Search results for: optimization and environmental impacts

Authors: Javad Jozaei, Rob G. Bell, Paula Blackett, Scott A. Stephens

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In the last few decades, Social Vulnerability Assessment (SVA) has been a favoured means in evaluating the susceptibility of social systems to drivers of change, including climate change and natural disasters. However, the application of SVA to inform responsive and practical strategies to deal with uncertain climate change impacts has always been challenging, and typically agencies resort back to conventional risk/vulnerability assessment. These challenges include complex nature of social vulnerability concepts which influence its applicability, complications in identifying and measuring social vulnerability determinants, the transitory social dynamics in a changing environment, and unpredictability of the scenarios of change that impacts the regime of vulnerability (including contention of when these impacts might emerge). Research suggests that the conventional quantitative approaches in SVA could not appropriately address these problems; hence, the outcomes could potentially be misleading and not fit for addressing the ongoing uncertain rise in risk. The second phase of New Zealand’s Resilience to Nature’s Challenges (RNC2) is developing a forward-looking vulnerability assessment framework and methodology that informs the decision-making and policy development in dealing with the changing coastal systems and accounts for complex dynamics of New Zealand’s coastal systems (including socio-economic, environmental and cultural). Also, RNC2 requires the new methodology to consider plausible drivers of incremental and unknowable changes, create mechanisms to enhance social and community resilience; and fits the New Zealand’s multi-layer governance system. This paper aims to analyse the conventional approaches and methodologies in SVA and offer recommendations for more responsive approaches that inform adaptive decision-making and policy development in practice. The research adopts a qualitative research design to examine different aspects of the conventional SVA processes, and the methods to achieve the research objectives include a systematic review of the literature and case study methods. We found that the conventional quantitative, reductionist and deterministic mindset in the SVA processes -with a focus the impacts of rapid stressors (i.e. tsunamis, floods)- show some deficiencies to account for complex dynamics of social-ecological systems (SES), and the uncertain, long-term impacts of incremental drivers. The paper will focus on addressing the links between resilience and vulnerability; and suggests how resilience theory and its underpinning notions such as the adaptive cycle, panarchy, and system transformability could address these issues, therefore, influence the perception of vulnerability regime and its assessment processes. In this regard, it will be argued that how a shift of paradigm from ‘specific resilience’, which focuses on adaptive capacity associated with the notion of ‘bouncing back’, to ‘general resilience’, which accounts for system transformability, regime shift, ‘bouncing forward’, can deliver more effective strategies in an era characterised by ongoing change and deep uncertainty.

Keywords: complexity, social vulnerability, resilience, transformation, uncertain risks

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Authors: Rama Debbarma

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The present study deals with the performance of Linear base isolation system to mitigate seismic response of structures characterized by random system parameters. This involves optimization of the tuning ratio and damping properties of the base isolation system considering uncertain system parameters. However, the efficiency of base isolator may reduce if it is not tuned to the vibrating mode it is designed to suppress due to unavoidable presence of system parameters uncertainty. With the aid of matrix perturbation theory and first order Taylor series expansion, the total probability concept is used to evaluate the unconditional response of the primary structures considering random system parameters. For this, the conditional second order information of the response quantities are obtained in random vibration framework using state space formulation. Subsequently, the maximum unconditional root mean square displacement of the primary structures is used as the objective function to obtain optimum damping parameters Numerical study is performed to elucidate the effect of parameters uncertainties on the optimization of parameters of linear base isolator and system performance.

Keywords: linear base isolator, earthquake, optimization, uncertain parameters

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Authors: Abdullah Ali H. Ahmadini, Firoz Ahmad, Intekhab Alam

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Geometric programming problem (GPP) is a well-known non-linear optimization problem having a wide range of applications in many engineering problems. The structure of GPP is quite dynamic and easily fit to the various decision-making processes. The aim of this paper is to highlight the bounded solution method for GPP with special reference to variation among right-hand side parameters. Thus this paper is taken the advantage of two-level mathematical programming problems and determines the solution of the objective function in a specified interval called lower and upper bounds. The beauty of the proposed bounded solution method is that it does not require sensitivity analyses of the obtained optimal solution. The value of the objective function is directly calculated under varying parameters. To show the validity and applicability of the proposed method, a numerical example is presented. The system reliability optimization problem is also illustrated and found that the value of the objective function lies between the range of lower and upper bounds, respectively. At last, conclusions and future research are depicted based on the discussed work.

Keywords: varying parameters, geometric programming problem, bounded solution method, system reliability optimization

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Authors: Bagher Bayat, Wouter Verhoef, Behnaz Arabi, Christiaan Van der Tol

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The aim of this study was to follow the canopy reflectance patterns in response to soil water deficit and to detect trends of changes in biophysical and biochemical parameters of grass (Poa pratensis species). We used visual interpretation, imaging spectroscopy and radiative transfer model inversion to monitor the gradual manifestation of water stress effects in a laboratory setting. Plots of 21 cm x 14.5 cm surface area with Poa pratensis plants that formed a closed canopy were subjected to water stress for 50 days. In a regular weekly schedule, canopy reflectance was measured. In addition, Leaf Area Index (LAI), Chlorophyll (a+b) content (Cab) and Leaf Water Content (Cw) were measured at regular time intervals. The 1-D bidirectional canopy reflectance model SAIL, coupled with the leaf optical properties model PROSPECT, was inverted using hyperspectral measurements by means of an iterative optimization method to retrieve vegetation biophysical and biochemical parameters. The relationships between retrieved LAI, Cab, Cw, and Cs (Senescent material) with soil moisture content were established in two separated groups; stress and non-stressed. To differentiate the water stress condition from the non-stressed condition, a threshold was defined that was based on the laboratory produced Soil Water Characteristic (SWC) curve. All parameters retrieved by model inversion using canopy spectral data showed good correlation with soil water content in the water stress condition. These parameters co-varied with soil moisture content under the stress condition (Chl: R2= 0.91, Cw: R2= 0.97, Cs: R2= 0.88 and LAI: R2=0.48) at the canopy level. To validate the results, the relationship between vegetation parameters that were measured in the laboratory and soil moisture content was established. The results were totally in agreement with the modeling outputs and confirmed the results produced by radiative transfer model inversion and spectroscopy. Since water stress changes all parts of the spectrum, we concluded that analysis of the reflectance spectrum in the VIS-NIR-MIR region is a promising tool for monitoring water stress impacts on vegetation.

Keywords: hyperspectral remote sensing, model inversion, vegetation responses, water stress

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Authors: Iván Rivet, Narges Dialami, Miguel Cervera, Michele Chiumenti

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Process parameters in Additive Manufacturing (AM) play a critical role in the mechanical performance of the final component. In order to find the input configuration that guarantees the optimal performance of the printed part, the process-performance relationship must be found. Fused Filament Fabrication (FFF) is the selected demonstrative AM technology due to its great popularity in the industrial manufacturing world. A material model that considers the different printing patterns present in a FFF part is used. A voxelized mesh is built from the manufacturing toolpaths described in the G-Code file. An Adaptive Mesh Refinement (AMR) based on the octree strategy is used in order to reduce the complexity of the mesh while maintaining its accuracy. High-fidelity and cost-efficient Finite Element (FE) simulations are performed and the influence of key process parameters in the mechanical performance of the component is analyzed. A robust optimization process based on appropriate failure criteria is developed to find the printing direction that leads to the optimal mechanical performance of the component. The Tsai-Wu failure criterion is implemented due to the orthotropy and heterogeneity constitutive nature of FFF components and because of the differences between the strengths in tension and compression. The optimization loop implements a modified version of an Anomaly Detection (AD) algorithm and uses the computed metrics to obtain the optimal printing direction. The developed methodology is verified with a case study on an industrial demonstrator.

Keywords: additive manufacturing, optimization, printing direction, mechanical performance, voxelization

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Authors: Karima Megdouli

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The ejector, a central element within the CO₂ transcritical ejection refrigeration system, holds significant importance in enhancing refrigeration capacity and minimizing compressor power usage. This study's objective is to introduce a technique for enhancing the effectiveness of the CO₂ transcritical two-phase ejector, utilizing Taguchi and ANOVA analysis. The investigation delves into the impact of geometric parameters, secondary flow temperature, and primary flow pressure on the efficiency of the ejector. Results indicate that employing a combination of Taguchi and ANOVA offers increased reliability and superior performance when optimizing the design of the CO₂ two-phase ejector.

Keywords: ejector, supersonic, Taguchi, ANOVA, optimization

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Authors: Renata Martins Pacheco, João Claro

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Wildfires are becoming an increasing concern worldwide, causing substantial social, economic, and environmental disruptions. This situation is especially relevant in Mediterranean-climate regions, present in all the five continents of the world, in which fire is not only a natural component of the environment but also perhaps one of the most important evolutionary forces. The rise in wildfire occurrences and their associated impacts suggests the need for identifying knowledge gaps and enhancing the basis of scientific evidence on how managers and policymakers may act effectively to address them. Considering that the main goal of a systematic map is to collate and catalog a body of evidence to describe the state of knowledge for a specific topic, it is a suitable approach to be used for this purpose. In this context, the aim of this study is to systematically map the research trends in wildfire management practices in Mediterranean-climate regions. A total of 201 wildfire management studies were analyzed and systematically mapped in terms of their: Year of publication; Place of study; Scientific outlet; Research area (Web of Science) or Research field (Scopus); Wildfire phase; Central research topic; Main objective of the study; Research methods; and Main conclusions or contributions. The results indicate that there is an increasing number of studies being developed on the topic (most from the last 10 years), but more than half of them are conducted in few Mediterranean countries (60% of the analyzed studies were conducted in Spain, Portugal, Greece, Italy or France), and more than 50% are focused on pre-fire issues, such as prevention and fuel management. In contrast, only 12% of the studies focused on “Economic modeling” or “Human factors and issues,” which suggests that the triple bottom line of the sustainability argument (social, environmental, and economic) is not being fully addressed by fire management research. More than one-fourth of the studies had their objective related to testing new approaches in fire or forest management, suggesting that new knowledge is being produced on the field. Nevertheless, the results indicate that most studies (about 84%) employed quantitative research methods, and only 3% of the studies used research methods that tackled social issues or addressed expert and practitioner’s knowledge. Perhaps this lack of multidisciplinary studies is one of the factors hindering more progress from being made in terms of reducing wildfire occurrences and their impacts.

Keywords: wildfire, Mediterranean-climate regions, management, policy

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Authors: Muhammad Umair Mushtaq, Ameena Iqbal, Muhammad Aqib Hassan Ali Khan, Ismat Nawaz, Sohail Yousaf, Mazhar Iqbal

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Heavy metals are one of the priority pollutants as they pose serious health and environmental threats. They can be removed by various physiochemical methods but are costly and responsible for additional environmental problems. Bioremediation that exploits plants and their associated microbes have been referred as cost effective and environmental friendly technique. In this study, a pot experiment was conducted in a greenhouse to evaluate the potential of Celosia cristata and effects of bacteria, Pseudomonas japonica, and organic amendment moss/compost on tolerating/accumulating heavy metals. Two weeks old seedlings were transferred to soil in pots, and after four weeks they were inoculated with bacterial strain, while after growth of six weeks they were watered with a metal containing synthetic wastewater and were harvested after a growth period of nine weeks. After harvesting, morphological and physiological parameters and metal content of plants were measured. The results showed highest plant growth and biomass production in case of organic amendments while highest metal uptake has been found in non-amended pots. Positive controls have shown highest Pb uptake of 2900 mg/kg DW, while P. japonica amended pots have shown highest Cd, Cr, Ni and Cu uptake of 963.53, 1481.17, 1022.01 and 602.17 mg/kg DW, respectively. In conclusion organic amendments have strong impacts on growth enhancement while P. japonica enhances metal translocation and accumulation to aerial parts with little significant involvement in plant growth.

Keywords: ornamental plants, plant microbe interaction, amendments, bacteria

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Authors: Miroslaw Wendeker, Piotr Kacejko, Mariusz Duk, Pawel Karpinski

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The research in the field of aircraft internal combustion engines is currently driven by the needs of decreasing fuel consumption and CO2 emissions, while fulfilling the level of safety. Currently, reciprocating aircraft engines are found in sports, emergency, agricultural and recreation aviation. Technically, they are most at a pre-war knowledge of the theory of operation, design and manufacturing technology, especially if compared to that high level of development of automotive engines. Typically, these engines are driven by carburetors of a quite primitive construction. At present, due to environmental requirements and dealing with a climate change, it is beneficial to develop aircraft piston engines and adopt the achievements of automotive engineering such as computer-controlled low-pressure injection, electronic ignition control and biofuels. The paper describes simulation research of the innovative power and control systems for the aircraft radial engine of high power. Installing an electronic ignition system in the radial aircraft engine is a fundamental innovative idea of this solution. Consequently, the required level of safety and better functionality as compared to the today’s plug system can be guaranteed. In this framework, this research work focuses on describing a methodology for optimizing the electronically controlled ignition system. This attempt can reduce emissions of toxic compounds as a result of lowered fuel consumption, optimized combustion and engine capability of efficient combustion of ecological fuels. New, redundant elements of the control system can improve the safety of aircraft. Consequently, the required level of safety and better functionality as compared to the today’s plug system can be guaranteed. The simulation research aimed to determine the vulnerability of the values measured (they were planned as the quantities measured by the measurement systems) to determining the optimal ignition angle (the angle of maximum torque at a given operating point). The described results covered: a) research in steady states; b) velocity ranging from 1500 to 2200 rpm (every 100 rpm); c) loading ranging from propeller power to maximum power; d) altitude ranging according to the International Standard Atmosphere from 0 to 8000 m (every 1000 m); e) fuel: automotive gasoline ES95. The three models of different types of ignition coil (different energy discharge) were studied. The analysis aimed at the optimization of the design of the innovative ignition system for an aircraft engine. The optimization involved: a) the optimization of the measurement systems; b) the optimization of actuator systems. The studies enabled the research on the vulnerability of the signals to the control of the ignition timing. Accordingly, the number and type of sensors were determined for the ignition system to achieve its optimal performance. The results confirmed the limited benefits, in terms of fuel consumption. Thus, including spark management in the optimization is mandatory to significantly decrease the fuel consumption. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: piston engine, radial engine, ignition system, CFD model, engine optimization

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Authors: M. Cangi, T. Dolar, C. Ersoy, Y. E. Aydogdu, A. I. Aydeniz, A. Mugan

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The drum is one of the critical parts in a washing machine in which the clothes are washed and spin by the rotational movement. It is activated by the drum shaft which is attached to an electric motor and subjected to dynamic loading. Being one of the critical components, failures of the drum require costly repairs of dynamic components. In this study, tolerance bands between the drum shaft and its two bearings were examined to develop a relationship between the fatigue life of the shaft and the interaction tolerances. Optimization of tolerance bands was completed in consideration of the fatigue life of the shaft as the cost function. The following methodology is followed: multibody dynamic model of a washing machine was constructed and used to calculate dynamic loading on the components. Then, these forces were used in finite element analyses to calculate the stress field in critical components which was used for fatigue life predictions. The factors affecting the fatigue life were examined to find optimum tolerance grade for a given test condition. Numerical results were verified by experimental observations.

Keywords: fatigue life, finite element analysis, tolerance analysis, optimization

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Authors: Manirath Wongsim

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Information Quality (IQ) has become a critical, strategic issue in Accounting Information Systems (AIS) adoption. In order to implement AIS adoption successfully, it is important to consider the quality of information use throughout the adoption process, which seriously impacts the effectiveness of AIS adoption practice and the optimization of AIS adoption decisions. There is a growing need for research to provide insights into issues and solutions related to IQ in AIS adoption. The need for an integrated approach to improve IQ in AIS adoption, as well as the unique characteristics of accounting data, demands an AIS adoption specific IQ framework. This research aims to explore ways of managing information quality and AIS adoption to investigate the relationship between the IQ issues and AIS adoption process. This study has led to the development of a framework for understanding IQ management in AIS adoption. This research was done on 44 respondents as ten organisations from manufacturing firms in Thailand. The findings of the research’s empirical evidence suggest that IQ dimensions in AIS adoption to provide assistance in all process of decision making. This research provides empirical evidence that information quality of AIS adoption affect decision making and suggests that these variables should be considered in adopting AIS in order to improve the effectiveness of AIS.

Keywords: information quality, information quality dimensions, accounting information systems, accounting information system adoption

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Authors: Jun-Ho Chung, Sung-Hyun Yoo, In-Hwan Choi, Hyun-Kook Lee, Moon-Kyu Song, Choon-Ki Ahn

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The extended finite impulse response (EFIR) filter is addressed to optimize membership functions (MFs) of the fuzzy model that has strong nonlinearity. MFs are important parts of the fuzzy logic system (FLS) and, thus optimizing MFs of FLS is one of approaches to improve the performance of output. We employ the EFIR as an alternative optimization option to nonlinear fuzzy model. The performance of EFIR is demonstrated on a fuzzy cruise control via a numerical example.

Keywords: fuzzy logic system, optimization, membership function, extended FIR filter

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Authors: Chen Guo, Heng Tang, Ben Niu

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Clustering splits objects into different groups based on similarity, making the objects have higher similarity in the same group and lower similarity in different groups. Thus, clustering can be treated as an optimization problem to maximize the intra-cluster similarity or inter-cluster dissimilarity. In real-world applications, the datasets often have some complex characteristics: sparse, overlap, high dimensionality, etc. When facing these datasets, simultaneously optimizing two or more objectives can obtain better clustering results than optimizing one objective. However, except for the objectives weighting methods, traditional clustering approaches have difficulty in solving multi-objective data clustering problems. Due to this, evolutionary multi-objective optimization algorithms are investigated by researchers to optimize multiple clustering objectives. In this paper, the Data Clustering algorithm based on Multi-objective Periodic Bacterial Foraging Optimization with two Learning Archives (DC-MPBFOLA) is proposed. Specifically, first, to reduce the high computing complexity of the original BFO, periodic BFO is employed as the basic algorithmic framework. Then transfer the periodic BFO into a multi-objective type. Second, two learning strategies are proposed based on the two learning archives to guide the bacterial swarm to move in a better direction. On the one hand, the global best is selected from the global learning archive according to the convergence index and diversity index. On the other hand, the personal best is selected from the personal learning archive according to the sum of weighted objectives. According to the aforementioned learning strategies, a chemotaxis operation is designed. Third, an elite learning strategy is designed to provide fresh power to the objects in two learning archives. When the objects in these two archives do not change for two consecutive times, randomly initializing one dimension of objects can prevent the proposed algorithm from falling into local optima. Fourth, to validate the performance of the proposed algorithm, DC-MPBFOLA is compared with four state-of-art evolutionary multi-objective optimization algorithms and one classical clustering algorithm on evaluation indexes of datasets. To further verify the effectiveness and feasibility of designed strategies in DC-MPBFOLA, variants of DC-MPBFOLA are also proposed. Experimental results demonstrate that DC-MPBFOLA outperforms its competitors regarding all evaluation indexes and clustering partitions. These results also indicate that the designed strategies positively influence the performance improvement of the original BFO.

Keywords: data clustering, multi-objective optimization, bacterial foraging optimization, learning archives

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

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Authors: Kamal Upadhyay, Zhou Hua, Yu Rui

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This paper aims to improve the streamline linked with the flow field and cavitation on the valve sleeve. We observed that local pressure fluctuation produces a low-pressure zone, central to the formation of vapor volume fraction within the valve chamber led to air-bubbles (or cavities). Thus, it allows simultaneously to a severe negative impact on the inner surface and lifespan of the valve sleeves. Cavitation reduction is a vitally important issue to pressure control valves. The optimization of the flow field is proposed in this paper to reduce the cavitation of valve sleeves. In this method, the inner wall of the valve sleeve is changed from a cylindrical surface to the conical surface, leading to the decline of the fluid flow velocity and the rise of the outlet pressure. Besides, the streamline is distributed inside the sleeve uniformly. Thus, the bubble generation is lessened. The fluid models are built and analysis of flow field distribution, pressure, vapor volume and velocity was carried out using computational fluid dynamics (CFD) and numerical technique. The results indicate that this structure can suppress the cavitation of valve sleeves effectively.

Keywords: streamline, cavitation, optimization, computational fluid dynamics

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Authors: William Li

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Lane-change path planning is a crucial and yet complex task in autonomous driving. The traditional path planning approach based on a system of carefully-crafted rules to cover various driving scenarios becomes unwieldy as more and more rules are added to deal with exceptions and corner cases. This paper proposes to divide the entire path planning to two stages. In the first stage the ego vehicle travels longitudinally in the source lane to reach a safe state. In the second stage the ego vehicle makes lateral lane-change maneuver to the target lane. The paper derives the safe state conditions based on lateral lane-change maneuver calculation to ensure collision free in the second stage. To determine the acceleration sequence that minimizes the time to reach a safe state in the first stage, the paper proposes three schemes, namely, kinetic model based optimization, deep reinforcement learning, and 5G vehicle-to-vehicle (V2V) communications. The paper investigates these schemes via simulation. The model-based optimization is sensitive to the model assumptions. The deep reinforcement learning is more flexible in handling scenarios beyond the model assumed by the optimization. The 5G V2V eliminates uncertainty in predicting future behaviors of surrounding vehicles by sharing driving intents and enabling cooperative driving.

Keywords: lane change, path planning, autonomous driving, deep reinforcement learning, 5G, V2V communications, connected vehicles

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Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

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Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: bridge management systems (BMS), cost optimization condition assessment, fund allocation, Markov chain

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Authors: Fares Senouci, Bachir Imine

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This document provides numerical and experimental optimization of the aerodynamic performance of a drone equipped with three types of horizontal stabilizer. To build this optimal configuration, an experimental and numerical study was conducted on three parameters: the geometry of the stabilizer (horizontal form or reverse V form), the position of the horizontal stabilizer (up or down), and the landing gear position (closed or open). The results show that up-stabilizer position with respect to the horizontal plane of the fuselage provides better aerodynamic performance, and that the landing gear increases the lift in the zone of stability, that is to say where the flow is not separated.

Keywords: aerodynamics, drag, lift, turbulence model, wind tunnel

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Authors: Abolaji Mayowa Akinyele

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The purpose of this study was to investigate student’s awareness, Knowledge and understanding of environmental issues for sustainable development. Findings revealed that; despite the positive attitude shown by students towards environmental education, a relatively low level of understanding of environmental concept was recorded in school settings regardless of efforts by government and other environmental agencies at creating awareness about environmental related issues. This brought about the investigation of students environmental education knowledge in high school settings. About 205 Students were randomly selected for data collection using validated instruments titled student’s knowledge and attitude questionnaire as well as student’s response to questions (interview) concerning global warming. T-test statistics, chi-square and simple percentage were the major statistical tools employed in data analysis. This study revealed that environment based-education (school curriculum) as well as efforts by government/environmental agencies (mass media) plays a major role in promoting students understanding, of environmental concepts, awareness of major environmental issues and positive attitude towards natural environment.

Keywords: environmental issues, sustainable development, students attitude, students knowledge

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Authors: Mustapha Ouardouz, Mina Amharref, Abdessamed Bernoussi

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The future energy, for limited energy resources countries, goes through renewable energies (solar, wind etc.). The renewable energies constitute a major component of the energy strategy to cover a substantial part of the growing needs and contribute to environmental protection by replacing fossil fuels. Indeed, sustainable development involves the promotion of renewable energy and the preservation of the environment by the use of clean energy technologies to limit emissions of greenhouse gases and reducing the pressure exerted on the forest cover. So the impact studies, of the energy use on the environment and farm-related risks are necessary. For that, a global approach integrating all the various sectors involved in such project seems to be the best approach. In this paper we present an approach based on the multi criteria analysis and the realization of one pilot to achieve the development of an innovative geo-intelligent environmental platform. An implementation of this platform will collect, process, analyze and manage environmental data in connection with the nature of used energy in the studied region. As an application we consider a region in the north of Morocco characterized by intense agricultural and industrials activities and using diverse renewable energy. The strategic goals of this platform are; the decision support for better governance, improving the responsiveness of public and private companies connected by providing them in real time with reliable data, modeling and simulation possibilities of energy scenarios, the identification of socio-technical solutions to introduce renewable energies and estimate technical and implantable potential by socio-economic analyzes and the assessment of infrastructure for the region and the communities, the preservation and enhancement of natural resources for better citizenship governance through democratization of access to environmental information, the tool will also perform simulations integrating environmental impacts of natural disasters, particularly those linked to climate change. Indeed extreme cases such as floods, droughts and storms will be no longer rare and therefore should be integrated into such projects.

Keywords: renewable energies, decision aided tool, environment, simulation

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Authors: Paschal Arsein Mugabe

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This paper examines sustainable development planning in the context of environmental concerns in rural areas of the Tanzania. It challenges mainstream approaches to development, focusing instead upon transformative action for environmental justice. The goal is to help shape future sustainable development agendas in local government, international agencies and civil society organisations. Research methods: The approach of the study is geographical, but also involves various Trans-disciplinary elements, particularly from development studies, sociology and anthropology, management, geography, agriculture and environmental science. The research methods included thematic and questionnaire interviews, participatory tools such as focus group discussion, participatory research appraisal and expert interviews for primary data. Secondary data were gathered through the analysis of land use/cover data and official documents on climate, agriculture, marketing and health. Also several earlier studies that were made in the area provided an important reference base. Findings: The findings show that, agricultural sustainability in Tanzania appears likely to deteriorate as a consequence of climate change. Noteworthy differences in impacts across households are also present both by district and by income category. Also food security cannot be explained by climate as the only influencing factor. A combination of economic, political and socio-cultural context of the community are crucial. Conclusively, it is worthy knowing that people understand their relationship between climate change and their livelihood.

Keywords: agriculture, climate change, environment, sustainable development

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Authors: Hadjadj Naima, K. Mahdi, D. Belhachat, F. S. Ait Chaouche, A. Ferradji

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The Nigella Sativa oil yield extracted by hydraulic pressing is influenced by the pressure temperature and size particles. The optimization of oil extraction is investigated. The rate of extraction of the whole seeds is very weak, a crushing of seeds is necessary to facilitate the extraction. This rate augments with the rise of the temperature and the pressure, and decrease of size particles. The best output (66%) is obtained for a granulometry lower than 1mm, a temperature of 50°C and a pressure of 120 bars.

Keywords: oil, Nigella sativa, extraction, optimization, temperature, pressure

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Authors: Jose Daniel Hoyos Giraldo, Jesus Hernan Jimenez Giraldo, Juan Pablo Alvarado Perilla

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Range and endurance are the main limitations of electric aircraft due to the nature of its source of power. The improvement of efficiency on this kind of systems is extremely meaningful to encourage the aircraft operation with less environmental impact. The propeller efficiency highly affects the overall efficiency of the propulsion system; hence its optimization can have an outstanding effect on the aircraft performance. An optimization method is applied to an aircraft propeller in order to maximize its range and endurance by estimating the best combination of geometrical parameters such as diameter and airfoil, chord and pitch distribution for a specific aircraft design at a certain cruise speed, then the rotational speed at which the propeller operates at minimum current consumption is estimated. The optimization is based on the Blade Element Momentum (BEM) method, additionally corrected to account for tip and hub losses, Mach number and rotational effects; furthermore an airfoil lift and drag coefficients approximation is implemented from Computational Fluid Dynamics (CFD) simulations supported by preliminary studies of grid independence and suitability of different turbulence models, to feed the BEM method, with the aim of achieve more reliable results. Additionally, Vortex Theory is employed to find the optimum pitch and chord distribution to achieve a minimum induced loss propeller design. Moreover, the optimization takes into account the well-known brushless motor model, thrust constraints for take-off runway limitations, maximum allowable propeller diameter due to aircraft height and maximum motor power. The BEM-CFD method is validated by comparing its predictions for a known APC propeller with both available experimental tests and APC reported performance curves which are based on Vortex Theory fed with the NASA Transonic Airfoil code, showing a adequate fitting with experimental data even more than reported APC data. Optimal propeller predictions are validated by wind tunnel tests, CFD propeller simulations and a study of how the propeller will perform if it replaces the one of on known aircraft. Some tendency charts relating a wide range of parameters such as diameter, voltage, pitch, rotational speed, current, propeller and electric efficiencies are obtained and discussed. The implementation of CFD tools shows an improvement in the accuracy of BEM predictions. Results also showed how a propeller has higher efficiency peaks when it operates at high rotational speed due to the higher Reynolds at which airfoils present lower drag. On the other hand, the behavior of the current consumption related to the propulsive efficiency shows counterintuitive results, the best range and endurance is not necessary achieved in an efficiency peak.

Keywords: BEM, blade design, CFD, electric aircraft, endurance, optimization, range

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Authors: J. Thiele

Abstract:

Teachers working at vocational Colleges are often confronted with the problem, that many students graduated from different schools and therefore each had a different education. Especially in mathematics many students lack fundamentals or had different priorities at their previous schools. Furthermore, these vocational Colleges have to provide Graduations for many different working-fields, with different core themes. The Colleges are interested in measuring the different Education levels of their students and providing assistance for those who need to catch up. The Project mathe-meistern was initiated to remedy this problem at vocational Colleges. For this purpose, online-tests were developed. The aim of these tests is to evaluate basic mathematical abilities of the students. The tests are online Multiple-Choice-Tests with a total of 65 Items. They are accessed online with a unique Transaction-Number (TAN) for each participant. The content is divided in several Categories (Arithmetic, Algebra, Fractions, Geometry, etc.). After each test, the student gets a personalized summary depicting their strengths and weaknesses in mathematical Basics. Teachers can visit a special website to examine the results of their classes or single students. In total 5830 students did participate so far. For standardization and optimization purposes the tests are being evaluated, using the classic and probabilistic Test-Theory regarding Objectivity, Reliability and Validity, annually since 2015. This Paper is about the Optimization process considering the Rasch-scaling and Standardization of the tests. Additionally, current results using standardized tests will be discussed. To achieve this Competence levels and Types of errors of students attending vocational Colleges in Nordrheinwestfalen, Germany, were determined, using descriptive Data and Distractorevaluations.

Keywords: diagnostical tests in mathematics, distractor devaluation, test-optimization, test-theory

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Authors: Veruska C. Dutra, Mary L. G. S. Senna

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The principle of sustainability has been studied by different sciences with the purpose of formulating clear and concrete models. Much has been discussed about sustainability, and several points of view have been used to try to explain it; environmental science emerges from various environmental discourses that are willing to establish a new concept for understanding this complexity. This way, we focus on the activity of ecotourism as a way to integrate sustainable practices proposed by environmental science, and thus, make it possible to create a new perspective for eco-tourists and the managers of tourist destinations towards nature. The aim of this study was to suggest a direction for environmental awareness, based on environmental science, to change the eco-tourist's view of nature in ecotourism tours. The methodology used was based on a case study concerning the Jalapão State Park - JSP, located in the State of Tocantins, Northern Brazil. The study was based on discussions, theoretical studies, bibliographical research and on-site research. We have identified that to incite the tourists’ awareness, they need to visit nature to understand the environmental problems and promote actions for its preservation. We highlight in this study actions to drive their human perception through environmental science, so that the ecotourism itinerary tours to the JSP, promote a balance between the natural environment and the tourist, making them, in this way, environmental tourists.

Keywords: science, environmental, ecoturism, Jalapão

Procedia PDF Downloads 339

Authors: K. Y. Chen, Y. N. Jia, H. Chua, C. W. Kan

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In United States (US), the environmental policy went through two stages that are government control period and market mechanism period. In the government control period in the 1970s, environmental problems in U.S. are treated by mandatory direct control method, including promulgation of laws, formulation of emission standards and mandatory installation of pollution treatment equipment. After the 1980s, the environmental policy in U.S. went into the second stage, in which the government strengthened the incentives and coordination effects of market. Since then, environmental governance had been partially replaced by means of economic regulation of the market. Green Tax Policy and Marketable Pollution Permits are good examples of government's economic interventions. U.S. Federal Government regards environmental industry as high-tech industry which is promoted in this period. Therefore, in the paper, we aim to analyse the effect of environmental investment on the sustainable development in the US. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: United States, public environmental investment, analysis, sustainable development

Procedia PDF Downloads 251

Authors: Ralph Lugon, Randolf Ramseyer

Abstract:

The beauty and quality of the natural heritage can be appreciated in different ways by different users, but the delicate balance of the environment in a nature reserve must be respected. The case of the territorial anchorage of the Grangettes natural reserve gives an interesting insight into the users' perception of the environmental constraints and standards of tourist activities. The nature reserve was once conceived as a sanctuary of natural heritage, a place where flora and fauna could flourish with minimal human interference. However, over time and with the transition to modernity, the values and meanings of the reserve have changed for visitors and the people living in the surrounding area. Today, The Grangettes nature reserve is a place of relaxation for urban dwellers with limited knowledge of nature and a lack of awareness of conservation issues. As a result, the reserve is now threatened by the negative impacts of human activities and mass tourism on its environment. Les Grangettes is a nature reserve that faces the challenge of preserving biodiversity while managing tourist flows. Ways must be found to accommodate new types of visitors from towns and cities who are looking for new activities, quality services and facilities, as well as aesthetic inspiration. To ensure the long-term conservation of the area, the flow of tourists must be carefully controlled. Through a dual qualitative-quantitative approach in 2021-22, this paper explores new visitor trends, changes in the reserve, and potential consequences for other stakeholders in the ecosystem. The purpose of this research is to assess users' perceptions of environmental constraints and standards on tourist activities in a nature reserve.

Keywords: outdoor recreation, nature-based tourism, over tourism, protected area, user's perceptions

Procedia PDF Downloads 79

Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

Procedia PDF Downloads 410

Authors: F. Rahimi Dehgolan, M. Behzadi, J. Fathi Sola

Abstract:

In this article, the Johnson-Cook material model’s constants for structural steel ST.37 have been determined by a method which integrates experimental tests, numerical simulation, and optimization. In the first step, a quasi-static test was carried out on a plain specimen. Next, the constants were calculated for it by minimizing the difference between the results acquired from the experiment and numerical simulation. Then, a quasi-static tension test was performed on three notched specimens with different notch radii. At last, in order to verify the results, they were used in numerical simulation of notched specimens and it was observed that experimental and simulation results are in good agreement. Changing the diameter size of the plain specimen in the necking area was set as the objective function in the optimization step. For final validation of the proposed method, diameter variation was considered as a parameter and its sensitivity to a change in any of the model constants was examined and the results were completely corroborating.

Keywords: constants, Johnson-Cook material model, notched specimens, quasi-static test, sensitivity

Procedia PDF Downloads 312

Authors: Johnstone Walubengo Wangusi

Abstract:

Climate change is undeniably altering the frequency, intensity, and geographic distribution of extreme weather events worldwide. In this paper, we explore the complex interconnections between climate change and extreme weather phenomena, drawing upon research from atmospheric science, geology, and climatology. We examine the underlying mechanisms driving these changes, the impacts on natural ecosystems and human societies, and strategies for adaptation and mitigation. By synthesizing insights from interdisciplinary research, this paper aims to provide a comprehensive understanding of the multifaceted relationship between climate change and extreme weather, informing efforts to address the challenges posed by a changing climate.

Keywords: climate change, extreme weather, atmospheric science, geology, climatology, impacts, adaptation, mitigation

Procedia PDF Downloads 64