Search results for: structural topology optimization

Authors: V. Nagammai

Abstract:

Very-large-scale integration (VLSI) is the process of creating an integrated circuit (IC) by combining thousands of transistors into a single chip. Development of technology increases the complexity in IC manufacturing which may vary the power consumption, increase the size and latency period. Topology defines a number of connections between network. In this project, NoC topology is generated using atlas tool which will increase performance in turn determination of constraints are effective. The routing is performed by XY routing algorithm and wormhole flow control. In NoC topology generation, the value of power, area and latency are predetermined. In previous work, placement, routing and shortest path evaluation is performed using an algorithm called floor planning with cluster reconstruction and path allocation algorithm (FCRPA) with the account of 4 3x3 switch, 6 4x4 switch, and 2 5x5 switches. The usage of the 4x4 and 5x5 switch will increase the power consumption and area of the block. In order to avoid the problem, this paper has used one 8x8 switch and 4 3x3 switches. This paper uses IPRCA which of 3 steps they are placement, clustering, and shortest path evaluation. The placement is performed using min – cut placement and clustering are performed using an algorithm called cluster generation. The shortest path is evaluated using an algorithm called Dijkstra's algorithm. The power consumption of each block is determined. The experimental result shows that the area, power, and wire length improved simultaneously.

Keywords: application specific noc, b* tree representation, floor planning, t tree representation

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Authors: Olusola Bamisile, Oluwaseun Ayodele, Mustafa Dagbasi

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The main objective of this research is to optimize the power produced by a solar chimney wind turbine. The cut out speed and the maximum possible production are considered while performing the optimization. Solar chimney is one of the solar technologies that can be used in rural areas at cheap cost. With over 50% of rural areas still yet to have access to electricity. The OptimTool in MATLAB is used to maximize power produced by the turbine subject to certain constraints. The results show that an optimized turbine produces about ten times the power of the normal turbine which is 111 W/h. The rest of the research discuss in detail solar chimney power plant and the optimization simulation used in this study.

Keywords: solar chimney, optimization, wind turbine, renewable energy systems

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Authors: Sello Mokwena, Monyepao Thabang

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In this study, we propose a comprehensive approach to address the challenges in person re-identification models. By combining a centroid tracking algorithm with a Siamese convolutional neural network model, our method excels in detecting, tracking, and capturing robust person features across non-overlapping camera views. The algorithm efficiently identifies individuals in the camera network, while the neural network extracts fine-grained global features for precise cross-image comparisons. The approach's effectiveness is further accentuated by leveraging the camera network topology for guidance. Our empirical analysis on benchmark datasets highlights its competitive performance, particularly evident when background subtraction techniques are selectively applied, underscoring its potential in advancing person re-identification techniques.

Keywords: camera network, convolutional neural network topology, person tracking, person re-identification, siamese

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Authors: Tofigh Hamidavi, Sepehr Abrishami, Pasquale Ponterosso, David Begg

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Structural design and analysis is an important and time-consuming process, particularly at the conceptual design stage. Decisions made at this stage can have an enormous effect on the entire project, as it becomes ever costlier and more difficult to alter the choices made early on in the construction process. Hence, optimisation of the early stages of structural design can provide important efficiencies in terms of cost and time. This paper suggests a structural design optimisation (SDO) framework in which Genetic Algorithms (GAs) may be used to semi-automate the production and optimisation of early structural design alternatives. This framework has the potential to leverage conceptual structural design innovation in Architecture, Engineering and Construction (AEC) projects. Moreover, this framework improves the collaboration between the architectural stage and the structural stage. It will be shown that this SDO framework can make this achievable by generating the structural model based on the extracted data from the architectural model. At the moment, the proposed SDO framework is in the process of validation, involving the distribution of an online questionnaire among structural engineers in the UK.

Keywords: building information, modelling, BIM, genetic algorithm, GA, architecture-engineering-construction, AEC, optimisation, structure, design, population, generation, selection, mutation, crossover, offspring

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Authors: Seyed Abbas Tabatabaei, Marjan Naderan Tahan, Arman Kadkhodai

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An efficient optimization approach, called feasible gate (FG), is developed to enhance the computation efficiency and solution quality of the previously developed highway alignment optimization (HAO) model. This approach seeks to realistically represent various user preferences and environmentally sensitive areas and consider them along with geometric design constraints in the optimization process. This is done by avoiding the generation of infeasible solutions that violate various constraints and thus focusing the search on the feasible solutions. The proposed method is simple, but improves significantly the model’s computation time and solution quality. On the other, highway alignment optimization through Feasible Gates, eventuates only economic model by considering minimum design constrains includes minimum reduce of circular curves, minimum length of vertical curves and road maximum gradient. This modelling can reduce passenger comfort and road safety. In most of highway optimization models, by adding penalty function for each constraint, final result handles to satisfy minimum constraint. In this paper, we want to propose a safety-function solution by introducing gift function.

Keywords: safety, highway geometry, optimization, alignment

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Authors: Farideh Halakou, Emel Sen, Attila Gursoy, Ozlem Keskin

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Protein–Protein Interactions (PPIs) mediate major biological processes in living cells. The study of PPIs as networks and analyze the network properties contribute to the identification of genes and proteins associated with diseases. In this study, we have created the sub-networks of brain and lung metastasis from primary tumor in breast cancer. To do so, we used seed genes known to cause metastasis, and produced their interactions through a network-topology based prioritization method named GUILDify. In order to have the experimental support for the sub-networks, we further curated them using STRING database. We proceeded by modeling structures for the interactions lacking complex forms in Protein Data Bank (PDB). The functional enrichment analysis shows that KEGG pathways associated with the immune system and infectious diseases, particularly the chemokine signaling pathway, are important for lung metastasis. On the other hand, pathways related to genetic information processing are more involved in brain metastasis. The structural analyses of the sub-networks vividly demonstrated their difference in terms of using specific interfaces in lung and brain metastasis. Furthermore, the topological analysis identified genes such as RPL5, MMP2, CCR5 and DPP4, which are already known to be associated with lung or brain metastasis. Additionally, we found 6 and 9 putative genes that are specific for lung and brain metastasis, respectively. Our analysis suggests that variations in genes and pathways contributing to these different breast metastasis types may arise due to change in tissue microenvironment. To show the benefits of using structural PPI networks instead of traditional node and edge presentation, we inspect two case studies showing the mutual exclusiveness of interactions and effects of mutations on protein conformation which lead to different signaling.

Keywords: breast cancer, metastasis, PPI networks, protein conformational changes

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Authors: A. Sreedevi, G. Anantaramu

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The present space research organizations are striving towards the development of lighter, smaller, more efficient, low cost, and highly reliable power supply. Switch mode power supplies (SMPS) overcome the demerits of linear power supplies such as low efficiency, difficulties in thermal management, and in boosting the output voltage. Space applications require a constant DC voltage to supply its load. As the load varies, the battery terminal voltage tends to vary accordingly. To avoid this variation in the load terminal voltage, a DC-DC regulator is required. The conventional regulator for space applications is isolated boost topology. The proposed topology uses an interleaved push-pull converter with a current doubler secondary to reduce the EMI issues and increase efficiency. The proposed topology uses a floating technique where the converter derives power from the battery and generates only the voltage that is required to fill the gap between the bus and the battery voltage. The direct voltage sense and current loop provide tight regulation of output and better stability. Converter is designed with 50 kHz switching frequency using UC 1825 PWM controller employing both voltage and peak current mode control. Experimental tests have been carried out on the converter under different input and load conditions to validate the design. The experimental results showed that the efficiency was greater than 91%. Stability analysis is done using venable stability analyzer.

Keywords: push pull converter, current doubler, converter, PWM control

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Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

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Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning

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Authors: Badr M. Alshammari, T. Guesmi

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In this paper, the concept of a non-dominated sorting multi-objective particle swarm optimization with local search (NSPSO-LS) is presented for the optimal design of multimachine power system stabilizers (PSSs). The controller design is formulated as an optimization problem in order to shift the system electromechanical modes in a pre-specified region in the s-plan. A composite set of objective functions comprising the damping factor and the damping ratio of the undamped and lightly damped electromechanical modes is considered. The performance of the proposed optimization algorithm is verified for the 3-machine 9-bus system. Simulation results based on eigenvalue analysis and nonlinear time-domain simulation show the potential and superiority of the NSPSO-LS algorithm in tuning PSSs over a wide range of loading conditions and large disturbance compared to the classic PSO technique and genetic algorithms.

Keywords: multi-objective optimization, particle swarm optimization, power system stabilizer, low frequency oscillations

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Authors: Gagandeep Singh

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The sensor field optimization is a serious issue in WSNs and has been ignored by many researchers. As in numerous real-time sensing fields the sensor nodes on the corners i.e. on the segment boundaries will become lifeless early because no extraordinary safety is presented for them. Accordingly, in this research work the central objective is on the segment based optimization by separating the sensor field between advance and normal segments. The inspiration at the back this sensor field optimization is to extend the time spam when the first sensor node dies. For the reason that in normal sensor nodes which were exist on the borders may become lifeless early because the space among them and the base station is more so they consume more power so at last will become lifeless soon.

Keywords: WSNs, ECRSEP, SEP, field optimization, energy

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Authors: Nadir Atayev, Mehman Hasanov

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Future spacecraft will require a structural change in the way data is transmitted due to the increase in the volume of data required for space communication. Current radio frequency communication systems are already facing a bottleneck in the volume of data sent to the ground segment due to their technological and regulatory characteristics. To overcome these issues, free space optics communication plays an important role in the integrated terrestrial space network due to its advantages such as significantly improved data rate compared to traditional RF technology, low cost, improved security, and inter-satellite free space communication, as well as uses a laser beam, which is an optical signal carrier to establish satellite-ground & ground-to-satellite links. In this approach, there is a need for high-speed and energy-efficient systems as a base platform for sending high-volume video & audio data. Nano Satellite and its branch CubeSat platforms have more technical functionality than large satellites, wheres cover an important part of the space sector, with their Low-Earth-Orbit application area with low-cost design and technical functionality for building networks using different communication topologies. Along the research theme developed in this regard, the output parameter indicators for the FSO of the optical communication transceiver subsystem on the existing CubeSat platforms, and in the direction of improving the mentioned parameters of this communication methodology, 3D optical switch and laser beam controlled optical transponder with 2U CubeSat structural subsystems and application in the Low Earth Orbit satellite network topology, as well as its functional performance and structural parameters, has been studied accordingly.

Keywords: cubesat, free space optics, nano satellite, optical laser communication.

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Authors: A. Sohouli, A. Suleman

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This study focuses on reliability analysis of variable stiffness composite laminate structures to investigate the potential structural improvement compared to conventional (straight fibers) composite laminate structures. A computational framework was developed which it consists of a deterministic design step and reliability analysis. The optimization part is Discrete Material Optimization (DMO) and the reliability of the structure is computed by Monte Carlo Simulation (MCS) after using Stochastic Response Surface Method (SRSM). The design driver in deterministic optimization is the maximum stiffness, while optimization method concerns certain manufacturing constraints to attain industrial relevance. These manufacturing constraints are the change of orientation between adjacent patches cannot be too large and the maximum number of successive plies of a particular fiber orientation should not be too high. Variable stiffness composites may be manufactured by Automated Fiber Machines (AFP) which provides consistent quality with good production rates. However, laps and gaps are the most important challenges to steer fibers that effect on the performance of the structures. In this study, the optimal curved fiber paths at each layer of composites are designed in the first step by DMO, and then the reliability analysis is applied to investigate the sensitivity of the structure with different standard deviations compared to the straight fiber angle composites. The random variables are material properties and loads on the structures. The results show that the variable stiffness composite laminate structures are much more reliable, even for high standard deviation of material properties, than the conventional composite laminate structures. The reason is that the variable stiffness composite laminates allow tailoring stiffness and provide the possibility of adjusting stress and strain distribution favorably in the structures.

Keywords: material optimization, Monte Carlo simulation, reliability analysis, response surface method, variable stiffness composite structures

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Authors: Beema Akbar, Varun P. Gopi, V. Suresh Babu

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Colon cancer causes the deaths of about half a million people every year. The common method of its detection is histopathological tissue analysis, it leads to tiredness and workload to the pathologist. A novel method is proposed that combines both structural and statistical pattern recognition used for the detection of colon cancer. This paper presents a comparison among the different classifiers such as Multilayer Perception (MLP), Sequential Minimal Optimization (SMO), Bayesian Logistic Regression (BLR) and k-star by using classification accuracy and error rate based on the percentage split method. The result shows that the best algorithm in WEKA is MLP classifier with an accuracy of 83.333% and kappa statistics is 0.625. The MLP classifier which has a lower error rate, will be preferred as more powerful classification capability.

Keywords: colon cancer, histopathological image, structural and statistical pattern recognition, multilayer perception

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Authors: Nwachukwu Ifeanyi

Abstract:

Wind energy is a vital component of the global renewable energy portfolio, with wind turbines serving as the primary means of harnessing this abundant resource. However, the efficiency and stability of wind turbines remain critical challenges in maximizing energy output and ensuring long-term operational viability. This study proposes a comprehensive approach utilizing computational aerodynamics and aeromechanics to optimize wind turbine performance across multiple objectives. The proposed research aims to integrate advanced computational fluid dynamics (CFD) simulations with structural analysis techniques to enhance the aerodynamic efficiency and mechanical stability of wind turbine blades. By leveraging multi-objective optimization algorithms, the study seeks to simultaneously optimize aerodynamic performance metrics such as lift-to-drag ratio and power coefficient while ensuring structural integrity and minimizing fatigue loads on the turbine components. Furthermore, the investigation will explore the influence of various design parameters, including blade geometry, airfoil profiles, and turbine operating conditions, on the overall performance and stability of wind turbines. Through detailed parametric studies and sensitivity analyses, valuable insights into the complex interplay between aerodynamics and structural dynamics will be gained, facilitating the development of next-generation wind turbine designs. Ultimately, this research endeavours to contribute to the advancement of sustainable energy technologies by providing innovative solutions to enhance the efficiency, reliability, and economic viability of wind power generation systems. The findings have the potential to inform the design and optimization of wind turbines, leading to increased energy output, reduced maintenance costs, and greater environmental benefits in the transition towards a cleaner and more sustainable energy future.

Keywords: computation, robotics, mathematics, simulation

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Authors: H. Ghodbane, A. A. Taleb, O. Kraa

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This paper presents geometric design of induction heating system. The objective of this design is to improve the temperature distribution in the load. The study of such a device requires the use of models or modeling representation, physical, mathematical, and numerical. This modeling is the basis of the understanding, the design, and optimization of these systems. The optimization technique is to find values of variables that maximize or minimize the objective function.

Keywords: optimization, modeling, geometric design system, temperature increase

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Authors: Abiodun Ladanu Ajala, Wuyi Oke

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Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

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Authors: Mohammed El Raey, Moustafa Osman Mohammed

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The spatial-ecological modeling is relating sustainable dispersions with social development. Sustainability with spatial-ecological model gives attention to urban environments in the design review management to comply with Earth’s System. Naturally exchange patterns of ecosystems have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. The probabilistic risk assessment (PRA) technique is utilized to assess the safety of industrial complex. The other analytical approach is the Failure-Safe Mode and Effect Analysis (FMEA) for critical components. The plant safety parameters are identified for engineering topology as employed in assessment safety of industrial ecology. In particular, the most severe accidental release of hazardous gaseous is postulated, analyzed and assessment in industrial region. The IAEA- safety assessment procedure is used to account the duration and rate of discharge of liquid chlorine. The ecological model of plume dispersion width and concentration of chlorine gas in the downwind direction is determined using Gaussian Plume Model in urban and ruler areas and presented with SURFER®. The prediction of accident consequences is traced in risk contour concentration lines. The local greenhouse effect is predicted with relevant conclusions. The spatial-ecological model is also predicted the distribution schemes from the perspective of pollutants that considered multiple factors of multi-criteria analysis. The data extends input–output analysis to evaluate the spillover effect, and conducted Monte Carlo simulations and sensitivity analysis. Their unique structure is balanced within “equilibrium patterns”, such as the biosphere and collective a composite index of many distributed feedback flows. These dynamic structures are related to have their physical and chemical properties and enable a gradual and prolonged incremental pattern. While this spatial model structure argues from ecology, resource savings, static load design, financial and other pragmatic reasons, the outcomes are not decisive in artistic/ architectural perspective. The hypothesis is an attempt to unify analytic and analogical spatial structure for development urban environments using optimization software and applied as an example of integrated industrial structure where the process is based on engineering topology as optimization approach of systems ecology.

Keywords: spatial-ecological modeling, spatial structure orientation impact, composite structure, industrial ecology

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Authors: Víctor Cecilio, Roberto Gómez, J. Alberto Escobar, Héctor Guerrero

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The study of the structural behavior of a support/pier of an elevated viaduct in Mexico City is presented. Detection of foundation piles with uncertain integrity prompted the review of possible situations that could jeopardy the structural safety of the pier. The objective of this paper is to evaluate the structural conditions of the support, taking into account the type of anomaly reported and the depth at which it is located, the position of the pile with uncertain integrity in the foundation system, the stratigraphy of the surrounding soil and the geometry and structural characteristics of the pier. To carry out the above, dynamic analysis, spectral modal, and step-by-step, with elastic and inelastic material models, were performed. Results were evaluated in accordance with the standards used for the design of the original structural project and with the Construction Regulations for Mexico’s Federal District (RCDF-2017, 2017). Comments on the response of the analyzed models are issued, and the conclusions are presented from a structural point of view.

Keywords: dynamic analysis, inelastic models, dubious foundation, bridge pier

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Authors: Pulak Swain, A. K. Ojha

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Portfolio optimization is based on dealing with the problems of efficient asset allocation. Risk and Expected return are two conflicting criteria in such problems, where the investor prefers the return to be high and the risk to be low. Using multi-objective approach we can solve those type of problems. However the information which we have for the input parameters are generally ambiguous and the input values can fluctuate around some nominal values. We can not ignore the uncertainty in input values, as they can affect the asset allocation drastically. So we use Robust Optimization approach to the problems where the input parameters comes under box uncertainty. In this paper, we solve the multi criteria robust problem with the help of  E- constraint method.

Keywords: portfolio optimization, multi-objective optimization, ϵ - constraint method, box uncertainty, robust optimization

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Authors: Susanta Kumar Gachhayat, S. K. Dash

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Multi objective non-convex economic dispatch problems of a thermal power plant are of grave concern for deciding the cost of generation and reduction of emission level for diminishing the global warming level for improving green-house effect. This paper deals with ramp rate constraints for achieving better inequality constraints so as to incorporate valve point loading for cost of generation in thermal power plant through ramp rate biogeography based optimization involving mutation and migration. Through 50 out of 100 trials, the cost function and emission objective function were found to have outperformed other classical methods such as lambda iteration method, quadratic programming method and many heuristic methods like particle swarm optimization method, weight improved particle swarm optimization method, constriction factor based particle swarm optimization method, moderate random particle swarm optimization method etc. Ramp rate biogeography based optimization applications prove quite advantageous in solving non convex multi objective economic dispatch problems subjected to nonlinear loads that pollute the source giving rise to third harmonic distortions and other such disturbances.

Keywords: economic load dispatch, ELD, biogeography-based optimization, BBO, ramp rate biogeography-based optimization, RRBBO, valve-point loading, VPL

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Authors: Thomas Odaker, Dieter Kranzlmueller, Jens Volkert

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We present an approach to triangle mesh simplification designed to be executed on the GPU. We use a quadric error metric to calculate an error value for each vertex of the mesh and order all vertices based on this value. This step is followed by the parallel removal of a number of vertices with the lowest calculated error values. To allow for the parallel removal of multiple vertices we use a set of per-vertex boundaries that prevent mesh foldovers even when simplification operations are performed on neighbouring vertices. We execute multiple iterations of the calculation of the vertex errors, ordering of the error values and removal of vertices until either a desired number of vertices remains in the mesh or a minimum error value is reached. This parallel approach is used to speed up the simplification process while maintaining mesh topology and avoiding foldovers at every step of the simplification.

Keywords: computer graphics, half edge collapse, mesh simplification, precomputed simplification, topology preserving

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Authors: Devin Atkin, Orly Yadid-Pecht

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The continual demands for increasing resolution and dynamic range in CMOS image sensors have resulted in exponential increases in the amount of data that needs to be read out of an image sensor, and existing readouts cannot keep up with this demand. Interesting approaches such as sparse and burst readouts have been proposed and show promise, but at considerable trade-offs in other specifications. To this end, we have begun designing and evaluating various new readout topologies centered around an attempt to parallelize the sensor readout. In this paper, we have designed, simulated, and started testing a new light-controlled oscillator topology with dual column and row readouts. We expect the parallel readout structure to offer greater speed and alleviate the trade-off typical in this topology, where slow pixels present a major framerate bottleneck.

Keywords: CMOS image sensors, high-speed capture, wide dynamic range, light controlled oscillator

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Authors: Jae Moon Im, Kwang Bok Shin, Sang Woo Lee

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In this paper, evaluation of structural integrity for composite lattice structure was conducted by compressive test. Composite lattice structure was manufactured by carbon fiber using filament winding method. In order to evaluate the structural integrity of composite lattice structure, compressive test was done using anti-buckling fixture. The delamination occurred 84 Tons of compressive load. It was found that composite lattice structure satisfied the design requirements.

Keywords: composite material, compressive test, lattice structure, structural integrity

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Authors: Bhrugesh Radadiya, Jaydeep Shah

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In Indian foundry industry, there is a need of defect free casting with minimum production cost in short lead time. Casting defect is a very large issue in foundry shop which increases the rejection rate of casting and wastage of materials. The various parameters influences on casting process such as mold machine related parameters, green sand related parameters, cast metal related parameters, mold related parameters and shake out related parameters. The mold related parameters are most influences on casting defects in sand casting process. This paper review the casting produced by foundry with shrinkage and blow holes as a major defects was analyzed and identified that mold related parameters such as mold temperature, pouring temperature and runner size were not properly set in sand casting process. These parameters were optimized using different optimization techniques such as Taguchi method, Response surface methodology, Genetic algorithm and Teaching-learning based optimization algorithm. Finally, concluded that a Teaching-learning based optimization algorithm give better result than other optimization techniques.

Keywords: casting defects, genetic algorithm, parametric optimization, Taguchi method, TLBO algorithm

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Authors: Natalya G. Filimonova, Mariya G. Ozerova, Irina N. Ermakova

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The long-term strategy of the economic development of Russia up to 2030 is based on the concept of sustainable growth. The determining factor of such development is complex changes in the economic system which may be achieved by making progressive changes in its structure. The structural changes determine the character and the direction of economic development, as well as they include all elements of this system without exception, and their regulated character ensures the most rapid aim achievement. This article has discussed the industrial structure of the agriculture in Russia. With the use of the system of indexes, the article has determined the directions, intensity, and speed of structural shifts. The influence of structural changes on agricultural production development has been found out. It is noticed that the changes in the industrial structure are synchronized with the changes in the organisation and economic structure. Efficiency assessment of structural changes allowed to trace the efficiency of structural changes and elaborate the main directions for agricultural policy improvement.

Keywords: Russian agricultural sectors, sectoral structure, organizational and economic structure, structural changes

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Authors: I. Brandys, M. Levy, K. Harush, Y. Haim, M. Korngold

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Theoretical optimization of a copper-water negative inclination heat pipe with internal composite wick structure has been performed, regarding a new introduced parameter: the ratio between the coarse mesh wraps and the fine mesh wraps of the composite wick. Since in many cases, the design of a heat pipe matches specific thermal requirements and physical limitations, this work demonstrates the optimization of a 1 m length, 8 mm internal diameter heat pipe without an adiabatic section, at a negative inclination angle of -10º. The optimization is based on a new introduced parameter, LR: the ratio between the coarse mesh wraps and the fine mesh wraps.

Keywords: heat pipe, inclination, optimization, ratio

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm

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Authors: Neda Nabid

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Friction-based supplemental devices have been extensively used for seismic protection and strengthening of structures, however, the conventional use of these dampers may not necessarily lead to an efficient structural performance. Conventionally designed friction dampers follow a uniform height-wise distribution pattern of slip load values for more practical simplicity. This can lead to localizing structural damage in certain story levels, while the other stories accommodate a negligible amount of relative displacement demand. A practical performance-based optimization methodology is developed to tackle with structural damage localization of RC frame buildings with friction energy dissipation devices under severe earthquakes. The proposed methodology is based on the concept of uniform damage distribution theory. According to this theory, the slip load values of the friction dampers redistribute and shift from stories with lower relative displacement demand to the stories with higher inter-story drifts to narrow down the discrepancy between the structural damage levels in different stories. In this study, the efficacy of the proposed design methodology is evaluated through the seismic performance of five different low to high-rise RC frames equipped with friction wall dampers under six real spectrum-compatible design earthquakes. The results indicate that compared to the conventional design, using the suggested methodology to design friction wall systems can lead to, by average, up to 40% reduction of maximum inter-story drift; and incredibly more uniform height-wise distribution of relative displacement demands under the design earthquakes.

Keywords: friction damper, nonlinear dynamic analysis, RC structures, seismic performance, structural damage

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Authors: Vassilios Moussas, Dimos N. Pantazis, Panagioths Stratakis

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The aim of this paper is to present the optimization methodology developed in the frame of a Coastal Transport Information System. The system will be used for the effective design of coastal transportation lines and incorporates subsystems that implement models, tools and techniques that may support the design of improved networks. The role of the optimization and decision subsystem is to provide the user with better and optimal scenarios that will best fulfill any constrains, goals or requirements posed. The complexity of the problem and the large number of parameters and objectives involved led to the adoption of an evolutionary method (Genetic Algorithms). The problem model and the subsystem structure are presented in detail, and, its support for simulation is also discussed.

Keywords: coastal transport, modeling, optimization

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Authors: Viktor Müller, Ulman Lindenberger

Abstract:

Neurophysiological evidence suggests that the physiological states of the system are characterized by specific network structures and network topology dynamics, demonstrating a robust interplay between network topology and function. It is also evident that interpersonal action coordination or social interaction (e.g., playing music in duets or groups) requires strong intra- and interbrain synchronization resulting in a specific hyper brain network activity across two or more brains to support such coordination or interaction. Such complex hyper brain networks can be described as multiplex or multilayer networks that have a specific multidimensional or multilayer network organization characteristic for superordinate systems and their constituents. The aim of the study was to describe multilayer hyper brain networks and synchronization patterns of guitarists playing guitar in a quartet by using electroencephalography (EEG) hyper scanning (simultaneous EEG recording from multiple brains) and following time-frequency decomposition and multilayer network construction, where within-frequency coupling (WFC) represents communication within different layers, and cross-frequency coupling (CFC) depicts communication between these layers. Results indicate that communication or coupling dynamics, both within and between the layers across the brains of the guitarists, play an essential role in action coordination and are particularly enhanced during periods of high demands on musical coordination. Moreover, multilayer hyper brain network topology and dynamical structure of guitar sounds showed specific guitar-guitar, brain-brain, and guitar-brain causal associations, indicating multilevel dynamics with upward and downward causation, contributing to the superordinate system dynamics and hyper brain functioning. It is concluded that the neuronal dynamics during interpersonal interaction are brain-wide and frequency-specific with the fine-tuned balance between WFC and CFC and can best be described in terms of multilayer multi-brain networks with specific network topology and connectivity strengths. Further sophisticated research is needed to deepen our understanding of these highly interesting and complex phenomena.

Keywords: EEG hyper scanning, intra- and interbrain coupling, multilayer hyper brain networks, social interaction, within- and cross-frequency coupling

Procedia PDF Downloads 46