Search results for: energy consumption prediction

Authors: Defne Uz

Abstract:

Horizontal Tail of helicopter is exposed to repeated oscillatory loading generated by aerodynamic and inertial loads, and bending moments depending on operating conditions and maneuvers of the helicopter. In order to ensure that maximum stress levels do not exceed certain fatigue limit of the material and to prevent damage, a numerical analysis approach can be utilized through the Finite Element Method. Therefore, in this paper, fatigue analysis of the Horizontal Tail model is studied numerically to predict high-cycle and low-cycle fatigue life related to defined loading. The analysis estimates the stress field at stress concentration regions such as around fastener holes where the maximum principal stresses are considered for each load case. Critical element identification of the main load carrying structural components of the model with rivet holes is performed as a post-process since critical regions with high-stress values are used as an input for fatigue life calculation. Once the maximum stress is obtained at the critical element and the related mean and alternating components, it is compared with the endurance limit by applying Soderberg approach. The constant life straight line provides the limit for several combinations of mean and alternating stresses. The life calculation based on S-N (Stress-Number of Cycles) curve is also applied with fully reversed loading to determine the number of cycles corresponds to the oscillatory stress with zero means. The results determine the appropriateness of the design of the model for its fatigue strength and the number of cycles that the model can withstand for the calculated stress. The effect of correctly determining the critical rivet holes is investigated by analyzing stresses at different structural parts in the model. In the case of low life prediction, alternative design solutions are developed, and flight hours can be estimated for the fatigue safe operation of the model.

Keywords: fatigue analysis, finite element method, helicopter horizontal tail, life prediction, stress concentration

Procedia PDF Downloads 133

Authors: Mohsen Saleh Asheghabadi, Alireza Jafari Jebeli

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Increasing population growth requires more sustainable development of energy. This non-contaminated energy has an inexhaustible energy source. One of the vital parameters in such structures is the choice of foundation type. Suction caissons are now used extensively worldwide for offshore wind turbine. Considering the presence of a number of offshore wind farms in earthquake areas, the study of the seismic behavior of suction caisson is necessary for better design. In this paper, the results obtained from three suction caisson models with different diameter (D) and skirt length (L) in saturated sand were compared with centrifuge test results. All models are analyzed using 3D finite element (FE) method taking account of elasto-plastic Mohr–Coulomb constitutive model for soil which is available in the ABAQUS library. The earthquake load applied to the base of models with a maximum acceleration of 0.65g. The results showed that numerical method is in relative good agreement with centrifuge results. The settlement and rotation of foundation decrease by increasing the skirt length and foundation diameter. The sand soil outside the caisson is prone to liquefaction due to its low confinement.

Keywords: liquefaction, suction caisson foundation, offshore wind turbine, numerical analysis, seismic behavior

Procedia PDF Downloads 110

Authors: Mahmoud Almasri, Xavier Marjou, Fanny Parzysz

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The demand for services provided by Unmanned Aerial Vehicles (UAVs) is increasing pervasively across several sectors including potential public safety, economic, and delivery services. As the number of applications using UAVs grows rapidly, more and more powerful, quality of service, and power efficient computing units are necessary. Recently, cellular technology draws more attention to connectivity that can ensure reliable and flexible communications services for UAVs. In cellular technology, flying with a high speed and altitude is subject to several key challenges, such as frequent handovers (HOs), high interference levels, connectivity coverage holes, etc. Additional HOs may lead to “ping-pong” between the UAVs and the serving cells resulting in a decrease of the quality of service and energy consumption. In order to optimize the number of HOs, we develop in this paper a Q-learning-based algorithm. While existing works focus on adjusting the number of HOs in a static network topology, we take into account the impact of cells deployment for three different simulation scenarios (Rural, Semi-rural and Urban areas). We also consider the impact of the decision distance, where the drone has the choice to make a switching decision on the number of HOs. Our results show that a Q-learning-based algorithm allows to significantly reduce the average number of HOs compared to a baseline case where the drone always selects the cell with the highest received signal. Moreover, we also propose which hyper-parameters have the largest impact on the number of HOs in the three tested environments, i.e. Rural, Semi-rural, or Urban.

Keywords: drones connectivity, reinforcement learning, handovers optimization, decision distance

Procedia PDF Downloads 90

Authors: Filiz Ersoz, Taner Ersoz, Tugrul Bayraktar

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Renewable energy is referred to as "clean energy" and common popular support for the use of renewable energy (RE) is to provide electricity with zero carbon dioxide emissions. This study provides useful insight into the European Union (EU) RE, especially, into electricity generation obtained from renewables, and their targets. The objective of this study is to identify groups of European countries, using multivariate statistical analysis and selected indicators. The hierarchical clustering method is used to decide the number of clusters for EU countries. The conducted statistical hierarchical cluster analysis is based on the Ward’s clustering method and squared Euclidean distances. Hierarchical cluster analysis identified eight distinct clusters of European countries. Then, non-hierarchical clustering (k-means) method was applied. Discriminant analysis was used to determine the validity of the results with data normalized by Z score transformation. To explore the relationship between the selected indicators, correlation coefficients were computed. The results of the study reveal the current situation of RE in European Union Member States.

Keywords: share of electricity generation, k-means clustering, discriminant, CO2 emission

Procedia PDF Downloads 403

Authors: Adeaga Ibiyemi Iyabo, Adeaga Oyetunde Adeoye

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Interestingly, mechanical drying methods has played a major role in the commercialization of agricultural and agricultural allied sectors. In the overall, drying enhances the favorable storability and preservation of agricultural produce which in turn promotes its producibility, marketability, salability, and profitability. Recent researches have shown that solar drying is easier, affordable, controllable, and of course, cleaner and purer than other means of drying methods. It is, therefore, needful to persistently appraise solar dryers with a view to improving on the existing advantages. In this paper, mathematical equations were formulated for solar dryer using mass conservation law, material balance law and least cost savings method. Computer codes were written in Visual Basic.Net. The developed computer software, which considered Ibadan, a strategic south-western geographical location in Nigeria, was used to investigate the relationship between variable orientation angle of flat plate collector on solar energy trapped, derived monthly heat load, available energy supplied by solar and fraction supplied by solar energy when 50000 Kg/Month of produce was dried over a year. At variable collector tilt angle of 10°.13°,15°,18°, 20°, the derived monthly heat load, available energy supplied by solar were 1211224.63MJ, 102121.34MJ, 0.111; 3299274.63MJ, 10121.34MJ, 0.132; 5999364.706MJ, 171222.859MJ, 0.286; 4211224.63MJ, 132121.34MJ, 0.121; 2200224.63MJ, 112121.34MJ, 0.104, respectively .These results showed that if optimum collector angle is not reached, those factors needed for efficient and cost reduction drying will be difficult to attain. Therefore, this software has revealed that off - optimum collector angle in commercial solar drying does not worth it, hence the importance of the software in decision making as to the optimum collector angle of orientation.

Keywords: energy, ibadan, heat - load, visual-basic.net

Procedia PDF Downloads 399

Authors: Doron Markel

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Water availability in most of the Middle East (especially in Jordan) is among the lowest in the world and has been even further exacerbated by the regional climatic change and the reduced rainfall. The Araba Valley in Israel is disconnected from the national water system. On the other hand, the Araba Valley, both in Israel and Jordan, is an excellent area for solar energy gaining. The Dead Sea (Israel and Jordan) is a hypersaline lake which its level declines at a rate of more than 1 m/y. The decline stems from the increasing use of all available freshwater resources that discharge into the Dead Sea and decreasing natural precipitation due to climate change in the Middle East. As an adaptation tool for this humanmade and Climate Change results, a comprehensive water-energy and environmental project were suggested: The Red Sea-Dead Sea Conveyance. It is planned to desalinate the Red Sea water, supply the desalinated water to both Israel and Jordan, and convey the desalination brine to the Dead Sea to stabilize its water level. Therefore, the World Bank had led a multi-discipline feasibility study between 2008 and 2013, that had mainly dealt with the mixing of seawater and Dead Sea Water. The possible consequences of such mixing were precipitation and possible suspension of secondary Gypsum, as well as blooming of Dunaliella red algae. Using a comprehensive hydrodynamic-geochemical model for the Dead Sea, it was predicted that while conveying up to 400 Million Cubic Meters per year of seawater or desalination brine to the Dead Sea, the latter would not be stratified as it was until 1979; hence Gypsum precipitation and algal blooms would be neglecting. Using another hydrodynamic-biological model for the Red Sea, it was predicted the Seawater pump from the Gulf of Eilat would not harm the ecological system of the gulf (including the sensitive coral reef), giving a pump depth of 120-160 m. Based on these studies, a pipeline conveyance was recommended to convey desalination brine to the Dead Sea with the use of a hydropower plant, utilizing the elevation difference of 400 m between the Red Sea and the Dead Sea. The complementary energy would come from solar panels coupled with innovative storage technology, needed to produce a continuous energy production for an appropriate function of the desalination plant. The paper will describe the proposed project as well as the feasibility study results. The possibility to utilize this water-energy-environmental project as a climate change adaptation strategy for both Israel and Jordan will also be discussed.

Keywords: Red Sea, Dead Sea, water supply, hydro-power, Gypsum, algae

Procedia PDF Downloads 100

Authors: Belaynesh Tsegay Beyene, Teklay Gebrecherkos, Atsebaha Gebrekidan Kahsay, Mahmud Abdulkader

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Background: Hepatitis B and C viruses are of important health and socioeconomic problem of the globe with remarkable diseases and deaths in Sub-Saharan African countries. The burden of hepatitis is unknown in the prison settings of Tigrai. Therefore, we aimed to describe the seroprevalence and associated factors of hepatitis B and C viruses among prisoners of Tigrai, Ethiopia. Methods: A cross-sectional study was carried out from February 2020 to May 2020 at the prison facilities of Tigrai. Demographics and associated factors were collected from 315 prisoners prospectively. Five milliliter of blood was collected and tested using rapid tests kits of HBsAg (Zhejiang orient Gene Biotech Co., Ltd., China) and HCV antibodies (Volkan Kozmetik Sanayi Ve Ticaret Ltd. STI, Turkey). Positive samples were confirmed using enzyme-linked immunosorbent assay (ELISA) (Beijing Wantai Biological Pharmacy Enterprise Co. Ltd). Data were analyzed using Statistical Package for Social Sciences (SPSS) version 20 and p < 0.05 was considered statistically significant. Results: The overall seroprevalence of HBV and HCV were 25 (7.9%) and 1(0.3%), respectively. The majority of hepatitis B viral infections were identified from the age groups of 18-25 years (10.7%) and unmarried prisoners (11.8%). Prisoners greater than 100 per cell [AOR =3.95, 95% CI= (1.15, 13.6, p =0.029)] and having history of alcohol consumption [AOR =3.01, 95% CI= (1.17, 7.74, p =0.022)] were significantly associated with HBV infections. Conclusions: The seroprevalence of HBV among prisoners was nearly high or borderline (7.9%) with a very low HCV prevalence (0.3%). HBV was most prevalent among young adults, large number of prisoners per cell and those who had history of alcohol consumption. This study recommends that there should be prison-focused intervention including regular health education by emphasis on the mode of transmission and introducing HBV screening policy for prisoners especially when they enter to the prison.

Keywords: seroprevalence, HBV, HCV, prisoners, Tigrai

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Authors: Mayowa Philips Ibitola, Abe Oluwaseun Banji, Olorunfemi Akinade-Solomon

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A total of 20 bottom sediment samples were collected from the Lekki Lagoon during the wet and dry season. The study was carried out to determine the textural characteristics, sediment distribution pattern and energy of transportation within the lagoon system. The sediment grain sizes and depth profiling was analyzed using dry sieving method and MATLAB algorithm for processing. The granulometric reveals fine grained sand both for the wet and dry season with an average mean value of 2.03 ϕ and -2.88 ϕ, respectively. Sediments were moderately sorted with an average inclusive standard deviation of 0.77 ϕ and -0.82 ϕ. Skewness varied from strongly coarse and near symmetrical 0.34- ϕ and 0.09 ϕ. The kurtosis average value was 0.87 ϕ and -1.4 ϕ (platykurtic and leptokurtic). Entirely, the bathymetry shows an average depth of 4.0 m. The deepest and shallowest area has a depth of 11.2 m and 0.5 m, respectively. High concentration of fine sand was observed at deep areas compared to the shallow areas during wet and dry season. Statistical parameter results show that the overall sediments are sorted, and deposited under low energy condition over a long distance. However, sediment distribution and sediment transport pattern of Lekki Lagoon is controlled by a low energy current and the down slope configuration of the bathymetry enhances the sorting and the deposition rate in the Lekki Lagoon.

Keywords: Lekki Lagoon, Marine sediment, bathymetry, grain size distribution

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Authors: Maryam Hamlehdar, Guillermo A. Narsilio

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To enhance the feasibility of utilising geothermal hot sedimentary aquifers (HSAs) for clean hydrogen production, one approach is the implementation of solar-integrated geothermal energy systems. This detailed modelling study conducts a thermo-economic assessment of an advanced Organic Rankine Cycle (ORC)-based hydrogen production system that uses low-temperature geothermal reservoirs, with a specific focus on hot sedimentary aquifers (HSAs) over a 30-year period. In the proposed hybrid system, solar-thermal energy is used to raise the water temperature extracted from the geothermal production well. This temperature increase leads to a higher steam output, powering the turbine and subsequently enhancing the electricity output for running the electrolyser. Thermodynamic modeling of a parabolic trough solar (PTS) collector is developed and integrated with modeling for a geothermal-based configuration. This configuration includes a closed regenerator cycle (CRC), proton exchange membrane (PEM) electrolyser, and thermoelectric generator (TEG). Following this, the study investigates the impact of solar energy use on the temperature enhancement of the geothermal reservoir. It assesses the resulting consequences on the lifecycle performance of the hydrogen production system in comparison with a standalone geothermal system. The results indicate that, with the appropriate solar collector area, a combined solar-geothermal hydrogen production system outperforms a standalone geothermal system in both cost and rate of production. These findings underscore a solar-assisted geothermal hybrid system holds the potential to generate lower-cost hydrogen with enhanced efficiency, thereby boosting the appeal of numerous low to medium-temperature geothermal sources for hydrogen production.

Keywords: clean hydrogen production, integrated solar-geothermal, low-temperature geothermal energy, numerical modelling

Procedia PDF Downloads 48

Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

Procedia PDF Downloads 378

Authors: Siamak Eskandari, Neda Ebadi

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After discovering and using Freon as refrigerant in refrigerators and air conditioners, researchers have been working hard to minimize massive environmental damage caused by this type of systems, including ozone depletion, heat production, and urban warming. However, there is a growing concern for global warming and climate change and its impacts on climates. Although gas air conditioners can provide comfort in short term, there are long-term consequences and effects, including global warming, polar ice melting, sea level rising, rising sea surface temperatures, reduction in seasonal precipitation, tropical storms, and drought. In this theoretical and practical study, Peltier electronic chip was used with no gas in the structure and operation. In fact, cooling and heating are based on bipolar electronics. With an innovative method, Peltier air conditioners provide cooling in warm seasons and heating in cold seasons in buildings. Such a system prevents ambient warming. The problem of air circulation between high buildings in large cities and draught will be considerably resolved through the use of the silent fan in the system. In addition, the system is designed and developed in accordance with international standards such as LEED and Energy Star.

Keywords: energy, Building cooling and heating, peltier, leed, energy star

Procedia PDF Downloads 180

Authors: Laggoun Chouki

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In this paper we present the design and mechanisms of the physics process and discuss the performances of continuous gas laser dynamics, based on molecules N2(v=1)→C02(001)(v=3). The main objectives of work in this area are, obtaining the high laser energies in short time durations needed for the feasibility studies the physical principles that can be used to make laser sources capable of delivering high average powers. We note that, in order to reach both objectives, one has to convert electrical or chemical energy into laser energy, using gaseous media. The process generating the wave excited, on the basis of the excited level vibration, Theoretical predictions are compared with experimental results. The feasibility and effectiveness of the proposed method is demonstrated by computer simulation.

Keywords: modelling, lasers, gas, numerical, nozzle

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Authors: N. Nandan A. M. Nagaraj, L. Sanjeev Kumar

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In the rapidly growing population, the requirement of electrical power is increasing day by day. In order to meet the needs, we need to generate the power using alternate method. In this paper, a presentable approach is developed by analysis and can be implemented by utilizing heat energy, which is generated in numerous ways in some of the rural areas in India. The thermoelectric generator unit will be developed by combing with control circuits and converts, which is used to light the LED lamps. The temperature difference which is available in the kitchens, especially the exhaust pipes/chimneys of wooden fire stoves, where more heat is dissipated into the atmosphere, can be utilized for electrical power generation. Hence, the temperature rise of surroundings atmosphere can be reduced.

Keywords: thermo electric generator, LED, converts, temperature

Procedia PDF Downloads 134

Authors: J. O. Bodunrin, S. J. Moloi

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This study reports on the x-ray crystallography (XRD) structure of cadmium-implanted p-type silicon, the current-voltage (I-V) and capacitance-voltage (C-V) characteristics of unimplanted and cadmium-implanted silicon-based diodes. Cadmium was implanted at the energy of 160 KeV to the fluence of 10¹⁵ ion/cm². The results obtained indicate that the diodes were well fabricated, and the introduction of cadmium results in a change in behavior of the diodes from normal exponential to ohmic I-V behavior. The C-V measurements, on the other hand, show that the measured capacitance increased after cadmium doping due to the injected charge carriers. The doping density of the p-Si material and the device's Schottky barrier height was extracted, and the doping density of the undoped p-Si material increased after cadmium doping while the Schottky barrier height reduced. In general, the results obtained here are similar to those obtained on the diodes fabricated on radiation-hard material, indicating that cadmium is a promising metal dopant to improve the radiation hardness of silicon. Thus, this study would assist in adding possible options to improve the radiation hardness of silicon to be used in high energy physics experiments.

Keywords: cadmium, capacitance-voltage, current-voltage, high energy physics experiment, x-ray crystallography, XRD

Procedia PDF Downloads 121

Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 152

Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 139

Authors: Anurag Bhambhani, Jan Peter Van Der Hoek, Zoran Kapelan

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The food system depends on the availability of Phosphorus (P) and Nitrogen (N). Growing population, depleting Phosphorus reserves and energy-intensive industrial nitrogen fixation are threats to their future availability. Recovering P and N from domestic sewage water offers a solution. Recovered P and N can be applied to agricultural land, replacing virgin P and N. Thus, recovery from sewage water offers a solution befitting a circular economy. To ensure minimum waste and maximum resource efficiency a circularity assessment method is crucial to optimize nutrient flows and minimize losses. Material Circularity Indicator (MCI) is a useful method to quantify the circularity of materials. It was developed for materials that remain within the market and recently extended to include biotic materials that may be composted or used for energy recovery after end-of-use. However, MCI has not been used in the context of nutrient recovery. Besides, MCI is time-static, i.e., it cannot account for dynamic systems such as the terrestrial nutrient cycles. Nutrient application to agricultural land is a highly dynamic process wherein flows and stocks change with time. The rate of recycling of nutrients in nature can depend on numerous factors such as prevailing soil conditions, local hydrology, the presence of animals, etc. Therefore, a dynamic model of nutrient flows with indicators is needed for the circularity assessment. A simple substance flow model of P and N will be developed with the help of flow equations and transfer coefficients that incorporate the nutrient recovery step along with the agricultural application, the volatilization and leaching processes, plant uptake and subsequent animal and human uptake. The model is then used for calculating the proportions of linear and restorative flows (coming from reused/recycled sources). The model will simulate the adsorption process based on the quantity of adsorbent and nutrient concentration in the water. Thereafter, the application of the adsorbed nutrients to agricultural land will be simulated based on adsorbate release kinetics, local soil conditions, hydrology, vegetation, etc. Based on the model, the restorative nutrient flow (returning to the sewage plant following human consumption) will be calculated. The developed methodology will be applied to a case study of resource recovery from wastewater. In the aforementioned case study located in Italy, biochar or zeolite is to be used for recovery of P and N from domestic sewage through adsorption and thereafter, used as a slow-release fertilizer in agriculture. Using this model, information regarding the efficiency of nutrient recovery and application can be generated. This can help to optimize the recovery process and application of the nutrients. Consequently, this will help to optimize nutrient recovery and application and reduce the dependence of the food system on the virgin extraction of P and N.

Keywords: circular economy, dynamic substance flow, nutrient cycles, resource recovery from water

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Authors: Abdulmalek Ahmed

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Formation pressure is the main function that affects drilling operation economically and efficiently. Knowing the pore pressure and the parameters that affect it will help to reduce the cost of drilling process. Many empirical models reported in the literature were used to calculate the formation pressure based on different parameters. Some of these models used only drilling parameters to estimate pore pressure. Other models predicted the formation pressure based on log data. All of these models required different trends such as normal or abnormal to predict the pore pressure. Few researchers applied artificial intelligence (AI) techniques to predict the formation pressure by only one method or a maximum of two methods of AI. The objective of this research is to predict the pore pressure based on both drilling parameters and log data namely; weight on bit, rotary speed, rate of penetration, mud weight, bulk density, porosity and delta sonic time. A real field data is used to predict the formation pressure using five different artificial intelligence (AI) methods such as; artificial neural networks (ANN), radial basis function (RBF), fuzzy logic (FL), support vector machine (SVM) and functional networks (FN). All AI tools were compared with different empirical models. AI methods estimated the formation pressure by a high accuracy (high correlation coefficient and low average absolute percentage error) and outperformed all previous. The advantage of the new technique is its simplicity, which represented from its estimation of pore pressure without the need of different trends as compared to other models which require a two different trend (normal or abnormal pressure). Moreover, by comparing the AI tools with each other, the results indicate that SVM has the advantage of pore pressure prediction by its fast processing speed and high performance (a high correlation coefficient of 0.997 and a low average absolute percentage error of 0.14%). In the end, a new empirical correlation for formation pressure was developed using ANN method that can estimate pore pressure with a high precision (correlation coefficient of 0.998 and average absolute percentage error of 0.17%).

Keywords: Artificial Intelligence (AI), Formation pressure, Artificial Neural Networks (ANN), Fuzzy Logic (FL), Support Vector Machine (SVM), Functional Networks (FN), Radial Basis Function (RBF)

Procedia PDF Downloads 140

Authors: Adedayo Adeleke, Dineo Pule

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The ongoing load-shedding in most parts of South Africa, combined with climate change causing severe drought conditions in Cape Town, has left electricity consumers seeking alternative sources of power and water. Solar energy, which is abundant in most parts of South Africa and is regarded as a clean and renewable source of energy, allows for the generation of electricity via solar photovoltaic systems. Rainwater harvesting is the collection and storage of rainwater from building rooftops, allowing people without access to water to collect it. The lack of dependable energy and water source must be addressed by shifting to solar energy via solar photovoltaic systems and rainwater harvesting. Before this can be done, the potential of building rooftops must be assessed to determine whether solar energy and rainwater harvesting will be able to meet or significantly contribute to Atlantis industrial areas' electricity and water demands. This research project presents methods and approaches for automatically extracting building rooftops in Atlantis industrial areas and evaluating their potential for solar photovoltaics and rainwater harvesting systems using Light Detection and Ranging (LiDAR) data and aerial imagery. The four objectives were to: (1) identify an optimal method of extracting building rooftops from aerial imagery and LiDAR data; (2) identify a suitable solar radiation model that can provide a global solar radiation estimate of the study area; (3) estimate solar photovoltaic potential overbuilding rooftop; and (4) estimate the amount of rainwater that can be harvested from the building rooftop in the study area. Mapflow, a plugin found in Quantum Geographic Information System(GIS) was used to automatically extract building rooftops using aerial imagery. The mean annual rainfall in Cape Town was obtained from a 29-year rainfall period (1991- 2020) and used to calculate the amount of rainwater that can be harvested from building rooftops. The potential for rainwater harvesting and solar photovoltaic systems was assessed, and it can be concluded that there is potential for these systems but only to supplement the existing resource supply and offer relief in times of drought and load-shedding.

Keywords: roof potential, rainwater harvesting, urban plan, roof extraction

Procedia PDF Downloads 105

Authors: Javed Mohammed

Abstract:

As urbanization process has been and will be happening in an unprecedented scale worldwide, strong requirements from academic research and practical fields for smart management and intelligent planning of cities are pressing to handle increasing demands of infrastructure and potential risks of inhabitants agglomeration in disaster management. Geo-spatial data and Geographic Information System (GIS) are essential components for building smart cities in a basic way that maps the physical world into virtual environment as a referencing framework. On higher level, GIS has been becoming very important in smart cities on different sectors. In the digital city era, digital maps and geospatial databases have long been integrated in workflows in land management, urban planning and transportation in government. People have anticipated GIS to be more powerful not only as an archival and data management tool but also as spatial models for supporting decision-making in intelligent cities. The purpose of this project is to offer observations and analysis based on a detailed discussion of Geographic Information Systems( GIS) driven Framework towards the development of Smart and Sustainable Cities through high penetration of Renewable Energy Technologies.

Keywords: digital maps, geo-spatial, geographic information system, smart cities, renewable energy, urban planning

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Authors: Subhojyoti Chatterjee, Peter J. Mahon, Feng Wang

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Resveratrol (RvL), a phenolic compound, is a key ingredient in wine and tomatoes that has been studied over the years because of its important bioactivities such as anti-oxidant, anti-aging and antimicrobial properties. Out of the two isomeric forms of resveratrol i.e. trans and cis, the health benefit is primarily associated with the trans form. Thus, studying the structural properties of the isomers will not only provide an insight into understanding the RvL isomers, but will also help in designing parameters for differentiation in order to achieve 99.9% purity of trans-RvL. In the present study, density function theory (DFT) study is conducted, using the B3LYP/6-311++G** model to explore the through bond and through space intramolecular interactions. Properties such as vibrational spectroscopy (IR and Raman), nuclear magnetic resonance (NMR) spectra, excess orbital energy spectrum (EOES), energy based decomposition analyses (EDA) and Fukui function are calculated. It is discovered that the structure of trans-RvL, although it is C1 non-planar, the backbone non-H atoms are nearly in the same plane; whereas the cis-RvL consists of two major planes of R1 and R2 that are not in the same plane. The absence of planarity gives rise to a H-bond of 2.67Å in cis-RvL. Rotation of the C(5)-C(8) single bond in trans-RvL produces higher energy barriers since it may break the (planar) entire conjugated structure; while such rotation in cis-RvL produces multiple minima and maxima depending on the positions of the rings. The calculated FT-IR spectrum shows very different spectral features for trans and cis-RvL in the region 900 – 1500 cm-1, where the spectral peaks at 1138-1158 cm-1 are split in cis-RvL compared to a single peak at 1165 cm-1 in trans-RvL. In the Raman spectra, there is significant enhancement of cis-RvL in the region above 3000cm-1. Further, the carbon chemical environment (13C NMR) of the RvL molecule exhibit a larger chemical shift for cis-RvL compared to trans-RvL (Δδ = 8.18 ppm) for the carbon atom C(11), indicating that the chemical environment of the C group in cis-RvL is more diverse than its other isomer. The energy gap between highest occupied molecular orbital (HOMO) and the lowest occupied molecular orbital (LUMO) is 3.95 eV for trans and 4.35 eV for cis-RvL. A more detailed inspection using the recently developed EOES revealed that most of the large energy differences i.e. Δεcis-trans > ±0.30 eV, in their orbitals are contributed from the outer valence shell. They are MO60 (HOMO), MO52-55 and MO46. The active sites that has been captured by Fukui function (f + > 0.08) are associated with the stilbene C=C bond of RvL and cis-RvL is more active at these sites than in trans-RvL, as cis orientation breaks the large conjugation of trans-RvL so that the hydroxyl oxygen’s are more active in cis-RvL. Finally, EDA highlights the interaction energy (ΔEInt) of the phenolic compound, where trans is preferred over the cis-RvL (ΔΔEi = -4.35 kcal.mol-1) isomer. Thus, these quantum mechanics results could help in unwinding the diversified beneficial activities associated with resveratrol.

Keywords: resveratrol, FT-IR, Raman, NMR, excess orbital energy spectrum, energy decomposition analysis, Fukui function

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Authors: Ashish Soni, Suman Kalyan Pal

Abstract:

Transition metal dichalcogenides (TMDCs) are an emerging paradigm for the generation of advanced materials which are capable of utilizing in future device applications. In recent years TMDCs have attracted researchers for their unique band structure in monolayers. Large-area monolayers could become the most appropriate candidate for flexible and thin optoelectronic devices. For this purpose, it is crucial to understand the generation and transport of charge carriers in low dimensions. A deep understanding of photo-generated hot charges and trapped charges is essential to improve the performance of optoelectronic devices. Carrier trapping by the defect states that are introduced during the growth process of the monolayer could influence the dynamical behaviour of charge carriers. Herein, we investigated some aspects of the ultrafast evolution of the initially generated hot carriers and trapped charges in large-area monolayer WS₂ by measuring transient absorption at energies above and below the band gap energy. Our excitation density and energy-dependent measurements reveal the trapping of the initially generated charge carrier. Our results could be beneficial for the development of TMDC-based optoelectronic devices.

Keywords: transient absorption, optoelectronics, 2D materials, TMDCs, exciton

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Authors: Nadia Sid, Alan Taylor, Marion Bourebrab

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The construction sector is on the critical path to decarbonise the European economy by 2050. In order to achieve this objective it must enable reducing its CO2 emission by 90% and its energy consumption by as much as 50%. For this reason, a new class of low environmental impact construction materials named “eco-material” are becoming increasingly important in the struggle against climate change. A European funded collaborative project ISOBIO coordinated by TWI is aimed at taking a radical approach to the use of bio-based aggregates to create novel construction materials that are usable in high volume in using traditional methods, as well as developing markets such as exterior insulation of existing house stocks. The approach taken for this project is to use finely chopped material protected from bio-degradation through the use of functionalized silica nanoparticles. TWI is exploring the development of novel inorganic-organic hybrid nano-materials, to be applied as a surface treatment onto bio-based aggregates. These nanoparticles are synthesized by sol-gel processing and then functionalised with silanes to impart multifunctionality e.g. hydrophobicity, fire resistance and chemical bonding between the silica nanoparticles and the bio-based aggregates. This talk will illustrate the approach taken by TWI to design the functionalized silica nanoparticles by using a material-by-design approach. The formulation and synthesize process will be presented together with the challenges addressed by those hybrid nano-materials. The results obtained with regards to the water repellence and fire resistance will be displayed together with preliminary public results of the ISOBIO project. (This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 641927).

Keywords: bio-sourced material, composite material, durable insulation panel, water repellent material

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Authors: A. Newman-Tancredi, R. Depoortère, P. Gruca, E. Litwa, M. Lason, M. Papp

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The N-methyl-D-aspartic acid (NMDA) receptor antagonist, ketamine, can elicit rapid-acting antidepressant (RAAD) effects in treatment-resistant patients, but it requires parenteral co-administration with a classical antidepressant under medical supervision. In addition, ketamine can also produce serious side effects that limit its long-term use, and there is much interest in identifying RAADs based on ketamine’s mechanism of action but with safer profiles. Ketamine elicits GABAergic interneuron inhibition, glutamatergic neuron stimulation, and, notably, activation of serotonin 5-HT1A receptors in the prefrontal cortex (PFC). Direct activation of the latter receptor subpopulation with selective ‘biased agonists’ may therefore be a promising strategy to identify novel RAADs and, consistent with this hypothesis, the prototypical cortical biased agonist, NLX-101, exhibited robust RAAD-like activity in the chronic mild stress model of depression (CMS). The present study compared the effects of a novel, selective 5-HT1A receptor-biased agonist, NLX-204, with those of ketamine and NLX-101. Materials and methods: CMS procedure was conducted on Wistar rats; drugs were administered either intraperitoneally (i.p.) or by bilateral intracortical microinjection. Ketamine: 10 mg/kg i.p. or 10 µg/side in PFC; NLX-204 and NLX-101: 0.08 and 0.16 mg/kg i.p. or 16 µg/side in PFC. In addition, interaction studies were carried out with systemic NLX-204 or NLX-101 (each at 0.16 mg/kg i.p.) in combination with intracortical WAY-100635 (selective 5-HT1A receptor antagonist; 2 µg/side) or muscimol (GABA-A receptor agonist, 12.5 ng/side). Anhedonia was assessed by CMS-induced decrease in sucrose solution consumption; anxiety-like behavior was assessed using the Elevated Plus Maze (EPM), and cognitive impairment was assessed by the Novel Object Recognition (NOR) test. Results: A single administration of NLX-204 was sufficient to reverse the CMS-induced deficit in sucrose consumption, similarly to ketamine and NLX-101. NLX-204 also reduced CMS-induced anxiety in the EPM and abolished CMS-induced NOR deficits. These effects were maintained (EPM and NOR) or enhanced (sucrose consumption) over a subsequent 2-week period of treatment. The anti-anhedonic response of the drugs was also maintained for several weeks Following treatment discontinuation, suggesting that they had sustained effects on neuronal networks. A single PFC administration of NLX-204 reversed deficient sucrose consumption, similarly to ketamine and NLX-101. Moreover, the anti-anhedonic activities of systemic NLX-204 and NLX 101 were abolished by coadministration with intracortical WAY-100635 or muscimol. Conclusions: (i) The antidepressant-like activity of NLX-204 in the rat CMS model was as rapid as that of ketamine or NLX-101, supporting targeting cortical 5-HT1A receptors with selective, biased agonists to achieve RAAD effects. (ii)The anti-anhedonic activity of systemic NLX-204 was mimicked by local administration of the compound in the PFC, confirming the involvement of cortical circuits in its RAAD-like effects. (iii) Notably, the effects of systemic NLX-204 and NLX-101 were abolished by PFC administration of muscimol, indicating that they act by (indirectly) eliciting a reduction in cortical GABAergic neurotransmission. This is consistent with ketamine’s mechanism of action and suggests that there are converging NMDA and 5-HT1A receptor signaling cascades in PFC underlying the RAAD-like activities of ketamine and NLX-204. Acknowledgements: The study was financially supported by NCN grant no. 2019/35/B/NZ7/00787.

Keywords: depression, ketamine, serotonin, 5-HT1A receptor, chronic mild stress

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Authors: Thomas Seemann, Melanie Seemann

Abstract:

The work environment has changed considerably due to the COVID pandemic. A growing body of empirical research shows that employees feel increasingly stressed and anxious. They consider themselves more detached from the organization they work for than previously. Organizations need to readjust their leadership practices to cope with this situation and rebuild work motivation and resilience. We propose a leadership tool that focuses on two key dimensions, which we call the "task channel" and the "energy channel." Managing the task channel comprises balancing the challenge [C] of a task and the corresponding skill set [S] of the individual performing the task. Recent research findings shed light on how to balance these two factors and create optimal work conditions in the workplace. Managing the energy channel comprise balancing the workload [WL] of an employee and his/her capacity to work [CW]. This ensures that the mid-term and long-term effectiveness of employees is maintained and energy depletion, fatigue, and burn-out are prevented. Organizations can actively apply strategies to leverage wellsprings and effectively reenergize their workforce. Thinking through and acting upon these factors will provide leaders with the insights they need to maximize their people's performance and, at the same time, establish a more mindful workplace.

Keywords: resilience, motivation, employee engagement, leadership

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Authors: Karina Reiter, Stefan Dullinger, Christoph Plutzar, Dietmar Moser

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Due to population growth and changing patterns of production and consumption, the demand for natural resources and, as a result, the pressure on Earth’s ecosystems are growing. Biodiversity mapping can be a useful tool for assessing species endangerment or detecting hotspots of extinction risks. This paper explores the benefits of using the change in trophic energy flows as a consequence of the human alteration of the biosphere in biodiversity mapping. To this end, multiple linear regression models were developed to explain species richness in areas where there is no human influence (i.e. wilderness) for three taxonomic groups (birds, mammals, amphibians). The models were then applied to predict (I) potential global species richness using potential natural vegetation (NPPpot) and (II) global ‘actual’ species richness after biomass appropriation using NPP remaining in ecosystems after harvest (NPPeco). By calculating the difference between predicted potential and predicted actual species numbers, maps of estimated species richness loss were generated. Results show that biomass appropriation for human use can indeed be linked to biodiversity loss. Areas for which the models predicted high species loss coincide with areas where species endangerment and extinctions are recorded to be particularly high by the International Union for Conservation of Nature and Natural Resources (IUCN). Furthermore, the analysis revealed that while the species distribution maps of the IUCN Red List of Threatened Species used for this research can determine hotspots of biodiversity loss in large parts of the world, the classification system for threatened and extinct species needs to be revised to better reflect local risks of extinction.

Keywords: biodiversity loss, biomass harvest, human appropriation of net primary production, species richness

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Authors: Adel A. Ghoneim

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Air conditioning devices are substantially utilized in the summer months, as a result maximum loads in Kuwait take place in these intervals. Peak energy consumption are usually more expensive to satisfy compared to other standard power sources. The primary objective of the current work is to enhance the performance of high concentrated photovoltaic (HCPV) systems in an attempt to minimize peak power usage in Kuwait using HCPV modules. High concentrated PV multi-junction solar cells provide a promising method towards accomplishing lowest pricing per kilowatt-hour. Nevertheless, these cells have various features that should be resolved to be feasible for extensive power production. A single diode equivalent circuit model is formulated to analyze multi-junction solar cells efficiency in Kuwait weather circumstances taking into account the effects of both the temperature and the concentration ratio. The diode shunt resistance that is commonly ignored in the established models is considered in the present numerical model. The current model results are successfully validated versus measurements from published data to within 1.8% accuracy. Present calculations reveal that the single diode model considering the shunt resistance provides accurate and dependable results. The electrical efficiency (η) is observed to increase with concentration to a specific concentration level after which it reduces. Implementing grid systems is noticed to increase with concentration to a certain concentration degree after which it decreases. Employing grid connected HCPV systems results in significant peak load reduction.

Keywords: grid connected, high concentrated photovoltaic systems, peak load, solar cells

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Authors: Mohammed Elsayed Lotfy Elsayed Abouzeid, Tomonobu Senjyu

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A novel multi-objective park and ride control approach is presented in this research. Park and ride will encourage the owners of the vehicles to leave their cars in the nearest points (on the edges of the crowded cities) and use public transportation facilities (train, bus, metro, or mon-rail) to reach their work inside the crowded city. The proposed control scheme is used to design electric vehicle charging stations (EVCS) to charge 1000 electric vehicles (EV) during their owners' work time. Cairo, Egypt is used as a case study. Photovoltaic (PV) and battery energy storage system (BESS) are used to meet the EVCS demand. Two multi-objective optimization techniques (MOGA and epsilon-MOGA) are utilized to get the optimal sizes of PV and BESS so as to meet the load demand and minimize the total life cycle cost. Detailed analysis and comparison are held to investigate the performance of the proposed control scheme using MATLAB.

Keywords: Battery Energy Storage System, Electric Vehicle, Park and Ride, Photovoltaic, Multi-objective

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Authors: Krunal Thakar

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Wire ropes combine high tensile strength and flexibility as compared to other general steel products. They are used in various application areas such as cranes, mining, elevators, bridges, cable cars, etc. The earliest reported use of wire ropes was for mining hoist application in 1830s. Over the period, there have been substantial advancement in the design of wire ropes for various application areas. Under operational conditions, wire ropes are subjected to varying tensile loads and bending loads resulting in material wear and eventual structural failure due to fretting fatigue. The conventional inspection methods to determine wire failure is only limited to outer wires of rope. However, till date, there is no effective mathematical model to examine the inter wire contact forces and wear characteristics. The scope of this paper is to present a computational simulation technique to evaluate inter wire contact forces and wear, which are in many cases responsible for rope failure. Two different type of ropes, IWRC-6xFi(29) and U3xSeS(48) were taken for structural strength evaluation and wear prediction. Both ropes have a double helix twisted wire profile as per JIS standards and are mainly used in cranes. CAD models of both ropes were developed in general purpose design software using in house developed formulation to generate double helix profile. Numerical simulation was done under two different load cases (a) Axial Tension and (b) Bending over Sheave. Different parameters such as stresses, contact forces, wear depth, load-elongation, etc., were investigated and compared between both ropes. Numerical simulation method facilitates the detailed investigation of inter wire contact and wear characteristics. In addition, various selection parameters like sheave diameter, rope diameter, helix angle, swaging, maximum load carrying capacity, etc., can be quickly analyzed.

Keywords: steel wire ropes, numerical simulation, material wear, structural strength, axial tension, bending over sheave

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Authors: Atiya Mahmood, Mubasharah Hanif, Ghazala Butt, Mehwish Zahoor Ahmed

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Acne vulgaris affects millions of adults.Despite extensive research, its food related etiology remains elusive. Objective:To assess the correlation between dietary intake and acne through a case-control survey of 300,15-25 year old respondents living in Pakistan. 50 acne patients and 150 age-and ethnicity-matched controls completed a questionnaire.Cases and controls were separated using SPSS-22 and univariate analysis was performed using the chi-square test. p value < 0.05 was considered statistically significant. We used adjusted odds ratios to assess the strength of associations with 95% confidence intervals. Most of the respondents were females(91.3%).Most(48.7%)acne patients were 20-25 yearsold.Acne severity was mild in 50%,moderate in 34%,severe in14%and very severe in 2%.Frequent low-fat foods(p<0.001)(OR=3.22),fat intake(p=0.03)(OR = 1.629),sweet snacks i.e. biscuits and candies etc. (p=0.013) (OR=1.9254), soft drinks(p= 0.045)(OR= 1.9091),butter(p<0.001) (OR= 1.8185),dairy products(p=0.043)(OR=0.624),salty foods(p= 0.011)(OR=1.961),chocolate (p=0.028)(OR=1.669), were associated with increased acne risk.No association was found with consumption of fried foods, desserts, fruit juices, raw fruit, fast food, vegetables, cheese, soy products, salt, and corn. Increased butter and chocolate consumption were linked to more severe forms of acne(p=0.049 and p=0.005 respectively).Most respondents (n=218) considered themselves to have healthy eating habits, indicating they were not educated about the nutritional aspects of acne treatment.Certain food item intake was significantly higher in acne patients to give an association between the two. Further studies must be conducted to develop a causative relationship. Nutrition aawareness is critical to reduce acne.

Keywords: correlation between dietary components and acne, dietary components, acne, nutrition

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