A new transition curve-3 (NTC-3), joining two straight lines by providing second-degree contact related to the properties of vehicle–road system without the necessity of a circular arc, is presented. The NTC-3 is offered by curvature and superelevation functions and is compared with the new generation transition curves-1 and -2 (NTC-1, NTC-2) and spiral curves. The properties of vehicle–road system, represented by function of lateral change of acceleration (LCA), are examined for these curves. Three criteria are taken into account to compare the curves. The NTC-3 and NTC-1 are compared in five-different motion models: model with constant velocity, model with positive acceleration, model with negative acceleration, model with negative acceleration – positive acceleration, and model with positive acceleration – negative acceleration. Examination of three criteria shows that NTC-3 is superior to the other curves on the basis of vehicle–road system.Key words: route design, transition curve, vehicle–road system, curvature, lateral change of acceleration, superelevation, motion model.

The Black Sea occurs within the Anatolian sector of the Alpine-Himalayan orogenic system. In this region northward moving African and Arabian plates collide with Eurasian plate. From this collision the Anatolian block moves westward with a rotation pole located approximately north of Sinai peninsula. Tectonic styles and rates in the circum Black Sea and along the Crimea have been poorly known. A GPS project was initiated in 1995 with the collaboration between Istanbul Technical University, MIT and Joint Institute of Physics of the Earth (Moscow). To carry out the project, two GPS campaigns were performed. Data have been analysed by the well-known GPS processing program, GAMIT which is a comprehensive GPS analysis package, and GLOBK, a Kalman filter. This paper presents the important outputs from the two GPS campaigns and gives suggestions for the future investigations in the region. The important outcome of the project is that the N-S motions along mostly in the Eastern margin of the Black Sea are in a few mm/year, such as SINO, a southern coast site, with a rate of 1.4 ± 1.7 mm/year in NW direction, and GELE, a northern coast site, with a rate of 2.2 ± 2.8 mm/year in SE direction, while the velocities in the Anatolian region are approximately 10-20± 3-5 mm/year.

In this paper, a new transition curve to be used in the design of the horizontal geometry of routes has been examined. This curve joins two straight lines with a single element. It is an alternative curve to the well-known classical transition curve, which is formed by spiral curve–circular arc spiral curve. In order to compare the suggested transition curve with the classical transition curve in terms of the vehicle-road dynamics, the curvature and superelevation functions of both curves are derived, and funcions of the lateral change of acceleration of both curves are obtained and illustrated graphically for the seven selected motion models. The comparisons that take into account the discontinuities in the form of jumps in the graphics of the lateral change of acceleration have shown that the new transition curve is superior to the classical transition curve for all seven motion models.

Layout is one of the most important missions of the surveying engineer, which aims to carry out the designed horizontal and vertical geometries of an engineering structure by satisfying the required accuracies. It is necessary to satisfy the required accuracies through the “achieved point standard deviation” which is defined by the product of the errors derived from known point coordinates and the layout measurements. In order to satisfy the required accuracy, the achieved accuracy should be smaller than the required one. The mission of the surveying engineer is planning the layout process by taking into consideration the required and the achieved standard deviations. In this paper, the planning process concerning the measurement error components is explained. The issues regarding the network design, the measurements, and the selection of the proper instruments for the layout are explained to make optimal decisions. The given decision making methods in this study are rather valuable in the special applica...

This study addresses the potential of machine learning (ML) algorithms in geophysical and geodetic research, particularly for enhancing GNSS time series analysis. We employed XGBoost and Long Short-Term Memory (LSTM) networks to analyze GNSS time series data from the tectonically active Anatolian region. The primary objective was to detect discontinuities associated with seismic events. Using over 13 years of daily data from 15 GNSS stations, our analysis was conducted in two main steps. First, we characterized the signals by identifying linear trends and seasonal variations, achieving $R^2$ values of 0.84 for the XGBoost v.2.1.0 model and 0.81 for the LSTM model. Next, we focused on the residual signals, which are primarily related to tectonic movements. We applied various threshold values and tested different hyperparameters to identify the best-fitting models. We designed a confusion matrix to evaluate and classify the performance of our models. Both XGBoost and LSTM demonstrated robust performance, with XGBoost showing higher true positive rates, indicating its superior ability to detect precise discontinuities. Conversely, LSTM exhibited a lower false positive rate, highlighting its precision in minimizing false alarms. Our findings indicate that the best fitting models for both methods are capable of detecting seismic events (Mw ≥ 4.0) with approximately 85% precision.