss. FD rapidly disrupts this balance, making WUE critical for assessing plant stress and recovery. Here, this study investigates the dynamics of landscape-scale WUE, and the components of GPP and AET under FD utilizing both observed data from the Missouri Ozark AmeriFlux site (US-MOz) and version 2 of the U.S. Department of Energy’s Earth, Energy, Exascale System Model (E3SM) Land Model (ELMv2). Observations and simulations reveal GPP as dominant for WUE during earlier FD events (2005, 2007, 2012), shifting to AET in recent events (2014, 2018). This agreement indicates that the ELM can capture the shifting dynamics of GPP and AET in regulating WUE under FD conditions. However, the ELM systematically underestimates both GPP and AET and does so in a manner that does not preserve their ratio. As a result, WUE is also underestimated, suggesting that GPP is more strongly underestimated than AET. Furthermore, the ELM also underestimates the speed of GPP recovery, producing an artificially prolonged GPP recovery time following FD events. Observed environmental drivers such as vapor pressure deficit (VPD), soil moisture (SM), and predawn leaf water potential (PLWP) effectively predict WUE, but ELM primarily highlights SM, underestimating VPD’s role. This study demonstrates that relying solely on soil moisture fails to capture the rapid hydraulic recovery observed in PLWP, underscoring the necessity of integrating plant hydraulics into land surface models to improve flash drought predictability.

Evapotranspiration↗

Converting 2D Nanofiber Membranes to 3D Hierarchical Assemblies with Structural and Compositional Gradients Regulates Cell Behavior

Abstract New methods are described for converting 2D electrospun nanofiber membranes to 3D hierarchical assemblies with structural and compositional gradients. Pore‐size gradients are generated by tuning the expansion of 2D membranes in different layers with incorporation of various amounts of a surfactant during the gas‐foaming process. The gradient in fiber organizations is formed by expanding 2D nanofiber membranes composed of multiple regions collected by varying rotating speeds of mandrel. A compositional gradient on 3D assemblies consisting of radially aligned nanofibers is prepared by dripping, diffusion, and crosslinking. Bone mesenchymal stem cells (BMSCs) on the 3D nanofiber assemblies with smaller pore size show significantly higher expression of hypoxia‐related markers and enhanced chondrogenic differentiation compared to BMSCs cultured on the assemblies with larger pore size. The basic fibroblast growth factor gradient can accelerate fibroblast migration from the surrounding area to the center in an in vitro wound healing model. Taken together, 3D nanofiber assemblies with gradients in pore sizes, fiber organizations, and contents of signaling molecules can be used to engineer tissue constructs for tissue repair and build biomimetic disease models for studying disease biology and screening drugs, in particular, for interface tissue engineering and modeling.

Chen, Shixuan↗

Turbulence Structures in the Very Stable Boundary Layer Under the Influence of Wind Profile Distortion

Abstract In very stable boundary layers (VSBL), a “cocktail” of submeso motions routinely result in elevated mean wind speed maxima above the ground, acting as a new source of turbulence generation. This new source of turbulent kinetic energy enhances turbulent mixing and causes mean wind profile distortion (WPD). As a results, this transient distortion in the wind profile adjusts the classical log‐law. Addressing how WPD‐induced turbulence regulates flow structures, turbulent fluxes, and transitions in stability regimes across layers remains a challenge. Eddy covariance data measured at four levels on a 62‐m tower are employed to address these questions. It is shown that the WPD initiates large turbulent eddies that penetrate downward, leading to enhanced vertical mixing and comparable turbulent transport efficiencies across layers. As a consequence, turbulence intensity and fluxes are increased. As the WPD is intensified, turbulent fluxes and turbulent flux transport caused by large eddies are also enhanced, leading to a transition from very stable to weakly stable regimes. Due to the influence of WPD‐induced large eddies, the large‐eddy turbulent Prandtl number does not deviate appreciably from unity and the partitioning between turbulent kinetic and potential energies is linearly related to the gradient Richardson number.

Meteorology & Atmospheric Sciences↗

DOE Final Report on Virginia Tech’s contribution to “Tokamak Disruption Simulation”

This work was performed by Virginia Tech in collaboration with multiple institutions led by Los Alamos National Laboratory as a part of the Tokamak Disruption Simulation SciDAC (Scientific Discovery through Advanced Computing) project supported jointly by the Department of Energy Office of Science and Ad- vanced Scientific Computing Research. This report summarizes Virginia Tech’s contributions to the Sci- DAC project. Virginia Tech researchers (presently University of Washington researchers) focused on the fundamental role of plasma-material interaction on transport, which could then have macroscopic effects on simulations of tokamak disruptions. The plasma sheath, which regulates plasma particle and energy fluxes to the wall, is an essential component in the study of plasma-material interaction (PMI). Understanding sheath theory by accounting for finite sheath thickness and transport in the vicinity of the sheath entrance can sig- nificantly modify typical assumptions that are made in the Bohm speed analysis, where the Bohm speed provides the lower bound of the plasma exit flow speed. Our work provides a modified Bohm speed formu- lation that accounts for the critical role of transport and for applications that are away from the asymptotic limits that are typically assumed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Machine learning-based ethylene and carbon monoxide estimation, real-time optimization, and multivariable feedback control of an experimental electrochemical reactor

Electrochemical reduction of CO 2 gas is a novel CO 2 utilization technique that has the potential to mitigate the global climate crisis caused by anthropogenic CO 2 emissions, and enable the large-scale storage of energy generated from renewable sources in the form of carbon-based chemicals and fuels. However, due to the complexity of the electrochemical reactions, the explicit first-principles models for CO2 reduction are not available yet, and there has been a limited effort to develop process modeling, optimization and control of CO 2 electrochemical reactors. To this end, a rotating cylinder electrode (RCE) reactor has been constructed at UCLA to understand the mass transfer and reaction kinetics effects separately on the productivity. In the RCE reactor, the applied potential strongly influences the reaction energetics and the electrode rotation speed affects the hydrodynamic boundary layer and modifies the film mass transfer coefficient, which involves convective and diffusive transport. Further, the present work aims to develop a multi-input multi-output (MIMO) control scheme for the RCE reactor that integrates techniques from artificial and recurrent neural network modeling, nonlinear optimization, and process controller design. Specifically, production rates of two products from the experimental reactor, ethylene and carbon monoxide, are controlled by manipulating two inputs, applied potential and catalyst rotation speed. Process dynamics and controllability are analyzed, a feedback control strategy is designed and the controllers are tuned accordingly. The experimental electrochemical cell is employed to gather data for process modeling and implement the multivariable control system. Finally, the experimental results are presented which demonstrate excellent closed-loop performance by the control system and regulation of the outputs at three different set-points including an economically-optimal set-point.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Silicon alloying enhances fast heating rate combustion of aluminum particles

Alloys and composites of aluminum (Al) have shown promise in regulating and enhancing particle combustion for energy generation applications. Recent work on aluminum-silicon (Al-Si) spherical alloy particles has shown improved combustion at low heating rates through enhanced diffusion accompanying a lower melting temperature. This study extends reactivity analysis to higher heating rates, comparing oxidation of Al-Si with Al. Flame speeds of Al-Si powder mixed with molybdenum trioxide (MoO 3 ) powder (Al-Si+MoO 3 ) exhibited a faster transition to steady propagation relative to Al+MoO 3 . Bomb calorimetry experiments revealed up to 5.8% greater early temperature rise for Al-Si powder. Rapid steady propagation for Al-Si mixture and faster temperature rise for Al-Si particles were attributed to accelerated kinetics evidenced in thermal equilibrium analysis of the mixtures using a differential scanning calorimeter (DSC). Larger DSC exotherms in the early stages of oxidation (i.e., 480–720 °C) correlated with early heat release and promoted steady flame propagation for Al-Si+MoO 3 compared with Al+MoO 3 . Furthermore, in multiple heating rate DSC studies, Al-Si+MoO 3 ignited at a lower heating rate (i.e., 15 ⁰C/min) than Al+MoO 3 (i.e., 20 ⁰C/min). Both mixtures ignited at temperatures less than 625 °C which is above the melting temperature of Al-Si (574 °C) and below Al (659 °C). Thus, alloy particle fuels with enhanced diffusion-controlled kinetics promote steady flame propagation and show promise for energy generation applications. This is especially promising for technologies driven by enhanced condensed phase combustion such as some propellant additives or applications dependent on reliable burn rates such as pyrotechnic time delay formulations and primers.

36 MATERIALS SCIENCE↗

An experimental and numerical investigation of HD diesel engine DOC efficiency in oxidizing NO to NO 2

Reducing pollutant emissions from heavy-duty (HD) diesel engines is critical due to their significant environmental impact, particularly concerning NOx emissions. Understanding and optimizing modern diesel oxidation catalyst (DOC) and selective catalytic reduction (SCR) performance is essential for improving exhaust aftertreatment (EAT) system efficiency to meet stringent emissions regulations. The oxidation of nitric oxide (NO) to nitrogen dioxide (NO 2 ) in DOC plays a key role in improving SCR efficiency in reducing NO x . This study investigates the DOC performance in oxidizing NO to NO2 and its impact on the SCR efficiency of a 2021 MY Navistar E39 HD diesel engine. The influence of engine speed, load, exhaust gas temperature, and composition on DOC efficiency is experimentally investigated. The relationships between DOC inlet temperature, oxygen availability and NO 2 /NO x ratio at the DOC inlet are examined to better understand their effects on the overall DOC efficiency. The results indicate that DOC NO oxidation efficiency is highly dependent on exhaust temperature, with optimal oxidation occurring within a specific temperature range (275-350°C). Below this threshold, the chemical reactions are kinetically limited, while at higher temperatures, thermodynamic constraints reduce the efficiency of DOC in oxidizing NO to NO 2 . The experimental data further reveal that the NO 2 /NO x ratio peaks at medium loads before declining at higher loads due to reduced residence time and mass transfer effects. Additionally, the SCR NO x conversion efficiency is significantly influenced by the NO 2 /NO x ratio, achieving peak performance when the NO 2 /NO x ratio approaches 0.5. A DOC chemistry model was developed and validated against the experimental data to predict DOC oxidation behavior under various operating conditions. The findings of this study provide insights into the interdependencies between DOC and SCR performance, contributing to the optimization of SCR systems for optimized NOx reduction.

33 ADVANCED PROPULSION SYSTEMS↗

One-Component, Vinyl-Functional Fluorosilicone Pastes for Direct Ink Write Additive Manufacturing

In this study, one-component (“all-in-one”) fluorosilicone pastes specifically designed for application in direct ink write (DIW) additive manufacturing (AM) have been developed. They consist of vinyl-functional, methyltrifluoropropyl-containing (MeTfpS) terpolysiloxane base polymer(s), hydrosilyl-functional cross-linker(s), UV-sensitive hydrosilylation catalyst, thixotropic additive, and trimethylsilylated fumed silica filler, with other additives that are optional. Their base polymers were completely amorphous and linear, with molecular weights (M n ) ranging from approximately 7000 to 50,000 and specifically targeted for the viscosity range ideal for DIW. These polymers were prepared by anionic ring-opening polymerizations (A-ROP) of appropriate mixtures of cyclic siloxanes initiated by oligomeric, difunctional tetramethylammonium silanolate in the presence of a difunctional tetramethyldivinyldisiloxane end-blocker and molecular weight regulator. Two series of these terpolymers were prepared: one containing 5 mol % MeTfpS repeat units but varying degrees of polymerization (DP) from 80 to 600 and the other containing 5, 10, and 15 mol % MeTfpS at a constant DP of 600. All polymers contained mostly random distributions of MeTfpS repeat units. The pastes were prepared by speed-mixing, ready for use in DIW, they exhibited ideal thixotropy, long-term (over a year) rheological stability, and can be quickly (within seconds) and permanently cured by room-temperature, UV-activated hydrosilylation in air. The resulting elastomers showed base polymer molecular weight- and composition-dependent stress-induced crystallization (SIC) at higher molecular weights and lower trifluoropropyl contents and tunable Shore A hardness (30A–40A) typical for soft polysiloxane rubbers. Preliminary DIW tests indicated excellent printability with high precision of printed shapes and clearly present these one-component pastes as prime candidates for simple and practical printing of silicone elastomer objects.

36 MATERIALS SCIENCE↗

NLR HPC Eagle GPU Node Metrics

Ganglia node metrics and iLO (Integrated Lights Out) power data captured from six representative Eagle GPU nodes The Eagle HPC operated at NLR from 2019 through 2024. Eagle was a 2,000-node, 8-petaflop system. This dataset is a representative sample of metrics for 6 of the GPU nodes. Each GPU node contained 2 CPUs and 2 GPUs. Data provided in compressed CSV format. Ganglia and iLO Power Time Series Fields ts: Timestamp dv: Device / Node - Rack and Unit - r103u17 == r(ack)103u(nit)17 mt: Metric (only present for Ganglia) vl: Value - Value in watts for iLO power (instantaneous value at sampling time) or specified Ganglia metric below Ganglia Metrics Metric name -- Metric description -- Unit cpu_aidle -- Percent of time since boot idle CPU -- Percent cpu_idle -- Percent CPU idle -- Percent cpu_nice -- Percent CPU nice -- Percent cpu_speed -- Speed in MHz of CPU -- MHz cpu_user -- Percent CPU user -- Percent cpu_wio -- The percentage of CPU Wait I/O -- Percent gpu0_bar1_memory -- Used GPU bar1 memory -- MB gpu0_decoder_util -- GPU decoder utilization -- Percent gpu0_ecc_db_error -- Total ECC error counts for the GPU -- Number gpu0_encoder_util -- GPU encoder utilization -- Percent gpu0_fan -- Fan speed -- RPM gpu0_fb_memory -- Used GPU framebuffer memory -- MB gpu0_graphics_clock_report -- Current clock speeds for the device -- MHz gpu0_mem_total -- Memory total -- MB gpu0_mem_util -- Memory utilization -- Percent gpu0_power_usage_report -- Power usage report -- Watts gpu0_temp -- GPU 1 temperature -- Celsius gpu1_bar1_memory -- Used GPU bar1 memory -- MB gpu1_decoder_util -- GPU decoder utilization -- Percent gpu1_ecc_db_error -- Total ECC error counts for the GPU -- Number gpu1_encoder_util -- GPU encoder utilization -- Percent gpu1_fan -- Fan speed -- RPM gpu1_fb_memory -- Used GPU framebuffer memory -- MB gpu1_graphics_clock_report -- Current clock speeds for the GPU -- MHz gpu1_mem_total -- Memory total -- MB gpu1_mem_util -- Memory utilization -- MB gpu1_power_usage_report -- Power usage report -- Watts gpu1_temp -- GPU 1 temperature -- Celsius ipmi_cpu1_temp -- CPU 1 temperature -- Celsius ipmi_cpu2_temp -- CPU 2 temperature -- Celsius ipmi_inlet_ambient_temp -- Temperature measured at intake -- Celsius ipmi_vr_p1_temp -- CPU 1 voltage regulator temperature -- Celsius ipmi_vr_p2_temp -- CPU 2 voltage regulator temperature -- Celsius mem_buffers -- Amount of buffered memory -- Bytes mem_cached -- Amount of cached memory -- Bytes mem_free -- Amount of available memory -- Bytes mem_shared -- Amount of shared memory -- Bytes mem_total -- Amount of available memory -- Bytes

97 MATHEMATICS AND COMPUTING↗

CANA v1.0.0: efficient quantification of canalization in automata networks

The biomolecular networks underpinning cell function exhibit canalization, or the buffering of fluctuations required to function in a noisy environment. We present a new major release of $\tt{CANA}$, v1.0.0, an open-source Python package for understanding canalization in automata network models, discrete dynamical systems in which activation of biomolecular entities (e.g. transcription of genes) is modeled as the activity of coupled automata. One understudied putative mechanism for canalization is the functional equivalence of biomolecular regulators (e.g. among the transcription factors for a gene). We study this mechanism using the theory of symmetry in discrete functions. We present a new exact method, $\tt{schematodes}$, for finding maximal symmetry groups among the inputs to discrete functions, and integrate it into $\tt{CANA}$. The $\tt{schematodes}$ method substantially outperforms the inexact method of previous $\tt{CANA}$ versions both in speed and accuracy. We apply $\tt{CANA}$ v1.0.0 to study symmetry in 74 experimentally supported automata network models from the Cell Collective (CC) repository. The symmetry distribution is significantly different in the CC than in random automata with the same in-degree (connectivity) and bias (average output) (Kolmogorov–Smirnov test, P ≪ .001). Its spread is much wider than in a null model (IQR 0.31 versus IQR 0.20 with equal medians), demonstrating that the CC is enriched in functions with extreme symmetry or asymmetry.

Boolean networks↗

Light Duty Engine Performance Characteristics with Dimethyl Ether and Propane

Here, this paper explores the performance characteristics of a compression ignition HYUNDAI 2.2L engine operating with Dimethyl Ether (DME). Test are carried out at three operating conditions that weigh heavily in the FTP75 certification cycle (1000rpm-12Nm, 1500rpm-50Nm, 2000rpm-100Nm). The engine features a high-pressure common rail fuel injection system designed to operate with liquified gases. The main component of the fuel system is a high-pressure pump that incorporates an electronic inlet metering valve commanded on a crank-angle base to control the rail pressure. The pump, which requires no pressure regulator, provides the flow needed to the injectors without flow returning to the inlet. This novel fueling system is leveraged in tests that are conducted to examine the impact of EGR, combustion phasing, injection pressure on efficiency and emissions. In addition, the impact of introducing 15% Propane by mass is examined. During the tests, the engine ECU is aided by an Engine Controller High Speed Oversight unit (ECHO) to provide combustion phasing control, improved cylinder-to-cylinder uniformity, and an effective optimization over the testing effort. The use of DME and Propane allowed for peak thermal efficiency of nearly 43%. These fuels enable significant carbon index (CI) reductions over the baseline Diesel fuel, with indications that 50% reduction in CO 2 over the Diesel engine are possible.

33 ADVANCED PROPULSION SYSTEMS↗

Programmable soft valves for digital and analog control

In soft devices, complex actuation sequences and precise force control typically require hard electronic valves and microcontrollers. Existing designs for entirely soft pneumatic control systems are capable of either digital or analog operation, but not both, and are limited by speed of actuation, range of pressure, time required for fabrication, or loss of power through pull-down resistors. Using the nonlinear mechanics intrinsic to structures composed of soft materials—in this case, by leveraging membrane inversion and tube kinking—two modular soft components are developed: a piston actuator and a bistable pneumatic switch. These two components combine to create valves capable of analog pressure regulation, simplified digital logic, controlled oscillation, nonvolatile memory storage, linear actuation, and interfacing with human users in both digital and analog formats. Three demonstrations showcase the capabilities of systems constructed from these valves: 1) a wearable glove capable of analog control of a soft artificial robotic hand based on input from a human user’s fingers, 2) a human-controlled cushion matrix designed for use in medical care, and 3) an untethered robot which travels a distance dynamically programmed at the time of operation to retrieve an object. This work illustrates pathways for complementary digital and analog control of soft robots using a unified valve design.

42 ENGINEERING↗

Demonstration of Grid Services Using Mixed Grid-Forming and Grid-Following Technologies at the Wheatridge Renewable Energy Facility (Final Technical Report)

This Final Technical Report summarizes the analytical, modeling, and engineering work performed to evaluate grid-forming (GFM) inverter capabilities within a large hybrid renewable energy facility. The project focused on assessing the ability of advanced inverter-based resources to provide essential reliability services through coordinated operation of grid-forming (GFM) and grid-following (GFL) technologies. During Budget Period 1, the project developed a comprehensive framework of GFM performance metrics, including angle support, voltage regulation, frequency response, damping behavior, and current-limiting performance. Extensive electromagnetic transient (EMT) studies and hardware-in-the-loop (HIL) testing were conducted to validate GFM behavior under a range of operating conditions, including weak-grid scenarios, voltage disturbances, and multi-resource interactions. The project also established validated modeling approaches, plant-level control integration strategies, commissioning frameworks, and high-speed measurement infrastructure to support future field demonstration. Although the project concluded prior to field demonstration, the results provide a utility-scale foundation for evaluating, modeling, and deploying grid-forming technologies. The methodologies and tools developed contribute to industry understanding of inverter-based resource behavior and support future power system reliability under increasing renewable penetration.

14 SOLAR ENERGY↗

Collaborative Research: Unveiling the Interplay Between Magnetic Reconnection and Turbulence — Theory and Modeling

This is the final technical report for the project "Collaborative Research: Unveiling the Interplay Between Magnetic Reconnection and Turbulence — Theory and Modeling." This project investigated the interplay between two fundamental plasma processes — turbulence and magnetic reconnection — and the associated heating and particle acceleration. In particular, we focused on a new regime where the plasmoid instability mediates the turbulent energy cascade. In this new regime, reconnecting current sheets are disrupted by the growth of plasmoids/flux ropes on time scales shorter than the typical turnover times of eddies, speeding up the energy cascade and steepening the turbulence energy spectrum. This project addressed the following outstanding open questions: (1) What are the fundamental differences between plasmoid‐mediated turbulence cascade in three dimensions (3D) and two dimensions (2D)? (2) What are the essential features of plasmoid‐mediated turbulence in weakly collisional or collisionless regimes beyond resistive MHD? (3) How does the interplay of turbulence and reconnection regulate the energy release and dissipation in space and astrophysical plasmas? To address these questions, we have carried out three investigations: (1) Three-dimensional plasmoid-mediated turbulence energy cascade; (2) plasmoid-mediated reconnection and turbulence in three-dimensional Hall MHD; (3) reconnection and heating in coronal loops. This technical report summarizes the key findings of these investigations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗