Search results for: temperature measurement

Authors: Wen-Juinn Chen, Yi-Phei Chou, Jou-Han Wang

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Tainan coast is suffering from beach erosion, wave overtopping, and lowland flooding; though most of the shoreline has been protected by seawalls, they still threatened by sea level rise. For coastal resources developing, coastal land utilization, and to draft an appropriate mitigate strategy. Firstly; we must assess the impact of beach erosion under a different scenario of climate change. Here, we have used the meteorological data since 1898 to 2012 to prove that the Tainan area did suffer the impact of climate change. The result shows the temperature has been raised to about 1.7 degrees since 1989. Also, we analyzed the tidal data near the Tainan coast (Anpin site and Junjunn site), it shows sea level rising with a rate about 4.1~4.8 mm/year, this phenomenon will have serious impacts on Tainan coastal area, especially it will worsen coastal erosion. So we have used Bruun rule to calculate the shoreline retreated rate at every two decade period since 2012. Wave data and bottom sand diameter D50 were used to calculate the closure depth that will be used in Bruun formula and the active length of the profile is computed by the beach slope and Dean's equilibrium concept. After analysis, we found that in 2020, the shoreline will be retreated about 3.0 to 12 meters. The maximum retreat is happening at Chigu coast. In 2060, average shoreline retreated distance is 22m, but at Chigu and Tsenwen, shoreline may be backward retreat about 70m and will be reached about 130m at 2100, this will cause a lot of coastal land loss to the sea, protect and mitigate project must be quickly performed.

Keywords: sea level rise, shoreline, coastal erosion, climate change

Procedia PDF Downloads 383

Authors: S. M. Moustafa, A. Ezzat, Y. S. Taha, G. H. Hassib, S. Hamada

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After the occurrence of 14, Nov, 1981 earthquake (M = 5.3), on Kalabska fault, south of Egypt, seismic stations distributed in and around the Kalabsha area, in order to monitoring, recording and studying the seismic activity in the area. In addition of that, from 1989 a number of piezometer wells drilled in the same area, distribed on at the both side of the active faults area and in different water bearing formations, in order to measuring the groundwater parameters (level, temperature, ph, and conductivity) to monitoring the relationship between those parameters and the seismic activity at Kalabsha area. The behavior of groundwater due to seismic activity over the world studied by several scientists i.e. H. Wakita (1979) on Izu-Oshima earthquake (M= 7.0) at Japan, M. E. Contadakis & G.asteriadis (1972), and Evans (1966), they found an anomalies on groundwater measurements prior, co, and post the occurrence of bigger earthquakes, referring to the probability of precursory evidence of impending earthquakes. In Kalabsha area south of Egypt, this study has been done using recorded seismic data, and the measurements of underground water parameters. same phenomena of anomalies founded on groundwater measurements pre, co. and post the occurrence of earthquakes with magnitude bigger than 3, and no systematic regularity exists for epicenter distance, duration of anomalies or time lag between anomalies appear and occurrence of events. Also the results found present strong relation between the groundwater in the upper unconfined aquifer Nubian Sandstone formation, and Kalabsha seismic activity, otherwise no relation between the seismic activities in the area with the deep groundwater in the lower confined aquifer Sandstone.

Keywords: seismicity, groundwater, Aswan, Egypt

Procedia PDF Downloads 356

Authors: Divyanka Sontakke, Arpit Thakre, D. K Shinde, Sujata Parmeshwaran

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Electrospinning is the most widely utilized method to create nanofibers because of the direct setup, the capacity to mass-deliver consistent nanofibers from different polymers, and the ability to produce ultrathin fibers with controllable diameters. Smooth and much arranged ultrafine Polyacrylonitrile (PAN) nanofibers with diameters going from submicron to nanometer were delivered utilizing Electrospinning technique. PAN powder was used as a precursor to prepare the solution utilized as a part of this process. At the point when the electrostatic repulsion contradicted surface tension, a charged stream of polymer solution was shot out from the head of the spinneret and along these lines ultrathin nonwoven fibers were created. The effect of electrospinning parameter such as applied voltage, feed rate, concentration of polymer solution and tip to collector distance on the morphology of electrospun PAN nanofibers were investigated. The nanofibers were heat treated for carbonization to examine the changes in properties and composition to make for electrical application. Scanning Electron Microscopy (SEM) was performed before and after carbonization to study electrical conductivity and morphological characterization. The SEM images have shown the uniform fiber diameter and no beads formation. The average diameter of the PAN fiber observed 365nm and 280nm for flat plat and rotating drum collector respectively. The four probe strategy was utilized to inspect the electrical conductivity of the nanofibers and the electrical conductivity is significantly improved with increase in oxidation temperature exposed.

Keywords: electrospinning, polyacrylonitrile carbon nanofibres, heat treatment, electrical conductivity

Procedia PDF Downloads 125

Authors: Yaara Oppenheimer-Shaanan, Nimrod Nachmias, Marina Campos Rocha, Neta Schlezinger, Noam Dotan, Asaf Levy

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Fusarium oxysporum, a fungus that attacks a broad range of plants and can cause infections in humans, operates across different kingdoms. This pathogen encounters varied conditions, such as temperature, pH, and nutrient availability, in plant and human hosts. The Fusarium oxysporum species complex, pervasive in soils globally, can affect numerous plants, including key crops like tomatoes and bananas. Controlling Fusarium infections can involve biocontrol agents that hinder the growth of harmful strains. Our research developed a computational method to identify toxin domains within a vast number of microbial genomes, leading to the discovery of nine distinct toxins capable of killing bacteria and fungi, including Fusarium. These toxins appear to function as enzymes, causing significant damage to cellular structures, membranes and DNA. We explored biological control using bacteria that produce polymorphic toxins, finding that certain bacteria, non-pathogenic to plants, offer a safe biological alternative for Fusarium management, as they did not harm macrophage cells or C. elegans. Additionally, we elucidated the 3D structures of two toxins with their protective immunity proteins, revealing their function as unique DNases. These potent toxins are likely instrumental in microbial competition within plant ecosystems and could serve as biocontrol agents to mitigate Fusarium wilt and related diseases.

Keywords: microbial toxins, antifungal, Fusarium oxysporum, bacterial-fungal intreactions

Procedia PDF Downloads 24

Authors: Jose A. Diaz-Olivares, Nafise Mahdavian, Farhad Abtahi, Kaj Lindecrantz, Abdelakram Hafid, Fernando Seoane

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Despite new recommendations and guidelines for the evaluation of occupational risk assessments and their prevention, work-related musculoskeletal disorders are still one of the biggest causes of work activity disruption, productivity loss, sick leave and chronic work disability. It affects millions of workers throughout Europe, with a large-scale economic and social burden. These specific efforts have failed to produce significant results yet, probably due to the limited availability and high costs of occupational risk assessment at work, especially when the methods are complex, consume excessive resources or depend on self-evaluations and observations of poor accuracy. To overcome these limitations, a pervasive system of risk assessment tools in real time has been developed, which has the characteristics of a systematic approach, with good precision, usability and resource efficiency, essential to facilitate the prevention of musculoskeletal disorders in the long term. The system allows the combination of different wearable sensors, placed on different limbs, to be used for data collection and evaluation by a software solution, according to the needs and requirements in each individual working environment. This is done in a non-disruptive manner for both the occupational health expert and the workers. The creation of this solution allows us to attend different research activities that require, as an essential starting point, the recording of data with ergonomic value of very diverse origin, especially in real work environments. The software platform is here presented with a complimentary smart clothing system for data acquisition, comprised of a T-shirt containing inertial measurement units (IMU), a vest sensorized with textile electronics, a wireless electrocardiogram (ECG) and thoracic electrical bio-impedance (TEB) recorder and a glove sensorized with variable resistors, dependent on the angular position of the wrist. The collected data is processed in real-time through a mobile application software solution, implemented in commercially available Android-based smartphones and tablet platforms. Based on the collection of this information and its analysis, real-time risk assessment and feedback about postural improvement is possible, adapted to different contexts. The result is a tool which provides added value to ergonomists and occupational health agents, as in situ analysis of postural behavior can assist in a quantitative manner in the evaluation of work techniques and the occupational environment.

Keywords: ergonomics, mobile technologies, risk assessment, smart textiles

Procedia PDF Downloads 98

Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

Procedia PDF Downloads 150

Authors: C. S. Wong, K. H. Badri, N. Ataollahi, K. P. Law, M. S. Su’ait, N. I. Hassan

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Novel bio-based polymer electrolyte was synthesized with LiClO4 as the main source of charge carrier. Initially, polyurethane-LiClO4 polymer electrolytes were synthesized via polymerization method with different NCO/OH ratios and labelled as PU1, PU2, PU3, and PU4. Subsequently, the chemical, thermal properties and ionic conductivity of the films produced were determined. Fourier transform infrared (FTIR) analysis indicates the co-ordination between Li+ ion and polyurethane in PU1 due to the greatest amount of hard segment of polyurethane in PU1 as proven by soxhlet analysis. The structures of polyurethanes were confirmed by 13 nuclear magnetic resonance spectroscopy (13C NMR) and FTIR spectroscopy. Differential scanning calorimetry (DSC) analysis indicates PU 1 has the highest glass transition temperature (Tg) corresponds to the most abundant urethane group which is the hard segment in PU1. Scanning electron microscopy (SEM) of the PU-LiClO4 shows the good miscibility between lithium salt and the polymer. The study found that PU1 possessed the greatest ionic conductivity (1.19 × 10-7 S.cm-1 at 298 K and 5.01 × 10-5 S.cm-1 at 373 K) and the lowest activation energy, Ea (0.32 eV) due to the greatest amount of hard segment formed in PU 1 induces the coordination between lithium ion and oxygen atom of carbonyl group in polyurethane. All the polyurethanes exhibited linear Arrhenius variations indicating ion transport via simple lithium ion hopping in polyurethane. This research proves the NCO content in polyurethane plays an important role in affecting the ionic conductivity of this polymer electrolyte.

Keywords: ionic conductivity, palm kernel oil-based monoester-OH, polyurethane, solid polymer electrolyte

Procedia PDF Downloads 390

Authors: Elin Julianti, Marlia Singgih, Masayoshi Arai, Jianyu Lin, Masteria Yunovilsa Putra, Muhammad Azhari, Agnia S. Muharam

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The search for a source of new medicinal compounds with anticancer activity from natural products has become important to resolve the ineffectiveness problem of pancreatic cancer therapy. Fungal marine microorganisms are prolific sources of bioactive natural products. In this present study, the ethyl acetate extract of cultured broth of Trichoderma longibrachiatum marine sponge-derived fungi exhibited selective cytotoxicity against human pancreatic carcinoma PANC-1 cells cultured under glucose-deficient conditions (IC50 = 98,4 µg/mL). The T. longibrachiatum was fermented by the static method at room temperature for 60 days. The culture broth was extracted using ethyl acetate by liquid-liquid extraction method. The liquid-liquid extraction was conducted toward the ethyl extract by using 90% MeOH-H₂O and n-|Hexane as a solvent. The extract of 90% MeOH-H₂O was fractionated by liquid extraction using by C₁₈ reversed-phase vacuum flash chromatography using mixtures of MeOH-H₂O, from 50:50 to 100:0, and 1% TFA MeOH as the eluents to yield six fractions. The fraction 2 (MeOH-H2O, 70:30) and fraction 3 (MeOH-H2O, 80:20) showed moderate cytotoxicity with IC50 value of 119.3 and 274.7 µg/mL, respectively. Fraction 4 (MeOH-H₂O, 90:10) showed the highest cytotoxicity activity with IC₅₀value of < 10 µg/mL. The chemical compounds of the fractions that are responsible for cytotoxic activity are potent for further investigation.

Keywords: cytotoxic activity, trichoderma longibrachiatum, marine-derived fungi, PANC-1 cell line

Procedia PDF Downloads 267

Authors: Mareen Brosterhaus, Antje Hammer, Steffen Kalina, Stefan Grau, Anjali A. Roeth, Hany Ashmawy, Thomas Gross, Marcel Binnebosel, Wolfram T. Knoefel, Tanja Manser

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Background: The identification of critical incidents in hospitals is an essential component of improving patient safety. To date, various methods have been used to measure and characterize such critical incidents. These methods are often viewed by physicians and nurses as external quality assurance, and this creates obstacles to the reporting events and the implementation of recommendations in practice. One way to overcome this problem is to use tools that directly involve staff in measuring indicators of quality and safety of care in the department. One such instrument is the global trigger tool (GTT), which helps physicians and nurses identify adverse events by systematically reviewing randomly selected patient records. Based on so-called ‘triggers’ (warning signals), indications of adverse events can be given. While the tool is already used internationally, its implementation in German hospitals has been very limited. Objectives: This study aimed to assess the feasibility and potential of the global trigger tool for identifying adverse events in German hospitals. Methods: A total of 120 patient records were randomly selected from two surgical, and one neurosurgery, departments of three university hospitals in Germany over a period of two months per department between January and July, 2017. The records were reviewed using an adaptation of the German version of the Institute for Healthcare Improvement Global Trigger Tool to identify triggers and adverse event rates per 1000 patient days and per 100 admissions. The severity of adverse events was classified using the National Coordinating Council for Medication Error Reporting and Prevention. Results: A total of 53 adverse events were detected in the three departments. This corresponded to adverse event rates of 25.5-72.1 per 1000 patient-days and from 25.0 to 60.0 per 100 admissions across the three departments. 98.1% of identified adverse events were associated with non-permanent harm without (Category E–71.7%) or with (Category F–26.4%) the need for prolonged hospitalization. One adverse event (1.9%) was associated with potentially permanent harm to the patient. We also identified practical challenges in the implementation of the tool, such as the need for adaptation of the global trigger tool to the respective department. Conclusions: The global trigger tool is feasible and an effective instrument for quality measurement when adapted to the departmental specifics. Based on our experience, we recommend a continuous use of the tool thereby directly involving clinicians in quality improvement.

Keywords: adverse events, global trigger tool, patient safety, record review

Procedia PDF Downloads 222

Authors: Arnaldo G. de Oliveira, Jr, Matthieu Tubino

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The transesterification process of triglycerides with alcohols that occurs during the biodiesel synthesis causes continuous changes in several physical properties of the reaction mixture, such as refractive index, viscosity and density. Amongst them, density can be an useful parameter to monitor the reaction, in order to predict the composition of the reacting mixture and to verify the conversion of the oil into biodiesel. In this context, a system was constructed in order to continuously determine changes in the density of the reacting mixture containing soybean oil, methanol and sodium methoxide (30 % w/w solution in methanol), stirred at 620 rpm at room temperature (about 27 °C). A polyethylene pipe network connected to a peristaltic pump was used in order to collect the mixture and pump it through a coil fixed on the plate of an analytical balance. The collected mass values were used to trace a curve correlating the mass of the system to the reaction time. The density variation profile versus the time clearly shows three different steps: 1) the dispersion of methanol in oil causes a decrease in the system mass due to the lower alcohol density followed by stabilization; 2) the addition of the catalyst (sodium methoxide) causes a larger decrease in mass compared to the first step (dispersion of methanol in oil) because of the oil conversion into biodiesel; 3) the final stabilization, denoting the end of the reaction. This density variation profile provides information that was used to predict the composition of the mixture over the time and the reaction rate. The precise knowledge of the duration of the synthesis means saving time and resources on a scale production system. This kind of monitoring provides several interesting features such as continuous measurements without collecting aliquots.

Keywords: biodiesel, density measurements, online continuous monitoring, synthesis

Procedia PDF Downloads 554

Authors: N. Boontian

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Biological conversion of biomass to methane has received increasing attention in recent years. Grasses have been explored for their potential anaerobic digestion to methane. In this review, extensive literature data have been tabulated and classified. The influences of several parameters on the potential of these feedstocks to produce methane are presented. Lignocellulosic biomass represents a mostly unused source for biogas and ethanol production. Many factors, including lignin content, crystallinity of cellulose, and particle size, limit the digestibility of the hemicellulose and cellulose present in the lignocellulosic biomass. Pretreatments have used to improve the digestibility of the lignocellulosic biomass. Each pretreatment has its own effects on cellulose, hemicellulose and lignin, the three main components of lignocellulosic biomass. Solid-state anaerobic digestion (SS-AD) generally occurs at solid concentrations higher than 15%. In contrast, liquid anaerobic digestion (AD) handles feedstocks with solid concentrations between 0.5% and 15%. Animal manure, sewage sludge, and food waste are generally treated by liquid AD, while organic fractions of municipal solid waste (OFMSW) and lignocellulosic biomass such as crop residues and energy crops can be processed through SS-AD. An increase in operating temperature can improve both the biogas yield and the production efficiency, other practices such as using AD digestate or leachate as an inoculant or decreasing the solid content may increase biogas yield but have negative impact on production efficiency. Focus is placed on substrate pretreatment in anaerobic digestion (AD) as a means of increasing biogas yields using today’s diversified substrate sources.

Keywords: anaerobic digestion, lignocellulosic biomass, methane production, optimization, pretreatment

Procedia PDF Downloads 360

Authors: Daniel Ferreira, José M. Marques Oliveira, Filipe Oliveira

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Wear phenomena is critical in injection moulding processes, causing failure of the components, and making the parts more expensive with an additional wasting time. When very abrasive materials are being injected inside the steel mould’s cavities, such as polymers reinforced with abrasive fibres, the consequences of the wear are more evident. Maraging steel (1.2709) is commonly employed in moulding components to resist in very aggressive injection conditions. In this work, the wear performance of the SLM produced 1.2709 maraging steel reinforced by ultrafine titanium and tungsten carbide (TiC-WC), was investigated using a pin-on-disk testing apparatus. A polypropylene reinforced with 40 wt.% fibreglass (PP40) disk, was used as the counterpart material. The wear tests were performed at 40 N constant load and 0.4 ms-1 sliding speed at room temperature and humidity conditions. The experimental results demonstrated that the wear rate in the 18Ni300-TiC-WC composite is lower than the unreinforced 18Ni300 matrix. The morphology and chemical composition of the worn surfaces was observed by 3D optical profilometry and scanning electron microscopy (SEM), respectively. The resulting debris, caused by friction, were also analysed by SEM and energy dispersive X-ray spectroscopy (EDS). Their morphology showed distinct shapes and sizes, which indicated that the wear mechanisms, may be different in maraging steel produced by casting and SLM. The coefficient of friction (COF) was recorded during the tests, which helped to elucidate the wear mechanisms involved.

Keywords: selective laser melting, nanocomposites, injection moulding, polypropylene with fibreglass

Procedia PDF Downloads 129

Authors: Divya Vats, Sanjay Mahajani

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The clarification of sugarcane juice plays a pivotal role in the production of non-centrifugal sugar (NCS), profoundly influencing the quality of the final NCS product. In this study, we have investigated the kinetics and mathematical modeling of the batch clarification process. The turbidity of the clarified cane juice (NTU) emerges as the determinant of the end product’s color. Moreover, this parameter underscores the significance of considering other variables as performance indicators for accessing the efficacy of the clarification process. Temperature-controlled experiments were meticulously conducted in a laboratory-scale batch mode. The primary objective was to discern the essential and optimized parameters crucial for augmenting the clarity of cane juice. Additionally, we explored the impact of pH and flocculant loading on the kinetics. Particle Image Velocimetry (PIV) is employed to comprehend the particle-particle and fluid-particle interaction. This technique facilitated a comprehensive understanding, paving the way for the subsequent multiphase computational fluid dynamics (CFD) simulations using the Eulerian-Lagrangian approach in the Ansys fluent. Impressively, these simulations accurately replicated comparable velocity profiles. The final mechanism of this study helps to make a mathematical model and presents a valuable framework for transitioning from the traditional batch process to a continuous process. The ultimate aim is to attain heightened productivity and unwavering consistency in product quality.

Keywords: non-centrifugal sugar, particle image velocimetry, computational fluid dynamics, mathematical modeling, turbidity

Procedia PDF Downloads 44

Authors: Frappi Sofia, Nicolas Pilcher, Sander DenHaring, Royale Hardenstine, Luis Silva, Collin Williams, Mattie Rodrigue, Vincent Pieriborne, Mohammed Qurban, Carlos M. Duarte

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Nowadays, elasmobranch populations are disappearing at a dangerous rate, mainly due to overexploitation, extensive fisheries, as well as climate change. The decline of these species can trigger a cascade effect, which may eventually lead to detrimental impacts on local ecosystems. The Elasmobranch in the Red Sea is facing one of the highest risks of extinction, mainly due to unregulated fisheries activities. Thus, it is of paramount importance to assess their current distribution and unveil their environmental preferences in order to improve conservation measures. Important data have been collected throughout the whole red Sea during the Red Sea Decade Expedition (RSDE) to achieve this goal. Elasmobranch sightings were gathered through the use of submarines, remotely operated underwater vehicles (ROV), scuba diving operations, and helicopter surveys. Over a period of 5 months, we collected 891 sightings, 52 with submarines, 138 with the ROV, 67 with the scuba diving teams, and 634 from helicopters. In total, we observed 657 and 234 individuals from the superorder Batoidea and Selachimorpha, respectively. The most common shark encountered was Iago omanensis, a deep-water shark of the order Carcharhiniformes. To each sighting, data on temperature, salinity density, and dissolved oxygen were integrated to reveal favorable conditions for each species. Additionally, an extensive literature review on elasmobranch research in the Eastern Red Sea has been carried out in order to obtain more data on local populations and to be able to highlight patterns of their distribution.

Keywords: distribution, elasmobranchs, habitat, rays, red sea, sharks

Procedia PDF Downloads 56

Authors: Alireza Rasekh, Peter Sergeant, Jan Vierendeels

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This paper copes with the numerical simulation for convective heat transfer in the stator disk of an axial flux permanent magnet (AFPM) electrical machine. Overheating is one of the main issues in the design of AFMPs, which mainly occurs in the stator disk, so that it needs to be prevented. A rotor-stator configuration with 16 magnets at the periphery of the rotor is considered. Air is allowed to flow through openings in the rotor disk and channels being formed between the magnets and in the gap region between the magnets and the stator surface. The rotating channels between the magnets act as a driving force for the air flow. The significant non-dimensional parameters are the rotational Reynolds number, the gap size ratio, the magnet thickness ratio, and the magnet angle ratio. The goal is to find correlations for the Nusselt number on the stator disk according to these non-dimensional numbers. Therefore, CFD simulations have been performed with the multiple reference frame (MRF) technique to model the rotary motion of the rotor and the flow around and inside the machine. A minimization method is introduced by a pattern-search algorithm to find the appropriate values of the reference temperature. It is found that the correlations are fast, robust and is capable of predicting the stator heat transfer with a good accuracy. The results reveal that the magnet angle ratio diminishes the stator heat transfer, whereas the rotational Reynolds number and the magnet thickness ratio improve the convective heat transfer. On the other hand, there a certain gap size ratio at which the stator heat transfer reaches a maximum.

Keywords: AFPM, CFD, magnet parameters, stator heat transfer

Procedia PDF Downloads 226

Authors: E. Nakamachi, K. Matsumoto, K. Yamamoto, Y. Morita, H. Sakamoto

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In recently, electromagnetic and mechanical stimulations have been recognized as the effective extracellular environment stimulation technique to enhance the defected peripheral nerve tissue regeneration. In this study, we developed a new hybrid bioreactor by adopting 50 Hz uniform alternative current (AC) magnetic stimulation and 4% strain mechanical stimulation. The guide tube for nerve regeneration is mesh structured tube made of biodegradable polymer, such as polylatic acid (PLA). However, when neural damage is large, there is a possibility that peripheral nerve undergoes necrosis. So it is quite important to accelerate the nerve tissue regeneration by achieving enhancement of nerve axonal extension rate. Therefore, we try to design and fabricate the system that can simultaneously load the uniform AC magnetic field stimulation and the stretch stimulation to cells for enhancement of nerve axonal extension. Next, we evaluated systems performance and the effectiveness of each stimulation for rat adrenal pheochromocytoma cells (PC12). First, we designed and fabricated the uniform AC magnetic field system and the stretch stimulation system. For the AC magnetic stimulation system, we focused on the use of pole piece structure to carry out in-situ microscopic observation. We designed an optimum pole piece structure using the magnetic field finite element analyses and the response surface methodology. We fabricated the uniform AC magnetic field stimulation system as a bio-reactor by adopting analytically determined design specifications. We measured magnetic flux density that is generated by the uniform AC magnetic field stimulation system. We confirmed that measurement values show good agreement with analytical results, where the uniform magnetic field was observed. Second, we fabricated the cyclic stretch stimulation device under the conditions of particular strains, where the chamber was made of polyoxymethylene (POM). We measured strains in the PC12 cell culture region to confirm the uniform strain. We found slightly different values from the target strain. Finally, we concluded that these differences were allowable in this mechanical stimulation system. We evaluated the effectiveness of each stimulation to enhance the nerve axonal extension using PC12. We confirmed that the average axonal extension length of PC12 under the uniform AC magnetic stimulation was increased by 16 % at 96 h in our bio-reactor. We could not confirm that the axonal extension enhancement under the stretch stimulation condition, where we found the exfoliating of cells. Further, the hybrid stimulation enhanced the axonal extension. Because the magnetic stimulation inhibits the exfoliating of cells. Finally, we concluded that the enhancement of PC12 axonal extension is due to the magnetic stimulation rather than the mechanical stimulation. Finally, we confirmed that the effectiveness of the uniform AC magnetic field stimulation for the nerve axonal extension using PC12 cells.

Keywords: nerve cell PC12, axonal extension, nerve regeneration, electromagnetic-mechanical stimulation, bioreactor

Procedia PDF Downloads 240

Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Irving Barragán-Vite

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Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, México, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r²=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r² value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids.

Keywords: wind power generation, artificial neural networks, wind speed, coefficient of determination

Procedia PDF Downloads 87

Authors: Fatemeh Deldarabdolmaleki, Mohamad Fakri Zaky Bin Ja'afar

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Having a daylit space together with view results in a pleasant and productive environment for office employees. A daylit space is a space which utilizes daylight as a basic source of illumination to fulfill user’s visual demands and minimizes the electric energy consumption. Malaysian weather is hot and humid all over the year because of its location in the equatorial belt. however, because most of the commercial buildings in Malaysia are air-conditioned, huge glass windows are normally installed in order to keep the physical and visual relation between inside and outside. As a result of climatic situation and mentioned new trend, an ordinary office has huge heat gain, glare, and discomfort for occupants. Balancing occupant’s comfort and energy conservation in a tropical climate is a real challenge. This study concentrates on evaluating a venetian blind system using per pixel analyzing tools based on the suggested cut-out metrics by the literature. Workplace area in a private office room has been selected as a case study. Eight-day measurement experiment was conducted to investigate the effect of different venetian blind angles in an office area under daylight conditions in Serdang, Malaysia. The study goal was to explore daylight comfort of a commercially available venetian blind system, its’ daylight sufficiency and excess (8:00 AM to 5 PM) as well as Glare examination. Recently developed software, analyzing High Dynamic Range Images (HDRI captured by CCD camera), such as radiance based Evalglare and hdrscope help to investigate luminance-based metrics. The main key factors are illuminance and luminance levels, mean and maximum luminance, daylight glare probability (DGP) and luminance ratio of the selected mask regions. The findings show that in most cases, morning session needs artificial lighting in order to achieve daylight comfort. However, in some conditions (e.g. 10° and 40° slat angles) in the second half of day the workplane illuminance level exceeds the maximum of 2000 lx. Generally, a rising trend is discovered toward mean window luminance and the most unpleasant cases occur after 2 P.M. Considering the luminance criteria rating, the uncomfortable conditions occur in the afternoon session. Surprisingly in no blind condition, extreme case of window/task ratio is not common. Studying the daylight glare probability, there is not any DGP value higher than 0.35 in this experiment.

Keywords: daylighting, energy simulation, office environment, Venetian blind

Procedia PDF Downloads 232

Authors: Kitty Kioskli, Theofanis Fotis, Nineta Polemi

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The European Union (EU) directive Artificial Intelligence (AI) Act in Article 9 requires that risk management of AI systems includes both technical and human oversight, while according to NIST_AI_RFM (Appendix C) and ENISA AI Framework recommendations, claim that further research is needed to understand the current limitations of social threats and human-AI interaction. AI threats within social contexts significantly affect the security and trustworthiness of the AI systems; they are interrelated and trigger technical threats as well. For example, lack of explainability (e.g. the complexity of models can be challenging for stakeholders to grasp) leads to misunderstandings, biases, and erroneous decisions. Which in turn impact the privacy, security, accountability of the AI systems. Based on the NIST four fundamental criteria for explainability it can also classify the explainability threats into four (4) sub-categories: a) Lack of supporting evidence: AI systems must provide supporting evidence or reasons for all their outputs. b) Lack of Understandability: Explanations offered by systems should be comprehensible to individual users. c) Lack of Accuracy: The provided explanation should accurately represent the system's process of generating outputs. d) Out of scope: The system should only function within its designated conditions or when it possesses sufficient confidence in its outputs. Biases may also stem from historical data reflecting undesired behaviors. When present in the data, biases can permeate the models trained on them, thereby influencing the security and trustworthiness of the of AI systems. Social related AI threats are recognized by various initiatives (e.g., EU Ethics Guidelines for Trustworthy AI), standards (e.g. ISO/IEC TR 24368:2022 on AI ethical concerns, ISO/IEC AWI 42105 on guidance for human oversight of AI systems) and EU legislation (e.g. the General Data Protection Regulation 2016/679, the NIS 2 Directive 2022/2555, the Directive on the Resilience of Critical Entities 2022/2557, the EU AI Act, the Cyber Resilience Act). Measuring social threats, estimating the risks to AI systems associated to these threats and mitigating them is a research challenge. In this paper it will present the efforts of two European Commission Projects (FAITH and THEMIS) from the HorizonEurope programme that analyse the social threats by building cyber-social exercises in order to study human behaviour, traits, cognitive ability, personality, attitudes, interests, and other socio-technical profile characteristics. The research in these projects also include the development of measurements and scales (psychometrics) for human-related vulnerabilities that can be used in estimating more realistically the vulnerability severity, enhancing the CVSS4.0 measurement.

Keywords: social threats, artificial Intelligence, mitigation, social experiment

Procedia PDF Downloads 34

Authors: Bahar Salavati Vie Le Sage, Ismaïl Ben Hariz, Flavien Viguier, Sirine Noura Kahil, Audrey Jacquin, Maxime Convert

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The ballast layer plays a key role in railroad maintenance and the geometry of the track structure. Ballast also holds the track in place as the trains roll over it. Track ballast is packed between the sleepers and on the sides of railway tracks. An imbalance in ballast volume on the tracks can lead to safety issues as well as a quick degradation of the overall quality of the railway segment. If there is a lack of ballast in the track bed during the summer, there is a risk that the rails will expand and buckle slightly due to the high temperatures. Furthermore, the knowledge of the ballast quantities that will be excavated during renewal works is important for efficient ballast management. The volume of excavated ballast per meter of track can be calculated based on excavation depth, excavation width, volume of track skeleton (sleeper and rail) and sleeper spacing. Since 2012, SNCF has been collecting 3D points cloud data covering its entire railway network by using 3D laser scanning technology (LiDAR). This vast amount of data represents a modelization of the entire railway infrastructure, allowing to conduct various simulations for maintenance purposes. This paper aims to present an automated method for ballast volume estimation based on the processing of LiDAR data. The estimation of abnormal volumes in ballast on the tracks is performed by analyzing the cross-section of the track. Further, since the amount of ballast required varies depending on the track configuration, the knowledge of the ballast profile is required. Prior to track rehabilitation, excess ballast is often present in the ballast shoulders. Based on 3D laser scans, a Digital Terrain Model (DTM) was generated and automatic extraction of the ballast profiles from this data is carried out. The surplus in ballast is then estimated by performing a comparison between this ballast profile obtained empirically, and a geometric modelization of the theoretical ballast profile thresholds as dictated by maintenance standards. Ideally, this excess should be removed prior to renewal works and recycled to optimize the output of the ballast renewal machine. Based on these parameters, an application has been developed to allow the automatic measurement of ballast profiles. We evaluated the method on a 108 kilometers segment of railroad LiDAR scans, and the results show that the proposed algorithm detects ballast surplus that amounts to values close to the total quantities of spoil ballast excavated.

Keywords: ballast, railroad, LiDAR , cloud point, track ballast, 3D point

Procedia PDF Downloads 77

Authors: Sagar Ghos, Andrew E. Elaryan, Syed Ashik Ali, Musharraf Zaman, Mohammed Ashiqur Rahman

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Achieving desired density during construction is an important indicator of pavement quality. Insufficient compaction often compromises pavement performance and service life. Intelligent compaction (IC) is an emerging technology for monitoring compaction quality during the construction of asphalt pavements. This paper aims to provide an overview of findings from four case studies in Oklahoma involving the compaction quality of asphalt pavements, namely SE 44th St project (Project 1) and EOC Turnpike project (Project 2), Highway 92 project (Project 3), and 108th Avenue project (Project 4). For this purpose, an IC technology, the intelligent compaction analyzer (ICA), developed at the University of Oklahoma, was used to evaluate compaction quality. Collected data include GPS locations, roller vibrations, roller speed, the direction of movement, and temperature of the asphalt mat. The collected data were analyzed using a widely used software, VETA. The average densities for Projects 1, 2, 3 and 4, were found as 89.8%, 91.50%, 90.7% and 87.5%, respectively. The maximum densities were found as 94.6%, 95.8%, 95.9%, and 89.7% for Projects 1, 2, 3, and 4, respectively. It was observed that the ICA estimated densities correlated well with the field core densities. The ICA results indicated that at least 90% of the asphalt mats were subjected to at least two roller passes. However, the number of passes required to achieve the desired density (94% to 97%) differed from project to project depending on the underlying layer. The results of these case studies show both opportunities and challenges in using IC for monitoring compaction quality during construction in real-time.

Keywords: asphalt pavement construction, density, intelligent compaction, intelligent compaction analyzer, intelligent compaction measure value

Procedia PDF Downloads 130

Authors: Raana Babadi Fathipour

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Over the past decades, the climatic CO2 concentration and worldwide normal temperature have been expanding, and this drift is anticipated to before long gotten to be more extreme. This situation of climate alter escalate abiotic stretch components (such as dry spell, flooding, saltiness, and bright radiation) that debilitate timberland and related environments as well as trim generation. These variables can contrarily influence plant development and advancement with a ensuing lessening in plant biomass aggregation and surrender, in expansion to expanding plant defenselessness to biotic stresses. As of late, biostimulants have ended up a hotspot as an viable and economical elective to reduce the negative impacts of stresses on plants. In any case, the larger part of biostimulants has destitute solidness beneath natural conditions, which leads to untimely debasement, shortening their organic movement. To unravel these bottlenecks, small scale- and nano-based definitions containing biostimulant atoms and/or microorganisms are picking up consideration as they illustrate a few points of interest over their routine details. In this survey, we center on the embodiment of plant development controllers and plant acquainted microorganisms as a technique to boost their application for plant assurance against abiotic stresses. We moreover address the potential restrictions and challenges confronted for the execution of this innovation, as well as conceivable outcomes with respect to future inquire about.

Keywords: bio stimulants, Seed priming, nano biotechnology, plant growth-promoting, rhizobacteria, plant growth regulators, microencapsulation

Procedia PDF Downloads 42

Authors: Saja M. Nabat Al-Ajrash, Charles Browning, Rose Eckerle, Li Cao, Robyn L. Bradford, Donald Klosterman

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An additive manufacturing process and subsequent pyrolysis cycle were used to fabricate SiC matrix/carbon fiber hybrid composites. The matrix was fabricated using a mixture of preceramic polymer and acrylate monomers, while polyacrylonitrile (PAN) precursor was used to fabricate fibers via electrospinning. The precursor matrix and reinforcing fibers at 0, 2, 5, or 10 wt% were printed using digital light processing, and both were simultaneously pyrolyzed to yield the final ceramic matrix composite structure. After pyrolysis, XRD and SEAD analysis proved the existence of SiC nanocrystals and turbostratic carbon structure in the matrix, while the reinforcement phase was shown to have a turbostratic carbon structure similar to commercial carbon fibers. Thermogravimetric analysis (TGA) in the air up to 1400 °C was used to evaluate the oxidation resistance of this material. TGA results showed some weight loss due to oxidation of SiC and/or carbon up to about 900 °C, followed by weight gain to about 1200 °C due to the formation of a protective SiO2 layer. Although increasing carbon fiber content negatively impacted the total mass loss for the first heating cycle, exposure of the composite to second-run air revealed negligible weight chance. This is explained by SiO2 layer formation, which acts as a protective film that prevents oxygen diffusion. Oxidation of SiC and the formation of a glassy layer has been proven to protect the sample from further oxidation, as well as provide healing of surface cracks and defects, as revealed by SEM analysis.

Keywords: silicon carbide, carbon fibers, additive manufacturing, composite

Procedia PDF Downloads 49

Authors: Seokyoon Moon, Yun-Ho Ahn, Heejoong Kim, Sujin Hong, Yunseok Lee, Youngjune Park

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Gas hydrate is a non-stoichiometric crystalline compound consisting of host water-framework and low molecular weight guest molecules. Small gaseous molecules such as CH₄, CO₂, and N₂ can be captured in the host water framework lattices of the gas hydrate with specific temperature and pressure conditions. The three well-known crystal structures of structure I (sI), structure II (sII), and structure H (sH) are determined by the size and shape of guest molecules. In this study, we measured the phase equilibria of binary (2,2-dimethyl-1-propanol + CO₂, CH₄, N₂) hydrates to explore their fundamental thermodynamic characteristics. We identified the structure of the binary gas hydrate by employing synchrotron high-resolution powder diffraction (HRPD), and the guest distributions in the lattice of gas hydrate were investigated via dispersive Raman and ¹³C solid-state nuclear magnetic resonance (NMR) spectroscopies. The end-to-end distance of 2,2-dimethyl-1-propanol was calculated to be 7.76 Å, which seems difficult to be enclathrated in large cages of sI or sII. However, due to the flexibility of the host water framework, binary hydrates of sI or sII types can be formed with the help of small gas molecule. Also, the synchrotron HRPD patterns revealed that the binary hydrate structure highly depends on the type of help gases; a cubic Fd3m sII hydrate was formed with CH₄ or N₂, and a cubic Pm3n sI hydrate was formed with CO₂. Interestingly, dispersive Raman and ¹³C NMR spectra showed that the unique tuning phenomenon occurred in binary (2,2-dimethyl-1-propanol + CO₂) hydrate. By optimizing the composition of NPA, we can achieve both thermodynamic stability and high CO₂ storage capacity for the practical application to CO₂ capture.

Keywords: clathrate, gas hydrate, neopentyl alcohol, CO₂, tuning phenomenon

Procedia PDF Downloads 215

Authors: Reza Hadjiaghaie Vafaie, Sevda Givtaj

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Automation and control of biological samples and solutions at the microscale is a major advantage for biochemistry analysis and biological diagnostics. Despite the known potential of miniaturization in biochemistry and biomedical applications, comparatively little is known about fluid automation and control at the microscale. Here, we study the electric field effect inside a fluidic channel and proper electrode structures with different patterns proposed to form forward, reversal, and rotational flows inside the channel. The simulation results confirmed that the ac electro-thermal flow is efficient for the control and automation of high-conductive solutions. In this research, the fluid pumping and mixing effects were numerically studied by solving physic-coupled electric, temperature, hydrodynamic, and concentration fields inside a microchannel. From an experimental point of view, the electrode structures are deposited on a silicon substrate and bonded to a PDMS microchannel to form a microfluidic chip. The motions of fluorescent particles in pumping and mixing modes were captured by using a CCD camera. By measuring the frequency response of the fluid and exciting the electrodes with the proper voltage, the fluid motions (including pumping and mixing effects) are observed inside the channel through the CCD camera. Based on the results, there is good agreement between the experimental and simulation studies.

Keywords: microfluidic, nano/micro actuator, AC electrothermal, Reynolds number, micropump, micromixer, microfabrication, mass transfer, biomedical applications

Procedia PDF Downloads 49

Authors: Alexander J. Severinsky, Allen L. Sessoms

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Atmospheric carbon dioxide (CO₂) has dominated the discussion about the causes of climate change. This is a reflection of the time horizon that has become the norm adopted by the IPCC as the planning horizon. Recently, it has become clear that a 100-year time horizon is much too long, and yet almost all mitigation efforts, including those in the near-term horizon of 30 years, are geared toward it. In this paper, we show that, for a 30-year time horizon, methane (CH₄) is the greenhouse gas whose radiative forcing exceeds that of CO₂. In our analysis, we used radiative forcing of greenhouse gases in the atmosphere since they directly affect the temperature rise on Earth. In 2019, the radiative forcing of methane was ~2.5 W/m² and that of carbon dioxide ~2.1 W/m². Under a business-as-usual (BAU) scenario until 2050, such forcing would be ~2.8 W/m² and ~3.1 W/m², respectively. There is a substantial spread in the data for anthropogenic and natural methane emissions as well as CH₄ leakages from production to consumption. We estimated the minimum and maximum effects of the reduction of these leakages. Such action may reduce the annual radiative forcing of all CH₄ emissions by between ~15% and ~30%. This translates into a reduction of the RF by 2050 from ~2.8 W/m² to ~2.5 W/m² in the case of the minimum effect and to ~2.15 W/m² in the case of the maximum. Under the BAU, we found that the RF of CO₂ would increase from ~2.1 W/m² nowadays to ~3.1 W/m² by 2050. We assumed a reduction of 50% of anthropogenic emission linearly over the next 30 years. That would reduce radiative forcing from ~3.1 W/m² to ~2.9 W/m². In the case of ‘net zero,’ the other 50% of reduction of only anthropogenic emissions would be limited to either from sources of emissions or directly from the atmosphere. The total reduction would be from ~3.1 to ~2.7, or ~0.4 W/m². To achieve the same radiative forcing as in the scenario of maximum reduction of methane leakages of ~2.15 W/m², then an additional reduction of radiative forcing of CO₂ would be approximately 2.7 -2.15=0.55 W/m². This is a much larger value than in expectations from ‘net zero’. In total, one needs to remove from the atmosphere ~660 GT to match the maximum reduction of current methane leakages and ~270 GT to achieve ‘net zero.’ This amounts to over 900 GT in total.

Keywords: methane leakages, methane radiative forcing, methane mitigation, methane net zero

Procedia PDF Downloads 121

Authors: N. Z. van Hierden, Q. Yu, F. Gauvin

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Cement manufacturing is, because of its production process, among the highest contributors to CO₂ emissions worldwide. As cement is one of the major components in 3D printed concrete, achieving sustainability and carbon neutrality can be particularly challenging. To improve the sustainability of 3D printed materials, different CO₂-reducing strategies can be used, each one with a distinct level of impact and complexity. In this work, we focus on the development of these sustainable mixtures and finding alternatives. Promising alternatives for cement and clinker replacement include the use of recycled building materials, amongst which (calcined) bricks and roof tiles. To study the potential of recycled clay-based building materials, the application of calcinated clay itself is studied as well. Compared to cement, the calcination temperature of clay-based materials is significantly lower, resulting in reduced CO₂ output. Reusing these materials is therefore a promising solution for utilizing waste streams while simultaneously reducing the cement content in 3D concrete mixtures. In addition, waste streams can be locally sourced, thereby reducing the emitted CO₂ during transportation. In this research, various alternative binders are examined, such as calcined clay blends (LC3) from recycled tiles and bricks, or locally obtained clay resources. Using various experiments, a high potential for mix designs including these resources has been shown with respect to material strength, while sustaining decent printability and buildability. Therefore, the defined strategies are promising and can lead to a more sustainable, low-CO₂ mixture suitable for 3D printing while using accessible materials.

Keywords: cement replacement, 3DPC, circular building materials, calcined clay, CO₂ reduction

Procedia PDF Downloads 60

Authors: Konstantinos Sotiriadis, Michael Tupý, Nikol Žižková, Vít Petránek

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The acid attack on cement mortars modified with rubber aggregates and EVA polymer binder was studied. Mortar specimens were prepared using a type CEM I 42.5 Portland cement and siliceous sand, as well as by substituting 25% of sand with shredded used automobile tires, and by adding EVA polymer in two percentages (5% and 10% of cement mass). Some specimens were only air cured, at laboratory conditions, and their compressive strength and water absorption were determined. The rest specimens were stored in acid solutions (HCl, H2SO4, HNO3) after 28 days of initial curing, and stored at laboratory temperature. Compressive strength tests, mass measurements and visual inspection took place for 28 days. Compressive strength and water absorption of the air-cured specimens were significantly decreased when rubber aggregates are used. The addition of EVA polymer further reduced water absorption, while had no important impact on strength. Compressive strength values were affected in a greater extent by hydrochloric acid solution, followed by sulfate and nitric acid solutions. The addition of EVA polymer decreased compressive strength loss for the specimens with rubber aggregates stored in hydrochloric and nitric acid solutions. The specimens without polymer binder showed similar mass loss, which was higher in sulfate acid solution followed by hydrochloric and nitric acid solutions. The use of EVA polymer delayed mass loss, while its content did not affect it significantly.

Keywords: acid attack, mortar, EVA polymer, rubber aggregates

Procedia PDF Downloads 265

Authors: Parth Mehta, Vedasri Bai Khavala, Prabhu Rajagopal, Tiju Thomas

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There is an increasing need for alternative clean fuels, and hydrogen (H₂) has long been considered a promising solution with a high calorific value (142MJ/kg). However, the storage of H₂ and expensive processes for its generation have hindered its usage. Sodium borohydride (NaBH₄) can potentially be used as an economically viable means of H₂ storage. Thus far, there have been attempts to optimize the life of NaBH₄ (half-life) in aqueous media by stabilizing it with sodium hydroxide (NaOH) for various pH values. Other reports have shown that H₂ yield and reaction kinetics remained constant for all ratios of H₂O to NaBH₄ > 30:1, without any acidic catalysts. Here we highlight the importance of pH and H₂O: NaBH₄ ratio (80:1, 40:1, 20:1 and 10:1 by weight), for NaBH₄ stabilization (half-life reaction time at room temperature) and corrosion minimization of H₂ reactor components. It is interesting to observe that at any particular pH>10 (e.g., pH = 10, 11 and 12), the H₂O: NaBH₄ ratio does not have the expected linear dependence with stability. On the contrary, high stability was observed at the ratio of 10:1 H₂O: NaBH₄ across all pH>10. When the H₂O: NaBH₄ ratio is increased from 10:1 to 20:1 and beyond (till 80:1), constant stability (% degradation) is observed with respect to time. For practical usage (consumption within 6 hours of making NaBH₄ solution), 15% degradation at pH 11 and NaBH₄: H₂O ratio of 10:1 is recommended. Increasing this ratio demands higher NaOH concentration at the same pH, thus requiring a higher concentration or volume of acid (e.g., HCl) for H₂ generation. The reactions are done with tap water to render the results useful from an industrial standpoint. The observed stability regimes are rationalized based on complexes associated with NaBH₄ when solvated in water, which depend sensitively on both pH and NaBH₄: H₂O ratio.

Keywords: hydrogen, sodium borohydride, stability optimization, H₂O:NaBH₄ ratio

Procedia PDF Downloads 95

Authors: Cora Bulmău

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Soil polluted with hydrocarbons spills is a major global concern today. As a response to this issue, our experimental study tries to put in evidence the option to choose for one environmentally friendly method: use of the biochar, despite to a classical procedure; incineration of contaminated soil. Biochar represents the solid product obtained through the pyrolysis of biomass, its additional use being as an additive intended to improve the quality of the soil. The positive effect of biochar addition to soil is represented by its capacity to adsorb and contain petroleum products within its pores. Taking into consideration the capacity of the biochar to interact with organic contaminants, the purpose of the present study was to experimentally establish the effects of the addition of wooden biomass-derived biochar on a soil contaminated with oil. So, the contaminated soil was amended with biochar (10%) produced by pyrolysis in different operational conditions of the thermochemical process. After 25 days, the concentration of petroleum hydrocarbons from soil treated with biochar was measured. An analytical method as Soxhlet extraction was adopted to estimate the concentrations of total petroleum products (TPH) in the soil samples: This technique was applied to contaminated soil, also to soils remediated by incineration/adding biochar. The treatment of soil using biochar obtained from pyrolysis of the Birchwood led to a considerable decrease in the concentrations of petroleum products. The incineration treatments conducted under experimental stage to clean up the same soil, contaminated with petroleum products, involved specific parameters: temperature of about 600°C, 800°C and 1000°C and treatment time 30 and 60 minutes. The experimental results revealed that the method using biochar has registered values of efficiency up to those of all incineration processes applied for the shortest time.

Keywords: biochar, biomass, remediaton, soil, TPH

Procedia PDF Downloads 206