Search results for: interpretive structural modeling (ISM)

Authors: Cody Stolle, Mojdeh Asadollahipajouh, Khaleb Pafford, Jada Iwuoha, Samantha White, Becky Mueller

Abstract:

Battery-electric vehicles (BEVs) are growing in sales and popularity in the United States as an alternative to traditional internal combustion engine vehicles (ICEVs). BEVs are generally heavier than corresponding models of ICEVs, with large battery packs located beneath the vehicle floorpan, a “skateboard” chassis, and have front and rear crush space available in the trunk and “frunk” or front trunk. The geometrical and frame differences between the vehicles may lead to incompatibilities with gasoline vehicles during vehicle-to-vehicle crashes as well as run-off-road crashes with roadside barriers, which were designed to handle lighter ICEVs with higher centers-of-mass and with dedicated structural chasses. Crash data were collected from 10 states spanning a five-year period between 2017 and 2021. Vehicle Identification Number (VIN) codes were processed with the National Highway Traffic Safety Administration (NHTSA) VIN decoder to extract BEV models from ICEV models. Crashes were filtered to isolate only vehicles produced between 2010 and 2021, and the crash circumstances (weather, time of day, maximum injury) were compared between BEVs and ICEVs. In Washington, 436,613 crashes were identified, which satisfied the selection criteria, and 3,371 of these crashes (0.77%) involved a BEV. The number of crashes which noted a fire were comparable between BEVs and ICEVs of similar model years (0.3% and 0.33%, respectively), and no differences were discernable for the time of day, weather conditions, road geometry, or other prevailing factors (e.g., run-off-road). However, crashes involving BEVs rose rapidly; 31% of all BEV crashes occurred in just 2021. Results indicate that BEVs are performing comparably to ICEVs, and events surrounding BEV crashes are statistically indistinguishable from ICEV crashes.

Keywords: battery-electric vehicles, transportation safety, infrastructure crashworthiness, run-off-road crashes, ev crash data analysis

Procedia PDF Downloads 89

Authors: Younes El Khchine, Mohammed Sriti

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A parametric study has been conducted to analyse the flow around S809 airfoil of wind turbine in order to better understand the characteristics and effects of laminar separation bubble (LSB) on aerodynamic design for maximizing wind turbine efficiency. Numerical simulations were performed at low Reynolds number by solving the Unsteady Reynolds Averaged Navier-Stokes (URANS) equations based on C-type structural mesh and using γ-Reθt turbulence model. Two-dimensional study was conducted for the chord Reynolds number of 1×105 and angles of attack (AoA) between 0 and 20.15 degrees. The simulation results obtained for the aerodynamic coefficients at various angles of attack (AoA) were compared with XFoil results. A sensitivity study was performed to examine the effects of Reynolds number and free-stream turbulence intensity on the location and length of laminar separation bubble and aerodynamic performances of wind turbine. The results show that increasing the Reynolds number leads to a delay in the laminar separation on the upper surface of the airfoil. The increase in Reynolds number leads to an accelerate transition process and the turbulent reattachment point move closer to the leading edge owing to an earlier reattachment of the turbulent shear layer. This leads to a considerable reduction in the length of the separation bubble as the Reynolds number is increased. The increase of the level of free-stream turbulence intensity leads to a decrease in separation bubble length and an increase the lift coefficient while having negligible effects on the stall angle. When the AoA increased, the bubble on the suction airfoil surface was found to moves upstream to leading edge of the airfoil that causes earlier laminar separation.

Keywords: laminar separation bubble, turbulence intensity, S809 airfoil, transition model, Reynolds number

Procedia PDF Downloads 87

Authors: Omotoyosi Bilikies Ilori, Adekunle Saheed Ajisebiyawo

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After the Second World War, there was an emergence of a new stage of capitalist globalization with its Neo-liberal ideology. There were global economic and political restructurings that affected third-world countries like Nigeria. Neo-liberalism is the driving force of globalization, which is the latest manifestation of imperialism that engenders endemic poverty in Nigeria. Poverty is severe and widespread in Nigeria. Poverty entails a situation where a person lives on less than one dollar per day and has no access to basic necessities of life. Poverty is inhuman and a breach of human rights. The Nigerian government initiated some strategies in the past to help in poverty reduction. Neo-liberalism manifested in the Third World, such as Nigeria, through the privatization of public enterprises, trade liberalization, and the rollback of the state investments in providing important social services. These main ideas of Neo-liberalism produced poverty in Nigeria and also encouraged the abandonment of the social contract between the government and the people. There is thus a gap in the provision of social services and subsidies for the masses, all of which Neo-liberal ideological positions contradict. This paper is a qualitative study which draws data from secondary sources. The theoretical framework is anchored on the market theory of capitalist globalization and public choice theory. The objectives of this study are to (i) examine the impacts of Neo-liberalism on poverty in Nigeria as a typical example of a Third World country and (ii) find out the effects of Neo-liberalism on the provision of social services and subsidies and employment. The findings from this study revealed that (i) the adoption of the Neo-liberal ideology by the Nigerian government has led to increased poverty and poor provision of social services and employment in Nigeria; and (ii) there is an increase in foreign debts which compounds poverty situation in Nigeria. This study makes the following recommendations: (i) Government should adopt strategies that are pro-poor to eradicate poverty; (ii) The Trade Unions and the masses should develop strategies to challenge Neo-liberalism and reject Neo-liberal ideology.

Keywords: neo-liberalism, poverty, employment, poverty reduction, structural adjustment programme

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Authors: Madhura Bandyopadhyay

Abstract:

Teaching writing within multicultural and multiethnic communities poses many unique challenges not the least of which is that of intercultural communication. When the writing is in English, pedagogical imperatives often encounter the universalizing tendencies of standardization of both language use and structural parameters which are often at odds with maintaining local practices which preserve cultural pluralism. English often becomes the contact zone within which individual identities of students play out against the standardization imperatives of the larger world. Writing classes can serve as places which become instruments of assimilation of ethnic minorities to a larger globalizing or nationalistic agenda. Hence, for those outside of the standard practices of writing English, adaptability towards a mastery of those practices valued as standard become the focus of teaching taking away from diversity of local English use and other modes of critical thinking. In a very multicultural and multiethnic context such as the US or Singapore, these dynamics become very important. This paper will argue that multiethnic writing classrooms can greatly benefit from taking up a cultural studies approach whereby the students’ lived environments and experiences are analyzed as cultural texts to produce writing. Such an approach eliminates limitations of using both literary texts as foci of discussion as in traditional approaches to teaching writing and the current trend in teaching composition without using texts at all. By bringing in students’ lived experiences into the classroom and analyzing them as cultural compositions stressing the ability to communicate across cultures, cultural competency is valued rather than adaptability while privileging pluralistic experiences as valuable even as universal shared experience are found. Specifically, while teaching writing in English in a multicultural classroom, a cultural studies approach makes both teacher and student aware of the diversity of the English language as it exists in our global context in the students’ experience while making space for diversity in critical thinking, structure and organization of writing effective in an intercultural context.

Keywords: English, multicultural, teaching, writing

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Authors: Vahid Ramezankhani, Keith J. Stevenson, Stanislav. S. Fedotov

Abstract:

Lithium-ion batteries (LIBs) play a pivotal role in achieving the key objective “zero-carbon emission” as countries agreed to reach a 1.5ᵒC global warming target according to the Paris agreement. Nowadays, due to the tremendous mobile and stationary consumption of small/large-format LIBs, the demand and consequently the price for such energy storage devices have been raised. The aforementioned challenges originate from the shrinkage of the major applied critical materials in these batteries, such as cobalt (Co), nickel (Ni), Lithium (Li), graphite (G), and manganese (Mn). Therefore, it is imperative to consider alternative elements to address issues corresponding to the limitation of resources around the globe. Potassium (K) is considered an effective alternative to Li since K is a more abundant element, has a higher operating potential, a faster diffusion rate, and the lowest stokes radius in comparison to the closest neighbors in the periodic table (Li and Na). Among all reported materials for metal-ion batteries, some of them possess the general formula AMXO4L [A = Li, Na, K; M = Fe, Ti, V; X = P, S, Si; L= O, F, OH] is of potential to be applied both as anode and cathode and enable researchers to investigate them in the full symmetric battery format. KTiPO4F (KTP structural material) has been previously reported by our group as a promising cathode with decent electronic properties. Herein, we report a synthesis, crystal structure characterization, morphology, as well as K-ion storage properties of KTiPO4F. Our investigation reveals that KTiPO4F delivers discharge capacity > 150 mAh/g at 26.6 mA/g (C/5 current rate) in the potential window of 0.001-3 V. Surprisingly, the cycling performance of C-KTiPO4F//K cell is stable for 1000 cycles at 130 mA/g (C current rate), presenting capacity > 130 mAh/g. More interestingly, we achieved to assemble full symmetric batteries where carbon-coated KTiPO4F serves as both negative and positive electrodes, delivering >70 mAh/g in the potential range of 0.001-4.2V.

Keywords: anode material, potassium battery, chemical characterization, electrochemical properties

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Authors: Juan José Mesas, Luis Sainz

Abstract:

The motivation for the development of this paper lies in the need for energy networks to reduce losses, improve performance, optimize their operation and try to benefit from the interconnection capacity with other networks enabled for other energy carriers. These interconnections generate interdependencies between some energy networks and others, which requires suitable models and methods for their analysis. Traditionally, the modeling and study of energy networks have been carried out independently for each energy carrier. Thus, there are well-established models and methods for the steady-state analysis of electrical networks, gas networks, and thermal networks separately. What is intended is to extend and combine them adequately to be able to face in an integrated way the steady-state analysis of networks with multiple energy carriers. Firstly, the added value of multi-energy networks, their operation, and the basic principles that characterize them are explained. In addition, two current aspects of great relevance are exposed: the storage technologies and the coupling elements used to interconnect one energy network with another. Secondly, the characteristic equations of the different energy networks necessary to carry out the steady-state analysis are detailed. The electrical network, the natural gas network, and the thermal network of heat and cold are considered in this paper. After the presentation of the equations, a particular case of the steady-state analysis of a specific multi-energy network is studied. This network is represented graphically, the interconnections between the different energy carriers are described, their technical data are exposed and the equations that have previously been presented theoretically are formulated and developed. Finally, the two iterative numerical resolution methods considered in this paper are presented, as well as the resolution procedure and the results obtained. The pros and cons of the application of both methods are explained. It is verified that the results obtained for the electrical network (voltages in modulus and angle), the natural gas network (pressures), and the thermal network (mass flows and temperatures) are correct since they comply with the distribution, operation, consumption and technical characteristics of the multi-energy network under study.

Keywords: coupling elements, energy carriers, multi-energy networks, steady-state analysis

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Authors: F. Pottmeyer, M. Weispfenning, K. A. Weidenmann

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Continuous carbon fiber reinforced plastics (CFRP) exhibit a high application potential for lightweight structures due to their outstanding specific mechanical properties. Embedded metal elements, so-called inserts, can be used to join structural CFRP parts. Drilling of the components to be joined can be avoided using inserts. In consequence, no bearing stress is anticipated. This is a distinctive benefit of embedded inserts, since continuous CFRP have low shear and bearing strength. This paper aims at the investigation of the load bearing capacity after preinduced damages from impact tests and thermal-cycling. In addition, characterization of mechanical properties during dynamic high speed pull-out testing under different loading velocities was conducted. It has been shown that the load bearing capacity increases up to 100% for very high velocities (15 m/s) in comparison with quasi-static loading conditions (1.5 mm/min). Residual strength measurements identified the influence of thermal loading and preinduced mechanical damage. For both, the residual strength was evaluated afterwards by quasi-static pull-out tests. Taking into account the DIN EN 6038 a high decrease of force occurs at impact energy of 16 J with significant damage of the laminate. Lower impact energies of 6 J, 9 J, and 12 J do not decrease the measured residual strength, although the laminate is visibly damaged - distinguished by cracks on the rear side. To evaluate the influence of thermal loading, the specimens were placed in a climate chamber and were exposed to various numbers of temperature cycles. One cycle took 1.5 hours from -40 °C to +80 °C. It could be shown that already 10 temperature cycles decrease the load bearing capacity up to 20%. Further reduction of the residual strength with increasing number of thermal cycles was not observed. Thus, it implies that the maximum damage of the composite is already induced after 10 temperature cycles.

Keywords: composite, joining, inserts, dynamic loading, thermal loading, residual strength, impact

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Authors: Sherif D. El Wakil, John Rice

Abstract:

The aim of the current work was to employ the finite element method to model a slab, with a small hole across its width, undergoing plastic plane strain deformation. The computational model had, however, to be validated by comparing its results with those obtained experimentally. Since they were in good agreement, the finite element method can therefore be considered a reliable tool that can help gain better understanding of the mechanism of ductile failure in structural members having stress raisers. The finite element software used was ANSYS, and the PLANE183 element was utilized. It is a higher order 2-D, 8-node or 6-node element with quadratic displacement behavior. A bilinear stress-strain relationship was used to define the material properties, with constants similar to those of the material used in the experimental study. The model was run for several tensile loads in order to observe the progression of the plastic deformation region, and the stress concentration factor was determined in each case. The experimental study involved employing the visioplasticity technique, where a circular mesh (each circle was 0.5 mm in diameter, with 0.05 mm line thickness) was initially printed on the side of an aluminum slab having a small hole across its width. Tensile loading was then applied to produce a small increment of plastic deformation. Circles in the plastic region became ellipses, where the directions of the principal strains and stresses coincided with the major and minor axes of the ellipses. Next, we were able to determine the directions of the maximum and minimum shear stresses at the center of each ellipse, and the slip-line field was then constructed. We were then able to determine the stress at any point in the plastic deformation zone, and hence the stress concentration factor. The experimental results were found to be in good agreement with the analytical ones.

Keywords: finite element method to model a slab, slab undergoing plastic deformation, stress distribution around a circular hole, visioplasticity

Procedia PDF Downloads 320

Authors: Adel A. Ghobbar

Abstract:

The airline industry is continuously challenging how to safely increase the service life of the aircraft with limited maintenance budgets. Operators are looking for the most qualified maintenance providers of aircraft components, offering the finest customer service. Component owner and maintenance provider is offering an Abacus agreement (Aircraft Component Leasing) to increase the efficiency and productivity of the customer service. To increase the customer service, the current focus on No Fault Found (NFF) units must change into the focus on Early Failure (EF) units. Since the effect of EF units has a significant impact on customer satisfaction, this needs to increase the reliability of EF units at minimal cost, which leads to the goal of this paper. By identifying the reliability of early failure (EF) units with regards to No Fault Found (NFF) units, in particular, the root cause analysis with an integrated cost analysis of EF units with the use of a failure mode analysis tool and a cost model, there will be a set of EF maintenance improvements. The data used for the investigation of the EF units will be obtained from the Pentagon system, an Enterprise Resource Planning (ERP) system used by Fokker Services. The Pentagon system monitors components, which needs to be repaired from Fokker aircraft owners, Abacus exchange pool, and commercial customers. The data will be selected on several criteria’s: time span, failure rate, and cost driver. When the selected data has been acquired, the failure mode and root cause analysis of EF units are initiated. The failure analysis approach tool was implemented, resulting in the proposed failure solution of EF. This will lead to specific EF maintenance improvements, which can be set-up to decrease the EF units and, as a result of this, increasing the reliability. The investigated EFs, between the time period over ten years, showed to have a significant reliability impact of 32% on the total of 23339 unscheduled failures. Since the EFs encloses almost one-third of the entire population.

Keywords: supportability, no fault found, FMEA, early failure, availability, operational reliability, predictive model

Procedia PDF Downloads 129

Authors: Sherif Fayez Lewis Ghaly

Abstract:

up to datefacupupdated planning has the mission of designing merchandise, plant life, procedures, enterprise, regions, and the development of a up to date. The requirements for up-to-date planning and the constructing of a updated have changed in recent years. everyday restructuring is turning inupupdated greater essential up-to-date hold the competitiveness of a manufacturing facilityupdated. restrictions in new regions, shorter existence cycles of product and manufacturing generation up-to-date a VUCA global (Volatility, Uncertainty, Complexity & Ambiguity) up-to-date greater frequent restructuring measures inside a manufacturing facilityupdated. A virtual up-to-date model is the making plans basis for rebuilding measures and up-to-date an fundamental up-to-date. short-time period rescheduling can now not be handled through on-web site inspections and manual measurements. The tight time schedules require 3177227fc5dac36e3e5ae6cd5820dcaa making plans fashions. updated the high variation fee of facup-to-dateries defined above, a method for rescheduling facupdatedries on the idea of a modern-day digital up to datery dual is conceived and designed for sensible software in updated restructuring projects. the point of interest is on rebuild approaches. The purpose is up-to-date preserve the planning basis (virtual up-to-date model) for conversions within a up to datefacupupdated updated. This calls for the application of a methodology that reduces the deficits of present techniques. The goal is up-to-date how a digital up to datery version may be up to date up to date during ongoing up to date operation. a method up-to-date on phoup to dategrammetry technology is presented. the focus is on developing a easy and fee-powerful up to date tune the numerous adjustments that arise in a manufacturing unit constructing in the course of operation. The method is preceded with the aid of a hardware and software assessment up-to-date become aware of the most cost effective and quickest version.

Keywords: building information modeling, digital factory model, factory planning, maintenance digital factory model, photogrammetry, restructuring

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Authors: Raheleh Farzanmanesh, Christopher J. Weston

Abstract:

Mangroves are forest ecosystems located in the inter-tidal regions of tropical and subtropical coastlines that provide many valuable economic and ecological benefits for millions of people, such as preventing coastal erosion, providing breeding, and feeding grounds, improving water quality, and supporting the well-being of local communities. In addition, mangroves capture and store high amounts of carbon in biomass and soils that play an important role in combating climate change. The decline in mangrove area has prompted government and private sector interest in mangrove conservation and restoration projects to achieve multiple Sustainable Development Goals, from reducing poverty to improving life on land. Mangrove aboveground biomass plays an essential role in the global carbon cycle, climate change mitigation and adaptation by reducing CO2 emissions. However, little information is available about the effectiveness of mangrove sustainable management on mangrove change area and aboveground biomass (AGB). Here, we proposed a method for mapping, modeling, and assessing mangrove area and AGB in two Global Environment Facility (GEF) blue forests projects based on Sentinel-2 Level 1C imagery during their conservation lifetime. The SVR regression model was used to estimate AGB in Tahiry Honko project in Madagascar and the Abu Dhabi Blue Carbon Demonstration Project (Abu Dhabi Emirates. The results showed that mangrove forests and AGB declined in the Tahiry Honko project, while in the Abu Dhabi project increased after the conservation initiative was established. The results provide important information on the impact of mangrove conservation activities and contribute to the development of remote sensing applications for mapping and assessing mangrove forests in blue carbon initiatives.

Keywords: blue carbon, mangrove forest, REDD+, aboveground biomass, Sentinel-2

Procedia PDF Downloads 74

Authors: Yatimah Alias, Tilagam Marimuthu, M. R. Mahmoudian, Sharifah Mohamad

Abstract:

The rapid growth of science and technology in energy and environmental fields has enlightened the substantial importance of the conducting polymer and metal composite materials engineered at nano-scale. In this study, polypyrrole-cobalt composites (PPy-Co Cs) and polypyrrole-nickel oxide composites (PPy-NiO Cs) were prepared by a simple and facile chemical polymerization method with an aqueous solution of pyrrole monomer in the presence of metal salt. These composites then fabricated into non-enzymatic hydrogen peroxide (H2O2) and glucose sensor. The morphology and composition of the composites are characterized by the Field Emission Scanning Electron Microscope, Fourier Transform Infrared Spectrum and X-ray Powder Diffraction. The obtained results were compared with the pure PPy and metal oxide particles. The structural and morphology properties of synthesized composites are different from those of pure PPy and metal oxide particles, which were attributed to the strong interaction between the PPy and the metal particles. Besides, a favorable micro-environment for the electrochemical oxidation of H2O2 and glucose was achieved on the modified glassy carbon electrode (GCE) coated with PPy-Co Cs and PPy-NiO Cs respectively, resulting in an enhanced amperometric response. Both PPy-Co/GCE and PPy-NiO/GCE give high response towards target analyte at optimum condition of 500 μl pyrrole monomer content. Furthermore, the presence of pyrrole monomer greatly increases the sensitivity of the respective modified electrode. The PPy-Co/GCE could detect H2O2 in a linear range of 20 μM to 80 mM with two linear segments (low and high concentration of H2O2) and the detection limit for both ranges is 2.05 μM and 19.64 μM, respectively. Besides, PPy-NiO/GCE exhibited good electrocatalytic behavior towards glucose oxidation in alkaline medium and could detect glucose in linear ranges of 0.01 mM to 0.50 mM and 1 mM to 20 mM with detection limit of 0.33 and 5.77 μM, respectively. The ease of modifying and the long-term stability of this sensor have made it superior to enzymatic sensors, which must kept in a critical environment.

Keywords: metal oxide, composite, non-enzymatic sensor, polypyrrole

Procedia PDF Downloads 267

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 130

Authors: Keunhong Chae, Seokho Yoon

Abstract:

Recently, the global navigation satellite system (GNSS) such as Galileo and GPS is employing more satellites to provide a higher degree of accuracy for the location service, thus calling for a more efficient signaling scheme among the satellites used in the overall GNSS network. In that the network throughput is improved, the spatial diversity can be one of the efficient signaling schemes; however, it requires multiple antenna that could cause a significant increase in the complexity of the GNSS. Thus, a diversity scheme called the cooperative signaling was proposed, where the virtual multiple-input multiple-output (MIMO) signaling is realized with using only a single antenna in the transmit satellite of interest and with modeling the neighboring satellites as relay nodes. The main drawback of the cooperative signaling is that the relay nodes receive the transmitted signal at different time instants, i.e., they operate in an asynchronous way, and thus, the overall performance of the GNSS network could degrade severely. To tackle the problem, several modified cooperative signaling schemes were proposed; however, all of them are difficult to implement due to a signal decoding at the relay nodes. Although the implementation at the relay nodes could be simpler to some degree by employing the time-reversal and conjugation operations instead of the signal decoding, it would be more efficient if we could implement the operations of the relay nodes at the source node having more resources than the relay nodes. So, in this paper, we propose a novel cooperative signaling scheme, where the data signals are combined in a unique way at the source node, thus obviating the need of the complex operations such as signal decoding, time-reversal and conjugation at the relay nodes. The numerical results confirm that the proposed scheme provides the same performance in the cooperative diversity and the bit error rate (BER) as the conventional scheme, while reducing the complexity at the relay nodes significantly. Acknowledgment: This work was supported by the National GNSS Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.

Keywords: global navigation satellite network, cooperative signaling, data combining, nodes

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Authors: T. Jayanthi, K. Velusamy, H. Seetha, S. A. V. Satya Murty

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Verification and Validation of Simulated Process Model is the most important phase of the simulator life cycle. Evaluation of simulated process models based on Verification and Validation techniques checks the closeness of each component model (in a simulated network) with the real system/process with respect to dynamic behaviour under steady state and transient conditions. The process of Verification and validation helps in qualifying the process simulator for the intended purpose whether it is for providing comprehensive training or design verification. In general, model verification is carried out by comparison of simulated component characteristics with the original requirement to ensure that each step in the model development process completely incorporates all the design requirements. Validation testing is performed by comparing the simulated process parameters to the actual plant process parameters either in standalone mode or integrated mode. A Full Scope Replica Operator Training Simulator for PFBR - Prototype Fast Breeder Reactor has been developed at IGCAR, Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder Reactor Simulator) wherein the main participants are engineers/experts belonging to Modeling Team, Process Design and Instrumentation and Control design team. This paper discusses the Verification and Validation process in general, the evaluation procedure adopted for PFBR operator training Simulator, the methodology followed for verifying the models, the reference documents and standards used etc. It details out the importance of internal validation by design experts, subsequent validation by external agency consisting of experts from various fields, model improvement by tuning based on expert’s comments, final qualification of the simulator for the intended purpose and the difficulties faced while co-coordinating various activities.

Keywords: Verification and Validation (V&V), Prototype Fast Breeder Reactor (PFBR), Kalpakkam Breeder Reactor Simulator (KALBR-SIM), steady state, transient state

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Authors: Daisy Biswas, Samar Kanti Bose, M. Mozaffar Hossain

Abstract:

The development of value added composite products from bamboo with the application of gluing technology can play a vital role in economic development and also in forest resource conservation of any country. In this study, the gluability of Bambusa balcooa and Bambusa vulgaris, two locally grown bamboo species of Bangladesh was assessed. As the culm wall thickness of bamboos decreases from bottom to top, a culm portion of up to 5.4 m and 3.6 m were used from the base of B. balcooa and B. vulgaris, respectively, to get rectangular strips of uniform thickness. The color of the B. vulgaris strips was yellowish brown and that of B. balcooa was reddish brown. The strips were treated in borax-boric, bleaching and carbonization for extending the service life of the laminates. The preservative treatments changed the color of the strips. Borax–boric acid treated strips were reddish brown. When bleached with hydrogen peroxide, the color of the strips turned into whitish yellow. Carbonization produced dark brownish strips having coffee flavor. Chemical constituents for untreated and treated strips were determined. B. vulgaris was more acidic than B. balcooa. Then the treated strips were used to develop three-layered bamboo laminated panel. Urea formaldehyde (UF) and polyvinyl acetate (PVA) were used as binder. The shear strength and abrasive resistance of the panel were evaluated. It was found that the shear strength of the UF-panel was higher than the PVA-panel for all treatments. Between the species, gluability of B. vulgaris was better and in some cases better than hardwood species. The abrasive resistance of B. balcooa is slightly higher than B. vulgaris; however, the latter was preferred as it showed well gluability. The panels could be used as structural panel, floor tiles, flat pack furniture component, and wall panel etc. However, further research on durability and creep behavior of the product in service condition is warranted.

Keywords: Bambusa balcooa, Bambusa vulgaris, polyvinyl acetate, urea formaldehyde

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Authors: Rachel P. Vasconcellos

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The Russian constructivism is usually enshrined in history as another ''modernist ism'', that is, as an artistic phenomenon related to the early twentieth century‘s zeitgeist. What we aim in this essay is to analyze the constructivist movement not over the Art History field neither through the aesthetic debate, but through a geographical critical theory, taking the main idea of construction in the concrete sense of production of space. Seen from the perspective of the critique of space, the constructivist production is presented as a plan of totality, designed as socialist society‘s spatiality, contemplating and articulating all its scalar levels: the objects of everyday life, the building, the city and the territory. The constructivist avant-garde manifests a geographical ideology, launching the foundation‘s basis of modern planning ideology. Taken in its political sense, the artistic avant-garde of the Russian Revolution intended to anticipate the forms of a social future already put in progress: their plastic research pointed to new formal expressions to revolutionary contents. With the foundation of new institutions under a new State, it was given to the specialized labor of artists, architects, and planners the task of designing the socialist society, based on the thesis of scientific socialism. Their projects were developed under the politico-economics imperatives to the Soviet modernization – that is: the structural needs of industrialization and inclusion of all people in the productive work universe. This context shapes the creative atmosphere of the constructivist avant-garde, which uses the methods of engineering to the transform everyday life. Architecture, urban planning, and state planning integrated must then operate as spatial arrangement morphologically able to produce socialist life. But due to the intrinsic contradictions of the process, the rational and geometric aesthetic of the City-Machine appears, finally, as an image of a scientific socialist utopia.

Keywords: city-machine, critique of space, production of space, soviet territorialization

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Authors: Kurias George, Ildefonso Cuesta Romeo, Clara Salueña Pérez, Jordi Sole Olle

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With the growing prevalence of wind energy there is a need, for modeling techniques to evaluate the impact of wind farms on meteorology and oceanography. This study presents an approach that utilizes the WRF (Weather Research and Forecasting )with that include a Wind Farm Parametrization model to simulate the dynamics around Parc Tramuntana project, a offshore wind farm to be located near the Gulf of Roses off the coast of Barcelona, Catalonia. The model incorporates parameterizations for wind turbines enabling a representation of the wind field and how it interacts with the infrastructure of the wind farm. Current results demonstrate that the model effectively captures variations in temeperature, pressure and in both wind speed and direction over time along with their resulting effects on power output from the wind farm. These findings are crucial for optimizing turbine placement and operation thus improving efficiency and sustainability of the wind farm. In addition to focusing on atmospheric interactions, this study delves into the wake effects within the turbines in the farm. A range of meteorological parameters were also considered to offer a comprehensive understanding of the farm's microclimate. The model was tested under different horizontal resolutions and farm layouts to scrutinize the wind farm's effects more closely. These experimental configurations allow for a nuanced understanding of how turbine wakes interact with each other and with the broader atmospheric and oceanic conditions. This modified approach serves as a potent tool for stakeholders in renewable energy, environmental protection, and marine spatial planning. environmental protection and marine spatial planning. It provides a range of information regarding the environmental and socio economic impacts of offshore wind energy projects.

Keywords: weather research and forecasting, wind turbine wake effects, environmental impact, wind farm parametrization, sustainability analysis

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Authors: Marta Błażkiewicz, Adam Konefał

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Currently, boron-neutron therapy is carried out mainly with the use of a neutron beam generated in research nuclear reactors. This fact limits the possibility of realization of a BNCT in centers distant from the above-mentioned reactors. Moreover, the number of active nuclear reactors in operation in the world is decreasing due to the limited lifetime of their operation and the lack of new installations. Therefore, the possibilities of carrying out boron-neutron therapy based on the neutron beam from the experimental reactor are shrinking. However, the use of nuclear power reactors for BNCT purposes is impossible due to the infrastructure not intended for radiotherapy. Therefore, a serious challenge is to find ways to perform boron-neutron therapy based on neutrons generated outside the research nuclear reactor. This work meets this challenge. Its goal is to develop a BNCT technique based on commonly available neutron sources such as Cf-252 and PuBe, which will enable the above-mentioned therapy in medical centers unrelated to nuclear research reactors. Advances in the field of neutron source fabrication make it possible to achieve strong neutron fluxes. The current stage of research focuses on the development of virtual models of the above-mentioned sources using the Monte Carlo simulation method. In this study, the GEANT4 tool was used, including the model for simulating neutron-matter interactions - High Precision Neutron. Models of neutron sources were developed on the basis of experimental verification based on the activation detectors method with the use of indium foil and the cadmium differentiation method allowing to separate the indium activation contribution from thermal and resonance neutrons. Due to the large number of factors affecting the result of the verification experiment, the 10% discrepancy between the simulation and experiment results was accepted.

Keywords: BNCT, virtual models, neutron sources, monte carlo, GEANT4, neutron activation detectors, gamma spectroscopy

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Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Oriol Gomis Bellmunt, Vinicius Albernaz Lacerda Freitas

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The use of distributed and renewable sources in power systems has grown significantly, recently. One the most popular sources are wind farms which have grown massively. However, ¬wind farms are connected to the grid, this can cause problems such as reduced voltage stability, frequency fluctuations and reduced dynamic stability. Variable speed generators (asynchronous) are used due to the uncontrollability of wind speed specially Doubley Fed Induction Generators (DFIG). The most important disadvantage of DFIGs is its sensitivity to voltage drop. In the case of faults, a large volume of reactive power is induced therefore, use of FACTS devices such as SVC and STATCOM are suitable for improving system output performance. They increase the capacity of lines and also passes network fault conditions. In this paper, in addition to modeling the reactive power control system in a DFIG with converter, FACTS devices have been used in a DFIG wind turbine to improve the stability of the power system containing two synchronous sources. In the following paper, recent optimal control systems have been designed to minimize fluctuations caused by system disturbances, for FACTS devices employed. For this purpose, a suitable method for the selection of nine parameters for MPSH-phase-post-phase compensators of reactive power compensators is proposed. The design algorithm is formulated ¬¬as an optimization problem searching for optimal parameters in the controller. Simulation results show that the proposed controller Improves the stability of the network and the fluctuations are at desired speed.

Keywords: renewable energy sources, optimization wind power plant, stability, reactive power compensator, double-feed induction generator, optimal control, genetic algorithm

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Authors: Federica Floridi

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The long tradition of contrastive idiom research has essentially been focusing on three domains: the comparison of structural types of idioms (e.g. verbal idioms, idioms with noun-phrase structure, etc.), the description of idioms belonging to the same thematic groups (Sachgruppen), the identification of different types of cross-linguistic equivalents (i.e. full equivalents, partial equivalents, phraseological parallels, non-equivalents). The diastratic, diachronic and diatopic aspects of the compared idioms, as well as their syntactic, pragmatic and semantic properties, have been rather ignored. Corpora (both monolingual and parallel) give the opportunity to investigate the actual use of correlating idioms in authentic texts of L1 and L2. Adopting the corpus-based approach, it is possible to draw attention to the frequency of occurrence of idioms, their syntactic embedding, their potential syntactic transformations (e.g., nominalization, passivization, relativization, etc.), their combinatorial possibilities, the variations of their lexical structure, their connotations in terms of stylistic markedness or register. This paper aims to present the results of a contrastive analysis of Russian and Italian idioms referring to the concepts of ‘beginning’ and ‘end’, that has been carried out by using the Russian National Corpus and the ‘La Repubblica’ corpus. Beyond the digital corpora, bilingual dictionaries, like Skvorcova - Majzel’, Dobrovol’skaja, Kovalev, Čerdanceva, as well as monolingual resources, have been consulted. The study has shown that many of the idioms that have been traditionally indicated as cross-linguistic equivalents on bilingual dictionaries cannot be considered correspondents. The findings demonstrate that even those idioms, that are formally identical in Russian and Italian and are presumably derived from the same source (e.g., conceptual metaphor, Bible, classical mythology, World literature), exhibit differences regarding usage. The ultimate purpose of this article is to highlight that it is necessary to review and improve the existing bilingual dictionaries considering the empirical data collected in corpora. The materials gathered in this research can contribute to this sense.

Keywords: corpora, cross-linguistic equivalence, idioms, Italian, Russian

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Authors: Scott Nielsen, Luca Longanesi, Chris Chuck

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Palm oil is obtained from the flesh and kernel of the fruit of oil palms and is the most productive and inexpensive oil crop. The global demand for palm oil is approximately 75 million metric tonnes, a 29% increase in global production of palm oil since 2016. This expansion of oil palm cultivation has resulted in mass deforestation, vast biodiversity destruction and increasing net greenhouse gas emissions. One possible alternative is to produce a saturated oil, similar to palm, from microbes such as oleaginous yeast. The yeasts can be cultured on sugars derived from second-generation sources and do not compete with tropical forests for land. One highly promising oleaginous yeast for this application is Metschnikowia pulcherrima. However, recent techno-economic modeling has shown that cell lysis and standard lipid extraction are major contributors to the cost of the oil. Typical cell disruption techniques to extract either single cell oils or proteins have been based around bead-beating, homogenization and acid lysis. However, these can have a detrimental effect on lipid quality and are energy-intensive. In this study, a vortex separator, which produces high sheer with minimal energy input, was investigated as a potential low energy method of lysing cells. This was compared to four more traditional methods (thermal lysis, acid lysis, alkaline lysis, and osmotic lysis). For each method, the yeast loading was also examined at 1 g/L, 10 g/L and 100 g/L. The quality of the cell disruption was measured by optical cell density, cell counting and the particle size distribution profile comparison over a 2-hour period. This study demonstrates that the vortex separator is highly effective at lysing the cells and could potentially be used as a simple apparatus for lipid recovery in an oleaginous yeast process. The further development of this technology could potentially reduce the overall cost of microbial lipids in the future.

Keywords: palm oil substitute, metschnikowia pulcherrima, cell disruption, cell lysis

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Authors: Shereif. H. Mahmoud

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Egypt has limited water resources, and it will be under water stress by the year 2030. Therefore, Egypt should consider natural and non-conventional water resources to overcome such a problem. Rain harvesting is one solution. This Paper presents a geographic information system (GIS) methodology - based on decision support system (DSS) that uses remote sensing data, filed survey, and GIS to identify potential RWH areas. The input into the DSS includes a map of rainfall surplus, slope, potential runoff coefficient (PRC), land cover/use, soil texture. In addition, the outputs are map showing potential sites for RWH. Identifying suitable RWH sites implemented in the ArcGIS model environment using the model builder of ArcGIS 10.1. Based on Analytical hierarchy process (AHP) analysis taking into account five layers, the spatial extents of RWH suitability areas identified using Multi-Criteria Evaluation (MCE). The suitability model generated a suitability map for RWH with four suitability classes, i.e. Excellent, Moderate, Poor, and unsuitable. The spatial distribution of the suitability map showed that the excellent suitable areas for RWH concentrated in the northern part of Egypt. According to their averages, 3.24% of the total area have excellent and good suitability for RWH, while 45.04 % and 51.48 % of the total area are moderate and unsuitable suitability, respectively. The majority of the areas with excellent suitability have slopes between 2 and 8% and with an intensively cultivated area. The major soil type in the excellent suitable area is loam and the rainfall range from 100 up to 200 mm. Validation of the used technique depends on comparing existing RWH structures locations with the generated suitability map using proximity analysis tool of ArcGIS 10.1. The result shows that most of exiting RWH structures categorized as successful.

Keywords: rainwater harvesting (RWH), geographic information system (GIS), analytical hierarchy process (AHP), multi-criteria evaluation (MCE), decision support system (DSS)

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

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Authors: Jamal Alqinai

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A pragmatic approach to translation studies the rules and principles governing the use of language over and above the rules of syntax or morphology, and what makes some uses of language more appropriate than others in [communicative] situations. It attempts to explain translation as a procedure and product from the point of view of how, why and what is done by the source text author (ST) and what is to be done in the target text (TT) rendition. The latter will be subject to evaluation not as generated by the linguistics system but as conveyed and manipulated by participants in a communicative situation according to the referential and pragmatic standards employed. The failure of a purely lexical or structural translation stems from ignoring the relation between words as signs and the effect they have on their users. A more refined approach would also consider those processes that are sometimes labeled extra-linguistic or intuitive and which translators strive to reproduce unscathed in the translation process. We need to grasp the kind of actions an ST author performs on his readers by combining linguistic and non-linguistic elements against a backdrop of beliefs and cultural values. In other words, aside from considering the cohesive ties at the textual level, one needs to understand how the whole ST discourse hangs together logically in order to reproduce a coherent TT. The latter can only be achieved by an analysis of the pragmatic elements of presuppositions, implicatures and acts performed in the ST. Establishing cohesive ties within a text may require seeking reference outside the immediate text. The illocutionary functions manifested in one language/culture are relatively autonomous cultural/linguistic categories, but are imaginable by members of other cultures and, to some extent , are translatable though not, of course, without translation loss. Globalization and the spread of literacy worldwide may have created a universal empathy to comprehend the performative aspect of utterances when explained by approximate glosses or by paraphrase. Yet, it is often the multilayered and the culture-specific nature of illocutionary functions that de-universalize their possible interpretations. This paper addresses the pragmatic interpretation of culturally specific texts with examples adduced from a number of distinct settings to illustrate the influence of the pragmatic factors at stake.

Keywords: pragmatic, presupposition, implicature, cohesion

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Authors: Gyozo Molnar, Nancy Spencer-Cavaliere

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Research in the area of physical activity and sport, while becoming multidisciplinary, is still dominated by post-positivist approaches that have the tendency to position the researcher as an expert and the participant as subordinate thereby perpetuating an unequal balance of power. Despite physical activity’s and sport’s universal appeal, their historic practices have excluded particular groups of people who assumed lesser forms of human capital. Adapted physical activity (APA) is a field that has responded to those segregations with specific application and relevance to people with impairments. Nevertheless, to date, similar to physical activity and sport, research in APA is still dominated by post-positivist epistemology. Stemming from this, there is gradually growing criticism within the field related to the abundance of research ‘on’ people with impairments and lack of research ‘with’ and ‘by’ people with impairments. Furthermore, research questions in the field are most often pursued from a single axis of analysis and constructed by non-disabled researchers. Concurrently, while calls for interdisciplinary approaches to understanding disability are growing in popularity, there is also a clear need to take an intersectionality-informed research methodology to understanding physical activity and sport and power (im)balances therein. In other words, impairment needs to be considered in conjunction with other socially and politically constructed and historically embedded differences such as gender, race, class, etc. when analyzing physical activity and sport experiences for people with impairments. Moreover, it is reasonable to argue that non-disabled researchers must recognize and theorize ableism in its complicated intersectional manifestation to show the structural constraints that disabled scholars face in the field. Consequently, this presentation will offer an alternative approach that acknowledges and prioritizes the perspectives and experiences of people with impairments to expand the field of APA. As such, the importance of broadening epistemologies in APA and prioritizing an appreciation for multiple bits of knowledge of people with impairments through intersections of social locations (e.g., gender, race, class) will be considered.

Keywords: adapted physical activity, disability, intersectionality, post-positivist, power imbalances

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Authors: Ahmad AlAbdullah, Ali AlQallaf, Mahdi Hussain, Mohammed AlAttar, Salman Ashknani, Magdy Helal

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We study the effectiveness of the parking service provided at Kuwaiti commercial malls and explore potential problems and feasible improvements. Commercial malls are important to Kuwaitis as the entertainment and shopping centers due to the lack of other alternatives. The difficulty and relatively long times wasted in finding a parking spot at the mall are real annoyances. We applied queuing analysis to one of the major malls that offer paid-parking (1040 parking spots) in addition to free parking. Patrons of the mall usually complained of the traffic jams and delays at entering the paid parking (average delay to park exceeds 15 min for about 62% of the patrons, while average time spent in the mall is about 2.6 hours). However, the analysis showed acceptable service levels at the check-in gates of the parking garage. Detailed review of the vehicle movement at the gateways indicated that arriving and departing cars both had to share parts of the gateway to the garage, which caused the traffic jams and delays. A simple comparison we made indicated that the largest commercial mall in Kuwait does not suffer such parking issues, while other smaller, yet important malls do, including the one we studied. It was suggested that well-designed inlets and outlets of that gigantic mall permitted smooth parking despite being totally free and mall is the first choice for most people for entertainment and shopping. A simulation model is being developed for further analysis and verification. Simulation can overcome the mathematical difficulty in using non-Poisson queuing models. The simulation model is used to explore potential changes to the parking garage entrance layout. And with the inclusion of the drivers’ behavior inside the parking, effectiveness indicators can be derived to address the economic feasibility of extending the parking capacity and increasing service levels. Outcomes of the study are planned to be generalized as appropriate to other commercial malls in Kuwait

Keywords: commercial malls, parking service, queuing analysis, simulation modeling

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Authors: M. Varin, A. M. Dubois, R. Gadbois-Langevin, B. Chalghaf

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Good knowledge of the physical environment is essential for an integrated forest planning. This information enables better forecasting of operating costs, determination of cutting volumes, and preservation of ecologically sensitive areas. The use of satellite images in stereoscopic pairs gives the capacity to generate high precision 3D models, which are scale-adapted for harvesting operations. These models could represent an alternative to 3D LiDAR data, thanks to their advantageous cost of acquisition. The objective of the study was to assess the quality of stereo-derived canopy height models (CHM) in comparison to a traditional LiDAR CHM and ground tree-height samples. Two study sites harboring two different forest stand types (broadleaf and conifer) were analyzed using stereo pairs and tri-stereo images from the WorldView-3 satellite to calculate CHM. Acquisition of multispectral images from an Unmanned Aerial Vehicle (UAV) was also realized on a smaller part of the broadleaf study site. Different algorithms using two softwares (PCI Geomatica and Correlator3D) with various spatial resolutions and band selections were tested to select the 3D modeling technique, which offered the best performance when compared with LiDAR. In the conifer study site, the CHM produced with Corelator3D using only the 50-cm resolution panchromatic band was the one with the smallest Root-mean-square deviation (RMSE: 1.31 m). In the broadleaf study site, the tri-stereo model provided slightly better performance, with an RMSE of 1.2 m. The tri-stereo model was also compared to the UAV, which resulted in an RMSE of 1.3 m. At individual tree level, when ground samples were compared to satellite, lidar, and UAV CHM, RMSE were 2.8, 2.0, and 2.0 m, respectively. Advanced analysis was done for all of these cases, and it has been noted that RMSE is reduced when the canopy cover is higher when shadow and slopes are lower and when clouds are distant from the analyzed site.

Keywords: very high spatial resolution, satellite imagery, WorlView-3, canopy height models, CHM, LiDAR, unmanned aerial vehicle, UAV

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Authors: Boris Blostotsky, Elia Efraim

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The phenomenon of buckling of structural elements under compression is revealed in many cases of loading and found consideration in many structures and mechanisms. In the present work the method and results of dynamic test for buckling of bar loaded by a compression force directed towards the pole are considered. Experimental determination of critical force for such system has not been made previously. The tested object is a bar with semi-rigid connection to the base at one of its ends, and with a hinge moving along a circle at the other. The test includes measuring the natural frequency of the bar at different values of compression load. The lateral stiffness is calculated based on natural frequency and reduced mass on the bar's movable end. The critical load is determined by extrapolation the values of lateral stiffness up to zero value. For the experimental investigation the special test-bed was created that allows the stability testing at positive and negative curvature of the movable end's trajectory, as well as varying the rotational stiffness of the other end connection. Decreasing a friction at the movable end allows extend the diapason of applied compression force. The testing method includes: - Methodology of the experiment planning, that allows determine the required number of tests under various loads values in the defined range and the type of extrapolating function; - Methodology of experimental determination of reduced mass at the bar's movable end including its own mass; - Methodology of experimental determination of lateral stiffness of uncompressed bar rotational semi-rigid connection at the base. For planning the experiment and for comparison of the experimental results with the theoretical values of critical load, the analytical dependencies of lateral stiffness of the bar with defined end conditions on compression load. In the particular case of perfectly rigid connection of the bar to the base, the critical load value corresponds to solution by S.P. Timoshenko. Correspondence of the calculated and experimental values was obtained.

Keywords: non-destructive test, buckling, dynamic method, semi-rigid connections

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Authors: Adel Francis

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Most of scheduling methods and software apply the critical path logic. This logic schedule activities, apply constraints between these activities and try to optimize and level the allocated resources. The extensive use of this logic produces a complex an erroneous network hard to present, follow and update. Planning and management building projects should tackle the coordination of works and the management of limited spaces, traffic, and supplies. Activities cannot be performed without the resources available and resources cannot be used beyond the capacity of workplaces. Otherwise, workspace congestion will negatively affect the flow of works. The objective of the space planning is to link the spatial and temporal aspects, promote efficient use of the site, define optimal site occupancy rates, and ensures suitable rotation of the workforce in the different spaces. The Chronographic scheduling modelling belongs to this category and models construction operations as well as their processes, logical constraints, association and organizational models, which help to better illustrate the schedule information using multiple flexible approaches. The model defined three categories of areas (punctual, surface and linear) and four different layers (space creation, systems, closing off space, finishing, and reduction of space). The Chronographical modelling is a more complete communication method, having the ability to alternate from one visual approach to another by manipulation of graphics via a set of parameters and their associated values. Each individual approach can help to schedule a certain project type or specialty. Visual communication can also be improved through layering, sheeting, juxtaposition, alterations, and permutations, allowing for groupings, hierarchies, and classification of project information. In this way, graphic representation becomes a living, transformable image, showing valuable information in a clear and comprehensible manner, simplifying the site management while simultaneously utilizing the visual space as efficiently as possible.

Keywords: building projects, chronographic modelling, CPM, critical path, precedence diagram, scheduling

Procedia PDF Downloads 155