Search results for: dynamic uncertainty

Authors: E. Farshidi

Abstract:

This paper presents a new general technique for analysis of noise in static log-domain translinear circuits. It is demonstrated that employing this technique, leads to a general, simple and routine method of the noise analysis. The circuit has been simulated by HSPICE. The simulation results are seen to conform to the theoretical analysis and shows benefits of the proposed circuit.

Keywords: Noise analysis, log-domain, static, dynamic, translinear loop, companding.

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Authors: Xun Liang

Abstract:

In this paper, we probe into the traffic assignment problem by the chromosome-learning-based path finding method in simulation, which is to model the driver' behavior in the with-in-a-day process. By simply making a combination and a change of the traffic route chromosomes, the driver at the intersection chooses his next route. The various crossover and mutation rules are proposed with extensive examples.

Keywords: Chromosome learning, crossover, mutation, traffic path finding.

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Authors: G. Kumaravelan, R. Sivakumar

Abstract:

Modeling the behavior of the dialogue management in the design of a spoken dialogue system using statistical methodologies is currently a growing research area. This paper presents a work on developing an adaptive learning approach to optimize dialogue strategy. At the core of our system is a method formalizing dialogue management as a sequential decision making under uncertainty whose underlying probabilistic structure has a Markov Chain. Researchers have mostly focused on model-free algorithms for automating the design of dialogue management using machine learning techniques such as reinforcement learning. But in model-free algorithms there exist a dilemma in engaging the type of exploration versus exploitation. Hence we present a model-based online policy learning algorithm using interconnected learning automata for optimizing dialogue strategy. The proposed algorithm is capable of deriving an optimal policy that prescribes what action should be taken in various states of conversation so as to maximize the expected total reward to attain the goal and incorporates good exploration and exploitation in its updates to improve the naturalness of humancomputer interaction. We test the proposed approach using the most sophisticated evaluation framework PARADISE for accessing to the railway information system.

Keywords: Dialogue management, Learning automata, Reinforcement learning, Spoken dialogue system

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Authors: Angelo Lerro, Manuela Battipede, Piero Gili, Alberto Brandl

Abstract:

Redundancy requirements for UAV (Unmanned Aerial Vehicle) are hardly faced due to the generally restricted amount of available space and allowable weight for the aircraft systems, limiting their exploitation. Essential equipment as the Air Data, Attitude and Heading Reference Systems (ADAHRS) require several external probes to measure significant data as the Angle of Attack or the Sideslip Angle. Previous research focused on the analysis of a patented technology named Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) as an alternative method to obtain reliable and accurate estimates of the aerodynamic angles. This solution is based on an innovative sensor fusion algorithm implementing soft computing techniques and it allows to obtain a simplified inertial and air data system reducing external devices. In fact, only one external source of dynamic and static pressures is needed. This paper focuses on the benefits which would be gained by the implementation of this system in UAV applications. A simplification of the entire ADAHRS architecture will bring to reduce the overall cost together with improved safety performance. Smart-ADAHRS has currently reached Technology Readiness Level (TRL) 6. Real flight tests took place on ultralight aircraft equipped with a suitable Flight Test Instrumentation (FTI). The output of the algorithm using the flight test measurements demonstrates the capability for this fusion algorithm to embed in a single device multiple physical and virtual sensors. Any source of dynamic and static pressure can be integrated with this system gaining a significant improvement in terms of versatility.

Keywords: Neural network, aerodynamic angles, virtual sensor, unmanned aerial vehicle, air data system, flight test.

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Authors: Abdellatif Kasbi, Abderrafii Rahali

Abstract:

During the recent years, much interest has been devoted to fractional order control that has appeared as a very eligible control approach for the systems experiencing parametric uncertainty and outer disturbances. The main purpose of this paper is to design and evaluate the performance of a fractional order proportional integral (FOPI) controller applied to control prototype variable speed wind generation system (WGS) that uses a doubly fed induction generator (DFIG). In this paper, the DFIG-machine is controlled according to the stator field-oriented control (FOC) strategy, which makes it possible to regulate separately the reactive and active powers exchanged between the WGS and the grid. The considered system is modeled and simulated using MATLAB-Simulink, and the performance of FOPI controller applied to the back-to-back power converter control of DFIG based grid connected variable speed wind turbine are evaluated and compared to the ones obtained with a conventional PI controller.

Keywords: Design, fractional order PI controller, wind generation system, doubly fed induction generator, wind turbine, field-oriented control.

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Authors: Alok Madan, Arshad K. Hashmi

Abstract:

The paper presents a plastic analysis procedure based on the energy balance concept for performance based seismic retrofit of multi-story multi-bay masonry infilled reinforced concrete (R/C) frames with a ‘soft’ ground story using passive energy dissipation (PED) devices with the objective of achieving a target performance level of the retrofitted R/C frame for a given seismic hazard level at the building site. The proposed energy based plastic analysis procedure was employed for developing performance based design (PBD) formulations for PED devices for a simulated application in seismic retrofit of existing frame structures designed in compliance with the prevalent standard codes of practice. The PBD formulations developed for PED devices were implemented for simulated seismic retrofit of a representative code-compliant masonry infilled R/C frame with a ‘soft’ ground story using friction dampers as the PED device. Non-linear dynamic analyses of the retrofitted masonry infilled R/C frames is performed to investigate the efficacy and accuracy of the proposed energy based plastic analysis procedure in achieving the target performance level under design level earthquakes. Results of non-linear dynamic analyses demonstrate that the maximum inter-story drifts in the masonry infilled R/C frames with a ‘soft’ ground story that is retrofitted with the friction dampers designed using the proposed PBD formulations are controlled within the target drifts under near-field as well far-field earthquakes.

Keywords: Energy Methods, Masonry Infilled Frame, Near-field Earthquakes, Seismic Protection, Supplemental damping devices.

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Authors: Amal Jmaii, Damien Rousseliere, Besma Belhadj

Abstract:

We explore the relationship between internal migration and poverty in Tunisia. We present a methodology combining potential outcomes approach with multiple imputation to highlight the effect of internal migration on poverty states. We find that probability of being poor decreases when leaving the poorest regions (the west areas) to the richer regions (greater Tunis and the east regions).

Keywords: Internal migration, Bayesian approach, poverty dynamics, Tunisia.

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Authors: Y. C. Mao, G. S. Chen

Abstract:

Bicycle configuration is not as large as those of motorcycles or automobiles, while it indeed composes a complicated dynamic system. People-s requirements on comfortability, controllability and safety grow higher as the research and development technologies improve. The shock absorber affects the vehicle suspension performances enormously. The absorber takes the vibration energy and releases it at a suitable time, keeping the wheel under a proper contact condition with road surface, maintaining the vehicle chassis stability. Suspension design for mountain bicycles is more difficult than that of city bikes since it encounters dynamic variations on road and loading conditions. Riders need a stiff damper as they exert to tread on the pedals when climbing, while a soft damper when they descend downhill. Various switchable shock absorbers are proposed in markets, however riders have to manually switch them among soft, hard and lock positions. This study proposes a novel design of the bicycle shock absorber, which provides automatic smooth tuning of the damping coefficient, from a predetermined lower bound to theoretically unlimited. An automatic quick releasing valve is involved in this design so that it can release the peak pressure when the suspension fork runs into a square-wave type obstacle and prevent the chassis from damage, avoiding the rider skeleton from injury. This design achieves the automatic tuning process by innovative plunger valve and fluidic passage arrangements without any electronic devices. Theoretical modelling of the damper and spring are established in this study. Design parameters of the valves and fluidic passages are determined. Relations between design parameters and shock absorber performances are discussed in this paper. The analytical results give directions to the shock absorber manufacture.

Keywords: Modelling, Simulation, Bicycle, Shock Absorber, Damping, Releasing Valve

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Authors: Chin Wen Cheong

Abstract:

This study employs a bivariate asymmetric GARCH model to reveal the hidden dynamics price changes and volatility among the emerging markets of Thailand and Malaysian after the Asian financial crisis from January 2001 to December 2008. Our results indicated that the equity markets are sharing the common information (shock) that transmitted among each others. These empirical findings are used to demonstrate the importance of shock and volatility dynamic transmissions in the cross-market hedging and market risk.

Keywords: multivariate ARCH, structural change, value at risk.

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Authors: K. A. Weidenmann, M. Grigo, B. Brylka, P. Elsner, T. Böhlke

Abstract:

In order to reduce fuel consumption, the weight of automobiles has to be reduced. Fiber reinforced polymers offer the potential to reach this aim because of their high stiffness to weight ratio. Additionally, the use of fiber reinforced polymers in automotive applications has to allow for an economic large-scale production. In this regard, long fiber reinforced thermoplastics made by direct processing offer both mechanical performance and processability in injection moulding and compression moulding. The work presented in this contribution deals with long glass fiber reinforced polypropylene directly processed in compression moulding (D-LFT). For the use in automotive applications both the temperature and the time dependency of the materials properties have to be investigated to fulfill performance requirements during crash or the demands of service temperatures ranging from -40 °C to 80 °C. To consider both the influence of temperature and time, quasistatic tensile tests have been carried out at different temperatures. These tests have been complemented by high speed tensile tests at different strain rates. As expected, the increase in strain rate results in an increase of the elastic modulus which correlates to an increase of the stiffness with decreasing service temperature. The results are in good accordance with results determined by dynamic mechanical analysis within the range of 0.1 to 100 Hz. The experimental results from different testing methods were grouped and interpreted by using different time temperature shift approaches. In this regard, Williams-Landel-Ferry and Arrhenius approach based on kinetics have been used. As the theoretical shift factor follows an arctan function, an empirical approach was also taken into consideration. It could be shown that this approach describes best the time and temperature superposition for glass fiber reinforced polypropylene manufactured by D-LFT processing.

Keywords: Composite, long fiber reinforced thermoplastics, mechanical properties, dynamic mechanical analysis, time temperature superposition.

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Authors: R. Bendib, A. Khelassi

Abstract:

In this paper we will consider the most known ratios control schemes ((L/D, V/B),(L/D,V/F), Ryskamp-s, and (D/(L+D),V/B)) for binary distillation column and we compare them in the basis of interactions and disturbance propagation. The models for these configurations are deuced using mathematical transformations taking the energy balance structure (LV) as a base model. The dynamic relative magnitude criterion (DRMC) is used to assess the interactions. The results show that the introduction of ratios in controlling the column tends to minimize the degree of interactions between the loops.

Keywords: Distillation, interaction, DRMC, configurations.

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Authors: M. Khlifa, A. Youssef, A. F. Zaed, A. Kraft, V. Arrighi

Abstract:

A series of polystyrene (PS) nanoparticles were prepared by grafting polystyrene from both aggregated silica and colloidally dispersed silica nanoparticles using atom-transfer radical polymerisation (ATRP). Cross-linking and macroscopic gelation were minimised by using a miniemulsion system. The thermal and mechanical behaviour of the nanocomposites have been examined by differential scanning calorimetry (DSC) and dynamic mechanical thermal analysis (DMTA).

Keywords: ATRP, nanocomposites, polystyrene, reinforcement.

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Authors: C. Ardil

Abstract:

Fighter aircraft selection is one of the most critical strategies for defense multiple criteria decision-making analysis to increase the decisive power of air defense and its superior power in the defense strategy. Vague set theory is an adequate approach for modeling vagueness, uncertainty, and imprecision in decision-making problems. This study integrates vague set theory and the technique for order of preference by similarity to ideal solution (TOPSIS) to support fighter aircraft selection. The proposed method is applied in the selection of fighter aircraft for the Air Force. In the proposed approach, the ratings of alternatives and the importance weights of criteria for fighter aircraft selection are represented by the vague set theory. Finally, an illustrative example for fighter aircraft selection is given to demonstrate the applicability and effectiveness of the proposed approach. The fighter aircraft candidates were selected under six criteria including costability, payloadability, maneuverability, speedability, stealthility, and survivability. Analysis results show that the best fighter aircraft is selected with the highest closeness coefficient value. The proposed method can also be applied to solve other multiple criteria decision analysis problems. 

Keywords: fighter aircraft selection, vague set theory, fuzzy set theory, neutrosophic set theory, multiple criteria decision making analysis, MCDMA, TOPSIS

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Authors: Debabrata Das, Pankaj Dutta

Abstract:

Along with forward supply chain organization needs to consider the impact of reverse logistics due to its economic advantage, social awareness and strict legislations. In this paper, we develop a system dynamics framework for a closed-loop supply chain with fuzzy demand and fuzzy collection rate by incorporating product exchange policy in forward channel and various recovery options in reverse channel. The uncertainty issues associated with acquisition and collection of used product have been quantified using possibility measures. In the simulation study, we analyze order variation at both retailer and distributor level and compare bullwhip effects of different logistics participants over time between the traditional forward supply chain and the closed-loop supply chain. Our results suggest that the integration of reverse logistics can reduce order variation and bullwhip effect of a closed-loop system. Finally, sensitivity analysis is performed to examine the impact of various parameters on recovery process and bullwhip effect.

Keywords: Bullwhip Effect, Fuzzy Possibility Measures, Reverse Supply Chain, System Dynamics.

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Authors: Md. Sayeed Salam

Abstract:

This paper presents an efficient emission constrained economic dispatch algorithm that deals with nonlinear cost function and constraints. It is then incorporated into the dynamic programming based hydrothermal coordination program. The program has been tested on a practical utility system having 32 thermal and 12 hydro generating units. Test results show that a slight increase in production cost causes a substantial reduction in emission.

Keywords: Emission constraint, Hydrothermal coordination, and Economic dispatch algorithm.

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Authors: Abeer Amayri, Akif A. Bulgak

Abstract:

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: Dorota Kobus-Ostrowska

Abstract:

Work for everyone, especially for person with disability is a condition in independence; it secures basic needs and develops manual and intellectual capabilities. The work is a source of income, and it builds and strengthens of self-esteem and competence. The purpose of this article is to identify work as an important factor in everyone’s life, despite Polish disabled persons rarely having the chance to undertake a job. In order to achieve this purpose, two methods were used: comparative and qualitative. The theoretical part of this article is based on studies of a wide range of Polish and foreign literature devoted to the issue of the occupational development of people with disabilities. The article was also enriched with the institutional and legal analysis types of support for people with disabilities in Poland. Currently, a Polish person with disability who wants to enter or return to the labor market is under a special protection. Those entities employing workers with disabilities may obtain a subsidy for the salary of a person with disabilities. Unfortunately, people with disability in Poland rarely participate in the workforce. The factors that contribute to this include the difficulty in obtaining work, the uncertainty of keeping it, and the low salary offered. Despite that domestic and foreign literature highlight the important role of disabled people as a workforce, very few people with disability in Poland are economically active.

Keywords: Disabled person, work, employer, rehabilitation.

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Authors: E. Farshidi, N. Ahmadpoor

Abstract:

In this paper, a alternative structure method for continuous time sigma delta modulator is presented. In this modulator for implementation of integrators in loop filter second generation current conveyors are employed. The modulator is designed in CMOS technology and features low power consumption (<2.8mW), low supply voltage (±1.65), wide dynamic range (>65db), and with 180khZ bandwidth. Simulation results confirm that this design is suitable for data converters.

Keywords: Current Conveyor, continuous, sigma delta, MOS, modulator

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Authors: M.A. Hosseini, P. Ebrahimi Naghani

Abstract:

In this research work, a novel parallel manipulator with high positioning and orienting rate is introduced. This mechanism has two rotational and one translational degree of freedom. Kinematics and Jacobian analysis are investigated. Moreover, workspace analysis and optimization has been performed by using genetic algorithm toolbox in Matlab software. Because of decreasing moving elements, it is expected much more better dynamic performance with respect to other counterpart mechanisms with the same degrees of freedom. In addition, using couple of cylindrical and revolute joints increased mechanism ability to have more extended workspace.

Keywords: Kinematics, Workspace, 3-CRS/PU, Parallel robot

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Authors: HongIl Ju, JongWook Han

Abstract:

In this paper we describes the authentication for DHCP (Dynamic Host Configuration Protocol) message which provides the efficient key management and reduces the danger replay attack without an additional packet for a replay attack. And the authentication for DHCP message supports mutual authentication and provides both entity authentication and message authentication. We applied the authentication for DHCP message to the home network environments and tested through a home gateway.

Keywords: DHCP, authentication, key management, replayattack, home network.

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Authors: S. P. Sharma, Monica Rani

Abstract:

In conventional reliability assessment, the reliability data of system components are treated as crisp values. The collected data have some uncertainties due to errors by human beings/machines or any other sources. These uncertainty factors will limit the understanding of system component failure due to the reason of incomplete data. In these situations, we need to generalize classical methods to fuzzy environment for studying and analyzing the systems of interest. Fuzzy set theory has been proposed to handle such vagueness by generalizing the notion of membership in a set. Essentially, in a Fuzzy Set (FS) each element is associated with a point-value selected from the unit interval [0, 1], which is termed as the grade of membership in the set. A Vague Set (VS), as well as an Intuitionistic Fuzzy Set (IFS), is a further generalization of an FS. Instead of using point-based membership as in FS, interval-based membership is used in VS. The interval-based membership in VS is more expressive in capturing vagueness of data. In the present paper, vague set theory coupled with conventional Lambda-Tau method is presented for reliability analysis of repairable systems. The methodology uses Petri nets (PN) to model the system instead of fault tree because it allows efficient simultaneous generation of minimal cuts and path sets. The presented method is illustrated with the press unit of the paper mill.

Keywords: Lambda -Tau methodology, Petri nets, repairable system, vague fuzzy set.

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Authors: Xiaoqing Wang, Fang Youyuan, Zheng Yanxing, Gu Tianyang, Zong Jianjian, Tong Jinrong

Abstract:

Compared with traditional distributed environment, the net-centric environment brings on more demanding challenges for information sharing with the characteristics of ultra-large scale and strong distribution, dynamic, autonomy, heterogeneity, redundancy. This paper realizes an information sharing model and a series of core services, through which provides an open, flexible and scalable information sharing platform.

Keywords: Net-centric environment, Information sharing, Metadata registry and catalog, Cross-domain data access control.

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

Abstract:

Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Classification, Bayesian network; structure learning, K2 algorithm, expert knowledge, surface water analysis.

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Authors: Ishapathik Das

Abstract:

The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: Model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs.

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Authors: R. Aparna, B. B. Amberker

Abstract:

Providing authentication for the messages exchanged between group members in addition to confidentiality is an important issue in Secure Group communication. We develop a protocol for Secure Authentic Communication where we address authentication for the group communication scheme proposed by Blundo et al. which only provides confidentiality. Authentication scheme used is a multiparty authentication scheme which allows all the users in the system to send and receive messages simultaneously. Our scheme is secure against colluding malicious parties numbering fewer than k.

Keywords: Secure Group Communication, Secret key, Authentication, Authentication code, Threshold.

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

Abstract:

Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages Automatic Identification System (AIS) messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring AIS messages. Our RRo method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measures to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Frechet Distance (DFD), Dynamic Time ´ Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an f-measure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: Spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization.

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Authors: Babar S. Kawish, Baber Aslam, Shoab A Khan

Abstract:

In this paper we show that adjusting ART in accordance with static network scenario can substantially improve the performance of AODV by reducing control overheads. We explain the relationship of control overheads with network size and request patterns of the users. Through simulation we show that making ART proportionate to network static time reduces the amount of control overheads independent of network size and user request patterns.

Keywords: AODV, ART, MANET, Route Cache, TTL.

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Authors: Faezeh Mosallat, Eric L. Bibeau, Tarek El Mekkawy

Abstract:

Parabolic solar trough systems have seen limited deployments in cold northern climates as they are more suitable for electricity production in southern latitudes. A numerical dynamic model is developed to simulate troughs installed in cold climates and validated using a parabolic solar trough facility in Winnipeg. The model is developed in Simulink and will be utilized to simulate a trigeneration system for heating, cooling and electricity generation in remote northern communities. The main objective of this simulation is to obtain operational data of solar troughs in cold climates and use the model to determine ways to improve the economics and address cold weather issues. In this paper the validated Simulink model is applied to simulate a solar assisted absorption cooling system along with electricity generation using Organic Rankine Cycle (ORC) and thermal storage. A control strategy is employed to distribute the heated oil from solar collectors among the above three systems considering the temperature requirements. This modelling provides dynamic performance results using measured meteorological data recorded every minute at the solar facility location. The purpose of this modeling approach is to accurately predict system performance at each time step considering the solar radiation fluctuations due to passing clouds. Optimization of the controller in cold temperatures is another goal of the simulation to for example minimize heat losses in winter when energy demand is high and solar resources are low. The solar absorption cooling is modeled to use the generated heat from the solar trough system and provide cooling in summer for a greenhouse which is located next to the solar field. The results of the simulation are presented for a summer day in Winnipeg which includes comparison of performance parameters of the absorption cooling and ORC systems at different heat transfer fluid (HTF) temperatures.

Keywords: Absorption cooling, parabolic solar trough, remote community, organic Rankine cycle.

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

Abstract:

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: Enhanced ideal gas molecular movement, Kriging, probability-based damage detection, probability of damage existence, surrogate modeling, uncertainty quantification.

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Authors: Nieves M. C. Talavera-Prieto, Abel G. M. Ferreira, António T. G. Portugal, Rui J. Moreira, Jaime B. Santos

Abstract:

The knowledge of biodiesel density over large ranges of temperature and pressure is important for predicting the behavior of fuel injection and combustion systems in diesel engines, and for the optimization of such systems. In this study, cottonseed oil was transesterified into biodiesel and its density was measured at temperatures between 288 K and 358 K and pressures between 0.1 MPa and 30 MPa, with expanded uncertainty estimated as ±1.6 kg⋅m- 3. Experimental pressure-volume-temperature (pVT) cottonseed data was used along with literature data relative to other 18 biodiesels, in order to build a database used to test the correlation of density with temperarure and pressure using the Goharshadi–Morsali–Abbaspour equation of state (GMA EoS). To our knowledge, this is the first that density measurements are presented for cottonseed biodiesel under such high pressures, and the GMA EoS used to model biodiesel density. The new tested EoS allowed correlations within 0.2 kg·m-3 corresponding to average relative deviations within 0.02%. The built database was used to develop and test a new full predictive model derived from the observed linear relation between density and degree of unsaturation (DU), which depended from biodiesel FAMEs profile. The average density deviation of this method was only about 3 kg.m-3 within the temperature and pressure limits of application. These results represent appreciable improvements in the context of density prediction at high pressure when compared with other equations of state.

Keywords: Biodiesel, Correlation, Density, Equation of state, Prediction.

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