Search results for: reduce order aeroelastic model (ROAM)

Authors: Yoshio Kurosawa

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The applications of soundproof materials for reduction of high frequency automobile interior noise have been researched. This paper presents a sound pressure prediction technique including wind noise by Hybrid Statistical Energy Analysis (HSEA) in order to reduce weight of acoustic insulations. HSEA uses both analytical SEA and experimental SEA. As a result of chassis dynamo test and road test, the validity of SEA modeling was shown, and utility of the method was confirmed.

Keywords: vibration, noise, road noise, statistical energy analysis

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Authors: C. Shih, J. R. Wang, H. C. Chang, S. W. Chen, S. C. Chiang, T. Y. Yu

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After the measurement uncertainty recapture (MUR) power uprates, Kuosheng nuclear power plant (NPP) was uprated the power from 2894 MWt to 2943 MWt. For power upgrade, several codes (e.g., TRACE, RELAP5, etc.) were applied to assess the safety of Kuosheng NPP. Hence, the main work of this research is to establish a RELAP5/MOD3.3 model of Kuosheng NPP with SNAP interface. The establishment of RELAP5/SNAP model was referred to the FSAR, training documents, and TRACE model which has been developed and verified before. After completing the model establishment, the startup test scenarios would be applied to the RELAP5/SNAP model. With comparing the startup test data and TRACE analysis results, the applicability of RELAP5/SNAP model would be assessed.

Keywords: RELAP5, TRACE, SNAP, BWR

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Authors: Burcu Akyildiz, Cigdem Kadaifci, Y. Ilker Topcu, Burc Ulengin

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In today’s business environment, companies should make strategic decisions to gain sustainable competitive advantage. Order selection is a crucial issue among these decisions especially for steel production industry. When the companies allocate a high proportion of their design and production capacities to their ongoing projects, determining which customer order should be chosen among the potential orders without exceeding the remaining capacity is the major critical problem. In this study, it is aimed to identify and prioritize the evaluation factors for the customer order selection problem. Conjoint analysis is used to examine the importance level of each factor which is determined as the potential profit rate per unit of time, the compatibility of potential order with available capacity, the level of potential future order with higher profit, customer credit of future business opportunity, and the negotiability level of production schedule for the order.

Keywords: conjoint analysis, order prioritization, profit management, structural steel firm

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Authors: Adrien Chatel, Ehsan Askari Mahvelati, Laurent Fitschy

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Once-Through-Steam-Generators are commonly used in the oil-sand industry in the heavy fuel oil extraction process. They are composed of three main parts: the burner, the radiant and convective sections. Natural gas is burned through staged diffusive flames stabilized by the burner. The heat generated by the combustion is transferred to the water flowing through the piping system in the radiant and convective sections. The steam produced within the pipes is then directed to the ground to reduce the oil viscosity and allow its pumping. With the rapid development of the oil-sand industry, the number of OTSG in operation has increased as well as the associated emissions of environmental pollutants, especially the Nitrous Oxides (NOₓ). To limit the environmental degradation, various international environmental agencies have established regulations on the pollutant discharge and pushed to reduce the NOₓ release. To meet these constraints, OTSG constructors have to rely on more and more advanced tools to study and predict the NOₓ emission. With the increase of the computational resources, Computational Fluid Dynamics (CFD) has emerged as a flexible tool to analyze the combustion and pollutant formation process. Moreover, to optimize the burner operating condition regarding the NOx emission, field characterization and measurements are usually accomplished. However, these kinds of experimental campaigns are particularly time-consuming and sometimes even impossible for industrial plants with strict operation schedule constraints. Therefore, the application of CFD seems to be more adequate in order to provide guidelines on the NOₓ emission and reduction problem. In the present work, two different software are employed to simulate the combustion process in an OTSG, namely the commercial software ANSYS Fluent and the open source software OpenFOAM. RANS (Reynolds-Averaged Navier–Stokes) equations combined with the Eddy Dissipation Concept to model the combustion and closed by the k-epsilon model are solved. A mesh sensitivity analysis is performed to assess the independence of the solution on the mesh. In the first part, the results given by the two software are compared and confronted with experimental data as a mean to assess the numerical modelling. Flame temperatures and chemical composition are used as reference fields to perform this validation. Results show a fair agreement between experimental and numerical data. In the last part, OpenFOAM is employed to simulate several operating conditions, and an Emission Characteristic Map of the combustion system is generated. The sources of high NOₓ production inside the OTSG are pointed and correlated to the physics of the flow. CFD is, therefore, a useful tool for providing an insight into the NOₓ emission phenomena in OTSG. Sources of high NOₓ production can be identified, and operating conditions can be adjusted accordingly. With the help of RANS simulations, an Emission Characteristics Map can be produced and then be used as a guide for a field tune-up.

Keywords: combustion, computational fluid dynamics, nitrous oxides emission, once-through-steam-generators

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Authors: Ahmed Mohamed Elnady Mohamed Elsafty

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This paper explains a developed applied objective model to measure the culture qualitatively and quantitatively, whether in individuals or in teams, in order to be able to use culture correctly or modify it efficiently. This model provides precise measurements and consistent interpretations by being comprehensive, updateable, and protected from being misled by imitations. Methodically, the provided model divides the culture into seven dimensions (total 43 cultural factors): First dimension is outcome-orientation which consists of five factors and should be highest in leaders. Second dimension is details-orientation which consists of eight factors and should be in highest intelligence members. Third dimension is team-orientation which consists of five factors and should be highest in instructors or coaches. Fourth dimension is change-orientation which consists of five factors and should be highest in soldiers. Fifth dimension is people-orientation which consists of eight factors and should be highest in media members. Sixth dimension is masculinity which consists of seven factors and should be highest in hard workers. Last dimension is stability which consists of seven factors and should be highest in soft workers. In this paper, the details of all cultural factors are explained. Practically, information collection about each cultural factor in the targeted person or team is essential in order to calculate the degrees of all cultural factors using the suggested equation of multiplying 'the score of factor presence' by 'the score of factor strength'. In this paper, the details of how to build each score are explained. Based on the highest degrees - to identify which cultural dimension is the prominent - choosing the tested individual or team in the supposedly right position at the right time will provide a chance to use minimal efforts to make everyone aligned to the organization’s objectives. In other words, making everyone self-motivated by setting him/her at the right source of motivation is the most effective and efficient method to achieve high levels of competency, commitment, and sustainability. Modifying a team culture can be achieved by excluding or including new members with relatively high or low degrees in specific cultural factors. For conclusion, culture is considered as the software of the human beings and it is one of the major compression factors on the managerial discretion. It represents the behaviors, attitudes, and motivations of the human resources which are vital to enhance quality and safety, expanding the market share, and defending against attacks from external environments. Thus, it is tremendously essential and useful to use such a comprehensive model to measure, use, and modify culture.

Keywords: culture dimensions, culture factors, culture measurement, cultural analysis, cultural modification, self-motivation, alignment to objectives, competency, sustainability

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Authors: Yinglisong, Jingge Chen, Jingxuan Chen, Yan Wang, Hui Huang, Jing Zhnag, Qianqian Zhang, Zhenzhen Zhang, Ji Zhang

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Purpose: The study aims to establish a nomogram prediction model for postpartum hemorrhage (PPH) in vaginal delivery. Patients and Methods: Clinical data were retrospectively collected from vaginal delivery patients admitted to a hospital in Zhengzhou, China, from June 1, 2022 - October 31, 2022. Univariate and multivariate logistic regression were used to filter out independent risk factors. A nomogram model was established for PPH in vaginal delivery based on the risk factors coefficient. Bootstrapping was used for internal validation. To assess discrimination and calibration, receiver operator characteristics (ROC) and calibration curves were generated in the derivation and validation groups. Results: A total of 1340 cases of vaginal delivery were enrolled, with 81 (6.04%) having PPH. Logistic regression indicated that history of uterine surgery, induction of labor, duration of first labor, neonatal weight, WBC value (during the first stage of labor), and cervical lacerations were all independent risk factors of hemorrhage (P <0.05). The area-under-curve (AUC) of ROC curves of the derivation group and the validation group were 0.817 and 0.821, respectively, indicating good discrimination. Two calibration curves showed that nomogram prediction and practical results were highly consistent (P = 0.105, P = 0.113). Conclusion: The developed individualized risk prediction nomogram model can assist midwives in recognizing and diagnosing high-risk groups of PPH and initiating early warning to reduce PPH incidence.

Keywords: vaginal delivery, postpartum hemorrhage, risk factor, nomogram

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Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

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Authors: Ehsan Mehryaar, Reza Bushehri

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One of the principal parameters defining the clay soil dynamic response is the strain-shear modulus relation. Predicting the strain and, subsequently, shear modulus reduction of the soil is essential for performance analysis of structures exposed to earthquake and dynamic loadings. Many soil properties affect soil’s dynamic behavior. In order to capture those effects, in this study, a database containing 1193 data points consists of maximum shear modulus, strain, moisture content, initial void ratio, plastic limit, liquid limit, initial confining pressure resulting from dynamic laboratory testing of 21 clays is collected for predicting the shear modulus vs. strain curve of soil. A model based on an extreme gradient boosting technique is proposed. A tree-structured parzan estimator hyper-parameter tuning algorithm is utilized simultaneously to find the best hyper-parameters for the model. The performance of the model is compared to the existing empirical equations using the coefficient of correlation and root mean square error.

Keywords: XGBoost, hyper-parameter tuning, soil shear modulus, dynamic response

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Authors: Jean Marie Ntaganda, Froduald Minani, Wellars Banzi, Lydie Mpinganzima, Japhet Niyobuhungiro, Jean Bosco Gahutu, Vincent Dusabejambo, Immaculate Kambutse

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In this paper, we present a nonlinear dynamic model for the interactive mechanism of the cardiovascular and respiratory system. The model is designed and analyzed for human during physical exercises. In order to verify the adequacy of the designed model, data collected in Rwanda are used for validation. We have simulated the impact of heart rate and alveolar ventilation as controls of cardiovascular and respiratory system respectively to steady state response of the main cardiovascular hemodynamic quantities i.e., systemic arterial and venous blood pressures, arterial oxygen partial pressure and arterial carbon dioxide partial pressure, to the stabilised values of controls. We used data collected in Rwanda for both male and female during physical activities. We obtained a good agreement with physiological data in the literature. The model may represent an important tool to improve the understanding of exercise physiology.

Keywords: exercise, cardiovascular/respiratory, hemodynamic quantities, numerical simulation, physical activity, sportsmen in Rwanda, system

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Authors: Ishit Sheth, Chandrasekhar Jinendran, Chinmaya Ranjan Sahu

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A fourteen degree of freedom (DOF) ride and handling control mathematical model is developed for a car using generalized boltzmann hamel equation which will create a basis for design of ride and handling controller. Mathematical model developed yield equations of motion for non-holonomic constrained systems in quasi-coordinates. The governing differential equation developed integrates ride and handling control of car. Model-based systems engineering approach is implemented for simulation using matlab/simulink, vehicle’s response in different DOF is examined and later validated using commercial software (ADAMS). This manuscript involves detailed derivation of full car vehicle model which provides response in longitudinal, lateral and yaw motion to demonstrate the advantages of the developed model over the existing dynamic model. The dynamic behaviour of the developed ride and handling model is simulated for different road conditions.

Keywords: Full Vehicle Model, MBSE, Non Holonomic Constraints, Boltzmann Hamel Equation

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Authors: M. Gulam Kibria, Shourav Ahmed, Kais Zaman

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In system analysis, the information on the uncertain input variables cause uncertainty in the system responses. Different probabilistic approaches for uncertainty representation and propagation in such cases exist in the literature. Different uncertainty representation approaches result in different outputs. Some of the approaches might result in a better estimation of system response than the other approaches. The NASA Langley Multidisciplinary Uncertainty Quantification Challenge (MUQC) has posed challenges about uncertainty quantification. Subproblem A, the uncertainty characterization subproblem, of the challenge posed is addressed in this study. In this subproblem, the challenge is to gather knowledge about unknown model inputs which have inherent aleatory and epistemic uncertainties in them with responses (output) of the given computational model. We use two different methodologies to approach the problem. In the first methodology we use sampling-based uncertainty propagation with first order error analysis. In the other approach we place emphasis on the use of Percentile-Based Optimization (PBO). The NASA Langley MUQC’s subproblem A is developed in such a way that both aleatory and epistemic uncertainties need to be managed. The challenge problem classifies each uncertain parameter as belonging to one the following three types: (i) An aleatory uncertainty modeled as a random variable. It has a fixed functional form and known coefficients. This uncertainty cannot be reduced. (ii) An epistemic uncertainty modeled as a fixed but poorly known physical quantity that lies within a given interval. This uncertainty is reducible. (iii) A parameter might be aleatory but sufficient data might not be available to adequately model it as a single random variable. For example, the parameters of a normal variable, e.g., the mean and standard deviation, might not be precisely known but could be assumed to lie within some intervals. It results in a distributional p-box having the physical parameter with an aleatory uncertainty, but the parameters prescribing its mathematical model are subjected to epistemic uncertainties. Each of the parameters of the random variable is an unknown element of a known interval. This uncertainty is reducible. From the study, it is observed that due to practical limitations or computational expense, the sampling is not exhaustive in sampling-based methodology. That is why the sampling-based methodology has high probability of underestimating the output bounds. Therefore, an optimization-based strategy to convert uncertainty described by interval data into a probabilistic framework is necessary. This is achieved in this study by using PBO.

Keywords: aleatory uncertainty, epistemic uncertainty, first order error analysis, uncertainty quantification, percentile-based optimization

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Authors: Flaurence Benjamain, Michel Casperance

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We present in this paper, first, a comparative study of three mathematical theories to achieve the fusion of information sources. This study aims to identify the characteristics inherent in theories of possibilities, belief functions (DST) and plausible and paradoxical reasoning to establish a strategy of choice that allows us to adopt the most appropriate theory to solve a problem of fusion in order, taking into account the acquired information and imperfections that accompany them. Using the new theory of plausible and paradoxical reasoning, also called Dezert-Smarandache Theory (DSmT), to fuse information multi-sources needs, at first step, the generation of the composites events witch is, in general, difficult. Thus, we present in this paper a new approach to construct pertinent paradoxical classes based on gray levels histograms, which also allows to reduce the cardinality of the hyper-powerset. Secondly, we developed a new technique for order and coding generalized focal elements. This method is exploited, in particular, to calculate the cardinality of Dezert and Smarandache. Then, we give an experimentation of classification of a remote sensing image that illustrates the given methods and we compared the result obtained by the DSmT with that resulting from the use of the DST and theory of possibilities.

Keywords: segmentation, image, approach, vision computing

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Authors: Jolanta Tamošaitienė

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The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.

Keywords: assessment, environment, agile, model, risk

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Authors: Ti-Jun Xiao, Zhe Xu

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Controllability is one of the fundamental issues in control systems. In this paper, we study the controllability of second order evolutional control systems in Hilbert spaces with memory and boundary controls, which model dynamic behaviors of some viscoelastic materials. Transferring the control problem into a moment problem and showing the Riesz property of a family of functions related to Cauchy problems for some integrodifferential equations, we obtain a general boundary controllability theorem for these second order evolutional control systems. This controllability theorem is applicable to various concrete 1D viscoelastic systems and recovers some previous related results. It is worth noting that Riesz sequences can be used for numerical computations of the control functions and the identification of new Riesz sequence is of independent interest for the basis-function theory. Moreover, using the Riesz sequences, we obtain the existence and uniqueness of (weak) solutions to these second order evolutional control systems in Hilbert spaces. Finally, we derive the exact boundary controllability of a viscoelastic beam equation, as an application of our abstract theorem.

Keywords: evolutional control system, controllability, boundary control, existence and uniqueness

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Authors: Eiji Nakamachi, Tsuyoshi Eguchi, Sayo Yamamoto, Yusuke Morita, H. Sakamoto

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In this study, we aim to reveal the relationship between the meniscal tearing and the articular cartilage injury of knee joint by using the dynamic explicit finite element (FE) method. Meniscal injuries reduce its functional ability and consequently increase the load on the articular cartilage of knee joint. In order to prevent the induction of osteoarthritis (OA) caused by meniscal injuries, many medical treatment techniques, such as artificial meniscus replacement and meniscal regeneration, have been developed. However, it is reported that these treatments are not the comprehensive methods. In order to reveal the fundamental mechanism of OA induction, the mechanical characterization of meniscus under the condition of normal and injured states is carried out by using FE analyses. At first, a FE model of the human knee joint in the case of normal state – ‘intact’ - was constructed by using the magnetron resonance (MR) tomography images and the image construction code, Materialize Mimics. Next, two types of meniscal injury models with the radial tears of medial and lateral menisci were constructed. In FE analyses, the linear elastic constitutive law was adopted for the femur and tibia bones, the visco-hyperelastic constitutive law for the articular cartilage, and the visco-anisotropic hyperelastic constitutive law for the meniscus, respectively. Material properties of articular cartilage and meniscus were identified using the stress-strain curves obtained by our compressive and the tensile tests. The numerical results under the normal walking condition revealed how and where the maximum compressive stress occurred on the articular cartilage. The maximum compressive stress and its occurrence point were varied in the intact and two meniscal tear models. These compressive stress values can be used to establish the threshold value to cause the pathological change for the diagnosis. In this study, FE analyses of knee joint were carried out to reveal the influence of meniscal injuries on the cartilage injury. The following conclusions are obtained. 1. 3D FE model, which consists femur, tibia, articular cartilage and meniscus was constructed based on MR images of human knee joint. The image processing code, Materialize Mimics was used by using the tetrahedral FE elements. 2. Visco-anisotropic hyperelastic constitutive equation was formulated by adopting the generalized Kelvin model. The material properties of meniscus and articular cartilage were determined by curve fitting with experimental results. 3. Stresses on the articular cartilage and menisci were obtained in cases of the intact and two radial tears of medial and lateral menisci. Through comparison with the case of intact knee joint, two tear models show almost same stress value and higher value than the intact one. It was shown that both meniscal tears induce the stress localization in both medial and lateral regions. It is confirmed that our newly developed FE analysis code has a potential to be a new diagnostic system to evaluate the meniscal damage on the articular cartilage through the mechanical functional assessment.

Keywords: finite element analysis, hyperelastic constitutive law, knee joint injury, meniscal tear, stress concentration

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Authors: Pedram Saadati, Zahra Nazari

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In the last decade, the role and importance of knowledge-based technological businesses in the insurance industry has greatly increased, and due to the weakness of previous studies in Iran, the current research deals with the design of the InsurTech empowerment model. In order to obtain the conceptual model of the research, a hybrid framework has been used. The statistical population of the research in the qualitative part were experts, and in the quantitative part, the InsurTech activists. The tools of data collection in the qualitative part were in-depth and semi-structured interviews and structured self-interaction matrix, and in the quantitative part, a researcher-made questionnaire. In the qualitative part, 55 indicators, 20 components and 8 concepts (dimensions) were obtained by the content analysis method, then the relationships of the concepts with each other and the levels of the components were investigated. In the quantitative part, the information was analyzed using the descriptive analytical method in the way of path analysis and confirmatory factor analysis. The proposed model consists of eight dimensions of supporter capability, supervisor of insurance innovation ecosystem, managerial, financial, technological, marketing, opportunity identification, innovative InsurTech capabilities. The results of statistical tests in identifying the relationships of the concepts with each other have been examined in detail and suggestions have been presented in the conclusion section.

Keywords: insurTech, knowledge-base, empowerment model, factor analysis, insurance

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Authors: James M. Wakiru, Liliane Pintelon, Peter Muchiri, Peter Chemweno

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The fast-changing business and operational environment are forcing organizations to adopt asset performance management strategies, not only to reduce costs but also maintain operational and production policies while addressing demand. To attain optimal asset performance management, a framework that ensures a continuous and systematic approach to analyzing an organization’s current maturity level and expected improvement regarding asset maintenance processes, strategies, technologies, capabilities, and systems is essential. Moreover, this framework while addressing maintenance-intensive organizations should consider the diverse business, operational and technical context (often dynamic) an organization is in and realistically prescribe or relate to the appropriate tools and systems the organization can potentially employ in the respective level, to improve and attain their maturity goals. This paper proposes an asset maintenance maturity model to assess the current capabilities, strength and weaknesses of maintenance processes an organization is using and analyze gaps for improvement via structuring set levels of achievement. At the epicentre of the proposed framework is the utilization of maintenance objective selected by an organization for various maintenance optimization programs. The framework adapts the Capability Maturity Model of assessing the maintenance process maturity levels in the organization.

Keywords: asset maintenance, maturity models, maintenance objectives, optimization

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Authors: Nikhil Yadav, Shubham Verma

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Gas lift is a common technique used to optimize oil production in wells. Prosper software is a powerful tool for modeling and optimizing gas lift systems in oil wells. This review paper examines the effectiveness of Prosper software in optimizing gas lift systems in oil-producing wells. The literature review identified several studies that demonstrated the use of Prosper software to adjust injection rate, depth, and valve characteristics to optimize gas lift system performance. The results showed that Prosper software can significantly improve production rates and reduce operating costs in oil-producing wells. However, the accuracy of the model depends on the accuracy of the input data, and the cost of Prosper software can be high. Therefore, further research is needed to improve the accuracy of the model and evaluate the cost-effectiveness of using Prosper software in gas lift system optimization

Keywords: gas lift, prosper software, injection rate, operating costs, oil-producing wells

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Authors: Derradji Chebli, Abdallah Bouguettoucha, Abdelbaki Reffas Khalil Guediri, Abdeltif Amrane

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The removal of Methyl Green dye (MG) from aqueous solutions using modified P-brutia cones (PBH and PBN), has been investigated work. The physical parameters such as pH, temperature, initial MG concentration, ionic strength are examined in batch experiments on the sorption of the dye. Adsorption removal of MG was conducted at natural pH 4.5 because the dye is only stable in the range of pH 3.8 to 5. It was observed in experiments that the P-brutia cones treated with NaOH (PBN) exhibited high affinity and adsorption capacity compared to the MG P-brutia cones treated with HCl (PBH) and biosorption capacity of modified P-brutia cones (PBN and PBH) was enhanced by increasing the temperature. This is confirmed by the thermodynamic parameters (ΔG° and ΔH°) which show that the adsorption of MG was spontaneous and endothermic in nature. The positive values of ΔS° suggested an irregular increase in the randomness for both adsorbent (PBN and PBH) during the adsorption process. The kinetic model pseudo-first order, pseudo-second order, and intraparticle diffusion coefficient were examined to analyze the sorption process; they showed that the pseudo-second-order model is the one that best describes the adsorption process (MG) on PBN and PBH with a correlation coefficient R²> 0.999. The ionic strength has shown that it has a negative impact on the adsorption of MG on two supports. A reduction of 68.5% of the adsorption capacity for a value Ce=30 mg/L was found for the PBH, while the PBN did not show a significant influence of the ionic strength on adsorption especially in the presence of NaCl. Among the tested isotherm models, the Langmuir isotherm was found to be the most relevant to describe MG sorption onto modified P-brutia cones with a correlation factor R²>0.999. The capacity adsorption of P-brutia cones, was confirmed for the removal of a dye, MG, from aqueous solution. We note also that P-brutia cones is a material very available in the forest and low-cost biomaterial

Keywords: adsorption, p-brutia cones, forest wastes, dyes, isotherm

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Authors: Farnaz Yusuf, Naseem A. Gaur

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The increase in environmental concerns, rapid depletion of fossil fuel reserves and intense interest in achieving energy security has led to a global research effort towards developing renewable sources of fuels. Second generation biofuels have attracted more attention recently as the use of lignocellulosic biomass can reduce fossil fuel dependence and is environment-friendly. Xylose is the main pentose and second most abundant sugar after glucose in lignocelluloses. Saccharomyces cerevisiae does not readily uptake and use pentose sugars. For an economically feasible biofuel production, both hexose and pentose sugars must be fermented to ethanol. Therefore, it is important to develop S. cerevisiae host platforms with more efficient xylose utilization. This work aims to construct a xylose fermenting yeast strains with engineered oxido-reductative pathway for xylose metabolism. Engineered strain was further improved by adaptive evolutionary engineering approach. The engineered strain is able to grow on xylose as sole carbon source with the maximum ethanol yield of 0.39g/g xylose and productivity of 0.139g/l/h at 96 hours. The further improvement in strain development involves over expression of pentose phosphate pathway and protein engineering of xylose reductase/xylitol dehydrogenase to change their cofactor specificity in order to reduce xylitol accumulation.

Keywords: biofuel, lignocellulosic biomass, saccharomyces cerevisiae, xylose

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Authors: Sidrah Ahmed

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The river and lakes flows are modeled mathematically by shallow water equations that are depth-averaged Reynolds Averaged Navier-Stokes equations under Boussinesq approximation. The temperature stratification dynamics influence the water quality and mixing characteristics. It is mainly due to the atmospheric conditions including air temperature, wind velocity, and radiative forcing. The experimental observations are commonly taken along vertical scales and are not sufficient to estimate small turbulence effects of temperature variations induced characteristics of shallow flows. Wind shear stress over the water surface influence flow patterns, heat fluxes and thermodynamics of water bodies as well. Hence it is crucial to couple temperature gradients with shallow water model to estimate the atmospheric effects on flow patterns. The Ripa system has been introduced to study ocean currents as a variant of shallow water equations with addition of temperature variations within the flow. Ripa model is a hyperbolic system of partial differential equations because all the eigenvalues of the system’s Jacobian matrix are real and distinct. The time steps of a numerical scheme are estimated with the eigenvalues of the system. The solution to Riemann problem of the Ripa model is composed of shocks, contact and rarefaction waves. Solving Ripa model with Riemann initial data with the central schemes is difficult due to the eigen structure of the system.This works presents the comparison of four different finite difference schemes for the numerical solution of Riemann problem for Ripa model. These schemes include Lax-Friedrichs, Lax-Wendroff, MacCormack scheme and a higher order finite difference scheme with WENO method. The numerical flux functions in both dimensions are approximated according to these methods. The temporal accuracy is achieved by employing TVD Runge Kutta method. The numerical tests are presented to examine the accuracy and robustness of the applied methods. It is revealed that Lax-Freidrichs scheme produces results with oscillations while Lax-Wendroff and higher order difference scheme produce quite better results.

Keywords: finite difference schemes, Riemann problem, shallow water equations, temperature gradients

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Authors: P. Javid, A. Aeenmehr, J. Taghavifar

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In this paper, supply air pressure of HVAC system has been modeled with second-order transfer function plus dead-time. In HVAC system, the desired input has step changes, and the output of proposed control system should be able to follow the input reference, so the idea of using model based predictive control is proceeded and designed in this paper. The closed loop control system is implemented in MATLAB software and the simulation results are provided. The simulation results show that the model based predictive control is able to control the plant properly.

Keywords: air conditioning system, GPC, dead time, air supply control

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Authors: Guowei Hou, Lixin Yu, Wei Zhuang, Hui Qin, Xue Yang

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Formal verification is proposed to ensure the correctness of the design and make functional verification more efficient. As cache plays a vital role in the design of System on Chip (SoC), and cache with Memory Management Unit (MMU) and cache memory unit makes the state space too large for simulation to verify, then a formal verification is presented for such system design. In the paper, a formal model checking verification flow is suggested and a new cache memory model which is called “exhaustive search model” is proposed. Instead of using large size ram to denote the whole cache memory, exhaustive search model employs just two cache blocks. For cache system contains data cache (Dcache) and instruction cache (Icache), Dcache memory model and Icache memory model are established separately using the same mechanism. At last, the novel model is employed to the verification of a cache which is module of a custom-built SoC system that has been applied in practical, and the result shows that the cache system is verified correctly using the exhaustive search model, and it makes the verification much more manageable and flexible.

Keywords: cache system, formal verification, novel model, system on chip (SoC)

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Authors: Owamah Hilary, O. C. Izinyon

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Many existing biogas kinetic models are difficult to apply to substrates they were not developed for, as they are substrate specific. Biodegradability kinetic (BIK) model and maximum biogas production potential and stability assessment (MBPPSA) model were therefore developed in this study for the anaerobic co-digestion of food waste and maize husk. Biodegradability constant (k) was estimated as 0.11d-1 using the BIK model. The results of maximum biogas production potential (A) obtained using the MBPPSA model corresponded well with the results obtained using the popular but complex modified Gompertz model for digesters B-1, B-2, B-3, B-4, and B-5. The (If) value of MBPPSA model also showed that digesters B-3, B-4, and B-5 were stable, while B-1 and B-2 were unstable. Similar stability observation was also obtained using the modified Gompertz model. The MBPPSA model can therefore be used as alternative model for anaerobic digestion feasibility studies and plant design.

Keywords: biogas, inoculum, model development, stability assessment

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Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

Abstract:

In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: artificial neural network, Taguchi method, real estate valuation model, investors

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Authors: Chui Ka Shing

Abstract:

This case study research attempts to examine the use of the Bar Model Method approach in learning and teaching mathematics in a primary school in Hong Kong. The objectives of the study are to find out to what extent (a) the Bar Model Method approach enhances the construction of students’ mathematics concepts, and (b) the school-based mathematics curriculum development with adopting the Bar Model Method approach. This case study illuminates the effectiveness of using the Bar Model Method to solve mathematics problems from Primary 1 to Primary 6. Some effective pedagogies and assessments were developed to strengthen the use of the Bar Model Method across year levels. Suggestions including school-based curriculum development for using Bar Model Method and further study were discussed.

Keywords: bar model method, curriculum development, mathematics education, problem solving

Procedia PDF Downloads 221

Authors: Basavaraj R. Endigeri, S. G. Sarganachari

Abstract:

Steel is widely used in machine parts, structural equipment and many other applications. In many steel structural elements, holes of different shapes and orientations are made with a view to satisfy the design requirements. The presence of holes in steel elements creates stress concentration, which eventually reduce the mechanical strength of the structure. Therefore, it is of great importance to investigate the state of stress around the holes for the safety and properties design of such elements. By literature survey, it is known that till date, there is no analytical solution to reduce the stress concentration by providing auxiliary holes at a definite location and radii in a steel plate. The numerical method can be used to determine the optimum location and radii of auxiliary holes. In the present work plate with an elliptical hole, for a steel material subjected to uniaxial load is analyzed and the effect of stress concentration is graphically represented .The introduction of auxiliary holes at a optimum location and radii with its effect on stress concentration is also represented graphically. The finite element analysis package ANSYS 11.0 is used to analyse the steel plate. The analysis is carried out using a plane 42 element. Further the ANSYS optimization model is used to determine the location and radii for optimum values of auxiliary hole to reduce stress concentration. All the results for different diameter to plate width ratio are presented graphically. The results of this study are in the form of the graphs for determining the locations and diameter of optimal auxiliary holes. The graph of stress concentration v/s central hole diameter to plate width ratio. The Finite Elements results of the study indicates that the stress concentration effect of central elliptical hole in an uniaxial loaded plate can be reduced by introducing auxiliary holes on either side of the central circular hole.

Keywords: finite element method, optimization, stress concentration factor, auxiliary holes

Procedia PDF Downloads 453

Authors: Lucas Paganin, Viliam Makis

Abstract:

With the advent of globalization, the market competition has become a major issue for most companies. One of the main strategies to overcome this situation is the quality improvement of the product at a lower cost to meet customers’ expectations. In order to achieve the desired quality of products, it is important to control the process to meet the specifications, and to implement the optimal maintenance policy for the machines and the production lines. Thus, the overall objective is to reduce process variation and the production and maintenance costs. In this paper, an integrated model involving Statistical Process Control (SPC) and maintenance is developed to achieve this goal. Therefore, the main focus of this paper is to develop the jointly optimal maintenance and statistical process control policy minimizing the total long run expected average cost per unit time. In our model, the production process can go out of control due to either the deterioration of equipment or other assignable causes. The equipment is also subject to failures in any of the operating states due to deterioration and aging. Hence, the process mean is controlled by an Xbar control chart using equidistant sampling epochs. We assume that the machine inspection epochs are the times when the control chart signals an out-of-control condition, considering both true and false alarms. At these times, the production process will be stopped, and an investigation will be conducted not only to determine whether it is a true or false alarm, but also to identify the causes of the true alarm, whether it was caused by the change in the machine setting, by other assignable causes, or by both. If the system is out of control, the proper actions will be taken to bring it back to the in-control state. At these epochs, a maintenance action can be taken, which can be no action, or preventive replacement of the unit. When the equipment is in the failure state, a corrective maintenance action is performed, which can be minimal repair or replacement of the machine and the process is brought to the in-control state. SMDP framework is used to formulate and solve the joint control problem. Numerical example is developed to demonstrate the effectiveness of the control policy.

Keywords: maintenance, semi-Markov decision process, statistical process control, Xbar control chart

Procedia PDF Downloads 93

Authors: Duncan Fraser

Abstract:

A 3-Dimensional (3D) conceptual site model was developed using the Leapfrog Works® platform utilising a comprehensive historical dataset for a large former Gasworks site in Fitzroy, Melbourne. The gasworks had been constructed across two fractured geological units with varying hydraulic conductivities. A Newer Volcanic (basaltic) outcrop covered approximately half of the site and was overlying a fractured Melbourne formation (Siltstone) bedrock outcropping over the remaining portion. During the investigative phase of works, a dense non-aqueous phase liquid (DNAPL) plume (coal tar) was identified within both geological units in the subsurface originating from multiple sources, including gasholders, tar wells, condensers, and leaking pipework. The first stage of model development was undertaken to determine the horizontal and vertical extents of the coal tar in the subsurface and assess the potential causality between potential sources, plume location, and site geology. Concentrations of key contaminants of interest (COIs) were also interpolated within Leapfrog to refine the distribution of contaminated soils. The model was subsequently used to develop a robust soil remediation strategy and achieve endorsement from an Environmental Auditor. A change in project scope, following the removal and validation of the three former gasholders, necessitated the additional excavation of a significant volume of residual contaminated rock to allow for the future construction of two-story underground basements. To assess financial liabilities associated with the offsite disposal or thermal treatment of material, the 3D model was updated with three years of additional analytical data from the active remediation phase of works. Chemical concentrations and the residual tar plume within the rock fractures were modelled to pre-classify the in-situ material and enhance separation strategies to prevent the unnecessary treatment of material and reduce costs.

Keywords: 3D model, contaminated land, Leapfrog, remediation

Procedia PDF Downloads 136

Authors: Nacer Eddine Chelbi, Ayet Bagane, Annie Saleh, Claude Sauvageau, Denis Gingras

Abstract:

As recently stated by National Highway Traffic Safety Administration (NHTSA), to demonstrate the expected performance of a highly automated vehicles system, test approaches should include a combination of simulation, test track, and on-road testing. In this paper, we propose a new validation method for autonomous vehicles involving on-road tests (Field Operational Tests), test track (Test Matrix) and simulation (Worst Case Scenarios). We concentrate our discussion on the simulation aspects, in particular, we extend recent work based on Importance Sampling by using a Metropolis-Hasting algorithm (MHS) to sample collected data from the Safety Pilot Model Deployment (SPMD) in lane-change scenarios. Our proposed MH sampling method will be compared to the Importance Sampling method, which does not perform well in high-dimensional problems. The importance of this study is to obtain a sampler that could be applied to high dimensional simulation problems in order to reduce and optimize the number of test scenarios that are necessary for validation and certification of autonomous vehicles.

Keywords: automated driving, autonomous emergency braking (AEB), autonomous vehicles, certification, evaluation, importance sampling, metropolis-hastings sampling, tests

Procedia PDF Downloads 289