Search results for: agent based modelling

Authors: Muhamad Azani Yahya, Umi Nadiah Nor Ali, Mohammed Alias Yusof, Norazman Mohamad Nor, Vikneswaran Munikanan

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In construction, concrete is one of the materials that can commonly be used as for structural elements. Concrete consists of cement, sand, aggregate and water. Concrete can be added with admixture in the wet condition to suit the design purpose such as to prolong the setting time to improve workability. For strength improvement, concrete is being added with other hybrid materials to increase strength; this is because the tensile strength of concrete is very low in comparison to the compressive strength. This paper shows the usage of a waterproofing agent in concrete to enhance the tensile strength. High tensile concrete is expensive because the concrete mix needs fiber and also high cement content to be incorporated in the mix. High tensile concrete being used for structures that are being imposed by high impact dynamic load such as blast loading that hit the structure. High tensile concrete can be defined as a concrete mix design that achieved 30%-40% tensile strength compared to its compression strength. This research evaluates the usage of a waterproofing agent in a concrete mix as an element of reinforcement to enhance the tensile strength. According to the compression and tensile test, it shows that the concrete mix with a waterproofing agent enhanced the mechanical properties of the concrete. It is also show that the composite concrete with waterproofing is a high tensile concrete; this is because of the tensile is between 30% and 40% of the compression strength. This mix is economical because it can produce high tensile concrete with low cost.

Keywords: high tensile concrete, waterproofing agent, concrete, rheology

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Authors: Zin Min Htet, Tikhomirova Irina Nikolaevna, Karpenko Marina A.

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In this paper, thermal insulation materials based on sodium liquid glass with light fillers as foam glass granules with different sizes and wollastonite - M325 (U.S.A production) were studied. Effective mineral thermal insulation materials are in demand in many industries because of their incombustibility and durability. A method for the preparation of such materials based on mechanically foamed sodium liquid glass and light mineral fillers is proposed. The thermal insulation properties depend on the type, amount of filler and on the foaming factor, which is determined by the concentration of the foaming agent. The water resistance of the material is provided by using an additive to neutralize the glass and transfer it to the silica gel.

Keywords: thermal insulation material, sodium liquid glass, foam glass granules, foaming agent, hardener, thermal conductivity, apparent density, compressive strength

Procedia PDF Downloads 190

Authors: Abdelhadi Adel, Kadri Ouahab

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This paper proposes a hybrid algorithm for the integration of systematic preventive maintenance policies in hybrid flow shop scheduling to minimize makespan. We have implemented a problem-solving approach for optimizing the processing time, methods based on metaheuristics. The proposed approach is inspired by the behavior of the human body. This hybridization is between a multi-agent system and inspirations of the human body, especially genetics. The effectiveness of our approach has been demonstrated repeatedly in this paper. To solve such a complex problem, we proposed an approach which we have used advanced operators such as uniform crossover set and single point mutation. The proposed approach is applied to three preventive maintenance policies. These policies are intended to maximize the availability or to maintain a minimum level of reliability during the production chain. The results show that our algorithm outperforms existing algorithms. We assumed that the machines might be unavailable periodically during the production scheduling.

Keywords: multi-agent systems, emergence, genetic algorithm, makespan, systematic maintenance, scheduling, hybrid flow shop scheduling

Procedia PDF Downloads 336

Authors: Zulkifli Zainal Abidin, Ahmad Shahril Mohd Ghani

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Agent-based systems technology has been addressed as a new paradigm for conceptualizing, designing, and implementing software systems. Agents are sophisticated systems that act autonomously across open and distributed environments in solving problems. Nevertheless, it is impractical to rely on a single agent to do all computing processes in solving complex problems. An increasing number of applications lately require multiple agents to work together. A multi-agent system (MAS) is a loosely coupled network of agents that interact to solve problems that are beyond the individual capacities or knowledge of each problem solver. However, the network of MAS still requires a main system to govern or oversees the operation of the agents in order to achieve a unified goal. We had developed a fleet management system (FMS) in order to manage the fleet of agents, plan route for the agents, perform real-time data processing and analysis, and issue sets of general and specific instructions to the agents. This FMS should be able to perform real-time data processing, communicate with the autonomous surface vehicle (ASV) agents and generate bathymetric map according to the data received from each ASV unit. The first algorithm is developed to communicate with the ASV via radio communication using standard National Marine Electronics Association (NMEA) protocol sentences. Next, the second algorithm will take care of the path planning, formation and pattern generation is tested using various sample data. Lastly, the bathymetry map generation algorithm will make use of data collected by the agents to create bathymetry map in real-time. The outcome of this research is expected can be applied on various other multi-agent systems.

Keywords: autonomous surface vehicle, fleet management system, multi agent system, bathymetry

Procedia PDF Downloads 273

Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

Procedia PDF Downloads 338

Authors: Hiroyuki Aoki

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The optoacoustic effect is the energy conversion phenomenon from light to sound. In recent years, this optoacoustic effect has been utilized for an imaging agent to visualize a tumor site in a living body. The optoacoustic imaging agent absorbs the light and emits the sound signal. The sound wave can propagate in a living organism with a small energy loss; therefore, the optoacoustic imaging method enables the molecular imaging of the deep inside of the body. In order to improve the imaging quality of the optoacoustic method, the more signal intensity is desired; however, it has been difficult to enhance the signal intensity of the optoacoustic imaging agent because the fundamental mechanism of the signal generation is unclear. This study deals with the mechanism to generate the sound wave signal from the optoacoustic imaging agent following the light absorption by experimental and theoretical approaches. The optoacoustic signal efficiency for the nano-particles consisting of metal and polymer were compared, and it was found that the polymer particle was better. The heat generation and transfer process for optoacoustic agents of metal and polymer were theoretically examined. It was found that heat generated in the metal particle rapidly transferred to the water medium, whereas the heat in the polymer particle was confined in itself. The confined heat in the small particle induces the massive volume expansion, resulting in the large optoacoustic signal for the polymeric particle agent. Thus, we showed that heat confinement is a crucial factor in designing the highly efficient optoacoustic imaging agent.

Keywords: nano-particle, opto-acoustic effect, in vivo imaging, molecular imaging

Procedia PDF Downloads 133

Authors: Sun Shi, Sun Cheng

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The pedestrian corridor is the most crowded area in the public space. The crowded severity has been focused on the field of evacuation strategies of the entrance in large public spaces. The aim of this paper is to analyze the walking efficiency in different spaces of pedestrian corridor with the variation of spatial parameters. The congestion condition caused by the variation of walking efficiency is modeled as well. This study established the space model of the walking corridor by setting the width, slope, turning form and turning angle of the pedestrian corridor. The pedestrian preference of walking mode varied with the difference of the crowded severity, walking speed, field of vision, sight direction and the expected destination, which is influenced by the characters of physical space form. Swarm software is applied to build Agent model. According to the output of the Agent model, the relationship between the pedestrian corridor width, ground slope, turning forms, turning angle and the walking efficiency, crowded severity is acquired. The results of the simulation can be applied to pedestrian corridor design in order to reduce the crowded severity and the potential safety risks caused by crowded people.

Keywords: crowded severity, multi-agent, pedestrian preference, urban space design

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Authors: Fouzia Qamar, Shahida Hasnain

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The objective of the present study was to evaluate the possible role of Agrobacterium tumefaciens as a possible insect biocontrol agent. Pests selected for the present challenge were adult males of Periplaneta americana and last instar larvae of Pieris brassicae and Spodoptera litura. Different ranges of bacterial doses were selected and tested to score the mortalities of the insects after 24 hours, for the lethal dose estimation studies. Mode of application for the inoculation of the bacteria, was the microinjection technique. The evaluation of the possible entomopathogenic carrying attribute of bacterial Ti plasmid, led to the conclusion that the loss of plasmid was associated with the loss of virulence against target insects.

Keywords: agrobacterium tumefaciens, toxicity assessment, biopesticidal attribute, entomopathogenic agent

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Authors: Ebuwa Osagie, Chet Biliyok, Yeung Hoi

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Regeneration energy requirement and ways to reduce it is the main aim of most CO2 capture researches currently being performed and thus, post-combustion carbon capture (PCC) option is identified to be the most suitable for the natural gas-fired power plants. From current research and development (R&D) activities worldwide, two main areas are being examined in order to reduce the regeneration energy requirement of amine-based PCC, namely: (a) development of new solvents with better overall performance than 30wt% monoethanolamine (MEA) aqueous solution, which is considered as the base-line solvent for solvent-based PCC, (b) Integration of the PCC Plant to the power plant. In scaling-up a PCC pilot plant to the size required for a commercial-scale natural gas-fired power plant, process modelling and simulation is very essential. In this work, an integrated process made up of a 482MWe natural gas-fired power plant, an MEA-based PCC plant which is developed and validated has been modelled and simulated. The PCC plant has four absorber columns and a single stripper column, the modelling and simulation was performed with Aspen Plus® V8.4. The gas turbine, the heat recovery steam generator and the steam cycle were modelled based on a 2010 US DOE report, while the MEA-based PCC plant was modelled as a rate-based process. The scaling of the amine plant was performed using a rate based calculation in preference to the equilibrium based approach for 90% CO2 capture. The power plant was integrated to the PCC plant in three ways: (i) flue gas stream from the power plant which is divided equally into four stream and each stream is fed into one of the four absorbers in the PCC plant. (ii) Steam draw-off from the IP/LP cross-over pipe in the steam cycle of the power plant used to regenerate solvent in the reboiler. (iii) Condensate returns from the reboiler to the power plant. The integration of a PCC plant to the NGCC plant resulted in a reduction of the power plant output by 73.56 MWe and the net efficiency of the integrated system is reduced by 7.3 % point efficiency. A secondary aim of this study is the parametric studies which have been performed to assess the impacts of natural gas on the overall performance of the integrated process and this is achieved through investigation of the capture efficiencies.

Keywords: natural gas-fired, power plant, MEA, CO2 capture, modelling, simulation

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Authors: Kisan Sarda, Bhavika Shingote

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This paper aims to evaluate regression modelling for prediction of Energy storage of solar photovoltaic (PV) system using Semi parametric regression techniques because there are some parameters which are known while there are some unknown parameters like humidity, dust etc. Here irradiation of solar energy is different for different places on the basis of Latitudes, so by finding out areas which give more storage we can implement PV systems at those places and our need of energy will be fulfilled. This regression modelling is done for daily, monthly and seasonal prediction of solar energy storage. In this, we have used R modules for designing the algorithm. This algorithm will give the best comparative results than other regression models for the solar PV cell energy storage.

Keywords: semi parametric regression, photovoltaic (PV) system, regression modelling, irradiation

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Authors: Sirine Sayed, Mahrez Ait Mohammed, Mourad Nachtane, Abdelwahed Barkaoui, Khalid Bouziane, Mostapha Tarfaoui

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This study addresses a critical challenge in transitioning to a hydrogen-based economy by introducing and validating a one-dimensional (1D) tool for modelling hydrogen permeability through hybrid materials, focusing on tank applications. The model developed integrates rigorous experimental validation, published data, and advanced computational modelling using the PanDiffusion framework, significantly enhancing its validity and applicability. By elucidating complex interactions between material properties, storage system configurations, and operational parameters, the tool demonstrates its capability to optimize design and operational parameters in real-world scenarios, as illustrated through a case study of hydrogen leakage. This comprehensive approach to assessing hydrogen permeability contributes significantly to overcoming key barriers in hydrogen infrastructure development, potentially accelerating the widespread adoption of hydrogen technology across various industrial sectors and marking a crucial step towards a more sustainable energy future.

Keywords: hydrogen storage, composite tank, permeability modelling, PanDiffusion, energy carrier, transportation technology

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Authors: Sina Saadati, Mohammadreza Razzazi

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Since Java is an object-oriented language, It can be used to solve a wide range of problems. One of the considerable usages of this language can be found in Agent-based modeling and simulation. Despite the significant power of Java, There is not an easy method to render a 3-dimensional human model. In this article, we are about to develop a library which helps modelers present a 3D human model and control it with Java. The library runs two server programs. The first one is a web page server that can connect to any browser and present an HTML code. The second server connects to the browser and controls the movement of the model. So, the modeler will be able to develop a simulation and display a good-looking human model without any knowledge of any graphical tools.

Keywords: agent-based modeling and simulation, human model, graphics, Java, distributed systems

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Authors: Jang kyun Cho, Jeong-dong Lee

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The advent of the Internet, mobile communications, and social network services has stimulated social interactions among consumers, allowing people to affect one another’s innovation adoptions by exchanging information more frequently and more quickly. Previous diffusion models, such as the Bass model, however, face limitations in reflecting such recent phenomena in society. These models are weak in their ability to model interactions between agents; they model aggregated-level behaviors only. The agent based model, which is an alternative to the aggregate model, is good for individual modeling, but it is still not based on an economic perspective of social interactions so far. This study assumes the presence of social utility from other consumers in the adoption of innovation and investigates the effect of individual interactions on innovation diffusion by developing a new model called the interaction-based diffusion model. By comparing this model with previous diffusion models, the study also examines how the proposed model explains innovation diffusion from the perspective of economics. In addition, the study recommends the use of a small-world network topology instead of cellular automata to describe innovation diffusion. This study develops a model based on individual preference and heterogeneous social interactions using utility specification, which is expandable and, thus, able to encompass various issues in diffusion research, such as reservation price. Furthermore, the study proposes a new framework to forecast aggregated-level market demand from individual level modeling. The model also exhibits a good fit to real market data. It is expected that the study will contribute to our understanding of the innovation diffusion process through its microeconomic theoretical approach.

Keywords: innovation diffusion, agent based model, small-world network, demand forecasting

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Authors: Maryam Gallab, Hafida Bouloiz, Youness Chater, Mohamed Tkiouat

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The aim of this paper is to present a model based on multi-agent systems in order to manage the maintenance activities and to ensure the reliability and availability of machines just with the required resources (operators, tools). The interest of the simulation is to solve the complexity of the system and to find results without cost or wasting time. An implementation of the model is carried out on the AnyLogic platform to display the defined performance indicators.

Keywords: maintenance, complexity, simulation, multi-agent systems, AnyLogic platform

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Authors: Kristina Pflug, Markus Busch

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Being able to predict polymer properties and processing behavior based on the applied operating reaction conditions in one of the key challenges in modern polymer reaction engineering. Especially, for cost-intensive processes such as the high-pressure polymerization of low-density polyethylene (LDPE) with high safety-requirements, the need for simulation-based process optimization and product design is high. A multi-scale modelling approach was set-up and validated via a series of high-pressure mini-plant autoclave reactor experiments. The approach starts with the numerical modelling of the complex reaction network of the LDPE polymerization taking into consideration the actual reaction conditions. While this gives average product properties, the complex polymeric microstructure including random short- and long-chain branching is calculated via a hybrid Monte Carlo-approach. Finally, the processing behavior of LDPE -its melt flow behavior- is determined in dependence of the previously determined polymeric microstructure using the branch on branch algorithm for randomly branched polymer systems. All three steps of the multi-scale modelling approach can be independently validated against analytical data. A triple-detector GPC containing an IR, viscosimetry and multi-angle light scattering detector is applied. It serves to determine molecular weight distributions as well as chain-length dependent short- and long-chain branching frequencies. 13C-NMR measurements give average branching frequencies, and rheological measurements in shear and extension serve to characterize the polymeric flow behavior. The accordance of experimental and modelled results was found to be extraordinary, especially taking into consideration that the applied multi-scale modelling approach does not contain parameter fitting of the data. This validates the suggested approach and proves its universality at the same time. In the next step, the modelling approach can be applied to other reactor types, such as tubular reactors or industrial scale. Moreover, sensitivity analysis for systematically varying process conditions is easily feasible. The developed multi-scale modelling approach finally gives the opportunity to predict and design LDPE processing behavior simply based on process conditions such as feed streams and inlet temperatures and pressures.

Keywords: low-density polyethylene, multi-scale modelling, polymer properties, reaction engineering, rheology

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Authors: Felix Baumann, Aleksandar Milutinovic, Dieter Roller

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Up to this point business process management projects in general and business process modelling projects in particular could not rely on a practical and scientifically validated method to estimate cost and effort. Especially the model development phase is not covered by a cost estimation method or model. Further phases of business process modelling starting with implementation are covered by initial solutions which are discussed in the literature. This article proposes a method of filling this gap by deriving a cost estimation method from available methods in similar domains namely software development or software engineering. Software development is regarded as closely similar to process modelling as we show. After the proposition of this method different ideas for further analysis and validation of the method are proposed. We derive this method from COCOMO II and Function Point which are established methods of effort estimation in the domain of software development. For this we lay out similarities of the software development rocess and the process of process modelling which is a phase of the Business Process Management life-cycle.

Keywords: COCOMO II, busines process modeling, cost estimation method, BPM COCOMO

Procedia PDF Downloads 441

Authors: Jingwei Du

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The need of optimizing air conditioning systems for existing buildings calls for control methods designed with energy-efficiency as a primary goal. The majority of current control methods boil down to two categories: empirical and model-based. To be effective, the former heavily relies on engineering expertise and the latter requires extensive historical data. Reinforcement Learning (RL), on the other hand, is a model-free approach that explores the environment to obtain an optimal control strategy often referred to as “policy”. This research adopts Proximal Policy Optimization (PPO) to improve chiller plant control, and enable the RL agent to collaborate with experienced engineers. It exploits the fact that while the industry lacks historical data, abundant operational data is available and allows the agent to learn and evolve safely under human supervision. Thanks to the development of language models, renewed interest in RL has led to modern, online, policy-based RL algorithms such as the PPO. This research took inspiration from “alignment”, a process that utilizes human feedback to finetune the pretrained model in case of unsafe content. The methodology can be summarized into three steps. First, an initial policy model is generated based on minimal prior knowledge. Next, the prepared PPO agent is deployed so feedback from both critic model and human experts can be collected for future finetuning. Finally, the agent learns and adapts itself to the specific chiller plant, updates the policy model and is ready for the next iteration. Besides the proposed approach, this study also used traditional RL methods to optimize the same simulated chiller plants for comparison, and it turns out that the proposed method is safe and effective at the same time and needs less to no historical data to start up.

Keywords: chiller plant, control methods, energy efficiency, proximal policy optimization, reinforcement learning

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Authors: Manel Brichni, Abdelhak-Djamel Seriai

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Systems are increasingly complex. To reduce their complexity, an abstract view of the system can simplify its development. To overcome this problem, we propose a method to decompose systems into subsystems while reducing their coupling. These subsystems represent components. Consisting of an existing object-oriented systems, the main idea of our approach is based on modelling as graphs all entities of an oriented object source code. Such modelling is easy to handle, so we can apply restructuring algorithms based on graph metrics. The particularity of our approach consists in integrating in addition to standard metrics, such as coupling and cohesion, some graph metrics giving more precision during the components identication. To treat this problem, we relied on the ROMANTIC approach that proposed a component-based software architecture recovery from an object oriented system.

Keywords: software reengineering, software component and interfaces, metrics, graphs

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Authors: Dylan Santos De Pinho, Arnaud Gay De Combes, Matthieu Steuhlet, Claude Jeannerat, Nabil Ouerhani

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The Industry 4.0 initiative has been launched to address huge challenges related to ever-smaller batch sizes. The end-user need for highly customized products requires highly adaptive production systems in order to keep the same efficiency of shop floors. Most of the classical Software solutions that operate the manufacturing processes in a shop floor are based on rigid Manufacturing Execution Systems (MES), which are not capable to adapt the production order on the fly depending on changing demands and or conditions. In this paper, we present a highly modular and flexible solution to orchestrate a set of production systems composed of a micro-milling machine-tool, a polishing station, a cleaning station, a part inspection station, and a rough material store. The different stations are installed according to a novel matrix configuration of a 3x3 vertical shelf. The different cells of the shelf are connected through horizontal and vertical rails on which a set of shuttles circulate to transport the machined parts from a station to another. Our software solution for orchestrating the tasks of each station is based on a Multi-Agent System. Each station and each shuttle is operated by an autonomous agent. All agents communicate with a central agent that holds all the information about the manufacturing order. The core innovation of this paper lies in the path planning of the different shuttles with two major objectives: 1) reduce the waiting time of stations and thus reduce the cycle time of the entire part, and 2) reduce the disturbances like vibration generated by the shuttles, which highly impacts the manufacturing process and thus the quality of the final part. Simulation results show that the cycle time of the parts is reduced by up to 50% compared with MES operated linear production lines while the disturbance is systematically avoided for the critical stations like the milling machine-tool.

Keywords: multi-agent systems, micro-manufacturing, flexible manufacturing, transfer systems

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Authors: Jugoslav Jokovic, Tijana Dimitrijevic, Nebojsa Doncov

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The goal of this paper is to investigate the possibilities and effectiveness of the TLM (Transmission Line Matrix) method for modelling of up-to-date microstrip antennas with circular geometry that have significant application in modern wireless communication systems. The coaxially fed microstrip antenna configurations with circular patch are analyzed by using the in-house 3DTLMcyl_cw solver based on computational electromagnetic TLM method adapted to the cylindrical grid and enhanced with the compact wire model. Opposed to the widely used rectangular TLM mesh, where a staircase approximation has to be used to describe curved boundaries, precise modelling of circular boundaries can be accomplished in the cylindrical grid irrespective of the mesh resolution. Using the compact wire model incorporated in cylindrical mesh, it is possible to model coaxial feed and include the influence of the real excitation in the antenna model. The conventional and inverted configuration of a coaxially fed circular patch antenna are considered, comparing the resonances obtained using TLM cylindrical model with results reached by the corresponding model in a rectangular grid as well as with experimental ones. Bearing in mind that accuracy of simulated results depends on a relevantly created model, besides structure geometry and dimensions, it is important to consider additional modelling issues, regarding appropriate mesh resolution and a relevant extension of a mesh around the considered structure that would provide convergence of the results.

Keywords: computational electromagnetic, coaxial feed, microstrip antenna, TLM modelling

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Authors: Muhammad Al Rizqi Dharma Fauzi, Dwi Yulian Fahruddin Shah, Andre Pratama, Ari Hasna Widyapuspa, Ganden Supriyanto

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Diabetes mellitus is still known as one of diseases which give a big amount of death in the world. From 2012 to 2014, diabetes is estimated to have resulted in 1.5 to 4.9 million deaths each year. In this paper, we present our research in the analysis and dose determination of Tenebrio molitor (Mealworm) extract as an anti-diabetic agent which is believed by Indonesian people as a traditional treatment to prevent and treat diabetes. We found that Tenebrio molitor extract has a potential as an anti-diabetic agent by in vitro test to Mus musculus which were divided into six group of treatment. Our dose determination analysis gave a conclusion that at 2,5 g/mL of concentration of the extract would give the optimal result in healing a wound given to Mus musculus which were induced by aloxane monohydrate. These results show that Tenebrio molitor extract is potential to be used as an Anti-Diabetic agent.

Keywords: diabetes, extraction, Tenebrio molitor, traditional medicine

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Authors: Deyu Zhou, Xiao Xue, Lizhen Cui

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With the increasing collaboration among various services and the growing complexity of user demands, there are more and more factors affecting the stable development of the cloud manufacturing service economic system (CMSE). This poses new challenges to the evolution analysis of the CMSE. Many researchers have modeled and analyzed the evolution process of CMSE from the perspectives of individual learning and internal factors influencing the system, but without considering other important characteristics of the system's individuals (such as heterogeneity, bounded rationality, etc.) and the impact of external environmental factors. Therefore, this paper proposes an integrated artificial social model for the cloud manufacturing service economic system, which considers both the characteristics of the system's individuals and the internal and external influencing factors of the system. The model consists of three parts: the Agent model, environment model, and rules model (Agent-Environment-Rules, AER): (1) the Agent model considers important features of the individuals, such as heterogeneity and bounded rationality, based on the adaptive behavior mechanisms of perception, action, and decision-making; (2) the environment model describes the activity space of the individuals (real or virtual environment); (3) the rules model, as the driving force of system evolution, describes the mechanism of the entire system's operation and evolution. Finally, this paper verifies the effectiveness of the AER model through computational and experimental results.

Keywords: cloud manufacturing service economic system (CMSE), AER model, artificial social modeling, integrated framework, computing experiment, agent-based modeling, social networks

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Authors: M. R. Ebrahimi, B. Mahdaviani

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Conventional electric distribution systems are radial in nature, supplied at one end through a main source. These networks generally have a simple protection system usually implemented using fuses, re-closers, and over-current relays. Recently, great attention has been paid to applying Distributed energy resources (DERs) throughout electric distribution systems. Presence of such generation in a network leads to losing coordination of protection devices. Therefore, it is desired to develop an algorithm which is capable of protecting distribution systems that include DER. On the other hand smart grid brings opportunities to the power system. Fast advancement in communication and measurement techniques accelerates the development of multi agent system (MAS). So in this paper, a new approach for the protection of distribution networks in the presence of DERs is presented base on MAS. The proposed scheme has been implemented on a sample 27-bus distribution network.

Keywords: distributed energy resource, distribution network, protection, smart grid, multi agent system

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Authors: Dejan Tanikić, Jelena Đoković, Saša Kalinović, Miodrag Manić, Saša Ranđelović

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This paper deals with measuring and modelling of the quality of the machined surface of the metal machining process. The average surface roughness (R_a) which represents the quality of the machined part was measured during the dry turning of the AISI 4140 steel. A large number of factors with the unknown relations among them influences this parameter, and that is why mathematical modelling is extremely complicated. Different values of cutting speed, feed rate, depth of cut (cutting regime) and workpiece hardness causes different surface roughness values. Modelling with soft computing techniques may be very useful in such cases. This paper presents the usage of the fuzzy logic-based system for determining metal machining process parameter in order to find the proper values of cutting regimes.

Keywords: fuzzy logic, metal machining, process modeling, surface roughness

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Authors: Hiroyuki Aoki

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Molecular imaging has attracted much attention recently, which visualizes biological molecules, cells, tissue, and so on. Among various in vivo imaging techniques, the fluorescence imaging method has been widely employed as a useful modality for small animals in pre-clinical researches. However, the higher signal intensity is needed for highly sensitive in vivo imaging. The objective of the current study is the development of a fluorescent imaging agent with high brightness for the tumor imaging of a mouse. The strategy to enhance the fluorescence signal of a bio-imaging agent is the increase of the absorption of the excitation light and the fluorescence conversion efficiency. We developed a nano-particle fluorescence imaging agent consisting of a π-conjugated polymer emitting a fluorescence signal in a near infrared region. A large absorption coefficient and high emission intensity at a near infrared optical window for biological tissue enabled highly sensitive in vivo imaging with a tumor-targeting ability by an EPR (enhanced permeation and retention) effect. The signal intensity from the π-conjugated fluorescence imaging agent is larger by two orders of magnitude compared to a quantum dot, which has been known as the brightest imaging agent. The π-conjugated polymer nano-particle would be a promising candidate in the in vivo imaging of small animals.

Keywords: fluorescence, conjugated polymer, in vivo imaging, nano-particle, near-infrared

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Authors: Y. Rae, A. Benaarbia, J. Hughes, Wei Sun

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This paper describes an elasto-visco-plastic computational modelling method which can be used to assess the cyclic plasticity responses of high temperature structures operating under thermo-mechanical loadings. The material constitutive equation used is an improved unified multi-axial Chaboche-Lemaitre model, which takes into account non-linear kinematic and isotropic hardening. The computational methodology is a three-dimensional framework following an implicit formulation and based on a radial return mapping algorithm. The associated user material (UMAT) code is developed and calibrated across isothermal hold-time low cycle fatigue tests for a typical turbine rotor steel for use in finite element (FE) implementation. The model is applied to a realistic industrial gas turbine rotor, where the study focuses its attention on the deformation heterogeneities and critical high stress areas within the rotor structure. The potential improvements of such FE visco-plastic approach are discussed. An integrated life assessment procedure based on R5 and visco-plasticity modelling, is also briefly addressed.

Keywords: unified visco-plasticity, thermo-mechanical, turbine rotor, finite element modelling

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Authors: David Gottlieb, Jason Yoder

Abstract:

The feeling of loneliness is not uncommon in modern society, and yet, there is a fundamental lack of understanding in its origins and purpose in nature. One interpretation of loneliness is that it is a subjective experience that punishes a lack of social behavior, and thus its emergence in human evolution is seemingly tied to the survival of early human tribes. Still, a common counterintuitive response to loneliness is a state of hypervigilance, resulting in social withdrawal, which may appear maladaptive to modern society. So far, no computational model of loneliness’ effect during evolution yet exists; however, agent-based models (ABM) can be used to investigate social behavior, and applying evolution to agents’ behaviors can demonstrate selective advantages for particular behaviors. We propose an ABM where each agent contains four social behaviors, and one goal-seeking behavior, letting evolution select the best behavioral patterns for resource allocation. In our paper, we use an algorithm similar to the boid model to guide the behavior of agents, but expand the set of rules that govern their behavior. While we use cohesion, separation, and alignment for simple social movement, our expanded model adds goal-oriented behavior, which is inspired by particle swarm optimization, such that agents move relative to their personal best position. Since agents are given the ability to form connections by interacting with each other, our final behavior guides agent movement toward its social connections. Finally, we introduce a mechanism to represent a state of loneliness, which engages when an agent's perceived social involvement does not meet its expected social involvement. This enables us to investigate a minimal model of loneliness, and using evolution we attempt to elucidate its value in human survival. Agents are placed in an environment in which they must acquire resources, as their fitness is based on the total resource collected. With these rules in place, we are able to run evolution under various conditions, including resource-rich environments, and when disease is present. Our simulations indicate that there is strong selection pressure for social behavior under circumstances where there is a clear discrepancy between initial resource locations, and against social behavior when disease is present, mirroring hypervigilance. This not only provides an explanation for the emergence of loneliness, but also reflects the diversity of response to loneliness in the real world. In addition, there is evidence of a richness of social behavior when loneliness was present. By introducing just two resource locations, we observed a divergence in social motivation after agents became lonely, where one agent learned to move to the other, who was in a better resource position. The results and ongoing work from this project show that it is possible to glean insight into the evolutionary advantages of even simple mechanisms of loneliness. The model we developed has produced unexpected results and has led to more questions, such as the impact loneliness would have at a larger scale, or the effect of creating a set of rules governing interaction beyond adjacency.

Keywords: agent-based, behavior, evolution, loneliness, social

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Authors: Kyle Burke Pfeiffer, Carmella Burdi, Karen Marsh

Abstract:

The evacuation and shelter-in-place planning process employed by most jurisdictions within the United States is not informed by a scientifically-derived framework that is inclusive of the behavioral and policy-related indicators of public compliance with evacuation orders. While a significant body of work exists to define these indicators, the research findings have not been well-integrated nor translated into useable planning factors for public safety officials. Additionally, refinement of the planning factors alone is insufficient to support science-based evacuation planning as the behavioral elements of evacuees—even with consideration of policy-related indicators—must be examined in the context of specific regional transportation and shelter networks. To address this problem, the Federal Emergency Management Agency and Argonne National Laboratory developed an agent-based model to support regional analysis of zone-based evacuation in southeastern Georgia. In particular, this model allows public safety officials to analyze the consequences that a range of hazards may have upon a community, assess evacuation and shelter-in-place decisions in the context of specified evacuation and response plans, and predict outcomes based on community compliance with orders and the capacity of the regional (to include extra-jurisdictional) transportation and shelter networks. The intention is to use this model to aid evacuation planning and decision-making. Applications for the model include developing a science-driven risk communication strategy and, ultimately, in the case of evacuation, the shortest possible travel distance and clearance times for evacuees within the regional boundary conditions.

Keywords: agent-based modeling for evacuation, decision-support for evacuation planning, evacuation planning, human behavior in evacuation

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Authors: Monica Hoeldtke Pietruchinski, Andrey Ricardo Pimentel

Abstract:

The teaching of computer programming for beginners has been presented to the community as a not simple or trivial task. Several methodologies and research tools have been developed; however, the problem still remains. This paper aims to present multi-agent system architecture to be incorporated to the educational collaborative game software for teaching programming that monitors, evaluates and encourages collaboration by the participants. A literature review has been made on the concepts of Collaborative Learning, Multi-agents systems, collaborative games and techniques to teach programming using these concepts simultaneously.

Keywords: architecture of multi-agent systems, collaborative evaluation, collaboration assessment, gamifying educational software

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Authors: Sagir M. Yusuf, Chris Baber

Abstract:

We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

Procedia PDF Downloads 156