Experimental and theoretical investigation of three-dimensional turbulent boundary layers and turbulence characteristics inside an axial flow inducer passage

Analytical and experimental investigations of the characteristics of three dimensional turbulent boundary layers in a rotating helical passage of an inducer rotor are reported. Expressions are developed for the velocity profiles in the inner layer, where the viscous effects dominate, in the outer layer, where the viscous effects are small, and in the interference layer, where the end walls influence the flow. The prediction of boundary layer growth is based on the momentum integral technique. The equations derived are general enough to be valid for all turbomachinery rotors with arbitrary pressure gradients. The experimental investigations are carried out in a flat plate inducer 3 feet in diameter. The mean velocity profiles, turbulence intensities and shear stresses, wall shear stress, and limiting streamline angles are measured at various radial and chordwise locations by using rotating probes. The measurements are in general agreement with the predictions. The radial flows are well represented by an expression which includes the effect of stagger angle and radial pressure gradient. The radial flows in the rotor channel are higher than those on a single blade. The collateral region exists only very near the blade surface. The radial component of turbulence intensity is higher than the streamwise component because of the effect of rotation

Towards Auto Contract Generation and Ensemble-based Smart Contract Vulnerability Detection

Smart contracts (SC) are computer programs that are major components of Blockchain. The "intelligent contract" is made up of the rules accepted by the parties concerned. When the transactions started by the parties obey these established rules, then only their transactions will be completed without the involvement of a third party. Because of the simplicity and succinct nature of the solidity language, most smart contracts are written in this language. Smart contracts have two limitations, which are vulnerabilities in SC and that smart contracts can\u27t be understood by all stakeholders, especially non-technical people who are involved in the business, since they are written in a programming language. Hence, the proposed paper used the XGBoost model and BPMN (Business Process Modeling Notation) tool to solve the first and second limitations of the SC respectively. Attackers are drawn to attention because of the popularity and fragility of the Solidity language. Once smart contracts have been launched, they can’t be changed. If that smart contract is vulnerable, attackers may then cash it. BPMN is used to represent business rules or contracts in graphical notation, so everyone involved in the business can understand the business rules. This BPMN diagram can be converted into a smart contract template through the BPMN-SOL tool. A few publications and existing tools exist on smart contract vulnerability detection, but they require more time to forecast and interpretation of vulnerability causes is also difficult. Thus, the proposed model experimented with several deep learning approaches and improved F1 score results by an average of 2% using the XGBoost model based on the ensemble technique to detect vulnerabilities of SCs, which are: Denial of Service (DOS), Unchecked external call, Re-entrancy, and Origin of Transaction. This paper also combined two important features to construct a data set, which are code snippets and n-grams

End wall flows in rotors and stators of a single stage compressor

A computer code for solving the parabolized Navier-Stokes equations for internal flows was developed. Oscillations that develop in the calculation procedure are discussed. The measurements made in the hub and annulus wall boundary layers are summarized. The flow in the hub wall boundary layer, starting ahead of the inlet guide vanes to the inlet of the rotor is traced

Optimal Attack against Cyber-Physical Control Systems with Reactive Attack Mitigation

This paper studies the performance and resilience of a cyber-physical control system (CPCS) with attack detection and reactive attack mitigation. It addresses the problem of deriving an optimal sequence of false data injection attacks that maximizes the state estimation error of the system. The results provide basic understanding about the limit of the attack impact. The design of the optimal attack is based on a Markov decision process (MDP) formulation, which is solved efficiently using the value iteration method. Using the proposed framework, we quantify the effect of false positives and mis-detections on the system performance, which can help the joint design of the attack detection and mitigation. To demonstrate the use of the proposed framework in a real-world CPCS, we consider the voltage control system of power grids, and run extensive simulations using PowerWorld, a high-fidelity power system simulator, to validate our analysis. The results show that by carefully designing the attack sequence using our proposed approach, the attacker can cause a large deviation of the bus voltages from the desired setpoint. Further, the results verify the optimality of the derived attack sequence and show that, to cause maximum impact, the attacker must carefully craft his attack to strike a balance between the attack magnitude and stealthiness, due to the simultaneous presence of attack detection and mitigation

Modeling and Detecting False Data Injection Attacks against Railway Traction Power Systems

Modern urban railways extensively use computerized sensing and control technologies to achieve safe, reliable, and well-timed operations. However, the use of these technologies may provide a convenient leverage to cyber-attackers who have bypassed the air gaps and aim at causing safety incidents and service disruptions. In this paper, we study false data injection (FDI) attacks against railways' traction power systems (TPSes). Specifically, we analyze two types of FDI attacks on the train-borne voltage, current, and position sensor measurements - which we call efficiency attack and safety attack -- that (i) maximize the system's total power consumption and (ii) mislead trains' local voltages to exceed given safety-critical thresholds, respectively. To counteract, we develop a global attack detection (GAD) system that serializes a bad data detector and a novel secondary attack detector designed based on unique TPS characteristics. With intact position data of trains, our detection system can effectively detect the FDI attacks on trains' voltage and current measurements even if the attacker has full and accurate knowledge of the TPS, attack detection, and real-time system state. In particular, the GAD system features an adaptive mechanism that ensures low false positive and negative rates in detecting the attacks under noisy system measurements. Extensive simulations driven by realistic running profiles of trains verify that a TPS setup is vulnerable to the FDI attacks, but these attacks can be detected effectively by the proposed GAD while ensuring a low false positive rate.Comment: IEEE/IFIP DSN-2016 and ACM Trans. on Cyber-Physical System

Three dimensional flow field inside compressor rotor, including blade boundary layers

The flow in a turbomachinery blade passage has a predominant flow direction. The viscous diffusion in the streamwise direction is usually small and the elliptic influence is transmitted upstream through the pressure field. Starting with a guessed pressure field, it is possible to converge on the full elliptic solution by iterating between a parabolic solution and an iteration of the pressure field. The main steps of the calculation are given. The blade boundary layers which are three dimensional with laminar, transitional, turbulent, and separation zones are investigated. The kinetic energy is analyzed, and the dissipation equation is presented. Measurements were made of the three dimensional flow inside an axial flow compressor passage

Cost-Benefit Analysis of Moving-Target Defense in Power Grids

We study moving-target defense (MTD) that actively perturbs transmission line reactances to thwart stealthy false data injection (FDI) attacks against state estimation in a power grid. Prior work on this topic has proposed MTD based on randomly selected reactance perturbations, but these perturbations cannot guarantee effective attack detection. To address the issue, we present formal design criteria to select MTD reactance perturbations that are truly effective. However, based on a key optimal power flow (OPF) formulation, we find that the effective MTD may incur a non-trivial operational cost that has not hitherto received attention. Accordingly, we characterize important tradeoffs between the MTD's detection capability and its associated required cost. Extensive simulations, using the MATPOWER simulator and benchmark IEEE bus systems, verify and illustrate the proposed design approach that for the first time addresses both key aspects of cost and effectiveness of the MTD.Comment: IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) - 201

A study of anti-inflammatory activity of the benzofuran compound (3,4-dihydro 4-oxo-benzofuro [3,2-d] pyrimidine-2-propionic acid) in chronic model of inflammation

Background: Benzofuran compounds are shown to have pharmacological properties such as antiarrhythmic, antidepressant, antifungal, and antibacterial activity. Some studies conducted on them have revealed that they are having anti-inflammatory property also. Hence, we carried out this study to know whether the benzofuran compound 3, 4-dihydro 4-oxo-benzofuro (3, 2-d) pyrimidine-2-propionic acid has got anti-inflammatory activity against chronic inflammation.Methods: Wistar albino rats were treated with benzofuran compound under study and phenylbutazone in the dose of 100 mg\kg, orally with 2% gum acacia as suspending agent and the effects were observed in chronic experimental model of inflammation namely, cotton pellet induced granuloma model.Results: In the present study, it was shown that the benzofuran compound under study has got significant anti-inflammatory activity against the chronic model of inflammation.Conclusion: Our experiment shows that the benzofuran compound under study has got significant anti-inflammatory activity and may, as well become an additional anti-inflammatory drug if further studies are conducted in this direction involving human beings

Screening of benzofuran compound 3-acetamido-2-p-anisoyl benzofuran for anti-inflammatory activity in acute models of inflammation

Background: Benzofurans are colourless solid compounds which are derived from coal tar. They have been shown to have many properties which are relevant to the field of pharmacology. For example they have significant antibacterial, antifungal, antidepressant and anti-arrhythmic properties. In some of the studies carried out on them they have shown to have anti-inflammatory activity also. So this study was conducted to know if the compound 3-acetamido-2-p-anisoyl benzofuran has anti-inflammatory activity in acute inflammation.Methods: The benzofuran compound understudy and phenylbutazone were administered orally to wistar albino rats in the dose of 100 mg/kg body weight, with 2% gum acacia as suspending agent and the effects were observed in acute models of inflammation viz, carrageenin induced rat paw edema, and turpentine induced peritonitis.Results: The results of our study showed that the benzofuran compound under study has significant anti-inflammatory activity in both the experimental models of acute inflammation.Conclusions: Results from our study show that the compound under study has significant anti-inflammatory activity and further detailed works with this compound in different doses are needed

N-ACETYLCYSTEINE REVERSES LATE GESTATIONAL STRESS INDUCED MATERNAL OXIDATIVE DAMAGE

Objective: This study was intended to investigate the effect of early and late gestational stress, on the levels of antioxidants and antioxidant enzymes in maternal serum that reflects oxidative damage. We also aimed at evaluating the protective role of N-acetylcysteine (NAC) against this oxidative stress. This study was carried out with speculation in mind that maternal oxidative damage could be the cause for developmental defects in off spring.Methods: Pregnant rats were exposed to restrain stress thrice daily, either during the first half or during the second half of gestation. Other groups were treated with N-acetylcysteine throughout pregnancy, along with exposure to either early gestational stress or late gestational stress. Control group was kept undisturbed throughout pregnancy. Immediately after delivery, blood was drawn to estimate the serum antioxidant levels.Results: Pregnant rats exposed to stress during the late gestational period showed significant variation in the level of serum MDA, Glutathione Reductase, reduced glutathione, SOD and total antioxidant capacity although, administration of NAC brought about improvement in the antioxidant status.Conclusion: NAC is an effective antioxidant that can bring down the oxidative damage caused by late gestational stress in rats.Â