Arbitrary 3D Geometries Research Articles

An experimental analysis of deepest bottom-left-fill packing methods for additive manufacturing

The adoption of Additive Manufacturing (AM) technology requires the efficient utilisation of the avail- able build volumes to minimise production times and costs. Three-dimensional algorithms, particularly the Deepest Bottom-Left-Fill (DBLF) heuristic, have been extensively used to tackle the problem of packing arbitrary 3D geometries within the AM sector. A particularly common method applied to more realistic packing problems is the combination of DBLF and metaheuristics such as Genetic Algorithms (GAs). Through a series of experiments, this paper experimentally investigates the practical aspects, and comparative performance of different DBLF based methods including a brute force algorithm and GA combined with DBLF for AM build volume packing. The insights into the relationship between algorithm efficiency (in terms of volume utilisation), simulation runtime, and practical requirements, in particular geometry rotation constraints are investigated. In addition to providing an increased comprehension of the practical aspects of applying DBLF algorithms in the AM context, this study confirms the limita- tions of traditional DBLF and the requirements for more flexible and intelligent placement strategies while experimentally demonstrating that higher degrees of freedom for part rotation contribute to small improvements in volume density. The resulting additional computational effort discourages this strategy, however.

Seamless and non-repetitive 4D texture variation synthesis and real-time rendering for measured optical material behavior

We show how to overcome the single weakness of an existing fully automatic system for acquisition of spatially varying optical material behavior of real object surfaces. While the expression of spatially varying material behavior with spherical dependence on incoming light as a 4D texture (an ABTF material model) allows flexible mapping onto arbitrary 3D geometry, with photo-realistic rendering and interaction in real time, this very method of texture-like representation exposes it to common problems of texturing, striking in two disadvantages. Firstly, non-seamless textures create visible artifacts at boundaries. Secondly, even a perfectly seamless texture causes repetition artifacts due to their organised placement in large numbers over a 3D surface. We have solved both problems through our novel texture synthesis method that generates a set of seamless texture variations randomly distributed over the surface at shading time. When compared to regular 2D textures, the inter-dimensional coherence of the 4D ABTF material model poses entirely new challenges to texture synthesis, which includes maintaining the consistency of material behavior throughout the 4D space spanned by the spatial image domain and the angular illumination hemisphere. In addition, we tackle the increased memory consumption caused by the numerous variations through a fitting scheme specifically designed to reconstruct the most prominent effects captured in the material model.

A time dependent Monte Carlo approach for nuclear reactor analysis in a 3-D arbitrary geometry

A highly reliable tool for transient simulation is vital in the safety analysis of a nuclear reactor. Despite this fact most tools still use diffusion theory and point-kinetics that involve many approximation such as discretization in space, energy, angle and time. However, Monte Carlo method inherently overcomes these restrictions and provides an appropriate foundation to accurately calculate the parameters of a reactor. In this paper fundamental parameters like multiplication factor (Keff) and mean generation time (tG) are calculated using Monte Carlo method and then employed in transient analysis for computing the neutron population, proportional to Keff, during a generation time considering precursors decay. Based on this approach, a dynamic Monte Carlo code named MCSP (Monte Carlo dynamic Simulation of Particles tracking) is developed for both the steady state and time-dependent simulation of particle tracking in an arbitrary 3D geometry. MCSP is able to use either continuous or multi-group energy cross section libraries. To speed up the simulation, the MCSP was empowered with parallel processing as well. Several test problems such as C5G7, LMW and TWIGL are examined to assess the performance of the method.

Superhydrophobic Surfaces Based on Fractal and Hierarchical Microstructures Using Two‐Photon Polymerization: Toward Flexible Superhydrophobic Films

AbstractIntroduction of hierarchical microstructures nowadays is considered as an important method to create superhydrophobic surfaces, but the majority of current studies mainly focus on arbitrary or simple 3D geometries. Therefore, only statistic results or particular conclusions can be obtained. Given this concern, two‐photon polymerization (TPP) is applied to create well‐defined 3D microstructures with high resolution, including fractal Sierpinski tetrahedrons, and hierarchical pyramid structures. Surfaces that have fractal structures with higher complexity are found to be more hydrophobic than their lower‐stage counterparts. Additionally, fractal Sierpinski tetrahedron structures prove to possess higher efficiency in achieving superhydrophobicity when compared to hierarchical pyramids. Further, TPP is also adopted in creating microstructures on flexible substrates. As a demonstration, an array of hierarchical pyramids is fabricated on a plastic film, and superhydrophobicity still remains even after 100 times of bending and relaxing. Moreover, owing to the convenience of spatial control from TPP, tuning of wetting performance in different regions of surfaces is achievable. With this technique, the role of the fractal and hierarchical microstructures in flexible natural creatures can be better understood, thus facilitating the applications, for which robust wetting control is required.

Abstracts of the Total Body PET conference 2018

Abstracts of the Total Body PET conference 2018

A simplified FEM eigenstrain residual stress reconstruction for surface treatments in arbitrary 3D geometries

Residual stress is of great significance for the structural integrity of components and assemblies. Its proper evaluation and integration into failure criteria may considerably enhance the engineering parts performance. Although experimental measurements of residual stress provide important input, the crucial next step is the incorporation of the information obtained into numerical modelling. Eigenstrain method is a powerful way of specifying residual stress in structures in a self-consistent way that satisfies the mechanics requirements of stress equilibrium and strain compatibility. This approach also enables the verification of experimental data consistency. In combination with the principle of transferability of eigenstrain, it allows the application of well-characterised material processing conditions to different solid geometries with the purpose of predicting residual stress. In the present work, a novel user-friendly implementation framework is presented that is able to predict the residual stress fields arising due to material surface treatment of arbitrary three-dimensional geometries. In the first instance, detailed analysis of potential sources of error was conducted, followed by verification of the validity of the procedure conducted by analysing relevant cases from the literature: laser shock peening and carburising combined with quenching. The work presented here opens new ways to use the eigenstrain method for real industrial applications where the mechanical components geometry is generally complex. Particularly, it enables the integration of residual stress into well-established FEM fatigue prediction codes when the experimental data available is limited.

DNA Nanoparticles Programmed from the Top Down with Variable Design Motifs

A hallmark of naturally evolved RNA assemblies, such as the ribosome, ribonuclease-P, and tRNAs, is their ability to fold from a single nucleic acid strand into complex, functional 3D structures with diverse biological functions in the cell. A long-standing aim of synthetic structural biology has been to mimic these properties of self-folding and functionality using a single strand of DNA, as a stepping stone to RNA, because of its fewer secondary structure conformations and increased preference to hybridize in solution. Deriving the rules for such self-assembly also allows for the ability to extend the design space to structures beyond the set of naturally evolved molecules. Toward this end, we have developed a top-down sequence design approach based on the principle of scaffolded DNA origami. First, we present a fully autonomous algorithm to produce a single-stranded DNA scaffold and complementary staple strands, which fold into nearly arbitrary target 3D objects, from Platonic solids to non-spherical topologies, with near quantitative synthetic yield, demonstrated for a dozen structures experimentally (Veneziano, Ratanalert, et al., Science, 2016). Second, we present a powerful approach that eliminates staple strands entirely, offering the ability to program a single DNA molecule to fold into these arbitrary 3D shapes on its own, similar to natural RNA assemblies. We examine the folding pathways of each of these design modalities using quantitative PCR and present a thermodynamic model to optimize sequence design, folding temperature, and yield (Ratanalert et al., in prep, 2016). Together, these algorithms solve a long-standing challenge of synthetic structural biology to program nearly arbitrary 3D geometries using synthetic nucleic acids.

Design of Wireframe DNA Nanostructures-DNA Gridiron.

Self-assembling nucleic acid molecules have shown merit as versatile materials for organizing and constructing nanoscale structures with both 2D and 3D geometries. This chapter focuses on strategies in designing DNA gridiron nanostructures based on four-arm junction. This design strategies aims at controlling DNA self-assembly with a higher degree of spatial precision by depicting arbitrary 3D geometries with their wireframe outlines using DNA helices (for edges) and four-arm junctions (for vertices).

Fabrication of multifunctional components in a glass chip with femtosecond laser direct writing

Femtosecond lasers have opened up new avenues in materials processing due to their unique characteristics of ultrashort pulse widths and extremely high peak intensities. The short pulse width suppresses the formation of a heat-affected zone, which is vital for ultrahigh precision fabrication, whereas the high peak intensity allows multiphoton absorption to be induced in materials that are transparent to the laser wavelength. More interestingly, irradiation with tightly focused femtosecond laser pulses inside transparent materials provides a facile route to modify the interior of transparent materials in a spatially selective manner, enabling three-dimensional (3D) fabrication and integration of multifunctional micro-/nano-structures and components in a monolithic substrate. For instance, femtosecond laser pulses have been used to write optical waveguides in both passive and active materials by locally modifying their refractive indices. In combination with wet chemical etching, femtosecond laser direct writing has also been used to fabricate microfluidic structures, including microchannels and chambers, microvalves, and micropumps. The same technique has been extended to fabricate free-space optics such as micromirrors and micro-optical lenses in glass materials. By virtue of its unique ability to build different types of functional components into a monolithic substrate, femtosecond laser direct writing offers a flexible approach to fabricate a wide variety of integrated devices and microsystems. Although femtosecond laser micromachining have indeed shown extreme flexibility for fabrication and integration of 3D multifunctional micro- components in bulk transparent materials, several major issues still exist, such as the limited size of the microfluidic structures, the limited fabrication resolution, high surface roughness, and so on. This review focuses primarily on the recent efforts to tackle the two issues as mentioned above. By use of femtosecond laser direct writing in porous glass immersed in water followed by post-annealing, we demonstrated microfluidic channels with nearly unlimited lengths and arbitrary 3D geometries. By controlling the laser peak intensity and polarization, a single nanoplane with sub-50-nm feature size could be achieved inside porous glass based on these strategies, several functional devices and their applications have been demonstrated, including 3D passive microfluidic mixer and an integrated micro-nanofluidic system for single DNA analysis. Furthermore, we demonstrate fabrication of 3D whispering gallery microcavities with quality (Q)-factors on the level of ~1×106 in glass chips by femtosecond laser direct writing followed by CO2 laser reflow.

Numerical modeling of the radiative transfer in a turbid medium using the synthetic iteration.

In this paper we propose the fast, but the accurate algorithm for numerical modeling of light fields in the turbid media slab. For the numerical solution of the radiative transfer equation (RTE) it is required its discretization based on the elimination of the solution anisotropic part and the replacement of the scattering integral by a finite sum. The solution regular part is determined numerically. A good choice of the method of the solution anisotropic part elimination determines the high convergence of the algorithm in the mean square metric. The method of synthetic iterations can be used to improve the convergence in the uniform metric. A significant increase in the solution accuracy with the use of synthetic iterations allows applying the two-stream approximation for the regular part determination. This approach permits to generalize the proposed method in the case of an arbitrary 3D geometry of the medium.

A simple and compact Python code for complex 3D topology optimization

This paper presents a 100-line Python code for general 3D topology optimization. The code adopts the Abaqus Scripting Interface that provides convenient access to advanced finite element analysis (FEA). It is developed for the compliance minimization with a volume constraint using the Bi-directional Evolutionary Structural Optimization (BESO) method. The source code is composed of a main program controlling the iterative procedure and five independent functions realizing input model preparation, FEA, mesh-independent filter and BESO algorithm. The code reads the initial design from a model database (.cae file) that can be of arbitrary 3D geometries generated in Abaqus/CAE or converted from various widely used CAD modelling packages. This well-structured code can be conveniently extended to various other topology optimization problems. As examples of easy modifications to the code, extensions to multiple load cases and nonlinearities are presented. This code is useful for researchers in the topology optimization field and for practicing engineers seeking automated conceptual design tools. With further extensions, the code could solve sophisticated 3D conceptual design problems in structural engineering, mechanical engineering and architecture practice. The complete code is given in the appendix section and can also be downloaded from the website: www.rmit.edu.au/research/cism/.

TetGen, a Delaunay-Based Quality Tetrahedral Mesh Generator

TetGen is a C++ program for generating good quality tetrahedral meshes aimed to support numerical methods and scientific computing. The problem of quality tetrahedral mesh generation is challenged by many theoretical and practical issues. TetGen uses Delaunay-based algorithms which have theoretical guarantee of correctness. It can robustly handle arbitrary complex 3D geometries and is fast in practice. The source code of TetGen is freely available. This article presents the essential algorithms and techniques used to develop TetGen. The intended audience are researchers or developers in mesh generation or other related areas. It describes the key software components of TetGen, including an efficient tetrahedral mesh data structure, a set of enhanced local mesh operations (combination of flips and edge removal), and filtered exact geometric predicates. The essential algorithms include incremental Delaunay algorithms for inserting vertices, constrained Delaunay algorithms for inserting constraints (edges and triangles), a new edge recovery algorithm for recovering constraints, and a new constrained Delaunay refinement algorithm for adaptive quality tetrahedral mesh generation. Experimental examples as well as comparisons with other softwares are presented.

Miniature 3D Gas Chromatography Columns with Integrated Fluidic Connectors Using High-resolution Stereolithography Fabrication

In this manuscript we report on design, fabrication, and characterization of miniature gas chromatography columns with arbitrary 3D geometry and integrated connectors as separation elements for a mobile ethylene sensor system. In contrast to planar microfabrication, these columns have been realized in a single step additive manufacturing process using high-resolution stereolithography printing. This maskless technology enables the combination of freeform 3D microstructures with packaging aspects in one bulk element. For applications in food monitoring, the columns were packed with Carbosieve®-SII particles as adsorbents. With the printed columns a minimal gas concentration of 35 ppb (3σ) ethylene can be detected. Retention times of 400 s for ethylene and 1035 s for water and no signal peak overlap show an improved separation capability.

Domain decomposition Fourier finite element method for the simulation of 3D marine CSEM measurements

We present a novel numerical method based on domain decomposition for the simulation of 3D geophysical marine controlled source electromagnetic (CSEM) measurements. Parts of the computational domain where it is reasonable to represent geoelectric properties in 2D, are discretized combining 2D mixed finite elements (FE) and Fourier expansion. The remaining part is discretized utilizing standard 3D FE methods. The method delivers high-accuracy simulations of marine CSEM problems with arbitrary 3D geometries while it considerably reduces the computational complexity of full 3D FE simulations for typical marine CSEM problems. For the particular scenarios considered in this work, the total CPU time required by the novel method is reduced approximately by a factor of five with respect to that needed by full 3D FE formulations.

Parallel Compressible Viscous Flow Simulations Using FLASH Code: Implementation for Arbitrary 3D Geometries

We implement computer graphics algorithms in the FLASH code to enable compressible high-speed flow simulation past any arbitrary two- and three-dimensional stationary bodies. The body shape is represented in a block-structured Cartesian adaptive mesh refinement grid. A high level of refinement is required to represent the body shape accurately and also resolve flow and shock features, resulting in very large grid sizes for 3D simulations. Simulations are done in parallel on IBM Blue Gene/Q computing system on which scalability of the code is also assessed. We also implement appropriate wall boundary conditions in FLASH to model viscous-wall effects. Navier- Stokes solutions for real applications like hypersonic flow control using micro vortex generators and flow past blunted cone-cylinder-flare geometry are shown.

QGSM development for spallation reactions modeling

The growing interest in spallation neutron sources, accelerator-driven systems, R&D of rare isotope beams, and development of external beam radiation therapy necessitated the improvement of nuclear reaction models for both stand-alone codes for the analysis of nuclear reactions and event generators within the Monte Carlo transport systems for calculations of interactions of high-energy particles with matter in a wide range of energy and in arbitrary 3D geometry of multicomponent targets. The exclusive approach to the description of nuclear reactions is the most effective for detailed calculation of inelastic interactions with atomic nuclei. It provides the correct description of particle production, single- and double-differential spectra, recoil, and fission product yields. This approach has been realized in the Quark Gluon String Model (QGSM) for nuclear reactions induced by photons, hadrons, and high energy heavy ions. In this article, improved versions of the QGSM model and a corresponding code have been developed tested and bench marked against experimental data for neutron production in spallation reactions on thin and thick targets in the energy range from a few MeV to several GeV/nucleon.

An evolutionary method for efficient computation of mutual capacitance for VLSI circuits based on the method of images

The problem of computing the capacitance coupling in Very Large Scale Integrated (VLSI) circuits is studied in this work. The proposed method is an approximate extended version of the method of images. The initial problem is formulated here as an optimization problem for the solution of which a genetic algorithm (GA) is employed. The proposed method is fast, general, does not rely on fitting techniques and is applicable to an arbitrary 2D or 3D geometry configuration of conductors. Extensive simulation results are presented for several practical case studies. Comparative results are given with other methods from literature and a commercial tool employing the Finite Element Method (FEM). The results show that the capacitance value computed by our method is in close agreement to the value obtained by the other methods from literature and also by the commercial tool with the average difference ranging between 2% and 5% while demonstrating better scalability as the problem complexity rises.

MOLOCH computer code for molecular-dynamics simulation of processes in condensed matter

Theoretical and experimental investigation into properties of condensed matter is one of the mainstreams in RFNC-VNIITF scientific activity. The method of molecular dynamics (MD) is an innovative method of theoretical materials science. Modern supercomputers allow the direct simulation of collective effects in multibillion atom sample, making it possible to model physical processes on the atomistic level, including material response to dynamic load, radiation damage, influence of defects and alloying additions upon material mechanical properties, or aging of actinides. During past ten years, the computer code MOLOCH has been developed at RFNC-VNIITF. It is a parallel code suitable for massive parallel computing. Modern programming techniques were used to make the code almost 100% efficient. Practically all instruments required for modelling were implemented in the code: a potential builder for different materials, simulation of physical processes in arbitrary 3D geometry, and calculated data processing. A set of tests was developed to analyse algorithms efficiency. It can be used to compare codes with different MD implementation between each other.

Nonlocal phenomena in the positive column of a medium-pressure glow discharge

Commercial CFDRC software (http://www.cfdrc.com/˜cfdplasma) is used to self-consistently simulate the plasma of the positive column (PC) of a medium-pressure dc discharge in argon. The software allows simulations in an arbitrary 3D geometry by using Poisson’s equation for the electric potential and fluid equations for the heavy components and by solving a nonlocal kinetic equation for electrons. It is shown that, in calculating the electron distribution function, the local approximation is almost always inapplicable not only at relatively low pressures (pR<1 cm Torr), but also at relatively high pressures (pR<10 cm Torr), i.e., under the real conditions of a diffuse PC usually met in practice. The use of the local approximation in solving the kinetic equation for electrons leads to significant errors in determining the main parameters of the PC. A paradoxical effect has been revealed: the peaks of the profiles of the excitation rates shift from the discharge axis toward the periphery as the pressure increases from low to medium values (1 cm Torr<pR<10 cm Torr). It is shown that the effect is related to the nonlocal character of the electron distribution function.

The influence of metastable atoms and the effect of the nonlocal character of the electron distribution on the characteristics of the positive column in an argon discharge

Commercial CFDRC software (http://www.cfdrc.com/˜cfdplasma) is used to self-consistently simulate the plasma of the positive column (PC) of a dc discharge in argon. The software allows simulations in an arbitrary 3D geometry by using Poisson’s equation for the electric potential and fluid equations for the heavy components and by solving a nonlocal kinetic equation for electrons. It is shown that, in calculating the electron distribution function, the local approximation is almost always inapplicable under real conditions of a diffuse PC usually met in practice (pR<(5–10) cm Torr). The influence of metastable atoms, which can substantially affect the parameters of the PC plasma, is considered. It is shown that superelasic collisions play an important role in enriching the fast component of the electron distribution function and that the Penning ionization can result in an ascending volt-ampere characteristic of the positive column.