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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

EVSE Cybersecurity and Resilience

Consequence-driven Cybersecurity Analysis for Extreme Fast Charging Electric Vehicle Infrastructure Electric vehicle (EV) development and associated charging infrastructure are expected to advance rapidly. Thirty percent of all global vehicle sales may be EVs and hybrid EVs by 2025, and they will rely on increasingly sophisticated strategies for grid integration. Next-generation EV charging infrastructure is expected to include interconnected renewable resources, such as photovoltaic (PV) arrays and battery storage systems, along with grid-edge devices. Although distributed energy resources (DERs) are useful in several ways, such as peak shaving at high demand times and backup supply for added resilience, the integration of vehicle charging and DERs could create more avenues for cyberattack. Physical and/or remote access to EV charging station components, including charge ports, power electronics, controllers, and local generation (e.g., PV and energy storage) could be paths to cause power fluctuations, leading to altered operations at the charging station, escalated privileges to administrative systems, exfiltration of financial information (including personally identifiable information), and reduced grid stability. One compromised EV supply equipment component can open the door to a variety of exploitable vulnerabilities. Cloud computing and mobile application control have the potential to expand the threat surface to non-repudiation and firmware integrity challenges. Vendor clouds have access to hundreds of chargers, and if compromised, can scale the attack surface exponentially. The high power and voltage levels of xFC infrastructure (e.g., 400 kW at 1000- V DC) increase the hazards and ability to impact the grid and vehicles more than lower-power charging systems. Legacy communications systems and protocols could also put EV infrastructure at risk of cyberattacks requiring a robust patch management process. Communications networks link EVs and chargers to several stakeholders - including charging station operators, grid operators, vendors/manufacturers, and aggregators - who have both physical and network access to share information for control, monitoring, and analytics. Information in these networks that is vulnerable to compromise includes the state of charge, charging duration, payment information, electricity price, and load control. Analyzing and prioritizing these interconnections risks could help address cybersecurity related to data leakage and manipulation.

charging↗
DOE OSTI2024

"Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs"

The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. These "phantom jams" or "stop-and-go waves,"are a significant source of wasted energy. Toward this goal, the CIRCLES project designed a control system referred to as the MegaController by the CIRCLES team, that could be deployed in real traffic. Our field experiment leveraged a heterogeneous fleet of 100 longitudinally-controlled vehicles as Lagrangian traffic actuators, each of which ran a controller with the architecture described in this paper. The MegaController is a hierarchical control architecture, which consists of two main layers. The upper layer is called Speed Planner, and is a centralized optimal control algorithm. It assigns speed targets to the vehicles, conveyed through the LTE cellular network. The lower layer is a control layer, running on each vehicle. It performs local actuation by overriding the stock adaptive cruise controller, using the stock on-board sensors. The Speed Planner ingests live data feeds provided by third parties, as well as data from our own control vehicles, and uses both to perform the speed assignment. The architecture of the speed planner allows for modular use of standard control techniques, such as optimal control, model predictive control, kernel methods and others, including Deep RL, model predictive control and explicit controllers. Depending on the vehicle architecture, all onboard sensing data can be accessed by the local controllers, or only some. Control inputs vary across different automakers, with inputs ranging from torque or acceleration requests for some cars, and electronic selection of ACC set points in others. The proposed architecture allows for the combination of all possible settings proposed above. Most configurations were tested throughout the ramp up to the MegaVandertest.

Lee, Jonathan↗
DOE OSTI2020

Controlling colloidal crystals via morphing energy landscapes and reinforcement learning

We report a feedback control method to remove grain boundaries and produce circular shaped colloidal crystals using morphing energy landscapes and reinforcement learning–based policies. We demonstrate this approach in optical microscopy and computer simulation experiments for colloidal particles in ac electric fields. First, we discover how tunable energy landscape shapes and orientations enhance grain boundary motion and crystal morphology relaxation. Next, reinforcement learning is used to develop an optimized control policy to actuate morphing energy landscapes to produce defect-free crystals orders of magnitude faster than natural relaxation times. Morphing energy landscapes mechanistically enable rapid crystal repair via anisotropic stresses to control defect and shape relaxation without melting. This method is scalable for up to at least N = 10 3 particles with mean process times scaling as N 0.5 . Further scalability is possible by controlling parallel local energy landscapes (e.g., periodic landscapes) to generate large-scale global defect-free hierarchical structures.

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

Orientation-controlled crystallization of γ-glycine films with enhanced piezoelectricity

Glycine, the simplest amino acid, is considered a promising functional biomaterial owing to its excellent biocompatibility and strong out-of-plane piezoelectricity. Practical applications require glycine films to be manufactured with their strong piezoelectric polar $\langle$001$\rangle$ direction aligned with the film thickness. Based on the recently-developed solidification approach of a polyvinyl alcohol (PVA) and glycine aqueous solution, in this work, we demonstrate that the crystal orientation of the as-synthesized film is determined by the orientation of glycine crystal nuclei. By controlling the local nucleation kinetics via surface curvature tuning, here we shifted the nucleation site from the edge to the middle of the liquid film, and thereby aligned the $\langle$001$\rangle$ direction vertically. As a result, the PVA–glycine–PVA sandwich film exhibits the highest average piezoelectric coefficient d 33 of 6.13 ± 1.13 pC N –1 . This work demonstrates a promising kinetic approach to achieve crystallization and property control in a scalable biocrystal manufacturing process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Comparison of Current and Future PM2.5 Air Quality in China Under CMIP6 and DPEC Emission Scenarios

The latest scenarios for the sixth Coupled Model Intercomparison Project (CMIP6) provide opportunities to explore future climate and air pollution mitigation pathways with socioeconomic features. However, to what extent inadequate consideration of region-specific policies in the CMIP6 scenarios would affect regional air quality projections is still not clear. Here, we simulated China’s future PM2.5 concentrations and compositions with local policy-based scenarios and the original CMIP6 datasets, for the first time estimating future air quality differences induced by the lack of local pollution control policies in the CMIP6 scenarios. We found that the CMIP6-driven projections overestimate major chemical aerosols by 10% – 70% in 2015 and fail to capture the rapid PM2.5 concentration decline during 2015–2019. Near-term differences further lead to 43% – 49% (5 – 9 µg/m3) PM2.5 overpredictions in 2050 in CMIP6 scenarios compared with policy-based mitigation scenarios. Our study demonstrates the indispensable influences of local policies on regional analyses and suggests that the research community should incorporate more region-specific information in future scenario designs.

Cheng, Jing↗
DOE OSTI2025

Cyber‐Resilient Distributed Energy Resource Control Algorithms for Smart Distribution Grids

ABSTRACT This paper focuses on the development of cyber‐resilient gradient‐based optimisation algorithms and theoretical proof for grid‐interactive distributed energy resource (DER) control to enable two grid services of virtual power plants (VPPs) dispatch and grid voltage regulation, considering the communication and security impacts. Firstly, the combined DER dispatch and voltage regulation as a real‐time gradient‐based optimisation problem is recapped. Thereafter, we consider a probabilistic traffic model to characterise packet delays and loss in a communication network, and study how the delays enter the process of information exchange among the grid measurement units, local DER controllers and the grid control centre that execute this control algorithm in a coordinated manner. Then, a strategy combining delay thresholds and message update rules is proposed to immunity the asynchrony resulting from the communications traffic and it avoids possible numerical instabilities and sensitivities of the power tracking and voltage regulation capabilities, resulting as cyber‐resilient DER control algorithms. Additionally, their convergence is theoretically proved. Effectiveness of proposed cyber‐resilient algorithms has been validated on the IEEE 37‐bus system in terms of convergence, VPP tracking and voltage regulation performance for smart distribution systems with high penetration of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Large-Area Lasing in Nanoscale Complex Media: The Critical Role of Local Dielectric Environment

Controlling how electromagnetic waves interact with complex media is critical for applications in imaging and focusing. Such lightwave interactions with complex media can lead to dramatic optical effects like lasing. While much work in random lasing focus on understanding how gain and scattering co-operatively generate lasing, little work has focused on how to manipulate the lasing threshold without modifying the structural disorder. Here, a simple, mostly unexplored, strategy is demonstrated that employs atomic layer deposition (ALD) to tune the local near-field environment while preserving the underpinning disorder—controlling lasing in a nanoscale complex medium on a large scale (>cm 2 ). The nanoscale complex medium is a quasi-2D system of coupled zinc oxide nanospheres with overall thickness deep in the sub-wavelength regime (≈λ/4). Near-ultraviolet femtosecond spectroscopy probes the broadband response of the gain nanomaterial, details how ALD process fundamentally modifies the fast-picosecond and slow-nanosecond carrier dynamics, and informs on the relevant timescales critical for lasing. Full-field electromagnetic simulations provide critical insights about how near-field dielectric environment modifies the nanostructure's scattering cross-section, which ultimately results in enhanced lasing. Importantly, these results highlight a simple path to control how electromagnetic waves interact in a complex medium, a key step toward large-scale implementation of complex lasers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effect of aspect ratio on plasma response to resonant magnetic perturbations in tokamak devices

A systematic numerical study is carried out, computing and comparing the plasma response to the resonant magnetic perturbation (RMP) field, applied for controlling edge localized modes (ELMs), in a series of tokamak plasmas with varying aspect ratio and utilizing the MARS-F code. The aspect ratio is scanned either by varying the plasma major radius at a fixed minor radius or by varying the latter while fixing the former. Both approaches yield similar results when compared in terms of quantities with proper normalizations. In general, a non-monotonic dependence of the resonant response field (normalized by the vacuum counterpart) near the plasma edge is found with varying aspect ratio, indicating that a given ELM control coil current configuration strongly favors plasmas with a certain aspect ratio. This optimal aspect ratio, on the other hand, depends on the toroidal as well as poloidal (i.e., coil phasing) spectra of the applied RMP field. The equilibrium (edge) safety factor, the plasma shape, and the plasma toroidal flow are all fixed to ensure that the effects identified here are predominantly due to the plasma aspect ratio.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Kinetic frustration by limited bond availability controls the LAT protein condensation phase transition on membranes

LAT is a membrane-linked scaffold protein that undergoes a phase transition to form a two-dimensional protein condensate on the membrane during T cell activation. Governed by tyrosine phosphorylation, LAT recruits various proteins that ultimately enable condensation through a percolation network of discrete and selective protein-protein interactions. Here, we describe detailed kinetic measurements of the phase transition, along with coarse-grained model simulations, that reveal that LAT condensation is kinetically frustrated by the availability of bonds to form the network. Unlike typical miscibility transitions in which compact domains may coexist at equilibrium, the LAT condensates are dynamically arrested in extended states, kinetically trapped out of equilibrium. Modeling identifies the structural basis for this kinetic arrest as the formation of spindle arrangements, favored by limited multivalent binding interactions along the flexible, intrinsically disordered LAT protein. These results reveal how local factors controlling the kinetics of LAT condensation enable formation of different, stable condensates, which may ultimately coexist within the cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Pleistocene Colorado River terraces in the canyonlands region (Utah, USA) record unsteady, transient incision and growth of the Cataract Canyon knickzone by salt tectonics

Colorado River terraces in the canyonlands region of southeastern Utah can be dated and analyzed to address the controls of incision and nature of the Colorado Plateau's largest channel-steepness anomaly, Cataract Canyon. Field correlations supported by luminescence and cosmogenic-nuclide ages on strath terraces along Meander Canyon, upstream of Cataract Canyon, reveal a complex record of unsteady incision over the past ~340 k.y. at an average rate of ~0.4 mm/yr. Both an upstream progression of rapid incision and a unique sigmoidal long-profile pattern of terraces indicate incision in response to episodic baselevel fall. Also, terraces converge downstream with the anomalously low-gradient modern channel above Cataract Canyon. Here we interpret these results as indicating that growth of the Cataract Canyon knickzone is due to an erosion-salt tectonics feedback since at least the Mid Pleistocene, which has imparted unsteady, and currently elevated, local baselevel. More broadly, the canyonlands region is marked by rapid and unsteady incision that is complicated by local geologic controls even while being absent of any regional or mantle-driven uplift.

58 GEOSCIENCES↗
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 OSTI2023

Deep reinforcement learning assisted co-optimization of Volt-VAR grid service in distribution networks

With the increasing penetration of distributed energy resources in distribution networks, Volt-VAR control and optimization (VVC/VVO) have become very important to ensure an acceptable quality of service to all customers. System operators can rely on slow-responding utility devices, including capacitor banks and on-load tap changing transformers, along with fast-responding battery and photovoltaic (PV) inverters for the VVC/VVO implementation. Because of variations in response time of these two classes of devices, and different control actions (discrete versus continuous), coordinated and optimal scheduling and operation have become of utmost importance. Here, this paper develops a look-ahead deep reinforcement learning (DRL)-based multi-objective VVO technique to improve the voltage profile of active distribution networks, decrease network and inverter power loss, and save the operational cost of the grid. It proposes a deep deterministic policy gradient (DDPG)-based approach to schedule the optimal reactive and/or active power set-points of fast-responding inverters, and a deep Q-network (DQN)-based DRL agent to schedule the discrete decisions variables of slow-responding assets. The reactive power output of PV and battery smart inverters are scheduled at 30-minute intervals and the capacitors’ commitment status is scheduled with several hour intervals. The proposed framework is validated on the modified IEEE 34-bus and 123-bus test cases with embedded PV and PV-plus-storage. To validate the efficacy of the proposed VVO, it is compared with several scenarios, including the base case without VVO, localized droop control of DERs, DDPG-only, and twin delayed DDPG (TD3) agent-based DRL techniques. The results justify the superior performance of the proposed method to improve the voltage profile, reduce network power loss, and minimize the look-ahead grid operational cost while minimizing the undesirable power losses in inverters as a result of power factor adjustments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Local Distortions and Metal–Semiconductor–Metal Transition in Quasi-One-Dimensional Nanowire Compounds AV 3 Q 3 O δ (A = K, Rb, Cs and Q = Se, Te)

Metal cluster compounds have garnered renewed interest in the search for novel superconductors and topological semimetals owing to structural instabilities of metal-cluster geometries and broken symmetries. Here we synthesized needle-like crystals of the V-cluster-based quasi-one-dimensional (Q1D) materials AV 3 Q 3 O δ (A = K, Rb, Cs, Q= Se, Te) which can also be viewed as being composed of parallel nanowires. We examine how changes in their average and local structure control their electronic properties. All compounds crystallize in the TIFe 3 Te 3 -type structure (P6 3 /m space group) with infinite (V 3 )Q 3 ) - double-walled columnar chains separated by A + cations. Our single-crystal and synchrotron powder diffraction studies indicate oxygen atoms partially occupy the center site of the V 6 octahedral metal cluster cages in KV 3 Te 3 O 0.33 , RbV 3 Te 3 O 0.32 , and CsV 3 Te 3 O 0.35 , whereas KV 3 Se 3 is structurally oxygen-free. Our synchrotron X-ray pair distribution function (PDF) analyses indicate that the oxygen-free V 6 cluster octahedra in KV 3 Se 3 are highly distorted perpendicular to the chain direction even at room temperature, reducing the symmetry of the average structure from hexagonal P6 3 /m to monoclinic P2 1 /m. Our theoretical calculation supports this P2 1 /m distortion and suggests the structure further distorts to P2 1 or P2 1 /c at lower temperatures. In contrast, the oxygen-centered V-cluster in KV 3 Te 3 O 0.33 exhibits a V-3-triangle-trimerization along the chain direction. This feature is discernible from the local PDF and is consistent with lattice dynamical calculations based on density functional theory. Resistivity measurements indicate that KV 3 Se 3 exhibits metallic behavior, whereas a dramatic metal-semiconductor-metal transition emerges in KV 3 Te 3 O 6.33 , RbV 3 Te 3 O 0.32 , and CsV 3 Te 3 O 0.35 because of oxygen disorder and changes in local structure captured from our electronic structure analyses of the Fermi surface. Our investigation of the AV 3 Q 3 O 6 family demonstrates the importance of understanding local changes in structure driven by electronic instabilities, which can guide the search for new quantum materials in other low-dimensional cluster-compound materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Shifting groundwater fluxes in bedrock fractures: Evidence from stream water radon and water isotopes

Geologic features (e.g., fractures and alluvial fans) can play an important role in the locations and volumes of groundwater discharge and degree of groundwater-surface water (GW-SW) interactions. However, the role of these features in controlling GW-SW dynamics and streamflow generation processes are not well constrained. GW-SW interactions and streamflow generation processes are further complicated by variability in precipitation inputs from summer and fall monsoon rains, as well as declines in snowpack and changing melt dynamics driven by warming temperatures. Using high spatial and temporal resolution radon and water stable isotope sampling and a 1D groundwater flux model, we evaluated how groundwater contributions and GW-SW interactions varied along a stream reach impacted by fractures (fractured-zone) and below the fractured hillslope (non-fractured zone) in Coal Creek, a Colorado River headwater stream affected by summer monsoons. During early summer, groundwater contributions from the fractured zone dominated, but declined throughout the summer. Groundwater contributions from the non-fractured zone were constant throughout the summer and became proportionally more important later in the summer. We hypothesize that groundwater in the non-fractured zone is dominantly sourced from a high-storage alluvial fan at the base of a tributary that is connected to Coal Creek throughout the summer and provides consistent groundwater influx. Water isotope data revealed that Coal Creek responds quickly to incoming precipitation early in the summer, and summer precipitation becomes more important for streamflow generation later in the summer. We quantified the change in catchment dynamic storage and found it negatively related to stream water isotope values, and positively related to modeled groundwater discharge and the ratio of fractured zone to non-fractured zone groundwater. Importantly, we interpret these relationships as declining hydrologic connectivity throughout the summer leading to late summer streamflow supported predominantly by shallow flow paths, with variable response to drying from geologic features based on their storage. As groundwater becomes more important for sustaining summer flows, quantifying local geologic controls on groundwater inputs and their response to variable moisture conditions may become critical for accurate predictions of streamflow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Role of 3D neoclassical particle flux in density pump-out during ELM control by RMP in DIII-D

Application of three-dimensional (3-D) resonant magnetic perturbations, for the purpose of controlling edge localized modes (ELMs) in high confinement (H-mode) tokamak fusion operations, routinely leads to significantly reduction of the plasma density during the discharge, a phenomenon termed 'density pump-out'. Understanding the density pump-out phenomenon due to 3-D fields is a longstanding challenging issue. This work discusses a self-consistent toroidal model that allows initial value simulation of the density pump-out effect. The model successfully reproduces pump-out phenomenology in DIII-D ELM suppression experiments. The radial particle flux, associated with the 3-D neoclassical effects (the neoclassical toroidal viscosity, NTV), is discovered to play an important role in producing the observed large density pump- out. The key physics is associated with the drift kinetic Landau resonances between the toroidal precession of trapped thermal ions and electrons from one side, and the magnetic field perturbation from the other side. Such resonances, occurring near the top of the pedestal region, substantially enhances the radial particle flux associated with NTV. As a general consequence of the resonant NTV flux, larger density pump- out occurs in plasmas with lower collisionality and slower toroidal rotation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

An overview of 3D field optimization for control of transport and edge instabilities on KSTAR

An international team from several laboratories and universities has made key advances over the last few years in the control of plasma transport and edge instabilities with applied 3D fields in the KSTAR tokamak to optimize long pulse operation scenarios. This overview begins with the optimization of both core and edge resonant magnetic perturbations (RMP) to improve fast ion confinement to avoid excessive limiter heat loads due to fast ion losses and successful modeling of the experimental results. Integrated and advanced plasma control techniques with machine learning (ML) and adaptive control were then used to optimize the 3D field spectrum in real-time to control edge localized modes (ELMs) while avoiding core locked modes that could disrupt the plasma. Accelerating the offline model of 3D fields with a surrogate ML model can optimize ELM suppression in the edge while limiting the impact of the applied RMP fields deeper in the plasma core in real-time. In addition, the impact of the 3D fields on the divertor heat load has been modeled and compared with experimental measurements. An analysis of a multi-machine database including KSTAR has been performed to better understand the metrics for the observed RMP thresholds for ELM suppression and the resulting plasma performance. Predictive modeling of the operational space for ELM suppression and density pumpout due to RMP has shown the importance of magnetic islands in the plasma edge and their impact on plasma turbulence. This research has culminated in the development of successful long pulse operational scenarios on KSTAR while attempting to overcome challenges of the new tungsten divertor.

3D fields↗
DOE OSTI2023

Solid‐State Reaction Heterogeneity During Calcination of Lithium‐Ion Battery Cathode

Abstract During solid‐state calcination, with increasing temperature, materials undergo complex phase transitions with heterogeneous solid‐state reactions and mass transport. Precise control of the calcination chemistry is therefore crucial for synthesizing state‐of‐the‐art Ni‐rich layered oxides (LiNi 1‐x‐y Co x Mn y O 2 , NRNCM) as cathode materials for lithium‐ion batteries. Although the battery performance depends on the chemical heterogeneity during NRNCM calcination, it has not yet been elucidated. Herein, through synchrotron‐based X‐ray, mass spectrometry microscopy, and structural analyses, it is revealed that the temperature‐dependent reaction kinetics, the diffusivity of solid‐state lithium sources, and the ambient oxygen control the local chemical compositions of the reaction intermediates within a calcined particle. Additionally, it is found that the variations in the reducing power of the transition metals (i.e., Ni, Co, and Mn) determine the local structures at the nanoscale. The investigation of the reaction mechanism via imaging analysis provides valuable information for tuning the calcination chemistry and developing high‐energy/power density lithium‐ion batteries.

Chemistry↗