Search Results (428)

This paper investigates the safety behavior of degraded lithium-ion battery modules taken from a 2016 Nissan Leaf (30 kWh, 106,394 km). The vehicle exhibited typical failure symptoms, including P33E6 faults, sudden range drops, and activation of turtle mode under load. Initial diagnostics based on LeafSpy data revealed strong cell imbalance, with a voltage spread exceeding 2.3 V under high current (≈170 A). The weakest cells dropped close to 1 V, suggesting severe internal degradation. To better understand this behavior, selected modules (cells 73–88) were removed and tested under controlled laboratory conditions. Capacity measurements in a 16S2P configuration showed 49.8 Ah in the 4.1–3.1 V range, corresponding to a state of health of about 59%, which is consistent with BMS estimates. However, high-current discharge tests on the weakest segment revealed a much more critical picture. One cell experienced rapid voltage collapse (from ~4.0 V to ~1.2 V), accompanied by a sharp increase in voltage divergence and visible thermal effects. Infrared observations indicated localized heating up to 43 °C and irreversible swelling, pointing to early-stage electro-thermal instability. These results suggest that moderate SOH values do not necessarily reflect actual safety margins under dynamic load conditions. Overall, the study shows that simple OBD-based diagnostics can help identify problematic modules, but additional load testing is necessary to assess real safety risks in aged EV battery systems. Full article

Maritime Autonomous Surface Ships (MASS) introduce new safety challenges associated with complex cyber–physical systems, distributed control architectures, and remote supervisory operation. Traditional maritime risk assessment approaches primarily focus on component failures and historical accident data and may therefore be insufficient for capturing interaction-driven hazards arising in autonomous vessel systems. This study develops a parallel and architecturally synchronized risk assessment framework integrating System-Theoretic Process Analysis (STPA) and Fault Tree Analysis (FTA) for the safety assessment of MASS. Within the proposed framework, both analyses evolve concurrently within a shared system architecture, enabling explicit traceability between hazards, unsafe control actions, causal scenarios, failure events, and accident propagation pathways. The framework is demonstrated through a case study of a Degree of Autonomy 3 short-sea freight vessel operating in a high-density North Sea traffic environment. The integrated analysis identifies dominant accident pathways related to perception degradation, communication disturbance, authority coordination conflicts, maneuver execution deviations, and incorrect collision-risk assessment. The results illustrate how the framework supports structured safety assessment of MASS while preserving traceability between systemic control deficiencies and accident propagation mechanisms. Full article

Large-scale integration of photovoltaics (PV) introduces complex source-load temporal volatility and grid-connection/off-grid transitions. Traditional static reliability assessments fail to capture these dynamics, resulting in “considerable deviations” in system indices. This paper proposes a reliability evaluation framework that couples temporal source-load trajectories with a multi-stage fault recovery process. Unlike traditional methods that rely on a single static snapshot, the proposed model evaluates the system state across a continuous 5-h restoration window. The novelty lies in the unique integration of a Dynamic Time Warping (DTW)–Kmedoids method to preserve temporal phase-shifts and a multi-stage Mixed-Integer Linear Programming (MILP) model to simulate PV grid-connection transitions throughout this window. By capturing the intra-outage evolution of sources and loads, the framework fundamentally corrects the “considerable deviations” of static assessments. Case studies demonstrate high precision with an error of less than 0.71% and a 20-fold speedup. Crucially, the framework corrects the 22.31% risk underestimation bias inherent in static models by tracking real-time source-load evolution. This confirms that temporal coordination performance is the primary determinant of the reliability ceiling in active distribution networks. The findings reveal that the precise alignment of intermittent generation and fluctuating demand defines the actual operational safety margin, providing a superior quantitative foundation for grid resilience enhancement. Full article

Under the global energy transition, liquefied petroleum gas (LPG) remains an important transitional fuel. However, persistent safety risks in storage and transportation continue to limit its sustainable development. This study aims to evaluate the sustainability of China’s LPG storage and transportation system and identify practical improvement pathways. A “1+4” C-STSM multidimensional framework was developed by combining accident fault-tree analysis, comparative review of domestic and international standards, and a systematic assessment of storage, transportation, monitoring, and safety technologies. The results show that the sustainability of LPG systems depends on the coordinated performance of infrastructure, transportation, monitoring, and safety barriers across the full supply chain. China has made progress in engineering facilities and safety management, but still faces weaknesses in intrinsic safety, barrier integrity, intelligent monitoring, and life-cycle governance. The main gap with international advanced practice lies in insufficient system integration rather than the lack of basic technologies. Improving LPG sustainability requires a coordinated pathway that combines safer infrastructure, intelligent monitoring, stronger barrier management, and better regulatory coordination. Such an approach can enhance industrial safety while supporting low-loss, low-emission energy transition. Full article

Malawi lies within the southern segment of the East African Rift System and is exposed to infrequent but potentially damaging earthquakes. While recent advances in fault mapping, seismic monitoring, and hazard modelling have substantially improved scientific understanding of earthquake hazard in the Malawi Rift Zone, the practical reduction in seismic risk remains limited. This Perspective paper argues that earthquake resilience in Malawi is constrained less by scientific uncertainty than by challenges in integrating existing hazard knowledge into governance, planning, and preparedness. Drawing exclusively on published geological, geophysical, engineering, and policy literature, the paper synthesises evidence on seismic hazard, historical earthquake impacts, institutional preparedness, and barriers to the operational use of scientific risk assessments. An integrated, multi-pillar framework is proposed to support improved coordination between science, governance, infrastructure practice, and community preparedness. The framework is conceptual in nature and is intended to inform policy dialogue, prioritisation, and future empirical research rather than to provide a validated operational model. While grounded in the Malawian context, the insights presented are relevant to other low-income, rift-hosted regions facing similar challenges in translating earthquake science into effective disaster risk reduction. Full article

Prior studies have shown that socio-economic and structural risks can be correlated with earthquake effects. The quantification of these effects was used to formulate robust disaster risk reduction (DRR) strategies and building codes. This is more pronounced in countries with complex tectonic settings, such as the Philippines, where strong-to-major earthquakes can occur. Here, we report the evaluation of deterministic ground shaking (GS) intensity measurements for Camarines Norte, the Philippines, with the objective of assessing and mapping the susceptibility of communities to intense ground motion. GS intensities and peak ground acceleration (PGA) were computed using the Rapid Earthquake Damage Assessment System (REDAS) software developed by the Philippine Institute of Volcanology and Seismology (PHIVOLCS). The PGA was computed as a fraction of acceleration due to gravity, while GS used the PHIVOLCS Earthquake Intensity Scale (PEIS). Simulations were based on recorded earthquakes and mapped active faults near the province. Geographic information systems were used to stack and refine each simulation. Results showed that 13 earthquakes and 13 seismic source zones classified most of the province as PEIS VIII or higher, with the PGA maximum at 0.66 g. The results implied that the province is susceptible to very destructive to completely devastating ground shaking, and it is recommended to incorporate these results into DRR policymaking. Full article

Photovoltaic (PV) plants are typically assessed using ~25-year financial horizons and 25–30-year module performance warranties. However, experience from demanding climates shows that actual lifetimes can be shorter and that dry-condition insulation tests may underestimate risks under wet operation. In such cases, repowering after roughly five years can restore energy yield and reduce operational faults, but it also creates repeated waves of waste and increases manufacturing demand. This study synthesizes evidence on moisture-induced insulation loss, backsheet degradation, and delamination-driven failure escalation and complements it with a transparent 30-year scenario comparing module replacement every 5, 10, and 30 years. The findings suggest that humidity-dependent ground-impedance deterioration, frequent inverter trips, delayed morning start-up, and shutdown risks can emerge within about five years at challenging sites, while dry testing may fail to capture these issues. In a severe scenario, five-year repowering requires six full module sets over 30 years, significantly increasing waste volumes and pressure on manufacturing and recycling systems. Therefore, PV sustainability assessments should reflect the effective repowering interval rather than nominal warranties. Promising solutions include repowering-ready, disassemblable module designs, such as those using soft PDMS gel encapsulation. Full article

Rainfall-induced landslides represent one of the most recurrent geohazards affecting the transportation network of southwestern Calabria (Italy). This study provides an integrated assessment of landslide occurrence and road damage along the Costa Viola by combining detailed geomorphological mapping, multi-temporal analyses, historical documentation (1950–2025), and GIS-based spatial data processing. A total of 261 landslides were mapped, affecting approximately 19% of the study area. Slides constitute the dominant movement type (66.7%), followed by complex landslides, flows, and falls. Landslide distribution is strongly controlled by geological and morphometric factors: more than 80% of mapped phenomena occur in highly fractured granitic and gneissic rocks, over 70% lie within 500 m of faults, and more than 90% are located within 300 m of streams. Slope gradient (25–55°) and local relief (350–550 m) further contribute to slope instability patterns. The historical dataset documents 237 landslide-induced road damage events over 75 years, with a marked increase in occurrence since the early 2000s. Most damage events affected the SS18 road and frequently corresponded to reactivations of pre-existing landslides, highlighting the long-term persistence of slope instability and the seasonal influence of intense autumn–winter precipitation. Overall, the results demonstrate that landslide hazard in the Costa Viola is governed by the interplay between structural, lithological, geomorphic, and climatic factors, compounded by anthropogenic modifications along road corridors. The combined landslide inventory and historical database provide a robust basis for risk mitigation, identification of critical road sectors, and future susceptibility and predictive modelling to support effective territorial planning. Full article

As the primary power source for high-speed railways, understanding the fault propagation mechanisms among the components of the catenary system is crucial for developing proactive maintenance strategies. To quantitatively characterize fault propagation risk among catenary components, this paper proposes a temporal evolution-based fault correlation risk assessment model from a data-driven perspective. First, fault correlations are defined based on temporal evolution, and a risk assessment model integrating credibility and discredibility is developed based on the MYCIN model to avoid misclassifying high-frequency but low-risk fault correlations as high-risk. Second, to address potential fault correlations that are not explicitly observed in historical data, a latent path-based risk inference graph is constructed to indirectly infer their risk levels through observable fault correlations. Third, to reveal the temporal evolution characteristics of fault propagation risk, a temporal evolution series of system risk coefficients after component faults is constructed, and risk decay node and risk stabilization node are defined. A case study based on real historical fault data collected from the operation and maintenance system of a high-speed railway catenary system validates the effectiveness of the proposed method. The results demonstrate that the framework can comprehensively assess both observable and potential fault correlation risks and capture their temporal evolution characteristics, providing quantitative support for time-targeted proactive maintenance strategies of catenary systems. Full article

Zonal ship central cooling systems, which are primarily implemented in naval platforms and advanced specialized vessels to ensure high survivability, exhibit complex fluid–thermal interactions and multi-level valve networks, challenging conventional resilience analysis, especially under large-scale fault scenarios and dynamic topology reconfiguration. This paper presents a physics-informed dynamic resilience assessment and reconfiguration optimization method tailored for such systems. To address the high-dimensional reconfiguration search space, a physics-informed pruning mechanism combining topological reachability filtering and nodal continuity-based feasible-flow verification is introduced, eliminating 42.6% of invalid topologies and reducing optimization time by approximately 38%. Additionally, a cumulative thermal severity (CTS) metric is developed to capture transient thermal shock risks, quantitatively assessing deviation from the 50 °C system safety boundary at the most critical node. Simulation results for a main seawater pump failure scenario demonstrate that the proposed reconfiguration strategy, which coordinates cross-zone tie valves and leverages healthy zones’ pressure margins, shortens recovery time by 47%, suppresses peak temperature from 51.5 °C to 50.2 °C, reduces maximum over-temperature from 1.5 °C to 0.2 °C, and decreases CTS from 8.5 °C·s to 0.1 °C·s (a 98.8% reduction). These findings demonstrate that physics-informed pruning substantially reduces the computational burden of high-dimensional reconfiguration, while the proposed CTS metric enables quantitative assessment of transient thermal-shock risk. Together, they offer robust methodological guidance for resilience-oriented decision support and fault-tolerant design in complex shipboard fluid–thermal systems. Full article

The steady operation of underground gas storage (UGS) is significant for securing national energy. However, long-term cyclic injection-production operation causes the dynamic changes in formation stress, potentially leading to fault reactivation and slippage. This could affect the seal performance of the fault zone and cause disastrous consequences. In this paper, a mechanical analysis model for fault slip is constructed to study the dynamic seal performance in response to long-term injection-production cycles. An intelligent approach is proposed to predicate the fault slip value based on machine learning algorithms. It can realize long-term prediction of fault slip value under a new condition of injection-production operation. The study shows that (1) formation pressure tends to accumulate near the fault zone due to the low permeability, and the interface of the reservoir layer, cap layer, and fault zone is the seal weak position of UGS; (2) the response of fault slip is driven by the injection-production rate and the reservoir pressure. There is a significant coupling relationship between the fault slip value and the accumulated injection gas volume; (3) the intelligent prediction approach can capture the nonlinear dynamic characteristics of slip tendency accurately, and it exhibits good prediction performance and generalization ability under the new operating condition. This study effectively assesses the dynamic risk for fault slip of depleted hydrocarbon reservoir UGS during the long-term injection-production procedure. It provides an effective technical approach for fault slip tendency analysis and injection-production process optimization, which is important for the sustainable operation of UGS reducing the risk of seal failure and supporting gas storage security. Full article

The Longmen Shan Fault Zone is marked by intricate geological structures and frequent seismic activity, which gives rise to persistent seismic hazards. To tackle the challenge of capturing the multi-temporal characteristics of earthquake frequency, this study combines machine learning with time series analysis to conduct earthquake frequency prediction research. Based on the 1970–2023 seismic dataset from the China Earthquake Networks Center, the seismic records were structured into four temporal scales: daily, weekly, monthly and quarterly. The minimum completeness magnitude (Mc) was determined as M3.0 by applying the G–R relationship. After conducting white noise tests and data normalization, ACF and PACF were utilized to select the optimal time-step parameters for the LSTM model. Considering the inherent characteristics of the seismic data, the 99th percentile of the frequency series was set as the threshold, and an auxiliary parameter was introduced to label high-frequency earthquake days for the construction of the LSTM model. Upon the completion of LSTM model fitting, heteroscedasticity tests were performed on the residuals between the predicted and observed values. Confirming the presence of significant heteroscedasticity, the GARCH model was incorporated to process these residuals, thus establishing a complete LSTM-GARCH coupled model. The results reveal that seismic activity in this region is normally low-frequency with occasional high-frequency occurrences. The proposed model achieves R² above 0.80 across all four temporal scales, accompanied by superior performance in all error metrics. This study validates that the LSTM-GARCH model can effectively extract the multi-scale patterns of earthquake frequency, with the best performance observed at the daily scale. Ablation experiments further demonstrate that this coupled model outperforms both the ARIMA and single LSTM models, providing reliable technical support for short-to-long-term earthquake prediction and regional disaster risk assessment. Full article

Unlike traditional power systems, the heterogeneous energy support of electric–gas regional distribution networks brings new challenges to resilience assessment. On the basis of identifying N-k fault uncertainty risks, establishing a resilience assessment methodology is one of the important issues in resilience research. Existing reliability assessment methods cannot accurately quantify resilience under N-k extreme fault scenarios. To address this limitation, we propose a non-simulation resilience assessment method. The approach can simultaneously quantify the dynamic interactions of heterogeneous energy flows and the impact of repair process time uncertainty on system resilience under extreme fault scenarios. Specifically, the resilience indexes are established by combining the load outage and mathematical expectation during/after the extreme fault and applying probabilistic knowledge to express the N-k load outage event, so as to effectively offset the data scarcity due to the limited N-k fault data samples. The internal consistency and parametric responsiveness of the proposed non-simulation method are demonstrated through systematic case comparisons under varying failure rates, repair times, and coupling conditions. Full article

Permanent ground deformation caused by fault movement threatens the safe operation of buried pipelines. Accurate fragility assessment of buried pipelines subjected to faulting is essential for pipeline design and risk management. However, buried pipelines exhibit nonlinear mechanical responses due to the coupled effects of multiple factors. Moreover, the effects of key parameters remain insufficiently quantified, limiting the accuracy and engineering applicability of existing fragility assessments. In this study, a three-dimensional finite element model incorporating large deformation and nonlinear pipe–soil interaction is developed and validated against representative experimental data. Using this model, numerical simulations are performed for 352 parameter combinations covering fault type, dip angle, burial depth, soil type, and pipe material. Nonlinear regression of the simulation results yielded predictive models for pipeline peak axial strain under normal-slip and reverse-slip faulting. A fragility framework is then established with fault displacement as the intensity measure, and fragility curves are derived for both faulting modes. The predicted peak axial strains agree with the finite element results: 78.6% (normal-slip) and 72.5% (reverse-slip) of predictions fall within ±20% error. The fragility curves enable quantitative estimation of fault-displacement thresholds. In the case study, the intact-to-damage displacement threshold is approximately 0.6 m for normal-slip faults but approximately 0.2 m for reverse-slip faults, indicating a higher failure likelihood under reverse-slip faulting. Within the investigated parameter ranges, the fault dip angle is the most significant factor affecting the pipeline failure probability for both normal-slip and reverse-slip faulting. Sandy soil and greater burial depth substantially increase the probability of moderate-to-severe damage, whereas higher steel grade increases the displacement threshold for transition from intact to failure. This study provides a rapid quantitative tool and a theoretical basis for pipeline design and risk quantification of buried pipelines in fault zones. Full article

User experience constitutes an essential element of effective interaction design. To enhance the user experience, it is necessary to identify the primary root causes related to human errors and then initiate actionable interventions for the high-priority root causes. Risk assessment of human errors in interaction design is characterized by subjective uncertainties and a lack of precise numerical values. However, very little attention has been given to these issues when assessing human errors. In this paper, a fuzzy fault tree analysis approach is proposed to execute risk assessment of human errors in interaction design. First, the system is analyzed, and a fault tree diagram is constructed. Subsequently, probabilities for each basic event are derived through the combination of fuzzy set theory and the similarity aggregation method. Then, the minimal cut sets (MCSs) are identified. Following this, the failure probability of the top event is determined, and the MCSs are ranked in accordance with their respective importance values. Finally, the results are evaluated, and the recommendations for corrective actions are provided for the high-priority MCSs. A practical case study of the in-vehicle information system in heavy trucks was conducted to demonstrate the feasibility and effectiveness of the proposed approach. The findings suggest that this approach can effectively address the subjective and even subconscious aspects of risk assessment related to human errors in interaction design, providing accurate results for risk evaluation. Furthermore, it can effectively address the situations where the probabilities related to human errors are imprecise, inadequate, and ambiguous. The proposed approach can be universally applied to enhance the user experience in interaction design. Full article