The increase in the rate of global warming directly affects the safety of buildings and structures on permafrost. The research presents the problem of reliability analysis for piles on permafrost soils by the stability criterion under the action of tangential forces of frost heaving. The two groups of piles reliability analysis methods are developed: for complete and limited statistical data about random variables in the models of limit states. Approximations of the dependences of the design resistances of permafrost soils to the shear along the freezing surface on the temperature are proposed. It can be used to estimate the freezing force that keeps the pile from buckling. The method for reliability monitoring and durability forecasting has been developed for piles on permafrost soils. The proposed method makes it possible to reasonably reduce the cost of reliability analysis in the initial periods, which can increase the number of buildings and structures being inspected by the similar costs.

Introduction. The scientific review article addresses the approaches to the modeling of random variables performed as part of the structural reliability analysis of elements provided that some statistical information missing (limited). The objectives of the research include the statement of the problem of the probabilistic structural reliability analysis subject to incomplete statistical data, the study of the development of approaches to the generation of models of random variables within the framework of this problem, as well as the assessment of the current state of affairs in this field and some development prospects for the coming years. Materials and methods. The principal model of a random variable, considered in the article, represents a p-box (pro­bability box) model. A p-box is an area of possible functions of distributed probabilities of a random variable generated by the two boundary functions of the probability distribution. The article addresses p-boxes generated using the fuzzy set theory, the probability theory, Kolmogorov–Smirnov boundaries, etc. Results. The approaches, considered in the article, are illustrated by the numerical examples of p-boxes that use the same statistical data. P-boxes, based on the probability theory, allow to accurately simulate a random variable; however, a priori information about the type of the distribution function is needed. P-boxes, based on the possibility theory, can be used even if an extremely small amount of statistical data is available, and it is also necessary to carefully address the issue of assigning the cutoff (risk) level. P-boxes based on the Chebyshev inequality and the Kolmogorov–Smirnov statistics allow to effectively simulate random variables regardless of the type of the probability distribution. However, these approaches may generate an assessment that is too uninformative for decisions to be made in a number of tasks. Conclusions. The choice of a probabilistic model of a random variable for the further reliability analysis of structural elements will depend on the amount and type of statistical data obtained about the random variable. In particular cases, if the statistical information represents a subset of intervals, special approaches based on the Dempster–Shafer theory can be used. A promising and relevant method that underlies both the development of probabilistic models of random variables and the analysis of structural reliability in case of missing statistical information encompasses the employment of numerical modeling methods that employ surrogate models (kriging, Bayesian networks, interval predictors, etc.) and neural network algorithms.

Introduction. The development of probabilistic approaches to the assessment of mechanical safety of bearing structural elements is one of the most relevant areas of research in the construction industry. In this research, probabilistic methods are developed to perform the reliability analysis of steel truss elements using the p-box (probability box) approach. This approach ensures a more conservative (interval-based) reliability assessment made within the framework of attaining practical objectives of the reliability analysis of planar trusses and their elements. The truss is analyzed as a provisional sequential mechanical system (in the language of the theory of reliability) consisting of elements that represent reliability values for each individual bar and truss node in terms of all criteria of limit states. Materials and methods. The co-authors suggest using p-blocks consisting of two boundary distribution functions designated for modeling random variables in the mathematical models of limit states performed within the framework of the truss reliability analysis instead of independent true functions of the probability distribution of random variables. Boundary distribution functions produce a probability distribution domain in which a true distribution function of a random variable is located. However this function is unknown in advance due to the aleatory and epistemic uncertainty. The choice of a p-block for modeling a random variable will depend on the type and amount of statistical information about the random variable. Results. The probabilistic snow load model and the numerical simulation of tests of steel samples of truss rods are employed to show that p-box models are optimal for modeling random variables to solve numerous practical problems of the probabilistic assessment of reliability of structural elements. The proposed p-box snow load model is based on the Gumbel distribution. The mathematical model used to perform the reliability analysis of planar steel truss elements is proposed. The co-authors provide calculation formulas to assess the reliability of a truss element for different types of p-blocks used to describe random variables depending on the amount of statistical data available. Conclusions. The application of statistically unsubstantiated hypotheses for choosing the probability distribution law or assessing the parameters of the probability distribution of a random variable leads to erroneous assessments of the reliability of structural elements, including trusses. P-boxes ensure a more careful reliability assessment of a structural element, but at the same time this assessment is less informative, as it is presented in the form of an interval. A more accurate reliability interval requires interval-based assessments of distribution parameters or types of p-boxes applied to mathematical models of the limit state, which entails an increase in the economic and labor costs of the statistical data.

Relevance. Loads on structures are complex stochastic elements that include several types of uncertainties simultaneously. The article describes a probabilistic approach to the load modeling on structural covers taking into account limited statistical data, when the parameters of distribution functions are presented in an interval form. The aim of the work is development of an approach to modeling the probabilistic distribution of random load on the structural surface in conditions of limited (incomplete) statistical information about the design load. Methods. The probability distribution of a particular type of loading is represented as p-boxes (probability boxes). A numerical example shows an algorithm for determining a p-box consisting of a sum of p-boxes that characterize different loads with different boundary distribution functions. Results. Based on the proposed approach, it is possible to define the intervals of normative and design loads with a given confidence level, to estimate the failure probability of structural elements, to assess the risk of an accident and also to make selection for structural element cross-section at the target level of reliability.

The article describes the approach to evaluation of a friction pile bearing capacity based on the parabolic distribution of a skin friction in multi-layer soil bases. The design equationsare obtained for evaluated the ultimate load on an axial loaded pile in multi-layer soil using the new design scheme. The advantage of the proposed approach is to obtain some experimental parameters that take into account the actual interaction of the pile and soil on the construction site. Negative friction forces (from the reaction force under the pile end) negatively affect the pile bearing capacity. The numerical example is given for a friction pile in the soil base with two layers. The proposed equation also allows calculating various parameters: the soil stress under the piletoe, the pile effective length, relative deformations along the pile, etc.