Incorporating legacy soil data to minimize errors in salinity change detection: a case study of Darab Plain,Iran

The results of a 1990 soil survey of a salinized region in Darab Plain, southern Iran, were combined with soil sampling data taken in 2002 from the same locations and employed as a basis for salinity change detection in the region. New preprocessing of satellite imagery was used, along with statistical analysis of the digital number (DN)?salinity relationship, in order to determine salinization of the area. Removal of outliers on the basis of interfering land uses improved the correlations. Nonlinear regression (NLR) in the form y?=?a +?bx ^α provided a suitable predictor of salinity (y, dS m^?1) for both 1990 and 2002 based on DNs (x). Among the 12 tested methods of salinity classification in this study, the six salinity class method with intervals 0–4, 4–10, 10–32, 32–64, 64–80 and >80 dS m^–1 was selected. A series of accuracy assessments through a trial-and-error procedure was the basis of the selection of the best method and led to a final accuracy of 91%. About 42% of the lands located on ‘no saline’ and ‘low salinity’ classes in 1990 had changed to the ‘medium’, ‘very high’ and ‘new agricultural land’ classes in 2002.     

Transactive energy management for optimal scheduling of interconnected microgrids with hydrogen energy storage

In recent years, renewable energy sources (RESs) have attracted substantial attention due to carbon-free and cost-effective advantages that have made them one of the main sources of energy generation in the modern structure of the power grid. This paper proposes the stochastic day-ahead scheduling model for optimal energy management of renewable-based microgrids. In this paper, each microgrid is equipped with 100% RESs including the PV system and wind turbine for full pollutant-free energy generation while the hydrogen energy storage (HES) system is used for alleviating the intermittences of the RESs aiming to dynamically balance the energy during a day. To model the fluctuations such as day-ahead market price in the microgrids, the autoregressive integrated moving average and fast forward selection methods are exerted for scenario production and reduction, respectively. Transactive energy as a sustainable and reliable technique is considered for controlling and coordinating energy sharing among the microgrids and the energy network for dynamic energy balancing in the deregulated environment. For energy management in the demand-side, the price and load response schemes are presented, aiming to revise the consumers' patterns in energy consumption in line with balancing energy and minimizing the microgrids’ energy cost. The effectiveness of the suggested model is validated using the modified IEEE 24-bus case study. The realistic modeling of the system based on the proposed model has led to an 8.51% increment in energy cost.     

Development of a high‐temperature two‐stage entrained flow gasifier model for the process of biomass gasification and syngas formation

This paper presents development of the Mitsubishi Heavy Industries (MHI) gasifier utilizing an analogy between a model with coal feedstock and the model with torrefied woody biomass. A computational fluid dynamics (CFD) model was primarily developed for coal gasification, and the simulation results were validated with similar published work and experimental measurements. The model was extended for the woody biomass to predict the gasifier performance under the gasification process. The results were used to compare the effect of fuel type on the gasifier performance and gaseous product compositions. The second‐level injection nozzles were modified tangentially, and the flow characteristics, species yields, and temperature were evaluated. The possibility of reducing the gasifier length from 13 to 8 m is also evaluated for different total length. The results revealed that using woody biomass leads to a decrease in the mole fraction of CO and H₂ at the gasifier outlet compared with coal. An opposite trend was observed for CO₂ and CH₄ compositions. The contributions of modified second‐level nozzles to the total gas composition and exit temperature only account for less than 3%. Reducing the gasifier length from 13 to 8 m increased the exit temperature from 1289 to 1340 K, but the changes in the exit gas composition were less than 2%. The new design of the MHI gasifier can reduce the investment costs by reducing the gasifier length as well as using biomass instead of coal.     

Experimental Investigation and Artificial Neural Network Modeling of Warm Galvanization and Hardened Chromium Coatings Thickness Effects on Fatigue Life of AISI 1045 Carbon Steel

Journal of Failure Analysis and Prevention - In the present study, the main purpose is investigation of the coatings thickness effect on the fatigue life of AISI 1045 steel. Herein, two different...     

Fault-aware grid scheduling using performance prediction by workload modeling

Computational grids hold great promise in utilizing geographically separated heterogeneous resources to solve large-scale complex problems. However, they suffer from a number of major technical hurdles, including distributed resource management and effective job scheduling. The main focus of this work is devoted on online scheduling of real time applications in distributed environments such as grids. Specifically, we are interested in applications with several independent tasks, each task with a prespecified lifecycle called deadline. Here, our goal is to schedule applications within an optimum overall time considering the specified deadlines. To achieve this, the resource performance prediction based on workload modeling and with the help of queuing techniques is employed. Afterward, a mathematical neural model is used to schedule the subtasks of the application. The main contributions of this work is to incorporate the impatiency factor as well as resource fault in performance modeling of nondedicated distributed systems, and also presenting an efficient and fast parallel scheduling algorithm under time constraint and heterogeneous resources. The proposed model is appropriate for implementation on parallel machines and in O(1) time. The new model was implemented on GridSim toolkit and under various conditions and with different parameters to evaluate the performance of scheduling algorithm. Simulation outcomes have shown that approximately in 87.8% of cases, our model schedules the tasks in such a way that all constraints are satisfied.

Practical human factors integration in the nuclear industry

Human factors integration (HFI) is the principal method for applying human factors to the development of socio-technical systems across safety-critical industry. The method has been developed successfully across industries from the defence sector right through to the medical sector, with various forms of application. Countries that are now seeing a nuclear renaissance have both the opportunity to apply new practices but also the challenge of true and cost-effective integration of human factors in new build projects. In this paper, we provide a framework of generic goals and a question set to guide appropriate and effective application of the method to project phases. The framework describes three main human factors goals of feasibility, usability and reliability and attempts to map these goals to project phases. We apply these concepts to the nuclear industry and indicate how practical HFI can facilitate a systems and lifecycle approach to human factors in the nuclear industry. We discuss some of the key socio-technical challenges now facing the industry.     

Phase Diagram of Na2O-B2O3-SiO2 System

The binary isopleth Na₂O.B₂O₃-SiO₂ of the Na₂O-B₂O₃ SiO₂ ternary system has been investigated. A phase diagram is presented based upon data from differential thermal analysis studies of prepared glasses and direct observation of the melting behavior using solid-state video imaging. Phase equilibria relations in the Na₂O-B₂O₃-SiO₂ ternary system have been reassessed by combining information from this study with existing data from the literature. A revised liquidus surface for the ternary is presented in which the form of the isotherms is updated.     

Firefly-inspired algorithm for discrete optimization problems: An application to manufacturing cell formation

The canonical firefly algorithm is basically developed for continuous optimization problems. However, lots of practical problems are formulated as discrete optimization problems. The main purpose of this paper is to present the discrete firefly algorithm (DFA) to solve discrete optimization problems. In the DFA, we define a firefly's position in terms of changes of probabilities that will be in one state or the other. Then by using this metaheuristic algorithm, the manufacturing cell formation problem is solved. To illustrate the behavior of the proposed model and verify the performance of the algorithm, we introduce a number of numerical examples to illustrate the use of the foregoing algorithm. The performance evaluation shows the effectiveness of the DFA. The proposed metaheuristic algorithm should thus be useful to both researchers and practitioners.