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Additive manufacturing (AM) is revolutionizing the manufacturing industry due to several advantages and capabilities, including use of rapid prototyping, fabrication of complex geometries, reduction of product development cycles and minimization of material waste. As metal AM becomes increasingly popular for aerospace and defense original equipment manufacturers (OEMs), a major barrier that remains is rapid qualification of components. Several potential defects (such as porosity, residual stress and microstructural inhomogeneity) occur during layer-by-layer processing. Current methods to qualify AM parts heavily rely on experimental testing, which is economically inefficient and technically insufficient to comprehensively evaluate components. Approaches for high fidelity qualification of AM parts are necessary.

This review summarizes the existing powder-based fusion computational models and their feasibility in AM processes through discrete aspects, including process and microstructure modeling.

Current progresses and challenges in high fidelity modeling of AM processes are presented.

Potential opportunities are discussed toward high-level assurance of AM component quality through a comprehensive computational tool.

There has been a lack of focus on multi-level issues within leadership research. Dionne and Dionne (2009) address this gap in the research by presenting a Monte Carlo simulation examining leadership at four levels of analysis within a group decision-making context. While their work makes a strong contribution to the sciences of leadership, group decision making, and team complexity, many aspects of the research demonstrate potential for great expansion and improvement. Toward this purpose, this commentary discusses and provides suggestions regarding the topics of computer simulation in team research, group decision-making theory, and the modeling of team complexity. It is intended to stimulate continued critical thinking and more innovative, practical, and carefully designed research efforts.

This paper aims to present the result of a scientometric analysis conducted using studies on high-performance computing in computational modelling. This was done with a view to showcasing the need for high-performance computers (HPC) within the architecture, engineering and construction (AEC) industry in developing countries, particularly in Africa, where the use of HPC in developing computational models (CMs) for effective problem solving is still low.

An interpretivism philosophical stance was adopted for the study which informed a scientometric review of existing studies gathered from the Scopus database. Keywords such as high-performance computing, and computational modelling were used to extract papers from the database. Visualisation of Similarities viewer (VOSviewer) was used to prepare co-occurrence maps based on the bibliographic data gathered.

Findings revealed the scarcity of research emanating from Africa in this area of study. Furthermore, past studies had placed focus on high-performance computing in the development of computational modelling and theory, parallel computing and improved visualisation, large-scale application software, computer simulations and computational mathematical modelling. Future studies can also explore areas such as cloud computing, optimisation, high-level programming language, natural science computing, computer graphics equipment and Graphics Processing Units as they relate to the AEC industry.

The study assessed a single database for the search of related studies.

The findings of this study serve as an excellent theoretical background for AEC researchers seeking to explore the use of HPC for CMs development in the quest for solving complex problems in the industry.

To develop new and existing coupled thermal and mechanical models of electromagnetic solids for the simulation of coupled field problems based on a consistent theoretical and computational framework.

The finite element computational models we describe involve the combination of classical electrodynamics, continuum mechanics, and thermodynamics. In order to create consistent coupled models, we employ the fundamental principles of thermodynamics as a common framework.

Our procedure requires the necessary thermodynamical considerations for building consistent multiphysics models and develops some novel implementation issues that are important from the designers' point of view. Additionally, efficient numerical algorithms for solving the arising static and dynamic nonlinearities are discussed.

The paper targets the simulation of coupled problems in macroscopic electromagnetic continua.

The application areas of the coupled field models are identified and illustrated by the solution of complex industrial problems.

We introduce new computational models and techniques for the solution of some coupled field problems in electromagnetic solids. While some elements of these computational models and techniques have been used for decades, the complete theoretical and computational framework is presented for the first time here.

The purpose of this paper is to access performance of existing computational techniques to model strongly non‐linear coupled thermo‐electric problems.

A thermistor is studied as an example of a strongly non‐linear diffusion problem. The temperature field and the current flow in the device are mutually coupled via ohmic heating and very rapid variations of electric conductivity with temperature and applied electric field, which makes the problem an ideal test case for the computational techniques. The finite volume fully coupled and fractional steps (splitting) approaches on a fixed computational grid are compared with a fully coupled front‐fixing method. The algorithms' input parameters are verified by comparison with published experiments.

It was found that fully coupled methods are more effective for non‐linear diffusion problems. The front fixing provides additional improvements in terms of accuracy and computational cost.

This paper for the first time compares in detail advantages and implementation complications of each method being applied to the coupled thermo‐electric problems. Particular attention is paid to conservation properties of the algorithms and accurate solutions in the transition region with rapid changes in material properties.

This paper aims to present an integrated optimisation‐modelling computational approach for virtual prototyping that helps design engineers to improve the reliability and performance of electronic components and systems through design optimisation at the early product development stage. The design methodology is used to identify the optimal design of lead‐free (Sn3.9Ag0.6Cu) solder joints in fine‐pitch copper column bumped flip‐chip electronic packages.

The design methodology is generic and comprises numerical techniques for computational modelling (finite element analysis) coupled with numerical methods for statistical analysis and optimisation. In this study, the integrated optimisation‐modelling design strategy is adopted to prototype virtually a fine‐pitch flip‐chip package at the solder interconnect level, so that the thermal fatigue reliability of the lead‐free solder joints is improved and important design rules to minimise the creep in the solder material, exposed to thermal cycling regimes, are formulated. The whole prototyping process is executed in an automated way once the initial design task is formulated and the conditions and the settings for the numerical analysis used to evaluate the flip‐chip package behaviour are specified. Different software modules that incorporate the required numerical techniques are used to identify the solution of the design optimisation problem related to solder joints reliability optimisation.

For fine‐pitch flip‐chip packages with copper column bumped die, it is found that higher solder joint volume and height of the copper column combined with lower copper column radius and solder wetting around copper column have a positive effect on the thermo‐mechanical reliability.

The findings of this research provide design rules for more reliable lead‐free solder joints for copper column bumped flip‐chip packages and help to establish further the technology as one of the viable routes for flip‐chip packaging.

The aim of this paper is to access performance of existing computational techniques to model strongly non‐linear field diffusion problems.

Multidimensional application of a finite volume front‐fixing method to various front‐type problems with moving boundaries and non‐linear material properties is discussed. Advantages and implementation problems of the technique are highlighted by comparing the front‐fixing method with computations using fixed grids. Particular attention is focused on conservation properties of the algorithm and accurate solutions close to the moving boundaries. The algorithm is tested using analytical solutions of diffusion problems with cylindrical symmetry with both spatial and temporal accuracy analysed.

Several advantages are identified in using a front‐fixing method for modelling of impulse phenomena in high‐temperature superconductors (HTS), namely high accuracy can be obtained with a small number of grid points, and standard numerical methods for convection problems with diffusion can be utilised. Approximately, first order of spatial accuracy is found for all methods (stationary or mobile grids) for 2D problems with impulse events. Nevertheless, errors resulting from a front‐fixing technique are much smaller in comparison with fixed grids. Fractional steps method is proved to be an effective algorithm for solving the equations obtained. A symmetrisation procedure has to be introduced to eliminate a directional bias for a standard asymmetric split in diffusion processes.

This paper for the first time compares in detail advantages and implementation complications of a front‐fixing method when applied to the front‐type field diffusion problems common to HTS. Particular attention is paid to accurate solutions in the region close to the moving front where rapid changes in material properties are responsible for large computational errors.

Team cohesion and other team processes are inherently dynamic mechanisms that contribute to team effectiveness. Unfortunately, extant research has typically treated team cohesion and other processes as static, and failed to capture how these processes change over time and the implications of these changes. In this chapter, we discuss the characteristics of team process dynamics and highlight the importance of temporal considerations when measuring team cohesion. We introduce innovative research methods that can be applied to assess and monitor team cohesion and other process dynamics. Finally, we discuss future directions for the research and practical applications of these new methods to enhance our understanding of the dynamics of team cohesion and other processes.

Strategies for accelerated multi-objective optimization of aerodynamic surfaces are investigated, including the possibility of exploiting surrogate modeling techniques for computational fluid dynamic (CFD)-driven design speedup of such surfaces. The purpose of this paper is to reduce the overall optimization time.

An algorithmic framework is described that is composed of: a search space reduction, fast surrogate models constructed using variable-fidelity CFD models and co-Kriging, and Pareto front refinement. Numerical case studies are provided demonstrating the feasibility of solving real-world problems involving multi-objective optimization of transonic airfoil shapes and accurate CFD simulation models of such surfaces.

It is possible, through appropriate combination of surrogate modeling techniques and variable-fidelity models, to identify a set of alternative designs representing the best possible trade-offs between conflicting design objectives in a realistic time frame corresponding to a few dozen of high-fidelity CFD simulations of the respective surfaces.

The proposed aerodynamic design optimization algorithmic framework is novel and holistic. It proved useful for fast design of aerodynamic surfaces using high-fidelity simulation data in moderately sized search space, which is extremely challenging when using conventional methods due to the excessive computational cost.

A computational technique was developed to model and simulate molecular or atomic behaviour of materials under static loads. Interatomic potential was used to maintain equilibrium among molecules or atoms under loads and constraints. In addition, a smeared continuum model was derived to represent a very large number of molecules or atoms collectively based on energy equivalency. The finite element method was applied to the smeared continuum model. Then, the molecular or atomic model was coupled with the finite element analysis model so that more flexible loads and constraints could be applied to the molecular or atomic model. In addition, such a coupling would be useful for transition from nanoscale to continuum scale. Some example problems were presented to illustrate the developed techniques. An example included a multi‐scale technique for woven fabric composites made of carbon nanotubes. The effective stiffnesses at different stages of the nano‐composites were computed.