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All sources NASA NTRS DOE OSTI

NASA NTRS2015

Space in Space: Designing for Privacy in the Workplace

Privacy is cultural, socially embedded in the spatial, temporal, and material aspects of the lived experience. Definitions of privacy are as varied among scholars as they are among those who fight for their personal rights in the home and the workplace. Privacy in the workplace has become a topic of interest in recent years, as evident in discussions on Big Data as well as the shrinking office spaces in which people work. An article in The New York Times published in February of this year noted that "many companies are looking to cut costs, and one way to do that is by trimming personal space". Increasingly, organizations ranging from tech start-ups to large corporations are downsizing square footage and opting for open-office floorplans hoping to trim the budget and spark creative, productive communication among their employees. The question of how much is too much to trim when it comes to privacy, is one that is being actively addressed by the National Aeronautics and Space Administration (NASA) as they explore habitat designs for future space missions. NASA recognizes privacy as a design-related stressor impacting human health and performance. Given the challenges of sustaining life in an isolated, confined, and extreme environment such as Mars, NASA deems it necessary to determine the acceptable minimal amount for habitable volume for activities requiring at least some level of privacy in order to support optimal crew performance. Ethnographic research was conducted in 2013 to explore perceptions of privacy and privacy needs among astronauts living and working in space as part of a long-distance, long-duration mission. The allocation of space, or habitable volume, becomes an increasingly complex issue in outer space due to the costs associated with maintaining an artificial, confined environment bounded by limitations of mass while located in an extreme environment. Privacy in space, or space in space, provides a unique case study of the complex notions of privacy, the impact of design and others on achieving it, and the sensemaking that occurs when privacy is less than expected. The findings show that privacy is not just a personal, individual need but is also a need that is shared among teams and groups. Moreover, the case of space in space reveals the influence the design of the built and social environments have on privacy needs and on achieving privacy. When the level of privacy is less than expected, sensemaking occurs and the lack of privacy is dealt with by means of absencing the present. creating new social norms, and "making space" by manipulating the spatial, temporal, material aspects of the lived experience. Although the Mars habitat study represents an extreme case of privacy in the workplace, lessons learned from outer space are applicable to life in the Earth-bound workplace. A mini-case study was conducted to evaluate office space at the headquarters of a major American airline that illustrates the usefulness of building unexpected bridges between the unknown, unfamiliar Mars habitat and the everyday workplace. The comparative studies reveal insight into the interconnected, social nature of the spatial, temporal, and material aspects of the lived experience and how users of the habitat and office workspace view privacy, self, and others through an embodied, design interaction.

Akin, Jonie↗

NASA NTRS2016

Galaxy Evolution Spectroscopic Explorer: Scientific Rationale

GESE is a mission concept consisting of a 1.5-m space telescope and UV multi-object slit spectrograph designed to help understand galaxy evolution in a critical era in the history of the universe, where the rate of star-formation stopped increasing and started to decline. To isolate and identify the various processes driving the evolution of these galaxies, GESE will obtain rest-frame far-UV spectra of 100,000 galaxies at redshifts, z approximately 1-2. To obtain such a large number of spectra, multiplexing over a wide field is an absolute necessity. A slit device such as a digital micro-mirror device (DMD) or a micro-shutter array (MSA) enables spectroscopy of a hundred or more sources in a single exposure while eliminating overlapping spectra of other sources and blocking unwanted background like zodiacal light. We find that a 1.5-m space telescope with a MSA slit device combined with a custom orbit enabling long, uninterrupted exposures (approximately 10 hr) are optimal for this spectroscopic survey. GESE will not be operating alone in this endeavor. Together with x-ray telescopes and optical/near-IR telescopes like Subaru/Prime Focus Spectrograph, GESE will detect "feedback" from young massive stars and massive black holes (AGN's), and other drivers of galaxy evolution.

digital micro-mirror device (DMD)↗

DOE OSTI2019

Discovery and Structure-Based Optimization of Potent and Selective WD Repeat Domain 5 (WDR5) Inhibitors Containing a Dihydroisoquinolinone Bicyclic Core

WD repeat domain 5 (WDR5) is a member of the WD40-repeat protein family that plays a critical role in multiple chromatin-centric processes. Overexpression of WDR5 correlates with a poor clinical outcome in many human cancers, and WDR5 itself has emerged as an attractive target for therapy. Most drug-discovery efforts center on the WIN site of WDR5 that is responsible for the recruitment of WDR5 to chromatin. In this paper, we describe discovery of a novel WDR5 WIN site antagonists containing a dihydroisoquinolinone bicyclic core using a structure-based design. These compounds exhibit picomolar binding affinity and selective concentration-dependent antiproliferative activities in sensitive MLL-fusion cell lines. Furthermore, these WDR5 WIN site binders inhibit proliferation in MYC-driven cancer cells and reduce MYC recruitment to chromatin at MYC/WDR5 co-bound genes. Thus, these molecules are useful probes to study the implication of WDR5 inhibition in cancers and serve as a potential starting point toward the discovery of anti-WDR5 therapeutics.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Mechanical adaptation of brachiopod shells via hydration-induced structural changes

The function-optimized properties of biominerals arise from the hierarchical organization of primary building blocks. Alteration of properties in response to environmental stresses generally involves time-intensive processes of resorption and reprecipitation of mineral in the underlying organic scaffold. Here, we report that the load-bearing shells of the brachiopod Discinisca tenuis are an exception to this process. These shells can dynamically modulate their mechanical properties in response to a change in environment, switching from hard and stiff when dry to malleable when hydrated within minutes. Using ptychographic X-ray tomography, electron microscopy and spectroscopy, we describe their hierarchical structure and composition as a function of hydration to understand the structural motifs that generate this adaptability. Key is a complementary set of structural modifications, starting with the swelling of an organic matrix on the micron level via nanocrystal reorganization and ending in an intercalation process on the molecular level in response to hydration.

36 MATERIALS SCIENCE↗

NASA NTRS2017

Operating Small Sat Swarms as a Single Entity: Introducing SODA

Swarm concepts are a growing topic of interest in the small satellite community. Compared to a small satellite constellation, a swarm has the distinction of being multiple spacecraft in close proximity, in approximately the same orbit. Furthermore, we envision swarms to have capabilities for cross-link communication and station-keeping. Of particular interest is a means to maintain operator-specified geometry, alignment, and/or separation.From NASA's decadal survey, it is clear that simultaneous measurements from a 3D volume of space are desired for a variety of Earth scientific studies. As this mission concept is ultimately extended to deep space, some degree of local control for the swarm to self-correct its configuration is required. We claim that the practicality of ground commanding each individual satellite in the swarm is simply not a feasible concept of operations. In other words, the current state-of-practice does not scale to very large swarms (e.g. 100 spacecraft or more) without becoming cost prohibitive. To contain the operations costs and complexity, a new approach is required: the swarm must be operated as a unit, responding to high-level specifications for relative position and velocity.The Mission Design Division at NASA Ames Research Center is looking to the near future for opportunities to develop satellite swarm technology. As part of this effort, we are developing SODA (Swarm Orbital Dynamics Advisor), a tool that provides the orbital maneuvers required to achieve a desired type of relative swarm motion. The purpose of SODA is two-fold. First, it encompasses the algorithms and orbital dynamics model to enable the desired relative motion of the swarm satellites. The process starts with the user specifying the properties of a swarm configuration. This could be as simple as varying in-track spacing of the swarm in one orbit, or as complex as maintaining a specified 3D geometrical orientation. We presume that science objectives will drive this choice. Given these inputs, the tool provides the most efficient maneuver(s) to achieve the objective.Second, SODA provides a variety of visualization tools. We acknowledge that the relationship between a desired relative motion amongst the swarm, and the corresponding orbital parameters for each individual satellite may not be immediately apparent for ground controllers and mission planners. The purpose of SODA's visualization tools is to illustrate this concept clearly with a variety of graphics and animations. After computing the optimal orbital maneuvers to modify the swarm, these results are simulated to demonstrate successful swarm control.Our emphasis in this paper is on the importance of relating the desired motion of the swarm satellites relative to one another with the required orbital element changes. One cannot joystick a drifting swarm satellite back into position; the underlying orbital mechanics dictate the most efficient recovery maneuvers. To illustrate this point, results from several case study simulations are presented. We conclude with our forward work for ongoing SODA development and potential science applications.

small satellites↗

DOE OSTI2022

Improving Schrödinger Equation Implementations with Gray Code for Adiabatic Quantum Computers

We reformulate the continuous-space Schrödinger equation in terms of spin Hamiltonians. For the kinetic energy operator, the critical concept facilitating the reduction in model complexity is the idea of position encoding. A binary encoding of position produces a spin-1/2 Heisenberg-like model and yields exponential improvement in space complexity when compared to classical computing. Encoding with a binary reflected Gray code (BRGC), and a Hamming-distance-2 Gray code (H2GC) reduces the model complexity down to the 𝑋⁢𝑍 and transverse Ising model, respectively. For 𝐴 qubits BRGC yields 2 𝐴 positions and is reduced to its 2-local form with O⁡(𝐴) ancillary qubits. H2GC yields 2 𝐴/2+1 positions with O⁡(𝐴 2 ) three-local penalty terms. We also identify the bijective mapping between diagonal unitaries and the Walsh series, producing the mapping of any real potential to a series of 𝑘 -local Ising models through the fast Walsh transform. Finally, in a finite volume, we provide some numerical evidence to support the claim that the total time needed for adiabatic evolution is protected by the infrared cutoff of the system. As a result, initial state preparation from a free-field wave function to an interacting system is expected to exhibit polynomial time complexity with volume and constant scaling with respect to lattice discretization for all encodings. For H2GC, if the evolution starts with the transverse Hamiltonian due to hardware restrictions, then penalties are dynamically introduced such that the low-lying spectrum reproduces the energy levels of the Laplacian. The adiabatic evolution of the penalty Hamiltonian is therefore sensitive to the ultraviolet scale. It is expected to exhibit polynomial time complexity with lattice discretization, or exponential time complexity with respect to the number of qubits given a fixed volume.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Enhancing Distribution System Resilience: A First-Order Meta-RL Algorithm for Critical Load Restoration

The increasing frequency of extreme events and the integration of distributed energy resources (DERs) into modern grids have elevated the need for resilient and efficient critical load restoration strategies in distribution systems. However, the stochastic nature of renewable DERs, limited energy resource availability and the intricate nonlinearities inherent in complex grid control problem make the problem challenging. Although reinforcement learning (RL) and warm-start RL methods have shown promising results, their performance often falls short in rapidly adapting to new, unseen situations and typically requires exhaustive problem-specific tuning. To address these gaps, we propose a First-Order Meta-based RL (FOM-RL) algorithm within an online framework for adaptive and robust critical load restoration. By harnessing local DERs as the enabling technology, FOM-RL allows the RL agent to swiftly adapt to new unseen scenarios by leveraging previously acquired knowledge of different tasks. Experimental results provide evidence that proposed algorithm learns more efficiently and showcases generalization capabilities across diverse set of operational scenarios. Moreover, a rigorous theoretical analysis yields a tight sublinear regret bound, sensitive to temporal variability, with a task-averaged optimality gap bounded by O(VM+D*/(Tsquare root(M))). These results suggest that optimality improves with task similarity and an increased number of tasks M, reaffirming the efficacy and scalability of the proposed approach in addressing the complexities of critical load restoration in distribution systems.

complexity theory↗

DOE OSTI2024

Deep Learning Image Segmentation for Atmospheric Rivers

Abstract The identification of atmospheric rivers (ARs) is crucial for weather and climate predictions as they are often associated with severe storm systems and extreme precipitation, which can cause large impacts on society. This study presents a deep learning model, termed ARDetect, for image segmentation of ARs using ERA5 data from 1960 to 2020 with labels obtained from the TempestExtremes tracking algorithm. ARDetect is a convolutional neural network (CNN)-based U-Net model, with its structure having been optimized using automatic hyperparameter tuning. Inputs to ARDetect were selected to be the integrated water vapor transport (IVT) and total column water (TCW) fields, as well as the AR mask from TempestExtremes from the previous time step to the one being considered. ARDetect achieved a mean intersection-over-union (mIoU) rate of 89.04% for ARs, indicating its high accuracy in identifying these weather patterns and a superior performance than most deep learning–based models for AR detection. In addition, ARDetect can be executed faster than the TempestExtremes method (seconds vs minutes) for the same period. This provides a significant benefit for online AR detection, especially for high-resolution global models. An ensemble of 10 models, each trained on the same dataset but having different starting weights, was used to further improve on the performance produced by ARDetect, thus demonstrating the importance of model diversity in improving performance. ARDetect provides an effective and fast deep learning–based model for researchers and weather forecasters to better detect and understand ARs, which have significant impacts on weather-related events such as floods and droughts.

Galea, Daniel↗

NASA NTRS2015

Asteroid Characterization Priorities for Planetary Defense

We propose a prioritized list of asteroid characterization needs for planetary defense. In particular, we consider the properties of asteroids that are of greatest interest for assessment of planetary defense options, including gravity tractors, kinetic impactors, and nuclear explosives. In addition, much of our discussion is relevant for impact assessments and subsequent emergency-response planning. Rather than intending this as a definitive answer, however, our purpose is to stimulate and focus disscussion regarding characterization needs for planetary defense, with a specific list as a starting point. A key theme is understanding the sensitivity of the outcome of an asteroid deflection or disruption effort to the asteroids physical properties.There is a range of previous work relevant to our topic, including some explicit discussions as well as many more that are implicitly relevant. We incorporate elements from such reports while extending them using our own experience and perspectives. After introducing our prioritized list, we provide further discussion on each element, with details on the relevance of each characteristic for modeling purposes, our rationale for the assigned priority, and examples of analyses that require improved characterization information. Our goal is to establish a framework that can be modified and adapted by the community for a variety of purposes, such as mission design and optimization, development of new measurement techniques, or prioritization of research efforts. The objective is to increase understanding and reduce uncertainties in the specific aspects of characterization that most benefit accurate assessments of practical techniques for planetary defense.

Miller, Paul↗

NASA NTRSDate not supplied

Making & Breaking the Rules for DED Design

Design for Additive Manufacturing (DfAM) is widely used to describe design activities and guidelines employed in the creation of Additively Manufactured (AM) parts. Basic design rules for widely adopted processes like Powder Bed Fusion (PBF) are relatively understood including material performance, part size constraints, self-supporting angles, overhangs, wall thicknesses, and feature resolution. Complexity is often inherent with PBF using organically inspired solutions through generative design and topology optimization software to create designs that often cannot be realized via traditional manufacturing processes. The design rules for Directed Energy Deposition (DED) are less well known, and, in some cases, the lack of understanding is likely inhibiting broader application of the various DED processes. This presentation covers key design rules for DED fusion processes and elucidates opportunities like multi-material deposition and build approaches ranging from basic features to complex large-scale parts. Complementary to the opportunistic characteristics of DfAM for DED, Manufacture for AM (MfAM) encompasses the restrictive aspects of the manufacturing lifecycle with limitations due to bead width and wall thickness, self-supporting angles, surface texture, microstructural evolution, and residual stresses. AM enabled part design must always consider the entire value chain starting with incoming feedstock (e.g. plate, wire, or powder) and progressing through the printing process, post-processing (e.g. machining, inspection), and final system assembly. Key considerations, like the tradeoffs between feature resolution and build rate, for process and part selection and economic assessments will be discussed as DED is often traded against other AM processes. After highlighting typical DED design rules, we will also show how some of those rules can be broken via use cases and part designs that span the full spectrum of DED processes with examples of various DED part designs.

Additive Manufacturing↗

NASA NTRS2025

Tutorial: MATLAB Implementation of a Successive Convexification Algorithm for 3 DoF Rocket Landings

The primary objective of this work is to fill in gaps and explore an alternate way of solving the 3 DoF rocket-powered landing problem presented in the 2016 AIAA paper by Szmuk, Ackimese, and Berning using successive convexification (SCvx). In the original paper, CVX, an automatic parsing package, was used to transcribe the high-level trajectory optimization problem into a format that could be read by a conic solver. The parsing step, generally computationally intensive, is hidden from the user. The use of CVX is sufficient for the generation of trajectories off-line due to the lack of runtime and flight software implementation constraints. For on-line applications, it is necessary to parse the problem for flight software implementation. References on hand-parsing powered descent guidance (PDG) problems are sparse. In this Tech Memo, the process of transcribing the 3 DoF PDG problem into the format required by MATLAB’s built-in second-order cone solver, coneprog.m, is presented in detail. Due to the abridged 3 DoF dynamics and the relatively simple nonlinearities, this reference is the natural starting point for anyone interested in grasping the concepts behind SCvx pertaining to PDG and the parsing step. Simulation results shown in this report were independently created by solving the problem using coneprog.m. The intent of this memo is to serve as a supplemental material to the original paper by breaking down the concept behind successive convexification and shed light into the parsing process. Readers are encouraged to first familiarize themselves with the material laid out in the original reference.

Alex Hayes↗

DOE OSTI2023

EDX Spatial: Leveraging cloud and hybrid data management resources for spatial data

In the last few years, the National Energy Technology Laboratory has started leveraging cloud-hosted services for hosting spatial data collections published on the Energy Data eXchange (EDX). Using cloud-hosted storage and compute options offers multiple benefits for visualization and tool development through utilization of spatial data resources. The transition from on-premises services to cloud-hosted services has enabled a few key features: increased accessibility of large derivative datasets, dynamic integration of external authoritative data resources directly from outside entities through representational state transfer application programming interfaces (REST API), and the ability to produce complex mapping applications, dashboards, and online maps. As a result of the shift, NETL has launched EDX Spatial, a platform that leverages on-premises resources combined with cloud compute capabilities to enable enhanced online mapping interfaces and optimize data access. In addition, a unified workflow for handling the public release of spatial data products through EDX has been developed, including standardization of data hosting practices, metadata, symbology, and application elements. This poster reviews the opportunity of leveraging cloud-hosted and hybrid data management solutions for spatial data, and discusses the benefits and lessons learned while leveraging these services through the data repository EDX.

Morkner, Paige↗

DOE OSTI2024

Dual-phase superconductivity in high-pressure high-temperature synthesized TaNbZrHfTi

We report on a novel TaNbZrHfTi-based high entropy alloy (HEA) which demonstrates distinctive dual-phase superconductivity. The HEA was synthesized under high pressures and high temperatures starting from a ball milled mixture of elemental metals in a large-volume Paris–Edinburgh cell with P ≈ 6 GPa and T = 2300 K. The synthesized HEA is a phase mixture of BCC (NbTa)0.45(ZrHfTi)0.55 with Tc1 = 6 K and FCC (NbTa)0.04(ZrHfTi)0.96 with Tc2 = 3.75 K. The measured magnetic field parameters for the HEA are lower critical field, Hc1(0) = 31 mT, and a relatively high upper critical field, Hc2(0) = 4.92 T. This dual-phase system is further characterized by the presence of a second magnetization peak, or the fishtail effect, observed in the virgin magnetization curves. This phenomenon, which does not distort the field-dependent magnetization hysteresis loops, suggests intricate pinning mechanisms that could be potentially tuned for optimized performance. The manifestation of these unique features in HEA superconductivity reinforces phase-dependent superconductivity and opens new avenues in the exploration of novel superconducting materials.

Materials Science↗

DOE OSTI2025

Advancing Multi-Hazard Risk and Safety Considerations for Aging Nuclear Facilities (Revision 1)

This project will demonstrate a multi-hazard time-dependent probabilistic risk assessment (PRA) approach for nuclear facilities considering aging-related deterioration of structures. A generic pressurized water reactor (PWR) reactor subjected to seismic mainshock-aftershock sequences considering the aging of the containment structure will be used as a case study to demonstrate the multi-hazard PRA approach. Using advanced modeling and simulation, seismic mainshock-aftershock fragility functions will be simulated for the containment structure considering aging effects. A multi-hazard PRA model for a generic PWR reactor will be built to quantify the multi-hazard core damage frequency (CDF) and large early release frequency (LERF) with explicit time-dependent modeling of event sequences. To date, the cascading impacts of multi-hazards are not adequately accounted for in the PRA models for nuclear facilities. In addition, for both initial and periodic evaluation of facilities to withstand natural phenomena hazards (NPH), deterioration of the SSCs due to aging and other effects is not adequately considered. By advancing multi-hazard considerations accounting for aging effects, this project will contribute to improved understanding of the safety of aging nuclear facilities. Project outcomes such as the multi-hazard CDF and LERF will also allow facility owners to optimize upgrade and retrofit protocols. This project is divided into two components: (1) advanced modeling and simulations; and (2) multi-hazard PRA. For the first component, Idaho National Laboratory’s (INL) Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) and BlackBear codes will be used to simulate the seismic response and damage of a containment structure under cascading mainshock-aftershock sequences with aging effects. Uncertainties related to the seismic inputs, material parameters, and environmental factors such as temperature and humidity will be identified and propagated to the fragility functions. These fragility functions, which consider aging effects, will be time dependent. The second component will take the fragility information from the first component to build a multi-hazard time-dependent PRA model starting from a generic PWR model to evaluate the multi-hazard CDF and LERF and characterize the associated consequences. For this component, OpenPRA Web Application and SAPHIRE code will be used. Events such as the Fukushima Daiichi accident have highlighted the importance of considering the cascading impacts of multi-hazards for PRA. Moreover, many of the reactors in the current nuclear fleet in the United States (US) are already operating well beyond their initially planned design life, and applications for further extensions to operating licenses are being considered. Therefore, considering multi-hazard effects and aging deterioration in the NPH risk assessment process will contribute to the safety of both existing and future nuclear facilities. Outcomes of this project will thus directly benefit the standards DOE-STD-1020-16 and DOE-HDBK-1224-18.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2005

At-Least Version of the Generalized Minimum Spanning Tree Problem: Optimization Through Ant Colony System and Genetic Algorithms

The At-Least version of the Generalized Minimum Spanning Tree Problem (L-GMST) is a problem in which the optimal solution connects all defined clusters of nodes in a given network at a minimum cost. The L-GMST is NPHard; therefore, metaheuristic algorithms have been used to find reasonable solutions to the problem as opposed to computationally feasible exact algorithms, which many believe do not exist for such a problem. One such metaheuristic uses a swarm-intelligent Ant Colony System (ACS) algorithm, in which agents converge on a solution through the weighing of local heuristics, such as the shortest available path and the number of agents that recently used a given path. However, in a network using a solution derived from the ACS algorithm, some nodes may move around to different clusters and cause small changes in the network makeup. Rerunning the algorithm from the start would be somewhat inefficient due to the significance of the changes, so a genetic algorithm based on the top few solutions found in the ACS algorithm is proposed to quickly and efficiently adapt the network to these small changes.

Janich, Karl W.↗

NASA NTRSDate not supplied

SatCORPS Global Cloud Composite (GCC): the Design and Delivery of A High Quality, High Resolution, Global Cloud Product Available in Near-Real Time

The NASA Satellite ClOud and Radiation Property retrieval System (SatCORPS) supports the development of an analysis ready and cloud-optimized data transformation pipeline and geospatial service enablement of a global cloud composite (GCC) product derived from global geostationary satellite imagery. This geospatial service will be available at high temporal and spatial resolution via the SatCORPS web mapping application for visualization and analysis as well as direct ingestion to common geospatial software and custom programming. The resulting global cloud composite products from the processing pipeline can then be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. Near real time global observations are created through the composition of five geostationary satellites that provides modelling and forecasting communities with the capability to provide high quality and timely information to start the projection process. The Global Cloud Composite product combines information from geostationary satellites, GOES-16, GOES-17, Himawari-8, Meteosat-11 and Meteosat-9 to create a single global composite netcdf file and images using the different products within the netcdf file. The SatCORPS team, though our Global Cloud Composite (GCC) product and web-based visualization tools including Geographical Information System (GIS) services provide near real time global cloud product information to both automated processes and traditional web users that is timely and high quality derived from geostationary satellites. The Global Cloud Composite product takes advantage of the scalable processing resources provided by the AWS batch service to provide new composites every thirty minutes. Because information from each of the low earth orbiting satellites is available on schedules tuned to the specific satellite, the processing algorithm temporally composites the final dataset as each satellite’s information becomes available. The SatCORPS team has leveraged our experience using Amazon Web Services (AWS) to build a low latency high availability tool that allows end users both human and automated to acquire high quality and high-resolution Geostationary Earth Orbiting (GEO) information at zero cost to the end user. This presentation will describe how we architected and implemented the service as well as lessons learned based on our experiences both developing and operating the system. The lessons learned include how we integrated multiple services including Amazon Batch, Amazon S3 and Amazon Lambda service to create a low cost but high-performance processing system that is capable of identifying and processing the most appropriate satellite overpass information into global cloud composites. We will also describe our web-based tools including our Geographic Information System that can be used for visualization and analysis. The products from the processing can be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. The SatCORPS Global Composite Cloud product provides sophisticated global composited cloud research products with very low latency that we see that as filling a rapidly growing need in the research and modelling community with no up-front nor ongoing costs associated with downloading or using the information.

AWS AMCE SMCE GCC SATCORPS GLOBAL CLOUD COMPOSITE ↗

DOE OSTI2020

Dynamic Modeling of Sequential Service Restoration in Islanded Single Master Microgrids

This paper presents a methodology for generating restoration sequences in distribution systems and microgrids with emphasis on deriving optimal switching times for remote control switches (RCS). Microgrid architecture considered are assumed to be operating in islanded single master mode. Control methods for handling the unbalance inherent in distribution systems using single-phase controlled PQ inverters were developed and incorporated in the proposed method. The problem of considering simultaneously both energy optimization and dynamic stability of the system, which is lacking in existing methods, was addressed by studying the transient behavior of microgrids based on extended EMTP simulations and then approximate and incorporate these behaviors into the optimization formulation for restoration. The approach is based on multi-objective optimization of final restored load and total restoration time. The methodology was studied on a modified IEEE 123 node test feeder. An EMTP simulation in PSCAD of the formed microgrids was used to validate the accuracy of the dynamic and steady-state characteristics of the resulting systems. By considering the transient behavior of DGs during restoration, a better restoration sequence that does not trigger protection relays could be realized.

42 ENGINEERING↗

DOE OSTI2022

Synthesis of Nano-Oxide Precipitates by Implantation of Ti, Y and O Ions in Fe-10%Cr: Towards an Understanding of Precipitation in Oxide Dispersion-Strengthened (ODS) Steels

The properties of oxide dispersion-strengthened steels are highly dependent on the nature and size distribution of their constituting nano-oxide precipitates. A fine control of the processes of synthesis would enable the optimization of pertinent properties for use in various energy systems. This control, however, requires knowledge of the precise mechanisms of nucleation and growth of the nanoprecipitates, which are still a matter of debate. In the present study, nano-oxide precipitates were produced via the implantation of Y, Ti, and O ions in two different sequential orders in an Fe-10%Cr matrix that was subsequently thermally annealed. The results show that the oxides that precipitate are not necessarily favoured thermodynamically, but rather result from complex kinetics aspects related to the interaction between the implanted elements and induced defects. When Y is implanted first, the formation of nanoprecipitates with characteristics similar to those in conventionally produced ODS steels, especially with a core/shell structure, is evidenced. In contrast, when implantation starts with Ti, the precipitation of yttria during subsequent high-temperature annealing is totally suppressed, and corundum Cr 2 O 3 precipitates instead. Moreover, the systematic involvement of {110} matrix planes in orientation relationships with the precipitates, independently of the precipitate nature, suggests matrix restriction effects on the early stages of precipitation.

36 MATERIALS SCIENCE↗