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At least 91 records · Page 5

Spread spectrum time domain reflectometry (SSTDR) and frequency domain reflectometry (FDR) cable inspection using machine learning

Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, justification for continued cable use must shift to a condition-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. The Pacific Northwest National Laboratory (PNNL) Accelerated and Real Time Experimental Nodal Analysis (ARENA) cable motor test bed was used to test the response of a commercial spread spectrum time domain reflectometry (SSTDR) system, a laboratory instrument software-controlled SSTDR, and a vector network analyzer-based frequency domain reflectometry (FDR) system to various cable anomalies. The three instrument systems were able to interrogate cables over a range of frequency bandwidths that can be helpful for human data analysis. Data were subjected to supervised and unsupervised machine learning (ML) analyses to distinguish normal undamaged cable responses from anomalous cable responses. Both supervised and unsupervised ML approaches produced encouraging results with an undamaged/anomalous prediction accuracy from 0.69% to 0.87%. Recommendations for further development and field implementation include increased and more balanced sample sets particularly including more training data.

SSTDR, FDR, Reflectometry, Machine Learning, ARENA↗

Enabling Production of Algal Biofuels by Techno-Economic Optimization of Co-Product Suites

Recent techno-economic analysis (TEA) has underscored that for algal biofuels to be cost competitive with petroleum fuels, co-products are necessary to offset the cost of fuel production. The co-product suite must scale with fuel production while also maximizing value from the non-fuel precursor components. The co-product suite also depends on algal biomass composition, which is highly dynamic and depends on environmental conditions during cultivation. Intentional shifts in composition during cultivation are often associated with reduced biomass productivity, which can increase feedstock production costs for the algae-based biorefinery. The optimal algae-based biorefinery configuration is thus a function of many factors. We have found that comprehensive TEA, which requires the construction of process models with detailed mass and energy balances, along with a complete accounting of capital and operating expenditures for a commercial-scale production facility, provides invaluable insight into the viability of a proposed biorefinery configuration. This insight is reflected in improved viability for one biorefining approach that we have developed over the last 10 years, namely, the Combined Algal Processing (CAP) approach. This approach fractionates algal biomass into carbohydrate-, lipid-, and protein-rich fractions, and tailors upgrading chemistry to the composition of each fraction. In particular, transitioning from valorization of only the lipids to a co-product suite from multiple components of high-carbohydrate algal biomass can reduce the minimum fuel selling price (MFSP) from more than $8/gallon of gasoline equivalent (GGE) to $2.50/GGE. This paper summarizes that progress and discusses several surprising implications in this optimization approach.

09 BIOMASS FUELS↗

Muconic Acid Production from P. putida Using High Protein Algae Hydrolysate

The composition of algal biomass is highly dynamic, with protein, lipid, and carbohydrate contents varying in response to nutrient and environmental conditions during cultivation. Because shifts in biomass composition are often associated with reduced biomass productivity, production costs can often increase if targeting higher biomass compositional quality (enriched in carbohydrates or lipids at reduced protein content) as input for the algal biorefinery. The optimal algal biorefinery configuration is thus a function of many factors. One of the key strengths of the Combined Algal Processing (CAP) process is the versatility of feedstocks and products produced. The concept has been demonstrated with ethanol and a variety of carboxylic acids (succinic, butyric, muconic) as coproducts along with lipid upgrading to biofuel. Modification of the approaches, processes and downstream upgrading to fuels has allowed the CAP process to reduce costs and improve efficiency. Muconic acid is a high-value, potential fermentation coproduct of interest because it can be easily converted to adipic acid, a high-volume monomer for the production of nylon and other valuable consumer plastics. As such, the production of muconic acid through CAP was explored to expand the suite of products from algal biomass and to begin exploring the valorization of high protein content biomass from rapidly grown algae biomass. We have established initial performance parameters and shown that the range of substrates consumed by the muconic acid-producing microbe, Pseudomonas putida, includes at least glucose, mannose, glycerol, and lactic acid. We achieved complete utilization of these four major hydrolysate substrates achieving productivities of 0.037 (g/L/h) from Scenedesmus obliquus and 0.029 (g/L/h) from Monoraphidium minutum hydrolysates. Final titer and process yield (mol of muconic acid per mol of substrate (molP/molS)) were 0.99 g/L and 0.42 molP/molS from S. obliquus hydrolysate and 0.75 g/L and 0.23 molP/molS from M. minutum hydrolysate, respectively.

BIOMASS FUELS↗

Entanglement suppression for $ΩΩ$ scattering

We study entanglement suppression in $s$-wave $ΩΩ$ scattering, where each baryon has spin $3/2$. By treating the $S$-matrix as a quantum operator acting on the spin states, we quantify its ability to generate entanglement and identify the conditions on the phase shifts of the spin channels that minimize entanglement generation in the system. In $ΩΩ$ scattering, only antisymmetric spin channels are allowed due to Fermi-Dirac statistics. Applying the entanglement-suppression framework to $ΩΩ$ scattering, we find two solutions for the phase shifts: one leading to a spin SU(4) symmetry and the other to a nonrelativistic conformal symmetry. We show that the solution associated with the nonrelativistic conformal symmetry originates from the specific structure of the Clebsch-Gordan coefficients in the $3/2 \otimes 3/2$ system.

Sone, Katsuyoshi [Tokyo Metropolitan U.] (ORCID:00↗

PET-FBA: A lightweight enzyme allocation and thermodynamics-constrained flux analysis approach to explore Escherichia coli metabolic adaptation to intracellular acidification

Escherichia coli employs diverse strategies to adapt to acidic environments that disrupt enzyme activity and the thermodynamic feasibility of essential reactions. To understand the impact of pH stress on cell metabolism, we present the PET-FBA (pH-, Enzyme protein allocation-, and Thermodynamics-constrained Flux Balance Analysis) framework. PET-FBA extends genome-scale modeling by integrating enzyme protein costs and reaction Gibbs free energy changes. Additionally, by incorporating pH-dependent enzyme kinetics in response to intracellular acidification, this framework enables the simulation of E. coli's metabolic adjustments across varying external pH levels. The model's accuracy is validated by comparing in silico growth simulations with experimental measurements under both anaerobic and aerobic conditions, as well as in silico gene knockouts of essential genes. By explicitly incorporating pH effects, our model accurately replicates the metabolic shift towards lactate production as the primary fermentation product at low pH in anaerobic conditions. This shift is only predicted when enzyme kinetics are dynamically adjusted as a function of pH. Further analysis revealed that this shift can be attributed to the reduced protein efficiency of the acetyl-CoA branch compared to lactate dehydrogenase under acidic stress, which then becomes crucial for maintaining NAD regeneration and cell growth at low pH. Furthermore, we identified strategies for enhancing cell growth under acidic anaerobic conditions by improving the enzyme activity of lactate dehydrogenase and pyruvate formate lyase, which increases NAD production efficiency and reduces enzyme protein allocation costs. Designed as a lightweight yet versatile framework, PET-FBA enables efficient genome-scale metabolic analysis. Using E. coli as a model system, our framework provides a systematic approach to understanding metabolic responses to environmental stress, pinpointing key metabolic bottlenecks, and identifying potential targets for strain optimization.

42 ENGINEERING↗

Future Projections of the El Niño—Southern Oscillation and Tropical Pacific Mean State in CMIP6

Abstract The El Niño—Southern Oscillation (ENSO) is an important mode of tropical Pacific atmosphere‐ocean variability that drives teleconnections with weather and climate globally. However, prior studies using state‐of‐the‐art climate models lack consensus regarding future ENSO projections and are often impacted by tropical Pacific sea‐surface temperature (SST) biases. We used 173 simulations from 29 climate models participating in the Coupled Model Intercomparison Project, version 6 (CMIP6) to analyze model biases and future ENSO projections. We analyzed two ENSO indices, namely the ENSO Longitude Index (ELI), which measures zonal shifts in tropical Pacific deep convection and accounts for changes in background SST, and the Niño 3.4 index, which measures SST anomalies in the central‐eastern equatorial Pacific. We found that the warm eastern tropical‐subtropical Pacific SST bias typical of previous generations of climate models persists into many of the CMIP6 models. Future projections of ENSO shift toward more El Niño‐like conditions based on ELI in 48% of simulations and 55% of models, in association with a future weakening of the zonal equatorial Pacific SST gradient. On the other hand, none of the models project a significant shift toward La Niña‐like conditions. The standard deviation of the Niño 3.4 index indicates a lack of consensus on whether an increase or decrease in ENSO variability is expected in the future. Finally, we found a possible relationship between historical SST and low‐level cloud cover biases in the ENSO region and future changes in ELI; however, this result may be impacted by limitations in data availability.

54 ENVIRONMENTAL SCIENCES↗

Time-temperature-stress superposition of PBX 9502 compressive creep data for lifetime predictions

The plastic-bonded explosive (PBX) 9502 is a viscoelastic, high-solids loaded polymer bound composite comprised of 95 weight% (wt%) TATB explosive crystals and 5 wt% FK-800 polymer binder. The uniaxial quasi-static mechanical properties have been studied and characterized extensively over 25+ years, including creep. Creep is the strain evolution over time as a result of an asymmetric load typically at temperatures above ambient. Creep measurements to failure can take excessively long periods of time depending on various factors including applied stress, temperature, and loading rate that render a single test to failure impossible. Using the principles of time-temperature-stress superposition (TTSSP), short-term creep tests at various applied stresses and temperatures can be used for long-term creep predictions. The TTSSP model shifts short-term test data using two factors, one for temperature and stress, creating a master curve at a reference test condition. The master curve can be shifted to predict the creep response at any desired test condition. PBX 9502 compression specimens were tested at three temperatures and various applied stresses. This work discusses the TTSSP analysis of PBX 9502 compressive creep data to create a single comprehensive master curve.

36 MATERIALS SCIENCE↗

Time-Temperature-Stress Superposition of PBX 9502 Compressive Creep Data for Lifetime Predictions

The plastic-bonded explosive (PBX) 9502 is a viscoelastic, high-solids loaded polymer bound composite comprised of 95 weight% (wt%) TATB explosive crystals and 5 wt% FK-800 polymer binder. The uniaxial quasi-static mechanical properties have been studied and characterized extensively over 25+ years, including creep. Creep is the strain evolution over time as a result of an asymmetric load typically at temperatures above ambient. Creep measurements to failure can take excessively long periods of time depending on various factors including applied stress, temperature, and loading rate that render a single test to failure impossible. Using the principles of time-temperature-stress superposition (TTSSP), short-term creep tests at various applied stresses and temperatures can be used for long-term creep predictions. The TTSSP model shifts short-term test data using two factors, one for temperature and stress, creating a master curve at a reference test condition. The master curve can be shifted to predict the creep response at any desired test condition. PBX 9502 compression specimens were tested at three temperatures and various applied stresses. This work discusses the TTSSP analysis of PBX 9502 compressive creep data to create a single comprehensive master curve.

36 MATERIALS SCIENCE↗

How Does Land Cover and Its Heterogeneity Length Scales Affect the Formation of Summertime Shallow Cumulus Clouds in Observations From the US Southern Great Plains?

This study investigates the effects of heterogeneous land covers on shallow cumulus (ShCu) clouds at the US Southern Great Plains using high-resolution satellite and land cover data. During late summer, ShCu occurs over cities the most frequently and over open waters the least frequently, and more often over forest than over grassland. The preferential occurrence of ShCu over forest relative to grassland is consistent with surface measurements showing larger heat fluxes over forests. This preferential occurrence also varies with the length scales of land patches with the largest cloud occurrence difference shifting from smaller length scales (<9 km) during midday to larger scales (>9 km) in the early afternoon. Consistent with theory, these signals are more pronounced under low wind conditions. The preferential length scale shift with time suggests the existence of secondary circulations that strengthen and promote convergence over larger spatial scales as the differential land surface heating intensifies.

54 ENVIRONMENTAL SCIENCES↗

DISCOVR strain pipeline screening – Part II: Winter and summer season areal productivities and biomass compositional shifts in climate-simulation photobioreactor cultures

Assessing the seasonal biomass productivity and compositional shift dynamics under simulated outdoor culture conditions of the top 22 algae strains selected during Tier I flask screening is an important step in the further prioritization of strains with regard to outdoor pond cultivation. These top 22 strains were subjected to Tier II testing in the PNNL Laboratory Environmental Algae Pond Simulator (LEAPS) photobioreactors, simulating light and temperature conditions of 20 cm deep outdoor ponds during the Arizona winter and summer season. All strains were grown in two consecutive nutrient-replete batch culture experiments at their particular optimal medium salinity to quantify their respective seasonal linear-phase areal biomass productivities. To determine biomass compositional shifts in response to nutrient-depletion, the LEAPS cultures were allowed to enter a 9-day nutrient depletion phase at the end of the second batch run. The following strains were evaluated in winter-season climate-simulated cultures and are listed in the order from highest (7.9 g m -2 day -1 ) to lowest (2.3 g m -2 day -1 ) areal N-replete biomass productivity: Monoraphidium minutum 26B-AM, Tetraselmis striata LANL1001, Chlorella vulgaris LRB AZ-1201, Micractinium reisseri NREL14-F2, Monoraphidium sp. MONOR1, Chlorella vulgaris NREL4-C12, Scenedesmus obliquus UTEX393, Scenedesmus acutus LRB-AP-0401, Nannochloropsis oceanica CCAP849/10, and Stichococcus minutus CCALA727. The following strains were evaluated in summer-season climate-simulated cultures and are listed in the order from highest (31.8 g m -2 day -1 ) to lowest (14.2 g m -2 day -1 ) areal N-replete biomass productivity: Picochlorum renovo NREL39-A8, Scenedesmus obliquus UTEX393, Porphyridium cruentum CCMP675, Picochlorum celeri TG2-WT-CSM/EMRE, Chlorella sorokiniana DOE1116, Stichococcus minor CCMP819, Picochlorum oklahomensis CCMP2329, Chlorella sorokiniana DOE1412 (UTEXB3016), Scenedesmus rubescens NREL46B-D3, Picochlorum soloecismus DOE101, Tetraselmis striata LANL1001, Scenedesmus obliquus DOE 0152.z, and Agmenellum quadruplicatum UTEX2268. All LEAPS cultures experienced a significant reduction in areal biomass productivity in response to nutrient-depletion, from 7-16% in the winter season simulation and up to 1-60% in the summer season simulation. Finally, for 10 of the strains tested, the carbohydrate content more than doubled upon nutrient depletion, and for 9 strains, the lipid content increased by over 50% of the initial content.

09 BIOMASS FUELS↗

Effect of Mn on eutectic phase equilibria in Al-rich Al-Ce-Ni alloys

Microstructural analysis of additively manufactured (AM) Al-Ce-Ni-Mn alloys has identified phases not predicted from existing ternary liquidus projections in the Al-Ce-Ni system. Because the rapid cooling rate of AM is orders of magnitude above that of traditional casting, it is unclear if these additional phases arose from the non-equilibrium processing conditions of AM, a drastic shift in phase stability in the system due to the addition of 1 wt% Mn, or some combination of these two influences. The phases and microstructure of cast samples of Al-Ce-Ni and Al-Ce-Ni-Mn alloys were characterized for several annealing conditions which revealed the equilibrium phases at different temperatures. Phase analysis confirmed that minute levels of Mn substituted for Ni in the system drastically shifts the liquidus projection in the Al-rich corner of the ternary phase diagram such that the eutectic Al 3 Ni phase is suppressed in favor of the Al 23 Ni 6 (Ce,Mn) 4 phase. Further addition of Mn promotes the formation of Al 20 Mn 2 Ce and Al 10 Mn 2 Ce phases. The phase analysis data was then used to improve the CALPHAD modeling of the liquidus projection and isothermal sections for the Al-rich Al-Ce-Ni-Mn quaternary system. Thermodynamic modeling and experimental analysis on phases in the AM sample of Al-Ce-Ni with Mn confirmed that the phases present are consistent with Mn-containing Al-Ce-Ni cast samples. Here, this investigation demonstrates the potential for using secondary alloying elements to drastically alter phase stability and microstructure in alloy systems.

36 MATERIALS SCIENCE↗

Datasets used in manuscript, 'High-Throughput Chromosomal Confirmation Capture (Hi-C) Metagenome Sequencing Reveals Moisture Impact on Soil Phage-Host Interactions'

Soil moisture shifts have largely unknown impacts on soil virus-host interactions. Here, we applied high-throughput chromosomal confirmation capture (Hi-C) metagenomics to link phage with their hosts in soils under wet and dry conditions. Bulk metagenomes and metatranscriptomes were analyzed from the same soil incubations. Host-associated phage diversity and the number of viruses per host increased following soil desiccation. Under wet conditions, the viral enrichment and host abundances were significantly negatively correlated, but the transcriptional activities of the phage were higher. Together, these results suggest that there was a general transition of phage from lytic to lysogenic during drying and that viral infection was higher under dry conditions. Soil desiccation also caused shifts in phage hosts and some of these were central in microbial co-occurrence networks, highlighting the impact of soil phages on microbiome structure. This study provides the first empirical evidence of phage-mediated bacterial dynamics during soil desiccation.

59 BASIC BIOLOGICAL SCIENCES↗

Non-conformal interface-cohesive modeling with the shifted boundary method

The accurate simulation of boundary- and interface-dominated problems on complex geometries remains challenging when boundary- or interface-fitted meshes are difficult to generate, particularly for curved boundaries, polycrystalline microstructures, and dense interface networks. The Shifted Boundary Method (SBM) alleviates this meshing burden by shifting the enforcement of boundary conditions from the true boundary to a nearby surrogate boundary and recovering the effect of the true boundary through geometric correction terms, thereby enabling standard finite element spaces on non-boundary-fitted meshes. In this report, we develop a general shiftedboundary and shifted-interface framework within the open-source MOOSE framework. We first present a general SBM implementation for complex geometries on non-boundary-fitted meshes. We then adopt the Shifted Interface Method (SIM) for internal interfaces and develop a unified shifted-interface treatment in which the interface law is enforced on a surrogate interface and the effect of the true interface is recovered through shifted jumps, fluxes, and tractions. This perspective brings scalar thermal-contact and vector-valued cohesive-zone mechanics into a single framework, the latter realized as the Shifted Cohesive Zone Method (SCZM) and coupled with history-dependent constitutive models from NEML2. We further extend the MOOSE mesh infrastructure to support cohesive-zone calculations on distributed meshes. The framework is verified and demonstrated through three progressive studies: Poisson’s equation on a smoothed starshaped domain, a manufactured thermal-contact problem on a non-interface-fitted mesh, and a two-dimensional polycrystalline representative volume element combining crystal plasticity with cohesive grain-boundary interfaces. Across these studies, the shifted formulations reproduce boundary- and interface-fitted reference solutions with high fidelity, indicating that the proposed framework provides an accurate and efficient route to boundary- and interface-dominated simulations on arbitrary geometries without requiring fitted meshes.

Yang, Cheng-Hau↗

A proposed methodology to reduce heat pump size with integrated thermal energy storage

Thermal energy storage (TES) offers a unique storage solution wherein heat is stored for later use to thermally condition an application. Heat pumps (HPs) move heat from relatively cold to a relatively hot with an input of work. Integrating TES into a HP system adds a third temperature body, and the HP can be selectively coupled to operate between any two: a constant temperature application, a temporally fluctuating ambient temperature, or a constant temperature TES. Since the HP-TES system enables operation under different conditions depending on the pair of temperature bodies, changes in efficiency and capacity can be expected. Thus, TES can shift HP operation to more favorable conditions to deliver heat to the application. Consequently, TES increases the apparent capacity of the HP which might enable a nominally smaller HP to be used effectively. This paper outlines a method by which TES can reduce the size of a HP without sacrificing heat delivered to the application. The method is demonstrated for a building cooling application which realized a reduction in nominal HP size from 3 tons to 2.4 tons.

Hirschey, Jason↗

Accelerated pattern matching method on a quantum computing system

A method of determining a pattern in a sequence of bits using a quantum computing system includes setting a first register of a quantum processor in a superposition of a plurality of string index states, encoding a bit string in a second register of the quantum processor, encoding a bit pattern in a third register of the quantum processor, circularly shifting qubits of the second register conditioned on the first register, amplifying an amplitude of a state combined with the first register in which the circularly shifted qubits of the second register matches qubits of the third register, measuring an amplitude of the first register and determining a string index state of the plurality of string index states associated with the amplified state, and outputting, by use of a classical computer, a string index associated with the first register in the measured state.

NIROULA, Pradeep↗

Modeling-Based Design and Optimization of a Gradient Composite Transition Joint

An innovative additively manufactured gradient composite transition joint (AM-GCTJ) has been designed to join dissimilar metals, to address the pressing issue of premature failure observed in conventional dissimilar metal welds (DMWs) when subjected to increased cyclic operating conditions of fossil fuel power plants. The transition design, guided by computational modeling, developed a gradient composite material distribution, facilitating a smooth transition in material volume fraction and physical properties between different alloys. This innovative design seeks to alleviate structural challenges arising from distinct material properties, including high thermal stress and potential cracking issues resulting from the thermal expansion mismatch typically observed in conventional DMWs. In this study, we investigated the creep properties of transition joints comprising Grade 91 steel and 304 stainless steel through a combination of simulations and creep testing experiments. The implementation of a gradient composite design in the plate transition joint resulted in a significant enhancement of creep resistance when compared to the baseline conventional DMW. For instance, the creep rupture life of the transition joint was improved by > 400% in a wide range of temperature and stress testing conditions. Meanwhile, the failure location shifted to the base material of Grade 91 steel. Such enhancement can be primarily attributed to the strong mechanical constraint facilitated by the gradient composite design, which effectively reduced the stresses on the less creep-resistant alloy in the transition zone. Beyond examining plate joints, it is crucial to assess the deformation response of tubular transition joints under pressure loading and transient temperature conditions to substantiate and demonstrate the effectiveness of the design. The simulation results affirm that the tubular transition joint demonstrates superior resistance compared to its counterpart DMW when subjected to multiaxial stresses in tubular structures. In addition, optimization of the transition joint’s geometry dimensions has been conducted to diminish the accumulated deformation and enhance the service life. Lastly, the scalability and potential of the innovative transition joints for large-diameter pipe applications are addressed.

Zhang, Wei↗

Theoretical study of intrinsic defects in cubic silicon carbide 3C-SiC

Using the local moment counter charge (LMCC) method to accurately represent the asymptotic electrostatic boundary conditions within density functional theory supercell calculations, we present a comprehensive analysis of the atomic structure and energy levels of point defects in cubic silicon carbide (3C-SiC). Finding that the classical long-range dielectric screening outside the supercell induced by a charged defect is a significant contributor to the total energy. we describe and validate a modified Jost screening model to evaluate this polarization energy. This leads to bulk-converged defect levels in finite size supercells. With the LMCC boundary conditions and a standard Perdew-Burke-Ernzerhof (PBE) exchange correlation functional, the computed defect level spectrum exhibits no band gap problem: the range of defect levels spans ~2.4 eV, an effective defect band gap that agrees with the experimental band gap. Comparing with previous literature, our LMCC-PBE defect results are in consistent agreement with the hybrid-exchange functional results of Oda et al. [J. Chem. Phys. 139, 124707 (2013)] rather than their PBE results. The difference with their PBE results is attributed to their use of a conventional jellium approximation rather than the more rigorous LMCC approach for handling charged supercell boundary conditions. The difference between standard dft and hybrid functional results for defect levels lies not in a band gap problem but rather in solving a boundary condition problem. The LMCC-PBE entirely mitigates the effect of the band gap problem on defect levels. The more computationally economical PBE enables a systematic exploration of 3C-SiC defects, where, most notably, we find that the silicon vacancy undergoes Jahn-Teller-induced distortions from the previously assumed T d symmetry, and that the divacancy, like the silicon vacancy, exhibits a site-shift bistability in p -type conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Adaptive Reinforcement Learning (ARL) Control of a Multi-port Resonant Converter in UAV Systems

This study presents an adaptive reinforcement learning (ARL) control framework for a multi-port resonant converter used in hybrid unmanned aerial vehicle (UAV) power systems. The converter integrates high-frequency half-bridge input ports connected to a rectified engine–generator set and a battery energy storage system, along with a semi-bridgeless active rectifier supplying the propulsion load. A deep RL agent is trained to dynamically regulate inter-port phase-shift commands in real time based on flight conditions and load power demand. The ARL controller autonomously identifies phase-shift combinations that maximize conversion efficiency while maintaining stable and coordinated power flow, even under rapidly varying operating scenarios. This data-driven approach eliminates the need for explicit system modeling or extensive manual tuning and enables coordinated control among multiple power ports without inter-port communication. Experimental results validate that the ARL based strategy achieves reliable power sharing and consistently high-efficiency operation across diverse UAV operating conditions.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗