MRC Laboratory of Molecular Biology
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Quantum annealing optimization of a heuristic surrogate model for PWR fuel loading
No full textAn efficient fuel arrangement must be generated by PWR operators every 6-18 months. This complex problem has been extensively researched with two broad approaches, heuristic and stochastic methods, becoming accepted. This initial study qualitatively introduces the concept of encoding full-core PWR fuel loading patterns in a form suitable for quantum annealing. The concepts of adiabatic quantum computers and quantum annealing are introduced, and a surrogate model encoding of a set of heuristics for loading pattern design produced in a form suitable for use in present-day quantum annealers. The simulated results show significant similarity to benchmark loading patterns
Zero power criticality benchmark evaluation of the MSRE in WIMS
No full textThis paper discusses work done to benchmark the deterministic code WIMS [1] against the Monte Carlo code Serpent [2] and experiment. Comparison is made against the Molten Salt Reactor Experiment at Oak Ridge National Laboratory as well as a Serpent model produced at the University of California, Berkeley. Producing a model for an MSR is possible thanks to the development of the next version of WIMS, WIMS11. The structure of the WIMS model built is discussed, and the final predicted criticality value for the MSR is given. This compares favourably with the Serpent model; however, both codes predict values considerably different to those expected. Potential reasons for this are suggested. However, it is concluded that WIMS has successfully been benchmarked against the current state of the art. This provides confirmation that this is a valid approach for molten salt reactor research analysis
Microstructurally-guided explicit continuum models for isotropic magnetorheological elastomers with iron particles
No full textThis work provides a family of explicit phenomenological models both in the F−H and F−B variable space. These models are derived directly from an analytical implicit homogenization model for isotropic magnetorheological elastomers (MREs), which, in turn, is assessed via full-field numerical simulations. The proposed phenomenological models are constructed so that they recover the same purely mechanical, initial and saturation magnetization and initial magnetostriction response of the analytical homogenization model for all sets of material parameters, such as the particle volume fraction and the material properties of the constituents (e.g., the matrix shear modulus, the magnetic susceptibility and magnetization saturation of the particles). The functional form of the proposed phenomenological models is based on simple energy functions with small number of calibration parameters thus allowing for the description of magnetoelastic solids more generally such as anisotropic (with particle-chains) ones, polymers comprising ferrofluid particles or particle clusters. This, in turn, makes them suitable to probe a large set of experimental or numerical results. The models of the present study show that in isotropic MREs, the entire magnetization response is insensitive to the shear modulus of the matrix material even when the latter ranges between 0.003-0.3MPa, while the magnetostriction response is extremely sensitive to the mechanical properties of the matrix material
Allocation strategies in a dockless bike sharing system: a community structure-based approach
No full textThis study develops a methodology to determine the optimal allocation position to deploy the bikes in a competitive dockless bike sharing market. The community structure approach in complex network theory is utilized to offer the bike allocation strategies to the market leader in two specific market regimes, with a potential competitor, and without a potential competitor. Two different heuristics are proposed to handle the two scenarios respectively due to different design objectives, wherein the first one aims to attract maximum users and the other one aims to use minimum resources to cover maximum service area. Two hypothetic networks are adopted to illustrate the difference in design under these two regimes. Two numerical studies–a simplified Sioux Falls network and a real network in Singapore–are used to demonstrate the algorithm performance and show the applicability of the model for the scenario that no potential competitor exists
The effect of reaction on compressor performance
No full textReaction is the fundamental parameter by which the asymmetry of the velocity triangle of a stage is set. Little is understood about the effect that reaction has on either the efficiency or the operating range of a compressor. A particular difficulty in understanding the effect of reaction is that the rotor and stator have a natural asymmetry caused by the centrifugal effects in the rotor boundary layer, being much larger than those in the stator boundary layer. In the thesis a novel approach has been taken: McKenzie’s ‘linear repeating stage’ concept is used to remove the centrifugal force effects. The centrifugal effects are then reintroduced as a body force. This allows the velocity triangle effect and centrifugal effect to be decoupled. The ability to accurately decouple these two asymmetries has led to a number of major findings. The thesis shows the surprising result that, depending on how the solidity of the stage is set, 50% reaction can either result in the maximum, or the minimum, profile loss. When the solidity is set by the shape factor of the suction-surface boundary layer at the blade trailing-edge, and conventional levels of design work coefficient (Ψ=0.44) and flow coefficient (Φ=0.60) are set, the profile loss becomes independent of reaction. When the centrifugal effects are removed, 50% reaction is shown to minimise endwall loss, maximise stage efficiency and maximise operating range. When the centrifugal effects are reintroduced, the compressor with the maximum design efficiency is found to rise in reaction by 5% (from 50% reaction to 55% reaction) and the compressor with the maximum operating range is found to rise in reaction by 15% (from 50% reaction to 65% reaction). In a real multistage compressor there is often a requirement for axial flow at the inlet and exit the compressor. This naturally results in high reaction. In the central stages of the compressor, it is possible to maximise the stage efficiency by reducing the reaction to 55%. This is done by raising the interstage swirl through the first stage and dropping it through the last stage. It is shown that if a 10 stage compressor, which originally had a constant stage reaction of 75%, was rebladed so that the central 8 stages had 55% reaction, then the overall design efficiency would rise by 0.58%
Environmental graphene conductivity sensing using terahertz time-domain reflection spectroscopy
No full textWe demonstrate how reflection terahertz time-domain spectroscopy (THz-TDS) can be used to measure conductivity of large area graphene films through silicon substrate. This through-substrate approach in turn allows an unhindered access to the graphene top surface and thus, opens up pathways to perform in situ and in-operando THz-TDS using environmental cells
On-chip Superconducting THz Metamaterial Bandpass Filter
No full textWe demonstrate a THz bandpass filter (BPF) made from high-temperature (Tc) superconducting BiSrCaCuO+δ(BSCCO). The filter offers a thermally tunable dual passband with a flat response in the first passband, a bandwidth of \sim 0.33 THz, and a sharp resonance band-edge transition to the rejection bands of \sim 316 and 96 dB/THz (for left and right edge, respectively), at temperature T=10 K far below T_{\mathrm{c}}. As temperature T increases, the sharpness of the band-edge transition to the rejection bands decreases. The proposed BPF can be useful in the realization of a superconducting based THz integrated circuitry
Array programming with NumPy
No full textArray programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis
Optofluidic hollow-core fibres as raman sensors for li-ion battery chemistry
No full textWe demonstrate a fibre-optic sensing method capable of monitoring chemical changes within Li:ion cells under real working conditions. Our technique is based on optofluidic single-ring hollow-core fibres, which uniquely allow light to be guided at the centre of a microfluidic channel. We integrate the fibres into working Li:ion cells, use them to take sub-microlitre samples of the electrolyte liquid, and analyse these by background-free Raman spectroscopy to identify early signs of battery degradation. Our approach complements existing battery monitoring systems and will enable us to identify degradation mechanisms that currently limit the lifetime and capacity of state-of-the-art energy storage systems
