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Space is a feature of all disasters, and it is through decisions on how space is developed, used, and reproduced that disasters manifest themselves. Critical urban theory sees urban space-cities-as an arena of contestation expressed through the relationship between people, power, and the built environment. Cities allow for an unpacking of this process of contestation through the interpretation of various temporal, spatial, social, and physical elements that together create complex issues and 'wicked problems'. In these urban spaces in all their complexity, disasters reveal both the worst injustices and inequalities present in a society. By drawing on three well-known cases-Hurricane Katrina in 2010; the Haiti earthquake in 2010; and the Great East Japan Earthquake and Tsunami in 2011-this paper not only explores the opportunities that critical urban theory presents for gaining a deeper understanding of disaster risk creation, but also it encourages disaster scholars to engage with it., (© 2023 The Authors. Disasters published by John Wiley & Sons Ltd on behalf of ODI.)

In this paper, a scalable end-to-end tree boosting system called XGBoost has been applied for predicting the magnitude of an earthquake from the early part of earthquake waveform data. This model uses the features extracted from the early P wave phase of the records as an input. The model's effectiveness has been verified by using data on earthquakes occurring in the Eurasian plate of Japan Islands from 1996 to 2021. Feature engineering has given 29 new features identified from the early P wave phase of the record, which show a high correlation with the magnitude of an earthquake. The comparison of predicted and actual magnitude shows that a trained XGboost model, which uses a single input record for magnitude prediction, gives an average prediction error of 0.004 ± 0.57 for earthquakes in the test dataset. In contrast, the average prediction error of –1.1 ± 0.80 and –0.65 ± 0.69 has been obtained for the magnitude estimated from conventional τc and Pd methods using the same test dataset. It is further seen that the average predicted magnitude of a single earthquake of magnitude 4.5 and 6.1 (MJMA) obtained by using multiple nearfield records using XGBoost model is 4.58 ± 0.33 and 6.32 ± 0.29, which is close to the actual magnitude of the earthquake. The results presented in this paper clearly show that the structured data can be effectively used by complex machine learning or deep learning models to predict earthquake magnitude from single or multiple records. [ABSTRACT FROM AUTHOR]

Earthquake swarms are most commonly composed of small‐magnitude earthquakes. However, a recent study by Yoshida, Uchida, et al. (2023, https://doi.org/10.1029/2023GL106023) analyzed a swarm beneath the Noto Peninsula in Japan that, after more than two years of moderate‐magnitude seismicity, triggered the moment magnitude (Mw) 6.2 Suzu mainshock in May 2023. Based on high‐precision earthquake locations and a slip inversion of the mainshock, these authors found that the Mw 6.2 Suzu earthquake occurred on the updip extension of a fault that was active during the swarm, likely driven by increased fluid pressure. After publication of that paper, a much larger and more destructive Mw 7.5 event occurred nearby on 1 January 2024. These events underscore the potential for swarms to be precursors to large, damaging earthquakes. Forecasting the eventual evolution of swarms is currently very challenging but could be aided in the future by new observations and models. Plain Language Summary: Although earthquake swarms often only contain small earthquakes, occasionally they can trigger large, damaging earthquakes. Yoshida, Uchida, et al. (2023, https://doi.org/10.1029/2023GL106023) examined the triggering of a magnitude 6.2 earthquake in Japan, which caused extensive damage, following two years of smaller earthquakes. This sequence, like many swarms, may have been driven by elevated fluid pressure migrating upwards within the crust. After publication of that paper, a much larger and more destructive Mw 7.5 event occurred nearby. Forecasting the eventual evolution of ongoing swarms is currently very challenging but could be aided in the future by new observations and models. Key Points: Earthquake swarms can be precursors to damaging earthquakes, including the 1 January 2024, Mw 7.5 Noto Peninsula, Japan eventFluid pressure changes often drive swarm activity, and their degree of confinement may influence swarm evolutionDirect observations of fluids in fault zones combined with numerical modeling may aid swarm forecasting in the future [ABSTRACT FROM AUTHOR]

The Fukushima power station in Japan was affected by a major earthquake and tsunami in March 2011, inspecting the primary containment vessel remains difficult due to high radioactivity. Long-reach robot arms are useful in inspecting such hazardous environments, and a coupled tendon-driven mechanism enables realizing a long, light-weight, and thin manipulator. However, high elastic elongation of tendons due to gravity may lead to unstable joint control. In this paper, we introduce dynamics-based control as a feasible strategy for a long-reach tendon-driven robotic arm. Additionally, a planning method to identify the joint angle path ensuring stability is proposed. Considering stability analysis, the potential due to the tendon elasticity and gravity is evaluated and used as an index of joint stability. The rapidly exploring random tree is used as the planning algorithm. The effectiveness of the proposed method was demonstrated through the successful manipulation of a 5-kg payload by a 10-m long robotic arm. [ABSTRACT FROM AUTHOR]

Disaster resilience is an interdisciplinary area of study. Collaboration between humanities and sciences is important to approach issues in this area. However, science and engineering consider disaster resilience as minimizing the scientifically estimated damage induced by natural hazards. In contrast, disaster resilience studies in the social sciences tend to focus on societal vulnerability. The views between the two disciplines can lead to inconsistency or contradiction. This paper discussed this issue. To do so, the author uses the case study focusing on the effects of predictions on Nankai Trough Earthquake countermeasures in Kochi City, Japan. First, this study revealed that not only the revision of hazard prediction but the historical background of land use development affected the large-scale earthquake damage estimation in Kochi City. Second, the upward revision of hazard prediction resulted in strengthening of community disaster management. However, it also accelerated residential relocation associated with class disparities. As a result, ironically, marginalized social groups were unevenly located in predicted tsunami inundation areas. However, such issues are not considered in the existing disaster resilience scheme and policy. Based on this analysis, it is argued that communicating scientific knowledge on hazards to society alone is not enough. Considering the local context, the perspective of literacy for disaster resilience from downstream' is also important. [ABSTRACT FROM AUTHOR]

A cross-region prediction model named SeisEML (an acronym for Seismological Ensemble Machine Learning) has been developed in this paper to predict the peak ground acceleration (PGA) at a given site during an earthquake. The SeisEML model consists of hybridized models, kernel-based algorithms, tree regression algorithms, and regression algorithms. The model ablation study is conducted to examine the performance and the selection of meta-machine learning models in the SeisEML. The training and testing dataset consists of 20852 and 6256 accelerograms recorded by the Kyoshin Network, Japan. The mean absolute error (MAE) and root mean square error (RMSE) have been utilized to compare the predicted peak ground acceleration (PGA) for the test data. The SeisEML model yields approximately half the MAE and RMSE values obtained with conventional attenuation relations. The SeisEML model has been used to compute Japan's iso acceleration contour map of three earthquakes ( M JMA 7.4, 6.6, and 6.1). The qualitative comparison of iso acceleration contours obtained from actual and predicted PGA using SeisEML clearly shows that the model can reliably predict the PGA distribution during an earthquake compared to the regional ground motion prediction equation (GMPE). The cross-region prediction was performed on the datasets of the Iranian earthquakes using SeisEML. The comparison of predicted and observed peak ground acceleration in terms of MAE and RMSE shows that the machine learning model's performance is superior to the regional attenuation relation. The predictions of PGA from the developed ML model indicate that this trained model has the potential for predicting regional and global scenarios with similar tectonic setups. The ML model developed in this paper can considerably enhance the reliability of PGA prediction for seismic hazard mapping of any region and can serve as a reliable substitute for GMPEs. [ABSTRACT FROM AUTHOR]

In Japan, recently there has been an increase in the failure of dry masonry retaining walls located in an urban residential area due to strong earthquakes. However, currently there are no established optimal seismic reinforcement methods for such dry masonry retaining walls due to issues related to workability and construction cost. This paper presents a novel reinforcement method wherein the tilting reinforcement bars were installed from top of the retaining wall whose individual blocks were integrated. A detailed investigation and discussion on the mechanical behavior of a dry masonry retaining wall is made by comparing the results among different experimental cases which had different seismic reinforcement treatment with the help of tilting table experiments conducted in a geotechnical centrifuge. The results highlighted that the proposed method, the application of tilting reinforcement bars together with the integration of individual wall blocks, led to the best seismic resilient performance of the retaining wall with the least measured soil deformations and soil strains at the backfill. Among all the tested cases, the proposed method resulted in the least mobilization of axial force and bending moment at the top of reinforcement bars which may result in the overall reduction of the construction cost (i.e., by reducing the number of reinforcement bars) aiming toward a performance‐based design. Lastly, an analytical evaluation of the factor of safety (FOS) against collapse as per the Mononobe‐Okabe theory was made which was found to be in excellent agreement with the centrifuge experiments revealing the proposed method to perform best among all the cases. [ABSTRACT FROM AUTHOR]

The role of non‐structural elements (NSEs) in the seismic performance of buildings has been highlighted in past years. Research studies following state‐of‐the‐art methodologies generally find that when the structural collapse is not of significant concern, NSEs tend to dominate the repair costs and financial investment required in a building. This paper examines field observations from interviews and data collected from commercial buildings via structural health monitoring (SHM) following the 2018 Osaka earthquake in Japan. It suggests that fragility functions used in current methodologies for estimating NSE damage may not be entirely representative of the in‐situ reality and possibly underestimate actual damage. Additionally, interviews with building owners/managers indicate that the alarm and financial impact of NSEs was not as critical as anticipated, with much of the observed NSE damage not of serious concern and tolerable in many cases. This article provides discussion and insight into possible causes for these differences before discussing how current methodologies can benefit from these observations. It is believed that many of the fragility functions currently used to estimate NSE damage may not be representative because of differences in installation conditions and loading protocols used in experimental testing, possible interaction with other elements, variability in the quality of workmanship during installation and possible wear, tear and degradation during service. On the other hand, it is seen how SHM data recorded during seismic events may provide valuable data for an alternative means to develop fragility functions. Furthermore, it is seen that when building recovery states (RSs) other than the implicitly assumed 'full recovery' state used in guidelines like FEMA P‐58 are explored, the role of NSEs in direct monetary losses significantly reduces. This coincides with the field observations in Japan regarding the impact of NSEs and supports the recent developments in functional recovery on what building owners and occupants are prepared to tolerate post‐earthquake. It indicates that when discussing the relative importance of different building performance groups, it is vital that the expected RS is also stated, as for most decision‐makers following major events, functionality rather than full recovery remains the primary goal; hence, repairs and proactive measures should bear this in mind for more effective use of resources. [ABSTRACT FROM AUTHOR]

Tsunamis resulting from earthquakes can cause extensive damage, including infrastructure destruction, injuries, and fatalities. To address these risks, numerous tsunami evacuation simulations have been conducted to assess evacuation strategies and identify issues, particularly in Japan, where the Nankai Trough earthquake is anticipated, affecting underground malls in urban areas. Our previous research primarily focused on evacuating from underground to the surface, neglecting surface evacuation. Therefore, this study extended the previous study to include horizontal evacuation following the exit from the underground mall to ground level. It also considered the impact of pedestrian road crossings as interactions with vehicular traffic within the simulation to enhance realism and verify the evacuation risk. The study also explores scenarios where evacuation guide stairs are unavailable, comparing the effectiveness of alternative staircases in the evacuation plan. Results indicate that while using alternative staircases temporarily increases the number of evacuees reaching the surface, road crossings on evacuation routes become significant bottlenecks, leading to surface congestion and delayed evacuations. This raises doubts about the effectiveness of alternative staircases and highlights the need to consider alternative evacuation routes as a secondary plan. Additionally, the study reveals that reduced pedestrian flow at road crossings can significantly impact on evacuation times. Ultimately, this study demonstrated that achieving a short evacuation time from underground malls to the ground level might not always yield the best evacuation plan. It underscored the importance of considering aboveground factors in evacuation planning to ensure safety in the event of a tsunami caused by an earthquake. [ABSTRACT FROM AUTHOR]

Ground motion recording with peak ground acceleration (PGA) exceeding 1.43 g was observed at the Yamamoto (MYGH10) station during the MW 7.1 Fukushima earthquake off the east coast of Honshu, Japan, in February 2021. In this study, we investigated the site amplification effect and nonlinear site response at the MYGH10 site using the horizontal‐to‐vertical spectral ratio (HVSR) and surface‐to‐borehole spectral ratio (SBSR), respectively. The site transfer function of station MYGH10 was presented using HVSRs (HVSR on the ground surface) and SBSR at different frequency bands. The dominant contributing frequency band of the PGA was determined by increasing the high cutoff frequency of the bandpass filter when filtering the acceleration recording, which was used to interpret the anomaly of the PGA by combining it with the site characteristics. We found an obvious site effect below the downhole sensor through the HVSRb (HVSR on the downhole bedrock) and determined the influence of the frequency band of the downhole site on ground motion. In addition, substantial discrepancies in the frequency and amplitude between the spectral ratio curves for the Fukushima mainshock records and the weak historical motions were identified. The calculated values of the degree of nonlinearity suggested that a strong nonlinear site response occurred at station MYGH10. Finally, the recovery of the site after strong shaking was evaluated by using the average spectral ratio curves of several aftershock records. [ABSTRACT FROM AUTHOR]