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At least 1,459 records · Page 81

Y-12 Groundwater Protection Program CY 2018 Triennial Report of the Monitoring Well Inspection and Maintenance Program Y-12 National Security Complex Oak Ridge, Tennessee

This document is the Triennial Report for the Well Inspection and Maintenance Program of the Y-12 National Security Complex (Y-12) Groundwater Protection Program (GWPP) at U.S. Department of Energy (DOE) Y-12 and includes monitoring well inspections and well maintenance activities performed at Y-12 during calendar years (CYs) 2016 through 2018. This report formally documents well inspections completed by GWPP on active and inactive groundwater monitoring wells that are part of the Y-12 monitoring network and includes well inspections performed by URS|CH2M Oak Ridge, L.L.C. (UCOR), which administers the DOE Office of Environmental Management Y-12 Water Resources Restoration Program (WRRP). The WRRP includes wells that are utilized for the regulatory monitoring of Resource Conservation and Recovery Act (RCRA) post-closure permits and Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) Remedial Effectiveness and Records of Decision and Solid Waste Disposal Facility (Landfill) permits and includes monitoring wells located at the CERCLA Environmental Management Waste Management Facility. Beginning in 2018, UCOR terminated three of their RCRA post-closure permits and is monitoring the former RCRA-permitted facilities under CERCLA. Consequently, the number of monitoring wells in the Y-12 network that receive UCOR-performed inspections has decreased significantly.

54 ENVIRONMENTAL SCIENCES↗

Testing of Advanced Capabilities to Enable In-time Safety Management and Assurance for Future Flight Operations

In order to refine an initial Concept of Operations, explore Concepts of Use, and expose/validate requirements for future In-Time Aviation Safety Management Systems (IASMS), testing architectures were created, along with a set of capabilities and underlying information exchange protocols. These systems were conceived and developed based on hazards associated with two envisioned urban area flight domains: (1) highly autonomous small uncrewed aerial systems (sUAS) operating at low altitudes, and (2) highly autonomous air taxis. The initial scope of this development is described in [1]; this report provides an update, focusing on the subsequent developments and test activities. As stated in [1], it is important to note that there are many capabilities already in use by the industry (or soon to be in use) that will play critical roles in future IASMS designs. Those reported here were developed to address a gap in the current state-of-the-art regarding specific hazards/risks, and/or to allow for investigation of the interplay between and across hazard types — particularly regarding how overall safety risk can be reduced or managed effectively. Results of testing and development activities are organized by the operational phase wherein a particular capability would be employed (i.e., preflight, in-flight, and post-flight/off-line). Pre-flight: A set of capabilities were developed to help mitigate safety risk prior to flight (e.g., during flight and mission planning). Results of testing summarize (1) validation activities to raise the Technology Readiness Level (TRL) and (2) evaluation activities where the capabilities were applied to flight/mission planning procedures and used by operators/pilots. For the latter, flight plans were automatically assessed, and operators/pilots were notified of hazardous flight segments so as to enable adjustment of the flight plan and re-evaluation, and/or to better inform go/no-go decisions. Capabilities addressed hazards associated with power consumption, third-party risk, wind, navigation system performance, radiofrequency interference, and proximity to geo-spatial threats (e.g., buildings, trees, and no-fly zones). In-flight: Flight experiments tested capabilities that detect and respond to hazards encountered during flight. In the first series, safety hazards were monitored and assessed onboard, and system-generated mitigation maneuvers were recorded (but not acted upon by the vehicle). In the second series, mitigation maneuver commands directed the aircraft in response to safety hazards (i.e., auto-mitigation). The sUAS used for testing is described in full, as is the test architecture, which included commercial avionics, research avionics, and onboard software designed to detect, assess, and respond to hazards. The onboard system was designed as a run-time assurance framework, consistent with [2] and supportive of both supervisory and automated modes. The primary functions included: real-time risk assessment (RTRA), auto-pilot monitoring, constraint monitoring, and contingency select/triggering. RTRA performs integrated risk assessment considering data from several hazard-related monitors (e.g., battery, motors, navigation, communications, population density, and loss-of-control). Post-flight/off-line: Data monitored and recorded during flights can enable IASMS capabilities that execute after flights have completed (or “off-line”). These include: (1) the ability to identify anomalies and trends that may only be observable when comparing data spanning a number of similar flights; (2) the ability to update and validate pre-flight and in-flight capabilities and any underlying models to improve their performance; (3) the ability to report anomalies/off-nominals that may indicate design changes or maintenance actions are needed; and (4) the ability for humans involved in operations to report safety-relevant observations to help in understanding the flight data and/or the operational context of a flight. Progress on three such capabilities is summarized; the first investigates anomaly detection given a limited set of flight logs and applies an approach previously used for space operations. The second explores what could be identified using a larger set of flight logs, including from web-based forums where flight logs are posted by sUAS autopilot users. The third creates a new means of collecting information on UAS incidents and accidents via the Aviation Safety Reporting System (ASRS).

sUAS↗

Quality assurance for online adapted treatment plans: Benchmarking and delivery monitoring simulation

Purpose: An important challenge facing online adaptive radiation therapy is the development of feasible and efficient quality assurance (QA). This project aimed to validate the deliverability of online adapted plans and develop a proof-of-concept online delivery monitoring system for online adaptive radiation therapy QA. Methods: The first part of this project benchmarked automatically online adapted prostate treatment plans using traditional portal dosimetry IMRT QA. The portal dosimetry QA results of online adapted plans were compared to original (unadapted) plans as well as randomly selected prostate IMRT plans from our clinic. In the second part, an online delivery monitoring system was designed and validated via a simulated treatment with intentional multileaf collimator (MLC) errors. This system was based on inputs from the dynamic machine information (DMI), which continuously reports actual MLC positions and machine monitor units (MUs) at intervals of 50 ms or less during delivery. Based on the DMI, the system performed two levels of monitoring/verification during the delivery: (1) dynamic monitoring of cumulative fluence errors resulting from leaf position deviations and visualization using fluence error maps (FEMs); and (2) verification of MLC positions against the treatment plan for potential errors in MLC motion and data transfer at each control point. Validation of the online delivery monitoring system was performed by introducing intentional systematic MLC errors (ranging from 0.5 to 2 mm) to the DMI files for both leaf banks. These DMI files were analyzed by the proposed system to evaluate the system’s performance in quantifying errors and revealing the source of errors, as well as to understand patterns in the FEMs. In addition, FEMs from 210 actual prostate IMRT beams were analyzed using the proposed system to further validate its ability to catch and identify errors, as well as establish error magnitude baselines for prostate IMRT delivery. Results: Online adapted plans were found to have similar delivery accuracy in comparison to clinical IMRT plans when validated with portal dosimetry IMRT QA. FEMs for the simulated deliveries with intentional MLC errors exhibited distinct patterns for different MLC error magnitudes and directions, indicating that the proposed delivery monitoring system is highly specific in detecting the source of errors. Implementing the proposed QA system for online adapted plans revealed excellent delivery accuracy: over 99% of leaf position differences were within 0.5 mm, and >99% of pixels in the FEMs had fluence errors within 0.5 MU. Patterns present in the FEMs and MLC control point analysis for actual patient cases agreed with the error pattern analysis results, further validating the system’s ability to reveal and differentiate MLC deviations. Calculation of the fluence map based on the DMI was performed within 2 ms after receiving each DMI input. Conclusions: The proposed online delivery monitoring system requires minimal additional resources and time commitment to the current clinical workflow while still maintaining high sensitivity to leaf position errors and specificity to error types. The presented online delivery monitoring system therefore represents a promising QA system candidate for online adaptive radiation therapy.

07 ISOTOPE AND RADIATION SOURCES↗

Unlocking Failure Mechanisms and Improvement of Practical Li–S Pouch Cells through In Operando Pressure Study

For Lithium-sulfur (Li-S) battery commercialization, the study at a pouch cell level is essential, as some problems ignored or deemed minimal at the smaller level could have a greater effect on the performance of the larger pouch cell. Herein, the failure mechanisms of Li-S pouch cells are deeply investigated via in operando pressure analysis. It is found that highly porous structures of cathodes/separators and slow electrolyte diffusion through cathodes/separators can both lead to poor initial wetting. Additionally, Li-metal anode dominates the thickness variation of the whole pouch cell, which is verified by in situ measured pressure variation. Consequently, a real-time approach that combined normalized pressure with dP/dV analysis is proposed and validated to diagnose the morphology evolution of Li-metal anode. Moreover, applied pressure and porosity/tortuosity ratio of the cathode are both identified as independent factors that influence anode performance. In addition to stabilizing anodes, high pressure is proven to improve the cathode connectivity and avoid cathode cracking over cycling, which improves the possibility of developing cathodes with high sulfur mass loading. Here, this work provides insights into Li-S pouch cell design (e.g., cathode and separator) and highlights pathways to improve cell capacity and cycling performance with applied and monitored pressure.

25 ENERGY STORAGE↗

Imputation for multisource data with comparison and assessment techniques

Missing data are prevalent issue in analyses involving data collection. The problem of missing data is exacerbated for multisource analysis, where data from multiple sensors are combined to arrive at a single conclusion. In this scenario, it is more likely to occur and can lead to discarding a large amount of data collected; however, the information from observed sensors can be leveraged to estimate those values not observed. We propose two methods for imputation of multisource data, both of which take advantage of potential correlation between data from different sensors, through ridge regression and a state-space model. These methods, as well as the common median imputation, are applied to data collected from a variety of sensors monitoring an experimental facility. Performance of imputation methods is compared with the mean absolute deviation; however, rather than using this metric to solely rank themethods,we also propose an approach to identify significant differences. Imputation techniqueswill also be assessed by their ability to produce appropriate confidence intervals, through coverage and length, around the imputed values. Finally, performance of imputed datasets is compared with a marginalized dataset through a weighted k-means clustering. In general, we found that imputation through a dynamic linearmodel tended to be the most accurate and to produce the most precise confidence intervals, and that imputing the missing values and down weighting them with respect to observed values in the analysis led to the most accurate performance.

97 MATHEMATICS AND COMPUTING↗

Contrasting Chemical Kinetic Parameters for Near In‐Service‐Temperature Aging and High‐Temperature Thermal Decomposition of Triaminotrinitrobenzene Formulations

Triaminotrinitrobenzene-based high explosives such as LX-17 offer high energy density and exceptional safety, yet their long-term aging behavior at low temperatures remains poorly understood. In this study, several legacy and new production lots of LX-17 were subjected to accelerated aging experiments below 100°C, during which the formation rate of the initial degradation product, monofurazan (F1), was monitored. Kinetic analysis was performed using a sample-age-aware computational approach, yielding activation energy estimates of 82–91 kJ mol −1 for the low-temperature initiation step—markedly lower than the ∼200 kJ mol −1 associated with high-temperature thermal decomposition. Extrapolation from established cookoff models supports the conclusion that the dominant degradation mechanism at low temperatures differs from that at high temperatures. In conclusion, our results provide a unified kinetic framework that bridges the gap between in-service conditions and high-temperature damage.

Chemistry - Chemical explosives↗

SCC Initiation Behavior of Alloy 182 in PWR Primary Water

SCC initiation behavior of 15% cold forged specimens cut from four different alloy 182 weldments was investigated in 360°C simulated PWR primary water under constant load at the yield stress using direct current potential drop to perform in-situ monitoring of SCC initiation time. Within each weldment, one or more specimens underwent SCC initiation within 24 hours of reaching full load while some specimens had much longer initiation times, in a few cases exceeding 2500 hours. Detailed examinations were conducted on these specimens with a focus on different microstructural features such as preexisting defects, grain orientation and second phases, highlighting an important role of microstructure in crack initiation of alloy 182.

Alloy 182↗

Predictions of macro-scale fracture geometries from acoustic emission point cloud data in a hydraulic fracturing experiment

Observations of laboratory fracture testing by means of acoustic emission (AE) can provide a wealth of information regarding the fracturing process and the subsequent damage of the material or structure under load. A method for determining the structure of macro-scale fractures from a point cloud of AE events was developed and tested at the laboratory scale. An unconfined hydraulic fracturing experiment was performed on granite while monitoring acoustic emissions from six piezoelectric transducers on the surfaces of the specimen. The granite specimen dimensions were 30 × 30 × 25 cm 3 . The motivation of the AE analysis was to provide location information for a secondary wellbore placement which intersects the hydraulic fracture to complete a hydraulically connected binary well-hydraulic fracture system. Information gained from the 3D event source locations was used to optimize the location and orientation of secondary production well placement to intersect the induced hydraulic fracture. A direct method was developed to predict the location, orientation and shape of the hydraulic fracture from a dense cloud of AE events. The predicted fracture plane, which was assumed to be planar, was rotated in both the pitch and roll directions, while an average error of AE event distance between the assumed plane and the individual event locations was determined for each rotation iteration, resulting with a predicted fracture plane in the minimum error orientation. Post-test fracture observations were made and digitized in 3D space from coring and slabbing the granite specimen. The actual fracture observations were compared with the predicted fracture structure from AE and showed marked correlation. In conclusion, the simple method of determining macro-scale fracture location, orientation, and extents provided a useful tool for materials that exhibit large and disperse clouds of AE activity where coalesced fracture structure is not apparent.

42 ENGINEERING↗

Iodine effective diffusion coefficients through volcanic rock: Influence of iodine speciation and rock geochemistry

Accurate prediction of the subsurface transport of iodine species is important for the assessment of long-term nuclear waste repository performance, as well as monitoring compliance with the Comprehensive Nuclear-Test-Ban Treaty, given that radioiodine decays into radioxenon. However, the transport of iodine through intact geologic media is not well understood, compromising our ability to assess risk associated with radioiodine migration. The current study's goal is to quantify the matrix diffusion of iodine species through saturated volcanic rock, with particular attention paid to the redox environment and potential speciation changes. Here, diffusion experiments were run for iodide through lithophysae-rich lava, lithophysae-poor lava, and welded tuff, whereas iodate diffusion was studied through welded tuff. Iodine transport was compared with a conservative tracer, HDO, and effective diffusion coefficients were calculated. Likely due to a combination of size and anion exclusion effects, iodine species diffused more slowly than the conservative tracer through all rock types tested. Furthermore, oxidation of iodide to iodate was observed in the lithophysae-poor lava, affecting transport. Results provide much needed data for subsurface transport models that predict radioiodine migration from underground sources, and indicate the pressing need for geochemical and redox interactions to be incorporated into these models.

58 GEOSCIENCES↗

Investigation of the role of deposition rate on optical, microstructure and ethanol sensing characteristics of nanostructured Sn doped In2O3 films

Highlights: • Deposition rate can play an important role in gas sensing of In{sub 2}O{sub 3}:Sn films. • The crystallite size and linear defects of the films is estimated by eCMWP method. • The correlation between the optical, microstructure and gas sensing properties is studied. • The size distribution behavior of samples is in agreement with the results of porosity. • Optimum deposition rate for In{sub 2}O{sub 3}:Sn films is 0.2 nm/s. - Abstract: In this paper, Sn doped In{sub 2}O{sub 3} (In{sub 2}O{sub 3}:Sn) nanostructured films as metal oxide semiconductor material which is very important in optoelectronics and gas sensing industries, were prepared by thermal evaporation technique. It is discussed how different deposition rate (0.1, 0.2, 0.3 and 0.4 nm/s) affects the optical, electrical, microstructural and ethanol gas sensing characteristics of In{sub 2}O{sub 3}:Sn films and must be precisely monitored. The gas sensing performance of the films was evaluated in terms of gas concentration and operating temperature. A correlation between the crystallite size, porosity, dislocation density, outer cut-off radius of dislocation, optical band gap, activation energy and sensitivity of the films was established. The results demonstrate that the maximum sensitivity to ethanol vapors can be obtained for the sample grown at deposition rate of 0.2 nm/s. The response and recovery times of this sensor exposed to 100 ppm of ethanol vapors were determined and found to be 9.0 s and 3.9 s, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The GlueX beamline and detector

The GlueX experiment at Jefferson Lab has been designed to study photoproduction reactions with a 9-GeV linearly polarized photon beam. The energy and arrival time of beam photons are tagged using a scintillator hodoscope and a scintillating fiber array. The photon flux is determined using a pair spectrometer, while the linear polarization of the photon beam is determined using a polarimeter based on triplet photoproduction. Charged-particle tracks from interactions in the central target are analyzed in a solenoidal field using a central straw-tube drift chamber and six packages of planar chambers with cathode strips and drift wires. Electromagnetic showers are reconstructed in a cylindrical scintillating fiber calorimeter inside the magnet and a lead-glass array downstream. Charged particle identification is achieved by measuring energy loss in the wire chambers and using the flight time of particles between the target and detectors outside the magnet. The signals from all detectors are recorded with flash ADCs and/or pipeline TDCs into memories allowing trigger decisions with a latency of 3.3 $μs$. The detector operates routinely at trigger rates of 40 kHz and data rates of 600 megabytes per second. Here, we describe the photon beam, the GlueX detector components, electronics, data-acquisition and monitoring systems, and the performance of the experiment during the first three years of operation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

PV backsheets survey protocol: A framework for geo-spatial field surveys for bulk material characterization and reliability analysis applied across 41 PV systems

As widespread adoption of photovoltaic (PV) technologies continues, understanding the lifetime of modules is paramount to the viability of the industry as an environmentally conscious alternative to traditional energy generation. Although power degradation can affect the total energy production of a module over its lifetime, module safety failures necessitate the removal of a module leading to a loss of not only the particular asset, but the earning potential of the device. Therefore, it is critical to ensure that the components that provide essential safety functions for PV module operate for their entire rated lifetime. PV backsheets provide necessary electrical insulation to the completed device and failure of this component is cause for a immediate removal of the module. Degradation of the PV module backsheet has led to module safety failures in large-scale installations, costing millions of dollars in damages and lost potential revenue. The spatio-temporal degradation of fielded PV modules is important to study in order to identify which modules within installations are experiencing the greatest exposure conditions and in turn have the highest chance of failure. This paper describes a comprehensive field survey protocol developed for monitoring PV module backsheet performance using solely non-destructive methods in commercial PV fields. The protocol establishes a field naming convention, sampling method, data handling requirements, and measurement procedures. By ensuring consistent data collection practices, the field survey protocol enables research groups to obtain data of uniform quality on backsheet performance over multiple years and locations. In this study, the developed protocol was implemented at forty-one PV sites. Eight different types of airside layer backsheet materials including poly(vinylidene fluoride) (PVDF), acrylic PVDF, poly(tetrafluoroethylene-co-hexafluoropropylene-co-vinylidene fluoride) (THV), poly(vinyl fluoride) (PVF), poly(ethylene terephthalate) (PET), fluoroethylene vinyl ether (FEVE), polyethylene naphthalate (PEN), and glass were identified using attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. The field survey results show that the spatial distribution of degradation indicators are non-uniform within a particular module, individual site, and across site locations. The degradation of PV modules increased in severity for modules mounted at the edge of rows (across a field) and near the junction box (within a module). This study demonstrates the sensitivity of material performance to exposure length across different materials and climates.

14 SOLAR ENERGY↗

Dry anaerobic digestion of cow manure and agricultural products in a full-scale plant: Efficiency and comparison with wet fermentation

Highlights: • The first full-scale, agricultural dry fermentation plant of Italy was monitored. • Recirculation rate, leachate, biogas and energy production were monitored. • Dry fermentation showed biogas yields similar to wet. • Retention time, recirculation of digestate and leachate are key factors. • Plant operation required significant man labor (loading and unloading of reactors). - Abstract: For years, anaerobic digestion processes have been implemented for the management of organic wastes, agricultural residues, and animal manure. Wet anaerobic digestion still represents the most common technology, while dry fermentation, dedicated to the treatment of solid inputs (TS > 20%) can be considered as an emerging technology, not in terms of technological maturity, but of diffusion. The first agricultural dry anaerobic digestion plant constructed in Italy was monitored from the start-up, for over a year. The plant was fed with manure and agricultural products, such as corn silage, triticale, ryegrass, alfalfa, and straw. Three Combined Heat and Power units, for a total installed power of 910 kW{sub e}, converted biogas into thermal and electric energy. The monitoring included the determination of quality and quantity of input feedstocks, of digestate (including recirculation rate), of leachate, biogas quality (CH{sub 4}, CO{sub 2}, H{sub 2}S), biogas yield, energy production, labor requirement for loading, and unloading operations. The results of the monitoring were compared to performance data obtained in several full scale wet digestion plants. The dry fermentation plant revealed a start-up phase that lasted several months, during which the average power resulted in 641 kW{sub e} (70.4% of nominal power), and the last period the power resulted in 788 kW{sub e} (86.6% of installed power). Improving the balance of the input, the dry fermentation process demonstrated biogas yields similar to wet anaerobic digestion, congruent to the energy potential of the biomasses used in the process. Furthermore, the operation of the plant required significant man labor, mainly related to loading and unloading of the anaerobic cells.

09 BIOMASS FUELS↗

Exploring Approaches for Accelerated Mass Spectrometric Detection of Fluorochemicals from Aqueous Solutions Using Indirect, Adsorbent-Facilitated Desorption Ionization

There is a growing need for rapid, low-cost analytical tools to screen water supplies for persistent contaminants. Due to their ubiquitous presence in the environment and their detrimental effects on human health, there is a public interest in widespread testing for perfluoroalkyl substances (PFAS). However, the most common methods for PFAS analysis can be time-intensive, requiring a preconcentration step followed by liquid chromatography–mass spectrometry (LC–MS), and are cost-prohibitive for most members of the public. To address these challenges, this study explores a novel method for rapid analysis of aqueous analytes by concentrating analytes on solid adsorbents and detecting them using mass spectrometric analysis via desorption ionization directly from the adsorbent surface. We demonstrate this general approach of indirect solution analysis (ISA) with desorption electrospray ionization (ISA-DESI) and laser desorption ionization (ISA-LDI). Various adsorbent materials were screened, including commercial mesoporous carbons, alumina, and metal–organic frameworks (MOFs). Using ISA-DESI, we consistently detect concentrations as low as 5–100 parts per trillion (ppt) for perfluorooctanoic acid (PFOA) and 10–100 ppt for perfluoroundecanoic acid (PFUnDA). This approach enables rapid detection in under 5 min, making it suitable for applications requiring trace detection with fast response times. We further demonstrate the use of ISA-DESI on a range of environmentally relevant contaminants. Advantages of this indirect solution analysis approach include simplified sample preparation, accelerated analysis, and low cost with readily available materials, making it a promising tool to accelerate mass spectrometric PFAS detection for identifying contaminated sites, performing laboratory studies, and monitoring industrial waste streams.

Bays, Nathan Robert [Sandia National Laboratories ↗

Infrared spectroscopic and modeling studies of H{sub 2}/CH{sub 4} microwave plasma gas phase from low to high pressure and power

InfraRed Tunable Diode Laser Absorption Spectroscopy technique has been implemented in a H{sub 2}/CH{sub 4} Micro-Wave (MW frequency f = 2.45 GHz) plasma reactor dedicated to diamond deposition under high pressure and high power conditions. Parametric studies such as a function of MW power, pressure, and admixtures of methane have been carried out on a wide range of experimental conditions: the pressure up to 270 mbar and the MW power up to 4 kW. These conditions allow high purity Chemical Vapor Deposition diamond deposition at high growth rates. Line integrated absorption measurements have been performed in order to monitor hydrocarbon species, i.e., CH{sub 3}, CH{sub 4}, C{sub 2}H{sub 2}, C{sub 2}H{sub 4}, and C{sub 2}H{sub 6}. The densities of the stable detected species were found to vary in the range of 10{sup 12}–10{sup 17} molecules cm{sup −3}, while the methyl radical CH{sub 3} (precursor of diamond growth under these conditions) measured into the plasma bulk was found up to 10{sup 14} molecules cm{sup −3}. The experimental densities have been compared to those provided by 1D-radial thermochemical model for low power and low pressure conditions (up to 100 mbar/2 kW). These densities have been axially integrated. Experimental measurements under high pressure and power conditions confirm a strong increase of the degree of dissociation of the precursor, CH{sub 4}, associated to an increase of the C{sub 2}H{sub 2} density, the most abundant reaction product in the plasma.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Wavefront modulation and controlling for Lamb waves using surface bonded slice lenses

We present that there is a growing interest in controlling the propagation of Lamb waves to achieve better performance for structural health monitoring and nondestructive evaluation. In this study, we present new methods of controlling Lamb waves using simple slice lenses through wavefront modulation. The lenses are made of metal slices with designed shapes. Once bonded on plates, the lenses modify the effective plate thickness, and therefore change the Lamb wave characteristics such as the wavenumber and phase velocity, providing convenient ways of modulating wavefront and controlling Lamb waves in plates. Numerically and experimentally, we demonstrated that a straight wavefront A 0 mode can be focused on the desired focal point using a plano-concave aspherical lens. We also demonstrated that the A 0 mode can be steered with different frequency components steered to different directions using a simple prism made of metal slices. The work shows that such simple slice lenses provide easy ways for controlling Lamb waves, and have a great potential for Lamb wave based applications.

42 ENGINEERING↗

A Data-Driven Method for Estimating Behind-the-Meter Photovoltaic Generation in Hawaii

Due to the increasing penetration of distributed behind-the-meter photovoltaic (PV) systems and the installed utility revenue metering limited to monitoring only the net power import/export of the household, it is increasingly challenging for utilities to effectively plan and operate the grid. This paper proposes a methodology that estimates behind-the-meter PV generation using a selected subset of monitored PV systems. It is a data-driven approach, and the PV output is estimated utilizing a statistic regression model. A Minimum Redundancy Maximum Relevance (MRMR) algorithm is applied to preselect the optimal subset of the monitored PV systems. The performance of this approach is compared with a spatial interpolation method and a model-based approach. The proposed method is validated using high-resolution meter data recorded from 18 residential rooftop PV systems located on the island of Maui, Hawaii.

Data-driven modeling↗

Estimation Matrix Calibration of PMU Data-driven State Estimation Using Neural Network

Linear state estimation (LSE) is a phasor measurement unit (PMU) data-based power system state estimation that incorporates a linear measurement model in rectangular coordinates. Due to the high computational efficiency and high observational time-resolution, LSE can act as a supplementary state estimation in a wide-area monitoring system (WAMS). The performance of LSE is relatively sensitive to noises in measurements. Therefore, the estimation accuracy relies heavily on the accuracy of the estimation matrix, which is directly influenced by the measurement weight matrix. This paper proposes two novel calibration method of the estimation matrix using neural networks. One is based on the minimum absolute network loss (ANL), and the other is based on the minimum average squared network loss (ASNL). Both methods are tested and compared with LSE algorithms on the IEEE 14-bus system

neural network↗