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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

A piloted simulation of the backup control system engagement for the YAH-64

A piloted simulator experiment, designed to evaluate and optimize certain backup control system (BUCS) engagement parameters and to provide pilot familiarization with aircraft response prior to flight test of the BUCS in the YAH-64 Advanced Attack Helicopter, is described. Key elements of the simulation were the representation of a control system jam, the pilot's breaking of a shear pin in the jammed control, and the resultant BUCS engagement. To minimize the excursions in aircraft motion which could result from the pilot's control inputs after shear pin breakage, the BUCS control function is blended in gradually. The experiment's results indicate that optimum time to full control authority after shear pin breakage is three seconds in all axes for certain critical tasks. Special pilot training in the recovery from a control system jam may be necessary to minimize unacceptably large aircraft transients in the off-axis.

Blanken, C. L.↗
NASA NTRS2006

Rate-Based Model Predictive Control of Turbofan Engine Clearance

An innovative model predictive control strategy is developed for control of nonlinear aircraft propulsion systems and sub-systems. At the heart of the controller is a rate-based linear parameter-varying model that propagates the state derivatives across the prediction horizon, extending prediction fidelity to transient regimes where conventional models begin to lose validity. The new control law is applied to a demanding active clearance control application, where the objectives are to tightly regulate blade tip clearances and also anticipate and avoid detrimental blade-shroud rub occurrences by optimally maintaining a predefined minimum clearance. Simulation results verify that the rate-based controller is capable of satisfying the objectives during realistic flight scenarios where both a conventional Jacobian-based model predictive control law and an unconstrained linear-quadratic optimal controller are incapable of doing so. The controller is evaluated using a variety of different actuators, illustrating the efficacy and versatility of the control approach. It is concluded that the new strategy has promise for this and other nonlinear aerospace applications that place high importance on the attainment of control objectives during transient regimes.

DeCastro, Jonathan A.↗
DOE OSTI2020

Multi-Timescale Integrated Dynamic and Scheduling Model (MIDAS-Solar)

Solar photovoltaic (PV) installations have experienced unprecedented growth in the United States. PV will become not only an energy producer but also a necessary provider of ancillary services at multiple timescales. Conventional methods to simulate power system operations - such as long-term production simulation (which typically considers schedules from hours to minutes by using an optimization framework) and short-term transient studies (which simulate dynamics from seconds to sub-seconds using state variables and differential equations) are not sufficient for studying the multiple-timescale variation of solar generation and its impact on system reliability. Long-term system economics and short-term system dynamics are highly coupled, particularly when the penetration level of renewable generation is extremely high, because the uncertainty and variability of solar generation will impact both power systems steady-state and dynamic performance. This project helps meet and exceed the Solar Energy Technologies Office goal of systems integration by directly addressing this stability and reliability challenge for electric grid planning and operation. This will be accomplished by developing temporally comprehensive, closed-loop simulation models that seamlessly simulate power systems operations from economic scheduling (day-ahead to hours) to dynamic response analysis (seconds to sub-seconds). Both a multi-timescale grid model and an integrated PV model will be developed in this project to accurately study the impacts of PV variability and uncertainty on system reliability at multiple timescales. Using quasi-dynamic simulation methods and data-driven security assessment (DSA) criteria will allow the dynamic characteristics of PV to be fed forward into longer-timescale scheduling models for a complete understanding of the effect of short-term PV dynamics on bulk systems operations (e.g., reserve scheduling and deployment). Upon completion of the proposed model, this project will help operators accurately assess system reliability by deploying energy and reserve scheduling under critical contingency conditions and studying interactions among all types of essential reliability services provided by modern PV power plants.

14 SOLAR ENERGY↗
NASA NTRS1999

Energetic Neutral Atom Imaging at Low Altitudes from the Swedish Microsatellite Astrid: Extraction of the Equatorial Ion Distribution

Energetic neutral atom (ENA) images obtained by the ENA imager on- board the Astrid satellite in the polar cap at 1000 km during a moderate magnetic storm (Dst greater than or equal to 80 nT) on 8 February 1995 are simulated using a parameterized model of the equatorial ion distribution and a six-component Chamberlain exo-sphere with parameters from the MSISE-90 model. By changing the ion parameters until a matching ENA image is obtained one can extract the equatorial ion distribution. Four consecutive images from different view points several of minutes apart are simulated assuming H(+) and O(+), respectively, as parent ions. The optimal set of parameters is extracted by minimizing the chi(exp 2) difference between simulated and observed ENA image using Powell's minimization algorithm. The optimal equatorial model ion distribution consists of O(+) peaked in around dusk. The lower intensity of fluxes obtained from vantage points closer to the pole is an effect of the loss cone of the parent ion distribution being empty.

Brandt, Pontus C:son↗
NASA NTRS1988

Simulation of the human-telerobot interface

A part of NASA's Space Station will be a Flight Telerobotic Servicer (FTS) used to help assemble, service, and maintain the Space Station. Since the human operator will be required to control the FTS, the design of the human-telerobot interface must be optimized from a human factors perspective. Simulation has been used as an aid in the development of complex systems. Simulation has been especially useful when it has been applied to the development of complex systems. Simulation should ensure that the hardware and software components of the human-telerobot interface have been designed and selected so that the operator's capabilities and limitations have been accommodated for since this is a complex system where few direct comparisons to existent systems can be made. Three broad areas of the human-telerobot interface where simulation can be of assistance are described. The use of simulation not only can result in a well-designed human-telerobot interface, but also can be used to ensure that components have been selected to best meet system's goals, and for operator training.

Stuart, Mark A.↗
NASA NTRS2020

Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning

Finding the most likely path to a set of failure states is important to the analysis of safety-critical systems that operate over a sequence of time steps, such as aircraft collision avoidance systems and autonomous cars. In many applications such as autonomous driving, failures cannot be completely eliminated due to the complex stochastic environment in which the system operates.As a result, safety validation is not only concerned about whether a failure can occur, but also discovering which failures are most likely to occur. This article presents adaptive stress testing (AST), a framework for finding the most likely path to a failure event in simulation. We consider a general black box setting for partially observable and continuous-valued systems operating in an environment with stochastic disturbances. We formulate the problem as a Markov decision process and use reinforcement learning to optimize it. The approach is simulation-based and does not require internal knowledge of the system, making it suitable for black-box testing of large systems. We present different formulations depending on whether the state is fully observable or partially observable. In the latter case, we present a modified Monte Carlo tree search algorithm that only requires access to the pseudorandom number generator of the simulator to overcome partial observability. We also present an extension of the framework, called differential adaptive stress testing (DAST), that can find failures that occur in one system but not in another. This type of differential analysis is useful in applications such as regression testing, where we are concerned with finding areas of relative weakness compared to a baseline. We demonstrate the effectiveness of the approach on an aircraft collision avoidance application, where a prototype aircraft collision avoidance system is stress tested to find the most likely scenarios of near mid-air collision.

Verification and Validation↗
NASA NTRS2019

Quantifying the Relative Impact of Model Microphysics Parameterizations and Scattering Models in Simulating Synthetic Radar and Microwave Radiometer Observations

Output from numerical weather models is often used to simulate observations from remote sensing instruments, for purposes ranging from data assimilation, synthetic retrievals of geophysical quantities, and optimization of observing systems. However, when hydrometeors are present, the level of detail provided by the weather model is generally insufficient to fully constrain the input to the radiative transfer model (RTM), and further assumptions must be made by the RTM user in order to produce synthetic observations. Using a hierarchy of models including cloud-resolving, double-moment, bin microphysical, and ice-habit predicting models, along with scattering properties from the OpenSSP, Atmospheric Radiative Transfer Simulator (ARTS) databases, as well as relatively simple geometries (e.g., cylindrical plates and columns), we demonstrate the spread in synthetic observation output and the extent to which it is reduced when microphysics is more strongly constrained by the model. As an intermediate step, an error budget for the RTM simulations was derived and from that we developed and will describe best practices for observation simulation (e.g., optimal number of hydrometeor size bins, truncation of the particle size distribution, angular resolution of scattering phase function). Some statistical comparisons with observations will also be presented.

Munchak, S. Joseph↗
DOE OSTI2019

Development of multi-objective core optimization framework and application to sodium-cooled fast test reactors

The optimization of a Sodium-cooled Fast Reactor (SFR) core is a challenging process, due to the large number of design parameters, the nonlinearities among inputs and outputs, and the complicated correlation among output parameters. This study attempts to develop a generalized framework for the SFR core optimization by coupling the sensitivity analysis, advanced optimization algorithm, and optionally the surrogate modeling. The framework is built based on the fast reactor modeling capability of the Argonne Reactor Computation (ARC) suite and the sensitivity analysis and optimization modules embedded in the DAKOTA code, both have been integrated within the NEAMS Workbench. The genetic algorithm is selected as the optimization method for its robustness, while the option of surrogate modeling is also explored to alleviate the computational burden caused by employing the ARC direct core physics simulation and thus enhance the efficiency of the optimization. Finally, the normalized deviations of performance parameters of the near-optimal solution from those of the ideal core are calculated and used as criteria to down select the final core design. The developed framework is applied to the Advanced Burner Test Reactor (ABTR) core, and optimal solutions are determined by balancing various objectives simultaneously, including peak fast flux, core volume, power, reactivity swing, plutonium mass feed, while at the same time satisfying the predefined constraints due to safety or economics considerations. The optimal ABTR core design obtained using the direct physical simulation and surrogated model are compared and discussed. It is found that using the accurately constructed surrogate models can significantly reduce the required computational time while maintaining satisfactory accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Development Optimization and Uncertainty Analysis Methods for Oil and Gas Reservoirs

Uncertainty complicates the development optimization of oil and gas exploration and production projects, but methods have been devised to analyze uncertainty and its impact on optimal decision-making. This paper compares two methods for development optimization and uncertainty analysis: Monte Carlo (MC) simulation and stochastic programming. Two example problems for a gas field development and an oilfield development are solved and discussed to elaborate the advantages and disadvantages of each method. Development optimization involves decisions regarding the configuration of initial capital investment and subsequent operational decisions. Uncertainty analysis involves the quantification of the impact of uncertain parameters on the optimum design concept. The gas field development problem is designed to highlight the differences in the implementation of the two methods and to show that both methods yield the exact same optimum design. The results show that both MC optimization and stochastic programming provide unique benefits, and that the choice of method depends on the goal of the analysis. While the MC method generates more useful information, along with the optimum design configuration, the stochastic programming method is more computationally efficient in determining the optimal solution. Reservoirs comprise multiple compartments and layers with multiphase flow of oil, water, and gas. We present a workflow for development optimization under uncertainty for these reservoirs, and solve an example on the design optimization of a multicompartment, multilayer oilfield development.

02 PETROLEUM↗
NASA NTRS1996

The Propulsive-Only Flight Control Problem

Attitude control of aircraft using only the throttles is investigated. The long time constants of both the engines and of the aircraft dynamics, together with the coupling between longitudinal and lateral aircraft modes make piloted flight with failed control surfaces hazardous, especially when attempting to land. This research documents the results of in-flight operation using simulated failed flight controls and ground simulations of piloted propulsive-only control to touchdown. Augmentation control laws to assist the pilot are described using both optimal control and classical feedback methods. Piloted simulation using augmentation shows that simple and effective augmented control can be achieved in a wide variety of failed configurations.

Blezad, Daniel J.↗
NASA NTRS2014

NDE and SHM Simulation for CFRP Composites

Ultrasound-based nondestructive evaluation (NDE) is a common technique for damage detection in composite materials. There is a need for advanced NDE that goes beyond damage detection to damage quantification and characterization in order to enable data driven prognostics. The damage types that exist in carbon fiber-reinforced polymer (CFRP) composites include microcracking and delaminations, and can be initiated and grown via impact forces (due to ground vehicles, tool drops, bird strikes, etc), fatigue, and extreme environmental changes. X-ray microfocus computed tomography data, among other methods, have shown that these damage types often result in voids/discontinuities of a complex volumetric shape. The specific damage geometry and location within ply layers affect damage growth. Realistic threedimensional NDE and structural health monitoring (SHM) simulations can aid in the development and optimization of damage quantification and characterization techniques. This paper is an overview of ongoing work towards realistic NDE and SHM simulation tools for composites, and also discusses NASA's need for such simulation tools in aeronautics and spaceflight. The paper describes the development and implementation of a custom ultrasound simulation tool that is used to model ultrasonic wave interaction with realistic 3-dimensional damage in CFRP composites. The custom code uses elastodynamic finite integration technique and is parallelized to run efficiently on computing cluster or multicore machines.

Leckey, Cara A. C.↗
DOE OSTI2018

OPTIMIZATION OPTIONS FOR NARROWING TRANSIENT TESTING PULSE WIDTHS NECESSARY TO ENHANCE LWR RIA SIMULATIONS IN THE TREAT FACILITY

The Transient Reactor Test (TREAT) Facility provided thousands of transient irradiations and plays a crucial role in nuclear-heated safety research. The facility’s flexible design and multi-mission nature saw historic experiments for numerous reactor fuels and transient types, but was never specifically adapted to address very-brief pulse transients akin to postulated Light Water Reactor (LWR) Reactivity Initiated Accidents (RIA). Since the behaviors of fuel under these conditions depends strongly on energy input duration and resulting cladding time/temperature response under pellet cladding mechanical interactions, this three-year project was conceived to investigate new pulse-narrowing capabilities. Kinetic models showed incremental improvements for minor facility enhancements including increased reactivity step insertions (to initiate the power pulse) and slightly-increased transient rod drive speed for pulse termination (“clipping”). Replacing peak fuel assemblies, repositioning non-transient control rods to hold down the “hot side” of the core, and balancing against required excess reactivity needs, the limiting fuel assembly power can be reduced by ~20 %. This is a remarkable discovery of latent capability in TREAT, not only in enabling the subject capabilities for reduced pulse widths, but also significantly “uprating” the core’s transient energy capacity. Incremental improvements can likely enhance TREAT’s capability into BWR-relevant missions; briefer PWR pulse shapes can only be achieved with an advanced clipping system. Helium 3 was found to offer the greatest benefits for clipping design and overall performance. A unique concept showed great promise for enabling a 3He-based system with a reasonable cost; this design concept will likely become the focal point of future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Thermo-hydraulic steam pipe models for district heating simulations: Simplifications to balance accuracy and simulation speed

Steam piping networks are essential for optimizing performance in industrial processes and district heating systems. However, dynamic models that balance thermo-hydraulic accuracy with computational efficiency remain limited. In response, this paper presents a new discretized steam pipe model based on the plug flow approach, capturing key thermo-hydraulic behaviors while simplifying steam phase change processes. Implemented in Modelica, the model accurately calculates temperature and pressure distributions along steam pipelines. To improve computational efficiency for district-scale simulations, five model simplifications are introduced: lumped thermo-hydraulic functions, empirical correlations, fluid state approximations, steady-state dynamics and inclusion of flow derivatives. These simplified models achieve 85%-98% accuracy in predicting pressure drop and condensation losses, including dynamic condensate behavior during pipe warm-up—a factor often overlooked in existing models. The models support diverse network configurations, scaling effectively to systems with multiple distribution pipes and connected building loads. Discrete models provide detailed insights but exhibit a cubic increase in simulation time as the network scales by N connected building O(N 2.42 ). In contrast, lumped models simulate 10–28 times faster than discrete, offering quadratic scaling of simulation time O(N 1.73 ). However, they still require 6 times more computation time than a lossless network, highlighting the inherent computational challenges of modeling compressible fluid flow. In conclusion, the steady-state lumped variant, with its near-linear scalability in computational time O(N 1.01 ), emerges as an efficient solution for preliminary design evaluations and extensive parametric studies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

A learned closure method applied to phase mixing in a turbulent gradient-driven gyrokinetic system in simple geometry

We present a new method for formulating closures that learn from kinetic simulation data. We apply this method to phase mixing in a simple gyrokinetic turbulent system – temperature-gradient-driven turbulence in an unsheared slab. The closure, called the learned multi-mode (LMM) closure, is constructed by, first, extracting an optimal basis from a nonlinear kinetic simulation using singular value decomposition. Subsequent nonlinear fluid simulations are projected onto this basis and the results are used to formulate the closure. We compare the closure with other closures schemes over a broad range of the relevant two-dimensional parameter space (collisionality and gradient drive). We find that the turbulent kinetic system produces phase-mixing rates much lower than the linear expectations, which the LMM closure is capable of capturing. We also compare radial heat fluxes. A Hammett–Perkins closure, generalized to include collisional effects, is quite successful throughout the parameter space, producing ${\sim }14\,\%$ root-mean-square (r.m.s.) error. The LMM closure is also very effective: when trained at three (two) points (in a 35 point parameter grid), the LMM closure produces $8\,\%$ ( $12\,\%$ ) r.m.s. errors. The LMM procedure can be readily generalized to other closure problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Using an Advanced Distribution Management System Test Bed to Evaluate the Impact of Model Quality on Volt/VAR Optimization: Preprint

In this paper, we present a test bed for evaluating existing and future advanced distribution management system (ADMS) applications in a realistic laboratory setting, including other utility management systems and field equipment. We present an example of using it to evaluate the impact of the ADMS network model quality on a Volt/VAR optimization (VVO) application. The test bed integrates a commercial ADMS with a real-time simulation model of a utility distribution feeder. Representative power and controller hardware are integrated through hardware-in-the-loop (HIL) techniques. The performance of the ADMS VVO application is also evaluated for different levels of measurement density. Initial results indicate that a higher model quality achieves the highest possible energy savings while avoiding voltage violations, whereas a lower model quality results in increased energy savings but at the expense of more voltage violations.

ADMS↗
DOE OSTI2017

Challenges in reducing the computational time of QSTS simulations for distribution system analysis.

The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modelling and impact analysis. Unlike conventional scenario - based studies , quasi - static time - series (QSTS) simulation s can realistically model time - dependent voltage controllers and the diversity of potential impacts that can occur at different times of year . However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1 - second resolution is often required , which could take conventional computers a computational time of 10 to 120 hours when an actual unbalanced distribution feeder is modeled . This computational burden is a clear l imitation to the adoption of QSTS simulation s in interconnection studies and for determining optimal control solutions for utility operations . Our ongoing research to improve the speed of QSTS simulation has revealed many unique aspects of distribution system modelling and sequential power flow analysis that make fast QSTS a very difficult problem to solve. In this report , the most relevant challenges in reducing the computational time of QSTS simulations are presented: number of power flows to solve, circuit complexity, time dependence between time steps, multiple valid power flow solutions, controllable element interactions, and extensive accurate simulation analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗