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NASA NTRS2018

Instrument Modeling Concepts for Tradespace Analysis of Satellite Constellations

Constellations are gaining popularity in government and commercial space-based missions for Earth Observation (EO) due to their risk tolerance and ability to improve observation sampling in space and time. NASA Goddard Space Flight Center (GSFC) is developing a pre-Phase A tool called Tradespace Analysis Tool for Constellations (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper will describe the concept of modeling the primary science instruments within TAT-C, using a radar as an example, but extendable to imagers, occulters and lidars. The modularity of TAT-C's software architecture allows for crisply defining the interface between TAT-C's user defined or internal variables and the payload variables. The described module will inform TAT-C users of payload-dependent performance differences among thousands of constellation architectures (e.g. revisit time of the sensor swath, differential signal to noise ratio (SNR), spatial resolution of measurements) and allow them to pick an appropriate constellation architecture for detailed development. The module may also inform operational decisions of satellite modes, based on ground optimization or onboard autonomy.

Nag, Sreeja↗

DOE OSTI2021

Evolutionary NAS in Light of Model Stability for Accurate Continual Learning

Continual learning, the capability to learn new knowledge from streaming data without forgetting the previous knowledge, is a critical requirement for dynamic learning systems, especially for emerging edge devices such as self-driving cars and drones. However, continual learning is still facing the catastrophic forgetting problem. Previous work illustrate that model performance on continual learning is not only related to the learning algorithms but also strongly dependent on the inherited model, i.e., the model where continual learning starts. The better stability of the inherited model, the less catastrophic forgetting and thus, the inherited model should be elaborately selected. Inspired by this finding, we develop an evolutionary neural architecture search (ENAS) algorithm that emphasizes the Stability of the inherited model, namely ENAS-S. ENAS-S aims to find optimal architectures for accurate continual learning on edge devices. On CIFAR-10 and CIFAR-100, we present that ENAS-S achieves competitive architectures with lower catastrophic forgetting and smaller model size when learning from a data stream, as compared with handcrafted DNNs.

Du, Xiaocong↗

DOE OSTI2021

A System of Agents for Supporting Optimization and Control of a Connected Community

The residential sector consumes a significant portion of the electricity sold in the United States. Above 60% of the energy used in the sector is used to operate heating, ventilation, and air conditioning (HVAC) systems and water heating (WH) systems. With the increase of intelligence in the grid and the new decision and control options enabled by the Internet of Things; control of these devices can be used to support the grid. Therefore, this article presents a scalable multiagent system for optimizing HVAC and WH systems while maintaining comfort. It allows a utility to orchestrate the shifting of energy from critical periods without direct control, but instead by using a price signal. The architecture, optimization formulation, implementation strategy and results from an implementation project are discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Design-controlled synthesis of IrO 2 sub-monolayers on Au nanoflowers: marrying plasmonic and electrocatalytic properties

We develop herein plasmonic–catalytic Au–IrO 2 nanostructures with a morphology optimized for efficient light harvesting and catalytic surface area; the nanoparticles have a nanoflower morphology, with closely spaced Au branches all partially covered by an ultrathin (1 nm) IrO 2 shell. This nanoparticle architecture optimizes optical features due to the interactions of closely spaced plasmonic branches forming electromagnetic hot spots, and the ultra-thin IrO 2 layer maximizes efficient use of this expensive catalyst. This concept was evaluated towards the enhancement of the electrocatalytic performances towards the oxygen evolution reaction (OER) as a model transformation. The OER can play a central role in meeting future energy demands but the performance of conventional electrocatalysts in this reaction is limited by the sluggish OER kinetics. We demonstrate an improvement of the OER performance for one of the most active OER catalysts, IrO 2 , by harvesting plasmonic effects from visible light illumination in multimetallic nanoparticles. We find that the OER activity for the Au–IrO 2 nanoflowers can be improved under LSPR excitation, matching best properties reported in the literature. Our simulations and electrocatalytic data demonstrate that the enhancement in OER activities can be attributed to an electronic interaction between Au and IrO 2 and to the activation of Ir–O bonds by LSPR excited hot holes, leading to a change in the reaction mechanism (rate-determinant step) under visible light illumination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2004

Laser Ranging to the Moon, Mars and Beyond

Current and future optical technologies will aid exploration of the Moon and Mars while advancing fundamental physics research in the solar system. Technologies and possible improvements in the laser-enabled tests of various physical phenomena are considered along with a space architecture that could be a cornerstone for robotic and human exploration in the solar system. In particular, accurate ranging to the Moon and Mars would not only lead to construction of a new space communication infrastructure enabling improved navigational accuracy, but would provide a significant improvement in several tests of gravitational theory: the equivalence principle, geodetic precession, PPN parameters beta and gamma, and the constancy of the gravitational constant G. Other tests would become possible with an optical architecture that would allow proceeding from cm to mm to sub-mm range accuracies. Looking to future exploration, what characteristics are desired for the next generation of ranging devices, what is the optimal architecture that would benefit both space exploration and fundamental physics, and what fundamental questions can be investigated?

Turyshev, Slava G.↗

DOE OSTI2018

Performance tuning of CEED software and first wave apps

The goal of this milestone was the performance tuning of the CEED software and first wave apps. In this milestone, the CEED team developed optimization techniques and tuned for performance the CEED software. Specifically, the focus was on the following: (1) Fast finite element operator storage and evaluation using partial assembly/matrix-free algorithms that take advantage of tensor-product element structure; (2) Architecture optimizations, including the development of performant discretization libraries targeting heterogeneous systems with multi-core CPUs, GPUs, and/or many-core CPUs in single node, cluster, or large-scale ECP supercomputer configurations; and (3) Global kernels for finite element operators, including the development of algorithms and libraries for fast gather-scatter exchanges for action assembly on unstructured graphs and for components needed for global linear solvers. A main part of this milestone was the performance tuning of the CEED first-wave ECP applications. This included the ExaSMR application – Coupled Monte Carlo Neutronics and Fluid Flow Simulation of Small Modular Reactors (ORNL), and the MARBL application – Next-Gen Multi-physics Simulation Code (LLNL). The artifacts delivered include performance improvements in CEED’s 1st wave of applications, and tuned CEED software for various architectures through a number of backends, freely available in the CEED’s repository on GitHub. See the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed for more details. In addition to details and results from the above R&D efforts, in this document we are also reporting on other project-wide activities performed in Q4 of FY18 including: CEED’s second annual meeting, a successful minisymposium at the premier international conference on high-order methods (ICOSAHOM), making the CEED milestone reports publicly available, new Laghos release, and other outreach efforts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Top-down design of protein architectures with reinforcement learning

As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approaches. We describe a “top-down” reinforcement learning–based design approach that solves this problem using Monte Carlo tree search to sample protein conformers in the context of an overall architecture and specified functional constraints. Cryo–electron microscopy structures of the designed disk-shaped nanopores and ultracompact icosahedra are very close to the computational models. The icosohedra enable very-high-density display of immunogens and signaling molecules, which potentiates vaccine response and angiogenesis induction. Our approach enables the top-down design of complex protein nanomaterials with desired system properties and demonstrates the power of reinforcement learning in protein design.

Science & Technology - Other Topics↗

NASA NTRS2012

Design and Performance Optimizations of Advanced Erosion-Resistant Low Conductivity Thermal Barrier Coatings for Rotorcraft Engines

Thermal barrier coatings will be more aggressively designed to protect gas turbine engine hot-section components in order to meet future rotorcraft engine higher fuel efficiency and lower emission goals. For thermal barrier coatings designed for rotorcraft turbine airfoil applications, further improved erosion and impact resistance are crucial for engine performance and durability, because the rotorcraft are often operated in the most severe sand erosive environments. Advanced low thermal conductivity and erosion-resistant thermal barrier coatings are being developed, with the current emphasis being placed on thermal barrier coating toughness improvements using multicomponent alloying and processing optimization approaches. The performance of the advanced thermal barrier coatings has been evaluated in a high temperature erosion burner rig and a laser heat-flux rig to simulate engine erosion and thermal gradient environments. The results have shown that the coating composition and architecture optimizations can effectively improve the erosion and impact resistance of the coating systems, while maintaining low thermal conductivity and cyclic oxidation durability

Zhu, Dongming↗

DOE OSTI2018

Concrete material science: Past, present, and future innovations

Concrete is flying off, but it is simultaneously facing tremendous challenges in terms of environmental impact, financial needs, societal acceptance and image. Based on an historical approach of the science of concrete and reinforced concrete in particular, this paper calls for the exploration of radical changes in three key aspects of concrete use: reinforcement, binder content, and implementation methods. More precisely, it is suggested that, in parallel to the introduction of robotic fabrication methods, digital technologies may be key for the introduction several innovations like (i) rebar-free reinforcement using non-convex granular media; (ii) compression-optimized concrete structures, using topology optimization, architectural geometry, and 3D-printing or origami-patterned formworks; (iii) truly digital concrete through the coupling of massive data collection and deep learning.

36 MATERIALS SCIENCE↗

DOE OSTI2023

ML-ACCEPT: Machine-Learning-enhanced Automated Circuit Configuration and Evaluation of Power Converters

This project, ML-ACCEPT, took a significant step toward achieving the first objective of the DIFFERENTIATE program: to help engineers to more rapidly and cost-effectively consider a wider range of more novel concepts before selecting an engineering-optimal architecture for high-fidelity detailed design and evaluation. Compared to existing methods, the ML-ACCEPT project investigated innovative technologies to make the design of power converters more cost-effective and time-efficient by i) integrating recent breakthroughs in ML, power electronics, simulation software, and optimization to research, develop, and developed a suite of ML-enhanced hypothesis generation tools for power converter design; and ii) facilitating the integration of the proposed software tools into existing power-converter design work-flows. Some existing tools for power-converter design have a certain level of intelligence to aid the design process, but to our knowledge none of them has ML-enhanced capability of automating the electrical circuit design process by selecting, configuring, and tailoring the individual components that enable available resources (e.g., high-voltage DC power) to be converted to the desired output (e.g., lower-voltage DC power with a desired voltage ripple), subject to application-specific (e.g., plasma generation and automotive applications) thermal and packaging considerations. The state-of-the-art circuit design of power converters is still heavily reliant on human experts to select the optimal topology and search for design parameters with human’s experience and intuitions, which can be very time-consuming, inefficient, and labor intensive. The team is composed of University of Michigan-Dearborn (UM-Dearborn), Lawrence Livermore National Laboratory (LLNL), Oak Ridge National Laboratory (ORNL), Modelon Inc., and lighthouse customers.

42 ENGINEERING↗

NASA NTRS2019

The Multi-Mission Earth Entry Vehicle for Sample Return Missions – Past, Present, and Future

The Multi-Mission Earth Entry Vehicle (MMEEV) is an enabling technology developed at NASA’s Langley Research Center (LaRC) over the last two decades for returning samples to Earth across a wide array of space science missions. Currently, the MMEEV is being considered for NASA’s Mars Sample Return (MSR) mission. The original vehicle concept, the Earth Entry Vehicle (EEV), was innovated at LaRC in 1998 as a robust solution to return Mars soil samples to Earth under stringent backward contamination requirements. These backward contamination requirements drove the EEV to have higher reliability than any capsule previously designed for a return-to-Earth sample return mission. The EEV achieved this high reliability by employing a passive (no active systems) vehicle architecture optimized for fault tolerance in a compact, low-mass configuration that is extensible to virtually any sample return mission. The original EEV concept utilized a carbon-carbon primary structure with high-density carbon phenolic thermal protection system. The capsule had a 60-degree sphere-cone forebody and a backshell geometry uniquely tailored to produce aerodynamics that would passively re-orient the vehicle if it entered the atmosphere with an off-nominal attitude. Contrary to every other sample return capsule conceived at the time, the EEV was designed to land without a parachute. The vehicle incorporated an integral energy-absorbing crushable structure that protected the Mars sample for landings on surfaces ranging from soft soil to solid concrete. This paper describes 20 years of technological advancements LaRC has incorporated into the EEV architecture to evolve it from the original, MSR-enabling vehicle, to a true multi-mission capability relevant to any sample return mission. The vehicle’s unique Integrated Composite Stiffener Structure (ICoSS) has been optimized for specific strength - supporting high-G atmospheric entries with steep entry angles that produce precise landing footprints on the ground. The vehicle geometry has been refined through wind tunnel testing and computational fluid dynamics simulations to improve the vehicle’s aerodynamic stability and robustness to off-nominal conditions from hypersonic to subsonic flight. The resulting configuration of the current MMEEV architecture is described, with details provided on its sample carrying capacity and atmospheric entry trajectory capabilities. The upgraded vehicle performance is mapped into current space science objectives, showing how the MMEEV supports future sample return missions and continues to be an enabling technology for NASA’s vision to return samples from Mars.

J M Corliss↗

DOE OSTI2020

CQNN: a CGRA-based QNN Framework

We propose a novel Coarse-Grained Reconfigurable Architecture-based (CGRA) QNN acceleration framework, CQNN. CQNN has a large number of basic components for binary functions. By programming CQNN at runtime according to the target QNN models, these basic components are integrated efficiently to support QNN functions with any data-width and hyper-parameter requirements and CQNN is reconfigured to have the optimal architecture for the target models. The framework includes compiler, architecture design, simulator and RTL generator. Experimental results show CQNNs can complete the inference of AlexNet and VGG-16 within 0.13ms and 2.63ms.

Geng, Tong↗

NASA NTRSDate not supplied

A Novel RF Architecture for Simultaneous Communication, Navigation, and Remote Sensing with Software-Defined Radio

The rapid growth of SmallSat and CubeSat missions at NASA has necessitated a re-evaluation of communication and remote-sensing architectures. Novel designs for CubeSat-sized single-board computers can now include larger Field-Programmable Gate Arrays (FPGAs) and faster System-on-Chip (SoCs) devices. These components substantially improve onboard processing capabilities so that varying subsystems no longer require an independent processor. By replacing individual Radio Frequency (RF) systems with a single software-defined radio (SDR) and processor, mission designers have greater control over reliability, performance, and efficiency. The presented architecture combines individual processing systems into a single design and establishes a modular SDR architecture capable of both remote-sensing and communication applications. This new approach based on a multi-input multi-output (MIMO) SDR features a scalable architecture optimized for Size, Weight, Power, and Cost (SWaP-C), with sufficient noise performance and phase-coherence to enable both remote-sensing and navigation applications, while providing a communication solution for simultaneous S-band and X-band transmission. This SDR design is developed around the NASA CubeSat Card Standard (CS2) that provides the required modularity through simplified backplane and interchangeable options for multiple radiation-hardened/tolerant processors. This architecture provides missions with a single platform for high-rate communication and a future platform to develop cognitive radio systems.

Advanced Avionics, Hybrid Processing, Data Process↗

DOE OSTI2018

System Levelized Cost of Energy Analysis for Floating Offshore Vertical-Axis Wind Turbines

The levelized cost of energy for an offshore wind plant consisting of floating vertical-axis wind turbines is studied in this report. A 5 MW Darrieus vertical-axis wind turbine rotor is used as the study turbine as this architecture was determined to have the greatest ability to reduce the system cost. The rotor structural design was used with blade manufacturing cost model studies to estimate its cost. A two-bladed, carbon fiber rotor was selected in this analysis since the lower topside mass resulted in a reduction of the platform costs which exceeded the increased rotor cost. A direct-drive, medium efficiency drivetrain was designed which represents 25% of the costs and 45% of the mass of the combined rotor/drivetrain system. A direct-drive, permanent magnet generator drivetrain was selected due to the improved reliability of this type of system, while the cost was not significantly higher than for geared drivetrains. A platform was designed by first identifying the optimal architecture for the vertical-axis wind turbine at a water depth of 150 m. A survey was performed of floating platform types, and six characteristic designs were analyzed which span the range of stability mechanisms available to floating systems. A multi-cellular tension-leg platform was identified as the lowest cost platform which additionally provided some interesting performance benefits. The small motions of the tension-leg platform benefit the system energy capture while limiting inertial loads placed on the rotor’s tower and blades. A final design was produced for the multi-cellular tension-leg platform considering operational fatigue, storm wind and wave conditions, and tow-out design cases. The driving design load was stability during tow-out while ballasting the platform. System levelized cost of energy was calculated, including operational expenses and balance of system costs estimated for the wind plant. Opportunities for reduction in the component costs are predicted and used to make projections of the system levelized cost of energy for future developments. The opportunities and challenges for floating vertical-axis wind turbines are identified by the system design and levelized cost of energy analysis.

17 WIND ENERGY↗

DOE OSTI2023

Role of Scaffold Architecture and Excess Surface Polymer Layers in a 3D-Interconnected Ceramic/Polymer Composite Electrolyte

3D-interconnected ceramic/polymer composite electrolytes offer promise to combine the benefits of both ceramic and polymer electrolytes. However, an in-depth understanding of the role of the ceramic scaffold's architecture, and the associated polymer/ceramic interfaces on the electrochemical properties of such composite electrolytes is still incomplete. Here, these factors are systematically evaluated using an interconnected composite electrolyte with a tunable and well-defined architecture. The ionic conductivity of the ceramic scaffold is strongly dependent on its porosity and tortuosity, as demonstrated experimentally and via theoretical modeling. The connectivity of the ceramic framework avoids the high interfacial impedance at the polymer/ceramic electrolyte interface within the composite. However, this work discovers that the interfacial impedance between the bulk composite and excess surface polymer layers of the composite membrane dominates the overall impedance, resulting in a 1–2 order drop of ionic conductivity compared to the ceramic scaffold. Despite the high impedance interfaces, an improved Li + transference number is found compared to the neat polymer (0.29 vs 0.05), attributed to the ceramic phase's contributions toward ion transport. Further, this leads to flatter overpotentials in lithium symmetric cell cycling. These results are expected to guide future research directions toward scalable manufacturing of composite electrolytes with optimized architecture and interfaces.

25 ENERGY STORAGE↗

DOE OSTI2018

Applications of synchrophasor technologies in power systems

Synchrophasors are time-synchronized electrical measurements that represent both the magnitude and phase angle of the electrical sinusoids. Synchrophasors are measured by fast time-stamped devices called phasor measurement units (PMUs) to constitute the basis of real-time monitoring and control actions in the electric grid. Due to its enhanced situational awareness capabilities, many applications of PMUs are presented in the literature in the past decades. This paper presents a comprehensive summary of synchrophasor technology, its architecture, optimal placement techniques and its applications in electric power transmission and distribution systems. These applications include wide-area situational awareness and monitoring, state estimation, fault location and protective relaying, islanding detection etc. This review also covers some of the existing challenges in its implementation and its potential applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Automatic signal decoding and sensor stability of a 3-electrode mixed-potential sensor for NO x /NH 3 quantification

Sensors to detect mixtures of NO x /NH 3 are needed to monitor emissions of diesel automobiles where a selective catalytic reduction system uses an NH 3 mediated reaction to reduce NO x . We report on the application of a three electrode La 0.8 Sr 0.2 CrO 3 , Au 0.5 Pd 0.5 , Pt mixed potential sensor using yttria-stabilized-zirconia (YSZ) as a solid electrolyte to NO x /NH 3 sensing. Artificial neural networks were used to automatically decode the concentrations of NO x /NH 3 and errors of less than 15% are achieved. The optimal architecture for ANN decoding and the maximum density of training data points are also determined. The stability of the sensor was monitored by electrochemical impedance spectroscopy. The impedance associated with YSZ oxygen ion conduction and the electrochemical reactions at the three-phase interface are tracked for a period of over 100 days.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Opening twisted polymer chains for simultaneously high printability and battery fast-charge

Fast-charging is key to the widespread adoption of battery-based electric vehicles. However, improving fast-charging through architecture optimization is expensive. To reduce costs and expand to commercialization, we applied roll-to-roll screen printing technology to create channels and decrease the tortuosity of electrodes. For the first time, this work successfully opened twisted polymer chains within high-solid-content inks to improve their screen printability and battery performance of as-printed electrodes. With LiNi 0.6 Mn 0.2 Co 0.2 O 2 as active materials, the 60% solid content ink presents superior screen printability after opening the twisted binder chains. As-printed electrode exhibits 33% higher charge capacity at 6 C than printed electrode with chains twisted ink at mass loading of 6.5 mg/cm 2 . Furthermore, coarse-grained molecular dynamics simulations are performed to study the underlying mechanism systematically. In conclusion, the new ink preparation procedure provides a scalable, effective strategy for manufacturing screen-printable battery ink and promotes screen-printed electrode technology.

25 ENERGY STORAGE↗