The dimensionless extinction coefficient, Ke, was measured for soot produced in 2m JP-8 pool fires. Light extinction and gravimetric sampling measurements were performed simultaneously at 635 and 1310nm wavelengths at three heights in the flame zone and in the overfire region. Measured average Ke values of 8.41.2 at 635nm and 8.71.1 at 1310nm in the overfire region agree well with values from 8-10 recently reported for different fuels and flame conditions. The overfire Ke values are also relatively independent of wavelength, in agreement with recent findings for JP-8 soot in smaller flames. Ke was nearly constant at 635nm for all sampling locations in the large fires. However, at 1310nm, the overfire Ke was higher than in the flame zone. Chemical analysis of physically sampled soot shows variations in carbon-to-hydrogen (C/H) ratio and polycyclic aromatic hydrocarbon (PAH) concentration that may account for the smaller Ke values measured in the flame zone. Rayleigh-Debye-Gans theory of scattering for polydisperse fractal aggregate (RDG-PFA) was applied to measured aggregate fractal dimensions and found to under-predict the extinction coefficient by 17-30% at 635nm using commonly accepted refractive indices of soot, and agreed well with the experiments using the more recently published refractive index of 1.99-0.89i. This study represents the first measurements of soot chemistry, morphology, and optical properties in the flame zone of large, fully-turbulent pool fires, and emphasizes the importance of accurate measurements of optical properties both in the flame zone and overfire regions for models of radiative transport and interpretation of laser-based diagnostics of soot volume fraction and temperature.
Cities without an early warning system of indwelling sensors can consider monitoring their networks manually, especially during times of heightened security levels. We consider the problem of calculating an optimal schedule for manual sampling in a municipal water network. Preliminary computations with a small-scale example indicate that during normal times, manual sampling can provide some benefit, but it is far inferior to an indwelling sensor network. However, given information that significantly constrains the nature of an imminent threat, manual sampling can perform as well as a small sensor network designed to handle normal threats. Copyright ASCE 2006.
Accurate material models are fundamental to predictive structural finite element models. Because potting foams are routinely used to mitigate shock and vibration of encapsulated components in electro/mechanical systems, accurate material models of foams are needed. A linear-viscoelastic foam constitutive model has been developed to represent the foam's stiffness and damping throughout an application space defined by temperature, strain rate or frequency and strain level. Validation of this linear-viscoelastic model, which is integrated into the Salinas structural dynamics code, is being achieved by modeling and testing a series of structural geometries of increasing complexity that have been designed to ensure sensitivity to material parameters. Both experimental and analytical uncertainties are being quantified to ensure the fair assessment of model validity. Quantitative model validation metrics are being developed to provide a means of comparison for analytical model predictions to observations made in the experiments. This paper is one of several recent papers documenting the validation process for simple to complex structures with foam encapsulated components. This paper specifically focuses on model validation over a wide temperature range and using a simple dumbbell structure for modal testing and simulation. Material variations of density and modulus have been included. A double blind validation process is described that brings together test data with model predictions.
This paper presents computational simulations and experiments of water flow and contaminant transport through pipes with incomplete mixing at pipe joints. The hydraulics and contaminant transport were modeled using computational fluid dynamics software that solves the continuity, momentum, energy, and species equations (laminar and turbulent) using finite-element methods. Simulations were performed of experiments consisting of individual and multiple pipe joints where tracer and clean water were separately introduced into the pipe junction. Results showed that the incoming flow streams generally remained separated within the junction, leading to incomplete mixing of the tracer. Simulations of the mixing matched the experimental results when appropriate scaling of the tracer diffusivity (via the turbulent Schmidt number) was calibrated based on results of single-joint experiments using cross and double-T configurations. Results showed that a turbulent Schmidt number between ∼0.001-0.01 was able to account for enhanced mixing caused by instabilities along the interface of impinging flows. Unequal flow rates within the network were also shown to affect the outlet concentration at each pipe junction, with "enhanced" or "reduced" mixing possible depending on the relative flow rates entering the junction. Copyright ASCE 2006.
In this paper we present the results of a study to quantify uncertainty in experimental modal parameters due to test set-up uncertainty, measurement uncertainty, and data analysis uncertainty. Uncertainty quantification is required to accomplish a number of tasks including model updating, model validation, and assessment of unit-tounit variation. We consider uncertainty in the modal parameters due to a number of sources including force input location/direction, force amplitude, instrumentation bias, support conditions, and the analysis method (algorithmic variation). We compute the total uncertainty due to all of these sources, and discuss the importance of proper characterization of bias errors on the total uncertainty. This uncertainty quantification was applied to modal tests designed to assess modeling capabilities for emerging designs of wind turbine blades. In an example, we show that unit-to-unit variation of the modal parameters of two nominally identical wind turbine blades is successfully assessed by performing uncertainty quantification. This study aims to demonstrate the importance of the proper pre-test design and analysis for understanding the uncertainty in modal parameters, in particular uncertainty due to bias error.
In order to predict blast damage on structures, it is current industry practice to decouple shock calculations from computational structural dynamics calculations. Pressure-time histories from experimental tests were used to assess computational models developed using a shock physics code (CTH) and a structural dynamics code (PRONTO3D). CTH was shown to be able to reproduce three independent characteristics of a blast wave: arrival time, peak overpressure, and decay time. Excellent agreement was achieved for early times, where the rigid wall assumptions used in the model analysis were valid. A one-way coupling was performed for this blast-structure interaction problem by taking the pressure-time history from the shock physics simulation and applying it to the structure at the corresponding locations in the PRONTO3D simulation to capture the structural deformation. In general, the one-way coupling was shown to be a cost-effective means of predicting the structural response when the time duration of the load was less than the response time of the structure. Therefore, the computational models were successfully evaluated for the internal blast problems studied herein.
This paper investigates methods for coupling analytical dynamic models of subcomponents with experimentally derived models in order to predict the response of the combined system, focusing on modal substructuring or Component Mode Synthesis (CMS), the experimental analog to the ubiquitous Craig-Bampton method. While the basic methods for combining experimental and analytical models have been around for many years, it appears that these are not often applied successfully. The CMS theory is presented along with a new strategy, dubbed the Maximum Rank Coordinate Choice (MRCC), that ensures that the constrained degrees of freedom can be found from the unconstrained without encountering numerical ill conditioning. The experimental modal substructuring approach is also compared with frequency response function coupling, sometimes called admittance or impedance coupling. These methods are used both to analytically remove models of a test fixture (required to include rotational degrees of freedom) and to predict the response of the coupled beams. Both rigid and elastic models for the fixture are considered. Similar results are obtained using either method although the modal substructuring method yields a more compact database and allows one to more easily interrogate the resulting system model to assure that physically meaningful results have been obtained. A method for coupling the fixture model to experimental measurements, dubbed the Modal Constraint for Fixture and Subsystem (MCFS) is presented that greatly improves the result and robustness when an elastic fixture model is used.
Like other interfaces, equilibrium grain boundaries are smooth at low temperature and rough at high temperature; however, little attention has been paid to roughening except for faceting boundaries. Using molecular dynamics simulations of face-centered cubic Ni, we studied two closely related grain boundaries with different boundary planes. In spite of their similarity, their boundary roughening temperatures differ by several hundred degrees, and boundary mobility is much larger above the roughening temperature. This has important implications for microstructural development during metallurgical processes.
We have discussed the key areas of the IR process that should not be circumvented if an organization is to achieve a high level of assurance in high-dollar, high-risk cost estimates; lessons learned; and possible solutions to improve the process. In summary, the best practices described are to do the following. Develop a corporate policy for review of cost estimates based on TPC and potential financial and reputation risk; Develop a database of qualified, experienced personnel, who can perform well as IR team members; Spell out the process for approval of review team members, including the executive approval process; Address review team availability by developing review team member alternates; Increase lead-time notice on high-dollar, high risk estimates by developing an advanced notice system with internal organizations; Improve coordination of the estimating team's responses to the review team's questions and concerns; and Develop alternatives such as representatives and electronic briefings to alleviate challenges in scheduling executives for cost estimate briefings. Each organization has its own needs, culture, and level of maturity. If you have an IR process that works, great! If not, we hope that we have sparked your interest in developing a process that works for your company. The goal is to continuously improve and further refine the process to meet the needs of both external and internal customers. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company for the US Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Accurate material models are fundamental to predictive structural finite element models. Because potting foams are routinely used to mitigate shock and vibration of encapsulated components in electro/mechanical systems, accurate material models of foams are needed. A linear-viscoelastic foam constitutive model has been developed to represent the foam's stiffness and damping throughout an application space defined by temperature, strain rate or frequency and strain level. Validation of this linear-viscoelastic model, which is integrated into the Salinas structural dynamics code, is being achieved by modeling and testing a series of structural geometries of increasing complexity that have been designed to ensure sensitivity to material parameters. Both experimental and analytical uncertainties are being quantified to ensure the fair assessment of model validity. Quantitative model validation metrics are being developed to provide a means of comparison for analytical model predictions to observations made in the experiments. This paper is one of several recent papers documenting the validation process for simple to complex structures with foam encapsulated components. This paper specifically focuses on model validation over a wide temperature range and using a simple dumbbell structure for modal testing and simulation. Material variations of density and modulus have been included. A double blind validation process is described that brings together test data with model predictions.
17th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2007 - Systems Engineering: Key to Intelligent Enterprises