Variable Power Levels Research Articles

Neutronic design of small modular long­life pressurized water reactor using thorium carbide fuel at a power level of 300–500 MWth

This study presents the neutronic design of a small modular long­life Pressurized Water Reactor (PWR) using thorium carbide fuel with 233U fissile material. The target optimization for this study is a reactor designed to operate for 20 years, with excess reacti­vity throughout the reactor operational cycle consistently below 1.00 % dk/k. The analysis involves dividing the reactor core into three fuel regions with 233U enrichment levels ranging from 3 % to 8 %, with a 1 % difference for each fuel region. To achieve optimum conditions, 231Pa was randomly added to the fuel. The fuel volume fraction in this design varied from 30 % to 65 %, with a 5 % incremental variation. Power level variations are also studied within the 300–500 MWth with increments of 50 MWth. Calculations were performed using the Standard Reactor Analysis Code (SRAC) program with the PIJ and CITATION modules for cell and core calculations utilizing JENDL­4.0 nuclide data. Neutronic calculations indicate that the fuel with a 60 % volume fraction achieves optimum conditions at a power level of 300 MWth. The best performance was observed with a fuel volume fraction of 65 %, reaching optimum conditions across power levels ranging from 300 to 500 MWth. For the fuel with the best performance, the power density distributions for low and high power levels follow the same pattern radially and axially. The power peaking factor (PPF) for all fuel configurations approaching the optimum conditions remains below two, a safe limit for the PWR. Other neutronic safety parameters, such as the Doppler coefficient and void fraction coefficient, also stay within the safe limits for the PWR, with both values remaining negative throughout the reactor operational cycle

Nonlinear magnonic coupler using backpropagating surface spin waves

We investigated a spin-wave propagation in a magnon-crystal structure formed from two lateral microwaveguides separated by a one-dimensional antidot array. The mechanisms of control of the backpropagating regime of the surface spin waves both with geometry tuning and with power level variation in the case of in-plane magnetization are investigated by the method of micro-magnetic modeling and the experimental method of Brillouin light scattering spectroscopy. It was shown that for the case of spin-waves propagation through the isolated channels the shape anisotropy in the coupling region can be tuned effectively by a variation of the distance between the channels. The regime of nonlinear switching of the signal and backward propagation was observed in microwave and Brillouin spectroscopy measurements. The proposed effect of the signal separation manifests itself in the spatially and frequency-selective regimes of spin-wave propagation. Proposed spin-wave coupler opens an alternative way for the design of the functional interconnections of spin-wave based units in the planar magnonic networks.

Metaheuristic‐based graded objective function strategy for optimal thyristor‐controlled series capacitors estimation in weak distribution systems with uncertain distributed generation

AbstractThis study proposes an optimal approach for enhancing the quality of a weak electrical power distribution system by utilizing thyristor‐controlled series capacitors (TCSC). The proposed approach considers various system components, including shunt capacitors and distributed generators that rely on renewable energy sources, which are characterized by uncertainty due to changing weather conditions. The proposed system maximizes the benefits of these components by updating its parameters to improve the distribution power system's quality under all operating conditions, which change due to the varying energy generated by the distributed generators and load changes. The optimal TCSC values are calculated for all operating conditions using the Hyper‐Spherical Search with graded objective functions management strategy (HSSA‐GOFMS) algorithm. The GOFMS converts all restrictions into objective functions with limits and prioritizes the search for objectives according to a sequential system of priorities. This strategy prevents the possibility of non‐convergence. The results demonstrate the effectiveness of the proposed approach in improving the performance quality of a weak electrical distribution system. The proposed strategy achieves the target voltage level limits within nominal values, even with the interference of the system with generators distributed at variable power levels. Furthermore, the proposed approach enhances the performance quality of the system under a wide range of load changes.

Ultra-wideband rectenna with the dual ground plane for wide dynamic input power and load range

ABSTRACT The ultra-wideband rectenna is designed to have a fractional bandwidth of more than 100%, allowing it to work from 1.4 GHz to 5.4 GHz, with a bandwidth of 4 GHz. The proposed design involves a square patch antenna that incorporates an inverted L-slot and utilises dual ground planes in the form of rectangular and semi-octagonal shapes. The intended rectenna simultaneously harvests energy from various frequency bands, including GSM 1800 MHz, UTMS 2100 MHz, ISM 2450 MHz, 2800 MHz, and 3600 MHz. The proposed rectifier circuit incorporates three impedance-matching (IM) branches, which effectively mitigate the nonlinear attributes of the rectifier system and ensure favourable IM across a broad spectrum of frequencies. The DC combining technique is employed to attain favourable conversion efficiency. The CE in the GSM 1800 MHz band was measured to be 74%. The CE in the UTMS 2100 MHz band was measured to be 66%. In the ISM2450 MHz frequency band, a CE of 76% was measured. The CE in the 2800 MHz frequency band was determined to be 67.5%. At 3600 MHz, the measured CE is recorded as 67%. The obtained optimal load value is 470 Ω and it provides more than 65% conversion efficiency (CE) at all the intended frequency bands. The proposed rectenna demonstrates an CE exceeding 50% across the entire range of input power level (IPL) variations from 0 to 11 dBm. Furthermore, it achieves an efficiency surpassing 60% when subjected to load variations ranging from 270 Ω to 750 Ω.

A High-Efficiency High-Power 170-176-GHz Frequency Stabilized Quadrature Radiator

In this article, we present a high-efficiency high-power radiator with on-chip frequency stabilization and quadrature generation capabilities for short-coherence-time imaging and wireless communication applications. To achieve efficient sub-terahertz (sub-THz) signal generation, a systematic design approach using the device-centric gain-plane optimization is employed. In addition, an on-chip frequency stabilization mechanism utilizing the inherent power level variation over the tuning range is proposed. To show the feasibility of this approach, a 170–176-GHz radiator prototype is demonstrated, which has an effective isotropic radiated power (EIRP) of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$+$</tex-math> </inline-formula> 24.6 dBm and a dc-to-RF efficiency of 9.2%. The prototype is fabricated in a 55-nm SiGe bipolar complementary metal–oxide–semiconductor (BiCMOS) process and achieves one of the highest output power and dc-to-RF efficiency among designs beyond <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$f_{\text{max}}$</tex-math> </inline-formula> /2. The frequency stabilization mechanism reduces the long-term frequency drifts by 4.3 times.

Deep-Neural-Network-Based Receiver Design for Downlink Non-Orthogonal Multiple-Access Underwater Acoustic Communication

The excavation of the ocean has led to the submersion of numerous autonomous vehicles and sensors. Hence, there is a growing need for multi-user underwater acoustic communication. On the other hand, due to the limited bandwidth of the underwater acoustic channel, downlink non-orthogonal multiple access (NOMA) is one of the fundamental pieces of technology for solving the problem of limited bandwidth, and it is expected to be beneficial for many modern wireless underwater acoustic applications. NOMA downlink underwater acoustic communication (UWA) is accomplished by broadcasting data symbols from a source station to several users, which uses superimposed coding with variable power levels to enable detection through successive interference cancellation (SIC) receivers. Nevertheless, comprehensive information of the channel condition and channel state information (CSI) are both essential for SIC receivers, but they can be difficult to obtain, particularly in an underwater environment. To address this critical issue, this research proposes downlink underwater acoustic communication using a deep neural network utilizing a 1D convolution neural network (CNN). Two cases are considered for the proposed system in the first case: in the first case, two users with different power levels and distances from the transmitter employ BPSK and QPSK modulations to support multi-user communication, while, in the second case, three users employ BPSK modulation. Users far from the base station receive the most power. The base station uses superimposed coding. The BELLHOP ray-tracing algorithm is utilized to generate the training dataset with user depth and range modifications. For training the model, a composite signal passes through the samples of the UWA channel and is fed to the model along with labels. The DNN receiver learns the characteristic of the UWA channel and does not depend on CSI. The testing CIR is used to evaluate the trained model. The results are compared to the traditional SIC receiver. The DNN-based DL NOMA underwater acoustic receiver outperformed the SIC receiver in terms of BER in simulation results for all the modulation orders.

End-to-End Deep Learning of Joint Geometric Probabilistic Shaping Using a Channel-Sensitive Autoencoder

In this paper, we propose an innovative channel-sensitive autoencoder (CSAE)-aided end-to-end deep learning (E2EDL) technique for joint geometric probabilistic shaping. The pretrained conditional generative adversarial network (CGAN) is introduced in the CSAE which performs differentiable substitution of the optical fiber channel model under variable input optical power (IOP) levels. This enables the CSAE-aided E2EDL to design optimal joint geometric probabilistic shaping schemes for optical fiber communication systems at varying IOPs. The results of the proposed CSAE-aided E2EDL technique show that for a dual-polarization 64-Gbaud signal with a transmission distance of 5 × 80 km, when the modulation format is a 64-quadrature amplitude modulation (QAM) or a 128-QAM, the maximum generalized mutual information (GMI) level learned via CSAE-aided E2EDL is 5.9826 or 6.8384 bits/symbol under varying IOPs, respectively. In addition, the pretrained CGAN, as a substitution for optical fiber transmission model, accurately characterizes the distortion of signals with different IOPs, with an average bit error ratio (BER) difference of only 1.83%, an average mean square error (MSE) of 0.0041 and an average K-L divergence of 0.0046. In summary, this paper delivers new insights into the application of E2EDL and demonstrates the feasibility of joint geometric probabilistic shaping-based E2EDL for fiber optic communication systems with varying IOPs.

Downlink Non-Orthogonal multiple access underwater acoustic communication receiver design Deep neural network

Downlink non-orthogonal multiple access (NOMA) is necessary to handle the underwater acoustic channel's limitations on bandwidth. NOMA downlink underwater acoustic (UWA) communication transmits data symbols from a source station to many users. Superimposed coding with variable power levels allows successive interference cancelation (SIC) receivers to decode data. However, SIC receivers require knowledge of channel conditions and channel state information (CSI). This is difficult to acquire, particularly in UWA communication. To address this problem, this paper proposes downlink underwater acoustic using 1D Convolution neural network (CNN). Two users with different power levels and distances from the transmitter employ BPSK modulation to support multiuser communication. Users far from the base station receive the most power. The base station uses superimposed coding. BELLHOP algorithm generates the training dataset with user depth modifications. For training the model, a composite signal passes through the samples of the UWA channel and is fed to the model along with labels. DNN receiver learns the characteristic of the UWA channel and does not depend on CSI. The testing CIR is used to evaluate the trained model. The results are compared to the traditional SIC receiver. The DNN-based DL NOMA underwater acoustic receiver outperformed the SIC receiver in simulations.

Design study of small modular gas-cooled fast reactor employing modified CANDLE burnup with radial direction shuffling scheme

Abstract Design Study of Small Modular Gas-cooled Fast Reactors Employing Modified CANDLE Burnup with Radial Direction Shuffling Scheme has been performed with the power level 325–525 MWt. In this study Modified CANDLE burn-up scheme with radial direction shuffling has been employed with special attention to minimize reactivity swing during burn-up. The reactor cores are divided into 10 regions with equal volume in radial direction. The shuffling scheme of Modified CANDLE in radial direction can be described as follows. The natural uranium input is initially loaded in region 1. After 10 years of burnup the fuel in region 1 is shifter to region 2, the fuel in region 2 is shifted to region 3, etc. till the fuel of region 9 is shifter to region 10. The fuel from region 10 is taken out. Region 1–5 basically breeding zones in which plutonium is accumulated in fuels, while regions 5–10 have enough accumulated plutonium so that they contribute significantly to the power production. We call region 5–10 as burning zone. Nitride fuel is adopted as fuel in this study. Some parametric studies have been performed including variation of core height and power level. The neutronic calculations have been performed using the SRAC 2006 code with JENDL 4.0 nuclear data library. The optimized result shows the reactor could be operated 10 years continuously with maximum excess reactivity less than 1 % Δk/k for 500 MWt output power, 160 cm core active height and 110 cm core active radius.

Isotope kinetics modeling in a circulating fuel system: a case study of the MBIR reactor loop

The paper presents the results of modeling of changes in the isotopic composition of the liquid-salt fuel circulating in the experimental channel of the MBIR reactor facility. The authors tested the ISTAR software environment adapted for solving burnup equations in problems with variable power levels. The loop channel parameters, including two heat exchanger options, were estimated to obtain the appropriate salt transit time through the loop channel zones. Two problems of a circulating fuel system (loop) modeling are considered, namely: (1) modeling the equilibrium salt isotope composition in such a system; and (2) developing a technique for modeling nonstationary isotope kinetics in the MBIR reactor loop. Non-stationary isotope kinetics can be modeled as sequential burnup of nuclides in the neutron field and decay during movement in the external circuit. The authors also developed an algorithm for modeling changes in the isotopic composition of fuel salt during its circulation, taking into account the sequential transfer of a given salt volume from the burnup zone to the zone outside the reactor core. Based on this algorithm, a software package was created using the Python 3.9 programming language and ISTAR modules. In addition, a description of the calculation methodology was given and some calculation results obtained using the software were presented. In the process of working with the program, it was found that, for the given times of the fuel being in each of the zones (2 and 200 seconds, respectively), modeling the change in the isotopic composition during the fuel campaign (500 days) will require the calculation of more than 500 thousand steps. In order to save time, it is necessary to find out whether it will be possible to reduce the number of calls to the neutronic calculation code due to a slight change in the isotopic composition of the fuel in the loop per one burnup step. Work is currently underway to optimize this process.

Nonlinear phase shifts induced by pumping spin waves in magnonic crystals

A nonlinear phase shift of low-power spin waves (SWs) induced by a high-power pumping SW excited both inside and outside the magnonic band-gaps of a magnonic crystal has been studied. The magnonic crystal with spatially periodic thickness is fabricated from an yttrium iron garnet film by chemical etching. The results show that the phase shift of the low-power SWs can be effectively controlled by variation of power level of the pumping SW. This induced nonlinear phase shift is weakened if the pump frequency lies in the magnonic bandgap. The data obtained are well explained by contradirectional coupling of the high-power forward and reflected spin waves. A theoretical model for this effect is presented. Our findings are important for the further progress in SW computing.

Efficient Digital Signal Recovery for Satellite Communications With Active Phased Arrays

In this letter, a transfer learning-assisted (TLA) digital signal recovery (DSR) method is proposed for the linearization of active phased arrays (APAs) for satellite communications to handle the transition to different communication scenarios. The frozen layers of a deep neural network (DNN) are pretrained to extract the main nonlinear characteristics of the APA, and the fine-tuning layers are adopted to achieve prompt update of the regression parameters according to the variations in average input power levels and steering angles. This allows satisfactory reception performance to be maintained in time when the nonlinearity of the APA changes. Experimental results on a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4 \times 4$</tex-math> </inline-formula> APA antenna at 28 GHz show that the proposed method improves the adjacent channel power ratio (ACPR) and the error vector magnitude (EVM) performance. Compared with the existing fully relearned DNN-DSR method, the proposed method achieves almost as good performance with only 1/10 of the data.

Development and validation of an AI-Driven model for the La Rance tidal barrage: A generalisable case study

In this work, an AI-Driven (autonomous) model representation of the La Rance tidal barrage was developed using novel parametrisation and Deep Reinforcement Learning (DRL) techniques. Our model results were validated with experimental measurements, yielding the first Tidal Range Structure (TRS) model validated against a constructed tidal barrage and made available to academics. In order to proper model La Rance, parametrisation methodologies were developed for simulating (i) turbines (in pumping and power generation modes), (ii) transition ramp functions (for opening and closing hydraulic structures) and (iii) equivalent lagoon wetted area. Furthermore, an updated DRL method was implemented for optimising the operation of the hydraulic structures that compose La Rance. The achieved objective of this work was to verify the capabilities of an AI-Driven TRS model to appropriately predict (i) turbine power and (ii) lagoon water level variations. In addition, the observed operational strategy and yearly energy output of our AI-Driven model appeared to be comparable with those reported for the La Rance tidal barrage. The outcomes of this work (developed methodologies and DRL implementations) are generalisable and can be applied to other TRS projects. Furthermore, this work provided insights which allow for more realistic simulation of TRS operation, enabled through our AI-Driven model.

Three‐dimensional shaped and contour pattern synthesis with multiple beam approach

AbstractA multiple‐beam synthesis method is proposed to generate three‐dimensional (3D) shaped and contour patterns from a planar phased array antenna. Three‐dimensional radiation patterns are synthesized primarily with optimum beam positions and variable mainbeam power levels of multiple beams, followed by calculating the resultant element weights. Contour patterns are synthesized from multiple beam peaks by mapping the individual beam power levels to their corresponding 3 dB beamwidth coverage areas at each designated location on the contour. The far‐field contour shape affected by the influence of the element pattern, mutual coupling, and scan loss is compensated by the peak power of the scanned beam patterns. The proposed synthesis supports dynamically changeable contour shapes. Flat‐topped, stepped 3D patterns and arbitrary contour shapes with shaped null zones inside the contour are simulated and implemented on a 16 × 16 element 5G mmWave planar phased array. Measured radiation patterns are compared with simulations and presented.

Experimental characterisation of laser surface remelting via acoustic emission wavelet decomposition

This paper presents a novel technique of monitoring laser surface remelting (LSR) via measurements of process generated acoustic emission (AE). The LSR conditions include a variable laser power level and an ambient air or argon 5.0 inert gas atmosphere. The microstructure and microhardness of the remelted surface layer are evaluated. The recorded AE signal datasets are analysed via the wavelet decomposition technique. The resulting energy and energy proportions of approximation and detail coefficients are calculated. The decomposed AE signal features are evaluated in correlation with the LSR process conditions. A supervised machine learning cubic support vector machine classifier type is used for the classification of laser pulses. The experimental results show an overall 98% classification accuracy into the corresponding LSR laser power level and atmosphere conditions, confirming the utility of monitoring the LSR process and the resulting material surface layer characteristics via the AE wavelet decomposition technique.

Balancing Awareness and Congestion in Vehicular Networks Using Variable Transmission Power

Vehicular ad Hoc networks (VANETs) support a variety of applications ranging from critical safety applications to “infotainment” or “comfort” applications. In North America, 75 MHz of the spectrum in the 5.9 GHz band has been allocated for vehicular communication. Safety applications rely on event-driven “alert” messages as well as the periodic broadcast of Basic Safety Messages (BSMs) containing critical information, e.g., position, speed, and heading from participating vehicles. The limited channel capacity and high message rates needed to ensure an adequate level of awareness make the reliable delivery of BSMs a challenging problem for VANETs. In this paper, we propose a decentralized congestion control algorithm that uses variable transmission power levels to reduce the channel busy ratio while maintaining a high level of awareness for nearby vehicles. The simulation results indicate that the proposed approach is able to achieve a suitable balance between awareness and bandwidth usage.

Superposition model of mode shapes composed of travelling torsional guided waves excited by multiple circular transducer arrays in pipes

In pipe inspection using ultrasonic guided wave technique, the current commercial transmitters are designed for the unidirectional guided wave excitation using multiple circular piezoelectric transducers arrays in the axial direction. However, the source with many individual transducer elements in arrays has difficulty in achieving an axisymmetric loading perfectly for defect detection. Therefore, a quasi-axisymmetric wave is formed due to many undesired wave modes are launched instead of a pure axisymmetric wave at a given excitation frequency. In this paper, a realistic superposition model of axial multiple transducer arrays is proposed. The model has many potential applications; one example is investigating the source influence on the generated quasi-axisymmetric wave effect. The analytical model is employed to achieve the predictions for investigating a transmitter’s influence for the unidirectional enhancement of torsional T(0,1) guided wave mode excitation in a pipe inspection system composing of three piezoelectric transducer ring arrays. The excitation function with variable power levels among transducers in arrays is also introduced. The predictive results using the analytical model for the distribution of circumferential displacement amplitudes over time are verified using the finite element method and a CLV-3D laser vibrometry measurement on a 219.1-mm-outer-diameter steel pipe without defect. A comparison between calculated and test results has been analysed quantitatively. The respective results are in good agreement. Thus, predictions for the superposed wavefield can be used to analyse the realistic characterisation of the excitation function in axial multiple transducer arrays. Additionally, a sensitivity analysis for part-circumferential crack detection using the quasi-axisymmetric torsional modes generated is also evaluated using finite element modelling.

Maximum lifetime convergecast tree in wireless sensor networks

We study the problem of building a maximum lifetime data collection tree for periodic convergecast applications in wireless sensor networks. We experimentally observe that if two nodes transmit the same number of data packets, the amount of energy consumption of the nodes is approximately the same even if the payload lengths of the transmitted packets are different. This is because the major energy consumption during a packet transmission arises from radio start-up and medium access control overhead. Our formulated lifetime maximization problem captures the energy expenditure due to message transmissions/ receptions in terms of the number of data packets transmitted/ received, in contrast to prior works, which consider the number of data units (amount of sensor data generated by a node) transmitted/ received. Variable transmission power levels of the radio and accounting for the sensor energy consumption are other factors that make our problem formulation different from those in prior work. We prove that this problem is NP-complete by reducing the set cover problem to it and propose an algorithm to solve it. The performance of the proposed algorithm is experimentally evaluated using Jain’s fairness index as a metric by implementing it on an actual testbed consisting of 20 sensor nodes and compared with those of the widely used shortest path tree and random data collection tree algorithms. The energy consumption of different nodes under the proposed algorithm are shown to be more balanced than under the shortest path tree and random data collection tree algorithms. Also, the performance of the proposed algorithm in large networks is studied through simulations and is compared with those of the state-of-the-art RaSMaLai algorithm, directed acyclic graph algorithm and clustering based OPTIC algorithm, and the shortest path tree, minimum spanning tree, and random tree based data collection schemes. Our simulations show that the proposed algorithm provides a significantly higher network lifetime compared to all the other considered data collection approaches.

WDM-Based 160 Gbps Radio Over Fiber System With the Application of Dispersion Compensation Fiber and Fiber Bragg Grating

The demand for data transmission is rising expensively for the applications of biomedical sensors data, multimedia technologies, and ultrahigh-definition online video streaming. Such applications require larger bandwidth with minimum latency and seamless service delivery. Radio-over-fiber (RoF), integrated with wavelength division multiplexing (WDM) technology, is being considered one of the promising technologies. However, the integration of optical fiber and wireless communication also generates non-linear effects as and when the number of users increases. That results in the introduction of signal noise, unwanted frequencies, low quality of signals, and increased latency. In this paper, a 16-channel 160 Gbps data rate WDM-based RoF system has been simulated and evaluated for optimum performance at a variable input power level, from 5 to −15 dBm, with the application of dispersion compensation fiber (DCF) and fiber Bragg grating (FBG), with channel spacing of 50 and 100 GHz. The performance of the system is evaluated with the existing WDM-RoF system. The performance metrics parameters chosen for evaluation are bit error rate (BER), quality factor (Q-factor), and eye diagrams and simulated on opti-system simulator. The optimum performance has been observed at a power level of −5 dBm for all these elected evaluation parameters. It has also been observed that, for channel spacing of 100 GHz, the network performed better in comparison with 50 GHz.

Temporal Variation in Cultural Seismic Noise and Noise Correlation Functions during COVID-19 Lockdown in Canada

AbstractThe COVID-19 pandemic of 2020 led to a widespread lockdown that restricted human activities, particularly land, air, and maritime traffic. The “quietness” on land and ocean that followed presents an opportunity to measure an unprecedented reduction in human-related seismic activities and study its effect on the short-period range of ambient noise cross-correlation functions (NCFs). We document the variations in seismic power levels and signal quality of short-period NCFs measured by four seismographs located near Canadian cities across the pandemic-defined timeline. Significant drops in seismic power levels are observed at all the locations around mid-March. These drops coincide with lockdown announcements by the various Canadian provinces where the stations are located. Mean seismic power reductions of ∼24% and ∼17% are observed near Montreal and Ottawa, respectively, in eastern Canada. Similar reductions of ∼27% and 17% are recorded in western Canada near Victoria and Sidney, respectively. None of the locations show full recovery in seismic power back to the pre-lockdown levels by the end of June, when the provinces moved into gradual reopening. The overall levels of seismic noise during lockdown are a factor of 5–10 lower at our study locations in western Canada, relative to the east. Signal quality of NCF measured in the secondary microseism frequency band for the station pair in western Canada is maximum before lockdown (late February–early March), minimum during lockdown (mid–late March), and increased to intermediate levels in the reopening phase (late May). A similar pattern is observed for the signal quality of the eastern Canada station pair, except for a jump in levels at similar periods during the lockdown phase. The signal quality of NCF within the secondary microseism band is further shown to be the lowest for the western Canada station pair during the 2020 lockdown phase, when compared with similar time windows in 2018 and 2019.