Search NASA⌕ Search

SEARCH · Search NASA

Results for “initialization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36

Synthesis of hierarchical graphene coated porous Si anode for lithium-ion batteries

The ultra-high capacity and widespread availability of Si materials have resulted in them being the focus of extensive studies to replace the graphite anode. However, the main barriers preventing the Si anodes from large-scale applications are their huge volume change and severe interface reactions in the lithiation/delithiation process, which pulverizes its structure and subsequently deteriorates its cycle life. Here, micrometer-scale porous Si coated with graphene coating (mpSi@G) has been synthesized by using SiO 2 nanoparticles and novel coal-derived humic acid as feedstocks through a magnesiothermic reduction, followed by spray drying and calcination techniques. SEM, Raman, and X-ray absorption analysis demonstrate that the hierarchical graphene shell and micrometer-sized porous Si structure effectively release the Si anode's mechanical stress upon lithiation to achieve good structural stability. Here, the synthesized mpSi@G anode delivers a high initial lithiation capacity of 2974.9 mAh g –1 at 0.1 A g –1 with an initial coulombic efficiency of 70.2 %. Furthermore, the conductive hierarchical graphene network, along with the tight contacts of porous-Si and the graphene shell, contribute to a high capacity of 1109.5 mAh g –1 at a high current density of 5.0 A g –1 , showing excellent rate capability.

25 ENERGY STORAGE↗

Insights Into Thermal Runaway Mechanisms: Fast Tomography Analysis of Metal Agglomerates in Lithium-Ion Batteries

Thermal Runaway (TR) in lithium-ion batteries (LIB) is a critical technological and social concern. Whilst such events are rare, TR is characterized by uncontrollable heating leading to catastrophic failures. To deepen the understanding of the failure process and subsequently develop more accurate TR prediction models and as a result safer battery systems, we present in this work high-speed X-ray tomography for in-depth investigations of the copper current collector melting and agglomeration during TR. The melting process presents valuable real-time internal information about heat evolution during TR, previously challenging to access but crucially important for validating TR models. In this work, controlled failure studies combined with high-speed X-ray tomography were performed on two different commercial LIB models, subjecting them to both external heating and nail penetration to induce TR. Through real-time observation via high-speed tomography, followed by segmentation, rendering, and analysis, the formation of copper agglomerates was qualitatively and quantitatively characterized and visualized for the first time. Agglomerates tended to form either from the battery's outermost layers or centrally, depending on the method of TR initiation, and gives an indirect insight into the internal temperature evolution and distribution. Moreover, an initial comparative analysis between the battery models also revealed differences in agglomerate size, which has been linked to the thicker copper current collectors of one of the cell models. We further discuss the impact of larger copper agglomerates on heat distribution and safety. This study not only sheds light on the intricate dynamics of TR in LIBs but also underscores the pivotal role of 'gold-standard' imaging techniques in advancing battery safety, crucial for the robust modeling of TR and the future design of electric vehicle safety systems.

25 ENERGY STORAGE↗

Mechanically induced thermal runaway severity analysis of Li-ion batteries and continuous energy release monitoring

The large-scale deployment of Li-ion batteries in stationary energy storage and electrical vehicle applications demands a strong focus on safety, particularly on the thermal runaway risk and severity evaluation. A standardized single-side mechanical indentation test protocol was developed to induce an internal short-circuit (ISC) and evaluate cells' thermal runaway severity at different state of charge (SOC). The observed hazard severity (OHS in five categories) and evaluated scores in this work have a comprehensive consideration of each cell's capacity, initial voltage, SOC, temperature and voltage change, allowing a better evaluation of the cells' thermal runaway potential. This method was applied to about 200 Li-ion batteries in order to build an extensive thermal runaway database covering various SOCs, capacities and chemistries. In this study, we monitored the transitions of stored electrochemical energy and applied mechanical energy into both thermal energy and acoustic emissions (AE). The surface temperature and mechanical failures were monitored by infrared imaging and AE to capture critical events within battery cells throughout the mechanical indentation tests. Furthermore, the initial temperature maps can predict two types of follow-up events: thermal runaway or gradual heat release via conduction. Analyzing each cell's severity, AEs, and leveraging the evolving database offer insights into predicting occurrences of thermal runaway. The test method, thermal runaway severity evaluation and prediction, and the corresponding database provide battery designers, manufacturers, and end-users a clear overview of Li-ion batteries' thermal runaway potential under mechanical abuse, advancing the safety design of Li-ion batteries.

Acoustic emission↗

Adaptive Interface-PINNs (AdaI-PINNs) for transient diffusion: Applications to forward and inverse problems in heterogeneous media

We model transient diffusion in heterogeneous materials using a novel physics-informed neural networks framework (PINNs) termed Adaptive interface physics-informed neural networks or AdaI-PINNs (Roy et al. arXiv preprint arXiv:2406.04626, 2024). AdaI-PINNs utilize different activation functions with trainable slopes tailored to each material region within the computational domain, allowing for a fully automated and adaptive PINNs approach to model interface problems with strongly and weakly discontinuous solutions. To enhance its performance in highly heterogeneous transient diffusion systems, we prescribe a suite of robust practices, including appropriate non-dimensionalization of equations, a biased sampling method, Glorot initialization, and the hard enforcement of boundary and initial conditions. Here we evaluate the efficacy of the proposed method on several benchmark forward and inverse problems. Comparative studies on one-dimensional and two-dimensional benchmark problems reveal that the modified AdaI-PINNs outperform its unmodified counterpart, achieving root-mean-square errors that are at least two orders of magnitude better in forward problems. For inverse problems, the maximum errors in the approximated diffusion coefficients by modified AdaI-PINNs are four orders of magnitude better than those of the unmodified version. Additionally, modified AdaI-PINNs demonstrate improved stability in problems with large material mismatches.

42 ENGINEERING↗

A comprehensive numerical investigation on spray models for Direct-Injection Spark-Ignition engines

Gasoline direct-injection spark-ignition (DISI) engines generate a large portion of their unburned hydrocarbon (UHC) and soot emissions during the cold-start phase. A predictive computational fluid dynamics (CFD) modeling framework can be used to understand the physical processes that characterize fuel spray evolution and fuel-film formation at cold start conditions, which can help to reduce engine-out particulate emissions. This study systematically evaluated spray submodels and developed a set of simulation best practices for physical-numerical submodels with the goal of enabling accurate simulations of liquid spray behavior in a DISI engine. Three comprehensive experimental datasets containing free-spray projected liquid volume (PLV), liquid volume fraction (LVF), and near-field X-ray radiography data were used to validate the simulation results and evaluate the spray submodels. Systematic analysis delved into injected parcel distribution, droplet collision, spray breakup, and evaporation via a detailed assessment of the relevant spray submodels. Moreover, the effects of turbulence models and the initial turbulent flow properties on the liquid spray evolution were examined. Based on extensive calibration efforts, a set of simulation best practices for the free spray was developed and validated against the PLV/LVF data. Simulation results indicated that the uniform distribution for parcel initialization, coupled with appropriate droplet collision submodels, provides an improved spray morphology compared to the cluster distribution. The findings also underscored the importance of calibrating the Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) breakup model constants and droplet heat transfer coefficient scaling factor to achieve favorable agreement regarding measured liquid penetration and spray widths. In conclusion, this study marks a substantial stride towards accurately predicting fuel film evolution and soot formation within DISI engine performance.

ECN Spray G↗

Vacuum vessel design with lofted toroidal surfaces for a QHS configuration

A vacuum vessel in between the hot plasma and the magnetic coils is crucial for a fusion reactor. In this study, a tool is presented to perform the initial design of such a vessel automatically. Starting from the last closed flux surface, an algorithm is developed which lofts this manifold out as much as possible. At the same time, the algorithm makes sure that no intersection with the coils takes place. In the presented work, this algorithm is applied to the HSX stellarator and it has been verified that the resulting vessel wall can be built from an engineering perspective. Using field line tracing, the strikepoints on the vessel wall indicate the initial locations for a divertor.

HSX↗

Shadow of the Future: Developing Trust and Software within the Exascale Computing Project

Collaboration and team science are emerging areas of interest in software production. Historically, multi-institutional research collaborations are difficult to initiate and maintain, negatively impacting communication, negotiation, and dialogue between industry, government, and academic researchers. The Exascale Computing Project (ECP), a massive, multi-team, high-stakes initiative, facilitated broader research collaboration under a shared funding structure and extended timeline to support scientific discovery. Here, we conducted interviews with ECP teams, representing a variety of domain specialties, research institutions, and programming backgrounds. Using thematic analysis, we assessed how ECP’s structure created an environment of increased trust among projects and how software shared between teams facilitated sustained collaboration. We found that the expectation of future collaboration, i.e., the shadow of the future, greatly enhanced trust among teams and the quality of scientific software produced. Based on our findings within ECP projects, we connect to the existing literature on trust in software engineering and share recommendations for sustainable multi-institutional collaboration and shared best software practices.

Exascale computing project↗

Temperature dependence of uranium and thorium partitioning in igneous zircons

Zircon is a key mineral in geochronology because of its chemical and physical durability and tendency to incorporate radioactive trace elements such as U and Th. Quantifying the partitioning of the actinide elements is critical to constrain initial non-secular equilibrium amounts of 230 Th in zircon. An excess or deficit of 206 Pb will be produced from such an initial excess/deficit of 230 Th from the secular equilibrium condition, which influences the calculated 206 Pb/ 238 U age (Schärer, 1984, Mattinson, 1973). However, there is no standard way to calculate Th/U partitioning ratios when applying age corrections to young igneous zircon, making uncertainties hard to estimate. To better understand U and Th partitioning of zircon/melt that is the cornerstone of the secular disequilibrium correction, zircon was synthesized in one-atmosphere experiments using basaltic andesite, andesite, and rhyolite starting materials, doped with Zr, U, and Th. Different experimental temperatures and oxygen fugacity conditions (ΔQFM−4 to ΔQFM+4) were explored to examine their effects on U and Th partitioning. In addition, we specifically quantify the effects of sector zoning, fractional crystallization, and melt composition on U and Th partitioning. By combining experimental and natural zircon data, we find that temperature has the primary control on the partitioning of U and Th in the zircon and calibrate an inverse relationship between these partition coefficients and crystallization temperatures. The calibrated equation can be applied to the 230 Th correction for an improvement in the accuracy of Th-corrected 206 Pb/ 238 U dates when the zircon crystallization temperature is known.

206Pb/238U dating↗

Experimental platforms for investigating feature-driven jets for HED mix model validation

High-energy-density (HED) systems, such as inertial confinement fusion (ICF), are susceptible to hydrodynamic instabilities that can significantly affect both experimental results and modeling predictions. Isolated features, such as fill tubes or divots in the capsule, can cause material to jet as a result of the compressive shock exciting the Richtmyer–Meshkov instability, and serve as one of the primary degradation mechanisms in ICF yield. Simulations of feature-driven jets and how they mix require extensive experimental validation, particularly for understanding to what degree the initial size and shape of a feature influence jet dynamics, and how much instability feeds through downstream layers. A better understanding of feature-driven jetting can improve our mix modeling capabilities and increase hydrodynamic simulation accuracy. This manuscript describes a series of experimental platforms fielded by Los Alamos National Laboratory as a part of the Mshock Omega 60 and ModCons Omega EP campaigns to explore feature-driven jetting. These platforms are designed to benchmark jet evolution and growth as a function of initial feature size and shape, investigate jet-layer interactions leading to instability feedthrough, and will be used to characterize jet-jet interactions resulting from clusters of features. In conclusion, preliminary results for both platforms are shown. The ModCons experiments are on-going, and a discussion of future work directions is included.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Extraction of lithium from battery recycling wastewater using synergistic D2EHPA and TBP

The recycling of spent lithium-ion batteries (LIBs) poses significant challenges, including the generation of large volumes of chemically complex wastewater. The composition of this wastewater is influenced by both the intrinsic chemistry of the batteries and the specific recycling processes employed. Notably, this wastewater contains economically valuable components, such as lithium, which can be recovered. Here, in this study, a solvent extraction (SX) process was investigated as a method to recover lithium from battery recycling wastewater, especially from anode-washing stage. Initially, various commercial extractants were evaluated, including di(2-ethylhexyl)phosphoric acid (D2EHPA), mono-2-ethylhexyl (2-ethylhexyl)phosphonate (PC88A), bis(2,4,4-trimethylpentyl)phosphinic acid (Cyanex 272), 2-hydroxy-5-nonylacetophenone oxime (LIX 84-I), tri-butyl phosphate (TBP), and their combinations. Among these, D2EHPA + TBP demonstrated a synergism to advance and maximize the lithium extraction. Subsequently, the effects of key parameters, including D2EHPA concentration, TBP concentration, contact time, initial pH, and aqueous-to-organic (A/O) phase ratio, were systematically investigated and optimized. A two-stage SX approach was employed to enhance lithium recovery. Under the optimized conditions of 30.0 vol% D2EHPA, 10.0 vol% TBP, 10 min of contact time, and a 1:1 A/O phase ratio, a lithium extraction efficiency of more than 88% in a two-stage solvent extraction was achieved. Lithium was subsequently stripped from the loaded organic solution using sulfuric acid (H 2 SO 4 ). Using 2.0 M H 2 SO 4 , lithium stripping was achieved after two counter-current stripping stages at an organic-to-aqueous (O/A) phase ratio of 6:1. This stripping process enriched the lithium concentration by a factor of four compared to the original lithium concentration in the anode-washing wastewater. The recyclability of the synergistic D2EHPA + TBP system was also evaluated over four extraction-stripping cycles. The results demonstrated that the system maintained high extraction and stripping efficiencies.

D2EHPA↗

Modeling low cycle fatigue (LCF) of additively manufactured Hastelloy X using An accelerated crystal plasticity fatigue damage model

This paper presents a microstructure-based model for low cycle fatigue (LCF) behavior and life of Nickel-based alloy Hastelloy X manufactured using laser-powder bed fusion (L-PBF) additive manufacturing (AM). AM Hastelloy X, a solution-strengthened alloy, is tested at elevated temperature under fully reversed LCF conditions at different strain levels. A generalized plane strain finite element model is generated from electron backscatter diffraction (EBSD) characterization. The constitutive behavior of the material under fatigue is modeled using crystal plasticity and calibrated with both monotonic tensile and cyclic stress–strain data. The fatigue micro-crack initiation and propagation in the microstructure is modeled using a modified Chaboche fatigue damage model. An embedded boundary condition with a homogenous medium is used to apply the cyclic deformation and prevent numerically introduced over-constraints during fatigue simulation. A ‘cycle-jump’ method is used to accelerate the fatigue simulation and reduce the computational cost. The simulation results are compared to LCF experiments, showing satisfactory matches in cyclic stress behavior and number of cycles to macro-crack initiation for all applied strain ranges. In addition, the model illustrates the potential for quantifying microscale fatigue life impacting factors such as microstructure and surface roughness, which is needed to accurately quantify the reliability of AM components in service.

36 MATERIALS SCIENCE↗

Numerical analysis of coalescence-induced bubble departure for enhanced boiling heat transfer

Boiling heat transfer plays a crucial role in a wide range of applications, such as power generation, refrigeration, electronics cooling, and pharmaceutics. Among the various factors that influence boiling heat transfer, the dynamics of vapor bubble nucleation, growth, and departure from the heated surface stand out as particularly important. An emerging phenomenon that can promote the departure of bubbles smaller than the Fritz diameter is coalescence-induced departure. If the dynamics of this process are fully understood, then surfaces can be engineered to promote faster bubble departure and substantially increase the performance of boiling heat transfer. Further, this work expands on published results by presenting a detailed numerical analysis of bubble coalescence and departure for a range of initial bubble diameters and size ratios between coalescing bubbles. Analysis of the results is focused on explaining how the release of surface energy and bubble surface dynamics lead to bubble departure, as well as fundamentally distinguishing capillary–inertial jumping and buoyant–inertial departure mechanisms across different bubble sizes and size ratios. The results show that both the initial sizes of the coalescing bubbles and the ratio between their sizes can determine whether the merged bubble will leave the surface through capillary–inertial jumping or buoyant departure. Below a certain bubble size, the release of surface energy by the merger is not sufficient to propel the merged bubble from the surface.

42 ENGINEERING↗

High and Ultra-High Temperature Reaction Kinetics by Single Nanoparticle Mass Spectrometry

Methodology is presented for non-destructive, optically-detected single nanoparticle (NP) mass spectrometry, with the goal of extracting surface reaction kinetics for single NPs at high temperatures. Methods for determining the NP charge, mass, and temperature as a function of time are discussed, and the data are used to extract both the absolute kinetics for mass change, as well as the efficiencies of the surface processes that cause them. Factors that contribute to the uncertainties in absolute and relative mass determination, and in the resulting kinetic parameters, are discussed. The method allows the NP-to-NP variations in initial reactivity to be measured directly, along with the time evolution of reactivity resulting from NP structural/compositional changes that occur under reaction conditions. The strengths and limitations of single nanoparticle mass spectrometry as a high temperature surface kinetics tool are discussed in the context of sublimation and O2 oxidation kinetics experiments for single hafnium (Hf) NPs at temperatures ranging above 2400 K. The Hf oxidation kinetics are compared to analogous oxidation experiments for silicon, graphite, and carbon black NPs. In all four cases, the oxidation chemistry was dominated by processes that result in net mass loss, and the distinct mechanisms responsible are discussed. All four NPs also eventually passivated, i.e., the efficiencies for oxidative etching decreased by at least two orders of magnitude, relative to the initial efficiencies. Furthermore, the passivation mechanisms, which are quite different for carbon, compared to silicon or hafnium, are discussed. Carbon NP passivation is attributed to structural isomerization leading to fully coordinated, fullerene-like NP surfaces, while for silicon and hafnium, passivation results from delayed formation of an oxide layer, triggered by accumulation of oxygen in the NP sub-surface region.

36 MATERIALS SCIENCE↗

The role of annealing and grain boundary controls on the mechanical properties of limestones and marbles

Chemical and mechanical processes are coupled in many geological and geochemical environments. Reactive processes anneal defects and restructure grain boundaries, modifying their elastic properties, levels of internal friction, wave propagation rates and fracture behaviors. The nature of these changes is, however, contingent on the initial state of the rock. Here, in this study, impulse excitation was used to measure changes in mechanical properties as a function of dry and steam heating time at 300 °C for three carbonate rocks: Carrara marble, Carthage marble (Burlington Limestone), and Texas Cream limestone (Edwards limestone), with initial porosities of about 1 %, 3 %, and 27 %, respectively. Frequency-dependent phenomena along with mineral recrystallization were observed. This was coupled with small-angle X-ray and neutron scattering analysis to determine the relationship between changes in bulk mechanical and microstructural properties. An observed decrease in both the Young's and shear moduli in the experimental limestones as a function of heating time reflects and quantifies a reduction in the stiffness of the rock due to annealing. The internal friction of the samples first increases then decreases with reaction time, reflecting defect annealing, but this was balanced against grain boundary dissolution apparently driven by condensation of steam in the confined grain-boundary environment. This suggests an increase in the boiling point under confinement leading to dissolution, increased porosity and widening of the grain boundaries. In addition, comparison of small-angle X-ray and neutron scattering results suggests that it is inappropriate to assume that pores are empty for quantitative analysis of typical small-angle scattering samples.

58 GEOSCIENCES↗

Cleavage at the nsp5–nsp6 site of SARS-CoV-2 main protease intermediate precursor is faster from a monomer than a dimer form

Our previous studies of severe acute respiratory syndrome coronavirus 2 main protease (MPro) precursor monomer indicate that the initial N-terminal nonstructural protein (nsp)4/nsp5 cleavage occurs intramolecularly, with a small fraction of the active site loop equilibrium being in the active state. To understand the influence of dimer formation of MPro upon N-terminal cleavage on the subsequent C-terminal nsp5/nsp6 intermolecular cleavage kinetics, the stepwise processing of a monomeric, inactive precursor containing the native terminal cleavage sites of MPro (MBP- (−6) MPro C145A(+3) -GB1-6H, 86.2 kDa) by mature WT MPro (MPro WT ) was investigated. Differential scanning fluorimetry and analytical ultracentrifugation measurements of various MPro constructs suggest that the C145A mutation decreases the dimer dissociation constant (K dimer ) by ∼26-fold, relative to WT C145 and H41A. The monomeric precursor’s nsp4–nsp5 site appears to saturate MProWT’s active sites and cleave faster, followed by a slower first-order cleavage at the C-terminal site. No detectable product resulting from the C-terminal cleavage is observed until most of the N-terminal cleavage is complete. The initial intermediate product (termed MPro C145A-IP ) is a homodimer with an estimated K dimer of <0.05 μM. In contrast, the first-order kinetics observed for the cleavage of the monomeric form of the intermediate product is at least 300 times faster than that of the dimer form. Room-temperature X-ray structure of the MPro C145A-IP –ensitrelvir complex is like that of the MPro WT –ensitrelvir complex and reveals a dynamic C-terminal region including MPro residues 302 to 306. These results are interpreted from the point of view of a mechanism in which nsp5–nsp6 cleavage may occur from a monomeric intermediate, and dimer formation restricts this cleavage.

60 APPLIED LIFE SCIENCES↗

GrainGNN: A dynamic graph neural network for predicting 3D grain microstructure

We propose GrainGNN, a surrogate model for the evolution of polycrystalline grain structure under rapid solidification conditions in metal additive manufacturing. High fidelity simulations of solidification microstructures are typically performed using multicomponent partial differential equations (PDEs) with moving interfaces. The inherent randomness of the PDE initial conditions (grain seeds) necessitates ensemble simulations to predict microstructure statistics, e.g., grain size, aspect ratio, and crystallographic orientation. Here, currently such ensemble simulations are prohibitively expensive and surrogates are necessary.In GrainGNN, we use a dynamic graph to represent interface motion and topological changes due to grain coarsening. We use a reduced representation of the microstructure using hand-crafted features; we combine pattern finding and altering graph algorithms with two neural networks, a classifier (for topological changes) and a regressor (for interface motion). Both networks have an encoder-decoder architecture; the encoder has a multi-layer transformer long-short-term-memory architecture; the decoder is a single layer perceptron.We evaluate GrainGNN by comparing it to high-fidelity phase field simulations for in-distribution and out-of-distribution grain configurations for solidification under laser power bed fusion conditions. GrainGNN results in 80%–90% pointwise accuracy; and nearly identical distributions of scalar quantities of interest (QoI) between phase field and GrainGNN simulations compared using Kolmogorov-Smirnov test. GrainGNN's inference speedup (PyTorch on single x86 CPU) over a high-fidelity phase field simulation (CUDA on a single NVIDIA A100 GPU) is 150×–2000× for 100-initial grain problem. Further, using GrainGNN, we model the formation of 11,600 grains in 220 seconds on a single CPU core.

36 MATERIALS SCIENCE↗

An efficient explicit implementation of a near-optimal quantum algorithm for simulating linear dissipative differential equations

We propose an efficient block-encoding technique for the implementation of the Linear Combination of Hamiltonian Simulations (LCHS) for simulating dissipative initial-value problems. This algorithm approximates a target nonunitary operator as a weighted sum of Hamiltonian evolutions, thereby emulating a dissipative problem by mixing various time scales. We introduce an efficient encoding of the LCHS into a quantum circuit based on a simple coordinate transformation that turns the dependence on the summation index into a trigonometric function. Classically, this method is equivalent to the use of a highly accurate Fejér-Clenshaw-Curtis quadrature formula. Quantumly, this significantly simplifies block-encoding of a dissipative problem and allows one to perform an exponential number of Hamiltonian simulations by a single Quantum Signal Processing (QSP) circuit. The resulting LCHS circuit has high success probability and the selector scales logarithmically with the number of terms in the LCHS sum and linearly with time. Careful analysis of error convergence proves that this method is more efficient than other LCHS circuits that have recently appeared in the literature. We verify the quantum circuit and its scaling by simulating it on a digital emulator of fault-tolerant quantum computers and, as a test problem, solve the advection-diffusion equation. The proposed algorithm can be used for simulating a wide class of nonunitary initial-value problems including the Liouville equation with added dissipation and linear embeddings of nonlinear systems, such as the Koopman-von Neumann and Carleman embeddings.

Novikau, I [Lawrence Livermore National Laboratory↗

Effect of die design on microstructure and mechanical joint strength in friction self-piercing riveted AA7055-T76 and AA7055-T76

In the present study, a unique friction self-piercing riveting (F-SPR) was applied to join high-strength, low-ductility aluminum alloy (AA) 7055-T76 and AA7055-T76 to mitigate a cracking issue. Also, the effect of die design on both joint formation and the mechanical joint performance were investigated. A crack-free joint was achieved when joining AA7055-T76 and AA7055-T76 by F-SPR. As the bottom diameter of the die increased, the mechanical interlocking distance initially increased then became almost saturated. At the same time, the solid-state bonding gradually disappeared, and the lap-shear fracture changed from bottom aluminum fracture to rivet pull-out with partial bottom aluminum fracture. The average maximum lap-shear joint strength of 11.57 kN and cross tension of 5.65 kN were achieved from the D2 die design owing to the combined contributions from high mechanical interlocking distance and good solid-state bonding at the joint interface. Ultrafine grain refinement was observed at the region next to the rivet shank outer surface and along the materials flow line between the top and bottom aluminum sheet in the rivet cavity. Further, because of the same joint-process parameters, the hardness profile at the joints made by different dies did not show obvious differences. As the distance from the base metal to the rivet outer surface decreased, frictional heat caused the hardness to initially decrease from 190 to 150 HV in the heat-affected zone. Hardness increased up to 175 HV in the thermomechanical affected zone (TMAZ-I) owing to large plastic deformation.

36 MATERIALS SCIENCE↗