33 research outputs found
An Experimental Factor Analysis Study Using SAW and TOPSIS to Select and Rank Organic Agriculture Cities in Turkey
The agriculture sector supports Turkey’s GDP portfolio economically and helps establish a sustainable labor force. Turkey has certain competitive advantages in terms of the organic production of agricultural goods like figs and hazelnuts. We conduct a factor analysis using Simple Additive Weighting (SAW) andTechnique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods combined with a 3-level set (export volume, export value, and adequacy rate) to rank 32 candidate cities of Turkey where organic agriculture activities should be given more emphasis to support overall production and export rates. 18 different sets of importance values were used for this purpose and their combinatorial effects on candidate cities were analyzed. The factor analysis results show that the cities Izmir, Aydin, Adiyaman, Gaziantep, Agri, Mus, and Van have the highest potentials among all Turkish cities in bothmethods, while Sanliurfa also shows high potential for organic agriculture in the TOPSIS method
Turbulent Boundary Layer Features via Lagrangian Coherent Structures, Proper Orthogonal Decomposition and Dynamic Mode Decomposition
High-speed stereo PIV-measurements have been performed in a turbulent boundary layer at Reθ of 9800 in order to elucidate the coherent structures. Snapshot proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) are used to visualize the flow structure depending on the turbulent kinetic energy and frequency content. The first six POD and DMD modes show the largest and the lowest amount of energy and frequency, respectively. Lagrangian coherent structure (LCS) based on the algorithm developed using the variational theory is also applied to track the flow via attracting and repelling trajectories. The shapes and the length of the trajectories show variation with increasing advection time. LCS trajectories are overlayed with the individual POD and DMD modes. Repelling and attracting lines cover the structure of these modes. Reconstructed flow fields from individual POD modes are also used to generate new LCS trajectories. The energy and frequency content have a direct impact on the length of the trajectories, where the longest reconstructed trajectories associate with the higher energy and lower frequency modes, and vise verse. The multiple intersection points between the repelling and attracting lines marked the low momentum regions
A Linear Approximation Method for a Stochastic Constraint for a Multi-Objective Nonlinear Eurobond Investment Portfolio Model
Nonlinear mathematical models are widely used better to reflect the stochastic structure of financial investment problems and to express them numerically. However, in some real-life situations, it is necessary to consider not only one purpose but many purposes simultaneously. Therefore, we have to define these models with multi-objective programming. This study defines a multi-objective nonlinear Eurobond investment portfolio and showcases the normal distribution of purchase and selling prices. The study then proposes a mechanism to convert the stochastic constraint into an equivalent deterministic form and provides near-optimal solutions in reasonable times
Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study
: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)
Anisotropic character of low-order turbulent flow descriptions through the proper orthogonal decomposition
Proper orthogonal decomposition (POD) is applied to distinct data sets in order to characterize the propagation of error arising from basis truncation in the description of turbulence. Experimental data from stereo particle image velocimetry measurements in a wind turbine array and direct numerical simulation data from a fully developed channel flow are used to illustrate dependence of the anisotropy tensor invariants as a function of POD modes used in low-order descriptions. In all cases, ensembles of snapshots illuminate a variety of anisotropic states of turbulence. In the near wake of a model wind turbine, the turbulence field reflects the periodic interaction between the incoming flow and rotor blade. The far wake of the wind turbine is more homogenous, confirmed by the increased magnitude of the anisotropy factor. By contrast, the channel flow exhibits many anisotropic states of turbulence. In the inner layer of the wall-bounded region, one observes one-component turbulence at the wall; immediately above, the turbulence is dominated by two components, with the outer layer showing fully three-dimensional turbulence, conforming to theory for wall-bounded turbulence. The complexity of flow descriptions resulting from truncated POD bases can be greatly mitigated by severe basis truncations. However, the current work demonstrates that such simplification necessarily exaggerates the anisotropy of the modeled flow and, in extreme cases, can lead to the loss of three-dimensionality. Application of simple corrections to the low-order descriptions of the Reynolds stress tensor significantly reduces the residual root-mean-square error. Similar error reduction is seen in the anisotropy tensor invariants. Corrections of this form reintroduce three-dimensionality to severe truncations of POD bases. A threshold for truncating the POD basis based on the equivalent anisotropy factor for each measurement set required many more modes than a threshold based on energy. The mode requirement to reach the anisotropy threshold after correction is reduced by a full order of magnitude for all example data sets, ensuring that economical low-dimensional models account for the isotropic quality of the turbulence field
Identification of Markov Process Within a Wind Turbine Array Boundary Layer
The Markovian properties within a wind turbine array boundary layer are explored for data taken in a wind tunnel containing a model wind turbine array. A stochastic analysis of the data is carried out using the mathematics of Markov processes. The data were obtained using hot-wire anemometry thus providing point velocity statistics. The theory of Markov process is applied to obtain a statistical description of longitudinal velocity increments inside the turbine wake. Comparison of two- and three-scale conditional probability density functions indicates the existence of Markovian properties in longitudinal velocity increments for scale differences larger than the Taylor microscale. This result is quantified by use of the Wilcoxon rank-sum test which verifies that this relationship holds independent of initial scale selection outside of the near-wake region behind a wind turbine. Furthermore, at the locations which demonstrate Markovian properties, there appears to be a well defined inertial subrange which follows Kolmogorov\u27s −5/3 scaling behavior. The results show that directly behind the tips of the rotor and the hub, the complex turbulent interactions and large scale structures of the near-wake affect the Markovian nature of the field. The presence of a Markov process in the remaining locations leads to characterization of the development multiscale statistics of the wind turbine wakes using the most recent states of the flow
Wind Turbine Boundary Layer Arrays for Cartesian and Staggered Configurations: Part II, Low-Dimensional Representations via the Proper Orthogonal Decomposition
Cartesian and row-offset wind turbine array configurations were tested investigating the wake interaction and recovery dynamics. The snapshot proper orthogonal decomposition is applied to velocity measurements. Resulting modes are used in constructing low-dimensional descriptions of turbulence statistics including the turbulence kinetic energy production and the flux of turbulence kinetic energy. Descriptions of the turbulent behavior are made on the basis of the span of the streamwise average profile of the Reynolds shear stress, , with the addition of orthogonal modes. The Reynolds stress criterion was selected for the convergence of the model as it is a good representation of the range of turbulent dynamics in the wake of a wind turbine. The description demonstrates that the turbulence kinetic energy production and the flux of turbulence kinetic energy are accurately rebuilt with approximately 1% of the total resultant orthogonal modes. Structures associated with the top-tip of the rotor blade reconstruct with fewer modes than those associated with the bottom-tip of the rotor or the nacelle. This confirms that the greatest part of the turbulence kinetic energy is located high in the turbine canopy as described by the turbulent stresses. Overall, behavior of individual turbines in recovered positions within the arrays requires fewer modes to converge than those in locations with less recovered inflows
Hessian-based Topology of Two-phase Slug Flow
Experimental slug flow is analyzed through a topological method and proper orthogonal decomposition (POD). Local phase fractions of a pipe cross-section, acquired through X-ray tomographic reconstruction, are analyzed by extracting critical points via eigenvalues associated with the Hessian matrix. Based on the sign of the eigenvalues, three types of critical points are classified: local maxima, minima and saddle points. Reduced order descriptions (ROD), obtained as results of the POD, are examined to investigate the flow dynamics associated with the primary eigenfunctions with respect to critical point placement and frequency. Voronoï mapping is employed for visualization of the critical points as a function of cross-sectional location, and quantification of the spatial distribution of the critical points. For each classification, the sum of the respective critical point over the cross-section correlates to the temporal holdup of liquid within the pipe. The local maxima and minima display an increase in their occurrence that relates to the liquid slug passage while the local saddle points follow the profile of the liquid holdup as the bubble is forming after the passage of the liquid slug. The total number of local maxima per snapshot as a function of time peaks prior to the liquid holdup peak, displaying the instabilities present in the flow field preceding the liquid slug reaching the top of the pipe. Applying critical point theory to the RODs reveals that the first two modes capture the liquid-dominated slug body region and the Taylor bubble/liquid film region. The observed time lag between the total maxima and the liquid holdup provides opportunity for implementation of predictive control monitoring in fields where instabilities influence system mechanics
Inverse Structure Functions in the Canonical Wind Turbine Array Boundary Layer
Wind tunnel measurements for a 3×3 canonical wind turbine array boundary layer are obtained using hot-wire anemometer velocity signals. Two downstream locations are considered, referring to the near- and far-wake, and 21 vertical points are acquired per profile. Velocity increments and exit distances are used to quantify inverse structure functions at both downstream locations. Inverse structure functions in the near-wake show a similar profile for the main vertical locations, but diverge as the moment is increased. In the far-wake, inverse structure functions converge toward a single function for all vertical location and moments. The scaling exponents for inverse structure functions are calculated directly and relatively, using extended self similarity. Scaling exponents show strong dependence on vertical position along the wind turbine profile in the near-wake and remain relatively constant in the farwake. Intermittency in the near-wake is indicated by the nonlinear behavior of the direct and relative scaling exponents when plotted against their respective moment