Impulse Correlation for Partially Filled Detonation Tubes

The effect of nozzles on the impulse obtained from a detonation tube of circular cross section has been the focus of many experimental and numerical studies. In these cases, the simplified detonation tube is closed at one end (forming the thrust surface) and open at the other end, enabling the attachment of an extension. A flowfield analysis of a detonation tube with an extension requires considering unsteady wave interactions making analytical and accurate numerical predictions difficult (especially in complicated extension geometries). To predict the impulse obtained from a detonation tube with an extension (considered a partially filled detonation tube), we utilize data from other researchers to generate a partial-fill correlation

Online identification and nonlinear control of the electrically stimulated quadriceps muscle

A new approach for estimating nonlinear models of the electrically stimulated quadriceps muscle group under nonisometric conditions is investigated. The model can be used for designing controlled neuro-prostheses. In order to identify the muscle dynamics (stimulation pulsewidth-active knee moment relation) from discrete-time angle measurements only, a hybrid model structure is postulated for the shank-quadriceps dynamics. The model consists of a relatively well known time-invariant passive component and an uncertain time-variant active component. Rigid body dynamics, described by the Equation of Motion (EoM), and passive joint properties form the time-invariant part. The actuator, i.e. the electrically stimulated muscle group, represents the uncertain time-varying section. A recursive algorithm is outlined for identifying online the stimulated quadriceps muscle group. The algorithm requires EoM and passive joint characteristics to be known a priori. The muscle dynamics represent the product of a continuous-time nonlinear activation dynamics and a nonlinear static contraction function described by a Normalised Radial Basis Function (NRBF) network which has knee-joint angle and angular velocity as input arguments. An Extended Kalman Filter (EKF) approach is chosen to estimate muscle dynamics parameters and to obtain full state estimates of the shank-quadriceps dynamics simultaneously. The latter is important for implementing state feedback controllers. A nonlinear state feedback controller using the backstepping method is explicitly designed whereas the model was identified a priori using the developed identification procedure

Performance Impact of Deflagration to Detonation Transition Enhancing Obstacles

A sub-model is developed to account for the drag and heat transfer enhancement resulting from deflagration-to-detonation (DDT) inducing obstacles commonly used in pulse detonation engines (PDE). The sub-model is incorporated as a source term in a time-accurate, quasi-onedimensional, CFD-based PDE simulation. The simulation and sub-model are then validated through comparison with a particular experiment in which limited DDT obstacle parameters were varied. The simulation is then used to examine the relative contributions from drag and heat transfer to the reduced thrust which is observed. It is found that heat transfer is far more significant than aerodynamic drag in this particular experiment

Numerical Analysis of a Pulse Detonation Cross Flow Heat Load Experiment

A comparison between experimentally measured and numerically simulated, time-averaged, point heat transfer rates in a pulse detonation (PDE) engine is presented. The comparison includes measurements and calculations for heat transfer to a cylinder in crossflow and to the tube wall itself using a novel spool design. Measurements are obtained at several locations and under several operating conditions. The measured and computed results are shown to be in substantial agreement, thereby validating the modeling approach. The model, which is based in computational fluid dynamics (CFD) is then used to interpret the results. A preheating of the incoming fuel charge is predicted, which results in increased volumetric flow and subsequent overfilling. The effect is validated with additional measurements

Neither dust nor black carbon causing apparent albedo decline in Greenland\u27s dry snow zone: Implications for MODIS C5 surface reflectance

Remote sensing observations suggest Greenland ice sheet (GrIS) albedo has declined since 2001, even in the dry snow zone. We seek to explain the apparent dry snow albedo decline. We analyze samples representing 2012–2014 snowfall across NW Greenland for black carbon and dust light-absorbing impurities (LAI) and model their impacts on snow albedo. Albedo reductions due to LAI are small, averaging 0.003, with episodic enhancements resulting in reductions of 0.01–0.02. No significant increase in black carbon or dust concentrations relative to recent decades is found. Enhanced deposition of LAI is not, therefore, causing significant dry snow albedo reduction or driving melt events. Analysis of Collection 5 Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data indicates that the decline and spectral shift in dry snow albedo contains important contributions from uncorrected Terra sensor degradation. Though discrepancies are mostly below the stated accuracy of MODIS products, they will require revisiting some prior conclusions with C6 data

Comparison of Numerically Simulated and Experimentally Measured Performance of a Rotating Detonation Engine

A quasi-two-dimensional, computational fluid dynamic (CFD) simulation of a rotating detonation engine (RDE) is described. The simulation operates in the detonation frame of reference and utilizes a relatively coarse grid such that only the essential primary flow field structure is captured. This construction and other simplifications yield rapidly converging, steady solutions. Viscous effects, and heat transfer effects are modeled using source terms. The effects of potential inlet flow reversals are modeled using boundary conditions. Results from the simulation are compared to measured data from an experimental RDE rig with a converging-diverging nozzle added. The comparison is favorable for the two operating points examined. The utility of the code as a performance optimization tool and a diagnostic tool are discussed

Multivariate Modeling Identifies Neutrophil- and Th17-Related Factors as Differential Serum Biomarkers of Chronic Murine Colitis

Diagnosis of chronic intestinal inflammation, which characterizes inflammatory bowel disease (IBD), along with prediction of disease state is hindered by the availability of predictive serum biomarker. Serum biomarkers predictive of disease state will improve trials for therapeutic intervention, and disease monitoring, particularly in genetically susceptible individuals. Chronic inflammation during IBD is considered distinct from infectious intestinal inflammation thereby requiring biomarkers to provide differential diagnosis. To address whether differential serum biomarkers could be identified in murine models of colitis, immunological profiles from both chronic spontaneous and acute infectious colitis were compared and predictive serum biomarkers identified via multivariate modeling.Discriminatory multivariate modeling of 23 cytokines plus chlorotyrosine and nitrotyrosine (protein adducts from reactive nitrogen species and hypochlorite) in serum and tissue from two murine models of colitis was performed to identify disease-associated biomarkers. Acute C. rodentium-induced colitis in C57BL/6J mice and chronic spontaneous Helicobacter-dependent colitis in TLR4(-/-) x IL-10(-/-) mice were utilized for evaluation. Colon profiles of both colitis models were nearly identical with chemokines, neutrophil- and Th17-related factors highly associated with intestinal disease. In acute colitis, discriminatory disease-associated serum factors were not those identified in the colon. In contrast, the discriminatory predictive serum factors for chronic colitis were neutrophil- and Th17-related factors (KC, IL-12/23p40, IL-17, G-CSF, and chlorotyrosine) that were also elevated in colon tissue. Chronic colitis serum biomarkers were specific to chronic colitis as they were not discriminatory for acute colitis.Immunological profiling revealed strikingly similar colon profiles, yet distinctly different serum profiles for acute and chronic colitis. Neutrophil- and Th17-related factors were identified as predictive serum biomarkers of chronic colitis, but not acute colitis, despite their presence in colitic tissue of both diseases thereby demonstrating the utility of mathematical modeling for identifying disease-associated serum biomarkers

Multivariate Modeling Identifies Neutrophil- and Th17-Related Factors as Differential Serum Biomarkers of Chronic Murine Colitis

Background: Diagnosis of chronic intestinal inflammation, which characterizes inflammatory bowel disease (IBD), along with prediction of disease state is hindered by the availability of predictive serum biomarker. Serum biomarkers predictive of disease state will improve trials for therapeutic intervention, and disease monitoring, particularly in genetically susceptible individuals. Chronic inflammation during IBD is considered distinct from infectious intestinal inflammation thereby requiring biomarkers to provide differential diagnosis. To address whether differential serum biomarkers could be identified in murine models of colitis, immunological profiles from both chronic spontaneous and acute infectious colitis were compared and predictive serum biomarkers identified via multivariate modeling.Methodology/Principal Findings: Discriminatory multivariate modeling of 23 cytokines plus chlorotyrosine and nitrotyrosine (protein adducts from reactive nitrogen species and hypochlorite) in serum and tissue from two murine models of colitis was performed to identify disease-associated biomarkers. Acute C. rodentium-induced colitis in C57BL/6J mice and chronic spontaneous Helicobacter-dependent colitis in TLR4−/− x IL-10−/− mice were utilized for evaluation. Colon profiles of both colitis models were nearly identical with chemokines, neutrophil- and Th17-related factors highly associated with intestinal disease. In acute colitis, discriminatory disease-associated serum factors were not those identified in the colon. In contrast, the discriminatory predictive serum factors for chronic colitis were neutrophil- and Th17-related factors (KC, IL-12/23p40, IL-17, G-CSF, and chlorotyrosine) that were also elevated in colon tissue. Chronic colitis serum biomarkers were specific to chronic colitis as they were not discriminatory for acute colitis.Conclusions/Significance: Immunological profiling revealed strikingly similar colon profiles, yet distinctly different serum profiles for acute and chronic colitis. Neutrophil- and Th17-related factors were identified as predictive serum biomarkers of chronic colitis, but not acute colitis, despite their presence in colitic tissue of both diseases thereby demonstrating the utility of mathematical modeling for identifying disease-associated serum biomarkers.</p