Zenon Medina-Cetina

Robot-Assisted Bridge Inspection

The Center for Robot-Assisted Search and Rescue (CRASAR®) deployed a customized AEOS man-portable unmanned surface vehicle and two commercially available underwater vehicles (the autonomous YSI EcoMapper and the tethered VideoRay) for inspection of the Rollover Pass bridge in the Bolivar peninsula of Texas in the aftermath of Hurricane Ike. A preliminary domain analysis with the vehicles identified key tasks in subsurface bridge inspection (mapping of the debris field and inspecting the bridge footings for scour), control challenges (navigation under loss of GPS, underwater obstacle avoidance, and stable positioning in high currents without GPS), possible improvements to human-robot interaction (having additional display units so that mission specialists can view and operate on imagery independently of the operator control unit, incorporating 2-way audio to allow operator and field personnel to communicate while launching or recovering the vehicle, and increased state sensing for reliability), and discussed the cooperative use of surface, underwater, and aerial vehicles. The article posits seven milestones in the development of a fully functional UMV for bridge inspection: standardize mission payloads, add health monitoring, improve teleoperation through better human-robot interaction, add 3D obstacle avoidance, improve station-keeping, handle large data sets, and support cooperative sensing.

Stochastic design of an early warning system

Early warning systems (EWS) are monitoring devices designed to avoid or to mitigate the impact posed by a threat. Since EWS are time-sensitive or stochastic, it is necessary to develop a design methodology that defines the integration of the participating monitoring information sources, the identification of potential warning thresholds, and the assessment of the associated risk within an explicit causal analysis. This paper proposes a framework for a stochastic design of an early warning system, introducing a risk measure as the reference variable that encapsulates the different effects retrieved by the monitoring instruments. Within a decision-making framework the risk measure serves as the index for defining the system warning thresholds. A Bayesian approach is proposed as a suitable tool for integrating and updating the joint states of information and the warning levels as the information flows through the warning system.

Risk Assessment of a Transmission Line Insulation Breakdown Due to Lightning and Severe Weather

The transmission line insulation breakdown is typically assessed by performing insulator chain tests, and by conducting network modeling and simulation studies incorporating various stress conditions. This paper investigates how historical data coming from the lightning detection network and measurement stations capturing associated weather conditions can be utilized to provide a predicted assessment of risk of insulation breakdown for a given exposure and associated weather threats. The proposed analysis is enabled by the space and time correlation of the transient data recorded in the substations at the end of the lines, as well as by the assimilation of data obtained from the lightning detection network and weather stations. The proposed modeling and simulation tools are utilized to facilitate the time and space correlation analysis that leads to predication of the risk.

Electrical resistivity imaging of unknown bridge foundations

Unknown bridge foundations pose a significant safety risk due to stream scour and erosion. Records from older structures may be non-existent, incomplete or incorrect. We evaluate 2D and 3D electrical resistivity imaging (ERI) as a means to reliably identify the depth of unknown bridge foundations. A survey procedure is described for mixed terrain/water environments in the presence of rough terrain. Some electrodes are installed on the stream banks while others are adapted for underwater use. Tests were conducted at five field sites, including three roadway bridges, a geotechnical test site and a railway bridge, containing drilled shafts and spread footings of both known and unknown depth extent. The 2D data acquisition was carried out in the dipole-dipole configuration. The 2D ERI method resolved the shape and depth extent of the larger bridge foundations but, with less accuracy, the shape and depth extent of the smaller foundations. The 3D ERI method is timeconsuming and does not add sufficient additional value over 2D ERI to become a practical tool for unknown bridge foundation investigations. The 2D ERI method is a cost-effective geophysical method that is relatively easy to use by bridge engineers.

Probabilistic Calibration of a Dynamic Model for Predicting Rainfall-Controlled Landslides

AbstractItaly has a number of regions with mid to high vulnerable areas from a hydrogeological point of view. The causes are the result of both the fragility of territory and the anthropic influence on its continuous modifications. A quantitative landslide risk analysis is then necessary to avoid or reduce human life and property losses. In particular, the prediction of landslide occurrence should be estimated taking into account the uncertainties affecting the analysis process. In this paper, a specific type of landslide, triggered by rainfall and characterized by the viscous behavior of soil, is discussed and analyzed. The goal is to illustrate the applicability of a probabilistic approach, based on Bayesian theorem, which aims at developing an advanced analysis, and to predict slow-slope movements. The proposed methodology relies on the probabilistic calibration of a well-defined, viscoplastic-dynamic model that is able to predict the soil mass displacement evolution from groundwater level inputs and r...

Joint states of information from different probabilistic geo-profile reconstruction methods

Development of technologies for site characterization has grown at a faster pace compared to the development of decision-making methods required for the assimilation of inferences they generate. In the case of geophysical surveying, such dephase adds to the dependency on the use of experts judgment in the interpretation of geophysical mappings. A systematic assimilation of this type of geo-surveying evidence is required, in particular for the integration of spatial geomorphological information (i.e., stratigraphy), characterized from different geophysical methods. This paper presents a methodology to address this challenge by the use of a probabilistic approach. A set of synthetic geophysical mappings are used to illustrate the applicability of the proposed methodology and its potential extrapolation to other scientific imaging disciplines.

Image-based sensing of 3-D displacements for enhanced soil model calibration

Calibration of soil constitutive parameters is performed traditionally by analyzing results from triaxial experiments, which are equipped to measure only vertical stress and strain responses and average volumetric responses. Material response characterization thus is relegated to an overall, averaged sense. The 3-D image-based sensing technique of 3D Digital Image Correlation (3D-DIC) allows capturing spatio-temporal displacement processes over triaxial specimen surfaces. Utilizing stereo digital images, 3D-DIC captures hundreds of thousands of local displacement measurements over a specimen’s surface. This work introduces the exploratory data analysis of displacement field’s ensembles that are currently used for the probabilistic calibration of constitutive parameters.

Local Deformation Analysis of a Sand Specimen using 3D Digital Image Correlation for the Calibration of a Simple Elasto-Plastic Model

The use of Digital Image Correlation (DIC) technique has become increasingly popular for displacement measurements and for characterizing localized material deformation. In this study, a three-dimensional digital image correlation (3D DIC) analysis was performed to investigate the displacements on the surface of a dense sand specimen during a triaxial compression test (drained, vacuum consolidated). The deformation of a representative volume of the material captured by 3D DIC is used for the estimation of the kinematic and volumetric conditions of the specimen at different stages of deformation, combined with the readings of the global axial compression of the specimen, which allow for the characterization of the Mohr-Coulomb plasticity model with hardening and softening law. A 2D finite element model is developed for comparing the experimental results under displacement controlled loading conditions. A comparison between model predictions and the expected displacement fields show good agreement, as to reproduce accurately the overall mechanical behavior of a dense sand specimen and to take into account the influence of local effects in the mechanical parameters obtained by 3D DIC.

Integrated approach for the optimal selection of environmentally friendly drilling systems

There is a pressing need in the energy industry to develop technologies capable of reducing the environmental impact during oil and gas drilling operations. However, these technologies have not been fully integrated into a decision-making system that can reflect a quantitative effort toward this goal. This paper introduces two quantitative decision methods for the selection of environmentally friendly drilling systems. One is based on a multi-attribute utility approach and the other one is based on the analysis of interventions or causal approach. To illustrate the applicability of the proposed methods and to contract their benefits and limitations, a case study is presented using data collected from Green Lake at McFaddin, TX, USA.

Towards an Uncertainty-Based Design of Foundations for Onshore Oil and Gas Environmentally Friendly Drilling (EFD) Systems

The petroleum industry endeavors to minimize the environmental impact during oil and gas drilling operations. For instance, by reducing the footprint during drilling operations using a reusable modular platform and a small mobile rig, in 2003 and 2004 Anadarko and Maurer Technology Inc. demonstrated a new foundation concept in the Arctic. Their objective was to drill in an ecologically sensitive area without disturbing the ground surface. Use of an elevated platform in environmentally sensitive areas requires the use of piles to support the elevated deck instead of gravel pads used in a conventional drilling system. The aim of this paper is to introduce an environmentally friendly foundation method for onshore drilling systems, and to conduct a parametric study of different foundations to improve the understanding of these types of foundation designs, by introducing uncertainty quantification for various rig weights and soil conditions (e.g., desert environments and wetland applications). This paper introduces a case study on pile capacity calculations depending on various soil types and pile types, and sets the basis for a full reliability analysis on this type of foundation.