Search NASA⌕ Search

SEARCH · Search NASA

Results for “adaptive structures space structures”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Automated Reconfigurable Mission Adaptive Digital Assembly Systems (ARMADAS)

To meet the needs of future deep space exploration, NASA is interested in large-scale hardware systems in the agency’s thrust areas of solar power, communications, habitats and science interests. Scalable in-space assembly of physical systems is critical to massless exploration and in-space reliance goals. The ARMADAS project demonstrates the autonomous assembly of digital materials and structures. This provides automation technologies with potential for meeting long duration and deep space infrastructure needs, such as construction and maintenance of long duration spaceport, surface infrastructure, and habitat scale systems. Project demonstrations to date include a system that can fit into a small satellite-sized payload, which automatically assembles into primary structures, such as a small habitat module or array/antenna, using onboard robotic assemblers.

In Space Assembly↗
NASA NTRS1996

Finite Element Simulation of Smart Structures

Finite element equations representing the behavior of piezoelectric materials when bounded to a typical structure and used as sensors and actuators were developed. Emphasis was placed on generating sensor output equations of piezoelectric sensors and responses of a typical structure bonded with piezoelectric sensors and actuators on the basis of finite element formulation. The model can predict not only structural responses due to both mechanical and electrical loading but also electrical potential due to mechanical or thermal effects. The resulted finite element equations were then used for simple control design and performance evaluation. In the control algorithm, voltages coming out from piezoelectric sensors, which are proportional to strains at sensing locations, are taken as input. The voltages applied to the piezoelectric actuators are used as output. The feasibility of integrating control algorithm with the element routine developed herein and FEAP was demonstrated. In particular, optimal independent modal space control was implemented in a software package on the basis of finite element formulation. A rudimentary finite element-control algorithm package was also developed to evaluate the performance of candidate control laws. A few numerical simulations using the software package developed herein were given. The integrated software package will provide a design tool to address issues such as how adaptive smart systems will scale to a full size aircraft, the amount of piezoelectric materials and the powers needed to actuate it for desired performance. It will also provide a viable new structural control design concept for practical applications in large flexible structures such as aerospace vehicles and aircraft.

Cui, Y. Lawrence↗
DOE OSTI2025

Machine learning approaches for intentional materials engineering

In this article, the development of nanoporous metals and metallic composites through dealloying processes presents significant opportunities in materials engineering. However, designing multicomponent precursor alloys and establishing corresponding processing methods that yield predictable compositions and nanostructures remain a complex challenge. This article explores how machine learning (ML)-augmented computational and experimental methodologies can tackle these challenges by predicting precursor alloy compositions, final nanoporous structures, and mechanical properties, while integrating ML-enabled autonomous experimentation for material design and quantification. We highlight recent advancements in applying ML to nanostructured materials design via dealloying and discuss how techniques from other nanomaterial designs can be adapted for improved control over morphological and compositional outcomes in nanoporous and nanocomposite materials. Furthermore, we explore the role of ML in autonomous synchrotron x-ray experimentation, enabling real-time feedback between modeling and experimental setups. ML-driven approaches to microstructure characterization and mechanical property prediction are also examined, with a focus on modeling and advanced imaging techniques such as three-dimensional nanotomography. Finally, this article outlines future directions for ML-enhanced materials science, emphasizing the exploration of high-dimensional parameter spaces and the incorporation of materials kinetics into processing and property evaluation, ultimately advancing the design of nanoporous structures and materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross-dataset tasks. Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1999

CEAS/AIAA/ICASE/NASA Langley International Forum on Aeroelasticity and Structural Dynamics 1999

The proceedings of a workshop sponsored by the Confederation of European Aerospace Societies (CEAS), the American Institute of Aeronautics and Astronautics (AIAA), the National Aeronautics and Space Administration (NASA), Washington, D.C., and the Institute for Computer Applications in Science and Engineering (ICASE), Hampton, Virginia, and held in Williamsburg, Virginia June 22-25, 1999 represent a collection of the latest advances in aeroelasticity and structural dynamics from the world community. Research in the areas of unsteady aerodynamics and aeroelasticity, structural modeling and optimization, active control and adaptive structures, landing dynamics, certification and qualification, and validation testing are highlighted in the collection of papers. The wide range of results will lead to advances in the prediction and control of the structural response of aircraft and spacecraft.

Woodrow Whitlow, Jr.↗
NASA NTRS1994

Pre-metatarsal skeletal development in tissue culture at unit- and microgravity

Explant organ culture was used to demonstrate that isolated embryonic mouse pre-metatarsal mesenchyme is capable of undergoing a series of differentiative and morphogenetic developmental events. Mesenchyme differentiation into chondrocytes, and concurrent morphogenetic patterning of the cartilage tissue, and terminal chondrocyte differentiation with subsequent matrix mineralization show that cultured tissue closely parallels in vivo development. Whole mount alizarin red staining of the cultured tissue demonstrates that the extracellular matrix around the hypertrophied chondrocytes is competent to support mineralization. Intensely stained mineralized bands are similar to those formed in pre-metatarsals developing in vivo. We have adapted the culture strategy for experimentation in a reduced gravity environment on the Space Shuttle. Spaceflight culture of pre-metatarsals, which have already initiated chondrogenesis and morphogenetic patterning, results in an increase in cartilage rod size and maintenance of rod shape, compared to controls. Older pre-metatarsal tissue, already terminally differentiated to hypertrophied cartilage, maintained rod structure and cartilage phenotype during spaceflight culture.

NASA Discipline Developmental Biology↗
NASA NTRSDate not supplied

Mycotecture Off Planet: Fungi as A Building Material on The Moon and Mars

A turtle carries its own habitat. While reliable, it costs energy and is not easily adapted for the environment. NASA makes the same trade-off when it transports habitats and other structures needed to lunar and planetary surfaces. Astronauts stayed on the lunar surface for up to 75 h (Apollo 17), so the lunar module (LM) could double as a habitat. An example of the “build it on Earth, launch it into space” approach is the Habitat Demonstration Unit (HDU) Deep Space Habitat, developed by the Habitat Systems Project (NASA AES). The hardware consists of a composite fiberglass resin-infused shell attached to eight steel ribs, providing living and working space for a crew of four. Even with the use of advanced materials, it weighs >14,000 kg (~ 466 kg/m2 living space), leading to high launch costs. Upmass and resupply will result in reduced surface operations, greater mission risk, loss of productivity and psychological stress.

L J Rothschild↗
DOE OSTI2023

Projection pursuit adaptation on polynomial chaos expansions

Here, the present work addresses the issue of accurate stochastic approximations in high-dimensional parametric space using tools from uncertainty quantification (UQ). The basis adaptation method and its accelerated algorithm in polynomial chaos expansions (PCE) were recently proposed to construct low-dimensional approximations adapted to specific quantities of interest (QoI). The present paper addresses one difficulty with these adaptations, namely their reliance on quadrature point sampling, which limits the reusability of potentially expensive samples. Projection pursuit (PP) is a statistical tool to find the “interesting” projections in high-dimensional data and thus bypass the curse-of-dimensionality. In the present work, we combine the fundamental ideas of basis adaptation and projection pursuit regression (PPR) to propose a novel method to simultaneously learn the optimal low-dimensional spaces and PCE representation from given data. While this projection pursuit adaptation (PPA) can be entirely data-driven, the constructed approximation exhibits mean-square convergence to the solution of an underlying governing equation and thus captures the supports and probability distributions associated with the physics constraints. The proposed approach is demonstrated on a borehole problem and a structural dynamics problem, demonstrating the versatility of the method and its ability to discover low-dimensional manifolds with high accuracy with limited data. In addition, the method can learn surrogate models for different quantities of interest while reusing the same data set.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2011

Multiclass Continuous Correspondence Learning

We extend the Structural Correspondence Learning (SCL) domain adaptation algorithm of Blitzer er al. to the realm of continuous signals. Given a set of labeled examples belonging to a 'source' domain, we select a set of unlabeled examples in a related 'target' domain that play similar roles in both domains. Using these 'pivot samples, we map both domains into a common feature space, allowing us to adapt a classifier trained on source examples to classify target examples. We show that when between-class distances are relatively preserved across domains, we can automatically select target pivots to bring the domains into correspondence.

correspondence learning↗
NASA NTRS2016

Neural Mechanisms to the Space Environment

Highly conserved neural systems have evolved to sense the inertial forces due to head translation and head tilt relative to gravitational vertical. These structures consist of ciliated mechanosensitive receptor cells inserted into a neuroepithelium surmounted by biomineral grains of calcium carbonate (CaCO3) called oto- (vertebrates) or stato-conia (invertebrates). Detection of these forces by receptor cells relies on the CaCO3 mass being weighted in Earths 1G. A change in gravity or orientation with respect to gravity has a profound effect on how an organism interacts with its environment, and it is evident that the nervous system responds to the new gravity state. This response might involve the peripheral receptors, the CaCO3 mass, the brain or any combination of these mechanisms based on the intensity and duration of the gravity change. Here, we examine the arguments supporting the different mechanisms of adaptation to the space environment. First, a pre- or post-synaptic alteration in the strength of synaptic transmission between the receptor cell and nerve afferent can adjust the system output. The number of synaptic ribbons in certain type II hair cells in rodent is labile, increasing following exposure to microgravity. An increase in number of synaptic ribbons in toadfish otolith hair cells following exposure to microgravity could potentially explain the observed afferent hypersensitivity to acceleration postflight. The physiological findings in the isolated statocyst in snails are in line with the vertebrate data, and conform to the proposition that G exposure leads to changes in gravireceptor function. At the same time this similarity in neural response to G exposure between the vertebrates and invertebrates is intriguing: the increased neural sensitivity in the vertebrate was detected in the nerve afferents, one synapse away from the receptor cell, whereas the increased neural sensitivity observed in the snail was detected directly at the receptor level. Second, the CaCO3 mass provides mechanical loading of receptor cell cilia, and their density alters sensitivity. A widely considered mechanism by which the animal responds to a chronic change in amplitude of gravity is a change in weight-lending CaCO3 mass. In G, it is argued, the organism counters the loss of gravity by increasing CaCO3 production, thereby increasing its mass, as a means to increase system gain. In hypergravity, the converse is argued. Earlier evidence in mollusks and recent results in mice suggest a remodeling might occur, especially after long-term space exposure. Lastly, we have to distinguish at least two kinds of neural feedbacks. One is connected with local mechanisms of self-regulation and specific for initial period of organ development when the neural connections are still absent. And the other feedback is related to neural self-regulation and specific for later stages of the organ development, and includes an efferent vestibular feedback. Complexity of the problem is enhanced by incompleteness of experiments, and consequently the experimental results have not led to a clear interpretation despite the numerous studies.

Boyle, Richard D.↗
DOE OSTI2024

The ReSWARM microgravity flight experiments: Planning, control, and model estimation for on‐orbit close proximity operations

Abstract On‐orbit close proximity operations involve robotic spacecraft maneuvering and making decisions for a growing number of mission scenarios demanding autonomy, including on‐orbit assembly, repair, and astronaut assistance. Of these scenarios, on‐orbit assembly is an enabling technology that will allow large space structures to be built in situ, using smaller building block modules. However, like many of these scenarios, robotic on‐orbit assembly involves several technical hurdles, such as changing system models. For instance, grappled modules moved by a free‐flying “assembler” robot can cause significant changes in the combined system inertia, which have cascading impacts on motion planning and control portions of the autonomy stack. Further, on‐orbit assembly and other scenarios require collision‐avoiding motion planning, particularly when operating in a “construction site” scenario of multiple assembler robots and structures. Multiple key technologies that address these complicating factors for autonomous microgravity close proximity operations are detailed in this work, in particular: (1) application of global long‐horizon planning, accomplished using offline and online sampling‐based planner options that consider the system dynamics; (2) adaptation of the recently proposed RATTLE information‐aware planning framework for on‐orbit reconfiguration model learning; and (3) connection with robust control tools to provide low‐level control robustness using current system knowledge. These approaches were demonstrated for an autonomous on‐orbit assembly use case by the RElative Satellite sWarming and Robotic Maneuvering (ReSWARM) experiments using NASA's Astrobee robots on the International Space Station. Results of the ReSWARM experiments are provided along with significant operational and implementation detail discussing the practicalities of hardware implementation and unique aspects of working with the Astrobee free‐flyer robots in microgravity. ReSWARM provides a base set of planning and control tools for robotic close proximity operations, demonstrates them in microgravity, and outlines some of the important hardware aspects that future autonomous free‐flyers will need to consider.

Robotics↗
DOE OSTI2019

Performance Improvements to the Prototype Design of the AGU

The existing design for the Magnet Structure of the prototype multi-segment AGU (Adaptive- Gap Undulator) has undergone analysis (see TN #298). To optimize performance, after review of said analysis, certain design modifications are proposed herein. A primary constraint of this proposed design is to use the existing fabricated parts from initial assembly SR-ID-SAGU-4300 with three pairs of feed-throughs spaced along the platen length of a single segment, but with foresight for the eventual multi-segment prototype. Measurements of the center segment are to be conducted on the frame and gap-drive system of the NSLS X9 MGU with its single driven axis. The eventual multi-segment prototype will also use the sister devices (X13, X27) for simultaneous measurement of both central and outboard segments at various segment gaps. Criteria effecting IVU performance like Gap Tolerance, Taper Error, and the critical Planarity of pole plane as in Figure 1 are used to evaluate the design. The error in planarity to be minimized is the deviation of vertical displacement (Y direction) with Platen length (beam Z direction).

36 MATERIALS SCIENCE↗
NASA NTRS1999

Integrated Modeling Tools for Thermal Analysis and Applications

Integrated modeling of spacecraft systems is a rapidly evolving area in which multidisciplinary models are developed to design and analyze spacecraft configurations. These models are especially important in the early design stages where rapid trades between subsystems can substantially impact design decisions. Integrated modeling is one of the cornerstones of two of NASA's planned missions in the Origins Program -- the Next Generation Space Telescope (NGST) and the Space Interferometry Mission (SIM). Common modeling tools for control design and opto-mechanical analysis have recently emerged and are becoming increasingly widely used. A discipline that has been somewhat less integrated, but is nevertheless of critical concern for high precision optical instruments, is thermal analysis and design. A major factor contributing to this mild estrangement is that the modeling philosophies and objectives for structural and thermal systems typically do not coincide. Consequently the tools that are used in these discplines suffer a degree of incompatibility, each having developed along their own evolutionary path. Although standard thermal tools have worked relatively well in the past. integration with other disciplines requires revisiting modeling assumptions and solution methods. Over the past several years we have been developing a MATLAB based integrated modeling tool called IMOS (Integrated Modeling of Optical Systems) which integrates many aspects of structural, optical, control and dynamical analysis disciplines. Recent efforts have included developing a thermal modeling and analysis capability, which is the subject of this article. Currently, the IMOS thermal suite contains steady state and transient heat equation solvers, and the ability to set up the linear conduction network from an IMOS finite element model. The IMOS code generates linear conduction elements associated with plates and beams/rods of the thermal network directly from the finite element structural model. Conductances for temperature varying materials are accommodated. This capability both streamlines the process of developing the thermal model from the finite element model, and also makes the structural and thermal models compatible in the sense that each structural node is associated with a thermal node. This is particularly useful when the purpose of the analysis is to predict structural deformations due to thermal loads. The steady state solver uses a restricted step size Newton method, and the transient solver is an adaptive step size implicit method applicable to general differential algebraic systems. Temperature dependent conductances and capacitances are accommodated by the solvers. In addition to discussing the modeling and solution methods. applications where the thermal modeling is "in the loop" with sensitivity analysis, optimization and optical performance drawn from our experiences with the Space Interferometry Mission (SIM), and the Next Generation Space Telescope (NGST) are presented.

Milman, Mark H.↗
NASA NTRS1986

Decentralized control experiments on NASA's flexible grid

Methods arising from the area of decentralized control are emerging for analysis and control synthesis for large flexible structures. In this paper the control strategy involves a decentralized model reference adaptive approach using a variable structure control. Local models are formulated based on desired damping and response time in a model-following scheme for various modal configurations. Variable structure controllers are then designed employing co-located angular rate and position feedback. In this scheme local control forces the system to move on a local sliding mode in some local error space. An important feature of this approach is that the local subsystem is made insensitive to dynamical interactions with other subsystems once the sliding surface is reached. Experiments based on the above have been performed for NASA's flexible grid experimental apparatus. The grid is designed to admit appreciable low-frequency structural dynamics, and allows for implementation of distributed computing components, inertial sensors, and actuation devices. A finite-element analysis of the grid provides the model for control system design and simulation; results of several simulations are reported on here, and a discussion of application experiments on the apparatus is presented.

Ozguner, U.↗
NASA NTRS2003

Electrical-Impedance-Based Ice-Thickness Gauges

Langley Research Center has developed electrical-impedance-based ice-thickness gauges and is seeking partners and collaborators to commercialize them. When used as parts of active monitoring and diagnostic systems, these gauges make it possible to begin deicing or to take other protective measures before ice accretes to dangerous levels. These gauges are inexpensive, small, and simple to produce. They can be adapted to use on a variety of stationary and moving structures that are subject to accumulation of ice. Examples of such structures include aircraft, cars, trucks, ships, buildings, towers, power lines (see figure), power-generating equipment, water pipes, freezer compartments, and cooling coils. A gauge of this type includes a temperature sensor and two or more pairs of electrically insulated conductors embedded in a surface on which ice could accumulate. The electrical impedances of the pairs of conductors vary with the thickness of any ice that may be present. Somewhat more specifically, when the pairs of conductors are spaced appropriately, the ratio between their impedances is indicative of the thickness of the ice. Therefore, the gauge includes embedded electronic circuits that measure the electrical impedances, plus circuits that process the combination of temperature and impedance measurements to determine whether ice is present and, if so, how thick it is. Of course, in the processing of the impedance measurements, the temperature measurements help the circuitry to distinguish between liquid water and ice. The basic design of a gauge of this type can be adapted to local conditions. For example, if there is a need to monitor ice over a wide range of thickness, then the gauge can include more than two sets of conductors having various spacings.

Weinstein, Leonard↗
DOE OSTI2024

Deep Multi-Agent Reinforcement Learning for Real-World Signalized Traffic Corridor Control

Signalized traffic control problem has been addressed recently with deep Reinforcement Learning (RL) approaches involving diverse state, action, and reward structures. While significant progress has been noted in the literature, open challenges still remain in the areas of adaptive signal phase timing, coordination in a multi-intersection corridor setting, and consideration of real-world traffic conditions. In the context of deep RL-based problem framing, extensions are needed that enable adaptive signal phase timings in an intersection agent's action space, computationally efficient information sharing among neighboring signalized intersection agents along a corridor, and experimentation in realistic simulation environments. In this paper, we develop a deep Advantage Actor Critic (A2C) multi-agent RL (MARL) approach capturing the research extensions above and apply it within a real-world calibrated Aimsun Next traffic corridor simulation model based on traffic data from the City of Coral Gables, Florida. For a multi-intersection corridor control setting, our numerical simulation experiments with a decentralized A2C MARL algorithm applied at different time periods led to a total average corridor travel delay reduction (expressed in seconds/mile averaged over vehicles) from 4.9% to 19.9% compared to state-of-the-art actuated control.

Shuvo, Salman S. [BATTELLE (PACIFIC NW LAB)]↗
NASA NTRS1998

Perspective on the impact of weightlessness on calcium and bone metabolism

As humans venture into space to colonize the moon and travel to distant planets in the 21st century, they will be confronted with a bone disease that could potentially limit their space exploration activities or put them at risk for fracture when they return to earth. It is now recognized that an unloading of the skeleton, either due to strict bed rest or in zero gravity, leads on average to a 1%-2% reduction in bone mineral density at selected skeletal sites each month. The mechanism by which unloading of the skeleton results in rapid mobilization of calcium stores from the skeleton is not fully understood, but it is thought to be related to down regulation in PTH and 1,25-dihydroxyvitamin D3 production. Bone modeling and mineralization in chick embryos is not affected by microgravity, suggesting that bone cells adapt and ultimately become addicted to gravity in order to maintain a structurally sound skeleton. Strategies need to be developed to decrease microgravity-induced bone resorption by either mimicking gravity's effect on bone metabolism, or enhancing physically or pharmacologically bone formation in order to preserve astronauts' bone health.

short duration↗
DOE OSTI2025

Ion density waves driving the formation of filamentary dust structures

The PlasmaKristall-4 (PK-4) experiment on the International Space Station allows for the study of the 3-dimensional interaction between plasma and dust particles. Previous simulations of the PK-4 environment have discovered fast moving ionization waves in the dc discharge. These ionization waves vary the plasma parameters by up to an order of magnitude, which may affect the mechanisms responsible for the self-organization of chains seen in the PK-4 experiment. Here, we adapt a molecular dynamics simulation to employ temporally varying plasma conditions in order to investigate the effect on the dust charging and electrostatic potential. In order to describe the differences between the average of the plasma conditions and the time-varying plasma condition, we present a model to reproduce the interaction that takes into account the negative potential from the dust grain and the positive potential from the ion wake.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗