Optimizing the Runoff Estimation with HEC-HMS Model Using Spatial Evapotranspiration by the SEBS Model

Most of the commonly used hydrological models do not account for the actual evapotranspiration (ETa) as a key contributor to water loss in semi-arid/arid regions. In this study, the HEC-HMS (Hydrologic Engineering Center Hydrologic Modeling System) model was calibrated, modified, and its performance in simulating runoff resulting from short-duration rainfall events was evaluated. The model modifications included integrating spatially distributed ETa, calculated using the surface energy balance system (SEBS), into the model. Evaluating the model’s performance in simulating runoff showed that the default HEC-HMS model underestimated the runoff with root mean squared error (RMSE) of 0.14 m³/s (R²?=?0.92) while incorporating SEBS ETa into the model reduced RMSE to 0.01 m³/s (R²?=?0.99). The integration of HECHMS and SEBS resulted in smaller and more realistic latent heat flux estimates translated into a lower water loss rate and a higher magnitude of runoff simulated by the HECHMS model. The difference between runoff simulations using the default and modified model translated into an average of 95,000 m³ runoff per rainfall event (equal to seasonal water requirement of ten-hectare winter wheat) that could be planned and triggered for agricultural purposes, flood harvesting, and groundwater recharge in the region. The effect of ETa on the simulated runoff volume is expected to be more pronounced during high evaporative demand periods, longer rainfall events, and larger catchments. The outcome of this study signifies the importance of implementing accurate estimates of evapotranspiration into a hydrological model.

     

An FEC scheme combined with weighted scheduling to reduce multicast packet loss in IPTV over PON

Congestion is one of the most important challenges in optical networks. In a Passive Optical Network (PON), the Optical Line Terminal (OLT) is a bottleneck and congestion prone. In this paper, a framework is proposed with Forward Error Correction (FEC) at the IP layer combined with Weighted Round Robin (WRR) at the scheduling level to overcome packet-loss due to congestion in the OLT in order to achieve efficient video multicasting over PON. In the FEC scheme, Reed-Solomon (RS(n,k)) with erasure coding is used, where (n−k) erroneous symbols per n symbol blocks can be corrected. In our framework, an Internet Protocol TeleVision (IPTV) service provider uses the mentioned RS coding and generates redundant packets from regular IPTV packets in such a way that an Optical Network Unit (ONU) can recover lost packets from received packets, thus resulting in a better video quality. Simulation results show that using the proposed framework, an ONU can recover many lost packets and achieve better video quality under different traffic loads for its users. For instance, the proposed method can reduce packet loss rate by almost 55% and 10% under traffic load 0.9, respectively, compared with the Round Robin (RR) and WRR methods under symmetric traffic load. When High Receivers Queue (HRQ) traffic (i.e., traffic received by many users) is twice Low Receivers Queue (LRQ) traffic (i.e., traffic received by a small number of users), this reduction is almost 86% and 30% under traffic load 0.9. Finally, when LRQ traffic is twice HRQ traffic, the reduction in packet loss rate is almost 70% and 91% at traffic load 0.5.     

Identification and classification of ERP critical failure factors in Iranian industries

Implementation of Enterprise Resource Planning systems (ERPs) is a complex and costly process, which usually results in serious failures. The majority of previous studies and research projects have been conducted in identifying ERP Critical Success Factors (CSFs) rather than Critical Failure Factors (CFFs). On the other hand, most studies have been devoted to developed countries, while in developing countries, many companies have moved towards using such systems. The majority of IT/IS management standards and guidelines have been developed by technologically-leading countries. But developing countries, which mostly confront with especial challenges, have a different condition from the implicit assumptions of leading countries. Iran is one of these countries that many of its ERP implementation projects led to failure. There is no comprehensive study that identifies ERP CFFs in Iranian industries. The main purpose of this study is to identify such factors and classify them to help other industries, consultants and implementers to prevent failures in the implementation of ERP projects. So, at first, with the semi structured interviews and literature reviews, 47 failure factors were identified. After that a questionnaire developed and sent to ERP project team members in Iranian industries that failed in their ERP projects. Robust Exploratory Factor Analysis (EFA) has been used for data analysis, which finally classified critical failure factors in seven groups named as vendor and consultant, human resources, managerial, project management, processes, organizational and technical. The results of this study have provided a very useful reference for scholars and managers to identify the relevant issues of ERP projects failure in developing countries.     

Solving non-convex economic dispatch problem with valve point effects using modified group search optimizer method

This paper presents a novel solution based on the group search optimizer (GSO) methodology in order to determine the feasible optimal solution of the economic dispatch (ED) problem considering valve loading effects. The basic disadvantage of the original GSO algorithm is the fact that it gives a near-optimal solution rather than an optimal one in a limited runtime period. In this paper, a new modified group search optimizer (MGSO) is presented for improving the scrounger and ranger operators of GSO. The proposed MGSO is applied on different test systems and compared with most of the recent methodologies. The results show the effectiveness of the proposed method and prove that MGSO can be applicable for solving the power system economic load dispatch problem, especially in large scale power systems.     

Mathematical Modelling of the Methane Conversion to Heavier Hydrocarbons in a Plasma Reactor

In this study, mathematical modeling of fixed-bed plasma reactor operated under isothermal condition was investigated. In this process, methane and acetylene were the inputted feed and ethane, ethylene, propylene, propane, i-butane, and n-butane were the output products. The amount of methane conversion obtained was 12.7% for the former feed, however, if pure methane was inputted this conversion rose to 13.8%. Furthermore, the plasma process enhanced the conversion as well as the selectivity toward the desired product and yield. In the present study, when methane and acetylene were fed at a molar ratio of CH₄/C₂H₂ = 10 to the reactor, the selectivity of C₂, C₃, and C₄ hydrocarbons was determined to be 30%, 24%, and 44%; respectively. A comparison between the thermal and the plasma process showed that the methane conversion and production yield in the plasma process were higher than in the thermal process under the same operating conditions. On the other hand, product selectivity in the plasma process was determined to be lower than that of the thermal process. Finally, results of the methane conversion processes in the plasma phase were compared with those available in the open literature.     

Modeling project criticality in IT project portfolios

Today's IT project portfolios (ITPP) contain many projects and varied interdependencies. Depending on a project's criticality to the ITPP, a failure can have massive consequences. However, existing methods usually only assess overall project portfolio risk and do not account for the criticality of single projects and their dependencies. Applying Bayesian network modeling to ITPPs, we bridge this gap and extend the current body of knowledge for the information systems and project management literatures. Our new method analyzes single projects' criticality in a portfolio context by considering both transitive dependencies and different dependency types in an integrated way. Since we demonstrate that single projects' criticality can vary substantially, being aware of which projects are critical is a key success factor for ITPP management. For practitioners, our method provides a straightforward procedure to enhance ITPP risk management.     

Effects of carbon nanotubes and interphase properties on the interfacial conductivity and electrical conductivity of polymer nanocomposites

L_c is the minimum length of carbon nanotubes (CNTs) required for efficient transfer of filler conductivity to polymer matrix in polymer CNT nanocomposites (PCNTs). In this work, L_c is correlated with the dimensions of the CNTs and the interphase thickness. Subsequently, the interfacial conductivity as well as the effective length and concentration of CNTs are expressed by CNT and interphase properties. Moreover, a simple model for the tunneling conductivity of PCNTs is developed with these effective terms. The impacts of all parameters on L_c, the interfacial conductivity, the fraction of CNTs in the networks and the conductivity of the PCNT are explained and justified. In addition, the predictions of the percolation threshold and conductivity are compared with the experimental results of several samples. The desirable values of interfacial conductivity are achieved by thin, short and super‐conductive CNTs, high waviness and a thick interphase. However, thin and long CNTs, low waviness, a thick interphase, poor tunneling resistivity due to the polymer matrix and a short tunneling distance advantageously affect the conductivity of PCNTs, because they produce large conductive networks. The predictions also show good agreement with the experimental measurements of percolation threshold and conductivity, which confirms the developed equations. © 2020 Society of Chemical Industry     

Application of fuzzy c-means algorithm as a novel method to predict density of mixtures of Athabasca bitumen and heavy n-alkane

The significant number of oil reservoir are bitumen and heavy oil. One of the approaches to enhance oil recovery of these types of reservoir is dilution of reservoir oil by injection of a solvent such as tetradecane into the reservoirs to modify viscosity and density of reservoir fluids. In this investigation, an effective and robust estimating algorithm based on fuzzy c-means (FCM) algorithm was developed to predict density of mixtures of Athabasca bitumen and heavy n-alkane as function of temperature, pressure and weight percent of the solvent. The model outputs were compared to experimental data from literature in different conditions. The coefficients of determination for training and testing datasets are 0.9989 and 0.9988. The comparisons showed that the proposed model can be an applicable tool for predicting density of mixtures of bitumen and heavy n-alkane.     

Short communication: Heritability estimates for susceptibility to Mycobacterium avium subspecies paratuberculosis infection defined by ELISA and fecal culture test results in Jersey cattle

Paratuberculosis (Johne’s disease), an enteric disorder in ruminants caused by Mycobacterium avium ssp. paratuberculosis, causes economic losses in excess of $200 million annually to the US dairy industry. Costly diagnostic testing, cumbersome control programs, incurability, and ineffective vaccination all make M. avium ssp. paratuberculosis susceptibility a good candidate for genetic studies and genetic selection a potentially useful adjunct to management-based control programs. No report has been published for heritability of susceptibility to M. avium ssp. paratuberculosis infection in Jersey cattle. The objective of this study was to estimate variance components and heritability for susceptibility to M. avium ssp. paratuberculosis infection in US Jersey cattle. Data consisted of complete serum ELISA and partial fecal culture results on a total of 2,861 Jersey cows from 23 commercial herds throughout the United States after editing. Four M. avium ssp. paratuberculosis susceptibility phenotypes were defined using (1) ELISA sample-to-positive ratios as a continuous trait, (2) ELISA results as a binary trait (positive = 1, negative = 0), (3) ELISA results as an ordered categorical trait, and (4) a combined test in which ELISA and fecal culture results were both taken into account in a binary analysis. Three statistical models, including linear, binary threshold, and ordered threshold sire models, were used to analyze the data. All analyses were executed using the restricted maximum likelihood method in ASReml 3 software. The heritability estimates were low to moderate and ranged from 0.08 (±0.03) to 0.27 (±0.11) based on different trait definitions. The nonzero heritability indicates that susceptibility to M. avium ssp. paratuberculosis infection in Jersey cattle is influenced by genetic factors. Therefore, selection of the least susceptible animals could decrease genetic predisposition to M. avium ssp. paratuberculosis infection in Jersey populations in future generations.     

Modeling of tensile strength in polymer particulate nanocomposites based on material and interphase properties

In this work, a simple model is presented to determine tensile/yield strength in polymer nanocomposites containing spherical nanofillers based on material and interphase properties. The accuracy of the proposed model is estimated by comparing with the experimental strength of several samples from the literature. In addition, the effects of thickness (t) and tensile strength (σ_i) of the interphase as well as the radius (R) and volume fraction ( ) of the nanoparticles on the tensile strength are explained according to the proposed model. The high level of nanoparticle strength (more than 100 GPa) commonly leads to overestimates of the tensile strength of nanocomposites, whereas the assumption of correct interphase properties produces accurate calculations. The tensile strength of nanocomposites does not change at σ_i < 38 MPa, while it increases by 140% at t = 20 nm and σ_i = 90 MPa. However, a maximum 14% growth in tensile strength is obtained with the optimum values of = 0.04 and R = 10 nm. Therefore, the concentration and size of the nanoparticles have minor effects on the tensile strength of nanocomposites, but the major influences of interphase thickness and strength are pronounced. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44869.