Search results for: reliable facility location model

Authors: Berna Çalışkan

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The integrated water management is a colloborative approach to planning that brings together institutions that influence all elements of the water cycle, waterways, watershed characteristics, wetlands, ponds, lakes, floodplain areas, stream channel structure. It encourages collaboration where it will be beneficial and links between water planning and other planning processes that contribute to improving sustainable urban development and liveability. Hydraulic considerations can influence the selection of a highway corridor and the alternate routes within the corridor. widening a roadway, replacing a culvert, or repairing a bridge. Because of this, the type and amount of data needed for planning studies can vary widely depending on such elements as environmental considerations, class of the proposed highway, state of land use development, and individual site conditions. The extraction of drainage networks provide helpful preliminary drainage data from the digital elevation model (DEM). A case study was carried out using the Arc Hydro extension within ArcGIS in the study area. It provides the means for processing and presenting spatially-referenced Stream Model. Study area’s flow routing, stream levels, segmentation, drainage point processing can be obtained using DEM as the 'Input surface raster'. These processes integrate the fields of hydrologic, engineering research, and environmental modeling in a multi-disciplinary program designed to provide decision makers with a science-based understanding, and innovative tools for, the development of interdisciplinary and multi-level approach. This research helps to manage transport project planning and construction phases to analyze the surficial water flow, high-level streams, wetland sites for development of transportation infrastructure planning, implementing, maintenance, monitoring and long-term evaluations to better face the challenges and solutions associated with effective management and enhancement to deal with Low, Medium, High levels of impact. Transport projects are frequently perceived as critical to the ‘success’ of major urban, metropolitan, regional and/or national development because of their potential to affect significant socio-economic and territorial change. In this context, sustaining and development of economic and social activities depend on having sufficient Water Resources Management. The results of our research provides a workflow to build a stream network how can classify suitability map according to stream levels. Transportation projects establish, develop, incorporate and deliver effectively by selecting best location for reducing construction maintenance costs, cost-effective solutions for drainage, landslide, flood control. According to model findings, field study should be done for filling gaps and checking for errors. In future researches, this study can be extended for determining and preventing possible damage of Sensitive Areas and Vulnerable Zones supported with field investigations.

Keywords: water resources management, hydro tool, water protection, transportation

Procedia PDF Downloads 50

Authors: M. S. Aparna, Pushparaj Shetty D.

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Nowadays social networking sites have become so popular that the producers or the sellers look for these sites as one of the best options to target the right audience to market their products. There are several tools available to monitor or analyze the social networks. Our task is to identify the right community web pages and find out the behavior analysis of the members by using these tools and formulate an appropriate strategy to market the products or services to achieve the set goals. The advertising becomes more effective when the information of the product/ services come from a known source. The strategy explores great buying influence in the audience on referral marketing. Our methodology proceeds with critical budget analysis and promotes viral influence propagation. In this context, we encompass the vital bits of budget evaluation such as the number of optimal seed nodes or primary influential users activated onset, an estimate coverage spread of nodes and maximum influence propagating distance from an initial seed to an end node. Our proposal for Buyer Prediction mathematical model arises from the urge to perform complex analysis when the probability density estimates of reliable factors are not known or difficult to calculate. Order Statistics and Buyer Prediction mapping function guarantee the selection of optimal influential users at each level. We exercise an efficient tactics of practicing community pages and user behavior to determine the product enthusiasts on social networks. Our approach is promising and should be an elementary choice when there is little or no prior knowledge on the distribution of potential buyers on social networks. In this strategy, product news propagates to influential users on or surrounding networks. By applying the same technique, a user can search friends who are capable to advise better or give referrals, if a product interests him.

Keywords: viral marketing, social network analysis, community web pages, buyer prediction, influence propagation, budget constraints

Procedia PDF Downloads 255

Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

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The swift proliferation of telehealth Internet of Things (IoT) devices has sparked concerns regarding energy consumption and the need for streamlined data processing. This paper presents an energy-efficient model that integrates telehealth IoT devices into a platform based on fog and cloud computing. This integrated system provides a sustainable and robust solution to address the challenges. Our model strategically utilizes fog computing as a localized data processing layer and leverages cloud computing for resource-intensive tasks, resulting in a significant reduction in overall energy consumption. The incorporation of adaptive energy-saving strategies further enhances the efficiency of our approach. Simulation analysis validates the effectiveness of our model in improving energy efficiency for telehealth IoT systems, particularly when integrated with localized fog nodes and both private and public cloud infrastructures. Subsequent research endeavors will concentrate on refining the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability across various healthcare and industry sectors.

Keywords: energy-efficient, fog computing, IoT, telehealth

Procedia PDF Downloads 71

Authors: Dana Alghool, Tarek ElMekkawy, Mohamed Haouari, Adel Elomari

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District cooling systems have captured the attentions of many researchers recently due to the enormous benefits offered by such system in comparison with traditional cooling technologies. It is considered a major component of urban cities due to the significant reduction of energy consumption. This paper aims to find the optimal design and operation of district cooling systems by developing a mixed integer linear programming model to minimize the annual total system cost and satisfy the end-user cooling demand. The proposed model is experimented with different cooling demand scenarios. The results of the very high cooling demand scenario are only presented in this paper. A sensitivity analysis on different parameters of the model was performed.

Keywords: Annual Cooling Demand, Compression Chiller, Mathematical Modeling, District Cooling Systems, Optimization

Procedia PDF Downloads 195

Authors: Likewin Thomas, M. V. Manoj Kumar, B. Annappa

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Traditional execution process follows the path of execution drawn by the process analyst without observing the behaviour of resource and other real-time constraints. Identifying process model, predicting the behaviour of resource and recommending the optimal path of execution for a real time process is challenging. The proposed AlfyMiner: αyM iner gives a new dimension in process execution with the novel techniques Process Model Analyser: PMAMiner and Resource behaviour Analyser: RBAMiner for recommending the probable path of execution. PMAMiner discovers next probable activity for currently executing activity in an online process using variant matching technique to identify the set of next probable activity, among which the next probable activity is discovered using decision tree model. RBAMiner identifies the resource suitable for performing the discovered next probable activity and observe the behaviour based on; load and performance using polynomial regression model, and waiting time using queueing theory. Based on the observed behaviour αyM iner recommend the probable path of execution with; next probable activity and the best suitable resource for performing it. Experiments were conducted on process logs of CoSeLoG Project1 and 72% of accuracy is obtained in identifying and recommending next probable activity and the efficiency of resource performance was optimised by 59% by decreasing their load.

Keywords: cross-organization process mining, process behaviour, path of execution, polynomial regression model

Procedia PDF Downloads 329

Authors: Tumisang Seodigeng, Hilary Rutto

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In this study we investigate the use of a laboratory batch digester to derive kinetic parameters for anaerobic digestion of garden grass and cattle dung. Laboratory experimental data from a 5 liter batch digester operating at mesophilic temperature of 32 C is used to derive parameters for Michaelis-Menten kinetic model. These fitted kinetics are further used to predict the scale-up parameters of a batch digester using DynoChem modeling and scale-up software. The scale-up model results are compared with performance data from 20 liter, 50 liter, and 200 liter batch digesters. Michaelis-Menten kinetic model shows to be a very good and easy to use model for kinetic parameter fitting on DynoChem and can accurately predict scale-up performance of 20 liter and 50 liter batch reactor based on parameters fitted on a 5 liter batch reactor.

Keywords: Biogas, kinetics, DynoChem Scale-up, Michaelis-Menten

Procedia PDF Downloads 492

Authors: Abdulrahman H. Alrashidi

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Kuwait Oil Company provides health care services through Ahmadi hospital for oil sector employee and their families. Due to increasing number of entitled patients in Ahmadi hospital, the company starts health insurance option in 2010. In addition, a new Ahmadi hospital decided to build to accumulate all entitled patients. Operation and management of new Ahmadi hospital investigated in this research. In order to maintain the high quality of medical services and satisfaction rate among oil sector community and reducing the operation cost. Six operation and management options evaluated in order to implement in new Ahmadi hospital. Qualitative Risk assessment method used to investigate proposed options for operation and management of new Ahmadi hospital. Evaluation criteria consist of quality of medical services, operation cost and satisfaction rate among oil sector community. Results show that using the same operation and management system in existing Ahmadi hospital with new Ahmadi hospital will bring cost higher. This approach brings risk to KOC. Results from risk assessment show that partially operated new Ahmadi hospital is the best opportunity to meet the objectives of KOC’s medical group.

Keywords: Kuwait Oil Company, new Ahmadi hospital, operation and management, risk assessment

Procedia PDF Downloads 355

Authors: Steffen Schieweck, Johannes Dregger, Sascha Kaczmarek, Michael ten Hompel

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Logistics distributors face the issue of having to provide increasing service levels while being forced to reduce costs at the same time. Same-day delivery, quick order processing and rapidly growing ranges of articles are only some of the prevailing challenges. One key aspect of the performance of an intra-logistics system is how often and in which amplitude congestions and dysfunctions affect the processing operations. By gaining knowledge of the so called ‘performance availability’ of such a system during the planning stage, oversizing and wasting can be reduced whereas planning transparency is increased. State of the art for the determination of this KPI are simulation studies. However, their structure and therefore their results may vary unforeseeably. This article proposes a concept for the establishment of ‘certified’ and hence reliable and comparable simulation models.

Keywords: intra-logistics, performance availability, simulation, warehousing

Procedia PDF Downloads 451

Authors: Ludivine Saint-Mard, Masato Nakajima, Gloria Senfaute

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In areas with low to moderate seismicity, the probabilistic seismic hazard analysis frequently uses a Poisson approach, which assumes independence in time and space of events to determine the annual probability of earthquake occurrence. Nevertheless, in countries with high seismic rate, such as Japan, it is frequently use non-poissonian model which assumes that next earthquake occurrence depends on the date of previous one. The objective of this paper is to apply a non-poissonian models in a region of low to moderate seismicity to get a feedback on the following questions: can we overcome the lack of data to determine some key parameters?, and can we deal with uncertainties to apply largely this methodology on an industrial context?. The Brownian-Passage-Time model was applied to a fault located in France and conclude that even if the lack of data can be overcome with some calculations, the amount of uncertainties and number of scenarios leads to a numerous branches in PSHA, making this method difficult to apply on a large scale of low to moderate seismicity areas and in an industrial context.

Keywords: probabilistic seismic hazard, non-poissonian model, earthquake occurrence, low seismicity

Procedia PDF Downloads 57

Authors: Frederic Schenker, Jonathan J. Hendriks, Gianluca Nicchiotti

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In a product industrialization perspective, the end-product shall always be at the peak of technological advancement and developed in the shortest time possible. Thus, the constant growth of complexity and a shorter time-to-market calls for important changes on both the technical and business level. Undeniably, the common understanding of the system is beclouded by its complexity which leads to the communication gap between the engineers and the sale department. This communication link is therefore important to maintain and increase the information exchange between departments to ensure a punctual and flawless delivery to the end customer. This evolution brings engineers to reason with more hindsight and plan ahead. In this sense, they use new viewpoints to represent the data and to express the model deliverables in an understandable way that the different stakeholder may identify their needs and ideas. This article focuses on the usage of Model-Based System Engineering (MBSE) in a perspective of system industrialization and reconnect the engineering with the sales team. The modeling method used and presented in this paper concentrates on displaying as closely as possible the needs of the customer. Firstly, by providing a technical solution to the sales team to help them elaborate commercial offers without omitting technicalities. Secondly, the model simulates between a vast number of possibilities across a wide range of components. It becomes a dynamic tool for powerful analysis and optimizations. Thus, the model is no longer a technical tool for the engineers, but a way to maintain and solidify the communication between departments using different views of the model. The MBSE contribution to cost optimization during New Product Introduction (NPI) activities is made explicit through the illustration of a case study describing the support provided by system models to architectural choices during the industrialization of a novel optical sensor.

Keywords: analytical model, architecture comparison, MBSE, product industrialization, SysML, system thinking

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Authors: Bunakiye R. Japheth, Ogude U. Cyril

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Since the process of transforming user requirements to modeling constructs are not very well supported by domain-specific frameworks, it became necessary to integrate domain requirements with the specific architectures to achieve an integrated customizable solutions space via artifact orientation. Domain-specific modeling language specifications of model-driven engineering technologies focus more on requirements within a particular domain, which can be tailored to aid the domain expert in expressing domain concepts effectively. Modeling processes through domain-specific language formalisms are highly volatile due to dependencies on domain concepts or used process models. A capable solution is given by artifact orientation that stresses on the results rather than expressing a strict dependence on complicated platforms for model creation and development. Based on this premise, domain-specific methods for producing artifacts without having to take into account the complexity and variability of platforms for model definitions can be integrated to support customizable development. In this paper, we discuss methods for the integration capabilities and necessities within a common structure and semantics that contribute a metamodel for artifact-orientation, which leads to a reusable software layer with concrete syntax capable of determining design intents from domain expert. These concepts forming the language formalism are established from models explained within the oil and gas pipelines industry.

Keywords: control process, metrics of engineering, structured abstraction, semantic model

Procedia PDF Downloads 137

Authors: Kharisma Utomo Mulyodinoto, Suwarno, Ahmed Abu-Siada

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Transformer insulating oil is a key component that can be utilized to detect incipient faults within operating transformers without taking them out of service. Dissolved gas-in-oil analysis has been widely accepted as a powerful technique to detect such incipient faults. While the measurement of dissolved gases within transformer oil samples has been standardized over the past two decades, analysis of the results is not always straightforward as it depends on personnel expertise more than mathematical formulas. In analyzing such data, the generation rate of each dissolved gas is of more concern than the absolute value of the gas. As such, history of dissolved gases within a particular transformer should be archived for future comparison. Lack of such history may lead to misinterpretation of the obtained results. IEEE C57.104-2008 standards have classified the health condition of the transformer based on the absolute value of individual dissolved gases along with the total dissolved combustible gas (TDCG) within transformer oil into 4 conditions. While the technique is easy to implement, it is considered as a very conservative technique and is not widely accepted as a reliable interpretation tool. Moreover, measured gases for the same oil sample can be within various conditions limits and hence, misinterpretation of the data is expected. To overcome this limitation, this paper introduces a fuzzy logic approach to predict the health condition of the transformer oil based on IEEE C57.104-2008 standards along with Roger ratio and IEC ratio-based methods. DGA results of 31 chosen oil samples from 469 transformer oil samples of normal transformers and pre-known fault-type transformers that were collected from Indonesia Electrical Utility Company, PT. PLN (Persero), from different voltage rating: 500/150 kV, 150/20 kV, and 70/20 kV; different capacity: 500 MVA, 60 MVA, 50 MVA, 30 MVA, 20 MVA, 15 MVA, and 10 MVA; and different lifespan, are used to test and establish the fuzzy logic model. Results show that the proposed approach is of good accuracy and can be considered as a platform toward the standardization of the dissolved gas interpretation process.

Keywords: dissolved gas analysis, fuzzy logic, health index, IEEE C57.104-2008, IEC ratio method, Roger ratio method

Procedia PDF Downloads 153

Authors: Jhoga Parth, T. Nasar, K. V. Anand

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An idealized definition of shoreline is that it is the zone of coincidence of three spheres such as atmosphere, lithosphere, and hydrosphere. Despite its apparent simplicity, this definition in practice a challenge to apply. In reality, the shoreline location deviates continually through time, because of various dynamic factors such as wave characteristics, currents, coastal orientation and the bathymetry, which makes the shoreline volatile. This necessitates us to monitor the shoreline in a temporal basis. If shoreline’s nature is understood at particular coastal stretch, it need not be the same trend at the other location, though belonging to the same sea front. Shoreline change is hence a local phenomenon and has to be studied with great intensity considering as many factors involved as possible. Erosion and accretion of sediment are such natures of a shoreline, which needs to be quantified by comparing with its predeceasing variations and understood before implementing any coastal projects. In recent years, advent of Global Positioning System (GPS) and Geographic Information System (GIS) acts as an emerging tool to quantify the intra and inter annual sediment rate getting accreted or deposited compared to other conventional methods in regards with time was taken and man power. Remote sensing data, on the other hand, paves way to acquire historical sets of data where field data is unavailable with a higher resolution. Short term and long term period shoreline change can be accurately tracked and monitored using a software residing in GIS - Digital Shoreline Analysis System (DSAS) developed by United States Geological Survey (USGS). In the present study, using DSAS, End Point Rate (EPR) is calculated analyze the intra-annual changes, and Linear Rate Regression (LRR) is adopted to study inter annual changes of shoreline. The shoreline changes are quantified for the scenario during the construction of breakwater in Ponnani river inlet along Kerala coast, India. Ponnani is a major fishing and landing center located 10°47’12.81”N and 75°54’38.62”E in Malappuram district of Kerala, India. The rate of erosion and accretion is explored using satellite and field data. The full paper contains the rate of change of shoreline, and its analysis would provide us understanding the behavior of the inlet at the study area during the construction of the training walls.

Keywords: DSAS, end point rate, field measurements, geo-informatics, shoreline variation

Procedia PDF Downloads 252

Authors: Ahteshamul Haq, Srikant Gupta, Murshid Kamal, Irfan Ali

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This case study designs and builds a multi-objective production planning model for a hardware firm with certain & uncertain data. During the time of interaction with the manager of the firm, they indicate some of the parameters may be vague. This vagueness in the formulated model is handled by the concept of fuzzy set theory. Triangular & Trapezoidal fuzzy numbers are used to represent the uncertainty in the collected data. The fuzzy nature is de-fuzzified into the crisp form using well-known defuzzification method via graded mean integration representation method. The proposed model attempts to maximize the production of the firm, profit related to the manufactured items & minimize the carrying inventory costs in both certain & uncertain environment. The recommended optimal plan is determined via fuzzy programming approach, and the formulated models are solved by using optimizing software LINGO 16.0 for getting the optimal production plan. The proposed model yields an efficient compromise solution with the overall satisfaction of decision maker.

Keywords: production planning problem, multi-objective optimization, fuzzy programming, fuzzy sets

Procedia PDF Downloads 205

Authors: Emmanuel Iyamuremye, Jean François Maniriho, Irenee Ndayambaje

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Mathematics is the foundational enabling discipline that underpins science, technology, and engineering disciplines. Science, technology, engineering, and mathematics (STEM) subjects are foreseen as the engine for socio-economic transformation. Rwanda has done reforms in education aiming at empowering and preparing students for the real world job by providing career pathways in science, technology, engineering, and mathematics related fields. While that considered so, the performance in mathematics has remained deplorable in both formative and national examinations. Therefore, this paper aims at exploring the extent to which the engage, explore, explain, elaborate and evaluate (5Es) instructional model contributing towards students’ achievement in mathematics. The present study adopted the pre-test, post-test non-equivalent control group quasi-experimental design. The 5Es instructional model was applied to the experimental group while the control group received instruction with the conventional teaching method for eight weeks. One research-made instrument, mathematics achievement test (MAT), was used for data collection. A pre-test was given to students before the intervention to make sure that both groups have equivalent characteristics. At the end of the experimental period, the two groups have undergone a post-test to ascertain the contribution of the 5Es instructional model. Descriptive statistics and analysis of covariance (ANCOVA) were used for the analysis of the study. For determining the improvement in mathematics, Hakes methods of calculating gain were used to analyze the pre-test and post-test scores. Results showed that students exposed to 5Es instructional model achieved significantly better performance in mathematics than students instructed using the conventional teaching method. It was also found that 5Es instructional model made lessons more interesting, easy and created friendship among students. Thus, 5Es instructional model was recommended to be adopted as a close substitute to the conventional teaching method in teaching mathematics in lower secondary schools in Rwanda.

Keywords: 5Es instructional model, achievement, conventional teaching method, mathematics

Procedia PDF Downloads 100

Authors: S. Burgalat, L. Teilhac, A. Brand, E. Chastel, M. Jumeline

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The paper presents actual benefits and drawbacks of a multidirectional autonomous hovercraft conceived with limited resources and designed for indoor exploration. Recent developments in the field have led to the apparition of very powerful automotive systems capable of very high calculation and exploration in complex unknown environments. They usually propose very complex algorithms, high precision/cost sensors and sometimes have heavy calculation consumption with complex data fusion. These systems are usually powerful but have a certain price, and the benefits may not be worth the cost, especially considering their hardware limitations and their power consumption. The present approach is to build a compromise between cost, power consumption and results preciseness.

Keywords: hovercraft, indoor exploration, autonomous, multidirectional, wireless control

Procedia PDF Downloads 270

Authors: Sunantha Teyarachakul

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We consider the worker-learning Newsvendor Model, under the case of lost-sales for unmet demand, with the research objective of proposing the cost-minimization order policy and lot size, scheduled to arrive at the beginning of the selling-period. In general, the New Vendor Model is used to find the optimal order quantity for the perishable items such as fashionable products or those with seasonal demand or short-life cycles. Technically, it is used when the product demand is stochastic and available for the single selling-season, and when there is only a one time opportunity for the vendor to purchase, with possibly of long ordering lead-times. Our work differs from the classical Newsvendor Model in that we incorporate the human factor (specifically worker learning) and its influence over the costs of processing units into the model. We describe this by using the well-known Wright’s Learning Curve. Most of the assumptions of the classical New Vendor Model are still maintained in our work, such as the constant per-unit cost of leftover and shortage, the zero initial inventory, as well as the continuous time. Our problem is challenging in the way that the best order quantity in the classical model, which is balancing the over-stocking and under-stocking costs, is no longer optimal. Specifically, when adding the cost-saving from worker learning to such expected total cost, the convexity of the cost function will likely not be maintained. This has called for a new way in determining the optimal order policy. In response to such challenges, we found a number of characteristics related to the expected cost function and its derivatives, which we then used in formulating the optimal ordering policy. Examples of such characteristics are; the optimal order quantity exists and is unique if the demand follows a Uniform Distribution; if the demand follows the Beta Distribution with some specific properties of its parameters, the second derivative of the expected cost function has at most two roots; and there exists the specific level of lot size that satisfies the first order condition. Our research results could be helpful for analysis of supply chain coordination and of the periodic review system for similar problems.

Keywords: inventory management, Newsvendor model, order policy, worker learning

Procedia PDF Downloads 411

Authors: Ana Corberan-Vallet, Karen C. Florez, Ingrid C. Marino, Jose D. Bermudez

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In 2016, the Region of the Americas was declared free of measles, a viral disease that can cause severe health problems. However, since 2017, measles has reemerged in Venezuela and has subsequently reached neighboring countries. In 2018, twelve American countries reported confirmed cases of measles. Governmental and health authorities in Colombia, a country that shares the longest land boundary with Venezuela, are aware of the need for a strong response to restrict the expanse of the epidemic. In this work, we apply a Bayesian hierarchical Poisson model with an underlying cluster structure to describe disease incidence in Colombia. Concretely, the proposed methodology provides relative risk estimates at the department level and identifies clusters of disease, which facilitates the implementation of targeted public health interventions. Socio-demographic factors, such as the percentage of migrants, gross domestic product, and entry routes, are included in the model to better describe the incidence of disease. Since the model does not impose any spatial correlation at any level of the model hierarchy, it avoids the spatial confounding problem and provides a suitable framework to estimate the fixed-effect coefficients associated with spatially-structured covariates.

Keywords: Bayesian analysis, cluster identification, disease mapping, risk estimation

Procedia PDF Downloads 149

Authors: Harris Niavis, Dimitra Politaki

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The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.

Keywords: blockchain, data quality, industry4.0, product quality

Procedia PDF Downloads 181

Authors: Dheyaa Hussein, Peter Armstrong

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The phenomenon of visual disorder is prominent in contemporary townscapes. This paper provides a theoretical framework for the assessment of visual consistency in townscape in order to achieve more favourable outcomes for users. In this paper, visual consistency refers to the amount of similarity between adjacent components of townscape. The paper investigates parameters which relate to visual consistency in townscape, explores the relationships between them and highlights their significance. The paper uses arithmetic methods from outside the domain of urban design to enable the establishment of an objective approach of assessment which considers subjective indicators including users’ preferences. These methods involve the standard of deviation, colour distance and the distance between points. The paper identifies urban space as a key representative of the visual parameters of townscape. It focuses on its two components, geometry and colour in the evaluation of the visual consistency of townscape. Accordingly, this article proposes four measurements. The first quantifies the number of vertices, which are points in the three-dimensional space that are connected, by lines, to represent the appearance of elements. The second evaluates the visual surroundings of urban space through assessing the location of their vertices. The last two measurements calculate the visual similarity in both vertices and colour in townscape by the calculation of their variation using methods including standard of deviation and colour difference. The proposed quantitative assessment is based on users’ preferences towards these measurements. The paper offers a theoretical basis for a practical tool which can alter the current understanding of architectural form and its application in urban space. This tool is currently under development. The proposed method underpins expert subjective assessment and permits the establishment of a unified framework which adds to creativity by the achievement of a higher level of consistency and satisfaction among the citizens of evolving townscapes.

Keywords: townscape, urban design, visual assessment, visual consistency

Procedia PDF Downloads 308

Authors: Nisha Nandlal Sharma, Julaluk Carmai, Saiprasit Koetniyom, Bernd Markert

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Whiplash Injuries are usually associated with car accidents. The sudden forward or backward jerk to head causes neck strain, which is the result of damage to the muscle or tendons. Neck pain and headaches are the two most common symptoms of whiplash. Symptoms of whiplash are commonly reported in studies but the Injury mechanism is poorly understood. Neck muscles are the most important factor to study the neck Injury. This study focuses on the development of finite element (FE) model of human neck muscle to study the whiplash injury mechanism and effect of active muscle contraction on occupant kinematics. A detailed study of Injury mechanism will promote development and evaluation of new safety systems in cars, hence reducing the occurrence of severe injuries to the occupant. In present study, an active human finite element (FE) model with 3D neck muscle model is developed. Neck muscle was modeled with a combination of solid tetrahedral elements and 1D beam elements. Muscle active properties were represented by beam elements whereas, passive properties by solid tetrahedral elements. To generate muscular force according to inputted activation levels, Hill-type muscle model was applied to beam elements. To simulate non-linear passive properties of muscle, solid elements were modeled with rubber/foam material model. Material properties were assigned from published experimental tests. Some important muscles were then inserted into THUMS (Total Human Model for Safety) 50th percentile male pedestrian model. To reduce the simulation time required, THUMS lower body parts were not included. Posterior to muscle insertion, THUMS was given a boundary conditions similar to experimental tests. The model was exposed to 4g and 7g rear impacts as these load impacts are close to low speed impacts causing whiplash. The effect of muscle activation level on occupant kinematics during whiplash was analyzed.

Keywords: finite element model, muscle activation, neck muscle, whiplash injury prevention

Procedia PDF Downloads 354

Authors: Lovorka Galetic, Zeljko Vukelic

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The advanced concepts of strategic and innovation management in the sphere of company dynamic and innovation capabilities, and achieving their mutual alignment and a synergy effect, are important elements in business today. This paper analyses the theory and empirically investigates the influence of a company’s dynamic capabilities on its innovation capabilities. A new multidimensional model of dynamic capabilities is presented, consisting of five factors appropriate to real time requirements, while innovation capabilities are considered pursuant to the official OECD and Eurostat standards. After examination of dynamic and innovation capabilities indicated their theoretical links, the empirical study testing the model and examining the influence of a company’s dynamic capabilities on its innovation capabilities showed significant results. In the study, a research model was posed to relate company dynamic and innovation capabilities. One side of the model features the variables that are the determinants of dynamic capabilities defined through their factors, while the other side features the determinants of innovation capabilities pursuant to the official standards. With regard to the research model, five hypotheses were set. The study was performed in late 2014 on a representative sample of large and very large Croatian enterprises with a minimum of 250 employees. The research instrument was a questionnaire administered to company top management. For both variables, the position of the company was tested in comparison to industry competitors, on a fivepoint scale. In order to test the hypotheses, correlation tests were performed to determine whether there is a correlation between each individual factor of company dynamic capabilities with the existence of its innovation capabilities, in line with the research model. The results indicate a strong correlation between a company’s possession of dynamic capabilities in terms of their factors, due to the new multi-dimensional model presented in this paper, with its possession of innovation capabilities. Based on the results, all five hypotheses were accepted. Ultimately, it was concluded that there is a strong association between the dynamic and innovation capabilities of a company. 

Keywords: dynamic capabilities, innovation capabilities, competitive advantage, business results

Procedia PDF Downloads 300

Authors: A. Saccani, I. Lancellotti, E. Bursi

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Scraps deriving from the production of epoxy-carbon fibers composites have been recycled as a reinforcement to produce building materials. Short chopped fibers (5-7 mm length) have been added at low volume content (max 10%) to produce mortars. The microstructure, mechanical properties (mainly flexural strength) and dimensional stability of the derived materials have been investigated. Two different types of matrix have been used: one based on conventional Portland Cement and the other containing geopolymers formed starting from activated metakaolin and fly ashes. In the second case the materials is almost completely made of recycled ingredients. This is an attempt to produce reliable materials solving waste disposal problems. The first collected results show promising results.

Keywords: building materials, carbon fibres, fly ashes, geopolymers

Procedia PDF Downloads 156

Authors: Stefano Zappacosta, Cristiano Bove, Maria Carmela Marinelli, Paola di Lauro, Katarina Spasenovic, Lorenzo Ostano, Giuseppe Aiello, Marco Pietrosanto

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This paper proposes a novel neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The proposed hybrid model can be used to classify four different increasing levels of hazard. The classification capability was compared with the flood hazard mapping River Basin Plans (PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale). The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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Authors: J. R. Wang, H. C. Chen, C. Shih, S. W. Chen, J. H. Yang, Y. Chiang

Abstract:

In this study, we focus on the establishment of the analysis model for Maanshan PWR nuclear power plant (NPP) by using RADTRAD and SNAP codes with the FSAR, manuals, and other data. In order to evaluate the cumulative dose at the Exclusion Area Boundary (EAB) and Low Population Zone (LPZ) outer boundary, Maanshan NPP RADTRAD/SNAP model was used to perform the analysis of the DBA LOCA case. The analysis results of RADTRAD were similar to FSAR data. These analysis results were lower than the failure criteria of 10 CFR 100.11 (a total radiation dose to the whole body, 250 mSv; a total radiation dose to the thyroid from iodine exposure, 3000 mSv).

Keywords: RADionuclide, transport, removal, and dose estimation (RADTRAD), symbolic nuclear analysis package (SNAP), dose, PWR

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Authors: N. Philipova

Abstract:

The influence of the geometric parameters of trapezoidal labyrinth channel on the emitter discharge is investigated in this work. The impact of the dentate angle, the dentate spacing, and the dentate height are studied among the geometric parameters of the labyrinth channel. Numerical simulations of the water flow movement are performed according to central cubic composite design using Commercial codes GAMBIT and FLUENT. Inlet pressure of the dripper is set up to be 1 bar. The objective of this paper is to derive a mathematical model of the emitter discharge depending on the dentate angle, the dentate spacing, the dentate height of the labyrinth channel. As a result, the obtained mathematical model is a second-order polynomial reporting 2-way interactions among the geometric parameters. The dentate spacing has the most important and positive influence on the emitter discharge, followed by the simultaneous impact of the dentate spacing and the dentate height. The dentate angle in the observed interval has no significant effect on the emitter discharge. The obtained model can be used as a basis for a future emitter design.

Keywords: drip irrigation, labyrinth channel hydrodynamics, numerical simulations, Reynolds stress model.

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Authors: Pillay J. D., D. De Wit, J. F. Ducray

Abstract:

Field hockey is a popular international sport which is played in more than 100 countries across the world. Due to the nature of hockey, players repeatedly perform a combination of forward flexion and rotational movements of the spine in order to strike the ball. These movements have been shown to increase the risk of pain and injury to the lumbar spine. The aim of this study was to determine the prevalence and incidence of low back pain (LBP) in male adolescent field hockey players and the characteristics of LBP in terms of location, chronicity, disability, and treatment sought, as well as its association with selected risk factors. A survey was conducted on 112 male adolescent field hockey players in the eThekwini Municipality of KwaZulu-Natal, South Africa. The questionnaire contained sections on the demographics of participants, general characteristics of participants, health and lifestyle characteristics, low back pain patterns, treatment of low back pain, and the level of disability associated with LBP. The data were statistically analysed using IBM SPSS version 25 with statistical significance set at p-value <0.05. Descriptive statistics such as mean and standard deviation were used to summarise responses to continuous variables as appropriate. Categorical variables were described using frequency tables. Associations between risk factors and low back pain were tested using Pearson’s chi-square test and t-tests as appropriate. A total of 68 questionnaires were completed for analysis (67% participation rate); the period prevalence of LBP was 63.2% (35.0%:beginning of the season, 32.4%:mid-season, 22.1%: end of season). Incidence was 38.2%. The most common location for LBP was the middle low back region (39.5%), and the most common duration of pain was a few hours (32.6%). Most participants (79.1%) did not classify their pain as a disability, and only 44.2% of participants received medical treatment for their LBP. An interesting finding was the association between hydration and LBP (p = 0.050), i.e., those individuals who did not hydrate frequently during matches and training were significantly more likely to experience LBP. The results of this study, although limited to a select group of adolescents, showed a higher prevalence of LBP than that of previous studies. More importantly, even though most participants did not experience LBP classified as a disability, LBP still had a large impact on participants, as nearly half of the participants consulted with a medical professional for treatment. Need for the application of further strategies in the prevention and management of LBP in field hockey, such as adequate warm-up and cool-down, stretching exercises, rest between sessions, etc., are recommended as simple strategies to reduce LBP prevalence.

Keywords: adolescents, field hockey players, incidence, low back pain, prevalence, risk factors

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Authors: Vincent Iacobellis, Kamran Behdinan

Abstract:

A finite element cohesive zone model is used to predict the temperature dependent material properties of a polyimide matrix composite with unidirectional carbon fiber arrangement. The cohesive zone parameters have been obtained from previous research involving an atomistic-to-continuum multiscale simulation of the fiber-matrix interface using the bridging cell multiscale method. The goal of the research was to both investigate the effect of temperature change on the composite behavior with respect to transverse loading as well as the validate the use of cohesive parameters obtained from atomistic-to-continuum multiscale modeling to predict fiber-matrix interfacial cracking. From the multiscale model cohesive zone parameters (i.e. maximum traction and energy of separation) were obtained by modeling the interface between the coarse-grained polyimide matrix and graphite based carbon fiber. The cohesive parameters from this simulation were used in a cohesive zone model of the composite microstructure in order to predict the properties of the macroscale composite with respect to changes in temperature ranging from 21 ˚C to 316 ˚C. Good agreement was found between the microscale RUC model and experimental results for stress-strain response, stiffness, and material strength at low and high temperatures. Examination of the deformation of the composite through localized crack initiation at the fiber-matrix interface also agreed with experimental observations of similar phenomena. Overall, the cohesive zone model was shown to be both effective at modeling the composite properties with respect to transverse loading as well as validated the use of cohesive zone parameters obtained from the multiscale simulation.

Keywords: cohesive zone model, fiber-matrix interface, microscale damage, multiscale modeling

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Authors: Monika Florczak-Wator

Abstract:

The model of positive obligations of the state concerning the protection of the rights of an individual was created within the jurisdiction of the German Federal Constitutional Court in the 1970s. That model assumes that the state should protect an individual against infringement of their fundamental rights by another individual. It is based on the idea concerning the modification of the function and duties of the state towards an individual and society. Initially the state was perceived as the main infringer of the fundamental rights of an individual formulating the individual’s obligations of negative nature (obligation of noninterference), however, at present the state is perceived as a guarantor and protector of the fundamental rights of an individual of positive nature (obligation of protection). Examination of the chosen judicial decisions of that court will enable us to determine what the obligation of protection is specifically about, when it is updated and whether it is accompanied by claims of an individual requesting the state to take actions protecting their fundamental rights against infringement by the private entities. The comparative perspective for the German model of positive obligations of the state will be an analogous model present in the jurisdiction of the European Court of Human Rights. It is justified to include it in the research as the Convention, similarly to the constitution, focuses on the protection of an individual against the infringement of their rights by the state and both models have been developed within the jurisdiction for several dozens of years. Analysis of the provisions of the Constitution of the Republic of Poland as well as judgements of the Polish Constitutional Tribunal will allow for the presentation of the application the model of the protective duties of the state in Poland.

Keywords: human rights, horizontal relationships, constitution, state protection

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Authors: Waldir Roque, Gustavo Oliveira, Moises Santos, Tatiana Simoes

Abstract:

Increasing the oil recovery factor of an oil reservoir has been a concern of the oil industry. Usually, the production placement zones are defined after some analysis of geological and petrophysical parameters, being the rock porosity, permeability and oil saturation of fundamental importance. In this context, the determination of hydraulic flow units (HFUs) renders an important step in the process of reservoir characterization since it may provide specific regions in the reservoir with similar petrophysical and fluid flow properties and, in particular, techniques supporting the placement of production zones that favour the tracing of directional wells. A HFU is defined as a representative volume of a total reservoir rock in which petrophysical and fluid flow properties are internally consistent and predictably distinct of other reservoir rocks. Technically, a HFU is characterized as a rock region that exhibit flow zone indicator (FZI) points lying on a straight line of the unit slope. The goal of this paper is to provide a trustful indication for oil production placement zones for the best-fit HFUs. The FZI cloud of points can be obtained from the reservoir quality index (RQI), a function of effective porosity and permeability. Considering log and core data the HFUs are identified and using the discrete rock type (DRT) classification, a set of connected cell clusters can be found and by means a graph centrality metric, the maximum closeness (MaxC) cell is obtained for each cluster. Considering the MaxC cells as production zones, an extensive analysis, based on several oil recovery factor and oil cumulative production simulations were done for the SPE Model 2 and the UNISIM-I-D synthetic fields, where the later was build up from public data available from the actual Namorado Field, Campos Basin, in Brazil. The results have shown that the MaxC is actually technically feasible and very reliable as high performance production placement zones.

Keywords: hydraulic flow unit, maximum closeness centrality, oil production simulation, production placement zone

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