Search results for: mixed-integer non-linear programming

Authors: Waheed Ahmad Safi, Shunichi Nakamura

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Concrete filled steel I-girder (CFIG) bridge was proposed and the bending and shear strength was confirmed by experiments. The area surrounded by the upper and lower flanges and the web is filled with concrete in CFIG, which is used to the intermediate support of a continuous girder. Three-dimensional finite element models were established to simulate the bending and shear behaviors of CFIG and to clarify the load transfer mechanism. Steel plates and filled concrete were modeled as a three-dimensional 8-node solid element and steel reinforcement bars as a three-dimensional 2-node truss element. The elements were mostly divided into the 50 x 50 mm mesh size. The non-linear stress-strain relation is assumed for concrete in compression including the softening effect after the peak, and the stress increases linearly for concrete in tension until concrete cracking but then decreases due to tension stiffening effect. The stress-strain relation for steel plates was tri-linear and that for reinforcements was bi-linear. The concrete and the steel plates were rigidly connected. The developed FEM model was applied to simulate and analysis the bending behaviors of the CFIG specimens. The vertical displacements and the strains of steel plates and the filled concrete obtained by FEM agreed very well with the test results until the yield load. The specimens collapsed when the upper flange buckled or the concrete spalled off. These phenomena cannot be properly analyzed by FEM, which produces a small discrepancy at the ultimate states. The FEM model was also applied to simulate and analysis the shear tests of the CFIG specimens. The vertical displacements and strains of steel and concrete calculated by FEM model agreed well with the test results. A truss action was confirmed by the FEM and the experiment, clarifying that shear forces were mainly resisted by the tension strut of the steel plate and the compression strut of the filled concrete acting in the diagonal direction. A trail design with the CFIG was carried out for a four-span continuous highway bridge and the design method was established. Construction cost was estimated about 12% lower than that of a conventional steel I-section girder.

Keywords: concrete filled steel I-girder, bending strength, FEM, limit states design, steel I-girder, shear strength

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Authors: Anoush Saadatmehr

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Design and build of large clear span structures have always been demanding in the construction industry targeting industrial and commercial buildings around the world. The function of these spectacular structures encompasses distinguished types of building such as aircraft and airship hangars, warehouses, bulk storage buildings, sports and recreation facilities. From an engineering point of view, there are various types of steel structure systems that are often adopted in large-span buildings like conventional trusses, space frames and cable-supported roofs. However, this paper intends to investigate and review an innovative light, economic and quickly erected large span steel structure renowned as “Stressed-Arch,” which has several advantages over the other common types of structures. This patented system integrates the use of cold-formed hollow section steel material with high-strength pre-stressing strands and concrete grout to establish an arch shape truss frame anywhere there is a requirement to construct a cost-effective column-free space for spans within the range of 60m to 180m. In this study and firstly, the main structural properties of the stressed-arch system and its components are discussed technically. These features include nonlinear behavior of truss chords during stress-erection, the effect of erection method on member’s compressive strength, the rigidity of pre-stressed trusses to overcome strict deflection criteria for cases with roof suspended cranes or specialized front doors and more importantly, the prominent lightness of steel structure. Then, the effects of utilizing pre-stressing strands to safeguard a smooth process of installation of main steel members and roof components and cladding are investigated. In conclusion, it is shown that the Stressed-Arch system not only provides an optimized light steel structure up to 30% lighter than its conventional competitors but also streamlines the process of building erection and minimizes the construction time while preventing the risks of working at height.

Keywords: large span structure, pre-stressed steel truss, stressed-arch building, stress-erection, steel structure

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Authors: Jennifer A. Kowalkowski

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Production agriculture (farming) is a physically, emotionally, and cognitively stressful occupation, where workers have little control over the stressors that impact both their work and their lives. In an occupation already rife with hazards, these occupational-related stressors have been shown to increase farm workers’ risks for illness, injury, disability, and death associated with their work. Despite efforts to mitigate the negative health effects from occupational-related stress (ORS) and to promote health and well-being (HWB) among farmers in the US, marked improvements have not been attained. Social support accessed through social networks has been shown to buffer against the negative health effects from stress, yet no studies have directly examined these relationships among farmers. The purpose of this study was to use social network analysis to explore the social networks of farm owner-operators and the social supports available to them for mitigating the negative health effects of ORS. A convenience sample of 71 farm owner-operators from a Midwestern County in the US completed and returned a mailed survey (55.5% response rate) that solicited information about their social networks related to ORS. Farmers reported an average of 2.4 individuals in their personal networks and higher levels of comfort discussing ORS with female network members. Farmers also identified few connections (3.4% density) and indicated low comfort with members of affiliation networks specific to ORS. Findings from this study highlighted that farmers accessed different social networks and resources for their personal HWB than for issues related to occupational(farm-related) health and safety. In addition, farmers’ social networks for personal HWB were smaller, with different relational characteristics than reported in studies of farmers’ social networks related to occupational health and safety. Collectively, these findings suggest that farmers conceptualize personal HWB differently than farm health and safety. Therefore, the same research approaches and targets that guide occupational health and safety research may not be appropriate for personal HWB for farmers. Interventions and programming targeting ORS and HWB have largely been offered through the same platforms or mechanisms as occupational health and safety programs. This may be attributed to the significant overlap between the farm as a family business and place of residence, or that ORS stems from farm-related issues. However, these assumptions translated to health research of farmers and farm families from the occupational health and safety literature have not been directly studied or challenged. Thismay explain why past interventions have not been effective at improving health outcomes for farmers and farm families. A close examination of findings from this study raises important questions for researchers who study agricultural health. Findings from this study have significant implications for future research agendas focused on addressing ORS, HWB, and health disparities for farmersand farm families.

Keywords: agricultural health, occupational-related stress, social networks, well-being

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Authors: Emilio A. Berny-Brandt, Sonia E. Ruiz

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Steel tubular towers serving as support structures for large wind turbines are subject to several hundred million stress cycles arising from the turbulent nature of the wind. This causes high-cycle fatigue which can govern tower design. The practice of maintaining the support structure after wind turbines reach its typical 20-year design life have become common, but without quantifying the changes in the reliability on the tower. There are several studies on this topic, but most of them are based on the S-N curve approach using the Miner’s rule damage summation method, the de-facto standard in the wind industry. However, the qualitative nature of Miner’s method makes desirable the use of fracture mechanics to measure the effects of fatigue in the capacity curve of the structure, which is important in order to evaluate the integrity and reliability of these towers. Temporal and spatially varying wind speed time histories are simulated based on power spectral density and coherence functions. Simulations are then applied to a SAP2000 finite element model and step-by-step analysis is used to obtain the stress time histories for a range of representative wind speeds expected during service conditions of the wind turbine. Rainflow method is then used to obtain cycle and stress range information of each of these time histories and a statistical analysis is performed to obtain the distribution parameters of each variable. Monte Carlo simulation is used here to evaluate crack growth over time in the tower base using the Paris-Erdogan equation. A nonlinear static pushover analysis to assess the capacity curve of the structure after a number of years is performed. The capacity curves are then used to evaluate the changes in reliability of a steel tower located in Oaxaca, Mexico, where wind energy facilities are expected to grow in the near future. Results show that fatigue on the tower base can have significant effects on the structural capacity of the wind turbine, especially after the 20-year design life when the crack growth curve starts behaving exponentially.

Keywords: crack growth, fatigue, Monte Carlo simulation, structural reliability, wind turbines

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Authors: Ella Tyuryumina, Alexey Neznanov

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Finding algorithms to predict the growth of tumors has piqued the interest of researchers ever since the early days of cancer research. A number of studies were carried out as an attempt to obtain reliable data on the natural history of breast cancer growth. Mathematical modeling can play a very important role in the prognosis of tumor process of breast cancer. However, mathematical models describe primary tumor growth and metastases growth separately. Consequently, we propose a mathematical growth model for primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoM-IV and corresponding software. We are interested in: 1) modelling the whole natural history of primary tumor and primary metastases; 2) developing adequate and precise CoM-IV which reflects relations between PT and MTS; 3) analyzing the CoM-IV scope of application; 4) implementing the model as a software tool. The CoM-IV is based on exponential tumor growth model and consists of a system of determinate nonlinear and linear equations; corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and primary metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for primary metastases; 3) ‘visible period’ for primary metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of the period of primary metastases appearance; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of BC and facilitate optimization of diagnostic tests. The following are calculated by CoM-IV: the number of doublings for ‘nonvisible’ and ‘visible’ growth period of primary metastases; tumor volume doubling time (days) for ‘nonvisible’ and ‘visible’ growth period of primary metastases. The CoM-IV enables, for the first time, to predict the whole natural history of primary tumor and primary metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-IV describes correctly primary tumor and primary distant metastases growth of IV (T1-4N0-3M1) stage with (N1-3) or without regional metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and manifestation of primary metastases.

Keywords: breast cancer, exponential growth model, mathematical modelling, primary metastases, primary tumor, survival

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Authors: H. Jamili, S. Shakiba

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Today, one of the main concerns of human beings is facing the unpleasant changes of the environment. Buildings are responsible for a significant amount of natural resources consumption and carbon emissions production. In such a situation, this thought comes to mind that changing each building into a phenomenon of benefit to the environment. A change in a way that each building functions as an element that supports the environment, and construction, in addition to answering the need of humans, is encouraged, the way planting a tree is, and it is no longer seen as a threat to alive beings and the planet. Prospect: Today, different ideas of developing materials that can smartly function are realizing. For instance, Programmable Materials, which in different conditions, can respond appropriately to the situation and have features of modification in shape, size, physical properties and restoration, and repair quality. Studies are to progress having this purpose to plan for these materials in a way that they are easily available, and to meet this aim, there is no need to use expensive materials and high technologies. In these cases, physical attributes of materials undertake the role of sensors, wires and actuators then materials will become into robots itself. In fact, we experience robotics without robots. In recent decades, AI and technology advances have dramatically improving the performance of materials. These achievements are a combination of software optimizations and physical productions such as multi-materials 3D printing. These capabilities enable us to program materials in order to change shape, appearance, and physical properties to interact with different situations. nIt is expected that further achievements like Memory Materials and Self-learning Materials are also added to the Smart Materials family, which are affordable, available, and of use for a variety of applications and industries. From the architectural standpoint, the building skin is significantly considered in this research, concerning the noticeable surface area the buildings skin have in urban space. The purpose of this research would be finding a way that the programmable materials be used in building skin with the aim of having an effective and positive interaction. A Pixel Façade would be a solution for programming a building skin. The Pixel Facadeincludes components that contain a series of attributes that help buildings for their needs upon their environmental criteria. A PIXEL contains series of smart materials and digital controllers together. It not only benefits its physical properties, such as control the amount of sunlight and heat, but it enhances building performance by providing a list of features, depending on situation criteria. The features will vary depending on locations and have a different function during the daytime and different seasons. The primary role of a PIXEL FAÇADE can be defined as filtering pollutions (for inside and outside of the buildings) and providing clean energy as well as interacting with other PIXEL FACADES to estimate better reactions.

Keywords: building skin, environmental crisis, pixel facade, programmable materials, smart materials

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Authors: Benjamin Blat Belmonte, Stephan Rinderknecht

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The transition to electric vehicles (EVs) stands at the forefront of innovative strategies designed to address environmental concerns and reduce fossil fuel dependency. As the number of EVs on the roads increases, so too does the potential for their integration into energy markets. This research dives deep into the transformative possibilities of using electric vehicle fleets, specifically electric bus fleets, not just as consumers but as active participants in the energy market. This paper investigates the feasibility and grid effects of electric vehicle fleet operators in the energy market. Our objective centers around a comprehensive exploration of the sector coupling domain, with an emphasis on the economic potential in both electricity and balancing markets. Methodologically, our approach combines data mining techniques with thorough pre-processing, pulling from a rich repository of electricity and balancing market data. Our findings are grounded in the actual operational realities of the bus fleet operator in Darmstadt, Germany. We employ a Mixed Integer Linear Programming (MILP) approach, with the bulk of the computations being processed on the High-Performance Computing (HPC) platform ‘Lichtenbergcluster’. Our findings underscore the compelling economic potential of EV fleets in the energy market. With electric buses becoming more prevalent, the considerable size of these fleets, paired with their substantial battery capacity, opens up new horizons for energy market participation. Notably, our research reveals that economic viability is not the sole advantage. Participating actively in the energy market also translates into pronounced positive effects on grid stabilization. Essentially, EV fleet operators can serve a dual purpose: facilitating transport while simultaneously playing an instrumental role in enhancing grid reliability and resilience. This research highlights the symbiotic relationship between the growth of EV fleets and the stabilization of the energy grid. Such systems could lead to both commercial and ecological advantages, reinforcing the value of electric bus fleets in the broader landscape of sustainable energy solutions. In conclusion, the electrification of transport offers more than just a means to reduce local greenhouse gas emissions. By positioning electric vehicle fleet operators as active participants in the energy market, there lies a powerful opportunity to drive forward the energy transition. This study serves as a testament to the synergistic potential of EV fleets in bolstering both economic viability and grid stabilization, signaling a promising trajectory for future sector coupling endeavors.

Keywords: electric vehicle fleet, sector coupling, optimization, electricity market, balancing market

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Authors: Charles Davidson

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This paper presents the Stoplight Analysis System of Partnering Organizations Readiness, offering a structured framework to evaluate conflict resolution collaboration feasibility, especially crucial in conflict areas, employing a colour-coded approach and specific assessment points, with implications for more informed decision-making and improved outcomes in peacebuilding initiatives. Derived from at total of 40 years of practical peacebuilding experience from the project’s two researchers as well as interviews of various other peacebuilding actors, this paper introduces the Stoplight Analysis System of Partnering Organizations Readiness, a comprehensive framework designed to facilitate effective collaboration in international/local peacebuilding partnerships by evaluating the readiness of both potential partner organisations and the location of the proposed project. ^The system employs a colour-coded approach, categorising potential partnerships into three distinct indicators: Red (no-go), Yellow (requires further research), and Green (promising, go ahead). Within each category, specific points are identified for assessment, guiding decision-makers in evaluating the feasibility and potential success of collaboration. The Red category signals significant barriers, prompting an immediate stoppage in the consideration of partnership. The Yellow category encourages deeper investigation to determine whether potential issues can be mitigated, while the Green category signifies organisations deemed ready for collaboration. This systematic and structured approach empowers decision-makers to make informed choices, enhancing the likelihood of successful and mutually beneficial partnerships. Methodologically, this paper utilised interviews from peacebuilders from around the globe, scholarly research of extant strategies, and a collaborative review of programming from the project’s two authors from their own time in the field. This method as a formalised model has been employed for the past two years across a litany of partnership considerations, and has been adjusted according to its field experimentation. This research holds significant importance in the field of conflict resolution as it provides a systematic and structured approach to peacebuilding partnership evaluation. In conflict-affected regions, where the dynamics are complex and challenging, the Stoplight Analysis System offers decision-makers a practical tool to assess the readiness of partnering organisations. This approach can enhance the efficiency of conflict resolution efforts by ensuring that resources are directed towards partnerships with a higher likelihood of success, ultimately contributing to more effective and sustainable peacebuilding outcomes.

Keywords: collaboration, conflict resolution, partnerships, peacebuilding

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Authors: Mercy Marimirofa, Farai Machinga, Alfred Zvoushe, Tsitsidzaishe Musvosvi

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Adolescent Birth rate (ABR) is an important indicator of both gender equality and equity in the country. This is the number of births to women aged between 15 and 19 years per 1000 live births. There has been a decreasing trend in ABR in Zimbabwe since 2014. However, the difference between rural areas and urban areas has continued to widen. A secondary analysis was conducted to assess the differences in ABR between the rural areas of Zimbabwe and the urban areas. This was also done to determine the root causes of high ABR in rural areas compared to urban areas and the impact this may cause to the economic development of the nation. The analysis was done according to geographical characteristics (provinces). A total of 69,335 females aged 10 to 19 years had live births among a total population of 791,914 females aged 15 to 19 years. The total Adolescent Birth rate in Zimbabwe is 87/1000 live births, while in rural areas, it is 114.4/1000 live births compared to urban areas, which is 49.7/1000 live births. A decrease in the ABR trends has been recorded since 2014 from 143/1000 live births among adolescents in rural areas to 97/1000 live births in urban areas. This shows that rural areas still have high rates of ABR compared to their urban counterparts, and the gap is still wide. High ABR is a result of early child marriages, teenage pregnancies as well as poverty. Most of these marriages (46%) are intergenerational relationships and have resulted in an increase in gender-based violence cases among adolescents, poor health outcomes, including pregnancy complications such as eclampsia, Cephalous Pelvic Disproportion (CPD), and obstructed labour. Maternal deaths among adolescence is also high compared to adults. Furthermore, the increase of school dropouts among adolescent girls is on the rise due to teen pregnancies. These challenges are being faced mostly by rural adolescent girls as compared to their urban counterparts. The widening gap in ABR between urban areas and rural areas is a matter of concern and needs to be addressed. There is a need to inform policy, programming, and interventions targeting rural areas to address the challenges and gaps in reducing ABR. This abstract is to inform policymakers on the strategies and resources required to address the challenges currently distressing adolescents. There is a need to improve access to Sexual and Reproductive Health (SRH) Services by adolescents and reduce the age of consent to access SRH services should be reduced from 18 years for ease access to young people to reduce teenage pregnancies. Comprehensive sexuality education, both in-school and out of school, should be strengthened to increase knowledge among young people on sexuality.

Keywords: adolescence birth rate, live birth, teenage pregnancies, SRH services

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Authors: Eric Awich Ochen

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The end of the conflict in Northern Uganda in 2006 brought about an opportunity for the youth to return to their original home and contribute to the peace building and development process of their communities. Post-conflict is used here to refer to the post-armed conflict situation and activities of rebels of Joseph Kony in northern Uganda. While the rebels remain very much active in the Sudan and Central African Republic, in Uganda the last confrontations occurred around 2006 or earlier, and communities have returned to their homes and began the process of rebuilding their lives. It is argued that socio-economic reconstruction is at the heart of peacebuilding and sustenance of positive peace in the aftermath of conflict, as it has a bearing on post-conflict stability and good governance. We recognize that several post-conflict interventions within Northern Uganda have targeted women and children with a strong emphasis on family socio-economic empowerment and capacity building, including access to micro finance. The aim of this study was to examine the participation of the youth in post-conflict peace building and development in Northern Uganda by assessing the breadth and width of their engagement and the stages of programming cycle that they are involved in, interrogating the space for participation and how they are facilitating or constraining participation. It was further aimed at examining the various dimensions of participation at play in Northern Uganda and where this fits within the conceptual debates on peace building and development in the region. Supporting young people emerging out of protracted conflict to re-establish meaningful socio-economic engagements and livelihoods is fundamental to their participation in the affairs of the community. The study suggests that in the post-conflict development context of Northern Uganda, participation has rarely been disaggregated or differentiated by sectors or groups. Where some disaggregation occurs, then the main emphasis has always been on either women or children. It appears therefore that little meaningful space has thus been created for young people to engage and participate in peace building initiatives within the region. In other cases where some space is created for youth participation, this has been in pre-conceived programs or interventions conceived by the development organizations with the youth or young people only invited to participate at particular stages of the project implementation cycle. Still within the implementation of the intervention, the extent to which young people participate is bounded, with little power to influence the course of the interventions or make major decisions. It is thus visible that even here young people mainly validate and legitimize what are predetermined processes only act as pawns in the major chess games played by development actors (dominant peace building partners). This paper, therefore, concludes that the engagement of the youth in post-conflict peace building has been quite problematic and tokenistic and has not given the adequate youth space within which they could ably participate and express themselves in the ensuing interventions.

Keywords: youth, conflict, peace building, participation

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Authors: Sangwoo Han, Saeed Khaleghi Rahimian, Ying Liu

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Vehicle electrification is gaining momentum, and many car manufacturers promise to deliver more electric vehicle (EV) models to consumers in the coming years. In controlling the battery pack, the battery management system (BMS) must maintain optimal battery performance while ensuring the safety of a battery pack. Tasks related to battery performance include determining state-of-charge (SOC), state-of-power (SOP), state-of-health (SOH), cell balancing, and battery charging. Safety related functions include making sure cells operate within specified, static and dynamic voltage window and temperature range, derating power, detecting faulty cells, and warning the user if necessary. The BMS often utilizes an RC circuit model to model a Li-ion cell because of its robustness and low computation cost among other benefits. Because an equivalent circuit model such as the RC model is not a physics-based model, it can never be a prognostic model to predict battery state-of-health and avoid any safety risk even before it occurs. A physics-based Li-ion cell model, on the other hand, is more capable at the expense of computation cost. To avoid the high computation cost associated with a full-order model, many researchers have demonstrated the use of a single particle model (SPM) for BMS applications. One drawback associated with the single particle modeling approach is that it forces to use the average current density in the calculation. The SPM would be appropriate for simulating drive cycles where there is insufficient time to develop a significant current distribution within an electrode. However, under a continuous or high-pulse electrical load, the model may fail to predict cell voltage or Li⁺ plating potential. To overcome this issue, a multi-particle reduced-order model is proposed here. The use of multiple particles combined with either linear or nonlinear charge-transfer reaction kinetics enables to capture current density distribution within an electrode under any type of electrical load. To maintain computational complexity like that of an SPM, governing equations are solved sequentially to minimize iterative solving processes. Furthermore, the model is validated against a full-order model implemented in COMSOL Multiphysics.

Keywords: battery management system, physics-based li-ion cell model, reduced-order model, single-particle and multi-particle model

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Authors: Edvard Kokanyan, Narine Babajanyan, Ninel Kokanyan, Marco Bazzan

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Lithium niobate (LN) crystals, renowned for their exceptional nonlinear optical, electro-optical, piezoelectric, and photorefractive properties, stand as foundational materials in diverse fields of study and application. While they have long been utilized in frequency converters of laser radiation, electro-optical modulators, and holographic information recording media, LN crystals doped with rare earth ions represent a compelling frontier for modern compact devices. These materials exhibit immense potential as key components in infrared lasers, optical sensors, self-cooling systems, and radiation balanced laser setups. In this study, we present the successful synthesis of Ho-doped lithium niobate (LN:Ho) thin films on sapphire substrates employing the Sol-Gel technique. The films exhibit a strong crystallographic orientation along the perpendicular direction to the substrate surface, with X-ray diffraction analysis confirming the predominant alignment of the film's "c" axis, notably evidenced by the intense (006) reflection peak. Further characterization through Raman spectroscopy, employing a confocal Raman microscope (LabRAM HR Evolution) with exciting wavelengths of 532 nm and 785 nm, unraveled intriguing insights. Under excitation with a 785 nm laser, Raman scattering obeyed selection rules, while employing a 532 nm laser unveiled additional forbidden lines reminiscent of behaviors observed in bulk LN:Ho crystals. These supplementary lines were attributed to luminescence induced by excitation at 532 nm. Leveraging data from anti-Stokes Raman lines facilitated the disentanglement of luminescence spectra from the investigated samples. Surface scanning affirmed the uniformity of both structure and luminescence across the thin films. Notably, despite the robust orientation of the "c" axis perpendicular to the substrate surface, Raman signals indicated a stochastic distribution of "a" and "b" axes, validating the mosaic structure of the films along the mentioned axis. This study offers valuable insights into the structural properties of Ho-doped lithium niobate thin films, with the observed luminescence behavior holding significant promise for potential applications in optoelectronic devices.

Keywords: lithium niobate, Sol-Gel, luminescence, Raman spectroscopy

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Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

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Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: erodible beds, finite element method, finite volume method, nonlinear elasticity, shallow water equations, stresses in soil

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Authors: Anicet Dansou

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Textile reinforced concrete (TRC)is increasingly used nowadays in various fields, in particular civil engineering, where it is mainly used for the reinforcement of damaged reinforced concrete structures. TRC is a composite material composed of multi- or uni-axial textile reinforcements coupled with a fine-grained cementitious matrix. The TRC composite is an alternative solution to the traditional Fiber Reinforcement Polymer (FRP) composite. It has good mechanical performance and better temperature stability but also, it makes it possible to meet the criteria of sustainable development better.TRCs are highly anisotropic composite materials with nonlinear hardening behavior; their macroscopic behavior depends on multi-scale mechanisms. The characterization of these materials through numerical simulation has been the subject of many studies. Since TRCs are multiscale material by definition, numerical multi-scale approaches have emerged as one of the most suitable methods for the simulation of TRCs. They aim to incorporate information pertaining to microscale constitute behavior, mesoscale behavior, and macro-scale structure response within a unified model that enables rapid simulation of structures. The computational costs are hence significantly reduced compared to standard simulation at a fine scale. The fine scale information can be implicitly introduced in the macro scale model: approaches of this type are called non-classical. A representative volume element is defined, and the fine scale information are homogenized over it. Analytical and computational homogenization and nested mesh methods belong to these approaches. On the other hand, in classical approaches, the fine scale information are explicitly introduced in the macro scale model. Such approaches pertain to adaptive mesh refinement strategies, sub-modelling, domain decomposition, and multigrid methods This research presents the main principles of numerical multiscale approaches. Advantages and limitations are identified according to several criteria: the assumptions made (fidelity), the number of input parameters required, the calculation costs (efficiency), etc. A bibliographic study of recent results and advances and of the scientific obstacles to be overcome in order to achieve an effective simulation of textile reinforced concrete in civil engineering is presented. A comparative study is further carried out between several methods for the simulation of TRCs used for the structural reinforcement of reinforced concrete structures.

Keywords: composites structures, multiscale methods, numerical modeling, textile reinforced concrete

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Authors: Demelash Kassaye

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The Ethiopia case study reveals a unique model of community policing that has developed from a particular political context in which there is a history of violent political transition, a political structure characterized by ethnic federalism and a political ideology that straddles liberal capitalism and democracy on the one hand, and state-led development and centralized control on the other. The police see community policing as a way to reduce crime. Communities speak about community policing as an opportunity to take on policing responsibilities themselves. Both of these objectives are brought together in an overarching rhetoric of community policing as a way of ‘mobilizing for development’ – whereby the community cooperate with the police to reduce crime, which otherwise inhibits development progress. Community policing in Amhara has primarily involved the placement of Community Police Officers at the kebele level across the State. In addition, a number of structures have also been established in the community, including Advisory Councils, Conflict Resolving Committees, family police and the use of shoe shiner’s and other trade associations as police informants. In addition to these newly created structures, community policing also draws upon pre-existing customary actors, such as militia and elders. Conflict Resolving Committees, Community Police Officers and elders were reported as the most common first ports of call when community members experience a crime. The analysis highlights that the model of community policing in Amhara increased communities’ access to policing services, although this is not always attended by increased access to justice. Community members also indicate that public perceptions of the police have improved since the introduction of community policing, in part due to individual Community Police Officers who have, with limited resources, innovated some impressive strategies to improve safety in their neighborhoods. However, more broadly, community policing has provided the state with more effective surveillance of the population – a potentially oppressive function in the current political context. Ultimately, community policing in Amhara is anything but straightforward. It has been a process of attempting to demonstrate the benefits of newfound (and controversial) ‘democracy’ following years of dictatorship, drawing on generations of customary dispute resolution, providing both improved access to security for communities and an enhanced surveillance capacity for the state. For external actors looking to engage in community policing, this case study reveals the importance of close analysis in assessing potential merits, risks and entry points of programming. Factors found to be central in shaping the nature of community policing in the Amhara case include the structure of the political system, state-society relations, cultures dispute resolution and political ideology.

Keywords: community policing, community, militias, ethiopia

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Authors: X. Li, Y. Liu, H. Wong, B. Pardoen, A. Fabbri, F. McGregor, E. Liu

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The target of this paper is to investigate how saturated poroelastic soils subject to freezing temperatures behave and how different boundary conditions can intervene and affect the thermo-hydro-mechanical (THM) responses, based on a particular but classical configuration of a finite homogeneous soil layer studied by Terzaghi. The essential relations on the constitutive behavior of a freezing soil are firstly recalled: ice crystal - liquid water thermodynamic equilibrium, hydromechanical constitutive equations, momentum balance, water mass balance, and the thermal diffusion equation, in general, non-linear case where material parameters are state-dependent. The system of equations is firstly linearized, assuming all material parameters to be constants, particularly the permeability of liquid water, which should depend on the ice content. Two analytical solutions solved by the classic Laplace transform are then developed, accounting for two different sets of boundary conditions. Afterward, the general non-linear equations with state-dependent parameters are solved using a commercial code COMSOL based on finite elements method to obtain numerical results. The validity of this numerical modeling is partially verified using the analytical solution in the limiting case of state-independent parameters. Comparison between the results given by the linearized analytical solutions and the non-linear numerical model reveals that the above-mentioned linear computation will always underestimate the liquid pore pressure and displacement, whatever the hydraulic boundary conditions are. In the nonlinear model, the faster growth of ice crystals, accompanying the subsequent reduction of permeability of freezing soil layer, makes a longer duration for the depressurization of water liquid and slower settlement in the case where the ground surface is swiftly covered by a thin layer of ice, as well as a bigger global liquid pressure and swelling in the case of the impermeable ground surface. Nonetheless, the analytical solutions based on linearized equations give a correct order-of-magnitude estimate, especially at moderate temperature variations, and remain a useful tool for preliminary design checks.

Keywords: chemical potential, cryosuction, Laplace transform, multiphysics coupling, phase transformation, thermodynamic equilibrium

Procedia PDF Downloads 80

Authors: Saeed Nazari, Masoom Nazari, Ali Hejazi, Siamak Sanoobari Ghazi Jahani, Mohammad Dehghani, Javad Vakili

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More than ever, digitization is an imperative for businesses to keep their competitive advantages, foster innovation and reduce paperwork. To design and successfully implement digital transformation initiatives within process safety management system, employees need to be equipped with the right tool, frameworks, and best practices. we developed a unique full stack application so-called SHEQTool which is entirely dynamic based on our extensive expertise, experience, and client feedback to help business processes particularly operations safety management. We use our best knowledge and scientific methodologies published by CCPS and OSHA Guidelines to streamline operations and integrated them into task management within Petrochemical Companies. We digitalize their main process safety management system elements and their sub elements such as hazard identification and risk management, training and communication, inspection and audit, critical changes management, contractor management, permit to work, pre-start-up safety review, incident reporting and investigation, emergency response plan, personal protective equipment, occupational health, and action management in a fully customizable manner with no programming needs for users. We review the feedback from main actors within petrochemical plant which highlights improving their business performance and productivity as well as keep tracking their functions’ key performance indicators (KPIs) because it; 1) saves time, resources, and costs of all paperwork on our businesses (by Digitalization); 2) reduces errors and improve performance within management system by covering most of daily software needs of the organization and reduce complexity and associated costs of numerous tools and their required training (One Tool Approach); 3) focuses on management systems and integrate functions and put them into traceable task management (RASCI and Flowcharting); 4) helps the entire enterprise be resilient to any change of your processes, technologies, assets with minimum costs (through Organizational Resilience); 5) reduces significantly incidents and errors via world class safety management programs and elements (by Simplification); 6) gives the companies a systematic, traceable, risk based, process based, and science based integrated management system (via proper Methodologies); 7) helps business processes complies with ISO 9001, ISO 14001, ISO 45001, ISO 31000, best practices as well as legal regulations by PDCA approach (Compliance).

Keywords: process, safety, digitalization, management, risk, incident, SHEQTool, OSHA, CCPS

Procedia PDF Downloads 69

Authors: A. Rezaei, M. Huisman, W. Van Paepegem

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Atomic interactions in molecular systems are mainly studied by particle mechanics. Nevertheless, researches have also put on considerable effort to simulate them using continuum methods. In early 2000, simple equivalent finite element models have been developed to study the mechanical properties of carbon nanotubes and graphene in composite materials. Afterward, many researchers have employed similar structural simulation approaches to obtain mechanical properties of nanostructured materials, to simplify interface behavior of fiber-reinforced composites, and to simulate defects in carbon nanotubes or graphene sheets, etc. These structural approaches, however, are limited to small deformations due to complicated local rotational coordinates. This article proposes a method for the finite element simulation of molecular mechanics. For ease in addressing the approach, here it is called Structural Finite Element Molecular Modeling (SFEMM). SFEMM method improves the available structural approaches for large deformations, without using any rotational degrees of freedom. Moreover, the method simulates molecular conformation, which is a big advantage over the previous approaches. Technically, this method uses nonlinear multipoint constraints to simulate kinematics of the atomic multibody interactions. Only truss elements are employed, and the bond potentials are implemented through constitutive material models. Because the equilibrium bond- length, bond angles, and bond-torsion potential energies are intrinsic material parameters, the model is independent of initial strains or stresses. In this paper, the SFEMM method has been implemented in ABAQUS finite element software. The constraints and material behaviors are modeled through two Fortran subroutines. The method is verified for the bond-stretch, bond-angle and bond-torsion of carbon atoms. Furthermore, the capability of the method in the conformation simulation of molecular structures is demonstrated via a case study of a graphene sheet. Briefly, SFEMM builds up a framework that offers more flexible features over the conventional molecular finite element models, serving the structural relaxation modeling and large deformations without incorporating local rotational degrees of freedom. Potentially, the method is a big step towards comprehensive molecular modeling with finite element technique, and thereby concurrently coupling an atomistic domain to a solid continuum domain within a single finite element platform.

Keywords: finite element, large deformation, molecular mechanics, structural method

Procedia PDF Downloads 153

Authors: K. Khouzami, J. Brassinne, C. Branca, E. Van Ruymbeke, B. Nysten, G. D’Angelo

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The development of hybrid organic-inorganic nanocomposites has recently attracted great interest. Typically, polymer silicates represent an emerging class of polymeric nanocomposites that offer superior material properties compared to each compound alone. Among these materials, complexes based on silicate clay and polysaccharides are one of the most promising nanocomposites. The strong electrostatic interaction between chitosan and montmorillonite can induce what is called physical hydrogel, where the coordination bonds or physical crosslinks may associate and dissociate reversibly and in a short time. These mechanisms could be the main origin of the uniqueness of their rheological behavior. However, owing to their structure intrinsically heterogeneous and/or the lack of dissipated energy, they are usually brittle, possess a poor toughness and may not have sufficient mechanical strength. Consequently, the properties of these nanocomposites cannot respond to some requirements of many applications in several fields. To address the issue of weak mechanical properties, covalent chemical crosslink bonds can be introduced to the physical hydrogel. In this way, quite homogeneous dually crosslinked microstructures with high dissipated energy and enhanced mechanical strength can be engineered. In this work, we have prepared a series of chitosan-montmorillonite nanocomposites chemically crosslinked by addition of poly (ethylene glycol) diglycidyl ether. This study aims to provide a better understanding of the mechanical behavior of dually crosslinked chitosan-based nanocomposites by relating it to their microstructures. In these systems, the variety of microstructures is obtained by modifying the number of cross-links. Subsequently, a superior uniqueness of the rheological properties of chemically crosslinked chitosan-montmorillonite nanocomposites is achieved, especially at the highest percentage of clay. Their rheological behaviors depend on the clay/chitosan ratio and the crosslinking. All specimens exhibit a viscous rheological behavior over the frequency range investigated. The flow curves of the nanocomposites show a Newtonian plateau at very low shear rates accompanied by a quite complicated nonlinear decrease with increasing the shear rate. Crosslinking induces a shear thinning behavior revealing the formation of network-like structures. Fitting shear viscosity curves via Ostward-De Waele equation disclosed that crosslinking and clay addition strongly affect the pseudoplasticity of the nanocomposites for shear rates γ ̇>20.

Keywords: chitosan, crossliking, nanocomposites, rheological properties

Procedia PDF Downloads 148

Authors: P. Mounnarath, U. Schmitz, Ch. Zhang

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Fragility analysis is an effective tool for the seismic vulnerability assessment of civil structures in the last several years. The design of the expansion joints according to various bridge design codes is almost inconsistent, and only a few studies have focused on this problem so far. In this study, the influence of the expansion joint clearances between the girder ends and the abutment backwalls on the seismic fragility assessment of continuous integral bridge frames is investigated. The gaps (ranging from 60 mm, 150 mm, 250 mm and 350 mm) are designed by following two different bridge design code specifications, namely, Caltrans and Eurocode 8-2. Five bridge models are analyzed and compared. The first bridge model serves as a reference. This model uses three-dimensional reinforced concrete fiber beam-column elements with simplified supports at both ends of the girder. The other four models also employ reinforced concrete fiber beam-column elements but include the abutment backfill stiffness and four different gap values. The nonlinear time history analysis is performed. The artificial ground motion sets, which have the peak ground accelerations (PGAs) ranging from 0.1 g to 1.0 g with an increment of 0.05 g, are taken as input. The soil-structure interaction and the P-Δ effects are also included in the analysis. The component fragility curves in terms of the curvature ductility demand to the capacity ratio of the piers and the displacement demand to the capacity ratio of the abutment sliding bearings are established and compared. The system fragility curves are then obtained by combining the component fragility curves. Our results show that in the component fragility analysis, the reference bridge model exhibits a severe vulnerability compared to that of other sophisticated bridge models for all damage states. In the system fragility analysis, the reference curves illustrate a smaller damage probability in the earlier PGA ranges for the first three damage states, they then show a higher fragility compared to other curves in the larger PGA levels. In the fourth damage state, the reference curve has the smallest vulnerability. In both the component and the system fragility analysis, the same trend is found that the bridge models with smaller clearances exhibit a smaller fragility compared to that with larger openings. However, the bridge model with a maximum clearance still induces a minimum pounding force effect.

Keywords: expansion joint clearance, fiber beam-column element, fragility assessment, time history analysis

Procedia PDF Downloads 437

Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

Procedia PDF Downloads 491

Authors: Ben Levenger

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Social life revolves around a central meeting place or gathering space. It is where the community integrates, earns social skills, and ultimately becomes part of the community. Following this premise, public spaces are one of the most important spaces that downtowns offer, providing locations for people to be witnessed, heard, and most importantly, seamlessly integrate into the downtown as part of the community. To facilitate this, these local spaces must be envisioned and designed to meet the changing needs of a downtown, offering a space and purpose for everyone. This paper will dive deep into analyzing, designing, and implementing public space design for small plazas or gathering spaces. These spaces often require a detailed level of study, followed by a broad stroke of design implementation, allowing for adaptability. This paper will highlight how to assess needs, define needed types of spaces, outline a program for spaces, detail elements of design to meet the needs, assess your new space, and plan for change. This study will provide participants with the necessary framework for conducting a grass-roots-level assessment of public space and programming, including short-term and long-term improvements. Participants will also receive assessment tools, sheets, and visual representation diagrams. Urbanism, for the sake of urbanism, is an exercise in aesthetic beauty. An economic improvement or benefit must be attained to solidify these efforts' purpose further and justify the infrastructure or construction costs. We will deep dive into case studies highlighting economic impacts to ground this work in quantitative impacts. These case studies will highlight the financial impact on an area, measuring the following metrics: rental rates (per sq meter), tax revenue generation (sales and property), foot traffic generation, increased property valuations, currency expenditure by tenure, clustered development improvements, cost/valuation benefits of increased density in housing. The economic impact results will be targeted by community size, measuring in three tiers: Sub 10,000 in population, 10,001 to 75,000 in population, and 75,000+ in population. Through this classification breakdown, the participants can gauge the impact in communities similar to their work or for which they are responsible. Finally, a detailed analysis of specific urbanism enhancements, such as plazas, on-street dining, pedestrian malls, etc., will be discussed. Metrics that document the economic impact of each enhancement will be presented, aiding in the prioritization of improvements for each community. All materials, documents, and information will be available to participants via Google Drive. They are welcome to download the data and use it for their purposes.

Keywords: downtown, economic development, planning, strategic

Procedia PDF Downloads 85

Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

Procedia PDF Downloads 151

Authors: Ana Julia Acevedo Urquiaga, Jose A. Acevedo Suarez, Ana Julia Urquiaga Rodriguez, Neyfe Sablon Cossio

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Despite the progress made in logistics and supply chains fields, it is unavoidable the development of business models that use efficiently information to facilitate the integrated logistics flows management between partners. Collaborative management is an important tool for materializing the cooperation between companies, as a way to achieve the supply chain efficiency and effectiveness. The first face of this research was a comprehensive analysis of the collaborative planning on the Cuban companies. It is evident that they have difficulties in supply chains planning where production, supplies and replenishment planning are independent tasks, as well as logistics and distribution operations. Large inventories generate serious financial and organizational problems for entities, demanding increasing levels of working capital that cannot be financed. Problems were found in the efficient application of Information and Communication Technology on business management. The general objective of this work is to develop a methodology that allows the deployment of a planning and control system in a coordinated way on the medicine’s logistics system in Cuba. To achieve these objectives, several mechanisms of supply chain coordination, mathematical programming models, and other management techniques were analyzed to meet the requirements of collaborative logistics management in Cuba. One of the findings is the practical and theoretical inadequacies of the studied models to solve the current situation of the Cuban logistics systems management. To contribute to the tactical-operative management of logistics, the Collaborative Logistics Flow Management Model (CLFMM) is proposed as a tool for the balance of cycles, capacities, and inventories, always to meet the final customers’ demands in correspondence with the service level expected by these. The CLFMM has as center the supply chain planning and control system as a unique information system, which acts on the processes network. The development of the model is based on the empirical methods of analysis-synthesis and the study cases. Other finding is the demonstration of the use of a single information system to support the supply chain logistics management, allows determining the deadlines and quantities required in each process. This ensures that medications are always available to patients and there are no faults that put the population's health at risk. The simulation of planning and control with the CLFMM in medicines such as dipyrone and chlordiazepoxide, during 5 months of 2017, permitted to take measures to adjust the logistic flow, eliminate delayed processes and avoid shortages of the medicines studied. As a result, the logistics cycle efficiency can be increased to 91%, the inventory rotation would increase, and this results in a release of financial resources.

Keywords: collaborative management, medicine logistic system, supply chain planning, tactical-operative planning

Procedia PDF Downloads 177

Authors: Nirjhar Dhang, S. Vinay Kumar

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Concrete is a non-homogeneous mix of coarse aggregates, sand, cement, air-voids and interfacial transition zone (ITZ) around aggregates. Adoption of these complex structures and material properties in numerical simulation would lead us to better understanding and design of concrete. In this work, the mesoscale model of concrete has been prepared from X-ray computerized tomography (CT) image. These images are converted into computer model and numerically simulated using commercially available finite element software. The mesoscale models are simulated under the influence of compressive displacement. The effect of shape and distribution of aggregates, continuous and discrete ITZ thickness, voids, and variation of mortar strength has been investigated. The CT scan of concrete cube consists of series of two dimensional slices. Total 49 slices are obtained from a cube of 150mm and the interval of slices comes approximately 3mm. In CT scan images, the same cube can be CT scanned in a non-destructive manner and later the compression test can be carried out in a universal testing machine (UTM) for finding its strength. The image processing and extraction of mortar and aggregates from CT scan slices are performed by programming in Python. The digital colour image consists of red, green and blue (RGB) pixels. The conversion of RGB image to black and white image (BW) is carried out, and identification of mesoscale constituents is made by putting value between 0-255. The pixel matrix is created for modeling of mortar, aggregates, and ITZ. Pixels are normalized to 0-9 scale considering the relative strength. Here, zero is assigned to voids, 4-6 for mortar and 7-9 for aggregates. The value between 1-3 identifies boundary between aggregates and mortar. In the next step, triangular and quadrilateral elements for plane stress and plane strain models are generated depending on option given. Properties of materials, boundary conditions, and analysis scheme are specified in this module. The responses like displacement, stresses, and damages are evaluated by ABAQUS importing the input file. This simulation evaluates compressive strengths of 49 slices of the cube. The model is meshed with more than sixty thousand elements. The effect of shape and distribution of aggregates, inclusion of voids and variation of thickness of ITZ layer with relation to load carrying capacity, stress-strain response and strain localizations of concrete have been studied. The plane strain condition carried more load than plane stress condition due to confinement. The CT scan technique can be used to get slices from concrete cores taken from the actual structure, and the digital image processing can be used for finding the shape and contents of aggregates in concrete. This may be further compared with test results of concrete cores and can be used as an important tool for strength evaluation of concrete.

Keywords: concrete, image processing, plane strain, interfacial transition zone

Procedia PDF Downloads 241

Authors: Kateriina Rannula, Elle Sõrmus, Siret Piirsalu

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Mixed generation classroom is a phenomenon that current higher education establishments are faced with daily trying to meet the needs of modern labor market with its emphasis on lifelong learning and retraining. Representatives of mainly X and Y generations in one classroom acquiring higher education is a challenge to lecturers considering all the characteristics that differ one generation from another. The importance of outlining different strategies and considering the needs of the students lies in the necessity for everyone to acquire the maximum of the provided knowledge as well as to understand each other to study together in one classroom and successfully cooperate in future workplaces. In addition to different generations, there are also learners with different native languages which have an impact on reading and understanding texts in third languages, including possible translation. Current research aims to investigate, describe and compare reading strategies among the representatives of generation X and Y. Hypotheses were formulated - representatives of generation X and Y use different reading strategies which is also different among first and third year students of the before mentioned generations. Current study is an empirical, qualitative study. To achieve the aim of the research, relevant literature was analyzed and a semi-structured questionnaire conducted among the first and third year students of Tallinn Health Care College. Questionnaire consisted of 25 statements on the text reading strategies, 3 multiple choice questions on preferences considering the design and medium of the text, and three open questions on the translation process when working with a text in student’s third language. The results of the questionnaire were categorized, analyzed and compared. Both, generation X and Y described their reading strategies to be 'scanning' and 'surfing'. Compared to generation X, first year generation Y learners valued interactivity and nonlinear texts. Students frequently used strategies of skimming, scanning, translating and highlighting together with relevant-thinking and assistance-seeking. Meanwhile, the third-year generation Y students no longer frequently used translating, resourcing and highlighting while Generation X learners still incorporated these strategies. Knowing about different needs of the generations currently inside the classrooms and on the labor market enables us with tools to provide sustainable education and grants the society a work force that is more flexible and able to move between professions. Future research should be conducted in order to investigate the amount of learning and strategy- adoption between generations. As for reading, main suggestions arising from the research are as follows: make a variety of materials available to students; allow them to select what they want to read and try to make those materials visually attractive, relevant, and appropriately challenging for learners considering the differences of generations.

Keywords: generation X, generation Y, learning strategies, reading strategies

Procedia PDF Downloads 180

Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

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The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

Procedia PDF Downloads 133

Authors: Ella Tyuryumina, Alexey Neznanov

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This study is an attempt to obtain reliable data on the natural history of breast cancer growth. We analyze the opportunities for using classical mathematical models (exponential and logistic tumor growth models, Gompertz and von Bertalanffy tumor growth models) to try to describe growth of the primary tumor and the secondary distant metastases of human breast cancer. The research aim is to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoMPaS and corresponding software. We are interested in: 1) modelling the whole natural history of the primary tumor and the secondary distant metastases; 2) developing adequate and precise CoMPaS which reflects relations between the primary tumor and the secondary distant metastases; 3) analyzing the CoMPaS scope of application; 4) implementing the model as a software tool. The foundation of the CoMPaS is the exponential tumor growth model, which is described by determinate nonlinear and linear equations. The CoMPaS corresponds to TNM classification. It allows to calculate different growth periods of the primary tumor and the secondary distant metastases: 1) ‘non-visible period’ for the primary tumor; 2) ‘non-visible period’ for the secondary distant metastases; 3) ‘visible period’ for the secondary distant metastases. The CoMPaS is validated on clinical data of 10-years and 15-years survival depending on the tumor stage and diameter of the primary tumor. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer growth models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. The CoMPaS model and predictive software: a) fit to clinical trials data; b) detect different growth periods of the primary tumor and the secondary distant metastases; c) make forecast of the period of the secondary distant metastases appearance; d) have higher average prediction accuracy than the other tools; e) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoMPaS: the number of doublings for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases. The CoMPaS enables, for the first time, to predict ‘whole natural history’ of the primary tumor and the secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on the primary tumor sizes. Summarizing: a) CoMPaS describes correctly the primary tumor growth of IA, IIA, IIB, IIIB (T1-4N0M0) stages without metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and inception of the secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, metastases in lymph nodes, primary tumor, survival

Procedia PDF Downloads 341

Authors: Eun Mi Ryu, Ah Young An, Ji Yeon Kang, Yeong Soo Shin, Hee Sun Kim

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As the number of fire incidents has been increased, fire incidents significantly damage economy and human lives. Especially when high strength reinforced concrete is exposed to high temperature due to a fire, deterioration occurs such as loss in strength and elastic modulus, cracking, and spalling of the concrete. Therefore, it is important to understand risk of structural safety in building structures by studying structural behaviors and rehabilitation of fire damaged high strength concrete structures. This paper aims at investigating rehabilitation effect on fire damaged high strength concrete beams using experimental and analytical methods. In the experiments, flexural specimens with high strength concrete are exposed to high temperatures according to ISO 834 standard time temperature curve. After heated, the fire damaged reinforced concrete (RC) beams having different cover thicknesses and fire exposure time periods are rehabilitated by removing damaged part of cover thickness and filling polymeric mortar into the removed part. From four-point loading test, results show that maximum loads of the rehabilitated RC beams are 1.8~20.9% higher than those of the non-fire damaged RC beam. On the other hand, ductility ratios of the rehabilitated RC beams are decreased than that of the non-fire damaged RC beam. In addition, structural analyses are performed using ABAQUS 6.10-3 with same conditions as experiments to provide accurate predictions on structural and mechanical behaviors of rehabilitated RC beams. For the rehabilitated RC beam models, integrated temperature–structural analyses are performed in advance to obtain geometries of the fire damaged RC beams. After spalled and damaged parts are removed, rehabilitated part is added to the damaged model with material properties of polymeric mortar. Three dimensional continuum brick elements are used for both temperature and structural analyses. The same loading and boundary conditions as experiments are implemented to the rehabilitated beam models and nonlinear geometrical analyses are performed. Structural analytical results show good rehabilitation effects, when the result predicted from the rehabilitated models are compared to structural behaviors of the non-damaged RC beams. In this study, fire damaged high strength concrete beams are rehabilitated using polymeric mortar. From four point loading tests, it is found that such rehabilitation is able to make the structural performance of fire damaged beams similar to non-damaged RC beams. The predictions from the finite element models show good agreements with the experimental results and the modeling approaches can be used to investigate applicability of various rehabilitation methods for further study.

Keywords: fire, high strength concrete, rehabilitation, reinforced concrete beam

Procedia PDF Downloads 446

Authors: Priyanka Chaudhary, M. Rizwan

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This paper presents a grid synchronization technique based on adaptive notch filter for SPV (Solar Photovoltaic) system along with MPPT (Maximum Power Point Tracking) techniques. An efficient grid synchronization technique offers proficient detection of various components of grid signal like phase and frequency. It also acts as a barrier for harmonics and other disturbances in grid signal. A reference phase signal synchronized with the grid voltage is provided by the grid synchronization technique to standardize the system with grid codes and power quality standards. Hence, grid synchronization unit plays important role for grid connected SPV systems. As the output of the PV array is fluctuating in nature with the meteorological parameters like irradiance, temperature, wind etc. In order to maintain a constant DC voltage at VSC (Voltage Source Converter) input, MPPT control is required to track the maximum power point from PV array. In this work, a variable step size P & O (Perturb and Observe) MPPT technique with DC/DC boost converter has been used at first stage of the system. This algorithm divides the dPpv/dVpv curve of PV panel into three separate zones i.e. zone 0, zone 1 and zone 2. A fine value of tracking step size is used in zone 0 while zone 1 and zone 2 requires a large value of step size in order to obtain a high tracking speed. Further, adaptive notch filter based control technique is proposed for VSC in PV generation system. Adaptive notch filter (ANF) approach is used to synchronize the interfaced PV system with grid to maintain the amplitude, phase and frequency parameters as well as power quality improvement. This technique offers the compensation of harmonics current and reactive power with both linear and nonlinear loads. To maintain constant DC link voltage a PI controller is also implemented and presented in this paper. The complete system has been designed, developed and simulated using SimPower System and Simulink toolbox of MATLAB. The performance analysis of three phase grid connected solar photovoltaic system has been carried out on the basis of various parameters like PV output power, PV voltage, PV current, DC link voltage, PCC (Point of Common Coupling) voltage, grid voltage, grid current, voltage source converter current, power supplied by the voltage source converter etc. The results obtained from the proposed system are found satisfactory.

Keywords: solar photovoltaic systems, MPPT, voltage source converter, grid synchronization technique

Procedia PDF Downloads 594