Report of Acoustic Test on PSLV IS.1/2L Structure

The results of acoustic conducted on PSLV IS.1/2L at Acoustic Test Facility are briefly given. It contains test set up, Instrumentation details and tables of spectral response

Vortex-induced-vibration of jack-ups with cylindrical legs in multiple modes

A simple mathematical model was developed based on the single-degree-of-freedom analogy and principle of conservation of energy evaluating various modes of Vortex-Induced-Vibration (VIV) of a jack-up with cylindrical legs in steady flow. Mass ratio, damping ratio and mode factor were found to be the important parameters controlling the inline and cross flow VIV and radius of gyration for the yaw VIV. Criteria for the initiation of the three VIV modes were developed for the cases of a single 2D cylinder, four rigidly coupled 2D cylinders in rectangular configuration and a jack-up experiencing uniform flow. The model tests demonstrated that the jack-up with cylindrical legs experienced cross flow and yaw VIV in uniform flows, with amplitude ratios greater than 0.1D. Further, there was considerable overlap of the lock-in ranges and coupling at higher current speeds of the aforementioned modes making the jack-up practically redundant throughout the operating currents. The analysis of the mean inline responses of the model revealed drag amplification due to the VIV. The test results validated the developed VIV model, VIV criteria and the importance of mass ratio in suppressing VIV. The mathematical method will enable practising engineers to consider the effect of VIV in jack-up designs

HYPOPLASTIC EFFECT OF PROSTOWIN VATI AND VASTIKARMA IN THE MANAGEMENT OF BENIGN PROSTATIC HYPERPLASIA

60 Patients were selected for the clinical study in 3 groups and 20 patients were in each group. The quality of life improved with the Prostowin Vati and Ksheerabala oil Vasti with the reduction in symptom score (IPSS and DPSS), Residual urine, Micturition time and improvement in Average flow rate. Old persons refuse operative treatment for their BPH symptoms and seeking a safe and effective treatment for easy life. In this situation the medicinal treatment may play an important role.Key words- Straining, Intermittency, International prostate symptom scoring system (IPSS), Danish Prostate Symptom scoring system (DPSS), Residua

Computational study of shock wave propagation and reflection in a micro shock tube

Paper presented at the 9th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Malta, 16-18 July, 2012.Micro shock tubes are miniature devices used for a variety of application in small scale devices likes MEMS equipments. The inherent low flow dimensions combined with low operating pressure makes these devices to behave differently compared to macro shock tubes. In the present study a CFD method was employed to study the shock propagation and reflection inside a micro shock tube. The shock propagation under rarefied conditions due to the low pressure prevailing in the system was studied, in detail. Navier-Stokes equation together with Maxwell’s slip equations were used to simulate the rarefied flow. In these devices, boundary layer effects become a significant parameter in controlling the shock movement and strength owing to its small flow diameter. This paper focuses on giving detail explanation for the disparities in flow physics and its effect on shock movement for micro shock tube under different low pressure and diameter conditions. The results show a greater loss in the shock strength as the diameter or pressure decreases and hence shock waves get attenuated.dc201

Non-stationary stochastic inventory lot-sizing with emission and service level constraints in a carbon cap-and-trade system

Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product’s demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation.The analysis of results helps supply chain managers to take right decision in different demand and service level situations

Vortex-induced-vibration of jack-ups with cylindrical legs in regular waves

A simple mathematical model is developed based on the single-degree-of-freedom analogy and principle of conservation of energy evaluating various modes of Vortex-Induced-Vibration (VIV) of a jack-up with cylindrical legs in regular waves. Similar to uniform current, mass ratio, damping ratio and mode factor are found to be the important parameters controlling the cross-flow VIV and radius of gyration also for the yaw VIV. Criteria for the initiation of the mentioned VIV modes are developed for the cases of a single 2D cylinder experiencing planar oscillatory flow, four rigidly coupled 2D cylinders in rectangular configuration experiencing planar oscillatory flow and jack-up experiencing regular waves. The newly developed VIV model is validated by a set of experiments conducted in a wind, wave and current flume. The importance of mass damping parameter is further demonstrated in suppressing VIV in regular waves. The mathematical method will equip engineers to consider the effect of VIV due to regular waves in jack-up designs

ANN-based decision making in station keeping for geotechnical drilling vessel

Offshore vessels (OVs) often require precise station-keeping and some vessels, for exam-ple, vessels involved in geotechnical drilling, generally use Spread Mooring (SM) or Dynamic Positioning (DP) systems. Most of these vessels are equipped with both systems to cover all ranges of water depths. However, determining which system to use for a particular operational scenario de-pends on many factors and requires significant balancing in terms of cost-benefit. Therefore, this research aims to develop a platform that will determine the cost factors for both the SM and DP station-keeping systems. Operational information and cost data are collected for several field oper-ations, and Artificial Neural Networks (ANN) are trained using those data samples. After that, the trained ANN is used to predict the components of cost for any given environmental situation, field-work duration and water depth. Later, the total cost is investigated against water depth for both DP and SM systems to determine the most cost-effective option. The results are validated using two operational scenarios for a specific geotechnical vessel. This decision-making algorithm can be further developed by adding up more operational data for various vessels and can be applied in the development of sustainable decision-making business models for OVs operators

Experimental research on kinematics of breaking waves

One important kinematic properties of breaking waves is the wave celerity. Constant wave celerity has been used for the wave breaking criterion by many researchers. However, this approach does not consider the variation of wave celerity at different phases before breaking. Hence, this article examines the aspects of the wave breaking criterion and dynamics of wave celerity before wave breaking. Breaking waves were generated using the JONSWAP focused spectrum and a semi-empirical formula for the wave celerity estimation was established

Real-Time Prediction of Reliability of Dynamic Positioning Sub-Systems for Computation of Dynamic Positioning Reliability Index (DP-RI) Using Long Short Term Memory (LSTM)

In this study, a framework using Long Short Term Memory (LSTM) for prediction of reliability of Dynamic Positioning (DP) sub-systems for computation of Dynamic Positioning Reliability Index (DP-RI) has been proposed. The DP System is complex with significant levels of integration between many sub-systems such as the Reference System, DP Control System, Thruster / Propulsion System, Power System, Electrical System and the Environment System to perform diverse control functions. The proposed framework includes a mathematical computation approach to compute reliability of DP sub-systems and a data driven approach to predict the reliability at a sub-system level for evaluation of model performance and accuracy. The framework results demonstrate excellent performance under a wide range of data availability and guaranteed lower computational burden for real-time non-linear optimization. There are three main components of the proposed architecture for the mathematical formulation of the DP sub-systems based on individual sensor arrangements within the sub-system, computation of reliability of sub-systems and optimized LSTM deep learning algorithm for prediction of its reliability. Firstly, the mathematical formulation for the reliability of sub-systems is determined based on the series/parallel arrangement of the sensors of each individual equipment item within the sub-systems. Secondly, the computation of the reliability of sub-systems is achieved through an integrated approach during complex operation of the vessel. Thirdly, the novel optimized LSTM network is constructed to predict the reliability of the subsystems while minimizing integral errors in the algorithm. In this paper, numerical simulations are set-up using a state-of-the-art advisory decision-making tool with mock-up and real-world data to give insights into the model performance and validate it against the existing risk assessment methodologies. Furthermore, we have analyzed the efficiency and stability of the proposed model against various levels of data availability. In conclusion the prediction accuracy of the proposed model is scalable and higher when compared with other model results

Non-stationary stochastic inventory lot-sizing with emission and service level constraints in a carbon cap-and-trade system

Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product's demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation. The analysis of results helps supply chain managers to take right decision in different demand and service level situations