Lee Glascoe

DEVELOPMENT AND APPLICATION OF A FAST-RUNNING TOOL TO CHARACTERIZE SHOCK DAMAGE WITHIN TUNNEL STRUCTURES

Successful but time-intensive use of high-fidelity computational capabilities for shock loading events and resultant effects on and within enclosed structures, e.g., tunnels, has led to an interest in developing more expedient methods of analysis. While several tools are currently available for the general study of the failure of structures under dynamic shock loads at a distance, presented are a pair of statistics- and physics-based tools that can be used to differentiate different types of damage (e.g., breach versus yield) as well as quantify the amount of damage within tunnels for loads close-in and with standoff. Use of such faster running tools allows for scoping and planning of more detailed model and test analysis and provides a way to address parametric sensitivity over a large multivariate space.

International challenge to model the long-range transport of radioxenon released from medical isotope production to six Comprehensive Nuclear-Test-Ban Treaty monitoring stations

After performing a first multi-model exercise in 2015 a comprehensive and technically more demanding atmospheric transport modelling challenge was organized in 2016. Release data were provided by the Australian Nuclear Science and Technology Organization radiopharmaceutical facility in Sydney (Australia) for a one month period. Measured samples for the same time frame were gathered from six International Monitoring System stations in the Southern Hemisphere with distances to the source ranging between 680 (Melbourne) and about 17,000 km (Tristan da Cunha). Participants were prompted to work with unit emissions in pre-defined emission intervals (daily, half-daily, 3-hourly and hourly emission segment lengths) and in order to perform a blind test actual emission values were not provided to them. Despite the quite different settings of the two atmospheric transport modelling challenges there is common evidence that for long-range atmospheric transport using temporally highly resolved emissions and highly space-resolved meteorological input fields has no significant advantage compared to using lower resolved ones. As well an uncertainty of up to 20% in the daily stack emission data turns out to be acceptable for the purpose of a study like this. Model performance at individual stations is quite diverse depending largely on successfully capturing boundary layer processes. No single model-meteorology combination performs best for all stations. Moreover, the stations statistics do not depend on the distance between the source and the individual stations. Finally, it became more evident how future exercises need to be designed. Set-up parameters like the meteorological driver or the output grid resolution should be pre-scribed in order to enhance diversity as well as comparability among model runs.

Constrained classification for infrastructure threat assessment

Validated computer simulation is an important aspect of critical infrastructure vulnerability assessment. The high computational cost of such models limits the number of threat scenarios that may be directly evaluated, which leads to a need for statistical emulation to predict outcomes for additional scenarios. Our particular area of interest is statistical methods for emulating complex computer codes that predict if a particular tunnel/explosive configuration results in the breaching of an underground transportation tunnel. In this case, there is considerable a priori information as to the properties of this breach classification boundary. We propose a constrained classifier, in the form of a parametric support vector machine, that allows us to incorporate expert knowledge into the shape of the decision boundary. We demonstrate the effectiveness of this technique with both a simulation study and by applying the method to a tunnel breach data set. This analysis reveals that constrained classification can offer substantial benefits for small sample sizes. The technique may be used either to provide a final classification result in the face of extremely limited data or as an interim step to guide adaptive sampling.

Assessing the Vulnerability of Large Critical Infrastructure Using Fully-Coupled Blast Effects Modeling

Structural failures, such as the MacArthur Maze I-880 overpass in Oakland, California and the I-35 bridge in Minneapolis, Minnesota, are recent examples of our national infrastructures fragility and serve as an important reminder of such infrastructure in our everyday lives. These two failures, as well as the World Trade Centers collapse and the levee failures in New Orleans, highlight the national importance of protecting our infrastructure as much as possible against acts of terrorism and natural hazards. This paper describes a process for evaluating the vulnerability of critical infrastructure to large blast loads using a fully-coupled finite element approach. A description of the finite element software and modeling technique is discussed along with the experimental validation of the numerical tools. We discuss how such an approach can be used for specific problems such as modeling the progressive collapse of a building.

A mitigation scheme for underwater blast: Experiments and modeling

A novel but relatively easy-to-implement mitigation concept to enforce standoff distance and reduce shock loading on a vertical, partially-submerged structure is evaluated experimentally using scaled aquarium experiments and numerically using a high-fidelity finite element code. Scaled, watertamped explosive experiments were performed using aquariums of different sizes. The effectiveness of different mitigation configurations, including air-filled media and an air gap, is assessed relative to an unmitigated detonation using the same charge weight and standoff distance. Experiments using an airfilled media mitigation concept effectively dampen the explosive response of an aluminum plate and reduce the final displacement at plate center by approximately half. Experiments using an air-gap resulted in a focused water slug hitting the plate, an effect we hypothesize to be due to water encasement of the charge. Finite element simulations used for the initial experimental design compare very well to experiments ...

Validation of HADES-based simulations of radiographic experiments

As a part of a code validation study, we have compared radiographic simulations generated using the HADES code against experimental measurements of a set of common materials of known composition and density: graphite, Teflon, Delrin, magnesium, silicon, titanium, and water cylinders. HADES calculations show good agreement with radiograph measurements. Discrepancies between simulation and experimental data are analyzed. Sources of error and future model improvement are discussed.

A Bayesian Measurement Error Model for Misaligned Radiographic Data

An understanding of the inherent variability in micro-computed tomography (micro-CT) data is essential to tasks such as statistical process control and the validation of radiographic simulation tools. These data present unique challenges to variability analysis due to the relatively low resolution of radiographs, and also due to minor variations from run to run which can result in misalignment or magnification changes between repeated measurements of a sample. Such positioning changes artificially inflate the variability of the data in ways that mask true physical phenomena. We present a novel Bayesian nonparametric regression model that incorporates both additive and multiplicative measurement error in addition to heteroscedasticity to address this problem. We use this model to assess the effects of sample thickness and sample position on measurement variability for an aluminum specimen. Supplementary materials for this article are available online.

California Natural Gas Pipelines: A Brief Guide

The purpose of this document is to familiarize the reader with the general configuration and operation of the natural gas pipelines in California and to discuss potential LLNL contributions that would support the Partnership for the 21st Century collaboration. First, pipeline infrastructure will be reviewed. Then, recent pipeline events will be examined. Selected current pipeline industry research will be summarized. Finally, industry acronyms are listed for reference.

Securing infrastructure from high explosive threats

Lawrence Livermore National Laboratory (LLNL) is working with the Department of Homeland Securitys Science and Technology Directorate, the Transportation Security Administration, and several infrastructure partners to characterize and help mitigate principal structural vulnerabilities to explosive threats. Given the importance of infrastructure to the nations security and economy, there is a clear need for applied research and analyses (1) to improve understanding of the vulnerabilities of these systems to explosive threats and (2) to provide decision makers with time-critical technical assistance concerning countermeasure and mitigation options. Fully-coupled high performance calculations of structural response to ideal and non-ideal explosives help bound and quantify specific critical vulnerabilities, and help identify possible corrective schemes. Experimental validation of modeling approaches and methodologies builds confidence in the prediction, while advanced stochastic techniques allow for optimal use of scarce computational resources to efficiently provide infrastructure owners and decision makers with timely analyses.