Search results for: equation modeling methods

Authors: Benjamin Leiby, Darryl Ahner

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This study demonstrates an alternative stochastic imputation approach for large datasets when preferred commercial packages struggle to iterate due to numerical problems. A large country conflict dataset motivates the search to impute missing values well over a common threshold of 20% missingness. The methodology capitalizes on correlation while using model residuals to provide the uncertainty in estimating unknown values. Examination of the methodology provides insight toward choosing linear or nonlinear modeling terms. Static tolerances common in most packages are replaced with tailorable tolerances that exploit residuals to fit each data element. The methodology evaluation includes observing computation time, model fit, and the comparison of known values to replaced values created through imputation. Overall, the country conflict dataset illustrates promise with modeling first-order interactions while presenting a need for further refinement that mimics predictive mean matching.

Keywords: correlation, country conflict, imputation, stochastic regression

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Authors: Mehdi Fuladipanah

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Sensitivity analysis as a technique is applied to determine influential input factors on model output. Variance-based sensitivity analysis method has more application compared to other methods because of including linear and non-linear models. In this paper, van Rijn’s movable bed roughness formula was selected to evaluate because of its reasonable results in sandy rivers. This equation contains four variables as: flow depth, sediment size,bBed form height and bed form length. These variable’s importance was determined using the first order of Fourier Amplitude Sensitivity Test. Sensitivity index was applied to evaluate importance of factors. The first order FAST based sensitivity indices test, explain 90% of the total variance that is indicating acceptance criteria of FAST application. More value of this index is indicating more important variable. Results show that bed form height, bed form length, sediment size and flow depth are more influential factors with sensitivity index: 32%, 24%, 19% and 15% respectively.

Keywords: sdensitivity analysis, variance, movable bed roughness formula, Sandy River

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Authors: R. Abdulrahman, A. Eardley, A. Soliman

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The proliferation in the development of mobile learning (m-learning) has played a vital role in the rapidly growing electronic learning market. This relatively new technology can help to encourage the development of in learning and to aid knowledge transfer a number of areas, by familiarizing students with innovative information and communications technologies (ICT). M-learning plays a substantial role in the deployment of learning methods for nursing students by using the Internet and portable devices to access learning resources ‘anytime and anywhere’. However, acceptance of m-learning by students is critical to the successful use of m-learning systems. Thus, there is a need to study the factors that influence student’s intention to use m-learning. This paper addresses this issue. It outlines the outcomes of a study that evaluates the unified theory of acceptance and use of technology (UTAUT) model as applied to the subject of user acceptance in relation to m-learning activity in nurse education. The model integrates the significant components across eight prominent user acceptance models. Therefore, a standard measure is introduced with core determinants of user behavioural intention. The research model extends the UTAUT in the context of m-learning acceptance by modifying and adding individual innovativeness (II) and quality of service (QoS) to the original structure of UTAUT. The paper goes on to add the factors of previous experience (of using mobile devices in similar applications) and the nursing students’ readiness (to use the technology) to influence their behavioural intentions to use m-learning. This study uses a technique called ‘convenience sampling’ which involves student volunteers as participants in order to collect numerical data. A quantitative method of data collection was selected and involves an online survey using a questionnaire form. This form contains 33 questions to measure the six constructs, using a 5-point Likert scale. A total of 42 respondents participated, all from the Nursing Institute at the Armed Forces Hospital in Saudi Arabia. The gathered data were then tested using a research model that employs the structural equation modelling (SEM), including confirmatory factor analysis (CFA). The results of the CFA show that the UTAUT model has the ability to predict student behavioural intention and to adapt m-learning activity to the specific learning activities. It also demonstrates satisfactory, dependable and valid scales of the model constructs. This suggests further analysis to confirm the model as a valuable instrument in order to evaluate the user acceptance of m-learning activity.

Keywords: mobile learning, nursing institute students’ acceptance of m-learning activity in Saudi Arabia, unified theory of acceptance and use of technology model (UTAUT), structural equation modelling (SEM)

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Authors: K. E. Oyetade, S. D. Eyono Obono

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One of the fundamental characteristics of Information and Communication Technology (ICT) has been the ever-changing nature of continuous release and models of ICTs with its impact on the academic, social, and psychological benefits of its introduction in schools. However, there seems to be a growing concern about its negative impact on students when introduced early in schools for teaching and learning. This study aims to design a model of child development factors affecting the early introduction of ICTs in schools in an attempt to improve the understanding of child development and introduction of ICTs in schools. The proposed model is based on a sound theoretical framework. It was designed following a literature review of child development theories and child development factors. The child development theoretical framework that fitted to the best of all child development factors was then chosen as the basis for the proposed model. This study hence found that the Jean Piaget cognitive developmental theory is the most adequate theoretical frameworks for modeling child development factors for ICT introduction in schools.

Keywords: child development factors, child development theories, ICTs, theory

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Authors: Falek Kamel

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Various approaches are usually used in the dynamic analysis of beams vibrating transversally. For this, numerical methods allowing the solving of the general eigenvalue problem are utilized. The equilibrium equations describe the movement resulting from the solution of a fourth-order differential equation. Our investigation is based on the finite element method. The findings of these investigations are the vibration frequencies obtained by the Jacobi method. Two types of the elementary mass matrix are considered, representing a uniform distribution of the mass along with the element and concentrated ones located at fixed points whose number is increased progressively separated by equal distances at each evaluation stage. The studied beams have different boundary constraints representing several classical situations. Comparisons are made for beams where the distributed mass is replaced by n concentrated masses. As expected, the first calculus stage is to obtain the lowest number of beam parts that gives a frequency comparable to that issued from the Rayleigh formula. The obtained values are then compared to theoretical results based on the assumptions of the Bernoulli-Euler theory. These steps are used for the second type of mass representation in the same manner.

Keywords: structural elements, beams vibrating, dynamic analysis, finite element method, Jacobi method

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Authors: Omid Shahmirzadi, Adam Lugowski, Kenneth Younge

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Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to-patent similarity and compare TFIDF (and related extensions), topic models (e.g., latent semantic indexing), and neural models (e.g., paragraph vectors). Contrary to expectations, the added computational cost of text embedding methods is justified only when: 1) the target text is condensed; and 2) the similarity comparison is trivial. Otherwise, TFIDF performs surprisingly well in other cases: in particular for longer and more technical texts or for making finer-grained distinctions between nearest neighbors. Unexpectedly, extensions to the TFIDF method, such as adding noun phrases or calculating term weights incrementally, were not helpful in our context.

Keywords: big data, patent, text embedding, text similarity, vector space model

Procedia PDF Downloads 157

Authors: Sara A. Pakvis, Giulia Scalet, Stefania Marconi, Ferdinando Auricchio, Matthijs Langelaar

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In recent developments in the field of multi-material additive manufacturing, differences in material properties are exploited to create printed shape-memory structures, which are referred to as 4D-printed structures. New printing techniques allow for the deliberate introduction of prestresses in the specimen during manufacturing, and, in combination with the right design, this enables new functionalities. This research focuses on bi-polymer 4D-printed structures, where the transformation process is based on a heat-induced glass transition in one material lowering its Young’s modulus, combined with an initial prestress in the other material. Upon the decrease in stiffness, the prestress is released, which results in the realization of an essentially pre-programmed deformation. As the design of such functional multi-material structures is crucial but far from trivial, a systematic methodology to find the design of 4D-printed structures is developed, where a finite element model is combined with a density-based topology optimization method to describe the material layout. This modeling approach is verified by a convergence analysis and validated by comparing its numerical results to analytical and published data. Specific aspects that are addressed include the interplay between the definition of the prestress and the material interpolation function used in the density-based topology description, the inclusion of a temperature-dependent stiffness relationship to simulate the glass transition effect, and the importance of the consideration of geometric nonlinearity in the finite element modeling. The efficacy of topology optimization to design 4D-printed structures is explored by applying the methodology to a variety of design problems, both in 2D and 3D settings. Bi-layer designs composed of thermoplastic polymers are printed by means of the fused deposition modeling (FDM) technology. Acrylonitrile butadiene styrene (ABS) polymer undergoes the glass transition transformation, while polyurethane (TPU) polymer is prestressed by means of the 3D-printing process itself. Tests inducing shape transformation in the printed samples through heating are performed to calibrate the prestress and validate the modeling approach by comparing the numerical results to the experimental findings. Using the experimentally obtained prestress values, more complex designs have been generated through topology optimization, and samples have been printed and tested to evaluate their performance. This study demonstrates that by combining topology optimization and 4D-printing concepts, stimuli-responsive structures with specific properties can be designed and realized.

Keywords: 4D-printing, glass transition, shape memory polymer, topology optimization

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Authors: L. Nouri Taiba, Y. Bouhamidi, F. Kaouah, Z. Bendjama, M. Trari

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In the present study, an ecofriendly biocomposite namely calcium alginate immobilized Ammi Visnaga (Khella) extraction waste (SWAV/CA) was prepared by electrostatic extrusion method and used on the cadmium biosorption from aqueous phase with and without the assistance of ultrasound in batch conditions. The influence of low frequency ultrasound (37 and 80 KHz) on the cadmium biosorption kinetics was studied. The obtained results show that the ultrasonic irradiation significantly enhances and improves the efficiency of the cadmium removal. The Pseudo first order, Pseudo-second-order, Intraparticle diffusion, and Elovich models were evaluated using the non-linear curve fitting analysis method. Modeling of kinetic results shows that biosorption process is best described by the pseudo-second order and Elovich, in both the absence and presence of ultrasound.

Keywords: biocomposite, biosorption, cadmium, non-linear analysis, ultrasound

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Authors: Muhammad Abu Bakar Tariq

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Construction industry plays a crucial role in the progress of societies and economies. Furthermore, construction projects have social as well as economic implications, thus, their success/failure have wider impacts. However, the industry is lagging behind in terms of efficiency and productivity. Building Information Modeling (BIM) is recognized as a revolutionary development in Architecture, Engineering and Construction (AEC) industry. There are numerous interest groups around the world providing definitions of BIM, proponents describing its advantages and opponents identifying challenges/barriers regarding adoption of BIM. This research is aimed at to determine what actually BIM is, along with its potential role in delivering successful construction projects. The methodology is critical analysis of secondary data sources i.e. information present in public domain, which include peer reviewed journal articles, industry and government reports, conference papers, books, case studies etc. It is discovered that clash detection and visualization are two major advantages of BIM. Clash detection option identifies clashes among structural, architectural and MEP designs before construction actually commences, which subsequently saves time as well as cost and ensures quality during execution phase of a project. Visualization is a powerful tool that facilitates in rapid decision-making in addition to communication and coordination among stakeholders throughout project’s life cycle. By eliminating inconsistencies that consume time besides cost during actual construction, improving collaboration among stakeholders throughout project’s life cycle, BIM can play a positive role to achieve efficiency and productivity that consequently deliver successful construction projects.

Keywords: building information modeling, clash detection, construction project success, visualization

Procedia PDF Downloads 245

Authors: Elisaveta Doncheva, Jelena Djokikj, Ognen Tuteski, Bojana Hadjieva

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In the past decade, additive manufacturing technology or 3D printing has been promoted as an efficient method for fabricating hybrid composite materials and structures with superior mechanical properties and complex shape and geometry. Fused deposition modeling (FDM) process is commonly used additive manufacturing technique for production of polymer products. Therefore, many studies and experiments are focused on investigating the possibilities for improving the obtained results on product properties as a key factor for expanding the spectrum of their application. This article provides an extensive review on recent research advances in FDM and reports on studies that cover the effects of process parameters, material, and design of the product properties. The paper conclusions provide a clear up-to date information for optimum efficiency and enhancement of the mechanical properties of 3D printed samples and recommends further research work and investigations.

Keywords: additive manufacturing, critical parameters, filament, print orientation, 3D printing

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Authors: Faezeh Aghazadeh, Mohammad Javad Sharifi

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The application of neural networks to model a full-scale industrial acetylene hydrogenation in olefin plant has been studied. The operating variables studied are the, input-temperature of the reactor, output-temperature of the reactor, hydrogen ratio of the reactor, [C₂H₂]input, and [C₂H₆]input. The studied operating variables were used as the input to the constructed neural network to predict the [C₂H₆]output at any time as the output or the target. The constructed neural network was found to be highly precise in predicting the quantity of [C₂H₆]output for the new input data, which are kept unaware of the trained neural network showing its applicability to determine the [C₂H₆]output for any operating conditions. The enhancement of [C₂H₆]output as compared with [C₂H₆]input was a consequence of low selective acetylene hydrogenation to ethylene.

Keywords: acetylene hydrogenation, Pd-Ag/Al₂O₃, artificial neural network, modeling, optimal design

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Authors: Nikolaos Simantiris, Markos Avlonitis

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This work builds a simulation platform, modeling the spatial diffusion of the invasive species Callinectes sapidus (blue crab) as a random walk, incorporating also generation, fatality, and fishing rates modeling the time evolution of its population. Antinioti lagoon in West Greece was used as a testbed for applying the simulation model. Field measurements from June 2020 to June 2021 on the lagoon’s setting, bathymetry, and blue crab juveniles provided the initial population simulation of blue crabs, as well as biological parameters from the current literature were used to calibrate simulation parameters. The scope of this study is to render the authors able to predict the evolution of the blue crab population in confined environments of the Ionian Islands region in West Greece. The first result of the simulation experiments shows the possibility for a robust prediction for blue crab population evolution in the Antinioti lagoon.

Keywords: antinioti lagoon, blue crab, stochastic simulation, random walk

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Authors: Kim Young-Jin, Kim Byung-Kon

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Although more efforts to expand the application of BIM (Building Information Modeling) technologies have be pursued in recent years than ever, it’s true that there have been various challenges in doing so, including a lack or absence of relevant institutions, lots of costs required to build BIM-related infrastructure, incompatible processes, etc. This, in turn, has led to a more prolonged delay in the expansion of their application than expected at an early stage. Especially, attempts to save costs for building BIM-related infrastructure and provide various BIM services compatible with domestic processes include studies to link between BIM and cloud computing technologies. Also in this study, the author attempted to develop a cloud BIM service operation model through analyzing the level of BIM applications for the construction sector and deriving relevant service areas, and find how to link BIM services to the cloud operation model, as through archiving BIM data and creating a revenue structure so that the BIM services may grow spontaneously, considering a demand for cloud resources.

Keywords: construction IT, BIM (building information modeling), cloud computing, BIM service based cloud computing

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Authors: Reza Ziaie Moayed, Javad Shamsi Soosahab

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Helical piles are being used extensively in engineering applications all over the world. There are insufficient studies on the helical piles' behavior in anisotropic soils. In this paper, numerical modeling was adopted to investigate the effect of elastic modulus anisotropy on helical pile behavior resting on anisotropic sand by using a finite element limit analysis. The load-displacement behavior of helical piles under compression and tension loads is investigated in different relative densities of soils, and the effect of the ratio of horizontal elastic modulus with respect to vertical elastic modulus (EH/EV) is evaluated. The obtained results illustrate that in sandy soils, the anisotropic ratio of elastic modulus (EH/EV) has notable effect on bearing capacity of helical piles in different relative density. Therefore, it may be recommended that the effect of anisotropic condition of soil elastic modulus should be considered in helical piles behavior.

Keywords: helical piles, bearing capacity, numerical modeling, soil anisotropy

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Authors: Velly Anatasia

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In the last few decades extensive research has been conducted into information technology (IT) adoption, testing a series of factors considered to be essential for improved diffusion. Some studies analyze IT characteristics such as usefulness, ease of use and/or security, others focus on the emotions and experiences of users and a third group attempts to determine the importance of socioeconomic user characteristics such as gender, educational level and income. The situation is similar regarding e-commerce, where the majority of studies have taken for granted the importance of including these variables when studying e-commerce adoption, as these were believed to explain or forecast who buys or who will buy on the internet. Nowadays, the internet has become a marketplace suitable for all ages and incomes and both genders and thus the prejudices linked to the advisability of selling certain products should be revised. The objective of this study is to test whether the socioeconomic characteristics of experienced e-shoppers such as gender rally moderate the effect of their perceptions of online shopping behavior. Current development of the online environment and the experience acquired by individuals from previous e-purchases can attenuate or even nullify the effect of these characteristics. The individuals analyzed are experienced e-shoppers i.e. individuals who often make purchases on the internet. The Technology Acceptance Model (TAM) was broadened to include previous use of the internet and perceived self-efficacy. The perceptions and behavior of e-shoppers are based on their own experiences. The information obtained will be tested using questionnaires which were distributed and self-administered to respondent accustomed using internet. The causal model is estimated using structural equation modeling techniques (SEM), followed by tests of the moderating effect of socioeconomic variables on perceptions and online shopping behavior. The expected findings of this study indicated that gender moderate neither the influence of previous use of the internet nor the perceptions of e-commerce. In short, they do not condition the behavior of the experienced e-shopper.

Keywords: Internet shopping, age groups, gender, income, electronic commerce

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Authors: Samuel Quashie

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Ph.D. Construction Management methodology and mixed methods are organized to guide the researcher to assemble and assess data in the research activities. Construction management research is close to business management and social science research. It also contributes to researching the phenomenon and answering the research question, generating an integrated management system for post-disaster reconstruction in construction and related industries. Research methodology and methods drive the research to achieve the goal or goals, contribute to knowledge, or increase knowledge. This statement means the research methodology, mixed methods, aim, objectives, and processes address the research question, facilitate its achievement and foundation to conduct the study. Mixed methods use project-based case studies, interviews, observations, literature and archival document reviews, research questionnaires, and surveys, and evaluation of integrated systems used in the construction industry and related industries to address the research work. The research mixed methods (qualitative, quantitative) define the research topic and establish a more in-depth study. The research methodology is action research, which involves the collaboration of participants and service users to collect and evaluate data, studying the phenomenon, research question(s) to improve the situation in post-disaster reconstruction phase management.

Keywords: methodology, Ph.D. research, post-disaster reconstruction, mixed-methods qualitative and quantitative

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Authors: N. H. Hamid, N. M. Mohamed, S. A. Anuar

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Precast residential houses are normally constructed in Malaysia using precast shear-key wall panel and precast wall panel are designed using BS8110 where there is no provision for earthquake. However, the safety of this house under moderate and strong earthquake is still questionable. Consequently, the full-scale of residential house are designed, constructed, tested and analyzed under in-plane lateral cyclic loading. Hysteresis loops are plotted based on the experimental work and compared with modeling of hysteresis loops using HYSTERES in RUAUMOKO 2D program. Modified Takeda hysteresis model is chosen to behave a similar pattern with experimental work. This program will display the earthquake excitations, spectral displacements, pseudo spectral acceleration, and deformation shape of the structure. It can be concluded that this building is suffering severe cracks and damage under moderate and severe earthquake.

Keywords: precast shear-key, hysteresis loops, spectral displacements, deformation shape

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Authors: Verónica Díaz

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A Cartesian graph, as a mathematical object, becomes a tool for configuration of change. Its best comprehension is done through everyday life problem-solving associated with its representation. Despite this, the current educational framework favors general graphs, without consideration of their argumentation. Students are required to find the mathematical function without associating it to the development of graphical language. This research describes the use made by students of configurations made prior to Cartesian graphs with regards to an everyday life problem related to a time and distance variation phenomenon. The theoretical framework describes the function conditions of study and their modeling. This is a qualitative, descriptive study involving six undergraduate case studies that were carried out during the first term in 2016 at University of Los Lagos. The research problem concerned the graphic modeling of a real person’s movement phenomenon, and two levels of analysis were identified. The first level aims to identify local and global graph interpretations; a second level describes the iconicity and referentiality degree of an image. According to the results, students were able to draw no figures before the Cartesian graph, highlighting the need for students to represent the context and the movement of which causes the phenomenon change. From this, they managed Cartesian graphs representing changes in position, therefore, achieved an overall view of the graph. However, the local view only indicates specific events in the problem situation, using graphic and verbal expressions to represent movement. This view does not enable us to identify what happens on the graph when the movement characteristics change based on possible paths in the person’s walking speed.

Keywords: cartesian graphs, higher education, movement modeling, problem solving

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Authors: Fagner O. Serrano, Danielle R. Bouchard, Todd A. Duhame

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Walking cadence (steps/min) is an effective way to prescribe exercise so an individual can reach a moderate intensity, which is recommended to optimize health benefits. To our knowledge, there is no study on the required walking cadence to reach a moderate intensity for people that present chronic conditions or risk factors for chronic conditions such as Cardiovascular Diseases (CVD). The objectives of this study were: 1- to identify the walking cadence needed for people at risk of CVD to a reach moderate intensity, and 2- to develop and test an equation using clinical variables to help professionals working with individuals at risk of CVD to estimate the walking cadence needed to reach moderate intensity. Ninety-one people presenting a minimum of two risk factors for CVD completed a medically supervised graded exercise test to assess maximum oxygen consumption at the first visit. The last visit consisted of recording walking cadence using a foot pod Garmin FR-60 and a Polar heart rate monitor, aiming to get participants to reach 40% of their maximal oxygen consumption using a portable metabolic cart on an indoor flat surface. The equation to predict the walking cadence needed to reach moderate intensity in this sample was developed as follows: The sample was randomly split in half and the equation was developed with one half of the participants, and validated using the other half. Body mass index, height, stride length, leg height, body weight, fitness level (VO2max), and self-selected cadence (over 200 meters) were measured using objective measured. Mean walking cadence to reach moderate intensity for people age 64.3 ± 10.3 years old at risk of CVD was 115.8  10.3 steps per minute. Body mass index, height, body weight, fitness level, and self-selected cadence were associated with walking cadence at moderate intensity when evaluated in bivariate analyses (r ranging from 0.22 to 0.52; all P values ≤0.05). Using linear regression analysis including all clinical variables associated in the bivariate analyses, body weight was the significant predictor of walking cadence for reaching a moderate intensity (ß=0.24; P=.018) explaining 13% of walking cadence to reach moderate intensity. The regression model created was Y = 134.4-0.24 X body weight (kg).Our findings suggest that people presenting two or more risk factors for CVD are reaching moderate intensity while walking at a cadence above the one officially recommended (116 steps per minute vs. 100 steps per minute) for healthy adults.

Keywords: cardiovascular disease, moderate intensity, older adults, walking cadence

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Authors: Sabina-Adriana Floria, Marius Gavrilescu, Florin Leon, Silvia Curteanu, Costel Anton

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Neuroevolution is a subfield of artificial intelligence used to solve various problems in different application areas. Specifically, neuroevolution is a technique that applies biologically inspired methods to generate neural network architectures and optimize their parameters automatically. In this paper, we use different biologically inspired optimization algorithms in an ensemble strategy with the aim of training multilayer perceptron neural networks, resulting in regression models used to simulate the industrial chemical process of obtaining bricks from silicone-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. In addition, the initial conditions that were taken into account during the design and commissioning of the installation can change over time, which leads to the need to add new mixes to adjust the operating conditions for the desired purpose, e.g., material properties and energy saving. The present approach follows the study by simulation of a process of obtaining bricks from silicone-based materials, i.e., the modeling and optimization of the process. Optimization aims to determine the working conditions that minimize the emissions represented by nitrogen monoxide. We first use a search procedure to find the best values for the parameters of various biologically inspired optimization algorithms. Then, we propose an adaptive ensemble strategy that uses only a subset of the best algorithms identified in the search stage. The adaptive ensemble strategy combines the results of selected algorithms and automatically assigns more processing capacity to the more efficient algorithms. Their efficiency may also vary at different stages of the optimization process. In a given ensemble iteration, the most efficient algorithms aim to maintain good convergence, while the less efficient algorithms can improve population diversity. The proposed adaptive ensemble strategy outperforms the individual optimizers and the non-adaptive ensemble strategy in convergence speed, and the obtained results provide lower error values.

Keywords: optimization, biologically inspired algorithm, neuroevolution, ensembles, bricks, emission minimization

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Authors: Liyew Yizengaw Yitayih

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This nanotechnology study focuses on how potassium ions (K+) affect lithium-ion (Li-ion) battery performance. By adding potassium ions (K+) to the lithium tin oxide (LiSnO) anode and employing styrene-butadiene rubber (SBR) as a binder, the doping of K+ was specifically studied. The methods employed in this study include computer modeling and simulation, material fabrication, and electrochemical characterization. The potassium ions (Li+) were successfully doped into the LiSnO lattice during charge/discharge cycles, which increased the lithium-ion diffusivity and electrical conductivity within the anode. However, it was found that internal doping of potassium ions (K+) into the LiSnO lattice occurred at high potassium ion concentrations (>16.6%), which hampered lithium ion transfer because of repulsion and physical blockage. The electrochemical efficiency of lithium-ion batteries was improved by this comprehensive study's presentation of potassium ions' (K+) potential advantages when present in the appropriate concentrations in electrode materials.

Keywords: lithium-ion battery, LiSnO anode, potassium doping, lithium-ion diffusivity, electronic conductivity

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Authors: Zelikha Labbani

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Many biotechnology methods have been used in plant breeding programs. The in vitro isolated microspore culture is the one of these methods. For durum wheat, the use of this technology has been limited for a long time due to the low number of embryos produced and also most regeneration plants are albina. The objective of this paper is to show that using isolated microspores culture on durum wheat is possible due to the development of the new methods using the new pretreatment of the microspores before their isolation and cultivation.

Keywords: isolated microspore culture, pretreatments, in vitro embryogenesis, plant breeding program

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Authors: Jiahui You, Kyung Jae Lee

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Hydraulic fracturing fluid (HFF) is widely used in shale reservoir productions. HFF contains diverse chemical additives, which result in the dissolution and precipitation of minerals through multiple chemical reactions. In this study, a new pore-scale Darcy–Brinkman–Stokes (DBS) model coupled with Level Set Method (LSM) is developed to address the microscopic phenomena occurring during the iron–HFF interaction, by numerically describing mass transport, chemical reactions, and pore structure evolution. The new model is developed based on OpenFOAM, which is an open-source platform for computational fluid dynamics. Here, the DBS momentum equation is used to solve for velocity by accounting for the fluid-solid mass transfer; an advection-diffusion equation is used to compute the distribution of injected HFF and iron. The reaction–induced pore evolution is captured by applying the LSM, where the solid-liquid interface is updated by solving the level set distance function and reinitialized to a signed distance function. Then, a smoothened Heaviside function gives a smoothed solid-liquid interface over a narrow band with a fixed thickness. The stated equations are discretized by the finite volume method, while the re-initialized equation is discretized by the central difference method. Gauss linear upwind scheme is used to solve the level set distance function, and the Pressure–Implicit with Splitting of Operators (PISO) method is used to solve the momentum equation. The numerical result is compared with 1–D analytical solution of fluid-solid interface for reaction-diffusion problems. Sensitivity analysis is conducted with various Damkohler number (DaII) and Peclet number (Pe). We categorize the Fe (III) precipitation into three patterns as a function of DaII and Pe: symmetrical smoothed growth, unsymmetrical growth, and dendritic growth. Pe and DaII significantly affect the location of precipitation, which is critical in determining the injection parameters of hydraulic fracturing. When DaII<1, the precipitation uniformly occurs on the solid surface both in upstream and downstream directions. When DaII>1, the precipitation mainly occurs on the solid surface in an upstream direction. When Pe>1, Fe (II) transported deeply into and precipitated inside the pores. When Pe<1, the precipitation of Fe (III) occurs mainly on the solid surface in an upstream direction, and they are easily precipitated inside the small pore structures. The porosity–permeability relationship is subsequently presented. This pore-scale model allows high confidence in the description of Fe (II) dissolution, transport, and Fe (III) precipitation. The model shows fast convergence and requires a low computational load. The results can provide reliable guidance for injecting HFF in shale reservoirs to avoid clogging and wellbore pollution. Understanding Fe (III) precipitation, and Fe (II) release and transport behaviors give rise to a highly efficient hydraulic fracture project.

Keywords: reactive-transport , Shale, Kerogen, precipitation

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Authors: Samson Olusegun Apantaku, Adetayo K. Aromolaran, Giyatt Hammed

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The study assessed the use of participatory research methods among Federal University of Agriculture Abeokuta, Nigeria (FUNAAB) researchers. Simple random sampling technique was used to select one hundred and twenty respondents from the study area. Data were collected using a questionnaire. Data collected were subjected to descriptive and inferential statistical analyses. Results showed that 75.8% of the respondents were males while only 21.3% were female. The mean age of the respondents was 38.8 years and most (77.5%) of them were married. 15% of the respondents were in professorial cadre, 21.7% and 20% of the respondents were senior lecturers/fellow and lecturer/research fellow I&II respectively. The results further revealed that 93.3% of the respondents were aware of participatory research methods and 82.5% of the respondents have utilized it before. The average period of usage was 2.7 years and participation by consultation (86.7%) and interactive participation (76.7%) were mostly used. Most (94.2%) indicated that fund was the major hindrance to the use of participatory research methods. The result of correlation analysis showed that there was significant relationship between the years of research experience, designation post (status) of the respondents and usage of participatory research methods (r = 0.034, 0.031, p < 0.05). The study concluded that most of the researchers were aware of and used participatory research methods, which could influence the quality of their research or make it acceptable to the end users. It was recommended that more funds should be made available and accessible for participatory research. All researchers should be trained and encouraged to make use of participatory research methods in their research activities so as to achieve effective research and capacity building that could enhance adoption of technologies and increase agricultural production in the country. Farmers’ capacity to participate in agricultural research should also be enhanced.

Keywords: participatory research, participatory research methods, awareness, utilization

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Authors: Juan Huang, Hugo Ninanya

Abstract:

Oil has been used as a source of energy and supply to make materials, such as asphalt or rubber for many years. This is the reason why new technologies have been implemented through time. However, research still needs to continue increasing due to new challenges engineers face every day, just like unconventional reservoirs. Various numerical methodologies have been applied in petroleum engineering as tools in order to optimize the production of reservoirs before drilling a wellbore, although not all of these have the same efficiency when talking about studying fracture propagation. Analytical methods like those based on linear elastic fractures mechanics fail to give a reasonable prediction when simulating fracture propagation in ductile materials whereas numerical methods based on the cohesive zone method (CZM) allow to represent the elastoplastic behavior in a reservoir based on a constitutive model; therefore, predictions in terms of displacements and pressure will be more reliable. In this work, a hydro-geomechanical coupled model of horizontal wells in fractured rock was developed using ABAQUS; both extended element method and cohesive elements were used to represent predefined fractures in a model (2-D). A power law for representing the rheological behavior of fluid (shear-thinning, power index <1) through fractures and leak-off rate permeating to the matrix was considered. Results have been showed in terms of aperture and length of the fracture, pressure within fracture and fluid loss. It was showed a high infiltration rate to the matrix as power index decreases. A sensitivity analysis is conclusively performed to identify the most influential factor of fluid loss.

Keywords: fracture, hydro-geomechanical model, non-Newtonian fluid, numerical analysis, sensitivity analysis

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Authors: Jatupon Em-Udom, Nirand Pisutha-Arnond

Abstract:

The phase-field-crystal, PFC, approach is a density-functional-type material model with an atomic resolution on a diffusive timescale. Spatially, the model incorporates periodic nature of crystal lattices and can naturally exhibit elasticity, plasticity and crystal defects such as grain boundaries and dislocations. Temporally, the model operates on a diffusive timescale which bypasses the need to resolve prohibitively small atomic-vibration time steps. The PFC model has been used to study many material phenomena such as grain growth, elastic and plastic deformations and solid-solid phase transformations. In this study, the pressure-controlled dynamic equation for the PFC model was developed to simulate a single-component system under externally applied pressure; these coupled equations are important for studies of deformable systems such as those under constant pressure. The formulation is based on the non-equilibrium thermodynamics and the thermodynamics of crystalline solids. To obtain the equations, the entropy variation around the equilibrium point was derived. Then the resulting driving forces and flux around the equilibrium were obtained and rewritten as conventional thermodynamic quantities. These dynamics equations are different from the recently-proposed equations; the equations in this study should provide more rigorous descriptions of the system dynamics under externally applied pressure.

Keywords: driving forces and flux, evolution equation, non equilibrium thermodynamics, Onsager’s reciprocal relation, phase field crystal model, thermodynamics of single-component solid

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Authors: Ichihan Tai, Bill Olson, Paul Blessner

Abstract:

Traditional early warning systems that alarm against crisis are generally based on structured or numerical data; therefore, a system that can make predictions based on unstructured textual data, an uncorrelated data source, is a great complement to the traditional early warning systems. The Chicago Board Options Exchange (CBOE) Volatility Index (VIX), commonly referred to as the fear index, measures the cost of insurance against market crash, and spikes in the event of crisis. In this study, news data is consumed for prediction of whether there will be a market-wide crisis by predicting the movement of the fear index, and the historical references to similar events are presented in an unsupervised manner. Topic modeling-based prediction and representation are made based on daily news data between 1990 and 2015 from The Wall Street Journal against VIX index data from CBOE.

Keywords: early warning system, knowledge management, market prediction, topic modeling.

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Authors: Arun Goel

Abstract:

Prediction of maximum local scour is necessary for the safety and economical design of the bridges. A number of equations have been developed over the years to predict local scour depth using laboratory data and a few pier equations have also been proposed using field data. Most of these equations are empirical in nature as indicated by the past publications. In this paper, attempts have been made to compute local depth of scour around bridge pier in dimensional and non-dimensional form by using linear regression, simple regression and SVM (Poly and Rbf) techniques along with few conventional empirical equations. The outcome of this study suggests that the SVM (Poly and Rbf) based modeling can be employed as an alternate to linear regression, simple regression and the conventional empirical equations in predicting scour depth of bridge piers. The results of present study on the basis of non-dimensional form of bridge pier scour indicates the improvement in the performance of SVM (Poly and Rbf) in comparison to dimensional form of scour.

Keywords: modeling, pier scour, regression, prediction, SVM (Poly and Rbf kernels)

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Authors: Victoria Masi Haruna Karatu, Nik Kamariah Nikmat

Abstract:

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: Remo Waser, Simon Maranda, Anastasia Stamatiou, Ludger J. Fischer, Joerg Worlitschek

Abstract:

In latent heat storage, a phase change material (PCM) is used to store thermal energy. The heat transfer rate during solidification is limited and considered as a key challenge in the development of latent heat storages. Thus, finned heat exchangers (HEX) are often utilized to increase the heat transfer rate of the storage system. In this study, a new modeling approach to calculating the heat transfer rate in latent thermal energy storages with complex HEX geometries is presented. This model allows for an optimization of the HEX design in terms of costs and thermal performance of the system. Modeling solidification processes requires the calculation of time-dependent heat conduction with moving boundaries. Commonly used computational fluid dynamic (CFD) methods enable the analysis of the heat transfer in complex HEX geometries. If applied to the entire storage, the drawback of this approach is the high computational effort due to small time steps and fine computational grids required for accurate solutions. An alternative to describe the process of solidification is the so-called temperature-based approach. In order to minimize the computational effort, a quasi-stationary assumption can be applied. This approach provides highly accurate predictions for tube heat exchangers. However, it shows unsatisfactory results for more complex geometries such as finned tube heat exchangers. The presented simulation model uses a temporal and spatial discretization of heat exchanger tube. The spatial discretization is based on the smallest possible symmetric segment of the HEX. The heat flow in each segment is calculated using finite volume method. Since the heat transfer fluid temperature can be derived using energy conservation equations, the boundary conditions at the inner tube wall is dynamically updated for each time step and segment. The model allows a prediction of the thermal performance of latent thermal energy storage systems using complex HEX geometries with considerably low computational effort.

Keywords: modelling of solidification, finned tube heat exchanger, latent thermal energy storage

Procedia PDF Downloads 254