Comparison of common dredging equipment air emissions

The purpose of this study is to provide a procedure to include emissions to the atmosphere resulting from the combustion of diesel fuel during dredging operations into the decision-making process of dredging equipment selection. The proposed procedure is demonstrated for typical dredging methods and data from the Illinois Waterway as performed by the U.S. Army Corps of Engineers, Rock Island District. The equipment included in this study is a 16-inch cutterhead pipeline dredge and a mechanical bucket dredge used during the 2005 dredging season on the Illinois Waterway. Considerable effort has been put forth to identify and reduce environmental impacts from dredging operations. Though environmental impacts of dredging have been studied no efforts have been applied to the evaluation of air emissions from comparable types of dredging equipment, as in this study. By identifying the type of dredging equipment with the lowest air emissions, when cost, site conditions, and equipment availability are comparable, adverse environmental impacts can be minimized without compromising the dredging project. A total of 48 scenarios were developed by varying the dredged material quantity, transport distance, and production rates. This produced an “envelope” of results applicable to a broad range of site conditions. Total diesel fuel consumed was calculated using standard cost estimating practices as defined in the U.S. Army Corps of Engineers Construction Equipment Ownership and Operating Expense Schedule (USACE, 2005). The diesel fuel usage was estimated for all equipment used to mobilize and/or operate each dredging crew for every scenario. A Limited Life Cycle Assessment (LCA) was used to estimate the air emissions from two comparable dredging operations utilizing SimaPro LCA software. An Environmental Impact Single Score (EISS) was the SimaPro output selected for comparison with the cost per CY of dredging, potential production rates, and transport distances to identify possible decision points. The total dredging time was estimated for each dredging crew and scenario. An average hourly cost for both dredging crews was calculated based on Rock Island District 2005 dredging season records (Graham 2007/08). The results from this study confirm commonly used rules of thumb in the dredging industry by indicating that mechanical bucket dredges are better suited for long transport distances and have lower air emissions and cost per CY for smaller quantities of dredged material. In addition, the results show that a cutterhead pipeline dredge would be preferable for moderate and large volumes of dredged material when no additional booster pumps are required. Finally, the results indicate that production rates can be a significant factor when evaluating the air emissions from comparable dredging equipment.

Modeling mechanical response of heterogeneous materials

Heterogeneous materials are ubiquitous in nature and as synthetic materials. These materials provide unique combination of desirable mechanical properties emerging from its heterogeneities at different length scales. Future structural and technological applications will require the development of advanced light weight materials with superior strength and toughness. Cost effective design of the advanced high performance synthetic materials by tailoring their microstructure is the challenge facing the materials design community. Prior knowledge of structure-property relationships for these materials is imperative for optimal design. Thus, understanding such relationships for heterogeneous materials is of primary interest. Furthermore, computational burden is becoming critical concern in several areas of heterogeneous materials design. Therefore, computationally efficient and accurate predictive tools are highly essential. In the present study, we mainly focus on mechanical behavior of soft cellular materials and tough biological material such as mussel byssus thread. Cellular materials exhibit microstructural heterogeneity by interconnected network of same material phase. However, mussel byssus thread comprises of two distinct material phases. A robust numerical framework is developed to investigate the micromechanisms behind the macroscopic response of both of these materials. Using this framework, effect of microstuctural parameters has been addressed on the stress state of cellular specimens during split Hopkinson pressure bar test. A voronoi tessellation based algorithm has been developed to simulate the cellular microstructure. Micromechanisms (microinertia, microbuckling and microbending) governing macroscopic behavior of cellular solids are investigated thoroughly with respect to various microstructural and loading parameters. To understand the origin of high toughness of mussel byssus thread, a Genetic Algorithm (GA) based optimization framework has been developed. It is found that two different material phases (collagens) of mussel byssus thread are optimally distributed along the thread. These applications demonstrate that the presence of heterogeneity in the system demands high computational resources for simulation and modeling. Thus, Higher Dimensional Model Representation (HDMR) based surrogate modeling concept has been proposed to reduce computational complexity. The applicability of such methodology has been demonstrated in failure envelope construction and in multiscale finite element techniques. It is observed that surrogate based model can capture the behavior of complex material systems with sufficient accuracy. The computational algorithms presented in this thesis will further pave the way for accurate prediction of macroscopic deformation behavior of various class of advanced materials from their measurable microstructural features at a reasonable computational cost.

Effects of silicon content and cooling rate on mechanical properties of heavy section ductile cast iron

The effects of Si and cooling rate are investigated for their effect on the mechanical properties and microstructure. Three alloys were chosen with varying C and Si contents and an attempt to keep the remainder of the elements present constant. Within each heat, three test blocks were poured. Two blocks had chills – one with a fluid flowing through it to cool it (active chill) and one without the fluid (passive) – and the third block did not have a chill. Cooling curves were gathered and analyzed. The mechanical properties of the castings were correlated to the microstructure, cooling rate and Si content of each block. It was found that an increase in Si content increased the yield stress, tensile strength and hardness but decreased the impact toughness, elongation and Young’s modulus. The fast cooling rates produced by the chills caused a high nodule count in the castings along with a fine ferrite grain size and a high degree of nodularity. The fine microstructures, in turn, increased the strength and ductile to brittle transition temperature (DBTT) of the castings. The fast cooling rate was not adequate to overcome the dramatic increase in DBTT that is caused by the addition of Si.

Analysis of a Non-Traditional Micro Tube Hydroforming Process

As the demand for miniature products and components continues to increase, the need for manufacturing processes to provide these products and components has also increased. To meet this need, successful macroscale processes are being scaled down and applied at the microscale. Unfortunately, many challenges have been experienced when directly scaling down macro processes. Initially, frictional effects were believed to be the largest challenge encountered. However, in recent studies it has been found that the greatest challenge encountered has been with size effects. Size effect is a broad term that largely refers to the thickness of the material being formed and how this thickness directly affects the product dimensions and manufacturability. At the microscale, the thickness becomes critical due to the reduced number of grains. When surface contact between the forming tools and the material blanks occur at the macroscale, there is enough material (hundreds of layers of material grains) across the blank thickness to compensate for material flow and the effect of grain orientation. At the microscale, there may be under 10 grains across the blank thickness. With a decreased amount of grains across the thickness, the influence of the grain size, shape and orientation is significant. Any material defects (either natural occurring or ones that occur as a result of the material preparation) have a significant role in altering the forming potential. To date, various micro metal forming and micro materials testing equipment setups have been constructed at the Michigan Tech lab. Initially, the research focus was to create a micro deep drawing setup to potentially build micro sensor encapsulation housings. The research focus shifted to micro metal materials testing equipment setups. These include the construction and testing of the following setups: a micro mechanical bulge test, a micro sheet tension test (testing micro tensile bars), a micro strain analysis (with the use of optical lithography and chemical etching) and a micro sheet hydroforming bulge test. Recently, the focus has shifted to study a micro tube hydroforming process. The intent is to target fuel cells, medical, and sensor encapsulation applications. While the tube hydroforming process is widely understood at the macroscale, the microscale process also offers some significant challenges in terms of size effects. Current work is being conducted in applying direct current to enhance micro tube hydroforming formability. Initially, adding direct current to various metal forming operations has shown some phenomenal results. The focus of current research is to determine the validity of this process.

TEST-ANALYSIS MODEL CORRELATION AND CALIBRATION OF A MULTI-COMPONENT PLASTIC PART

The goal of this project is to learn the necessary steps to create a finite element model, which can accurately predict the dynamic response of a Kohler Engines Heavy Duty Air Cleaner (HDAC). This air cleaner is composed of three glass reinforced plastic components and two air filters. Several uncertainties arose in the finite element (FE) model due to the HDAC’s component material properties and assembly conditions. To help understand and mitigate these uncertainties, analytical and experimental modal models were created concurrently to perform a model correlation and calibration. Over the course of the project simple and practical methods were found for future FE model creation. Similarly, an experimental method for the optimal acquisition of experimental modal data was arrived upon. After the model correlation and calibration was performed a validation experiment was used to confirm the FE models predictive capabilities.