Search results for: computational complexity

Authors: Aleš Florian, Lenka Ševelová

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Complex sensitivity analysis of stresses in a concrete slab of the real type of rigid pavement made from recycled materials is performed. The computational model of the pavement is designed as a spatial (3D) model, is based on a nonlinear variant of the finite element method that respects the structural nonlinearity, enables to model different arrangements of joints, and the entire model can be loaded by the thermal load. Interaction of adjacent slabs in joints and contact of the slab and the subsequent layer are modeled with the help of special contact elements. Four concrete slabs separated by transverse and longitudinal joints and the additional structural layers and soil to the depth of about 3m are modeled. The thickness of individual layers, physical and mechanical properties of materials, characteristics of joints, and the temperature of the upper and lower surface of slabs are supposed to be random variables. The modern simulation technique Updated Latin Hypercube Sampling with 20 simulations is used. For sensitivity analysis the sensitivity coefficient based on the Spearman rank correlation coefficient is utilized. As a result, the estimates of influence of random variability of individual input variables on the random variability of principal stresses s1 and s3 in 53 points on the upper and lower surface of the concrete slabs are obtained.

Keywords: concrete, FEM, pavement, sensitivity, simulation

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Authors: Jirod Chaisan, Somchai Maneewan, Chantana Punlek, Ninnart Rachapradit, Surapong Chirarattananon, Pattana Rakkwamsuk

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In this paper, simulation modeling of heat transfer, air flow and distribution emitted from CO2 was performed in a regenerated air. The study room was divided in 3 types: common room, small lecture room and large lecture room under evaluated condition in two case: released and unreleased CO2 including of used hybrid air ventilation system for regenerated air under Thailand climate conditions. The carbon dioxide was located on the center of the room and released rate approximately 900-1200 ppm corresponded with indoor air quality standard (IAQs). The indoor air in the thermal comfort zone was calculated and simulated with the numerical method that using real data from the handbook guideline. The results of the study showed that in the case of hybrid air ventilation system explained thermal and CO2 distribution due to the system was adapted significantly in the comfort zone. The results showed that when CO2 released on the center of the other room, the CO2 high concentration in comfort zone so used hybrid air ventilation that decreased CO2 with regeneration air including of reduced temperature indoor. However, the study is simulation modeling and guideline only so the future should be the experiment of hybrid air ventilation system for evaluated comparison of the systems.

Keywords: air ventilation, indoor air quality, thermal comfort, thermoelectric, photovoltaic, dehumidify

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

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Authors: Shryas Bhurat, Aryan Vashistha, Sampreet Dinakar Nayak, Ayush Gupta

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As the technology is advancing more towards high computational resources, there is a paradigm shift in the usage of these resources to optimize the design process. This paper discusses the usage of ‘Generative Design using Artificial Intelligence’ to build better models that adapt the operations like selection, mutation, and crossover to generate results. The human mind thinks of the simplest approach while designing an object, but the intelligence learns from the past & designs the complex optimized CAD Models. Generative Design takes the boundary conditions and comes up with multiple solutions with iterations to come up with a sturdy design with the most optimal parameter that is given, saving huge amounts of time & resources. The new production techniques that are at our disposal allow us to use additive manufacturing, 3D printing, and other innovative manufacturing techniques to save resources and design artistically engineered CAD Models. Also, this paper discusses the Genetic Algorithm, the Non-Domination technique to choose the right results using biomimicry that has evolved for current habitation for millions of years. The computer uses parametric models to generate newer models using an iterative approach & uses cloud computing to store these iterative designs. The later part of the paper compares the topology optimization technology with Generative Design that is previously being used to generate CAD Models. Finally, this paper shows the performance of algorithms and how these algorithms help in designing resource-efficient models.

Keywords: genetic algorithm, bio mimicry, generative modeling, non-dominant techniques

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Authors: Matjaž Šraml, Marko Renčelj, Tomaž Tollazzi, Chiara Gruden

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Road safety is a worldwide issue with numerous and heterogeneous factors influencing it. On the side, driver state – comprising distraction/inattention, fatigue, drowsiness, extreme emotions, and socio-cultural factors highly affect road safety. On the other side, the vehicle state has an important role in mitigating (or not) the road risk. Finally, the road environment is still one of the main determinants of road safety, defining driving task complexity. At the same time, thanks to technological development, a lot of detailed data is easily available, creating opportunities for the detection of driver state, vehicle characteristics and road conditions and, consequently, for the design of ad hoc interventions aimed at improving driver performance, increase awareness and mitigate road risks. This is the challenge faced by the i-DREAMS project. i-DREAMS, which stands for a smart Driver and Road Environment Assessment and Monitoring System, is a 3-year project funded by the European Union’s Horizon 2020 research and innovation program. It aims to set up a platform to define, develop, test and validate a ‘Safety Tolerance Zone’ to prevent drivers from getting too close to the boundaries of unsafe operation by mitigating risks in real-time and after the trip. After the definition and development of the Safety Tolerance Zone concept and the concretization of the same in an Advanced driver-assistance system (ADAS) platform, the system was tested firstly for 2 months in a driving simulator environment in 5 different countries. After that, naturalistic driving studies started for a 10-month period (comprising a 1-month pilot study, 3-month baseline study and 6 months study implementing interventions). Currently, the project team has approved a common evaluation approach, and it is developing the assessment of the usage and outcomes of the i-DREAMS system, which is turning positive insights. The i-DREAMS consortium consists of 13 partners, 7 engineering universities and research groups, 4 industry partners and 2 partners (European Transport Safety Council - ETSC - and POLIS cities and regions for transport innovation) closely linked to transport safety stakeholders, covering 8 different countries altogether.

Keywords: advanced driver assistant systems, driving simulator, safety tolerance zone, traffic safety

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Authors: Mwehe Mathenge, Ben G. J. S. Sonneveld, Jacqueline E. W. Broerse

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Smallholder farmers are important drivers of agriculture productivity, food security, and poverty reduction in Sub-Saharan Africa. However, they are faced with myriad challenges in their efforts at participating in agribusiness markets. How the geographic explicit factors existing at the local level interact to impede smallholder farmers' decision to participates (or not) in agribusiness markets is not well understood. Deconstructing the spatial complexity of the local environment could provide a deeper insight into how geographically explicit determinants promote or impede resource-poor smallholder farmers from participating in agribusiness. This paper’s objective was to identify, map, and analyze local spatial autocorrelation in factors that impede poor smallholders from participating in agribusiness markets. Data were collected using geocoded researcher-administered survey questionnaires from 392 households in Western Kenya. Three spatial statistics methods in geographic information system (GIS) were used to analyze data -Global Moran’s I, Cluster and Outliers Analysis (Anselin Local Moran’s I), and geographically weighted regression. The results of Global Moran’s I reveal the presence of spatial patterns in the dataset that was not caused by spatial randomness of data. Subsequently, Anselin Local Moran’s I result identified spatially and statistically significant local spatial clustering (hot spots and cold spots) in factors hindering smallholder participation. Finally, the geographically weighted regression results unearthed those specific geographic explicit factors impeding market participation in the study area. The results confirm that geographically explicit factors are indispensable in influencing the smallholder farming decisions, and policymakers should take cognizance of them. Additionally, this research demonstrated how geospatial explicit analysis conducted at the local level, using geographically disaggregated data, could help in identifying households and localities where the most impoverished and resource-poor smallholder households reside. In designing spatially targeted interventions, policymakers could benefit from geospatial analysis methods in understanding complex geographic factors and processes that interact to influence smallholder farmers' decision-making processes and choices.

Keywords: agribusiness markets, GIS, smallholder farmers, spatial statistics, disaggregated spatial data

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Authors: Mouna Hamed, Ammar B. Brahim

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The objective of this work was to develop a theoretical model to study the dynamic thermal behavior of a flat plate solar collector integrated with a phase change material (PCM). The PCM acted as a heat source for the solar system during low intensity solar radiation and night. The energy balance equations for the various components of the collector as well as for the PCM were formulated and numerically solved using MATLAB computational program. The effect of natural convection on heat during the melting process was taken into account by using an effective thermal conductivity. The model was used to investigate the effect of inlet water temperature, water mass flow rate, and PCM thickness on the outlet water temperature and the melt fraction during charging and discharging modes. A comparison with a collector without PCM was made. Results showed that charging and discharging processes of PCM have six stages. The adding of PCM caused a decrease in temperature during charge and an increase during discharge. The rise was most enhanced for higher inlet water temperature, PCM thickness and for lower mass flow rate. Analysis indicated that the complete melting time was shorter than the solidification time due to the high heat transfer coefficient during melting. The increases in PCM height and mass flow rate were not linear with the melting and solidification times.

Keywords: thermal energy storage, phase change material, melting, solidification

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Authors: Selfa Johnson Zwalnan, Nanchen Nimyel Caleb, Gideon Duvuna Ayuba

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Air conditioning accounts for a significant share of the overall energy consumed in residential buildings. Solar thermal gains in buildings account for a significant component of the air conditioning load in buildings. This study compares the solar thermal gain and air conditioning load of a proposed building design with a typical conventional building in the climatic conditions of Jos, Nigeria, using a combined experimental and computational method using TRNSYS software. According to the findings of this study, the proposed design building's annual average solar thermal gains are lower compared to the reference building's average solar heat gains. The study case building's decreased solar heat gain is mostly attributable to the somewhat lower temperature of the building zones because of the greater building volume and lower fenestration ratio (ratio of external opening area to the area of the external walls). This result shows that the innovative building design adjusts to the local climate better than the standard conventional construction in Jos to maintain a suitable temperature within the building. This finding means that the air-conditioning electrical energy consumption per volume of the proposed building design will be lower than that of a conventional building design.

Keywords: building simulation, solar gain, comfort temperature, temperature, carbon foot print

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Authors: Manoj Malviya, Shubham Shinde

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The present study focuses on the determination of torsional stiffness of a space frame chassis and comparison of elements used in the Finite Element Analysis of frame. The study also discusses various concepts and design aspects of a space frame chassis with the emphasis on their applicability in BAJA SAE vehicles. Torsional stiffness is a very important factor that determines the chassis strength, vehicle control, and handling. Therefore, it is very important to determine the torsional stiffness of the vehicle before designing an optimum chassis so that it should not fail during extreme conditions. This study determines the torsional stiffness of frame with respect to suspension shocks, roll-stiffness and anti-roll bar rates. A spring model is developed to study the effects of suspension parameters. The engine greatly contributes to torsional stiffness, and therefore, its effects on torsional stiffness need to be considered. Deflections in the tire have not been considered in the present study. The proper element shape should be selected to analyze the effects of various loadings on chassis while implementing finite element methods. The study compares the accuracy of results and computational time for different element types. Shape functions of these elements are also discussed. Modelling methodology is discussed for the multibody analysis of chassis integrated with suspension arms and engine. Proper boundary conditions are presented so as to replicate the real life conditions.

Keywords: space frame chassis, torsional stiffness, multi-body analysis of chassis, element selection

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Authors: Qiyao Han, Xianhai Meng

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Urban infrastructures refer to the fundamental facilities and systems that serve cities. Due to the global climate change and human activities in recent years, many urban areas around the world are facing enormous challenges from natural and man-made disasters, like flood, earthquake and terrorist attack. For this reason, urban resilience to disasters has attracted increasing attention from researchers and practitioners. Given the complexity of infrastructure systems and the uncertainty of disasters, this paper suggests that studies of resilience could focus on urban functional sustainability (in social, economic and environmental dimensions) supported by infrastructure systems under disturbance. It is supposed that urban infrastructure systems with high resilience should be able to reconfigure themselves without significant declines in critical functions (services), such as primary productivity, hydrological cycles, social relations and economic prosperity. Despite that some methods have been developed to integrate the resilience and sustainability of individual infrastructure components, more work is needed to enable system-level integration. This research presents a conceptual analysis framework for integrating resilience and sustainability based on fractal theory. It is believed that the ability of an ecological system to maintain structure and function in face of disturbance and to reorganize following disturbance-driven change is largely dependent on its self-similar and hierarchical fractal structure, in which cross-scale resilience is produced by the replication of ecosystem processes dominating at different levels. Urban infrastructure systems are analogous to ecological systems because they are interconnected, complex and adaptive, are comprised of interconnected components, and exhibit characteristic scaling properties. Therefore, analyzing resilience of ecological system provides a better understanding about the dynamics and interactions of infrastructure systems. This paper discusses fractal characteristics of ecosystem resilience, reviews literature related to system-level infrastructure resilience, identifies resilience criteria associated with sustainability dimensions, and develops a conceptual analysis framework. Exploration of the relevance of identified criteria to fractal characteristics reveals that there is a great potential to analyze infrastructure systems based on fractal. In the conceptual analysis framework, it is proposed that in order to be resilient, urban infrastructure system needs to be capable of “maintaining” and “reorganizing” multi-scale critical functions under disasters. Finally, the paper identifies areas where further research efforts are needed.

Keywords: fractal, urban infrastructure, sustainability, system-level resilience

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Authors: Madhuka G. P. D. Udantha, Gihan V. Dias, Surangika Ranathunga

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Today Websites contain very interesting applications. But there are only few methodologies to analyze User navigations through the Websites and formulating if the Website is put to correct use. The web logs are only used if some major attack or malfunctioning occurs. Web Logs contain lot interesting dealings on users in the system. Analyzing web logs has become a challenge due to the huge log volume. Finding interesting patterns is not as easy as it is due to size, distribution and importance of minor details of each log. Web logs contain very important data of user and site which are not been put to good use. Retrieving interesting information from logs gives an idea of what the users need, group users according to their various needs and improve site to build an effective and efficient site. The model we built is able to detect attacks or malfunctioning of the system and anomaly detection. Logs will be more complex as volume of traffic and the size and complexity of web site grows. Unsupervised techniques are used in this solution which is fully automated. Expert knowledge is only used in validation. In our approach first clean and purify the logs to bring them to a common platform with a standard format and structure. After cleaning module web session builder is executed. It outputs two files, Web Sessions file and Indexed URLs file. The Indexed URLs file contains the list of URLs accessed and their indices. Web Sessions file lists down the indices of each web session. Then DBSCAN and EM Algorithms are used iteratively and recursively to get the best clustering results of the web sessions. Using homogeneity, completeness, V-measure, intra and inter cluster distance and silhouette coefficient as parameters these algorithms self-evaluate themselves to input better parametric values to run the algorithms. If a cluster is found to be too large then micro-clustering is used. Using Cluster Signature Module the clusters are annotated with a unique signature called finger-print. In this module each cluster is fed to Associative Rule Learning Module. If it outputs confidence and support as value 1 for an access sequence it would be a potential signature for the cluster. Then the access sequence occurrences are checked in other clusters. If it is found to be unique for the cluster considered then the cluster is annotated with the signature. These signatures are used in anomaly detection, prevent cyber attacks, real-time dashboards that visualize users, accessing web pages, predict actions of users and various other applications in Finance, University Websites, News and Media Websites etc.

Keywords: anomaly detection, clustering, pattern recognition, web sessions

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Authors: Christian Ihwiwhu, Nnamdi Obioha, Udeme John, Edward Bobade, Oghenerunor Bekibele, Adedeji Awujoola, Ibi-Ada Itotoi

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Understanding the complexity in the distribution of hydrocarbon in a simple structure with flow baffles and connectivity issues is critical in targeting and developing the remaining pay in a mature asset. Subtle facies changes (heterogeneity) can have a drastic impact on reservoir fluids movement, and this can be crucial to identifying sweet spots in mature fields. This study aims to evaluate selected reservoirs in Ovhor Field, Niger Delta, Nigeria, with the objective of optimising production from the field by targeting undeveloped oil reserves, bypassed pay, and gaining an improved understanding of the selected reservoirs to increase the company’s reservoir limits. The task at the Ovhor field is complicated by poor stratigraphic seismic resolution over the field. 3-D geological (sedimentology and stratigraphy) interpretation, use of results from quantitative interpretation, and proper understanding of production data have been used in recognizing flow baffles and undeveloped compartments in the field. The full field 3-D model has been constructed in such a way as to capture heterogeneities and the various compartments in the field to aid the proper simulation of fluid flow in the field for future production prediction, proper history matching and design of good trajectories to adequately target undeveloped oil in the field. Reservoir property models (porosity, permeability, and net-to-gross) have been constructed by biasing log interpreted properties to a defined environment of deposition model whose interpretation captures the heterogeneities expected in the studied reservoirs. At least, two scenarios have been modelled for most of the studied reservoirs to capture the range of uncertainties we are dealing with. The total original oil in-place volume for the four reservoirs studied is 157 MMstb. The cumulative oil and gas production from the selected reservoirs are 67.64 MMstb and 9.76 Bscf respectively, with current production rate of about 7035 bopd and 4.38 MMscf/d (as at 31/08/2019). Dynamic simulation and production forecast on the 4 reservoirs gave an undeveloped reserve of about 3.82 MMstb from two (2) identified oil restoration activities. These activities include side-tracking and re-perforation of existing wells. This integrated approach led to the identification of bypassed oil in some areas of the selected reservoirs and an improved understanding of the studied reservoirs. New wells have/are being drilled now to test the results of our studies, and the results are very confirmatory and satisfying.

Keywords: facies, flow baffle, bypassed pay, heterogeneities, history matching, reservoir limit

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Authors: Tengku Sepora Tengku Mahadi

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Where the speed of book writing lags behind the high need for such material for tertiary studies, translation offers a way to enhance the equilibrium in this demand-supply equation. Nevertheless, translation is confronted by obstacles that threaten its effectiveness. The primary challenge to the production of efficient translations may well be related to the text-type and in terms of its complexity. A text that is intricately written with unique rhetorical devices, subject-matter foundation and cultural references will undoubtedly challenge the translator. Longer time and greater effort would be the consequence. To understand these text-related challenges, the present paper set out to analyze a lawbook entitled Learning the Law by David Melinkoff. The book is chosen because it has often been used as a textbook or for reference in many law courses in the United Kingdom and has seen over thirteen editions; therefore, it can be said to be a worthy book for studies in law. Another reason is the existence of a ready translation in Malay. Reference to this translation enables confirmation to some extent of the potential problems that might occur in its translation. Understanding the organization and the language of the book will help translators to prepare themselves better for the task. They can anticipate the research and time that may be needed to produce an effective translation. Another premise here is that this text-type implies certain ways of writing and organization. Accordingly, it seems practicable to adopt the functional theory of language as suggested by Michael Halliday as its theoretical framework. Concepts of the context of culture, the context of situation and measures of the field, tenor and mode form the instruments for analysis. Additional examples from similar materials can also be used to validate the findings. Some interesting findings include the presence of several other text-types or sub-text-types in the book and the dependence on literary discourse and devices to capture the meanings better or add color to the dry field of law. In addition, many elements of culture can be seen, for example, the use of familiar alternatives, allusions, and even terminology and references that date back to various periods of time and languages. Also found are parts which discuss origins of words and terms that may be relevant to readers within the United Kingdom but make little sense to readers of the book in other languages. In conclusion, the textual analysis in terms of its functions and the linguistic and textual devices used to achieve them can then be applied as a guide to determine the effectiveness of the translation that is produced.

Keywords: functional theory of language, lawbook text-type, rhetorical devices, culture

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Authors: Yitian Ren, Liyin Shen, Tao Zhou, Xiao Li

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The past urbanization process in China has brought out series of problems, the Chinese government has then positioned small towns in essential roles for implementing the strategy 'The National New-type Urbanization Plan (2014-2020)'. As the connector and transfer station of cities and countryside, small towns are important force to narrow the gap between urban and rural area, and to achieve the mission of new-type urbanization in China. The sustainable development of small towns plays crucial role because cities are not capable enough to absorb the surplus rural population. Nevertheless, there are various types of barriers hindering the sustainable development of small towns, which led to the limited development of small towns and has presented a bottleneck in Chinese urbanization process. Therefore, this paper makes deep understanding of these barriers, thus effective actions can be taken to address them. And this paper chooses the perspective of Southwest China (refers to Sichuan province, Yunnan province, Guizhou province, Chongqing Municipality City and Tibet Autonomous Region), cause the urbanization rate in Southwest China is far behind the average urbanization level of the nation and the number of small towns accounts for a great proportion in mainland China, also the characteristics of small towns in Southwest China are distinct. This paper investigates the barriers of sustainable development of small towns which located in Southwest China by using the content analysis method, combing with the field work and interviews in sample small towns, then identified and concludes 18 barriers into four dimensions, namely, institutional barriers, economic barriers, social barriers and ecological barriers. Based on the research above, questionnaire survey and data analysis are implemented, thus the key barriers hinder the sustainable development of small towns in Southwest China are identified by using fuzzy set theory, those barriers are, lack of independent financial power, lack of construction land index, financial channels limitation, single industrial structure, topography variety and complexity, which mainly belongs to institutional barriers and economic barriers. In conclusion part, policy suggestions are come up with to improve the politic and institutional environment of small town development, also the market mechanism are supposed to be introduced to the development process of small towns, which can effectively overcome the economic barriers, promote the sustainable development of small towns, accelerate the in-situ urbanization by absorbing peasants in nearby villages, and achieve the mission of new-type urbanization in China from the perspective of people-oriented.

Keywords: barrier analysis, sustainable development, small town, Southwest China

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Authors: Kevin Molina, Daniel Ortega, Manuel Martinez, Andres Gonzalez-Estrada, William Pinto

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Due to the increasing environmental impact, the wind energy is getting strong. This research studied the relationship between the power produced by a horizontal axis wind turbine (HAWT) and the aerodynamic profiles used for its construction. The analysis is studied using the Computational Fluid Dynamic (CFD), presenting the parallel between the energy generated by a turbine designed with selected profiles and another one optimized. For the study, a selection process was carried out from profile NACA 6 digits recommended by the National Renewable Energy Laboratory (NREL) for the construction of this type of turbines. The selection was taken into account different characteristics of the wind (speed and density) and the profiles (aerodynamic coefficients Cl and Cd to different Reynolds and incidence angles). From the selected profiles, was carried out a sensitivity analysis optimization process between its geometry and the aerodynamic forces that are induced on it. The 3D model of the turbines was realized using the Blade Element Momentum method (BEM) and both profiles. The flow fields on the turbines were simulated, obtaining the forces induced on the blade, the torques produced and an increase of 3% in power due to the optimized profiles. Therefore, the results show that the sensitivity analysis optimization process can assist to increment the wind turbine power.

Keywords: blade element momentum, blade, fluid structure interaction, horizontal axis wind turbine, profile design

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Authors: Ahmed Negm, George Aggidis, Xiandong Ma

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With the diverse nature of urban cities, customer demand patterns, landscape topologies or even seasonal weather trends; managing our water distribution networks (WDNs) has proved a complex task. These unpredictable circumstances manifest as pipe failures, intermittent supply and burst events thus adding to water loss, energy waste and increased carbon emissions. Whilst these events are unavoidable, advanced pressure management has proved an effective tool to control and mitigate them. Henceforth, water utilities have struggled with developing a real-time control method that is resilient when confronting the challenges of water distribution. In this paper we use deep reinforcement learning (DRL) algorithms as a novel pressure control strategy to minimise pressure violations and leakage under both burst and background leakage conditions. Agents based on asynchronous actor critic (A2C) and recurrent proximal policy optimisation (Recurrent PPO) were trained and compared to benchmarked optimisation algorithms (differential evolution, particle swarm optimisation. A2C manages to minimise leakage by 32.48% under burst conditions and 67.17% under background conditions which was the highest performance in the DRL algorithms. A2C and Recurrent PPO performed well in comparison to the benchmarks with higher processing speed and lower computational effort.

Keywords: deep reinforcement learning, pressure management, water distribution networks, leakage management

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Authors: Zia Ullah, Muhammad Asim, Shi Sujuan, Rayyan Khan, Aaqib Shaheen, LIU Haobao

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The plant-specific auxin efflux proteins PIN-FORMED (PIN) have been well depicted in many plant species for their essential roles in regulating the transport of auxins in several phases of plant growth. Little is known about the various functions of the PIN family genes in the Nicotiana tabacum (N. tabacum) species during plant growth. To define the expression pattern of the NtPIN1a gene under abiotic stresses and hormone treatment, transgenic tobacco with promoterNtPIN1a::GUS construct was employed. Comprehensive computational analyses of the NtPIN1a promoter confirmed the existence of common core promoter elements including CAAT-box, TATA-box, hormone, and abiotic stress-responsive elements such as ABRE, P-box, MYC, MYB, ARE, and GC-motifs. The transgenic plants with the promoter of NtPIN1a displayed a promising expression of β-glucuronidase (GUS) in germinating seeds, root tips, shoot-apex, and developing leaves under optimal conditions. While the differential expression of GUS in moderate salt, drought, low potassium stresses, and externally high auxin level at two different time points, suggested NtPIN1a played a key role in growth processes and the plants’ response to abiotic stresses. This analysis provides a foundation for more in-depth discoveries of the biological functions of NtPIN1a in Nicotiana species and this promoter may be employed in genetic engineering of other crops for enhanced stress tolerance.

Keywords: tobacco, nicotiana tabacum, pin, promoter, GUS, abiotic stresses, auxin

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Authors: Chaitanya R. Mali, V. Vinod, Ashwin W. Patwardhan

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Design of long vertical steam generator (SG) tubes in nuclear power plant involves an understanding of different aspects of flow boiling phenomenon such as flow instabilities, flow regimes, dry out, critical heat flux, pressure drop, etc. The knowledge of the prediction of local thermal hydraulic characteristics is necessary to understand these aspects. For this purpose, the methodology has been developed which covers all the flow boiling regimes to model full range flow boiling phenomenon. In this methodology, the vertical tube is divided into four sections based on vapor fraction value at the end of each section. Different modeling strategies have been applied to the different sections of the vertical tube. Computational fluid dynamics simulations have been performed on a vertical SG tube of 0.0126 m inner diameter and 23 m length. The thermal hydraulic parameters such as vapor fraction, liquid temperature, heat transfer coefficient, pressure drop, heat flux distribution have been analyzed for different designed heat duties (1.1 MW (20%) to 3.3 MW (60%)) and flow conditions (10 % to 80 %). The sensitivity of different boiling parameters such as bubble departure diameter, nucleation site density, bubble departure frequency on the thermal hydraulic parameters was also studied. Flow instability has been observed at 20 % designed heat duty and 20 % flow conditions.

Keywords: thermal hydraulics, boiling, vapor fraction, sensitivity

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Authors: Dawei Cai, Yuya Tokuda

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The market of localization based service (LBS) is expanding. The acquisition of physical location is the fundamental basis for LBS. GPS, the de facto standard for outdoor localization, does not work well in indoor environment due to the blocking of signals by walls and ceiling. To acquire high accurate localization in an indoor environment, many techniques have been developed. Triangulation approach is often used for identifying the location, but a heavy and complex computation is necessary to calculate the location of the distances between the object and several source points. This computation is also time and power consumption, and not favorable to a mobile device that needs a long action life with battery. To provide a low power consumption approach for a mobile device, this paper presents a fast calculation approach to identify the location of the object without online solving solutions to simultaneous quadratic equations. In our approach, we divide the location identification into two parts, one is offline, and other is online. In offline mode, we make a mapping process that maps the location area to distance space and find a simple formula that can be used to identify the location of the object online with very light computation. The characteristic of the approach is a good tradeoff between the accuracy and computational amount. Therefore, this approach can be used in smartphone and other mobile devices that need a long work time. To show the performance, some simulation experimental results are provided also in the paper.

Keywords: indoor localization, location based service, triangulation, fast calculation, mobile device

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Authors: Yuan Wan, Shumei Cui, Shaopeng Wu

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Toroidal windings were taken advantage of to reduce of axial length of the motor, so as to match the applications that have severe restrictions on the axial length. But slotting in the out edge of the stator will decrease the heat-dissipation capacity of the water cooling of the housing. Besides, the windings in the outer slots will increase the copper loss, which will further increase the difficult for heat dissipation of the motor. At present, carbon-fiber composite retaining sleeve are increasingly used to be mounted over the magnets to ensure the rotor strength at high speeds. Due to the poor thermal conductivity of carbon-fiber sleeve, the cooling of the rotor becomes very difficult, which may result in the irreversible demagnetization of magnets for the excessively high temperature. So it is necessary to analyze the temperature rise of such motor. This paper builds a computational fluid dynamic (CFD) model of a toroidal-winding high-speed permanent magnet synchronous motor (PMSM) with water cooling of housing and forced air cooling of rotor. Thermal analysis was carried out based on the model and the factors that affects the temperature rise were investigated. Then thermal optimization for the prototype was achieved. Finally, a small-size prototype was manufactured and the thermal analysis results were verified.

Keywords: thermal analysis, temperature rise, toroidal windings, high-speed PMSM, CFD

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Authors: Mokhtar Djeddou, Amine Mehel, Georges Fokoua, Anne Tanière, Patrick Chevrier

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Commuters' exposure to air pollution, particularly to particle matter, inside vehicles is a significant health issue. Assessing particles concentrations and characterizing their distribution is an important first step to understand and propose solutions to improve car cabin air quality. It is known that particles dynamics is intimately driven by particles-turbulence interactions. In order to analyze and model pollutants distribution inside the car the cabin, it is crucialto examine first the single-phase flow topology and turbulence characteristics. Within this context, Computational Fluid Dynamics (CFD) simulations were conducted to model airflow inside a full-scale car cabin using Reynolds Averaged Navier-Stokes (RANS)approach combined with the first order Realizable k- εmodel to close the RANS equations. To validate the numerical model, a campaign of velocity field measurements at different locations in the front and back of the car cabin has been carried out using hot-wire anemometry technique. Comparison between numerical and experimental results shows a good agreement of velocity profiles. Additionally, visualization of streamlines shows the formation of jet flow developing out of the dashboard air vents and the formation of large vortex structures, particularly in the back seats compartment. These vortex structures could play a key role in the accumulation and clustering of particles in a turbulent flow

Keywords: car cabin, CFD, hot wire anemometry, vortical flow

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Authors: P. Vindin, R. Cordier, N. J. Wilson, H. Lee

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Engagement in community-based activities such as education, employment, and social relationships can improve the quality of life for individuals with Autism Spectrum Disorder (ASD). Community mobility is vital to attaining independence for individuals with ASD. Learning to drive and gaining a driver’s license is a critical link to community mobility; however, for individuals with ASD acquiring safe driving skills can be a challenging process. Issues related to anxiety, executive function, and social communication may affect driving behaviours. Driving training and education aimed at addressing barriers faced by learner drivers with ASD can help them improve their driving performance. A multi-site randomized controlled trial (RCT) was conducted to evaluate the effectiveness of an autism-specific driving training intervention for improving the on-road driving performance of learner drivers with ASD. The intervention was delivered via a training manual and interactive website consisting of five modules covering varying driving environments starting with a focus on off-road preparations and progressing through basic to complex driving skill mastery. Seventy-two learner drivers with ASD aged 16 to 35 were randomized using a blinded group allocation procedure into either the intervention or control group. The intervention group received 10 driving lessons with the instructors trained in the use of an autism-specific driving training protocol, whereas the control group received 10 driving lessons as usual. Learner drivers completed a pre- and post-observation drive using a standardized driving route to measure driving performance using the Driving Performance Checklist (DPC). They also completed anxiety, executive function, and social responsiveness measures. The findings showed that there were significant improvements in driving performance for both the intervention (d = 1.02) and the control group (d = 1.15). However, the differences were not significant between groups (p = 0.614) or study sites (p = 0.842). None of the potential moderator variables (anxiety, cognition, social responsiveness, and driving instructor experience) influenced driving performance. This study is an important step toward improving community mobility for individuals with ASD showing that an autism-specific driving training intervention can improve the driving performance of leaner drivers with ASD. It also highlighted the complexity of conducting a multi-site design even when sites were matched according to geography and traffic conditions. Driving instructors also need more and clearer information on how to communicate with learner drivers with restricted verbal expression.

Keywords: autism spectrum disorder, community mobility, driving training, transportation

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Authors: Yuri Boiko, Ci Lin, Iluju Kiringa, Tet Yeap

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The performance of a BLDC motor controlled by the Kalman filter-based position-sensorless drive is studied in terms of its dependence on the system’s parameters' variations. The effects of system’s parameters changes on the dynamic behavior of state variables are verified. Simulated is a closed-loop control scheme with a Kalman filter in the feedback line. Distinguished are two separate data sampling modes in analyzing feedback output from the BLDC motor: (1) equal angular separation and (2) equal time intervals. In case (1), the data are collected via equal intervals Δθ of rotor’s angular position θᵢ, i.e., keeping Δθ=const. In case (2), the data collection time points tᵢ are separated by equal sampling time intervals Δt=const. Demonstrated are the effects of the parameters changes on the sensorless control flow, in particular, reduction of the torque ripples, switching spikes, torque load balancing. It is specifically shown that an efficient suppression of commutation induced torque ripples is achievable selection of the sampling rate in the Kalman filter settings above certain critical value. The computational cost of such suppression is shown to be higher for the motors with lower induction values of the windings.

Keywords: BLDC motor, Kalman filter, sensorless drive, state variables, torque ripples reduction, sampling rate

Procedia PDF Downloads 124

Authors: Jing Nan

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The air breakdown voltage in compact circuit breakers is a critical factor in the design and reliability of electrical distribution systems. This voltage determines the threshold at which the air insulation between conductors will fail or 'break down,' leading to an arc. This phenomenon is highly sensitive to the conditions within the breaker, such as the temperature and the distance between electrodes. Typically, air breakdown voltage models have been reliable for predicting failure under standard operational temperatures. However, in conditions post-arcing, where temperatures can soar above 2000K, these models face challenges due to the complex physics of ionization and electron behaviour at such high-energy states. Building upon the foundational understanding that the breakdown mechanism is initiated by free electrons and propelled by electric fields, which lead to ionization and, potentially, to avalanche or streamer formation, we acknowledge the complexity introduced by high-temperature environments. Recognizing the limitations of existing experimental data, a notable research gap exists in the accurate prediction of breakdown voltage at elevated temperatures, typically observed post-arcing, where temperatures exceed 2000K.To bridge this knowledge gap, we present a method that integrates gap distance and high-temperature effects into air breakdown voltage assessment. The proposed model is grounded in the physics of ionization, accounting for the dynamic behaviour of free electrons which, under intense electric fields at elevated temperatures, lead to thermal ionization and potentially reach the threshold for streamer formation as Meek's criterion. Employing the Saha equation, our model calculates equilibrium electron densities, adapting to the atmospheric pressure and the hot temperature regions indicative of post-arc temperature conditions. Our model is rigorously validated against established experimental data, demonstrating substantial improvements in predicting air breakdown voltage in the high-temperature regime. This work significantly improves the predictive power for air breakdown voltage under conditions that closely mimic operational stressors in compact circuit breakers. Looking ahead, the proposed methods are poised for further exploration in alternative insulating media, like SF6, enhancing the model's utility for a broader range of insulation technologies and contributing to the future of high-temperature electrical insulation research.

Keywords: air breakdown voltage, high-temperature insulation, compact circuit breakers, electrical discharge, saha equation

Procedia PDF Downloads 53

Authors: Akinbo Razak Yinka, Adesanya Kehinde Kazeem, Oladokun Oluwagbenga Peter

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Time series data are sequences of observations collected over a period of time. Such data can be used to predict health outcomes, such as disease progression, mortality, hospitalization, etc. The Statistical approach is based on mathematical models that capture the patterns and trends of the data, such as autocorrelation, seasonality, and noise, while Neural methods are based on artificial neural networks, which are computational models that mimic the structure and function of biological neurons. This paper compared both parametric and non-parametric time series models of patients treated for malaria in Maternal and Child Health Centres in Lagos State, Nigeria. The forecast methods considered linear regression, Integrated Moving Average, ARIMA and SARIMA Modeling for the parametric approach, while Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) Network were used for the non-parametric model. The performance of each method is evaluated using the Mean Absolute Error (MAE), R-squared (R2) and Root Mean Square Error (RMSE) as criteria to determine the accuracy of each model. The study revealed that the best performance in terms of error was found in MLP, followed by the LSTM and ARIMA models. In addition, the Bootstrap Aggregating technique was used to make robust forecasts when there are uncertainties in the data.

Keywords: ARIMA, bootstrap aggregation, MLP, LSTM, SARIMA, time-series analysis

Procedia PDF Downloads 41

Authors: Soroush Pakniyat-Jahromi, Jessica Bucciarelli, Souparno Mitra, Neda Motamedi, Ralph Amazan, Samuel Rothman, Jose Tiburcio, Douglas Reich, Vicente Liz

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Violence is defined as an act of physical force that is intended to cause harm and may lead to physical and/or psychological damage. Violence toward healthcare workers (HCWs) is more common in psychiatric settings, emergency departments, and nursing homes; however, healthcare workers in medical setting are not spared from such events. Workplace violence has a huge burden in the healthcare industry and has a major impact on the physical and mental wellbeing of staff. The purpose of this study is to compare the prevalence of patient agitation and violence in medical-surgical settings in BronxCare Hospital (BCH) Bronx, New York, one year before and during the COVID-19 pandemic. Data collection occurred between June 2021 and August 2021, while the sampling time was from 2019 to 2021. The data were separated into two separate time categories: pre-COVID-19 (03/2019-03/2020) and COVID-19 (03/2020-03/2021). We created frequency tables for 19 variables. We used a chi-square test to determine a variable's statistical significance. We tested all variables against “restraint type”, determining if a patient was violent or became violent enough to restrain. The restraint types were “chemical”, “physical”, or both. This analysis was also used to determine if there was a statistical difference between the pre-COVID-19 and COVID-19 timeframes. Our data shows that there was an increase in incidents of violence in COVID-19 era (03/2020-03/2021), with total of 194 (62.8%) reported events, compared to pre COVID-19 era (03/2019-03/2020) with 115 (37.2%) events (p: 0.01). Our final analysis, completed using a chi-square test, determined the difference in violence in patients between pre-COVID-19 and COVID-19 era. We then tested the violence marker against restraint type. The result was statistically significant (p: 0.01). This is the first paper to systematically review the prevalence of violence in medical-surgical units in a hospital in New York, pre COVID-19 and during the COVID-19 era. Our data is in line with the global trend of increased prevalence of patient agitation and violence in medical settings during the COVID-19 pandemic. Violence and its management is a challenge in healthcare settings, and the COVID-19 pandemic has brought to bear a complexity of circumstances, which may have increased its incidence. It is important to identify and teach healthcare workers the best preventive approaches in dealing with patient agitation, to decrease the number of restraints in medical settings, and to create a less restrictive environment to deliver care.

Keywords: COVID-19 pandemic, patient agitation, restraints, violence

Procedia PDF Downloads 112

Authors: K. K. Lee, H. W. Han, H. L. Kang, T. A. Kim, S. H. Han

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For the robust optimization of the manufacturing product design, there are design objectives that must be achieved, such as a minimization of the mean and standard deviation in objective functions within the required sensitivity constraints. The authors utilized the sensitivity of objective functions and constraints with respect to the effective design variables to reduce the computational burden associated with the evaluation of the probabilities. The individual mean and sensitivity values could be estimated easily by using the 9 level orthogonal array based response surface models optimized by the stepwise regression. The present study evaluates a proposed procedure from the robust optimization of rubber domes that are commonly used for keyboard switching, by using the 9 level orthogonal array and stepwise regression along with a desirability function. In addition, a new robust optimization process, i.e., the I2GEO (Identify, Integrate, Generate, Explore and Optimize), was proposed on the basis of the robust optimization in rubber domes. The optimized results from the response surface models and the estimated results by using the finite element analysis were consistent within a small margin of error. The standard deviation of objective function is decreasing 54.17% with suggested sensitivity based robust optimization. (Business for Cooperative R&D between Industry, Academy, and Research Institute funded Korea Small and Medium Business Administration in 2017, S2455569)

Keywords: objective function, orthogonal array, response surface model, robust optimization, stepwise regression

Procedia PDF Downloads 262

Authors: Shankha Pratim Bhattacharya

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In general building repair and renovation projects are minor in nature. It requires less attention as the primary cost involvement is relatively small. Although the building repair and maintenance projects look simple, it involves much complexity during execution. Many of the present research indicate that few uncertain situations are usually linked with maintenance projects. Those may not be read properly in the planning stage of the projects, and finally, lead to time overrun. Building repair and maintenance become essential and periodical after commissioning of the building. In Institutional buildings, the regular maintenance projects also include addition –alteration, modification activities. Increase in the student admission, new departments, and sections, new laboratories and workshops, up gradation of existing laboratories are very common in the institutional buildings in the developing nations like India. The project becomes very critical because it undergoes space problem, architectural design issues, structural modification, etc. One of the prime factors in the institutional building maintenance and modification project is the time constraint. Mostly it required being executed a specific non-work time period. The present research considered only the institutional buildings of the Eastern part of India to analyse the repair and maintenance project delay. A general survey was conducted among the technical institutes to find the causes and corresponding nature of construction delay factors. Five technical institutes are considered in the present study with repair, renovation, modification and extension type of projects. Construction delay factors are categorically subdivided into four groups namely, material, manpower (works), Contract and Site. The survey data are collected for the nature of delay responsible for a specific project and the absolute amount of delay through proposed and actual duration of work. In the first stage of the paper, a relative importance index (RII) is proposed for the delay factors. The occurrence of the delay factors is also judged by its frequency-severity nature. Finally, the delay factors are then rated and linked with the type of work. In the second stage, a regression analysis is executed to establish an empirical relationship between the actual time of a project and the percentage of delay. It also indicates the impact of the factors for delay responsibility. Ultimately, the present paper makes an effort to identify the critical delay factors for the repair and renovation type project in the Eastern Indian Institutional building.

Keywords: delay factor, institutional building, maintenance, relative importance index, regression analysis, repair

Procedia PDF Downloads 231

Authors: Iyad Jadalhaq, Mohammed El Hadi El Maknouzi

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The place of Islamic law in the legal system of the UAE is best understood by introducing a differentiation between its role as a formal source of law and its influence as a material source of law. What this differentiation helps clarify is that the corpus of Islamic law constitutes a much deeper influence on adjudication, law-making and the legal profession in the UAE, than it might appear at first sight, by considering its formal position in the division of labor between courts, or legislative lists of sources of law. This paper aims to examine the role of Shariah in the UAE private law system by determining the comprehensiveness of Sharia in the legal system as a whole, and not in a limited way related to it as a source of law according to Article 1 of the Civil Transactions Law. Turning to the role of the Shariah as a formal source of law, it is useful to start from Article 1 of the UAE Civil Code. This provision lays out the formal hierarchy of sources of UAE private law, these being legislation, Islamic law, and custom. Hence, when deciding a civil dispute, a judge should first refer to positive legislation in force in the UAE. Lacking the rule to cover the case before him/her, the judge ought then to refer directly to Islamic law. If the matter lacks regulation in Islamic law, only then may the judge appeal to custom. Accordingly, in connection to civil transactions, Shariah is presented here, formally, as the second source of law. Still, Shariah law addresses many other issues beyond civil transactions, including matters of morals, worship, and belief. However, in Article 1 of the UAE Civil Code, the reference to Islamic law ought to be understood as limited to the rules it lays out for civil transactions. There are four main sets of courts in the judicial systems of the UAE, whose competence is based on whether a dispute touches upon civil and commercial transactions, criminal offenses, personal statuses, or labor relations. This sectorial and multi-tiered organization of courts as a whole constitutes an institutional development compatible with the long-standing affirmation in the Shariah of the legitimacy of the judiciary. Indeed, Islamic law authorizes the governing authorities to organize the judiciary, including by allocating specific types of cases to particular kinds of judges depending on the value of the case, or by assigning judges to a specific place in which they are to exercise their jurisdictional function. In view of this, the contemporary organization of courts in the UAE can be regarded as an organic adaptation, aligned with Shariah rules on the assignment of jurisdictional authority, to the growing complexity of modern society. Therefore, we can conclude to the comprehensive role of Shariah in the entire legal system of the United Arab Emirates, including legislation, a judicial system, institutional, and administrative work.

Keywords: Islamic jurisprudence, Shariah, UAE civil code, UAE private law

Procedia PDF Downloads 99

Authors: Balram Panjwani, Bernd Wittgens, Jan Erik Olsen, Stein Tore Johansen

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The Norwegian ferroalloy industry is a world leader in sustainable production of ferrosilicon, silicon and manganese alloys with the lowest global specific energy consumption. One of the byproducts during the metal reduction process is energy rich off-gas and usually this energy is not harnessed. A novel concept for sustainable energy recovery from ferroalloy off-gas is discussed. The concept is founded on the idea of introducing a combustion chamber in the off-gas section in which energy rich off-gas mainly consisting of CO will be combusted. This will provide an additional degree of freedom for optimizing energy recovery. A well-controlled and high off-gas temperature will assure a significant increase in energy recovery and reduction of emissions to the atmosphere. Design and operation of the combustion chamber depend on many parameters, including the total power capacity of the combustion chamber, sufficient residence time for combusting the complex Poly Aromatic Hydrocarbon (PAH), NOx, as well as converting other potential pollutants. The design criteria for the combustion chamber have been identified and discussed and sizing of the combustion chamber has been carried out considering these design criteria. Computational Fluid Dynamics (CFD) has been utilized extensively for sizing the combustion chamber. The results from our CFD simulations of the flow in the combustion chamber and exploring different off-gas fuel composition are presented. In brief, the paper covers all aspect which impacts the sizing of the combustion chamber, including insulation thickness, choice of insulating material, heat transfer through extended surfaces, multi-staging and secondary air injection.

Keywords: CFD, combustion chamber, arc furnace, energy recovery

Procedia PDF Downloads 297