Search results for: solar irradiation modeling

Authors: Shulamit Sternin

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Athletes experience injuries that can have both a physical and psychological impact on the individual. In such instances, athletes are able to rely on the established field of sports psychology to facilitate holistic rehabilitation. Musicians, like athletes rely on their bodies to perform in much the same way athletes do and are also susceptible to injury. Due to the similar performative nature of succeeding as an athletes or a musician, these careers share many of the same primary psychological concerns and therefore it is reasonable that athletes and musicians may require similar rehabilitation post-injury. However, musicians face their own unique psychological challenges and understanding the needs of an injured athlete can serve as a foundation for understanding the injured musician but is not enough to fully rehabilitate an injured musician. The current research surrounding musicians and their injuries is primarily focused on physiological aspects of injury and rehabilitation; the psychological aspects have not yet received adequate attention resulting in poor musician rehabilitation post- injury. This review paper uses current models of psychological response to injury in athletes to draw parallels with the psychological response to injury in musicians. Search engines such as Medline and PsycInfo were systematically searched using specific key words, such as psychological response, injury, athlete, and musician. Studies that focused on post-injury psychology of either the musician or the athlete were included. Within the literature there is evidence to support psychological responses, unique to the musician, that are not accounted for by current models of response in athletes. The models of psychological response to injury in athletes are inadequate tools for application to the musician. Future directions for performance arts research that can fill the gaps in our understanding and modeling of musicians’ response to injury are discussed. A better understanding of the psychological impact of injuries on musicians holds significant implications for health care practitioners working with injured musicians. Understanding the unique barriers musicians face post-injury, and how support for this population must be tailored to properly suit musicians’ needs will aid in more holistic rehabilitation and a higher likelihood of musician’s returning to pre-injury performance levels.

Keywords: athlete, injury, musician, psychological response

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Authors: Shivahari Revathi Venkateswaran

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Segmenting customers plays a significant role in churn prediction. It helps the marketing team with proactive and reactive customer retention. For the reactive retention, the retention team reaches out to customers who already showed intent to disconnect by giving some special offers. When coming to proactive retention, the marketing team uses churn prediction model, which ranks each customer from rank 1 to 100, where 1 being more risk to churn/disconnect (high ranks have high propensity to churn). The churn prediction model is built by using XGBoost model. However, with the churn rank, the marketing team can only reach out to the customers based on their individual ranks. To profile different groups of customers and to frame different marketing strategies for targeted groups of customers are not possible with the churn ranks. For this, the customers must be grouped in different segments based on their profiles, like demographics and other non-controllable attributes. This helps the marketing team to frame different offer groups for the targeted audience and prevent them from disconnecting (proactive retention). For segmentation, machine learning approaches like k-mean clustering will not form unique customer segments that have customers with same attributes. This paper finds an alternate approach to find all the combination of unique segments that can be formed from the user attributes and then finds the segments who have uplift (churn rate higher than the baseline churn rate). For this, search algorithms like fast search and recursive search are used. Further, for each segment, all customers can be targeted using individual churn ranks from the churn prediction model. Finally, a UI (User Interface) is developed for the marketing team to interactively search for the meaningful segments that are formed and target the right set of audience for future marketing campaigns and prevent them from disconnecting.

Keywords: churn prediction modeling, XGBoost model, uplift segments, proactive marketing, search algorithms, retention, k-mean clustering

Procedia PDF Downloads 56

Authors: Francisco Vidal Vázquez, Pekka Simell, Christian Frilund, Matti Reinikainen, Ilkka Hiltunen, Tim Böltken, Benjamin Andris, Paolo Piermartini

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Carbon capture and utilization (CCU) are one of the key topics in mitigation of CO2 emissions. There are many different technologies that are applied for the production of diverse chemicals from CO2 such as synthetic natural gas, Fischer-Tropsch products, methanol and polymers. Power-to-Gas and Power-to-Liquids concepts arise as a synergetic solution for storing energy and producing value added products from the intermittent renewable energy sources and CCU. VTT is a research and technology development company having energy in transition as one of the key focus areas. VTT has extensive experience in piloting and upscaling of new energy and chemical processes. Recently, VTT has developed and commissioned a Mobile Synthesis Unit (MOBSU) in close collaboration with INERATEC, a spin-off company of Karlsruhe Institute of Technology (KIT, Germany). The MOBSU is a multipurpose synthesis unit for CO2 upgrading to energy carriers and chemicals, which can be transported on-site where CO2 emission and renewable energy are available. The MOBSU is initially used for production of fuel compounds and chemical intermediates by combination of two consecutive processes: reverse Water-Gas Shift (rWGS) and Fischer-Tropsch synthesis (FT). First, CO2 is converted to CO by high-pressure rWGS and then, the CO and H2 rich effluent is used as feed for FT using an intensified reactor technology developed and designed by INERATEC. Chemical equilibrium of rWGS reaction is not affected by pressure. Nevertheless, compression would be required in between rWGS and FT in the case when rWGS is operated at atmospheric pressure. This would also require cooling of rWGS effluent, water removal and reheating. For that reason, rWGS is operated using precious metal catalyst in the MOBSU at similar pressure as FT to simplify the process. However, operating rWGS at high pressures has also some disadvantages such as methane and carbon formation, and more demanding specifications for materials. The main parts of FT module are an intensified reactor, a hot trap to condense the FT wax products, and a cold trap to condense the FT liquid products. The FT synthesis is performed using cobalt catalyst in a novel compact reactor technology with integrated highly-efficient water evaporation cooling cycle. The MOBSU started operation in November 2016. First, the FT module is tested using as feedstock H2 and CO. Subsequently, rWGS and FT modules are operated together using CO2 and H2 as feedstock of ca. 5 Nm3/hr total flowrate. On spring 2017, The MOBSU unit will be integrated together with a direct air capture (DAC) of CO2 unit, and a PEM electrolyser unit at Lappeenranta University of Technology (LUT) premises for demonstration of the SoletAir concept. This would be the first time when synthetic fuels are produced by combination of DAC unit and electrolyser unit which uses solar power for H2 production.

Keywords: CO2 utilization, demonstration, Fischer-Tropsch synthesis, intensified reactors, reverse water-gas shift

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Authors: Nacera Yassa, Abdelmalek Saidoune, Ghania Ouadfel, Hamza Houassine

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The rapid advancement in electrical technologies has underscored the increasing importance of multiphase machines across various industrial sectors. These machines offer significant advantages in terms of efficiency, compactness, and reliability compared to their single-phase counterparts. However, early detection and diagnosis of electrical faults remain critical challenges to ensure the durability and safety of these complex systems. This paper presents an advanced analytical model for multiphase machines, with a particular focus on dual stator asynchronous machines. The primary objective is to develop a robust diagnostic tool capable of effectively detecting and locating electrical faults in these machines, including short circuits, winding faults, and voltage imbalances. The proposed methodology relies on an analytical approach combining electrical machine theory, modeling of magnetic and electrical circuits, and advanced signal analysis techniques. By employing detailed analytical equations, the developed model accurately simulates the behavior of multiphase machines in the presence of electrical faults. The effectiveness of the proposed model is demonstrated through a series of case studies and numerical simulations. In particular, special attention is given to analyzing the dynamic behavior of machines under different types of faults, as well as optimizing diagnostic and recovery strategies. The obtained results pave the way for new advancements in the field of multiphase machine diagnostics, with potential applications in various sectors such as automotive, aerospace, and renewable energies. By providing precise and reliable tools for early fault detection, this research contributes to improving the reliability and durability of complex electrical systems while reducing maintenance and operation costs.

Keywords: faults, diagnosis, modelling, multiphase machine

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Authors: Adriana Postal, Silvio C. Sampaio, Marcio A. Villas Boas, Josué P. Castro

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This study deals with the estimation of reference evapotranspiration (ET₀) in an agricultural context, focusing on efficient irrigation management to meet the growing interest in the sustainable management of water resources. Given the importance of water in agriculture and its scarcity in many regions, efficient use of this resource is essential to ensure food security and environmental sustainability. The methodology used involved the application of artificial intelligence techniques, specifically Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs), to predict ET₀ in the state of Paraná, Brazil. The models were trained and validated with meteorological data from the Brazilian National Institute of Meteorology (INMET), together with data obtained from a producer's weather station in the western region of Paraná. Two optimizers (SGD and Adam) and different meteorological variables, such as temperature, humidity, solar radiation, and wind speed, were explored as inputs to the models. Nineteen configurations with different input variables were tested; amidst them, configuration 9, with 8 input variables, was identified as the most efficient of all. Configuration 10, with 4 input variables, was considered the most effective, considering the smallest number of variables. The main conclusions of this study show that MLP ANNs are capable of accurately estimating ET₀, providing a valuable tool for irrigation management in agriculture. Both configurations (9 and 10) showed promising performance in predicting ET₀. The validation of the models with cultivator data underlined the practical relevance of these tools and confirmed their generalization ability for different field conditions. The results of the statistical metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²), showed excellent agreement between the model predictions and the observed data, with MAE as low as 0.01 mm/day and 0.03 mm/day, respectively. In addition, the models achieved an R² between 0.99 and 1, indicating a satisfactory fit to the real data. This agreement was also confirmed by the Kolmogorov-Smirnov test, which evaluates the agreement of the predictions with the statistical behavior of the real data and yields values between 0.02 and 0.04 for the producer data. In addition, the results of this study suggest that the developed technique can be applied to other locations by using specific data from these sites to further improve ET₀ predictions and thus contribute to sustainable irrigation management in different agricultural regions. The study has some limitations, such as the use of a single ANN architecture and two optimizers, the validation with data from only one producer, and the possible underestimation of the influence of seasonality and local climate variability. An irrigation management application using the most efficient models from this study is already under development. Future research can explore different ANN architectures and optimization techniques, validate models with data from multiple producers and regions, and investigate the model's response to different seasonal and climatic conditions.

Keywords: agricultural technology, neural networks in agriculture, water efficiency, water use optimization

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Authors: Prashant Verma, Prafulla K. Swain, K. K. Singh, Mukti Khetan

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Objective: In India, around 20,000 women die every year due to abortion-related complications. In the modelling of count variables, there is sometimes a preponderance of zero counts. This article concerns the estimation of various count regression models to predict the average number of spontaneous abortion among women in the Punjab state of India. It also assesses the factors associated with the number of spontaneous abortions. Materials and methods: The study included 27,173 married women of Punjab obtained from the DLHS-4 survey (2012-13). Poisson regression (PR), Negative binomial (NB) regression, zero hurdle negative binomial (ZHNB), and zero-inflated negative binomial (ZINB) models were employed to predict the average number of spontaneous abortions and to identify the determinants affecting the number of spontaneous abortions. Results: Statistical comparisons among four estimation methods revealed that the ZINB model provides the best prediction for the number of spontaneous abortions. Antenatal care (ANC) place, place of residence, total children born to a woman, woman's education and economic status were found to be the most significant factors affecting the occurrence of spontaneous abortion. Conclusions: The study offers a practical demonstration of techniques designed to handle count variables. Statistical comparisons among four estimation models revealed that the ZINB model provided the best prediction for the number of spontaneous abortions and is recommended to be used to predict the number of spontaneous abortions. The study suggests that women receive institutional Antenatal care to attain limited parity. It also advocates promoting higher education among women in Punjab, India.

Keywords: count data, spontaneous abortion, Poisson model, negative binomial model, zero hurdle negative binomial, zero-inflated negative binomial, regression

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Authors: Victoria Masi Haruna Karatu, Nik Kamariah Nikmat

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In recent times awareness about the environment and green purchase has been on the increase across nations due to global warming. Previous researchers have attempted to determine what actually influences the purchase intention of consumers in this environmentally conscious epoch. The consumers too have become conscious of what to buy and who to buy from in their purchasing decisions as this action will reflect their concern about the environment and their personal well-being. This trend is a widespread phenomenon in most developed countries of the world. On the contrary evidence revealed that only 5% of the populations of Nigeria involve in green purchase activities thus making the country lag behind its counterparts in green practices. This is not a surprise as Nigeria is facing problems of inadequate green knowledge, non-enforcement of environmental regulations, sensitivity to the price of green products when compared with the conventional ones and distrust towards green products which has been deduced from prior studies of other regions. The main objectives of this study is to examine the direct antecedents of green purchase intention (green availability, government regulations, perceived green knowledge, perceived value and green price sensitivity) in Nigeria and secondly to establish the mediating role of perceived behavioral control on the relationship between these antecedents and green purchase intention. The study adopts quantitative method whereby 700 questionnaires were administered to lecturers in three Nigerian universities. 502 datasets were collected which represents 72 percent response rate. After screening the data only 440 were usable and analyzed using structural equation modeling (SEM) and bootstrapping. From the findings, three antecedents have significant direct relationships with green purchase intention (perceived green knowledge, perceived behavioral control, and green availability) while two antecedents have positive and significant direct relationship with perceived behavioral control (perceived value and green price sensitivity). On the other hand, PBC does not mediate any of the paths from the predictors to criterion variable. This result is discussed in the Nigerian context.

Keywords: Green Availability, Green Price Sensitivity, Green Purchase Intention, Perceived Green Knowledge, Perceived Value

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Authors: Tarun Kumar Dalakoti, Debajyoti Majumder, Aditya Prasad Das, Samir Chandra Saxena

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India’s ambitious target to achieve a 50 percent share of energy from non-fossil fuels and the 500-gigawatt (GW) renewable energy capacity before the deadline of 2030, coupled with the global pursuit of sustainable development, will compel the nation to embark on a rapid clean energy transition. As a result, electricity market reforms will emerge as critical policy instruments to facilitate this transition and achieve ambitious environmental targets. This paper will present a comprehensive analysis of the various electricity market reforms to be introduced in the Indian Electricity sector to facilitate the integration of clean energy sources and will assess their impact on the overall energy landscape. The first section of this paper will delve into the policy mechanisms to be introduced by the Government of India and the Central Electricity Regulatory Commission to promote clean energy deployment. These mechanisms include extensive provisions for the integration of renewables in the Indian Electricity Grid Code, 2023. The section will also cover the projection of RE Generation as highlighted in the National Electricity Plan, 2023. It will discuss the introduction of Green Energy Market segments, the waiver of Inter-State Transmission System (ISTS) charges for inter-state sale of solar and wind power, the notification of Promoting Renewable Energy through Green Energy Open Access Rules, and the bundling of conventional generating stations with renewable energy sources. The second section will evaluate the tangible impact of these electricity market reforms. By drawing on empirical studies and real-world case examples, the paper will assess the penetration rate of renewable energy sources in India’s electricity markets, the decline of conventional fuel-based generation, and the consequent reduction in carbon emissions. Furthermore, it will explore the influence of these reforms on electricity prices, the impact on various market segments due to the introduction of green contracts, and grid stability. The paper will also discuss the operational challenges to be faced due to the surge of RE Generation sources as a result of the implementation of the above-mentioned electricity market reforms, including grid integration issues, intermittency concerns with renewable energy sources, and the need for increasing grid resilience for future high RE in generation mix scenarios. In conclusion, this paper will emphasize that electricity market reforms will be pivotal in accelerating the global transition towards clean energy systems. It will underscore the importance of a holistic approach that combines effective policy design, robust regulatory frameworks, and active participation from market actors. Through a comprehensive examination of the impact of these reforms, the paper will shed light on the significance of India’s sustained commitment to a cleaner, more sustainable energy future.

Keywords: renewables, Indian electricity grid code, national electricity plan, green energy market

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Authors: Suman Dutta, Manish Agrawal, C. S. Jog

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Accurate computation of hydrodynamic forces on floating structures and their deformation finds application in the ocean and naval engineering and wave energy harvesting. This manuscript presents a monolithic, finite element strategy for fluid-structure interaction involving hyper-elastic solids partly submerged in an incompressible fluid. A velocity-based Arbitrary Lagrangian-Eulerian (ALE) formulation has been used for the fluid and a displacement-based Lagrangian approach has been used for the solid. The flexibility of the ALE technique permits us to treat the free surface of the fluid as a Lagrangian entity. At the interface, the continuity of displacement, velocity and traction are enforced using the mortar method. In the mortar method, the constraints are enforced in a weak sense using the Lagrange multiplier method. In the literature, the mortar method has been shown to be robust in solving various contact mechanics problems. The time-stepping strategy used in this work reduces to the generalized trapezoidal rule in the Eulerian setting. In the Lagrangian limit, in the absence of external load, the algorithm conserves the linear and angular momentum and the total energy of the system. The use of monolithic coupling with an energy-conserving time-stepping strategy gives an unconditionally stable algorithm and allows the user to take large time steps. All the governing equations and boundary conditions have been mapped to the reference configuration. The use of the exact tangent stiffness matrix ensures that the algorithm converges quadratically within each time step. The robustness and good performance of the proposed method are demonstrated by solving benchmark problems from the literature.

Keywords: ALE, floating body, fluid-structure interaction, monolithic, mortar method

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Authors: Minho Kwak, Suhwan Yun, Choonsoo Park

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Nose shape optimizations of high-speed train are performed for the improvement of aerodynamic characteristics. Based on the commercial train, KTX-Sancheon, multi-objective optimizations are conducted for the improvement of the side wind stability and the micro-pressure wave following the optimization for the reduction of aerodynamic drag. 3D nose shapes are modelled by the Vehicle Modeling Function. Aerodynamic drag and side wind stability are calculated by three-dimensional compressible Navier-Stokes solver, and micro pressure wave is done by axi-symmetric compressible Navier-Stokes solver. The Maxi-min Latin Hypercube Sampling method is used to extract sampling points to construct the approximation model. The kriging model is constructed for the approximation model and the NSGA-II algorithm was used as the multi-objective optimization algorithm. Nose length, nose tip height, and lower surface curvature are design variables. Because nose length is a dominant variable for aerodynamic characteristics of train nose, two optimization processes are progressed respectively with and without the design variable, nose length. Each pareto set was obtained and each optimized nose shape is selected respectively considering Honam high-speed rail line infrastructure in South Korea. Through the optimization process with the nose length, when compared to KTX Sancheon, aerodynamic drag was reduced by 9.0%, side wind stability was improved by 4.5%, micro-pressure wave was reduced by 5.4% whereas aerodynamic drag by 7.3%, side wind stability by 3.9%, micro-pressure wave by 3.9%, without the nose length. As a result of comparison between two optimized shapes, similar shapes are extracted other than the effect of nose length.

Keywords: aerodynamic characteristics, design variable, multi-objective optimization, train nose shape

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Authors: Reza Miresmaeili, Asghar Heydari Astaraee, Fereshteh Dolati

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In the present study, an analytical model based on dislocation density model was developed to simulate grain refinement in surface mechanical attrition treatment (SMAT). The correlation between SMAT time and development in plastic strain on one hand, and dislocation density evolution, on the other hand, was established to simulate the grain refinement in SMAT. A dislocation density-based constitutive material law was implemented using VUHARD subroutine. A random sequence of shots is taken into consideration for multiple impacts model using Python programming language by utilizing a random function. The simulation technique was to model each impact in a separate run and then transferring the results of each run as initial conditions for the next run (impact). The developed Finite Element (FE) model of multiple impacts describes the coverage evolution in SMAT. Simulations were run to coverage levels as high as 4500%. It is shown that the coverage implemented in the FE model is equal to the experimental coverage. It is depicted that numerical SMAT coverage parameter is adequately conforming to the well-known Avrami model. Comparison between numerical results and experimental measurements for residual stresses and depth of deformation layers confirms the performance of the established FE model for surface engineering evaluations in SMA treatment. X-ray diffraction (XRD) studies of grain refinement, including resultant grain size and dislocation density, were conducted to validate the established model. The full width at half-maximum in XRD profiles can be used to measure the grain size. Numerical results and experimental measurements of grain refinement illustrate good agreement and show the capability of established FE model to predict the gradient microstructure in SMA treatment.

Keywords: dislocation density, grain refinement, severe plastic deformation, simulation, surface mechanical attrition treatment

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Authors: Dehni Abdellatif, Lounis Mourad

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The new approach of applied spatial geostatistics in materials sciences, agriculture accuracy, agricultural statistics, permitted an apprehension of managing and monitoring the water and groundwater qualities in a relationship with salt-affected soil. The anterior experiences concerning data acquisition, spatial-preparation studies on optical and multispectral data has facilitated the integration of correction models of electrical conductivity related with soils temperature (horizons of soils). For tomography apprehension, this physical parameter has been extracted from calibration of the thermal band (LANDSAT ETM+6) with a radiometric correction. Our study area is Oran region (Northern West of Algeria). Different spectral indices are determined such as salinity and sodicity index, the Combined Spectral Reflectance Index (CSRI), Normalized Difference Vegetation Index (NDVI), emissivity, Albedo, and Sodium Adsorption Ratio (SAR). The approach of geostatistical modeling of electrical conductivity (salinity), appears to be a useful decision support system for estimating corrected electrical resistivity related to the temperature of surface soils, according to the conversion models by substitution, the reference temperature at 25°C (where hydrochemical data are collected with this constraint). The Brightness temperatures extracted from satellite reflectance (LANDSAT ETM+) are used in consistency models to estimate electrical resistivity. The confusions that arise from the effects of salt stress and water stress removed followed by seasonal application of the geostatistical analysis in Geographic Information System (GIS) techniques investigation and monitoring the variation of the electrical conductivity in the alluvial aquifer of Es-Sénia for the salt-affected soil.

Keywords: geostatistical modelling, landsat, brightness temperature, conductivity

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Authors: Alokananda Ghosh, Shraban Sarkar

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The study aims to identify suitable sites for new hospitals with critical obstetric care facilities in Birbhum, one of the vulnerable and underserved districts of Eastern India, considering six main and 14 sub-criteria, using GIS-based Analytic Hierarchy Process (AHP) and Multi-Attribute Utility Theory (MAUT) approach. The criteria were identified through field surveys and previous literature. After collecting expert decisions, a pairwise comparison matrix was prepared using the Saaty scale to calculate the weights through AHP. On the contrary, objective weighting methods, i.e., Entropy and Criteria Importance through Interaction Correlation (CRITIC), were used to perform the MAUT. Finally, suitability maps were prepared by weighted sum analysis. Sensitivity analyses of AHP were performed to explore the effect of dominant criteria. Results from AHP reveal that ‘maternal death in transit’ followed by ‘accessibility and connectivity’, ‘maternal health care service (MHCS) coverage gap’ were three important criteria with comparatively higher weighted values. Whereas ‘accessibility and connectivity’ and ‘maternal death in transit’ were observed to have more imprint in entropy and CRITIC, respectively. While comparing the predictive suitable classes of these three models with the layer of existing hospitals, except Entropy-MAUT, the other two are pointing towards the left-over underserved areas of existing facilities. Only 43%-67% of existing hospitals were in the moderate to lower suitable class. Therefore, the results of the predictive models might bring valuable input in future planning.

Keywords: hospital site suitability, analytic hierarchy process, multi-attribute utility theory, entropy, criteria importance through interaction correlation, multi-criteria decision analysis

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Authors: Jitendra Sharma

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Here a Homogeneous Charge is used as in a spark-ignited engine, but the charge is compressed to auto ignition as in a diesel. The main difference compared with the Spark Ignition (SI) engine is the lack of flame propagation and hence the independence from turbulence. Compared with the diesel engine. HCCI has a homogeneous charge and have no problems associated with soot and Nox but HC and CO were higher than in SI mode. It was not possible to achieve high IMEP (Indicated Mean Effective Pressure) values with HCCI. The Homogeneous charge compression ignition (HCCI) is an attractive technology because of its high efficiency and low emissions. However, HCCI lakes a direct combustion trigger making control of combustion timing challenging, especially during transients. To aid in HCCI engine control we present a simple model of the HCCI combustion process valid over a range of intake pressures, intake temperatures, equivalence ratios and engine speeds. HCCI a new combustion technology that may develop as an alternative to diesel engines with high efficiency and low Knox and particulate matter emissions. The homogenous charge compression ignition (HCCI) is a promising new engine technology that combines elements of the diesel and gasoline engine operating cycles. HCCI as a way to increase the efficiency of the gasoline engine. The attractive properties are increased fuel efficiency due to reduced throttling losses, increased expansion ratio and higher thermodynamic efficiency. With the advantages there are some mechanical limitations to the operation of the HCCI engine. The implementation of homogenous charge compression ignition (HCCI) to gasoline engines is constrained by many factors. The main drawback of HCCI is the absence of direct combustion timing control. Therefore all the right conditions for auto ignition have to be set before combustion starts. This paper describes the past and current research done on HCCI engine. Many research got considerable success in doing detailed modeling of HCCI combustion. This paper aims at studying the fundamentals of HCCI combustion, the strategy to control the limitation of HCCI engine.

Keywords: HCCI, diesel engine, combustion, elementary investigation

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Authors: Asrat M.Belachew, Tiago Pereira, Institute of Mathematics, Computer Sciences, Avenida Trabalhador São Carlense, 400, São Carlos, 13566-590, Brazil

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Infectious diseases are among the most prominent threats to human beings. They cause morbidity and mortality to an individual and collapse the social, economic, and political systems of the whole world collectively. Mathematical models are fundamental tools and provide a comprehensive understanding of how infectious diseases spread and designing the control strategy to mitigate infectious diseases from the host population. Modeling the spread of infectious diseases using a compartmental model of inhomogeneous populations is good in terms of complexity. However, in the real world, there is a situation that accounts for heterogeneity, such as ages, locations, and contact patterns of the population which are ignored in a homogeneous setting. In this work, we study how classical an SEIR infectious disease spreading of the compartmental model can be extended by incorporating the mobility of population between heterogeneous cities during an outbreak of infectious disease. We have formulated an SEIR multi-cities epidemic spreading model using a system of 4k ordinary differential equations to describe the disease transmission dynamics in k-cities during the day and night. We have shownthat the model is epidemiologically (i.e., variables have biological interpretation) and mathematically (i.e., a unique bounded solution exists all the time) well-posed. We constructed the next-generation matrix (NGM) for the model and calculated the basic reproduction number R0for SEIR-epidemic spreading model with cities mobility. R0of the disease depends on the spectral radius mobility operator, and it is a threshold between asymptotic stability of the disease-free equilibrium and disease persistence. Using the eigenvalue perturbation theorem, we showed that sending a fraction of the population between cities decreases the reproduction number of diseases in interconnected cities. As a result, disease transmissiondecreases in the population.

Keywords: SEIR-model, mathematical model, city mobility, epidemic spreading

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Authors: Liliia N. Butymova, Vladimir Y. Modorsky, Nikolai A. Shevelev

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Prediction of vibration processes in gas transmittal units (GTU) is an urgent problem. Despite numerous scientific publications on the problem of vibrations in general, there are not enough works concerning FSI-modeling interaction processes between several deformable blades in gas-dynamic flow. Since it is very difficult to solve the problem in full scope, with all factors considered, a unidirectional dynamic coupled 1FSI model is suggested for use at the first stage, which would include, from symmetry considerations, two blades, which might be considered as the first stage of solving more general bidirectional problem. ANSYS CFX programmed multi-processor was chosen as a numerical computation tool. The problem was solved on PNRPU high-capacity computer complex. At the first stage of the study, blades were believed oscillating with the same frequency, although oscillation phases could be equal and could be different. At that non-stationary gas-dynamic forces distribution over the blades surfaces is calculated in run of simulation experiment. Oscillations in the “gas — structure” dynamic system are assumed to increase if the resultant of these gas-dynamic forces is in-phase with blade oscillation, and phase shift (φ=0). Provided these oscillation occur with phase shift, then oscillations might increase or decrease, depending on the phase shift value. The most important results are as follows: the angle of phase shift in inter-blade oscillation and the gas-dynamic force depends on the flow velocity, the specific inter-blade gap, and the shaft rotation speed; a phase shift in oscillation of adjacent blades does not always correspond to phase shift of gas-dynamic forces affecting the blades. Thus, it was discovered, that asynchronous oscillation of blades might cause either attenuation or intensification of oscillation. It was revealed that clocking effect might depend not only on the mutual circumferential displacement of blade rows and the gap between the blades, but also on the blade dynamic deformation nature.

Keywords: aeroelasticity, ANSYS CFX, oscillation, phase shift, clocking effect, vibrations

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Authors: Stephanie Wall, Guido Wimmers

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The construction and operation of buildings greatly contribute to environmental degradation through resource and energy consumption and greenhouse gas emissions. The design of the envelope system affects the environmental impact of a building in two major ways; 1) high thermal performance and air tightness can significantly reduce the operational energy of the building and 2) the material selection for the envelope largely impacts the embodied energy of the building. Life cycle assessment (LCA) is a scientific methodology that is used to systematically analyze the environmental load of processes or products, such as buildings, over their life. The paper will discuss the results of a comparative LCA of different envelope designs and the long-term monitoring of the Wood Innovation Research Lab (WIRL); a Passive House (PH), industrial building under construction in Prince George, Canada. The WIRL has a footprint of 30m x 30m on a concrete raft slab foundation and consists of shop space as well as a portion of the building that includes a two-story office/classroom space. The lab building goes beyond what was previously thought possible in regards to energy efficiency of industrial buildings in cold climates due to their large volume to surface ratio, small floor area, and high air change rate, and will be the first PH certified industrial building in Canada. These challenges were mitigated through the envelope design which utilizes solar gains while minimizing overheating, reduces thermal bridges with thick (570mm) prefabricated truss walls filled with blown in mineral wool insulation and a concrete slab and roof insulated with EPS rigid insulation. The envelope design results in lower operational and embodied energy when compared to buildings built to local codes or with steel. The LCA conducted using Athena Impact Estimator for Buildings identifies project specific hot spots as well illustrates that for high-efficiency buildings where the operational energy is relatively low; the embodied energy of the material selection becomes a significant design decision as it greatly impacts the overall environmental footprint of the building. The results of the LCA will be reinforced by long-term monitoring of the buildings envelope performance through the installation of temperature and humidity sensors throughout the floor slab, wall and roof panels and through detailed metering of the energy consumption. The data collected from the sensors will also be used to reinforce the results of hygrothermal analysis using WUFI®, a program used to verify the durability of the wall and roof panels. The WIRL provides an opportunity to showcase the use of wood in a high performance envelope of an industrial building and to emphasize the importance of considering the embodied energy of a material in the early stages of design. The results of the LCA will be of interest to leading researchers and scientists committed to finding sustainable solutions for new construction and high-performance buildings.

Keywords: high performance envelope, life cycle assessment, long term monitoring, passive house, prefabricated panels

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Authors: Melkamu Tadesse Getachew

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Intelligent control systems have revolutionized biomedical engineering, advancing research and enhancing medical practice. This review paper examines the impact of intelligent control on various aspects of biomedical engineering. It analyzes how these systems enhance precision and accuracy in biomedical instrumentation, improving diagnostics, monitoring, and treatment. Integration challenges are addressed, and potential solutions are proposed. The paper also investigates the optimization of drug delivery systems through intelligent control. It explores how intelligent systems contribute to precise dosing, targeted drug release, and personalized medicine. Challenges related to controlled drug release and patient variability are discussed, along with potential avenues for overcoming them. The comparison of algorithms used in intelligent control systems in biomedical control is also reviewed. The implications of intelligent control in computational and systems biology are explored, showcasing how these systems enable enhanced analysis and prediction of complex biological processes. Challenges such as interpretability, human-machine interaction, and machine reliability are examined, along with potential solutions. Intelligent control in biomedical engineering also plays a crucial role in risk management during surgical operations. This section demonstrates how intelligent systems improve patient safety and surgical outcomes when integrated into surgical robots, augmented reality, and preoperative planning. The challenges associated with these implementations and potential solutions are discussed in detail. In summary, this review paper comprehensively explores the widespread impact of intelligent control on biomedical engineering, showing the future of human health issues promising. It discusses application areas, challenges, and potential solutions, highlighting the transformative potential of these systems in advancing research and improving medical practice.

Keywords: Intelligent control systems, biomedical instrumentation, drug delivery systems, robotic surgical instruments, Computational monitoring and modeling

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Authors: Suleyman Karabal, Timothy L. Burnett, Egemen Avcu, Andrew H. Sherry, Philip J. Withers

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SA508 Grade 3 steel is widely used in the construction of nuclear pressure vessels, where its fracture toughness plays a critical role in ensuring operational safety and reliability. Understanding the ductile failure mechanisms in this steel grade is crucial for designing robust pressure vessels that can withstand severe nuclear environment conditions. In the present study, round bar specimens of SA508 Grade 3 steel with four distinct notch geometries were subjected to tensile loading while capturing continuous 2D images at 5-second intervals in order to monitor any alterations in their geometries to construct true stress-strain curves of the specimens. 3D reconstructions of X-ray computed tomography (CT) images at high-resolution (a spatial resolution of 0.82 μm) allowed for a comprehensive assessment of the influences of second-phase particles (i.e., manganese sulfide inclusions and cementite particles) on ductile failure initiation as a function of applied plastic strain. Additionally, based on 2D and 3D images, plasticity modeling was executed, and the results were compared to experimental data. A specific ‘two-parameter criterion’ was established and calibrated based on the correlation between stress triaxiality and equivalent plastic strain at failure initiation. The proposed criterion demonstrated substantial agreement with the experimental results, thus enhancing our knowledge of ductile fracture behavior in this steel grade. The implementation of X-ray CT and fractography analysis provided new insights into the diverse roles played by different populations of second-phase particles in fracture initiation under varying stress triaxiality conditions.

Keywords: ductile fracture, two-parameter criterion, x-ray computed tomography, stress triaxiality

Procedia PDF Downloads 71

Authors: M. S. Jouini, A. Al-Sumaiti, M. Tembely, K. Rahimov

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Characterizing rock properties of carbonate reservoirs is highly challenging because of rock heterogeneities revealed at several length scales. In the last two decades, the Digital Rock Physics (DRP) approach was implemented successfully in sandstone rocks reservoirs in order to understand rock properties behaviour at the pore scale. This approach uses 3D X-ray Microtomography images to characterize pore network and also simulate rock properties from these images. Even though, DRP is able to predict realistic rock properties results in sandstone reservoirs it is still suffering from a lack of clear workflow in carbonate rocks. The main challenge is the integration of properties simulated at different scales in order to obtain the effective rock property of core plugs. In this paper, we propose several approaches to characterize absolute permeability in some carbonate core plugs samples using multi-scale numerical simulation workflow. In this study, we propose a procedure to simulate porosity and absolute permeability of a carbonate rock sample using textures of Micro-Computed Tomography images. First, we discretize X-Ray Micro-CT image into a regular grid. Then, we use a textural parametric model to classify each cell of the grid using supervised classification. The main parameters are first and second order statistics such as mean, variance, range and autocorrelations computed from sub-bands obtained after wavelet decomposition. Furthermore, we fill permeability property in each cell using two strategies based on numerical simulation values obtained locally on subsets. Finally, we simulate numerically the effective permeability using Darcy’s law simulator. Results obtained for studied carbonate sample shows good agreement with the experimental property.

Keywords: multiscale modeling, permeability, texture, micro-tomography images

Procedia PDF Downloads 169

Authors: Meera Shanker

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Excellent education and financial need have encouraged Indian women to go out and work in well-paid and high-status occupations. In the era of cutthroat competition, women are expected to work hard to produce the desired result; hence, workload and expectations haveincreased. At home, they are anticipated to take care of family members, children, and household work. Women are stretching themselves mechanically to remain in the job competition and try to give their best at home. Consequentially, they are under tremendous pressure, stressed, and having issues related to physical-mental wellness. Mental healthcare is often ignored and not accepted due to a lack of awareness and cultural barriers. These further compounds the problem, resulting in decreased productivity in economic terms and an increase in stress-related physical-mental ailments. The main objective of the study was to find out the impact of stress on the physical-mental wellbeing of working women in India, along with their awareness and acceptability related to mental health. Six hundred and one woman working at various levels took part in this study, responding to the items related to stress and physical-mental illness. Finally, 21 items were retained under four meaningful factors measuring stress dimensions along with 17 items with three factors measuring physical-mental wellbeing. Confirmatory Factor Analysis (CFA), path analysis, in Structural Equation Modeling (SEM), was used to get a relationship, validity of the instruments. The psychometric properties of items and Cronbach’s Alpha reliabilities calculated for the subscales were relatively acceptable. The subscale correlations, regression, and path analysis of stress dimensions with physical-mental illness were found to be positive, indicating the growing stress among working women in India, which is impacting their physical-mental health. Single item analysis revealed that 77 percent of women have never visited psychologists. However, 70 percent of working women were not ready to seek the help of a psychologist.

Keywords: working women, stress, physical-mental well-being, confirmatory factor analysis

Procedia PDF Downloads 168

Authors: Mohammed Abu Shquier

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This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

Procedia PDF Downloads 22

Authors: Said Moqeem Sadat, Saito Takahiro, Inuzuka Norikazu, Sugiyama Ikuo

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Kabul city is the capital of Afghanistan with a population of about 4.0 million in 2009 and 6.5 million in 2025. It is geographically located in a narrow plain valley along the Kabul River and is surrounded by high mountains. Due to its sharp geological condition, the city has been suffering from floods caused by storm water and snow melting water in the rainy season. Meanwhile, potable water resources are becoming a critical issue as the underground water table is decreasing falling rapidly due to domestic usage, industrial and agricultural activities usage especially in the dry season. This paper focuses on flood water management in Kabul including suburban agricultural area considering not only for flood protection but also: 1. To reserve the quality underground water for the future population growth. 2. To irrigate farming area in dry season using storm water ponds in rainy season. 3. To discharge city contaminated flood water to the downstream safely using existing channels/new pipes. Cost and benefit is considered in this study to find out a suitable flood protection method both in rural area and city center from a view point of 1 to 3 mentioned above. In this analysis, cost mainly consists of lost opportunity to develop lands due to flood ponds in addition to construction and maintenance one including connecting channels for water collecting/discharging. Benefit mainly consists of damage reduction of flood loss due to counter measures (this is corresponding cost) in addition to the contribution to agricultural crops. As far as reservation of the ground water for the future city growth is concerned, future demand and supply are compared in case that the pumping amount is limited by this irrigation system.

Keywords: cost-benefit, hydrological modeling, water management, water quality

Procedia PDF Downloads 254

Authors: Eric York, James Tadio, Silas Owusu Antwi

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Laundry wastewater contains a diverse range of chemical pollutants that can have detrimental effects on human health and the environment. In this study, simulation studies by Spyder Python software v 3.2 to assess the efficacy of biochar in removing PO₄³⁻ from wastewater were conducted. Through modeling and simulation, the mechanisms involved in the adsorption process of phosphate by biochar were studied by altering variables which is specific to the phosphate from common laundry phosphate detergents, such as the aqueous solubility, initial concentration, and temperature using the Dudinin Approach (DA). Results showed that the concentration equilibrate at near the highest concentrations for Sugar beet-120 mgL⁻¹, Tailing-85 mgL⁻¹, CaO- rich-50 mgL⁻¹, Eggshell and rice straw-48 mgL⁻¹, Undaria Pinnatifida Roots-190 mgL⁻¹, Ca-Alginate Granular Beads -240 mgL⁻¹, Laminaria Japonica Powder -900 mgL⁻¹, Pinesaw dust-57 mgL⁻¹, Ricehull-190 mgL⁻¹, sesame straw- 470 mgL⁻¹, Sugar Bagasse-380 mgL⁻¹, Miscanthus Giganteus-240 mgL⁻¹, Wood Bc-130 mgL⁻¹, Pine-25 mgL⁻¹, Sawdust-6.8 mgL⁻¹, Sewage Sludge-, Rice husk-12 mgL⁻¹, Corncob-117 mgL⁻¹, Maize straw- 1800 mgL⁻¹ while Peanut -Eucalyptus polybractea-, Crawfish equilibrated at near concentration. CO₂ activated Thalia, sewage sludge biochar, Broussonetia Papyrifera Leaves equilibrated just at the lower concentration. Only Soyer bean Stover exhibited a sharp rise and fall peak in mid-concentration at 2 mgL⁻¹ volume. The modelling results were consistent with experimental findings from the literature, ensuring the accuracy, repeatability, and reliability of the simulation study. The simulation study provided insights into adsorption for PO₄³⁻ from wastewater by biochar using concentration per volume that can be adsorbed ideally under the given conditions. Studies showed that applying the principle experimentally in real wastewater with all its complexity is warranted and not far-fetched.

Keywords: simulation studies, phosphate removal, biochar, adsorption, wastewater treatment

Procedia PDF Downloads 96

Authors: Ganbat Danaa, Chuluundorj Puntsag

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The steel structures of the Oyu-Tolgoi mining Concentrator plant are corroded during operation, which raises doubts about the continued use of some important structures of the plant, which is one of the problems facing the plant's regular operation. As a part of the main operation of the plant, the bottom part of the pressure vessel, which plays an important role in the reliable operation of the concentrate filter-drying unit, was heavily corroded, so it was necessary to study by engineering calculations, modeling, and simulation using modern advanced engineering programs and methods. The purpose of this research is to investigate whether the corroded part of the pressure vessel can be used normally in the future using advanced engineering software and to predetermine the remaining life of the time of the pressure vessel based on engineering calculations. When the thickness of the bottom part of the pressure vessel was thinned by 0.5mm due to corrosion detected by non-destructive testing, finite element analysis using ANSYS WorkBench software was used to determine the mechanical stress, strain and safety factor in the wall and bottom of the pressure vessel operating under 2.2 MPa working pressure, made conclusions on whether it can be used in the future. According to the recommendations, by using sand-blast cleaning and anti-corrosion paint, the normal, continuous and reliable operation of the Concentrator plant can be ensured, such as ordering new pressure vessels and reducing the installation period. By completing this research work, it will be used as a benchmark for assessing the corrosion condition of steel parts of pressure vessels and other metallic and non-metallic structures operating under severe conditions of corrosion, static and dynamic loads, and other deformed steels to make analysis of the structures and make it possible to evaluate and control the integrity and reliable operation of the structures.

Keywords: corrosion, non-destructive testing, finite element analysis, safety factor, structural reliability

Procedia PDF Downloads 39

Authors: Yaxin Bi, Peter Nicholl

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The rapid advancement of Information and communication technologies (ICT) is extremely influencing every aspect of Higher Education. It has transformed traditional teaching, learning, assessment and feedback into a new era of Digital Education. This also introduces many challenges in capturing and understanding student engagement with their studies in Higher Education. The School of Computing at Ulster University has developed a Feedback And Notification (FAN) Online tool that has been used to send students links to personalized feedback on their submitted assessments and record students’ frequency of review of the shared feedback as well as the speed of collection. The feedback that the students initially receive is via a personal email directing them through to the feedback via a URL link that maps to the feedback created by the academic marker. This feedback is typically a Word or PDF report including comments and the final mark for the work submitted approximately three weeks before. When the student clicks on the link, the student’s personal feedback is viewable in the browser and they can view the contents. The FAN tool provides the academic marker with a report that includes when and how often a student viewed the feedback via the link. This paper presents an investigation into student engagement through analyzing the interaction timestamps and frequency of review by the student. We have proposed an approach to modeling interaction timestamps and use sentiment classification techniques to analyze the data collected over the last five years for a set of modules. The data studied is across a number of final years and second-year modules in the School of Computing. The paper presents the details of quantitative analysis methods and describes further their interactions with the feedback overtime on each module studied. We have projected the students into different groups of engagement based on sentiment analysis results and then provide a suggestion of early targeted intervention for the set of students seen to be under-performing via our proposed model.

Keywords: feedback, engagement, interaction modelling, sentiment analysis

Procedia PDF Downloads 85

Authors: Anastasios Manos, Despina Elisabeth Filippidou

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Introduction: Historical buildings are an inte-gral part of the cultural heritage of every place, and beyond the obvious need for protection against risks, they have specific requirements regarding the handling of hazards and disasters such as fire, floods, earthquakes, etc. Ensuring high levels of protection and safety for these buildings is impera-tive for two distinct but interconnected reasons: a) they themselves constitute cultural heritage, and b) they are often used as museums/cultural spaces, necessitating the protection of both human life (vis-itors and workers) and the cultural treasures they house. However, these buildings present serious constraints in implementing the necessary measures to protect them from destruction due to their unique architecture, construction methods, and/or the structural materials used in the past, which have created an existing condition that is sometimes challenging to reshape and operate within the framework of modern regulations and protection measures. One of the most devastating risks that threaten historical buildings is fire. Catastrophic fires demonstrate the need for timely evaluation of fire safety measures in historical buildings. Recog-nizing the criticality of protecting historical build-ings from the risk of fire, the Confederation of Fire Protection Associations in Europe (CFPA E) issued specific guidelines in 2013 (CFPA-E Guideline No 30:2013 F) for the fire protection of historical buildings at the European level. However, until now, few actions have been implemented towards leveraging modern technologies in the field of con-struction and maintenance of buildings, such as Building Information Modeling (BIM) and the Inter-net of Things (IoT), for the protection of historical buildings from risks like fires, floods, etc. The pro-ject BIM4Cult has bee developed in order to fill this gap. It is a tool for timely assessing and monitoring of the fire safety level of historical buildings using BIM and IoT technologies in an integrated manner. The tool serves as a decision support expert system for improving the fire safety of historical buildings by continuously monitoring, controlling and as-sessing critical risk factors for fire.

Keywords: Iot, fire, BIM, expert system

Procedia PDF Downloads 49

Authors: Zainab Olabisi Tairu

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The human species is facing some of the most challenging issues encountered as civilization and development occurs. The most salient factors threatening all species globally are habitats loss and degradation, overexploitation, competition with unwanted invasive species, pollution, global climate and various individual lifestyles of indigenous species. In order to avoid or minimize the effect of our actions on the environment and to balance employee work life with their private life, Green Human Resource is important and must be practiced in every organization including Higher Learning Institutions. This study addressed Green HRM from an institutional perspective, University systems are involved in numerous and complex social, educational and extra-curricular activities. The University community must be challenged to rethink and re-construct their environmental policies and practices in order to contribute to sustainable development. Many institutions only look at sustainability from the technology improvement aspect and waste management. People are the principal actors for sustainability development at the institutional level. The aim of the study is to explore the concept of Green Human Resource Management at a case site. Divine Word University (DWU) an Institution of Higher Education that embraced the ‘Printing & Paper use Policy’, also commonly referred to as the ‘paperless policy’, the use of solar as an alternative source of energy, water conservation and improvement in internet technology (IT) with the aim of becoming a green institution in effort to help save the environment. This study used Participatory Action Research as the Overarching methodological framework and Egg of sustainability and Wellbeing as the theoretical perspective in analyzing the data, engaging Case study strategy and a mixed method design at DWU. Focus group interview were conducted with three departments at the University, semi-structure interviews with the senior managers, survey questionnaire administered to students and staff with a sample size of 176 participants, in addition, policy documents were also exploited as extra source of data. Waste management including e-waste appeared to be one of the main concerns at DWU. A vast majority of DWU staff and students expressed the need for their institution to do more on sustainability education. The findings revealed that members of the community are not fully integrated like the Egg of sustainability and wellbeing in order to achieve sustainable development goal. The concept of Green Human Resource Management in Universities lies with the idea that Universities must bear profound responsibilities to manage its stakeholders in an environmental friendly way. Human resource management can help local institutions to recognize the need for changes of lifestyle, production, consumption as well as the end product in order to combat or at least reduce human Induced which produce or aggravate it.

Keywords: sustainability, environmental management, higher education institutions, green human resource management

Procedia PDF Downloads 226

Authors: Filip Varga, Nina Jeran, Martina Biosic, Zlatko Satovic, Martina Grdisa

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Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir./ Sch. Bip.), a species endemic to the eastern Adriatic coastline, is the source of natural insecticide pyrethrin. Pyrethrin is a mixture of six compounds (pyrethrin I and II, cinerin I and II, jasmolin I and II) that exhibits high insecticidal activity with no detrimental effects to the environment. A recently optimized matrix-solid phase dispersion method (MSPD), using florisil as the sorbent, acetone-ethyl acetate (1:1, v/v) as the elution solvent, and sodium sulfate anhydrous as the drying agent was utilized to extract the pyrethrins from 10 wild populations (20 individuals per population) distributed along the Croatian coast. All six components in the extracts were qualitatively and quantitatively determined by high-performance liquid chromatography with a diode array detector (HPLC-DAD). Pearson’s correlation index was calculated between pyrethrin compounds, and differences between the populations using the analysis of variance were tested. Additionally, the correlation of each pyrethrin component with spatio-ecological variables (bioclimate, soil properties, elevation, solar radiation, and distance from the coastline) was calculated. Total pyrethrin content ranged from 0.10% to 1.35% of dry flower weight, averaging 0.58% across all individuals. Analysis of variance revealed significant differences between populations based on all six pyrethrin compounds and total pyrethrin content. On average, the lowest total pyrethrin content was found in the population from Pelješac peninsula (0.22% of dry flower weight) in which total pyrethrin content lower than 0.18% was detected in 55% of the individuals. The highest average total pyrethrin content was observed in the population from island Zlarin (0.87% of dry flower weight), in which total pyrethrin content higher than 1.00% was recorded in only 30% of the individuals. Pyrethrin I/pyrethrin II ratio as a measure of extract quality ranged from 0.21 (population from the island Čiovo) to 5.88 (population from island Mali Lošinj) with an average of 1.77 across all individuals. By far, the lowest quality of extracts was found in the population from Mt. Biokovo (pyrethrin I/II ratio lower than 0.72 in 40% of individuals) due to the high pyrethrin II content typical for this population. Pearson’s correlation index revealed a highly significant positive correlation between pyrethrin I content and total pyrethrin content and a strong negative correlation between pyrethrin I and pyrethrin II. The results of this research clearly indicate high intra- and interpopulation diversity of Dalmatian pyrethrum with regards to pyrethrin content and composition. The information obtained has potential use in plant genetic resources conservation and biodiversity monitoring. Possibly the largest potential lies in designing breeding programs aimed at increasing pyrethrin content in commercial breeding lines and reintroduction in agriculture in Croatia. Acknowledgment: This work has been fully supported by the Croatian Science Foundation under the project ‘Genetic background of Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir/ Sch. Bip.) insecticidal potential’ - (PyrDiv) (IP-06-2016-9034).

Keywords: Dalmatian pyrethrum, HPLC, MSPD, pyrethrin

Procedia PDF Downloads 122

Authors: Jacob Seddlemeyer, Tahar Messadi, Hongmei Gu, Mahboobeh Hemmati

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The main purpose of this first tier of the study is to quantify and compare the embodied environmental impacts associated with alternative materials applied to Adohi Hall, a residence building at the University of Arkansas campus, Fayetteville, AR. This 200,000square foot building has5 stories builtwith mass timber and is compared to another scenario where the same edifice is built with a steel frame. Based on the defined goal and scope of the project, the materials respectivetothe respective to the two building options are compared in terms of Global Warming Potential (GWP), starting from cradle to the construction site, which includes the material manufacturing stage (raw material extract, process, supply, transport, and manufacture) plus transportation to the site (module A1-A4, based on standard EN 15804 definition). The consumedfossil fuels and emitted CO2 associated with the buildings are the major reason for the environmental impacts of climate change. In this study, GWP is primarily assessed to the exclusion of other environmental factors. The second tier of this work is to evaluate Tally’s performance in the decision-making process through the design phases, as well as determine its strengths and weaknesses. Tally is a Life Cycle Assessment (LCA) tool capable of conducting a cradle-to-grave analysis. As opposed to other software applications, Tally is specifically targeted at buildings LCA. As a peripheral application, this software tool is directly run within the core modeling application platform called Revit. This unique functionality causes Tally to stand out from other similar tools in the building sector LCA analysis. The results of this study also provide insights for making more environmentally efficient decisions in the building environment and help in the move forward to reduce Green House Gases (GHGs) emissions and GWP mitigation.

Keywords: comparison, GWP, LCA, materials, tally

Procedia PDF Downloads 208