S Levent Yilmaz

University of Pittsburgh, Pittsburgh, PA, United States

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Publications (18)30.43 Total impact

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    ABSTRACT: Because patients can remain colonized with vancomycin-resistant enterococci (VRE) for long periods of time, VRE may spread from one health care facility to another. Using the Regional Healthcare Ecosystem Analyst, an agent-based model of patient flow among all Orange County, California, hospitals and communities, we quantified the degree and speed at which changes in VRE colonization prevalence in a hospital may affect prevalence in other Orange County hospitals. A sustained 10% increase in VRE colonization prevalence in any 1 hospital caused a 2.8% (none to 62%) average relative increase in VRE prevalence in all other hospitals. Effects took from 1.5 to >10 years to fully manifest. Larger hospitals tended to have greater affect on other hospitals. When monitoring and controlling VRE, decision makers may want to account for regional effects. Knowing a hospital's connections with other health care facilities via patient sharing can help determine which hospitals to include in a surveillance or control program.
    American journal of infection control 08/2013; 41(8):668-73. · 3.01 Impact Factor
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    ABSTRACT: OBJECTIVE: As healthcare systems continue to expand and interconnect with each other through patient sharing, administrators, policy makers, infection control specialists, and other decision makers may have to take account of the entire healthcare 'ecosystem' in infection control. MATERIALS AND METHODS: We developed a software tool, the Regional Healthcare Ecosystem Analyst (RHEA), that can accept user-inputted data to rapidly create a detailed agent-based simulation model (ABM) of the healthcare ecosystem (ie, all healthcare facilities, their adjoining community, and patient flow among the facilities) of any region to better understand the spread and control of infectious diseases. RESULTS: To demonstrate RHEA's capabilities, we fed extensive data from Orange County, California, USA, into RHEA to create an ABM of a healthcare ecosystem and simulate the spread and control of methicillin-resistant Staphylococcus aureus. Various experiments explored the effects of changing different parameters (eg, degree of transmission, length of stay, and bed capacity). DISCUSSION: Our model emphasizes how individual healthcare facilities are components of integrated and dynamic networks connected via patient movement and how occurrences in one healthcare facility may affect many other healthcare facilities. CONCLUSIONS: A decision maker can utilize RHEA to generate a detailed ABM of any healthcare system of interest, which in turn can serve as a virtual laboratory to test different policies and interventions.
    Journal of the American Medical Informatics Association 04/2013; · 3.57 Impact Factor
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    ABSTRACT: Objective. Implementation of contact precautions in nursing homes to prevent methicillin-resistant Staphylococcus aureus (MRSA) transmission could cost time and effort and may have wide-ranging effects throughout multiple health facilities. Computational modeling could forecast the potential effects and guide policy making. Design. Our multihospital computational agent-based model, Regional Healthcare Ecosystem Analyst (RHEA). Setting. All hospitals and nursing homes in Orange County, California. Methods. Our simulation model compared the following 3 contact precaution strategies: (1) no contact precautions applied to any nursing home residents, (2) contact precautions applied to those with clinically apparent MRSA infections, and (3) contact precautions applied to all known MRSA carriers as determined by MRSA screening performed by hospitals. Results. Our model demonstrated that contact precautions for patients with clinically apparent MRSA infections in nursing homes resulted in a median 0.4% (range, 0%-1.6%) relative decrease in MRSA prevalence in nursing homes (with 50% adherence) but had no effect on hospital MRSA prevalence, even 5 years after initiation. Implementation of contact precautions (with 50% adherence) in nursing homes for all known MRSA carriers was associated with a median 14.2% (range, 2.1%-21.8%) relative decrease in MRSA prevalence in nursing homes and a 2.3% decrease (range, 0%-7.1%) in hospitals 1 year after implementation. Benefits accrued over time and increased with increasing compliance. Conclusions. Our modeling study demonstrated the substantial benefits of extending contact precautions in nursing homes from just those residents with clinically apparent infection to all MRSA carriers, which suggests the benefits of hospitals and nursing homes sharing and coordinating information on MRSA surveillance and carriage status.
    Infection Control and Hospital Epidemiology 02/2013; 34(2):151-60. · 4.02 Impact Factor
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    ABSTRACT: BACKGROUND:: Hospital infection control strategies and programs may not consider control of methicillin-resistant Staphylococcus aureus (MRSA) in nursing homes in a county. METHODS:: Using our Regional Healthcare Ecosystem Analyst, we augmented our existing agent-based model of all hospitals in Orange County (OC), California, by adding all nursing homes and then simulated MRSA outbreaks in various health care facilities. RESULTS:: The addition of nursing homes substantially changed MRSA transmission dynamics throughout the county. The presence of nursing homes substantially potentiated the effects of hospital outbreaks on other hospitals, leading to an average 46.2% (range, 3.3%-156.1%) relative increase above and beyond the impact when only hospitals are included for an outbreak in OC's largest hospital. An outbreak in the largest hospital affected all other hospitals (average 2.1% relative prevalence increase) and the majority (∼90%) of nursing homes (average 3.2% relative increase) after 6 months. An outbreak in the largest nursing home had effects on multiple OC hospitals, increasing MRSA prevalence in directly connected hospitals by an average 0.3% and in hospitals not directly connected through patient transfers by an average 0.1% after 6 months. A nursing home outbreak also had some effect on MRSA prevalence in other nursing homes. CONCLUSIONS:: Nursing homes, even those not connected by direct patient transfers, may be a vital component of a hospital's infection control strategy. To achieve effective control, a hospital may want to better understand how regional nursing homes and hospitals are connected through both direct and indirect (with intervening stays at home) patient sharing.
    Medical care 01/2013; · 2.94 Impact Factor
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    ABSTRACT: A new computational methodology, termed “irregularly portioned Lagrangian Monte Carlo-finite difference” (IPLMCFD), is developed for large eddy simulation (LES) of turbulent combustion via the filtered density function (FDF). This is a hybrid methodology which couples a Monte Carlo FDF simulator with a structured Eulerian finite difference LES solver. The IPLMCFD is scalable to thousands of processors; thus it is suited for simulation of complex reactive flows. The scalability and consistency of the hybrid solver and the realizability and reliability of the generated results are demonstrated via LES of several turbulent flames under both nonpremixed and premixed conditions.
    SIAM Journal on Scientific Computing 01/2013; 35(4). · 1.94 Impact Factor
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    ABSTRACT: Efforts to control life-threatening infections, such as with methicillin-resistant Staphylococcus aureus (MRSA), can be complicated when patients are transferred from one hospital to another. Using a detailed computer simulation model of all hospitals in Orange County, California, we explored the effects when combinations of hospitals tested all patients at admission for MRSA and adopted procedures to limit transmission among patients who tested positive. Called "contact isolation," these procedures specify precautions for health care workers interacting with an infected patient, such as wearing gloves and gowns. Our simulation demonstrated that each hospital's decision to test for MRSA and implement contact isolation procedures could affect the MRSA prevalence in all other hospitals. Thus, our study makes the case that further cooperation among hospitals-which is already reflected in a few limited collaborative infection control efforts under way-could help individual hospitals achieve better infection control than they could achieve on their own.
    Health Affairs 10/2012; 31(10):2295-303. · 4.64 Impact Factor
  • 48th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit; 07/2012
  • 48th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit; 07/2012
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    ABSTRACT: Acute care facilities are connected via patient sharing, forming a network. However, patient sharing extends beyond this immediate network to include sharing with long-term care facilities. The extent of long-term care facility patient sharing on the acute care facility network is unknown. The objective of this study was to characterize and determine the extent and pattern of patient transfers to, from, and between long-term care facilities on the network of acute care facilities in a large metropolitan county. We applied social network constructs principles, measures, and frameworks to all 2007 annual adult and pediatric patient transfers among the healthcare facilities in Orange County, California, using data from surveys and several datasets. We evaluated general network and centrality measures as well as individual ego measures and further constructed sociograms. Our results show that over the course of a year, 66 of 72 long-term care facilities directly sent and 67 directly received patients from other long-term care facilities. Long-term care facilities added 1,524 ties between the acute care facilities when ties represented at least one patient transfer. Geodesic distance did not closely correlate with the geographic distance among facilities. This study demonstrates the extent to which long-term care facilities are connected to the acute care facility patient sharing network. Many long-term care facilities were connected by patient transfers and further added many connections to the acute care facility network. This suggests that policy-makers and health officials should account for patient sharing with and among long-term care facilities as well as those among acute care facilities when evaluating policies and interventions.
    PLoS ONE 12/2011; 6(12):e29342. · 3.53 Impact Factor
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    ABSTRACT: The ``Irregularly Portioned Lagrangian Monte Carlo'' (IPLMC) [1] in LES/FDF is extended to include the Eulerian flow solver in a coupled manner. The resulting methodology is for LES of reacting flows on massively parallel platforms, and is intended for LES of turbulent reacting flows described by complex kinetics. The new solver provides much improved scalability over its predecessor for utilization of a higher number of processors. Sample results are presented of LES of non-premixed flames, along with scalability benchmarks. [4pt] [1] Yilmaz, S. L., Nik, M. B., Sheikhi, M. R. H., Strakey, P. A., and Givi, P., An Irregularly Portioned Lagrangian Monte Carlo Method for Turbulent Flow Simulation, J. Sci. Comput., 47(1):109--125 (2011).
    11/2011;
  • 47th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit; 07/2011
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    ABSTRACT: "Turbulence is the most important unsolved problem of classical physics". That was Richard Feynman decades ago, referring to a century old problem. Today, the situation is no different. Turbulent combustion, which deals with a fluid mixture reacting and mixing under turbulent conditions (as found in rockets, jet engines, power generators, car engines, furnaces,...), is harder still. While a solution that would satisfy a physicist is yet to be found, engineers all over the world are tackling the problem with computational modeling and simulation. There are a plethora of models for turbulence and combustion with a whole wide range of competing characteristics of applicability, accuracy, reliability and computational cost. Nowadays, reliability is the key feature required of such modeling (but, most often than not, sacrificed or oversight) for the design of environment friendly and efficient machines. There exists an unproven (but undeniable) direct correlation between reliability and computational cost. However, the era of sacrificing the former because one cannot overcome and afford the latter for a full scale engineering application is over, thanks to TeraGrid and other resources for open research coupled with relentless efforts of countless developers to provide software that runs faster and better. This project is one sampling of how these resources are utilized to overcome an important research problem. We take on the Filtered Density Function (FDF) for large eddy simulation (LES) of turbulent reacting flow, which is a novel and robust methodology that can provide very accurate predictions for a wide range flow conditions. FDF involves an expensive particle/mesh algorithm where stiff chemical reaction computations cause quite interesting, problem specific, and in most cases extremely imbalanced (a couple of orders of magnitude) computational loads. The authors present the Irregularly Portioned Lagrangian Monte Carlo[?], an advanced implementation of FDF based on a simple and smart parallelization strategy that is implemented via optimized solvers and high-level public domain parallelization libraries (eg. Zoltan[?]). The methodology and a discussion of the implementation is presented along with results and benchmarks on the TeraGrid (NICS/Kraken and PSC/Bigben). Scaling and speed up comparisons demonstrate that a conventional parallelization is unable to scale beyond a 100 processors, whereas the new implementation can efficiently utilize 1000 processors for the same size problem, and has enabled the FDF methodology to tackle ever larger problems.
    07/2011;
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    ABSTRACT: Since hospitals in a region often share patients, an outbreak of methicillin-resistant Staphylococcus aureus (MRSA) infection in one hospital could affect other hospitals. Using extensive data collected from Orange County (OC), California, we developed a detailed agent-based model to represent patient movement among all OC hospitals. Experiments simulated MRSA outbreaks in various wards, institutions, and regions. Sensitivity analysis varied lengths of stay, intraward transmission coefficients (β), MRSA loss rate, probability of patient transfer or readmission, and time to readmission. Each simulated outbreak eventually affected all of the hospitals in the network, with effects depending on the outbreak size and location. Increasing MRSA prevalence at a single hospital (from 5% to 15%) resulted in a 2.9% average increase in relative prevalence at all other hospitals (ranging from no effect to 46.4%). Single-hospital intensive care unit outbreaks (modeled increase from 5% to 15%) caused a 1.4% average relative increase in all other OC hospitals (ranging from no effect to 12.7%). MRSA outbreaks may rarely be confined to a single hospital but instead may affect all of the hospitals in a region. This suggests that prevention and control strategies and policies should account for the interconnectedness of health care facilities.
    Infection Control and Hospital Epidemiology 06/2011; 32(6):562-72. · 4.02 Impact Factor
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    AIAA Journal 07/2010; 48(7):1513-1522. · 1.17 Impact Factor
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    ABSTRACT: Reynolds-Averaged Navier-Stokes (RANS) simulations of Lean Premixed Combustion (LPC) of methane–air in a bluff-body stabilized combustor were performed with several widely used turbulent combustion methodologies in order to assess their prediction capabilities. The methods employed are the Eddy Dissipation Concept (EDC), the Composition Probability Density Function (CPDF) and the Joint Velocity–Frequency-Composition PDF (VFCPDF) models. Where needed, two different models were employed for turbulent transport closure, namely the Renormalization Group (RNG) k-ϵ and Reynolds Stress Transport (RSM) models. The combustion chemistry was represented by two separate augmented reduced mechanisms (ARM9 and ARM19) in order to assess the influence of chemical mechanisms on calculations. Mean temperature and major species predictions of all of the employed methodologies compared well with the experimental data. Intermediate and emission species predictions were sensitive to the resolution of turbulence viscosity, which changes the effective diffusivity of the species. NO emissions predictions were in error by an average ±5 ppm with the EDC models and the CPDF model, with the VFCPDF model showing a somewhat better prediction of NOx. Calculations for some intermediate species (especially H2) deviated qualitatively from the experimental data, which highlights some of the limitations of these methodologies commonly used in detailed prediction of emissions for various fuel blends.
    Combustion Science and Technology 07/2010; 182(7):794-821. · 0.98 Impact Factor
  • S. Levent Yilmaz, Peyman Givi, Peter Strakey
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    ABSTRACT: The scalar filtered density function (SFDF) methodology is extended for large eddy simulation (LES) of a turbulent, stoichiometric premixed methane/air flame. The SFDF takes account of subgrid scales (SGS) by considering the mass weighted probability density function (PDF) of the SGS scalar quantities. A transport equation is derived for the SFDF in which the effects of chemical reactions appear in closed form. The SGS mixing is modeled via the linear mean square estimation (LMSE) model, and the convective fluxes are modeled via a SGS viscosity. The modeled SFDF transport equation is solved by a hybrid finite-difference/Monte Carlo scheme. A novel irregular domain decomposition procedure is employed for scalable parallelization which facilitates affordable simulations with realistic chemical reactions and flow parameters. Oxidation chemistry is modeled via a 5-step reduced, and a 15-step augmented reduced mechanism. Results are presented of the mean and rms values of the velocity, the temperature, and mass fractions of the major and the minor species. These results are assessed by comparison against laboratory data.
    Journal of Propulsion and Power 11/2008; · 0.61 Impact Factor
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    ABSTRACT: Reduction of NOx is a subject of significant current interest in stationary gas turbines. The objective of this study is to examine the effects of turbulence on non-thermal NOx formation in a syngas flame. This is archived by a detailed parametric study via PDF simulations of a partially stirred reactor and a dumped axisymmetric premixed flame. Several different detailed and reduced kinetics schemes are considered. The simulated results demonstrate the strong dependence of combustion process on turbulence. It is shown that the amount of NOx formation is significantly influenced by the inlet conditions. That is, the turbulence intensity can be tweaked to attain optimal ultra-low NOx emissions at a given temperature.
    11/2006;
  • S. L. Yilmaz, P. Givi, P. A. Strakey
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    ABSTRACT: The joint velocity-scalar-frequency probability density function (PDF) methodology is employed for prediction of a bluff-body stabilized lean premixed methane-air flame. A reduced mechanism with CO and NO chemistry is used to describe fuel oxidation. The predicted ; mean and rms values of the velocity, temperature and concentrations of major and minor species are compared with laboratory measurements. This technical effort was performed in support of the National Energy Technology Laboratorys on-going research in Assessment of Turbo-Chemistry Models for Gas Turbine Combustion Emissions under the RDS contract DE-AC26-04NT41817.