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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Application of Artificial Neural Network Model for Optimized Control of Condenser Water Temperature Set-Point in a Chilled Water System

Here, in this study, real-time predictive control and optimization model based on an ANN (artificial neural network) was developed to evaluate the cooling energy saving performance of the optimized control of CndWT (condenser water temperature). For this purpose, the difference in TCEC (total cooling energy consumption) between the conventional control strategy when the CndWT produced by the cooling tower is fixed and the optimized control strategy when real-time control of the CndWT through the optimal ANN model is applied was compared and analyzed. For the modeling of the building to be simulated, the co-simulation of EnergyPlus and MATLAB was built through the middleware Building Controls Virtual Test Bed. For the prediction of TCEC, an ANN model was developed through MATLAB's neural network toolbox. The model accuracy of the ANN was examined through Cv(RMSE) index and as a result, Cv(RMSE) of the optimized ANN model turned out to be approximately 25 %. More importantly, the predictive control technique was able to save TCEC by 5.6 % compared to the conventional control method constantly fixing CndWT set-point to 30 °C. These results showed that the CndWT needs to be dynamically controlled using artificial intelligence technique such as ANN model and that significant energy savings were achievable compared to the conventional fixed control.

42 ENGINEERING↗
DOE OSTI2024

Developing a Control Strategy for Minimum Airflow Setting Considering CO2 Level and Energy Consumption in a Variable Air Volume System

In an office building equipped with a Variable Air Volume (VAV) system, this paper introduces a novel method for controlling the minimum supply airflow fraction in each zone’s VAV box, having a capability to consider indoor CO2 level and energy consumption. The EnergyPlus simulation using the medium office prototype model was employed, which evaluated the performance of the energy and CO2 concentration for five VAV box airflow control strategies. The paper focuses on CO2 concentration-based airflow control method and compares it with other four methods including conventional single-max, reduced minimum single-max, demand-controlled ventilation(DCV), and dualmax control methods according to guidelines and common practices. The newly proposed control strategy directly correlates the minimum airflow fraction to CO2 concentration. A general trend emerged when comparing CO2 concentrations—lower minimum airflow fractions were associated with higher concentrations. The proposed control method effectively maintained low CO2 concentrations and enabled a lower airflow fraction contributing to energy consumption reduction. It was confirmed that heating energy consumption in climate zone 4A, 5B, and 6A showed a maximum saving of approximately 30% compared to the conventional single-max and dual max control strategies. It was found that cooling energy consumption in climate zone 4A and 6A can achieve a maximum saving of approximately 10% compared to the conventional control strategies. The proposed CO2 concentration-based control logic is promising as it not only improves the indoor air quality lowering the CO2 concentration in the occupied spaces, but also contributes to HVAC energy savings.

Lee, Jong Man↗
DOE OSTI2021

Deep Learning Explicit Differentiable Predictive Control Laws for Buildings

We present a differentiable predictive control (DPC) methodology for learning constrained control laws for unknown nonlinear systems. DPC poses an approximate solution to multiparametric programming problems emerging from explicit nonlinear model predictive control (MPC). Contrary to approximate MPC, DPC does not require supervision by an expert controller. Instead, a system dynamics model is learned from a small dataset of recorded observations of the perturbed system's dynamics and the control law is optimized offline by interaction with the learned system model. The DPC method is based on two sequential steps, i) system identification using a constrained neural state-space model, and ii) optimization of an explicit control law parametrized by another neural network in closed-loop simulation with the identified neural state-space model. The combination of a differentiable closed-loop system and penalty methods for constraint handling of system outputs and inputs allows us to optimize the control law's parameters directly by backpropagating economic MPC loss through the learned system model. By incorporating domain knowledge and leveraging established techniques from optimal control, our method leverages deep neural networks as nonlinear function approximators for system identification and control while avoiding concomitant costs of intractably large datasets, and computationally expensive over-parametrized models. The scalability, data efficiency, and constrained optimal control capability of the proposed DPC method are demonstrated in simulation using a multi-zone building emulator.

Drgona, Jan↗
DOE OSTI2021

Modeling active control of resistive wall mode with power saturation and sensor noise on HL-2M

The resistive wall mode (RWM) control on the HL-2M tokamak is simulated with the MARS-F code (Liu et al 2000 Phys. Plasmas 7 3681), aiming at quantifying control current and voltage requirements when more realistic issues are taken into account, i.e. the control power saturation and the sensor signal noise. The fluid model predicts a narrow stability region for the n = 1 RWM without magnetic feedback, in the 2D parameter space of the plasma pressure versus the toroidal flow speed. Magnetic feedback can fully stabilize the RWM on HL-2M. Without considering the voltage limitation and the sensor signal noise, it is found that plasma flow helps active control of the mode, by reducing the required critical feedback gain for both flux-to-current and flux-to-voltage control schemes. In the absence of the sensor signal noise, the lowest control voltage saturation level, below which the RWM control is lost, is found to roughly satisfy a linear relation to the plasma flow frequency, indicating that subsonic plasma flow is effective in relaxing the control power requirement for the RWM feedback stabilization. The presence of the sensor signal noise substantially modifies the feedback results. A statistical study finds that the sensor signal noise, with the standard deviation of 0.1 G on HL-2M, roughly doubles the required control voltage for successful mode control. The synergistic stabilization effect due to plasma flow is somewhat weakened by the presence of the sensor signal noise. At a given rotation, the tolerable voltage limit generally increases with increasing feedback gain due to the sensor signal noise.

Physics↗
DOE OSTI2025

Evaluating the limitations of Bayesian metabolic control analysis

AbstractBayesian Metabolic Control Analysis (BMCA) has emerged as a promising framework for inferring metabolic control coefficients in data-limited scenarios by integrating Bayesian inference with linlog rate laws. However, its predictive accuracy and limitations remain underexplored. This study systematically evaluates BMCA’s ability to infer elasticity values, flux control coefficients (FCCs), and concentration control coefficients (CCCs) under varying data availability conditions using three synthetic metabolic network models. Our findings highlight the strengths and weaknesses of BMCA, guiding its application in metabolic engineering and emphasizing the need for methodological refinements.Author summaryUnderstanding how enzymes control metabolic pathways is crucial for optimizing biomanufacturing and synthetic biology applications. Bayesian Metabolic Control Analysis (BMCA) is a promising computational method that integrates Bayesian inference with metabolic control analysis to estimate key control parameters, even in cases with limited experimental data. However, the accuracy and limitations of BMCA remain unclear. In this study, we systematically evaluate BMCA using three synthetic metabolic networks to determine how different types of physiological data impact its predictive performance. We find that BMCA requires flux and enzyme concentration data for accurate predictions, while external metabolite concentrations contribute little. Additionally, BMCA fails to predict elasticity values beyond a magnitude of 1.5 and reliably infer allosteric regulation, even when strong regulatory interactions exist. In addition, BMCA does not accurately rank metabolic control points, which may limit its utility in identifying key enzymes in engineered pathways. Our work provides practical insights into when and how BMCA can be applied, guiding future research in metabolic modeling and control analysis.

Shin, Janis (ORCID:0000000216572455)↗
DOE OSTI2020

Effect of oral plaque control on postoperative pneumonia following lung cancer surgery

Abstract Background There have been few studies on the relationship between oral status and postoperative pneumonia (POP) in patients with lung cancer, and whether improving their oral condition assists with a lower incidence of POP before lung cancer surgery remains controversial. This retrospective study was conducted by a stomatologist to assess the effect of controlling oral pathogenic bacteria of patients with lung cancer to prevent POP. Methods A total of 235 patients with lung cancer who underwent lobectomy by open thoracotomy between July 2015 and December 2018 were selected and given the choice of being in the experimental or control group. A total of 122 participants in the experimental group received professional oral plaque control, and 113 participants in the control group did not receive plaque control. All clinical data of participants in both groups were retrospectively studied to determine the incidence of POP at the thirtieth day of discharge from hospital. Results Eight in the experimental group and six in the control group were excluded from the study. It was found that four of 114 patients suffered from POP in the experimental group (incidence = 3.51%). A total of 17 of 107 patients in the control group had pulmonary infection (incidence = 15.89%). Odds ratio was 0.19. The incidence of POP in the experimental group was significantly lower than that of the control group ( P < 0.05). Conclusions Professional oral plaque control is associated with a lower incidence of POP following lung cancer surgery and is therefore a favorable factor for preventing POP, and should be carried out before the surgical treatment of lung cancer. Key points Professional oral plaque control was associated with a lower incidence of POP following lung cancer surgery, and it is recommended this should be carried out before the surgical treatment of lung cancer.

Jia, Chunling↗
DOE OSTI2023

Experimental Performance of a Nonlinear Control Strategy to Regulate Temperature of a High-Temperature Solar Reactor

Abstract Despite the significant potential of solar thermochemical process technology for storing solar energy as solid-state solar fuel, several challenges have made its industrial application difficult. It is important to note that solar energy has a transient nature that causes instability and reduces process efficiency. Therefore, it is crucial to implement a robust control system to regulate the process temperature and tackle the shortage of incoming solar energy during cloudy weather. In our previous works, different model-based control strategies were developed namely a proportional integral derivative controller (PID) with gain scheduling and adaptive model predictive control (MPC). These methods were tested numerically to regulate the temperature inside a high-temperature tubular solar reactor. In this work, the proposed control strategies were experimentally tested under various operation conditions. The controllers were challenged to track different setpoints (500 °C, 1000 °C, and 1450 °C) with different amounts of gas/particle flowrates. Additionally, the flow controller was tested to regulate the reactor temperature under a cloudy weather scenario. The ultimate goal was to produce 5 kg of reduced solar fuel magnesium manganese oxide (MgMn2O4) successfully, and the controllers were able to track the required process temperature and reject disturbances despite the system's strong nonlinearity. The experimental results showed a maximum error in the temperature setpoint of less than 0.5% (6 °C), and the MPC controller demonstrated superior performance in reducing the control effort and rejecting disturbances.

Energy & Fuels↗
DOE OSTI2021

Automated Cyber Security Testing Platform for Industrial Control Systems

Nuclear Power Plants (NPPs) are a complex system of coupled physics controlled by a network of Programmable Logic Controllers (PLCs). These PLCs communicate process data across the network to coordinate control actions with each other and inform the operators of process variables and control decisions. Networking the PLCs allows more effective process control and provides the operator more information which results in more efficient plant operation. This interconnectivity creates new security issues, as operators have more access to the plant controls, so will bad actors. As plant networks become more digitized and encompass more sophisticated controllers, the network surface exposed to cyber interference grows. Understanding the dynamics of these coupled systems of physics, control logic, and network communications is critical to their protection. The research into the cybersecurity of the Operational Technologies of NPPs is developing and requires a platform that can allow high fidelity physics simulations to interact with digital networks of controllers. This will require three main components: a network simulation environment, a physics simulator, and virtual PLCs (vPLC) that represent typical industry hardware. A platform that incorporates these three components to provide the most accurate representation of actual NPP networks and controllers is developed in this paper.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Sodium Void Worth and Control Rod Worth Measurements in ZPPR 15

Sodium void worth and control rod worth were measured in Phases A, B, C and D of the ZPPR15 experimental program. Sodium voiding was simulated by replacing stainless steel cans containing sodium by empty stainless steel cans of the same sizes. The control rod worth measurements were measurements of simulated control rods (CRs) and simulated empty control rod positions (CRPs). A CRP consisted of a 2 x 2 array of drawers filled with sodium plates. A CR consisted of a 2 x 2 array of drawers containing alternating columns of boron carbide plates and sodium plates in the front 18 inches and just sodium plates in the back 18 inches. The ZPPR staff published the measured sodium void worths and control rod worths and the statistical uncertainties in the measured values. In reality, the published uncertainty for each of these measurements is only one component of the total uncertainty. There are additional contributions from uncertainties related to measurement technique, plate compositions and reproducibility. However, the dominant uncertainty for the sodium void worth and control rod worth measurements is the uncertainty in βeff which is required to convert from the natural measurement units, cents, to the calculation units, pcm or Δ/k 1 k 2 . A full uncertainty analysis was performed for the sodium void worth and control rod worth measurements. The significant uncertainties were quantified, and a total uncertainty was derived for each sodium void worth or control rod worth measurement. The ZPPR-15 experimental records were used to create detailed as-built Monte Carlo models of the sodium void worth and control rod worth configurations. These models were used to compute the sodium void worths and control rod worths. (C/E – 1) and the related uncertainty in (C/E – 1) were derived for the measured worths.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

A Comprehensive Study of the Impact of Inverter-Based Resource (IBR) Modeling and Control on Protection Relay Elements

Inverter-based resources (IBRs) exhibit fault responses that differ significantly from those of synchronous generators, which can challenge the reliable operation of many commonly used power system protection elements. The fault response of IBRs is primarily influenced by their control algorithms and configurations, but the impact of these controls on protection relays is not yet fully understood. This presentation provides a comprehensive study of how IBR modeling and controls affect transmission line protection. Key modeling and control aspects include the DC source, inverter model, power level control, current control, and current limiting. The study reveals that certain aspects - such as the type of DC source (battery, PV, or hybrid), inverter model (average vs. switching), and power level control methods (PQ dispatch vs. Vdc-Vac control for grid-following IBRs, and droop vs. VSM for grid-forming IBRs) - do not significantly affect relay response. However, faster control loops, such as current control and current limiting, do influence the relay behavior. Additionally, the study explores the effects of other factors, including momentary cessation, operating points, fast/slow current responses, and grid strength on relay performance. Finally, the study offers recommendations for both IBR and protection engineers to improve IBR fault response and enhance the reliability of protection systems.

14 SOLAR ENERGY↗
DOE OSTI2020

Leveraging Real-World Driving Data for Design and Impact Evaluation of Energy Efficient Control Strategies

Modeling and simulation are crucial in the development of advanced energy efficient control strategies. Utilizing real-world driving data as the underlying basis for control design and simulation lends veracity to projected real-world energy savings. Standardized drive cycles are limited in their utility for evaluating advanced driving strategies that utilize connectivity and on-vehicle sensing, primarily because they are typically intended for evaluating emissions and fuel economy under controlled conditions. Real-world driving data, because of its scale, is a useful representation of various road types, driving styles, and driving environments. The scale of real-world data also presents challenges in effectively using it in simulations. A fast and efficient simulation methodology is necessary to handle the large number of simulations performed for design analysis and impact evaluation of control strategies. In this study, two methods are presented of leveraging real-world data in both design optimization of energy efficient control strategies and in evaluating the real-world impact of those control strategies upon large-scale deployment. Through these methodologies, strategies with highest impact on energy savings were selected to be implemented as control algorithms. The developed algorithms were incorporated into a vehicle dynamics and powertrain control architecture implemented on a Cadillac CT6 demonstration vehicle. The control algorithms were then exercised on real-world driving scenarios to determine their impact on collective energy savings. The methodology utilizes the large-scale driving data sets maintained by the National Renewable Energy Laboratory to extract real-world driving scenarios and efficient simulation software tools. The insights obtained through this research help in guiding technology selection for energy efficient driving controls.

ARPA-E↗
NASA NTRS1973

Analytical and experimental performance of optimal controller designs for a supersonic inlet

The techniques of modern optimal control theory were applied to the design of a control system for a supersonic inlet. The inlet control problem was approached as a linear stochastic optimal control problem using as the performance index the expected frequency of unstarts. The details of the formulation of the stochastic inlet control problem are presented. The computational procedures required to obtain optimal controller designs are discussed, and the analytically predicted performance of controllers designed for several different inlet conditions is tabulated. The experimental implementation of the optimal control laws is described, and the experimental results obtained in a supersonic wind tunnel are presented. The control laws were implemented with analog and digital computers. Comparisons are made between the experimental and analytically predicted performance results. Comparisons are also made between the results obtained with continuous analog computer controllers and discrete digital computer versions.

Zeller, J. R.↗
NASA NTRS1975

Mechanization of and experience with a triplex fly-by-wire backup control system

A redundant three-axis analog control system was designed and developed to back up a digital fly-by-wire control system for an F-8C airplane. Forty-two flights, involving 58 hours of flight time, were flown by six pilots. The mechanization and operational experience with the backup control system, the problems involved in synchronizing it with the primary system, and the reliability of the system are discussed. The backup control system was dissimilar to the primary system, and it provided satisfactory handling through the flight envelope evaluated. Limited flight tests of a variety of control tasks showed that control was also satisfactory when the backup control system was controlled by a minimum-displacement (force) side stick. The operational reliability of the F-8 digital fly-by-wire control system was satisfactory, with no unintentional downmodes to the backup control system in flight. The ground and flight reliability of the system's components is discussed.

Lock, W. P.↗
NASA NTRS1974

Three-axis attitude control for solar-powered electric propulsion spacecraft

Spacecraft utilizing solar electric propulsion (SEP) for certain long-term interplanetary missions will depend on large, flexible solar arrays. The resulting spacecraft configurations present some complex flight control problems. Questions regarding a general design approach are discussed along with options for three-axis control forces, tradeoffs for three-axis control forces, controllers for SEP attitude control, sensors for SEP attitude control, aspects of nonrigid vehicle interaction with attitude control, thrust vector control SEP dynamics, and mass expulsion control SEP dynamics. It is found that the state-of-the-art of control system design is mature enough to support an SEP project.

Bouvier, H. K.↗
NASA NTRS1976

Mechanization of and experience with a triplex fly-by-wire backup control system

A redundant three axis analog control system was designed and developed to back up a digital fly by wire control system for an F-8C airplane. The mechanization and operational experience with the backup control system, the problems involved in synchronizing it with the primary system, and the reliability of the system are discussed. The backup control system was dissimilar to the primary system, and it provided satisfactory handling through the flight envelope evaluated. Limited flight tests of a variety of control tasks showed that control was also satisfactory when the backup control system was controlled by a minimum displacement (force) side stick. The operational reliability of the F-8 digital fly by wire control system was satisfactory, with no unintentional downmodes to the backup control system in flight. The ground and flight reliability of the system's components is discussed.

Lock, W. P.↗
NASA NTRS1975

Space Shuttle flight control system

The Space Shuttle is a control stabilized vehicle with control provided by an all digital, fly-by-wire flight control system. This paper gives a description of the several modes of flight control which correspond to the Shuttle mission phases. These modes are ascent flight control (including open loop first stage steering, the use of four computers operating in parallel and inertial guidance sensors), on-orbit flight control (with a discussion of reaction control, phase plane switching logic, jet selection logic, state estimator logic and OMS thrust vector control), entry flight control and TAEM (terminal area energy management to landing). Also discussed are redundancy management and backup flight control.

Klinar, W. J.↗
NASA NTRS1975

Distribution of control decisions in remote manipulation

The particular characteristics of the problem of distributing control decisions between man and computer in remotely controlled manipulation are discussed. State of the art is reviewed from two viewpoints: (1) specifications of both control commands and control context of sensor signals the operator inputs to the manipulator control computer; (2) operations the manipulator control computer performs on operator commands and realtime sensor signals to control the manipulator for a specified task. JPL breadboard systems, system components, and control experiments are described related to the development and evaluation of manipulator control systems with capabilities of distributing control decisions between man and computer.

Bejczy, A. K.↗
NASA NTRS1978

Propulsion/flight control integration technology (PROFIT) software system definition

The Propulsion Flight Control Integration Technology (PROFIT) program is designed to develop a flying testbed dedicated to controls research. The control software for PROFIT is defined. Maximum flexibility, needed for long term use of the flight facility, is achieved through a modular design. The Host program, processes inputs from the telemetry uplink, aircraft central computer, cockpit computer control and plant sensors to form an input data base for use by the control algorithms. The control algorithms, programmed as application modules, process the input data to generate an output data base. The Host program formats the data for output to the telemetry downlink, the cockpit computer control, and the control effectors. Two applications modules are defined - the bill of materials F-100 engine control and the bill of materials F-15 inlet control.

Carlin, C. M.↗