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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Design of Low Complexity Model Reference Adaptive Controllers

Flight research experiments have demonstrated that adaptive flight controls can be an effective technology for improving aircraft safety in the event of failures or damage. However, the nonlinear, timevarying nature of adaptive algorithms continues to challenge traditional methods for the verification and validation testing of safety-critical flight control systems. Increasingly complex adaptive control theories and designs are emerging, but only make testing challenges more difficult. A potential first step toward the acceptance of adaptive flight controllers by aircraft manufacturers, operators, and certification authorities is a very simple design that operates as an augmentation to a non-adaptive baseline controller. Three such controllers were developed as part of a National Aeronautics and Space Administration flight research experiment to determine the appropriate level of complexity required to restore acceptable handling qualities to an aircraft that has suffered failures or damage. The controllers consist of the same basic design, but incorporate incrementally-increasing levels of complexity. Derivations of the controllers and their adaptive parameter update laws are presented along with details of the controllers implementations.

Hanson, Curt↗
NASA NTRS1972

An input adaptive, pursuit tracking model of the human opertor

Developed and evaluated is a simple model of the input adaptive behavior of the human operator (HO) in a pursuit tracking task in which the plant controlled consists of a pure gain. If it is assumed that the HO is approximately an optimal predictor using only position and velocity information, then there is a simple method of computing the values of the model parameters in terms of the autocorrelation function of the input signal. Experimental evidence indicates that the ability of the HO to use velocity information decreases with increasing signal velocity indicating that a biased estimator of the velocity weighting should be used. A suitable approximation is derived which has rapid convergence and low variance. The model thus derived is compared to actual subject transfer functions and is found to be in close agreement. In addition to tracking random processes the model can adapt to and track deterministic signals, such as sine waves, up to approximately the frequency at which human operators begin to track precognitively.

Ware, J. R.↗
DOE OSTI2026

Modeling and Calibration of Supplier Selection Problem in Freight Agent-Based Simulations

Freight transportation modeling often struggles with data limitations, especially in accurately representing complex supplier selection processes and their impact on network flows. This research addresses this critical gap by developing a large-scale, calibrated agent-based model for supplier selection, complemented by a probabilistic heuristic for international shipments. Our approach integrates trade relationships between industry sectors, transportation costs, and a supplier-rating model adapted from existing literature. The model’s core objective is to minimize the discrepancy between modeled and observed commodity flows while ensuring a close match to regional shipping distance distributions. Implemented and tested across four major U.S. metropolitan areas—Atlanta, Chicago, Dallas–Fort Worth, and Los Angeles—the model demonstrates high fidelity in replicating observed freight patterns. Key findings reveal consistent alignment with national shipping distance trends and highlight significant spatial variations in commodity trade assignments and demand across the study regions. This behaviorally informed and transport-sensitive framework is designed to approximate real-world decision making, providing a robust tool for policymakers and planners to evaluate targeted interventions, assess infrastructure investments, and enhance supply chain resilience in the face of disruptions.

Ismael, Abdelrahman (ORCID:0000000303712110)↗
NASA NTRSDate not supplied

High Fidelity Adaptively Refined CFD and Reduced Order Models of a High Aspect Ratio Aeroelastic Wing Wind Tunnel Model

Robust adaptive mesh refinement for transonic conditions is one of the most difficult challenges to advancing CFD usage for certification by analysis. Transonic fluid-structure interaction cases represent an even more difficult challenge for adaptive mesh refinement. Production aircraft furthermore have structural models that have gaps and discontinuities that make the interdomain transfer of loads and deflections difficult. This adds to the challenge of adaptive mesh refinement. An initial attempt to create an adaptive mesh refinement process that refines regions of high flow gradient based around the HeldenMesh software is presented. The method is applied to the Integrated Adaptive Wing Technology Maturation (IAWTM) configuration. That has developed an aspect ratio 13.5 wing aeroelastic wind-tunnel model for testing in the Transonic Dynamics Tunnel (TDT). The high levels of deformation of this wing make the adaptation of meshes for the static shape difficult and has necessitated some creativity in how to efficiently adapt meshes. A time-domain identification of the unsteady system based on flexible modes using the adapted meshes is performed.

Robert E. Bartels↗
NASA NTRS1993

The annual pressure cycle on Mars: Results from the LMD Martian atmospheric general circulation model

We have been developing a General Circulation Model (GCM) of the martian atmosphere since 1989. The model has been described rather extensively elsewhere and only the main characteristics are given here. The dynamical part of the model, adapted from the LMD terrestrial climate model, is based on a finite-difference formulation of the classical 'primitive equations of meteorology.' The radiative transfer code includes absorption and emission by CO2 (carefully validated by comparison to line-by-line calculations) and dust in the thermal range and absorption and scattering by dust in the visible range. Other physical parameterizations are included: modeling of vertical turbulent mixing, dry convective adjustment (in order to prevent vertical unstable temperature profiles), and a multilayer model of the thermal conduction in the soil. Finally, the condensation-sublimation of CO2 is introduced through specification of a pressure-dependent condensation temperature. The atmospheric and surface temperatures are prevented from falling below this critical temperature by condensation and direct precipitation onto the surface of atmospheric CO2. The only prespecified spatial fields are the surface thermal inertia, albedo, and topography.

Hourdin, Frederic↗
NASA NTRS1981

On adaptive regulation of flexible spacecraft

It is pointed out that the regulation of shape and attitude disturbances in large space structures (LSS) using adaptive control remains an actively studied, yet controversial approach, just as adapative control itself. The controversy arises because the utility of many methods of adapatively controlling distributed parameter systems (DPS) is unsubstantiated. However, it appears that adaptive control can be applied to solve problems in LSS control which are not amenable to more common control methods. The present investigation has the objective to clarify the application of adaptive control to LSS. Attention is given to the characteristics of adaptive model control, aspects of simultaneous mode shape adaption, questions of multivariable simultaneous identification and control, and direct adaptive multivariable control.

Lawrence, D. A.↗
NASA NTRS1990

Artificial intelligence techniques for modeling database user behavior

The design and development of the adaptive modeling system is described. This system models how a user accesses a relational database management system in order to improve its performance by discovering use access patterns. In the current system, these patterns are used to improve the user interface and may be used to speed data retrieval, support query optimization and support a more flexible data representation. The system models both syntactic and semantic information about the user's access and employs both procedural and rule-based logic to manipulate the model.

Tanner, Steve↗
NASA NTRS2012

Adaptive Control with Reference Model Modification

This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example

Stepanyan, Vahram↗
DOE OSTI2025

Regional-scale soil carbon predictions can be enhanced by transferring global-scale soil–environment relationships

Accurate modelling and mapping soil organic carbon are crucial for supporting soil health restoration and climate change mitigation at both regional and global scales. However, regional soil predictions often suffer from data scarcity and high prediction uncertainty. Utilizing a pre-trained global-to-regional soil carbon predictive model can be a potential solution to address this challenge. Despite its promise, how to construct and apply the global-scale model to enhance regional-scale soil carbon mapping remains largely unexplored. Here, we propose the Global Soil Carbon Pre-trained Model (GSoilCPM), a deep-learning-based domain adaptative model, to enhance regional-scale soil carbon predictions. Based on large amount of environmental covariate data and 106,167 soil samples across the globe, we verify our hypothesis of the effectiveness of this 'global-to-regional' modelling strategy. The pre-trained model can be then transferred and fine-tuned to bridge the regional- and global-scale soil–environment relationships. We applied and validated this modelling strategy in four regional-scale study areas, three in the Northern Hemisphere and one in the Southern Hemisphere, each with distinct environmental background. Compared to traditional modelling approaches as a baseline, four case studies all demonstrated significant improvement in prediction accuracy across diverse environments and varying data availabilities. The average percentage improvement across all regions is 10.93% (absolute values decreased by 1.20 g kg−1 averagely) in MAE and 29.04% (absolute values increased by 0.10 averagely) in CCC. The applicability and future horizons of using GSoilCPM were further discussed. We further reveal that regions with fewer soil samples or lower baseline accuracy benefit more from the pre-trained global model. Our findings highlight the advantages of leveraging the generalized knowledge from global models to enhance specifically localized soil modelling, positioning a potential paradigm shift in digital soil mapping, and far-reaching implications for soil monitoring and land management.

Deep learning↗
NASA NTRS2008

Overview of NASA's Integrated Design and Engineering Analysis (IDEA)Environment

Historically, the design of subsonic and supersonic aircraft has been divided into separate technical disciplines (such as propulsion, aerodynamics and structures) each of which performs their design and analysis in relative isolation from others. This is possible in most cases either because the amount of interdisciplinary coupling is minimal or because the interactions can be treated as linear. The design of hypersonic airbreathing vehicles, like NASA s X-43, is quite the opposite. Such systems are dominated by strong non-linear interactions between disciplines. The design of these systems demands that a multi-disciplinary approach be taken. Furthermore, increased analytical fidelity at the conceptual design phase is highly desirable as many of the non-linearities are not captured by lower fidelity tools. Only when these systems are designed from a true multi-disciplinary perspective can the real performance benefits be achieved and complete vehicle systems be fielded. Toward this end, the Vehicle Analysis Branch at NASA Langley Research Center has been developing the Integrated Design & Engineering Analysis (IDEA) Environment. IDEA is a collaborative environment for parametrically modeling conceptual and preliminary launch vehicle configurations using the Adaptive Modeling Language (AML) as the underlying framework. The environment integrates geometry, configuration, propulsion, aerodynamics, aerothermodynamics, trajectory, closure and structural analysis into a generative, parametric, unified computational model where data is shared seamlessly between the different disciplines. Plans are also in place to incorporate life cycle analysis tools into the environment which will estimate vehicle operability, reliability and cost. IDEA is currently being funded by NASA s Hypersonics Project, a part of the Fundamental Aeronautics Program within the Aeronautics Research Mission Directorate. The environment is currently focused around a two-stage-to-orbit configuration with a turbine based combined cycle (TBCC) first stage and reusable rocket second stage. This paper provides an overview of the development of the IDEA environment, a description of the current status and detail of future plans.

Robinson, Jeffrey S.↗