Computationally efficient representation of statistically described material microstructure for tractable forming simulations

The purpose of this project is to reduce a large statistical distribution of metal microstructure orientations to a manageable distribution to be used in metal forming simulations. Microstructure sensitive simulations at the macro-scale are impractical, because with so many state variables associated with material microstructure data, these simulations are extremely computationally expensive. The goal was to develop a framework to accurately model plastic material response while repre- senting the material microstructure in a more compact form, reducing 106 or more microstructure orientations to a significantly smaller statistical distribution of representative orientations. This will significantly increase the computational efficiency and make the design process known as mi- crostructure sensitive design (MSD) feasible for industry applications. This framework is applied to metals with both cubic and hexagonal structure to validate this approach for slip and twinning deformation mechanisms. Performing microstructure sensitive metal-forming simulations is widely recognized as a computational challenge because of the need to store large sets of state variables related to microstructure data. This makes the investigation of the accuracy of smaller, representative data sets in these simulations profitable. The project accomplished two main goals; the development of an effective fitting algorithm to generate compacted data sets and validation of the framework for data compaction on metals with cubic structure, and hexagonal symmetry, with and without twinning. The research was applied to oxygen-free high-conductivity copper (OFHC Cu) and 6016 aluminum (Al-6016) for application of the framework to cubic metals. An anisotropic (clock-rolled) zirconium (Zr) texture was used to develop the framework for hexagonal metals. The minimum accurate data set for cubic was determined to be 825 orientations and for hexagonal metals, considering twinning and absence of twinning, the minimum number was 1600 orientations. This compaction method will increase the computational speed of microstructure sensitive forming simulations by several orders of magnitude, contributing to the computational feasibility of microstructure informed design

Harnessing Markets for Water Quality

This issue of IMPACT is devoted to exploring and understanding the opportunities and challenges of harnessing markets to improve water quality. It looks at how markets could be implemented to address the growing concern of nonpoint source pollution as well as point sources. Recently, the EPA proposed a water quality trading proposal, which is summarized, reviewed, and critiqued

Computationally efficient representation of statistically described material microstructure for tractable forming simulations

The purpose of this project is to reduce a large statistical distribution of metal microstructure orientations to a manageable distribution to be used in metal forming simulations. Microstructure sensitive simulations at the macro-scale are impractical, because with so many state variables associated with material microstructure data, these simulations are extremely computationally expensive. The goal was to develop a framework to accurately model plastic material response while representing the material microstructure in a more compact form, reducing 106 or more microstructure orientations to a significantly smaller statistical distribution of representative orientations. This will significantly increase the computational efficiency and make the design process known as microstructure sensitive design (MSD) feasible for industry applications. This framework is applied to metals with both cubic and hexagonal structure to validate this approach for slip and twinning deformation mechanisms. Performing microstructure sensitive metal-forming simulations is widely recognized as a computational challenge because of the need to store large sets of state variables related to microstructure data. This makes the investigation of the accuracy of smaller, representative data sets in these simulations profitable. The project accomplished two main goals; the development of an effective fitting algorithm to generate compacted data sets and validation of the framework for data compaction on metals with cubic structure, and hexagonal symmetry, with and without twinning. The research was applied to oxygen-free high-conductivity copper (OFHC Cu) and 6016 aluminum (Al-6016) for application of the framework to cubic metals. An anisotropic (clock-rolled) zirconium (Zr) texture was used to develop the framework for hexagonal metals. The minimum accurate data set for cubic was determined to be 825 orientations and for hexagonal metals, considering twinning and absence of twinning, the minimum number was 1600 orientations. This compaction method will increase the computational speed of microstructure sensitive forming simulations by several orders of magnitude, contributing to the computational feasibility of microstructure informed design

Ambient Rivers Monitoring in NH Coastal Watersheds 2004

The Department of Environmental Services (DES) received funding from the New Hampshire Estuaries Project (NHEP) to conduct monitoring activities in 2004. The activities described in this report were led by the DES Watershed Assistance Section and involved water monitoring in tidal tributaries. These monitoring activities were completed with the overall purpose of improving the understanding of water quality trends. The Department of Environmental Services completed all tasks as planned. This report includes the sample collection information, field data, and laboratory data. Data summaries and interpretations will come at a later time in other DES and NHEP publications

Commentary on Resilient Families Help Make Resilient Children

This commentary outlines the strengths of the resilience-based family therapy approach. It describes the need for additional research in this area to advance the field and particular challenges that the field faces