APPLICATION OF REINFORCEMENT LEARNING IN MANAGED PRESSURE DRILLING

Automation in any industry has a control system as its base, and control systems are composed of a controller. In recent years an area of machine learning known as reinforcement learning (RL) has been focused on solving control problems for engineers and scientists. RL methods are actively applied to design control mechanisms for various industrial applications and in this study, the focus will be on designing such algorithms and modeling the given control problem into a structure where these RL algorithms can be applied. In the oil and gas industry, there has been a push to expand operations into areas where usual drilling methods are not successful mainly because of narrow operational windows, and technologies such as Managed Pressure Drilling (MPD) are found to be very successful in solving this issue. MPD is a control technique that is aimed at controlling the bottom hole pressure between narrow operational windows. The standard technique used for automating MPD is a proportional-integral-derivative (PID) controller, but many other non-linear control systems have also been employed to do the same task. This study seeks to add value to the drilling process by developing an Reinforcement Learning (RL) based agent to tune the PID controller. After tuning the PID controller, the system dynamics will be optimized and kept under boundary conditions of the drilling environment. The goal is to provide a reference bottom hole pressure set point and tuning parameters to the PID controller so that the optimum pressure can be reached safely at a certain depth. During the study, the most important features were the depth of the drilling bit, the fracture pressure, and pore pressure at that depth. The RL agent first proposes a suitable reference bottom hole pressure based on the fracture and pore pressure and then tunes the PID controller to achieve the desired pressure set point. The task of training this RL agent is handled in a specialized simulator environment which can calculate the bottom hole pressure at every simulation step and give feedback to the agent about the status. The agent uses a policy gradient method called Proximal Policy Optimization (PPO) and then later on Multi-armed bandit algorithms. PPO is implemented using Mathwork’s Reinforcement Learning Toolbox, and after some tuning of hyperparameters, the agent is able to narrow down to an optimal policy for various depth scenarios, whereas the latter is developed in python. At the end of this study, the agent is able to replace the decision maker and automatically suggest reference bottom hole pressure and tune the PID accordingly

Command Injection Attacks in Smart Grids: A Survey

Cybersecurity is important in the realization of various smart grid technologies. Several studies have been conducted to discuss different types of cyberattacks and provide their countermeasures. The false command injection attack (FCIA) is considered one of the most critical attacks that have been studied. Various techniques have been proposed in the literature to detect FCIAs on different components of smart grids. The predominant focus of current surveys lies on FCIAs and detection techniques for such attacks. This article presents a survey of existing works on FCIAs and classifies FCIAs in smart grids according to the targeted component. The impacts of FCIAs on smart grids are also discussed. Subsequently, this article provides an extensive review of detection studies, categorizing them based on the type of detection technique employed

Efficient Pellets. Influencing Production Parameters to make energy efficient pellets

Feed manufacturing is an important aspect of animal production that occupies a huge share of the economics of commercial animal production. The feed produced has different physically quantifiable parameters that determine its quality, such as hardness, length, and durability. These parameters are influenced by the equipment and production characteristics such as the conditioning temperature, type of mill used for grinding, roller type, etc. We performed an experiment that analyzed the quality parameters after making pellets using the same diet but with different conditioning temperatures, rollers, roller die distance, and die dimensions. The effect of these parameters and their interactions were then studied. We used 6 dies, three with 5-mm die holes and three with 3-mm die holes with varying thicknesses, with dimpled and corrugated rollers at varying roller-die gaps. Increasing the conditioning temperature improved the durability of the pellets. Increasing the roller die gap with the thinnest and medium thickness of 5 mm die reduced the durability, whereas it improved it for the thickest die. Increasing the roller die gap generally improved the quality of 3 mm dies. Increasing the thickness of the die also improved pellet quality. Interaction effects are complicated, and there is a need for more research to better understand the

Embedding Information into or onto Additively Manufactured Parts: A Review of QR Codes, Steganography and Watermarking Methods

The paper gives a detailed review of the approaches adopted for embedding information into/onto additively manufactured parts. The primary purpose of this paper is to review all the techniques adopted for embedding information, highlight notable trends and improvements in these works, and provide design and manufacturing pipelines to realize most of these works. It classifies these approaches into four different categories and summarizes the works carried out in each field. It also compares all the results in textual and tabular forms and then gives a detailed conclusion of the best works in terms of application and effectiveness. The four categories discussed are 3D QR codes, 3D watermarking, steganography and nonclassified methods. Lastly, it discusses the future extensions and potential improvements in the field of embedding information, while exploring manufacturing technologies

Outcome of N-Acetylcysteine Nebulization Versus Salbutamol Nebulization in Children with Acute Bronchiolitis

Background: A substantial proportion of children will experience at least one episode with bronchiolitis, and as much as 2-3% of all children will be hospitalized with bronchiolitis during their first year of life. Bronchiolitis is the most common reason for hospitalization of children in many countries, challenging both economy, area and staffing in paediatric departments. Objective: To determine outcome (in terms of clinical severity score and hospital stay) of N-acetylcysteine nebulization versus salbutamol nebulization in children with acute bronchiolitis. Material and Methods: The study cases were randomly divided into 2 groups by draws methods. Group A, each child was nebulized with 20 mg NAC in 3 ml of 0.9% of saline while group B was nebulized with 2.5 mg salbutamol in 3 ml of 0.9% saline solution. Patients of each group were nebulized three times a day (8 hours apart) for 5 days. These patients were closely monitored for the severity of the disease daily and clinical severity score was employed to record any improvement in both cases.  All the data was entered and analyzed using SPSS-18. Results: Of these 390 study cases, 228 (58.5%) were boys while 162 (41.5%) were girls. Mean age of our study cases was 7.92 ± 5.18 months . Most of the study cases i.e. 264 (67.7%) were from poor social background and mothers of most of these children were less educated as 85.6% of the mothers of these children were having their educational status equal/less than matriculation. Mean hospital stay in our study was 4.73 ± 0.829 days. Mean baseline clinical severity score was 5.52 ± 813. Mean clinical severity score after therapy was 1.85 ± 0.812 (with minimum clinical severity score was 1 while maximum was score was 4). Clinical severity score in group A was 1.21 ± 0.405 while in group B was 2.49 ± 0.578 (p= 0.000). Conclusion: Our study results support the use N – acetylcysteine nebulization in children with acute bronchiolitis as compared with salbutamol nebulization. N – acetylcysteine nebulization was found to be more effective in improving clinical severity score and reducing duration of hospitalization. Its use was safe, reliable and no adverse side effects were noted. Keywords: Acute Bronchiolitis, Salbutamol, N – acetylcysteine