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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Reinforcement Learning Control for Enhancing Marine Hydrokinetic Turbine Energy Generation

This paper proposes a reinforcement learning-based method to maximize power generation for a direct-drive marine hydrokinetic turbine. A high levelized cost of energy (LCOE) is preventative in the widespread adoption of many marine energy conversion technologies. A straightforward way to reduce LCOE is to increase conversion efficiency and ensure maximum energy generation. The proposed method utilizes a damping control methodology, varying applied generator torque via a linear relationship between the applied damping coefficient and rotor speed. A state-action-reward-state-action (SARSA) algorithm has been used to learn the optimal control action for a given flow velocity. The proposed SARSA methodology uses Gaussian radial basis functions to create a three-dimensional surface to estimate the relationship between damping coefficient, incoming flow velocity, and coefficient of power (C p ). Here, the SARSA algorithm was compared against a baseline optimal tip speed ratio controller over a year-long flow velocity case profile while considering the effects of biofouling on the turbine system, where the proposed RL method generated 0.92% more energy than the baseline.

Damp↗
DOE OSTI2025

The impact of capillary heterogeneity on CO 2 flow and trapping across scales

Capillary heterogeneity has been identified over the last decade as a key control on subsurface CO 2 flow behavior during geological CO 2 sequestration. These heterogeneities can be formed in all sedimentary rocks, ranging from slight variations in the sand grain sizes to extensive sequences of interbedded sands, shales, and limestones. Capillary heterogeneity has been largely, although not entirely, overlooked in subsurface flow modeling because it is assumed to only directly influence fluid redistribution over scales of centimeters to meters. However, even small-scale fluid movements can result in dramatic impacts on the mobility and trapping of the CO 2 over kilometers. Therefore, neglecting capillary heterogeneity at multiple scales could potentially lead to errors in modeling and predicting field-scale plume migration. In this review paper, we aim to provide a consistent overview to (1) establish that capillary heterogeneity can have a major impact on CO 2 plume migration, (2) establish the respective length scales at which capillary heterogeneity matters, and (3) provide guidance for numerical modeling. This review covers pertinent literature and extracts key observations from the core to the field scales. Experimental studies have shown that millimeter-decimeter scale capillary heterogeneity can cause the so-called capillary heterogeneity trapping in addition to pore-scale residual trapping. Even at such a small scale, capillary heterogeneity can already lead to complex upscaled constitutive relationships, such as flow-rate dependent and anisotropic relative permeability, which affects field-scale CO 2 migration even when field-scale heterogeneities are present. Under gravity-dominated flow regimes, centimeter-meter scale capillary heterogeneity can entrap a significant amount of CO 2 at field scale, not just after imbibition but also during drainage. In certain cases, the presence of capillary heterogeneity can even completely stop the vertical movement of the CO 2 plume, hence greatly reducing leakage risks. At meter-kilometer scale, the influence of capillary heterogeneity is more pronounced and can hinder or redirect CO 2 migration in both lateral and vertical directions. The impact of capillary heterogeneity across multiple spatial scales poses a great challenge in modeling CO 2 migration at field scale, because it is practically impossible to build a field-scale earth model with grid blocks at millimeter scale. We recommend a hierarchical modeling approach to address this challenge. At field scale, earth models are built to capture geological features and heterogeneities in high but still practical grid resolutions. For each facies or rock type of the field-scale model, high- resolution meter-scale “conceptual” models are built with millimeter-scale grid blocks to capture representative fine-scale bedding geometries and heterogeneities in various environments of deposition, bridging the gap from subcore scale to the size of a field-scale simulation grid block. Upscaling is then used to preserve the smaller-scale flow dynamics of various rock types in field-scale simulations. Here, future work is needed to (1) refine, improve, and validate the hierarchical modeling approach; (2) build libraries of fine-scale bedding models for facies in various environments of deposition; (3) quantify multiscale capillary heterogeneity effects under subsurface uncertainties; (4) gain learning from different storage formations; and (5) establish best practices that balance accuracy and computational speed.

Capillary heterogeneity↗
DOE OSTI2024

Analysis of Power-Maximizing Region 2 Controllers for Wind and Marine Turbines

Wind and marine energy are rapidly growing and complementary technologies that share some techniques for simplified modeling and control, particularly in below-rated flow speeds. A turbine operator has several choices of controller for maximizing power in Region 2. The simple and ubiquitous KΩ 2 control law is often effective but limited in its flexibility. Alternative controllers use reference tracking to split the control objectives into a low-bandwidth optimal tip-speed ratio tracking loop to maximize steady-state power and a higher-bandwidth proportional-integral control loop to reject inflow turbulence. Several options exist for identifying the slowly varying optimal set point during operation, based on estimating the inflow velocity or filtering the power or torque signals. This study compares the trade-offs between performance and other design priorities for a few choices of reference-tracking controller in the literature for reference wind and marine turbines. Analysis is performed in the frequency domain using the linearization of each controller, and the impact of turbulent disturbances on the closed-loop system is described. The controllers are simulated in OpenFAST to analyze their performance with higher-order nonlinear turbine dynamics.

17 WIND ENERGY↗
DOE OSTI2024

Transient Optimization of the Cryogenic Moderator System Controller at the Spallation Neutron Source for Improved Performance

The high-energy neutron beam generated at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory is moderated to use cold (slow) neutrons for scientific discoveries. The Cryogenic Moderator System (CMS) removes heat from the neutron beam using cryogenic hydrogen (H 2 ) moderators connected via heat exchangers to a helium (He) refrigeration loop that dissipates heat using a compressor-brake system. However, the CMS is affected by sporadic losses in beam power, referred to as "beam trips," as these events generate significant disturbances in cooling requirements. To accommodate the heat load transients during beam trips, the CMS uses a decentralized control strategy consisting of four flow valves and one electric heater adjusted by independent proportional-integral (PI) controllers. During the CMS’s initial commissioning, the PI gains were calibrated based only on tracking performance, overlooking their effectiveness in disturbance rejection. A data-driven, control-oriented closed-loop model was developed to recalibrate the PI gains and minimize the transient disturbances caused by beam trips. The model consists of three main components: (1) a physics-based model of the He refrigeration loop, (2) a machine-learning model of the cryogenic H 2 cooling trains, and (3) the control logic used for feedback set-point tracking. Experimental results showed that the recalibrated gains obtained in this study improved the CMS’s transient response during beam trips.

Maldonado Puente, Bryan↗
DOE OSTI2026

Flow synthesis of iron oxide nanoparticles: using multiple precursor additions to improve size control

Controlling the size of iron oxide nanoparticles while maintaining uniformity in flow-based synthesis systems has been a great challenge in nanoparticle synthesis. Using an extended LaMer mechanism, we improve both the size and shape uniformity as compared to a conventional flow synthesis. The key to this approach is the injection of additional Fe precursor during the flow reaction, providing extra precursor during the growth process leading to a size focusing step. This approach has also allowed for the systematic variation of the nanoparticle size produced in the flow reaction. This work represent a new synthetic concept for improving the size uniformity of iron oxide nanoparticles in flow-based synthesis and has potential for application across a wide range of nanoparticle systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Traffic Signal Control for Large-Scale Urban Traffic Networks: Real-World Experiments using Vision-Based Sensors

Effective control of traffic signals plays a critical role in ensuring smooth vehicle flow in urban areas. Expertly engineered traffic signal controllers can considerably minimize travel delays and enhance sustainability. In this paper, the team proposes the Model Predictive Control (MPC) traffic signal control strategy using real-time traffic flow data from a vision-based camera as feedback information. Also, a realistic signal timing plan that considers National Electrical Manufacturers Association (NEMA) constraints has been developed to be applied to real-world scenarios. The primary aim is to reduce the number of vehicles across all links in the controlled area, thereby optimizing traffic flow and reducing energy consumption. To validate the proposed method, several real-life experiments were conducted at 24 intersections in Chattanooga, Tennessee, by collaborating with traffic field engineers. These experiments demonstrated significant performance improvements in comparison to the existing method.

data processing↗
DOE OSTI2026

Comparing Tandem Cell Designs for Electrochemical CO 2 Reduction to Ethylene

Electrochemical carbon dioxide reduction (CO 2 R) is a promising approach for the decentralized production of fuels such as ethylene (C 2 H 4 ). However, the use of Cu, the most efficient metal CO 2 R catalyst for the generation of C 2 H 4 known to date, generally yields a product stream with poor selectivity. In an effort to increase selectivity, the reaction from CO 2 to C 2 H 4 can be broken down into two steps using tandem CO 2 R electrolyzers: formation of CO from CO 2 and subsequent reduction of CO to C 2 H 4 . Here, in this study, we present two novel tandem electrolyzer architectures that closely integrate two cathodes, one for CO generation and one for conversion to C 2 H 4 , while still enabling independent electrical control of the cathodic surfaces. Cathode segmentation in each of these designs also permits the controlled sequencing of mass flow of chemical intermediates in the order of Au to Cu cathode catalysts, in contrast to earlier work relying on uncontrolled, passive diffusion to facilitate the flow of chemical intermediates between catalysts. When comparing the performance of the newly developed electrolyzer cell designs with a dual electrolyzer system, we found that the dual electrolyzer system yields the highest C 2 H 4 faradaic efficiencies (FEs) of 31% and C 2 H 4 concentrations (∼8 mol %). However, a single Cu-containing electrolyzer outperformed all three tandem systems in terms of C 2 H 4 FE (34%). Our findings, enabled by independent control of the two tandem cathode surfaces, indicate that tandem CO 2 R systems need to be evaluated carefully by testing them at various relevant current densities.

C2H4↗
DOE OSTI2025

Kinematic flow from the flow of cuts

The wavefunction coefficients of conformally coupled scalars in power-law FRW cosmologies satisfy differential equations governed by a set of simple combinatorial rules known as the kinematic flow. In this paper we derive the kinematic flow, expressed using a set of differential forms referred to as the cut basis, from a geometric perspective, relying solely on the cosmological hyperplane arrangement and without invoking bulk physics. Each element of the cut basis corresponds to the positive geometry associated to an independent cut of the physical FRW-form and can be labeled by decorating (minors of) the truncated Feynman graph with an acyclic orientation. We provide a straightforward prescription to associate a logarithmic differential form to each element of the cut basis by considering its corresponding decorated graph. Moreover, we show that the residues of the physical FRW-form are canonical forms of certain graphical zonotopes labeled by the same set of decorated graphs. These zonotopes control the cut combinatorics -- flow of cuts -- of the physical FRW-form and the cut basis (by construction). Using the theory of relative twisted cohomology and intersection theory, we derive a closed form formula for the differential equations of the cut basis. We also introduce combinatorial rules that compute the kinematic differential of any basis element without explicit calculation. The combinatorics of our differential equations is a natural consequence of the flow of cuts and is equivalent (up to rescaling) to the kinematic flow for the recently studied time integral basis. In particular, our differential equations decouple into exponentially many sectors, one for each way of cutting a subset of edges of the graph.

General Relativity and Quantum Cosmology↗
DOE OSTI2025

Per-Phase Control for CHB Converters with Negative-Sequence Current and DC Voltage Balancing Control

This paper presents a per-phase controller for a grid-connected Cascaded H-Bridge (CHB) converter featuring negative sequence current regulation and DC bus voltage balancing capabilities. Unlike conventional three-phase controllers, each phase of the CHB can be separately and controlled to regulate the DC voltage and reactive power flow. per-phase negative sequence current control strategy is incorporated into the proposed controller to ensure compliance with IEEE Standard 2800-2022, which requires the absorption of negative-sequence reactive current during grid voltage disturbances. Furthermore, a feed-forward control-based DC bus voltage balancing method is employed, which eliminates the need for the integrator commonly used in traditional approaches. The performance of the proposed controller is validated under various unbalanced grid scenarios and DC bus voltage imbalances through electromagnetic transient (EMT) simulation using a three-phase, three-level grid-connected CHB–Dual Active Bridge (DAB) converter testbed developed on MATLAB/Simulink. Additionally, the performance of the negative-sequence current regulation is investigated through simulation under different unbalanced grid voltage scenarios.

negative sequence current↗
DOE OSTI2024

3D‐Mapping and Manipulation of Photocurrent in an Optoelectronic Diamond Device

Abstract Establishing connections between material impurities and charge transport properties in emerging electronic and quantum materials, such as wide‐bandgap semiconductors, demands new diagnostic methods tailored to these unique systems. Many such materials host optically‐active defect centers which offer a powerful in situ characterization system, but one that typically relies on the weak spin‐electric field coupling to measure electronic phenomena. In this work, charge‐state sensitive optical microscopy is combined with photoelectric detection of an array of nitrogen‐vacancy (NV) centers to directly image the flow of charge carriers inside a diamond optoelectronic device, in 3D and with temporal resolution. Optical control is used to change the charge state of background impurities inside the diamond on‐demand, resulting in drastically different current flow such as filamentary channels nucleating from specific, defective regions of the device. Conducting channels that control carrier flow, key steps toward optically reconfigurable, wide‐bandgap optoelectronics are then engineered using light. This work might be extended to probe other wide‐bandgap semiconductors (SiC, GaN) relevant to present and emerging electronic and quantum technologies.

Wood, Alexander A.↗
DOE OSTI2024

Self-Focused Pulse Propagation Is Mediated by Spatiotemporal Optical Vortices

We show that the dynamics of high-intensity laser pulses undergoing self-focused propagation in a nonlinear medium can be understood in terms of the topological constraints imposed by the formation and evolution of spatiotemporal optical vortices (STOVs). STOVs are born from point phase defects on the sides of the pulse nucleated by spatiotemporal phase shear. These defects grow into closed loops of spatiotemporal vorticity that initially exclude the pulse propagation axis, but then reconnect to form a pair of toroidal vortex rings that wrap around it. STOVs constrain the intrapulse flow of electromagnetic energy, controlling the focusing-defocusing cycles and pulse splitting inherent to nonlinear pulse propagation. Here, we illustrate this in two widely studied but very different regimes, relativistic self-focusing in plasma and nonrelativistic self-focusing in gas, demonstrating that STOVs mediate nonlinear propagation irrespective of the detailed physics.

42 ENGINEERING↗
DOE OSTI2025

Irradiation Vehicles for Evaluating SiC/SiC Cladding Bowing Under Neutron Flux Gradients

Silicon carbide fiber–reinforced silicon carbide matrix (SiC/SiC) composites are among the most promising candidates for long term accident-tolerant nuclear fuel cladding. A key challenge related to their deployment is lateral bowing caused by differential radiation-induced swelling under dose or temperature gradients, which could obstruct coolant flow or interfere with control rod/blade movements. Although previous modeling efforts have predicted bowing behavior in light-water reactor (LWR) environments, experimental validation remains limited, especially at prototypic LWR temperatures. This study addresses that gap by irradiating six reduced-length SiC/SiC cladding tubes (~600 mm) in the High Flux Isotope Reactor (HFIR) at ~300°C, which is representative of LWR conditions. The tubes will be housed in a sealed vessel with an inert gas gap to maintain target temperatures and prevent direct coolant contact. Arranged in three pairs, each set will receive a different radiation dose (low, medium, high), with the central pair receiving ~0.1 displacements per atom (dpa)—the expected dose for peak bowing. The experiment will determine the dose-dependent bowing behavior and validate predictive finite element models. In this work, the tubes are freely suspended from pins to allow for unconstrained bowing; however, we present a concept for introducing localized constraints to represent grid spacer effects. Post-irradiation examination will include swelling measurements and profilometry to assess bowing and compare the results with model predictions. This work aims to confirm the conditions under which maximum bowing occurs so as to improve the reliability of SiC/SiC performance models in nuclear applications.

Russell, Nick [ORNL] (ORCID:0000000296099820)↗
DOE OSTI2024

7-8 GHz Point-to-Point Testing

Wireless spectrum is a limiting resource for continued economic growth in the United States. As discussed in the recent National Spectrum Strategy (NSS), wireless spectrum underpins several aspects of the U.S. economy and the demand for additional spectrum is driving the need for realizing spectrum sharing to enable continued development. At the same time, wireless spectrum is an essential foundation of critical energy infrastructure, including electric, oil, and natural gas resources. In particular, wireless point-to-point (P2P) links are the backbone of vast infrastructure networks that enable the flow of sensor and control information needed to manage critical energy sector infrastructure in the United States. These links will only become more important as the energy sector incorporates more diverse sensing and more efficient control mechanisms, which increases system complexity and data volume requiring more resilient communications. Therefore, the continued economic development of the U.S. depends on determining novel approaches to spectrum management that balance both broad access for advanced wireless technologies and resilience for critical infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Developing Drag Models for Non-Spherical Particles through Machine Learning

The overarching goal of this project is to produce comprehensive experimental and numerical datasets for gas-solid flows in well-controlled settings to understand the aerodynamic drag of non-spherical particles in the dense regime. The datasets and the gained knowledge will be utilized to train deep neural networks in TensorFlow to formulate a general drag model for use directly in NETL MFiX-DEM module in order to help to advance the accuracy and prediction fidelity of the computational tools that will be used in designing and optimizing fluidized beds and chemical looping reactors.

42 ENGINEERING↗
DOE OSTI2025

High-Fidelity Analysis of EV Integration on Real Utility Feeders in Colorado

Residential electric vehicle (EV) charging has the potential to alter long-held assumptions on load characteristics impacting distribution grid planning, operations, and design standards. This study identifies analysis and control methods to increase the affordability of residential EV charging both for Xcel Energy and their customers. The project also provides solutions for more reliable grid interconnection that can support a reliable utility business model prepared for increasing EV charging load in the coming years. For this project, we referenced Level 2 alternating current (AC) onboard charging profiles for various vehicle models and high-fidelity charging data collected at the experimental setup established at the EV Research Infrastructure Laboratory at the National Renewable Energy Laboratory (NREL). Next, we developed EV adoption models for 2030 and 2040 for the Boulder and Aurora regions in Colorado. Moreover, we evaluated different smart charging control algorithms and compared their performance. We developed time-of-use (TOU)-based and grid-aware active EV charging control methods and integrated them within the study region to understand field impacts. Diving deeper, we selected 10 feeders in Boulder and Aurora for high-fidelity grid modeling down to the house level. We executed detailed grid analysis comparing the smart charge management (SCM) algorithms we developed. Finally, we created a novel tool, Electric Vehicle Infrastructure--Distribution System Integration Tool (EVI-DiST), to integrate all the approaches in a single software environment to provide easy integration, fast simulation, and detailed evaluation capability for utility engineers and other stakeholders.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Colorado Residential Resiliency and Managed Charging

Validate and model impacts of electric vehicle (EV) home charging on service transformers; analyze diverse grid locations and configurations to determine 'risk factors'; finalize/deliver new design tools and typical EV load curves; improve/issue new construction standards for transformers, secondaries, and services. To ensure residential charging equity, smart charge management strategies will be studied and analyzed with the goal of creating affordable demand charges for customers.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Infrastructure-Based Cooperative Perception at a Traffic Intersection: Overview and Challenges

Traffic intersections are crucial and challenging nodes in transportation networks where multiple lanes of vehicles and pedestrians converge. About one-quarter of traffic fatalities and about one-half of all traffic injuries in the United States happen at traffic intersections . Effective management of these intersections is important to ensure safety and efficiency of all users - vehicles, pedestrians, cyclists, and vulnerable road users (VRUs). With advancements in sensor perception technologies such as radar, light detection and ranging (lidar), and cameras, traffic intersections are developing into dynamic and data-rich environments. By using these data to create a real-time digital twin, we can enable real-time data-driven decision making and a range of applications such as sharing perception information to connected vehicles (CVs) and connected autonomous vehicles (CAVs), safety affirmative signaling, and curb optimizing to improve efficiency and enhance safety.This paper presents an overview of the concept and examines the challenges involved in implementing an infrastructure-based cooperative perception engine at a traffic intersection. In addition to outlining the physical components, this study also addresses important challenges involved in a multi-sensor system. We present results from deploying the National Renewable Energy Laboratory's (NREL's) Infrastructure Perception and Control (IPC) mobile trailer at a traffic intersection in the city of Colorado Springs, Colorado, USA that employed multiple radars and lidars to capture the data. This study provides necessary practical learning for the Cooperative Driving Automation (CDA) and traffic engineering communities for next-generation infrastructure-based cooperative perception that promises improvements in signal control for optimized traffic flow, among other applications, and documents findings for ongoing research and development efforts in other areas.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗