Adaptive Slicing for Multi-Axis Hybrid Plasma Deposition and Milling

Hybrid Plasma Deposition and Milling (HPDM), a five-axis manufacturing system integrated material additive and subtractive processes, can be used to create overhang metallic components directly without the usage of sacrificial support structure. Different from conventional slicing methods, a new slicing algorithm with changeable direction and thickness is proposed in this paper. Minimal overhang length is selected as the objective function to optimize the build direction. The thickness is adjusted to meet allowable overhang length and allowable cups height. The input mesh is first decomposed into non-uniform thickness segment meshes and then each segment is cut into uniform thickness slices. The output slices consist of split slices between two adjacent segment meshes and inner slices for each segment mesh. Examples and analyses confirm the feasibility and effectiveness.Mechanical Engineerin

Multi-Perspective Fusion Network for Commonsense Reading Comprehension

Commonsense Reading Comprehension (CRC) is a significantly challenging task, aiming at choosing the right answer for the question referring to a narrative passage, which may require commonsense knowledge inference. Most of the existing approaches only fuse the interaction information of choice, passage, and question in a simple combination manner from a \emph{union} perspective, which lacks the comparison information on a deeper level. Instead, we propose a Multi-Perspective Fusion Network (MPFN), extending the single fusion method with multiple perspectives by introducing the \emph{difference} and \emph{similarity} fusion\deleted{along with the \emph{union}}. More comprehensive and accurate information can be captured through the three types of fusion. We design several groups of experiments on MCScript dataset \cite{Ostermann:LREC18:MCScript} to evaluate the effectiveness of the three types of fusion respectively. From the experimental results, we can conclude that the difference fusion is comparable with union fusion, and the similarity fusion needs to be activated by the union fusion. The experimental result also shows that our MPFN model achieves the state-of-the-art with an accuracy of 83.52\% on the official test set

Numerical analysis of heat transfer and fluid flow in multilayer deposition of PAW-based wire and arc additive manufacturing

A three-dimensional numerical model has been developed to investigate the fluid flow and heat transfer behaviors in multilayer deposition of plasma arc welding (PAW) based wire and arc additive manufacture (WAAM). The volume of fluid (VOF) and porosity enthalpy methods are employed to track the molten pool free surface and solidification front, respectively. A modified double ellipsoidal heat source model is utilized to ensure constant arc heat input in calculation in the case that molten pool surface dynamically changes. Transient simulations were conducted for the 1st, 2nd and 21st layer depositions. The shape and size of deposited bead and weld pool were predicted and compared with experimental results. The results show that for each layer of deposition the Marangoni force plays the most important role in affecting fluid flow, conduction is the dominant method of heat dissipation compared to convection and radiation to the air. As the layer number increases, the length and width of molten pool and the width of deposited bead increase, whilst the layer height decreases. However these dimensions remain constant when the deposited part is sufficiently high. In high layer deposition, where side support is absent, the depth of the molten pool at the rear part is almost flat in the Y direction. The profile of the deposited bead is mainly determined by static pressure caused by gravity and surface tension pressure, therefore the bead profile is nearly circular. The simulated profiles and size dimensions of deposited bead and molten pool were validated with experimental weld appearance, cross-sectional images and process camera images. The simulated results are in good agreement with experimental results

Towards Omni-Tomography—Grand Fusion of Multiple Modalities for Simultaneous Interior Tomography

We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and others. Here we propose “omni-tomography”, a novel concept for the grand fusion of multiple tomographic modalities for simultaneous data acquisition in a region of interest (ROI). Omni-tomography can be instrumental when physiological processes under investigation are multi-dimensional, multi-scale, multi-temporal and multi-parametric. Both preclinical and clinical studies now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities. Over the past decade, two approaches have been used for multimodality fusion: Software based image registration and hybrid scanners such as PET-CT, PET-MRI, and SPECT-CT among others. While there are intrinsic limitations with both approaches, the main obstacle to the seamless fusion of multiple imaging modalities has been the bulkiness of each individual imager and the conflict of their physical (especially spatial) requirements. To address this challenge, omni-tomography is now unveiled as an emerging direction for biomedical imaging and systems biomedicine

Improving exact algorithms for MAX-2-SAT

We study three new techniques which will speed up the branch-and-bound algorithm for the MAX-2-SAT problem: The first technique is a new lower bound function for the algorithm and we show that the new lower bound function is consistently better than other lower bound functions. The other two techniques are based on the strongly connected components of the implication graph of a 2CNF formula: One uses the graph to simplify the formula and the other uses the graph to design a new variable ordering. The experiments show that the simplification can reduce the size of the input substantially when used in preprocessing and that the new variable ordering performs much better when the clause-to-variable ratio is less than 2. The result of this research is a high-performance implementation of an exact algorithm for MAX-2-SAT which outperforms any implementation we know about in the same category. It also shows that our MAX-2-SAT implementation is a feasible and effective tool to solve large instances of the Max-Cut problem in graph theory.