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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 127 records · Page 7

Optimizing High Performance Markov Clustering for Pre-Exascale Architectures

HipMCL is a high-performance distributed memory implementation of the popular Markov Cluster Algorithm (MCL) and can cluster large-scale networks within hours using a few thousand CPU-equipped nodes. It relies on sparse matrix computations and heavily makes use of the sparse matrix-sparse matrix multiplication kernel (SpGEMM). The existing parallel algorithms in HipMCL are not scalable to Exascale architectures, both due to their communication costs dominating the runtime at large concurrencies and also due to their inability to take advantage of accelerators that are increasingly popular. In this work, we systematically remove scalability and performance bottlenecks of HipMCL. We enable GPUs by performing the expensive expansion phase of the MCL algorithm on GPU. Additionally, we propose a CPU-GPU joint distributed SpGEMM algorithm called pipelined Sparse SUMMA and integrate a probabilistic memory requirement estimator that is fast and accurate. Furthermore, we develop a new merging algorithm for the incremental processing of partial results produced by the GPUs, which improves the overlap efficiency and the peak memory usage. We also integrate a recent and faster algorithm for performing SpGEMM on CPUs. We validate our new algorithms and optimizations with extensive evaluations. With the enabling of the GPUs and integration of new algorithms, HipMCL is up to 12.4x faster, being able to cluster a network with 70 million proteins and 68 billion connections just under 15 minutes using 1024 nodes of ORNL's Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗

Automation Hooks Architecture Trade Study for Flexible Test Orchestration

We describe the conclusions of a technology and communities survey supported by concurrent and follow-on proof-of-concept prototyping to evaluate feasibility of defining a durable, versatile, reliable, visible software interface to support strategic modularization of test software development. The objective is that test sets and support software with diverse origins, ages, and abilities can be reliably integrated into test configurations that assemble and tear down and reassemble with scalable complexity in order to conduct both parametric tests and monitored trial runs. The resulting approach is based on integration of three recognized technologies that are currently gaining acceptance within the test industry and when combined provide a simple, open and scalable test orchestration architecture that addresses the objectives of the Automation Hooks task. The technologies are automated discovery using multicast DNS Zero Configuration Networking (zeroconf), commanding and data retrieval using resource-oriented Restful Web Services, and XML data transfer formats based on Automatic Test Markup Language (ATML). This open-source standards-based approach provides direct integration with existing commercial off-the-shelf (COTS) analysis software tools.

Lansdowne, Chatwin A.↗

EFIT-Prime: Probabilistic and physics-constrained reduced-order neural network model for equilibrium reconstruction in DIII-D

We introduce EFIT-Prime, a novel machine learning surrogate model for EFIT (Equilibrium FIT) that integrates probabilistic and physics-informed methodologies to overcome typical limitations associated with deterministic and ad hoc neural network architectures. EFIT-Prime utilizes a neural architecture search-based deep ensemble for robust uncertainty quantification, providing scalable and efficient neural architectures that comprehensively quantify both data and model uncertainties. Physically informed by the Grad–Shafranov equation, EFIT-Prime applies a constraint on the current density J tor and a smoothness constraint on the first derivative of the poloidal flux, ensuring physically plausible solutions. Furthermore, the spatial location of the diagnostics is explicitly incorporated in the inputs to account for their spatial correlation. Extensive evaluations demonstrate EFIT-Prime's accuracy and robustness across diverse scenarios, most notably showing good generalization on negative-triangularity discharges that were excluded from training. Timing studies indicate an ensemble inference time of 15 ms for predicting a new equilibrium, offering the possibility of plasma control in real-time, if the model is optimized for speed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Development and Testing of a Variable Conductance Thermal Acquisition, Transport, and Switching System

This paper describes the development and testing of a scalable thermal management architecture for instruments, subsystems, or systems that must operate in severe space environments with wide variations in sink temperature. The architecture involves a serial linkage of one or more hot-side variable conductance heat pipes (VCHPs) to one or more cold-side loop heat pipes (LHPs). The VCHPs provide wide area heat acquisition, limited distance thermal transport, modest against gravity pumping, concentrated LHP startup heating, and high switching ratio variable conductance operation. The LHPs provide localized heat acquisition, long distance thermal transport, significant against gravity pumping, and high switching ratio variable conductance operation. The single-VCHP, single-LHP system described herein was developed to maintain thermal control of a small robotic lunar lander throughout the lunar day-night thermal cycle. It is also applicable to other variable heat rejection space missions in severe environments. Operationally, despite a 60-70% gas blocked VCHP condenser during ON testing, the system was still able to provide 2-4 W/K ON conductance, 0.01 W/K OFF conductance, and an end-to-end switching ratio of 200-400. The paper provides a detailed analysis of VCHP condenser performance, which quantified the gas blockage situation. Future multi-VCHP/multi-LHP thermal management system concepts that provide power/transport length scalability are also discussed.

Bugby, David C.↗

Hierarchical Model-Free Transactive Control of Building Loads to Support Grid Services

Residential buildings consume 4.4 quads of electricity annually, approximately 37% of the total electricity consumption in the United States. This represents a vast resource that can be used for demand management and other ancillary services. This project aims to develop a robust, scalable hierarchical transactional control mechanism incorporating elements of model-free control (MFC) and game theory to harness buildings to provide ancillary services to the grid. This approach is being taken to address the challenges of incorporating traditional transactional control schemes into existing buildings. The challenges include small individual building sizes requiring aggregation of many buildings, unpredictable energy usage that makes model identification difficult, and satisfying the sensitive occupant comfort constraints. In the proposed approach, by separating the control mechanism into two layers above and below the load aggregator, MFC can be used below the aggregator to modulate flexible building loads in response to pricing signals with guaranteed performance. This allows the burden of identifying an accurate model of the system to be shifted to the above-aggregator layer, where fluctuations in individual building usage have less impact on predicted building system behavior. Game theory concepts can then be used to determine pricing curves and control signals among regional aggregators. Managing this control in a game-theoretic approach will allow us to build in financial incentives that increase customer engagement. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable on small, embedded devices. In a broader sense, developing a strategy capable of effectively incorporating residential and small commercial buildings will allow greater throughput of existing and emerging grid services in addition to future transactive energy grid management methods. Using MFC within a hierarchical control architecture will allow the shifting of existing forecasting challenges to an aggregate level, where dynamics are slower and more predictable. This will enable a smooth interface between the grid services requests of utilities and the reliable control required by participating buildings. MFC, which supports distributed control architecture, permits a scalable solution that can be deployed to neighborhood-size systems as well as individual buildings. This project focuses on three objectives: (1) developing the mathematical framework, algorithm toolkit, and software toolset of the two-layer transactive control testbed; (2) developing a scalable solution for application over many residential and small-size commercial buildings with sparse distributed communication; and (3) field testing and implementation on hardware of the control strategies developed in the previous two objectives. The research and development activities are focused and designed to be impactful within the relevant 2025 targets timeframe. An open-source control framework for exploiting variability and dispatchability of building loads will be delivered as the outcome of the project. This capability enables greater participation of loads in electricity markets and ancillary services that are both useful for the utility and financially beneficial for building owners.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Development and Testing of a Variable Conductance Thermal Acquisition, Transport, and Switching System

This paper describes the development and testing of a scalable thermal control architecture for instruments, subsystems, or systems that must operate in severe space environments with wide variations in sink temperature. The architecture is comprised by linking one or more hot-side variable conductance heat pipes (VCHPs) in series with one or more cold-side loop heat pipes (LHPs). The VCHPs provide wide area heat acquisition, limited distance thermal transport, modest against gravity pumping, concentrated LHP startup heating, and high switching ratio variable conductance operation. The LHPs provide localized heat acquisition, long distance thermal transport, significant against gravity pumping, and high switching ratio variable conductance operation. Combining two variable conductance devices in series ensures very high switching ratio isolation from severe environments like the Earth's moon, where each lunar day spans 15 Earth days (270 K sink, with a surface-shielded/space viewing radiator) and each lunar night spans 15 Earth days (80-100 K radiative sink, depending on location). The single VCHP-single LHP system described herein was developed to maintain thermal control of International Lunar Network (ILN) anchor node lander electronics, but it is also applicable to other variable heat rejection space missions in severe environments. The LHPVCHP system utilizes a stainless steel wire mesh wick ammonia VCHP, a Teflon wick propylene LHP, a pair of one-third square meter high  radiators (one capillary-pumped horizontal radiator and a second gravity-fed vertical radiator), a half-meter of transport distance, and a wick-bearing co-located flow regulator (CLFR) to allow operation with a hot (deactivated) radiator. The VCHP was designed with a small reservoir formed by extending the length of its stainless steel heat pipe tubing. The system was able to provide end-to-end switching ratios of 300-500 during thermal vacuum testing at ATK, including 3-5 W/K ON conductance and 0.01 W/K OFF conductance. The test results described herein also include an in-depth analysis of VCHP condenser performance to explain VCHP switching operation in detail. Future multi-VCHP/multi-LHP thermal management system concepts that provide scalability to higher powers/longer transport lengths are also discussed in the paper.

Bugby, D. C.↗

Deep generative models for vehicle speed trajectories

Generating realistic vehicle speed trajectories is a crucial component in evaluating vehicle fuel economy and in predictive control of self-driving cars. Traditional generative models rely on Markov chain methods and can produce accurate synthetic trajectories but are subject to the curse of dimensionality. They do not allow to include conditional input variables into the generation process. In this paper, we show how extensions to deep generative models allow accurate and scalable generation. Proposed architectures involve recurrent and feed-forward layers and are trained using adversarial techniques. Our models are shown to perform well on generating vehicle trajectories using a model trained on GPS data from Chicago metropolitan area.

33 ADVANCED PROPULSION SYSTEMS↗

Through‐Plane Conductive Hydrophobic Electrodes for CO 2 Electrolysis to Ethylene

Copper catalyst gas diffusion electrodes (GDEs) have demonstrated unique electrochemical selectivity converting CO 2 to C 2 -hydrocarbons such as ethylene and ethanol but have been challenged by their hydrophobic chemical stability and internal electrical resistance leading to low energy efficiency. Carbon-supported GDEs have low electrical resistance but lack sufficient stability at industrially relevant current densities. While polymer-supported GDEs have improved hydrophobicity, they also display high in-plane electrical resistance, particularly at industrial scales. Here, in this work, we demonstrate a composite gas diffusion layer that combines hydrophobic porous polymers with an electrically conductive backbone addressing these core gas diffusion electrode (GDE) scaling challenges. We investigate the material properties of standalone porous perfluoropolyether (PFPE) polymers, including porosity and surface morphology, under varying processing conditions and then incorporate these polymers into a porous copper foam. This composite enhances the mechanical rigidity necessary for cell assembly and provides a through-plane electrical conduction path to reduce electrical resistive losses. This enhanced PFPE composite GDE displays efficient CO 2 reduction, achieving 15% ethylene energy efficiency at 100 cm 2 . These findings contribute to the development of advanced catalyst materials and electrode architectures and promote scalable strategies for electrochemical conversion of CO 2 into high-value carbon products.

Chemistry↗

Unraveling the Effects of Hierarchical Bimodal Microscale Porosity on Thick Electrodes

The thick electrode design is preferential in high-energy lithium-ion batteries (LIBs) systems. However, the sluggish ionic transport in homogeneous porous thick electrodes severely limits the areal capacity at high charging/discharging rates. The hierarchical porous design is a promising approach to mitigate kinetic limitations because it can distribute mass effectively in natural systems. In this study, the effects of bimodal microscale pores are fully investigated in thick electrodes from both architectural and electrochemical perspectives. Notably, by introduction of the bimodal microscale porous structure, the rate capability improves remarkably in thick electrodes with a low porosity (39%). Herein, by combining experimental results with simulations, this work presents a rational design guideline for preparing thick electrodes with a porosity at the commercial level, as well as simultaneous high energy and power densities, which brings new insights into the advanced electrode architecture design in scalable high-energy and high-power energy storage systems for practical applications.

25 ENERGY STORAGE↗

Solid neon as a noise-resilient host for electron qubits above 100 mK

Solid neon can be used as a solid host for single-electron qubits. At temperatures of around 10 mK, electron-on-solid-neon charge qubits exhibit long coherence times and high operation fidelities. However, a systematic characterization of the noise features of such systems is needed for the development of scalable quantum information architectures. Here, in this work, we show that solid neon can be used as a noise-resilient host for electron qubits above 100 mK. We examine the resilience of solid neon against charge and thermal noise when electron-on-solid-neon charge qubits are operated away from the charge-insensitive sweet spot and at elevated temperatures. We show that the extracted high-frequency charge noise density of electron-on-solid-neon qubits, projected as voltage fluctuations on nearby electrodes, is between 10 −4 μV 2 Hz −1 and 10 −6 μV 2 Hz −1 at 0.01 MHz to 1 MHz, which is comparable to common semiconductor hosts. We also show that the electron-on-solid-neon charge qubits operating at frequencies of around 5 GHz can maintain echo coherence times of over 1 μs at temperatures up to 400 mK.

42 ENGINEERING↗

Virtual Cable Impedance based Load Sharing in a Microgrid for Parallel Connected Grid Forming Converters

This paper presents a novel approach to power sharing between direct connected grid-forming converters, utilizing virtual cable impedance and droop-based outer loop control. To enhance stability, resistive droop is implemented, while virtual cable impedance with non-zero resistive and inductive components ensures improved power sharing. The inner loop controller employs a Lyapunov energy function to achieve superior dynamic performance. The proposed control architecture is validated through comprehensive modeling and real-time processor-in-the-loop simulations, demonstrating its robustness and efficiency under various operating conditions. The results highlight the potential of this control strategy to improve the reliability and efficiency of renewable energy systems. Additionally, a comparative analysis with traditional methods underscores the advantages of the proposed approach in terms of stability and performance. The proposed control architecture offers a scalable and flexible solution for grid-forming converters, enabling seamless integration of renewable energy sources. Its robustness and adaptability make it an attractive solution for real-world applications. Furthermore, the approach can be extended to other power electronic systems, enhancing overall system performance and efficiency. By providing a reliable and efficient control strategy, this paper contributes to the advancement of renewable energy systems and their adoption in the energy sector. The proposed control strategy has far-reaching implications for the widespread adoption of renewable energy sources, enabling a more sustainable and efficient energy future. The overall system is modeled in MATLAB/Simulink and PLECS software domain.

grid forming converters (GFM)↗

HPS-RL: Hyperparameter tuning for deep RL applications (HPS-RL) v1

Genetic Algorithms meets Deep RL for Hyperparameters Hyperparameter optimization and architecture search can easily become cumbersome and finding the right hyperparameters can seriously impact the robustness of the deep RL application being developed. We use genetic algorithms to evolve optimum deep RL architectures in a scalable manner. HPS-RL is designed to work with multiple gym enviornments, allow users to test their own optimization functions and tune multi-objective parameters in multiple deep RL algorithms. HPS-RL uses multi-threading and is being extended with mpipy for distributed processing on HPC. https://arxiv.org/abs/2201.11182

Kiran, Mariam↗

The SONATA data format for efficient description of large-scale network models

Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation, as well as sharing of such large-scale models, a broadly applicable, flexible, and high-performance data format is necessary. To address this need, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. It is designed for memory and computational efficiency and works across multiple platforms. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. SONATA is used in multiple modeling and visualization tools, and we also provide reference Application Programming Interfaces and model examples to catalyze further adoption. SONATA format is free and open for the community to use and build upon with the goal of enabling efficient model building, sharing, and reproducibility.

59 BASIC BIOLOGICAL SCIENCES↗

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗

Evaluation of Data Lake Design for the Accelerator Control System

In this modern world, the user expects faster processing and real-time response to operate accelerator control devices. The existing framework with its infrastructure does not have the ability to satisfy these future needs. Therefore, modernization is required to reach industry standards and develop a modular framework that can provide flexibility and dynamic scalability. The data lake architecture, comprising three layers, ingestion, processing, and data consumption, provides flexibility and scalability to meet current and future demands for the accelerator control system.

Jaikar, Amol [Fermilab]↗

The DART System for Far-IR/Submillimeter Space Missions

The DART is a system of two cylindrical-parabolic reflectors. One reflector will produce a line focus; two reflectors properly oriented will produce a point focus. For far-infrared/submillimeter missions, the DART presents a compelling new telescope architecture that is scalable to alrge apertures, and with it's large membrane area is well suited to passive cooling.

Dragovan, Mark↗

Ground System Architectures Workshop GMSEC SERVICES SUITE (GSS): an Agile Development Story

The GMSEC (Goddard Mission Services Evolution Center) Services Suite (GSS) is a collection of tools and software services along with a robust customizable web-based portal that enables the user to capture, monitor, report, and analyze system-wide GMSEC data. Given our plug-and-play architecture and the needs for rapid system development, we opted to follow the Scrum Agile Methodology for software development. Being one of the first few projects to implement the Agile methodology at NASA GSFC, in this presentation we will present our approaches, tools, successes, and challenges in implementing this methodology. The GMSEC architecture provides a scalable, extensible ground and flight system for existing and future missions. GMSEC comes with a robust Application Programming Interface (GMSEC API) and a core set of Java-based GMSEC components that facilitate the development of a GMSEC-based ground system. Over the past few years, we have seen an upbeat in the number of customers who are moving from a native desktop application environment to a web based environment particularly for data monitoring and analysis. We also see a need to provide separation of the business logic from the GUI display for our Java-based components and also to consolidate all the GUI displays into one interface. This combination of separation and consolidation brings immediate value to a GMSEC-based ground system through increased ease of data access via a uniform interface, built-in security measures, centralized configuration management, and ease of feature extensibility.

Software Development/Agile↗

Effect of electron-nuclear spin interactions for electron-spin qubits localized in InGaAs self-assembled quantum dots

The effect of electron-nuclear spin interactions on qubit operations is investigated for a qubit represented by the spin of an electron localized in an InGaAs self-assembled quantum dot. The localized electron wave function is evaluated within the atomistic tight-binding model. The electron Zeeman splitting induced by the electron-nuclear spin interaction is estimated in the presence of an inhomogeneous environment characterized by a random nuclear spin configuration, by the dot-size distribution, alloy disorder, and interface disorder. Due to these inhomogeneities, the electron Zeeman splitting varies from one qubit to another by the order of 10(-6), 10(-6), 10(-7), and 10(-9) eV, respectively. Such fluctuations cause errors in exchange operations due to the inequality of the Zeeman splitting between two qubits. However, the error can be made lower than the quantum error threshold if an exchange energy larger than 10(-4) eV is used for the operation. This result shows that the electron-nuclear spin interaction does not hinder quantum-dot based quantum computer architectures from being scalable even in the presence of inhomogeneous environments.

Whaley, K. Birgitta↗