Search results for: sustainable energy solutions

Authors: Shreyas Kumar, Mili Shangari

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Integrating artificial intelligence (AI) in the cyber insurance sector represents a significant advancement, offering the potential to revolutionize risk assessment, fraud detection, and claims processing. However, this integration introduces a range of regulatory and economic challenges that must be addressed to ensure responsible and effective deployment of AI technologies. This paper examines the multifaceted regulatory landscape governing AI in cyber insurance and explores the economic implications of compliance, innovation, and market dynamics. AI's capabilities in processing vast amounts of data and identifying patterns make it an invaluable tool for insurers in managing cyber risks. Yet, the application of AI in this domain is subject to stringent regulatory scrutiny aimed at safeguarding data privacy, ensuring algorithmic transparency, and preventing biases. Regulatory bodies, such as the European Union with its General Data Protection Regulation (GDPR), mandate strict compliance requirements that can significantly impact the deployment of AI systems. These regulations necessitate robust data protection measures, ethical AI practices, and clear accountability frameworks, all of which entail substantial compliance costs for insurers. The economic implications of these regulatory requirements are profound. Insurers must invest heavily in upgrading their IT infrastructure, implementing robust data governance frameworks, and training personnel to handle AI systems ethically and effectively. These investments, while essential for regulatory compliance, can strain financial resources, particularly for smaller insurers, potentially leading to market consolidation. Furthermore, the cost of regulatory compliance can translate into higher premiums for policyholders, affecting the overall affordability and accessibility of cyber insurance. Despite these challenges, the potential economic benefits of AI integration in cyber insurance are significant. AI-enhanced risk assessment models can provide more accurate pricing, reduce the incidence of fraudulent claims, and expedite claims processing, leading to overall cost savings and increased efficiency. These efficiencies can improve the competitiveness of insurers and drive innovation in product offerings. However, balancing these benefits with regulatory compliance is crucial to avoid legal penalties and reputational damage. The paper also explores the potential risks associated with AI integration, such as algorithmic biases that could lead to unfair discrimination in policy underwriting and claims adjudication. Regulatory frameworks need to evolve to address these issues, promoting fairness and transparency in AI applications. Policymakers play a critical role in creating a balanced regulatory environment that fosters innovation while protecting consumer rights and ensuring market stability. In conclusion, the integration of AI in cyber insurance presents both regulatory and economic challenges that require a coordinated approach involving regulators, insurers, and other stakeholders. By navigating these challenges effectively, the industry can harness the transformative potential of AI, driving advancements in risk management and enhancing the resilience of the cyber insurance market. This paper provides insights and recommendations for policymakers and industry leaders to achieve a balanced and sustainable integration of AI technologies in cyber insurance.

Keywords: artificial intelligence (AI), cyber insurance, regulatory compliance, economic impact, risk assessment, fraud detection, cyber liability insurance, risk management, ransomware

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Authors: Kai Zhang, Xi Jiang

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Effect of fuel variabilities on premixed combustion of bio-syngas mixtures is of great importance in bio-syngas utilisation. The uncertainties of concentrations of fuel constituents such as H2, CO and CH4 may lead to unpredictable combustion performances, combustion instabilities and hot spots which may deteriorate and damage the combustion hardware. Numerical modelling and simulations can assist in understanding the behaviour of bio-syngas combustion with pre-defined species concentrations, while the evaluation of variabilities of concentrations is expensive. To be more specific, questions such as ‘what is the burning velocity of bio-syngas at specific equivalence ratio?’ have been answered either experimentally or numerically, while questions such as ‘what is the likelihood of burning velocity when precise concentrations of bio-syngas compositions are unknown, but the concentration ranges are pre-described?’ have not yet been answered. Uncertainty quantification (UQ) methods can be used to tackle such questions and assess the effects of fuel compositions. An efficient probabilistic UQ method based on Polynomial Chaos Expansion (PCE) techniques is employed in this study. The method relies on representing random variables (combustion performances) with orthogonal polynomials such as Legendre or Gaussian polynomials. The constructed PCE via Galerkin Projection provides easy access to global sensitivities such as main, joint and total Sobol indices. In this study, impacts of fuel compositions on combustion (adiabatic flame temperature and laminar flame speed) of bio-syngas fuel mixtures are presented invoking this PCE technique at several equivalence ratios. High-pressure effects on bio-syngas combustion instability are obtained using detailed chemical mechanism - the San Diego Mechanism. Guidance on reducing combustion instability from upstream biomass gasification process is provided by quantifying the significant contributions of composition variations to variance of physicochemical properties of bio-syngas combustion. It was found that flame speed is very sensitive to hydrogen variability in bio-syngas, and reducing hydrogen uncertainty from upstream biomass gasification processes can greatly reduce bio-syngas combustion instability. Variation of methane concentration, although thought to be important, has limited impacts on laminar flame instabilities especially for lean combustion. Further studies on the UQ of percentage concentration of hydrogen in bio-syngas can be conducted to guide the safer use of bio-syngas.

Keywords: bio-syngas combustion, clean energy utilisation, fuel variability, PCE, targeted uncertainty reduction, uncertainty quantification

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Authors: Siri Marthe Arbo, Afaf Saai, Sture Sørli, Mette Nedreberg

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This work aims to establish a reliable approach for optimizing a Laser Metal Deposition (LMD) process for a critical maritime component, based on the material properties and structural performance required by the maritime industry. The component of interest is a water jet impeller, for which specific requirements for material properties are defined. The developed approach is based on the assessment of the effects of LMD process parameters on microstructure and material performance of standard AM 2205 duplex stainless steel powder. Duplex stainless steel offers attractive properties for maritime applications, combining high strength, enhanced ductility and excellent corrosion resistance due to the specific amounts of ferrite and austenite. These properties are strongly affected by the microstructural characteristics in addition to microstructural defects such as porosity and welding defects, all strongly influenced by the chosen LMD process parameters. In this study, the influence of deposition speed and heat input was evaluated. First, the influences of deposition speed and heat input on the microstructure characteristics, including ferrite/austenite fraction, amount of porosity and welding defects, were evaluated. Then, the achieved mechanical properties were evaluated by standard testing methods, measuring the hardness, tensile strength and elongation, bending force and impact energy. The measured properties were compared to the requirements of the water jet impeller. The results show that the required amounts of ferrite and austenite can be achieved directly by the LMD process without post-weld heat treatments. No intermetallic phases were observed in the material produced by the investigated process parameters. A high deposition speed was found to reduce the ductility due to the formation of welding defects. An increased heat input was associated with reduced strength due to the coarsening of the ferrite/austenite microstructure. The microstructure characterizations and measured mechanical performance demonstrate the great potential of the LMD process and generate a valuable database for the optimization of the LMD process for duplex stainless steels.

Keywords: duplex stainless steel, laser metal deposition, process optimization, microstructure, mechanical properties

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Authors: Pelin Atav, Gözen Güner Aktaş, Nur Ayalp

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Today’s world has started to develop design process within an interdisciplinary working environment. There is an aim of creating the most permanent design for the future. While satisfying people’s needs, environment and people relationships should be considered. When this relationship was considered for the future, the sustainability term comes to mind. The term Sustainability has been adapted very well by designer and architects. It is also one of the main and significant parts of the design process. As the education process cultivates the future professionals, the awareness of those concepts in the education process has a vital importance. The question is stated as thus: Are the 3rd and 4th year design studio students, familiar and sensitive to the concept of sustainability in the TOBB ETU University Interior Design Studio. Design studios and the instructors should be taken into consideration while this sustainability term is taught. The term "Sustainability" can not be learned without making any application in the actual real world. While students make this study, They can have the chance to search the topic of sustainability step by step. Due to having various extent, sustainability term becomes quite a comprehensive issue. In order not to create negative consequences, designers and architects work by adapting this term. In terms of material, construction process, lighting, building service, furniture, systems that are used, energy consumption issues that are considered and creating positive drawbacks for the future are aimed. This research is aimed at how university education shapes designer’s works in terms of sustainability. By giving a project that is a main interest in the field of sustainability, students are expected to reach well-thought-of results and analysis. Project process were conducted with instructor and student studies together. According to critics from their instructors, students try to product well- designed results. TOBB University was choosen as a research area situated in Ankara in Turkey. Third and fourth class (interior designer/architect department) students who are from the Faculty of Fine Arts Design and Architecture are the subject group selected for this study. Aim of this study is demonstrating sustainability as a term having application in design studio. Thus, awareness of sustainability terms will be evaluated and its development process in the university education will be observed. Consequently, results that are expected is how sustainability term is conducted in project and for the sustainability term awareness in design studios and their projects have been sufficient or not.

Keywords: design education, design process, interior design studios, sustainability

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Authors: Kali Prasad Sarma

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Indiscriminate disposal of municipal solid waste (MSW) in open dumping site is a common scenario in developing countries like India which poses a risk to the environment as well as human health. The objective of the present investigation was to find out the concentration of heavy metals (Pb, Cr, Ni, Mn, Zn, Cu, and Cd) and other physicochemical parameters of leachate and soil collected from an open dumping site of Tezpur town, Assam, India and its associated potential ecological risk. Tezpur is an urban agglomeration coming under the category of Class I UAs/Towns with a population of 105,377 as per data released by Government of India for Census 2011. Impact of the leachate on the groundwater was also addressed in our study. The concentrations of heavy metals were determined using ICP-OES. Energy dispersive X-Ray (SEM-EDS) microanalysis was also conducted to see the presence of the studied metals in the soil. X-Ray diffraction analysis (XRD) and Fourier Transform Infrared (FTIR) spectroscopy were also used to identify dominant minerals present in the soil samples. The trend of measured heavy metals in the soil samples was found in the following order: Mn > Pb > Cu > Zn > Cr > Ni > Cd. The assessment of heavy metal contamination in the soil was carried out by calculating enrichment factor (EF), geo-accumulation index (Igeo), contamination factor (Cfi), degree of contamination (Cd), pollution load index (PLI) and ecological risk factor (Eri). The study showed that the concentrations of Pb, Cu, and Cd were much higher than their respective average shale value and the EF of the soil samples depicted very severe enrichment for Pb, Cu, and Cd; moderate enrichment for Cr and Zn. Calculated Igeo values indicated that the soil is moderate to strongly contaminated with Pb and uncontaminated to moderately contaminated with Cd and Cu. The Cfi value for Pb indicates a very strong contamination level of the metal in the soil. The Cfi values for Cu and Cd were 2.37 and 1.65 respectively indicating moderate contamination level. To apportion the possible sources of heavy metal contamination in soil, principal components analysis (PCA) has been adopted. From the leachate, heavy metals are accumulated at the dumping site soil which could easily percolate through the soil and reach the groundwater. The possible relation of groundwater contamination due to leachate percolation was examined by analyzing the heavy metal concentrations in groundwater with respect to distance from the dumping site. The concentrations of Cd and Pb in groundwater (at a distance of 20m from dumping site) exceeded the permissible limit for drinking water as set by WHO. Occurrence of elevated concentration of potentially toxic heavy metals such as Pb and Cd in groundwater and soil are much environmental concern as it is detrimental to human health and ecosystem.

Keywords: groundwater, heavy metal contamination, leachate, open dumping site

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Authors: Imran Hanif, Amanda Persdotter, Sedigheh Bigdeli, Jesper Liske, Torbjorn Jonsson

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Renewable fuels such as biomass/waste for power production is an attractive alternative to fossil fuels in order to achieve a CO₂ -neutral power generation. However, the combustion results in the release of corrosive species. This puts high demands on the corrosion resistance of the alloys used in the boiler. Stainless steels containing nickel and/or nickel containing coatings are regarded as suitable corrosion resistance material especially in the superheater regions. However, the corrosive environment in the boiler caused by the presence of water vapour and reactive alkali very rapidly breaks down the primary protection, i.e., the Cr-rich oxide scale formed on stainless steels. The lifetime of the components, therefore, relies on the properties of the oxide scale formed after breakaway, i.e., the secondary protection. The aim of the current study is to investigate the role of varying nickel content (0–82%) on the high-temperature corrosion of model alloys with 18% Cr (Fe in balance) in the laboratory mimicking industrial conditions at 600°C. The influence of nickel is investigated on both the primary protection and especially the secondary protection, i.e., the scale formed after breakaway, during the oxidation/corrosion process in the dry O₂ (primary protection) and more aggressive environment such as H₂O, K₂CO₃ and KCl (secondary protection). All investigated alloys experience a very rapid loss of the primary protection, i.e., the Cr-rich (Cr, Fe)₂O₃, and the formation of secondary protection in the aggressive environments. The microstructural investigation showed that secondary protection of all alloys has a very similar microstructure in all more aggressive environments consisting of an outward growing iron oxide and inward growing spinel-oxide (Fe, Cr, Ni)₃O₄. The oxidation kinetics revealed that it is possible to influence the protectiveness of the scale formed after breakaway (secondary protection) through the amount of nickel in the alloy. The difference in oxidation kinetics of the secondary protection is linked to the microstructure and chemical composition of the complex spinel-oxide. The detailed microstructural investigations were carried out using the extensive analytical techniques such as electron back scattered diffraction (EBSD), energy dispersive X-rays spectroscopy (EDS) via the scanning and transmission electron microscopy techniques and results are compared with the thermodynamic calculations using the Thermo-Calc software.

Keywords: breakaway corrosion, EBSD, high-temperature oxidation, SEM, TEM

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Authors: Rafid Mueen, Konstantin Konstantinov, Micheal Lerch, Zhenxiang Cheng

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In the past two decades, the concern for skin protection from ultraviolet (UV) radiation has attracted considerable attention due to the increased intensity of UV rays that can reach the Earth’s surface as a result of the breakdown of ozone layer. Recently, UVA has also attracted attention, since, in comparison to UVB, it can penetrate deeply into the skin, which can result in significant health concerns. Sunscreen agents are one of the significant tools to protect the skin from UV irradiation, and it is either organic or in organic. Developing of inorganic UV blockers is essential, which provide efficient UV protection over a wide spectrum rather than organic filters. Furthermore inorganic UV blockers are good comfort, and high safety when applied on human skin. Inorganic materials can absorb, reflect, or scatter the ultraviolet radiation, depending on their particle size, unlike the organic blockers, which absorb the UV irradiation. Nowadays, most inorganic UV-blocking filters are based on (TiO2) and ZnO). ZnO can provide protection in the UVA range. Indeed, ZnO is attractive for in sunscreen formulization, and this relates to many advantages, such as its modest refractive index (2.0), absorption of a small fraction of solar radiation in the UV range which is equal to or less than 385 nm, its high probable recombination of photogenerated carriers (electrons and holes), large direct band gap, high exciton binding energy, non-risky nature, and high tendency towards chemical and physical stability which make it transparent in the visible region with UV protective activity. A significant issue for ZnO use in sunscreens is that it can generate ROS in the presence of UV light because of its photocatalytic activity. Therefore it is essential to make a non-photocatalytic material through modification by other metals. Several efforts have been made to deactivate the photocatalytic activity of ZnO by using inorganic surface modifiers. The doping of ZnO by different metals is another way to modify its photocatalytic activity. Recently, successful doping of ZnO with different metals such as Ce, La, Co, Mn, Al, Li, Na, K, and Cr by various procedures, such as a simple and facile one pot water bath, co-precipitation, hydrothermal, solvothermal, combustion, and sol gel methods has been reported. These materials exhibit greater performance than undoped ZnO towards increasing the photocatalytic activity of ZnO in visible light. Therefore, metal doping can be an effective technique to modify the ZnO photocatalytic activity. However, in the current work, we successfully reduce the photocatalytic activity of ZnO through Na doped ZnO fabricated via sol-gel and hydrothermal methods.

Keywords: photocatalytic, ROS, UVA, ZnO

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Authors: Jigg Pelayo, Ricardo Villar, Einstine Opiso

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The rampant and unintended spread of urban areas resulted in increasing artificial component features in the land cover types of the countryside and bringing forth the urban heat island (UHI). This paved the way to wide range of negative influences on the human health and environment which commonly relates to air pollution, drought, higher energy demand, and water shortage. Land cover type also plays a relevant role in the process of understanding the interaction between ground surfaces with the local temperature. At the moment, the depiction of the land surface temperature (LST) at city/municipality scale particularly in certain areas of Misamis Oriental, Philippines is inadequate as support to efficient mitigations and adaptations of the surface urban heat island (SUHI). Thus, this study purposely attempts to provide application on the Landsat 8 satellite data and low density Light Detection and Ranging (LiDAR) products in mapping out quality automated LST model and crop-level land cover classification in a local scale, through theoretical and algorithm based approach utilizing the principle of data analysis subjected to multi-dimensional image object model. The paper also aims to explore the relationship between the derived LST and land cover classification. The results of the presented model showed the ability of comprehensive data analysis and GIS functionalities with the integration of object-based image analysis (OBIA) approach on automating complex maps production processes with considerable efficiency and high accuracy. The findings may potentially lead to expanded investigation of temporal dynamics of land surface UHI. It is worthwhile to note that the environmental significance of these interactions through combined application of remote sensing, geographic information tools, mathematical morphology and data analysis can provide microclimate perception, awareness and improved decision-making for land use planning and characterization at local and neighborhood scale. As a result, it can aid in facilitating problem identification, support mitigations and adaptations more efficiently.

Keywords: LiDAR, OBIA, remote sensing, local scale

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Authors: Aubrey Langeland, Richard Neitzel, Kowit Nambunmee

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Electronic waste, ‘e-waste’, refers generally to discarded electronics and electrical equipment, including products from cell phones and laptops to wires, batteries and appliances. While e-waste represents a transformative source of income in low- and middle-income countries, informal e-waste workers use rudimentary methods to recover materials, simultaneously releasing harmful chemicals into the environment and creating a health hazard for themselves and surrounding communities. Valuable materials such as precious metals, copper, aluminum, ferrous metals, plastic and components are recycled from e-waste. However, persistent organic pollutants such as polychlorinated biphenyls (PCBs) and some polybrominated diphenyl ethers (PBDEs), and heavy metals are toxicants contained within e-waste and are of great concern to human and environmental health. The current study seeks to evaluate the environmental contamination resulting from informal e-waste recycling in a predominantly agricultural community in northeastern Thailand. To accomplish this objective, five types of environmental samples were collected and analyzed for concentrations of eight metals commonly associated with e-waste recycling during the period of July 2016 through July 2017. Rice samples from the community were collected after harvest and analyzed using inductively coupled plasma mass spectrometry (ICP-MS) and gas furnace atomic spectroscopy (GF-AS). Soil samples were collected and analyzed using methods similar to those used in analyzing the rice samples. Surface water samples were collected and analyzed using absorption colorimetry for three heavy metals. Environmental air samples were collected using a sampling pump and matched-weight PVC filters, then analyzed using Inductively Coupled Argon Plasma-Atomic Emission Spectroscopy (ICAP-AES). Finally, surface wipe samples were collected from surfaces in homes where e-waste recycling activities occur and were analyzed using ICAP-AES. Preliminary1 results indicate that some rice samples have concentrations of lead and cadmium significantly higher than limits set by the United States Department of Agriculture (USDA) and the World Health Organization (WHO). Similarly, some soil samples show levels of copper, lead and cadmium more than twice the maximum permissible level set by the USDA and WHO, and significantly higher than other areas of Thailand. Surface water samples indicate that areas near e-waste recycling activities, particularly the burning of e-waste products, result in increased levels of cadmium, lead and copper in surface waters. This is of particular concern given that many of the surface waters tested are used in irrigation of crops. Surface wipe samples measured concentrations of metals commonly associated with e-waste, suggesting a danger of ingestion of metals during cooking and other activities. Of particular concern is the relevance of surface contamination of metals to child health. Finally, air sampling showed that the burning of e-waste presents a serious health hazard to workers and the environment through inhalation and deposition2. Our research suggests a need for improved methods of e-waste recycling that allows workers to continue this valuable revenue stream in a sustainable fashion that protects both human and environmental health. 1Statistical analysis to be finished in October 2017 due to follow-up field studies occurring in July and August 2017. 2Still awaiting complete analytic results.

Keywords: e-waste, environmental contamination, informal recycling, metals

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Authors: Moustafa Osman Mohammed

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Construction industry, as one of the main contributor in depletion of natural resources, influences climate change. This paper discusses incremental and evolutionary development of the proposed models for optimization of a life-cycle analysis to explicit strategy for evaluation systems. The main categories are virtually irresistible for introducing uncertainties, uptake composite structure model (CSM) as environmental management systems (EMSs) in a practice science of evaluation small and medium-sized enterprises (SMEs). The model simplified complex systems to reflect nature systems’ input, output and outcomes mode influence “framework measures” and give a maximum likelihood estimation of how elements are simulated over the composite structure. The traditional knowledge of modeling is based on physical dynamic and static patterns regarding parameters influence environment. It unified methods to demonstrate how construction systems ecology interrelated from management prospective in procedure reflects the effect of the effects of engineering systems to ecology as ultimately unified technologies in extensive range beyond constructions impact so as, - energy systems. Sustainability broadens socioeconomic parameters to practice science that meets recovery performance, engineering reflects the generic control of protective systems. When the environmental model employed properly, management decision process in governments or corporations could address policy for accomplishment strategic plans precisely. The management and engineering limitation focuses on autocatalytic control as a close cellular system to naturally balance anthropogenic insertions or aggregation structure systems to pound equilibrium as steady stable conditions. Thereby, construction systems ecology incorporates engineering and management scheme, as a midpoint stage between biotic and abiotic components to predict constructions impact. The later outcomes’ theory of environmental obligation suggests either a procedures of method or technique that is achieved in sustainability impact of construction system ecology (SICSE), as a relative mitigation measure of deviation control, ultimately.

Keywords: sustainability, environmental impact assessment, environemtal management, construction ecology

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Authors: Mustafa Metin Donma, Orkide Donma

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Obesity is a disease with an ever-increasing prevalence throughout the world. The metabolic network associated with obesity is very complicated. In metabolic syndrome (MetS), it becomes even more difficult to understand. Within this context, hormones, cytokines, and many others participate in this complex matrix. The collaboration among all of these parameters is a matter of great wonder. Cortisol, as a stress hormone, is closely associated with obesity. Thyroid hormones are involved in the regulation of energy as well as glucose metabolism with all of its associates. Fetuin A is known for years; however, the involvement of this parameter in obesity discussions is rather new. Recently, it has been defined as one of the new generation markers of obesity. In this study, the aim was to introduce complex interactions among all to be able to make clear comparisons, at least for a part of this complicated matter. Morbid obese (MO) children participated in the study. Two groups with 46 MO children and 43 with MetS were constituted. All children included in the study were above 99th age- and sex-adjusted body mass index (BMI) percentiles according to World Health Organization criteria. Forty-three morbid obese children in the second group had also MetS components. Informed consent forms were filled by the parents of the participants. The institutional ethics committee has given approval for the study protocol. Data as well as the findings of the study were evaluated from a statistical point of view. Two groups were matched for their age and gender compositions. Significantly higher body mass index (BMI), waist circumference, thyrotropin, and insulin values were observed in the MetS group. Triiodothyronine concentrations did not differ between the groups. Elevated levels for thyroxin, cortisol, and fetuin-A were detected in the MetS group compared to the first group (p > 0.05). In MO MetS- group, cortisol was correlated with thyroxin and fetuin-A (p < 0.05). In the MO MetS+ group, none of these correlations were present. Instead, a correlation between cortisol and thyrotropin was found (p < 0.05). In conclusion, findings have shown that cortisol was the key player in severely obese children. The association of this hormone with the participants of thyroid hormone metabolism was quite important. The lack of association with fetuin A in the morbid obese MetS+ group has suggested the possible interference of MetS components in the behavior of this new generation obesity marker. The most remarkable finding of the study was the unique correlation between cortisol and thyrotropin in the morbid obese MetS+ group, suggesting that thyrotropin may serve as a target along with cortisol in the morbid obese MetS+ group. This association may deserve specific attention during the development of remedies against MetS in the pediatric population.

Keywords: children, cortisol, fetuin A, morbid obesity, thyrotropin

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Authors: Salomão Manuel Francisco, Manuel António Salgueiro Da Silva, Bento Filipe Barreiras Pinto Cavadas, Teresa Monteiro Seixas

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In bachelor's degrees in Physics Education framework in Angola, and to a certain extent, within the community of Portuguese language countries (CPLP), teaching methodologies rely heavily on theoretical memorization and mathematical demonstrations. This approach often discourages students, particularly the female population, as the reliance on theoretical mathematical demonstrations generates the perception of Physics as an arduous, challenging discipline. To address this challenge and recognize the value of practical application as an evaluative criterion of material truth, we propose a practical activity in Environmental Physics that will be shared with Angolan higher education teachers, who will receive full scaffolding and support from the authors. These teachers, adopting and developing similar activities in a classroom setting, will contribute to the environmental education framework as well. Additionally, this work aligns with different goals of UNESCO's 2030 agenda, namely, specifically, goals 4, 5, 7, 11, 13, and 17. The experimental activity developed in this work is centered around the demonstration of the photovoltaic effect and its application for renewable energy production. The first objective of the activity is to study the variation of electrical power supplied by a photovoltaic system (PV) to an electrical circuit as the angle of light incidence changes. Students can observe that the power supplied to the circuit is greater when light rays fall perpendicularly on the PV. However, as the angle of incidence increases, resulting in a larger area covered by the light rays, the power supplied to the circuit decreases due to lower irradiance. The second objective is to demonstrate that the power output can be maximized by adjusting the circuit load resistance at each irradiance value. In these two parts of the activity, students can analyze experimental data taking into account the irradiance law and the equivalent circuit description of a PV cell. Through detailed data analysis, students are also expected to assess the effects of temperature on PV efficiency degradation and the efficiency enhancement provided by light concentration mechanisms. As a third objective, students can explore how the color of incident light affects the PV output power, considering the quantum nature of light and its interaction with the PV system.

Keywords: experiments, irradiation law, physic teaching, photovoltaic effect

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Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

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Authors: Syed Asif Hassan, Tabrej Khan

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Multiple sclerosis (MS) is a chronic demyelinating autoimmune disorder, of the central nervous system (CNS). In the present scenario, the current therapies either do not halt the progression of the disease or have side effects which limit the usage of current Disease Modifying Therapies (DMTs) for a longer period of time. Therefore, keeping the current treatment failure schema, we are focusing on screening novel analogues of the available DMTs that specifically bind and inhibit the Sphingosine1-phosphate receptor1 (S1PR1) thereby hindering the lymphocyte propagation toward CNS. The novel drug-like analogs molecule will decrease the frequency of relapses (recurrence of the symptoms associated with MS) with higher efficacy and lower toxicity to human system. In this study, an integrated approach involving ligand-based virtual screening protocol (Ultrafast Shape Recognition with CREDO Atom Types (USRCAT)) to identify the non-toxic drug like analogs of the approved DMTs were employed. The potency of the drug-like analog molecules to cross the Blood Brain Barrier (BBB) was estimated. Besides, molecular docking and simulation using Auto Dock Vina 1.1.2 and GOLD 3.01 were performed using the X-ray crystal structure of Mtb LprG protein to calculate the affinity and specificity of the analogs with the given LprG protein. The docking results were further confirmed by DSX (DrugScore eXtented), a robust program to evaluate the binding energy of ligands bound to the ligand binding domain of the Mtb LprG lipoprotein. The ligand, which has a higher hypothetical affinity, also has greater negative value. Further, the non-specific ligands were screened out using the structural filter proposed by Baell and Holloway. Based on the USRCAT, Lipinski’s values, toxicity and BBB analysis, the drug-like analogs of fingolimod and BG-12 showed that RTL and CHEMBL1771640, respectively are non-toxic and permeable to BBB. The successful docking and DSX analysis showed that RTL and CHEMBL1771640 could bind to the binding pocket of S1PR1 receptor protein of human with greater affinity than as compared to their parent compound (Fingolimod). In this study, we also found that all the drug-like analogs of the standard MS drugs passed the Bell and Holloway filter.

Keywords: antagonist, binding affinity, chemotherapeutics, drug-like, multiple sclerosis, S1PR1 receptor protein

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Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

Procedia PDF Downloads 56

Authors: M. A. Spielmann, L. Schebek

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In order to reach the long-term national climate goals of the German government for the building sector, substantial energetic measures have to be executed. Historically, those measures were primarily energetic efficiency measures at the buildings’ shells. Advanced technologies for the on-site generation of heat (or other types of energy) often are not feasible at this small spatial scale of a single building. Therefore, the present approach uses the spatially larger dimension of a quarter. The main focus of the present paper is the long-term economic-ecological assessment of available decentralized heat-generating (CHP power plants and electrical heat pumps) technologies at the quarter level for the German unrefurbished residential buildings. Three distinct terms have to be described methodologically: i) Quarter approach, ii) Economic assessment, iii) Ecological assessment. The quarter approach is used to enable synergies and scaling effects over a single-building. For the present study, generic quarters that are differentiated according to significant parameters concerning their heat demand are used. The core differentiation of those quarters is made by the construction time period of the buildings. The economic assessment as the second crucial parameter is executed with the following structure: Full costs are quantized for each technology combination and quarter. The investment costs are analyzed on an annual basis and are modeled with the acquisition of debt. Annuity loans are assumed. Consequently, for each generic quarter, an optimal technology combination for decentralized heat generation is provided in each year of the temporal boundaries (2016-2050). The ecological assessment elaborates for each technology combination and each quarter a Life Cycle assessment. The measured impact category hereby is GWP 100. The technology combinations for heat production can be therefore compared against each other concerning their long-term climatic impacts. Core results of the approach can be differentiated to an economic and ecological dimension. With an annual resolution, the investment and running costs of different energetic technology combinations are quantified. For each quarter an optimal technology combination for local heat supply and/or energetic refurbishment of the buildings within the quarter is provided. Coherently to the economic assessment, the climatic impacts of the technology combinations are quantized and compared against each other.

Keywords: building sector, economic-ecological assessment, heat, LCA, quarter level

Procedia PDF Downloads 211

Authors: Carl-Magnus Everitt, Bo Alfredsson

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Contact mechanics and tribology have been combined with fundamental fatigue and fracture mechanics to form the asperity mechanism which supplies an explanation for the surface-initiated rolling contact fatigue damage, called pitting or spalling. The cracks causing the pits initiates at one surface point and thereafter they slowly grow into the material before chipping of a material piece to form the pit. In the current study, the lubrication aspects on fatigue initiation are simulated by passing a single asperity through a thermal elastohydrodynamic lubricated, TEHL, contact. The physics of the lubricant was described with Reynolds equation and the lubricants pressure-viscosity relation was modeled by Roelands equation, formulated to include temperature dependence. A pressure dependent shear limit was incorporated. To capture the full phenomena of the sliding contact the temperature field was resolved through the incorporation of the energy flow. The heat was mainly generated due to shearing of the lubricant and from dry friction where metal contact occurred. The heat was then transported, and conducted, away by the solids and the lubricant. The fatigue damage caused by the asperities was evaluated through Findley’s fatigue criterion. The results show that asperities, in the size of surface roughness found in applications, may cause surface initiated fatigue damage and crack initiation. The simulations also show that the asperities broke through the lubricant in the inlet, causing metal to metal contact with high friction. When the asperities thereafter moved through the contact, the sliding provided the asperities with lubricant releasing the metal contact. The release of metal contact was possible due to the high viscosity the lubricant obtained from the high pressure. The metal contact in the inlet caused higher friction which increased the risk of fatigue damage. Since the metal contact occurred in the inlet it increased the fatigue risk more for asperities subjected to negative slip than positive slip. Therefore the fatigue evaluations showed that the asperities subjected to negative slip yielded higher fatigue stresses than the asperities subjected to positive slip of equal magnitude. This is one explanation for why pitting is more common in the dedendum than the addendum on pinion gear teeth. The simulations produced further validation for the asperity mechanism by showing that asperities cause surface initiated fatigue and crack initiation.

Keywords: fatigue, rolling, sliding, thermal elastohydrodynamic

Procedia PDF Downloads 107

Authors: N. A. Masevhe, M. Nemukula, S. S. Gololo, K. G. Kgosana

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Background and Study Significance: Legume seeds are important in agriculture as they are used for feed formulations due to their nutrient-dense, low-cost, and easy accessibility. Although they are important sources of energy, proteins, carbohydrates, vitamins, and minerals, they contain abundant quantities of anti-nutritive factors that reduce the bioavailability of nutrients, digestibility of proteins, and mineral absorption in livestock. However, the removal of these factors is too costly as it requires expensive state-of-the-art techniques such as high pressure and thermal processing. Basic Methodologies: The aim of the study was to investigate cost-effective methods that can be used to reduce the inherent phytates as putative antinutrients in the legume seeds. The seeds of Arachis hypogaea, Pisum sativum and Vigna radiata L. were subjected to the single processing methods viz raw seeds plus dehulling (R+D), soaking plus dehulling (S+D), ordinary cooking plus dehulling (C+D), infusion plus dehulling (I+D), autoclave plus dehulling (A+D), microwave plus dehulling (M+D) and five combined methods (S+I+D; S+A+D; I+M+D; S+C+D; S+M+D). All the processed seeds were dried, ground into powder, extracted, and analyzed on a microplate reader to determine the percentage of phytates per dry mass of the legume seeds. Phytic acid was used as a positive control, and one-way ANOVA was used to determine the significant differences between the means of the processing methods at a threshold of 0.05. Major Findings: The results of the processing methods showed the percentage yield ranges of 39.1-96%, 67.4-88.8%, and 70.2-93.8% for V. radiata, A. hypogaea and P. sativum, respectively. Though the raw seeds contained the highest contents of phytates that ranged between 0.508 and 0.527%, as expected, the R+D resulted in a slightly lower phytate percentage range of 0.469-0.485%, while other processing methods resulted in phytate contents that were below 0.35%. The M+D and S+M+D methods showed low phytate percentage ranges of 0.276-0.296% and 0.272-0.294%, respectively, where the lowest percentage yield was determined in S+M+D of P. sativum. Furthermore, these results were found to be significantly different (p<0.05). Though phytates cause micronutrient deficits as they chelate important minerals such as calcium, zinc, iron, and magnesium, their reduction may enhance nutrient bioavailability since they cannot be digested by the ruminants. Concluding Statement: Despite the nutritive aspects of the processed legume seeds, which are still in progress, the M+D and S+M+D methods, which significantly reduced the phytates in the investigated legume seeds, may be recommended to the local farmers and feed-producing industries so as to enhance animal health and production at an affordable cost.

Keywords: anti-nutritive factors, extraction, legume seeds, phytate

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Authors: Nazym Zhumabayeva, Aleksandr Mezin, Alexandra Knysheva

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Women's underrepresentation in STEM is critical, worsened by ineffective engagement in educational practices. UNICEF Kazakhstan and GameLab KBTU's collaborative initiatives aim to enhance female STEM participation by fostering an inclusive environment. Learning from LEVEL UP's 2023 program, which featured a hackathon, the 2024 strategy pivots towards non-competitive gamification. Although the data from last year's project showed higher than average student engagement, observations and in-depth interviews with participants showed that the format was stressful for the girls, making them focus on points rather than on other values. This study presents a gamified educational system, DPG Lab, aimed at incentivizing young women's participation in STEM through the development of digital public goods (DPGs). By prioritizing collaborative gamification elements, the project seeks to create an inclusive learning environment that increases engagement and interest in STEM among young women. The DPG Lab aims to find a solution to minimize competition and support collaboration. The project is designed to motivate female participants towards the development of digital solutions through an introduction to the concept of DPGs. It consists of a short online course, a simulation videogame, and a real-time online quest with an offline finale at the KBTU campus. The online course offers short video lectures on open-source development and DPG standards. The game facilitates the practical application of theoretical knowledge, enriching the learning experience. Learners can also participate in a quest that encourages participants to develop DPG ideas in teams by choosing missions throughout the quest path. At the offline quest finale, the participants will meet in person to exchange experiences and accomplishments without engaging in comparative assessments: the quest ensures that each team’s trajectory is distinct by design. This marks a shift from competitive hackathons to a collaborative format, recognizing the unique contributions and achievements of each participant. The pilot batch of students is scheduled to commence in April 2024, with the finale anticipated in June. It is projected that this group will comprise 50 female high-school students from various regions across Kazakhstan. Expected outcomes include increased engagement and interest in STEM fields among young female participants, positive emotional and psychological impact through an emphasis on collaborative learning environments, and improved understanding and skills in DPG development. GameLab KBTU intends to undertake a hypothesis evaluation, employing a methodology similar to that utilized in the preceding LEVEL UP project. This approach will encompass the compilation of quantitative metrics (conversion funnels, test results, and surveys) and qualitative data from in-depth interviews and observational studies. For comparative analysis, a select group of participants from the previous year's project will be recruited to engage in the DPG Lab. By developing and implementing a gamified framework that emphasizes inclusion, engagement, and collaboration, the study seeks to provide practical knowledge about effective gamification strategies for promoting gender diversity in STEM. The expected outcomes of this initiative can contribute to the broader discussion on gamification in education and gender equality in STEM by offering a replicable and scalable model for similar interventions around the world.

Keywords: collaborative learning, competitive learning, digital public goods, educational gamification, emerging regions, STEM, underprivileged groups

Procedia PDF Downloads 41

Authors: Mehrnaz Mostafavi

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Nanoliposomes, minute lipid-based vesicles at the nano-scale, show promise in the realm of photothermal therapy (PTT). This study presents an extensive overview of nanoliposomes in PTT, exploring their distinct attributes and the significant progress in this therapeutic methodology. The research delves into the fundamental traits of nanoliposomes, emphasizing their adaptability, compatibility with biological systems, and their capacity to encapsulate diverse therapeutic substances. Specifically, it examines the integration of light-absorbing materials, like gold nanoparticles or organic dyes, into nanoliposomal formulations, enabling their efficacy as proficient agents for photothermal treatment Additionally, this paper elucidates the mechanisms involved in nanoliposome-mediated PTT, highlighting their capability to convert light energy into localized heat, facilitating the precise targeting of diseased cells or tissues. This precise regulation of light absorption and heat generation by nanoliposomes presents a non-invasive and precisely focused therapeutic approach, particularly in conditions like cancer. The study explores advancements in nanoliposomal formulations aimed at optimizing PTT outcomes. These advancements include strategies for improved stability, enhanced drug loading, and the targeted delivery of therapeutic agents to specific cells or tissues. Furthermore, the paper discusses multifunctional nanoliposomal systems, integrating imaging components or targeting elements for real-time monitoring and improved accuracy in PTT. Moreover, the review highlights recent preclinical and clinical trials showcasing the effectiveness and safety of nanoliposome-based PTT across various disease models. It also addresses challenges in clinical implementation, such as scalability, regulatory considerations, and long-term safety assessments. In conclusion, this paper underscores the substantial potential of nanoliposomes in advancing PTT as a promising therapeutic approach. Their distinctive characteristics, combined with their precise ability to convert light into heat, offer a tailored and efficient method for treating targeted diseases. The encouraging outcomes from preclinical studies pave the way for further exploration and potential clinical applications of nanoliposome-based PTT.

Keywords: nanoliposomes, photothermal therapy, light absorption, heat conversion, therapeutic agents, targeted delivery, cancer therapy

Procedia PDF Downloads 77

Authors: Aidin Foroutan, David S. Wishart, Leluo L. Guan, Carolyn Fitzsimmons

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Maximizing efficiency and growth potential of beef cattle requires not only genetic selection (i.e. residual feed intake (RFI)) but also adequate nutrition throughout all stages of growth and development. Nutrient restriction during gestation has been shown to negatively affect post-natal growth and development as well as fertility of the offspring. This, when combined with RFI may affect progeny traits. This study aims to investigate the impact of selection for divergent genetic potential for RFI and maternal nutrition during early- to mid-gestation, on bull calf traits such as fertility and muscle development using multiple ‘omics’ approaches. Comparisons were made between High-diet vs. Low-diet and between High-RFI vs. Low-RFI animals. An epigenetics experiment on semen samples identified 891 biomarkers associated with growth and development. A gene expression study on Longissimus thoracis muscle, semimembranosus muscle, liver, and testis identified 4 genes associated with muscle development and immunity of which Myocyte enhancer factor 2A [MEF2A; induces myogenesis and control muscle differentiation] was the only differentially expressed gene identified in all four tissues. An initial metabolomics experiment on serum samples using nuclear magnetic resonance (NMR) identified 4 metabolite biomarkers related to energy and protein metabolism. Once all the biomarkers are identified, bioinformatics approaches will be used to create a database covering all the ‘omics’ data collected from this project. This database will be broadened by adding other information obtained from relevant literature reviews. Association analyses with these data sets will be performed to reveal key biological pathways affected by RFI and maternal nutrition. Through these association studies between the genome and metabolome, it is expected that candidate biomarker genes and metabolites for feed efficiency, fertility, and/or muscle development are identified. If these gene/metabolite biomarkers are validated in a larger animal population, they could potentially be used in breeding programs to select superior animals. It is also expected that this work will lead to the development of an online tool that could be used to predict future traits of interest in an animal given its measurable ‘omics’ traits.

Keywords: biomarker, maternal nutrition, omics, residual feed intake

Procedia PDF Downloads 175

Authors: Benedictus Asriparusa, Lathifah Al Hakimi, Aulia Husada

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A large amount of energy is being wasted by the release of natural gas associated with the oil industry. This release interrupts the environment particularly atmosphere layer condition globally which contributes to global warming impact. This research presents an overview of the methods employed by researchers in PT. Chevron Pacific Indonesia in the Minas area to determine a new prediction method of measuring and reducing gas flaring and its emission. The method emphasizes advanced research which involved analytical studies, numerical studies, modeling, and computer simulations, amongst other techniques. A flaring system is the controlled burning of natural gas in the course of routine oil and gas production operations. This burning occurs at the end of a flare stack or boom. The combustion process releases emissions of greenhouse gases such as NO2, CO2, SO2, etc. This condition will affect the chemical composition of air and environment around the boundary layer mainly during transition season. Transition season in Indonesia is absolutely very difficult condition to predict its pattern caused by the difference of two air mass conditions. This paper research focused on transition season in 2013. A simulation to create the new pattern of the pollutants distribution is needed. This paper has outlines trends in gas flaring modeling and current developments to predict the dominant variables in the pollutants distribution. A Fluent model is used to simulate the distribution of pollutants gas coming out of the stack, whereas WRF model output is used to overcome the limitations of the analysis of meteorological data and atmospheric conditions in the study area. Based on the running model, the most influence factor was wind speed. The goal of the simulation is to predict the new pattern based on the time of fastest wind and slowest wind occurs for pollutants distribution. According to the simulation results, it can be seen that the fastest wind (last of March) moves pollutants in a horizontal direction and the slowest wind (middle of May) moves pollutants vertically. Besides, the design of flare stack in compliance according to EPA Oil and Gas Facility Stack Parameters likely shows pollutants concentration remains on the under threshold NAAQS (National Ambient Air Quality Standards).

Keywords: flare motion, new prediction, pollutants distribution, transition season, WRF model

Procedia PDF Downloads 527

Authors: Ross J. Maestas

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Biofuels are derived from multiple renewable bioenergy feedstocks including animal fats, wood, starchy grains, and oil seeds. Transportation agencies have considered growing the latter two on underutilized and nontraditional lands that they manage, such as in the Right of Way (ROW), abandoned weigh stations, and at maintenance yards. These crops provide the opportunity to generate revenue or supplement fuel once converted and offer a solution to increasing fuel costs and instability by creating a ‘home-grown’ alternative. Biofuels are non-toxic, biodegradable, and emit less Green House Gasses (GHG) than fossil fuels, therefore allowing agencies to meet sustainability goals and regulations. Furthermore, they enable land managers to achieve soil erosion and roadside aesthetic strategies. The research sought to understand if the cultivation of a biofuel feedstock within the Arkansas State Highway Transportation Department’s (AHTD) managed and marginalized lands is feasible by identifying potential land areas and crops. To determine potential plots the parcel data was downloaded from Arkansas’s GIS office. ArcGIS was used to query the data for all variations of the names of property owned by AHTD and a KML file was created that identifies the queried parcel data in Google Earth. Furthermore, biofuel refineries in the state were identified to optimize the harvest to transesterification process. Agricultural data was collected from federal and state agencies and universities to assess various oil seed crops suitable for conversion and suited to grow in Arkansas’s climate and ROW conditions. Research data determined that soybean is the best adapted biofuel feedstock for Arkansas with camelina and canola showing possibilities as well. Agriculture is Arkansas’s largest industry and soybean is grown in over half of the state’s counties. Successful cultivation of a feedstock in the aforementioned areas could potentially offer significant employment opportunity for which the skilled farmers already exist. Based on compiled data, AHTD manages 21,489 acres of marginalized land. The result of the feasibility assessment offer suggestions and guidance should AHTD decide to further investigate this type of initiative.

Keywords: Arkansas highways, biofuels, renewable energy initiative, marginalized lands

Procedia PDF Downloads 315

Authors: Stephanie Chen, Mitja Echim, Christof Büskens

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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

Procedia PDF Downloads 389

Authors: Florim Grajcevci, Flamur Grajcevci, Fatos Tahiri, Hamdi Kurteshi

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The territory of Kosova is actually included in one of the most seismic-prone regions in Europe. Therefore, the earthquakes are not so rare in Kosova; and when they occurred, the consequences have been rather destructive. The importance of assessing the seismic resistance of existing masonry structures has drawn strong and growing interest in the recent years. Engineering included those of Vulnerability, Loss of Buildings and Risk assessment, are also of a particular interest. This is due to the fact that this rapidly developing field is related to great impact of earthquakes on the socioeconomic life in seismic-prone areas, as Kosova and Prishtina are, too. Such work paper for Prishtina city may serve as a real basis for possible interventions in historic buildings as are museums, mosques, old residential buildings, in order to adequately strengthen and/or repair them, by reducing the seismic risk within acceptable limits. The procedures of the vulnerability assessment of building structures have concentrated on structural system, capacity, and the shape of layout and response parameters. These parameters will provide expected performance of the very important existing building structures on the vulnerability and the overall behavior during the earthquake excitations. The structural systems of existing historical buildings in Pristina, Kosovo, are dominantly unreinforced brick or stone masonry with very high risk potential from the expected earthquakes in the region. Therefore, statistical analysis based on the observed damage-deformation, cracks, deflections and critical building elements, would provide more reliable and accurate results for the regional assessments. The analytical technique was used to develop a preliminary evaluation methodology for assessing seismic vulnerability of the respective structures. One of the main objectives is also to identify the buildings that are highly vulnerable to damage caused from inadequate seismic performance-response. Hence, the damage scores obtained from the derived vulnerability functions will be used to categorize the evaluated buildings as “stabile”, “intermediate”, and “unstable”. The vulnerability functions are generated based on the basic damage inducing parameters, namely number of stories (S), lateral stiffness (LS), capacity curve of total building structure (CCBS), interstory drift (IS) and overhang ratio (OR).

Keywords: vulnerability, ductility, seismic microzone, ductility, energy efficiency

Procedia PDF Downloads 394

Authors: Calister Wingang Makebe, Wilson Ambindei Agwanande, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1 as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated, and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

Procedia PDF Downloads 58

Authors: Andreia Garrido, Artur Conde, Ana Cunha, Ric De Vos

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Climate changes predictions point to increases in abiotic stress for crop plants in Portugal, like pronounced temperature variation and decreased precipitation, which will have negative impact on grapevine physiology and consequently, on grape berry and wine quality. Short-term mitigation strategies have, therefore, been implemented to alleviate the impacts caused by adverse climatic periods. These strategies include foliar application of kaolin, an inert mineral, which has radiation reflection proprieties that decreases stress from excessive heat/radiation absorbed by its leaves, as well as smart irrigation strategies to avoid water stress. However, little is known about the influence of these mitigation measures on grape berries, neither on the photosynthetic activity nor on the photosynthesis-related metabolic profiles of its various tissues. Moreover, the role of fruit photosynthesis on berry quality is poorly understood. The main objective of our work was to assess the effects of kaolin and irrigation treatments on the photosynthetic activity of grape berry tissues (exocarp and seeds) and on their global metabolic profile, also investigating their possible relationship. We therefore collected berries of field-grown plants of the white grape variety Alvarinho from two distinct microclimates, i.e. from clusters exposed to high light (HL, 150 µmol photons m⁻² s⁻¹) and low light (LL, 50 µmol photons m⁻² s⁻¹), from both kaolin and non-kaolin (control) treated plants at three fruit developmental stages (green, véraison and mature). Plant irrigation was applied after harvesting the green berries, which also enabled comparison of véraison and mature berries from irrigated and non-irrigated growth conditions. Photosynthesis was assessed by pulse amplitude modulated chlorophyll fluorescence imaging analysis, and the metabolite profile of both tissues was assessed by complementary metabolomics approaches. Foliar kaolin application resulted in, for instance, an increased photosynthetic activity of the exocarp of LL-grown berries at green developmental stage, as compared to the control non-kaolin treatment, with a concomitant increase in the levels of several lipid-soluble isoprenoids (chlorophylls, carotenoids, and tocopherols). The exocarp of mature berries grown at HL microclimate on kaolin-sprayed non-irrigated plants had higher total sugar levels content than all other treatments, suggesting that foliar application of this mineral results in an increased accumulation of photoassimilates in mature berries. Unbiased liquid chromatography-mass spectrometry-based profiling of semi-polar compounds followed by ASCA (ANOVA simultaneous component analysis) and ANOVA statistical analysis indicated that kaolin had no or inconsistent effect on the flavonoid and phenylpropanoid composition in both seed and exocarp at any developmental stage; in contrast, both microclimate and irrigation influenced the level of several of these compounds depending on berry ripening stage. Overall, our study provides more insight into the effects of mitigation strategies on berry tissue photosynthesis and phytochemistry, under contrasting conditions of cluster light microclimate. We hope that this may contribute to develop sustainable management in vineyards and to maintain grape berries and wines with high quality even at increasing abiotic stress challenges.

Keywords: climate change, grape berry tissues, metabolomics, mitigation strategies

Procedia PDF Downloads 100

Authors: Bernd Sauer, Michel Werner, Stefan Emrich, Michael Kopnarski, Oliver Koch

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Friction reduction is an important aspect in the context of sustainability and energy transition. Rolling bearings are therefore used in many applications in which components move relative to each other. Conventionally lubricated rolling bearings are used in a wide range of applications, but are not suitable under certain conditions. Conventional lubricants such as grease or oil cannot be used at very high or very low temperatures. In addition, these lubricants evaporate at very low ambient pressure, e.g. in a high vacuum environment, making the use of solid lubricated bearings unavoidable. With the use of solid-lubricated bearings, predicting the service life becomes more complex. While the end of the service life of bearings with conventional lubrication is mainly caused by the failure of the bearing components due to material fatigue, solid-lubricated bearings fail at the moment when the lubrication layer is worn and the rolling elements come into direct contact with the raceway during operation. In order to extend the service life of these bearings beyond the service life of the initial coating, the use of transfer lubrication is recommended, in which pockets or sacrificial cages are used in which the balls run and can thus absorb the lubricant, which is then available for lubrication in tribological contact. This contribution presents the results of wear and service life tests on solid-lubricated rolling bearings with sacrificial cage pockets. The cage of the bearing consists of a polyimide (PI) matrix with 15% molybdenum disulfide (MoS2) and serves as a lubrication depot alongside the silver-coated balls. The bearings are tested under high vacuum (pE < 10-2 Pa) at a temperature of 300 °C on a four-bearing test rig. First, investigations of the bearing system within the bearing service life are presented and the torque curve, the wear mass and surface analyses are discussed. With regard to wear, it can be seen that the bearing rings tend to increase in mass over the service life of the bearing, while the balls and the cage tend to lose mass. With regard to the elementary surface properties, the surfaces of the bearing rings and balls are examined in terms of the mass of the elements on them. Furthermore, service life investigations with different material pairings are presented, whereby the focus here is on the service life achieved in addition to the torque curve, wear development and surface analysis. It was shown that MoS2 in the cage leads to a longer service life, while a silver (Ag) coating on the balls has no positive influence on the service life and even appears to reduce it in combination with MoS2.

Keywords: ball bearings, molybdenum disulfide, solid lubricated bearings, solid lubrication mechanisms

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Authors: Ajay Mandal, Jitendar Kumar Tiwari, N. Sathish, A. K. Srivastava

Abstract:

A fundamental investigation is performed on the development of graphene (Gr) reinforced stainless steel 316L (SS 316L) metal matrix composite via selective laser melting (SLM) in order to improve specific strength and wear resistance property of SS 316L. Firstly, SS 316L powder and graphene were mixed in a fixed ratio using low energy planetary ball milling. The milled powder is then subjected to the SLM process to fabricate composite samples at a laser power of 320 W and exposure time of 100 µs. The prepared composite was mechanically tested (hardness and tensile test) at ambient temperature, and obtained results indicate that the properties of the composite increased significantly with the addition of 0.2 wt. % Gr. Increment of about 25% (from 194 to 242 HV) and 70% (from 502 to 850 MPa) is obtained in hardness and yield strength of composite, respectively. Raman mapping and XRD were performed to see the distribution of Gr in the matrix and its effect on the formation of carbide, respectively. Results of Raman mapping show the uniform distribution of graphene inside the matrix. Electron back scatter diffraction (EBSD) map of the prepared composite was analyzed under FESEM in order to understand the microstructure and grain orientation. Due to thermal gradient, elongated grains were observed along the building direction, and grains get finer with the addition of Gr. Most of the mechanical components are subjected to several types of wear conditions. Therefore, it is very necessary to improve the wear property of the component, and hence apart from strength and hardness, a tribological property of composite was also measured under dry sliding condition. Solid lubrication property of Gr plays an important role during the sliding process due to which the wear rate of composite reduces up to 58%. Also, the surface roughness of worn surface reduces up to 70% as measured by 3D surface profilometry. Finally, it can be concluded that SLM is an efficient method of fabricating cutting edge metal matrix nano-composite having Gr like reinforcement, which was very difficult to fabricate through conventional manufacturing techniques. Prepared composite has superior mechanical and tribological properties and can be used for a wide variety of engineering applications. However, due to the unavailability of a considerable amount of literature in a similar domain, more experimental works need to perform, such as thermal property analysis, and is a part of ongoing study.

Keywords: selective laser melting, graphene, composite, mechanical property, tribological property

Procedia PDF Downloads 127

Authors: Muhammad Arif Jalil, Xaythavay Luangvilay, Montree Bunruangses, Somchat Sonasang, Preecha Yupapin

Abstract:

Black and white holes form the entangled pair⟨BH│WH⟩, where a white hole occurs when the particle moves at the same speed as light. The entangled black-white hole pair is at the center with the radian between the gap. When the speed of particle motion is slower than light, the black hole is gravitational (positive gravity), where the white hole is smaller than the black hole. On the downstream side, the entangled pair appears to have a black hole outside the gap increases until the white holes disappear, which is the emptiness paradox. On the upstream side, when moving faster than light, white holes form times tunnels, with black holes becoming smaller. It will continue to move faster and further when the black hole disappears and becomes a wormhole (Singularity) that is only a white hole in emptiness (Emptiness). This research studies use of black and white holes generated by a two-level circuit for communication transmission carriers, in which high ability and capacity of data transmission can be obtained. The black and white hole pair can be generated by the two-level system circuit when the speech of a particle on the circuit is equal to the speed of light. The black hole forms when the particle speed has increased from slower to equal to the light speed, while the white hole is established when the particle comes down faster than light. They are bound by the entangled pair, signal and idler, ⟨Signal│Idler⟩, and the virtual ones for the white hole, which has an angular displacement of half of π radian. A two-level system is made from an electronic circuit to create black and white holes bound by the entangled bits that are immune or cloning-free from thieves. Start by creating a wave-particle behavior when its speed is equal to light black hole is in the middle of the entangled pair, which is the two bit gate. The required information can be input into the system and wrapped by the black hole carrier. A timeline (Tunnel) occurs when the wave-particle speed is faster than light, from which the entangle pair is collapsed. The transmitted information is safely in the time tunnel. The required time and space can be modulated via the input for the downlink operation. The downlink is established when the particle speed is given by a frequency(energy) form is down and entered into the entangled gap, where this time the white hole is established. The information with the required destination is wrapped by the white hole and retrieved by the clients at the destination. The black and white holes are disappeared, and the information can be recovered and used.

Keywords: cloning free, time machine, teleportation, two-level system

Procedia PDF Downloads 59