Wear and frictional performance of metals under dry/waste cooking oil lubricant conditions

The development of recycled, renewable and sustainable products to replace fossil products is a vital concern from industrial, environmental and academic viewpoints. Lubricants are one of the synthetic products widely used in numerous fields of the manufacturing and industrial sectors. Furthermore in 2005, more than 38 million metric tons of oils were used in the lubrication techniques of various industrial applications in the United States (US). In other words, the need for alternative friendly lubricants needs to increase by about 36 billion gallons to meet expected demands in 2022. This need motivates the current investigation of the potential use of waste cooking oil as a lubricant for tribological applications. A review of the available literature reviewed no work related to this topic. However, many works have been conducted on vegetable oils and their potential as lubricant. The current study establishes the basis for the research in the area of waste cooking oil as a lubricant; focusing on the oil and its blend characteristics and applications in journal bearings. At the first stage of this study, comprehensive experiments were conducted on the wear and the frictional behaviour of brass, aluminium and mild steel metals sliding against a stainless steel counterface under dry contact condition for comparison purposes with the lubricant results. Furthermore, predicting the tribological performance of materials is a very complex task and many attempts to model the wear and frictional behaviour of materials have failed. In this study, the artificial neural networks approach is used as a tool to predict wear, roughness, interface temperature and the frictional behaviour of metals under different operating parameters. For the wear experiments under dry contact conditions, the wear and frictional performance of brass, aluminium and mild steel metals was investigated at different operating parameters: sliding distances (0 – 10.8 km) and applied loads (0 – 50 N) against a stainless steel counterface at a sliding velocity of 2.8 m/s. Experiments were performed using a block-on-ring (BOR) machine. To categorise the wear mechanism and damage features on the worn surfaces and the collected debris, scanning electron microscopy was used. A thermal imager was used to measure the interface temperature between the contacted bodies. The results of the dry tests revealed that the operating parameters significantly influence the wear and frictional behaviour of all the metals. Brass metal exhibited better wear and frictional behaviour compared to the other metals tested. This is mainly due to the presence of 4% of Pb which helped reduce the aggressiveness of the material removal. Three different wear mechanisms were observed: two-body abrasion (brass), three-body abrasion (mild steel) and adhesive (aluminium). Friction coefficient trends were almost steady for brass and mild steel, however, aluminium/stainless steel exhibited slight fluctuations due to the modifications of the worn surface due to the sliding. A biolubricant extracted from waste cooking oil (WCO) was developed in this study. Different blends of lubricant were prepared: fully synthetic 100%SO, 75%SO+25%WCO, 50%SO+50%WCO 25%SO+75%WCO and 100%WCO. The prepared waste cooking oil was blended with 5% (wt) of EVA copolymer and 2% (wt) of EC and synthetic oils. Viscosity, pour point and flash points of the blends were examined and compared with industrial lubricants, (10W-50, 15W-40, 5W-40, and 5W-30). The possibility of using WCO with its blend as a lubricant was tested using two techniques. First, a new tribology machine was designed and fabricated locally to study the wear and frictional performance of brass, aluminium and mild steel under lubricant conditions considering different sliding distances (up to 10.8 km), applied loads (10 N – 40 N) and sliding speed of 2.8 m/s at different lubricant temperatures (22oC, 40oC, 80oC). For consistent comparison purposes with the dry data, 113 kPa applied pressure was used as the dry contact condition was conducted mainly on 50N applied load which is equivalent to 113 kPa. This study found promising potential for the use of WCO as a lubricant from a viscosity viewpoint. The viscosity of the waste cooking oil was significantly enhanced with the addition of 5% (wt) of EVA copolymer and 2% (wt) of EC. Blending the waste cooking oil with the fully synthetic oil also showed good improvement in performance. Based on the viscosity data, it is found that the pure waste cooking oil is very comparable with W5-30 oil which is recommended for gasoline and diesel engines. Increasing the applied load reduced the specific wear rate due to the presence of the lubricant which assisted to absorb the heat in the interface and clear (polish) the rubbed surfaces. The lubricant temperature was the key in determining the wear behaviour of the materials. Increasing the temperature reduced the viscosity, leading to less lifting during the experiments (i.e. a high specific wear rate). Conversely, the lubricant temperature showed no remarkable influence on the frictional behaviour. This is mainly due to the chemical adsorption of the fatty acids on the worn surfaces which acted as coated layer. From the journal bearing testing results, the waste cooking oil and its blends exhibited a similar trend in oil pressure values to the ones obtained for the fully synthetic oil, thus demonstrating the potential of waste cooking oil and its blends for journal bearing applications. The complexity of predicting the wear and frictional performance of the materials motivates the tribologist to adopt an artificial neural network (ANN) approach, as it can be used to make such predictions with caution. In developing an ANN for this study, training function, performance and adopting functions were found to be the keys to predicting wear, roughness and interface temperature. The large input data of the friction coefficient (12009 x 3 x 3) made the prediction of friction coefficient difficult and led to poor ANN performance. Using individual inputs for each parameter and training the ANN in several steps improved the performance. About 95.5% prediction performance was recorded, particularly for the wear, roughness and interface temperature

Political Advertising In Kuwait - A Functional Discourse Analysis

Most political advertising studies focus on the U.S. or other western democracies like the U.K. and other European countries. In general, political advertising studies focused on the content of political advertising especially on the subject of issues vs. images in advertising. In addition, many studies of political advertising content focus on the topic of negative advertising. The practice of political advertising has been found to vary depending on the political and media structure within a country as well as cultural and legal elements. Therefore, the gap in the literature about the practice of political advertising in the Middle-East is worth examining as it is reasonable to expect different in the use of issue vs. image appeals and in terms of the use of negative advertising. This dissertation focuses on political advertisement content in Kuwait as one of the developing democracies in the Middle-East. One of the important cultural and political elements of Kuwaiti politics is the non-secular nature of the country according to the Kuwaiti constitution. The interest of the study is to explore the content appeals used in political advertising in Kuwait and compare it to relevant literature that examines advertising in the U.S and other parts of the world. In addition, comparisons of advertisements\u27 content between winners and losers in elections will be made to explore possible differences. Because of lack of previous studies about Kuwait, interviews with parliament members, candidates, campaign managers and advertising practitioners were done to give context and better understanding of the ads. Findings of both the qualitative and the quantitative parts of the study indicate unique practice of political advertising in Kuwait including lack of negative advertisements, which is a significant characteristic of political advertisement world wide. In addition, contrary to experts\u27 suggestions in the interviews, political advertisements in Kuwait uses more character based discourse than policy based discourse

Analytical Solutions and Multiscale Creep Analysis of Functionally Graded Cylindrical Pressure Vessels

This study deals with the time-dependent creep analysis of functionally graded thick-cylinders under various thermal and mechanical boundary conditions. Firstly, exact thermoelastic stress, and iterative creep solutions for a heat generating and rotating cylindrical vessel made of functionally graded thermal and mechanical properties are proposed. Equations of equilibrium, compatibility, stress-strain, and strain-displacement relations are solved to obtain closed-form initial stress and strain solutions. It is found that material gradient indices have significant influences on thermoelastic stress profiles. For creep analysis, Norton’s model is incorporated into rate forms of the above-mentioned equations to obtain time-dependent stress and strain results using an iterative method. Validity of our solutions are at first verified using finite element analysis, and numerical results found in the recent literature have been enhanced. Investigation of effects of material gradients reveals that radial variation of density and creep coefficient have significant effects on strains histories, while Young’s modulus and thermal property distributions only influence stress redistribution at an early stage of creep deformation. Next, a more realistic model of introducing microscale creep effects into a macroscopic modeling is employed to investigate the creep behavior of functionally graded hollow cylinders. Finite element (FE) simulations are employed to evaluate the position-dependent parameters associated with creep constitutive law at the microscale. A macroscopic FE model solves the non-linear boundary value problem to determine the time-varying creep stresses and strains. The framework proposed is capable of predicting the creep response of functionally graded pressure vessels based on the constitutive behavior of the creeping matrix, and volume fraction profile. Effective creep properties have been computed using three different micromechanical models and the homogenized creep response and its effect on the macroscopic behavior are compared. Considering the computational expenses associated with the large 3D finite element models, the simple 2D axisymmetric model is able to closely capture the creep behavior in such multiscale methods. Finally, a multi-objective particle swarm optimization algorithm is implemented to minimize the initial stress and final creep strain of functionally graded cylinder subjected to mechanical and thermal loads

Development of efficient algorithms for model predictive control of fast systems

Die nichtlineare modellprädiktive Regelung (NMPC) ist ein vielversprechender Regelungsalgorithmus, der auf der Echtzeitlüsung eines nichtlinearen dynamischen Optimie- rungsproblems basiert. Nichtlineare Modellgleichungen wie auch die Steuerungs- und Zustandsbeschränkungen werden als Gleichungs- bzw. Ungleichungsbeschränkungen des Optimalsteuerungsproblems behandelt. Jedoch wurde die NMPC wegen des recht hohen Rechenaufwandes bisher meist auf relativ langsame Prozesse angewendet. Daher bildet die Rechenzeit bei Anwendung der NMPC auf schnelle Prozesse einen gewissen Engpass wie z. B. bei mechanischen und/oder elektrischen Prozessen. In dieser Arbeit wird eine neue Lüsungsstrategie für dynamische Optimierungsprobleme vorgeschlagen, wie sie in NMPC auftreten, die auch auf sog. schnelle Systeme anwendbar ist. Diese Strategie kombiniert Mehrschieß -Verfahrens mit der Methode der Kollokation auf finiten Elementen. Mittels Mehrschieß -Verfahren wird das nichtlineare dynamische Optimierungsproblem in ein hochdimensionales statisches Optimierungsproblem (nonlinear program problem, NLP) überführt, wobei Diskretisierungs- und Parametrisierungstechniken zum Einsatz kommen. Um das NLP-Problem zu lüsen, müssen die Zustandswerte und ihre Gradienten am Ende jedes Diskretisierung-Intervalles berechnet werden. In dieser Arbeit wird die Methode der Kollokation auf finiten Elementen benutzt, um diese Aufgabe zu lüsen. Dadurch lassen sich die Zustandsgrüß en und ihre Gradienten am Ende jedes Diskretisierungs-Intervalls auch mit groß er Genauigkeit berechnen. Im Ergebnis künnen die Vorteile beider Methoden (Mehrschieß -Verfahren und Kollokations-Methoden) ausgenutzt werden und die Rechenzeit lässt sich deutlich reduzieren. Wegen des komplexen Optimierungsproblems ist es im Allgemeinen schwierig, eine Stabilitätsanalyse für das zugehürige NMPC durchzuführen. In dieser Arbeit wird eine neue Formulierung des Optimalsteuerungsproblems vorgeschlagen, durch die die Stabilität des NMPC gesichert werden kann. Diese Strategie besteht aus den folgenden drei Eigenschaften. Zunächst wird ein Hilfszustand über eine lineare Zustandsgleichung in das Optimierungsproblem eingeführt. Die Zustandsgleichungen werden durch Hilfszustände ergänzt, die man in Form von Ungleichungsnebenbedingungen einführt. Wenn die Hilfszustände stabil sind, lässt sich damit die Stabilität des Gesamtsystems sichern. Die Eigenwerte der Hilfszustände werden so gewählt, dass das Optimalsteuerungsproblem lüsbar ist. Dazu benutzt man die Eigenwerte als Optimierungsvariable. Damit lassen sich die Stabilitätseigenschaften in einem stationären Punkt des Systemmodells untersuchen. Leistungsfähigkeit und Effektivität des vorgeschlagenen Algorithmus werden an Hand von Fallstudien belegt. Die Bibliothek Numerische Algorithmus Group (NAG), Mark 8, wird eingesetzt, um die linearen und nichtlinearen Gleichungen, die aus der Kollokation resultieren, zu lüsen. Weiterhin wird zur Lüsung des NLP-Problems der Lüser IPOPT für C/C++- Umgebung eingesetzt. Insbesondere wird der vorgeschlagene Algorithmus zur Steuerung einer Verladebrücke im Labor des Institutes für Automatisierungs- und Systemtechnik angewendet.Nonlinear model predictive control (NMPC) has been considered as a promising control algorithm which is based on a real-time solution of a nonlinear dynamic optimization problem. Nonlinear model equations and controls as well as state restrictions are treated as equality and inequality constraints of the optimal control problem. However, NMPC has been applied mostly in relatively slow processes until now, due to its high computational expense. Therefore, computation time needed for the solution of NMPC leads to a bottleneck in its application to fast systems such as mechanical and/or electrical processes. In this dissertation, a new solution strategy to efficiently solve NMPC problems is proposed so that it can be applied to fast systems. This strategy combines the multiple shooting method with the collocation on finite elements method. The multiple shooting method is used for transforming the nonlinear optimal control problem into nonlinear program (NLP) problem using discretization and parametrization techniques. To solve this NLP problem the values of state variables and their gradients at the end of each shooting need to be computed. We use collocation on finite elements to carry out this task, thus, a high precision approximation of the state variables and their sensitivities in each shoot are achieved. As a result, the advantages of both the multiple shooting and the collocation method can be employed and therefore the computation efficiency can be considerably enhanced. Due to the nonlinear and complex optimal control problem formulation, in general, it is difficult to analyze the stability properties of NMPC systems. In this dissertation we propose a new formulation of the optimal control problem to ensure the stability of the NMPC problems. It consists the following three features. First, we introduce auxiliary states and linear state equations into the finite horizon dynamic optimization problem. Second, we enforce system states to be contracted with respect to the auxiliary state variables by adding inequality constraints. Thus, the stability features of the system states will conform to the stability properties of the auxiliary states, i.e. the system states will be stable, if the auxiliary states are stable. Third, the eigenvalues of the linear state equations introduced will be determined to stabilize the auxiliary states and at the same time make the optimal control problem feasible. This is achieved by considering the eigenvalues as optimization variables in the optimal control problem. Moreover, features of this formulation are analyzed at the stationary point of the system model. To show the effectiveness and performance of the proposed algorithm and the new optimal control problem formulation we present a set of NMPC case studies. We use the numerical algorithm group (NAG) library Mark 8 to solve numerically linear and nonlinear systems that resulted from the collocation on finite elements to compute the states and sensitivities, in addition, the interior point optimizer (IPOPT) and in C/C++ environment. Furthermore, to show more applicability, the proposed algorithm is applied to control a laboratory loading bridge