Exascale computing promises quantities of data too large to efficiently store and transfer across networks in order to be able to analyze and visualize the results. We investigate compressed sensing (CS) as an in situ method to reduce the size of the data as it is being generated during a large-scale simulation. CS works by sampling the data on the computational cluster within an alternative function space such as wavelet bases and then reconstructing back to the original space on visualization platforms. While much work has gone into exploring CS on structured datasets, such as image data, we investigate its usefulness for point clouds such as unstructured mesh datasets often found in finite element simulations. We sample using a technique that exhibits low coherence with tree wavelets found to be suitable for point clouds. We reconstruct using the stagewise orthogonal matching pursuit algorithm that we improved to facilitate automated use in batch jobs. We analyze the achievable compression ratios and the quality and accuracy of reconstructed results at each compression ratio. In the considered case studies, we are able to achieve compression ratios up to two orders of magnitude with reasonable reconstruction accuracy and minimal visual deterioration in the data. Our results suggest that, compared to other compression techniques, CS is attractive in cases where the compression overhead has to be minimized and where the reconstruction cost is not a significant concern.
The significantly higher buoyancy of hydrogen compared to natural gas means that hazardous zones defined in the IGF code may be inaccurate if applied to hydrogen. This could place undue burden on ship design or could lead to situations that are unknowingly unsafe. We present dispersion analyses to examine three vessel case studies: (1) abnormal external vents of full blowdown of a liquid hydrogen tank due to a failed relief device in still air and with crosswind; (2) vents due to naturally-occurring boil-off of liquid within the tank; and (3) a leak from the pipes leading into the fuel cell room. The size of the hydrogen plumes resulting from a blowdown of the tank depend greatly on the wind conditions. It was also found that for normal operations releasing a small amount of "boil- off" gas to regulate the pressure in the tank does not create flammable concentrations.
This presentation describes the SF-BREEZE feasibility study and how gas dispersion analysis can be used to examine maritime hazardous zone regulations applied to hydrogen.
The proposed Aero-MINE technology will extract energy from wind without any exterior moving parts. Aero-MINEs can be integrated into buildings or function stand-alone, and are scalable. This gives them advantages similar to solar panels, but with the added benefit of operation in cloudy or dark conditions. Furthermore, compared to solar panels, Aero-MINEs can be manufactured at lower cost and with less environmental impact. Power generation is isolated internally by the pneumatic transmission of air and the outlet air-jet nozzles amplify the effectiveness. Multiple units can be connected to one centrally located electric generator. Aero-MINEs are ideal for the built-environment, with numerous possible configurations ranging from architectural integration to modular bolt-on products. Traditional wind turbines suffer from many fundamental challenges. The fast-moving blades produce significant aero-acoustic noise, visual disturbances, light-induced flickering and impose wildlife mortality risks. The conversion of massive mechanical torque to electricity is a challenge for gears, generators and power conversion electronics. In addition, the installation, operation and maintenance of wind turbines is required at significant height. Furthermore, wind farms are often in remote locations far from dense regions of electricity customers. These technical and logistical challenges add significantly to the cost of the electricity produced by utility-scale wind farms. In contrast, distributed wind energy eliminates many of the logistical challenges. However, solutions such as micro-turbines produce relatively small amounts of energy due to the reduction in swept area and still suffer from the motion-related disadvantages of utility-scale turbines. Aero-MINEs combine the best features of distributed generation, while eliminating the disadvantages.
The HyRAM software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM is designed to facilitate the use of state-of-the-art science and engineering models to conduct robust, repeatable assessments of hydrogen safety, hazards, and risk. HyRAM is envisioned as a unifying platform combining validated, analytical models of hydrogen behavior, a stan- dardized, transparent QRA approach, and engineering models and generic data for hydrogen installations. HyRAM is being developed at Sandia National Laboratories for the U. S. De- partment of Energy to increase access to technical data about hydrogen safety and to enable the use of that data to support development and revision of national and international codes and standards. This document provides a description of the methodology and models contained in the HyRAM version 1.1. HyRAM 1.1 includes generic probabilities for hydrogen equipment fail- ures, probabilistic models for the impact of heat flux on humans and structures, and computa- tionally and experimentally validated analytical and first order models of hydrogen release and flame physics. HyRAM 1.1 integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing hydrogen hazards (thermal effects from jet fires, overpressure effects from deflagrations), and assessing impact on people and structures. HyRAM is a prototype software in active development and thus the models and data may change. This report will be updated at appropriate developmental intervals.
A computational fluid dynamics (CFD) analysis of a natural gas vehicle experie ncing a mechanical failure of a pressure relief device on a full CNG cylinder was completed to determine the resulting amount and location of flammable gas. The resulting overpressure if it were to ignite was also calculated. This study completes what is d iscussed in Ekoto et al. [1] which covers other related leak scenarios. We are not determining whether or not this is a credible release, rather just showing the result of a possible worst case scenario. The Sandia National Laboratories computational tool Netflow was used to calculate the leak velocity and temperature. The in - house CFD code Fuego was used to determine the flow of the leak into the maintenance garage. A maximum flammable mass of 35 kg collected along the roof of the garage. This would result in an overpressure that could do considerable damage if it were to ignite at the time of this maximum volume. It is up to the code committees to decide whet her this would be a credible leak, but if it were, there should be preventions to keep the flammable mass from igniting. Keywords: Natural Gas Vehicle Maintenance Facility, Pressure Relief Device Failure, CFD
The objective of this work is to investigate the efficacy of using calibration strategies from Uncertainty Quantification (UQ) to determine model coefficients for LES. As the target methods are for engineering LES, uncertainty from numerical aspects of the model must also be quantified. 15 The ultimate goal of this research thread is to generate a cost versus accuracy curve for LES such that the cost could be minimized given an accuracy prescribed by an engineering need. Realization of this goal would enable LES to serve as a predictive simulation tool within the engineering design process.