Academic literature on the topic 'Johns Hopkins Turbulent Database'

Abstract. Rank-Ordered Multifractal Analysis (ROMA) was introduced by Chang and Wu (2008) to describe the multifractal characteristic of intermittent events. The procedure provides a natural connection between the rank-ordered spectrum and the idea of one-parameter scaling for monofractals. This technique has successfully been applied to MHD turbulence simulations and turbulence data observed in various space plasmas. In this paper, the technique is applied to the probability distributions in the inertial range of the turbulent fluid flow, as given in the vast Johns Hopkins University (JHU) turbulence database. In addition, a new way of finding the continuous ROMA spectrum and the scaled probability distribution function (PDF) simultaneously is introduced.

We present a new subgrid stress model for the large eddy simulation of turbulent flows based on the solution of transport equations for stress tensor components. The model was a priori term-by-term calibrated against an open DNS database on forced isotropic turbulence (Johns Hopkins University database). After that, it was applied in a large eddy simulation of non-premixed turbulent combustion. To demonstrate the impact of the new subgrid stress model on scalar fields, we excluded the backward effect of heat release on the subgrid stresses, considering an isothermal reaction (i.e., diluted mixture; the density variations associated with chemical heat release can be neglected) and a Burke–Schumann reaction sheet approximation. A periodic box filled with a homogeneous turbulent velocity field and a three-layer top-hat mixture fraction field was studied. Four simulations were performed in which a fixed model for mixture fraction and its variance was combined with either the proposed subgrid stress model or one of the standard models, including Smagorinsky, dynamic Smagorinsky and WALE. Qualitatively correct backscatter was observed in a simulation with the new model. The differences in the statistics of the mixture fraction and reactive component fields caused by the new subgrid stress model were analyzed and discussed. The importance of using an advanced subgrid stress model was highlighted.

In a channel flow, the velocity fluctuations are inhomogeneous and anisotropic. Yet, the small-scale properties of the flow are expected to behave in an isotropic manner in the very-large-Reynolds-number limit. We consider the statistical properties of small-scale velocity fluctuations in a turbulent channel flow at moderately high Reynolds number ($Re_{\unicode[STIX]{x1D70F}}\approx 1000$), using the Johns Hopkins University Turbulence Database. Away from the wall, in the logarithmic layer, the skewness of the normal derivative of the streamwise velocity fluctuation is approximately constant, of order 1, while the Reynolds number based on the Taylor scale is $R_{\unicode[STIX]{x1D706}}\approx 150$. This defines a small-scale anisotropy that is stronger than in turbulent homogeneous shear flows at comparable values of $R_{\unicode[STIX]{x1D706}}$. In contrast, the vorticity–strain correlations that characterize homogeneous isotropic turbulence are nearly unchanged in channel flow even though they do vary with distance from the wall with an exponent that can be inferred from the local dissipation. Our results demonstrate that the statistical properties of the fluctuating velocity gradient in turbulent channel flow are characterized, on one hand, by observables that are insensitive to the anisotropy, and behave as in homogeneous isotropic flows, and on the other hand by quantities that are much more sensitive to the anisotropy. How this seemingly contradictory situation emerges from the simultaneous action of the flux of energy to small scales and the transport of momentum away from the wall remains to be elucidated.

We consider the time dependence of a hierarchy of scaled $L^{2m}$-norms $D_{m,\unicode[STIX]{x1D714}}$ and $D_{m,\unicode[STIX]{x1D703}}$ of the vorticity $\unicode[STIX]{x1D74E}=\unicode[STIX]{x1D735}\times \boldsymbol{u}$ and the density gradient $\unicode[STIX]{x1D735}\unicode[STIX]{x1D703}$, where $\unicode[STIX]{x1D703}=\log (\unicode[STIX]{x1D70C}^{\ast }/\unicode[STIX]{x1D70C}_{0}^{\ast })$, in a buoyancy-driven turbulent flow as simulated by Livescu & Ristorcelli (J. Fluid Mech., vol. 591, 2007, pp. 43–71). Here, $\unicode[STIX]{x1D70C}^{\ast }(\boldsymbol{x},t)$ is the composition density of a mixture of two incompressible miscible fluids with fluid densities $\unicode[STIX]{x1D70C}_{2}^{\ast }>\unicode[STIX]{x1D70C}_{1}^{\ast }$, and $\unicode[STIX]{x1D70C}_{0}^{\ast }$ is a reference normalization density. Using data from the publicly available Johns Hopkins turbulence database, we present evidence that the $L^{2}$-spatial average of the density gradient $\unicode[STIX]{x1D735}\unicode[STIX]{x1D703}$ can reach extremely large values at intermediate times, even in flows with low Atwood number $At=(\unicode[STIX]{x1D70C}_{2}^{\ast }-\unicode[STIX]{x1D70C}_{1}^{\ast })/(\unicode[STIX]{x1D70C}_{2}^{\ast }+\unicode[STIX]{x1D70C}_{1}^{\ast })=0.05$, implying that very strong mixing of the density field at small scales can arise in buoyancy-driven turbulence. This large growth raises the possibility that the density gradient $\unicode[STIX]{x1D735}\unicode[STIX]{x1D703}$ might blow up in a finite time.

The two-dimensional space spanned by the velocity gradient invariantsQandRis expanded to three dimensions by the decomposition ofRinto its strain production −1/3sijsjkskiand enstrophy production 1/4ωiωjsijterms. The {Q;R} space is a planar projection of the new three-dimensional representation. In the {Q; −sss; ωωs} space the Lagrangian evolution of the velocity gradient tensorAijis studied via conditional mean trajectories (CMTs) as introduced by Martínet al. (Phys. Fluids, vol. 10, 1998, p. 2012). From an analysis of a numerical data set for isotropic turbulence ofReλ~ 434, taken from the Johns Hopkins University (JHU) turbulence database, we observe a pronounced cyclic evolution that is almost perpendicular to theQ–Rplane. The relatively weak cyclic evolution in theQ–Rspace is thus only a projection of a much stronger cycle in the {Q; −sss; ωωs} space. Further, we find that the restricted Euler (RE) dynamics are primarily counteracted by the deviatoric non-local part of the pressure Hessian and not by the viscous term. The contribution of the Laplacian ofAij, on the other hand, seems the main responsible for intermittently alternating between low and high intensityAijstates.

OBJECTIVE: Human cytomegalovirus (CMV) is a commonly recognized viral cause of perinatal sensorineural hearing loss. CMV-infected infants are also at risk for developmental neurological deficits. This retrospective study assesses the impact of CMV-induced deafness on pediatric cochlear implant outcomes. STUDY DESIGN AND SETTING: Thirteen patients from the Johns Hopkins pediatric cochlear implant database were identified with CMV-related deafness. A retrospective review of the medical records of the Johns Hopkins Hospital was performed. RESULTS: The mean age at implantation was 5.6 years. Follow-up audiometric data ranged from 6 to 48 months postoperatively. Mean speech perception scores were 4.5 (out of 6) following implantation. CONCLUSION: We have shown that cochlear implants can provide useful speech comprehension to patients with CMV-related deafness. Speech recognition scores were within the range established by our overall pediatric implant population. SIGNIFICANCE: This observation underscores the importance of a multidisciplinary rehabilitation program following implantation in these patients at risk for cognitive delay. EBM RATING: C

Context The Department of Pathology of the Johns Hopkins University pioneered in the late 19th century the application of the scientific method to the study of medicine and fostered the development of residency training programs. Objective To trace the history of the Johns Hopkins Pathology Residency Program and assess with quantifiable outcomes the performance of former residents. Design We reviewed archival and departmental records from September 1899 to June 2014 to create a database of pathology residents. We then analyzed resident in-service examinations, American Board of Pathology examinations, and career paths. Results In 115 years the department trained 555 residents who came from 133 medical schools located in 23 countries. Residents performed well on the in-service examinations, obtaining mean scaled total scores that were significantly better (P = .02) than those of the national peer groups. Residents (371 of 396, 94%) passed their boards typically at the first attempt, a percentage pass that was higher than the national average for both anatomic (P < .001) and clinical (P = .002) pathology. Approximately half of the residents went into private practice, whereas a third followed an academic career. Of the latter group, 124 (75%) became professors of pathology, 31 (19%) chairs of pathology departments, 10 (6%) deans of medical schools, 5 (3%) were elected into the National Academy of Sciences, and 1 won the Nobel prize. Conclusions While maintaining its original core values, the Johns Hopkins Pathology Residency Program has trained physicians to be outstanding researchers, diagnosticians, and leaders in pathology.

Abstract Introduction: At the beginning of the COVID-19 pandemic in the United States, some states combated viral spread via lockdowns. In Maryland, where Johns Hopkins Hospital (JHH) is located, the closures began with public schools (March 12, 2020; 3/12/20); followed by bars, restaurants, movie theaters, gyms and gatherings of >50 people (3/16/20) with 250 Maryland State Police troopers being activated to aid in enforcement. All non-essential businesses were closed on 3/23/20, with a statewide "stay-at-home order" announced on 3/30/20. At this time, we anecdotally noted a decline in the number of adult patients presenting to JHH with new diagnoses of acute leukemia (AL). In this retrospective study, we quantified changes in new AL diagnoses over this period. Methods: The study was approved by the JHH IRB. All patients with new presentations of AL undergo diagnostic flow cytometry (FC) analysis at our institution on peripheral blood and/or bone marrow samples. The FC database was searched for new diagnoses of adult (≥ 18 years) and pediatric (<18 years) AL during the following timeframes: [1] 3/13-6/10/20 (90 days after the first announced restriction) and [2] 2/11-3/12/20 (30 days prior to the first restriction). The database was searched for the same time periods in 2019 (3/13-6/10/19 and 2/10-3/12/19). A diagnosis of AL was considered new if the patient had not previously been diagnosed with AL or evolved to AL from an underlying myeloid neoplasm. Clinical data were collected from the electronic medical record. We used a Fisher's exact test to compare the distribution of new patients in the 30 days prior and 90 days following the announced COVID-19 restrictions in Maryland in 2020 to that of new patients in the corresponding time periods for 2019. The Cochran-Armitage test was used to compare trends in new patients with AL in the 30 days prior and 90 days following COVID-19 restrictions, as compared to the same time period in 2019. Statistical significance was defined as a p-value <0.05. Results: Between 3/13- 6/10/20, there were 25 new diagnoses of AL (11 women/14 men) with a median age of 51 years (range: 2.6 - 89 years; 10 pediatric/15 adult). During the same 90 day period in 2019, there were 32 new diagnoses of AL (18 women/14 men) with a median age of 63 years (range: 8 - 93 years; 2 pediatric/30 adult). Figure 1 shows the distribution of new AL diagnoses in adult patients by date of presentation. This decrease was most pronounced in the first 30 days, in which only one new adult patient with AL presented to JHH. The distribution of adult patients diagnosed in the 30 days prior and 90 days following the March 2020 restrictions was significantly different from the corresponding time period in 2019 (p=0.03); however, the overall trend of new adult AL diagnoses in the 30 days prior and the 90 days following the March 2020 restrictions was not significantly different from the corresponding time period in 2019 (p= 0.77). Of note, many patients with AL reported symptoms that overlapped with those of COVID-19 including fatigue (40%), dyspnea (35%) and fever (22%). 35.1% of patients diagnosed with AL after restrictions had no characteristic symptoms of COVID-19, as compared to 12.5% of patients diagnosed with AL during this period in 2019 (Table 1). Discussion: These data suggest that new presentations of adult AL were delayed by COVID-19-related restrictions. Given the acuity of AL, this delay may have affected clinical outcomes. Interestingly, pediatric new AL cases did not decrease during this time period. The reasons are unclear, though parents appear to have remained willing to seek care for their children even during the uncertain days at the beginning of the pandemic, perhaps due to the media reporting that COVID-19 infection was less aggressive in young people. Given the possibility of additional lockdowns due to COVID-19 variants or new pandemics, these data highlight the importance of encouraging patients to seek care in the event of illness, screening patients for both infectious and non-infectious disease, and ensuring that routine medical care remains accessible. Figure 1 Figure 1. Disclosures Brown: Kura: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; KIte: Membership on an entity's Board of Directors or advisory committees. Webster: AmGen: Consultancy; Pfizer: Consultancy.

Flow structures in turbulent flows span many orders of magnitude of length and time scales. They range from the length scale at which very small eddies lose their coherence as their translational kinetic energy is dissipated into heat, up to eddies the size of which is related to that of the macroscopic system. The behaviour of the range of flow structures can be captured by assuming that the fluid is a continuum, and they can be described by solving the Navier-Stokes equations. However, analytical solutions of the Navier-Stokes equations exist only for simple cases. A complete description of turbulent flow in which the flow variables velocity and pressure are resolved as a function of space and time can be obtained only numerically. The instantaneous range of scales in turbulent flows increases rapidly with the Reynolds number. As a result, most engineering problems have a wide range of scales that can be computed using direct numerical simulation (DNS). As the complexity of the calculated flows increases, an improvement in turbulence models is often needed. One way to overcome this problem is to search for models that better capture the features of turbulence. Furthermore, the models should be parameterised in a way that allows flows to be simulated under a wide range of conditions. DNS is a useful tool in this endeavour, and it can be used to complement the long-established methodologies of experimental research. A large number of computational grids must be used to simulate a high Reynolds number inflows that occur in the complicated geometries often encountered in practical applications. This approach requires a considerable amount of computational power. For example, reducing the grid spacing in half increases the computational cost by a factor of about sixteen. Challenges presented by limitations imposed by computer hardware significantly limit the number of practical numerical solutions required to satisfy engineering needs. In this work, we propose an alternative approach. Rather than running an application that solves the Navier-Stokes equations on one computer, we have developed a platform that allows a group of computers to communicate with one another working together to obtain a solution of a specific flow problem. This approach helps to overcome the problem of hardware limitations. However, to grasp these challenges, we must devise new strategies to computational paradigms associated with parallel computing. In the case of solving the Navier-Stokes equations, we have to deal with significant computational and memory requirements. To overcome these requirements, software should be able to be run on many high-performance computers simultaneously, and network communication may become a new limiting issue that is specific only to parallel environments. Translating to parallel environments triggers several scenarios that do not exist when developing software that executes sequential operations. For example, "racing conditions" may appear that result in many threads that attempt to use different values of a shared variable, or they simultaneously attempt to overwrite it. The order of executions may be random as the operating system can swap between the threads at any time. Attempts to synchronise the threads may result in "deadlock" when all resources become simultaneously locked. Debugging and problem-solving in parallel environments is quite often difficult due to the potentially random nature of the orders in which threads run. All of these features require the development of new paradigms, and we must transform our way of envisioning the development of software for parallel execution. The solution to this problem is the motivation for the work presented in this thesis. A significant contribution of this work is to strategically use the ideas of thread injection to speed up the execution of sequential code. Bottlenecks are identified, and thread injection is used to parallelise the code that may be distributed to many different systems. This approach is implemented by creating a class that takes control over the sequential instructions that create the bottlenecks. The challenge to engineers and scientists is to determine how a given task can be split into components that can be run in parallel. The method is illustrated by applying it to Channelflow (Gibson, 2014), which is open-source Direct Numerical Simulation software used to simulate flows between two parallel plates. Another challenge that arises when approaching representations of real geometries is the scale and magnitude of the data samples. For example, Johns Hopkins Turbulent Database (JHTB) contains results of the solution of direct numerical simulation (DNS) of isotropic turbulent flow in the incompressible fluid in 3D space and only requires 100 TB data. Much more data needed to perform a simulation, and this is just a straightforward model. A natural answer to this challenge is to exploit the opportunities offered by contemporary applications of ‘database technology’ in computational fluid dynamics (CFD) and turbulence research. Direct numerical solution of the Navier-Stokes equations resolves all of the flow structures that influence turbulent flows. Still, in the case of Large Eddy Simulation, the Navier-Stokes equations are spatially filtered so that they are expressed in terms of the velocities of larger-scale structures. The rate of viscous dissipation is quantified by modelling the shear stress, and this process can lead to inaccuracies. A means of rapid testing and evaluation of models is therefore required, and this involves working with large data sets. The contribution of this work is the development of a computational platform that allows LES models to be dynamically loaded and to be rapidly evaluated against DNS data. An idea permeating the methodology is that a core is defined that contains the ‘know-how’ associated with accessing and manipulating data, and which operates independently of a plug-in. The thesis presents an example that demonstrates how users can examine the accuracy of LES models and obtain results almost instantaneously. Such methods allow engineers or scientists to propose their own LES models and implement them as a plug- in with only a few lines of code. We have demonstrated how it can be done by converting the Smagorinsky model to a plug-in to be used on our platform.

Benjamin G. Kohl (1938-2010) taught at Vassar College from 1966 till his retirement as Andrew W. Mellon Professor of the Humanities in 2001. His doctoral research at The Johns Hopkins University was directed by Frederic C. Lane, and his principal historical interests focused on northern Italy during the Renaissance, especially on Padua and Venice. His scholarly production includes the volumes Padua under the Carrara, 1318-1405 (1998), and Culture and Politics in Early Renaissance Padua (2001), and the online database The Rulers of Venice, 1332-1524 (2009). The database is eloquent testimony of his priority attention to historical sources and to their accessibility, and also of his enthusiasm for collaboration and sharing among scholars.

This chapter explores Chinese loan finance in Africa and its relevance for Africa’s economic modernization and structural transformation between 1960 and 2016. Drawing on an original database of Chinese loan finance China–Africa Research Initiative at Johns Hopkins University’s School of Advanced International Studies (SAIS-CARI), the chapter begins by outlining the changing actors involved in lending from China and the different kinds of loan instrument. It then examines the sectors in which Chinese lending clusters, shedding light on the degree to which African borrowers use these loans directly or indirectly to support structural transformation projects in industrialization and agro-finance, and related infrastructure. The chapter pays special attention to the modalities of structuring loan finance and providing guarantees of repayment in risky environments when many countries have only recently emerged from a long debt crisis. Finally, it considers concern over rising debt levels in a number of African countries.

Abstract Super-resolution is an innovative technique that upscales the resolution of an image or a video and thus enables us to reconstruct high-fidelity images from low-resolution data. This study performs super-resolution analysis on turbulent flow fields spatially and temporally using various state-of-the-art machine learning techniques like ESPCN, ESRGAN and TecoGAN to reconstruct high-resolution flow fields from low-resolution flow field data, especially keeping in mind the need for low resource consumption and rapid results production/verification. The dataset used for this study is extracted from the ‘isotropic 1024 coarse’ dataset which is a part of Johns Hopkins Turbulence Databases (JHTDB). We have utilized pre-trained models and fine tuned them to our needs, so as to minimize the computational resources and the time required for the implementation of the super-resolution models. The advantages presented by this method far exceed the expectations and the outcomes of regular single structure models. The results obtained through these models are then compared using MSE, PSNR, SAM, VIF and SCC metrics in order to evaluate the upscaled results, find the balance between computational power and output quality, and then identify the most accurate and efficient model for spatial and temporal super-resolution of turbulent flow fields.

Continuing preliminary data submitted last year, this paper focuses on effect of operation point on the structure of a tip leakage vortex (TLV) in compressor-like settings. Experiments are being performed at the Johns Hopkins University refractive index-matched facility. The transparent acrylic blades of the one and a half stage compressor have the same geometry, but lower aspect ratio as the inlet guide vanes and the first stage of the Low Speed Axial Compressor facility at NASA Glenn. The refractive index of the liquid, an aqueous NaI solution is matched with that of the blades and transparent casing, facilitating unobstructed stereo-PIV measurements. As the flow rate is reduced close to stall conditions, the leakage flow is confined to rotor chordwise sections further towards the leading edge, and the TLV rollup occurs further upstream, and more radially inward. However, as the leakage flow stops in the aft part of the passage, the near-stall TLV migrates faster to the PS side of the next blade. Instantaneous realizations demonstrate that the TLV consists of multiple interlaced vortices and never rolls up into a single structure, but when phased-averaged, it appears as single structure. The circumferential velocity peak is located radially inward of the mean vorticity center. Turbulent kinetic energy (TKE) is high in the TLV center, in the shear layer connecting the suction side (SS) corner to the TLV feeding vorticity into it, as well as in the region of flow separation on the endwall casing where the leakage flow meets the passage flow. The normal and shear Reynolds stress demonstrate high inhomogeneity and anisotropy, with the streamwise velocity fluctuations being the largest contributor to TKE. The dominant inplane contributors to TKE production rate involve contraction in the region of endwall casing separation and near the SS tip corner, and shear production in the shear layer. Fragmentation and rapid growth of the TLV occurs at mid passage, moving upstream with decreasing flow rate.

This experimental study examines the effect of tip gap size on the flow structure and turbulence in the tip region of an axial turbomachine. The experiments have been performed in the Johns Hopkins University (JHU) optically index-matched facility using an axial compressor settings designed based on the geometry of the inlet guide vanes (IGV) and the first stage of the Low Speed Axial Compressor (LSAC) facility at NASA Glenn. Two sets of rotor blades with similar cross sections, but with tip gap sizes of 0.49% and 2.3% of the blade chord (or 1.1% and 5.4% of the blade span) have been installed and tested. The measurements include performance tests, visualization of the tip leakage vortex (TLV) using cavitation, and stereo PIV (SPIV) measurements in several meridional planes. Increasing the tip gap size causes a substantial reduction in pressure rise across the machine for the same flow rate. The cavitation images, whose trends agree with the velocity and vorticity distributions obtained by the SPIV measurements, show that TLV rollup in the less loaded blade occurs at later chordwise location, and that the vortex remains located closer to the suction side (SS) corner of the originating blade. The delayed detachment from the blade with increasing gap is attributed to the increase of distance of the ‘image vortex’ (wall interaction) from the TLV. The wider gap also reduces the entrainment by the TLV of the endwall boundary layer after it separates at the point where the backward leakage flow meets the main passage flow. The previously observed TLV breakup, which is evident for the narrow gap in the aft part of the rotor passage, is delayed significantly for the wider gap. Consistent changes also appear in the distributions of turbulent kinetic energy, which peaks in the vicinity of the TLV core, the endwall boundary layer separation, and in the shear layer connecting the TLV center to the SS corner of the blade tip.