Friction stir welding (FSW) is an advantageous solid-state joining process, suitable for many materials in the energy, aerospace, naval and automotive industries. Like all other welding processes, friction stir welding requires non-destructive evaluation (NDE). The time and resources to preform NDE is expensive. To reduce these costs, nontraditional NDE methods are being developed for FSW. Spectral based defect recognition uses the forces during the welding process to validate weld quality. Although spectral NDE methods have shown promise as an alternative NDE processes, many research welding speeds do not correspond to manufacturing speeds, nor do they explain the relationship between the spectral data and the process. The purpose of this work is to explore the possibility of acquiring additional information about the defect. Namely the defect’s type, location, and magnitude. In this study, welds with “wormhole” defects were produced at 2000, 2500 and 3000 mmpm in 5754 aluminum. The welding process forces and torque were measured and analyzed spectrally. The welded plates were then imaged with x-ray photography, a validated NDE method. It was found that low frequencies (0 – 4 Hz) in the y & z force signals correlate with defect presence in high speed FSW. In addition, the strong correlation between the spectral data and the presence of a defect allowed for defect magnitude predictions. Linear fits were applied to the defect measurements and the spectral data. Large error inhibits the wide use of this prediction method.

Friction stir welding (FSW) is an advantageous solid-state joining process, suitable for many materials in the energy, aerospace, naval and automotive industries. Like all other welding processes, friction stir welding requires non-destructive evaluation (NDE). The time and resources to preform NDE is expensive. To reduce these costs, nontraditional NDE methods are being developed for FSW. Spectral based defect recognition uses the forces during the welding process to validate weld quality. Although spectral NDE methods have shown promise as an alternative NDE processes, many research welding speeds do not correspond to manufacturing speeds, nor do they explain the relationship between the spectral data and the process. The purpose of this work is to explore the possibility of acquiring additional information about the defect. Namely the defect’s type, location, and magnitude. In this study, welds with “wormhole” defects were produced at 2000, 2500 and 3000 mmpm in 5754 aluminum. The welding process forces and torque were measured and analyzed spectrally. The welded plates were then imaged with x-ray photography, a validated NDE method. It was found that low frequencies (0 – 4 Hz) in the y & z force signals correlate with defect presence in high speed FSW. In addition, the strong correlation between the spectral data and the presence of a defect allowed for defect magnitude predictions. Linear fits were applied to the defect measurements and the spectral data. Large error inhibits the wide use of this prediction method.

A friction stir weld (FSW) is a solid state joining operation whose processing parameters are currently determined by lengthy trial and error methods. To implement FSWing rapidly in various applications will require an approach for predicting process parameters based on the physics of the process. Based on hot working conditions for metals, a kinematic model has been proposed for calculating the shear strain and shear strain rates during the FSW process, validation of the proposed model with direct measuring is difficult however. Since the shear strain and shear strain rates predicted for the FSW process, are similar to those predicted in metal cutting, validation of the FSW algorithms with microstructural studies of metal chips may be possible leading to the ability to predict FSW processing parameters.

The workpiece materials used in this study are CuNb nano-layered composites (NLC) which are produced in bulk form by accumulative roll bonding (ARB). CuNb NLC panels are of interest because of their increase in strength and radiation damage tolerance when compared to either of their bulk constituents. These increased properties stem from the bi-metal interface, and the nanometer length-scale of the layers. However to be commercially viable, methods to successfully join the ARB NLC which retain the layered structure panels are needed. Friction stir welding is investigated in this study as a possible joining method that can join the material while maintaining its layered structure and hence its properties. Mechanical properties of the weld were measured at a macro level using tensile testing, and at a local level via nano-indentation. The post weld layer structure was analyzed to provide insight into the flow paths. The grain orientation of the resulting weld nugget was also analyzed using electron backscatter diffraction and transmission Kikuchi diffraction. Results from this study show that the nano-layered structure can be maintained in the CuNb NLC by control of the friction stir welding parameters. The resulting microstructure is dependent on the strain experienced during the joining process. A variation in layer thickness reduction is correlated with increasing shear strain. Above a critical level of shear strain, the NLC microstructure was observed to fragment into equiaxed grains with a higher hardness than the NLC panels. Results from this study are also used to further the understanding of the material flow and hot working conditions experienced during the friction stir welding process.

Friction stir welding (FSW) is a solid-state joining process that offers advantages over traditional fusion welding. The amount of heat generated during a FSW process greatly influences the final properties of the weld. The heat is generated through two main mechanisms: friction and plastic deformation, with friction being the larger contributor in a FSW process. There is a need to develop better predictive models of the heat generation and heat transfer in FSW. Almost all models seen in the literature validate temperature predictions on only one side of the tool/workpiece interface, thus ignoring possible inaccuracy that comes from incorrect partitioning of heat generated by friction. This work seeks to model and validate both sides of the interface by matching experimental results for both the plunge and steady state phases of FSW for AA 6061-T6. Proper model validation allowed for a study of the sensitivity of the model predictions to changes in the friction coefficient and heat transfer coefficient at the tool/workpiece interface. Most models in the literature use the Coulomb friction law with a fixed friction coefficient, even though the Norton law better incorporates local material behavior. As such, for the plunge phase of FSW, a method for achieving a time dependent friction coefficient was developed and employed to match experimental temperatures, using Norton's viscoplastic friction law. A friction coefficient of 0.65 was used at the start of the plunge phase, decreasing to 0.08 during the steady state phase. This decrease in magnitude from plunge to steady state is similar to the decrease of the Coulomb friction coefficient calculated by Meyghani et al in a 2017 study. Tuning the models resulted in temperature predictions that differed from experimental measurements by no more than 1.5 percent for the non-steady state plunge and by no more than 9 percent for the steady state simulation. For both models, changes in the heat transfer coefficient had a large effect on tool temperature and very little effect on workpiece temperatures. Increasing the friction coefficient led to a proportional increase in temperature for both the tool and workpiece.

The performance of a coupled viscoplastic model of FSW has been evaluated over a variety of tool RPMs and feed rates. Initial results suggested that further optimization of the material parameters and an additional ability to model the thermal recovery of the material would improve the overall performance of the model. Therefore, an experimental/numeric approach was taken to improve and quantitatively compare the performance of the model based upon the thermal profile of the workpiece. First, an experimental method for obtaining real-time temperature measurements during Friction Stir Processing (FSP) of 304L Stainless Steel was developed. The focus of the method was to ensure that the obtained temperatures were both accurate and repeatable. The method was then used to obtain thermal cycle data from nine welds, each at different operating conditions ranging in tool rotational speed from 300 to 500 RPMs and in feed rate from 0.85 to 2.54 mm/s (2 - 6 in/min). Then a family of nine numerical models was created, each model corresponding to one welding condition. The performance due to improved convergence stability and the added thermal recovery term are also discussed. A gradient following technique was used to optimization and iteratively adjust nine material parameters to minimize the difference between the numerical and experimental temperature for the whole family of models. The optimization decreased the squared error between the numerical and measured temperatures by 76%. Recommendations are also made that may allow the optimization method to return greater dividends.

Friction stir welding (FSW) has been studied extensively for the past two decades. Thermal modeling has been of particular interest, as the quality of the weld is dependent upon the temperature history of the work piece during the process. Since direct temperature measurements of the welded zone are not possible, an analytical model was developed to predict the temperature in this area. This model requires parameters that cannot be easily experimentally determined, so a best fit for these parameters was acquired via regression analysis by comparing the model to experimental data acquired outside of the weld zone. The model was then validated by comparing it to additional temperature data, not including the data used for regression analysis.

Friction stir welding (FSWing) is a solid state, thermo-mechanical process that utilizes a non-consumable rotating weld tool to consolidate a weld joint. In the FSW process, the weld tool is responsible for generating both the heat required to soften the material and the forces necessary to deform and consolidate the former weld seam. Thus, weld tool geometry, material selection, and process parameters are important to the quality of the weld. To study the effects of the weld tool geometry on the resulting welds, a previous study was conducted using varying degree taper, microwave-sintered tungsten carbide (WC) weld tools to FSW Ti-6Al-4V. Fully consolidated welds were down selected for this study to evaluate the resulting mechanical properties and to document the microstructure. X-ray diffraction (XRD) was used to compare the parent material texture with that in the weld nugget. The purpose of this study is to quantify the temperatures obtained during FSWing by interpreting the resulting microstructure. This information is useful in process optimization as well as weld tool material selection.

No description available.

No description available.