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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

From Machine Learning to Nuclear Digital Twins

This presentation provides multiple case studies of Machine Learning, Uncertainty Quantification, Reduced Order Modeling, to achieve digital transformation and provide the components for nuclear digital twinning. The presentation is for an international virtual event titled: Consultancy Meeting on Applications of AI and Pattern Recognition Techniques for Uncertainty Quantification in Nuclear Power Modelling and Simulation held Oct 21-22, 2021.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

In-situ thermomechanical measurements during burst testing of Zr claddings using digital image correlation and infrared thermography techniques

Burst testing has long been a relied-on method for assessing fuel cladding materials in light-water reactoraccident scenarios. However, burst testing historically provided minimal in-situ observations beyond a few thermocouple readings, pressure from transducers, and post-test deformation measurements. Acquisition of full cladding thermomechanical data throughout a burst test would be invaluable to fuel system qualification, material model development and fuel performance code validation, such as the BISON fuel performance code. Recently, methodologies for simultaneously applying 2-dimensional digital image correlation and infrared thermography techniques to quantify the relationship between temperature, internal cladding pressure, and deformation during burst testing were developed. This work details results from the application of these techniques to burst testing of Zircaloy-4 cladding segments subjected to loss-of-coolant accident transients in an air environment. Two types of tests were performed with: (a) cladding segments connected to a fixed pressure reservoir as well as (b) closed systems where internal pressure increased during transients. In-situ thermomechanical measurements including strain and thermal gradient data are presented, demonstrating the effectiveness of applying combined surface measurement techniques to burst testing

Bell, Sam↗
DOE OSTI2023

Mesoscale shock structure in particulate composites

Multiscale experiments in heterogeneous materials and the knowledge of their physics under shock compression are limited. Here, this study examines the multiscale shock response of particulate composites comprised of soda-lime glass particles in a PMMA matrix using full-field high speed digital image correlation (DIC) for the first time. Normal plate impact experiments, and complementary numerical simulations, are conducted at stresses ranging from 1.1 - 3.1 GPa to elucidate the mesoscale mechanisms responsible for the distinct shock structure observed in particulate composites. The particle velocity from the macroscopic measurement at continuum scale shows a relatively smooth velocity profile, with shock thickness decreasing with an increase in shock stress, and the composite exhibits strain rate scaling as the second power of the shock stress. In contrast, the mesoscopic response was highly heterogeneous, which led to a rough shock front and the formation of a train of weak shocks traveling at different velocities. Additionally, the normal shock was seen to diffuse the momentum in the transverse direction, affecting the shock rise and the rounding-off observed at the continuum scale measurements. The numerical simulations indicate that the reflections at the interfaces, wave scattering, and interference of these reflected waves are the primary mechanisms for the observed rough shock fronts.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Linkage Between Electro-Chemical Mechanical Instabilities in Battery Materials

Battery chemistry must be diversified to achieve a sustainable energy landscape by effectively utilizing renewable energy sources. Alkali metal-ion, all-solid-state, metal–air batteries, and multivalent batteries offer unique cost, safety, raw material abundance, energy, and power density solutions. However, realizing these “beyond Li-ion batteries” must uncover their working principles and performance & property relationships. In this aspect, mitigating chemo-mechanical instabilities in the structure and surface of the electrodes plays a crucial role in their performance. Unfortunately, the coupling between electrochemical and mechanical interactions is often poorly understood due to a lack of operando characterization. Here, this review article explains the working principles of curvature measurement and digital image correlation for measuring stress and strain generations in battery materials. We provided specific examples of how these operando mechanical measurements shed light on instabilities in alkali metal ion electrodes, solid electrolytes, Li-O 2 batteries, and aqueous Zn-ion batteries. Operando mechanical measurements offer an effective way to map changes in the physical fingerprint of the battery materials, therefore providing crucial information to elucidate instabilities in battery materials.

25 ENERGY STORAGE↗
DOE OSTI2020

Implications of post-processing induced microstructural changes on the deformation and fracture response of additively manufactured Ti–6Al–4V

Ti–6Al–4V parts fabricated via electron beam melting (EBM) powder bed fusion are often subjected to hot isostatic pressing below the β-transus temperature to mitigate defects. During which the pressure aids in pore closure and the thermal exposure results in coarsening of α phase while retaining the columnar prior-β phase grain morphology present in the as-fabricated condition. The same post-processing treatment can also be carried out above β-transus temperature which is an effective way to modify both the grain morphology and the associated α textures. Here, the objective of this work is to correlate thermally induced microstructural changes to the deformation and fracture response of the EBM processed Ti–6Al–4V. To this end, we have carried out both sub-transus and super-transus heat-treatments of the as-fabricated material. The mechanical response of the as-fabricated and all heat-treated materials are characterized by in-situ tensile tests under a high-resolution digital optical microscope. This enabled us to capture large-scale panoramic images of the deforming microstructure, and overcome the trade-off between the image resolution and the field of view during in-situ experiments. The series of images captured throughout the imposed deformation are subsequently used to perform microstructure-based digital image correlation to measure microstructural-scale strains over a large area. The results of the in-situ tests together with detailed fractographic analyses are then used to elucidate how the heterogeneous deformation spanning over multiple microstructural length-scales, for example, at the scale of lamellae, colonies of lamellae and grain boundaries, affect the overall deformation and fracture response of the post-processed materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Comparative Study of Direct and Indirect Additive Manufacturing Approaches for the Production of a Wind Energy Component

Additive manufacturing (AM) was developed in the 1980s to create three-dimensional prototypes through layer-wise approaches to fabrication. Since then, these approaches have seen improvements in both materials and processing technologies. To date, there are now 7 types of additive manufacturing processes and hundreds of materials, which can be directly printed – going directly from digital design to fabricated components. In this project, Oak Ridge National Laboratory (ORNL), Vestas Wind Systems, and The National Renewable Energy Laboratory (NREL) collaborated to evaluate the effectiveness of state-of-the-art large-scale AM processes in the production of a structural component for use in a wind turbine nacelle, through both direct and indirect manufacturing approaches. Here, experienced AM design engineers detail techniques for AM design, including topology optimization (TO), support minimization, reverse engineering, and techniques for mitigating poor interlaminar performance. Fabrication of the components is presented, including printing parameters and postprocessing, and followed with full-scale component testing by a 3rd party testing laboratory. To evaluate the potential of the developed approaches, a complete techno-economic analysis is provided which evaluates the cost of these techniques given current and near to long-term projections of AM system capabilities.

17 WIND ENERGY↗
DOE OSTI2023

A review of materials used in tomographic volumetric additive manufacturing

Abstract Volumetric additive manufacturing is a novel fabrication method allowing rapid, freeform, layer-less 3D printing. Analogous to computer tomography (CT), the method projects dynamic light patterns into a rotating vat of photosensitive resin. These light patterns build up a three-dimensional energy dose within the photosensitive resin, solidifying the volume of the desired object within seconds. Departing from established sequential fabrication methods like stereolithography or digital light printing, volumetric additive manufacturing offers new opportunities for the materials that can be used for printing. These include viscous acrylates and elastomers, epoxies (and orthogonal epoxy-acrylate formulations with spatially controlled stiffness) formulations, tunable stiffness thiol-enes and shape memory foams, polymer derived ceramics, silica-nanocomposite based glass, and gelatin-based hydrogels for cell-laden biofabrication. Here we review these materials, highlight the challenges to adapt them to volumetric additive manufacturing, and discuss the perspectives they present. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2020

A method for characterization of multiple dynamic constitutive parameters of FRCs

We propose a method to measure multiple dynamic material constitutive parameters of unidirectional fiber reinforced composites (FRCs) in a single experiment. Dynamic short-beam shear (DSBS) experiments were performed on a modified Kolsky compression bar, with integration of high-speed imaging and digital image correlation (DIC). The unidirectional FRCs investigated were S-2 glass fiber reinforced matrix of TGDDM-Jeffamine® D230 with monoamine functionalized partially reacted substructures (mPRS) and commercially available SC-15. Analytical solutions of normal and shear strains of a composite beam were derived based on Timoshenko beam theory, assuming material to be transversely isotropic and have different moduli in tension and compression in each principle material orientation. Tensile and compressive moduli were inversely computed through monitoring normal strain slope when specimen was constantly loaded at a speed of ~7.3 m/s within a small deflection. Non-linear shear stress-strain behavior of the composite was described via Ramberg–Osgood equation. Finite element (FE) analysis was conducted in ABAQUS, simultaneously defining via user subroutine UMAT the transverse isotropy of material, bi-modulus constitutive model, and non-linear shear stress-strain relation. The method proposed in this work was validated by comparing strain distributions computed by FE model and DIC measurements. Comparing with traditional dynamic tensile, compressive, and shear experiments on FRCs, this method significantly simplifies the specimen preparation and design of complicated gripping fixtures for multiple experiments. Here, systematic errors resulting from variations of specimen geometry and dimension, loading direction, and instrumentation are reduced, thereby providing compatible data for numerical studies on impact behavior of composites.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Raman Digital Twin of Monolayer Janus Transition Metal Dichalcogenides

Monolayer transition metal dichalcogenides (TMDs) are a key class of two-dimensional (2D) materials with broad technological potential. Their Janus counterparts exhibit unique properties due to broken out-of-plane symmetry and further enrich the functionalities of TMDs. However, experimental synthesis and identification of Janus TMDs remain challenging. It is thus highly desirable to have a rapid, simple, and in situ characterization technique to monitor, in real time, the conversion process from the parent to Janus structure. Raman spectroscopy stands out for such a task as it is a powerful, nondestructive, and very commonly used tool to characterize 2D materials both in situ and ex situ. To realize the full potential of Raman spectroscopy on rapid characterization of Janus TMDs, we present a computational “Raman digital twin” library for various monolayer Janus TMDs in both 2H and Td phases. We focus on group-6 TMDs: MoS 2 , WS 2 , MoSe 2 , WSe 2 , MoTe 2 , WTe 2 and their Janus variants: MoSSe, MoSTe, MoSeTe, WSSe, WSTe, and WSeTe. Using first-principles density functional theory (DFT), we calculate their vibrational properties and predict distinct Raman fingerprints. These phonon and Raman signatures reflect each material’s structural symmetry and atomic composition, enabling clear identification via Raman spectroscopy. Our theoretical work supports experimental efforts by providing benchmarks for material identification, structural analysis, and quality control. In conclusion, the computational library expedites the discovery and development of Janus 2D materials, facilitating tighter integration between theoretical predictions and experimental validation.

Chalcogenides↗
DOE OSTI2023

Compute in‐Memory with Non‐Volatile Elements for Neural Networks: A Review from a Co‐Design Perspective

Abstract Deep learning has become ubiquitous, touching daily lives across the globe. Today, traditional computer architectures are stressed to their limits in efficiently executing the growing complexity of data and models. Compute‐in‐memory (CIM) can potentially play an important role in developing efficient hardware solutions that reduce data movement from compute‐unit to memory, known as the von Neumann bottleneck. At its heart is a cross‐bar architecture with nodal non‐volatile‐memory elements that performs an analog multiply‐and‐accumulate operation, enabling the matrix‐vector‐multiplications repeatedly used in all neural network workloads. The memory materials can significantly influence final system‐level characteristics and chip performance, including speed, power, and classification accuracy. With an over‐arching co‐design viewpoint, this review assesses the use of cross‐bar based CIM for neural networks, connecting the material properties and the associated design constraints and demands to application, architecture, and performance. Both digital and analog memory are considered, assessing the status for training and inference, and providing metrics for the collective set of properties non‐volatile memory materials will need to demonstrate for a successful CIM technology.

36 MATERIALS SCIENCE↗
DOE OSTI2026

BLEECAM™ (Benchmarking Life Cycle Environmental, Economic, and Social Metrics for Critical and Advanced Minerals and Materials) [SWR-25-125]

The National Laboratory of the Rockies' (NLR) Benchmarking Life Cycle Environmental, Economic, and Social Metrics for Critical and Advanced Minerals and Materials (BLEECAM™) is an open-source, integrated decision-support tool for evaluating the impacts, risks, and trade-offs across U.S. and global materials supply chains. Funded by the U.S. Department of Energy, BLEECAM supports supply chain and market analysis. The tool integrates multi-objective supply chain optimization, system dynamics, network design, lifecycle assessment, techno-economic modeling, and social impact assessment methods to evaluate how supply chains evolve over time, geography, and deployment scenarios. BLEECAM also supports analysis related to energy infrastructure, data centers and digital infrastructure, advanced manufacturing, and other sectors that depend on critical materials.

Khalifa, SherifA. [National Laboratory of the Rock↗
DOE OSTI2025

Building Cybersecurity Educational Materials for Students: The Windfarm Capture-The-Flag Exercise

Securing and protecting critical infrastructure in an increasingly digital world is vital but it is all too often an afterthought. It is especially important that students become aware of internet safety and security at an early age. However, the availability of interactive and educational cybersecurity material targeted toward students is minimal in the United States. Here we show an example of interactive cyber security educational material that an educator can use in their classroom to encourage students to think about the interaction between real-world physical objects, cyber security, and information security. By putting together a “capture-the-flag” exercise, students can see in real time how hackers and cybercriminals exploit vulnerabilities and gain access information. The students try to “capture” the “flag” (i.e., information) in the wind farm by looking for oddities in the code or by taking advantage of weaknesses in everyday protocols. Students can also see how cybersecurity interacts with the power grid through the wind farm project scenario and how a hacker could cause serious problems to a critical infrastructure sector. Our goal for the project is getting students interested in cybersecurity and help them develop an awareness of how important having robust security systems is. We also hope that this project demonstrates the importance of introducing these concepts early and inspires others to create similar projects geared toward students.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A linked-scale coupled model of mass erosion and redistribution in plasma-exposed micro-foam surfaces

Surface evolution due to exposure to harsh environments is of importance in many scientific and technological applications. In plasma-exposed materials, the surface receives charged particles from the plasma, leading to a series of processes that drive the system far from equilibrium and may lead to the severe deterioration of the surface properties. Although surface morphological changes are driven by atomic collisions taking place over picoseconds and nanometers, these processes result in mass loss and redistribution of matter over much larger length and time scales. This necessitates a multi-scale approach capable of capturing the range of processes linking primary atomic collision events with engineering-level surface geometry changes. In this paper, we develop a computational model to simulate the morphological evolution and effective erosion rate of micro-architected tungsten foams during low-energy plasma ion bombardment. Furthermore, the model acts on several length scales, with the energy and angular dependence of the sputtering yield of flat tungsten surfaces determined using the SRIM code based on the binary collision approximation. This information is introduced into a low-fluence, short-term Monte Carlo raytracing model, and further into a high-fluence, long-term particle transport model. In the latter, material particles representing billions of atoms are described in a digitized 3-D representation of the foam structure from X-ray tomography data, and are sputtered off and redeposited using the atomistic information. We show that the redeposition of sputtered atoms leads to partial self-healing in the bottom layers with a sharp reduction in the sputtering coefficient of low density foams, roughly 25% of the solid W value. This is in qualitative agreement with recent experiments on low porosity W structures. At high fluence, the foam structure degrades considerably as there are fewer ligaments available to recapture sputtered atoms and, consequently, the sputtering rate increases again.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Additively manufactured β-Ti5553 with laser powder bed fusion: Microstructures and mechanical properties of bulk and lattice parts

Ti5553 (Ti-5Al-5Mo-5V-3Cr wt%) is a titanium alloy widely used for its high strength-to-weight ratio and good formability at elevated temperatures. Unlike Ti-6Al-4V, Ti5553 does not undergo martensitic transformation, preventing cracking of brittle martensite upon rapid cooling. This makes it a strong candidate for additive manufacturing (AM), particularly laser powder bed fusion (L-PBF). L-PBF offers the unique opportunity to make fine lattice structures to reduce component weight. Despite the growing field of AM, there have been limited studies on L-PBF Ti5553 lattices and how their properties differ from the bulk. Here the present work addresses this knowledge gap by investigating microstructures and properties of L-PBF bulk and lattice parts and the effect of post L-PBF heat treatments. Electron microscopy and mechanical testing show that the high dislocation density formed during L-PBF increases bulk part’s yield strength by approximately 100 MPa compared to the conventional alloy. Digital image correlation during compression testing of octet truss lattices reveals a layer-by-layer failure mode. Compared to the bulk, the lattice contains copious ω nanoprecipitation, weaker <001> texture, smaller average grain sizes, and larger content of high-angle grain boundaries. These features elicit differences in Taylor factor distributions for the lattice depending on load direction, underlining challenges in predicting lattice mechanical response based on bulk properties. By examining the processing-structure-property relationships in the bulk and lattice, the present results delineate their microstructural and mechanical differences and establish a benchmark for the future design applications of L-PBF Ti5553.

36 MATERIALS SCIENCE↗
DOE OSTI2021

In-Situ Calibrated Modeling of Residual Stresses Induced in Machining under Various Cooling and Lubricating Environments

Although many functional characteristics, such as fatigue life and damage resistance depend on residual stresses, there are currently no industrially viable ‘Digital Process Twin’ models (DPTs) capable of efficiently and quickly predicting machining-induced stresses. By leveraging advances in ultra-high-speed in-situ experimental characterization of machining and finishing processes under plane strain (orthogonal/2D) conditions, we have developed a set of physics-based semi-analytical models to predict residual stress evolution in light of the extreme gradients of stress, strain and temperature, which are unique to these thermo-mechanical processes. Initial validation trials of this novel paradigm were carried out in Ti-6Al4V and AISI 4340 alloy steel. A variety dry, cryogenically cooled and oil lubricated conditions were evaluated to determine the model’s ability to capture the tribological changes induced due to lubrication and cooling. The preliminarily calibrated and validated model exhibited an average correlation of better than 20% between the predicted stresses and experimental data, with calculation times of less than a second. Based on such fast-acting DPTs, the authors envision future capabilities in pro-active surface engineering of advanced structural components (e.g., turbine blades).

36 MATERIALS SCIENCE↗
DOE OSTI2026

Smaller feature size impairs densification in digital light processing 3D printed ceramic samples

In this study, we investigate how geometric miniaturization affects the sintering densification behavior of alumina cylinders with various wall thicknesses (down to ∼500 µm in green body) fabricated via digital light processing (DLP). As the wall thickness decreased, the density of the sintered samples consistently declined. Microstructural characterization revealed the presence of a crack-rich surface skin that is ∼500 µm thick. As the wall thickness decreases, the skin's volume fraction rises, and its poor local densification increasingly dominates the part average, leading to an overall decrease in the density of the sintered samples. For the thinnest wall (500 µm) cylinder, macroscopic warping occurred during sintering. We suggest that warping further disrupts particle packing and induces through-thickness nonuniformity, further impairing densification in addition to the skin-fraction effect. These results highlight how geometric miniaturization may adversely influence the sintering behavior and final density of DLP-printed ceramics through distinct densification-limiting mechanisms.

Materials science↗
DOE OSTI2023

Leveraging the digital thread for physics-based prediction of microstructure heterogeneity in additively manufactured parts

A major limitation of additive manufacturing (AM) processes is that local conditions of material deposition frequently lead to unintentional heterogeneities in microstructure and properties within a single component, despite nominally uniform process conditions. Up to now, there has been no way to a priori determine the distribution of these heterogeneities, requiring expensive trial-and-error approaches to fabrication, testing, and characterization. Here, a physics-based framework for creating a digital representation of the laser powder bed fusion (PBF) process is proposed to predict the variation in solidification behavior that leads to heterogeneous microstructures in an as-built part. By leveraging in situ process data stored in the part’s digital thread, the scan path and process parameters were input into a heat transfer model which predicted solidification data at the melt pool scale. A two-step unsupervised clustering algorithm was used to first cluster the local solidification conditions (12.5µm 3 voxels) and then to cluster the regional behavior on the scale of multiple scan passes and print layers (250µm 3 super-voxels). This process was used to identify regions with similar solidification characteristics for multiple locations in a Stainless Steel 316-L component. The corresponding as-built part was sectioned and characterized using electron backscatter diffraction (EBSD). Quantitative analysis of the pole figures confirmed that the predicted regions of heterogeneity in the solidification conditions corresponded with differences in the observed microstructure. In conclusion, this work shows a viable path for estimating the microstructural heterogeneity for additively manufactured parts to either limit microstructural variation throughout a part or to enable functionality-based variation of the microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The Toughness of Interlocking Metasurfaces

Interlocking metasurfaces (ILMs) are arrays of autogenous latching unit cells patterned across a surface. These create structural joints similar to bioinspired suture joints but patterned over a 2D surface rather than a 1D seam. This enables ILMs to be an alternative to conventional joining technologies such as bolts, welds, and adhesives. However, compared to conventional joining methods, relatively little is known of the engineering considerations for designing structural ILMs. Herein, the interfacial toughness of an archetypal ILM is examined for the first time. Under the conditions studied here, the ILM is substantially tougher than the material from which it is made, in this case, exhibiting up to a 50% increase in interfacial crack initiation energy over the solid base material, a photocured 3D‐printed polymer. Through experimental tests using in‐situ digital image correlation along with complementary computational analyses, the mechanism of toughening in the ILM structure and the origins of toughness anisotropy are revealed. The increase in toughness is associated with cross‐cell interactions, that is, load‐sharing across unit cells, which give rise to a finite process zone length with different effective material properties. In this way, ILM toughening is analogous to crack blunting in ductile materials or fiber bridging in composites; yet here, the ILM is composed of a single‐phase base material and so the architected toughening is geometric in nature and hence amenable to future topological optimization.

fracture↗