Search results for: counting with uncertainties

Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

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This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

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Authors: V. Ziegler, F. Schneider, M. Pesch

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With the EDM264, GRIMM offers a solution for mobile short- and long-term measurements in outdoor areas and at production sites. For research as well as permanent areal observations on a near reference quality base. The model EDM264 features a powerful and robust measuring cell based on optical particle counting (OPC) principle with all the advantages that users of GRIMM's portable aerosol spectrometers are used to. The system is embedded in a compact weather-protection housing with all-weather sampling, heated inlet system, data logger, and meteorological sensor. With TSP, PM10, PM4, PM2.5, PM1, and PMcoarse, the EDM264 provides all fine dust fractions real-time, valid for outdoor applications and calculated with the proven GRIMM enviro-algorithm, as well as six additional dust mass fractions pm10, pm2.5, pm1, inhalable, thoracic and respirable for IAQ and workplace measurements. This highly versatile instrument performs real-time monitoring of particle number, particle size and provides information on particle surface distribution as well as dust mass distribution. GRIMM's EDM264 has 31 equidistant size channels, which are PSL traceable. A high-end data logger enables data acquisition and wireless communication via LTE, WLAN, or wired via Ethernet. Backup copies of the measurement data are stored in the device directly. The rinsing air function, which protects the laser and detector in the optical cell, further increases the reliability and long term stability of the EDM264 under different environmental and climatic conditions. The entire sample volume flow of 1.2 L/min is analyzed by 100% in the optical cell, which assures excellent counting efficiency at low and high concentrations and complies with the ISO 21501-1standard for OPCs. With all these features, the EDM264 is a world-leading dust monitor for precise monitoring of particulate matter and particle number concentration. This highly reliable instrument is an indispensable tool for many users who need to measure aerosol levels and air quality outdoors, on construction sites, or at production facilities.

Keywords: aerosol research, aerial observation, fence line monitoring, wild fire detection

Procedia PDF Downloads 115

Authors: R. Vetrimurugan, Terry Lim, M. J. Goodson, R. Nagarajan

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This study investigates the cleaning performance of high intensity 360 kHz frequency on the removal of nano-dimensional and sub-micron particles from various surfaces, uniformity of the cleaning tank and run to run variation of cleaning process. The uniformity of the cleaning tank was measured by two different methods i.e 1. ppbTM meter and 2. Liquid Particle Counting (LPC) technique. In the second method, aluminium metal spacer components was placed at various locations of the cleaning tank (such as centre, top left corner, bottom left corner, top right corner, bottom right corner) and the resultant particles removed by 360 kHz frequency was measured. The result indicates that the energy was distributed more uniformly throughout the entire cleaning vessel even at the corners and edges of the tank when megasonic sweeping technology is applied. The result also shows that rinsing the parts with 360 kHz frequency at final rinse gives lower particle counts, hence higher cleaning efficiency as compared to other frequencies. When megasonic sweeping technology is applied each piezoelectric transducers will operate at their optimum resonant frequency and generates stronger acoustic cavitational force and higher acoustic streaming velocity. These combined forces are helping to enhance the particle removal and at the same time improve the overall cleaning performance. The multiple extractions study was also carried out for various frequencies to measure the cleaning potential and asymptote value.

Keywords: power distribution, megasonic sweeping, cavitation intensity, particle removal, laser particle counting, nano, submicron

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Authors: S. Visetpotjanakit, C. Khrautongkieo

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Radiation monitoring in the environment and foodstuffs is one of the main responsibilities of Office of Atoms for Peace (OAP) as the nuclear regulatory body of Thailand. The main goal of the OAP is to assure the safety of the Thai people and environment from any radiological incidents. Various radioanalytical methods have been developed to monitor radiation and radionuclides in the environmental and foodstuff samples. To validate our analytical performance, several proficiency test exercises from the International Atomic Energy Agency (IAEA) have been performed. Here, the results of a proficiency test exercise referred to as the Proficiency Test for Tritium, Cobalt, Strontium and Caesium Isotopes in Seawater 2017 (IAEA-RML-2017-01) are presented. All radionuclides excepting ³H were analysed using various radioanalytical methods, i.e. direct gamma-ray counting for determining ⁶⁰Co, ¹³⁴Cs and ¹³⁷Cs and developed radiochemical techniques for analysing ¹³⁴Cs, ¹³⁷Cs using AMP pre-concentration technique and 90Sr using di-(2-ethylhexyl) phosphoric acid (HDEHP) liquid extraction technique. The analysis results were submitted to IAEA. All results passed IAEA criteria, i.e. accuracy, precision and trueness and obtained ‘Accepted’ statuses. These confirm the data quality from the OAP environmental radiation laboratory to monitor radiation in the environment.

Keywords: international atomic energy agency, proficiency test, radiation monitoring, seawater

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Authors: Md. Shafiullah, Ali T. Al-Awami

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This project proposes optimal scheduling of imported power of a load aggregator with the utilization of EVs to maximize its profit. As with the increase of renewable energy resources, electricity price in competitive market becomes more uncertain and, on the other hand, with the penetration of renewable distributed generators in the distribution network the predicted load of a load aggregator also becomes uncertain in real time. Though there is uncertainties in both load and price, the use of EVs storage capacity can make the operation of load aggregator flexible. LA submits its offer to day-ahead market based on predicted loads and optimized use of its EVs to maximize its profit, as well as in real time operation it uses its energy storage capacity in such a way that it can maximize its profit. In this project, load aggregators profit maximization algorithm is formulated and the optimization problem is solved with the help of CVX. As in real time operation the forecasted loads differ from actual load, the mismatches are settled in real time balancing market. Simulation results compare the profit of a load aggregator with a hypothetical group of 1000 EVs and without EVs.

Keywords: CVX, electricity market, load aggregator, load and price uncertainties, profit maximization, real time balancing operation

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Authors: Jihoon Lim, Patrick Kirchen, Ryozo Nagamune

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This paper proposes a linear parameter-varying (LPV) controller capable of reducing nitrogen oxide (NOx) emissions with low ammonia (NH3) slip downstream of selective catalytic reduction (SCR) systems. SCR systems are widely adopted in diesel engines due to high NOx conversion efficiency. However, the nonlinearity of the SCR system and sensor uncertainty result in a challenging control problem. In order to overcome the control challenges, an LPV controller is proposed based on gain-scheduling parameters, that is, exhaust gas temperature and exhaust gas flow rate. Based on experimentally obtained data under the non-road transient driving cycle (NRTC), the simulations firstly show that the proposed controller yields high NOx conversion efficiency with a desired low NH3 slip. The performance of the proposed LPV controller is then compared with other controllers, including a gain-scheduling PID controller and a sliding mode controller. Additionally, the robustness is also demonstrated using the uncertainties ranging from 10 to 30%. The results show that the proposed controller is robustly stable under uncertainties.

Keywords: diesel engine, gain-scheduling control, linear parameter-varying, selective catalytic reduction

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Authors: Shield B. Lin, Ziraguen O. Williams

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In a task to assist NASA in analyzing the dynamic forces caused by operational countermeasures of an astronaut’s exercise platform impacting the spacecraft, an active proportional-integral-derivative controller commanding a linear actuator is proposed in a vibration isolation system to regulate the movement of the exercise platform. Computer simulation shows promising results that most exciter forces can be reduced or even eliminated. This paper emphasizes on parameter uncertainties, variations and exciter force variations. Drift and variations of system parameters in the vibration isolation system for astronaut’s exercise platform are analyzed. An active controlled scheme is applied with the goals to reduce the platform displacement and to minimize the force being transmitted to the spacecraft structure. The controller must be robust enough to accommodate the wide variations of system parameters and exciter forces. Computer simulation for the vibration isolation system was performed via MATLAB/Simulink and Trick. The simulation results demonstrate the achievement of force reduction with small platform displacement under wide ranges of variations in system parameters.

Keywords: control, counterweight, isolation, vibration

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Authors: Mehran Naghizaderokni, Asscar Janalizadechobbasty

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There are more probabilistic and deterministic liquefaction evaluation procedures in order to judge whether liquefaction will occur or not. A review of this approach reveals that there is a need for a comprehensive procedure that accounts for different sources of uncertainty in liquefaction evaluation. In fact, for the same set of input parameters, different methods provide different factors of safety and/or probabilities of liquefaction. To account for the different uncertainties, including both the model and measurement uncertainties, reliability analysis is necessary. This paper has obtained information from Standard Penetration Test (SPT) and some empirical approaches such as: Seed et al, Highway bridge of Japan approach to soil liquefaction, The Overseas Coastal Area Development Institute of Japan (OCDI) and reliability method to studying potential of liquefaction in soil of Babol city in the north of Iran are compared. Evaluation potential of liquefaction in soil of Babol city is an important issue since the soil of some area contains sand, seismic area, increasing level of underground waters and consequently saturation of soil; therefore, one of the most important goals of this paper is to gain suitable recognition of liquefaction potential and find the most appropriate procedure of evaluation liquefaction potential to decrease related damages.

Keywords: reliability analysis, liquefaction, Babol, civil, construction and geological engineering

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Authors: Erin Curtis, Avraham Schwiger

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Neuropsychological testing and evaluation is a crucial step in providing patients with effective diagnoses and treatment while in clinical care. The variety of batteries used in these evaluations can help clinicians better understand the nuanced declivities in a patient’s cognitive, behavioral, or emotional functioning, consequently equipping clinicians with the insights to make intentional choices about a patient’s care. Despite the knowledge these batteries can yield, some aspects of neuropsychological testing remain largely inaccessible to certain patient groups as a result of fundamental cultural, educational, or social differences. One such battery includes the Dot Counting Test (DCT), during which patients are required to count a series of dots on a page as rapidly and accurately as possible. As the battery progresses, the dots appear in clusters that are designed to be easily multiplied. This task evaluates a patient’s cognitive functioning, attention, and level of effort exerted on the evaluation as a whole. However, there is evidence to suggest that certain social groups, particularly Latinx groups, may perform worse on this task as a result of cultural or educational differences, not reduced cognitive functioning or effort. As such, this battery fails to account for baseline differences among patient groups, thus creating questions surrounding the accuracy, generalizability, and value of its results. Accessibility and cultural sensitivity are critical considerations in the testing and treatment of marginalized groups, yet have been largely ignored in the literature and in clinical settings to date. Implications and improvements to applications are discussed.

Keywords: culture, latino, neuropsychological assessment, neuropsychology, accessibility

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Authors: Abeer Amayri, Akif A. Bulgak

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Due to today’s globalization as well as outsourcing practices of the companies, the Supply Chain (SC) performances have become more dependent on the efficient movement of material among places that are geographically dispersed, where there is more chance for disruptions. One such disruption is the quality and delivery uncertainties of outsourcing. These uncertainties could lead the products to be unsafe and, as is the case in a number of recent examples, companies may have to end up in recalling their products. As a result of these problems, there is a need to develop a methodology for selecting suppliers globally in view of risks associated with low quality and late delivery. Accordingly, we developed a two-stage stochastic model that captures the risks associated with uncertainty in quality and delivery as well as a solution procedure for the model. The stochastic model developed simultaneously optimizes supplier selection and purchase quantities under price discounts over a time horizon. In particular, our target is the study of global organizations with multiple sites and multiple overseas suppliers, where the pricing is offered in suppliers’ local currencies. Our proposed methodology is applied to a case study for a US automotive company having two assembly plants and four potential global suppliers to illustrate how the proposed model works in practice.

Keywords: global supply chains, quality, stochastic programming, supplier selection

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Authors: Nabil Saad, David Morgan, Manish Gupta

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Visibility has become a key component of air quality and is regulated in many areas by environmental laws such as the EPA Clean Air Act and Regional Haze Rule. Typically, visibility is calculated by estimating the optical absorption and scattering of both gases and aerosols. A major component of the aerosols’ climatic effect is due to their scattering and absorption of solar radiation, which are governed by their optical and physical properties. However, the accurate assessment of this effect on global warming, climate change, and air quality is made difficult due to uncertainties in the calculation of single scattering albedo (SSA). Experimental complications arise in the determination of the single scattering albedo of an aerosol particle since it requires the simultaneous measurement of both scattering and extinction. In fact, aerosol optical absorption, in particular, is a difficult measurement to perform, and it’s often associated with large uncertainties when using filter methods or difference methods. In this presentation, we demonstrate the use of a new open-path Optical Extinction Analyzer (OEA) in conjunction with a nephelometer and two particle sizers, emphasizing the benefits that co-employment of the OEA offers to derive the complex refractive index of aerosols and their single scattering albedo parameter. Various use cases, data reproducibility, and instrument calibration will also be presented to highlight the value proposition of this novel Open-Path OEA.

Keywords: aerosols, extinction, visibility, albedo

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Authors: Morteza Aien, Masoud Rashidinejad, Mahmud Fotuhi-Firuzabad

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Power systems are innately uncertain systems. To face with such uncertain systems, robust uncertainty assessment tools are appealed. This paper inspects the uncertainty assessment formulation of the load flow (LF) problem considering different kinds of uncertainties, developed in its companion paper through some case studies. The proposed methodology is based on the evidence theory and joint propagation of possibilistic and probabilistic uncertainties. The load and wind power generation are considered as probabilistic uncertain variables and the electric vehicles (EVs) and gas turbine distributed generation (DG) units are considered as possibilistic uncertain variables. The cumulative distribution function (CDF) of the system output parameters obtained by the pure probabilistic method lies within the belief and plausibility functions obtained by the joint propagation approach. Furthermore, the imprecision in the DG parameters is explicitly reflected by the gap between the belief and plausibility functions. This gap, due to the epistemic uncertainty on the DG resources parameters grows as the penetration level increases.

Keywords: electric vehicles, joint possibilistic- probabilistic uncertainty modeling, uncertain load flow, wind turbine generator

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

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Surrogate model has received increasing attention for use in detecting damage of structures based on vibration modal parameters. However, uncertainties existing in the measured vibration data may lead to false or unreliable output result from such model. In this study, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The kriging technique allows one to genuinely quantify the surrogate error, therefore it is chosen as metamodeling technique. Enhanced version of ideal gas molecular movement (EIGMM) algorithm is used as main algorithm for model updating. The developed approach is applied to detect simulated damage in numerical models of 72-bar space truss and 120-bar dome truss. The simulation results show the proposed method can perform well in probability-based damage detection of structures with less computational effort compared to direct finite element model.

Keywords: probability-based damage detection (PBDD), Kriging, surrogate modeling, uncertainty quantification, artificial intelligence, enhanced ideal gas molecular movement (EIGMM)

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Authors: Okay Gunes

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In this article, for the first time in the literature for this subject we propose a new method for the measuring of well-being inequality through a model composed of superimposing satisfaction waves. The displacement of households’ satisfactory state (i.e. satisfaction) is defined in a satisfaction string. The duration of the satisfactory state for a given period of time is measured in order to determine the relationship between utility and total satisfactory time, itself dependent on the density and tension of each satisfaction string. Thus, individual cardinal total satisfaction values are computed by way of a one-dimensional form for scalar sinusoidal (harmonic) moving wave function, using satisfaction waves with varying amplitudes and frequencies which allow us to measure well-being inequality. One advantage to using satisfaction waves is the ability to show that individual utility and consumption amounts would probably not commute; hence it is impossible to measure or to know simultaneously the values of these observables from the dataset. Thus, we crystallize the problem by using a Heisenberg-type uncertainty resolution for self-adjoint economic operators. We propose to eliminate any estimation bias by correlating the standard deviations of selected economic operators; this is achieved by replacing the aforementioned observed uncertainties with households’ perceived uncertainties (i.e. corrected standard deviations) obtained through the logarithmic psychophysical law proposed by Weber and Fechner.

Keywords: Heisenberg uncertainty principle, superimposing satisfaction waves, Weber–Fechner law, well-being inequality

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Authors: Qudama Albu-Jasim, Majdi Kanaan

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A case study about the load rating and strengthening evaluation of the six-span of steel girders bridge in Colton city of State of California is investigated. To simulate the load rating strengthening assessment for the Colton Overhead bridge, a three-dimensional finite element model built in the CSiBridge program is simulated. Three-dimensional finite-element models of the bridge are established considering the nonlinear behavior of critical bridge components to determine the feasibility and strengthening capacity under load rating analysis. The bridge was evaluated according to Caltrans Bridge Load Rating Manual 1st edition for rating the superstructure using the Load and Resistance Factor Rating (LRFR) method. The analysis for the bridge was based on load rating to determine the largest loads that can be safely placed on existing I-girder steel members and permitted to pass over the bridge. Through extensive numerical simulations, the bridge is identified to be deficient in flexural and shear capacities, and therefore strengthening for reducing the risk is needed. An in-depth parametric study is considered to evaluate the sensitivity of the bridge’s load rating response to variations in its structural parameters. The parametric analysis has exhibited that uncertainties associated with the steel’s yield strength, the superstructure’s weight, and the diaphragm configurations should be considered during the fragility analysis of the bridge system.

Keywords: load rating, CSIBridge, strengthening, uncertainties, case study

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Authors: Minh-Phuong Ngoc Bui, Abdennour Abbas

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Microbial spoilage of food/drug has been a constant nuisance and an unavoidable problem throughout history that affects food/drug quality and safety in a variety of ways. A simple and rapid test of fungi and bacteria in food/drugs and environmental clinical samples is essential for proper management of contamination. A number of different techniques have been developed for detection and enumeration of foodborne microorganism including plate counting, enzyme-linked immunosorbent assay (ELISA), polymer chain reaction (PCR), nucleic acid sensor, electrical and microscopy methods. However, the significant drawbacks of these techniques are highly demand of operation skills and the time and cost involved. In this report, we introduce a rapid method for detection of bacteria and fungi in food/drug products using a specific interaction between a reducing agent (tris(2-carboxylethyl)phosphine (TCEP)) and the microbial surface proteins. The chemical reaction was transferred to a transduction system using gold nanoplates-enhanced chemiluminescence. We have optimized our nanoplates synthetic conditions, characterized the chemiluminescence parameters and optimized conditions for the microbial assay. The new detection method was applied for rapid detection of bacteria (E.coli sp. and Lactobacillus sp.) and fungi (Mucor sp.), with limit of detection as low as single digit cells per mL within 10 min using a portable luminometer. We expect our simple and rapid detection method to be a powerful alternative to the conventional plate counting and immunoassay methods for rapid screening of microorganisms in food/drug products.

Keywords: microorganism testing, gold nanoplates, chemiluminescence, reducing agents, luminol

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Authors: Alexandra Monteiro, K. Bousson, Fernando J. O. Moreira, Ricardo Reis

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Fixed-wing flying vehicles are usually controlled by means of control surfaces such as elevators, ailerons, and rudders. The failure of these systems may lead to severe or even fatal crashes. These failures resulted in increased popularity for research activities on propulsion control in the last decades. The present work deals with a hybrid control architecture in which the propulsion-controlled vehicle maintains its traditional control surfaces, addressing the issue of robust lateral-directional dynamics control. The challenges stem from the parameter uncertainties in the stability and control derivatives and some unknown terms in the flight dynamics model. Two approaches are implemented and tested: linear quadratic regulation with robustness characteristics and H∞ control. The problem is centered on roll-yaw controller design with full state-feedback, which is able to deal with a standalone propulsion control mode as well as a hybrid mode combining both propulsion control and conventional control surface concepts while maintaining the original flight maneuverability characteristics. The results for both controllers emphasized very good control performances; however, the H∞ controller showed higher stabilization rates and robustness albeit with a slightly higher control magnitude than using the linear quadratic regulator.

Keywords: robust propulsion control, h-infinity control, lateral-directional flight dynamics, parameter uncertainties

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Authors: Mohamed Noureldin, Jinkoo Kim

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The sensitivity of the seismic response parameters to the uncertain modeling variables of pile-founded fixed steel jacket platforms are investigated using tornado diagram, first-order second-moment, and static pushover analysis techniques. The effects of both aleatory and epistemic uncertainty on seismic response parameters have been investigated for an existing offshore platform. The sources of uncertainty considered in the present study are categorized into three different categories: the uncertainties associated with the soil-pile modeling parameters in clay soil, the platform jacket structure modeling parameters, and the uncertainties related to ground motion excitations. It has been found that the variability in parameters such as yield strength or pile bearing capacity has almost no effect on the seismic response parameters considered, whereas the global structural response is highly affected by the ground motion uncertainty. Also, some uncertainty in soil-pile property such as soil-pile friction capacity has a significant impact on the response parameters and should be carefully modeled. Based on the results, it is highlighted that which uncertain parameters should be considered carefully and which can be assumed with reasonable engineering judgment during the early structural design stage of fixed steel jacket platforms.

Keywords: fixed jacket offshore platform, pile-soil structure interaction, sensitivity analysis

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Authors: Sami W. Tabsh

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The strength of reinforced concrete depends on the member dimensions and material properties. The properties of concrete and steel materials are not constant but random variables. The variability of concrete strength is due to batching errors, variations in mixing, cement quality uncertainties, differences in the degree of compaction and disparity in curing. Similarly, the variability of steel strength is attributed to the manufacturing process, rolling conditions, characteristics of base material, uncertainties in chemical composition, and the microstructure-property relationships. To account for such uncertainties, codes of practice for reinforced concrete design impose resistance factors to ensure structural reliability over the useful life of the structure. In this investigation, the effects of reductions in concrete and reinforcing steel strengths from the nominal values, beyond those accounted for in the structural design codes, on the structural reliability are assessed. The considered limit states are flexure, shear and axial compression based on the ACI 318-11 structural concrete building code. Structural safety is measured in terms of a reliability index. Probabilistic resistance and load models are compiled from the available literature. The study showed that there is a wide variation in the reliability index for reinforced concrete members designed for flexure, shear or axial compression, especially when the live-to-dead load ratio is low. Furthermore, variations in concrete strength have minor effect on the reliability of beams in flexure, moderate effect on the reliability of beams in shear, and sever effect on the reliability of columns in axial compression. On the other hand, changes in steel yield strength have great effect on the reliability of beams in flexure, moderate effect on the reliability of beams in shear, and mild effect on the reliability of columns in axial compression. Based on the outcome, it can be concluded that the reliability of beams is sensitive to changes in the yield strength of the steel reinforcement, whereas the reliability of columns is sensitive to variations in the concrete strength. Since the embedded target reliability in structural design codes results in lower structural safety in beams than in columns, large reductions in material strengths compromise the structural safety of beams much more than they affect columns.

Keywords: code, flexure, limit states, random variables, reinforced concrete, reliability, reliability index, shear, structural safety

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Authors: Reza Alikhani

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This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.

Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience

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Authors: M. Gulam Kibria, Shourav Ahmed, Kais Zaman

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In system analysis, the information on the uncertain input variables cause uncertainty in the system responses. Different probabilistic approaches for uncertainty representation and propagation in such cases exist in the literature. Different uncertainty representation approaches result in different outputs. Some of the approaches might result in a better estimation of system response than the other approaches. The NASA Langley Multidisciplinary Uncertainty Quantification Challenge (MUQC) has posed challenges about uncertainty quantification. Subproblem A, the uncertainty characterization subproblem, of the challenge posed is addressed in this study. In this subproblem, the challenge is to gather knowledge about unknown model inputs which have inherent aleatory and epistemic uncertainties in them with responses (output) of the given computational model. We use two different methodologies to approach the problem. In the first methodology we use sampling-based uncertainty propagation with first order error analysis. In the other approach we place emphasis on the use of Percentile-Based Optimization (PBO). The NASA Langley MUQC’s subproblem A is developed in such a way that both aleatory and epistemic uncertainties need to be managed. The challenge problem classifies each uncertain parameter as belonging to one the following three types: (i) An aleatory uncertainty modeled as a random variable. It has a fixed functional form and known coefficients. This uncertainty cannot be reduced. (ii) An epistemic uncertainty modeled as a fixed but poorly known physical quantity that lies within a given interval. This uncertainty is reducible. (iii) A parameter might be aleatory but sufficient data might not be available to adequately model it as a single random variable. For example, the parameters of a normal variable, e.g., the mean and standard deviation, might not be precisely known but could be assumed to lie within some intervals. It results in a distributional p-box having the physical parameter with an aleatory uncertainty, but the parameters prescribing its mathematical model are subjected to epistemic uncertainties. Each of the parameters of the random variable is an unknown element of a known interval. This uncertainty is reducible. From the study, it is observed that due to practical limitations or computational expense, the sampling is not exhaustive in sampling-based methodology. That is why the sampling-based methodology has high probability of underestimating the output bounds. Therefore, an optimization-based strategy to convert uncertainty described by interval data into a probabilistic framework is necessary. This is achieved in this study by using PBO.

Keywords: aleatory uncertainty, epistemic uncertainty, first order error analysis, uncertainty quantification, percentile-based optimization

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Authors: Mitra Saberi, Saeideh Fakhari, Amir Karam, Ali Ahmadabadi

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Geomorphology is the scientific study of the characteristics of form and shape of the Earth's surface. The existence of types of landforms and their variation is mainly controlled by changes in the shape and position of land and topography. In fact, the interest and application of fractal issues in geomorphology is due to the fact that many geomorphic landforms have fractal structures and their formation and transformation can be explained by mathematical relations. The purpose of this study is to identify and analyze the fractal behavior of landforms of macro geomorphologic regions of Iran, as well as studying and analyzing topographic and landform characteristics based on fractal relationships. In this study, using the Iranian digital elevation model in the form of slopes, coefficients of deposition and alluvial fan, the fractal dimensions of the curves were calculated through the box counting method. The morphometric characteristics of the landforms and their fractal dimension were then calculated for 4criteria (height, slope, profile curvature and planimetric curvature) and indices (maximum, Average, standard deviation) using ArcMap software separately. After investigating their correlation with fractal dimension, two-way regression analysis was performed and the relationship between fractal dimension and morphometric characteristics of landforms was investigated. The results show that the fractal dimension in different pixels size of 30, 90 and 200m, topographic curves of different landform units of Iran including mountain, hill, plateau, plain of Iran, from1.06in alluvial fans to1.17in The mountains are different. Generally, for all pixels of different sizes, the fractal dimension is reduced from mountain to plain. The fractal dimension with the slope criterion and the standard deviation index has the highest correlation coefficient, with the curvature of the profile and the mean index has the lowest correlation coefficient, and as the pixels become larger, the correlation coefficient between the indices and the fractal dimension decreases.

Keywords: box counting method, fractal dimension, geomorphology, Iran, landform

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Authors: Young Yoon, Jinsoo Kim

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The adoption of information and communication technologies (ICT) in all industry is growing under industry 4.0. Many oil companies also are increasingly adopting ICT to improve the efficiency of existing operations, take more accurate and quicker decision making and reduce entire cost by optimization. It is true that ICT is playing an important role in the process of unconventional oil and gas development and companies must take advantage of ICT to gain competitive advantage. In this study, real option approach has been applied to Unconventional gas R&D project to evaluate ICT of them. Many unconventional gas reserves such as shale gas and coal-bed methane(CBM) has developed due to technological improvement and high energy price. There are many uncertainties in unconventional development on the three stage(Exploration, Development, Production). The traditional quantitative benefits-cost method, such as net present value(NPV) is not sufficient for capturing ICT value. We attempted to evaluate the ICT valuation by applying the compound option model; the model is applied to real CBM project case, showing how it consider uncertainties. Variables are treated as uncertain and a Monte Carlo simulation is performed to consider variables effect. Acknowledgement—This work was supported by the Energy Efficiency & Resources Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20152510101880) and by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-205S1A3A2046684).

Keywords: information and communication technologies, R&D, real option, unconventional gas

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Authors: Jose Manuel Rodriguez-Dominguez, Rodrigo Barba-Gonzalez, Ernesto Tapia-Campos

Abstract:

Sprekelia formosissima (L.) Herbert is a bulbous ornamental species of the monocotyledonous Amaryllidaceae family, and it is a perennial, herbaceous monotypic plant commonly known as ‘Aztec Lily’ or ‘Jacobean Lily’; it is distributed through Mexico and Guatemala. Its scarlet flowers with curved petals have made it an exceptional ornamental pot plant. Cytogenetic studies in this species have shown differences in chromosome number (2n=60, 120, 150, 180) with a basic number x=30. Different reports have shown a variable ploidy level (diploid, tetraploid, pentaploid and hexaploid); however, triploid plants have not been reported. In this work, triploid plants of S. formosissima were obtained by crossing tetraploid (2n=4x=120) with diploid (2n=2x=60) genotypes of this species; the seeds obtained from the crosses were placed in pots with a moist substrate made of Peat Moss: Vermiculite (7:3) for germination. Root tips were collected, and metaphasic chromosome preparations were performed. For chromosome counting, the best five metaphases obtained were photographed with a Leica DMRA2 microscope (Leica Microsystems, Germany) microscopy coupled to an Evolution QEI camera under phase contrast (Media-Cybernetics). Chromosomes counting in root-tip cells showed that 100% of the plants were triploid (2n=3x=90). Although tetraploid or pentaploid plants of S. formosissima are highly appreciated, they usually have lower growth rates than related diploid ones. For this reason, it is important to obtain triploid plants, which have advantages such as higher growth rates than tetraploid and pentaploid, larger flowers than those of the diploid plants and they are expected to not be able to produce seeds because their gametes are aneuploids. Furthermore, triploids may become very important for genomic research in the future, creating opportunities for discovering and monitoring genomic and transcriptomic changes in unbalanced genomes, hence the importance of this work.

Keywords: Amaryllidaceae, cytogenetics, ornamental, ploidy level

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Authors: Hoda Manafian, Stephen Holland

Abstract:

Silver Springs are one of Florida's first tourist attractions. They are one of the largest artesian spring formations in the world, producing nearly 550 million gallons of crystal-clear water daily that is one of the most popular sites for water-based leisure activities. As part of managing the use of a state park, the state is interested in establishing a baseline count of number of boating users to compare this to the quality of the natural resources and environment in the park. Understanding the status of the environmental resources and also the human recreational experience is the main objective of the project. Two main goals of current study are 1) to identify the distribution of different types of watercrafts (kayak, canoe, motor boat, Jet Ski, paddleboard and pontoon). 2) To document the level of real crowdedness in the river during different seasons, months, and hours of each day based on the reliable information gained from camera versus self-reported method by tourists themselves in the past studies (the innovative achievement of this study). In line with these objectives, on-site surveys and also boat counting using a time-lapse camera at the Riverside launch was done during 12 months of 2015. 700 on-site surveys were conducted at three watercraft boat ramp sites (Rays Wayside, Riverside launch area, Ft. King Waterway) of recreational users. We used Virtualdub and ImageJ software for counting boats for meeting the first and second goals, since this two software can report even the hour of presence of watercraft in the water in addition to the number of users and the type of watercraft. The most crowded hours were between 9-11AM from February to May and kayak was the most popular watercraft. The findings of this research can make a good foundation for better management in this state park in future.

Keywords: eco-tourism, Florida state, visitors' perception, water-based recreation

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Authors: Saad M. Darwish, Magda M. Madbouly, Murad B. Khorsheed

Abstract:

Sign Languages (SL) are the most accomplished forms of gestural communication. Therefore, their automatic analysis is a real challenge, which is interestingly implied to their lexical and syntactic organization levels. Hidden Markov models (HMM’s) have been used prominently and successfully in speech recognition and, more recently, in handwriting recognition. Consequently, they seem ideal for visual recognition of complex, structured hand gestures such as are found in sign language. In this paper, several results concerning static hand gesture recognition using an algorithm based on Type-2 Fuzzy HMM (T2FHMM) are presented. The features used as observables in the training as well as in the recognition phases are based on Singular Value Decomposition (SVD). SVD is an extension of Eigen decomposition to suit non-square matrices to reduce multi attribute hand gesture data to feature vectors. SVD optimally exposes the geometric structure of a matrix. In our approach, we replace the basic HMM arithmetic operators by some adequate Type-2 fuzzy operators that permits us to relax the additive constraint of probability measures. Therefore, T2FHMMs are able to handle both random and fuzzy uncertainties existing universally in the sequential data. Experimental results show that T2FHMMs can effectively handle noise and dialect uncertainties in hand signals besides a better classification performance than the classical HMMs. The recognition rate of the proposed system is 100% for uniform hand images and 86.21% for cluttered hand images.

Keywords: hand gesture recognition, hand detection, type-2 fuzzy logic, hidden Markov Model

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Authors: Johannes Gantner, Michael Held, Matthias Fischer

Abstract:

The refurbishment of the building stock in terms of energy supply and efficiency is one of the major challenges of the German turnaround in energy policy. As the building sector accounts for 40% of Germany’s total energy demand, additional insulation is key for energy efficient refurbished buildings. Nevertheless the energetic benefits often the environmental and economic performances of insulation materials are questioned. The methods Life Cycle Assessment (LCA) as well as Life Cycle Costing (LCC) can form the standardized basis for answering this doubts and more and more become important for material producers due efforts such as Product Environmental Footprint (PEF) or Environmental Product Declarations (EPD). Due to increasing use of LCA and LCC information for decision support the robustness and resilience of the results become crucial especially for support of decision and policy makers. LCA and LCC results are based on respective models which depend on technical parameters like efficiencies, material and energy demand, product output, etc.. Nevertheless, the influence of parameter uncertainties on lifecycle results are usually not considered or just studied superficially. Anyhow the effect of parameter uncertainties cannot be neglected. Based on the example of an exterior wall the overall lifecycle results are varying by a magnitude of more than three. As a result simple best case worst case analyses used in practice are not sufficient. These analyses allow for a first rude view on the results but are not taking effects into account such as error propagation. Thereby LCA practitioners cannot provide further guidance for decision makers. Probabilistic analyses enable LCA practitioners to gain deeper understanding of the LCA and LCC results and provide a better decision support. Within this study, the environmental and economic impacts of an exterior wall system over its whole lifecycle are illustrated, and the effect of different uncertainty analysis on the interpretation in terms of resilience and robustness are shown. Hereby the approaches of error propagation and Monte Carlo Simulations are applied and combined with statistical methods in order to allow for a deeper understanding and interpretation. All in all this study emphasis the need for a deeper and more detailed probabilistic evaluation based on statistical methods. Just by this, misleading interpretations can be avoided, and the results can be used for resilient and robust decisions.

Keywords: uncertainty, life cycle assessment, life cycle costing, Monte Carlo simulation

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Authors: Anthony Credoz, Nathalie Nief, Remy Hedacq, Salvador Jordana, Laurent Cazes

Abstract:

Groundwater monitoring is classically performed in a network of piezometers in industrial sites. Groundwater flow parameters, such as direction, sense and velocity, are deduced from indirect measurements between two or more piezometers. Groundwater sampling is generally done on the whole column of water inside each borehole to provide concentration values for each piezometer location. These flow and concentration values give a global ‘static’ image of potential plume of contaminants evolution in the shallow aquifer with huge uncertainties in time and space scales and mass discharge dynamic. TOTAL R&D Subsurface Environmental team is challenging this classical approach with an innovative dynamic way of characterization of shallow aquifer groundwater. The current study aims at optimizing the tools and methodologies for (i) a direct and multilevel measurement of groundwater velocities in each piezometer and, (ii) a calculation of potential flux of dissolved contaminant in the shallow aquifer. Lab-scale experiments have been designed to test commercial and R&D tools in a controlled sandbox. Multiphysics modeling were performed and took into account Darcy equation in porous media and Navier-Stockes equation in the borehole. The first step of the current study focused on groundwater flow at porous media/piezometer interface. Huge uncertainties from direct flow rate measurements in the borehole versus Darcy flow rate in the porous media were characterized during experiments and modeling. The structure and location of the tools in the borehole also impacted the results and uncertainties of velocity measurement. In parallel, direct-push tool was tested and presented more accurate results. The second step of the study focused on mass flux of dissolved contaminant in groundwater. Several active and passive commercial and R&D tools have been tested in sandbox and reactive transport modeling has been performed to validate the experiments at the lab-scale. Some tools will be selected and deployed in field assays to better assess the mass discharge of dissolved contaminants in an industrial site. The long-term subsurface environmental strategy is targeting an in-situ, real-time, remote and cost-effective monitoring of groundwater.

Keywords: dynamic characterization, groundwater flow, lab-scale, mass flux

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Authors: Piyush V. Surjagade, Jiamei Deng, Paul Doney, S. R. Shimjith, A. John Arul

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In sophisticated and complex systems such as nuclear power plants, maintaining the system's stability in the presence of uncertainties and disturbances and obtaining a fast dynamic response are the most challenging problems. Thus, to ensure the satisfactory and safe operation of nuclear power plants, this work proposes a new fast, robust optimal switching control strategy for pressurized water reactor-type nuclear power plants. The proposed control strategy guarantees a substantial degree of robustness, fast dynamic response over the entire operational envelope, and optimal performance during the nominal operation of the plant. To improve the robustness, obtain a fast dynamic response, and make the system optimal, a bank of controllers is designed. Various controllers, like a baseline proportional-integral-derivative controller, an optimal linear quadratic Gaussian controller, and a robust adaptive L1 controller, are designed to perform distinct tasks in a specific situation. At any instant of time, the most suitable controller from the bank of controllers is selected using the switching logic unit that designates the controller by monitoring the health of the nuclear power plant or transients. The proposed switching control strategy optimizes the overall performance and increases operational safety and efficiency. Simulation studies have been performed considering various uncertainties and disturbances that demonstrate the applicability and effectiveness of the proposed switching control strategy over some conventional control techniques.

Keywords: switching control, robust control, optimal control, nuclear power control

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Authors: Thiwanka Weerakkody, Lakmali Handagiripathira, Poshitha Dabare, Thisari Guruge

Abstract:

The determination of gross alpha and beta activity in water is important in a wide array of environmental studies and these parameters are considered in international legislations on the quality of water. This technique is commonly applied as screening method in radioecology, environmental monitoring, industrial applications, etc. Measuring of Gross Alpha and Beta emitters by using iSolo alpha beta counting system is an adequate nuclear technique to assess radioactivity levels in natural and waste water samples due to its simplicity and low cost compared with the other methods. Twelve water samples (Six samples of commercially available bottled drinking water and six samples of industrial waste water) were measured by standard method EPA 900.0 consisting of the gas-less, firm wear based, single sample, manual iSolo alpha beta counter (Model: SOLO300G) with solid state silicon PIPS detector. Am-241 and Sr90/ Y90 calibration standards were used to calibrate the detector. The minimum detectable activities are 2.32mBq/L and 406mBq/L, for alpha and beta activity, respectively. Each of the 2L water samples was evaporated (at low heat) to a small volume and transferred into 50mm stainless steel counting planchet evenly (for homogenization) and heated by IR lamp and the constant weighted residue was obtained. Then the samples were counted for gross alpha and beta. Sample density on the planchet area was maintained below 5mg/cm. Large quantities of solid wastes sludges and waste water are generated every year due to various industries. This water can be reused for different applications. Therefore implementation of water treatment plants and measuring water quality parameters in industrial waste water discharge is very important before releasing them into the environment. This waste may contain different types of pollutants, including radioactive substances. All these measured waste water samples having gross alpha and beta activities, lower than the maximum tolerance limits for industrial waste water discharge of industrial waste in to inland surface water, that is 10-9µCi/mL and 10-8µCi/mL for gross alpha and beta respectively (National Environmental Act, No. 47 of 1980). This is according to extraordinary gazette of the democratic socialist republic of Sri Lanka in February 2008. The measured water samples were below the recommended radioactivity levels and do not pose any radiological hazard when releasing the environment. Drinking water is an essential requirement of life. All the drinking water samples were below the permissible levels of 0.5Bq/L for gross alpha activity and 1Bq/L for gross beta activity. The values have been proposed by World Health Organization in 2011; therefore the water is acceptable for consumption of humans without any further clarification with respect to their radioactivity. As these screening levels are very low, the individual dose criterion (IDC) would usually not be exceeded (0.1mSv y⁻¹). IDC is a criterion for evaluating health risks from long term exposure to radionuclides in drinking water. Recommended level of 0.1mSv/y expressed a very low level of health risk. This monitoring work will be continued further for environmental protection purposes.

Keywords: drinking water, gross alpha, gross beta, waste water

Procedia PDF Downloads 155