Search results for: reduce order aeroelastic model (ROAM)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30587

Search results for: reduce order aeroelastic model (ROAM)

30077 Response Delay Model: Bridging the Gap in Urban Fire Disaster Response System

Authors: Sulaiman Yunus

Abstract:

The need for modeling response to urban fire disaster cannot be over emphasized, as recurrent fire outbreaks have gutted most cities of the world. This necessitated the need for a prompt and efficient response system in order to mitigate the impact of the disaster. Promptness, as a function of time, is seen to be the fundamental determinant for efficiency of a response system and magnitude of a fire disaster. Delay, as a result of several factors, is one of the major determinants of promptgness of a response system and also the magnitude of a fire disaster. Response Delay Model (RDM) intends to bridge the gap in urban fire disaster response system through incorporating and synchronizing the delay moments in measuring the overall efficiency of a response system and determining the magnitude of a fire disaster. The model identified two delay moments (pre-notification and Intra-reflex sequence delay) that can be elastic and collectively plays a significant role in influencing the efficiency of a response system. Due to variation in the elasticity of the delay moments, the model provides for measuring the length of delays in order to arrive at a standard average delay moment for different parts of the world, putting into consideration geographic location, level of preparedness and awareness, technological advancement, socio-economic and environmental factors. It is recommended that participatory researches should be embarked on locally and globally to determine standard average delay moments within each phase of the system so as to enable determining the efficiency of response systems and predicting fire disaster magnitudes.

Keywords: delay moment, fire disaster, reflex sequence, response, response delay moment

Procedia PDF Downloads 201
30076 A Simulation Model and Parametric Study of Triple-Effect Desalination Plant

Authors: Maha BenHamad, Ali Snoussi, Ammar Ben Brahim

Abstract:

A steady-state analysis of triple-effect thermal vapor compressor desalination unit was performed. A mathematical model based on mass, salinity and energy balances is developed. The purpose of this paper is to develop a connection between process simulator and process optimizer in order to study the influence of several operating variables on the performance and the produced water cost of the unit. A MATLAB program is used to solve the model equations, and Aspen HYSYS is used to model the plant. The model validity is examined against a commercial plant and showed a good agreement between industrial data and simulations results. Results show that the pressures of the last effect and the compressed vapor have an important influence on the produced cost, and the increase of the difference temperature in the condenser decreases the specific heat area about 22%.

Keywords: steady-state, triple effect, thermal vapor compressor, Matlab, Aspen Hysys

Procedia PDF Downloads 168
30075 Modified Genome-Scale Metabolic Model of Escherichia coli by Adding Hyaluronic Acid Biosynthesis-Related Enzymes (GLMU2 and HYAD) from Pasteurella multocida

Authors: P. Pasomboon, P. Chumnanpuen, T. E-kobon

Abstract:

Hyaluronic acid (HA) consists of linear heteropolysaccharides repeat of D-glucuronic acid and N-acetyl-D-glucosamine. HA has various useful properties to maintain skin elasticity and moisture, reduce inflammation, and lubricate the movement of various body parts without causing immunogenic allergy. HA can be found in several animal tissues as well as in the capsule component of some bacteria including Pasteurella multocida. This study aimed to modify a genome-scale metabolic model of Escherichia coli using computational simulation and flux analysis methods to predict HA productivity under different carbon sources and nitrogen supplement by the addition of two enzymes (GLMU2 and HYAD) from P. multocida to improve the HA production under the specified amount of carbon sources and nitrogen supplements. Result revealed that threonine and aspartate supplement raised the HA production by 12.186%. Our analyses proposed the genome-scale metabolic model is useful for improving the HA production and narrows the number of conditions to be tested further.

Keywords: Pasteurella multocida, Escherichia coli, hyaluronic acid, genome-scale metabolic model, bioinformatics

Procedia PDF Downloads 119
30074 Numerical Analysis of the Turbulent Flow around DTMB 4119 Marine Propeller

Authors: K. Boumediene, S. E. Belhenniche

Abstract:

This article presents a numerical analysis of a turbulent flow past DTMB 4119 marine propeller by the means of RANS approach; the propeller designed at David Taylor Model Basin in USA. The purpose of this study is to predict the hydrodynamic performance of the marine propeller, it aims also to compare the results obtained with the experiment carried out in open water tests; a periodical computational domain was created to reduce the unstructured mesh size generated. The standard kw turbulence model for the simulation is selected; the results were in a good agreement. Therefore, the errors were estimated respectively to 1.3% and 5.9% for KT and KQ.

Keywords: propeller flow, CFD simulation, RANS, hydrodynamic performance

Procedia PDF Downloads 487
30073 The Onset of Ironing during Casing Expansion

Authors: W. Assaad, D. Wilmink, H. R. Pasaribu, H. J. M. Geijselaers

Abstract:

Shell has developed a mono-diameter well concept for oil and gas wells as opposed to the traditional telescopic well design. A Mono-diameter well design allows well to have a single inner diameter from the surface all the way down to reservoir to increase production capacity, reduce material cost and reduce environmental footprint. This is achieved by expansion of liners (casing string) concerned using an expansion tool (e.g. a cone). Since the well is drilled in stages and liners are inserted to support the borehole, overlap sections between consecutive liners exist which should be expanded. At overlap, the previously inserted casing which can be expanded or unexpanded is called the host casing and the newly inserted casing is called the expandable casing. When the cone enters the overlap section, an expandable casing is expanded against a host casing, a cured cement layer and formation. In overlap expansion, ironing or lengthening may appear instead of shortening in the expandable casing when the pressure exerted by the host casing, cured cement layer and formation exceeds a certain limit. This pressure is related to cement strength, thickness of cement layer, host casing material mechanical properties, host casing thickness, formation type and formation strength. Ironing can cause implications that hinder the deployment of the technology. Therefore, the understanding of ironing becomes essential. A physical model is built in-house to calculate expansion forces, stresses, strains and post expansion casing dimensions under different conditions. In this study, only free casing and overlap expansion of two casings are addressed while the cement and formation will be incorporated in future study. Since the axial strain can be predicted by the physical model, the onset of ironing can be confirmed. In addition, this model helps in understanding ironing and the parameters influencing it. Finally, the physical model is validated with Finite Element (FE) simulations and small-scale experiments. The results of the study confirm that high pressure leads to ironing when the casing is expanded in tension mode.

Keywords: casing expansion, cement, formation, metal forming, plasticity, well design

Procedia PDF Downloads 174
30072 The Case for Strategic Participation: How Facilitated Engagement Can Be Shown to Reduce Resistance and Improve Outcomes Through the Use of Strategic Models

Authors: Tony Mann

Abstract:

This paper sets out the case for involving and engaging employees/workers/stakeholders/staff in any significant change that is being considered by the senior executives of the organization. It establishes the rationale, the approach, the methodology of engagement and the benefits of a participative approach. It challenges the new norm of imposing change for fear of resistance and instead suggests that involving people has better outcomes and a longer-lasting impact. Various strategic models are introduced and illustrated to explain how the process can be most effective. The paper highlights one model in particular (the Process Iceberg® Organizational Change model) that has proven to be instrumental in developing effective change. Its use is demonstrated in its various forms and explains why so much change fails to address the key elements and how we can be more productive in managing change. ‘Participation’ in change is too often seen as negative, expensive and unwieldy. The paper aims to show that another model: UIA=O+E, can offset the difficulties and, in fact, produce much more positive and effective change.

Keywords: facilitation, stakeholders, buy-in, digital workshops

Procedia PDF Downloads 96
30071 An ALM Matrix Completion Algorithm for Recovering Weather Monitoring Data

Authors: Yuqing Chen, Ying Xu, Renfa Li

Abstract:

The development of matrix completion theory provides new approaches for data gathering in Wireless Sensor Networks (WSN). The existing matrix completion algorithms for WSN mainly consider how to reduce the sampling number without considering the real-time performance when recovering the data matrix. In order to guarantee the recovery accuracy and reduce the recovery time consumed simultaneously, we propose a new ALM algorithm to recover the weather monitoring data. A lot of experiments have been carried out to investigate the performance of the proposed ALM algorithm by using different parameter settings, different sampling rates and sampling models. In addition, we compare the proposed ALM algorithm with some existing algorithms in the literature. Experimental results show that the ALM algorithm can obtain better overall recovery accuracy with less computing time, which demonstrate that the ALM algorithm is an effective and efficient approach for recovering the real world weather monitoring data in WSN.

Keywords: wireless sensor network, matrix completion, singular value thresholding, augmented Lagrange multiplier

Procedia PDF Downloads 378
30070 Controlled Release of Glucosamine from Pluronic-Based Hydrogels for the Treatment of Osteoarthritis

Authors: Papon Thamvasupong, Kwanchanok Viravaidya-Pasuwat

Abstract:

Osteoarthritis affects a lot of people worldwide. Local injection of glucosamine is one of the alternative treatment methods to replenish the natural lubrication of cartilage. However, multiple injections can potentially lead to possible bacterial infection. Therefore, a drug delivery system is desired to reduce the frequencies of injections. A hydrogel is one of the delivery systems that can control the release of drugs. Thermo-reversible hydrogels can be beneficial to the drug delivery system especially in the local injection route because this formulation can change from liquid to gel after getting into human body. Once the gel is in the body, it will slowly release the drug in a controlled manner. In this study, various formulations of Pluronic-based hydrogels were synthesized for the controlled release of glucosamine. One of the challenges of the Pluronic controlled release system is its fast dissolution rate. To overcome this problem, alginate and calcium sulfate (CaSO4) were added to the polymer solution. The characteristics of the hydrogels were investigated including the gelation temperature, gelation time, hydrogel dissolution and glucosamine release mechanism. Finally, a mathematical model of glucosamine release from Pluronic-alginate-hyaluronic acid hydrogel was developed. Our results have shown that crosslinking Pluronic gel with alginate did not significantly extend the dissolution rate of the gel. Moreover, the gel dissolution profiles and the glucosamine release mechanisms were best described using the zeroth-order kinetic model, indicating that the release of glucosamine was primarily governed by the gel dissolution.

Keywords: controlled release, drug delivery system, glucosamine, pluronic, thermoreversible hydrogel

Procedia PDF Downloads 265
30069 Comparison of Wake Oscillator Models to Predict Vortex-Induced Vibration of Tall Chimneys

Authors: Saba Rahman, Arvind K. Jain, S. D. Bharti, T. K. Datta

Abstract:

The present study compares the semi-empirical wake-oscillator models that are used to predict vortex-induced vibration of structures. These models include those proposed by Facchinetti, Farshidian, and Dolatabadi, and Skop and Griffin. These models combine a wake oscillator model resembling the Van der Pol oscillator model and a single degree of freedom oscillation model. In order to use these models for estimating the top displacement of chimneys, the first mode vibration of the chimneys is only considered. The modal equation of the chimney constitutes the single degree of freedom model (SDOF). The equations of the wake oscillator model and the SDOF are simultaneously solved using an iterative procedure. The empirical parameters used in the wake-oscillator models are estimated using a newly developed approach, and response is compared with experimental data, which appeared comparable. For carrying out the iterative solution, the ode solver of MATLAB is used. To carry out the comparative study, a tall concrete chimney of height 210m has been chosen with the base diameter as 28m, top diameter as 20m, and thickness as 0.3m. The responses of the chimney are also determined using the linear model proposed by E. Simiu and the deterministic model given in Eurocode. It is observed from the comparative study that the responses predicted by the Facchinetti model and the model proposed by Skop and Griffin are nearly the same, while the model proposed by Fashidian and Dolatabadi predicts a higher response. The linear model without considering the aero-elastic phenomenon provides a less response as compared to the non-linear models. Further, for large damping, the prediction of the response by the Euro code is relatively well compared to those of non-linear models.

Keywords: chimney, deterministic model, van der pol, vortex-induced vibration

Procedia PDF Downloads 214
30068 Control-Oriented Enhanced Zero-Dimensional Two-Zone Combustion Modelling of Internal Combustion Engines

Authors: Razieh Arian, Hadi Adibi-Asl

Abstract:

This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine

Procedia PDF Downloads 334
30067 BIM-Based Tool for Sustainability Assessment and Certification Documents Provision

Authors: Taki Eddine Seghier, Mohd Hamdan Ahmad, Yaik-Wah Lim, Samuel Opeyemi Williams

Abstract:

The assessment of building sustainability to achieve a specific green benchmark and the preparation of the required documents in order to receive a green building certification, both are considered as major challenging tasks for green building design team. However, this labor and time-consuming process can take advantage of the available Building Information Modeling (BIM) features such as material take-off and scheduling. Furthermore, the workflow can be automated in order to track potentially achievable credit points and provide rating feedback for several design options by using integrated Visual Programing (VP) to handle the stored parameters within the BIM model. Hence, this study proposes a BIM-based tool that uses Green Building Index (GBI) rating system requirements as a unique input case to evaluate the building sustainability in the design stage of the building project life cycle. The tool covers two key models for data extraction, firstly, a model for data extraction, calculation and the classification of achievable credit points in a green template, secondly, a model for the generation of the required documents for green building certification. The tool was validated on a BIM model of residential building and it serves as proof of concept that building sustainability assessment of GBI certification can be automatically evaluated and documented through BIM.

Keywords: green building rating system, GBRS, building information modeling, BIM, visual programming, VP, sustainability assessment

Procedia PDF Downloads 319
30066 Krembo Wings Youth Movement for Children with and without Disabilities: An Inclusive Model from an Educational Perspective to a Professional Approach

Authors: Claudia Koby, Merav Boaz, Meirav Zaiger Kober

Abstract:

Krembo Wings is an all-inclusive youth movement which brings children and youth with any disability together with their able-bodied peers (counselors) for weekly fun and educational social activities. Krembo Wings utilizes a socio-educational framework to create and lead social change through members with and without disabilities. All the work that Krembo Wings engages in stems from its central goal of promoting inclusion and integration using social and psychological theories to develop its unique model and approach. The key to Krembo Wings' approach in promoting inclusion is active participation – each member, with and without disabilities, is enabled to participate to their fullest capacity in the youth movement and its activities. In order for this to be achieved, all activities are adjustable and are modified to fit the abilities of each member. Additionally, youth counselors – most of whom are members without disabilities – go through extensive training in order to act as 'intermediaries' for their partner with disabilities, enabling and facilitating their partner's participation in a way that allows them to be as independent and active as possible. The relationship is one of friendship and not of caretaking. There is always a nurse on-hand to tend to any caretaking needs. Two essential elements of Krembo Wings' model is the broadening of concepts – shifting and changing the understanding of certain concepts such as what it means to be 'independent' or 'able' – and the development of a unique language – creating a language which both reflects and shapes reality. These elements of Krembo Wings' model foster the development of the values of acceptance and appreciation of those who are 'different'. It instills in members and counselors a new way of perceiving the world, one in which inclusion and integration are achievable and natural. Krembo Wings is certain that implementation of this model will promote the participation and inclusion of individuals with disabilities in society while promoting diversity. This model can serve as a platform which can be replicated and adjusted to suit any environment.

Keywords: innovative model for inclusion, socio-educational movement, youth leadership, youth with and without disabilities

Procedia PDF Downloads 121
30065 A Non-Linear Eddy Viscosity Model for Turbulent Natural Convection in Geophysical Flows

Authors: J. P. Panda, K. Sasmal, H. V. Warrior

Abstract:

Eddy viscosity models in turbulence modeling can be mainly classified as linear and nonlinear models. Linear formulations are simple and require less computational resources but have the disadvantage that they cannot predict actual flow pattern in complex geophysical flows where streamline curvature and swirling motion are predominant. A constitutive equation of Reynolds stress anisotropy is adopted for the formulation of eddy viscosity including all the possible higher order terms quadratic in the mean velocity gradients, and a simplified model is developed for actual oceanic flows where only the vertical velocity gradients are important. The new model is incorporated into the one dimensional General Ocean Turbulence Model (GOTM). Two realistic oceanic test cases (OWS Papa and FLEX' 76) have been investigated. The new model predictions match well with the observational data and are better in comparison to the predictions of the two equation k-epsilon model. The proposed model can be easily incorporated in the three dimensional Princeton Ocean Model (POM) to simulate a wide range of oceanic processes. Practically, this model can be implemented in the coastal regions where trasverse shear induces higher vorticity, and for prediction of flow in estuaries and lakes, where depth is comparatively less. The model predictions of marine turbulence and other related data (e.g. Sea surface temperature, Surface heat flux and vertical temperature profile) can be utilized in short term ocean and climate forecasting and warning systems.

Keywords: Eddy viscosity, turbulence modeling, GOTM, CFD

Procedia PDF Downloads 194
30064 Development of a Model Based on Wavelets and Matrices for the Treatment of Weakly Singular Partial Integro-Differential Equations

Authors: Somveer Singh, Vineet Kumar Singh

Abstract:

We present a new model based on viscoelasticity for the Non-Newtonian fluids.We use a matrix formulated algorithm to approximate solutions of a class of partial integro-differential equations with the given initial and boundary conditions. Some numerical results are presented to simplify application of operational matrix formulation and reduce the computational cost. Convergence analysis, error estimation and numerical stability of the method are also investigated. Finally, some test examples are given to demonstrate accuracy and efficiency of the proposed method.

Keywords: Legendre Wavelets, operational matrices, partial integro-differential equation, viscoelasticity

Procedia PDF Downloads 328
30063 A Model of Knowledge Management Culture Change

Authors: Reza Davoodi, Hamid Abbasi, Heidar Norouzi, Gholamabbas Alipourian

Abstract:

A dynamic model shaping a process of knowledge management (KM) culture change is suggested. It is aimed at providing effective KM of employees for obtaining desired results in an organization. The essential requirements for obtaining KM culture change are determined. The proposed model realizes these requirements. Dynamics of the model are expressed by a change of its parameters. It is adjusted to the dynamic process of KM culture change. Building the model includes elaboration and integration of interconnected components. The “Result” is a central component of the model. This component determines a desired organizational goal and possible directions of its attainment. The “Confront” component engenders constructive confrontation in an organization. For this reason, the employees are prompted toward KM culture change with the purpose of attaining the desired result. The “Assess” component realizes complex assessments of employee proposals by management and peers. The proposals are directed towards attaining the desired result in an organization. The “Reward” component sets the order of assigning rewards to employees based on the assessments of their proposals.

Keywords: knowledge management, organizational culture change, employee, result

Procedia PDF Downloads 402
30062 Second Order Statistics of Dynamic Response of Structures Using Gamma Distributed Damping Parameters

Authors: Badreddine Chemali, Boualem Tiliouine

Abstract:

This article presents the main results of a numerical investigation on the uncertainty of dynamic response of structures with statistically correlated random damping Gamma distributed. A computational method based on a Linear Statistical Model (LSM) is implemented to predict second order statistics for the response of a typical industrial building structure. The significance of random damping with correlated parameters and its implications on the sensitivity of structural peak response in the neighborhood of a resonant frequency are discussed in light of considerable ranges of damping uncertainties and correlation coefficients. The results are compared to those generated using Monte Carlo simulation techniques. The numerical results obtained show the importance of damping uncertainty and statistical correlation of damping coefficients when obtaining accurate probabilistic estimates of dynamic response of structures. Furthermore, the effectiveness of the LSM model to efficiently predict uncertainty propagation for structural dynamic problems with correlated damping parameters is demonstrated.

Keywords: correlated random damping, linear statistical model, Monte Carlo simulation, uncertainty of dynamic response

Procedia PDF Downloads 275
30061 Hyper Parameter Optimization of Deep Convolutional Neural Networks for Pavement Distress Classification

Authors: Oumaima Khlifati, Khadija Baba

Abstract:

Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

Procedia PDF Downloads 82
30060 SQL Generator Based on MVC Pattern

Authors: Chanchai Supaartagorn

Abstract:

Structured Query Language (SQL) is the standard de facto language to access and manipulate data in a relational database. Although SQL is a language that is simple and powerful, most novice users will have trouble with SQL syntax. Thus, we are presenting SQL generator tool which is capable of translating actions and displaying SQL commands and data sets simultaneously. The tool was developed based on Model-View-Controller (MVC) pattern. The MVC pattern is a widely used software design pattern that enforces the separation between the input, processing, and output of an application. Developers take full advantage of it to reduce the complexity in architectural design and to increase flexibility and reuse of code. In addition, we use White-Box testing for the code verification in the Model module.

Keywords: MVC, relational database, SQL, White-Box testing

Procedia PDF Downloads 414
30059 Evaluating the Terrace Benefits of Erosion in a Terraced-Agricultural Watershed for Sustainable Soil and Water Conservation

Authors: Sitarrine Thongpussawal, Hui Shao, Clark Gantzer

Abstract:

Terracing is a conservation practice to reduce erosion and widely used for soil and water conservation throughout the world but is relatively expensive. A modification of the Soil and Water Assessment Tool (called SWAT-Terrace or SWAT-T) explicitly aims to improve the simulation of the hydrological process of erosion from the terraces. SWAT-T simulates erosion from the terraces by separating terraces into three segments instead of evaluating the entire terrace. The objective of this work is to evaluate the terrace benefits on erosion from the Goodwater Creek Experimental Watershed (GCEW) at watershed and Hydrologic Response Unit (HRU) scales using SWAT-T. The HRU is the smallest spatial unit of the model, which lumps all similar land uses, soils, and slopes within a sub-basin. The SWAT-T model was parameterized for slope length, steepness and the empirical Universal Soil Erosion Equation support practice factor for three terrace segments. Data from 1993-2010 measured at the watershed outlet were used to evaluate the models for calibration and validation. Results of SWAT-T calibration showed good performance between measured and simulated erosion for the monthly time step, but poor performance for SWAT-T validation. This is probably because of large storms in spring 2002 that prevented planting, causing poorly simulated scheduling of actual field operations. To estimate terrace benefits on erosion, models were compared with and without terraces. Results showed that SWAT-T showed significant ~3% reduction in erosion (Pr <0.01) at the watershed scale and ~12% reduction in erosion at the HRU scale. Studies using the SWAT-T model indicated that the terraces have advantages to reduce erosion from terraced-agricultural watersheds. SWAT-T can be used in the evaluation of erosion to sustainably conserve the soil and water.

Keywords: Erosion, Modeling, Terraces, SWAT

Procedia PDF Downloads 197
30058 Order Optimization of a Telecommunication Distribution Center through Service Lead Time

Authors: Tamás Hartványi, Ferenc Tóth

Abstract:

European telecommunication distribution center performance is measured by service lead time and quality. Operation model is CTO (customized to order) namely, a high mix customization of telecommunication network equipment and parts. CTO operation contains material receiving, warehousing, network and server assembly to order and configure based on customer specifications. Variety of the product and orders does not support mass production structure. One of the success factors to satisfy customer is to have a proper aggregated planning method for the operation in order to have optimized human resources and highly efficient asset utilization. Research will investigate several methods and find proper way to have an order book simulation where practical optimization problem may contain thousands of variables and the simulation running times of developed algorithms were taken into account with high importance. There are two operation research models that were developed, customer demand is given in orders, no change over time, customer demands are given for product types, and changeover time is constant.

Keywords: CTO, aggregated planning, demand simulation, changeover time

Procedia PDF Downloads 261
30057 Analytics Model in a Telehealth Center Based on Cloud Computing and Local Storage

Authors: L. Ramirez, E. Guillén, J. Sánchez

Abstract:

Some of the main goals about telecare such as monitoring, treatment, telediagnostic are deployed with the integration of applications with specific appliances. In order to achieve a coherent model to integrate software, hardware, and healthcare systems, different telehealth models with Internet of Things (IoT), cloud computing, artificial intelligence, etc. have been implemented, and their advantages are still under analysis. In this paper, we propose an integrated model based on IoT architecture and cloud computing telehealth center. Analytics module is presented as a solution to control an ideal diagnostic about some diseases. Specific features are then compared with the recently deployed conventional models in telemedicine. The main advantage of this model is the availability of controlling the security and privacy about patient information and the optimization on processing and acquiring clinical parameters according to technical characteristics.

Keywords: analytics, telemedicine, internet of things, cloud computing

Procedia PDF Downloads 318
30056 Development of a Numerical Model to Predict Wear in Grouted Connections for Offshore Wind Turbine Generators

Authors: Paul Dallyn, Ashraf El-Hamalawi, Alessandro Palmeri, Bob Knight

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In order to better understand the long term implications of the grout wear failure mode in large-diameter plain-sided grouted connections, a numerical model has been developed and calibrated that can take advantage of existing operational plant data to predict the wear accumulation for the actual load conditions experienced over a given period, thus limiting the need for expensive monitoring systems. This model has been derived and calibrated based on site structural condition monitoring (SCM) data and supervisory control and data acquisition systems (SCADA) data for two operational wind turbine generator substructures afflicted with this challenge, along with experimentally derived wear rates.

Keywords: grouted connection, numerical model, offshore structure, wear, wind energy

Procedia PDF Downloads 447
30055 Artificial Intelligence Methods for Returns Expectations in Financial Markets

Authors: Yosra Mefteh Rekik, Younes Boujelbene

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We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

Procedia PDF Downloads 440
30054 Reinforcement Learning for Quality-Oriented Production Process Parameter Optimization Based on Predictive Models

Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Producing faulty products can be costly for manufacturing companies and wastes resources. To reduce scrap rates in manufacturing, process parameters can be optimized using machine learning. Thus far, research mainly focused on optimizing specific processes using traditional algorithms. To develop a framework that enables real-time optimization based on a predictive model for an arbitrary production process, this study explores the application of reinforcement learning (RL) in this field. Based on a thorough review of literature about RL and process parameter optimization, a model based on maximum a posteriori policy optimization that can handle both numerical and categorical parameters is proposed. A case study compares the model to state–of–the–art traditional algorithms and shows that RL can find optima of similar quality while requiring significantly less time. These results are confirmed in a large-scale validation study on data sets from both production and other fields. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, production process optimization, evolutionary algorithms, policy optimization, actor critic approach

Procedia PDF Downloads 90
30053 Optimization of the Mechanical Performance of Fused Filament Fabrication Parts

Authors: Iván Rivet, Narges Dialami, Miguel Cervera, Michele Chiumenti

Abstract:

Process parameters in Additive Manufacturing (AM) play a critical role in the mechanical performance of the final component. In order to find the input configuration that guarantees the optimal performance of the printed part, the process-performance relationship must be found. Fused Filament Fabrication (FFF) is the selected demonstrative AM technology due to its great popularity in the industrial manufacturing world. A material model that considers the different printing patterns present in a FFF part is used. A voxelized mesh is built from the manufacturing toolpaths described in the G-Code file. An Adaptive Mesh Refinement (AMR) based on the octree strategy is used in order to reduce the complexity of the mesh while maintaining its accuracy. High-fidelity and cost-efficient Finite Element (FE) simulations are performed and the influence of key process parameters in the mechanical performance of the component is analyzed. A robust optimization process based on appropriate failure criteria is developed to find the printing direction that leads to the optimal mechanical performance of the component. The Tsai-Wu failure criterion is implemented due to the orthotropy and heterogeneity constitutive nature of FFF components and because of the differences between the strengths in tension and compression. The optimization loop implements a modified version of an Anomaly Detection (AD) algorithm and uses the computed metrics to obtain the optimal printing direction. The developed methodology is verified with a case study on an industrial demonstrator.

Keywords: additive manufacturing, optimization, printing direction, mechanical performance, voxelization

Procedia PDF Downloads 56
30052 Model Driven Architecture Methodologies: A Review

Authors: Arslan Murtaza

Abstract:

Model Driven Architecture (MDA) is technique presented by OMG (Object Management Group) for software development in which different models are proposed and converted them into code. The main plan is to identify task by using PIM (Platform Independent Model) and transform it into PSM (Platform Specific Model) and then converted into code. In this review paper describes some challenges and issues that are faced in MDA, type and transformation of models (e.g. CIM, PIM and PSM), and evaluation of MDA-based methodologies.

Keywords: OMG, model driven rrchitecture (MDA), computation independent model (CIM), platform independent model (PIM), platform specific model(PSM), MDA-based methodologies

Procedia PDF Downloads 448
30051 NOx Prediction by Quasi-Dimensional Combustion Model of Hydrogen Enriched Compressed Natural Gas Engine

Authors: Anas Rao, Hao Duan, Fanhua Ma

Abstract:

The dependency on the fossil fuels can be minimized by using the hydrogen enriched compressed natural gas (HCNG) in the transportation vehicles. However, the NOx emissions of HCNG engines are significantly higher, and this turned to be its major drawback. Therefore, the study of NOx emission of HCNG engines is a very important area of research. In this context, the experiments have been performed at the different hydrogen percentage, ignition timing, air-fuel ratio, manifold-absolute pressure, load and engine speed. Afterwards, the simulation has been accomplished by the quasi-dimensional combustion model of HCNG engine. In order to investigate the NOx emission, the NO mechanism has been coupled to the quasi-dimensional combustion model of HCNG engine. The three NOx mechanism: the thermal NOx, prompt NOx and N2O mechanism have been used to predict NOx emission. For the validation purpose, NO curve has been transformed into NO packets based on the temperature difference of 100 K for the lean-burn and 60 K for stoichiometric condition. While, the width of the packet has been taken as the ratio of crank duration of the packet to the total burnt duration. The combustion chamber of the engine has been divided into three zones, with the zone equal to the product of summation of NO packets and space. In order to check the accuracy of the model, the percentage error of NOx emission has been evaluated, and it lies in the range of ±6% and ±10% for the lean-burn and stoichiometric conditions respectively. Finally, the percentage contribution of each NO formation has been evaluated.

Keywords: quasi-dimensional combustion , thermal NO, prompt NO, NO packet

Procedia PDF Downloads 245
30050 A New Tactical Optimization Model for Bioenergy Supply Chain

Authors: Birome Holo Ba, Christian Prins, Caroline Prodhon

Abstract:

Optimization is an important aspect of logistics management. It can reduce significantly logistics costs and also be a good tool for decision support. In this paper, we address a planning problem specific to biomass supply chain. We propose a new mixed integer linear programming (MILP) model dealing with different feed stock production operations such as harvesting, packing, storage, pre-processing and transportation, with the objective of minimizing the total logistic cost of the system on a regional basis. It determines the optimal number of harvesting machine, the fleet size of trucks for transportation and the amount of each type of biomass harvested, stored and pre-processed in each period to satisfy demands of refineries in each period. We illustrate the effectiveness of the proposal model with a numerical example, a case study in Aube (France department), which gives preliminary and interesting, results on a small test case.

Keywords: biomass logistics, supply chain, modelling, optimization, bioenergy, biofuels

Procedia PDF Downloads 509
30049 Effectiveness of Variable Speed Limit Signs in Reducing Crash Rates on Roadway Construction Work Zones in Alaska

Authors: Osama Abaza, Tanay Datta Chowdhury

Abstract:

As a driver's speed increases, so do the probability of an incident and likelihood of injury. The presence of equipment, personnel, and a changing landscape in construction zones create greater potential for incident. This is especially concerning in Alaska, where summer construction activity, coinciding with the peak annual traffic volumes, cannot be avoided. In order to reduce vehicular speeding in work zones, and therefore the probability of crash and incident occurrence, variable speed limit (VSL) systems can be implemented in the form of radar speed display trailers since the radar speed display trailers were shown to be effective at reducing vehicular speed in construction zones. Allocation of VSL not only help reduce the 85th percentile speed but also it will predominantly reduce mean speed as well. Total of 2147 incidents along with 385 crashes occurred only in one month around the construction zone in the Alaska which seriously requires proper attention. This research provided a thorough crash analysis to better understand the cause and provide proper countermeasures. Crashes were predominantly recoded as vehicle- object collision and sideswipe type and thus significant amount of crashes fall in the group of no injury to minor injury type in the severity class. But still, 35 major crashes with 7 fatal ones in a one month period require immediate action like the implementation of the VSL system as it proved to be a speed reducer in the construction zone on Alaskan roadways.

Keywords: speed, construction zone, crash, severity

Procedia PDF Downloads 240
30048 Supplier Selection and Order Allocation Using a Stochastic Multi-Objective Programming Model and Genetic Algorithm

Authors: Rouhallah Bagheri, Morteza Mahmoudi, Hadi Moheb-Alizadeh

Abstract:

In this paper, we develop a supplier selection and order allocation multi-objective model in stochastic environment in which purchasing cost, percentage of delivered items with delay and percentage of rejected items provided by each supplier are supposed to be stochastic parameters following any arbitrary probability distribution. To do so, we use dependent chance programming (DCP) that maximizes probability of the event that total purchasing cost, total delivered items with delay and total rejected items are less than or equal to pre-determined values given by decision maker. After transforming the above mentioned stochastic multi-objective programming problem into a stochastic single objective problem using minimum deviation method, we apply a genetic algorithm to get the later single objective problem solved. The employed genetic algorithm performs a simulation process in order to calculate the stochastic objective function as its fitness function. At the end, we explore the impact of stochastic parameters on the given solution via a sensitivity analysis exploiting coefficient of variation. The results show that as stochastic parameters have greater coefficients of variation, the value of objective function in the stochastic single objective programming problem is worsened.

Keywords: dependent chance programming, genetic algorithm, minimum deviation method, order allocation, supplier selection

Procedia PDF Downloads 251