Search results for: mathematical proportions

Authors: Seydou Sinde

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The aims of this paper are to formulate mathematical expressions that can be used to estimate the standpipe pressure (SPP). The developed formulas take into account the main factors that, directly or indirectly, affect the behavior of SPP values. Fluid rheology and well hydraulics are some of these essential factors. Mud Plastic viscosity, yield point, flow power, consistency index, flow rate, drillstring, and annular geometries are represented by the frictional pressure (Pf), which is one of the input independent parameters and is calculated, in this paper, using Herschel-Bulkley rheological model. Other input independent parameters include the rate of penetration (ROP), applied load or weight on the bit (WOB), bit revolutions per minute (RPM), bit torque (TRQ), and hole inclination and direction coupled in the hole curvature or dogleg (DL). The technique of repeating parameters and Buckingham PI theorem are used to reduce the number of the input independent parameters into the dimensionless revolutions per minute (RPMd), the dimensionless torque (TRQd), and the dogleg, which is already in the dimensionless form of radians. Multivariable linear and polynomial regression technique using PTC Mathcad Prime 4.0 is used to analyze and determine the exact relationships between the dependent parameter, which is SPP, and the remaining three dimensionless groups. Three models proved sufficiently satisfactory to estimate the standpipe pressure: multivariable linear regression model 1 containing three regression coefficients for vertical wells; multivariable linear regression model 2 containing four regression coefficients for deviated wells; and multivariable polynomial quadratic regression model containing six regression coefficients for both vertical and deviated wells. Although that the linear regression model 2 (with four coefficients) is relatively more complex and contains an additional term over the linear regression model 1 (with three coefficients), the former did not really add significant improvements to the later except for some minor values. Thus, the effect of the hole curvature or dogleg is insignificant and can be omitted from the input independent parameters without significant losses of accuracy. The polynomial quadratic regression model is considered the most accurate model due to its relatively higher accuracy for most of the cases. Data of nine wells from the Middle East were used to run the developed models with satisfactory results provided by all of them, even if the multivariable polynomial quadratic regression model gave the best and most accurate results. Development of these models is useful not only to monitor and predict, with accuracy, the values of SPP but also to early control and check for the integrity of the well hydraulics as well as to take the corrective actions should any unexpected problems appear, such as pipe washouts, jet plugging, excessive mud losses, fluid gains, kicks, etc.

Keywords: standpipe, pressure, hydraulics, nondimensionalization, parameters, regression

Procedia PDF Downloads 84

Authors: Antonio A. M. Laudani, Igor O. Golosnoy, Ole T. Thomsen

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Rotor blades of large, modern wind turbines are highly susceptible to downward lightning strikes, as well as to triggering upward lightning; consequently, it is necessary to equip them with an effective lightning protection system (LPS) in order to avoid any damage. The performance of existing LPSs is affected by carbon fibre reinforced polymer (CFRP) structures, which lead to lightning-induced damage in the blades, e.g. via electrical sparks. A solution to prevent internal arcing would be to electrically bond the LPS and the composite structures such that to obtain the same electric potential. Nevertheless, elevated temperatures are achieved at the joint interfaces because of high contact resistance, which melts and vaporises some of the epoxy resin matrix around the bonding. The produced high-pressure gasses open up the bonding and can ignite thermal sparks. The objective of this paper is to predict the current density distribution and the temperature field in the adhesive joint cross-section, in order to check whether the resin pyrolysis temperature is achieved and any damage is expected. The finite element method has been employed to solve both the current and heat transfer problems, which are considered weakly coupled. The mathematical model for electric current includes Maxwell-Ampere equation for induced electric field solved together with current conservation, while the thermal field is found from heat diffusion equation. In this way, the current sub-model calculates Joule heat release for a chosen bonding configuration, whereas the thermal analysis allows to determining threshold values of voltage and current density not to be exceeded in order to maintain the temperature across the joint below the pyrolysis temperature, therefore preventing the occurrence of outgassing. In addition, it provides an indication of the minimal number of bonding points. It is worth to mention that the numerical procedures presented in this study can be tailored and applied to any type of joints other than adhesive ones for wind turbine blades. For instance, they can be applied for lightning protection of aerospace bolted joints. Furthermore, they can even be customized to predict the electromagnetic response under lightning strikes of other wind turbine systems, such as nacelle and hub components.

Keywords: carbon fibre reinforced polymer, equipotential bonding, finite element method, FEM, lightning protection system, LPS, wind turbine blades

Procedia PDF Downloads 164

Authors: Triveni Gogoi, Rima Chatterjee

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Shear wave velocity (Vs) estimation is an important approach in the seismic exploration and characterization of a hydrocarbon reservoir. There are varying methods for prediction of S-wave velocity, if recorded S-wave log is not available. But all the available methods for Vs prediction are empirical mathematical models. Shear wave velocity can be estimated using P-wave velocity by applying Castagna’s equation, which is the most common approach. The constants used in Castagna’s equation vary for different lithologies and geological set-ups. In this study, multiple regression analysis has been used for estimation of S-wave velocity. The EMERGE module from Hampson-Russel software has been used here for generation of S-wave log. Both single attribute and multi attributes analysis have been carried out for generation of synthetic S-wave log in Upper Assam basin. Upper Assam basin situated in North Eastern India is one of the most important petroleum provinces of India. The present study was carried out using four wells of the study area. Out of these wells, S-wave velocity was available for three wells. The main objective of the present study is a prediction of shear wave velocities for wells where S-wave velocity information is not available. The three wells having S-wave velocity were first used to test the reliability of the method and the generated S-wave log was compared with actual S-wave log. Single attribute analysis has been carried out for these three wells within the depth range 1700-2100m, which corresponds to Barail group of Oligocene age. The Barail Group is the main target zone in this study, which is the primary producing reservoir of the basin. A system generated list of attributes with varying degrees of correlation appeared and the attribute with the highest correlation was concerned for the single attribute analysis. Crossplot between the attributes shows the variation of points from line of best fit. The final result of the analysis was compared with the available S-wave log, which shows a good visual fit with a correlation of 72%. Next multi-attribute analysis has been carried out for the same data using all the wells within the same analysis window. A high correlation of 85% has been observed between the output log from the analysis and the recorded S-wave. The almost perfect fit between the synthetic S-wave and the recorded S-wave log validates the reliability of the method. For further authentication, the generated S-wave data from the wells have been tied to the seismic and correlated them. Synthetic share wave log has been generated for the well M2 where S-wave is not available and it shows a good correlation with the seismic. Neutron porosity, density, AI and P-wave velocity are proved to be the most significant variables in this statistical method for S-wave generation. Multilinear regression method thus can be considered as a reliable technique for generation of shear wave velocity log in this study.

Keywords: Castagna's equation, multi linear regression, multi attribute analysis, shear wave logs

Procedia PDF Downloads 229

Authors: Pin-Ling Yin, Dung-Ying Lin

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Satellites play an important role in our daily lives, from monitoring the Earth's environment and providing real-time disaster imagery to predicting extreme weather events. As technology advances and demands increase, the tasks undertaken by satellites have become increasingly complex, with more stringent resource management requirements. A common challenge in satellite mission scheduling is the limited availability of resources, including onboard memory, ground station accessibility, and satellite power. In this context, efficiently scheduling and managing the increasingly complex satellite missions under constrained resources has become a critical issue that needs to be addressed. The core of Satellite Onboard Activity Planning (SOAP) lies in optimizing the scheduling of the received tasks, arranging them on a timeline to form an executable onboard mission plan. This study aims to develop an optimization model that considers the various constraints involved in satellite mission scheduling, such as the non-overlapping execution periods for certain types of tasks, the requirement that tasks must fall within the contact range of specified types of ground stations during their execution, onboard memory capacity limits, and the collaborative constraints between different types of tasks. Specifically, this research constructs a mixed-integer programming mathematical model and solves it with a commercial optimization package. Simultaneously, as the problem size increases, the problem becomes more difficult to solve. Therefore, in this study, a heuristic algorithm has been developed to address the challenges of using commercial optimization package as the scale increases. The goal is to effectively plan satellite missions, maximizing the total number of executable tasks while considering task priorities and ensuring that tasks can be completed as early as possible without violating feasibility constraints. To verify the feasibility and effectiveness of the algorithm, test instances of various sizes were generated, and the results were validated through feedback from on-site users and compared against solutions obtained from a commercial optimization package. Numerical results show that the algorithm performs well under various scenarios, consistently meeting user requirements. The satellite mission scheduling algorithm proposed in this study can be flexibly extended to different types of satellite mission demands, achieving optimal resource allocation and enhancing the efficiency and effectiveness of satellite mission execution.

Keywords: mixed-integer programming, meta-heuristics, optimization, resource management, satellite mission scheduling

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Authors: Michael Mihalicz, Aziz Guergachi

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Background: The science of modelling choice preferences has evolved over centuries into an interdisciplinary field contributing to several branches of Microeconomics and Mathematical Psychology. Early theories in Decision Science rested on the logic of rationality, but as it and related fields matured, descriptive theories emerged capable of explaining systematic violations of rationality through cognitive mechanisms underlying the thought processes that guide human behaviour. Cognitive limitations are not, however, solely responsible for systematic deviations from rationality and many are now exploring the effect of visceral factors as the more dominant drivers. The current study builds on the existing literature by exploring sleep deprivation, thermal comfort, stress, hunger, fear, anger and sadness as moderators to three distinct elements that define individual risk preference under Cumulative Prospect Theory. Methodology: This study is designed to compare the risk preference of participants experiencing an elevated affective or visceral state to those in a neutral state using nonparametric elicitation methods across three domains. Two experiments will be conducted simultaneously using different methodologies. The first will determine visceral states and risk preferences randomly over a two-week period by prompting participants to complete an online survey remotely. In each round of questions, participants will be asked to self-assess their current state using Visual Analogue Scales before answering a series of lottery-style elicitation questions. The second experiment will be conducted in a laboratory setting using psychological primes to induce a desired state. In this experiment, emotional states will be recorded using emotion analytics and used a basis for comparison between the two methods. Significance: The expected results include a series of measurable and systematic effects on the subjective interpretations of gamble attributes and evidence supporting the proposition that a portion of the variability in human choice preferences unaccounted for by cognitive limitations can be explained by interacting visceral states. Significant results will promote awareness about the subconscious effect that emotions and other drive states have on the way people process and interpret information, and can guide more effective decision making by informing decision-makers of the sources and consequences of irrational behaviour.

Keywords: decision making, emotions, prospect theory, visceral factors

Procedia PDF Downloads 149

Authors: Taik Kim

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Mathematics anxiety has an important consequence for teacher practices that influence students’ attitudes and achievement. Elementary prospective teachers have the highest levels of mathematics anxiety in comparison with other college majors. In his teaching practice, the researcher developed a highly successful teaching model to reduce pre-service teachers’ higher math anxiety and simultaneously to improve their pedagogical math content knowledge. There were eighty one participants from 2015 to 2018 who took the Mathematics for Elementary Teachers I and II. As the analysis data indicated, elementary prospective teachers’ math anxiety was greatly reduced with improving their math pedagogical knowledge. U.S encounters a critical shortage of well qualified educators. To solve the issue, it is essential to engage students in a long-term commitmentto shape better teachers, who will, in turn, produce k-12 school students that are better-prepared for college students. It is imperative that new instructional strategies are implemented to improve student learning and address declining interest, poor preparedness, a lack of diverse representation, and low persistence of students in mathematics. Many four year college students take math courses from the math department in the College of Arts& Science and then take methodology courses from the College of Education. Before taking pedagogy, many students struggle in learning mathematics and lose their confidence. Since the content course focus on college level math, instead of pre service teachers’ teaching area, per se elementary math, they do not have a chance to improve their teaching skills on topics which eventually they teach. The research, a joint appointment of math and math education, has been involved in teaching content and pedagogy. As the result indicated, participants were able to math content at the same time how to teach. In conclusion, the new initiative to use several teaching strategies was able not only to increase elementary prospective teachers’ mathematical skills and knowledge but also to improve their attitude toward mathematics. We need an innovative teaching strategy which implements evidence-based tactics in redesigning a education and math to improve pre service teachers’math skills and which can improve students’ attitude toward math and students’ logical and reasoning skills. Implementation of these best practices in the local school district is particularly important because K-8 teachers are not generally familiar with lab-based instruction. At the same time, local school teachers will learn a new way how to teach math. This study can be a vital teacher education model expanding throughout the State and nationwide. In summary, this study yields invaluable information how to improve teacher education in the elementary level and, eventually, how to enhance K-8 students’ math achievement.

Keywords: quality of education and improvement method, teacher education, innovative teaching and learning methodologies, math education

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Authors: Kassem Natouf, Ihab Jnad

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In coastal aquifers, the interface between fresh groundwater and salty seawater may shift inland, reaching coastal wells and causing an increase in the salinity of the water they pump, putting them out of service. Many Arab coastal sites suffer from this phenomenon due to the increased pumping of coastal groundwater. This research aims to prepare a comprehensive study describing the common characteristics of the phenomenon of seawater intrusion with coastal freshwater aquifers in the Arab region, its general and specific causes and negative effects, in a way that contributes to overcoming this phenomenon, and to exchanging expertise between Arab countries in studying and analyzing it, leading to overcoming it. This research also aims to build geographical and relational databases for data, information and studies available in Arab countries about seawater intrusion with freshwater so as to provide the data and information necessary for managing groundwater resources on Arab coasts, including studying the effects of climate change on these resources and helping decision-makers in developing executive programs to overcome the seawater intrusion with groundwater. The research relied on the methodology of analysis and comparison, where the available information and data about the phenomenon in the Arab region were collected. After that, the information and data collected were studied and analyzed, and the causes of the phenomenon in each case, its results, and solutions for prevention were stated. Finally, the different cases were compared, and the common causes, results, and methods of treatment between them were deduced, and a technical report summarizing that was prepared. To overcome the phenomenon of seawater intrusion with fresh groundwater: (1) It is necessary to develop efforts to monitor the quantity and quality of groundwater on the coasts and to develop mathematical models to predict the impact of climate change, sea level rise, and human activities on coastal groundwater. (2) Over-pumping of coastal aquifers is an important cause of seawater intrusion. To mitigate this problem, Arab countries should reduce groundwater pumping and promote rainwater harvesting, surface irrigation, and water recycling practices. (3) Artificial recharge of coastal groundwater with various forms of water, whether fresh or treated, is a promising technology to mitigate the effects of seawater intrusion.

Keywords: coastal aquifers, seawater intrusion, fresh groundwater, salinity increase, Arab region, groundwater management, climate change effects, sustainable water practices, over-pumping, artificial recharge, monitoring and modeling, data databases, groundwater resources, negative effects, comparative analysis, technical report, water scarcity, groundwater quality, decision-making, environmental impact, agricultural practices

Procedia PDF Downloads 34

Authors: B. Kriheli, E. Levner, T. C. E. Cheng, C. T. Ng

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During the last decades, research interest in planning, scheduling, and control of emergency response operations, especially people rescue and evacuation from the dangerous zone of marine accidents, has increased dramatically. Until the survivors (called ‘targets’) are found and saved, it may cause loss or damage whose extent depends on the location of the targets and the search duration. The problem is to efficiently search for and detect/rescue the targets as soon as possible with the help of intelligent mobile robots so as to maximize the number of saved people and/or minimize the search cost under restrictions on the amount of saved people within the allowable response time. We consider a special situation when the autonomous mobile robots (AMR), e.g., unmanned aerial vehicles and remote-controlled robo-ships have no operator on board as they are guided and completely controlled by on-board sensors and computer programs. We construct a mathematical model for the search process in an uncertain environment and provide a new fast algorithm for scheduling the activities of the autonomous robots during the search-and rescue missions after an accident at sea. We presume that in the unknown environments, the AMR’s search-and-rescue activity is subject to two types of error: (i) a 'false-negative' detection error where a target object is not discovered (‘overlooked') by the AMR’s sensors in spite that the AMR is in a close neighborhood of the latter and (ii) a 'false-positive' detection error, also known as ‘a false alarm’, in which a clean place or area is wrongly classified by the AMR’s sensors as a correct target. As the general resource-constrained discrete search problem is NP-hard, we restrict our study to finding local-optimal strategies. A specificity of the considered operational research problem in comparison with the traditional Kadane-De Groot-Stone search models is that in our model the probability of the successful search outcome depends not only on cost/time/probability parameters assigned to each individual location but, as well, on parameters characterizing the entire history of (unsuccessful) search before selecting any next location. We provide a fast approximation algorithm for finding the AMR route adopting a greedy search strategy in which, in each step, the on-board computer computes a current search effectiveness value for each location in the zone and sequentially searches for a location with the highest search effectiveness value. Extensive experiments with random and real-life data provide strong evidence in favor of the suggested operations research model and corresponding algorithm.

Keywords: disaster management, intelligent robots, scheduling algorithm, search-and-rescue at sea

Procedia PDF Downloads 169

Authors: Mohamed K. Khalil, Mohamed S. Ragab

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Atomizers are used in many engineering applications including diesel engines, petrol engines and spray combustion in furnaces as well as gas turbine engines. These atomizers are used to increase the specific surface area of the fuel, which achieve a high rate of fuel mixing and evaporation. In all combustion systems reduction in mean drop size is a challenge which has many advantages since it leads to rapid and easier ignition, higher volumetric heat release rate, wider burning range and lower exhaust concentrations of the pollutant emissions. Pressure atomizers have a different configuration for design such as swirl atomizer (simplex), dual orifice, spill return, plain orifice, duplex and fan spray. Simplex pressure atomizers are the most common type of all. Among all types of atomizers, pressure swirl types resemble a special category since they differ in quality of atomization, the reliability of operation, simplicity of construction and low expenditure of energy. But, the disadvantages of these atomizers are that they require very high injection pressure and have low discharge coefficient owing to the fact that the air core covers the majority of the atomizer orifice. To overcome these problems, dual orifice atomizer was designed. This paper proposes a detailed mathematical model design procedure for both pressure swirl atomizer (Simplex) and dual orifice atomizer, examines the effects of varying fuel type and makes a clear comparison between the two types. Using five types of fuel (JP-5, JA1, JP-4, Diesel and Bio-Diesel) as a case study, reveal the effect of changing fuel type and its properties on atomizers design and spray characteristics. Which effect on combustion process parameters; Sauter Mean Diameter (SMD), spray cone angle and sheet thickness with varying the discharge coefficient from 0.27 to 0.35 during takeoff for high bypass turbofan engines. The spray atomizer performance of the pressure swirl fuel injector was compared to the dual orifice fuel injector at the same differential pressure and discharge coefficient using Excel. The results are analyzed and handled to form the final reliability results for fuel injectors in high bypass turbofan engines. The results show that the Sauter Mean Diameter (SMD) in dual orifice atomizer is larger than Sauter Mean Diameter (SMD) in pressure swirl atomizer, the film thickness (h) in dual orifice atomizer is less than the film thickness (h) in pressure swirl atomizer. The Spray Cone Angle (α) in pressure swirl atomizer is larger than Spray Cone Angle (α) in dual orifice atomizer.

Keywords: gas turbine engines, atomization process, Sauter mean diameter, JP-5

Procedia PDF Downloads 165

Authors: Anderson Braga Mendes

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Itaipu Hydroelectric Power Plant is settled on the Paraná River, which is a natural boundary between Brazil and Paraguay; thus, the facility is shared by both countries. Itaipu Power Plant is the biggest hydroelectric generator in the world, and provides clean and renewable electrical energy supply for 17% and 76% of Brazil and Paraguay, respectively. The plant started its generation in 1984. It counts on 20 Francis turbines and has installed capacity of 14,000 MWh. Its historic generation record occurred in 2016 (103,098,366 MWh), and since the beginning of its operation until the last day of 2016 the plant has achieved the sum of 2,415,789,823 MWh. The distinct sedimentologic aspects of the drainage area of Itaipu Power Plant, from its stretch upstream (Porto Primavera and Rosana dams) to downstream (Itaipu dam itself), were taken into account in order to best estimate the increase/decrease in the sediment yield by using data from 2001 to 2016. Such data are collected through a network of 14 automatic sedimentometric stations managed by the company itself and operating in an hourly basis, covering an area of around 136,000 km² (92% of the incremental drainage area of the undertaking). Since 1972, a series of lifespan studies for the Itaipu Power Plant have been made, being first assessed by Sir Hans Albert Einstein, at the time of the feasibility studies for the enterprise. From that date onwards, eight further studies were made through the last 44 years aiming to confer more precision upon the estimates based on more updated data sets. From the analysis of each monitoring station, it was clearly noticed strong increase tendencies in the sediment yield through the last 14 years, mainly in the Iguatemi, Ivaí, São Francisco Falso and Carapá Rivers, the latter situated in Paraguay, whereas the others are utterly in Brazilian territory. Five lifespan scenarios considering different sediment yield tendencies were simulated with the aid of the softwares SEDIMENT and DPOSIT, both developed by the author of the present work. Such softwares thoroughly follow the Borland & Miller methodology (empirical method of area-reduction). The soundest scenario out of the five ones under analysis indicated a lifespan foresight of 168 years, being the reservoir only 1.8% silted by the end of 2016, after 32 years of operation. Besides, the mass balance in the reservoir (water inflows minus outflows) between 1986 and 2016 shows that 2% of the whole Itaipu lake is silted nowadays. Owing to the convergence of both results, which were acquired by using different methodologies and independent input data, it is worth concluding that the mathematical modeling is satisfactory and calibrated, thus assigning credibility to this most recent lifespan estimate.

Keywords: Borland and Miller method, hydroelectricity, Itaipu Power Plant, lifespan, mass balance

Procedia PDF Downloads 274

Authors: Lorenzo Petrucci

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This paper is intended to give insight into the potential use of small-scale off-grid trigeneration systems powered by biogas generated in a dairy farm. The off-grid plant object of analysis comprises a dual-fuel Genset as well as electrical and thermal storage equipment and an adsorption machine. The loads are the different apparatus used in the dairy farm, a household where the workers live and a small electric vehicle whose batteries can also be used as a power source in case of emergency. The insertion in the plant of an adsorption machine is mainly justified by the abundance of thermal energy and the simultaneous high cooling demand associated with the milk-chilling process. In the evaluated operational scenario, our research highlights the importance of prioritizing specific small loads which cannot sustain an interrupted supply of power over time. As a consequence, a photovoltaic and thermal panel is included in the plant and is tasked with providing energy independently of potentially disruptive events such as engine malfunctioning or scarce and unstable supplies of fuels. To efficiently manage the plant an energy dispatch strategy is created in order to control the flow of energy between the power sources and the thermal and electric storages. In this article we elaborate on models of the equipment and from these models, we extract parameters useful to build load-dependent profiles of the prime movers and storage efficiencies. We show that under reasonable assumptions the analysis provides a sensible estimate of the generated energy. The simulations indicate that a Diesel Generator sized to a value 25% higher than the total electrical peak demand operates 65% of the time below the minimum acceptable load threshold. To circumvent such a critical operating mode, dump loads are added through the activation and deactivation of small resistors. In this way, the excess of electric energy generated can be transformed into useful heat. The combination of PVT and electrical storage to support the prioritized load in an emergency scenario is evaluated in two different days of the year having the lowest and highest irradiation values, respectively. The results show that the renewable energy component of the plant can successfully sustain the prioritized loads and only during a day with very low irradiation levels it also needs the support of the EVs’ battery. Finally, we show that the adsorption machine can reduce the ice builder and the air conditioning energy consumption by 40%.

Keywords: hybrid power plants, mathematical modeling, off-grid plants, renewable energy, trigeneration

Procedia PDF Downloads 174

Authors: M. Duk, L. Grabowski, P. Magryta

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Today's very important element relating to air transport is the environment impact issues. Nowadays there are no emissions standards for turbine and piston engines used in air transport. However, it should be noticed that the environmental effect in the form of exhaust gases from aircraft engines should be as small as possible. For this purpose, R&D centers often use special software to simulate and to estimate the negative effect of engine working process. For cooperation between the Lublin University of Technology and the Polish aviation company WSK "PZL-KALISZ" S.A., to achieve more effective operation of the ASz62IR engine, one of such tools have been used. The AVL Boost software allows to perform 1D simulations of combustion process of piston engines. ASz62IR is a nine-cylinder aircraft engine in a radial configuration. In order to analyze the impact of its working process on the environment, the mathematical model in the AVL Boost software have been made. This model contains, among others, model of the operation cycle of the cylinders. This model was based on a volume change in combustion chamber according to the reciprocating movement of a piston. The simplifications that all of the pistons move identically was assumed. The changes in cylinder volume during an operating cycle were specified. Those changes were important to determine the energy balance of a cylinder in an internal combustion engine which is fundamental for a model of the operating cycle. The calculations for cylinder thermodynamic state were based on the first law of thermodynamics. The change in the mass in the cylinder was calculated from the sum of inflowing and outflowing masses including: cylinder internal energy, heat from the fuel, heat losses, mass in cylinder, cylinder pressure and volume, blowdown enthalpy, evaporation heat etc. The model assumed that the amount of heat released in combustion process was calculated from the pace of combustion, using Vibe model. For gas exchange, it was also important to consider heat transfer in inlet and outlet channels because of much higher values there than for flow in a straight pipe. This results from high values of heat exchange coefficients and temperature coefficients near valves and valve seats. A Zapf modified model of heat exchange was used. To use the model with the flight scenarios, the impact of flight altitude on engine performance has been analyze. It was assumed that the pressure and temperature at the inlet and outlet correspond to the values resulting from the model for International Standard Atmosphere (ISA). Comparing this model of operation cycle with the others submodels of the ASz62IR engine, it could be noticed, that a full analysis of the performance of the engine, according to the ISA conditions, can be made. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under

Keywords: aviation propulsion, AVL Boost, engine model, operation cycle, aircraft engine

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Authors: Kang Lin Peng

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Space tourism emerged in 2001 and became famous in 2021, following the development of space technology. The space market is twisted because of the excess demand. Space tourism is currently rare and extremely expensive, with biased luxury product pricing, which is the seller’s market that consumers can not bargain with. Spaceship companies such as Virgin Galactic, Blue Origin, and Space X have been charged space tourism prices from 200 thousand to 55 million depending on various heights in space. There should be a reasonable price based on a fair basis. This study aims to derive a spacetime pricing model, which is different from the general pricing model on the earth’s surface. We apply general relativity theory to deduct the mathematical formula for the space tourism pricing model, which covers the traditional time-independent model. In the future, the price of space travel will be different from current flight travel when space travel is measured in lightyear units. The pricing of general commodities mainly considers the general equilibrium of supply and demand. The pricing model considers risks and returns with the dependent time variable as acceptable when commodities are on the earth’s surface, called flat spacetime. Current economic theories based on the independent time scale in the flat spacetime do not consider the curvature of spacetime. Current flight services flying the height of 6, 12, and 19 kilometers are charging with a pricing model that measures time coordinate independently. However, the emergence of space tourism is flying heights above 100 to 550 kilometers that have enlarged the spacetime curvature, which means tourists will escape from a zero curvature on the earth’s surface to the large curvature of space. Different spacetime spans should be considered in the pricing model of space travel to echo general relativity theory. Intuitively, this spacetime commodity needs to consider changing the spacetime curvature from the earth to space. We can assume the value of each spacetime curvature unit corresponding to the gradient change of each Ricci or energy-momentum tensor. Then we know how much to spend by integrating the spacetime from the earth to space. The concept is adding a price p component corresponding to the general relativity theory. The space travel pricing model degenerates into a time-independent model, which becomes a model of traditional commodity pricing. The contribution is that the deriving of the space tourism pricing model will be a breakthrough in philosophical and practical issues for space travel. The results of the space tourism pricing model extend the traditional time-independent flat spacetime mode. The pricing model embedded spacetime as the general relativity theory can better reflect the rationality and accuracy of space travel on the universal scale. The universal scale from independent-time scale to spacetime scale will bring a brand-new pricing concept for space traveling commodities. Fair and efficient spacetime economics will also bring to humans’ travel when we can travel in lightyear units in the future.

Keywords: space tourism, spacetime pricing model, general relativity theory, spacetime curvature

Procedia PDF Downloads 128

Authors: Ken Zakreski

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Regulating Canadian Facebook Groups, of a size and type, when they reach a threshold of audio video content. Consider the evolution of the Streaming Act, Parl GC Bill C-11 (44-1) and the regulations that will certainly follow. The Canadian Heritage Minister's office stipulates, "the Broadcasting Act only applies to audio and audiovisual content, not written journalism.” Governance— After 10 years, a community radio station for Gabriola Island, BC – Canadian Radio-television and Telecommunications Commission (“CRTC”) was approved but never started – became a Facebook Group “Community Bulletin Board - Life on Gabriola“ referred to as CBBlog. After CBBlog started and began to gather real traction, a member of the Group cloned the membership and ran their competing Facebook group under the banner of "free speech”. Here we see an inflection point [change of cultural stewardship] with two different mathematical results [engagement and membership growth]. Canada's telecommunication history of “portability” and “interoperability” made that Facebook Group CBBlog the better option, over broadcast FM radio for a community pandemic information sharing service for Gabriola Island, BC. A culture of ignorance flourishes in social media. Often people do not understand their own experience, or the experience of others because they do not have the concepts needed for understanding. It is thus important they are not denied concepts required for their full understanding. For example, Legislators need to know something about gay culture before they can make any decisions about it. Community Media policies and CRTC regulations are known and regulators can use that history to forge forward with regulations for internet platforms of a size and content type that reach a threshold of audio / video content. Mostly volunteer run media services, provide order of magnitude lower costs over commercial media. (Treating) Facebook Groups as new media.? Cathy Edwards, executive director of the Canadian Association of Community Television Users and Stations (“CACTUS”), calls it new media in that the distribution platform is not the issue. What does make community groups community media? Cathy responded, "... it's bylaws, articles of incorporation that state they are community media, they have accessibility, commitments to skills training, any member of the community can be a member, and there is accountability to a board of directors". Eligibility for funding through CACTUS requires these same commitments. It is risky for a community to invest into a platform as ownership has not been litigated. Is a FaceBook Group an asset of a not for profit society? The memo, from law student, Jared Hubbard summarizes, “Rights and interests in a Facebook group could, in theory, be transferred as property... This theory is currently unconfirmed by Canadian courts. “

Keywords: social media, governance, community media, Canadian radio

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Authors: Epaminondas G. Kyriakidis, Theodosis D. Dimitrakos, Constantinos C. Karamatsoukis

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The vehicle routing problem (VRP) is a well-known problem in Operations Research and has been widely studied during the last fifty-five years. The context of the VRP is that of delivering or collecting products to or from customers who are scattered in a geographical area and have placed orders for these products. A vehicle or a fleet of vehicles start their routes from a depot and visit the customers in order to satisfy their demands. Special attention has been given to the capacitated VRP in which the vehicles have limited carrying capacity for the goods that are delivered or collected. In the present work, we present a specific capacitated stochastic vehicle routing problem which has many realistic applications. We develop and analyze a mathematical model for a specific vehicle routing problem in which a vehicle starts its route from a depot and visits N customers according to a particular sequence in order to collect from them two similar but not identical products. We name these products, product 1 and product 2. Each customer possesses items either of product 1 or product 2 with known probabilities. The number of the items of product 1 or product 2 that each customer possesses is a discrete random variable with known distribution. The actual quantity and the actual type of product that each customer possesses are revealed only when the vehicle arrives at the customer’s site. It is assumed that the vehicle has two compartments. We name these compartments, compartment 1 and compartment 2. It is assumed that compartment 1 is suitable for loading product 1 and compartment 2 is suitable for loading product 2. However, it is permitted to load items of product 1 into compartment 2 and items of product 2 into compartment 1. These actions cause costs that are due to extra labor. The vehicle is allowed during its route to return to the depot to unload the items of both products. The travel costs between consecutive customers and the travel costs between the customers and the depot are known. The objective is to find the optimal routing strategy, i.e. the routing strategy that minimizes the total expected cost among all possible strategies for servicing all customers. It is possible to develop a suitable dynamic programming algorithm for the determination of the optimal routing strategy. It is also possible to prove that the optimal routing strategy has a specific threshold-type strategy. Specifically, it is shown that for each customer the optimal actions are characterized by some critical integers. This structural result enables us to design a special-purpose dynamic programming algorithm that operates only over these strategies having this structural property. Extensive numerical results provide strong evidence that the special-purpose dynamic programming algorithm is considerably more efficient than the initial dynamic programming algorithm. Furthermore, if we consider the same problem without the assumption that the customers are ordered, numerical experiments indicate that the optimal routing strategy can be computed if N is smaller or equal to eight.

Keywords: dynamic programming, similar products, stochastic demands, stochastic preferences, vehicle routing problem

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Authors: Rui Brito

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This contribution regards a literature review of inventory management that is a relevant topic for the firms, due to its important use of capital with implications in firm’s profitability within the complexity of a more competitive and globalized world. Firms look for small inventories in order to reduce holding costs, namely opportunity cost, warehousing and handling costs, deterioration and being out of style, but larger inventories are required by some reasons, such as customer service, ordering cost, transportation cost, supplier’s payment to reduce unit costs or to take advantage of price increase in the near future, and equipment setup cost. Thus, management shall address a trade-off between small inventories and larger inventories. This literature review concerns three types of inventory (spare parts, safety stock, and vendor) whose management usually is beyond the scope of logistics. The applied methodology consisted of an online search of databases regarding scientific documents in English, namely Elsevier, Springer, Emerald, Wiley, and Taylor & Francis, but excluding books except if edited, using search engines, such as Google Scholar and B-on. The search was based on three keywords/strings (themes) which had to be included just as in the article title, suggesting themes were very relevant to the researchers. The whole search period was between 2009 and 2018 with the aim of collecting between twenty and forty studies considered relevant within each of the key words/strings specified. Documents were sorted by relevance and to prevent the exclusion of the more recent articles, based on lower quantity of citations partially due to less time to be cited in new research articles, the search period was divided into two sub-periods (2009-2015 and 2016-2018). The number of surveyed articles by theme showed a variation from 40 to 200 and the number of citations of those articles showed a wider variation from 3 to 216. Selected articles from the three themes were analyzed and the first seven of the first sub-period and the first three of the second sub-period with more citations were read in full to make a synopsis of each article. Overall, the findings show that the majority of article types were models, namely mathematical, although with different sub-types for each theme. Almost all articles suggest further studies, with some mentioning it for their own author(s), which widen the diversity of the previous research. Identified research gaps concern the use of surveys to know which are the models more used by firms, the reasons for not using the models with more performance and accuracy, and which are the satisfaction levels with the outcomes of the inventories management and its effect on the improvement of the firm’s overall performance. The review ends with the limitations and contributions of the study.

Keywords: inventory management, safety stock, spare parts inventory, vendor managed inventory

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Authors: Amparo Camacho

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ABET accredited programs must assess the development of student learning outcomes (SOs) in engineering programs. Different institutions implement different strategies for this assessment, and they are usually designed “in house.” This paper presents a proposal for including standardized tests to complement the ABET assessment model in an engineering college made up of six distinct engineering programs. The engineering college formulated a model of quality assurance in education to be implemented throughout the six engineering programs to regularly assess and evaluate the achievement of SOs in each program offered. The model uses diverse techniques and sources of data to assess student performance and to implement actions of improvement based on the results of this assessment. The model is called “Assessment Process Model” and it includes SOs A through K, as defined by ABET. SOs can be divided into two categories: “hard skills” and “professional skills” (soft skills). The first includes abilities, such as: applying knowledge of mathematics, science, and engineering and designing and conducting experiments, as well as analyzing and interpreting data. The second category, “professional skills”, includes communicating effectively, and understanding professional and ethnical responsibility. Within the Assessment Process Model, various tools were used to assess SOs, related to both “hard” as well as “soft” skills. The assessment tools designed included: rubrics, surveys, questionnaires, and portfolios. In addition to these instruments, the Engineering College decided to use tools that systematically gather consistent quantitative data. For this reason, an in-house exam was designed and implemented, based on the curriculum of each program. Even though this exam was administered during various academic periods, it is not currently considered standardized. In 2017, the Engineering College included three standardized tests: one to assess mathematical and scientific reasoning and two more to assess reading and writing abilities. With these exams, the college hopes to obtain complementary information that can help better measure the development of both hard and soft skills of students in the different engineering programs. In the first semester of 2017, the three exams were given to three sample groups of students from the six different engineering programs. Students in the sample groups were either from the first, fifth, and tenth semester cohorts. At the time of submission of this paper, the engineering college has descriptive statistical data and is working with various statisticians to have a more in-depth and detailed analysis of the sample group of students’ achievement on the three exams. The overall objective of including standardized exams in the assessment model is to identify more precisely the least developed SOs in order to define and implement educational strategies necessary for students to achieve them in each engineering program.

Keywords: assessment, hard skills, soft skills, standardized tests

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Authors: Swati Tomar, Sunil Kumar Gupta

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Anammox is a novel and promising technology that has changed the traditional concept of biological nitrogen removal. The process facilitates direct oxidation of ammonical nitrogen under anaerobic conditions with nitrite as an electron acceptor without the addition of external carbon sources. The present study investigated the feasibility of anammox hybrid reactor (AHR) combining the dual advantages of suspended and attached growth media for biodegradation of ammonical nitrogen in wastewater. The experimental unit consisted of 4 nos. of 5L capacity AHR inoculated with mixed seed culture containing anoxic and activated sludge (1:1). The process was established by feeding the reactors with synthetic wastewater containing NH4-H and NO2-N in the ratio 1:1 at HRT (hydraulic retention time) of 1 day. The reactors were gradually acclimated to higher ammonium concentration till it attained pseudo steady state removal at a total nitrogen concentration of 1200 mg/l. During this period, the performance of the AHR was monitored at twelve different HRTs varying from 0.25-3.0 d with increasing NLR from 0.4 to 4.8 kg N/m3d. AHR demonstrated significantly higher nitrogen removal (95.1%) at optimal HRT of 1 day. Filter media in AHR contributed an additional 27.2% ammonium removal in addition to 72% reduction in the sludge washout rate. This may be attributed to the functional mechanism of filter media which acts as a mechanical sieve and reduces the sludge washout rate many folds. This enhances the biomass retention capacity of the reactor by 25%, which is the key parameter for successful operation of high rate bioreactors. The effluent nitrate concentration, which is one of the bottlenecks of anammox process was also minimised significantly (42.3-52.3 mg/L). Process kinetics was evaluated using first order and Grau-second order models. The first-order substrate removal rate constant was found as 13.0 d-1. Model validation revealed that Grau second order model was more precise and predicted effluent nitrogen concentration with least error (1.84±10%). A new mathematical model based on mass balance was developed to predict N2 gas in AHR. The mass balance model derived from total nitrogen dictated significantly higher correlation (R2=0.986) and predicted N2 gas with least error of precision (0.12±8.49%). SEM study of biomass indicated the presence of the heterogeneous population of cocci and rod shaped bacteria of average diameter varying from 1.2-1.5 mm. Owing to enhanced NRE coupled with meagre production of effluent nitrate and its ability to retain high biomass, AHR proved to be the most competitive reactor configuration for dealing with nitrogen laden wastewater.

Keywords: anammox, filter media, kinetics, nitrogen removal

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Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Within agent-based modeling, opinion dynamics is the field that focuses on modeling people's opinions. In this prolific field, most of the literature is dedicated to the exploration of the two 'degrees of freedom' and how they impact the model’s properties (e.g., the average final opinion, the number of final clusters, etc.). These degrees of freedom are (1) the interaction rule, which determines how agents update their own opinion, and (2) the network topology, which defines the possible interaction among agents. In this work, we show that the third degree of freedom exists. This can be used to change a model's output up to 100% of its initial value or to transform two models (both from the literature) into each other. Since opinion dynamics models are representations of the real world, it is fundamental to understand how people’s opinions can be measured. Even for abstract models (i.e., not intended for the fitting of real-world data), it is important to understand if the way of numerically representing opinions is unique; and, if this is not the case, how the model dynamics would change by using different representations. The process of measuring opinions is non-trivial as it requires transforming real-world opinion (e.g., supporting most of the liberal ideals) to a number. Such a process is usually not discussed in opinion dynamics literature, but it has been intensively studied in a subfield of psychology called psychometrics. In psychometrics, opinion scales can be converted into each other, similarly to how meters can be converted to feet. Indeed, psychometrics routinely uses both linear and non-linear transformations of opinion scales. Here, we analyze how this transformation affects opinion dynamics models. We analyze this effect by using mathematical modeling and then validating our analysis with agent-based simulations. Firstly, we study the case of perfect scales. In this way, we show that scale transformations affect the model’s dynamics up to a qualitative level. This means that if two researchers use the same opinion dynamics model and even the same dataset, they could make totally different predictions just because they followed different renormalization processes. A similar situation appears if two different scales are used to measure opinions even on the same population. This effect may be as strong as providing an uncertainty of 100% on the simulation’s output (i.e., all results are possible). Still, by using perfect scales, we show that scales transformations can be used to perfectly transform one model to another. We test this using two models from the standard literature. Finally, we test the effect of scale transformation in the case of finite precision using a 7-points Likert scale. In this way, we show how a relatively small-scale transformation introduces both changes at the qualitative level (i.e., the most shared opinion at the end of the simulation) and in the number of opinion clusters. Thus, scale transformation appears to be a third degree of freedom of opinion dynamics models. This result deeply impacts both theoretical research on models' properties and on the application of models on real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

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Authors: Vlad Andrei Raducanu, Mariana Lucia Angelescu, Ion Cinca, Vasile Danut Cojocaru, Doina Raducanu

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By using smart digital tools, such as generative design (GD) and digital fabrication (DF), problems of high actuality concerning resources optimization (materials, energy, time) can be solved and applications or products of free-form type can be created. In the new digital technology materials are active, designed in response to a set of performance requirements, which impose a total rethinking of old material practices. The article presents the design procedure key steps of a free-form architectural object - a column type one with connections to get an adaptive 3D surface, by using the parametric design methodology and by exploiting the properties of conventional metallic materials. In parametric design the form of the created object or space is shaped by varying the parameters values and relationships between the forms are described by mathematical equations. Digital parametric design is based on specific procedures, as shape grammars, Lindenmayer - systems, cellular automata, genetic algorithms or swarm intelligence, each of these procedures having limitations which make them applicable only in certain cases. In the paper the design process stages and the shape grammar type algorithm are presented. The generative design process relies on two basic principles: the modeling principle and the generative principle. The generative method is based on a form finding process, by creating many 3D spatial forms, using an algorithm conceived in order to apply its generating logic onto different input geometry. Once the algorithm is realized, it can be applied repeatedly to generate the geometry for a number of different input surfaces. The generated configurations are then analyzed through a technical or aesthetic selection criterion and finally the optimal solution is selected. Endless range of generative capacity of codes and algorithms used in digital design offers various conceptual possibilities and optimal solutions for both technical and environmental increasing demands of building industry and architecture. Constructions or spaces generated by parametric design can be specifically tuned, in order to meet certain technical or aesthetical requirements. The proposed approach has direct applicability in sustainable architecture, offering important potential economic advantages, a flexible design (which can be changed until the end of the design process) and unique geometric models of high performance.

Keywords: parametric design, algorithmic procedures, free-form architectural object, sustainable architecture

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Stefano Iannello, Massimiliano Materazzi

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Fluidized bed reactor technologies are one of the most valuable pathways for thermochemical conversions of biogenic fuels due to their good operating flexibility. Nevertheless, there are still issues related to the mixing and separation of heterogeneous phases during operation with highly volatile feedstocks, including biomass and waste. At high temperatures, the volatile content of the feedstock is released in the form of the so-called endogenous bubbles, which generally exert a “lift” effect on the particle itself by dragging it up to the bed surface. Such phenomenon leads to high release of volatile matter into the freeboard and limited mass and heat transfer with particles of the bed inventory. The aim of this work is to get a better understanding of the behaviour of a single reacting particle in a hot fluidized bed reactor during the devolatilization stage. The analysis has been undertaken at different fluidization regimes and temperatures to closely mirror the operating conditions of waste-to-energy processes. Beechwood and polypropylene particles were used to resemble the biomass and plastic fractions present in waste materials, respectively. The non-invasive X-ray technique was coupled to particle tracking algorithms to characterize the motion of a single feedstock particle during the devolatilization with high resolution. A high-energy X-ray beam passes through the vessel where absorption occurs, depending on the distribution and amount of solids and fluids along the beam path. A high-speed video camera is synchronised to the beam and provides frame-by-frame imaging of the flow patterns of fluids and solids within the fluidized bed up to 72 fps (frames per second). A comprehensive mathematical model has been developed in order to validate the experimental results. Beech wood and polypropylene particles have shown a very different dynamic behaviour during the pyrolysis stage. When the feedstock is fed from the bottom, the plastic material tends to spend more time within the bed than the biomass. This behaviour can be attributed to the presence of the endogenous bubbles, which drag effect is more pronounced during the devolatilization of biomass, resulting in a lower residence time of the particle within the bed. At the typical operating temperatures of thermochemical conversions, the synthetic polymer softens and melts, and the bed particles attach on its outer surface, generating a wet plastic-sand agglomerate. Consequently, this additional layer of sand may hinder the rapid evolution of volatiles in the form of endogenous bubbles, and therefore the establishment of a poor drag effect acting on the feedstock itself. Information about the mixing and segregation of solid feedstock is of prime importance for the design and development of more efficient industrial-scale operations.

Keywords: fluidized bed, pyrolysis, waste feedstock, X-ray

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Authors: Sourav Ray, Christoph Stein, Marcus Weber

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A new class of drug candidates, initially derived from mathematical modeling of ligand-receptor interactions, activate the μ-opioid receptor (MOR) preferentially at acidic extracellular pH-levels, as present in injured tissues. This is of commercial interest because it may preclude the adverse effects of conventional MOR agonists like fentanyl, which include but are not limited to addiction, constipation, sedation, and apnea. Animal studies indicate the importance of taking the pH value of the chemical environment of MOR into account when designing new drugs. Hydrogen bonds (HBs) play a crucial role in stabilizing protein secondary structure and molecular interaction, such as ligand-protein interaction. These bonds may depend on the pH value of the chemical environment. For the MOR, antagonist naloxone and agonist [D-Ala2,N-Me-Phe4,Gly5-ol]-enkephalin (DAMGO) form HBs with ionizable residue HIS 297 at physiological pH to modulate signaling. However, such interactions were markedly reduced at acidic pH. Although fentanyl-induced signaling is also diminished at acidic pH, HBs with HIS 297 residue are not observed at either acidic or physiological pH for this strong agonist of the MOR. Molecular dynamics (MD) simulations can provide greater insight into the interaction between the ligand of interest and the HIS 297 residue. Amino acid protonation states are adjusted to the model difference in system acidity. Unbiased and unrestrained MD simulations were performed, with the ligand in the proximity of the HIS 297 residue. Ligand-receptor complexes were embedded in 1-palmitoyl-2-oleoyl-sn glycero-3-phosphatidylcholine (POPC) bilayer to mimic the membrane environment. The occurrence of HBs between the different ligands and the HIS 297 residue of MOR at acidic and physiological pH values were tracked across the various simulation trajectories. No HB formation was observed between fentanyl and HIS 297 residue at either acidic or physiological pH. Naloxone formed some HBs with HIS 297 at pH 5, but no such HBs were noted at pH 7. Interestingly, DAMGO displayed an opposite yet more pronounced HB formation trend compared to naloxone. Whereas a marginal number of HBs could be observed at even pH 5, HBs with HIS 297 were more stable and widely present at pH 7. The HB formation plays no and marginal role in the interaction of fentanyl and naloxone, respectively, with the HIS 297 residue of MOR. However, HBs play a significant role in the DAMGO and HIS 297 interaction. Post DAMGO administration, these HBs might be crucial for the remediation of opioid tolerance and restoration of opioid sensitivity. Although experimental studies concur with our observations regarding the influence of HB formation on the fentanyl and DAMGO interaction with HIS 297, the same could not be conclusively stated for naloxone. Therefore, some other supplementary interactions might be responsible for the modulation of the MOR activity by naloxone binding at pH 7 but not at pH 5. Further elucidation of the mechanism of naloxone action on the MOR could assist in the formulation of cost-effective naloxone-based treatment of opioid overdose or opioid-induced side effects.

Keywords: effect of system acidity, hydrogen bond formation, opioid action, receptor activation

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Authors: Nico Fuchs, Fabian Wüllhorst, Laura Maier, Dirk Müller

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The decarbonization of building stocks necessitates the modernization of existing buildings. Key measures for this include reducing energy demands through insulation of the building envelope, replacing heat generators, and installing solar systems. Given limited financial resources, it is impractical to modernize all buildings in a portfolio simultaneously; instead, prioritization of buildings and modernization measures for a given planning horizon is essential. Optimization models for modernization pathways can assist portfolio managers in this prioritization. However, modeling and solving these large-scale optimization problems, often represented as mixed-integer problems (MIP), necessitates simplifying the operation of building energy systems particularly with respect to system dynamics and transient behavior. This raises the question of which level of simplification remains sufficient to accurately account for realistic costs and emissions of building energy systems, ensuring a fair comparison of different modernization measures. This study addresses this issue by comparing a two-stage simulation-based optimization approach with a single-stage mathematical optimization in a mixed-integer linear programming (MILP) formulation. The simulation-based approach serves as a benchmark for realistic energy system operation but requires a restriction of the solution space to discrete choices of modernization measures, such as the sizing of heating systems. After calculating the operation of different energy systems in terms of the resulting final energy demands in simulation models on a first stage, the results serve as input for a second stage MILP optimization, where the design of each building in the portfolio is optimized. In contrast to the simulation-based approach, the MILP-based approach can capture a broader variety of modernization measures due to the efficiency of MILP solvers but necessitates simplifying the building energy system operation. Both approaches are employed to determine the cost-optimal design and dimensioning of several buildings in a portfolio to meet climate targets within limited yearly budgets, resulting in a modernization pathway for the entire portfolio. The comparison reveals that the MILP formulation successfully captures design decisions of building energy systems, such as the selection of heating systems and the modernization of building envelopes. However, the results regarding the optimal dimensioning of heating technologies differ from the results of the two-stage simulation-based approach, as the MILP model tends to overestimate operational efficiency, highlighting the limitations of the MILP approach.

Keywords: building energy system optimization, model accuracy in optimization, modernization pathways, building stock decarbonization

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Authors: Shofiayuningtyas Luftiani

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Some private schools in Indonesia started integrating the online program Gizmos in the teaching-learning process. Gizmos was developed to supplement the existing curriculum by integrating it into the instructional programs. The program has some features using an inquiry-based simulation, in which students conduct exploration by using a worksheet while teachers use the teacher guidelines to direct and assess students’ performance In this study, the discussion about Gizmos highlights its features as the assessment media of mathematics learning for secondary school students. The discussion is based on the case study and literature review from the Indonesian context. The purpose of applying Gizmos as an assessment media refers to the diagnostic assessment. As a part of the diagnostic assessment, the teachers review the student exploration sheet, analyze particularly in the students’ difficulties and consider findings in planning future learning process. This assessment becomes important since the teacher needs the data about students’ persistent weaknesses. Additionally, this program also helps to build student’ understanding by its interactive simulation. Currently, the assessment over-emphasizes the students’ answers in the worksheet based on the provided answer keys while students perform their skill in translating the question, doing the simulation and answering the question. Whereas, the assessment should involve the multiple perspectives and sources of students’ performance since teacher should adjust the instructional programs with the complexity of students’ learning needs and styles. Consequently, the approach to improving the assessment components is selected to challenge the current assessment. The purpose of this challenge is to involve not only the cognitive diagnosis but also the analysis of skills and error. Concerning the selected setting for this diagnostic assessment that develops the combination of cognitive diagnosis, skills analysis and error analysis, the teachers should create an assessment rubric. The rubric plays the important role as the guide to provide a set of criteria for the assessment. Without the precise rubric, the teacher potentially ineffectively documents and follows up the data about students at risk of failure. Furthermore, the teachers who employ the program of Gizmos as the diagnostic assessment might encounter some obstacles. Based on the condition of assessment in the selected setting, the obstacles involve the time constrain, the reluctance of higher teaching burden and the students’ behavior. Consequently, the teacher who chooses the Gizmos with those approaches has to plan, implement and evaluate the assessment. The main point of this assessment is not in the result of students’ worksheet. However, the diagnostic assessment has the two-stage process; the process to prompt and effectively follow-up both individual weaknesses and those of the learning process. Ultimately, the discussion of Gizmos as the media of the diagnostic assessment refers to the effort to improve the mathematical learning process.

Keywords: diagnostic assessment, error analysis, Gizmos online program, skills analysis

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Authors: Morteza Sharifhasan, Davoud Hosseini, Mohammad. R. Salimpour

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The geothermal energy is considered as a worldwide important renewable energy in recent years due to rising environmental pollution concerns. Low- and medium-grade geothermal heat (< 200 ºC) is commonly employed for space heating and in domestic hot water supply. However, there is also much interest in converting the abundant low- and medium-grade geothermal heat into electrical power. The Iranian Ministry of Power - through the Iran Renewable Energy Organization (SUNA) – is going to build the first Geothermal Power Plant (GPP) in Iran in the Sabalan area in the Northwest of Iran. This project is a 5.5 MWe single flash steam condensing power plant. The efficiency of GPPs is low due to the relatively low pressure and temperature of the saturated steam. In addition to GPPs, Gas Turbines (GTs) are also known by their relatively low efficiency. The Iran ministry of Power is trying to increase the efficiency of these GTs by adding bottoming steam cycles to the GT to form what is known as combined gas/steam cycle. One of the most effective methods for increasing the efficiency is combined heat and power (CHP). This paper investigates the feasibility of superheating the saturated steam that enters the steam turbine of the Sabalan GPP (SGPP-1) to improve the energy efficiency and power output of the GPP. This purpose is achieved by combining the GPP with two 3.5 MWe GTs. In this method, the hot gases leaving GTs are utilized through a superheater similar to that used in the heat recovery steam generator of combined gas/steam cycle. Moreover, brine separated in the separator, hot gases leaving GTs and superheater are used for the supply of domestic hot water (in this paper, the cycle combined of GTs and CHP systems is named the modified SGPP-1) . In this research, based on the Heat Balance presented in the basic design documents of the SGPP-1, mathematical/numerical model of the power plant are developed together with the mentioned GTs and CHP systems. Based on the required hot water, the amount of hot gasses needed to pass through CHP section directly can be adjusted. For example, during summer when hot water is less required, the hot gases leaving both GTs pass through the superheater and CHP systems respectively. On the contrary, in order to supply the required hot water during the winter, the hot gases of one of the GTs enter the CHP section directly, without passing through the super heater section. The results show that there is an increase in thermal efficiency up to 40% through using the modified SGPP-1. Since the gross efficiency of SGPP-1 is 9.6%, the achieved increase in thermal efficiency is significant. The power output of SGPP-1 is increased up to 40% in summer (from 5.5MW to 7.7 MW) while the GTs power output remains almost unchanged. Meanwhile, the combined-cycle power output increases from the power output of the two separate plants of 12.5 MW [5.5+ (2×3.5)] to the combined-cycle power output of 14.7 [7.7+(2×3.5)]. This output is more than 17% above the output of the two separate plants. The modified SGPP-1 is capable of producing 215 T/Hr hot water ( 90 ºC ) for domestic use in the winter months.

Keywords: combined cycle, chp, efficiency, gas turbine, geothermal power plant, gas turbine, power output

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Authors: Ujjwall Sai Sunder Uppuluri

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Group theory is a powerful tool that researchers can use to provide a structural foundation for their Agent Based Models. These Agent Based models are argued by this paper to be the future of the Social Science Disciplines. More specifically, researchers can use them to apply evolutionary theory to the study of complex social systems. This paper illustrates one such example of how theoretically an Agent Based Model can be formulated from the application of Group Theory, Systems Dynamics, and Evolutionary Biology to analyze the strategies pursued by states to mitigate risk and maximize usage of resources to achieve the objective of economic growth. This example can be applied to other social phenomena and this makes group theory so useful to the analysis of complex systems, because the theory provides the mathematical formulaic proof for validating the complex system models that researchers build and this will be discussed by the paper. The aim of this research, is to also provide researchers with a framework that can be used to model political entities such as states on a 3-dimensional plane. The x-axis representing resources (tangible and intangible) available to them, y the risks, and z the objective. There also exist other states with different constraints pursuing different strategies to climb the mountain. This mountain’s environment is made up of risks the state faces and resource endowments. This mountain is also layered in the sense that it has multiple peaks that must be overcome to reach the tallest peak. A state that sticks to a single strategy or pursues a strategy that is not conducive to the climbing of that specific peak it has reached is not able to continue advancement. To overcome the obstacle in the state’s path, it must innovate. Based on the definition of a group, we can categorize each state as being its own group. Each state is a closed system, one which is made up of micro level agents who have their own vectors and pursue strategies (actions) to achieve some sub objectives. The state also has an identity, the inverse being anarchy and/or inaction. Finally, the agents making up a state interact with each other through competition and collaboration to mitigate risks and achieve sub objectives that fall within the primary objective. Thus, researchers can categorize the state as an organism that reflects the sum of the output of the interactions pursued by agents at the micro level. When states compete, they employ a strategy and that state which has the better strategy (reflected by the strategies pursued by her parts) is able to out-compete her counterpart to acquire some resource, mitigate some risk or fulfil some objective. This paper will attempt to illustrate how group theory combined with evolutionary theory and systems dynamics can allow researchers to model the long run development, evolution, and growth of political entities through the use of a bottom up approach.

Keywords: complex systems, evolutionary theory, group theory, international political economy

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Authors: Sherif Fakher

Abstract:

Hydrogen has been gaining a lot of global attention as an uprising contributor in the energy sector. Labeled as an energy carrier, hydrogen is used in many industries and can be used to generate electricity via fuel cells. Blue hydrogen involves the production of hydrogen from hydrocarbons using different processes that emit CO₂. However, the CO₂ is captured and stored. Hence, very little environmental damage occurs during the hydrogen production process. This research investigates the ability to use different catalysts for the production of hydrogen from different hydrocarbon sources, including coal, oil, and gas, using a two-step Aquathermolysis reaction. The research presents the results of experiments conducted to evaluate different catalysts and also highlights the main advantages of this process over other blue hydrogen production methods, including methane steam reforming, autothermal reforming, and oxidation. Two methods of hydrogen generation were investigated including partial oxidation and aquathermolysis. For those two reactions, the reaction kinetics, thermodynamics, and medium were all investigated. Following this, experiments were conducted to test the hydrogen generation potential from both methods. The porous media tested were sandstone, ash, and prozzolanic material. The spent oils used were spent motor oil and spent vegetable oil from cooking. Experiments were conducted at temperatures up to 250 C and pressures up to 3000 psi. Based on the experimental results, mathematical models were developed to predict the hydrogen generation potential at higher thermodynamic conditions. Since both partial oxidation and aquathermolysis require relatively high temperatures to undergo, it was important to devise a method by which these high temperatures can be generated at a low cost. This was done by investigating two factors, including the porous media used and the reliance on the spent oil. Of all the porous media used, the ash had the highest thermal conductivity. The second step was the partial combustion of part of the spent oil to generate the heat needed to reach the high temperatures. This reduced the cost of the heat generation significantly. For the partial oxidation reaction, the spent oil was burned in the presence of a limited oxygen concentration to generate carbon monoxide. The main drawback of this process was the need for burning. This resulted in the generation of other harmful and environmentally damaging gases. Aquathermolysis does not rely on burning, which makes it the cleaner alternative. However, it needs much higher temperatures to run the reaction. When comparing the hydrogen generation potential for both using gas chromatography, aquathermolysis generated 23% more hydrogen using the same volume of spent oil compared to partial oxidation. This research introduces the concept of using spent oil for hydrogen production. This can be a very promising method to produce a clean source of energy using a waste product. This can also help reduce the reliance on freshwater for hydrogen generation which can divert the usage of freshwater to other more important applications.

Keywords: blue hydrogen production, catalytic aquathermolysis, direct carbon dioxide capture, CCUS

Procedia PDF Downloads 31

Authors: Bartosz Piechowicz, Stanislaw Sadlo, Przemyslaw Grodzicki, Magdalena Podbielska

Abstract:

Apples are popular fruits. They are eaten freshly and/or after processing. For instance Golden Delicious is an apple variety commonly used in production of foods for babies and toddlers. It is no wonder that complex analyses of the pesticide residue levels in those fruits have been carried out since eighties, and continued for the next years up to now. The results obtained were presented, usually as a teamwork, at the scientific sessions organised by the (IOR) Institute of Plant Protection-National Research Institute in Poznań and published in Scientific Works of the Institute (now Progress in Plant Protection/ Postępy w Ochronie Roślin) or Journal of Plant Protection Research, and in many non-periodical publications. These reports included studies carried out by IOR Laboratories in Poznań, Sośnicowice, Rzeszów and Bialystok. First detailed studies on the presence of pesticide residues in apple fruits by the laboratory in Rzeszów were published in 1991 in the article entitled 'The presence of pesticides in apples of late varieties from the area of south-eastern Poland in the years 1986-1989', in Annals of National Institute of Hygiene in Warsaw. These surveys gave the scientific base for business contacts between the Polish company Alima and the American company Gerber. At the beginning of XXI century, in Poland, systematic and complex studies on the deposition of pesticide residues in apples were initiated. First of all, the levels of active ingredients of plant protection products applied against storage diseases at 2-3 weeks before the harvest were determined. It is known that the above mentioned substances usually generate the highest residue levels. Also, the assessment of the fungicide residues in apples during their storage in controlled atmosphere and during their processing was carried out. Taking into account the need of actualisation the Maximum Residue Levels of pesticides, in force in Poland and in other European countries, and rationalisation of the ways of their determination, a lot of field tests on the behaviour of more important fungicides on the mature fruits just before their harvesting, were carried out. A rate of their disappearance and mathematical equation that showed the relationship between the residue level of any substance and the used dose, have been determined. The two parameters have allowed to evaluate the Maximum Residue Levels (MRLs) of pesticides, which were in force at that time, and to propose a coherent model of their determination in respect to the new substances. The obtained results were assessed in terms of the health risk for adult consumers and children, and to such determination of terms of treatment that mature apples could meet the rigorous level of 0.01 mg/kg.

Keywords: apple, disappearance, health risk, MRL, pesticide residue, research

Procedia PDF Downloads 274

Authors: Osman Turkoglu, Alvin Estilo, Ritu Gupta, Liliam Pineda-Salgado, Rajesh Pandey

Abstract:

Background: Hepatotoxicity can be linked to a variety of clinical symptoms and histopathological signs, posing a great challenge in the surveillance of suspected drug-induced liver injury (DILI) cases in the safety database. Additionally, the majority of such cases are rare, idiosyncratic, highly unpredictable, and tend to demonstrate unique individual susceptibility; these qualities, in turn, lend to a pharmacovigilance monitoring process that is often tedious and time-consuming. Objective: Develop a multifactorial algorithm to assist pharmacovigilance physicians in identifying high-risk hepatotoxicity cases associated with DILI from the sponsor’s safety database (Argus). Methods: Multifactorial selection criteria were established using Structured Query Language (SQL) and the TIBCO Spotfire® visualization tool, via a combination of word fragments, wildcard strings, and mathematical constructs, based on Hy’s law criteria and pattern of injury (R-value). These criteria excluded non-eligible cases from monthly line listings mined from the Argus safety database. The capabilities and limitations of these criteria were verified by comparing a manual review of all monthly cases with system-generated monthly listings over six months. Results: On an average, over a period of six months, the algorithm accurately identified 92% of DILI cases meeting established criteria. The automated process easily compared liver enzyme elevations with baseline values, reducing the screening time to under 15 minutes as opposed to multiple hours exhausted using a cognitively laborious, manual process. Limitations of the algorithm include its inability to identify cases associated with non-standard laboratory tests, naming conventions, and/or incomplete/incorrectly entered laboratory values. Conclusions: The newly developed multifactorial algorithm proved to be extremely useful in detecting potential DILI cases, while heightening the vigilance of the drug safety department. Additionally, the application of this algorithm may be useful in identifying a potential signal for DILI in drugs not yet known to cause liver injury (e.g., drugs in the initial phases of development). This algorithm also carries the potential for universal application, due to its product-agnostic data and keyword mining features. Plans for the tool include improving it into a fully automated application, thereby completely eliminating a manual screening process.

Keywords: automation, drug-induced liver injury, pharmacovigilance, post-marketing

Procedia PDF Downloads 152