Experimental and numerical analysis of dry contact in the pin on disc test

The reduction of friction and wear in systems presenting metal-to-metal contacts, as in several mechanical components, represents a traditional challenge in tribology. In this context, this work presents a computational study based on the linear Archard's wear law and finite element modeling (FEM), in order to analyze unlubricated sliding wear observed in typical pin on disc tests. Such modeling was developed using finite element software Abaqus® with 3-D deformable geometries and elastic–plastic material behavior for the contact surfaces. Archard's wear model was implemented into a FORTRAN user subroutine (UMESHMOTION) in order to describe sliding wear. Modeling of debris and oxide formation mechanisms was taken into account by the use of a global wear coefficient obtained from experimental measurements. Such implementation considers an incremental computation for surface wear based on the nodal displacements by means of adaptive mesh tools that rearrange local nodal positions. In this way, the worn track was obtained and new surface profile is integrated for mass loss assessments. This work also presents experimental pin on disc tests with AISI 4140 pins on rotating AISI H13 discs with normal loads of 10, 35, 70 and 140 N, which represent, respectively, mild, transition and severe wear regimes, at sliding speed of 0.1 m/s. Numerical and experimental results were compared in terms of wear rate and friction coefficient. Furthermore, in the numerical simulation the stress field distribution and changes in the surface profile across the worn track of the disc were analyzed. The applied numerical formulation has shown to be more appropriate to predict mild wear regime than severe regime, especially due to the shorter running-in period observed in lower loads that characterizes this kind of regime.

Effects of tire pressures on flexible pavements. Final report.

Mode of access: Internet.

Hybrid incremental modeling based on least squares and fuzzy K-NN for monitoring tool wear in turning processes

There is now an emerging need for an efficient modeling strategy to develop a new generation of monitoring systems. One method of approaching the modeling of complex processes is to obtain a global model. It should be able to capture the basic or general behavior of the system, by means of a linear or quadratic regression, and then superimpose a local model on it that can capture the localized nonlinearities of the system. In this paper, a novel method based on a hybrid incremental modeling approach is designed and applied for tool wear detection in turning processes. It involves a two-step iterative process that combines a global model with a local model to take advantage of their underlying, complementary capacities. Thus, the first step constructs a global model using a least squares regression. A local model using the fuzzy k-nearest-neighbors smoothing algorithm is obtained in the second step. A comparative study then demonstrates that the hybrid incremental model provides better error-based performance indices for detecting tool wear than a transductive neurofuzzy model and an inductive neurofuzzy model.

Tool cutting force modeling and wear estimation of micro -end-milling operations

The applications of micro-end-milling operations have increased recently. A Micro-End-Milling Operation Guide and Research Tool (MOGART) package has been developed for the study and monitoring of micro-end-milling operations. It includes an analytical cutting force model, neural network based data mapping and forecasting processes, and genetic algorithms based optimization routines. MOGART uses neural networks to estimate tool machinability and forecast tool wear from the experimental cutting force data, and genetic algorithms with the analytical model to monitor tool wear, breakage, run-out, cutting conditions from the cutting force profiles. ^ The performance of MOGART has been tested on the experimental data of over 800 experimental cases and very good agreement has been observed between the theoretical and experimental results. The MOGART package has been applied to the micro-end-milling operation study of Engineering Prototype Center of Radio Technology Division of Motorola Inc. ^

Tool cutting force modeling and wear estimation of micro-end-milling operations

The applications of micro-end-milling operations have increased recently. A Micro-End-Milling Operation Guide and Research Tool (MOGART) package has been developed for the study and monitoring of micro-end-milling operations. It includes an analytical cutting force model, neural network based data mapping and forecasting processes, and genetic algorithms based optimization routines. MOGART uses neural networks to estimate tool machinability and forecast tool wear from the experimental cutting force data, and genetic algorithms with the analytical model to monitor tool wear, breakage, run-out, cutting conditions from the cutting force profiles. The performance of MOGART has been tested on the experimental data of over 800 experimental cases and very good agreement has been observed between the theoretical and experimental results. The MOGART package has been applied to the micro-end-milling operation study of Engineering Prototype Center of Radio Technology Division of Motorola Inc.

Predictive analytical and numerical modeling for orthogonal cutting

In this thesis, a predictive analytical and numerical modeling approach for the orthogonal cutting process is proposed to calculate temperature distributions and subsequently, forces and stress distributions. The models proposed include a constitutive model for the material being cut based on the work of Weber, a model for the shear plane based on Merchants model, a model describing the contribution of friction based on Zorev’s approach, a model for the effect of wear on the tool based on the work of Waldorf, and a thermal model based on the works of Komanduri and Hou, with a fraction heat partition for a non-uniform distribution of the heat in the interfaces, but extended to encompass a set of contributions to the global temperature rise of chip, tool and work piece. The models proposed in this work, try to avoid from experimental based values or expressions, and simplifying assumptions or suppositions, as much as possible. On a thermo-physical point of view, the results were affected not only by the mechanical or cutting parameters chosen, but also by their coupling effects, instead of the simplifying way of modeling which is to contemplate only the direct effect of the variation of a parameter. The implementation of these models was performed using the MATLAB environment. Since it was possible to find in the literature all the parameters for AISI 1045 and AISI O2, these materials were used to run the simulations in order to avoid arbitrary assumption.

Power cycling lifetime estimation of IGBT power modules based on chip temperature modeling

In this doctoral thesis, methods to estimate the expected power cycling life of power semiconductor modules based on chip temperature modeling are developed. Frequency converters operate under dynamic loads in most electric drives. The varying loads cause thermal expansion and contraction, which stresses the internal boundaries between the material layers in the power module. Eventually, the stress wears out the semiconductor modules. The wear-out cannot be detected by traditional temperature or current measurements inside the frequency converter. Therefore, it is important to develop a method to predict the end of the converter lifetime. The thesis concentrates on power-cycling-related failures of insulated gate bipolar transistors. Two types of power modules are discussed: a direct bonded copper (DBC) sandwich structure with and without a baseplate. Most common failure mechanisms are reviewed, and methods to improve the power cycling lifetime of the power modules are presented. Power cycling curves are determined for a module with a lead-free solder by accelerated power cycling tests. A lifetime model is selected and the parameters are updated based on the power cycling test results. According to the measurements, the factor of improvement in the power cycling lifetime of modern IGBT power modules is greater than 10 during the last decade. Also, it is noticed that a 10 C increase in the chip temperature cycle amplitude decreases the lifetime by 40%. A thermal model for the chip temperature estimation is developed. The model is based on power loss estimation of the chip from the output current of the frequency converter. The model is verified with a purpose-built test equipment, which allows simultaneous measurement and simulation of the chip temperature with an arbitrary load waveform. The measurement system is shown to be convenient for studying the thermal behavior of the chip. It is found that the thermal model has a 5 C accuracy in the temperature estimation. The temperature cycles that the power semiconductor chip has experienced are counted by the rainflow algorithm. The counted cycles are compared with the experimentally verified power cycling curves to estimate the life consumption based on the mission profile of the drive. The methods are validated by the lifetime estimation of a power module in a direct-driven wind turbine. The estimated lifetime of the IGBT power module in a direct-driven wind turbine is 15 000 years, if the turbine is located in south-eastern Finland.

Modeling of burden distribution in the blast furnace

The blast furnace is the main ironmaking production unit in the world which converts iron ore with coke and hot blast into liquid iron, hot metal, which is used for steelmaking. The furnace acts as a counter-current reactor charged with layers of raw material of very different gas permeability. The arrangement of these layers, or burden distribution, is the most important factor influencing the gas flow conditions inside the furnace, which dictate the efficiency of the heat transfer and reduction processes. For proper control the furnace operators should know the overall conditions in the furnace and be able to predict how control actions affect the state of the furnace. However, due to high temperatures and pressure, hostile atmosphere and mechanical wear it is very difficult to measure internal variables. Instead, the operators have to rely extensively on measurements obtained at the boundaries of the furnace and make their decisions on the basis of heuristic rules and results from mathematical models. It is particularly difficult to understand the distribution of the burden materials because of the complex behavior of the particulate materials during charging. The aim of this doctoral thesis is to clarify some aspects of burden distribution and to develop tools that can aid the decision-making process in the control of the burden and gas distribution in the blast furnace. A relatively simple mathematical model was created for simulation of the distribution of the burden material with a bell-less top charging system. The model developed is fast and it can therefore be used by the operators to gain understanding of the formation of layers for different charging programs. The results were verified by findings from charging experiments using a small-scale charging rig at the laboratory. A basic gas flow model was developed which utilized the results of the burden distribution model to estimate the gas permeability of the upper part of the blast furnace. This combined formulation for gas and burden distribution made it possible to implement a search for the best combination of charging parameters to achieve a target gas temperature distribution. As this mathematical task is discontinuous and non-differentiable, a genetic algorithm was applied to solve the optimization problem. It was demonstrated that the method was able to evolve optimal charging programs that fulfilled the target conditions. Even though the burden distribution model provides information about the layer structure, it neglects some effects which influence the results, such as mixed layer formation and coke collapse. A more accurate numerical method for studying particle mechanics, the Discrete Element Method (DEM), was used to study some aspects of the charging process more closely. Model charging programs were simulated using DEM and compared with the results from small-scale experiments. The mixed layer was defined and the voidage of mixed layers was estimated. The mixed layer was found to have about 12% less voidage than layers of the individual burden components. Finally, a model for predicting the extent of coke collapse when heavier pellets are charged over a layer of lighter coke particles was formulated based on slope stability theory, and was used to update the coke layer distribution after charging in the mathematical model. In designing this revision, results from DEM simulations and charging experiments for some charging programs were used. The findings from the coke collapse analysis can be used to design charging programs with more stable coke layers.

Graded Meshes In Bio-thermal Problems With Transmission-line Modeling Method.

In this study, the transmission-line modeling (TLM) applied to bio-thermal problems was improved by incorporating several novel computational techniques, which include application of graded meshes which resulted in 9 times faster in computational time and uses only a fraction (16%) of the computational resources used by regular meshes in analyzing heat flow through heterogeneous media. Graded meshes, unlike regular meshes, allow heat sources to be modeled in all segments of the mesh. A new boundary condition that considers thermal properties and thus resulting in a more realistic modeling of complex problems is introduced. Also, a new way of calculating an error parameter is introduced. The calculated temperatures between nodes were compared against the results obtained from the literature and agreed within less than 1% difference. It is reasonable, therefore, to conclude that the improved TLM model described herein has great potential in heat transfer of biological systems.

Variability Modeling Of Rainfall, Deforestation, And Incidence Of American Tegumentary Leishmaniasis In Orán, Argentina, 1985-2007.

American tegumentary leishmaniasis (ATL) is a disease transmitted to humans by the female sandflies of the genus Lutzomyia. Several factors are involved in the disease transmission cycle. In this work only rainfall and deforestation were considered to assess the variability in the incidence of ATL. In order to reach this goal, monthly recorded data of the incidence of ATL in Orán, Salta, Argentina, were used, in the period 1985-2007. The square root of the relative incidence of ATL and the corresponding variance were formulated as time series, and these data were smoothed by moving averages of 12 and 24 months, respectively. The same procedure was applied to the rainfall data. Typical months, which are April, August, and December, were found and allowed us to describe the dynamical behavior of ATL outbreaks. These results were tested at 95% confidence level. We concluded that the variability of rainfall would not be enough to justify the epidemic outbreaks of ATL in the period 1997-2000, but it consistently explains the situation observed in the years 2002 and 2004. Deforestation activities occurred in this region could explain epidemic peaks observed in both years and also during the entire time of observation except in 2005-2007.

Modeling The Effects Of Temperature And Ph On The Resistance Of Alicyclobacillus Acidoterrestris In Conventional Heat-treated Fruit Beverages Through A Meta-analysis Approach.

In this work, all publicly-accessible published findings on Alicyclobacillus acidoterrestris heat resistance in fruit beverages as affected by temperature and pH were compiled. Then, study characteristics (protocols, fruit and variety, °Brix, pH, temperature, heating medium, culture medium, inactivation method, strains, etc.) were extracted from the primary studies, and some of them incorporated to a meta-analysis mixed-effects linear model based on the basic Bigelow equation describing the heat resistance parameters of this bacterium. The model estimated mean D* values (time needed for one log reduction at a temperature of 95 °C and a pH of 3.5) of Alicyclobacillus in beverages of different fruits, two different concentration types, with and without bacteriocins, and with and without clarification. The zT (temperature change needed to cause one log reduction in D-values) estimated by the meta-analysis model were compared to those ('observed' zT values) reported in the primary studies, and in all cases they were within the confidence intervals of the model. The model was capable of predicting the heat resistance parameters of Alicyclobacillus in fruit beverages beyond the types available in the meta-analytical data. It is expected that the compilation of the thermal resistance of Alicyclobacillus in fruit beverages, carried out in this study, will be of utility to food quality managers in the determination or validation of the lethality of their current heat treatment processes.

Supercritical CO2 recovery of caffeine from green coffee oil: new experimental solubility data and modeling

The caffeine solubility in supercritical CO2 was studied by assessing the effects of pressure and temperature on the extraction of green coffee oil (GCO). The Peng-Robinson¹ equation of state was used to correlate the solubility of caffeine with a thermodynamic model and two mixing rules were evaluated: the classical mixing rule of van der Waals with two adjustable parameters (PR-VDW) and a density dependent one, proposed by Mohamed and Holder² with two (PR-MH, two parameters adjusted to the attractive term) and three (PR-MH3 two parameters adjusted to the attractive and one to the repulsive term) adjustable parameters. The best results were obtained with the mixing rule of Mohamed and Holder² with three parameters.

In vitro wear resistance of three types of polymethyl methacrylate denture teeth

The wear resistance of denture teeth is important to the longevity of removable prostheses of edentulous patients. The ability of denture teeth to maintain a stable occlusal relationship over time may be influenced by this property. The purpose of this in vitro study was to evaluate the wear resistance of polymethyl methacrylate (PMMA) denture teeth based on their chemical composition when opposed by a ceramic antagonist. The maxillary canines (n=10) of 3 PMMA denture teeth (Trubyte Biotone, cross-linked PMMA; Trilux, highly cross-linked IPN (interpenetrating polymer network)-PMMA; and Vivodent, highly cross-linked PMMA) were secured in an in vitro 2-body wear-testing apparatus that produced sliding contact of the specimens (4.5 cycles/s, sliding distance of 20 mm, under 37°C running water) against glazed or airborne particle abraded ceramic. Wear resistance was measured as height loss (mm) under 300 g (sliding force) after 100,000 cycles, using a digital measuring microscope. Mean values were analyzed by 2-way ANOVA and Tukey's test (a=0.05). The wear of Trubyte Biotone (0.93 ± 0.14 mm) was significantly higher than that of both other types of teeth tested against abraded ceramic (p<0.05). The Vivodent tooth (0.64 ± 0.17 mm) exhibited the best wear resistance among the denture teeth tested against airborne particle abraded ceramic. There were no statistically significant differences (p>0.05) in wear among the 3 denture teeth evaluated against glazed ceramic. Trilux and Vivodent teeth tested against either glazed or airborne particle abraded ceramic did not differ significantly from each other (p<0.05). All teeth showed significantly more wear against airborne particle abraded ceramic than against glazed ceramic (p<0.05). In conclusion, the three types of PMMA denture teeth presented significantly different wear resistance against the abraded ceramic. The high-strength PMMA denture teeth were more wear-resistant than the conventional PMMA denture tooth.

Abrasion wear resistance of different artificial teeth opposed to metal and composite antagonists

One of the most important properties of artificial teeth is the abrasion wear resistance, which is determinant in the maintenance of the rehabilitation's occlusal pattern. OBJECTIVES: This in vitro study aims to evaluate the abrasion wear resistance of 7 brands of artificial teeth opposed to two types of antagonists. MATERIAL AND METHODS: Seven groups were prepared with 12 specimens each (BIOLUX & BL, TRILUX & TR, BLUE DENT & BD, BIOCLER & BC, POSTARIS & PO, ORTHOSIT & OR, GNATHOSTAR & GN), opposed to metallic (M & nickel-chromium alloy), and to composite antagonists (C & Solidex indirect composite). A mechanical loading device was used (240 cycles/min, 4 Hz speed, 10 mm antagonist course). Initial and final contours of each specimen were registered with aid of a profile projector (20x magnification). The linear difference between the two profiles was measured and the registered values were subjected to ANOVA and Tukey's test. RESULTS: Regarding the antagonists, only OR (M = 10.45 ± 1.42 µm and C = 2.77 ± 0.69 µm) and BC (M = 6.70 ± 1.37 µm and C = 4.48 ± 0.80 µm) presented statistically significant differences (p < 0.05). Best results were obtained with PO (C = 2.33 ± 0.91 µm and M = 1.78 ± 0.42 µm), followed by BL (C = 3.70 ± 1.32 µm and M = 3.70 ± 0.61 µm), statistically similar for both antagonists (p>0.05). Greater result variance was obtained with OR, which presented the worse results opposed to Ni-Cr (10.45 ± 1.42 µm), and results similar to the best ones against composite (2.77 ± 0.69 µm). CONCLUSIONS: Within the limitations of this study, it may be concluded that the antagonist material is a factor of major importance to be considered in the choice of the artificial teeth to be used in the prosthesis.

Control of erosive tooth wear: possibilities and rationale

Dental erosion is a type of wear caused by non bacterial acids or chelation. There is evidence of a significant increase in the prevalence of dental wear in the deciduous and permanent teeth as a consequence of the frequent intake of acidic foods and drinks, or due to gastric acid which may reach the oral cavity following reflux or vomiting episodes. The presence of acids is a prerequisite for dental erosion, but the erosive wear is complex and depends on the interaction of biological, chemical and behavioral factors. Even though erosion may be defined or described as an isolated process, in clinical situations other wear phenomena are expected to occur concomitantly, such as abrasive wear (which occurs, e.g, due to tooth brushing or mastication). In order to control dental loss due to erosive wear it is crucial to take into account its multifactorial nature, which predisposes some individuals to the condition.