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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Algorithmic considerations of integrated design for CSI on a hypercube architecture

An approach is presented to the integrated design problem for actively controlled large, flexible mechanical systems for which Control Structure Interaction (CSI) problems are of concern. The two coupled design problems were identified as the optimal Structural Design problem the optimal Controller Design problem. These two problems can be addressed within a decision making loop that would consider each separately, and then sequentially analyze the effects of one on the other. Embedded in such a loop would be the simulation and coordination tasks as part of the decision tools required in a total (software) package. All of the above are compute-intensive tasks. In any such task, possible decompositions and gains due to the inherent parallelism have to be exploited. The problems under consideration, as applied to large flexible mechanical structures, are particularly suited to be mapped onto multicomputer systems in a hypercube topology.

Oezguener, UE.↗
DOE OSTI2018

Nanovoid Incorporated IrxCu Metallic Aerogels for Oxygen Evolution Reaction Catalysis

Ir-based nanomaterials are regarded as state-of-the-art cathode electrocatalysts in proton exchange membrane water electrolyzers (PEMWEs). Engineering the morphology of Ir-based three-dimensional architectures as electrocatalysts toward oxygen evolution reaction (OER) has been rarely studied. Here, we report the gelation of IrxCu metallic hydrogels self-assembled with ultrafine and nanovoid incorporated building blocks for enhancing the electrocatalytic performance toward OER. The composition-optimized Ir3Cu metallic aerogels exhibited improved catalytic activity and durability toward OER. The mesosized voids generated through the in situ galvanic replacement reaction and the macrosized porous systems make a great contribution to the increased number of active sites. First-principle calculations revealed the intrinsic optimized binding energy of Ir by alloying with Cu. The best catalytic performance necessities a balance of the adsorption and desorption energy. The well-defined morphology and enhanced OER electrochemical performances of nanovoid incorporated IrxCu metallic aerogels hold great promise in further applications in PEMWEs.

Shi, Qiurong↗
DOE OSTI2021

HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization

We present a new software, HYPPO, that enables the automatic tuning of hyperparameters of various deep learning (DL) models. Unlike other hyperparameter optimization (HPO) methods, HYPPO uses adaptive surrogate models and directly accounts for uncertainty in model predictions to find accurate and reliable models that make robust predictions. Using asynchronous nested parallelism, we are able to significantly alleviate the computational burden of training complex architectures and quantifying the uncertainty. HYPPO is implemented in Python and can be used with both TensorFlow and PyTorch libraries. We demonstrate various software features on time-series prediction and image classification problems as well as a scientific application in computed tomography image reconstruction. Finally, we show that (1) we can reduce by an order of magnitude the number of evaluations necessary to find the most optimal region in the hyperparameter space and (2) we can reduce by two orders of magnitude the throughput for such HPO process to complete.

adaptation models↗
DOE OSTI2020

Virtualized Logical Qubits: A 2.5D Architecture for Error-Corrected Quantum Computing

Current, near-term quantum devices have shown great progress in the last several years culminating recently with a demonstration of quantum supremacy. In the medium-term, however, quantum machines will need to transition to greater reliability through error correction, likely through promising techniques like surface codes which are well suited for near-term devices with limited qubit connectivity. We discover quantum memory, particularly resonant cavities with transmon qubits arranged in a 2.5D architecture, can efficiently implement surface codes with substantial hardware savings and performance/fidelity gains. Specifically, we virtualize logical qubits by storing them in layers of qubit memories connected to each transmon. Surprisingly, distributing each logical qubit across many memories has a minimal impact on fault tolerance and results in substantially more efficient operations. Our design permits fast transversal application of CNOT operations between logical qubits sharing the same physical address (same set of cavities) which are 6x faster than standard lattice surgery CNOTs. We develop a novel embedding which saves approximately 10x in transmons with another 2x savings from an additional optimization for compactness. Although qubit virtualization pays a 10x penalty in serialization, advantages in the transversal CNOT and in area efficiency result in fault-tolerance and performance comparable to conventional 2D transmon-only architectures. Our simulations show our system can achieve fault tolerance comparable to conventional two-dimensional grids while saving substantial hardware. Furthermore, our architecture can produce magic states at 1.22x the baseline rate given a fixed number of transmon qubits. Here, this is a critical benchmark for future fault-tolerant quantum computers as magic states are essential and machines will spend the majority of their resources continuously producing them. This architecture substantially reduces the hardware requirements for fault-tolerant quantum computing and puts within reach a proof-of-concept experimental demonstration of around 10 logical qubits, requiring only 11 transmons and 9 attached cavities in total.

quantum computing↗
DOE OSTI2018

Wind turbine sensor array for monitoring avian and bat collisions

Assessment of avian and bat collisions with wind turbines is necessary to ensure that the benefits of renewable wind power generation are not outweighed by mortality of protected species. An onboard, integrated multisensor system capable of providing detection of turbine collision events, including taxonomic information, was developed. The conceptual design of a multisensor system including a vibration sensing node, an optics node, and an bioacoustic node with an event–driven trigger architecture was field–tested on utility–scale wind turbines. A pixel density computational model was built to estimate the spatial coverage and target resolution to the optimized configuration for camera placement. Field test results of the vibration node showed that nearly half of the recorded impact events were successfully identified by visual inspection and running short–time Fourier transform on recorded vibration signals. The remaining undetected impact events were masked under background noise due to low impact energy and high background noise of the operating turbine, which result in subsequent low signal–to–noise ratio. Furthermore, our results demonstrate the feasibility of triggering the system through single impact event sensed by vibration sensors.

17 WIND ENERGY↗
DOE OSTI2019

In Vitro Fabrication and Biocompatibility Assay of a Biomimetic Osteoblastic Niche

A novel HAp-CS/Gel biomimetic osteoblastic niche was fabricated by freeze-drying, and its mechanical strength and biocompatibility were characterized. HAp-CS/Gel scaffolds in various ratios of 100:5, 100:10, and 100:20 (CS/Gel to HAp) were prepared by freeze-drying prior to chemical cross-linking followed by infrared spectrum analysis, EDS, FITR, SEM, fluorescence microscopy, MTT, and ALP experiments. Results from the infrared spectrum analysis showed that HAp doping remained the surface morphology and the architecture of scaffold with interconnected pores in the size range of 135 to 150 μm. The HAp doping ratio of 100:20 was found to be optimal based on its high porosity of 90%, better water uptake folds of 19.1. In addition, EDS and FITR analyses demonstrated that HAps were uniformly distributed on the surface of a scaffold with aggregates and particles, which has sufficient roughness for cell attachment and proliferation of osteoblasts. Under SEM and fluorescent microscopy, osteoblasts seeded onto the scaffold showed evenly distributed viable cells, which is believed to form a biomimetic niche. In the present study, we further demonstrate that osteoblasts can maintain their function and grow well on the scaffold through MTT and ALP tests. Thus, the scaffold has favorable physical properties and biocompatibility to support the proliferation and differentiation of osteoblasts and further to support the constructs of biomimetic osteoblastic niche.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

An ant-nest-like cathode substrate for lithium-sulfur batteries with practical cell fabrication parameters

We report that electrochemical performances of lithium-sulfur batteries have received much progress in recent years. However, their practical deployment encounters challenges with respect to optimizing the cell-fabrication parameters (e.g., amounts of the active material and electrolyte). We present here an “ant-nest-like” cathode substrate with unique architecture to synchronously attain high electrochemical performance and necessary cell-fabrication parameters. The cells with a high sulfur loading (11.5 mg cm -2 ), a high sulfur content (75 wt.%), and a low electrolyte/sulfur ratio (9 μL mg -1 ) display a high areal capacity and energy density of, respectively, 7 mA h cm -2 and 14 mW h cm -2 with a capacity retention of 70% after 150 cycles. Moreover, the cells exhibit a low self-discharge behavior with a low self-discharge constant of 0.0013 per day and a long rest period of one month. Lastly, these dynamic and static electrochemical stabilities are attributed to the ant-nest-like structure and low surface area of the cathode substrate that allows, respectively, the accommodation and encapsulation of a high amount of active material and reduces the consumption of electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2017

A 5- μ m pitch charge-coupled device optimized for resonant inelastic soft X-ray scattering

Here, we have developed a charge-coupled device (CCD) with 5 μm × 45 μm pixels on high-resistivity silicon. The fully depleted 200 μm-thick silicon detector is back-illuminated through a 10 nm-thick in situ doped polysilicon window and is thus highly efficient for soft through > 8 keV hard X-rays. The device described here is a 1.5 megapixel CCD with 2496 × 620 pixels. The pixel and camera geometry was optimized for Resonant Inelastic X-ray Scattering (RIXS) and is particularly advantageous for spectrometers with limited arm lengths. In this article, we describe the device architecture, construction and operation, and its performance during tests at the Advance Light Source (ALS) 8.0.1 RIXS beamline. The improved spectroscopic performance, when compared with a current standard commercial camera, is demonstrated with a ~280 eV (C K ) X-ray beam on a graphite sample. Readout noise is typically 3-6 electrons and the point spread function for soft C K X-rays in the 5 μm direction is 4.0 μm ± 0.2 μm. Finally, the measured quantum efficiency of the CCD is greater than 75% in the range from 200 eV to 1 keV.

36 MATERIALS SCIENCE↗
DOE OSTI2023

TAMM: Tensor algebra for many-body methods

Tensor algebra operations such as contractions in computational chemistry consume a significant fraction of the computing time on large-scale computing platforms. The widespread use of tensor contractions between large multi-dimensional tensors in describing electronic structure theory has motivated the development of multiple tensor algebra frameworks targeting heterogeneous computing platforms. In this paper, we present Tensor Algebra for Many-body Methods (TAMM), a framework for productive and performance-portable development of scalable computational chemistry methods. TAMM decouples the specification of the computation from the execution of these operations on available high-performance computing systems. With this design choice, the scientific application developers (domain scientists) can focus on the algorithmic requirements using the tensor algebra interface provided by TAMM, whereas high-performance computing developers can direct their attention to various optimizations on the underlying constructs, such as efficient data distribution, optimized scheduling algorithms, and efficient use of intra-node resources (e.g., graphics processing units). The modular structure of TAMM allows it to support different hardware architectures and incorporate new algorithmic advances. We describe the TAMM framework and our approach to the sustainable development of scalable ground- and excited-state electronic structure methods. We present case studies highlighting the ease of use, including the performance and productivity gains compared to other frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Visualization System for Evolutionary Neural Networks for Deep Learning

Deep learning is actively used in a wide range of fields for scientific discovery. To effectively apply deep learning to a particular problem, it is important to select an appropriate network architecture and other hyper-parameters (at each layer). Evolving architectures and hyper-parameters using a genetic algorithm is one current approach to search the huge space of all possible configurations to find those more optimal for the problem. However, examining an evolutionary process and tuning the genetic algorithm are challenging, pushing most users to treat the process as a black box. To address this challenge, we propose a visualization system for evolutionary neural networks for deep learning. The key feature of our visualization system is to provide a visual analytics environment for evaluating a genetic algorithm in order to improve the underlying operations to reduce time to find good solutions. Our system is able to not only visualize how a genetic algorithm traverses its search space but also allows users to examine evolving networks in-depth to get insights to improve performance through interactive visualization components.

Chae, Junghoon↗
DOE OSTI2021

Compressive Neural Representations of Volumetric Scalar Fields

Here, we present an approach for compressing volumetric scalar fields using implicit neural representations. Our approach represents a scalar field as a learned function, wherein a neural network maps a point in the domain to an output scalar value. By setting the number of weights of the neural network to be smaller than the input size, we achieve compressed representations of scalar fields, thus framing compression as a type of function approximation. Combined with carefully quantizing network weights, we show that this approach yields highly compact representations that outperform state-of-the-art volume compression approaches. The conceptual simplicity of our approach enables a number of benefits, such as support for time-varying scalar fields, optimizing to preserve spatial gradients, and random-access field evaluation. We study the impact of network design choices on compression performance, highlighting how simple network architectures are effective for a broad range of volumes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Meta-optic accelerators for object classifiers

Rapid advances in deep learning have led to paradigm shifts in a number of fields, from medical image analysis to autonomous systems. These advances, however, have resulted in digital neural networks with large computational requirements, resulting in high energy consumption and limitations in real-time decision-making when computation resources are limited. Here, we demonstrate a meta-optic–based neural network accelerator that can off-load computationally expensive convolution operations into high-speed and low-power optics. In this architecture, metasurfaces enable both spatial multiplexing and additional information channels, such as polarization, in object classification. End-to-end design is used to co-optimize the optical and digital systems, resulting in a robust classifier that achieves 93.1% accurate classification of handwriting digits and 93.8% accuracy in classifying both the digit and its polarization state. This approach could enable compact, high-speed, and low-power image and information processing systems for a wide range of applications in machine vision and artificial intelligence.

42 ENGINEERING↗
DOE OSTI2023

DMTN-219: Proposal and Prototype for Prompt Processing

The Prompt Processing framework has long been a gray area in the overall Rubin Observatory architecture. This document attempts to fill that hole by proposing a concrete design with an accompanying prototype implementation that should meet minimum requirements. Additional features and optimizations that could be incorporated later are also described.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1991

Space Transfer Vehicle Concepts and Requirements Study. Volume 2, Book 2: System and Program Requirements Trade Studies

During the 90-day study, support was provided to NASA in defining a point-of-departure space transfer vehicle (STV). The resulting STV concept was performance optimized with a two-stage LTV/LEV configuration. Appendix A reports on the effort during this period of the study. From the end of the 90-day study until the March Interim Review, effort was placed on optimizing the two-stage vehicle approach identified in the 90-day effort. After the March Interim Review, the effort was expanded to perform a full architectural trade study with the intent of developing a decision database to support STV system decisions in response to changing SEI infrastructure concepts. Several of the architecture trade studies were combined in a System Architecture Trade Study. In addition to this trade, system optimization/definition trades and analyses were completed and some special topics were addressed. Program- and system-level trade study and analyses methodologies and results are presented in this section. Trades and analyses covered in this section are: (1) a system architecture trade study; (2) evolution; (3) safety and abort considerations; (4) STV as a launch vehicle upper stage; and (5) optimum crew and cargo split.

Weber, Gary A.↗
NASA NTRS1995

CFD Research, Parallel Computation and Aerodynamic Optimization

During the last five years, CFD has matured substantially. Pure CFD research remains to be done, but much of the focus has shifted to integration of CFD into the design process. The work under these cooperative agreements reflects this trend. The recent work, and work which is planned, is designed to enhance the competitiveness of the US aerospace industry. CFD and optimization approaches are being developed and tested, so that the industry can better choose which methods to adopt in their design processes. The range of computer architectures has been dramatically broadened, as the assumption that only huge vector supercomputers could be useful has faded. Today, researchers and industry can trade off time, cost, and availability, choosing vector supercomputers, scalable parallel architectures, networked workstations, or heterogenous combinations of these to complete required computations efficiently.

Ryan, James S.↗
DOE OSTI2023

Towards a Software Development Framework for Interconnected Science Ecosystems

The innovative science of the future must be multi-domain and interconnected to usher in the next generation of “self-driving” laboratories enabling consequential discoveries and transformative inventions. Such a disparate and interconnected ecosystem of scientific instruments will need to evolve using a system-of-systems (SoS) approach. The key to enabling application integration with such an SoS will be the use of Software Development Kits (SDKs). Currently, SDKs facilitate scientific research breakthroughs via algorithmic automation, databases and storage, optimization and structure, pervasive environmental monitoring, among others. However, existing SDKs lack instrument-interoperability and reusability capabilities, do not effectively work in an open federated architectural environment, and are largely isolated within silos of the respective scientific disciplines. Inspired by the scalable SoS framework, this work proposes the development of INTERSECT-SDK to provide a coherent environment for multi-domain scientific applications to benefit from the open federated architecture in an interconnected ecosystem of instruments. This approach will decompose functionality into loosely coupled software services for interoperability among several solutions that do not scale beyond a single domain and/or application. Furthermore, the proposed environment will allow operational and managerial inter-dependence while providing opportunities for the researchers to reuse software components from other domains and build universal solution libraries. We demonstrate this research for microscopy use-case, where we show how INTERSECT-SDK is developing the tools necessary to enable advanced scanning methods and accelerate scientific discovery.

Malviya, Addi Thakur↗
DOE OSTI2023

Towards 5G-Enabled Operational Technology for Process Monitoring and Network Slicing

Cyber-Physical Systems (CPS) are deployed to monitor physical processes in critical cyber-enabled services like power generation. However, CPS ecosystems are typically designed without robust security. While it is important to ensure optimal performance of the Operational Technology (OT) environments, security cannot be overlooked. To modernize traditional OT services, 5G technology is being integrated. 5G technology offers low latency and high availability, making it a suitable infrastructure for managing and monitoring physical processes. How-ever, integrating 5G mechanisms into large-scale OT networks introduces new implementation and performance challenges. Therefore, this paper presents a 5G-enabled CPS architecture (5G-CPS) that describes the necessary components, services, and communication protocols and conducts feasibility study to integrate 5G technology in industrial control system networks to understand the performance merits. The 5G-CPS architecture aims to minimize implementation and operational challenges associated with integrating 5G technology into constrained OT.

Aguayo, Jared M.↗
DOE OSTI2021

Compensated Contacts for Three-Terminal Transistor Solar Cells

The heterojunction bipolar transistor solar cell (HBTSC) is an alternative to conventional double-junction solar cells that combines the advantages of three-terminal architectures with a compact design. A critical part of the HBTSC fabrication is the implementation of the middle contact, the one associated to the base layer in the transistor structure, because this layer can be damaged by the diffusion of metallic species during contact annealing. As a solution we propose to implement a "compensated contact", that is, to leave a thin (< 200 nm) portion of emitter or collector between the base layer and the contact metals and compensate its doping during contact annealing. Using an Au/Zn/Au metal structure to compensate a 150 nm thick portion of the collector, we obtain a specific contact resistance ~8 10-4 ..omega.. cm2. This value is fairly invariant for annealing temperatures between 400 and 460 degrees C and annealing times between 2 and 5 minutes, and it does not improve by adding Pd to the metallic stack. Optimizing the compensated contact technology opens the path to the realization of III-V-material-based HBTSCs with open-circuit voltages and fill factors comparable to those of conventional multijunction architectures.

contact resistance↗