Recent Developments of Multiple Myeloma: Analysis and Analytical Modeling Using Real Data

Analytical modeling and thermal analysis of deep coaxial borehole heat exchanger with stratified-seepage-segmented finite line source method (S3-FLS)

Estimation of the energy production of a parabolic trough solar thermal power plant using analytical and artificial neural networks models

The threat of Internet worms has been, and continues to be, one of the most important issues faced by networking researchers and network users. The need for accurate and efficient modeling and analysis methods cannot be understated. Models that accurately reflect the behavior of existing and yet-to-be deployed worms is critical to understanding how to deal with this ongoing threat. Recently developed analytical models, have been used to generate propagation trends that match with historic worm outbreaks. However in this effort, the values used for some of the parameters are different from empirically measured information, such as probe rate per unit IP address space. Although not found in simpler models, new analytical models are under development that can take into account various network and worm characteristics. But in order to build and test them accurately real world data has been used. In our work, we have focused on packet-level detail in the simulation models, which can take into account realistic network characteristics that include, queuing delay, packet-loss, link delays and also realistic worm characteristics at the expense of additional computational complexity. Using our simulator we show how it can be a useful tool in analyzing and evaluating analytical worm models. We study the worm propagation pattern predicted by one particular analytical model and compare it to our packet-level simulations.

This paper presents the analytical modeling and finite element (FE) analysis, using ABAQUS software, of the new types of steel reinforced lightweight aggregate concrete (SRLAC) columns with cross-shaped (+shaped and X-shaped) steel section, using proposed three analytical and two FE models in total. The stress-strain material models for different components in the columns, including the confined zones of the lightweight aggregate concrete (LWAC) using three and four concrete zones divisions approaches and with and without taking into account the stirrups reaction effect, are established first. The analytical models for determining the axial load-deformation behavior of the SRLAC columns are drawn based on the materials models. The analytical and FE models' results are compared with previously reported test results of the axially loaded SRLAC columns. The proposed analytical and FE models accurately predict the axial behavior and capacities of the new types of SRLAC columns with acceptable agreements for the load-displacement curves. The LWAC strength, steel section ratio, and steel section configuration affect the contact stress between the concrete and steel sections. The average ratios of the ultimate test load to the three analytical models and FEA model loads, Put /Pa1, Put /Pa2, Put /Pa3, and Put /PFE1, for the tested specimens are 0.96, 1.004, 1.016, and 1.019, respectively. Finally, the analytical parametric studies are also studied, in terms of the effects of confinement, LWAC strength, steel section ratio, and the reinforcement ratio on the axial capacity of the SRLAC column. When concrete strength, confinements, area of steel sections, or reinforcement bars ratio increased, the axial capacities increased.

This thesis studies the dimensioning for UMTS Radio Access Networks. In this thesis, dimensioning is investigated with specific focus on the transport network of the Iub interface, which connects the Node B with the RNC. This interface is considered as one of the most important economic factors for the UMTS network dimensioning. In order to cover large urban and rural areas, a large number of Node Bs are required and thus the transport resources for the Iub interface become considerably costly. The ultimate goal of this thesis is to investigate important aspects related to the UMTS radio access network dimensioning, and to propose novel analytical methods to provide suitable estimations on the required transport capacity for the UMTS radio access network in order to achieve maximum utilization of the transport resources. In order to provide a comprehensive investigation on the dimensioning of the Iub interface, various traffic types, different evolutions of UMTS radio access networks as well as different transport solutions, QoS mechanisms and network topologies are studied in this thesis. In the framework of this thesis, UMTS Rel99 is considered as the basic UMTS network. Furthermore, evolved UMTS networks such as HSDPA and HSUPA, and the evolved transport from ATM to IP are investigated. For each evolution of the UMTS radio access network, its specific protocol stacks, important features, its specific trafficand resource control functions and their impacts on the Iub dimensioning are studied. For the dimensioning process, two basic types of traffic are distinguished, elastic and circuit-switched traffic. They are associated with non real time data applications and delay-sensitive real time services, which are identified as the two main traffic classes served in the current UMTS networks. The fundamental property of elastic traffic is its rate adaptability, which is caused by the feedback mechanism of TCP. In this thesis, the theory of processor sharing is applied to the dimensioning of the Iub interface for elastic traffic for satisfying its desired end-to-end application QoS. To consider the specific UMTS functions and network structures, the basic processor sharing model has been significantly extended in this thesis to dimension the radio access networks under various scenarios of traffic, QoS framework, resource control functions, different transport technologies and network structures. In case of circuitswitched traffic, which needs to meet a guaranteed blocking probability, the classical Erlang models are applied. In addition, a number of queuing models are proposed in this thesis to dimension the Iub link for guaranteeing a required transport network QoS. For validating the developed analytical models as well as for performance evaluation, several simulation models were developed in this thesis to model different UMTS radio access networks. By performing extensive simulations and analysis of the simulation results, important dimensioning rules are derived and the proposed analytical dimensioning models are demonstrated. Through validating with simulation results, it is demonstrated that the proposed analytical models in this thesis are able to capture relevant characteristics and provide accurate dimensioning results, and thus can be applied for UMTS radio access network dimensioning. At the end, a dimensioning tool is developped in this thesis, containing all developed analytical models. This tool can perform dimensioning for various traffic scenarios, transport solutions, QoS mechanisms and network topologies for different UMTS radio access networks. Overall, the investigations and the analytical dimensioning models presented in this

Unmanned aerial communication platforms have been recently considered as an effective solution to provide homogeneous and extended network coverage to terrestrial users. Unmanned Aerial Vehicles (UAVs) are expected to increase the network reliability and users' Quality of Experience (QoE). The first target of this paper is to analyze the propagation characteristics of drone transmission at different frequencies i.e., 3.5 GHz, 28 GHz, 60 GHz, and up to 180 GHz with 20GHz step. In the considered setup drone is flying at different heights i.e., from 50m up to 250m altitude and we carry out 3D ray tracing simulations assuming a propagation environment that is defined by the real building data from Helsinki city. Ground users are placed outdoors. We study the validity of a previously proposed geometrical Line of Sight (LOS) probability model between ground user and drone, and based on simulations we propose new modeling parameters. In the second part of the paper, the ray tracing results are compared with the analytical reference model. Finally, a new set of parameters is proposed for tuned analytical model based on acquired ray tracing results. The proposed analytical model provides significantly low Root Mean Square Error (RMSE) when compared with the analytical reference model.

During the pullout test, the pullout clamping system was modified and installed inside the pullout box with confinement from the fill material, hereinafter called the in-soil pullout test, which significantly reduced the necking phenomenon and the displacements mobilized during the pullout test. Subsequently, an analytical model was developed to predict the in-soil pullout resistance. In addition, a numerical modeling analysis, under the three-dimensional stress field conditions using the FLAC3D (fast Lagrangian analysis continua) program, was carried out to simulate the behavior of in-soil pullout tests. The laboratory in-soil pullout test results were then compared with the corresponding data obtained from the analytical and numerical modeling methods. The in-soil pullout resistance was greater than the corresponding result from previous pullout tests wherein the clamping system was conventionally installed outside the pullout box. The predicted pullout resistance results from FLAC3D agreed reasonably with the results from laboratory tests and with the results from the analytical modeling. The interaction coefficients, R, applied in the finite difference modeling of in-soil pullout tests were 0.90 and 0.65 for zinc-coated and polyvinyl chloride (PVC) coated hexagonal wire meshes, respectively. The predicted and measured pullout resistance of zinc-coated hexagonal wire mesh is approximately 20% greater than that of PVC-coated hexagonal wire mesh at the same applied normal pressure, because of the higher stiffness, EA, and higher shear stiffness, ks, of the zinc-coated mesh.Key words: hexagonal wire mesh, in-soil pullout test, pullout resistance, analytical modeling, numerical modeling.

Wind farm power control is key to reliable large-scale wind integration. The design of a sophisticated wind farm controller, however, is challenging partly because there is a lack of models that appropriately simplify the complex overall dynamics of a large number of wind turbine control systems (WTCSs). In this paper, using system identification approaches, we develop a simple approximate model that attempts to mimic the active and reactive power dynamics of two generic WTCS models under normal operating conditions: an analytical model described by nonlinear differential equations, and an empirical one by input-output measurement data. The approximate model contains two parts-one for active power and one for reactive-each of which is a third-order system that would have been linear if not for a static nonlinearity. For each generic model, we also provide an identification scheme that sequentially determines the approximate model parameters. Finally, we show via simulation that, despite its structural simplicity, the approximate model is accurate and versatile, capable of closely imitating several different analytical and empirical WTCS models from the literature and from real data. The results suggest that the approximate model may be used to facilitate research on wind farm power control.

The purpose of this paper is to evaluate and compare past models of transfer lines. After a discussion of the nature of transfer lines and their stoppages, the assumptions and derivations of seven analytical models are compared. The major discrepancies in assumptions concern whether failures are time dependent or operation dependent. The comparison of derivations includes a translation of all results to a common set of symbols. The predictions of the models at various banking levels are observed to vary significantly. Model validation is discussed in two phases. First the validity of the assumptions is tested by real data from a transfer line. The major problem is the failure of the real data to satisfy the assumptions of the model. Finally, the predictions of the analytical models are compared with a simulation model which uses the actual data. The difference between analytical and simulation models was found to be significant.

Wind farm power control is key to reliable large-scale wind integration. The design of a sophisticated wind farm controller, however, is nontrivial partly because there is a lack of models that appropriately simplify the complex overall dynamics of a large number of wind turbine control systems (WTCSs). In this chapter, we use system identification techniques to develop a simple approximate model that attempts to mimic the active and reactive power dynamics of two generic WTCS models under normal operating conditions: an analytical model described by nonlinear differential equations, and an empirical one by input–output measurement data. The approximate model contains two parts—one for active power and one for reactive power—each of which is a third-order system that would have been linear if not for a static nonlinearity. For each generic model, we also provide an identification scheme that sequentially determines the approximate model parameters. Finally, we show via simulation that, despite its structural simplicity, the approximate model is sufficient and versatile, capable of closely imitating several different analytical and empirical WTCS models from the literature and from real data. The results suggest that the approximate model may be used to facilitate research in wind farm power control, which we will carry out in subsequent chapters.

Purpose The purpose of this paper is to explore a methodology that allows to represent turbomachinery rotating parts by replacing the blades with a body force field. The objective is to capture interactions between a fan and an air intake at reduced cost, as compared to full annulus unsteady computations. Design/methodology/approach The blade effects on the flow are taken into account by adding source terms to the Navier-Stokes equations. These source terms give the proper amount of flow turning, entropy, and blockage to the flow. Two different approaches are compared: the source terms can be computed using an analytic model, or they can directly be extracted from RANS computations with the blade’s geometry. Findings The methodology is first applied to an isolated rotor test case, which allows to show that blockage effects have a strong impact on the performance of the rotor. It is also found that the analytic body force model underestimates the mass flow in the blade row for choked conditions. Finally, the body force approach is used to capture the coupling between a fan and an air intake at high angle of attacks. A comparison with full annulus unsteady computations shows that the model adequately captures the potential effects of the fan on the air intake. Originality/value To the authors’ knowledge, it is the first time that the analytic model used in this paper is combined with the blockage source terms. Furthermore, the capability of the model to deal with flows in choked conditions was never assessed.

We discuss the role of theoretical and, in particular, analytical modeling in mechanical problems for electronic packaging, including requirements for a feasible theoretical model, how such a model is developed, the role of mathematics, what can be gained by using theoretical modeling, as well as the interaction of analytical, numerical (computer-aided) and experimental models. Peculiarities of theoretical modeling in Structural Analysis are also briefly discussed.

Summary. This paper describes techniques for the identification of well-test interpretation models from pressure-derivative data. Artificial pressure-derivative data. Artificial intelligence (AI) techniques are used to separate the derivative response from signal and differentiation noise, and a rule-based recognition system characterizes the response using a symbolic representation. Introduction The use of computers for well-test analysis has played an important role in the development and application of new interpretation techniques. With nonlinear regression, algorithms have been developed that can perform automated type-curve matching when perform automated type-curve matching when given a specific model and a first estimation of its parameters. Such algorithms not only speed the interpretation procedure but also increase the confidence in the results by allowing quantification of the quality of the match obtained. Correct application of these methods, however, depends on the choice of the interpretation model. An interpretation procedure that uses the pressure derivative is regarded as the pressure derivative is regarded as the most appropriate tool for the diagnosis of an interpretation model for well-test data. The derivative is not only more sensitive to the different flow regimes and flow-regime transitions but also is more generally applicable and therefore provides a substitute for all the specialized analyses. In traditional graphical analysis, the choice of an interpretation model is essentially a visual process. Based on a log-log plot of the pressure derivative, an expert can perform model identification by recognizing features that are specific to particular analytical models. The combination of the various models then gives an interpretation model. Although the human visual perception process is not fully understood, significant process is not fully understood, significant work in AI has been conducted to develop machine vision systems. These systems operate not on the image itself but on a symbolic representation containing the information needed for the task under consideration. This paper describes the development of techniques to automate the modelidentification step of well-test interpretation by use of AI. The computer's choice of a model is based on the pressure-derivative curve and simulates the visual diagnosis performed by a human expert. The reasoning performed by a human expert. The reasoning involved in such a diagnosis uses a symbolic representation of the derivative curve, which in the case of a human expert is built almost unconsciously. Techniques were developed to replicate this visual-perception step. A major difficulty in the analysis of real data, particularly when the pressure derivative is used, is the separation of the true reservoir response from signal or differentiation noise. Again, this is relatively simple for a human observer, but difficult to implement in a computer program. This paper describes an algorithm developed to overcome this problem. The algorithm was able to distinguish response from noise correctly, thereby allowing for correct model identification. In a manner analogous to a human expert, the technique constructs an interpretation model for the duration of the data by combining the features of the different flow periods of the response. The adequacy of a periods of the response. The adequacy of a model is determined by qualitative and quantitative information. Once a model is chosen, its parameters are estimated with a correlation or an appropriate table. The system developed in this work can perform model identification on real or perform model identification on real or hypothetical data. Because the method also provides parameter estimation, it can be provides parameter estimation, it can be used with an automated type-curve-matching analysis, allowing full automation of welltest interpretation. The task of identifying an interpretation model by use of the derivative of well-test data can be separated into three components:observation-extraction of the features present on the data derivative and present on the data derivative and representation of these features,knowledge of the models-methods for the construction and description of interpretation models, andmatching-criteria for choosing appropriate interpretation models for given data. The development of the specialized rule base and logical approach for these three components took considerable work before the algorithms were able to interpret real data reliably. The purpose of this paper is to describe this development as an aid to others who may wish to attempt a similar approach. JPT P. 342

SummaryRecent theoretical studies have predicted that adiabatic compressed air energy storage (ACAES) can be an effective energy storage option in the future. However, major experimental projects and commercial ventures have so far failed to yield any viable prototypes. Here we explore the underlying reasons behind this failure. By developing an analytical idealized model of a typical ACAES design, we derive a design-dependent efficiency limit for a system with hypothetical, perfect components. This previously overlooked limit, equal to 93.6% under continuous cycling for a typical design, arises from irreversibility associated with the transient pressure in the system. Although the exact value is design dependent, the methodology we present for finding the limit is applicable for a wide range of designs. Turning to real systems, the limit alone does not fully explain the failure of practical ACAES research. However, reviewing the available evidence alongside our analytical model, we reason that underestimation of the system complexity, difficulty with the integration of off-the-shelf components, and a number of misleading performance claims are the primary reasons hindering ACAES development.

Radio frequency microelectromechanical system (RF MEMS) switch technology might have potential to replace the semiconductor technology in future communication systems as well as communication satellites, wireless and mobile phones. This study is to explore the possibilities of RF MEMS switch design and optimization with aluminium nitride (AlN) thin film as the piezoelectric actuation material. Achieving low actuation voltage and high contact force with optimal geometry using the principle of piezoelectric effect is the main motivation for this research. Analytical and numerical modelling of single beam type RF MEMS switch used to analyse the design parameters and optimize them for the minimum actuation voltage and high contact force. An analytical model using isotropic AlN material properties used to obtain the optimal parameters. The optimized geometry of the device length, width and thickness are 2000 µm, 500 µm and 0.6 µm respectively obtained for the single beam RF MEMS switch. Low actuation voltage and high contact force with optimal geometry are less than 2 Vand 100 µN obtained by analytical analysis. Additionally, the single beam RF MEMS switch are optimized and validated by comparing the analytical and finite element modelling (FEM) analysis.