Search results for: electric mining shovel

Authors: S. Sabatino, V. Calderaro, V. Galdi, G. Graber, L. Ippolito

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Climate change is a rapidly growing global threat caused mainly by increased emissions of carbon dioxide (CO₂) into the atmosphere. These emissions come from multiple sources, including industry, power generation, and the transport sector. The need to tackle climate change and reduce CO₂ emissions is indisputable. A crucial solution to achieving decarbonization in the transport sector is the adoption of electric vehicles (EVs). These vehicles use lithium (Li-Ion) batteries as an energy source, making them extremely efficient and with low direct emissions. However, Li-Ion batteries are not without problems, including the risk of overheating and performance degradation. To ensure its safety and longevity, it is essential to use a battery management system (BMS). The BMS constantly monitors battery status, adjusts temperature and cell balance, ensuring optimal performance and preventing dangerous situations. From the monitoring carried out, it is also able to optimally manage the battery to increase its life. Among the parameters monitored by the BMS, the main ones are State of Charge (SoC), State of Health (SoH), and State of Power (SoP). The evaluation of these parameters can be carried out in two ways: offline, using benchtop batteries tested in the laboratory, or online, using batteries installed in moving vehicles. Online estimation is the preferred approach, as it relies on capturing real-time data from batteries while operating in real-life situations, such as in everyday EV use. Actual battery usage conditions are highly variable. Moving vehicles are exposed to a wide range of factors, including temperature variations, different driving styles, and complex charge/discharge cycles. This variability is difficult to replicate in a controlled laboratory environment and can greatly affect performance and battery life. Online estimation captures this variety of conditions, providing a more accurate assessment of battery behavior in real-world situations. In this article, a hybrid approach based on a neural network and a statistical method for real-time estimation of SoC, SoH, and SoP parameters of interest is proposed. These parameters are estimated from the analysis of a one-day driving profile of an electric vehicle, assumed to be divided into the following four phases: (i) Partial discharge (SoC 100% - SoC 50%), (ii) Partial discharge (SoC 50% - SoC 80%), (iii) Deep Discharge (SoC 80% - SoC 30%) (iv) Full charge (SoC 30% - SoC 100%). The neural network predicts the values of ohmic resistance and incremental capacity, while the statistical method is used to estimate the parameters of interest. This reduces the complexity of the model and improves its prediction accuracy. The effectiveness of the proposed model is evaluated by analyzing its performance in terms of square mean error (RMSE) and percentage error (MAPE) and comparing it with the reference method found in the literature.

Keywords: electric vehicle, Li-Ion battery, BMS, state-of-charge, state-of-health, state-of-power, artificial neural networks

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Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

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Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

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Authors: Aguasanta Miguel Sarmiento, José Miguel Dávila, María Luisa de la Torre

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Acid mine drainage (AMD) is an acidic leachate with high levels of metals and sulphates in solution, which seriously affects the durability and strength of metallic materials used in the construction of structural and mechanical components. This paper presents the results of the evolution over time of the reduction in tensile strength and defects in AISI 304 stainless steel in contact with acid mine drainage. For this purpose, a total of 30 bars with a diameter of 8 mm and a length of 14 cm were placed transversely in the course of a stream contaminated by AMD from the sulphide mines of the Iberian Pyritic Belt (SW Spain). This stream has average pH values of 2.6, a potential of 660 mV and average concentrations of 12 g/L of sulphates, 1.2 g/L of Fe, 191 mg/L of Zn, etc. Every two months of exposure, 6 stainless steel bars were extracted from the acid stream. They were subjected to surface roughness analysis carried out with the help of Mitutoyo Surftest SJ-210 surface roughness tester. The analysis was carried out at three different points on 5 specimens from each series. The average reading of each parameter is calculated in order to ensure the accuracy of the measurements and the surface coverage. Arithmetic mean roughness value (Ra), mean roughness depth (Rz) and root mean square roughness (Rq) were measured. Five specimens from each series were statically tensile tested using universal equipment (Servosis ME 403 of 200kN). The specimens were clamped at their ends with two grips for cylindrical sections and the tensile force was applied at a constant speed of 0.5 kN/s, according to the requirements of standard UNE-EN ISO 6892-1: 2020. To determine the modulus of elasticity, limits close to 15% and 55% of the maximum load were used, depending on the course of each test. Field Emission Scanning Electron Microscopy (FESEM) was used to observe corrosion products and defects generated by exposure to AMD. Energy dispersive X-ray spectrometry (EDS) was used to analyse the chemical composition of the corrosion products formed. For this purpose, small pieces were cut from the resulting specimens, cleaned and embedded in epoxy resin. The results show that after only 5 months of exposure of AISI 304 stainless steel to the mining environment, the surface roughness increases significantly, with average depths almost 6 times greater than the initial one. Cracks are observed on the surface of the material, which increase in size with the time of exposure. A large number of grains with a composition of more than 57% Pb and 16% Sn can be observed inside these cracks. Tensile tests show a reduction in the resistance of this material after only two months of exposure. The results show the serious problems that would result from the use of this material for the use of mechanical components in a sulphide mining environment, not only because of the significant reduction in the lifetime of such components, but also because of the implications for human safety.

Keywords: acid mine drainage, corrosion, mechanical properties, stainless steel

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Authors: Eliane Ferreira da Silva

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This paper aims to mobilize and sensitize public administration leaders to good practices and encourage investment in the PV system in Brazil. It presents a case study methodology for dimensioning the PV system in the roofs of the public buildings of the Esplanade of the Ministries, Brasilia, capital of the country, with predefined resources, starting with the Sustainable Esplanade Project (SEP), of the exponential growth of photovoltaic solar energy in the world and making a comparison with the solar power plant of the Ministry of Mines and Energy (MME), active since: 6/10/2016. In order to do so, it was necessary to evaluate the energy efficiency of the buildings in the period from January 2016 to April 2017, (16 months) identifying the opportunities to reduce electric energy expenses, through the adjustment of contracted demand, the tariff framework and correction of existing active energy. The instrument used to collect data on electric bills was the e-SIC citizen information system. The study considered in addition to the technical and operational aspects, the historical, cultural, architectural and climatic aspects, involved by several actors. Identifying the reductions of expenses, the study directed to the following aspects: Case 1) economic feasibility for exchanges of common lamps, for LED lamps, and, Case 2) economic feasibility for the implementation of photovoltaic solar system connected to the grid. For the case 2, PV*SOL Premium Software was used to simulate several possibilities of photovoltaic panels, analyzing the best performance, according to local characteristics, such as solar orientation, latitude, annual average solar radiation. A simulation of an ideal photovoltaic solar system was made, with due calculations of its yield, to provide a compensation of the energy expenditure of the building - or part of it - through the use of the alternative source in question. The study develops a methodology for public administration, as a major consumer of electricity, to act in a responsible, fiscalizing and incentive way in reducing energy waste, and consequently reducing greenhouse gases.

Keywords: energy efficiency, esplanade of ministries, photovoltaic solar energy, public buildings, sustainable building

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Authors: Guido Lorenzi, Massimo Santarelli, Carlos Augusto Santos Silva

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The growth of non-dispatchable renewable energy sources in the European electricity generation mix is promoting the research of technically feasible and cost-effective solutions to make use of the excess energy, produced when the demand is low. The increasing intermittent renewable capacity is becoming a challenge to face especially in Europe, where some countries have shares of wind and solar on the total electricity produced in 2015 higher than 20%, with Denmark around 40%. However, other consumption sectors (mainly transportation) are still considerably relying on fossil fuels, with a slow transition to other forms of energy. Among the opportunities for different mobility concepts, electric (EV) and biofuel-powered vehicles (BPV) are the options that currently appear more promising. The EVs are targeting mainly the light duty users because of their zero (Full electric) or reduced (Hybrid) local emissions, while the BPVs encourage the use of alternative resources with the same technologies (thermal engines) used so far. The batteries which are applied to EVs are based on ions of Lithium because of their overall good performance in energy density, safety, cost and temperature performance. Biofuels, instead, can be various and the major difference is in their physical state (liquid or gaseous). In this study gaseous biofuels are considered and, more specifically, Synthetic Natural Gas (SNG) produced through a process of Power-to-Gas consisting in an electrochemical upgrade (with Solid Oxide Electrolyzers) of biogas with CO2 recycling. The latter process combines a first stage of electrolysis, where syngas is produced, and a second stage of methanation in which the product gas is turned into methane and then made available for consumption. A techno-economic comparison between the two alternatives is possible, but it does not capture all the different aspects involved in the two routes for the promotion of a more sustainable mobility. For this reason, a more comprehensive methodology, i.e. Life Cycle Assessment, is adopted to describe the environmental implications of using excess electricity (directly or indirectly) for new vehicle fleets. The functional unit of the study is 1 km and the two options are compared in terms of overall CO2 emissions, both considering Cradle to Gate and Cradle to Grave boundaries. Showing how production and disposal of materials affect the environmental performance of the analyzed routes is useful to broaden the perspective on the impacts that different technologies produce, in addition to what is emitted during the operational life. In particular, this applies to batteries for which the decommissioning phase has a larger impact on the environmental balance compared to electrolyzers. The lower (more than one order of magnitude) energy density of Li-ion batteries compared to SNG implies that for the same amount of energy used, more material resources are needed to obtain the same effect. The comparison is performed in an energy system that simulates the Western European one, in order to assess which of the two solutions is more suitable to lead the de-fossilization of the transport sector with the least resource depletion and the mildest consequences for the ecosystem.

Keywords: electrical energy storage, electric vehicles, power-to-gas, life cycle assessment

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Authors: N. Gharbi

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Constraint Satisfaction problems are mathematical problems that are often used to model many real-world problems for which we look if there exists a solution satisfying all its constraints. Table constraints are important for modeling parts of many problems since they list all combinations of allowed or forbidden values. However, they admit practical limitations because they are sometimes too large to be represented in a direct way. In this paper, we present a survey of the different categories of the proposed approaches to compress table constraints in order to reduce both space and time complexities.

Keywords: constraint programming, compression, data mining, table constraints

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Authors: Javier Sandoval Bustamante, Pardis Sheikhzadeh, Vijayanarasimha Hindupur Pakka

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In the pursuit of achieving net-zero carbon emissions, the integration of low carbon technologies into electricity distribution networks is paramount. This paper delves into the critical assessment of how the integration of low carbon technologies, such as heat pumps, electric vehicle chargers, and photovoltaic systems, impacts the infrastructure and operation of electricity distribution networks. The study employs rigorous methodologies, including power flow analysis and headroom analysis, to evaluate the feasibility and implications of integrating these technologies into existing distribution systems. Furthermore, the research utilizes Local Area Energy Planning (LAEP) methodologies to guide local authorities and distribution network operators in formulating effective plans to meet regional and national decarbonization objectives. Geospatial analysis techniques, coupled with building physics and electric energy systems modeling, are employed to develop geographic datasets aimed at informing the deployment of low carbon technologies at the local level. Drawing upon insights from the Local Energy Net Zero Accelerator (LENZA) project, a comprehensive case study illustrates the practical application of these methodologies in assessing the rollout potential of LCTs. The findings not only shed light on the technical feasibility of integrating low carbon technologies but also provide valuable insights into the broader transition towards a sustainable and electrified energy future. This paper contributes to the advancement of knowledge in power electrical engineering by providing empirical evidence and methodologies to support the integration of low carbon technologies into electricity distribution networks. The insights gained are instrumental for policymakers, utility companies, and stakeholders involved in navigating the complex challenges of energy transition and achieving long-term sustainability goals.

Keywords: energy planning, energy systems, digital twins, power flow analysis, headroom analysis

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Authors: Vibha Venkataramu, B. V. Venkatarama Reddy

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Natural river sand is the most preferred choice as fine aggregate in masonry mortars. Uncontrolled mining of sand from riverbeds for several decades has had detrimental effects on the environment. Several countries across the world have put strict restrictions on sand mining from riverbeds. However, in countries like India, the huge infrastructural boom has made the local construction industry to look for alternative materials to sand. This study aims at understanding the suitability of granulated blast furnace slag (GBS) as fine aggregates in masonry mortars. Apart from characterising the material properties of GBS, such as particle size distribution, pH, chemical composition, etc., of GBS, tests were performed on the mortars with GBS as fine aggregate. Additionally, the properties of five brick tall, stack bonded masonry prisms with various types of GBS mortars were studied. The mortars with mix proportions 1: 0: 6 (cement: lime: fine aggregate), 1: 1: 6, and 1: 0: 3 were considered for the study. Fresh and hardened properties of mortar, such as flow and compressive strength, were studied. To understand the behaviour of GBS mortars on masonry, tests such as compressive strength and flexure bond strength were performed on masonry prisms made with a different type of GBS mortars. Furthermore, the elastic properties of masonry with GBS mortars were also studied under compression. For comparison purposes, the properties of corresponding control mortars with natural sand as fine aggregate and masonry prisms with sand mortars were also studied under similar testing conditions. From the study, it was observed the addition of GBS negatively influenced the flow of mortars and positively influenced the compressive strength. The GBS mortars showed 20 to 25 % higher compressive strength at 28 days of age, compared to corresponding control mortars. Furthermore, masonry made with GBS mortars showed nearly 10 % higher compressive strengths compared to control specimens. But, the impact of GBS on the flexural strength of masonry was marginal.

Keywords: building materials, fine aggregate, granulated blast furnace slag in mortars, masonry properties

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Authors: Halkiopoulos Constantinos, Gkintoni Evgenia, Koutsopoulou Ioanna, Antonopoulou Hera

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E-sports and e-gaming have emerged in recent years since the increase in internet use have become universal and e-gamers are the new reality in our homes. The excessive involvement of young adults with e-sports has already been revealed and the adverse consequences have been reported in researches in the past few years, but the issue has not been fully studied yet. The present research is conducted in Greece and studies the psychological profile of video game players and provides information on personality traits, habits and emotional status that affect online gamers’ behaviors in order to help professionals and policy makers address the problem. Three standardized self-report questionnaires were administered to participants who were young male and female adults aged from 19-26 years old. The Profile of Mood States (POMS) scale was used to evaluate people’s perceptions of their everyday life mood; the personality features that can trace back to people’s habits and anticipated reactions were measured by Eysenck Personality Questionnaire (EPQ), and the Trait Emotional Intelligence Questionnaire (TEIQue) was used to measure which cognitive (gamers’ beliefs) and emotional parameters (gamers’ emotional abilities) mainly affected/ predicted gamers’ behaviors and leisure time activities?/ gaming behaviors. Data mining techniques were used to analyze the data, which resulted in machine learning algorithms that were included in the software package R. The research findings attempt to designate the effect of personality traits, emotional status and emotional intelligence influence and correlation with e-sports, gamers’ behaviors and help policy makers and stakeholders take action, shape social policy and prevent the adverse consequences on young adults. The need for further research, prevention and treatment strategies is also addressed.

Keywords: e-sports, e-gamers, personality traits, POMS, emotional intelligence, data mining, R

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Authors: Piotr Kacejko, Mariusz Duk, Miroslaw Wendeker

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This paper presents an adaptive controller to track the maximum power point of a photovoltaic modules (PV) under fast irradiation change on the city-bus roof. Photovoltaic systems have been a prominent option as an additional energy source for vehicles. The Municipal Transport Company (MPK) in Lublin has installed photovoltaic panels on its buses roofs. The solar panels turn solar energy into electric energy and are used to load the buses electric equipment. This decreases the buses alternators load, leading to lower fuel consumption and bringing both economic and ecological profits. A DC–DC boost converter is selected as the power conditioning unit to coordinate the operating point of the system. In addition to the conversion efficiency of a photovoltaic panel, the maximum power point tracking (MPPT) method also plays a main role to harvest most energy out of the sun. The MPPT unit on a moving vehicle must keep tracking accuracy high in order to compensate rapid change of irradiation change due to dynamic motion of the vehicle. Maximum power point track controllers should be used to increase efficiency and power output of solar panels under changing environmental factors. There are several different control algorithms in the literature developed for maximum power point tracking. However, energy performances of MPPT algorithms are not clarified for vehicle applications that cause rapid changes of environmental factors. In this study, an adaptive MPPT algorithm is examined at real ambient conditions. PV modules are mounted on a moving city bus designed to test the solar systems on a moving vehicle. Some problems of a PV system associated with a moving vehicle are addressed. The proposed algorithm uses a scanning technique to determine the maximum power delivering capacity of the panel at a given operating condition and controls the PV panel. The aim of control algorithm was matching the impedance of the PV modules by controlling the duty cycle of the internal switch, regardless of changes of the parameters of the object of control and its outer environment. Presented algorithm was capable of reaching the aim of control. The structure of an adaptive controller was simplified on purpose. Since such a simple controller, armed only with an ability to learn, a more complex structure of an algorithm can only improve the result. The presented adaptive control system of the PV system is a general solution and can be used for other types of PV systems of both high and low power. Experimental results obtained from comparison of algorithms by a motion loop are presented and discussed. Experimental results are presented for fast change in irradiation and partial shading conditions. The results obtained clearly show that the proposed method is simple to implement with minimum tracking time and high tracking efficiency proving superior to the proposed method. This work has been financed by the Polish National Centre for Research and Development, PBS, under Grant Agreement No. PBS 2/A6/16/2013.

Keywords: adaptive control, photovoltaic energy, city bus electric load, DC-DC converter

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Authors: Andrew R. Beatty

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The exploitation of Australia’s vast mineral wealth is regulated by a matrix of planning, environment and heritage legislation, and despite the desire for a ‘balance’ between economic, environmental and heritage values, Aboriginal objects and places are often detrimentally impacted by mining approvals. The Australian experience is not novel. There are other cases of clashes between the rights of traditional landowners and businesses seeking to exploit mineral or other resources on or beneath those lands, including in the United States, Canada, and Brazil. How one reconciles the rights of traditional owners with those of resource companies is an ongoing legal problem of general interest. In Australia, planning and environmental approvals for resource projects are ordinarily issued by State or Territory governments. Federal legislation such as the Aboriginal and Torres Strait Islander Heritage Protection Act 1984 (Cth) is intended to act as a safety net when State or Territory legislation is incapable of protecting Indigenous objects or places in the context of approvals for resource projects. This paper will analyse the context and effectiveness of legislation enacted to protect Indigenous heritage in the planning process. In particular, the paper will analyse how the statutory objects of such legislation need to be weighed against the statutory objects of competing legislation designed to facilitate and control resource exploitation. Using a current claim in the Federal Court of Australia for the protection of a culturally significant landscape as a case study, this paper will examine the challenges faced in ascribing value to cultural heritage within the wider context of environmental and planning laws. Our findings will reveal that there is an inherent difficulty in defining and weighing competing economic, environmental and heritage considerations. An alternative framework will be proposed to guide regulators towards making decisions that result in better protection of Indigenous heritage in the context of resource management.

Keywords: environmental law, heritage law, indigenous rights, mining

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Authors: Purevdolgor Luvsantseren, Ajnai Luvsan-Ish, Oyuntsetseg Sandag, Javzmaa Tsend, Akhit Tileubai, Baasandorj Chilhaasuren, Jargalbat Puntsagdash, Galbadrakh Chuluunbaatar

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One of the indicators of the quality of university services is student satisfaction. Aim: We aimed to study the level of satisfaction of students in the first year of premedical courses in the course of Medical Physics using the cluster method. Materials and Methods: In the framework of this goal, a questionnaire was collected from a total of 324 students who studied the medical physics course of the 1st course of the premedical course at the Mongolian National University of Medical Sciences. When determining the level of satisfaction, the answers were obtained on five levels of satisfaction: "excellent", "good", "medium", "bad" and "very bad". A total of 39 questionnaires were collected from students: 8 for course evaluation, 19 for teacher evaluation, and 12 for student evaluation. From the research, a database with 39 fields and 324 records was created. Results: In this database, cluster analysis was performed in MATLAB and R programs using the k-means method of data mining. Calculated the Hopkins statistic in the created database, the values are 0.88, 0.87, and 0.97. This shows that cluster analysis methods can be used. The course evaluation sub-fund is divided into three clusters. Among them, cluster I has 150 objects with a "good" rating of 46.2%, cluster II has 119 objects with a "medium" rating of 36.7%, and Cluster III has 54 objects with a "good" rating of 16.6%. The teacher evaluation sub-base into three clusters, there are 179 objects with a "good" rating of 55.2% in cluster II, 108 objects with an "average" rating of 33.3% in cluster III, and 36 objects with an "excellent" rating in cluster I of 11.1%. The sub-base of student evaluations is divided into two clusters: cluster II has 215 objects with an "excellent" rating of 66.3%, and cluster I has 108 objects with an "excellent" rating of 33.3%. Evaluating the resulting clusters with the Silhouette coefficient, 0.32 for the course evaluation cluster, 0.31 for the teacher evaluation cluster, and 0.30 for student evaluation show statistical significance. Conclusion: Finally, to conclude, cluster analysis in the model of the medical physics lesson “good” - 46.2%, “middle” - 36.7%, “bad” - 16.6%; 55.2% - “good”, 33.3% - “middle”, 11.1% - “bad” in the teacher evaluation model; 66.3% - “good” and 33.3% of “bad” in the student evaluation model.

Keywords: questionnaire, data mining, k-means method, silhouette coefficient

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Authors: S. Mondal, L. M. Olsen-Kettle, L. Gross

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Fracture propagation and damage evolution are extremely important for many industrial applications including mining industry, composite materials, earthquake simulations, hydraulic fracturing. The influence of pre-existing flaws and rock heterogeneity on the processes and mechanisms of rock fracture has important ramifications in many mining and reservoir engineering applications. We simulate the damage evolution and fracture propagation in an isotropic sandstone specimen containing a pre-existing 3-D surface flaw in different configurations under uniaxial compression. We apply a damage model based on the unified strength theory and solve the solid deformation and damage evolution equations using the Finite Element Method (FEM) with tetrahedron elements on unstructured meshes through the simulation software, eScript. Unstructured meshes provide higher geometrical flexibility and allow a more accurate way to model the varying flaw depth, angle, and length through locally adapted FEM meshes. The heterogeneity of rock is considered by initializing material properties using a Weibull distribution sampled over a cubic grid. In our model, we introduce a length scale related to the rock heterogeneity which is independent of the mesh size. We investigate the effect of parameters including the heterogeneity of the elastic moduli and geometry of the single flaw in the stress strain response. The generation of three typical surface cracking patterns, called wing cracks, anti-wing cracks and far-field cracks were identified, and these depend on the geometry of the pre-existing surface flaw. This model results help to advance our understanding of fracture and damage growth in heterogeneous rock with the aim to develop fracture simulators for different industry applications.

Keywords: finite element method, heterogeneity, isotropic damage, uniaxial compression

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Authors: Jayson Cheyne, David Butler, Iain Bomphray

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In recent years, lithium-ion batteries have been used increasingly for electric vehicles and large energy storage systems due to their high-power density and long lifespan. Despite this, thermal runaway remains a significant safety problem because of its uncontrollable and irreversible nature - which can lead to fires and explosions. In large-scale lithium-ion packs and modules, thermal runaway propagation between cells can escalate fire hazards and cause significant damage. Thus, safety measures are required to mitigate thermal runaway propagation. The current research explores composite phase change materials (PCM) containing expanded graphite (EG) for thermal runaway mitigation. PCMs are an area of significant interest for battery thermal management due to their ability to absorb substantial quantities of heat during phase change. Moreover, the introduction of EG can support heat transfer from the cells to the PCM (owing to its high thermal conductivity) and provide shape stability to the PCM during phase change. During the research, a thermal model was established for an array of 16 cylindrical cells to simulate heat dissipation with and without the composite PCM. Two conditions were modeled, including the behavior during charge/discharge cycles (i.e., throughout regular operation) and thermal runaway. Furthermore, parameters including cell spacing, composite PCM thickness, and EG weight percentage (WT%) were varied to establish the optimal material parameters for enabling thermal runaway mitigation and effective thermal management. Although numerical modeling is still ongoing, initial findings suggest that a 3mm PCM containing 15WT% EG can effectively suppress thermal runaway propagation while maintaining shape stability. The next step in the research is to validate the model through controlled experimental tests. Additionally, with the perceived fire safety concerns relating to PCM materials, fire safety tests, including UL-94 and Limiting Oxygen Index (LOI), shall be conducted to explore the flammability risk.

Keywords: battery safety, electric vehicles, phase change materials, thermal management, thermal runaway

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Authors: Gary Pattemore, Michael Edgar, Andrew Job, Marina Auad, Kathryn Job

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As critical commodities become more scarce, significant time and resources have been used to better understand complicated ore bodies and extract their full potential. These challenging ore bodies provide several pain points for geologists and engineers to overcome, poor handling of these issues flows downs stream to the processing plant affecting throughput rates and recovery. Many open cut mines utilise blast hole drilling to extract additional information to feed back into the modelling process. This method requires samples to be collected during or after blast hole drilling. Samples are then sent for assay with turnaround times varying from 1 to 12 days. This method is time consuming, costly, requires human exposure on the bench and collects elemental data only. To address this challenge, research has been undertaken to utilise hyperspectral imaging across a broad spectrum to scan samples, collars or take down hole measurements for minerals and moisture content and grade abundances. Automation of this process using unmanned vehicles and on-board processing reduces human in pit exposure to ensure ongoing safety. On-board processing allows data to be integrated into modelling workflows with immediacy. The preliminary results demonstrate numerous direct and indirect benefits from this new technology, including rapid and accurate grade estimates, moisture content and mineralogy. These benefits allow for faster geo modelling updates, better informed mine scheduling and improved downstream blending and processing practices. The paper presents recommendations for implementation of the technology in open cut mining environments.

Keywords: grade control, hyperspectral scanning, artificial intelligence, autonomous mining, machine learning

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Authors: Juliana A. Galhardi, Daniel M. Bonotto

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Coal is an important non-renewable energy source of and can be associated with radioactive elements. In Figueira city, Paraná state, Brazil, it was recorded high uranium activity near the coal mine that supplies a local thermoelectric power plant. In this context, the radon activity (Rn-222, produced by the Ra-226 decay in the U-238 natural series) was evaluated in groundwater, river water and effluents produced from the acid mine drainage in the coal reject dumps. The samples were collected in August 2013 and in February 2014 and analyzed at LABIDRO (Laboratory of Isotope and Hydrochemistry), UNESP, Rio Claro city, Brazil, using an alpha spectrometer (AlphaGuard) adjusted to evaluate the mean radon activity concentration in five cycles of 10 minutes. No radon activity concentration above 100 Bq.L-1, which was a previous critic value established by the World Health Organization. The average radon activity concentration in groundwater was higher than in surface water and in effluent samples, possibly due to the accumulation of uranium and radium in the aquifer layers that favors the radon trapping. The lower value in the river waters can indicate dilution and the intermediate value in the effluents may indicate radon absorption in the coal particles of the reject dumps. The results also indicate that the radon activities in the effluents increase with the sample acidification, possibly due to the higher radium leaching and the subsequent radon transport to the drainage flow. The water samples of Laranjinha River and Ribeirão das Pedras stream, which, respectively, supply Figueira city and receive the mining effluent, exhibited higher pH values upstream the mine, reflecting the acid mine drainage discharge. The radionuclides transport indicates the importance of monitoring their activity concentration in natural waters due to the risks that the radioactivity can represent to human health.

Keywords: radon, radium, acid mine drainage, coal

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Authors: Saloni Khandelwal

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The Aravalli hills are one of the oldest and most distinctive mountain chains of peninsular India spanning in around 692 Km. More than 60% of it falls in the state of Rajasthan and influences ecological equilibrium in about 30% of the state. Because of natural and human-induced activities, physical gaps in the Aravallis are increasing, new gaps are coming up, and its physical structure is changing. There are no strict regulations to protect and monitor the Aravallis and no comprehensive research and study has been done for the enhancement of ecosystem functions of these ranges. Through this study, various factors leading to Aravalli’s degradation are identified and its impacts on selected areas are analyzed. A literature study is done to identify factors responsible for the degradation. To understand the severity of the problem at the lowest level, two tehsils from different districts in Rajasthan, which are the most affected due to illegal mining and increasing physical gaps are selected for the study. Case-1 of three-gram panchayats in Kishangarh Tehsil of Ajmer district focuses on the expanding physical gaps in the Aravalli range, and case-2 of three-gram panchayats in Tijara Tehsil of Alwar district focuses on increasing illegal mining in the Aravalli range. For measuring the degradation, physical, biological and social indicators are identified through literature review and for both the cases analysis is done on the basis of these indicators. Primary survey and focus group discussions are done with villagers, mining owners, illegal miners, and various government officials to understand dependency of people on the Aravalli and its importance to them along with the impact of degradation on their livelihood and environment. From the analysis, it has been found that green cover is continuously decreasing in both cases, dense forest areas do not exist now, the groundwater table is depleting at a very fast rate, soil is losing its moisture resulting in low yield and shift in agriculture. Wild animals which were easily seen earlier are now extinct. Cattles of villagers are dependent on the forest area in the Aravalli range for food, but with a decrease in fodder, their cattle numbers are decreasing. There is a decrease in agricultural land and an increase in scrub and salt-affected land. Analysis of various national and state programmes, acts which were passed to conserve biodiversity has been done showing that none of them is helping much to protect the Aravalli. For conserving the Aravalli and its forest areas, regional level and local level initiatives are required and are proposed in this study. This study is an attempt to formulate conservation and management strategies for the Aravalli range. These strategies will help in improving biodiversity which can lead to the revival of its ecosystem functions. It will also help in curbing the pollution at the regional and local level. All this will lead to the sustainable development of the region.

Keywords: Aravalli, ecosystem, LULC, Rajasthan

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Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: Ayshan Gurbanova

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Despite based on the fact that drill bit which is the smallest part of bottom hole assembly costs only in between 10% and 15% of the total expenses made, they are the first equipment that is in contact with the formation itself. Hence, it is consequential to choose the appropriate type and dimension of drilling bit, which will prevent majority of problems by not demanding many tripping procedure. However, within the advance in technology, it is now seamless to be beneficial in the terms of many concepts such as subsequent time of operation, energy, expenditure, power and so forth. With the intention of applying the method to Azerbaijan, the field of Shallow Water Absheron Peninsula has been suggested, where the mainland has been located 15 km away from the wildcat wells, named as “NKX01”. It has the water depth of 22 m as indicated. In 2015 and 2016, the seismic survey analysis of 2D and 3D have been conducted in contract area as well as onshore shallow water depth locations. With the aim of indicating clear elucidation, soil stability, possible submersible dangerous scenarios, geohazards and bathymetry surveys have been carried out as well. Within the seismic analysis results, the exact location of exploration wells have been determined and along with this, the correct measurement decisions have been made to divide the land into three productive zones. In the term of the method, Electric Impulse Technology (EIT) is based on discharge energies of electricity within the corrosivity in rock. Take it simply, the highest value of voltages could be created in the less range of nano time, where it is sent to the rock through electrodes’ baring as demonstrated below. These electrodes- higher voltage powered and grounded are placed on the formation which could be obscured in liquid. With the design, it is more seamless to drill horizontal well based on the advantage of loose contact of formation. There is also no chance of worn ability as there are no combustion, mechanical power exist. In the case of energy, the usage of conventional drilling accounts for 1000 𝐽/𝑐𝑚3 , where this value accounts for between 100 and 200 𝐽/𝑐𝑚3 in EIT. Last but not the least, from the test analysis, it has been yielded that it achieves the value of ROP more than 2 𝑚/ℎ𝑟 throughout 15 days. Taking everything into consideration, it is such a fact that with the comparison of data analysis, this method is highly applicable to the fields of Azerbaijan.

Keywords: drilling, drill bit cost, efficiency, cost

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Sarah Niklas, Lynne Chester, Mark Diesendorf

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Geopolitical tensions, climate change and recent movements favouring a transformative shift in institutional power structures have influenced the economics of conventional energy supply for decades. This study takes a multi-dimensional approach to illustrate the potential of renewable energy (RE) technology to provide a pathway to a low-carbon economy driven by ecologically sustainable, independent and socially just energy. This comparative analysis identifies economic, political and social drivers that shaped the adoption of RE policy in two significantly different economies, Germany and Australia, with strong and weak commitments to RE respectively. Two complementary political-economy theories frame the document-based analysis. Régulation Theory, inspired by Marxist ideas and strongly influenced by contemporary economic problems, provides the background to explore the social relationships contributing the adoption of RE within the macro-economy. Varieties of Capitalism theory, a more recently developed micro-economic approach, examines the nature of state-firm relationships. Together these approaches provide a comprehensive lens of analysis. Germany’s energy policy transformed substantially over the second half of the last century. The development is characterised by the coordination of societal, environmental and industrial demands throughout the advancement of capitalist regimes. In the Fordist regime, mass production based on coal drove Germany’s astounding economic recovery during the post-war period. Economic depression and the instability of institutional arrangements necessitated the impulsive seeking of national security and energy independence. During the postwar Flexi-Fordist period, quality-based production, innovation and technology-based competition schemes, particularly with regard to political power structures in and across Europe, favoured the adoption of RE. Innovation, knowledge and education were institutionalized, leading to the legislation of environmental concerns. Lastly the establishment of government-industry-based coordinative programs supported the phase out of nuclear power and the increased adoption of RE during the last decade. Australia’s energy policy is shaped by the country’s richness in mineral resources. Energy policy largely served coal mining, historically and currently one of the most capital-intense industry. Assisted by the macro-economic dimensions of institutional arrangements, social and financial capital is orientated towards the export-led and strongly demand-oriented economy. Here energy policy serves the maintenance of capital accumulation in the mining sector and the emerging Asian economies. The adoption of supportive renewable energy policy would challenge the distinct role of the mining industry within the (neo)-liberal market economy. The state’s protective role of the mining sector has resulted in weak commitment to RE policy and investment uncertainty in the energy sector. Recent developments, driven by strong public support for RE, emphasize the sense of community in urban and rural areas and the emergence of a bottom-up approach to adopt renewables. Thus, political economy frameworks on both the macro-economic (Regulation Theory) and micro-economic (Varieties of Capitalism theory) scales can together explain the strong commitment to RE in Germany vis-à-vis the weak commitment in Australia.

Keywords: political economy, regulation theory, renewable energy, social relationships, energy transitions

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Authors: Rafayel K. Kostanyan

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The opportunities of use of metallic magnesium as a generator of hydrogen gas, as well as thermal and electric energy is presented in the paper. Various schemes of magnesium application are discussed and power characteristics of corresponding devices are presented. Economic estimation of hydrogen price obtained by different methods is made, including the use of magnesium as a source of hydrogen for transportation in comparison with gasoline. Details and prospects of our new inexpensive technology of magnesium production from magnesium hydroxide and magnesium bearing rocks (which are available worldwide and in Armenia) are analyzed. It is estimated the threshold cost of Mg production at which application of this metal in power engineering is economically justified.

Keywords: energy, electrodialysis, magnesium, new technology

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Authors: Remzi Yildirim, Fatih. V. Çelebi, H. Haldun Göktaş, A. Behzat Şahin

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This study is about a single component cylindrical structured lens with gradient curve which we used for bending laser beams. It operates under atmospheric conditions and bends the laser beam independent of temperature, pressure, polarity, polarization, magnetic field, electric field, radioactivity, and gravity. A single piece cylindrical lens that can bend laser beams is invented. Lenses are made of transparent, tinted or colored glasses and used for undermining or absorbing the energy of the laser beams.

Keywords: laser, bending, lens, light, nonlinear optics

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Authors: Remzi Yildirim, Fatih V. Çelebi, H. Haldun Göktaş, A. Behzat Şahin

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This study is about a single component cylindrical structured lens with gradient curve which we used for bending laser beams. It operates under atmospheric conditions and bends the laser beam independent of temperature, pressure, polarity, polarization, magnetic field, electric field, radioactivity, and gravity. A single piece cylindrical lens that can bend laser beams is invented. Lenses are made of transparent, tinted or colored glasses and used for undermining or absorbing the energy of the laser beams.

Keywords: laser, bending, lens, light, nonlinear optics

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Authors: Christin Koch, Andreas Winkel, Martin Kahlmeyer, Stefan Böhm

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Due to environmental regulations on greenhouse gas emissions and the depletion of fossil fuels, there is an increasing interest in electric vehicles.To maximize their driving range, batteries with high storage capacities are needed. In most electric cars, rechargeable lithium-ion batteries are used because of their high energy density. However, it has to be taken into account that these batteries generate a large amount of heat during the charge and discharge processes. This leads to a decrease in a lifetime and damage to the battery cells when the temperature exceeds the defined operating range. To ensure an efficient performance of the battery cells, reliable thermal management is required. Currently, the cooling is achieved by heat sinks (e.g., cooling plates) bonded to the battery cells with a thermally conductive adhesive (TCA) that directs the heat away from the components. Especially when large amounts of heat have to be dissipated spontaneously due to peak loads, the principle of heat conduction is not sufficient, so attention must be paid to the mechanism of heat storage. An efficient method to store thermal energy is the use of phase change materials (PCM). Through an isothermal phase change, PCM can briefly absorb or release thermal energy at a constant temperature. If the phase change takes place in the transition from solid to liquid, heat is stored during melting and is released to the ambient during the freezing process upon cooling. The presented work displays the great potential of thermally conductive adhesives filled with microencapsulated PCM to limit peak temperatures in battery systems. The encapsulation of the PCM avoids the effects of aging (e.g., migration) and chemical reactions between the PCM and the adhesive matrix components. In this study, microencapsulation has been carried out by in situ polymerization. The microencapsulated PCM was characterized by FT-IR spectroscopy, and the thermal properties were measured by DSC and laser flash method. The mechanical properties, electrical and thermal conductivity, and adhesive toughness of the TCA/PCM composite were also investigated.

Keywords: phase change material, microencapsulation, adhesive bonding, thermal management

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Authors: Branci Sarra, Branci Saadia

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Because of the multiplied data growth, many computer science tools have been developed to process and analyze these Big Data. High-performance computing architectures have been designed to meet the treatment needs of Big Data (view transaction processing standpoint, strategic, and tactical analytics). The purpose of this article is to provide a historical and global perspective on the recent trend of high-performance computing architectures especially what has a relation with Analytics and Data Mining.

Keywords: high performance computing, HPC, big data, data analysis

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Authors: Kristýna Weissová

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This study is focused on two selected model taxa of invertebrates - Hymenoptera: Aculeata and Lepidopterawithnocturnalactivity, recordedatthesitesof lignite dumps and their surroundings in the North Bohemian Lignite Basin, Czech Republic. There search was conducted on 10 landfills, 3 study areas were determined on each landfill - primary and secondary succession and recultivation. A total of 3,202 individuals belonging to 232 species and 17 families of sagebrushinsects were collected. died, 74%of the species occurred on the primary succes sionare as, that is 2x more species than on the reclaimed areas. Of the total number of species and on all areas, 60 rare species were recorded - 29 vulnerable, 21 endangered, 8 critically endangered, and 2 extinct The areas of primary succession were again confirmed to be the richest in terms of rare species, hosting 39 rare species of Hymenoptera: Aculeata. In addition, bothextinct species were represented only on plots of primary succession. The family Crabronidae had the largestre presentation of species on theareasofleft primary succession, the family Halictidae was the most represented on the reclaimed areas and areas of secondary succession. A total of 3,634 moths were collected, assigned to 262 species and 10 families. A similar number of species occurred on the primary succession and reclaimed areas, but the reclaimed area had a greater abundance. Secondary successionsiteshostedha lf as many species and alsocontainedlow abundance compared to other management types. The results show that there claimed areas host a numerically larger group and more species of moths than the successionalareas. Rare species did not occur at any site. A higher number of days in locations without water bodies, wetland vegetation, and locations with a highre presentation of woody species. It is advisable to combine individual types of landscape management in such a way as to create a colorfulmosaic that supports biodiversity. In particular, we recommend incorporating natural successionintoreclamation plans, which is a refuge for many rare species of invertebrates, which has not yetbeenroutinely and purposefully practiced.

Keywords: hymenoptera: aculeata, lepidoptera, reclamation, succession, post-mining ara

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Authors: Jiri Beranovsky, Jaroslav Knapek, Tomas Kralik, Kamila Vavrova

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The paper deals with the results of research focused on the complex aspects of the use of intentionally grown biomass on agricultural land for the production of solid biofuels as an alternative for individual household heating. . The study primarily deals with the analysis of CO2 emissions of the logistics cycle of biomass for the production of energy pellets. Growing, harvesting, transport and storage are evaluated in the pellet production cycle. The aim is also to take into account the consumption profile during the year in terms of heating of common family houses, which are typical end-market segment for these fuels. It is assumed that in family houses, bio-pellets are able to substitute typical fossil fuels, such as brown coal and old wood burning heating devices and also electric boilers. One of the competing technology with the pellets are heat pumps. The results show the CO2 emissions related with considered fuels and technologies for their utilization. Comparative analysis is aimed biopellets from intentionally grown biomass, brown coal, natural gas and electricity used in electric boilers and heat pumps. Analysis combines CO2 emissions related with individual fuels utilization with costs of these fuels utilization. Cost of biopellets from intentionally grown biomass is derived from the economic models of individual energy crop plantations. At the same time, the restrictions imposed by EU legislation on Ecodesign's fuel and combustion equipment requirements and NOx emissions are discussed. Preliminary results of analyzes show that to achieve the competitiveness of pellets produced from specifically grown biomass, it would be necessary to either significantly ecological tax on coal (from about 0.3 to 3-3.5 EUR/GJ), or to multiply the agricultural subsidy per area. In addition to the Czech Republic, the results are also relevant for other countries, such as Bulgaria and Poland, which also have a high proportion of solid fuels for household heating.

Keywords: CO2 emissions, heating costs, energy crop, pellets, brown coal, heat pumps, economical evaluation

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Authors: Piotr-Robert Lazik, Harald Garrecht

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Many concrete technologists are looking for a solution to replace Fly Ashes that would be unavailable in a few years as an element that occurs as a major component of many types of concrete. The importance of such component is clear - it saves cement and reduces the amount of CO₂ in the atmosphere that occurs during cement production. Wood Ashes from electrostatic filter can be used as a valuable substitute in concrete. The laboratory investigations showed that the wood ash concrete had a compressive strength comparable to coal fly ash concrete. These results indicate that wood ash can be used to manufacture normal concrete.

Keywords: wood ashes, fly ashes, electric filter, replacement, concrete technology

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Authors: Leila Motamed-Jahromi, Mohsen Hatami, Alireza Keshavarz

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This research aims at obtaining the equations of pulse propagation in nonlinear plasmonic waveguides created with As₂S₃ chalcogenide materials. Via utilizing Helmholtz equation and first-order perturbation theory, two components of electric field are determined within frequency domain. Afterwards, the equations are formulated in time domain. The obtained equations include two coupled differential equations that considers nonlinear dispersion.

Keywords: nonlinear optics, plasmonic waveguide, chalcogenide, propagation equation

Procedia PDF Downloads 414