A 7.0\% Determination of the Baryon Fraction in the Intergalactic Medium from Localized Fast Radio Bursts

The dispersion measure (DM)--redshift relation of fast radio bursts (FRBs) has been proposed as a potential new tool for probing intergalactic medium (IGM) and for studying cosmology. However, the poor knowledge of the baryon fraction in the IGM ($f_{\mathrm{IGM}}$) and its degeneracy with cosmological parameters impose restrictions on the cosmological applications of FRBs. Furthermore, DMs contributed by the IGM ($\mathrm{DM_{IGM}}$) and host galaxy ($\mathrm{DM_{host}}$), the important cosmological quantities, cannot be exactly extracted from observations, which would bring uncontrolled systematic uncertainties in FRB cosmology. In this work, we use seventeen localized FRBs to constrain $f_{\mathrm{IGM}}$ and possibly its redshift evolution. Other cosmological probes such as Type Ia supernovae, baryon acoustic oscillations, and cosmic microwave background radiation are combined to break parameter degeneracy. Taking into account the probability distributions of $\mathrm{DM_{IGM}}$ and $\mathrm{DM_{host}}$ derived from the the IllustrisTNG simulation, we obtain a robust measurement of $f_{\mathrm{IGM}}=0.857\pm0.060$, representing a precision of 7.0\%. We find that there is no strong evidence for the redshift dependence of $f_{\mathrm{IGM}}$ at the current observational data level. The rapid progress in localizing FRBs will significantly improve the constraints on $f_{\mathrm{IGM}}$.Comment: 9 pages, 3 figures, 2 table

The Hubble Tension Survey: A Statistical Analysis of the 2012-2022 Measurements

In order to investigate the potential Hubble tension, we compile a catalogue of 216 measurements of the Hubble--Lema\^itre constant $H_0$ between 2012 and 2022, which includes 109 model-independent measurements and 107 $\Lambda$CDM model-based measurements. Statistical analyses of these measurements show that the deviations of the results with respect to the average $H_0$ are far larger than expected from their error bars if they follow a Gaussian distribution. We find that $x\sigma$ deviation is indeed equivalent in a Gaussian distribution to $x_{\rm eq}\sigma$ deviation in the frequency of values, where $x_{\rm eq}=0.72x^{0.88}$. Hence, a tension of 5$\sigma$, estimated between the Cepheid-calibrated type Ia supernovae and cosmic microwave background (CMB) data, is indeed a 3$\sigma$ tension in equivalent terms of a Gaussian distribution of frequencies. However, this recalibration should be independent of the data whose tension we want to test. If we adopt the previous analysis of data of 1976-2019, the equivalent tension is reduced to $2.25\sigma$. Covariance terms due to correlations of measurements do not significantly change the results. Nonetheless, the separation of the data into two blocks with $H_0<71$ and $H_0\ge 71$ km s$^{-1}$ Mpc$^{-1}$ finds compatibility with a Gaussian distribution for each of them without removing any outlier. These statistical results indicate that the underestimation of error bars for $H_0$ remains prevalent over the past decade, dominated by systematic errors in the methodologies of CMB and local distance ladder analyses.Comment: Accepted to be published in MNRA

Investigating Spatial Interdependence in E-Bike Choice Using Spatially Autoregressive Model

Increased attention has been given to promoting e-bike usage in recent years. However, the research gap still exists in understanding the effects of spatial interdependence on e-bike choice. This study investigated how spatial interdependence affected the e-bike choice. The Moran’s I statistic test showed that spatial interdependence exists in e-bike choice at aggregated level. Bayesian spatial autoregressive logistic analyses were then used to investigate the spatial interdependence at individual level. Separate models were developed for commuting and non-commuting trips. The factors affecting e-bike choice are different between commuting and non-commuting trips. Spatial interdependence exists at both origin and destination sides of commuting and non-commuting trips. Travellers are more likely to choose e-bikes if their neighbours at the trip origin and destination also travel by e-bikes. And the magnitude of this spatial interdependence is different across various traffic analysis zones. The results suggest that, without considering spatial interdependence, the traditional methods may have biased estimation results and make systematic forecasting errors.</p

Pseudo-LIDAR data analysis and feed-forward wind turbine control design

To investigate potential improvement in wind turbine control employing LIDAR measurement, pseudo-LIDAR wind speed data is produced with Bladed using a designed sampling strategy, and assessed with preliminary frequency-domain analysis. A model-inverse feed-forward controller is adapted to combine with feedback control so as to enhance pitch control performance at high wind speed. This controller is applied to an industrial-scale 5MW wind turbine model and the control performance is compared with a baseline feedback controller. Simulation study demonstrates that the combined feed-forward/feedback control scheme has improvements in reducing pitch angle variation and reduction of load relevant metrics

LIDAR-assisted wind turbine gain scheduling control for load reduction

A gain-scheduled feedforward controller employing pseudo-LIDAR wind measurement is designed to augment the baseline feedback controller for wind turbine load reduction during above rated operation. The feedforward controller is firstly designed based on a linearised wind turbine model at one specific wind speed, then expanded for full above rated operational envelope with gain scheduling. The wind evolution model is established using the pseudo-LIDAR measurement data which is generated from Bladed using a designed sampling strategy. The combined feedforward and baseline control system is simulated on a 5MW industrial wind turbine model developed at Strathclyde University. Simulation results demonstrate that the gain scheduling feedforward control strategy can improve the rotor and tower load reduction performance for large wind turbines

LIDAR-based wind speed modelling and control system design

Abstract—The main objective of this work is to explore the feasibility of using LIght Detection And Ranging (LIDAR) measurement and develop feedforward control strategy to improve wind turbine operation. Firstly the Pseudo LIDAR measurement data is produced using software package GH Bladed across a distance from the turbine to the wind measurement points. Next the transfer function representing the evolution of wind speed is developed. Based on this wind evolution model, a model-inverse feedforward control strategy is employed for the pitch control at above-rated wind conditions, in which LIDAR measured wind speed is fed into the feedforward. Finally the baseline feedback controller is augmented by the developed feedforward control. This control system is developed based on a Supergen 5MW wind turbine model linearised at the operating point, but tested with the nonlinear model of the same system. The system performances with and without the feedforward control channel are compared. Simulation results suggest that with LIDAR information, the added feedforward control has the potential to reduce blade and tower loads in comparison to a baseline feedback control alone

Direct effect of solvent viscosity on the physical mass transfer for wavy film flow in a packed column

The interphase mass transfer plays a critical role in determining the height of packed column used in absorption process. In a recent experiments2, the direct impact of viscosity on the physical mass transfer coefficient was observed to be higher in a packed column as compared to the wetted wall column. We offer a plausible mechanism involving the wavy film and eddy enhanced mass transfer in a packed column to explain underlying physics via analytical and numerical studies. The analytically derived mass transfer coefficient matches well with experimental observation in a packed column. The countercurrent flow simulations in a packed column with both uniform and wavy films also confirm this behavior. The predicted k_L shows steep variation with for a wavy film than a uniform film, further confirms the proposed theory. A similar relation for a wavy film is also observed in theoretical, experimental and numerical studies