Chen Model Research Articles

Lattice Boltzmann simulation of low-Reynolds-number cavitating contracting-nozzle flow interacting with a moving valve

Investigating internal-injector cavitating flow dynamics is difficult but important. The interaction of nozzle cavitation with the moving needle valve dictates the fuel mass flow rate and therefore spray combustion performance and emissions. In the present study, a two-dimensional low-Reynolds-number cavitating contracting-nozzle flow interacting with a moving valve is simulated using the lattice Boltzmann (LB) method. The Bhatnagar–Gross–Krook algorithm coupled with the immersed boundary method and an improved pseudo-potential multiphase flow model are employed and further developed based on the open-source LB code PALABOS. The performance of the immersed boundary method is first verified in a case where an oscillating cylinder moves according to a sine function in water. In order to improve the pseudo-potential model on its limitation of the density ratio, so to be used in engineering multiphase flow, the Carnahan–Starling equation of state is incorporated together with the exact difference method force scheme and an upgraded interaction force term. The upgraded pseudo-potential model proves via validations to be effective in improving numerical stability at large density ratios. With a seamless cooperation of the improved Shan–Chen model and the immersed boundary method achieved in PALABOS, cavitation in a contracting nozzle is simulated for a whole cycle of the valve motion. Cavitation dynamics under different fuel mass flow rates is investigated. It is found that cavitation dynamics, including interface conditions, cavitation bubble distributions, and inside-bubble vapor-phase flow fields, is distinctly different when the flow path is widely open and completely shut by the valve.

Validating the Entrepreneurial Intention Model on the University Students in Saudi Arabia

The main objective of this paper is to examine the applicability of Linan and Chen's entrepreneurial intention model (EIM) in predicting the entrepreneurial intention. EIM is an adaptation of the Theory of Planned Behavior that focuses on entrepreneurial intention and hypothesizing slightly different patterns of relationship with regards to subjective norms. The model also includes human capital and demographic factors. Snowball sampling method was used to collect data using the entrepreneurial intention questionnaire (EIQ) through several social media platforms. The survey indicates that the overall entrepreneurial intention of Saudi students is high (mean = 5.41). Eight out of the seventeen hypothesized relationships were found to be significant. Among the demographic variables, gender-personal attitude was significant whereas self employment experience and years of business education were found to be significantly related with perceived behavioral control. The statistical analysis using partial least square structural equation modelling validated the model. All the three antecedents of entrepreneurial intention were significantly related with entrepreneurial intention. The results of this study will help policy makers to get deep understanding into the phenomenon of entrepreneurship among Saudi university students and thereby develop a conducive environment. This study also validates the entrepreneurial intention model in a different cultural context.

China Markets and Global Stock Return Predictability

This paper explores the China equity market's impact on the global equity markets through the lens of asset pricing. We study the predictive properties of the lagged China returns for global stock returns and find that the lagged China returns can significantly predict other markets' stock returns, but not vice versa. We augmented three selected global equity pricing models (Chen, Roll, and Ross's model (CRR), Ang and Bekaert's model (AB), and Rapach, Strauss, and Zhou's model (RSZ)) with the lagged China returns respectively, and find that these popular global stock return predictors cannot explain the predictive power of the lagged China returns. Moreover, we find that only the lagged China returns can lead the international returns at the one-month horizon but not the lagged US returns. Further evidence reveals it is due to that the information diffusion of the China market occurs at the longer-horizons (e.g. one-month) while the information diffusion of the US market occurs at the shorter-horizons (e.g. one-week). Lastly, we documented that the lagged China returns during the low investor-attention period have stronger predictability compared to the predictive performance during the high attention period, which is in line with the information friction theory that when the attention-constrained investors make investment decisions they fail to allocate attention to certain economic state variables, which causes the slow information diffusion across markets and leads to the cross-market return predictability. Overall, our results indicate that the lagged China returns should be regarded as a global state variable that helps us predict future stock returns.

A systematic evaluation of biomethane production from sugarcane trash pretreated by different methods

Biomethane production was systematically evaluated with sugarcane trash pretreated by liquid hot water (LHW), dilute acid (DA) and KOH solutions. Multiple linear regression analysis identified glucan in pretreated solid residue as well as C5 sugars and acetic acid in pretreatment hydrolysate as the key parameters affecting biomethane potentials. Moreover, biomethane production was best simulated using Chen & Hashimoto model with a predicted highest methane yield of 187 mL/g initial total solids (TS) based on LHW (130 °C for 15 min) and KOH (10% on trash, 150 °C for 60 min) pretreatments. KOH pretreatment led to a biomethane yield of 167 mL/g initial TS at day 25, 82%, 34% and 33% higher than those achieved with untreated and pretreated trash samples with optimal LHW and DA conditions, respectively. This study led to the identification of best kinetic model and pretreatment condition for biomethane production from sugarcane trash through a systematic evaluation.

Predicting Wind Wave Suppression on Irregular Long Waves

The applicability of the wind wave suppression model developed by Chen and Belcher (2000) to irregular wave environments is investigated in this study. Monochromatic and irregular wave environments were simulated in the W2 (Wind/Wave) laboratory at the University of Maine under varying wind speeds. The Chen and Belcher (2000) model accurately predicts the reduction of the energy density of the wind waves in the presence of the monochromatic waves as a function of wave steepness, but under predicts this energy dissipation for the irregular waves. This is due to the consideration of a single wave frequency in the estimation of the growth rate and wave-induced stress of the monochromatic waves. The same formulations for the growth rate and wave-induced stress cannot be applied to irregular waves because their spectra contain energy over a wide range of frequencies. A revised version of the model is proposed to account for the energy contained within multiple wave frequencies from the power spectra for the mechanically generated irregular waves. The revised model shows improved results when applied to irregular wave environments.

Mechanical and Wear Properties of Aluminum-Based Nanocomposites Fabricated through Ultrasonic Assisted Stir Casting

Abstract The aluminum alloy AA6061 with 0.004, 0.008, 0.012, and 0.016 volume fractions of silicon carbide (SiCp) nanocomposites were fabricated using a semi-solid stirring assisted ultrasonic cavitation technique. Specimens are tested for morphology, density, mechanical, and wear properties. The density, strength, and microhardness of the nanocomposites increased with the increase of SiCp nano-reinforcement particles in the matrix. The yield strength of the SiCp-reinforced nanocomposites was evaluated by considering various strengthening mechanisms. It is found that the yield strength of the nanocomposites increased by 96 % for 0.004, 172 % for 0.008, 158 % for 0.012, and 206 % for 0.016 volume fractions of SiCp compared to the base alloy. The dislocation mismatch effect and Orowan strengthening effect are found to play a significant role in the SiCp-reinforced AA6061 nanocomposites. The dislocation mismatch effect increased with the reinforcement particles’ size reduction in the matrix. The Orowan strengthening effect increased up to 1.56 nm critical size of SiCp, and above that it decreased slightly. The experimental results are compared to predicted results obtained from various analytical models. The experimental results are observed to be in close agreement with the Mirza and Chen model. The wear loss of nanocomposites decreased with an increase in the nano-sized SiCp reinforcement quantity in the matrix. The amount of 0.004, 0.008, 0.012, and 0.016 volume fractions of nano-sized SiCp reinforcement additions to the AA6061 alloy matrix decreases the wear coefficient by 19.23 %, 38.46 %, 57.69 %, and 62.69 %, respectively. The worn surfaces were also analyzed using a scanning electron microscope and energy-dispersive X-rays.

Lattice Boltzmann simulations of droplet dynamics in two-phase separation with temperature field

This paper adds a temperature field based on the Shan–Chen model and constructs a new model. The two-phase separation, fluid flow, and heat transfer characteristics under the temperature field were studied by using this model. The performance of the three processes of collision, interface opening, and coalescence experienced by droplet formation was analyzed in detail. The results show that the velocity and temperature on the liquid film of the droplet are symmetric with respect to the central position of the liquid film. Moreover, the droplet velocity is also symmetric about the center of the droplet, which provides a theoretical basis for the droplet to maintain stability. By changing the wall temperature difference, the temperature distribution formula in the square cavity is proposed, which is highly consistent with the simulated value, and the maximum error is 10.1%. The proposed new model makes a meaningful supplement to the improvement of two-phase separation.

Characterization of forming limits at fracture for aluminum alloy 6K21-T4 sheets in non-linear strain paths using a biaxial tension/shear loading test

A good knowledge of forming limits at fracture (FLF) for aluminum sheets exhibiting poor formability at room temperature in various non-linear strain paths (N-LSPs) is essential for fully exploiting their forming ability and avoiding their fracture failure. However, the FLF over a wide range of strain states in N-LSPs with pre-strain paths between uniaxial tension and simple shear cannot be determined through the existing two-stage loading test methods. To solve the problem and fill the gap, a new two-stage loading test method employing an optimized butterfly specimen is proposed in this paper, in which strain path changes are controlled by changing biaxial loading conditions acting on the specimen. To validate the capability of the new test method to characterize the FLF in the N-LSPs and investigate the effect of the loading path changes on aluminum 6K21-T4 sheet formability at fracture, different proportional and non-proportional loading experiments using the butterfly specimen obtained from the aluminum sheets are performed. Experimental results indicate that the forming limit strains at fracture over a wide scope of strain states in the N-LSPs can be effectively determined by utilizing the proposed method, thus filling the gap mentioned above. Additionally, four newly developed ductile fracture criteria (a new model proposed in this paper, Hu−Chen 2017, Lou−Huh 2012 and MMC3) together with a non-linear damage accumulation rule (N-LDAR) are employed to forecast the FLF for the 6K21-T4 sheets in the N-LSPs. The results show that both the proposed new model with the N-LDAR and the Hu−Chen model along with the N-LDAR can provide the highest prediction accuracy for the FLF in the N-LSPs. However, the prediction accuracy of the proposed model is much higher that of the Hu−Chen 2017 model for aluminum alloy 5083-O sheets.

Prediction of Indian Monsoon Rainfall by Interval based Simplified High Order Fuzzy Time Series Model

Rain is of uttermost importance for agriculture based economies. Most of the Asian countries, India in particular largely depend on a good rainfall. The prediction of rainfall will not only help government to make better future policies but also farmers and agro based companies can make better future management. Rainfall forecasting involves high degree of uncertainty and for such conditions fuzzy time series and other soft computing techniques are best to deal with. The utility of a forecasting method lies with the accuracy with the predicted values. In this paper rainfall prediction by fuzzy time series model is proposed in which two difference values of the interval corresponding to the fuzzified forecasted value is proposed. This model is tested on real time data of average monsoon rainfall in India. The predicted values are compared with Chen model. The results show that the proposed model have less error compared to Chen’s model.

Analysis Prediction of Prambanan Temple Visitors with Fuzzy Time Series Chen Model and Seasonal Auto Regressive Integrated Moving Average (SARIMA) Model

The number of visitors in tourist attractions are almost always changes each time, even for tourist attractions that are already well-known among local and foreign people, usually will tend to increase at certain times, as in the Prambanan Temple. Based on data from TWC (Taman Wisata Candi) unit office, the number of visitors of Prambanan Temple during holidays at the end of 2018 increased by 8% from the previous year. Because of its increase, the manager of tourist attractions must always try to provide the best service. Therefore, the manager of Prambanan Temple needs to know the prediction of the number of visitors in the future so that they can prepare services and innovations to increase its attractiveness. The data of Prambanan Temple visitors number is seasonal, so the visitors number prediction at Prambanan Temple will be determined using the method for seasonal data. This research tries to compare the two methods, namely Fuzzy Time Series Chen Model and Seasonal Auto Regressive Integrated Moving Average (SARIMA) Model. The results of these methods are the visitors number prediction with different errors, so it can be seen which method is better between the two.

Numerical Investigation of Binary Fluid Flow through Propped Fractures by Lattice Boltzmann Method

Abstract In this paper, a pore-scale multiphase, multicomponent Shan–Chen model with proper pressure boundary scheme is developed and implemented to model binary flows in porous media, which enable...

A Flexible Skewed Link Model for Ordinal Outcomes: An Application to Infertility

BACKGROUND: An important issue in modeling categorical response data is the choice of the links. The commonly used complementary log-log link is inclined to link misspecification due to its positive and fixed skewness parameter.
 AIM: The objective of this paper is to introduce a flexible skewed link function for modeling ordinal data with some covariates.
 METHODS: We introduce a flexible skewed link model for the cumulative ordinal regression model based on Chen model.
 RESULTS: The main advantage suggested by the proposed links is the skewed link provide much more identifiable than the existing skewed links. The propriety of posterior distributions under proper and improper priors is explored in detail. An efficient Markov chain Monte Carlo algorithm is developed for sampling from the posterior distribution.
 CONCLUSION: The proposed methodology is motivated and illustrated by ovary hyperstimulation syndrome data.

Comparison and evaluation of Shan–Chen model and most commonly used equations of state in multiphase lattice Boltzmann method

A method to couple the Equation of State (EoS) with the Shan–Chen model (SC) is proposed in this paper. The difference between previously proposed approaches and the one developed here is in the manner of determining parameters of the EoS, which are a function of the critical properties of a substance. The modified relationships of the parameter that controls the strength of the inter-particle force as a function of temperature are developed for each EoS. These modified relationships eliminate the difference between pressures calculated by the SC model and each EoS. A comparison between the SC model and different popular EoSs is presented based on the proposed approach. Four models—the SC model, van der Waals EoS, Redlich–Kwong EoS, and Carnahan and Starling' EoS—are evaluated and compared, and the sign of the strength-controlling parameter (G) is discussed. The effects of the range of coexistence density, an arbitrary constant (ρo), temperature, and G on surface tension are discussed. The results of simulations show that the SC model sometimes yields negative values of surface tension when ρo is set below 1.5. Therefore, ρo should be set to 1 or ≥ 1.5.

Assessment of seismic damage on frame structures across the earth fissure under earthquake

An accurate evaluation of structural damage is essential to performance-based seismic design for the structure across the earth fissure. By comparing the calculation results from three commonly used damage models and the experimental results, a weighted combination method using Chen model was selected in this paper as the seismic damage evaluation. A numerical model considering the soil-structure interaction (SSI) was proposed using ABAQUS software. The model was calibrated by comparing with the experimental results. The results from the analysis indicated that, for the structure across the earth fissure, the existence of earth fissure changed the damage distribution of the structural members. The damage of structural members in the hanging wall was greater than that in the foot wall. Besides, the earth fissure enlarged the damage degree of the structural members at the same location and changed the position of the weak story. Moreover, the damage degree of the structure across the earth fissure was greater than that of the structure without the earth fissure under the same excitation. It is expected that the results from this research would enhance the understanding of the performance-based seismic design for the structure across the earth fissure.

Influence of fluid flow rate on the fouling resistance of calcium sulfate aqueous solution in subcooled flow boiling condition

Fouling is one of the customarily happened, fundamental and expensive problems in heat transfer systems. It causes the reduction in heat transfer performance of the heat exchangers, energy loss and also, damage to the apparatus. Effect of fluid flow rate on the salt deposition was complicated in the previous researches. In this paper, a comprehensive rigorous investigation was performed to make clear the effect of fluid flow rate of calcium sulfate aqueous solution on the heat transfer coefficient and fouling resistance in subcooled flow boiling condition. Large numbers of experiments performed at different flow rates (2.5–11.5 l/min), solution concentrations (1.75–2.20 g/l), fluid bulk temperatures (55–75 °C), and heat fluxes (8–95 kW/m2). Chen model, Gungor and Winterton model, and Kandlikar model approved pure water experimental data. It was found that increasing the heat flux increased the fouling rate and consequently, sharply decreased the heat transfer coefficient. It was also found that increase in the flow rate may cause both increase or decrease of the fouling layer, which depends on the applied heat flux. At low heat fluxes, deposition is mass transfer controlled, and increasing Re enhances the fouling rate while at high heat fluxes the deposition is chemical reaction controlled, and incresing Re decreases the fouling rate.

Fish Production Forecasting in India using Nested Interval Based Fuzzy Time Series Model

The livestock and agriculture is like lifeline of Indian villagers and economy. India is ranked first in livestock population and second in fish production. Fish is major part of eating in south and most of eastern part of India and use aquaculture for fish production India s also a major producer of fish through aquaculture, and ranks second in the world. In such condition forecasting of livestock is important in making policies and marketing, planning of products related to livestock and fishes. Fuzzy time series (FTS) is of great importance for such forecasting. But the problem with FTS forecast lies with the accuracy. There are many methods for linguistic values as variables for data of time series, but limitations starts with the error in forecasted and actual value. The present work studies the forecasting of fish production in India rainfall forecasting by FTS using two interval differences is proposed. The presented method is tested on the official data of deptt. of Animal Husbandry, Dairying and Fisheries, Government of India and compared with Chen’s models used for university enrollment. The forecasted values shows better result compared to Chen model.

Signal flow graph and control of realizable autonomous nonlinear Chen model with quaternion variables

In this work, we continue our study of autonomous nonlinear dynamical systems with quaternion variables. We present a novel chaotic Chen system with quaternion variables. This system in real form is high (nine) dimensional. We study the dynamics and basic properties of this model with quaternion variables. We also evaluate the stability of the trivial points and restrict the conditions under which the nonlinear novel quaternion Chen system has negative, zero, or positive Lyapunov exponents. A signal flow graph and an electronic circuit implementation are designed, analyzed, and constructed to realize the novel Chen system. The control problem of chaotic nonlinear systems with quaternion variables is investigated. We propose and design an approach to build a controller for these systems. The viability and usefulness of the suggested approach are illustrated by an application to the chaotic Chen model with quaternion variables. Using the proposed method, the attractors of the quaternion Chen model are transformed to trivial fixed point, quasi-periodic, or periodic (limit cycle) states. The mathematical results for the controller according to this method are confirmed numerically.

Co-opting the International Writing Program during the Cold War

Abstract This article examines the Hong Kong writer Gu Cangwu 古蒼梧 (1945–) and his grassroots activism during the Cold War, namely, his appropriation of the University of Iowa's International Writing Program (IWP). At the IWP from 1970 to 1971, Gu grew critical of US foreign policy, coedited a newsletter produced in the IWP offices, participated in political demonstrations, and published correspondence in Hong Kong in support of the Baodiao movement. The author argues that Gu's activities co-opted a Cold War institution to promote collective political action among the Chinese diaspora and, importantly, among audiences back in Hong Kong, amplified political resistance against both the United States and the United Kingdom. An examination of Gu's writings, including his correspondence, poems, and 2012 faux memoir Jiu jian 舊箋 (Old Letters), in relation to Kuan-hsing Chen's model of “Asia as method” and minjian society, establishes how Gu's political awakening in the United States and the overall student-led Baodiao movement enlarges Chen's conceptual framework. Rather than arising out of indigenous practices, the transpacific movement began overseas among the Chinese diaspora and, in the eyes of Gu, led to genuine political change in Hong Kong.

Circus Ring to Zoo to Museum: The Fragility of Factors in Characteristic-based Asset Pricing Models

Economically relevant factors in asset pricing models should impound information on the future path of state variables that drive asset risk premia. Imposing this condition, we investigate which publicly available characteristics predict individual stock returns during the sample period used by Fama and French (1993) i.e. their discovery period and the post-1993 or out-of-sample period. We find four characteristics have significant predictive power, in the cross-section, over and above that of their factors. In the out-of-sample period, five new characteristics become significant predictors. Similar results are seen for the Chen and Zhang (2010) model. Next, we find that characteristics that forecast stock returns before and after major economic events are very different. Finally, we find that the ability of characteristics to reflect economic uncertainty and sentiment changes in sign and magnitude over time- often vanishing altogether. Our results suggest that the search for a unique characteristic-based asset pricing model is unlikely to be fruitful given the secular variation in the relation between the sources of macroeconomic risks and firm-level characteristics.

How Consumers Justify Their Unethical Behavior: The Role of Moral Recognition Strategies (Moral Rationalization, and Decoupling), Complemented by Culture, on the Purchase of Counterfeits in Pakistan.

Moral recognition, defined as an individual’s interpretation of a situation as a moral dilemma. However, individuals will not constantly interpret situations as a moral dilemma in the same way with the same intensity under all conditions. literature suggests that when two conditions of moral recognition are met (Moral rationalization, and decoupling), individuals will interpret a situation as a moral dilemma differently. In Moral rationalization, individuals use to reconstruct immoral actions into less immoral actions. Thus, allows them to violate moral principles while preserving some semblance of being Moral like purchasing counterfeits due to their low prices. Here, consumers are more likely to be benefit-seeking by restructuring their actions to be less immoral, i.e. searching for a relevant justification for morality (involving moral justification, euphemistic language, advantageous comparison, displacement of responsibility, diffusion of responsibility, distortion of consequences, attribution of blame; Bandura et al.1996), coordinating justification with situations, and reaching a judgment. Moral decoupling is defined as the psychological process chosen to defend improper conduct, by which one separates judgments of performance from judgments of morality (Bhattacharjee et al.2013). When individuals adopt this strategy, they focus on the social benefits (i.e., image, status consumption, etc.) and economic benefits (i.e., perceived fashion content, physical appearance, performance, scarcity, etc.). Chen et. al. (2018) linked these two strategies in an empirical assessment to explore the effect of dimensions of moral recognition (moral rationalization and moral decoupling) on counterfeit purchases mediated by moral judgment and perceived benefits respectively. We modified the Chen model with the complementary effect of materialistic culture in this relationship. We argue that moral recognition firstly affects counterfeit purchase (CP) through Moral rationalization, and then through moral judgment in a two-step mediation. Secondly, through moral decoupling and further through perceived benefits. Thirdly, directly affecting CP complemented by materialistic culture as a moderator. Empirical validity was established by conducting a survey using a close-ended questionnaire. Data was collected from 230 consumers and analyzed using confirmatory factor analysis and structured equation modeling. The results suggested that moral recognition seems to limit purchase intention (PI) directly. Similarly, it neutralizes Moral Rationalization (MR), and Decoupling (MD) behaviors. Moreover, MR tends to positively affect PI both directly, and well as indirectly through moral judgment (MJ). Similarly, MD also has a direct and positive effect on PI, as well as perceived benefits (PB), however, PB and PI relationship was not substantiated. Hence, MR seems to negatively affect PI through MD, as well as through MR and MJ as a first and second-order mediator. Lastly, materialism seems to promote counterfeit purchase, at the same time positively complement the effect of MR on PI, in a way that MR would have a more pronounced effect on PI in case of the higher materialistic consumer.