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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 577 records · Page 32

Uranium(III)-carbon multiple bonding supported by arene δ-bonding in mixed-valence hexauranium nanometre-scale rings

Despite the fact that non-aqueous uranium chemistry is over 60 years old, most polarised-covalent uranium-element multiple bonds involve formal uranium oxidation states IV, V, and VI. The paucity of uranium(III) congeners is because, in common with metal-ligand multiple bonding generally, such linkages involve strongly donating, charge-loaded ligands that bind best to electron-poor metals and inherently promote disproportionation of uranium(III). Here, we report the synthesis of hexauranium-methanediide nanometre-scale rings. Combined experimental and computational studies suggest overall the presence of formal uranium(III) and (IV) ions, though electron delocalisation in this Kramers system cannot be definitively ruled out, and the resulting polarised-covalent U = C bonds are supported by iodide and δ-bonded arene bridges. The arenes provide reservoirs that accommodate charge, thus avoiding inter-electronic repulsion that would destabilise these low oxidation state metal-ligand multiple bonds. Using arenes as electronic buffers could constitute a general synthetic strategy by which to stabilise otherwise inherently unstable metal-ligand linkages.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Deep Reinforcement Learning for Distribution System Restoration Using Distributed Energy Resources and Tie-Switches

Distributed energy resources (DERs), such as solar PVs and energy storage, can be used to restore distribution system critical loads after the extreme weather events to increase grid resilience. However, coordinating multiple DERs together with tie-switches for multi-step restoration process under renewable uncertainty is challenging. This paper proposes a deep reinforcement learning to control discrete actions of switching on/off tie switches and DERs for critical load restoration. The restoration problem is first cast into the Markov decision process suitable for DRL. Then, the original soft actor critic (SAC) method for continuous actions has been extended to handle discrete and continuous actions. Numerical comparison results with other stochastic optimization-based approaches on the modified IEEE 33-bus system show that the proposed method can achieve fast critical load restoration in the presence of substation power outage while maintaining system voltage limit throughout the restoration process.

active distribution systems↗

Targeted brain proteomics uncover multiple pathways to Alzheimer's dementia

Objective Previous gene expression analysis identified a network of coexpressed genes that is associated with β‐amyloid neuropathology and cognitive decline in older adults. The current work targeted influential genes in this network with quantitative proteomics to identify potential novel therapeutic targets. Methods Data came from 834 community‐based older persons who were followed annually, died, and underwent brain autopsy. Uniform structured postmortem evaluations assessed the burden of β‐amyloid and other common age‐related neuropathologies. Selected reaction monitoring quantified cortical protein abundance of 12 genes prioritized from a molecular network of aging human brain that is implicated in Alzheimer's dementia. Regression and linear mixed models examined the protein associations with β‐amyloid load and other neuropathological indices as well as cognitive decline over multiple years preceding death. Results Average age at death was 88.6 years. Overall, 349 participants (41.9%) had Alzheimer's dementia at death. A higher level of PLXNB1 abundance was associated with more β‐amyloid load ( p = 1.0 × 10 −7 ) and higher PHFtau tangle density ( p = 2.3 × 10 −7 ), and the association of PLXNB1 with cognitive decline is mediated by these known Alzheimer's disease pathologies. On the other hand, higher IGFBP5, HSPB2, and AK4 and lower ITPK1 levels were associated with faster cognitive decline, and, unlike PLXNB1, these associations were not fully explained by common neuropathological indices, suggesting novel mechanisms leading to cognitive decline. Interpretation Using targeted proteomics, this work identified cortical proteins involved in Alzheimer's dementia and begins to dissect two different molecular pathways: one affecting β‐amyloid deposition and another affecting resilience without a known pathological footprint. Ann Neurol 2018;83:78–88

Yu, Lei↗

Performance and Application of Parallel OVERFLOW Codes on Distributed and Shared Memory Platforms

The presentation discusses recent studies on the performance of the two parallel versions of the aerodynamics CFD code, OVERFLOW_MPI and _MLP. Developed at NASA Ames, the serial version, OVERFLOW, is a multidimensional Navier-Stokes flow solver based on overset (Chimera) grid technology. The code has recently been parallelized in two ways. One is based on the explicit message-passing interface (MPI) across processors and uses the _MPI communication package. This approach is primarily suited for distributed memory systems and workstation clusters. The second, termed the multi-level parallel (MLP) method, is simple and uses shared memory for all communications. The _MLP code is suitable on distributed-shared memory systems. For both methods, the message passing takes place across the processors or processes at the advancement of each time step. This procedure is, in effect, the Chimera boundary conditions update, which is done in an explicit "Jacobi" style. In contrast, the update in the serial code is done in more of the "Gauss-Sidel" fashion. The programming efforts for the _MPI code is more complicated than for the _MLP code; the former requires modification of the outer and some inner shells of the serial code, whereas the latter focuses only on the outer shell of the code. The _MPI version offers a great deal of flexibility in distributing grid zones across a specified number of processors in order to achieve load balancing. The approach is capable of partitioning zones across multiple processors or sending each zone and/or cluster of several zones into a single processor. The message passing across the processors consists of Chimera boundary and/or an overlap of "halo" boundary points for each partitioned zone. The MLP version is a new coarse-grain parallel concept at the zonal and intra-zonal levels. A grouping strategy is used to distribute zones into several groups forming sub-processes which will run in parallel. The total volume of grid points in each group are approximately balanced. A proper number of threads are initially allocated to each group, and in subsequent iterations during the run-time, the number of threads are adjusted to achieve load balancing across the processes. Each process exploits the multitasking directives already established in Overflow.

Djomehri, M. Jahed↗

A Mixed integer linear programming‐based distributed energy management for networked microgrids considering network operational objectives and constraints

Abstract Mixed integer linear programming (MILP)–based distributed energy management for networked microgrids embedded modern distribution systems is proposed. Considering the diverse ownership of microgrids, distributed energy resources (DERs) that interface directly with utilities and responsive loads, an alternating direction method of multipliers–based distributed framework was formulated for the scheduling of networked microgrids embedded modern distribution systems by adjusting nodal price signals iteratively. In addition, to make the formulated optimization problems resolvable through more accessible and popular MILP solvers, different linearisation techniques were employed to transform the nonlinear terms into linear or mixed integer linear formats. The proposed MILP‐based distributed method preserves all participants' autonomy (e.g., microgrids, DERs that interface directly with utilities and responsive loads), while incentivising them to actively participate in the distribution system operation with price signals. The proposed method is validated with results of numerical simulation using a modern distribution system consisting of multiple networked microgrids, DERs that interface directly with utilities, as well as responsive loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DESIGN OF A THIRD HARMONIC CAVITY WITH LOW R/Q FOR THE ESR IN BNL EIC

For the electron Storage Ring (ESR) of Brookhaven Na-tional Lab Electron Ion Collider (BNL EIC), beam loading is a great concern due to the high beam current together with abortion gap, especially for harmonic cavities due to higher operational frequency. There were attempts to use feedback/feedforward control, using multiple cavities with counter-phasing [1]. A straightforward way to lower beam loading effect is to design a cavity with low R/Q. In this paper, we show such a design for the 3rd harmonic cavity for BNL EIC ESR.

43 PARTICLE ACCELERATORS↗

HOM DAMPER DESIGN FOR BNL EIC 197MHZ CRAB CAVITY

For the electron Storage Ring (ESR) of Brookhaven Na-tional Lab Electron Ion Collider (BNL EIC), beam loading is a great concern due to the high beam current together with abortion gap, especially for harmonic cavities due to higher operational frequency. There were attempts to use feedback/feedforward control, using multiple cavities with counter-phasing [1]. A straightforward way to lower beam loading effect is to design a cavity with low R/Q. In this paper, we show such a design for the 3rd harmonic cavity for BNL EIC ESR.

43 PARTICLE ACCELERATORS↗

System tests with electric thruster beam and accelerator directly powered from laboratory solar arrays

Laboratory high voltage solar arrays were operated directly connected to power the beam and accelerator loads of an 8-centimeter ion thruster. The beam array comprised conventional 2 by 2 centimeter solar cells; the accelerator array comprised multiple junction edge-illuminated solar cells. Conventional laboratory power supplies powered the thruster's other loads. Tests were made to evaluate thruster performance and to investigate possible electrical interactions between the solar arrays and the thruster. Thruster performance was the same as with conventional laboratory beam and accelerator power supplies. Most of the thruster beam short circuits that occurred during solar array operation were cleared spontaneously without automatic or manual intervention. No spontaneous clearing occurred during conventional power supply operation.

Stover, J. B.↗

Correlation of Canopy Distortion with Asymmetric Loading in Large Diameter Ringsail Parachutes

The second generation of the main parachutes for the Orion Capsule Parachute Assembly System (CPAS) were subjected to multiple flight tests. Three of the tests included were instrumented with the Tension Measuring System (TMS) to record main dispersion bridle loads. While these units were not able to resolve the individual suspension line loads, they were able to record a course representation of the asymmetric loading of the main parachutes during inflation. These tests were also equipped with upward looking cameras mounted on the test vehicles to collect detailed imagery of main deployment and inflation. When analyzed independently, both data sources exhibit similar features. These similarities provide evidence that the suspension line loads and the distortions in the canopy geometry are not independent. This paper will examine both data sources simultaneously to establish a correlation between asymmetric loading at the canopy skirt and the deformations of the canopy. This correlation will be used to build a model which can estimate individual suspension line loads from a measured riser load and detailed imagery.

Parachutes↗

Mechanical Modeling and Testing of Pouch Cells under Various Loading Conditions

Understanding the mechanical behaviors of batteries is critical to improve battery safety since mechanical failure may directly lead to short-circuits. Nevertheless, mechanical modeling of batteries is challenging since a cell usually contains multiple thin layers with drastically different material properties, and they exhibit different responses under different loading conditions. In this work, we developed a mechanical model for a large-format pouch cell, where the cell is represented by thick shell elements that are not only computationally efficient but also account for different thickness and material properties of individual components. Moreover, the mechanical properties of active materials in electrodes are described by a continuous surface cap model that can capture both compaction and shear deformation modes and can include strain rate effect and damage. Furthermore, to evaluate the model capabilities, we conducted abuse tests under various loading conditions (quasi-static compression, shear and impact). It is shown that the model prediction of load-displacement relationship and failure condition agree with experimental results, which demonstrates that the developed model can capture the mechanical behaviors of a cell in different abuse events. Details of element formulation, material parameters evaluation and test setup are presented. Capabilities, limitations and future directions of model development are also discussed.

25 ENERGY STORAGE↗

AMICE2 measurements of lab-generated and ambient aerosols at BNL from 2025-07-21 to 2025-08-22

From July 21 through August 22, 2025 the Absorption Measurement Inter-Comparison Experiment phase 2 (AMICE2) was conducted at Brookhaven National Laboratory. The experiment included concurrent operation of several filter-based instruments and in situ instruments sampling from a common sample line. The common sample line provided all instruments with either lab-generated aerosols composed of external mixtures of nigrosin, cabojet, and ammonium sulfate, or with ambient aerosol drawn through an external stack. This data set contains measurements from the CAPS PMssa instrument taken as a reference instrument at 532 nm and against which the effectiveness of the filter corrections may be assessed. It also contains attenuation coefficients from all filter-based instruments and filter transmittances in order to permit correction for filter loading, and the SSA and COA to permit corrections for aerosol darkness. Finally, two sets of multiplicative corrections are provided for the AE-33, TAP, and MA-350 instruments: the first one, Corr1, corrects for filter amplification factor and loading, the second one, Corr2, corrects for the aerosol darkness in terms of the natural log of COA.

Aerosol Extinction↗

Durability/life of fiber composites in hygrothermomechanical environments

Statistical analysis and multiple regression were used to determine and quantify the significant hygrothermomechanical variables which infuence the tensile durability/life (cycle loading, fatigue) of boron-fiber/epoxy-matrix (B/E) and high-modulus-fiber/epoxy-matrix (HMS/E) composites. The use of the multiple regression analysis reduced the variables from fifteen, assumed initially, to six or less with a probability of greater than 0.999. The reduced variables were used to derive predictive models for compression an intralaminar shear durability/life of B/E and HMS/E composites assuming isoparametric fatigue behavior. The predictive models were subsequently generalized to predict the durability/life of graphite-fiber-r generalized model is of simple form, predicts conservative values compared with measured data and should be adequate for use in preliminary designs.

Chamis, C. C.↗

Durability/life of fiber composites in hygrothermomechanical environments

Statistical analysis and multiple regression were used to determine and quantify the significant hygrothermomechanical variables which influence the tensile durability/life (cycle loading, fatigue) of boron-fiber/epoxy-matrix (B/E) and high-modulus-fiber/epoxy-matrix (HMS/E) composites. The use of the multiple regression analysis reduced the variables from fifteen, assumed initially, to six or less with a probability of greater than 0.999. The reduced variables were used to derive predictive models for compression and intralaminar shear durability/life of B/E and HMS/E composites assuming isoparametric fatigue behavior. The predictive models were subsequently generalized to predict the durability/life of graphite/fiber-r generalized model is of simple form, predicts conservative values compared with measured data and should be adequate for use in preliminary designs. Previously announced in STAR as N82-14287

Chamis, C. C.↗

Multiple cooperating manipulators: The case of kinematically redundant arms

Existing work concerning two or more manipulators simultaneously grasping and transferring a common load is continued and extended. Specifically considered is the case of one or more arms being kinematically redundant. Some existing results in the modeling and control of single redundant arms and multiple manipulators are reviewed. The cooperating situation is modeled in terms of a set of coordinates representing object motion and internal object squeezing. Nominal trajectories in these coordinates are produced via actuator load distribution algorithms introduced previously. A controller is developed to track these desired object trajectories while making use of the kinematic redundancy to additionally aid the cooperation and coordination of the system. It is shown how the existence of kinematic redundancy within the system may be used to enhance the degree of cooperation achievable.

Walker, Ian D.↗

Restoring Distribution System Under Renewable Uncertainty Using Reinforcement Learning

Distributed energy resources (DERs) in distribution systems, including renewable generation, micro-turbine, and energy storage, can be used to restore critical loads following extreme events to increase grid resiliency. However, properly coordinating multiple DERs in the system for multi-step restoration process under renewable uncertainty and fuel availability is a complicated sequential optimal control problem. Due to its capability to handle system non-linearity and uncertainty, reinforcement learning (RL) stands out as a potentially powerful candidate in solving complex sequential control problems. Moreover, the offline training of RL provides excellent action readiness during online operation, making it suitable to problems such as load restoration, where in-time, correct and coordinated actions are needed. In this study, a distribution system prioritized load restoration based on a simplified single-bus system is studied: with imperfect renewable generation forecast, the performance of an RL controller is compared with that of a deterministic model predictive control (MPC). Our experiment results show that the RL controller is able to learn from experience, adapt to the imperfect forecast information and provide a more reliable restoration process when compared with the baseline controller.

61 RADIATION PROTECTION AND DOSIMETRY↗

Restoring Distribution System Under Renewable Uncertainty Using Reinforcement Learning: Preprint

Distributed energy resources (DER) in distribution systems, including renewable generation, micro-turbine, and energy storage, can be used to restore critical loads following extreme events to increase grid resiliency. However, properly coordinating multiple DERs in the system for multi-step restoration process under renewable uncertainty and fuel availability is a complicated sequential optimal control problem. Due to its capability to handle system non-linearity and uncertainty, reinforcement learning (RL) stands out as a potentially powerful candidate in solving complex sequential control problems. Moreover, the offline training of RL provides excellent action readiness during online operation, making it suitable to problems such as load restoration, where in-time, correct and coordinated actions are needed. In this study, a distribution system prioritized load restoration based on a simplified single-bus system is studied: with imperfect renewable generation forecast, the performance of an RL controller is compared with that of a deterministic model predictive control (MPC). Our experiment results show that the RL controller is able to learn from experience, adapt to the imperfect forecast information and provide a more reliable restoration process when compared with the baseline MPC controller.

61 RADIATION PROTECTION AND DOSIMETRY↗

Restoring Distribution System Under Renewable Uncertainty Using Reinforcement Learning

Distributed energy resources (DER) in distribution systems, including renewable generation, micro-turbine, and energy storage, can be used to restore critical loads following extreme events to increase grid resiliency. However, properly coordinating multiple DERs in the system for multi-step restoration process under renewable uncertainty and fuel availability is a complicated sequential optimal control problem. Due to its capability to handle system non-linearity and uncertainty, reinforcement learning (RL) stands out as a potentially powerful candidate in solving complex sequential control problems. Moreover, the offline training of RL provides excellent action readiness during online operation, making it suitable to problems such as load restoration, where in-time, correct and coordinated actions are needed. In this study, a distribution system prioritized load restoration based on a simplified single-bus system is studied: with imperfect renewable generation forecast, the performance of an RL controller is compared with that of a deterministic model predictive control (MPC). Our experiment results show that the RL controller is able to learn from experience, adapt to the imperfect forecast information and provide a more reliable restoration process when compared with the baseline MPC controller.

61 RADIATION PROTECTION AND DOSIMETRY↗

Wind Farm Wakes and Farm-to-Farm Interactions: Lidar and Wind Tunnel Tests

Recent experimental and numerical evidence has shown that the cumulative wake generated from the overlapping of multiple wakes within a wind farm could reduce power performance and enhance fatigue loads of wind turbines installed in neighboring downstream wind farms and may also extend up to distances one order of magnitude larger than those typically considered for intra-farm wake interactions. Similar to individual wind turbine wakes, wind farm wakes have a velocity deficit and added turbulence intensity, both affected by the turbine rotor thrust forces and the incoming turbulence intensity. Therefore, the evolution of wind farm wakes will vary for different operational and atmospheric conditions. In this paper, lidar measurements collected during the American WAKE experimeNt (AWAKEN) and wind tunnel tests of wind farms reproduced by porous disks are leveraged to investigate wind farm wakes.

17 WIND ENERGY↗