Search results for: emission modeling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5254

Search results for: emission modeling

1414 Failure Analysis of Khaliqabad Landslide along Mangla Reservoir Rim

Authors: Fatima Mehmood, Khalid Farooq

Abstract:

After the Mangla dam raising in 2010, the maximum reservoir impoundment level of 378.5 m SPD (Survey of Pakistan Datum) was achieved in September 2014. The reservoir drawdown was started on September 29, 2014 and a landslide occurred on Mirpur-Kotli Road near Khaliqabad on November 27, 2014. This landslide took place due to the failure of a slope along the reservoir rim. This study was undertaken to investigate the causative factors of Khaliqabad landslide. Site visits were carried out for recording the field observations and collection of the soil samples. The soil was subjected to different laboratory tests for the determination of index and engineering properties. The shear strength tests were performed at various levels of density and degrees of saturation. These soil parameters were used in an integrated SEEP-SLOPE/W analysis to obtain the drop in factor of safety with time and reservoir drawdown. The results showed the factor of safety dropped from 1.28 to 0.85 over a period of 60 days. The ultimate reduction in the shear strength of soil due to saturation with the simultaneous removal of the stabilizing effect of reservoir caused the disturbing forces to increase, and thus failure happened. The findings of this study can serve as a guideline for the modeling of the slopes experiencing rapid drawdown scenario with the consideration of more realistic distribution of soil moisture/ properties across the slope

Keywords: geotechnical investigation, landslide, reservoir drawdown, shear strength, slope stability

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1413 Electric Arc Furnaces as a Source of Voltage Fluctuations in the Power System

Authors: Zbigniew Olczykowski

Abstract:

The paper presents the impact of work on the electric arc furnace power grid. The arc furnace operating will be modeled at different power conditions of steelworks. The paper will describe how to determine the increase in voltage fluctuations caused by working in parallel arc furnaces. The analysis of indicators characterizing the quality of electricity recorded during several cycles of measurement made at the same time at three points grid, with different power and different short-circuit rated voltage, will be carried out. The measurements analysis presented in this paper were conducted in the mains of one of the Polish steel. The indicators characterizing the quality of electricity was recorded during several cycles of measurement while making measurements at three points of different power network short-circuit power and various voltage ratings. Measurements of power quality indices included the one-week measurement cycles in accordance with the EN-50160. Data analysis will include the results obtained during the simultaneous measurement of three-point grid. This will determine the actual propagation of interference generated by the device. Based on the model studies and measurements of quality indices of electricity we will establish the effect of a specific arc on the mains. The short-circuit power network’s minimum value will also be estimated, this is necessary to limit the voltage fluctuations generated by arc furnaces.

Keywords: arc furnaces, long-term flicker, measurement and modeling of power quality, voltage fluctuations

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1412 Analytical and Numerical Investigation of Friction-Restricted Growth and Buckling of Elastic Fibers

Authors: Peter L. Varkonyi, Andras A. Sipos

Abstract:

The quasi-static growth of elastic fibers is studied in the presence of distributed contact with an immobile surface, subject to isotropic dry or viscous friction. Unlike classical problems of elastic stability modelled by autonomous dynamical systems with multiple time scales (slowly varying bifurcation parameter, and fast system dynamics), this problem can only be formulated as a non-autonomous system without time scale separation. It is found that the fibers initially converge to a trivial, straight configuration, which is later replaced by divergence reminiscent of buckling phenomena. In order to capture the loss of stability, a new definition of exponential stability against infinitesimal perturbations for systems defined over finite time intervals is developed. A semi-analytical method for the determination of the critical length based on eigenvalue analysis is proposed. The post-critical behavior of the fibers is studied numerically by using variational methods. The emerging post-critical shapes and the asymptotic behavior as length goes to infinity are identified for simple spatial distributions of growth. Comparison with physical experiments indicates reasonable accuracy of the theoretical model. Some applications from modeling plant root growth to the design of soft manipulators in robotics are briefly discussed.

Keywords: buckling, elastica, friction, growth

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1411 Hydrological Modelling to Identify Critical Erosion Areas in Gheshlagh Dam Basin

Authors: Golaleh Ghaffari

Abstract:

A basin sediment yield refers to the amount of sediment exported by a basin over a period of time, which will enter a reservoir located at the downstream limit of the basin. The Soil and Water Assessment Tool (SWAT, 2008) was used to hydrology and sediment transport modeling at daily and monthly time steps within the Gheshlagh dam basin in north-west of Iran. The SWAT model and Geographic Information System (GIS) techniques were applied to evaluate basin hydrology and sediment yield using historical flow and sediment data and to identify and prioritize critical sub-basins based on sediment transport. The results of this study indicated that simulated daily discharge and sediment values matched the observed values satisfactorily. The model predicted that mean annual basin precipitation for the total study period (413 mm) was partitioned in to evapotranspiration (36%), percolation/groundwater recharge (21%) and stream water (25%), yielding 18% surface runoff. Potential source areas of erosion were also identified with the model. The range of the annual contributing erosive zones varied spatially from 0.1 to 103 t/ha according to the slope and land use at the basin scale. Also the fifteen sub basins create the 60% of the total sediment yield between the all (102) sub basins. The results of the study indicated that SWAT can be a useful tool for assessing hydrology and sediment yield response of the watersheds in the region.

Keywords: erosion, Gheshlagh dam, sediment yield, SWAT

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1410 Estimation of Residual Stresses in Thick Walled Cylinder by Radial Basis Artificial Neural

Authors: Mohammad Heidari

Abstract:

In this paper a method for high strength steel is proposed of residual stresses in autofrettaged tubes by combination of artificial neural networks is presented. Many different thick walled cylinders that were subjected to different conditions were studied. At first, the residual stress is calculated by analytical solution. Then by changing of the parameters that influenced in residual stresses such as percentage of autofrettage, internal pressure, wall ratio of cylinder, material property of cylinder, bauschinger and hardening effect factor, a neural network is created. These parameters are the input of network. The output of network is residual stress. Numerical data, employed for training the network and capabilities of the model in predicting the residual stress has been verified. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 2.75% in predicting residual stress of thick wall cylinder. Further analysis of residual stress of thick wall cylinder under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach.

Keywords: thick walled cylinder, residual stress, radial basis, artificial neural network

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1409 Modeling Factors Affecting Fertility Transition in Africa: Case of Kenya

Authors: Dennis Okora Amima Ondieki

Abstract:

Fertility transition has been identified to be affected by numerous factors. This research aimed to investigate the most real factors affecting fertility transition in Kenya. These factors were firstly extracted from the literature convened into demographic features, social, and economic features, social-cultural features, reproductive features and modernization features. All these factors had 23 factors identified for this study. The data for this study was from the Kenya Demographic and Health Surveys (KDHS) conducted in 1999-2003 and 2003-2008/9. The data was continuous, and it involved the mean birth order for the ten periods. Principal component analysis (PCA) was utilized using 23 factors. Principal component analysis conveyed religion, region, education and marital status as the real factors. PC scores were calculated for every point. The identified principal components were utilized as forecasters in the multiple regression model, with the fertility level as the response variable. The four components were found to be affecting fertility transition differently. It was found that fertility is affected positively by factors of region and marital and negatively by factors of religion and education. These four factors can be considered in the planning policy in Kenya and Africa at large.

Keywords: fertility transition, principal component analysis, Kenya demographic health survey, birth order

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1408 Feasibility of Small Autonomous Solar-Powered Water Desalination Units for Arid Regions

Authors: Mohamed Ahmed M. Azab

Abstract:

The shortage of fresh water is a major problem in several areas of the world such as arid regions and coastal zones in several countries of Arabian Gulf. Fortunately, arid regions are exposed to high levels of solar irradiation most the year, which makes the utilization of solar energy a promising solution to such problem with zero harmful emission (Green System). The main objective of this work is to conduct a feasibility study of utilizing small autonomous water desalination units powered by photovoltaic modules as a green renewable energy resource to be employed in different isolated zones as a source of drinking water for some scattered societies where the installation of huge desalination stations are discarded owing to the unavailability of electric grid. Yanbu City is chosen as a case study where the Renewable Energy Center exists and equipped with all sensors to assess the availability of solar energy all over the year. The study included two types of available water: the first type is brackish well water and the second type is seawater of coastal regions. In the case of well water, two versions of desalination units are involved in the study: the first version is based on day operation only. While the second version takes into consideration night operation also, which requires energy storage system as batteries to provide the necessary electric power at night. According to the feasibility study results, it is found that utilization of small autonomous desalinations unit is applicable and economically accepted in the case of brackish well water. While in the case of seawater the capital costs are extremely high and the cost of desalinated water will not be economically feasible unless governmental subsidies are provided. In addition, the study indicated that, for the same water production, the utilization of energy storage version (day-night) adds additional capital cost for batteries, and extra running cost for their replacement, which makes the unit price not only incompetent with day-only unit but also with conventional units powered by diesel generator (fossil fuel) owing to the low prices of fuel in the kingdom. However, the cost analysis shows that the price of the produced water per cubic meter of day-night unit is similar to that produced from the day-only unit provided that the day-night unit operates theoretically for a longer period of 50%.

Keywords: solar energy, water desalination, reverse osmosis, arid regions

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1407 Numerical Simulations on the Torsional Behavior of Multistory Concrete Masonry Buildings

Authors: Alvaro Jose Cordova, Hsuan Teh Hu

Abstract:

The use of concrete masonry constructions in developing countries has become very frequent, especially for domestic purpose. Most of them with asymmetric wall configurations in plan resulting in significant torsional actions when subjected to seismic loads. The study consisted on the finding of a material model for hollow unreinforced concrete masonry and a validation with experimental data found in literature. Numerical simulations were performed to 20 buildings with variations in wall distributions and heights. Results were analyzed by inspection and with a non-linear static method. The findings revealed that eccentricities as well as structure rigidities have a strong influence on the overall response of concrete masonry buildings. In addition, slab rotations depicted more accurate information about the torsional behavior than maximum versus average displacement ratios. The failure modes in low buildings were characterized by high tensile strains in the first floor. Whereas in tall buildings these strains were lowered significantly by higher compression stresses due to a higher self-weight. These tall buildings developed multiple plastic hinges along the height. Finally, the non-linear static analysis exposed a brittle response for all masonry assemblies. This type of behavior is undesired in any construction and the need for a material model for reinforced masonry is pointed out.

Keywords: concrete damaged plasticity, concrete masonry, macro-modeling, nonlinear static analysis, torsional capacity

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1406 [Keynote Talk]: The Challenges and Solutions for Developing Mobile Apps in a Small University

Authors: Greg Turner, Bin Lu, Cheer-Sun Yang

Abstract:

As computing technology advances, smartphone applications can assist in student learning in a pervasive way. For example, the idea of using a mobile apps for the PA Common Trees, Pests, Pathogens, in the field as a reference tool allows middle school students to learn about trees and associated pests/pathogens without bringing a textbook. In the past, some researches study the mobile software Mobile Application Software Development Life Cycle (MADLC) including traditional models such as the waterfall model, or more recent Agile Methods. Others study the issues related to the software development process. Very little research is on the development of three heterogenous mobile systems simultaneously in a small university where the availability of developers is an issue. In this paper, we propose to use a hybride model of Waterfall Model and the Agile Model, known as the Relay Race Methodology (RRM) in practice, to reflect the concept of racing and relaying for scheduling. Based on the development project, we observe that the modeling of the transition between any two phases is manifested naturally. Thus, we claim that the RRM model can provide a de fecto rather than a de jure basis for the core concept in the MADLC. In this paper, the background of the project is introduced first. Then, the challenges are pointed out followed by our solutions. Finally, the experiences learned and the future work are presented.

Keywords: agile methods, mobile apps, software process model, waterfall model

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1405 Machine Learning Algorithms for Rocket Propulsion

Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

Abstract:

In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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1404 Effects of Transformational Leadership and Political Competition on Corporate Performance of Nigeria National Petroleum Corporation

Authors: Justine Ugochukwu Osuagwu, Sazali Abd Wahab

Abstract:

The performance and operation of NNPC have faced series of attacks by all stakeholders as many have observed lots of inefficiency not only on the part of the management but the staff. This has raised questions of whether their operations and performance are being seriously affected by lack of transformational leadership, and the political competition prevalent in the country. The author has applied the administrative leadership theory and institutional theory as a guide to this study and empirically relates such theories to the study. The study also has utilized the quantitative approach where questionnaires were distributed to 370 participants, and the correctly filled and returned questionnaires were used for the analysis using structural equation modeling. The path coefficient of transformational leadership to performance is strong and positive with β = 0.672; t-value = 14.245; p-value = 0.000. Also, the result found that political competition does not mediate the relationship between transformational leadership and performance of NNPC. (β = -0.008; t-value = -0.600; p- value > 0.05). However, the indirect path is all insignificant, meaning that transformational leadership has relationship with corporate performance.The study found that,while political competition does not serve as a mediator in the relationship between transformational leadership and corporate performance, these styles of leadership have a direct and positive impact on corporate performance. The direct relationship between transformational leadership and political competition was not discovered, despite the fact that political competition has a direct and significant impact, both positive and negative, on corporate performance. As a result, both political competition and transformational leadership have the potential to significantly alter corporate performance.

Keywords: performance, transformational leadership, political competition, corporation performance, Nigeria national petroleum corporation

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1403 Random Forest Classification for Population Segmentation

Authors: Regina Chua

Abstract:

To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

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1402 Experiments on Weakly-Supervised Learning on Imperfect Data

Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

Abstract:

Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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1401 Application of Computational Flow Dynamics (CFD) Analysis for Surge Inception and Propagation for Low Head Hydropower Projects

Authors: M. Mohsin Munir, Taimoor Ahmad, Javed Munir, Usman Rashid

Abstract:

Determination of maximum elevation of a flowing fluid due to sudden rejection of load in a hydropower facility is of great interest to hydraulic engineers to ensure safety of the hydraulic structures. Several mathematical models exist that employ one-dimensional modeling for the determination of surge but none of these perfectly simulate real-time circumstances. The paper envisages investigation of surge inception and propagation for a Low Head Hydropower project using Computational Fluid Dynamics (CFD) analysis on FLOW-3D software package. The fluid dynamic model utilizes its analysis for surge by employing Reynolds’ Averaged Navier-Stokes Equations (RANSE). The CFD model is designed for a case study at Taunsa hydropower Project in Pakistan. Various scenarios have run through the model keeping in view upstream boundary conditions. The prototype results were then compared with the results of physical model testing for the same scenarios. The results of the numerical model proved quite accurate coherence with the physical model testing and offers insight into phenomenon which are not apparent in physical model and shall be adopted in future for the similar low head projects limiting delays and cost incurred in the physical model testing.

Keywords: surge, FLOW-3D, numerical model, Taunsa, RANSE

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1400 Control Power in Doubly Fed Induction Generator Wind Turbine with SVM Control Inverter

Authors: Zerzouri Nora, Benalia Nadia, Bensiali Nadia

Abstract:

This paper presents a grid-connected wind power generation scheme using Doubly Fed Induction Generator (DFIG). This can supply power at constant voltage and constant frequency with the rotor speed varying. This makes it suitable for variable speed wind energy application. The DFIG system consists of wind turbine, asynchronous wound rotor induction generator, and inverter with Space Vector Modulation (SVM) controller. In which the stator is connected directly to the grid and the rotor winding is in interface with rotor converter and grid converter. The use of back-to-back SVM converter in the rotor circuit results in low distortion current, reactive power control and operate at variable speed. Mathematical modeling of the DFIG is done in order to analyze the performance of the systems and they are simulated using MATLAB. The simulation results for the system are obtained and hence it shows that the system can operate at variable speed with low harmonic current distortion. The objective is to track and extract maximum power from the wind energy system and transfer it to the grid for useful work.

Keywords: Doubly Fed Induction Generator, Wind Energy Conversion Systems, Space Vector Modulation, distortion harmonics

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1399 A Causal Model for Environmental Design of Residential Community for Elderly Well-Being in Thailand

Authors: Porntip Ruengtam

Abstract:

This article is an extension of previous research presenting the relevant factors related to environmental perceptions, residential community, and the design of a healing environment, which have effects on the well-being and requirements of Thai elderly. Research methodology began with observations and interviews in three case studies in terms of the management processes and environment design of similar existing projects in Thailand. The interview results were taken to summarize with related theories and literature. A questionnaire survey was designed for data collection to confirm the factors of requirements in a residential community intended for the Thai elderly. A structural equation model (SEM) was formulated to explain the cause-effect factors for the requirements of a residential community for Thai elderly. The research revealed that the requirements of a residential community for Thai elderly were classified into three groups when utilizing a technique for exploratory factor analysis. The factors were comprised of (1) requirements for general facilities and activities, (2) requirements for facilities related to health and security, and (3) requirements for facilities related to physical exercise in the residential community. The results from the SEM showed the background of elderly people had a direct effect on their requirements for a residential community from various aspects. The results should lead to the formulation of policies for design and management of residential communities for the elderly in order to enhance quality of life as well as both the physical and mental health of the Thai elderly.

Keywords: elderly, environmental design, residential community, structural equation modeling

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1398 Bayesian Analysis of Topp-Leone Generalized Exponential Distribution

Authors: Najrullah Khan, Athar Ali Khan

Abstract:

The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

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1397 Remote Sensing-Based Prediction of Asymptomatic Rice Blast Disease Using Hyperspectral Spectroradiometry and Spectral Sensitivity Analysis

Authors: Selvaprakash Ramalingam, Rabi N. Sahoo, Dharmendra Saraswat, A. Kumar, Rajeev Ranjan, Joydeep Mukerjee, Viswanathan Chinnasamy, K. K. Chaturvedi, Sanjeev Kumar

Abstract:

Rice is one of the most important staple food crops in the world. Among the various diseases that affect rice crops, rice blast is particularly significant, causing crop yield and economic losses. While the plant has defense mechanisms in place, such as chemical indicators (proteins, salicylic acid, jasmonic acid, ethylene, and azelaic acid) and resistance genes in certain varieties that can protect against diseases, susceptible varieties remain vulnerable to these fungal diseases. Early prediction of rice blast (RB) disease is crucial, but conventional techniques for early prediction are time-consuming and labor-intensive. Hyperspectral remote sensing techniques hold the potential to predict RB disease at its asymptomatic stage. In this study, we aimed to demonstrate the prediction of RB disease at the asymptomatic stage using non-imaging hyperspectral ASD spectroradiometer under controlled laboratory conditions. We applied statistical spectral discrimination theory to identify unknown spectra of M. Oryzae, the fungus responsible for rice blast disease. The infrared (IR) region was found to be significantly affected by RB disease. These changes may result in alterations in the absorption, reflection, or emission of infrared radiation by the affected plant tissues. Our research revealed that the protein spectrum in the IR region is impacted by RB disease. In our study, we identified strong correlations in the region (Amide group - I) around X 1064 nm and Y 1300 nm with the Lambda / Lambda derived spectra methods for protein detection. During the stages when the disease is developing, typically from day 3 to day 5, the plant's defense mechanisms are not as effective. This is especially true for the PB-1 variety of rice, which is highly susceptible to rice blast disease. Consequently, the proteins in the plant are adversely affected during this critical time. The spectral contour plot reveals the highly correlated spectral regions 1064 nm and Y 1300 nm associated with RB disease infection. Based on these spectral sensitivities, we developed new spectral disease indices for predicting different stages of disease emergence. The goal of this research is to lay the foundation for future UAV and satellite-based studies aimed at long-term monitoring of RB disease.

Keywords: rice blast, asymptomatic stage, spectral sensitivity, IR

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1396 Mapping of Renovation Potential in Rudersdal Municipality Based on a Sustainability Indicator Framework

Authors: Barbara Eschen Danielsen, Morten Niels Baxter, Per Sieverts Nielsen

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Europe is currently in an energy and climate crisis, which requires more sustainable solutions than what has been used to before. Europe uses 40% of its energy in buildings so there has come a significant focus on trying to find and commit to new initiatives to reduce energy consumption in buildings. The European Union has introduced a building standard in 2021 to be upheld by 2030. This new building standard requires a significant reduction of CO2 emissions from both privately and publicly owned buildings. The overall aim is to achieve a zero-emission building stock by 2050. EU is revising the Energy Performance of Buildings Directive (EPBD) as part of the “Fit for 55” package. It was adopted on March 14, 2023. The new directive’s main goal is to renovate the least energy-efficient homes in Europe. There will be a cost for the home owner with a renovation project, but there will also be an improvement in energy efficiency and, therefore, a cost reduction. After the implementation of the EU directive, many homeowners will have to focus their attention on how to make the most effective energy renovations of their homes. The new EU directive will affect almost one million Danish homes (30%), as they do not meet the newly implemented requirements for energy efficiency. The problem for this one mio homeowners is that it is not easy to decide which renovation project they should consider. The houses are build differently and there are many possible solutions. The main focus of this paper is to identify the most impactful solutions and evaluate their impact and evaluating them with a criteria based sustainability indicator framework. The result of the analysis give each homeowner an insight in the various renovation options, including both advantages and disadvantages with the aim of avoiding unnecessary costs and errors while minimizing their CO2 footprint. Given that the new EU directive impacts a significant number of home owners and their homes both in Denmark and the rest of the European Union it is crucial to clarify which renovations have the most environmental impact and most cost effective. We have evaluated the 10 most impactful solutions and evaluated their impact in an indicator framework which includes 9 indicators and covers economic, environmental as well as social factors. We have packaged the result of the analysis in three packages, the most cost effective (short term), the most cost effective (long-term) and the most sustainable. The results of the study secure transparency and thereby provides homeowners with a tool to help their decision-making. The analysis is based on mostly qualitative indicators, but it will be possible to evaluate most of the indicators quantitively in a future study.

Keywords: energy efficiency, building renovation, renovation solutions, building energy performance criteria

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1395 A Dynamic Cardiac Single Photon Emission Computer Tomography Using Conventional Gamma Camera to Estimate Coronary Flow Reserve

Authors: Maria Sciammarella, Uttam M. Shrestha, Youngho Seo, Grant T. Gullberg, Elias H. Botvinick

Abstract:

Background: Myocardial perfusion imaging (MPI) is typically performed with static imaging protocols and visually assessed for perfusion defects based on the relative intensity distribution. Dynamic cardiac SPECT, on the other hand, is a new imaging technique that is based on time varying information of radiotracer distribution, which permits quantification of myocardial blood flow (MBF). In this abstract, we report a progress and current status of dynamic cardiac SPECT using conventional gamma camera (Infinia Hawkeye 4, GE Healthcare) for estimation of myocardial blood flow and coronary flow reserve. Methods: A group of patients who had high risk of coronary artery disease was enrolled to evaluate our methodology. A low-dose/high-dose rest/pharmacologic-induced-stress protocol was implemented. A standard rest and a standard stress radionuclide dose of ⁹⁹ᵐTc-tetrofosmin (140 keV) was administered. The dynamic SPECT data for each patient were reconstructed using the standard 4-dimensional maximum likelihood expectation maximization (ML-EM) algorithm. Acquired data were used to estimate the myocardial blood flow (MBF). The correspondence between flow values in the main coronary vasculature with myocardial segments defined by the standardized myocardial segmentation and nomenclature were derived. The coronary flow reserve, CFR, was defined as the ratio of stress to rest MBF values. CFR values estimated with SPECT were also validated with dynamic PET. Results: The range of territorial MBF in LAD, RCA, and LCX was 0.44 ml/min/g to 3.81 ml/min/g. The MBF between estimated with PET and SPECT in the group of independent cohort of 7 patients showed statistically significant correlation, r = 0.71 (p < 0.001). But the corresponding CFR correlation was moderate r = 0.39 yet statistically significant (p = 0.037). The mean stress MBF value was significantly lower for angiographically abnormal than that for the normal (Normal Mean MBF = 2.49 ± 0.61, Abnormal Mean MBF = 1.43 ± 0. 0.62, P < .001). Conclusions: The visually assessed image findings in clinical SPECT are subjective, and may not reflect direct physiologic measures of coronary lesion. The MBF and CFR measured with dynamic SPECT are fully objective and available only with the data generated from the dynamic SPECT method. A quantitative approach such as measuring CFR using dynamic SPECT imaging is a better mode of diagnosing CAD than visual assessment of stress and rest images from static SPECT images Coronary Flow Reserve.

Keywords: dynamic SPECT, clinical SPECT/CT, selective coronary angiograph, ⁹⁹ᵐTc-Tetrofosmin

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1394 The Impact of Missense Mutation in Phosphatidylinositol Glycan Class A Associated to Paroxysmal Nocturnal Hemoglobinuria and Multiple Congenital Anomalies-Hypotonia-Seizures Syndrome 2: A Computational Study

Authors: Ashish Kumar Agrahari, Amit Kumar

Abstract:

Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal blood disorder that manifests with hemolytic anemia, thrombosis, and peripheral blood cytopenias. The disease is caused by the deficiency of two glycosylphosphatidylinositols (GPI)-anchored proteins (CD55 and CD59) in the hemopoietic stem cells. The deficiency of GPI-anchored proteins has been associated with the somatic mutations in phosphatidylinositol glycan class A (PIGA). However, the mutations that do not cause PNH is associated with the multiple congenital anomalies-hypotonia-seizures syndrome 2 (MCAHS2). To best of our knowledge, no computational study has been performed to explore the atomistic level impact of PIGA mutations on the structure and dynamics of the protein. In the current work, we are mainly interested to get insights into the molecular mechanism of PIGA mutations. In the initial step, we screened the most pathogenic mutations from the pool of publicly available mutations. Further, to get a better understanding, pathogenic mutations were mapped to the modeled structure and subjected to 50ns molecular dynamics simulation. Our computational study suggests that four mutations are highly vulnerable to altering the structural conformation and stability of the PIGA protein, which illustrates its association with PNH and MCAHS2 phenotype.

Keywords: homology modeling, molecular dynamics simulation, missense mutations PNH, MCAHS2, PIGA

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1393 Experimental Quantification and Modeling of Dissolved Gas during Hydrate Crystallization: CO₂ Hydrate Case

Authors: Amokrane Boufares, Elise Provost, Veronique Osswald, Pascal Clain, Anthony Delahaye, Laurence Fournaison, Didier Dalmazzone

Abstract:

Gas hydrates have long been considered as problematic for flow assurance in natural gas and oil transportation. On the other hand, they are now seen as future promising materials for various applications (i.e. desalination of seawater, natural gas and hydrogen storage, gas sequestration, gas combustion separation and cold storage and transport). Nonetheless, a better understanding of the crystallization mechanism of gas hydrate and of their formation kinetics is still needed for a better comprehension and control of the process. To that purpose, measuring the real-time evolution of the dissolved gas concentration in the aqueous phase during hydrate formation is required. In this work, CO₂ hydrates were formed in a stirred reactor equipped with an Attenuated Total Reflection (ATR) probe coupled to a Fourier Transform InfraRed (FTIR) spectroscopy analyzer. A method was first developed to continuously measure in-situ the CO₂ concentration in the liquid phase during solubilization, supersaturation, hydrate crystallization and dissociation steps. Thereafter, the measured concentration data were compared with those of equilibrium concentrations. It was observed that the equilibrium is instantly reached in the liquid phase due to the fast consumption of dissolved gas by the hydrate crystallization. Consequently, it was shown that hydrate crystallization kinetics is limited by the gas transfer at the gas-liquid interface. Finally, we noticed that the liquid-hydrate equilibrium during the hydrate crystallization is governed by the temperature of the experiment under the tested conditions.

Keywords: gas hydrate, dissolved gas, crystallization, infrared spectroscopy

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1392 Hybrid Hunger Games Search Optimization Based on the Neural Networks Approach Applied to UAVs

Authors: Nadia Samantha Zuñiga-Peña, Norberto Hernández-Romero, Omar Aguilar-Mejia, Salatiel García-Nava

Abstract:

Using unmanned aerial vehicles (UAVs) for load transport has gained significant importance in various sectors due to their ability to improve efficiency, reduce costs, and access hard-to-reach areas. Although UAVs offer numerous advantages for load transport, several complications and challenges must be addressed to exploit their potential fully. Complexity relays on UAVs are underactuated, non-linear systems with a high degree of coupling between their variables and are subject to forces with uncertainty. One of the biggest challenges is modeling and controlling the system formed by UAVs carrying a load. In order to solve the controller problem, in this work, a hybridization of Neural Network and Hunger Games Search (HGS) metaheuristic algorithm is developed and implemented to find the parameters of the Super Twisting Sliding Mode Controller for the 8 degrees of freedom model of UAV with payload. The optimized controller successfully tracks the UAV through the three-dimensional desired path, demonstrating the effectiveness of the proposed solution. A comparison of performance shows the superiority of the neural network HGS (NNHGS) over the HGS algorithm, minimizing the tracking error by 57.5 %.

Keywords: neural networks, hunger games search, super twisting sliding mode controller, UAVs.

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1391 Finite Element Modeling and Mechanical Properties of Aluminum Proceed by Equal Channel Angular Pressing Process

Authors: F. Al-Mufadi, F. Djavanroodi

Abstract:

During the last decade ultrafine grained (UFG) and nano-structured (NS) materials have experienced a rapid development. In this research work finite element analysis has been carried out to investigate the plastic strain distribution in equal channel angular process (ECAP). The magnitudes of standard deviation (S. D.) and inhomogeneity index (Ci) were compared for different ECAP passes. Verification of a three-dimensional finite element model was performed with experimental tests. Finally the mechanical property including impact energy of ultrafine grained pure commercially pure Aluminum produced by severe plastic deformation method has been examined. For this aim, equal channel angular pressing die with the channel angle, outer corner angle and channel diameter of 90°, 20° and 20 mm had been designed and manufactured. Commercial pure Aluminum billets were ECAPed up to four passes by route BC at the ambient temperature. The results indicated that there is a great improvement at the hardness measurement, yield strength and ultimate tensile strength after ECAP process. It is found that the magnitudes of HV reach 67 HV from 21 HV after the final stage of process. Also, about 330% and 285% enhancement at the YS and UTS values have been obtained after the fourth pass as compared to the as-received conditions, respectively. On the other hand, the elongation to failure and impact energy have been reduced by 23% and 50% after imposing four passes of ECAP process, respectively.

Keywords: SPD, ECAP, FEM, pure Al, mechanical properties

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1390 Influence of Valve Lift Timing on Producer Gas Combustion and Its Modeling Using Two-Stage Wiebe Function

Authors: M. Sreedhar Babu, Vishal Garg, S. B. Akella, Shibu Clement, N. K. S Rajan

Abstract:

Producer gas is a biomass derived gaseous fuel which is extensively used in internal combustion engines for power generation application. Unlike the conventional hydrocarbon fuels (Gasoline and Natural gas), the combustion properties of producer gas fuel are much different. Therefore, setting of optimal spark time for efficient engine operation is required. Owing to the fluctuating tendency of producer gas composition during gasification process, the heat release patterns (dictating the power output and emissions) obtained are quite different from conventional fuels. It was found that, valve lift timing is yet another factor which influences the burn rate of producer gas fuel, and thus, the heat release rate of the engine. Therefore, the present study was motivated to estimate the influence of valve lift timing analytically (Wiebe model) on the burn rate of producer gas through curve fitting against experimentally obtained mass fraction burn curves of several producer gas compositions. Furthermore, Wiebe models are widely used in zero-dimensional codes for engine parametric studies and are quite popular. This study also addresses the influence of hydrogen and methane concentration of producer gas on combustion trends, which are known to cause dynamics in engine combustion.

Keywords: combustion duration (CD), crank angle (CA), mass fraction burnt (MFB), producer sas (PG), Wiebe Combustion Model (WCM), wide open throttle (WOT)

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1389 Control of Doxorubicin Release Rate from Magnetic PLGA Nanoparticles Using a Non-Permanent Magnetic Field

Authors: Inês N. Peça , A. Bicho, Rui Gardner, M. Margarida Cardoso

Abstract:

Inorganic/organic nanocomplexes offer tremendous scope for future biomedical applications, including imaging, disease diagnosis and drug delivery. The combination of Fe3O4 with biocompatible polymers to produce smart drug delivery systems for use in pharmaceutical formulation present a powerful tool to target anti-cancer drugs to specific tumor sites through the application of an external magnetic field. In the present study, we focused on the evaluation of the effect of the magnetic field application time on the rate of drug release from iron oxide polymeric nanoparticles. Doxorubicin, an anticancer drug, was selected as the model drug loaded into the nanoparticles. Nanoparticles composed of poly(d-lactide-co-glycolide (PLGA), a biocompatible polymer already approved by FDA, containing iron oxide nanoparticles (MNP) for magnetic targeting and doxorubicin (DOX) were synthesized by the o/w solvent extraction/evaporation method and characterized by scanning electron microscopy (SEM), by dynamic light scattering (DLS), by inductively coupled plasma-atomic emission spectrometry and by Fourier transformed infrared spectroscopy. The produced particles yielded smooth surfaces and spherical shapes exhibiting a size between 400 and 600 nm. The effect of the magnetic doxorubicin loaded PLGA nanoparticles produced on cell viability was investigated in mammalian CHO cell cultures. The results showed that unloaded magnetic PLGA nanoparticles were nontoxic while the magnetic particles without polymeric coating show a high level of toxicity. Concerning the therapeutic activity doxorubicin loaded magnetic particles cause a remarkable enhancement of the cell inhibition rates compared to their non-magnetic counterpart. In vitro drug release studies performed under a non-permanent magnetic field show that the application time and the on/off cycle duration have a great influence with respect to the final amount and to the rate of drug release. In order to determine the mechanism of drug release, the data obtained from the release curves were fitted to the semi-empirical equation of the the Korsmeyer-Peppas model that may be used to describe the Fickian and non-Fickian release behaviour. Doxorubicin release mechanism has shown to be governed mainly by Fickian diffusion. The results obtained show that the rate of drug release from the produced magnetic nanoparticles can be modulated through the magnetic field time application.

Keywords: drug delivery, magnetic nanoparticles, PLGA nanoparticles, controlled release rate

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1388 Hybrid Laser-Gas Metal Arc Welding of ASTM A106-B Steel Pipes

Authors: Masoud Mohammadpour, Nima Yazdian, Radovan Kovacevic

Abstract:

The Oil and Gas industries are vigorously looking for new ways to increase the efficiency of their pipeline constructions. Besides the other approaches, implementing of new welding methods for joining pipes can be the best candidate on this regard. Hybrid Laser Arc Welding (HLAW) with the capabilities of high welding speed, deep penetration, and excellent gap bridging ability can be a possible alternative method in pipeline girth welding. This paper investigates the feasibility of applying the HLAW to join ASTM A106-B as the mostly used piping material for transporting high-temperature and high-pressure fluids and gases. The experiments were carried out on six-inch diameter pipes with the wall thickness of 10mm. AWS ER 70 S6 filler wire with diameter of 1.2mm was employed. Relating to this welding procedure, characterization of welded samples such as hardness, tensile testing and Charpy V-notch testing were performed and the results will be reported in this paper. In order to have better understanding about the thermal history and the microstructural alterations caused by the welding heat cycle, a comprehensive Finite Element (FE) model was also conducted. The obtained results have shown that the Gas Metal Arc Welding (GMAW) procedure with the minimum number of 5 passes to complete the wall thickness, was reduced to only single pass by using the HLAW process with the welding time less than 15s.

Keywords: finite element modeling, high-temperature service, hybrid laser/arc welding, welding pipes

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1387 A Theoretical Study of and Phase Change Material Layered Roofs under Specific Climatic Regions in Turkey and the United Kingdom

Authors: Tugba Gurler, Irfan Kurtbas

Abstract:

Roof influences considerably energy demand of buildings. In order to reduce this energy demand, various solutions have been proposed, such as roofs with variable thermal insulation, cool roofs, green roofs, heat exchangers and ventilated roofs, and phase change material (PCM) layered roofs. PCMs suffer from relatively low thermal conductivity despite of their promise of the energy-efficiency initiatives for thermal energy storage (TES). This study not only presents the thermal performance of the concrete roof with PCM layers but also evaluates the products with different design configurations and thicknesses under Central Anatolia Region, Turkey and Nottinghamshire, UK weather conditions. System design limitations and proposed prediction models are discussed in this study. A two-dimensional numerical model has been developed, and governing equations have been solved at each time step. Upper surfaces of the roofs have been modelled with heat flux conditions, while lower surfaces of the roofs with boundary conditions. In addition, suitable roofs have been modeled under symmetry boundary conditions. The results of the designed concrete roofs with PCM layers have been compared with common concrete roofs in Turkey. The UK and the numerical modeling results have been validated with the data given in the literature.

Keywords: phase change material, regional energy demand, roof layers, thermal energy storage

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1386 Li2S Nanoparticles Impact on the First Charge of Li-ion/Sulfur Batteries: An Operando XAS/XES Coupled With XRD Analysis

Authors: Alice Robba, Renaud Bouchet, Celine Barchasz, Jean-Francois Colin, Erik Elkaim, Kristina Kvashnina, Gavin Vaughan, Matjaz Kavcic, Fannie Alloin

Abstract:

With their high theoretical energy density (~2600 Wh.kg-1), lithium/sulfur (Li/S) batteries are highly promising, but these systems are still poorly understood due to the complex mechanisms/equilibria involved. Replacing S8 by Li2S as the active material allows the use of safer negative electrodes, like silicon, instead of lithium metal. S8 and Li2S have different conductivity and solubility properties, resulting in a profoundly changed activation process during the first cycle. Particularly, during the first charge a high polarization and a lack of reproducibility between tests are observed. Differences observed between raw Li2S material (micron-sized) and that electrochemically produced in a battery (nano-sized) may indicate that the electrochemical process depends on the particle size. Then the major focus of the presented work is to deepen the understanding of the Li2S material charge mechanism, and more precisely to characterize the effect of the initial Li2S particle size both on the mechanism and the electrode preparation process. To do so, Li2S nanoparticles were synthetized according to two ways: a liquid path synthesis and a dissolution in ethanol, allowing Li2S nanoparticles/carbon composites to be made. Preliminary chemical and electrochemical tests show that starting with Li2S nanoparticles could effectively suppress the high initial polarization but also influence the electrode slurry preparation. Indeed, it has been shown that classical formulation process - a slurry composed of Polyvinylidone Fluoride polymer dissolved in N-methyle-2-pyrrolidone - cannot be used with Li2S nanoparticles. This reveals a complete different Li2S material behavior regarding polymers and organic solvents when going at the nanometric scale. Then the coupling between two operando characterizations such as X-Ray Diffraction (XRD) and X-Ray Absorption and Emission Spectroscopy (XAS/XES) have been carried out in order to interpret the poorly understood first charge. This study discloses that initial particle size of the active material has a great impact on the working mechanism and particularly on the different equilibria involved during the first charge of the Li2S based Li-ion batteries. These results explain the electrochemical differences and particularly the polarization differences observed during the first charge between micrometric and nanometric Li2S-based electrodes. Finally, this work could lead to a better active material design and so to more efficient Li2S-based batteries.

Keywords: Li-ion/Sulfur batteries, Li2S nanoparticles effect, Operando characterizations, working mechanism

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1385 QSAR, Docking and E-pharmacophore Approach on Novel Series of HDAC Inhibitors with Thiophene Linker as Anticancer Agents

Authors: Harish Rajak, Preeti Patel

Abstract:

HDAC inhibitors can reactivate gene expression and inhibit the growth and survival of cancer cells. The 3D-QSAR and Pharmacophore modeling studies were performed to identify important pharmacophoric features and correlate 3D-chemical structure with biological activity. The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. Pharmacophore hypothesis represents the 3D arrangement of molecular features necessary for activity. A series of 55 compounds with well-assigned HDAC inhibitory activity was used for 3D-QSAR model development. Best 3D-QSAR model, which is a five PLS factor model with good statistics and predictive ability, acquired Q2 (0.7293), R2 (0.9811) and standard deviation (0.0952). Molecular docking were performed using Histone Deacetylase protein (PDB ID: 1t69) and prepared series of hydroxamic acid based HDAC inhibitors. Docking study of compound 43 show significant binding interactions Ser 276 and oxygen atom of dioxine cap region, Gly 151 and amino group and Asp 267 with carboxyl group of CONHOH, which are essential for anticancer activity. On docking, most of the compounds exhibited better glide score values between -8 to -10.5. We have established structure activity correlation using docking, energetic based pharmacophore modelling, pharmacophore and atom based 3D QSAR model. The results of these studies were further used for the design and testing of new HDAC analogs.

Keywords: Docking, e-pharmacophore, HDACIs, QSAR, Suberoylanilidehydroxamic acid.

Procedia PDF Downloads 294