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The effects of laser beam welding (LBW) process parameters on the characteristics of Nd:YAG laser butt welding 1.5 mm thick 2205 duplex stainless steel. Specifically, the study focuses on the depth of penetration, bead width, ultimate tensile strength (UTS) and elongation. To achieve this, a parametric study is conducted using a central composite design (CCD) with response surface methodology (RSM) to establish mathematical regression equations that identify the key process parameters and their effects on the responses. The investigations showed that the size of the meltpool at the fusion zone (FZ) increases as the laser power increases. This leads to the formation of wider and deeper weld beads, ultimately leading to stronger and more flexible joints. Similarly, pulse width and scanning speed have a significant impact on the weld bead geometry, UTS, and elongation. It is observed that the FZ is free of any visible cracks, voids, or porosity. The LBW process parameters have been optimized to reduce operating costs by lowering the line energy, without compromising the welding quality. The optimal UTS value for the welded joint is around 865 MPa, which is almost equivalent to 99% of the UTS of the 2205 duplex stainless steel base material (BM). To obtain high-quality welded joints, it is recommended to use a laser power ranging from 423 to 425 W, scanning speed of 5.3 mm/s and pulse width of 5.4 ms. [ABSTRACT FROM AUTHOR]

While the equivalence between online and traditional classrooms has been well-researched, very little of this includes college-level introductory Physics. Only one study explored Physics at the whole-class level rather than specific course components such as a single lab or a homework platform. In this work, we compared the failure rate, grade distribution, and withdrawal rates in an introductory undergraduate Physics course across several learning modes including traditional face-to-face instruction, synchronous video instruction, and online classes. Statistically significant differences were found for student failure rates, grade distribution, and withdrawal rates but yielded small effect sizes. Post-hoc pair-wise test was run to determine differences between learning modes. Online students had a significantly lower failure rate than students who took the class via synchronous video classroom. While statistically significant differences were found for grade distributions, the pair-wise comparison yielded no statistically significance differences between learning modes when using the more conservative Bonferroni correction in post-hoc testing. Finally, in this study, student withdrawal rates were lowest for students who took the class in person (in-person classroom and synchronous video classroom) than online. Students that persist in an online introductory Physics class are more likely to achieve an A than in other modes. However, the withdrawal rate is higher from online Physics courses. Further research is warranted to better understand the reasons for higher withdrawal rates in online courses. Finding the root cause to help eliminate differences in student performance across learning modes should remain a high priority for education researchers and the education community as a whole.

While the equivalence between online and traditional classrooms has been well researched, very little effort has been expended to do such comparisons for college level introductory chemistry. The existing literature has only one study that investigated chemistry lectures at an entire course level as opposed to particular course components such as individual topics or exams. Regarding lab courses, only one study is available and it involves moderating variables that are largely uncontrolled. In this work, we compared the student pass rates, withdrawal rates, and grade distributions between asynchronous online and traditional formats of an introductory chemistry lecture as well as its associated lab course. The study was based on the 823 university records available for the 2015-2016 academic year. Student pass and withdrawal rates between the two modes were quite similar and did not appear to be statistically significant. However, grade distributions for both the lecture and lab differed between the two learning modes, showing significant statistical associations. Online students were more likely to earn As in both lecture and lab while traditional in-person students were more likely to earn Cs or Ds. Further research should include replication of this study with a larger data set. Additionally, this study should be repeated in three to five years to determine if advances in course design, standardization and delivery platforms further reduce or eliminate differences between learning modes. Future studies should also use qualitative tools for a better understanding of why students fail or withdraw from courses.

Several heat treatment procedures are designed considering critical temperatures of phase transformation evaluated through dilatometric testing of 20MnMoNi55 steel to transform low carbon bainitic as‐received material into ferrite‐martensite dual‐phase steels consisting of varied martensite fractions. A thorough metallographic study correlated with the micro‐hardness of constituent phases ensures morphological characteristics along with its fractional variations in as‐received and dual‐phase steels. The impact of fractional variation in constituent phases on the uniaxial monotonic deformation characteristics of dual‐phase steels has been observed with a correlation study between experimental tensile and finite element simulated results. Therefore, a physical‐based model with a 2‐dimensional representative volume element has been established, addressing actual morphological characteristics obtained from metallographic studies. Moreover, the constitutive flow behaviours of ferrite and martensite are also derived from the dislocation‐based hardening model to address the actual deformation phenomenon. Finally, an inhomogeneous deformation behaviour among constituent phases and localization of plastic strain in ferrite matrix has been observed with von‐Mises stress, and equivalent plastic strain distribution through finite element simulated results. This phenomenon is again confirmed with kernel average misorientation mapping and geometrically necessary dislocation density evaluation through electron backscattered diffraction of tensile samples subjected to different degrees of plastic strain. [ABSTRACT FROM AUTHOR]

Understanding the flow characteristics within the molten pool and the creation of the weld shape holds significant theoretical and engineering importance. Numerical simulation is the best method for understanding the flow behaviour in the molten pool due to its greater flexibility and cost competitiveness, which enable efficient exploration of such intricate phenomena. The dimensions of the geometry are generally crucial in determining the flow pattern in the molten pool. Marangoni convection may occur in thin plates due to changes in surface tension, while thicker plates may experience buoyancy forces from natural convection. It would be intriguing to understand the flow pattern when thin plates are treated with a smaller laser beam diameter. Three numerical models have been created in the present paper using COMSOL Multiphysics to analyse the flow characteristics within the molten pool. The first model assumes laminar flow in the molten pool, while the other two models assume turbulent flow (yPlus and k-ω model). The models incorporate a pulsed heat source that is simulated using COMSOL's events interface, which adjusts the time steps depending on the speed of the solution changes. The three models consider the temperature dependent thermo-physical properties, track the solid-liquid phase interface with keyhole, account for Marangoni convection and buoyancy forces. The melt pool shapes calculated by the models are compared with experimental results and found to be comparable. The intensity of the flow in the molten pool is determined by using dimensionless numbers like the Marangoni number and the ratio of the Marangoni number to the Grashof number. [ABSTRACT FROM AUTHOR]