70 research outputs found
Turbulence Modeling Validation, Testing, and Development
The primary objective of this work is to provide accurate numerical solutions for selected flow fields and to compare and evaluate the performance of selected turbulence models with experimental results. Four popular turbulence models have been tested and validated against experimental data often turbulent flows. The models are: (1) the two-equation k-epsilon model of Wilcox, (2) the two-equation k-epsilon model of Launder and Sharma, (3) the two-equation k-omega/k-epsilon SST model of Menter, and (4) the one-equation model of Spalart and Allmaras. The flows investigated are five free shear flows consisting of a mixing layer, a round jet, a plane jet, a plane wake, and a compressible mixing layer; and five boundary layer flows consisting of an incompressible flat plate, a Mach 5 adiabatic flat plate, a separated boundary layer, an axisymmetric shock-wave/boundary layer interaction, and an RAE 2822 transonic airfoil. The experimental data for these flows are well established and have been extensively used in model developments. The results are shown in the following four sections: Part A describes the equations of motion and boundary conditions; Part B describes the model equations, constants, parameters, boundary conditions, and numerical implementation; and Parts C and D describe the experimental data and the performance of the models in the free-shear flows and the boundary layer flows, respectively
Synthetic Turbulence, Fractal Interpolation and Large-Eddy Simulation
Fractal Interpolation has been proposed in the literature as an efficient way
to construct closure models for the numerical solution of coarse-grained
Navier-Stokes equations. It is based on synthetically generating a
scale-invariant subgrid-scale field and analytically evaluating its effects on
large resolved scales. In this paper, we propose an extension of previous work
by developing a multiaffine fractal interpolation scheme and demonstrate that
it preserves not only the fractal dimension but also the higher-order structure
functions and the non-Gaussian probability density function of the velocity
increments. Extensive a-priori analyses of atmospheric boundary layer
measurements further reveal that this Multiaffine closure model has the
potential for satisfactory performance in large-eddy simulations. The
pertinence of this newly proposed methodology in the case of passive scalars is
also discussed
The Lag Model Applied to High Speed Flows
The Lag model has shown great promise in prediction of low speed and transonic separations. The predictions of the model, along with other models (Spalart-Allmaras and Menter SST) are assessed for various high speed flowfields. In addition to skin friction and separation predictions, the prediction of heat transfer are compared among these models, and some fundamental building block flowfields, are investigated
Turbulence compressibility corrections
The basic objective of this research was to identify, develop and recommend turbulence models which could be incorporated into CFD codes used in the design of the National AeroSpace Plane vehicles. To accomplish this goal, a combined effort consisting of experimental and theoretical phases was undertaken. The experimental phase consisted of a literature survey to collect and assess a database of well documented experimental flows, with emphasis on high speed or hypersonic flows, which could be used to validate turbulence models. Since it was anticipated that this database would be incomplete and would need supplementing, additional experiments in the NASA Ames 3.5-Foot Hypersonic Wind Tunnel (HWT) were also undertaken. The theoretical phase consisted of identifying promising turbulence models through applications to simple flows, and then investigating more promising models in applications to complex flows. The complex flows were selected from the database developed in the first phase of the study. For these flows it was anticipated that model performance would not be entirely satisfactory, so that model improvements or corrections would be required. The primary goals of the investigation were essentially achieved. A large database of flows was collected and assessed, a number of additional hypersonic experiments were conducted in the Ames HWT, and two turbulence models (kappa-epsilon and kappa-omega models with corrections) were determined which gave superior performance for most of the flows studied and are now recommended for NASP applications
Convergence to SPDEs in Stratonovich form
We consider the perturbation of parabolic operators of the form
by large-amplitude highly oscillatory spatially dependent
potentials modeled as Gaussian random fields. The amplitude of the potential is
chosen so that the solution to the random equation is affected by the
randomness at the leading order. We show that, when the dimension is smaller
than the order of the elliptic pseudo-differential operator , the
perturbed parabolic equation admits a solution given by a Duhamel expansion.
Moreover, as the correlation length of the potential vanishes, we show that the
latter solution converges in distribution to the solution of a stochastic
parabolic equation with a multiplicative term that should be interpreted in the
Stratonovich sense. The theory of mild solutions for such stochastic partial
differential equations is developed. The behavior described above should be
contrasted to the case of dimensions that are larger than or equal to the order
of the elliptic pseudo-differential operator . In the latter case, the
solution to the random equation converges strongly to the solution of a
homogenized (deterministic) parabolic equation as is shown in the companion
paper [2]. The stochastic model is therefore valid only for sufficiently small
space dimensions in this class of parabolic problems.Comment: 21 page
Π’ΡΠΎΠΌΠ±ΠΎΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΎΠΊΠΊΠ»ΡΠ·ΠΈΡ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΎΡΡΡΡΠΌ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΈΠ½ΡΡΠ»ΡΡΠΎΠΌ
Currently, reperfusion therapy is the main method of treating patients with ischemic stroke (IS). The safety and efficacy of systemic thrombolytic therapy with a recombinant tissue plasminogen activator in patients with IS within 3 hours, and then 4.5 hours after the onset of symptoms of the disease was demonstrated in the NINDS (1995) and ECASS III (2008) studies. In 2018, based on the results of five studies, clear indications were formulated for performing thrombectomy (TE) in patients with IS, which involve the detection of thrombosis of a large stroke-associated artery. Given the continuous growth in the number of the adult population, which constitutes the bulk of patients with IS, information on the prevalence of patients with thrombotic occlusion of cerebral arteries, who are potential candidates for TE, may be important for regional vascular centers.Aim of study. To describe IS patients admitted within the 6-hour βtherapeutic windowβ.Materials and methods. The study included 145 patients with cerebral IS who were admitted within the first 6 hours after the onset of symptoms of the disease. All patients underwent computed tomographic (CT) angiography in order to verify the occlusion of the cerebral artery.Results. In our study, a correlation was established between the NIHSS severity of IS and the likelihood of verification of stroke-related artery thrombosis by CT angiography, but in 32.6% of patients with severe stroke (NIHSS at least score 14), no thrombotic occlusion was detected, and in 13% of patients with a clinic of mild acute cerebrovascular accident (NIHSS no more than 6), on the contrary, thrombotic occlusion was detected. Mortality in patients with verified thrombotic occlusion of the cerebral artery was higher than in patients without it (38% versus 10.5%, p<0.001). Such a significant difference in the mortality rate was due to the initially more severe stroke (NIHSS at admission 17 [10; 23] versus 5 [2; 10], p><0.001) in patients with thrombotic occlusion of a stroke-related artery, as well as a higher incidence of severe swallowing disorders (30% versus 9.5%, p ><0.002), which are a risk factor for pneumonia, as well as a higher frequency of such a comorbid background as chronic kidney disease and atrial fibrillation (30% versus 13.7%, p=0.018% and 58% versus 29.5%, p=0.001, respectively). CONCLUSION 1. Thrombosis of the cerebral stroke-associated artery was detected in 34.5% of patients with ischemic stroke who were admitted within the first 6 hours from the onset of the disease. 2. The main reason for the failure to perform thrombectomy in patients with ischemic stroke admitted within the 6-hour therapeutic window is the lack of verification of stroke-related artery thrombosis using computed tomographic angiography. Due to thrombosis at a different location (other than thrombosis of the internal carotid artery and / or M1 segment of the middle cerebral artery), 10% of patients with verified thrombosis did not meet the currently existing selection criteria for thrombectomy. Keywords: ischemic stroke, reperfusion therapy, cerebral artery thrombosis, cryptogenic stroke>Λ0.001). Such a significant difference in the mortality rate was due to the initially more severe stroke (NIHSS at admission 17 [10; 23] versus 5 [2; 10], pΛ0.001) in patients with thrombotic occlusion of a stroke-related artery, as well as a higher incidence of severe swallowing disorders (30% versus 9.5%, pΛ0.002), which are a risk factor for pneumonia, as well as a higher frequency of such a comorbid background as chronic kidney disease and atrial fibrillation (30% versus 13.7%, p=0.018% and 58% versus 29.5%, p=0.001, respectively).Conclusion. 1. Thrombosis of the cerebral stroke-associated artery was detected in 34.5% of patients with ischemic stroke who were admitted within the first 6 hours from the onset of the disease. 2. The main reason for the failure to perform thrombectomy in patients with ischemic stroke admitted within the 6-hour therapeutic window is the lack of verification of stroke-related artery thrombosis using computed tomographic angiography. Due to thrombosis at a different location (other than thrombosis of the internal carotid artery and / or M1 segment of the middle cerebral artery), 10% of patients with verified thrombosis did not meet the currently existing selection criteria for thrombectomy.Β Π Π½Π°ΡΡΠΎΡΡΠ΅Π΅ Π²ΡΠ΅ΠΌΡ ΡΠ΅ΠΏΠ΅ΡΡΡΠ·ΠΈΠΎΠ½Π½Π°Ρ ΡΠ΅ΡΠ°ΠΏΠΈΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΠΌ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Π»Π΅ΡΠ΅Π½ΠΈΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΈΠ½ΡΡΠ»ΡΡΠΎΠΌ (ΠΠ). ΠΠ΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΡ ΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎΠΉ ΡΡΠΎΠΌΠ±ΠΎΠ»ΠΈΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ ΠΏΡΠΈ ΠΏΠΎΠΌΠΎΡΠΈ ΡΠ΅ΠΊΠΎΠΌΠ±ΠΈΠ½Π°Π½ΡΠ½ΠΎΠ³ΠΎ ΡΠΊΠ°Π½Π΅Π²ΠΎΠ³ΠΎ Π°ΠΊΡΠΈΠ²Π°ΡΠΎΡΠ° ΠΏΠ»Π°Π·ΠΌΠΈΠ½ΠΎΠ³Π΅Π½Π° Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΠ Π² ΠΏΡΠ΅Π΄Π΅Π»Π°Ρ
3 ΡΠ°ΡΠΎΠ², Π° Π² ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠ΅ΠΌ 4,5 ΡΠ°ΡΠ° ΠΎΡ Π½Π°ΡΠ°Π»Π° ΡΠΈΠΌΠΏΡΠΎΠΌΠΎΠ² Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ Π±ΡΠ»Π° ΠΏΡΠΎΠ΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠΎΠ²Π°Π½Π° Π² ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡΡ
NINDS (1995) ΠΈ ECASS III (2008). Π 2018 Π³ΠΎΠ΄Ρ, ΠΎΡΠ½ΠΎΠ²ΡΠ²Π°ΡΡΡ Π½Π° ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ°Ρ
ΠΏΡΡΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ, Π±ΡΠ»ΠΈ ΡΡΠΎΡΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½Ρ ΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΠΎΠΊΠ°Π·Π°Π½ΠΈΡ Π΄Π»Ρ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΡΡΠΎΠΌΠ±ΡΠΊΡΠΎΠΌΠΈΠΈ (Π’Π) Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΠ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΏΠΎΠ΄ΡΠ°Π·ΡΠΌΠ΅Π²Π°ΡΡ Π²ΡΡΠ²Π»Π΅Π½ΠΈΠ΅ ΡΡΠΎΠΌΠ±ΠΎΠ·Π° ΠΊΡΡΠΏΠ½ΠΎΠΉ ΠΈΠ½ΡΡΠ»ΡΡ-ΡΠ²ΡΠ·Π°Π½Π½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ. Π ΡΡΠ»ΠΎΠ²ΠΈΡΡ
Π½Π΅ΠΏΡΠ΅ΡΡΠ²Π½ΠΎΠ³ΠΎ ΡΠΎΡΡΠ° ΡΠΈΡΠ»Π° Π²Π·ΡΠΎΡΠ»ΠΎΠ³ΠΎ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ, ΡΠΎΡΡΠ°Π²Π»ΡΡΡΠ΅Π³ΠΎ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ ΠΌΠ°ΡΡΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΠ, ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΎ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½Π½ΠΎΡΡΠΈ Π±ΠΎΠ»ΡΠ½ΡΡ
Ρ ΡΡΠΎΠΌΠ±ΠΎΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΠΊΠΊΠ»ΡΠ·ΠΈΠ΅ΠΉ ΡΠ΅ΡΠ΅Π±ΡΠ°Π»ΡΠ½ΡΡ
Π°ΡΡΠ΅ΡΠΈΠΉ, ΡΠ²Π»ΡΡΡΠΈΡ
ΡΡ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΡΠΌΠΈ ΠΏΡΠ΅ΡΠ΅Π½Π΄Π΅Π½ΡΠ°ΠΌΠΈ Π΄Π»Ρ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ Π’Π, ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ Π²Π°ΠΆΠ½ΠΎΠΉ Π΄Π»Ρ ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠΎΡΡΠ΄ΠΈΡΡΡΡ
ΡΠ΅Π½ΡΡΠΎΠ².Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ. ΠΡ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΠΎΠ²Π°ΡΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΠ, ΠΏΠΎΡΡΡΠΏΠ°ΡΡΠΈΡ
Π² 6-ΡΠ°ΡΠΎΠ²ΠΎΠΌ Β«ΡΠ΅ΡΠ°ΠΏΠ΅Π²ΡΠΈΡΠ΅ΡΠΊΠΎΠΌ ΠΎΠΊΠ½Π΅Β».ΠΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. Π ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π²ΠΊΠ»ΡΡΠ΅Π½Ρ 145 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΡΠ΅ΡΠ΅Π±ΡΠ°Π»ΡΠ½ΡΠΌ ΠΠ, ΠΏΠΎΡΡΡΠΏΠΈΠ²ΡΠΈΡ
Π² ΠΏΠ΅ΡΠ²ΡΠ΅ 6 ΡΠ°ΡΠΎΠ² ΠΎΡ Π½Π°ΡΠ°Π»Π° ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠΈΠΌΠΏΡΠΎΠΌΠΎΠ² Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ. ΠΡΠ΅ΠΌ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ°ΠΌ Ρ ΡΠ΅Π»ΡΡ Π²Π΅ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΎΠΊΠΊΠ»ΡΠ·ΠΈΠΈ ΡΠ΅ΡΠ΅Π±ΡΠ°Π»ΡΠ½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ Π²ΡΠΏΠΎΠ»Π½ΡΠ»ΠΈ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΡΡ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΡΡ (ΠΠ’) Π°Π½Π³ΠΈΠΎΠ³ΡΠ°ΡΠΈΡ.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. Π Π½Π°ΡΠ΅ΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π±ΡΠ»Π° ΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½Π° ΠΊΠΎΡΡΠ΅Π»ΡΡΠΈΡ ΠΌΠ΅ΠΆΠ΄Ρ ΡΡΠΆΠ΅ΡΡΡΡ ΠΠ ΠΏΠΎ ΡΠΊΠ°Π»Π΅ NIHSS ΠΈ Π²Π΅ΡΠΎΡΡΠ½ΠΎΡΡΡΡ Π²Π΅ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΏΡΠΈ ΠΏΠΎΠΌΠΎΡΠΈ ΠΠ’-Π°Π½Π³ΠΈΠΎΠ³ΡΠ°ΡΠΈΠΈ ΡΡΠΎΠΌΠ±ΠΎΠ·Π° ΠΈΠ½ΡΡΠ»ΡΡ-ΡΠ²ΡΠ·Π°Π½Π½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ, Π½ΠΎ Ρ 32,6% ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΊΠ»ΠΈΠ½ΠΈΠΊΠΎΠΉ ΡΡΠΆΠ΅Π»ΠΎΠ³ΠΎ ΠΈΠ½ΡΡΠ»ΡΡΠ° (NIHSS Π½Π΅ ΠΌΠ΅Π½Π΅Π΅ 14 Π±Π°Π»Π»ΠΎΠ²) Π½Π΅ Π±ΡΠ»ΠΎ Π²ΡΡΠ²Π»Π΅Π½ΠΎ ΡΡΠΎΠΌΠ±ΠΎΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΠΊΠΊΠ»ΡΠ·ΠΈΠΈ, Π° Ρ 13% ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΊΠ»ΠΈΠ½ΠΈΠΊΠΎΠΉ Π»Π΅Π³ΠΊΠΎ ΠΏΡΠΎΡΠ΅ΠΊΠ°ΡΡΠ΅Π³ΠΎ ΠΎΡΡΡΠΎΠ³ΠΎ Π½Π°ΡΡΡΠ΅Π½ΠΈΡ ΠΌΠΎΠ·Π³ΠΎΠ²ΠΎΠ³ΠΎ ΠΊΡΠΎΠ²ΠΎΠΎΠ±ΡΠ°ΡΠ΅Π½ΠΈΡ (NIHSS Π½Π΅ Π±ΠΎΠ»Π΅Π΅ 6 Π±Π°Π»Π»ΠΎΠ²), Π½Π°ΠΏΡΠΎΡΠΈΠ², ΡΡΠΎΠΌΠ±ΠΎΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΎΠΊΠΊΠ»ΡΠ·ΠΈΡ Π±ΡΠ»Π° Π²ΡΡΠ²Π»Π΅Π½Π°. ΠΠ΅ΡΠ°Π»ΡΠ½ΠΎΡΡΡ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ Π²Π΅ΡΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΡΡΠΎΠΌΠ±ΠΎΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΠΊΠΊΠ»ΡΠ·ΠΈΠ΅ΠΉ ΡΠ΅ΡΠ΅Π±ΡΠ°Π»ΡΠ½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ Π±ΡΠ»Π° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ Π·Π½Π°ΡΠΈΠΌΠΎ Π²ΡΡΠ΅, ΡΠ΅ΠΌ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Π±Π΅Π· ΡΠ°ΠΊΠΎΠ²ΠΎΠΉ (38% ΠΏΡΠΎΡΠΈΠ² 10,5%, Ρ<0,001). Π‘ΡΠΎΠ»Ρ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½Π°Ρ ΡΠ°Π·Π½ΠΈΡΠ° ΠΌΠ΅ΠΆΠ΄Ρ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠΌΠΈ Π»Π΅ΡΠ°Π»ΡΠ½ΠΎΡΡΠΈ Π±ΡΠ»Π° ΠΎΠ±ΡΡΠ»ΠΎΠ²Π»Π΅Π½Π° ΠΈΡΡ
ΠΎΠ΄Π½ΠΎ Π±ΠΎΠ»Π΅Π΅ ΡΡΠΆΠ΅Π»ΡΠΌ ΠΈΠ½ΡΡΠ»ΡΡΠΎΠΌ (ΠΎΡΠ΅Π½ΠΊΠ° ΠΏΠΎ NIHSS ΠΏΡΠΈ ΠΏΠΎΡΡΡΠΏΠ»Π΅Π½ΠΈΠΈ 17 [10; 23] ΠΏΡΠΎΡΠΈΠ² 5 [2; 10], p><0,001, ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ Π·Π½Π°ΡΠΈΠΌΠΎ) Ρ Π±ΠΎΠ»ΡΠ½ΡΡ
Ρ ΡΡΠΎΠΌΠ±ΠΎΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΠΊΠΊΠ»ΡΠ·ΠΈΠ΅ΠΉ ΠΈΠ½ΡΡΠ»ΡΡ-ΡΠ²ΡΠ·Π°Π½Π½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ, Π° ΡΠ°ΠΊΠΆΠ΅ Π±ΠΎΠ»ΡΡΠ΅ΠΉ ΡΠ°ΡΡΠΎΡΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ Π·Π½Π°ΡΠΈΠΌΡΡ
Π³ΡΡΠ±ΡΡ
ΡΠ°ΡΡΡΡΠΎΠΉΡΡΠ² Π³Π»ΠΎΡΠ°Π½ΠΈΡ (30% ΠΏΡΠΎΡΠΈΠ² 9,5%, p><0,002, ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ Π·Π½Π°ΡΠΈΠΌΠΎ), ΡΠ²Π»ΡΡΡΠΈΡ
ΡΡ ΡΠ°ΠΊΡΠΎΡΠΎΠΌ ΡΠΈΡΠΊΠ° ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΏΠ½Π΅Π²ΠΌΠΎΠ½ΠΈΠΈ ΠΈ ΡΠ°ΠΊΠΎΠ³ΠΎ ΠΊΠΎΠΌΠΎΡΠ±ΠΈΠ΄Π½ΠΎΠ³ΠΎ ΡΠΎΠ½Π°, ΠΊΠ°ΠΊ Ρ
ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠ°Ρ Π±ΠΎΠ»Π΅Π·Π½Ρ ΠΏΠΎΡΠ΅ΠΊ ΠΈ ΡΠΈΠ±ΡΠΈΠ»Π»ΡΡΠΈΡ ΠΏΡΠ΅Π΄ΡΠ΅ΡΠ΄ΠΈΠΉ (30% ΠΏΡΠΎΡΠΈΠ² 13,7%, Ρ=0,018 ΠΈ 58% ΠΏΡΠΎΡΠΈΠ² 29,5%, Ρ=0,001 ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ). ΠΡΠ²ΠΎΠ΄Ρ 1. Π’ΡΠΎΠΌΠ±ΠΎΠ· ΡΠ΅ΡΠ΅Π±ΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΈΠ½ΡΡΠ»ΡΡ-ΡΠ²ΡΠ·Π°Π½Π½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ Π²ΡΡΠ²Π»Π΅Π½ Ρ 34,5% ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΈΠ½ΡΡΠ»ΡΡΠΎΠΌ, ΠΏΠΎΡΡΡΠΏΠ°ΡΡΠΈΡ
Π² ΠΏΠ΅ΡΠ²ΡΠ΅ 6 ΡΠ°ΡΠΎΠ² ΠΎΡ Π½Π°ΡΠ°Π»Π° Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ. 2. ΠΡΠ½ΠΎΠ²Π½ΠΎΠΉ ΠΏΡΠΈΡΠΈΠ½ΠΎΠΉ Π½Π΅Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΡΡΠΎΠΌΠ±ΡΠΊΡΠΎΠΌΠΈΠΈ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΈΠ½ΡΡΠ»ΡΡΠΎΠΌ, ΠΏΠΎΡΡΡΠΏΠΈΠ²ΡΠΈΡ
Π² 6-ΡΠ°ΡΠΎΠ²ΠΎΠΌ Β«ΡΠ΅ΡΠ°ΠΏΠ΅Π²ΡΠΈΡΠ΅ΡΠΊΠΎΠΌ ΠΎΠΊΠ½Π΅Β», ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΡΡΡΡΡΡΠ²ΠΈΠ΅ Π²Π΅ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΡΡΠΎΠΌΠ±ΠΎΠ·Π° ΠΈΠ½ΡΡΠ»ΡΡ-ΡΠ²ΡΠ·Π°Π½Π½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ ΠΏΡΠΈ ΠΏΠΎΠΌΠΎΡΠΈ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠΉ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π°Π½Π³ΠΈΠΎΠ³ΡΠ°ΡΠΈΠΈ. ΠΠΎ ΠΏΡΠΈΡΠΈΠ½Π΅ ΡΡΠΎΠΌΠ±ΠΎΠ·Π° Π΄ΡΡΠ³ΠΎΠΉ Π»ΠΎΠΊΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ (ΠΎΡΠ»ΠΈΡΠ½ΠΎΠΉ ΠΎΡ ΡΡΠΎΠΌΠ±ΠΎΠ·Π° Π²Π½ΡΡΡΠ΅Π½Π½Π΅ΠΉ ΡΠΎΠ½Π½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ ΠΈ/ΠΈΠ»ΠΈ Π1 ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ° ΡΡΠ΅Π΄Π½Π΅ΠΉ ΠΌΠΎΠ·Π³ΠΎΠ²ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ) 10% ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ Π²Π΅ΡΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠΌ ΡΡΠΎΠΌΠ±ΠΎΠ·ΠΎΠΌ Π½Π΅ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΎΠ²Π°Π»ΠΈ ΡΡΡΠ΅ΡΡΠ²ΡΡΡΠΈΠΌ Π² Π½Π°ΡΡΠΎΡΡΠ΅Π΅ Π²ΡΠ΅ΠΌΡ ΠΊΡΠΈΡΠ΅ΡΠΈΡΠΌ ΠΎΡΠ±ΠΎΡΠ° Π΄Π»Ρ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΡΡΠΎΠΌΠ±ΡΠΊΡΠΎΠΌΠΈΠΈ. ΠΠ»ΡΡΠ΅Π²ΡΠ΅ ΡΠ»ΠΎΠ²Π°: ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΈΠ½ΡΡΠ»ΡΡ, ΡΠ΅ΠΏΠ΅ΡΡΡΠ·ΠΈΠΎΠ½Π½Π°Ρ ΡΠ΅ΡΠ°ΠΏΠΈΡ, ΡΡΠΎΠΌΠ±ΠΎΠ· ΠΌΠΎΠ·Π³ΠΎΠ²ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ, ΠΊΡΠΈΠΏΡΠΎΠ³Π΅Π½Π½ΡΠΉ ΠΈΠ½ΡΡΠ»ΡΡ>Λ 0,001). Π‘ΡΠΎΠ»Ρ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½Π°Ρ ΡΠ°Π·Π½ΠΈΡΠ° ΠΌΠ΅ΠΆΠ΄Ρ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠΌΠΈ Π»Π΅ΡΠ°Π»ΡΠ½ΠΎΡΡΠΈ Π±ΡΠ»Π° ΠΎΠ±ΡΡΠ»ΠΎΠ²Π»Π΅Π½Π° ΠΈΡΡ
ΠΎΠ΄Π½ΠΎ Π±ΠΎΠ»Π΅Π΅ ΡΡΠΆΠ΅Π»ΡΠΌ ΠΈΠ½ΡΡΠ»ΡΡΠΎΠΌ (ΠΎΡΠ΅Π½ΠΊΠ° ΠΏΠΎ NIHSS ΠΏΡΠΈ ΠΏΠΎΡΡΡΠΏΠ»Π΅Π½ΠΈΠΈ 17 [10; 23] ΠΏΡΠΎΡΠΈΠ² 5 [2; 10], pΛ 0,001, ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ Π·Π½Π°ΡΠΈΠΌΠΎ) Ρ Π±ΠΎΠ»ΡΠ½ΡΡ
Ρ ΡΡΠΎΠΌΠ±ΠΎΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΠΊΠΊΠ»ΡΠ·ΠΈΠ΅ΠΉ ΠΈΠ½ΡΡΠ»ΡΡ-ΡΠ²ΡΠ·Π°Π½Π½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ, Π° ΡΠ°ΠΊΠΆΠ΅ Π±ΠΎΠ»ΡΡΠ΅ΠΉ ΡΠ°ΡΡΠΎΡΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ Π·Π½Π°ΡΠΈΠΌΡΡ
Π³ΡΡΠ±ΡΡ
ΡΠ°ΡΡΡΡΠΎΠΉΡΡΠ² Π³Π»ΠΎΡΠ°Π½ΠΈΡ (30% ΠΏΡΠΎΡΠΈΠ² 9,5%, pΛ 0,002, ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ Π·Π½Π°ΡΠΈΠΌΠΎ), ΡΠ²Π»ΡΡΡΠΈΡ
ΡΡ ΡΠ°ΠΊΡΠΎΡΠΎΠΌ ΡΠΈΡΠΊΠ° ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΏΠ½Π΅Π²ΠΌΠΎΠ½ΠΈΠΈ ΠΈ ΡΠ°ΠΊΠΎΠ³ΠΎ ΠΊΠΎΠΌΠΎΡΠ±ΠΈΠ΄Π½ΠΎΠ³ΠΎ ΡΠΎΠ½Π°, ΠΊΠ°ΠΊ Ρ
ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠ°Ρ Π±ΠΎΠ»Π΅Π·Π½Ρ ΠΏΠΎΡΠ΅ΠΊ ΠΈ ΡΠΈΠ±ΡΠΈΠ»Π»ΡΡΠΈΡ ΠΏΡΠ΅Π΄ΡΠ΅ΡΠ΄ΠΈΠΉ (30% ΠΏΡΠΎΡΠΈΠ² 13,7%, Ρ=0,018 ΠΈ 58% ΠΏΡΠΎΡΠΈΠ² 29,5%, Ρ=0,001 ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ).ΠΡΠ²ΠΎΠ΄Ρ. 1. Π’ΡΠΎΠΌΠ±ΠΎΠ· ΡΠ΅ΡΠ΅Π±ΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΈΠ½ΡΡΠ»ΡΡ-ΡΠ²ΡΠ·Π°Π½Π½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ Π²ΡΡΠ²Π»Π΅Π½ Ρ 34,5% ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΈΠ½ΡΡΠ»ΡΡΠΎΠΌ, ΠΏΠΎΡΡΡΠΏΠ°ΡΡΠΈΡ
Π² ΠΏΠ΅ΡΠ²ΡΠ΅ 6 ΡΠ°ΡΠΎΠ² ΠΎΡ Π½Π°ΡΠ°Π»Π° Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ. 2. ΠΡΠ½ΠΎΠ²Π½ΠΎΠΉ ΠΏΡΠΈΡΠΈΠ½ΠΎΠΉ Π½Π΅Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΡΡΠΎΠΌΠ±ΡΠΊΡΠΎΠΌΠΈΠΈ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΈΠ½ΡΡΠ»ΡΡΠΎΠΌ, ΠΏΠΎΡΡΡΠΏΠΈΠ²ΡΠΈΡ
Π² 6-ΡΠ°ΡΠΎΠ²ΠΎΠΌ Β«ΡΠ΅ΡΠ°ΠΏΠ΅Π²ΡΠΈΡΠ΅ΡΠΊΠΎΠΌ ΠΎΠΊΠ½Π΅Β», ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΡΡΡΡΡΡΠ²ΠΈΠ΅ Π²Π΅ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΡΡΠΎΠΌΠ±ΠΎΠ·Π° ΠΈΠ½ΡΡΠ»ΡΡ-ΡΠ²ΡΠ·Π°Π½Π½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ ΠΏΡΠΈ ΠΏΠΎΠΌΠΎΡΠΈ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠΉ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π°Π½Π³ΠΈΠΎΠ³ΡΠ°ΡΠΈΠΈ. ΠΠΎ ΠΏΡΠΈΡΠΈΠ½Π΅ ΡΡΠΎΠΌΠ±ΠΎΠ·Π° Π΄ΡΡΠ³ΠΎΠΉ Π»ΠΎΠΊΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ (ΠΎΡΠ»ΠΈΡΠ½ΠΎΠΉ ΠΎΡ ΡΡΠΎΠΌΠ±ΠΎΠ·Π° Π²Π½ΡΡΡΠ΅Π½Π½Π΅ΠΉ ΡΠΎΠ½Π½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ ΠΈ/ΠΈΠ»ΠΈ Π1 ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ° ΡΡΠ΅Π΄Π½Π΅ΠΉ ΠΌΠΎΠ·Π³ΠΎΠ²ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ) 10% ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ Π²Π΅ΡΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠΌ ΡΡΠΎΠΌΠ±ΠΎΠ·ΠΎΠΌ Π½Π΅ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΎΠ²Π°Π»ΠΈ ΡΡΡΠ΅ΡΡΠ²ΡΡΡΠΈΠΌ Π² Π½Π°ΡΡΠΎΡΡΠ΅Π΅ Π²ΡΠ΅ΠΌΡ ΠΊΡΠΈΡΠ΅ΡΠΈΡΠΌ ΠΎΡΠ±ΠΎΡΠ° Π΄Π»Ρ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΡΡΠΎΠΌΠ±ΡΠΊΡΠΎΠΌΠΈΠΈ.
Three-dimensional modelling of arc behaviour and gas shield quality in tandem gasβmetal arc welding using anti-phase pulse synchronization
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