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At least 613 records · Page 34

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NASA NTRS1999

New Approaches to HSCT Multidisciplinary Design and Optimization

New approaches to MDO have been developed and demonstrated during this project on a particularly challenging aeronautics problem- HSCT Aeroelastic Wing Design. To tackle this problem required the integration of resources and collaboration from three Georgia Tech laboratories: ASDL, SDL, and PPRL, along with close coordination and participation from industry. Its success can also be contributed to the close interaction and involvement of fellows from the NASA Multidisciplinary Analysis and Optimization (MAO) program, which was going on in parallel, and provided additional resources to work the very complex, multidisciplinary problem, along with the methods being developed. The development of the Integrated Design Engineering Simulator (IDES) and its initial demonstration is a necessary first step in transitioning the methods and tools developed to larger industrial sized problems of interest. It also provides a framework for the implementation and demonstration of the methodology. Attachment: Appendix A - List of publications. Appendix B - Year 1 report. Appendix C - Year 2 report. Appendix D - Year 3 report. Appendix E - accompanying CDROM.

Schrage, Daniel P.↗

DOE OSTI2021

The nth-plant scenario for blended feedstock conversion and preprocessing nationwide: biorefineries and depots

The sustainability of the biofuel industry depends on the development of a mature conversion technology on a national level that can take advantage of the economies of scale: the nth-plant. Defining the future location and supply logistics of conversion plants is imperative to ultimately transform the nation’s renewable biomass resources into cost-competitive, high-performance feedstock for production of biofuels and bioproducts. Since the US has put restrictions on production levels of conventional biofuels from edible resources, the nation needs to plan for the widespread accessibility and development of the cellulosic biofuel scenario. Conventional feedstock supply systems will be unable to handle cellulosic biomass nationwide, making it essential to expand the industry with an advanced feedstock supply system incorporating a distributed network of preprocessing depots and conversion plants, or biorefineries. Current studies are mostly limited to designing supply systems for specific regions of the country. We developed a national database with potential locations for depots and biorefineries to meet the nation’s target demand of cellulosic biofuel. Blended feedstock with switchgrass and corn stover (harvested by either a two- or three-pass method) are considered in a Mixed Integer Linear Programming model to deliver on-spec biomass that considers both, a desired quantity and quality at the biorefinery. A total delivered feedstock cost that is less than $79.07/dt (2016$) is evaluated for years 2022, 2030, and 2040. In 2022, 124 depots and 59 biorefineries could be supplied with 42.8 million dt of corn stover and switchgrass. In 2030 and 2040, the total accessible biomass could increase to 215% and 393% respectively when compared to 2022. However, an $8/dry tons reduction in targeted delivery cost could reduce total accessible biomass by 67%. Kansas, Nebraska, South Dakota and Texas were identified as potential states with a strong biofuel economy given that they had six or more biorefineries located in all scenarios. In some scenarios, Colorado, Alabama, Georgia, Minnesota, Mississippi and South Carolina would greatly benefit from a depot network as these could only deliver to a biorefinery in a nearby state. To elaborate the impact of a nationwide consideration, the findings were compared with existing literature for different US regions. We also present results for biorefinery capacities that are double, triple, and quadruple in size.

09 BIOMASS FUELS↗

NASA NTRS2013

A Mars Sample Return Sample Handling System

We present a sample handling system, a subsystem of the proposed Dragon landed Mars Sample Return (MSR) mission [1], that can return to Earth orbit a significant mass of frozen Mars samples potentially consisting of: rock cores, subsurface drilled rock and ice cuttings, pebble sized rocks, and soil scoops. The sample collection, storage, retrieval and packaging assumptions and concepts in this study are applicable for the NASA's MPPG MSR mission architecture options [2]. Our study assumes a predecessor rover mission collects samples for return to Earth to address questions on: past life, climate change, water history, age dating, understanding Mars interior evolution [3], and, human safety and in-situ resource utilization. Hence the rover will have "integrated priorities for rock sampling" [3] that cover collection of subaqueous or hydrothermal sediments, low-temperature fluidaltered rocks, unaltered igneous rocks, regolith and atmosphere samples. Samples could include: drilled rock cores, alluvial and fluvial deposits, subsurface ice and soils, clays, sulfates, salts including perchlorates, aeolian deposits, and concretions. Thus samples will have a broad range of bulk densities, and require for Earth based analysis where practical: in-situ characterization, management of degradation such as perchlorate deliquescence and volatile release, and contamination management. We propose to adopt a sample container with a set of cups each with a sample from a specific location. We considered two sample cups sizes: (1) a small cup sized for samples matching those submitted to in-situ characterization instruments, and, (2) a larger cup for 100 mm rock cores [4] and pebble sized rocks, thus providing diverse samples and optimizing the MSR sample mass payload fraction for a given payload volume. We minimize sample degradation by keeping them frozen in the MSR payload sample canister using Peltier chip cooling. The cups are sealed by interference fitted heat activated memory alloy caps [5] if the heating does not affect the sample, or by crimping caps similar to bottle capping. We prefer cap sealing surfaces be external to the cup rim to prevent sample dust inside the cups interfering with sealing, or, contamination of the sample by Teflon seal elements (if adopted). Finally the sample collection rover, or a Fetch rover, selects cups with best choice samples and loads them into a sample tray, before delivering it to the Earth Return Vehicle (ERV) in the MSR Dragon capsule as described in [1] (Fig 1). This ensures best use of the MSR payload mass allowance. A 3 meter long jointed robot arm is extended from the Dragon capsule's crew hatch, retrieves the sample tray and inserts it into the sample canister payload located on the ERV stage. The robot arm has capacity to obtain grab samples in the event of a rover failure. The sample canister has a robot arm capture casting to enable capture by crewed or robot spacecraft when it returns to Earth orbit

Wilson, David↗

DOE OSTI2024

Resilient water infrastructure partnerships in institutionally complex systems face challenging supply and financial risk tradeoffs

Abstract As regions around the world invest billions in new infrastructure to overcome increasing water scarcity, better guidance is needed to facilitate cooperative planning and investment in institutionally complex and interconnected water supply systems. This work combines detailed water resource system ensemble modeling with multiobjective intelligent search to explore infrastructure investment partnership design in the context of ongoing canal rehabilitation and groundwater banking in California. Here we demonstrate that severe tradeoffs can emerge between conflicting goals related to water supply deliveries, partnership size, and the underlying financial risks associated with cooperative infrastructure investments. We show how hydroclimatic variability and institutional complexity can create significant uncertainty in realized water supply benefits and heterogeneity in partners’ financial risks that threaten infrastructure investment partnership viability. We demonstrate how multiobjective intelligent search can design partnerships with substantially higher water supply benefits and a fraction of the financial risk compared to status quo planning processes. This work has important implications globally for efforts to use cooperative infrastructure investments to enhance the climate resilience and financial stability of water supply systems.

Science & Technology - Other Topics↗

DOE OSTI2022

Toward a machine-guided approach to energetic material discovery

In this article, we trained a machine learning (ML) model to connect microstructural details of an energetic material formulation to its performance for the purpose of guiding the discovery of new explosive formulations. Our hypothesis was that the algorithm would robustly learn the training data and produce an accurate surrogate model. Specifically, the algorithm learned the relationship between details of the void size distribution (VSD), initiating shock pressure, and the energetic material performance. We used realistic constraints on the VSD and a range of cases were ingested by a physically informed reactive flow model working within a hydrodynamic solver running on high-performance computing resources. The ML algorithm produced a surrogate model that accurately predicted known test points around the parameter space. In addition to the utility of the model and the process used for its development, we noted interesting comparisons between what we, the authors—subject matter experts, would heuristically conclude from the training data and the surrogate model predictions. We detected nuanced details that were missed by the surrogate model; however, these details are not important to an energetic material formulator. We concluded that the algorithm did indeed robustly learn the training data and produce an accurate surrogate model. We further concluded that the surrogate model is a powerful tool to guide the formulator in the absence of subject matter experts and limited-access computing resources.

42 ENGINEERING↗

DOE OSTI2024

Large area nanoscale patterning of functional materials using organosilicate ink based nanotransfer printing

Abstract This paper presents a versatile nanotransfer printing method for achieving large-area sub-micron patterns of functional materials. Organosilicate ink formulations combined with effective release layers have been shown to facilitate patterning of materials through the commonly used patterning approaches—lift off, physical etching and chemical etching. In this paper, we demonstrate that organosilicate ink formulations function as an effective resist owing to its superior physico-chemical stability whereas the release layers ensure clean removal of the resist post patterning. We successfully demonstrate patterning of sub-micron structures (800 nm feature sizes) of chromium metal through the lift off approach, silicon through reactive ion etching technique and silicon dioxide through wet chemical etching technique illustrating the versatility of the reported method. This patterning methodology represents a significant advancement in enabling nanostructure fabrication within resource-constrained laboratories. The approach requires nothing more than a master mold containing the desired structures, a spin coater, a low-temperature hotplate, and a desktop reactive ion etch tool.

Engineering↗

DOE OSTI2020

Efficient and Flexible Hierarchical Data Layouts for a Unified Encoding of Scalar Field Precision and Resolution

To address the problem of ever-growing scientific data sizes making data movement a major hindrance to analysis, we introduce a novel encoding for scalar fields: a unified tree of resolution and precision, specifically constructed so that valid cuts correspond to sensible approximations of the original field in the precision-resolution space. Furthermore, we introduce a highly flexible encoding of such trees that forms a parameterized family of data hierarchies. We discuss how different parameter choices lead to different trade-offs in practice, and show how specific choices result in known data representation schemes such as zfp[52], idx[58], and jpeg2000 [76]. Lastly, we provide system-level details and empirical evidence on how such hierarchies facilitate common approximate queries with minimal data movement and time, using real-world data sets ranging from a few gigabytes to nearly a terabyte in size. Experiments suggest that our new strategy of combining reductions in resolution and precision is competitive with state-of-the-art compression techniques with respect to data quality, while being significantly more flexible and orders of magnitude faster, and requiring significantly reduced resources.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1975

Design Data Collection with Skylab Microwave Radiometer-Scatterometer S-193, Volume 1

The author has identified the following significant results. Observations with S-193 have provided radar design information for systems to be flown on spacecraft, but only at 13.9 GHz and for land areas over the United States and Brazil plus a few other areas of the world for which this kind of analysis was not made. Observations only extended out to about 50 deg angle of incidence. The value of a sensor with such a gross resolution for most overland resource and status monitoring systems seems marginal, with the possible exception of monitoring soil moisture and major vegetation variations. The complementary nature of the scatterometer and radiometer systems was demonstrated by the correlation analysis. Although radiometers must have spatial resolutions dictated by antenna size, radars can use synthetic aperture techniques to achieve much finer resolutions. Multiplicity of modes in the S-193 sensors complicated both the system development and its employment. An attempt was made in the design of the S-193 to arrange optimum integration times for each angle and type of measurement. This unnecessarily complicated the design of the instrument, since the gains in precision achieved in this way were marginal. Either a software-controllable integration time or a set of only two or three integration times would have been better.

Moore, R. K.↗

NASA NTRS1998

The SGI/Cray T3E: Experiences and Insights

The NASA Goddard Space Flight Center is home to the fifth most powerful supercomputer in the world, a 1024 processor SGI/Cray T3E-600. The original 512 processor system was placed at Goddard in March, 1997 as part of a cooperative agreement between the High Performance Computing and Communications Program's Earth and Space Sciences Project (ESS) and SGI/Cray Research. The goal of this system is to facilitate achievement of the Project milestones of 10, 50 and 100 GFLOPS sustained performance on selected Earth and space science application codes. The additional 512 processors were purchased in March, 1998 by the NASA Earth Science Enterprise for the NASA Seasonal to Interannual Prediction Project (NSIPP). These two "halves" still operate as a single system, and must satisfy the unique requirements of both aforementioned groups, as well as guest researchers from the Earth, space, microgravity, manned space flight and aeronautics communities. Few large scalable parallel systems are configured for capability computing, so models are hard to find. This unique environment has created a challenging system administration task, and has yielded some insights into the supercomputing needs of the various NASA Enterprises, as well as insights into the strengths and weaknesses of the T3E architecture and software. The T3E is a distributed memory system in which the processing elements (PE's) are connected by a low latency, high bandwidth bidirectional 3-D torus. Due to the focus on high speed communication between PE's, the T3E requires PE's to be allocated contiguously per job. Further, jobs will only execute on the user specified number of PE's and PE timesharing is possible but impractical. With a highly varied job mix in both size and runtime of jobs, the resulting scenario is PE fragmentation and an inability to achieve near 100% utilization. SGI/Cray has provided several scheduling and configuration tools to minimize the impact of fragmentation. These tools include PScheD (the political scheduler), GRM (the global resource manager) and NQE (the Network Queuing Environment). Features and impact of these tools will be discussed, as will resulting performance and utilization data. As a distributed memory system, the T3E is designed to be programmed through explicit message passing. Consequently, certain assumptions related to code design are made by the operating system (UNICOS/mk) and its scheduling tools. With the exception of HPF, which does run on the T3E, however poorly, alternative programming styles have the potential to impact the T3E in unexpected and undesirable ways. Several examples will be presented (preceeded with the disclaimer, "Don't try this at home! Violators will be prosecuted!")

Bernard, Lisa Hamet↗

NASA NTRS2004

Evolutionary computing for the design search and optimization of space vehicle power subsystems

Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment. Out preliminary results demonstrate that this approach has the potential to improve the space system trade study process by allowing engineers to statistically weight subsystem goals of mass, cost and performance then automatically size power elements based on anticipated performance of the subsystem rather than on worst-case estimates.

power↗

NASA NTRS2013

ISRU Propellant Selection for Space Exploration Vehicles

Chemical propulsion remains the only viable solution as technically matured technology for the near term human space transportation to Lunar and Mars. Current mode of space travel requires us to "take everything we will need", including propellant for the return trip. Forcing the mission designers to carry propellant for the return trip limits payload mass available for mission operations and results in a large and costly (and often unaffordable) design. Producing propellant via In-Situ Resource Utilization (ISRU) will enable missions with chemical propulsion by the "refueling" of return-trip propellant. It will reduce vehicle propellant mass carrying requirement by over 50%. This mass reduction can translates into increased payload to enhance greater mission capability, reduces vehicle size, weight and cost. It will also reduce size of launch vehicle fairing size as well as number of launches for a given space mission and enables exploration missions with existing chemical propulsion. Mars remains the ultimate destination for Human Space Exploration within the Solar System. The Mars atmospheric consist of 95% carbon dioxide (CO2) and the presence of Ice (water) was detected on Mars surfaces. This presents a basic chemical building block for the ISRU propellant manufacturing. However, the rationale for the right propellant to produce via ISRU appears to be limited to the perception of "what we can produce" as oppose to "what is the right propellant". Methane (CH4) is often quoted as a logical choice for Mars ISRU propellant, however; it is believed that there are better alternatives available that can result in a better space transportation architecture. A system analysis is needed to determine on what is the right propellant choice for the exploration vehicle. This paper examines the propellant selection for production via ISRU method on Mars surfaces. It will examine propellant trades for the exploration vehicle with resulting impact on vehicle performance, size, and on launch vehicles. It will investigate propellant manufacturing techniques that will be applicable on Mars surfaces and address related issues on storage, transfer, and safety. Finally, it will also address the operability issues associated with the impact of propellant selection on ground processing and launch vehicle integration.

Chen, Timothy T.↗

NASA NTRS2016

Comparing Eyewitness-Derived Trajectories of Bright Meteors to Ground Truth Data

The NASA Meteoroid Environment Office is a US government agency tasked with analyzing meteors of public interest. When queried about a meteor observed over the United States, the MEO must respond with a characterization of the trajectory, orbit, and size within a few hours. If the event is outside meteor network coverage and there is no imagery recorded by the public, a timely assessment can be difficult if not impossible. In this situation, visual reports made by eyewitnesses may be the only resource available. This has led to the development of a tool to quickly calculate crude meteor trajectories from eyewitness reports made to the American Meteor Society. A description of the tool, example case studies, and a comparison to ground truth data observed by the NASA All Sky Fireball Network are presented.

Moser, D. E.↗

NASA NTRSDate not supplied

Quantitative Characterization of Lunar Regolith Simulants for Direct Comparison to Apollo Soil Samples

Introduction: Sustained characterization efforts of lunar regolith simulant properties are not only integral for verification of commercially-produced material designed for a wide array of testing applications but are also necessary in establishing a comprehensive comparison to a lunar reference source. As a resource for the lunar science and engineering communities, the Simulant Development Lab (SDL) within the Astromaterials Research & Exploration Science (ARES) division at the Johnson Space Center (JSC) is actively pursuing closure of existing knowledge gaps in fundamental simulant attributes, including chemistry, mineralogy, particle size distribution, particle geometry, bulk and relative density, magnetic susceptibility, and shear strength (i.e., cohesion and angle of internal friction), as well as producing Figures of Merit for comparison of lunar simulants to Apollo regolith samples.

R. Kovtun↗

NASA NTRSDate not supplied

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗

DOE OSTI2023

Grid-Forming PV Inverter: Technology Development and Microgrid Applications

Presently, excluding residential backup power applications, grid-forming (GFM) inverters are commercially available for battery energy storage system (BESS) and some PV plus battery systems but not yet for stand-alone PV. This tech update investigates the control design for GFM PV inverter, especially the control required to provide active power reserve and to stabilize the dc link voltage. Subsequently, the use cases of GFM PV plants in utility-level microgrids are discussed considering fully inverter-based microgrids (i.e., with PV and BESS) as well as mixed-source microgrids (i.e., with PV and diesel generator). Scenarios where active power up-reserve from GFM PV plants is beneficial are illustrated. Moreover, requirements and specifications for GFM PV plant, especially for its active power reserve function are developed. In addition, stability of an example utility-level microgrid with two GFM PV plants and a diesel generator is analyzed to shed light on the potential unstable interaction between multiple GFM resources and the countermeasures. This research aims to advance GFM PV technology to offer more flexibility in microgrid design. With GFM PV available, depending on the level of reliability required, cost-benefit analysis, etc., the GFM BESS or diesel generator may be sized smaller while leveraging the full potential of PV generation inside the microgrid.

14 SOLAR ENERGY↗

DOE OSTI2021

Fast All-sky Radiation Model for Solar applications (FARMS) [SWR-16-18]

The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.

Xie, Yu↗

DOE OSTI2023

Fast All-sky Radiation Model for Solar applications (FARMS) 2023 [SWR-16-18]

Xie, Yu↗

DOE OSTI2023

Relationships between maternally-transferred mercury and hatchling development, behavior, and survival in the American alligator ( Alligator mississippiensis )

Mercury is a toxic and pervasive environmental contaminant that can be transferred from mother to offspring during development. Consequences of maternally-transferred mercury have been observed in vertebrate taxa, including reduced clutch viability, reduced offspring size, and behavioral alterations. These sublethal effects have been assumed to decrease survivorship, though this is seldom assessed. Here, we examined how maternally-transferred mercury interacts with incubation temperature to influence reproductive success, offspring behavior, and subsequent survival in the American alligator (Alligator mississippiensis). We collected nine clutches of eggs from a mercury contaminated reservoir on the Savannah River Site, South Carolina, and incubated eggs at either female- or male-promoting temperatures. Clutch-averaged mercury in egg yolk was high relative to other studies in crocodilians and ranged from 0.248 to 0.554 ppm compared to 0.018–0.052 ppm at a site with low levels of mercury contamination; mercury levels in hatchling blood ranged from 0.090 to 0.490 ppm ($\overline{x}$= 0.240 ppm, n = 158). We found few, mostly negligible correlations between life history traits and mercury but noted a positive relationship with egg mass, possibly mediated by correlated maternal effects such as resource provisioning. Incubation temperature exerted strong effects on hatchling phenotypes, with warmer, male-promoting temperatures producing larger and bolder hatchlings. Presumptive females, produced from cooler incubation temperatures, spent more time in warm areas during behavior trials. Hatchlings were released 10–15 days post-hatch and surveyed over eight months to assess survival. Survivorship was positively correlated with hatchling size and negatively correlated with proportional time spent in warm areas. Presumptive females had much lower survival, and overall survivorship for the eight-month period was 0.185–0.208, depending on the modelling approach. Finally, our study suggests that, within the range of concentrations we observed, incubation temperature has a stronger effect on offspring behavior and survival than maternally-transferred mercury pollution in American alligators.

59 BASIC BIOLOGICAL SCIENCES↗