Search results for: dynamic trading

Authors: Lara Bettinelli, Bernhard Glatz, Josef Fink

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Planning engineers and researchers use various calculation models with different levels of complexity, calculation efficiency and accuracy in dynamic calculations of railway bridges under high-speed traffic. When choosing a vehicle model to depict the dynamic loading on the bridge structure caused by passing high-speed trains, different goals are pursued: On the one hand, the selected vehicle models should allow the calculation of a bridge’s vibrations as realistic as possible. On the other hand, the computational efficiency and manageability of the models should be preferably high to enable a wide range of applications. The commonly adopted and straightforward vehicle model is the moving load model (MLM), which simplifies the train to a sequence of static axle loads moving at a constant speed over the structure. However, the MLM can significantly overestimate the structure vibrations, especially when resonance events occur. More complex vehicle models, which depict the train as a system of oscillating and coupled masses, can reproduce the interaction dynamics between the vehicle and the bridge superstructure to some extent and enable the calculation of more realistic bridge accelerations. At the same time, such multi-body models require significantly greater processing capacities and precise knowledge of various vehicle properties. The European standards allow for applying the so-called additional damping method when simple load models, such as the MLM, are used in dynamic calculations. An additional damping factor depending on the bridge span, which should take into account the vibration-reducing benefits of the vehicle-bridge interaction, is assigned to the supporting structure in the calculations. However, numerous studies show that when the current standard specifications are applied, the calculation results for the bridge accelerations are in many cases still too high compared to the measured bridge accelerations, while in other cases, they are not on the safe side. A proposal to calculate the additional damping based on extensive dynamic calculations for a parametric field of simply supported bridges with a ballasted track was developed to address this issue. In this contribution, several different approaches to determine the additional damping of the supporting structure considering the vehicle-bridge interaction when using the MLM are compared with one another. Besides the standard specifications, this includes the approach mentioned above and two additional recently published alternative formulations derived from analytical approaches. For a bridge catalogue of 65 existing bridges in Austria in steel, concrete or composite construction, calculations are carried out with the MLM for two different high-speed trains and the different approaches for additional damping. The results are compared with the calculation results obtained by applying a more sophisticated multi-body model of the trains used. The evaluation and comparison of the results allow assessing the benefits of different calculation concepts for the additional damping regarding their accuracy and possible applications. The evaluation shows that by applying one of the recently published redesigned additional damping methods, the calculation results can reflect the influence of the vehicle-bridge interaction on the design-relevant structural accelerations considerably more reliable than by using normative specifications.

Keywords: Additional Damping Method, Bridge Dynamics, High-Speed Railway Traffic, Vehicle-Bridge-Interaction

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Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

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Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

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Authors: N. Akhavan, Sh. Tavousi Tafreshi, A. Ghasemi

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Seismic behavior of irregular structures through the past decades indicate that the stated buildings do not have appropriate performance. Among these subjects, the current paper has investigated the behavior of special steel moment frame with different configuration of soft storey vertically. The analyzing procedure has been evaluated with respect to incremental dynamic analysis (IDA), and numeric process was carried out by OpenSees finite element analysis package. To this end, nine 2D steel frames, with different numbers of stories and irregularity positions, which were subjected to seven pairs of ground motion records orthogonally with respect to Ibarra-Krawinkler deterioration model, have been investigated. This paper aims at evaluating the response of two-dimensional buildings incorporating soft storey which subjected to bi-directional seismic excitation. The IDAs were implemented for different stages of PGA with various ground motion records, in order to determine maximum inter-storey drift ratio. According to statistical elements and fracture range (standard deviation), the vulnerability or exceedance from above-mentioned cases has been examined. For this reason, fragility curves for different placement of soft storey in the first, middle and the last floor for 4, 8, and 16 storey buildings have been generated and compared properly.

Keywords: special steel moment frame, soft storey, incremental dynamic analysis, fragility curve

Procedia PDF Downloads 349

Authors: Volker Wannack

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Regional, national, and international strategies focusing on hydrogen (H₂) and blockchain are driving significant advancements in hydrogen and blockchain technology worldwide. These strategies lay the foundation for the groundbreaking "Blockchain Based Hydrogen Market (BBH₂)" project. The primary goal of this project is to develop a functional Blockchain Minimum Viable Product (B-MVP) for the hydrogen market. The B-MVP will leverage blockchain as an enabling technology with a common database and platform, facilitating secure and automated transactions through smart contracts. This innovation will revolutionize logistics, trading, and transactions within the hydrogen market. The B-MVP has transformative potential across various sectors. It benefits renewable energy producers, surplus energy-based hydrogen producers, hydrogen transport and distribution grid operators, and hydrogen consumers. By implementing standardized, automated, and tamper-proof processes, the B-MVP enhances cost efficiency and enables transparent and traceable transactions. Its key objective is to establish the verifiable integrity of climate-friendly "green" hydrogen by tracing its supply chain from renewable energy producers to end users. This emphasis on transparency and accountability promotes economic, ecological, and social sustainability while fostering a secure and transparent market environment. A notable feature of the B-MVP is its cross-border operability, eliminating the need for country-specific data storage and expanding its global applicability. This flexibility not only broadens its reach but also creates opportunities for long-term job creation through the establishment of a dedicated blockchain operating company. By attracting skilled workers and supporting their training, the B-MVP strengthens the workforce in the growing hydrogen sector. Moreover, it drives the emergence of innovative business models that attract additional company establishments and startups and contributes to long-term job creation. For instance, data evaluation can be utilized to develop customized tariffs and provide demand-oriented network capacities to producers and network operators, benefitting redistributors and end customers with tamper-proof pricing options. The B-MVP not only brings technological and economic advancements but also enhances the visibility of national and international standard-setting efforts. Regions implementing the B-MVP become pioneers in climate-friendly, sustainable, and forward-thinking practices, generating interest beyond their geographic boundaries. Additionally, the B-MVP serves as a catalyst for research and development, facilitating knowledge transfer between universities and companies. This collaborative environment fosters scientific progress, aligns with strategic innovation management, and cultivates an innovation culture within the hydrogen market. Through the integration of blockchain and hydrogen technologies, the B-MVP promotes holistic innovation and contributes to a sustainable future in the hydrogen industry. The implementation process involves evaluating and mapping suitable blockchain technology and architecture, developing and implementing the blockchain, smart contracts, and depositing certificates of origin. It also includes creating interfaces to existing systems such as nomination, portfolio management, trading, and billing systems, testing the scalability of the B-MVP to other markets and user groups, developing data formats for process-relevant data exchange, and conducting field studies to validate the B-MVP. BBH₂ is part of the "Technology Offensive Hydrogen" funding call within the research funding of the Federal Ministry of Economics and Climate Protection in the 7th Energy Research Programme of the Federal Government.

Keywords: hydrogen, blockchain, sustainability, innovation, structural change

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Authors: K. I. M. Guerra, L. A. P. Silva, J. C. Leal

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This study aims to understand with more amplitude and clarity the behavior of a porous medium where a pressure wave travels, translated into relative displacements inside the material, using mathematical tools derived from topology and symplectic geometry. The paper starts with a given partial differential equation based on the continuity and conservation theorems to describe the traveling wave through the porous body. A solution for this equation is proposed after all boundary, and initial conditions are fixed, and it’s accepted that the solution lies in a manifold U of purely spatial dimensions and that is embedded in the Real n-dimensional manifold, with spatial and kinetic dimensions. It’s shown that the U manifold of lower dimensions than IRna, where it is embedded, inherits properties of the vector spaces existing inside the topology it lies on. Then, a second manifold (U*), embedded in another space called IRnb of stress dimensions, is proposed and there’s a non-degenerative function that maps it into the U manifold. This relation is proved as a transformation in between two corresponding admissible solutions of the differential equation in distinct dimensions and properties, leading to a more visual and intuitive understanding of the whole dynamic process of a stress wave through a porous medium and also highlighting the dimensional invariance of Terzaghi’s theory for any coordinate system.

Keywords: poremechanics, soil dynamics, symplectic geometry, wave propagation

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Authors: Wiem Zemzem, Moncef Tagina

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In this work, we are addressing the problem of an autonomous mobile robot navigating in a large, unknown and dynamic environment using reinforcement learning abilities. This problem is principally related to the exploration/exploitation dilemma, especially the need to find a solution letting the robot detect the environmental change and also learn in order to adapt to the new environmental form without ignoring knowledge already acquired. Firstly, a new action selection strategy, called ε-greedy-MPA (the ε-greedy policy favoring the most promising actions) is proposed. Unlike existing exploration/exploitation policies (EEPs) such as ε-greedy and Boltzmann, the new EEP doesn’t only rely on the information of the actual state but also uses those of the eventual next states. Secondly, as the environment is large, an exploration favoring least recently visited states is added to the proposed EEP in order to accelerate learning. Finally, various simulations with ball-catching problem have been conducted to evaluate the ε-greedy-MPA policy. The results of simulated experiments show that combining this policy with the Qlearning method is more effective and efficient compared with the ε-greedy policy in stationary environments and the utility-based reinforcement learning approach in non stationary environments.

Keywords: autonomous mobile robot, exploration/ exploitation policy, large, dynamic environment, reinforcement learning

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Authors: Giorgio Visentin, Inna S. Kalinina, Alexei A. Buchachenko

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In the ambit of intermolecular interactions, a combination rule is defined as a relation linking a potential parameter for the interaction of two unlike species with the same parameters for interaction pairs of like species. Some of their most exemplificative applications cover the construction of molecular dynamics force fields and dispersion-corrected density functionals. Here, an extended combination rule is proposed, relating the dipole-dipole dispersion coefficients for the interaction of like target species to the same coefficients for the interaction of the target and a set of partner species. The rule can be devised in two different ways, either by uniform discretization of the Casimir-Polder integral on a Gauss-Legendre quadrature or by relating the dynamic polarizabilities of the target and the partner species. Both methods return the same system of linear equations, which requires the knowledge of the dispersion coefficients for interaction between the partner species to be solved. The test examples show a high accuracy for dispersion coefficients (better than 1% in the pristine test for the interaction of Yb atom with rare gases and alkaline-earth metal atoms). In contrast, the rule does not ensure correct monotonic behavior of the dynamic polarizability of the target species. Acknowledgment: The work is supported by Russian Science Foundation grant # 17-13-01466.

Keywords: combination rule, dipole-dipole dispersion coefficient, Casimir-Polder integral, Gauss-Legendre quadrature

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Authors: Zainab Yahaya Suleiman

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Physical fitness, as one of the most important keys to a healthy wellbeing, is the basis of dynamic and creative intellectual activity. As a result, the fitness world is expanding every day. It is believed that a fitness centre is a place of healing and also the natural environment is vital to speedy recovery. The aim of this paper is to propose and designs a suitable location for a fitness centre in Batagarawa metropolis. Batagarawa city is enriched with four tertiary institutions with diverse commerce and culture but lacks the facility of a well-equipped fitness centre. The proposed fitness centre intends to be an organically sound centre that will make use of principles of organic architecture to create a new pleasant environment between man and his environments. Organic architecture is the science of designing a building within pleasant natural resources and features surrounding the environment. It is regarded as visual poetry and reinterpretation of nature’s principles; as well as embodies a settlement of person, place, and materials. Using organic architecture, the design was interlaced with the dynamic, organic and monumental features surrounding the environment. The city has inadequate/no facility that is considered organic where one can keep fit in a friendly, conducive and adequate location. Thus, the need for establishing a fitness centre to cater for this need cannot be over-emphasised. Conclusively, a fitness centre will be an added advantage to this fast growing centre of learning.

Keywords: organic architecture, fitness center, environment, natural resources, natural features, building design

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Authors: A. P. Srivastava, D. Srivastava, D. J. Browne

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Relaxation dynamics of Zr44Cu40Al8Ag8 bulk metallic glass (BMG) has been probed using dynamic mechanical analyzer. The BMG sample was casted in the form of a plate of dimension 55 mm x 40 mm x 3 mm using tilt casting technique. X-ray diffraction and transmission electron microscope have been used for the microstructural characterization of as-cast BMG. For the mechanical spectroscopy study, samples in the form of a bar of size 55 mm X 2 mm X 3 mm were machined from the BMG plate. The mechanical spectroscopy was performed on dynamic mechanical analyzer (DMA) by 50 mm 3-point bending method in a nitrogen atmosphere. It was observed that two glass transition process were competing in supercooled liquid region around temperature 390°C and 430°C. The supercooled liquid state was completely characterized using DMA and differential scanning calorimeter (DSC). In addition to the main α-relaxation process, presence of β relaxation process around temperature 360°C; below the glass transition temperature was also observed. The β relaxation process could be described by Arrhenius law with the activation energy of 160 kJ/mole. The volume of the flow unit associated with this relaxation process has been estimated. The results from DMA study has been used to characterize the shear transformation zone in terms of activation volume and size. High fragility parameter value of 34 and higher activation volume indicates that this alloy could show good plasticity in supercooled liquid region. The possible mechanism for the relaxation processes has been discussed.

Keywords: DMA, glass transition, metallic glass, thermoplastic forming

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Authors: Zakaria Baka, Halima Alem

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Cancer is a major worldwide health problem that has caused around ten million deaths in 2020. In addition, efforts to develop new anti-cancer drugs still face a high failure rate. This is partly due to the lack of preclinical models that recapitulate in-vivo drug responses. Indeed conventional cell culture approach (known as 2D cell culture) is far from reproducing the complex, dynamic and three-dimensional environment of tumors. To set up more in-vivo-like cancer models, 3D bioprinting seems to be a promising technology due to its ability to achieve 3D scaffolds containing different cell types with controlled distribution and precise architecture. Moreover, the introduction of microfluidic technology makes it possible to simulate in-vivo dynamic conditions through the so-called “cancer-on-chip” platforms. Whereas several cancer types have been modeled through the cancer-on-chip approach, such as lung cancer and breast cancer, only a few works describing ovarian cancer models have been described. The aim of this work is to combine 3D bioprinting and microfluidic technics with setting up a 3D dynamic model of ovarian cancer. In the first phase, alginate-gelatin hydrogel containing SKOV3 cells was used to achieve tumor-like structures through an extrusion-based bioprinter. The desired form of the tumor-like mass was first designed on 3D CAD software. The hydrogel composition was then optimized for ensuring good and reproducible printability. Cell viability in the bioprinted structures was assessed using Live/Dead assay and WST1 assay. In the second phase, these bioprinted structures will be included in a microfluidic device that allows simultaneous testing of different drug concentrations. This microfluidic dispositive was first designed through computational fluid dynamics (CFD) simulations for fixing its precise dimensions. It was then be manufactured through a molding method based on a 3D printed template. To confirm the results of CFD simulations, doxorubicin (DOX) solutions were perfused through the dispositive and DOX concentration in each culture chamber was determined. Once completely characterized, this model will be used to assess the efficacy of anti-cancer nanoparticles developed in the Jean Lamour institute.

Keywords: 3D bioprinting, ovarian cancer, cancer-on-chip models, microfluidic techniques

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Authors: Vajhollah Ghorbanizadeh, Seyed Mohsen Asadi, Mirali Seyednaghavi, Davoud Hoseynpour

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In the current era, all organizations need knowledge to be able to manage the diverse human resources. Creative, dynamic and knowledge-based Human resources are important competitive advantage and the scarcest resource in today's knowledge-based economy. In addition managers with skills of knowledge management must be aware of human resource management science. It is now generally accepted that successful implementation of knowledge management requires dynamic interaction between knowledge management and human resource management. This is emphasized at systematic approach to knowledge management as well. However human resource management can be complementary of knowledge management because human resources management with the aim of empowering human resources as the key resource organizations in the 21st century, the use of other resources, creating and growing and developing today. Thus, knowledge is the major capital of every organization which is introduced through the process of knowledge management. In this context, knowledge management is systematic approach to create, receive, organize, access, and use of knowledge and learning in the organization. This article aims to define and explain the concepts of knowledge management and human resource management and the importance of these processes and concepts. Literature related to knowledge management and human resource management as well as related topics were studied, then to design, illustrate and provide a theoretical model to explain the factors affecting the relationship between knowledge management and human resource management and knowledge management system approach, for schematic design and are drawn.

Keywords: systemic approach, human resources, knowledge, human resources management, knowledge management

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Authors: Prasanjit Das, M. M. K. Khan, M. G. Rasul, Jie Wu, I. Youn

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Mineral scale formation is undoubtedly a more serious problem in the mineral industry than other process industries. To better understand scale growth and suppression, an experimental model is proposed in this study for supersaturated crystallised solutions commonly found in mineral process plants. In this experiment, surface crystallisation of potassium nitrate (KNO3) on the wall of the agitation tank and agitation effects on the scale growth and suppression are studied. The new quantitative scale suppression model predicts that at lower agitation speed, the scale growth rate is enhanced and at higher agitation speed, the scale suppression rate increases due to the increased flow erosion effect. A lab-scale agitation tank with and without baffles were used as a benchmark in this study. The fluid dynamic effects on scale growth and suppression in the agitation tank with three different size impellers (diameter 86, 114, 160 mm and model A310 with flow number 0.56) at various ranges of rotational speed (up to 700 rpm) and solution with different concentration (4.5, 4.75 and 5.25 mol/dm3) were investigated. For more elucidation, the effects of the different size of the impeller on wall surface scale growth and suppression rate as well as bottom settled scale accumulation rate are also discussed. Emphasis was placed on applications in the mineral industry, although results are also relevant to other industrial applications.

Keywords: agitation tank, crystallisation, impeller speed, scale

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Authors: Zuhal Mohammed, Khalid Siddig, Harald Grethe

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Vocational training (VT) has been identified as a potential engine for achieving economic and social development, particularly in developing countries, while during the last two decades it is deemed as an essential determinant of human capital accumulation. Furthermore, it has a crucial role in reducing inequality, wage gaps and unemployment and in promoting skill decomposition. Government plays an important role in the human capital formulation by providing finance for education. In some countries, a large portion of the public educational investment is devoted to academic education (primary, secondary and tertiary). This is reflected in disproportionately increasing investment in various education sectors other than vocational education and VT. Nevertheless, the finance of VT system is not likely to increase or even remain at its existing level. This paper conducts an in-depth analysis to quantify the impacts of various options for expanding the public expenditure on education as well as vocational training in the Sudan. The study uses a recursive dynamic CGE modelling framework that accommodates VT and allows depicting the impact of various policies targeting the vocational training system with special focus on the agricultural sector. This allows for depicting the potential effects of various resource allocation policies not only among education versus non-education sectors, but also between the various types of education and training. Moreover, the study assesses the role of VT system in the economy through its influence on workers’ skill improvement and their movement across sectors. The results show that an increase in the public educational investment will lead to decrease the supply of low and high educated workers as results of increasing the school participation of the students in the short run. While in the medium to long run, this measure guides to increase the productivity of the labour and thus the growth rate of the gross domestic product (GDP). Therefore, the findings of the study provide Sudanese policymakers with needed information to help to adopt measures to reduce unemployment, enhance workers’ skill and ultimately improve livelihoods.

Keywords: vocational training, recursive dynamic CGE, skill level, labour market, economic growth, Sudan

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Authors: Assem M. F. Sallam, Ah. El-S. Makled

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This paper presents a study on the trajectory of a two stage launch vehicle. The study includes dynamic responses of motion parameters as well as the variation of angles affecting the orientation of the launch vehicle (LV). LV dynamic characteristics including state vector variation with corresponding altitude and velocity for the different LV stages separation, as well as the angle of attack and flight path angles are also discussed. A flight trajectory study for the drop zone of first stage and the jettisoning of fairing are introduced in the mathematical modeling to study their effect. To increase the accuracy of the LV model, atmospheric model is used taking into consideration geographical location and the values of solar flux related to the date and time of launch, accurate atmospheric model leads to enhancement of the calculation of Mach number, which affects the drag force over the LV. The mathematical model is implemented on MATLAB based software (Simulink). The real available experimental data are compared with results obtained from the theoretical computation model. The comparison shows good agreement, which proves the validity of the developed simulation model; the maximum error noticed was generally less than 10%, which is a result that can lead to future works and enhancement to decrease this level of error.

Keywords: launch vehicle modeling, launch vehicle trajectory, mathematical modeling, Matlab- Simulink

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Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

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In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: availability, design for maintenance (DFM), dynamic maintenance, life cycle cost (LCC), maintenance free operating period (MFOP), simultaneous optimization

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Authors: F. Mohammadsadeghi

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Relevance of research: Axial compressors are used in both aircraft engine construction and ground-based gas turbine engines. The compressor is considered to be one of the main gas turbine engine units, which define absolute and relative indicators of engine in general. Failure of compressor often leads to drastic consequences. Therefore, safe (stable) operation must be maintained when using axial compressor. Currently, we can observe a tendency of increase of power unit, productivity, circumferential velocity and compression ratio of axial compressors in gas turbine engines of aircraft and ground-based application whereas metal consumption of their structure tends to fall. This causes the increase of dynamic loads as well as danger of damage of high load compressor or engine structure elements in general due to transient processes. In operating practices of aeronautical engineering and ground units with gas turbine drive the operational stability failure of gas turbine engines is one of relatively often failure causes what can lead to emergency situations. Surge occurrence is considered to be an absolute buckling failure. This is one of the most dangerous and often occurring types of instability. However detailed were the researches of this phenomenon the development of measures for surge before-the-fact prevention is still relevant. This is why the research of transient processes for axial compressors is necessary in order to provide efficient, stable and secure operation. The paper addresses the problem of automatic control system improvement by integrating the anti-surge algorithms for axial compressor of aircraft gas turbine engine. Paper considers dynamic exhaustion of gas dynamic stability of compressor stage, results of numerical simulation of airflow flowing through the airfoil at design and stalling modes, experimental researches to form the criteria that identify the compressor state at pre-surge mode detection. Authors formulated basic ways for developing surge preventing systems, i.e. forming the algorithms that allow detecting the surge origination and the systems that implement the proposed algorithms.

Keywords: axial compressor, rotation stall, Surg, unstable operation of gas turbine engine

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Authors: Zabeehullah, Fahim Arif, Yawar Abbas

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Software Defined Network (SDN) is a next genera-tion networking model which simplifies the traditional network complexities and improve the utilization of constrained resources. Currently, most of the SDN based Internet of Things(IoT) environments use traditional network routing strategies which work on the basis of max or min metric value. However, IoT network heterogeneity, dynamic traffic flow and complexity demands intelligent and self-adaptive routing algorithms because traditional routing algorithms lack the self-adaptions, intelligence and efficient utilization of resources. To some extent, SDN, due its flexibility, and centralized control has managed the IoT complexity and heterogeneity but still Software Defined IoT (SDIoT) lacks intelligence. To address this challenge, we proposed a model called Deep Routing Strategy (DRS) which uses Deep Learning algorithm to perform routing in SDIoT intelligently and efficiently. Our model uses real-time traffic for training and learning. Results demonstrate that proposed model has achieved high accuracy and low packet loss rate during path selection. Proposed model has also outperformed benchmark routing algorithm (OSPF). Moreover, proposed model provided encouraging results during high dynamic traffic flow.

Keywords: SDN, IoT, DL, ML, DRS

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Authors: Fawaz A. Binsarra, Halim Boussabaine

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The notion of complexity science has been attracting the interest of researchers and professionals due to the need of enhancing the efficiency of understanding complex systems dynamic and structure of interactions. In addition, complexity analysis has been used as an approach to investigate complex systems that contains a large number of components interacts with each other to accomplish specific outcomes and emerges specific behavior. The design process is considered as a complex action that involves large number interacted components, which are ranked as design tasks, design team, and the components of the design process. Those three main aspects of the building design process consist of several components that interact with each other as a dynamic system with complex information flow. In this paper, the goal is to uncover the complex structure of information interactions in building design process. The Investigating of Royal Institute of British Architects Plan Of Work 2013 information interactions as a case study to uncover the structure and building design process complexity using network analysis software to model the information interaction will significantly enhance the efficiency of the building design process outcomes.

Keywords: complexity, process, building desgin, Riba, design complexity, network, network analysis

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Authors: Minhyuk Heo, Jihwan Yun, Seonghun Park

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It has been reported that intervertebral fusion surgery, which removes most of the ligaments and muscles of the spine, increases the degenerative disease in adjacent spinal segments. Therefore, it is required to develop a lumbar interspinous process fixation device that minimizes the risks and side effects from the surgery. The objective of the current study is to design an interspinous process fixation device with simple structures in order to minimize soft tissue removal and operation time during intervertebral fusion surgery. For the design concepts of a lumbar fixation device, the principle of the ratchet was first applied on the joining parts of the device in order to shorten the operation time. The coil spring structure was selected for connecting parts between the spinous processes so that a normal range of motion in spinal segments is preserved and degenerative spinal diseases are not developed in the adjacent spinal segments. The stiffness of the spring was determined not to interrupt the motion of a lumbar spine. The designed value of the spring stiffness allows the upper part of the spring to move ~10° which is higher than the range of flexion and extension for normal lumbar spine (6°-8°), when a moment of 10Nm is applied on the upper face of L1. A finite element (FE) model composed of L1 to L5 lumbar spines was generated to verify the mechanical integrity and the dynamic stability of the designed lumbar fixation device and to further optimize the lumbar fixation device. The FE model generated above produced the same pressure value on intervertebral disc and dynamic behavior as the normal intact model reported in the literature. The consistent results from this comparison validates the accuracy in the modeling of the current FE model. Currently, we are trying to generate an abnormal model with defects in one or more components of the normal FE model above. Then, the mechanical integrity and the dynamic stability of the designed lumbar fixation device will be analyzed after being installed in the abnormal model and then the lumbar fixation device will be further optimized.

Keywords: lumbar interspinous process fixation device, finite element method, lumbar spine, kinematics

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Authors: Walid Moudani

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The Crew Reserve Assignment Problem (CRAP) considers the assignment of the crew members to a set of reserve activities covering all the scheduled flights in order to ensure a continuous plan so that operations costs are minimized while its solution must meet hard constraints resulting from the safety regulations of Civil Aviation as well as from the airlines internal agreements. The problem considered in this study is of highest interest for airlines and may have important consequences on the service quality and on the economic return of the operations. In this communication, a new mathematical formulation for the CRAP is proposed which takes into account the regulations and the internal agreements. While current solutions make use of Artificial Intelligence techniques run on main frame computers, a low cost approach is proposed to provide on-line efficient solutions to face perturbed operating conditions. The proposed solution method uses a dynamic programming approach for the duties scheduling problem and when applied to the case of a medium airline while providing efficient solutions, shows good potential acceptability by the operations staff. This optimization scheme can then be considered as the core of an on-line Decision Support System for crew reserve assignment operations management.

Keywords: airlines operations management, combinatorial optimization, dynamic programming, crew scheduling

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Authors: Bruk Gebregziabher

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The safe and efficient operation of Autonomous Mobile Robots (AMRs) in complex environments, such as manufacturing, logistics, and agriculture, necessitates accurate multiobject tracking and predictive collision avoidance. This paper presents algorithms and techniques for addressing these challenges using Lidar sensor data, emphasizing ensemble Kalman filter. The developed predictive collision avoidance algorithm employs the data provided by lidar sensors to track multiple objects and predict their velocities and future positions, enabling the AMR to navigate safely and effectively. A modification to the dynamic windowing approach is introduced to enhance the performance of the collision avoidance system. The overall system architecture encompasses object detection, multi-object tracking, and predictive collision avoidance control. The experimental results, obtained from both simulation and real-world data, demonstrate the effectiveness of the proposed methods in various scenarios, which lays the foundation for future research on global planners, other controllers, and the integration of additional sensors. This thesis contributes to the ongoing development of safe and efficient autonomous systems in complex and dynamic environments.

Keywords: autonomous mobile robots, multi-object tracking, predictive collision avoidance, ensemble Kalman filter, lidar sensors

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Authors: Ruchi Makani, B. V. R. Reddy

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Mobile Adhoc Networks (MANETs) are gaining popularity due to their potential of providing low-cost mobile connectivity solutions to real-world communication problems. Integrating Intrusion Detection Systems (IDS) in MANETs is a tedious task by reason of its distinctive features such as dynamic topology, de-centralized authority and highly controlled/limited resource environment. IDS primarily use automated soft-computing techniques to monitor the inflow/outflow of traffic packets in a given network to detect intrusion. Use of machine learning techniques in IDS enables system to make decisions on intrusion while continuous keep learning about their dynamic environment. An appropriate IDS model is essential to be selected to expedite this application challenges. Thus, this paper focused on fuzzy-logic based machine learning IDS technique for MANETs and presented their applicability for achieving effectiveness in identifying the intrusions. Further, the selection of appropriate protocol attributes and fuzzy rules generation plays significant role for accuracy of the fuzzy-logic based IDS, have been discussed. This paper also presents the critical attributes of MANET’s routing protocol and its applicability in fuzzy logic based IDS.

Keywords: AODV, mobile adhoc networks, intrusion detection, anomaly detection, fuzzy logic, fuzzy membership function, fuzzy inference system

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Authors: Pierre Tize Mha, Mohammad Jahazi, Amèvi Togne, Olivier Pantalé

Abstract:

Large-size forged blocks made of medium carbon high-strength steels are extensively used in the automotive industry as dies for the production of bumpers and dashboards through the plastic injection process. The manufacturing process of the large blocks starts with ingot casting, followed by open die forging and a quench and temper heat treatment process to achieve the desired mechanical properties and numerical simulation is widely used nowadays to predict these properties before the experiment. But the temperature gradient inside the specimen remains challenging in the sense that the temperature before loading inside the material is not the same, but during the simulation, constant temperature is used to simulate the experiment because it is assumed that temperature is homogenized after some holding time. Therefore to be close to the experiment, real distribution of the temperature through the specimen is needed before the mechanical loading. Thus, We present here a robust algorithm that allows the calculation of the temperature gradient within the specimen, thus representing a real temperature distribution within the specimen before deformation. Indeed, most numerical simulations consider a uniform temperature gradient which is not really the case because the surface and core temperatures of the specimen are not identical. Another feature that influences the mechanical properties of the specimen is recrystallization which strongly depends on the deformation conditions and the type of deformation like Upsetting, Cogging...etc. Indeed, Upsetting and Cogging are the stages where the greatest deformations are observed, and a lot of microstructural phenomena can be observed, like recrystallization, which requires in-depth characterization. Complete dynamic recrystallization plays an important role in the final grain size during the process and therefore helps to increase the mechanical properties of the final product. Thus, the identification of the conditions for the initiation of dynamic recrystallization is still relevant. Also, the temperature distribution within the sample and strain rate influence the recrystallization initiation. So the development of a technique allowing to predict the initiation of this recrystallization remains challenging. In this perspective, we propose here, in addition to the algorithm allowing to get the temperature distribution before the loading stage, an analytical model leading to determine the initiation of this recrystallization. These two techniques are implemented into the Abaqus finite element software via the UAMP and VUHARD subroutines for comparison with a simulation where an isothermal temperature is imposed. The Artificial Neural Network (ANN) model to describe the plastic behavior of the material is also implemented via the VUHARD subroutine. From the simulation, the temperature distribution inside the material and recrystallization initiation is properly predicted and compared to the literature models.

Keywords: dynamic recrystallization, finite element modeling, artificial neural network, numerical implementation

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Authors: Muhammad Bilal Mustafa, Javed Hussain, Simeon Babatunde

Abstract:

The Covid-19 pandemic has exposed the vulnerabilities of countless organisations beyond their size, type, and location. However, some groups and sectors are disproportionally get impacted by the pandemic. In the context of the UK, ethnic Small and Medium Enterprises (SMEs) turn out to be the most precarious group among all private sectors. Many ethnic SMEs shut down their business operations during a pandemic. A large portion of Black, Asian and minority ethnic (BAME) owners have huge concerns regarding their business’ survival and resilience. The current UK-centric studies have focused on the large business population, and there is a gap in ethnic SMEs and how they get affected by the Covid-19 pandemic. Moreover, there is a need to further knowledge and academic research to investigate the fundamental factors that could strengthen the resilience of ethnic SMEs as well as contribute to long-term sustainability. Therefore, this study aims to capture the effect of the Covid-19 pandemic on ethnic SMEs in the UK and assess the survival measures taken by ethnic SMEs during Covid-19. Besides, this study adopts a dynamic capabilities perspective that how firms' specific capabilities enable ethnic SMEs to exploit entrepreneurial opportunities during the Covid-19 pandemic. Finally, this research will help ethnic SMEs to develop vigorous resilience to address future external shocks and market uncertainties.

Keywords: COVID-19 pandemic, ethnic minority SMEs, entrepreneurial resilience, dynamic capabilities, sustainability

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Authors: Shahrokh Barati

Abstract:

In this paper, we introduced AIDS disease at first, then proposed dynamic model illustrate its progress, after expression of a short history of nonlinear modeling by polynomial phasing systems, we considered the stability conditions of the systems, which contained a huge amount of researches in order to modeling and control of AIDS in dynamic nonlinear form, in this approach using a frame work of control any polynomial phasing modeling system which have been generalized by part of phasing model of T-S, in order to control the system in better way, the stability conditions were achieved based on polynomial functions, then we focused to design the appropriate controller, firstly we considered the equilibrium points of system and their conditions and in order to examine changes in the parameters, we presented polynomial phase model that was the generalized approach rather than previous Takagi Sugeno models, then with using case we evaluated the equations in both open loop and close loop and with helping the controlling feedback, the close loop equations of system were calculated, to simulate nonlinear model of AIDS disease, we used polynomial phasing controller output that was capable to make the parameters of a nonlinear system to follow a sustainable reference model properly.

Keywords: polynomial fuzzy, AIDS, nonlinear AIDS model, fuzzy control systems

Procedia PDF Downloads 468

Authors: E. Ghasemi Ardi, K. J. Dong, A. B. Yu, R. Y. Yang

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In current work, a numerical model based on the discrete element method (DEM) was developed which provided information about particle dynamic and impact event condition inside a laboratory scale impact mill (Fritsch). It showed that each particle mostly experiences three impacts inside the mill. While the first impact frequently happens at front surface of the rotor’s rib, the frequent location of the second impact is side surfaces of the rotor’s rib. It was also showed that while the first impact happens at small impact angle mostly varying around 35º, the second impact happens at around 70º which is close to normal impact condition. Also analyzing impact energy revealed that varying mill speed from 6000 to 14000 rpm, the ratio of first impact’s average impact energy and minimum required energy to break particle (Wₘᵢₙ) increased from 0.30 to 0.85. Moreover, it was seen that second impact poses intense impact energy on particle which can be considered as the main cause of particle splitting. Finally, obtained information from DEM simulation along with obtained data from conducted experiments was implemented in semi-empirical equations in order to find selection and breakage functions. Then, using a back-calculation approach, those parameters were used to predict the PSDs of ground particles under different impact energies. Results were compared with experiment results and showed reasonable accuracy and prediction ability.

Keywords: single particle breakage, particle dynamic, population balance model, particle size distribution, discrete element method

Procedia PDF Downloads 291

Authors: Supriya Mahida, Sangita, Yogesh U. Shah, Shanta Kumar

Abstract:

The global production of thermocol increasing day by day, due to vast applications of the use of thermocole in many sectors. Thermocol being non-biodegradable and more toxic than plastic leads towards a number of problems like its management into value-added products, environmental damage and landfill problems due to weight to volume ratio. Utilization of waste thermocol for modification of bitumen binders resulted in waste thermocol modified bitumen (WTMB) used in road construction and maintenance technology. Modification of bituminous mixes through incorporating thermocol into bituminous mixes through a dry process is one of the new options besides recycling process which consumes lots of waste thermocol. This process leads towards waste management and remedies against thermocol waste disposal. The present challenge is to dispose the thermocol waste under different forms in road infrastructure, either through the dry process or wet process to be developed in future. This paper focuses on the use of thermocol wastes which is mixed with VG 10 bitumen in proportions of 0.5%, 1%, 1.5%, and 2% by weight of bitumen. The physical properties of neat bitumen are evaluated and compared with modified VG 10 bitumen having thermocol. Empirical characterization like penetration, softening, and viscosity of bitumen has been carried out. Thermocol and waste thermocol modified bitumen (WTMB) were further analyzed by Fourier Transform Infrared Spectroscopy (FT-IR), field emission scanning electron microscopy (FESEM), and Dynamic Shear Rheometer (DSR).

Keywords: DSR, FESEM, FT-IR, thermocol wastes

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Authors: Majid Habib Khan, Jinwei Zhao, Xinhong Hei, Liu Jiedong, Rana Shahzad Noor, Muhammad Imran

Abstract:

Deep learning is increasingly employed in image classification, yet the scarcity and high cost of labeled data for training remain a challenge. Limited samples often lead to overfitting due to biased sample distribution. This paper introduces a dynamic distribution calibration method for few-shot learning. Initially, base and new class samples undergo normalization to mitigate disparate feature magnitudes. A pre-trained model then extracts feature vectors from both classes. The method dynamically selects distribution characteristics from base classes (both adjacent and remote) in the embedding space, using a threshold value approach for new class samples. Given the propensity of similar classes to share feature distributions like mean and variance, this research assumes a Gaussian distribution for feature vectors. Subsequently, distributional features of new class samples are calibrated using a corrected hyperparameter, derived from the distribution features of both adjacent and distant base classes. This calibration augments the new class sample set. The technique demonstrates significant improvements, with up to 4% accuracy gains in few-shot classification challenges, as evidenced by tests on miniImagenet and CUB datasets.

Keywords: deep learning, computer vision, image classification, few-shot learning, threshold

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Authors: N. Balamurugan, N. V. Mahalakshmi

Abstract:

Compression ignition (CI) engines are known for their high thermal efficiency in comparison with spark-ignited (SI) engines. This makes CI engines a potential candidate for the future prime source of power for transportation sector to reduce greenhouse gas emissions and to shrink carbon footprint. However, CI engines produce high levels of NOx and soot emissions. Conventional methods to reduce NOx and soot emissions often result in the infamous NOx-soot trade-off. The injection parameters are one of the most important factors in the working of CI engines. The engine performance, power output, economy etc., is greatly dependent on the effectiveness of the injection parameters. The injection parameter has their direct impact on combustion process and pollutant formation. The injection parameter’s values are required to be optimised according to the application of the engine. Control of fuel injection mode is one method for reduction of NOx and soot emissions that is achievable. This study aims to assess, compare and analyse the influence of the effect of injection characteristics that is SOI timing studied on combustion and emissions in in-cylinder combustion processes with that of conventional DI Diesel Engine system using the commercial Computational Fluid Dynamic (CFD) package STAR- CD ES-ICE.

Keywords: variation of injection timing, compression ignition engine, spark-ignited, Computational Fluid Dynamic

Procedia PDF Downloads 295

Authors: Palash Dey, Sudip Talukdar

Abstract:

In this work, a cross-breed approach is presented for obtaining both the amount of the damage intensity and location of damage existing in thin-walled members. This cross-breed approach is developed based on response surface methodology (RSM) and genetic algorithm (GA). Theoretical finite element (FE) model of cracked angle section thin walled curved beam has been linked to the developed approach to carry out trial experiments to generate response surface functions (RSFs) of free, forced and heterogeneous dynamic response data. Subsequently, the error between the computed response surface functions and measured dynamic response data has been minimized using GA to find out the optimum damage parameters (amount of the damage intensity and location). A single crack of varying location and depth has been considered in this study. The presented approach has been found to reveal good accuracy in prediction of crack parameters and possess great potential in crack detection as it requires only the current response of a cracked beam.

Keywords: damage parameters, finite element, genetic algorithm, response surface methodology, thin walled curved beam

Procedia PDF Downloads 248