Search results for: graph500 benchmark

Authors: Shilpa Sahoo, Michel Louge, Anthony Reeves, Olivier Desjardins, Susan Daniel, Sadik Omowunmi

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The microgravity on the International Space Station (ISS) was exploited to study the imbibition of water into a network of hydrophilic cylindrical capillaries on time and length scales long enough to observe details hitherto inaccessible under Earth gravity. When a drop touches a porous medium, it spreads as if laid on a composite surface. The surface first behaves as a hydrophobic material, as liquid must penetrate pores filled with air. When contact is established, some of the liquid is drawn into pores by a capillarity that is resisted by viscous forces growing with length of the imbibed region. This process always begins with an inertial regime that is complicated by possible contact pinning. To study imbibition on Earth, time and distance must be shrunk to mitigate gravity-induced distortion. These small scales make it impossible to observe the inertial and pinning processes in detail. Instead, in the International Space Station (ISS), astronaut Luca Parmitano slowly extruded water spheres until they touched any of nine capillary plates. The 12mm diameter droplets were large enough for high-speed GX1050C video cameras on top and side to visualize details near individual capillaries, and long enough to observe dynamics of the entire imbibition process. To investigate the role of contact pinning, a text matrix was produced which consisted nine kinds of porous capillary plates made of gold-coated brass treated with Self-Assembled Monolayers (SAM) that fixed advancing and receding contact angles to known values. In the ISS, long-term microgravity allowed unambiguous observations of the role of contact line pinning during the inertial phase of imbibition. The high-speed videos of spreading and imbibition on the porous plates were analyzed using computer vision software to calculate the radius of the droplet contact patch with the plate and height of the droplet vs time. These observations are compared with numerical simulations and with data that we obtained at the ESA ZARM free-fall tower in Bremen with a unique mechanism producing relatively large water spheres and similarity in the results were observed. The data obtained from the ISS can be used as a benchmark for further numerical simulations in the field.

Keywords: droplet imbibition, hydrophilic surface, inertial phase, porous medium

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Authors: Ledi Neçaj

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Objectives: The target of this paper is (1) to explain objectively physical activity model throughout three chronic cardiopulmonary conditions, and (2) to study the connection among physical activity dimensions with disease severity, self-reported physical and emotional functioning, and exercise performance. Material and Methods: This is a cross-sectional study of patients in their domestic environment. Patients with cardiopulmonary diseases were: chronic obstructive pulmonary disease (COPD), (n-63), coronary heart failure (n=60), and patients with implantable cardioverter defibrillator (n=60). Main results measures: Seven ambulatory physical activity dimensions (total steps, percentage time active, percentage time ambulating at low, medium, and hard intensity, maximum cadence for 30 non-stop minutes, and peak performance) have been measured with an accelerometer. Results: Subjects with COPD had the lowest amount of ambulatory physical activity compared with topics with coronary heart failure and cardiac dysrhythmias (all 7 interest dimensions, P<.05); total step counts have been: 5319 as opposed to 7464 as opposed to 9570, respectively. Six-minute walk distance becomes correlated (r=.44-.65, P<.01) with all physical activity dimensions inside the COPD pattern, the most powerful correlations being with total steps and peak performance. In topics with cardiac impairment, maximal oxygen intake had the most effective small to slight correlations with five of the physical activity dimensions (r=.22-.40, P<.05). In contrast, correlations among 6-minute walk test distance and physical activity have been higher (r=.48-.61, P<.01) albeit in a smaller pattern of most effective patients with coronary heart failure. For all three samples, self-reported physical and mental health functioning, age, frame mass index, airflow obstruction, and ejection fraction had both exceptionally small and no significant correlations with physical activity. Conclusions: Findings from this study present a profitable benchmark of physical activity patterns in individuals with cardiopulmonary diseases for comparison with future studies. All seven dimensions of ambulatory physical activity have disfavor between subjects with COPD, heart failure, and cardiac dysrhythmias. Depending on the research or clinical goal, the use of one dimension, such as total steps, may be sufficient. Although physical activity had high correlations with performance on a six-minute walk test relative to other variables, accelerometers-based physical activity monitoring provides unique, important information about real-world behavior in patients with cardiopulmonary not already captured with existing measures.

Keywords: ambulatory physical activity, walking, monitoring, COPD, heart failure, implantable defibrillator, exercise performance

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Authors: Chiahsu Yang, Peiling Wu, Ted Ho

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From emphasizing economic development to stressing public happiness, the international community mainly hopes to be able to understand whether the quality of life for the public is becoming better. The Better Life Index (BLI) constructed by OECD uses living conditions and quality of life as starting points to cover 11 areas of life and to convey the state of the general public’s well-being. In light of the BLI framework, the Directorate General of Budget, Accounting and Statistics (DGBAS) of the Executive Yuan instituted the Gross National Happiness Index to understand the needs of the general public and to measure the progress of the aforementioned conditions in residents across the island. Whereas living conditions consist of income and wealth, jobs and earnings, and housing conditions, health status, work and life balance, education and skills, social connections, civic engagement and governance, environmental quality, personal security. The ICT area consists of health care, living environment, ICT-enabled communication, transportation, government, education, pleasure, purchasing, job & employment. In the wake of further science and technology development, rapid formation of information societies, and closer integration between lifestyles and information societies, the public’s well-being within information societies has indeed become a noteworthy topic. the Board of Science and Technology of the Executive Yuan use the OECD’s BLI as a reference in the establishment of the Taiwan-specific ICT-Enabled Better Life Index. Using this index, the government plans to examine whether the public’s quality of life is improving as well as measure the public’s satisfaction with current digital quality of life. This understanding will enable the government to gauge the degree of influence and impact that each dimension of digital services has on digital life happiness while also serving as an important reference for promoting digital service development. The content of the ICT Enabled Better Life Index. Information and communications technology (ICT) has been affecting people’s living styles, and further impact people’s quality of life (QoL). Even studies have shown that ICT access and usage have both positive and negative impact on life satisfaction and well-beings, many governments continue to invest in e-government programs to initiate their path to information society. This research is the few attempts to link the e-government benchmark to the subjective well-being perception, and further address the gap between user’s perception and existing hard data assessment, then propose a model to trace measurement results back to the original public policy in order for policy makers to justify their future proposals.

Keywords: information and communications technology, quality of life, satisfaction, well-being

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Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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Authors: Sylvain Perrin, Thomas Saillour

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The Grande-Motte port and seafront development project on the French Mediterranean coastline entailed evaluating wave impact loads (pressures and forces) on the new beach seawall and comparing the resulting scour potential at the base of the existing and new seawall. A physical model was built at ARTELIA’s hydraulics laboratory in Grenoble (France) to provide insight into the evolution of scouring overtime at the front of the wall, quasi-static and impulsive wave force intensity and distribution on the wall, and water and sand overtopping discharges over the wall. The beach was constituted of fine sand and approximately 50 m wide above mean sea level (MSL). Seabed slopes were in the range of 0.5% offshore to 1.5% closer to the beach. A smooth concrete structure will replace the existing concrete seawall with an elevated curved crown wall. Prior the start of breaking (at -7 m MSL contour), storm-driven maximum spectral significant wave heights of 2.8 m and 3.2 m were estimated for the benchmark historical storm event dated of 1997 and the 50-year return period storms respectively, resulting in 1 m high waves at the beach. For the wave load assessment, a tensor scale measured wave forces and moments and five piezo / piezo-resistive pressure sensors were placed on the wall. Light-weight sediment physical model and pressure and force measurements were performed with scale 1:18. The polyvinyl chloride light-weight particles used to model the prototype silty sand had a density of approximately 1 400 kg/m3 and a median diameter (d50) of 0.3 mm. Quantitative assessments of the seabed evolution were made using a measuring rod and also a laser scan survey. Testing demonstrated the occurrence of numerous impulsive wave impacts on the reflector (22%), induced not by direct wave breaking but mostly by wave run-up slamming on the top curved part of the wall. Wave forces of up to 264 kilonewtons and impulsive pressure spikes of up to 127 kilonewtons were measured. Maximum scour of -0.9 m was measured for the new seawall versus -0.6 m for the existing seawall, which is imputable to increased wave reflection (coefficient was 25.7 - 30.4% vs 23.4 - 28.6%). This paper presents a methodology for the setup and operation of a physical model in order to assess the hydrodynamic and morphodynamic processes at a beach seawall during storms events. It discusses the pros and cons of such methodology versus others, notably regarding structures peculiarities and model effects.

Keywords: beach, impacts, scour, seawall, waves

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Authors: Ali Abdul Kadhim, Fue Lien

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Solid particle distribution on an impingement surface has been simulated utilizing a graphical processing unit (GPU). In-house computational fluid dynamics (CFD) code has been developed to investigate a 3D turbulent impinging jet using the lattice Boltzmann method (LBM) in conjunction with large eddy simulation (LES) and the multiple relaxation time (MRT) models. This paper proposed an improvement in the LBM-cellular automata (LBM-CA) probabilistic method. In the current model, the fluid flow utilizes the D3Q19 lattice, while the particle model employs the D3Q27 lattice. The particle numbers are defined at the same regular LBM nodes, and transport of particles from one node to its neighboring nodes are determined in accordance with the particle bulk density and velocity by considering all the external forces. The previous models distribute particles at each time step without considering the local velocity and the number of particles at each node. The present model overcomes the deficiencies of the previous LBM-CA models and, therefore, can better capture the dynamic interaction between particles and the surrounding turbulent flow field. Despite the increasing popularity of LBM-MRT-CA model in simulating complex multiphase fluid flows, this approach is still expensive in term of memory size and computational time required to perform 3D simulations. To improve the throughput of each simulation, a single GeForce GTX TITAN X GPU is used in the present work. The CUDA parallel programming platform and the CuRAND library are utilized to form an efficient LBM-CA algorithm. The methodology was first validated against a benchmark test case involving particle deposition on a square cylinder confined in a duct. The flow was unsteady and laminar at Re=200 (Re is the Reynolds number), and simulations were conducted for different Stokes numbers. The present LBM solutions agree well with other results available in the open literature. The GPU code was then used to simulate the particle transport and deposition in a turbulent impinging jet at Re=10,000. The simulations were conducted for L/D=2,4 and 6, where L is the nozzle-to-surface distance and D is the jet diameter. The effect of changing the Stokes number on the particle deposition profile was studied at different L/D ratios. For comparative studies, another in-house serial CPU code was also developed, coupling LBM with the classical Lagrangian particle dispersion model. Agreement between results obtained with LBM-CA and LBM-Lagrangian models and the experimental data is generally good. The present GPU approach achieves a speedup ratio of about 350 against the serial code running on a single CPU.

Keywords: CUDA, GPU parallel programming, LES, lattice Boltzmann method, MRT, multi-phase flow, probabilistic model

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Authors: Anisur Rahman, Sabyasachi Behera, Pawan Pathak, Benazir Patil, Rajesh Khanna

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Background: Nearly half of India’s population is expected to reside in urban areas by 2030. The extent to which India's health system can provide for this large and growing city-based population will determine the country's success in achieving universal health coverage and improved national health indices. National Urban Health Mission (NUHM) strive for improving access to primary health care in urban areas. Implementation of NUHM solicits sensitive, effective and sustainable strategies to strengthen the service delivery mechanisms. The Challenge Initiative for Healthy Cities (TCIHC) is working with the Government of India and three provincial states to develop effective service delivery mechanisms for reproductive, maternal, newborn and child health (RMNCH) through a health systems approach for the urban poor. Method: A rapid assessment study was conceptualized and executed to generate evidence in order to address the challenges impeding in functioning of urban health facilities to deliver effective, efficient and equitable health care services in 7 cities spread across two project States viz. Madhya Pradesh and Odisha. Results: The findings of the assessment reflect: 1. The overall ecosystem pertaining to planning and management of public health interventions is not conducive. 2. The challenges regarding population dynamics like migration keeps on influencing the demand-supply-enabling environment triangle for both public and private service providers. 3. Lack of norms for planning and benchmark for service delivery further impedes urban health system as a whole. 4. Operationalization of primary level services have enough potential to meet the demand of slum dwellers at large. 5. Lack of policy driven strategies on how to integrate the NUHM with other thematic areas of Maternal, Newborn & Child Health (MNCH) and Family Planning (FP). 5. The inappropriate capacity building and acute shortage of Human Resources has huge implication on service provisioning and adherence to the service delivery protocols. Conclusion: The findings from rapid assessment are aimed to inform pertinent stakeholders to develop a multiyear city health action plan to strengthen the health systems in order to improve the efficacy of service delivery mechanism in urban settings.

Keywords: city health plan, health system, rapid assessment, urban mission

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Authors: Arvind Salem

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Voters across the country are transferring the power of redistricting from the state legislatures to commissions to secure “fairer” districts by curbing the influence of gerrymandering on redistricting. Gerrymandering, intentionally drawing distorted districts to achieve political advantage, has become extremely prevalent, generating widespread voter dissatisfaction and resulting in states adopting commissions for redistricting. However, the efficacy of these commissions is dubious, with some arguing that they constitute a panacea for gerrymandering, while others contend that commissions have relatively little effect on gerrymandering. A result showing that commissions are effective would allay these fears, supplying ammunition for activists across the country to advocate for commissions in their state and reducing the influence of gerrymandering across the nation. However, a result against commissions may reaffirm doubts about commissions and pressure lawmakers to make improvements to commissions or even abandon the commission system entirely. Additionally, these commissions are publicly funded: so voters have a financial interest and responsibility to know if these commissions are effective. Currently, nine states place commissions in charge of redistricting, Arizona, California, Colorado, Michigan, Idaho, Montana, Washington, and New Jersey (Hawaii also has a commission but will be excluded for reasons mentioned later). This study compares the degree of gerrymandering in the 2022 election (“after”) to the election in which voters decided to adopt commissions (“before”). The before-election provides a valuable benchmark for assessing the efficacy of commissions since voters in those elections clearly found the districts to be unfair; therefore, comparing the current election to that one is a good way to determine if commissions have improved the situation. At the time Hawaii adopted commissions, it was merely a single at-large district, so it is before metrics could not be calculated, and it was excluded. This study will use three methods to quantify the degree of gerrymandering: the efficiency gap, the percentage of seats and the percentage of votes difference, and the mean-median difference. Each of these metrics has unique advantages and disadvantages, but together, they form a balanced approach to quantifying gerrymandering. The study uses a Wilcoxon Signed-Rank Test with a null hypothesis that the value of the metrics is greater than or equal to after the election than before and an alternative hypothesis that the value of these metrics is greater in the before the election than after using a 0.05 significance level and an expected difference of 0. Accepting the alternative hypothesis would constitute evidence that commissions reduce gerrymandering to a statistically significant degree. However, this study could not conclude that commissions are effective. The p values obtained for all three metrics (p=0.42 for the efficiency gap, p=0.94 for the percentage of seats and percentage of votes difference, and p=0.47 for the mean-median difference) were extremely high and far from the necessary value needed to conclude that commissions are effective. These results halt optimism about commissions and should spur serious discussion about the effectiveness of these commissions and ways to change them moving forward so that they can accomplish their goal of generating fairer districts.

Keywords: commissions, elections, gerrymandering, redistricting

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Authors: Dragan Ribarić

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We employ the so-called problem-dependent linked interpolation concept to develop two cubic 4-node quadrilateral Mindlin plate finite elements with 12 external degrees of freedom. In the problem-independent linked interpolation, the interpolation functions are independent of any problem material parameters and the rotation fields are not expressed in terms of the nodal displacement parameters. On the contrary, in the problem-dependent linked interpolation, the interpolation functions depend on the material parameters and the rotation fields are expressed in terms of the nodal displacement parameters. Two cubic 4-node quadrilateral plate elements are presented, named Q4-U3 and Q4-U3R5. The first one is modelled with one displacement and two rotation degrees of freedom in every of the four element nodes and the second element has five additional internal degrees of freedom to get polynomial completeness of the cubic form and which can be statically condensed within the element. Both elements are able to pass the constant-bending patch test exactly as well as the non-zero constant-shear patch test on the oriented regular mesh geometry in the case of cylindrical bending. In any mesh shape, the elements have the correct rank and only the three eigenvalues, corresponding to the solid body motions are zero. There are no additional spurious zero modes responsible for instability of the finite element models. In comparison with the problem-independent cubic linked interpolation implemented in Q9-U3, the nine-node plate element, significantly less degrees of freedom are employed in the model while retaining the interpolation conformity between adjacent elements. The presented elements are also compared to the existing problem-independent quadratic linked-interpolation element Q4-U2 and to the other known elements that also use the quadratic or the cubic linked interpolation, by testing them on several benchmark examples. Simple functional upgrading from the quadratic to the cubic linked interpolation, implemented in Q4-U3 element, showed no significant improvement compared to the quadratic linked form of the Q4-U2 element. Only when the additional bubble terms are incorporated in the displacement and rotation function fields, which complete the full cubic linked interpolation form, qualitative improvement is fulfilled in the Q4-U3R5 element. Nevertheless, the locking problem exists even for the both presented elements, like in all pure displacement elements when applied to very thin plates modelled by coarse meshes. But good and even slightly better performance can be noticed for the Q4-U3R5 element when compared with elements from the literature, if the model meshes are moderately dense and the plate thickness not extremely thin. In some cases, it is comparable to or even better than Q9-U3 element which has as many as 12 more external degrees of freedom. A significant improvement can be noticed in particular when modeling very skew plates and models with singularities in the stress fields as well as circular plates with distorted meshes.

Keywords: Mindlin plate theory, problem-independent linked interpolation, problem-dependent interpolation, quadrilateral displacement-based plate finite elements

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Authors: Mihail Calalb

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The aim of this research is to identify ways for achieving sustainable conceptual understanding within science lessons. For this purpose, a set of teaching and learning strategies, parts of the theory of visible teaching and learning (VTL), is studied. As a result, a new didactic approach named "learning by being" is proposed and its correlation with educational paradigms existing nowadays in science teaching domain is analysed. In the context of VTL the author describes the main strategies of "learning by being" such as guided self-scaffolding, structuring of information, and recurrent use of previous knowledge or help seeking. Due to the synergy effect of these learning strategies applied simultaneously in class, the impact factor of learning by being on cognitive achievement of students is up to 93 % (the benchmark level is equal to 40% when an experienced teacher applies permanently the same conventional strategy during two academic years). The key idea in "learning by being" is the assumption by the student of cognitive goals. From this perspective, the article discusses the role of student’s personal learning effort within several teaching strategies employed in VTL. The research results emphasize that three mandatory student – related moments are present in each constructivist teaching approach: a) students’ personal learning effort, b) student – teacher mutual feedback and c) metacognition. Thus, a successful educational strategy will target to achieve an involvement degree of students into the class process as high as possible in order to make them not only know the learning objectives but also to assume them. In this way, we come to the ownership of cognitive goals or students’ deep intrinsic motivation. A series of approaches are inherent to the students’ ownership of cognitive goals: independent research (with an impact factor on cognitive achievement equal to 83% according to the results of VTL); knowledge of success criteria (impact factor – 113%); ability to reveal similarities and patterns (impact factor – 132%). Although it is generally accepted that the school is a public service, nonetheless it does not belong to entertainment industry and in most of cases the education declared as student – centered actually hides the central role of the teacher. Even if there is a proliferation of constructivist concepts, mainly at the level of science education research, we have to underline that conventional or frontal teaching, would never disappear. Research results show that no modern method can replace an experienced teacher with strong pedagogical content knowledge. Such a teacher will inspire and motivate his/her students to love and learn physics. The teacher is precisely the condensation point for an efficient didactic strategy – be it constructivist or conventional. In this way, we could speak about "hybridized teaching" where both the student and the teacher have their share of responsibility. In conclusion, the core of "learning by being" approach is guided learning effort that corresponds to the notion of teacher–student harmonic oscillator, when both things – guidance from teacher and student’s effort – are equally important.

Keywords: conceptual understanding, learning by being, ownership of cognitive goals, science learning

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Authors: Ozlem Uguz, Ali Demirci, Hanzade Haykiri-Acma, Serdar Yaman

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Lignitic coal holds its position as Turkey’s most important indigenous energy source to generate energy in thermal power plants. Hence, efficient and environmental-friendly use of lignite in electricity generation is of great importance. Thus, clean coal technologies have been planned to mitigate emissions and provide more efficient burning in power plants. In this context, oxygen enriched combustion (oxy-combustion) is regarded as one of the clean coal technologies, which based on burning with oxygen concentrations higher than that in air. As it is known that the most of the Turkish coals are low rank with high mineral matter content, unburnt carbon trapped in ash is, unfortunately, high, and it leads significant losses in the overall efficiencies of the thermal plants. Besides, the necessity of burning huge amounts of these low calorific value lignites to get the desired amount of energy also results in the formation of large amounts of ash that is rich in unburnt carbon. Oxygen enriched combustion technology enables to increase the burning efficiency through the complete burning of almost all of the carbon content of the fuel. This also contributes to the protection of air quality and emission levels drop reasonably. The aim of this study is to investigate the unburnt carbon content and the burning reactivities of several different lignite samples under oxygen enriched conditions. For this reason, the combined effects of temperature and oxygen/nitrogen ratios in the burning atmosphere were investigated and interpreted. To do this, Turkish lignite samples from Adıyaman-Gölbaşı and Kütahya-Tunçbilek regions were characterized first by proximate and ultimate analyses and the burning profiles were derived using DTA (Differential Thermal Analysis) curves. Then, these lignites were subjected to slow burning process in a horizontal tube furnace at different temperatures (200ºC, 400ºC, 600ºC for Adıyaman-Gölbaşı lignite and 200ºC, 450ºC, 800ºC for Kütahya-Tunçbilek lignite) under atmospheres having O₂+N₂ proportions of 21%O₂+79%N₂, 30%O₂+70%N₂, 40%O₂+60%N₂, and 50%O₂+50%N₂. These burning temperatures were specified based on the burning profiles derived from the DTA curves. The residues obtained from these burning tests were also analyzed by proximate and ultimate analyses to detect the unburnt carbon content along with the unused energy potential. Reactivity of these lignites was calculated using several methodologies. Burning yield under air condition (21%O₂+79%N₂) was used a benchmark value to compare the effectiveness of oxygen enriched conditions. It was concluded that oxygen enriched combustion method enhanced the combustion efficiency and lowered the unburnt carbon content of ash. Combustion of low-rank coals under oxygen enriched conditions was found to be a promising way to improve the efficiency of the lignite-firing energy systems. However, cost-benefit analysis should be considered for a better justification of this method since the use of more oxygen brings an unignorable additional cost.

Keywords: coal, energy, oxygen enriched combustion, reactivity

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Authors: M. Verde, G. Falzarano

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The paper examines the connection between corporate social responsibility (CSR), capability approach and poverty reduction; in particular, the local employment development (LED) by way of CSR initiatives. The joint action of LED/CSR results in a win-win situation, not only for the enterprises but also for all the stakeholders involved; in this regard, subsidiarity and coordination between national and regional/local authorities are central to a socially-oriented market economy. In the first section, the CSR is analysed on the basis of its social function in the fight against poverty, as a 'capabilities deprivation'. In the central part, the attention is focused on the relationship between CSR and LED; ergo, on the role of the enterprises in fostering capabilities development (the employment). Besides, all the potential solutions are presented, stressing the possible combinations, in the last part. The benchmark is the enterprise as an economic and a social institution: the business should not be combined with profit merely, paying more attention to its sustainable impact and social contribution. In which way could it be possible? The answer is the CSR. The impact of CSR on poverty reduction is still little explored. The companies help to reduce poverty through economic contribution, human rights and social inclusion; hence, the business becomes an 'agent of development' in order to fight against 'inequality'. The starting point is the pyramid of social responsibility, where ethic and philanthropic responsibilities involve programmes and actions aimed at personal development of the individuals, improving human standard of living in all forms, including poverty, when people do not have a choice between different 'life options', ranging from level of education to employment. At this point, CSR comes into play and works on two dimensions: poverty reduction and poverty prevention, by means of a series of initiatives: first of all, job creation and precarious work reduction. Empowerment of the local actors, financial support and combination of top down and bottom up initiatives are some of CSR areas of activity. Several positive effects occur on individual levels of educations, access to capital, individual health status, empowerment of youth and woman, access to social networks and it was observed that these effects depend on the type of CSR strategy. Indeed, CSR programmes should take into account fundamental criteria, such as the transparency, the information about benefits, a coordination unit among institutions and more clear guidelines. In this way, the advantages to the corporate reputation and to the community translate into a better job matching on the labour market, inter alia. It is important to underline that the success depends on the specific measures of the areas in question, by adapting them to the local needs, in light of general principles and index; therefore, the concrete commitment of the all stakeholders involved is decisive in order to achieve the goals. The enterprise would represent a concrete contribution for the pursuit of sustainable development and for the dissemination of a social and well being awareness.

Keywords: capability approach, local employment development, poverty, social inclusion

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Authors: Alexandru-Ion Marinescu

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There exist a plethora of methods in the scientific literature which tackle the well-established task of credit score evaluation. In its most abstract form, a credit scoring algorithm takes as input several credit applicant properties, such as age, marital status, employment status, loan duration, etc. and must output a binary response variable (i.e. “GOOD” or “BAD”) stating whether the client is susceptible to payment return delays. Data imbalance is a common occurrence among financial institution databases, with the majority being classified as “GOOD” clients (clients that respect the loan return calendar) alongside a small percentage of “BAD” clients. But it is the “BAD” clients we are interested in since accurately predicting their behavior is crucial in preventing unwanted loss for loan providers. We add to this whole context the constraint that the algorithm must yield an actual, tractable mathematical formula, which is friendlier towards financial analysts. To this end, we have turned to genetic algorithms and genetic programming, aiming to evolve actual mathematical expressions using specially tailored mutation and crossover operators. As far as data representation is concerned, we employ a very flexible mechanism – LINQ expression trees, readily available in the C# programming language, enabling us to construct executable pieces of code at runtime. As the title implies, they model trees, with intermediate nodes being operators (addition, subtraction, multiplication, division) or mathematical functions (sin, cos, abs, round, etc.) and leaf nodes storing either constants or variables. There is a one-to-one correspondence between the client properties and the formula variables. The mutation and crossover operators work on a flattened version of the tree, obtained via a pre-order traversal. A consequence of our chosen technique is that we can identify and discard client properties which do not take part in the final score evaluation, effectively acting as a dimensionality reduction scheme. We compare ourselves with state of the art approaches, such as support vector machines, Bayesian networks, and extreme learning machines, to name a few. The data sets we benchmark against amount to a total of 8, of which we mention the well-known Australian credit and German credit data sets, and the performance indicators are the following: percentage correctly classified, area under curve, partial Gini index, H-measure, Brier score and Kolmogorov-Smirnov statistic, respectively. Finally, we obtain encouraging results, which, although placing us in the lower half of the hierarchy, drive us to further refine the algorithm.

Keywords: expression trees, financial credit scoring, genetic algorithm, genetic programming, symbolic evolution

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Authors: Juan S. Mantilla, Peter Thomson

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Seismic events may result in discomfort on occupants of the buildings, structural damage or even buildings collapse. Traditional design aims to reduce dynamic response of structures by increasing stiffness, thus increasing the construction costs and the design forces. Structural control systems arise as an alternative to reduce these dynamic responses. A commonly used control systems in buildings are the passive friction dampers, which adds energy dissipation through damping mechanisms induced by sliding friction between their surfaces. Passive friction dampers are usually implemented on the diagonal of braced buildings, but such devices have the disadvantage that are optimal for a range of sliding force and out of that range its efficiency decreases. The above implies that each passive friction damper is designed, built and commercialized for a specific sliding/clamping force, in which the damper shift from a locked state to a slip state, where dissipates energy through friction. The risk of having a variation in the efficiency of the device according to the sliding force is that the dynamic properties of the building can change as result of many factor, even damage caused by a seismic event. In this case the expected forces in the building can change and thus considerably reduce the efficiency of the damper (that is designed for a specific sliding force). It is also evident than when a seismic event occurs the forces in each floor varies in the time what means that the damper's efficiency is not the best at all times. Semi-Active Friction devices adapt its sliding force trying to maintain its motion in the slipping phase as much as possible, because of this, the effectiveness of the device depends on the control strategy used. This paper deals with the development and performance evaluation of a low cost Semiactive Variable Friction Damper (SAVFD) in reduced scale to reduce vibrations of structures subject to earthquakes. The SAVFD consist in a (1) hydraulic brake adapted to (2) a servomotor which is controlled with an (3) Arduino board and acquires accelerations or displacement from (4) sensors in the immediately upper and lower floors and a (5) power supply that can be a pair of common batteries. A test structure, based on a Benchmark structure for structural control, was design and constructed. The SAVFD and the structure are experimentally characterized. A numerical model of the structure and the SAVFD is developed based on the dynamic characterization. Decentralized control algorithms were modeled and later tested experimentally using shaking table test using earthquake and frequency chirp signals. The controlled structure with the SAVFD achieved reductions greater than 80% in relative displacements and accelerations in comparison to the uncontrolled structure.

Keywords: earthquake response, friction damper, semiactive control, shaking table

Procedia PDF Downloads 357

Authors: M. Tammaro, S. Manzo, J. Rimauro, A. Salluzzo, S. Schiavo

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The solar photovoltaic (PV) modules are considered to have a negligible environmental impact compared to the fossil energy. Therefore also the waste management and the corresponding potential environmental hazard needs to be considered. The case of the photovoltaic panel is unique because the time lag from the manufacturing to the decommissioning as waste usually takes 25-30 years. Then the environmental hazard associated with end life of PV panels has been largely related to their metal contents. The principal concern regards the presence of heavy metals as Cd in thin film (TF) modules or Pb and Cr in crystalline silicon (c-Si) panels. At the end of life of PV panels, these dangerous substances could be released in the environment, if special requirements for their disposal are not adopted. Nevertheless, in literature, only a few experimental study about metal emissions from silicon crystalline/thin film panels and the corresponding environmental effect are present. As part of a study funded by the Italian national consortium for the waste collection and recycling (COBAT), the present work was aimed to analyze experimentally the potential release into the environment of hazardous elements, particularly metals, from PV waste. In this paper, for the first time, eighteen releasable metals a large number of photovoltaic panels, by c-Si and TF, manufactured in the last 30 years, together with the environmental effects by a battery of ecotoxicological tests, were investigated. Leaching tests are conducted on the crushed samples of PV module. The test is conducted according to Italian and European Standard procedure for hazard assessment of the granular waste and of the sludge. The sample material is shaken for 24 hours in HDPE bottles with an overhead mixer Rotax 6.8 VELP at indoor temperature and using pure water (18 MΩ resistivity) as leaching solution. The liquid-to-solid ratio was 10 (L/S=10, i.e. 10 liters of water per kg of solid). The ecotoxicological tests were performed in the subsequent 24 hours. A battery of toxicity test with bacteria (Vibrio fisheri), algae (Pseudochirneriella subcapitata) and crustacea (Daphnia magna) was carried out on PV panel leachates obtained as previously described and immediately stored in dark and at 4°C until testing (in the next 24 hours). For understand the actual pollution load, a comparison with the current European and Italian benchmark limits was performed. The trend of leachable metal amount from panels in relation to manufacturing years was then highlighted in order to assess the environmental sustainability of PV technology over time. The experimental results were very heterogeneous and show that the photovoltaic panels could represent an environmental hazard. The experimental results showed that the amounts of some hazardous metals (Pb, Cr, Cd, Ni), for c-Si and TF, exceed the law limits and they are a clear indication of the potential environmental risk of photovoltaic panels "as a waste" without a proper management.

Keywords: photovoltaic panel, environment, ecotoxicity, metals emission

Procedia PDF Downloads 244

Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

Procedia PDF Downloads 285

Authors: C. Amer, M. Sahin

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The design of an optimised horizontal axis 5-meter-long wind turbine rotor blade in according with IEC 61400-2 standard is a research and development project in order to fulfil the requirements of high efficiency of torque from wind production and to optimise the structural components to the lightest and strongest way possible. For this purpose, a research study is presented here by focusing on the structural characteristics of a composite wind turbine blade via finite element modelling and analysis tools. In this work, first, the required data regarding the general geometrical parts are gathered. Then, the airfoil geometries are created at various sections along the span of the blade by using CATIA software to obtain the two surfaces, namely; the suction and the pressure side of the blade in which there is a hat shaped fibre reinforced plastic spar beam, so-called chassis starting at 0.5m from the root of the blade and extends up to 4 m and filled with a foam core. The root part connecting the blade to the main rotor differential metallic hub having twelve hollow threaded studs is then modelled. The materials are assigned as two different types of glass fabrics, polymeric foam core material and the steel-balsa wood combination for the root connection parts. The glass fabrics are applied using hand wet lay-up lamination with epoxy resin as METYX L600E10C-0, is the unidirectional continuous fibres and METYX XL800E10F having a tri-axial architecture with fibres in the 0,+45,-45 degree orientations in a ratio of 2:1:1. Divinycell H45 is used as the polymeric foam. The finite element modelling of the blade is performed via MSC PATRAN software with various meshes created on each structural part considering shell type for all surface geometries, and lumped mass were added to simulate extra adhesive locations. For the static analysis, the boundary conditions are assigned as fixed at the root through aforementioned bolts, where for dynamic analysis both fixed-free and free-free boundary conditions are made. By also taking the mesh independency into account, MSC NASTRAN is used as a solver for both analyses. The static analysis aims the tip deflection of the blade under its own weight and the dynamic analysis comprises normal mode dynamic analysis performed in order to obtain the natural frequencies and corresponding mode shapes focusing the first five in and out-of-plane bending and the torsional modes of the blade. The analyses results of this study are then used as a benchmark prior to modal testing, where the experiments over the produced wind turbine rotor blade has approved the analytical calculations.

Keywords: dynamic analysis, fiber reinforced composites, horizontal axis wind turbine blade, hand-wet layup, modal testing

Procedia PDF Downloads 402

Authors: Chin-Chia Jane

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In a transportation network, travel time refers to the transmission time from source node to destination node, whereas reliability refers to the probability of a successful connection from source node to destination node. With an increasing emphasis on quality of service (QoS), both performance indexes are significant in the design and analysis of transportation systems. In this work, we extend the well-known flow network model for transportation networks so that travel time and reliability are integrated into the QoS measurement simultaneously. In the extended model, in addition to the general arc capacities, each intermediate node has a time weight which is the travel time for per unit of commodity going through the node. Meanwhile, arcs and nodes are treated as binary random variables that switch between operation and failure with associated probabilities. For pre-specified travel time limitation and demand requirement, the QoS of a transportation network is the probability that source can successfully transport the demand requirement to destination while the total transmission time is under the travel time limitation. This work is pioneering, since existing literatures that evaluate travel time reliability via a single optimization path, the proposed QoS focuses the performance of the whole network system. To compute the QoS of transportation networks, we first transfer the extended network model into an equivalent min-cost max-flow network model. In the transferred network, each arc has a new travel time weight which takes value 0. Each intermediate node is replaced by two nodes u and v, and an arc directed from u to v. The newly generated nodes u and v are perfect nodes. The new direct arc has three weights: travel time, capacity, and operation probability. Then the universal set of state vectors is recursively decomposed into disjoint subsets of reliable, unreliable, and stochastic vectors until no stochastic vector is left. The decomposition is made possible by applying existing efficient min-cost max-flow algorithm. Because the reliable subsets are disjoint, QoS can be obtained directly by summing the probabilities of these reliable subsets. Computational experiments are conducted on a benchmark network which has 11 nodes and 21 arcs. Five travel time limitations and five demand requirements are set to compute the QoS value. To make a comparison, we test the exhaustive complete enumeration method. Computational results reveal the proposed algorithm is much more efficient than the complete enumeration method. In this work, a transportation network is analyzed by an extended flow network model where each arc has a fixed capacity, each intermediate node has a time weight, and both arcs and nodes are independent binary random variables. The quality of service of the transportation network is an integration of customer demands, travel time, and the probability of connection. We present a decomposition algorithm to compute the QoS efficiently. Computational experiments conducted on a prototype network show that the proposed algorithm is superior to existing complete enumeration methods.

Keywords: quality of service, reliability, transportation network, travel time

Procedia PDF Downloads 194

Authors: Mao Zhaofang, Xu Yida, Fang Kan, Fu Enyuan, Zhao Zhao

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Nowadays, last-mile distribution plays an increasingly important role in the whole industrial chain delivery link and accounts for a large proportion of the whole distribution process cost. Promoting the upgrading of logistics networks and improving the layout of final distribution points has become one of the trends in the development of modern logistics. Due to the discrete and heterogeneous needs and spatial distribution of customer demand, which will lead to a higher delivery failure rate and lower vehicle utilization, last-mile delivery has become a time-consuming and uncertain process. As a result, courier companies have introduced a range of innovative parcel storage facilities, including pick-up points and lockers. The introduction of pick-up points and lockers has not only improved the users’ experience but has also helped logistics and courier companies achieve large-scale economy. Against the backdrop of the COVID-19 of the previous period, contactless delivery has become a new hotspot, which has also created new opportunities for the development of collection services. Therefore, a key issue for logistics companies is how to design/redesign their last-mile distribution network systems to create integrated logistics and distribution networks that consider pick-up points and lockers. This paper focuses on the introduction of self-pickup facilities in new logistics and distribution scenarios and the heterogeneous demands of customers. In this paper, we consider two types of demand, including ordinary products and refrigerated products, as well as corresponding transportation vehicles. We consider the constraints associated with self-pickup points and lockers and then address the location-routing problem with self-pickup facilities and heterogeneous demands (LRP-PFHD). To solve this challenging problem, we propose a mixed integer linear programming (MILP) model that aims to minimize the total cost, which includes the facility opening cost, the variable transport cost, and the fixed transport cost. Due to the NP-hardness of the problem, we propose a hybrid adaptive large-neighbourhood search algorithm to solve LRP-PFHD. We evaluate the effectiveness and efficiency of the proposed algorithm by using instances generated based on benchmark instances. The results demonstrate that the hybrid adaptive large neighbourhood search algorithm is more efficient than MILP solvers such as Gurobi for LRP-PFHD, especially for large-scale instances. In addition, we made a comprehensive analysis of some important parameters (e.g., facility opening cost and transportation cost) to explore their impacts on the results and suggested helpful managerial insights for courier companies.

Keywords: city logistics, last-mile delivery, location-routing, adaptive large neighborhood search

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Authors: A. M. Ferrari, L. Volpi, M. Pini, C. Siligardi, F. E. Garcia Muina, D. Settembre Blundo

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A long tradition in the ceramic manufacturing since the 18th century, primarily due to the availability of raw materials and an efficient transport system, let to the birth and development of the Italian ceramic tiles district that nowadays represents a reference point for this sector even at global level. This economic growth has been coupled to attention towards environmental sustainability issues throughout various initiatives undertaken over the years at the level of the production sector, such as certification activities and sustainability policies. In this way, starting from an evaluation of the sustainability in all its aspects, the present work aims to develop a benchmarking helping both producers and consumers. In the present study, throughout the Life Cycle Sustainability Assessment (LCSA) framework, the sustainability has been assessed in all its dimensions: environmental with the Life Cycle Assessment (LCA), economic with the Life Cycle Costing (LCC) and social with the Social Life Cycle Assessment (S-LCA). The annual district production of stoneware tiles during the 2016 reference year has been taken as reference flow for all the three assessments, and the system boundaries cover the entire life cycle of the tiles, except for the LCC for which only the production costs have been considered at the moment. In addition, a preliminary method for the evaluation of local and indoor emissions has been introduced in order to assess the impact due to atmospheric emissions on both people living in the area surrounding the factories and workers. The Life Cycle Assessment results, obtained from IMPACT 2002+ modified assessment method, highlight that the manufacturing process is responsible for the main impact, especially because of atmospheric emissions at a local scale, followed by the distribution to end users, the installation and the ordinary maintenance of the tiles. With regard to the economic evaluation, both the internal and external costs have been considered. For the LCC, primary data from the analysis of the financial statements of Italian ceramic companies show that the higher cost items refer to expenses for goods and services and costs of human resources. The analysis of externalities with the EPS 2015dx method attributes the main damages to the distribution and installation of the tiles. The social dimension has been investigated with a preliminary approach by using the Social Hotspots Database, and the results indicate that the most affected damage categories are health and safety and labor rights and decent work. This study shows the potential of the LCSA framework applied to an industrial sector; in particular, it can be a useful tool for building a comprehensive benchmark for the sustainability of the ceramic industry, and it can help companies to actively integrate sustainability principles into their business models.

Keywords: benchmarking, Italian ceramic industry, life cycle sustainability assessment, porcelain stoneware tiles

Procedia PDF Downloads 95

Authors: Samuele Ghignoli, Valentina de Lorenzi, Gianmarco Ferri, Stefano Luin, Francesco Cardarelli

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Insulin and glucagon are the two essential hormones for maintaining proper blood glucose homeostasis, which is disrupted in Diabetes. A constantly growing research interest has been focused on the study of the subcellular structures involved in hormone secretion, namely insulin- and glucagon-containing granules, and on the mechanisms regulating their behaviour. Yet, while several successful attempts were reported describing the dynamic properties of insulin granules, little is known about their counterparts in α cells, the glucagon-containing granules. To fill this gap, we used αTC1 clone 9 cells as a model of α cells and ZIGIR as a fluorescent Zinc chelator for granule labelling. We started by using spatiotemporal fluorescence correlation spectroscopy in the form of imaging-derived mean square displacement (iMSD) analysis. This afforded quantitative information on the average dynamical and structural properties of glucagon granules having insulin granules as a benchmark. Interestingly, the iMSD sensitivity to average granule size allowed us to confirm that glucagon granules are smaller than insulin ones (~1.4 folds, further validated by STORM imaging). To investigate possible heterogeneities in granule dynamic properties, we moved from correlation spectroscopy to single particle tracking (SPT). We developed a MATLAB script to localize and track single granules with high spatial resolution. This enabled us to classify the glucagon granules, based on their dynamic properties, as ‘blocked’ (i.e., trajectories corresponding to immobile granules), ‘confined/diffusive’ (i.e., trajectories corresponding to slowly moving granules in a defined region of the cell), or ‘drifted’ (i.e., trajectories corresponding to fast-moving granules). In cell-culturing control conditions, results show this average distribution: 32.9 ± 9.3% blocked, 59.6 ± 9.3% conf/diff, and 7.4 ± 3.2% drifted. This benchmarking provided us with a foundation for investigating selected experimental conditions of interest, such as the glucagon-granule relationship with the cytoskeleton. For instance, if Nocodazole (10 μM) is used for microtubule depolymerization, the percentage of drifted motion collapses to 3.5 ± 1.7% while immobile granules increase to 56.0 ± 10.7% (remaining 40.4 ± 10.2% of conf/diff). This result confirms the clear link between glucagon-granule motion and cytoskeleton structures, a first step towards understanding the intracellular behaviour of this subcellular compartment. The information collected might now serve to support future investigations on glucagon granules in physiology and disease. Acknowledgment: This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 866127, project CAPTUR3D).

Keywords: glucagon granules, single particle tracking, correlation spectroscopy, ZIGIR

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Authors: Ch. Sridevi, A. Chalapathi Rao, P. Srinivasulu

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The location accuracy of data products is a critical parameter in assessing the geometric performance of satellite sensors. This study focuses on reliability analysis of onboard sensors to evaluate their performance in terms of location accuracy performance over time. The analysis utilizes field failure data and employs the weibull distribution to determine the reliability and in turn to understand the improvements or degradations over a period of time. The analysis begins by scrutinizing the location accuracy error which is the root mean square (RMS) error of differences between ground control point coordinates observed on the product and the map and identifying the failure data with reference to time. A significant challenge in this study is to thoroughly analyze the possibility of an infant mortality phase in the data. To address this, the Weibull distribution is utilized to determine if the data exhibits an infant stage or if it has transitioned into the operational phase. The shape parameter beta plays a crucial role in identifying this stage. Additionally, determining the exact start of the operational phase and the end of the infant stage poses another challenge as it is crucial to eliminate residual infant mortality or wear-out from the model, as it can significantly increase the total failure rate. To address this, an approach utilizing the well-established statistical Laplace test is applied to infer the behavior of sensors and to accurately ascertain the duration of different phases in the lifetime and the time required for stabilization. This approach also helps in understanding if the bathtub curve model, which accounts for the different phases in the lifetime of a product, is appropriate for the data and whether the thresholds for the infant period and wear-out phase are accurately estimated by validating the data in individual phases with Weibull distribution curve fitting analysis. Once the operational phase is determined, reliability is assessed using Weibull analysis. This analysis not only provides insights into the reliability of individual sensors with regards to location accuracy over the required period of time, but also establishes a model that can be applied to automate similar analyses for various sensors and parameters using field failure data. Furthermore, the identification of the best-performing sensor through this analysis serves as a benchmark for future missions and designs, ensuring continuous improvement in sensor performance and reliability. Overall, this study provides a methodology to accurately determine the duration of different phases in the life data of individual sensors. It enables an assessment of the time required for stabilization and provides insights into the reliability during the operational phase and the commencement of the wear-out phase. By employing this methodology, designers can make informed decisions regarding sensor performance with regards to location accuracy, contributing to enhanced accuracy in satellite-based applications.

Keywords: bathtub curve, geometric performance, Laplace test, location accuracy, reliability analysis, Weibull analysis

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Authors: Alba Barbara-i-Molinero, Rosalia Cascon-Pereira, Ana Beatriz Hernandez

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Students’ transitions from high school to the university have been challenged by the lack of continuity between both contexts. This mismatch directly affects students by generating feelings of anxiety and uncertainty, which increases the dropout rates and reduces students’ academic success. This discontinuity emanates because ‘transitions concern a restructuring of what the person does and who the person perceives him or herself to be’. Hence, identity becomes essential in these transitions. Generally, identity is the answer to questions such as who am I? or who are we? This is integrated by personal identity, and as many social identities as groups, the individual feels he/she is a part. A case in point to construct a social identity is the identification with a profession. For this reason, a way to lighten the generated tension during transitions is applying strategies orientated to enhance students’ professional identity in their point of entry to the higher education institution. That would create a sense of continuity between high school and higher education contexts, increasing their Professional Identity Strength. To develop the strategies oriented to enhance students Professional Identity, it is important to analyze what influences it. There exist several influencing factors that influence Professional Identity (e.g., professional status, the recommendation of family and peers, the academic environment, or the chosen bachelor degree). There is a gap in the literature analyzing the impact of these factors on more than one bachelor degree. In this regards, our study takes an additional step with the aim of evaluating the influence of several factors on Professional Identity using a cohort of university students from multiple degrees between the ages of 17-19 years. To do so, we used hierarchical regression analyses to assess the impact of the following factors: External Motivation Conditionals (EMC), Educational Experience Conditionals (EEC) and Personal Motivational Conditional (PMP). After conducting the analyses, we found that the assessed factors influenced students’ professional identity differently according to their bachelor degree and discipline. For example, PMC and EMC positively affected science students, while architecture, law and economics and engineering students were just influenced by PMC. Basing on that influences, we proposed three different strategies aimed to enhance students’ professional identity, in the short and long term. These strategies are: to enhance students’ professional identity before the incorporation to university through campuses and icebreaker activities; to apply recruitment strategies aimed to provide realistic information of the bachelor degree; and to incorporate different activities, such as in-vitro, in situ and self-directed activities aimed to enhance longitudinally students’ professional identity from the university. From these results, theoretical contributions and practical implications arise. First, we contribute to the literature by identifying which factors influence students from different bachelor degrees since there is still no evidence. And, second, using as a benchmark the obtained results, we contribute from a practical perspective, by proposing several alternative strategies to increase students’ professional identity strength aiming to lighten their transition from high school to higher education.

Keywords: professional identity, higher education, educational strategies , students

Procedia PDF Downloads 114

Authors: Daniel Martin Fellows, Sean P. Walton, Jennifer Thompson, Oubay Hassan, Ella Quigley, Kevin Tinkham

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Fire performance is a crucial aspect to consider when designing cladding products, and testing this performance is extremely expensive. Appropriate use of numerical simulation of fire performance has the potential to reduce the total number of fire tests required when designing a product by eliminating poor-performing design ideas early in the design phase. Due to the complexity of fire and the large spectrum of failures it can cause, multi-disciplinary models are needed to capture the complex fire behavior and its structural effects on its surroundings. Working alongside Tata Steel U.K., the authors have focused on completing a coupled CFD-FEA simulation model suited to test Polyisocyanurate (PIR) based sandwich panel products to gain confidence before costly experimental standards testing. The sandwich panels are part of a thermally insulating façade system primarily for large non-domestic buildings. The work presented in this paper compares two coupling methodologies of a replicated physical experimental standards test LPS 1181-1, carried out by Tata Steel U.K. The two coupling methodologies that are considered within this research are; one-way and two-way. A one-way coupled analysis consists of importing thermal data from the CFD solver into the FEA solver. A two-way coupling analysis consists of continuously importing the updated changes in thermal data, due to the fire's behavior, to the FEA solver throughout the simulation. Likewise, the mechanical changes will also be updated back to the CFD solver to include geometric changes within the solution. For CFD calculations, a solver called Fire Dynamic Simulator (FDS) has been chosen due to its adapted numerical scheme to focus solely on fire problems. Validation of FDS applicability has been achieved in past benchmark cases. In addition, an FEA solver called ABAQUS has been chosen to model the structural response to the fire due to its crushable foam plasticity model, which can accurately model the compressibility of PIR foam. An open-source code called FDS-2-ABAQUS is used to couple the two solvers together, using several python modules to complete the process, including failure checks. The coupling methodologies and experimental data acquired from Tata Steel U.K are compared using several variables. The comparison data includes; gas temperatures, surface temperatures, and mechanical deformation of the panels. Conclusions are drawn, noting improvements to be made on the current coupling open-source code FDS-2-ABAQUS to make it more applicable to Tata Steel U.K sandwich panel products. Future directions for reducing the computational cost of the simulation are also considered.

Keywords: fire engineering, numerical coupling, sandwich panels, thermo fluids

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Authors: Biswaranjan D. Mohapatra, Ipsha Hota, Swarna P. Mantry, Nibedita Behera, Kumar S. K. Varadwaj

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Designing highly active and low-cost oxygen evolution (2H₂O → 4H⁺ + 4e⁻ + O₂) electrocatalyst is one of the most active areas of advanced energy research. Some precious metal-based electrocatalysts, such as IrO₂ and RuO₂, have shown excellent performance for oxygen evolution reaction (OER); however, they suffer from high-cost and low abundance which limits their applications. Recently, layered double hydroxides (LDHs), composed of layers of divalent and trivalent transition metal cations coordinated to hydroxide anions, have gathered attention as an alternative OER catalyst. However, LDHs are insulators and coupled with carbon materials for the electrocatalytic applications. Graphene covalently doped with nitrogen has been demonstrated to be an excellent electrocatalyst for energy conversion technologies such as; oxygen reduction reaction (ORR), oxygen evolution reaction (OER) & hydrogen evolution reaction (HER). However, they operate at high overpotentials, significantly above the thermodynamic standard potentials. Recently, we reported remarkably enhanced catalytic activity of benzoate or 1-pyrenebutyrate functionalized N-doped graphene towards the ORR in alkaline medium. The molecular and heteroatom co-doping on graphene is expected to tune the electronic structure of graphene. Therefore, an innovative catalyst architecture, in which LDHs are anchored on aromatic acid functionalized ‘N’ doped graphene may presumably boost the OER activity to a new benchmark. Herein, we report fabrication of Co₂Fe-LDH on aromatic acid (AA) functionalized ‘N’ doped reduced graphene oxide (NG) and studied their OER activities in alkaline medium. In the first step, a novel polyol method is applied for synthesis of AA functionalized NG, which is well dispersed in aqueous medium. In the second step, Co₂Fe LDH were grown on AA functionalized NG by co-precipitation method. The hybrid samples are abbreviated as Co₂Fe LDH/AA-NG, where AA is either Benzoic acid or 1, 3-Benzene dicarboxylic acid (BDA) or 1, 3, 5 Benzene tricarboxylic acid (BTA). The crystal structure and morphology of the samples were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM) and transmission electron microscope (TEM). These studies confirmed the growth of layered single phase LDH. The electrocatalytic OER activity of these hybrid materials was investigated by rotating disc electrode (RDE) technique on a glassy carbon electrode. The linear sweep voltammetry (LSV) on these catalyst samples were taken at 1600rpm. We observed significant OER performance enhancement in terms of onset potential and current density on Co₂Fe LDH/BTA-NG hybrid, indicating the synergic effect. This exploration of molecular functionalization effect in doped graphene and LDH system may provide an excellent platform for innovative design of OER catalysts.

Keywords: π-π functionalization, layered double hydroxide, oxygen evolution reaction, reduced graphene oxide

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Authors: Roberto Pili, Alessandro Romagnoli, Hartmut Spliethoff, Christoph Wieland

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Internal combustion engines (ICE) are today the most common energy system to drive vehicles and transportation systems. Numerous studies state that 50-60% of the fuel energy content is lost to the ambient as sensible heat. ORC offers a valuable alternative to recover such waste heat from ICE, leading to fuel energy savings and reduced emissions. In contrast, the additional weight of the ORC affects the net energy balance of the overall system and the ORC occupies additional volume that competes with vehicle transportation capacity. Consequently, a lower income from delivered freight or passenger tickets can be achieved. The economic feasibility of integrating an ORC into an ICE and the resulting economic impact of weight and volume have not been analyzed in open literature yet. This work intends to define such a benchmark for ORC applications in the transportation sector and investigates the current situation on the market. The applied methodology refers to the freight market, but it can be extended to passenger transportation as well. The economic parameter X is defined as the ratio between the variation of the freight revenues and the variation of fuel costs when an ORC is installed as a bottoming cycle for an ICE with respect to a reference case without ORC. A good economic situation is obtained when the reduction in fuel costs is higher than the reduction of revenues for the delivered freight, i.e. X<1. Through this constraint, a maximum allowable change of transport capacity for a given relative reduction in fuel consumption is determined. The specific fuel consumption is influenced by the ORC in two ways. Firstly because the transportable freight is reduced and secondly because the total weight of the vehicle is increased. Note, that the generated electricity of the ORC influences the size of the ICE and the fuel consumption as well. Taking the above dependencies into account, the limiting condition X = 1 results in a second order equation for the relative change in transported cargo. The described procedure is carried out for a typical city bus, a truck of 24-40 t of payload capacity, a middle-size freight train (1000 t), an inland water vessel (Va RoRo, 2500 t) and handysize-like vessel (25000 t). The maximum allowable mass and volume of the ORC are calculated in dependence of its efficiency in order to satisfy X < 1. Subsequently, these values are compared with weight and volume of commercial ORC products. For ships of any size, the situation appears already highly favorable. A different result is obtained for road and rail vehicles. For trains, the mass and the volume of common ORC products have to be reduced at least by 50%. For trucks and buses, the situation looks even worse. The findings of the present study show a theoretical and practical approach for the economic application of ORC in the transportation sector. In future works, the potential for volume and mass reduction of the ORC will be addressed, together with the integration of an economic assessment for the ORC.

Keywords: ORC, transportation, volume, weight

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Authors: Guo Bingkun

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With the rapid development of China's social economy and the continuous improvement of urbanization level, people's living standards have undergone tremendous changes, and more and more people are gathering in cities. The demand for urban residents' housing has been greatly released in the past decade. The demand for housing and related construction land required for urban development has brought huge pressure to urban operations, and land prices have also risen rapidly in the short term. On the other hand, from the comparison of the eastern and western regions of China, there are also great differences in urban socioeconomics and land prices in the eastern, central and western regions. Although judging from the current overall market development, after more than ten years of housing market reform and development, the quality of housing and land use efficiency in Chinese cities have been greatly improved. However, the current contradiction between land demand for urban socio-economic development and land supply, especially the contradiction between land supply and demand for urban residential land, has not been effectively alleviated. Since land is closely linked to all aspects of society, changes in land prices will be affected by many complex factors. Therefore, this paper studies the factors that may affect urban residential land prices and compares them among eastern, central and western cities, and finds the main factors that determine the level of urban residential land prices. This paper provides guidance for urban managers in formulating land policies and alleviating land supply and demand. It provides distinct ideas for improving urban planning and improving urban planning and promotes the improvement of urban management level. The research in this paper focuses on residential land prices. Generally, the indicators for measuring land prices mainly include benchmark land prices, land price level values, parcel land prices, etc. However, considering the requirements of research data continuity and representativeness, this paper chooses to use residential land price level values. Reflects the status of urban residential land prices. First of all, based on the existing research at home and abroad, the paper considers the two aspects of land supply and demand and, based on basic theoretical analysis, determines some factors that may affect urban housing, such as urban expansion, taxation, land reserves, population, and land benefits. Factors of land price and correspondingly selected certain representative indicators. Secondly, using conventional econometric analysis methods, we established a model of factors affecting urban residential land prices, quantitatively analyzed the relationship and intensity of influencing factors and residential land prices, and compared the differences in the impact of urban residential land prices between the eastern, central and western regions. Compare similarities. Research results show that the main factors affecting China's urban residential land prices are urban expansion, land use efficiency, taxation, population size, and residents' consumption. Then, the main reason for the difference in residential land prices between the eastern, central and western regions is the differences in urban expansion patterns, industrial structures, urban carrying capacity and real estate development investment.

Keywords: urban housing, urban planning, housing prices, comparative study

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Authors: Vikrant Gupta, Amrit Goswami

Abstract:

The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: Asegid Belay Kebede, Getachew Biru Worku

Abstract:

The Earth and its inhabitants have faced an existential threat as a result of severe manmade actions. Global warming and climate change have been the most apparent manifestations of this threat throughout the world, with increasingly intense heat waves, temperature rises, flooding, sea-level rise, ice sheet melting, and so on. One of the major contributors to this disaster is the ever-increasing production and consumption of energy, which is still primarily fossil-based and emits billions of tons of hazardous GHG. The transportation industry is recognized as the biggest actor in terms of emissions, accounting for 24% of direct CO2 emissions and being one of the few worldwide sectors where CO2 emissions are still growing. Rail transportation, which includes all from light rail transit to high-speed rail services, is regarded as one of the most efficient modes of transportation, accounting for 9% of total passenger travel and 7% of total freight transit. Nonetheless, there is still room for improvement in the transportation sector, which might be done by incorporating alternative and/or renewable energy sources. As a result of these rapidly changing global energy situations and rapidly dwindling fossil fuel supplies, we were driven to analyze the possibility of renewable energy sources for traction applications. Even a small achievement in energy conservation or harnessing might significantly influence the total railway system and have the potential to transform the railway sector like never before. As a result, the paper begins by assessing the potential for photovoltaic (PV) power generation on train rooftops and existing infrastructure such as railway depots, passenger stations, traction substation rooftops, and accessible land along rail lines. As a result, a method based on a Google Earth system (using Helioscopes software) is developed to assess the PV potential along rail lines and on train station roofs. As an example, the Addis Ababa light rail transit system (AA-LRTS) is utilized. The case study examines the electricity-generating potential and economic performance of photovoltaics installed on AALRTS. As a consequence, the overall capacity of solar systems on all stations, including train rooftops, reaches 72.6 MWh per day, with an annual power output of 10.6 GWh. Throughout a 25-year lifespan, the overall CO2 emission reduction and total profit from PV-AA-LRTS can reach 180,000 tons and 892 million Ethiopian birrs, respectively. The PV-AA-LRTS has a 200% return on investment. All PV stations have a payback time of less than 13 years, and the price of solar-generated power is less than $0.08/kWh, which can compete with the benchmark price of coal-fired electricity. Our findings indicate that PV-AA-LRTS has tremendous potential, with both energy and economic advantages.

Keywords: sustainable development, global warming, energy crisis, photovoltaic energy conversion, techno-economic analysis, transportation system, light rail transit

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Authors: Ferzat Anka

Abstract:

Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

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