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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Phased array-based nonlinear wave mixing technique: Application to lack-of-fusion porosity characterization in additively manufactured metals

The objective of this research is to demonstrate the effectiveness of a phased array-based nonlinear wave mixing technique to characterize internal, localized microscale damage in an additively manufactured (AM) component. By using phased arrays for the generation of the incident waves, it is possible to produce a nonlinear wave mixing scanning technique without the need for immersion or changing coupling conditions. The phased arrays can be configured to generate incident waves in multiple directions that meet the resonance conditions required for nonlinear wave mixing at a variety of internal locations. This allows for the scanning of a specimen without the removal and re-coupling of the source transducers, leading to greater scanning speed and repeatability. To demonstrate the accuracy of this phased array wave mixing approach, measurements of acoustic nonlinearity in an AM component are first made with a bulk wave second harmonic generation through thickness measurement. Next, nonlinear wave mixing measurements are made with single element transducers to confirm the sensitivity of the proposed nonlinear wave mixing approach to lack-of-fusion porosity in AM metals. Finally, phased arrays are used to highlight the effectiveness of the proposed nonlinear wave mixing technique in these same AM components.

Acoustics↗
DOE OSTI2025

Modeling Structured Electrodes and Graded Porosity for Improving Discharge Rate Capability in Ultra-Thick Graphite|LiNi 0.6 Mn 0.2 Co 0.2 O 2 Batteries

Long-range electric vehicles (EVs) require high-energy-density batteries that also meet the power demands of high current charge and discharge. Ultra-thick (>100 μm) Lithium-ion battery electrodes are critical to enable this need, but slow ion transport in conventional uniform electrodes (UEs) reduces battery capacity at increasing charge/discharge rates. We present a 3D computational analysis on the impact of structured electrode (SE) and graded electrode (GE) geometries on the discharge rate capability of ultra-thick graphite|LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC-622) battery cells based on the footprint of a commercial EV pouch cell. SE cathodes with either a “grid” or “line” geometry and GEs with two layers of porosity were modeled. Based on the results of 230 models, we found that the electrolyte volume fraction is a key parameter that impacts capacity improvements in UEs, GEs, and SEs at 2 C–6 C discharge rates. SEs have the greatest discharge rate capability, outperforming GEs and UEs due to reduced Lithium-ion concentration gradients across the electrode thickness, which mitigates electrolyte depletion at high rates. The best SE model has a “grid” geometry with gravimetric and volumetric energy density improvements of 0.9%–4% at C/2–2 C and 18%–24% at 4 C–6 C relative to UEs.

25 ENERGY STORAGE↗
DOE OSTI2024

Simulating the effect of grain structure and porosity on creep for powder bed fusion 316H

This report details results from modeling studies focused on identifying the potential factors influencing creep performance of 316H stainless steel manufactured using Laser Powder Bed Fusion (LPBF), with a focus on experimentally-observed and predicted differences between the response of the AM material and conventionally manufactured wrought 316H. The studies presented here systematically look at the role of grain structure, porosity and texture in the anisotropic creep behavior of the material under conditions expected in high temperature advanced nuclear reactors. A physics-based Crystal Plasticity Finite Element modeling approach has allowed us to look at these factors in isolation and study their role in the material's long-term deformation behavior. An update to the precipitation model used in the constitutive framework for 316H is also presented here, with the aim of improving the accuracy of our results from this modeling effort. This work is a step in the direction of gaining mechanistic understanding of the long-term deformation behavior of LPBF 316H, helping us model its long term performance and reducing the qualification time for the material.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Enhancing particle-to-sCO2 heat exchanger effectiveness through novel high-porosity metallic foams

In this project, a novel concept of Octet-shape based lattice frame material was developed for deployment in particle-to-sCO2 heat exchangers for CSP application. A comprehensive experimental and numerical program was performed to investigate and characterize the thermal and flow transport behavior in high porosity lattice frame material. The thermal properties include effective thermal conductivity and interstitial heat transfer coefficient and flow properties including permeability and inertial coefficient. Above quantities were determined for both air flow and heated particle flow through the porous channels which were representative of the hot channel in a typical counter flow heat exchanger. The cold side of the heat exchanger feature minichannels which are known to be very efficient in thermal transport. The goal of this project was to enhance the overall heat transfer coefficient (Up) on the hot side by introducing Octet-shape based lattice frame material through enhancement in effective thermal conductivity of the channel and through enhancement in the interstitial heat transfer coefficient.

14 SOLAR ENERGY↗
DOE OSTI2025

Influence of sizing concentration on strength, stiffness, and porosity in textile grade carbon fiber (TCF)-Epoxy composites: Revealing inverse trends

The effect of fiber sizing (i.e., surface treatment) concentration (0 %, 1.36 %, 1.52 %, 1.94 %, and 2.13 %) on the mechanical properties (tensile, flexural, interlaminar shear strength (ILSS), and low velocity impact) of textile grade carbon fiber (TCF)-epoxy composite is examined. An inverse relationship between the strength and stiffness of the composite is observed with increased sizing concentration. The root mean square (RMS) roughness of the fiber surface increased from 17.8 nm (unsized) to 22.7 nm with 2.13 % sizing concentration. It was found that the tensile strength increased by 131 % from 221.4 ± 18.5 MPa (unsized) to 510.8 ± 28.05 MPa (for 1.36 % sizing) and further by 155 %–563.7 ± 14.95 MPa at 2.13 % sizing. On the contrary, the stiffness is initially increased by 126 % from 33.52 ± 7.80 GPa (unsized) to 75.9 ± 3.21 GPa (for 1.36 % sizing) but reduced with further increase in the sizing concentration. A single fiber pull-out test is simulated using the finite element method to validate the reverse trend in strength and stiffness. The varying sizing concentration is simulated by introducing an interface of varying thickness between fibers and matrix. Simulation results confirm that a thicker interface, corresponding to a higher sizing concentration, decreases interfacial shear stress, enhancing material strength while decreasing stiffness. The reverse trend in strength and stiffness with the sizing concentration aligns with experimental observations. In conclusion, the present study emphasizes the importance of sizing concentration for mechanical properties and provide a design criterion for customized high-strength and high-stiffness applications.

Porosity↗
DOE OSTI2026

Raptor: A Python Library for Porosity Predictions in Additive Manufacturing

Raptor is an efficient Python library for simulating stochastic lack-of-fusion (sLoF) defects in additive manufacturing (AM) processes. These defects arise from stochastic variations in the melt pool boundary leading to undermelting from insufficient overlap between adjacent melt pools or successive layers (Grasso & Colosimo, 2017; Khairallah et al., 2016). Performance variability of AM parts is a pressing challenge in qualification and certification of AM parts; this is in part due to the poorly understood formation rate and statistics of sLoF defects. Raptor is designed to capture the explicit morphologies of sLoF defects and their statistics to accelerate qualification and certification efforts of AM parts in critical applications.

Subraveti, Vamsi [Vanderbilt University]↗
DOE OSTI2025

High-Throughput Characterization Tools/Algorithms To Outline Porosity Variability in AM Samples as a Function of Processing Conditions

This report documents the development and deployment of advanced algorithms and tools that enable high-throughput characterization for metal additive manufacturing (AM), with a particular focus on process parameter optimization and material/part qualification for nuclear applications. While the method ologies presented support diverse characterization techniques, the majority of the work is centered on AI-driven algorithms for X-ray computed tomography (XCT) to accelerate defect detection and materials analysis at scale.

36 MATERIALS SCIENCE↗