Three dimensional finite element simulation of polymer melting and flow in a single-screw extruder : optimization of screw channel geometry

Single-screw extrusion is one of the widely used processing methods in plastics industry, which was the third largest manufacturing industry in the United States in 2007 [5]. In order to optimize the single-screw extrusion process, tremendous efforts have been devoted for development of accurate models in the last fifty years, especially for polymer melting in screw extruders. This has led to a good qualitative understanding of the melting process; however, quantitative predictions of melting from various models often have a large error in comparison to the experimental data. Thus, even nowadays, process parameters and the geometry of the extruder channel for the single-screw extrusion are determined by trial and error. Since new polymers are developed frequently, finding the optimum parameters to extrude these polymers by trial and error is costly and time consuming. In order to reduce the time and experimental work required for optimizing the process parameters and the geometry of the extruder channel for a given polymer, the main goal of this research was to perform a coordinated experimental and numerical investigation of melting in screw extrusion. In this work, a full three-dimensional finite element simulation of the two-phase flow in the melting and metering zones of a single-screw extruder was performed by solving the conservation equations for mass, momentum, and energy. The only attempt for such a three-dimensional simulation of melting in screw extruder was more than twenty years back. However, that work had only a limited success because of the capability of computers and mathematical algorithms available at that time. The dramatic improvement of computational power and mathematical knowledge now make it possible to run full 3-D simulations of two-phase flow in single-screw extruders on a desktop PC. In order to verify the numerical predictions from the full 3-D simulations of two-phase flow in single-screw extruders, a detailed experimental study was performed. This experimental study included Maddock screw-freezing experiments, Screw Simulator experiments and material characterization experiments. Maddock screw-freezing experiments were performed in order to visualize the melting profile along the single-screw extruder channel with different screw geometry configurations. These melting profiles were compared with the simulation results. Screw Simulator experiments were performed to collect the shear stress and melting flux data for various polymers. Cone and plate viscometer experiments were performed to obtain the shear viscosity data which is needed in the simulations. An optimization code was developed to optimize two screw geometry parameters, namely, screw lead (pitch) and depth in the metering section of a single-screw extruder, such that the output rate of the extruder was maximized without exceeding the maximum temperature value specified at the exit of the extruder. This optimization code used a mesh partitioning technique in order to obtain the flow domain. The simulations in this flow domain was performed using the code developed to simulate the two-phase flow in single-screw extruders.

Automated optimization of polymer extrusion dies using finite element analysis

An extrusion die is used to continuously produce parts with a constant cross section; such as sheets, pipes, tire components and more complex shapes such as window seals. The die is fed by a screw extruder when polymers are used. The extruder melts, mixes and pressures the material by the rotation of either a single or double screw. The polymer can then be continuously forced through the die producing a long part in the shape of the die outlet. The extruded section is then cut to the desired length. Generally, the primary target of a well designed die is to produce a uniform outlet velocity without excessively raising the pressure required to extrude the polymer through the die. Other properties such as temperature uniformity and residence time are also important but are not directly considered in this work. Designing dies for optimal outlet velocity variation using simple analytical equations are feasible for basic die geometries or simple channels. Due to the complexity of die geometry and of polymer material properties design of complex dies by analytical methods is difficult. For complex dies iterative methods must be used to optimize dies. An automated iterative method is desired for die optimization. To automate the design and optimization of an extrusion die two issues must be dealt with. The first is how to generate a new mesh for each iteration. In this work, this is approached by modifying a Parasolid file that describes a CAD part. This file is then used in a commercial meshing software. Skewing the initial mesh to produce a new geometry was also employed as a second option. The second issue is an optimization problem with the presence of noise stemming from variations in the mesh and cumulative truncation errors. In this work a simplex method and a modified trust region method were employed for automated optimization of die geometries. For the trust region a discreet derivative and a BFGS Hessian approximation were used. To deal with the noise in the function the trust region method was modified to automatically adjust the discreet derivative step size and the trust region based on changes in noise and function contour. Generally uniformity of velocity at exit of the extrusion die can be improved by increasing resistance across the die but this is limited by the pressure capabilities of the extruder. In optimization, a penalty factor that increases exponentially from the pressure limit is applied. This penalty can be applied in two different ways; the first only to the designs which exceed the pressure limit, the second to both designs above and below the pressure limit. Both of these methods were tested and compared in this work.

Multiscale constitutive modeling of polymer materials

Materials are inherently multi-scale in nature consisting of distinct characteristics at various length scales from atoms to bulk material. There are no widely accepted predictive multi-scale modeling techniques that span from atomic level to bulk relating the effects of the structure at the nanometer (10-9 meter) on macro-scale properties. Traditional engineering deals with treating matter as continuous with no internal structure. In contrast to engineers, physicists have dealt with matter in its discrete structure at small length scales to understand fundamental behavior of materials. Multiscale modeling is of great scientific and technical importance as it can aid in designing novel materials that will enable us to tailor properties specific to an application like multi-functional materials. Polymer nanocomposite materials have the potential to provide significant increases in mechanical properties relative to current polymers used for structural applications. The nanoscale reinforcements have the potential to increase the effective interface between the reinforcement and the matrix by orders of magnitude for a given reinforcement volume fraction as relative to traditional micro- or macro-scale reinforcements. To facilitate the development of polymer nanocomposite materials, constitutive relationships must be established that predict the bulk mechanical properties of the materials as a function of the molecular structure. A computational hierarchical multiscale modeling technique is developed to study the bulk-level constitutive behavior of polymeric materials as a function of its molecular chemistry. Various parameters and modeling techniques from computational chemistry to continuum mechanics are utilized for the current modeling method. The cause and effect relationship of the parameters are studied to establish an efficient modeling framework. The proposed methodology is applied to three different polymers and validated using experimental data available in literature.

AN EXPERIMENTAL INVESTIGATION INTO THE EFFECTS OF BIODIESEL BLENDS ON PARTICULATE MATTER OXIDATION IN A CATALYZED PARTICULATE FILTER DURING ACTIVE REGENERATION

Active regeneration experiments were carried out on a production 2007 Cummins 8.9L ISL engine and associated DOC and CPF aftertreatment system. The effects of SME biodiesel blends were investigated in this study in order to determine the PM oxidation kinetics associated with active regeneration, and to determine the effect of biodiesel on them. The experimental data from this study will also be used to calibrate the MTU-1D CPF model. Accurately predicting the PM mass retained in the CPF and the oxidation characteristics will provide the basis for computation in the ECU that will minimize the fuel penalty associated with active regeneration. An active regeneration test procedure was developed based on previous experimentation at MTU. During each experiment, the PM mass in the CPF is determined by weighing the filter at various phases. In addition, DOC and CPF pressure drop, particle size distribution, gaseous emissions, temperature, and PM concentration data are collected and recorded throughout each experiment. The experiments covered a range of CPF inlet temperatures using ULSD, B10, and B20 blends of biodiesel. The majority of the tests were performed at CPF PM loading of 2.2 g/L with in-cylinder dosing, although 4.1 g/L and a post-turbo dosing injector were also used. The PM oxidation characteristics at different test conditions were studied in order to determine the effects of biodiesel on PM oxidation during active regeneration. A PM reaction rate calculation method was developed to determine the global activation energy and the corresponding pre-exponential factor for all test fuels. The changing sum of the total flow resistance of the wall, cake, and channels was also determined as part of the data analysis process in order to check on the integrity of the data and to correct input data to be consistent with the expected trends of the resistance based on the engine conditions used in the test procedure. It was determined that increasing the percent biodiesel content in the test fuel tends to increase the PM reaction rate and the regeneration efficiency of fuel dosing, i.e., at a constant CPF inlet temperature, B20 test fuel resulted in the highest PM reaction rate and regeneration efficiency of fuel dosing. Increasing the CPF inlet temperature also increases PM reaction rate and regeneration efficiency of fuel dosing. Performing active regeneration with B20 as opposed to ULSD allows for a lower CPF temperature to be used to reach the same level of regeneration efficiency, or it allows for a shorter regeneration time at a constant CPF temperature, resulting in decreased fuel consumption for the engine during active regeneration in either scenario.

Compatibility of ultra high performance concrete as repair material : bond characterization with concrete under different loading scenarios

The rehabilitation of concrete structures, especially concrete bridge decks, is a major challenge for transportation agencies in the United States. Often, the most appropriate strategy to preserve or rehabilitate these structures is to provide some form of a protective coating or barrier. These surface treatments have typically been some form of polymer, asphalt, or low-permeability concrete, but the application of UHPC has shown promise for this application mainly due to its negligible permeability, but also as a result of its excellent mechanical properties, self-consolidating nature, rapid gain strength, and minimal creep and shrinkage characteristics. However, for widespread acceptance, durability and performance of the composite system must be fully understood, specifically the bond between UHPC and NSC often used in bridge decks. It is essential that the bond offers enough strength to resist the stress due to mechanical loading or thermal effects, while also maintaining an extended service-life performance. This report attempts to assess the bond strength between UHPC and NSC under different loading configurations. Different variables, such as roughness degree of the concrete substrates, age of bond, exposure to freeze-thaw cycles and wetting conditions of the concrete substrate, were included in this study. The combination of splitting tensile test with 0, 300, 600 and 900 freeze-thaw cycles was carried out to assess the bond performance under severe ambient conditions. The slant-shear test was utilized with different interface angles to provide a wide understanding of the bond performance under different combinations of compression and shear stresses. The pull-off test is the most accepted method to evaluate the bond strength in the field. This test which studies the direct tensile strength of the bond, the most severe loading condition, was used to provide data that can be correlated with the other tests that only can be used in the laboratory. The experimental program showed that the bond performance between UHPC and NSC is successful, as the strength regardless the different degree of roughness of the concrete substrate, the age of the composite specimens, the exposure to freeze-thaw cycles and the different loading configurations, is greater than that of concrete substrate and largely satisfies with ACI 546.3R-06.

THE USE OF LIFE-CYCLE ANALYSIS TO REDUCE THE ENVIRONMENTAL IMPACT OF MATERIALS IN MANUFACTURING

This thesis is composed of three life-cycle analysis (LCA) studies of manufacturing to determine cumulative energy demand (CED) and greenhouse gas emissions (GHG). The methods proposed could reduce the environmental impact by reducing the CED in three manufacturing processes. First, industrial symbiosis is proposed and a LCA is performed on both conventional 1 GW-scaled hydrogenated amorphous silicon (a-Si:H)-based single junction and a-Si:H/microcrystalline-Si:H tandem cell solar PV manufacturing plants and such plants coupled to silane recycling plants. Using a recycling process that results in a silane loss of only 17 versus 85 percent, this results in a CED savings of 81,700 GJ and 290,000 GJ per year for single and tandem junction plants, respectively. This recycling process reduces the cost of raw silane by 68 percent, or approximately $22.6 and $79 million per year for a single and tandem 1 GW PV production facility, respectively. The results show environmental benefits of silane recycling centered around a-Si:H-based PV manufacturing plants. Second, an open-source self-replicating rapid prototype or 3-D printer, the RepRap, has the potential to reduce the environmental impact of manufacturing of polymer-based products, using distributed manufacturing paradigm, which is further minimized by the use of PV and improvements in PV manufacturing. Using 3-D printers for manufacturing provides the ability to ultra-customize products and to change fill composition, which increases material efficiency. An LCA was performed on three polymer-based products to determine the CED and GHG from conventional large-scale production and are compared to experimental measurements on a RepRap producing identical products with ABS and PLA. The results of this LCA study indicate that the CED of manufacturing polymer products can possibly be reduced using distributed manufacturing with existing 3-D printers under 89% fill and reduced even further with a solar photovoltaic system. The results indicate that the ability of RepRaps to vary fill has the potential to diminish environmental impact on many products. Third, one additional way to improve the environmental performance of this distributed manufacturing system is to create the polymer filament feedstock for 3-D printers using post-consumer plastic bottles. An LCA was performed on the recycling of high density polyethylene (HDPE) using the RecycleBot. The results of the LCA showed that distributed recycling has a lower CED than the best-case scenario used for centralized recycling. If this process is applied to the HDPE currently recycled in the U.S., more than 100 million MJ of energy could be conserved per annum along with significant reductions in GHG. This presents a novel path to a future of distributed manufacturing suited for both the developed and developing world with reduced environmental impact. From improving manufacturing in the photovoltaic industry with the use of recycling to recycling and manufacturing plastic products within our own homes, each step reduces the impact on the environment. The three coupled projects presented here show a clear potential to reduce the environmental impact of manufacturing and other processes by implementing complimenting systems, which have environmental benefits of their own in order to achieve a compounding effect of reduced CED and GHG.

STUDIES OF FUNCTIONALIZED NANOPARTICLES FOR SMART SELF-ASSEMBLY AND AS CONTROLLED DRUG DELIVERY

This dissertation is related to the studies of functionalized nanoparticles for self-assembly and as controlled drug delivery system. The whole topic is composed of two parts. In the first part, the research was conducted to design and synthesize a new type of ionic peptide-functionalized copolymer conjugates for self-assembly into nanoparticle fibers and 3D scaffolds with the ability of multi-drug loading and governing the release rate of each drug for tissue engineering. The self-assembly study confirmed that such peptide-functionalized amphiphilic copolymers underwent different self-assembly behavior. The bigger nanoparticles were more easily assembled into nanoparticle fibers and 3D scaffolds with larger pore size, while the smaller nanoparticle underwent faster self-assembly to form more compact 3D scaffolds with smaller porosity but more stable structure. Controlled release studies confirmed the ability of governing simultaneous release of different model drugs with independent release rate from a same scaffold. Cytotoxicity tests showed that all synthesized peptides, copolymers and peptide-copolymer conjugates were biocompatible with SW-620 cell lines and NIH3T3 cell lines. This new type of self-assembled scaffolds combined the advantages of peptide nanofibers and versatile controlled release of polymeric nanoparticles to achieve simultaneous multi-drug loading and controlled release of each drug, uniform distribution and flexibility of hydrogel scaffolds. The investigations in second part were first to design and synthesize organic biocide-loaded nanoparticles for low-leaching wood preservation using a cost-effective one-pot method to synthesize amphiphilic chitosan-g-PMMA nanoparticles loading with ~25-28 wt.% of the fungicide tebuconazole with particle size of ~100 nm diameter by FESEM. FESEM analysis confirmed efficient penetration of nanoparticles throughout the treated wooden stake with dimension of 19 × 19 × 455 mm^3. Leaching studies showed that biocide introduced into sapwood via nanoparticles leached only ~9% compared with the amount leached from tebuconazole solution-treated control, while soil jar tests showed that the nanoparticle-treated wood blocks were effectively protected from biological decay tested against G. trabeum, a brown rot fungus. Copper oxide nanoparticles with and without polymer stabilizers were also investigated to use as inorganic wood preservatives to clarify the factor affecting copper leaching from treated wood. Copper oxide nanoparticles with uniform diameters of ~10 nm and ~50 nm were prepared, and the leachates from southern pine sapwood treated with these nanoparticles were analyzed. It was found by TEM and EDS analysis that significant numbers of nanoparticles leached from the treated wood. The 50 nm nanoparticles leached slightly less than a soluble copper salt control, but 10 nm nanoparticles leached substantially more than the control. The effect of polymer stabilizers on nanoparticle leaching was also investigated. Results showed that polymer stabilizers increased leaching. The trends showed that nanoparticle size was a major factor in copper leaching.