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Nowadays, rapid prototyping is emerging as end use product in low volume. The accuracy of the fabricated components depends on various process parameters. Process parameters used in this investigation are layer thickness (150, 200 and 250 µm), infill pattern (linear, hexagonal and star fill), raster angle (0°, 45° and 90°) and infill density (40, 60 and 80%). Linear and radial dimension of knuckle joint are selected for the response factor.

The experiments are design by using response surface methodology (RSM). Four design variables at three levels are used to examine their influence on percentage error in linear dimension and radial dimension of the component. A prototype Knuckle joint is selected as component. Minitab-14 software is used for the design of experiments.

Experimental measure data is analyzed by using “smaller is better” quality characteristics. A regression model for the forecasting of percentage error in linear and radial dimension is developed. The developed model is within precision range. The optimum level of process for linear and radial dimensions are obtained: layer thickness of 150 µm, Infill pattern of linear, Raster angle of 90° and infill density of 40%.

It proves that both the mathematical model is significant and can be able to approximate the desired output value close to the accurate dimensions. While comparing the calculated F-values for both linear and radial dimension with the standard table (F-table, 0.05), it is found that at the given set of degree of freedom the standard F-values (6.61) is lower for that regression, linear, square and interaction source of the predicted model, for which p-values have already less than 0.05. It is desirable for significant process parameters.

The dimensional accuracy with respect to average percentage error of FDM produced knuckle joint is successfully examined. The effect of process parameters, namely, layer thickness, infill pattern, raster angle and infill density on average percentage error was investigated by RSM and analysis of variance table.

The novelty of this work lies in the fact that only few studies are available in archival literature related to influence of these process parameters on percentage error in linear and radial dimension for Polycarbonate (PC) material.

The novelty of this work lies in the fact only few studies are available in archival literature related to influence of these process parameters on percentage error in linear and radial dimension for Polycarbonate (PC) material.

The purpose of this paper is to examine the relationship between stock prices and exchange rates in 12 OECD countries.

The authors examine the nexus of stock prices and exchange rates for 12 OECD countries by using the vector error correction model, the bounds testing methodology and linear and non‐linear Granger causality methods.

The empirical results substantiate that a long‐run level equilibrium relationship among the exchange rates and stock prices exists in only seven out of twelve countries. The results of the linear causality tests indicate that significant short‐run and long‐run causal relationships exist between the two financial markets. The results of the tests for non‐linear Granger causality suggest that unidirectional and bidirectional non‐linear causal relationships exist between stock prices and exchange rates among these OECD countries.

The findings from this paper suggest the causal relationships between stock prices and exchange rates are not only linear, but also non‐linear.

Gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the theoretical as well as practical points of view. The range of applications of FEMs in this area is wide and cannot be presented in a single paper; therefore aims to give the reader an encyclopaedic view on the subject. The bibliography at the end of the paper contains 2,025 references to papers, conference proceedings and theses/dissertations dealing with the analysis of beams, columns, rods, bars, cables, discs, blades, shafts, membranes, plates and shells that were published in 1992‐1995.

This paper aims to present an approach for calibrating the numerical models of dynamical systems that have spatially localized nonlinear components. The approach implements the extended constitutive relation error (ECRE) method using multi-harmonic coefficients and is conceived to separate the errors in the representation of the global, linear and local, nonlinear components of the dynamical system through a two-step process.

The first step focuses on the system’s predominantly linear dynamic response under a low magnitude periodic excitation. In this step, the discrepancy between measured and predicted multi-harmonic coefficients is calculated in terms of residual energy. This residual energy is in turn used to spatially locate errors in the model, through which one can identify the erroneous model inputs which govern the linear behavior that need to be calibrated. The second step involves measuring the system’s nonlinear dynamic response under a high magnitude periodic excitation. In this step, the response measurements under both low and high magnitude excitation are used to iteratively calibrate the identified linear and nonlinear input parameters.

When model error is present in both linear and nonlinear components, the proposed iterative combined multi-harmonic balance method (MHB)-ECRE calibration approach has shown superiority to the conventional MHB-ECRE method, while providing more reliable calibration results of the nonlinear parameter with less dependency on a priori knowledge of the associated linear system.

This two-step process is advantageous as it reduces the confounding effects of the uncertain model parameters associated with the linear and locally nonlinear components of the system.

The traditional network scheduling methods such as the Critical Path Method (CPM), Programme Evaluation Review Technique (PERT), and bar charting are typically not effective for the planning of linear construction projects. Linear scheduling methods, on the other hand, model the progress of repetitive activities in sloping lines and are more effective for linear modelling and analysis. Nonetheless, their use in the construction industry has so far been very limited. Among other reasons for this is the unfamiliarity of construction personnel with these techniques, which plays a major role in hampering their application. This paper introduces a graphically based approach to assist in the linear programming (LP) modelling of linear scheduling analysis. The Planning & Optimization for Linear Operations (POLO) system provides a graphic LP modelling environment in which model formulation can be easily accomplished in a graphic and interactive fashion. Thus, the application of linear scheduling methods can be facilitated. The Isle of Palms Connector Bridge project in Mount Pleasant, South Carolina is used to demonstrate the use of the system.

The purpose of this paper is to investigate how performance of linear assets can be analysed and displayed, considering both the technical asset and the user context, to simplify cognitive tasks of planning and decision making.

Linear, or continuous assets, such as roads, railways, electrical grids and pipelines, are large, geographically spread out technical systems. Linear assets are comprised of system, subsystem and component levels. Thus, asset managers are involved with each level of the linear asset; asset management has strategic, tactical and operational levels. A methodology is developed to link together the technical and organisational levels and to measure asset performance considering their spatial extension. Geographical location and time are used as independent variables.

For performance measurement of linear assets, it is found that the spatial extension is an equally generic dimension as time is for technical assets in general. Furthermore, as linear assets actually are combinations of linear and point assets; separate analysis of these assets is a prerequisite. Asset performance has been studied in a case study in terms failures and cost; the results indicate that the methodology visualise poor, as well as good, performance in an easy to interpret manner. Besides, the results indicate that other parameters related to dependability can be presented in a similar way.

This study highlights the importance of including the spatial or geographical extension of linear assets in infrastructure managers’ performance measurement. It is believed that the methodology can make planning and decision making more effective by pointing out improvement areas in technical assets, in a way that is appealing to both technicians and managers.

As infrastructure managers are improving their analysis and visualisation of performance, the public's interest of following the information increases, which in turn contributes to the connection between infrastructure managers and the public.

The presented methodology and case study analysed performance in function of both the technical and organisational levels, including the spatial component. It is believed that the methodology for analysing and visualising performance of linear assets is distinctive.

A linear and geometrically non‐linear computation of a laminated composite torispherical shell subjected to internal pressure was performed by using the layered finite element whose formulation is based on degeneration principle. Geometric non‐linearity in terms of large deformations with total Lagrangian formulation was taken into account. The effect of the lamination schemes on geometric non‐linear behaviour and stress resultant distributions was analysed. The fibre directions have not a great influence on the shape of the load‐displacement curves. In contrast to the hoop stress resultant distribution, the moment distribution is significantly influenced by the lamination schemes. The influence of the lamination schemes on bending moments is greater in non‐linear than in linear computations. Likewise, the effect of the fibre orientation is greater on the hoop than on the meridional moment distribution. In unsymmetric laminated shells the values of the hoop moments exceed those of the meridional moments which is a considerable difference from metallic isotropic shells.

The purpose of this paper is to examine the price–volume relationship in the bitcoin market to validate near-stock properties of bitcoin.

Daily data of bitcoin returns, returns volatility and trading volume (TV) are utilized for the period August 17, 2010–April 16, 2017. Linear and non-linear causality tests are employed to examine price–volume relationship in the bitcoin market.

The linear causality analysis indicates that the bitcoin TV cannot be used to predict return; however, the reverse causality is significant. In contrast, the non-linear causality analysis shows that there are non-linear feedbacks between the bitcoin TV and returns. The bitcoin TV, which represents new information, leads to price changes, and large positive price changes lead to increased trading activity. Similarly, in recent periods (post-break period), the results of the non-linear causality test show a unidirectional causality from TV to the volatility of returns.

This study uses the average index value of major bitcoin exchanges. But further research on this relationship using data from different bitcoin exchanges may provide further insights into the price–volume relationship of bitcoin and its near-stock properties.

These findings from the non-linear causality analysis, therefore, suggest that investors cannot simply base their decisions on the linear dynamics of the bitcoin market. This is because new information in terms of the TV is neither linearly related to the price nor it is a one-to-one kind of relationship as most investors commonly understand it to be. Rather, investors’ decisions should be based on non-linear models, in general, and the best-fitting non-linear model, in particular.

The study examines bitcoin’s near-stock properties in a price–volume relationship framework with the help of both linear and non-linear causality tests, which to the best of the authors’ knowledge remains unexplored.

Aims to discuss iron loss analysis and experimenting with linear oscillating actuator for linear compressor.

The iron loss analysis of the linear oscillating actuator is performed by using ANSYS and iron loss curves, which is obtained by an Epstein test apparatus.

The way to calculate the iron loss of the linear oscillating actuator for the linear compressor and the method to experiment the iron loss of that can be studied.

Iron loss analysis of the linear compressor considering the motor part and the structure part is needed.

Each iron loss analysis method examined here can be used to analyze the iron loss of the linear motor.

Introduction Operations research, i.e. the application of scientific methodology to operational problems in the search for improved understanding and control, can be said to have started with the application of mathematical tools to military problems of supply bombing and strategy, during the Second World War. Post‐war these tools were applied to business problems, particularly production scheduling, inventory control and physical distribution because of the acute shortages of goods and the numerical aspects of these problems.