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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Methane Mitigation Thermoelectric Generator (MMTEG) (Final Scientific/ Technical Report)

Gas Technology Institute (GTI) has completed a $1.815M (plus $500K cost share), 54-month Co-operative agreement with the Department of Energy’s National Energy Technology Laboratory to develop a Methane Mitigation Thermoelectric Generator (MMTEG) system for gas field applications. This novel system uses fugitive gas to produce electrical power and consists of Thermoelectric Generators (TEG) driven by a linear burner, an air compressor, an accumulator, valves, batteries, and power electronics. The electrical power generated by the system is used to compress air and, in turn, the air is used to operate the pneumatic valves at the well site instead of using natural gas (NG) which would then be vented. The team completed the project objectives which included (1) Design, fabricate and test an integrated 6We nominal MMTEG prototype system, (2) Design a “retrofit kit” MMTEG system capable of being field tested at a gas well production site, and (3) build and test the field MMTEG system in a laboratory environment. Multiple system options were developed prior to selecting a “Passive” system which meets cost, NG savings, and greenhouse gas (GHG) reduction targets although not as efficient as initially planned. The MMTEG system is built primarily from commercial off-the-shelf parts (in some cases re-purposed) including the heat exchanger, heat rejection, electronic components, and also the TEGs. The team developed and implemented a novel system including the control system developed by Morrison Applied Sciences (MAS). The team completed incremental demonstrations of the hardware prior to the MMTEG system demonstration. A one-year simulation of the air delivery and battery charging subsystems was completed prior to the integration into the MMTEG system. In addition, the team simulated two-years of thermal cycles for integrated Burner/TEG/heat rejection subsystem. Finally, the entire MMTEG system was assembled, and troubleshooting was completed over a two-week period. Next, the MMTEG system was tested to simulate over 15 weeks of entire system operation over approximately four weeks in an accelerated test fashion with minimal intervention (such as changing fuel tanks). The MMTEG system met the key goals of a unit cost of under $1500 while saving 97% of NG expended today (including leakage) on average by pneumatic systems venting to the atmosphere. The MMTEG system reduced GHG emissions by 1000X (using the methane intensification factor of 28 relative to CO2). GTI is currently pursuing a field test of the MMTEG system. Interfacing with producers has provided additional insight into system improvements. Planned improvements include additional weather protection and control system improvements including the implementation of a long- range radio capability to notify operators if there is a fault.

03 NATURAL GAS↗
DOE OSTI2021

Development of a new control rod drive mechanism design for the ISU AGN-201M reactor

The Aerojet General Nucleonics (AGN) model 201-Modified, known as the AGN-201M reactor, plays an essential role in the educational and research activities at Idaho State University (ISU). The ISU AGN-201M's original Control Rod Drive Mechanism (CRDM) has been in operation for more than fifty years with no large-scale redesigns. The CRDM is required to eject the fuel rods within one second during a SCRAM event (also known as a 'reactor trip') and adjust the control rods' insertion speed, and keeps the rod insertion sequence correct. The existing control rod drive mechanisms meet these criteria but experience a few concerns due to aging. Concerns include complex maintenance and costly repairs for old electromechanical components, rod position feedback errors, and the impediment of the plate during a SCRAM due to binding of the lead screws of the existing mechanism. During a binding event, the drive mechanism becomes locked, preventing the control rod's magnetic plate from moving in or out under the reactor's normal and emergency operating conditions. Although, the binding has no effect on the ability of the rod to exit the core during the SCRAM. To counteract the concerns and issues with the current CRDM, a new design has been proposed using newer components and a simplified design. The new design utilizes more advanced electric and mechanical components that are commercially available. The new CRDM system is divided into four main aspects: (1) control rod movement design (motor, lead screw, guide rods), (2) control rod ejection (springs, electromagnet), (3) control rod position and feedback (position transducer, microswitches), and (4) material selection and structural analysis. The new design aims to reduce the overall complexity and probability of failure to improve the reactor's overall reliability. With proper material selection and improved structural design, the new drives are lighter with little to no change in structural integrity. The new control rod drive mechanism eliminates binding scenarios by using a single lead screw and implementing additional guide rods. An advanced linear position sensor and microswitches replace the existing and aging synchro system for accurate rod position feedback resulting in better reactivity control. The new design meets the reactor's operational limits by having an average reactivity insertion of 0.065% Δk/k per second, which corresponds to a total control rod insertion time of 19.23 s, while the control rod's ejection time remains less than one second during a SCRAM event. The new design ensures the reactor's long-term viability for educational and research activities by increasing the reliability and safety of operation for years to come.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Nitrogen fixation and mucilage production on maize aerial roots is controlled by aerial root development and border cell functions

Exploring natural diversity for biological nitrogen fixation in maize and its progenitors is a promising approach to reducing our dependence on synthetic fertilizer and enhancing the sustainability of our cropping systems. We have shown previously that maize accessions from the Sierra Mixe can support a nitrogen-fixing community in the mucilage produced by their abundant aerial roots and obtain a significant fraction of their nitrogen from the air through these associations. In this study, we demonstrate that mucilage production depends on root cap and border cells sensing water, as observed in underground roots. The diameter of aerial roots correlates with the volume of mucilage produced and the nitrogenase activity supported by each root. Young aerial roots produce more mucilage than older ones, probably due to their root cap’s integrity and their ability to produce border cells. Transcriptome analysis on aerial roots at two different growth stages before and after mucilage production confirmed the expression of genes involved in polysaccharide synthesis and degradation. Genes related to nitrogen uptake and assimilation were up-regulated upon water exposure. Altogether, our findings suggest that in addition to the number of nodes with aerial roots reported previously, the diameter of aerial roots and abundance of border cells, polysaccharide synthesis and degradation, and nitrogen uptake are critical factors to ensure efficient nitrogen fixation in maize aerial roots.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Learning Local Volt/VAR Controllers Toward Efficient Network Operation with Stability Guarantees: Preprint

This paper considers the problem of voltage regulation in distribution network. The primary motivation is to keep voltages within pre-assigned operating limits by commanding the reactive power output of distributed energy resources (DERs) deployed in the grid. We develop a framework for developing local Volt/Var control that comprises of two main steps. In the first, exploiting historical data and for each DER, we learn a function representing desirable equilibrium points for the power network. These points approximate solutions of an Optimal Power Flow problem. In the second, we propose a control scheme for steering the network towards these favorable configurations. Theoretical conditions are derived to formally guarantee the stability of the developed control scheme and numerical simulations illustrate the effectiveness of the proposed approach.

data-driven control↗
DOE OSTI2021

Developing an Eco-Cooperative Automated Control System (Eco-CAC)

The goal of the project was to develop a novel Eco-Cooperative Automated Control (Eco-CAC) system that integrates vehicle dynamics (VD) control with connected and automated vehicle (CAV) applications. In particular, the team developed a novel integrated control system that (1) routes vehicles in a fuel/energy-efficient manner for internal combustion engine vehicles (ICEVs), battery-only electric vehicles (BEVs), and hybrid electric vehicles (HEVs); (2) selects vehicle speeds based on anticipated traffic network evolution; (3) minimizes vehicle fuel/energy consumption near signalized intersections; and (4) intelligently modulates the longitudinal motion of vehicles within a cooperative platoon to minimize its fuel/energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Two-Stage Reinforcement Learning Policy Search for Grid-Interactive Building Control

This paper develops an intelligent grid-interactive building controller, which optimizes building operation during both normal hours and demand response (DR) events. To avoid costly on-demand computation and to adapt to non-linear building models, the controller utilizes reinforcement learning (RL) and makes real-time decisions based on a near-optimal control policy. Learning such a policy typically amounts to solving a hard non-convex optimization problem. We propose to address this problem with a novel global-local policy search method. In the first stage, an RL algorithm based on zero-order gradient estimation is leveraged to search for the optimal policy globally, due to its scalability and the potential to escape some poor performing local optima. The obtained policy is then fine-tuned locally to bring the first-stage solution closer to that of the original unsmoothed problem. Experiments on a simulated five-zone commercial building demonstrate the advantages of the proposed method over existing learning approaches. They also show that the learned control policy outperforms a pragmatic linear model predictive controller (MPC) and approaches the performance of an oracle MPC in testing scenarios. Using a state-of-the-art advanced computing system, we demonstrate that the controller can be learned and deployed within hours of training.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

An Agile/XP software development process for modernizing the accelerator control system at Fermilab

Fermilab is undergoing the most ambitious upgrade to its accelerator control system of the 21st century. As part of the ACORN project, hundreds of legacy control system applications written in C/C++ will be re-imagined and developed from the ground up. In addition, applications to support Fermilab’s new super-conducting linear accelerator are already under construction. To manage the development of modern controls applications, the Controls department has adopted an Agile software development process based on eXtreme Programming. In this paper we will describe our process and detail our experience applying it to the development of two case studies.

Diamond, John [Fermilab]↗
DOE OSTI2025

Resilient Operation of Networked Community Microgrids with High Solar Penetration

This project, funded by the US Department of Energy’s Solar Energy Technologies Office (SETO), focused on the operation of microgrids as a coordinated network. The primary objective, which was successfully achieved, was to develop both control strategies and hardware solutions to support the resilient and efficient operation of networked microgrids with high solar penetration. The work was structured around the following four main tasks: • Development of distributed and scalable optimization algorithms for AC-coupled networked microgrids. • Design and implementation of a novel DC interconnection hardware to enable precise power exchange between microgrids. • Laboratory operational validation of the developed technologies using 480 V testbeds and commercially available hardware. • Field operational validation of the complete solution in Adjuntas, Puerto Rico, interconnecting two kW-scale, split-phase microgrids of Casa Pueblo’s microgrids. This project addressed multiple technical challenges across the domains of optimization, control, hardware interconnection, and protection. One of its key contributions was delivering tangible, real-world solutions for networking microgrids. In contrast to purely theoretical or simulation-based work, this project included full-scale hardware operational validation both in the lab and in the field. The work conducted as part of this project—in collaboration with the University of Puerto Rico; the University of Tennessee, Knoxville; the University of Central Florida; and Casa Pueblo—has advanced the state of the art in networked microgrids. Key contributions include the development of distributed control strategies, practical solutions for real-world implementation challenges, and the introduction of a novel DC interlink approach for microgrid interconnection. The project featured both laboratory and field validation using commercial off-the-shelf components. The field deployment successfully validated that a group of microgrids can operate in a coordinated manner, enabling precise power flow between systems and mutual support during extreme events. This project resulted in 15 journal publications and 15 conference papers; 5 graduate students and 15 undergraduate students were supported. The codes of distributed optimization and forecasting were made open-source through OSTI.gov for distributed optimization and forecasting. All the publications are available in the ORNL-hosted project landing page. The DC interlink with state-of-charge balancing control was operationally validated in Adjuntas by interconnecting two real-world, 240 V split-phase microgrids. To the best knowledge of the team, this represents the first operational validation of AC microgrids interconnected via DC-interlinks. As a culmination of this project, a follow-on grant was awarded to support the technology transfer of the distributed optimization framework to a commercial microgrid controller, Stellar Edge, developed by the California-based company New Sun Road.

14 SOLAR ENERGY↗
DOE OSTI2023

Development of a wind turbine model and simulation platform using an acausal approach: Multiphysics modeling, validation, and control

This article presents the development of the Control-oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS). CRAFTS has a modular, hierarchical model architecture that enables rapid and accurate simulation of wind turbines. The architecture facilitates the incorporation of model variants, and its system reconfiguration features help simulate multiple design variants. CRAFTS also supports the integration of models developed on a causality-free platform (e.g., Modelica®) with existing causal models. This article focuses on the validation of a land-based wind turbine models against OpenFAST, an industry-standard platform, for several test cases. Closed-loop scenarios are also tested using the standard ROSCO controller and compared against OpenFAST. In addition, a nonlinear controller developed in our prior work is also evaluated. The test cases demonstrate the user-friendly and computationally efficient capabilities of CRAFTS to facilitate control co-design, assist in incorporating multiphysics models, be adaptable to design variants, and allow for rapid simulations to validate models and evaluate controllers.

17 WIND ENERGY↗
DOE OSTI2022

Instantiation of HCML Demonstrating Bayesian Predictive Modeling for Attentional Control

The research team developed models of Attentional Control (AC) that are unique to existing modeling approaches in the literature. The goal was to enable the research team to (1) make predictions about AC and human performance in real-world scenarios and (2) to make predictions about individual characteristics based on human data. First, the team developed a proof-of-concept approach for representing an experimental design and human subjects data in a Bayesian model, then demonstrated an ability to draw inferences about conditions of interest relevant to real-world scenarios. Ultimately, this effort was successful, and we were able to make reasonable (meaning supported by behavioral data) inferences about conditions of interest to develop a risk model for AC (where risk is defined as a mismatch between AC and attentional demand). The team additionally defined a path forward for a human-constrained machine learning (HCML) approach to make predictions about an individual's state based on performance data. The effort represents a successful first step in both modeling efforts and serves as a basis for future work activities. Numerous opportunities for future work have been defined.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Demand Flexibility Controls Library using Semantics (DFLEXLIBS) v0.1

DFLEXLIBS is a library/repository of HVAC-based demand flexibility control applications developed using Python. The library is based on portable control applications that exclusively contain control logic and are abstract to building details, such as point names and communication protocols. The library leverages semantic models and control platform-oriented interfaces to configure and run the controls in specific buildings. To date, the library contains two applications and two interfaces (for BOPTEST and VOLTTRON) and has been demonstrated in five heterogeneous buildings.

Paul, Lazlo↗
DOE OSTI2025

Tracking and Positioning System for Floating Solar (CRADA Abstract)

The project goal is to develop a floating solar photovoltaics (FPV) tracking & position system that: (1) increases annual energy production of FPV projects by >10%, (2) lowers levelized cost of energy (LCOE) for FPV by >10%, and (3) leverages U.S. contract supply chain & manufacturing. The outcome of the project will be a certified tracking product that has undergone extensive field testing and is ready for commercial sales. The primary objectives for each budget period are: • BP1: Define product requirements, develop initial controls architecture and design other sub-components, complete small-scale pilot testing, install a larger-scale pilot, secure sites for commercial pilots, and develop the beta-version of a user portal. • BP2: complete control system and sub-component design, successful demonstration and testing at a commercial pilot, certification & bankability, finalize user portal, and complete various commercialization activities related to supply chain, customer acquisition, and sales. PNNL will provide support during both project phases for prototype development and testing of the controls architecture, software, and hardware components of the tracking and positioning system. PNNL will provide support during both project phases for prototype development and testing of the controls architecture, software, and hardware components of the tracking and positioning system. This effort represents PNNL’s first opportunity to support the floating solar photovoltaics (FPV) industry with capabilities, facilities, and personnel developed to contribute to the marine energy (e.g., wave and tidal energy) sector. This portfolio expansion leverages internal and DOE EERE investments and the growing visibility of PNNL-Sequim’s Marine and Coastal Research Laboratory (MCRL) and our marine research capabilities, in general. The development of effective and low-cost FPV platforms is a potential way to increase the nation’s set of tools for providing emission-free electricity without utilizing valuable terrestrial resources. Successful commercialization of such a project may lead to economic benefits through job creation, supply chain creation, and access to a cheaper source of electricity.

14 SOLAR ENERGY↗
DOE OSTI2020

Battery Electric Vehicle Eco-Cooperative Adaptive Cruise Control in the Vicinity of Signalized Intersections

This study develops a connected eco-driving controller for battery electric vehicles (BEVs), the BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The developed controller can assist BEVs while traversing signalized intersections with minimal energy consumption. The calculation of the optimal vehicle trajectory is formulated as an optimization problem under the constraints of (1) vehicle acceleration/deceleration behavior, defined by a vehicle dynamics model; (2) vehicle energy consumption behavior, defined by a BEV energy consumption model; and (3) the relationship between vehicle speed, location, and signal timing, defined by vehicle characteristics and signal phase and timing (SPaT) data shared under a connected vehicle environment. The optimal speed trajectory is computed in real-time by the proposed BEV eco-CACC-I controller, so that a BEV can follow the optimal speed while negotiating a signalized intersection. The proposed BEV controller was tested in a case study to investigate its performance under various speed limits, roadway grades, and signal timings. In addition, a comparison of the optimal speed trajectories for BEVs and internal combustion engine vehicles (ICEVs) was conducted to investigate the impact of vehicle engine types on eco-driving solutions. Lastly, the proposed controller was implemented in microscopic traffic simulation software to test its networkwide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed controller can effectively reduce stop-and-go traffic in the vicinity of signalized intersections and that the BEV Eco-CACC-I controller produces average savings of 9.3% in energy consumption and 3.9% in vehicle delays.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

High precision real-time insertion device and monochromator synchronization at NSLS-II

We report that insertion devices have become the dominant photon source at synchrotron and free electron laser light source facilities the world over. Undulators, characterized by their small deflection parameter, exhibit a high degree of constructive interference in photon production from high energy charged particle beams leading to very high photon rates at specific harmonics of the fundamental frequency with relatively narrow spectral widths. Spectroscopic measurements of interest typically span several of these harmonic widths, which requires precision adjustment of an undulator’s magnetic gap to maintain peak flux within the much narrower bandwidth of a beamline monochromator at the desired energy. High precision insertion device controls are developed at NSLS-II including real-time linked control of monochromator hardware allowing for fast, high precision, hardware triggered, spectroscopic measurements. Furthermore, this fast fly scan method is described, compared statistically for self consistency, and shown to be far superior in both efficiency and accuracy as compared to standard step scan measurements.

36 MATERIALS SCIENCE↗