Search results for: optimal capacitors placement

Authors: Cuong D. Dao, Rob J.I. Basten, Andreas Hartmann

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This paper studies the optimal maintenance planning of preventive maintenance and renewal activities for components in a single railway track when the available time for maintenance is limited. The rail-track system consists of several types of components, such as rail, ballast, and switches with different preventive maintenance and renewal intervals. To perform maintenance or renewal on the track, a train free period for maintenance, called a possession, is required. Since a major possession directly affects the regular train schedule, maintenance and renewal activities are clustered as much as possible. In a highly dense and utilized railway network, the possession time on the track is critical since the demand for train operations is very high and a long possession has a severe impact on the regular train schedule. We present an optimization model and investigate the maintenance schedules with and without the possession capacity constraint. In addition, we also integrate the social-economic cost related to the effects of the maintenance time to the variable possession cost into the optimization model. A numerical example is provided to illustrate the model.

Keywords: rail-track components, maintenance, optimal clustering, possession capacity

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Authors: R. B. Mishra

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Hidden Markov Model (HMM) has been used in prediction and determination of states that generate different neural activations as well as mental working conditions. This paper addresses two applications of HMM; one to determine the optimal sequence of states for two neural states: Active (AC) and Inactive (IA) for the three emission (observations) which are for No Working (NW), Waiting (WT) and Working (W) conditions of human beings. Another is for the determination of optimal sequence of intentionality i.e. Believe (B), Desire (D), and Intention (I) as the states and three observational sequences: NW, WT and W. The computational results are encouraging and useful.

Keywords: hiden markov model, believe desire intention, neural activation, simulation

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Authors: Igor Kuzminov

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Till now, the nature of lightning is not established. A hypothesis of the origin of lightning is proposed. The lightning charge is formed by electromagnetic induction. The role of the conductor is performed by the air mass of the cloud. This conductor moves in the Earth's magnetic field. The upper and lower edges of the cloud are the plates of the capacitor. Lightning is a special case of electromagnetic processes in an atmosphere. The category of lightning occurs in the process of accumulation of a charge. The process of accumulation goes constantly, but the charge is not fixed. Naturally, the hypothesis demands the carrying out of additional experiments and official acknowledgement. As the proof of a hypothesis can serve that the maximal lighting activity in an equatorial zone where cosφ it is close to 1. An experiment conducted privately showed that there is a potential difference in the atmosphere at different levels. The probability of applied value development of power installation is great.

Keywords: electromagnetic induction, Earth's magnetic field, plates of the capacitors, charge accumulation

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Authors: Alexander Vaninsky

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The objective of this paper is finding the way of economic restructuring - that is, change in the shares of sectoral gross outputs - resulting in the maximum possible increase in the gross domestic product (GDP) combined with decreases in energy consumption and CO2 emissions. It uses an input-output model for the GDP and factorial models for the energy consumption and CO2 emissions to determine the projection of the gradient of GDP, and the antigradients of the energy consumption and CO2 emissions, respectively, on a subspace formed by the structure-related variables. Since the gradient (antigradient) provides a direction of the steepest increase (decrease) of the objective function, and their projections retain this property for the functions' limitation to the subspace, each of the three directional vectors solves a particular problem of optimal structural change. In the next step, a type of factor analysis is applied to find a convex combination of the projected gradient and antigradients having maximal possible positive correlation with each of the three. This convex combination provides the desired direction of the structural change. The national economy of the United States is used as an example of applications.

Keywords: economic restructuring, input-output analysis, divisia index, factorial decomposition, E3 models

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Authors: Nishant Shrivastava, D. K. Sehgal

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In Finite Element Technique nodal stresses are calculated through displacement as nodes. In this process, the displacement calculated at nodes is sufficiently good enough but stresses calculated at nodes are not sufficiently accurate. Therefore, the accuracy in the stress computation in FEM models based on the displacement technique is obviously matter of concern for computational time in shape optimization of engineering problems. In the present work same is focused to find out unique points within the element as well as the boundary of the element so, that good accuracy in stress computation can be achieved. Generally, major optimal stress points are located in domain of the element some points have been also located at boundary of the element where stresses are fairly accurate as compared to nodal values. Then, it is subsequently concluded that there is an existence of unique points within the element, where stresses have higher accuracy than other points in the elements. Therefore, it is main aim is to evolve a generalized procedure for the determination of the optimal stress location inside the element as well as at the boundaries of the element and verify the same with results from numerical experimentation. The results of quadratic 9 noded serendipity elements are presented and the location of distinct optimal stress points is determined inside the element, as well as at the boundaries. The theoretical results indicate various optimal stress locations are in local coordinates at origin and at a distance of 0.577 in both directions from origin. Also, at the boundaries optimal stress locations are at the midpoints of the element boundary and the locations are at a distance of 0.577 from the origin in both directions. The above findings were verified through experimentation and findings were authenticated. For numerical experimentation five engineering problems were identified and the numerical results of 9-noded element were compared to those obtained by using the same order of 25-noded quadratic Lagrangian elements, which are considered as standard. Then root mean square errors are plotted with respect to various locations within the elements as well as the boundaries and conclusions were drawn. After numerical verification it is noted that in a 9-noded element, origin and locations at a distance of 0.577 from origin in both directions are the best sampling points for the stresses. It was also noted that stresses calculated within line at boundary enclosed by 0.577 midpoints are also very good and the error found is very less. When sampling points move away from these points, then it causes line zone error to increase rapidly. Thus, it is established that there are unique points at boundary of element where stresses are accurate, which can be utilized in solving various engineering problems and are also useful in shape optimizations.

Keywords: finite elements, Lagrangian, optimal stress location, serendipity

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Authors: Imèn Khanchouch, Malika Charrad, Mohamed Limam

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The interpretation of the quality of clusters and the determination of the optimal number of clusters is still a crucial problem in clustering. We focus in this paper on multi-SOM clustering method which overcomes the problem of extracting the number of clusters from the SOM map through the use of a clustering validity index. We then tested multi-SOM using real and artificial data sets with different evaluation criteria not used previously such as Davies Bouldin index, Dunn index and silhouette index. The developed multi-SOM algorithm is compared to k-means and Birch methods. Results show that it is more efficient than classical clustering methods.

Keywords: clustering, SOM, multi-SOM, DB index, Dunn index, silhouette index

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Authors: Andrey V. Timofeev

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The paper presents new results concerning selection of optimal information fusion formula for ensembles of C-OTDR channels. The goal of information fusion is to create an integral classificator designed for effective classification of seismoacoustic target events. The LPBoost (LP-β and LP-B variants), the Multiple Kernel Learning, and Weighing of Inversely as Lipschitz Constants (WILC) approaches were compared. The WILC is a brand new approach to optimal fusion of Lipschitz Classifiers Ensembles. Results of practical usage are presented.

Keywords: Lipschitz Classifier, classifiers ensembles, LPBoost, C-OTDR systems

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Authors: Mohammed Darwish

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Workplace injuries cost organizations significant amount of money. Causes of injuries at workplace are very well documented in the literature and attributed to variety of reasons. One important reason is the long working-hours. The purpose of this paper is to develop a mathematical model that finds the optimal working-hours at workplace. The developed model minimizes the expected total cost which consists of the expected cost incurred due to unsafe conditions of workplace, the other cost is related to the lost production due to work incidents, and the production cost.

Keywords: 8-hour workday, mathematical model, optimal working hours, workplace injuries

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Authors: Ruchika Goyal, Ashwani Kumar, Sandeep Jain

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The experimental data for anticancer potential of curcumin nanoparticles was calculated by means of eclectic data. The optimal descriptors were examined using Monte Carlo method based CORAL SEA software. The statistical quality of the model is following: n = 14, R² = 0.6809, Q² = 0.5943, s = 0.175, MAE = 0.114, F = 26 (sub-training set), n =5, R²= 0.9529, Q² = 0.7982, s = 0.086, MAE = 0.068, F = 61, Av Rm² = 0.7601, ∆R²m = 0.0840, k = 0.9856 and kk = 1.0146 (test set) and n = 5, R² = 0.6075 (validation set). This data can be used to build predictive QSAR models for anticancer activity.

Keywords: anticancer potential, curcumin, model, nanoparticles, optimal descriptors, QSAR

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Authors: Silas A. Ihedioha

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In this work; it is considered that an investor’s portfolio is comprised of two assets; a risky stock which price process is driven by the geometric Brownian motion and a risk-free asset with Ornstein-Uhlenbeck Stochastic interest rate of return, where consumption, taxes, transaction costs and dividends are involved. This paper aimed at the optimization of the investor’s expected utility of consumption and terminal return on his investment at the terminal time having power utility preference. Using dynamic optimization procedure of maximum principle, a second order nonlinear partial differential equation (PDE) (the Hamilton-Jacobi-Bellman equation HJB) was obtained from which an ordinary differential equation (ODE) obtained via elimination of variables. The solution to the ODE gave the closed form solution of the investor’s problem. It was found the optimal investment in the risky asset is horizon dependent and a ratio of the total amount available for investment and the relative risk aversion coefficient.

Keywords: optimal, investment, Ornstein-Uhlenbeck, utility maximization, stochastic interest rate, maximum principle

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Authors: Anil Kumar Pandey

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Power plane noise is the most significant source of signal integrity (SI) issues in a high-speed digital design. In this paper, power integrity (PI) analysis of multiple power planes in a power delivery system of a 12-layer high-speed FPGA board is presented. All 10 power planes of HSD board are analyzed separately by using 3D Electromagnetic based PI solver, then the transient simulation is performed on combined PI data of all planes along with voltage regulator modules (VRMs) and 70 current drawing chips to get the board level power noise coupling on different high-speed signals. De-coupling capacitors are placed between power planes and ground to reduce power noise coupling with signals.

Keywords: power integrity, power-aware signal integrity analysis, electromagnetic simulation, channel simulation

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Authors: Parshanth Maroju, Ramandeep Behl, Sandile S. Motsa

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In this study, we proposed a simple and interesting family of fourth-order multi-point methods without memory for obtaining simple roots. This family requires only three functional evaluations (viz. two of functions f(xn), f(yn) and third one of its first-order derivative f'(xn)) per iteration. Moreover, the accuracy and validity of new schemes is tested by a number of numerical examples are also proposed to illustrate their accuracy by comparing them with the new existing optimal fourth-order methods available in the literature. It is found that they are very useful in high precision computations. Further, the dynamic study of these methods also supports the theoretical aspect.

Keywords: basins of attraction, nonlinear equations, simple roots, Newton's method

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Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

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With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

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Authors: Zohreh Mohammadi, Jan Kaspar, Peter Lohmander, Robert Marusak, Harald Vacik, Ljusk Ola Eriksson

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Storms are important damaging agents in European forest ecosystems. In the latest decades, significant economic losses in European forestry occurred due to storms. This study investigates the problem of optimal harvest planning when forest stands risk to be felled by storms. One of the most applicable mathematical methods which are being used to optimize forest management is stochastic dynamic programming (SDP). This method belongs to the adaptive optimization class. Sequential decisions, such as harvest decisions, can be optimized based on sequential information about events that cannot be perfectly predicted, such as the future storms and the future states of wind protection from other forest stands. In this paper, stochastic dynamic programming is used to maximize the expected present value of the profits from an area consisting of several forest stands. The region of analysis is the Czech Republic. The harvest decisions, in a particular time period, should be simultaneously taken in all neighbor stands. The reason is that different stands protect each other from possible winds. The optimal harvest age of a particular stand is a function of wind speed and different wind protection effects. The optimal harvest age often decreases with wind speed, but it cannot be determined for one stand at a time. When we consider a particular stand, this stand also protects other stands. Furthermore, the particular stand is protected by neighbor stands. In some forest stands, it may even be rational to increase the harvest age under the influence of stronger winds, in order to protect more valuable stands in the neighborhood. It is important to integrate wind risk in forestry decision-making.

Keywords: Czech republic, forest stands, stochastic dynamic programming, wind risk

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Authors: Peter Egri, Tamas Kis

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Scheduling problems have been studied by the algorithmic mechanism design research from the beginning. This paper is focusing on a practically important, but theoretically rather neglected field: the project scheduling problem where the jobs connected by precedence constraints compete for various nonrenewable resources, such as materials. Although the centralized problem can be solved in polynomial-time by applying the algorithm of Carlier and Rinnooy Kan from the Eighties, obtaining materials in a decentralized environment is usually far from optimal. It can be observed in practical production scheduling situations that project managers tend to cache the required materials as soon as possible in order to avoid later delays due to material shortages. This greedy practice usually leads both to excess stocks for some projects and materials, and simultaneously, to shortages for others. The aim of this study is to develop a model for the material allocation problem of a production plant, where a central decision maker—the inventory—should assign the resources arriving at different points in time to the jobs. Since the actual due dates are not known by the inventory, the mechanism design approach is applied with the projects as the self-interested agents. The goal of the mechanism is to elicit the required information and allocate the available materials such that it minimizes the maximal tardiness among the projects. It is assumed that except the due dates, the inventory is familiar with every other parameters of the problem. A further requirement is that due to practical considerations monetary transfer is not allowed. Therefore a mechanism without money is sought which excludes some widely applied solutions such as the Vickrey–Clarke–Groves scheme. In this work, a type of Serial Dictatorship Mechanism (SDM) is presented for the studied problem, including a polynomial-time algorithm for computing the material allocation. The resulted mechanism is both truthful and Pareto optimal. Thus the randomization over the possible priority orderings of the projects results in a universally truthful and Pareto optimal randomized mechanism. However, it is shown that in contrast to problems like the many-to-many matching market, not every Pareto optimal solution can be generated with an SDM. In addition, no performance guarantee can be given compared to the optimal solution, therefore this approximation characteristic is investigated with experimental study. All in all, the current work studies a practically relevant scheduling problem and presents a novel truthful material allocation mechanism which eliminates the potential benefit of the greedy behavior that negatively influences the outcome. The resulted allocation is also shown to be Pareto optimal, which is the most widely used criteria describing a necessary condition for a reasonable solution.

Keywords: material allocation, mechanism without money, polynomial-time mechanism, project scheduling

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Authors: Marta Kozuń, Krystian Toczewski, Sylwester Gerus, Justyna Wolicka, Kamila Boberek, Jarosław Filipiak, Dariusz Patkowski

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Long gap esophageal atresia is a congenital defect and is a challenge for pediatric surgeons all over the world. There are different surgical techniques in use to treat atresia. One of them is esophageal elongation but the optimal suture placement technique to achieve maximum elongation with low-risk complications is still unknown. The aim of the study was to characterize the process of esophageal elongation from the biomechanical point of view. Esophagi of white Pekin Duck was used as a model based on the size of this animal which is similar to a newborn (2.5-4kg). The specimens were divided into two groups: the control group (CG) and the group with sutures (SG). The esophagi of the control group were mounted in the grips of the MTS Tytron 250 testing machine and tensile test until rupture was performed. The loading speed during the test was 10mm/min. Then the SG group was tested. Each esophagus was cut into two equal parts and that were fused together using surgical sutures. The distance between both esophagus parts was 20mm. Ten both ends were mounted on the same testing machine and the tensile test with the same parameters was conducted. For all specimens, force and elongation were recorded. The biomechanical properties, i.e., the maximal force and maximal elongation, were determined on the basis of force-elongation curves. The maximal elongation was determined at the point of maximal force. The force achieved with the suture group was 10.1N±1.9N and 50.3N±11.6N for the control group. The highest elongation was also obtained for the control group: 18mm±3mm vs. 13.5mm ±2.4mm for the suture group. The presented study expands the knowledge of elongation of esophagi. It is worth emphasizing that the duck esophagus differs from the esophagus of a newborn, i.e., its wall lacks striated muscle cells. This is why the parts of animal esophagi used in the research are may characterized by different biomechanical properties in comparison with newborn tissue.

Keywords: long gap atresia treatment, esophageal elongation, biomechanical properties, soft tissue

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Authors: Pawel Martynowicz

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Vibrations are a crucial problem for slender structures such as towers, masts, chimneys, wind turbines, bridges, high buildings, etc., that is why most of them are equipped with vibration attenuation or fatigue reduction solutions. In this work, a slender structure (i.e., wind turbine tower-nacelle model) equipped with nonlinear, semiactive tuned vibration absorber(s) is analyzed. For this study purposes, magnetorheological (MR) dampers are used as semiactive actuators. Several optimal-based approaches to structural vibration attenuation are investigated against the standard ‘ground-hook’ law and passive tuned vibration absorber(s) implementations. The common approach to optimal control of nonlinear systems is offline computation of the optimal solution, however, so determined open loop control suffers from lack of robustness to uncertainties (e.g., unmodelled dynamics, perturbations of external forces or initial conditions), and thus perturbation control techniques are often used. However, proper linearization may be an issue for highly nonlinear systems with implicit relations between state, co-state, and control. The main contribution of the author is the development as well as numerical and experimental verification of the Pontriagin maximum-principle-based vibration control concepts that produce directly actuator control input (not the demanded force), thus force tracking algorithm that results in control inaccuracy is entirely omitted. These concepts, including one-step optimal control, quasi-optimal control, and optimal-based modified ‘ground-hook’ law, can be directly implemented in online and real-time feedback control for periodic (or semi-periodic) disturbances with invariant or time-varying parameters, as well as for non-periodic, transient or random disturbances, what is a limitation for some other known solutions. No offline calculation, excitations/disturbances assumption or vibration frequency determination is necessary, moreover, all of the nonlinear actuator (MR damper) force constraints, i.e., no active forces, lower and upper saturation limits, hysteresis-type dynamics, etc., are embedded in the control technique, thus the solution is optimal or suboptimal for the assumed actuator, respecting its limitations. Depending on the selected method variant, a moderate or decisive reduction in the computational load is possible compared to other methods of nonlinear optimal control, while assuring the quality and robustness of the vibration reduction system, as well as considering multi-pronged operational aspects, such as possible minimization of the amplitude of the deflection and acceleration of the vibrating structure, its potential and/or kinetic energy, required actuator force, control input (e.g. electric current in the MR damper coil) and/or stroke amplitude. The developed solutions are characterized by high vibration reduction efficiency – the obtained maximum values of the dynamic amplification factor are close to 2.0, while for the best of the passive systems, these values exceed 3.5.

Keywords: magnetorheological damper, nonlinear tuned vibration absorber, optimal control, real-time structural vibration attenuation, wind turbines

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Authors: Eunice Christabel Chukwu

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Introduction: Diabetes is a chronic medical condition which is characterized by high levels of glucose in the blood and urine; it is usually diagnosed by means of a glucose tolerance test (GTT). Diabetes can cause a range of health problems if left unmanaged, as it can lead to serious complications. It is essential to manage the condition effectively, particularly in the workplace where the impact on work productivity can be significant. This paper discusses the modelling of optimal control of diabetes in the workplace using a control theory approach. Background: Diabetes mellitus is a condition caused by too much glucose in the blood. Insulin, a hormone produced by the pancreas, controls the blood sugar level by regulating the production and storage of glucose. In diabetes, there may be a decrease in the body’s ability to respond to insulin or a decrease in insulin produced by the pancreas which will lead to abnormalities in the metabolism of carbohydrates, proteins, and fats. In addition to the health implications, the condition can also have a significant impact on work productivity, as employees with uncontrolled diabetes are at risk of absenteeism, reduced performance, and increased healthcare costs. While several interventions are available to manage diabetes, the most effective approach is to control blood glucose levels through a combination of lifestyle modifications and medication. Methodology: The control theory approach involves modelling the dynamics of the system and designing a controller that can regulate the system to achieve optimal performance. In the case of diabetes, the system dynamics can be modelled using a mathematical model that describes the relationship between insulin, glucose, and other variables. The controller can then be designed to regulate the glucose levels to maintain them within a healthy range. Results: The modelling of optimal control of diabetes in the workplace using a control theory approach has shown promising results. The model has been able to predict the optimal dose of insulin required to maintain glucose levels within a healthy range, taking into account the individual’s lifestyle, medication regimen, and other relevant factors. The approach has also been used to design interventions that can improve diabetes management in the workplace, such as regular glucose monitoring and education programs. Conclusion: The modelling of optimal control of diabetes in the workplace using a control theory approach has significant potential to improve diabetes management and work productivity. By using a mathematical model and a controller to regulate glucose levels, the approach can help individuals with diabetes to achieve optimal health outcomes while minimizing the impact of the condition on their work performance. Further research is needed to validate the model and develop interventions that can be implemented in the workplace.

Keywords: mathematical model, blood, insulin, pancreas, model, glucose

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Authors: Amina Umulisa

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Background: Despite efforts to enhance profitability and project planning, Rwanda has experienced a decline in project success rates, notably in housing projects managed by the Rwanda Social Security Board (RSSB). This study aims to assess the impact of investment strategies and project planning practices on the performance of pension funds projects in Rwanda, focusing on housing projects by RSSB. Methods: Using descriptive and correlational research designs, this study surveyed 109 randomly selected respondents from a pool of 148 workers. Data analysis was conducted using descriptive and inferential statistics in STATA version 18. Results: Findings revealed that 54% of respondents acknowledged the importance of personnel generation. Additionally, 61% agreed with the effectiveness of training programs, and 79% supported the cost of human resource utilization. In terms of project management practices, 65.7% could determine when a project needed adjustments, 65.7% agreed with the approved budget, and 73% supported forecasted expenses. Furthermore, 68% agreed with order placement, 76.0% with using the right materials, and 64.4% with defining project scope. The study found significant associations between order placement and project quality outcomes (r=0.711, P-value <0.001), as well as with time management (Pearson was 0.701 and sing was 0.00) and cost management (r=0.885, P-value <0.001). Moreover, project time targets were found to significantly affect quality management (Pearson was 0.798, sing was 0.000), time management, and cost management (r=0.740, P-value <0.001). Conclusion: The findings highlight the positive association between the project implementation stage and quality management, indicating effective project planning practices among senior staff. However, there is a need to enhance project team collaboration and coordination to improve the performance of constructed houses.

Keywords: project success rates, investment strategies, training programs, cost management

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Authors: Siti Indati Mustapa, Hussain Ali Bekhet

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Transportation sector represents more than 40% of total energy consumption in Malaysia. This sector is a major user of fossils based fuels, and it is increasingly being highlighted as the sector which contributes least to CO2 emission reduction targets. Considering this fact, this paper attempts to investigate the problem of reducing CO2 emission using linear programming approach. An optimization model which is used to investigate the optimal level of CO2 emission reduction in the road transport sector is presented. In this paper, scenarios have been used to demonstrate the emission reduction model: (1) utilising alternative fuel scenario, (2) improving fuel efficiency scenario, (3) removing fuel subsidy scenario, (4) reducing demand travel, (5) optimal scenario. This study finds that fuel balancing can contribute to the reduction of the amount of CO2 emission by up to 3%. Beyond 3% emission reductions, more stringent measures that include fuel switching, fuel efficiency improvement, demand travel reduction and combination of mitigation measures have to be employed. The model revealed that the CO2 emission reduction in the road transportation can be reduced by 38.3% in the optimal scenario.

Keywords: CO2 emission, fuel consumption, optimization, linear programming, transportation sector, Malaysia

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Authors: Bongsik Park, Jae Hyun Park, Jae-Yeol Cho

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Mixed structure, which is a kind of hybrid system, is incorporating steel beam and prestressed concrete beam. Hybrid bridge adopting mixed structure have some merits. Main span length can be made longer by using steel as main span material. In case of cable-stayed bridge having asymmetric span length, negative reaction at side span can be restrained without extra restraining devices by using weight difference between main span material and side span material. However angle of refraction might happen because of rigidity difference between materials and stress concentration also might happen because of abnormal loading transmission at joint in the hybrid bridge. Therefore the joint might be a weak point of the structural system and it needs to pay attention to design of the joint. However, design codes and standards about the joint in the hybrid-bridge have not been established so the joint designs in most of construction cases have been very conservative or followed previous design without extra verification. In this study parametric study using finite element analysis for optimal design of hybrid bridge joint is conducted. Before parametric study, finite element analysis was conducted based on previous experimental data and it is verified that analysis result approximated experimental data. Based on the finite element analysis results, parametric study was conducted. The parameters were selected as those have influences on joint behavior. Based on the parametric study results, optimal design of hybrid bridge joint has been determined.

Keywords: parametric study, optimal design, hybrid bridge, finite element analysis

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Authors: J. Jayasuriya

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In this research paper, a procedure for installing and assessment of a solar PV plant to generate optimal solar energy SPAV hostel at Vijayawada city was analyzed. The hostel was experiencing power disruption and had a need for an unceasing energy source. The solar panel is one of the best solutions to obtain uninterrupted clean renewable energy for an institutional building as it neither makes din nor pollutes the atmosphere. The electricity usage per month was initially measured to discriminate the energy change. The solar array was installed with its financial and environmental assessment considering recent market prices. All the aspects related to a solar PV plant were considered for the feasibility and efficiency of PV plant near this site i.e., the orientation of the site, the size and shape of the terrace, the sun path were considered while installing panels. Various precautions were taken to intercept the factors which cause interference in energy generation, with respect to temperature, overshadowing, the wiring of panels, pollution etc. The solar panels were frequently installed, monitored and maintained properly to procure optimal energy output. Result obtained with the assessment of the proposed plant and deflation in the electric bill will show the maximal energy that can be generated in a month on that particular site.

Keywords: solar efficiency, building sustainability, PV panel, solar energy

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Authors: Ahmed Altalb

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Fertilizers are natural materials, or industrial contain nutrients, which help to improve soil fertility and is considered (nitrogen, phosphorus, and potassium) is important elements for the growth of crops properly. Fertilization is necessary in order to improve the quality of agricultural products and the recovery in agricultural activities. The use of organic fertilizers and chemical lead to reduce the loss of nutrients in agricultural soils, and this leads to an increase in the production of agricultural crops. Fertilizers are one of the key factors in the increase of agricultural production as well as other factors such as irrigation and improved seeds and Prevention and others; the fertilizers will continue to be a cornerstone of the agriculture in order to produce the food to feed of world population. The use of fertilizers has become commonplace today, especially the chemical fertilizers for the development of agricultural production, due to the provision of nutrients for plants and in high concentrations and easily dissolves in water and ease of use. The choose the right type of fertilizer depends on the soil type and the type of crop. In this subject, find the relationship between the agricultural extension and the optimal use of fertilizers. The extension plays the important role in the advise and educate of farmers in how they optimal use the fertilizers in a scientific way. This article aims to identify the concept the fertilizers. Identify the role of fertilizers in increasing the agricultural production, identify the role of agricultural extension in the optimal use of fertilizers and rural development.

Keywords: agricultural, extension, fertilizers, production

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Authors: Rim Chang Hyon, Song Hak Jin, Song Kwang Hyok, Jong Ki Hun

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The calibration of the articulated arm coordinate measuring machine (AACMM) is key to improving calibration accuracy and saving calibration time. To reduce the time consumed for calibration, we should choose the proper calibration gauges and develop a reasonable calibration method. In addition, we should get the exact optimal solution by accurately removing the rough errors within the experimental data. In this paper, we present a calibration method of the portable coordinate measuring arm (PCMA) using the 1.2m long bar guage with cone-holes. First, we determine the locations of the bar gauge and establish an optimal objective function for identifying the structural parameter errors. Next, we make a mathematical model of the calibration algorithm and present a new mathematical method to remove the rough errors within calibration data. Finally, we find the optimal solution to identify the kinematic parameter errors by using Levenberg-Marquardt algorithm. The experimental results show that our calibration method is very effective in saving the calibration time and improving the calibration accuracy.

Keywords: AACMM, kinematic model, parameter identify, measurement accuracy, calibration

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Authors: Marc S. Paolella, Pawel Polak

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The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and non-ellipticity. It introduces a so-called risk fear portfolio strategy which combines portfolio optimization with active risk monitoring. The former selects optimal portfolio weights. The latter, independently, initiates market exit in case of excessive risks. The strategy agrees with the stylized fact of stock market major sell-offs during the initial stage of market downturns. The advantages of the new framework are illustrated with an extensive empirical study. It leads to superior multivariate density and Value-at-Risk forecasting, and better portfolio performance. The proposed risk fear portfolio strategy outperforms various competing types of optimal portfolios, even in the presence of conservative transaction costs and frequent rebalancing. The risk monitoring of the optimal portfolio can serve as an early warning system against large market risks. In particular, the new strategy avoids all the losses during the 2008 financial crisis, and it profits from the subsequent market recovery.

Keywords: comfort, financial crises, portfolio optimization, risk monitoring

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Authors: Yassir Abdelrazig, Ren Moses

Abstract:

Roadway planning and design is a very complex process involving five key phases before a project is completed; planning, project development, final design, right-of-way, and construction. The planning phase for a new roadway transportation project is a very critical phase as it greatly affects all latter phases of the project. A location study is usually performed during the preliminary planning phase in a new roadway project. The objective of the location study is to develop alignment alternatives that are cost efficient considering land acquisition and construction costs. This paper describes a methodology to develop optimal preliminary roadway alignments utilizing spatial-data. Four optimization criteria are taken into consideration; roadway length, land cost, land slope, and environmental impacts. The basic concept of the methodology is to convert the proposed project area into a grid, which represents the search space for an optimal alignment. The aforementioned optimization criteria are represented in each of the grid’s cells. A spatial-data optimization technique is utilized to find the optimal alignment in the search space based on the four optimization criteria. Two case studies for new roadway projects in Duval County in the State of Florida are presented to illustrate the methodology. The optimization output alignments are compared to the proposed Florida Department of Transportation (FDOT) alignments. The comparison is based on right-of-way costs for the alignments. For both case studies, the right-of-way costs for the developed optimal alignments were found to be significantly lower than the FDOT alignments.

Keywords: gemoetric design, optimization, planning, roadway planning, roadway design

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Authors: A. Khosrozadeh, M. A. Darabi, M. Xing, Q. Wang

Abstract:

Fabrication of a high-performance supercapacitor (SC) using a flexible cellulose-based composite film of polyaniline (PANI), reduced graphene oxide (RGO), and silver nanowires (AgNWs) is reported. The flexibility, high capacitive behaviour, and cyclic stability of the entire device make it a good candidate for wearable SCs. The results show that a capacitance as high as 73.4 F/g (1.6 F/cm2) at a discharge rate of 1.1 A/g is achieved by the device. In addition, the SC demonstrates a power density up to 468.8 W/kg and an energy density up to 5.1 wh/kg. The flexibility of the composite film is attributed to the binding effect of cellulose fibers as well as reinforcing effect of AgNWs. The excellent electrochemical performance of the device is found to be owing to the synergistic effect between PANI/RGO/AgNWs ternary in a cushiony cellulose matrix and porous structure of the composite.

Keywords: cellulose, polyaniline, reduced graphene oxide, silver, super capacitor

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Authors: Karthikeyan Kalirajan, Ashok Joshi

Abstract:

An optimization problem is to setup to maximize the terminal kinetic energy of a maneuverable reentry vehicle (MaRV). The target location, the impact angle is given as constraints. The MaRV uses an explicit guidance law called Vector guidance. This law has two gains which are taken as decision variables. The problem is to find the optimal value of these gains which will result in minimum miss distance and impact angle error. Using a simple 3DOF non-rotating flat earth model and Lockheed martin HP-MARV as the reentry vehicle, the nature of solutions of the optimization problem is studied. This is achieved by carrying out a parametric study for a range of closed loop gain values and the corresponding impact angle error and the miss distance values are generated. The results show that there are well defined lower and upper bounds on the gains that result in near optimal terminal guidance solution. It is found from this study, that there exist common permissible regions (values of gains) where all constraints are met. Moreover, the permissible region lies between flat regions and hence the optimization algorithm has to be chosen carefully. It is also found that, only one of the gain values is independent and that the other dependent gain value is related through a simple straight-line expression. Moreover, to reduce the computational burden of finding the optimal value of two gains, a guidance law called Diveline guidance is discussed, which uses single gain. The derivation of the Diveline guidance law from Vector guidance law is discussed in this paper.

Keywords: Marv guidance, reentry trajectory, trajectory optimization, guidance gain selection

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Authors: Levicatus Mugenyi, Joaniter Nankabirwa, Emmanuel Arinaitwe, John Rek, Niel Hens, Moses Kamya, Grant Dorsey

Abstract:

Background: Indoor residual spraying (IRS) reduces vector densities and malaria transmission, however, the most effective spraying intervals for IRS have not been well established. We aim to estimate the optimal timing interval for IRS using a modeling approach. Methods: We use a generalized additive model to estimate the optimal timing interval for IRS using the predicted malaria incidence. The model is applied to post IRS cohort clinical data from children aged 0.5–10 years in selected households in Tororo, historically a high malaria transmission setting in Uganda. Six rounds of IRS were implemented in Tororo during the study period (3 rounds with bendiocarb: December 2014 to December 2015, and 3 rounds with actellic: June 2016 to July 2018). Results: Monthly incidence of malaria from October 2014 to February 2019 decreased from 3.25 to 0.0 per person-years in the children under 5 years, and 1.57 to 0.0 for 5-10 year-olds. The optimal time interval for IRS differed between bendiocarb and actellic and by IRS round. It was estimated to be 17 and 40 weeks after the first round of bendiocarb and actellic, respectively. After the third round of actellic, 36 weeks was estimated to be optimal. However, we could not estimate from the data the optimal time after the second and third rounds of bendiocarb and after the second round of actellic. Conclusion: We conclude that to sustain the effect of IRS in a high-medium transmission setting, the second rounds of bendiocarb need to be applied roughly 17 weeks and actellic 40 weeks after the first round, and the timing differs for subsequent rounds. The amount of rainfall did not influence the trend in malaria incidence after IRS, as well as the IRS timing intervals. Our results suggest that shorter intervals for the IRS application can be more effective compared to the current practice, which is about 24 weeks for bendiocarb and 48 weeks for actellic. However, when considering our findings, one should account for the cost and drug resistance associated with IRS. We also recommend that the timing and incidence should be monitored in the future to improve these estimates.

Keywords: incidence, indoor residual spraying, generalized additive model, malaria

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Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

Abstract:

The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

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