Search results for: forest fire fuel
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2883

Search results for: forest fire fuel

1233 Evaluating Reliability Indices in 3 Critical Feeders at Lorestan Electric Power Distribution Company

Authors: Atefeh Pourshafie, Homayoun Bakhtiari

Abstract:

The main task of power distribution companies is to supply the power required by customers in an acceptable level of quality and reliability. Some key performance indicators for electric power distribution companies are those evaluating the continuity of supply within the network. More than other problems, power outages (due to lightning, flood, fire, earthquake, etc.) challenge economy and business. In addition, end users expect a reliable power supply. Reliability indices are evaluated on an annual basis by the specialized holding company of Tavanir (Power Produce, Transmission& distribution company of Iran) . Evaluation of reliability indices is essential for distribution companies, and with regard to the privatization of distribution companies, it will be of particular importance to evaluate these indices and to plan for their improvement in a not too distant future. According to IEEE-1366 standard, there are too many indices; however, the most common reliability indices include SAIFI, SAIDI and CAIDI. These indices describe the period and frequency of blackouts in the reporting period (annual or any desired timeframe). This paper calculates reliability indices for three sample feeders in Lorestan Electric Power Distribution Company and defines the threshold values in a ten-month period. At the end, strategies are introduced to reach the threshold values in order to increase customers' satisfaction.

Keywords: power, distribution network, reliability, outage

Procedia PDF Downloads 455
1232 Resource Assessment of Animal Dung for Power Generation: A Case Study

Authors: Gagandeep Kaur, Yadwinder Singh Brar, D. P. Kothari

Abstract:

The paper has an aggregate analysis of animal dung for converting it into renewable biomass fuel source that could be used to help the Indian state Punjab to meet rising power demand. In Punjab district Bathinda produces over 4567 tonnes of animal dung daily on a renewable basis. The biogas energy potential has been calculated using values for the daily per head animal dung production and total no. of large animals in Bathinda of Punjab. The 379540 no. of animals in district could produce nearly 116918 m3 /day of biogas as renewable energy. By converting this biogas into electric energy could produce 89.8 Gwh energy annually.

Keywords: livestock, animal dung, biogas, renewable energy

Procedia PDF Downloads 495
1231 Strategies to Achieve Deep Decarbonisation in Power Generation: A Review

Authors: Abdullah Alotaiq

Abstract:

The transition to low-carbon power generation is essential for mitigating climate change and achieving sustainability. This process, however, entails considerable costs, and understanding the factors influencing these costs is critical. This is necessary to cater to the increasing demand for low-carbon electricity across the heating, industry, and transportation sectors. A crucial aspect of this transition is identifying cost-effective and feasible paths for decarbonization, which is integral to global climate mitigation efforts. It is concluded that hybrid solutions, combining different low-carbon technologies, are optimal for minimizing costs and enhancing flexibility. These solutions also address the challenges associated with phasing out existing fossil fuel-based power plants and broadening the spectrum of low-carbon power generation options.

Keywords: review, power generation, energy transition, decarbonisation

Procedia PDF Downloads 39
1230 Numerical Investigation of the Effect of the Spark Plug Gap on Engine-Like Conditions

Authors: Fernanda Pinheiro Martins, Pedro Teixeira Lacava

Abstract:

The objective of this research is to analyze the effects of different spark plug conditions in engine-like conditions by applying computational fluid dynamics analysis. The 3D models applied consist of 3-Zones Extended Coherent Flame (ECFM-3Z) and Imposed Stretch Spark Ignition Model (ISSIM), respectively, for the combustion and the spark plug modelling. For this study, it was applied direct injection fuel system in a single cylinder engine operating with E0. The application of realistic operating conditions (load and speed) to the different cases studied will provide a deeper understanding of the effects of the spark plug gap, a result of parts outwearing in most of the cases, to the development of the combustion in engine-like conditions.

Keywords: engine, CFD, direct injection, combustion, spark plug

Procedia PDF Downloads 111
1229 Using Greywolf Optimized Machine Learning Algorithms to Improve Accuracy for Predicting Hospital Readmission for Diabetes

Authors: Vincent Liu

Abstract:

Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

Procedia PDF Downloads 35
1228 Sustainable Energy Production from Microalgae in Queshm Island, Persian Gulf

Authors: N. Moazami, R. Ranjbar, A. Ashori

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Out of hundreds of microalgal strains reported, only very few of them are capable for production of high content of lipid. Therefore, the key technical challenges include identifying the strains with the highest growth rates and oil contents with adequate composition, which were the main aims of this work. From 147 microalgae screened for high biomass and oil productivity, the Nannochloropsis sp. PTCC 6016, which attained 52% lipid content, was selected for large scale cultivation in Persian Gulf Knowledge Island. Nannochloropsis strain PTCC 6016 belongs to Eustigmatophyceae (Phylum heterokontophyta) isolated from Mangrove forest area of Qheshm Island and Persian Gulf (Iran) in 2008. The strain PTCC 6016 had an average biomass productivity of 2.83 g/L/day and 52% lipid content. The biomass productivity and the oil production potential could be projected to be more than 200 tons biomass and 100000 L oil per hectare per year, in an outdoor algal culture (300 day/year) in the Persian Gulf climate.

Keywords: biofuels, microalgae, Nannochloropsis, raceway open pond, bio-jet

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1227 Tree Species Classification Using Effective Features of Polarimetric SAR and Hyperspectral Images

Authors: Milad Vahidi, Mahmod R. Sahebi, Mehrnoosh Omati, Reza Mohammadi

Abstract:

Forest management organizations need information to perform their work effectively. Remote sensing is an effective method to acquire information from the Earth. Two datasets of remote sensing images were used to classify forested regions. Firstly, all of extractable features from hyperspectral and PolSAR images were extracted. The optical features were spectral indexes related to the chemical, water contents, structural indexes, effective bands and absorption features. Also, PolSAR features were the original data, target decomposition components, and SAR discriminators features. Secondly, the particle swarm optimization (PSO) and the genetic algorithms (GA) were applied to select optimization features. Furthermore, the support vector machine (SVM) classifier was used to classify the image. The results showed that the combination of PSO and SVM had higher overall accuracy than the other cases. This combination provided overall accuracy about 90.56%. The effective features were the spectral index, the bands in shortwave infrared (SWIR) and the visible ranges and certain PolSAR features.

Keywords: hyperspectral, PolSAR, feature selection, SVM

Procedia PDF Downloads 398
1226 Traditional Practices of Conserving Biodiversity: A Case Study around Jim Corbett National Park, Uttarakhand, India

Authors: Rana Parween, Rob Marchant

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With the continued loss of global biodiversity despite the application of modern conservation techniques, it has become crucial to investigate non-conventional methods. Accelerated destruction of ecosystems due to altered land use, climate change, cultural and social change, necessitates the exploration of society-biodiversity attitudes and links. While the loss of species and their extinction is a well-known and well-documented process that attracts much-needed attention from researchers, academics, government and non-governmental organizations, the loss of traditional ecological knowledge and practices is more insidious and goes unnoticed. The growing availability of 'indirect experiences' such as the internet and media are leading to a disaffection towards nature and the 'Extinction of Experience'. Exacerbated by the lack of documentation of traditional practices and skills, there is the possibility for the 'extinction' of traditional practices and skills before they are fully recognized and captured. India, as a mega-biodiverse country, is also known for its historical conservation strategies entwined in traditional beliefs. Indigenous communities hold skillsets, knowledge, and traditions that have accumulated over multiple generations and may play an important role in conserving biodiversity today. This study explores the differences in knowledge and attitudes towards conserving biodiversity, of three different stakeholder groups living around Jim Corbett National Park, based on their age, traditions, and association with the protected area. A triangulation designed multi-strategy investigation collected qualitative and quantitative data through a questionnaire survey of village elders, the general public, and forest officers. Following an inductive approach to analyzing qualitative data, the thematic content analysis was followed. All coding and analysis were completed using NVivo 11. Although the village elders and some general public had vast amounts of traditional knowledge, most of it was related to animal husbandry and the medicinal value of plants. Village elders were unfamiliar with the concept of the term ‘biodiversity’ albeit their way of life and attitudes ensured that they care for the ecosystem without having the scientific basis underpinning biodiversity conservation. Inherently, village elders were keen to conserve nature; the superimposition of governmental policies without any tangible benefit or consultation was seen as detrimental. Alienating villagers and consequently the village elders who are the reservoirs of traditional knowledge would not only be damaging to the social network of the area but would also disdain years of tried and tested techniques held by the elders. Forest officers advocated for biodiversity and conservation education for women and children. Women, across all groups, when questioned about nature conservation, showed more interest in learning and participation. Biodiversity not only has an ethical and cultural value, but also plays a role in ecosystem function and, thus, provides ecosystem services and supports livelihoods. Therefore, underpinning and using traditional knowledge and incorporating them into programs of biodiversity conservation should be explored with a sense of urgency.

Keywords: biological diversity, mega-biodiverse countries, traditional ecological knowledge, society-biodiversity links

Procedia PDF Downloads 89
1225 Machine Learning Automatic Detection on Twitter Cyberbullying

Authors: Raghad A. Altowairgi

Abstract:

With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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1224 Application of Advanced Remote Sensing Data in Mineral Exploration in the Vicinity of Heavy Dense Forest Cover Area of Jharkhand and Odisha State Mining Area

Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

Abstract:

The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8

Procedia PDF Downloads 102
1223 Consumer Preferences for Low-Carbon Futures: A Structural Equation Model Based on the Domestic Hydrogen Acceptance Framework

Authors: Joel A. Gordon, Nazmiye Balta-Ozkan, Seyed Ali Nabavi

Abstract:

Hydrogen-fueled technologies are rapidly advancing as a critical component of the low-carbon energy transition. In countries historically reliant on natural gas for home heating, such as the UK, hydrogen may prove fundamental for decarbonizing the residential sector, alongside other technologies such as heat pumps and district heat networks. While the UK government is set to take a long-term policy decision on the role of domestic hydrogen by 2026, there are considerable uncertainties regarding consumer preferences for ‘hydrogen homes’ (i.e., hydrogen-fueled appliances for space heating, hot water, and cooking. In comparison to other hydrogen energy technologies, such as road transport applications, to date, few studies have engaged with the social acceptance aspects of the domestic hydrogen transition, resulting in a stark knowledge deficit and pronounced risk to policymaking efforts. In response, this study aims to safeguard against undesirable policy measures by revealing the underlying relationships between the factors of domestic hydrogen acceptance and their respective dimensions: attitudinal, socio-political, community, market, and behavioral acceptance. The study employs an online survey (n=~2100) to gauge how different UK householders perceive the proposition of switching from natural gas to hydrogen-fueled appliances. In addition to accounting for housing characteristics (i.e., housing tenure, property type and number of occupants per dwelling) and several other socio-structural variables (e.g. age, gender, and location), the study explores the impacts of consumer heterogeneity on hydrogen acceptance by recruiting respondents from across five distinct groups: (1) fuel poor householders, (2) technology engaged householders, (3) environmentally engaged householders, (4) technology and environmentally engaged householders, and (5) a baseline group (n=~700) which filters out each of the smaller targeted groups (n=~350). This research design reflects the notion that supporting a socially fair and efficient transition to hydrogen will require parallel engagement with potential early adopters and demographic groups impacted by fuel poverty while also accounting strongly for public attitudes towards net zero. Employing a second-order multigroup confirmatory factor analysis (CFA) in Mplus, the proposed hydrogen acceptance model is tested to fit the data through a partial least squares (PLS) approach. In addition to testing differences between and within groups, the findings provide policymakers with critical insights regarding the significance of knowledge and awareness, safety perceptions, perceived community impacts, cost factors, and trust in key actors and stakeholders as potential explanatory factors of hydrogen acceptance. Preliminary results suggest that knowledge and awareness of hydrogen are positively associated with support for domestic hydrogen at the household, community, and national levels. However, with the exception of technology and/or environmentally engaged citizens, much of the population remains unfamiliar with hydrogen and somewhat skeptical of its application in homes. Knowledge and awareness present as critical to facilitating positive safety perceptions, alongside higher levels of trust and more favorable expectations for community benefits, appliance performance, and potential cost savings. Based on these preliminary findings, policymakers should be put on red alert about diffusing hydrogen into the public consciousness in alignment with energy security, fuel poverty, and net-zero agendas.

Keywords: hydrogen homes, social acceptance, consumer heterogeneity, heat decarbonization

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1222 Removal of Metals from Heavy Oil

Authors: Ali Noorian

Abstract:

Crude oil contains various compounds of hydrocarbons but low concentrations of inorganic compounds or metals. Vanadium and Nickel are the most common metals in crude oil. These metals usually exist in solution in the oil and residual fuel oil in the refining process is condensed. Deleterious effects of metals in petroleum have been known for some time. These metals do not only contaminate the product but also cause intoxication and loss of catalyst and corrosion to equipment. In this study, removal of heavy metals and petroleum residues were investigated. These methods include physical, chemical and biological treatment processes. For example, processes such as solvent extraction and hydro-catalytic and catalytic methods are effective and practical methods, but typically often have high costs and cause environmental pollution. Furthermore, biological methods that do not cause environmental pollution have been discussed in recent years, but these methods have not yet been industrialized.

Keywords: removal, metal, heavy oil, nickel, vanadium

Procedia PDF Downloads 355
1221 The Art of Looking (Back): The Female Gaze in Portrait de la Jeune Fille en Feu and Little Women

Authors: Louisa Browne Kirk

Abstract:

In recent press interviews to promote Portrait de la jeune fille en feu (2019, translated to Portrait of a Lady on Fire in English), director and screenwriter Céline Sciamma and actors Adèle Haenel and Noémie Merlant repeatedly state that they understand the film as (if not uniquely, then unusually) produced via and supportive of ‘the female gaze’. Such a way of seeing stands in opposition to ‘the male gaze’, first theorised by Laura Mulvey as the way in which the female figure is a bearer, not maker, of meaning, a silent signifier through and against whom the male creator/viewer produces his fantasies and obsessions. What, then, is the female gaze? How does a woman produce meaning in and through film? Portrait de la jeune fille en feu and another very recent film, Little Women (2019, directed by Greta Gerwig), are unlikely companion films that understand the female gaze to be the act of one woman looking at another woman, a looking that is mediated through the production of art. In Sciamma’s film this looking is sexual and mediated through painting and in Gerwig’s film looking is familial and mediated through writing. In the schema of these films, art, love, looking and meaning are produced through collaboration. The painted and the painter, the written and the writer, are no longer rendered as subject and object but as dual creators, both always seeing and seen. The gaze of the cinematic woman, mediated through shared artistic practice, is ‘the desire-that-gives’.

Keywords: female gaze, Gerwig, Sciamma, shared artistic practice

Procedia PDF Downloads 159
1220 Mathematical Modeling of the Water Bridge Formation in Porous Media: PEMFC Microchannels

Authors: N. Ibrahim-Rassoul, A. Kessi, E. K. Si-Ahmed, N. Djilali, J. Legrand

Abstract:

The static and dynamic formation of liquid water bridges is analyzed using a combination of visualization experiments in a microchannel with a mathematical model. This paper presents experimental and theoretical findings of water plug/capillary bridge formation in a 250 μm squared microchannel. The approach combines mathematical and numerical modeling with experimental visualization and measurements. The generality of the model is also illustrated for flow conditions encountered in manipulation of polymeric materials and formation of liquid bridges between patterned surfaces. The predictions of the model agree favorably the observations as well as with the experimental recordings.

Keywords: green energy, mathematical modeling, fuel cell, water plug, gas diffusion layer, surface of revolution

Procedia PDF Downloads 503
1219 Comparison of MODIS-Based Rice Extent Map and Landsat-Based Rice Classification Map in Determining Biomass Energy Potential of Rice Hull in Nueva Ecija, Philippines

Authors: Klathea Sevilla, Marjorie Remolador, Bryan Baltazar, Imee Saladaga, Loureal Camille Inocencio, Ma. Rosario Concepcion Ang

Abstract:

The underutilization of biomass resources in the Philippines, combined with its growing population and the rise in fossil fuel prices confirms demand for alternative energy sources. The goal of this paper is to provide a comparison of MODIS-based and Landsat-based agricultural land cover maps when used in the estimation of rice hull’s available energy potential. Biomass resource assessment was done using mathematical models and remote sensing techniques employed in a GIS platform.

Keywords: biomass, geographic information system (GIS), remote sensing, renewable energy

Procedia PDF Downloads 468
1218 Using Machine Learning Techniques for Autism Spectrum Disorder Analysis and Detection in Children

Authors: Norah Mohammed Alshahrani, Abdulaziz Almaleh

Abstract:

Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: autism spectrum disorder, machine learning, feature selection, support vector machine

Procedia PDF Downloads 129
1217 A Study on Aquatic Bycatch Mortality Estimation Due to Prawn Seed Collection and Alteration of Collection Method through Sustainable Practices in Selected Areas of Sundarban Biosphere Reserve (SBR), India

Authors: Samrat Paul, Satyajit Pahari, Krishnendu Basak, Amitava Roy

Abstract:

Fishing is one of the pivotal livelihood activities, especially in developing countries. Today it is considered an important occupation for human society from the era of human settlement began. In simple terms, non-target catches of any species during fishing can be considered as ‘bycatch,’ and fishing bycatch is neither a new fishery management issue nor a new problem. Sundarban is one of the world’s largest mangrove land expanding up to 10,200 sq. km in India and Bangladesh. This largest mangrove biome resource is used by the local inhabitants commercially to run their livelihood, especially by forest fringe villagers (FFVs). In Sundarban, over-fishing, especially post larvae collection of wild Penaeus monodon, is one of the major concerns, as during the collection of P. monodon, different aquatic species are destroyed as a result of bycatch mortality which changes in productivity and may negatively impact entire biodiversity, of the ecosystem. Wild prawn seed collection gear like a small mesh sized net poses a serious threat to aquatic stocks, where the collection isn’t only limited to prawn seed larvae. As prawn seed collection processes are inexpensive, require less monetary investment, and are lucrative; people are easily engaged here as their source of income. Wildlife Trust of India’s (WTI) intervention in selected forest fringe villages of Sundarban Tiger Reserve (STR) was to estimate and reduce the mortality of aquatic bycatches by involving local communities in newly developed release method and their time engagement in prawn seed collection (PSC) by involving them in Alternate Income Generation (AIG). The study was conducted for their taxonomic identification during the period of March to October 2019. Collected samples were preserved in 70% ethyl alcohol for identification, and all the preserved bycatch samples were identified morphologically by the expertise of the Zoological Survey of India (ZSI), Kolkata. Around 74 different aquatic species, where 11 different species are molluscs, 41 fish species, out of which 31 species were identified, and 22 species of crustacean collected, out of which 18 species were identified. Around 13 different species belong to a different order, and families were unable to identify them morphologically as they were collected in the juvenile stage. The study reveals that for collecting one single prawn seed, eight individual life of associated faunas are being lost. Zero bycatch mortality is not practical; rather, collectors should focus on bycatch reduction by avoiding capturing, allowing escaping, and mortality reduction, and must make changes in their fishing method by increasing net mesh size, which will avoid non-target captures. But as the prawns are small in size (generally 1-1.5 inches in length), thus increase net size making economically less or no profit for collectors if they do so. In this case, returning bycatches is considered one of the best ways to a reduction in bycatch mortality which is a more sustainable practice.

Keywords: bycatch mortality, biodiversity, mangrove biome resource, sustainable practice, Alternate Income Generation (AIG)

Procedia PDF Downloads 126
1216 Performance and Voyage Analysis of Marine Gas Turbine Engine, Installed to Power and Propel an Ocean-Going Cruise Ship from Lagos to Jeddah

Authors: Mathias U. Bonet, Pericles Pilidis, Georgios Doulgeris

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An aero-derivative marine Gas Turbine engine model is simulated to be installed as the main propulsion prime mover to power a cruise ship which is designed and routed to transport intending Muslim pilgrims for the annual hajj pilgrimage from Nigeria to the Islamic port city of Jeddah in Saudi Arabia. A performance assessment of the Gas Turbine engine has been conducted by examining the effect of varying aerodynamic and hydrodynamic conditions encountered at various geographical locations along the scheduled transit route during the voyage. The investigation focuses on the overall behavior of the Gas Turbine engine employed to power and propel the ship as it operates under ideal and adverse conditions to be encountered during calm and rough weather according to the different seasons of the year under which the voyage may be undertaken. The variation of engine performance under varying operating conditions has been considered as a very important economic issue by determining the time the speed by which the journey is completed as well as the quantity of fuel required for undertaking the voyage. The assessment also focuses on the increased resistance caused by the fouling of the submerged portion of the ship hull surface with its resultant effect on the power output of the engine as well as the overall performance of the propulsion system. Daily ambient temperature levels were obtained by accessing data from the UK Meteorological Office while the varying degree of turbulence along the transit route and according to the Beaufort scale were also obtained as major input variables of the investigation. By assuming the ship to be navigating the Atlantic Ocean and the Mediterranean Sea during winter, spring and summer seasons, the performance modeling and simulation was accomplished through the use of an integrated Gas Turbine performance simulation code known as ‘Turbomach’ along with a Matlab generated code named ‘Poseidon’, all of which have been developed at the Power and Propulsion Department of Cranfield University. As a case study, the results of the various assumptions have further revealed that the marine Gas Turbine is a reliable and available alternative to the conventional marine propulsion prime movers that have dominated the maritime industry before now. The techno-economic and environmental assessment of this type of propulsion prime mover has enabled the determination of the effect of changes in weather and sea conditions on the ship speed as well as trip time and the quantity of fuel required to be burned throughout the voyage.

Keywords: ambient temperature, hull fouling, marine gas turbine, performance, propulsion, voyage

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1215 Development of Al Foam by a Low-Cost Salt Replication Method for Industrial Applications

Authors: B. Soni, S. Biswas

Abstract:

Metal foams of Al find diverse applications in several industrial sectors such as in automotive and sports equipment industry as impact, acoustic and vibration absorbers, the aerospace industry as structural components in turbines and spatial cones, in the naval industry as low frequency vibration absorbers, and in construction industry as sound barriers inside tunnels, as fire proof materials and structure protection systems against explosions and even in heat exchangers, orthopedic components, and decorative items. Here, we report on the development of Al foams by a low cost and convenient technique of salt replication method with efficient control over size, geometry and distribution of the pores. Sodium bicarbonate was used as the foaming agent to form the porous refractory salt pattern. The mixed refractory salt slurry was microwave dried followed by sintering for selected time periods. Molten Al was infiltrated into the salt pattern in an inert atmosphere at a pressure of 2 bars. The final products were obtained by leaching out the refractory salt pattern. Mechanical properties of the derived samples were studied with a universal testing machine. The results were analyzed in correlation with their microstructural features evaluated with a scanning electron microscope (SEM).

Keywords: metal foam, Al, salt replication method, mechanical properties, SEM

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1214 Sampling and Characterization of Fines Created during the Shredding of Non Hazardous Waste

Authors: Soukaina Oujana, Peggy Zwolinski

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Fines are heterogeneous residues created during the shredding of non-hazardous waste. They are one of the most challenging issues faced by recyclers, because they are at the present time considered as non-sortable and non-reusable mixtures destined to landfill. However, fines contain a large amount of recoverable materials that could be recycled or reused for the production of solid recovered fuel. This research is conducted in relation to a project named ValoRABES. The aim is to characterize fines and establish a suitable sorting process in order to extract the materials contained in the mixture and define their suitable recovery paths. This paper will highlight the importance of a good sampling and will propose a sampling methodology for fines characterization. First results about the characterization will be also presented.

Keywords: fines, non-hazardous waste, recovery, shredding residues, waste characterization, waste sampling

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1213 Characterization and the Study of Energy Potential of Municipal Solid Waste Disposed in Bauchi Town and Environs

Authors: Aliyu Mohammed Lawal, Dahiru Yau Gital

Abstract:

The characterisation and the energy potential of the municipal solid wastes in Bauchi town and environs were studied. It was found that, 35,000 tonnes of waste was generated annually at 0.19 kg/capital/day of which, the combination of plastics, rubber, polyethene bags constituted about 33%, followed by textile materials, leathers, wood 26%, combination of papers, cartons 19%, crop stalks/grass 11% and the remaining incombustible materials 11%. The heating value or calorific value of the wastes was determined using a digital calorimeter to be 6.43 MJ/kg, almost one-third of the energy content of peat which has a value of 15.9 MJ/kg. The calorific value of the fuel was found to be significant; hence, the waste could be used for energy generation.

Keywords: calorific value, characterization, digital calorimeter, incombustible, municipal solid waste

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1212 Catalytic Pyrolysis of Sewage Sludge for Upgrading Bio-Oil Quality Using Sludge-Based Activated Char as an Alternative to HZSM5

Authors: Ali Zaker, Zhi Chen

Abstract:

Due to the concerns about the depletion of fossil fuel sources and the deteriorating environment, the attempt to investigate the production of renewable energy will play a crucial role as a potential to alleviate the dependency on mineral fuels. One particular area of interest is the generation of bio-oil through sewage sludge (SS) pyrolysis. SS can be a potential candidate in contrast to other types of biomasses due to its availability and low cost. However, the presence of high molecular weight hydrocarbons and oxygenated compounds in the SS bio-oil hinders some of its fuel applications. In this context, catalytic pyrolysis is another attainable route to upgrade bio-oil quality. Among different catalysts (i.e., zeolites) studied for SS pyrolysis, activated chars (AC) are eco-friendly alternatives. The beneficial features of AC derived from SS comprise the comparatively large surface area, porosity, enriched surface functional groups, and presence of a high amount of metal species that can improve the catalytic activity. Hence, a sludge-based AC catalyst was fabricated in a single-step pyrolysis reaction with NaOH as the activation agent and was compared with HZSM5 zeolite in this study. The thermal decomposition and kinetics were invested via thermogravimetric analysis (TGA) for guidance and control of pyrolysis and catalytic pyrolysis and the design of the pyrolysis setup. The results indicated that the pyrolysis and catalytic pyrolysis contains four obvious stages, and the main decomposition reaction occurred in the range of 200-600°C. The Coats-Redfern method was applied in the 2nd and 3rd devolatilization stages to estimate the reaction order and activation energy (E) from the mass loss data. The average activation energy (Em) values for the reaction orders n = 1, 2, and 3 were in the range of 6.67-20.37 kJ for SS; 1.51-6.87 kJ for HZSM5; and 2.29-9.17 kJ for AC, respectively. According to the results, AC and HZSM5 both were able to improve the reaction rate of SS pyrolysis by abridging the Em value. Moreover, to generate and examine the effect of the catalysts on the quality of bio-oil, a fixed-bed pyrolysis system was designed and implemented. The composition analysis of the produced bio-oil was carried out via gas chromatography/mass spectrometry (GC/MS). The selected SS to catalyst ratios were 1:1, 2:1, and 4:1. The optimum ratio in terms of cracking the long-chain hydrocarbons and removing oxygen-containing compounds was 1:1 for both catalysts. The upgraded bio-oils with AC and HZSM5 were in the total range of C4-C17, with around 72% in the range of C4-C9. The bio-oil from pyrolysis of SS contained 49.27% oxygenated compounds, while with the presence of AC and HZSM5 dropped to 13.02% and 7.3%, respectively. Meanwhile, the generation of benzene, toluene, and xylene (BTX) compounds was significantly improved in the catalytic process. Furthermore, the fabricated AC catalyst was characterized by BET, SEM-EDX, FT-IR, and TGA techniques. Overall, this research demonstrated AC is an efficient catalyst in the pyrolysis of SS and can be used as a cost-competitive catalyst in contrast to HZSM5.

Keywords: catalytic pyrolysis, sewage sludge, activated char, HZSM5, bio-oil

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1211 The Thermal Properties of Nano Magnesium Hydroxide Blended with LDPE/EVA/Irganox1010 for Insulator Application

Authors: Ahmad Aroziki Abdul Aziz, Sakinah Mohd Alauddin, Ruzitah Mohd Salleh, Mohammed Iqbal Shueb

Abstract:

This paper illustrates the effect of nano Magnesium Hydroxide (MH) loading on the thermal properties of Low Density Polyethylene (LDPE)/ Poly (ethylene-co vinyl acetate)(EVA) nano composite. Thermal studies were conducted, as it understanding is vital for preliminary development of new polymeric systems. Thermal analysis of nano composite was conducted using thermo gravimetric analysis (TGA), and differential scanning calorimetry (DSC). Major finding of TGA indicated two main stages of degradation process found at (350 ± 25 oC) and (480 ± 25 oC) respectively. Nano metal filler expressed better fire resistance as it stand over high degree of temperature. Furthermore, DSC analysis provided a stable glass temperature around 51 (±1 oC) and captured double melting point at 84 (±2 oC) and 108 (±2 oC). This binary melting point reflects the modification of nano filler to the polymer matrix forming melting crystals of folded and extended chain. The percent crystallinity of the samples grew vividly with increasing filler content. Overall, increasing the filler loading improved the degradation temperature and weight loss evidently and a better process and phase stability was captured in DSC.

Keywords: thermal properties, nano MH, nano particles, cable and wire, LDPE/EVA

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1210 Aerodynamic Analysis of Multiple Winglets for Aircrafts

Authors: S. Pooja Pragati, B. Sudarsan, S. Raj Kumar

Abstract:

This paper provides a practical design of a new concept of massive Induced Drag reductions of stream vise staggered multiple winglets. It is designed to provide an optimum performance of a winglet from conventional designs. In preparing for a mechanical design, aspects such as shape, dimensions are analyzed to yield a huge amount of reduction in fuel consumption and increased performance. Owing to its simplicity of application and effectiveness we believe that it will enable us to consider its enhanced version for the grid effect of the staggered multiple winglets on the deflected mass flow of the wing system. The objective of the analysis were to compare the aerodynamic characteristics of two winglet configuration and to investigate the performance of two winglets shape simulated at selected cant angle of 0,45,60 degree.

Keywords: multiple winglets, induced drag, aerodynamics analysis, low speed aircrafts

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1209 Investigating Water-Oxidation Using a Ru(III) Carboxamide Water Coordinated Complex

Authors: Yosra M. Badiei, Evelyn Ortiz, Marisa Portenti, David Szalda

Abstract:

Water-oxidation half-reaction is a critical reaction that can be driven by a sustainable energy source (e.g., solar or wind) and be coupled with a chemical fuel making reaction which stores the released electrons and protons from water (e.g., H₂ or methanol). The use of molecular water-oxidation catalysts (WOC) allow the rationale design of redox active metal centers and provides a better understanding of their structure-activity-relationship. Herein, the structure of a Ru(III) complex bearing a doubly deprotonated N,N'-bis(aryl)pyridine-2,6-dicarboxamide ligand which contains a water molecule in its primary coordination sphere was elucidated by single-crystal X-ray diffraction. Further spectroscopic experimental data and pH-dependent electrochemical studies reveal its water-oxidation reactivity. Emphasis on mechanistic details for O₂ formation of this complex will be addressed.

Keywords: water-oxidation, catalysis, ruthenium, artificial photosynthesis

Procedia PDF Downloads 182
1208 Optimal Scheduling for Energy Storage System Considering Reliability Constraints

Authors: Wook-Won Kim, Je-Seok Shin, Jin-O Kim

Abstract:

This paper propose the method for optimal scheduling for battery energy storage system with reliability constraint of energy storage system in reliability aspect. The optimal scheduling problem is solved by dynamic programming with proposed transition matrix. Proposed optimal scheduling method guarantees the minimum fuel cost within specific reliability constraint. For evaluating proposed method, the timely capacity outage probability table (COPT) is used that is calculated by convolution of probability mass function of each generator. This study shows the result of optimal schedule of energy storage system.

Keywords: energy storage system (ESS), optimal scheduling, dynamic programming, reliability constraints

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1207 To Improve or Not to Improve Reflections from Jerash Urban Improvement Project, Jordan

Authors: Dina Dahood Dabash

Abstract:

Palestine Refugee Camps have never been settings that can be overlooked; they even became (as physical settings) a cornerstone topic of negotiations whenever Palestinian matters are on the table (specifically in Jordan). Consequently, maintaining the familiar face of the camp with its dilapidated shelters and narrow streets that rarely allowed its residents to extinguish a fire or evacuate a building safely has become a fundamental method to protect the “right of the return” from the perspective of various stakeholders. When the Infrastructure and Camp Improvement Programme (ICIP) was established in 2007 as an additional UNRWA program, some concerns were raised around the newly established section, mainly due to its direct impact on the “image” of the camp through a provision of a relatively nonconventional service that differs from what the Agency used to provide in the past seventy years. By presenting the Urban Improvement Project in Jerash camp (UIP) -Jordan, this paper aims to contribute to the ongoing discussion around enduring the improvement of Palestine refugee camps “programmatically” in UNRWA or not. The UIP as a co-product by UNRWA and the camp’s community within one of the most vulnerable refugee camps in Jordan offers a remarkable opportunity to excerpt lessons that can contribute to the strategic shaping of the ICIP. The paper concludes with five mine uptakes mainly related to community engagement, power structures and UNRWA's role in camps.

Keywords: camp improvement program, Jerash camp, Palestine refugee camps, UNRWA.

Procedia PDF Downloads 191
1206 Application of Harris Hawks Optimization Metaheuristic Algorithm and Random Forest Machine Learning Method for Long-Term Production Scheduling Problem under Uncertainty in Open-Pit Mines

Authors: Kamyar Tolouei, Ehsan Moosavi

Abstract:

In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

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1205 Real-Time Recognition of Dynamic Hand Postures on a Neuromorphic System

Authors: Qian Liu, Steve Furber

Abstract:

To explore how the brain may recognize objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor~(DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network~(SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modeled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study's largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognize the postures with an accuracy of around 86.4% -only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much-improved cost to performance trade-off in its approach.

Keywords: spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system

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1204 Different Formula of Mixed Bacteria as a Bio-Treatment for Sewage Wastewater

Authors: E. Marei, A. Hammad, S. Ismail, A. El-Gindy

Abstract:

This study aims to investigate the ability of different formula of mixed bacteria as a biological treatments of wastewater after primary treatment as a bio-treatment and bio-removal and bio-adsorbent of different heavy metals in natural circumstances. The wastewater was collected from Sarpium forest site-Ismailia Governorate, Egypt. These treatments were mixture of free cells and mixture of immobilized cells of different bacteria. These different formulas of mixed bacteria were prepared under Lab. condition. The obtained data indicated that, as a result of wastewater bio-treatment, the removal rate was found to be 76.92 and 76.70% for biological oxygen demand, 79.78 and 71.07% for chemical oxygen demand, 32.45 and 36.84 % for ammonia nitrogen as well as 91.67 and 50.0% for phosphate after 24 and 28 hrs with mixed free cells and mixed immobilized cells, respectively. Moreover, the bio-removals of different heavy metals were found to reach 90.0 and 50. 0% for Cu ion, 98.0 and 98.5% for Fe ion, 97.0 and 99.3% for Mn ion, 90.0 and 90.0% Pb, 80.0% and 75.0% for Zn ion after 24 and 28 hrs with mixed free cells and mixed immobilized cells, respectively. The results indicated that 13.86 and 17.43% of removal efficiency and reduction of total dissolved solids were achieved after 24 and 28 hrs with mixed free cells and mixed immobilized cells, respectively.

Keywords: wastewater bio-treatment , bio-sorption heavy metals, biological desalination, immobilized bacteria, free cell bacteria

Procedia PDF Downloads 183