Search results for: carbon dioxide capture

Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Dhritilekha Deka, Deepak Patwa, Ravi K., Archana M. Nair

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Bioaccumulation of heavy metal contaminants due to intense anthropogenic interference degrades the environment and ecosystem functions. Conventional physicochemical methods involve energy-intensive and costly methodologies. Phytoremediation, on the other hand, provides an efficient nature-based strategy for the reclamation of heavy metal-contaminated sites. However, the slow process and adaptation to high-concentration contaminant sequestration often limit the efficiency of the method. This necessitates natural amendments such as biochar to improve phytoextraction and stabilize the green cover. Biochar is a highly porous structure with high carbon sequestration potential and containing negatively charged functional groups that provide binding sites for the positively charged metals. This study aims to develop and determine the synergy between sugarcane bagasse biochar content and phytoremediation. A 60-day pot experiment using perennial tussock vetiver grass (Chrysopogon zizanioides) was conducted for different biochar contents of 1%, 2%, and 4% for the removal of cadmium and zinc. A concentration of 500 ppm is maintained for the amended and unamended control (CK) samples. The survival rates of the plants, biomass production, and leaf area index were measured for the plant growth characteristics. Results indicate a visible change in the plant growth and the heavy metal concentration with the biochar content. The bioconcentration factor (BCF) in the plant improved significantly for the 4% biochar content by 57% in comparison to the control CK treatment in Cd-treated soils. The Zn soils indicated the highest reduction in the metal concentration by 50% in the 2% amended samples and an increase in the BCF in all the amended samples. The translocation from the rhizosphere to the shoots was low but not dependent on the amendment content and varied for each contaminant type. The root-to-shoot ratio indicates higher values compared to the control samples. The enhanced tolerance capacities can be attributed to the nutrients released by the biochar in the soil. The study reveals the high potential of biochar as a phytoremediation amendment, but its effect is dependent on the soil and heavy metal and accumulator species.

Keywords: phytoextraction, biochar, heavy metals, chrysopogon zizanioides, bioaccumulation factor

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Authors: D. Heinemann, S. Schramm, S. Knabner, D. Baumgarten

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Purpose: Applying solder paste to printed circuit boards (PCB) with stencils has been the method of choice over the past years. A new method uses a jet printer to deposit tiny droplets of solder paste through an ejector mechanism onto the board. This allows for more flexible PCB layouts with smaller components. Due to the viscosity of the solder paste, air blisters can be trapped in the cartridge. This can lead to missing solder joints or deviations in the applied solder volume. Therefore, a built-in and real-time inspection of the printing process is needed to minimize uncertainties and increase the efficiency of the process by immediate correction. The objective of the current study is the design of an optimal imaging system and the development of an automatic algorithm for the detection of applied solder joints from optical from the captured images. Methods: In a first approach, a camera module connected to a microcomputer and LED strips are employed to capture images of the printed circuit board under four different illuminations (white, red, green and blue). Subsequently, an improved system including a ring light, an objective lens, and a monochromatic camera was set up to acquire higher quality images. The obtained images can be divided into three main components: the PCB itself (i.e., the background), the reflections induced by unsoldered positions or screw holes and the solder joints. Non-uniform illumination is corrected by estimating the background using a morphological opening and subtraction from the input image. Image sharpening is applied in order to prevent error pixels in the subsequent segmentation. The intensity thresholds which divide the main components are obtained from the multimodal histogram using three probability density functions. Determining the intersections delivers proper thresholds for the segmentation. Remaining edge gradients produces small error areas which are removed by another morphological opening. For quantitative analysis of the segmentation results, the dice coefficient is used. Results: The obtained PCB images show a significant gradient in all RGB channels, resulting from ambient light. Using different lightings and color channels 12 images of a single PCB are available. A visual inspection and the investigation of 27 specific points show the best differentiation between those points using a red lighting and a green color channel. Estimating two thresholds from analyzing the multimodal histogram of the corrected images and using them for segmentation precisely extracts the solder joints. The comparison of the results to manually segmented images yield high sensitivity and specificity values. Analyzing the overall result delivers a Dice coefficient of 0.89 which varies for single object segmentations between 0.96 for a good segmented solder joints and 0.25 for single negative outliers. Conclusion: Our results demonstrate that the presented optical imaging system and the developed algorithm can robustly detect solder joints on printed circuit boards. Future work will comprise a modified lighting system which allows for more precise segmentation results using structure analysis.

Keywords: printed circuit board jet-printing, inspection, segmentation, solder paste detection

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Authors: Nataša Todorović, Jovana Nikolov, Ivana Stojković, Milan Vraneš, Jovana Panić, Slobodan Gadžurić

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The detection of ²¹⁰Pb levels in aquatic environments evokes interest in various scientific studies. Its precise determination is important not only for the radiological assessment of drinking waters but also ²¹⁰Pb, and ²¹⁰Po distribution in the marine environment are significant for the assessment of the removal rates of particles from the ocean and particle fluxes during transport along the coast, as well as particulate organic carbon export in the upper ocean. Measurement techniques for ²¹⁰Pb determination, gamma spectrometry, alpha spectrometry, or liquid scintillation counting (LSC) are either time-consuming or demand expensive equipment or complicated chemical pre-treatments. However, one other possibility is to measure ²¹⁰Pb on an LS counter if it is in equilibrium with its progeny ²¹⁰Bi - through the Cherenkov counting method. It is unaffected by the chemical quenching and assumes easy sample preparation but has the drawback of lower counting efficiencies than standard LSC methods, typically from 10% up to 20%. The aim of the presented research in this paper is to investigate the possible increment of detection efficiency of Cherenkov counting during ²¹⁰Pb/²¹⁰Bi detection on an LS counter Quantulus 1220. Considering naturally low levels of ²¹⁰Pb in aqueous samples, the addition of ionic liquids to the counting vials with the analysed samples has the benefit of detection limit’s decrement during ²¹⁰Pb quantification. Our results demonstrated that ionic liquid, 1-butyl-3-methylimidazolium salicylate, is more efficient in Cherenkov counting efficiency increment than the previously explored 2-hydroxypropan-1-amminium salicylate. Consequently, the impact of a few other ionic liquids that were synthesized with the same cation group (1-butyl-3-methylimidazolium benzoate, 1-butyl-3-methylimidazolium 3-hydroxybenzoate, and 1-butyl-3-methylimidazolium 4-hydroxybenzoate) was explored in order to test their potential influence on Cherenkov counting efficiency. It was confirmed that, among the explored ones, only ionic liquids in the form of salicylates exhibit a wavelength shifting effect. Namely, the addition of small amounts (around 0.8 g) of 1-butyl-3-methylimidazolium salicylate increases the detection efficiency from 16% to >70%, consequently reducing the detection threshold by more than four times. Moreover, the addition of ionic liquids could find application in the quantification of other radionuclides besides ²¹⁰Pb/²¹⁰Bi via Cherenkov counting method.

Keywords: liquid scintillation counting, ionic liquids, Cherenkov counting, ²¹⁰PB/²¹⁰BI in water

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Authors: Vijaya Dixit Aasheesh Dixit

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Shipbuilding industry operates in Engineer Procure Construct (EPC) context. Product mix of a shipyard comprises of various types of ships like bulk carriers, tankers, barges, coast guard vessels, sub-marines etc. Each order is unique based on the type of ship and customized requirements, which are engineered into the product right from design stage. Thus, to execute every new project, a shipyard needs to upgrade its production expertise. As a result, over the long run, holistic learning occurs across different types of projects which contributes to the knowledge base of the shipyard. Simultaneously, in the short term, during execution of a project comprising of multiple sister ships, repetition of similar tasks leads to learning at activity level. This research aims to capture above learnings of a shipyard and incorporate learning curve effect in project scheduling and materials procurement to improve project performance. Extant literature provides support for the existence of such learnings in an organization. In shipbuilding, there are sequences of similar activities which are expected to exhibit learning curve behavior. For example, the nearly identical structural sub-blocks which are successively fabricated, erected, and outfitted with piping and electrical systems. Learning curve representation can model not only a decrease in mean completion time of an activity, but also a decrease in uncertainty of activity duration. Sister ships have similar material requirements. The same supplier base supplies materials for all the sister ships within a project. On one hand, this provides an opportunity to reduce transportation cost by batching the order quantities of multiple ships. On the other hand, it increases the inventory holding cost at shipyard and the risk of obsolescence. Further, due to learning curve effect the production scheduled of each consequent ship gets compressed. Thus, the material requirement schedule of every next ship differs from its previous ship. As more and more ships get constructed, compressed production schedules increase the possibility of batching the orders of sister ships. This work aims at integrating materials management with project scheduling of long duration projects for manufacturing of multiple sister ships. It incorporates the learning curve effect on progressively compressing material requirement schedules and addresses the above trade-off of transportation cost and inventory holding and shortage costs while satisfying budget constraints of various stages of the project. The activity durations and lead time of items are not crisp and are available in the form of probabilistic distribution. A Stochastic Mixed Integer Programming (SMIP) model is formulated which is solved using evolutionary algorithm. Its output provides ordering dates of items and degree of order batching for all types of items. Sensitivity analysis determines the threshold number of sister ships required in a project to leverage the advantage of learning curve effect in materials management decisions. This analysis will help materials managers to gain insights about the scenarios: when and to what degree is it beneficial to treat a multiple ship project as an integrated one by batching the order quantities and when and to what degree to practice distinctive procurement for individual ship.

Keywords: learning curve, materials management, shipbuilding, sister ships

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Authors: Nada Poropat Jeletic, Gordana Hrzica

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Bilingual conversational corpora represent a meaningful and the most comprehensive data source for investigating the genuine contact phenomena in non-monitored bi-lingual speech productions. They can be particularly useful for bilingual research since some features of bilingual interaction can hardly be accessed with more traditional methodologies (e.g., elicitation tasks). The method of language sampling provides the resources for describing language interaction in a bilingual community and/or in bilingual situations (e.g. code-switching, amount of languages used, number of languages used, etc.). To capture these phenomena in genuine communication situations, such sampling should be as close as possible to spontaneous communication. Bilingual spoken corpus design is methodologically demanding. Therefore this paper aims at describing the methodological challenges that apply to the corpus design of the conversational corpus design of the Istrian Istrovenetian-Croatian Bilingual Corpus. Croatian is the first official language of the Croatian-Italian officially bilingual Istria County, while Istrovenetian is a diatopic subvariety of Venetian, a longlasting lingua franca in the Istrian peninsula, the mother tongue of the members of the Italian National Community in Istria and the primary code of informal everyday communication among the Istrian Italophone population. Within the CLARIN infrastructure, TalkBank is being used, as it provides relevant procedures for designing and analyzing bilingual corpora. Furthermore, it allows public availability allows for easy replication of studies and cumulative progress as a research community builds up around the corpus, while the tools developed within the field of corpus linguistics enable easy retrieval and analysis of information. The method of language sampling employed is kept at the level of spontaneous communication, in order to maximise the naturalness of the collected conversational data. All speakers have provided written informed consent in which they agree to be recorded at a random point within the period of one month after signing the consent. Participants are administered a background questionnaire providing information about the socioeconomic status and the exposure and language usage in the participants social networks. Recording data are being transcribed, phonologically adapted within a standard-sized orthographic form, coded and segmented (speech streams are being segmented into communication units based on syntactic criteria) and are being marked following the CHAT transcription system and its associated CLAN suite of programmes within the TalkBank toolkit. The corpus consists of transcribed sound recordings of 36 bilingual speakers, while the target is to publish the whole corpus by the end of 2020, by sampling spontaneous conversations among approximately 100 speakers from all the bilingual areas of Istria for ensuring representativeness (the participants are being recruited across three generations of native bilingual speakers in all the bilingual areas of the peninsula). Conversational corpora are still rare in TalkBank, so the Corpus will contribute to BilingBank as a highly relevant and scientifically reliable resource for an internationally established and active research community. The impact of the research of communities with societal bilingualism will contribute to the growing body of research on bilingualism and multilingualism, especially regarding topics of language dominance, language attrition and loss, interference and code-switching etc.

Keywords: conversational corpora, bilingual corpora, code-switching, language sampling, corpus design methodology

Procedia PDF Downloads 126

Authors: L. Pu, C. Unluer

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MgO cements have the potential to sequester CO2 in construction products, and can be partial or complete replacement of PC in concrete. Construction block is a promising application for reactive MgO cements. Main advantages of blocks are: (i) suitability for sequestering CO2 due to their initially porous structure; (ii) lack of need for in-situ treatment as carbonation can take place during fabrication; and (iii) high potential for commercialization. Both strength gain and carbon sequestration of MgO cements depend on carbonation process. Fly ash and ground granulated blast-furnace slag (GGBS) are pozzolanic material and are proved to improve many of the performance characteristics of the concrete, such as strength, workability, permeability, durability and corrosion resistance. A very limited amount of work has been reported on the production of MgO blocks on a large scale so far. A much more extensive study, wherein blocks with different mix design is needed to verify the feasibility of commercial production. The changes in the performance of the samples were evaluated by compressive strength testing. The properties of the carbonation products were identified by X-ray diffraction (XRD) and scanning electron microscopy (SEM)/ field emission scanning electron microscopy (FESEM), and the degree of carbonation was obtained by thermogravimetric analysis (TGA), XRD and energy dispersive X-ray (EDX). The results of this study enabled the understanding the relationship between lab-scale samples and scale-up blocks based on their mechanical performance and microstructure. Results indicate that for both scaled-up and lab-scale samples, MgO samples always had the highest strength results, followed by MgO-fly ash samples and MgO-GGBS had relatively lowest strength. The lower strength of MgO with fly ash/GGBS samples at early stage is related to the relatively slow hydration process of pozzolanic materials. Lab-scale cubic samples were observed to have higher strength results than scaled-up samples. The large size of the scaled-up samples made it more difficult to let CO2 to reach inner part of the samples and less carbonation products formed. XRD, TGA and FESEM/EDX results indicate the existence of brucite and HMCs in MgO samples, M-S-H, hydrotalcite in the MgO-fly ash samples and C-S-H, hydrotalctie in the MgO-GGBS samples. Formation of hydration products (M-S-H, C-S-H, hydrotalcite) and carbonation products (hydromagnecite, dypingite) increased with curing duration, which is the reason of increasing strength. This study verifies the advantage of large-scale MgO blocks over common PC blocks and the feasibility of commercial production of MgO blocks.

Keywords: reactive MgO, fly ash, ground granulated blast-furnace slag, carbonation, CO₂

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Authors: Md. Kausar Alam, Ramin Motamed

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The damaging effects of liquefaction-induced ground movements have been frequently observed in past earthquakes, such as the 2010-2011 Canterbury Earthquake Sequence (CES) in New Zealand and the 2011 Tohoku earthquake in Japan. To reduce the consequences of soil liquefaction at shallow depths, various ground improvement techniques have been utilized in engineering practice, among which this research is focused on experimentally evaluating the press-in sheet piling technique. The press-in sheet pile technique eliminates the vibration, hammering, and noise pollution associated with dynamic sheet pile installation methods. Unfortunately, there are limited experimental studies on the press-in sheet piling technique for liquefaction mitigation using 1g shake table tests in which all the controlling mechanisms of liquefaction-induced foundation settlement, including sand ejecta, can be realistically reproduced. In this study, a series of moderate scale 1g shake table experiments were conducted at the University of Nevada, Reno, to evaluate the performance of this technique in liquefiable soil layers. First, a 1/5 size model was developed based on a recent UC San Diego shaking table experiment. The scaled model has a density of 50% for the top crust, 40% for the intermediate liquefiable layer, and 85% for the bottom dense layer. Second, a shallow foundation is seated atop an unsaturated sandy soil crust. Third, in a series of tests, a sheet pile with variable embedment depth is inserted into the liquefiable soil using the press-in technique surrounding the shallow foundations. The scaled models are subjected to harmonic input motions with amplitude and dominant frequency properly scaled based on the large-scale shake table test. This study assesses the performance of the press-in sheet piling technique in terms of reductions in the foundation movements (settlement and tilt) and generated excess pore water pressures. In addition, this paper discusses the cost-effectiveness and carbon footprint features of the studied mitigation measures.

Keywords: excess pore water pressure, foundation settlement, press-in sheet pile, soil liquefaction

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Authors: Yana Snegireva

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Carbonate reservoirs are known for their heterogeneity, resulting from various geological processes such as diagenesis and fracturing. These complexities may cause great challenges in understanding fluid flow behavior and predicting the production performance of naturally fractured reservoirs. The investigation of carbonate reservoirs is crucial, as many petroleum reservoirs are naturally fractured, which can be difficult due to the complexity of their fracture networks. This can lead to geological uncertainties, which are important for global petroleum reserves. The problem outlines the key challenges in carbonate reservoir modeling, including the accurate representation of fractures and their connectivity, as well as capturing the impact of fractures on fluid flow and production. Traditional reservoir modeling techniques often oversimplify fracture networks, leading to inaccurate predictions. Therefore, there is a need for a modern approach that can capture the complexities of carbonate reservoirs and provide reliable predictions for effective reservoir management and production optimization. The modern approach to carbonate reservoir modeling involves the utilization of the hybrid fracture modeling approach, including the discrete fracture network (DFN) method and implicit fracture network, which offer enhanced accuracy and reliability in characterizing complex fracture systems within these reservoirs. This study focuses on the application of the hybrid method in the Nepsko-Botuobinskaya anticline of the Eastern Siberia field, aiming to prove the appropriateness of this method in these geological conditions. The DFN method is adopted to model the fracture network within the carbonate reservoir. This method considers fractures as discrete entities, capturing their geometry, orientation, and connectivity. But the method has significant disadvantages since the number of fractures in the field can be very high. Due to limitations in the amount of main memory, it is very difficult to represent these fractures explicitly. By integrating data from image logs (formation micro imager), core data, and fracture density logs, a discrete fracture network (DFN) model can be constructed to represent fracture characteristics for hydraulically relevant fractures. The results obtained from the DFN modeling approaches provide valuable insights into the East Siberia field's carbonate reservoir behavior. The DFN model accurately captures the fracture system, allowing for a better understanding of fluid flow pathways, connectivity, and potential production zones. The analysis of simulation results enables the identification of zones of increased fracturing and optimization opportunities for reservoir development with the potential application of enhanced oil recovery techniques, which were considered in further simulations on the dual porosity and dual permeability models. This approach considers fractures as separate, interconnected flow paths within the reservoir matrix, allowing for the characterization of dual-porosity media. The case study of the East Siberia field demonstrates the effectiveness of the hybrid model method in accurately representing fracture systems and predicting reservoir behavior. The findings from this study contribute to improved reservoir management and production optimization in carbonate reservoirs with the use of enhanced and improved oil recovery methods.

Keywords: carbonate reservoir, discrete fracture network, fracture modeling, dual porosity, enhanced oil recovery, implicit fracture model, hybrid fracture model

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Authors: Jose Daniel Giraldo Arias, Camilo Rojas Gomez, David Villegas Delgado, Gullermo Idarraga Alarcon, Juan Meza Meza

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The reverse engineering processes are widely used in the industry with the main goal to determine the materials and the manufacture used to produce a component. There are a lot of characterization techniques and computational tools that are used in order to get this information. A study case of a reverse engineering applied to a secondary sandwich- hybrid type structure used in a helicopter is presented. The methodology used consists of five main steps, which can be applied to any other similar component: Collect information about the service conditions of the part, disassembly and dimensional characterization, functional characterization, material properties characterization and manufacturing processes characterization, allowing to obtain all the supports of the traceability of the materials and processes of the aeronautical products that ensure their airworthiness. A detailed explanation of each step is covered. Criticality and comprehend the functionalities of each part, information of the state of the art and information obtained from interviews with the technical groups of the helicopter’s operators were analyzed,3D optical scanning technique, standard and advanced materials characterization techniques and finite element simulation allow to obtain all the characteristics of the materials used in the manufacture of the component. It was found that most of the materials are quite common in the aeronautical industry, including Kevlar, carbon, and glass fibers, aluminum honeycomb core, epoxy resin and epoxy adhesive. The stacking sequence and volumetric fiber fraction are a critical issue for the mechanical behavior; a digestion acid method was used for this purpose. This also helps in the determination of the manufacture technique which for this case was Vacuum Bagging. Samples of the material were manufactured and submitted to mechanical and environmental tests. These results were compared with those obtained during reverse engineering, which allows concluding that the materials and manufacture were correctly determined. Tooling for the manufacture was designed and manufactured according to the geometry and manufacture process requisites. The part was manufactured and the mechanical, and environmental tests required were also performed. Finally, a geometric characterization and non-destructive techniques allow verifying the quality of the part.

Keywords: reverse engineering, sandwich-structured composite parts, helicopter, mechanical properties, prototype

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Authors: Sagar Saroha, Sawan S. Sinha, Sunil Lakshmipathy

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Reynolds averaged Navier-Stokes (RANS) model is the popular computational tool for prediction of turbulent flows. Being computationally less expensive as compared to direct numerical simulation (DNS), RANS has received wide acceptance in industry and research community as well. However, for high Reynolds number flows, the traditional RANS approach based on the Boussinesq hypothesis is incapacitated to capture all the essential flow characteristics, and thus, its performance is restricted in high Reynolds number flows of practical interest. RANS performance turns out to be inadequate in regimes like flow over curved surfaces, flows with rapid changes in the mean strain rate, duct flows involving secondary streamlines and three-dimensional separated flows. In the recent decade, partially averaged Navier-Stokes (PANS) methodology has gained acceptability among seamless bridging methods of turbulence- placed between DNS and RANS. PANS methodology, being a scale resolving bridging method, is inherently more suitable than RANS for simulating turbulent flows. The superior ability of PANS method has been demonstrated for some cases like swirling flows, high-speed mixing environment, and high Reynolds number turbulent flows. In our work, we intend to evaluate PANS in case of separated turbulent flows past bluff bodies -which is of broad aerodynamic research and industrial application. PANS equations, being derived from base RANS, continue to inherit the inadequacies from the parent RANS model based on linear eddy-viscosity model (LEVM) closure. To enhance PANS’ capabilities for simulating separated flows, the shortcomings of the LEVM closure need to be addressed. Inabilities of the LEVMs have inspired the development of non-linear eddy viscosity models (NLEVM). To explore the potential improvement in PANS performance, in our study we evaluate the PANS behavior in conjugation with NLEVM. Our work can be categorized into three significant steps: (i) Extraction of PANS version of NLEVM from RANS model, (ii) testing the model in the homogeneous turbulence environment and (iii) application and evaluation of the model in the canonical case of separated non-homogeneous flow field (flow past prismatic bodies and bodies of revolution at high Reynolds number). PANS version of NLEVM shall be derived and implemented in OpenFOAM -an open source solver. Homogeneous flows evaluation will comprise the study of the influence of the PANS’ filter-width control parameter on the turbulent stresses; the homogeneous analysis performed over typical velocity fields and asymptotic analysis of Reynolds stress tensor. Non-homogeneous flow case will include the study of mean integrated quantities and various instantaneous flow field features including wake structures. Performance of PANS + NLEVM shall be compared against the LEVM based PANS and LEVM based RANS. This assessment will contribute to significant improvement of the predictive ability of the computational fluid dynamics (CFD) tools in massively separated turbulent flows past bluff bodies.

Keywords: bridging methods of turbulence, high Re-CFD, non-linear PANS, separated turbulent flows

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Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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Authors: Chethana V. Casiker, Jagadishakumara B., Sunil G. M., Chaithra K., M. Soubadra Devy

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A majority of the world’s food crops depends on insects for pollination, among which bees are the most dominant taxon. Bees pollinate vegetables, fruits and oilseeds which are rich in essential micronutrients. Besides being a prerequisite for a nutritionally secure diet, agrarian economies such as India depend heavily on pollination for good yield and quality of the product. As cities all over the world expand rapidly, large tracts of green spaces are being built up. This, along with high usage of agricultural chemicals has reduced floral diversity and shrunk bee habitats. Indeed, pollinator decline is being reported from various parts of the world. Further, the FAO has reported a huge increase in the area of land under cultivation of pollinator-dependent crops. In the light of increasing demand for pollination and disappearing natural habitats, it is critical to understand whether and how urban spaces can support pollinators. To this end, this study investigates the influence of landscape and local habitat quality on bee community dynamics. To capture the dynamics of expanding cityscapes, the study employs a space for time substitution, wherein a transect along the gradient of urbanization substitutes a timeframe of increasing urbanization. This will help understand how pollinators would respond to changes induced by increasing intensity of urbanization in the future. Bengaluru, one of the fastest growing cities of Southern India, is an excellent site to study impacts associated with urbanization. With sites moving away from the Bengaluru’s centre and towards its peripheries, this study captures the changes in bee species diversity and richness along a gradient of urbanization. Bees were sampled under different land use types as well as in different types of vegetation, including plantations, croplands, fallow land, parks, lake embankments, and private gardens. The relationship between bee community metrics and key drivers such as a percentage of built-up area, land use practices, and floral resources was examined. Additionally, data collected using questionnaire interviews were used to understand people’s perceptions towards and level of dependence on pollinators. Our results showed that urban areas are capable of supporting bees. In fact, a greater diversity of bees was recorded in urban sites compared to adjoining rural areas. This suggests that bees are able to seek out patchy resources and survive in small fragments of habitat. Bee abundance and species richness correlated positively with floral abundance and richness, indicating the role of vegetation in providing forage and nesting sites which are crucial to their survival. Bee numbers were seen to decrease with increase in built-up area demonstrating that impervious surfaces could act as deterrents. Findings from this study challenge the popular notion of cities being biodiversity-bare spaces. There is indeed scope for conserving bees in urban landscapes, provided that there are city-scale planning and local initiative. Bee conservation can go hand in hand with efforts such as urban gardening and terrace farming that could help cities urbanize sustainably.

Keywords: bee, landscape ecology, urbanization, urban pollination

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Authors: Abbas Ahmadi, Bijan Raie, Mohammad Reza Neyshabouri, Mohammad Ali Ghorbani, Farrokh Asadzadeh

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In recent years, vast areas of Urmia Lake in Dasht-e-Tabriz has dried up leading to saline sediments exposure on the surface lake coastal areas being highly susceptible to wind erosion. This study was conducted to investigate wind erosion and its relevance to soil physicochemical properties and also modeling of wind erodibility (WE) using artificial intelligence techniques. For this purpose, 96 soil samples were collected from 0-5 cm depth in 414000 hectares using stratified random sampling method. To measure the WE, all samples (<8 mm) were exposed to 5 different wind velocities (9.5, 11, 12.5, 14.1 and 15 m s-1 at the height of 20 cm) in wind tunnel and its relationship with soil physicochemical properties was evaluated. According to the results, WE varied within the range of 76.69-9.98 (g m-2 min-1)/(m s-1) with a mean of 10.21 and coefficient of variation of 94.5% showing a relatively high variation in the studied area. WE was significantly (P<0.01) affected by soil physical properties, including mean weight diameter, erodible fraction (secondary particles smaller than 0.85 mm) and percentage of the secondary particle size classes 2-4.75, 1.7-2 and 0.1-0.25 mm. Results showed that the mean weight diameter, erodible fraction and percentage of size class 0.1-0.25 mm demonstrated stronger relationship with WE (coefficients of determination were 0.69, 0.67 and 0.68, respectively). This study also compared efficiency of multiple linear regression (MLR), gene expression programming (GEP), artificial neural network (MLP), artificial neural network based on genetic algorithm (MLP-GA) and artificial neural network based on whale optimization algorithm (MLP-WOA) in predicting of soil wind erodibility in Dasht-e-Tabriz. Among 32 measured soil variable, percentages of fine sand, size classes of 1.7-2.0 and 0.1-0.25 mm (secondary particles) and organic carbon were selected as the model inputs by step-wise regression. Findings showed MLP-WOA as the most powerful artificial intelligence techniques (R2=0.87, NSE=0.87, ME=0.11 and RMSE=2.9) to predict soil wind erodibility in the study area; followed by MLP-GA, MLP, GEP and MLR and the difference between these methods were significant according to the MGN test. Based on the above finding MLP-WOA may be used as a promising method to predict soil wind erodibility in the study area.

Keywords: wind erosion, erodible fraction, gene expression programming, artificial neural network

Procedia PDF Downloads 50

Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

Procedia PDF Downloads 49

Authors: Chabungbam Niranjit Khuman, Makarand Madhao Ghangrekar, Arunabha Mitra

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The cost of aeration is one of the limiting factors in the upscaling of microbial fuel cells (MFC) for field-scale applications. Wetland macrophytes have the ability to release oxygen into the water to maintain aerobic conditions in their root zone. In this experiment, the efficacy of rhizospheric oxygen release of wetland macrophytes as a source of oxygen in the cathodic chamber of MFC was conducted. The experiment was conducted in an MFC consisting of a three-liter anodic chamber made of ceramic cylinder and a 27 L cathodic chamber. Untreated carbon felts were used as electrodes (i.e., anode and cathode) and connected to an external load of 100 Ω using stainless steel wire. Wetland macrophytes (Canna indica) were grown in the cathodic chamber of the MFC in a hydroponic fashion using a styrofoam sheet (termed as macrophytes assisted-microbial fuel cell, M-MFC). The catholyte (i.e., water) in the M-MFC had negligible contact with atmospheric air due to the styrofoam sheet used for maintaining the hydroponic condition. There was no mixing of the catholyte in the M-MFC. Sucrose based synthetic wastewater having chemical oxygen demand (COD) of 3000 mg/L was fed into the anodic chamber of the MFC in fed-batch mode with a liquid retention time of four days. The C. indica thrived well throughout the duration of the experiment without much care. The average dissolved oxygen (DO) concentration and pH value in the M-MFC were 3.25 mg/L and 7.07, respectively, in the catholyte. Since the catholyte was not in contact with air, the DO in the catholyte might be considered as solely liberated from the rhizospheric oxygen release of C. indica. The maximum COD removal efficiency of M-MFC observed during the experiment was 76.9%. The inadequacy of terminal electron acceptor in the cathodic chamber in M-MFC might have hampered the electron transfer, which in turn, led to slower specific microbial activity, thereby resulting in lower COD removal efficiency than the traditional MFC with aerated catholyte. The average operating voltage (OV) and open-circuit voltage (OCV) of 294 mV and 594 mV, respectively, were observed in M-MFC. The maximum power density observed during polarization was 381 mW/m³, and the maximum sustainable power density observed during the experiment was 397 mW/m³ in M-MFC. The maximum normalized energy recovery and coulombic efficiency of 38.09 Wh/m³ and 1.27%, respectively, were observed. Therefore, it was evidenced that rhizospheric oxygen release of wetland macrophytes (C. indica) was capable of sustaining the cathodic reaction in MFC for field-scale applications.

Keywords: hydroponic, microbial fuel cell, rhizospheric oxygen release, wetland macrophytes

Procedia PDF Downloads 120

Authors: Omaima A. Sharaf, Tarek A. Moussa, Said M. Badr El-Din, H. Moawad

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Background: Polycyclic aromatic hydrocarbons (PAHs) pose great environmental and human health concerns for their widespread occurrence, persistence, and carcinogenic properties. PAHs releases due to anthropogenic activities to the wider environment have led to higher concentrations of these contaminants than would be expected from natural processes alone. This may result in a wide range of environmental problems that can accumulate in agricultural ecosystems, which threatened to become a negative impact on sustainable agricultural development. Thus, this study aimed to evaluate the physico-chemical, and microbial properties of the compost leachate (CL) to assess its role as nutrient and microbial source (biostimulation/bioaugmentation) for developing a cost-effective bioremediation technology for PAHs contaminated sites. Material and Methods: PAHs-degrading bacteria were isolated from CL that was collected from a composting site located in central Scotland, UK. Isolation was carried out by enrichment using phenanthrene (PHR), pyrene (PYR) and benzo(a)pyrene (BaP) as the sole source of carbon and energy. The isolates were characterized using a variety of phenotypic and molecular properties. Six different isolates were identified based on the difference in morphological and biochemical tests. The efficiency of these isolates in PAHs utilization was assessed. Further analysis was performed to define taxonomical status and phylogenic relation between the most potent PAHs-utilizing bacterial strains and other standard strains, using molecular approach by partial 16S rDNA gene sequence analysis. Results indicated that the 16S rDNA sequence analysis confirmed the results of biochemical identification, as both of biochemical and molecular identification of the isolates assigned them to Bacillus licheniformis, Pseudomonas aeruginosa, Alcaligenes faecalis, Serratia marcescens, Enterobacter cloacae and Providenicia which were identified as the prominent PAHs-utilizers isolated from CL. Conclusion: This study indicates that the CL samples contain a diverse population of PAHs-degrading bacteria and the use of CL may have a potential for bioremediation of PAHs contaminated sites.

Keywords: polycyclic aromatic hydrocarbons, physico-chemical analyses, compost leachate, microbial and biochemical analyses, phylogenic relations, 16S rDNA sequence analysis

Procedia PDF Downloads 255

Authors: Haowen Xu, Xiaobing Liu, Jin Dong, Jianming Lian

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Emerging smart buildings often employ cyberinfrastructure, cyber-physical systems, and Internet of Things (IoT) technologies to increase the automation and responsiveness of building operations for better energy efficiency and lower carbon emission. These operations include the control of Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems, which are often considered a major source of energy consumption in both commercial and residential buildings. Developing energy-saving control models for optimizing HVAC operations usually requires the collection of high-quality instrumental data from iterations of in-situ building experiments, which can be time-consuming and labor-intensive. This abstract describes a digital twin approach to automate building energy experiments for optimizing HVAC operations through the design and development of an adaptive web-based platform. The platform is created to enable (a) automated data acquisition from a variety of IoT-connected HVAC instruments, (b) real-time situational awareness through domain-based visualizations, (c) adaption of HVAC optimization algorithms based on experimental data, (d) sharing of experimental data and model predictive controls through web services, and (e) cyber-physical control of individual instruments in the HVAC system using outputs from different optimization algorithms. Through the digital twin approach, we aim to replicate a real-world building and its HVAC systems in an online computing environment to automate the development of building-specific model predictive controls and collaborative experiments in buildings located in different climate zones in the United States. We present two case studies to demonstrate our platform’s capability for real-time situational awareness and cyber-physical control of the HVAC in the flexible research platforms within the Oak Ridge National Laboratory (ORNL) main campus. Our platform is developed using adaptive and flexible architecture design, rendering the platform generalizable and extendable to support HVAC optimization experiments in different types of buildings across the nation.

Keywords: energy-saving buildings, digital twins, HVAC, cyber-physical system, BIM

Procedia PDF Downloads 88

Authors: Miaomiao Zhang, Sabrina Beckmann, Haluk Ertan, Rocky Chau, Mike Manefield

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Phenazines are a large class of nitrogen-containing aromatic heterocyclic compounds, which are almost exclusively produced by bacteria from diverse genera including Pseudomonas and Streptomyces. Phenazine-1-carboxylic acid (PCA) as one of 'core' phenazines are converted from chorismic acid before modified to other phenazine derivatives in different cells. Phenazines have attracted enormous interests because of their multiple roles on biocontrol, bacterial interaction, biofilm formation and fitness of their producers. However, in spite of ecological importance, degradation as a part of phenazines’ fate only have extremely limited attention now. Here, to isolate PCA-degrading bacteria, 200 mg L-1 PCA was supplied as sole carbon, nitrogen and energy source in minimal mineral medium. Quantitative PCR and Reverse-transcript PCR were employed to study abundance and activity of functional gene MFORT 16269 in PCA degradation, respectively. Intermediates and products of PCA degradation were identified with LC-MS/MS. After enrichment and isolation, a PCA-degrading strain was selected from soil and was designated as Rhodanobacter sp. PCA2 based on full 16S rRNA sequencing. As determined by HPLC, strain PCA2 consumed 200 mg L-1 (836 µM) PCA at a rate of 17.4 µM h-1, accompanying with significant cells yield from 1.92 × 105 to 3.11 × 106 cells per mL. Strain PCA2 was capable of degrading other phenazines as well, including phenazine (4.27 µM h-1), pyocyanin (2.72 µM h-1), neutral red (1.30 µM h-1) and 1-hydroxyphenazine (0.55 µM h-1). Moreover, during the incubation, transcript copies of MFORT 16269 gene increased significantly from 2.13 × 106 to 8.82 × 107 copies mL-1, which was 2.77 times faster than that of the corresponding gene copy number (2.20 × 106 to 3.32 × 107 copies mL-1), indicating that MFORT 16269 gene was activated and played roles on PCA degradation. As analyzed by LC-MS/MS, decarboxylation from the ring structure was determined as the first step of PCA degradation, followed by cleavage of nitrogen-containing ring by dioxygenase which catalyzed phenazine to nitrosobenzene. Subsequently, phenylhydroxylamine was detected after incubation for two days and was then transferred to aniline and catechol. Additionally, genomic and proteomic analyses were also carried out for strain PCA2. Overall, the findings presented here showed that a newly isolated strain Rhodanobacter sp. PCA2 was capable of degrading phenazines through decarboxylation and cleavage of nitrogen-containing ring, during which MFORT 16269 gene was activated and played important roles.

Keywords: decarboxylation, MFORT16269 gene, phenazine-1-carboxylic acid degradation, Rhodanobacter sp. PCA2

Procedia PDF Downloads 213

Authors: L. Kanoksak, N. Sukanya, L. Napatsorn, T. Siriporn

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A growing population and demand for packaging are driving up the usage of natural resources as raw materials in the pulp and paper industry. Long-term effects of environmental is disrupting people's way of life all across the planet. Finding pulp sources to replace wood pulp is therefore necessary. To produce wood pulp, various other potential plants or plant parts can be employed as substitute raw materials. For example, pulp and paper were made from agricultural residue that mainly included pulp can be used in place of wood. In this study, cocoa pod husks were an agricultural residue of the cocoa and chocolate industries. To develop composite materials to replace wood pulp in packaging materials. The paper was coated with polybutylene adipate-co-terephthalate (PBAT). By selecting and cleaning fresh cocoa pod husks, the size was reduced. And the cocoa pod husks were dried. The morphology and elemental composition of cocoa pod husks were studied. To evaluate the mechanical and physical properties, dried cocoa husks were extracted using the soda-pulping process. After selecting the best formulations, paper with a PBAT bioplastic coating was produced on a paper-forming machine Physical and mechanical properties were studied. By using the Field Emission Scanning Electron Microscope/Energy Dispersive X-Ray Spectrometer (FESEM/EDS) technique, the structure of dried cocoa pod husks showed the main components of cocoa pod husks. The appearance of porous has not been found. The fibers were firmly bound for use as a raw material for pulp manufacturing. Dry cocoa pod husks contain the major elements carbon (C) and oxygen (O). Magnesium (Mg), potassium (K), and calcium (Ca) were minor elements that were found in very small levels. After that cocoa pod husks were removed from the soda-pulping process. It found that the SAQ5 formula produced pulp yield, moisture content, and water drainage. To achieve the basis weight by TAPPI T205 sp-02 standard, cocoa pod husk pulp and modified starch were mixed. The paper was coated with bioplastic PBAT. It was produced using bioplastic resin from the blown film extrusion technique. It showed the contact angle, dispersion component and polar component. It is an effective hydrophobic material for rigid packaging applications.

Keywords: cocoa pod husks, agricultural residue, composite material, rigid packaging

Procedia PDF Downloads 64

Authors: Regiane A. Oliveira, Carlos E. Vaz Rossell, Rubens Maciel Filho

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Lactic acid, besides a valuable chemical may be considered a platform for other chemicals. In fact, the feasibility of hemicellulosic sugars as feedstock for lactic acid production process, may represent the drop of some of the barriers for the second generation bioproducts, especially bearing in mind the 5-carbon sugars from the pre-treatment of sugarcane bagasse. Bearing this in mind, the purpose of this study was to use the hemicellulosic liquor from sugarcane bagasse as a substrate to produce lactic acid by fermentation. To release of sugars from hemicellulose it was made a pre-treatment with a diluted sulfuric acid in order to obtain a xylose's rich liquor with low concentration of inhibiting compounds for fermentation (≈ 67% of xylose, ≈ 21% of glucose, ≈ 10% of cellobiose and arabinose, and around 1% of inhibiting compounds as furfural, hydroxymethilfurfural and acetic acid). The hemicellulosic sugars associated with 20 g/L of yeast extract were used in a fermentation process with Lactobacillus plantarum to produce lactic acid. The fermentation process pH was controlled with automatic injection of Ca(OH)2 to keep pH at 6.00. The lactic acid concentration remained stable from the time when the glucose was depleted (48 hours of fermentation), with no further production. While lactic acid is produced occurs the concomitant consumption of xylose and glucose. The yield of fermentation was 0.933 g lactic acid /g sugars. Besides, it was not detected the presence of by-products, what allows considering that the microorganism uses a homolactic fermentation to produce its own energy using pentose-phosphate pathway. Through facultative heterofermentative metabolism the bacteria consume pentose, as is the case of L. plantarum, but the energy efficiency for the cell is lower than during the hexose consumption. This implies both in a slower cell growth, as in a reduction in lactic acid productivity compared with the use of hexose. Also, L. plantarum had shown to have a capacity for lactic acid production from hemicellulosic hydrolysate without detoxification, which is very attractive in terms of robustness for an industrial process. Xylose from hydrolyzed bagasse and without detoxification is consumed, although the hydrolyzed bagasse inhibitors (especially aromatic inhibitors) affect productivity and yield of lactic acid. The use of sugars and the lack of need for detoxification of the C5 liquor from sugarcane bagasse hydrolyzed is a crucial factor for the economic viability of second generation processes. Taking this information into account, the production of second generation lactic acid using sugars from hemicellulose appears to be a good alternative to the complete utilization of sugarcane plant, directing molasses and cellulosic carbohydrates to produce 2G-ethanol, and hemicellulosic carbohydrates to produce 2G-lactic acid.

Keywords: fermentation, lactic acid, hemicellulosic sugars, sugarcane

Procedia PDF Downloads 360

Authors: A. Zapata, Orlando Arroyo, R. Bonett

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Over the last two decades, the growing demand for housing in Latin American countries has led to the development of construction projects based on low and medium-rise buildings with thin reinforced concrete walls. This system, known as Thin Walls Reinforced Concrete Buildings (TWRCB), uses walls with thicknesses from 100 to 150 millimetres, with flexural reinforcement formed by welded wire mesh (WWM) with diameters between 5 and 7 millimetres, arranged in one or two layers. These walls often have irregular structural configurations, including combinations of rectangular shapes. Experimental and numerical research conducted in regions where this structural system is commonplace indicates inherent weaknesses, such as limited ductility due to the WWM reinforcement and thin element dimensions. Because of its complexity, numerical analyses have relied on two-dimensional models that don't explicitly account for the floor system, even though it plays a crucial role in distributing seismic forces among the resilient elements. Nonetheless, the numerical analyses assume a rigid diaphragm hypothesis. For this purpose, two study cases of buildings were selected, low-rise and mid-rise characteristics of TWRCB in Colombia. The buildings were analyzed in Opensees using the MVLEM-3D for walls and shell elements to simulate the slabs to involve the effect of coupling diaphragm in the nonlinear behaviour. Three cases are considered: a) models without a slab, b) models with rigid slabs, and c) models with flexible slabs. An incremental static (pushover) and nonlinear dynamic analyses were carried out using a set of 44 far-field ground motions of the FEMA P-695, scaled to 1.0 and 1.5 factors to consider the probability of collapse for the design base earthquake (DBE) and the maximum considered earthquake (MCE) for the model, according to the location sites and hazard zone of the archetypes in the Colombian NSR-10. Shear base capacity, maximum displacement at the roof, walls shear base individual demands and probabilities of collapse were calculated, to evaluate the effect of absence, rigid and flexible slabs in the nonlinear behaviour of the archetype buildings. The pushover results show that the building exhibits an overstrength between 1.1 to 2 when the slab is considered explicitly and depends on the structural walls plan configuration; additionally, the nonlinear behaviour considering no slab is more conservative than if the slab is represented. Include the flexible slab in the analysis remarks the importance to consider the slab contribution in the shear forces distribution between structural elements according to design resistance and rigidity. The dynamic analysis revealed that including the slab reduces the collapse probability of this system due to have lower displacements and deformations, enhancing the safety of residents and the seismic performance. The strategy of including the slab in modelling is important to capture the real effect on the distribution shear forces in walls due to coupling to estimate the correct nonlinear behaviour in this system and the adequate distribution to proportionate the correct resistance and rigidity of the elements in the design to reduce the possibility of damage to the elements during an earthquake.

Keywords: thin wall reinforced concrete buildings, coupling slab, rigid diaphragm, flexible diaphragm

Procedia PDF Downloads 61

Authors: Hernan Arturo Blas López, Gustavo Henndel Lopes, Antonio Carlos Silva Costa Teixeira, Carmen Elena Flores Barreda, Patricia Araujo Pantoja

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Phenols are toxic for life and the environment and may come from many sources. Uncured phenolic monomers present in phenolic resins used as binders in grinding wheels and emery paper can contaminate industrial wastewaters in abrasives manufacture plants. Furthermore, vestiges of resol and novolacs resins generated by wear and tear of abrasives are also possible sources of water contamination by phenolics in these facilities. Fortunately, advanced oxidation by dark Fenton and photo-Fenton techniques are capable of oxidizing phenols and their degradation products up to their mineralization into H₂O and CO₂. The maximal allowable concentrations for phenols in Peruvian waterbodies is very low, such that insufficiently treated effluents from the abrasives industry are a potential environmental noncompliance. The current case study highlights findings obtained during the lab-scale application of Fenton’s and photo-assisted Fenton’s chemistries to real industrial wastewater samples from an abrasives manufacture plant in Peru. The goal was to reduce the phenolic content and sample toxicity. For this purpose, two independent variables-reaction time and effect of ultraviolet radiation–were studied as for their impacts on the concentration of total phenols, total organic carbon (TOC), biological oxygen demand (BOD) and chemical oxygen demand (COD). In this study, diluted samples (1 L) of the industrial effluent were treated with Fenton’s reagent (H₂O₂ and Fe²⁺ from FeSO₄.H₂O) during 10 min in a photochemical batch reactor (Alphatec RFS-500, Brazil) at pH 2.92. In the case of photo-Fenton tests with ultraviolet lamps of 9 W, UV-A, UV-B and UV-C lamps were evaluated. All process conditions achieved 100% of phenols degraded within 5 minutes. TOC, BOD and COD decreased by 49%, 52% and 86% respectively (all processes together). However, Fenton treatment was not capable of reducing BOD, COD and TOC below a certain value even after 10 minutes, contrarily to photo-Fenton. It was also possible to conclude that the processes here studied degrade other compounds in addition to phenols, what is an advantage. In all cases, elevated effluent dilution factors and high amounts of oxidant agent impact negatively the overall economy of the processes here investigated.

Keywords: fenton oxidation, wastewater treatment, phenols, abrasives industry

Procedia PDF Downloads 302

Authors: Aurea C. L. Lacerda, Paulo R. H. Moreno, Bruna M. P. Vianna, Cristina H. R. Serra, Airton Martin, André R. Baby, Vladi O. Consiglieri, Telma M. Kaneko

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The modified Franz cell is the most widely used model for in vitro permeation studies, however it still presents some disadvantages. Thus, some alternative methods have been developed such as Skin PAMPA, which is a bio- artificial membrane that has been applied for skin penetration estimation of xenobiotics based on HT permeability model consisting. Skin PAMPA greatest advantage is to carry out more tests, in a fast and inexpensive way. The membrane system mimics the stratum corneum characteristics, which is the primary skin barrier. The barrier properties are given by corneocytes embedded in a multilamellar lipid matrix. This layer is the main penetration route through the paracellular permeation pathway and it consists of a mixture of cholesterol, ceramides, and fatty acids as the dominant components. However, there is no consensus on the membrane composition. The objective of this work was to compare the performance among different bio-artificial membranes for studying the permeation in skin PAMPA system. Material and methods: In order to mimetize the lipid composition`s present in the human stratum corneum six membranes were developed. The membrane composition was equimolar mixture of cholesterol, ceramides 1-O-C18:1, C22, and C20, plus fatty acids C20 and C24. The membrane integrity assay was based on the transport of Brilliant Cresyl Blue, which has a low permeability; and Lucifer Yellow with very poor permeability and should effectively be completely rejected. The membrane characterization was performed using Confocal Laser Raman Spectroscopy, using stabilized laser at 785 nm with 10 second integration time and 2 accumulations. The membrane behaviour results on the PAMPA system were statistically evaluated and all of the compositions have shown integrity and permeability. The confocal Raman spectra were obtained in the region of 800-1200 cm-1 that is associated with the C-C stretches of the carbon scaffold from the stratum corneum lipids showed similar pattern for all the membranes. The ceramides, long chain fatty acids and cholesterol in equimolar ratio permitted to obtain lipid mixtures with self-organization capability, similar to that occurring into the stratum corneum. Conclusion: The artificial biological membranes studied for Skin PAMPA showed to be similar and with comparable properties to the stratum corneum.

Keywords: bio-artificial membranes, comparison, confocal Raman, skin PAMPA

Procedia PDF Downloads 497

Authors: Felipe Riveros, Ricardo Alvarez, Claudia Rahmann, Rodrigo Moreno

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Around the world, many countries have committed to a decarbonization of their electricity system. Under this global drive, converter-interfaced generators (CIG) such as wind and photovoltaic generation appear as cornerstones to achieve these energy targets. Despite its benefits, an increasing use of CIG brings several technical challenges in power systems, especially from a stability viewpoint. Among the key differences are limited short circuit current capacity, inertia-less characteristic of CIG, and response times within the electromagnetic timescale. Along with the integration of CIG into the power system, one enabling technology for the energy transition towards low-carbon power systems is battery energy storage systems (BESS). Because of the flexibility that BESS provides in power system operation, its integration allows for mitigating the variability and uncertainty of renewable energies, thus optimizing the use of existing assets and reducing operational costs. Another characteristic of BESS is that they can also support power system stability by injecting reactive power during the fault, providing short circuit currents, and delivering fast frequency response. However, most methodologies for sizing and allocating BESS in power systems are based on economic aspects and do not exploit the benefits that BESSs can offer to system stability. In this context, this paper presents a methodology for determining the optimal allocation of battery energy storage systems (BESS) in weak power systems with high levels of CIG. Unlike traditional economic approaches, this methodology incorporates stability constraints to allocate BESS, aiming to mitigate instability issues arising from weak grid conditions with low short-circuit levels. The proposed methodology offers valuable insights for power system engineers and planners seeking to maintain grid stability while harnessing the benefits of renewable energy integration. The methodology is validated in the reduced Chilean electrical system. The results show that integrating BESS into a power system with high levels of CIG with stability criteria contributes to decarbonizing and strengthening the network in a cost-effective way while sustaining system stability. This paper potentially lays the foundation for understanding the benefits of integrating BESS in electrical power systems and coordinating their placements in future converter-dominated power systems.

Keywords: battery energy storage, power system stability, system strength, weak power system

Procedia PDF Downloads 52

Authors: Tugba Altin

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In an era where the impacts of climate change resonate more pronouncedly than ever, communities globally grapple with events bearing both tangible and intangible ramifications. Situating this within the evolving landscapes of Psychological and Behavioral Sciences, this research probes the profound psychological and behavioral responses evoked by such events. The Lytton Creek Fire of 2021 epitomizes these challenges. While tangible destruction is immediate and evident, the intangible repercussions—emotional distress, disintegration of cultural landscapes, and disruptions in place attachment (PA)—require meticulous exploration. PA, emblematic of the emotional and cognitive affiliations individuals nurture with their environments, emerges as a cornerstone for comprehending how environmental cataclysms influence cultural identity and bonds to land. This study, harmonizing the core tenets of an interpretive phenomenological approach with a hermeneutic framework, underscores the pivotal nature of this attachment. It delves deep into the realm of individuals' experiences post the Lytton Creek Fire, unraveling the intricate dynamics of PA amidst such calamity. The study's methodology deviates from conventional paradigms. Instead of traditional interview techniques, it employs walking audio sessions and photo elicitation methods, granting participants the agency to immerse, re-experience, and vocalize their sentiments in real-time. Such techniques shed light on spatial narratives post-trauma and capture the otherwise elusive emotional nuances, offering a visually rich representation of place-based experiences. Central to this research is the voice of the affected populace, whose lived experiences and testimonies form the nucleus of the inquiry. As they renegotiate their bonds with transformed environments, their narratives reveal the indispensable role of cultural landscapes in forging place-based identities. Such revelations accentuate the necessity of integrating both tangible and intangible trauma facets into community recovery strategies, ensuring they resonate more profoundly with affected individuals. Bridging the domains of environmental psychology and behavioral sciences, this research accentuates the intertwined nature of tangible restoration with the imperative of emotional and cultural recuperation post-environmental disasters. It advocates for adaptation initiatives that are rooted in the lived realities of the affected, emphasizing a holistic approach that recognizes the profundity of human connections to landscapes. This research advocates the interdisciplinary exchange of ideas and strategies in addressing post-disaster community recovery strategies. It not only enriches the climate change discourse by emphasizing the human facets of disasters but also reiterates the significance of an interdisciplinary approach, encompassing psychological and behavioral nuances, for fostering a comprehensive understanding of climate-induced traumas. Such a perspective is indispensable for shaping more informed, empathetic, and effective adaptation strategies.

Keywords: place attachment, community recovery, disaster response, restorative landscapes, sensory response, visual methodologies

Procedia PDF Downloads 47

Authors: Ozcan Yavas, Berrak Erol Nalbur, Sermin Gunarslan

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A materiality matrix is a tool that organizations use to prioritize their activities and adapt to the increasing sustainability requirements in recent years. For the materiality index to move from business models to the sustainability business model stage, it must be done with all partners in the raw material, supply, production, product, and end-of-life product stages. Within the scope of this study, the Materiality Matrix was used to transform the business model into a sustainability business model and to create a sustainability roadmap in a factory producing electric buses. This matrix determines the necessary roadmap for all stakeholders to participate in the process, especially in sectors that produce sustainable products, such as the electric vehicle sector, and to act together with the cradle-to-cradle approach of sustainability roadmaps. Global Reporting Initiative analysis was used in the study conducted with 1150 stakeholders within the scope of the study, and 43 questions were asked to the stakeholders under the main headings of 'Legal Compliance Level,' 'Environmental Strategies,' 'Risk Management Activities,' 'Impact of Sustainability Activities on Products and Services,' 'Corporate Culture,' 'Responsible and Profitable Business Model Practices' and 'Achievements in Leading the Sector' and Economic, Governance, Environment, Social and Other. The results of the study aimed to include five 1st priority issues and four 2nd priority issues in the sustainability strategies of the organization in the short and medium term. When the studies carried out in the short term are evaluated in terms of Sustainability and Environmental Risk Management, it is seen that the studies are still limited to the level of legal legislation (60%) and individual studies in line with the strategies (20%). At the same time, the stakeholders expect the company to integrate sustainability activities into its business model within five years (35%) and to carry out projects to become the first company that comes to mind with its success leading the sector (20%). Another result obtained within the study's scope is identifying barriers to implementation. It is seen that the most critical obstacles identified by stakeholders with climate change and environmental impacts are financial deficiency and lack of infrastructure in the dissemination of sustainable products. These studies are critical for transitioning to sustainable business models for the electric vehicle sector to achieve the EU Green Deal and CBAM targets.

Keywords: sustainability business model, materiality matrix, electricity bus, carbon neutrality, sustainability management

Procedia PDF Downloads 37

Authors: Ehsan Mohseni

Abstract:

The aim of this thesis is to provide numerical analyses of reinforced concrete beams-column joints with/without CFRP (Carbon Fiber Reinforced Polymer) in order to achieve a better understanding of the behaviour of strengthened beamcolumn joints. A comprehensive literature survey prior to this study revealed that published studies are limited to a handful only; the results are inconclusive and some are even contradictory. Therefore in order to improve on this situation, following that review, a numerical study was designed and performed as presented in this thesis. For the numerical study, dimensions, end supports, and characteristics of the beam and column models were the same as those chosen in an experimental investigation performed previously where ten beamcolumn joint were tested tofailure. Finite element analysis is a useful tool in cases where analytical methods are not capable of solving the problem due to the complexities associated with the problem. The cyclic behaviour of FRP strengthened reinforced concrete beam-columns joints is such a case. Interaction of steel (longitudinal and stirrups), concrete and FRP, yielding of steel bars and stirrups, cracking of concrete, the redistribution of stresses as some elements unload due to crushing or yielding and the confinement of concrete due to the presence of FRP are some of the issues that introduce the complexities into the problem.Numerical solutions, however, can provide further in formation about the behaviour in lieu of the costly experiments or complex closed form solutions. This thesis presents the results of a numerical study on beam-column joints subjected to cyclic loads that are strengthened with CFRP wraps or strrips in a variety of configurations. The analyses are performed by Abaqus finite element program and are calibrated with the experiments. A range of issues in beam-column joints including the cracking load, the ultimate load, lateral load-displacement curves of joints, are investigated.The numerical results for different configurations of strengthening are compared. Finally, the computed numerical results are compared with those obtained from experiments. the cracking load, the ultimate load, lateral load-displacement curves obtained from numerical analysis for all joints were in very good agreement with the corresponding experimental ones.The results obtained from the numerical analysis in most cases implies that this method is conservative and therefore can be used in design applications with confidence.

Keywords: numerical analysis, strengthening, CFRP, reinforced concrete joints

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Authors: Olayeye Olubunmi Shola

Abstract:

Amidst increasing global environmental concerns, sustainable urban planning has emerged as a vital strategy in counteracting the negative impacts of urbanization on the environment. However, the emphasis on sustainability often disregards crucial elements of fairness and equal participation within urban settings. This abstract presents a comprehensive overview of the challenges, objectives, significance, and methodologies for addressing social inequalities in the development of eco-cities, with a specific focus on Abuja, Nigeria. Sustainable urban planning, particularly in the context of developing eco-cities, aims to construct cities prioritizing environmental sustainability and resilience. Nonetheless, a significant gap exists in addressing the enduring social disparities within these initiatives. Equitable distribution of resources, access to services, and social inclusivity are essential components that must be integrated into urban planning frameworks for cities that are genuinely sustainable and habitable. Abuja, the capital city of Nigeria, provides a distinctive case for examining the intersection of sustainability and social justice in urban planning. Despite the urban development, Abuja grapples with challenges such as socio-economic disparities, unequal access to essential services, and inadequate housing among its residents. Recognizing and redressing these disparities within the framework of eco-city development is critical for nurturing an inclusive and sustainable urban environment. The primary aim of this study is to scrutinize and pinpoint the social discrepancies within Abuja's initiatives for eco-city development. Specific objectives include: Evaluating the current socio-economic landscape of Abuja to identify disparities in resource, service, and infrastructure access. Comprehending the existing sustainable urban planning initiatives and their influence on social fairness. Suggesting strategies and recommendations to improve fairness and inclusivity within Abuja's plans for eco-city development. This research holds substantial importance for urban planning practices and policy formulation, not only in Abuja but also on a global scale. By highlighting the crucial role of social equity and inclusivity in the development of eco-cities, this study aims to provide insights that can steer more comprehensive, people-centered urban planning practices. Addressing social disparities within sustainability initiatives is crucial for achieving genuinely sustainable and fair urban spaces. The study will employ qualitative and quantitative methodologies. Data collection will involve surveys, interviews, and observations to capture the diverse experiences and perspectives of various social groups within Abuja. Furthermore, quantitative data on infrastructure, service access, and socio-economic indicators will be collated from government reports, academic sources, and non-governmental organizations. Analytical tools such as Geographic Information Systems (GIS) will be utilized to map and visualize spatial disparities in resource allocation and service access. Comparative analyses and case studies of successful interventions in other cities will be conducted to derive applicable strategies for Abuja's context. In conclusion, this study aims to contribute to the discourse on sustainable urban planning by advocating for equity and inclusivity in the development of eco-cities. By centering on Abuja as a case study, it aims to provide practical insights and solutions for the creation of more fair and sustainable urban environments.

Keywords: fairness, sustainability, geographical information system, equity

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Authors: Pedro Llanos, Diego García

Abstract:

Spaceflight is considered the last frontier in terms of science, technology, and engineering. But it is also the next frontier in terms of human physiology and performance. After more than 200,000 years humans have evolved under earth’s gravity and atmospheric conditions, spaceflight poses environmental stresses for which human physiology is not adapted. Hypoxia, accelerations, and radiation are among such stressors, our research involves suborbital flights aiming to develop effective countermeasures in order to assure sustainable human space presence. The physiologic baseline of spaceflight participants is subject to great variability driven by age, gender, fitness, and metabolic reserve. The objective of the present study is to characterize different physiologic variables in a population of STEM practitioners during an aerobatic flight. Cardiovascular and pulmonary responses were determined in Science Astronaut Candidates (SACs) during unusual attitude aerobatic flight indoctrination. Physiologic data recordings from 20 subjects participating in high-G flight training were analyzed. These recordings were registered by wearable sensor-vest that monitored electrocardiographic tracings (ECGs), signs of dysrhythmias or other electric disturbances during all the flight. The same cardiovascular parameters were also collected approximately 10 min pre-flight, during each high-G/unusual attitude maneuver and 10 min after the flights. The ratio (pre-flight/in-flight/post-flight) of the cardiovascular responses was calculated for comparison of inter-individual differences. The resulting tracings depicting the cardiovascular responses of the subjects were compared against the G-loads (Gs) during the aerobatic flights to analyze cardiovascular variability aspects and fluid/pressure shifts due to the high Gs. In-flight ECG revealed cardiac variability patterns associated with rapid Gs onset in terms of reduced heart rate (HR) and some scattered dysrhythmic patterns (15% premature ventricular contractions-type) that were considered as triggered physiological responses to high-G/unusual attitude training and some were considered as instrument artifact. Variation events were observed in subjects during the +Gz and –Gz maneuvers and these may be due to preload and afterload, sudden shift. Our data reveal that aerobatic flight influenced the breathing rate of the subject, due in part by the various levels of energy expenditure due to the increased use of muscle work during these aerobatic maneuvers. Noteworthy was the high heterogeneity in the different physiological responses among a relatively small group of SACs exposed to similar aerobatic flights with similar Gs exposures. The cardiovascular responses clearly demonstrated that SACs were subjected to significant flight stress. Routine ECG monitoring during high-G/unusual attitude flight training is recommended to capture pathology underlying dangerous dysrhythmias in suborbital flight safety. More research is currently being conducted to further facilitate the development of robust medical screening, medical risk assessment approaches, and suborbital flight training in the context of the evolving commercial human suborbital spaceflight industry. A more mature and integrative medical assessment method is required to understand the physiology state and response variability among highly diverse populations of prospective suborbital flight participants.

Keywords: g force, aerobatic maneuvers, suborbital flight, hypoxia, commercial astronauts

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