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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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MoChlo: A Versatile, Modular Cloning Toolbox for Chloroplast Biotechnology
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Suppressing the Capacitor Voltage Fluctuations in Low Frequency Operation of Modular Multilevel Converters
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T-Type Modular DC Circuit Breaker (T-Breaker) as a Compensator for Future DC Grids
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GridAPPS-D Distributed App Architecture and API for Modular and Distributed Grid Operations
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Analyzing Cyber-Physical Modularity and Interdependence Using Bio-Inspired Graph Modeling
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Standard Modular Architecture for Consumer End Plug and Play Interfaces
The growth in load and generation sources at the edge of the grid is driving the innovation in power electronic (PE) grid interfaces at the consumer end to improve the grid resiliency, reliability, security, and cost of the future infrastructure. Novel PE technologies are key enablers for the future grid infrastructure to handle the issues that arise because of the projected growth. This paper introduces a novel fundamental building block (FBB) architecture with plug-and play features. An example framework that enables co-ordination of multiple FBBs hierarchically to provide various grid functions is also presented. The FBBs are designed to be equipped with advanced features like online health monitoring, embedded intelligence, and decision-making capability for enhancing the metrics of consumer end plug and play interfaces. The paper elaborates on the proposed architecture and the developed framework i.e., the controls, communication, protection, and the corresponding timing requirements for the building blocks. The architecture and the framework have been validated through simulations and the communication framework has been validated with a control hardware in the loop platform.
MiniMod: A Modular Miniapplication Benchmarking Framework for HPC.
Abstract not provided.
Modular Spiking Neural Circuits for Mapping Long Short-Term Memory on a Neurosynaptic Processor
Due to the distributed and asynchronous nature of neural computation through low-energy spikes, brain-inspired hardware systems offer high energy efficiency and massive parallelism. One such platform is the IBM TrueNorth neurosynaptic system. Recently, TrueNorth compatible representation learning algorithms have emerged, achieving close to the state-of-the-art performance in various data sets. However, its application in temporal sequence processing models, such as recurrent neural networks (RNNs), is still only at the proof of concept level. There is an inherent difficulty in capturing temporal dynamics of an RNN using spiking neurons, which is only exasperated by the hardware constraints in connectivity and synaptic weight resolution. This paper presents a design flow that overcomes these difficulties and maps a special case of recurrent networks called long short-term memory (LSTM) onto a spike-based platform. The framework utilizes various approximation techniques, such as activation discretization, weight quantization, and scaling and rounding, spiking neural circuits that implement the complex gating mechanisms, and a store-and-release technique to enable neuron synchronization and faithful storage. While the presented techniques can be applied to map LSTM to any spiking neural network (SNN) simulator/emulator, here we choose the TrueNorth chip as the target platform by adhering to its hardware constraints. Three LSTM applications, parity check, extended Reber grammar, and question classification, are evaluated. The tradeoffs among accuracy, performance, and energy tradeoffs achieved on TrueNorth are demonstrated. Finally, this is compared with the performance on an SNN platform without hardware constraints, which represents the upper bound of the achievable accuracy.
Simulation of Modular Multilevel Converter System Via an Analytical Approach
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Modular High Field Quadrupole Design for Electron-Ion Collider
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Economic Implementation of 99.98% Efficiency in Natural-Cooling Modular MVDC SSCBs
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Cell Capacitor Voltage Switching-Cycle Balancing Control for Modular Multilevel Converters
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Development of Packaging and Modular Control of Thermoelectric Clothes Dryer, With Performance Evaluation
This paper provides an overview of a thermoelectric heat pump clothes dryer which was developed with the aim of reducing the significant primary energy consumption attributed to residential electric clothes drying in the United States (623 TBtu/yr). The use of thermoelectric modules in place of the conventional electric resistance heater resulted in a 40% reduction in the energy consumption of the system, compared to the minimum energy efficiency standard. This was achieved for the first time for a standard test load of 8.45 lb, using a clothes dryer prototype with a thermoelectric heat pump module as the sole heating mechanism. The current experimental prototype was developed after extensive modeling, system design and control optimization, and experimental system-level evaluation of control parameters. The demonstration of improved energy consumption has laid the foundation for future development of this technology.