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 enables the printing of metallic parts, such as customized implants for patients, durable single-crystal parts for use in harsh environments, and the printing of parts with site-specific chemical compositions and properties from 3D designs. However, the selection of alloys, printing processes and process variables results in an exceptional diversity of microstructures, properties and defects that affect the serviceability of the printed parts. Control of these attributes using the rich knowledge base of metallurgy remains a challenge because of the complexity of the printing process. Transforming 3D designs created in the virtual world into high-quality products in the physical world needs a new methodology not commonly used in traditional manufacturing. Rapidly developing powerful digital tools such as mechanistic models and machine learning, when combined with the knowledge base of metallurgy, have the potential to shape the future of metal printing. Starting from product design to process planning and process monitoring and control, these tools can help improve microstructure and properties, mitigate defects, automate part inspection and accelerate part qualification. Here, we examine advances in metal printing focusing on metallurgy, as well as the use of mechanistic models and machine learning and the role they play in the expansion of the additive manufacturing of metals. Several key industries routinely use metal printing to make complex parts that are difficult to produce by conventional manufacturing. Here, we show that a synergistic combination of metallurgy, mechanistic models and machine learning is driving the continued growth of metal printing.

Metallurgy, mechanistic models and machine learning in metal printing

Metal additive manufacturing technologies, such as powder bed fusion process, directed energy deposition (DED) process, sheet lamination process, etc., are one of promising flexible manufacturing technologies due to direct fabrication characteristics of a metallic freeform with a three-dimensional shape from computer aided design data. DED processes can create an arbitrary shape on even and uneven substrates through line-by-line deposition of a metallic material. Theses DED processes can easily fabricate a heterogeneous material with desired properties and characteristics via successive and simultaneous depositions of different materials. In addition, a hybrid process combining DED with different manufacturing processes can be conveniently developed. Hence, researches on the DED processes have been steadily increased in recent years. This paper reviewed recent research trends of DED processes and their applications. Principles, key technologies and the state-of-the art related to the development of process and system, the optimization of deposition conditions and the application of DED process were discussed. Finally, future research issues and opportunities of the DED process were identified.

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Directed Energy Deposition (DED) Process: State of the Art

Today, developments in technology have gained momentum more than ever, and the need for efficiency in production as well as in the ecological domain has increased significantly. Studies examining dry machining and coolant removal have been superseded by those presenting new cooling and lubrication techniques. The effects on surface roughness directly related to final product quality are being investigated in terms of tool life and employee health. This has resulted in more frequent use of the eco-friendly minimum quantity lubrication (MQL) technique, which has now become a major competitor to dry and coolant machining. In this study, AISI D2 cold work tool steel, a material widely used in the mold industry, was used as the workpiece. Tests were carried out under dry and MQL conditions and the temperature, cutting tool vibration amplitude, tool wear, surface roughness and tool life were evaluated. The experiments were carried out using two different cutting tool coating types (CVD-chemical vapor deposition and PVD-physical vapor deposition) and three different cutting speeds (60, 90 and 120 m/min) at a constant cutting depth (1 mm) and feed rate (0.09 mm/rev). Results revealed that tool wear, cutting temperature and cutting tool vibration amplitude were lower by 23, 25, and 45%, respectively, compared to dry cutting. Because of these improvements, the surface roughness of the workpiece was improved by 89% and tool life was increased by up to 267%.

The effect of vibration and cutting zone temperature on surface roughness and tool wear in eco-friendly MQL turning of AISI D2

Additive manufacturing of low-cost porous titanium-based composites for biomedical applications: Advantages, challenges and opinion for future development

The earthmoving of permafrost soil is a critical task for excavation of minerals and construction on new territories. Failure by abrasive wear is the main reason for excavation parts of earthmoving and soil cutting machines. Therefore investigation of this type of wear is a challenge for developing efficient and wear resistant working parts. This paper is focused on conducting tribological experiments with sliding the steel samples over the surface of diabase stone sample where abrasive wear conditions of soil cutting are modeled experimentally. The worn surfaces of all samples have been examined and transfer of metal and stone particles revealed. The acoustic emission (AE) signals have been recorded and related to the results of worn surface analysis. he acoustic emission (AE) signals have been recorded and related to the results of worn surface analysis. As shown the wear intensity correlates to that of acoustic emission. Both acoustic emission signal median frequency and energy are found to be sensitiv...

An experimental modeling and acoustic emission monitoring of abrasive wear in a steel/diabase pair

The study presents the results of comparative experimental studies of wear resistance in the conditions of dry sliding friction for samples of ferrite-pearlite steel with different structural conditions. Samples of steel 13Mn6 (DIN 17145) were prepared for research. The first group of samples was material after hot rolling. The second group was the material printed by electron beam additive manufacturing. It was found that the wear resistance of the printed material is two times higher than the material in the rolled state. It was found that differences in the structural state of the printed and rolled samples have a significant effect on the mechanisms of surface deformation of the material.

An experimental study of the wear resistance of ferrite-pearlite steel printed by electron beam additive manufacturing

The experimental studies of brass scratching in different structural states have been performed. To obtain the ultrafine-grained (UFG) structure, the method of equal-channel angular pressing was used with subsequent heat treatment. Scratching was carried out at the room temperature. The optimal combination of the ECAP passes and the heat treatment is established, which provides high scratch resistance, a small amount of damage and the formation of deposits of minimum height.

The annealing effect on scratch testing behavior of ultrafine-grained brass

Study of the Structure and Mechanical Properties of Aluminum Bronze Printed by Electron Beam Additive Manufacturing

Polyethylene terephthalate (PET) track membrane (TM) has a great opportunity to use as a bio implant in ophthalmology’s surgery due to its physical and chemical properties and biological comparability. Sterilization of medical implants can change its properties and can influence on regeneration process and success of surgical treatment. We researched influence on the PET track membrane of two sterilization methods wide used in medicine. The first sterilization method was steam sterilization. The second method was γ-irradiation of Co60 radionuclide sterilization. The sterilization processes influence on the track membrane properties was assessed by surface topography analysis, IR Fourier spectroscopy, wetting angle and surface energy of TM surface measurement.

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Andrey V. Filippov

Papers

An experimental modeling and acoustic emission monitoring of abrasive wear in a steel/diabase pair

An experimental study of the wear resistance of ferrite-pearlite steel printed by electron beam additive manufacturing

The annealing effect on scratch testing behavior of ultrafine-grained brass

Study of the Structure and Mechanical Properties of Aluminum Bronze Printed by Electron Beam Additive Manufacturing

Sterilization influence on PET track membrane properties