Search results for: optimization and visualization

Authors: Mohamed Belhorma, Aboubakar S. Bouchikhi, Belkacem Bounab

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This paper addresses modeling a Double A-Arm suspension, a three-dimensional nonlinear model has been developed using the multibody systems formalism. Dynamical study of the different components responses was done, particularly for the wheel assembly. To validate those results, the system was constructed and simulated by RecurDyn, a professional multibody dynamics simulation software. The model has been used as the Objectif function in an optimization algorithm for ride quality improvement.

Keywords: double A-Arm suspension, multibody systems, ride quality optimization, dynamic simulation

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Traditional optimization methods like evolutionary algorithms are widely used in production processes to find an optimal or near-optimal solution of control parameters based on the simulated environment space of a process. These algorithms are computationally intensive and therefore do not provide the opportunity for real-time optimization. This paper utilizes the Deep Reinforcement Learning (DRL) framework to find an optimal or near-optimal solution for control parameters. A model based on maximum a posteriori policy optimization (Hybrid-MPO) that can handle both numerical and categorical parameters is used as a benchmark for comparison. A comparative study shows that DRL can find optimal solutions of similar quality as compared to evolutionary algorithms while requiring significantly less time making them preferable for real-time optimization. The results are confirmed in a large-scale validation study on datasets from production and other fields. A trained XGBoost model is used as a surrogate for process simulation. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, evolutionary algorithms, production process optimization, real-time optimization, hybrid-MPO

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Authors: Ashraf Osman

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Effective deployable bridges that are characterized by an increased capacity to weight ratio are recently needed for post-disaster rapid mobility and military operations. In deployable bridging, replacing metals as the fabricating material with advanced composite laminates as lighter alternatives with higher strength is highly advantageous. This article presents a hierarchical optimization strategy of a composite bridge treadway considering maximum strength design and bridge weight minimization. Shape optimization of a generic deployable bridge beam cross-section is performed to achieve better stress distribution over the bridge treadway hull. The developed cross-section weight is minimized up to reserving the margins of safety of the deployable bridging code provisions. Hence, the strength of composite bridge plates is maximized through varying the plies orientation. Different loading cases are considered of a tracked vehicle patch load. The orthotropic plate properties of a composite sandwich core are used to simulate the bridge deck structural behavior. Whereas, the failure analysis is conducted using Tsai-Wu failure criterion. The naturally inspired particle swarm optimization technique is used in this study. The proposed technique efficiently reduced the weight to capacity ratio of the developed bridge beam.

Keywords: CFRP deployable bridges, disaster relief, military bridging, optimization of composites, particle swarm optimization

Procedia PDF Downloads 116

Authors: Saeed Ur Rahman, Naveed Ullah, Muhammad Irshad Khan, Quensheng Cao, Niaz Muhammad Khan

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In this paper the optimization performance of non-uniform linear antenna array is presented. The Particle Swarm Optimization (PSO) algorithm is presented to minimize Side Lobe Level (SLL) and Half Power Beamwidth (HPBW). The purpose of using the PSO algorithm is to get the optimum values for inter-element spacing and excitation amplitude of linear antenna array that provides a radiation pattern with minimum SLL and HPBW. Various design examples are considered and the obtain results using PSO are confirmed by comparing with results achieved using other nature inspired metaheuristic algorithms such as real coded genetic algorithm (RGA) and biogeography (BBO) algorithm. The comparative results show that optimization of linear antenna array using the PSO provides considerable enhancement in the SLL and HPBW.

Keywords: linear antenna array, minimum side lobe level, narrow half power beamwidth, particle swarm optimization

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Authors: Corinne Zurmuehle, Andreas Christoph Weber

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In 2019, the Swiss Federal Institute of Sport Magglingen (SFISM) conducted a mixed-methods study on the Swiss elite sports system, which yielded a large quantity of research data. In a quantitative online survey, 1151 elite sports athletes, 542 coaches, and 102 Performance Directors of national sports federations (NF) have submitted their perceptions of the national support measures of the Swiss elite sports system. These data provide an essential database for the further development of the Swiss elite sports system. The results were published in a report presenting the results divided into 40 Olympic summer and 14 winter sports (Olympic classification). The authors of this paper assume that, in practice, this division is too unspecific to assess where further measures would be needed. The aim of this paper is to find appropriate parameters for data visualization in order to identify disparities in sports promotion that allow an assessment of where further interventions by Swiss Olympic (NF umbrella organization) are required. Method: First, the variable 'salary earned from sport' was defined as a variable to measure the impact of elite sports promotion. This variable was chosen as a measure as it represents an important indicator for the professionalization of elite athletes and therefore reflects national level sports promotion measures applied by Swiss Olympic. Afterwards, the variable salary was tested with regard to the correlation between Olympic classification [a], calculating the Eta coefficient. To estimate the appropriate parameters for data visualization, the correlation between salary and four further parameters was analyzed by calculating the Eta coefficient: [a] sport; [b] prioritization (from 1 to 5) of the sports by Swiss Olympic; [c] gender; [d] employment level in sports. Results & Discussion: The analyses reveal a very small correlation between salary and Olympic classification (ɳ² = .011, p = .005). Gender demonstrates an even small correlation (ɳ² = .006, p = .014). The parameter prioritization was correlating with small effect (ɳ² = .017, p = .001) as did employment level (ɳ² = .028, p < .001). The highest correlation was identified by the parameter sport with a moderate effect (ɳ² = .075, p = .047). The analyses show that the disparities in sports promotion cannot be determined by a particular parameter but presumably explained by a combination of several parameters. We argue that the possibility of combining parameters for data visualization should be enabled when the analysis is provided to Swiss Olympic for further strategic decision-making. However, the inclusion of multiple parameters massively multiplies the number of graphs and is therefore not suitable for practical use. Therefore, we suggest to apply interactive dashboards for data visualization using Business Intelligence Software. Practical & Theoretical Contribution: This contribution provides the first attempt to use Business Intelligence Software for strategic decision-making in national level sports regarding the prioritization of national resources for sports and athletes. This allows to set specific parameters with a significant effect as filters. By using filters, parameters can be combined and compared against each other and set individually for each strategic decision.

Keywords: data visualization, business intelligence, Swiss elite sports system, strategic decision-making

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Authors: K. K. Lee, H. W. Han, H. L. Kang, T. A. Kim, S. H. Han

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For the robust optimization of the manufacturing product design, there are design objectives that must be achieved, such as a minimization of the mean and standard deviation in objective functions within the required sensitivity constraints. The authors utilized the sensitivity of objective functions and constraints with respect to the effective design variables to reduce the computational burden associated with the evaluation of the probabilities. The individual mean and sensitivity values could be estimated easily by using the 9 level orthogonal array based response surface models optimized by the stepwise regression. The present study evaluates a proposed procedure from the robust optimization of rubber domes that are commonly used for keyboard switching, by using the 9 level orthogonal array and stepwise regression along with a desirability function. In addition, a new robust optimization process, i.e., the I2GEO (Identify, Integrate, Generate, Explore and Optimize), was proposed on the basis of the robust optimization in rubber domes. The optimized results from the response surface models and the estimated results by using the finite element analysis were consistent within a small margin of error. The standard deviation of objective function is decreasing 54.17% with suggested sensitivity based robust optimization. (Business for Cooperative R&D between Industry, Academy, and Research Institute funded Korea Small and Medium Business Administration in 2017, S2455569)

Keywords: objective function, orthogonal array, response surface model, robust optimization, stepwise regression

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Authors: Yanhua Ma, Lu Zhai, Xinchen Wang, Hongyu Liang

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In this paper, by understanding the development status of the human-machine interface in today's automobile cab, a subjective and objective evaluation system for evaluating the optimization of human-machine interface matching in automobile cab was established. The man-machine interface of the car cab was divided into a software interface and a hard interface. Objective evaluation method of software human factor analysis is used to evaluate the hard interface matching; The analytic hierarchy process is used to establish the evaluation index system for the software interface matching optimization, and the multi-level fuzzy comprehensive evaluation method is used to evaluate hard interface machine. This article takes Dongfeng Sokon (DFSK) C37 model automobile as an example. The evaluation method given in the paper is used to carry out relevant analysis and evaluation, and corresponding optimization suggestions are given, which have certain reference value for designers.

Keywords: analytic hierarchy process, fuzzy comprehension evaluation method, human-machine interface, matching optimization, software human factor analysis

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Authors: S. Vasundra, D. Venkatesh

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Wireless networks have gone through an extraordinary growth in the past few years, and will keep on playing a crucial role in future data communication. The present wireless networks aim to make communication possible anywhere and anytime. With the converging of mobile and wireless communications with Internet services, the boundary between mobile personal telecommunications and wireless computer networks is disappearing. Wireless networks of the next generation need the support of all the advances on new architectures, standards, and protocols. Since an ad hoc network may consist of a large number of mobile hosts, this imposes a significant challenge on the design of an effective and efficient routing protocol that can work well in an environment with frequent topological changes. This paper proposes improved ant colony optimization (IACO) technique. It also maintains load balancing in wireless networks. The simulation results show that the proposed IACO performs better than existing routing techniques.

Keywords: wireless networks, ant colony optimization, load balancing, architecture

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Authors: Misha Mirza

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In recent years, the definition of journalism in Pakistan has changed, so has the mindset of people and their approach towards a news story. For the audience, news has become more interesting than a drama or a film. This research thus provides an insight into Pakistan’s evolving media landscape. It tries not only to bring forth the outcomes of cross-platform cooperation among print and broadcast journalism but also gives an insight into the interactive data visualization techniques being used. The storytelling in journalism in Pakistan has evolved from depicting merely the truth to tweaking, fabricating and producing docu-dramas. It aims to look into how news is translated to a visual. Pakistan acquires a diverse cultural heritage and by engaging audience through media, this history translates into the storytelling platform today. The paper explains how journalists are thriving in a converging media environment and provides an analysis of the narratives in television talk shows today.’ Jack of all, master of none’ is being challenged by the journalists today. One has to be a quality information gatherer and an effective storyteller at the same time. Are journalists really looking more into what sells rather than what matters? Express Tribune is a very popular news platform among the youth. Not only is their newspaper more attractive than the competitors but also their style of narrative and interactive web stories lead to well-rounded news. Interviews are used as the basic methodology to get an insight into how data visualization is compassed. The quest for finding out the difference between visualization of information versus the visualization of knowledge has led the author to delve into the work of David McCandless in his book ‘Knowledge is beautiful’. Journalism in Pakistan has evolved from information to combining knowledge, infotainment and comedy. What is being criticized the most by the society most often becomes the breaking news. Circulation in today’s world is carried out in cultural and social networks. In recent times, we have come across many examples where people have gained overnight popularity by releasing songs with substandard lyrics or senseless videos perhaps because creativity has taken over information. This paper thus discusses the various platforms of convergence journalism from Pakistan’s perspective. The study concludes with proving how Pakistani pop culture Truck art is coexisting with all the platforms in convergent journalism. The changing media landscape thus challenges the basic rules of journalism. The slapstick humor and ‘jhatka’ in Pakistani talk shows has evolved from the Pakistani truck art poetry. Mobile journalism has taken over all the other mediums of journalism; however, the Pakistani culture coexists with the converging landscape.

Keywords: convergence journalism in Pakistan, data visualization, interactive narrative in Pakistani news, mobile journalism, Pakistan's truck art culture

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Authors: Zeyu Zhang, Guisheng Yin, Ziying Zhang, Liguo Zhang

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This paper mainly studies the path planning method based on ant colony optimization (ACO), and proposes heuristic integration ant colony optimization (HIACO). This paper not only analyzes and optimizes the principle, but also simulates and analyzes the parameters related to the application of HIACO in path planning. Compared with the original algorithm, the improved algorithm optimizes probability formula, tabu table mechanism and updating mechanism, and introduces more reasonable heuristic factors. The optimized HIACO not only draws on the excellent ideas of the original algorithm, but also solves the problems of premature convergence, convergence to the sub optimal solution and improper exploration to some extent. HIACO can be used to achieve better simulation results and achieve the desired optimization. Combined with the probability formula and update formula, several parameters of HIACO are tested. This paper proves the principle of the HIACO and gives the best parameter range in the research of path planning.

Keywords: ant colony optimization, heuristic integration, path planning, probability formula

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Authors: ChunYi Peng, Wei Hsuan CHeng, Shyh Kuang Ueng

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This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

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Authors: Mohamed Rahal, Djaouida Guetta

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In this paper, the one-dimensional unconstrained global optimization problem of continuous functions satifying a Hölder condition is considered. We extend the algorithm of sequential covering SCA for Lipschitz functions to a large class of Hölder functions. The convergence of the method is studied and the algorithm can be applied to systems of nonlinear equations. Finally, some numerical examples are presented and illustrate the efficiency of the present approach.

Keywords: global optimization, Hölder functions, sequential covering method, systems of nonlinear equations

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Authors: Manjula Sutagundar, B. G. Sheeparamatti, D. S. Jangamshetti

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Micro Electro Mechanical Systems (MEMS) resonators have shown the potential of replacing quartz crystal technology for sensing and high frequency signal processing applications because of inherent advantages like small size, high quality factor, low cost, compatibility with integrated circuit chips. This paper presents the optimization and modelling and simulation of the optimized micro cantilever resonator. The objective of the work is to optimize the dimensions of a micro cantilever resonator for a specified range of resonant frequency and specific quality factor. Optimization is carried out using genetic algorithm. The genetic algorithm is implemented using MATLAB. The micro cantilever resonator is modelled in CoventorWare using the optimized dimensions obtained from genetic algorithm. The modeled cantilever is analysed for resonance frequency.

Keywords: MEMS resonator, genetic algorithm, modelling and simulation, optimization

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Authors: Belloufi Mohammed, Sellami Badreddine

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Conjugate gradient methods have played a special role for solving large scale optimization problems due to the simplicity of their iteration, convergence properties and their low memory requirements. In this work, we propose a new class of conjugate gradient methods which ensures sufficient descent. Moreover, we propose a new search direction with the Wolfe line search technique for solving unconstrained optimization problems, a global convergence result for general functions is established provided that the line search satisfies the Wolfe conditions. Our numerical experiments indicate that our proposed methods are preferable and in general superior to the classical conjugate gradient methods in terms of efficiency and robustness.

Keywords: unconstrained optimization, conjugate gradient method, sufficient descent property, numerical comparisons

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Authors: Ozan Yavuz Baytemir, Ender Cigeroglu, Gokhan Osman Ozgen

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Vibration is an important issue in the design of various components of aerospace, marine and vehicular applications. In order not to lose the components’ function and operational performance, vibration isolation design involving the optimum isolator properties selection and isolator positioning processes appear to be a critical study. Knowing the growing need for the vibration isolation system design, this paper aims to present two types of software capable of implementing modal analysis, response analysis for both random and harmonic types of excitations, static deflection analysis, Monte Carlo simulations in addition to study of parameter and location optimization for different types of isolation problem scenarios. Investigating the literature, there is no such study developing a software-based tool that is capable of implementing all those analysis, simulation and optimization studies in one platform simultaneously. In this paper, the theoretical system model is generated for a 6-DOF rigid body. The vibration isolation system of any mechanical structure is able to be optimized using hybrid method involving both global search and gradient-based methods. Defining the optimization design variables, different types of optimization scenarios are listed in detail. Being aware of the need for a user friendly vibration isolation problem solver, two types of graphical user interfaces (GUIs) are prepared and verified using a commercial finite element analysis program, Ansys Workbench 14.0. Using the analysis and optimization capabilities of those GUIs, a real application used in an air-platform is also presented as a case study at the end of the paper.

Keywords: hybrid optimization, Monte Carlo simulation, multi-degree-of-freedom system, parameter optimization, location optimization, passive vibration isolation analysis

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Authors: Lu Xi, Li Pan, Wen Mengmeng

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The stiffness of each component has different influences on the stiffness of the machine tool. Taking the five-axis gantry machining center as an example, we made the modal analysis of the machine tool, followed by raising and lowering the stiffness of the pillar, slide plate, beam, ram and saddle so as to study the stiffness matching among these components on the standard of whether the stiffness of the modified machine tool changes more than 50% relative to the stiffness of the original machine tool. The structural optimization of the machine tool can be realized by changing the stiffness of the components whose stiffness is mismatched. For example, the stiffness of the beam is mismatching. The natural frequencies of the first six orders of the beam increased by 7.70%, 0.38%, 6.82%, 7.96%, 18.72% and 23.13%, with the weight increased by 28Kg, leading to the natural frequencies of several orders which had a great influence on the dynamic performance of the whole machine increased by 1.44%, 0.43%, 0.065%, which verified the correctness of the optimization method based on stiffness matching proposed in this paper.

Keywords: machine tool, optimization, modal analysis, stiffness matching

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Authors: Christian Angerer, Markus Lienkamp

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Electric vehicles offer a high variety of possible drivetrain topologies with up to 4 motors. Multi-motor-designs can have several advantages regarding traction, vehicle dynamics, safety and even efficiency. With a rising number of motors, the whole drivetrain becomes more complex. All permutations of gearings, drivetrain-layouts, motor-types and –sizes lead up in a very large solution space. Single elements of this solution space can be analyzed by simulation methods. In addition to longitudinal vehicle behavior, which most optimization-approaches are restricted to, also lateral dynamics are important for vehicle dynamics, stability and efficiency. In order to compete large solution spaces and to find an optimal result, genetic algorithm based optimization is state-of-the-art. As lateral dynamics simulation is way more CPU-intensive, optimization takes much more time than in case of longitudinal-only simulation. Therefore, this paper shows an approach how to create meta-models from a 14-degree of freedom vehicle model in order to enable a numerically efficient drivetrain-layout optimization process under consideration of lateral dynamics. Different meta-modelling approaches such as neural networks or DoE are implemented and comparatively discussed.

Keywords: driving dynamics, drivetrain layout, genetic optimization, meta-modeling, lateral dynamicx

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Authors: Ting-Yu Lin, Han-Liang Lin

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This article is about the urban form of visualization by Cityengine. City is composed of different domains, and each domain has its own fabric because of arrangement. For example, a neighborhood unit contains fabrics such as schools, street networks, residential and commercial spaces. Therefore, studying urban morphology can help us understand the urban form in planning process. Streets, plots, and buildings seem as urban fabrics, and they configure urban form. Traditionally, urban morphology usually discussed single parameter, which is building type, ignoring other parameters such as streets and plots. However, urban space is three-dimensional, instead of two-dimensional. People perceive urban space by their visualization. Therefore, using visualization can fill the gap between two dimensions and three dimensions. Hence, the study of urban morphology will strengthen the understanding of whole appearance of a city. Cityengine is a software which can edit, analyze and monitor the data and visualize the result for GIS, a common tool to analyze data and display the map for urban plan and urban design. Cityengine can parameterize the data of streets, plots and building types and visualize the result in three-dimensional way. The research will reappear the real urban form by visualizing. We can know whether the urban form can be parameterized and the parameterized result can match the real urban form. Then, visualizing the result by software in three dimension to analyze the rule of urban form. There will be three stages of the research. It will start with a field survey of Tainan East District in Taiwan to conclude the relationships between urban fabrics of street networks, plots and building types. Second, to visualize the relationship, it will turn the relationship into codes which Cityengine can read. Last, Cityengine will automatically display the result by visualizing.

Keywords: Cityengine, urban fabric, urban morphology, visual simulation

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Authors: Kaoru Tomita

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This study explores how visual information helps us to learn foreign language pronunciation. Visual assistance and its effect for learning foreign language have been discussed widely. For example, simplified illustrations in textbooks are used for telling learners which part of the articulation organs are used for pronouncing sounds. Vowels are put into a chart that depicts a vowel space. Consonants are put into a table that contains two axes of place and manner of articulation. When comparing a still picture and a moving picture for visualizing learners’ pronunciation, it becomes clear that the former works better than the latter. The visualization of vowels was applied to class activities in which native and non-native speakers’ English was compared and the learners’ feedback was collected: the positions of six vowels did not scatter as much as they were expected to do. Specifically, two vowels were not discriminated and were arranged very close in the vowel space. It was surprising for the author to find that learners liked analyzing their own pronunciation by linking formant ones and twos on a sheet of paper with a pencil. Even a simple method works well if it leads learners to think about their pronunciation analytically.

Keywords: feedback, pronunciation, visualization, vowel

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Authors: Zukhrof Romadhon, Nani Kurniati

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Availability of Spare parts is critical to support maintenance tasks and the production system. Managing spare part inventory deals with some parameters and objective functions, as well as the tradeoff between inventory costs and spare parts availability. Several mathematical models and methods have been developed to optimize the spare part policy. Many researchers who proposed optimization models need to be considered to identify other potential models. This work presents a review of several pertinent literature on spare part inventory optimization and analyzes the gaps for future research. Initial investigation on scholars and many journal database systems under specific keywords related to spare parts found about 17K papers. Filtering was conducted based on five main aspects, i.e., replenishment policy, objective function, echelon network, lead time, model solving, and additional aspects of part classification. Future topics could be identified based on the number of papers that haven’t addressed specific aspects, including joint optimization of spare part inventory and maintenance.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenance

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Authors: Jaber Nikpouri, Arsalan Amralizadeh

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In robotics manipulators, the trajectory should be optimum, thus the torque of the robot can be minimized in order to save power. This paper includes an optimal path planning scheme for a robotic manipulator. Recently, techniques based on metaheuristics of natural computing, mainly evolutionary algorithms (EA), have been successfully applied to a large number of robotic applications. In this paper, the improved BBO algorithm is used to minimize the objective function in the presence of different obstacles. The simulation represents that the proposed optimal path planning method has satisfactory performance.

Keywords: biogeography-based optimization, path planning, obstacle detection, robotic manipulator

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Authors: Seyedehsomayeh Hosseini

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Much attention has been paid over centuries to understanding and solving the problem of minimization of functions. Compared to linear programming and nonlinear unconstrained optimization problems, nonlinear constrained optimization problems are much more difficult. Since the procedure of finding an optimizer is a search based on the local information of the constraints and the objective function, it is very important to develop techniques using geometric properties of the constraints and the objective function. In fact, differential geometry provides a powerful tool to characterize and analyze these geometric properties. Thus, there is clearly a link between the techniques of optimization on manifolds and standard constrained optimization approaches. Furthermore, there are manifolds that are not defined as constrained sets in R^n an important example is the Grassmann manifolds. Hence, to solve optimization problems on these spaces, intrinsic methods are used. In a nondifferentiable problem, the gradient information of the objective function generally cannot be used to determine the direction in which the function is decreasing. Therefore, techniques of nonsmooth analysis are needed to deal with such a problem. As a manifold, in general, does not have a linear structure, the usual techniques, which are often used in nonsmooth analysis on linear spaces, cannot be applied and new techniques need to be developed. This paper presents necessary and sufficient conditions for a strict local minimum of extended real-valued, nonsmooth functions defined on Riemannian manifolds.

Keywords: Riemannian manifolds, nonsmooth optimization, lower semicontinuous functions, subdifferential

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Authors: Mohammad Ruhul Amin, Nusrat Jahan

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Natural gas is a cleaner fuel compared to the others. But it needs some treatment before it is in a state to be used. So natural gas purification is an integral part of any process where natural gas is used as raw material or fuel. There are several impurities in natural gas that have to be removed before use. CO2 is one of the major contaminants. In this project we have removed CO2 by amine process by using MEA solution. We have built up the whole amine process for removing CO2 in Aspen Hysys and simulated the process. At the end of simulation we have got very satisfactory results by using MEA solution for the removal of CO2. Simulation result shows that amine absorption process enables to reduce CO2 content from NG by 58%. HYSYS optimizer allowed us to get a perfect optimized plant. After optimization the profit of existing plant is increased by 2.34 %.Simulation and optimization by Aspen-HYSYS simulator makes available us to enormous information which will help us to further research in future.

Keywords: Aspen–Hysys, CO2 removal, flowsheet development, MEA solution, natural gas optimization

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Authors: Arya Prakash Padhi, Anupam Chakrabarti, Rajib Chowdhury

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Topology or layout optimization often gives better performing economic structures and is very helpful in the conceptual design phase. But traditionally it is being done in finite element-based optimization schemes which, although gives a good result, is very time-consuming especially in 3D structures. Among other alternatives machine learning, especially deep learning-based methods, have a very good potential in resolving this computational issue. Here convolutional neural network (3D-CNN) based variational auto encoder (VAE) is trained using a dataset generated from commercially available topology optimization code ABAQUS Tosca using solid isotropic material with penalization (SIMP) method for compliance minimization. The encoded data in latent space is then fed to a 3D generative adversarial network (3D-GAN) to generate the outcome in 64x64x64 size. Here the network consists of 3D volumetric CNN with rectified linear unit (ReLU) activation in between and sigmoid activation in the end. The proposed network is seen to provide almost optimal results with significantly reduced computational time, as there is no iteration involved.

Keywords: 3D generative adversarial network, deep learning, structural topology optimization, variational auto encoder

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Authors: Julius M. Ndambuki, Gislar E. Kifanyi, Samuel N. Odai, Charles Gyamfi

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Conjunctive management of surface and groundwater resources is a challenging task due to the spatial and temporal variability nature of hydrology as well as hydrogeology of the water storage systems. Surface water-groundwater hydrogeology is highly uncertain; thus it is imperative that this uncertainty is explicitly accounted for, when managing water resources. Various methodologies have been developed and applied by researchers in an attempt to account for the uncertainty. For example, simulation-optimization models are often used for conjunctive water resources management. However, direct application of such an approach in which all realizations are considered at each iteration of the optimization process leads to a very expensive optimization in terms of computational time, particularly when the number of realizations is large. The aim of this paper, therefore, is to introduce and apply an efficient approach referred to as Retrospective Optimization Approximation (ROA) that can be used for optimizing conjunctive use of surface water and groundwater over a multiple hydrogeological model simulations. This work is based on stochastic simulation-optimization framework using a recently emerged technique of sample average approximation (SAA) which is a sampling based method implemented within the Retrospective Optimization Approximation (ROA) approach. The ROA approach solves and evaluates a sequence of generated optimization sub-problems in an increasing number of realizations (sample size). Response matrix technique was used for linking simulation model with optimization procedure. The k-means clustering sampling technique was used to map the realizations. The methodology is demonstrated through the application to a hypothetical example. In the example, the optimization sub-problems generated were solved and analysed using “Active-Set” core optimizer implemented under MATLAB 2014a environment. Through k-means clustering sampling technique, the ROA – Active Set procedure was able to arrive at a (nearly) converged maximum expected total optimal conjunctive water use withdrawal rate within a relatively few number of iterations (6 to 7 iterations). Results indicate that the ROA approach is a promising technique for optimizing conjunctive water use of surface water and groundwater withdrawal rates under hydrogeological uncertainty.

Keywords: conjunctive water management, retrospective optimization approximation approach, sample average approximation, uncertainty

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Authors: Tomoaki Hashimoto

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In recent decades, probabilistic constrained optimal control problems have attracted much attention in many research field. Although probabilistic constraints are generally intractable in an optimization problem, several tractable methods haven been proposed to handle probabilistic constraints. In most methods, probabilistic constraints are reduced to deterministic constraints that are tractable in an optimization problem. However, there is a gap between the transformed deterministic constraints in case of known and unknown probability distribution. This paper examines the conservativeness of probabilistic constrained optimization method with the unknown probability distribution. The objective of this paper is to provide a quantitative assessment of the conservatism for tractable constraints in probabilistic constrained optimization with the unknown probability distribution.

Keywords: optimal control, stochastic systems, discrete time systems, probabilistic constraints

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Authors: Martha C. Orazulume, Jibril D. Jiya

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Flexible satellites are equipped with various appendages which vibrate under the influence of any excitation and make the attitude of the satellite to be unstable. Therefore, the system must be able to adjust to balance the effect of these appendages in order to point accurately and satisfactorily which is one of the most important problems in satellite design. Proportional Integral Derivative (PID) Controller is simple to design and computationally efficient to implement which is used to stabilize the effect of these flexible appendages. However, manual turning of the PID is time consuming, waste energy and money. Particle Swarm Optimization (PSO) is used to tune the parameters of PID Controller. Simulation results obtained show that PSO tuned PID Controller is able to re-orient the spacecraft attitude as well as dampen the effect of mechanical resonance and yields better performance when compared with manually tuned PID Controller.

Keywords: Attitude Control, Flexible Satellite, Particle Swarm Optimization, PID Controller and Optimization

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Authors: Akram Mahdaviparsa, Tamera McCuen, Vahideh Karimimansoob

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Fire service is responsible for protecting life, assets, and natural resources from fire and other hazardous incidents. Search and rescue in unfamiliar buildings is a vital part of firefighters’ responsibilities. Providing firefighters with precise building information in an easy-to-understand format is a potential solution for mitigating the negative consequences of fire hazards. The negative effect of insufficient knowledge about a building’s indoor environment impedes firefighters’ capabilities and leads to lost property. A data rich building information modeling (BIM) is a potentially useful source in three-dimensional (3D) visualization and data/information storage for fire emergency response. Therefore, this research’s purpose is prioritizing the required information for firefighters from the most important information to the least important. A survey was carried out with firefighters working in the Norman Fire Department to obtain the importance of each building information item. The results show that “the location of exit doors, windows, corridors, elevators, and stairs”, “material of building elements”, and “building data” are the three most important information specified by firefighters. The results also implied that the 2D model of architectural, structural and way finding is more understandable in comparison with the 3D model, while the 3D model of MEP system could convey more information than the 2D model. Furthermore, color in visualization can help firefighters to understand the building information easier and quicker. Sufficient internal consistency of all responses was proven through developing the Pearson Correlation Matrix and obtaining Cronbach’s alpha of 0.916. Therefore, the results of this study are reliable and could be applied to the population.

Keywords: BIM, building fire response, ranking, visualization

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Authors: Totok R. Biyanto, Arif T. Mardianto, M. Farid R. R., Luthfi Machmudi, kandi mulakasti

Abstract:

The main objective of this research is optimizing the electrocoagulation process design as a post-treatment for biologically vinasse effluent process. The first principle model with three independent variables that affect the energy consumption of electrocoagulation process i.e. current density, electrode distance, and time of treatment process are chosen as optimized variables. The process condition parameters were determined with the value of pH, electrical conductivity, and temperature of vinasse about 6.5, 28.5 mS/cm, 52 oC, respectively. Aluminum was chosen as the electrode material of electrocoagulation process. Duelist algorithm was used as optimization technique due to its capability to reach a global optimum. The optimization results show that the optimal process can be reached in the conditions of current density of 2.9976 A/m2, electrode distance of 1.5 cm and electrolysis time of 119 min. The optimized energy consumption during process is 34.02 Wh.

Keywords: optimization, vinasse effluent, electrocoagulation, energy consumption

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Authors: Maria Kountouridou, Dino Domic

Abstract:

Within an increasingly competitive and dynamic environment, the higher education sector is becoming more commodified, with the concept of branding to become exceedingly imperative and an inextricable ingredient for the university’s success. Branding in higher education has proven to be an effective strategy that managed to receive considerable attention in the recent few years, and a growing number of articles have begun to appear in the literature. However, a clear void in the literature confirms that the concept of students’ perceptions towards the university’s brand image has not been researched extensively. An investigation on this central concept is of paramount importance since it will facilitate the development of an inductively generated theoretical model concerning branding in higher education. This research focuses on examining the impact of the ‘positive-visualization-course in brand identity’ upon the perception of freshmen students towards a university’s brand image. A grounded theory methodology has been selected, consisting of semi-structured interviews. Forty-two students have participated in the research, among which twenty-five women and seventeen men. The identification of the sample emerged through the use of the snowball sampling technique. The participants were divided into two groups (experimental and control group) after the researcher had taken into consideration the factor ‘program of study’, to eliminate any possible interaction between the participants of each group. An experiment was carried out where a ‘positive-visualization-course in brand identity’ was conducted among the participants of the experimental group, while the participants of the control group have not been exposed to the course. For the purpose of this research, the term ‘positive-visualization-course in brand identity’ refers to a course where brand history, past achievements/recognitions/awards, its values, and its mission are presented. Prior to the course implementation, face-to-face semi-structured interviews were carried out among the participants of both groups, with the aim of examining the freshmen students’ perceptions towards the university’s brand image. One week after the course implementation, the researcher carried out semi-structured interviews with the participants of the experimental group only in order to identify whether students’ perceptions had been affected after the course completion. Four months after the course completion, semi-structured interviews were carried out among the participants of both groups. Eight months after the course completion, semi-structured interviews were conducted with the aim of identifying the freshmen students’ updated perceptions. Data has been analyzed using substantive coding (open and selective coding), theoretical coding, field memos, and constant comparative analysis. The findings strongly suggest that the ‘positive-visualization-course in brand identity’ can positively affect freshmen students’ perceptions towards a university’s brand image. Additionally, other factors conduce to the formation of perception throughout the months. This study contributes and expands upon the existing literature by presenting an inductively generated theoretical model to guide future research in the links between ‘positive-visualization-course in brand identity’ and the perception of freshmen students towards a university’s brand image.

Keywords: brand image, brand name, branding, higher education marketing, perception

Procedia PDF Downloads 155