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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

50 MW Segmented Ultralight Morphing Rotors for Wind Energy

A multi-institutional team designed a 50 Megawatt (MW) rated wind turbine featuring downwind aeroelastic morphing to reduce blade loads and allow an ultralight segmented rotor (mass reduction of about 25% compared to a conventional upwind rotor). The team used a control co-design approach with state-of-the art simulations including for the rotor and tower design using non-linear fluid-structure interactions and control algorithms, and the team also designed, built, and field-tested an aeroelastically-scaled downwind rotor to demonstrate this novel technology and validate the design tool fidelity. In a follow-on phase, these results were used along with an updated Levelized Cost Of Energy (LCOE) methodology to co-design a more detailed set of 25 MW rated turbine designs (including individual pitch control) based on minimum LCOE with highly flexible blades for an Atlantic Ocean offshore fixed-bottom design targeted towards market technology evaluation. A set of upwind and downwind designs at 25 MW rated scales were found to provide the best LCOE, with strong improvements over all previous offshore reference turbines (NREL 5MW, DTU 10 MW and IEA 15 MW). The optimized design would represent the world’s largest offshore turbine design, which combines several state-of-the-art structural, aerodynamic, and control technologies into a new and optimized system concept.

17 WIND ENERGY↗
DOE OSTI2020

Analysis of MHD stability and active mode control on KSTAR for high confinement, disruption-free plasma

Long-pulse plasma operation at high normalized beta, $β_N$, above the $\textit{n}$= 1 ideal MHD no-wall stability limit in KSTAR is presently limited by tearing instabilities rather than resistive wall modes. H-mode plasma operation during the recent KSTAR device campaign produced discharges having strong $\textit{m/n}$= 2/1 tearing instabilities at $β_N$ lower than the ideal MHD no-wall beta limit. The unstable tearing mode consequently reduced plasma confinement and toroidal plasma rotation significantly. We report the experiment confirmed that an extended duration of electron cyclotron heating (ECH) at the initial phase of the discharge plays a critical role in mode destabilization. To study destabilizing mechanisms that affect the mode growth, the stability of the observed tearing modes from plasmas with significantly different $β_N$ is computed by using the resistive DCON code and the M3D-C 1 code. Equilibrium reconstructions that include constraints from internal profile diagnostics, and computed fast particle pressure are used as input for reliable computation of stability. The classical tearing stability index, Δ', from resistive DCON is computed to be unstable when the island is fully saturated with large amplitude, while the unstable mode is not computed by M3D-C 1 . The modified Rutherford equation (MRE) describing the evolution of the island width has been constructed for KSTAR plasmas by using plasma parameters computed by the TRANSP code. The MRE model estimates a saturated island width corresponding to ~10% of the plasma minor radius for equilibrium at high $β_N$ 3 having a stable Δ' from the resistive DCON. In preparation for long-pulse plasma operation at higher beta utilizing increased plasma heating power, a resistive wall mode (RWM) active feedback control algorithm has been completed and enabled on KSTAR. To accurately determine the $\textit{n}$= 1component produced by RWMs, an algorithm has been developed that includes magnetic sensor compensation of the prompt applied field and the field from the induced current on the passive conductors. Use of multiple toroidal sensor arrays is enabled by modifying the sensor toroidal angles assumed in mode decomposition to include the effect of varied mode helicities in the outboard region where the mode measurement is made. This analysis on stability, transport, and control provides the required foundation for disruption prediction and avoidance research on KSTAR.

resistive wall mode (RWM)↗
NASA NTRS2015

Validation of an Integrated Airframe and Turbofan Engine Simulation for Evaluation of Propulsion Control Modes

The National Aeronautics and Space Administration (NASA) has developed independent airframe and engine models that have been integrated into a single real-time aircraft simulation for piloted evaluation of propulsion control algorithms. In order to have confidence in the results of these evaluations, the integrated simulation must be validated to demonstrate that its behavior is realistic and that it meets the appropriate Federal Aviation Administration (FAA) certification requirements for aircraft. The paper describes the test procedures and results, demonstrating that the integrated simulation generally meets the FAA requirements and is thus a valid testbed for evaluation of propulsion control modes.

aircraft engine simulation↗
NASA NTRS2015

Validation of an Integrated Airframe and Turbofan Engine Simulation for Evaluation of Propulsion Control Modes

The National Aeronautics and Space Administration (NASA) has developed independent airframe and engine models that have been integrated into a single real-time aircraft simulation for piloted evaluation of propulsion control algorithms. In order to have confidence in the results of these evaluations, the integrated simulation must be validated to demonstrate that its behavior is realistic and that it meets the appropriate Federal Aviation Administration (FAA) certification requirements for aircraft. The paper describes the test procedures and results, demonstrating that the integrated simulation generally meets the FAA requirements and is thus a valid testbed for evaluation of propulsion control modes.

aircraft engine simulation↗
DOE OSTI2019

Data-based Aggregate Model of Refrigerators for Electric Power Grid Services

Electrical power system stability under high penetration of intermittent renewable energy generation, such as wind and solar energy, has become a high concern. It is unpredictable and hard to control due to little inertial behavior characteristic to these generation resources. To help mitigate possibly undesirable frequency excursions, demand-side frequency control presents an emerging solution. By observing the frequency deviation, devices could switch operating modes for a short time to rebalance generation. To analyze device level control algorithms, aggregate models for their behavior are needed. Refrigerators are household devices that could help with load modulation. This paper uses real measured data to analyze the refrigerator behavior, learn about its operating mode and power consumption ranges. A Markov chain process is proposed to model the transition of a refrigerator population from one operating mode to another, such that the overall load is modulated according to the control input. The Markov-chain model can be used to design control so that the overall load is modulated according to the control input.

Markov chain model, demand response, refrigerator,↗
NASA NTRS1990

Automation in the Space Station module power management and distribution Breadboard

The Space Station Module Power Management and Distribution (SSM/PMAD) Breadboard, located at NASA's Marshall Space Flight Center (MSFC) in Huntsville, Alabama, models the power distribution within a Space Station Freedom Habitation or Laboratory module. Originally designed for 20 kHz ac power, the system is now being converted to high voltage dc power with power levels on a par with those expected for a space station module. In addition to the power distribution hardware, the system includes computer control through a hierarchy of processes. The lowest level process consists of fast, simple (from a computing standpoint) switchgear, capable of quickly safing the system. The next level consists of local load center processors called Lowest Level Processors (LLP's). These LLP's execute load scheduling, perform redundant switching, and shed loads which use more than scheduled power. The level above the LLP's contains a Communication and Algorithmic Controller (CAC) which coordinates communications with the highest level. Finally, at this highest level, three cooperating Artificial Intelligence (AI) systems manage load prioritization, load scheduling, load shedding, and fault recovery and management. The system provides an excellent venue for developing and examining advanced automation techniques. The current system and the plans for its future are examined.

Walls, Bryan↗
DOE OSTI2022

Traffic Signal Control With Adaptive Online-Learning Scheme Using Multiple-Model Neural Networks

This article proposes a new traffic signal control algorithm to deal with unknown-traffic-system uncertainties and reduce delays in vehicle travel time. Unknown-traffic-system dynamics are approximated using a recurrent neural network (NN). To accurately identify the traffic system model, an online-learning scheme is developed to switch among a set of candidate NNs (i.e., multiple-model NNs) based on their estimation errors. Then, a bank of optimal signal-timing controllers is designed based on the online identification of the traffic system. Simulation studies have been carried out for the obtained control strategies using multiple-model NNs, and the desired results have been obtained. Moreover, compared with the widely used actuated traffic signal control schemes, it is shown that the proposed method can reduce vehicle travel delays and improve traffic system robustness.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

An Edge-Cloud Integrated Solution for Buildings Demand Response Using Reinforcement Learning

Buildings, as major energy consumers, can provide great untapped demand response (DR) resources for grid services. However, their participation remains low in real-life. One major impediment for popularizing DR in buildings is the lack of cost-effective automation systems that can be widely adopted. Existing optimization-based smart building control algorithms suffer from high costs on both building-specific modeling and on-demand computing resources. To tackle these issues, this paper proposes a cost-effective edge-cloud integrated solution using reinforcement learning (RL). Beside RL’s ability to solve sequential optimal decision-making problems, its adaptability to easy-to-obtain building models and the off-line learning feature are likely to reduce the controller’s implementation cost. Using a surrogate building model learned automatically from building operation data, an RL agent learns an optimal control policy on cloud infrastructure, and the policy is then distributed to edge devices for execution. Simulation results demonstrate the control efficacy and the learning efficiency in buildings of different sizes. A preliminary cost analysis on a 4-zone commercial building shows the annual cost for optimal policy training is only 2.25% of the DR incentive received. Results of this study show a possible approach with higher return on investment for buildings to participate in DR programs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Microreactor Automated Control System Test Bed Digital Architecture for Real-Time, Hardware-in-the-Loop Simulation

This work describes progress made towards the development of a real-time hardware-in-the-loop (HIL) test bed for non-nuclear testing of microreactor control schemes and failure modes. Non-nuclear testing is a crucial step in developing robust control algorithms for managing microreactor dynamics. The creation of an HIL simulation harnesses the realistic dynamics of physical analogue systems while additionally considering the challenges of variable communication delay. This collaborative effort between Oak Ridge National Laboratory and Idaho National Laboratory has resulted in a LabVIEW-based gRPC communication protocol which couples a TRANSFORM Modelica simulation of nuclear components to the ViBRANT physical hardware for realistic feedback and visual representation of control action in real time. A modular python client structure is developed to manage FMU-based Modelica simulation and real-time gRPC communication. HIL testing suggests that the modeled reactor with natural convection molten salt loop coolant configuration responds well to PID control of drum positioning for modulation of reactor core power, however, future efforts will be made to explore the added thermal inertial delay of system level control and downstream demand changes. Development of this platform with a generalized methodology provides a foundation for exploring a variety of reactor configurations and failure modes in rapid order to provide insight into the most effective avenues of study for further research and development.

McConnell, Jono [ORNL] (ORCID:0000000238984741)↗
DOE OSTI2018

Completing the Connected Home with Smart Window Shades

Heat transfer through windows accounts for a significant percentage of a building’s energy use and adds substantially to the peak cooling load of a home. Window attachment manufacturers currently offer motorized shading devices for certain product lines, but this automation is typically marketed as a convenience and security feature for the homeowner and often does not include energy optimized control algorithms or dynamic and responsive features. This paper describes the experimental results of testing the energy performance of high-efficiency, dynamically operated, cellular shades in Pacific Northwest National Laboratory’s (PNNL) Lab Homes. The results of both heating and cooling season experiments will be presented, where testing is designed to assess the whole home energy savings resulting from both the thermal insulating properties as well as the automated and dynamic control strategies of shading devices. Control schemes tested include common “connected home” strategies where controls are integrated and coordinated between the window shading device, building thermostats, and external sensors. The presentation will also include results from testing designed to examine the benefits (in terms of comfort, energy savings, and responsiveness) of coordinating the operation of cellular shades with HVAC as a demand-response measure. These experiments demonstrate that highly insulating, dynamic window coverings that are reliably controlled can dramatically reduce the heating and cooling energy associated with windows and should be considered an important component of any “smart” home design.

energy savings, cellular shades, honeycomb shades,↗
NASA NTRS1979

Algorithms for the Automated Power Systems Management

The system breadboard for the demonstration of Automated Power Systems Management (APSM) functions has been designed, fabricated, and is in the final stages of verification and testing. APSM functions fall into categories of fault detection and correction, commanding system and subsystem test and diagnoses, relay position monitoring, data acquisition and processing, and power management. All these functions are accomplished through software residing in 8-bit microprocessors dedicated to each group of Viking Orbiter power breadboard subassemblies and a 16-bit microprocessor serving as the central processor for the power system. This paper describes key monitoring, diagnostic, and control algorithms used in the APSM breadboard.

Moser, R. L.↗
NASA NTRS2003

Neural Flight Control System

The Neural Flight Control System (NFCS) was developed to address the need for control systems that can be produced and tested at lower cost, easily adapted to prototype vehicles and for flight systems that can accommodate damaged control surfaces or changes to aircraft stability and control characteristics resulting from failures or accidents. NFCS utilizes on a neural network-based flight control algorithm which automatically compensates for a broad spectrum of unanticipated damage or failures of an aircraft in flight. Pilot stick and rudder pedal inputs are fed into a reference model which produces pitch, roll and yaw rate commands. The reference model frequencies and gains can be set to provide handling quality characteristics suitable for the aircraft of interest. The rate commands are used in conjunction with estimates of the aircraft s stability and control (S&C) derivatives by a simplified Dynamic Inverse controller to produce virtual elevator, aileron and rudder commands. These virtual surface deflection commands are optimally distributed across the aircraft s available control surfaces using linear programming theory. Sensor data is compared with the reference model rate commands to produce an error signal. A Proportional/Integral (PI) error controller "winds up" on the error signal and adds an augmented command to the reference model output with the effect of zeroing the error signal. In order to provide more consistent handling qualities for the pilot, neural networks learn the behavior of the error controller and add in the augmented command before the integrator winds up. In the case of damage sufficient to affect the handling qualities of the aircraft, an Adaptive Critic is utilized to reduce the reference model frequencies and gains to stay within a flyable envelope of the aircraft.

Gundy-Burlet, Karen↗
DOE OSTI2022

Inverse Calculation of Burden Distribution Matrix Using B-spline Model Based PDF control in Blast Furnace Burden Charging Process

The inverse calculation of burden distribution matrix (BDM) is one of the most important challenges in the blast furnace operation in iron-making processes. In general, blast furnace consumes 65% of the total energy for the whole steel-making. Focusing on this practical challenge, this article proposes a new burden distribution spatial model in calculating burden charging process, and develops a B-spline approximation-based probability density function (PDF) control algorithm to assign the expected thickness distribution of burden layer and, thus, develops a new method for the required inverse calculation of BDM. First, a novel method for the thickness distribution of burden layer is given using B-spline model to produce an expected distribution shape subjected to a desired tracking within a specific spatial constraint. Then, according to the coexistence of continuous and bounded discrete variables in BDM, a novel hybrid optimization control method by combining integer programming and PDF tracking is further established for the effective inverse calculation of BDM. Finally, the proposed PDF-based iterative inverse calculation of BDM using B-spline models are tested using various data from industrial examples. Furthermore, the simulation results show that the proposed method is well suited to solve the BDM inverse calculation problem in practice.

42 ENGINEERING↗
DOE OSTI2024

Active Aerodynamic Load Control for Wind Turbines

The goal of this project was to develop and demonstrate an advanced dielectric barrier discharge (DBD) plasma actuator technology. We set out to demonstrate the efficacy and impact of the new actuator technology as a key component of an active load control system for wind turbines. A DBD plasma actuator consists of a thin layer of dielectric material separating a pair of offset electrodes. One of those electrodes is embedded between the dielectric layer and a non-conductive substrate, while the other is exposed to air. When driven by an appropriate high voltage waveform, the device ionizes the air near the surface of the dielectric and adjacent to the exposed electrode. Collisions between the ions in the plasma and neutral air molecules result in a wall-jet – a region of induced air velocity that can be used to modify the flow around a lifting body. Use of the device near the trailing edge of a wind turbine blade, designed in such a way as to amplify the effects of the flow-modifying device, can result in large changes to the global forces experienced by the blade. Because of the fast response time of the device, it can allow the turbine to react in real time to changes in the wind associated with turbulence, wind shear, gusts, and the like, when paired with appropriate sensors and control algorithms. The goal of this project was to increase the capacity of the device to induce velocity on its surface at the levels required by large, utility-scale wind turbines. The first technical goal was to increase the induced velocity from the current industry-best of about 4 m/s to 10 m/s by modifying the electrical waveform used to drive the device and by introducing a semi-conductive surface coating to control electrostatic charge build-up on the surface. The second goal was to use the device to modify the lift on a representative airfoil in a wind tunnel, demonstrating a reduction in lift coefficient of 0.2 or better. The third goal was to produce an actuator-induced velocity of 20 m/s. Alongside our partners at the University of Texas at Dallas, we also applied modern, advanced design methods to optimize the impact of the technology on the design of wind turbines. We also had planned to install a segmented, active load control system on a test turbine to demonstrate the ability to reduce unsteady aerodynamic forces on the turbine associated with changes in the wind. The highest induced velocity achieved during this research was 11 m/s. However, practical design constraints limited the change in lift coefficient to about 0.12 for a representative airfoil in the wind tunnel at a Reynolds number of 400,000. The primary conclusion is that the plasma actuator control authority remains insufficient for practical purposes when extrapolated to Reynolds numbers over 1 million. The potential impact of the active lift control concept was evaluated through detailed simulations for three wind turbine sizes: a 3.4MW onshore turbine, a 10MW offshore turbine, and a 15MW offshore turbine. A feedback control system was designed for each turbine within two scenarios: one where the active lift control is used as a retrofit capability on the baseline design, and the other where the designers were permitted to “upscale” the turbines in order increase annual energy production. The levelized cost of energy was then evaluated for the range of turbine sizes and design configuration. It was found that the LCOE reduction associated with active lift control fell in the range of 0.7% to 7.2%, with the highest reduction associated with upscaling the 3.4MW turbine.

17 WIND ENERGY↗
DOE OSTI2018

Narrowing Frequency Probability Density Function for Achieving Minimized Uncertainties in Power Systems Operation – a Stochastic Distribution Control Perspective

With the increased penetration of renewables and other distributed energy resources (DERs), the frequency response in power systems exhibits stochastic nature, where the standard deterministic swing equation should be either represented or transferred into an Ito stochastic differential equation whose solution should be the non-stationary transient behavior of the probability density function (PDF) of the frequency. This transfers the frequency quality control for power systems into a stochastic distribution control problem, where the shape of the frequency distribution, namely the frequency PDF, needs to be directly controlled. In this context, this requires the development of control strategies via controlling the power balance so that the PDF of the frequency is made as narrow as possible whilst centered at its required mean value simple because such a sharp distribution shape means less uncertainties or randomness for the frequency response. In this paper, the formulation of the stochastic swing equation will be made first taking into account of DERs. This will then be followed by the development of stochastic distribution control model that links the power sources with the PDF of the frequency using Fokker Planck Kolmogorov (FPK) equations. A generic constrained optimization problem will be formulated where the cost function is composed of a functional distance between the actual and the desired PDFs of the frequency. A feasible solution using B-spine Neural Networks based stochastic distribution control model will be described. Using the obtained stochastic distribution control model, a set of control algorithms will be described that uses available power sources to shape the PDF of the frequency or to minimize the randomness of the frequency via minimized entropy approach. Future directions will be discussed in the later part of the paper

Swing equation, Power Systems, stchastic distribut↗
NASA NTRS2015

Use of a Closed-Loop Tracking Algorithm for Orientation Bias Determination of an S-Band Ground Station

The Space Communications and Navigation (SCaN) Testbed project completed installation and checkout testing of a new S-Band ground station at the NASA Glenn Research Center in Cleveland, Ohio in 2015. As with all ground stations, a key alignment process must be conducted to obtain offset angles in azimuth (AZ) and elevation (EL). In telescopes with AZ-EL gimbals, this is normally done with a two-star alignment process, where telescope-based pointing vectors are derived from catalogued locations with the AZ-EL bias angles derived from the pointing vector difference. For an antenna, the process is complicated without an optical asset. For the present study, the solution was to utilize the gimbal control algorithms closed-loop tracking capability to acquire the peak received power signal automatically from two distinct NASA Tracking and Data Relay Satellite (TDRS) spacecraft, without a human making the pointing adjustments. Briefly, the TDRS satellite acts as a simulated optical source and the alignment process proceeds exactly the same way as a one-star alignment. The data reduction process, which will be discussed in the paper, results in two bias angles which are retained for future pointing determination. Finally, the paper compares the test results and provides lessons learned from the activity.

ground station↗
NASA NTRS2015

Use of a Closed-Loop Tracking Algorithm for Orientation Bias Determination of an S-Band Ground Station

The Space Communications and Navigation (SCaN) Testbed project completed installation and checkout testing of a new S-Band ground station at the NASA Glenn Research Center in Cleveland, Ohio in 2015. As with all ground stations, a key alignment process must be conducted to obtain offset angles in azimuth (AZ) and elevation (EL). In telescopes with AZ-EL gimbals, this is normally done with a two-star alignment process, where telescope-based pointing vectors are derived from catalogued locations with the AZ-EL bias angles derived from the pointing vector difference. For an antenna, the process is complicated without an optical asset. For the present study, the solution was to utilize the gimbal control algorithms closed-loop tracking capability to acquire the peak received power signal automatically from two distinct NASA Tracking and Data Relay Satellite (TDRS) spacecraft, without a human making the pointing adjustments. Briefly, the TDRS satellite acts as a simulated optical source and the alignment process proceeds exactly the same way as a one-star alignment. The data reduction process, which will be discussed in the paper, results in two bias angles which are retained for future pointing determination. Finally, the paper compares the test results and provides lessons learned from the activity.

reflector antenna↗
DOE OSTI2021

Influence of Fuel Properties on Gasoline Direct Injection Particulate Matter Emissions Over First 200 s of World-Harmonized Light-Duty Test Procedure Using an Engine Dynamometer and Novel “Virtual Drivetrain” Software

Abstract The influence of fuel properties on particulate matter (PM) emissions from a catalytic gasoline particulate filter (GPF) equipped gasoline direct injection (GDI) engine was investigated using novel “virtual drivetrain” software and an engine mated to an engine dynamometer. The virtual drivetrain software was developed in labview to operate the engine on an engine dynamometer as if it were in a vehicle undergoing a driving cycle. The software uses a physics-based approach to determine vehicle acceleration and speed based on engine load and a programed “shift” schedule to control engine speed. The software uses a control algorithm to modulate engine load and braking to match a calculated vehicle speed with the prescribed speed trace of the driving cycle of choice. The first 200 s of the World-harmonized Light-duty Test Procedure (WLTP) driving cycle was tested using six different fuel formulations of varying volatility, aromaticity, and ethanol concentration. The first 200 s of the WLTP was chosen as the test condition because it is the most problematic section of the driving cycle for controlling PM emissions due to the cold start and cold drive off. It was found that there was a strong correlation between aromaticity of the fuel and the engine-out PM emissions, with the highest emitting fuel producing more than double the mass emissions of the low PM production fuel. However, the post-GPF PM emissions depended greatly on the soot loading state of the GPF. The fuel with the highest engine-out PM emissions produced comparable post-GPF emissions to the lowest PM producing fuel over the driving cycle when the GPF was loaded over three cycles with the respective fuels. These results demonstrate the importance of GPF loading state when aftertreatment systems are used for PM reduction. It also shows that GPF control may be more important than fuel properties, and that regulatory compliance for PM can be achieved with proper GPF control calibration irrespective of fuel type.

Energy & Fuels↗