Search results for: carbon emission efficiency

Authors: Theddeus Tochukwu Akano, Omotayo Abayomi Fakinlede

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Proper understanding of the behavior of compliant mechanisms use by athletes is important in order to avoid catastrophic failure. Such compliant mechanisms like the flex-run require the knowledge of their dynamic response and deformation behavior under quickly varying loads. The modeling of finite deformations of the compliant athletic system is described by Neo-Hookean model under contact-impact conditions. The dynamic impact-contact governing equations for both the target and impactor are derived based on the updated Lagrangian approach. A method where contactor and target are considered as a united body is applied in the formulation of the principle of virtual work for the bodies. In this paper, methods of continuum mechanics and nonlinear finite element method were deployed to develop a model that could capture the behavior of the compliant athletic system under quickly varying loads. A hybrid system of symbolic algebra (AceGEN) and a compiled back end (AceFEM) were employed, leveraging both ease of use and computational efficiency. The simulated results reveal the effect of the various contact-impact conditions on the deformation behavior of the impacting compliant mechanism.

Keywords: eigenvalue problems, finite element method, robin boundary condition, sturm-liouville problem

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Authors: Rajiv Arora

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Biodiesel may be economical if produced from inexpensive feedstock which commonly contains high level of free fatty acids (FFA) as an inhibitor in production of methyl ester. In this study, a two-step process for biodiesel production from high FFA spent bleach earth oil in a batch reactor is developed. Oil sample extracted from spent bleaching earth (SBE) was utilized for biodiesel process. In the first step, FFA of the SBE oil was reduced to 1.91% through sulfuric acid catalyzed esterification. In the second step, the product prepared from the first esterification process was carried out transesterification with an alkaline catalyst. The influence of four variables on conversion efficiency to methyl ester, i.e., methanol/ SBE oil molar ratio, catalyst amount, reaction temperature and reaction time, was studied in the second stage. The optimum process variables in the transesterification were methanol/oil molar ratio 6:1, heterogeneous catalyst conc. 5 wt %, reaction temperature 65 °C and reaction time 60 minutes to produce biodiesel. Major fuel properties of SBE biodiesel were measured to comply with ASTM and EN standards. Therefore, an optimized process for production of biodiesel from a low-cost high FFA source was accomplished.

Keywords: biodiesel, esterification, free fatty acids, residual oil, spent bleaching earth, transesterification

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Authors: A. Ramalho, L. Romeiro, R. Ventura, A. Suleman

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A real-time path planning framework for Unmanned Air Vehicles, and in particular multi-rotors is proposed. The framework is designed to provide feasible trajectories from the current UAV position to a goal state, taking into account constraints such as obstacle avoidance, problem kinematics, and vehicle limitations such as maximum speed and maximum acceleration. The framework computes feasible paths online, allowing to avoid new, unknown, dynamic obstacles without fully re-computing the trajectory. These features are achieved using an iterative process in which the robot computes and optimizes the trajectory while performing the mission objectives. A first trajectory is computed using a modified Rapidly-Exploring Random Tree (RRT) algorithm, that provides trajectories that respect a maximum curvature constraint. The trajectory optimization is accomplished using the Interior Point Optimizer (IPOPT) as a solver. The framework has proven to be able to compute a trajectory and optimize to a locally optimal with computational efficiency making it feasible for real-time operations.

Keywords: interior point optimization, multi-rotors, online path planning, rapidly exploring random trees, trajectory optimization

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Authors: Alim Asamatdinov

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Superabsorbent polymer hydrogels can swell to absorb huge volumes of water or aqueous solutions. This property has led to many practical applications of these new materials, particularly in agriculture for improving the water retention of soils and the water supply of plants. This article reviews the methods of polymeric hydrogels, measurements and treatments of their properties, as well as their effects on soil and on plant growth. The thermodynamic approach used to describe the swelling behaviour of polymer networks proves to be quite helpful in modelling the hydrogel efficiency of water-absorbing additives. The paper presents the results of a study of the physical and chemical properties of hydrogels based on of the production of "Nitron" (Polyacrylonitrile) wastes fibre and salts of the 3-rd transition metals and formalin. The developed hydrogels HG-Al, HG-Cr and HG-formalin have been tested for water holding the capacity of sand. Such a conclusion was also confirmed by data from the method of determining the wilting point by vegetative thumbnails. In the entering process using a dose of 0.1% of the swelling polymeric hydrogel in sand with a culture of barley the difference between the wilting point in comparison with the control was negligible. This indicates that the moisture which was contained in the hydrogel is involved in moisture availability for plant growth, to the same extent as that in the capillaries.

Keywords: hydrogel, chemical, polymer, sandy, colloid

Procedia PDF Downloads 126

Authors: Hanjun Zhao

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Limited efficacy of current antivirals and antiviral-resistant mutations impair anti-influenza treatment. Here, we evaluated the in vitro and in vivo antiviral effect of three defective interfering genes (DIG-3) of influenza virus. Virus replication was significantly reduced in 293T and A549 cells transfected with DIG-3. Mice transfected with DIG-3 encoded by jetPEI-vector, as prophylaxis and therapeutics against A(H7N7) virus respectively, had significantly better survivals (80% and 50%) than control mice (0%). We further developed a dual-functional peptide TAT-P1, which delivers DIG-3 with high transfection efficiency and concomitantly exerts antiviral activity by preventing endosomal acidification. TAT-P1/DIG-3 was more effective than jetPEI/DIG-3 in treating A(H7N7) or A(H1N1)pdm09-infected mice and showed potent prophylactic protection on A(H7N7) or A(H1N1)pdm09-infected mice. The addition of P1 peptide, preventing endosomal acidification, could enhance the protection of TAT-P1/DIG-3 on A(H1N1)pdm09-infected mice. Dual-functional TAT-P1 with DIG-3 can effectively protect or treat mice infected by avian and seasonal influenza virus infection.

Keywords: antiviral peptide, dual-functional peptide, defective interfering genes, influenza virus

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Authors: Kewei Xu, Jens Friedrich, Kevin Dwinger, Wei Fan, Xijin Zhang

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Parallel Compressor Model (PCM) is a simplified approach to predict compressor performance with inlet distortions. In PCM calculation, it is assumed that the sub-compressors’ outlet static pressure is uniform and therefore simplifies PCM calculation procedure. However, if the compressor’s outlet duct is not long and straight, such assumption frequently induces error ranging from 10% to 15%. This paper provides a revised calculation method of PCM that can correct the error. The revised method employs energy equation, momentum equation and continuity equation to acquire needed parameters and replace the equal static pressure assumption. Based on the revised method, PCM is applied on two compression system with different blades types. The predictions of their performance in non-uniform inlet conditions are yielded through the revised calculation method and are employed to evaluate the method’s efficiency. Validating the results by experimental data, it is found that although little deviation occurs, calculated result agrees well with experiment data whose error ranges from 0.1% to 3%. Therefore, this proves the revised calculation method of PCM possesses great advantages in predicting the performance of the distorted compressor with limited exhaust duct.

Keywords: parallel compressor model (pcm), revised calculation method, inlet distortion, outlet unequal pressure distribution

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Authors: Sohan Sengupta, Arnab Pramanik, Abhrajyoti Ghosh, Maitree Bhattacharyya

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Newly emerged phyto-pathogens and multi drug resistance have been threating the world for last few decades. Actinomycetes, the most endowed group of microorganisms isolated from unexplored regions of the world may be the ultimate solution to these problems. Thus the aim of this study was to isolate several bioactive actinomycetes strains capable of producing antimicrobial secondary metabolite from Sundarbans, the only mangrove tiger land of the world. Fifty four actinomycetes were isolated and analyzed for antimicrobial activity against fifteen test organisms including three phytopathogens. Nine morphologically distinct and biologically active isolates were subjected to polyphasic identification study. 16s rDNA sequencing indicated eight isolates to reveal maximum similarity to the genus streptomyces, whereas one isolate presented only 93.57% similarity with Streptomyces albogriseolus NRRL B-1305T. Seventy-one carbon sources and twenty-three chemical sources utilization assay revealed their metabolic relatedness. Among these nine isolates three specific strains were found to have notably higher degree of antimicrobial potential effective in a broader range including phyto-pathogenic fungus. PCR base whole genome screen for PKS and NRPS genes, confirmed the occurrence of bio-synthetic gene cluster in some of the isolates for novel antibiotic production. Finally the strain SMS_SU21, which showed antimicrobial activity with MIC value of 0.05 mg ml-1and antioxidant activity with IC50 value of 0.242±0.33 mg ml-1 was detected to be the most potential one. True prospective of this strain was evaluated utilizing GC-MS and the bioactive compound responsible for antimicrobial activity was purified and characterized. Rare bioactive actinomycetes were isolated from unexplored heritage site. Diversity of the biosynthetic gene cluster for antimicrobial compound production has also been evaluated. Antimicrobial compound SU21-C has been identified and purified which is active against a broad range of pathogens.

Keywords: actinomycetes, sundarbans, antimicrobial, pks nrps, phyto-pathogens, GC-MS

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Authors: Gichun Cha, Byoungjoon Yu, Jihwan Park, Minsoo Park, Junghyun Im, Sehwan Park, Sujung Sin, Seunghee Park

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The goal of this research is to estimate a structural shape change using terrestrial laser scanning. This study proceeds with development of data reduction and shape change estimation algorithm for large-capacity scan data. The point cloud of scan data was converted to voxel and sampled. Technique of shape estimation is studied to detect changes in structure patterns, such as skyscrapers, bridges, and tunnels based on large point cloud data. The point cloud analysis applies the octree data structure to speed up the post-processing process for change detection. The point cloud data is the relative representative value of shape information, and it used as a model for detecting point cloud changes in a data structure. Shape estimation model is to develop a technology that can detect not only normal but also immediate structural changes in the event of disasters such as earthquakes, typhoons, and fires, thereby preventing major accidents caused by aging and disasters. The study will be expected to improve the efficiency of structural health monitoring and maintenance.

Keywords: terrestrial laser scanning, point cloud, shape information model, displacement measurement

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Authors: Apichaya Aneksampant, Xuefei Tu, Masami Fukushima, Mitsuo Yamamoto

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The restoration of seaweed beds recovery has been developed using a fertilization technique for supplying dissolved iron to barren coastal areas. The fertilizer is composed of iron oxides as a source of iron and compost as humic substance (HS) source, which can serve as chelator of iron to stabilize the dissolved species under oxic seawater condition. However, elution mechanisms of iron from iron oxide surfaces have not sufficiently elucidated. In particular, roles of microbial activities in the elution of iron from the fertilizer are not sufficiently understood. In the present study, a fertilizer (iron oxide/compost = 1/1, v/v) was incubated in a water tank at Mashike coast, Hokkaido Japan. Microorganisms in the 6-month fertilizer were isolated and identified as Exiguobacterium oxidotolerans sp. (T-2-2). The identified bacteria were inoculated to perform iron elution test in a postgate B medium, prepared in artificial seawater. Hematite was used as a model iron oxide and anthraquinone-2,7-disolfonate (AQDS) as a model for HSs. The elution test performed in presence and absence of bacteria inoculation. ICP-AES was used to analyze total iron and a colorimetric technique using ferrozine employed for the determination of ferrous ion. During the incubation period, sample contained hematite and T-2-2 in both presence and absence of AQDS continuously showed the iron elution and reached at the highest concentration after 9 days of incubation and then slightly decrease to stabilize within 20 days. Comparison to the sample without T-2-2, trace amount of iron was observed, suggesting that iron elution to seawater can be attributed to bacterial activities. The levels of total organic carbon (TOC) in the culture solution with hematite decreased. This may be to the adsorption of organic compound, AQDS, to hematite surfaces. The decrease in UV-vis absorption of AQDS in the culture solution also support the results of TOC that AQDS was adsorbed to hematite surfaces. AQDS can enhance the iron elution, while the adsorption of organic matter suppresses the iron elution from hematite.

Keywords: anthraquinone-2, 7-disolfonate, barren ground, E.oxidotolerans sp., hematite, humic substances, iron elution

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Authors: M. Aladwani, Y. Alarfaj

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The construction industry is currently experiencing a shift towards digitisation. This transformation is driven by adopting technologies like Building Information Modelling (BIM), drones, and augmented reality (AR). These advancements are revolutionizing the process of designing, constructing, and operating projects. BIM, for instance, is a new way of communicating and exploiting technology such as software and machinery. It enables the creation of a replica or virtual model of buildings or infrastructure projects. It facilitates simulating construction procedures, identifying issues beforehand, and optimizing designs accordingly. Drones are another tool in this revolution, as they can be utilized for site surveys, inspections, and even deliveries. Moreover, AR technology provides real-time information to workers involved in the project. Implementing these technologies in the construction industry has brought about improvements in efficiency, safety measures, and sustainable practices. BIM helps minimize rework and waste materials, while drones contribute to safety by reducing workers' exposure to areas. Additionally, AR plays a role in worker safety by delivering instructions and guidance during operations. Although the digital transformation within the construction industry is still in its early stages, it holds the potential to reshape project delivery methods entirely. By embracing these technologies, construction companies can boost their profitability while simultaneously reducing their environmental impact and ensuring safer practices.

Keywords: BIM, digital construction, construction technologies, digital transformation

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Authors: Muhlisin, Moh. Sofyan Budiarto

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Corporate social responsibility (CSR) initiatives based on charity and philanthropy have not alleviated many sustainable environmental issues, particularly in industrial towns. The collaborative governance strategy is seen to be an option for resolving difficulties of coordination and communication between businesses, the government, and the community so that the goals of urban environmental management can be met via collaborative efforts. The purpose of this research is to identify the different forms of environmental CSR implementation by corporate entities and to create a CSR collaborative governance model in environmental management. This qualitative investigation was carried out in 2020 in Cilegon City, one of Indonesia’s industrial cities. To investigate their support, a total of 20 informants from three stakeholder groups, namely the government, corporate entities, and the community, were questioned. According to the study’s findings, cleaner production, eco-office, energy and natural resource conservation, waste management, renewable energy, climate change adaptation, and environmental education are all examples of CSR application in the environmental sector. The environmental potential of CSR implementation is to create collaborative governance. The role of business entities in providing the beginning circumstances is critical, while the government offers facilitative leadership and the CSR forum launches institutional design. These three factors are crucial to the efficiency of collaborative governance in industrial cities' environmental management.

Keywords: collaborative governance, CSR forum, environmental CSR, industrial city

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Authors: Vibol San, Vin Spoann

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Manufacturing plays an important role in job creation around the world. In 2013, it is estimated that there were more than half a billion jobs in manufacturing. In Cambodia in 2015, the primary industry occupies 26.18% of the total economy, while agriculture is contributing 29% and the service sector 39.43%. The number of industrial factories, which are dominated by garment and textiles, has increased since 1994, mainly in Phnom Penh city. Approximately 56% out of total 1302 firms are operated in the Capital city in Cambodia. Industrialization to achieve the economic growth and social development is directly responsible for environmental degradation, threatening the ecosystem and human health issues. About 96% of total firms in Phnom Penh city are the most and moderately polluting firms, which have contributed to environmental concerns. Despite an increasing array of laws, strategies and action plans in Cambodia, the Ministry of Environment has encountered some constraints in conducting the monitoring work, including lack of human and financial resources, lack of research documents, the limited analytical knowledge, and lack of technical references. Therefore, the necessary information on industrial pollution to set strategies, priorities and action plans on environmental protection issues is absent in Cambodia. In the absence of this data, effective environmental protection cannot be implemented. The objective of this study is to estimate industrial pollution load by employing the Industrial Pollution Projection System (IPPS), a rapid environmental management tool for assessment of pollution load, to produce a scientific rational basis for preparing future policy direction to reduce industrial pollution in Phnom Penh city. Due to lack of industrial pollution data in Phnom Penh, industrial emissions to the air, water and land as well as the sum of emissions to all mediums (air, water, land) are estimated using employment economic variable in IPPS. Due to the high number of employees, the total environmental load generated in Phnom Penh city is estimated to be 476.980.93 tons in 2014, which is the highest industrial pollution compared to other locations in Cambodia. The result clearly indicates that Phnom Penh city is the highest emitter of all pollutants in comparison with environmental pollutants released by other provinces. The total emission of industrial pollutants in Phnom Penh shares 55.79% of total industrial pollution load in Cambodia. Phnom Penh city generates 189,121.68 ton of VOC, 165,410.58 ton of toxic chemicals to air, 38,523.33 ton of toxic chemicals to land and 28,967.86 ton of SO2 in 2014. The results of the estimation show that Textile and Apparel sector is the highest generators of toxic chemicals into land and air, and toxic metals into land, air and water, while Basic Metal sector is the highest contributor of toxic chemicals to water. Textile and Apparel sector alone emits 436,015.84 ton of total industrial pollution loads. The results suggest that reduction in industrial pollution could be achieved by focusing on the most polluting sectors.

Keywords: most polluting area, polluting industry, pollution load, pollution intensity

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Authors: Dimassi Wissem

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In this work, we investigate the effect of combination between the porous silicon (PS) layer passivized with Lithium Bromide (LiBr) and grooving of grain boundaries (GB) in multi crystalline silicon. The grain boundaries were grooved in order to reduce the area of these highly recombining regions. Using optimized conditions, grooved GB's enable deep phosphorus diffusion and deep metallic contacts. We have evaluated the effects of LiBr on the surface properties of porous silicon on the performance of silicon solar cells. The results show a significant improvement of the internal quantum efficiency, which is strongly related to the photo-generated current. We have also shown a reduction of the surface recombination velocity and an improvement of the diffusion length after the LiBr process. As a result, the I–V characteristics under the dark and AM1.5 illumination were improved. It was also observed a reduction of the GB recombination velocity, which was deduced from light-beam-induced-current (LBIC) measurements. Such grooving in multi crystalline silicon enables passivization of GB-related defects. These results are discussed and compared to solar cells based on untreated multi crystalline silicon wafers.

Keywords: Multicrystalline silicon, LiBr, porous silicon, passivation

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Authors: Kwame B. O. Amoah

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This paper focuses on retrofitting an old existing office building to a net-zero energy building (NZEB). An existing small office building in Melbourne, Florida, was chosen as a case study to integrate state-of-the-art design strategies and energy-efficient building systems to improve building performance and reduce energy consumption. The study aimed to explore possible ways to maximize energy savings and renewable energy generation sources to cover the building's remaining energy needs necessary to achieve net-zero energy goals. A series of retrofit options were reviewed and adopted with some significant additional decision considerations. Detailed processes and considerations leading to zero energy are well documented in this study, with lessons learned adequately outlined. Based on building energy simulations, multiple design considerations were investigated, such as emerging state-of-the-art technologies, material selection, improvements to the building envelope, optimization of the HVAC, lighting systems, and occupancy loads analysis, as well as the application of renewable energy sources. The comparative analysis of simulation results was used to determine how specific techniques led to energy saving and cost reductions. The research results indicate this small office building can meet net-zero energy use after appropriate design manipulations and renewable energy sources.

Keywords: energy consumption, building energy analysis, energy retrofits, energy-efficiency

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Authors: Cheng-Jhe Lee, Chiun-Chieh Hsu

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Due to the rapid development of the Internet and the increased availability of digital documents, the excessive information on the Internet has led to information overflow problem. In order to solve these problems for effective information retrieval, document clustering in text mining becomes a popular research topic. Clustering is the unsupervised classification of data items into groups without the need of training data. Many conventional document clustering methods perform inefficiently for large document collections because they were originally designed for relational database. Therefore they are impractical in real-world document clustering and require special handling for high dimensionality and high volume. We propose the FIHC (Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering, where the intuition of FIHC is that there exist some common words for each cluster. FIHC uses such words to cluster documents and builds hierarchical topic tree. In this paper, we combine FIHC algorithm with ontology to solve the semantic problem and mine the meaning behind the words in documents. Furthermore, we use the closed frequent itemsets instead of only use frequent itemsets, which increases efficiency and scalability. The experimental results show that our method is more accurate than those of well-known document clustering algorithms.

Keywords: FIHC, documents clustering, ontology, closed frequent itemset

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Authors: Artur Tyliszczak, Ewa Szymanek, Maciej Marek

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Flow through granular materials is important to a vast array of industries, for instance in construction industry where granular layers are used for bulkheads and isolators, in chemical engineering and catalytic reactors where large surfaces of packed granular beds intensify chemical reactions, or in energy production systems, where granulates are promising materials for heat storage and heat transfer media. Despite the common usage of granulates and extensive research performed in this field, phenomena occurring between granular solid elements or between solids and fluid are still not fully understood. In the present work we analyze the heat exchange process between the flowing medium (gas, liquid) and solid material inside the granular layers. We consider them as a composite of isolated solid elements and inter-granular spaces in which a gas or liquid can flow. The structure of the layer is controlled by shapes of particular granular elements (e.g., spheres, cylinders, cubes, Raschig rings), its spatial distribution or effective characteristic dimension (total volume or surface area). We will analyze to what extent alteration of these parameters influences on flow characteristics (turbulent intensity, mixing efficiency, heat transfer) inside the layer and behind it. Analysis of flow inside granular layers is very complicated because the use of classical experimental techniques (LDA, PIV, fibber probes) inside the layers is practically impossible, whereas the use of probes (e.g. thermocouples, Pitot tubes) requires drilling of holes inside the solid material. Hence, measurements of the flow inside granular layers are usually performed using for instance advanced X-ray tomography. In this respect, theoretical or numerical analyses of flow inside granulates seem crucial. Application of discrete element methods in combination with the classical finite volume/finite difference approaches is problematic as a mesh generation process for complex granular material can be very arduous. A good alternative for simulation of flow in complex domains is an immersed boundary-volume penalization (IB-VP) in which the computational meshes have simple Cartesian structure and impact of solid objects on the fluid is mimicked by source terms added to the Navier-Stokes and energy equations. The present paper focuses on application of the IB-VP method combined with large eddy simulation (LES). The flow solver used in this work is a high-order code (SAILOR), which was used previously in various studies, including laminar/turbulent transition in free flows and also for flows in wavy channels, wavy pipes and over various shape obstacles. In these cases a formal order of approximation turned out to be in between 1 and 2, depending on the test case. The current research concentrates on analyses of the flows in dense granular layers with elements distributed in a deterministic regular manner and validation of the results obtained using LES-IB method and body-fitted approach. The comparisons are very promising and show very good agreement. It is found that the size, number of elements and their distribution have huge impact on the obtained results. Ordering of the granular elements (or lack of it) affects both the pressure drop and efficiency of the heat transfer as it significantly changes mixing process.

Keywords: granular layers, heat transfer, immersed boundary method, numerical simulations

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Authors: Mengjie Zhou

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Under the rapid promotion of digital logistics, the old consumption space in cities is undergoing profound transformation and reconstruction. This article systematically analyzes the impact of digital logistics on existing consumer spaces in cities and how these spaces can adapt to and lead this change through distinct ‘spatial production’ models. The digital transformation of the logistics industry has significantly improved logistics efficiency and service quality while also putting forward new requirements for the form and function of consumer space. In this process, the old consumption space in cities not only faces the trend of material consumption transforming into spiritual consumption but also needs to face profound changes in consumer behavior patterns. Taking Fengying Xili in Changsha as an empirical case, this article explores in detail how it successfully transformed from a traditional consumption space to a modern cultural consumption space by introducing new business formats, optimizing spatial layout, and improving service quality while preserving its historical heritage. This case not only provides valuable practical experience for the transformation of old urban consumption spaces but also demonstrates the feasibility and potential of the new model of ‘spatial production’.

Keywords: digital logistics, urban consumption space, space production, urban renewal

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Authors: Olayinka Oduwole, Steve Sheard

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The magnetic separation of biological cells using super-magnetic beads has been used widely for various bioassays. These bioassays can further be integrated with other laboratory components to form a biosensor which can be used for cell sorting, mixing, purification, transport, manipulation etc. These bio-sensing applications have also been facilitated by the wide availability of magnetic beads which range in size and magnetic properties produced by different manufacturers. In order to improve the efficiency and separation capabilities of these biosensors, it is important to determine the magnetic force induced velocities and interaction of beads within the magnetic field; this will help biosensor users choose the desired magnetic bead for their specific application. This study presents for the first time the interaction between a pair of different sized super-paramagnetic beads suspended in a static fluid moving within a uniform magnetic field using a modified finite-time-finite-difference scheme. A captured video was used to record the trajectory pattern and a good agreement was obtained between the simulated trajectories and the video data. The model is, therefore, a good approximation for predicting the velocities as well as the interaction between various magnetic particles which differ in size and magnetic properties for bio-sensing applications requiring a low concentration of magnetic beads.

Keywords: biosensor, magnetic field, magnetic separation, super-paramagnetic bead

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Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Djaafar Fatiha, Ghalem Bachir, Hadri Bagdad

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We studied mainly the influence of temperature, thickness, molar fraction and the doping of the various layers (emitter, base, BSF and window) on the performances of a photovoltaic solar cell. In a first stage, we optimized the performances of the InGaP/GaAs dual-junction solar cell while varying its operation temperature from 275°K to 375 °K with an increment of 25°C using a virtual wafer fabrication TCAD Silvaco. The optimization at 300 °K led to the following result: Icc =14.22 mA/cm2, Voc =2.42V, FF=91.32 %, η= 22.76 % which is close with those found in the literature. In a second stage ,we have varied the molar fraction of different layers as well their thickness and the doping of both emitters and bases and we have registered the result of each variation until obtaining an optimal efficiency of the proposed solar cell at 300°K which was of Icc=14.35mA/cm2,Voc=2.47V,FF=91.34,and η=23.33% for In(1-x)Ga(x)P molar fraction( x=0.5).The elimination of a layer BSF on the back face of our cell, enabled us to make a remarkable improvement of the short-circuit current (Icc=14.70 mA/cm2) and a decrease in open circuit voltage Voc and output η which reached 1.46V and 11.97% respectively. Therefore, we could determine the critical parameters of the cell and optimize its various technological parameters to obtain the best performance for a dual junction solar cell .This work opens the way with new prospects in the field of the photovoltaic one. Such structures will thus simplify the manufacturing processes of the cells; will thus reduce the costs while producing high outputs of photovoltaic conversion.

Keywords: modeling, simulation, multijunction, optimization, Silvaco ATLAS

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: Zhuomin Zou, Thijs Van Landeghem, Elke Gruyaert

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Using supplementary cementitious materials, such as blast-furnace slag and limestone, to replace cement clinker is a promising method to reduce the carbon emissions from cement production. To efficiently use slag and limestone, it is necessary to carefully select the particle size distribution (PSD) of the binders. This study investigated the effects of the PSD of binders on the performance of slag-limestone ternary cement. The Portland cement (PC) was prepared by grinding 95% clinker + 5% gypsum. Based on the PSD parameters of the binders, three types of ternary cements with a similar overall PSD were designed, i.e., NO.1 fine slag, medium PC, and coarse limestone; NO.2 fine limestone, medium PC, and coarse slag; NO.3. fine PC, medium slag, and coarse limestone. The binder contents in the ternary cements were (a) 50 % PC, 40 % slag, and 10 % limestone (called high cement group) or (b) 35 % PC, 55 % slag, and 10 % limestone (called low cement group). The pure PC and binary cement with 50% slag and 50% PC prepared with the same binders as the ternary cement were considered as reference cements. All these cements were used to investigate the mortar performance in terms of workability, strength at 2, 7, 28, and 90 days, carbonation resistance, and non-steady state chloride migration resistance at 28 and 56 days. Results show that blending medium PC with fine slag could exhibit comparable performance to blending fine PC with medium/coarse slag in binary cement. For the three ternary cements in the high cement group, ternary cement with fine limestone (NO.2) shows the lowest strength, carbonation, and chloride migration performance. Ternary cements with fine slag (NO.1) and with fine PC (NO.3) show the highest flexural strength at early and late ages, respectively. In addition, compared with ternary cement with fine PC (NO.3), ternary cement with fine slag (NO.1) has a similar carbonation resistance and a better chloride migration resistance. For the low cement group, three ternary cements have a similar flexural and compressive strength before 7 days. After 28 days, ternary cement with fine limestone (NO.2) shows the highest flexural strength while fine PC (NO.3) has the highest compressive strength. In addition, ternary cement with fine slag (NO.1) shows a better chloride migration resistance but a lower carbonation resistance compared with the other two ternary cements. Moreover, the durability performance of ternary cement with fine PC (NO.3) is better than that of fine limestone (NO.2).

Keywords: limestone, particle size distribution, slag, ternary cement

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Authors: Muhammad Awais, Wei Li, Anjum Munir

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Biomass gasification is a process of converting solid biomass ingredients into a combustible gas which can be used in electricity generation. Regardless of their applications in many fields, biomass gasification technology is still facing many cleaning issues of syngas. Tar production in biomass gasification process is one of the biggest challenges for this technology. The aimed of this study is to evaluate the tar contents in syngas produced from wood chips, corn cobs, coconut shells and mixture of corn cobs and wood chips as biomass fuel and tar removal efficiency of different cleaning units integrated with gassifier. Performance of different cleaning units, i.e., cyclone separator, wet scrubber, biomass filter, and auxiliary filter was tested under two biomass fuels. Results of this study indicate that wood chips produced less tar of 1736 mg/Nm³ as compared to corn cobs which produced tor 2489 mg/Nm³. It is also observed that coconut shells produced a high amount of tar. It was observed that when wood chips were used as a fuel, syngas tar contents were reduced from 6600 to 112 mg/Nm³ while in case of corn cob, they were reduced from 7500 mg/Nm³ to 220 mg/Nm³. Overall tar removal efficiencies of cyclone separator, wet scrubber, biomass filter, and auxiliary filter was 72%, 63%, 74%, 35% respectively.

Keywords: biomass, gasification, tar, cleaning system, biomass filter

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Authors: Arifa Batool, Ghulam Hussain Bhatti, Syed Mujtaba Shah

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Inorganic n-type (TiO2, CdO) and p-type (NiO, CuO) metal oxide nanoparticles were synthesized by a facile wet chemical method at room temperature. The morphological, compositional, structural and optical properties were investigated by scanning electron microscopy, energy dispersive X-ray spectroscopy, FT-IR, XRD analysis, UV/Visible and fluorescence spectroscopy. All semiconducting nanoparticles were photosensitized with Ru (II) based Z907 dye in ethanol solvent by grafting. Grafting of dye on the surface of nanoparticles was confirmed by UV/Visible and FT-IR spectroscopy. The synthesized photo-active nanohybrid was thoroughly blended with P3HT, a solid electrolyte and I-V measurements under solar stimulated radiations 1000 W/m2 (AM 1.5) were recorded. Maximum incident photon to current conversion efficiency (IPCE) of 0.9% was achieved with dye functionalized Z907-TiO2 hybrid, IPCE of 0.72% was achieved with bulk-heterojunction of TiO2-Z907-CuO and IPCE of 0.68% was attained with nanocomposite of TiO2-CdO. TiO2 based Solar cells have maximum Jscvalue i.e.4.63 mA/cm2. Dye-functionalized TiO2-based photovoltaic devices were found more efficient than the reference device but the morphology of the device was a major check in progress.

Keywords: solar cell, bulk heterojunction, nanocomposites, photosensitization, dye sensitized solar cell

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Authors: Polycarpe Feussi

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Globalization, technological and customer increasing changes, amongst other drivers, result in higher levels of uncertainty and unpredictability for organizations. In order for organizations to cope with the uncertain and fast-changing economic and business environment, these organizations need to innovate in order to achieve flexibility. In simple terms, the organizations must develop strategies leading to the ability of these organizations to provide horizontal information connections across the supply chain to create and deliver products that meet customer needs by synchronization of customer demands with product creation. The generated information will create efficiency and effectiveness throughout the whole supply chain regarding production, storage, and distribution, as well as eliminating redundant activities and reduction in response time. In an integrated supply chain, spanning activities include coordination with distributors and suppliers. This paper explains how through postponement strategies, flexibility can be achieved in an organization. In order to achieve the above, a thorough literature review was conducted via the search of online websites that contains material from scientific journal data-bases, articles, and textbooks on the subject of postponement and flexibility. The findings of the research are found in the last part of the paper. The first part introduces the concept of postponement and its importance in supply chain management. The second part of the paper provides the methodology used in the process of writing the paper.

Keywords: postponement strategies, supply chain management, flexibility, logistics

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Authors: Han Longxiang

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In the process of treating industrial oily wastewater with complex components, the traditional treatment methods (flotation, coagulation, microwave heating, etc.) often produce high operating costs, secondary pollution, and other problems. In order to solve these problems, the materials with high flux and stability applied to surfactant-stabilized emulsions separation have gained huge attention in the treatment of oily wastewater. Nevertheless, four stable oil-in-water emulsions can be formed due to different surfactants (surfactant-free, anionic surfactant, cationic surfactant, and non-ionic surfactant), and the previous advanced materials can only separate one or several of them, cannot effectively separate in one step. Herein, a facile synthesis method of graphene-based multilevel filter materials (GMFM) which can efficiently separate the oil-in-water emulsions stabilized with different surfactants only through its gravity. The prepared materials with high stability of 20 cycles show a high flux of ~ 5000 L m-2 h-1 with a high separation efficiency of > 99.9 %. GMFM can effectively separate the emulsion stabilized by mixed surfactants and oily wastewater from factories. The results indicate that the GMFM have a wide range of applications in oil-in-water emulsions separation in industry and environmental science.

Keywords: emulsion, filtration, graphene, one-step

Procedia PDF Downloads 76

Authors: M. Merabet-Khelassi, Z. Houiene, L. Aribi-Zouioueche, O. Riant

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Lipases (EC.3.1.1.3) are efficient biotools widely used for their remarkable chemo-, regio- and enantio-selectivity, especially, in kinetic resolution of racemates. They offer access to a large panel of enantiopure building blocks, such as secondary benzylic alcohols, commonly used as synthetic intermediates in pharmaceutical and agrochemical industries. Due to the stability of lipases in both water and organic solvents poor in water, they are able to catalyze both transesterifications of arylalkylcarbinols and hydrolysis of their corresponding acetates. The use of enzymatic hydrolysis in aqueous media still limited. In this presentation, we expose a practical methodology for the preparation of optically enriched acetates using a Candida antarctica lipase B-catalyzed hydrolysis in non-aqueous media in the presence of alkaline carbonate salts. The influence of several parameters which can intervene on the enzymatic efficiency such as the impact of the introduction of the carbonates salts, its amount and the nature of the alkaline earth metal are discussed. The obtained results show that the use of sodium carbonate with CAL-B enhances drastically both reactivity and selectivity of this immobilized lipase. In all cases, the resulting alcohols and remaining acetates are obtained in high ee values (up to > 99 %), and the selectivities reach (E > 500).

Keywords: alkaline-hydrolysis, enzymatic kinetic resolution, lipases, arylalkylcarbinol, non-aqueous media

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Authors: Awatef Chniguir, Tarek Farah, Zouhair Ben Jemaa, Safya Belguith

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Optimal routing allows minimizing energy consumption in wireless sensor networks (WSN). Clustering has proven its effectiveness in organizing WSN by reducing channel contention and packet collision and enhancing network throughput under heavy load. Therefore, nowadays, with the emergence of the Internet of Things, heterogeneity is essential. Stable election protocol (SEP) that has increased the network stability period and lifetime is the first clustering protocol for heterogeneous WSN. SEP and its descendants, namely SEP, Threshold Sensitive SEP (TSEP), Enhanced TSEP (ETSSEP) and Current Energy Allotted TSEP (CEATSEP), were studied. These algorithms’ performance was evaluated based on different metrics, especially first node death (FND), to compare their stability. Simulations were conducted on the MATLAB tool considering two scenarios: The first one demonstrates the fraction variation of advanced nodes by setting the number of total nodes. The second considers the interpretation of the number of nodes while keeping the number of advanced nodes permanent. CEATSEP outperforms its antecedents by increasing stability and, at the same time, keeping a low throughput. It also operates very well in a large-scale network. Consequently, CEATSEP has a useful lifespan and energy efficiency compared to the other routing protocol for heterogeneous WSN.

Keywords: clustering, heterogeneous, stability, scalability, IoT, WSN

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Authors: Joelle Penniston, E. B. Gueguim-Kana

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Biohydrogen has been identified as a promising alternative to the use of non-renewable fossil reserves, owing to its sustainability and non-polluting nature. pH is considered as a key parameter in fermentative biohydrogen production processes, due to its effect on the hydrogenase activity, metabolic activity as well as substrate hydrolysis. The present study assesses the influence of regulating pH on dark fermentative biohydrogen production. Four experimental hydrogen production schemes were evaluated. Two were implemented using suspended cells under regulated pH growth conditions (Sus_R) and suspended and non-regulated pH (Sus_N). The two others regimes consisted of alginate immobilized cells under pH regulated growth conditions (Imm_R) and immobilized and non-pH regulated conditions (Imm_N). All experiments were carried out at 37.5°C with glucose as sole source of carbon. Sus_R showed a lag time of 5 hours and a peak hydrogen fraction of 36% and a glucose degradation of 37%, compared to Sus_N which showed a peak hydrogen fraction of 44% and complete glucose degradation. Both suspended culture systems showed a higher peak biohydrogen fraction compared to the immobilized cell system. Imm_R experiments showed a lag phase of 8 hours, a peak biohydrogen fraction of 35%, while Imm_N showed a lag phase of 5 hours, a peak biohydrogen fraction of 22%. 100% glucose degradation was observed in both pH regulated and non-regulated processes. This study showed that biohydrogen production in batch mode with suspended cells in a non-regulated pH environment results in a partial degradation of substrate, with lower yield. This scheme has been the culture mode of choice for most reported studies in biohydrogen research. The relatively lower slope in pH trend of the non-regulated pH experiment with immobilized cells (Imm_N) compared to Sus_N revealed that that immobilized systems have a better buffering capacity compared to suspended systems, which allows for the extended production of biohydrogen even under non-regulated pH conditions. However, alginate immobilized cultures in flask systems showed some drawbacks associated to high rate of gas production that leads to increased buoyancy of the immobilization beads. This ultimately impedes the release of gas out of the flask.

Keywords: biohydrogen, sustainability, suspended, immobilized

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Authors: M. Zake, I. Barmina, R. Valdmanis, A. Kolmickovs

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Experimental investigations of the DC electric field effect on thermal decomposition of biomass, formation of the axial flow of volatiles (CO, H2, CxHy), mixing of volatiles with swirling airflow at low swirl intensity (S ≈ 0.2-0.35), their ignition and on formation of combustion dynamics are carried out with the aim to understand the mechanism of electric field influence on biomass gasification, combustion of volatiles and heat energy production. The DC electric field effect on combustion dynamics was studied by varying the positive bias voltage of the central electrode from 0.6 kV to 3 kV, whereas the ion current was limited to 2 mA. The results of experimental investigations confirm the field-enhanced biomass gasification with enhanced release of volatiles and the development of endothermic processes at the primary stage of thermochemical conversion of biomass determining the field-enhanced heat energy consumption with the correlating decrease of the flame temperature and heat energy production at this stage of flame formation. Further, the field-enhanced radial expansion of the flame reaction zone correlates with a more complete combustion of volatiles increasing the combustion efficiency by 3 % and decreasing the mass fraction of CO, H2 and CxHy in the products, whereas by 10 % increases the average volume fraction of CO2 and the heat energy production downstream the combustor increases by 5-10 %

Keywords: biomass, combustion, electrodynamic control, gasification

Procedia PDF Downloads 432