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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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CREEPY: Computationally-Redundant, Energy-Efficient Processing for Y'all.
Abstract not provided.
Wafer-scale TaOx device variability and implications for neuromorphic computing applications.
Abstract not provided.
Advances in Quantum Computation and Quantum Technologies: A Design Automation Perspective
Not provided.
Single Diode Parameter Extraction from In-Field Photovoltaic I-V Curves on a Single Board Computer.
Abstract not provided.
Intrusion Detection & Response using an Unsupervised Artificial Neural Network on a Single Board Computer for Building Control Resilience.
Abstract not provided.
A Resurgence in Neuromorphic Architectures Enabling Remote Sensing Computation.
Abstract not provided.
A Computational Simulation of Using Tungsten Gratings in Near-Field Thermophotovoltaic Devices
Near-field thermophotovoltaic (NFTPV) devices have received much attention lately as an alternative energy harvesting system, whereby a heated emitter exchanges super-Planckian thermal radiation with a photovoltaic (PV) cell to generate electricity. This work describes the use of a grating structure to enhance the power throughput of NFTPV devices, while increasing the energy conversion efficiency by ensuring that a large portion of the radiation entering the PV cell is above the band gap. The device contains a high-temperature tungsten grating that radiates photons to a room-temperature In 0.18 Ga 0.82 Sb PV cell through a vacuum gap of several tens of nanometers. Scattering theory is used along with the rigorous coupled-wave analysis (RCWA) to calculate the radiation energy exchange between the grating emitter and the TPV cell. A parametric study is performed by varying the grating depth, period, and ridge width in the range that can be fabricated using available fabrication technologies. It is found that the power output can be increased by 40% while improving the efficiency from 29.9% to 32.0% with a selected grating emitter as compared to the case of a flat tungsten emitter. Reasons for the enhancement are found to be due to the enhanced energy transmission coefficient close to the band gap. Furthermore, this work shows a possible way of improving NFTPV and sheds light on how grating structures interact with thermal radiation at the nanoscale.
Computational Evaluation of Thermal Response of Open-Cell Foam With Circular Pore (Computional Evaluation of Thermal Response of Open-Cell Foam with Circular Pore)
The evaluation of effective material properties in heterogeneous materials (e.g., composites or multicomponent structures) critically relevant to a wide spectrum of applications, including nuclear power, electronic packaging, flame retardants, hypersonics, and gas turbine power. The work described in this paper is centered around the numerical assessment of the thermal behavior of porous materials obtained from finite element thermal modeling and simulation. Here, two-dimensional, steady state analyses were performed on unit cells with centered, circular pores using a second order accurate Galerkin finite element method (FEM). The effective thermal conductivities of the porous systems were examined, encompassing a range of porosities from 4.9% to 60.1%. The geometries of the models were generated based on ordered circular pores for each modeled porosity level. The system response quantity (SRQ) under investigation was the dimensionless effective thermal conductivity across the unit cell. The dimensionless effective thermal conductivity was compared across all simulated cases, producing a trend between porosity and effective thermal conductivity. In the presented investigation, the method of manufactured solutions (MMS) was used to perform code verification, and the grid convergence index (GCI) was employed to estimate discretization uncertainty as solution verification. Code verification concluded an approximately second order accurate Galerkin FEM solver. It was found that the introduction of porosity to the unit cell material structure reduces effective thermal conductivity, as anticipated. Numerical results obtained in this study are compared to an analytical solution and to a sample of empirical data.
Nuclear Facility Safety Enhancement Using Sandia National Laboratories' Computer Codes.
Abstract not provided.
Characterization of 3D printed computational imaging element for use in task-specific compressive classification.
Abstract not provided.
Polynomial Preconditioned GMRES in Trilinos: Practical Considerations for High Performance Computing.
Abstract not provided.
Neuromorphic computing for temporal scientific data classification
In this work, we apply a spiking neural network model and an associated memristive neuromorphic implementation to an application in classifying temporal scientific data. We demonstrate that the spiking neural network model achieves comparable results to a previously reported convolutional neural network model, with significantly fewer neurons and synapses required.