Oxidative Electrochemical Coupling Between Bi and Mn in Rechargeable Alkaline MnO2 Cathodes
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The results of the ATS-5 solar cell experiment after one year in synchronous orbit are reported. A partial failure in the experimental electronics package has caused a loss of data from half the 80 experimental solar cells. Procedures for extracting data due to a partial spacecraft failure are described and discussed. Data from the remaining 40 solar cells, including 15 mounted on a thin flexible structure are analyzed. Data are corrected to a solar intensity of 140 mW/sq cm and a temperature of 25 C. It was found that after one year in synchronous orbit: (1) cells with 1.52-mm-thick coverslides did not show a clear-cut advantage over those with 0.15-mm coverslides, (2) cells with solderless grid lines are degrading at the same rate as are cells with solder-dipped grid lines, (3) cells not quite completely covered with coverslides suffered a large power loss in comparison to cells fully covered, (4) no clear-cut advantage of 10-cm cells over 2-cm cells has yet been observed, (5) cells mounted on the flexible panel with relatively little backshielding did not degrade any faster than those with substantial backshielding, and (6) the flight data in large part confirms the adequacy of the ground-based techniques used in our preflight radiation test program.
Metal organic frameworks (MOFs) are porous crystalline materials that display a wide variety of physical and chemical properties. Their single crystal structure determination is often challenging because in most cases micro- or nano-sized crystals spontaneously form upon MOF synthesis, which cannot be recrystallized. The production of larger single crystals for structure determination involves optimizing, and thus modifying, the conditions of synthesis, in which success cannot be guaranteed. Failure to produce crystals suitable for single-crystal X-ray diffraction leaves the 3D structure of the MOF compound unknown, and scientists must resort to more challenging structure solution methods based on X-ray powder or electron diffraction data. These laborious tasks can be avoided by using serial crystallography techniques which merge data collected on many micro-crystals. Here, we report the application of three synchrotron serial crystallography methods. We call these “mesh”, “grid” and “mesh&collect” scans. “Still” images (no rotation) are collected in the mesh scan approach, whereas small rotational wedges are collected in the grid scan method. The third protocol, mesh&collect, combines the acquisition of still images and rotational wedges. Using these means, we determine the ab initio structure of benchmark MOFs, MIL-100(Fe) and ZIF-8, that differ largely in unit cell size. These methods are expected to be widely applicable and facilitate structure determination of many MOF microcrystalline systems.
Integrated energy systems (IESs) seek to minimize power generating costs in future power grids through the coupling of different energy technologies. To accommodate fluctuations in load demand due to the penetration of renewable energy sources, flexible operation capabilities must be fully exploited, and even power plants that are traditionally considered as base-load units need to be operated according to unconventional paradigms. Thermomechanical loads induced by frequent power adjustments can accelerate the wear and tear. If a unit is flexibly operated without respecting limits on materials, the risk of failures of expensive components will eventually increase, nullifying the additional profits ensured by flexible operation. In addition to the bounds on power variations (explicit constraints),the solution of the unit dispatch problem needs to meet the limits on the variation of key process variables, including temperature, pressure and flow rate (implicit constraints).The FARM (Feasible Actuator Range Modifier) module was developed to enable existing optimization algorithms to identify solutions to the unit dispatch problem that are both economically favorable and technologically sustainable. Thanks to the iterative dispatcher–validator scheme, FARM permits addressing all the imposed constraints without excessively increasing the computational costs. In this work, the algorithms constituting the module are described, and the performance was assessed by solving the unit dispatch problem for an IES composed of three units, i.e., balance of plant, gas turbine, and high-temperature steam electrolysis. Finally, the FARM module provides dedicated tools for visualizing the response of the constrained variables of interest during operational transients and a tool aiding the operator at making decisions. These techniques might represent the first step towards the deployment of an ecological interface design (EID) for IES units.
The Voyager Plasma Science (PLS) instrument is capable of returning integral (DC) current measurements, similar in some respects to measurements made with a Langmuir probe or a retarding potential analyzer, although there are significant differences. The integral measurements were made during a calibration sequence in the solar wind, during Cruise Science Maneuvers, and within the magnetospheres of Jupiter and Saturn by Voyager 1. After the failure of the PLS experiment following the Saturn encounter, that instrument was placed in the DC return mode returning possibly usable data from early 1981 through early 1985. The DC return measurements are difficult to interpret and are above threshold values only for relatively large fluxes; the determination of the measured current level is dependent on the operating temperature of the preamplifiers which further complicates the interpretation. Nevertheless, these measurements can be used to determine the efficiency of the suppressor grid at preventing the loss of secondary electrons off the collector plate. Some DC return measurements have been invaluable in aiding in the interpretation of some electron plasma measurements not previously understood. It is found that electron spectra can be significantly modified by the presence of second generation secondary electrons produced by either first generation secondaries or photoelectrons on the support ring of the negative high voltage modulator grid within the instrument housing.
The ePIC collaboration is realizing the first experiment of the future Electron-Ion Collider (EIC) at the Brookhaven National Laboratory that will allow for a precision study of the nucleons and the nucleus at the scale of sea quarks and gluons through the study of electron-proton/ion collisions. This paper will discuss the current workflow for running centralized simulation campaigns for ePIC on the Open Science Grid (OSG) infrastructure. This involves monthly releases of ePIC software and container deployments to CVMFS, generation of input datasets in HepMC format according to collaboration-defined policy, using Snakemake in CI/CD for validation and benchmarking, and submitting jobs to the OSG condor scheduler for opportunistic running on available resources. File transfers utilize XrootD, and Rucio is used for data management. The workflow is continuously refined to improve daily throughput (currently 50-100k core hours per day) and minimize job failures. Since May 2023, monthly simulation campaigns employing the workflow have cumulatively used over 20 million core hours on the OSG and produced over 350 TB of simulation data. The campaigns incorporate simulations for the broad science program of the EIC and are actively used for the detector and physics studies in preparation of the Technical Design Report (TDR).
This report documents the design and evaluation of an integrated online-learning pipeline developed within the AdCyDER project for Distributed Energy Resource (DER) cybersecurity. The pipeline couples a Reinforcement Learning (RL) attack classifier — which produces an attack-type probability distribution — with a Stackelberg game-theoretic (GT) defense selector that consumes those distributions alongside SME-encoded priors over (defense, attack) effectiveness pairings and perdefense costs to choose grid-health-preserving defenses. The objective is not attack classification per se but production of distributions that drive effective defense selection through the Stackelberg layer, learned from delayed grid-health feedback rather than labeled attack data. AdCyDER as a whole is broader than the work presented here; this report covers the specific RL/GT loop integration and its evaluation. We present the integrated pipeline (SCADA telemetry with Fronius inverter physics, Suricata IDS, time-windowed aggregation, per-facility LSTM classifier, Stackelberg optimizer, OpenC2 actuators), an experimental campaign of 28 eight-hour iterations across three baseline modes, and a pipeline-ordered diagnostic protocol. The protocol identifies two distinct failure modes within the loop: paired supervised ceilings on the same features establish that the deployed online RL classifier (macro F1 ≈ 0.07) sits at least 4.7× below a same-architecture supervised LSTM (≈ 0.34) and 10–11× below a linear feature-signal ceiling (≈ 0.70–0.79 depending on per-facility isolation), localizing the dominant failure to the training procedure; and the reward signal driving online updates carries weak directional coupling with classifier correctness in the methodology-expected direction (multi-lens convergent: top-decile P(true) records produce more frequent state changes and slightly larger improvements, top-vs-bot Cohen’s 𝑑 ≈ −0.19), but at effect magnitudes too small to drive gradient-based learning at the campaign sample size. The original learning hypothesis is not supported by the data. The primary contributions are the diagnostic methodology — proposed as a transferable falsification protocol for online RL/GT defense pipelines learning from delayed environmental reward — and the open, reproducible experimental infrastructure. We outline reward reformulation as the highest-priority aspirational next step given the underpowered-but-aligned Q6 reading, with hardware-in-the-loop evaluation as the broadest scope-expansion option.
This study compared random and t-way combinatorial inputs of a network simulator, to determine if these two approaches produce significantly different deadlock detection for varying network configurations. Modeling deadlock detection is important for analyzing configuration changes that could inadvertently degrade network operations, or to determine modifications that could be made by attackers to deliberately induce deadlock. Discrete event simulation of a network may be conducted using random generation, of inputs. In this study, we compare random with combinatorial generation of inputs. Combinatorial (or t-way) testing requires every combination of any t parameter values to be covered by at least one test. Combinatorial methods can be highly effective because empirical data suggest that nearly all failures involve the interaction of a small number of parameters (1 to 6). Thus, for example, if all deadlocks involve at most 5-way interactions between n parameters, then exhaustive testing of all n-way interactions adds no additional information that would not be obtained by testing all 5-way interactions. While the maximum degree of interaction between parameters involved in the deadlocks clearly cannot be known in advance, covering all t-way interactions may be more efficient than using random generation of inputs. In this study we tested this hypothesis for t = 2, 3, and 4 for deadlock detection in a network simulation. Achieving the same degree of coverage provided by 4-way tests would have required approximately 3.2 times as many random tests; thus combinatorial methods were more efficient for detecting deadlocks involving a higher degree of interactions. The paper reviews explanations for these results and implications for modeling and simulation.
Structural health monitoring (SHM) has the capacity to reduce failure by detecting damage during service life, by periodic, automated monitoring. Guided Wave (GW) Ultrasound is a common SHM approach for aerospace structures. Modelling the physics of GW SHM systems provides a route for understanding system dependencies, capabilities and limitations as damage evolves during service life. Such a toolset can strengthen the understanding of the connection between GW SHM results and the true material state. The most useful modelling tools are those that provide versatile solutions with respect to the simulated component geometry and computational grid connectivity. This work details a versatile application programming interface (API) for the elastodynamic finite integration technique for modelling GW SHM of metals. The custom code implementation, EFIT-CompCell, allows for the modelling of diverse geometries by automatically balancing the message passing interface parallelization layout. The user provides the basic parameters of the simulation and the software automatically performs an initial balancing based on anticipated computational loads, and establishes the CPU communication patterns for any geometry. This work describes the programming philosophy and code structure used to create EFIT-CompCell and compares its performance and capacity to simulation tools that are more specialized for specific architectures. Results are presented for a simulation of GW SHM of an aluminum fuselage section being tested by the FAA. The simulation consists of 733M voxels which took approximately 70 hours to complete 25000 time steps using 40 Intel Xeon E5-4650v2 Ivy Bridge processor cores.
Traditionally, it is assumed that microgrids transition seamlessly from grid‐connected operation to islanded mode in the event of sudden main grid outages. In reality, the islanding process, especially unintentional islanding, is rarely seamless. Instead, it is subject to voltage and frequency fluctuations caused by the instantaneous disconnection of the point of common coupling (PCC) switch, variations in loads and renewable generation output and even the protection tripping of distributed energy resources (DERs). To mitigate these fluctuations and facilitate a smooth islanding process, we propose a stochastic microgrid scheduling model that incorporates chance‐constrained resilience measures. Specifically, the resilience measure is defined as the probability of successful islanding (PSI), that is, the probability that a microgrid can mitigate the generation‐demand imbalance caused by the disconnection of the PCC switch, variations in load and renewable generation and DER tripping. This measure is modelled using chance constraints. Unlike existing reliability and resilience indices, which typically neglect the possibility of microgrid/DER failure under extreme events and assume their survival while primarily focussing on reducing impact duration or magnitude, the proposed PSI‐based framework explicitly addresses microgrid and DER survival during the islanding transition. The formulated nonlinear chance constraints are approximated using a multiinterval approach and equivalently represented as a mixed‐integer linear programming (MILP) formulation. Case study results validate the proposed method, showing that the PSI estimation error is reduced to less than 8%, compared to approximately 28% with existing methods. Various sensitivity analyses on the DER tripping rate and PSI settings were performed to validate the robustness of the proposed method. In particular, the necessity of accounting for DER tripping in the PSI calculation was demonstrated.
The Composite Infrared Spectrometer (CIRS) of the Cassini mission to Saturn has two interferometers covering the far infrared FIR and mid infrared, MIR wavelength region. The FIR is a polarizing Michelson interferometer which presents a collimated output beam to the FIR focal plane. The focal plane consists of a parabolic focus mirror and an analyzer grid, which splits the output beams into transmitted and reflected components. The two polarizations are focussed onto two thermopile detectors; each consisting of a gold black foil welded to the top of two bismuth pyramids. The gold black is 30 microns thick, and the weld area is approximately 2 microns in diameter. The detectors are extremely fragile and the weld can be broken with a miniscule amount of airflow. The detectors consistently passed acoustic testing to qualification levels that simulated the launch environment of the Titan IV launch vehicle. However, they experienced a 50% failure rate when installed in the focal plane assembly during instrument level acoustic tests. A test focal plane was developed with small pressure transducers in the nominal detector locations. These tests indicated over 10 dB of acoustic amplification in the focal plane within the instrument during testing. New techniques were developed to allow testing of the focal plane without over testing the instrument, and modifications were made the focal plane assembly to successfully attenuate the amplification.
The Grid Visualization Tool (GVT) is a computer program for displaying the path of a mobile robotic explorer (rover) on a terrain map. The GVT reads a map-data file in either portable graymap (PGM) or portable pixmap (PPM) format, representing a gray-scale or color map image, respectively. The GVT also accepts input from path-planning and activity-planning software. From these inputs, the GVT generates a map overlaid with one or more rover path(s), waypoints, locations of targets to be explored, and/or target-status information (indicating success or failure in exploring each target). The display can also indicate different types of paths or path segments, such as the path actually traveled versus a planned path or the path traveled to the present position versus planned future movement along a path. The program provides for updating of the display in real time to facilitate visualization of progress. The size of the display and the map scale can be changed as desired by the user. The GVT was written in the C++ language using the Open Graphics Library (OpenGL) software. It has been compiled for both Sun Solaris and Linux operating systems.
This project developed a framework for asset and system risk management that can be incorporated into current electricity system operations to improve economic efficiency and establish an Electric Assets Risk Bureau. We leveraged scoring and ratings from banking and financial institutions alongside current optimization methods in dispatching power systems to help system operators and electricity markets schedule resources. This approach is based on the observation that there are major discrepancies between the power scheduled by a system operator and the actual power generated/consumed. These discrepancies—exacerbated by unplanned contingencies (e.g., natural disasters)—are caused by multiple factors, including the different financial, environmental and risk preferences of power producers, consumers, and aggregators. We developed a framework that counteracts two failures in electricity system operations: imperfect information and missing markets for products. The technical approach included five tasks. Tasks 1 and 2 supported the development of risk scores at the asset level with historical data collected for this project. Tasks 3, 4, and 5 incorporated scoring into decision-making at the system level. The proposed effort achieved PERFORM's Program Objectives because the proposed outputs and algorithms do not exist in the electricity industry and are an innovative approach to managing risk. Since the acknowledged need to better assess and act upon risk profiles for grid assets has not been met by the industry, this project will also impact ARPA-E's Mission Areas, including improving energy efficiency and giving the U.S. a technological lead in advanced energy technologies.
In the last decade, the realization of small, inexpensive, and powerful devices with sensors, computers, and wireless communication has promised the development of massive sized sensor networks with dense deployments over large areas capable of high fidelity situational assessments. However, most management models have been based on centralized control and research has concentrated on methods for passing data from sensor devices to the central controller. Most implementations have been small but, as it is not scalable, this methodology is insufficient for massive deployments. Here, a specific application of a large sensor network for adaptive noise reduction demonstrates a new paradigm where communities of sensor/computer devices assess local conditions and make local decisions from which emerges a global behaviour. This approach obviates many of the problems of centralized control as it is not prone to single point of failure and is more scalable, efficient, robust, and fault tolerant
The flow field in the region of a solid rocket motor field joint is very important since fluid dynamic and mechanical propellant stresses can couple to cause a motor failure at a joint. Presented here is an examination of the flow field in the region of the Advanced Solid Rocket Motor (ASRM) field joints. The analyses were performed as a first step in assessing the design of the ASRM forward and aft field joints in order to assure the proper operation of the motor prior to further development of test firing. The analyses presented here were performed by employing a two-dimensional axisymmetric assumption. Fluent/BFC, a three dimensional full Navier-Stokes flow field code, was used to make the numerical calculations. This code utilizes a staggered grid formulation along with the SIMPLER numerical algorithm. Wall functions are used to determine the character of the laminar sublayer, and a standard kappa-epsilon turbulence model is used to close the fluid dynamic equations. The analyses performed to this date verify that the ASRM field joint design operates properly. The fluid dynamic stresses at the field joints are small due to the inherent design of the field joints. A problem observed in some other solid rocket motors is that large fluid dynamic stresses are generated at the motor joint on the downstream propellant grain due to forward facing step geometries. The design of the ASRM field joints are such that this is not a problem as shown by the analyses. Also, the analyses of the inhibitor stub left protruding into the port flow from normal propellant burn back show that more information is necessary to complete these analyses. These analyses were performed as parametric analyses in relation to the height of the inhibitor stub left protruding into the motor port. A better estimate of the amount of the inhibitor stub remaining at later burn times must be determined since the height which the inhibitor stub protrudes into the port flow drastically affects the fluid dynamics induced stresses on the propellant grain at the field joints.
Volt-VAR control (VVC) methods based on deep reinforcement learning (DRL) can effectively control distribution grid voltage and minimize power loss by implementing corrective and preventive control measures on the reactive power output of inverter-based distributed energy resources (DERs). However, model-free DRL-based VVC approaches usually cannot capture the important topological feature of the power system since they use a fully-connected network (FCN) to deliver the action. Therefore, this paper proposes a graph convolutional network (GCN)-based DRL approach that can employ the topological information of the network to take better control action for regulating the voltage. Our implementation allows for both centralized and decentralized configurations, utilizing a single agent and multiple agents respectively. Although the centralized GCN-based DRL approach has its advantages of minimizing voltage fluctuation and power loss, it is not suitable for large scale power systems due to its challenges in terms of scalability, computation speed and potential single points of failure. Therefore, these problems can be resolved using the decentralized GCN-based DRL approach. Moreover, to ensure the safe operation of the model, our proposed approach incorporates an exponential barrier function while formulating the reward function for each agent. To validate performance of the proposed approaches, the proposed model is tested on modified IEEE test systems and the performances are measured in terms on voltage fluctuation reduction, minimization of power loss and computational speed. Finally, the results show that the proposed topology-aware approach outperforms the FCN-based DRL approach in terms of reducing voltage fluctuation and minimizing power loss of the network. Moreover, it is shown that the decentralized GCN-based DRL has faster computational speed than other approaches.
A three dimensional analysis of the non-uniform flow around the liquid oxygen (LOX) posts in the Space Shuttle Main Engine (SSME) powerhead was performed to determine possible factors contributing to the failure of the posts. Also performed was three dimensional numerical fluid flow analysis of the high pressure fuel turbopump (HPFTP) exhaust system, consisting of the turnaround duct (TAD), two-duct hot gas manifold (HGM), and the Version B transfer ducts. The analysis was conducted in the following manner: (1) modeling the flow around a single and small clusters (2 to 10) of posts; (2) modeling the velocity field in the cross plane; and (3) modeling the entire flow region with a three dimensional network type model. Shear stress functions which will permit viscous analysis without requiring excessive numbers of computational grid points were developed. These wall functions, laminar and turbulent, have been compared to standard Blasius solutions and are directly applicable to the cylinder in cross flow class of problems to which the LOX post problem belongs.
A portable computer called BLASIM was developed at NASA LeRC to assess ice impact damage on aircraft engine blades. In addition to ice impact analyses, the code also contains static, dynamic, resonance margin, and supersonic flutter analysis capabilities. Solid, hollow, superhybrid, and composite blades are supported. An optional preprocessor (input generator) was also developed to interactively generate input for BLASIM. The blade geometry can be defined using a series of airfoils at discrete input stations or by a finite element grid. The code employs a coarse, fixed finite element mesh containing triangular plate finite elements to minimize program execution time. Ice piece is modeled using an equivalent spherical objective that has a high velocity opposite that of the aircraft and parallel to the engine axis. For local impact damage assessment, the impact load is considered as a distributed force acting over a region around the impact point. The average radial strain of the finite elements along the leading edge is used as a measure of the local damage. To estimate damage at the blade root, the impact is treated as an impulse and a combined stress failure criteria is employed. Parametric studies of local and root ice impact damage, and post-impact dynamics are discussed for solid and composite blades.