Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

Additive manufacturing of metallic components – Process, structure and properties

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The Theory of Industrial Organization

Two-photon excitation provides a means of activating chemical or physical processes with high spatial resolution in three dimensions and has made possible the development of three-dimensional fluorescence imaging, optical data storage, and lithographic microfabrication. These applications take advantage of the fact that the two-photon absorption probability depends quadratically on intensity, so under tight-focusing conditions, the absorption is confined at the focus to a volume of order λ3 (where λ is the laser wavelength). Any subsequent process, such as fluorescence or a photoinduced chemical reaction, is also localized in this small volume. Although three-dimensional data storage and microfabrication have been illustrated using two-photon-initiated polymerization of resins incorporating conventional ultraviolet-absorbing initiators, such photopolymer systems exhibit low photosensitivity as the initiators have small two-photon absorption cross-sections (δ). Consequently, this approach requires high laser power, and its widespread use remains impractical. Here we report on a class of π;-conjugated compounds that exhibit large δ (as high as 1, 250 × 10−50 cm4 s per photon) and enhanced two-photon sensitivity relative to ultraviolet initiators. Two-photon excitable resins based on these new initiators have been developed and used to demonstrate a scheme for three-dimensional data storage which permits fluorescent and refractive read-out, and the fabrication of three-dimensional micro-optical and micromechanical structures, including photonic-bandgap-type structures.

Two-photon polymerization initiators for three-dimensional optical data storage and microfabrication

Additive manufacturing (AM) is poised to bring about a revolution in the way products are designed, manufactured, and distributed to end users. This technology has gained significant academic as well as industry interest due to its ability to create complex geometries with customizable material properties. AM has also inspired the development of the maker movement by democratizing design and manufacturing. Due to the rapid proliferation of a wide variety of technologies associated with AM, there is a lack of a comprehensive set of design principles, manufacturing guidelines, and standardization of best practices. These challenges are compounded by the fact that advancements in multiple technologies (for example materials processing, topology optimization) generate a "positive feedback loop" effect in advancing AM. In order to advance research interest and investment in AM technologies, some fundamental questions and trends about the dependencies existing in these avenues need highlighting. The goal of our review paper is to organize this body of knowledge surrounding AM, and present current barriers, findings, and future trends significantly to the researchers. We also discuss fundamental attributes of AM processes, evolution of the AM industry, and the affordances enabled by the emergence of AM in a variety of areas such as geometry processing, material design, and education. We conclude our paper by pointing out future directions such as the "print-it-all" paradigm, that have the potential to re-imagine current research and spawn completely new avenues for exploration. The fundamental attributes and challenges/barriers of Additive Manufacturing (AM).The evolution of research on AM with a focus on engineering capabilities.The affordances enabled by AM such as geometry, material and tools design.The developments in industry, intellectual property, and education-related aspects.The important future trends of AM technologies.

The status, challenges, and future of additive manufacturing in engineering

Laser direct deposition is widely used for rapid freeform fabrication of fully dense components with good metallurgical properties directly from computer-aided design drawings. Because of complex physics involved such as laser powder interaction, laser substrate interaction, track interface evolution, and melt-solid interaction, it is important to develop simulation models to better understand the characteristics and mechanisms in the process so that optimization and control of a laser direct deposition process are possible. In this paper, a new comprehensive three-dimensional self-consistent transient model is presented for a coaxial laser direct deposition process, which considers physical behaviors such as laser particle interaction, mass addition, heat transfer, fluid flow, melting, and solidification. A continuum model is built to deal with different phases (gas, liquid, solid, and mushy zone) in the calculation domain. An improved level-set method, which takes the conservative form while being implicitly solved with other governing equations, is proposed to track the evolution of free liquid/gas interface during the deposition process. To make the model more physically complete than those in the literature, a newly derived mass source term, which considers the rate of the gas phase being replaced by the deposited material due to the moving interface in some control volumes, is incorporated into the continuity equation. Corresponding new source terms of enthalpy and momentum due to the moving interface are also derived and embedded in the energy and momentum equations. The governing equations are discretized using the finite volume approach to better predict the fluid motion mainly driven by capillary and thermocapillary forces. The simulated track heights, widths, molten pool depths, and track profiles agree well with the experimental results.

Modeling of transport phenomena during the coaxial laser direct deposition process

Transient, three-dimensional heat transfer model for the laser assisted machining of silicon nitride: I. Comparison of predictions with measured surface temperature histories

A numerical and experimental analysis of plasma enhanced machining (PEM) of Inconel 718 is presented in this paper. Surface temperatures due to plasma heating are systematically characterized through numerical modeling and experimental investigation using infrared radiation thermometry. A three-dimensional finite difference model is established to determine the temperature distribution in a cylindrical workpiece subjected to intense localized heating. The results are compared with experimental results obtained with a radiation pyrometer. A sensitivity analysis is presented to examine the effects of machining parameters on the temperature distribution. Benefits of PEM are also demonstrated through the reduction of cutting forces and improved surface roughness over a wide range of cutting conditions. In addition, improvement of productivity in machining Inconel with PEM is illustrated.

Plasma enhanced machining of Inconel 718: modeling of workpiece temperature with plasma heating and experimental results

This paper describes a deep-learning-based method for porosity monitoring in laser additive manufacturing process. A high-speed digital camera was mounted coaxially to the process laser beam for in-process sensing of melt-pool data, and convolutional neural network models were designed to learn melt-pool features to predict the porosity attributes in deposited specimens during laser additive manufacturing. With the image processing tools developed in this paper, the extraction of porosity information from raw quality inspection data, such as cross-section images and tomography data sets, can be automated. The CNN models with a compact architecture, part of whose hyperparameters were selected through cross-validation analysis, achieved a classification accuracy of 91.2% for porosity occurrence detection in the direct laser deposition of sponge Titanium powders and presented predictive capacity for micro pores below 100 μm. For local volume porosity prediction, the model also achieved a root mean square error of 1.32% and exhibited high fidelity for both high porosity and low porosity specimens.

In-Process monitoring of porosity during laser additive manufacturing process

This research is concerned with the analytical and experimental study on the high-speed face milling of 7075-T6 aluminum alloys with a single insert fly-cutter. The results are analyzed in terms of cutting forces, chip morphology, and surface integrity of the workpiece machined with carbide and diamond inserts. It is shown that a high cutting speed leads to a high chip flow angle, very low thrust forces and a high shear angle, while producing a thinner chip. Chip morphology studies indicate that shear localization can occur at higher feeds even for 7075-T6, which is known to produce continuous chips. The resultant compressive residual stresses are shown for the variation of cutting parameters and cutting tool material. The analysis of the high-speed cutting process mechanics is presented, based on the calculation results using extended oblique machining theory and finite element simulation.

Yung C. Shin

Papers

Modeling of transport phenomena during the coaxial laser direct deposition process

Transient, three-dimensional heat transfer model for the laser assisted machining of silicon nitride: I. Comparison of predictions with measured surface temperature histories

Plasma enhanced machining of Inconel 718: modeling of workpiece temperature with plasma heating and experimental results

In-Process monitoring of porosity during laser additive manufacturing process

Analysis on high-speed face-milling of 7075-T6 aluminum using carbide and diamond cutters