Search Results (7)

The study presents an engineering solution for maintaining traffic flow during road and utility operations, such as trench excavation. The analysis of existing organizational and technical approaches, along with global experience in temporary bridge use, showed that most foreign analogs were developed for military purposes and are not fully suitable for urban conditions in Kazakhstan and CIS countries. As an alternative solution, the development of a mobile overpass adapted for operation in dense urban environments is proposed. The present study continues earlier research focused on optimizing the placement of mobile overpass supports while accounting for the nonlinear deformation behavior of the soil foundation. At the previous stage, a rational distance between the supports and the trench edge was substantiated, and horizontal soil deformations were reduced. In the current study, the primary focus is on the design of the undercarriage, which determines the mobility, stability, and operational feasibility of the structure. A morphological analysis and synthesis method is applied to select a rational configuration of the undercarriage. A 3D model and a 1:4 scale test bench were developed, followed by load tests of 50–200 kg. The maximum deflection of −1.19 mm at 200 kg demonstrated an almost linear deformation pattern. The constructed regression model ($R^2=0.97$) confirmed the accuracy and reliability of the design. The developed mobile overpass is versatile, cost-effective, and practical, improving the resilience of urban transport infrastructure, reducing traffic congestion during roadworks, and creating a foundation for serial production in Kazakhstan and CIS countries. Full article

This study addresses the problem of traffic congestion in large cities caused by long-term repairs of underground utility networks. An innovative mobile overpass is considered, which combines the functions of a vehicle and a temporary bridge, allowing passenger cars up to 3.5 t to pass directly over repair trenches without detours. The research focuses on optimizing the placement of overpass supports relative to the trench edge to reduce soil deformation and prevent trench wall instability. A numerical methodology is developed in ANSYS Workbench that integrates finite element analysis of the soil-support system with parametric optimization using the nonlinear Drucker–Prager elastoplastic model. The soil parameters are obtained from oedometer compression tests (KPr-1M) and direct shear tests (PSG-2M) on clayey soils and then used to calibrate the numerical model. The optimization results show that the optimal distance from the trench wall to the overpass support is $L_{\min } = 2.78$ m, which is 13.5% greater than the initial design value. This modification reduces the maximum horizontal displacement of the trench wall by more than a factor of two and ensures compliance with the displacement criteria. Comparison between experimental and numerical compression curves yields an average deviation of 37.55%, with errors below 5% at higher stress levels, confirming that the Drucker–Prager model is suitable for engineering optimization of mobile overpass support placement on similar soils. The proposed methodology can be applied to the design and verification of temporary bridge systems operating above utility trenches in urban environments. Full article

This paper presents results from numerical simulations validated by experimental results related to the effects of dynamic soil-structure interaction (DSSI) on the dynamic response of bridges. An in-service overpass was shaken using the T-Rex, a large-amplitude mobile shaker from the National Hazards Engineering Research Infrastructure (NHERI) facilities. Studies implementing Finite Element Modeling (FEM) to develop time histories, response spectra, and eigenmodes were conducted in a forward-modeling problem setup. Two models were created to assess the DSSI effects on the dynamic response of the bridge. One model included elements that incorporate DSSI effects, while the other had fixed-base boundary conditions. The response from the DSSI FEM model matched the field results better than the fixed-base model in terms of the peak response amplitudes and identified natural frequencies and modes. The influence of a series of factors, such as the soil shear wave velocity, bridge height, bridge foundation embedment depth, and the corresponding rigidity, slenderness, and embedment ratios, on the bridge response is presented. Full article

In this paper, simulation and experimental tests are reported for a hybrid robot being used for indoor and outdoor inspections. Automatic or tele-operated surveys can be performed by mobile robots, which represent the most efficient solution in terms of power consumption, control, robustness, and overall costs. In the context of structures and infrastructure inspection, robots must be able to move on horizontal or sloped surfaces and overpass obstacles. In this paper, the mechatronic design, simulations, and experimental activity are proposed for a hybrid robot being used for indoor and outdoor inspections, when the environmental conditions do not allow autonomous navigation. In particular, the hybrid robot is equipped with external and internal sensors to acquire information on the main structural elements, avoiding the need for experienced personnel being directly inside the inspection site, taking information from the environment and aiding the pilot to understand the best maneuvers/decisions to take. Given the current state of research and shortcomings worldwide, this paper discusses inspection robots taking into account the main issues in their use, functionality and standard systems, and how internal sensors can be set in order to improve inspection robots’ performances. On this basis, an illustrative study case is proposed. Full article

The quality of geospatial data collection depends, among other things, on the reliability and efficiency of the GNSS receivers or even better integrated GNSS/INS systems used for positioning. High-precision positioning is currently not only the domain of professional receivers but can also be achieved by using simple devices, including smartphones. This research focused on the quality of 2D and 3D kinematic positioning of different geodetic and low-cost GNSS devices, using the professional mobile mapping system (MMS) as a reference. Kinematic positioning was performed simultaneously with a geodetic Septentrio AsteRx-U receiver, two u-blox receivers—ZED-F9P and ZED-F9R—and a Xiaomi Mi 8 smartphone and then compared with an Applanix Corporation GPS/INS MMS reference trajectory. The field tests were conducted in urban and non-urban environments with and without obstacles, on road sections with large manoeuvres and curves, and under overpasses and tunnels. Some general conclusions can be drawn from the analysis of the different scenarios. As expected, some results in GNSS positioning are subject to position losses, large outliers and multipath effects; however, after removing them, they are quite promising, even for the Xiaomi Mi8 smartphone. From the comparison of the GPS and GNSS solutions, as expected, GNSS processing achieved many more solutions for position determination and allowed a relevant higher number of fixed ambiguities, even if this was not true in general for the Septentrio AsteRx-U, in particular in a surveyed non-urban area with curves and serpentines characterised by a reduced signal acquisition. In GNSS mode, the Xiaomi Mi8 smartphone performed well in situations with a threshold of less than 1 m, with the percentages varying from 50% for the urban areas to 80% for the non-urban areas, which offers potential in view of future improvements for applications in terrestrial navigation. Full article

The use of Unmanned Aerial Vehicles (UAVs) for surveying is at the forefront of their use in the Architectural Engineering and Construction (AEC) industry. UAVs make accessing hard-to-reach construction regions simpler and more cost-effective because of their small size, ease of mobility, and the wealth of information given by their integrated sensors. Accordingly, their use is thriving in different AEC sectors such as the management and inspection of engineering facilities such as concrete bridges. Overpass bridge engineering inspections are still applied using high accuracy surveying instruments in situ to ensure meeting the quality standards of construction. One important application is to measure the bridge pier caps centerline fitting using total stations, which is costly in terms of time and labor. Therefore, in this article, a new approach based on consumer-grade UAV imaging is proposed for replacing the traditional surveying techniques which are expected to improve automation and reduce time and cost. The proposed method utilized a sequence of processes on the UAV point clouds of the bridge concrete pier caps to finally extract the pier pads center and check their alignment. In two experiments, point clouds are created using DJI Phantom 3 images taken over bridge pier projects under construction, and concrete pad centers are then estimated and compared to the reference total station measurements. The results of both tests reveal the ability of the proposed method to attain the required accuracy for the pads’ alignment, as the root mean square error (RMSE) is one centimeter and two centimeters for the first and second tests, respectively. In addition, the new approach can reduce implementation time and the project budget. Full article

With self-provisioning of resources as premise, dew computing aims at providing computing services by minimizing the dependency over existing internetwork back-haul. Mobile devices have a huge potential to contribute to this emerging paradigm, not only due to their proximity to the end user, ever growing computing/storage features and pervasiveness, but also due to their capability to render services for several hours, even days, without being plugged to the electricity grid. Nonetheless, misusing the energy of their batteries can discourage owners to offer devices as resource providers in dew computing environments. Arguably, having accurate estimations of remaining battery would help to take better advantage of a device’s computing capabilities. In this paper, we propose a model to estimate mobile devices battery availability by inspecting traces of real mobile device owner’s activity and relevant device state variables. The model includes a feature extraction approach to obtain representative features/variables, and a prediction approach, based on regression models and machine learning classifiers. On average, the accuracy of our approach, measured with the mean squared error metric, overpasses the one obtained by a related work. Prediction experiments at five hours ahead are performed over activity logs of 23 mobile users across several months. Full article