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At least 199 records · Page 11

Fiber Optic Sensors for Smart Materials and Structures

In this paper we describe recently developed fiber sensors which are capable of monitoring the health of smart-structures. The unobstrusive geometry of these sensors make them an excellent choice for embedding the sensor in composite materials to measure internal states of strain in structures and materials. Some of these sensors have gage lengths that can be tailored from tens of microns to many meters. We will describe various demodulation schemes (Pseudo-Heterodyne, Synthetic-Heterodyne, Homodyne, Differential-Cross Multiplier, and Single Channel Phase-Tracker) to obtain high bandwidth measurements, enabling measurement of static to high frequency impact generated strains with a dynamic response exceeding tens of thousands of microstrains. In addition, we will show that we can tailor the fiber sensor to either measure only strain and reject temperature response or measure only the temperature, or measure both temperature and strain simultaneously. We will also demonstrate the ability to measure multiple strain components inside a host simultaneously using a single fiber sensor embedded in the host using a certain sensor type and transverse strain immunity using another sensor type. Additionally we will show the ability to measure temperature up to 100 C using fiber optic sensors.

Singh, H.↗

Co-Simulation of Electric Power Distribution Systems and Buildings including Ultra-Fast HVAC Models and Optimal DER Control

Smart homes and virtual power plant (VPP) controls are growing fields of research with potential for improved electric power grid operation. A novel testbed for the co-simulation of electric power distribution systems and distributed energy resources (DERs) is employed to evaluate VPP scenarios and propose an optimization procedure. DERs of specific interest include behind-the-meter (BTM) solar photovoltaic (PV) systems as well as heating, ventilation, and air-conditioning (HVAC) systems. The simulation of HVAC systems is enabled by a machine learning procedure that produces ultra-fast models for electric power and indoor temperature of associated buildings that are up to 133 times faster than typical white-box implementations. Hundreds of these models, each with different properties, are randomly populated into a modified IEEE 123-bus test system to represent a typical U.S. community. Advanced VPP controls are developed based on the Consumer Technology Association (CTA) 2045 standard to leverage HVAC systems as generalized energy storage (GES) such that BTM solar PV is better utilized locally and occurrences of distribution system power peaks are reduced, while also maintaining occupant thermal comfort. An optimization is performed to determine the best control settings for targeted peak power and total daily energy increase minimization with example peak load reductions of 25+%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Community-scale interaction of energy efficiency and demand flexibility in residential buildings

Demand-side management (DSM) strategies, including energy efficiency (EE) and demand flexibility (DF), contribute to cost-effective operation of the electricity grid. From a system-level perspective, such programs reduce costs, enhance reliability, and reduce network issues. Similarly, DSM programs help participating customers reduce utility bills while maintaining occupant comfort. Understanding the relationship between EE and DF is key to realizing the full potential of DSM programs. In this study, we modeled an all-electric residential community based on a 498-home community that is planned for construction in Fort Collins, Colorado in the United States. We used this community model to study the relationship between different EE measures, including building envelope upgrades and smart appliances, and DF enabled by a home energy management system (HEMS) responding to a time-varying tariff. Various EE levels in the homes – code-minimum, zero energy ready, and even higher levels of envelope efficiency – were simulated. DF is enabled by the HEMS, which coordinates behind-the-meter resources, including flexible building loads, PV, and home battery systems, to minimize utility bills while maintaining occupant comfort. When comparing to the code-minimum homes, EE upgrades alone reduce HVAC energy use during peak hours by up to 50% and the HVAC utility bill by up to $312/year. With the addition of HEMS, the average daily peak demand can be reduced by up to 0.58 MW or 1.2 kW/home in the higher envelope efficiency homes. The combination of EE upgrades, HEMS, and home battery systems is expected to save homeowners up to $590/year while increasing community load flexibility. However, HEMS and home battery systems are less effective in increasing the DF in the more efficient homes due to the lower load.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hierarchical, Grid-Aware, and Economically Optimal Coordination of Distributed Energy Resources in Realistic Distribution Systems

Renewable portfolio standards are targeting high levels of variable solar photovoltaics (PV) in electric distribution systems, which makes reliability more challenging to maintain for distribution system operators (DSOs). Distributed energy resources (DERs), including smart, connected appliances and PV inverters, represent responsive grid resources that can provide flexibility to support the DSO in actively managing their networks to facilitate reliability under extreme levels of solar PV. This flexibility can also be used to optimize system operations with respect to economic signals from wholesale energy and ancillary service markets. Here, we present a novel hierarchical scheme that actively controls behind-the-meter DERs to reliably manage each unbalanced distribution feeder and exploits the available flexibility to ensure reliable operation and economically optimizes the entire distribution network. Each layer of the scheme employs advanced optimization methods at different timescales to ensure that the system operates within both grid and device limits. The hierarchy is validated in a large-scale realistic simulation based on data from the industry. Simulation results show that coordination of flexibility improves both system reliability and economics, and enables greater penetration of solar PV. Discussion is also provided on the practical viability of the required communications and controls to implement the presented scheme within a large DSO.

distribution network↗

Modeling and Detection of Future Cyber-Enabled DSM Data Attacks

Demand-Side Management (DSM) is an essential tool to ensure power system reliability and stability. In future smart grids, certain portions of a customer’s load usage could be under the automatic control of a cyber-enabled DSM program, which selectively schedules loads as a function of electricity prices to improve power balance and grid stability. In this scenario, the security of DSM cyberinfrastructure will be critical as advanced metering infrastructure and communication systems are susceptible to cyber-attacks. Such attacks, in the form of false data injections, can manipulate customer load profiles and cause metering chaos and energy losses in the grid. The feedback mechanism between load management on the consumer side and dynamic price schemes employed by independent system operators can further exacerbate attacks. To study how this feedback mechanism may worsen attacks in future cyber-enabled DSM programs, we propose a novel mathematical framework for (i) modeling the nonlinear relationship between load management and real-time pricing, (ii) simulating residential load data and prices, (iii) creating cyber-attacks, and (iv) detecting said attacks. In this framework, we first develop time-series forecasts to model load demand and use them as inputs to an elasticity model for the price-demand relationship in the DSM loop. This work then investigates the behavior of such a feedback loop under intentional cyber-attacks. We simulate and examine load-price data under different DSM-participation levels with three types of random additive attacks: ramp, sudden, and point attacks. We conduct two investigations for the detection of DSM attacks. The first studies a supervised learning approach, with various classification models, and the second studies the performance of parametric and nonparametric change point detectors. Results conclude that higher amounts of DSM participation can exacerbate ramp and sudden attacks leading to better detection of such attacks, especially with supervised learning classifiers. We also find that nonparametric detection outperforms parametric for smaller user pools, and random point attacks are the hardest to detect with any method.

97 MATHEMATICS AND COMPUTING↗

Advanced Semi-Supervised Learning with Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Semi-Supervised Learning With Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

EVs-at-RISC: A Secure and Resilient Interoperable SCM Control System Architecture for Electric Vehicle’s-at-Scale (Final Technical Report)

The EVs-at-RISC project was a five-year research, development, and demonstration initiative to create foundational tools for utility-scale fleet aggregation and Smart Charge Management (SCM) of Electric Vehicles (EV), Electric Vehicle Charging Infrastructure (EVCI), and related Distributed Energy Resources (DER). Rather than seeking to develop and demonstrate highly perfected SCM algorithms and control strategies, this project instead focused on creating foundational software solutions that enable unprecedented digital interoperability across the communications technologies and vendor platforms used to manage EV , EVCI, and DER, as well as existing energy management infrastructure operated by utilities, grid operators, and aggregators. This project then extends these novel interoperability capabilities to develop and deploy powerful middleware abstractions across grid edge networks and EVCI/DER fleet aggregations incorporating modern software tools and best practices, such as CI/CD, to bring the immense capabilities of infrastructure-as-code and policy-as-code to modern grid edge network environments. This addresses the foremost systemic issues preventing realization of any net operational benefits from scaled deployment of behind-the-meter EV, EVCI, and DER assets in electric power grids and markets today. The results of this approach and project unlock massive potential for new SCM capabilities to be easily prototyped, evaluated, and deployed at-scale within the existing grid edge network infrastructure and EVCI/DER technology ecosystem. The EVs-at-RISC project achieves this by extending Open Field Message Bus (OpenFMB), a conceptual model for digital interoperability and distributed intelligence in traditional front-of-meter utility SCADA networks, validating our hypothesis that OpenFMB could be similarly used to solve systemic digital interoperability issues in behind-the-meter environments and unlock real-world utility-scale SCM capabilities without requiring any new proprietary vendor solutions or significant infrastructure reconfiguration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A contextual sensor system for non-intrusive machine status and energy monitoring

Event-driven contexts in manufacturing occur pervasively as a result of interactions among involved entities such as machines, workers, materials, and environment. One of the primary tasks in smart manufacturing is to derive a context-aware system conveniently incorporating worker knowledge for generating timely actionable intelligence for workers on factory floor and supervisors to respond. In this paper, we propose to design a human-and-machine interaction recognition framework by using a causality concept to collect contextual data for classifications of normal and abnormal machine operations. The causes and effects are between workers and machines for this initial research. To apply the causality to recognize worker interactions, initially a reliable way to identify the states of machines is necessary. The proposed contextual sensor system, consisting of a power meter for measuring machine operation conditions, a visual camera for capturing worker and machine interactions via a finite state machine model, and an algorithm for determining power signatures of individual components via energy disaggregation is implemented on semiconductor fabrication machines (manual or PLC controlled) each with multiple components. The experiment results demonstrate its context extraction capability such as components states and their corresponding energy usage in real time as well as its ability to identify anomalous operation conditions.

47 OTHER INSTRUMENTATION↗

Transactive Campus Energy Systems: An R&D Testbed for Renewables, Integration, Efficiency, and Grid Services (CRADA 356 / Amendment 1)

The Clean Energy and Transactive Campus (CETC) work described in this report was done as part of Amendment 1 to Campus Cooperative Research and Development Agreement (CRADA) 356, the Transactive Campus CRADA with the Washington State Department of Commerce (Commerce) between the U.S. Department of Energy’s (DOE’s), Pacific Northwest National Laboratory (PNNL) and the Commerce through the Clean Energy Fund (CEF). The original project team consisted of PNNL, the University of Washington (UW) and Washington State University (WSU), to connect the PNNL, UW, and WSU campuses to construct and operate the testbed as both a regional flexibility resource and as a platform for research and development (R&D) for buildings/grid integration. Building on the foundational transactive system established by the Pacific Northwest Smart Grid Demonstration (PNWSGD), the purpose of the project was to construct the testbed as both a regional flexibility resource and as a platform for R&D on buildings/grid integration and information-based energy efficiency. The testbed supports the integration of renewables and other regional needs, using the flexibility provided by building loads, energy storage, and smart inverters for batteries and photovoltaic (PV) solar systems, at four physical scales: multiple campuses, campus, microgrid and building.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electrical Fault and Power Quality Detection Algorithms and Customer-Owned DERs Monitoring with a Cyber Grid Guard System and DLT

In this study, the electrical fault and power quality detection algorithms and customer-owned DERs monitoring use cases were implemented, with a Cyber Grid Guard system and DLT. Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substations, and are associated with customer-owned distributed energy resources (DERs). Data from these IEDs, such as power meters and protection relays, must be kept confidential and of high integrity. Blockchain technology has the potential to increase microgrid resilience by enhancing data sharing security. The growing use of IEDs and customer-owned renewable energy sources (DERs) may make it necessary to connect Distributed Ledger Technology (DLT) with power system applications. We implemented the electrical faulted phase detection and power quality monitoring algorithms with a Cyber Grid Guard (CGG) system using DLT. In addition, the DERs (wind turbine farms) use case and protective relay cyber-event tests were assessed, by using the CGG system with DLT. In the experimental model, the testbed was created by using a real-time simulator and CGG system with power meters/ protective relays in the loop. The data collected from the CGG system and IEDs were compared with the same time stamp source. These results showed the successful assessment of protection, control and monitoring applications using a CGG system with DLT. In the future, power system applications for the ESGT with DERs and the CGG system will be based on executing smart contracts between electrical utilities and customer-owned DERs.

Piesciorovsky, Emilio↗

Electrical substation grid testbed for DLT applications of electrical fault detection, power quality monitoring, DERs use cases and cyber-events

Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substation, and are associated with customer-owned distributed energy resources (DERs). The integrity and confidentiality of data from these IEDs, like power meters and protective relays, is crucial. Blockchain technology could improve the resilience of microgrids by improving the security of data sharing. The penetration of customer-owned DERs (renewable energy sources) and the increasing deployment of IEDs can lead to integrate power system applications with Distributed Ledger Technology (DLT). In this study, we implemented the electrical faulted phase detection and power quality monitoring algorithms with a Cyber Grid Guard (CGG) system using DLT. In addition, the DERs (wind turbine farms) use case and protective relay cyber-event tests were assessed, by using the CGG system with DLT. In the experimental model, the testbed was created by using a real-time simulator and CGG system with power meters/ protective relays in-the-loop. The data collected from the CGG system and IEDs were compared with the same time stamp source. These results had shown the successful assessment of protection, control and monitoring applications using a CGG system with DLT. In the future, the ESGT with DERs and the CGG system will be used in other power system applications, based on implementing smart contracts between electrical utilities with customer-owned DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SMART CarbonSAFE Model

The modeling work for this project built upon previous work done for the CarbonSAFE Rocky Mountain Phase I. A geologic and dynamic model was built in Petrel version 2019.3 for the area of the Colorado Plateau near Price, Utah. It is located at the north end of the San Rafael Swell in a natural gas field called Drunkards Wash. The model is 61.5 km east-west and 53 km north to south with 123x106x21 cells, giving a cell dimension of 50x50 m2. The 21 layers in the Z direction are of varying thickness depending on the formation. The Carmel, the seal layer, has 3 layers and is about 200 meters thick around the injection well. The Navajo Sandstone, the principal reservoir, has 5 layers and is about 100 meters thick. The Kayenta has 5 layers and is roughly 50 meters thick and the Wingate, a secondary reservoir, has 5 layers and is 120 meters thick. The base of the model is the Chinle Formation with 3 layers and about 120 meters of thickness..

Carbon Dioxide↗

Medium-Voltage Testbed for Comparing Advanced Power Line Sensors vs. Measurement Transformers with Electrical Grid Events

Electrical utilities have relied upon potential transformers (PTs) and current transformers (CTs) for very accurate metering and to provide reliable signals for protective relays. Less expensive alternative sensing technologies offer the possibility of wider deployment, particularly in grids that employ distributed energy resources. In this work, the performance of an advanced medi-um-voltage sensor is compared with a reference PT and CT and experimentally evaluated for different power grid scenarios on an advanced outdoor power line sensor testbed at the US De-partment of Energy’s Oak Ridge National Laboratory. The sensor is based on a capacitive divider for voltage monitoring and a Rogowski coil with integrator for current monitoring. The advanced outdoor power line sensor testbed has a real-time simulator that was used to generate transient scenarios (e.g., electrical faults, capacitor bank operation, service restoration), while the analog signals were recorded by the same high resolution power meter. The behavior of analog signals, harmonic components, total harmonic distortion, and crest factors were assessed for this power line sensor compared with the reference PT/CT, because of the absence for testing standards for advanced outdoor power line sensors.

Piesciorovsky, Emilio↗

Developing and Evaluating a Smart Curtailment Strategy Integrated with a Wind Turbine Manufacturer Platform

The Renewable Energy Wildlife Institute lead a team of scientists, wind developers, and turbine manufacturers in a study to develop and test a “smart curtailment” system intended to help reduce bat collisions with wind turbines. The Vestas Bat Protection System (VBPS) is a newly developed software module within the Supervisory Control and Data Acquisition (SCADA) system of Vestas turbines. The VBPS combines data from commercially available environmental sensors and the turbine’s built-in sensors with the Vestas SCADA system. VBPS is designed to receive environmental data from sensors on the turbine such as temperature, wind speed, wind direction, time of day, and time of year, relays that information to the SCADA system to determine whether to execute turbine curtailments at any given time. The goals of this study were to 1) develop a bat fatality risk model based on bat activity data and environmental data collected in year 1, and to 2) evaluate the VBPS, using the bat fatality risk model to implement curtailment, in comparison to “blanket curtailment” (turbines curtailed when wind speed is below 5.0 meters per second (m/s)) and “control” (normally operating, feathered below 3.0 m/s) turbines in year 2. The field study took place at a wind energy facility in Iowa during the fall bat migration seasons (July – October) in 2021 and 2022. For VBPS to succeed as a viable strategy for the minimization of bat fatalities, it should meet or exceed the performance of blanket curtailment. Specifically, the VBPS should meet the following performance targets to demonstrate whether it an effective, practical risk reduction measure: (1) Turbines operating VBPS should have equal or fewer bat fatalities compared to turbines operating with blanket curtailment, and significantly fewer bat fatalities compared to control turbines; and (2) Turbines operating VBPS should have greater power production compared to turbines operating with blanket curtailment. The study was completed in accordance with the Statement of Project Objectives and within the terms of the Budget Justification. This Final Report describes the progress, challenges, and outcomes of the study.

17 WIND ENERGY↗

Further Development Of Aperture: A Precise Extremely Large Reflective Telescope Using Re-Configurable Elements: NASA Innovative Advanced Concepts (NIAC) - Phase II

One of the pressing needs for space ultraviolet-visible astronomy is a design to allow larger mirrors than the James Webb Space Telescope primary. The diameter of the rocket fairing limits the mirror diameter such that all future missions calling for mirrors up to 16 meters in diameter or larger will require a mirror that is deployed post-launch. In response to the deployment requirement, we address the issues of this concept called "A Precise Extremely Large Reflective Telescope Using Reconfigurable Elements (APERTURE) with both hardware experiments and software simulations... We designed and built several fixtures with O-rings to hold a membrane. We established a coating process to make a membrane that was coated on one side with Cr and the other side with Cr-Terfenol-D-NiCo. The Terfenol-D (T-D hereafter) is the MSM (Magnetic Smart Memory) we use. We bought and established a procedure for measuring a deformation over time and purchased a Shack Hartmann system from Imagine Optic (https://www.imagine-optic.com). The first substrate we used was DuPont (TM) Kapton® polyimide film. Due to material creep, we found the stability over a 48-hour period with a Kapton substrate was not as good as desired (greater than 1 micron). We then switched to CP1 Polyimide. We found the CP1 much more stable to creep, being stable from about 3 hours to 48 hours to within a measurement error to below approximately 0.1 micron. We produced a 13 micron maximum deviation on a 50-millimeter-diameter piece of CP1 (25 microns thick). The T-D coating was about 2 microns, and the other layers, about 10 nanometers. The magnetic field at the base was about 0.1 teslas. We can make the T-D film at least 5 times thicker and the magnetic field at least 5 times stronger, and hence make deformations as much as 25 times larger. We have a formed a collaboration produced at the NIAC (NASA Innovative Advanced Concepts) mid-term review with Dr. Ron Shiri of Goddard Space Flight Center (GSFC) to explore making controlled deviations on lambda/14-lambda/20 scales which are required to bring a surface to the diffraction limit. We carried out only preliminary work on Si using a Coordinate Measuring Machine (CMM), which produced deviations on the 1 micron level. We are still working on a program to bring to GSFC a flat enough (radius of curvature greater than 10 microns) -coated a Si piece with Cr, T-D, NiCo. Then we plan to carry out tests with an interferometer. Further, we formed a new collaboration with Prof. Rajan Vaidyanathan of the University of Central Florida to replace the CP1 with a shape memory alloy (SMA). With his collaboration, we acquired new Federal funding outside of NASA to explore the use of SMAs (we use NiTi). Our preliminary results indicate that we can produce deformations greater than 1 micron on approximately 100 microns thick. Furthermore we have shown that the NiTi can deploy to better than 1 micron of its set original and then trained shape.

Re-Configurable Elements↗

Toward Adaptive X-Ray Telescopes

Future x-ray observatories will require high-resolution (less than 1 inch) optics with very-large-aperture (greater than 25 square meter) areas. Even with the next generation of heavy-lift launch vehicles, launch-mass constraints and aperture-area requirements will limit the surface areal density of the grazing-incidence mirrors to about 1 kilogram per square meter or less. Achieving sub-arcsecond x-ray imaging with such lightweight mirrors will require excellent mirror surfaces, precise and stable alignment, and exceptional stiffness or deformation compensation. Attaining and maintaining alignment and figure control will likely involve adaptive (in-space adjustable) x-ray optics. In contrast with infrared and visible astronomy, adaptive optics for x-ray astronomy is in its infancy. In the middle of the past decade, two efforts began to advance technologies for adaptive x-ray telescopes: The Generation-X (Gen-X) concept studies in the United States, and the Smart X-ray Optics (SXO) Basic Technology project in the United Kingdom. This paper discusses relevant technological issues and summarizes progress toward adaptive x-ray telescopes.

O'Dell, Stephen L.↗

Entry System Design Considerations for Mars Landers

The objective for the next generation or Mars landers is to enable a safe landing at specific locations of scientific interest. The 1st generation entry, descent and landing systems, ex. Viking and Pathfinder, provided successful landing on Mars but by design were limited to large scale, 100s of km, landing sites with minimal local hazards. The 2 nd generation landers, or smart landers, will provide scientists with access to previously unachievable landing sites by providing precision landing to less than 10 km of a target landing site, with the ability to perform local hazard avoidance, and provide hazard tolerance. This 2nd generation EDL system can be utilized for a range of robotic missions with vehicles sized for science payloads from the small 25-70 kg, Viking, Pathfinder, Mars Polar Lander and Mars Exploration Rover-class, to the large robotic Mars Sample Return, 300 kg plus, science payloads. The 2nd generation system can also be extended to a 3nd generation EDL system with pinpoint landing, 10's of meters of landing accuracy, for more capable robotic or human missions. This paper will describe the design considerations for 2nd generation landers. These landers are currently being developed by a consortium of NASA centers, government agencies, industry and academic institutions. The extension of this system and additional considerations required for a 3nd generation human mission to Mars will be described.

Lockwood, Mary Kae↗