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Advances in Rotational Seismic Measurements

Rotational motion is increasingly understood to be a significant part of seismic wave motion. Rotations can be important in earthquake strong motion and in Induced Seismicity Monitoring. Rotational seismic data can also enable shear selectivity and improve wavefield sampling for vertical geophones in 3D surveys, among other applications. However, sensor technology has been a limiting factor to date. The US Department of Energy (DOE) and Applied Technology Associates (ATA) are funding a multi-year project that is now entering Phase 2 to develop and deploy a new generation of rotational sensors for validation of rotational seismic applications. Initial focus is on induced seismicity monitoring, particularly for Enhanced Geothermal Systems (EGS) with fracturing. The sensors employ Magnetohydrodynamic (MHD) principles with broadband response, improved noise floors, robustness, and repeatability. This paper presents a summary of Phase 1 results and Phase 2 status.

58 GEOSCIENCES↗

Quantitative Non-Destructive Evaluation of Fatigue Damage Based on Multi-Sensor Fusion

Based on sensor fusion and machine learning, this project developed a novel non-destructive evaluation (NDE) methodology, which consists of a remaining useful life (RUL) prediction framework and regression models for predicting residual stress and full width at half maximum (FWHM). A series of fatigue testing experiments were conducted using 5052-H32 aluminum alloy specimens. All specimens were measured using linear ultrasonic (LU) and nonlinear ultrasonic (NLU) testing methods non-destructively. Machine learning models were developed to use LU and NLU measurements to predict loading condition, fatigue level, residual stress, and FWHM. It was demonstrated that the developed methodology could distinguish new and fatigue specimens with an accuracy of 97.53%. Also, the prediction errors for residual stress and FWHM were as low as 4.73% and 1.62%, respectively. An interactive database was created to publicly share the data generated from the project. It is envisioned that the developed NDE technology will equip manufacturers with a responsive screening system for incoming used metallic components, and potentially lead to a significant increase in using used metallic components for remanufacturing.

42 ENGINEERING↗

Design of a Dry Dilution Refrigerator for MMC Gamma Detector Arrays

The goal of this LCP is to develop an ultra-high resolution gamma detector based on magnetic microcalorimeters (MMCs) for accurate non-destructive analysis (NDA) of nuclear materials. For highest energy resolution, we will introduce erbium-doped silver (Ag:Er) as a novel sensor material to replace current Au:Er sensors. The detector sensitivity will be increased by developing arrays of 32 Ag:Er pixels read out by 16 SQUID preamplifiers. MMC detectors require operating temperatures of ~15 mK and thus the use of a dilution refrigerator, and the desire for user-friendly operation without cryogenic liquids requires that this refrigerator use pulse-tube pre-cooling to ~4 K. For long-term reliability, we intend to re-design the heat switch that is needed to apply the magnetizing current to the Ag:Er sensor and that used to fail in earlier designs after months of operation. A cryogenic Compton veto will be installed to reduce the spectral background of the MMC, especially at low energies where ultra-high energy resolution is most important. The goals for FY16 were 1) to purchase a liquid-cryogen-free dilution refrigerator and adapt it for MMC operation, and 2) to fabricate Ag:Er-based MMC γ-detectors with improved performance and optimize their response. This report discusses the design of the instruments, and progress in MMC detector fabrication. Details of the MMC fabrication have been discussed in an April 2016 report to DOE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Wireless Sensing and Communication Capability from In-Core to a Monitoring Center

Significant cost savings can be made if electrical cables can be replaced by wireless technology in current Nuclear Power Plants (NPP) and in advance reactor designs. Wireless technology can also provide in-core opportunities by significantly reducing the number of penetrations in the pressure vessel, cost and complexity of sensor installation and by increasing the efficiency of current and advanced reactors. Unlike other deployment scenarios for an industrial environment, operators need to have centralized control over all the networks. Centralized control will reduce implementation costs, provide single point control and enable monitoring of network devices, improve security, and enhance connectivity. Micro-sensors that can simultaneously monitor temperature and pressure within a fuel rod inside nuclear reactors will enable preventative actions during abnormal operating conditions. This ability could avert accidents and enable the expedient development of accident tolerant fuels. A novel micro-sensor suite (~ mm) to simultaneously measure multiple parameters such as temperature, strain, pressure, and neutron/gamma flux inside a fuel rod is being developed for use in reactors. The necessary communication architecture is also being developed to transmit measurement signals from the core to the plant's data cloud or control room. A three three-tier strategy has been developed to support wireless transmission of in-core measurements to the control room or to a secure cloud platform for control, analytics, and decision-making purposes. 1. In-core: data signal from in-core to outside of the pressure vessel within the containment building 2. Containment building: data signal from inside to the outside of the containment building and into the balance of the plant network 3. Balance of the plant network: information transmitted to the data cloud and control room This plan presents a wireless sensing and communication system for use within a reactor core and elsewhere. The communication technology is advantageous to compensate for network equipment failures and adverse data transmission conditions. Wireless technology will significantly increase the resiliency of the plants network system. The wireless system naturally provides multiple transmission path capability and data redundancy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of an in-situ corrosion monitor for molten salt reactors

A novel in-situ corrosion sensor for structural alloys exposed to molten salts has been initially demonstrated. The measurement is based upon observing the change in magnetic susceptibility of salt wetted structural alloys as corrosion occurs. In halide salts corrosion of structural alloys proceeds primarily through dissolution of the least noble component of the alloy into the melt. All currently available structural alloys intended for use with molten salt reactors (MSRs) include nickel, chromium, and iron. Chromium is preferentially oxidized from the alloy surface by exposure to halide salts at high temperature. Diffusion within the alloy results in progressively deeper depletion of chromium from the alloy surface. Relevant chromium bearing structural alloys are paramagnetic. However, once the chromium has been depleted, they become ferromagnetic. Thus, structural alloy corrosion in an MSR results in development of a ferromagnetic surface layer whose depth increases with increasing corrosion. The corrosion sensor functions by employing the progressive increase in ferromagnetism as a transduction mechanism through including the corroding alloy in a magnetic circuit. Development of the sensor remains a work in progress. To date we have characterized the sensor response of structural alloy samples with varying degrees of corrosion at room temperature. Over the next year we plan to demonstrate sensor performance at MSR operating temperatures (up to 750 °C) in a piping geometry.

Holcomb, David↗

Field surveying data of low-cost networked flood sensors in southeast Texas

Floods are common natural disasters worldwide and pose substantial risks to life, property, food production, and natural resources. Effective measures for flood mitigation and warning are essential. Southeast Texas is still at significant risk of flooding, and Lamar University is assisting the region with asset management of a flood sensor network for flooding events. This network provides real-time water stage information. Lamar University developed a survey program to measure elevation and coordinates at each sensor site location to make this data more useful for flood monitoring and mapping. This paper overviews the measurement of the elevation and coordinates of 74 networked flood sensors and various flood stage thresholds at critical points that flood decision-makers can use for reference at each site. In the first phase of this program, these sensors were deployed throughout a 7-county region spanning nearly 6,000 square miles in Southeast Texas. The latitude and longitude of the sensors and their elevations were determined using survey-grade Global Navigation Satellite System (GNSS) technology. Various Continually Operating Reference Stations (CORS) were utilized for post-processing to achieve sub-inch resolution. The flood stage thresholds, water level sensors elevation, and the elevations and positions of other critical surrounding points are viewable to the public through two online repositories and a web-based sensor management dashboard. The data is used to aid with decisions related to road closures or modeling efforts by mitigation decision-makers, emergency managers, and the public, including the Texas Department of Transportation, Houston Transtar, the National Weather Service, and the Sabine River Authority of Texas (SRA).

54 ENVIRONMENTAL SCIENCES↗

Absorption spectroscopy based high-speed oxygen concentration measurements at elevated gas temperatures

A sensor built upon tunable diode laser absorption spectroscopy (TDLAS) has been developed for concentration measurements in high-temperature (up to 800 K) gas streams; while the sensor measures gas oxygen and water concentration, temperature and pressure, this work focuses on the challenges and solutions to transient oxygen measurement. A 760-nm diode laser was used to probe a pair of oxygen absorption transitions, and a Herriott cell based multi-pass arrangement was utilized to compensate for the extremely weak oxygen absorption as well as the high gas temperature. This multi-pass arrangement provides a 4297.4-mm absorption path length across a 76.2-mm diameter duct, and an O 2 detection limit ([O 2 ] where SNR=1) of ca. 0.1%. Laboratory validation of the HITRAN spectral parameters of the chosen absorption transitions was performed over a range of high temperatures and oxygen concentrations relevant to engine-exhaust applications. The insensitivity of the Herriott cell arrangement to vibrations and spatial temperature gradients was demonstrated. Conclusions from applications to single- and multi-cylinder engine exhaust are presented and demonstrate the new sensor’s ability to measure fast intra-cycle gas-property transients, and provide insights relevant to advancing internal-combustion-engine technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CRCNS21 Computational Models of Multisensory Integration by Upper Limb in Humanoids and Amputees

This international collaborative research project between Johns Hopkins University (JHU) and the Technical University of Munich (TUM) investigated how the human brain processes and integrates multiple types of sensory information, such as touch and force, with the goal of improving prosthetic limbs for amputees and advancing sensory capabilities in humanoid robots. The research advanced our understanding of how the brain responds to sensory feedback in upper-limb amputees. Through experiments in which amputees received electrical stimulation while performing phantom hand movements, we demonstrated that sensory feedback activates the cortical sensorimotor and multisensory regions, and that these regions communicate dynamically during stimulation. Experiments with intact-limb participants explored the integration of visual, haptic, and force feedback, as well as in virtual reality motor training, further showing how the brain processes multimodal sensory information. In addition, this research inspired work on examining the reliability of where amputees perceive sensations over time, which contributed to a successful doctoral fellowship for continued investigation. Our collaborators at TUM improved multimodal sensor technology combining tactile and thermal feedback for humanoid robots, demonstrating the feasibility of integrating multiple sensor types into a unified system for detecting and responding to environmental stimuli. The experimental methods and analysis techniques developed across both teams, including functional network analysis and multimodal sensor integration, provide a foundation for future research in prosthetics and robotics. This research benefits the public by generating knowledge about how amputees process restored sensory information. Advances in humanoid sensing contribute to safer human-robot interaction. The project also fostered international collaboration and cross-disciplinary training: one TUM doctoral student spent a summer at JHU working on multimodal sensor integration, while two JHU students traveled to TUM to host workshops on neuromorphic sensory encoding and sensory integration.

42 ENGINEERING↗

NDT System for Metal Components in Concrete Structures (Final Report)

Steel reinforcements embedded within concrete can corrode and crack, leading to weakening of the structures, and existing NDT (non-destructive testing) techniques do not provide the full picture. Condition assessment is critical in evaluating these structures in order to ensure safe, long-term operation of the nuclear power plants. Improved NDT techniques are needed as the nation’s generating stations age and require action based on increasingly critical inspection data. The power industry uses eddy current test (ECT) during in-service inspections to detect and monitor defects such as cracks and corrosion in metals, particularly metal pipes. However, the detection of defects in the reinforcing steel embedded in concrete is far more challenging for numerous reasons. Primary among them is the concrete layer’s thickness, which prevents the ability to have a close proximity between sensor and metallic sample. One solution to this problem is to create a higher sensitivity technique which can inspect at depth, with good spatial resolution and excellent directional sensitivity, to isolate the metal buried deep in the concrete and characterize defects in the metal. The goal of the phase II research program was to study and develop a new reinforced concrete NDT technology based on anisotropic magnetoresistive (AMR) sensors designed specifically for ECT of steel reinforcements in concrete. The first technical objective was to demonstrate the capability of inspecting steel reinforcement structures, including metal rebar and tensioning cable at or below 6” of depth embedded in concrete. Another objective was to be able to confidently identify multiple layers of reinforcements at varying depths. In addition, the technique needed to be able to provide condition assessment of the metal, providing data on the structure and positioning of the steel members, material loss, and detection of the presence of breaks. An important part of the research and development was aimed at achieving superior performance compared to existing technology. The ability to detect corrosion breaks in unbonded multi-wire and multi-strand tendons was another important objective. The final objective that led to a successful program was to build a complete prototype portable scanning system capable of demonstrating the probe performance in the field. All of these objectives were met, which provided data for the system development work going forward. RMD worked with the engineering firm Simpson Gumpertz & Heger to develop a detailed problem definition for concrete structures and the necessary sensor specifications. In addition, we developed finite element simulation models for the eddy current based NDT system through the analysis of the electromagnetic (EM) properties of sample materials and the orientation of the transmitter, sensor array (receivers), metal, and intervening materials like concrete and air. Based on the modeling and specifications, we designed and fabricated prototype sensor modules. We then acquired and fabricated test samples to characterize and optimize the sensors. Finally, we built a complete prototype for testing on actual concrete structures. This new NDT technology has high promise for greatly improving capabilities in the inspection of steel reinforcements within concrete structures, such as rebar, liners, anchors, and prestressing cables. This method could be valuable in the maintenance of nuclear power plants, and many other structures critical to our nation’s infrastructure.

42 ENGINEERING↗

Monitoring Waste Tanks Using Guided Wave Technology - 18576

There are many challenges associated with the inspections of double-shell storage tanks containing radioactive waste, including limited space for accessibility and maneuverability, environments with high radiation, temperature and toxicity, and unknown physical conditions. Contents of the tank and limited space may prevent access of scanning devices that employ conventional NDE techniques such as ultrasonics, eddy current, or magnetic based methods. Resolving these challenges will become more urgent as the nuclear industry is forced to address the complications of the aging nuclear infrastructure - specifically at tank storage locations on laboratory sites across the DOE complex. A powerful, new approach to inspecting and monitoring the structural integrity of large structures, such as double-shelled tanks, is being developed using ultrasonic guided waves. Acoustic waves that propagate in a plate or other structure where the wavelength is larger than the thickness of the structure are known as ultrasonic guided waves. Ultrasonic guided waves can potentially propagate distances of tens to hundreds of feet in plate-like structures, such as those that comprise the walls and bottom of a storage tank. Guided waves enable the examination of relatively large inspection volumes from the outside surface of the structure. In double-shell tanks, the technology offers promise for examining the floor of the structure or the walls by placing guided wave sensors at accessible locations in the annulus. This guided wave technology has the capability to detect and localize areas of damage or degradation. While guided wave has recently been used in the nuclear and oil and gas industries for inspecting one-dimensional piping systems, current research is developing methods to apply this technology to the two-dimensional surfaces of double-shell storage tanks. Permanently installed sensors are being developed which would remotely collect data that would be analyzed to monitor the structural condition of the tank. Initial tests have been conducted on single plate structures to study guided wave interaction with various shapes and sizes of pertinent simulated damage mechanisms, and the experimental results were compared with hybrid finite-element numerical models. Dispersion curves were calculated to study guided wave modes and their properties in carbon steel plates and to evaluate behaviors at joints between plates. The next steps in the research process include applying the transmitters and sensors to full scale mockups, developing more mature data interpretation, and then demonstrations at an actual site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Operator Evaluation of Mobile Robotic Systems for Inventory, Inspection, and Contamination Survey Tasks in D and D Environments - 17314

The Nuclear and Applied Robotics Group (NRG) has developed two mobile systems with simple, intuitive Human-Machine Interfaces (HMIs). Thus, the systems can be operated by operators who are not robotics experts to perform inventory, inspection and routine contamination surveys in areas where Special Nuclear Material (SNM) is stored and handled. This effort presents feedback collected from EM operators using the two systems at the Portsmouth Gaseous Diffusion Plant in Piketon, OH who used the robotic solutions to perform tasks on site and with minimal training. This approach has the potential to address issues related to ALARA, ergonomics, and reliably completing dull, repetitive tasks while maintaining domain-specific experts in the control loop. The two systems were shipped to - and demonstrated in - a DOE designated area and demonstrated completing contamination testing using a combination of real and surrogate sensors. This paper reviews the initial hardware development, demonstration requirements, and the modifications/improvements made to deploy the systems for this effort. It then summarizes the feedback garnered from EM operators who used the systems at the DOE facility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Nanomaterial-Treated Filters for the Uptake of Heavy Metals from Water Sources

We describe the synthesis and properties of ligand-modified gold nanoparticles (AuNPs) grown on stainless steel wool filters. Their selectivity and efficiency with regards to heavy metal uptake from groundwater and other sources of drinking water found at or near DOE facilities were also investigated. The nanomaterial-treated filters are advantageous because they serve as inactive supports that allow for efficient flow of the contaminated water, and can be easily replaced after heavy metal uptake. They are also comparable to nanomaterials free in solution with regards to the effectiveness of remediation of drinking water. Environmental stewardship is at the forefront of core competencies at SRNS. This includes treatment and remediation of contaminated groundwater. Among contaminants present in water resources, hazardous heavy metals and radioactive contaminants are the main concerns in the DOE complex. With the advent of nanotechnology, new remediation technologies have emerged. AuNPs have unique optical properties and enormous surface areas, making them good candidates for water remediation. They can be functionalized with ligands, e.g. citrate and L-cysteine, allowing them to serve as an excellent platform for environmental stewardship applications. Objectives: 1. Nanomaterial development and characterization Ligand-modified AuNPs: (a) in solution and (b) on stainless steel wool filters 2. Nanomaterial evaluation for efficiency and selectivity of heavy metal uptake, including Cu{sup 2+} and Zn{sup 2+}. Materials and Methods: Chloroauric acid (HAuCl{sub 4}), sodium citrate (reducing and capping agent); Stainless steel wool (SSW) was used as a support and filter; L-cysteine- ligand for surface functionalization; Zinc acetate and copper nitrate: heavy metal ions contaminants. Au NPs were prepared by wet chemistry methods. They were characterized by UV-Vis, Zeta sizer and potential, SEM, EDS and EDS mapping to understand their physico-chemical properties. Results and Discussions: Surface modification of AuNPs with surfactants changes their optical properties. Citrate capped AuNPs demonstrate high loading capacity for both heavy metals. L-cysteine capped AuNPs demonstrate high loading capacity for Zn{sup 2+}. Citrate capped AuNPs have excellent sensitivity towards heavy metal ions (0.05 mM can be detected). L-cysteine capped AuNPs can detect heavy metal ions at low concentrations, making them useful for sensing. Conclusions: AuNPs in solution and on SSW were successfully synthesized and characterized. Two functional sensing and remediation technologies - colorimetric sensor and AuNP-treated filters - were developed through wet chemistry methods. AuNP SSW filters exhibit different characteristics (size, shape, etc.) than AuNPs in solution and are efficient at the uptake of heavy metal ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Load monitoring and compensation strategies for guided-waves based structural health monitoring using piezoelectric transducers

Accurate interpretation of in-situ piezoelectric sensor signals is a challenging task. This article presents the development of a numerical compensation model based on physical insight to address the influence of structural loads on piezo-sensor signals. The model requires knowledge of in-situ strain and temperature distribution in a structure while acquiring sensor signals. The parameters of the numerical model are obtained using experiments on flat aluminum plate under uniaxial tensile loading. It is shown that the model parameters obtained experimentally can be used for different structures, and sensor layout. Furthermore, the combined effects of load and temperature on the piezo-sensor response are also investigated and it is observed that both of these factors have a coupled effect on the sensor signals. It is proposed to obtain compensation model parameters under a range of operating temperatures to address this coupling effect. An important outcome of this study is a new load monitoring concept using in-situ piezoelectric sensor signals to track changes in the load paths in a structure.

environmental compensation↗

Multi-element germanium detectors for synchrotron applications

In this paper, we have developed a series of monolithic multi-element germanium detectors, based on sensor arrays produced by the Forschungzentrum Julich, and on Application-specific integrated circuits (ASICs) developed at Brookhaven. Devices have been made with element counts ranging from 64 to 384. These detectors are being used at NSLS-II and APS for a range of diffraction experiments, both monochromatic and energy-dispersive. Compact and powerful readout systems have been developed, based on the new generation of FPGA system-on-chip devices, which provide closely coupled multi-core processors embedded in large gate arrays. Finally, we will discuss the technical details of the systems, and present some of the results from them.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Dynamic Multi-Sensor Multi-Mission Optimal Planning Tool

Remote sensing systems have firmly established a role in providing immense value to commercial industry, scientific exploration, and national security. Continued maturation of sensing technology has reduced the cost of deploying highly-capable sensors while at the same time increased reliance on the information these sensors can provide. The demand for time on these sensors is unlikely to diminish. Coordination of next-generation sensor systems, larger constellations of satellites, unmanned aerial vehicles, ground telescopes, etc. is prohibitively complex for existing heuristics-based scheduling techniques. The project was a two-year collaboration spanning multiple Sandia centers and included a partnership with Texas A&M University. We have developed algorithms and software for collection scheduling, remote sensor field-of-view pointing models, and bandwidth-constrained prioritization of sensor data. Our approach followed best practices from the operations research and computational geometry communities. These models provide several advantages over state of the art techniques. In particular, our approach is more flexible compared to heuristics that tightly couple models and solution techniques. First, our mixed-integer linear models afford a rigorous analysis so that sensor planners can quantitatively describe a schedule relative to the best possible. Optimal or near-optimal schedules can be produced with commercial solvers in operational run-times. These models can be modified and extended to incorporate different scheduling and resource constraints and objective function definitions. Further, we have extended these models to proactively schedule sensors under weather and ad hoc collection uncertainty. This approach stands in contrast to existing deterministic schedulers which assume a single future weather or ad hoc collection scenario. The field-of-view pointing algorithm produces a mosaic with the fewest number of images required to fully cover a region of interest. The bandwidth-constrained algorithms find the highest priority information that can be transmitted. All of these are based on mixed-integer linear programs so that, in the future, collection scheduling, field-of-view, and bandwidth prioritization can be combined into a single problem. Experiments conducted using the developed models, commercial solvers, and benchmark datasets have demonstrated that proactively scheduling against uncertainty regularly and significantly outperforms deterministic schedulers.

47 OTHER INSTRUMENTATION↗

Recent advances in MoS{sub 2} nanostructured materials for energy and environmental applications – A review

Molybdenum disulfide (MoS{sub 2}), a layered transition metal dichalcogenide with an analogous structure to graphene, has attracted enormous attention worldwide owing to its use in a variety of applications such as energy storage, energy conversion, environmental remediation and sensors. MoS{sub 2} and graphene have almost similar functional properties such as high charge carrier transport, high wear resistance and good mechanical strength and friction. However, MoS{sub 2} is advantageous over graphene due to its low-cost, abundancy, tailorable morphologies and tuneable band gap with good visible light absorption properties. In this review, we have focussed mainly on recent advances in MoS{sub 2} nanostructured materials for the applications in the broad area of energy and environment. Special attention has been paid to their applications in dye-sensitized solar cells, supercapacitor, Li-ion battery, hydrogen evolution reaction, photocatalysis for the degradation of organic pollutants, chemical/bio sensors and gas sensors. Finally, the challenges to design MoS{sub 2} nanostructures suitable for energy and environmental applications are also highlighted. - Highlights: • Applications of MoS{sub 2} nanostructures towards energy, environmental remediation and sensors were summarized. • Recent advances in the development of MoS{sub 2} nanostructured materials were systematically investigated. • Wide range of energy applications including DSSCs, supercapacitors, Li-ion batteries and HER were reviewed. • Key challenges and optimization of structure for superior performance associated with MoS{sub 2} nanostructures were discussed. • Advances of environmental remediation based on MoS{sub 2} nanostructures were significantly highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Void-Engineered Metamaterial Delay Line with Built-In Impedance Matching for Ultrasonic Applications

Metamaterials exhibit unique ultrasonic properties that are not always achievable with traditional materials. However, the structures and geometries needed to achieve such properties are often complex and difficult to obtain using common fabrication techniques. In the present research work, we report a novel metamaterial acoustic delay line with built-in impedance matching that is fabricated using a common 3D printer. Delay lines are commonly used in ultrasonic inspection when signals need to be separated in time for improved sensitivity. However, if the impedance of the delay line is not perfectly matched with those of both the sensor and the target medium, a strong standing wave develops in the delay line, leading to a lower energy transmission. The presented metamaterial delay line was designed to match the acoustic impedance at both the sensor and target medium interfaces. This was achieved by introducing graded engineered voids with different densities at both ends of the delay line. The measured impedances of the designed metamaterial samples show a good match with the theoretical predictions. The experimental test results with concrete samples show that the acoustic energy transmission is increased by 120% and the standing wave in the delay line is reduced by over a factor of 2 compared to a commercial delay line.

36 MATERIALS SCIENCE↗

Machine Learning Approach for Spatiotemporal Multivariate Optimization of Environmental Monitoring Sensor Locations

Abstract Long-term environmental monitoring is critical for managing the soil and groundwater at contaminated sites. Recent improvements in state-of-the-art sensor technology, communication networks, and artificial intelligence have created opportunities to modernize this monitoring activity for automated, fast, robust, and predictive monitoring. In such modernization, it is required that sensor locations be optimized to capture the spatiotemporal dynamics of all monitoring variables as well as to make it cost-effective. The legacy monitoring datasets of the target area are important to perform this optimization. In this study, we have developed a machine-learning approach to optimize sensor locations for soil and groundwater monitoring based on ensemble supervised learning and majority voting. For spatial optimization, Gaussian process regression (GPR) is used for spatial interpolation, while the majority voting is applied to accommodate the multivariate temporal dimension. Results show that the algorithms significantly outperform the random selection of the sensor locations for predictive spatiotemporal interpolation. While the method has been applied to a four-dimensional dataset (with two-dimensional space, time, and multiple contaminants), we anticipate that it can be generalizable to higher-dimensional datasets for environmental monitoring sensor location optimization.

Siddiquee, Masudur R.↗