The study titled "Uncertainty Modeling of Thermal Fields in Underground Cable Networks Using Fuzzy Inference Systems" presents a novel approach to analyzing and predicting the thermal behavior of underground power cables in non-homogeneous soils. By employing fuzzy inference systems, this work captures the inherent variability in soil thermal properties, cable loading conditions, and environmental influences. The proposed model integrates expert knowledge and linguistic variables to offer a more flexible and adaptive method for estimating thermal fields around buried cables. This approach enhances the accuracy of temperature predictions and improves the decision-making process for optimizing cable layout and material selection. The fuzzy system accommodates imprecise data without relying solely on deterministic values, enabling more resilient thermal management. Simulation results demonstrate the system’s capability to deliver robust temperature forecasts, aiding in the prevention of overheating and prolonging the operational life of underground electrical infrastructure. This framework is a valuable contribution to smart power grid design and thermal optimization.

The implementation of fuzzy inference systems (FIS) for uncertainty modeling in underground cable networks presents several challenges. One of the primary issues lies in accurately defining membership functions for soil properties, cable loading, and environmental conditions, which are often site-specific and influenced by seasonal variability. Another challenge is the integration of expert knowledge into the fuzzy rule base, which can be subjective and may introduce inconsistencies if not carefully validated. Additionally, the lack of high-resolution field data can limit the calibration and validation of the FIS model, affecting prediction accuracy. Computational complexity also arises when dealing with large-scale cable networks and multiple interacting variables. Moreover, translating the fuzzy model outputs into actionable insights for real-time thermal management can be difficult, especially in systems where quick responses are critical. Finally, aligning fuzzy-based models with conventional engineering design standards and regulatory frameworks remains a key hurdle for widespread adoption in practical underground cable system planning. This theme encompasses advanced fuzzy inference techniques, soft computing approaches, and intelligent systems for addressing uncertainties in the thermal analysis and optimization of underground cable networks. It invites contributions that explore modeling, simulation, predictive diagnostics, and decision support systems under variable soil, environmental, and load conditions. Potential topics included, but not limited to:

1. Fuzzy logic-based thermal simulation for underground power cables in heterogeneous soils

2. Hybrid fuzzy-neural models for predicting cable temperature under load variability

3. Application of type-2 fuzzy systems in soil thermal property estimation

4. Uncertainty quantification in cable ampacity calculations using soft computing

5. Fuzzy rule-based systems for dynamic thermal rating of underground cables

6. Integration of fuzzy inference with finite element models for subsurface heat transfer

7. Modeling the impact of soil moisture uncertainty on cable thermal behavior

8. Fuzzy logic controllers for real-time thermal monitoring of underground cables

9. Multi-criteria decision analysis using fuzzy sets for thermal backfill material selection

10. Risk assessment of underground cable overheating using fuzzy probability models

Thermal safety of energetic materials is a critical concern in the design, storage, transportation, and application of high-energy compounds such as propellants, explosives, and pyrotechnics. Energetic materials are highly reactive and can undergo violent decomposition under thermal stimulation, which poses a significant hazard in accidental fire scenarios. When exposed to external heat flux, these materials may experience complex processes including melting, pyrolysis, gas generation, ignition, and combustion. The onset of self-sustaining reactions or thermal runaway is often linked to the generation and accumulation of heat exceeding the material’s heat dissipation capacity. During thermal decomposition, energetic materials can release substantial quantities of heat and gas, contributing to pressure buildup and secondary hazards. Therefore, the study of their thermal decomposition mechanisms, safety thresholds, and combustion behavior is essential for assessing the risks and preventing catastrophic incidents. Understanding the thermal safety characteristics of energetic materials is fundamental for the safe lifecycle management and regulation of these hazardous substances. Topics of interest include, but are not limited to: decomposition kinetics and reaction pathways of energetic materials, fire and explosion risk evaluation, thermal stability enhancement strategies, and advanced modeling of thermally induced events.