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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Parameter estimation for distributed parameter models of complex, flexible structures

Distributed parameter modeling of structural dynamics has been limited to simple spacecraft configurations because of the difficulty of handling several distributed parameter systems linked at their boundaries. Although there is other computer software able to generate such models or complex, flexible spacecraft, unfortunately, neither is suitable for parameter estimation. Because of this limitation the computer software PDEMOD is being developed for the express purposes of modeling, control system analysis, parameter estimation and structure optimization. PDEMOD is capable of modeling complex, flexible spacecraft which consist of a three-dimensional network of flexible beams and rigid bodies. Each beam has bending (Bernoulli-Euler or Timoshenko) in two directions, torsion, and elongation degrees of freedom. The rigid bodies can be attached to the beam ends at any angle or body location. PDEMOD is also capable of performing parameter estimation based on matching experimental modal frequencies and static deflection test data. The underlying formulation and the results of using this approach for test data of the Mini-MAST truss will be discussed. The resulting accuracy of the parameter estimates when using such limited data can impact significantly the instrumentation requirements for on-orbit tests.

Taylor, Lawrence W., Jr.↗
NASA NTRS2017

Coupled Data Assimilation for Integrated Earth System Analysis and Prediction: Goals, Challenges, and Recommendations

The purpose of this report is to identify fundamental issues for coupled data assimilation (CDA), such as gaps in science and limitations in forecasting systems, in order to provide guidance to the World Meteorological Organization (WMO) on how to facilitate more rapid progress internationally. Coupled Earth system modeling provides the opportunity to extend skillful atmospheric forecasts beyond the traditional two-week barrier by extracting skill from low-frequency state components such as the land, ocean, and sea ice. More generally, coupled models are needed to support seamless prediction systems that span timescales from weather, subseasonal to seasonal (S2S), multiyear, and decadal. Therefore, initialization methods are needed for coupled Earth system models, either applied to each individual component (called Weakly Coupled Data Assimilation - WCDA) or applied the coupled Earth system model as a whole (called Strongly Coupled Data Assimilation - SCDA). Using CDA, in which model forecasts and potentially the state estimation are performed jointly, each model domain benefits from observations in other domains either directly using error covariance information known at the time of the analysis (SCDA), or indirectly through flux interactions at the model boundaries (WCDA). Because the non-atmospheric domains are generally under-observed compared to the atmosphere, CDA provides a significant advantage over single-domain analyses. Next, we provide a synopsis of goals, challenges, and recommendations to advance CDA: Goals: (a) Extend predictive skill beyond the current capability of NWP (e.g. as demonstrated by improving forecast skill scores), (b) produce physically consistent initial conditions for coupled numerical prediction systems and reanalyses (including consistent fluxes at the domain interfaces), (c) make best use of existing observations by allowing observations from each domain to influence and improve the full earth system analysis, (d) develop a robust observation-based identification and understanding of mechanisms that determine the variability of weather and climate, (e) identify critical weaknesses in coupled models and the earth observing system, (f) generate full-field estimates of unobserved or sparsely observed variables, (g) improve the estimation of the external forcings causing changes to climate, (h) transition successes from idealized CDA experiments to real-world applications. Challenges: (a) Modeling at the interfaces between interacting components of coupled Earth system models may be inadequate for estimating uncertainty or error covariances between domains, (b) current data assimilation methods may be insufficient to simultaneously analyze domains containing multiple spatiotemporal scales of interest, (c) there is no standardization of observation data or their delivery systems across domains, (d) the size and complexity of many large-scale coupled Earth system models makes it is difficult to accurately represent uncertainty due to model parameters and coupling parameters, (e) model errors lead to local biases that can transfer between the different Earth system components and lead to coupled model biases and long-term model drift, (e) information propagation across model components with different spatiotemporal scales is extremely complicated, and must be improved in current coupled modeling frameworks, (h) there is insufficient knowledge on how to represent evolving errors in non-atmospheric model components (e.g. as sea ice, land and ocean) on the timescales of NWP.

CDA↗
DOE OSTI2025

A Comparative Study of Physics‐Informed and Data‐Driven Neural Networks for Compound Flood Simulation at River‐Ocean Interfaces: A Case Study of Hurricane Irene

Simulating compound flooding (CF) at the river-ocean interface within large-scale Earth System Models (ESMs) presents significant challenges due to complex interactions between river discharge, storm surge, and tides. This study assesses the comparative advantages of physics-informed and data-driven machine learning (ML) approaches for enhancing local ESM performance. We systematically compare data-driven neural network models (i.e., CNNs, U-Net, Long Short-Term Memory (LSTM), Gated Recurrent Unit), and physics-informed neural network (PINN) models, including vanilla PINN and a finite-difference-based PINN (FD-PINN). Specifically, FD-PINN is introduced to enhance computational efficiency, accelerating vanilla PINNs by ∼6.5 times while improving accuracy. To enhance data-driven model training, a new data-generation approach is developed to sample historical fluvial and coastal flood events, which ensures a robust data set for extreme event prediction. The models are evaluated using a realistic one-dimensional river domain extracted from an ESM's river mesh and the Hurricane Irene event as an independent test case. Results show that FD-PINN achieves accurate predictions with significantly reduced computational costs relative to vanilla PINNs. Among data-driven models, the best overall performance is achieved by a CNN-LSTM hybrid, which balances accuracy and efficiency. While a fully connected CNN (CNN-FC) provides the best accuracy, it incurs high computational cost. Architectures lacking strong temporal modeling tend to underperform on unseen events. These findings highlight the importance of sequence-aware designs for robust generalization. This study reveals the trade-offs between physics-informed and data-driven models and proposes an adaptive hybrid framework for integrating ML into ESMs to enhance local flood simulations.

Earth Systems Modeling↗
NASA NTRSDate not supplied

Evaluating the Utility of Pressure Scanners for Unsteady Pressure Measurements in Wind Tunnel Characterization of the Space Launch System

In many aerodynamic measurement applications, the ability to make time-accurate measurements with pressure scanners provides practical advantages over making the same measurements directly using flush-mounted transducers. The pneumatic distortion due to the tubing between the sensing module and surface port limits the usefulness of such measurements to averaged, steady data only. This issue has restricted the application of pressure scanners for unsteady pressure measurements in wind tunnel and flight-testing applications. The Wiener-filtered inverse system response model has been proven to be effective in reconstructing complex unsteady pressure signals acquired remotely using pressure scanners. In this work, the feasibility of using pressure scanning systems for time-resolved pressure measurements in the NASA Langley 14- by 22-Foot Subsonic Wind Tunnel was evaluated. Results demonstrated good agreement between the reference transducers and reconstructed pressure scanner measurements up to frequencies of approximately 500 Hz.

Unsteady pressure↗
NASA NTRS1967

System automatically provides dynamic launch decision criteria

Saturn 5 Dynamic Launch Decision Criteria model provides instantaneous criteria, derived from the parametric behavior of a complex system such as a space launch vehicle plus its payload, for the decision making of launch management personnel.

Doig, J. E.↗
NASA NTRS1999

Cellular Decomposition Based Hybrid-Hierarchical Control Systems with Applications to Flight Management Systems

The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.

Caines, P. E.↗
NASA NTRS2012

Architecting the Human Space Flight Program with Systems Modeling Language (SysML)

The next generation of missions in NASA's Human Space Flight program focuses on the development and deployment of highly complex systems (e.g., Orion Multi-Purpose Crew Vehicle, Space Launch System, 21st Century Ground System) that will enable astronauts to venture beyond low Earth orbit and explore the moon, near-Earth asteroids, and beyond. Architecting these highly complex system-of-systems requires formal systems engineering techniques for managing the evolution of the technical features in the information exchange domain (e.g., data exchanges, communication networks, ground software) and also, formal correlation of the technical architecture to stakeholders' programmatic concerns (e.g., budget, schedule, risk) and design development (e.g., assumptions, constraints, trades, tracking of unknowns). This paper will describe how the authors have applied System Modeling Language (SysML) to implement model-based systems engineering for managing the description of the End-to-End Information System (EEIS) architecture and associated development activities and ultimately enables stakeholders to understand, reason, and answer questions about the EEIS under design for proposed lunar Exploration Missions 1 and 2 (EM-1 and EM-2).

scheduling↗
DOE OSTI2024

Reduced-dimension Bayesian optimization for model calibration of transient vapor compression cycles

Development and calibration of first-principles dynamic models of vapor compression cycles (VCCs) is of critical importance for applications that include control design and fault detection and diagnostics. Nevertheless, the inherent complexity of models that are represented by large systems of differential–algebraic equations leads to significant challenges for model calibration processes that utilize classical gradient-based methods. Bayesian optimization (BO) is a sample-efficient and gradient-free approach using a probabilistic surrogate model and optimal search over a feasible parameter space. Despite the benefits of BO in reducing computational costs, challenges remain in dealing with a high-dimensional calibration task resulting from a large set of parameters that have significant impacts on system behavior and need to be calibrated simultaneously. This paper presents a reduced-dimension BO framework for calibrating transient VCCs models where the calibration space is projected to a low-dimensional subspace for accelerating convergence of the solution algorithm and consequently reducing the number of transient simulations. The proposed approach was demonstrated via two case studies associated with different VCC applications where 10 parameters were calibrated in each case using laboratory measurements. The reduced-dimension BO framework only required 1 / 8 th of the iterations associated with a standard BO method that deals with high-dimensional calibration parameters for converged solutions and yielded comparable accuracy. Furthermore, both calibrated models revealed significant accuracy improvements compared to uncalibrated models.

Ma, Jiacheng↗
DOE OSTI2025

A fully-integrated lattice Boltzmann method for fluid–structure interaction

Here we present a fully-integrated lattice Boltzmann (LB) method for fluid–structure interaction (FSI) simulations that efficiently models deformable solids in complex suspensions and active systems. Our Eulerian method (LBRMT) couples finite-strain solids to the LB fluid on the same fixed computational grid with the reference map technique (RMT). An integral part of the LBRMT is a new LB boundary condition for moving deformable interfaces across different densities. With this fully Eulerian solid–fluid coupling, the LBRMT is well-suited for parallelization and simulating multi-body contact without remeshing or extra meshes. We validate its accuracy via a benchmark of a deformable solid in a lid-driven cavity, then showcase its versatility through examples of soft solids rotating and settling. The LBRMT achieves a spatial convergence rate between first-order and second-order for FSI simulations and is designed for low to intermediate Reynolds number flows with finite inertia at small Mach numbers. With simulations of complex suspensions mixing, we highlight the potential of the LBRMT for studying collective behavior in soft matter and biofluid dynamics.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Computerized structural sizing at NASA Langley Research Center

Programs at the NASA Langley Research Center associated with the development of computerized structural sizing technology are reviewed. Particular attention is given to (1) lightweight columns for space structure applications, (2) stiffened composite panels for aerospace structures, (3) thermal structures for high-speed aircraft and space vehicles, (4) structural sizing methodology for finite-element structural models, (5) the sizing of large complex structural systems in multidisciplinary environments. Improvements to computational efficiency are noted with reference to a reduced number of sizing variables, a reduced number of constraints, and improved sizing algorithms.

Stroud, W. J.↗
NASA NTRS1993

Fault management for data systems

Issues related to automating the process of fault management (fault diagnosis and response) for data management systems are considered. Substantial benefits are to be gained by successful automation of this process, particularly for large, complex systems. The use of graph-based models to develop a computer assisted fault management system is advocated. The general problem is described and the motivation behind choosing graph-based models over other approaches for developing fault diagnosis computer programs is outlined. Some existing work in the area of graph-based fault diagnosis is reviewed, and a new fault management method which was developed from existing methods is offered. Our method is applied to an automatic telescope system intended as a prototype for future lunar telescope programs. Finally, an application of our method to general data management systems is described.

Boyd, Mark A.↗
NASA NTRS1995

Minimum fan turbine inlet temperature mode evaluation

Measured reductions in turbine temperature which resulted from the application of the F-15 performance seeking control (PSC) minimum fan turbine inlet temperature (FTIT) mode during the dual-engine test phase is presented as a function of net propulsive force and flight condition. Data were collected at altitudes of 30,000 and 45,000 feet at military and partial afterburning power settings. The FTIT reductions for the supersonic tests are less than at subsonic Mach numbers because of the increased modeling and control complexity. In addition, the propulsion system was designed to be optimized at the mid supersonic Mach number range. Subsonically at military power, FTIT reductions were above 70 R for either the left or right engines, and repeatable for the right engine. At partial afterburner and supersonic conditions, the level of FTIT reductions were at least 25 R and as much as 55 R. Considering that the turbine operates at or very near its temperature limit at these high power settings, these seemingly small temperature reductions may significantly lengthen the life of the turbine. In general, the minimum FTIT mode has performed well, demonstrating significant temperature reductions at military and partial afterburner power. Decreases of over 100 R at cruise flight conditions were identified. Temperature reductions of this magnitude could significantly extend turbine life and reduce replacement costs.

Orme, John S.↗
NASA NTRS1995

Maximum thrust mode evaluation

Measured reductions in acceleration times which resulted from the application of the F-15 performance seeking control (PSC) maximum thrust mode during the dual-engine test phase is presented as a function of power setting and flight condition. Data were collected at altitudes of 30,000 and 45,000 feet at military and maximum afterburning power settings. The time savings for the supersonic acceleration is less than at subsonic Mach numbers because of the increased modeling and control complexity. In addition, the propulsion system was designed to be optimized at the mid supersonic Mach number range. Recall that even though the engine is at maximum afterburner, PSC does not trim the afterburner for the maximum thrust mode. Subsonically at military power, time to accelerate from Mach 0.6 to 0.95 was cut by between 6 and 8 percent with a single engine application of PSC, and over 14 percent when both engines were optimized. At maximum afterburner, the level of thrust increases were similar in magnitude to the military power results, but because of higher thrust levels at maximum afterburner and higher aircraft drag at supersonic Mach numbers the percentage thrust increase and time to accelerate was less than for the supersonic accelerations. Savings in time to accelerate supersonically at maximum afterburner ranged from 4 to 7 percent. In general, the maximum thrust mode has performed well, demonstrating significant thrust increases at military and maximum afterburner power. Increases of up to 15 percent at typical combat-type flight conditions were identified. Thrust increases of this magnitude could be useful in a combat situation.

Orme, John S.↗
NASA NTRS1995

Acceleration techniques for dependability simulation

As computer systems increase in complexity, the need to project system performance from the earliest design and development stages increases. We have to employ simulation for detailed dependability studies of large systems. However, as the complexity of the simulation model increases, the time required to obtain statistically significant results also increases. This paper discusses an approach that is application independent and can be readily applied to any process-based simulation model. Topics include background on classical discrete event simulation and techniques for random variate generation and statistics gathering to support simulation.

Barnette, James David↗
NASA NTRS1999

Reinforcement Learning in a Nonstationary Environment: The El Farol Problem

This paper examines the performance of simple learning rules in a complex adaptive system based on a coordination problem modeled on the El Farol problem. The key features of the El Farol problem are that it typically involves a medium number of agents and that agents' pay-off functions have a discontinuous response to increased congestion. First we consider a single adaptive agent facing a stationary environment. We demonstrate that the simple learning rules proposed by Roth and Er'ev can be extremely sensitive to small changes in the initial conditions and that events early in a simulation can affect the performance of the rule over a relatively long time horizon. In contrast, a reinforcement learning rule based on standard practice in the computer science literature converges rapidly and robustly. The situation is reversed when multiple adaptive agents interact: the RE algorithms often converge rapidly to a stable average aggregate attendance despite the slow and erratic behavior of individual learners, while the CS based learners frequently over-attend in the early and intermediate terms. The symmetric mixed strategy equilibria is unstable: all three learning rules ultimately tend towards pure strategies or stabilize in the medium term at non-equilibrium probabilities of attendance. The brittleness of the algorithms in different contexts emphasize the importance of thorough and thoughtful examination of simulation-based results.

Bell, Ann Maria↗
NASA NTRS2004

Progressive Response Surfaces

Response surface functions are often used as simple and inexpensive replacements for computationally expensive computer models that simulate the behavior of a complex system over some parameter space. Progressive response surfaces are ones that are built up progressively as global information is added from new sample points in the parameter space. As the response surfaces are globally upgraded based on new information, heuristic indications of the convergence of the response surface approximation to the exact (fitted) function can be inferred. Sampling points can be incrementally added in a structured fashion, or in an unstructured fashion. Whatever the approach, at least in early stages of sampling it is usually desirable to sample the entire parameter space uniformly. At later stages of sampling, depending on the nature of the quantity being resolved, it may be desirable to continue sampling uniformly over the entire parameter space (Progressive response surfaces), or to switch to a focusing/economizing strategy of preferentially sampling certain regions of the parameter space based on information gained in early stages of sampling (Adaptive response surfaces). Here we consider Progressive response surfaces where a balanced indication of global response over the parameter space is desired.We use a variant of Moving Least Squares to fit and interpolate structured and unstructured point sets over the parameter space. On a 2-D test problem we compare response surface accuracy for three incremental sampling methods: Progressive Lattice Sampling; Simple-Random Monte Carlo; and Halton Quasi-Monte-Carlo sequences. We are ultimately after a system for constructing efficiently upgradable response surface approximations with reliable error estimates.

Romero, V. J.↗