Search results for: process model

Authors: Valentina Futoryanova, Hugh Hunt

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One of the common failure modes of the diesel engine turbochargers is high cycle fatigue of the turbine wheel blades. Mistuning of the blades due to the casting process is believed to contribute to the failure mode. Laser vibrometer is used to characterize mistuning for a population of turbine wheels through the analysis of the blade response to piezo speaker induced noise. The turbine wheel design under investigation is radial and is typically used in 6-12 L diesel engine applications. Amplitudes and resonance frequencies are reviewed and summarized. The study also includes test results for a paddle wheel that represents a perfectly tuned system and acts as a reference. Mass spring model is developed for the paddle wheel and the model suitability is tested against the actual data. Randomization is applied to the stiffness matrix to model the mistuning effect in the turbine wheels. Experimental data is shown to have good agreement with the model.

Keywords: vibration, radial turbines, mistuning, turbine blades, modal analysis, periodic structures, finite element

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Authors: Syamala Krishnannair

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A multivariate statistical process monitoring methodology using dissimilarity scale-based singular spectrum analysis (SSA) is proposed for the detection and diagnosis of process faults in the base metal flotation plant. Process faults are detected based on the multi-level decomposition of process signals by SSA using the dissimilarity structure of the process data and the subsequent monitoring of the multiscale signals using the unified monitoring index which combines T² with SPE. Contribution plots are used to identify the root causes of the process faults. The overall results indicated that the proposed technique outperformed the conventional multivariate techniques in the detection and diagnosis of the process faults in the flotation plant.

Keywords: fault detection, fault diagnosis, process monitoring, dissimilarity scale

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Authors: Chaudhuri Manoj Kumar Swain, Susmita Das

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This paper explores a detailed procedure of predicting a path loss (PL) model and its application in estimating the coverage probability in a WiMAX network. For this a hybrid approach is followed in predicting an empirical PL model of a 2.65 GHz WiMAX network deployed in a suburban environment. Data collection, statistical analysis, and regression analysis are the phases of operations incorporated in this approach and the importance of each of these phases has been discussed properly. The procedure of collecting data such as received signal strength indicator (RSSI) through experimental set up is demonstrated. From the collected data set, empirical PL and RSSI models are predicted with regression technique. Furthermore, with the aid of the predicted PL model, essential parameters such as PL exponent as well as the coverage probability of the network are evaluated. This research work may assist in the process of deployment and optimisation of any cellular network significantly.

Keywords: WiMAX, RSSI, path loss, coverage probability, regression analysis

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Authors: Rossella Arcucci, Luisa D'Amore, Simone Celestino, Giuseppe Scotti, Giuliano Laccetti

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This work is the first dowel in a rather wide research activity in collaboration with Euro Mediterranean Center for Climate Changes, aimed at introducing scalable approaches in Ocean Circulation Models. We discuss designing and implementation of a parallel algorithm for solving the Variational Data Assimilation (DA) problem on Graphics Processing Units (GPUs). The algorithm is based on the fully scalable 3DVar DA model, previously proposed by the authors, which uses a Domain Decomposition approach (we refer to this model as the DD-DA model). We proceed with an incremental porting process consisting of 3 distinct stages: requirements and source code analysis, incremental development of CUDA kernels, testing and optimization. Experiments confirm the theoretic performance analysis based on the so-called scale up factor demonstrating that the DD-DA model can be suitably mapped on GPU architectures.

Keywords: data assimilation, GPU architectures, ocean models, parallel algorithm

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Authors: Ana Fonseca, Stefany Villacis

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In this paper, the influence of several scenarios on a model of solar assisted mashing process in a brewery, while applying the model to different locations and therefore changing the environmental conditions, was analyzed. Assorted beer producer locations in different countries around the globe with contrasting climatic zones such as Guayaquil (Ecuador), Bangkok (Thailand), Mumbai (India), Veracruz (Mexico) and Brisbane (Australia) were evaluated and compared with a base case study Oldenburg (Germany), and results were drawn. The evaluation was restricted to the results obtained using TRNSYS 16 as simulating tool. On the base case, an annual Solar Fraction (SF) of 0.50 was encountered, results showed highly affection when modifying the pump control of the primary circuit and when increasing the area of collectors. A sensitivity analysis of the system for the selected locations was performed, resulting in Guayaquil the highest annual SF with a ratio of 2.5 times the expected value as compared with the base case. In contrast, Brisbane presented the lowest ratio, resulting in half of the expected one due to its lower irradiance. In conclusion, cities in Sunbelt countries have the technical potential to apply solar heat for their low-temperature industrial processes, in this case implementing a green brewery in Guayaquil.

Keywords: evacuated tubular solar collector, irradiance, mashing process, solar fraction, solar thermal

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Authors: Seung-Un Chae, Heung-Yul Kim, Sa-Kil Kim

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This paper presents the findings of preliminary study on human control performance in case of fire. The relationship between human control and human decision is studied in decision processes and stress model of human in a fire. Human behavior aspects involved in the decision process during a fire incident. The decision processes appear that six of individual perceptual processes: recognition, validation, definition, evaluation, commitment, and reassessment. Then, human may be stressed in order to get an optimal decision for their activity. This paper explores problems in human control processes and stresses in a catastrophic situation. Thus, the future approach will be concerned to reduce stresses and ambiguous irrelevant information.

Keywords: human reliability, decision processes, stress model, fire

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Authors: Mahsa Ja’fari, Mohammad R. Khosravi-Nikou, Mohsen Motavassel

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A comprehensive development towards the production of ultra-clean fuels as a feed stoke is getting to raise due to the increasing use of diesel fuels and global air pollution. Production of environmental-friendly fuels can be achievable by some limited single methods and most integrated ones. Oxidative desulfurization (ODS) presents vast ranges of technologies possessing suitable characteristics with regard to the Fenton process. Using toluene as a model fuel feed with dibenzothiophene (DBT) as a sulfur compound under various operating conditions is the attempt of this study. The results showed that this oxidative process followed a pseudo-first order kinetics. Removal efficiency of 77.43% is attained under reaction time of 40 minutes with (Fe⁺²/H₂O₂) molar ratio of 0.05 in acidic pH environment. In this research, temperature of 50 °C represented the most influential role in proceeding the reaction.

Keywords: design of experiment (DOE), dibenzothiophene (DBT), optimization, oxidative desulfurization (ODS)

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Authors: Kristin Thooft

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— Increasing pressure to manage healthcare costs has resulted in shifting care towards ambulatory settings and is driving a focus on cost transparency. There are few nurse staffing to workload models developed for ambulatory settings, less for multi-specialty clinics. Of the existing models, few have been evaluated against outcomes to understand any impact. This evaluation took place after the AWARD model for nurse staffing to workload was implemented in a multi-specialty clinic at a regional healthcare system in the Midwest. The multi-specialty clinic houses 26 medical and surgical specialty practices. The AWARD model was implemented in two specialty practices in October 2020. Donabedian’s Structure-Process-Outcome (SPO) model was used to evaluate outcomes based on changes to the structure and processes of care provided. The AWARD model defined and quantified the processes, recommended changes in the structure of day-to-day nurse staffing. Cost of care per patient visit, total visits, a total nurse performed visits used as structural and process measures, influencing the outcomes of cost of care and access to care. Independent t-tests were used to compare the difference in variables pre-and post-implementation. The SPO model was useful as an evaluation tool, providing a simple framework that is understood by a diverse care team. No statistically significant changes in the cost of care, total visits, or nurse visits were observed, but there were differences. Cost of care increased and access to care decreased. Two weeks into the post-implementation period, the multi-specialty clinic paused all non-critical patient visits due to a second surge of the COVID-19 pandemic. Clinic nursing staff was re-allocated to support the inpatient areas. This negatively impacted the ability of the Nurse Manager to utilize the AWARD model to plan daily staffing fully. The SPO framework could be used for the ongoing assessment of nurse staffing performance. Additional variables could be measured, giving a complete picture of the impact of nurse staffing. Going forward, there must be a continued focus on the outcomes of care and the value of nursing

Keywords: ambulatory, clinic, evaluation, outcomes, staffing, staffing model, staffing to workload

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Authors: Kayode Oshinubi, Brice Kammegne, Jacques Demongeot

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The use of mathematical tools like Partial Differential Equations and Ordinary Differential Equations have become very important to predict the evolution of a viral disease in a population in order to take preventive and curative measures. In December 2019, a novel variety of Coronavirus (SARS-CoV-2) was identified in Wuhan, Hubei Province, China causing a severe and potentially fatal respiratory syndrome, i.e., COVID-19. Since then, it has become a pandemic declared by World Health Organization (WHO) on March 11, 2020 which has spread around the globe. A reaction-diffusion system is a mathematical model that describes the evolution of a phenomenon subjected to two processes: a reaction process in which different substances are transformed, and a diffusion process that causes a distribution in space. This article provides a mathematical study of the Susceptible, Exposed, Infected, Recovered, and Vaccinated population model of the COVID-19 pandemic by the bias of reaction-diffusion equations. Both local and global asymptotic stability conditions for disease-free and endemic equilibria are determined using the Lyapunov function are considered and the endemic equilibrium point exists and is stable if it satisfies Routh–Hurwitz criteria. Also, adequate conditions for the existence and uniqueness of the solution of the model have been proved. We showed the spatial distribution of the model compartments when the basic reproduction rate $\mathcal{R}_0 < 1$ and $\mathcal{R}_0 > 1$ and sensitivity analysis is performed in order to determine the most sensitive parameters in the proposed model. We demonstrate the model's effectiveness by performing numerical simulations. We investigate the impact of vaccination and the significance of spatial distribution parameters in the spread of COVID-19. The findings indicate that reducing contact with an infected person and increasing the proportion of susceptible people who receive high-efficacy vaccination will lessen the burden of COVID-19 in the population. To the public health policymakers, we offered a better understanding of the COVID-19 management.

Keywords: COVID-19, SEIRV epidemic model, reaction-diffusion equation, basic reproduction number, vaccination, spatial distribution

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Authors: Katalina Grigorova, Kaloyan Mironov

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The paper focuses on the benefits of business process modeling. Although this discipline is developing for many years, there is still necessity of creating new opportunities to meet the ever-increasing users’ needs. Because one of these needs is related to the conversion of business process models from one standard to another, the authors have developed a converter between BPMN and EPC standards using workflow patterns as intermediate tool. Nowadays there are too many systems for business process modeling. The variety of output formats is almost the same as the systems themselves. This diversity additionally hampers the conversion of the models. The presented study is aimed at discussing problems due to differences in the output formats of various modeling environments.

Keywords: business process modeling, business process modeling standards, workflow patterns, converting models

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Authors: Wajih Abbassi, Zouhaier Ben Khelifa

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The present research points towards the empirical validation of three options valuation models, the ad-hoc Black-Scholes model as proposed by Berkowitz (2001), the constant elasticity of variance model of Cox and Ross (1976) and the Kou jump-diffusion model (2002). Our empirical analysis has been conducted on a sample of 26,974 options written on three indexes, the S&P 500, Nasdaq 100 and the Russell 2000 that were negotiated during the year 2007 just before the sub-prime crisis. We start by presenting the theoretical foundations of the models of interest. Then we use the technique of trust-region-reflective algorithm to estimate the structural parameters of these models from cross-section of option prices. The empirical analysis shows the superiority of the Kou jump-diffusion model. This superiority arises from the ability of this model to portray the behavior of market participants and to be closest to the true distribution that characterizes the evolution of these indices. Indeed the double-exponential distribution covers three interesting properties that are: the leptokurtic feature, the memory less property and the psychological aspect of market participants. Numerous empirical studies have shown that markets tend to have both overreaction and under reaction over good and bad news respectively. Despite of these advantages there are not many empirical studies based on this model partly because probability distribution and option valuation formula are rather complicated. This paper is the first to have used the technique of nonlinear curve-fitting through the trust-region-reflective algorithm and cross-section options to estimate the structural parameters of the Kou jump-diffusion model.

Keywords: jump-diffusion process, Kou model, Leptokurtic feature, trust-region-reflective algorithm, US index options

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Authors: Zhenghua Dai, Jianliang Xu, Fuchen Wang

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Non-catalyst partial oxidation technology has been widely used to produce syngas by reforming of hydrocarbon, including gas (natural gas, shale gas, refinery gas, coalbed gas, coke oven gas, pyrolysis gas, etc.) and liquid (residual oil, asphalt, deoiled asphalt, biomass oil, etc.). For natural gas non-catalyst partial oxidation, the H₂/CO(v/v) of syngas is about 1.8, which is agreed well with the request of FT synthesis. But for other process, such as carbonylation and glycol, the H₂/CO(v/v) should be close to 1 and 2 respectively. So the syngas composition of non-catalyst partial oxidation should be adjusted to satisfy the request of different chemical synthesis. That means a multi-reforming method by CO₂ and H₂O addition. The natural gas non-catalytic partial oxidation hot model was established. The effects of O₂/CH4 ratio, steam, and CO₂ on the syngas composition were studied. The results of the experiment indicate that the addition of CO₂ and steam into the reformer can be applied to change the syngas H₂/CO ratio. The reactor network model (RN model) was established according to the flow partition of industrial reformer and GRI-Mech 3.0. The RN model results agree well with the industrial data. The effects of steam, CO₂ on the syngas compositions were studied with the RN model.

Keywords: non-catalyst partial oxidation, natural gas, H₂/CO, CO₂ and H₂O addition, multi-reforming method

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Authors: Farida Kaouah, Chahida Oussalah, Wassila Hachi, Salim Boumaza, Mohamed Trari

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A catalyst of ZnO nanoparticles was used in the photocatalytic process of treatment for potential use towards bisphenol A (BPA) degradation in an aqueous solution. To achieve this study, the effect of parameters such as the catalyst dose, initial concentration of BPA and pH on the photocatalytic degradation of BPA was studied. The results reveal that the maximum degradation (more than 93%) of BPA occurred with ZnO catalyst in 120 min of stirring at natural pH (7.1) under solar light irradiation. It was found that chemical oxygen demand (COD) reduction takes place at a faster rate under solar light as compared to that of UV light. The kinetic studies were achieved and revealed that the photocatalytic degradation process obeyed a Langmuir–Hinshelwood model and followed a pseudo-first order rate expression. This work envisages the great potential that sunlight mediated photocatalysis has in the removal of bisphenol A from wastewater.

Keywords: bisphenol A, photocatalytic degradation, sunlight, zinc oxide, Langmuir–Hinshelwood model, chemical oxygen demand

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Authors: Julio Manuel de Luis Ruiz, Javier Sedano Cibrián, Rubén Pérez Álvarez, Raúl Pereda García, Cristina Diego Soroa

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Nowadays, the use of drones has been extended to practically any human activity. One of the main applications is focused on the surveying field. In this regard, software programs that process the images captured by the sensor from the drone in an almost automatic way have been developed and commercialized, but they only allow contrasting the results through control points. This work proposes the contrast of a 3D model obtained from a flight developed by a drone and a non-metric camera (due to its low cost), with a second model that is obtained by means of the historically-endorsed classical methods. In addition to this, the contrast is developed over a certain territory with a significant unevenness, so as to test the model generated with photogrammetry, and considering that photogrammetry with drones finds more difficulties in terms of accuracy in this kind of situations. Distances, heights, surfaces and volumes are measured on the basis of the 3D models generated, and the results are contrasted. The differences are about 0.2% for the measurement of distances and heights, 0.3% for surfaces and 0.6% when measuring volumes. Although they are not important, they do not meet the order of magnitude that is presented by salespeople.

Keywords: accuracy, classical topographic, model tridimensional, photogrammetry, Uav.

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Authors: Jan Stodt, Christoph Reich

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The usage of machine learning models for prediction is growing rapidly and proof that the intended requirements are met is essential. Audits are a proven method to determine whether requirements or guidelines are met. However, machine learning models have intrinsic characteristics, such as the quality of training data, that make it difficult to demonstrate the required behavior and make audits more challenging. This paper describes an ML audit framework that evaluates and reviews the risks of machine learning applications, the quality of the training data, and the machine learning model. We evaluate and demonstrate the functionality of the proposed framework by auditing an steel plate fault prediction model.

Keywords: audit, machine learning, assessment, metrics

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Authors: K. Sekulová, M. Šimon

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This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated.

Keywords: ergonomics, musculoskeletal disorders, occupational diseases, risk factors

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Authors: Anthony Usoro

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In this paper, two classes of bilinear time series model are obtained under certain conditions from the general bilinear autoregressive moving average model. Bilinear Autoregressive (BAR) and Bilinear Moving Average (BMA) Models have been identified. From the general bilinear model, BAR and BMA models have been proved to exist for q = Q = 0, => j = 0, and p = P = 0, => i = 0 respectively. These models are found useful in modelling most of the economic and financial data.

Keywords: autoregressive model, bilinear autoregressive model, bilinear moving average model, moving average model

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Authors: Kyle Burke Pfeiffer, Carmella Burdi, Karen Marsh

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The evacuation and shelter-in-place planning process employed by most jurisdictions within the United States is not informed by a scientifically-derived framework that is inclusive of the behavioral and policy-related indicators of public compliance with evacuation orders. While a significant body of work exists to define these indicators, the research findings have not been well-integrated nor translated into useable planning factors for public safety officials. Additionally, refinement of the planning factors alone is insufficient to support science-based evacuation planning as the behavioral elements of evacuees—even with consideration of policy-related indicators—must be examined in the context of specific regional transportation and shelter networks. To address this problem, the Federal Emergency Management Agency and Argonne National Laboratory developed an agent-based model to support regional analysis of zone-based evacuation in southeastern Georgia. In particular, this model allows public safety officials to analyze the consequences that a range of hazards may have upon a community, assess evacuation and shelter-in-place decisions in the context of specified evacuation and response plans, and predict outcomes based on community compliance with orders and the capacity of the regional (to include extra-jurisdictional) transportation and shelter networks. The intention is to use this model to aid evacuation planning and decision-making. Applications for the model include developing a science-driven risk communication strategy and, ultimately, in the case of evacuation, the shortest possible travel distance and clearance times for evacuees within the regional boundary conditions.

Keywords: agent-based modeling for evacuation, decision-support for evacuation planning, evacuation planning, human behavior in evacuation

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Authors: Negin Binesh, Mohammad Hossein Niksokhan, Amin Sarang

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Best Management Practices (BMPs) are considered as one of the most important structural adaptive measures to climate change and urban development challenges in recent decades. However, not every location is appropriate for applying BMPs in the watersheds. In this paper, location prioritization of two kinds of BMPs was done: Pourous pavement and Detention pond. West Flood-Diversion (WFD) catchment in northern parts of Tehran, Iran, was considered as the case study. The methodology includes integrating the results of Storm Water Management Model (SWMM) into Fuzzy Analytic Hierarchy Process (FAHP) method using Geographic Information System (GIS). The results indicate that mostly suburban areas of the watershed in northern parts are appropriate for applying detention basin, and downstream high-density urban areas are more suitable for using permeable pavement.

Keywords: adaptive measures, BMPs, location prioritization, urban flooding

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Authors: Paula Linna

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During the recent years interest in inclusive business has increased. Still, research on inclusive business development is at infancy. This study provides empirical evidence on inclusive business development of mini-grid solution for the rural African communities. This study tests how well the insights of creation theory can explain inclusive business development process which often occurs under uncertainty due to demands for developing new technology, new business model and establishing business in new market. These several uncertain elements of business development impact what kind of business strategies the entrepreneur can practice and what kind of decision making tools to use. In addition, community engagement is essential for the successful operative management of a mini-grid solution. This study advances the understanding of inclusive business development and can be used as the foundation for future work to facilitate the process of new business venture creation at the BOP particularly when developing community-operated entrepreneurship model.

Keywords: creation theory, base of the pyramid (BOP), community-operated entrepreneurship, rural African communities

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Authors: T. Nozu, K. Hibi, T. Nishiie

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This paper discusses the applicability of the numerical model for a damage prediction method of the accidental hydrogen explosion occurring in a hydrogen facility. The numerical model was based on an unstructured finite volume method (FVM) code “NuFD/FrontFlowRed”. For simulating unsteady turbulent combustion of leaked hydrogen gas, a combination of Large Eddy Simulation (LES) and a combustion model were used. The combustion model was based on a two scalar flamelet approach, where a G-equation model and a conserved scalar model expressed a propagation of premixed flame surface and a diffusion combustion process, respectively. For validation of this numerical model, we have simulated the previous two types of hydrogen explosion tests. One is open-space explosion test, and the source was a prismatic 5.27 m3 volume with 30% of hydrogen-air mixture. A reinforced concrete wall was set 4 m away from the front surface of the source. The source was ignited at the bottom center by a spark. The other is vented enclosure explosion test, and the chamber was 4.6 m × 4.6 m × 3.0 m with a vent opening on one side. Vent area of 5.4 m2 was used. Test was performed with ignition at the center of the wall opposite the vent. Hydrogen-air mixtures with hydrogen concentrations close to 18% vol. were used in the tests. The results from the numerical simulations are compared with the previous experimental data for the accuracy of the numerical model, and we have verified that the simulated overpressures and flame time-of-arrival data were in good agreement with the results of the previous two explosion tests.

Keywords: deflagration, large eddy simulation, turbulent combustion, vented enclosure

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Authors: Teguh Sugiarto, Amir Mohamadian Amiri

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Background: This study aims to explore if there is fraud in the company's financial report distribution using the number first digit Lucas, Fibonacci and Benford. Research methods: In this study, the author uses a number model contained in the first digit of the model Lucas, Fibonacci and Benford, to make a distinction between implementation by using the scale above and below 5%, the rate of occurrence of a difference against the digit number contained on Lucas, Fibonacci and Benford. If there is a significant difference above and below 5%, then the process of follow-up and detection of occurrence of fraud against the financial statements can be made. Findings: From research that has been done can be concluded that the number of frequency levels contained in the financial statements of PT Bank BRI Tbk in a year in the same conscientious results for model Lucas, Fibonacci and Benford.

Keywords: Lucas, Fibonacci, Benford, first digit

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Authors: Akhtar Nawaz, Sahar Noor, Iftikhar Hussain

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This paper considers advanced hybrid manufacturing planning both push and pull system in which each customer order has a due date by demand forecast and customer orders. We present a tool for model for tool development that requires an absolute due dates and customer orders in a manufacturing supply chain. It is vital for the manufacturing companies to face the problem of variations in demands, increase in varieties by maintaining safety stock and to minimize components obsolescence and uselessness. High inventory cost and low delivery lead time is expected in push type of system and on contrary high delivery lead time and low inventory cost is predicted in the pull type. For this tool for model we need an MRP system for the push and pull environment and control of inventories in push parts and lead time in the pull part. To retain process data quickly, completely and to improve responsiveness and minimize inventory cost, a tool is required to deal with the high product variance and short cycle parts. In practice, planning and scheduling are interrelated and should be solved simultaneously with supply chain to ensure that the due dates of customer orders are met. The proposed tool for model considers alternative process plans for job types, with precedence constraints for job operations. Such a tool for model has not been treated in the literature. To solve the model, tool was developed, so a new technique was required to deal with the issue of high product variance and short life cycles in assemble to order.

Keywords: hybrid manufacturing system, supply chain system, make to order, make to stock, assemble to order

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Authors: Jianliang Xu, Zhenghua Dai, Zhongjie Shen, Haifeng Liu, Fuchen Wang

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In an entrained flow gasifier, the combustible components are converted into the gas phase, and the mineral content is converted into ash. Most of the ash particles or droplets are deposited on the refractory or membrane wall and form a slag layer that flows down to the quenching system. The captured particle reaction process and slag flow and phase transformation play an important role in gasifier performance and safe and stable operation. The reaction characteristic of captured char particles on the molten slag had been studied by applied a high-temperature stage microscope. The gasification process of captured chars with CO2 on the slag surface was observed and recorded, compared to the original char gasification. The particle size evolution, heat transfer process are discussed, and the gasification reaction index of the capture char particle are modeled. Molten slag layer promoted the char reactivity from the analysis of reaction index, Coupled with heat transfer analysis, shrinking particle model (SPM) was applied and modified to predict the gasification time at carbon conversion of 0.9, and results showed an agreement with the experimental data. A comprehensive model with gas-particle-slag flow and reaction models was used to model the different industry gasifier. The carbon conversion information in the spatial space and slag layer surface are investigated. The slag flow characteristic, such as slag velocity, molten slag thickness, slag temperature distribution on the membrane wall and refractory brick are discussed.

Keywords: char, slag, numerical simulation, gasification, wall reaction, membrane wall

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Authors: Runliang Wang, Jianhua Liu, Duo Jia, Xiaoyu Ding

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The contact between sealing surfaces plays a vital role in guaranteeing the sealing performance of various seals. To date, analyses of sealing structures have rarely considered both structural parameters (macroscale) and surface roughness information (microscale) of sealing surfaces due to the complex modeling process. Meanwhile, most of the contact analyses applied to seals were conducted only under normal loading, which still existssome distance from real loading conditions in engineering. In this paper, a multiscale rough contact model, which took both macrostructural parameters of seals and surface roughness information of sealing surfaces into consideration for the cone-cone seal, was established. By using the finite element method (FEM), the combined normal and tangential loading was applied to the model to simulate the assembly process of the cone-cone seal. The evolution of the contact behaviors during the assembly process, such as the real contact area (RCA), the distribution of contact pressure, and contact status, are studied in detail. The results showed the non-linear relationship between the RCA and the load, which was different from the normal loading cases. In addition, the evolution of the real contact area of cone-cone seals with isotropic and anisotropic rough surfaces are also compared quantitatively.

Keywords: contact mechanics, FEM, randomly rough surface, real contact area, sealing

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Authors: Shank Kulkarni, Alireza Tabarraei

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The fantastic properties of polyurea such as flexibility, durability, and chemical resistance have brought it a wide range of application in various industries. Effective prediction of the response of polyurea under different loading and environmental conditions necessitates the development of an accurate constitutive model. Similar to most polymers, the behavior of polyurea depends on both strain and strain rate. Therefore, the constitutive model should be able to capture both these effects on the response of polyurea. To achieve this objective, in this paper, a nonlinear hyper-viscoelastic constitutive model is developed by the superposition of a hyperelastic and a viscoelastic model. The proposed constitutive model can capture the behavior of polyurea under compressive loading conditions at various strain rates. Four parameter Ogden model and Mooney Rivlin model are used to modeling the hyperelastic behavior of polyurea. The viscoelastic behavior is modeled using both a three-parameter standard linear solid (SLS) model and a K-BKZ model. Comparison of the modeling results with experiments shows that Odgen and SLS model can more accurately predict the behavior of polyurea. The material parameters of the model are found by curve fitting of the proposed model to the uniaxial compression test data. The proposed model can closely reproduce the stress-strain behavior of polyurea for strain rates up to 6500 /s.

Keywords: constitutive modelling, ogden model, polyurea, SLS model, uniaxial compression test

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Authors: Mohammed Seyam, Faridah Othman, Ahmed El-Shafie

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The early warning of high stream flow events (HSF) and floods is an important aspect in the management of surface water and rivers systems. This process can be performed using either process-based models or data driven-based models such as artificial intelligence (AI) techniques. The main goal of this study is to develop efficient AI-based model for predicting the real-time hourly stream flow (Q) and apply it as early warning tool of HSF and floods in the downstream area of the Selangor River basin, taken here as a paradigm of humid tropical rivers in Southeast Asia. The performance of AI-based models has been improved through the integration of the lag time (Lt) estimation in the modelling process. A total of 8753 patterns of Q, water level, and rainfall hourly records representing one-year period (2011) were utilized in the modelling process. Six hydrological scenarios have been arranged through hypothetical cases of input variables to investigate how the changes in RF intensity in upstream stations can lead formation of floods. The initial SF was changed for each scenario in order to include wide range of hydrological situations in this study. The performance evaluation of the developed AI-based model shows that high correlation coefficient (R) between the observed and predicted Q is achieved. The AI-based model has been successfully employed in early warning throughout the advance detection of the hydrological conditions that could lead to formations of floods and HSF, where represented by three levels of severity (i.e., alert, warning, and danger). Based on the results of the scenarios, reaching the danger level in the downstream area required high RF intensity in at least two upstream areas. According to results of applications, it can be concluded that AI-based models are beneficial tools to the local authorities for flood control and awareness.

Keywords: floods, stream flow, hydrological modelling, hydrology, artificial intelligence

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Authors: Angela Luft, Sebastian Bremen, Nicolae Balc

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Additive manufacturing processes have entered large parts of the industry and their range of application have progressed and grown significantly in the course of time. A major advantage of additive manufacturing is the innate flexibility of the machines. This corelates with the ongoing demand of creating highly flexible production environments. However, the potential of additive manufacturing technologies to enhance the flexibility of production systems has not yet been truly considered and quantified in a systematic way. In order to determine the potential of additive manufacturing technologies with regards to the strategic flexibility design in production systems, an integrated evaluation model has been developed, that allows for the simultaneous consideration of both conventional as well as additive production resources. With the described model, an operational scope of action can be identified and quantified in terms of mix and volume flexibility, process complexity, and machine capacity that goes beyond the current cost-oriented approaches and offers a much broader and more holistic view on the potential of additive manufacturing. A respective evaluation model is presented this paper.

Keywords: additive manufacturing, capacity planning, production systems, strategic production planning, flexibility enhancement

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Authors: Hussein Altartouri

Abstract:

In this paper the kinematic and kinetic models of an omnidirectional holonomic mobile robot is presented. The kinematic and kinetic models form the OmniDrive model. Therefore, a mathematical model for the robot equipped with three- omnidirectional wheels is derived. This model which takes into consideration the kinematics and kinetics of the robot, is developed to state space representation. Relative analysis of the velocities and displacements is used for the kinematics of the robot. Lagrange’s approach is considered in this study for deriving the equation of motion. The drive train and the mechanical assembly only of the Festo Robotino® is considered in this model. Mainly the model is developed for motion control. Furthermore, the model can be used for simulation purposes in different virtual environments not only Robotino® View. Further use of the model is in the mechatronics research fields with the aim of teaching and learning the advanced control theories.

Keywords: mobile robot, omni-direction wheel, mathematical model, holonomic mobile robot

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Authors: Zeinab Yazdanfar, Dilan Robert, Daniel Lester, S. Setunge

Abstract:

Scour has been identified as the most common threat to bridge stability worldwide. Traditionally, scour around bridge piers is calculated using the empirical approaches that have considerable limitations and are difficult to generalize. The multi-physic nature of scouring which involves turbulent flow, soil mechanics and solid-fluid interactions cannot be captured by simple empirical equations developed based on limited laboratory data. These limitations can be overcome by direct numerical modeling of coupled hydro-mechanical scour process that provides a robust prediction of bridge scour and valuable insights into the scour process. Several numerical models have been proposed in the literature for bridge scour estimation including Eulerian flow models and coupled Euler-Lagrange models incorporating an empirical sediment transport description. However, the contact forces between particles and the flow-particle interaction haven’t been taken into consideration. Incorporating collisional and frictional forces between soil particles as well as the effect of flow-driven forces on particles will facilitate accurate modeling of the complex nature of scour. In this study, a coupled Computational Fluid Dynamics and Discrete Element Model (CFD-DEM) has been developed to simulate the scour process that directly models the hydro-mechanical interactions between the sediment particles and the flowing water. This approach obviates the need for an empirical description as the fundamental fluid-particle, and particle-particle interactions are fully resolved. The sediment bed is simulated as a dense pack of particles and the frictional and collisional forces between particles are calculated, whilst the turbulent fluid flow is modeled using a Reynolds Averaged Navier Stocks (RANS) approach. The CFD-DEM model is validated against experimental data in order to assess the reliability of the CFD-DEM model. The modeling results reveal the criticality of particle impact on the assessment of scour depth which, to the authors’ best knowledge, hasn’t been considered in previous studies. The results of this study open new perspectives to the scour depth and time assessment which is the key to manage the failure risk of bridge infrastructures.

Keywords: bridge scour, discrete element method, CFD-DEM model, multi-phase model

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