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At least 739 records · Page 41

HelioSwarm: Relative Orbit Maintenance in Eccentric P/2 Lunar Resonant Orbit

Science missions employing multi-point measurements require planned and repeatable swarm geometries. Cis-lunar orbits enable heliophysics studies of solar wind but introduce new challenges in relative motion control. For a multi-satellite swarm in lunar-resonant orbit, insertion and maintenance maneuvers address orbit eccentricity and evolution, as well as three-body gravitational perturbations. Local Velocity-Normal-Conormal coordinates prove to be an effective framework for relative motion design and control. Parametric studies investigate maneuver placement efficiency in controlling relative motion in cis-lunar orbit.

Relative Motion↗

Physics-Based Analysis of Cell Imbalances and Aging in Lithium-Ion Battery Modules and Packs

Lithium-ion battery (LIB) packs are a key solution for grid-scale energy storage, enabling grid resilience and supporting critical infrastructure. LIB modules and packs experience current imbalances and uneven cell aging due to various design and operational factors, and require a battery management system (BMS) to continuously monitor and control. In this context, a physics-based modeling framework for LIB modules and packs (liionpack) was enhanced to identify design and control strategies that minimize current imbalance and improve module/pack operation. Simulations of an 8-cell parallel-connected module demonstrate that reducing current imbalance leads to more uniform cell aging and improved module/pack-level degradation predictions. The analysis shows that current imbalance are affected by the electrical resistances. Terminal location significantly affects imbalance, with opposite-end terminal connections at intermediate branches minimizing the imbalance, and the pack circuit construction influences the accuracy of physics-based analysis at the pack scale. This framework enables design optimization of modules and packs through a fast and easy evaluation of pack performance and aging, and supports the development of aging-informed balancing strategies compatible with BMS implementation. Thereby, offering practical pathways to improve reliability and cycle life predictions in large-scale battery energy storage systems.

Ayalasomayajula, Surya Mitra [Oak Ridge National L↗

Control coordination in inverter‐based microgrids using AoI‐based 5G schedulers

Abstract A coordinated set point automatic adjustment with correction enabled (C‐SPAACE) framework that uses 5G communication for real‐time control coordination between inverter‐based resources (IBR) in microgrids is proposed. Utilising slicing capability, 5G offers low‐latency communication to C‐SPAACE under normal conditions. However, given the multitude of power grid use cases, a certain 5G slice for C‐SPAACE may have access only to limited radio spectrum resources, which if not managed well, greatly undermines the communication needs of C‐SPAACE framework. Thus, optimally scheduling the available spectrum resources among IBRs in a sliced 5G network‐based C‐SPAACE framework becomes a critical problem. To address this issue, the authors utilise a novel age of information (AoI) metric and designs an AoI‐based 5G scheduler to provide low‐latency communication to C‐SPAACE. Following this, a co‐simulation environment is designed using PSCAD/EMTDC and Python to simulate a microgrid supported by 5G communication. Time‐domain simulation case studies are performed using the proposed co‐simulation environment to evaluate the performance of C‐SPAACE using 5G with both AoI‐based and other baseline (non‐AoI) schedulers.

Choudhury, Biplav↗

WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions

Abstract. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) is a state-of-the-art land surface model that simulates the intricate interactions between the terrestrial land surface and other components of the Earth system. Originating from the Community Land Model (CLM) version 4.5, ELM has been under active development, with added new features and functionality, including plant hydraulics, radiation–topography interaction, subsurface multiphase flow, and more explicit land use and management practices. This study integrates ELM v2.1 with the Weather Research and Forecasting (WRF; WRF-ELM) model through a modified Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) framework, enabling affordable high-resolution regional modeling by leveraging ELM's innovative features alongside WRF's diverse atmospheric parameterization options. This framework includes a top-level driver for variable communication between WRF and ELM and Earth System Modeling Framework (ESMF) caps for the WRF atmospheric component and ELM workflow control, encompassing initialization, execution, and finalization. Importantly, this LILAC–ESMF framework demonstrates a more modular approach compared to previous coupling efforts between WRF and land surface models. It maintains the integrity of ELM's source code structure and facilitates the transfer of future developments in ELM to WRF-ELM. To test the ability of the coupled model to capture land–atmosphere interactions over regions with a variety of land uses and land covers, we conducted high-resolution (4 km) WRF-ELM ensemble simulations over the Great Lakes region (GLR) in the summer of 2018 and systematically compared the results against observations, reanalysis data, and WRF-CTSM (WRF coupled with the Community Terrestrial Systems Model). In general, the coupled WRF-ELM model has reasonably captured the spatial distribution of surface state variables and fluxes across the GLR, particularly over the natural vegetation areas. The evaluation results provide a baseline reference for further improvements in ELM in the regional application of high-resolution weather and climate predictions. Our work serves as an example to the model development community for expanding an advanced land surface model's capability to represent fully-coupled land–atmosphere interactions at fine spatial scales. The development and release of WRF-ELM marks a significant advancement for the ELM user community, providing opportunities for fine-scale regional representation, parameter calibration in coupled mode, and examination of new schemes with atmospheric feedback.

54 ENVIRONMENTAL SCIENCES↗

Control of Mixing and Reactive Flow Processes

The interdisciplinary field of reactive flow control is one that holds a great deal of promise for the optimization of complex phenomena occurring in many practical systems, ranging from automobile and gas turbine engines to environmental thermal destruction systems. The fundamental underpinnings of combustion control, however, require a detailed level of understanding of complex reactive flow phenomena, and, in the case of closed-loop active control, require the ability to sense (monitor) and actuate (manipulate) flow processes in a spatially distributed manner in "near real time". Hence the ultimate growth and success of the field of reactive flow control is intimately linked: 1) to advances in the understanding, simulation, and model reduction for complex reactive flows, 2) to the development of experimental diagnostic techniques, in particular, to the development of physically robust sensors, and 3) to the development of a framework or frameworks for generation of closed loop control algorithms suitable for unsteady, nonlinear reactive flow systems. The present paper seeks to outline the potential benefits and technical challenges that exist for mixing and combustion control in fundamental as well as practical systems and to identify promising research directions that could help meet these challenges.

Karagozian, A. R.↗

Quantum optimal control for pure-state preparation using one initial state

This paper presents a framework for solving the pure-state preparation problem using numerical optimal control. As an example, we consider the case where a number of qubits are dispersively coupled to a readout cavity. Herein, we model open system quantum dynamics using the Markovian Lindblad master equation driven by external control pulses. The main result of this paper develops a basis of density matrices (a parameterization) where each basis element is a density matrix by itself. Utilizing a specific objective function, we show how an ensemble of the basis elements can be used as a single initial state throughout the optimization process—independent of the system dimension. We apply the general framework to the specific application of ground-state reset of one and two qubits coupled to a readout cavity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An Automated Disruption-Tolerant Key Management Framework for Critical Systems

Key management is critical to secure operation. Distributed control systems, such as Supervisory Control and Data Acquisition (SCADA) systems, have unique operational requirements that make conventional key management solutions less effective and burdensome. This paper presents a novel Kerberos-based framework for automated, disruption-tolerant key management for control system environments. Here, experimental tests and their results are presented to quantify the expected performance overhead of this approach. Additionally, Zeek sensor analytics are presented to aid in monitoring the health and security of the key management framework operation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

An encoder–decoder LSTM-based EMPC framework applied to a building HVAC system

Numerous studies have demonstrated the benefit of economic model predictive control (EMPC) applied to building heating, ventilation, and air conditioning (HVAC) systems. However, the construction and training of predictive models for building HVAC systems are widely recognized as a key technological barrier preventing large-scale adoption of EMPC for buildings. In this work, an encoder–decoder long short-term memory-based EMPC framework is developed. The key advantage of the approach is that a model may be automatically generated from a list of inputs and outputs. From the definition of inputs and outputs, the constructed model may be trained and automatically embedded into the EMPC framework for real-time estimation and control. The overall end-to-end EMPC framework from model training to on-line estimation and control are described. To this end, the encoder–decoder model provides a natural framework for state estimation (encoder), which is required to provide an initial condition for the predictive model of EMPC (decoder). Closed-loop simulations using EnergyPlus are performed to demonstrate the approach. The simulated closed-loop system consists of a building zone from a multi-zone building, which is served by an air handling unit-variable air volume HVAC system. For the HVAC example considered, the trained encoder–decoder model can predict the indoor air temperature and HVAC sensible cooling rate of a building zone over a two-day horizon with high accuracy. Overall, we find that considering a time-of-use electric rate structure, the EMPC, which manipulates the zone temperature setpoint, can reduce the HVAC power consumption cost relative to keeping the zone temperature setpoint at its maximum value (i.e., minimum energy approach).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

RFSoC based digital low level RF control firmware and software suite (mimo_llrf) v1.0

It features a framework of a firmware and software architecture in support of building a digital low-level RF control system for accelerators, where precised digital RF generation and measurement are needed across many RF channels. It primarily supports the Xilinx RFSoC chips (xczu48dr, xczu47dr, xczu29dr) and their evaluation boards (zcu208, zcu216), for a highly integrated solution enabling the need for synchronous low-level RF systems, including: multi-tile synchronization, external reference for sampling clocks, deterministic delay, aligned NCO phase for digital mixers, and built-in EPICS IOC.

Du, Qiang [Lawrence Berkeley National Laboratory (↗

Bridging microscopic dynamics and rheology in the yielding of charged colloidal suspensions

The yielding of soft materials is critical to many natural and industrial processes, yet experimental insights into microscopic aspects of yielding are limited. This study combines angle X-ray scattering, X-ray photon correlation spectroscopy, and in situ rheology (Rheo-SAXS-XPCS) with fast lubrication dynamics simulations to examine how interparticle interactions influence yielding in charged colloidal suspensions. By tuning attraction through salt addition, we compare repulsive and attractive systems under deformation. Repulsive suspensions yield uniformly with Andrade-like creep and minimal structural change. In contrast, attractive suspensions show complex behaviors, including shear banding, delayed yielding, and resolidification, governed by transient dynamics at shear band interfaces. These results directly link microscopic particle dynamics to macroscopic flow and demonstrate how interaction potentials control rheological behavior. This work offers a framework for designing soft materials with tailored properties for applications in coatings, food processing, drug delivery, and other technologies requiring precise mechanical control.

Molecular Dynamics Simulation↗

A "Kane's Dynamics" Model for the Active Rack Isolation System

Many microgravity space science experiments require vibratory acceleration levels unachievable without active isolation. The Boeing Corporation's Active Rack Isolation System (ARIS) employs a novel combination of magnetic actuation and mechanical linkages to address these isolation requirements on the International Space Station (ISS). ARIS provides isolation at the rack (International Standard Payload Rack (ISPR)) level. Effective model-based vibration isolation requires: (1) an appropriate isolation device, (2) an adequate dynamic (i.e., mathematical) model of that isolator, and (3) a suitable, corresponding controller. ARIS provides the ISS response to the first requirement. This paper presents one response to the second, in a state space framework intended to facilitate an optimal-controls approach to the third. The authors use "Kane's Dynamics" to develop a state-space, analytical (algebraic) set of linearized equations of motion for ARIS.

Hampton, R. D.↗

Fluoroarene Separations in Metal-Organic Frameworks with Two Proximal Mg 2+ Coordination Sites

Fluoroarenes which are widely used in medicinal, agricultural, and materials chemistry, and yet their production remains a critical challenge in organic synthesis. Indeed, the nearly identical physical properties of these vital building blocks hinders their purification by traditional methods, such as flash chromatography or distillation. As a result, the Balz-Schiemann reaction is currently employed to prepare fluoroarenes instead of more atom-economical C-H fluorination reactions, which produce inseparable mixtures of regioisomers. Herein, we propose an alternative solution to this problem: the purification of mixtures of fluoroarenes using metal-organic frameworks (MOFs). Specifically, we demonstrate that controlling the interaction of fluoroarenes with adjacent coordinatively unsaturated Mg 2+ centers within a MOF enables the separation of fluoroarene mixtures with unparalleled selectivities. Liquid-phase multicomponent equilibrium adsorption data and breakthrough measurements coupled with van der Waals-corrected density functional theory calculations reveal that the materials Mg 2 (dobdc) (dobdc 4- = 2,5-dioxidobenzene-1,4-dicarboxylate) and Mg 2 ( m -dobdc) ( m -dobdc 4- = 2,4-dioxidobenzene-1,5-dicarboxylate) are capable of separating the difluorobenzene isomers from one another. Additionally, these frameworks facilitate the separations of fluoroanisoles, fluorotoluenes, and fluorochlorobenzenes. In addition to enabling currently unfeasible separations for the production of fluoroarenes, our results suggest that carefully controlling the interaction of isomers with not one but two strong binding sites within a MOF provides a general strategy for achieving challenging liquid-phase separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Overview of Quantum Sensing Materials and Techniques for Energy Sector Applications

The energy sector has become increasingly dependent upon highly sensitive sensing devices for a wide range of applications. Variables such as temperature, pH, electromagnetic fields, ions, and pressure must be measured with high precision, often in harsh conditions (e.g. highly corrosive environments due to high temperature, pressure and humidity). These sensors are deployed in infrastructure such as transformers, pipelines, mines, nuclear power plants, and other areas to ensure safe operating conditions and uninterrupted, optimized service. Moreover, new opportunities for sensors have emerged due to the expansion of smart grids/meters, driverless vehicles, and the discovery of new oil, gas, and critical mineral deposits. The continued maturation of quantum sensing technologies offers exciting opportunities for quantum-enhanced measurements within the energy sector that may provide significant improvements in sensitivity beyond the classical limit. Here, an overview of established and emerging quantum materials for sensing applications will be provided, from trapped ions to color centers in diamond and silicon carbide. Associated quantum sensing methods for these materials will be discussed, with an emphasis on platforms that are nearing commercial viability. Specific application opportunities within the energy sector for quantum sensors will then be analyzed, including oil/gas discovery, greenhouse gas emission monitoring, pH and ion sensing, current measurement in electric vehicle batteries, and quantum-enhanced spectroscopy. Remaining barriers, such as quantum sensor platform miniaturization and ruggedization, will also be analyzed. A specific project at the National Energy Technology Laboratory involving the functionalization of qubits using metal-organic frameworks for enhanced quantum sensing will also be highlighted. Here, nitrogen vacancy centers (NV) in nanodiamonds, a commercially available qubit with long coherence times and utilizable quantum properties at room temperature, are encapsulated in a controlled way using the metal-organic framework ZIF-8. The ZIF-8 provides a well-defined, porous scaffold that can be controlled to promote the selective uptake of specific target analytes, such as gas molecules or ions. The quantum sensing performance of this composite material is either preserved or enhanced following ZIF-8 encapsulation; the optically detected magnetic resonance response of the NV nanodiamonds with and without the ZIF-8 coating are identical, while the ZIF-8 coating increases the longitudinal spin relaxation lifetime (T1) of the NV centers, an important parameter for spin relaxometry-based quantum sensing experiments. Taken together, these results demonstrate the importance of qubit functionalization as a crucial step for rationally designing high performance quantum sensors.

Crawford, Scott↗

Enhancing Autonomous Control of Microreactors Using Multi-Agent Reinforcement Learning

In order for microreactors to be economically competitive, operation costs will need to be minimized through some degree of autonomous control. Previous work has demonstrated the effectiveness of reinforcement learning (RL) for load-following control in a drum-controlled microreactor. This study extends that work by exploring the potential of RL to independently control each of the reactor’s drums. We compare a single-agent RL approach with a multi-agent RL (MARL) framework, testing them for generalization across different load-following power profiles and control timescales, and for robustness in cases of randomly disabled control drums. Since the point kinetics simulation environment used in this study cannot resolve spatial effects, we assume that in the absence of spatially localized disturbances, optimal drum movements should be symmetrical. We demonstrate that single-agent RL is able to achieve accurate performance only when symmetric actions are ignored; otherwise, it fails to train a useful controller. Meanwhile, the MARL framework performs symmetric actions by design and trains a robust, accurate agent, as evidenced by mean absolute errors in power matching of 0.41% for the training power profile, 0.68% for a profile with half the drums disabled, and 0.21% for a profile on a realistic load-following time horizon.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

A "Kanes's Dynamics" Model for the Active Rack Isolation System

Many microgravity space-science experiments require vibratory acceleration levels unachievable without active isolation. The Boeing Corporation's Active Rack Isolation System (ARIS) employs a novel combination of magnetic actuation and mechanical linkages, to address these isolation requirements on the International Space Station (ISS). ARIS provides isolation at the rack (international Standard Payload Rack, or ISPR) level. Effective model-based vibration isolation requires (1) an appropriate isolation device, (2) an adequate dynamic (i.e., mathematical) model of that isolator, and (3) a suitable, corresponding controller. ARIS provides the ISS response to the first requirement. This paper presents one response to the second, in a state-space framework intended to facilitate an optimal-controls approach to the third. The authors use "Kane's Dynamics" to develop an state-space, analytical (algebraic) set of linearized equations of motion for ARIS.

Hampton, R. David↗

Homopolymer self-assembly of poly(propylene sulfone) hydrogels via dynamic noncovalent sulfone-sulfone bonding

Natural biomolecules such as peptides and DNA can dynamically self-organize into diverse hierarchical structures. Mimicry of this homopolymer self-assembly using synthetic systems has remained limited but would be advantageous for the design of adaptive bio/nanomaterials. Here, we report both experiments and simulations on the dynamic network self-assembly and subsequent collapse of the synthetic homopolymer poly(propylene sulfone). The assembly is directed by dynamic noncovalent sulfone–sulfone bonds that are susceptible to solvent polarity. The hydration history, specified by the stepwise increase in water ratio within lower polarity water-miscible solvents like dimethylsulfoxide, controls the homopolymer assembly into crystalline frameworks or uniform nanostructured hydrogels of spherical, vesicular, or cylindrical morphologies. These electrostatic hydrogels have a high affinity for a wide range of organic solutes, achieving >95% encapsulation efficiency for hydrophilic small molecules and biologics. This system validates sulfone–sulfone bonding for dynamic self-assembly, presenting a robust platform for controllable gelation, nanofabrication, and molecular encapsulation.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic modeling and simulation of pressure swing adsorption processes using toPSAil

Pressure swing adsorption (PSA) has attracted significant recent interest for chemical process intensification due to its potential for high energy efficiency and amenability to small, modular designs. However, the lack of simulation tools that are readily available, transparent, and trusted, has been identified as a serious impediment to widespread adoption of PSA, as well as to further research on PSA modeling, numerical solution, optimization, and control. This paper presents a complete framework for dynamic modeling and simulation of PSA processes and its implementation in an open-source simulator called toPSAil. Further, the presentation is tutorial and includes many modeling and implementation details often overlooked in existing literature. Novel methods are presented for handling flow reversals and implementing various pressure–flow relationships, along with controlled boundary conditions. Finally, the code contains several innovations designed to improve efficiency and reduce the extensive trial-and-error tuning often required to produce a working PSA cycle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Roadmap on thermodynamics and thermal metamaterials

Thermal metamaterials represent a transformative paradigm in modern physics, synergizing thermodynamic principles with metamaterial engineering to master heat flow at will. As next-generation technologies demand multi-scale thermal control, this field urgently requires systematic frameworks to unify its multidisciplinary advances. Curated through a global collaboration involving over 50 specialists across 25 subdisciplines, this review primarily summarizes two decades of advancements, ranging from theoretical breakthroughs to functional implementations. The review reveals groundbreaking innovations in heat manipulation through the exploration of both classical and non-classical transport regimes, topological thermal control mechanisms, and quantum-informed phonon engineering strategies. By bridging physical insights like non-Hermitian thermal dynamics and valleytronic phonon transport with cutting-edge applications, we demonstrate paradigm-shifting capabilities: environment-adaptive thermal cloaks, AI-optimized metamaterials, and nonlinear thermal circuits enabling heat-based computation. Experimental milestones include 3D thermal null media with reconfigurable invisibility and thermal designs breaking classical conductivity limits. Here, this collaborative effort establishes an indispensable roadmap for physicists, highlighting pathways to quantum thermal management, entropy-controlled energy systems, and topological devices. As thermal metamaterials transition from laboratory marvels to technological cornerstones, this work provides the foundational lexicon and design principles for the coming era of intelligent thermal matter.

heat conduction control↗