Search results

One of the most basic pieces of information useful to hospitality operations is gross sales, and the ability to forecast them is strategically important. These forecasts could provide powerful information to cut costs, increase efficient use of resources, and improve the ability to compete in a constantly changing environment. This study tests sophisticated, yet simple‐to‐use time series models to forecast sales. The results show that, with slight re‐arrangement of historical sales data, easy‐to‐use time series models can accurately forecast gross sales.

This paper aims to compare different univariate forecasting methods to provide a more accurate short-term forecasting model on the crude oil price for rendering a reference to manages.

Six different univariate methods, namely the classical decomposition model, the trigonometric regression model, the regression model with seasonal dummy variables, the grey forecast, the hybrid grey model and the seasonal autoregressive integrated moving average (SARIMA), have been used.

The authors found that the grey forecast is a reliable forecasting method for crude oil prices.

The contribution of this research study is using a small size of data and comparing the forecasting results of the six univariate methods. Three commonly used evaluation criteria, mean absolute error (MAE), root mean squared error (RMSE) and mean absolute percent error (MAPE), were adopted to evaluate the model performance. The outcome of this work can help predict the crude oil price.

The purpose of this study is to propose the time series decomposition approach to analyze and predict the failure data of the repairable systems.

This study employs NHPP to model the failure data. Initially, Nelson's graph method is employed to estimate the mean number of repairs and the MCRF value for the repairable system. Second, the time series decomposition approach is employed to predict the mean number of repairs and MCRF values.

The proposed method can analyze and predict the reliability for repairable systems. It can analyze the combined effect of trend‐cycle components and the seasonal component of the failure data.

This study only adopts simulated data to verify the proposed method. Future research may use other real products' failure data to verify the proposed method. The proposed method is superior to ARIMA and neural network model prediction techniques in the reliability of repairable systems.

Results in this study can provide a valuable reference for engineers when constructing quality feedback systems for assessing current quality conditions, providing logistical support, correcting product design, facilitating optimal component‐replacement and maintenance strategies, and ensuring that products meet quality requirements.

The time series decomposition approach was used to model and analyze software aging and software failure in 2007. However, the time series decomposition approach was rarely used for modeling and analyzing the failure data for repairable systems. This study proposes the time series decomposition approach to analyze and predict the failure data of the repairable systems and the proposed method is better than the ARIMA model and neural networks in predictive accuracy.

In order to avoid the problem of volumetric locking often encountered when using constant strain tetrahedral finite elements, the purpose of this paper is to present a new composite tetrahedron element which is especially designed for the combined finite-discrete element method (FDEM).

A ten-noded composite tetrahedral (COMPTet) finite element, composed of eight four-noded low order tetrahedrons, has been implemented based on Munjiza’s multiplicative decomposition approach. This approach naturally decomposes deformation into translation, rotation, plastic stretches, elastic stretches, volumetric stretches, shear stretches, etc. The problem of volumetric locking is avoided via a selective integration approach that allows for different constitutive components to be evaluated at different integration points.

A number of validation cases considering different loading and boundary conditions and different materials for the proposed element are presented. A practical application of the use of the COMPTet finite element is presented by quantitative comparison of numerical model results against simple theoretical estimates and results from acrylic fracturing experiments. All of these examples clearly show the capability of the composite element in eliminating volumetric locking.

For this tetrahedral element, the combination of “composite” and “low order sub-element” properties are good choices for FDEM dynamic fracture propagation simulations: in order to eliminate the volumetric locking, only the information from the sub-elements of the composite element are needed which is especially convenient for cases where re-meshing is necessary, and the low order sub-elements will enable robust contact interaction algorithms, which maintains both relatively high computational efficiency and accuracy.

We provide a method for automatically extending small‐strain state‐update algorithms and their correspondent consistent tangents into the finite deformation range within the framework of multiplicative plasticity. The procedure, when it applies, operates at the level of kinematics and, hence, can be implemented once and for all independently of the material‐specific details of the constitutive model. The versatility of the method is demonstrated by a numerical example.

This study aims to propose a novel viscoelastic–viscoplastic combined constitutive model for glassy amorphous polymers within the framework of thermodynamics at finite strain that is capable of capturing their rate-dependent inelastic mechanical behavior in wide ranges of deformation rate and amount.

The rheology model whose viscoelastic and viscoplastic elements are connected in series is set in accordance with the multi-mechanism theory. Then, the constitutive functions are formulated on the basis of the multiplicative decomposition of the deformation gradient implicated by the rheology model within the framework of thermodynamics. Dynamic mechanical analysis (DMA) and loading/unloading/no-load tests for polycarbonate (PC) are conducted to identify the material parameters and demonstrate the capability of the proposed model.

The performance was validated in comparison with the series of the test results with different rates and amounts of deformation before unloading together. It has been confirmed that the proposed model can accommodate various material behaviors empirically observed, such as rate-dependent elasticity, elastic hysteresis, strain softening, orientation hardening and strain recovery.

This paper presents a novel rheological constitutive model in which the viscoelastic element connected in series with the viscoplastic one exclusively represents the elastic behavior, and each material response is formulated according to the multiplicatively decomposed deformation gradients. In particular, the yield strength followed by the isotropic hardening reflects the relaxation characteristics in the viscoelastic constitutive functions so that the glass transition temperature could be variant within the wide range of deformation rate. Consequently, the model enables us to properly represent the loading process up to large deformation regime followed by unloading and no-load processes.

The purpose of this paper is to investigate the application of the element‐free Galerkin (EFG) method to the simulation of metal forming processes and to propose a strategy to deal with volumetric locking problem in this context.

The J₂ elastoplastic material model, employed in the work, assumes a multiplicative decomposition of the deformation gradient into an elastic and a plastic part and incorporates a non‐linear isotropic hardening response. The constitutive model is written in terms of the rotated Kirchhoff stress and the logarithmic strain measure. A Total Lagrangian formulation of the problem is considered in order to improve the computational performance of the proposed algorithm. The imposition of the essential boundary conditions and also of the unilateral contact with friction condition are made by the application of the Augmented Lagrangian method. Here, aspects related to the volumetric locking are investigated and an F‐bar approach is applied.

The results show that the proposed approach presents no volumetric locking phenomenon when using the mean dilation approach. Moreover, differently from finite element approximations, no hour‐glass instabilities in the deformation pattern are observed, avoiding in this way the need to devise additional stabilization procedures in the proposed procedure.

This paper demonstrates the implementation and validation of the mean dilation approach, in the scope of the EFG, which was successful in coping with the volumetric locking phenomena and presented no hour‐glass instabilities in the problem cases considered in this work.

This study examines forecast accuracy associated with the forecast of 55 revenue data series of 18 local governments. The last 18 months (6 quarters; or 2 years) of the data are held-out for accuracy evaluation. Results show that forecast software, damped trend methods, and simple exponential smoothing methods perform best with monthly and quarterly data; and use of monthly or quarterly data is marginally better than annualized data. For monthly data, there is no advantage to converting dollar values to real dollars before forecasting and reconverting using a forecasted index. With annual data, naïve methods can outperform exponential smoothing methods for some types of data; and real dollar conversion generally outperforms nominal dollars. The study suggests benchmark forecast errors and recommends a process for selecting a forecast method.

This paper aims to clarify the CO₂ emissions of global construction industries under the consideration of different patterns of international trade and thus to draw a comprehensive picture for understanding the international paths of CO₂ transfer to global construction industries.

This research inventories the CO₂ emissions induced by the final demand of 15 economies for construction products and explores the CO₂ intensities of these economies based on a multi-regional input–output model. This paper further decomposes CO₂ emissions into four components based on different patterns of international trade to estimate the roles of four patterns of international trade in shaping the environmental pressures from global construction industries.

The results indicate that the CO₂ intensities of the construction industries in Russia, India and China were higher than those in other economies, and the CO₂ intensities of global construction industries experienced a decline over the years 2000–2014. The decomposition analysis demonstrates that domestic and foreign CO₂ emissions accounted for 42.67 and 54.23%, respectively, of the CO₂ emissions of the construction industries in the 15 economies during the period 2000–2007. Although the major part of the CO₂ emissions of the construction industries come from domestic production systems, the final demand for construction products in the 15 economies caused substantial emissions in other economies. Further decomposition by upstream industrial production source indicates that 58.65% of domestic emissions and 66.53% of foreign emissions can be traced back to the electricity industry.

Although the major patterns of CO₂ emissions of the construction industry have been identified in this paper, the difficulty of understanding the relationship between upstream production industries or countries and the construction industry deserves more attention in the future research.

Previous research on inventorying CO₂ emissions has generally been limited to evaluating the impact of industrial consumption activities on national or global emission accounting, tending to ignore the effects of different international trade patterns on the change in industrial CO₂ emissions. This research is the first attempt to account for and decompose the CO₂ emissions of global construction industries under consideration of the effects of different patterns of international trade on environmental pressures. The decomposition and upstream industrial distributions of different patterns of CO₂ emission provide a comprehensive picture for better understanding of the emission pattern and source of the CO₂ emissions of global construction industries. The research outcomes reveal how the final demand of a country for construction products induces CO₂ emissions in both domestic and foreign systems, thus providing basic information and references for policy adjustment and strategy design in relation to mitigation of climate change and sustainable development.

The numerical simulation of metal forming processes follows a highly non‐linear analysis where general aspects such as elastoplasticity, finite deformation and contact mechanics are combined. Approximated solutions obtained by finite element techniques require strong computational effort, that contradicts the need of interactive industrial applications. The first part of the work deals with the description of the main elements of the formulation, with attention to mathematical modelling and the approximating algorithms in the incremental iterative frame of non‐linear analysis, ending with the results obtained in hot rolling simulation. The second part is dedicated to computational efficiency analysis and the presentation of the related methods and results obtained in this work.