Field To Flight: A Techno-Economic Analysis of Stover to Aviation Biofuels Supply Chain

Greenhouse gas emissions have been a growing concern. The transportation sector contributes to one-third of GHG emissions in the United States from fossil fuel burning. The Renewable Fuel Standard set a requirement for 16 billion gallons (ethanol equivalent) of cellulosic biofuels to be used in the market. Aviation biofuels can help to meet both of these problems as well as improve U.S. energy security. Investment in the biofuel industry carries a lot of risk. The biofuel industry is run by the private sector, but can be incentivized by government. Cellulosic biofuels carry even more risk than first generation biofuels, because conversion technology is more expensive. As a result, incentives are needed to reduce the risk for private investors. Government can implement policies to reduce the risk in investment in aviation biofuels. The issue is choosing which policy will provide the most reduction in risk, while providing a lowest cost to the government. This analysis focuses on aviation biofuel production using fast pyrolysis from corn stover. Cost benefit analysis is used to calculate the net present value, internal rate of return, and benefit-cost ratio for a plant. We look at deterministic and stochastic cases. For the stochastic cases, this study uses @Risk, a Palisades Corporation software to determine the risk of investment in aviation biofuels. Uncertainty is added to fuel price and four technical variables: capital cost, final fuel yield, hydrogen cost, and feedstock cost. The fuel price can be steady or increasing at DOE projections. We look at the impact of three policies: reverse auction, competitive capital subsidy, and carbon tax. For the reverse auction and capital subsidy, we used contract lengths of 5, 10, and 15 years to see the impact a longer contract could have on probability of loss. All three policies reduced risk in investment of aviation biofuels. A reverse auction reduced risk of investment the most. As the contract length increased, the probability of loss and coefficient of variation in net present value were reduced substantially. When fuel price increased stochastically and a contract length of 15 years was used, probability of loss was reduced to 9.9 percent

Lattice Models of Quantum Gravity

Standard Regge Calculus provides an interesting method to explore quantum gravity in a non-perturbative fashion but turns out to be a CPU-time demanding enterprise. One therefore seeks for suitable approximations which retain most of its universal features. The $Z_2$-Regge model could be such a desired simplification. Here the quadratic edge lengths $q$ of the simplicial complexes are restricted to only two possible values $q=1+\epsilon\sigma$, with $\sigma=\pm 1$, in close analogy to the ancestor of all lattice theories, the Ising model. To test whether this simpler model still contains the essential qualities of the standard Regge Calculus, we study both models in two dimensions and determine several observables on the same lattice size. In order to compare expectation values, e.g. of the average curvature or the Liouville field susceptibility, we employ in both models the same functional integration measure. The phase structure is under current investigation using mean field theory and numerical simulation.Comment: 4 pages, 1 figure

Bound States in Sharply Bent Waveguides: Analytical and Experimental Approach

Quantum wires and electromagnetic waveguides possess common features since their physics is described by the same wave equation. We exploit this analogy to investigate experimentally with microwave waveguides and theoretically with the help of an effective potential approach the occurrence of bound states in sharply bent quantum wires. In particular, we compute the bound states, study the features of the transition from a bound to an unbound state caused by the variation of the bending angle and determine the critical bending angles at which such a transition takes place. The predictions are confirmed by calculations based on a conventional numerical method as well as experimental measurements of the spectra and electric field intensity distributions of electromagnetic waveguides

Computer-aided Melody Note Transcription Using the Tony Software: Accuracy and Efficiency

accepteddate-added: 2015-05-24 19:18:46 +0000 date-modified: 2017-12-28 10:36:36 +0000 keywords: Tony, melody, note, transcription, open source software bdsk-url-1: https://code.soundsoftware.ac.uk/attachments/download/1423/tony-paper_preprint.pdfdate-added: 2015-05-24 19:18:46 +0000 date-modified: 2017-12-28 10:36:36 +0000 keywords: Tony, melody, note, transcription, open source software bdsk-url-1: https://code.soundsoftware.ac.uk/attachments/download/1423/tony-paper_preprint.pdfWe present Tony, a software tool for the interactive an- notation of melodies from monophonic audio recordings, and evaluate its usability and the accuracy of its note extraction method. The scientific study of acoustic performances of melodies, whether sung or played, requires the accurate transcription of notes and pitches. To achieve the desired transcription accuracy for a particular application, researchers manually correct results obtained by automatic methods. Tony is an interactive tool directly aimed at making this correction task efficient. It provides (a) state-of-the art algorithms for pitch and note estimation, (b) visual and auditory feedback for easy error-spotting, (c) an intelligent graphical user interface through which the user can rapidly correct estimation errors, (d) extensive export functions enabling further processing in other applications. We show that Tony’s built in automatic note transcription method compares favourably with existing tools. We report how long it takes to annotate recordings on a set of 96 solo vocal recordings and study the effect of piece, the number of edits made and the annotator’s increasing mastery of the software. Tony is Open Source software, with source code and compiled binaries for Windows, Mac OS X and Linux available from https://code.soundsoftware.ac.uk/projects/tony/

What makes slow samples slow in the Sherrington-Kirkpatrick model

Using results of a Monte Carlo simulation of the Sherrington-Kirkpatrick model, we try to characterize the slow disorder samples, namely we analyze visually the correlation between the relaxation time for a given disorder sample $J$ with several observables of the system for the same disorder sample. For temperatures below $T_c$ but not too low, fast samples (small relaxation times) are clearly correlated with a small value of the largest eigenvalue of the coupling matrix, a large value of the site averaged local field probability distribution at the origin, or a small value of the squared overlap $$. Within our limited data, the correlation remains as the system size increases but becomes less clear as the temperature is decreased (the correlation with$$ is more robust) . There is a strong correlation between the values of the relaxation time for two distinct values of the temperature, but this correlation decreases as the system size is increased. This may indicate the onset of temperature chaos