Statistical Modeling for Forecasting Pipeline Reliability: Postwar Reconstruction Strategies for Heating Networks in Ukraine

Statistical models have been formulated to analyze the operational problem and forecast the reliability of Ukraine’s urban heating pipeline network, thereby fostering sustainable territorial development. Utilizing statistical modeling methodologies, these models establish the dependability of heat pipelines and construct predictive statistical models to investigate the interplay between reliability parameters of primary heat pipelines and their operational lifespans across diverse types of damage scenarios. The reliability parameter serves as a crucial indicator of dependability, with the statistical reliability models articulated through regression ratios. This methodology unearths the varying dynamics of primary heat pipelines, involving their operational durations and distinct damage profiles. The proportional distribution of distinct types of damage, such as leaks, ruptures, valve impairments, and other forms of deterioration, is also readily examined. The ramifications of this chapter extend to facilitating the assessment of both predictive and extant reliability outcomes, stratified by damage types in heat pipelines. By applying the developed statistical models, the projected number of existing and projected damages, categorized by the specific types of damage afflicting primary heat pipelines, is calculated. This examination holds promise in forecasting reliability trends for pipelines within alternative systems and networks. In addition, this research holds immense practical value in the backdrop of postwar reconstruction in Ukraine. The country’s pressing demand for reevaluation, reparation, reconstruction, and strategic reconfiguration of a substantial portion of its pipeline network underscores the research’s pertinence. Moreover, pipelines in Ukraine underpin the country’s infrastructure framework, underscoring their indispensable role.