Drag-reduction strategies in wall-bounded turbulent flows using deep reinforcement learning

In this work we compare different drag-reduction strategies that compute their actuation based on the fluctuations at a given wall-normal location in turbulent open channel flow. In order to perform this study, we implement and describe in detail the reinforcement-learning interface to a computationally-efficient, parallelized, high-fidelity solver for fluid-flow simulations. We consider opposition control (Choi, Moin, and Kim, Journal of Fluid Mechanics 262, 1994) and the policies learnt using deep reinforcement learning (DRL) based on the state of the flow at two inner-scaled locations ($y^+ = 10$ and $y^+ = 15$). By using deep deterministic policy gradient (DDPG) algorithm, we are able to discover control strategies that outperform existing control methods. This represents a first step in the exploration of the capability of DRL algorithm to discover effective drag-reduction policies using information from different locations in the flow.Comment: 6 pages, 5 figure

Dynamic Characteristics of Bubbling and Turbulent Fluidization Using Hurst Analysis Technique

A non-intrusive vibration monitoring technique was used to study the flow behavior in a fluidized bed. This technique has several advantages compared to other techniques, such as pressure probes and optical fiber probes which may influence the measurement because they are intrusive. Experiments were conducted in a 15 cm diameter by 2 m tall fluidized bed using 470 micron sand particles. Auto correlation functions, mutual information function and Hurst exponent analyses were used to analyze the fluidized bed hydrodynamics near the transition point from bubbling to turbulent fluidization regime. These methods were able to detect the regime transition point using vibration signals

Application of low transformation-temperature filler to reduce the residual stresses in welded component

Tensile residual stress is a major issue in integrity of the welded structures. Undesirable tensile residual stress in welding may reduce fracture toughness and fatigue life of welded structures. The low transformation-temperature (LTT) fillers, due to introducing compressive residual stresses caused by prior martensitic transformation, can reduce tensile residual stresses in the weld zone. The effects of using LTT fillers on welding residual stresses of high strength steel sheets are studied and compared with conventional fillers. 3D finite element simulations including coupled thermal-metallurgical-mechanical analyses are developed using SYSWELD software to predict the welding residual stresses. For validation of the finite element model, the residual stresses are measured through hole drilling strain gage method. The results indicate that using the LTT fillers cause a decrease of the longitudinal tensile residual stresses of the weld metal from 554 MPa to 216 MPa in comparison with conventional fillers. The transverse residual stresses of the weld line are changed from tensile 156 MPa to compressive 289 MPa with using LTT fillers instead of conventional fillers

Recovering 6D Object Pose: A Review and Multi-modal Analysis

A large number of studies analyse object detection and pose estimation at visual level in 2D, discussing the effects of challenges such as occlusion, clutter, texture, etc., on the performances of the methods, which work in the context of RGB modality. Interpreting the depth data, the study in this paper presents thorough multi-modal analyses. It discusses the above-mentioned challenges for full 6D object pose estimation in RGB-D images comparing the performances of several 6D detectors in order to answer the following questions: What is the current position of the computer vision community for maintaining "automation" in robotic manipulation? What next steps should the community take for improving "autonomy" in robotics while handling objects? Our findings include: (i) reasonably accurate results are obtained on textured-objects at varying viewpoints with cluttered backgrounds. (ii) Heavy existence of occlusion and clutter severely affects the detectors, and similar-looking distractors is the biggest challenge in recovering instances' 6D. (iii) Template-based methods and random forest-based learning algorithms underlie object detection and 6D pose estimation. Recent paradigm is to learn deep discriminative feature representations and to adopt CNNs taking RGB images as input. (iv) Depending on the availability of large-scale 6D annotated depth datasets, feature representations can be learnt on these datasets, and then the learnt representations can be customized for the 6D problem

Changes in body mass index and lipid profile in psoriatic patients after treatment with standard protocol of infliximab

Psoriasis is a chronic and inflammatory dermatologic disease. Psoriasis may predispose to cardiovascular disease and diabetes. However, the role of tumor necrosis factor (TNF) inhibitor in mediating this risk is controversial. Regarding frequent use of infliximab in psoriasis, and the hypothesis that anti TNF-α treatment may increase Body Mass Index (BMI) and alter lipid profile in these patients, the aim of this study was to assess changes in BMI and Lipid Profile and level of leptin in Psoriatic Patients under Treatment of Standard Protocol of Infliximab in a 24 week period. This study was accomplished as a before-after study. Twenty-seven psoriatic patients were included, and standard infliximab therapy was applied. All patients underwent 3 times of blood collection and in each session; LDL, HDL, Total Cholesterol, Triglycerides, Leptin, and PASI score were measured at the start of the study and at the 12th and 24th week of follow-up. Twenty-five patients consisted of 18 (72) male and 7 (28) female subjects were evaluated. The mean age of the patients was 36.91±13.31 years. PASI score demonstrated significant decrease after 24 weeks; however, BMI and HDL and leptin showed a significant increase during treatment. Significant negative correlation was seen between Leptin and PASI score changes (r=0.331, P=0.042). HDL and BMI had the most correlations with leptin (positive correlation) and PASI score (negative correlation). Results demonstrated a dramatic decrease in PASI, increase in BMI and HDL and increased in leptin; somewhat correlated to each other. These results suggest that patients taking infliximab should take more care of their weight and lipid profile, while on treatment. © 2016 Tehran University of Medical Sciences. All rights reserved