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This paper gives a review of the finite element techniques (FE) applied in the area of material processing. The latest trends in metal forming, non‐metal forming and powder metallurgy are briefly discussed. The range of applications of finite elements on the subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An appendix included at the end of the paper presents a bibliography on finite element applications in material processing for the last five years, and more than 1100 references are listed.

The representation of Heterogeneous Object (HO) is divided into two categories: Data model (DM) and material evaluation paradigm (MEP). A hybrid methodology with geometry model and volumetric dataset to represent heterogeneous properties is proposed in this paper. Geometry model of an object can guarantee the accuracy of the final HO slices; and volumetric dataset lends the flexible manipulability and other advantages to HO representation. Two MEPs, namely distance field (DF) based and Fixed Reference Features & Active Grading Source(s) (FRF&AGS) are presented to facilitate the process of HO representation according to the designer)s input parameters. The DM can be modified interactively with users until the final satisfactory result is obtained. In this paper, a scheme of HO slicing is described. In this method, we utilize the slices contour of geometrical model as constraint to reconstruct the HO slices, which can theoretically achieve the same accuracy with the geometrical shape. Some examples of Heterogeneous object represented with our scheme are provided.

The purpose of this paper is to identify the relationships between process modeling and Industry 4.0, the strategic themes and the most used process modeling language in smart factories. The study also presents the growth of the field of study worldwide, the perspectives, main challenges, trends and suggestions for future works.

To do this, a science mapping was performed using the software SciMAT, supported by VOS viewer.

The results show that the Business Process Model and Notation (BPMN), Unified Modelling Language (UML) and Petri Net are the most relevant languages to smart manufacturing. The authors also highlighted the need to develop new languages or extensions capable of representing the dynamism, interoperability and multiple technologies of smart factories.

It was possible to identify the most used process modeling languages in smart environments and understand how these languages assist control and manage smart processes. Besides, the authors highlighted challenges, new perspectives and the need for future works in the field.

The purpose of this paper is to present principles from the complex approach in education and describe some practical pedagogic experiences enhancing how “real world” perspectives have influenced and contributed to curriculum development.

Necessity of integration in terms of knowledge modeling is an historical trend in Engineering and Computer Sciences curricula. Integration of particular technical aspects with wide global aspects is a response to globalization demands. Globalization demands require new approaches, at both educational and teaching levels. Also, educational level embeds a wide range of pedagogical proposals or teaching proposals. Since the 1990s, Engineering and Computer Sciences curricula have emphasized, increasingly, the project‐oriented approach in the Engineering field of knowledge and software engineering contents has migrated to beginners or fresh‐man level in Computer Sciences courses. This approach is called the Complex Approach in education. COOL – “Comprehensive Object‐Oriented Learning” – is an educational project mentored by Emeritus Professor Kristen Nygaard, from the Department of Informatics at Oslo University, which deals with the complex approach in education. Professor Nygaard passed away in 2002. This project was published in 2006 under the title of “Comprehensive Object‐Oriented Learning: the Learner’s Perspective”. This paper analyses theoretical aspects in Nygaard's project and also compares aspects with the author's work teaching Object Oriented Modeling in Computer Sciences and Engineering, at Federal University of Santa Catarina – UFSC, Florianopolis, Brazil. The author's pedagogic proposal, developed on those contexts, since 1997, is supported by Nygaard theory and also by Edgar Morin “Complex Thought” theory adopted by UNESCO, titled Complex Thought cathedra.

Innovation, in terms of Engineering and Computer Sciences curriculum development, is deeply related to the complex approach educational paradigm. Consequently, innovation in terms of pedagogic practices is also deeply related to the complex approach perspective. Complex approach overpasses fragmented view of knowledge towards integrative view concerning curriculum development in technological areas.

The comprehensive object‐oriented learning presented here is applied to Computer Science and Engineering. However its development and application could impact other disciplines and education, especially in relation to technology integration in education.

The paper presents and discusses COOL as a concept and approach for enhanced learning, in a novel manner, taking account of theoretical underpinnings developed aligned to modern thinking.

StarLogo is a computer modeling tool that empowers students to understand the world through the design and creation of complex systems models. StarLogo enables students to program software creatures to interact with one another and their environment, and study the emergent patterns from these interactions. Building an easy‐to‐understand, yet powerful tool for students required a great deal of thought about the design of the programming language, environment, and its implementation. The salient features are StarLogo's great degree of transparency (the capability to see how a simulation is built), its support to let students create their own models (not just use models built by others), its efficient implementation (supporting simulations with thousands of independently executing creatures on desktop computers), and its flexible and simple user interface (which enables students to interact dynamically with their simulation during model testing and validation). The resulting platform provides a uniquely accessible tool that enables students to become full‐fledged practitioners of modeling. In addition, we describe the powerful insights and deep scientific understanding that students have developed through the use of StarLogo.

The purpose of this paper is to derive the small-signal/canonical model derivation of the high-side active clamp forward converter (ACFC) with diode rectification for ideal and with resistive parasitics. It also covers the analysis of ACFC small-signal model with resistive parasitics using computer-aided modeling software Personal Computer Simulation Program with Integrated Circuit Emphasis (PSPICE) 16.6. The effects of variation of system parameters on the ACFC’s state transfer functions and operations have been highlighted in this paper.

The large-signal model and small-signal model of the ACFC with diode rectification has been derived using AC small-signal modeling approach.

The operating point of the converter changes with the consideration of resistive parasitics compared with the ideal case. The response obtained from the hardware matches with the time domain response of the averaged model and switch model developed in PSPICE.

This paper limits the study of ACFC small-signal behavior by using computer-aided design software PSPICE. The dead time of the converter is not considered because it is negligible when compared with the on and off time. The leakage inductance which plays a role in zero voltage switching of the ACFC switches is neglected in the analysis as it is very small compared to the magnetizing inductance. The switching losses are not considered in the modeling.

The mathematical computation of deriving the system transfer functions from canonical model is complex and time consuming.

The modeling with resistive parasitics improves the effectiveness of the equivalent model. Also, the analysis with computer-aided modeling software PSPICE gives reliable results in less time.

The purpose of this paper is to review the available reduced order modeling approaches in the literature for predicting the flow and specially temperature fields inside data centers in terms of the involved design parameters.

This paper begins with a motivation for flow/thermal modeling needs for designing an energy‐efficient thermal management system in data centers. Recent studies on air velocity and temperature field simulations in data centers through computational fluid dynamics/heat transfer (CFD/HT) are reviewed. Meta‐modeling and reduced order modeling are tools to generate accurate and rapid surrogate models for a complex system. These tools, with a focus on low‐dimensional models of turbulent flows are reviewed. Reduced order modeling techniques based on turbulent coherent structures identification, in particular the proper orthogonal decomposition (POD) are explained and reviewed in more details. Then, the available approaches for rapid thermal modeling of data centers are reviewed. Finally, recent studies on generating POD‐based reduced order thermal models of data centers are reviewed and representative results are presented and compared for a case study.

It is concluded that low‐dimensional models are needed in order to predict the multi‐parameter dependent thermal behavior of data centers accurately and rapidly for design and control purposes. POD‐based techniques have shown great approximation for multi‐parameter thermal modeling of data centers. It is believed that wavelet‐based techniques due to the their ability to separate between coherent and incoherent structures – something that POD cannot do – can be considered as new promising tools for reduced order thermal modeling of complex electronic systems such as data centers

The paper reviews different numerical methods and provides the reader with some insight for reduced order thermal modeling of complex convective systems such as data centers.

Many literature reviews on project management (PM) research are limited to studies published only in PM journals but some reviews do expand their analysis on PM research published also in journals belonging to the management studies field. However, the authors found no previous literature reviews comparing the PM content in different sectors outside the management studies field. Therefore, the analysis and findings of PM content derived from the sector-specific engineering and technology-focused journals are new. The paper aims to discuss this issue.

The authors analyze PM content in nine different sectors, where each sector and its inherent research is connected to specific engineering, technological, or industry-related disciplines. The authors conduct an evidence-informed literature review on PM knowledge in the distinct literatures of these nine sectors. The period of analysis is 24 years from 1986-2009. The authors discuss potential consequences of the findings’ sector-specificity for future PM domain development.

The perspective on different origins of PM leads to a meta-level PM concept covering several different PM domains, each with its own sector specific and separated development path.

The literature analysis purposefully excluded PM journals and management studies, and the authors focused only on sector-specific engineering and technology-focused journals that represent knowledge and wisdom of different PM contents in nine sectors.

The findings have significant potential to contribute to scholarly discussion on the development of a universal PM theory. For applicability across sectors, the authors suggest a modular PM theory with different sector-specific modules for knowledge, concepts, and underlying assumptions.

Currently, this discussion has been mainly focused on theorizing concepts and approaches in management studies only. This study expands the understanding to engineering and technology-focused journals across nine industry sectors/domains.

Following a successful career in industry, Dr. Douglas V. Shick, a newly minted entrepreneur, established NRS Associates, LLC, to perform consulting services based on two highly technical computer-modeling programs. Doug was heavily involved in the development of one program, an innovative computer simulation software for modeling a particular manufacturing process, through intrapreneurial activity during his corporate experience. Doug established his business on September 1, 2001, and on September 10 announced his services by e-mail to everyone he knew. The unforeseen events of the next day, September 11, produced some unexpected aftereffects that Doug had to factor into his developing business.

This paper aims to provide a design of intelligent model‐based topology analyzer that can be used to improve plant operation.

POOM process modeling methodology is proposed to model and partition plant topology so that plant operation can be designed in effective manner as mapped to plant topology partitions. Plant topology is divided into areas based on the operation required and material flow and isolation paths are identified automatically using intelligent algorithm.

It is possible to define hierarchical plant structure (topology) partitions that can be mapped to plant operation levels, which are described by ANSI/ISA‐S88. In addition, the use of design knowledge can be useful to define conceptual partitions such as Block, which is essential to link design and operation knowledge. Plant operation (jobs) can be flexibly defined in view of plant structure partitions in terms of resources (materials, plant structural areas) required and operation scheduling.

It is important to link to production scheduling to ensure effective use of topology partitions in real time based on available resources. The proposed approach can be improved via the integration with intelligent production scheduling.

Production and manufacturing plants will be able to use the proposed approach to design and validate plant operation and to improve plant maintenance while reducing operation risks by identifying plant structures required for each operation task. The proposed technique can be helpful to engineers and R&D members to consider in their design and investigation for process safety, risk management, and plant operation and management.

The idea of topology analysis is quite new where it is usually implemented using search algorithms without considering domain knowledge and operation structures. This paper proposes a valuable technique to link plant structure with plant operation hierarchies, which is important for design and engineering practices and R&D activities for plant operation.