Development of functional ionic liquids for separation and recovery of rare earth elements

“This research focused on the design and synthesis of task-specific ionic liquids for enhanced extraction and separation of rare earth elements (REEs). Two novel ammonium-based functional ionic liquids (FILs) with oxygen donating groups: trioctyl(2-ethoxy-2-oxoethyl)ammonium dihexyl diglycolamate, [OcGBOEt][DHDGA], and tricaprylmethylammonium dihexyl diglycolamate, [A336][DHDGA] were synthesized and tested for the recovery and separation of selected REEs from aqueous solutions. Functionalities with different denticities were incorporated into both anionic and cationic parts of ionic liquids, which are solely composed of incinerable atoms including C, H, O, and N. The structural, physical, and chemical properties of the synthesized FILs were studied using nuclear magnetic resonance (1H- and 13C-NMR), Fourier transform infrared spectroscopy (FTIR), high-resolution mass spectrometry (HRMS), thermal gravimetric analysis (TGA), disc scanning calorimetry (DSC) in addition to density and viscosity analysis. The influence of key process parameters on the extraction efficiency of the synthesized FILs was examined in detail using europium as an example of REEs. The extraction mechanism of the synthesized FILs was systematically investigated using FTIR and NMR spectroscopies in addition to the slope analysis approach. The better extractability, enhanced selectivity towards heavy rare earth, and improved loading capacity of the new FILs are the key advances of this research which will immensely contribute to the field of hydrometallurgical separation of REEs”--Abstract, page iii

Applying Bayesian networks to model uncertainty in project scheduling

PhDRisk Management has become an important part of Project Management. In spite of numerous advances in the field of Project Risk Management (PRM), handling uncertainty in complex projects still remains a challenge. An important component of Project Risk Management (PRM) is risk analysis, which attempts to measure risk and its impact on different project parameters such as time, cost and quality. By highlighting the trade-off between project parameters, the thesis concentrates on project time management under uncertainty. The earliest research incorporating uncertainty/risk in projects started in the late 1950’s. Since then, several techniques and tools have been introduced, and many of them are widely used and applied throughout different industries. However, they often fail to capture uncertainty properly and produce inaccurate, inconsistent and unreliable results. This is evident from consistent problems of cost and schedule overrun. The thesis will argue that the simulation-based techniques, as the dominant and state-of-the-art approach for modelling uncertainty in projects, suffers from serious shortcomings. More advanced techniques are required. Bayesian Networks (BNs), are a powerful technique for decision support under uncertainty that have attracted a lot of attention in different fields. However, applying BNs in project risk management is novel. The thesis aims to show that BN modelling can improve project risk assessment. A literature review explores the important limitations of the current practice of project scheduling under uncertainty. A new model is proposed which applies BNs for performing the famous Critical Path Method (CPM) calculation. The model subsumes the benefits of CPM while adding BN capability to properly capture different aspects of uncertainty in project scheduling

Fluid - Structure - Soil Interaction of Cylindrical Liquid Storage Tank Subjected to Horizontal Earthquake Loading

Shallow founded tanks are strategic structures used to store a variety of kind of liquids. The fluid develops hydrodynamic effect on solid domain of container during an earthquake. This paper provides the theoretical background for numerical model on seismic response of fluid-structure-soil interaction. The Finite Element Method (FEM) was used for seismic response of shallow founded cylindrical container. The Fluid- Structure-Soil interaction of shallow founded tank was analysed according to theories of I. Limit States - the ultimate limit state (ULS) and II. Limit States - the serviceability limit state (SLS) pursuant to EN 1997-1. Summary of the results: the maximum rotation of foundation is growing with the reduction of the stiffness of the subsoil and the vertical and horizontal bearing capacity depends on the strength properties of the subsoil

The Relationship between Innovative Behavior and Sustainable Development

This paper aims to review the previous studies in order to collect the effects of innovative behavior on sustainable development. However, there is just a limited research between innovative behavior and sustainable development. This paper provides a collection of prior studies which have been done regarding the relationship among innovative behavior, innovation, and sustainable development. The importance of this paper refers to sustainable development that is usually focused by companies, which are involved in economic, environmental, and social perspectives. Sustainable development and innovative behavior constitute engines of development today. Innovative behavior is related to the human behavior which can be related to problem recognition, idea generation, supporting idea and idea implementation.  This research attempts to review past studies for the purpose of justifying the relation between innovative behavior and sustainable development. Therefore, this paper calls to pay attention to such question as how the attributes of innovative behavior can effect sustainable development. Keywords: Sustainable development, Innovative behavio

A new approach for supply chain risk management: Mapping SCOR into Bayesian network

Purpose: Increase of costs and complexities in organizations beside the increase of uncertainty and risks have led the managers to use the risk management in order to decrease risk taking and deviation from goals. SCRM has a close relationship with supply chain performance. During the years different methods have been used by researchers in order to manage supply chain risk but most of them are either qualitative or quantitative. Supply chain operation reference (SCOR) is a standard model for SCP evaluation which have uncertainty in its metrics. In This paper by combining qualitative and quantitative metrics of SCOR, supply chain performance will be measured by Bayesian Networks. Design/methodology/approach: First qualitative assessment will be done by recognizing uncertain metrics of SCOR model and then by quantifying them, supply chain performance will be measured by Bayesian Networks (BNs) and supply chain operations reference (SCOR) in which making decision on uncertain variables will be done by predictive and diagnostic capabilities. Findings: After applying the proposed method in one of the biggest automotive companies in Iran, we identified key factors of supply chain performance based on SCOR model through predictive and diagnostic capability of Bayesian Networks. After sensitivity analysis, we find out that ‘Total cost’ and its criteria that include costs of labors, warranty, transportation and inventory have the widest range and most effect on supply chain performance. So, managers should take their importance into account for decision making. We can make decisions simply by running model in different situations. Research limitations/implications: A more precise model consisted of numerous factors but it is difficult and sometimes impossible to solve big models, if we insert all of them in a Bayesian model. We have adopted real world characteristics with our software and method abilities. On the other hand, fewer data exist for some of the performance metrics. Practical implications: Mangers often use simple qualitative metrics for SCRM. However, combining qualitative and quantitative metrics will be more useful. Industries can recognize the important uncertain metrics by predicting supply chain performance and diagnosing possible happenings. Originality/value: This paper proposed a Bayesian method based on SCOR metrics which has the ability to manage supply chain risks and improve supply chain performance. This is the only presented case study for measuring supply chain performance by SCOR metrics.Peer Reviewe

Investigations of Flare Gas Emissions in Taq Taq Oil Field on the Surrounding Land

Environmental pollution caused by oil takes many different forms; one of the most damaging sources is simply the combustion of oil products, such as a well flare burn-off. This paper presents the results of a survey of the agriculture lands around the Taq Taq Oil Production Company. The aim of the survey was to determine the potential contamination caused by the gas emissions from the well flares. Taq Taq field is located in the Kurdistan Region of Iraq, 60 km north of the giant Kirkuk oil field, 85 km south-east of Erbil and 120 km north-west of Suleimani. Samples of soil were collected from several locations around the site and analyzed to determine the content of Polycyclic Aromatic Hydrocarbons PAH present. A gas chromatography linked to a mass spectrometry (GCMS) machine was used for these measurements. The PAH contamination at each location of soil was determined and the 16-PAHs, as listed in the US Environmental Protection Agency (EPA) documentation were investigated. The average content of total PAH in all samples of the agricultural soil was 0.654 mg·kg-1 with the concentrations ranging from 0.310 to 0.869 mg·kg-1. It was found that the PAH concentrations decreased with increasing distance from the TTOPCO oil field, indicating that pollution was evident, the area close to the field being more affected by the gas pollution

A new approach for supply chain risk management: Mapping SCOR into Bayesian network

Purpose: Increase of costs and complexities in organizations beside the increase of uncertainty and risks have led the managers to use the risk management in order to decrease risk taking and deviation from goals. SCRM has a close relationship with supply chain performance. During the years different methods have been used by researchers in order to manage supply chain risk but most of them are either qualitative or quantitative. Supply chain operation reference (SCOR) is a standard model for SCP evaluation which have uncertainty in its metrics. In This paper by combining qualitative and quantitative metrics of SCOR, supply chain performance will be measured by Bayesian Networks. Design/methodology/approach: First qualitative assessment will be done by recognizing uncertain metrics of SCOR model and then by quantifying them, supply chain performance will be measured by Bayesian Networks (BNs) and supply chain operations reference (SCOR) in which making decision on uncertain variables will be done by predictive and diagnostic capabilities. Findings: After applying the proposed method in one of the biggest automotive companies in Iran, we identified key factors of supply chain performance based on SCOR model through predictive and diagnostic capability of Bayesian Networks. After sensitivity analysis, we find out that ‘Total cost’ and its criteria that include costs of labors, warranty, transportation and inventory have the widest range and most effect on supply chain performance. So, managers should take their importance into account for decision making. We can make decisions simply by running model in different situations. Research limitations/implications: A more precise model consisted of numerous factors but it is difficult and sometimes impossible to solve big models, if we insert all of them in a Bayesian model. We have adopted real world characteristics with our software and method abilities. On the other hand, fewer data exist for some of the performance metrics. Practical implications: Mangers often use simple qualitative metrics for SCRM. However, combining qualitative and quantitative metrics will be more useful. Industries can recognize the important uncertain metrics by predicting supply chain performance and diagnosing possible happenings. Originality/value: This paper proposed a Bayesian method based on SCOR metrics which has the ability to manage supply chain risks and improve supply chain performance. This is the only presented case study for measuring supply chain performance by SCOR metrics.Peer Reviewe

Exploring the advantages of content management systems for managing engineering knowledge in product-service systems

Knowledge management has drawn great interest in manufacturing industries and related business practices. With the requirement for better managing the massive data and knowledge generated during different lifecycle stages of products, manufacturing industries are looking for effective way to acquire, save, process and share knowledge from and between different stakeholders, so as to make appropriate decisions and continuously improve business operations. Current (conventional) engineering information systems in manufacturing applications, such as Enterprise Resource Planning, Computerized Maintenance Management and Product Lifecycle Management Systems are difficult to inter-operate and integrate with each other when dealing with growing amount of data and knowledge as a product goes through its lifecycle stages. As informational and communication technologies (ICT) are being developed much faster in other sectors such as financial, business and social media, it is important to explore the potential of latest ICT tools predominantly used in those sectors for engineering applications and identify any advantages and benefits over the conventional engineering information systems. This paper presents an experiment in using an Open Source Content Management System, for the implementation of a collaborative product-service system for the planning and execution of maintenance and service operations of high-value complex numerical control machine tools in advanced manufacturing systems