Search results for: Computational modelling and simulation

Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

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Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: Optimal control, ensemble Kalman Filter, topography reconstruction, data assimilation, shallow water equations.

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Authors: A. Shaygani, R. Saifi, M. S. Saidi, M. Sani

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Particle size distribution, the most important characteristics of aerosols, is obtained through electrical characterization techniques. The dynamics of charged nanoparticles under the influence of electric field in Electrical Mobility Spectrometer (EMS) reveals the size distribution of these particles. The accuracy of this measurement is influenced by flow conditions, geometry, electric field and particle charging process, therefore by the transfer function (transfer matrix) of the instrument. In this work, a wire-cylinder corona charger was designed and the combined fielddiffusion charging process of injected poly-disperse aerosol particles was numerically simulated as a prerequisite for the study of a multichannel EMS. The result, a cloud of particles with no uniform charge distribution, was introduced to the EMS. The flow pattern and electric field in the EMS were simulated using Computational Fluid Dynamics (CFD) to obtain particle trajectories in the device and therefore to calculate the reported signal by each electrometer. According to the output signals (resulted from bombardment of particles and transferring their charges as currents), we proposed a modification to the size of detecting rings (which are connected to electrometers) in order to evaluate particle size distributions more accurately. Based on the capability of the system to transfer information contents about size distribution of the injected particles, we proposed a benchmark for the assessment of optimality of the design. This method applies the concept of Von Neumann entropy and borrows the definition of entropy from information theory (Shannon entropy) to measure optimality. Entropy, according to the Shannon entropy, is the ''average amount of information contained in an event, sample or character extracted from a data stream''. Evaluating the responses (signals) which were obtained via various configurations of detecting rings, the best configuration which gave the best predictions about the size distributions of injected particles, was the modified configuration. It was also the one that had the maximum amount of entropy. A reasonable consistency was also observed between the accuracy of the predictions and the entropy content of each configuration. In this method, entropy is extracted from the transfer matrix of the instrument for each configuration. Ultimately, various clouds of particles were introduced to the simulations and predicted size distributions were compared to the exact size distributions.

Keywords: Aerosol Nano-Particle, CFD, Electrical Mobility Spectrometer, Von Neumann entropy.

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Authors: Marcel Schneider, Nils Nießen

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Microscopic simulation tool kits allow for consideration of the two processes of railway operations and the previous timetable production. Block occupation conflicts on both process levels are often solved by using defined train priorities. These conflict resolutions (dispatching decisions) generate reactionary delays to the involved trains. The sum of reactionary delays is commonly used to evaluate the quality of railway operations, which describes the timetable robustness. It is either compared to an acceptable train performance or the delays are appraised economically by linear monetary functions. It is impossible to adequately evaluate dispatching decisions without a well-founded objective function. This paper presents a new approach for the evaluation of dispatching decisions. The approach uses mode choice models and considers the behaviour of the end-customers. These models evaluate the reactionary delays in more detail and consider other competing modes of transport. The new approach pursues the coupling of a microscopic model of railway operations with the macroscopic choice mode model. At first, it will be implemented for railway operations process but it can also be used for timetable production. The evaluation considers the possibility for the customer to interchange to other transport modes. The new approach starts to look at rail and road, but it can also be extended to air travel. The result of mode choice models is the modal split. The reactions by the end-customers have an impact on the revenue of the train operating companies. Different purposes of travel have different payment reserves and tolerances towards late running. Aside from changes to revenues, longer journey times can also generate additional costs. The costs are either time- or track-specific and arise from required changes to rolling stock or train crew cycles. Only the variable values are summarised in the contribution margin, which is the base for the monetary evaluation of delays. The contribution margin is calculated for different possible solutions to the same conflict. The conflict resolution is optimised until the monetary loss becomes minimal. The iterative process therefore determines an optimum conflict resolution by monitoring the change to the contribution margin. Furthermore, a monetary value of each dispatching decision can also be derived.

Keywords: Choice of mode, monetary evaluation, railway operations, reactionary delays.

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Authors: Josef Novák, Alena Kohoutková

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The performance of concrete structures in fire depends on several factors which include, among others, the change in material properties due to the fire. Today, fiber reinforced concrete (FRC) belongs to materials which have been widely used for various structures and elements. While the knowledge and experience with FRC behavior under ambient temperature is well-known, the effect of elevated temperature on its behavior has to be deeply investigated. This paper deals with an experimental investigation and stress‑strain relations for hybrid fiber reinforced concrete (HFRC) which contains siliceous aggregates, polypropylene and steel fibers. The main objective of the experimental investigation is to enhance a database of mechanical properties of concrete composites with addition of fibers subject to elevated temperature as well as to validate existing stress-strain relations for HFRC. Within the investigation, a unique heat transport test, compressive test and splitting tensile test were performed on 150 mm cubes heated up to 200, 400, and 600 °C with the aim to determine a time period for uniform heat distribution in test specimens and the mechanical properties of the investigated concrete composite, respectively. Both findings obtained from the presented experimental test as well as experimental data collected from scientific papers so far served for validating the computational accuracy of investigated stress-strain relations for HFRC which have been developed during last few years. Owing to the presence of steel and polypropylene fibers, HFRC becomes a unique material whose structural performance differs from conventional plain concrete when exposed to elevated temperature. Polypropylene fibers in HFRC lower the risk of concrete spalling as the fibers burn out shortly with increasing temperature due to low ignition point and as a consequence pore pressure decreases. On the contrary, the increase in the concrete porosity might affect the mechanical properties of the material. To validate this thought requires enhancing the existing result database which is very limited and does not contain enough data. As a result of the poor database, only few stress-strain relations have been developed so far to describe the structural performance of HFRC at elevated temperature. Moreover, many of them are inconsistent and need to be refined. Most of them also do not take into account the effect of both a fiber type and fiber content. Such approach might be vague especially when high amount of polypropylene fibers are used. Therefore, the existing relations should be validated in detail based on other experimental results.

Keywords: Elevated temperature, fiber reinforced concrete, mechanical properties, stress strain relation.

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Authors: Cheima Ben Soltane, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: Feature Extraction, Speaker Modeling, Feature Matching, Mel Frequency Cepstrum Coefficient (MFCC), Gaussian mixture model (GMM), Vector Quantization (VQ), Linde-Buzo-Gray (LBG), Expectation Maximization (EM), pre-processing, Voice Activity Detection (VAD), Short Time Energy (STE), Background Noise Statistical Modeling, Closed-Set Tex-Independent Speaker Identification System (CISI).

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Authors: Nishant Shrivastava, D. K. Sehgal

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

Keywords: Finite element, Lagrangian, optimal stress location, serendipity.

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Authors: Alok Madan, Ashok Gupta, Arshad K. Hashmi

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Non-linear dynamic time history analysis is considered as the most advanced and comprehensive analytical method for evaluating the seismic response and performance of multi-degree-of-freedom building structures under the influence of earthquake ground motions. However, effective and accurate application of the method requires the implementation of advanced hysteretic constitutive models of the various structural components including masonry infill panels. Sophisticated computational research tools that incorporate realistic hysteresis models for non-linear dynamic time-history analysis are not popular among the professional engineers as they are not only difficult to access but also complex and time-consuming to use. In addition, commercial computer programs for structural analysis and design that are acceptable to practicing engineers do not generally integrate advanced hysteretic models which can accurately simulate the hysteresis behavior of structural elements with a realistic representation of strength degradation, stiffness deterioration, energy dissipation and ‘pinching’ under cyclic load reversals in the inelastic range of behavior. In this scenario, push-over or non-linear static analysis methods have gained significant popularity, as they can be employed to assess the seismic performance of building structures while avoiding the complexities and difficulties associated with non-linear dynamic time-history analysis. “Push-over” or non-linear static analysis offers a practical and efficient alternative to non-linear dynamic time-history analysis for rationally evaluating the seismic demands. The present paper is based on the analytical investigation of the effect of distribution of masonry infill panels over the elevation of planar masonry infilled reinforced concrete [R/C] frames on the seismic demands using the capacity spectrum procedures implementing nonlinear static analysis [pushover analysis] in conjunction with the response spectrum concept. An important objective of the present study is to numerically evaluate the adequacy of the capacity spectrum method using pushover analysis for performance based design of masonry infilled R/C frames for near-field earthquake ground motions.

Keywords: Nonlinear analysis, capacity spectrum method, response spectrum, seismic demand, near-field earthquakes.

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Authors: Carolina B. Baguio

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One of the purposes of the robust method of estimation is to reduce the influence of outliers in the data, on the estimates. The outliers arise from gross errors or contamination from distributions with long tails. The trimmed mean is a robust estimate. This means that it is not sensitive to violation of distributional assumptions of the data. It is called an adaptive estimate when the trimming proportion is determined from the data rather than being fixed a “priori-. The main objective of this study is to find out the robustness properties of the adaptive trimmed means in terms of efficiency, high breakdown point and influence function. Specifically, it seeks to find out the magnitude of the trimming proportion of the adaptive trimmed mean which will yield efficient and robust estimates of the parameter for data which follow a modified Weibull distribution with parameter λ = 1/2 , where the trimming proportion is determined by a ratio of two trimmed means defined as the tail length. Secondly, the asymptotic properties of the tail length and the trimmed means are also investigated. Finally, a comparison is made on the efficiency of the adaptive trimmed means in terms of the standard deviation for the trimming proportions and when these were fixed a “priori". The asymptotic tail lengths defined as the ratio of two trimmed means and the asymptotic variances were computed by using the formulas derived. While the values of the standard deviations for the derived tail lengths for data of size 40 simulated from a Weibull distribution were computed for 100 iterations using a computer program written in Pascal language. The findings of the study revealed that the tail lengths of the Weibull distribution increase in magnitudes as the trimming proportions increase, the measure of the tail length and the adaptive trimmed mean are asymptotically independent as the number of observations n becomes very large or approaching infinity, the tail length is asymptotically distributed as the ratio of two independent normal random variables, and the asymptotic variances decrease as the trimming proportions increase. The simulation study revealed empirically that the standard error of the adaptive trimmed mean using the ratio of tail lengths is relatively smaller for different values of trimming proportions than its counterpart when the trimming proportions were fixed a 'priori'.

Keywords: Adaptive robust estimate, asymptotic efficiency, breakdown point, influence function, L-estimates, location parameter, tail length, Weibull distribution.

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Authors: M. De Filippo, J. S. Kuang

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In construction industry, reinforced concrete (RC) slabs represent fundamental elements of buildings and bridges. Different methods are available for analysing the structural behaviour of slabs. In the early ages of last century, the yield-line method has been proposed to attempt to solve such problem. Simple geometry problems could easily be solved by using traditional hand analyses which include plasticity theories. Nowadays, advanced finite element (FE) analyses have mainly found their way into applications of many engineering fields due to the wide range of geometries to which they can be applied. In such cases, the application of an elastic or a plastic constitutive model would completely change the approach of the analysis itself. Elastic methods are popular due to their easy applicability to automated computations. However, elastic analyses are limited since they do not consider any aspect of the material behaviour beyond its yield limit, which turns to be an essential aspect of RC structural performance. Furthermore, their applicability to non-linear analysis for modeling plastic behaviour gives very reliable results. Per contra, this type of analysis is computationally quite expensive, i.e. not well suited for solving daily engineering problems. In the past years, many researchers have worked on filling this gap between easy-to-implement elastic methods and computationally complex plastic analyses. This paper aims at proposing a numerical procedure, through which a pseudo-lower bound solution, not violating the yield criterion, is achieved. The advantages of moment distribution are taken into account, hence the increase in strength provided by plastic behaviour is considered. The lower bound solution is improved by detecting over-yielded moments, which are used to artificially rule the moment distribution among the rest of the non-yielded elements. The proposed technique obeys Nielsen’s yield criterion. The outcome of this analysis provides a simple, yet accurate, and non-time-consuming tool of predicting the lower-bound solution of the collapse load of RC slabs. By using this method, structural engineers can find the fracture patterns and ultimate load bearing capacity. The collapse triggering mechanism is found by detecting yield-lines. An application to the simple case of a square clamped slab is shown, and a good match was found with the exact values of collapse load.

Keywords: Computational mechanics, lower bound method, reinforced concrete slabs, yield-line.

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Authors: Elif Gencturk, Ekin Yurdakul, Ahmet Y. Celik, Senol Mutlu, Kutlu O. Ulgen

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Yeast cells are generally used as a model system of eukaryotes due to their complex genetic structure, rapid growth ability in optimum conditions, easy replication and well-defined genetic system properties. Thus, yeast cells increased the knowledge of the principal pathways in humans. During fermentation, carbohydrates (hexoses and pentoses) degrade into some toxic by-products such as 5-hydroxymethylfurfural (5-HMF or HMF) and furfural. HMF influences the ethanol yield, and ethanol productivity; it interferes with microbial growth and is considered as a potent inhibitor of bioethanol production. In this study, yeast single cell behavior under HMF application was monitored by using a continuous flow single phase microfluidic platform. Microfluidic device in operation is fabricated by hot embossing and thermo-compression techniques from cyclo-olefin polymer (COP). COP is biocompatible, transparent and rigid material and it is suitable for observing fluorescence of cells considering its low auto-fluorescence characteristic. The response of yeast cells was recorded through Red Fluorescent Protein (RFP) tagged Nop56 gene product, which is an essential evolutionary-conserved nucleolar protein, and also a member of the box C/D snoRNP complexes. With the application of HMF, yeast cell proliferation continued but HMF slowed down the cell growth, and after HMF treatment the cell proliferation stopped. By the addition of fresh nutrient medium, the yeast cells recovered after 6 hours of HMF exposure. Thus, HMF application suppresses normal functioning of cell cycle but it does not cause cells to die. The monitoring of Nop56 expression phases of the individual cells shed light on the protein and ribosome synthesis cycles along with their link to growth. Further computational study revealed that the mechanisms underlying the inhibitory or inductive effects of HMF on growth are enriched in functional categories of protein degradation, protein processing, DNA repair and multidrug resistance. The present microfluidic device can successfully be used for studying the effects of inhibitory agents on growth by single cell tracking, thus capturing cell to cell variations. By metabolic engineering techniques, engineered strains can be developed, and the metabolic network of the microorganism can thus be manipulated such that chemical overproduction of target metabolite is achieved along with the maximum growth/biomass yield.  

Keywords: COP, HMF, ribosome biogenesis, thermoplastic microbioreactor, yeast.

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Authors: Roberto de Lieto Vollaro, Emanuele de Lieto Vollaro, Gianluca Coltrinari

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The building sector is responsible, in many industrialized countries, for about 40% of the total energy requirements, so it seems necessary to devote some efforts in this area in order to achieve a significant reduction of energy consumption and of greenhouse gases emissions. The paper presents a study aiming at providing a design methodology able to identify the best configuration of the system building/plant, from a technical, economic and environmentally point of view. Normally, the classical approach involves a building's energy loads analysis under steady state conditions, and subsequent selection of measures aimed at improving the energy performance, based on previous experience made by architects and engineers in the design team. Instead, the proposed approach uses a sequence of two wellknown scientifically validated calculation methods (TRNSYS and RETScreen), that allow quite a detailed feasibility analysis. To assess the validity of the calculation model, an existing, historical building in Central Italy, that will be the object of restoration and preservative redevelopment, was selected as a casestudy. The building is made of a basement and three floors, with a total floor area of about 3,000 square meters. The first step has been the determination of the heating and cooling energy loads of the building in a dynamic regime by means, which allows simulating the real energy needs of the building in function of its use. Traditional methodologies, based as they are on steady-state conditions, cannot faithfully reproduce the effects of varying climatic conditions and of inertial properties of the structure. With this model is possible to obtain quite accurate and reliable results that allow identifying effective combinations building-HVAC system. The second step has consisted of using output data obtained as input to the calculation model, which enables to compare different system configurations from the energy, environmental and financial point of view, with an analysis of investment, and operation and maintenance costs, so allowing determining the economic benefit of possible interventions. The classical methodology often leads to the choice of conventional plant systems, while our calculation model provides a financial-economic assessment for innovative energy systems and low environmental impact. Computational analysis can help in the design phase, particularly in the case of complex structures with centralized plant systems, by comparing the data returned by the calculation model for different design options.

Keywords: Energy, Buildings, Systems, Evaluation.

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Authors: A. Lauvray, F. Poulhaon, P. Michaud, P. Joyot, E. Duc

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Additive Friction Stir Manufacturing, or AFSM, is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. There is still a lack in understanding of the physical phenomena taking place during the process. This research aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system due to pure friction. An analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable, due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes through a numerical modeling followed by an experimental validation to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, frictional heat generation, process

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Authors: Sujana Dhar, Asis Mazumdar

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The effects of global warming on India vary from the submergence of low-lying islands and coastal lands to the melting of glaciers in the Indian Himalayas, threatening the volumetric flow rate of many of the most important rivers of India and South Asia. In India, such effects are projected to impact millions of lives. As a result of ongoing climate change, the climate of India has become increasingly volatile over the past several decades; this trend is expected to continue. Climate change is one of the most important global environmental challenges, with implications for food production, water supply, health, energy, etc. Addressing climate change requires a good scientific understanding as well as coordinated action at national and global level. The climate change issue is part of the larger challenge of sustainable development. As a result, climate policies can be more effective when consistently embedded within broader strategies designed to make national and regional development paths more sustainable. The impact of climate variability and change, climate policy responses, and associated socio-economic development will affect the ability of countries to achieve sustainable development goals. A very well calibrated Soil and Water Assessment Tool (R2 = 0.9968, NSE = 0.91) was exercised over the Khatra sub basin of the Kangsabati River watershed in Bankura district of West Bengal, India, in order to evaluate projected parameters for agricultural activities. Evapotranspiration, Transmission Losses, Potential Evapotranspiration and Lateral Flow to reach are evaluated from the years 2041-2050 in order to generate a picture for sustainable development of the river basin and its inhabitants. India has a significant stake in scientific advancement as well as an international understanding to promote mitigation and adaptation. This requires improved scientific understanding, capacity building, networking and broad consultation processes. This paper is a commitment towards the planning, management and development of the water resources of the Kangsabati River by presenting detailed future scenarios of the Kangsabati river basin, Khatra sub basin, over the mentioned time period. India-s economy and societal infrastructures are finely tuned to the remarkable stability of the Indian monsoon, with the consequence that vulnerability to small changes in monsoon rainfall is very high. In 2002 the monsoon rains failed during July, causing profound loss of agricultural production with a drop of over 3% in India-s GDP. Neither the prolonged break in the monsoon nor the seasonal rainfall deficit was predicted. While the general features of monsoon variability and change are fairly well-documented, the causal mechanisms and the role of regional ecosystems in modulating the changes are still not clear. Current climate models are very poor at modelling the Asian monsoon: this is a challenging and critical region where the ocean, atmosphere, land surface and mountains all interact. The impact of climate change on regional ecosystems is likewise unknown. The potential for the monsoon to become more volatile has major implications for India itself and for economies worldwide. Knowledge of future variability of the monsoon system, particularly in the context of global climate change, is of great concern for regional water and food security. The major findings of this paper were that of all the chosen projected parameters, transmission losses, soil water content, potential evapotranspiration, evapotranspiration and lateral flow to reach, display an increasing trend over the time period of years 2041- 2050.

Keywords: Change, future water availability scenario, modeling, SWAT, global warming, sustainability.

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Authors: Moustafa Osman Mohammed

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Integration sustainability outcomes give attention to construction ecology in the design review of urban environments to comply with Earth’s System that is composed of integral parts of the (i.e., physical, chemical and biological components). Naturally, exchange patterns of industrial ecology have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. When engineering topology is affecting internal and external processes in system networks, it postulated the valence of the first-level spatial outcome (i.e., project compatibility success). These instrumentalities are dependent on relating the second-level outcome (i.e., participant security satisfaction). The construction ecology-based topology (i.e., as feedback energy system) flows from biotic and abiotic resources in the entire Earth’s ecosystems. These spatial outcomes are providing an innovation, as entails a wide range of interactions to state, regulate and feedback “topology” to flow as “interdisciplinary equilibrium” of ecosystems. The interrelation dynamics of ecosystems are performing a process in a certain location within an appropriate time for characterizing their unique structure in “equilibrium patterns”, such as biosphere and collecting a composite structure of many distributed feedback flows. These interdisciplinary systems regulate their dynamics within complex structures. These dynamic mechanisms of the ecosystem regulate physical and chemical properties to enable a gradual and prolonged incremental pattern to develop a stable structure. The engineering topology of construction ecology for integration sustainability outcomes offers an interesting tool for ecologists and engineers in the simulation paradigm as an initial form of development structure within compatible computer software. This approach argues from ecology, resource savings, static load design, financial other pragmatic reasons, while an artistic/architectural perspective, these are not decisive. The paper described an attempt to unify analytic and analogical spatial modeling in developing urban environments as a relational setting, using optimization software and applied as an example of integrated industrial ecology where the construction process is based on a topology optimization approach.

Keywords: Construction ecology, industrial ecology, urban topology, environmental planning.

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Authors: Bimali Sanjeevani Weerakoon, Toshiaki Osuga, Takehisa Konishi

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Magnetic Resonance Imaging Contrast Agents (MRI-CM) are significant in the clinical and biological imaging as they have the ability to alter the normal tissue contrast, thereby affecting the signal intensity to enhance the visibility and detectability of images. Superparamagnetic Iron Oxide (SPIO) nanoparticles, coated with dextran or carboxydextran are currently available for clinical MR imaging of the liver. Most SPIO contrast agents are T2 shortening agents and Resovist (Ferucarbotran) is one of a clinically tested, organ-specific, SPIO agent which has a low molecular carboxydextran coating. The enhancement effect of Resovist depends on its relaxivity which in turn depends on factors like magnetic field strength, concentrations, nanoparticle properties, pH and temperature. Therefore, this study was conducted to investigate the impact of field strength and different contrast concentrations on enhancement effects of Resovist. The study explored the MRI signal intensity of Resovist in the physiological range of plasma from T2-weighted spin echo sequence at three magnetic field strengths: 0.47 T (r1=15, r2=101), 1.5 T (r1=7.4, r2=95), and 3 T (r1=3.3, r2=160) and the range of contrast concentrations by a mathematical simulation. Relaxivities of r1 and r2 (L mmol-1 Sec-1) were obtained from a previous study and the selected concentrations were 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 2.0, and 3.0 mmol/L. T2-weighted images were simulated using TR/TE ratio as 2000 ms /100 ms. According to the reference literature, with increasing magnetic field strengths, the r1 relaxivity tends to decrease while the r2 did not show any systematic relationship with the selected field strengths. In parallel, this study results revealed that the signal intensity of Resovist at lower concentrations tends to increase than the higher concentrations. The highest reported signal intensity was observed in the low field strength of 0.47 T. The maximum signal intensities for 0.47 T, 1.5 T and 3 T were found at the concentration levels of 0.05, 0.06 and 0.05 mmol/L, respectively. Furthermore, it was revealed that, the concentrations higher than the above, the signal intensity was decreased exponentially. An inverse relationship can be found between the field strength and T2 relaxation time, whereas, the field strength was increased, T2 relaxation time was decreased accordingly. However, resulted T2 relaxation time was not significantly different between 0.47 T and 1.5 T in this study. Moreover, a linear correlation of transverse relaxation rates (1/T2, s–1) with the concentrations of Resovist can be observed. According to these results, it can conclude that the concentration of SPIO nanoparticle contrast agents and the field strengths of MRI are two important parameters which can affect the signal intensity of T2-weighted SE sequence. Therefore, when MR imaging those two parameters should be considered prudently.

Keywords: Concentration, Resovist, Field strength, Relaxivity, Signal intensity.

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Authors: K. Al Ammari, B. G. Clarke

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Soil improvement using vibro stone column techniques consists of two main parts: (1) the installed load bearing columns of well-compacted, coarse-grained material and (2) the improvements to the surrounding soil due to vibro compaction. Extensive research work has been carried out over the last 20 years to understand the improvement in the composite foundation performance due to the second part mentioned above. Nevertheless, few of these studies have tried to quantify some of the key design parameters, namely the changes in the stiffness and stress state of the treated soil, or have consider these parameters in the design and calculation process. Consequently, empirical and conservative design methods are still being used by ground improvement companies with a significant variety of results in engineering practice. Two-dimensional finite element study to develop an axisymmetric model of a single stone column reinforced foundation was performed using PLAXIS 2D AE to quantify the effect of the vibro installation of this column in soft saturated clay. Settlement and bearing performance were studied as an essential part of the design and calculation of the stone column foundation. Particular attention was paid to the large deformation in the soft clay around the installed column caused by the lateral expansion. So updated mesh advanced option was taken in the analysis. In this analysis, different degrees of stone column lateral expansions were simulated and numerically analyzed, and then the changes in the stress state, stiffness, settlement performance and bearing capacity were quantified. It was found that application of radial expansion will produce a horizontal stress in the soft clay mass that gradually decrease as the distance from the stone column axis increases. The excess pore pressure due to the undrained conditions starts to dissipate immediately after finishing the column installation, allowing the horizontal stress to relax. Changes in the coefficient of the lateral earth pressure K ٭, which is very important in representing the stress state, and the new stiffness distribution in the reinforced clay mass, were estimated. More encouraging results showed that increasing the expansion during column installation has a noticeable effect on improving the bearing capacity and reducing the settlement of reinforced ground, So, a design method should include this significant effect of the applied lateral displacement during the stone column instillation in simulation and numerical analysis design.

Keywords: Bearing capacity, design, Installation, numerical analysis, settlement, stone column.

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Authors: F. Saccucci

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Gamification has now started to take root in the post-secondary classroom. Educators have learned much about gamification to date but there is still a great deal to learn. One definition of gamification is the ability to engage post-secondary students with games that are fun and correlate to class room curriculum. There is no shortage of literature illustrating the advantages of gamification in the class room. This study is an extension of similar thought as well as an extension of a previous study where in class testing proved with the used of paired T-test that gamification did significantly improve the students’ understanding of subject material. Gamification itself in the class room can range from high end computer simulated software to paper based games of which both have advantages and disadvantages. This analysis used a paper based game to highlight certain qualitative advantages of gamification. The paper based game in this analysis was inexpensive, required low preparation time for the faculty member and consumed approximately 20 minutes of class room time. Data for the study was collected through in class student feedback surveys and narrative from the faculty member moderating the game. Students were randomly selected into groups of four. Qualitative advantages identified in this analysis included: 1. Students had a chance to meet, connect and know other students. 2. Students enjoyed the gamification process given there was a sense of fun and competition. 3. The post assessment that followed the simulation game was not part of their grade calculation therefore it was an opportunity to participate in a low risk activity whereby students could subsequently self-assess their understanding of the subject material. 4. In the view of the student, content knowledge did increase after the gamification process. These qualitative advantages identified in this analysis contribute to the argument that there should be an attempt to use gamification in today’s post-secondary class room. The analysis also highlighted that eighty (80) percent of the respondents believe twenty minutes devoted to the gamification process was appropriate, however twenty (20) percentage of respondents believed that rather than scheduling a gamification process and its post quiz in the last week, a review for the final exam may have been more useful. An additional study to this hopes to determine if the scheduling of the gamification had any correlation to a percentage of the students not wanting to be engaged in the process. As well, the additional study hopes to determine at what incremental level of time invested in class room gamification produce no material incremental benefits to the student as well as determine if any correlation exist between respondents preferring not to have it at the end of the semester to students not believing the gamification process added to the increase of their curricular knowledge.

Keywords: Gamification, inexpensive, qualitative advantages, post-secondary.

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Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

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Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: Diesel engine, machine learning, NOx emission, semi-empirical.

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Authors: I. Lucas, N. Schomberg, F-A. Couturier

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Most empirical studies have analyzed how liquidity risks faced by individual institutions turn into systemic risk. Recent banking crisis has highlighted the importance of grasping and controlling the systemic risk, and the acceptance by Central Banks to ease their monetary policies for saving default or illiquid banks. This last point shows that banks would pay less attention to liquidity risk which, in turn, can become a new important channel of loss. The financial regulation focuses on the most important and “systemic” banks in the global network. However, to quantify the expected loss associated with liquidity risk, it is worth to analyze sensitivity to this channel for the various elements of the global bank network. A small bank is not considered as potentially systemic; however the interaction of small banks all together can become a systemic element. This paper analyzes the impact of medium and small banks interaction on a set of banks which is considered as the core of the network. The proposed method uses the structure of agent-based model in a two-class environment. In first class, the data from actual balance sheets of 22 large and systemic banks (such as BNP Paribas or Barclays) are collected. In second one, to model a network as closely as possible to actual interbank market, 578 fictitious banks smaller than the ones belonging to first class have been split into two groups of small and medium ones. All banks are active on the European interbank network and have deposit and market activity. A simulation of 12 three month periods representing a midterm time interval three years is projected. In each period, there is a set of behavioral descriptions: repayment of matured loans, liquidation of deposits, income from securities, collection of new deposits, new demands of credit, and securities sale. The last two actions are part of refunding process developed in this paper. To strengthen reliability of proposed model, random parameters dynamics are managed with stochastic equations as rates the variations of which are generated by Vasicek model. The Central Bank is considered as the lender of last resort which allows banks to borrow at REPO rate and some ejection conditions of banks from the system are introduced.

Liquidity crunch due to exogenous crisis is simulated in the first class and the loss impact on other bank classes is analyzed though aggregate values representing the aggregate of loans and/or the aggregate of borrowing between classes. It is mainly shown that the three groups of European interbank network do not have the same response, and that intermediate banks are the most sensitive to liquidity risk.

Keywords: Systemic Risk, Financial Contagion, Liquidity Risk, Interbank Market, Network Model.

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Authors: Malte Brettel, Niklas Friederichsen, Michael Keller, Marius Rosenberg

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The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the process- and supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-Physical-Systems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decision-makers to assess their need for transformation towards Industry 4.0 practices. 

Keywords: Industry 4.0., Mass Customization, Production networks, Virtual Process-Chain.

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Authors: Alexander Buhr, Klaus Ehrenfried

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Trackside induced airflow velocities, also known as slipstream velocities, are an important criterion for the design of high-speed trains. The maximum permitted values are given by the Technical Specifications for Interoperability (TSI) and have to be checked in the approval process. For train manufactures it is of great interest to know in advance, how new train geometries would perform in TSI tests. The Reynolds number in moving model experiments is lower compared to full-scale. Especially the limited model length leads to a thinner boundary layer at the rear end. The hypothesis is that the boundary layer rolls up to characteristic flow structures in the train wake, in which the maximum flow velocities can be observed. The idea is to enlarge the boundary layer using roughness elements at the train model head so that the ratio between the boundary layer thickness and the car width at the rear end is comparable to a full-scale train. This may lead to similar flow structures in the wake and better prediction accuracy for TSI tests. In this case, the design of the roughness elements is limited by the moving model rig. Small rectangular roughness shapes are used to get a sufficient effect on the boundary layer, while the elements are robust enough to withstand the high accelerating and decelerating forces during the test runs. For this investigation, High-Speed Particle Image Velocimetry (HS-PIV) measurements on an ICE3 train model have been realized in the moving model rig of the DLR in Göttingen, the so called tunnel simulation facility Göttingen (TSG). The flow velocities within the boundary layer are analysed in a plain parallel to the ground. The height of the plane corresponds to a test position in the EN standard (TSI). Three different shapes of roughness elements are tested. The boundary layer thickness and displacement thickness as well as the momentum thickness and the form factor are calculated along the train model. Conditional sampling is used to analyse the size and dynamics of the flow structures at the time of maximum velocity in the train wake behind the train. As expected, larger roughness elements increase the boundary layer thickness and lead to larger flow velocities in the boundary layer and in the wake flow structures. The boundary layer thickness, displacement thickness and momentum thickness are increased by using larger roughness especially when applied in the height close to the measuring plane. The roughness elements also cause high fluctuations in the form factors of the boundary layer. Behind the roughness elements, the form factors rapidly are approaching toward constant values. This indicates that the boundary layer, while growing slowly along the second half of the train model, has reached a state of equilibrium.

Keywords: Boundary layer, high-speed PIV, ICE3, moving train model, roughness elements.

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Authors: Shinji Kajiwara

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The basic ability of a vehicle is to “run”, “turn” and “stop”. The safeness and comfort during a drive on various road surfaces and speed depends on the performance of these basic abilities of the vehicle. Stability and maneuverability of a vehicle are vital in automotive engineering. The stability of a vehicle is the ability of the vehicle to revert back to a stable state during a drive when faced with crosswinds and irregular road conditions. Maneuverability of a vehicle is the ability of the vehicle to change direction during a drive swiftly based on the steering of the driver. The stability and maneuverability of a vehicle can also be defined as the driving stability of the vehicle. Since the fossil fueled vehicle is the main type of transportation today, the environmental factor in automotive engineering is also vital. By improving the fuel efficiency of the vehicle, the overall carbon emission will be reduced, thus reducing the effect of global warming and greenhouse gas on the Earth. Another main focus of the automotive engineering is the safety performance of the vehicle, especially with the worrying increase of vehicle collision every day. With better safety performance of a vehicle, every driver will be more confident driving every day. Next, let us focus on the “turn” ability of a vehicle. By improving this particular ability of the vehicle, the cornering limit of the vehicle can be improved, thus increasing the stability and maneuverability factor. In order to improve the cornering limit of the vehicle, a study to find the balance between the steering systems, the stability of the vehicle, higher lateral acceleration and the cornering limit detection must be conducted. The aim of this research is to study and develop a new suspension system that will boost the lateral acceleration of the vehicle and ultimately improving the cornering limit of the vehicle. This research will also study environmental factor and the stability factor of the new suspension system. The double wishbone suspension system is widely used in a four-wheel vehicle, especially for high cornering performance sports car and racing car. The double wishbone designs allow the engineer to carefully control the motion of the wheel by controlling such parameters as camber angle, caster angle, toe pattern, roll center height, scrub radius, scuff, and more. The development of the new suspension system will focus on the ability of the new suspension system to optimize the camber control and to improve the camber limit during a cornering motion. The research will be carried out using the CAE analysis tool. Using this analysis tool we will develop a JSAE Formula Machine equipped with the double wishbone system and also the new suspension system and conduct simulation and conduct studies on the performance of both suspension systems.

Keywords: Automobile, Camber Thrust, Cornering force, Suspension.

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Authors: S. Mehrab Amiri, Nasser Talebbeydokhti

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Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme.  In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.

Keywords: Artificial neural network, morphodynamic model, sediment continuity equation, shallow water equations.

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Authors: Adel A. Ghoneim

Abstract:

In most existing buildings in hot climate, cooling loads lead to high primary energy consumption and consequently high CO2 emissions. These can be substantially decreased with integrated renewable energy systems. Kuwait is characterized by its dry hot long summer and short warm winter. Kuwait receives annual total radiation more than 5280 MJ/m2 with approximately 3347 h of sunshine. Solar energy systems consist of PV modules and parabolic trough collectors are considered to satisfy electricity consumption, domestic water heating, and cooling loads of an existing building. This paper presents the results of an extensive program of energy conservation and energy generation using integrated photovoltaic (PV) modules and Parabolic Trough Collectors (PTC). The program conducted on an existing institutional building intending to convert it into a Net-Zero Energy Building (NZEB) or near net Zero Energy Building (nNZEB). The program consists of two phases; the first phase is concerned with energy auditing and energy conservation measures at minimum cost and the second phase considers the installation of photovoltaic modules and parabolic trough collectors. The 2-storey building under consideration is the Applied Sciences Department at the College of Technological Studies, Kuwait. Single effect lithium bromide water absorption chillers are implemented to provide air conditioning load to the building. A numerical model is developed to evaluate the performance of parabolic trough collectors in Kuwait climate. Transient simulation program (TRNSYS) is adapted to simulate the performance of different solar system components. In addition, a numerical model is developed to assess the environmental impacts of building integrated renewable energy systems. Results indicate that efficient energy conservation can play an important role in converting the existing buildings into NZEBs as it saves a significant portion of annual energy consumption of the building. The first phase results in an energy conservation of about 28% of the building consumption. In the second phase, the integrated PV completely covers the lighting and equipment loads of the building. On the other hand, parabolic trough collectors of optimum area of 765 m2 can satisfy a significant portion of the cooling load, i.e about73% of the total building cooling load. The annual avoided CO2 emission is evaluated at the optimum conditions to assess the environmental impacts of renewable energy systems. The total annual avoided CO2 emission is about 680 metric ton/year which confirms the environmental impacts of these systems in Kuwait.

Keywords: Building integrated renewable systems, Net-Zero Energy Building, solar fraction, avoided CO2 emission.

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Authors: Mohd Azman Abdul Latif, Erwan Basiron

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A flaw or drift from expected operational performance in one component (NAND, PMIC, controller, DRAM, etc.) may affect the reliability of the entire Solid State Drive (SSD) system. Therefore, it is important to ensure the required quality of each individual component through qualification testing specified using standards or user requirements. Qualification testing is time-consuming and comes at a substantial cost for product manufacturers. A highly technical team, from all the eminent stakeholders is embarking on reliability prediction from beginning of new product development, identify critical to reliability parameters, perform full-blown characterization to embed margin into product reliability and establish control to ensure the product reliability is sustainable in the mass production. The paper will discuss a comprehensive development framework, comprehending SSD end to end from design to assembly, in-line inspection, in-line testing and will be able to predict and to validate the product reliability at the early stage of new product development. During the design stage, the SSD will go through intense reliability margin investigation with focus on assembly process attributes, process equipment control, in-process metrology and also comprehending forward looking product roadmap. Once these pillars are completed, the next step is to perform process characterization and build up reliability prediction modeling. Next, for the design validation process, the reliability prediction specifically solder joint simulator will be established. The SSD will be stratified into Non-Operating and Operating tests with focus on solder joint reliability and connectivity/component latent failures by prevention through design intervention and containment through Temperature Cycle Test (TCT). Some of the SSDs will be subjected to the physical solder joint analysis called Dye and Pry (DP) and Cross Section analysis. The result will be feedbacked to the simulation team for any corrective actions required to further improve the design. Once the SSD is validated and is proven working, it will be subjected to implementation of the monitor phase whereby Design for Assembly (DFA) rules will be updated. At this stage, the design change, process and equipment parameters are in control. Predictable product reliability at early product development will enable on-time sample qualification delivery to customer and will optimize product development validation, effective development resource and will avoid forced late investment to bandage the end-of-life product failures. Understanding the critical to reliability parameters earlier will allow focus on increasing the product margin that will increase customer confidence to product reliability.

Keywords: e2e reliability prediction, SSD, TCT, Solder Joint Reliability, NUDD, connectivity issues, qualifications, characterization and control.

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Authors: S. Chuenchooklin

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This research was conducted in the Pua Watershed whereas located in the Upper Nan River Basin in Nan province, Thailand. Nan River basin originated in Nan province that comprises of many tributary streams to produce as inflow to the Sirikit dam provided huge reservoir with the storage capacity of 9510 million cubic meters. The common problems of most watersheds were found i.e. shortage water supply for consumption and agriculture utilizations, deteriorate of water quality, flood and landslide including debris flow, and unstable of riverbank. The Pua Watershed is one of several small river basins that flow through the Nan River Basin. The watershed includes 404 km2 representing the Pua District, the Upper Nan Basin, or the whole Nan River Basin, of 61.5%, 18.2% or 1.2% respectively. The Pua River is a main stream producing all year streamflow supplying the Pua District and an inflow to the Upper Nan Basin. Its length approximately 56.3 kilometers with an average slope of the channel by 1.9% measured. A diversion weir namely Pua weir bound the plain and mountainous areas with a very steep slope of the riverbed to 2.9% and drainage area of 149 km2 as upstream watershed while a mild slope of the riverbed to 0.2% found in a river reach of 20.3 km downstream of this weir, which considered as a gauged basin. However, the major branch streams of the Pua River are ungauged catchments namely: Nam Kwang and Nam Koon with the drainage area of 86 and 35 km2 respectively. These upstream watersheds produce runoff through the 3-streams downstream of Pua weir, Jao weir, and Kang weir, with an averaged annual runoff of 578 million cubic meters. They were analyzed using both statistical data at Pua weir and simulated data resulted from the hydrologic modeling system (HEC–HMS) which applied for the remaining ungauged basins. Since the Kwang and Koon catchments were limited with lack of hydrological data included streamflow and rainfall. Therefore, the mathematical modeling: HEC-HMS with the Snyder-s hydrograph synthesized and transposed methods were applied for those areas using calibrated hydrological parameters from the upstream of Pua weir with continuously daily recorded of streamflow and rainfall data during 2008-2011. The results showed that the simulated daily streamflow and sum up as annual runoff in 2008, 2010, and 2011 were fitted with observed annual runoff at Pua weir using the simple linear regression with the satisfied correlation R2 of 0.64, 062, and 0.59, respectively. The sensitivity of simulation results were come from difficulty using calibrated parameters i.e. lag-time, coefficient of peak flow, initial losses, uniform loss rates, and missing some daily observed data. These calibrated parameters were used to apply for the other 2-ungauged catchments and downstream catchments simulated.

Keywords: Streamflow, hydrological model, ungauged catchments.

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Authors: Mathias U. Bonet, Pericles Pilidis, Georgios Doulgeris

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A gas turbine-powered cruise Liner is scheduled to transport pilgrim passengers from Lagos-Nigeria to the Islamic port city of Jeddah in Saudi Arabia. Since the gas turbine is an air breathing machine, changes in the density and/or mass flow at the compressor inlet due to an encounter with variations in weather conditions induce negative effects on the performance of the power plant during the voyage. In practice, all deviations from the reference atmospheric conditions of 15 ^oC and 1.103 bar tend to affect the power output and other thermodynamic parameters of the gas turbine cycle. Therefore, this paper seeks to evaluate how a simple cycle marine gas turbine power plant would react under a variety of scenarios that may be encountered during a voyage as the ship sails across the Atlantic Ocean and the Mediterranean Sea before arriving at its designated port of discharge. It is also an assessment that focuses on the effect of varying aerodynamic and hydrodynamic conditions which deteriorate the efficient operation of the propulsion system due to an increase in resistance that results from some projected levels of the ship hull fouling. The investigated passenger ship is designed to run at a service speed of 22 knots and cover a distance of 5787 nautical miles. The performance evaluation consists of three separate voyages that cover a variety of weather conditions in winter, spring and summer seasons. Real-time daily temperatures and the sea states for the selected transit route were obtained and used to simulate the voyage under the aforementioned operating conditions. Changes in engine firing temperature, power output as well as the total fuel consumed per voyage including other performance variables were separately predicted under both calm and adverse weather conditions. The collated data were obtained online from the UK Meteorological Office as well as the UK Hydrographic Office websites, while adopting the Beaufort scale for determining the magnitude of sea waves resulting from rough weather situations. The simulation of the gas turbine performance and voyage analysis was effected through the use of an integrated Cranfield-University-developed computer code known as ‘Turbomatch’ and ‘Poseidon’. It is a project that is aimed at developing a method for predicting the off design behavior of the marine gas turbine when installed and operated as the main prime mover for both propulsion and powering of all other auxiliary services onboard a passenger cruise liner. Furthermore, it is a techno-economic and environmental assessment that seeks to enable the forecast of the marine gas turbine part and full load performance as it relates to the fuel requirement for a complete voyage.

Keywords:

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Authors: Ren-Jy Ben, Jo-Chi Jao, Chiu-Ya Liao, Ya-Ru Tsai, Lain-Chyr Hwang, Po-Chou Chen

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Cancer is still one of the serious diseases threatening the lives of human beings. How to have an early diagnosis and effective treatment for tumors is a very important issue. The animal carcinoma model can provide a simulation tool for the studies of pathogenesis, biological characteristics, and therapeutic effects. Recently, drug delivery systems have been rapidly developed to effectively improve the therapeutic effects. Liposome plays an increasingly important role in clinical diagnosis and therapy for delivering a pharmaceutic or contrast agent to the targeted sites. Liposome can be absorbed and excreted by the human body, and is well known that no harm to the human body. This study aimed to compare the therapeutic effects between encapsulated (doxorubicin liposomal, Lipodox) and un-encapsulated (doxorubicin, Dox) anti-tumor drugs using magnetic resonance imaging (MRI). Twenty-four New Zealand rabbits implanted with VX2 carcinoma at left thighs were classified into three groups: control group (untreated), Dox-treated group, and LipoDox-treated group, 8 rabbits for each group. MRI scans were performed three days after tumor implantation. A 1.5T GE Signa HDxt whole body MRI scanner with a high resolution knee coil was used in this study. After a 3-plane localizer scan was performed, three-dimensional (3D) fast spin echo (FSE) T2-weighted Images (T2WI) was used for tumor volumetric quantification. Afterwards, two-dimensional (2D) spoiled gradient recalled echo (SPGR) dynamic contrast-enhanced (DCE) MRI was used for tumor perfusion evaluation. DCE-MRI was designed to acquire four baseline images, followed by contrast agent Gd-DOTA injection through the ear vein of rabbit. A series of 32 images were acquired to observe the signals change over time in the tumor and muscle. The MRI scanning was scheduled on a weekly basis for a period of four weeks to observe the tumor progression longitudinally. The Dox and LipoDox treatments were prescribed 3 times in the first week immediately after the first MRI scan; i.e. 3 days after VX2 tumor implantation. ImageJ was used to quantitate tumor volume and time course signal enhancement on DCE images. The changes of tumor size showed that the growth of VX2 tumors was effectively inhibited for both LipoDox-treated and Dox-treated groups. Furthermore, the tumor volume of LipoDox-treated group was significantly lower than that of Dox-treated group, which implies that LipoDox has better therapeutic effect than Dox. The signal intensity of LipoDox-treated group is significantly lower than that of the other two groups, which implies that targeted therapeutic drug remained in the tumor tissue. This study provides a radiation-free and non-invasive MRI method for therapeutic monitoring of targeted liposome on an animal tumor model.

Keywords: Doxorubicin, dynamic contrast-enhanced MRI, lipodox, magnetic resonance imaging, VX2 tumor model.

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Authors: Márcia Afonso, Cristina Fael, Marisa Dinis-Almeida

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Population growth in cities has led to an increase in the infrastructures construction, including buildings and roadways. This aspect leads directly to the soils waterproofing. In turn, changes in precipitation patterns are developing into higher and more frequent intensities. Thus, these two conjugated aspects decrease the rainwater infiltration into soils and increase the volume of surface runoff. The practice of green and sustainable urban solutions has encouraged research in these areas. The porous asphalt pavement, as a green infrastructure, is part of practical solutions set to address urban challenges related to land use and adaptation to climate change. In this field, permeable pavements with porous asphalt mixtures (PA) have several advantages in terms of reducing the runoff generated by the floods. The porous structure of these pavements, compared to a conventional asphalt pavement, allows the rainwater infiltration in the subsoil, and consequently, the water quality improvement. This green infrastructure solution can be applied in cities, particularly in streets or parking lots to mitigate the floods effects. Over the years, the pores of these pavements can be filled by sediment, reducing their function in the rainwater infiltration. Thus, double layer porous asphalt (DLPA) was developed to mitigate the clogging effect and facilitate the water infiltration into the lower layers. This study intends to deepen the knowledge of the performance of DLPA when subjected to clogging. The experimental methodology consisted on four evaluation phases of the DLPA infiltration capacity submitted to three precipitation events (100, 200 and 300 mm/h) in each phase. The evaluation first phase determined the behavior after DLPA construction. In phases two and three, two 500 g/m² clogging cycles were performed, totaling a 1000 g/m² final simulation. Sand with gradation accented in fine particles was used as clogging material. In the last phase, the DLPA was subjected to simple sweeping and vacuuming maintenance. A precipitation simulator, type sprinkler, capable of simulating the real precipitation was developed for this purpose. The main conclusions show that the DLPA has the capacity to drain the water, even after two clogging cycles. The infiltration results of flows lead to an efficient performance of the DPLA in the surface runoff attenuation, since this was not observed in any of the evaluation phases, even at intensities of 200 and 300 mm/h, simulating intense precipitation events. The infiltration capacity under clogging conditions decreased about 7% on average in the three intensities relative to the initial performance that is after construction. However, this was restored when subjected to simple maintenance, recovering the DLPA hydraulic functionality. In summary, the study proved the efficacy of using a DLPA when it retains thicker surface sediments and limits the fine sediments entry to the remaining layers. At the same time, it is guaranteed the rainwater infiltration and the surface runoff reduction and is therefore a viable solution to put into practice in permeable pavements.

Keywords: Clogging, double layer porous asphalt, infiltration capacity, rainfall intensity.

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Authors: Kari Björn

Abstract:

Introduction of games has expanded the application area of computer-aided learning tools to wide variety of age groups of learners. Serious games engage the learners into a real-world -type of simulation and potentially enrich the learning experience. Institutional background of a Bachelor’s level engineering program in Information and Communication Technology is introduced, with detailed focus on one of its majors, Health Technology. As part of a Customer Oriented Software Application thematic semester, one particular course of “eHealth Business and Solutions” is described and reflected in a gamified framework. Learning a consistent view into vast literature of business management, strategies, marketing and finance in a very limited time enforces selection of topics relevant to the industry. Health Technology is a novel and growing industry with a growing sector in consumer wearable devices and homecare applications. The business sector is attracting new entrepreneurs and impatient investor funds. From engineering education point of view the sector is driven by miniaturizing electronics, sensors and wireless applications. However, the market is highly consumer-driven and usability, safety and data integrity requirements are extremely high. When the same technology is used in analysis or treatment of patients, very strict regulatory measures are enforced. The paper introduces a course structure using gamification as a tool to learn the most essential in a new market: customer value proposition design, followed by a market entry game. Students analyze the existing market size and pricing structure of eHealth web-service market and enter the market as a steering group of their company, competing against the legacy players and with each other. The market is growing but has its rules of demand and supply balance. New products can be developed with an R&D-investment, and targeted to market with unique quality- and price-combinations. Product cost structure can be improved by investing to enhanced production capacity. Investments can be funded optionally by foreign capital. Students make management decisions and face the dynamics of the market competition in form of income statement and balance sheet after each decision cycle. The focus of the learning outcome is to understand customer value creation to be the source of cash flow. The benefit of gamification is to enrich the learning experience on structure and meaning of financial statements. The paper describes the gamification approach and discusses outcomes after two course implementations. Along the case description of learning challenges, some unexpected misconceptions are noted. Improvements of the game or the semi-gamified teaching pedagogy are discussed. The case description serves as an additional support to new game coordinator, as well as helps to improve the method. Overall, the gamified approach has helped to engage engineering student to business studies in an energizing way.

Keywords: Engineering education, integrated curriculum, learning experience, learning outcomes.

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