Directed nonabelian sandpile models on trees

We define two general classes of nonabelian sandpile models on directed trees (or arborescences) as models of nonequilibrium statistical phenomena. These models have the property that sand grains can enter only through specified reservoirs, unlike the well-known abelian sandpile model. In the Trickle-down sandpile model, sand grains are allowed to move one at a time. For this model, we show that the stationary distribution is of product form. In the Landslide sandpile model, all the grains at a vertex topple at once, and here we prove formulas for all eigenvalues, their multiplicities, and the rate of convergence to stationarity. The proofs use wreath products and the representation theory of monoids.Comment: 43 pages, 5 figures; introduction improve

Corn Harvesting Handling Marketing in Ohio

PDF pages: 3

Energy Utilization in Crop and Dairy Production in Organic and Conventional Livestock Production Systems

Searching for livestock production systems with a high energy utilization is of interest because of resource use and pollution aspects and because energy use is an indicator of the intensification of production processes. Due to interactions between crop and livestock enterprises and between levels of different input factors and their effects on yields, it is proposed to analyze agricultural energy utilization through system modelling of data from farm studies. Energy use in small grains, grass-clover and fodder beets registered in organic and conventional mixed dairy farms was analyzed and used together with crop yields in order to model energy prices on three Danish soil types. Conventional crop yields were higher but they also used more indirect energy with input factors, especially fertilizers. The conventional yields were not sufficiently higher to compensate for the extra use of energy compared with the organic crops. The organic crops had lower energy prices on all soil types, with the smallest difference on irrigated sandy soils. Sensitivity analyses were made for the effects of changes in irrigation and fertilizer levels. One conclusion was that better energy utilization in grain crops might be found at intermediate levels of fertilizer use, especially on irrigated soils. Actual farm diesel use was on average 47% higher than expected from standard values, suggesting that care should be taken when basing energetic analysis of farming methods on experimental data alone. On the same farms, the energy use in dairy production registered in organic and conventional mixed dairy farms was analyzed and used together with milk and meat yields in order to model energy prices for three different feeding strategies and two soil types. Conventional dairy production is more intensive with a greater feeding ration and a higher proportion of high-protein Seed, but has also higher yields. The conventional yields were not sufficiently higher to compensate for rite extra use of energy compared with the organic feeding ration. However, the loll er energy price in organic dairy production is dependent on the composition of the feeding strategy. Substitution of 500 SFU of grain with grass pellets makes an ordinary organic feeding ration based on conventional crop production competable. In general, the crop energy price models car? be used together with the dairy production to model the effects of different feeding and crop rotation strategies on the overall energy utilization in mixed dairy production systems

Machining and grinding of ultrahigh-strength steels and stainless steel alloys

Machining and grinding of ultrahigh-strength steels and stainless steel alloy

The behaviour of a two-component backfilling grout used in a Tunnel-Boring Machine

The instantaneous filling of the annulus that is created behind the segment lining at the end of the tail during the TBM advance is an operation of paramount importance. Its main goal is to minimize the surface settlements due to any over-excavation generated by the passage of the TBM. To correctly achieve the goals, a simultaneous backfilling system and the injected material should satisfy the technical, operational and performance characteristics. A two-component system injection for the back-filling is progressively substituting the use of traditional mortars. In this paper different systems of back-filling grout and in particular the two-component system are analyzed and the results of laboratory tests are presented and discusse

Predicting Porosity and Microstructure of 3D Printed Part Using Machine Learning

Additive Manufacturing (AM) is characterized as building a 3-D object one layer at a time. Due to flexibility in design and functionality, additive manufacturing (AM) is an attractive technology for the manufacturing industry. Still, the lack of consistency in quality is one of the main limitations preventing the use of this process to produce end-use products. Current techniques in additive manufacturing face a significant challenge concerning various processing parameters, including scan speed/velocity, laser power, layer thickness, etc. which leads to the inconsistency of the quality of the printed products. Therefore, this research focuses on change, especially on the monitoring and regulation of processes, and helps us predict the level of porosity in a 3D printed part and classify grain growth structure as equiaxed or columnar given the simulation data using state-of-the-art machine learning algorithms. The input parameters considered in this study that affects porosity and grain growth structure are energy density, gas atmosphere, powder particle size and shape, and overlap rate. The data for training machine learning models are collected using ANSYS Additive Manufacturing simulations. The total data collected for porosity prediction is 482 data points, and for the grain growth structure is 12,333 data points. In order to predict the porosity and grain growth structure, a technique based on Artificial Intelligence (Machine learning) is suggested to make the necessary compensations to process monitoring and control, which will subsequently improve the quality of the final product. A feed-forward ANN model is trained in this methodology using an error back-propagation algorithm to predict the porosity level. Also, different classification models such as Support Vector Machines, Meta-classifier classify the microstructure as columnar or equiaxed grains, resulting in part quality improvement. The Backpropagation Neural Network model for porosity prediction gave an accuracy of 100% while outperforming other models. The best results for microstructure prediction are achieved by Meta-classifier, K-Nearest Neighbor, and Random Forest classifier with 100% accuracy. The findings in this study provide evidence and insight that Artificial intelligence and machine learning techniques can be used in the field of Additive Manufacturing for real-time process control and monitoring with the scope of implementation on a larger scale.Master of Science in EngineeringIndustrial and Systems Engineering, College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/156397/1/Priya Dhage Final Thesis.pdfDescription of Priya Dhage Final Thesis.pdf : Thesi

Action Contraction

The question we consider in this paper is: “When can a combination of fine-grain execution steps be contracted into an atomic action execution”? Our answer is basically: “When no observer can see the difference.” This is worked out in detail by defining a notion of coupled split/atomic simulation refinement between systems which differ in the atomicity of their actions, and proving that this collapses to Parrow and Sjödin’s coupled similarity when the systems are composed with an observer

Design and manufacturing of a Selective Laser Sintering test bench to test sintering materials

The goal of this project is to design and build a prototype of recoating system for a laser cutting machine to turn it into a selective laser sintering printing machine. This prototype will be used to study new sintering materials and to design, if decided, a SLS 3D printing Machine (Selective Laser Sintering). This project has been developed in the installations and funded by Fundació CIM. The project develops the mechanical design and the electronic system design. Both parts are explained on this paper, so new users can use the machine and can understand the system. With this paper, it is expected that it can be improved in a future to test other parameters and configurations. The paper is divided in three basic blocks that are summed up here: The first block is an introduction to the 3D printing technologies. The most used of them are explained and selective laser sintering is explained in deep. With this block the reader can understand why it is important to develop the SLS technology and what has to be done to improve the machines and the technology. The second block is a discussion on the mechanical design of the machine. The general idea of the machine is explained so the user can understand why the machine is designed in this way. After that, each part is detailed to see how the different mechanical challenges where overtaken. At the end of the block, there is a small calculations section needed on the electronic part. The third block is an extensive explanation of the electronic system that controls and moves the machine. In that block, the different components are explained so the user can understand its basics working principles. It is also explained how the selection of the electronic components was done. Then everything is put together to see the whole electronic system. Along with this paper, there are annexes that provide some extra information for the reader. One of this annexes refers to the mechanical part and the other one has some datasheets and coding for the electronic section. The whole design has been done in SOLIDWORKS cad software and its electric extension ELECWORKS. The programming job was done with Arduino compiler

EVALUATIONS IN 2003 OF FIVE AREAS OF INVESTMENT IN R&D BY NSW AGRICULTURE: SUMMARY

In 2003 the economic, social and environmental impacts of five areas of research and extension where NSW Agriculture has made significant investments were evaluated. These investment areas included net feed efficiency in beef cattle; the management of temperate weeds in temperate pastures; conservation farming in the northern NSW cropping zone; wheat breeding in NSW; and extension in water use efficient technologies. The benefit cost analyses were conducted over the period from 1980 to 2020. For these five project areas NSW Agriculture invested $114m, including some support from industry. The industry returns totalled$1311m giving an average benefit-cost ratio of 11.5, ranging from 4.5 to 22.2.Research and Development/Tech Change/Emerging Technologies,