Probabilistic Grid reliability analysis with energy storage systems (progress)
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Poster for DAHCS LDRD demo day
Abstract Galaxies are biased tracers of the underlying cosmic web, which is dominated by dark matter (DM) components that cannot be directly observed. Galaxy formation simulations can be used to study the relationship between DM density fields and galaxy distributions. However, this relationship can be sensitive to assumptions in cosmology and astrophysical processes embedded in galaxy formation models, which remain uncertain in many aspects. In this work, we develop a diffusion generative model to reconstruct DM fields from galaxies. The diffusion model is trained on the CAMELS simulation suite that contains thousands of state-of-the-art galaxy formation simulations with varying cosmological parameters and subgrid astrophysics. We demonstrate that the diffusion model can predict the unbiased posterior distribution of the underlying DM fields from the given stellar density fields while being able to marginalize over uncertainties in cosmological and astrophysical models. Interestingly, the model generalizes to simulation volumes ≈500 times larger than those it was trained on and across different galaxy formation models. The code for reproducing these results can be found athttps://github.com/victoriaono/variational-diffusion-cdm✎.
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Proposed reliability model used in the computation of system reliability from a knowledge of the reliability of component parts
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Probability method for position and motion of large numbers of constant-level balloons - atmospheric circulation
Publication presents a total long range planning model for project oriented organizations. The total model consists of planning systems which originate - /1/ at the project level and consolidate into an overall plan, and /2/ from a budetary ceiling and allocate to the individual projects. Analysis of /1/ and /2/ is provided for management decision making.
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Learning scheme for solving unsupervised learning problems with correct estimate convergence and for state estimates of Gauss-Markov sequences with additive and multiplicative observed noise
Likely fundamental inadequacies in the model of planetary contamination advanced by Sagan and Coleman are discussed. It is shown that a relatively minor modification of the basic Sagan-Coleman formula yields approximations that are generally adequate with data in the range of interest. This approximation formula differs from the original Sagan-Coleman version only through an initial conditioning on landing outcome. It always yields an upper (conservative) bound for the total probability of contamination, this appealing feature is lost if the conditioning on landing outcome is deleted.
Recent advances in observational techniques related to geodetic work (VLBI, laser ranging) make it imperative that more consideration should be given to modeling problems. Uncertainties in the effect of atmospheric refraction, polar motion and precession-nutation parameters, cannot be dispensed with in the context of centimeter level geodesy. Even physical processes that have generally been previously altogether neglected (station motions) must now be taken into consideration. The problem of modeling functions of time or space, or at least their values at observation points (epochs) is explored. When the nature of the function to be modeled is unknown. The need to include a limited number of terms and to a priori decide upon a specific form may result in a representation which fails to sufficiently approximate the unknown function. An alternative approach of increasing application is the modeling of unknown functions as stochastic processes.
The design of an optimal merged keycode data base information retrieval system is detailed. A probability distribution of n-bit binary words that minimized false drops was developed for the case where the set of desired records was a subset of tagged records.
In order to estimate the potential risks due to carbon fibers (CF) released from aircraft accidents, it was necessary to quantify the probability of an accident or incident at a major hub airport. This probability was contingent upon various conditions surrounding the incident including the phase of operation, aircraft type, and the weather conditions. The type of accident predicted was categorized according to its location relative to the runway and the severity of damage sustained. The methodology utilized to estimate the probability of a specific type of accident is outlined and the various models that were developed in the course of this work are described.
There are no author-identified significant results in this report.
The statistical problems of airborne carbon fibers falling onto electrical circuits were idealized and analyzed. The probability of making contact between randomly oriented finite length fibers and sets of parallel conductors with various spacings and lengths was developed theoretically. The probability of multiple fibers joining to bridge a single gap between conductors, or forming continuous networks is included. From these theoretical considerations, practical statistical analyses to assess the likelihood of causing electrical malfunctions was produced. The statistics obtained were confirmed by comparison with results of controlled experiments.
A financial accounting model that incorporates physical and institutional uncertainties was developed for geothermal projects. Among the uncertainties it can handle are well depth, flow rate, fluid temperature, and permit and construction times. The outputs of the model are cumulative probability distributions of financial measures such as capital cost, levelized cost, and profit. These outputs are well suited for use in an investment decision incorporating risk. The model has the powerful feature that conditional probability distribution can be used to account for correlations among any of the input variables. The model has been applied to a geothermal reservoir at Heber, California, for a 45-MW binary electric plant. Under the assumptions made, the reservoir appears to be economically viable.