Search results for: data life cycle

Authors: Jihyun Park

Abstract:

This research suggests that meaning in life or Ikigai can be associated with better academic performances in Japanese college students. To measure meaning in life in Japanese college students, the Ikigai questionnaire and the Meaning in Life Questionnaire (MLQ) are both used, and the survey was collected using Microsoft Teams Forms for a total of 80 Japanese college students. The data revealed that students who have a higher than a 3.0 grade point average (GPA) showed the highest score in both the Ikigai and MLQ. The participants with between a 2.0 and a 3.0 GPA reported lower scores in both MLQ and Ikigai than the previous participants. The group of students who have lower than a 2.0 GPA had the lowest scores for MLQ and Ikigai. This result can indicate that implementing meaning in life or Ikigai to early college students can bring about better academic performance, which also can improve students’ college life better as well.

Keywords: college students' academic performance, Ikigai, meaning in life, purpose of life

Procedia PDF Downloads 93

Authors: A. D. Parekh

Abstract:

The present work describes relative contributions of operating parameters on required heat transfer area of three heat exchangers viz. evaporator, condenser and cascade condenser of two stage R404A-R508B cascade refrigeration system using Taguchi method. The operating parameters considered in present study includes (1) condensing temperature of high temperature cycle and low temperature cycle (2) evaporating temperature of low temperature cycle (3) degree of superheating in low temperature cycle (4) refrigerating effect. Heat transfer areas of three heat exchangers are studied with variation of above operating parameters and also optimum working levels of each operating parameter has been obtained for minimum heat transfer area of each heat exchanger using Taguchi method. The analysis using Taguchi method reveals that evaporating temperature of low temperature cycle and refrigerating effect contribute relatively largely on the area of evaporator. Condenser area is mainly influenced by both condensing temperature of high temperature cycle and refrigerating effect. Area of cascade condenser is mainly affected by refrigerating effect and the effects of other operating parameters are minimal.

Keywords: cascade refrigeration system, Taguchi method, heat transfer area, ANOVA, optimal solution

Procedia PDF Downloads 338

Authors: A. D. Parekh

Abstract:

The present work describes relative contributions of operating parameters on required heat transfer area of three heat exchangers viz. evaporator, condenser and cascade condenser of two stage R404A-R508B cascade refrigeration system using Taguchi method. The operating parameters considered in present study includes (1) condensing temperature of high temperature cycle and low temperature cycle (2) evaporating temperature of low temperature cycle (3) degree of superheating in low temperature cycle (4) refrigerating effect. Heat transfer areas of three heat exchangers are studied with variation of above operating parameters and also optimum working levels of each operating parameter has been obtained for minimum heat transfer area of each heat exchanger using Taguchi method. The analysis using Taguchi method reveals that evaporating temperature of low temperature cycle and refrigerating effect contribute relatively largely on the area of evaporator. Condenser area is mainly influenced by both condensing temperature of high temperature cycle and refrigerating effect. Area of cascade condenser is mainly affected by refrigerating effect and the effects of other operating parameters are minimal.

Keywords: cascade refrigeration system, Taguchi method, heat transfer area, ANOVA, optimal solution

Procedia PDF Downloads 384

Authors: Yasmeen A. S. Essawy, Khaled Nassar

Abstract:

With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: building information modeling (BIM), elemental graph data model (EGDM), geometric and topological data models, graph theory

Procedia PDF Downloads 384

Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

Current real-estate value estimation, difficult for laymen, usually is performed by specialists. This paper presents an automated estimation process based on big data and machine-learning technology that calculates influences of building conditions on real-estate price measurement. The present study analyzed actual building sales sample data for Nonhyeon-dong, Gangnam-gu, Seoul, Korea, measuring the major influencing factors among the various building conditions. Further to that analysis, a prediction model was established and applied using RapidMiner Studio, a graphical user interface (GUI)-based tool for derivation of machine-learning prototypes. The prediction model is formulated by reference to previous examples. When new examples are applied, it analyses and predicts accordingly. The analysis process discerns the crucial factors effecting price increases by calculation of weighted values. The model was verified, and its accuracy determined, by comparing its predicted values with actual price increases.

Keywords: apartment complex, big data, life-cycle building value analysis, machine learning

Procedia PDF Downloads 374

Authors: Muhammad Ahsan

Abstract:

The effective decommissioning of oil and gas fields and related assets is one of the most important challenges facing the oil and gas industry today and in the future. Decommissioning decisions can no longer be avoided by the operators and the industry as a whole. Decommissioning yields no return on investment and carries significant regulatory liabilities. The main objective of this paper is to provide an approach and mechanism for the estimation of emissions associated with decommissioning of Oil and Gas fields. The model uses gate to gate approach and considers field life from development phase up to asset end life. The model incorporates decommissioning processes which includes; well plugging, plant dismantling, wellhead, and pipeline dismantling, cutting and temporary fabrication, new manufacturing from raw material and recycling of metals. The results of the GHG emissions during decommissioning phase are 2.31x10-2 Kg CO2 Eq. per Mcf of the produced natural gas. Well plug and abandonment evolved to be the most GHG emitting activity with 84.7% of total field decommissioning operational emissions.

Keywords: LCA (life cycle analysis), gas field, decommissioning, emissions

Procedia PDF Downloads 187

Authors: Justin Reverdi, Sixin Zhang, Serge Gratton, Said Aoues, Thomas Pellegrini

Abstract:

In Vapor Cycle Systems, the flow sensor plays a key role in different monitoring and control purposes. However, physical sensors can be expensive, inaccurate, heavy, cumbersome, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor based on other standard sensors is a good alternative. In this paper, a data-driven model using a Convolutional Neural Network is proposed to estimate the flow of the compressor. To fit the model to our dataset, we tested different loss functions. We show in our application that a Dynamic Time Warping based loss function called DILATE leads to better dynamical performance than the vanilla mean squared error (MSE) loss function. DILATE allows choosing a trade-off between static and dynamic performance.

Keywords: deep learning, dynamic time warping, vapor cycle system, virtual sensor

Procedia PDF Downloads 146

Authors: Hassan Alsada

Abstract:

Tank overfill accidents are major concerns for industries handling large volumes of hydrocarbons. Buncefield, Jaipur, Puerto Rico, and West Virginia are just a few accidents with catastrophic consequences. Thus, it is very important for any industry to take the right safety measures for overfill prevention. Moreover, one of the main causative factors in the overfill accidents was inadequate risk analysis and, subsequently, inadequate design. This study aims to provide a full assessment in accordance with the Functional safety standard: “IEC 615 11 – Safety instrumented systems for the process industry” to the tank overfill scenario according to the standard’s Safety Life Cycle (SLC), which includes: the analysis phase, the implementation phase, and the operation phase. The paper discusses in depth the tank overfills Independent Protection Layers (IPLs) with systematic analysis to avoid the safety risks of under-design and the financial risk of facility overdesign. The result shows a clear and systematic assessment in compliance with the standards that can help to assist existing tank overfilling setup or a guide to support designing new storage facilities overfill protection.

Keywords: IEC 61511, PHA, LOPA, process safety, safety, health, environment, safety instrumented systems, safety instrumented function, functional safety, safety life cycle

Procedia PDF Downloads 90

Authors: Fatma H. Galal, Alaaeddeen M. Seufi

Abstract:

Due to the increasing usage of mobile phone, experiments were designed to investigate ‎the effect of acute dose exposure on the mosquito life cycle. 50 tubes (5 ml size) ‎containing 3 ml water and a first instar larva of the mosquito, Culex univittatus were put ‎between two mobile cell phones switched on talking mode for 4 continuous hours. A ‎control group of tubes (unexposed to radiation) were used. Larval and pupal durations ‎were calculated. Furthermore, adult emergence and sex ratio were observed for both ‎treated and control larvae. Results indicated that the employed dose of radiation reduced ‎total larval duration to about half the value of control. 1st, 2nd, 3rd and 4th larval ‎durations were reduced significantly by mobile radiation when compared to controls. ‎Meanwhile pupal duration was elongated significantly by mobile radiation when ‎compared to control. Sex ratio was significantly shifted in favor of females in the case of ‎radiated mosquitoes. Successful adult emergence was decreased significantly in the case ‎of radiated insects when compared to controls. Molecular studies to investigate the ‎effects of mobile radiation on insects and other model organisms are going on.‎

Keywords: mosquito, mobilr radiation, larval and pupal durations, sex ratio

Procedia PDF Downloads 186

Authors: Mohamed Boubekri

Abstract:

Daylight in general and sunlight in particular are vital to life on earth, and it is not difficult to believe that their absence fosters conditions that promote disease. Through photosynthesis and other processes, sunlight provides photochemical ingredients necessary for our lives. There are fundamental biological, hormonal, and physiological functions coordinated by cycles that are crucial to life for cells, plants, animals, and humans. Many plants and animals, including humans, develop abnormal behaviors when sunlight is absent because their diurnal cycle is disturbed. Building​ codes disregard this aspect of daylighting when promulgating windows for buildings. This paper discusses the health aspects of daylighting design.

Keywords: daylighting, health, sunlight, sleep, disorders, circadian rythm, cancer

Procedia PDF Downloads 338

Authors: Edicio M. Faller

Abstract:

The use of technology in the delivery of teaching and learning is vital nowadays especially in education. Computer Assisted Learning Module (CALM) software is the use of computer in the delivery of instruction with a tailored fit program intended for a specific lesson or a set of topics. The CALM software developed in this study is intended to supplement the traditional teaching methods in technical-vocational (TECH-VOC) instruction specifically the Consumer Electronics Servicing course. There are three specific objectives of this study. First is to create a learning enhancement and review materials on the selected lessons. Second, is to computerize the end-of-chapter quizzes. Third, is to generate a computerized mock exam and summative assessment. In order to obtain the objectives of the study the researcher adopted the Agile Model where the development of the study undergoes iterative and incremental process of the Software Development Life Cycle. The study conducted an acceptance testing using a survey questionnaire to evaluate the CALM software. The results showed that CALM software was generally interpreted as very satisfactory. To further improve the CALM software it is recommended that the program be updated, enhanced and lastly, be converted from stand-alone to a client/server architecture.

Keywords: computer assisted learning module, software development life cycle, computerized mock exam, consumer electronics servicing

Procedia PDF Downloads 395

Authors: Joel Bonales, Venecia Solorzano, Carlos Garcia

Abstract:

A great percentage of the wastewater generated in developing countries don’t receive any treatment, which leads to numerous environmental impacts. In response to this, a paradigm change in the current wastewater treatment model based on large scale plants towards a small and medium scale based model has been proposed. Nevertheless, small scale wastewater treatment (SS-WTTP) with novel technologies such as anaerobic digesters, as well as the utilization of derivative co-products such as biogas, still presents diverse environmental impacts which must be assessed. This study consisted in a Life Cycle Assessment (LCA) performed to a SS-WWTP which treats wastewater from a small commercial block in the city of Morelia, Mexico. The treatment performed in the SS-WWTP consists in anaerobic and aerobic digesters with a daily capacity of 5,040 L. Two different scenarios were analyzed: the current plant conditions and a hypothetical energy use of biogas obtained in situ. Furthermore, two different allocation criteria were applied: full impact allocation to the system’s main product (treated water) and substitution credits for replacing Mexican grid electricity (biogas) and clean water pumping (treated water). The results showed that the analyzed plant had bigger impacts than what has been reported in the bibliography in the basis of wastewater volume treated, which may imply that this plant is currently operating inefficiently. The evaluated impacts appeared to be focused in the aerobic digestion and electric generation phases due to the plant’s particular configuration. Additional findings prove that the allocation criteria applied is crucial for the interpretation of impacts and that that the energy use of the biogas obtained in this plant can help mitigate associated climate change impacts. It is concluded that SS-WTTP is a environmentally sound alternative for wastewater treatment from a systemic perspective. However, this type of studies must be careful in the selection of the allocation criteria and replaced products, since these factors have a great influence in the results of the assessment.

Keywords: biogas, life cycle assessment, small scale treatment, wastewater treatment

Procedia PDF Downloads 125

Authors: Ali Badiei

Abstract:

The increasing urgency of climate change mitigation underscores the necessity for integrating advanced analytical frameworks that encompass both energy dynamics and environmental impacts. This study focuses on the convergence of Dynamic Energy Models (DEMs) and Life Cycle Assessment (LCA) tools, highlighting their combined potential to address the dual challenges of accurate energy system modelling and comprehensive sustainability evaluation. While DEMs excel in simulating time-dependent energy performance, LCAs provide insights into the cumulative environmental impacts over a product or system's lifecycle, including embodied and operational emissions. The integration of these methodologies is fraught with challenges. Discrepancies in data granularity, temporal resolutions, and system boundaries often lead to inconsistencies that hinder seamless interoperability. Furthermore, the computational complexity of merging time-sensitive energy simulations with lifecycle inventories demands innovative approaches to data harmonization and software compatibility. Despite these barriers, such integration offers substantial opportunities for enhancing the precision of sustainability assessments and informing evidence-based policy decisions. This paper examines the state of the art through a comprehensive review of existing frameworks and applications. UK case studies on energy-efficient buildings, particularly those adhering to Passivhaus standards, serve as focal points for evaluating the combined use of DEMs and LCA tools. The findings reveal that, while Passivhaus buildings significantly reduce operational energy consumption—meeting ultra-low energy targets—their embodied carbon emissions often offset initial gains. This underscores the importance of using integrated tools to optimize both operational and embodied carbon reduction strategies. Key outcomes of this research include the identification of gaps in current methodologies and the proposition of a unified framework to bridge these gaps. The study also highlights opportunities to utilize these integrated tools for policy formation and industrial practice innovation. By facilitating a lifecycle-focused understanding of energy systems, the integration of DEMs and LCAs can inform policies that incentivize sustainable construction practices and guide investments in low-carbon technologies. In conclusion, overcoming the technical and methodological challenges of linking DEMs and LCAs is critical for achieving holistic energy system optimization and supporting global net-zero carbon goals. This research advocates for multidisciplinary collaboration between energy modelers, environmental scientists, and policymakers to unlock the full potential of these tools in fostering sustainable development.

Keywords: energy, modelling, life cycle assessment, dynamic

Procedia PDF Downloads 10

Authors: Enrique Moliner, Alba Lafarga, Isaac Herraiz, Evelina Castellana, Mihaela Mirea

Abstract:

NENU2PHAR (GA 887474) is an EU-funded project aimed at the development of polyhydroxyalkanoates (PHAs) from micro-algae. These biobased and biodegradable polymers are being tested and validated in different high-volume market applications including food packaging, cosmetic packaging, 3D printing filaments, agro-textiles and medical devices, counting on the support of key players like Danone, BEL Group, Sofradim or IFG. At the moment the project has achieved to produce PHAs from micro-algae with a cumulated yield around 17%, i.e. 1 kg PHAs produced from 5.8 kg micro-algae biomass, which in turn capture 11 kg CO₂ for growing up. These algae-based plastics can therefore offer the same environmental benefits than current bio-based plastics (reduction of greenhouse gas emissions and fossil resource depletion), using a 3rd generation biomass feedstock that avoids the competition with food and the environmental impacts of agricultural practices. The project is also dealing with other sustainability aspects like the ecodesign and life cycle assessment of the plastic products targeted, considering not only the use of the biobased plastics but also many other ecodesign strategies. This paper will present the main progresses and results achieved to date in the project.

Keywords: NENU2PHAR, Polyhydroxyalkanoates, micro-algae, biopolymer, ecodesign, life cycle assessment

Procedia PDF Downloads 91

Authors: Joe Hachem, Marianne Cuif-Sjostrand, Thierry Schuhler, Dominique Orhon, Assaad Zoughaib

Abstract:

The exhaust gas recirculation, EGR, implementation on gas turbines is increasingly gaining the attention of many researchers. This emerging technology presents many advantages, such as lowering the NOx emissions and facilitating post-combustion carbon capture as the carbon dioxide concentration in the cycle increases. As interesting as this technology may seem, the gas turbine, or its thermodynamic equivalent, the Brayton cycle, shows an intrinsic efficiency decrease with increasing EGR rate. In this paper, a thermodynamic model is presented to show the cycle efficiency decrease with EGR, alternative values of design parameters of both the pressure ratio (PR) and the turbine inlet temperature (TIT) are then proposed to optimize the cycle efficiency with different EGR rates. Results show that depending on the given EGR rate, both the design PR & TIT should be increased to compensate for the deficit in efficiency.

Keywords: gas turbines, exhaust gas recirculation, design parameters optimization, thermodynamic approach

Procedia PDF Downloads 149

Authors: E. Kempen, M. J. Labuschagne, M. P. Jama

Abstract:

There is evidence that experiential learning is truly influential and favored by the millennial generation. However, little is known about the role and attributes an educator has to adopt during the experiential learning cycle, especially when applied in optometry education. This study aimed to identify the roles and attributes of an optometry educator during the different modes of the experiential learning cycle. Methods: A qualitative case study design was used. Data was collected using an open-ended questionnaire survey, following the application of nine different teaching-learning methods based on the experimental learning cycle. The total sample population of 68 undergraduate students from the Department of Optometry at the University of the Free State, South Africa were invited to participate. Focus group interviews (n=15) added additional data that contributed to the interpretation and confirmation of the data obtained from the questionnaire surveys. Results: The perceptions and experiences of the students identified a variety of roles and attributes as well as recommendations on the effective adoption of these roles and attributes. These roles and attributes included being knowledgeable, creating an interest, providing guidance, being approachable, building confidence, implementing ground rules, leading by example, and acting as a mediator. Conclusion: The findings suggest that the actions of an educator have the most substantial impact on students’ perception of a learning experience. Not only are the recommendations based on the views of a millennial generation, but the implementation of the personalized recommendations may also transform a learning environment. This may lead an optometry student to a deeper understanding of knowledge.

Keywords: experiences and perceptions, experiential learning, millennial generation, recommendation for optometry education

Procedia PDF Downloads 117

Authors: S. Sabzchi Asl, N. Tahouni, M. H. Panjeshahi

Abstract:

Benchmarking of a process with respect to energy consumption, without accomplishing a full retrofit study, can save both engineering time and money. In order to achieve this goal, the first step is to develop a conceptual-mathematical model that can easily be applied to a group of similar processes. In this research, we have aimed to identify a set of key parameters for the model which is supposed to be used for benchmarking of combined cycle power plants. For this purpose, three similar combined cycle power plants were studied. The results showed that ambient temperature, pressure and relative humidity, number of HRSG evaporator pressure levels and relative power in part load operation are the main key parameters. Also, the relationships between these parameters and produced power (by gas/ steam turbine), gas turbine and plant efficiency, temperature and mass flow rate of the stack flue gas were investigated.

Keywords: combined cycle power plant, energy benchmarking, modelling, retrofit

Procedia PDF Downloads 305

Authors: Saeedeh Bakhtiari, Johannes Depessemier, Stijn Hertelé, Wim De Waele

Abstract:

High cycle fatigue comprising up to 10⁷ load cycles has been the subject of many studies, and the behavior of many materials was recorded adequately in this regime. However, many applications involve larger numbers of load cycles during the lifetime of machine components. In this ultra-high cycle regime, other failure mechanisms play, and the concept of a fatigue endurance limit (assumed for materials such as steel) is often an oversimplification of reality. When machine component design demands a high geometrical complexity, cast iron grades become interesting candidate materials. Grey cast iron is known for its low cost, high compressive strength, and good damping properties. However, the ultra-high cycle fatigue behavior of cast iron is poorly documented. The current work focuses on the ultra-high cycle fatigue behavior of EN-GJL-250 (GG25) grey cast iron by developing an ultrasonic (20 kHz) fatigue testing system. Moreover, the testing machine is instrumented to measure the temperature and the displacement of  the specimen, and to control the temperature. The high resonance frequency allowed to assess the  behavior of the cast iron of interest within a matter of days for ultra-high numbers of cycles, and repeat the tests to quantify the natural scatter in fatigue resistance.

Keywords: GG25, cast iron, ultra-high cycle fatigue, ultrasonic test

Procedia PDF Downloads 177

Authors: Dong Seop Lee, Byung Sik Kim

Abstract:

In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. These artificial intelligence technologies are applied in various services, including disaster management. Disaster information management does not just support disaster work, but it is also the foundation of smart disaster management. Furthermore, it gets historical disaster information using artificial intelligence technology. Disaster information is one of important elements of entire disaster cycle. Disaster information management refers to the act of managing and processing electronic data about disaster cycle from its’ occurrence to progress, response, and plan. However, information about status control, response, recovery from natural and social disaster events, etc. is mainly managed in the structured and unstructured form of reports. Those exist as handouts or hard-copies of reports. Such unstructured form of data is often lost or destroyed due to inefficient management. It is necessary to manage unstructured data for disaster information. In this paper, the Optical Character Recognition approach is used to convert handout, hard-copies, images or reports, which is printed or generated by scanners, etc. into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored in the disaster database system. Gathering and creating disaster information based on Optical Character Recognition for unstructured data is important element as realm of the smart disaster management. In this paper, Korean characters were improved to over 90% character recognition rate by using upgraded OCR. In the case of character recognition, the recognition rate depends on the fonts, size, and special symbols of character. We improved it through the machine learning algorithm. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle such as historical disaster progress, damages, response, and recovery. The expected effect of this research will be able to apply it to smart disaster management and decision making by combining artificial intelligence technologies and historical big data.

Keywords: disaster information management, unstructured data, optical character recognition, machine learning

Procedia PDF Downloads 130

Authors: Reema Alghamdi, Rasees Aleisa, Layan Sukkar

Abstract:

The primary objective of this research is to conduct an examination of the Flo menstrual cycle application. We do that by evaluating the user experience and their satisfaction with integrated AI features. The study seeks to gather data from primary resources, primarily through surveys, to gather different insights about the application, like its usability functionality in addition to the overall user satisfaction. The focus of our project will be particularly directed towards the impact and user perspectives regarding the integration of artificial intelligence features within the application, contributing to an understanding of the holistic user experience.

Keywords: period, women health, machine learning, AI features, menstrual cycle

Procedia PDF Downloads 77

Authors: Nabil Beroual, Tewfik Sari

Abstract:

We consider the Gause-type predator-prey system in the case where the response function is not smooth at the origin. We discuss the conditions under which this system has exactly one stable limit cycle or has a positive stable equilibrium point, and we describe the basin of attraction of the stable limit cycle and the stable equilibrium point, respectively. Our results correct previous results of the existing literature.

Keywords: predator-prey model, response function, singularity, basin of attraction, limit cycle

Procedia PDF Downloads 179

Authors: Daniel Tochwin

Abstract:

Continuous improvement is an essential part of effective process performance management. In order to achieve continuous quality improvement, each organization must use the appropriate selection of tools and techniques. The basic condition for success is a proper understanding of the business need faced by the company and the selection of appropriate methods to improve a given production process. The main aim of this article is to analyze the methods of conduct which are popular in practice when implementing process improvements and then to determine whether the tested methods include repetitive systematics of the approach, i.e., a similar sequence of the same or similar actions. Based on an extensive literature review, 4 methods of continuous improvement of production processes were selected: A3 report, Gemba Kaizen, PDCA cycle, and Deming cycle. The research shows that all frequently used improvement methods are generally based on the PDCA cycle, and the differences are due to "(re)interpretation" and the need to adapt the continuous improvement approach to the specific business process. The research shows that all the frequently used improvement methods are generally based on the PDCA cycle, and the differences are due to "(re) interpretation" and the need to adapt the continuous improvement approach to the specific business process.

Keywords: continuous improvement, lean methods, process improvement, PDCA

Procedia PDF Downloads 80

Authors: Sayali Vyas, Atharva Desai, Shreyas Badave, Apurv Kulkarni, B. Rajiv

Abstract:

The Failure Modes and Effect Analysis (FMEA) is an efficient evaluation technique to identify potential failures in products, processes, and services. FMEA is designed to identify and prioritize failure modes. It proves to be a useful method for identifying and correcting possible failures at its earliest possible level so that one can avoid consequences of poor performance. In this paper, FMEA tool is used in detection of failures of various components of heat exchanger cycle and to identify critical failures of the components which may hamper the system’s performance. Further, a detailed Pareto analysis is done to find out the most critical components of the cycle, the causes of its failures, and possible recommended actions. This paper can be used as a checklist which will help in maintainability of the system.

Keywords: FMEA, heat exchanger cycle, Ishikawa diagram, pareto analysis, RPN (Risk Priority Number)

Procedia PDF Downloads 402

Authors: Bahadir Aydin

Abstract:

Today it is difficult to reach accurate knowledge because of mass data. This huge data makes the environment more and more caotic. Data is a main piller of intelligence. There is a close tie between knowledge and intelligence. Information gathered from different sources can be modified, interpreted and classified by using knowledge development process. This process is applied in order to attain intelligence. Within this process the effect of knowledge is crucial. Knowledge is classified as explicit and tacit knowledge. Tacit knowledge can be seen as "only the tip of the iceberg”. This tacit knowledge accounts for much more than we guess in all intelligence cycle. If the concept of intelligence scrutinized, it can be seen that it contains risks, threats as well as success. The main purpose for all organization is to be succesful by eliminating risks and threats. Therefore, there is a need to connect or fuse existing information and the processes which can be used to develop it. By the help of process the decision-maker can be presented with a clear holistic understanding, as early as possible in the decision making process. Planning, execution and assessments are the key functions that connects to information to knowledge. Altering from the current traditional reactive approach to a proactive knowledge development approach would reduce extensive duplication of work in the organization. By new approach to this process, knowledge can be used more effectively.

Keywords: knowledge, intelligence cycle, tacit knowledge, KIDW

Procedia PDF Downloads 520

Authors: A. Er-Raki, D. Hartmann, J. P. Belaud, S. Negny

Abstract:

This paper has a double purpose: firstly, a literature review of the life cycle analysis (LCA) and secondly a comparison between conventional (static) LCA and multi-level dynamic LCA on the following items: (i) inventories evolution with time (ii) temporal evolution of the databases. The first part of the paper summarizes the state of the art of the static LCA approach. The different static LCA limits have been identified and especially the non-consideration of the spatial and temporal evolution in the inventory, for the characterization factors (FCs) and into the databases. Then a description of the different levels of integration of the notion of temporality in life cycle analysis studies was made. In the second part, the dynamic inventory has been evaluated firstly for a single nuclear plant and secondly for the entire French nuclear power fleet by taking into account the construction durations of all the plants. In addition, the databases have been adapted by integrating the temporal variability of the French energy mix. Several iterations were used to converge towards the real environmental impact of the energy mix. Another adaptation of the databases to take into account the temporal evolution of the market data of the raw material was made. An identification of the energy mix of the time studied was based on an extrapolation of the production reference values of each means of production. An application to the construction of the French nuclear power plants from 1971 to 2000 has been performed, in which a dynamic inventory of raw material has been evaluated. Then the impacts were characterized by the ILCD 2011 characterization method. In order to compare with a purely static approach, a static impact assessment was made with the V 3.4 Ecoinvent data sheets without adaptation and a static inventory considering that all the power stations would have been built at the same time. Finally, a comparison between static and dynamic LCA approaches was set up to determine the gap between them for each of the two levels of integration. The results were analyzed to identify the contribution of the evolving nuclear power fleet construction to the total environmental impacts of the French energy mix during the same period. An equivalent strategy using a dynamic approach will further be applied to identify the environmental impacts that different scenarios of the energy transition could bring, allowing to choose the best energy mix from an environmental viewpoint.

Keywords: LCA, static, dynamic, inventory, construction, nuclear energy, energy mix, energy transition

Procedia PDF Downloads 105

Authors: Hye Rim Lee, Eui Jun Jeong, Ji Hye Yoo

Abstract:

This study makes an integrated investigation on how life satisfaction is associated with the Korean game users' psychological variables (self-esteem, game and life self- efficacy), social variables (bonding and bridging social capital), and demographic variables (age, gender). The data used for the empirical analysis came from a representative sample survey conducted in South Korea. Results show that self-esteem and game efficacy were an important antecedent to the degree of users’ life satisfaction. Both bonding social capital and bridging social capital enhance the level of the users’ life satisfaction. The importance of perspectives as well as their implications for the game users and further associated research, are explored.

Keywords: life satisfaction, self-esteem, game efficacy, life-efficacy, social capital

Procedia PDF Downloads 590

Authors: Qazi Salman Khalid, Muhammad Khalid, Shahid Maqsood

Abstract:

This paper presents a solution for optimizing the cycle time in an assembly line with human-robot collaboration and diverse operators. A genetic algorithm with tailored parameters is used to address the assembly line balancing problem in the automobile sector. A mathematical model is developed, depicting the problem. Currently, the firm runs on the largest candidate rule; however, it causes a lag in orders, which ultimately gets penalized. The results of the study show that the proposed GA is effective in providing efficient solutions and that the cycle time has significantly impacted productivity.

Keywords: line balancing, cycle time, genetic algorithm, productivity

Procedia PDF Downloads 138

Authors: Guoqian Ren, Haijiang Li, Jisong Zhang

Abstract:

Over the past 40 years, urban development has undergone large-scale, high-speed expansion, beyond what was previously considered normal and in a manner not proportionally related to population growth or physical considerations. With more scientific and refined decision-making in the urban construction process, new urbanization approaches, aligned with public-private partnerships (PPPs) which evolved in the early 1990s, have become acceptable and, in some situations, even better solutions to outstanding urban municipal construction projects, especially in developing countries. However, as the main driving force to deal with urban public services, PPPs are still problematic regarding value for money (VFM) process in most large-scale construction projects. This paper therefore reviews recent PPP articles in popular project management journals and relevant toolkits, published in the last 10 years, to identify the indicators that influence VFM within PPPs across regions. With increasing concerns about profitability and environmental and social impacts, the current PPP structure requires a more integrated platform to manage multi-performance project life cycles. Building information modelling (BIM), a popular approach to the procurement process in AEC sectors, provides the potential to ensure VFM while also working in tandem with the semantic approach to holistically measure life cycle costs (LCC) and achieve better sustainability. This paper suggests that BIM applied to the entire PPP life cycle could support holistic decision-making regarding VFM processes and thus meet service targets.

Keywords: public-private partnership, value for money, building information modelling, semantic approach

Procedia PDF Downloads 211

Authors: Piyangkun Kukutapan, Siridech Boonsang

Abstract:

The article proposes maximum power point tracking without mechanical sensor using Multilayer Perceptron Neural Network (MLPNN). The aim of article is to reduce the cost and complexity but still retain efficiency. The experimental is that duty cycle is generated maximum power, if it has suitable qualification. The measured data from DC generator, voltage (V), current (I), power (P), turnover rate of power (dP), and turnover rate of voltage (dV) are used as input for MLPNN model. The output of this model is duty cycle for driving the converter. The experiment implemented using Arduino Uno board. This diagram is compared to MPPT using MLPNN and P&O control (Perturbation and Observation control). The experimental results show that the proposed MLPNN based approach is more efficiency than P&O algorithm for this application.

Keywords: maximum power point tracking, multilayer perceptron netural network, optimal duty cycle, DC generator

Procedia PDF Downloads 325

Authors: S. Bennoud, S. Hocine, H. Slme

Abstract:

Developments in turbine cooling technology play an important role in increasing the thermal efficiency and the power output of recent gas turbines, in particular the turbojets. Advanced turbojets operate at high temperatures to improve thermal efficiency and power output. These temperatures are far above the permissible metal temperatures. Therefore, there is a critical need to cool the blades in order to give theirs a maximum life period for safe operation. The focused objective of this work is to calculate the turbojet performances, as well as the calculation of turbine blades cooling. The developed application able the calculation of turbojet performances to different altitudes in order to find a point of optimal use making possible to maintain the turbine blades at an acceptable maximum temperature and to limit the local variations in temperatures in order to guarantee their integrity during all the lifespan of the engine.

Keywords: brayton cycle, turbine blades cooling, turbojet cycle, turbojet performances

Procedia PDF Downloads 220