Search results for: electrolyte-supported model

Authors: Yu-Jen Chang, Yun Chen, Hei-Lam Wong

Abstract:

The Economic Lot Scheduling Problem (ELSP) is a valuable mathematical model that can support decision-makers to make scheduling decisions. The basic period approach is effective for solving the ELSP. The assumption for applying the basic period approach is that a product must use its maximum production rate to be produced. However, a product can lower its production rate to reduce the average total cost when a facility has extra idle time. The past researches discussed how a product adjusts its production rate under the common cycle approach. To the best of our knowledge, no studies have addressed how a product lowers its production rate under the basic period approach. This research is the first paper to discuss this topic. The research develops a simple fixed rate approach that adjusts the production rate of a product under the basic period approach to solve the ELSP. Our numerical example shows our approach can find a better solution than the traditional basic period approach. Our mathematical model that applies the fixed rate approach under the basic period approach can serve as a reference for other related researches.

Keywords: economic lot, basic period, genetic algorithm, fixed rate

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Authors: Fouzia Brihmat

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Economic planning models, which are used to build microgrids and distributed energy resources, are the current norm for expressing such confidence (DER). These models often decide both short-term DER dispatch and long-term DER investments. This research investigates the most cost-effective hybrid (photovoltaic-diesel) renewable energy system (HRES) based on Total Net Present Cost (TNPC) in an Algerian Saharan area, which has a high potential for solar irradiation and has a production capacity of 1GW/h. Lead-acid batteries have been around much longer and are easier to understand, but have limited storage capacity. Lithium-ion batteries last longer, are lighter, but generally more expensive. By combining the advantages of each chemistry, we produce cost-effective high-capacity battery banks that operate solely on AC coupling. The financial implications of this research describe the corrosion process that occurs at the interface between the active material and grid material of the positive plate of a lead-acid battery. The best cost study for the HRES is completed with the assistance of the HOMER Pro MATLAB Link. Additionally, during the course of the project's 20 years, the system is simulated for each time step. In this model, which takes into consideration decline in solar efficiency, changes in battery storage levels over time, and rises in fuel prices above the rate of inflation. The trade-off is that the model is more accurate, but it took longer to compute. As a consequence, the model is more precise, but the computation takes longer. We initially utilized the Optimizer to run the model without MultiYear in order to discover the best system architecture. The optimal system for the single-year scenario is the Danvest generator, which has 760 kW, 200 kWh of the necessary quantity of lead-acid storage, and a somewhat lower COE of $0.309/kWh. Different scenarios that account for fluctuations in the gasified biomass generator's production of electricity have been simulated, and various strategies to guarantee the balance between generation and consumption have been investigated. The technological optimization of the same system has been finished and is being reviewed in a recent paper study.

Keywords: battery, corrosion, diesel, economic planning optimization, hybrid energy system, lead-acid battery, multi-year planning, microgrid, price forecast, PV, total net present cost

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Authors: Aminu Fagge Muhammad

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The digital economy is fast becoming the most innovative and widest reaching economy in the world, especially in developing countries. The paper aimed at examining role of digital economy in the emerging countries like Nigeria. The methodology used in the study is Business Model Perspective: lying between the process and structural perspectives, bring in the idea of the new business models that are being enabled e.g. e-business or e-commerce. The paper concluded that, the policy objectives and measures, and processes and structures necessary to enhance digital economy growth and its contribution to socio-economic development. The finding reveals that, digital infrastructure is in part incomplete, costly and poorly-performing in emerging economies like Nigeria. The wider digital ecosystem suffers a shortfall in human capabilities, weak financing, and poor governance. It is also found that, Growth in the digital economy is exacerbating digital exclusion, inequality, adverse incorporation and other digital harms. It is recommended that, government in partnership with private sector should build strong local infrastructure to enable broadband availability and accessibility and to create an enabling environment for strong competition in the telecom and technology ecosystem.

Keywords: Digital Economy, Emerging Countries, Business Model , Nigeria

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Authors: Shu-Lien Chou, Chung-Feng Liu

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Self-health management of chronic illnesses plays an important part in chronic illness treatments. However, various kinds of health information (health education materials) which government or healthcare institutions provide for patients may not achieve the expected outcome. One of the critical reasons affecting patients’ use intention could be patients’ perceived Information overload regarding the health information. This study proposed an extended model of Theory of Planned Behavior, which integrating perceived information overload as another construct to explore patients’ use intention of the health information for self-health management. The independent variables are attitude, subject norm, perceived behavior control and perceived information overload while the dependent variable is behavior intention to use the health information. The cross-sectional study used a structured questionnaire for data collection, focusing on the chronic patients with coronary artery disease (CAD), who are the potential users of the health information, in a medical center in Taiwan. Data were analyzed using descriptive statistics of the basic information distribution of the questionnaire respondents, and the Partial Least Squares (PLS) structural equation model to study the reliability and construct validity for testing our hypotheses. A total of 110 patients were enrolled in this study and 106 valid questionnaires were collected. The PLS analysis result indicates that the patients’ perceived information overload of health information contributes the most critical factor influencing the behavioral intention. Subjective norm and perceived behavioral control of TPB constructs had significant effects on patients’ intentions to use health information also, whereas the attitude construct did not. This study demonstrated a comprehensive framework, which extending perceived information overload into TPB model to predict patients’ behavioral intention of using heath information. We expect that the results of this study will provide useful insights for studying health information from the perspectives of academia, governments, and healthcare providers.

Keywords: chronic patients, health information, information overload, theory of planned behavior

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Authors: Prudhvinath Reddy Ankireddy, Narasimha Mangadoddy

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Spiral concentrators are commonly used in various industries, including mineral and coal processing, to efficiently separate materials based on their density and size. In these concentrators, a mixture of solid particles and fluid (usually water) is introduced as feed at the top of a spiral channel. As the mixture flows down the spiral, centrifugal and gravitational forces act on the particles, causing them to stratify based on their density and size. Spiral flows exhibit complex fluid dynamics, and interactions involve multiple phases and components in the process. Understanding the behavior of these phases within the spiral concentrator is crucial for achieving efficient separation. An experimental bi-component particle interaction study is conducted in this work utilizing magnetite (heavier density) and silica (lighter density) with different proportions processed in the spiral concentrator. The observation separation reveals that denser particles accumulate towards the inner region of the spiral trough, while a significant concentration of lighter particles are found close to the outer edge. The 5th turn of the spiral trough is partitioned into five zones to achieve a comprehensive distribution analysis of bicomponent particle segregation. Samples are then gathered from these individual streams using an in-house sample collector, and subsequent analysis is conducted to assess component segregation. Along the trough, there was a decline in the concentration of coarser particles, accompanied by an increase in the concentration of lighter particles. The segregation pattern indicates that the heavier coarse component accumulates in the inner zone, whereas the lighter fine component collects in the outer zone. The middle zone primarily consists of heavier fine particles and lighter coarse particles. The zone-wise results reveal that there is a significant fraction of segregation occurs in inner and middle zones. Finer magnetite and silica particles predominantly accumulate in outer zones with the smallest fraction of segregation. Additionally, numerical simulations are also carried out using the computational fluid dynamics (CFD) model based on the volume of fluid (VOF) approach incorporating the RSM turbulence model. The discrete phase model (DPM) is employed for particle tracking, thereby understanding the particle segregation of magnetite and silica along the spiral trough.

Keywords: spiral concentrator, bi-component particle segregation, computational fluid dynamics, discrete phase model

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Authors: Yuxin Wu, Yu-Shing Wang, Zitao Zhang

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A high-speed and time-lapse S-wave velocity measurement system has been built up for S-wave tomography in sand. This system is based on bender elements and applied to model pile tests in a tailor-made pressurized chamber to monitor the shear wave velocity distribution during pile installation in sand. Tactile pressure sensors are used parallel together with bender elements to monitor the stress changes during the tests. Strain gages are used to monitor the shaft resistance and toe resistance of pile. Since the shear wave velocity (Vs) is determined by the shear modulus of sand and the shaft resistance of pile is also influenced by the shear modulus of sand around the pile, the purposes of this study are to time-lapse monitor the S-wave velocity distribution change at a certain horizontal section during pile installation and to correlate the S-wave velocity distribution and shaft resistance of pile in sand.

Keywords: bender element, pile, shaft resistance, shear wave velocity, tomography

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Authors: Tauhidur Rahman, Arnab Kumar Sinha

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This paper presents a comparative study of Arch bridges based on their varying rise to span ratio. The comparison is done between different steel Arch bridges which have variable span length and rise to span ratio keeping the same support condition. The aim of our present study is to select the optimum value of rise to span ratio of Arch bridge as the cost of the Arch bridge increases with the increasing of the rise. In order to fulfill the objective, several rise to span ratio have been considered for same span of Arch bridge and various structural parameters such as Bending moment, shear force etc have been calculated for different model. A comparative study has been done for several Arch bridges finally to select the optimum rise to span ratio of the Arch bridges. In the present study, Finite Element model for medium to long span, with different rise to span ratio have been modeled and are analyzed with the help of a Computational Software named MIDAS Civil to evaluate the results such as Bending moments, Shear force, displacements, Stresses, influence line diagrams, critical loads. In the present study, 60 models of Arch bridges for 80 to 120 m span with different rise to span ratio has been thoroughly investigated.

Keywords: arch bridge, analysis, comparative study, rise to span ratio

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Authors: M. Seguini, D. Nedjar

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In this paper, the nonlinear analysis of Timoshenko beam undergoing moderate large deflections and resting on nonlinear two-parameter random foundation is presented, taking into account the effects of shear deformation, beam’s properties variation and the spatial variability of soil characteristics. The finite element probabilistic analysis has been performed by using Timoshenko beam theory with the Von Kàrmàn nonlinear strain-displacement relationships combined to Vanmarcke theory and Monte Carlo simulations, which is implemented in a Matlab program. Numerical examples of the newly developed model is conducted to confirm the efficiency and accuracy of this later and the importance of accounting for the foundation second parameter (Winkler-Pasternak). Thus, the results obtained from the developed model are presented and compared with those available in the literature to examine how the consideration of the shear and spatial variability of soil’s characteristics affects the response of the system.

Keywords: nonlinear analysis, soil-structure interaction, large deflection, Timoshenko beam, Euler-Bernoulli beam, Winkler foundation, Pasternak foundation, spatial variability

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Authors: Surajit Das Barman, Rakibuzzaman Shah, Apurv Kumar

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Bushfire is known as one of the ascendant factors to create pyrocumulus thundercloud that causes the ignition of new fires by pyrocumulonimbus (pyroCb) lightning strikes and creates major losses of lives and property worldwide. A conceptual model-based risk planning would be beneficial to predict the lightning striking zones on the surface of the earth underneath the pyroCb thundercloud. PyroCb thundercloud can generate both positive cloud-to-ground (+CG) and negative cloud-to-ground (-CG) lightning in which +CG tends to ignite more bushfires and cause massive damage to nature and infrastructure. In this paper, a simple line charge structured thundercloud model is constructed in 2-D coordinates using the method of image charge to predict the probable +CG lightning striking zones on the earth’s surface for two conceptual thundercloud charge configurations: titled dipole and conventional tripole structure with excessive lower positive charge regions that lead to producing +CG lightning. The electric potential and surface charge density along the earth’s surface for both structures via continuously adjusting the position and the charge density of their charge regions is investigated. Simulation results for tilted dipole structure confirm the down-shear extension of the upper positive charge region in the direction of the cloud’s forward flank by 4 to 8 km, resulting in negative surface density, and would expect +CG lightning to strike within 7.8 km to 20 km around the earth periphery in the direction of the cloud’s forward flank. On the other hand, the conceptual tripole charge structure with enhanced lower positive charge region develops negative surface charge density on the earth’s surface in the range |x| < 6.5 km beneath the thundercloud and highly favors producing +CG lightning strikes.

Keywords: pyrocumulonimbus, cloud-to-ground lightning, charge structure, surface charge density, forward flank

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Authors: Rowan P. Martnishn

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During the execution of a National Endowment of the Arts grant, approximately 55 interviews were collected from professionals across various fields. These interviews were used to create deliverables – historical connections for creations that began as art and evolved entirely into computing technology. With dozens of hours’ worth of transcripts to be analyzed by qualitative coders, a quantitative methodology was created to sift through the documents. The initial step was to both clean and format all the data. First, a basic spelling and grammar check was applied, as well as a Python script for normalized formatting which used an open-source grammatical formatter to make the data as coherent as possible. 10 documents were randomly selected to manually review, where words often incorrectly translated during the transcription were recorded and replaced throughout all other documents. Then, to remove all banter and side comments, the transcripts were spliced into paragraphs (separated by change in speaker) and all paragraphs with less than 300 characters were removed. Secondly, a keyword extractor, a form of natural language processing where significant words in a document are selected, was run on each paragraph for all interviews. Every proper noun was put into a data structure corresponding to that respective interview. From there, a Bidirectional and Auto-Regressive Transformer (B.A.R.T.) summary model was then applied to each paragraph that included any of the proper nouns selected from the interview. At this stage the information to review had been sent from about 60 hours’ worth of data to 20. The data was further processed through light, manual observation – any summaries which proved to fit the criteria of the proposed deliverable were selected, as well their locations within the document. This narrowed that data down to about 5 hours’ worth of processing. The qualitative researchers were then able to find 8 more connections in addition to our previous 4, exceeding our minimum quota of 3 to satisfy the grant. Major findings of the study and subsequent curation of this methodology raised a conceptual finding crucial to working with qualitative data of this magnitude. In the use of artificial intelligence there is a general trade off in a model between breadth of knowledge and specificity. If the model has too much knowledge, the user risks leaving out important data (too general). If the tool is too specific, it has not seen enough data to be useful. Thus, this methodology proposes a solution to this tradeoff. The data is never altered outside of grammatical and spelling checks. Instead, the important information is marked, creating an indicator of where the significant data is without compromising the purity of it. Secondly, the data is chunked into smaller paragraphs, giving specificity, and then cross-referenced with the keywords (allowing generalization over the whole document). This way, no data is harmed, and qualitative experts can go over the raw data instead of using highly manipulated results. Given the success in deliverable creation as well as the circumvention of this tradeoff, this methodology should stand as a model for synthesizing qualitative data while maintaining its original form.

Keywords: B.A.R.T.model, keyword extractor, natural language processing, qualitative coding

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Authors: Barham J. Nareeman, Ilham I. Mohammed

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Excavations in urban developed area are generally supported by deep excavation walls such as; diaphragm wall, bored piles, soldier piles and sheet piles. In some cases, these walls may be braced by internal braces or tie back anchors. Tie back anchors are by far the predominant method for wall support, the large working space inside the excavation provided by a tieback anchor system has a significant construction advantage. This paper aims to analyze a deep excavation bracing system of contiguous pile wall braced by pre-stressed tie back anchors, which is a part of a huge residential building project, located in Turkey/Gaziantep province. The contiguous pile wall will be constructed with a length of 270 m that consists of 285 piles, each having a diameter of 80 cm, and a center to center spacing of 95 cm. The deformation analysis was carried out by a finite element analysis tool using PLAXIS. In the analysis, beam element method together with an elastic perfect plastic soil model and Soil Hardening Model was used to design the contiguous pile wall, the tieback anchor system, and the soil. The two soil clusters which are limestone and a filled soil were modelled with both Hardening soil and Mohr Coulomb models. According to the basic design, both soil clusters are modelled as drained condition. The simulation results show that the maximum horizontal movement of the walls and the maximum settlement of the ground are convenient with 300 individual case histories which are ranging between 1.2mm and 2.3mm for walls, and 15mm and 6.5mm for the settlements. It was concluded that tied-back contiguous pile wall can be satisfactorily modelled using Hardening soil model.

Keywords: deep excavation, finite element, pre-stressed tie back anchors, contiguous pile wall, PLAXIS, horizontal deflection, ground settlement

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Authors: S. Neelima, P. S. Subramanyam

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The major tool for distribution planning is load forecasting, which is the anticipation of the load in advance. Artificial neural networks have found wide applications in load forecasting to obtain an efficient strategy for planning and management. In this paper, the application of neural networks to study the design of short term load forecasting (STLF) Systems was explored. Our work presents a pragmatic methodology for short term load forecasting (STLF) using proposed two-stage model of wavelet transform (WT) and artificial neural network (ANN). It is a two-stage prediction system which involves wavelet decomposition of input data at the first stage and the decomposed data with another input is trained using a separate neural network to forecast the load. The forecasted load is obtained by reconstruction of the decomposed data. The hybrid model has been trained and validated using load data from Telangana State Electricity Board.

Keywords: electrical distribution systems, wavelet transform (WT), short term load forecasting (STLF), artificial neural network (ANN)

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Authors: Shu-Yuan Lin, Tung-Chin Chou

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As products become increasingly similar in competitive markets, achieving product segmentation and differentiation through packaging design has become the primary task when designing retail product packaging. When the main focus of brand marketing is no longer the product itself, emotional marketing, such as the use of humorous packaging designs, may be employed to successfully promote the brand. Such efforts will capture the hearts of consumers, generate discussions, and allow the brand to leave a deep impression in consumers. In this study, snack packaging was used to develop a relationship model that illustrated the effect of humorous packaging designs on brand awareness and brand attitude. The study was divided into three stages: In the first stage, in-depth interviews and focus group interviews were conducted with experts to construct 24 indicators for assessing humorous packaging designs. In the second stage, survey questionnaires were distributed to a young consumer group; the results showed that the group had a high and low product involvement with chocolate and dried shredded squid, respectively. Humorous packaging designs were subsequently created for two snack types to produce a study sample of 12 different packaging. In the third stage, packaging designs were evaluated by obtaining scores for the consumers’ brand awareness, brand attitude, and perceived effects of the packaging designs. Finally, a relationship model was developed to show the effect of humorous packaging designs on brand awareness and brand attitude, confirming that two perceived effects of humorous packaging designs (i.e., ‘pleasant and emotionally healing’ and ‘connected to people’s daily life’) exhibited a significant and positive effect on ‘perceived brand value,’ where the effect of ‘pleasant and emotionally healing’ was the most significant. In addition, ‘pleasant and emotionally healing’ exerted a significant and positive effect on ‘brand purchase intention.’ Furthermore, packaging designs with humorous elements helped foster brand awareness.

Keywords: brand awareness, brand attitude, humorous design, packaging design

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Authors: Mounia El Hafyani, Khalid El Himdi

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Precipitation is one of the key variables in water resource planning. The importance of modeling wet and dry durations is a crucial pointer in engineering hydrology. The objective of this study is to model and analyze the distribution of wet and dry durations. For this purpose, the daily rainfall data from 1967 to 2017 of the Moroccan city of Kenitra’s station are used. Three models are implemented for the distribution of wet and dry durations, namely the first-order Markov chain, the second-order Markov chain, and the truncated negative binomial law. The adherence of the data to the proposed models is evaluated using Chi-square and Kolmogorov-Smirnov tests. The Akaike information criterion is applied to assess the most effective model distribution. We go further and study the law of the number of wet and dry days among k consecutive days. The calculation of this law is done through an algorithm that we have implemented based on conditional laws. We complete our work by comparing the observed moments of the numbers of wet/dry days among k consecutive days to the calculated moment of the three estimated models. The study shows the effectiveness of our approach in modeling wet and dry durations of daily precipitation.

Keywords: Markov chain, rainfall, truncated negative binomial law, wet and dry durations

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Authors: Janne Engblom, Elias Oikarinen

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A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models are dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Arellano-Bover/Blundell-Bond Generalized method of moments (GMM) estimator which is an extension of the Arellano-Bond model where past values and different transformations of past values of the potentially problematic independent variable are used as instruments together with other instrumental variables. The Arellano–Bover/Blundell–Bond estimator augments Arellano–Bond by making an additional assumption that first differences of instrument variables are uncorrelated with the fixed effects. This allows the introduction of more instruments and can dramatically improve efficiency. It builds a system of two equations—the original equation and the transformed one—and is also known as system GMM. In this study, Finnish housing price dynamics were examined empirically by using the Arellano–Bover/Blundell–Bond estimation technique together with ordinary OLS. The aim of the analysis was to provide a comparison between conventional fixed-effects panel data models and dynamic panel data models. The Arellano–Bover/Blundell–Bond estimator is suitable for this analysis for a number of reasons: It is a general estimator designed for situations with 1) a linear functional relationship; 2) one left-hand-side variable that is dynamic, depending on its own past realizations; 3) independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; 4) fixed individual effects; and 5) heteroskedasticity and autocorrelation within individuals but not across them. Based on data of 14 Finnish cities over 1988-2012 differences of short-run housing price dynamics estimates were considerable when different models and instrumenting were used. Especially, the use of different instrumental variables caused variation of model estimates together with their statistical significance. This was particularly clear when comparing estimates of OLS with different dynamic panel data models. Estimates provided by dynamic panel data models were more in line with theory of housing price dynamics.

Keywords: dynamic model, fixed effects, panel data, price dynamics

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Authors: Joon-Hyung Kim, Him-Chan Lee, Jin-Hyuk Kim, Yong-Kab Lee, Young-Seok Choi

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The crude oil in an oil well exists in various phases such as gas, seawater, and sand, as well as oil. Therefore, a phase separator is needed at the front of a single-phase pump for pressurization and transfer. On the other hand, the application of a multiphase pump can provide such advantages as simplification of the equipment structure and cost savings, because there is no need for a phase separation process. Therefore, the crude oil transfer method using a multiphase pump is being applied to recently developed oil wells. Due to this increase in demand, technical demands for the development of multiphase pumps are sharply increasing, but the progress of research into related technologies is insufficient, due to the nature of multiphase pumps that require high levels of skills. This study was conducted to verify the reliability of pump performance evaluation using numerical analysis, which is the basis of the development of a multiphase pump. For this study, a model was designed by selecting the specifications of the pump under study. The performance of the designed model was evaluated through numerical analysis and experiment, and the results of the performance evaluation were compared to verify the reliability of the result using numerical analysis.

Keywords: multiphase pump, numerical analysis, experiment, performance evaluation, reliability verification

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Authors: M. Kadela

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The load caused by the traffic movement should be transferred in the road constructions in a harmless way to the pavement as follows: − on the stiff upper layers of the structure (e.g. layers of asphalt: abrading and binding), and − through the layers of principal and secondary substructure, − on the subsoil, directly or through an improved subsoil layer. Reliable description of the interaction proceeding in a system “road construction – subsoil” should be in such case one of the basic requirements of the assessment of the size of internal forces of structure and its durability. Analyses of road constructions are based on: − elements of mechanics, which allows to create computational models, and − results of the experiments included in the criteria of fatigue life analyses. Above approach is a fundamental feature of commonly used mechanistic methods. They allow to use in the conducted evaluations of the fatigue life of structures arbitrarily complex numerical computational models. Considering the work of the system “road construction – subsoil”, it is commonly accepted that, as a result of repetitive loads on the subsoil under pavement, the growth of relatively small deformation in the initial phase is recognized, then this increase disappears, and the deformation takes the character completely reversible. The reliability of calculation model is combined with appropriate use (for a given type of analysis) of constitutive relationships. Phenomena occurring in the initial stage of the system “road construction – subsoil” is unfortunately difficult to interpret in the modeling process. The classic interpretation of the behavior of the material in the elastic-plastic model (e-p) is that elastic phase of the work (e) is undergoing to phase (e-p) by increasing the load (or growth of deformation in the damaging structure). The paper presents the essence of the calibration process of cooperating subsystem in the calculation model of the system “road construction – subsoil”, created for the mechanistic analysis. Calibration process was directed to show the impact of applied constitutive models on its deformation and stress response. The proper comparative base for assessing the reliability of created. This work was supported by the on-going research project “Stabilization of weak soil by application of layer of foamed concrete used in contact with subsoil” (LIDER/022/537/L-4/NCBR/2013) financed by The National Centre for Research and Development within the LIDER Programme. M. Kadela is with the Department of Building Construction Elements and Building Structures on Mining Areas, Building Research Institute, Silesian Branch, Katowice, Poland (phone: +48 32 730 29 47; fax: +48 32 730 25 22; e-mail: m.kadela@ itb.pl). models should be, however, the actual, monitored system “road construction – subsoil”. The paper presents too behavior of subsoil under cyclic load transmitted by pavement layers. The response of subsoil to cyclic load is recorded in situ by the observation system (sensors) installed on the testing ground prepared for this purpose, being a part of the test road near Katowice, in Poland. A different behavior of the homogeneous subsoil under pavement is observed for different seasons of the year, when pavement construction works as a flexible structure in summer, and as a rigid plate in winter. Albeit the observed character of subsoil response is the same regardless of the applied load and area values, this response can be divided into: - zone of indirect action of the applied load; this zone extends to the depth of 1,0 m under the pavement, - zone of a small strain, extending to about 2,0 m.

Keywords: road structure, constitutive model, calculation model, pavement, soil, FEA, response of soil, monitored system

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Authors: M. Boudjerda, B. Touaibia, M. K. Mihoubi

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In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.

Keywords: water management, agricultural demand, dam and reservoir operation, Foum el-Gherza dam, dynamic programming, artificial neural network

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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Authors: Joann Douziech

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Individuals with intellectual and developmental disabilities (IDD) possess characteristics that present both challenges and gifts. Individuals with IDD require and are worthy of intentional, strategic, and specialized support throughout their lifespan to ensure optimum quality-of-life outcomes. The current global advocacy movement advancing the rights of individuals with IDD emphasizes a high degree of choice over life decisions. For some individuals, this degree of choice results in a variety of negative health and well-being outcomes. Improving the quality of life outcomes requires the combination of a commitment to the rights of the individual with a responsibility to provide support and choice commensurate with individual capacity. A belief that individuals with IDD are capable of learning and they are worthy of being taught provides the foundation for a holistic model of support throughout their lifespan. This model is based on three pillars of engineering the environment, promoting skill development and maintenance, and staff support. In an ever-changing world, supporting quality of life requires attention to moments, phases, and changes in stages throughout the lifespan. Balancing these complexities with strategic, responsive, and dynamic interventions enhances the quality of life of individuals with ID throughout their lifespan.

Keywords: achieving optimum quality of life, comprehensive support, lifespan approach, philosophy and pedagogy

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Authors: Zukhrof Romadhon, Nani Kurniati

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

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

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Authors: Nicolas Bigot, M'hamed Boutaous, Nahiene Hamila, Shihe Xin

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Composite materials with polymer matrices are widely used in most industrial areas, particularly in aeronautical and automotive ones. Thanks to the development of a high-performance thermoplastic semicrystalline polymer matrix, those materials exhibit more and more efficient properties. The polymer matrix in composite materials can manifest a specific crystalline structure characteristic of crystallization in a fibrous medium. In order to guarantee a good mechanical behavior of structures and to optimize their performances, it is necessary to define realistic mechanical constitutive laws of such materials considering their physical structure. The interaction between fibers and matrix is a key factor in the mechanical behavior of composite materials. Transcrystallization phenomena which develops in the matrix around the fibers constitute the interphase which greatly affects and governs the nature of the fiber-matrix interaction. Hence, it becomes fundamental to quantify its impact on the thermo-mechanical behavior of composites material in relationship with processing conditions. In this work, we propose a numerical model coupling the thermal and crystallization kinetics in long fiber-based composite materials, considering both the spherulitic and transcrystalline types of the induced structures. After validation of the model with comparison to results from the literature and noticing a good correlation, a parametric study has been led on the effects of the thermal kinetics, the fibers volume fractions, the deformation, and the pressure on the crystallization rate in the material, under processing conditions. The ratio of the transcrystallinity is highlighted and analyzed with regard to the thermal kinetics and gradients in the material. Experimental results on the process are foreseen and pave the way to establish a mechanical constitutive law describing, with the introduction of the role on the crystallization rates and types on the thermo-mechanical behavior of composites materials.

Keywords: composite materials, crystallization, heat transfer, modeling, transcrystallization

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Authors: Elif Aykin Dincer, Mustafa Erbas

Abstract:

The vacuum drying behavior of beef slices (10 x 4 x 0.2 cm3) was experimentally investigated at the temperature of 60, 70, and 80°C under 25 mbar ultimate vacuum pressure and the mathematical models (Lewis, Page, Midilli, Two-term, Wangh and Singh and Modified Henderson and Pabis) were used to fit the vacuum drying of beef slices. The increase in drying air temperature resulted in a decrease in drying time. It took approximately 206, 180 and 157 min to dry beef slices from an initial moisture content to a final moisture content of 0.05 kg water/kg dry matter at 60, 70 and 80 °C of vacuum drying, respectively. It is also observed that the drying rate increased with increasing drying temperature. The coefficients (R2), the reduced chi-square (x²) and root mean square error (RMSE) values were obtained by application of six models to the experimental drying data. The best model with the highest R2 and, the lowest x² and RMSE values was selected to describe the drying characteristics of beef slices. The Page model has shown a better fit to the experimental drying data as compared to other models. In addition, the effective moisture diffusivities of beef slices in the vacuum drying at 60 - 80 °C varied in the range of 1.05 – 1.09 x 10-10 m2/s. Consequently, this results can be used to simulate vacuum drying process of beef slices and improve efficiency of the drying process.

Keywords: beef slice, drying models, effective diffusivity, vacuum

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Authors: Fathi Abid, Bilel Kaffel

Abstract:

The olive tree, the olive harvest during winter season and the production of olive oil better known by professionals under the name of the crushing operation have interested institutional traders such as olive-oil offices and private companies such as food industry refining and extracting pomace olive oil as well as export-import public and private companies specializing in olive oil. The major problem facing producers of olive oil each winter campaign, contrary to what is expected, it is not whether the harvest will be good or not but whether the sale price will allow them to cover production costs and achieve a reasonable margin of profit or not. These questions are entirely legitimate if we judge by the importance of the issue and the heavy complexity of the uncertainty and competition made tougher by a high level of indebtedness and the experience and expertise of speculators and producers whose objectives are sometimes conflicting. The aim of this paper is to study the formation mechanism of olive oil prices in order to learn about speculators’ behavior and expectations in the market, how they contribute by their industry knowledge and their financial alliances and the size the financial challenge that may be involved for them to build private information hoses globally to take advantage. The methodology used in this paper is based on two stages, in the first stage we study econometrically the formation mechanisms of olive oil price in order to understand the market participant behavior by implementing ARMA, SARMA, GARCH and stochastic diffusion processes models, the second stage is devoted to prediction purposes, we use a combined wavelet- ANN approach. Our main findings indicate that olive oil market participants interact with each other in a way that they promote stylized facts formation. The unstable participant’s behaviors create the volatility clustering, non-linearity dependent and cyclicity phenomena. By imitating each other in some periods of the campaign, different participants contribute to the fat tails observed in the olive oil price distribution. The best prediction model for the olive oil price is based on a back propagation artificial neural network approach with input information based on wavelet decomposition and recent past history.

Keywords: olive oil price, stylized facts, ARMA model, SARMA model, GARCH model, combined wavelet-artificial neural network, continuous-time stochastic volatility mode

Procedia PDF Downloads 339

Authors: A. M. Naraghi, V. Gonzalez, M. O'Sullivan, C. G. Walker, M. Poshdar, F. Ying, M. Abdelmegid

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Discrete Event Simulation (DES) and Agent Based Simulation (ABS) are two simulation approaches that have been proposed to support decision-making in the construction industry. Despite the wide use of these simulation approaches in the construction field, their applications for production and material planning is still limited. This is largely due to the dynamic and complex nature of construction material supply chain systems. Moreover, managing the flow of construction material is not well integrated with site logistics in traditional construction planning methods. This paper presents a hybrid of DES and ABS to simulate on-site and off-site material supply processes. DES is applied to determine the best production scenarios with information of on-site production systems, while ABS is used to optimize the supply chain network. A case study of a construction piling project in New Zealand is presented illustrating the potential benefits of using the proposed hybrid simulation model in construction material flow planning. The hybrid model presented can be used to evaluate the impact of different decisions on construction supply chain management.

Keywords: construction supply-chain management, simulation modeling, decision-support tools, hybrid simulation

Procedia PDF Downloads 207

Authors: Tianyu Chen

Abstract:

China's school district education policy has encouraged parents to purchase properties in school districts with high-quality education resources. Shanghai has implemented "Simultaneous Admission to Public and Private Schools" (SAPPS) since 2018, which has covered all nine-year compulsory education by 2020. This study examines the impact of SAPPS on the housing market, specifically the premium effect of houses located in dual-school districts. Based on the Hedonic Pricing Model and the Signaling Theory, data is collected from 585 second-hand house transactions in Pudong New Area, Shanghai, and it is analyzed with the Difference-in-Differences (DID) model. The results indicate that the implementation of SAPPS has exacerbated the premium of dual school district housing and weakened the effect of the policy to a certain degree. To ensure equal access to education for all students, the government should work both on the supply and demand sides of the education resource equation.

Keywords: simultaneous admission to public and private schools, housing prices, education policy, education equity

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Authors: Magda Cepeda, Frances Hodgson, Ann Jopson

Abstract:

There are different barriers people face when choosing to cycle for commuting purposes. This study examined the role of psycho-social factors predicting the intention to cycle to commute in Mexico City. An extended version of the theory of planned behaviour was developed and utilized with a simple random sample of 401 road users. We applied exploratory and confirmatory factor analysis and after identifying five factors, a structural equation model was estimated to find the relationships among the variables. The results indicated that cycling attributes, attitudes to cycling, social comparison and social image and prestige were the most important factors influencing intention to cycle. Although the results from this study are specific to Mexico City, they indicate areas of interest to transportation planners in other regions especially in those cities where intention to cycle its linked to its perceived image and there is political ambition to instigate positive cycling cultures. Moreover, this study contributes to the current literature developing applications of the Theory of Planned Behaviour.

Keywords: cycling, latent variable model, perception, theory of planned behaviour

Procedia PDF Downloads 353

Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

Abstract:

Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Azlinda Saadon

Abstract:

This paper provides detail review on river bank erosion studies with respect to their processes, methods of measurements and factors governing river bank erosion. Bank erosion processes are commonly associated with river changes initiation and development, through width adjustment and planform evolution. It consists of two main types of erosion processes; basal erosion due to fluvial hydraulic force and bank failure under the influence of gravity. Most studies had only focused on one factor rather than integrating both factors. Evidences of previous works have shown integration between both processes of fluvial hydraulic force and bank failure. Bank failure is often treated as probabilistic phenomenon without having physical characteristics and the geotechnical aspects of the bank. This review summarizes the findings of previous investigators with respect to measurement techniques and prediction rates of river bank erosion through field investigation, physical model and numerical model approaches. Factors governing river bank erosion considering physical characteristics of fluvial erosion are defined.

Keywords: river bank erosion, bank erosion, dimensional analysis, geotechnical aspects

Procedia PDF Downloads 435

Authors: Chinazo Onyeka Eziuzo

Abstract:

This work presents the simulation and control of the flywheel system in the rotor of a wind turbine using Simulink and OpenFAST for assessing the effect on the mechanical loads. This concept allows the flywheel system to serve two main tasks: supporting the power system and mitigating the mechanical loads in the wind turbine. These tasks are grouped into four control scenarios; scenario 1 represents steadying the power infeed in the Flywheel, scenario 2 represents steadying power with FW and grid loss, scenario 3 represents mitigating excitations from gravity, and scenario 4 represents damping in-plane blade vibrations. The s-function of the OpenFAST model was used to substitute the given 1st Eigen mode model of the WT. After that, the simulations were run for the above-listed scenarios. Additionally, the effects of the control options on the mechanical loads were assessed, and it was established that the FW system assists in steadying infeed power and mechanical load mitigation.

Keywords: simulation, control, wind turbine, OpenFAST

Procedia PDF Downloads 127