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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Field testing of linear individual pitch control on the two-bladed controls advanced research turbine

This paper presents the results of field tests using linear individual pitch control (LIPC) on the two-bladed Controls Advanced Research Turbine 2 (CART2) at the National Renewable Energy Laboratory (NREL). LIPC has recently been introduced as an alternative to the conventional individual pitch control (IPC) strategy for two-bladed wind turbines. The main advantage of LIPC over conventional IPC is that it requires, at most, only two feedback loops to potentially reduce the periodic blade loads. In previous work, LIPC was designed to implement blade pitch angles at a fixed frequency (e.g., the once-per-revolution (1P) frequency), which made it only applicable in above-rated wind turbine operating conditions. In this study, LIPC is extended to below-rated operating conditions by gain scheduling the controller on the rotor speed. With this extension, LIPC and conventional IPC are successfully applied to the NREL CART2 wind turbine. Lastly, the field-test results obtained during the measurement campaign indicate that LIPC significantly reduces the wind turbine loads for both below-rated and above-rated operation.

17 WIND ENERGY↗
DOE OSTI2016

Maximization of the annual energy production of wind power plants by optimization of layout and yaw-based wake control: Maximization of wind plant AEP by optimization of layout and wake control

This paper presents a wind plant modeling and optimization tool that enables the maximization of wind plant annual energy production (AEP) using yaw-based wake steering control and layout changes. The tool is an extension of a wake engineering model describing the steady-state effects of yaw on wake velocity profiles and power productions of wind turbines in a wind plant. To make predictions of a wind plant's AEP, necessary extensions of the original wake model include coupling it with a detailed rotor model and a control policy for turbine blade pitch and rotor speed. This enables the prediction of power production with wake effects throughout a range of wind speeds. We use the tool to perform an example optimization study on a wind plant based on the Princess Amalia Wind Park. In this case study, combined optimization of layout and wake steering control increases AEP by 5%. The power gains from wake steering control are highest for region 1.5 inflow wind speeds, and they continue to be present to some extent for the above-rated inflow wind speeds. The results show that layout optimization and wake steering are complementary because significant AEP improvements can be achieved with wake steering in a wind plant layout that is already optimized to reduce wake losses.

17 WIND ENERGY↗
DOE OSTI2024

Autonomous control for Heat-Pipe microreactor using Data-Driven model predictive control

To enable a self-regulating capability for heat pipe (HP) microreactors, an anticipatory control strategy achieved via model predictive control (MPC) could proactively respond to potential disturbances and deviations in operating setpoints. This paper demonstrates data-driven methods for predicting the distribution and transient of temperatures and heat fluxes at selected components and regions in a 37-HP system, based on which the optimal control actions in response to changes in user-defined setpoints can be found. We present the development and validation of linear state-space model, feedfoward, and recurrent neural networks. Here, we compare the performance of MPCs with different modeling approaches in terms of following setpoints for temperatures and averaged output heat fluxes. The accuracies of the three data-driven models are similar, but the control actions initiated by neural-network-based MPC can better adapt to drastic changes in setpoints yet generate the smallest errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Learning-based CO 2 concentration prediction: Application to indoor air quality control using demand-controlled ventilation

There have been increasing concerns over the air quality inside buildings as high levels of bio-effluents can cause nausea, dizziness, headaches, and fatigue to the people working in those spaces. First published in 2004 as Standard 62.1, ASHRAE Standard 62.2-2019 requires highly occupied spaces to implement heating, ventilation, and air conditioning (HVAC) that can dilute contaminants produced by occupants. In this regard, occupant-centric ventilation control has been regarded as an effective practice to maintain a satisfactory indoor air quality (IAQ) when dealing with highly variable occupancy environments. However, few established models in current literature and practice consider dynamic occupancy behavior and adaptive IAQ control. To address this gap, a dynamic indoor CO2 model is constructed using machine learning algorithms to forecast CO2concentrations across a range of forecasting horizons. Herein, we tuned and compared six state-of-the-algorithms—including Support Vector Machine, Ada Boost, Random Forest, Gradient Boosting, Logistic Regression, and Multilayer Perceptron. The algorithms’ performances are validated using CO 2 and historical meteorological data collected from a campus classroom with a variable occupancy rate. Simulation results showed that Multilayer Perceptron can strongly predict the volatile CO 2 behavior and also outperforms other algorithms in terms of accuracy. Furthermore, a control strategy capable of modeling and detecting dynamic patterns of CO 2 level is utilized to modulate the ventilation rate in real-time and also reduce the energy consumption. The proposed controller reduced the HVAC fan’s energy consumption by 51.4% and provide ventilation as needed per the ASHRAE standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Nonlinear behavior in high-frequency aggregate control of thermostatically controlled loads

Coordinated control of electric loads can provide valuable grid services, such as frequency regulation. However, due to the nonlinear characteristics of such load ensembles, it is important to systematically analyze their behavior and establish a thorough understanding of undesirable phenomena that can potentially arise. In this paper, we analyze the frequency response of an aggregate control scheme, with the goal of exploring controller performance limits. We show that rapid switching commands can induce oscillations in the power output due to the inherent lockout mechanism of the underlying devices. Here, we demonstrate that highly detailed aggregate models are required to capture such phenomena. Such models enable deeper understanding of the control boundaries and therefore play an important role in avoiding the introduction of undesirable effects on the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Development and assessment of a model predictive controller enabling anticipatory control strategies for a heat-pipe system

To support the reliable and resilient operation of modular reactors and microreactors, anticipatory control strategies have been proposed for achieving faster-than-real-time predictions and decision-making capabilities in anticipation of potential anomalies, including setpoint changes and cyber incidents. Here this work presents how anticipatory control strategies can be implemented via model predictive control (MPC) of a single heat pipe’s temperature. Considering the uncertainty in developing and applying MPC, this work evaluates MPC performance given three different model forms: a linear response surface model, an artificial neural network (ANN), and an autoregressive model with exogenous input (ARX). This work also evaluates the impacts of different input biases and variance on MPC performance in order to account for potential sensor reading variations due to cyber incidents. We observe that nonparametric models such as the ANN and ARX result in more fluctuated control actions compared to the MPC applied to the linear response surface model. However, when the cyber incidents are of a large magnitude, the linear response surface model produces smaller feasible regions than the nonparametric models under identical constraints.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Improved inertial control for permanent magnet synchronous generator wind turbine generators

With increasing integrations of large‐scale systems based on permanent magnet synchronous generator wind turbine generators (PMSG‐WTGs), the overall inertial response of a power system will tend to deteriorate as a result of the decoupling of rotor speed and grid frequency through the power converter as well as the scheduled retirement of conventional synchronous generators. Thus, PMSG‐WTGs can provide value to an electric grid by contributing to the system's inertial response through the inherent kinetic energy stored in their rotating masses and fast power converter control. In this study, an improved inertial control method based on the maximum power point tracking operation curve is introduced to enhance the overall frequency support capability of PMSG‐WTGs in the case of large supply–demand imbalances. Moreover, this method is implemented in the CART2‐PMSG integrated model in MATLAB/Simulink to investigate its impact on the wind turbine's structural loads during the inertial response process. Simulation results indicate that the proposed method can effectively reduce the frequency nadir, arrest the rate of change of frequency, and alleviate the secondary frequency dip while imposing no negative impact on the major mechanical components of the wind turbine.

Wu, Ziping↗
DOE OSTI2015

Controlling hollow relativistic electron beam orbits with an inductive current divider

A passive method for controlling the trajectory of an intense, hollow electron beam is proposed using a vacuum structure that inductively splits the beam's return current. A central post carries a portion of the return current (I{sub 1}), while the outer conductor carries the remainder (I{sub 2}). An envelope equation appropriate for a hollow electron beam is derived and applied to the current divider. The force on the beam trajectory is shown to be proportional to (I{sub 2}-I{sub 1}), while the average force on the envelope (the beam width) is proportional to the beam current I{sub b} = (I{sub 2} + I{sub 1}). The values of I{sub 1} and I{sub 2} depend on the inductances in the return-current path geometries. Proper choice of the return-current geometries determines these inductances and offers control over the beam trajectory. Solutions using realistic beam parameters show that, for appropriate choices of the return-current-path geometry, the inductive current divider can produce a beam that is both pinched and straightened so that it approaches a target at near-normal incidence with a beam diameter that is on the order of a few mm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

PID self tuning control based on Mamdani fuzzy logic control for quadrotor stabilization

Quadrotor as one type of UAV have the ability to perform Vertical Take Off and Landing (VTOL). It allows the Quadrotor to be stationary hovering in the air. PID (Proportional Integral Derivative) control system is one of the control methods that are commonly used. It is usually used to optimize the Quadrotor stabilization at least based on the three Eulerian angles (roll, pitch, and yaw) as input parameters for the control system. The three constants of PID can be obtained in various methods. The simplest method is tuning manually. This method has several weaknesses. For example if the three constants are not exact, the resulting response will deviate from the desired result. By combining the methods of PID with fuzzy logic systems where human expertise is implemented into the machine language is expected to further optimize the control system.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

String instability mitigation of adaptive cruise control without modifying control laws: trajectory shaper and parameter estimation

Vehicle automation technologies equip vehicles with adaptive cruise control (ACC) systems, which relieve driving fatigue. However, recent studies have shown that the current ACC systems are string-unstable (i.e., exacerbate traffic congestion). To achieve string stability, most existing studies directly modify the control algorithms of ACC systems. Alternatively, this study proposes a trajectory shaper (TS)-based method, which only modifies the trajectory information of the predecessor vehicle, so that the ego vehicle driven by a string-unstable ACC system leverages the modified trajectory information to achieve string stability. To devise the TS-based method, an offline-online parameter estimation method integrating batch optimization and an extended Kalman filter is applied to estimate the parameters of an ACC system. The proposed TS-based method is cost-effective during implementation, as it avoids modifying existing ACC control algorithms (which entails a complex analysis of control systems and parameter tuning). In conclusion, the effectiveness of the proposed TS-based method is validated through extensive numerical experiments.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Enhancing strontium clock atom interferometry using quantum optimal control

Strontium clock atom interferometry is a promising new technology, with multiple experiments under development around the world to explore its potential for dark matter and gravitational wave detection. In these detectors, large momentum transfer using sequences of many laser pulses is necessary, and thus high-fidelity pulses are important since small errors become magnified. Quantum optimal control (QOC) is a framework for developing control pulse waveforms that achieve high fidelity and are robust against experimental imperfections. Resonant single-photon transitions using the narrow clock transition of strontium involve significantly different quantum dynamics than more established atom interferometry methods based on far-detuned two-photon Raman or Bragg transitions, which leads to new opportunities and challenges when applying QOC. Here, we study in simulation QOC pulses for strontium clock interferometry and demonstrate their advantage over basic square pulses (primitive pulses) and composite pulses in terms of robustness against multiple noise channels. In conclusion, this could improve the scale of large momentum transfer in Sr clock interferometers, paving the way to achieving these scientific goals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Reinforcement-Learning-Based Smart Water Heater Control: An Actual Deployment

Utilizing smart control algorithms for electric water heaters (EWHs) is essential for fully harnessing the demand response (DR) potential of EWHs. For this reason, the use of reinforcement learning (RL) algorithms for EWHs has received increasing attention in recent years. However, existing RL approaches are either simulation-based or use pretrained RL agents. To this end, this paper presents the real-world deployment of a set of model-free RL approaches that aim to minimize the electricity cost of a EWH under a time-of-use electricity pricing policy using standard DR commands (e.g., shed, load up). The experiment results showed that the RL agents can help save electricity cost in the range of 11% to 14% compared to the baseline operation. This study demonstrated that RL-based EWH controllers can be deployed in real world without any prior training and can still save electricity cost.

deep learning↗
DOE OSTI2015

Requirements for Control Room Computer-Based Procedures for use in Hybrid Control Rooms

Many plants in the U.S. are currently undergoing control room modernization. The main drivers for modernization are the aging and obsolescence of existing equipment, which typically results in a like-for-like replacement of analogue equipment with digital systems. However, the modernization efforts present an opportunity to employ advanced technology that would not only extend the life, but enhance the efficiency and cost competitiveness of nuclear power. Computer-based procedures (CBPs) are one example of near-term advanced technology that may provide enhanced efficiencies above and beyond like for like replacements of analog systems. Researchers in the LWRS program are investigating the benefits of advanced technologies such as CBPs, with the goal of assisting utilities in decision making during modernization projects. This report will describe the existing research on CBPs, discuss the unique issues related to using CBPs in hybrid control rooms (i.e., partially modernized analog control rooms), and define the requirements of CBPs for hybrid control rooms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Evaluation of fuel-borne sodium effects on a DOC-DPF-SCR heavy-duty engine emission control system: Simulation of full-useful life

Here we report that for renewable fuels to displace petroleum, they must be compatible with emissions control devices. Pure biodiesel contains up to 5 ppm Na + K and 5 ppm Ca + Mg metals, which have the potential to degrade diesel emissions control systems. This study aims to address these concerns, identify deactivation mechanisms, and determine if a lower limit is needed. Accelerated aging of a production exhaust system was conducted on an engine test stand over 1001 h using 20% biodiesel blended into ultra-low sulfur diesel (B20) doped with 14 ppm Na. This Na level is equivalent to exposure to Na at the uppermost expected B100 value in a B20 blend for the system full-useful life. During the study, NOx emissions exceeded the engine certification limit of 0.33 g/bhp-hr before the 435,000-mile requirement. Replacing aged diesel oxidation catalyst (DOC), diesel particulate filter (DPF), and selective catalytic reduction (SCR) devices with new degreened parts showed that each device contributed equally to the NOx increase. Following this systems-based evaluation, a detailed investigation of the individual components was completed. Na was determined to have minimal impact on DOC activity. For this system, it is estimated that B20-Na resulted in 50% more ash into the DPF. However, the Na did not diffuse into the cordierite DPF nor degrade its mechanical properties. The SCR degradation was found to be caused by a small amount of precious group metals (PGM) contamination that increased NH3 oxidation, and lowered NOx reduction. Therefore, we determined that the primary effect of Na in this study is through increased ash in the DPF rather than deactivation of the catalytic activity.

42 ENGINEERING↗
NASA NTRS1987

Irradiance and spectral distribution control system for controlled environment chambers

This paper describes a closed-loop control system for controlling the irradiance and spectral quality generated by fluorescent lamps in a controlled environment chamber. The 400 to 800 nm irradiance and the ratio of the red waveband (600 to 700 nm) to the far-red waveband (700 to 800 nm) were independently controlled and varied as functions of time. A suggested application is to investigate the possibility of synergistic effects of changing irradiance levels and changing spectral distributions on photoperiodism and photomorphogenesis.

NASA Center KSC↗
NASA NTRS2012

Lossless Convexification of Control Constraints for a Class of Nonlinear Optimal Control Problems

In this paper we consider a class of optimal control problems that have continuous-time nonlinear dynamics and nonconvex control constraints. We propose a convex relaxation of the nonconvex control constraints, and prove that the optimal solution to the relaxed problem is the globally optimal solution to the original problem with nonconvex control constraints. This lossless convexification enables a computationally simpler problem to be solved instead of the original problem. We demonstrate the approach in simulation with a planetary soft landing problem involving a nonlinear gravity field.

planetary soft landing↗
NASA NTRS2016

Propellantless Attitude Control of Solar Sail Technology Utilizing Reflective Control Devices

Solar sails offer an opportunity for a CubeSatscale, propellant-free spacecraft technology that enables long-term and long-distance missions not possible with traditional methods. Solar sails operate using the transfer of linear momentum from photons of sunlight reflected from the surface of the sail. To propel the spacecraft, no mechanically moving parts, thrusters, or propellant are needed. However, attitude control, or orientation, is still performed using traditional methods involving reaction wheels and propellant ejection, which severely limit mission lifetime. For example, the current state of the art solutions employed by upcoming missions couple solar sails with a state of the art propellant ejection gas system. Here, the use of the gas thruster has limited the lifetime of the mission. To solve the limited mission lifetime problem, the Propellantless Attitude Control of Solar Sail Technology Utilizing Reflective Control Devices project team is working on propellantless attitude control using thin layers of material, an optical film, electrically switchable from transparent to reflective. The technology is based on a polymer-dispersed liquid crystal (PDLC), which allows this switch upon application of a voltage. This technology removes the need for propellant, which reduces weight and cost while improving performance and lifetime.

Solar sail technology↗