Development of the DKMT Element for Error Estimation in Composite Plate Structures

This paper presents an application of the Discrete Kirchhoff-Mindlin Triangular (DKMT) element for error estimation in composite structures. The DKMT element passed the patch tests and gave good results in many plate bending applications. The DKMT element formulation in composite application uses the same technique as the Discrete Kirchhoff-Mindlin Quadrilateral (DKMQ) composite introduced. The benchmark tests for composite plates have been analyzed, as validation, using the methods employed by Srinivas (1973) and Pagano (1970). The DKMT plate bending element gave a good performance in convergence tests and can be used as one of tools in analyzing composite structures. Moreover, error estimation using various recovery methods such as Averaging, Projection and Superconvergent Patch Recovery (SPR) has been studied. All recovery methods used give similar results

Error Estimation for the DKMQ24 Shell Element Using Various Recovery Methods

This paper presents an application of DKMQ24 element for error estimation using error estimator Z2 and various recovery methods such as Averaging (AVR), Projection (PROJ) and Superconvergent Patch Recovery (SPR). The stresses found by using these recovery methods will be compared to the reference solution. We found that Averaging and SPR method gave better results compared with the Projection method

Developing Models and Tools for Exploring the Synergies between Energy Transition and the Digital Economy

Developing models and tools to explore the synergies between energy transition and the digital economy has been an interesting topic, aiming to provide significant contributions to the domains of technological innovation, economic development, sustainability, and global establishment. All efforts from these models and tools can support the advanced and establishing countries by collaborating among all members, researchers, governments, and others.     Our continuing research presented the revolutionary potential of insights derived from data and demonstrated the connection between the digital economy and the search for sustainable energy solutions. The second phase of this ongoing investigation focuses on how the digital economy might catalyze beneficial changes in the energy sector. These computerized tools are crucial for improving the efficiency of renewable energy production, anticipating energy demand accurately, and optimizing patterns of energy usage. These technologies enable decision-makers in the energy sector to use complex algorithms and data processing to make precise and well-informed decisions. They represent a substantial shift from older, less data-driven techniques.The following argument highlights how important predictive analytics is for forecasting changes in energy consumption. Data analytics and machine learning models can foresee changes in demand and help energy providers make plans by examining historical data and current patterns. This capacity is essential for guaranteeing the best possible use of resources, avoiding waste, and preserving the equilibrium between energy production and consumption. Optimizing energy use is another important area where the digital economy could be helpful. Machine learning algorithms can make recommendations for ways to improve energy efficiency by analyzing usage patterns and user behavior. This contributes to general energy conservation, which is in line with environmental goals, in addition to perhaps saving consumers money.Numerous studies highlight how ICT-assisted modeling is becoming more and more common in various contexts. These include data modeling (representing and analyzing data structures) and behavior/pattern modeling (understanding and forecasting trends in diverse processes). The phrase refers to the cross-platform accessibility and adaptability of these technologies when referring to web-based and mobile-based applications. The conversation highlights the broad applicability of these technologies and suggests that they are not exclusive to any industry or business. The cross-domain applicability of ICT-assisted modeling is demonstrated by its potential benefits for corporate, government, and public groups. The concept of a digital twin with rich visualization is introduced as a particularly intriguing application. Creating a virtual representation of a real system or process allows for comprehensive tracking, assessment, and optimization. The paragraph argues that the energy sector's efforts to manage energy more effectively can benefit significantly from the adoption of digital twins. Moreover, the potential advantages of digital twins extend to the healthcare sector, where modeling and digitalization can address challenges in this field. In addition, the conversation presents the idea of digital platforms that offer rewards for environmentally conscious actions within the energy sector. These platforms can use innovative market mechanisms to encourage actions that contribute to environmental goals. The discussion claims that digital platforms can encourage demand response and energy conservation by offering users incentives to adjust their energy consumption patterns in response to market or environmental signals. The focus on sustainability draws attention to how integrating digital platforms into energy markets might help society and the environment more broadly. Incentives for demand response and energy conservation not only encourage the more economical use of resources but also contribute to global initiatives aimed at lowering carbon footprints and mitigating the effects of climate change. The 5th International Scientific Conference on Innovations in Digital Economy: SPBPU IDE-2023 has already been held on 12 - 13 October 2023 at Peter the Great St. Petersburg Polytechnic University located at Novorossiyskaya, Saint Petersburg, Russia, with interesting topics such as (i) Economic efficiency and the social consequences of implementing digital innovations, (ii) Regional innovation systems and clusters as drivers of economic growth during the Fourth Industrial Revolution, (iii) Industrial, service and agricultural digitalization, (iv) Responses of the educational system and labor market to digital-driven changes in the economic system, (v) Digital transformation in the government sector, (vi) Digital transformation in the financial sector. This conference is organized by the Graduate School of Industrial Economics (GSIE) of Peter the Great Saint Petersburg Polytechnic University (SPbPU) and the Centre for Sustainable Infrastructure Development (CSID) of Universitas Indonesia (UI). SPBPU IDE-2023 is expected to have a significant impact on the economic, social, and environmental aspects of both regional and national levels. A thorough examination of this phenomenon was evident in the 21 papers that were presented, which mostly focused on researching important aspects such as support systems, finance structures, and regulatory frameworks that control industry operations. The expected results of these research efforts include increased efficiency in investment use, enhanced competitiveness of businesses, and a significant shift towards an ecologically conscious approach to industrial activity. Especially in industrial activities, there is a significant impact on the progress in the economic, social, and environmental conditions of regions and the country as a whole in Russia. The discussion is supported by the presentation of 21 papers, which primarily examine the main forms of support, financing, and regulation of industrial activities, identifying problematic aspects of state support for them. Their approaches are expected to result in more efficient investment utilization, enhanced competitiveness of enterprises, and a shift towards an environmentally focused approach in industrial activities

Digital Innovation: Creating Competitive Advantages

The diffusion of innovations during the fourth industrial revolution reshaped economic systems and caused structural changes in different economic sectors. These innovations have become the basis of the new digital infrastructure of society. Digital technology is used to manage integrated product whole-life cycles and enhance efficient, reliable, and sustainable business operations. Intelligent production processes and supply chains can be used to optimize entire end-to-end workflows and create business competitive advantages. Artificial intelligence, internet of things, machine learning, blockchain, big data and other digital technologies have been used to create business agility and resilience and further transform societal behavior.Digitalization creates new ways for companies to create business added value. Modernizing business enterprises by combining digital technologies, physical resources, and the creativity of individuals, is an essential step in innovative business transformation that may constitute a competitive advantage. Companies need to transform their business processes and enhance the satisfaction of their customers by using digital technologies that connect people, systems, and products or render their services more effective and efficient. Digital technologies create new ways for companies to integrate customers’ requirements into product development or service delivery across entire process chains. Digital technologies are becoming increasingly important due to strong market competition. Many studies have shown that there is a strong correlation between business growth and the use of digital technologies to create innovative business models. Technological innovations create new products, processes, and services that generate more added value for companies.&nbsp

Accelerating Sustainable Energy Development through Industry 4.0 Technologies

Utilizing Industry 4.0 technologies to create a sustainable energy industry enables a decentralized energy system in which energy can be effectively produced, managed, and controlled from local resources. Furthermore, the technologies also enable data capture and analysis to improve energy performance. As digital energy is being developed and increasingly decentralized, renewable energy is now a more attractive option for creating sustainable development. The technologies are capable of integrating different energy sources to respond to an increasingly demanding and distributed market by providing sustainable and efficient resources. The technologies of the fourth industrial revolution (Industry 4.0) are already being used in the energy sector to transform the business processes of the industry. Energy management systems based on emerging technologies, including artificial intelligence (AI), internet of things (IoT), big data, blockchain, and machine learning (ML), have been used to support industry players in analyzing the energy market, improving the supply–demand chain, real-time monitoring, and generating more options for using alternative sources of energy, such as storage devices, fuel cells, and intelligent energy performance. The optimization of the energy industry can be achieved through energy production and distribution efficiency by the digitization of manufacturing processes and service delivery. Optimized energy pricing and capital resources, predictive operation and maintenance plans, efficiency of energy usage, and further maximizing asset lifetime and usage are among the solutions produced from the technologies of Industry 4.0. These technologies are set to transform the energy industry to being more sustainable. This transformation has happened through the provision of integrated information in both planning and operational processes. Industry 4.0 technologies contribute to the efficiency and effectiveness of energy product life-cycles and value chains, therefore impacting business strategies to produce better energy management systems.         Smart energy ecosystems that employ cyber-physical systems enhance all production and consumption energy chain processes. Smart applications in energy production and usage consumption processes can be used efficiently in managing and optimizing energy, such as by storing energy on demand or reducing consumption. Utilizing Industry 4.0 technologies to create a sustainable energy industry enables a decentralized energy system in which energy can be effectively produced, managed, and controlled from local resources. Furthermore, the technologies also enable data capture and analysis to improve energy performance. As digital energy is being developed and increasingly decentralized, renewable energy is now a more attractive option for creating sustainable development. The technologies are capable of integrating different energy sources to respond to an increasingly demanding and distributed market by providing sustainable and efficient resources

Numerical evaluation of DKMQ element for plates and shells

Dans le cadre linéaire, les modèles de Mindlin-Reissner pour les plaques épaisses et de Naghdi pour les coques épaisses sont les plus utilisés. Il est connu que la discrétisation par éléments finis de ces modèles conduit à un phénomène de verrouillage numérique quand l’épaisseur tend vers zéro. Il s’agit du verrouillage en cisaillement dans le cas des plaques et du verrouillage en cisaillement et en membrane dans le cas des coques. Il existe quelques éléments finis qui permettent d’éviter ces difficultés ou du moins de les réduire. L’élément DKMQ pour les plaques et sa version DKMQ24 pour les coques, sont des éléments de bas ordre, basés sur une formulation mixte, qui ont été proposés il y a quelques années afin d’éviter ces phénomènes de verrouillage. Dans cette thèse, on s’est attaché à évaluer numériquement les performances de ces éléments. Outre les cas tests classiques, on s’est focalisé sur l’analyse de la condition inf-sup discrète pour l’élément DKMQ. Nous avons étudié également le test de la s-norme proposé par Bathe, pour l’élément DKMQ24. Enfin, nous avons effectué une analyse d’erreur a posteriori pour les éléments DKMQ et DKMQ24, en utilisant l’estimateur d’erreur Z2 (dû à Zienkiewicz et Zhu), associé aux techniques de recouvrement de la moyenne, de projection ou encore SPR. Les résultats obtenus ont permis de quantifier les performances de ces deux éléments finis pour les problèmes de verrouillage, et d’en dégager les limites. Deux applications importantes de ces éléments DKMQ et DKMQ24 ont été ensuite présentées, la première concerne la simulation des poutres à parois minces à section ouverte et la seconde le calcul des plaques composites.In the linear case, the Mindlin-Reissner model for thick plates and the Naghdi model for thick shells are commonly used. The finite element discretization of these models leads to numerical locking phenomenon when the thickness approaches zero : shear locking for plates and both shear and membrane locking for shells. There are some finite elements that could reduce or even eliminate this phenomenon. DKMQ element for plates or DKMQ24 element for shells, are low-order elements, based on a mixed formulation, introduced a few years ago to prevent the numerical locking phenomenon. In this thesis, we concentrated on numerical evaluation of the performance of these elements. Besides the classical benchmark tests, we also focused on the analysis of discrete inf-sup condition for DKMQ element. We studied the s-norm test proposed by Bathe for DKMQ24 element. Finally, we performed a posteriori error estimation for DKMQ and DKMQ24 elements, using the error estimator Z2 (proposed by Zienkiewicz and Zhu), associated with the averaging, projection or SPR recovery methods. The results obtained have enabled us to quantify the performance of these two finite elements for locking problems, and to identify their limits. Two important applications of these elements DKMQ and DKMQ24 were then presented ; the first one concerns thin-walled beams with open cross-section and the second one composite plates

Évaluation numérique des éléments finis DKMQ pour les plaques et les coques

In the linear case, the Mindlin-Reissner model for thick plates and the Naghdi model for thick shells are commonly used. The finite element discretization of these models leads to numerical locking phenomenon when the thickness approaches zero : shear locking for plates and both shear and membrane locking for shells. There are some finite elements that could reduce or even eliminate this phenomenon. DKMQ element for plates or DKMQ24 element for shells, are low-order elements, based on a mixed formulation, introduced a few years ago to prevent the numerical locking phenomenon. In this thesis, we concentrated on numerical evaluation of the performance of these elements. Besides the classical benchmark tests, we also focused on the analysis of discrete inf-sup condition for DKMQ element. We studied the s-norm test proposed by Bathe for DKMQ24 element. Finally, we performed a posteriori error estimation for DKMQ and DKMQ24 elements, using the error estimator Z2 (proposed by Zienkiewicz and Zhu), associated with the averaging, projection or SPR recovery methods. The results obtained have enabled us to quantify the performance of these two finite elements for locking problems, and to identify their limits. Two important applications of these elements DKMQ and DKMQ24 were then presented ; the first one concerns thin-walled beams with open cross-section and the second one composite plates.Dans le cadre linéaire, les modèles de Mindlin-Reissner pour les plaques épaisses et de Naghdi pour les coques épaisses sont les plus utilisés. Il est connu que la discrétisation par éléments finis de ces modèles conduit à un phénomène de verrouillage numérique quand l’épaisseur tend vers zéro. Il s’agit du verrouillage en cisaillement dans le cas des plaques et du verrouillage en cisaillement et en membrane dans le cas des coques. Il existe quelques éléments finis qui permettent d’éviter ces difficultés ou du moins de les réduire. L’élément DKMQ pour les plaques et sa version DKMQ24 pour les coques, sont des éléments de bas ordre, basés sur une formulation mixte, qui ont été proposés il y a quelques années afin d’éviter ces phénomènes de verrouillage. Dans cette thèse, on s’est attaché à évaluer numériquement les performances de ces éléments. Outre les cas tests classiques, on s’est focalisé sur l’analyse de la condition inf-sup discrète pour l’élément DKMQ. Nous avons étudié également le test de la s-norme proposé par Bathe, pour l’élément DKMQ24. Enfin, nous avons effectué une analyse d’erreur a posteriori pour les éléments DKMQ et DKMQ24, en utilisant l’estimateur d’erreur Z2 (dû à Zienkiewicz et Zhu), associé aux techniques de recouvrement de la moyenne, de projection ou encore SPR. Les résultats obtenus ont permis de quantifier les performances de ces deux éléments finis pour les problèmes de verrouillage, et d’en dégager les limites. Deux applications importantes de ces éléments DKMQ et DKMQ24 ont été ensuite présentées, la première concerne la simulation des poutres à parois minces à section ouverte et la seconde le calcul des plaques composites

An evaluation on the performance of two simple triangular bending plate elements

This paper will study and compare two different three-node triangular bending plate elements with three degree of freedom per node, i.e. MITC3 and DKMT. Both elements, which were developed based on Reissner-Mindlin plate theory and independent shear strain field, have simple formulation and have already been used widely. In this paper, numerical tests for circular plate case are conducted to verify the performance and show the convergence of these two triangular elements

An evaluation on the performance of two simple triangular bending plate elements

This paper will study and compare two different three-node triangular bending plate elements with three degree of freedom per node, i.e. MITC3 and DKMT. Both elements, which were developed based on Reissner-Mindlin plate theory and independent shear strain field, have simple formulation and have already been used widely. In this paper, numerical tests for circular plate case are conducted to verify the performance and show the convergence of these two triangular elements

A unified polygonal locking-free thin/thick smoothed plate element

A novel cell-based smoothed finite element method is proposed for thin and thick plates based on Reissner-Mindlin plate theory and assumed shear strain fields. The domain is discretized with arbitrary polygons and on each side of the polygonal element, discrete shear constraints are considered to relate the kinematical and the independent shear strains. The plate is made of functionally graded material with effective properties computed using the rule of mixtures. The influence of various parameters, viz., the plate aspect ratio and the material gradient index on the static bending response and the first fundamental frequency is numerically studied. It is seen that the proposed element: (a) has proper rank; (b) does not require derivatives of shape functions and hence no isoparametric mapping required; (c) independent of shape and size of elements and (d) is free from shear locking