Search results for: Process models

Authors: Ibrahim Naeimifar, Omid Naeemifar

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Evaluation of the excavation-induced ground movements is an important design aspect of support systems in urban areas. Geological and geotechnical conditions of an excavation area have significant effects on excavation-induced ground movements and the related damage. This paper is aimed at studying the performance of excavation walls supported by nails in jointed rock medium. The performance of nailed walls is investigated based on evaluating the excavation-induced ground movements. For this purpose, a set of calibrated 2D finite element models is developed by taking into account the nail-rock-structure interactions, the anisotropic properties of jointed rock, and the staged construction process. The results of this paper highlight effects of different parameters such as joint inclinations, the anisotropy of rocks and nail inclinations on deformation parameters of excavation wall supported by nails.

Keywords: finite element, jointed rock, nailing, performance

Procedia PDF Downloads 288

Authors: Heng Chia Ying, Charmaine Tan Chai Nie, Burra Venkata Durga Kumar

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Process scheduling is the method of process management that determines which process the CPU will proceed with for the next task and how long it takes. Some issues were found in process management, particularly for Priority Scheduling (PS) and Round Robin Scheduling (RR). The proposed recommendations made for IPRRS are to combine the strengths of both into a combining algorithm while they draw on others to compensate for each weakness. A significant improvement on the combining technique of scheduler, Incorporating Priority Round-Robin Scheduler (IPRRS) address an algorithm for both high and low priority task to sustain the indefinite blocking issue faced in the priority scheduling algorithm and minimize the average turnaround time (ATT) and average waiting time (AWT) in RR scheduling algorithm. This paper will delve into the simple rules introduced by IPRRS and enhancements that both PS and RR bring to the execution of processes in the operating system. Furthermore, it incorporates the best aspects of each algorithm to build the optimum algorithm for a certain case in terms of prioritized processes, ATT, and AWT.

Keywords: round Robin scheduling, priority scheduling, indefinite blocking, process management, sustain, turnaround time

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Authors: Jonas Pedro Fabris, Alberth Almeida Amorim Souza, Maria Emilia Camargo, Suzana Leitão Russo

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With the law Nº. 9279, of May 14, 1996, the Brazilian government regulates rights and obligations relating to industrial property considering the economic development of the country as granting patents, trademark registration, registration of industrial designs and other forms of protection copyright. In this study, we show the application of the methodology of Box and Jenkins in the series of deposits of industrial design at the National Institute of Industrial Property for the period from May 1996 to April 2013. First, a graphical analysis of the data was done by observing the behavior of the data and the autocorrelation function. The best model found, based on the analysis of charts and statistical tests suggested by Box and Jenkins methodology, it was possible to determine the model number for the deposit of industrial design, SARIMA (2,1,0)(2,0,0), with an equal to 9.88% MAPE.

Keywords: ARIMA models, autocorrelation, Box and Jenkins Models, industrial design, MAPE, time series

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Authors: C. Pislaru, A. Shebani

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This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for modelling the non-linear dynamic models, where the K-Means clustering algorithm used in this paper to select the centers of radial basis function network, because it is reliable, offers fast convergence and can handle large data sets. The least mean square method is used to adjust the weights to the output layer, and Euclidean distance method used to measure the width of the Gaussian function.

Keywords: system identification, nonlinear systems, neural networks, radial basis function, K-means clustering algorithm

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Authors: Muhammad Imran, Iqra Basit, Mobushir Riaz Khan, Sajid Rasheed Ahmad

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The present study investigates the space-time impact of climate change on the rice crop calendar in tropical Gujranwala, Pakistan. The climate change impact was quantified through the climatic variables, whereas the existing calendar of the rice crop was compared with the phonological stages of the crop, depicted through the time series of the Normalized Difference Vegetation Index (NDVI) derived from Landsat data for the decade 2005-2015. Local maxima were applied on the time series of NDVI to compute the rice phonological stages. Panel models with fixed and cross-section fixed effects were used to establish the relation between the climatic parameters and the time-series of NDVI across villages and across rice growing periods. Results show that the climatic parameters have significant impact on the rice crop calendar. Moreover, the fixed effect model is a significant improvement over cross-sectional fixed effect models (R-squared equal to 0.673 vs. 0.0338). We conclude that high inter-annual variability of climatic variables cause high variability of NDVI, and thus, a shift in the rice crop calendar. Moreover, inter-annual (temporal) variability of the rice crop calendar is high compared to the inter-village (spatial) variability. We suggest the local rice farmers to adapt this change in the rice crop calendar.

Keywords: Landsat NDVI, panel models, temperature, rainfall

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Authors: Valeria Bondarenko

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We proposed algorithms for: estimation of parameters fBm (volatility and Hurst exponent) and for the approximation of random time series by functional of fBm. We proved the consistency of the estimators, which constitute the above algorithms, and proved the optimal forecast of approximated time series. The adequacy of estimation algorithms, approximation, and forecasting is proved by numerical experiment. During the process of creating software, the system has been created, which is displayed by the hierarchical structure. The comparative analysis of proposed algorithms with the other methods gives evidence of the advantage of approximation method. The results can be used to develop methods for the analysis and modeling of time series describing the economic, physical, biological and other processes.

Keywords: mathematical model, random process, Wiener process, fractional Brownian motion

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Authors: Fadilah Fadilah, Sperisa Distantina, Santi T. Wijayanti, Rahmawati Andayani

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Chemical modification process on glucomannan from porang via carboxymethylation have been conducted. The process was done in two stages, the alkalization, and the carboxymethylation. The alkalization was done by adding NaOH solution into the medium which was contained glucomannan and then stirred it in ambient temperature for thirty minutes. The carboxymethylation process was done by adding sodium mono chloroacetate solution into the alkalization product. The carboxymethylation process was conducted for a certain time, and the product was then analyzed for determining the degree of substitution. In this research, the influence of medium to the degree of substitution was studied. Three different medium were used, namely water, 70% ethanol, and 90% ethanol. The results show that 70% ethanol was a better medium than two others because give a higher degree of substitution. Using 70% ethanol as a medium, the experiments for studying the influence of temperature on the carboxymethylation stages were conducted. The results show that the degree of substitution at 65°C is higher than at 45°C.

Keywords: carboxymethylation, degree of substitution, ethanol medium, glucomannan

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Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

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Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

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Authors: J. L. Andrade-Pineda, J.M. León-Blanco, M. Calle, P. L. González-R

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The enrollment in current Master's degree programs usually pursues gaining the expertise required in real-life workplaces. The experience we present here concerns the learning process of "Project Management Methodology (PMM)", around a cooperative/collaborative mechanism aimed at affording students measurable learning goals and providing the teacher with the ability of focusing on the weaknesses detected. We have designed a mixed summative/formative evaluation, which assures curriculum engage while enriches the comprehension of PMM key concepts. In this experience we converted the students into active actors in the evaluation process itself and we endowed ourselves as teachers with a flexible process in which along with qualifications (score), other attitudinal feedback arises. Despite the high level of self-affirmation on their discussion within the interactive assessment sessions, they ultimately have exhibited a great ability to review and correct the wrong reasoning when that was the case.

Keywords: cooperative-collaborative learning, educational management, formative-summative assessment, leadership training

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Authors: Habtamu Tkubet Ebuy

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Purpose Conventional dynamic energy simulation tools go beyond the static dimension of simplified methods by providing better and more accurate prediction of building performance. However, their ability to forecast actual performance is undermined by a low representation of human interactions. The purpose of this study is to examine the potential benefits of incorporating information on occupant diversity into occupant behavior models used to simulate building performance. The co-simulation of the stochastic behavior of the occupants substantially increases the accuracy of the simulation. Design/methodology/approach In this article, probabilistic models of the "opening and closing" behavior of the window of inhabitants have been developed in a separate multi-agent platform, SimOcc, and implemented in the building simulation, TRNSYS, in such a way that the behavior of the window with the interconnectivity can be reflected in the simulation analysis of the building. Findings The results of the study prove that the application of complex behaviors is important to research in predicting actual building performance. The results aid in the identification of the gap between reality and existing simulation methods. We hope this study and its results will serve as a guide for researchers interested in investigating occupant behavior in the future. Research limitations/implications Further case studies involving multi-user behavior for complex commercial buildings need to more understand the impact of the occupant behavior on building performance. Originality/value This study is considered as a good opportunity to achieve the national strategy by showing a suitable tool to help stakeholders in the design phase of new or retrofitted buildings to improve the performance of office buildings.

Keywords: occupant behavior, co-simulation, energy consumption, thermal comfort

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Authors: Cheng-Lung Yu, Ying-His Liao

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Some evidence show that public art accelerates local economic growth. Even local governments award the collaboration of public-private partnership to sustain the creation of public art for urban economic development. Through the public-private partnership of public art establishment it is obvious that public construction projects have been led by the governmental policy yet the private developers have played crucial roles to drive the innovative business models such as tourism investment, real estate value up and community participation. This study shows that the types of collaboration have been driven by Taichung city governmental policy from the regulation of public art establishment in the past three years. Through some cases empirical analyzes the authors discover the trends concerning the public art development to support local economic growth in Taiwan.

Keywords: public art, public art establishment regulation, construction management, urban governance

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Authors: Won Kyung Ham, Kang Hoon Cho, Sang C. Park

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Presented in this paper is a framework of a software ‘WEMax’. The WEMax is invented for analysis and simulation for manned assembly lines to sustain and improve performance of manufacturing systems. In a manufacturing system, performance, such as productivity, is a key of competitiveness for output products. However, the manned assembly lines are difficult to forecast performance, because human labors are not expectable factors by computer simulation models or mathematical models. Existing approaches to performance forecasting of the manned assembly lines are limited to matters of the human itself, such as ergonomic and workload design, and non-human-factor-relevant simulation. Consequently, an approach for the forecasting and improvement of manned assembly line performance is needed to research. As a solution of the current problem, this study proposes a framework that is for generation and simulation of virtual manned assembly lines, and the framework has been implemented as a software.

Keywords: performance forecasting, simulation, virtual manned assembly line, WEMax

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Authors: Yuchen Sharon Sung, Yingjui Tseng

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High-rise residential buildings have become the most mainstream housing pattern in the world’s metropolises under the current trend of urbanization. The facades of high-rise buildings are essential elements of the urban landscape. The skins of these facades are important media between the interior and exterior of high- rise buildings. It not only connects between users and environments, but also plays an important functional and aesthetic role. This research involves a study of skins of high-rise residential buildings using the methodology of shape grammar to find out the rules which determine the combinations of the facade patterns and analyze the patterns’ parameters using software Grasshopper. We chose a number of facades of high-rise residential buildings as source to discover the underlying rules and concepts of the generation of facade skins. This research also provides the rules that influence the composition of facade skins. The items of the facade skins, such as windows, balconies, walls, sun visors and metal grilles are treated as elements in the system of facade skins. The compositions of these elements will be categorized and described by logical rules; and the types of high-rise building facade skins will be modelled by Grasshopper. Then a variety of analyzed patterns can also be applied on other facade skins through this parametric mechanism. Using these patterns established in the models, researchers can analyze each single item to do more detail tests and architects can apply each of these items to construct their facades for other buildings through various combinations and permutations. The goal of these models is to develop a mechanism to generate prototypes in order to facilitate generation of various facade skins.

Keywords: facade skin, grasshopper, high-rise residential building, shape grammar

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Authors: V. D. Thi, M. Li, M. Khelifa, M. El Ganaoui, Y. Rogaume

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This paper presents a two-dimensional model to study the heat and moisture transfer through porous building materials. Dynamic and static coupled models of heat and moisture transfer in porous material under low temperature are presented and the coupled models together with variable initial and boundary conditions have been considered in an analytical way and using the finite element method. The resulting coupled model is converted to two nonlinear partial differential equations, which is then numerically solved by an implicit iterative scheme. The numerical results of temperature and moisture potential changes are compared with the experimental measurements available in the literature. Predicted results demonstrate validation of the theoretical model and effectiveness of the developed numerical algorithms. It is expected to provide useful information for the porous building material design based on heat and moisture transfer model.

Keywords: finite element method, heat transfer, moisture transfer, porous materials, wood

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Authors: Benbiao Song, Yan Gao, Zhuo Liu

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Geostatistical modeling is the key technic for reservoir characterization, the quality of geological models will influence the prediction of reservoir performance greatly, but few studies have been done to quantify the factors impacting geostatistical reservoir modeling accuracy. In this study, 16 fluvial prototype models have been established to represent different geological complexity, 6 cases range from 16 to 361 wells were defined to reproduce all those 16 prototype models by different methodologies including SIS, object-based and MPFS algorithms accompany with different constraint parameters. Modeling accuracy ratio was defined to quantify the influence of each factor, and ten realizations were averaged to represent each accuracy ratio under the same modeling condition and parameters association. Totally 5760 simulations were done to quantify the relative contribution of each factor to the simulation accuracy, and the results can be used as strategy guide for facies modeling in the similar condition. It is founded that data density, geological trend and geological complexity have great impact on modeling accuracy. Modeling accuracy may up to 90% when channel sand width reaches up to 1.5 times of well space under whatever condition by SIS and MPFS methods. When well density is low, the contribution of geological trend may increase the modeling accuracy from 40% to 70%, while the use of proper variogram may have very limited contribution for SIS method. It can be implied that when well data are dense enough to cover simple geobodies, few efforts were needed to construct an acceptable model, when geobodies are complex with insufficient data group, it is better to construct a set of robust geological trend than rely on a reliable variogram function. For object-based method, the modeling accuracy does not increase obviously as SIS method by the increase of data density, but kept rational appearance when data density is low. MPFS methods have the similar trend with SIS method, but the use of proper geological trend accompany with rational variogram may have better modeling accuracy than MPFS method. It implies that the geological modeling strategy for a real reservoir case needs to be optimized by evaluation of dataset, geological complexity, geological constraint information and the modeling objective.

Keywords: fluvial facies, geostatistics, geological trend, modeling strategy, modeling accuracy, variogram

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Authors: Rony Reátegui, Cesar Chácara, Benjamin Castañeda, Rafael Aguilar

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Nowadays, heritage building information modeling (HBIM) is considered an efficient tool to represent and manage information of cultural heritage (CH). The basis of this tool relies on a 3D model generally obtained from a cloud-to-BIM procedure. There are different methods to create an HBIM model that goes from manual modeling based on the point cloud to the automatic detection of shapes and the creation of objects. The selection of these methods depends on the desired level of development (LOD), level of information (LOI), grade of generation (GOG), as well as on the availability of commercial software. This paper presents the 3D modeling of a stone masonry chapel using Recap Pro, Revit, and Dynamo interface following a three-step methodology. The first step consists of the manual modeling of simple structural (e.g., regular walls, columns, floors, wall openings, etc.) and architectural (e.g., cornices, moldings, and other minor details) elements using the point cloud as reference. Then, Dynamo is used for generative modeling of complex structural elements such as vaults, infills, and domes. Finally, semantic information (e.g., materials, typology, state of conservation, etc.) and pathologies are added within the HBIM model as text parameters and generic models families, respectively. The application of this methodology allows the documentation of CH following a relatively simple to apply process that ensures adequate LOD, LOI, and GOG levels. In addition, the easy implementation of the method as well as the fact of using only one BIM software with its respective plugin for the scan-to-BIM modeling process means that this methodology can be adopted by a larger number of users with intermediate knowledge and limited resources since the BIM software used has a free student license.

Keywords: cloud-to-BIM, cultural heritage, generative modeling, HBIM, parametric modeling, Revit

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Authors: Chothmal

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In this paper, we present a route discovery process which uses the signal strength on a link as a parameter of its inclusion in the route discovery method. The proposed signal-to-interference and noise ratio (SINR) based multipath reactive routing protocol is named as SINR-MP protocol. The proposed SINR-MP routing protocols has two following two features: a) SINR-MP protocol selects routes based on the SINR of the links during the route discovery process therefore it select the routes which has long lifetime and low frame error rate for data transmission, and b) SINR-MP protocols route discovery process is multipath which discovers more than one SINR based route between a given source destination pair. The multiple routes selected by our SINR-MP protocol are node-disjoint in nature which increases their robustness against link failures, as failure of one route will not affect the other route. The secondary route is very useful in situations where the primary route is broken because we can now use the secondary route without causing a new route discovery process. Due to this, the network overhead caused by a route discovery process is avoided. This increases the network performance greatly. The proposed SINR-MP routing protocol is implemented in the trail version of network simulator called Qualnet.

Keywords: ad hoc networks, quality of service, video streaming, H.264/SVC, multiple routes, video traces

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Authors: Zakaria Baka, Halima Alem

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Cancer is a major worldwide health problem that has caused around ten million deaths in 2020. In addition, efforts to develop new anti-cancer drugs still face a high failure rate. This is partly due to the lack of preclinical models that recapitulate in-vivo drug responses. Indeed conventional cell culture approach (known as 2D cell culture) is far from reproducing the complex, dynamic and three-dimensional environment of tumors. To set up more in-vivo-like cancer models, 3D bioprinting seems to be a promising technology due to its ability to achieve 3D scaffolds containing different cell types with controlled distribution and precise architecture. Moreover, the introduction of microfluidic technology makes it possible to simulate in-vivo dynamic conditions through the so-called “cancer-on-chip” platforms. Whereas several cancer types have been modeled through the cancer-on-chip approach, such as lung cancer and breast cancer, only a few works describing ovarian cancer models have been described. The aim of this work is to combine 3D bioprinting and microfluidic technics with setting up a 3D dynamic model of ovarian cancer. In the first phase, alginate-gelatin hydrogel containing SKOV3 cells was used to achieve tumor-like structures through an extrusion-based bioprinter. The desired form of the tumor-like mass was first designed on 3D CAD software. The hydrogel composition was then optimized for ensuring good and reproducible printability. Cell viability in the bioprinted structures was assessed using Live/Dead assay and WST1 assay. In the second phase, these bioprinted structures will be included in a microfluidic device that allows simultaneous testing of different drug concentrations. This microfluidic dispositive was first designed through computational fluid dynamics (CFD) simulations for fixing its precise dimensions. It was then be manufactured through a molding method based on a 3D printed template. To confirm the results of CFD simulations, doxorubicin (DOX) solutions were perfused through the dispositive and DOX concentration in each culture chamber was determined. Once completely characterized, this model will be used to assess the efficacy of anti-cancer nanoparticles developed in the Jean Lamour institute.

Keywords: 3D bioprinting, ovarian cancer, cancer-on-chip models, microfluidic techniques

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Authors: Juliana Bastos dos Santos, Francisca Dantas Mendes, Abdul Jabbar Mohammad Khatri, Adam Abdul Jabbar Khatri

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This research aims to describe the experimentation of color extraction from household waste, for the application of the natural vegetable dyeing technique, as a more sustainable option for the upcycling process. Based on the research of the case study, this article intends to record the process of collecting the materials, extracting the colors and their applicability. The study aims to deepen the knowledge about possible alternatives that generate less impact on the environment throughout the process of plant stamping and, also, to spread the concepts of sustainability in fashion. Therefore, this content becomes relevant for valuing an artisanal production process, reconnecting with ancestral knowledge. This article also intends to serve as a record of ancestral artisanal processes, based on the indigenous and African matrices that are pillars of Brazilian culture.

Keywords: natural dyeing, sustainability, organic residue, fashion, reuse

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Authors: Changqiao Wu, Guoqing Ding, Xin Chen

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In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Keywords: dynamic system modeling, neural network, normal equation, second order gradient descent

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Authors: Ying Yuken, Pengfei Wang, Zhang Qilin, Xiao Ben

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Based on the main entrance and garden area (ME&G) project of Shanghai Disneyland, this paper introduces the application of BIM technology in this kind of low-rise comprehensive building with complex facade system, electromechanical system and decoration system. BIM technology is applied to the whole process of design, construction and completion of the whole project. With the construction of BIM application framework of the whole project, the key points of BIM modeling methods of different systems and the integration and coordination of BIM models are elaborated in detail. The specific application methods of BIM technology in similar complex low-rise building projects are sorted out. Finally, the paper summarizes the benefits of BIM technology application, and puts forward some suggestions for BIM management mode and practical application of similar projects in the future.

Keywords: BIM, complex low-rise building, BIM modeling, model integration and coordination, 3D scanning

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Authors: Abigail Wiafe, Charles Nutrokpor, Adelaide Oduro-Asante

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The advancement of technology is rapidly making people more receptive to music as computer-generated music requires minimal human interventions. Though algorithms are applied to generate music, the human experience of emotions is still explored. Thus, this study investigates the emotions humans experience listening to computer-generated music that possesses aesthetic qualities. Forty-two subjects participated in the survey. The selection process was purely arbitrary since it was based on convenience. Subjects listened and evaluated the emotions experienced from the computer-generated music through an online questionnaire. The Likert scale was used to rate the emotional levels after the music listening experience. The findings suggest that computer-generated music possesses aesthetic qualities that do not affect subjects' emotions as long as they are pleased with the music. Furthermore, computer-generated music has unique creativity, and expressioneven though the music produced is meaningless, the computational models developed are unable to present emotional contents in music as humans do.

Keywords: aesthetic, algorithms, emotions, computer-generated music

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Authors: Niveen M. Hassan-Abbas

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The COVID-19 pandemic created a range of stressors, among them difficulties related to work conditions, financial changes, lack of childcare, and confinement or isolation due to social distancing. Among families and married individuals, these stressors were often expressed in additional daily hassles, with an influence on mental health. This study examined two moderated mediation models based on Bodenmann’s systemic-transactional stress model. Specifically, the models tested the hypothesis that intra-dyadic stress mediates the association between extra-dyadic stress and mental health, while two measures of family functioning, cohesion, and flexibility, moderate the relationship between extra and intra-dyadic stress. Participants were 480 heterosexual married Palestinians from Israel who completed self-report questionnaires. The results showed partial mediation patterns supporting both models, indicating that family cohesion and flexibility weakened the mediating effect of intra-dyadic stress on the relationship between extra-dyadic stress and mental health. These findings increase our understanding of the variables that affected mental health during the pandemic and suggested that when faced with extra-dyadic stress, married individuals with good family environments are less likely to experience high levels of intra-dyadic stress, which is in turn associated with preserved mental health. Limitations and implications for planning interventions for couples and families during the pandemic are discussed.

Keywords: Palestinian families in Israel, COVID-19 pandemic, family cohesion and flexibility, extra-dyadic stress, intra-dyadic stress, mental health

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Authors: Bojana Tot, Goran BošKović, Goran Vujić

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Route optimisation is a process of planning one or multiple routes, with the purpose of minimizing overall costs, while achieving the highest possible performance under a set of given constraints. It combines routing or route planning, which is the process of creating the most cost-effective route by minimizing the distance or travelled time necessary to reach a set of planned stops, and route scheduling, which is the process of assigning an arrival and service time for each stop, with drivers being given shifts that adhere to their working hours. The objective of this paper is to provide benefits on the implementation of waste collection route optimisation and thus achieve economic efficiency for public utility companies, better service for citizens and positive environment and health.

Keywords: waste management, environment, collection route optimisation, GIS

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Authors: Donatello Cardone

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Bilinear hysteresis models are usually used to describe the cyclic behavior of high damping rubber bearings. However, they neglect a number of phenomena (such as the interaction between axial load and shear force, buckling and post-buckling behavior, cavitation, scragging effects, etc.) that can significantly influence the dynamic behavior of such isolation devices. In this work, an advanced hysteresis model is examined and properly calibrated using consolidated procedures. Results of preliminary numerical analyses, performed in OpenSees, are shown and compared with the results of experimental tests on high damping rubber bearings and simulation analyses using alternative nonlinear models. The findings of this study can provide an useful tool for the accurate evaluation of the seismic response of structures with rubber-based isolation systems.

Keywords: seismic isolation, high damping rubber bearings, numerical modeling, axial-shear force interaction

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Authors: Achim Kampker, Heiner H. Heimes, Mathias Ordung, Christoph Lienemann, Ansgar Hollah, Nemanja Sarovic

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Electric cars with their fast innovation cycles and their disruptive character offer a high degree of freedom regarding innovative design for remanufacturing. Remanufacturing increases not only the resource but also the economic efficiency by a prolonged product life time. The reduced power train wear of electric cars combined with high manufacturing costs for batteries allow new business models and even second life applications. Modular and intermountable designed battery packs enable the replacement of defective or outdated battery cells, allow additional cost savings and a prolongation of life time. This paper discusses opportunities for future remanufacturing value chains of electric cars and their battery components and how to address their potentials with elaborate designs. Based on a brief overview of implemented remanufacturing structures in different industries, opportunities of transferability are evaluated. In addition to an analysis of current and upcoming challenges, promising perspectives for a sustainable electric car circular economy enabled by design for remanufacturing are deduced. Two mathematical models describe the feasibility of pursuing a circular economy of lithium ion batteries and evaluate remanufacturing in terms of sustainability and economic efficiency. Taking into consideration not only labor and material cost but also capital costs for equipment and factory facilities to support the remanufacturing process, cost benefit analysis prognosticate that a remanufacturing battery can be produced more cost-efficiently. The ecological benefits were calculated on a broad database from different research projects which focus on the recycling, the second use and the assembly of lithium ion batteries. The results of this calculations show a significant improvement by remanufacturing in all relevant factors especially in the consumption of resources and greenhouse warming potential. Exemplarily suitable design guidelines for future remanufacturing lithium ion batteries, which consider modularity, interfaces and disassembly, are used to illustrate the findings. For one guideline, potential cost improvements were calculated and upcoming challenges are pointed out.

Keywords: circular economy, electric mobility, lithium ion batteries, remanufacturing

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Authors: Preshanthan Moodley, E. B. Gueguim-Kana

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The objective of this study was to develop a method to pretreat sugarcane leaf waste using microwave-assisted (MA) inorganic salt. The effects of process parameters of salt concentration, microwave power intensity and pretreatment time on reducing sugar yield from enzymatically hydrolysed sugarcane leaf waste were investigated. Pretreatment models based on MA-NaCl, MA-ZnCl2 and MA-FeCl3 were developed. Maximum reducing sugar yield of 0.406 g/g was obtained with 2 M FeCl3 at 700W for 3.5 min. Scanning electron microscopy (SEM) and Fourier Transform Infrared analysis (FTIR) showed major changes in lignocellulosic structure after MA-FeCl3 pretreatment with 71.5 % hemicellulose solubilization. This pretreatment was further assessed on sorghum leaves and Napier grass under optimal MA-FeCl3 conditions. A 2 fold and 3.1-fold increase in sugar yield respectively were observed compared to previous reports. This pretreatment was highly effective for enhancing enzymatic saccharification of lignocellulosic biomass.

Keywords: acid, pretreatment, salt, sugarcane leaves

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Authors: Dena A. Hussain

Abstract:

The objective of this project is to design an Information and Communication Technologies (ICT) tool based on a standardized platform to assist the work-integrated learning process of caretakers of disabled children. The tool should assist the intercommunication between caretakers and improve the learning process through knowledge bridging between all involved caretakers. Some children are born with disabilities while others have special needs after an illness or accident. Special needs children often need help in their learning process and require tools and services in a different way. In some cases the child has multiple disabilities that affect several capabilities in different ways. These needs are to be transformed into different learning techniques that the staff or personal (called caretakers in this project) caring for the child needs to learn and adapt. The caretakers involved are also required to learn new learning or training techniques and utilities specialized for the child’s needs. In many cases the number of people caring for the child’s development is rather large; the parents, specialist pedagogues, teachers, therapists, psychologists, personal assistants, etc. Each group of specialists has different objectives and in some cases the merge between theses specifications is very unique. This makes the synchronization between different caretakers difficult, resulting often in low level cooperation. By better intercommunication between professions both the child’s development could be improved but also the caretakers’ methods and knowledge of each other’s work processes and their own profession. This introduces a unique work integrated learning environment for all personnel involve, merging learning and knowledge in the work environment and at the same time assist the children’s development process. Creating an iterative process generates a unique learning experience for all involved. Using a work integrated platform will help encourage and support the process of all the teams involved in the process.We believe that working with children who have special needs is a continues learning/working process that is always integrated to achieve one main goal, which is to make a better future for all children.

Keywords: information and communication technologies (ICT), work integrated learning (WIL), sustainable learning, special needs children

Procedia PDF Downloads 294

Authors: Pierre Tize Mha, Mohammad Jahazi, Amèvi Togne, Olivier Pantalé

Abstract:

Large-size forged blocks made of medium carbon high-strength steels are extensively used in the automotive industry as dies for the production of bumpers and dashboards through the plastic injection process. The manufacturing process of the large blocks starts with ingot casting, followed by open die forging and a quench and temper heat treatment process to achieve the desired mechanical properties and numerical simulation is widely used nowadays to predict these properties before the experiment. But the temperature gradient inside the specimen remains challenging in the sense that the temperature before loading inside the material is not the same, but during the simulation, constant temperature is used to simulate the experiment because it is assumed that temperature is homogenized after some holding time. Therefore to be close to the experiment, real distribution of the temperature through the specimen is needed before the mechanical loading. Thus, We present here a robust algorithm that allows the calculation of the temperature gradient within the specimen, thus representing a real temperature distribution within the specimen before deformation. Indeed, most numerical simulations consider a uniform temperature gradient which is not really the case because the surface and core temperatures of the specimen are not identical. Another feature that influences the mechanical properties of the specimen is recrystallization which strongly depends on the deformation conditions and the type of deformation like Upsetting, Cogging...etc. Indeed, Upsetting and Cogging are the stages where the greatest deformations are observed, and a lot of microstructural phenomena can be observed, like recrystallization, which requires in-depth characterization. Complete dynamic recrystallization plays an important role in the final grain size during the process and therefore helps to increase the mechanical properties of the final product. Thus, the identification of the conditions for the initiation of dynamic recrystallization is still relevant. Also, the temperature distribution within the sample and strain rate influence the recrystallization initiation. So the development of a technique allowing to predict the initiation of this recrystallization remains challenging. In this perspective, we propose here, in addition to the algorithm allowing to get the temperature distribution before the loading stage, an analytical model leading to determine the initiation of this recrystallization. These two techniques are implemented into the Abaqus finite element software via the UAMP and VUHARD subroutines for comparison with a simulation where an isothermal temperature is imposed. The Artificial Neural Network (ANN) model to describe the plastic behavior of the material is also implemented via the VUHARD subroutine. From the simulation, the temperature distribution inside the material and recrystallization initiation is properly predicted and compared to the literature models.

Keywords: dynamic recrystallization, finite element modeling, artificial neural network, numerical implementation

Procedia PDF Downloads 80

Authors: M. Heydari Vini

Abstract:

There is a complicated relation between effective input parameters of cold rolling and output rolling force and exit thickness of strips.in many mathematical models, the effect of some rolling parameters have been ignored and the outputs have not a desirable accuracy. In the other hand, there is a special relation among input thickness of strips,the width of the strips,rolling speeds,mandrill tensions and the required exit thickness of strips with rolling force and the real exit thickness of the rolled strip. First of all, in this paper the effective parameters of cold rolling process modeled using an artificial neural network according to the optimum network achieved by using a written program in MATLAB,it has been shown that the prediction of rolling stand parameters with different properties and new dimensions attained from prior rolled strips by an artificial neural network is applicable.

Keywords: cold rolling, artificial neural networks, rolling force, real rolled thickness of strips

Procedia PDF Downloads 505