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 paper deals with the evolution of the deformation relief formed on lateral faces of single crystals of Hadfield steel during dry sliding friction. The use of single crystals with the predetermined orientation enables to analyze the development of shear systems subject to the duration of tribological tests. As the test duration increases, slip bands are curved and thicken in the near-surface region. After 24 hours of friction, single crystals of Hadfield steel demonstrate the maximum hardening. Afterwards, the wear process begins, which is followed by the repeated strain hardening of the specimens. After 48 hours of friction, the height of the deformation relief nearly halves on all of the three faces, as compared to that observed after 24 hours of friction. Differences in the propagation height of slip bands on the faces occur due to the uneven running-in as well as the complex involvement pattern of shear systems into the deformation process.

Deformation relief evolution during sliding friction of Hadfield steel single crystal

The effect of ECAP pass number on wear, microhardness and tribological dynamic behavior of UFG Al– 6 wt % Mg alloy has been studied. The UFG Al–6 wt % Mg samples demonstrated higher wear resistance after 4 and 8 ECAP passes as compared to as-received alloys state. The dynamics of sliding and loudness level generated in sliding showed moderate increase of vibrations and noise on ECAP UFG samples.

Sliding dynamics on ultrafine grained Al–6 wt % Mg made by equal channel single pressing

Infrared thermography inspection of severe friction on UFG stainless steel, copper and aluminum alloy

The effect of AE sensor positioning on the bulk ultrafine-grained materials used for sliding against steel ball has been investigated. Two versions of AE sensor positioning have been tested and showed the different attenuation levels. The experimentally obtained AE signal waveforms have been analyzed under the AE signal parameters such as a median frequency and AE energy. It was established that the AE sensor positioned on the sample supporting plate in the vicinity of the sample tested allowed redistribution of the signal energy from a low-frequency to high-frequency range as well as extending the median frequency range as compared to those obtained by mounting the sensor on the immobile sample holder.

Andrey V. Filippov

Papers

Deformation relief evolution during sliding friction of Hadfield steel single crystal

Sliding dynamics on ultrafine grained Al–6 wt % Mg made by equal channel single pressing

Infrared thermography inspection of severe friction on UFG stainless steel, copper and aluminum alloy

Towards the effect of acoustic emission (AE) sensor positioning within AE signal parameters in sliding on bulk ultrafine-grained materials

Dynamics of friction processes on Al–Zn–Mg–Cu alloy with coarse-grained or ultrafine-grained structure