R134a flow patterns in small diameter tubes

R134a vapour-liquid two-phase flow patterns were studied in vertical small diameter tubes. The observed flow patterns include bubbly, dispersed bubble, slug, churn, annular and mist flow. Six integrated flow pattern maps, derived for two internal diameters (2.01 and 4.26 mm) and three different pressures (6.0, 10.0, 14.0 bar), are presented. Some transition boundaries, such as slug-churn and churn-annular, were found to be very sensitive to diameter and pressure. On the contrary, the boundaries of dispersed bubble-churn and bubbly-slug are less affected. The transition boundaries are compared with the existing models for normal size tubes showing significant differences

The effect of tube diameter on vertical two-phase flow regimes in small tubes

Flow boiling flow patterns in four circular tubes with internal diameters of 1.10, 2.01, 2.88 and 4.26 mm were investigated in the present project. The experiments were conducted in vertical upward two-phase flow using R134a as the working fluid. The observed flow patterns include dispersed bubble, bubbly, confined bubble, slug, churn, annular and mist flow. The flow characteristics in the 2.88 and 4.26 mm tubes are similar to those typically described in normal size tubes. The smaller diameter tubes, 1.10 and 2.01 mm, exhibit strong "small tube characteristics" as described in earlier studies. The sketched flow maps show that the transition boundaries of slug-churn and churn-annular depend strongly on diameter. On the contrary, the dispersed bubble to churn and bubbly to slug boundaries are less affected. The transition boundaries are compared with existing models for normal size tubes showing poor agreement

Vertical upward flow patterns in small diameter tubes

Two-phase flow patterns were studied in vertical small diameter tubes using R134a as the working fluid. The observed flow patterns include bubbly, dispersed bubble, confined bubble, slug, churn, annular and mist flow. Twelve flow pattern maps, derived from four internal diameters (1.10, 2.01, 2.88 and 4.26 mm) and three different pressures (6, 10, 14 bar), are presented. The flow patterns exhibit strong “small tube characteristics” described in earlier studies when the tube diameter is 2 mm or less. Slug-churn and churn-annular boundaries depend on diameter and pressure. Dispersed bubble-churn and bubbly-slug are less affected. The transition boundaries are compared with existing models for normal size tubes showing poor agreement. Various coordinate systems were considered for the flow maps. The results show that the Lockhard-Martinelli Parameter and mass flow flux can account for the effect of fluid pressure on flow patterns

Investigation of Partial Discharge in Solid Dielectric under DC Voltage

A partial discharge, or PD, is defined as an electrical discharge that is localized within only a part of the insulation between two separated conductors. Recent research on PD mainly focuses on the study of PD characteristics under AC voltage. Compared with DC, PD under AC is more serious and can be easily detected in terms of PD number. As the results of these concentrated research, the understanding of PD under AC condition has been significantly improved and features extracted from PD measurements have been used to diagnose the insulation condition of many power apparatus. Recently, rapid development in HVDC transmission and power grids connection, and widely applied DC cable and gas-insulated switchgear because of their benefit in long distance usage lead to an increasing concern about PD under DC. However, available study for the condition is little and related research is therefore necessary and essential for understanding the lifetime and reliability of apparatus. <br/

Topology of Entanglement in Multipartite States with Translational Invariance

The topology of entanglement in multipartite states with translational invariance is discussed in this article. Two global features are foundby which one can distinguish distinct states. These are the cyclic unit and the quantised geometric phase. Furthermore the topology is indicated by the fractional spin. Finally a scheme is presented for preparation of these types of states in spin chain systems, in which the degeneracy of the energy levels characterises the robustness of the states with translational invariance.Comment: major revision. accepted by EPJ

Combined therapy with GABA and proinsulin/alum acts synergistically to restore long-term normoglycemia by modulating T-cell autoimmunity and promoting β-cell replication in newly diabetic NOD mice.

Antigen-based therapies (ABTs) fail to restore normoglycemia in newly diabetic NOD mice, perhaps because too few β-cells remain by the time that ABT-induced regulatory responses arise and spread. We hypothesized that combining a fast-acting anti-inflammatory agent with an ABT could limit pathogenic responses while ABT-induced regulatory responses arose and spread. γ-Aminobutyric acid (GABA) administration can inhibit inflammation, enhance regulatory T-cell (Treg) responses, and promote β-cell replication in mice. We examined the effect of combining a prototypic ABT, proinsulin/alum, with GABA treatment in newly diabetic NOD mice. Proinsulin/alum monotherapy failed to correct hyperglycemia, while GABA monotherapy restored normoglycemia for a short period. Combined treatment restored normoglycemia in the long term with apparent permanent remission in some mice. Proinsulin/alum monotherapy induced interleukin (IL)-4- and IL-10-secreting T-cell responses that spread to other β-cell autoantigens. GABA monotherapy induced moderate IL-10 (but not IL-4) responses to β-cell autoantigens. Combined treatment synergistically reduced spontaneous type 1 T-helper cell responses to autoantigens, ABT-induced IL-4 and humoral responses, and insulitis, but enhanced IL-10 and Treg responses and promoted β-cell replication in the islets. Thus, combining ABT with GABA can inhibit pathogenic T-cell responses, induce Treg responses, promote β-cell replication, and effectively restore normoglycemia in newly diabetic NOD mice. Since these treatments appear safe for humans, they hold promise for type 1 diabetes intervention

Removal of sulfamethoxazole and sulfapyridine by carbon nanotubes in fixed-bed columns

Sulfamethoxazole (SMX) and sulfapyridine (SPY), two representative sulfonamide antibiotics, have gained increasing attention because of the ecological risks these substances pose to plants, animals, and humans. This work systematically investigated the removal of SMX and SPY by carbon nanotubes (CNTs) in fixed-bed columns under a broad range of conditions including: CNT incorporation method, solution pH, bed depth, adsorbent dosage, adsorbate initial concentration, and flow rate. Fixed-bed experiments showed that pH is a key factor that affects the adsorption capacity of antibiotics to CNTs. The Bed Depth Service Time model describes well the relationship between service time and bed depth and can be used to design appropriate column parameters. During fixed-bed regeneration, small amounts of SMX (3%) and SPY (9%) were irreversibly bonded to the CNT/sand porous media, thus reducing the column capacity for subsequent reuse from 67.9 to 50.4 mg g−1 for SMX and from 91.9 to 72.9 mg g−1 for SPY. The reduced column capacity resulted from the decrease in available adsorption sites and resulting repulsion (i.e., blocking) of incoming antibiotics from those previously adsorbed. Findings from this study demonstrate that fixed-bed columns packed with CNTs can be efficiently used and regenerated to remove antibiotics from water

An adaptive dwell time scheduling model for phased array radar based on three-way decision

Real-time resource allocation is crucial for phased array radars to undertake multi-task with limited resources such as in the situation of multi-target tracking, in which targets need to be prioritized so that resources can be allocated accordingly and effectively. In this paper, a three-way decision-based model is proposed for adaptive scheduling of phased radar dwell time. Using the model, the threat posed by a target is measured by an evaluation function, and therefore, a target is assigned to one of the three possible decision regions, i.e., positive region, negative region, and boundary region. A different region has a various priority in terms of resource demand, and as such, a different radar resource allocation decision is applied to each region to satisfy different tracking accuracy of multi-target. In addition, the dwell time scheduling model can be further optimized by implementing a strategy for determining a proper threshold of three-way decision making to optimize the thresholds adaptively in real-time. The advantages and the performance of the proposed model has been verified by experimental simulations with comparison to the traditional two-way decision model and the three-way decision model without threshold optimization. The experiential results have demonstrated that the performance of the proposed model has a certain advantage in detecting high threat targets. 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Intelligent Aircraft Maneuvering Decision Based on CNN

© 2019 Association for Computing Machinery. Aiming at the maneuvering decision of aircraft in air combat, an intelligent maneuvering decision model based on convolutional neural network(CNN) is proposed in this paper. Firstly, the situation data, maneuvering decision variables and evaluation indexs are given, and a CNN model that can realize intelligent maneuvering decision is established. Then, according to the evaluation indexes, the structure and parameters of the CNN model are adjusted through the simulation experiments to improve the accuracy and robustness of the maneuvering decision. After that, the validity of the intelligent maneuvering decision model proposed in this paper is verified through comparative experiments that the CNN model can make stable maneuvering decisions with high accuracy. Finally, the flight path in an air combat process is presented