WIRELESSLY COORDINATED OPEN-LOOP COHERENT DISTRIBUTED ANTENNA ARRAYS USING SOFTWARE-DEFINED RADIO
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Ultra-High Operation Temperature SiC-matrix Solar Thermal Air Receiver (HOTSSTAR) enabled by additive manufacturing: Test Facility & Performance Evaluations
Solar Heat for Industrial Processes (SHIP) cavity receivers are capable of generating electricity or industrial process heat by absorbing thermal energy from solar radiation, focused on a small area. The concentration of solar radiation on the small area of the receiver enables the achievement of high temperatures (ranging from 400°C to 1,100°C) of a working fluid, thus making the SHIP technology thermodynamically comparable with conventional power plants. A volumetric receiver consists of a porous structure-generally made of silicon carbide or metal, which absorbs solar radiation and converts it into heat energy. Heat energy from the porous materials is then transferred to the fluid following through them. A volumetric receiver acts as a convective heat exchanger, transferring heat to the fluid through convection. Open-loop volumetric receivers work with air at atmospheric pressure and are suitable for single-cycle or multi-cycle energy plants. A Model Based Systems Engineering (MBSE) approach was used to develop a test bed at Sandia national Laboratories (SNL) capable of demonstrating an open-loop volumetric air receiver developed by General Electric Aerospace (GE Aerospace). This paper presents the development of the various MBSE methods, test bed, and testing operations for the GE air receiver, which was experimentally demonstrated to achieve 1,350°C for over 3 hours of operation and an approximate 70% receiver efficiency. By being able to achieve such high temperatures >1,000°C, this work provides the potential to support many SHIP industrial use cases.
14 SOLAR ENERGY↗
MODEL DEVELOPMENT AND VERIFICATION OF A 1,350°C AIR RECEIVER TEST SYSTEM
Open-loop volumetric receivers work with air at atmospheric pressure and are suitable for single-cycle or multicycle power plants. A novel additively manufactured (AM) silicon carbide (SiC), ceramic matrix composite (CMC) volumetric receiver was developed that consisted of a lattice structure, which absorbs solar radiation and converts it into heat energy. Heat energy from the porous receiver was transferred to heated ambient air. The receiver acted as a convective heat exchanger, transferring heat to the fluid through convection. Engineering was facilitated to develop a high-temperature air receiver test bed at Sandia national Laboratories (SNL) capable of demonstrating a 50kWth open-loop volumetric SiC air receiver module developed by General Electric Aerospace Research (GE Aerospace). This paper presents the development of the high temperature AM SiC-CMC air receiver, the test bed, and the first testing operations of this device, which was experimentally demonstrated to achieve 1,350°C for over 3.5 hours of operation, based on input flux levels of 67–91 W/cm2 0.5-2.5 kg/s flow rates. From the test campaign results, based on the measured convective heat transfer to the airflow and bounded radiative-loss assumptions, the solar-thermal efficiency of HOTSSTAR test module was estimated to be approximately as high as 74% for representative test conditions.
14 SOLAR ENERGY↗
Detecting isolated resonance curves using fixed frequency voltage control tests
Isolated resonance curves, or isolas, are resonance branches of the harmonically forced system that exist separately from the main nonlinear forced response curve, leading to excessive vibrations. Traditional stepped or swept sine simulations and tests rely on continuation along the frequency parameter, typically resulting in a jump phenomenon along the primary resonance branch, prior to the disconnected isola. The main objective of this research is to propose an approach to identify isolated resonance curves by performing continuation along the input amplitude that initializes the response from a low-amplitude solution in the linear regime. Furthermore, this is achieved with the open-loop fixed frequency voltage control method that continues along the shaker voltage parameter and measures the so-called S-curves, which are theoretically a continuous solution branch that connect to the isola. The methodology is demonstrated on a fixture-wing-pylon assembly with a vibro-impact nonlinearity localized in a pylon subcomponent attachment. Multi-harmonic balance simulations are deployed to compute both the nonlinear forced response curves and S-curves to demonstrate the isola detection strategy on a reduced-order finite element model of the nonlinear system. Swept sine and fixed frequency voltage control tests are then conducted on the physical structure to demonstrate the isola detection experimentally, revealing the existence of the large amplitude vibrations that are undetected in the forces levels and frequencies measured with traditional frequency sweeping.
Characterization and Analytical Technique↗
Physics-Informed Neural Networks for PDE-Constrained Optimization and Control
The goal of optimal control is to determine a sequence of inputs for maximizing or minimizing a given performance criterion subject to the dynamics and constraints of the system under observation. This work introduces Control Physics-Informed Neural Networks (PINNs), which simultaneously learn both the system states and the optimal control signal in a single-stage framework that leverages the system’s underlying physical laws. While prior approaches often follow a two-stage process-modeling, the system first and then devising its control—the presented novel framework embeds the necessary optimality conditions directly into the network architecture and loss function. We demonstrate the effectiveness of the novel methodology by solving various open-loop optimal control problems governed by analytical, one-dimensional, and two-dimensional partial differential equations (PDEs).
97 MATHEMATICS AND COMPUTING↗
Servomotor-driven leveling elements for machine tool frame-to-floor alignment
This paper presents the results of aligning the frame to concrete floor of a large 5-axis machine tool by leveling element adjustments using servomotors instead of manual operation. The machine tool leveling elements used in this study are mechanical devices that attach the machine tool frame to the concrete foundation. These leveling elements are also adjustable so that each location along the machine tool can be uniquely adjusted such that the geometric errors of the frame are minimized, and the accuracy of the machine tool is improved. Off-the-shelf servomotors and connection equipment were installed at each of 12 leveling element locations for a precision 5-axis machine tool at Oak Ridge National Laboratory. The servomotors allow a technician to align the machine tool frame remotely, instead of crawling under the machine tool to iteratively manually adjust each of the 12 leveling elements. The open-loop servomotor-leveling element system design is presented in this paper as well as machine tool frame alignment results. The servomotor system significantly reduces leveling element adjustment time, eliminates the need for under-machine access, reduces technician physical strain, and significantly improves the adjustment repeatability.
Honeycutt, Andrew [ORNL]↗
Pareto-optimal target definition for multi-axis random vibration testing
In random vibration testing with multiple control channels, existing control laws require specification of a complete spectral density matrix at each control frequency. Spectral density matrices include autospectral densities on the diagonal and cross-spectral densities on the off-diagonal. In practice, the off-diagonal terms are often unknown, and recent vibration testing research has focused on fixing the diagonal and specifying the off-diagonal to minimize the required control energy, subject to a constraint that the target matrix is positive semidefinite. This paper shows that, even with a fixed diagonal, off-diagonal terms strongly affect control residuals. This overlooked effect occurs in both square and rectangular systems. By jointly considering input energy and control residuals, open-loop inputs are derived directly from the diagonal without specifying the off-diagonal terms. Vibration targets that can be used in closed-loop control are then derived using the optimal inputs, with positive semidefinite constraints applied during the derivation. The result is a set of Pareto-optimal control solutions. For each solution in the set, any other possible solution produces greater control error, greater input energy, or both. A balanced solution is selected automatically, though others can be chosen based on test needs. Simulations and experiments show that the proposed method outperforms state-of-the-art energy-minimizing approaches, achieving significant reductions in both control error and input energy.
Autospectral density↗
Optimisation of the Kaplan hydropower system via PID 2 and digital twin
Here, this paper proposes a proportional–integral-double–derivative (PID 2 ) optimisation method for the Kaplan hydropower system by building a digital twin. The study first uses one multilayer perceptron (MLP) to model the hydroturbine dynamic and then adopts three connected MLPs to model the generator dynamic, both in an open-loop fashion. Inspired by stochastic distribution control (SDC) theory, we regard the training of the turbine's neural network model as a process control problem, and we propose minimising entropy loss to update the network parameters. The next step is to build the digital twin by connecting the neural network models with a PID 2 controller and a lead-lag exciter and run the whole model in a closed-loop fashion. After that, a binary search approach is applied to optimise the PID 2 parameters based on the obtained digital twin model. The simulation results show that the proposed method can reduce the mean square tracking error by more than 90%. Furthermore, the method is extended to jointly optimise the PID 2 controller and excitation system gains through multiobjective optimisation, leveraging Pareto frontier analysis to balance active power and voltage tracking performance. Simulation results confirm the effectiveness of the proposed method, achieving a 83.46% reduction in relative mean square error of active power, a 47.13% reduction in terminal voltage tracking error, and an 82.78% improvement in the overall scalarized objective.
Hydropower system↗
Quantum optimal control of superconducting qubits based on machine-learning characterization
Implementing fast and high-fidelity quantum operations using open-loop quantum optimal control relies on having an accurate model of the quantum dynamics. Any deviations between this model and the complete dynamics of the device, such as the presence of spurious modes or pulse distortions, can degrade the performance of optimal controls in practice. Here, we propose an experimentally simple approach to realize optimal quantum controls tailored to the device parameters and environment while specifically characterizing this quantum system. Concretely, we use physics-inspired machine learning to infer an accurate model of the dynamics from experimentally available data and then optimize our experimental controls on this trained model. We show the power and feasibility of this approach by optimizing arbitrary single-qubit operations in detailed numerical simulations of a superconducting transmon qubit. Furthermore, we demonstrate that this framework produces an accurate description of the device dynamics under arbitrary controls, together with the precise pulses achieving arbitrary single-qubit gates with a high fidelity of ∼99.99%.
Artificial neural networks↗
Demand Response Under Stochastic, Price-Dependent User Behavior
This letter focuses on price-based demand response (DR) implemented through dynamic adjustments of electricity prices. It extends existing DR models to a stochastic framework in which customer response is represented by price-dependent random variables, leveraging models and tools from the theory of stochastic optimization with decision-dependent distributions. The inherent epistemic uncertainty in the customers' responses renders open-loop, model-based DR strategies impractical. We propose a stochastic, feedback-based pricing strategy to compensate for estimation errors and uncertainty in customer response, establish theoretical results demonstrating the stability and near-optimality of the proposed approach, and validate its effectiveness through numerical simulations.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Closed-Loop Wind Turbine Controllers for Active Wake Mixing Strategies
Wind turbine active wake mixing (AWM) is an exciting new field of research where dynamic actuation, usually on the blade pitch angles, is used to increase wind farm-wide power production. From a controls perspective, the current state-of-the-art AWM strategies are very simple: a dynamic, usually periodic, reference signal is prescribed to actuators in an open-loop (OL) fashion. The actuation is then presumed to have a certain desired effect on the system, i.e., the wind turbine and the flow it affects. However, this system is highly nonlinear and experiences disturbances in the form of wind variations that are not known a priori. As a result, the OL approach might not yield optimal results. In this article, a novel approach is presented, which closes the loop on AWM controllers. A feedback loop is implemented, which uses measurements of the individual blade bending moments that are widely available on modern wind turbines to determine the individual blade pitch angles. A proof of concept of this implementation is presented in this article, and a thorough comparison with the OL method is executed using high-fidelity flow simulations. These simulations show that the novel closed-loop controller does not substantially increase wake mixing but achieves similar performance as the OL controller while reducing fatigue loads on the controlled turbine.
17 WIND ENERGY↗
Real-Time High-Accuracy Digital Wireless Time, Frequency, and Phase Calibration for Coherent Distributed Antenna Arrays
his work presents a fully-digital high-accuracy real-time calibration procedure for frequency and time alignment of open-loop wirelessly coordinated coherent distributed antenna array (CDA) modems, enabling radio frequency (RF) phase coherence of spatially separated commercial off-the-shelf (COTS) software-defined radios (SDRs) without cables or external references such as the global navigation satellite system (GNSS). Building on previous work using high-accuracy spectrally-sparse time of arrival (ToA) waveforms and a multistep ToA refinement process, a high-accuracy two-way time transfer (TWTT)-based time–frequency coordination approach is demonstrated. Due to the two-way nature of the high-accuracy TWTT approach, the time and frequency estimates are Doppler and multipath tolerant, so long as the channel is reciprocal over the synchronization epoch. This technique is experimentally verified using COTS SDRs in a lab environment in static and dynamic scenarios and with significant multipath scatterers. Time, frequency, and phase stability were evaluated by beamforming over coaxial cables to an oscilloscope which achieved time and phase precisions of ~60– 70 ps , with median coherent gains above 99% using optimized coordination parameters, and a beamforming frequency root-mean-square error (RMSE) of 3.73 ppb in a dynamic scenario. Finally, experiments were conducted to compare the performance of this technique with previous works using an analog continuous-wave two-tone (CWTT) frequency reference technique in both static and dynamic settings.
Clock synchronization↗
High-repetition rate, CEP-stable shortwave infrared source with two-cycle pulses for field-resolved spectroscopy
We report on a passively carrier-envelope phase (CEP)-stable optical parametric amplifier generating two-cycle pulses at 2060 nm with energies of up to 2.25 µJ operating at a repetition rate of 400 kHz, specifically designed for applications in field-resolved spectroscopy. The measured pulse duration is 13.6 fs, resulting in two cycles of the carrier wave. Due to the robust CEP-stable front-end design, we achieve an open-loop CEP stability of 250 mrad (rms) and the capability for fast CEP modulation.
47 OTHER INSTRUMENTATION↗
Hot, Cold, or Just Right? Using a Wide-View Infrared Biometric Sensor to Improve Occupant Comfort and Reduce Overcooling in Buildings via Closed-loop Control (CRADA Final Report)
This research adds to the understanding of building energy management by fundamentally challenging the long-standing paradigm of controlling an environmental parameter—air temperature—and assuming occupant comfort will follow. The project developed and demonstrated a novel approach that directly senses physiological indicators of human comfort to enable closedloop, human-centric control of heating, ventilation, and air conditioning (HVAC) systems. This work shifts the focus from open-loop environmental control to a closed-loop system that prioritizes the occupants' actual thermal state. The primary benefit to the public is the potential for a simultaneous improvement in the quality of indoor environments, where people spend most of their time, and a significant reduction in national energy consumption. Overcooling, or the overuse of cooling energy in a way that discomforts occupants, wastes approximately 0.5 Quads of primary energy annually in U.S. commercial buildings and creates unproductive indoor environments.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Floating Photovoltaics in Hydropower Reservoirs in the United States
This report presents a comprehensive analysis of the feasibility of floating photovoltaics (FPV) in federally regulated reservoirs within the continental United States (CONUS) and to present a methodology for capturing the true costs of deployment, potential environmental impacts, and regulatory pathways for open-loop hydropower reservoirs. It is intended for stakeholders who may not be solar industry experts but who are interested in exploring the potential for FPV in their reservoirs. While there are promising opportunities, particularly in enhancing dissolved oxygen (DO) levels and potentially improving compliance with existing hydropower licenses, the current capital costs of FPV are not yet competitive with traditional land-based solar installations at the utility-scale when comparing the LCOE results. A competitive financial outlook is achievable when applying a 30% Investment Tax Credit (ITC) and considering a 5% reduction from the baseline capital expenditures (CapEx) at the Tuckertown Reservoir in North Carolina case study. The study is structured around three key pillars of research: technical potential, environmental impacts and regulatory considerations, and technoeconomic analysis. This report provides a nationwide assessment of the opportunities for FPV in terms of capacity, measured in direct current megawatts (MWDC), in reservoirs managed by the U.S. Bureau of Reclamation (USBR), the U.S. Army Corps of Engineers (USACE), and the Federal Energy Regulatory Commission (FERC). Additionally, the report introduces a heuristic model for estimating the CapEx of utility-scale FPV projects (1–100 MW), offering a baseline cost estimate for stakeholders. Finally, the report applies these models to a case study of a hydropower reservoir in North Carolina to present site-specific results.
13 - HYDRO ENERGY↗
A Generic and Multifunctional Electromagnetic Transient Model for Grid-Following Inverters
This article presents a generic and multi-functional electromagnetic transient (EMT) dynamic model of grid following (GFL) inverter-based resource (IBR) using the PSCAD software platform. The features of the developed model includes the flexibility in selecting various types and combinations of DC sources covering PV modules, battery modules, ideal DC source module, as well as flexibility in selecting either switched or averaged model of inverter. This model also covers exhaustive lists of controller logic covering open-loop/closed-loop PQ dispatch control, DC voltage and AC terminal voltage control along with the conventional current control designed in dq-domain, ate- domain and positive-negative sequence domain. Moreover, this model is equipped with the flexibility in selecting various types of current limiting schemes that includes saturation-based as well as latching-based current limiter, anti-windup protection. Moreover, the EMT model is agnostic to the MVA rating and is suitable for interfacing transmission systems by being complaint with the IEEE Std. 2800. The generality in the power circuits and the multi-functional options in operation and control of the developed EMT model makes it suitable for both academia and industry to study various power system aspects not limited to but such as fault behavior of GFL IBR and impacts on protection system, transient stability of a system interfaced with large number of GFL IBRs etc.
14 SOLAR ENERGY↗
PSH Assessment and Site Identification [Slides]
NLR's Pumped Storage Hydropower (PSH) geospatial and cost model algorithms are applied to the Chemehuevi Reservation to assess the potential for PSH within the reservation. The algorithm identifies both "open-loop" PSH opportunities formed by constructing a new reservoir within the reservation paired with bordering Lake Havasu and "closed-loop" systems formed by two new reservoirs within the reservation. Options range from 28 to 538 MW of electrical generation power at maximum generation and 10 hours of storage. CAPEX is estimates as 4422 2022 $\$$/kW of generating power, which is meaningfully higher than the lowest cost systems identified in NLR's national scale assessments. Further economic analysis is needed to fully evaluate whether this would be an attractive option to meet the Chemehuevi Reservation's goals.
25 ENERGY STORAGE↗
Plume Impingement Software Module for Real-Time Proximity Operations
Successfully executing proximity operations in space, such as docking or in-orbit servicing, requires sophisticated spacecraft design that accounts for induced environments. As a chaser vehicle’s attitude control thrusters fire, they create rarefied plumes that can impact the target vehicle, with the potential to overload components, exceed thermal limits, and spin the target vehicle out of control. High-fidelity simulations of the thruster plume impingement environment require the direct simulation Monte Carlo (DSMC) method, but DSMC is too computationally expensive to simulate proximity operations that involve thousands of thruster firings. For this analysis to be tractable, engineering models of the plume flowfield and impingement events are used to simulate these trajectories [1]. Currently, on-orbit plume impingement environments are modeled through an inefficient open-loop analysis cycle where the vehicle’s flight controller and plume impingement teams iterate on the trajectories until they pass the target vehicle’s plume requirements. As complex on-orbit missions evolve and become more frequent, lengthy design cycles will become operational bottlenecks. To address this gap, this work develops an advanced plume impingement module capable of operating at real-time scale that can be integrated with existing mission planning tools and onboard flight systems. The plume module leverages state-of-the-art plume simulation techniques [2] to deliver fast, physics-based impingement predictions in a software architecture that can be tailored to diverse proximity operations scenarios. A prototype of this plume impingement module is built to demonstrate the feasibility of real-time performance. This prototype completes plume impingement calculations in microseconds per target geometry mesh point. The software serves as a foundational capability for plume-aware trajectory design, operational risk assessment, and future autonomous decision-making systems.
Plume Impingement↗