MRC Laboratory of Molecular Biology
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A combined oscillation cycle involving self-excited thermo-acoustic and hydrodynamic instability mechanisms
No full textThe paper examines the combined effects of several interacting thermo-acoustic and hydrodynamic instability mechanisms that are known to influence self-excited combustion instabilities often encountered in the late design stages of modern low-emission gas turbine combustors. A compressible large eddy simulation approach is presented, comprising the flame burning regime independent, modeled probability density function evolution equation/stochastic fields solution method. The approach is subsequently applied to the PRECCINSTA (PREDiction and Control of Combustion INSTAbilities) model combustor and successfully captures a fully self-excited limit-cycle oscillation without external forcing. The predicted frequency and amplitude of the dominant thermo-acoustic mode and its first harmonic are shown to be in excellent agreement with available experimental data. Analysis of the phase-resolved and phase- averaged fields leads to a detailed description of the superimposed mass flow rate and equivalence ratio fluctuations underlying the governing feedback loop. The prevailing thermo-acoustic cycle features regular flame liftoff and flashback events in combination with a flame angle oscillation, as well as multiple hydrodynamic phenomena, i.e., toroidal vortex shedding and a precessing vortex core. The periodic excitation and suppression of these hydrodynamic phenomena is confirmed via spectral proper orthogonal decomposition and found to be controlled by an oscillation of the instantaneous swirl number. Their local impact on the heat release rate, which is predominantly modulated by flame-vortex roll- up and enhanced mixing of fuel and oxidizer, is further described and investigated. Finally, the temporal relationship between the flame “surface area,” flame-averaged mixture fraction, and global heat release rate is shown to be directly correlated
A Mems Vibrating Beam Accelerometer for High Resolution Seismometry and Gravimetry
No full textA differential MEMS vibrating beam accelerometer (VBA) demonstrating excellent stability for seismology and gravimetry applications is presented. The accelerometer response demonstrates excellent linearity over an acceleration range of ±1 g (1 g = 9.8 m s) with a scale factor of 9825 Hz/g. An approximately flat output Allan deviation with an average value of 15 ng is recorded over integration times τ = 1 s - 1000 s with a best-case bias instability of < 10 ng and a noise floor of 10 ng/√H. These results, taken collectively, set new benchmarks for vibrating beam MEMS accelerometers
The significance of source-receiver interaction in the response of piled foundations to ground-borne vibration from underground railways
No full textThe numerical prediction of vibration in buildings due to underground railways involves modelling many physical phenomena. Not least of these is the dynamic soil-structure interaction that exists between the various elements of the system. The majority of existing models assume that the interaction between the railway tunnel and the building's foundation is negligible, with the two sub-systems behaving as though they are uncoupled. This paper presents some initial results from a three-dimensional model that accounts for the through-soil coupling between a tunnel and a piled foundation. The model is based on the pipe-in-pipe model, of a circular, longitudinally invariant tunnel excited by wheel-rail roughness, coupled to a boundary-element model of the foundation using an iterative wave-scattering approach. Initial test cases, involving single piles and pile-groups, highlight new details of tunnel-pile and pile-pile interaction, as well as predicting the effect of piles on ground vibration levels
Applications in opto-electronics: general discussion.
No full textApplications in opto-electronics: general discussion
Learning to stop: A unifying principle for legged locomotion in varying environments
No full textEvolutionary studies have unequivocally proven the transition of living organisms from water to land. Consequently, it can be deduced that locomotion strategies must have evolved from one environment to the other. However, the mechanism by which this transition happened and its implications on bio-mechanical studies and robotics research have not been explored in detail. This paper presents a unifying control strategy for locomotion in varying environments based on the principle of 'learning to stop'. Using a common reinforcement learning framework, deep deterministic policy gradient, we show that our proposed learning strategy facilitates a fast and safe methodology for transferring learned controllers from the facile water environment to the harsh land environment. Our results not only propose a plausible mechanism for safe and quick transition of locomotion strategies from a water to land environment but also provide a novel alternative for safer and faster training of robots
Spatial distributive effects of public green space and COVID-19 infection in London
No full textWhile public green spaces (PGS) are opined to be central in the pandemic recovery, higher accessibility to PGS also mean a higher risk of infection spread from the raised possibility of people encountering each other. This study explores the distributive effects of accessibility of PGS on the COVID-19 cases distribution using a geo-spatially varying network-based risk model at the borough level in London. The coupled effect of social deprivation with accessibility of the PGS was used as an adjustment factor to identify vulnerability. Results indicate that highly connected green spaces with high choice measure were associated with high risk of infection transmission. Socially deprived areas demonstrated higher possibility of infection spread even with moderate connectivity of the PGS. The study demonstrated that only applying a uniform social distancing measure without characterising the infrastructure and social conditions may lead to higher infection transmission
Estimating the marginal cost of reducing power outage durations in China: A parametric distance function approach
No full textThe increasing penetration of intermittent renewables and the accelerated climate change are challenging the power system operation in China, and understanding the cost of reducing power outage durations is essential in supporting the equipment maintenance, infrastructure investments and regulation policies. Therefore, this study first uses production theory combined with a parametric distance function approach to estimate the marginal costs (MCs) of reducing power outage durations by 1 h. Then, we establish a fixed-effects panel data model to investigate the impacts of different environmental factors on the estimated MCs. Finally, the estimated MCs are applied to the evaluations and designs of interruption compensation prices in the demand response mechanism. The significant findings are that: (1) The national MC shows an increasing trend during the period from 2002 to 2017 in China, ranging from 1.27 billion yuan/hour to 11.63 billion yuan/hour. (2) The MCs vary substantially among different provinces, and provinces with better reliability levels will have higher MCs. (3) The current compensations for power outages are only about 6% to 61% of the estimated MCs, indicating that grid companies would like to pay for the compensations rather than to enhance the system reliability from the supply side
Numerical study of acoustophoretic manipulation of particles in microfluidic channels
No full textThe microfluidic technology based on surface acoustic waves (SAW) has been developing rapidly, as it can precisely manipulate fluid flow and particle motion at microscales. We hereby present a numerical study of the transient motion of suspended particles in a microchannel. In conventional studies, only the microchannel’s bottom surface generates SAW and only the final positions of the particles are analyzed. In our study, the microchannel is sandwiched by two identical SAW transducers at both the bottom and top surfaces while the channel’s sidewalls are made of poly-dimethylsiloxane (PDMS). Based on the perturbation theory, the suspended particles are subject to two types of forces, namely the Acoustic Radiation Force (ARF) and the Stokes Drag Force (SDF), which correspond to the first-order acoustic field and the second-order streaming field, respectively. We use the Finite Element Method (FEM) to compute the fluid responses and particle trajectories. Our numerical model is shown to be accurate by verifying against previous experimental and numerical results. We have determined the threshold particle size that divides the SDF-dominated regime and the ARF-dominated regime. By examining the time scale of the particle movement, we provide guidelines on the device design and operation
On the design of the world's smallest flow sensor package
No full textIn this letter, a miniature flow sensing system has been designed, simulated, manufactured, and tested. The system is comprised of a thermal flow sensing die, a package body, a lid, and leveling epoxy. The lid design is crucial to the system performance, and a reference design was shown to create vortices within the flow channel, resulting in nonlinear and nonrepeatable sensor response. Two novel lid designs were investigated that showed increased sensitivity and repeatability, while minimizing the effect of vortices disrupting the sensor response. These structures were named 'vortex guides.' The first design provided a double increase in the signal sensitivity, while the second design isolated the vortices away from the sensors functional area, providing predictable flow response over a wider flow range. This enables high-sensitivity, large-range, low-cost miniature flow sensing for mass-market production