Search results for: energy consumption prediction

Authors: Muhammet Baldan, Emel Timuçin

Abstract:

Molecular solubility prediction plays a crucial role in various fields, such as drug discovery, environmental science, and material science. In this study, we compare the performance of five machine learning algorithms—linear regression, support vector machines (SVM), random forests, gradient boosting machines (GBM), and neural networks—for predicting molecular solubility using the AqSolDB dataset. The dataset consists of 9981 data points with their corresponding solubility values. MACCS keys (166 bits), RDKit properties (20 properties), and structural properties(3) features are extracted for every smile representation in the dataset. A total of 189 features were used for training and testing for every molecule. Each algorithm is trained on a subset of the dataset and evaluated using metrics accuracy scores. Additionally, computational time for training and testing is recorded to assess the efficiency of each algorithm. Our results demonstrate that random forest model outperformed other algorithms in terms of predictive accuracy, achieving an 0.93 accuracy score. Gradient boosting machines and neural networks also exhibit strong performance, closely followed by support vector machines. Linear regression, while simpler in nature, demonstrates competitive performance but with slightly higher errors compared to ensemble methods. Overall, this study provides valuable insights into the performance of machine learning algorithms for molecular solubility prediction, highlighting the importance of algorithm selection in achieving accurate and efficient predictions in practical applications.

Keywords: random forest, machine learning, comparison, feature extraction

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Authors: Amela Ajanovic, Reinhard Haas

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Electric vehicles (EVs) are considered as an important means to cope with current environmental problems in transport. However, their high capital costs and limited driving ranges state major barriers to a broader market penetration. The core objective of this paper is to investigate the future market prospects of various types of EVs from an economic and ecological point of view. Our method of approach is based on the calculation of total cost of ownership of EVs in comparison to conventional cars and a life-cycle approach to assess the environmental benignity. The most crucial parameters in this context are km driven per year, depreciation time of the car and interest rate. The analysis of future prospects it is based on technological learning regarding investment costs of batteries. The major results are the major disadvantages of battery electric vehicles (BEVs) are the high capital costs, mainly due to the battery, and a low driving range in comparison to conventional vehicles. These problems could be reduced with plug-in hybrids (PHEV) and range extenders (REXs). However, these technologies have lower CO₂ emissions in the whole energy supply chain than conventional vehicles, but unlike BEV they are not zero-emission vehicles at the point of use. The number of km driven has a higher impact on total mobility costs than the learning rate. Hence, the use of EVs as taxis and in car-sharing leads to the best economic performance. The most popular EVs are currently full hybrid EVs. They have only slightly higher costs and similar operating ranges as conventional vehicles. But since they are dependent on fossil fuels, they can only be seen as energy efficiency measure. However, they can serve as a bridging technology, as long as BEVs and fuel cell vehicle do not gain high popularity, and together with PHEVs and REX contribute to faster technological learning and reduction in battery costs. Regarding the promotion of EVs, the best results could be reached with a combination of monetary and non-monetary incentives, as in Norway for example. The major conclusion is that to harvest the full environmental benefits of EVs a very important aspect is the introduction of CO₂-based fuel taxes. This should ensure that the electricity for EVs is generated from renewable energy sources; otherwise, total CO₂ emissions are likely higher than those of conventional cars.

Keywords: costs, mobility, policy, sustainability,

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Authors: Min Chen, Rubi Gupta

Abstract:

Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

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Authors: Muhammad Tayyab Afzal, Muhammad Arslan, Mirza Muhammad Waqar

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One of the key components of the water cycle is evapotranspiration (ET), which represents water consumption by vegetated and non-vegetated surfaces. Conventional techniques for measurements of ET are point based and representative of the local scale only. Satellite remote sensing data with large area coverage and high temporal frequency provide representative measurements of several relevant biophysical parameters required for estimation of ET at regional scales. The objective is of this research is to exploit satellite data in order to estimate evapotranspiration. This study uses Surface Energy Balance System (SEBS) model to calculate daily actual evapotranspiration (ETa) in Larkana District, Sindh Pakistan using Landsat TM data for clouds-free days. As there is no flux tower in the study area for direct measurement of latent heat flux or evapotranspiration and sensible heat flux, therefore, the model estimated values of ET were compared with reference evapotranspiration (ETo) computed by FAO-56 Penman Monteith Method using meteorological data. For a country like Pakistan, agriculture by irrigation in the river basins is the largest user of fresh water. For the better assessment and management of irrigation water requirement, the estimation of consumptive use of water for agriculture is very important because it is the main consumer of water. ET is yet an essential issue of water imbalance due to major loss of irrigation water and precipitation on cropland. As large amount of irrigated water is lost through ET, therefore its accurate estimation can be helpful for efficient management of irrigation water. Results of this study can be used to analyse surface conditions, i.e. temperature, energy budgets and relevant characteristics. Through this information we can monitor vegetation health and suitable agricultural conditions and can take controlling steps to increase agriculture production.

Keywords: SEBS, remote sensing, evapotranspiration, ETa

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Authors: Ok-Kyun Im, Kyoung Hee Kim

Abstract:

We live in an era that faces global challenges of climate changes and resource depletion. With the rapid urbanization and growing energy consumption in the built environment, building facades become ever more important in architectural practice and environmental stewardship. Furthermore, building facade undergoes complex dynamics of social, cultural, environmental and technological changes. Kinetic facades have drawn attention of architects, designers, and engineers in the field of adaptable, responsive and interactive architecture since 1980’s. Materials and building technologies have gradually evolved to address the technical implications of kinetic facades. The kinetic façade is becoming an independent system of the building, transforming the design methodology to sustainable building solutions. Accordingly, there is a need for a new design methodology to guide the design of a kinetic façade and evaluate its sustainable performance. The research objectives are two-fold: First, to establish a new design methodology for kinetic facades and second, to develop a micro-oculi façade system and assess its performance using the established design method. The design approach to the micro-oculi facade is comprised of 1) façade geometry optimization and 2) dynamic building energy simulation. The façade geometry optimization utilizes multi-objective optimization process, aiming to balance the quantitative and qualitative performances to address the sustainability of the built environment. The dynamic building energy simulation was carried out using EnergyPlus and Radiance simulation engines with scripted interfaces. The micro-oculi office was compared with an office tower with a glass façade in accordance with ASHRAE 90.1 2013 to understand its energy efficiency. The micro-oculi facade is constructed with an array of circular frames attached to a pair of micro-shades called a micro-oculus. The micro-oculi are encapsulated between two glass panes to protect kinetic mechanisms with longevity. The micro-oculus incorporates rotating gears that transmit the power to adjacent micro-oculi to minimize the number of mechanical parts. The micro-oculus rotates around its center axis with a step size of 15deg depending on the sun’s position while maximizing daylighting potentials and view-outs. A 2 ft by 2ft prototyping was undertaken to identify operational challenges and material implications of the micro-oculi facade. In this research, a systematic design methodology was proposed, that integrates multi-objectives of kinetic façade design criteria and whole building energy performance simulation within a holistic design process. This design methodology is expected to encourage multidisciplinary collaborations between designers and engineers to collaborate issues of the energy efficiency, daylighting performance and user experience during design phases. The preliminary energy simulation indicated that compared to a glass façade, the micro-oculi façade showed energy savings due to its improved thermal properties, daylighting attributes, and dynamic solar performance across the day and seasons. It is expected that the micro oculi façade provides a cost-effective, environmentally-friendly, sustainable, and aesthetically pleasing alternative to glass facades. Recommendations for future studies include lab testing to validate the simulated data of energy and optical properties of the micro-oculi façade. A 1:1 performance mock-up of the micro-oculi façade can suggest in-depth understanding of long-term operability and new development opportunities applicable for urban façade applications.

Keywords: energy efficiency, kinetic facades, sustainable architecture, urban facades

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Authors: M. Naveed Iqbal, Sheza Fatima, Noman Shabbir

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In the presence of energy crisis in Pakistan, off-grid remote areas are not on priority list. The use of new large scale coal fired power plants will also make this situation worst. Therefore, the greatest challenge in our society is to explore new ways to power off grid remote areas with renewable energy sources. It is time for a sustainable energy policy which puts consumers, the environment, human health, and peace first. The renewable energy is one of the biggest growing sectors of the energy industry. Therefore, the large scale use of micro grid is thus described here with modeling, simulation, planning and operating of the micro grid. The goal of this research paper is to go into detail of a library of major components of micro grid. The introduction will go through the detail view of micro grid definition. Then, the simulation of Micro Grid in MATLAB/ Simulink including the Photo Voltaic Cell will be described with the detailed modeling. The simulation with the design and modeling will be introduced too.

Keywords: micro grids, distribution generation, PV, off-grid operations

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Authors: Mazarine Roquet, Pierre Dewallef

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The building sector, both residential and tertiary, accounts for a significant share of greenhouse gas emissions. In Belgium, partly due to poor insulation of the building stock, but certainly because of the massive use of fossil fuels for heating buildings, this share reaches almost 30%. To reduce carbon emissions from urban building heating, district heating networks emerge as a promising solution as they offer various assets such as improving the load factor, integrating combined heat and power systems, and enabling energy source diversification, including renewable sources and waste heat recovery. However, mainly for sake of simple operation, most existing district heating networks still operate at high or medium temperatures ranging between 120°C and 60°C (the socalled second and third-generations district heating networks). Although these district heating networks offer energy savings in comparison with individual boilers, such temperature levels generally require the use of fossil fuels (mainly natural gas) with combined heat and power. The fourth-generation district heating networks improve the transport and energy conversion efficiency by decreasing the operating temperature between 50°C and 30°C. Yet, to decarbonise the building heating one must increase the waste heat recovery and use mainly wind, solar or geothermal sources for the remaining heat supply. Fifth-generation networks operating between 35°C and 15°C offer the possibility to decrease even more the transport losses, to increase the share of waste heat recovery and to use electricity from renewable resources through the use of heat pumps to generate low temperature heat. The main objective of this contribution is to exhibit on a real-life test case the benefits of replacing an existing third-generation network by a fifth-generation one and to decarbonise the heat supply of the building stock. The second objective of the study is to highlight the difficulties resulting from the use of a fifth-generation, low-temperature, district heating network. To do so, a simulation model of the district heating network including its regulation is implemented in the modelling language Modelica. This model is applied to the test case of the heating network on the University of Liège's Sart Tilman campus, consisting of around sixty buildings. This model is validated with monitoring data and then adapted for low-temperature networks. A comparison of primary energy consumptions as well as CO2 emissions is done between the two cases to underline the benefits in term of energy independency and GHG emissions. To highlight the complexity of operating a lowtemperature network, the difficulty of adapting the mass flow rate to the heat demand is considered. This shows the difficult balance between the thermal comfort and the electrical consumption of the circulation pumps. Several control strategies are considered and compared to the global energy savings. The developed model can be used to assess the potential for energy and CO2 emissions savings retrofitting an existing network or when designing a new one.

Keywords: building simulation, fifth-generation district heating network, low-temperature district heating network, urban building heating

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Authors: Vijay S. Katta, Vinod Kushwah, Rudraksh Tiwari, Mulayam Singh Gaur, Priti Dimri, Ashok Kumar Sharma

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The formation process of seismic activities because of abrupt slip on faults, tectonic plate moments due to accumulated stress in the Earth’s crust. The prediction of seismic activity is a very challenging task. We have studied the changes in surface latent heat temperatures which are observed prior to significant earthquakes have been investigated and could be considered for short term earthquake prediction. We analyzed the surface latent heat temperature (SLHT) variation for inland earthquakes occurred in Chamba, Himachal Pradesh (32.5 N, 76.1E, M-4.5, depth-5km) nearby the main boundary fault region, the data of SLHT have been taken from National Center for Environmental Prediction (NCEP). In this analysis, we have calculated daily variations with surface latent heat temperature (0C) in the range area 1⁰x1⁰ (~120/KM²) with the pixel covering epicenter of earthquake at the center for a three months period prior to and after the seismic activities. The mean value during that period has been considered in order to take account of the seasonal effect. The monthly mean has been subtracted from daily value to study anomalous behavior (∆SLHT) of SLHT during the earthquakes. The results found that the SLHTs adjacent the epicenters all are anomalous high value 3-5 days before the seismic activities. The abundant surface water and groundwater in the epicenter and its adjacent region can provide the necessary condition for the change of SLHT. To further confirm the reliability of SLHT anomaly, it is necessary to explore its physical mechanism in depth by more earthquakes cases.

Keywords: surface latent heat temperature, satellite data, earthquake, magnetic storm

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Authors: M. Heydari Vini

Abstract:

There is a complicated relation between effective input parameters of cold rolling and output rolling force and exit thickness of strips.in many mathematical models, the effect of some rolling parameters have been ignored and the outputs have not a desirable accuracy. In the other hand, there is a special relation among input thickness of strips,the width of the strips,rolling speeds,mandrill tensions and the required exit thickness of strips with rolling force and the real exit thickness of the rolled strip. First of all, in this paper the effective parameters of cold rolling process modeled using an artificial neural network according to the optimum network achieved by using a written program in MATLAB,it has been shown that the prediction of rolling stand parameters with different properties and new dimensions attained from prior rolled strips by an artificial neural network is applicable.

Keywords: cold rolling, artificial neural networks, rolling force, real rolled thickness of strips

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Authors: P. Mandree, S. O. Ramchuran, F. O'Brien, L. Sethunya, S. Khumalo

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South Africa is identified as one of the five emerging waste management markets, globally. The waste sector in South Africa influences the areas of energy, water and food at an economic and social level. Recently, South African industries have focused on waste valorization and diversification of the current product offerings in an attempt to reduce industrial waste, target a zero waste-to-landfill initiative and recover energy. South Africa has a number of waste streams including industrial and agricultural biomass, municipal waste and marine waste. Large volumes of agricultural and forestry residues, in particular, are generated which provides significant opportunity for production of bio-based fuels and chemicals. This could directly impact development of a rural economy. One of the largest agricultural industries is the sugar industry, which contributes significantly to the country’s economy and job creation. However, the sugar industry is facing challenges due to fluctuations in sugar prices, increasing competition with low-cost global sugar producers, increasing energy and agricultural input costs, lower consumption and aging facilities. This study is aimed at technology development for the production of various bio-based chemicals using feedstock from the sugar refining process. Various indigenous bacteria and yeast species were assessed for the potential to produce platform chemicals in flask studies and at 30 L fermentation scale. Quantitative analysis of targeted bio-based chemicals was performed using either gas chromatography or high pressure liquid chromatography to assess production yields and techno-economics in order to compare performance to current commercial benchmark processes. The study also creates a decision platform for the research direction that is required for strain development using Industrial Synthetic Biology.

Keywords: bio-based chemicals, biorefinery, industrial synthetic biology, waste valorization

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Authors: Biruhi Tesfaye, Avinash M. Potdar

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The laboratory test process to determine the California bearing ratio (CBR) of black cotton soils is not only overpriced but also time-consuming as well. Hence advanced prediction of CBR plays a significant role as it is applicable In pavement design. The prediction of CBR of treated soil was executed by Artificial Neural Networks (ANNs) which is a Computational tool based on the properties of the biological neural system. To observe CBR values, combined eggshell and waste glass was added to soil as 4, 8, 12, and 16 % of the weights of the soil samples. Accordingly, the laboratory related tests were conducted to get the required best model. The maximum CBR value found at 5.8 at 8 % of eggshell waste glass powder addition. The model was developed using CBR as an output layer variable. CBR was considered as a function of the joint effect of liquid limit, plastic limit, and plastic index, optimum moisture content and maximum dry density. The best model that has been found was ANN with 5, 6 and 1 neurons in the input, hidden and output layer correspondingly. The performance of selected ANN has been 0.99996, 4.44E-05, 0.00353 and 0.0067 which are correlation coefficient (R), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE) respectively. The research presented or summarized above throws light on future scope on stabilization with waste glass combined with different percentages of eggshell that leads to the economical design of CBR acceptable to pavement sub-base or base, as desired.

Keywords: CBR, artificial neural network, liquid limit, plastic limit, maximum dry density, OMC

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Authors: Nastaran Moosavi, Mohammad Mokhtari

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Seismic inversion is a technique which has been in use for years and its main goal is to estimate and to model physical characteristics of rocks and fluids. Generally, it is a combination of seismic and well-log data. Seismic inversion can be carried out through different methods; we have conducted and compared post-stack and pre- stack seismic inversion methods on real data in one of the fields in the Persian Gulf. Pre-stack seismic inversion can transform seismic data to rock physics such as P-impedance, S-impedance and density. While post- stack seismic inversion can just estimate P-impedance. Then these parameters can be used in reservoir identification. Based on the results of inverting seismic data, a gas reservoir was detected in one of Hydrocarbon oil fields in south of Iran (Persian Gulf). By comparing post stack and pre-stack seismic inversion it can be concluded that the pre-stack seismic inversion provides a more reliable and detailed information for identification and prediction of hydrocarbon reservoirs.

Keywords: density, p-impedance, s-impedance, post-stack seismic inversion, pre-stack seismic inversion

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Authors: Soon-Gil Yoon, Min-Ju Choi, Sung-Ho Shin, Junghyo Nah, Jin-Seok Choi, Hyun-A Song, Goeun Choi, Jin-Ho Choy

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Layered double hydroxides (LDHs) with positively charged brucite-like layers and negatively charged interlayer anions are considered a critical nanoscale building block with potential for application in catalysts, biological sensors, and optical, electrical, and magnetic devices. LDHs also have a great potential as an energy conversion device, a key component in common modern electronics. Although LDHs are theoretically predicted to be centrosymmetric, we report here the first observations of the flexoelectric nature of LDHs and demonstrate their potential as an effective energy conversion material. We clearly show a linear energy conversion relationship between the output powers and curvature radius via bending with both the LDH nanosheets and thin films, revealing a direct evidence for flexoelectric effects. These findings potentially open up avenues to incorporate a flexoelectric coupling phenomenon into centrosymmetric materials such as LDHs and to harvest high-power energy using LDH nanosheets. In the present study, for enhancement of the output power, Zn-Al:LDH nanosheets were composited with piezoelectric CH3NH3PbI3 (MAPbI3) dye films and their enhanced energy harvesting was demonstrated in detail.

Keywords: layered double hydroxides, flexoelectric, piezoelectric, energy harvesting

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Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

Abstract:

Existing buildings are permanently subjected to change, continuously renovated and repaired in their long service life. Old buildings are destroyed and their material and components are recycled or reused for constructing new ones. In this process, importance of sustainability principles for building construction is obviously known and great significance must be attached to consumption of resources, resulting effects on the environment and economic costs. Utilization strategies for extending buildings service life and delay in destroying have positive effect on environment protection. In addition, simpler alterability or expandability of buildings’ structures and reducing energy and natural resources consumption have benefits for users, producers and environment. To solve these problems, by applying theories of open building, structural components of some conventional building systems have been analyzed and then, a new geometry adaptive building system is developed which can transform and support different imposed loads. In order to achieve this goal, various research methods and tools such as professional and scientific literatures review, comparative analysis, case study and computer simulation were applied and data interpretation was implemented using descriptive statistics and logical arguments. Therefore, hypothesis and proposed strategies were evaluated and an adaptable and reusable 2-dimensional building system was presented which can respond appropriately to dwellers and end-users needs and provide reusability of structural components of building system in new construction or function. Investigations showed that this incremental building system can be successfully applied in achieving the architectural design objectives and by small modifications on components and joints, it is easy to obtain different and adaptable load-optimized component alternatives for flexible spaces.

Keywords: adaptability, durability, open building, service life, structural building system

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Authors: M. Nuhu, S. Bilal, A. A. Hamisu, J. A. Abbas, Y. Z. Aminu, P. O. Helen

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Exergy and energy analysis of preheating unit of FCCU of KRPC has been calculated and presented in this study. From the design, the efficiency of each heat exchanger was 86%. However, on completion of this work the efficiencies was calculated to be 39.90%, 55.66%, 56.22%, and 57.14% for 16E02, 16E03, 16E04, and 16E05 respectively. 16E04 has the minimum energy loss of 0.86%. The calculated second law and exergy efficiencies of the system were 43.01 and 56.99% respectively.

Keywords: exergy analysis, ideal work, efficiency, exergy destruction, temperature

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Authors: Ahmed A. A. Fadol, Guangji Tong, Wlaa Mohamed

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This paper provides a comprehensive analysis of food insecurity in Sudan, focusing on consumption patterns and their implications, employing the Integrated Food Security Phase Classification (IPC) assessment framework. Years of conflict and economic instability have driven large segments of the population in Sudan into crisis levels of acute food insecurity according to the (IPC). A substantial number of people are estimated to currently face emergency conditions, with an additional sizeable portion categorized under less severe but still extreme hunger levels. In this study, we explore the multifaceted nature of food insecurity in Sudan, considering its historical, political, economic, and social dimensions. An analysis of consumption patterns and trends was conducted, taking into account cultural influences, dietary shifts, and demographic changes. Furthermore, we employ logistic regression and random forest analysis to identify significant independent variables influencing food security status in Sudan. Random forest clearly outperforms logistic regression in terms of area under curve (AUC), accuracy, precision and recall. Forward projections of the IPC for Sudan estimate that 15 million individuals are anticipated to face Crisis level (IPC Phase 3) or worse acute food insecurity conditions between October 2023 and February 2024. Of this, 60% are concentrated in Greater Darfur, Greater Kordofan, and Khartoum State, with Greater Darfur alone representing 29% of this total. These findings emphasize the urgent need for both short-term humanitarian aid and long-term strategies to address Sudan's deepening food insecurity crisis.

Keywords: food insecurity, consumption patterns, logistic regression, random forest analysis

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Authors: Robert Lindner

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In recent years a multitude of international efforts, including the United Nations’ aspirational 2030 Agenda for Sustainable Development, provided a new momentum to facilitate energy access and rural electrification projects to combat energy poverty in developing states in Asia. Rural electrification projects promise to facilitate other sustainable development aims, such as the empowerment of local communities through the creation of economic opportunities or increased disaster resilience. This study applies a multi-governance research framework to study the cases of the ongoing energy system transition in Myanmar and Cambodia. It explores what impact the international aid community, especially multilateral development banks and international development agencies, has on the governance of the transitions and how diverging aid donor interest shape policy making and project planning. The study is based on policy analysis and expert interviews, as well as extensive field research. It critically examines the current development trajectories and the strategies of the stakeholders involved. It concludes that institutional and technological competition between donors, as well as a lack of transparency and inclusion in the project planning and implementation phases, contributes to insufficient coordination in national energy policy making and project implementation at the local level. The study further discusses possible alternative approaches that might help to promote the spread of sustainable energy technologies.

Keywords: energy governance, developing countries, multi-level governance, energy transitions

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Authors: Dana Alghool, Tarek ElMekkawy, Mohamed Haouari, Adel Elomari

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District cooling systems have captured the attentions of many researchers recently due to the enormous benefits offered by such system in comparison with traditional cooling technologies. It is considered a major component of urban cities due to the significant reduction of energy consumption. This paper aims to find the optimal design and operation of district cooling systems by developing a mixed integer linear programming model to minimize the annual total system cost and satisfy the end-user cooling demand. The proposed model is experimented with different cooling demand scenarios. The results of the very high cooling demand scenario are only presented in this paper. A sensitivity analysis on different parameters of the model was performed.

Keywords: Annual Cooling Demand, Compression Chiller, Mathematical Modeling, District Cooling Systems, Optimization

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Authors: Sang Heon Han, Daejun Chang, Won Yang

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NOx reduction characteristics of syngas fuel were numerically investigated for the 2MW pilot scale heavy oil furnace of KITECH (Korea Institute of Industrial Technology). The secondary fuel and syngas was fed into the furnace with two purposes- partial replacement of main fuel and reburning of NOx. Some portion of syngas was fed into the flame zone to partially replace the heavy oil, while the other portion was fed into the furnace downstream to reduce NOx generation. The numerical prediction was verified by comparing it with the experimental results. Syngas of KITECH’s experiment, assumed to be produced from biomass, had very low calorific value and contained 3% hydrocarbon. This study investigated the precise behavior of NOx generation and NOx reduction as well as thermo-fluidic characteristics inside the furnace, which was unavailable with experiment. In addition to 3% hydrocarbon syngas, 5%, and 7% hydrocarbon syngas were numerically tested as reburning fuels to analyze the effect of hydrocarbon proportion to NOx reduction. The prediction showed that the 3% hydrocarbon syngas is as much effective as 7% hydrocarbon syngas in reducing NOx.

Keywords: syngas, reburning, heavy oil, furnace

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Authors: Aliyu Mohammed Lawal, Dahiru Yau Gital

Abstract:

The characterisation and the energy potential of the municipal solid wastes in Bauchi town and environs were studied. It was found that, 35,000 tonnes of waste was generated annually at 0.19 kg/capital/day of which, the combination of plastics, rubber, polyethene bags constituted about 33%, followed by textile materials, leathers, wood 26%, combination of papers, cartons 19%, crop stalks/grass 11% and the remaining incombustible materials 11%. The heating value or calorific value of the wastes was determined using a digital calorimeter to be 6.43 MJ/kg, almost one-third of the energy content of peat which has a value of 15.9 MJ/kg. The calorific value of the fuel was found to be significant; hence, the waste could be used for energy generation.

Keywords: calorific value, characterization, digital calorimeter, incombustible, municipal solid waste

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Authors: Jitka Hroudová, Martin Sedlmajer, Jiří Zach

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Problems insulation of building structures is often closely connected with the problem of moisture remediation. In the case of historic buildings or if only part of the redevelopment of envelope of structures, it is not possible to apply the classical external thermal insulation composite systems. This application is mostly effective thermal insulation plasters with high porosity and controlled capillary properties which assures improvement of thermal properties construction, its diffusion openness towards the external environment and suitable treatment capillary properties of preventing the penetration of liquid moisture and salts thereof toward the outer surface of the structure. With respect to the current trend of reducing the energy consumption of building structures and reduce the production of CO2 is necessary to develop capillary-active materials characterized by their low density, low thermal conductivity while maintaining good mechanical properties. The aim of researchers at the Faculty of Civil Engineering, Brno University of Technology is the development and study of hygrothermal behaviour of optimal materials for thermal insulation and rehabilitation of building structures with the possible use of alternative, less energy demanding binders in comparison with conventional, frequently used binder, which represents cement. The paper describes the evaluation of research activities aimed at the development of thermal insulation and repair materials using lightweight aggregate and alternative binders such as metakaolin and finely ground fly ash.

Keywords: thermal insulating plasters, rehabilitation materials, thermal conductivity, lightweight aggregate, alternative binders.

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Authors: Oladipo Oluwaseun Peter

Abstract:

Daily consumption of crude oil is alarming as a result of increasing demand for energy. Waste generation tends to rise with the level of economic advancement of a nation. Hence, this project work researches how wastes which could pose toxic if left unattended to can be processed through biodigestion in order to generate biofuel which could serve as a good substitute for petroleum, a non renewable energy source, so as to reduce over-dependence on petroleum and to prevent environmental pollution. Anaerobic digestion was carried out on organic wastes comprising brewery spent grains, rice husks and poultry droppings in a plastic biodigester of 1000 liters volume using the poultry droppings as a natural inoculums source. The feed composition in ratio 5:3:2, spent grain, rice husks and poultry droppings were mixed with water in the ratio 1:6. Thus, 600 Kg of water was used to prepare the slurry with 100 Kg of feed materials. A plastic biodigester was successfully constructed, and the problem of corrosion and rusting were completely overcome as a result of the use of non-corroding materials of construction. A reasonable quantity of biogas, 33.63m3, was generated over a period of 60 days of biodigestion. The bioslurry was processed through two different process routes; evaporation and filteration. Evaporation process of analysis shows high values of 0.64%, 2.11% and 0.034% for nitrogen, phosphorous and potassium respectively, while filteration process gives 00.61%, 1.93% and 0.026% for nitrogen, phosphorous and potassium respectively.

Keywords: biodigestion, biofuel, digestion, slurry, biogas

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Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

Abstract:

Existing buildings are permanently subjected to change, continuously renovated and repaired in their long service life. Old buildings are destroyed and their material and components are recycled or reused for constructing new ones. In this process, importance of sustainability principles for building construction is obviously known and great significance must be attached to consumption of resources, resulting effects on the environment and economic costs. Utilization strategies for extending buildings service life and delay in destroying have positive effect on environment protection. In addition, simpler alterability or expandability of buildings’ structures and reducing energy and natural resources consumption have benefits for users, producers and environment. To solve these problems, by applying theories of open building, structural components of some conventional building systems have been analyzed and then, a new geometry adaptive building system is developed which can transform and support different imposed loads. In order to achieve this goal, various research methods and tools such as professional and scientific literatures review, comparative analysis, case study and computer simulation were applied and data interpretation was implemented using descriptive statistics and logical arguments. Therefore, hypothesis and proposed strategies were evaluated and an adaptable and reusable 2-dimensional building system was presented which can respond appropriately to dwellers and end-users needs and provide reusability of structural components of building system in new construction or function. Investigations showed that this incremental building system can be successfully applied in achieving the architectural design objectives and by small modifications on components and joints, it is easy to obtain different and adaptable load-optimized component alternatives for flexible spaces.

Keywords: adaptability, durability, open building, service life, structural building system

Procedia PDF Downloads 347

Authors: Jacob Green, Cecilia Cabrera, Maximilian Jakobs, Andrea Dimitracopoulos, Mark van der Wilk, Ryan Greenhalgh

Abstract:

Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials and to find highly active compounds faster. Interest from the machine learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is most suitable, as different papers benchmark on different datasets and methods, leading to varying conclusions that are not easily compared. Our large-scale empirical study links together numerous earlier works on different datasets and methods, thus offering a comprehensive overview of the existing property classes, datasets, and their interactions with different methods. We emphasise the importance of uncertainty quantification and the time and, therefore, cost of applying these methods in the drug development decision-making cycle. To the best of the author's knowledge, it has been observed that the optimal approach varies depending on the dataset and that engineered features with classical machine learning methods often outperform deep learning. Specifically, QSAR datasets are typically best analysed with classical methods such as Gaussian Processes, while ADMET datasets are sometimes better described by Trees or deep learning methods such as Graph Neural Networks or language models. Our work highlights that practitioners do not yet have a straightforward, black-box procedure to rely on and sets a precedent for creating practitioner-relevant benchmarks. Deep learning approaches must be proven on these benchmarks to become the practical method of choice in drug property prediction.

Keywords: activity (QSAR), ADMET, classical methods, drug property prediction, empirical study, machine learning

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Authors: A. H. El-Shazly, A. El-Tayeb, M. F. Elkady, Mona G. E. Ibrahim, Abdelazim M. Negm

Abstract:

In this paper, corona discharge plasma reactor was used for degradation of organic pollution in aqueous solutions in batch reactor. This work examines the possibility of increasing the organic pollution removal efficiency from wastewater using non-thermal plasma. Three types of organic pollution phenol, acid blue 25 and methylene blue are presented to investigate experimentally the amount of organic pollution removal efficiency from wastewater. Measurement results for phenol degradation percentage are 71% in 35 min and 96% when its residence time is 60 min. In addition, the degradation behavior of acid blue 25 utilizing dual pin-to-plate corona discharge plasma system displays a removal efficiency of 82% in 11 min. The complete decolorization was accomplished in 35 min for concentration of acid blue 25 up to 100 ppm. Furthermore, the methylene blue degradation touched up to 85% during 35 min treatment in corona discharge plasma a batch reactor system. The decolorization ratio, conductivity, corona current and discharge energy are considered at various concentration molarity for AlCl3, CaCl2, KCl and NaCl under different molar concentration. It was observed that the attendance of salts at the same concentration level considerably diminished the rate and the extent of decolorization. The research presented that the corona system could be positively utilized in a diversity of organically contaminated at diverse concentrations. Energy consumption requirements for decolorization was considered. The consequences will be valuable for designing the plasma treatment systems appropriate for industrial wastewaters.

Keywords: wastewater treatment, corona discharge, non-thermal plasma, organic pollution

Procedia PDF Downloads 318

Authors: Riana V. Ramanantsalama, Aristide Andrianarimisa, Achille P. Raselimanana, Steven M. Goodman

Abstract:

Few details are available on the consumption of ectoparasites, specifically bat flies (Diptera: Nycteribiidae and Streblidae), by their chiropteran hosts while grooming. Such details could provide information on the dynamics of host-parasite interactions. This study presents data on ectoparasite ingestion rates for an endemic Malagasy fruit bat (Pteropodidae: Rousettus madagascariensis) occupying a cave day roost colony in northern Madagascar. Using quantified behavioral analyses, grooming and associated ingestion rates were measured from infrared videos taken in close proximity to day-roosting bats. The recorded individual bats could be visually identified to age (adult, juvenile) and sex (male, female), allowing analyses of the proportion of time these different classes allocated to consuming ectoparasites via auto-grooming (self) or allo-grooming (intraspecific) per 10 min video recording session. These figures could then be extrapolated to estimates of individual daily consumption rates. Based on video recordings, adults spent significantly more time auto-grooming and allo-grooming than juveniles. The latter group was not observed consuming ectoparasites. Grooming rates and the average number of ectoparasites consumed per day did not differ between adult males and females. The mean extrapolated number consumed on a daily basis for individual adults was 37 ectoparasites. When these figures are overlaid on the estimated number of adult Rousettus occurring at the roost site during the dry season, the projected daily consumption rate was 57,905 ectoparasites. To the best knowledge of the authors of this study, the details presented here represent the first quantified data on bat consumption rates of their ectoparasites, specifically dipterans. These results provide new insights into host-parasite predation dynamics. More research is needed to explore the mechanism zoonotic diseases isolated from bat flies might be transmitted to their bat hosts, specifically those pathogens that can be communicated via an oral route.

Keywords: diptera, host-parasite interactions, Madagascar, nycteribiidae, pteropodidae, Rousettus madagascariensis

Procedia PDF Downloads 133

Authors: Italo Luigi de Paoli

Abstract:

The use of synthetic soil for the vegetables cultivation in conditions of limited water consumption The separate collection of urban organic waste and green waste for the countries of the European Union averages 100 kg / inhabitant x year with an annual growth of about 10%. The production of quality compost averages 38% - 40% of the production of organic waste material. Most of the compost produced is used as an organic soil improver in those nutrient-poor soils in order to improve its quality. This study seeks to enhance the production of quality compost by creating a synthetic soil, where the percentages of compost on average oscillate between 50% and 60% in which, with appropriate precautions, different species of horticultural can be grown in conditions of high environmental safety without the use of pesticides and with a consumption of water used for irrigation limited to the actual evaporation of the plants. The project started in 2018 and is still ongoing, confirms its validity through a series of different horticultural productions, especially if this technology is applied where the availability of land suitable for the cultivation of vegetables is limited and where the use of water for irrigation represents a cultural criticality. Furthermore, the creation of "open field" crops, together with their automation, represents a further possibility in the concrete development of such technologies, giving the final product organoleptic characteristics equal if not superior to what the market offers today for human nutrition.

Keywords: water scarcity, compost, vegetable foods, syntetic soil

Procedia PDF Downloads 161

Authors: Eric Kumar, Erica Cochran, Zhiang Zhang, Wei Liang, Ronak Mody

Abstract:

The objective of this article was to create a modelling framework that exposes the marginal costs of shifting workloads across geographically distributed data-centers. Geographical distribution of internet services helps to optimize their performance for localized end users with lowered communications times and increased availability. However, due to the geographical and temporal effects, the physical embodiments of a service's data center infrastructure can vary greatly. In this work, we first identify that the sources of variances in the physical infrastructure primarily stem from local weather conditions, specific user traffic profiles, energy sources, and the types of IT hardware available at the time of deployment. Second, we create a traffic simulator that indicates the IT load at each data-center in the set as an approximator for user traffic profiles. Third, we implement a framework that quantifies the global level energy demands using building energy models and the traffic profiles. The results of the model provide a time series of energy demands that can be used for further life cycle analysis of internet services.

Keywords: data-centers, energy, life cycle, network simulation

Procedia PDF Downloads 130

Authors: James Purnama, Riri Fitri Sari

Abstract:

We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

Procedia PDF Downloads 525

Authors: Pakorn Uttayopas, Chawalit Kittichaikarn

Abstract:

This paper presents an experimental investigation for the characteristics of an energy harvesting device exploiting flow-induced vibration in a wind tunnel. A stationary bluff body is connected with a downstream tip body via an aluminium cantilever beam. Various lengths of aluminium cantilever beam and different shapes of downstream tip body are considered. The results show that the characteristics of the energy harvester’s vibration depend on both the length of the aluminium cantilever beam and the shape of the downstream tip body. The highest ratio between vibration amplitude and bluff body diameter was found to be 1.39 for an energy harvester with a symmetrical triangular tip body and L/D₁ = 5 at 9.8 m/s of flow speed (Re = 20077). Using this configuration, the electrical energy was extracted with a polyvinylidene fluoride (PVDF) piezoelectric beam with different load resistances, of which the optimal value could be found on each Reynolds number. The highest power output was found to be 3.19 µW, at 9.8 m/s of flow speed (Re = 20077) and 27 MΩ of load resistance.

Keywords: downstream structures, energy harvesting, flow-induced vibration, piezoelectric material, wind tunnel

Procedia PDF Downloads 222