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All sources NASA NTRS DOE OSTI

DOE OSTI2024

Dynamic Shaping of Grid Response of Multi-Machine Multi-Inverter Systems Through Grid-Forming IBRs

We consider the problem of controlling the frequency response of weakly-coupled multi-machine multi-inverter low-inertia power systems via grid-forming inverter-based resources (IBRs). In contrast to existing methods, our approach relies on dividing the larger system into multiple strongly-coupled subsystems, without ignoring either the underlying network or approximating the subsystem response as an aggregate harmonic mean model. Rather, through a structured clustering and recursive dynamic shaping approach, the frequency response of the overall system to load perturbations is shaped appropriately. We demonstrate the proposed approach for a three-node triangular configuration and a small-scale radial network. Furthermore, previous synchronization analysis for heterogeneous systems requires the machines to satisfy certain proportionality property. In our approach, the effective transfer functions for each cluster can be tuned by the IBRs to satisfy such property, enabling us to apply the shaping control to systems with a wider range of heterogeneous machines.

frequency-shaping control↗

DOE OSTI2025

Assessing the Heat Transfer Modeling Capabilities of CFD Software for Involute-Shaped Plate Research Reactors

The ongoing efforts to convert High-Performance Research Reactors (HPRRs) using Highly Enriched Uranium (HEU) to Low-Enriched Uranium (LEU) fuel require reliable thermal–hydraulic assessments of modified core designs. The involute-shaped fuel plates used in several major HPRRs present unique modeling challenges due to their compact core geometries and high heat flux conditions. This study evaluates the capability of three commercial CFD tools, STAR-CCM+, COMSOL, and ANSYS CFX, to predict cladding-to-coolant heat transfer using Reynolds-Averaged Navier–Stokes (RANS) methods within the thermal–hydraulic regimes of involute-shaped plate reactors. Broad sensitivity analysis was conducted across a range of reactor-relevant parameters using two turbulence models (k−ϵ and k−ω SST) and different near-wall treatment strategies. The results were benchmarked against the Sieder–Tate correlation and experimental data from historic studies. The codes produced consistent results, showing good agreement with the empirical correlation of Sieder–Tate and the experimental measurements. The findings support the use of these commercial CFD codes as effective tools for assessing the thermal–hydraulic performance of involute-shaped plate HPRRs and guide future LEU core development.

CFD↗

NASA NTRS1999

Three-Lobed Shape Bifurcation of Rotating Liquid Drops

The evolution of axisymmetric equilibrium shapes of a rotating liquid drop can be extended beyond the 2-lobed shape bifurcation point if the rotating drop is driven in the n=2 axisymmetric shape oscillation (perturbation), where n is the mode of oscillation.

Drops Bifurcation Shape Oscillation↗

NASA NTRS1994

(abstract) Asteroid 4769 Casalia: Intrepretation of Optical Lightcurves Using a Radar-Derived Shape Model

A 167-parameter, 3-D shape model of Castalia, obtained from inversion of delay-Doppler images, constrained the object's subradar latitude on the date of the observations by defining an annular sky region that contains Castalia's pole. We have used the shape model and nominal Hapke parameters for S asteroids to model Castalia lightcurves obtained at Table Mountain Observatory on August 23-25, 1989, at solar phase angles ranging from 58(deg) to 90(deg). This investigation defines the projected pole's azimuthal orientation around the radar line of sight and therefore yields a least-squares estimate of the orientation of Castalia's north or south pole; there is insufficient geometric leverage to distinguish the rotation sense or to estimate values of Hapke parameters. The model lightcurves match the TMO data surprisingly well, given the modest number of shape parameters in the model and the fact that part of the asteroid was not seen by the radar.

asteroid Castalia shape radar 3-D model optical li↗

NASA NTRS2005

Medical applications of shape memory polymers

Shape memory polymers are described here and major advantages in some applications are identified over other medical materials such as shape memory alloys (SMA). A number of medical applications are anticipated for shape memory polymers. Some simple applications are already utilized in medical world, others are in examination process. Lately, several important applications are being considered for CHEM foams for self-deployable vascular and coronary devices. One of these potential applications, the endovascular treatment of aneurysm was experimentally investigated with encouraging results and is described in this paper as well.

cold hibernated elastic memory (CHEM)↗

NASA NTRS2004

The Sensitivity of Shaped Pupil Coronagraphs to Optical Aberrations

Unlike focal-plane coronagraphs that use occulting spots and Lyot stops to eliminate diffraction, pupil-plane coronagraphs operate by shaping the pupil to redirect the diffracted stellar light into a tight core. As in focal-plane coronagraphs, the optical aberrations in the telescope must be sufficiently corrected to enable high contrast imaging. However, in shaped-pupil coronagraphs, the low-order aberrations resulting from misalignment and optical figure drift have a much smaller influence upon the contrast at at the inner working angle. These weaker sensitivities greatly relax the strict low-order wavefront stability required for high-contrast imaging the cost of some throughput. In this paper, we present the simulated performance of the concentric ring shaped pupil concepts comparing them to focal-plane coronagraphs that are optimized for the same inner working angles.

extrasolar planets↗

NASA NTRS2002

Onboard Autonomous Rock Shape Analysis for Mars Rovers

In the quest to maximize the scientific return of future robotic missions, it is imperative that our rovers be capable of determining the importance of the science they collect so that they may prioritize the acquisition and relay of that data. As an important step in this process, we present an automated technique to allow a rover to classify the shape and other geologic characteristics of rocks from two-dimensional photographic images and three-dimensional stereographically produced data. Experiments were conducted in the Matlab environment using images returned by JPL's Mars Pathfinder mission. Our method begins by first segmenting the rocks from the background using a combination of image intensity and height data. Various metrics are then used to classify the region's sphericity, roundness, and other geometric properties. Preliminary experiments to determine the most useful metrics were conducted by characterizing the two-dimensional rock shape while the three-dimensional shape was later studied with metrics derived from these two-dimensional techniques. Seven measures were developed and implemented. The performance of each measure was characterized by analyzing imagesfrom the Pathfinder mission and ranking the rocks according to the measured properties. Combined, the measures would provide a tool by which an automated rover could discover a greater amount of information about the data it collects, leading to a more productive mission.

image segmentation↗

NASA NTRS2014

Adaptive Shape Functions and Internal Mesh Adaptation for Modelling Progressive Failure in Adhesively Bonded Joints

Enhanced finite elements are elements with an embedded analytical solution that can capture detailed local fields, enabling more efficient, mesh independent finite element analysis. The shape functions are determined based on the analytical model rather than prescribed. This method was applied to adhesively bonded joints to model joint behavior with one element through the thickness. This study demonstrates two methods of maintaining the fidelity of such elements during adhesive non-linearity and cracking without increasing the mesh needed for an accurate solution. The first method uses adaptive shape functions, where the shape functions are recalculated at each load step based on the softening of the adhesive. The second method is internal mesh adaption, where cracking of the adhesive within an element is captured by further discretizing the element internally to represent the partially cracked geometry. By keeping mesh adaptations within an element, a finer mesh can be used during the analysis without affecting the global finite element model mesh. Examples are shown which highlight when each method is most effective in reducing the number of elements needed to capture adhesive nonlinearity and cracking. These methods are validated against analogous finite element models utilizing cohesive zone elements.

computational mechanics↗

NASA NTRS2015

The Low-Degree Shape of Mercury

The shape of Mercury, particularly when combined with its geoid, provides clues to the planet’s internal structure, thermal evolution, and rotational history. Elevation measurements of the northern hemisphere acquired by the Mercury Laser Altimeter on the MESSENGER spacecraft, combined with 378 occultations of radio signals from the spacecraft in the planet’s southern hemisphere, reveal the low-degree shape of Mercury. Mercury’s mean radius is 2439.36±0.02 km, and there is a 0.14-km offset between the planet’s centers of mass and figure. Mercury is oblate, with a polar radius 1.65 km less than the mean equatorial radius. The difference between the semimajor and semiminor equatorial axes is 1.25 km with the long axis oriented 15° west of Mercury’s dynamically defined principal axis. Mercury’s geoid is also oblate and elongated, but it deviates from a sphere by a factor of 10 less than Mercury’s shape, implying compensation of elevation variations on a global scale.

Mercury↗

NASA NTRS2016

Applications of Displacement Transfer Functions to Deformed Shape Predictions of the GIII Swept-Wing Structure

The displacement transfer functions (DTFs) were applied to the GIII swept wing for the deformed shape prediction. The calculated deformed shapes are very close to the correlated finite element results as well as the measured data. The convergence study showed that using 17 strain stations, the wing-tip displacement prediction error was 1.6 percent, and that there is no need to use a large number of strain stations for G-III wing shape predictions.

on board string sensing system↗

NASA NTRS2016

Engineering Design Tools for Shape Memory Alloy Actuators: CASMART Collaborative Best Practices and Case Studies

The primary goal of the Consortium for the Advancement of Shape Memory Alloy Research and Technology (CASMART) is to enable the design of revolutionary applications based on shape memory alloy (SMA) technology. In order to help realize this goal and reduce the development time and required experience for the fabrication of SMA actuation systems, several modeling tools have been developed for common actuator types and are discussed herein along with case studies, which highlight the capabilities and limitations of these tools. Due to their ability to sustain high stresses and recover large deformations, SMAs have many potential applications as reliable, lightweight, solid-state actuators. Their advantage over classical actuators can also be further improved when the actuator geometry is modified to fit the specific application. In this paper, three common actuator designs are studied: wires, which are lightweight, low-profile, and easily implemented; springs, which offer actuation strokes upwards of 200 at reduced mechanical loads; and torque tubes, which can provide large actuation forces in small volumes and develop a repeatable zero-load actuation response (known as the two-way shape memory effect). The modeling frameworks, which have been implemented in the design tools, are developed for each of these frequently used SMA actuator types. In order to demonstrate the versatility and flexibility of the presented design tools, as well as validate their modeling framework, several design challenges were completed. These case studies include the design and development of an active hinge for the deployment of a solar array or foldable space structure, an adaptive solar array deployment and positioning system, a passive air temperature controller for regulation flow temperatures inside of a jet engine, and a redesign of the Corvette active hatch, which allows for pressure equalization of the car interior. For each of the presented case studies, a prototype or proof-of-concept was fabricated and the experimental results and lessons learned are discussed. This analysis presents a collection of CASMART collaborative best practices in order to allow readers to utilize the available design tools and understand their modeling principles. These design tools, which are based on engineering models, can provide first-order optimal designs and are a basic and efficient method for either demonstrating design feasibility or refining design parameters. Although the design and integration of an SMA-based actuation system always requires application- and environment-specific engineering considerations, common modeling tools can significantly reduce the investment required for actuation system development and provide valuable engineering insight.

Design tools↗

NASA NTRSDate not supplied

Data-Driven Study of Shape Memory Behavior of Multi-Component Ni-Ti Alloys

Ni-Ti based shape memory alloys (SMAs) have found wide-spread use in aerospace, automotive, biomedical, and commercial applications owing to their favorable properties and ease of operation. Especially important for many NASA applications is the ability to tune the martensitic transformation temperature of Ni-Ti alloys by varying the alloy composition and processing conditions. Recently, researchers at NASA have compiled an extensive database of shape memory properties of materials, including over 8,000 multi-component Ni-Ti alloys containing 37 different alloying elements. Using this dataset, machine learning models are trained to predict transformation temperatures, hysteresis, and transformation strain with extremely low mean absolute errors. These models are used to learn relationships between shape memory behavior and input parameters in the composition and processing space. ML predictions are validated through new experiments. The combination of an extensive experimental dataset and accurate learning models, together, make our approach highly suitable for the rapid discovery and design of novel SMAs with targeted properties. We are not aware of any current approaches capable of predicting SMA transformation behavior over such a wide range of compositions and processing conditions.

Shape memory alloys↗

NASA NTRSDate not supplied

Data-Driven Study of Shape Memory Behavior of Multi-component Ni-Ti Alloys

Ni-Ti based shape memory alloys (SMAs) have found wide-spread use in aerospace, automotive, biomedical, and commercial applications owing to their favorable properties and ease of operation. Especially important for many NASA applications is the ability to tune the martensitic transformation temperature of Ni-Ti alloys by varying the composition and processing conditions. Recently, researchers at NASA have compiled an extensive database of shape memory properties of materials, including over 8,000 multi-component Ni-Ti alloys containing 37 different alloying elements. Using this dataset, machine learning models are trained to predict transformation temperatures, hysteresis, and transformation strain with extremely small errors. These models are used to learn relationships between shape memory behavior and input parameters in the composition and processing space. ML predictions are validated through new experiments. The combination of an extensive dataset and accurate learning models, together, make our approach highly suitable for the rapid discovery of novel SMAs with targeted properties.

Shape Memory Alloys↗

NASA NTRSDate not supplied

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗

DOE OSTI2024

Shape Optimization of Header Pipes in Power Plants for Enhanced Efficiency and Environmental Sustainability

In a power plant, the header pipe plays a pivotal role in optimizing the performance of diverse systems by serving as a central conduit for the collection and distribution of steam within the plant. This paper investigates the significance of header pipes within power plant setups, highlighting their critical influence on reliability, efficiency, and the performance of the power plant as a whole. The concept of shape optimization emerges as a crucial factor in power plant design and operation, with the potential to maximize performance while minimizing the use of materials. Shape optimization not only enhances efficiency but also contributes to reducing the environmental footprint of power plant installations. In this paper, we initially developed a methodology designed for optimizing header shapes with the primary goal of reducing the usage of costly new alloy materials and lowering the overall maintenance operation expenses. Secondly, we conducted a case study based on an authentic header sourced from an operational power plant.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2021

Shape Persistent, Highly Conductive Ionogels from Ionic Liquids Reinforced with Cellulose Nanocrystal Network

Abstract Shape‐persistent, conductive ionogels where both mechanical strength and ionic conductivity are enhanced are developed using multiphase materials composed of cellulose nanocrystals and hyperbranched polymeric ionic liquids (PILs) as a mechanically strong supporting network matrix for ionic liquids with an interrupted ion‐conducting pathway. The integration of needlelike nanocrystals and PIL promotes the formation of multiple hydrogen bonding and electrostatic ionic interaction capacitance, resulting in the formation of interconnected networks capable of confining a high amount of ionic liquid (≈95 wt%) without losing its self‐sustained shape. The resulting nanoporous and robust ionogels possess outstanding mechanical strength with a high compressive elastic modulus (≈5.6 MPa), comparable to that of tough, rubbery materials. Surprisingly, these rigid materials preserve the high ionic conductivity of original ionic liquids (≈7.8 mS cm −1 ), which are distributed within and supported by the nanocrystal network‐like rigid frame. On the one hand, such stable materials possess superior ionic conductivities in comparison to traditional solid electrolytes; on the other hand, the high compression resistance and shape‐persistence allow for easy handling in comparison to traditional fluidic electrolytes. The synergistic enhancement in ion transport and solid‐like mechanical properties afforded by these ionogel materials make them intriguing candidates for sustainable electrodeless energy storage and harvesting matrices.

Lee, Hansol↗

DOE OSTI2022

Shape-Controlled NaTaO 3 by Flux-Mediated Synthesis

NaTaO 3 is a stable and wide bandgap n-type semiconductor material with many different applications. Here, a flux-mediated synthesis method is presented for NaTaO 3 resulting in highly distinctive, substrate covering shapes via precursor chemistry variation at comparatively low temperatures. It is found that the microstructure of the resulting NaTaO 3 films can be varied from nanocubes to smooth thin films. These shapes and surface chemistries can be correlated by employing density functional theory calculations and surface sensitive X-ray photoemission spectroscopy. This study provides guidance on how to synthesize the material and tailor its shape and surface termination for different applications. Finally, as a proof of concept of one possible application, NaTaO 3 is applied to perovskite solar cells as the electron transport layer, resulting in conversion efficiencies of >19%. Further, this study provides a new strategy for designing ternary oxide thin films for renewable energy applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2025

Shape‐Stabilization of Phase Change Materials with Carbon‐Conscious Poly(hydroxy)Urethane Foams

Thermal energy regulation is a significant challenge, contributing to over 30% of annual greenhouse gas emission (GHG) emissions. Phase change materials (PCMs) offer a promising solution by storing thermal energy, which can enable the reuse of waste heat for heating and cooling; however, developing materials for shape-stabilized PCMs remains crucial. This work investigates a self-foaming poly(hydroxy)urethane (PHU), derived from a non-isocyanate polyurethane (NIPU), as a porous support for shape-stabilizing paraffinic and salt hydrate PCMs. PHU-encapsulated paraffinic PCMs exhibited excellent thermal stability over repeated cycles. Thermal stability with salt hydrate PCMs, specifically calcium chloride hexahydrate (CaCl 2 •6H 2 O), is achieved by the incorporation of 5 wt.% barium carbonate (BaCO 3 ) into the PHU foam. This enabled stable cycling for over 48 cycles with desirable thermal properties, i.e., a melting point ≈30 °C, high enthalpy (ca. 138 J g −1 per cycle), and a consistent freezing point ≈20 °C, making it suitable for applications in buildings and electric vehicle battery insulation. Also, incorporating graphite (1.5–10 wt.%) into the foam enhanced the thermal conductivity of shape-stabilized CaCl 2 •6H 2 O during heating and cooling cycles. Overall, the approach detailed here offers a carbon-conscious and chemically tunable material for thermal energy storage.

25 ENERGY STORAGE↗