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At least 757 records · Page 42

Community structure and function during periods of high performance and system upset in a full-scale mixed microalgal wastewater resource recovery facility

Microalgae have the potential to exceed current nutrient recovery limits from wastewater, enabling water resource recovery facilities (WRRFs) to achieve increasingly stringent effluent permits. The use of photobioreactors (PBRs) and the separation of hydraulic retention and solids residence time (HRT/SRT) further enables increased biomass in a reduced physical footprint while allowing operational parameters (e.g., SRT) to select for desired functional communities. However, as algal technology transitions to full-scale, there is a need to understand the effect of operational and environmental parameters on complex microbial dynamics among mixotrophic microalgae, bacterial groups, and pests (i.e., grazers and pathogens) and to implement robust process controls for stable long-term performance. Here, we examine a full-scale, intensive WRRF utilizing mixed microalgae for tertiary treatment in the US (EcoRecover, Clearas Water Recovery Inc.) during a nine-month monitoring campaign. We investigated the temporal variations in microbial community structure (18S and 16S rRNA genes), which revealed that stable system performance of the EcoRecover system was marked by a low-diversity microalgal community (D INVSIMPSON = 2.01) dominated by Scenedesmus sp. (MRA = 55 %-80 %) that achieved strict nutrient removal (effluent TP < 0.04 mg·L -1 ) and steady biomass concentration (TSS monthly avg . = 400–700 mg·L −1 ). Operational variables including pH, alkalinity, and influent ammonium (NH 4 + ), correlated positively (p < 0.05, method = Spearman) with algal community during stable performance. Further, the use of these parameters as operational controls along with N/P loading and SRT allowed for system recovery following upset events. Importantly, the presence or absence of bacterial nitrification did not directly impact algal system performance and overall nutrient recovery, but partial nitrification (potentially resulting from NO 2 − accumulation) inhibited algal growth and should be considered during long-term operation. The microalgal communities were also adversely affected by zooplankton grazers (ciliates, rotifers) and fungal parasites (Aphelidium), particularly during periods of upset when algal cultures were experiencing culture turnover or stress conditions (e.g., nitrogen limitation, elevated temperature). Altogether, the active management of system operation in order to maintain healthy algal cultures and high biomass productivity can result in significant periods (>4 months) of stable system performance that achieve robust nutrient recovery, even in winter months in northern latitudes (WI, USA).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Peer-to-peer communication control for resilient operations of networked cyberphysical systems

This report includes two main accomplishments of the peer-to-peer communication control for resilient operation of networked microgrids project in FY24, which include a scheme for cyberattack-aware coordination of networked microgrids for supporting voltages of bulk power systems and a scheme for price signal-based operations of EV-rich networked microgrids with mixed ownership. First, the cyberattack-aware scheme enables networked microgrids to distributedly determine the amount of reactive power injection to support the voltage of bulk power system (BPS) in a fair manner. In this scheme, a risk-informed algorithm is presented to generate the peer-to- peer (P2P) communication graph with minimal risk of attack on communication links. To deal with cyberattacks on MG controllers, the resilient consensus algorithm (CA) is utilized for MG controllers to robustly estimate the total reactive power headroom, from which the MGs can accurately provide the needed amount of reactive power injection for supporting the voltage of BPS. The CA implementation and performance within the P2P communication framework are demonstrated on the IEEE 39-bus system with 6 microgrids contained in the distribution feeder under different cyberattack scenarios. Second, the price-based scheme enables the usage of the real-time price signal for the operations of electric vehicle (EV)-rich networked-microgrids with mixed ownership, in which not all the microgrids can communicate with the distribution system operator (DSO). In this scheme, a max consensus is introduced to enable the real-time price signal to be propagated from the DSO to all the microgrids, from which each microgrid controller will manage the DERs to balance the load demand and the power injection from the EV charging stations within its microgrid. Numerical results over one day with 288 slots of 5-minute intervals on the modified 123-node test feeder including 3 microgrids with high penetration of EV are presented to evaluate how the price signal affects the operations of networked microgrids under different charging strategies of the EV charging stations. The result indicates that our proposed EVCS (dis)charging strategy, which leverages the flexibility of EVs to support the grid through discharging during peak demand, proves to be a cost-effective solution that reduces operational costs while improving the social welfare of EV charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Recent activities within the Aeroservoelasticity Branch at the NASA Langley Research Center

The objective of research in aeroservoelasticity at the NASA Langley Research Center is to enhance the modeling, analysis, and multidisciplinary design methodologies for obtaining multifunction digital control systems for application to flexible flight vehicles. Recent accomplishments are discussed, and a status report on current activities within the Aeroservoelasticity Branch is presented. In the area of modeling, improvements to the Minimum-State Method of approximating unsteady aerodynamics are shown to provide precise, low-order aeroservoelastic models for design and simulation activities. Analytical methods based on Matched Filter Theory and Random Process Theory to provide efficient and direct predictions of the critical gust profile and the time-correlated gust loads for linear structural design considerations are also discussed. Two research projects leading towards improved design methodology are summarized. The first program is developing an integrated structure/control design capability based on hierarchical problem decomposition, multilevel optimization and analytical sensitivities. The second program provides procedures for obtaining low-order, robust digital control laws for aeroelastic applications. In terms of methodology validation and application the current activities associated with the Active Flexible Wing project are reviewed.

Noll, Thomas E.↗

Recent activities within the aeroservoelasticity branch at the NASA Langley Research Center

The objective of research in aeroservoelasticity at the NASA Langley Research Center is to enhance the modeling, analysis, and multidisciplinary design methodologies for obtaining multifunction digital control systems for application to flexible flight vehicles. Recent accomplishments are discussed, and a status report on current activities within the Aeroservoelasticity Branch is presented. In the area of modeling, improvements to the Minimum-State Method of approximating unsteady aerodynamics are shown to provide precise, low-order aeroservoelastic models for design and simulation activities. Analytical methods based on Matched Filter Theory and Random Process Theory to provide efficient and direct predictions of the critical gust profile and the time-correlated gust loads for linear structural design considerations are also discussed. Two research projects leading towards improved design methodology are summarized. The first program is developing an integrated structure/control design capability based on hierarchical problem decomposition, multilevel optimization and analytical sensitivities. The second program provides procedures for obtaining low-order, robust digital control laws for aeroelastic applications. In terms of methodology validation and application the current activities associated with the Active Flexible Wing project are reviewed.

Noll, Thomas↗

Design and analysis of a wake steering controller with wind direction variability

Wind farm control strategies are being developed to mitigate wake losses in wind farms, increasing energy production. Wake steering is a type of wind farm control in which a wind turbine's yaw position is misaligned from the wind direction, causing its wake to deflect away from downstream turbines. Current modeling tools used to optimize and estimate energy gains from wake steering are designed to represent wakes for fixed wind directions. However, wake steering controllers must operate in dynamic wind conditions and a turbine's yaw position cannot perfectly track changing wind directions. Research has been conducted on robust wake steering control optimized for variable wind directions. In this paper, the design and analysis of a wake steering controller with wind direction variability is presented for a two-turbine array using the FLOw Redirection and Induction in Steady State (FLORIS) control-oriented wake model. First, the authors propose a method for modeling the turbulent and low-frequency components of the wind direction, where the slowly varying wind direction serves as the relevant input to the wake model. Next, we explain a procedure for finding optimal yaw offsets for dynamic wind conditions considering both wind direction and yaw position uncertainty. We then performed simulations with the optimal yaw offsets applied using a realistic yaw offset controller in conjunction with a baseline yaw controller, showing good agreement with the predicted energy gain using the probabilistic model. Using the Gaussian wake model in FLORIS as an example, we compared the performance of yaw offset controllers optimized for static and dynamic wind conditions for different turbine spacings and turbulence intensity values, assuming uniformly distributed wind directions. For a spacing of five rotor diameters and a turbulence intensity of 10 %, robust yaw offsets optimized for variable wind directions yielded an energy gain equivalent to 3.24 % of wake losses recovered, compared to 1.42 % of wake losses recovered with yaw offsets optimized for static wind directions. In general, accounting for wind direction variability in the yaw offset optimization process was found to improve energy production more as the separation distance increased, whereas the relative improvement remained roughly the same for the range of turbulence intensity values considered.

17 WIND ENERGY↗

Trajectory Planning and Online Performance Model Estimation for Advanced Air Mobility

We propose a framework for adaptive guidance based on optimal control and estimation using closed-loop performance models. In the proposed approach, parameters of a reduced-order performance model are estimated in real time so that trajectories and guidance commands are replanned with more accurate knowledge of the system's response and performance capabilities. To apply this methodology to flight control systems, we introduce a simple yet expressive performance model modified from a reference linear design model. The proposed framework is applied to guidance of a simulated Advanced Air Mobility class concept aircraft experiencing control effector failures. We demonstrate that, by optimizing performance model parameters in real time, guidance commands can be intelligently adjusted to recover system stability and the performance of a full-order vehicle model, even in the event of effector failures. Furthermore, the reduced-order performance model requires a fraction of the computational cost of the full-order model, facilitating real-time use of adaptive, optimal guidance.

Differential dynamic programming↗

Trajectory Planning and Online Performance Model Estimation for Advanced Air Mobility

We propose a framework for adaptive guidance based on optimal control and estimation using closed-loop performance models. In the proposed approach, parameters of a reduced-order performance model are estimated in real time so that trajectories and guidance commands are replanned with more accurate knowledge of the system's response and performance capabilities. To apply this methodology to flight control systems, we introduce a simple yet expressive performance model modified from a reference linear design model. The proposed framework is applied to guidance of a simulated Advanced Air Mobility class concept aircraft experiencing control effector failures. We demonstrate that, by optimizing performance model parameters in real time, guidance commands can be intelligently adjusted to recover system stability and the performance of a full-order vehicle model, even in the event of effector failures. Furthermore, the reduced-order performance model requires a fraction of the computational cost of the full-order model, facilitating real-time use of adaptive, optimal guidance.

Differential dynamic programming↗

Robust Vision-based Multi-spacecraft Guidance Navigation and Control using CNN-based Pose Estimation

In this paper, we present an end-to-end simulation framework for tracking an uncooperative Target spacecraft in Low Earth Orbit using a CubeSat-class Ego spacecraft outfitted with a camera. Currently, capturing high-fidelity realistic images in space for this scenario is difficult and exorbitantly expensive. Therefore, we developed a framework to simulate the spacecraft orbits in Basilisk software and generate high-fidelity realistic images of spacecraft in Unreal Engine, including the effects from Sun, Earth, Moon and stars. The Ego spacecraft uses cameras to capture images of the uncooperative Target and estimates its position and attitude using a CNN based 6DOF pose estimation pipeline, eliminating need for large SWAP-C(Size, Weight, Power and Cost) sensors like LIDAR or reliance on inter-spacecraft communication, This CNN, which is motivated by ESA’s Pose Estimation challenge of 2019, is trained using simulated data from our end-to-end simulation framework. We compare the performance of two distinct CNNbased algorithms for pose estimation along a nominal trajectory. In presence of non-Gaussian modeling uncertainties, the statedependent estimation error is characterized with a quadratic upper-bound. The quadratically-bounded error can be used by a robust controller to maneuver

Rahmani, Amir↗

Experimental Safe Extremum Seeking for Accelerators

Here, we demonstrate the recent designs of safe extremum seeking (Safe ES) on the 1-km-long charged particle accelerator at the Los Alamos Neutron Science Center (LANSCE). Safe ES is a modification of extremum seeking (ES) which, in addition to minimizing an analytically unknown cost, also employs a safety filter based on an analytically unknown control barrier function (CBF) safety metric. Tuning is necessitated by accelerators being large complex systems, with many drifting parameters due to thermal effects and degradation. At the same time, safe operation (the maintenance of state constraints) is crucial, as damage brings astronomical costs, both financially and in operation downtime. Our measured (but analytically unknown) safety metric is the beam current. We perform multivariable Safe ES on three accelerator applications, in which we adapt 4, 6, and 3 magnet strength parameters, respectively. Two of the three applications are for validated simulation models of beamlines at LANSCE: the first for the proton radiography (pRad) beamline of 800-MeV protons for spot size tuning; the second on a high-performance code, HPSim, for tuning the low-energy beam transport (LEBT) region that contains a beam of 750-keV protons. The third is an experimental tuning of the steering magnets in the LEBT at LANSCE.

43 PARTICLE ACCELERATORS↗

NASA Tech Briefs, August 2011

Topics covered include: Miniature, Variable-Speed Control Moment Gyroscope; NBL Pistol Grip Tool for Underwater Training of Astronauts; HEXPANDO Expanding Head for Fastener-Retention Hexagonal Wrench; Diagonal-Axes Stage for Pointing an Optical Communications Transceiver; Improvements in Speed and Functionality of a 670-GHz Imaging Radar; IONAC-Lite; Large Ka-Band Slot Array for Digital Beam-Forming Applications; Development of a 150-GHz MMIC Module Prototype for Large-Scale CMB Radiation; Coupling Between Waveguide-Fed Slot Arrays; PCB-Based Break-Out Box; Multiple-Beam Detection of Fast Transient Radio Sources; Router Agent Technology for Policy-Based Network Management; Remote Asynchronous Message Service Gateway; Automatic Tie Pointer for In-Situ Pointing Correction; Jitter Correction; MSLICE Sequencing; EOS MLS Level 2 Data Processing Software Version 3; DspaceOgre 3D Graphics Visualization Tool; Metallization for Yb14MnSb11-Based Thermoelectric Materials; Solvent/Non-Solvent Sintering To Make Microsphere Scaffolds; Enhanced Fuel-Optimal Trajectory-Generation Algorithm for Planetary Pinpoint Landing; Self-Cleaning Coatings and Materials for Decontaminating Field-Deployable Land and Water-Based Optical Systems; Separation of Single-Walled Carbon Nanotubes with DEP-FFF; Li Anode Technology for Improved Performance; Post-Fragmentation Whole Genome Amplification-Based Method; Microwave Tissue Soldering for Immediate Wound Closure; Principles, Techniques, and Applications of Tissue Microfluidics; Robotic Scaffolds for Tissue Engineering and Organ Growth; Stress-Driven Selection of Novel Phenotypes; Method for Accurately Calibrating a Spectrometer Using Broadband Light; Catalytic Microtube Rocket Igniter; Stage Cylindrical Immersive Display; Vacuum Camera Cooler; Atomic Oxygen Fluence Monitor; Thermal Management Tools for Propulsion System Trade Studies and Analysis; Introduction to Physical Intelligence; Technique for Solving Electrically Small to Large Structures for Broadband Applications; Accelerated Adaptive MGS Phase Retrieval; Large Eddy Simulation Study for Fluid Disintegration and Mixing; Tropospheric Correction for InSAR Using Interpolated ECMWF Data and GPS Zenith Total Delay; Technique for Calculating Solution Derivatives With Respect to Geometry Parameters in a CFD Code; Acute Radiation Risk and BRYNTRN Organ Dose Projection Graphical User Interface; Probabilistic Path Planning of Montgolfier Balloons in Strong, Uncertain Wind Fields; Flight Simulation of ARES in the Mars Environment; Low-Outgassing Photogrammetry Targets for Use in Outer Space; Planning the FUSE Mission Using the SOVA Algorithm; Monitoring Spacecraft Telemetry Via Optical or RF Link; and Robust Thermal Control of Propulsion Lines for Space Missions.

Source record↗

Higher-order interaction effects among operating conditions and feedstocks shape reactor microbiomes and fatty acid production profiles

Arrested anaerobic digestion (AAD) offers a promising route for producing fatty acids (FAs) from organic residues, yet optimal conditions for selectively generating medium-chain fatty acids (MCFAs) remain poorly defined. Here, we systematically evaluated the main and interaction effects of pH (5, 7, 9), feedstock (food waste, manure), temperature (35 and 45 °C), and inoculum source on microbiome composition and FA production. Anaerobic digester sludge and a novel bison rumen inoculum were compared. Significant higher-order interactions among operating parameters governed FA profiles and microbiome structure. Butyric acid production was driven by a three-way interaction among pH, feedstock, and temperature (p < 0.001), with maximum concentrations achieved in food waste reactors at pH 5.0 and 35 °C (1.2 ± 0.1 g L −1 with sludge and 1.1 ± 0.3 g L −1 with rumen). MCFA production exhibited significant four-way interactions (p < 0.1 to p < 0.001). At 45 °C and pH 5.0, inoculum source tuned MCFA selectivity: sludge favored pentanoic acid (0.4 ± 0.1 g L −1 ), whereas rumen favored hexanoic and heptanoic acids (up to 0.4 ± 0.2 g L −1 ). Manure reactors produced < 0.2 g L −1 MCFAs under all conditions. Genera, including Megasphaera, Prevotella, and Lactobacillus, were associated with production of specific MCFAs. PICRUSt2-based pathway predictions were consistent with MCFA production patterns and suggested a potential role for lactic acid–driven chain elongation pathways. This study provides insights into how interacting operating conditions shape AAD microbiomes, their FA profiles, and advances the trajectory of research aimed at engineering robust and controllable microbiomes for waste valorization.

09 BIOMASS FUELS↗

Partners for life: building microbial consortia for the future

We report new technologies have allowed researchers to better design, build, and analyze complex consortia. These developments are fueling a wider implementation of consortium-based bioprocessing by leveraging synthetic biology, delivering on the field’s multitudinous promises of higher efficiencies, superior resiliency, augmented capabilities, and modular bioprocessing. Here we chronicle current progress by presenting a range of screening, computational, and biomolecular tools enabling robust population control, efficient division of labor, and programmatic spatial organization; furthermore, we detail corresponding advancements in areas including machine learning, biocontainment, and standardization. Additionally, we show applications in myriad sectors, including medicine, energy and waste sustainability, chemical production, agriculture, and biosensors. Concluding remarks outline areas of growth that will promote the utilization of complex community structures across the biotechnology spectrum.

59 BASIC BIOLOGICAL SCIENCES↗

An optoelectronic heterostructure for neuromorphic computing: CdS/V 3 O 5

Nonvolatile resistive switching is one of the key phenomena for emerging applications in optoelectronics and neuromorphic computing. In most of the cases, an electric field is applied to a two terminal dielectric material device and leads to the formation of a low resistance filament due to ion migration. However, the stochastic nature of the ion migration can be an impediment for the device robustness and controllability, with uncontrolled variations of high and low resistance states or threshold voltages. Here, we report an optically induced resistive switching based on a CdS/V 3 O 5 heterostructure which can overcome this issue. V 3 O 5 is known to have a second order insulator to metal transition around T c ≈ 415 K, with an electrically induced threshold switching at room temperature. Upon illumination, the direct transfer of the photoinduced carriers from the CdS into V 3 O 5 produces a nonvolatile resistive switching at room temperature. The initial high resistance can be recovered by reaching the high temperature metallic phase, i.e., temperatures above T c . Interestingly, this resistive switching becomes volatile around the T c . In conclusion, by locally manipulating the volatile and nonvolatile resistive switching using electric field and light, this system is a promising platform for hardware based neuromorphic computing implementations.

97 MATHEMATICS AND COMPUTING↗

Bifurcation from L-mode to internal transport barrier triggered by a magnetic island in tokamak plasmas

Magnetic islands are believed to be responsible for triggering the internal transport barrier (ITB) around the rational surface and hence improves confinement in magnetic confinement fusion plasma, for more than two decades. Although some recent theoretical or modelling works support this hypothesis, the direct experimental demonstration on the ITB triggered by a magnetic island is still missing. Here, we report the first experimental observation that the increase in the magnetic island width triggers the bifurcation of the plasma transport state from a low confinement mode (L-mode) to an ITB mode in tokamak plasma. At medium island widths, the bifurcation appears with a dithering phase, i.e. plasma transitions from L-mode to ITB or vice versa quasi-periodically. As the island width further increases, the dithering ITB transitions into a steady ITB. The electron temperature gradient inside the ITB increases with island width. The trigger of the ITB and further enhancement of the ITB performance are also demonstrated by locking the island via applying a resonant magnetic perturbation field. The reduction of density fluctuations in the ITB region is observed and indicates turbulence suppression during ITB formation. These findings offer new insights for understanding ITB formation and robust ITB control.

internal transport barrier↗

( LaCo O 3 ) n / ( SrCo O 2.5 ) n superlattices: Tunable ferromagnetic insulator

Ferromagnetic insulators have great potential for spintronic applications. For such applications, it is essential to find materials with a robust and controllable ferromagnetic insulating phase. Yet, because ferromagnetism in functional transition-metal oxides is usually coupled to metallicity, ferromagnetic insulators are very rare and independent control of their magnetic and electrical properties is difficult. In this study, the electrical, magnetic, and optical properties of (LaCoO 3 ) n /(SrCoO 2.5 ) n superlattice films are investigated for the manipulation of the ferromagnetic insulating phase. While the superlattices remain insulating irrespective of the periodicity n, the electronic structure and magnetic state vary drastically. Superlattices with large periodicities n of 10 and 20 show a ferromagnetic transition at a critical temperature T C of ~80K. With decreasing periodicity and increasing interface density of the superlattices, system with n =4 becomes almost nonmagnetic, while in systems with n =2 and 1, a reentrant ferromagnetic phase is observed at T C of ~180 and ~225K, respectively. Optical spectroscopy reveals that the fine control of the magnetic ground state is achieved by the modified electronic structure associated with the spin-state transition. Our findings indicate an important design principle to create and manipulate the ferromagnetic insulating properties of Co-based oxide thin films.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Charge Management for an Inductively Charged On-Demand Battery-Electric Shuttle Service with High Penetration of Renewable Energy

This paper presents a charge management control strategy for an on-demand battery-electric shuttle van operating at the National Renewable Energy Laboratory (NREL) campus and supported by day-time inductive charging at the vehicle's waiting spot. A new control algorithm has been proposed for reducing the demand charge costs incurred from wireless charging of the on-demand shuttle. A custom controller has been developed to monitor the shuttle, wireless charger, renewable energy generation, and various loads at NREL's campus, and regulate charging behavior for demand response. The intermittent renewable generation and sporadic operation of the on-demand shuttle service contribute to a high level of uncertainty in expected campus load profile, which must be carefully managed. The control algorithm predicts energy profile to estimate the mobility needs of the vehicle and maintain uninterrupted service during operation while still minimizing peak demand. The proposed controller has been designed and optimized using a Simulink model for the entire system. Next, it has been implemented and tested in real-time on the NREL campus. Two primary vehicle-use cases, charge sustaining and charge depletion operation, are tested under different load profiles and drive cycles to assess the controller's effectiveness at reducing peak demand and therefore demand charges. The proposed controller showed robust performance under different driving scenarios with high correlation between simulated and experimental data. The results showed that proper demand response can be achieved with an average of 94% reduction of charging loads during peak demand events.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗