bluuebunny/crossref_metadata_2025 huggingface dataset:
On Energy-Security Tradeoffs and Cooperation for Wireless Ad Hoc Networks
Authors: Comaniciu Cristina
Published: July 2021

In this paper we discuss the inherent security-energy tradeoffs that exist in wireless ad hoc networks. We propose a closed form cost computation approximation formula to determine the energy cost of monitoring for an intrusion detection algorithm based on its computational complexity and data size. Based on energy and security costs, we formulate a game theoretic distributed monitoring algorithm that enforces cooperative behavior for individual nodes by means of reward functions. Various energy-security tradeoffs operating points for the network intrusion detection can be achieved by tuning the rewards parameter.
Evolution of Mobility in Future Wireless Networks
Authors: Rajkumar Ajay
Published: July 2021

With an ever increasing appetite for data over wireless networks, one is forced to think where the additional capacity in the wireless networks come from to carry the traffic? Some would argue that additional spectrum needs to be made available or a substantial increase in spectral efficiency has to come by. However, notwithstanding the above, an additional area that has important implications is to evolve seamless and non-seamless session mobility across disparate access technologies such as WiFi to offload some of the traffic to these alternate networks. Similarly, selective handover of specific flows across smaller cells such as Femto and Pico cells of the same access technology will have an impact on the overall capacity of the network. This not only will improve the capacity of these networks but may also enhance the quality of experience for users.
Activity Modelling and Comparative Evaluation of WSN MAC Security Attacks
Authors: Pawar Pranav M. , Nielsen Rasmus H. , Prasad Neeli R. , Ohmori Shingo , Prasad Ramjee
Published: July 2021

Applications of wireless sensor networks (WSNs) are growing tremendously in the domains of habitat, tele-health, industry monitoring, vehicular networks, home automation and agriculture. This trend is a strong motivation for malicious users to increase their focus on WSNs and to develop and initiate security attacks that disturb the normal functioning of the network in a severe manner. Such attacks affect the performance of the network by increasing the energy consumption, by reducing throughput and by inducing long delays. Of all existing WSN attacks, medium access control (MAC) layer attacks are considered the most harmful as they directly affect the available resources and thus the nodes’ energy consumption.The first endeavour of this paper is to model the activities of MAC layer security attacks to understand the flow of activities taking place when mounting the attack and when actually executing it. The second aim of the paper is to simulate these attacks on hybrid MAC mechanisms, which shows the performance degradation of a WSN under the considered attacks. The modelling and implementation of the security attacks give an actual view of the network which can be useful in further investigating secure mechanisms to reduce the degradation of the performance in WSNs due to an attack. Lastly, the paper proposes some solutions to reduce the effects of an attack.
Vulnerabilities and Countermeasures – A Survey on the Cyber Security Issues in the Transmission Subsystem of a Smart Grid
Authors: Deng Yi , Shukla Sandeep
Published: July 2021

With the increased investment and deployment of embedded computing and communication technologies in the power system – the smart grid vision is shaping up into a reality. The future power grid is a large cyber physical system (CPS) which is vulnerable to cyber security threats. Among the three major subsystems of a power grid – generation, transmission and distribution – this survey focuses on the transmission subsystem because most of the cyberization of the grid has been happening in this subsystem. This is due to the need for distributed measurement, monitoring and control to retain the stability, security, and reliability of power transmission system. Given the geographically dispersed generation facilities, substations, control centers, data concentrators etc., efficient data communication is required, and therefore large scale networking – either proprietary or leased – is happening. The goal of this paper is not to be comprehensive to include all efforts of securing the transmission system from cyber borne threats, but to provide a survey of various vulnerabilities, and countermeasures proposed by various research efforts. One of the focus area in this survey is the Phasor Measurement Units (PMUs) and Wide Area Measurement System (WAMS) technology – mostly due to our familiarity with the issues for this specific technology deployment – rather than any attempt to indicate that this is the most vulnerable technology in the transmission subsystem. Our hope is that this survey will familiarize any uninitiated reader with the issues and provide incentive to undertake systematic research programs to thwart cyber attacks on our national power delivery infrastructure.
Understanding the Security, Privacy and Trust Challenges of Cloud Computing
Authors: Nayak Debabrata
Published: July 2021

The overall objective of this paper is to understand the Security, Privacy and Trust Challenges and to advise on policy and other interventions which should be considered in order to ensure that Indian users of cloud environments are offered appropriate protections, and to underpin Indian cloud ecosystem. Cloud computing is increasingly subject to interest from policymakers and regulatory authorities. The Indian regulator needs to develop a pan-Indian ‘cloud strategy’ that will serve to support growth and jobs and build an innovation advantage for India. However, the concern is that currently a number of challenges and risks with respect to security, privacy and trust exist that may undermine the attainment of these policy objectives. Our approach has been to undertake an analysis of the technological, operational and legal intricacies of cloud computing, taking into consideration the Indian dimension and the interests and objectives of all stakeholders (citizens, individual users, companies, cloud service providers, regulatory bodies and relevant public authorities). This paper represents an evolutionary progression in understanding the implications of cloud computing for security, privacy and trust. Starting from an overview of the challenges identified in the area of cloud, the study builds upon real-life case study implementations of cloud computing for its analysis and subsequent policy considerations. As such, we intend to offer additional value for policymakers beyond a comprehensive understanding of the current theoretical or empirically derived evidence base, which will understand the cloud computing and the associated open questions surrounding some of the important security, privacy and trust issues.
Mobility and Spatio-Temporal Exposure Control
Authors: M. Køien Geir
Published: July 2021

Modern risk assessment methods cover many issues and encompass both risk analysis and corresponding prevention/mitigation measures.However, there is still room for improvement and one aspect that may benefit from more work is “exposure control”.The “exposure” an asset experiences plays an important part in the risks facing the asset.Amongst the aspects that all too regularly get exposed is user identities and user location information,and in a context with mobile subscriber and mobility in the service hosting (VM migration/mobility) the problems associated with lost identity/location privacy becomes urgent.In this paper we look at “exposure control” as a way for analyzing and protecting user identity and user location data.
An Introduction to Formal Standardization and the Work on ICT Standardization in ISO/IEC – JTC1
Authors: Madelung Niels , Andersen Katrine Bergh
Published: July 2021

The purpose of this article is (a) to give the reader an introduction to formal standardization and (b) an overview of international standardization activities in the field of ICT.

In the first part of the article the introduction to formal standardization will be exemplified at a national level by the national Danish standardization organization (DS), at a European level by the European standardization organizations (CEN/CELENEC and ETSI) and at a global level by the international standardization organizations (ISO, IEC and ITU).

The second part of the article will provide the reader with an overview of the standards and ongoing standardization activities in JTC1 – the joint technical committee between ISO and IEC on ICT standardization. This paragraph will include a number of illustrative examples to give an in-depth impression of the work in the joint technical committee.
IEEE 802.11ah: A Long Range 802.11 WLAN at Sub 1 GHz
Authors: Sun Weiping , Choi Munhwan , Choi Sunghyun
Published: July 2021

IEEE 802.11ah is an emerging Wireless LAN (WLAN) standard that defines a WLAN system operating at sub 1 GHz license-exempt bands. Thanks to the favorable propagation characteristics of the low frequency spectra, 802.11ah can provide much improved transmission range compared with the conventional 802.11 WLANs operating at 2.4 GHz and 5 GHz bands. 802.11ah can be used for various purposes including large scale sensor networks, extended range hotspot, and outdoor Wi-Fi for cellular traffic offloading, whereas the available bandwidth is relatively narrow.

In this paper, we give a technical overview of 802.11ah Physical (PHY) layer and Medium Access Control (MAC) layer. For the 802.11ah PHY, which is designed based on the down-clocked operation of IEEE 802.11ac’s PHY layer, we describe its channelization and transmission modes. Besides, 802.11ah MAC layer has adopted some enhancements to fulfill the expected system requirements. These enhancements include the improvement of power saving features, support of large number of stations, efficient medium access mechanisms and throughput enhancements by greater compactness of various frame formats. Through the numerical analysis, we evaluate the transmission range for indoor and outdoor environments and the theoretical throughput with newly defined channel access mechanisms.
The Challenge of Zero Touch and Explainable AI
Authors: Dutta Biswadeb , Krichel Andreas , Odini Marie-Paule
Published: July 2021

With ever increasing complexity and dynamicity in digital service provider networks, especially with the emergence of 5G, operators seek more automation to reduce the cost of operations, time to service and revenue of new and innovative services, and increase the efficiency of resource utilization, Complex algorithms leveraging ML (machine learning) are introduced, often with the need for frequent training as the networks evolve. Inference is then applied either in the core directly, or in the management stack to trigger actions and configuration changes automatically. This is the essence of Zero Touch. The challenge that analysts are often faced with is to trace back from the inference or prediction to the original events or symptoms that led to the triggered action, which ML model version or pipeline was used. This paper describes the challenges faced by analysts and provides some solutions.
I2BN: Intelligent Intent Based Networks
Authors: Szilágyi Péter
Published: July 2021

Intent based network management reduces the complexity of network programming from a growing set of deeply technical APIs to context-free high-level objectives that the network should autonomously achieve and keep. The practical implementation of an intent based network requires substantial automation technology embedded in the network. Automation should cover the entire lifecycle of intents, from their ingestion to fulfillment and assurance. This article investigates the feasibility of automatically assembling interworking implementation units into intent specific automation pipelines, where units are reusable self-learning closed loop micro-services with self-declared capabilities. Each closed loop may gain knowledge and respond to dynamically changing network conditions, thereby enabling network autonomy in reaching the declared intent objectives. The human-network intent interface for expressing intents is proposed to be based on the aggregation of the deployed network and service automation capabilities, rather than a formalism decoupled from the actual network implementation. This principle removes the ambiguity and compatibility gap between human intent definition and machine intent fulfillment, while retaining the flexibility and extendibility of the intents offered by any specific system via onboarding additional micro-services with novel capabilities. The concepts discussed by the article fit into the architecture and closed loop work items already defined by ETSI ZSM and provides considerations towards new areas such as intent driven autonomous networks and enablers for automation.
Inspection Mobile Robot’s Control System with Remote IoT-based Data Transmission
Authors: Kondratenko Yuriy , Gerasin Oleksandr , Kozlov Oleksiy , Topalov Andriy , Kilimanov Bogdan
Published: July 2021

The article presents the main stages of the development of remote control system for the inspection mobile robot operating on inclined ferromagnetic surfaces. The mobile robot remains on the surface and moves along working areas using separate clamping permanent magnets and caterpillars. The focus is on the control system’s architecture and remote data transmission based on Internet of Things technologies. Features of non-expensive Arduino Uno and WeMos D1 R2 mini microcontrolled development boards, cloud service Blynk, as well as multi-tab Android application interactions are revealed at the inspection mobile robot movement on the inclined surface. Experimental results of the proposed system show a good compatibility of chosen hardware, user-friendly human-machine interface and high mobility for future research of modern control algorithms at Internet of Things approach implementation for the extreme robotics.
Moving Object Tracking for SLAM-based Augmented Reality
Authors: Oliveira Douglas Coelho Braga de , Silva Rodrigo Luis de Souza da
Published: July 2021

Augmented Reality (AR) systems based on the Simultaneous Localization and Mapping (SLAM) problem have received much attention in the last few years. SLAM allows AR applications on unprepared environments, i.e., without markers. However, by eliminating the marker object, we lose the referential for virtual object projection and the main source of interaction between real and virtual elements. In the recent literature, we found works that integrate an object recognition system to the SLAM in a way the objects are incorporated into the map. In this work, we propose a novel optimization framework for an object-aware SLAM system capable of simultaneously estimating the camera and moving objects positioning in the map. In this way, we can combine the advantages of both marker- and SLAM-based methods. We implement our proposed framework over state-of-the-art SLAM software and demonstrate potential applications for AR like the total occlusion of the marker object.
Design and Development of an Android App Based on Firebase in the Study of Unsportsmanlike Behaviors in Grassroots Tennis Competitions
Authors: García José , De Lera V. , Lacambra D. , Gimeno F. , Alesanco Álvaro
Published: July 2021

This paper presents the design, development and evaluation of an android application based on the Google Firebase platform aimed to facilitate the creation of questionnaires and collection of data for the management of sports and unsportsmanlike behaviors in grassroots tennis competitions. Although sportsmanship among players is the most common situation, in low categories sometimes aggressive or violent situations may occur and not always with the presence of referees. In recent years, the use of conventional questionnaires has been the most widespread tool to obtain information on sports and unsportsmanlike behaviors in sports competitions. The developed system allows tennis tournament organizers to easily create forms linked to the players in order to evaluate different psychological aspects during the competition. Players are notified and they answer the proposed questions on their mobile devices at the end of the matches. By using the application it is easy to collect the responses of the competitors and process and evaluate them. The developed system is based on a client-server architecture where the Firebase platform acts as system server and the application is the client that communicates with it. The application was validated by a tournament administrator showing a high level of usability. Afterwards it has been tested in a real tournament with 20 players (in a total of 34 matches) answering a form consisting of 13 questions to evaluate sports and unsportsmanlike behaviors. The results in this pilot tournament showed the perception of sportsmanship of the players as very good, but also showed that parents or companions interfere in children’s matches and two potential cases of unsportsmanlike conduct were detected. This system may become a versatile and useful tool for improvement of players’ psychological wellbeing during grassroots tennis competitions.
Rice Disease Recognition Using Effective Deep Neural Networks
Authors: Mathulaprangsan S. , Patarapuwadol S. , Lanthong K. , Jetpipattanapong D. , Sateanpattanakul S.
Published: July 2021

Rice is the most important grain in Thailand for both consuming and exporting. One of the critical problems in rice cultivation is rice diseases, which affects directly to the yield. Early disease recognition is handled by a human, which is difficult to achieve high accuracy and the performance depends on the farmer’s experience. To overcome this problem, we did three folds of contributions. First, an infield rice diseases image dataset, named K5RD, was created. Second, a number of additional techniques to enhance the classification scores including data augmentations and learning rate adjustment strategies were carefully surveyed. Third, a set of selective deep learning models including ResNets and DenseNets were applied to classify such rice diseases. The experimental results reveal that the proposed framework can achieve high performance, which its F1 score is higher than 98% on average, and has the potential to be implemented as a practical system to provide to Thai farmers in the future.
Crawling the Deep Web Using Asynchronous Advantage Actor Critic Technique
Authors: Madan Kapil , Bhatia Rajesh
Published: July 2021

In the digital world, World Wide Web magnitude is expanding very promptly. Now a day, a rising number of data-centric websites require a mechanism to crawl the information. The information accessible through hyperlinks can easily be retrieved with general-purpose search engines. A massive chunk of the structured information is invisible behind the search forms. Such immense information is recognized as the deep web and has structured information as compared to the surface web. Crawling the content of deep web is very challenging and requires filling the search forms with suitable queries. This paper proposes an innovative technique using an Asynchronous Advantage Actor-Critic (A3C) to explore the unidentified deep web pages. It is based on the policy gradient deep reinforcement learning technique that parameterizes the policy and value function based on the reward system. A3C has one coordinator and various agents. These agents learn from different environments, update the local gradients to a coordinator, and produce a more stable system. The proposed technique has been validated with Open Directory Project (ODP). The experimental outcome shows that the proposed technique outperforms most of the prevailing techniques based on various metrics such as average precision-recall, average harvest rate, and coverage ratio.
Fine-Grained User Location Prediction using Meta-Path Context with Attention Mechanism
Authors: Wang Zhixiao , Yan Wenyao , Gao Ang
Published: July 2021

The prevalence of Location-Based Social Networks (LBSNs) significantly improves the location-aware capability of services by providing Geo-tagged information. Relied on a great number of user check-in data in the location-based social networks, their essential mobility modes are able to be comprehensively studied, which is basic for forecasting the next venue where a specific user is going to visit considering his relevant historical check-in data. Since there exist different kinds of nodes and interactions between nodes, these information could be look upon as a network that is made up of heterogeneous information. In this network a few of different semantic meta paths could be obtained. Enlightened from the competitive advantage of embedding method relied upon meta-path contexts in the heterogeneous information network, we study a joint deep learning scheme exploring different meta-path context information to forecast fine-grained location. In order to capture different semantics in a user-location interaction, we adopt a simple but high-efficient attention method to learn the meta-path importance or weights. In the terms of model optimization, considering we have only positive sample data and there exists intrinsically latent feedback in check-in information, herein a pairwise learning method is utilized for maximizing the margin between visited and invisible venues. Experiment in different data-sets validate the competitive performance of the suggested approach under different assessment criterion.
Joint Representations of Texts and Labels with Compositional Loss for Short Text Classification
Authors: Hao Ming , Wang Weijing , Zhou Fang
Published: July 2021

Short text classification is an important foundation for natural language processing (NLP) tasks. Though, the text classification based on deep language models (DLMs) has made a significant headway, in practical applications however, some texts are ambiguous and hard to classify in multi-class classification especially, for short texts whose context length is limited. The mainstream method improves the distinction of ambiguous text by adding context information. However, these methods rely only the text representation, and ignore that the categories overlap and are not completely independent of each other. In this paper, we establish a new general method to solve the problem of ambiguous text classification by introducing label embedding to represent each category, which makes measurable difference between the categories. Further, a new compositional loss function is proposed to train the model, which makes the text representation closer to the ground-truth label and farther away from others. Finally, a constraint is obtained by calculating the similarity between the text representation and label embedding. Errors caused by ambiguous text can be corrected by adding constraints to the output layer of the model. We apply the method to three classical models and conduct experiments on six public datasets. Experiments show that our method can effectively improve the classification accuracy of the ambiguous texts. In addition, combining our method with BERT, we obtain the state-of-the-art results on the CNT dataset.
Research on Data Release and Location Monitoring Technology of Sensor Network Based on Internet of Things
Authors: Lin Bin
Published: July 2021

The Internet of Things is another information technology revolution and industrial wave after computer, Internet and mobile communication. It is becoming a key foundation and an important engine for the green, intelligent and sustainable development of economic society. The new networked intelligent production mode characterized by the integration innovation of the Internet of Things is shaping the core competitiveness of the future manufacturing industry. The application of sensor network data positioning and monitoring technology based on the Internet of Things in industry, power and other industries is a hot field for the development of the Internet of Things. Sensor network processing and industrial applications are becoming increasingly complex, and new features have appeared in the sensor network scale and infrastructure in these fields. Therefore, the Internet of Things perception data processing has become a research hotspot in the deep integration process between industry and the Internet of Things. This paper deeply analyzes and summarizes the characteristics of sensor network perception data under the new trend of the Internet of Things as well as the research on location monitoring technology, and makes in-depth exploration from the release and location monitoring of sensor network perception data of the Internet of Things. Sensor network technology integrated sensor technology, micro-electromechanical system technology, wireless communication technology, embedded computing technology and distributed information processing technology in one, with easy layout, easy control, low power consumption, flexible communication, low cost and other characteristics. Therefore, based on the release and location monitoring technologies of sensor network data based on the Internet of Things in different applications, this paper studies the corresponding networking technologies, energy management, data management and fusion methods. Standardization system in wireless sensor network low cost, and convenient data management needs, design the iot oriented middleware, and develops the software and hardware system, the application demonstration, the results show that the design of wireless sensor network based on iot data monitoring and positioning technology is better meet the application requirements, fine convenient integration of software and hardware, and standardized requirements and suitable for promotion.
Research on Outlier Detection for High-Dimensional Data Based on PPCLOF
Authors: Chen Chen , Luo Kaiwen , Min Lan , Li Shenglin
Published: July 2021

Aiming at the “dimension disaster” problem encountered in the outlier detection of high-dimensional data, this paper uses the projection pursuit algorithm to perform non-linear dimensionality reduction on high-dimensional data by calculating the phase relationship between dimensions. According to the sample points obtained by dimensionality reduction, the LOF (Local Outlier Factor) algorithm is applied to calculate the outlier factor to obtain the relevant outlier data. In order to improve the calculation accuracy and efficiency of the LOF algorithm, clustering method is used to cut the outlier calculation data to reduce the amount of calculation. Experiments on real-world and artificial datasets, compared with the existing algorithms, demonstrated the effectiveness and efficiency of the proposed algorithm.
Research on Web Data Mining Based on Topic Crawler
Authors: Guo Hongjian
Published: July 2021

This paper analyzes the method of Web information data mining based on topic crawler. This paper puts forward the architecture of Web information search and data mining, and introduces the key technology and operation principle of the architecture. After analyzing the functions and shortcomings of ordinary crawler, this paper focuses on the working principle, implementation method and performance analysis of this crawler, as well as the functions of this crawler different from other crawlers and its application in Web information search and data mining system. The experimental results show that the crawler can get all kinds of information resources on the world wide web, which is helpful to the monitoring and management of network cultural content.
Creating and Capturing Artificial Emotions in Autonomous Robots and Software Agents
Authors: Hoffmann Claus , Linden Pascal , Vidal Maria-Esther
Published: July 2021

This paper presents ARTEMIS, a control system for autonomous robots or software agents. ARTEMIS can create human-like artificial emotions during interactions with their environment. We describe the underlying mechanisms for this. The control system also captures its past artificial emotions. A specific interpretation of a knowledge graph, called an Agent Knowledge Graph, stores these artificial emotions. ARTEMIS then utilizes current and stored emotions to adapt decision making and planning processes. As proof of concept, we realize a concrete software agent based on the ARTEMIS control system. This software agent acts as a user assistant and executes their orders and instructions. The environment of this user assistant consists of several other autonomous agents that offer their services. The execution of a user’s orders requires interactions of the user assistant with these autonomous service agents. These interactions lead to the creation of artificial emotions within the user assistant. The first experiments show that it is possible to realize an autonomous user assistant with plausible artificial emotions with ARTEMIS and record these artificial emotions in its Agent Knowledge Graph. The results also show that captured emotions support successful planning and decision making in complex dynamic environments. The user assistant with emotions surpasses an emotionless version of the user assistant.
An Empirical Study of Web Page Structural Properties
Authors: Chamberland-Thibeault Xavier , Hallé Sylvain
Published: July 2021

The paper reports results on an empirical study of the structural properties of HTML markup in websites. A first large-scale survey is made on 708 contemporary (2019–2020) websites, in order to measure various features related to their size and structure: DOM tree size, maximum degree, depth, diversity of element types and CSS classes, among others. The second part of the study leverages archived pages from the Internet Archive, in order to retrace the evolution of these features over a span of 25 years. The goal of this research is to serve as a reference point for studies that include an empirical evaluation on samples of web pages.
Application of the LDA Model to Semantic Annotation of Web-based English Educational Resources
Authors: Du Wei , Zhu Haiyan , Saeheaw Teeraporn
Published: July 2021

Based on the LDA model, this paper builds a three-layer semantic model of Web English educational resources “document-topic-keyword”, models the semantic topics of resource documents, and obtains the semantic topics and keywords of document resources as the semantic labels of resources. The experimental results show that document LDA topic modeling is beneficial to the macroscopic classification of Web English educational resources. The experimental results show that LDA topic modeling of documents is useful for macroscopic cataloging of Web English educational resources, highlighting teaching priorities, difficulties, and interrelationships, while LDA modeling of teaching topics with the same teaching content expands the metadata generation method of resource description based on the basic education metadata standard and provides more information about the inherent characteristics of resources. The semantic information can be used to mine the semantic thematic features and detailed differences inherent in the resources, and the final performance analysis verifies the parallel computing advantages of the LDA model in a big data environment.
Photographic Image Intelligent Fuzzy Assistant Teaching System Based on Augmented Reality and Web
Authors: Fan Xiaoying
Published: July 2021

Due to the limitation of time and space, the traditional photographic image intelligent fuzzy teaching system can not provide targeted auxiliary teaching for students with different learning abilities. The design of intelligent fuzzy assistant teaching system of photographic image based on augmented reality and web is carried out, including the hardware design of server and peripheral equipment selection, and the design of intelligent fuzzy assistant teaching system of photographic image based on Web and augmented reality, such as intelligent fuzzy assistant teaching display, student learning behavior evaluation software design, etc. Experiments show that, compared with the traditional system, the photographic image intelligent fuzzy assistant teaching system based on augmented reality and web has more correct allocation of teaching resources, stronger pertinence and practical value.
Modal analysis of industrial fluid structure systems with symmetric formulations in a finite element code
Authors: Sigrist Jean-François
Published: July 2021

The present paper deals with numerical developments performed in the finite element code ANSYS in order to implement coupled fluid structure formulations using symmetric matrices. The so-called (u, p, φ) formulation with mass and stiffness coupling is developed in the ANSYS code, enhancing the modeling possibilities of the existing fluid elements. Theoretical bases of the formulation are first exposed, test-cases and industrial application are then proposed. It is shown that computing times are decreased by 90% using a symmetric formulation instead of a non-symmetric one, allowing modal analysis of complex structures with fluid coupling for industrial purposes.
A natural element updated Lagrangian approach for modelling fluid structure interactions
Authors: Galavís Andrés , González David , Cueto Elias , Chinesta Francisco , Doblaré Manuel
Published: July 2021

In this paper we present a novel methodology for the numerical simulation of fluid structure interactions in the presence of free surfaces. It is based on the use of the Natural Element Method (NEM) in an updated Lagrangian framework, together with the integration of the Navier-Stokes equations by employing a Galerkin-characteristics formulation. Tracking of the free-surface is made by employing shape constructors, in particular α- shapes. A theoretical description of the method is made and also some examples of the performance of the technique are included.
Explicit finite element method for in-vivo mechanics of abdominal aortic aneurysm
Authors: Gasbarro Michelle D. , Shimada Kenji , Martino Elena S. Di
Published: July 2021

In this paper we present a strongly-coupled, dynamic, fluid structure interaction analysis of the abdominal aorta in the presence of aneurysm, using an explicit finite element method. All dominating features of the biological system under study were taken into account, including blood dynamics and wall mechanics and the interaction between the two. The inclusion of the surrounding organs and structures that are in contact with the infra-renal aortic segment added physiological realism to the simulation and proved to be a good approach to integrate the interaction of the aorta with its environment. A similar solution strategy could be advantageous to the study of other cardiovascular structures that require a strong coupling among fluid, solid and surrounding entity behaviors.
Proper orthogonal decomposition investigation in fluid structure interaction
Authors: Liberge Erwan , Benaouicha Mustapha , Hamdouni Aziz
Published: July 2021

This paper describes Reduced Order Modeling (ROM) in Fluid Structure Interaction (FSI) and discusses Proper Orthogonal Decomposition (POD) utilization. The ROM method was selected because its performance in fluid mechanics. The principal problems of its application in FSI are due the space character of the modes resulting from the POD whereas domains are mobile. To use POD in moving domain, a charateristic function of fluid is introduced in order to work on a fixed rigid domain, and the global velocity (fluid and structure) is studied. The POD modes efficiency is tested to reconstruct velocity field in one and two-dimensional FSI case. Then reducing dynamic system using POD is introduced in moving boundaries problem. In addition, the one dimensional case of Burgers equation coupled with spring equation is tested.
Response of piles to inclined uplift loads
Authors: Mroueh Hussein , Shahrour Isam
Published: July 2021

This paper presents a three-dimensional finite element analysis of the response of piles to inclined uplift loads. It deals with the influence of the soil-pile interface on this response. Calculations are carried out for several load’s inclinations and different conditions at the soil-pile interface. The concept of the “critical depth” at the soil-pile interface is investigated. Analyses show that the lateral behaviour of the pile is independent from both the load’s inclination and the interface condition, while both the load’s inclination and the soil-pile interface largely affect the axial response of piles.
A new fluid structure coupling
Authors: Aquelet Nicolas , Tutt Benjamin
Published: July 2021

The modelling of parachutes at Irvin Aerospace Inc. was based on the penalty Euler-Lagrange coupling method to compute the interaction between an Arbitrary Lagrange Euler formulation for the air flow and an updated Lagrangian finite element formulation for the canopy dynamics. This approach did not permit the effect of fabric porosity to be accounted for. In this paper, a new porosity Euler-Lagrange coupling models the fabric permeability by assessing the interaction forces based on the Ergun porous flow model. This paper provides validations for the technique when considering parachute applications and discusses the interest of this development to the parachute designer.
A delayed damage model for the prediction of dynamic fracture experiments
Authors: Suffis Arnaud , Combescure Alain , Chevrier Pierre
Published: July 2021

A delayed damage model was recently introduced to avoid artificial localization and mesh dependence in a softening material during a finite element analysis. This model is also interesting for transient applications because it requires only local information to predict damage and plastic strain rates. The physical idea behind this model is that the void growth rate cannot be infinite and hence the damage rate must be bounded. This paper shows that such a model does not require artificial numerical parameters and can be identified using classical spall fracture experiments. It was applied successfully to experiments performed on two aluminum alloys and one titanium alloy. The identification of the delayed damage parameters is presented. The model is applied to a simple numerical experiment which shows clearly that it avoids artificial numerical localization.
Un élément fini de poutre fissurée
Authors: Arem Saber El , Maitournam Habibou
Published: July 2021

In this paper, an original method for construction of a cracked beam finite element is presented. The additional flexibility due to the cracks is identified from three-dimensional finite element calculations taking into account the unilateral contact conditions between the cracks lips. Based on this flexibility which is distributed over the entire length of the element, a new cracked finite element stiffness matrix is deduced. Considerable gain in computing efforts is reached compared to the nodal representation of the cracked section when dealing with the numerical integration of differential equations in structural dynamics.
Simulation thermomécanique du soudage par friction-malaxage
Authors: Feulvarch Eric , Boitout Frédéric , Bergheau Jean-Michel
Published: July 2021

Friction Stir Welding is a welding process where the heat generation is provided by the mechanical dissipation due to the deformations and the friction between the tool and the sheets. This paper describes a finite element model to simulate the heating phenomenon during the steady-state of the process. The stress equilibrium, the energy conservation and the mass conservation are studied in a fully coupled model using a tetrahedral finite element. An example is presented for an aluminium alloy 7075.
Elastoplasticité anisotrope non normale en grandes déformations avec endommagement
Authors: Badreddine Houssem , Saanouni Khémaïs , Dogui Abdelwaheb , Gahbich M. Amen
Published: July 2021

This work is devoted to the numerical integration of an elastoplastic model strongly coupled with ductile damage and formulated in finite deformation. This model with mixed nonlinear work hardening (kinematic and isotropic) is based on a non associative and non normal plasticity theory. The integration is based on the elastic prediction – plastic correction procedure. The proposed constitutive models as well as the associated integration scheme are implemented into ABAQUS/Explicit thanks to VUMAT subroutine. The global resolution is done using the classical Dynamic Explicit (DE) strategy with ABAQUS/Explicit F.E. code. Application is made to the prediction of rupture in anisotropic thin sheet subjected to a hydro bulging test with circular and elliptic matrices. A conparison between the numerical and experimental results shows the capacity of such a modeling to reproduce the anisotropic thin sheet rupture.
Error estimates for the unilateral buckling load of a plate involving the membrane efforts consistency error
Authors: Ayadi Mekki
Published: July 2021

The paper deals with error estimates for the unilateral buckling critical load of a thin plate in presence of an obstacle. The error on the membrane efforts tensor is taken into account. First, using the Mindlin’s plate model together with a finite elements scheme of degree one, an error estimate, depending on the mesh size h, is established. In order to validate this theoretical error estimate, some numerical experiments are presented. Second, using the Kirchhoff-Love’s plate model, an abstract error estimate is achieved. Its drawback is that it contains a hard term to evaluate.
Sensitivity analysis of a strongly coupled aero-structural system using the discrete direct and adjoint methods
Authors: Marcelet Meryem , Peter Jacques , Carrier Gérald
Published: July 2021

This paper is dedicated to the sensitivity analysis of a static aeroelastic system with respect to design parameters governing its jig-shape. The gradients of interest are computed using either the discrete direct differentiation or adjoint vector methods. The aerodynamic load is predicted by the nonlinear Euler equations and transferred to the structure through a consistent and conservative procedure. The induced structural displacement field is computed using beam theory and the matrix of the aerodynamic influence coefficients. Finally, a threedimensional wing-body case is used to verify the successful implementation of the analytical sensitivity analysis methods.
Multi-level gradient-based methods and parametrisation in aerodynamic shape design
Authors: Martinelli Massimiliano , Beux François
Published: July 2021

The present study focuses on multi-level approaches in the context of discrete gradient-based methods for aerodynamic shape design. More precisely, the minimisation is done alternatively on different control subspaces according to multigrid-like cycles, providing at each sub-level a particular gradient preconditioning. Starting from an existing multi-level gradient-based formulation associated to shape grid-points coordinates, a possible generalisation to more compact shape representations is proposed through the construction of adequate sets of embedded shape sub-parametrisations. The behaviour of the new formulation is illustrated on different 2D inverse problems for inviscid flows.
Turbine cascade design via multigrid-aided finite-difference progressive optimization
Authors: Catalano Luciano A. , Dadone Andrea , Daloiso Vito S.E.
Published: July 2021

This paper proposes an efficient and robust procedure for the design optimization of turbomachinery cascades in inviscid and turbulent transonic flow conditions. It employs a progressive strategy, based on the simultaneous convergence of the design process and of all iterative solutions involved (flow analysis, gradient evaluation), also including the global refinement from a coarse to a sufficiently fine mesh. Cheap, flexible and easy-to-program Multigrid-Aided Finite Differences are employed for the computation of the sensitivity derivatives. The entire approach is combined with an upwind finite-volume method for the Euler and the Navier-Stokes equations on cell-vertex unstructured (triangular) grids, and validated versus the inverse design of a turbine cascade. The methodology turns out to be robust and highly efficient, the converged design optimization being obtained in a computational time equal to that required by 15 to 20 (depending on the application) multigrid flow analyses on the finest grid.
Multimodel design strategies applied to sonic boom reduction
Authors: Alauzet Frédéric , Borel-Sandou Sophie , Daumas Laurent , Dervieux Alain , Dinh Quang , Kleinveld Steven , Loseille Adrien , Mesri Youssef , Rogé Gilbert
Published: July 2021

The shape optimization of a supersonic aircraft need a composite model combining a 3D CFD high-fidelity model and a simplified boom propagation model. The management of this complexity is studied in an optimization loop, with exact discrete adjoints of 3D flow and mesh deformation system. The introduction of a mesh adaptation algorithm is also considered.
Optimisation du procédé de pliage pour la mise en forme de pièces de sécurité automobile
Authors: Bahloul Riadh , Mkaddem Ali , Santo Philippe Dal , Potiron Alain , Saïdane Delphine
Published: July 2021

In this work, the process optimisation of security parts manufacturing is simulated by a finite element modelling including a material damage formulation. Objective functions, stress and damage values occurring in the part at the end of a bending operation, are analysed by means of numerical Design of Experiments and Response Surface Methodology. The process optimisation is carried out by global minimisation and by means of Evolution Strategies. A multi-objective optimisation is carried out in order to identify the best choice of material and process parameters giving a reliable part-life.
Unstable and limited crack propagation
Authors: Tie Bing , Adouani Haithem , Berdin Clotilde , Cattet Silvère
Published: July 2021

We consider in this paper the unstable and limited extension of brittle cracks when they initiate near or in local brittle zones and extend through them towards tougher material zones. Our aim is to predict their arrest and in this case, one observes the so-called “pop-in” phenomenon. We use the cohesive zone models as constitutive law of brittle cracks, which are numerically modelled using interface-type elements. Non-linear solvers including loading step adaptive strategy are developed, that is necessary to overcome convergence difficulties during the pop-in. Some numerical aspects specifically related to the pop-in modelling are discussed. Parametric studies on CT specimens are carried out to point out the influential numerical, plastic and fracture parameters. As an example, the yield strength mismatch between the local brittle zone and the tougher material plays a very important role on the pop-in phenomenon and makes its modelling dependent upon the element size at the crack-tip.
Enriched space-time finite elements for fluid-structure interaction
Authors: Legay Antoine , Zilian Andreas
Published: July 2021

This paper presents a new numerical approach to deal with fluid structure interaction problems where a thin structure is immersed in an incompressible fluid. Spacetime finite elements are used to discretized the equations using a discontinuous time scheme. In order to take into account the discontinuities due to the structure in the fluid domain, the approximation fluid fields are enriched with appropriate discontinuous functions through a partition of unity (XFEM). The method allows incompatible meshes between fluid and structure, the structure mesh can move freely in the fluid fixed Eulerian mesh.