赵一帆

Prospects for seasonal forecasting of iceberg distributions in the North Atlantic

An efficient approach to ocean–iceberg modelling provides a means for assessing prospects for seasonal forecasting of iceberg distributions in the northwest Atlantic, where icebergs present a hazard to mariners each spring. The stand-alone surface (SAS) module that is part of the Nucleus for European Modelling of the Ocean (NEMO) is coupled with the NEMO iceberg module (ICB) in a “SAS-ICB” configuration with horizontal resolution of 0.25°. Iceberg conditions are investigated for three recent years, 2013–2015, characterized by widely varying iceberg distributions. The relative simplicity of SAS-ICB facilitates efficient investigation of sensitivity to iceberg fluxes and prevailing environmental conditions. SAS-ICB is provided with daily surface ocean analysis fields from the global Forecasting Ocean Assimilation Model (FOAM) of the Met Office. Surface currents, temperatures and height together determine iceberg advection and melting rates. Iceberg drift is further governed by surface winds, which are updated every 3 h. The flux of icebergs from the Greenland ice sheet is determined from engineering control theory and specified as an upstream flux in the vicinity of Davis Strait for January or February. Simulated iceberg distributions are evaluated alongside observations reported and archived by the International Ice Patrol. The best agreement with observations is obtained when variability in both upstream iceberg flux and oceanographic/atmospheric conditions is taken into account. Including interactive icebergs in an ocean–atmosphere model with sufficient seasonal forecast skill, and provided with accurate winter iceberg fluxes, it is concluded that seasonal forecasts of spring/summer iceberg conditions for the northwest Atlantic are now a realistic prospect.

Mechanical performance of composite bonded joints in the presence of localised process-induced zero-thickness defects

Processing parameters and environmental conditions can introduce variation into the performance of adhesively bonded joints. The effect of such variation on the mechanical performance of the joints is not well understood. Moreover, there is no validated non-destructive inspection (NDI) available to ensure bond integrity post-process and in-service so as to guarantee initial and continued airworthiness in aerospace sector. This research studies polymer bond defects produced in the laboratory scale single-lap composite-to-composite joints that may represent the process-induced defects occurring in actual processing scenarios such as composite joining and repair in composite aircrafts. The effect of such defects on the degradation of a joint’s mechanical performance is then investigated via quasi-static testing in conjunction with NDI ultrasonic C-scanning and pulsed thermography. This research is divided into three main sections: 1- manufacturing carbon fibre-reinforced composite joints containing representative nearly zero-thickness bond defects, 2- mechanical testing of the composite joints, and 3- assessment of the NDI capability for detection of the bond defects in such joints.

Identifying challenges in quantifying uncertainty: Case study in infrared thermography

Driver workload estimation using a novel hybrid method of error reduction ratio causality and support vector machine

Analysis of autopilot disengagements occurring during autonomous vehicle testing

In present-day highly-automated vehicles, there are occasions when the driving system disengages and the human driver is required to take-over.  This is of great importance to a vehicle’s safety and ride comfort.  In the U.S state of California, the Autonomous Vehicle Testing Regulations requires every manufacturer testing autonomous vehicles on public roads to submit an annual report summarizing the disengagements of the technology experienced during testing.  On 1 January 2016, seven manufacturers submitted their first disengagement reports: Bosch, Delphi, Google, Nissan, Mercedes-Benz, Volkswagen, and Tesla Motors.  This work analyses the data from these disengagement reports with the aim of gaining a better understanding of the situations in which a driver is required to take over, as this is potentially useful in improving SAE Level 2 and Level 3 automation technologies.   Disengagement events from testing are classified into different groups based on attributes such and the causes of disengagement are investigated and compared in detail. The mechanisms and time taken for of take-over transition occurred in disengagements are studied. Finally, recommendations for OEMs, manufacturers, and government organizations are also discussed.

A Wavelet‐Based Correlation Analysis Framework to Study Cerebromuscular Activity in Essential Tremor

A Pilot Study Investigating a Novel Non-Linear Measure of Eyes Open versus Eyes Closed EEG Synchronization in People with Alzheimer’s Disease and Healthy Controls

A Novel Control Framework of Haptic Take-Over System for Automated Vehicles

A confidence map based damage assessment approach using pulsed thermographic inspection

In the context of non-destructive testing, quantification of uncertainty caused by various factors such as inspection technique, testing environment and the operator is important and challenge. This paper introduces a concept of contour-based confidence map and an application framework for pulsed thermography that offers enhanced flexibility and reliability of inspection. This approach has been successfully applied to detect three flat-bottom holes of diameter 32, 16 and 8 mm drilled onto a 5 mm thick aluminium plate with a high accuracy of damage detection (R > 0.97). Its suitability and effectiveness in assessing impact damage occurring in composites have also been demonstrated.

An Orientation Sensor-Based Head Tracking System for Driver Behaviour Monitoring