Analytical Model For Estimation Research Articles

Analytical model for stage-discharge estimation in meandering compound channels with submerged flexible vegetation

For overbank flows, submerged flexible vegetation on floodplains increases channel resistance and decreases channel conveyance capability. This study presents an analytical model for estimating the stage-discharge relationship in a meandering compound channel with dense, submerged, flexible vegetation on floodplains under high flow conditions. The mean velocity within a canopy was linked to the depth-averaged velocity, and a relationship between the two velocities was proposed. The governing equation was deduced in curvilinear coordinates, and the lateral shear stresses were found to be negligible, as validated by our experimental measurements in a large-scale meandering channel. Then, analytical solutions of subarea discharges and total discharge were derived by ignoring lateral shear stresses. Measurements from two flume experiments and one field study were used to verify the proposed model. The field case involved a natural river with both submerged and emergent grass on the floodplains. Good agreement between predictions and measurements indicated that the model accurately predicted subarea discharges and the stage-discharge relationships in a meandering compound channel with submerged vegetation. Finally, the predictions of this model were sensitive to the secondary flow parameters in the main channel but insensitive to those on the floodplains.

Equilibrium based analytical model for estimation of pressure magnification during deflagration of hydrogen air mixtures

Abstract During postulated accident sequences in nuclear reactors, hydrogen may get released from the core and form a flammable mixture in the surrounding containment structure. Ignition of such mixtures and the subsequent pressure rise are an imminent threat for safe and sustainable operation of nuclear reactors. Methods for evaluating post ignition characteristics are important for determining the design safety margins in such scenarios. This study presents two thermo-chemical models for determining the post ignition state. The first model is based on internal energy balance while the second model uses the concept of element potentials to minimize the free energy of the system with internal energy imposed as a constraint. Predictions from both the models have been compared against published data over a wide range of mixture compositions. Important differences in the regions close to flammability limits and for stoichiometric mixtures have been identified and explained. The equilibrium model has been validated for varied temperatures and pressures representative of initial conditions that may be present in the containment during accidents. Special emphasis has been given to the understanding of the role of dissociation and its effect on equilibrium pressure, temperature and species concentrations.

Analytical Model for Estimation of Heat Transfer in Gas Metal ARC Weldingtorch Nozzle

An analytical model for estimation of heat flow behaviour in gas metal arc welding torch nozzle and contact tip have been worked out. The variation in heat flow behaviour under different locations has been satisfactorily analysed. The theoretical model may provide wider opportunity to design different GMAW torch nozzle for welding of various plate thicknesses and groove design.

An Improved Analytical Model for Prediction of Heat Generation in Angular Contact Ball Bearing

High cutting speeds and feed rates are essential requirements of a machine tool to achieve enhanced performance. The performance of high speed spindle is significantly influenced by the thermal behavior of bearings. The prediction of more accurate thermal behavior of spindle bearings largely depends on the quantification of heat generation at high speeds. In the present work, an improved analytical model for estimation of heat generation in angular contact ball bearings used in a high speed spindle is proposed. The proposed model takes into consideration the change in diametral clearance after assembly and during operation owing to thermal expansion of bearing parts, which in turn influences the gyroscopic and spinning moments contributing to heat generation. The analysis reveals that the proposed model predicts the heat generation of bearings which has minimal deviation with experimental values, at speeds >2,000 rpm compared to previous models.

Delay model for dynamically switching coupled on-chip interconnects

Purpose – The purpose of this paper is to propose an analytical model for estimating propagation delay in coupled resistance-inductance-capacitance (RLC) interconnects. Design/methodology/approach – With higher frequency of operation, longer length of interconnect and fast transition time of the signal, the resistor capacitor (RC) models are not sufficient to estimate the delay accurately. To mitigate this problem, accurate delay models for coupled interconnects are required. In this paper, an analytical model for estimation of interconnect delay is developed for simultaneously switching lines. Two distributed RLC lines coupled inductively and capacitively are considered. To validate the proposed model, SPICE results are compared with the proposed analytical results. Each line in the coupled structure is terminated by a capacitive load of 30fF. The driving signal is considered symmetrical with equal rise and fall time of 5 ps and OFF/ON time of 45 ps. The model is validated for both in-phase and out of phase switching of lines. Findings – It is observed that the model works well for both the phases of inputs switching. The derived expressions of delay exhibit complete physical insight, and the results obtained are in excellent agreement with SPICE results. Comparison of analytical delay with SPICE delay shows an average error of < 2.7 per cent. Originality/value – The analytical expressions for interconnect delay are derived for the first time under simultaneously switching scenario. This model is useful to estimate delay across the inductively and capacitively coupled interconnects.

OPTIMIZATION OF MULTI-FIDELITY DATA USING CO-KRIGING FOR HIGH DIMENSIONAL PROBLEMS

ABSTRACTThis paper deals with an efficient and multi-fidelity design strategy for high dimensional industrial problems. The most significant factors have been determined based on the Muschelknautz method of modeling (MM) using the screening approach. For cyclone separator, only four (from seven) geometrical parameters are significant. An optimized sampling plan based on random Latin hypercube (LHS) has been used to fit Co-Kriging based on CFD data and an analytical model for estimation of pressure drop. Co-Kriging exhibits better accuracy than ordinary Kriging and blind Kriging if only the high fidelity data is used. For global optimization, the Co-Kriging surrogate in conjunction with genetic algorithms (GA) is used. CFD simulations based on the Reynolds stress turbulence model are also used in this study. A new set of geometrical ratios (design) has been obtained (optimized) to achieve minimum pressure drop. A comparison of numerical simulation of the new design and the Stairmand design confirms the superior performance of the new design compared to the Stairmand design.

A two-phase design space exploration strategy for system-level real-time application mapping onto MPSoC

In this paper, we present a two-phase design space exploration (DSE) approach to address the problem of real-time application mapping on a flexible MPSoC platform. Our approach is composed of two independent phases – analytical estimation/pruning and system simulation – communicating via a well-defined interface. The strength of the resulting strategy is twofold. On one hand, it is capable of combining the benefits of analytical models and simulation tools (i.e., speed and accuracy). And on the other hand, separating pruning and evaluation phases facilitates the integration of different or additional pruning techniques as well as other existing simulation tools. Finally, we also present several proof-of-concept DSE experiments to illustrate distinct aspects and capabilities of our framework. These experimental results reveal that our approach, compared to other approaches based only on analytical estimation models or simulations guided by e.g. genetic algorithms, not only can explore a large design space and reach a valid solution in a time-efficient way, but also can provide solutions optimizing resource usage efficiency, system traffic and processor load balancing.

Analytical Model for Estimation of Maximum Normal Stress in Steel Beam‐Columns Based on Wireless Measurement of Average Strains from Vibrating Wire Strain Gages

AbstractIn this article, an analytical model is developed for estimation of the maximum normal stress in a beam‐column member subjected simultaneously to an axial load and bending moments. The analytical model is derived by defining the relationship between the maximum strain and average strains measured wirelessly from vibrating wire strain gages. On the basis of the experimental tests on a two‐dimensional steel frame structure with beam‐column members, the performance of the estimation model is evaluated by comparing the maximum strains directly obtained from electrical strain gages and the estimated maximum strains from the model. Using the model, a practical monitoring of the maximum stress in steel beam‐columns is made possible by measuring three average strains at arbitrary locations.

Simple analytical models for estimating the queue lengths from probe vehicles at traffic signals

As mobile traffic sensor technology gets more attention, mathematical models are being developed that utilize this new data type in various intelligent transportation systems applications. This study introduces simple analytical estimation models for queue lengths from tracked or probe vehicles at traffic signals using stochastic modeling approach. Developed models estimate cycle-to-cycle queue lengths by using primary parameters such as arrival rate, probe vehicle proportions, and signal phase durations. Valuable probability distributions and moment generating functions for probe information types are formulated. Fully analytical closed-form expressions are given for the case ignoring the overflow queue and approximation models are presented for the overflow case. Derived models are compared with the results from VISSIM-microscopic simulation. Analytical steady-state and cycle-to-cycle estimation errors are also derived. Numerical examples are shown for the errors of these estimators that change with probe vehicle market penetration levels, arrival rates, and volume-to-capacity ratios.

Analytical model for estimation of digging forces and specific energy of cable shovel

An analytical algorithm for the estimation of the resistance forces exerted on the dipper of a cable shovel and the specific energy consumed in the cutting-loading process is presented. Forces due to payload and to cutting of geomaterials under given initial conditions, cutting trajectory of the bucket, bucket's design, and geomaterial properties are analytically computed. The excavation process has been modeled by means of a kinematical shovel model, as well as of dynamic payload and cutting resistance models. For the calculation of the cutting forces, a logsandwich passive failure mechanism of the geomaterial is considered, as has been found by considering that a slip surface propagates like a mixed mode crack. Subsequently, the Upper-Bound theorem of Limit Analysis Theory is applied for the approximate calculation of the maximum reacting forces exerted on the dipper of the cable shovel. This algorithm has been implemented into an Excel™ spreadsheet to facilitate user-friendly, transparent calculations and built-in data analysis techniques. Its use is demonstrated with a realistic application of a medium-sized shovel. It was found, among others, that the specific energy of cutting exhibits a size effect, such that it decreases as the (-1)-power of the cutting depth for the considered example application.

A simple analytical model for estimation of melt film variables in thermoplastic vibration welding

The strength of vibration welds of thermoplastics is governed by the weld zone microstructure, which in turn, is closely tied to the welding process variables, such as the thickness of the weld melt film and the temperature profiles therein. The mathematical model described in this report is aimed at describing the role of the rheology of the melt—specifically the magnitude and shear rate dependence of the melt viscosity—in governing the melt film variables during the steady state penetration phase (Phase III) of vibration welding. The steady state momentum balance and heat transfer within the melt film are solved by using the power law model for viscosity. Closed-form analytical expressions are obtained for estimating the melt film thickness, the shear rates, and the temperature field within the film. This model has been used to estimate weld zone variables for four different polymers displaying a wide range of viscosities and shear thinning behaviors. POLYM. ENG. SCI., 54:499–511, 2014. © 2013 Society of Plastics Engineers

Urban link travel time estimation based on sparse probe vehicle data

In the urban signalized network, travel time estimation is a challenging subject especially because urban travel times are intrinsically uncertain due to the fluctuations in traffic demand and supply, traffic signals, stochastic arrivals at the intersections, etc. In this paper, probe vehicles are used as traffic sensors to collect traffic data (speeds, positions and time stamps) in an urban road network. However, due to the low polling frequencies (e.g. 1min or 5min), travel times recorded by probe vehicles provide only partial link or route travel times. This paper focuses on the estimation of complete link travel times. Based on the information collected by probe vehicles, a three-layer neural network model is proposed to estimate complete link travel time for individual probe vehicle traversing the link. This model is discussed and compared with an analytical estimation model which was developed by Hellinga et al. (2008). The performance of these two models are evaluated with data derived from VISSIM simulation model. Results suggest that the Artificial Neural Network model outperforms the analytical model.

Hadoop and memcached: Performance and power characterization and analysis

Given the rapid expansion in cloud computing in the past few years, there is a driving necessity of having cloud workloads running on a backend servers analyzed and characterized for performance and power consumption. In this research, we focus on Hadoop framework and Memcached, which are distributed model frameworks for processing large scale data intensive applications for different purposes. Hadoop is used for short jobs requiring low response time; it is a popular open source implementation of MapReduce for the analysis of large datasets, while Memcached is a high performance distributed memory object caching system that could speed up throughput of web applications by reducing the effect of bottlenecks on database load. In this paper, we characterize different workloads running on Hadoop framework and Memcached for different processor configurations and microarchitecture parameters. We implement an analytical estimation model for performance and power using different server processor microarchitecture parameters. The proposed analytical estimation model uses analytical method to scale different processor microarchitecture parameters such as CPI with respect to processor core frequency. We also propose an analytical model to estimate power consumption scaling for different processor core frequency. The combination of both performance and power consumption analytical models enables the estimation of performance per watt for different cloud benchmarks. The proposed estimation models are verified to estimate power and performance with less than 10% error deviation.

Analytical model for estimation of eddy current and power loss in conducting plate and its application

A model is developed to study the eddy current induced in a thin conducting but nonmagnetic plate of finite size when exposed to a time varying magnetic field. The applied field may be uniform or vary in space. This model can accurately estimate the eddy current contour in the plate and loss due to eddy current. Power losses for plates of various dimensions and at different frequencies are calculated to establish the accuracy of the model. We have also calculated the magnetic field generated by the induced eddy current when the plate of finite size is placed between the two parallel poles of a dipole magnet made of magnetic material of very high permeability. The force acting on the plate due to the interaction of the induced eddy current and the applied external field is also calculated. The model can predict the time variation of force and eddy current. The model may be applicable to understand the effect of eddy current on the vacuum chamber of an accelerator. Various other applications, where this model is useful, are also reported. The results are compared against the results obtained by a simulation using a finite element based code. Here the rectangular plate is considered but the model can be applicable for other geometries as well.

A New Mathematical Model for Force Gravity Drainage in Fractured Porous Media

In force gas/oil gravity drainage process in fractured porous media, gas is flowing in both matrix and fractures leading to produce a finite gas pressure gradient. Consequently, viscous force plays an important role for displacing matrix oil toward fractures in addition to gravity force that is required to be modeled appropriately. A new analytical model for estimation of steady state oil saturation distribution with assumption of fixed gas pressure gradient throughout the matrix is presented. Moreover, based on some results of this analytical model a different numerical formulation is developed to predict the performance of oil production process. Comparison of the results obtained from this numerical model with the results of a conventional simulator demonstrates that the newly developed model can be applied with satisfactory accuracy. Numerical simulations show that the viscous displacement in fractured porous media can reduce the capillary threshold height, and thus it suggests the force gravity drainage as a favorable production mechanism when the matrix length is close to the threshold height.

UDSM subthreshold leakage model for NMOS transistor stacks

In this paper, a new, analytical model for subthreshold leakage estimation in the ultra deep submicron (UDSM) realm is proposed. Most previous attempts at subthreshold leakage estimation in transistor stacks are not tailored for the UDSM realm and are based on either a look up table approach, and/or assume that all the transistors in the stack have a fixed width. The analytical estimation model proposed in this paper is capable of estimating subthreshold leakage in UDSM NMOS transistor stacks with different transistor widths. The model achieves this by estimating the stack nodal voltages. In this paper, transistor stacks of two, three and four transistors are considered. Compared to SPICE simulations using PTM's BSIM4 models, our analytical model achieved an average error of 8.1% for the one, two, three and four transistor stacks for 65, 45 and 32 nm CMOS process technologies. The model also exhibits significant runtime savings when compared with SPICE.

Incorporating Uncertainty into the Estimation of the Passing Sight Distance Requirements

Abstract: Passing sight distance (PSD) is provided to ensure the safety of passing maneuvers on two lane two way roads. Many random variables determine the minimum length required for a safe passing maneuver. Current PSD design practices replace these random variables by single‐value means in the calculation process, disregarding their inherent variations, which results in a single‐value PSD design criteria. The main objective of the article is to derive a PSD distribution that accounts for the variations in the contributing random variables. Two models are devised, a Monte‐Carlo simulation model used to obtain the PSD distribution and a closed form analytical estimation model used for verification purposes. The Monte‐Carlo simulation model uses random sampling to select the values of the contributing parameters from their corresponding distributions in each run. The analytical model accounts for each parameter variation by using their means and standard deviations in a closed form estimation method. The means and standard deviations of the PSD using both models are compared for verification purposes. Both models use the same PSD formulation. The analysis is conducted for a design speed of 80 Km/h (50 mph). A PSD distribution is developed accordingly. The results of both models differ only by less than 2%. The obtained distribution is used to estimate the reliability index of the current PSD standards at a design speed of 80 Km/h (50 mph).

A New Analytical Model for Estimation of Scratch‐Induced Damage in Brittle Solids

Scratch tests are of fundamental interest both for understanding machining‐induced damage and for evaluating the scratch resistance of brittle materials. An improved blister field model for the scratch process is proposed where the blister field strength is explicitly determined in terms of the material properties, loading conditions, and geometry of the scratch tool. Additionally, one new expanding cylindrical cavity model is implemented to estimate the plastic zone size surrounding the scratch groove. A quantitative evaluation of the damage zone size is conducted by combining the above two models. The predicted damage zone sizes are in good agreement with the results available elsewhere in literature.

Development of analytical models for estimation of urban stormwater runoff

The estimation of urban stormwater runoff volume is usually of fundamental importance in the determination of the relative magnitudes of storage capacity and treatment rate for various storage/treatment facilities and in the evaluation of system runoff quantity and quality control performances. Recognizing the increasingly complex nature of urbanized watersheds, stormwater runoff volumes estimated without adequate consideration of the rainfall–runoff transformation process may be not reliable, and desired levels of system performance control may not be achieved. In contrast to the continuous simulation approach, derived probability distribution theory is employed in the development of event-based analytical probabilistic models for runoff volume. As a key element in the model development, different types of the rainfall–runoff transformations are formulated in light of various hydrological considerations associated with conceptualizing runoff generation mechanisms. The emphasis of this paper is to illustrate methodologies in the development of analytical probabilistic models for runoff volumes and to demonstrate that analytical models can be derived with various degrees of complexity based on different types of rainfall–runoff transformations. The verification of the developed analytical models is performed in case studies. By comparing the results from analytical models to those from continuous simulation, it is concluded that the closed-form analytical models not only demonstrate the capability of providing comparable results to continuous simulation, but also can be highly efficient and flexible in the estimation of urban stormwater runoff volumes.

Analytical estimation of torque enhancement of the SR machine with saw-shaped (shark) pole surfaces

The paper presents an electromagnetic analysis of the switched-reluctance (SR) machine with saw-shaped (shark) pole surfaces. This design aspect facilitates an increase of the ‘maximum/minimum’ inductance ratio, relative to the flat-pole structure, and, as such, it has drawn attention as a concept for the enhancement of the ‘torque/volume’ ratio. The analysis is based on the analytical model for estimation of the minimum and maximum inductances, which determine the extreme flux-linkage against current characteristics. These characteristics are used to predict the average phase torque at a constant current, from a given set of geometric parameters and the B–H curve describing the machine. The optimisation of the axial airgap profile is carried out by varying the tooth angle and the axial airgap pitch of the shark structure, while the other geometric parameters were kept the same as in the conventional (flat-pole) machine, which was optimised to produce the maximum torque/volume ratio. The maximum torque achievable with the shark machine is compared with the torque of the conventional SR machine at their rated currents.