Search results for: cost-based structural optimization

Authors: Serges Mendomo Meye, Li Guowei, Shen Zhenzhong

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Earthquake is one of the main loads threatening dam safety. Once the dam is damaged, it will bring huge losses of life and property to the country and people. Therefore, it is very important to research the seismic safety of the dam. Due to the complex foundation conditions, high fortification intensity, and high scientific and technological content, it is necessary to adopt reasonable methods to evaluate the seismic safety performance of concrete arch dams built and under construction in strong earthquake areas. Structural seismic vulnerability analysis can predict the probability of structural failure at all levels under different intensity earthquakes, which can provide a scientific basis for reasonable seismic safety evaluation and decision-making. In this paper, the response surface method (RSM) is applied to the seismic vulnerability analysis of arch dams, which improves the efficiency of vulnerability analysis. Based on the central composite test design method, the material-seismic intensity samples are established. The response surface model (RSM) with arch crown displacement as performance index is obtained by finite element (FE) calculation of the samples, and then the accuracy of the response surface model (RSM) is verified. To obtain the seismic vulnerability curves, the seismic intensity measure ??(?1) is chosen to be 0.1~1.2g, with an interval of 0.1g and a total of 12 intensity levels. For each seismic intensity level, the arch crown displacement corresponding to 100 sets of different material samples can be calculated by algebraic operation of the response surface model (RSM), which avoids 1200 times of nonlinear dynamic calculation of arch dam; thus, the efficiency of vulnerability analysis is improved greatly.

Keywords: high concrete arch dam, performance index, response surface method, seismic vulnerability analysis, vector-valued intensity measure

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Authors: Eunice Oluwakemi Chukwuma-Nwuba

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Nigeria is a developing country with an increasing rate of graduate unemployment. This has triggered successive government administrations to promote the variety of programmes to address the situation. However, none of these efforts yielded the desired outcome. Accordingly, in 2006 the government included entrepreneurship module in the curriculum of universities as a compulsory general programme for all undergraduate courses. This is in the hope that the programme will help to promote entrepreneurial mind-set and new venture creation among graduates and as a result reduce the rate of graduate unemployment. The study explores the effectiveness of entrepreneurship education in promoting entrepreneurship. This study is significant in view of the endemic graduate unemployment in Nigeria and the social consequences such as youth restiveness and militancy. It is guided by the theory of planned behaviour. It employed the two-stage structural equation modelling (AMOS) to model entrepreneurial intentions as a function of innovative teaching methods, traditional teaching methods and culture Personal attitude and subjective norm are proposed to mediate the relationships between the exogenous and the endogenous variables. The first stage was tested using multi-group confirmatory factor analysis (MGCFA) framework to confirm that the two groups assign the same meaning to the scale items and to obtain goodness-of-fit indices. The multi-group confirmatory factor analysis included the tests of configural, metric and scalar invariance. With the attainment of full configural invariance and partial metric and scalar invariance, the second stage – the structural model was applied hypothesising that, the entrepreneurial intentions of graduates (respondents who have participated in the compulsory entrepreneurship programme) will be higher than those of undergraduates (respondents who are yet to participate in the programme). The study uses the quasi-experimental design. The samples comprised 409 graduates (experimental group) and 402 undergraduates (control group) from six federal universities in Nigeria. Our findings suggest that personal attitude is positively related with entrepreneurial intentions, largely confirming prior literature. However, unlike previous studies, our results indicate that subjective norm has significant direct and indirect impact on entrepreneurial intentions indicating that reference people of the participants have important roles to play in their decision to be entrepreneurial. Furthermore, unlike the assertions in prior studies, the result suggests that traditional teaching methods have indirect effect on entrepreneurial intentions supporting that since personal characteristics can change in an educational situation, an education purposively directed at entrepreneurship might achieve similar results if not better. This study has implication for practice and theory. The research extends to the theoretical understanding of the formation of entrepreneurial intentions and explains the role of the reference others in relation to how graduates perceive entrepreneurship. Further, the study adds to the body of knowledge on entrepreneurship education in Nigeria universities and provides a developing country perspective. It proposes further research in the exploration of entrepreneurship education and entrepreneurial intentions of graduates from across the country’s universities as necessary and imperative.

Keywords: entrepreneurship education, entrepreneurial intention, structural equation modeling, theory of planned behaviour

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Authors: Nasim Abuali Galehdari, Thomas J. Ryan, Ajit D. Kelkar

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In recent years, nanotechnology has played an important role in the design of an efficient radiation shielding polymeric composites. It is well known that, high loading of nanomaterials with radiation absorption properties can enhance the radiation attenuation efficiency of shielding structures. However, due to difficulties in dispersion of nanomaterials into polymer matrices, there has been a limitation in higher loading percentages of nanoparticles in the polymer matrix. Therefore, the objective of the present work is to provide a methodology to fabricate and then to characterize the functionally graded radiation shielding structures, which can provide an efficient radiation absorption property along with good structural integrity. Sandwich structures composed of Ultra High Molecular Weight Polyethylene (UHMWPE) fabric as face sheets and functionally graded epoxy nanocomposite as core material were fabricated. A method to fabricate a functionally graded core panel with controllable gradient dispersion of nanoparticles is discussed. In order to optimize the design of functionally graded sandwich composites and to analyze the stress distribution throughout the sandwich composite thickness, a finite element method was used. The sandwich panels were discretized using 3-Dimensional 8 nodded brick elements. Classical laminate analysis in conjunction with simplified micromechanics equations were used to obtain the properties of the face sheets. The presented finite element model would provide insight into deformation and damage mechanics of the functionally graded sandwich composites from the structural point of view.

Keywords: nanotechnology, functionally graded material, radiation shielding, sandwich composites, finite element method

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Authors: Jung-Hwan Oh, Rajesh Kumar, Il-Kwon Oh

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Porous graphene has extensive potential applications in variety of fields such as hydrogen storage, CO oxidation, gas separation, supercapacitors, fuel cells, nanoelectronics, oil adsorption, and so on. However, the generation of some carbon atoms vacancies for precise small holes have been not extensively studied to prevent the agglomerates of graphene sheets and to obtain porous graphene with high surface area. Recently, many research efforts have been presented to develop physical and chemical synthetic approaches for porous graphene. But physical method has very high cost of manufacture and chemical method consumes so many hours for porous graphene. Herein, we propose a porous graphene contained holes with atomic scale precision by embedding metal nano-particles through microwave irradiation for hydrogen storage and CO oxidation multi- functionalities. This proposed synthetic method is appropriate for fast and convenient production of three dimensional nanostructures, which have nanoholes on the graphene surface in consequence of microwave irradiation. The metal nanoparticles are dispersed quickly on the graphene surface and generated uniform nanoholes on the graphene nanosheets. The morphological and structural characterization of the porous graphene were examined by scanning electron microscopy (SEM), transmission scanning electron microscopy (TEM) and RAMAN spectroscopy, respectively. The metal nanoparticle-embedded porous graphene exhibits a microporous volume of 2.586cm3g-1 with an average pore radius of 0.75 nm. HR-TEM analysis was carried out to further characterize the microstructures. By investigating the RAMAN spectra, we can understand the structural changes of graphene. The results of this work demonstrate a possibility to produce a new class of porous graphene. Furthermore, the newly acquired knowledge for the diffusion into graphene can provide useful guidance for the development of the growth of nanostructure.

Keywords: CO oxidation, hydrogen storage, nanocomposites, porous graphene

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Authors: Ayush Satija, Ritu Raj

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Escalating demand for elevated structures as a remedy for traffic congestion has led to a surge in the construction of viaducts and bridges predominantly employing prestressed beams. However, post-tensioned I-girder superstructures are gaining traction for their attributes like structural efficiency, cost-effectiveness, and easy construction. Recently, Ultra-high-performance fiber-reinforced concrete (UHPFRC) has emerged as a revolutionary material in reshaping conventional infrastructure engineering. UHPFRC offers exceptional properties including high compressive and tensile strength, alongside enhanced durability. Its adoption in bridges yields benefits, notably a remarkable strength-to-weight ratio enabling the design of lighter and slender structural elements, enhancing functionality and sustainability. Despite its myriad advantages, integration of UHPFRC in construction is still evolving, hindered by factors like cost, material availability, and design standardization. Consequently, there's a need to assess the feasibility of substituting ordinary concrete (OC) with UHPFRC in bridges, focusing on economic considerations. This research undertakes an efficacy study between post-tensioned I-girders fabricated from UHPFRC and OC, evaluating cost parameters associated with concrete production, reinforcement, and erection. The study reveals that UHPFRC becomes economically viable for spans exceeding 40.0m. This shift in cost-effectiveness is attributed to factors like reduced girder depth, elimination of un-tensioned steel, diminished need for shear reinforcement and decreased erection costs.

Keywords: post tensioned I girder, superstructure, ultra-high-performance fiber reinforced concrete, ordinary concrete

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Authors: Maha Bakakri, Rachid Tadili, Fatiha Lemmini

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Morocco is one of the few countries that have kept their traditional crafts, despite the competition of modern industry and its impact on manual labor. Therefore the optimization of energy consumption becomes an obligation and this is the purpose of this document. In this work we present some characteristics of the furnace studied, its operating principle and the experimental measurements of the evolutions of the temperatures inside and outside the walls of the furnace, values which will be used later in the calculation of its thermal losses. In order to determine the major source of the thermal losses of the furnace we have established the heat balance of the furnace. The energy consumed, the useful energy and the thermal losses through the walls and the chimney of the furnace are calculated thanks to the experimental measurements which we realized for several firings. The results show that the energy consumption of this type of furnace is very high and that the main source of energy loss is mainly due to the heat losses of the combustion gases that escape from the furnace by the chimney while the losses through the walls are relatively small. it have opted for energy recovery as a solution where we can recover some of the heat lost through the use of a heat exchanger system using a double tube introduced into the flue gas exhaust stack compartment. The study on the heat recovery system is presented and the heat balance inside the exchanger is established. In this paper we also present the numerical modeling of heat transfer by conduction through the walls of the furnace. A numerical model has been established based on the finite volume method and the double scan method. It makes it possible to determine the temperature profile of the furnace and thus to calculate the thermal losses of its walls and to deduce the thermal losses due to the combustion gases. Validation of the model is done using the experimental measurements carried out on the furnace. The results obtained in this work, relating to the energy consumed during the operation of the furnace are important and are part of the energy efficiency framework that has become a key element in global energy policies. It is the fastest and cheapest way to solve energy, environmental and economic security problems.

Keywords: energy cunsumption, energy recovery, modeling, energy eficiency

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Authors: Kakali Bhadra

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Binding of small molecules to DNA and recently to RNA, continues to attract considerable attention for developing effective therapeutic agents for control of gene expression. This work focuses towards understanding interaction of harmalol, a dihydro beta-carboline alkaloid, with different nucleic acid motifs viz. double stranded CT DNA, single stranded A-form poly(A), double-stranded A-form of poly(C)·poly(G) and clover leaf tRNAphe by different spectroscopic, calorimetric and molecular modeling techniques. Results of this study converge to suggest that (i) binding constant varied in the order of CT DNA > poly(C)·poly(G) > tRNAphe > poly(A), (ii) non-cooperative binding of harmalol to poly(C)·poly(G) and poly(A) and cooperative binding with CT DNA and tRNAphe, (iii) significant structural changes of CT DNA, poly(C)·poly(G) and tRNAphe with concomitant induction of optical activity in the bound achiral alkaloid molecules, while with poly(A) no intrinsic CD perturbation was observed, (iv) the binding was predominantly exothermic, enthalpy driven, entropy favoured with CT DNA and poly(C)·poly(G) while it was entropy driven with tRNAphe and poly(A), (v) a hydrophobic contribution and comparatively large role of non-polyelectrolytic forces to Gibbs energy changes with CT DNA, poly(C)·poly(G) and tRNAphe, and (vi) intercalated state of harmalol with CT DNA and poly(C)·poly(G) structure as revealed from molecular docking and supported by the viscometric data. Furthermore, with competition dialysis assay it was shown that harmalol prefers hetero GC sequences. All these findings unequivocally pointed out that harmalol prefers binding with ds CT DNA followed by ds poly(C)·poly(G), clover leaf tRNAphe and least with ss poly(A). The results highlight the importance of structural elements in these natural beta-carboline alkaloids in stabilizing different DNA and RNA of various motifs for developing nucleic acid based better therapeutic agents.

Keywords: calorimetry, docking, DNA/RNA-alkaloid interaction, harmalol, spectroscopy

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Authors: Ranadhir Roy

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Inverse problems arise in medical (molecular) imaging. These problems are characterized by large in three dimensions, and by the diffusion equation which models the physical phenomena within the media. The inverse problems are posed as a nonlinear optimization where the unknown parameters are found by minimizing the difference between the predicted data and the measured data. To obtain a unique and stable solution to an ill-posed inverse problem, a priori information must be used. Mathematical conditions to obtain stable solutions are established in Tikhonov’s regularization method, where the a priori information is introduced via a stabilizing functional, which may be designed to incorporate some relevant information of an inverse problem. Effective determination of the Tikhonov regularization parameter requires knowledge of the true solution, or in the case of optical imaging, the true image. Yet, in, clinically-based imaging, true image is not known. To alleviate these difficulties we have applied the penalty/modified barrier function (PMBF) method instead of Tikhonov regularization technique to make the inverse problems well-posed. Unlike the Tikhonov regularization method, the constrained optimization technique, which is based on simple bounds of the optical parameter properties of the tissue, can easily be implemented in the PMBF method. Imposing the constraints on the optical properties of the tissue explicitly restricts solution sets and can restore uniqueness. Like the Tikhonov regularization method, the PMBF method limits the size of the condition number of the Hessian matrix of the given objective function. The accuracy and the rapid convergence of the PMBF method require a good initial guess of the Lagrange multipliers. To obtain the initial guess of the multipliers, we use a least square unconstrained minimization problem. Three-dimensional images of fluorescence absorption coefficients and lifetimes were reconstructed from contact and noncontact experimentally measured data.

Keywords: constrained minimization, ill-conditioned inverse problems, Tikhonov regularization method, penalty modified barrier function method

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Authors: Pedro Mota Veiga

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This study comprehensively evaluates the repercussions of innovation, digital advancements, and technological capabilities on the operational performance of companies across fifteen European Union countries following the initial wave of the COVID-19 pandemic. Drawing insights from longitudinal data sourced from the 2019 World Bank business surveys and subsequent 2020 World Bank COVID-19 follow-up business surveys, our extensive examination involves a diverse sample of 5763 family businesses. In exploring the relationships between these variables, we adopt a nuanced approach to assess the impact of innovation and digital and technological capabilities on performance. This analysis unfolds along two distinct perspectives: one rooted in necessity and the other insufficiency. The methodological framework employed integrates partial least squares structural equation modeling (PLS-SEM) with condition analysis (NCA), providing a robust foundation for drawing meaningful conclusions. The findings of the study underscore a positive influence on the performance of family firms stemming from both technological capabilities and digital advancements. Furthermore, it is pertinent to highlight the indirect contribution of innovation to enhanced performance, operating through its impact on digital capabilities. This research contributes valuable insights to the broader understanding of how innovation, coupled with digital and technological capabilities, can serve as pivotal factors in shaping the post-COVID-19 landscape for businesses across the European Union. The intricate analysis of family businesses, in particular adds depth to the comprehension of the dynamics at play in diverse economic contexts within the European Union.

Keywords: digital capabilities, technological capabilities, family firms performance, innovation, NCA, PLS-SEM

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Authors: Tarek M. Alguhane, Ayman H. Khalil, M. N. Fayed, Ayman M. Ismail

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This paper deals with different modeling aspects of masonry infill: no infill model, Layered shell infill model, and strut infill model. These models consider the complicated behavior of the in-filled plane frames under lateral load similar to an earthquake load. Three strut infill models are used: NBCC (2005) strut infill model, ASCE/SEI 41-06 strut infill model and proposed strut infill model based on modification to Canadian, NBCC (2005) strut infill model. Pushover and modal analyses of a masonry infill concrete frame with a single storey and an existing 5-storey RC building have been carried out by using different models for masonry infill. The corresponding hinge status, the value of base shear at target displacement as well as their dynamic characteristics have been determined and compared. A validation of the structural numerical models for the existing 5-storey RC building has been achieved by comparing the experimentally measured and the analytically estimated natural frequencies and their mode shapes. This study shows that ASCE/SEI 41-06 equation underestimates the values for the equivalent properties of the diagonal strut while Canadian, NBCC (2005) equation gives realistic values for the equivalent properties. The results indicate that both ASCE/SEI 41-06 and Canadian, NBCC (2005) equations for strut infill model give over estimated values for dynamic characteristic of the building. Proposed modification to Canadian, NBCC (2005) equation shows that the fundamental dynamic characteristic values of the building are nearly similar to the corresponding values using layered shell elements as well as measured field results.

Keywords: masonry infill, framed structures, RC buildings, non-structural elements

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Authors: Antonia Hoffmann, Andrea Stübner

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Resource scarcity and rising material prices are forcing companies to rethink their business models. The conventional linear system of economic growth and rising social needs further exacerbates the problem of resource scarcity. Therefore, it is necessary to separate economic growth from resource consumption. This can be achieved through the circular economy (CE), which focuses on sustainable product life cycles. However, companies face challenges in implementing CE into their businesses. Small and medium-sized enterprises are particularly affected by these problems, as they have a limited resource base. Collaboration and social interaction between different actors can help to overcome these obstacles. Based on a self-generated sample of 1,023 German small and medium-sized enterprises, we use a questionnaire to investigate the influence of social capital and its three dimensions - structural, relational, and cognitive capital - on the implementation of CE and the mediating effect of dynamic capabilities in explaining these relationships. Using regression analyses and structural equation modeling, we find that social capital is positively associated with CE implementation and dynamic capabilities partially mediate this relationship. Interestingly, our findings suggest that not all social capital dimensions are equally important for CE implementation. We theoretically and empirically explore the network forms of social capital and extend the CE literature by suggesting that dynamic capabilities help organizations leverage social capital to drive the implementation of CE practices. The findings of this study allow us to suggest several implications for managers and institutions. From a practical perspective, our study contributes to building circular production and service capabilities in small and medium-sized enterprises. Various CE activities can transform products and services to contribute to a better and more responsible world.

Keywords: circular economy, dynamic capabilities, SMEs, social capital

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Authors: F. F. Zahra, E. G. Touria, Y. Samia, M. Ahmed, H. Hasna, B. M. Latifa

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The presence of radioactive contaminants in wastewater poses a significant environmental and health risk, necessitating effective treatment solutions. This study investigates the optimization of chitosan-Argan nutshell beads for the removal of radioactive elements from wastewater, utilizing Response Surface Methodology (RSM) to enhance the treatment efficiency. Chitosan, known for its biocompatibility and adsorption properties, was combined with Argan nutshell powder to form composite beads. These beads were then evaluated for their capacity to remove radioactive contaminants from synthetic wastewater. The Box-Behnken design (BBD) under RSM was employed to analyze the influence of key operational parameters, including initial contaminant concentration, pH, bead dosage, and contact time, on the removal efficiency. Experimental results indicated that all tested parameters significantly affected the removal efficiency, with initial contaminant concentration and pH showing the most substantial impact. The optimized conditions, as determined by RSM, were found to be an initial contaminant concentration of 50 mg/L, a pH of 6, a bead dosage of 0.5 g/L, and a contact time of 120 minutes. Under these conditions, the removal efficiency reached up to 95%, demonstrating the potential of chitosan-Argan nutshell beads as a viable solution for radioactive wastewater treatment. Furthermore, the adsorption process was characterized by fitting the experimental data to various isotherm and kinetic models. The adsorption isotherms conformed well to the Langmuir model, indicating monolayer adsorption, while the kinetic data were best described by the pseudo-second-order model, suggesting chemisorption as the primary mechanism. This study highlights the efficacy of chitosan-Argan nutshell beads in removing radioactive contaminants from wastewater and underscores the importance of optimizing treatment parameters using RSM. The findings provide a foundation for developing cost-effective and environmentally friendly treatment technologies for radioactive wastewater.

Keywords: adsorption, argan nutshell, beads, chitosan, mechanism, optimization, radioactive wastewater, response surface methodology

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Authors: Mohammadreza Mojtahedi

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Rapid urbanization presents multifaceted challenges, including environmental degradation and public health concerns. As the inevitability of urban sprawl continues, it becomes essential to devise strategies to alleviate its pressures on natural ecosystems and elevate socio-economic benchmarks within cities. This research investigates urban agriculture's economic contributions, emphasizing its pivotal role in food provisioning and export potential. Adopting a descriptive-analytical approach, field survey data was primarily collected via questionnaires. The tool's validity was affirmed by expert opinions, and its reliability secured by achieving a Cronbach's alpha score over 0.70 from 30 preliminary questionnaires. The research encompasses Neishabour's populace of 264,375, extracting a sample size of 384 via Cochran's formula. Findings reveal the significance of urban agriculture in food supply and its potential for exports, underlined by a p-value < 0.05. Neishabour's urban farming can augment the export of organic commodities, fruits, vegetables, ornamental plants, and foster product branding. Moreover, it supports the provision of fresh produce, bolstering dietary quality. Urban agriculture further impacts urban development metrics—enhancing environmental quality, job opportunities, income levels, and aesthetics, while promoting rainwater utilization. Popular cultivations include peaches, Damask roses, and poultry, tailored to available spaces. Structural equation modeling indicates urban agriculture's overarching influence, accounting for a 56% variance, predominantly in food sufficiency and export proficiency.

Keywords: urban agriculture, food supply, export potential, urban development, environmental health, structural equation modeling

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Authors: Pardis Abolghasemi, Benyamin Hatamsaz

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Background: Diabetic nephropathy is a serious health problem described by specific kidney structure and functional disturbance. Renoprotective effects of the stem cells secretase have been shown in many kidney diseases. The aim is to evaluate the capability of human Wharton’s jelly mesenchymal stem cells conditioned media (hWJMSCs-CM) to alleviate DN in streptozotocin (STZ)-induced diabetes. Methods: Diabetic nephropathy was induced by injection of STZ (60 mg/kg, IP) in twenty rats. Conditioned media was extracted from hWJMSCs at third passages. At week 8, diabetic rats were divided into two groups: treated (hWJMSCs-CM, 500 μl/rat for three weeks, IP) and not treated (DN). In the 11th week, three groups (control, DN and DN+hWJMSCs-CM) were kept in metabolic cages and urine was collected for 24h. Blood pressure (BP) and heart rate (HR) were continuously recorded. The serum samples were maintained for measuring BUN, Cr and angiotensin-converting enzyme (ACE) activity. The left kidney was kept at -80°C for ACE activity assessment. The right kidney and pancreas were used for histopathologic evaluation. Result: Diabetic nephropathy was detected by microalbuminuria and increased albumin/creatinine ratio, as well as the pancreas and renal structural disturbance. Glomerular filtration rate, BP and HR increased in the DN group. The ACE activity was elevated in the serum and kidneys of the DN group. Administration of hWJMSCs-CM modulated the renal functional and structural disturbance and decreased the ACE activity. Conclusion: Conditioned media was extracted from hWJMSCs may have a Renoprotective effect in diabetic nephropathy. This may happen through regulation of ACE activity and renin-angiotensin system inhibition.

Keywords: diabetic nephropathy, mesenchymal stem cells, immunomodulation, anti-inflammation

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Authors: M. Ravindiran, P. Shankar

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This paper deals with the comparison of two synthesis methods, namely, sol-gel, and combustion to prepare Fe doped ZnO nano material. Characterization results for structural, optical and magnetic properties were analyzed for the sol gel and combustion synthesis derived materials. Magnetic studies of the prepared compounds reveal that the combustion synthesis derived material has good magnetization of 50 emu/gm with a better hysteresis loop curve.

Keywords: DMS, combustion, ferromagnetic, synthesis methods

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Authors: Olamide Shittu, Olayinka Akanle

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Value Chain Analysis is a common method of examining the stages involved in the production of a product, mostly agricultural produce, from the input to the consumption stage including the actors involved in each stage. However, the Functional Institutional Analysis is the most common method in literature employed to analyze the value chain of products. Apart from studying the relatively neglected phenomenon of recycled polymer products in Lagos Metropolis, this paper adopted the use of social network analysis to attempt a grounded theory of the nature of social network that exists among the value chain actors of the subject matter. The study adopted a grounded theory approach by conducting in-depth interviews, administering questionnaires and conducting observations among the identified value chain actors of recycled polymer products in Lagos Metropolis, Nigeria. The thematic analysis of the collected data gave the researchers the needed background to formulate a truly representative network of the social relationships among the value chain actors of recycled polymer products in Lagos Metropolis. The paper introduced concepts such as Transient and Perennial Social Ties to explain the observed social relations among the actors. Some actors have more social capital than others as a result of the structural holes that exist in their triad network. Households and resource recoverers are at disadvantaged position in the network as they have high constraints in their relationships with other actors. The study attempted to provide a new perspective in the study of the environmental value chain by analyzing the network of actors to bring about policy action points and improve recycling in Nigeria. Government and social entrepreneurs can exploit the structural holes that exist in the network for the socio-economic and sustainable development of the state.

Keywords: recycled polymer products, social network analysis, social ties, value chain analysis

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Authors: Samuel Asiedu-Addo, Jonathan Annan, Yarhands Dissou Arthur

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The study aims to explore the relational effect of lecturers’ personal attribute on student’s interest in statistics. In this study personal attributes of lecturers’ such as lecturer’s dynamism, communication strategies and rapport in the classroom as well as applied knowledge during lecture were examined. Here, exploratory research design was used to establish the effect of lecturer’s personal attributes on student’s interest. Data were analyzed by means of confirmatory factor analysis and structural equation modeling (SEM) using the SmartPLS 3 program. The study recruited 376 students from the faculty of technical and vocational education of the University of Education Winneba Kumasi campus, and Ghana Technology University College as well as Kwame Nkrumah University of science and Technology. The results revealed that personal attributes of an effective lecturer were lecturer’s dynamism, rapport, communication and applied knowledge contribute (52.9%) in explaining students interest in statistics. Our regression analysis and structural equation modeling confirm that lecturers personal attribute contribute effectively by predicting student’s interest of 52.9% and 53.7% respectively. The paper concludes that the total effect of a lecturer’s attribute on student’s interest is moderate and significant. While a lecturer’s communication and dynamism were found to contribute positively to students’ interest, they were insignificant in predicting students’ interest. We further showed that a lecturer’s personal attributes such as applied knowledge and rapport have positive and significant effect on tertiary student’s interest in statistic, whilst lecturers’ communication and dynamism do not significantly affect student interest in statistics; though positively related.

Keywords: student interest, effective teacher, personal attributes, regression and SEM

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Authors: Ziaullah, Shah Wahab Ali

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Micro-grid equipped with heterogeneous energy resources present the idea of small scale distributed energy management (DEM). DEM helps in minimizing the transmission and operation costs, power management and peak load demands. Micro-grids are collections of small, independent controllable power-generating units and renewable energy resources. Micro-grids also motivate to enable active customer participation by giving accessibility of real-time information and control to the customer. The capability of fast restoration against faulty situation, integration of renewable energy resources and Information and Communication Technologies (ICT) make micro-grid as an ideal system for distributed power systems. Micro-grids can have a bank of energy storage devices. The energy management system of micro-grid can perform real-time energy forecasting of renewable resources, energy storage elements and controllable loads in making proper short-term scheduling to minimize total operating costs. We present a review of existing micro-grids optimization objectives/goals, constraints, solution approaches and tools used in micro-grids for energy management. Cost-benefit analysis of micro-grid reveals that cooperation among different micro-grids can play a vital role in the reduction of import energy cost and system stability. Cooperative micro-grids energy trading is an approach to electrical distribution energy resources that allows local energy demands more control over the optimization of power resources and uses. Cooperation among different micro-grids brings the interconnectivity and power trading issues. According to the literature, it shows that open area of research is available for cooperative micro-grids energy trading. In this paper, we proposed and formulated the efficient energy management/trading module for interconnected micro-grids. It is believed that this research will open new directions in future for energy trading in cooperative micro-grids/interconnected micro-grids.

Keywords: distributed energy management, information and communication technologies, microgrid, energy management

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Authors: Sang Koo Jeon, Seung Hoon Nahm, Oh Heon Kwon

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The unit cell of solid oxide fuel cell (SOFC) must be stacked as several layers type to obtain the high power. The most of researcher have concerned about the performance of stacked SOFC rather than the structural stability of stacked SOFC and especially interested how to design for reducing the electrical loss and improving the high efficiency. Consequently, the stacked SOFC able to produce the electrical high power and related parts like as manifold, gas seal, bipolar plate were developed to optimize the stack design. However, the unit cell of SOFC was just layered on the interconnector without the adhesion and the hydrogen and oxygen were injected to the interfacial layer in the high temperature. On the operating condition, the interfacial layer can be the one of the weak point in the stacked SOFC. Therefore the evaluation of the structural safety for the failure is essentially needed. In this study, interfacial adhesion between SOFC and metal adhesive was estimated in the high temperature environment. The metal adhesive was used to strongly connect the unit cell of SOFC with interconnector and provide the electrical conductivity between them. The four point bending test was performed to measure the interfacial adhesion. The unit cell of SOFC and SiO2 wafer were diced and then attached by metal adhesive. The SiO2 wafer had the center notch to initiate a crack from the tip of the notch. The modified stereomicroscope combined with the CCD camera and system for measuring the length was used to observe the fracture behavior. Additionally, the interfacial adhesion was evaluated in the high temperature condition because the metal adhesive was affected by high temperature. Also the specimen was exposed in the furnace during several hours and then the interfacial adhesion was evaluated. Finally, the interfacial adhesion energy was quantitatively determined and compared in the each condition.

Keywords: solid oxide fuel cell (SOFC), metal adhesive, adhesion, high temperature

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Authors: Lingju Wu, Hao Hua

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This paper presents a digital fashion production methodology and workflow based on fused deposition modeling additive manufacturing technology, as demonstrated through a 3D printed fashion show held at Southeast University in Nanjing, China. Unlike traditional fashion, 3D printed fashion allows for the creation of complex geometric shapes and unique structural designs, facilitating diverse reconfiguration and sustainable production of textile fabrics. The proposed methodology includes two components: morphogenesis and the 3D printing process. The morphogenesis part comprises digital design methods such as mesh deformation, structural reorganization, particle flow stretching, sheet partitioning, and spreading methods. The 3D printing process section includes three types of methods: sculptural objects, multi-material composite fabric, and self-forming composite fabrics. This paper focuses on multi-material composite fabrics and self-forming composite fabrics, both of which involve weaving fabrics with 3D-printed material sandwiches. Multi-material composite fabrics create specially tailored fabric from the original properties of the printing path and multiple materials, while self-forming fabrics apply pre-stress to the flat fabric and then print the sandwich, allowing the fabric's own elasticity to interact with the printed components and shape into a 3D state. The digital design method and workflow enable the integration of abstract sensual aesthetics and rational thinking, showcasing a digital aesthetic that challenges conventional handicraft workshops. Overall, this paper provides a comprehensive framework for the production of 3D-printed fashion, from concept to final product.

Keywords: digital fashion, composite fabric, self-forming structure, additive manufacturing, generating design

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Authors: Seyed Mehdi Ghezi, Hesam Hasanpoor

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This scientific article explores enhancement methods for ensemble learning with the aim of improving the performance of classifiers in the analysis and classification of brain signals. The research approach in this field consists of two main parts, each with its own strengths and weaknesses. The choice of approach depends on the specific research question and available resources. By combining these approaches and leveraging their respective strengths, researchers can enhance the accuracy and reliability of classification results, consequently advancing our understanding of the brain and its functions. The first approach focuses on utilizing machine learning methods to identify the best features among the vast array of features present in brain signals. The selection of features varies depending on the research objective, and different techniques have been employed for this purpose. For instance, the genetic algorithm has been used in some studies to identify the best features, while optimization methods have been utilized in others to identify the most influential features. Additionally, machine learning techniques have been applied to determine the influential electrodes in classification. Ensemble learning plays a crucial role in identifying the best features that contribute to learning, thereby improving the overall results. The second approach concentrates on designing and implementing methods for selecting the best classifier or utilizing meta-classifiers to enhance the final results in ensemble learning. In a different section of the research, a single classifier is used instead of multiple classifiers, employing different sets of features to improve the results. The article provides an in-depth examination of each technique, highlighting their advantages and limitations. By integrating these techniques, researchers can enhance the performance of classifiers in the analysis and classification of brain signals. This advancement in ensemble learning methodologies contributes to a better understanding of the brain and its functions, ultimately leading to improved accuracy and reliability in brain signal analysis and classification.

Keywords: ensemble learning, brain signals, classification, feature selection, machine learning, genetic algorithm, optimization methods, influential features, influential electrodes, meta-classifiers

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Authors: Kiatkulchai Jitt-Aer, Graham Wall, Dylan Jones

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As a result of the Indian Ocean tsunami in 2004, logistics applied to disaster relief operations has received great attention in the humanitarian sector. As learned from such disaster, preparing and responding to the aspect of delivering essential items from distribution centres to affected locations are of the importance for relief operations as the nature of disasters is uncertain especially in suffering figures, which are normally proportional to quantity of supplies. Thus, this study proposes a spatial decision support system (SDSS) for humanitarian logistics by integrating Geographical Information Systems (GIS) and the capacitated vehicle routing problem (CVRP). The GIS is utilised for acquiring demands simulated from the tsunami flooding model of the affected area in the first stage, and visualising the simulation solutions in the last stage. While CVRP in this study encompasses designing the relief routes of a set of homogeneous vehicles from a relief centre to a set of geographically distributed evacuation points in which their demands are estimated by using both simulation and randomisation techniques. The CVRP is modeled as a multi-objective optimization problem where both total travelling distance and total transport resources used are minimized, while demand-cost efficiency of each route is maximized in order to determine route priority. As the model is a NP-hard combinatorial optimization problem, the Clarke and Wright Saving heuristics is proposed to solve the problem for the near-optimal solutions. The real-case instances in the coastal area of Phuket, Thailand are studied to perform the SDSS that allows a decision maker to visually analyse the simulation scenarios through different decision factors.

Keywords: demand simulation, humanitarian logistics, geographical information systems, relief operations, capacitated vehicle routing problem

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Authors: Misra Ayse Adsiz, Selim Selvi

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In today's world, technology is competing with time. In order to catch up with the world's companies and adapt quickly to the changes, it is necessary to speed up the processes and keep pace with the rate of change of the technology. The missile system design processes, which are handled with classical methods, keep behind in this race. Because customer requirements are not clear, and demands are changing again and again in the design process. Therefore, in the system design process, a methodology suitable for the missile system design dynamics has been investigated and the processes used for catching up the era are examined. When commonly used design processes are analyzed, it is seen that any one of them is dynamic enough for today’s conditions. So a hybrid design process is established. After a detailed review of the existing processes, it is decided to focus on the Scrum Framework and Agile Philosophy. Scrum is a process framework. It is focused on to develop software and handling change management with rapid methods. In addition, agile philosophy is intended to respond quickly to changes. In this study, it is aimed to integrate Scrum framework and agile philosophy, which are the most appropriate ways for rapid production and change adaptation, into the missile system design process. With this approach, it is aimed that the design team, involved in the system design processes, is in communication with the customer and provide an iterative approach in change management. These methods, which are currently being used in the software industry, have been integrated with the product design process. A team is created for system design process. The roles of Scrum Team are realized with including the customer. A scrum team consists of the product owner, development team and scrum master. Scrum events, which are short, purposeful and time-limited, are organized to serve for coordination rather than long meetings. Instead of the classic system design methods used in product development studies, a missile design is made with this blended method. With the help of this design approach, it is become easier to anticipate changing customer demands, produce quick solutions to demands and combat uncertainties in the product development process. With the feedback of the customer who included in the process, it is worked towards marketing optimization, design and financial optimization.

Keywords: agile, design, missile, scrum

Procedia PDF Downloads 153

Authors: Assabo Mohamed, Bile Mohamed, Ali Farah, Isman Souleiman, Olga Alos Ramos, Marie Cadet

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The life of a nuclear power plant is regularly punctuated by short or long period outages to carry out maintenance operations and/or nuclear fuel reloading. During these stops periods, it is essential to conserve all the secondary circuit equipment to avoid corrosion priming. This kind of circuit is one of the main components of a nuclear reactor. Indeed, the conservation materials on shutdown of a nuclear unit improve circuit performance and reduce the maintenance cost considerably. This study is a part of the optimization of the dry preservation of equipment from the water station of the nuclear reactor. The main objective is to provide tools to guide Electricity Production Nuclear Centre (EPNC) in order to achieve the criteria required by the chemical specifications of conservation materials. A theoretical model of drying exchangers of water station is developed by the software Engineering Equation Solver (EES). It used to size requirements and air quality needed for dry conservation of equipment. This model is based on heat transfer and mass transfer governing the drying operation. A parametric study is conducted to know the influence of aerothermal factor taking part in the drying operation. The results show that the success of dry conservation of equipment of the secondary circuit of nuclear reactor depends strongly on the draining, the quality of drying air and the flow of air injecting in the secondary circuit. Finally, theoretical case study performed on EES highlights the importance of mastering the entire system to balance the air system to provide each exchanger optimum flow depending on its characteristics. From these results, recommendations to nuclear power plants can be formulated to optimize drying practices and achieve good performance in the conservation of material from the water at the stop position.

Keywords: dry conservation, optimization, sizing, water station

Procedia PDF Downloads 250

Authors: Jianghua Chen

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Sustainable urban development requires the coordination of economic growth and resource environment, and industrial transformation and upgrading is the key link. Based on the decoupling theory and the improved decoupling decomposition model, the quantitative evaluation and comprehensive analysis of the degree of decoupling between resource consumption and economic development in Jiangsu Province are carried out by utilizing the data related to resource consumption and economic growth of the secondary and tertiary industries in Jiangsu Province from 2013 to 2018, so as to explore the sustainable development path of industrial transformation in Jiangsu Province. The results show that from the decoupling status, the degree of decoupling of economic development of the secondary industry to the required coke resources, water resources and human resources is gradually deepening, and the decoupling index of economic development of the tertiary industry to the required water resources is fluctuating; from the perspective of the driving factors, the technological effect is the main driving factor for decoupling the economic growth of Jiangsu Province to the resources, and the structural effect has a significant impact on the driving index of the decoupling of economic growth of the secondary and tertiary industries to the consumption of resources in Jiangsu Province. In terms of driving factors, the technology effect is the main driving factor for economic growth in Jiangsu Province to realize decoupling of resources, while the structural effect is the main driving factor for economic growth in Jiangsu Province's second and third industries to realize decoupling of resources. Finally, we discuss the difficulties of industrial transformation and layout faced by Jiangsu Province at present.

Keywords: resource consumption, economic growth, industrial transformation, decoupling theory

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Authors: Vaso K. Kapnopoulou, Piero Caridis

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The fatigue of ship structural details is of major concern in the maritime industry as it can generate fracture issues that may compromise structural integrity. In the present study, a fatigue analysis of the lower hopper knuckle connection of a bulk carrier was conducted using the Finite Element Method by means of ABAQUS/CAE software. The fatigue life was calculated using Miner’s Rule and the long-term distribution of stress range by the use of the two-parameter Weibull distribution. The cumulative damage ratio was estimated using the fatigue damage resulting from the stress range occurring at each load condition. For this purpose, a cargo hold model was first generated, which extends over the length of two holds (the mid-hold and half of each of the adjacent holds) and transversely over the full breadth of the hull girder. Following that, a submodel of the area of interest was extracted in order to calculate the hot spot stress of the connection and to estimate the fatigue life of the structural detail. Two hot spot locations were identified; one at the top layer of the inner bottom plate and one at the top layer of the hopper plate. The IACS Common Structural Rules (CSR) require that specific dynamic load cases for each loading condition are assessed. Following this, the dynamic load case that causes the highest stress range at each loading condition should be used in the fatigue analysis for the calculation of the cumulative fatigue damage ratio. Each load case has a different effect on ship hull response. Of main concern, when assessing the fatigue strength of the lower hopper knuckle connection, was the determination of the maximum, i.e. the critical value of the stress range, which acts in a direction normal to the weld toe line. This acts in the transverse direction, that is, perpendicularly to the ship's centerline axis. The load cases were explored both theoretically and numerically in order to establish the one that causes the highest damage to the location examined. The most severe one was identified to be the load case induced by beam sea condition where the encountered wave comes from the starboard. At the level of the cargo hold model, the model was assumed to be simply supported at its ends. A coarse mesh was generated in order to represent the overall stiffness of the structure. The elements employed were quadrilateral shell elements, each having four integration points. A linear elastic analysis was performed because linear elastic material behavior can be presumed, since only localized yielding is allowed by most design codes. At the submodel level, the displacements of the analysis of the cargo hold model to the outer region nodes of the submodel acted as boundary conditions and applied loading for the submodel. In order to calculate the hot spot stress at the hot spot locations, a very fine mesh zone was generated and used. The fatigue life of the detail was found to be 16.4 years which is lower than the design fatigue life of the structure (25 years), making this location vulnerable to fatigue fracture issues. Moreover, the loading conditions that induce the most damage to the location were found to be the various ballasting conditions.

Keywords: dynamic load cases, finite element method, high cycle fatigue, lower hopper knuckle

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Authors: Jun Hee Lee, Young Kyu Kim, Seong Jae Hong, Chamroeun Chhorn, Seung Woo Lee

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Roller-compacted concrete pavement (RCCP), an environmental friendly pavement of which load carry capacity benefitted from both hydration and aggregate interlock from roller compacting, demonstrated a superb structural performance for a relatively small amount of water and cement content. Even though an excellent structural performance can be secured, it is required to investigate roller-compacted concrete (RCC) under environmental loading and its long-term durability under critical conditions. In order to secure long-term durability, an appropriate internal air-void structure is required for this concrete. In this study, a method for improving the long-term durability of RCCP is suggested by analyzing the internal air-void structure and corresponding durability of RCC. The method of improving the long-term durability involves measurements of air content, air voids, and air-spacing factors in RCC that experiences changes in terms of type of air-entraining agent and its usage amount. This test is conducted according to the testing criteria in ASTM C 457, 672, and KS F 2456. It was found that the freezing-thawing and scaling resistances of RCC without any chemical admixture was quite low. Interestingly, an improvement of freezing-thawing and scaling resistances was observed for RCC with appropriate the air entraining (AE) agent content; Relative dynamic elastic modulus was found to be more than 80% for those mixtures. In RCC with AE agent mixtures, large amount of air was distributed within a range of 2% to 3%, and an air void spacing factor ranging between 200 and 300 μm (close to 250 μm, recommended by PCA) was secured. The long-term durability of RCC has a direct relationship with air-void spacing factor, and thus it can only be secured by ensuring the air void spacing factor through the inclusion of the AE in the mixture.

Keywords: durability, RCCP, air spacing factor, surface scaling resistance test, freezing and thawing resistance test

Procedia PDF Downloads 238

Authors: Nabil Al-Zaqri

Abstract:

Semiconductor photocatalysts with surface defects display incredible light absorption bandwidth, and these defects function as highly active sites for oxidation processes by interacting with the surface band structure. Accordingly, engineering the photocatalyst with surface oxygen vacancies will enhance the semiconductor nanostructure's photocatalytic efficiency. Herein, a CeO2₋ₓ nanostructure is designed under the influence of low-frequency ultrasonic waves to create surface oxygen vacancies. This approach enhances the photocatalytic efficiency compared to many heterostructures while keeping the intrinsiccrystal structure intact. Ultrasonic waves induce the acoustic cavitation effect leading to the dissemination of active elements on the surface, which results in vacancy formation in conjunction with larger surface area and smaller particle size. The structural analysis of CeO₂₋ₓ revealed higher crystallinity, as well as morphological optimization, and the presence of oxygen vacancies is verified through Raman, X-rayphotoelectron spectroscopy, temperature-programmed reduction, photoluminescence, and electron spinresonance analyses. Oxygen vacancies accelerate the redox cycle between Ce₄+ and Ce₃+ by prolongingphotogenerated charge recombination. The ultrasound-treated pristine CeO₂ sample achieved excellenthydrogen production showing a quantum efficiency of 1.125% and efficient organic degradation. Ourpromising findings demonstrated that ultrasonic treatment causes the formation of surface oxygenvacancies and improves photocatalytic hydrogen evolution and pollution degradation. Conclusion: Defect engineering of the ceria nanoparticles with oxygen vacancies was achieved for the first time using low-frequency ultrasound treatment. The U-CeO₂₋ₓsample showed high crystallinity, and morphological changes were observed. Due to the acoustic cavitation effect, a larger surface area and small particle size were observed. The ultrasound treatment causes particle aggregation and surface defects leading to oxygen vacancy formation. The XPS, Raman spectroscopy, PL spectroscopy, and ESR results confirm the presence of oxygen vacancies. The ultrasound-treated sample was also examined for pollutant degradation, where 1O₂was found to be the major active species. Hence, the ultrasound treatment influences efficient photocatalysts for superior hydrogen evolution and an excellent photocatalytic degradation of contaminants. The prepared nanostructure showed excellent stability and recyclability. This work could pave the way for a unique post-synthesis strategy intended for efficient photocatalytic nanostructures.

Keywords: surface defect, CeO₂₋ₓ, photocatalytic, water treatment, H₂ production

Procedia PDF Downloads 124

Authors: Soha Saad, Jean Bigeon, Florence Ossart, Etienne Sourdille

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Developing better solutions for train rescheduling problems has been drawing the attention of researchers for decades. Most researches in this field deal with minor incidents that affect a large number of trains due to cascading effects. They focus on timetables, rolling stock and crew duties, but do not take into account infrastructure limits. The present work addresses electric infrastructure incidents that limit the power available for train traction, and hence the transportation capacity of the railway system. Rescheduling is needed in order to optimally share the available power among the different trains. We propose a rescheduling process based on dynamic multiphysics railway simulations that include the mechanical and electrical properties of all the system components and calculate physical quantities such as the train speed profiles, voltage along the catenary lines, temperatures, etc. The optimization problem to solve has a large number of continuous and discrete variables, several output constraints due to physical limitations of the system, and a high computation cost. Our approach includes a phase of sensitivity analysis in order to analyze the behavior of the system and help the decision making process and/or more precise optimization. This approach is a quantitative method based on simulation statistics of the dynamic railway system, considering a predefined range of variation of the input parameters. Three important settings are defined. Factor prioritization detects the input variables that contribute the most to the outputs variation. Then, factor fixing allows calibrating the input variables which do not influence the outputs. Lastly, factor mapping is used to study which ranges of input values lead to model realizations that correspond to feasible solutions according to defined criteria or objectives. Generalized Sobol indexes are used for factor prioritization and factor fixing. The approach is tested in the case of a simple railway system, with a nominal traffic running on a single track line. The considered incident is the loss of a feeding power substation, which limits the power available and the train speed. Rescheduling is needed and the variables to be adjusted are the trains departure times, train speed reduction at a given position and the number of trains (cancellation of some trains if needed). The results show that the spacing between train departure times is the most critical variable, contributing to more than 50% of the variation of the model outputs. In addition, we identify the reduced range of variation of this variable which guarantees that the output constraints are respected. Optimal solutions are extracted, according to different potential objectives: minimizing the traveling time, the train delays, the traction energy, etc. Pareto front is also built.

Keywords: optimization, rescheduling, railway system, sensitivity analysis, train timetable

Procedia PDF Downloads 387

Authors: M. K. Benhaoua, A. E. H. Benyamina, T. Djeradi, P. Boulet

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In this paper, we propose adaptive routing that considers the routing of communications in order to optimize the overall performance. The routing technique uses a newly proposed Algorithm to route communications between the tasks. The routing we propose of the communications leads to a better optimization of several performance metrics (time and energy consumption). Experimental results show that the proposed routing approach provides significant performance improvements when compared to those using static routing.

Keywords: multi-processor systems-on-chip (mpsocs), network-on-chip (noc), heterogeneous architectures, adaptive routin

Procedia PDF Downloads 360