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Dynamics and structure of turbulent premixed flames

In earlier work (Mantel & Bilger, 1994) the structure of the turbulent premixed flame was investigated using statistics based on conditional averaging with the reaction progress variable as the conditioning variable. The DNS data base of Trouve and Poinsot (1994) was used in this investigation. Attention was focused on the conditional dissipation and conditional axial velocity in the flame with a view to modeling these quantities for use in the conditional moment closure (CMC) approach to analysis of kinetics in premixed flames (Bilger, 1993). Two remarkable findings were made: there was almost no acceleration of the axial velocity in the flame front itself; and the conditional scalar dissipation remained as high, or higher, than that found in laminar premixed flames. The first finding was surprising since in laminar flames all the fluid acceleration occurs through the flame front, and this could be expected also for turbulent premixed flames at the flamelet limit. The finding gave hope of inventing a new approach to the dynamics of turbulent premixed flames through use of rapid distortion theory or an unsteady Bernoulli equation. This could lead to a new second order closure for turbulent premixed flames. The second finding was contrary to our measurements with laser diagnostics in lean hydrocarbon flames where it is found that conditional scalar dissipation drops dramatically below that for laminar flamelets when the turbulence intensity becomes high. Such behavior was not explainable with a one-step kinetic model, even at non-unity Lewis number. It could be due to depletion of H2 from the reaction zone by preferential diffusion. The capacity of the flame to generate radicals is critically dependent on the levels of H2 present (Bilger, et al., 1991). It seemed that a DNS computation with a multistep reduced mechanism would be worthwhile if a way could be found to make this feasible. Truly innovative approaches to complex problems often come only when there is the opportunity to work close at hand with the (in this case numerical) experimental data. Not only can one spot patterns and relationships in the data which could be important, but one can also get to know the limitations of the technique being used, so that when the next experiment is being designed it will address resolvable questions. A three-year grant from the Australian Research Council has enabled us to develop a small capability at the University of Sydney to work on DNS of turbulent reacting flow, and to analyze data bases generated at CTR. Collaboration between the University of Sydney and CTR is essential to this project and finding a workable modus operandum for this collaboration, given the constraints involved, has been a major objective of the past year's effort. The overall objectives of the project are: (1) to obtain a quantitative understanding of the dynamics of turbulent premixed flames at high turbulence levels with a view to developing improved second order closure models; and (2) to carry out new DNS experiments on turbulent premixed flames using a carefully chosen multistep reduced mechanism for the chemical kinetics, with a view to elucidating the laser diagnostic findings that are contrary to the findings for DNS using one-step kinetics. In this first year the objectives have been to make the existing CTR data base more accessible to coworkers at the University of Sydney, to make progress on understanding the dynamics of the flame in this existing CTR data base, and to carefully construct a suitable multistep reduced mechanism for use in a new set of DNS experiments on turbulent premixed flames.

Bilger, R. W.↗

Mass Spectrometer Transient Analysis

This software implements a complete preprocessing pipeline for transient mass spectrometry (MS) data collected during TAP (Temporal Analysis of Products) experiments. It is designed to extract chemically meaningful fluxes from overlapping ion signals by applying a calibrated defragmentation matrix and solving the resulting linear system using non-negative least squares (NNLS) regression. The core script, preprocess_mass_spec.py, performs the following operations: Gain correction: Applies amplifier gain scalars derived from inert-packed calibration pulses to normalize signal intensities across AMUs and acquisition settings. Background subtraction: Removes experiment baselines using user-defined time windows, ensuring compatibility with slow-diffusing species and preventing negative values that would interfere with NNLS. Options to subtract before and after defragmentation. Defragmentation: Constructs a fragmentation matrix A from zeroth moments of calibration pulses (equal molar gas:inert mixtures) and solves Ax=b at each time point, where b is the raw MS signal and x is the estimated species flux. The matrix is normalized to inert signals and accounts for instrument-specific fragmentation behavior. Pulse-mode handling: Supports both averaged and individual pulse modes, enabling statistical treatment of fluxes and calculation of standard deviations. Integration and output: Computes zeroth moments (integrated fluxes) and exports time-resolved and integrated data in CSV format, suitable for downstream kinetic modeling. The software is validated using both virtual TAP simulations (VTAP) and experimental data from propane dehydrogenation (PDH) on CrOx/Al2O3 catalysts. It preserves temporal resolution by applying NNLS point-by-point across the pulse duration (typically 6,000+ time slices per pulse), leveraging the linear superposition principle to reconstruct full flux profiles. The defragmented outputs are compatible with kinetic extraction methods such as the G and Y procedures, which are used to derive rate–concentration relationships from TAP data. The details of these validations are discussed in detail in the supporting manuscript and supporting information. Example data and output files are also included. The methodology is robust to experimental noise and drift, with calibration protocols that account for pulse size effects, MS aging, and inert gas normalization. The software is modular, reproducible, and tailored for high-throughput TAP-MS workflows in catalysis research.

Kristy, Stephen [Idaho National Laboratory (INL), ↗

Predictability of Malaria Transmission Intensity in the Mpumalanga Province, South Africa, Using Land Surface Climatology and Autoregressive Analysis

There has been increasing effort in recent years to employ satellite remotely sensed data to identify and map vector habitat and malaria transmission risk in data sparse environments. In the current investigation, available satellite and other land surface climatology data products are employed in short-term forecasting of infection rates in the Mpumalanga Province of South Africa, using a multivariate autoregressive approach. The climatology variables include precipitation, air temperature and other land surface states computed by the Off-line Land-Surface Global Assimilation System (OLGA) including soil moisture and surface evaporation. Satellite data products include the Normalized Difference Vegetation Index (NDVI) and other forcing data used in the Goddard Earth Observing System (GEOS-1) model. Predictions are compared to long- term monthly records of clinical and microscopic diagnoses. The approach addresses the high degree of short-term autocorrelation in the disease and weather time series. The resulting model is able to predict 11 of the 13 months that were classified as high risk during the validation period, indicating the utility of applying antecedent climatic variables to the prediction of malaria incidence for the Mpumalanga Province.

Grass, David↗

Simulating Collisions for Hydrokinetic Turbines

Evaluations of blade-strike on an axial-flow Marine Hydrokinetic turbine were conducted using a conventional methodology as well as an alternative modeling approach proposed in the present document. The proposed methodology integrates the following components into a Computational Fluid Dynamics (CFD) model: (i) advanced eddy-resolving flow simulations, (ii) ambient turbulence based on field data, (iii) moving turbine blades in highly transient flows, and (iv) Lagrangian particles to mimic the potential fish pathways. The sensitivity of blade-strike prob- ability to the following conditions was also evaluated: (i) to the turbulent environment, (ii) to fish size and (iii) to mean stream flow velocity. The proposed methodology provided fraction of collisions and offered the capability of analyzing the causal relationships between the flow environment and resulting strikes on rotating blades. Overall, the conventional methodology largely overestimates the probability of strike, and lacks the ability to produce potential fish and aquatic biota trajectories as they interact with the rotating turbine. By using a set of experimental correlations of exposure-response of living fish colliding on moving blades, the occurrence, frequency and intensity of the particle collisions was next used to calculate the survival rate of fish crossing the MHK turbine. This step indicated survival rates always greater than 98%. Although the proposed CFD framework is computationally more expensive, it provides the advantage of evaluating multiple mechanisms of stress and injury of hydrokinetic turbine devices on fish.

CFD↗

A computationally efficient P 1 radiation model for modern combustion systems utilizing pre-conditioned conjugate gradient methods

The iterative convergence of the P 1 radiation model can be slow in optically thin scenarios when employing classical iterative methods. In order to remedy this shortcoming, an in-house P 1 radiation model was interfaced with high performance, scalable, linear solver libraries. Next, the accuracies of P 1 radiation model calculations was assessed by comparing its predictions against discrete ordinates (DO) model calculations for prototypical problems representative of modern combustion systems. Corresponding benchmark results were also included for comparison. Utilizing Pre-Conditioners (PC) to the Conjugate Gradients (CG) method, the convergence time of the P 1 radiation model reduced by a factor of 30 for modest problem sizes and a factor of 70 for larger sized problems when compared against classical Gauss Seidel sweeps. Additionally, PC provided 50% computational savings compared to employing CG in a standalone mode. The P 1 model calculation times were about 25–30% of the DO model calculation time. The time to solution also scaled linearly with an increase in problem size. The weighted sum of gray gases model employed in this study in conjunction with the P 1 model provided good agreement against benchmark data with L 2 error norms (defined relative to corresponding DO calculations) improving when isotropic intensities were prevalent.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Toward Magnetic Resonance–Only Simulation: Segmentation of Bone in MR for Radiation Therapy Verification of the Head

Purpose: To develop a practical method to localize bones in magnetic resonance (MR) images, to create “computed tomography–like” MR images (ctMRI) that could be used for radiation therapy verification, and to generate MR-based digitally reconstructed radiographs (DRR). Methods and Materials: Using T1-weighted MR images, an air mask was derived from the manual contouring of all airways within the head and neck region using axial images at 6 anatomic levels. Compact bone, spongy bone, and soft tissue masks were then automatically generated using the statistical data derived from MR intensities and the air mask. ctMRI were then generated by mapping the MR intensities of the voxels within these masks into the CT number ranges of corresponding tissues. MR-based DRRs created from ctMRI were quantitatively evaluated using the co-registered MR and CT head images of 20 stereotactic radiosurgery patients. Ten anatomical points, positioned on the skull segmented using a threshold of 300 HU, in CT and ctMRI, were used to determine the differences in distance between MR-based DRRs and CT-based DRRs, and to evaluate the geometric accuracy of ctMRI and MR-based DRRs. Results: The bony structures were identified on ctMRI and were visible in the MR-based DRRs. From the 20 patient cases, the mean geometric difference and standard deviation between the 10 anatomical points on MR-based and CT-based DRRs was −0.05 ± 0.85 mm, respectively. This included uncertainty in image fusion. The maximum distance difference was 1.88 mm. Conclusions: A practical method was developed to segment bone from MR images. The ctMRI created can be used for radiation treatment verification when MR-only simulation is performed. MR-based DRRs can be used in place of CT-based DRRs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Implementing intensity modulated radiotherapy to the prostate bed: Dosimetric study and early clinical results

Salvage intensity modulated radiotherapy (IMRT) to the prostate bed has hardly been studied so far. We present here a feasibility study and early clinical results for 10 patients. These patients were selected on the basis of having either a biochemical relapse or high risk histology after prostatectomy. They were treated using “sliding-window” IMRT to 68 Gy in 34 fractions. Three-dimensional conformal radiotherapy (3D-CRT) plans were generated using the same planning computed tomography data set. Dose coverage of planning target volumes (PTVs) and of organs-at-risk (OAR, namely: rectum, bladder, and femoral heads) were compared. Acute toxicity and chronic toxicity were measured using the Common Toxicity Criteria for Adverse Events version 3.0 scale. IMRT significantly reduces the dose above the prescription dose given to the PTV1 (mean dose: IMRT 67.2 Gy vs 3D-CRT 67.7 Gy (p = 0.0137)), without altering dose coverage for PTV2 (mean dose: IMRT 68.1 Gy vs 3D-CRT 68.0 Gy (p = 0.3750)). Doses to OAR were lower with IMRT and differences were statistically significant (mean dose: IMRT 51.4 Gy vs 3D-CRT 56.6 Gy for rectum (p = 0.002), IMRT 45.1 Gy vs 3D-CRT 53.1 Gy for bladder (p = 0.002), and IMRT 26.1 Gy vs 3D-CRT 28.4 Gy for femoral heads (p = 0.0059)). There was no acute or chronic genitourinary or gastrointestinal toxicity >1 with a median follow-up of 38 months. IMRT to the prostatic fossa is feasible and reduces dose to OAR, with consequential limited toxicity.

61 RADIATION PROTECTION AND DOSIMETRY↗

Interior-Point Methods for Estimating Seasonal Parameters in Discrete-Time Infectious Disease Models

Infectious diseases remain a significant health concern around the world. Mathematical modeling of these diseases can help us understand their dynamics and develop more effective control strategies. In this work, we show the capabilities of interior-point methods and nonlinear programming (NLP) formulations to efficiently estimate parameters in multiple discrete-time disease models using measles case count data from three cities. These models include multiplicative measurement noise and incorporate seasonality into multiple model parameters. Our results show that nearly identical patterns are estimated even when assuming seasonality in different model parameters, and that these patterns show strong correlation to school term holidays across very different social settings and holiday schedules. We show that interior-point methods provide a fast and flexible approach to parameterizing models that can be an alternative to more computationally intensive methods.

60 APPLIED LIFE SCIENCES↗

Sequential Inference of Hospitalization Electronic Health Records Using Probabilistic Models

In the dynamic hospital setting, decision support can be a valuable tool for improving patient outcomes. Data-driven inference of future outcomes is challenging in this dynamic setting, where long sequences such as laboratory tests and medications are updated frequently. This is due in part to heterogeneity of data types and mixed-sequence types contained in variable length sequences. In this work we design a probabilistic unsupervised model for multiple arbitrary-length sequences contained in hospitalization Electronic Health Record (EHR) data. The model uses a latent variable structure and captures complex relationships between medications, diagnoses, laboratory tests, neurological assessments, and medications. It can be trained on original data, without requiring any lossy transformations or time binning. Inference algorithms are derived that use partial data to infer properties of the complete sequences, including their length and presence of specific values. We train this model on data from subjects receiving medical care in the Kaiser Permanente Northern California integrated healthcare delivery system. The results are evaluated against held-out data for predicting the length of sequences and presence of Intensive Care Unit (ICU) in hospitalization bed sequences. Our method outperforms a baseline approach, showing that in these experiments the trained model captures information in the sequences that is informative of their future values.

97 MATHEMATICS AND COMPUTING↗

Environmental data display

Methods for using a combination of computer-generated color graphics and image processing techniques to display a large data base of environment information are described. The data source can be either field data or mathematical models, reduced to summary statistics that characterize the data field as a whole. Sharp gradients are plotted into contour plots, which can also feature shades, degree of brightness, and saturation levels for fine-tuning the image. The basic concepts of digital image processing are reviewed, including location of the pixels, intensity mapping operations, pseudocolor enhancements, neighborhood averaging, and smoothing. Sample applications are presented in terms of emissions and air quality distributions over the south coast air basin of southern California.

Hussey, K. J.↗

Geological mapping potential of computer-enhanced images from the Shuttle Imaging Radar - Lisbon Valley Anticline, Utah

Computer-enhancement techniques applied to the SIR-A data from the Lisbon Valley area in the northern portion of the Paradox basin increased the value of the imagery in the development of geologically useful maps. The enhancement techniques include filtering to remove image speckle from the SIR-A data and combining these data with Landsat multispectral scanner data. A method well-suited for the combination of the data sets utilized a three-dimensional domain defined by intensity-hue-saturation (IHS) coordinates. Such a system allows the Landsat data to modulate image intensity, while the SIR-A data control image hue and saturation. Whereas the addition of Landsat data to the SIR-A image by means of a pixel-by-pixel ratio accentuated textural variations within the image, the addition of color to the combined images enabled isolation of areas in which gray-tone contrast was minimal. This isolation resulted in a more precise definition of stratigraphic units.

Curlis, J. D.↗

Holographic Storage as a Solution to Space Imaging Requirements

The data growth experienced in the recent past has been of staggering proportions. Over the past 10 years, tape data storage density (with the same form factor) has increased according to Moore's law, doubling every 18 months. However, during the same period, data transfer speeds have only increased at a rate of about 1.3 times every 18 months, and thus have fallen behind data density growth rates by a factor of at least 3. Coupled with data media density growth, data storage requirements have gone up significantly. According to a recent Computer Technology Review article (March 1998) the total storage at a typical Fortune 1000 site is projected to escalate from just 10 TB in 1997 to 1 PB by the year 2000. In the next 5 years, a typical large database system for U.S. government agencies is expected to accept 5 TB per day, maintain 300 TB on-line (within 15 seconds to 1 minute access time), and archive from 15 to 100 PB. Additionally, data intensive programs such as NASA's Earth Observation System (EOS) and the intelligence data archival systems at the Rome Air Development Center, and scientific laboratories such as Thomas Jefferson National Accelerator Facility will have enormously large scientific databases with very large storage requirements.

Halem, Milton↗

Data Fusion for a Vision-Radiological System for Source Tracking and Discovery

A multidisciplinary approach to allow the tracking of the movement of radioactive sources by fusing data from multiple radiological and visual sensors is under development. The goal is to improve the ability to detect, locate, track and identify nuclear/radiological threats. The key concept is that such widely available visual and depth sensors can impact radiological detection, since the intensity fall-off in the count rate can be correlated to movement in three dimensions. To enable this, we pose an important question; what is the right combination of sensing modalities and vision algorithms that can best compliment a radiological sensor, for the purpose of detection and tracking of radioactive material? Similarly what is the best radiation detection methods and unfolding algorithms suited for data fusion with tracking data? Data fusion of multi-sensor data for radiation detection have seen some interesting developments lately. Significant examples include intelligent radiation sensor systems (IRSS), which are based on larger numbers of distributed similar or identical radiation sensors coupled with position data for network capable to detect and locate radiation source. Other developments are gamma-ray imaging systems based on Compton scatter in segmented detector arrays. Similar developments using coded apertures or scatter cameras for neutrons have recently occurred. The main limitation of such systems is not so much in their capability but rather in their complexity and cost which is prohibitive for large scale deployment. Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development on two separate calibration algorithms for characterizing the fused sensor system. The deviation from a simple inverse square-root fall-off of radiation intensity is explored and accounted for. In particular, the computer vision system enables a map of distance-dependence of the sources being tracked. Infrared, laser or stereoscopic vision sensors are all options for computer-vision implementation depending on interior vs exterior deployment, resolution desired and other factors. Similarly the radiation sensors will be focused on gamma-ray or neutron detection due to the long travel length and ability to penetrate even moderate shielding. There is a significant difference between the vision sensors and radiation sensors in the way the 'source' or signals are generated. A vision sensor needs an external light-source to illuminate the object and then detects the re-emitted illumination (or lack thereof). However, for a radiation detector, the radioactive material is the source itself. The only exception to this is the field of active interrogations where radiation is beamed into a material to entice new/additional radiation emission beyond what the material would emit spontaneously. The aspect of the nuclear material being the source itself means that all other objects in the environment are 'illuminated' or irradiated by the source. Most radiation will readily penetrate regular material, scatter in new directions or be absorbed. Thus if a radiation source is located near a larger object that object will in turn scatter some radiation that was initially emitted in a direction other than the direction of the radiation detector, this can add to the count rate that is observed. The effect of these scatter is a deviation from the traditional distance dependence of the radiation signal and is a key challenge that needs a combined system calibration solution and algorithms. Thus both an algebraic approach as well as a statistical approach have been developed and independently evaluated to investigate the sensitivity to this deviation from the simplified radiation fall-off as a function of distance. The resulting calibrated system algorithms are used and demonstrated in various laboratory scenarios, and later in realistic tracking scenarios. The selection and testing of radiological and computer-vision sensors for the additional specific scenarios will be the subject of ongoing and future work. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-E-QI-14: Quantitative Variogram Detection of Mild, Unilateral Disease in Elastase-Treated Rats

Purpose: Determining the presence of mild or early disease in the lungs can be challenging and subjective. We present a rapid and objective method for evaluating lung damage in a rat model of unilateral mild emphysema based on a new approach to heterogeneity assessment. We combined octree decomposition (used in three-dimensional (3D) computer graphics) with variograms (used in geostatistics to assess spatial relationships) to evaluate 3D computed tomography (CT) lung images for disease. Methods: Male, Sprague-Dawley rats (232 ± 7 g) were intratracheally dosed with 50 U/kg of elastase dissolved in 200 μL of saline to a single lobe (n=6) or with saline only (n=5). After four weeks, 3D micro-CT images were acquired at end expiration on mechanically ventilated rats using prospective gating. Images were masked, and lungs were decomposed to homogeneous blocks of 2×2×2, 4×4×4, and 8×8×8 voxels using octree decomposition. The spatial variance – the square of the difference of signal intensity – between all pairs of the 8×8×8 blocks was calculated. Variograms – graphs of distance vs. variance - were made, and data were fit to a power law and the exponent determined. The mean HU values, coefficient of variation (CoV), and the emphysema index (EI) were calculated and compared to the variograms. Results: The variogram analysis showed that significant differences between groups existed (p<0.01), whereas the mean HU (p=0.07), CoV (p=0.24), and EI (p=0.08) did not. Calculation time for the variogram for a typical 1000 block decomposition was ∼6 seconds, and octree decomposition took ∼2 minutes. Decomposing the images prior to variogram calculation resulted in a ∼700x decrease in time as compared to other published approaches. Conclusions: Our results suggest that the approach combining octree decomposition and variogram analysis may be a rapid, non-subjective, and sensitive imaging-based biomarker for quantitative characterization of lung disease.

60 APPLIED LIFE SCIENCES↗

Advanced Manufacturing for Thermal and Environmental Control Systems: Achieving National Energy Goals

This project was part of a regional initiative in the five counties of Central New York (CNY) that received funding from the U.S. Department of Energy (DOE) and four other federal agencies through the 2012 Advanced Manufacturing Jobs and Innovation Accelerator Challenge (AMJIAC). The CNY initiative was focused on cultivating the emergent regional cluster in “Advanced Manufacturing for Thermal and Environmental Control (AM-TEC).” As one component of the CNY AM-TEC initiative, the DOE-funded project supported five research & development seed projects that strategically targeted: 1) needs and opportunities of CNY AM-TEC companies, and 2) the goal of DOE’s Advanced Manufacturing Office (AMO) to reduce energy consumption by 50% across product life-cycles over 10 years. The project also sought to fulfill the AMO mission of developing and demonstrating new, energy-efficient processing and materials technologies at a scale adequate to prove their value to manufacturers and spur investment. The five seed projects demonstrated technologies and processes that can reduce energy intensity and improve production as well as use less energy throughout their lifecycles. The project was conducted over three years in two 18-month budget periods. During the first budget period, two projects proposed in the original AMJAIC application were successfully completed: Seed Project 1 focused on saving energy in heat transfer processes via development of nano structured surfaces to significantly increase heat flux; Seed Project 2 addressed saving energy in data centers via subzero cooling of the computing processors. Also during the first budget period, a process was developed and executed to select a second round of seed projects via a competitive request for proposals from regional companies and university collaborators. Applicants were encouraged to form industry-academic partnerships to leverage experience and resources of public and private sectors in the CNY region. Proposals were evaluated by a national panel of experts. Three projects were selected for awards and were completed successfully during the second budget period: Seed Project 3 focused on enabling self-powered furnaces to permit residents to shelter in place during power outages; Seed Project 4 addressed development of a novel method of controlling air conditioning systems that could enable flexible load matching in market segments not possible with existing technologies; and Seed Project 5 focused on the creation of smarter occupancy sensors to enable effective highly localized demand based ventilation.

30 DIRECT ENERGY CONVERSION↗

Uranus occults SAO158687

Experience gained in obtaining atmospheric parameters, oblatenesses, and diameters of Jupiter and Mars from recent stellar occultations by these planets is used to predict what can be learned from the March 1977 occultation of the star SAO158687 by Uranus. The spectra of this star and Uranus are compared to indicate the relative instrument intensities of the two objects, the four passbands where the relative intensities are most nearly equal are listed, and expected photon fluxes from the star are computed on the assumption that it has UBVRI colors appropriate for a K5 main-sequence object. It is shown that low photon noise errors can be achieved by choosing appropriate passbands for observation, and the rms error expected for the Uranus temperature profiles obtained from the occultation light curves is calculated. It is suggested that observers of this occultation should record their data digitally for optimum time resolution.

Elliot, J. L.↗

Measurement potential of laser speckle velocimetry

Laser speckle velocimetry, the measurement of fluid velocity by measuring the translation of speckle pattern or individual particles that are moving with the fluid, is described. The measurement is accomplished by illuminating the fluid with consecutive pulses of Laser Light and recording the images of the particles or the speckles on a double exposed photographic plate. The plate contains flow information throughout the image plane so that a single double exposure may provide data at hundreds or thousands of points in the illuminated region of the fluid. Conventional interrogation of the specklegram involves illuminating the plate to form Young's fringes, whose spacing is inversely proportional to the speckle separation. Subsequently the fringes are digitized and analyzed in a computer to determine their frequency and orientation, yielding the velocity magnitude and orientation. The Young's fringe technique is equivalent to performing a 2-D spatial correlation of the double exposed specklegram intensity pattern, and this observation suggests that correlation should be considered as an alternative processing method. The principle of the correlation technique is examined.

Adrian, R. J.↗

A comparative study of computational solutions to flow over a backward-facing step

A comparative study was conducted for computational fluid dynamic solutions to flow over a backward-facing step. This flow is a benchmark problem, with a simple geometry, but involves complicated flow physics such as free shear layers, reattaching flow, recirculation, and high turbulence intensities. Three Reynolds-averaged Navier-Stokes flow solvers with k-epsilon turbulence models were used, each using a different solution algorithm: finite difference, finite element, and hybrid finite element - finite difference. Comparisons were made with existing experimental data. Results showed that velocity profiles and reattachment lengths were predicted reasonably well by all three methods, while the skin friction coefficients were more difficult to predict accurately. It was noted that, in general, selecting an appropriate solver for each problem to be considered is important.

Mizukami, M.↗