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At least 199 records · Page 11

A Novel Nonintrusive Method to Resolve the Thermal Dome Effect of Pyranometers: Radiometric Calibration and Implications

Traditionally the calibration equation for pyranometers assumes that the measured solar irradiance is solely proportional to the thermopile s output voltage; therefore, only a single calibration factor is derived. This causes additional measurement uncertainties because it does not capture sufficient information to correctly account for a pyranometer s thermal effect. In our updated calibration equation, temperatures from the pyranometer's dome and case are incorporated to describe the instrument's thermal behavior, and a new set of calibration constants are determined, thereby reducing measurement uncertainties. In this paper, we demonstrate why a pyranometer's uncertainty using the traditional calibration equation is always larger than a few percent, but with the new approach can become much less than 1% after the thermal issue is resolved. The highlighted calibration results are based on NIST traceable light sources under controlled laboratory conditions. The significance of the new approach lends itself to not only avoiding the uncertainty caused by a pyranometer's thermal effect but also the opportunity to better isolate and characterize other instrumental artifacts, such as angular response and nonlinearity of the thermopile, to further reduce additional uncertainties. We also discuss some of the implications, including an example of how the thermal issue can potentially impact climate studies by evaluating aerosol s direct radiative effect using field measurements with and without considering the pyranometer s thermal effect. The results of radiative transfer model simulation show that a pyranometer s thermal effect on solar irradiance measurements at the surface can be translated into a significant alteration of the calculated distribution of solar energy inside the column atmosphere.

Ji. Q.↗

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach.

Distributed↗

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach.

Distributed↗

Development of a Test-Bed for Testing and Refining EarthEn’s Supercritical CO 2 Based Energy Storage System

EarthEn’s energy storage concept leverages supercritical carbon dioxide (sCO 2 ) as a working fluid and relies on compact, high-performance components operating at elevated pressures and temperatures. To accelerate component development and reduce technical risk prior to larger-scale demonstrations, Oak Ridge National Laboratory (ORNL) developed a 100 kW-scale sCO 2 test-bed under a Cooperative Research and Development Agreement with EarthEn (CRADA NO. NFE-24-10050). The objective of the work was to design and construct a flexible experimental facility capable of reproducing key thermodynamic state points and heat-transfer conditions relevant to EarthEn’s thermal energy storage (TES) cycle, with particular emphasis on enabling development and evaluation of next-generation heat exchangers and TES concepts. The test-bed consists of a closed-loop sCO 2 circulation system housed within an open-topped enclosure. In its as-installed configuration, dense-phase sCO 2 is recirculated through a printed circuit recuperator, an electrically heated section, a throttling device used to simulate turbine expansion, and a water-cooled printed circuit heat exchanger that rejects heat to the building chilled-water system before returning to the pump. The pump is driven by a variable frequency drive, enabling controlled adjustment of flow and operating point. A comprehensive instrumentation suite was integrated to support both safe operation and high-quality data collection. Installed sensors include Coriolis flow meters for sCO 2 flow rate and density, resistance temperature detectors and thermocouples distributed throughout the loop (including the heated section and key heat exchanger ports), and pressure transducers for absolute and differential pressure measurements. The facility was designed to support high-pressure (19 MPa nominal) and high-temperature (575°C nominal) operation with credited overpressure protection provided by a rupture disk. Nominal operating conditions were selected to support 100 kW-class testing while maintaining flexibility for non-heated and heated shakedown, control development, and future integration of advanced TES test sections. In parallel with facility development, a system-level thermal-hydraulic model was created using Modelica-based tools to support component sizing, anticipate performance over targeted test conditions, and establish a framework for future model calibration against experimental data. At the conclusion of the project performance period, the facility was in final assembly, and the pressure boundary was nearly completed. However, several practical challenges associated with high-pressure/high-temperature systems and specialized component procurement impacted schedule and prevented initial pump-driven operation and full commissioning within the available resources. This report documents the as-built design, operating capabilities, and instrumentation, and it summarizes key lessons learned related to heater fabrication and testing, first-of-a-kind assembly factors, specialty flange supply constraints, and fill pump corrective actions. Finally, it outlines a phased plan for future commissioning and experimental campaigns, including control and instrumentation shakedown, heater characterization, model calibration, and testing at state points representative of EarthEn’s TES cycle.

25 ENERGY STORAGE↗

A Novel Non-Intrusive Method to Resolve the Thermal-Dome-Effect of Pyranometers: Radiometric Calibration and Implications

Traditionally the calibration equation for pyranometers assumes that the measured solar irradiance is solely proportional to the thermopile's output voltage; therefore only a single calibration factor is derived. This causes additional measurement uncertainties because it does not capture sufficient information to correctly account for a pyranometer's thermal effect. In our updated calibration equation, temperatures from the pyranometer's dome and case are incorporated to describe the instrument's thermal behavior, and a new set of calibration constants are determined, thereby reducing measurement uncertainties. In this paper, we demonstrate why a pyranometer's uncertainty using the traditional calibration equation is always larger than a-few-percent, but with the new approach can become much less than 1% after the thermal issue is resolved. The highlighted calibration results are based on NIST-traceable light sources under controlled laboratory conditions. The significance of the new approach lends itself to not only avoiding the uncertainty caused by a pyranometer's thermal effect but also the opportunity to better isolate and characterize other instrumental artifacts, such as angular response and non-linearity of the thermopile, to further reduce additional uncertainties. We also discuss some of the implications, including an example of how the thermal issue can potentially impact climate studies by evaluating aerosol's direct-radiative effect using field measurements with and without considering the pyranometer's thermal effect. The results of radiative transfer model simulation show that a pyranometer's thermal effect on solar irradiance measurements at the surface can be translated into a significant alteration of the calculated distribution of solar energy inside the column atmosphere.

Ji, Qiang↗

Monolithic Microwave Integrated Circuit (MMIC) Phased Array Demonstrated With ACTS

Monolithic Microwave Integrated Circuit (MMIC) arrays developed by the NASA Lewis Research Center and the Air Force Rome Laboratory were demonstrated in aeronautical terminals and in mobile or fixed Earth terminals linked with NASA's Advanced Communications Technology Satellite (ACTS). Four K/Ka-band experimental arrays were demonstrated between May 1994 and May 1995. Each array had GaAs MMIC devices at each radiating element for electronic beam steering and distributed power amplification. The 30-GHz transmit array used in uplinks to ACTS was developed by Lewis and Texas Instruments. The three 20-GHz receive arrays used in downlinks from ACTS were developed in cooperation with the Air Force Rome Laboratory, taking advantage of existing Air Force integrated-circuit, active-phased-array development contracts with the Boeing Company and Lockheed Martin Corporation. Four demonstrations, each related to an application of high interest to both commercial and Department of Defense organizations, were conducted. The location, type of link, and the data rate achieved for each of the applications is shown. In one demonstration-- an aeronautical terminal experiment called AERO-X--a duplex voice link between an aeronautical terminal on the Lewis Learjet and ACTS was achieved. Two others demonstrated duplex voice links (and in one case, interactive video links as well) between ACTS and an Army high-mobility, multipurpose wheeled vehicle (HMMWV, or "humvee"). In the fourth demonstration, the array was on a fixed mount and was electronically steered toward ACTS. Lewis served as project manager for all demonstrations and as overall system integrator. Lewis engineers developed the array system including a controller for open-loop tracking of ACTS during flight and HMMWV motion, as well as a laptop data display and recording system used in all demonstrations. The Jet Propulsion Laboratory supported the AERO-X program, providing elements of the ACTS Mobile Terminal. The successful performance of experimental, proof-of-concept MMIC K/Ka-band arrays developed with U.S. industry in field demonstrations with ACTS indicates that high density MMIC integration at 20 and 30 GHz is indeed feasible. The successful development and demonstration of the MMIC array systems was possible only because of significant intergovernmental and Government/industry cooperation and the high level of teamwork within Lewis. The results provide a strong incentive for continuing the focused development of MMIC-array technology for satellite communications applications, with emphasis on packaging and cost issues, and for continuing the planning and conducting of other appropriate demonstrations or experiments of phased-array technology with ACTS. Given the present pressures on reducing funding for research and development in Government and industry, the extent to which this can be continued in a cooperative manner will determine whether MMIC array technology will make the transition from the proof-of-concept level to the operational system level.

Source record↗

Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control

Grid emergency voltage control (GEVC) is paramount in electric power systems to improve voltage stability and prevent cascading outages and blackouts in case of contingencies. While most deep reinforcement learning (DRL)-based paradigms perform single agents in a static environment, real-world agents for GEVC are expected to cooperate in a dynamically shifting grid. Moreover, due to high uncertainties from combinatory natures of various contingencies and load consumption, along with the complexity of dynamic grid operation, the data efficiency and control performance of the existing DRL-based methods are challenged. To address these limitations, we propose a multi-agent graph-attention (GATT)-based DRL algorithm for GEVC in multi-area power systems. Here, we develop graph convolutional network (GCN)-based agents for feature representation of the graph-structured voltages to improve the decision accuracy in a data-efficient manner. Furthermore, a cutting-edge attention mechanism concentrates on effective information sharing among multiple agents, synergizing different-sized subnetworks in the grid for cooperative learning. We address several key challenges in the existing DRL-based GEVC approaches, including low scalability and poor stability against high uncertainties. Test results in the IEEE benchmark system verify the advantages of the proposed method over several recent multi-agent DRL-based algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Titan Orbiter Aerorover Mission with Enceladus Science (TOAMES)

Cassini and Huygens have made exciting discoveries at Titan and Enceladus, and at the same time made us aware of how little we understand about these bodies. For example, the source, and/or recycling mechanism, of methane in Titan's atmosphere is still puzzling. Indeed, river beds (mostly dry) and lakes have been spotted, and occasional clouds have been seen, but the physics to explain the observations is still mostly lacking, since our "image" of Titan is still sketchy and quite incomplete. Enceladus, only -500 km in extent, is even more puzzling, with its fiery plumes of vapor, dust and ice emanating from its south polar region, "feeding" Saturn's E ring. Long term variability of magnetospheric plasma, neutral gas, E-ring ice grain density, radio emissions, and corotation of Saturn's planetary magnetic field in response to Enceladus plume activity are of great interest for Saturn system science. Both Titan and Enceladus are bodies of considerable astrobiological interest in view of high organic abundances at Titan and potential subsurface liquid water at Enceladus. We propose to develop a new mission to Titan and Enceladus, the Titan Orbiter Aerorover Mission with Enceladus Science (TOAMES), to address these questions using novel new technologies. TOAMES is a multi-faceted mission that starts with orbit insertion around Saturn using aerobraking with Titan's extended atmosphere. We then have an orbital tour around Saturn (for 1-2 years) and close encounters with Enceladus, before it goes into orbit around Titan (via aerocapture). During the early reconnaissance phase around Titan, perhaps 6 months long, the orbiter will use altimetry, radio science and remote sensing instruments to measure Titan's global topography, subsurface structure and atmospheric winds. This information will be used to determine where and when to release the Aerorover, so that it can navigate safely around Titan and identify prime sites for surface sampling and analysis. In situ instruments will sample the upper atmosphere which may provide the seed population for the complex organic chemistry on the surface. The Aerorover will probably use a "hot air" Montgolfier balloon concept using the waste heat from the MMRTG 1-2 kwatts. New technologies will need to be developed and miniaturization will be required to maintain functionality while controlling mass, power and cost. Duty cycling will be used. The Aerorover will have all the instruments needed to sample Titan's atmosphere and surface with possible methane lakes-rivers. It will e.g., use multi-spectral imagers and for last 6 months of mission, balloon payload will land on surface at predetermined site to take core samples of the surface and use seismometers to help probe the interior. All remote (and active) sensors on the orbiter will share a - 1 meter telescope, called MIDAS (Multiple Instrument Distributed Aperture Sensor). MIDAS observations in stable orbit at Titan can provide full global maps of Titan's surface and could additionally provide long term observations of the Saturn system including Enceladus for extended mission phases over many years, potentially for decades. Experience from the Hubble Space Telescope has shown strong public interest and commitment to exciting generational missions.

Sittler, Edward C.↗

Local cation ordering in compositionally complex Ruddlesden–Popper n = 1 oxides

The Ruddlesden–Popper (RP) layered perovskite structure is of great interest due to its inherent tunability, and the emergence and growth of the compositionally complex oxide (CCO) concept endows the RP family with further possibilities. Here, a comprehensive assessment of thermodynamic stabilization, local order/disorder, and lattice distortion was performed in the first two reported examples of lanthanum-deficient La n+1 B n O 3n+1 (n = 1, B = Mg, Co, Ni, Cu, Zn) obtained via various processing conditions. Chemical short-range order (CSRO) at the B-site and the controllable excess interstitial oxygen (δ) in RP-CCOs are uncovered by neutron pair distribution function analysis. Reverse Monte Carlo analysis of the data, Metropolis Monte Carlo simulations, and extended x-ray absorption fine structure analysis implies a modest degree of magnetic element segregation on the local scale. Further, ab initio molecular dynamics simulations results obtained from special quasirandom structure disagree with experimentally observed CSRO but confirm Jahn–Teller distortion of CuO 6 octahedra. These findings highlight potential opportunities to control local order/disorder and excess interstitial oxygen in layered RP-CCOs and demonstrate a high degree of freedom for tailoring application-specific properties. They also suggest a need for expansion of theoretical and data modeling approaches in order to meet the innate challenges of CCO and related high-entropy phases.

36 MATERIALS SCIENCE↗

Applying Biomimetic Algorithms for Extra-Terrestrial Habitat Generation

The objective is to simulate and optimize distributed cooperation among a network of robots tasked with cooperative excavation on an extra-terrestrial surface. Additionally to examine the concept of directed Emergence among a group of limited artificially intelligent agents. Emergence is the concept of achieving complex results from very simple rules or interactions. For example, in a termite mound each individual termite does not carry a blueprint of how to make their home in a global sense, but their interactions based strictly on local desires create a complex superstructure. Leveraging this Emergence concept applied to a simulation of cooperative agents (robots) will allow an examination of the success of non-directed group strategy achieving specific results. Specifically the simulation will be a testbed to evaluate population based robotic exploration and cooperative strategies while leveraging the evolutionary teamwork approach in the face of uncertainty about the environment and partial loss of sensors. Checking against a cost function and 'social' constraints will optimize cooperation when excavating a simulated tunnel. Agents will act locally with non-local results. The rules by which the simulated robots interact will be optimized to the simplest possible for the desired result, leveraging Emergence. Sensor malfunction and line of sight issues will be incorporated into the simulation. This approach falls under Swarm Robotics, a subset of robot control concerned with finding ways to control large groups of robots. Swarm Robotics often contains biologically inspired approaches, research comes from social insect observation but also data from among groups of herding, schooling, and flocking animals. Biomimetic algorithms applied to manned space exploration is the method under consideration for further study.

Birge, Brian↗

Enabling Cybersecurity, Situational Awareness and Resilience in Distribution Grids with High Penetration of Photovoltaics (CARE-PV) (Final Report)

Since legacy distribution systems have very limited visibility beyond the substation, high penetration of PV at the grid edge presents some unique operational challenges. One approach to address these challenges is to use information from advanced metering infrastructure (AMI) and µPMUs. However, exploiting this information is impacted by a number of factors, including multi-timescale measurements, volume of data generated, communication network impairments (e.g., information loss and latency) and susceptibility to cyber-attacks. Therefore, one of the critical tasks involved in the management of a distribution grid is to develop complete situational awareness by integrating cyber-security mechanisms with state estimation strategies and leveraging this situational awareness to assure energy services at strategic locations while exploiting AMI/PV inverter/ µPMU data. This CARE-PV project addresses the fundamental challenges in situational awareness and resilience to cyber and physical vectors by exploiting the synergy between innovative modeling, estimation, data analytics, testing and validation using smart PV inverters designed at K-State and facilities at NREL. Specifically, the project involved the development, testing and validation of the following novel enabling technologies: (Thrust 1) Resilience to cyber vectors that impact data integrity was addressed via a two-level defense strategy that combines cyber intrusion detection using self-learning, cooperative smart PV inverters, and a novel moving target defense framework to combat data integrity attacks. (Thrust 2) Resilience to cyber-physical vectors that impact situational awareness by limiting data availability was addressed via novel centralized and decentralized, sparsity-based static and dynamic state estimation approaches that enhance observability even when the underlying system is unobservable. (Thrust 3) Leveraging a unique probabilistic sensitivity analysis approach accompanied by one-of-a-kind dominant influencer set computation, the vulnerability of critical infrastructure at strategic locations was evaluated so that proactive PV-based control strategies can be used to support operations under normal/outage scenarios. These CARE-PV project innovations were demonstrated on both small-scale IEEE and larger utility-scale testbeds (Thrust 4). Feedback from Industry Advisory Board members was used to formulate a commercialization pathway for a subset of CARE-PV technologies. These CARE-PV technologies will ultimately lead to reliable and secure, large-scale integration of renewable energy and mitigate the risk of energy disruption resulting from cyber incidents and other emerging threats within the energy environment.

14 SOLAR ENERGY↗

Comparing Cetane Number Measurement Methods

Cetane number is one of the most important fuel performance metrics for mixing controlled compression-ignition “diesel” engines, quantifying a fuel’s propensity for autoignition when injected into end-of-compression-type temperature and pressure conditions. The historical default and referee method on a Cooperative Fuel Research (CFR) engine configured with indirect fuel injection and variable compression ratio is cetane number (CN) rating. A subject fuel is evaluated against primary reference fuel blends, with heptamethylnonane defining a low-reactivity endpoint of CN = 15 and hexadecane defining a high-reactivity endpoint of CN = 100. While the CN scale covers the range from zero (0) to 100, typical testing is in the range of 30 to 65 CN. Alternatively, several constant-volume combustion chamber (CVCC)-based cetane rating devices have been developed to rate fuels with an equivalent derived cetane number (DCN) or indicated cetane number (ICN). These devices measure ignition delay for fuel injected into a fixed volume of high-temperature and high-pressure air to simulate end-of-compression-type conditions. In this study, a range of novel fuel compounds are evaluated across three CVCC methods: the Ignition Quality Tester (IQT), Fuel Ignition Tester (FIT), and Advanced Fuel Ignition Delay Analyzer (AFIDA). Resulting DCNs and ICNs are compared for fuels within the normal diesel fuel range of reactivity, as well as very high (~100) and very low DCNs/ICNs (~5). Distinct differences between results from various devices are discussed. This is important to consider because some new, high-efficiency advanced compression-ignition (CI) engine combustion strategies operate with more kinetically controlled distributed combustion as opposed to mixing controlled diffusion flames. These advanced combustion strategies may benefit from new fuel chemistries, but current rating methods of CN, DCN, and ICN may not fully describe their performance. In addition, recent evidence suggests ignition delay in modern on-road diesel engines with high-pressure common rail fuel injection systems may no longer directly correlate to traditional CN fuel ratings. Simulated end-of-compression conditions are compared for CN, DCN, and ICN and discussed in the context of modern diesel engines to provide additional insight. Results highlight the potential need for revised and/or multiple fuel test conditions to measure fuel performance for advanced CI strategies.

47 OTHER INSTRUMENTATION↗

Biogeochemistry of upland to wetland soils, sediments, and surface waters across Mid-Atlantic and Great Lakes coastal interfaces

Transferable and mechanistic understanding of cross-scale interactions is necessary to predict how coastal systems respond to global change. Cohesive datasets across geographically distributed sites can be used to examine how transferable a mechanistic understanding of coastal ecosystem control points is. To address the above research objectives, data were collected by the EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) Consortium – a regionally distributed network of researchers that collaborated on experimental design, methodology, collection, analysis, and publication. The EXCHANGE Consortium collected samples from 52 coastal terrestrial-aquatic interfaces (TAIs) during Fall of 2021. At each TAI, samples collected include soils from across a transverse elevation gradient (i.e., coastal upland forest, transitional forest, and wetland soils), surface waters, and nearshore sediments across research sites in the Great Lakes and Mid-Atlantic regions (Chesapeake and Delaware Bays) of the continental USA. The first campaign measures surface water quality parameters, bulk geochemical parameters on water, soil, and sediment samples, and physicochemical parameters of sediment and soil.

54 ENVIRONMENTAL SCIENCES↗

Quantum-Classical Hybrid for Information Processing

Based upon quantum-inspired entanglement in quantum-classical hybrids, a simple algorithm for instantaneous transmissions of non-intentional messages (chosen at random) to remote distances is proposed. The idea is to implement instantaneous transmission of conditional information on remote distances via a quantum-classical hybrid that preserves superposition of random solutions, while allowing one to measure its state variables using classical methods. Such a hybrid system reinforces the advantages, and minimizes the limitations, of both quantum and classical characteristics. Consider n observers, and assume that each of them gets a copy of the system and runs it separately. Although they run identical systems, the outcomes of even synchronized runs may be different because the solutions of these systems are random. However, the global constrain must be satisfied. Therefore, if the observer #1 (the sender) made a measurement of the acceleration v(sub 1) at t =T, then the receiver, by measuring the corresponding acceleration v(sub 1) at t =T, may get a wrong value because the accelerations are random, and only their ratios are deterministic. Obviously, the transmission of this knowledge is instantaneous as soon as the measurements have been performed. In addition to that, the distance between the observers is irrelevant because the x-coordinate does not enter the governing equations. However, the Shannon information transmitted is zero. None of the senders can control the outcomes of their measurements because they are random. The senders cannot transmit intentional messages. Nevertheless, based on the transmitted knowledge, they can coordinate their actions based on conditional information. If the observer #1 knows his own measurements, the measurements of the others can be fully determined. It is important to emphasize that the origin of entanglement of all the observers is the joint probability density that couples their actions. There is no centralized source, or a sender of the signal, because each receiver can become a sender as well. An observer receives a signal by performing certain measurements synchronized with the measurements of the others. This means that the signal is uniformly and simultaneously distributed over the observers in a decentralized way. The signals transmit no intentional information that would favor one agent over another. All the sequence of signals received by different observers are not only statistically equivalent, but are also point-by-point identical. It is important to assume that each agent knows that the other agent simultaneously receives the identical signals. The sequences of the signals are true random, so that no agent could predict the next step with the probability different from those described by the density. Under these quite general assumptions, the entangled observers-agents can perform non-trivial tasks that include transmission of conditional information from one agent to another, simple paradigm of cooperation, etc. The problem of behavior of intelligent agents correlated by identical random messages in a decentralized way has its own significance: it simulates evolutionary behavior of biological and social systems correlated only via simultaneous sensoring sequences of unexpected events.

Zak, Michail↗

How Inverter-Based Resources (IBRs) Affect Protection Relay Elements

This presentation starts with the details of IEEE 2800-2022 requirements of IBR for balanced and unbalanced faults. Then, it shows how to design a droop based GFM control to be IEEE 2800-2022 compliant. An performance evaluation is carried out to see if three OEM GFM inverters 2800-2022 compliant or not. And finally we show how IEEE 2800-2022 complaint and non-compliant GFM inverter will impact the transmission line protection elements, such as directional element and FID. Finally, recommendations are made if the GFM is not IEEE 2800-2022 compliant to disable the protection elements that rely on reliable and regulated negative sequence current.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Unalakleet Microgrid Optimization for Tribal Community Resilience

The Unalakleet Microgrid Optimization Project aimed to strengthen the reliability and efficiency of the isolated electric power system that serves the Tribal community of Unalakleet, Alaska. The community relies entirely on a local wind-diesel microgrid, consisting of four 475 kW diesel generators and six 100 kW wind turbines, to provide electricity to approximately 745 residents and Tribal facilities. Because Unalakleet is not on a road system and is located nearly 400 miles from the nearest major power grid, maintaining a resilient and efficient local energy system is critical. The scope of this project included upgrading a portion of the transmission line between the wind farm and the power plant to increase voltage and reduce line losses, along with modernizing the Supervisory Control and Data Acquisition (SCADA) system to improve monitoring, control, and data management of the power system. These upgrades were designed to increase wind energy utilization, reduce diesel fuel consumption by tens of thousands of gallons annually, and improve overall grid stability. By allowing more of the community’s electricity to be supplied by local renewable wind resources, the project was designed to lower operating costs, reduce dependence on imported fuel, and strengthen the long-term resilience of the power system. These improvements represent an important step toward the community’s long-term energy vision of expanding renewable generation, incorporating energy storage, and eventually achieving “diesels-off” operation, where essential Tribal loads are powered primarily by local renewable resources.

17 WIND ENERGY↗

A Systematic Framework for Tuning Open-Source Multifunctional IBR Models To Emulate OEM Black-Box Fault Dynamics

This paper presents a systematic framework to tune a generic IBR EMT model to match with an OEM provided balckbox inverter model based on the fault current responses. The key learnings and findings are summarized as follows: The tunable key parameters include inner control loops and current limiters to align the fault current magnitude, sequence content, and phase trajectories with the OEM models across diverse fault type and locations. The tuned model's fidelity is validated through comparative analysis with an OEM blackbox model, assessing both the fault current response and the responses of multiple relay elements. The results demonstrate the tuned generic model can trigger relay decision logic that is identical or near identical to that of the OEM model, thus generating very good match model for fault studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The NASA Low-Pressure Turbine Flow Physics Program: A Review

An overview of the NASA Glenn Low-Pressure Turbine (LPT) Flow Physics Program will be presented. The flow in the LPT is unique for the gas turbine. It is characterized by low Reynolds number and high freestream turbulence intensity and is dominated by interplay of three basic mechanisms: transition, separation and wake interaction. The flow of most interest is on the suction surface, where large losses are generated due to separation. The LPT is a large, multistage, heavy, jet engine component that suffers efficiency degradation between takeoff and cruise conditions due to decrease in Reynolds number with altitude. The performance penalty is around 2 points for large commercial bypass engines and as much as 7 points for small, high cruise altitude, military engines. The gas-turbine industry is very interested in improving the performance of the LPT and in reducing its weight, part count and cost. Many improvements can be accomplished by improved airfoil design, mainly by increasing the airfoil loading that can yield reduction of airfoils and improved performance. In addition, there is a strong interest in reducing the design cycle time and cost. Key enablers of the needed improvements are computational tools that can accurately predict LPT flows. Current CFD tools in use cannot yet satisfactorily predict the unsteady, transitional and separated flow in the LPT. The main reasons are inadequate transition & turbulence models and incomplete understanding of the LPT flow physics. NASA Glenn has established its LPT program to answer these needs. The main goal of the program is to develop and assess models for unsteady CFD of LPT flows. An approach that consists of complementing and augmenting experimental and computational work elements has been adopted. The work is performed in-house and by several academic institutions, in cooperation and interaction with industry. The program was reviewed at the Minnowbrook II meeting in 1997. This review will summarize the progress that was made since and will introduce newly started projects. The LPT program is focused on three areas: acquisition of experimental and numerical databases and on modeling and computation. Priority was initially given to experiments. There are three classes of experiments: simulated LPT passages, linear cascade, both with and without wakes, and low-speed rotating rig. They are being conducted as follows: At NASA GRC on a flat surface with blade pressure distribution, at the US Naval Academy on a curved surface. The addition of wakes is studied at the University of Minnesota in a curved passage with a retractable wake generator, and at Texas A&M University in a linear cascade with continuously running wake generator. The pressure distribution of the Pratt & Whitney blade 'Pak B' is used in all these experiments. Experiments have been performed also in the GEAE Low-Speed Rotating Turbine (LSRT) rig with GE-designed airfoils. Work on numerically generated database is in progress at the University of Kentucky, using the DNS/LES code LESTool developed there. Turbulence/transition model assessment and development is performed also at the University of Kentucky, where a new intermittency transport model was developed and many experimental test cases have been numerically computed. Assessments of models using simulations of multistage LPT experiments were performed at Virginia Commonwealth University using the Corsair code. Work on suction surface separation delay, using passive and active flow-control, has also been initiated. Following the overview, Principal Investigators attending the workshop will present in detail several of the projects supported by NASA.

Ashpis, David E.↗