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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16

Unified Universal Control and Coordination of Inverter-Based Resources, and Validation for a PV + Battery Hybrid Plant

As renewable energy deployment grows, hybrid power plants (HPPs) combining photovoltaic (PV) and battery systems must evolve to offer both energy and grid stability services. These systems typically include a mix of grid-following (GFL) and grid-forming (GFM) inverters, presenting unique coordination and control challenges. This Department of Energy–funded project developed and validated a Unified Universal Control and Coordination (UUCC) framework for such PV + battery hybrid plants, enabling seamless and stable operation, including ultrafast black start, autonomous synchronization, and robust frequency and voltage regulation, under different grid conditions. The project significantly advanced the understanding of inverter-based resource (IBR) control by developing and validating three complementary system-level approaches for hybrid GFL/GFM operation: 1. A combined Virtual Resistance (VR)-based GFL and Virtual Oscillator Control (VOC)-based GFM method, where each inverter type is governed by a specialized control strategy. Together, these achieve stable, fast-response coordination, eliminating inrush current and enabling smooth black start and grid synchronization across a wide range of grid strengths. 2. A Deadbeat-based UUCC strategy, which uses discrete-time, switching-cycle-level control for both GFL and GFM inverters. This approach replaces traditional PI/PLL control with a control parameter-free, high-bandwidth framework that supports stable LVRT and instantaneous synchronization under all conditions. 3. A benchmark comparison with Siemens’ commercial GFM microgrid controller, which provided a fast baseline platform. The commercial approach decoupled v & f control was implemented on a commercial microgrid controller.The baseline commercial benchmark helped highlight superior transient response and black start performance offered by the deadbeat and VOC approaches. These technical contributions offer substantial improvements over conventional inverter control schemes, which often rely on slow phase-locked loop (PLL)-based synchronization, require careful control parameters tuning, and prone to unstable in weak grids with GFL inverters and in stiff grid with GFM inverters therefore challenging for hybrid GFL+GFM under all grid conditions. The deadbeat-based UUCC framework enables simpler, faster, and more robust operation of hybrid IBR systems using wide-bandgap (WBG) devices such as SiC power semiconductors. The rapid expansion of hybrid distributed energy resources (DERs), including residential and commercial PV-BESS installations such as Tesla Powerwall, PV with vehicle-to-grid (V2G) capability, and other integrated configurations, presents complex operational challenges for medium-voltage radial distribution feeders. These networks are subject to frequent disturbances such as faults, switching operations, rapid reclosing sequences, and feeder reconfigurations, all of which introduce dynamic stress on IBRs. In addition, planned feeder segmentation and deliberate islanding for resilience will require DERs that can autonomously perform blackstart, establish voltage and frequency references, and resynchronize with the main grid. The advanced deadbeat-based UUCC control and blackstart functionalities developed in this project directly address these requirements, enabling decentralized and autonomous operation of inverter-dominated DERs in distribution systems under a wide range of fault and reconfiguration scenarios. From a public benefit perspective, these innovations enable more reliable and cost-effective integration of renewable energy into distribution networks. The ability to autonomously black start and stabilize grids under varying grid conditions support accelerates recovery from outages and support decentralized resilient energy systems. By reducing system complexity and improving performance, this project lays critical groundwork for future inverter-dominated power grids that are clean, reliable, and accessible to all.

14 SOLAR ENERGY↗

Dynamic Oscillation and Motion of Oil‐in‐Water Emulsion Droplets

The interplay of interfacial tensions on droplets results in a range of self‐powered motions that mimic those of living systems and serve as a tunable model to understand their complex non‐equilibrium behavior. Spontaneous shape deformations and oscillations are crucial features observed in nature but difficult to incorporate in synthetic artificial systems. Here, we report sessile oil‐in‐water emulsions that exhibit rapid oscillating behavior. The oscillations depend on the nature and concentration of the surfactant, the chemical composition of the oil, and the wettability of the solid substrate. The rapid changes in the contact angle per oscillation are observed using side‐view optical microscopy. We propose that the changes in the interfacial tension of the oil droplets is due to the partitioning of the surfactant into the oil phase and the movement of self‐emulsified oil out of the parent droplets giving rise to the rhythmic variation in droplet contact‐line. The ability to control and understand droplet oscillation can help model similar oscillations in out‐of‐equilibrium systems in nature and reproduce biomimetic behavior in artificial systems for various applications, such as microfluidic lab‐on‐a‐chip and adaptive materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Gauss-Radau-Laguerre Discrete Variable Representation for Use in Continuum Electron Dynamics

In this work, we detail an implementation, suitable for calculations on highly correlated ionizing systems, of a modified finite element discrete variable representation (FE-DVR) appended with a Gauss-Radau-Laguerre element. The appended element includes exterior complex scaling (ECS) to impose outgoing wave boundary conditions on treatments of processes involving continuum electrons. In this “infinite range” ECS (irECS), the complications that introduce reflections from the end of the grid when the last ECS finite element has finite range are avoided by the use of the Laguerre-weighted exponentially decaying tails, while outgoing wave boundary conditions are still imposed via the ECS transformation. For highly correlated systems in the absence of strong external fields we find that accurate two-electron integrals are essential in this modified FE-DVR. To accurately compute the two-electron integrals over the entire ECS contour, we present a detailed examination of the implications from the boundary terms that arise in a solution of Poisson’s equation with the Radau-Laguerre basis. A boundary term correction is necessary, and when included, the Radau-Laguerre DVR can accurately describe highly correlated states such as the doubly excited states of helium over the entire ECS contour.

elements↗

Field-Driven Out-of-Equilibrium Collective Patterns for Swarm Micro-Robotics

Soft robotics has been rapidly advancing, offering significant improvements over traditional rigid robotic systems through the use of compliant materials that enhance adaptability and interaction with the environment. However, current approaches face critical challenges, including the reliance on complex “top-down” fabrication techniques and the difficulty of wireless powering and control at the microscale. Swarm robotics introduces a paradigm shift, leveraging collective dynamics to achieve cooperative and adaptable behaviors among multiple robotic units. Inspired by nature, this “bottom-up” approach enables swarm robots to execute task-specific reconfigurations, enhancing flexibility and robustness. Field-driven active colloids emerge as a promising platform for swarm microrobotics, capable of self-propulsion and self-organization into dynamic collective patterns under external field excitation and manipulation. These systems mimic biologically inspired swarm behaviors, such as flocking and vortex formation, providing a versatile foundation for designing innovative swarm microrobots. Here, this review discusses the principles of electric and magnetic field-driven collective self-organization, focusing on the particle dynamics, the emergence of collective swarm patterns, and illustrative examples of functional swarm microrobots. It concludes with future perspectives on harnessing these systems for adaptive, scalable, and multifunctional microrobotic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗

Revealing Parallel Inter‐ and Intra‐Ligand Charge Transfer Dynamics in [Ru(L) 2 (dppz)] 2+ Molecular Lightswitch with N K‐Edge X‐Ray Absorption Spectroscopy

In photoactive metal complexes the localization of photoexcited charges dictates the site of chemical reactivity, but few studies measure the charge redistribution in these systems with spatial precision. Herein, we track the inter- and intra-ligand charge transfer processes that underpin light-driven charge separation in the well-studied “molecular lightswitch” [Ru(bpy) 2 dppz] 2+ (aqueous [Ruthenium II (2,2′-bipyridine)2(dipyrido[3,2-a:2′,3′-c]phenazine)] 2+ [Cl − ] 2 ) by probing the electronic structure of ligand nitrogen atoms in real-time using ultrafast X-ray absorption spectroscopy and first principles calculations. We confirm the localization of excited electron density on the phenazine N atoms of dppz and we newly identify two parallel electron transfer pathways to populate this state. Sub-70 fs electron transfer to the phenazine portion of dppz is observed and attributed to intra-ligand electron transfer following Ru-to-dppz metal-to-ligand charge transfer (MLCT) excitation. This fast charge transfer was not reported in prior ultrafast studies. The slower (ca. 2 ps) charge transfer reported extensively in time-resolved optical absorption and emission studies is reassigned here to inter-ligand electron “hopping” between nearly isoenergetic ligand moieties following Ru-to-bpy MLCT excitation. In conclusion, the results demonstrate much faster charge separation than previously identified in this well-studied system, highlighting how extended azaacene ligand motifs promote the competitive charge transfer processes needed to drive light-driven electron transfer chemistry.

Donor-acceptor systems↗

Reduced-dimension Bayesian optimization for model calibration of transient vapor compression cycles

Development and calibration of first-principles dynamic models of vapor compression cycles (VCCs) is of critical importance for applications that include control design and fault detection and diagnostics. Nevertheless, the inherent complexity of models that are represented by large systems of differential–algebraic equations leads to significant challenges for model calibration processes that utilize classical gradient-based methods. Bayesian optimization (BO) is a sample-efficient and gradient-free approach using a probabilistic surrogate model and optimal search over a feasible parameter space. Despite the benefits of BO in reducing computational costs, challenges remain in dealing with a high-dimensional calibration task resulting from a large set of parameters that have significant impacts on system behavior and need to be calibrated simultaneously. This paper presents a reduced-dimension BO framework for calibrating transient VCCs models where the calibration space is projected to a low-dimensional subspace for accelerating convergence of the solution algorithm and consequently reducing the number of transient simulations. The proposed approach was demonstrated via two case studies associated with different VCC applications where 10 parameters were calibrated in each case using laboratory measurements. The reduced-dimension BO framework only required 1 / 8 th of the iterations associated with a standard BO method that deals with high-dimensional calibration parameters for converged solutions and yielded comparable accuracy. Furthermore, both calibrated models revealed significant accuracy improvements compared to uncalibrated models.

Ma, Jiacheng↗

Ionic Liquid-Enhanced Interfaces to Boost Reactive C O2 Capture

The addition of ionic liquids (ILs) to a mixture containing a molecular solvent and other ionic species can induce the heterogeneous redistribution of cations and anions at the gas–liquid interface. This nonuniform redistribution of cations and anions driven by the differences in the solvophilicity of ions can improve the thermophysical and interfacial properties of such mixtures, creating a local chemical environment that is conducive to some reactions. In this work, ILs are added to a mixture of potassium hydroxide (KOH) and ethylene glycol (EG), used as a reactive absorbent and electrolyte in the migration-assisted moisture-gradient (MAMG) process for CO 2 capture. Molecular dynamics (MD) simulations are employed to probe into the effects of complex ion–ion and ion–solvent interactions and to examine the chemical composition at the gas–liquid interface. A total of 12 systems are investigated using molecular simulations to identify trends in the performance of IL additives based on the choice of cation, anion, and IL concentration. The cation effects are studied using IL additives based on 1-ethyl-3-methylimidazolium ([EMIM] + ) and 1-butyl-3-methylimidazolium ([BMIM] + ), while the impact of anions is examined using additives based on dicyanamide [DCA] − , triflate [TfO] − , bistriflimide [NTf 2 ] − , and hexafluorophosphate [PF 6 ] − anions, respectively. The influence of the IL concentration is also evaluated at molar concentrations between 1% and 4%. The simulation results indicate that the use of IL additives can affect the physical CO 2 solubility, surface tension, and the localization of CO 2 around the [OH] − ions at the gas–liquid interface. It is also evident that the choice of cations, anions, and IL concentration determines the extent to which the IL additives impact the local physicochemical properties. Physical dissolution, diffusive transport, and interaction with [OH] − are critical intermediate steps toward reactive CO 2 capture using a liquid absorbent. Hence, the improvement in one or more of these properties, aided by IL additives, is expected to improve the overall CO 2 capture performance. Experiments reaffirmed the impact of IL additives on CO 2 capture performance and the sensitivity to the choice of the cation, anion, and concentration of the IL additive.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integrative mapping reveals molecular features underlying the mechanism of nucleocytoplasmic transport

Nuclear pore complexes (NPCs) enable rapid, selective, and robust nucleocytoplasmic transport. To explain how transport emerges from the system components and their interactions, we used experimental data and theoretical information to construct an integrative Brownian dynamics model of transport through an NPC, coupled to a kinetic model of transport in the cell. The model recapitulates key aspects of transport for a wide range of molecular cargoes, including preribosomes and viral capsids. Our model quantifies how flexible phenylalanine-glycine (FG) repeat proteins create an entropic barrier to passive diffusion and how this barrier is selectively lowered in facilitated diffusion by the many transient interactions of nuclear transport receptors with the FG repeats. Selective transport is enhanced by “fuzzy” multivalent interactions, redundant FG repeat mass, coupling to the energy-dependent RanGTP concentration gradient, and exponential dependence of transport kinetics on the transport barrier. Our model will facilitate rational modulation of the NPC and its artificial mimics.

Raveh, Barak [School of Computer Science and Engin↗

Credible Criticality Safety Margin in the 30B Package with LEU+ UF 6 and Hypothetical Water Ingress

The commercial nuclear industry is pursuing advancements in fuel and reactor design that increase the uranium enrichment above 5 wt. % 235 U. These advancements will necessitate the ability to transport bulk quantities of UF 6 at increased enrichments. Currently, the 30B cylinder is the primary container used by the industry for UF 6 storage and transportation and has a long history of successful shipments. This container can support up to 2,277 kg of UF 6 at a maximum enrichment of 5 wt. % 235 U. Previous evaluations have assessed the potential impact of criticality safety for 30B transport at higher enrichments but assumed moderator intrusion would not require evaluation. Although current regulations allow for the exception of moderator intrusion for UF 6 packages through the design and quality control of the package content, this exception is limited to enrichments up to 5 wt. % 235 U. Thus, an investigation of moderator intrusion into a 30B cylinder should be performed. Moderator intrusion into a 30B cylinder is a unique condition for criticality safety evaluation in transportation because of the violent chemical reactions that occur between UF 6 and H 2 O. The resulting intrusion is strongly dependent on the breach size, breach location, breach interface solid/ullage of the UF 6 content, the UF 6 distribution (which is temperature dependent), and temperature/pressure conditions which are dynamic in accident conditions. Additionally, the complexity of the HF-UO 2 F 2 -H 2 O interface that occurs during the event can influence the potential solubility of uranium in the system, as well as influence the amount of UF 6 reaction with H 2 O. With the operating experience from Orano Federal Services LLC, the UF 6 chemical expertise from Oak Ridge National Laboratory (ORNL), and the criticality safety expertise from ORNL, this paper evaluates the neutronic conditions (i.e., k eff ) that apply the understood chemistry and experimental conditions that occur during moderator intrusion of a breached 30B cylinder under postulated accidents. This report examines the historical evaluations of UF 6 transport and expands these evaluations for the enrichments expected for nuclear industry advancement. These simulations primarily feature a homogeneous mixture of UF 6 and H 2 O as an infinite media system and as a sphere with water reflection given an impurity limit of 0.5 wt. % UF 6 . This report demonstrates that this H/U limit is valid up to 8 wt. % enrichment for both H 2 O and HF as the moderating mixture. The water-reflected homogeneous mixed spheres evaluated demonstrate the amount of safety margin applied by restricting the 30B cylinder impurity limit to 0.5 wt. %. Additionally, this report evaluates moderator ingress scenarios of a 30B cylinder. The 30B cylinder simulations vary the cylinder orientation, the mass of UF 6 in the system, the mass of H 2 O in the system, and how much H 2 O has reacted with UF 6 . The moderator ingress of a 30B cylinder was evaluated for the water-reflected homogeneous mixed spheres to demonstrate the amount of safety margin applied by restricting the 30B cylinder impurity limit to 0.5 wt. %. These simulations are standard practice and are independent of the UF 6 -H 2 O reaction. This work also explored more complex simulations that layer the H 2 O over the UF 6 , which incorporates the amount of reacted UF 6 as a separate layer and considers solubility limits of UO 2 F 2 in H 2 O as it is produced. This approach is intended to simulate the postulated event of a large hairline crack occurring on a submerged cylinder. Finally, this work considers the potential of H 2 O mixing into the UF 6 solid heterogeneously using a sponge-like model. The water ingress into the UF 6 is treated as random size spheres, and the reaction products form into a layer over the spheres.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Compact representation and long-time extrapolation of real-time data for quantum systems using the ESPRIT algorithm

Representing real-time data as a sum of complex exponentials provides a compact form that enables both denoising and extrapolation. As a fully data-driven method, the Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm is agnostic to the underlying physical equations, making it broadly applicable to various observables and experimental or numerical setups. In this work, we consider applications of the ESPRIT algorithm primarily to extend real-time dynamical data from simulations of quantum systems. We evaluate ESPRIT's performance in the presence of noise and compare it to other extrapolation methods. We demonstrate its ability to extract information from short-time dynamics to reliably predict long-time behavior and determine the minimum time interval required for accurate results. We discuss how this insight can be leveraged in numerical methods that propagate quantum systems in time, and we show how ESPRIT can predict infinite-time values of dynamical observables, offering a purely data-driven approach to characterizing quantum phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

X-ray and molecular dynamics study of the temperature-dependent structure of molten NaF-Zr⁢F 4

The local atomic structure of NaF-Zr⁢F 4 (53–47 mol%) molten system and its evolution with temperature are examined with x-ray scattering measurements which are then used to validate the quality of ab initio and neural network-based molecular dynamics (NNMD) calculations in the temperature range 515–700°⁢C. The machine-learning enhanced NNMD calculations offer improved efficiency while maintaining accuracy at higher distances compared to ab initio calculations. Looking at the evolution of the pair distribution function with increasing temperature, a fundamental change in the liquid structure within the selected temperature range, accompanied by a slight decrease in overall correlation is revealed. NNMD calculations indicate the coexistence of three different fluorozirconate complexes: [Zr⁢F 6 ] 2– , [Zr⁢F 7 ] 3– , and [Zr⁢F 8 ] 4– , with a shift in the dominant coordination state from the 7-coordinated Zr cation toward a 6-coordinated cation with increasing temperature. The study also highlights the metastability of different local coordination structures, with frequent interconversions between the 6- and 7-coordinate states. Analysis of the Zr-F-Zr angular distribution function reveals the presence of both “edge-sharing” and “corner-sharing” fluorozirconate complexes with specific bond angles and distances in accord with previous studies, while the next-nearest-neighbor cation-cation correlations demonstrate a clear preference for unlike cations as nearest-neighbor pairs, emphasizing nonrandom arrangement. Finally, these findings contribute to a comprehensive understanding of the complex local structure of the molten salt, providing insights into temperature-dependent preferences and correlations within the molten system.

36 MATERIALS SCIENCE↗

Advances in understanding vacuum break dynamics in liquid helium-cooled tubes for accelerator beamline applications

Understanding air propagation and condensation following a catastrophic vacuum break in particle accelerator beamlines cooled by liquid helium is essential for ensuring operational safety. This review summarizes experimental and theoretical work conducted in our cryogenics lab to address this issue. Systematic measurements were performed to study nitrogen gas propagation in uniform copper tubes cooled by both normal liquid helium (He I) and superfluid helium (He II). These experiments revealed a nearly exponential deceleration of the gas front, with stronger deceleration observed in He II-cooled tubes. To interpret these results, a one-dimensional (1D) theoretical model was developed, incorporating gas dynamics, heat transfer, and condensation mechanisms. The model successfully reproduced key experimental observations in the uniform tube system. However, recent experiments involving a bulky copper cavity designed to mimic the geometry of a superconducting radiofrequency (SRF) cavity revealed strong anisotropic flow patterns of nitrogen gas within the cavity, highlighting limitations in extrapolating results from simplified tube geometries to real accelerator beamlines. To address these complexities, we outline plans for systematic studies using tubes with multiple bulky cavities and the development of a two-dimensional (2D) model to simulate gas dynamics in these more intricate configurations. As a result, these efforts aim to provide a comprehensive understanding of vacuum breaks in particle accelerators and improve predictive capabilities for their operational safety.

Beamline tube↗

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗

Dynamics and thermodynamics of the 𝑆 = $\frac{5}{2}$ almost Heisenberg triangular lattice antiferromagnet K 2⁢ Mn⁢(SeO 3 ) 2

Here, we report calorimetric, magnetic, and neutron scattering studies on an 𝑆 = 5/2, nearly Heisenberg triangular-lattice antiferromagnet K 2 ⁢Mn⁢(SeO 3 ) 2 with weak XXZ easy-axis anisotropy. Multiple magnetic phases are identified, including a noncollinear Y phase in zero field, a field-induced collinear 𝑚 = 1/3 magnetization plateau, and a high-field V phase. In the Y phase, the magnetic excitation spectrum exhibits both single-magnon excitations and an extended high-energy continuum. Both features are well described by nonlinear spin wave theory. In the field-induced phases, complex effects of the spectrum renormalization even for large 𝑆 = 5/2 material are clearly detectable. These results underscore the essential role of magnon-magnon interactions in the dynamics of large-𝑆 Heisenberg spin systems on a triangular lattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Federated Learning for Efficient Condition Monitoring and Anomaly Detection in Industrial Cyber-Physical Systems

Detecting and localizing anomalies in cyber-physical systems (CPS) has become increasingly challenging as systems grow in complexity, particularly due to varying sensor reliability and node failures in distributed environments. While federated learning (FL) offers a foundation for distributed model training, existing approaches lack mechanisms to handle these CPS-specific challenges. This paper presents an enhanced FL framework that introduces three key innovations: adaptive model aggregation based on sensor reliability, dynamic node selection for resource optimization, and Weibull-based checkpointing for fault tolerance. Our framework enables reliable condition monitoring while addressing the computational and reliability challenges of industrial CPS deployments. Experiments on NASA Bearing and Hydraulic System Datasets demonstrate superior performance over state-of-the-art FL methods, achieving 99.5% AUC-ROC in anomaly detection and maintaining accuracy under node failures. Statistical validation using Mann-Whitney (U) test confirms significant improvements (p < 0.05) in both detection accuracy and computational efficiency across diverse operational scenarios.1

Marfo, William [University of Texas at El Paso,Dep↗

UltraSep Acoustic Separation Platform

UltraSep is an intelligent ultrasonic separation platform that transforms solid–liquid separation through real-time eigenfrequency resonance locking and ultra-low power energy optimization. By dynamically matching ultrasonic output to system resonance while maximizing particulate removal per unit of applied energy, UltraSep replaces centrifugation and fouling-prone filtration with precision-controlled acoustic forces that significantly reduce power consumption, mechanical complexity, and operating cost while improving recovery performance. This integrated platform unites patented resonance-based acoustic control and energy-per-removal optimization with chemistry-enhanced separation and proprietary system software into a scalable, high-impact commercial technology.

42 ENGINEERING↗