Analytical solution of the peak bending moment of an M boom for membrane deployable structures
Not Available
Yang, Hui (ORCID:000000032014598X)↗
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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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Prediction and Optimization of Truss Performance for Lightweight Intelligent Packaging and Deployable Structures
Goal: create an efficient computational tool capable of predicting the complex, nonlinear response of truss lattices containing extremely Iarge numbers of beams and nodes.
97 MATHEMATICS AND COMPUTING↗
ADDRESSING TECHNICAL AND REGULATORY REQUIREMENTS TO DEPLOY STRUCTURAL HEALTH MONITORING SYSTEMS ON COMMERCIAL AIRCRAFT.
Abstract not provided.
Roach, Dennis P.↗
Extremely Lightweight Optical Structures for Rapid Deployment
The structures that surround and support optical components play a key role in the performance of the overall optical system. For aerospace applications, creating an opto-mechanical structure that is athermal, lightweight, robust, and can be quickly developed from concept through to hardware is challenging. This project demonstrates a design and fabrication method for optical structures using origami-style folded, photo-etched sheetmetal pieces that are micro-welded to each other or to 3d printed metal components. Thin flexures, critical for athermal mounting of optics, can be thinner with sheetmetal than from standard machining, which leads to more compact designs and the ability to mount smaller optics. Building a structure by starting with the thinnest features, then folding that thin material to make the ''thicker'' sections is the opposite of standard machining (cutting thin features from thicker blocks). A design method is shown with mass savings of >90%, and stiffness to weight ratio improvements of 5x to 10x compared to standard methods for space systems hardware. Designs and processes for small, flexured, actively aligned systems are demonstrated as are methods for producing lightweight, structural, Miura-core sandwich panels in both flat and curved configurations. Concepts for deployable panels and component hinges are explored, as is a lens subcell with tunable piston movement with temperature change and an ultralight sunshade.
42 ENGINEERING↗
Influence on Structural Loading of a Wave Energy Converter by Controlling Variable-Geometry Components and the Power Take-Off: Preprint
Oceans are a harsh environment and can impose significant loads on deployed structures. Deployment of wave energy converters (WECs) faces a design challenge with apparently contradictory goals. A WEC should be designed to maximize the energy absorbed while ensuring the operating wave condition does not exceed the failure limits of the device itself. Therefore, the loads endured by the support structure are a design constraint for the system. Adaptability to different sea states is, therefore, highly desirable. This work uses a WEC-Sim model of a Variable Geometry Oscillating Wave Energy Converter (VGOSWEC) mounted on a support structure simulated under different wave scenarios. A VGOSWEC resembles a paddle pitching about a fixed hinge perpendicular to the incoming waves-fronts. Therefore, the hinge experiences loads perpendicular to its axis as it maintains its position. The geometry of the VGOSWEC was varied by opening a series of controllable flaps on the pitching paddle when the structure experiences threshold loads. Since opening the flaps lets the waves transmit through the paddle, it is hypothesized that opening the flaps should result in load shedding at the base of the support structure. This load shedding is achieved by reducing the moments about the hinge axis. This work compares the hydrodynamic coefficients, natural periods, and Response Amplitude Operators (RAOs) from completely closed to completely open configurations of the controllable flaps. These comparisons quantify the effects of letting the waves transmit through the VGOSWEC. This work shows that the completely open configuration can reduce the pitch and surge loads on the base of the support structure by as much as 80%. It was observed that at the paddle's resonance frequency, the loads on the structure increased substantially. This increase in loads can be mitigated by a rotational Power Take-off (PTO) damping about the hinge axis. Changing the rotational PTO damping was identified as an additional design parameter that can be used to control the loads experienced by the WEC's support structure.
fixed and floating structures↗
Influence on Structural Loading of a Wave Energy Converter by Controlling Variable-Geometry Components and the Power Take-Off
Oceans are harsh environments and can impose significant loads on deployed structures. The deployment of wave energy converters (WECs) faces a design challenge with apparently contradictory goals. A WEC should be designed to maximize the energy absorbed while ensuring the operating wave condition does not exceed the failure limits of the device itself. Therefore, the loads endured by the support structure are a design constraint for the system. Adaptability to different sea states is, therefore, highly desirable. This work uses a WEC-Sim model of a variable-geometry oscillating wave energy converter (VGOSWEC) mounted on a support structure simulated under different wave scenarios. A VGOSWEC resembles a paddle pitching about a fixed hinge perpendicular to the incoming wave fronts. Therefore, the hinge experiences loads perpendicular to its axis as it maintains its position. The geometry of the VGOSWEC is varied by opening a series of controllable flaps on the pitching paddle when the structure experiences threshold loads. Because opening the flaps lets the waves transmit through the paddle, it is hypothesized that opening the flaps should result in load shedding at the base of the support structure. The load shedding is achieved by reducing the moments about the hinge axis. This work compares the hydrodynamic coefficients, natural periods, and response amplitude operators from completely closed to completely open configurations of the controllable flaps. The comparisons quantify the effects of letting the waves transmit through the VGOSWEC. This work shows that the completely open configuration can reduce the pitch and surge loads on the base of the support structure by as much as 80%. It was observed that at the paddle's resonance frequency, the loads on the structure increased substantially. This increase in loads can be mitigated by a rotational power take-off damping about the hinge axis. Changing the rotational power take-off damping was identified as an additional design parameter that can be used to control the loads experienced by the WEC's support structure.
fixed and floating structures↗
A Probabilistic Reasoner Based on Bayes Risk for Damage Detection in Structural Systems
Structural health monitoring (SHM) systems are used to inform operation of structural systems subject to loads and environments that may affect their integrity. SHM systems rely on continuous monitoring of the structure to determine its health state. These systems are often coupled with a model of the deployed structure to determine the consequences of changes in the system by forecasting the response to future states. These models, which may be thought of as digital twins, need to be updated to reflect the latest state of the structural system. This work makes use of an uncertainty-aware machine learning model that enforces distance preservation of the original input space to determine deviations from the training data input space distributions. This workflow enables domain shift detection to determine whether damage is present in the structure. The uncertainty metrics generated by this network are then used in a Bayes risk framework to design an optimal damage detector given cost and risk considerations. The approach is demonstrated on a computational example with simulated damage.
Najera-Flores, David [ATA Engineering, Inc.]↗
Influence on Structural Loading of a Wave Energy Converter by Controlling Variable-Geometry Components and the Power Take-Off
Oceans are harsh environments and can impose significant loads on deployed structures. A wave energy converter (WEC) should be designed to maximize the energy absorbed while ensuring the operating wave condition does not exceed the failure limits of the device itself. Therefore, the loads endured by the support structure are a design constraint for the system. Furthermore, the WEC should be adaptable to different sea states. Herethis work uses a WEC-Sim model of a variable-geometry oscillating wave energy converter (VGOSWEC) mounted on a support structure simulated under different wave scenarios. A VGOSWEC resembles a paddle pitching about a fixed hinge perpendicular to the incoming wave fronts. The geometry of the VGOSWEC is varied by opening a series of controllable flaps on the pitching paddle when the structure experiences threshold loads. It is hypothesized that opening the flaps should result in load shedding at the base of the support structure by reducing the moments about the hinge axis. This work compares the hydrodynamic coefficients, natural periods, and response amplitude operators from completely closed to completely open configurations of the controllable flaps. This work shows that the completely open configuration can reduce the pitch and surge loads on the base of the support structure by as much as 80%. Increased loads at the structure’s natural period can be mitigated by an axial power take-off damping acting as an additional design parameter to control the loads at the WEC’s support structure.
16 TIDAL AND WAVE POWER↗
2.2.1.410 - Significant Cost Reduction Potential for Wave Energy Conversion Devices with Variable-Geometry Modules
The Technology Commercialization Fund (TCF) award is built upon NREL's previous research exploring a bottom-fixed variable-geometry oscillating surge wave energy converter (VGOSWEC); however, unlike previous investigations, the VGOSWEC will be raised off the sea floor. Researchers believe that advances in offshore pilings and foundations, such as 3D printing, will provide low cost and easily deployable structures. There are several benefits to designing a raised VGOSWEC such as 1) reducing issues with sediment transport and environmental impacts near shore, 2) less expensive deployment and installation as work boats will not risk grounding in shallow water, and 3) deeper water deployments improve the wave resource.
oscillating surge wave energy converter↗
From Bricks to Clicks: Mapping the White Space in Building Innovation
It is a critical national imperative to transform the buildings sector, yet innovation is impeded by deployment failures that leave promising technologies stranded. Conventional market reports and techno-economic analysis provide an insufficient understanding of markets and resource allocation for emerging building technologies. They omit crucial commercialization factors such as ecosystem maturity and adoption friction, where the coordinated participation of a network of suppliers, contractors, financiers, regulators, and integrators is required to scale solutions. This study addresses these gaps by introducing an evaluation framework grounded in front-line data from six years of the DOE's IMPEL incubator, comprising experience from 300 building-sector innovators and the adjacent, complex ecosystem. Our methodology synthesizes top-down market analysis with bottom-up, practitioner-level data across five megatrends: (M1) Affordable materials and industrialized construction; (M2) Healthy and efficient mechanical systems; (M3) Intelligent building operations; (M4) Buildings as grid assets; and (M5) High-density power and cooling for data centers and therein identify twelve "white space" technology opportunities. Next, we develop a multi-criteria scoring rubric to rank these opportunities based on parameters, i.e., Affordability, Quality of Life, Reliability, and Security, yielding composite ‘Demand’ and ‘Maturity’ indices. Our results indicate that the most significant white spaces may not be incremental products but a new class of ‘Ecosystem Enablers’, such as logistics platforms, orchestration layers, and automated compliance software that solve structural deployment gaps. This paper summarizes this transparent, evidence-based, practitioner-informed evaluation framework for policymakers and investors to re-evaluate policy and resource allocation and unlock scalable market transformation.
Singh, Reshma↗
Multivascular networks and functional intravascular topologies within biocompatible hydrogels
Solid organs transport fluids through distinct vascular networks that are biophysically and biochemically entangled, creating complex three-dimensional (3D) transport regimes that have remained difficult to produce and study. We establish intravascular and multivascular design freedoms with photopolymerizable hydrogels by using food dye additives as biocompatible yet potent photoabsorbers for projection stereolithography. We demonstrate monolithic transparent hydrogels, produced in minutes, comprising efficient intravascular 3D fluid mixers and functional bicuspid valves. We also elaborate entangled vascular networks from space-filling mathematical topologies and explore the oxygenation and flow of human red blood cells during tidal ventilation and distension of a proximate airway. Moreover, we deploy structured biodegradable hydrogel carriers in a rodent model of chronic liver injury to highlight the potential translational utility of this materials innovation.
59 BASIC BIOLOGICAL SCIENCES↗
Fiber Optic Sensor for Corrosion Monitoring in Molten Salt Irradiation Experiments
Molten salt reactors (MSRs) are one of the more promising advanced reactor concepts because they offer passive safety, high-temperature process heat, and the potential for improved fuel cycle economics through online reprocessing [1]. However, before MSRs can be reliably deployed, structural materials must be identified that can survive extended exposure to highly-corrosive salts during irradiation at high temperatures. The U.S. Department of Energy (DOE) is funding the design and eventual construction of a Versatile Test Reactor (VTR) that will include experimental facilities for testing under conditions representative of several advanced reactors, including MSRs [2]. These facilities will allow testing of candidate structural materials during irradiation with flowing salt. If properly designed, these experiments will allow for post-irradiation characterization of weight loss in the structural material coupons. However, significantly more information could be gained if the corrosion could be monitored in situ.There are currently no commercially available sensors for in situ corrosion monitoring at temperatures in the range of 500–900°C [3]. An in situ corrosion sensor would also have to survive high-dose neutron irradiation and extended exposure chemically aggressive media (e.g., molten salts). While there are ongoing efforts to use the change in magnetic susceptibility of Cr-containing alloys, this technique is limited to Cr-containing structural materials and there are concerns when using a magnetic susceptibility sensor at temperatures approaching the Curie temperature of iron (770°C) [4].
Petrie, Christian M.↗
Structural Characterization of Deployed Thermoplastic and Thermoset Composite Tidal Turbine Blades
The National Renewable Energy Laboratory worked with Verdant Power to manufacture, and characterize, novel thermoplastic composite blades on their Gen5d 5 m diameter turbines at the Roosevelt Island Tidal Energy (RITE) site in the East River in N.Y. to demonstrate a low-cost manufacturing process for marine energy structures. Verdant had designed, manufactured, and deployed epoxy thermoset composite blades on three Gen5d turbines in October 2020. At a maintenance cycle in May 2021, a Gen5d turbine equipped with the NREL thermoplastic blades was deployed and retrieved in October 2021. Modal, static and fatigue structural characterization was performed on both blade types before and after the deployment. The static and modal test results showed that the thermoplastic blades were slightly stiffer than the epoxy blades both dry and after the deployment. The epoxy blades had about 8% increase in strain at the applied load after the deployment, whereas the thermoplastic blade strains were not changed significantly. Ultimately the thermoplastic blade failed during fatigue testing due to a crack which is thought to have initiated between the internal foam and the laminate at the location of the internal instrumentation. The Verdant Power Gen5d epoxy blades did not have this internal instrumentation and did not have this failure, performing adequately through the operational period. A lack of design information and fatigue data for both the thermoplastic laminates and the adhesive used means that further work is needed to fully understand his failure and the root cause analysis is ongoing. This paper provides details on the thermoplastic blade manufacturing, materials, test methodology and results.
17 WIND ENERGY↗
Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer
Deep learning has contributed to major advances in the prediction of protein structure from sequence, a fundamental problem in structural bioinformatics. With predictions now approaching the accuracy of crystallographic experiments, and with accelerators like GPUs and TPUs making inference using large models rapid, genome-level structure prediction becomes an obvious aim. Leadership-class computing resources can be used to perform genome-scale protein structure prediction using state-of-the-art deep learning models, providing a wealth of new data for systems biology applications. Here we describe our efforts to efficiently deploy the AlphaFold v.2 program, for full-proteome structure prediction, at scale on the Oak Ridge Leadership Computing Facility's resources, including the Summit supercomputer. We performed inference to produce the predicted structures for 40,526 protein sequences, corresponding to four prokaryotic proteomes and one plant proteome, using under 4,400 total Summit node hours, equivalent to using the majority of the supercomputer for a little over one hour. We also designed an optimized structure refinement that reduced the time for the relaxation stage of the AlphaFold pipeline by over 10X for longer sequences. We demonstrate the types of analyses that can be performed on proteome-scale collections of sequences, including a search for novel quaternary structures and implications for functional annotation.
Gao, Mu↗
Smart material based multilayered microbeam structures for spatial self-deployment and reconfiguration: A residual stress approach
Alleviation of the potentially damaging effects induced by residual stresses was comprehensively investigated in previous research. Here, this paper, however, presents a spatially self-deployable and reconfigurable multilayered microbeam which takes advantage of residual stresses and shape memory effects. Reconfigurable mechanism of a typical four-layered microbeam composed of Pt\Ni 50 Ti 50 \Ni 50 Ti 50 \Pt is introduced, followed by analytical modeling of the maximum distance of the self-deployed gap as functions of variable structural and material parameters, including compressive residual stress in Pt layers and tensile residual stress in Ni 50 Ti 50 layers. Analytical solutions given by the static model agree well with the results obtained via finite element models (FEMs). Fabrication, characterization, and in-situ experiments were carried out to validate the feasibility of deployment of the as-released four-layered microbeam. The maximum distance of the gap was measured to be 41.39 μm at 20 °C, which could be increased to 51.73 μm thanks to controllable reconfiguration driven by shape memory effects. Theoretical analysis of such self-deployment and reconfiguration suggested a tensile residual stress increase by 52 MPa in Ni 50 Ti 50 layers. The multilayered microbeam structure with capabilities of self-deployment and reconfiguration offers great potential for various emerging applications, such as micro robotics, medical drug delivery devices, and intelligent chip scale spacecraft.
36 MATERIALS SCIENCE↗
A Validated Finite Element Modeling Tool for Hydrodynamic Loading and Structural Analysis of Ocean Deployed Macroalgae Farms
The objective of this project was to develop and validate a fine-tuned, 3D computational modeling tool for high-fidelity simulations of macroalgae cultivation and harvest systems. To develop this tool, a full understanding of the geometric, material and hydrodynamic properties associated with farming kelp in exposed environments was necessary. Experiments and numerical modeling were done at increasing scales from 1) tank tests with a 1 m model, 2) to field tests with a 61 m culture line at a sheltered site, 3) to field tests with a 122 m culture line at an exposed site and to 4) a 5- line array at the exposed site with 186 m of culture length. The results of the experimental tank tests yielded a set of hydrodynamic drag-area coefficients for a 1 m aggregate based on densely grown kelp at 16 kg/m with a length up to 3 m as described in Fredriksson et al. This work provided the basis to model kelp as a 1 m aggregate based on in-situ geometric and material properties to include measurements of kelp blade length and width, number of blades, yield per m, material mass density and cantilever tests to obtain modulus of elasticity.
54 ENVIRONMENTAL SCIENCES↗
Uncertainty-Aware, Structure-Preserving Machine Learning Approach for Domain Shift Detection From Nonlinear Dynamic Responses of Structural Systems
Complex structural systems deployed for aerospace, civil, or mechanical applications must operate reliably under varying operational conditions. Structural health monitoring (SHM) systems help ensure the reliability of these systems by providing continuous monitoring of the state of the structure. SHM relies on synthesizing measured data with a predictive model to make informed decisions about structural states. However, these models—which may be thought of as a form of a digital twin—need to be updated continuously as structural changes (e.g., due to damage) arise. We propose an uncertainty-aware machine learning model that enforces distance preservation of the original input state space and then encodes a distance-aware mechanism via a Gaussian process (GP) kernel. The proposed approach leverages the spectral-normalized neural GP algorithm to combine the flexibility of neural networks with the advantages of GP, subjected to structure-preserving constraints, to produce an uncertainty-aware model. This model is used to detect domain shift due to structural changes that cannot be observed directly because they may be spatially isolated (e.g., inside a joint or localized damage). This work leverages detection theory to detect domain shift systematically given statistical features of the prediction variance produced by the model. The proposed approach is demonstrated on a nonlinear structure being subjected to damage conditions. In conclusion, it is shown that the proposed approach is able to rely on distances of the transformed input state space to predict increased variance in shifted domains while being robust to normative changes.
Algorithms↗