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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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The Fluid Dynamics Uncertainty Quantification Challenge Problem: XFOIL vs. MFOIL

Uncertainty quantification (UQ) has become more critical in aerospace engineering due to the growing dependence on computational tools for design optimization and performance analyses of aerospace vehicles. Even though the significance of UQ in assessing the credibility of computational analyses is well recognized, its costs and complexity impede its integration into standard practices, particularly in computational fluid dynamics (CFD) and other fluid analyses. This paper presents a UQ study for low-fidelity computational aerodynamics analyses with XFOIL and mfoil (i.e., the MATLAB version of XFOIL with several implementation modifications); these tools are utilized widely in both research and education. The main contributions of this paper are as follows: 1) improved precision in quantifying the uncertainty of the baseline Monte Carlo results used to benchmark surrogate modeling techniques for UQ, 2) quantification of the effect of the implementation differences between XFOIL and mfoil on solution quantities of interest (QoIs), such as lift and pitching moment coefficients, and 3) development of an open-source UQ library for use with XFOIL and mfoil, which has educational values and helps promote UQ for fluid analyses with aerospace applications. Results and discussions revolve around cases 1-4 of the challenge problem posed by the AIAA Fluid Dynamics Technical Committee’s Uncertainty Quantification Discussion Group (UQDG). In case 3, this work employs CFDverify, an open-source solution verification software, to quantify the discretization error and evaluate the extrapolated QoIs based on the grid convergence index (GCI). This UQ study differentiates itself from previous studies in the rigor of handling baseline Monte Carlo uncertainty and in including mfoil, which is a more accessible alternative to XFOIL. Finally, despite the growing computing power, low-fidelity computational tools remain valuable, such as for aerodynamic shape optimization at Mach numbers below 0.65 and low-to-mid Reynolds numbers.

Lay, Aidan S [University of Tennessee, Knoxville (

Additive manufacturing of high‐density silicon carbide ceramics through post‐processing spark plasma sintering

This research advances the field of additive manufacturing (AM) of silicon carbide (SiC) ceramics by integrating spark plasma sintering (SPS) to enhance material density, mechanical strength, and thermal properties. Traditional AM techniques struggle to achieve the high‐density SiC required for demanding applications, such as aerospace engineering, where high thermal conductivity and mechanical strength are paramount. Here, our study addresses these challenges by incorporating SPS as a post‐processing step, achieving near‐theoretical maximum densities and significantly reducing porosity, thereby resulting in outstanding thermal conductivity in SiC ceramics. We developed a specialized SiC ink optimized for 3D printing, ensuring structural integrity after deposition through tailored rheological properties. The application of SPS facilitates rapid, uniform sintering, essential for attaining superior density, mechanical properties, and thermal performance. Our experimental results, confirmed through scanning electron microscopy analysis, demonstrate significant microstructural properties, mechanical strength, and thermal conductivity, showcasing the effectiveness of integrating SPS in AM processes. This innovative approach not only expands the capabilities of AM in producing complex, high‐density ceramic structures but also broadens the potential applications of SiC in demanding environments.

36 MATERIALS SCIENCE

Development of a Western U.S. Fusion Energy Commercialization Hub

Fusion energy, if successfully commercialized and globally adopted, could substantially increase U.S. energy dominance and provide essentially unlimited baseload power for the national grid. It also stands to provide the U.S. with a strong source of economic growth through the 2030s and 2040s, giving the U.S. a new and highly internationally competitive industry for export. Fusion can also provide the increased electrical power generation capacity required to power current and future artificial intelligence (AI) activities. In October 2024, the CleanTech Alliance held a fusion energy commercialization regional hub workshop alongside its annual Seattle Fusion Week conference. The event brought together fusion companies, researchers, economic development experts, federal and state government representatives, and power utilities from the western states of Washington, California, Colorado and Nevada. Attendees discussed the potential of regionally focused commercialization of fusion energy in three pillars: technology, workforce, and economic development. Mel Clark, President & CEO, CleanTech Alliance, and Dr. Javier Garay, Associate Dean for Research and Professor of Mechanical and Aerospace Engineering, at the University of California San Diego (UCSD) and Founding Director of the UCSD Fusion Engineering institute, are co-PIs for this project. The project is sponsored by the U.S. Department of Energy’s Office of Fusion Energy Sciences (FES) through a Field Work Proposal to Pacific Northwest National Laboratory (PNNL) with Karl Mueller as point-of-contact. Chris Ajemian (Principal, Ajemian Consulting, LLC) and Dr. Christopher Keane (Professor of Physics and former Vice-President for Research, Washington State University) co-organized the workshop and were the editors for this report. This report details the current state of the work of the four western states to develop industry-led collaboration with national laboratories, universities, and government at all levels to hasten the commercialization of fusion energy. It provides a summary of fusion energy R&D needs, presents the ideas the attendees at the workshop identified for deepening regional collaboration, and makes findings and recommendations for next steps.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

FAIR Data and Interpretable AI Framework for Architectured Metamaterials

Our interdisciplinary effort successfully generated FAIR (Findable, Accessible, Interoperable, and Reusable) benchmark datasets for mechanical metamaterials while introducing a novel Artificial Intelligence (AI) framework known as Learning Refined Compositional Rules (LRCR). This framework was specifically designed to bridge the gap across varying computational length scales and extract the underlying physical mechanisms that connect a material's structural geometry to its bulk acoustic properties. Historically, the discovery of such structured materials relied heavily on human intuition or opaque, black-box optimization algorithms that were difficult to generalize. By combining interpretable machine learning techniques with rigorous experimental validation, this project established clear, generalizable design guidelines for tuning wave dispersion and controlling vibrations. Ultimately, the public availability of these structured datasets and algorithms will significantly reduce computational costs and accelerate the design of advanced multi-functional acoustic devices, offering broad societal impacts across fields like aerospace engineering, telecommunications, and biomedical implant design.

36 MATERIALS SCIENCE

Scalable foundation models for numerical simulations on HPC platforms

In recent years, foundation models (FMs) have begun to reshape numerical simulations on high-performance computing (HPC) platforms. These large, pre-trained AI models enable rapid predictions across a broad range of physical domains, including Earth system modeling, fluid dynamics, materials science, as well as complex multi-modal simulations in aerospace engineering and fusion research. By training on diverse datasets, FMs learn intricate relationships and underlying physical behavior while also enabling the quantification of uncertainty in their predictions. This capability allows simulations that once required days of numerical calculation to be completed in minutes (FM inference), supporting real-time design optimization, uncertainty-aware decision making, and more comprehensive exploration of complex scenarios.

AI

Enhanced domain dynamics in alternating current poled rhombohedral Pb(Mg 1/3 Nb 2/3 )O 3 –PbTiO 3 single crystals

Abstract The understanding of domain dynamics in ferroelectric materials is crucial for optimizing their performance in piezoelectric and electro‐optic applications. Although previous studies have focused on static domain structures and macroscopic characteristics, the time‐resolved approach of domains remains largely unexplored. In this study, we compare the dynamic responses of direct current (DC) and alternating current (AC) poled [001]‐oriented rhombohedral Pb(Mg 1/3 Nb 2/3 )O 3 –PbTiO 3 (PMN–PT) single crystals using X‐ray photon correlation spectroscopy (XPCS) during the application of external electric fields. Our results demonstrate that the AC‐poled sample exhibit enhanced reconfiguration of domain variants in response to driving fields compared to the DC‐poled counterpart, as evidenced by accelerated correlation decay and faster relaxation time. This phenomenon is attributed to enhanced reversible domain wall motion achieved through AC poling, which facilitates field‐induced domain realignment. These findings provide insight into the relationship between dynamics and macroscopic properties in relaxor‐PT single crystals for high‐performance applications.

36 MATERIALS SCIENCE

New Deformation Mechanisms in Nanocrystalline Nano-porous Small Scale Metals as Defined by Kinetically-driven Microstructures

This report describes recent advances in the design and fabrication of nanostructured metallic pillars with hierarchical microstructures using a novel nanoscale additive manufacturing approach. Through a hydrogel-infusion-based two-photon lithography (TPL) method, we successfully fabricated 3D nickel nanopillars exhibiting both nanocrystalline and nanoporous features. The resulting “bamboo-like” internal architecture comprises 30–50 nm grains and voids with similarly scaled pores. These geometrically tunable pillars, with diameters ranging from ~130 to 550 nm, serve as an ideal platform for probing deformation mechanisms in structurally heterogeneous metals at the nanoscale.

36 MATERIALS SCIENCE

Rheology improvement for silicon nitride and resin slurries for vat photopolymerization printing and sintering

This work presents the formulation, rheological characterization, and sintering of silicon nitride (Si₃N₄) slurries for vat photopolymerization (VPP) using digital light processing (DLP). Bimodal Si₃N₄ powder was dispersed into commercial photopolymer resin using two different dispersants with opposing effects on surface charge, resulting in varied slurry stability and flow behavior. Slurries were engineered to exhibit shear-thinning behavior suitable for VPP, and their flow properties were quantified using a power-law fluid model. The formulations achieved cure depths of approximately 40 µm and enabled printing of green bodies. Post-processing included thermal debinding and liquid-phase sintering, yielding primarily β-Si₃N₄ with a minor Y-Si-Al-O-N glass phase. The sintered parts reached ~85% of theoretical density and demonstrated a flexural strength of ~330 MPa. Microstructural analysis revealed closed porosity along with some defects related to powder agglomeration and interlayer adhesion. These findings provide insights into slurry formulation strategies for additive manufacturing of high-performance non-oxide ceramics.

Aerospace engineering

Multiple‐Repeated Plasma Surface Treatments for Significantly Improving Bonding Performance of Metal‐Carbon‐Fiber‐Reinforced Thermoplastic Polymer Dissimilar Adhesive Joints

This work investigates how multiple‐repeated plasma surface treatments can significantly enhance adhesively bonded metal‐carbon‐fiber‐reinforced thermoplastic polymer (CFRTP) dissimilar joints, a topic that has been rarely investigated compared to other parameters during the plasma treatment process. By conducting double cantilever beam tests on adhesively bonded AA6061‐carbon‐fiber‐reinforced polyphthalamide (CFRPPA) dissimilar joints, it is shown that the average Mode I specific fracture energy after 20 repetitions of the same plasma treatment, using processing parameters without noticeably changing surface roughness, can be improved and saturated up to almost 2000% compared to non‐treated joints and almost 240% compared to a single plasma treatment commonly used in the literature. The improvement can be attributed to the enhanced chemical bonding at the CFRPPA‐adhesive interface. This study is important for achieving strong bonding performance of CFRTP‐related structural joints using multiple plasma treatments, a simple and effective method.

36 MATERIALS SCIENCE

Physicochemical properties of digital light processing 3D-Printed alumina and mullite ceramics

Alumina ceramics fabricated using conventional techniques such as uniaxial pressing or injection molding are popular due to their low density, excellent insulation, and mechanical properties. However, these methods often limit the fabrication of complex geometries with high dimensional accuracy due to tooling constraints and limited design freedom. To overcome these limitations, this study employed Digital Light Processing (DLP) additive manufacturing (AM), which enables the production of precise structures. In addition, the optimization of sintering parameters to enhance the densification and performance of alumina and mullite ceramics was investigated, with a specific focus on how varying sintering temperatures and hold times affect part shrinkage, geometric accuracy, and material integrity. Flexural strength of both alumina and mullite specimens was clearly influenced by the way the layers was stacked. When layers were arranged across the direction of the applied load (Z = 4; XZ), the strength was higher than when they were stacked along the same direction as the load (Z = 3; XY). Weibull analysis based on these results showed high modulus values across all samples, indicating good reliability in the flexural strength measurements. This reliability, combined with the clear influence of sintering parameters, highlights how processing conditions effect the material properties and mechanical performance of parts produced through DLP additive manufacturing. In conclusion, these findings open new avenues for ceramic AM across various applications, enhancing the potential for innovation in fields such as aerospace, biomedical engineering, and energy.

36 MATERIALS SCIENCE

The ATTO-Campina site: A new observatory for tropical convection and gas-aerosol-cloud-precipitation interactions in the Amazon

We present results from ATTO-Campina, a new permanent observational site in central Amazon, about 4 km from the ATTO towers. Operational since 2020, ATTO-Campina characterizes atmospheric, cloud and rainfall properties through remote sensing. The goal is to provide continuous, complementary measurements to the ATTO towers, addressing the rainforest’s complex gas-aerosol-cloud-precipitation dynamics. Using a 3.5-year dataset, we classified convective clouds into three types: shallow cumulus (ShCu), congestus (Con) or (Deep) clouds. The shallow-to-deep transition takes about three hours, starting with ShCu formation at 11:00 local time. The accumulated rainfall peak follows at about 16:00. Only weak downdrafts are present in the upper troposphere where previous studies indicate new particle formation (NPF) occurrence. Strong downdrafts are mostly limited to heights below 5 km. Con and Deep convective days have higher concentrations of ultrafine aerosol and lower concentrations of accumulation-mode particles compared to ShCu. Convective clouds also significantly modify gas mixing ratios. Deep convective clouds are associated with high near-surface O3, consistent with downward transport from the midtroposphere. Our results showcase the added detail achieved by integrating data from the ATTO towers and ATTO-Campina sites. Together, these sites support better understanding of interconnected gas-aerosol-cloud-precipitation processes in the Amazon and their evolution under climate change.

54 ENVIRONMENTAL SCIENCES

Study of Helium Irradiation Effect on Al6061 Alloy Fabricated by Additive Friction Stir Deposition

Additive friction stir deposition (AFS-D) is considered a productive method of additive manufacturing (AM) due to its ability to produce dense mechanical parts at a faster deposition rate compared to other AM methods. Al6061 alloy finds extensive application in aerospace and nuclear engineering; nevertheless, exposure to radiation or high-energy particles over time tends to deteriorate their mechanical performance. However, the effect of radiation on the components manufactured using the AFS-D method is still unexamined. In this work, samples from the as-fabricated Al6061 alloy, by AFS-D, and the Al6061 feedstock rod were irradiated with He+ ions to 10 dpa at ambient temperature. The microstructural and mechanical changes induced by irradiation of He+ were examined using a scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), transmission electron microscopy (TEM), and nanoindentation. This study demonstrates that, at 10 dpa of irradiation damage, the feedstock Al6061 produced a bigger size of He bubbles than the AFS-D Al6061. Nanoindentation analysis revealed that both the feedstock Al6061 and AFS-D Al6061 samples have experienced radiation-induced hardening. These studies provide a valuable understanding of the microstructural and mechanical performance of AFS-D materials in radiation environments, offering essential data for the selection of materials and processing methods for potential application in aerospace and nuclear engineering.

36 MATERIALS SCIENCE