Technical University of Civil Engineering of Bucharest

This study proposes a modeling framework based on piecewise constant regression with a Periodic Autoregressive (PAR) remainder. Model complexity is controlled using Rissanen’s Minimum Description Length (MDL) criterion, while Fourier-based compression reduces dimensionality without compromising likelihood, improving computational efficiency. A multi-island Genetic Algorithm (GA) jointly estimates changepoint (CP) configurations and seasonal order. Monte Carlo (MC) experiments under Dobrogea conditions show reliable detection of all three change points when shifts exceed 1.5 innovation standard deviations. Applied to Medgidia precipitation (1965–2019), the method identifies an early shift while retaining a parsimonious AR(1) structure. By separating true climatic shifts from noise, the framework provides a robust basis for water resource assessment and infrastructure planning.

Fractional power series in several variables are investigated within the framework of fractional calculus. By employing the Riemann-Liouville fractional integral and Caputo derivative, a generalized Taylor’s formula for multivariable functions is established, extending previously known results for the single-variable case. A sufficient condition for representing a multivariable function as a fractional power series is stated and a framework for obtaining approximate solutions of fractional partial differential equations is provided. In addition, the paper presents a method for determining restricted local extrema of multivariable functions. Illustrative examples are included.

This study presents a seismic risk assessment of the residential building stock located in the Ploiesti-Nord neighbourhood of Ploiesti, Romania, an area significantly impacted by the 1940 and 1977 Vrancea intermediate-depth earthquakes. Site conditions were investigated based on various methods in the literature. The neighbourhood's residential buildings, constructed prior to 1977, primarily consist of five- and ten-story structures built using either masonry or reinforced concrete systems. Unlike previous studies in Bucharest, which evaluated seismic risk at the level of the city's entire building stock, this research focuses on structural typology-specific risk metrics in Ploiesti-Nord, addressing a critical gap in localized seismic risk assessment. The seismic hazard of Ploiesti is exclusively influenced by the Vrancea intermediate-depth source and is comparatively higher than that of Bucharest. Field inspections revealed localized structural interventions still visible on several buildings, though many have undergone thermal rehabilitation. Findings indicate that the highest relative losses and damage levels occur in five-story unreinforced masonry buildings and ten-story reinforced concrete shear wall structures. Conversely, the lowest risk metrics were observed in five-story large panel buildings. Notably, the five-story reinforced or confined masonry buildings, due to their large number of apartments, contribute most significantly to the total seismic losses in the study area.

Changepoint (CP) detection in climate time series is challenging due to seasonality, trends, and serial correlation. This study introduces a method that combines regression modeling with autoregressive error structures to detect abrupt regime shifts. The model breaks down the series into seasonal means, a linear trend, and shift offsets, while capturing seasonally varying autocorrelation using a periodic autoregressive process (PAR). Parameters are estimated via the iterative Cochrane–Orcutt method and Yule–Walker equations, and the model selection is guided by the Minimum Description Length principle (MDL). A multi-island genetic algorithm (GA) searches for optimal CPs and autoregressive (AR) orders. Validation on synthetic data shows the approach reliably detects CPs across varying shift magnitudes and autocorrelation levels. A homogenization procedure for the monthly series from a network of meteorological stations across a study region is also proposed and built on the aforementioned GA approach to minimize an MDL objective function. • Proposing a Minimum Description Length methodology to detect and correct changepoints of hydrological time series. • Introducing a multi-island genetic algorithm to select the changepoint locations and the autoregressive order. • Performing the homogenization of the precipitation series.

Height systems form a mathematical interface between physical geodesy, engineering surveying, and digital cartography. Although satellite positioning efficiently provides ellipsoidal heights, practical infrastructure, mapping, hydrological, and monitoring tasks require gravity-related heights that are compatible with national vertical datums. This paper develops a denominator-based framework in which dynamic, orthometric, and normal heights are interpreted as metric realizations of a common geopotential number. Starting from the line-integral definition of geopotential, the principal height formulae are derived; first-order sensitivities to geoid undulation, height anomaly, and mean gravity are established; and uncertainty propagation is analyzed. A Romania-oriented computational experiment, explicitly defined as a representative model-behavior study rather than an official national adjustment, uses lowland, plateau, and mountain-influenced settings consistent with the Constanta and Black Sea 1975 normal-height context. The results show that modeled normal-orthometric separations remain below 3 mm in representative low-relief locations but increase to 17.1 mm in Suceava, 29.5 mm in Cluj-Napoca, and 85.6 mm in the mountain-influenced Brasov case. The dynamic-normal differences remain small at low elevations but become systematic where the normal-gravity denominator departs from the selected reference value. The Monte Carlo experiment indicates standard uncertainties of approximately 4.2–4.4 cm for normal heights when a 1.5 cm ellipsoidal-height uncertainty and a 4.0 cm quasi-geoid uncertainty are assumed. A single-point covariance example gives 31.7 mm for normal-height conversion and 36.9 mm for orthometric-height conversion under the stated correlation assumptions. The transformation-surface comparison further shows that a quadratic local model reduces leave-one-out cross-validation error from 16.73 mm to 9.95 mm relative to a planar model in the synthetic Romania-oriented scenario. The study concludes that the height-system label must be treated as part of the mathematical model and metadata, and it proposes a geopotential-centered computational pathway for survey adjustment, uncertainty control, and metadata-safe geospatial export.