Subsurface Sensing Research Articles

Gradient Boosting Decision Tree-Based PMM Model Integrated Into FDTD Method for Solving Subsurface Sensing Problems

Gradient Boosting Decision Tree-Based PMM Model Integrated Into FDTD Method for Solving Subsurface Sensing Problems

Investigating Road Ice Formation Mechanisms Using Road Weather Information System (RWIS) Observations

Ice formation on roads leads to a higher incidence of accidents and increases winter de-icing/anti-icing costs. This study analyzed 3 years (2019–2021) of Road Weather Information System (RWIS) sub-hourly measurements collected by the Montana Department of Transportation (MDT) to understand the first-order factors of road ice formation and its mechanisms. First, road ice is formed only when the road pavement surface temperature is equal to or below the freezing point (i.e., 32 °F (i.e., 0 °C)), while the corresponding 2 m air temperature could be above 32 °F. Nevertheless, when the road pavement was below 32 °F ice often did not form on the roads. Therefore, one challenge is to know under what conditions road ice forms. Second, the pavement surface temperature is critical for road ice formation. The clear road (i.e., with no ice or snow) surface pavement temperature is generally warmer than the air temperature during both day and night. This feature is different from a natural land surface, where the land skin temperature is lower than the air temperature on cloud-free nights due to radiative cooling. Third, subsurface temperature, measured using a RWIS subsurface sensor below a road surface, did not vary as much as the pavement temperature and, thus, may not be a good index for road ice formation. Fourth, urban heat island effects lead to black ice formation more frequently than roads located in other regions. Fifth, evaporative cooling from the water surface near a road segment further reduces the outlying air temperature, a mechanism that increases heat loss for bridges or lake-side roads in addition to radiative cooling. Additionally, mechanical lifting via mountains and hills is also an efficient mechanism that makes the air condense and, consequently, form ice on the roads. Forecasting road ice formation is in high demand for road safety. These observed features may help to develop a road ice physical model consisting of functions of hyper-local weather conditions, local domain knowledge, the road texture, and geographical environment.

3-D Simulation of Wave Propagation in the Fractured Porous Media for Subsurface Sensing: A Rotated Staggered Finite-Difference Algorithm Based on Equivalent Medium Theory

3-D Simulation of Wave Propagation in the Fractured Porous Media for Subsurface Sensing: A Rotated Staggered Finite-Difference Algorithm Based on Equivalent Medium Theory

Revisiting talus and free-air temperatures after 50 years of change at an American pika (Ochotona princeps) study site in the Southern Rockies

Climate change in mountain regions has exposed high-elevation species to rapidly changing temperatures. Although climate exposure can be reduced in certain microclimates, the quality of microclimatic refugia might also degrade with climate change. The American pika (Ochotona princeps) often inhabits high elevations, and is considered climate-sensitive due to its narrow thermal tolerance and recent extirpations in some warmer portions of its range. Pikas behaviorally thermoregulate by taking refuge in the subsurface microclimates found in taluses and other rocky habitats, where daily thermal fluctuations are attenuated and somewhat decoupled from free-air temperatures. Changes in microclimate might reduce the efficacy of this behavioral thermoregulation. This study compares recent (2009–2021) subsurface temperatures at a long-term pika study site with a rare instance of historical (1963–1964) data from the same location. We also place historical and recent microclimates in context using long-term data on free-air temperatures from the same area. Recent free-air temperatures were often warmer than historical records, and subsurface temperatures exhibited even stronger warming between periods. Temperatures measured in the talus were often dramatically warmer in recent records, especially at the deeper of two subsurface sensor placements in this study. Winter months showed the greatest changes in both talus and free-air temperatures. Differences between historical and recent microclimates were not explained by the precise placement of sensors, as recent temperatures were similar across a wide variety of subsurface placements, and temporal changes in free-air temperatures at the historical study site were also reflected in data from nearby weather stations. Together, these results suggest that subsurface microclimates important for pika thermoregulation have changed over the past few decades, perhaps even faster than observed changes in free-air temperatures. The generality of these results and their potential ramifications for ecosystem processes and services should be explored.

Autonomous, Long-Range, Sensor Emplacement Using Unmanned Aircraft Systems

Automated, in-ground sensor emplacement can significantly improve remote, terrestrial, data collection capabilities. Utilizing a multicopter, unmanned aircraft system (UAS) for this purpose allows sensor insertion with minimal disturbance to the target site or surrounding area. However, developing an emplacement mechanism for a small multicopter, autonomy to manage the target selection and implantation process, as well as long-range deployment are challenging to address. We have developed an autonomous, multicopter UAS that can implant subsurface sensor devices. We enhanced the UAS autopilot with autonomy for target and landing zone selection, as well as ensuring the sensor is implanted properly in the ground. The multicopter UAS, limited by onboard energy, can be carried by a transport aircraft to within 1 km of the desired sensor location site and deployed by a novel parachuting-canister system. Through a comprehensive set of field trials and testing, we assess the effectiveness of each subsystem. We evaluate our system on missions covering distances up to 25 km away in mountains 1 km above the takeoff location.

Internet of Things Geosensor Network for Cost-Effective Landslide Early Warning Systems.

Worldwide, cities with mountainous areas struggle with an increasing landslide risk as a consequence of global warming and population growth, especially in low-income informal settlements. Landslide Early Warning Systems (LEWS) are an effective measure to quickly reduce these risks until long-term risk mitigation measures can be realized. To date however, LEWS have only rarely been implemented in informal settlements due to their high costs and complex operation. Based on modern Internet of Things (IoT) technologies such as micro-electro-mechanical systems (MEMS) sensors and the LoRa (Long Range) communication protocol, the Inform@Risk research project is developing a cost-effective geosensor network specifically designed for use in a LEWS for informal settlements. It is currently being implemented in an informal settlement in the outskirts of Medellin, Colombia for the first time. The system, whose hardware and firmware is open source and can be replicated freely, consists of versatile LoRa sensor nodes which have a set of MEMS sensors (e.g., tilt sensor) on board and can be connected to various different sensors including a newly developed low cost subsurface sensor probe for the detection of ground movements and groundwater level measurements. Complemented with further innovative measurement systems such as the Continuous Shear Monitor (CSM) and a flexible data management and analysis system, the newly developed LEWS offers a good benefit-cost ratio and in the future can hopefully find application in other parts of the world.

CO2 Monitoring Technologies at the UK Geoenergy Test Bed

The UK GeoEnergy Test Bed (GTB) is a field research platform initiated by the British Geological Survey and University of Nottingham. The GTB will be used to undertake research to refine strategies and tools for monitoring the zone above CO2 storage reservoir; an essential part of proving site conformance. Research at the GTB will support the emerging CO2 storage industry by enabling testing of innovative sensors and advancing understanding of fluid migration in the shallow subsurface, which will in turn enable more effective monitoring strategies for large-scale storage sites. The GTB comprises an array of above surface and subsurface sensors focused on two CO2 injection wells, one deep (~212 m) and one shallow (~12 m). A permanent sensor array (plus intermittent mobile surveys) will be used to study the acoustic, electro-magnetic, mechanical, geochemical and other relevant properties of the volume of rock and pore fluids around the injection wells, and CO2 levels in the soil and air. The first CO2 injection is planned during 2021. The GTB offers a unique facility in the UK to study CO2 migration at a location where rocks have not previously been exposed to significant quantities of CO2.

Compact Matrix-Exponential-Based FDTD with Second-Order PML and Direct Z-Transform for Modeling Complex Subsurface Sensing and Imaging Problems

To simulate complex subsurface sensing and imaging problems with both propagating and evanescent waves by the finite-difference time-domain (FDTD) method, the highly-accurate second-order perfectly matched layer (SO-PML) formulations based on the direct Z-transform (DZT) and the matrix exponential (ME) techniques are compactly and efficiently proposed for modeling open-domain problems. During mathematical deductions, several manipulations, for example, convolution computations, formulation reorganizations, or variable substitutions, can be circumvented due to the fact that the ME-based method shows a compact first-order differential matrix form. Besides, any material attributes can be completely circumvented because of using electric and magnetic flux densities, consequently, the proposed DZT-SO-PML could be applied without needing any alteration. Moreover, the DZT-SO-PML method can not only preserve better absorption accuracies, but also attain palpable improvements in computational efficiencies, even if the distance between the DSP-SO-PML truncation and the target becomes closer for modeling 3D open-domain subsurface sensing and imaging problems. Finally, numerical examples have been carried out to illustrate and validate these proposed formulations.

Autonomous Airborne 3D SAR Imaging System for Subsurface Sensing: UWB-GPR on Board a UAV for Landmine and IED Detection

This work presents an enhanced autonomous airborne Synthetic Aperture Radar (SAR) imaging system able to provide full 3D radar images from the subsurface. The proposed prototype and methodology allow the safe detection of both metallic and non-metallic buried targets even in difficult-to-access scenarios without interacting with the ground. Thus, they are particularly suitable for detecting dangerous targets, such as landmines and Improvised Explosive Devices (IEDs). The prototype is mainly composed by an Ultra-Wide-Band (UWB) radar module working from Ultra-High-Frequency (UHF) band and a high accuracy dual-band Real Time Kinematic (RTK) positioning system mounted on board an Unmanned Aerial Vehicle (UAV). The UAV autonomously flies over the region of interest, gathering radar measurements. These measurements are accurately geo-referred so as to enable their coherent combination to obtain a well-focused SAR image. Improvements in the processing chain are also presented in order to deal with some issues associated to UAV-based measurements (such as non-uniform acquisition grids) as well as to enhance the resolution and the signal to clutter ratio of the image. Both the prototype and the methodology were validated with measurements, showing their capability to provide high-resolution 3D SAR images.

MIMO Borehole Radar Imaging Based on High Degree of Freedom for Efficient Subsurface Sensing

This paper presents an efficient multiple-input multiple-output (MIMO) borehole radar imaging method based on a high degree of freedom for subsurface sensing. The variable separations between the different transmitter and receiver pairs in MIMO borehole radar are considered and introduced as imaging coefficients into the expanded unified MIMO sample set, which gives the MIMO sample set desired characteristics of a high degree of freedom. By exploiting the high degree of freedom in the unified MIMO expanded sample set, the sample interpolation and energy migration of target reflections can be done in once efficient imaging processing for all transmitters of the MIMO radar system, and finally, accurate target image with low sidelobe level (SL) can be delivered. The computational cost of the proposed method will barely increase with the number of transmitters in the MIMO radar survey, which enables the proposed method to handle MIMO borehole radar imaging in an accurate and efficient manner. The imaging properties of the proposed method are proven to be superior to the conventional imaging methods in SL and computational cost, which is suitable for large MIMO borehole imaging surveys in subsurface sensing applications.

Mixed Total Field/Scattered Field-Based Discontinuous Galerkin Frequency-Domain Method for Subsurface Sensing

To model the responses of electromagnetic surveys for geophysical subsurface sensing, a mixed total field/scattered field-based discontinuous Galerkin frequency-domain (TF/SF DGFD) method is proposed in this paper. The proposed TF/SF DGFD method is implemented at a subdomain level based on the domain decomposition technique. Different subdomains can employ either the TF DGFD framework or the SF DGFD framework, which are then coupled through the Riemann transmission condition. To balance the computation efficiency and accuracy for practical applications, the proposed method prefers to using the SF DGFD framework for subdomains with sources and using the TF DGFD framework for the remaining subdomains. At the interfaces between total field and scattered field subdomains, the Riemann transmission condition is slightly modified by incorporating the background fields due to the physically imposed sources in the background media. In this way, the proposed method only requires surface integrals of the background fields as extra overhead instead of elementwise integration of the scattering objects for the purely scattered field-based method, which can improve the computational efficiency. Also, it is more accurate than the purely TF DGFD method given the same mesh. Numerical examples are studied to examine the performance of the proposed method, which is proven to have better accuracy than the TF DGFD method. The TF/SF DGFD method will facilitate modeling of electromagnetic surveys under complicated geophysical environments for subsurface sensing.

Quantifying the Impacts of Acoustic Target Detections Using a Range-Independent Model Versus Range-Dependent Model

The purpose of this study is to identify and quantify the difference in detections of a subsurface target from a subsurface sensor source between range-independent and range-dependent versions of the same acoustic propagation model. Environmental data were pulled from open source databases to provide an application for the comparison and using novel measures of merit, the authors were able to quantify the difference in detection performance between models. This study suggests that provided multiple types of environments are considered, it is possible to use a range-independent model to give good approximations to the accuracy of detections, one would achieve using a full range-dependent sound propagation model.

Incorporating Full Attenuation Mechanisms of Poroelastic Media for Realistic Subsurface Sensing

Porous materials are ubiquitous in the subsurface formations of the earth where acoustic and seismic waves are used for remote sensing. However, it is not well understood how the dissipation and the dispersion of poroelastic waves are caused by the viscoelastic and viscous properties of the constituents such as solid grains and pore fluid and by the viscoelastic dissipation of the solid frame, as well as the viscodynamic coupling of the pore fluid to the solid frame due to its global and local flows relative to the solid grains. Such attenuation mechanisms have seldom been incorporated in subsurface sensing simulations, although they can be very important to applications. In this paper, we propose a complete attenuation model, including both full stiffness and viscodynamic dissipation, for poroelastic media in seismic wave simulations. Completely based on a generalized Zener model, the effects associated with physical dissipation and frequency-dependent dispersion are accurately simulated by a finite-difference time-domain algorithm. Verifications with analytical solutions show the accuracy, efficiency, and flexibility of our method. Numerical results demonstrate that the attenuation of Biot’s model in the sediment of the seafloor has significant effects on acoustic wave scattering from complex geologic structures.

An Accurate 3-D CFS-PML Based Crank–Nicolson FDTD Method and Its Applications in Low-Frequency Subsurface Sensing

An unsplit-field and accurate Crank–Nicolson cycle-sweep-uniform finite-difference time-domain (CNCSU-FDTD) method based on the complex-frequency-shifted perfectly matched layer (CFS-PML) is proposed. It is applied to 3-D low-frequency subsurface electromagnetic sensing problems. The presented CNCSU-FDTD takes advantage of both CFS-PML and unconditionally stable CN method so that it can attenuate evanescent waves, eliminate late-time reflections, and overcome the stability limits of the FDTD method. The time step intervals in CNCSU-FDTD can be 1000 times larger than that in the regular FDTD for the low-frequency sensing centered at 25 Hz while remaining accurate. Several 3-D numerical examples in the airborne transient electromagnetics system have been demonstrated to validate the proposed method. The CFS-PML-based CNCSU-FDTD method not only attains good accuracy but also saves several dozen times of CPU time as compared with the regular FDTD method.

Least-Square-Based Nonuniform Borehole SAR Imaging for Subsurface Sensing

This paper presents the least-square-based nonuniform borehole synthetic aperture radar (SAR) imaging method with cosine accuracy factor for subsurface sensing. Based on the Stolt migration, the frequency-wavenumber spectrum of nonuniform data is efficiently approximated in the least-square-sense for the target space generation. The nonuniform power exponent basis is interpolated into several uniform power exponent bases with cosine accuracy factors, and then a virtual uniform sample set with a larger scale is generated for frequency-wavenumber spectrum approximation and imaging process. The proposed method can give accurate subsurface image result with nonuniform data at a greatly reduced computational cost. The approximation error and computational cost of the proposed method are analyzed and compared with those of Gaussian nonuniform imaging method. The imaging capabilities of the proposed method are theoretically simulated and experimentally demonstrated for distributed targets. The results show that the normalized mean square error and normalized maximum error of the proposed method are at least 8.07 dB and 4.29 dB, respectively, lower than those of conventional Stolt migration method. The imaging properties of this proposed method are shown to be superior to the conventional Stolt migration method, Gaussian nonuniform imaging method and Kirchhoff migration method, which is suitable for large nonuniform SAR imaging applications.

Micro-cavitation on demand via the nanoparticle mediated interaction of light and sound

The safe utilization of controlled cavitation for HIFU therapy and ultrasound assisted drug delivery requires nucleation sites for bubble formation. We consider the potential for nucleating transient vapor cavities using laser-illuminated gold nanoparticles combined with high-intensity focused ultrasound. An transparent polyacrylamide gel phantom was seeded with 82-nm diameter gold particles and exposed to 20 ns pulses from a 532 nm Nd:Yag laser. Laser firing was synchronized with the arrival of a burst of 1.1 MHz focused ultrasound. Acoustic emissions from ensuing inertial cavitation were detected passively using a 15 MHz focused transducer. At a laser energy of 0.10 mJ/pulse, the resulting inertial cavitation nucleation threshold pressure (peak-negative focal pressure) was as low as 0.92 MPa. In comparison, a peak-negative focal pressure of 4.50 MPa was required to nucleate detectable cavitation without laser illumination (nano-particles were present in both cases). Experimental results agree well with a simple model for transient heating and cavity formation. Since the particles are durable, one can re-activate them as needed, essentially yielding cavitation nuclei “on demand.” [Work supported by the Dept. of the Army (Award No. DAMD17-02-2-0014) and the Center for Subsurface Sensing and Imaging Systems (NSF ERC Award No. EEC-9986821).]

Floating Monopole Antenna on a Tethered Subsurface Sensor at 433 MHz for Ocean Monitoring Applications

Low-cost tethered buoys are important for seawater observation, coastal area monitoring, and pollution sensing. Underwater sensor networks operating at 433 MHz (ISM band) suffer high attenuation due to seawater conductivity. Significant propagation distance cannot be achieved through seawater or along the seabed. This paper reports a novel technique for communication between sensors operating in shallow water. A sensor tethered to the bottom was connected to a floating monopole antenna via an insulated wire transmission line. Experiments and calculations show that the attenuation along the transmission line was 38 dB/m. Surface propagation for buoy-to-base station was approximately 1 dB/m with a communication range of 30 m using a 10-dBm transmitter circuit with receiver sensitivity of ${-}$ 110 dBm. For buoy to buoy the surface propagation was measured as 3.5 dB/m with a communication range of 4 m. Experiments were carried out in calm water conditions. The results demonstrate that significant sensor network coverage of coastal regions is possible.

Passive Cooperative Targets for Subsurface Physical and Chemical Measurements: A Systems Perspective

We investigate the use of a commercially available ground-penetrating radar (GPR) for probing the response of subsurface sensors designed as passive cooperative targets. Such sensors must meet two design criteria: introduce a signature unique to the sensor which will hence be differentiated from clutter, and introduce in this signature a response characteristic allowing for recovering the physical quantity under investigation. Using piezoelectric substrates for converting the incoming electromagnetic pulse to an acoustic wave confined to the sensor surface (surface acoustic wave transducer) allows for shrinking the sensor dimensions while providing sensing capability through the piezoelectric substrate acoustic wave velocity dependence with the physical quantity under investigation. Two broad ranges of sensing mechanisms are discussed: intrinsic piezoelectric substrate velocity dependence with a quantity—restricted to the measurement of temperature or strain and, hence, torque or pressure—and extrinsic load dependence on the sensor, allowing for the measurement of variable capacitive or resistive loads. In all cases, the delay introduced by the physical quantity variation induces a phase rotation of the returned signal of a few periods at most, to be measured with a resolution of a fraction of a period: the GPR receiver sampling time reference must exhibit a long term stability at least as good as the targeted phase measurement needed to recover the physical quantity. We show that the commercial GPR exhibits excessive time-base drift, yielding a loss in the sensing capability, while a quartz-oscillator-based alternative implementation of the classical stroboscopic sampling receiver compensates for such a drawback.

Observed and simulated hydrologic response for a first‐order catchment during extreme rainfall 3 years after wildfire disturbance

AbstractHydrologic response to extreme rainfall in disturbed landscapes is poorly understood because of the paucity of measurements. A unique opportunity presented itself when extreme rainfall in September 2013 fell on a headwater catchment (i.e., <1 ha) in Colorado, USA that had previously been burned by a wildfire in 2010. We compared measurements of soil‐hydraulic properties, soil saturation from subsurface sensors, and estimated peak runoff during the extreme rainfall with numerical simulations of runoff generation and subsurface hydrologic response during this event. The simulations were used to explore differences in runoff generation between the wildfire‐affected headwater catchment, a simulated unburned case, and for uniform versus spatially variable parameterizations of soil‐hydraulic properties that affect infiltration and runoff generation in burned landscapes. Despite 3 years of elapsed time since the 2010 wildfire, observations and simulations pointed to substantial surface runoff generation in the wildfire‐affected headwater catchment by the infiltration‐excess mechanism while no surface runoff was generated in the unburned case. The surface runoff generation was the result of incomplete recovery of soil‐hydraulic properties in the burned area, suggesting recovery takes longer than 3 years. Moreover, spatially variable soil‐hydraulic property parameterizations produced longer duration but lower peak‐flow infiltration‐excess runoff, compared to uniform parameterization, which may have important hillslope sediment export and geomorphologic implications during long duration, extreme rainfall. The majority of the simulated surface runoff in the spatially variable cases came from connected near‐channel contributing areas, which was a substantially smaller contributing area than the uniform simulations.

Effects of the Artificial Skin's Thickness on the Subsurface Pressure Profiles of Flat, Curved, and Braille Surfaces

The primary interface of contact between a robotic or prosthetic hand and the external world is through the artificial skin. To make sense of that contact, tactile sensors are needed. These sensors are normally embedded in soft, synthetic materials for protecting the subsurface sensor from damage or for better hand-to-object contact. It is important to understand how the mechanical signals transmit from the artificial skin to the embedded tactile sensors. In this paper, we made use of a finite element model of an artificial fingertip with viscoelastic and hyperelastic behaviors to investigate the subsurface pressure profiles when flat, curved, and Braille surfaces were indented on the surface of the model. Furthermore, we investigated the effects of 1, 3 and 5 mm thickness of the skin on the subsurface pressure profiles. The simulation results were experimentally validated using a 25.4 {\mu}m thin pressure detecting film that was able to follow the contours of a non-planar surface, which is analogous to an artificial bone. Results show that the thickness of the artificial skin has an effect on the peak pressure, on the span of the pressure distribution, and on the overall shape of the pressure profile that was encoded on a curved subsurface structure. Furthermore, the flat, curved, and Braille surfaces can be discriminated from one another with the 1 and 3 mm artificial skin layers, but not with the 5 mm thick skin.