The effect of moisture conditioning on the mechanical and physical properties of long glass fibre reinforced nylon 66 materials

The effect of moisture conditioning on the mechanical and physical properties of ICI's 'Verton' range of long glass fibre reinforced Nylon 66 materials have been investigated using injection moulded test specimens. Natural and black grades, at glass loadings of 35%, 50% and 60% by weight have been examined together with a natural un-reinforcd Nylon 66 grade.The tensile strength of the matrix polymer reduced from 80 MPa at dry - "as moulded" to 30 MPa when fully moisture saturated. Dry - "as moulded" tensile strength values for the glass reinforced grades ranged between 198 MPa and 255 MPa for the natural grades and between 183 MPa and 251 MPa for the black. With moisture conditioning for 1000 hours (42 days) at 60ºC these values were reduced from 92 MPa to 119 MPa for the natural grades and 87 MPa to 120 MPa for the black. The dry - "as moulded" flexural strength values ranged between 280 MPa to 365 MPa and 249 MPa to 369 MPa for the natural and black materials, respectively. As with tensile strength these values were also reduced with moisture uptake. For the same moisture conditions the values of strength measured in flexure were reduced more than in tension. For natural materials the values ranged between 80 MPa to 102 MPa and from 70 MPa to 92 MPa for the black. The dry impact strength of notched samples ranging from 22 kJ/m^2 to 42 kJ/m^2 was found to increase to approximately 63 kJ/m^2 for the natural glass/Nylon 66 materials when fully moisture conditioned. The impact strength of black materials ranged from 15 kJ/m^2 to 37 kJ/m^2 dry and increased to approximately 61 kJ/m^2 with moisture conditioning for 1000 hours at 60ºC. All changes in mechanical and physical properties were interpreted in terms of the effects of Fickian moisture uptake on the likely properties of the 'skin' and 'core' regions of injection moulded samples

Excited state absorption in Mn2+ doped phosphate glass.

The possibility of obtaining laser action from Mn2+ doped glass has been investigated. The excited state absorption at the expected laser wavelength was measured and explains the unsuccessful attempts to obtain laser action

Vapor Equilibrium Data for the Binary Mixtures of Dimethyl Carbonate and Ethyl Methyl Carbonate in Compressed Carbon Dioxide

Phase equilibrium data for the binary systems of carbon dioxide + dimethyl carbonate and carbon dioxide + ethyl methyl carbonate were obtained. All systems were measured for isotherms ranging from 298.2 K to 328.2 K with pressure ranging between 0.13 MPa and 10.6 MPa. A static equilibrium technique was established with samples quantified using an offline method. The results were modeled using the Peng–Robinson equation of state with van der Waals one-fluid mixing rules

A Case History of Tehri Tunnels

Tehri Dam Project, a multipurpose river valley project, is being constructed in Garhwal, Himalaya. The project consists of a 260 m high earth and rock fill dam with a clay core, four diversion tunnels each of 11 m finish diameter, four head race tunnels each of 8.5 m finish diameter and two underground powerhouses cavities each measuring 180 m long, 49.5 m high and 21.5 m wide. The project is located near the district headquarters of Tehri in the state of Uttar Pradesh. The rock masses in the project area are fragile, tectonically active and geologically disturbed. The terrain is rugged and inaccessible and therefore precludes thorough geotechnical investigations for the design of the cavern. The diversion and the head race tunnels were therefore used to conduct geotechnical investigations with the purpose of collecting geotechnical data for the design of two caverns. Goodman Jack tests were used to estimate the modulus of deformation of the rock masses. Load cells and tape extensometers were used to monitor the support pressure and the tunnel closures. The modulus of deformation varied from 0.18 to 0.32 kg/cm.sq. X 105. Tunnel closures were about 0.3% of the tunnel size. The support pressure stabilized within three months of excavation and the measured support pressures varied between 0.16 and 1.14 kg/cm.sq. This geotechnical data indicate that the rock masses behaviour was elastic in nature and the cavern could be designed without much difficulties

Real-Time Implementation of Intelligent Actuator Control with a Transducer Health Monitoring Capability

This paper presents a concept of feedback control for smart actuators that are compatible with smart sensors, communication protocols, and a hierarchical Integrated System Health Management (ISHM) architecture developed by NASA s Stennis Space Center. Smart sensors and actuators typically provide functionalities such as automatic configuration, system condition awareness and self-diagnosis. Spacecraft and rocket test facilities are in the early stages of adopting these concepts. The paper presents a concept combining the IEEE 1451-based ISHM architecture with a transducer health monitoring capability to enhance the control process. A control system testbed for intelligent actuator control, with on-board ISHM capabilities, has been developed and implemented. Overviews of the IEEE 1451 standard, the smart actuator architecture, and control based on this architecture are presented

Cavern Wall Support Requirements in a Hydro-Electric Project

Construction of a 23m wide, 57m high, and 210m long underground power house cavern is in progress as a part of the multi-purpose Sardar Sarovar Project in India. The rock mass around the cavern is basalt which is intruded by a number of dolerite dykes. In view of the high side walls of the cavern, and the presence of a 1 to 2m thick shear zone running across the cavern width, a comprehensive approach was worked out for estimation of the wall support requirements. The approach included estimation of the roof support requirements using the four available approaches, and comparison of these requirements with the roof support system actually provided, and established as safe and adequate by the instrumentation data of six years. A favourable comparison established the reliability of the approaches used, and the most reliable of these approaches, i.e., the Barton\u27s approach was then used with confidence for estimation of the wall support requirements

Correlation-Aware Neural Networks for DDoS Attack Detection In IoT Systems

We present a comprehensive study on applying machine learning to detect distributed Denial of service (DDoS) attacks using large-scale Internet of Things (IoT) systems. While prior works and existing DDoS attacks have largely focused on individual nodes transmitting packets at a high volume, we investigate more sophisticated futuristic attacks that use large numbers of IoT devices and camouflage their attack by having each node transmit at a volume typical of benign traffic. We introduce new correlation-aware architectures that take into account the correlation of traffic across IoT nodes, and we also compare the effectiveness of centralized and distributed detection models. We extensively analyze the proposed architectures by evaluating five different neural network models trained on a dataset derived from a 4060-node real-world IoT system. We observe that long short-term memory (LSTM) and a transformer-based model, in conjunction with the architectures that use correlation information of the IoT nodes, provide higher performance (in terms of F1 score and binary accuracy) than the other models and architectures, especially when the attacker camouflages itself by following benign traffic distribution on each transmitting node. For instance, by using the LSTM model, the distributed correlation-aware architecture gives 81% F1 score for the attacker that camouflages their attack with benign traffic as compared to 35% for the architecture that does not use correlation information. We also investigate the performance of heuristics for selecting a subset of nodes to share their data for correlation-aware architectures to meet resource constraints.Comment: 16 pages, 17 figures, journa