Publications

Results 76–100 of 127

Search results

Jump to search filters

Probability Distribution of von Mises Stress in the Presence of Pre-Load

Segalman, Daniel J.; Field, Richard V.; Reese, Garth M.

Random vibration under preload is important in multiple endeavors, including those involving launch and re-entry. There are some methods in the literature to begin to address this problem, but there is nothing that accommodates the existence of preloads and the necessity of making probabilistic statements about the stress levels likely to be encountered. An approach to achieve to this goal is presented along with several simple illustrations.

More Details
TYPE SAND Report YEAR 2013
DOIOSTI

Statistical surrogate models for prediction of high-consequence climate change

Field, Richard V.; Constantine, Paul G.; Boslough, Mark

In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest. A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.

More Details
TYPE SAND Report YEAR 2011
DOIOSTI

Computational thermal, chemical, fluid, and solid mechanics for geosystems management

Martinez, Mario J.; Red-Horse, John R.; Carnes, Brian; Mesh, Mikhail; Field, Richard V.; Davison, Scott M.; Yoon, Hongkyu; Bishop, Joseph E.; Newell, Pania; Notz, Patrick K.; Turner, D.Z.; Subia, Samuel R.; Hopkins, Polly L.; Moffat, Harry K.; Jove-Colon, Carlos; Dewers, Thomas; Klise, Katherine A.

This document summarizes research performed under the SNL LDRD entitled - Computational Mechanics for Geosystems Management to Support the Energy and Natural Resources Mission. The main accomplishment was development of a foundational SNL capability for computational thermal, chemical, fluid, and solid mechanics analysis of geosystems. The code was developed within the SNL Sierra software system. This report summarizes the capabilities of the simulation code and the supporting research and development conducted under this LDRD. The main goal of this project was the development of a foundational capability for coupled thermal, hydrological, mechanical, chemical (THMC) simulation of heterogeneous geosystems utilizing massively parallel processing. To solve these complex issues, this project integrated research in numerical mathematics and algorithms for chemically reactive multiphase systems with computer science research in adaptive coupled solution control and framework architecture. This report summarizes and demonstrates the capabilities that were developed together with the supporting research underlying the models. Key accomplishments are: (1) General capability for modeling nonisothermal, multiphase, multicomponent flow in heterogeneous porous geologic materials; (2) General capability to model multiphase reactive transport of species in heterogeneous porous media; (3) Constitutive models for describing real, general geomaterials under multiphase conditions utilizing laboratory data; (4) General capability to couple nonisothermal reactive flow with geomechanics (THMC); (5) Phase behavior thermodynamics for the CO2-H2O-NaCl system. General implementation enables modeling of other fluid mixtures. Adaptive look-up tables enable thermodynamic capability to other simulators; (6) Capability for statistical modeling of heterogeneity in geologic materials; and (7) Simulator utilizes unstructured grids on parallel processing computers.

More Details
TYPE SAND Report YEAR 2011
DOIOSTI

Predicting fracture in micron-scale polycrystalline silicon MEMS structures

Boyce, Brad L.; Foulk, James W.; Field, Richard V.; Ohlhausen, J.A.

Designing reliable MEMS structures presents numerous challenges. Polycrystalline silicon fractures in a brittle manner with considerable variability in measured strength. Furthermore, it is not clear how to use a measured tensile strength distribution to predict the strength of a complex MEMS structure. To address such issues, two recently developed high throughput MEMS tensile test techniques have been used to measure strength distribution tails. The measured tensile strength distributions enable the definition of a threshold strength as well as an inferred maximum flaw size. The nature of strength-controlling flaws has been identified and sources of the observed variation in strength investigated. A double edge-notched specimen geometry was also tested to study the effect of a severe, micron-scale stress concentration on the measured strength distribution. Strength-based, Weibull-based, and fracture mechanics-based failure analyses were performed and compared with the experimental results.

More Details
TYPE SAND Report YEAR 2010
DOIOSTI
Results 76–100 of 127
Results 76–100 of 127
Top