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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
NASA NTRS1978

Design of a compensation for an ARMA model of a discrete time system

The design of an optimal dynamic compensator for a multivariable discrete time system is studied. Also the design of compensators to achieve minimum variance control strategies for single input single output systems is analyzed. In the first problem the initial conditions of the plant are random variables with known first and second order moments, and the cost is the expected value of the standard cost, quadratic in the states and controls. The compensator is based on the minimum order Luenberger observer and it is found optimally by minimizing a performance index. Necessary and sufficient conditions for optimality of the compensator are derived. The second problem is solved in three different ways; two of them working directly in the frequency domain and one working in the time domain. The first and second order moments of the initial conditions are irrelevant to the solution. Necessary and sufficient conditions are derived for the compensator to minimize the variance of the output.

Mainemer, C. I.↗
NASA NTRS2011

Numerical Investigation of Rotorcraft Fuselage Drag Reduction Using Active Flow Control

The effectiveness of unsteady zero-net-mass-flux jets for fuselage drag reduction was evaluated numerically on a generic rotorcraft fuselage in forward flight with a rotor. Previous efforts have shown significant fuselage drag reduction using flow control for an isolated fuselage by experiment and numerical simulation. This work will evaluate a flow control strategy, that was originally developed on an isolated fuselage, in a more relevant environment that includes the effects of a rotor. Evaluation of different slot heights and jet velocity ratios were performed. Direct comparisons between an isolated fuselage and rotor/fuselage simulations were made showing similar flow control performance at a -3deg fuselage angle-of-attack condition. However, this was not the case for a -5deg angle-of-attack condition where the performance between the isolated fuselage and rotor/fuselage were different. The fuselage flow control resulted in a 17% drag reduction for a peak C(sub mu) of 0.0069 in a forward flight simulation where mu = 0:35 and CT/sigma = 0:08. The CFD flow control results also predicted a favorable 22% reduction of the fuselage download at this same condition, which can have beneficial compounding effects on the overall performance of the vehicle. This numerical investigation was performed in order to provide guidance for a future 1/3 scale wind tunnel experiment to be performed at the NASA 14-by 22-Foot Subsonic Tunnel.

Allan, Brian G.↗
NASA NTRS2016

Why Do Models Overestimate Surface Ozone in the Southeast United States?

Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NO(x) triple bond NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC(exp 4)RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25 deg x 0.3125 deg horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NO(x) from the US Environmental Protection Agency (EPA) is too high. This finding is based on SEAC(exp 4)RS observations of NO(x) and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO2 columns. Our results indicate that NEI NO(x) emissions from mobile and industrial sources must be reduced by 30-60%, dependent on the assumption of the contribution by soil NO(x) emissions. Upper-tropospheric NO2 from lightning makes a large contribution to satellite observations of tropospheric NO2 that must be accounted for when using these data to estimate surface NO(x) emissions. We find that only half of isoprene oxidation proceeds by the high-NO(x) pathway to produce ozone; this fraction is only moderately sensitive to changes in NO(x) emissions because isoprene and NO(x) emissions are spatially segregated. GEOS-Chem with reduced NO(x) emissions provides an unbiased simulation of ozone observations from the aircraft and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NO(x) oxidation products. However, the model is still biased high by 6 plus or minus 14 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This bias may reflect a combination of excessive vertical mixing and net ozone production in the model boundary layer.

Oxidation↗
NASA NTRS2016

Transition Delay in Hypersonic Boundary Layers via Optimal Perturbations

The effect of nonlinear optimal streaks on disturbance growth in a Mach 6 axisymmetric flow over a 7deg half-angle cone is investigated in an e ort to expand the range of available techniques for transition control. Plane-marching parabolized stability equations are used to characterize the boundary layer instability in the presence of azimuthally periodic streaks. The streaks are observed to stabilize nominally planar Mack mode instabilities, although oblique Mack mode disturbances are destabilized. Experimentally measured transition onset in the absence of any streaks correlates with an amplification factor of N = 6 for the planar Mack modes. For high enough streak amplitudes, the transition threshold of N = 6 is not reached by the Mack mode instabilities within the length of the cone, but subharmonic first mode instabilities, which are destabilized by the presence of the streaks, reach N = 6 near the end of the cone. These results suggest a passive flow control strategy of using micro vortex generators to induce streaks that would delay transition in hypersonic boundary layers.

Boundary layer transition↗
NASA NTRSDate not supplied

Enhancement of an Electrified Tilt-Wing Propulsion System using Turbine Electrified Energy Management

Hybrid gas-electric aircraft propulsion architectures provide flexibility in the way that power and energy is managed when compared to their traditional pure-gas counterparts. In this paper, investigations are conducted for the impact this added flexibility has on the operability of turbomachinery. Specifically, the Turbine Electrified Energy Management (TEEM) concept is applied. It takes a controls approach to improving operability of the turbomachinery by utilizing electric hardware. In this paper, TEEM is applied to a propulsion system for a 15 passenger vertical lift concept vehicle. This is the first application of TEEM to a turbine engine that generates power. The study establishes TEEM as being applicable to this smaller thrust/power class of air transportation vehicle and explore show power can be otherwise managed in the propulsion system to benefit the aircraft. The simulation study demonstrates significant improvements in transient operability that expands the engine design space to enable a more efficient and lighter-weight engine design. Simulation results also demonstrate tighter regulation of the power turbine and rotor speeds, a slight decrease in bulk fuel burn, and an increase in the maximum thrust of ~7%. This is achieved through the power management control strategy and modestly sized electric machines with re-usable energy storage.

Turbine Electrified Energy Management↗
DOE OSTI2020

Antibody dynamics to SARS‐CoV‐2 in asymptomatic COVID‐19 infections

Abstract Background The missing asymptomatic COVID‐19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic. Measure Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty‐three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS‐CoV‐2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset. Results A combination test of NAT and serological testing for IgM antibody discovered 55.5% of the total of 63 asymptomatic infections, which significantly raises the detection sensitivity when compared with the NAT alone (19%). Serum proteome microarray analysis demonstrated that asymptomatics mainly produced IgM and IgG antibodies against S1 and N proteins out of 20 proteins of SARS‐CoV‐2. Different from strong and persistent N‐specific antibodies, S1‐specific IgM responses, which evolved in asymptomatic individuals as early as the seventh day after exposure, peaked on days from 17 days to 25 days, and then disappeared in two months, might be used as an early diagnostic biomarker. 11.8% (6/51) mild patients and 38.1% (24/63) asymptomatic individuals did not produce neutralizing antibody. In particular, neutralizing antibody in asymptomatics gradually vanished in two months. Conclusion Our findings might have important implications for the definition of asymptomatic COVID‐19 infections, diagnosis, serological survey, public health, and immunization strategies.

Lei, Qing↗
DOE OSTI2022

Toward control co-design of utility-scale wind turbines: Collective vs. individual blade pitch control

A large-eddy simulation framework has been coupled with controller modules to systematically investigate the impacts of collective (CPC) and individual (IPC) pitch control strategies on utility-scale wind turbine energy production and fatigue loads. Wind turbine components were parameterized using an actuator surface model to simulate the rotor blades and the turbine nacelle. The baseline CPC and IPC algorithms, consisting of single-input single-output proportional–integral controllers and two integral controllers, respectively, were incorporated into the numerical framework. A series of simulations were carried out to investigate the relative performance of the two controllers under various turbulent inflow conditions, spanning hub-height velocities of 7 to 14 m/s. The numerical simulation results of this study showed that, in comparison to the CPC, the IPC controller could successfully reduce the damage equivalent loads of utility-scale turbines at regions 2 and 3 of turbine operation by about 3% and 40%, respectively, without any penalty on the power production of the turbine. It was also shown that, despite its minor impact on the turbulence kinetic energy of the wake, the IPC controller did not influence the recovery of the turbine wake.

17 WIND ENERGY↗
DOE OSTI2024

Model Quality and Measurement Density Impact on Volt/Volt Ampere Reactive Optimization Performance

The operation of the utility grid is being reshaped by the continuous addition of distributed energy resources and advanced metering infrastructure, which challenge existing grid control strategies. Some utilities deploy advanced distribution management systems (ADMS) to assist with the consolidation of various applications and to augment situational awareness in response to the new power delivery dynamics. An ADMS is an integrated software platform that provides utilities with a way to enhance their reliability, control, and optimization with advanced applications, such as volt/VAR optimization (VVO). A VVO application could serve as a vehicle to deliver cost savings by providing the utility with a method to reduce rates by controlling the voltage and decreasing the energy usage in their service territory. Some utilities are reluctant to integrate an ADMS, because it is a significant investment that requires approval from the public regulatory commission and/or their customers. This paper evaluates the impact on VVO performance when using a lower-quality network model supplemented with additional measurements, which could provide an implementation for cost savings. The results show that a better model quality would provide the highest energy savings; however, some level of telemetry is necessary in all scenarios to prevent voltage exceedances.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

Minimum fuel spacecraft reorientation

Fuel optimal solutions for the reorientation of an inertially symmetric rigid spacecraft with independent 3-axes controls are investigated. All possible optimal control strategies are identified. These include bangbang solutions, finite order singular arcs and infinite order singular arcs. Higher order necessary conditions for optimality of finite order singular arcs are presented. Numerical examples of fuel optimal solutions with fixed maneuver time are presented involving all of the theoretically possible control logics.

Seywald, H.↗
NASA NTRS1994

Preliminary test results from the CELSS Test Facility Engineering Development Unit

As part of the NASA Controlled Ecological Life Support System (CELSS) Program, a CELSS Test Facility (CTF) is being planned for installation on the Space Station. The CTF will be used to provide data on the productivity and efficiency of a variety of CELSS higher plant crops grown in the microgravity environment of the Space Station. Tight environmental control will be maintained while data on gas exchange rates and biomass accumulation rates are collected. In order to obtain an early realistic determination of the subsystem and system requirements necessary to provide the environmental conditions specified for CTF crop productivity experiments, an Engineering Development Unit (EDU) has been designed, constructed and is in the process of subsystem and system testing at NASA Ames Research Center. The EDU is a ground test-bed which will be used to characterize the integrated performance of major subsystem technologies, to evaluate hardware candidates and control strategies required for the CTF, and to further define the ability to meet CTF requirements within present Space Station constraints. This paper reviews the functional requirements for the EDU, and focuses on the performance evaluation and test results of the various subsystems. Preliminary integrated performance results and control system operation are addressed, and plans for future science and technology testing are discussed.

Kliss, Mark H.↗
NASA NTRS2003

First Results from a Hardware-in-the-Loop Demonstration of Closed-Loop Autonomous Formation Flying

A closed-loop system for the demonstration of formation flying technologies has been developed at NASA s Goddard Space Flight Center. Making use of a GPS signal simulator with a dual radio frequency outlet, the system includes two GPS space receivers as well as a powerful onboard navigation processor dedicated to the GPS-based guidance, navigation, and control of a satellite formation in real-time. The closed-loop system allows realistic simulations of autonomous formation flying scenarios, enabling research in the fields of tracking and orbit control strategies for a wide range of applications. A sample scenario has been set up where the autonomous transition of a satellite formation from an initial along-track separation of 800 m to a final distance of 100 m has been demonstrated. As a result, a typical control accuracy of about 5 m has been achieved which proves the applicability of autonomous formation flying techniques to formations of satellites as close as 50 m.

Gill, E.↗
DOE OSTI2020

Field Validation of Wake Steering Control with Wind Direction Variability

Wake steering is a wind farm control strategy wherein upstream turbines are misaligned with the wind direction to redirect their wakes away from downstream turbines, increasing overall wind plant power. Wake steering is often analyzed assuming steady mean wind directions across the wind farm. However, in practice, the wind direction varies considerably over time because of large-scale weather phenomena. Wind direction variability causes the increase in power production from wake-steering to be less than predicted by steady-state models, but more robust wake-steering strategies can be designed that account for variable wind conditions. This paper compares the achieved yaw offsets and power gains from two different 2-turbine wake-steering experiments at a commercial wind farm with model predictions using the FLOw Redirection and Induction in Steady State (FLORIS) control-oriented model, assuming both fixed and variable wind directions. The impact of wind direction variability is modeled by including wind direction and yaw uncertainty in the FLORIS calculations. The field results match the trends predicted, assuming wind direction variability. Specifically, the yaw offsets achieved in the intended control regions are lower than desired, resulting in less power gain, while a slight loss in power occurs for wind directions outside of the intended control region because of unintentional yaw misalignment. The agreement between the model and field results suggests that the wind direction variability model can be used to design wake-steering controllers that are more robust to variable wind conditions present in the field.

17 WIND ENERGY↗
DOE OSTI2020

Development of Real-Time System Identification to Detect Abnormal Operations in a Gas Turbine Cycle

Here, we present a novel online system identification methodology for monitoring the performance of power systems. This methodology was demonstrated in a gas turbine recuperated power plant designed for a hybrid configuration. A 120-kW Garrett microturbine modified to test dynamic control strategies for hybrid power systems designed at the National Energy Technology Laboratory (NETL) was used to implement and validate this online system identification methodology. The main component of this methodology consists of an empirical transfer function model implemented in parallel to the turbine speed operation and the fuel control valve, which can monitor the process response of the gas turbine system while it is operating. During fully closed-loop operations or automated control, the output of the controller, fuel valve position, and the turbine speed measurements were fed for a given period of time to a recursive algorithm that determined the transfer function parameters during the nominal condition. After the new parameters were calculated, they were fed into the transfer function model for online prediction. The turbine speed measurement was compared against the transfer function prediction, and a control logic was implemented to capture when the system operated at nominal or abnormal conditions. To validate the ability to detect abnormal conditions during dynamic operations, drifting in the performance of the gas turbine system was evaluated. A leak in the turbomachinery working fluid was emulated by bleeding 10% of the airflow from the compressor discharge to the atmosphere, and electrical load steps were performed before and after the leak. This tool could detect the leak 7 s after it had occurred, which accounted for a fuel flow increase of approximately 15.8% to maintain the same load and constant turbine speed operations.

algorithms↗
NASA NTRS1991

Optimal aircraft performance during microburst encounter

The effects of microburst characteristics on the optimal penetration performance of jet transport and general aviation aircraft are presented. The purpose is to determine the best possible performance that can be achieved in a broad range of microbursts. A secondary goal is to illustrate good strategies for dealing with a range of microbursts during takeoff and landing. Over 1100 optimal trajectories were computed for two aircraft types flying through idealized microbursts using a Successive Quadratic Programs trajectory optimization algorithm. Contours of safety metrics are plotted as functions of the length scales, magnitudes, and locations of horizontal wind shears and vertical downdrafts. These performance contours show three length-scale regimes for optimal microburst penetration. At short length scales, hazards usually associated with gustiness predominate (e.g., high normal load factor, rotational upset). At intermediate length scales, a degraded ability to maintain flight path and/or vertical velocity poses the most serious threat. At very long microburst length scales, excessive touchdown velocities may result. The ability to transit a microburst successfully also varies strongly with microburst location. The results show that both aircraft types could penetrate some very severe microbursts if optimal control histories were followed. Nevertheless, these control strategies assume perfect prior knowledge of the wind, and practical limits to successful encounter with real-time control capabilities would be lower. The optimally controlled jet transport can successfully penetrate higher intensity microbursts than can the general aviation aircraft.

Psiaki, Mark L.↗
DOE OSTI2021

Coordinated Optimal Control of PV Inverters and HVAC Loads in Distribution Systems

The increasing integration of distributed energy resources (DERs), such as photovoltaics (PVs) and smart buildings into distribution systems complicate power system operation and controls. This paper proposes a coordinated optimal control strategy for PV inverters and Heating, ventilation, and air conditioning (HVAC) loads in smart buildings to minimize the total network loss in a distribution system. For the HVAC units, we enforce minimum on and off time constraints to avoid frequent switching that can degrade the unit. The proposed control will dispatch optimal control signals of active and reactive power to PV inverters and on/off commands to HVAC units while maintaining the nodal voltage within a secure range and the temperature of HVAC units at a comfort level. The simulation results on a modified IEEE 33-node distribution system demonstrate that the proposed coordinated control scheme can reduce the network loss.

Pani, Naveen↗
DOE OSTI2023

Bayesian filtering for model predictive control of stochastic gene expression in single cells

This study describes a method for controlling the production of protein in individual cells using stochastic models of gene expression. By combining modern microscopy platforms with optogenetic gene expression, experimentalists are able to accurately apply light to individual cells, which can induce protein production. Here we use a finite state projection based stochastic model of gene expression, along with Bayesian state estimation to control protein copy numbers within individual cells. We compare this method to previous methods that use population based approaches. We also demonstrate the ability of this control strategy to ameliorate discrepancies between the predictions of a deterministic model and stochastic switching system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Hardware-in-the-Loop Evaluation for Potential High Limit Estimation-Based PV Plant Active Control

This paper validates the efficacy of an artificial intelligence (AI)-based photovoltaic (PV) plant control and optimization approach in enabling PV plants as accountable grid reliability service providers. The validation is performed in a realistic laboratory controller-hardware-in-the-loop environment, leveraging accurate PV plant modeling and standard industrial communication protocols. Through simulations that account for diverse weather conditions and active control scenarios, the results highlight the superior performance of the AI-based solution in comparison to a state-of-the-art reference-control grouping-based approach. Such a finding contributes to mitigating the risk of overcurtailment and uninstructed deviations of active PV plant controls, and offers practical guidance for its field deployment. Furthermore, it establishes a standardized testing framework for comparing various PV active control strategies.

hardware-in-the-loop↗
DOE OSTI2024

Hardware-in-the-Loop Evaluation for Potential High Limit Estimation-Based PV Plant Active Control: Preprint

This paper validates the effectiveness of an Artificial Intelligence (AI)-driven PV plant control and optimization approach, namely, the Automated Learner for Intermittency Control by Extrapolation (ALICE), in empowering PV plant as a dependable grid reliability service provider. The validation is performed in a realistic laboratory controller-hardware-in-the-loop (CHIL) environment, leveraging accurate PV plant modeling and standard industrial communication protocol. Simulation results, considering both varying weather conditions and active control scenarios, demonstrate the superior performance of ALICE in improving the grid service delivery precision and reducing the over-curtailment compared to a state-of-the-art approach, i.e., reference-control grouping based approach. Such a work could help mitigate risks and provide practical guidance during the field deployment of ALICE, while establishing a standardized testing framework for evaluating various PV active control strategies.

hardware-in-the-loop↗