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Some functional properties of engineering materials, i.e. physical, mechanical and thermal ones, depend directly on the microstructure, which is a result of processes occurring in the material during the forming and thermomechanical processing. The proper microstructure can be obtained in many cases by the phase transformation. This phenomenon is one of the most important processes during hot forming and heat treatment. The purpose of this paper is to develop a new comprehensive hybrid model for modeling diffusion phase transformations. A problem has been divided into several tasks and is carried out on several stages. The purpose of this stage is a development of the structure of a hybrid model, development of an algorithm used in the diffusion module and one-dimensional heat flow and diffusion modeling. Generally, the processes of phase transformations are studied well enough but there are not many tools for their complex simulations. The problems of phase transformation simulation are related to the proper consideration of diffusion, movement of phase boundaries and kinetics of transformation. The proposed new model at the final stage of development will take into account the varying grain growth rate, different shape of growing grains and will allow for proper modeling of heat flow and carbon diffusion during the transformation in many processes, where heating, annealing and cooling can be considered (e.g. homogenizing and normalizing).

One of the most suitable methods for modeling of microstructure evolution during the phase transformation is cellular automata (CA), while lattice Boltzmann method (LBM) suits for modeling of diffusion and heat flow. Then, the proposed new hybrid model is based on CA and LBM methods and uses high performing parallel computations.

The first simulation results obtained for one-dimensional modeling confirm the correctness of interaction between LBM and CA in common numerical solution and the possibility of using these methods for modeling of phase transformations. The advantages of the LBM method can be used for the simulation of heat flow and diffusion during the transformation taking into account the results obtained from the simulations. LBM creates completely new possibilities for modeling of phase transformations in combination with CA.

The studies are focused on diffusion phase transformations in solid state in condition of low cooling rate (e.g. transformation of austenite into ferrite and pearlite) and during the heating and annealing (e.g. transformation of the ferrite-pearlite structure into austenite, the alignment of carbon concentration in austenite and growth of austenite grains) in carbon steels within a wide range of carbon content. The paper presents the comprehensive modeling system, which can operate with the technological processes with phase transformation during heating, annealing or cooling.

A brief review of the modeling of phase transformations and a description of the structure of a new CA and LBM hybrid model and its modules are presented in the paper. In the first stage of model implementation, the one-dimensional LBM model of diffusion and heat flow was developed. The examples of simulation results for several variants of modeling with different boundary conditions are shown.

A fundamental principle of materials engineering is that the microstructure of a material controls the properties. The phase transformation is an important phenomenon that determines the final microstructure. Recently, many analytical and numerical methods were used for modeling of phase transformation, but some limitations can be seen in relation to the choice of the shape of growing grains, introduction of varying grain growth rate and modeling of diffusion phenomena. There are also only few comprehensive studies that combine the final microstructure with the actual conditions of its formation. Therefore, the objective of the work is a development of a new hybrid model based on lattice Boltzmann method (LBM) and cellular automata (CA) for modeling of the diffusional phase transformations. The model has a modular structure and simulates three basic phenomena: carbon diffusion, heat flow and phase transformation. The purpose of this study is to develop a model of heat flow with consideration of enthalpy of transformation as one of the most important parts of the proposed new hybrid model. This is one of the stages in the development of the complex model, and the obtained results will be used in a combined solution of heat flow and carbon diffusion during the modeling of diffusion phase transformations.

Different values of overheating/overcooling affect different values in the enthalpy of transformation and thus the rate of transformation. CA and LBM are used in the hybrid model in part related to heat flow. LBM is used for modeling of heat flow, while CA is used for modeling of the microstructure evolution during the phase transformation.

The use of LBM and CA in one numerical solution creates completely new possibilities for modeling of phase transformations. CA and LBM in comparison with commonly used approaches significantly simplify interface and interaction between different parts of the model, which operates in a common domain. The CA can be used practically for all possible processes that consist of nucleation and grains growth. The advantages of the LBM method can be well used for the simulation of heat flow during the transformation, which is confirmed by numerical results.

The developed heat flow model will be combined with the carbon diffusion model at the next stage of work, and the new complex hybrid model at the final stage will provide new solutions in numerical simulation of phase transformations and will allow comprehensive modeling of the diffusional phase transformations in many processes. Heating, annealing and cooling can be considered.

The paper presents the developed model of heat flow (temperature module), which is one of the main parts of the new hybrid model devoted to modeling of phase transformation. The model takes into account the enthalpy of transformation, and the connection with the model of microstructure evolution was obtained.

Relationship management evolves with dynamic and complex environments of megaprojects. However, studies on the longitudinal measurement of relationship management performance for each stakeholder in dynamic and complex project environments are lacking. The purpose of this research is to propose an NK-network evolution model to evaluate stakeholder performance on relationship management in the development of megaprojects.

The model input includes the stakeholder-associated issues and stakeholders' relational strategies, the co-effects of which determine the internal effects of relationship management in megaprojects. The model processing simulates the stakeholder performance of relationship management under the dynamic and complex nature of megaprojects. The NK model shows the dynamic stakeholder interactions on relationship management, whereas the network model presents the complex stakeholder structures of the relationships between stakeholders and relevant issues. The model output is the evolution graph to reveal the weak stakeholder performance on relationship management in the timeline of the project duration.

The research finding reveals that all stakeholders experience the plunge of stakeholder performance of relationship management at the decision-making moment of the planning stage. Construction, environmental and pressure groups may experience the hardship of relationship management at the start of the construction stage. The government is likely to suffer difficulties in relationship management in the late construction stage. Local industry groups would face challenges in relationship management in the middle of the construction stage and handover stage.

The research provides a useful approach to measuring weak moments of relationship management for each stakeholder in various project phases, considering the dynamic and complex environments of megaprojects. The proposed model extends the current knowledge body on how to make project stakeholder analysis by modelling dynamic and complex environments of megaprojects, with bridging the knowledge domains of evolution modeling techniques and network methods.

The numerical simulation of dispersed-phase evolution in injection molding process of polymer blends is of great significance in both adjusting material microstructure and improving performances of the final products. This paper aims to present a numerical strategy for the simulation of dispersed-phase evolution for immiscible polymer blends in injection molding.

First, the dispersed-phase modeling is discussed in detail. Then the Maffettone–Minale model, affine deformation model, breakup model and coalescence statistical model are chosen for the dispersed-phase evolution. A general coupled model of microscopic morphological evolution and macroscopic flow field is constructed. Besides, a stable finite element simulation strategy based on pressure-stabilizing/Petrov–Galerkin/streamline-upwind/Petrov–Galerkin method is adopted for both scales.

Finally, the simulation results are compared and evaluated with the experimental data, suggesting the reliability of the presented numerical strategy.

The coupled modeling of dispersed-phase and complex flow field during injection molding and the tracing and simulation of droplet evolution during the whole process can be achieved.

Service‐oriented architecture is becoming increasingly important for healthcare delivery as it assures seamless integration internally between various teams and departments, and externally between healthcare organizations and their partners. In order to make healthcare more efficient and effective, we need to understand and evaluate its processes, and one way of achieving that is through process modeling. Modeling healthcare processes within a service‐oriented environment opens up new perspectives and raises challenging questions. The purpose of this paper is to investigate one of these questions, namely the suitability of web service orchestration and choreography, two closely related but fundamentally different methodologies for modeling web service‐based healthcare processes.

The authors use a case‐based approach that first developed a set of 12 features for modeling healthcare processes and then used the features to compare orchestration and choreography for modeling part of the scheduled workflow.

The findings show that neither methodology can, by itself, meet all healthcare modeling requirements in the context of the case study. The appropriate methodology must be selected after consideration of the specific modeling needs. The authors identified usability, capabilities, and evolution as three key considerations to assist with selection of a methodology for healthcare process modeling. Further, sometimes one method will not meet all modeling needs and hence the authors recommend combining the two methodologies in order to harness the benefits of modeling healthcare processes in a service‐oriented environment.

Although literature exists on process modeling of web services for healthcare, there are no criteria describing necessary features for micro‐level modeling, nor is there a comparison of the two leading service composition methodologies within the healthcare context. This paper provides some necessary formalization for process modeling in healthcare.

When considering an agreeable development a realistic attitude towards presumed options is to be taken. Two prerequisites in particular prove necessary: first, a realistic model of man in his world, and second, a pragmatic philosophy to evaluate the given facts towards an appropriate, sustainable strategy of action. Mere tradition, wishful thinking, emotion, just hopeful illusions or escapism will not help. A responsible, guided attempt to control change is needed. Man, the dominant factor for the evolution of the life sphere has no other choice than consciously using his capacity to understand and to decide responsibly on his future.

The purpose of this paper is to address both the evolutionary and control aspects associated with the management of artificial superintelligence. Through empirical analysis, the authors examine the diffusion pattern of those high technologies that can be considered as forerunners to the adoption of artificial superintelligence (ASI).

The evolutionary perspective is divided into three parts, based on major developments in this area, namely, robotics, automation and artificial intelligence (AI). The authors then provide several dynamic models of the possible future evolution of superintelligence. These include diffusion modeling, predator–prey models and hostility models. The problem of control in superintelligence is reviewed next, where the authors discuss Asimov’s Laws and IEEE initiative. The authors also provide an empirical analysis of the application of diffusion modeling to three technologies from the industries of manufacturing, communication and energy, which can be considered as potential precursors to the evolution of the field of ASI. The authors conclude with a case study illustrating emerging solutions in the form of long-term social experiments to address the problem of control in superintelligence.

The results from the empirical analysis of the manufacturing, communication and energy sectors suggest that the technology diffusion model fits well with the data of robotics, telecom and solar installations till date. The results suggest a gradual diffusion process, like any other high technology. Thus, there appears to be no threat of “existential catastrophe” (Bostrom, 2014). The case study indicates that any future threat can be pre-empted by some long-term social measures.

This paper contributes to the emerging stream of artificial superintelligence. As humanity comes closer to grappling with the important question of the management and control of this technology for the future, it is important that modeling efforts be made to understand the extant perspective of the development of the high-technology diffusion. Presently, there are relatively few such efforts available in the literature.

Domain-specific process modeling has been proposed in the literature as a solution to several problems in business process management. The problems arise when using only the generic Business Process Model and Notation (BPMN) standard for modeling. This language includes domain ambiguity and difficult long-term model evolution. Domain-specific modeling involves developing concept definitions, domain-specific processes and eventually industry-standard BPMN models. This entails a multi-layered modeling approach, where any of these artifacts can be modified by various stakeholders and changes done by one person may influence models used by others. There is therefore a need for tool support to keep track of changes done and their potential impacts. The paper aims to discuss these issues.

The authors use a multi-context systems-based approach to infer the impacts that changes may cause in the models; and alsothe authors incrementally map components of business process models to ontologies.

Advantages of the framework include: identifying conflicts/inconsistencies across different business modeling layers; expressing rich information on the relations between two layers; calculating the impact of changes taking place in one layer to the rest of the layers; and selecting incrementally the most appropriate semantic models on which the transformations can be based.

The authors consider this work as one of the foundational bricks that will enable further advances toward the governance of multi-layer business process modeling systems. Extensive usability tests would enable to further confirm the findings of the paper.

The approach described here should improve the maintainability, reuse and clarity of business process models and in extension improve data governance in large organizations. The approaches described here should improve the maintainability, reuse and clarity of business process models. This can improve data governance in large organizations and for large collections of processes by aiding various stakeholders to understand problems with process evolutions, changes and inconsistencies with business goals.

This paper fulfills an identified gap to enabling semantically aided domain–specific process modeling.

A multi-physics process model is developed to analyze reactive melt infiltration (RMI) fabrication of ceramic-matrix composite (CMC) materials and components. The paper aims to discuss this issue.

Within this model, the following key physical phenomena governing this process are accounted for: capillary and gravity-driven unsaturated flow of the molten silicon into the SiC/SiC CMC preform; chemical reactions between the silicon melt and carbon (either the one produced by the polymer-binder pyrolysis or the one residing within the dried matrix slurry); thermal-energy transfer and source/sink phenomena accompanying reactive-flow infiltration; volumetric changes accompanying chemical reactions of the molten silicon with the SiC preform and cooling of the as-fabricated CMC component to room temperature; development of residual stresses within, and thermal distortions of, the as-fabricated CMC component; and grain-microstructure development within the SiC matrix during RMI.

The model is validated, at the material level, by comparing its predictions with the experimental and modeling results available in the open literature. The model is subsequently applied to simulate RMI fabrication of a prototypical gas-turbine engine hot-section component, i.e. a shroud. The latter portion of the work revealed the utility of the present computational approach to model fabrication of complex-geometry CMC components via the RMI process.

To the authors’ knowledge, the present work constitutes the first reported attempt to apply a multi-physics RMI process model to a gas-turbine CMC component.

The purpose of this paper is to model the strain localization in J₂ materials with damage evolution using embedded strong discontinuity modes.

In this procedure, an heuristic bandwidth scale is adopted to model the damage evolution in the shear bands. The bifurcation triggering conditions and band growth directions are studied for these materials.

The resulting formulation does not require a specific mesh refinement to model a localization, provides mesh independent results also insensitive to element distortions and allows calibration of the model response using experimental data. The formulation capability is shown embedding the strong discontinuity modes into quadrilateral and higher order elements.

The work described in this paper extends the use of strong discontinuity modes to materials with damage evolution.