Search results for: dynamic monitoring

Authors: Francisco Liaño-Carrera, Jorge Enrique Baños-Illana, Arturo Gómez-Barrero, José Isaac Ramírez-Macías, Erik Omar Paredes-JuáRez, David Salas-Monreal, Mayra Lorena Riveron-Enzastiga

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Topographical changes in coastal areas are usually assessed with airborne LIDAR and conventional photogrammetry. In recent times Unmanned Aerial Vehicles (UAV) have been used several in photogrammetric applications including coastline evolution. However, its use goes further by using the points cloud associated to generate beach Digital Elevation Models (DEM). We present a methodology for monitoring coastal topographic changes along a 50 km coastline in Veracruz, Mexico using high-resolution images (less than 10 cm ground resolution) and dense points cloud captured with an UAV. This monitoring develops in the context of the port of Veracruz expansion project which construction began in 2015 and intends to characterize coast evolution and prevent and mitigate project impacts on coastal environments. The monitoring began with a historical coastline reconstruction since 1979 to 2015 using aerial photography and Landsat imagery. We could define some patterns: the northern part of the study area showed accretion while the southern part of the study area showed erosion. Since the study area is located off the port of Veracruz, a touristic and economical Mexican urban city, where coastal development structures have been built since 1979 in a continuous way, the local beaches of the touristic area are been refilled constantly. Those areas were not described as accretion since every month sand-filled trucks refill the sand beaches located in front of the hotel area. The construction of marinas and the comitial port of Veracruz, the old and the new expansion were made in the erosion part of the area. Northward from the City of Veracruz the beaches were described as accretion areas while southward from the city, the beaches were described as erosion areas. One of the problems is the expansion of the new development in the southern area of the city using the beach view as an incentive to buy front beach houses. We assessed coastal changes between seasons using high-resolution images and also points clouds during 2016 and preliminary results confirm that UAVs can be used in permanent coast monitoring programs with excellent performance and detail.

Keywords: digital elevation model, high-resolution images, topographic coast monitoring, unmanned aerial vehicle

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Authors: Ivan Ramos Sampe Immanuel, Linung Kresno Adikusumo, Liston Sitanggang

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Achieving the production targets of oil and gas in an upstream oil and gas company represents a complex undertaking necessitating collaborative engagement from a multidisciplinary team. In addition to conducting exploration activities and executing well intervention programs, an upstream oil and gas enterprise must assess the feasibility of attaining predetermined production goals. The monitoring of production performance serves as a critical activity to ensure organizational progress towards the established oil and gas performance targets. Subsequently, decisions within the upstream oil and gas management team are informed by the received information pertaining to the respective production performance. To augment the decision-making process, the implementation of a production performance dashboard emerges as a viable solution, providing an integrated and centralized tool. The deployment of a production performance dashboard manifests as an instrumental mechanism fostering a user-friendly interface for monitoring production performance, while concurrently preserving the intrinsic characteristics of granular data. The integration of diverse data sources into a unified production performance dashboard establishes a singular veritable source, thereby enhancing the organization's capacity to uphold a consolidated and authoritative foundation for its business requisites. Additionally, the heightened accessibility of the production performance dashboard to business users constitutes a compelling substantiation of its consequential impact on facilitating the monitoring of organizational targets.

Keywords: production, performance, dashboard, data analytics

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Authors: Nima Pirhadi, Shao Yong Bo, Xusheng Wan, Jianguo Lu, Jilei Hu

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Although gravels and gravelly soils are assumed to be non-liquefiable because of high conductivity and small modulus; however, the occurrence of this phenomenon in some historical earthquakes, especially recently earthquakes during 2008 Wenchuan, Mw= 7.9, 2014 Cephalonia, Greece, Mw= 6.1 and 2016, Kaikoura, New Zealand, Mw = 7.8, has been promoted the essential consideration to evaluate risk assessment and hazard analysis of seismic gravelly soil liquefaction. Due to the limitation in sampling and laboratory testing of this type of soil, in situ tests and site exploration of case histories are the most accepted procedures. Of all in situ tests, dynamic penetration test (DPT), Which is well known as the Chinese dynamic penetration test, and shear wave velocity (Vs) test, have been demonstrated high performance to evaluate seismic gravelly soil liquefaction. However, the lack of a sufficient number of case histories provides an essential limitation for developing new models. This study at first investigates recent earthquakes that caused liquefaction in gravelly soils to collect new data. Then, it adds these data to the available literature’s dataset to extend them and finally develops new models to assess seismic gravelly soil liquefaction. To validate the presented models, their results are compared to extra available models. The results show the reasonable performance of the proposed models and the critical effect of gravel content (GC)% on the assessment.

Keywords: liquefaction, gravel, dynamic penetration test, shear wave velocity

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Authors: Seung-Won Lee, JongSoo Lee, Won-Jik Yang, Hyung-Joon Kim

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A capacity spectrum method (CSM), one of methodologies to evaluate seismic fragilities of building structures, has been long recognized as the most convenient method, even if it contains several limitations to predict the seismic response of structures of interest. This paper proposes the procedure to estimate seismic fragility curves using an incremental dynamic analysis (IDA) rather than the method adopting a CSM. To achieve the research purpose, this study compares the seismic fragility curves of a 5-story reinforced concrete (RC) moment frame obtained from both methods, an IDA method and a CSM. Both seismic fragility curves are similar in slight and moderate damage states whereas the fragility curve obtained from the IDA method presents less variation (or uncertainties) in extensive and complete damage states. This is due to the fact that the IDA method can properly capture the structural response beyond yielding rather than the CSM and can directly calculate higher mode effects. From these observations, the CSM could overestimate seismic vulnerabilities of the studied structure in extensive or complete damage states.

Keywords: seismic fragility curve, incremental dynamic analysis, capacity spectrum method, reinforced concrete moment frame

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Authors: Michael Ayomoh, Adriaan Roux, Oyindamola Omotuyi

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This paper presents an efficient robot navigation model in a multi-target domain amidst static and dynamic workspace obstacles. The problem is that of developing an optimal algorithm to minimize the total travel time of a robot as it visits all target points within its task domain amidst unknown workspace obstacles and finally return to its initial position. In solving this problem, a classical algorithm was first developed to compute the optimal number of paths to be travelled by the robot amidst the network of paths. The principle of shortest distance between robot and targets was used to compute the target point visitation order amidst workspace obstacles. Algorithm premised on the standard polar coordinate system was developed to determine the length of obstacles encountered by the robot hence giving room for a geometrical estimation of the total surface area occupied by the obstacle especially when classified as a relevant obstacle i.e. obstacle that lies in between a robot and its potential visitation point. A stochastic model was developed and used to estimate the likelihood of a dynamic obstacle bumping into the robot’s navigation path and finally, the navigation/obstacle avoidance algorithm was hinged on the hybrid virtual force field (HVFF) method. Significant modelling constraints herein include the choice of navigation path to selected target points, the possible presence of static obstacles along a desired navigation path and the likelihood of encountering a dynamic obstacle along the robot’s path and the chances of it remaining at this position as a static obstacle hence resulting in a case of re-routing after routing. The proposed algorithm demonstrated a high potential for optimal solution in terms of efficiency and effectiveness.

Keywords: multi-target, mobile robot, optimal path, static obstacles, dynamic obstacles

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Authors: Mustafa Taskin, Ozgur Demir, M. Mert Serveren

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The precise study of the impact of underwater explosions on structures is of great importance in the design and engineering calculations of floating structures, especially those used for military purposes, as well as power generation facilities such as offshore platforms that can become a target in case of war. Considering that ship and submarine structures are mostly curved surfaces, it is extremely important and interesting to examine the destructive effects of underwater explosions on curvilinear surfaces. In this study, geometric nonlinear dynamic analysis of cylindrical composite sandwich shells subjected to instantaneous pressure load is performed. The instantaneous pressure load is defined as an underwater explosion and the effects of the liquid medium are taken into account. There are equations in the literature for pressure due to underwater explosions, but these equations have been obtained for flat plates. For this reason, the instantaneous pressure load equations are arranged to be suitable for curvilinear structures before proceeding with the analyses. Fluid-solid interaction is defined by using Taylor's Plate Theory. The lower and upper layers of the cylindrical composite sandwich shell are modeled as composite laminate and the middle layer consists of soft core. The geometric nonlinear dynamic equations of the shell are obtained by Hamilton's principle, taken into account the von Kàrmàn theory of large displacements. Then, time dependent geometric nonlinear equations of motion are solved with the help of generalized differential quadrature method (GDQM) and dynamic behavior of cylindrical composite sandwich shells exposed to underwater explosion is investigated. An algorithm that can work parametrically for the solution has been developed within the scope of the study.

Keywords: cylindrical composite sandwich shells, generalized differential quadrature method, geometric nonlinear dynamic analysis, underwater explosion

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Authors: Felicia Kikelomo Oluwalola

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The study was designed to identify the challenges to change and innovation in educational system in Nigeria. Educational institutions, like all other organizations, require constant monitoring, to identify areas for potential improvement. However, educational reforms are often not well-implemented. This results in massive wastage of finances, human resources, and lost potential. Educational institutions are organised on many levels, from the individual classroom under the management of a single teacher, to groups of classrooms supervised by a Head Teacher or Executive Teacher, to a whole-school structure, under the guidance of the principal. Therefore, there is need for changes and innovation in our educational system since we are in the era of computer age. In doing so, this paper examined the psychology of change, concept of change and innovation with suggested view points. Educational administrators and individuals should be ready to have the challenge of monitoring changes in technologies. Educational planners/policy makers should be encouraged to involve in change process.

Keywords: challenges, change, education, innovation

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Authors: M. Ramadan, B. Salah

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This paper introduces a framework to digitalize lean manufacturing tools to enhance smart lean-based manufacturing environments or Lean 4.0 manufacturing systems. The paper discusses the integration between lean tools and the powerful features of recent real-time data capturing systems with the help of Information and Communication Technologies (ICT) to develop an intelligent real-time monitoring and controlling system of production operations concerning lean targets. This integration is represented in the Lean 4.0 system called Dynamic Value Stream Mapping (DVSM). Moreover, the paper introduces the practice of Radio Frequency Identification (RFID) and ICT to smartly support lean tools and practices during daily production runs to keep the lean system alive and effective. This work introduces a practical description of how the lean method tools 5S, standardized work, and poka-yoke can be digitalized and smartly monitored and controlled through DVSM. A framework of the three tools has been discussed and put into practice in a German switchgear manufacturer.

Keywords: lean manufacturing, Industry 4.0, radio frequency identification, value stream mapping

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Authors: Bireswar Paul, Amitava Datta

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Indoor air environment is a big concern in the last few decades in the developing countries, with increased focus on monitoring the air quality. In this work, an experimental study has been conducted to establish the existence of carbon nanoparticles below the size range of 10 nm in the non-sooting zone of a LPG/air partially premixed flame. Mainly, four optical techniques, UV absorption spectroscopy, fluorescence spectroscopy, dynamic light scattering and TEM have been used to characterize and measure the size of carbon nanoparticles in the sampled materials collected from the inner surface of the flame front. The existence of the carbon nanoparticles in the sampled material has been confirmed with the typical nature of the absorption and fluorescence spectra already reported in the literature. The band gap energy shows that the particles are made up of three to six aromatic rings. The size measurement by DLS technique also shows that the particles below the size range of 10 nm. The results of DLS are also corroborated by the TEM image of the same material. 

Keywords: indoor air, carbon nanoparticle, lpg, partially premixed flame, optical techniques

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Authors: F. Fekak, A. Gravouil, M. Brun, B. Depale

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During an earthquake, a bridge crane may be subjected to multiple impacts between crane wheels and rail. In order to model such phenomena, a time-history dynamic analysis with a multi-scale approach is performed. The high frequency aspect of the impacts between wheels and rails is taken into account by a Lagrange explicit event-capturing algorithm based on a velocity-impulse formulation to resolve contacts and impacts. An implicit temporal scheme is used for the rest of the structure. The numerical coupling between the implicit and the explicit schemes is achieved with a heterogeneous asynchronous time-integrator.

Keywords: bridge crane, earthquake, dynamic analysis, explicit, implicit, impact

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Authors: Lee Tasker, Ali Karrech, Jeffrey Shragge, Matthew Josh

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Monitoring for the deterioration of concrete infrastructure is an important assessment tool for an engineer and difficulties can be experienced with monitoring for deterioration within an infrastructure. If a failure crack, or fluid seepage through such a crack, is observed from the surface often the source location of the deterioration is not known. Geophysical methods are used to assist engineers with assessing the subsurface conditions of materials. Techniques such as Ground Penetrating Radar (GPR) provide information on the location of buried infrastructure such as pipes and conduits, positions of reinforcements within concrete blocks, and regions of voids/cavities behind tunnel lining. This experiment underlines the application of GPR as an infrastructure-monitoring tool to highlight and monitor regions of possible deterioration within a concrete test wall due to an increase in the generation of fractures; in particular, during a time period of applied load to a concrete wall up to and including structural failure. A three-point load was applied to a concrete test wall of dimensions 1700 x 600 x 300 mm³ in increments of 10 kN, until the wall structurally failed at 107.6 kN. At each increment of applied load, the load was kept constant and the wall was scanned using GPR along profile lines across the wall surface. The measured radar amplitude responses of the GPR profiles, at each applied load interval, were reconstructed into depth-slice grids and presented at fixed depth-slice intervals. The corresponding depth-slices were subtracted from each data set to compare the radar amplitude response between datasets and monitor for changes in the radar amplitude response. At lower values of applied load (i.e., 0-60 kN), few changes were observed in the difference of radar amplitude responses between data sets. At higher values of applied load (i.e., 100 kN), closer to structural failure, larger differences in radar amplitude response between data sets were highlighted in the GPR data; up to 300% increase in radar amplitude response at some locations between the 0 kN and 100 kN radar datasets. Distinct regions were observed in the 100 kN difference dataset (i.e., 100 kN-0 kN) close to the location of the final failure crack. The key regions observed were a conical feature located between approximately 3.0-12.0 cm depth from surface and a vertical linear feature located approximately 12.1-21.0 cm depth from surface. These key regions have been interpreted as locations exhibiting an increased change in pore-space due to increased mechanical loading, or locations displaying an increase in volume of micro-cracks, or locations showing the development of a larger macro-crack. The experiment showed that GPR is a useful geophysical monitoring tool to assist engineers with highlighting and monitoring regions of large changes of radar amplitude response that may be associated with locations of significant internal structural change (e.g. crack development). GPR is a non-destructive technique that is fast to deploy in a production setting. GPR can assist with reducing risk and costs in future infrastructure maintenance programs by highlighting and monitoring locations within the structure exhibiting large changes in radar amplitude over calendar-time.

Keywords: 4D GPR, engineering geophysics, ground penetrating radar, infrastructure monitoring

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Authors: Janne Engblom, Elias Oikarinen

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The understanding of housing price dynamics is of importance to a great number of agents: to portfolio investors, banks, real estate brokers and construction companies as well as to policy makers and households. A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models is dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Common Correlated Effects estimator (CCE) of dynamic panel data which also accounts for cross-sectional dependence which is caused by common structures of the economy. In presence of cross-sectional dependence standard OLS gives biased estimates. In this study, U.S housing price dynamics were examined empirically using the dynamic CCE estimator with first-difference of housing price as the dependent and first-differences of per capita income, interest rate, housing stock and lagged price together with deviation of housing prices from their long-run equilibrium level as independents. These deviations were also estimated from the data. The aim of the analysis was to provide estimates with comparisons of estimates between 1980-1999 and 2000-2012. Based on data of 50 U.S cities over 1980-2012 differences of short-run housing price dynamics estimates were mostly significant when two time periods were compared. Significance tests of differences were provided by the model containing interaction terms of independents and time dummy variable. Residual analysis showed very low cross-sectional correlation of the model residuals compared with the standard OLS approach. This means a good fit of CCE estimator model. Estimates of the dynamic panel data model were in line with the theory of housing price dynamics. Results also suggest that dynamics of a housing market is evolving over time.

Keywords: dynamic model, panel data, cross-sectional dependence, interaction model

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Authors: Khaled A. Alsaif, Mosaad A. Foda

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In the following article, we present the dynamic simulation of an unmanned aerial vehicle with main fuel engine in the middle to carry most of the weight. This configuration will increase the flight time of the vehicle for a given payload size as opposed to the traditional quad rotor, where only DC motors are used. A parametric study to investigate the effect of the propellers ratio (main rotor propeller diameter to secondary rotor propeller diameter), the angle of incidence of the main rotor and the twist angle of the main rotor blades on selected performance criteria is presented.

Keywords: unmanned aerial vehicle (UAV), quadrotor, petrol quadcopter, flying robot

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Authors: Inga Badasyan

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Every year we do monitoring of water pollution of catchment basin of Debed River. Next, the Ministry of Nature Protection does modeling programme. Finely, we are managing the impact of water pollution in Debed river. Ecosystem technologies efficiency performance were estimated based on the physical, chemical, and macrobiological analyses of water on regular base between 2012 to 2015. Algae community composition was determined to assess the ecological status of Debed river, while vegetation was determined to assess biodiversity. Last time, experts werespeaking about global warming, which is having bad impact on the surface water, freshwater, etc. As, we know that global warming is caused by the current high levels of carbon dioxide in the water. Geochemical modelling is increasingly playing an important role in various areas of hydro sciences and earth sciences. Geochemical modelling of highly concentrated aqueous solutions represents an important topic in the study of many environments such as evaporation ponds, groundwater and soils in arid and semi-arid zones, costal aquifers, etc. The sampling time is important for benthic macroinvertebrates, for that reason we have chosen in the spring (abundant flow of the river, the beginning of the vegetation season) and autumn (the flow of river is scarce). The macroinvertebrates are good indicator for a chromic pollution and aquatic ecosystems. Results of our earlier investigations in the Debed river reservoirs clearly show that management problem of ecosystem reservoirs is topical. Research results can be applied to studies of monitoring water quality in the rivers and allow for rate changes and to predict possible future changes in the nature of the lake.

Keywords: ecohydrological monitoring, flood risk management, global warming, aquatic macroinvertebrates

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Authors: L. A. Toro, N. Prieto, J. J. Vargas

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There are many control charts for monitoring mean and variance. Among these, the X y R, X y S, S2 Hotteling and Shewhart control charts, for mentioning some, are widely used for monitoring mean a variance in industrial processes. In particular, the Shewhart charts are based on the information about the process contained in the current observation only and ignore any information given by the entire sequence of points. Moreover, that the Shewhart chart is a control chart without memory. Consequently, Shewhart control charts are found to be less sensitive in detecting smaller shifts, particularly smaller than 1.5 times of the standard deviation. These kind of small shifts are important in many industrial applications. In this study and effective alternative to Shewhart control chart was implemented. In case of univariate process an Exponentially Moving Average (EWMA) control chart was developed and Multivariate Exponentially Moving Average (MEWMA) control chart in case of multivariate process. Both of these charts were based on memory and perform better that Shewhart chart while detecting smaller shifts. In these charts, information the past sample is cumulated up the current sample and then the decision about the process control is taken. The mentioned characteristic of EWMA and MEWMA charts, are of the paramount importance when it is necessary to control industrial process, because it is possible to correct or predict problems in the processes before they come to a dangerous limit.

Keywords: control charts, multivariate exponentially moving average (MEWMA), exponentially moving average (EWMA), industrial control process

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Authors: Shital Jhunjhunwala, Shweta Saraf

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Research Question: The study, based on a survey, empirically tests the impact of the board’s engagement in the decision-making process on firm outcomes. It also examines the moderating effect of board leadership and board independence on the relationship. Research Findings: Boards’ engagement in the decision-making process is found to be vital for firm performance, wherein effective monitoring by the board outperforms their strategic guidance role in achieving desired outcomes. The separation of CEO and Chairman positively moderates the board’s engagement in protecting stakeholders’ interests, but lack of independence and passive behaviour of independent directors raises concern on the efficacy of independent directors. Theoretical Implications: The study provides the framework for process-oriented corporate governance research, where investigation of boards’ behaviour inside the boardroom develops a deeper understanding of board processes. Practitioner Implications: The study highlights the necessity of developing boards’ focus in a company on monitoring managerial actions. It suggests the need to separate the position of CEO and Chairman for addressing the interest of all stakeholders. It recommends policymakers review the existing mandate on board independence and create alternate monitoring mechanisms for addressing agency conflict.

Keywords: board, decision-making process, engagement, independence, leadership, innovation, stakeholders, firm performance, qualitative, India

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Authors: Federico Pittino, Thomas Arnold

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The shredding of waste materials is a key step in the recycling process towards the circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need for frequent maintenance of critical components. Maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for one year, and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for the efficient operation of industrial shredders.

Keywords: predictive maintenance, circular economy, industrial shredder, cost optimization, statistical machine learning

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Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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The increase in the demand for precision optics, coupled with the absence of much research output in the ultra high precision grinding of precision optics as compared to the ultrahigh precision diamond turning of optical metals has fostered the need for more research in the ultra high precision grinding of an optical lens. Furthermore, the increase in the stringent demands for nanometric surface finishes through lapping, polishing and grinding processes necessary for the use of borosilicate-crown glass in the automotive and optics industries has created the demand to effectively monitor the surface roughness during the production process. Acoustic emission phenomenon has been proven as useful monitoring technique in several manufacturing processes ranging from monitoring of bearing production to tool wear estimation. This paper introduces a rare and unique approach with the application of acoustic emission technique to monitor the surface roughness of borosilicate-crown glass during an ultra high precision grinding process. This research was carried out on a 4-axes Nanoform 250 ultrahigh precision lathe machine using an ultra high precision grinding spindle to machine the flat surface of the borosilicate-crown glass with the tip of the grinding wheel. A careful selection of parameters and design of experiment was implemented using Box-Behnken method to vary the wheel speed, feed rate and depth of cut at three levels with a 3-center point design. Furthermore, the average surface roughness was measured using Taylor Hobson PGI Dimension XL optical profilometer, and an acoustic emission data acquisition device from National Instruments was utilized to acquire the signals while the data acquisition codes were designed with National Instrument LabVIEW software for acquisition at a sampling rate of 2 million samples per second. The results show that the raw and root mean square amplitude values of the acoustic signals increased with a corresponding increase in the measured average surface roughness values for the different parameter combinations. Therefore, this research concludes that acoustic emission monitoring technique is a potential technique for monitoring the surface roughness in the ultra high precision grinding of borosilicate-crown glass.

Keywords: acoustic emission, borosilicate-crown glass, surface roughness, ultra high precision grinding

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Authors: Mohamed H. Khalil

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Water is one of the most crucial elements which influence human lives and development. Noteworthy, over the last few years, GIS plays a significant role in optimizing water management systems, especially after exponential developing in this sector. In this context, the Egyptian government initiated an advanced ‘GIS-Web Based System’. This system is efficiently designed to tangibly assist and optimize the complement and integration of data between departments of Call Center, Operation and Maintenance, and laboratory. The core of this system is a unified ‘Data Model’ for all the spatial and tabular data of the corresponding departments. The system is professionally built to provide advanced functionalities such as interactive data collection, dynamic monitoring, multi-user editing capabilities, enhancing data retrieval, integrated work-flow, different access levels, and correlative information record/track. Noteworthy, this cost-effective system contributes significantly not only in the completeness of the base-map (93%), the water network (87%) in high level of details GIS format, enhancement of the performance of the customer service, but also in reducing the operating costs/day-to-day operations (~ 5-10 %). In addition, the proposed system facilitates data exchange between different departments (Call Center, Operation and Maintenance, and laboratory), which allowed a better understanding/analyzing of complex situations. Furthermore, this system reflected tangibly on: (i) dynamic environmental monitor/water quality indicators (ammonia, turbidity, TDS, sulfate, iron, pH, etc.), (ii) improved effectiveness of the different water departments, (iii) efficient deep advanced analysis, (iv) advanced web-reporting tools (daily, weekly, monthly, quarterly, and annually), (v) tangible planning synthesizing spatial and tabular data; and finally, (vi) scalable decision support system. It is worth to highlight that the proposed future plan (second phase) of this system encompasses scalability will extend to include integration with departments of Billing and SCADA. This scalability will comprise advanced functionalities in association with the existing one to allow further sustainable contributions.

Keywords: GIS Web-Based, base-map, water network, decision support system

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Authors: Kamal Hammad, Alexey Fedorenko, Ivan Sergeichev

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This study uses analytical modeling, experimental testing, and explicit numerical simulations to evaluate failure and spall damage in Carbon Fiber-Reinforced Polymer (CFRP) composite confinement vessels. It investigates the response of composite materials to explosive loading dynamic impact, revealing varied failure modes. Hashin damage was used to model inplane failure, while the Virtual Crack Closure Technique (VCCT) modeled inter-laminar damage. Results show moderate agreement between simulations and experiments regarding free surface velocity and failure stresses, with discrepancies due to wire alignment imperfections and wave reverberations in the experimental test. The findings can improve design and risk-reduction strategies in high-risk scenarios, leading to enhanced safety and economic efficiency in material assessment and structural design processes.

Keywords: explicit, numerical, spall, damage, CFRP, composite, vessels, explosive, dynamic, impact, Hashin, VCCT

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Authors: Huawei Ma, Wencai Du, Shengbin Liang

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Smart Home Healthcare technologies for the elderly represent a transformative paradigm that leverages emerging technologies to provide the elderly’ health indicators and daily life monitoring, emergency calls, environmental monitoring, behavior perception, and other services to ensure the health and safety of the elderly who are aging in their own home. However, the excessive complexity in the main adopted framework has affected the acceptance and adoption of the elderly. Therefore, this paper proposes a lightweight synergy architecture of IoT data and service for elderly home smart health environment. It includes the modeling of IoT applications and their workflows, data interoperability, interaction, and storage paradigms to meet the growing needs of older people so that they can lead an active, fulfilling, and quality life.

Keywords: smart home healthcare, IoT, independent living, lightweight framework

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Authors: Sreejith Jayachandran, Mojtaba Ghods, Morteza Mohammadzaheri

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The modern busy world is running behind new embedded technologies based on computers and software; meanwhile, some people forget to do their health condition and regular medical check-ups. Some of them postpone medical check-ups due to a lack of time and convenience, while others skip these regular evaluations and medical examinations due to huge medical bills and hospital expenses. Engineers and medical experts have come together to give birth to a new device in the telemonitoring system capable of monitoring, checking, and evaluating the health status of the human body remotely through the internet for the needs of all kinds of people. The remote health monitoring device is a microcontroller-based embedded unit. Various types of sensors in this device are connected to the human body, and with the help of an Arduino UNO board, the required analogue data is collected from the sensors. The microcontroller on the Arduino board processes the analogue data collected in this way into digital data and transfers that information to the cloud, and stores it there, and the processed digital data is instantly displayed through the LCD attached to the machine. By accessing the cloud storage with a username and password, the concerned person’s health care teams/doctors and other health staff can collect this data for the assessment and follow-up of that patient. Besides that, the family members/guardians can use and evaluate this data for awareness of the patient's current health status. Moreover, the system is connected to a Global Positioning System (GPS) module. In emergencies, the concerned team can position the patient or the person with this device. The setup continuously evaluates and transfers the data to the cloud, and also the user can prefix a normal value range for the evaluation. For example, the blood pressure normal value is universally prefixed between 80/120 mmHg. Similarly, the RHMS is also allowed to fix the range of values referred to as normal coefficients. This IoT-based miniature system (11×10×10) cm³ with a low weight of 500 gr only consumes 10 mW. This smart monitoring system is manufactured with 100 GBP, which can be used not only for health systems, it can be used for numerous other uses including aerospace and transportation sections.

Keywords: embedded technology, telemonitoring system, microcontroller, Arduino UNO, cloud storage, global positioning system, remote health monitoring system, alert system

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Authors: Marita Heyns

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Job insecurity is a distressing phenomenon which has far reaching consequences for both employees and their organizations. Previously, much attention has been given to the link between job insecurity and individual level performance outcomes, while less is known about how subjectively perceived job insecurity might transfer beyond the individual level to affect performance of the organization on an aggregated level. Research focusing on how employees’ fear of job loss might affect the organization’s ability to respond proactively to volatility and drastic change through applying its capabilities of sensing, seizing, and reconfiguring, appears to be practically non-existent. Equally little is known about the potential underlying mechanisms through which job insecurity might affect the dynamic capabilities of an organization. This study examines how job insecurity might affect dynamic organizational capability through trust as an underling process. More specifically, it considered the simultaneous roles of trust at an impersonal (organizational) level as well as trust at an interpersonal level (in leaders and co-workers) as potential underlying mechanisms through which job insecurity might affect the organization’s dynamic capability to respond to opportunities and imminent, drastic change. A quantitative research approach and a stratified random sampling technique enabled the collection of data among 314 managers at four different plant sites of a large South African steel manufacturing organization undergoing dramatic changes. To assess the study hypotheses, the following statistical procedures were employed: Structural equation modelling was performed in Mplus to evaluate the measurement and structural models. The Chi-square values test for absolute fit as well as alternative fit indexes such as the Comparative Fit Index and the Tucker-Lewis Index, the Root Mean Square Error of Approximation and the Standardized Root Mean Square Residual were used as indicators of model fit. Composite reliabilities were calculated to evaluate the reliability of the factors. Finally, interaction effects were tested by using PROCESS and the construction of two-sided 95% confidence intervals. The findings indicate that job insecurity had a lower-than-expected detrimental effect on evaluations of the organization’s dynamic capability through the conducive buffering effects of trust in the organization and in its leaders respectively. In contrast, trust in colleagues did not seem to have any noticeable facilitative effect. The study proposes that both job insecurity and dynamic capability can be managed more effectively by also paying attention to factors that could promote trust in the organization and its leaders; some practical recommendations are given in this regard.

Keywords: dynamic organizational capability, impersonal trust, interpersonal trust, job insecurity

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Authors: Nadia Yaghoobi, Seyed Majid Esmaeilzadeh

Abstract:

Due to advancements in wireless communication, new sensor capabilities have been created. In addition to the automation industry, the Internet of Things (IoT) has been used in environmental issues and has provided the possibility of communication between different devices for data collection and exchange. Water quality depends on many factors which are essential for maintaining the minimum sustainability of water. Regarding the great dependence of fishes on the quality of the aquatic environment, water quality can directly affect their activity. Therefore, monitoring water quality is an important issue to consider, especially in the fish farming industry. The conventional method of water quality testing is to collect water samples manually and send them to a laboratory for testing and analysis. This time-consuming method is a waste of manpower and is not cost-effective. The water quality measurement system implemented in this project monitors water quality in real-time through various sensors (parameters: water temperature, water level, dissolved oxygen, humidity and ambient temperature, water turbidity, PH). The Wi-Fi module, ESP8266, transmits data collected by sensors wirelessly to ThingSpeak and the smartphone app. Also, with the help of these instantaneous data, water temperature and water level can be controlled by using a heater and a water pump, respectively. This system can have a detailed study of the pollution and condition of water resources and can provide an environment for safe fish farming.

Keywords: dissolved oxygen, IoT, monitoring, ThingSpeak, water level, water quality, WiFi module

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Authors: N. Seemuang, T. McLeay, T. Slatter

Abstract:

Worn tools have a direct effect on the surface finish and part accuracy. Tool condition monitoring systems have been developed over a long period and used to avoid a loss of productivity resulting from using a worn tool. However, the majority of tool monitoring research has applied expensive sensing systems not suitable for production. In this work, the cutting sound in turning machine was studied using microphone. Machining trials using seven cutting conditions were conducted until the observable flank wear width (FWW) on the main cutting edge exceeded 0.4 mm. The cutting inserts were removed from the tool holder and the flank wear width was measured optically. A microphone with built-in preamplifier was used to record the machining sound of EN24 steel being face turned by a CNC lathe in a wet cutting condition using constant surface speed control. The sound was sampled at 50 kS/s and all sound signals recorded from microphone were transformed into the frequency domain by FFT in order to establish the frequency content in the audio signature that could be then used for tool condition monitoring. The extracted feature from audio signal was compared to the flank wear progression on the cutting inserts. The spectrogram reveals a promising feature, named as ‘spindle noise’, which emits from the main spindle motor of turning machine. The spindle noise frequency was detected at 5.86 kHz of regardless of cutting conditions used on this particular CNC lathe. Varying cutting speed and feed rate have an influence on the magnitude of power spectrum of spindle noise. The magnitude of spindle noise frequency alters in conjunction with the tool wear progression. The magnitude increases significantly in the transition state between steady-state wear and severe wear. This could be used as a warning signal to prepare for tool replacement or adapt cutting parameters to extend tool life.

Keywords: tool wear, flank wear, condition monitoring, spindle noise

Procedia PDF Downloads 320

Authors: Sai Hung Cheung, Zhe Shao

Abstract:

It is of our great interest to quantify the risk to structural dynamic systems due to earthquake-induced tsunamis in view of recent earthquake-induced tsunamis in Padang, 2004 and Tohoku, 2011 which brought huge losses of lives and properties. Despite continuous advancement in computational simulation of the tsunami and wave-structure interaction modeling, it still remains computationally challenging to evaluate the reliability of a structural dynamic system when uncertainties related to the system and its modeling are taken into account. The failure of the structure in a tsunami-wave-structural system is defined as any response quantities of the system exceeding specified thresholds during the time when the structure is subjected to dynamic wave impact due to earthquake-induced tsunamis. In this paper, an approach based on a novel integration of a recently proposed moving least squares response surface approach for stochastic sampling and the Subset Simulation algorithm is proposed. The effectiveness of the proposed approach is discussed by comparing its results with those obtained from the Subset Simulation algorithm without using the response surface approach.

Keywords: response surface, stochastic simulation, structural reliability tsunami, risk

Procedia PDF Downloads 659

Authors: Ahmadreza Jabalameli, Mohammad Ebrahimpour Borujeni

Abstract:

This study aims to evaluate the effectiveness of intensive short-term dynamic psychotherapy (ISTDP) on ambiguity tolerance, emotional intelligence and stress coping strategies in financial market traders. The methodology of this study was quasi-experimental, pre-test and post-test with control group. The statistical population of this study includes all students at Jabalameli Information Technology Academy in 2022. Among them, 30 people were selected by voluntary sampling through interviews, and were randomly divided into two experimental and control groups of 51 people. And the components were measured according to McLain Ambiguity Tolerance Questionnaire, Bar-On Emotional Intelligence and Lazarus Stress Coping Strategies. The data were obtained by SPSS software and were analyzed by using multivariate analysis of covariance. The results indicate that intensive short-term dynamic psychotherapy influences the emotional intelligence as well as the ambiguity tolerance of traders.

Keywords: ISTDP, ambiguity tolerance, trading, emotional intelligence, stress

Procedia PDF Downloads 67

Authors: Sayed Isahaq Hossain, K. T. Chang, Moustapha Ndour

Abstract:

Inference of the phreatic line through earth dams is of paramount importance because it could be directly associated with piping phenomena which may lead to the dam failure. Normally in the field, the instrumentations such as ‘diver’ and ‘standpipe’ are to be used to identify the seepage conditions which only provide point data with a fair amount of interpolation or assumption. Here in this paper, we employed high-resolution fiber optic cable sensors (FOCS) based on Raman Scattering in order to obtain a very accurate phreatic line and seepage profile. Unlike the above-mention devices which pinpoint the water level location, this kind of Distributed Fiber Optics Sensing gives us more reliable information due to its inherent characteristics of continuous measurement.

Keywords: standpipe, diver, FOCS, monitoring, Raman scattering

Procedia PDF Downloads 341

Authors: Jun Tian, Yu Yang, Liping Zhang, Qianhua Kan

Abstract:

Experimental results show that SA 508-3 steel exhibits temperature dependent cyclic softening characteristic and obvious ratcheting behaviors, and dynamic strain age was observed at temperature range of 200 ºC to 350 ºC. Based on these observations, a temperature dependent cyclic plastic constitutive model was proposed by introducing the nonlinear cyclic softening and kinematic hardening rules, and the dynamic strain age was also considered into the constitutive model. Comparisons between experiments and simulations were carried out to validate the proposed model at elevated temperature.

Keywords: constitutive model, elevated temperature, ratcheting, SA 508-3

Procedia PDF Downloads 285

Authors: Mahan Qwamizadeh, Kun Zhou, Zuoqi Zhang, Yong Wei Zhang

Abstract:

Typical load-bearing biological materials like bone, mineralized tendon and shell, are biocomposites made from both organic (collagen) and inorganic (biomineral) materials. This amazing class of materials with intrinsic internally designed hierarchical structures show superior mechanical properties with regard to their weak components from which they are formed. Extensive investigations concentrating on static loading conditions have been done to study the biological materials failure. However, most of the damage and failure mechanisms in load-bearing biological materials will occur whenever their structures are exposed to dynamic loading conditions. The main question needed to be answered here is: What is the relation between the layout and architecture of the load-bearing biological materials and their dynamic behavior? In this work, a staggered model has been developed based on the structure of natural materials at nanoscale and Finite Element Analysis (FEA) has been used to study the dynamic behavior of the structure of load-bearing biological materials to answer why the staggered arrangement has been selected by nature to make the nanocomposite structure of most of the biological materials. The results showed that the staggered structures will efficiently attenuate the stress wave rather than the layered structure. Furthermore, such staggered architecture is effectively in charge of utilizing the capacity of the biostructure to resist both normal and shear loads. In this work, the geometrical parameters of the model like the thickness and aspect ratio of the mineral inclusions selected from the typical range of the experimentally observed feature sizes and layout dimensions of the biological materials such as bone and mineralized tendon. Furthermore, the numerical results validated with existing theoretical solutions. Findings of the present work emphasize on the significant effects of dynamic behavior on the natural evolution of load-bearing biological materials and can help scientists to design bioinspired materials in the laboratories.

Keywords: load-bearing biological materials, nanostructure, staggered structure, stress wave decay

Procedia PDF Downloads 439