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At least 613 records · Page 34

Functional group activation and coupling agent migration induced by plasma treatment in adhesive for enhanced toughness of metal-composite joints

Commercial adhesive paste was additionally activated using low-power oxygen plasma with different plasma exposure durations to investigate its interfacial bonding contribution in adhesively-bonded Aural-5/CFRP-PA6 double cantilever beam (DCB) joints with plasma-treated adherends. The plasma-treated adhesive showed enhanced functional peak intensities in Fourier transfer infrared spectroscopy (FTIR) as plasma exposure time was increased, and some degree of oxidation was also detected via X-ray photoelectron spectroscopy (XPS). A small molecule, dicyandiamde (coupling agent) in adhesive was migrated to adhesive layer, where double concentration of coupling agent was detected after 10 minutes of plasma treatment. As a result, characterization of the adhesive/CFRP-PA6 interface after DCB fracture showed additional chemical bonds formed through amine-initiated epoxy ring opening polymerization, as well as amide bonds and ester bonds. In conclusion, these additional bonds at the adhesive/CFRP-PA6 interfaces led to significantly increased failure extensions and fracture energies of the joints as the plasma exposure time on the adhesive increased, compared to the joints with plasma-treated adherends but non-plasma-treated adhesive as commonly seen in the literature.

36 MATERIALS SCIENCE↗

Structure of Ti-6Al-4V nanostructured titanium alloy joint obtained by resistance spot welding

The structure of weld joints of the titanium alloy Ti-6Al-4V in the initial ultrafine-grained state, obtained by resistance spot welding, is studied using the optical and scanning electron microscopy method and the X-ray structure analysis. The carried out studies show the relationship of the metal structure in the weld zone with main joint zones. The structure in the core zone and the heat affected zone is represented by finely dispersed grains of needle-shaped martensite, differently oriented in these zones. The change in the microhardness in the longitudinal section of the weld joint clearly correlates with structural changes during welding.

36 MATERIALS SCIENCE↗

Cross-Domain Recognition by Identifying Joint Subspaces of Source Domain and Target Domain

This paper introduces here a new method to solve the cross-domain recognition problem. Different from the traditional domain adaption methods which rely on a global domain shift for all classes between the source and target domains, the proposed method is more flexible to capture individual class variations across domains. By adopting a natural and widely used assumption that the data samples from the same class should lay on an intrinsic low-dimensional subspace, even if they come from different domains, the proposed method circumvents the limitation of the global domain shift, and solves the cross-domain recognition by finding the joint subspaces of the source and target domains. Specifically, given labeled samples in the source domain, we construct a subspace for each of the classes. Then we construct subspaces in the target domain, called anchor subspaces, by collecting unlabeled samples that are close to each other and are highly likely to belong to the same class. The corresponding class label is then assigned by minimizing a cost function which reflects the overlap and topological structure consistency between subspaces across the source and target domains, and within the anchor subspaces, respectively. We further combine the anchor subspaces to the corresponding source subspaces to construct the joint subspaces. Subsequently, one-versus-rest support vector machine classifiers are trained using the data samples belonging to the same joint subspaces and applied to unlabeled data in the target domain. We evaluate the proposed method on two widely used datasets: 1) object recognition dataset for computer vision tasks and 2) sentiment classification dataset for natural language processing tasks. Comparison results demonstrate that the proposed method outperforms the comparison methods on both datasets.

97 MATHEMATICS AND COMPUTING↗

Optimizing diffusion bonding parameters to maximize the strength of AA6061 aluminum and AZ61A magnesium alloy joints

The main difficulty when joining magnesium (Mg) and aluminum (Al) alloys by fusion welding process lies in the existence of oxide films and formation of brittle intermetallic in the weld region. However, solid-state welding processes such as friction welding and diffusion bonding are suitable processes to join these two materials. The diffusion bonding process parameters such as bonding temperature, bonding pressure, holding time, and surface roughness of the bond specimen play a major role to determine the joint strength. In this investigation, an attempt was made to develop empirical relationships to predict the lap shear strength and bonding strength of diffusion bonded dissimilar joints of AZ61A magnesium and AA6061 aluminum alloys, incorporating the above-mentioned parameters. Response surface methodology (RSM) was applied to optimize the diffusion bonding process parameters to attain the maximum shear strength and bonding strength of the joint. From this investigation, it is found that the bonds fabricated with the bonding temperature of 420.43°C, bonding pressure of 7.70 MPa, holding time of 27.15 min, and surface roughness of 0.10 μm exhibited maximum shear strength and bonding strength of 51.24 and 72.10 MPa, respectively.

36 MATERIALS SCIENCE↗

Functional Adaptation of LPS-affected Dentoalveolar Fibrous Joints in Rats

We report the functional interplay between cementum of the root and alveolar bone of the socket is tuned by a uniquely positioned 70–80 µm wide fibrous and lubricious ligament in a dentoalveolar joint (DAJ). In this study, structural and biomechanical properties of the DAJ, periodontal ligament space (PDL-space also known as the joint space), alveolar bone of the socket, and cementum of the tooth root that govern the biomechanics of a lipopolysaccharide (LPS)-affected DAJ were mapped both in space and time. The hemi-maxillae from 20 rats (4 control at 6 weeks of age, 4 control and 4 LPS-affected at 12 weeks of age, 4 control and 4 LPS-affected at 16 weeks of age) were investigated using a hybrid technique; micro-X-ray computed tomography (5 µm resolution) in combination with biomechanical testing in situ. Temporal variations in bone and cementum volume fractions were evaluated. Trends in mineral apposition rates (MAR) in additional six Sprague Dawley rats (3 controls, 3 LPS-affected) were revealed by transforming spatial fluorochrome signals to functional growth rates (linearity factor - RW) of bone, dentin, and cementum using a fast Fourier transform on fluorochrome signals from 100-µm hemi-maxillae sections. An overall change in LPS-affected DAJ biomechanics (a 2.5–4.5X increase in tooth displacement and 2X tooth rotation at 6 weeks, no increase in displacement and a 7X increase in rotation at 12 weeks; 27% increase in bone effective strain at 6 weeks and 11% at 12 weeks relative to control) was associated with structural changes in the coronal regions of the DAJ (15% increase in PDL-space from 0 to 6 weeks but only 5% from 6 to 12 weeks compared to control). A significant increase (p < 0.05) in PDL-space between ligated and age-matched control was observed. The bone fraction of ligated at 12 weeks was significantly lower than its age-matched control, and no significant differences (p > 0.05) between groups were observed at 6 weeks. Cementum in the apical regions grew faster but nonlinearly (11% and 20% increase in cementum fraction (CF) at 6 and 12 weeks) compared to control. Alveolar bone revealed site-specific nonlinear growth with an overall increase in MAR (108.5 µm/week to 126.7 µm/week after LPS treatment) compared to dentin (28.3 µm/week in control vs. 26.1 µm/week in LPS-affected) and cementum (126.5 µm/week in control vs. 119.9 µm/week in LPS-affected). A significant increase in CF (p < 0.05) in ligated specimens was observed at 6 weeks of age. Anatomy-specific responses of cementum and bone to the mechano-chemo stimuli, and their collective temporal contribution to observed changes in PDL-space were perpetuated by altered tooth movement. Data highlight the “resilience” of DAJ function through the predominance of nonlinear growth response of cementum, changes in PDL-space, and bone architecture. Despite the significant differences in bone and cementum architectures, data provided insights into the reactionary effects of cementum as a built-in compensatory mechanism to reestablish functional competence of the DAJ. The spatial shifts in architectures of alveolar bone and cementum, and consequently ligament space, highlight adaptations farther away from the site of insult, which also is another novel insight from this study. These adaptations when correlated within the context of joint function (biomechanics) illustrate that they are indeed necessary to sustain DAJ function albeit being pathological.

60 APPLIED LIFE SCIENCES↗

WE-AB-207B-02: A Bayesian Network Approach for Joint Prediction of Tumor Control and Radiation Pneumonitis (RP) in Non-Small-Cell Lung Cancer (NSCLC)

Purpose: NSCLC radiotherapy treatment is a trade-off between controlling the tumor while limiting radiation-induced toxicities. Here we identify hierarchical biophysical relationships that could simultaneously influence both local control (LC) and RP by using an integrated Bayesian Networks (BN) approach. Methods: We studied 79 NSCLC patients treated on prospective protocol with 56 cases of LC and 21 events of RP. Beyond dosimetric information, each patient had 193 features including 12 clinical factors, 60 circulating blood cytokines before and during radiotherapy, 62 microRNAs, and 59 single-nucleotide polymorphisms (SNPs). The most relevant biophysical predictors for both LC and RP were identified using a Markov blanket local discovery algorithm and the corresponding BN was constructed using a score-learning algorithm. The area under the free-response receiver operating characteristics (AU-FROC) was used for performance evaluation. Cross-validation was employed to guard against overfitting pitfalls. Results: A BN revealing the biophysical interrelationships jointly in terms of LC and RP was developed and evaluated. The integrated BN included two SNPs, one microRNA, one clinical factor, three pre-treatment cytokines, relative changes of two cytokines between pre and during-treatment, and gEUDs of the GTV (a=-20) and lung (a=1). On cross-validation, the AUC prediction of independent LC was 0.85 (95% CI: 0.75–0.95) and RP was 0.83 (0.73–0.92). The AU-FROC of the integrated BN to predict both LC/RP was 0.81 (0.71–0.90) based on 2000 stratified bootstrap, indicating minimal loss in joint prediction power. Conclusions: We developed a new approach for multiple outcome utility application in radiotherapy based on integrated BN techniques. The BN developed from large-scale retrospective data is able to simultaneously predict LC and RP in NSCLC treatments based on individual patient characteristics. The joint prediction is only slightly compromised compared to independent predictions. Our approach shows promise for use in clinical decision support system for personalized radiotherapy subject to multiple endpoints. These studies were supported by a grant from the NCI/NIH P01-CA59827.

60 APPLIED LIFE SCIENCES↗

Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)

We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO2 EOR projects utilizing the water-alternating-gas (WAG) process. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.

02 PETROLEUM↗

Investigation of Bolt Preload Relaxation for JWST Thermal Heat Strap Assembly Joints with Aluminum-1100 and Indium Gaskets

Accurately predicting fastener preload relaxation in the James Webb Space Telescope (JWST) heat strap assemblies is essential to insure adequate thermal performance during its mission lifecycle. The mechanisms for preload relaxation in the strap joints include Al-1100 material creep, indium gasket flow-out, and embedment of the joint faying surfaces. This report documents the results from a bolted joint relaxation test, including analysis and curve fitting of the test data for predicting preloads five years after initial torque application. The report also includes the derivation of a preload uncertainty factor enveloping both torque/preload application scatter and expected preload relaxation at the end of mission life.

Joint↗

Investigation of Bolt Preload Relaxation for JWST Thermal Heat Strap Assembly Joints with Aluminum-1100 and Indium Gaskets

Accurately predicting fastener preload relaxation in the James Webb Space Telescope (JWST) heat strap assemblies is essential to insure adequate thermal performance during its mission lifecycle. The mechanisms for preload relaxation in the strap joints include Al-1100 material creep, indium gasket flow-out, and embedment of the joint faying surfaces. This report documents the results from a bolted joint relaxation test, including analysis and curve fitting of the test data for predicting preloads five years after initial torque application. The report also includes the derivation of a preload uncertainty factor enveloping both torque/preload application scatter and expected preload relaxation at the end of mission life.

Preload↗

Flat-H Redundant Frangible Joint Design Evolution 2018: Feasibility Study Conclusions

This paper reports results of an investigation into developing a single failure tolerant pyrotechnic linear separation system which features completely redundant explosive trains suitable for human spaceflight. It is a follow up to “Flat-H Redundant Frangible Joint Design Evolution 2017” and “Flat-H Redundant Frangible Joint Evolution”. The paper chronicles the history of the redundant frangible joint development program including testing, analysis, and design improvements from 2014 to the present culminating in a successful proof-of-concept prototype. The paper describes work done to address debris control and containment of combustion products. A performance optimization strategy is presented along with optimization results. Additionally a novel containment manifold design is presented with test results.

Structures↗

Electrifying the U.S. Transportation System with the Joint Office

The Joint Office of Energy and Transportation is accelerating an electrified transportation system that is convenient, reliable, affordable, accessible, and equitable. The Joint Office was created under the Bipartisan Infrastructure Law (BIL) to leverage the combined expertise of the U.S. Departments of Energy and Transportation. This is an overview fact sheet describing the Joint Office of Energy and Transportation.

ADVANCED PROPULSION SYSTEMS↗

A new algorithm for three‐dimensional joint inversion of body wave and surface wave data and its application to the Southern California plate boundary region

Abstract We introduce a new algorithm for joint inversion of body wave and surface wave data to get better 3‐D P wave ( V p ) and S wave ( V s ) velocity models by taking advantage of the complementary strengths of each data set. Our joint inversion algorithm uses a one‐step inversion of surface wave traveltime measurements at different periods for 3‐D V s and V p models without constructing the intermediate phase or group velocity maps. This allows a more straightforward modeling of surface wave traveltime data with the body wave arrival times. We take into consideration the sensitivity of surface wave data with respect to V p in addition to its large sensitivity to V s , which means both models are constrained by two different data types. The method is applied to determine 3‐D crustal V p and V s models using body wave and Rayleigh wave data in the Southern California plate boundary region, which has previously been studied with both double‐difference tomography method using body wave arrival times and ambient noise tomography method with Rayleigh and Love wave group velocity dispersion measurements. Our approach creates self‐consistent and unique models with no prominent gaps, with Rayleigh wave data resolving shallow and large‐scale features and body wave data constraining relatively deeper structures where their ray coverage is good. The velocity model from the joint inversion is consistent with local geological structures and produces better fits to observed seismic waveforms than the current Southern California Earthquake Center (SCEC) model.

Fang, Hongjian↗

Joint Modeling of Wind Speed and Wind Direction Through a Conditional Approach

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. In this work, we develop a conditional approach to model these two variables, where the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. To accommodate the circular nature of wind direction, a von Mises mixture model is used; the conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the dependence of the Weibull parameters on wind direction. A Monte Carlo simulation study indicates that our method outperforms two other approaches in estimation efficiency: one that utilizes periodic spline quantile regression and another that generates data from the commonly used Abe-Ley distribution for cylindrical data. We illustrate our method by using the output from a regional climate model to investigate how the joint distribution of wind speed and direction may change under some future climate scenarios. Our method indicates significant changes in the variation of wind speed with respect to some directions.

17 WIND ENERGY↗

Surface engineering to enhance heat generation and joint strength in dissimilar materials AZ31 and DP590 ultrasonic welding

A multiscale simulation approach was developed and employed to optimize the sheet surface conditions for higher interfacial temperature and joint strength in ultrasonic welding of magnesium alloy AZ31 and dual-phase steel DP590. First, a mesoscale model was used to study the relationship between friction coefficient and surface roughness, which can be modified by various engineering methods. Then a macroscopic process model was employed to study the effects of surface roughness on heat generation, indicating that a temperature increase can be achieved with rougher surfaces on two sides of both DP590 and AZ31 sheets. Samples prepared by sanding and filing, as well as grinding, were first characterized for surface roughness and then welded under ultrasonic vibration. An infrared camera was used to measure temperatures in situ for model validation. Overall, lap shear test results for the welded joint showed that the joint strength can be improved by 10~25% using filing and round grinding methods as a result of the enhanced heat generation and mechanical interlocking on the interface.

42 ENGINEERING↗

Analysis of Acoustic Emission Propagation in Metal-to-Metal Adhesively Bonded Joints

Acoustic emission (AE) monitoring shows promise as one of the most effective methods for condition monitoring of adhesively-bonded joints. Previous research has demonstrated its ability to detect, locate and classify adhesive joint failure, though in these studies little attention appears to have been paid to the differences in AE wave propagation through the bonded and un-bonded sections of the specimens tested, or to the effects of the wave modes excited or the propagation distances. This paper details an experimental study conducted on large aluminium sheet specimens to identify the effects of the presence of an adhesive layer on AE wave propagation. Three specimens are considered; a single aluminium sheet, two aluminium sheets placed together without adhesive, and an adhesively-bonded specimen. A pencil lead break (PLB) is used as a simulated AE source, and is applied to the three specimens at varying propagation distances and orientations. The acquired signals are processed using wavelet-transforms to explore time-frequency features, and compared with modified group-velocity curves based on the Rayleigh–Lamb equations to allow identification of wave-modes and edge-reflections. The effects of propagation distance and source orientation are investigated while comparison is made between the three specimens. It is concluded that while the wave propagation modes can be approximated as being constant throughout all three specimens, there is a significant change in the received waveforms due to the attenuation of high-frequency components exhibited by the bonded specimen. These findings may be utilised to provide a deeper understanding of acquired AE data, improving the current abilities to identify, locate and characterise damage mechanisms occurring within adhesive joints, ultimately improving safety in the use of adhesive bonding for critical applications.

42 ENGINEERING↗

Simultaneous optimal system and controller design for multibody systems with joint friction using direct sensitivities

Abstract Real-world multibody systems are often subject to phenomena like friction, joint clearances, and external events. These phenomena can significantly impact the optimal design of the system and its controller. This work addresses the gradient-based optimization methodology for multibody dynamic systems with joint friction using a direct sensitivity approach. The Brown–McPhee model has been used to characterize the joint friction in the system. This model is suitable for the study due to its accuracy for dynamic simulation and its compatibility with sensitivity analysis. This novel methodology supports codesign of the multibody system and its controller, which is especially relevant for applications like robotics and servo-mechanical systems, where the actuation and design are highly dependent on each other. Numerical results are obtained using a software package written in Julia with state-of-the-art libraries for automatic differentiation and differential equations. Three case studies are provided to demonstrate the attractive properties of simultaneous optimal design and control approach for certain applications.

Verulkar, Adwait↗

Triaxial Constraint and Tensile Strength Enhancement in Brazed Joints

A brazed joint consists of a low-melting point and thin interlayer sandwiched between the high-melting-point base materials, in which the interlayer strength is typically lower than that of the base material. When this butt-joined composite is loaded uniaxially in the direction perpendicular to the plane of the brazing layer, the tensile strength is found to be much higher than that of the braze. This seems to violate the iso-stress condition in such a butt-joint serial configuration. Furthermore, the stress triaxiality has been usually ascribed, but without a quantitative rationalization, as being responsible for this tensile strength enhancement. Here a complete finite element simulation has been conducted to study the dependence of triaxiality and strength enhancement on geometric and material parameters. Two asymptotic limit solutions (based on Bridgman and Xia–Shih solutions, respectively) have been identified to understand the simulation results. The critical role of void evolution has been revealed when making a quantitative comparison to available experiments. In addition, ductility of the brazed joint, which has not been fully addressed in literature, is investigated by the Gurson–Tvergaard–Needleman model.

36 MATERIALS SCIENCE↗

Improving Joint Formation and Tensile Properties of Dissimilar Friction Stir Welding of Aluminum and Magnesium Alloys by Solving the Pin Adhesion Problem

Friction stir welding (FSW), as a solid-state welding technology invented by TWI in 1991, has potential to join dissimilar Al/Mg alloys. In this study, the pin adhesion phenomenon affecting joint quality during FSW of 6061-T6 aluminum and AZ31B magnesium alloys was investigated. The adhesion phenomenon induced by higher heat input easily transformed the tapered-and-screwed pin into a tapered pin, which greatly reduced the tool’s ability to drive the plasticized materials and further deteriorated joint formation. Under the condition without the pin adhesion, the complex intercalated interlayer at the bottom of stir zone was beneficial to mechanical interlocking of Al/Mg alloys, improving tensile properties. However, the formation of intermetallic compounds was still the main reason of the joint fracture, significantly deteriorating tensile properties. Under the welding speed of 60 mm/min without the pin adhesion phenomenon, the maximum tensile strength of 107 MPa and elongation of 1.2% were achieved.

36 MATERIALS SCIENCE↗