Correlations from ion-pairing and the Nernst-Einstein equation

We present a new approximation to ionic conductivity well suited to dynamical atomic-scale simulations, based on the Nernst-Einstein equation. In our approximation, ionic aggregates constitute the elementary charge carriers, and are considered as non-interacting species. This approach conveniently captures the dominant effect of ion-ion correlations on conductivity, short range interactions in the form of clustering. In addition to providing better estimates to the conductivity at a lower computational cost than exact approaches, this new method allows to understand the physical mechanisms driving ion conduction in concentrated electrolytes. As an example, we consider Li$^+$ conduction in poly(ethylene oxide), a standard solid-state polymer electrolyte. Using our newly developed approach, we are able to reproduce recent experimental results reporting negative cation transference numbers at high salt concentrations, and to confirm that this effect can be caused by a large population of negatively charged clusters involving cations

Romans 12 living : older adults and the call to serve

https://place.asburyseminary.edu/ecommonsatsdissertations/2120/thumbnail.jp

Plant taxonomy of the Salish and Kootenai Indians of western Montana

A detailed study of the native plants used the tribes of the Flathead Reservation

Fabrication and Compressive Behavior of Corrugated Aramid-Epoxy Cellular Solids

Cellular solids are materials whose base material does not always occupy the entire solid fraction available. A number of cellular solids can provide blast protection and absorb impact energy, but few perform well resisting blunt object (ballistic) penetration. In this thesis, a method is proposed for fabricating cellular solids from aramid-epoxy composites that can absorb impact energy and resist blunt object penetration. The aramid-epoxy samples were fabricated using wet-layup techniques, with two different styles of Kevlar 49 woven fabric in a variety of orientations. Test sample density ranged from 0.08 0.23 g/cm3. Different lamination orientations, assembly techniques, and bonding adhesives were investigated and assessed for their effect on quasi-static and dynamic crushing. A maximum plateau stress of 1.5 MPa was recorded with corresponding energy absorption of 4.2 J/g; values comparable to commercially produced metal foams. Methods for prediction of mechanical properties are presented/assessed along with suggestions for further improvements

A trajectory planning scheme for spacecraft in the space station environment

Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is special because the space station will define a multivehicle environment in space. The optimization surface is a complex nonlinear function of the initial conditions of the chase and target crafts. Small permutations in the input conditions can result in abrupt changes to the optimization surface. Since no prior knowledge about the number or location of local minima on the surface is available, the optimization must be capable of functioning on a multimodal surface. It was reported in the literature that the simulated annealing algorithm is more effective on such surfaces than descent techniques using random starting points. The simulated annealing optimization was found to be capable of identifying a minimum fuel, two-burn trajectory subject to four constraints which are integrated into the optimization using a barrier method. The computations required to solve the optimization are fast enough that missions could be planned on board the space station. Potential applications for on board planning of missions are numerous. Future research topics may include optimal planning of multi-waypoint maneuvers using a knowledge base to guide the optimization, and a study aimed at developing robust annealing schedules for potential on board missions

Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics in Materials

Understanding the dynamical processes that govern the performance of functional materials is essential for the design of next generation materials to tackle global energy and environmental challenges. Many of these processes involve the dynamics of individual atoms or small molecules in condensed phases, e.g. lithium ions in electrolytes, water molecules in membranes, molten atoms at interfaces, etc., which are difficult to understand due to the complexity of local environments. In this work, we develop graph dynamical networks, an unsupervised learning approach for understanding atomic scale dynamics in arbitrary phases and environments from molecular dynamics simulations. We show that important dynamical information can be learned for various multi-component amorphous material systems, which is difficult to obtain otherwise. With the large amounts of molecular dynamics data generated everyday in nearly every aspect of materials design, this approach provides a broadly useful, automated tool to understand atomic scale dynamics in material systems.Comment: 25 + 7 pages, 5 + 3 figure

Spatial Endogenous Fire Risk and Efficient Fuel Management and Timber Harvest

This paper integrates a spatial fire behavior model and a stochastic dynamic optimization model to determine the optimal spatial pattern of fuel management and timber harvest. Each years fire season causes the loss of forest values and lives in the western US. This paper uses a multi-plot analysis and incorporates uncertainty about fire ignition locations and weather conditions to inform policy by examining the role of spatial endogenous risk - where management actions on one stand affect fire risk in that and adjacent stands. The results support two current strategies, but question two other strategies, for managing forests with fire risk.Resource /Energy Economics and Policy,

Effect of Corn Price on Profitability of Control Vs Phytase Enhanced Diet of Hogs

Economic Simulation model (SIMETAR) was used to investigate the effect of future corn price on profitability of control and phytase enhanced diet of hogs. The completed simulation model was used to estimate probability distribution for control vs lower excretion diet profitability under different corn prices. Data used was collected from recent field trials in Oklahoma that tested the effect of phytase enhanced diets on reducing phosphorus emission. The results showed that as the market price of corn increases control diet will be more profitable than phytase enhanced diet, given the cost of other remaining feed ingredient is constant for both the diets.profitability, SIMETAR, control diet, phytase enhanced diet, swine, Production Economics,