A SIMPLE METHOD FOR ANALYSIS OF SLIDING STRUCTURES CONSIDERING VARIATIONS OF FRICTION COEFFICIENT

In this paper, the responses of multidegree of freedom (MDOF) structures on sliding foundations, subjected to harmonic or random base motions, are investigated taking into consideration the variations of friction forces. The variation of friction force is a consequence of variation of friction coefficient, which depends on such parameters as relative velocity and the existing pressure. Modelling of the friction force under the foundation raft is accomplished by using a fictitious rigid link with a rigid-perfectly plastic material. This results in identical equations of motion for the sliding structure, both in the sliding and nonsliding (stick) phases and considerably decreases the required number of time steps for the nonlinear analysis. Since the force in the link is of constant value, to consider the varying friction force, a compensatory force, which is the difference between the exact friction force and the constant force in the rigid link, is applied to the foundation raft. A model of variable friction coefficient for Teflon-steel interfaces is used for the assessment of the method and the results are compared with existing literature, through which, the capability of the method is illustrated. It is shown that by using exact model of friction lower values for the superstructure responses are predicted compared with those obtained by using Coulomb friction model. Furthermore the effect of the stiffness of the structure on the differences between the results of the two models is also studied.     

Numerical Study on the Peak Strength of Masonry Spandrels with Arches

This article presents a numerical study on the force-deformation behavior of masonry spandrels supported on arches which are analyzed using simplified micro models. The model is validated against results from quasi-static cyclic tests on masonry spandrels. A large range of spandrels with different arch geometries, material properties, and axial load ratios are studied. The numerical results are compared to peak strength values predicted with an existing mechanical model. Finally, estimates for the initial stiffness and the spandrel rotation associated with the onset of strength degradation are derived.     

Simulation Of Shake Table Tests on Out-of-Plane Masonry Buildings. Part (II): Combined Finite-Discrete Elements

ABSTRACT

Out-of-plane response of unreinforced masonry elements is frequently the most critical aspect of the seismic performance of existing masonry buildings. The response of such elements is usually governed by equilibrium rather than strength. Hence, it is customary to resort to rigid-body models, accounting for possible rotations, and/or sliding. However, the results of such analyses depend on the initial choice of the mechanism. In this article, the shaking-table experiments on a brick-masonry specimen, and on a stone-masonry specimen have been modeled by resorting to a combined finite-discrete element strategy. Despite the coarse discretization of both discrete and finite elements, the three-dimensional models are able to capture the experimentally observed multi-degree-of-freedom mechanisms, without any a priori assumption on the mechanism. A sensitivity analysis is carried out, addressing eight different parameters. The identification of the mechanism is sufficiently robust, but the assessment of its activation and failure is best done by combining the finite-discrete element model with a simplified model of the recognised mechanism.     

LEAST SQUARES ESTIMATES OF THE REGIONAL EMPLOYMENT MULTIPLIER: AN APPRAISAL*

Basically, we have attempted to show the following in the course of setting out the algebra of regression analysis of selected regional employment multiplier models: (1) When the basic features of the model are shaped by the assumption of an unlagged response of local employment to changes in export employment, the least squares estimates of the multipliers are highly sensitive to the export coefficients vector A, given the sample observation matrix X. In a completely disaggregated model such as Equation (21), the multipliers are solely determined by the export coefficients and thus are entirely independent of sample observations. However, this independence does not hold in the case of a partially disaggregated model. The identity relation is also destroyed when a lag relationship is introduced into a completely disaggregated model. (2) A simple lag model produces results bascially different from those obtained by an unlagged model if the overall differences between current and lagged observations are significant. (3) Given a matrix of sample observations on employment, it is possible to estimate the upper limits of a least-squares aggregate multiplier and its variance simply from knowledge of the export coefficients (4) The export coefficients vector has also an important bearing upon the correlation coefficient. The correlation is unity if and only if the export coefficients vector is proportional to the local employment coefficients vector, while it is zero if and only if the export coefficients vector is a vector all of whose elements are one. Also, the correlation coefficient is equal to one when a completely disaggregated model is used. There is finally the question of what these results mean in terms of the formulation of a multiplier model. First of all, in view of the crucial importance of the export coefficients and the difficulties of estimating them, most of the existing models do not seem to offer promising results. Furthermore, all the models examined here have made some simplifying assumption with respect to the constancy of the export coefficients. It remains highly uncertain whether these coefficients are reasonably stable over time. Of course, it would be theoretically more acceptable to relax the assumption of the invariance of export coefficients and to obtain such coefficients at different points of time for each industry. However, this would be accomplished only at the cost of increased difficulties of estimating larger numbers of export coefficients. In addition, there is some doubt as to the validity of the assumption that export employment is proportional to export sales. Since a lag relationship is important not only in terms of attempts to formulate multiplier models more realistically, but also in terms of its significant effect on the multiplier values obtained, the nature and the form of a lagged response and its estimation problems need to be investigated in depth. Finally, problems of least squares bias and efficiency, inference, and prediction which may arise in the context of various models presented here remain to be investigated. A detailed analysis of such problems must be the subject of further investigation.     

Computational Comparison of Five Maximal Covering Models for Locating Ambulances

This article categorizes existing maximum coverage optimization models for locating ambulances based on whether the models incorporate uncertainty about (1) ambulance availability and (2) response times. Data from Edmonton, Alberta, Canada are used to test five different models, using the approximate hypercube model to compare solution quality between models. The basic maximum covering model, which ignores these two sources of uncertainty, generates solutions that perform far worse than those generated by more sophisticated models. For a specified number of ambulances, a model that incorporates both sources of uncertainty generates a configuration that covers up to 26% more of the demand than the configuration produced by the basic model.     

Nonlinear Multivariate Spatial Modeling Using NLPCA and Pair‐Copulas

A novel geostatistical modeling approach is developed to model nonlinear multivariate spatial dependence using nonlinear principal component analysis (NLPCA) and pair‐copulas. In spatial studies, multivariate measurements are frequently collected at each location. The dependence between such measurements can be complex. In this article, a multivariate geostatistical model is developed that can capture both nonlinear spatial dependence across locations and nonlinear dependence between measurements at a particular location. Nonlinear multivariate dependence between spatial variables is removed using NLPCA. Subsequently, a pair‐copula based model is fitted to each transformed variable to model the univariate nonlinear spatial dependencies. NLPCA and pair‐copulas, within the proposed model, are compared with stepwise conditional transformation (SCT) and conventional kriging. The results show that, for the two case studies presented, the proposed model that utilizes NLPCA and pair‐copulas reproduces nonlinear multivariate structures and univariate distributions better than existing methods based on SCT and kriging.     

Simulation of Shake Table Tests on Out-of-Plane Masonry Buildings. Part (III): Two-Step FEM Approach

ABSTRACT

This article presents numerical simulations of two full-scale masonry structures which were tested on the shaking table within the scope of the workshop “Methods and challenges on the out-of-plane assessment of existing masonry buildings”. The numerical models have been developed on the basis of the blind-prediction models which have been improved after the publication of the test results. The solution procedure is divided into two steps with separate numerical simulations for each one. In the first step the collapse mechanism of the structure is determined by means of pushover analysis using a continuum, plasticity-based model. In the second step the dynamic response of the structure is simulated using a multibody model approach and frictional contacts. Results of the tests show reasonable, yet far from perfect predictive capabilities of the used numerical methods.     

Predictive Tri-Linear Benchmark Curve for In-Plane Behavior of Adobe Walls

In the present study, numerical simulations are conducted to estimate the in-plane response of adobe walls subjected to pseudo-static cyclic loading based on the finite element code ABAQUS. The simplified micro-modeling approach is adopted and an interface model reported in ABAQUS material library is applied as material model for zero-thickness interface elements. The comparison between obtained results and field test data results in good agreement. Parametric studies are carried out to evaluate the effectiveness of independent parameters changes on response of adobe walls. It is noted that mechanical properties of joints and adobe units play an active role on in-plane behavior of walls. A tri-linear benchmark curve is proposed to predict the response of aforementioned walls. In this regard, a statistical study is performed to derive the predictive tri-linear benchmark curve. The regressive analysis on 59 numerical models resulted in proposing predictive models. Finally, by comparing tri-linear curves obtained from the regressive analysis, numerical analysis, and experimental study, appropriate accuracy of theoretical model can be found.     

MODELLING OF RC BEAM-COLUMN JOINTS AND STRUCTURAL WALLS

The deformation of beam-column joints may contribute significantly to drift of reinforced concrete (RC) frames. In addition, failure may occur in the joints due to cumulative concrete crushing from applied beam and column moments, bond slip of embedded bars or shear failure as in the case of existing frames with nonductile detailing. When subjected to earthquake loading, failure in RC structural wall is similar to failure of frame joints as it may occur due to cumulative crushing from high flexural stresses, bond slip failure of lap splice, shear failure or a combination of various mechanisms of failure. It is important to include these behavioural characteristics in a simple model that can be used in the analysis of RC frames and RC walls to predict their response under earthquake loading and determine their failure modes.

Global macro models for the beam-column joint and for RC structural walls are developed. The proposed models represent shear and bond slip deformations as well as flexural deformations in the plastic hinge regions. The models are capable of idealising the potential failure mechanism due to crushing of concrete, bond slip or shear with allowance for the simultaneous progress in each mode. The model predictions are compared with available experimental data and good correlation is observed between analytical results and the test measurements.     

A Partitioning Model of Urban Retail Structure

A model based on renewal theory generates the number of retail establishments in a place as the outcome of a competitive partitioning process. The available market, measured for example by population or by existing retail sales, is shared among businesses until no market potential market remains. Competing businesses obtain different shares of the market, and the number of establishments is predicted as a discrete random variable. Several alternative formulations are presented of varying generality. One version is successfully tested, using GLIM, on ten business types (SIC two-digit classes) in 232 cities of New York State for 1977 and 1987. The model correctly predicts the form and the variance structure of the relationship between number of establishments and place size. It is shown how the model may be combined with models of city-size distributions to predict aggregate frequency distributions of retail establishments across urban systems.     

ECONOMIC GEOGRAPHY OF FIRMS AND SKILLED LABOR*

ABSTRACT This paper investigates the relationship between firm location and skilled‐labor location. While existing new economic geography (NEG) models could not explicitly analyze the relationship due to their assumptions, I construct a new NEG‐type model allowing for different location dynamics of firms and skilled labor for this objective. The main results are as follows. First, a relatively large pool of skilled labor attracts firms when trade costs are small, while it might repel firms when trade costs are sufficiently large. Second, assuming that skilled workers are mobile between regions, the model shows that skilled workers agglomerate faster than firms with decreasing trade costs. Third, the model supports the hypothesis that firms follow skilled labor rather than the reverse. These results are consistent to Indian and Chinese experiences, and some “creative‐class” or “skilled‐city” stories.     

A numerical model for gravity wave dissipation in the thermosphere

Two simplified models of internal gravity wave dissipation due to viscosity, thermal conduction and ion-drag, in a multilayered, isothermal thermosphere are developed. Each of these models uses the WKB approximation, ray theory and the time-averaged equation of energy conservation, but whereas one of the models (A) employs all of the gravity wave equations appropriate to a dissipative atmosphere, the other (B) does not. Results derived from these models for one particular wave are compared to each other and also to some previously published results of Klostermeyer, which employed a full-wave, model. A breakdown of the WKB approximation in the lower, non-isothermal thermosphere leads to models A and B underestimating the total dissipation there. In the middle thermosphere model A estimates the dissipation reasonably well, while model B grossly overestimates the dissipation. In the upper thermosphere model A underestimates the total upward energy flux, probably as a result of the neglect of coupling into the dissipative waves at these levels, while no energy remains in model B. Results from model A show that when dissipation due to viscosity and thermal conduction are included correctly and simultaneously, the dissipation due to viscosity can exceed that due to thermal conduction by a factor of three. It is argued that ray theory may either overestimate or underestimate the energy flux reaching the upper boundary of a thermospheric model depending on both its height and the particular thermospheric model used.     

Balancing Spatial and Non-Spatial Variation in Varying Coefficient Modeling: A Remedy for Spurious Correlation

This study discusses the importance of balancing spatial and non-spatial variation in spatial regression modeling. Unlike spatially varying coefficients (SVC) modeling, which is popular in spatial statistics, non-spatially varying coefficients (NVC) modeling has largely been unexplored in spatial fields. Nevertheless, as we will explain, consideration of non-spatial variation is needed not only to improve model accuracy but also to reduce spurious correlation among varying coefficients, which is a major problem in SVC modeling. We consider a Moran eigenvector approach modeling spatially and non-spatially varying coefficients (S&NVC). A Monte Carlo simulation experiment comparing our S&NVC model with existing SVC models suggests both modeling accuracy and computational efficiency for our approach. Beyond that, somewhat surprisingly, our approach identifies true and spurious correlations among coefficients nearly perfectly, even when usual SVC models suffer from severe spurious correlations. It implies that S&NVC model should be used even when the analysis purpose is modeling SVCs. Finally, our S&NVC model is employed to analyze a residential land price data set. Its results suggest existence of both spatial and non-spatial variation in regression coefficients in practice. The S&NVC model is now implemented in the R package spmoran.     

基于系统动力学的我国旅游景区门票定价研究

已有景区门票定价研究大都从现实景区数据出发,建立门票价格、景区属性和社会经济指标的多元回归模型。然而这种计量研究,并没有从景区门票定价的多目标性出发,也忽视了影响门票定价各因素之间的相互影响关系。本文构建ISM模型分析影响景区门票定价的主要因素及其相互关系,根据因素相互作用关系建立景区门票定价系统因果关系图和系统流图,并设定系统动力学方程。仿真结果显示,成本票价逐年下降并于2022年降至最低,而最终票价将呈现先降低后升高的趋势。     

Exploring Spatial Process Dynamics Using Irregular Cellular Automaton Models

Cellular automaton models have enjoyed popularity in recent years as easily constructed models of many complex spatial processes, particularly in the natural sciences, and more recently in geography also. Most such models adopt a regular lattice (often a grid) as the basis for the spatial relations of adjacency that govern evolution of the model. A number of variations on the cellular automaton formalism have been introduced in geography but the impact of such variations on the likely behavior of the models has not been explored. This paper proposes a method for beginning to explore these issues and suggests that this is a new approach to the investigation of the relationships between spatial structure and dynamics of spatial processes. A framework for this exploration is suggested, and details of the required methods and measures are provided. In particular, a measure of spatial pattern—spatial information—based on entropy concepts is introduced. Initial results from investigation along the proposed lines are reported, which suggest that a distinction can he made between spatially robust and fragile processes. Some implications of this result and the methodology presented are briefly discussed.     

Asymmetric Entrant Locaiton with a Discrete Consumer Distribution: Spatial Price Discrimination Versus Mill Pricing

In this paper I examine the profit-maximizing locations of entrants. Suppose that firms practice spatial price discrimination and consumer locations are discrete, such as five equally spaced towns on a roadway. With completely inelastic consumer demand an entrant between two existing firms is often indifferent between the symmetric (central) location and a continuum of asymmetric (noncentral) locations. However, downward-sloping consumer demand often causes the entrant to strictly prefer either of two asymmetric locations to any other location. These results are very different from those found in mill-pricing (free-on-board or f.o.b.-pricing) models.     

THE PURE THEORY OF HOUSEHOLD LOCATION AN AXIOMATIC APPROACH*

In this paper, I present an axiomatic basis for the neoclassical model of household location in a monocentric urban area. I generalize the existing framework and demonstrate that many of the conclusions derived using parametric models continue to hold even without the popularly assumed well-behaved utility and transportation cost functions.     

An Equity Model for Locating Environmentally Hazardous Facilities

This paper develops a multiobjective mathematical location model to identify possible locations for environmentally hazardous facilities. Risk and equity are recognized as the most important criteria in determining site selection. In contrast to earlier models, the equity objective explicitly considers the existing distribution of environmental burdens when siting new hazardous facilities. Proposed environmentally hazardous facilities are located so that the burdens associated with new and existing hazards are shared as equally as possible among all areas. The application of the model, in a case study of the Greenpoint/Williamsburg neighborhood in Brooklyn, New York, illustrates the trade‐offs associated with various risk and equity scenarios. Sensitivity analyses demonstrate how the existing distribution of environmental burdens may act as a constraint and limit the degree of equity that may be obtained when locating new facilities.     

Determining Market Areas Captured by Competitive Facilities: A Continuous Equilibrium Modeling Approach

Many existing models concerning locations and market areas of competitive facilities assume that customers patronize a facility based on distance to that facility, or perhaps on a function of distances between the customer and the different facilities available. Customers are generally assumed to be located at certain discrete demand points in a two-dimensional space, or continuously distributed over a one-dimensional line segment. In this paper these assumptions are relaxed by employment of a continuum optimization model to characterize the equilibrium choice behavior of customers for a given set of competitive facilities over a heterogeneous two-dimensional space. Customers are assumed to be scattered continuously over the space and each customer is assumed to choose a facility based on both congested travel time to the facility and on the attributes of the facility. The model is formulated as a calculus of variations problem and its optimality conditions are shown to be equivalent to the spatial customer-choice equilibrium conditions. An efficient numerical method using finite element technique is proposed and illustrated with a numerical example.     

Fitting Constrained Poisson Regression Models to Interurban Migration Flows

This paper demonstrates the effects of fitting singly and doubly constrained spatial interaction models using the Poisson regression approach. A large data set containing migration flows between labor market areas in Great Britain in 1970–71 is used. The results of fitting unconstrained, singly constrained, and doubly constrained models are compared with respect to goodness of fit and the interpretability of parameter estimates. The addition of other explanatory variables to the model is also explored.