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Mechanical and Thermal Forcing for Upslope Flows and Cumulus Convection over the Sierras de Córdoba

Abstract The upslope flow processes affecting the vertical extent of orographic cumulus convection are examined using observations from the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. Specifically, clear air returns from the U.S. Department of Energy (DOE) second-generation C-band scanning Atmospheric Radiation Measurement (ARM) precipitation radar (CSAPR2) are used to characterize the structure and variability of the ridge-normal (i.e., up/downslope) flow components, which transport mass to the crest of Argentina’s Sierras de Córdoba and contribute to convective initiation. Data are compiled for the entire CACTI period (October–April), including days with clear skies, shallow cumuli, cumulus congestus, and deep convection. To examine shared variability among >70 000 radar scans, we use (i) a principal component analysis (PCA) to isolate modes of variability in the upslope flow and (ii) composite analysis based on convective outcomes, determined from GOES-16 satellite observations. These data are contextualized with observed surface sensible heat fluxes, thermodynamic profiles, and synoptic-scale analysis. Results indicate distinct thermally and mechanically forced upslope flow modes, modulated by diurnal heating and synoptic-scale variations, respectively. In some instances, there is a superposition of thermal and mechanical forcing, yielding either deeper or shallower upslope flow. The composite analyses based on satellite data show that successively deeper convective outcomes are associated with successively deeper upslope flow layers that more readily transport mass to the ridge crest in conjunction with lower lifting condensation levels, facilitating convective initiation. These results help to isolate the forcing mechanisms for orographic convection and thus provide a foundation for parameterizing orographic convective processes in coarse resolution models.

Meteorology & Atmospheric Sciences

Complete Demonstration of a Prototype Version of FORCE User Interface and Conduct Analyst Survey Collecting Feedback on Interface Features and Usability

In 2024 the US Department of Energy (DOE) Office of Nuclear Energy (NE) Integrated Energy System (IES) program continued to develop the Framework for Optimization of Resources and Economics (FORCE) analysis ecosystem into a more traditional toolset with simplified software installation, automated workflows, and interactive results visualization. The DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench continued to be leveraged for user input, application workflow and runtime environment, and interactive results visualization capabilities. This report documents the demonstration of a FORCE User Interface (UI) prototype and the results of a survey of analysts’ using the Holistic Energy Resource Optimization Network (HERON) tool in FORCE with the prototype UI.

97 MATHEMATICS AND COMPUTING

Evaluations of Connectors, Inlets, and Adapters on Side-Load and Withstand Force

This report examines the mechanical forces that direct current fast charging (DCFC) electric vehicle supply equipment (EVSE) connectors and electric vehicle (EV) inlet ports experience during normal usage. As we witness the fast and growing variety of EVs, charge port locations, and bigger and more powerful EVSE configurations including the SAE J3400 North American Charging Standard (NACS), which has increased the use of adapters with J3400 and J1772 compatibility. These new conditions contribute to increased mechanical forces due to their size, weight and lever arm effect, which creates the need to study and compare these forces to the limits on UL2251 and IEC 62196-1 standards. This report focuses solely on high power DC charging EVSE connectors, EV inlets and adapters for the specific compatibility cases on J3400 with J1772. We first describe the details of the 100N and the 750N side-load evaluations as described in the standards, then present the data obtained by replicating these tests to finally go into more detail on the findings and our recommendations.

100N

On Transforming the Specific Force Vector for an ECEF Inertial Navigation System

An inertial measurement unit accumulates the instantaneous specific force applied to the sensor over a small window of time. Importantly, this accumulation occurs in the sensor’s frame, yet the specific force must be mathematically integrated in a different navigation frame, and these two frames may be rotating with respect to each other. Consequently, a correction is needed to not only account for the frame difference but also for the time variation in the frame difference. Many references provide derivations of this correction [1], but the derivation is often abbreviated, and important assumptions are sometimes left unstated. This memo addresses this gap and provides a clear derivation of the specific force transform with all assumptions specifically stated. This derivation is specific to the Earth-centered, Earth-fixed navigation frame, but, hopefully, the derivation is sufficiently clear that readers can apply it to other navigation frames. Generally, notation follows the same format as described in both [1, 2].

47 OTHER INSTRUMENTATION

ClimGen: Learning the Forcing-Response Relationship in Climate System

Solar Radiation Management (SRM) is emerging as a potential geoengineering strategy to address the anthropogenic impact on climate, but its effective implementation requires an iterative and large ensemble of highly accurate and efficient climate projections. Traditional climate projections rely on executing computationally demanding and time-consuming numerical climate models. Recent advances in machine learning (ML) aim to enhance these approaches by emulating traditional methods. In this work, we propose a novel framework for directly learning the relationship between solar radiation flux at the top of the atmosphere and the corresponding surface temperature response. To evaluate the feasibility of this direct ML-based projection, we developed a dataset using an intermediate complexity model, incorporating a comprehensive suite of different forcing patterns and evaluation metrics to rigorously assess the ML model’s performance. We introduce a Conditional Denoising Diffusion Probabilistic Model (cDDPM) for this task, which demonstrates encouraging skill in representing climate statistics under previously unseen forcing patterns. This approach provides a promising pathway for direct climate projections by accurately learning the forcing-response relationship, with a wide range of applications in impact mitigation, emissions policy design, and SRM strategies.

Chen, Tse-Chun [BATTELLE (PACIFIC NW LAB)] (ORCID:

Imaging Bias‐Driven Domain Wall Motion With Scanning Oscillator Piezoresponse Force Microscopy

Understanding ferroelectric domain wall dynamics at the nanoscale across a broad range of timescales requires measuring domain wall position under different applied electric fields. The success of piezoresponse force microscopy (PFM) as a tool to apply local electric fields at different positions and imaging their changing position, together with the information obtained from associated switching spectroscopies has fueled numerous studies of the dynamics of ferroelectric domains to determine the impact of intrinsic parameters such as crystalline order, defects and pinning centers, as well as boundary conditions such as environment. However, the investigation of sub-coercive reversible domain wall vibrational modes requires the development of new tools that enable visualizing domain wall motion under varying applied fields with high temporal and spatial resolution while also accounting for spurious electrostatic effects. Here, scanning oscillator piezoresponse force microscopy extends the investigation of domain wall dynamics to new regimes, providing direct visualization of domain wall position as a function of an external electric field that varies in time and location. In conclusion, this enables studying the energetics of field-driven ferroelectric domain wall motion, which is shown to obey a thermally activated flow regime in the millisecond timescale.

Piezoresponse Force Microscopy

Modeling Europium (II/III) ion solvation in the LiCl-KCl eutectic mixture with polarizable force fields

Here, the solvation processes of Europium (II/III) ions within the molten salt eutectic mixture, 3LiCl-2KCl, are investigated over temperatures ranging from 673 K to 1173 K. New polarizable ion force fields are proposed to model Europium ions in a molten salt eutectic mixture with a goal of accurately capturing the underlying physics in the solutions. In contrast to rigid-ion models, the polarizable Drude model with an adjusted WBK (Wang-Buckingham) force field significantly improves predictions for diffusion coefficients, the average diffusion activation energy, and changes in excess ion chemical potential and partial molar entropy, producing good agreement with experimental measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

On forced RF generation of CW magnetrons for accelerators

CW magnetrons, initially developed for industrial RF heaters, were suggested to power RF cavities of superconducting accelerators due to their higher efficiency and lower cost than traditionally used klystrons, IOTs or solid-state amplifiers. RF amplifiers driven by a master oscillator serve as coherent RF sources. CW magnetrons are regenerative RF generators with a huge regenerative gain. This causes regenerative instability with a quite large noise when a magnetron operates with the anode voltage above the threshold of self-excitation. Traditionally, an injection locking by a small signal is used for stabilization of magnetrons. In this case CW magnetrons with the injection-locked oscillations generate a high level of noise. This may preclude use of standard CW magnetrons in this operating mode in the Superconducting RF (SRF) accelerators. In this article we described a method developed for forced RF generation of CW magnetrons when the magnetron startup is provided by the injected forcing signal and the regenerative noise is suppressed. The method is most suitable for powering high Q-factor cavities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

Correlation of Surface Acoustic Wave (SAW) force myography sensor output with elbow joint torque

Accurate assessment of skeletal muscle forces and net joint torque is essential for preventing fatigue-related injuries, optimizing physical training, and monitoring disease progression in neuromuscular conditions. However, existing joint torque evaluation techniques are hindered by limited portability and high operational costs, confining their use to controlled laboratory or clinical settings. Despite substantial advances in wearable joint torque estimation systems, ongoing challenges such as power constraints, bulky wired setups, and susceptibility to environmental or motion artifacts underscore the urgent need for truly batteryless, wireless solutions deployable in real-world settings. This paper proposes a novel surface acoustic wave (SAW)-based force myography (FMG) system for noninvasive measurement of joint torque, validated against a gold-standard electromechanical dynamometer. The approach uses a single SAW sensor embedded in an armband to detect volumetric biceps brachii changes, with a second-order polynomial mapping sensor output and elbow angle to torque. Seven participants were tested in both isometric (15°–90°) and isokinetic (10°/s and 20°/s) supinated elbow flexion tasks. Under isometric conditions, subject-specific calibration achieved a normalized root-mean-square error (NRMSE) of 13.6% ± 6.0% and R 2 = 0.834 ± 0.180, while a group-level model yielded 14.4% ± 6.8% and 0.808 ± 0.208, respectively. For isokinetic trials, the group model produced an NRMSE of 24.1% ± 6.6% at 10°/s and 24.9% ± 08.9% at 20°/s, highlighting the feasibility of using a single-sensor SAW-FMG setup across different speeds. Because SAW devices support wireless, battery-free operation, the proposed system offers a pathway to portable, real-time monitoring for sports medicine, rehabilitation, and clinical diagnostics.

36 MATERIALS SCIENCE

Nanorod Pair Complexes Manipulated via Magnetic Casimir Forces

Here, we demonstrate a route to modulate Casmir–Lifshitz interactions between anisotropic nanoparticles and magnetic fluids. By semiclassical quantum electrodynamics, we study ground state dispersion forces for cylindrical dielectric nanorods made of polystyrene (PS) and zinc oxide (ZnO) embedded in toluene-based host media with gold-coated magnetite nanoparticles and also predict magnetic contributions to the fully retarded excited state interaction. The variation in magnetic permeability enables tuning between repulsive and attractive interactions, and measurable magnetic Casimir traps are predicted between a pair of ZnO–PS nanoparticles whose equilibrium position can be modulated over an order of magnitude with a small variation in the size of the magnetite nanoparticle. This provides an alternative magnetic Casimir-effect pathway to reversibly tune quantum electromagnetic forces at the nanoscale for the assembly and enhancement of colloidal stability.

Excited-state interaction

Defect Self-Elimination in Nanocube Superlattices Through the Interplay of Brownian, van der Waals, and Ligand-Based Forces and Torques

Understanding defect healing is necessary for realizing devices based on nanoparticle-superlattices with controlled electronic and optoelectronic performance. However, key questions remain regarding nanoparticle interactions and resulting assembly dynamics and defect self-elimination. In particular, for anisotropic particles, additional degrees of freedom beyond those of spherical particles, such as rotational dynamics and toques, significantly impact phenomena. Here, in this work, we investigate nanocube (NC) superlattices by employing liquid phase transmission electron microscopy, continuum theories and molecular dynamics simulations. Analyzing interparticle forces and torques due to van der Waals, Brownian, and ligand interactions, we find that the latter dominates and that the anisotropic NC morphology introduces significant torques. In imperfect regions, unbalanced forces and torques induce NC translations and rotations that are transmitted to neighboring NCs, prompting “chain interactions” in a 2D network, which lead to defect self-elimination. This fundamental understanding will further enable design and fabrication of defect-free superlattices, as well as those with tailored defects, via assembly of anisotropic particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

A Transferable Force Field for Predicting Adsorption and Diffusion of Water in Cationic Zeolites with Coupled Cluster Accuracy

We present a transferable force field for water in proton-exchanged, alkali (Li, Na, K, Rb, and Cs) metal-exchanged, and alkaline-earth (Mg, Ca, Sr, and Ba) metal-exchanged zeolites. The fitting methodology is based on adsorbate–adsorbent interaction energies obtained from periodic density functional theory calculations and corrected using the coupled-cluster method applied to small model clusters. To ensure an accurate prediction of both adsorption and diffusion properties of water, sets of configurations that sample both adsorption sites and intracrystalline hopping transition states were used in the fitting. The quality of the force field is assessed for a wide range of zeolites with different topologies and chemical compositions, demonstrating good agreement between theoretical predictions and experimental measurements of water adsorption and diffusion.

Adsorption

Representing Anthropogenic Dust From Agricultural Sources in E3SMv1: Implementation, Evaluation, and Assessment of the Radiative Forcing

Dust emissions related to anthropogenic activities (i.e., anthropogenic dust) is not represented in most global climate models and its radiative impact remains unassessed. In this study, we develop a new and physically based method to parameterize anthropogenic dust emission from agricultural sources (i.e., agricultural dust, or AD) based on the DOE's Energy Exascale Earth System Model version 1 (E3SMv1). This method relates AD emission to the crop land use fraction in the E3SMv1 land component. Major AD sources simulated by our parameterization include those over Central America, the Sahel, North India, and North China. The annual averaged AD emission with diameter less than 10 μm is 567 Tg yr −1 in present-day (year 2000), which contributes to 13.3% of total dust emission. Model evaluation against satellite and ground-based observations shows that the new parameterization can represent AD emissions and global dust cycle reasonably well. We find that the total dust emission increases by 13.1% (495 Tg yr −1 ) from 1850 to 2000 due to the cropland land use fraction changes without considering the impact from climate changes. This induces a net dust direct effective radiative forcing of −0.041 W m −2 at top of the atmosphere. This dust-induced cooling exceeds 10% of the total anthropogenic aerosol direct effective radiative forcing from 1750 to 2014 estimated by the Intergovernmental Panel on Climate Change Sixth Assessment Report. Our findings indicate an important role of anthropogenic dust in global climate change, which should be included in future climate change assessments.

agricultural dust

Updated Results of the Nuclear Accident Dosimetry Intercomparison at the Armed Forces Radiobiology Research Institute’s TRIGA Reactor (IER-602 CED-4a Report)

The IER-602 3b document (Angus, et al. 2024) reported the initial, 24-hour results of the international nuclear accident intercomparison, which took place at the Armed Forces Radiobiological Research Institute during June 24-28, 2024. This report provides updated results and further analysis of the intercomparison.

61 RADIATION PROTECTION AND DOSIMETRY

New electric force and charge exchange modules in discrete element model enables particle dynamics simulation in electric field

Discrete element modeling (DEM) is an important technique for particle dynamics simulation. The field of metal additive manufacturing often utilizes DEM to simulate the rheological behaviors of powder. Standard contact and short-range interactions are sufficient in most cases but insufficient to describe the particle dynamics with the influence of an electric field. Modeling such a system requires additional physics to describe the particle–field interactions. The relevant physics has been experimentally understood but is not yet available in DEM. Here, we develop a charge exchange and an electric force module. The electric force module governs particle response to the electric field, while the charge exchange module enables particles to acquire proper charge during contact with charged geometries. We validate the modules against analytical calculations and high-speed videos of electrostatic powder deposition experiments. Notably, the model struggles to capture the initial particle levitation. We later deploy a modified electric field, as supported by static electric field simulation, to better approximate the electric field penetration into the powder layer. This modification improves the model’s capability of simulating realistic particle levitation. The results highlight the challenges of modeling particle behaviors in the electric field while demonstrating the feasibility of obtaining quantitative results, which are difficult to measure experimentally.

charge exchange

Colloidal phenomena reflect the interplay between interfacial solution structure, interparticle forces, and dynamical response

The physical and chemical properties of colloidal systems are central to both natural and synthetic processes that enable a wide range of energy and environmental applications. These properties are an emergent outcome of the structure that colloidal systems adopt in response to the interplay of electrical, van der Waals, hydration, and steric forces coupled to the inherent fluctuations of the system. Here, in this study, we review the nature of those forces and show how variations in their relative importance lead to distinct free energy landscapes and consequent dynamic behaviors, illustrated for colloidal dispersions, nanocrystal superlattices, and mesocrystlline solids formed through oriented attachment. We end by discussing the challenges to future progress arising from the need to seamless couple from molecular to particle to ensemble scales.

42 ENGINEERING

Unsteady aerodynamic loads on pitching aerofoils represented by Gaussian body force distributions

The actuator line model (ALM) is an approach commonly used to represent lifting and dragging devices like wings and blades in large-eddy simulations (LES). The crux of the ALM is the projection of the actuator point forces onto the LES grid by means of a Gaussian regularisation kernel. The minimum width of the kernel is constrained by the grid size; however, for most practical applications like LES of wind turbines, this value is an order of magnitude larger than the optimal value that maximises accuracy. This discrepancy motivated the development of corrections for the actuator line, which, however, neglect the effect of unsteady spanwise shed vorticity. In this work we develop a model for the impact of spanwise shed vorticity on the unsteady loading of an aerofoil modelled as a Gaussian body force distribution, where the model is applicable within the regime of unsteady attached flow. The model solution is derived both in the time and frequency domain and features an explicit dependence on the Gaussian kernel width. We verify the model with ALM-LES for both pitch steps and periodic pitching. The model solution is compared with Theodorsen theory and validated with both computational fluid dynamics using body fitted grids and experiment. It is concluded that the optimal kernel width for unsteady aerodynamics is approximately 40 % of the chord. The ALM is able to predict the magnitude of the unsteady loading up to a reduced frequency of 𝑘 ≈ 0.2.

17 WIND ENERGY

Nonadiabatic Force Matching for Alchemical Free-Energy Estimation

We propose a method to compute free-energy differences from nonadiabatic alchemical transformations by using flow-based generative models. The method, nonadiabatic force matching, hinges on estimating the dissipation along an alchemical switching process in terms of a nonadiabatic force field that can be learned through stochastic flow matching. The learned field can be used in conjunction with short-time trajectory data to evaluate upper and lower bounds on the alchemical free energy that variationally converge to the exact value if the field is optimal. Applying the method to evaluate the alchemical free energy of atomistic models shows that it can substantially reduce the simulation cost of a free-energy estimate at a negligible loss of accuracy when compared with thermodynamic integration.

Computational chemistry