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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Very Large Eddy Simulation Technique for Noise Prediction and Control in Turbomachinery and Propulsion

The summer fellowship research project focused on further developing an advanced computational technique based on Very Large Eddy Simulation (VLES) for analysis and control of major sources of noise in turbomachinery and propulsion systems, including jet noise and fan noise. Major part of the work during the 10-week tenure dealt with implementing a low-order, implicit A-stable time-stepping scheme in the existing explicit VLES code of Dr. Ray Hixon. The preliminary plan of the work also included application of a new time marching formulation to the problem of viscous gust-airfoil interaction. Other research items selected for implementation (possibly in the future) included investigating a set of new subgrid turbulent models for the code, and code application to a number of test cases, including a supersonic jet and swirling flow downstream of a rotor stage.

Golubev, Vladimir V.↗
DOE OSTI2022

Hygrothermal simulation of exterior retrofits in a cold climate

This work presents results from moisture modeling as part of a project undertaken by Pacific Northwest National Laboratory and its research partners, the University of Minnesota, and the Oak Ridge National Laboratory. The research goal is to identify exterior wall retrofit systems for cold climates that are low cost, energy efficient, and do not result in moisture durability problems. A base case wall was identified representing a typical wood frame construction, circa 1950. Retrofit options were selected based on input from industry, academia, and published work and seven options were constructed and installed at the University of Minnesota’s cold weather exposure facility in Cloquet, MN. Measurements were carried out during winter months and the data was used for model validation. Hygrothermal simulations were then carried out using WUFI (Version 6.4) in accordance with standard ANSI/ASRHAE 160-2016, Criteria for Moisture-Control Design Analysis in Buildings. Simulations were run out to three years and results show that the exterior retrofits improve thermal performance and do not negatively impact moisture durability of the existing wall.

Aldykiewicz Jr, Antonio↗
DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1978

The Total In-Flight Simulator (TIFS) aerodynamics and systems: Description and analysis

The aerodynamics, control system, instrumentation complement and recording system of the USAF Total In/Flight Simulator (TIFS) airplane are described. A control system that would allow the ailerons to be operated collectively, as well as, differentially to entrance the ability of the vehicle to perform the dual function of maneuver load control and gust alleviation is emphasized. Mathematical prediction of the rigid body and the flexible equations of longitudinal motion using the level 2.01 FLEXSTAB program are included along with a definition of the vehicle geometry, the mass and stiffness distribution, the calculated mode frequencies and mode shapes, and the resulting aerodynamic equations of motion of the flexible vehicle. A complete description of the control and instrumentation system of the aircraft is presented, including analysis, ground test and flight data comparisons of the performance and bandwidth of the aerodynamic surface servos. Proposed modification for improved performance of the servos are also presented.

Andrisani, D., II↗
NASA NTRS1993

Robust tracking control of a magnetically suspended rigid body

This study is an application of H-infinity and microsynthesis for designing robust tracking controllers for the Large Angle Magnetic Suspension Test Facility. The modeling, design, analysis, simulation, and testing of a control law that guarantees tracking performance under external disturbances and model uncertainties is investigated. The type of uncertainties considered and the tracking performance metric used is discussed. This study demonstrates the tradeoff between tracking performance at low frequencies and robustness at high frequencies. Two sets of controllers were designed and tested. The first set emphasized performance over robustness, while the second set traded off performance for robustness. Comparisons of simulation and test results are also included. Current simulation and experimental results indicate that reasonably good robust tracking performance can be attained for this system, using multivariable robust control approach.

Lim, Kyong B.↗
NASA NTRS1994

Robust tracking control of a magnetically suspended rigid body

This study is an application of H-infinity and micro-synthesis for designing robust tracking controllers for the Large Angle Magnetic Suspension Test Facility. The modeling, design, analysis, simulation, and testing of a control law that guarantees tracking performance under external disturbances and model uncertainties is investigated. The type of uncertainties considered and the tracking performance metric used is discussed. This study demonstrates the tradeoff between tracking performance at low frequencies and robustness at high frequencies. Two sets of controllers were designed and tested. The first set emphasized performance over robustness, while the second set traded off performance for robustness. Comparisons of simulation and test results are also included. Current simulation and experimental results indicate that reasonably good robust tracking performance can be attained for this system using multivariable robust control approach.

Lim, Kyong B.↗
DOE OSTI2022

Model-based Co-Simulation of Heat Pump Water Heater with Phase Change Materials Thermal Energy Storage

The study analysis the behavior of a new developed heat pump water heater technology which integrates a phase change materials storage with a standard heat pump water heater to maximize the performance parameters of the Unified Energy Factor (UEF) and First Hour Rating (FHR). A model-based control development co-simulation platform is developed to include equipment models, such as heat pump, standard water tank, phase change materials storage tank, and integrate them with control model to support controls design, analysis, verification, and validation. Simulation results are compared with lab test results to validate the accuracy of developed co-simulation platform

Sun, Jian↗
NASA NTRS1995

PLATSIM: An efficient linear simulation and analysis package for large-order flexible systems

PLATSIM is a software package designed to provide efficient time and frequency domain analysis of large-order generic space platforms implemented with any linear time-invariant control system. Time domain analysis provides simulations of the overall spacecraft response levels due to either onboard or external disturbances. The time domain results can then be processed by the jitter analysis module to assess the spacecraft's pointing performance in a computationally efficient manner. The resulting jitter analysis algorithms have produced an increase in speed of several orders of magnitude over the brute force approach of sweeping minima and maxima. Frequency domain analysis produces frequency response functions for uncontrolled and controlled platform configurations. The latter represents an enabling technology for large-order flexible systems. PLATSIM uses a sparse matrix formulation for the spacecraft dynamics model which makes both the time and frequency domain operations quite efficient, particularly when a large number of modes are required to capture the true dynamics of the spacecraft. The package is written in MATLAB script language. A graphical user interface (GUI) is included in the PLATSIM software package. This GUI uses MATLAB's Handle graphics to provide a convenient way for setting simulation and analysis parameters.

Maghami, Periman↗
NASA NTRS2001

Robust Nonlinear Feedback Control of Aircraft Propulsion Systems

This is the final report on the research performed under NASA Glen grant NASA/NAG-3-1975 concerning feedback control of the Pratt & Whitney (PW) STF 952, a twin spool, mixed flow, after burning turbofan engine. The research focussed on the design of linear and gain-scheduled, multivariable inner-loop controllers for the PW turbofan engine using H-infinity and linear, parameter-varying (LPV) control techniques. The nonlinear turbofan engine simulation was provided by PW within the NASA Rocket Engine Transient Simulator (ROCETS) simulation software environment. ROCETS was used to generate linearized models of the turbofan engine for control design and analysis as well as the simulation environment to evaluate the performance and robustness of the controllers. Comparison between the H-infinity, and LPV controllers are made with the baseline multivariable controller and developed by Pratt & Whitney engineers included in the ROCETS simulation. Simulation results indicate that H-infinity and LPV techniques effectively achieve desired response characteristics with minimal cross coupling between commanded values and are very robust to unmodeled dynamics and sensor noise.

Garrard, William L.↗
DOE OSTI2024

Practical Insights on Applying Simulation-Based Control Methods in Experimental Studies

Advanced nuclear reactors are crucial to the future of energy both in the United States and around the globe. In contrast to the current operating fleet, they are characterized as being deployable in remote locations and able to operate in semi-autonomous or autonomous fashion. This leap forward necessitates a new reactor control paradigm. Because advanced nuclear reactors are still under development in the United States, the creation of new control methods to achieve autonomous operations has been based on systems modeling and simulation. However, an important factor in successfully deploying these new control methods is the ability to seamlessly transition from simulation environments to real-world settings. Control methods tested in both simulation and experimental settings need to be investigated in the context of advanced reactor applications. This work developed a series of simple controllers for Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor operating in load-following scenarios. These controllers were tested in both simulation and experimental settings, and a comparative performance analysis was performed. The simulation tests leveraged the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software developed in a previous stage of the current effort, along with the MARVEL Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The experimental tests leveraged the COMMAND software, MARVEL models, and the U.S. Department of Energy Microreactor Program’s Microreactor Automated Control System (MACS). MACS was developed to serve as a control method testbed. It was customized to mirror the MARVEL microreactor, and COMMAND enabled MACS to emulate the physics of MARVEL. The load-following controller was developed using the simulation platform, with efforts to emulate real systems by introducing actuator saturation and noise. These factors were incrementally accounted for in the controller design. After finalizing the controller design, it was implemented with the experimental setup. The experimental conditions tested included an initial test under conditions similar to the final simulation test, and two additional scenarios. The first scenario introduced additional actuator saturation to account for equipment aging over time, which was unknown to the controller. The second scenario introduced sensor delay, a phenomenon anticipated with the use of remote operations or wireless communication in advanced reactors. These tests revealed several notable differences. While the controller performed well in simulation, it exhibited several limitations when transitioning to hardware. The main challenges involved maintaining the steady-state target power, as evidenced by larger error values between the true reactor power and setpoint power, as well as persistent oscillations in controlled reactor power. These issues could lead to unacceptable transient conditions in real reactor testing. Introducing actuator aging and stochastic delays in the experimental setup significantly impacted controller performance, resulting in increased overshoot and undershoot, and exacerbated error and oscillations previously mentioned. These findings underscore the importance of experimental testbeds for testing and validating control methods, as controllers developed using only theory and/or simulation may perform unexpectedly when applied to actual hardware. This research emphasizes the need for an experimental testbed for achieving such validation.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
NASA NTRS1991

Modelling and simulation of a heat exchanger

Two models for two different control systems are developed for a parallel heat exchanger. First by spatially lumping a heat exchanger model, a good approximate model which has a high system order is produced. Model reduction techniques are applied to these to obtain low order models that are suitable for dynamic analysis and control design. The simulation method is discussed to ensure a valid simulation result.

Xia, Lei↗
DOE OSTI2020

A Novel Simulation-Based Framework for Sensor Error Impact Analysis in Smart Building Systems: A Case Study for a Demand-Controlled Ventilation System

Sensors are one of the fundamental components for sensor-rich controls in buildings but are prone to different errors. Existing studies show that sensor errors hold a place among top-priority faults in building systems. Before we take countermeasures to mitigate the sensor errors, it is vital to prioritize key sensors and quantify the collective impacts of concurrent sensor errors. In response to this, a simulation-based methodology is introduced to conduct a comprehensive sensor error impact analysis in building systems, which adds a stochastic sensor prioritization through a sensitivity analysis on top of a commonly used deterministic sensor error quantification. The synergies of these two parts help better interpret the sensor error impacts on building energy consumption, ventilation performance, thermal comfort, etc. A sensor-rich CO2-based Demand-Controlled Ventilation system is used as a case study to demonstrate the viability of the methodology as a proof-of-the-concept. The results show that the energy savings potential and ventilation performance are mostly influenced by the accuracy of the AHU outdoor airflow sensors. The accuracy of zone level airflow sensors has a negligible impact on both energy savings and ventilation performance. The accuracy of zone CO2 sensors has more influence on the ventilation performance compared with the accuracy of zone airflow sensors. Compared with the baseline case with zero errors, the largest deviation percentages could reach 16.90% and 94.32%, respectively, in terms of the Heating, Ventilation, and Air-Conditioning (HVAC) annual energy consumption and the Outdoor Air Ratio (OAR) when multiple key sensors suffer from normal error intensities simultaneously.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1994

Aeroelastic simulation of higher harmonic control

This report describes the development of an aeroelastic analysis of a helicopter rotor and its application to the simulation of helicopter vibration reduction through higher harmonic control (HHC). An improved finite-state, time-domain model of unsteady aerodynamics is developed to capture high frequency aerodynamic effects. An improved trim procedure is implemented which accounts for flap, lead-lag, and torsional deformations of the blade. The effect of unsteady aerodynamics is studied and it is found that its impact on blade aeroelastic stability and low frequency response is small, but it has a significant influence on rotor hub vibrations. Several different HHC algorithms are implemented on a hingeless rotor and their effectiveness in reducing hub vibratory shears is compared. All the controllers are found to be quite effective, but very differing HHC inputs are required depending on the aerodynamic model used. Effects of HHC on rotor stability and power requirements are found to be quite small. Simulations of roughly equivalent articulated and hingeless rotors are carried out, and it is found that hingeless rotors can require considerably larger HHC inputs to reduce vibratory shears. This implies that the practical implementation of HHC on hingeless rotors might be considerably more difficult than on articulated rotors.

Robinson, Lawson H.↗
NASA NTRS1974

The AIROscope pointing and stabilization system

The AIROscope pointing and stabilization system is described. The system is configured with three gimbal axes and rate integrating gyro stabilization to provide a stable platform for infrared astronomy. Error signals for on and off-axis pointing are derived from a video sensor which also drives a ground station display. Other features of the system include direct drive torque motors and electronic suspension damping. Results of analysis and simulations used to design the control loops, and a pointing error analysis are presented.

Murphy, J. P.↗
DOE OSTI2023

Integrative teaching of metabolic modeling and flux analysis with interactive python modules

Abstract The modeling of rates of biochemical reactions—fluxes—in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint‐based (Metabolic Flux Analysis and flux balance analysis) approaches. Although different resources exist for teaching these methods individually, to‐date no resources have been developed to teach these approaches in an integrative way that equips learners with an understanding of each modeling paradigm, how they relate to one another, and the information that can be gleaned from each. We have developed a series of modeling simulations in Python to teach kinetic modeling, metabolic control analysis, 13C‐metabolic flux analysis, and flux balance analysis. These simulations are presented in a series of interactive notebooks with guided lesson plans and associated lecture notes. Learners assimilate key principles using models of simple metabolic networks by running simulations, generating and using data, and making and validating predictions about the effects of modifying model parameters. We used these simulations as the hands‐on computer laboratory component of a four‐day metabolic modeling workshop and participant survey results showed improvements in learners' self‐assessed competence and confidence in understanding and applying metabolic modeling techniques after having attended the workshop. The resources provided can be incorporated in their entirety or individually into courses and workshops on bioengineering and metabolic modeling at the undergraduate, graduate, or postgraduate level.

Kaste, Joshua A. M.↗
NASA NTRS2007

Orion Orbit Control Design and Analysis

The analysis of candidate thruster configurations for the Crew Exploration Vehicle (CEV) is presented. Six candidate configurations were considered for the prime contractor baseline design. The analysis included analytical assessments of control authority, control precision, efficiency and robustness, as well as simulation assessments of control performance. The principles used in the analytic assessments of controllability, robustness and fuel performance are covered and results provided for the configurations assessed. Simulation analysis was conducted using a pulse width modulated, 6 DOF reaction system control law with a simplex-based thruster selection algorithm. Control laws were automatically derived from hardware configuration parameters including thruster locations, directions, magnitude and specific impulse, as well as vehicle mass properties. This parameterized controller allowed rapid assessment of multiple candidate layouts. Simulation results are presented for final phase rendezvous and docking, as well as low lunar orbit attitude hold. Finally, on-going analysis to consider alternate Service Module designs and to assess the pilot-ability of the baseline design are discussed to provide a status of orbit control design work to date.

Jackson, Mark↗
NASA NTRS1974

Verification test results of Apollo stabilization and control systems during undocked operations

The results are presented of analysis and simulation testing of both the Skylark 1 reaction control system digital autopilot (RCS DAP) and the thrust vector control (TVC) autopilot for use during the undocked portions of the Apollo/Soyuz Test Project Mission. The RCS DAP testing was performed using the Skylab Functional Simulator (SLFS), a digital computer program capable of simulating the Apollo and Skylab autopilots along with vehicle dynamics including bending and sloshing. The model is used to simulate three-axis automatic maneuvers along with pilot controlled manual maneuvers using the RCS DAP. The TVC autopilot was tested in two parts. A classical stability analysis was performed on the vehicle considering the effects of structural bending and sloshing when under control of the TVC autopilot. The time response of the TVC autopilot was tested using the SLFS. Results indicate that adequate performance stability margins can be expected for the CSM/DM configuration when under the control of the Apollo control systems tested.

Copeland, E. L.↗