In situ Measurement of Oil Slick Thickness in Open Water Environments

During an oil spill response, one of the parameters impacting the choice and management of the applied cleaning technique is the thickness of the floating oil. Studies have shown that technologies to accurately measure oil thickness in real-time under open water operational conditions are not commercially available. Aiming to enhance the efficiency of the currently used cleanup processes, we present the development of a capacitive-based measurement device that can measure the thickness of various types of floating oil. The presented device measures the capacitance of the oil/water/air that it contacts and uses this data to estimate the locations of the oil-air and oil-water interfaces. Determining the interfaces location provides the data necessary to calculate the thickness of the oil layer. This sensor can operate in open water environments while being dragged through waves, and does not require any calibration against different types of oil or water. In addition, the device is equipped with specialized software- and hardware-based mechanisms to mitigate the fouling problem caused by highly-viscous oils. The sensor is designed to be vertically mounted to a skimmer, boom, or floating buoy and provide thickness readings (up to 50 cm) remotely, A second configuration allows a user to measure readings directly from a handheld unit (up to 10 cm). To assess the performance of the sensor, extensive testing of the initial prototype was performed at Ohmsett facility. The experimental results demonstrated high sensor accuracy in most of the test cases. Based on the testing results, several improvements were identified and are currently being implemented to enhance the performance of the sensor while working under harsh dynamic-liquid conditions

In situ Sensors for Oil Spill Detection and Thickness Measurement: Methods and Challenges

Oil thickness information is essential for enhancing the effectiveness of oil-spill remediation techniques such as mechanical skimmers, chemical dispersants, and in situ burning. Even though remote sensing methods can provide a global assessment of the spill extent, they are not suitable for providing accurate estimates of the local oil spill thickness due to varying oil properties and dynamic environmental conditions. To measure the thickness of oil spills locally and with high accuracy, in situ sensors were proposed in the literature relying on optical, electrical, acoustic, and vision sensing modalities. These sensing systems have different structures including single probes, multi-electrode arrays, and movable electrodes. This article provides a critical review of in situ oil spill detection and thickness measurement systems. It focuses on explaining their working principles, properties, and limitations. The ultimate aim of this work is to facilitate the understanding of the state-of-the-art oil spill sensors and to provide an objective assessment of their ability to measure oil film thicknesses in open water environments. Despite its importance, this topic is poorly studied in the instrumentation and measurement domain. To the best of our knowledge, no similar reviews are available in the literature

Virtual Testing Methods of Cyber-Physical Systems: A Framework for Testing Instrumentation and Measurement Systems

The development of some instrumentation and measurement systems poses significant challenges due to their continuous interaction with environments that are both harsh and highly dynamic. They are often described as “Untestable” because their testing is sometimes expensive, time-consuming, and infeasible. One example is oil-spill measurement systems that aim to measure the thickness of oil floating on the water surface in open water environments. In contrast to analog sensors relying on calibration functions, such integrated measurement systems use algorithms with multiple inputs to produce their measurement. Intending to facilitate the development of such systems, we shed light on virtual testing methods designed for testing Cyber-physical Systems (CPSs). CPSs are smart and autonomous systems composed of collaborating computational elements (software) that control physical entities (hardware). Effective validation and verification techniques are required to confirm their correctness. These methods were applied to test continuous controllers in the automotive domain. In this article, we review some of these testing methods and provide a framework for applying them to measurement systems that are difficult to test in real life. We provide a case study based on an oil spill measurement system that relies on multiple sensors to estimate the oil thickness in open water environments. Applying this approach creates a reduced set of test cases to be applied in real field testing reducing its cost and time

Thickness measurement device and methods of use

Provided herein are systems, methods and apparatuses for a thickness measurement device based on a capacitive array

Sensors for Oil Slick Detection and Thickness Measurement

During a response to an oil spill, one of the key features impacting the effectiveness of the cleaning techniques is knowing, in real-time, the actual thickness of oil in a slick area. To enhance the efficiency of the currently used cleanup processes, the Bureau of Safety and Environmental Enforcement (BSEE) Oil Spill Preparedness Division (OSPD) contracted the American University of Beirut (AUB) to build an oil-thickness measurement device that improves situational awareness and guides response operators during oil recovery operations

Design Optimization of a Multiphase Coplanar Capacitive Sensor

Detecting oil under the ice in arctic regions with current remote sensing techniques is challenging due to several factors, such as the attenuation of radio-frequency electromagnetic waves and the unknown properties of oil that vary depending on its type and the environmental conditions. To address this problem, we propose a planar capacitive sensor that works in the quasi-electrostatic domain to detect and characterize oil under ice based on its dielectric properties. This paper focuses on the design optimization process that was conducted with the aim of improving the sensitivity and penetration depth of our proposed sensor. Our design optimization process studies different geometrical and electrical parameters and compares the sensor performance obtained from using grounded (passive) backplanes and driven (active) guards. It includes a set of simulations performed using ANSYS electrostatic simulation software and a set of experiments performed under indoor laboratory conditions. The results demonstrated the effectiveness of the optimized sensor design, which is based on a pair of trapezoidal electrodes that are implemented on separate PCBs and surrounded by driven guards. Another major novelty of our proposed sensor design is based on measuring the mutual capacitance between the two sensor plates after changing the horizontal distance between them using a dynamic mounting setup. This allows us to take a number of capacitance measurements at different penetration depths of the electric field before using them to detect the presence of oil and estimate its thickness. Further tests in real-world scenarios are planned for future work