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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition

The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. Here this paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Nuclear microreactor transient and load-following control with deep reinforcement learning

The economic feasibility of nuclear microreactors will depend on minimizing operating costs through advancements in autonomous control, especially when these microreactors are operating alongside other types of energy systems (e.g., renewable energy). This study explores the application of deep reinforcement learning (RL) for real-time drum control in microreactors, exploring performance in regard to load-following scenarios. By leveraging a point kinetics model with thermal and xenon feedback, we first establish a baseline using a single-output RL agent, then compare it against a traditional proportional–integral–derivative (PID) controller. This study demonstrates that RL controllers, including both single- and multi-agent RL (MARL) frameworks, can achieve similar or even superior load-following performance as traditional PID control across a range of load-following scenarios. In short transients, the RL agent was able to reduce the tracking error rate in comparison to PID by one half to one third. Over extended 300-minute load-following scenarios in which xenon feedback becomes a dominant factor, PID maintained better accuracy, but RL still remained within a 1% error margin despite being trained only on short-duration scenarios. This highlights RL’s strong ability to generalize and extrapolate to longer, more complex transients, affording substantial reductions in training costs and reduced overfitting. Furthermore, when control was extended to multiple drums, MARL enabled independent drum control as well as maintained reactor symmetry constraints without sacrificing performance---an objective that standard single-agent RL could not learn. We also found that, as increasing levels of Gaussian noise were added to the power measurements, the RL controllers were able to maintain lower error rates than PID, and to do so with at least 10% and upwards of 150% less control effort. These findings illustrate RL's potential for autonomous nuclear reactor control, laying the groundwork for future integration into high-fidelity simulations and experimental validation efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1995

Advanced interactive display formats for terminal area traffic control

The basic design considerations for perspective Air Traffic Control displays are described. A software framework has been developed for manual viewing parameter setting (MVPS) in preparation for continued, ongoing developments on automated viewing parameter setting (AVPS) schemes. The MVPS system is based on indirect manipulation of the viewing parameters. Requests for changes in viewing parameter setting are entered manually by the operator by moving viewing parameter manipulation pointers on the screen. The motion of these pointers, which are an integral part of the 3-D scene, is limited to the boundaries of screen. This arrangement has been chosen, in order to preserve the correspondence between the new and the old viewing parameter setting, a feature which contributes to preventing spatial disorientation of the operator. For all viewing operations, e.g. rotation, translation and ranging, the actual change is executed automatically by the system, through gradual transitions with an exponentially damped, sinusoidal velocity profile, in this work referred to as 'slewing' motions. The slewing functions, which eliminate discontinuities in the viewing parameter changes, are designed primarily for enhancing the operator's impression that he, or she, is dealing with an actually existing physical system, rather than an abstract computer generated scene. Current, ongoing efforts deal with the development of automated viewing parameter setting schemes. These schemes employ an optimization strategy, aimed at identifying the best possible vantage point, from which the Air Traffic Control scene can be viewed, for a given traffic situation.

Grunwald, Arthur J.↗
DOE OSTI2025

Tuning transition metal nanoparticles on a non-traditional support via experimental design

The ability to control metal nanoparticle size and morphology on supported catalysts is crucial for optimizing catalytic performance in targeted applications. Here, this work presents a systematic approach for tuning Ni particle and crystallite size on an unconventional, low-porosity silica fume support through select thermal treatments. The catalyst was synthesized via the deposition of nickelocene onto silica fume, resulting in well-dispersed Ni nanoparticles. A face-centered central composite design was employed to systematically assess the effects of time, temperature, and sintering gas environment on metal particle growth. The results demonstrate that the sintering gas environment is the primary factor governing particle and crystallite evolution, with temperature as the next most significant influence. Nickel nanoparticles sintered at temperatures of 650 °C and above under inert conditions exhibited substantial growth and polycrystalline structures, whereas samples treated in oxidative environments formed NiO, restricting particle mobility. Minimally oxidative (500 ppm O₂) environments facilitated rapid sintering while effectively removing residual ligands from the one-step nickelocene deposition process. Extensive structural characterization via a combination of scanning transmission electron microscopy, X-ray diffraction, hydrogen temperature programmed reduction, and small-angle X-ray scattering revealed that oxidative treatments enhanced metal-support interactions, as evidenced by increased reduction temperatures and narrower particle size distributions. These findings establish quantitative relationships between sintering parameters and Ni nanoparticle characteristics, providing a framework for rational catalyst design through controlled thermal treatments. This methodology is broadly applicable to other catalytic systems and provides a quantitative foundation for catalyst design.

CVD↗
DOE OSTI2021

CPS Testbed Architectures for WAMPAC using Industrial Substation and Control Center Platforms and Attack-Defense Evaluation

Advanced persistent threats and cyberattacks can impact wide-area monitoring, protection, and control (WAMPAC) system operation. Many cyber-physical system (CPS) testbeds have been developed for attack-defense experimentation and attack-resiliency tools evaluation for WAMPAC, but they are limited to a simulation-and-emulation based environment. This paper presents a quasi-realistic CPS attack-defense testbed-based framework for WAMPAC applications using the industrial substation and control center platforms such as eTerra integrated with the hardware-in-the-loop CPS smart grid testbed available at Iowa State University. The proposed framework includes various combinations of industry-grade substation and control center platforms, communication topologies, real-time digital simulators, and a novel cyber-physical distributed intrusion-and-anomaly detection system (D-IADS) for WAMPAC applications. The D-IADS includes a master at the control center and geographically distributed sensor devices at each substation. Each D-IADS sensor deployed at a substation or control center network monitors ingress and egress traffic, detect intrusions, and dispatch alerts to the D-IADS master. The D-IADS master centrally monitors and analyze the alerts and controls D-IADS sensors. We considered an EMP60 synthetic CPS grid as a case study to demonstrate the framework and proposed D-IADS for WAMPAC applications against cyberattack vectors such as Man-in-the-Middle DNP3 attack, denial-of-service, and data-integrity attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Autonomous Closed-Loop Experimental Characterization and Dynamic Model Validation of a Scaled Underwater Kite

This paper presents the closed-loop experimental framework and dynamic model validation for a 1/12-scale underwater kite design. The pool-based tow testing framework described herein, which involves a fully actuated, closed-loop controlled kite and flexible tether, significantly expands upon the capabilities of any previously developed open-source framework for experimental underwater kite characterization. Specifically, the framework has allowed for the validation of three closed-loop flight control strategies, along with a critical comparison between dynamic model predictions and experimental results. In this paper, we provide a detailed presentation of the experimental tow system and kite setup, describe the control algorithms implemented and tested, and quantify the level of agreement between our multi-degree-of-freedom kite dynamic model and experimental data. Finally, we also present a sensitivity analysis that helps to identify the most influential parameters to kite performance and further explain the remaining mismatches between the model and data.

42 ENGINEERING↗
DOE OSTI2026

Safe Deep Reinforcement Learning for Active Distribution System Model Predictive Control with EVs and DERs

The temporal and spatial mismatch between PV generation and electric vehicle (EV) charging and discharging may cause voltage violations in active distribution networks. Despite the widespread use of deep reinforcement learning (DRL) in power system optimization and control, it lacks guarantees on constraint satisfaction during both training and deployment. This paper proposes a Lagrangian-based safe DRL approach for model predictive control (MPC) of active distribution systems with large-scale integration of PVs, EVs, and energy storage systems (ESSs). A Transformer-LSTM time-series model is proposed to forecast EV charging demand, which is then formulated as a constraint to ensure charging requirements are met. Using this prediction, a Lagrangian-based safe soft actor-critic (SAC) framework is developed for real-time control in a three-phase unbalanced distribution system, enforcing voltage safety constraints while optimizing the cumulative net reward. By integrating the forecasting model with multi-period constraints, the proposed framework jointly coordinates PV systems, EV charging and discharging, and ESS scheduling within the MPC horizon. Numerical experiments on a modified IEEE 123-bus system with real-world data show that, under a high PV penetration scenario, the proposed method increases the net reward by 30.74% and reduces average voltage violations from 0.0011 p.u. to 0.0002 p.u. compared with standard SAC. Compared with the optimal power flow (OPF) approach, it achieves similar voltage security while yielding lower line losses. It also maintains real-time control capability, reducing operation latency to 53.21 ms per 15-minute control interval. The proposed method remains effective under varying PV/EV penetrations and load conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Defect Termination in the UiO-66 Family of Metal–Organic Frameworks: The Role of Water and Modulator

The defect concentration in the prototypical metal–organic framework UiO-66 can be well controlled during synthesis, leading to precisely tunable physicochemical properties for this structure. However, there has been a long-standing debate regarding the nature of the compensating species present at the defective sites. Here, we present unambiguous spectroscopic evidence that the missing-linker defect sites in an ambient environment are compensated with both carboxylate and water (bound through intermolecular hydrogen bonding), which is further supported by ab initio calculations. In contrast to the prevailing assumption that the monocarboxylate groups (COO – ) of the modulators form bidentate bonding with two Zr 4+ sites, COO – is found to coordinate to an open Zr 4+ site in an unidentate mode. The neighboring Zr 4+ site is terminated by a coordinating H 2 O molecule, which helps to stabilize the COO – group. Lastly, this finding not only provides a new understanding of defect termination in UiO-66, but also sheds light on the origin of its catalytic activity.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Dynamic Assurance of Autonomous Systems Through Ground Control Software

Assurance cases have emerged as a way to build trust in complex autonomous systems. Many assurance case justifications for such systems need to be constantly reevaluated based on the current system context and performance. Autonomous systems, especially those deployed in remote environments, often have a ground control system that enables monitoring and remote operations. In this paper, we propose a dynamic assurance framework that aims at connecting the assurance case with the ground control system. We use the ground control system to facilitate dynamic evaluation of quantitative assurance measures that support various justifications in the assurance case. We demonstrate the proposed dynamic assurance framework on the NASA Ames Research Center project Troupe. We use a combination of in-house and external tools to identify the assurance measures, formalize the related requirements, and generate monitors that feed the data to the external ground control system.

dynamic assurance case↗
DOE OSTI2024

Impedance Emulation Control of Wave Energy Converters

Modeling and control of wave energy conversion (WEC) systems for maximum power extraction is challenging due to complex multiphysics that include fluids, mechanics, and machine drives. To uncover an intuitive model that clearly depicts WEC system operation, we utilize a force-current equivalent circuit framework which then enables us to design an impedance emulation control strategy. To provide context for our framework, we focus on a standard reference model-3 (RM3) point absorber device coupled to a permanent magnet synchronous generator. After the proposed extremum seeking controller is computed, we experimentally validate its performance on a platform that consists of two back-to-back connected inverters that emulate the WEC system.

wave energy conversion, impedance emulation, machi↗
DOE OSTI2020

Thermally Activated Adsorption in Metal–Organic Frameworks with a Temperature‐Tunable Diffusion Barrier Layer

Abstract Modification of the external surfaces of metal–organic frameworks offers a new level of control over their adsorption behavior. It was previously shown that capping of MOFs with ethylenediamine (EDA) can effectively retain small gaseous molecules at room temperature. Reported here is a temperature‐induced variation in the capping‐layer gate‐opening mechanism through a combination of in situ infared experiments and ab initio simulations of the capping layer. An atypical acceleration and increase in the loading of weakly adsorbed molecules upon raising the temperature above room temperature is observed. These findings show the discovery of novel temperature‐dependent kinetics that goes beyond standard kinetics and suggest a new avenue for tailoring selective adsorption by thermally tuning the surface barrier.

Tan, Kui↗
DOE OSTI2020

Thermally activated adsorption in metal–organic frameworks with a temperature–tunable diffusion barrier layer

Modification of the external surfaces of metal organic frameworks offers a new level of control over their adsorption behavior. Here, we have previously shown that capping of MOFs with ethylenediamine (EDA) can effectively retain small gaseous molecules at room temperature. Here, we report a temperature–induced variation in the capping–layer gate opening mechanism through a combination of in situ IR experiments and ab initio simulations of the capping layer. We find an atypical acceleration and increase in the loading of weakly adsorbed molecules upon raising the temperature above room temperature. Our findings show the discovery of a novel temperature–dependent kinetics that goes beyond standard kinetics and suggest a new avenue for tailoring selective adsorption by thermally tuning the surface barrier.

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

Simultaneous Control of Pore-Space Partition and Charge Distribution in Multi-Modular Metal–Organic Frameworks

Here we report here a strategy for making anionic pacs type porous materials by combining pore space partition with charge reallocation. The method uses the first negatively charged pore partition ligand (2,5,8-tri-(4-pyridyl)-1,3,4,6,7,9-hexaazaphenalene, H-tph) that simultaneously enables pore partition and charge reallocation. Over two dozen anionic pacs materials have been made to demonstrate their excellent chemical stability and a high degree of tunability. Notably, Ni 3 -bdt-tph (bdt=1,4-benzeneditetrazolate) exhibits month-long water stability, while CoV-bdt-tph sets a new benchmark for C 2 H 2 storage capacity under ambient conditions for ionic MOFs. In addition to tunable in-framework modules, we show feasibility to tune the type and concentration of extra-framework counter cations and their influence on both stability and capability to separate industrial C 3 H 8 /C 3 H 6 and C 6 H 6 /C 6 H 12 mixtures.

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

Coupled aero-hydro-geotech real-time hybrid simulation of offshore wind turbine monopile structures

Real-time hybrid simulation (RTHS) divides a structural system into an analytical and experimental substructure. The former is based on a well-established analytical model while the latter consists of a physical model in the laboratory, for which there is not a well-established analytical model. This paper extends real-time hybrid simulation to monopile-type Offshore Wind Turbines (OWTs) to enable the investigation of their behavior considering the response of pile foundations under operational and more severe conditions. The embedded foundation and surrounding soil of the OWT are modeled physically in a soil box in the laboratory while the remaining parts of the system and loading are modeled analytically. The program OpenFAST, developed by the National Renewable Energy Laboratory (NREL), is linked to the RTHS coordinator to determine the hydrodynamic and aerodynamic loads acting on the OWT, along with modeling the dynamics of the electric power generation equipment and associated controller for the OWT. The RTHS framework along with its initial implementation and validation are described in this paper. RTHSs of a 5 MW OWT subjected to operational and more severe conditions are performed to experimentally validate the framework. The framework offers a realistic approach to investigate the behavior of OWT structures supported on monopiles. Furthermore, this approach accounts for the coupled response of the OWT structure with its foundation, while experimentally capturing the nonlinearities of the soil-foundation interaction in real-time.

17 WIND ENERGY↗
DOE OSTI2026

Revealing multiscale competing processes in the solid-state synthesis of single-crystalline layered oxide positive electrodes

Solid-state synthesis involves a web of coupled chemical reactions and physical changes that unfold across multiple scales. Efforts to fine-tune its parameters have historically followed heuristic, trial-driven workflows that demand significant time and resources. In this study, we aimed to open this black box by employing multiscale in situ synchrotron imaging and diffraction. Using LiNi 0.5 Mn 0.3 Co 0.2 O 2 battery positive electrode material as a model system and Ba-based sintering aids, we reveal dopant segregation, intergranular mass transport, and porosity evolution as key drivers of single-crystalline particle formation. Notably, we uncovered a dynamic competition between particle-level grain coalescence and atomic-scale cation disordering, both of which are thermally activated yet have opposing impacts on battery performance. These findings highlight the coupled, multiscale nature of structure development and offer a mechanistic basis for optimizing the solid-state synthesis process. This framework provides a path toward more controlled, efficient, and scalable production of high-performance battery positive electrode materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nonlinear Elimination Applied to Radiation Diffusion

We apply a nonlinearly preconditioned, quasi-Newton framework to accelerate the numerical solution of the thermal radiative transfer (TRT) equations. This framework was inspired by the unpublished method that has existed for years in Teton, Lawrence Livermore National Laboratory’s deterministic TRT code. In this paper, we cast this iteration scheme within a formal nonlinear preconditioning framework and compare its performance against other iteration schemes in the framework. With proper choices of iteration controls for the various levels of the solver, we can recover the standard linearized one-step method, a full nonlinear Newton scheme, as well as the method in Teton. In brief, the nonlinear preconditioning TRT scheme formally eliminates the material temperature equation from the nonlinear system in a nonlinear analog of a Schur complement. This nonlinear elimination step involves solving a decoupled nonlinear equation for each spatial degree of freedom and is therefore inexpensive. By applying a quasi-Newton iteration scheme on the new system, we obtain a three-level iteration scheme that is at least as efficient as commonly used TRT schemes. The new method allows full convergence to the nonlinear backward Euler time-discretized system, increasing accuracy and robustness, while using a similar number of linear iterations as the more common linearized one-step methods Eq. (4).

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

World beyond the nearest neighbors

The structure beyond the nearest neighbor atoms in liquid and glass is characterized by the medium-range order (MRO). In the conventional approach, the MRO is considered to result directly from the short-range order (SRO) in the nearest neighbors. To this bottom–up approach starting with the SRO, we propose to add a top–down approach in which global collective forces drive liquid to form density waves. The two approaches are in conflict with each other, and the compromise produces the structure with the MRO. The driving force to produce density waves provides the stability and stiffness to the MRO, and controls various mechanical properties. This dual framework provides a novel perspective for description of the structure and dynamics of liquid and glass.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Predicting core transport in ITER baseline discharges with neon injections

Achieving self-consistent performance predictions for ITER requires integrated modeling of core transport and divertor power exhaust under realistic impurity conditions. We present results from a systematic power-flow and impurity-content study for the ITER 15 MA baseline scenario constrained directly by existing SOLPS-ITER neon-seeded divertor solutions. Using the OMFIT STEP workflow, stationary temperature and density profiles are predicted with TGYRO for $1.5 \unicode{x2A7D} Z_\textrm{eff} \unicode{x2A7D} 2.5$, and the corresponding power crossing the separatrix $P_\textrm{sep}$ is evaluated. We find that $P_\textrm{sep}$ varies by more than a factor of 1.7 across this scan and matches the ${\sim}100$ MW SOLPS-ITER prediction when $Z_\textrm{eff} \simeq 1.6$ or when auxiliary heating is reduced to ${\sim}75\%$ of nominal. Rotation-sensitivity studies show that plausible variations in toroidal flow magnitude modify $P_\textrm{sep}$ by $\lesssim 20\%$, while AURORA modeling confirms that charge-exchange radiation inside the separatrix is dynamically negligible under predicted ITER neutral densities. These results identify a restricted compatibility window, $Z_\textrm{eff} \approx 1.6$ –1.75 and $0.75 \lesssim f_{P_\textrm{aux}} \unicode{x2A7D} 1.0$, in which core transport predictions remain aligned with neon-seeded divertor protection targets. This self-consistent, model-constrained framework provides actionable guidance for impurity control and auxiliary-heating scheduling in early ITER operation and supports future whole-device scenario optimization.

ITER↗