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Optimum kernel particle filter for asymmetric laplace noise in multivariate models
No full textIn this paper we present on-line Bayesian filtering methods for non-linear multivariate time series models corrupted by generalised asymmetric Laplace noise. We derive the optimum kernel for a particle filter applied to multivariate non-linear state-space models with scalar observations, where the observation noise is additive and asymmetric Laplacian. We show that sampling from this multivariate kernel is tractable using commonly available methods for use in particle filters, and that its associated likelihood can be evaluated. A particle filter is implemented for a test case using the developed kernel, and its performance is compared to that of a traditional bootstrap filter. The proposed methods show potential for application to systems with heavy-tailed skew noise
Turbulent flame shape switching at conditions relevant for gas turbines
No full textA numerical investigation is conducted to shed light on the reasons leading to different flame configurations in gas turbine (GT) combustion chambers of aeronautical interest. Large eddy simulations (LES) with a flamelet-based combustion closure are employed for this purpose to simulate the DLR-AT big optical single sector (BOSS) rig fitted with a Rolls-Royce developmental lean burn injector. The reacting flow field downstream this injector is sensitive to the intricate turbulent-combustion interaction and exhibits two different configurations: (i) a penetrating central jet leading to an M-shape lifted flame; or (ii) a diverging jet leading to a V-shaped flame. The LES results are validated using available BOSS rig measurements, and comparisons show the numerical approach used is consistent and works well. The turbulent-combustion interaction model terms and parameters are then varied systematically to assess the flame behavior. The influences observed are discussed from physical and modeling perspectives to develop physical understanding on the flame behavior in practical combustors for both scientific and design purposes
Investigating Remote Tactile Feedback for Mid-Air Text-Entry in Virtual Reality
No full textIn this paper, we investigate the utility of remote tactile feedback for freehand text-entry on a mid-air Qwerty keyboard in VR. To that end, we use insights from prior work to design a virtual keyboard along with different forms of tactile feedback, both spatial and non-spatial, for fingers and for wrists. We report on a multi-session text-entry study with 24 participants where we investigated four vibrotactile feedback conditions: on-fingers, on-wrist spatialized, on-wrist non-spatialized, and audio-visual only. We use micro-metrics analyses and participant interviews to analyze the mechanisms underpinning the observed performance and user experience. The results show comparable performance across feedback types. However, participants overwhelmingly prefer the tactile feedback conditions and rate on-fingers feedback as significantly lower in mental demand, frustration, and effort. Results also show that spatialization of vibrotactile feedback on the wrist as a way to provide finger-specific feedback is comparable in performance and preference to a single vibration location. The micro-metrics analyses suggest that users compensated for the lack of tactile feedback with higher visual and cognitive attention, which ensured similar performance but higher user effort
Modelling astrid-like Sodium-cooled fast reactor with Serpent-DYN3D code sequence
No full textThis study explores the feasibility of applying the Serpent-DYN3D sequence to the analysis of Sodium-cooled Fast Reactors (SFRs) with complex core geometries, such as the ASTRID-like design. The core is characterised by a highly heterogeneous configuration and was likely to challenge the accuracy of the Serpent-DYN3D sequence. It includes axially heterogeneous fuel assemblies, non-uniform fuel assembly heights and large sodium plena. Consequently, the influence of generation and correction methods of various homogenised, few-group cross-sections (XS) on the accuracy of the full-core nodal diffusion DYN3D calculations is presented. An attempt to compare the approximate time effort spent on models preparation against the accuracy of the result is made. Results are compared to reference full-core Serpent MC (Monte Carlo) solutions. Initially, XS data was generated in Serpent using traditional methods (2D single assemblies and 2D super-cells). Full core calculations and MC simulations offered a moderate agreement. Therefore, XS generation with 2D fuel-reflector models and 3D single assembly models was verified. Super-homogenisation (SPH) factors for XS correction were applied. In conclusion, the performed work suggests that Serpent-DYN3D sequence could be used for the analysis of highly heterogeneous SFR designs similar to the studied ASTRID-like, with an only small penalty on the accuracy of the core reactivity and radial power distribution prediction. However, the XS generation route would need to include the correction with SPH factors and generation of XS with various MC models, for different core regions. At a certain point, there are diminishing returns to using more complex XS generation methods, as the accuracy of full-core deterministic calculations improves only slightly, while the time effort required increases significantly
Core design study for a small modular boiling water reactor
No full textThe hybrid Small Modular Boiling Water Reactor (SMBWR) is a new conceptual design of BWR-type SMR. The main features of SMBWR include a natural circulation loop in its coolant recirculation system and external superheaters system integrated into the steam cycle. A full core analysis of SMBWR is performed with the nodal diffusion code PANTHER using homogenised constant libraries generated by WIMS. The study compared a number of core geometry configurations and fuel management schemes to suppress excess reactivity throughout fuel depletion. Three options for SMBWR core aspect ratio using the same power density are investigated with the aim to assess the effect on the neutronic and thermal-hydraulic performance of the SMBWR. It is found that the thin and tall core configuration (192 fuel assemblies and 3.60 m) showed the least favourable performance out of the three options as it has the largest core pressure drop and thus requires taller chimney to develop natural circulation
Weak Intermolecular CH···N Hydrogen Bonding: Determination of <sup>13</sup>CH-<sup>15</sup>N Hydrogen-Bond Mediated J Couplings by Solid-State NMR Spectroscopy and First-Principles Calculations
No full textWeak hydrogen bonds are increasingly hypothesized to play key roles in a wide range of chemistry from catalysis to gelation to polymer structure. Here, 15N/13C spin-echo magic-angle spinning (MAS) solid-state nuclear magnetic resonance (NMR) experiments are applied to "view" intermolecular CH···N hydrogen bonding in two selectively labeled organic compounds, 4-[15N] cyano-4′-[13C2] ethynylbiphenyl (1) and [15N313C6]-2,4,6-triethynyl-1,3,5-triazine (2). The synthesis of 2-15N313C6 is reported here for the first time via a multistep procedure, where the key element is the reaction of [15N3]-2,4,6-trichloro-1,3,5-triazine (5) with [13C2]-[(trimethylsilyl)ethynyl]zinc chloride (8) to afford its immediate precursor [15N313C6]-2,4,6-tris[(trimethylsilyl)ethynyl]-1,3,5-triazine (9). Experimentally determined hydrogen-bond-mediated 2hJCN couplings (4.7 ± 0.4 Hz (1) and 4.1 ± 0.3 Hz (2)) are compared with density functional theory (DFT) gauge-including projector augmented wave (GIPAW) calculations, whereby species-independent coupling values 2hKCN (29.0 × 1019 kg m-2 s-2 A-2 (1) and 27.9 × 1019 kg m-2 s-2 A-2 (2)) quantitatively demonstrate the J couplings for these "weak" CH···N hydrogen bonds to be of a similar magnitude to those for conventionally observed NH···O hydrogen-bonding interactions in uracil (2hKNO: 28.1 and 36.8 × 1019 kg m-2 s-2 A-2). Moreover, the GIPAW calculations show a clear correlation between increasing 2hJCN (and 3hJCN) coupling and reducing C(H)···N and H···N hydrogen-bonding distances, with the Fermi contact term accounting for at least 98% of the isotropic 2hJCN coupling
Author Correction: SciPy 1.0: fundamental algorithms for scientific computing in Python (Nature Methods, (2020), 17, 3, (261-272), 10.1038/s41592-019-0686-2)
No full textAn amendment to this paper has been published and can be accessed via a link at the top of the paper
Functional movements of the GABA type A receptor.
No full textWe have performed a parallel tempering crankshaft motion Monte Carlo simulation on a model of the GABA type A receptor with the aim of exploring a wide variety of local conformational space. We develop a novel method to analyse the protein movements in terms of a correlation tensor and use this to explore the gating process, that is, how agonist binding could cause ion channel opening. We find that simulated binding impulses to varying clusters of GABA binding site residues produce channel opening, and that equivalent impulses to single GABA sites produce partial opening
Automating Concrete Construction: Digital Design of Non-prismatic Reinforced Concrete Beams
No full textThe construction industry is responsible for nearly half of the UK’s carbon emissions, mainly due to the large amount of concrete used. Traditional formwork methods for concrete result in prismatic building elements with a constant cross-section, but the shear forces and bending moments that beams have to withstand are far from constant along their length. Up to 40% of the concrete in a typical beam could be removed. An iterative optimisation process has been implemented in a parametric modelling framework to generate and analyse optimal forms for non-prismatic beams that take into account the constraints imposed by the fabrication process, namely the use of fabric formwork. The aim of the resulting design tool is to facilitate the adoption of non-prismatic elements by the construction industry
Optimal encoding in stochastic latent-variable models
No full textIn this work we explore encoding strategies learned by statistical models of sensory coding in noisy spiking networks. Early stages of sensory communication in neural systems can be viewed as encoding channels in the information-theoretic sense. However, neural populations face constraints not commonly considered in communications theory. Using restricted Boltzmann machines as a model of sensory encoding, we find that networks with sufficient capacity learn to balance precision and noise-robustness in order to adaptively communicate stimuli with varying information content. Mirroring variability suppression observed in sensory systems, informative stimuli are encoded with high precision, at the cost of more variable responses to frequent, hence less informative stimuli. Curiously, we also find that statistical criticality in the neural population code emerges at model sizes where the input statistics are well captured. These phenomena have well-defined thermodynamic interpretations, and we discuss their connection to prevailing theories of coding and statistical criticality in neural populations