Search results for: discrete element simulation

Authors: Sara Mosallanejad, Bogdan Z. Dlugogorski, Jeff Gore, Mohammednoor Altarawneh

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Ammonium nitrate (NH­₄NO₃, AN) is commonly used as the main component of AN emulsion and fuel oil (ANFO) explosives, that use extensively in civilian and mining operations for underground development and tunneling applications. The emulsion formulation and wettability of AN prills, which affect the physical stability and detonation of ANFO, highly depend on the surface tension, density, viscosity of the used liquid. Therefore, for engineering applications of this material, the determination of density and surface tension of concentrated aqueous solutions of AN is essential. The molecular dynamics (MD) simulation method have been used to investigate the density and the surface tension of high concentrated ammonium nitrate solutions; up to its solubility limit in water. Non-polarisable models for water and ions have carried out the simulations, and the electronic continuum correction model (ECC) uses a scaling of the charges of the ions to apply the polarisation implicitly into the non-polarisable model. The results of calculated density and the surface tension of the solutions have been compared to available experimental values. Our MD simulations show that the non-polarisable model with full-charge ions overestimates the experimental results while the reduce-charge model for the ions fits very well with the experimental data. Ions in the solutions show repulsion from the interface using the non-polarisable force fields. However, when charges of the ions in the original model are scaled in line with the scaling factor of the ECC model, the ions create a double ionic layer near the interface by the migration of anions toward the interface while cations stay in the bulk of the solutions. Similar ions orientations near the interface were observed when polarisable models were used in simulations. In conclusion, applying the ECC model to the non-polarisable force field yields the density and surface tension of the AN solutions with high accuracy in comparison to the experimental measurements.

Keywords: ammonium nitrate, electronic continuum correction, non-polarisable force field, surface tension

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Authors: Abdullah Alenezi, Mane Alsudrawi, Rafat Misak

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Kuwait is faced with a potentially wide and harmful range of both natural and anthropogenic hazardous events such as dust storms, floods, fires, nuclear accidents, earthquakes, oil spills, tsunamis and other disasters. For Kuwait can be highly vulnerable to these complex environmental risks, an up-to-date and in-depth understanding of their typology, genesis, and impact on the Kuwaiti society is needed. Adequate anticipation and management of environmental crises further require a comprehensive system of decision support to the benefit of decision makers to further bridge the gap between (technical) risk understanding and public action. For that purpose, the Kuwait Institute for Scientific Research (KISR), intends to establish a decision support center for management of the environmental crisis in Kuwait. The center will support policy makers, stakeholders and national committees with technical information that helps them efficiently and effectively assess, monitor to manage environmental disasters using decision support tools. These tools will build on state of the art quantification and visualization techniques, such as remote sensing information, Geographical Information Systems (GIS), simulation and prediction models, early warning systems, etc. The center is conceived as a central facility which will be designed, operated and managed by KISR in coordination with national authorities and decision makers of the country. Our vision is that by 2035 the center will be recognized as a leading national source of scientific advice on national risk management in Kuwait and build unity of effort among Kuwaiti’s institutions, government agencies, public and private organizations through provision and sharing of information. The project team now focuses on capacity building through upgrading some KISR facilities manpower development, build strong collaboration with international alliance.

Keywords: decision support, environment, hazard, Kuwait

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Authors: V. Thomas, O. Delaune, W. Hennig, S. Hoover

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Measurement of radioactive isotopes of atmospheric xenon is used to detect, locate and identify any confined nuclear tests as part of the Comprehensive Nuclear Test-Ban Treaty (CTBT). In this context, the Alternative Energies and French Atomic Energy Commission (CEA) has developed a fixed device to continuously measure the concentration of these fission products, the SPALAX process. During its atmospheric transport, the radioactive xenon will undergo a significant dilution between the source point and the measurement station. Regarding the distance between fixed stations located all over the globe, the typical volume activities measured are near 1 mBq m⁻³. To avoid the constraints induced by atmospheric dilution, the development of a mobile detection system is in progress; this system will allow on-site measurements in order to confirm or infringe a suspicious measurement detected by a fixed station. Furthermore, this system will use beta/gamma coincidence measurement technique in order to drastically reduce environmental background (which masks such activities). The detector prototype consists of a gas cell surrounded by two large silicon wafers, coupled with two square NaI(Tl) detectors. The gas cell has a sample volume of 30 cm³ and the silicon wafers are 500 µm thick with an active surface area of 3600 mm². In order to minimize leakage current, each wafer has been segmented into four independent silicon pixels. This cell is sandwiched between two low background NaI(Tl) detectors (70x70x40 mm³ crystal). The expected Minimal Detectable Concentration (MDC) for each radio-xenon is in the order of 1-10 mBq m⁻³. Three 4-channels digital acquisition modules (Pixie-NET) are used to process all the signals. Time synchronization is ensured by a dedicated PTP-network, using the IEEE 1588 Precision Time Protocol. We would like to present this system from its simulation to the laboratory tests.

Keywords: beta/gamma coincidence technique, low level measurement, radioxenon, silicon pixels

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Authors: Azam Fazelpour, Saeed Reza Dehghani, Vlastimil Masek, Yuri S. Muzychka

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The study uses a novel image analysis based on thermal imaging to detect temperature contours created on salt ice surface during transient phenomena. Thermal cameras detect objects by using their emissivities and IR radiance. The ice surface temperature is not uniform during transient processes. The temperature starts to increase from the boundary of ice towards the center of that. Thermal cameras are able to report temperature changes on the ice surface at every individual moment. Various contours, which show different temperature areas, appear on the ice surface picture captured by a thermal camera. Identifying the exact boundary of these contours is valuable to facilitate ice surface temperature analysis. Image processing techniques are used to extract each contour area precisely. In this study, several pictures are recorded while the temperature is increasing throughout the ice surface. Some pictures are selected to be processed by a specific time interval. An image segmentation method is applied to images to determine the contour areas. Color thermal images are used to exploit the main information. Red, green and blue elements of color images are investigated to find the best contour boundaries. The algorithms of image enhancement and noise removal are applied to images to obtain a high contrast and clear image. A novel edge detection algorithm based on differences in the color of the pixels is established to determine contour boundaries. In this method, the edges of the contours are obtained according to properties of red, blue and green image elements. The color image elements are assessed considering their information. Useful elements proceed to process and useless elements are removed from the process to reduce the consuming time. Neighbor pixels with close intensities are assigned in one contour and differences in intensities determine boundaries. The results are then verified by conducting experimental tests. An experimental setup is performed using ice samples and a thermal camera. To observe the created ice contour by the thermal camera, the samples, which are initially at -20° C, are contacted with a warmer surface. Pictures are captured for 20 seconds. The method is applied to five images ,which are captured at the time intervals of 5 seconds. The study shows the green image element carries no useful information; therefore, the boundary detection method is applied on red and blue image elements. In this case study, the results indicate that proposed algorithm shows the boundaries more effective than other edges detection methods such as Sobel and Canny. Comparison between the contour detection in this method and temperature analysis, which states real boundaries, shows a good agreement. This color image edge detection method is applicable to other similar cases according to their image properties.

Keywords: color image processing, edge detection, ice contour boundary, salt ice, thermal image

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Authors: Zhuanfang Fred Zhang, Tim C. Johnson, Yilin Fang, Chris E. Strickland

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A variety of geophysical techniques are available to image the opaque subsurface with little or no contact with the soil. It is common to conduct time-lapse surveys of different types for a given site for improved results of subsurface imaging. Regardless of the chosen survey methods, it is often a challenge to process the massive amount of survey data. The currently available software applications are generally based on the one-dimensional assumption for a desktop personal computer. Hence, they are usually incapable of imaging the three-dimensional (3D) processes/variables in the subsurface of reasonable spatial scales; the maximum amount of data that can be inverted simultaneously is often very small due to the capability limitation of personal computers. Presently, high-performance or integrating software that enables real-time integration of multi-process geophysical methods is needed. E4D-MP enables the integration and inversion of time-lapsed large-scale data surveys from geophysical methods. Using the supercomputing capability and parallel computation algorithm, E4D-MP is capable of processing data across vast spatiotemporal scales and in near real time. The main code and the modules of E4D-MP for inverting individual or combined data sets of time-lapse 3D electrical resistivity, spectral induced polarization, and gravity surveys have been developed and demonstrated for sub-surface imaging. E4D-MP provides capability of imaging the processes (e.g., liquid or gas flow, solute transport, cavity development) and subsurface properties (e.g., rock/soil density, conductivity) critical for successful control of environmental engineering related efforts such as environmental remediation, carbon sequestration, geothermal exploration, and mine land reclamation, among others.

Keywords: gravity survey, high-performance computing, sub-surface monitoring, electrical resistivity tomography

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Authors: Melike Sultan Karasu Asnaz, Ayse Ozdogan Dolcek

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Crop drying, which aims to reduce the moisture content to a certain level, is a method used to extend the shelf life and prevent it from spoiling. One of the oldest food preservation techniques is open sunor shade drying. Even though this technique is the most affordable of all drying methods, there are some drawbacks such as contamination by insects, environmental pollution, windborne dust, and direct expose to weather conditions such as wind, rain, hail. However, solar dryers that provide a hygienic and controllable environment to preserve food and extend its shelf life have been developed and used to dry agricultural products. Thus, foods can be dried quickly without being affected by weather variables, and quality products can be obtained. This research is mainly devoted to investigating the modelling of drying kinetics of cantaloupe in a forced convection solar dryer. Mathematical models for the drying process should be defined to simulate the drying behavior of the foodstuff, which will greatly contribute to the development of solar dryer designs. Thus, drying experiments were conducted and replicated five times, and various data such as temperature, relative humidity, solar irradiation, drying air speed, and weight were instantly monitored and recorded. Moisture content of sliced and pretreated cantaloupe were converted into moisture ratio and then fitted against drying time for constructing drying curves. Then, 10 quasi-theoretical and empirical drying models were applied to find the best drying curve equation according to the Levenberg-Marquardt nonlinear optimization method. The best fitted mathematical drying model was selected according to the highest coefficient of determination (R²), and the mean square of the deviations (χ^²) and root mean square error (RMSE) criterial. The best fitted model was utilized to simulate a thin layer solar drying of cantaloupe, and the simulation results were compared with the experimental data for validation purposes.

Keywords: solar dryer, mathematical modelling, drying kinetics, cantaloupe drying

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Authors: Gao Youtao, Zhao Tanran, Jin Bingyu, Xu Bo

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Global navigation satellite system(GNSS) can deliver navigation information for spacecraft orbiting on low-Earth orbits and medium Earth orbits. However, the GNSS cannot navigate the spacecraft on high-Earth orbit or deep space probes effectively. With the deep space exploration becoming a hot spot of aerospace, the demand for a deep space satellite navigation system is becoming increasingly prominent. Many researchers discussed the feasibility and performance of a satellite navigation system on periodic orbits around the Earth-Moon libration points which can be called Lagrangian point satellite navigation system. Autonomous orbit determination (AOD) is an important performance for the Lagrangian point satellite navigation system. With this ability, the Lagrangian point satellite navigation system can reduce the dependency on ground stations. AOD also can greatly reduce total system cost and assure mission continuity. As the elliptical restricted three-body problem can describe the Earth-Moon system more accurately than the circular restricted three-body problem, we study the autonomous orbit determination of Lagrangian navigation constellation using only crosslink range based on elliptical restricted three body problem. Extended Kalman filter is used in the autonomous orbit determination. In order to compare the autonomous orbit determination results based on elliptical restricted three-body problem to the results of autonomous orbit determination based on circular restricted three-body problem, we give the autonomous orbit determination position errors of a navigation constellation include four satellites based on the circular restricted three-body problem. The simulation result shows that the Lagrangian navigation constellation can achieve long-term precise autonomous orbit determination using only crosslink range. In addition, the type of the libration point orbit will influence the autonomous orbit determination accuracy.

Keywords: extended Kalman filter, autonomous orbit determination, quasi-periodic orbit, navigation constellation

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Authors: Gregor Kosec

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Simple and robust numerical approach for solving flow problems is presented, where involved physical fields are represented through the local approximation functions, i.e., the considered field is approximated over a local support domain. The approximation functions are then used to evaluate the partial differential operators. The type of approximation, the size of support domain, and the type and number of basis function can be general. The solution procedure is formulated completely through local computational operations. Besides local numerical method also the pressure velocity is performed locally with retaining the correct temporal transient. The complete locality of the introduced numerical scheme has several beneficial effects. One of the most attractive is the simplicity since it could be understood as a generalized Finite Differences Method, however, much more powerful. Presented methodology offers many possibilities for treating challenging cases, e.g. nodal adaptivity to address regions with sharp discontinuities or p-adaptivity to treat obscure anomalies in physical field. The stability versus computation complexity and accuracy can be regulated by changing number of support nodes, etc. All these features can be controlled on the fly during the simulation. The presented methodology is relatively simple to understand and implement, which makes it potentially powerful tool for engineering simulations. Besides simplicity and straightforward implementation, there are many opportunities to fully exploit modern computer architectures through different parallel computing strategies. The performance of the method is presented on the lid driven cavity problem, backward facing step problem, de Vahl Davis natural convection test, extended also to low Prandtl fluid and Darcy porous flow. Results are presented in terms of velocity profiles, convergence plots, and stability analyses. Results of all cases are also compared against published data.

Keywords: fluid flow, meshless, low Pr problem, natural convection

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Authors: Rico Herrero

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The study looked into the different lived experiences of senior high school to work immersion and how they were able to cope up in the transition stage from being classroom students into immersion students in work immersion site. The participants of the study were the ten senior high school students from Punta Integrated School. Using interview guide questions, the researchers motivated the participants to reveal their thoughts, feelings, and experiences in the interviews via video recording. The researchers utilized the qualitative research design, but the approach used was grounded theory. The findings revealed the participants’ lived experiences on how to cope or overcome the transition stage during the work immersion program. They unanimously responded to the interview questions. And based on the themes that emerged from the testimonies of the Senior High School students, the classroom learners benefited a lot from authentic learning opportunity of immersion program. Work immersion provides the students the opportunity to learn and develop their skills/ competencies related to the field of specialization. The hands-on training provides them simulation of work. They realized that theoretical learning in school is not enough to be equipped to work. Immersion program also provides venue for values and standard transformation. Senior High School students felt a high demand of self-confidence at the beginning of their race. Good thing, self-esteem of an individual helps bring out one’s potential at its best. Students find it challenging to get along with people in all ages. But, the endeavour absolutely helps them to grow maturely. Participants also realized that it’s not easy to deal with time pressure. Hence, the immersion program taught them to learn about time management. Part of the best training is to expose the learners to the harsh reality. Despite of the things that the school had taught them, still, students realized that they are not yet ready to deal with the demands of work. Furthermore, they also found out that they need to develop an interpersonal skill to improve their human relationships.

Keywords: grounded theory, lived experiences, senior high school, work immersion

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Authors: Xiaoqin Wang, Li Yin

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Background and purpose: In many practices, one estimates causal effects arising from a complex stochastic process, where a sequence of treatments are assigned to influence a certain outcome of interest, and there exist time-dependent covariates between treatments. When covariates are plentiful and/or continuous, statistical modeling is needed to reduce the huge dimensionality of the problem and allow for the estimation of causal effects. Recently, Wang and Yin (Annals of statistics, 2020) derived a new general formula, which expresses these causal effects in terms of the point effects of treatments in single-point causal inference. As a result, it is possible to conduct the modeling via point effects. The purpose of the work is to study the modeling of these causal effects via point effects. Challenges and solutions: The time-dependent covariates often have influences from earlier treatments as well as on subsequent treatments. Consequently, the standard parameters – i.e., the mean of the outcome given all treatments and covariates-- are essentially all different (null paradox). Furthermore, the dimension of the parameters is huge (curse of dimensionality). Therefore, it can be difficult to conduct the modeling in terms of standard parameters. Instead of standard parameters, we have use point effects of treatments to develop likelihood-based parametric approach to the modeling of these causal effects and are able to model the causal effects of a sequence of treatments by modeling a small number of point effects of individual treatment Achievements: We are able to conduct the modeling of the causal effects from a sequence of treatments in the familiar framework of single-point causal inference. The simulation shows that our method achieves not only an unbiased estimate for the causal effect but also the nominal level of type I error and a low level of type II error for the hypothesis testing. We have applied this method to a longitudinal study of COVID-19 mortality among Scandinavian countries and found that the Swedish approach performed far worse than the other countries' approach for COVID-19 mortality and the poor performance was largely due to its early measure during the initial period of the pandemic.

Keywords: causal effect, point effect, statistical modelling, sequential causal inference

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Authors: Philip A. Moore Jr., Jerry Martin, Hong Li

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Research has shown that over half of the nitrogen (N) excreted from broiler chickens is emitted to the atmosphere before the manure is removed from the barns, resulting in air and water pollution, as well as the loss of a valuable fertilizer resource. The objective of this study was to determine the fertilizer efficiency of N captured from the exhaust air from poultry houses using acid scrubbers. This research was conducted using 24 plots located on a Captina silt loam soil. There were six treatments: (1) unfertilized control, (2) aluminum sulfate (alum) scrubber solution, (3) potassium bisulfate scrubber solution, (4) sodium bisulfate scrubber solution, (5) sulfuric acid scrubber solution and (6) ammonium nitrate fertilizer dissolved in water. There were four replications per treatment in a randomized block design. The scrubber solutions were obtained from acid scrubbers attached to exhaust fans on commercial broiler houses. All N sources were applied at an application rate equivalent to 112 kg N ha⁻¹. Forage yields were measured five times throughout the growing season. Five months after the fertilizer sources were applied, a rainfall simulation study was conducted to determine the potential effects on phosphorus (P) runoff. Forage yields were significantly higher in plots fertilized with scrubber solutions from potassium bisulfate and sodium bisulfate than plots fertilized with scrubber solutions made from alum or sulfuric acid or ammonium nitrate, which were higher than the controls (7.61, 7.46, 6.87, 6.72, 6.45, and 5.12 Mg ha ⁻¹, respectively). Forage N uptake followed similar trends as yields. Phosphorus runoff and water soluble P was significantly lower in plots fertilized with the scrubber solutions made from aluminum sulfate. This study demonstrates that N captured using ammonia scrubbers is as good or possibly better than commercial ammonium nitrate fertilizer.

Keywords: air quality, ammonia emissions, nitrogen fertilizer, poultry

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Authors: Gautier Girard, Marion Martiny, Sebastien Mercier, Mohamad Jrad, Mohamed-Slim Bahi, Laurent Bodin, Francois Lechleiter, David Nevo, Sophie Dareys

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Reliability of electronic devices has always been of highest interest for Aero-MIL and space applications. In any electronic device, Printed Circuit Board (PCB), providing interconnection between components, is a key for reliability. During the last decades, PCB technologies evolved to sustain and/or fulfill increased original equipment manufacturers requirements and specifications, higher densities and better performances, faster time to market and longer lifetime, newer material and mixed buildups. From the very beginning of the PCB industry up to recently, qualification, experiments and trials, and errors were the most popular methods to assess system (PCB) reliability. Nowadays OEM, PCB manufacturers and scientists are working together in a close relationship in order to develop predictive models for PCB reliability and lifetime. To achieve that goal, it is fundamental to characterize precisely base materials (laminates, electrolytic copper, …), in order to understand failure mechanisms and simulate PCB aging under environmental constraints by means of finite element method for example. The laminates are woven composites and have thus an orthotropic behaviour. The in-plane properties can be measured by combining classical uniaxial testing and digital image correlation. Nevertheless, the out-of-plane properties cannot be evaluated due to the thickness of the laminate (a few hundred of microns). It has to be noted that the knowledge of the out-of-plane properties is fundamental to investigate the lifetime of high density printed circuit boards. A homogenization method combining analytical and numerical approaches has been developed in order to obtain the complete elastic orthotropic behaviour of a woven composite from its precise 3D internal structure and its experimentally measured in-plane elastic properties. Since the mechanical properties of the resin surrounding the fibres are unknown, an inverse method is proposed to estimate it. The methodology has been applied to one laminate used in hyperfrequency spatial applications in order to get its elastic orthotropic behaviour at different temperatures in the range [-55°C; +125°C]. Next; numerical simulations of a plated through hole in a double sided PCB are performed. Results show the major importance of the out-of-plane properties and the temperature dependency of these properties on the lifetime of a printed circuit board. Acknowledgements—The support of the French ANR agency through the Labcom program ANR-14-LAB7-0003-01, support of CNES, Thales Alenia Space and Cimulec is acknowledged.

Keywords: homogenization, orthotropic behaviour, printed circuit board, woven composites

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Authors: Abhimanyu Kumar

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The relationship between religion and medicine is much evident in the context of Buddhism. This paper is an attempt to look at the processes of social and cultural evolution of scientific creativity in the field of medicine and institutionalization of medical practices. The objective of the paper is to understand the Buddhist responses towards health as understood from the Vinaya Piṭaka and the Jātaka. This work is a result of the analysis of two important Buddhist texts: the Vinaya Piṭaka and the Jātaka. Broadly the Vinaya Piṭaka is concerned with the growth of Buddhist monasticism. The Vinaya Piṭaka is considered one of the most important sacred texts of the Buddhists, and contains rules for monastic life. These rules deal with such aspects as formal meetings of the saṃgha (monastery), expiation, confession, training, and legal questions. The Jātaka stories, on the other hand, are in the form of folk narratives, and provide a major source of medical consultation for all classes. These texts help us to ascertain the ‘proficiency and perceptions’ of the prevailing medical traditions. The Jātakas are a collection of 547 stories about the past lives of the Buddha, who is represented in anthropomorphic and animal form. The Jātaka connects itself between existing cognitive environments related to ethics and Buddhist didacticism. These stories are a reflection of the connection between the past and contemporary times (in the sense of time of creation of the story) as well. This is visible through the narrative strategy of the text, where every story is sub-divided into the story of the past and story of the present, and there is a significant identification element or connection that established at the end of each story. The minimal presence of philosophical content and the adoption of a narrative strategy make it possible for more of everyday life. This study gives me an opportunity to raise questions about how far were the body and mind closely interrelated in the Buddhist perceptions, and also did the society act like a laboratory for the Buddhists to practice healing activities? How far did religious responses to afflictions, be they leprosy or plague or anger, influence medical care; what impact did medical practitioners, religious authorities and the regulation of medical activity and practice have on healing the body and the mind; and, how has the healing environment been viewed. This paper is working with the idea that medical science in early India was not only for the curative purpose of diseases, but it fulfilled a greater cause of promoting, maintaining and restoring human health. In this regard, studying these texts gives an insight regarding religious responses to epidemics, from leprosy to plague, as well as to behavioral disorder such as anger. In other words, it deals with the idea about healing the body and healing the soul from a religious perspective.

Keywords: food for health, folk narratives, human body, materia medica, social sickness

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Authors: Imran, Murad Ali Rahat

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One of the factors affecting crop production and nutrient availability is acidic stress. The most important element decreasing under acidic stress conditions is phosphorus deficiency, which results in stunted growth and yield because of inefficient nutrient cycling. At the Agriculture Research Institute Mingora Swat, Pakistan, tests were carried out for the first time throughout the course of two consecutive summer seasons in 2016 (year 1) and 2017 (year 2) with the goal of increasing crop productivity and nutrient availability under acidic stress. Three organic supplies (peach nano-black carbon, compost, and dry-based peach wastes), three phosphorus rates, and two advantageous microorganisms (Trichoderma and PSB) were incorporated in the experimental treatments. The findings showed that, in conditions of acid stress, peach organic sources had a significant impact on yield and yield components. The application of nano-black carbon produced the greatest thousand seed weight of 164.6 g among organic sources, however the use of phosphorus solubilizing bacteria (PSB) for seed inoculation increased the thousand seed weight of beneficial microbes when compared to Trichoderma soil application. The thousand seed weight was significantly impacted by the quantities of phosphorus. The treatment of 100 kg P ha-1 produced the highest thousand seed weight (167.3 g), which was followed by 75 kg P ha-1 (162.5 g). Compost amendments provided the highest seed yield (2,140 kg ha-1) and were comparable to the application of nano-black carbon (2,120 kg ha-1). With peach residues, the lowest seed output (1,808 kg ha-1) was observed.Compared to seed inoculation with PSB (1,913 kg ha-1), soil treatment with Trichoderma resulted in the maximum seed production (2,132 kg ha-1). Applying phosphorus to the soybean crop greatly increased its output. The highest seed yield (2,364 kg ha-1) was obtained with 100 kg P ha-1, which was comparable to 75 kg P ha-1 (2,335 kg ha-1), while the lowest seed yield (1,569 kg ha-1) was obtained with 50 kg P ha-1. The average values showed that compared to control plots (3.3 g kg-1), peach organic sources produced greatest SOC (10.0 g kg-1). Plots with treated soil had a maximum soil P of 19.7 mg kg-1, while plots under stress had a maximum soil P of 4.8 mg kg-1. While peach compost resulted in the lowest soil P levels, peach nano-black carbon yielded the highest soil P levels (21.6 mg kg-1). Comparing beneficial bacteria with PSB to Trichoderma (18.3 mg/kg-1), the former also shown an improvement in soil P (21.1 mg kg-1). Regarding P treatments, the application of 100 kg P per ha produced significantly higher soil P values (26.8 mg /kg-1), followed by 75 kg P per ha (18.3 mg /kg-1), and 50 kg P ha-1 produced the lowest soil P values (14.1 mg /kg-1). Comparing peach wastes and compost to peach nano-black carbon (13.7 g kg-1), SOC rose. In contrast to PSB (8.8 g kg-1), soil-treated Trichoderma was shown to have a greater SOC (11.1 g kg-1). Higher among the P levels.

Keywords: acidic stress, trichoderma, beneficial microbes, nano-black carbon, compost, peach residues, phosphorus, soybean

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Authors: Susana Aragoneses Garrido

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Every day, the roads are scenery of numerous accidents involving vehicles, producing thousands of deaths and serious injuries all over the world. Investigations have revealed that Human Factors (HF) are one of the main causes of road accidents in modern societies. Distracted driving (including external or internal aspects of the vehicle), which is considered as a human factor, is a serious and emergent risk to road safety. Consequently, a further analysis regarding this issue is essential due to its transcendence on today’s society. The objectives of this investigation are the detection and assessment of the HF in order to provide solutions (including a better vehicle design), which might mitigate road accidents. The methodology of the project is divided in different phases. First, a statistical analysis of public databases is provided between Spain and The UK. Second, data is classified in order to analyse the major causes involved in road accidents. Third, a simulation between different paths and vehicles is presented. The causes related to the HF are assessed by Failure Mode and Effects Analysis (FMEA). Fourth, different car models are evaluated using the Rapid Upper Body Assessment (RULA). Additionally, the JACK SIEMENS PLM tool is used with the intention of evaluating the Human Factor causes and providing the redesign of the vehicles. Finally, improvements in the car design are proposed with the intention of reducing the implication of HF in traffic accidents. The results from the statistical analysis, the simulations and the evaluations confirm that accidents are an important issue in today’s society, especially the accidents caused by HF resembling distractions. The results explore the reduction of external and internal HF through the global analysis risk of vehicle accidents. Moreover, the evaluation of the different car models using RULA method and the JACK SIEMENS PLM prove the importance of having a good regulation of the driver’s seat in order to avoid harmful postures and therefore distractions. For this reason, a car redesign is proposed for the driver to acquire the optimum position and consequently reducing the human factors in road accidents.

Keywords: analysis vehicles, asssesment, ergonomics, car redesign

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Authors: Vanessa Morgado, Ricardo Bettencourt da Silva, Carla Palma

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The environmental pollution by microplastics is well recognized. Microplastics were already detected in various matrices from distinct environmental compartments worldwide, some from remote areas. Various methodologies and techniques have been used to determine microplastic in such matrices, for instance, sediment samples from the ocean bottom. In order to determine microplastics in a sediment matrix, the sample is typically sieved through a 5 mm mesh, digested to remove the organic matter, and density separated to isolate microplastics from the denser part of the sediment. The physical analysis of microplastic consists of visual analysis under a stereomicroscope to determine particle size, colour, and shape. The chemical analysis is performed by an infrared spectrometer coupled to a microscope (micro-FTIR), allowing to the identification of the chemical composition of microplastic, i.e., the type of polymer. Creating legislation and policies to control and manage (micro)plastic pollution is essential to protect the environment, namely the coastal areas. The regulation is defined from the known relevance and trends of the pollution type. This work discusses the assessment of contamination trends of a 700 km² oceanic area affected by contamination heterogeneity, sampling representativeness, and the uncertainty of the analysis of collected samples. The methodology developed consists of objectively identifying meaningful variations of microplastic contamination by the Monte Carlo simulation of all uncertainty sources. This work allowed us to unequivocally conclude that the contamination level of the studied area did not vary significantly between two consecutive years (2018 and 2019) and that PET microplastics are the major type of polymer. The comparison of contamination levels was performed for a 99% confidence level. The developed know-how is crucial for the objective and binding determination of microplastic contamination in relevant environmental compartments.

Keywords: measurement uncertainty, micro-ATR-FTIR, microplastics, ocean contamination, sampling uncertainty

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Authors: Nakul V. Naphade, Sandra G. L. Persiani, Yew Wah Wong, Pramod S. Kamath, Avinash H. Anantharam, Hui Ling Aw, Yann Grynberg

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Achieving zero-energy targets in existing buildings is known to be a difficult task requiring important cuts in the building energy consumption, which in many cases clash with the functional necessities of the building wherever the on-site energy generation is unable to match the overall energy consumption. Between the building’s consumption optimization limit and the energy, target stretches a case-specific optimization grey zone, which requires tailored intervention and enhanced user’s commitment. In the view of the future adoption of more stringent energy-efficiency targets in the context of hot-humid tropical climates, this study aims to define the energy optimization grey zone by assessing the energy-efficiency limit in the state-of-the-art typical mid- and high-rise full AC office buildings, through the integration of currently available technologies. Energy models of two code-compliant generic office-building typologies were developed as a baseline, a 20-storey ‘high-rise’ and a 7-storey ‘mid-rise’. Design iterations carried out on the energy models with advanced market ready technologies in lighting, envelope, plug load management and ACMV systems and controls, lead to a representative energy model of the current maximum technical potential. The simulations showed that ZEB targets could be achieved in fully AC buildings under an average of seven floors only by compromising on energy-intense facilities (as full AC, unlimited power-supply, standard user behaviour, etc.). This paper argues that drastic changes must be made in tropical buildings to span the energy optimization grey zone and achieve zero energy. Fully air-conditioned areas must be rethought, while smart technologies must be integrated with an aggressive involvement and motivation of the users to synchronize with the new system’s energy savings goal.

Keywords: energy simulation, office building, tropical climate, zero energy buildings

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Authors: Mouna Baassi, Mohamed Moussaoui, Sanchaita Rajkhowa, Hatim Soufi, Said Belaaouad

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The objective of this paper is to address the challenging task of targeting Human Immunodeficiency Virus type 1 Reverse Transcriptase (HIV-1 RT) in the treatment of AIDS. Reverse Transcriptase inhibitors (RTIs) have limitations due to the development of Reverse Transcriptase mutations that lead to treatment resistance. In this study, a combination of statistical analysis and bioinformatics tools was adopted to develop a mathematical model that relates the structure of compounds to their inhibitory activities against HIV-1 Reverse Transcriptase. Our approach was based on a series of compounds recognized for their HIV-1 RT enzymatic inhibitory activities. These compounds were designed via software, with their descriptors computed using multiple tools. The most statistically promising model was chosen, and its domain of application was ascertained. Furthermore, compounds exhibiting comparable biological activity to existing drugs were identified as potential inhibitors of HIV-1 RT. The compounds underwent evaluation based on their chemical absorption, distribution, metabolism, excretion, toxicity properties, and adherence to Lipinski's rule. Molecular docking techniques were employed to examine the interaction between the Reverse Transcriptase (Wild Type and Mutant Type) and the ligands, including a known drug available in the market. Molecular dynamics simulations were also conducted to assess the stability of the RT-ligand complexes. Our results reveal some of the new compounds as promising candidates for effectively inhibiting HIV-1 Reverse Transcriptase, matching the potency of the established drug. This necessitates further experimental validation. This study, beyond its immediate results, provides a methodological foundation for future endeavors aiming to discover and design new inhibitors targeting HIV-1 Reverse Transcriptase.

Keywords: QSAR, ADMET properties, molecular docking, molecular dynamics simulation, reverse transcriptase inhibitors, HIV type 1

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Authors: Vera Wilden, Benno Hoffmeister, Markus Feldmann

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Glued laminated timber (glulam) is a preferred choice for long span girders, e.g., for gyms or storage halls. While the material provides sufficient strength to resist the bending moments, large spans lead to increased slenderness of such members and to a higher susceptibility to stability issues, in particular to lateral torsional buckling (LTB). Rules for the determination of the ultimate LTB resistance are provided by Eurocode 5. The verifications of the resistance may be performed using the so called equivalent member method or by means of theory 2nd order calculations (direct method), considering equivalent imperfections. Both methods have significant limitations concerning their applicability; the equivalent member method is limited to rather simple cases; the direct method is missing detailed provisions regarding imperfections and requirements for numerical modeling. In this paper, the results of a test series on slender glulam beams in three- and four-point bending are presented. The tests were performed in an innovative, newly developed testing rig, allowing for a very precise definition of loading and boundary conditions. The load was introduced by a hydraulic jack, which follows the lateral deformation of the beam by means of a servo-controller, coupled with the tested member and keeping the load direction vertically. The deformation-controlled tests allowed for the identification of the ultimate limit state (governed by elastic stability) and the corresponding deformations. Prior to the tests, the structural and geometrical imperfections were determined and used later in the numerical models. After the stability tests, the nearly undamaged members were tested again in pure bending until reaching the ultimate moment resistance of the cross-section. These results, accompanied by numerical studies, were compared to resistance values obtained using both methods according to Eurocode 5.

Keywords: experimental tests, glued laminated timber, lateral torsional buckling, numerical simulation

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Authors: Pooja Kumari, Anandkumar Tengli

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Aurora kinase enzyme, a protein on overexpression, leads to metastasis and is extremely important for women’s health in terms of prevention or treatment. While creating a targeted technique, the aim of the work is to design purine molecules that inhibit in aurora kinase enzyme and helps to suppress breast cancer. Purine molecules attached to an amino acid in DNA block protein synthesis or halt the replication and metastasis caused by the aurora kinase enzyme. Various protein related to the overexpression of aurora protein was docked with purine molecule using Biovia Drug Discovery, the perpetual software. Various parameters like X-ray crystallographic structure, presence of ligand, Ramachandran plot, resolution, etc., were taken into consideration for selecting the target protein. A higher negative binding scored molecule has been taken for simulation studies. According to the available research and computational analyses, purine compounds may be powerful enough to demonstrate a greater affinity for the aurora target. Despite being clinically effective now, purines were originally meant to fight breast cancer by inhibiting the aurora kinase enzyme. In in-silico studies, it is observed that purine compounds have a moderate to high potency compared to other molecules, and our research into the literature revealed that purine molecules have a lower risk of side effects. The research involves the design, synthesis, and identification of active purine molecules against breast cancer. Purines are structurally similar to the normal metabolites of adenine and guanine; hence interfere/compete with protein synthesis and suppress the abnormal proliferation of cells/tissues. As a result, purine target metastasis cells and stop the growth of kinase; purine derivatives bind with DNA and aurora protein which may stop the growth of protein or inhibits replication and stop metastasis of overexpressed aurora kinase enzyme.

Keywords: aurora kinases, in silico studies, medicinal chemistry, combination therapies, chronic cancer, clinical translation

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Authors: Mareike Dornhoefer, Madjid Fathi

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Water supply and water quality are key problems of mankind at the moment and - due to increasing population - in the future. Management disciplines like water, environment and quality management therefore need to closely interact, to establish a high level of water quality and to guarantee water supply in all parts of the world. Groundwater remediation is one aspect in this process. From a knowledge management perspective it is only possible to solve complex ecological or environmental problems if different factors, expert knowledge of various stakeholders and formal regulations regarding water, waste or chemical management are interconnected in form of a knowledge base. In general knowledge management focuses the processes of gathering and representing existing and new knowledge in a way, which allows for inference or deduction of knowledge for e.g. a situation where a problem solution or decision support are required. A knowledge base is no sole data repository, but a key element in a knowledge based system, thus providing or allowing for inference mechanisms to deduct further knowledge from existing facts. In consequence this knowledge provides decision support. The given paper introduces an environmental knowledge system in water management. The proposed environmental knowledge system is part of a research concept called Green Knowledge Management. It applies semantic technologies or concepts such as ontology or linked open data to interconnect different data and information sources about environmental aspects, in this case, water quality, as well as background material enriching an established knowledge base. Examples for the aforementioned ecological or environmental factors threatening water quality are among others industrial pollution (e.g. leakage of chemicals), environmental changes (e.g. rise in temperature) or floods, where all kinds of waste are merged and transferred into natural water environments. Water quality is usually determined with the help of measuring different indicators (e.g. chemical or biological), which are gathered with the help of laboratory testing, continuous monitoring equipment or other measuring processes. During all of these processes data are gathered and stored in different databases. Meanwhile the knowledge base needs to be established through interconnecting data of these different data sources and enriching its semantics. Experts may add their knowledge or experiences of previous incidents or influencing factors. In consequence querying or inference mechanisms are applied for the deduction of coherence between indicators, predictive developments or environmental threats. Relevant processes or steps of action may be modeled in form of a rule based approach. Overall the environmental knowledge system supports the interconnection of information and adding semantics to create environmental knowledge about water environment, supply chain as well as quality. The proposed concept itself is a holistic approach, which links to associated disciplines like environmental and quality management. Quality indicators and quality management steps need to be considered e.g. for the process and inference layers of the environmental knowledge system, thus integrating the aforementioned management disciplines in one water management application.

Keywords: water quality, environmental knowledge system, green knowledge management, semantic technologies, quality management

Procedia PDF Downloads 217

Authors: M. Baratieri, M. Beccali, S. Corradino, B. Di Pietra, C. La Grassa, F. Monteleone, G. Morosinotto, G. Puglisi

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The energy renovation of existing buildings represents an important opportunity to increase the decarbonization and the sustainability of urban environments. In this context, the work carried out has the objective of demonstrating the technical and economic feasibility of an energy renovate of a public building destined for offices located on the island of Lampedusa in the Mediterranean Sea. By applying the Italian transpositions of European Directives 2010/31/EU and 2009/28/EC, the building has been renovated from the current energy requirements of 111.7 kWh/m² to 16.4 kWh/m². The result achieved classifies the building as nZEB (nearly Zero Energy Building) according to the Italian national definition. The analysis was carried out using in parallel a quasi-stationary software, normally used in the professional field, and a dynamic simulation model often used in the academic world. The proposed interventions cover the components of the building’s envelope, the heating-cooling system and the supply of energy from renewable sources. In these latter points, the analysis has focused more on assessing two aspects that affect the supply of renewable energy. The first concerns the use of advanced logic control systems for air conditioning units in order to increase photovoltaic self-consumption. With these adjustments, a considerable increase in photovoltaic self-consumption and a decrease in the electricity exported to the Island's electricity grid have been obtained. The second point concerned the evaluation of the building's energy classification considering the real efficiency of the heating-cooling plant. Normally the energy plants have lower operational efficiency than the designed one due to multiple reasons; the decrease in the energy classification of the building for this factor has been quantified. This study represents an important example for the evaluation of the best interventions for the energy renovation of buildings in the Mediterranean Climate and a good description of the correct methodology to evaluate the resulting improvements.

Keywords: heat pumps, HVAC systems, nZEB renovation, renewable energy sources

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Authors: S. Ebadzadsahraei, H. Kazemian

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The main objective of this research was to measure particulate matter (PM₂.₅) and Volatile Organic Compound (VOCs) as two classes of air pollutants, at Prince George (PG) neighborhood in warm and cold seasons. To fulfill this objective, analytical protocols were developed for accurate sampling and measurement of the targeted air pollutants. PM₂.₅ samples were analyzed for their chemical composition (i.e., toxic trace elements) in order to assess their potential source of emission. The City of Prince George, widely known as the capital of northern British Columbia (BC), Canada, has been dealing with air pollution challenges for a long time. The city has several local industries including pulp mills, a refinery, and a couple of asphalt plants that are the primary contributors of industrial VOCs. In this research project, which is the first study of this kind in this region it measures physical and chemical properties of particulate air pollutants (PM₂.₅) at the city neighborhood. Furthermore, this study quantifies the percentage of VOCs at the city air samples. One of the outcomes of this project is updated data about PM₂.₅ and VOCs inventory in the selected neighborhoods. For examining PM₂.₅ chemical composition, an elemental analysis methodology was developed to measure major trace elements including but not limited to mercury and lead. The toxicity of inhaled particulates depends on both their physical and chemical properties; thus, an understanding of aerosol properties is essential for the evaluation of such hazards, and the treatment of such respiratory and other related diseases. Mixed cellulose ester (MCE) filters were selected for this research as a suitable filter for PM₂.₅ air sampling. Chemical analyses were conducted using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for elemental analysis. VOCs measurement of the air samples was performed using a Gas Chromatography-Flame Ionization Detector (GC-FID) and Gas Chromatography-Mass Spectrometry (GC-MS) allowing for quantitative measurement of VOC molecules in sub-ppb levels. In this study, sorbent tube (Anasorb CSC, Coconut Charcoal), 6 x 70-mm size, 2 sections, 50/100 mg sorbent, 20/40 mesh was used for VOCs air sampling followed by using solvent extraction and solid-phase micro extraction (SPME) techniques to prepare samples for measuring by a GC-MS/FID instrument. Air sampling for both PM₂.₅ and VOC were conducted in summer and winter seasons for comparison. Average concentrations of PM₂.₅ are very different between wildfire and daily samples. At wildfire time average of concentration is 83.0 μg/m³ and daily samples are 23.7 μg/m³. Also, higher concentrations of iron, nickel and manganese found at all samples and mercury element is found in some samples. It is able to stay too high doses negative effects.

Keywords: air pollutants, chemical analysis, particulate matter (PM₂.₅), volatile organic compound, VOCs

Procedia PDF Downloads 138

Authors: Éva Pintér, Péter Bagó, Nikolett Deutsch, Miklós Hetényi

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The process of digital transformation has a profound influence on all sectors of the worldwide economy and the business environment. The influence of blockchain technology can be observed in the digital economy and e-government, rendering it an essential element of a nation's growth strategy. The banking industry is experiencing significant expansion and development of financial technology firms. Utilizing developing technologies such as artificial intelligence (AI), machine learning (ML), and big data (BD), these entrants are offering more streamlined financial solutions, promptly addressing client demands, and presenting a challenge to incumbent institutions. The advantages of digital transformation are evident in the corporate realm, and firms that resist its adoption put their survival at risk. The advent of digital technologies has revolutionized the business environment, streamlining processes and creating opportunities for enhanced communication and collaboration. Thanks to the aid of digital technologies, businesses can now swiftly and effortlessly retrieve vast quantities of information, all the while accelerating the process of creating new and improved products and services. Big data analytics is generally recognized as a transformative force in business, considered the fourth paradigm of science, and seen as the next frontier for innovation, competition, and productivity. Big data, an emerging technology that is shaping the future of the banking sector, offers numerous advantages to banks. It enables them to effectively track consumer behavior and make informed decisions, thereby enhancing their operational efficiency. Banks may embrace big data technologies to promptly and efficiently identify fraud, as well as gain insights into client preferences, which can then be leveraged to create better-tailored products and services. Moreover, the utilization of big data technology empowers banks to develop more intelligent and streamlined models for accurately recognizing and focusing on the suitable clientele with pertinent offers. There is a scarcity of research on big data analytics in the banking industry, with the majority of existing studies only examining the advantages and prospects associated with big data. Although big data technologies are crucial, there is a dearth of empirical evidence about the role of big data analytics (BDA) capabilities in bank performance. This research addresses a gap in the existing literature by introducing a model that combines the resource-based view (RBV), the technical organization environment framework (TOE), and dynamic capability theory (DC). This study investigates the influence of Big Data Analytics (BDA) utilization on the performance of market and risk management. This is supported by a comparative examination of Hungarian mobile banking services.

Keywords: big data, digital transformation, dynamic capabilities, mobile banking

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Authors: Lokesh Soni, Sushanta Kumar Sethi, Gaurav Manik

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This work attempts to use molecular simulations to create equilibrated structures of a range of commercially used polymers. Generated equilibrated structures for polyvinyl acetate (isotactic), polyvinyl alcohol (atactic), polystyrene, polyethylene, polyamide 66, poly dimethyl siloxane, poly carbonate, poly ethylene oxide, poly amide 12, natural rubber, poly urethane, and polycarbonate (bisphenol-A) and poly ethylene terephthalate are employed to estimate the correct chain length that will correctly predict the chain parameters and properties. Further, the equilibrated structures are used to predict some properties like density, solubility parameter, cohesive energy density, surface energy, and Flory-Huggins interaction parameter. The simulated densities for polyvinyl acetate, polyvinyl alcohol, polystyrene, polypropylene, and polycarbonate are 1.15 g/cm3, 1.125 g/cm3, 1.02 g/cm3, 0.84 g/cm3 and 1.223 g/cm3 respectively are found to be in good agreement with the available literature estimates. However, the critical repeating units or the degree of polymerization after which the solubility parameter showed saturation were 15, 20, 25, 10 and 20 respectively. This also indicates that such properties that dictate the miscibility of two or more polymers in their blends are strongly dependent on the chosen polymer or its characteristic properties. An attempt has been made to correlate such properties with polymer properties like Kuhn length, free volume and the energy term which plays a vital role in predicting the mentioned properties. These results help us to screen and propose a useful library which may be used by the research groups in estimating the polymer properties using the molecular simulations of chains with the predicted critical lengths. The library shall help to obviate the need for researchers to spend efforts in finding the critical chain length needed for simulating the mentioned polymer properties.

Keywords: Kuhn length, Flory Huggins interaction parameter, cohesive energy density, free volume

Procedia PDF Downloads 188

Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Oriol Gomis Bellmunt, Vinicius Albernaz Lacerda Freitas

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The use of distributed and renewable sources in power systems has grown significantly, recently. One the most popular sources are wind farms which have grown massively. However, ¬wind farms are connected to the grid, this can cause problems such as reduced voltage stability, frequency fluctuations and reduced dynamic stability. Variable speed generators (asynchronous) are used due to the uncontrollability of wind speed specially Doubley Fed Induction Generators (DFIG). The most important disadvantage of DFIGs is its sensitivity to voltage drop. In the case of faults, a large volume of reactive power is induced therefore, use of FACTS devices such as SVC and STATCOM are suitable for improving system output performance. They increase the capacity of lines and also passes network fault conditions. In this paper, in addition to modeling the reactive power control system in a DFIG with converter, FACTS devices have been used in a DFIG wind turbine to improve the stability of the power system containing two synchronous sources. In the following paper, recent optimal control systems have been designed to minimize fluctuations caused by system disturbances, for FACTS devices employed. For this purpose, a suitable method for the selection of nine parameters for MPSH-phase-post-phase compensators of reactive power compensators is proposed. The design algorithm is formulated ¬¬as an optimization problem searching for optimal parameters in the controller. Simulation results show that the proposed controller Improves the stability of the network and the fluctuations are at desired speed.

Keywords: renewable energy sources, optimization wind power plant, stability, reactive power compensator, double-feed induction generator, optimal control, genetic algorithm

Procedia PDF Downloads 83

Authors: Weichao Yu, Kai Wen, Weihe Huang, Yang Yang, Jing Gong

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Metal-loss corrosion is a major threat to the safety and integrity of gas pipelines as it may result in the burst failures which can cause severe consequences that may include enormous economic losses as well as the personnel casualties. Therefore, it is important to ensure the corroding pipeline integrity and efficiency, considering the value of wall thickness, which plays an important role in the failure probability of corroding pipeline. Actually, the wall thickness is controlled during pipe purchase stage. For example, the API_SPEC_5L standard regulates the allowable tolerance of the wall thickness from the specified value during the pipe purchase. The allowable wall thickness tolerance will be used to determine the wall thickness distribution characteristic such as the mean value, standard deviation and distribution. Taking the uncertainties of the input variables in the burst limit-state function into account, the reliability approach rather than the deterministic approach will be used to evaluate the failure probability. Moreover, the cost of pipe purchase will be influenced by the allowable wall thickness tolerance. More strict control of the wall thickness usually corresponds to a higher pipe purchase cost. Therefore changing the wall thickness tolerance will vary both the probability of a burst failure and the cost of the pipe. This paper describes an approach to optimize the wall thickness tolerance considering both the safety and economy of corroding pipelines. In this paper, the corrosion burst limit-state function in Annex O of CSAZ662-7 is employed to evaluate the failure probability using the Monte Carlo simulation technique. By changing the allowable wall thickness tolerance, the parameters of the wall thickness distribution in the limit-state function will be changed. Using the reliability approach, the corresponding variations in the burst failure probability will be shown. On the other hand, changing the wall thickness tolerance will lead to a change in cost in pipe purchase. Using the variation of the failure probability and pipe cost caused by changing wall thickness tolerance specification, the optimal allowable tolerance can be obtained, and used to define pipe purchase specifications.

Keywords: allowable tolerance, corroding pipeline segment, operation cost, production cost, reliability approach

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

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Authors: Natasha Botha, Gary Corderely, Helen M. Inglis

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With the move to cleaner energy applications the transport industry is working towards on-board hydrogen, or compressed natural gas-fuelled vehicles. A popular method for storage is to use composite overwrapped pressure vessels (COPV) because of their high strength to weight ratios. The proper design of these COPVs are according to international standards; this study aims to provide a preliminary design for a 350 Bar Type IV COPV (i.e. a polymer liner with a composite overwrap). Netting analysis, a popular analytical approach, is used as a first step to generate an initial design concept for the composite winding. This design is further improved upon by following the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel standards, Section X: Fibre-reinforced composite pressure vessels. A design program based on these two approaches is developed using Python. A numerical model of a burst test simulation is developed based on the two approaches and compared. The results indicate that the netting analysis provides a good preliminary design, while the ASME-based design is more robust and accurate as it includes a better approximation of the material behaviour. Netting analysis is an easy method to follow when considering an initial concept design for the composite winding when not all the material characteristics are known. Once these characteristics have been fully defined with experimental testing, an ASME-based design should always be followed to ensure that all designs conform to international standards and practices. Future work entails more detailed numerical testing of the design for improvement, this will include the boss design. Once finalised prototype manufacturing and experimental testing will be conducted, and the results used to improve on the COPV design.

Keywords: composite overwrapped pressure vessel, netting analysis, design, American Society of Mechanical Engineers section x, fiber-reinforced, hydrogen storage

Procedia PDF Downloads 239

Authors: Iliyasu Musa Omoyine, Musa Sunday Abraham, Oladele Sunday Blessing, Iliya Ibrahim Abdullahi, Ibegbu Augustine Oseloka, Nuhu Nana-Hawau, Animoku Abdulrazaq Amoto, Yusuf Abdullateef Onoruoiza, Sambo Sohnap James, Akpulu Steven Peter, Ajayi Abayomi

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The neuroprotective role of inflammation from detrimental intrinsic and extrinsic factors has been reported. However, the overactivation of astrocytes and microglia due to lead toxicity produce excessive pro-inflammatory cytokines, mediating neurodegenerative diseases. The present study investigated the mitigatory effects of quercetin on neuroinflammation, correlating with memory function in lead-exposed rats. In this study, Wistar rats were administered orally with Quercetin (Q: 60 mg/kg) and Succimer as a standard drug (S: 10 mg/kg) for 21 days after lead exposure (Pb: 125 mg/kg) of 21 days or in combination with Pb, once daily for 42 days. Working and reference memory was assessed using an Eight-arm radial water maze (8-ARWM). The changes in brain lead level, the neuronal nitric oxide synthase (nNOS) activity, and the level of neuroinflammatory markers such as tumour necrosis factor-alpha (TNF-α) and Interleukin 1 Beta (IL-1β) were determined. Immunohistochemically, astrocyte expression was evaluated. The results showed that the brain level of lead was increased significantly in lead-exposed rats. The expression of astrocytes increased in the CA3 and CA1 regions of the hippocampus, and the levels of brain TNF-α and IL-1β increased in lead-exposed rats. Lead impaired reference and working memory by increasing reference memory errors and working memory incorrect errors in lead-exposed rats. However, quercetin treatment effectively improved memory and inhibited neuroinflammation by reducing astrocytes’ expression and the levels of TNF-α and IL-1β. The expression of astrocytes and the levels of TNF-α and IL-1β correlated with memory function. The possible explanation for quercetin’s anti-neuroinflammatory effect is that it modulates the activity of cellular proteins involved in the inflammatory response; inhibits the transcription factor of nuclear factor-kappa B (NF-κB), which regulates the expression of proinflammatory molecules; inhibits kinases required for the synthesis of Glial fibrillary acidic protein (GFAP) and modifies the phosphorylation of some proteins, which affect the structure and function of intermediate filament proteins; and, lastly, induces Cyclic-AMP Response Element Binding (CREB) activation and neurogenesis as a compensatory mechanism for memory deficits and neuronal cell death. In conclusion, the levels of neuroinflammatory markers negatively correlated with memory function. Thus, quercetin may be a promising therapy in neuroinflammation and memory dysfunction in populations prone to lead exposure.

Keywords: lead, quercetin, neuroinflammation, memory

Procedia PDF Downloads 42